WO2021049671A1 - マイクロｒｎａを含む体液抽出物 - Google Patents

マイクロｒｎａを含む体液抽出物 Download PDF

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WO2021049671A1
WO2021049671A1 PCT/JP2020/037487 JP2020037487W WO2021049671A1 WO 2021049671 A1 WO2021049671 A1 WO 2021049671A1 JP 2020037487 W JP2020037487 W JP 2020037487W WO 2021049671 A1 WO2021049671 A1 WO 2021049671A1
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mir
hsa
microrna
urine
micrornas
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French (fr)
Japanese (ja)
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隆雄 安井
馬場　嘉信
裕樹 市川
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Tokai National Higher Education and Research System NUC
Craif Inc
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Tokai National Higher Education and Research System NUC
Craif Inc
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Priority to EP20862815.6A priority Critical patent/EP4029940A4/en
Priority to JP2021545654A priority patent/JP7660898B2/ja
Priority to CN202080063346.XA priority patent/CN115038796A/zh
Priority to US17/641,054 priority patent/US20230265521A1/en
Publication of WO2021049671A1 publication Critical patent/WO2021049671A1/ja
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Priority to JP2025052355A priority patent/JP2025098184A/ja
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Definitions

  • the present disclosure relates to body fluid extracts containing microRNA.
  • Extracellular vesicles such as exosomes, microvesicles, and apoptotic bodies may contain microRNA (miRNA).
  • miRNA microRNA
  • EV Extracellular vesicles
  • miRNA microRNA
  • Differences in EV-encapsulated miRNA between two groups of humans can be a warning sign of various diseases (Non-Patent Document 20).
  • Encapsulation of miRNAs in EVs is considered to have the advantage of reducing the effect of ribonucleases on RNA degradation (Non-Patent Document 21), and miRNAs in EVs are considered to be more stable than free floating miRNAs. Be done.
  • Non-Patent Document 4 three methods have been used for EV recovery: ultracentrifugation or fractional centrifugation, immunocompatibility-based capture, and size exclusion chromatography.
  • Promising alternatives such as polymer precipitation (Non-Patent Document 22), microfluidic-based platforms (Non-Patent Documents 23-26), and size-based filtration methods (Non-Patent Document 27) have been reported.
  • these existing methods for recovering EV-encapsulating miRNAs were not sufficient for recovering EVs from EV-containing urine at very low concentrations ( ⁇ 0.01% by volume) (Non-Patent Document 28).
  • the ultracentrifugation method is the most commonly used method for the recovery of EV in urine. 200 to 300 types of miRNA have been identified in urine by ultracentrifugation (Non-Patent Documents 29 to 31). Over 2,000 types of human miRNAs have been reported. It was not clear whether the remaining 90% was actually present in the urine.
  • the present disclosure provides a body fluid extract containing microRNA.
  • EVs are efficiently captured on the nanowires.
  • the present inventors can effectively capture EV and miRNA in urine by contacting urine with the nanowires, and thereby obtain a type of miRNA that could not be extracted by conventional methods. It has been found that a urine extract containing can be obtained.
  • An extract of urine which includes the following (i) to (xvi): (I) Any of the microRNAs listed in data S1 or Table 2; (Ii) Any of the microRNAs listed in Table 4-1; (Iii) Any of the microRNAs listed in Table 4-2; (Iv) Any of the microRNAs listed in Table 4-3; (V) Any of the microRNAs listed in Table 4-4; (Vi) Any of the microRNAs listed in Table 4-5; (Vii) Any of the microRNAs listed in Table 4-6; (Viii) Any of the microRNAs listed in Table 4-7; (Ix) Any of the microRNAs listed in Table 4-8; (X) Any microRNA listed in Table 4-9; (Xi) Any of the microRNAs listed in Table 4-10; (Xii) Any of the microRNAs listed in Table 4-11; (Xiii) Any of the microRNAs listed in Table 4-12; (Xiv) Any of
  • the urine extract according to (1) above which comprises extracellular vesicles, wherein the microRNA is contained in the extracellular vesicles, or the microRNA is extracted from the extracellular vesicles.
  • the microRNAs are miR-3117-5p, miR-3118, miR-3121-3p, miR-3121-5p, miR-3126-5p, miR-3128, miR-3133, miR-3134, miR-3136.
  • miR-3136-5p miR-3139, miR-3142, miR-3143, miR-3145-3p, miR-3163, miR-3166, miR-3167, miR-16-1--3p, miR-424 -3p, miR-519c-5p, miR-525-5p, miR-551b-5p, miR-558, miR-921, miR-942-3p, miR-3126-3p, miR-3127-5p, miR-3129 -5p, miR-3144-5p, miR-3150a-5p, miR-3152-5p, miR-3155a, miR-3157-3p, miR-3159, miR-3165, miR-3678-3p, miR-4321, miR -4521, miR-4800-3p, miR-4999-5p, miR-5096, miR-5187-5p, miR-6874-5p, miR-3127-3p, miR-3130-5p, miR-3131, miR-3141 , MiR-3150b
  • Urine extract At least one microRNA selected from the group consisting of miR-3163, miR-16-1--3p, miR-424-3p, miR-558, miR-3127-5p, and miR-4521.
  • the microRNA is at least one microRNA selected from the group consisting of miR-378a-5p, miR-520c-3p, and miR-526b-3p, or all microRNAs (1) above.
  • microRNAs are let-7i-3p, miR-183-5p, miR-202-5p, miR-409-5p, miR-4661-5p, miR-4800-3p, miR-5587-5p, miR. -372-3p, miR-378b, miR-520b, miR-1266-3p, miR-3605-5p, miR-3612, miR-4645-3p, miR-4694-3p, miR-4752, miR-6816-3p , MiR-8087, let-7f-2-3p, miR-15a-3p, miR-20a-3p, miR-33b-3p, miR-34c-5p, miR-93-5p, miR-130a-5p, miR -135a-5p, miR-135b-5p, miR-185-5p, miR-203a-3p, miR-302d-5p, miR-337-3p, miR-378c, miR-422a, miR-449c-5p, miR
  • microRNA is at least one or all microRNAs selected from the group consisting of miR-183-5p, miR-202-5p, and miR-409-5p.
  • Urine extract. (10) The microRNAs are miR-372-3p, miR-520b, miR-15a-3p, miR-34c-5p, miR-135a-5p, miR-185-5p, miR-337-3p, miR-422a. , MiR-506-3p, miR-520c-3p, miR-1284, miR-1323, and miR-4273, which are at least one or all microRNAs selected from the group, according to (8) above. Urine extract.
  • the microRNAs are miR-4521, let-7c-3p, let-7i-5p, miR-16-1--3p, miR-26a-1--3p, miR-28-5p, miR-105-5p.
  • MicroRNA is derived from miR-16-1--3p, miR-28-5p, miR-297, miR-300, miR-330-3p, miR-454-5p, miR-1297, and miR-4295.
  • the urine extract according to (12) above which is at least one or all microRNAs selected from the group.
  • the urine extract according to (12) above, wherein the microRNA is miR-520c-3p.
  • the urine extract according to any one of (12) to (14) above, wherein the urine is urine of a subject having liver cancer.
  • the microRNA is miR-16-1--3p, miR-23b-3p, miR-28-5p, miR-92a-2-5p, miR-142-3p, miR-195-3p, miR-196b. -5p, miR-299-3p, miR-492, miR-513b-5p, miR-601, miR-619-5p, miR-1285-3p, miR-3155a, miR-3162-5p, miR-3678-3p , MiR-4283, miR-4295, miR-4511, miR-4531, miR-5096, miR-5187-5p, let-7f-2-3p, miR-520c-3p, and miR-4783-5p.
  • MicroRNA is derived from miR-16-1--3p, miR-23b-3p, miR-28-5p, miR-142-3p, miR-195-3p, miR-299-3p, and miR-4295.
  • the urine extract according to (16) above, wherein the microRNA is miR-520c-3p.
  • the urine extract according to any one of (16) to (18) above, wherein the urine is urine of a subject having bladder cancer.
  • the microRNA is miR-4531, miR-28-5p, miR-103a-2-5p, miR-105-5p, miR-124-3p, miR-151a-5p, miR-151b, miR-200a. -5p, miR-300, miR-424-3p, miR-519c-5p, miR-551b-5p, miR-617, miR-873-3p, miR-921, miR-1288-3p, miR-3124-5p , MiR-3155a, miR-3917, miR-4283, miR-4727-3p, miR-5096, miR-5187-5p, miR-6074, miR-6874-5p, miR-6892-5p, miR-15a-3p , MiR-135b-5p, miR-520c-3p, miR-4783-5p, and miR-7849-3p, which are at least one or all microRNAs selected from the group (1) to (3) above.
  • MicroRNA is at least one or all microRNAs selected from the group consisting of miR-28-5p, miR-105-5p, miR-124-3p, miR-151a-5p, and miR-300.
  • the urine is the urine of a healthy person, (1) to (6), (8) to (10), (12) to (14), (16 to (18), and (20) ⁇ .
  • (25) A method of inspecting the possibility that the subject has cancer.
  • a method comprising one or more selected from the group consisting of the following (a) to (e): (A) From the group consisting of miR-3163, miR-16-1--3p, miR-424-3p, miR-558, miR-3127-5p, and miR-4521 in urine or urine extract obtained from the subject.
  • microRNA In urine or urine extract obtained from the subject, miR-16-1--3p, miR-28-5p, miR-297, miR-300, miR-330-3p, miR-454-5p, miR Detecting at least one or all microRNAs selected from the group consisting of -1297 and miR-4295, where the subject has liver cancer if the amount of microRNA is higher than a predetermined value.
  • (D) In the urine or urine extract obtained from the subject, miR-16-1--3p, miR-23b-3p, miR-28-5p, miR-142-3p, miR-195-3p, miR- Detecting at least one or all microRNAs selected from the group consisting of 299-3p, and miR-4295, where the subject has a bladder if the amount of microRNA is higher than a predetermined value. Indicates that there is a possibility of urinary bladder; (E) At least selected from the group consisting of miR-28-5p, miR-105-5p, miR-124-3p, miR-151a-5p, and miR-300 in urine or urine extract obtained from the subject.
  • a method comprising one or more selected from the group consisting of (A) to (E): (A) In the urine or urine extract obtained from the subject in (a) above, at least one micro selected from the group consisting of miR-378a-5p, miR-520c-3p, and miR-526b-3p.
  • RNA or all microRNAs where the amount of microRNAs is lower than a given value, indicates that the subject may have lung cancer;
  • miR-372-3p, miR-520b, miR-15a-3p, miR-34c-5p, miR-135a-5p, miR- At least one or all selected from the group consisting of 185-5p, miR-337-3p, miR-422a, miR-506-3p, miR-520c-3p, miR-1284, miR-1323, and miR-4273.
  • microRNAs Further detection of microRNAs, and here, if the amount of microRNAs is below a given value, indicates that the subject may have pancreatic cancer; (C) Further detection of miR-520c-3p in the urine or urine extract obtained from the subject in (c) above, and where the amount of microRNA is lower than a predetermined value, Indicates that the subject may have liver cancer; (D) Further detection of miR-520c-3p in the urine or urine extract obtained from the subject in (d) above, and where the amount of microRNA is lower than a predetermined value, Indicates that the subject may have bladder cancer; (E) In the urine or urine extract obtained from the subject in (e) above, at least one or all microRNAs selected from the group consisting of miR-15a-3p and miR-520c-3p are further detected.
  • the urine extract according to (1) above which comprises one or more microRNAs selected from the group consisting of the following: hsa-miR-103a-3p, hsa-miR-1193, hsa-miR-127-3p, hsa-miR-1247-3p, hsa-miR-1263, hsa-miR-173g-3p, hsa-miR-129- 2-3p, hsa-miR-1293, hsa-miR-130a-5p, hsa-miR-1469, hsa-miR-15b-3p, hsa-miR-193b-3p, hsa-miR-2861, hsa-miR- 298, hsa-miR-30d-5p, hsa-miR-3122, hsa-miR-3137, hsa-miR-3174, hsa-mi
  • the urine extract according to (1) above which comprises one or more microRNAs selected from the group consisting of the following: hsa-miR-103a-2-5p, hsa-miR-1193, hsa-miR-3622a-5p, hsa-miR-363-3p, hsa-miR-4521, hsa-miR-4996-5p, hsa-miR- 518f-3p, hsa-miR-5580-5p, hsa-miR-3125, hsa-miR-3130-3p, hsa-miR-3678-3p, hsa-miR-4750-5p, hsa-miR-5194, hsa- miR-578, hsa-miR-625-5p, hsa-miR-6755-3p, hsa-miR-1293, hsa-miR-12
  • the urine extract according to (1) above which comprises one or more microRNAs selected from the group consisting of the following: hsa-miR-103a-2-5p, hsa-miR-106a-3p, hsa. -MiR-1185-2-3p, hsa-miR-1193, hsa-miR-1273g-3p, hsa-miR-1293, hsa-miR-1301-5p, hsa-miR-152-5p, hsa-miR-184 , Hsa-miR-200c-5p, hsa-miR-2909, hsa-miR-298, hsa-miR-302b-3p, hsa-miR-3116, hsa-miR-3122, hsa-miR-3125, hsa-miR -3126-3p, hsa-miR-3129-3
  • a method of predicting the possibility that the subject has lung cancer To detect one or more microRNAs selected from the following group in the urine of the subject, and Methods including predicting the possibility that the subject has cancer using the expression level of the microRNA as an index: hsa-miR-4443, hsa-miR-4515, hsa-miR-47343-5p, hsa-miR- 1908-3p, hsa-miR-4314, hsa-miR-296-3p, hsa-miR-6772-5p, hsa-miR-370-3p, hsa-miR-4708-3p, hsa-miR-4499, hsa- miR-6759-5p, hsa-miR-3160-3p, hsa-miR-219a-2-3p, hsa-miR-564, hsa-miR-4269,
  • the miRNA detected is one or more microRNAs selected from the group consisting of the following: methods: hsa-miR-6788-5p, hsa-miR- 6500-3p, hsa-miR-5189-5p, hsa-miR-7151-3p, hsa-miR-891a-5p, hsa-miR-3126-5p, hsa-miR-8083, hsa-miR-4428, hsa- miR-4474-3p, hsa-miR-7850-5p, hsa-miR-4700-5p, hsa-miR-6828-5p, hsa-miR-668-5p, hsa-miR-3943-5p, hsa-miR- 4654, hsa-miR-4436a, hsa-miR-173
  • the detected miRNA is one or more microRNAs selected from the group consisting of the following: methods: hsa-miR-4644, hsa-miR-4754, hsa-miR-477-3p, hsa-miR-4445-3p, hsa-miR-4436b-3p, hsa-miR-4262, hsa-miR-1306-3p, hsa-miR-4514, hsa-miR-4296, hsa-miR-4458, hsa-miR-4520-5p, hsa-miR-766-5p, hsa-miR-548ao-3p, hsa-miR-758-5p, hsa-miR-4451, hsa-miR-4300, hsa-miR-4453, hs
  • the detected miRNA is one or more microRNAs selected from the group consisting of the following: methods: hsa-miR-4768-3p, hsa-miR- 1265, hsa-miR-4321, hsa-miR-4423-5p, hsa-miR-1294, and hsa-miR-4520-3p.
  • 5D The method according to any one of (5), (5A), (5B), and (5C) above, wherein the detected miRNA is 5 or more microRNAs selected from the group consisting of the following. Is the way.
  • (5E) The method according to any one of (5), (5A), (5B), and (5C) above, wherein the detected miRNA is 10 or more microRNAs selected from the group consisting of the following. Is the way.
  • (5F) The method according to any one of (5), (5A), (5B), and (5C) above, wherein the detected miRNA is 15 or more microRNAs selected from the group consisting of the following. Is the way.
  • (5G) The method according to any one of (5), (5A), (5B), and (5C) above, wherein the detected miRNA is 20 or more microRNAs selected from the group consisting of the following. Is the way.
  • (5H) The method according to any one of (5D) to (5G) above, wherein the prediction accuracy and specificity exceed 50%.
  • the method comprising predicting the possibility that the subject is cancer using the above as an index: hsa-miR-147b, hsa-miR-3912-5p, hsa-miR-148a-5p, hsa-miR-6773-5p, hsa-miR-3681-5p, hsa-miR-3976, hsa-miR-3121-5p, hsa-miR-6082, hsa-miR-106b-5p, hsa-miR-758-3p, hsa-miR-4418, hsa-miR-216a-5p, hsa-miR-34a-3p, hsa-miR-516b-5p, hsa-miR-140-5p, hsa-miR-7154-5p, hsa-miR-616-5p, hsa- miR-5701,
  • the detected miRNA is one or more microRNAs selected from the group consisting of the following: methods: hsa-miR-147b, hsa-miR-3922- 5p, hsa-miR-148a-5p, hsa-miR-6673-5p, hsa-miR-3681-5p, hsa-miR-3976, hsa-miR-3121-5p, hsa-miR-6082, hsa-miR- 106b-5p, hsa-miR-758-3p, hsa-miR-4418, hsa-miR-216a-5p, hsa-miR-34a-3p, hsa-miR-516b-5p, hsa-miR-140-5p, hsa-miR-7154-5p, hsa-miRs
  • the detected miRNA is one or more microRNAs selected from the group consisting of the following: methods: hsa-miR-147b, hsa-miR-3922- 5p, hsa-miR-148a-5p, hsa-miR-6673-5p, hsa-miR-3681-5p, hsa-miR-3976, hsa-miR-3121-5p, hsa-miR-6082, hsa-miR- 106b-5p, hsa-miR-758-3p, hsa-miR-4418, hsa-miR-216a-5p, hsa-miR-34a-3p, hsa-miR-516b-5p, hsa-miR-140-5p, hsa-miR-7154-5p, hsa-miRs
  • the detected miRNA is one or more microRNAs selected from the group consisting of the following: methods: hsa-miR-147b, hsa-miR-3922- 5p, hsa-miR-148a-5p, hsa-miR-6673-5p, hsa-miR-3681-5p, hsa-miR-3976, hsa-miR-3121-5p, hsa-miR-6082, hsa-miR- 106b-5p, hsa-miR-758-3p, hsa-miR-4418, hsa-miR-216a-5p, hsa-miR-34a-3p, hsa-miR-516b-5p, hsa-miR-140-5p, hsa-miR-7154-5p, hsa-miRs
  • (6D) The method according to any one of (6), (6A), (6B), and (6C) above, wherein the detected miRNA is 5 or more microRNAs selected from the group consisting of the following. Is the way.
  • (6E) The method according to any one of (6), (6A), (6B), and (6C) above, wherein the detected miRNA is 10 or more microRNAs selected from the group consisting of the following. Is the way.
  • (6F) The method according to any one of (6), (6A), (6B), and (6C) above, wherein the detected miRNA is 15 or more microRNAs selected from the group consisting of the following. Is the way.
  • (6G) The method according to any one of (6), (6A), (6B), and (6C) above, wherein the detected miRNA is 20 or more microRNAs selected from the group consisting of the following. Is the way.
  • (6H) The method according to any one of (6D) to (6G) above, wherein any or all of the prediction accuracy, sensitivity and specificity exceed 50%.
  • (6I) The method according to any one of (6D) to (6G) above, wherein any or all of the prediction accuracy, sensitivity and specificity exceed 60%.
  • (6J) The method according to any one of (6D) to (6G) above, wherein any or all of the prediction accuracy, sensitivity and specificity exceed 70%.
  • (6K) The method according to any one of (6D) to (6G) above, wherein any or all of the prediction accuracy, sensitivity and specificity exceed 80%.
  • (6L) The method according to any one of (6D) to (6K) above, wherein the area under the curve (AUC) of the receiver operating characteristic curve (ROC) exceeds 0.5, exceeds 0.6. A method of greater than 0.7, greater than 0.8, greater than 0.9, or greater than 0.95.
  • (6M) The method according to (6L) above, which predicts whether or not a subject has the possibility of lung cancer based on a cutoff value of true positive rate> false positive rate.
  • the pH of urine to be brought into contact with nanowires is a numerical range in which 2, 3, 4, or 5 is the lower limit and 11, 10, 9, 8, 7, 6, or 5 is the upper limit.
  • the urine extract according to (8) or (8A) above, wherein the nanowire is a metal oxide nanowire or a nanowire whose surface is coated with a metal oxide.
  • Extract. (10D') The above-mentioned (9), (9A), (9B), (9C), (9D) or (9E) containing 65% or more of extracellular vesicles contained in urine.
  • Urine extract. (10E) The urine according to (9), (9A), (9B), (9C), (9D) or (9E) above, which contains 70% or more of extracellular vesicles contained in urine. Extract. (10E') The above-mentioned (9), (9A), (9B), (9C), (9D) or (9E), which contains 75% or more of extracellular vesicles contained in urine. Urine extract.
  • a method for detecting microRNA in a subject's body fluid in which at least one microRNA selected from the following group or all microRNAs is detected as a body fluid sample obtained from the subject. Methods are provided that include detection by contact with a microRNA detector: hsa-miR-103a-2-5p, hsa-miR-106a-3p, hsa-miR-1185-2-3p.
  • An extract of urine which includes the following (i) to (xvi): (I) Any of the microRNAs listed in data S1 or Table 2; (Ii) Any of the microRNAs listed in Table 4-1; (Iii) Any of the microRNAs listed in Table 4-2; (Iv) Any of the microRNAs listed in Table 4-3; (V) Any of the microRNAs listed in Table 4-4; (Vi) Any of the microRNAs listed in Table 4-5; (Vii) Any of the microRNAs listed in Table 4-6; (Viii) Any of the microRNAs listed in Table 4-7; (Ix) Any of the microRNAs listed in Table 4-8; (X) Any microRNA listed in Table 4-9; (Xi) Any of the microRNAs listed in Table 4-10; (Xii) Any of the microRNAs listed in Table 4-11; (Xiii) Any of the microRNAs listed in Table 4-12; (Xiv) Any of the microRNAs listed in Table 4-13; (Xv) Any of the micro
  • the urine extract may contain a plurality of combinations of microRNAs from a particular table, and may contain a plurality of such combinations ⁇ .
  • the urine extract according to the above [1] which contains microRNA selected from the group consisting of ⁇ 1 or more, 2 or more, 3 or more, 4 or more, 5 of each of the microRNAs in each table independently. It may contain more than 10 kinds, more than 10 kinds, more than 15 kinds, or more than 20 kinds ⁇ .
  • the urine extract according to the above [1]. (Ii) Any of the microRNAs shown in Table 4-1 ⁇ 1 or more, 2 or more, 3 or more, 4 or more, 5 or more, 10 or more, 15 or more, or 20 or more micros Can be RNA ⁇ Urine extract, which is a urine extract of lung cancer patients. [4] The urine extract according to the above [1].
  • RNA ⁇ Urine extract which comprises, is a urine extract of breast cancer patients. [5] The urine extract according to the above [1].
  • RNA ⁇ Urine extract Any of the microRNAs shown in Table 4-3 ⁇ 1 or more, 2 or more, 3 or more, 4 or more, 5 or more, 10 or more, 15 or more, or 20 or more micro Can be RNA ⁇ Urine extract, which is a urine extract of patients with kidney cancer. [6] The urine extract according to the above [1].
  • RNA ⁇ A urine extract which comprises, is a urine extract of a leukemia patient. [7] The urine extract according to the above [1].
  • Vi Any of the microRNAs shown in Table 4-5 ⁇ 1 or more, 2 or more, 3 or more, 4 or more, 5 or more, 10 or more, 15 or more, or 20 or more micro Can be RNA ⁇ A urine extract that contains, is a urine extract of a lymphoma patient. [8] The urine extract according to the above [1].
  • RNA ⁇ Urine extract which comprises, is a urine extract of pancreatic cancer patients. [9] The urine extract according to the above [1].
  • RNA ⁇ A urine extract which comprises, is a urine extract of a prostate cancer patient. [10] The urine extract according to the above [1].
  • RNA ⁇ Urine extract Any of the microRNAs shown in Table 4-8 ⁇ 1 or more, 2 or more, 3 or more, 4 or more, 5 or more, 10 or more, 15 or more, or 20 or more micro Can be RNA ⁇ Urine extract, which is a urine extract of gastric cancer patients. [11] The urine extract according to the above [1]. (X) Any of the microRNAs shown in Table 4-9 ⁇ 1 or more, 2 or more, 3 or more, 4 or more, 5 or more, 10 or more, 15 or more, or 20 or more micro Can be RNA ⁇ Urine extract, which is a urine extract of patients with urothelial cancer. [12] The urine extract according to the above [1].
  • RNA ⁇ A urine extract which comprises, is a urine extract of a melanoma patient. [13] The urine extract according to the above [1].
  • Xii Any of the microRNAs shown in Table 4-11 ⁇ 1 or more, 2 or more, 3 or more, 4 or more, 5 or more, 10 or more, 15 or more, or 20 or more micro Can be RNA ⁇ Urine extract, which is a urine extract of ovarian cancer patients. [14] The urine extract according to the above [1].
  • RNA ⁇ Urine extract which is a urine extract of thyroid cancer patients. [15] The urine extract according to the above [1].
  • Xiii Any of the microRNAs shown in Table 4-13 ⁇ 1 or more, 2 or more, 3 or more, 4 or more, 5 or more, 10 or more, 15 or more, or 20 or more micro Can be RNA ⁇ Urine extract, which is a urine extract of cervical cancer patients. [16] The urine extract according to the above [1].
  • RNA ⁇ Urine extract which is a urine extract of patients with rectal colon cancer.
  • RNA ⁇ Urine extract Any of the microRNAs shown in Table 4-15 ⁇ 1 or more, 2 or more, 3 or more, 4 or more, 5 or more, 10 or more, 15 or more, or 20 or more micro Can be RNA ⁇ Urine extract, which is a urine extract of patients with endometrial cancer.
  • the expression level of 20 or more types of microRNA ⁇ which comprises predicting the possibility that the subject has cancer.
  • the microRNA is one kind.
  • the expression level of 2 or more, 3 or more, 4 or more, 5 or more, 10 or more, 15 or more, or 20 or more microRNAs ⁇ is set for each microRNA.
  • the microRNA In the urine extract obtained from the subject, one or more of the microRNAs whose expression levels are increased in cancer patients in each table ⁇ In each table, the microRNA is one or more.
  • the expression level of 2, 2 or more, 3 or more, 4 or more, 5 or more, 10 or more, 15 or more, or 20 or more microRNAs ⁇ is set for each microRNA. If the urine is above the threshold of, lung cancer, breast cancer, kidney cancer, leukemia, lymphoma, pancreatic cancer, prostate cancer, melanoma, ovarian cancer, thyroid cancer, cervical cancer, rectal colon
  • the urine extract obtained from the subject miR-641, let-7a-3p, miR-1279, miR-548aa, miR-548t-3p, miR-548av-3p, miR-376b-5p, and Any one or more of microRNAs selected from the group consisting of miR-9851-3p ⁇ 1 or more, 2 or more, 3 or more, 4 or more, 5 or more, 10 or more, 15 or more, or If the expression level of more than 20 types of microRNA ⁇ is equal to or higher than the first threshold value set for each microRNA, the urine may be derived from a patient with kidney cancer. The method according to any one of the above [20] to [22].
  • the expression level of 4 or more, 5 or more, 10 or more, 15 or more, or 20 or more microRNAs ⁇ is equal to or higher than the first threshold value set for each microRNA.
  • the urine extract obtained from the subject selected from the group consisting of miR-30e-3p, miR-3166, miR-3942-5p, miR-4482-5p, miR-4493, and miR-5008-3p.
  • Any one or more of the microRNAs to be used ⁇ 1 or more, 2 or more, 3 or more, 4 or more, 5 or more, 10 or more, 15 or more, or 20 or more microRNAs can be used ⁇
  • the urine may be derived from a patient having lymphoma, [20] to [22] above. The method described in any of.
  • the expression level of any one or more of ⁇ may be 1 or more, 2 or more, 3 or more, 4 or more, 5 or more, 10 or more, 15 or more, or 20 or more microRNAs ⁇ , which of the above [20] to [22] indicates that the urine may be derived from a patient having pancreatic cancer when the value is equal to or higher than the first threshold value set for each microRNA.
  • the method described in Crab. [29] In the urine extract obtained from the subject, when the expression level of miR-1324 is equal to or higher than the first threshold value set for each microRNA, the urine is derived from a patient having prostate cancer.
  • any one or more of microRNAs selected from the group consisting of miR-4795-3p, miR-5707 and miR-655-5p ⁇ 1 or more and 2 types The expression level of 3 or more, 4 or more, 5 or more, 10 or more, 15 or more, or 20 or more microRNAs ⁇ is equal to or greater than the first threshold set for each microRNA.
  • any one or more of microRNAs selected from the group consisting of miR-335-5p, miR-27a-5p, miR-499a-3p, and miR-8084 is set for each microRNA.
  • the urine may be derived from a patient having cervical cancer in some cases.
  • the expression level of more than one species ⁇ which can be 1 or more, 2 or more, 3 or more, 4 or more, 5 or more, 10 or more, 15 or more, or 20 or more microRNAs ⁇ is per microRNA.
  • the first threshold value is a value equal to or less than the third quartile value of the corresponding microRNA in a healthy subject.
  • urine may be derived from a patient with thyroid cancer.
  • ⁇ It can be 1 or more, 2 or more, 3 or more, 4 or more, 5 or more, 10 or more, 15 or more, or 20 or more microRNAs ⁇ MicroRNAs with higher expression than the first threshold, or microRNAs with lower expression than non-cancer patients in cancer patients, are above the second threshold.
  • a method in which urine may be derived from a patient who does not have cancer. [41] A method for predicting the likelihood that a subject will have early-stage cancer in a subject having or suspected of having cancer, in Tables 22-1 and 23 of the subject's urine extract.
  • MicroRNA described in any of the tables -1 to 23-14 ⁇ In each table the microRNA is 1 or more, 2 or more, 3 or more, 4 or more, 5 or more, 10 or more, A method comprising predicting the likelihood that a subject will have early-stage cancer using the expression of 15 or more, or 20 or more, microRNAs ⁇ as indicators.
  • a method for predicting the likelihood that a subject will have stage I early cancer in a subject who has or is suspected of having cancer and is any of Tables 22-1 to 22-13. Expression of microRNAs listed in the table ⁇ In each table, the microRNAs are 1 or more, 2 or more, 3 or more, 4 or more, 5 or more, 10 or more, 15 or more, or 20 or more.
  • the method according to [41] above which comprises predicting the possibility that the subject has early-stage cancer using the microRNA of [43]
  • a method for analyzing a urine sample Contacting a urine sample with nanowires ⁇ which can be nanowires in a nanowire-embedded fluid device with nanowires ⁇ Extracting the microRNA captured on the nanowires and Including confirming whether or not a specific microRNA is contained in the extracted microRNA by contacting it with a nucleic acid containing a sequence capable of hybridizing with the microRNA.
  • microRNAs listed in data S1 or Table 2 Any of the microRNAs listed in data S1 or Table 2; (Ii) Any of the microRNAs listed in Table 4-1; (Iii) Any of the microRNAs listed in Table 4-2; (Iv) Any of the microRNAs listed in Table 4-3; (V) Any of the microRNAs listed in Table 4-4; (Vi) Any of the microRNAs listed in Table 4-5; (Vii) Any of the microRNAs listed in Table 4-6; (Viii) Any of the microRNAs listed in Table 4-7; (Ix) Any of the microRNAs listed in Table 4-8; (X) Any microRNA listed in Table 4-9; (Xi) Any of the microRNAs listed in Table 4-10; (Xii) Any of the microRNAs listed in Table 4-11; (Xiii) Any of the microRNAs listed in Table 4-12; (Xiv) Any of the microRNAs listed in Table 4-13; (Xv) Any of the microRNAs listed in Table 4-14; and
  • microRNA selected from the group consisting of ⁇ In each table, 1 type or more, 2 types or more, 3 types or more, 4 types or more, 5 types or more, 10 types or more, 15 types or more, Or it can be more than 20 microRNAs ⁇ .
  • Urine is the urine of a subject who has or is suspected of having lung cancer.
  • Specific micro RNA (Ii) Any of the microRNAs shown in Table 4-1 ⁇ 1 or more, 2 or more, 3 or more, 4 or more, 5 or more, 10 or more, 15 or more, or 20 or more micros Can be RNA ⁇ Is the way. [46] The method according to the above [43] or [44].
  • Urine is the urine of a subject who has or is suspected of having breast cancer.
  • Specific micro RNA (Iii) MicroRNA of any of the microRNAs shown in Table 4-2 ⁇ 1 type or more, 2 types or more, 3 types or more, 4 types or more, 5 types or more, 10 types or more, 15 types or more, or 20 types Can be the above micro RNA ⁇ Is the way. [47] The method according to the above [43] or [44].
  • Urine is the urine of a subject who has or is suspected of having breast cancer.
  • Specific micro RNA (Iv) Any of the microRNAs shown in Table 4-3 ⁇ 1 or more, 2 or more, 3 or more, 4 or more, 5 or more, 10 or more, 15 or more, or 20 or more micro Can be RNA ⁇ Is the way. [48] The method according to the above [43] or [44]. Urine is the urine of a subject who has or is suspected of having leukemia. Specific micro RNA, (V) Any of the microRNAs shown in Table 4-4 ⁇ 1 or more, 2 or more, 3 or more, 4 or more, 5 or more, 10 or more, 15 or more, or 20 or more micro Can be RNA ⁇ Is the way. [49] The method according to the above [43] or [44].
  • Urine is the urine of a subject with or suspected of having lymphoma, Specific micro RNA, (Vi) Any of the microRNAs shown in Table 4-5 ⁇ 1 or more, 2 or more, 3 or more, 4 or more, 5 or more, 10 or more, 15 or more, or 20 or more micro Can be RNA ⁇ Is the way. [50] The method according to the above [43] or [44]. Urine is the urine of a subject who has or is suspected of having pancreatic cancer. Specific micro RNA, (Vii) Any of the microRNAs shown in Table 4-6 ⁇ 1 or more, 2 or more, 3 or more, 4 or more, 5 or more, 10 or more, 15 or more, or 20 or more micro Can be RNA ⁇ Is the way.
  • Urine is the urine of a subject who has or is suspected of having prostate cancer.
  • Specific micro RNA (Viii) Any of the microRNAs shown in Table 4-7 ⁇ 1 or more, 2 or more, 3 or more, 4 or more, 5 or more, 10 or more, 15 or more, or 20 or more micro Can be RNA ⁇ Is the way.
  • Urine is the urine of a subject who has or is suspected of having gastric cancer.
  • Specific micro RNA (Ix) Any of the microRNAs shown in Table 4-8 ⁇ 1 or more, 2 or more, 3 or more, 4 or more, 5 or more, 10 or more, 15 or more, or 20 or more micro Can be RNA ⁇ Is the way. [53] The method according to the above [43] or [44]. Urine is the urine of a subject who has or is suspected of having urothelial cancer. Specific micro RNA, (X) Any of the microRNAs shown in Table 4-9 ⁇ 1 or more, 2 or more, 3 or more, 4 or more, 5 or more, 10 or more, 15 or more, or 20 or more micro Can be RNA ⁇ Is the way. [54] The method according to the above [43] or [44].
  • Urine is the urine of a subject who has or is suspected of having melanoma.
  • Specific micro RNA (Xi) Any of the microRNAs shown in Table 4-10 ⁇ 1 or more, 2 or more, 3 or more, 4 or more, 5 or more, 10 or more, 15 or more, or 20 or more micro Can be RNA ⁇ Is the way. [55] The method according to the above [43] or [44]. Urine is the urine of a subject who has or is suspected of having ovarian cancer.
  • Urine is the urine of a subject who has or is suspected of having thyroid cancer.
  • Specific micro RNA (Xiii) Any of the microRNAs shown in Table 4-12 ⁇ 1 or more, 2 or more, 3 or more, 4 or more, 5 or more, 10 or more, 15 or more, or 20 or more micro Can be RNA ⁇ Is the way.
  • Urine is the urine of a subject who has or is suspected of having cervical cancer.
  • micro RNA Any of the microRNAs shown in Table 4-13 ⁇ 1 or more, 2 or more, 3 or more, 4 or more, 5 or more, 10 or more, 15 or more, or 20 or more micro Can be RNA ⁇ Is the way. [58] The method according to the above [43] or [44]. Urine is the urine of a subject who has or is suspected of having rectal colon cancer. Specific micro RNA, (Xiii) Any of the microRNAs shown in Table 4-14 ⁇ 1 or more, 2 or more, 3 or more, 4 or more, 5 or more, 10 or more, 15 or more, or 20 or more micro Can be RNA ⁇ Is the way. [59] The method according to the above [43] or [44].
  • Urine is the urine of a subject who has or is suspected of having endometrial cancer.
  • Specific micro RNA (Xiii) Any of the microRNAs shown in Table 4-15 ⁇ 1 or more, 2 or more, 3 or more, 4 or more, 5 or more, 10 or more, 15 or more, or 20 or more micro Can be RNA ⁇ Is the way.
  • the microRNA has a p-value of less than 0.005 ⁇ in each table, the microRNA is one or more and two or more. 3 or more, 4 or more, 5 or more, 10 or more, 15 or more, or 20 or more microRNAs ⁇ .
  • a method for analyzing a urine sample is one or more and two or more. 3 or more, 4 or more, 5 or more, 10 or more, 15 or more, or 20 or more microRNAs ⁇ .
  • Specific micro RNA (B) MicroRNAs listed in any of Tables 22-1 to 22-13 ⁇ In each table, 1 or more, 2 or more, 3 or more, 4 or more, 5 or more, respectively, Can be 10 or more, 15 or more, or 20 or more microRNAs ⁇ Is the way. [63] The method for analyzing a urine sample according to the above [61].
  • Specific micro RNA (A) MicroRNAs listed in any of Tables 22-1 and 23-1 to 23-14 ⁇ In each table, 1 or more, 2 or more, 3 or more, 4 or more, respectively. It can be 5 or more, 10 or more, 15 or more, or 20 or more microRNAs ⁇ A method of microRNA having an accuracy of 70% or higher.
  • microRNAs can be 5 or more, 10 or more, 15 or more, or 20 or more microRNAs ⁇ A method of microRNA having an accuracy of 90% or higher.
  • a method for analyzing a urine sample Contacting the urine sample with nanowires Extracting the microRNA captured on the nanowires and Including confirming whether or not a specific microRNA is contained in the extracted microRNA by contacting it with a nucleic acid containing a sequence capable of hybridizing with the microRNA.
  • Specific micro RNA MicroRNAs listed in any of Tables 22-1 to 22-13 and Tables 23-1 to 23-14 ⁇ In each table, 1 or more, 2 or more, 3 or more independently, respectively. 4 or more, 5 or more, 10 or more, 15 or more, or 20 or more microRNAs ⁇ , the method of which is a microRNA having an accuracy of 70% or more in the table. [71] The method for analyzing urine according to the above [69]. Specific micro RNA (C) MicroRNAs listed in any of Tables 22-1 to 22-13 and Tables 23-1 to 23-14 ⁇ In each table, 1 or more, 2 or more, 3 or more independently, respectively.
  • microRNAs can be 4 or more, 5 or more, 10 or more, 15 or more, or 20 or more microRNAs ⁇ The method, wherein the microRNA has an accuracy of 80% or more in the table.
  • a method for analyzing a urine sample is described in Tables 22-1 to 22-13 and Tables 23-1 to 23-14 ⁇ In each table, 1 or more, 2 or more, 3 types, respectively. It can be 4 or more, 5 or more, 10 or more, 15 or more, or 20 or more microRNAs ⁇ The method, wherein the microRNA has an accuracy of 90% or more in the table.
  • a nanowire-embedded fluid device having nanowires of metal oxides (eg, zinc oxide) Extracting the microRNA captured on the nanowires and Including confirming whether or not a specific microRNA is contained in the extracted microRNA by contacting it with a nucleic acid containing a sequence capable of hybridizing with the microRNA.
  • metal oxides eg, zinc oxide
  • miR-134-5p miR-346, miR-564, miR-574-3p, miR-575, miR-632, miR-661, miR-663a, miR-658, miR-297, miR-139-3p, miR-149-3p, miR-20b-3p, miR-431-3p, miR-550a-5p, miR-885-5p, miR-936, miR-937-3p, miR-943, miR-1228-5p, miR-1184, miR-1204, miR-1538, miR-1909-5p, miR-1910-5p, miR-1912-3p, miR-196b-3p, miR-1972, miR-3153, miR-3162-5p, miR-1193, miR-4260, miR-4253, miR-4326, miR-4269, miR-4276, miR-3622a-3p, miR-3646, miR-3652, miR-3180, miR-550b-3p, miR-134-5p
  • a method for analyzing a urine sample Contacting a urine sample with nanowires in a nanowire-embedded fluid device having nanowires of metal oxides (eg, zinc oxide) Extracting the microRNA captured on the nanowires and Including confirming whether or not a specific microRNA is contained in the extracted microRNA by contacting it with a nucleic acid containing a sequence capable of hybridizing with the microRNA.
  • metal oxides eg, zinc oxide
  • a method for analyzing a urine sample Contacting a urine sample with nanowires in a nanowire-embedded fluid device having nanowires of metal oxides (eg, zinc oxide) Extracting the microRNA captured on the nanowires and Including confirming whether or not a specific microRNA is contained in the extracted microRNA by contacting it with a nucleic acid containing a sequence capable of hybridizing with the microRNA.
  • metal oxides eg, zinc oxide
  • miR-105-5p miR-192-5p, miR-198, miR-129-5p, miR-187-3p, miR-210-3p, miR-212-3p, miR-214-3p, miR-200b- 3p, miR-125b-5p, miR-138-5p, miR-134-5p, miR-184, miR-185-5p, miR-206, miR-106b-5p, miR-34c-5p, miR-99b- 5p, miR-296-5p, miR-130b-3p, miR-302c-5p, miR-370-3p, miR-373-3p, miR-378a-3p, miR-382-5p, miR-340-3p, miR-342-3p, miR-337-3p, miR-323a-3p, miR-324-5p, miR-346, miR-422a, miR-425-3p, miR-369-5p, miR-323b-5p, miR-409
  • a method for analyzing a urine sample Contacting a urine sample with nanowires in a nanowire-embedded fluid device having nanowires of metal oxides (eg, zinc oxide) Extracting the microRNA captured on the nanowires and Including confirming whether or not a specific microRNA is contained in the extracted microRNA by contacting it with a nucleic acid containing a sequence capable of hybridizing with the microRNA.
  • metal oxides eg, zinc oxide
  • RNA let-7b-5p miR-25-3p, miR-28-5p, miR-29a-3p, miR-29b-3p, miR-105-5p, miR-192-5p, miR-196a-5p, miR- 197-3p, miR-198, miR-199a-5p, miR-129-5p, miR-30d-5p, miR-147a, miR-10a-5p, miR-34a-5p, miR-181a-5p, miR- 181b-5p, miR-187-3p, miR-199b-5p, miR-204-5p, miR-210-3p, miR-221-5p, miR-212-3p, miR-214-3p, miR-221- 3p, miR-223-3p, miR-200b-3p, miR-23b-3p, miR-30b-5p, miR-122-5p, miR-124-3p, miR-125b-5p, miR-138-5p, miR-125a
  • microRNA can be 1 or more, 2 or more, 3 or more, 4 or more, 5 or more, 10 or more, 15 or more, or 20 or more.
  • microRNA can be 1 or more, 2 or more, 3 or more, 4 or more, 5 or more, 10 or more, 15 or more, or 20 or more.
  • the method [81] A method for predicting the likelihood that a subject will have early-stage cancer in a subject who has or is suspected of having cancer.
  • the microRNA further satisfies the condition that the expression is improved in cancer patients in Tables 4-1 to 4-15 ⁇ in each table, the microRNA Can be 1 or more, 2 or more, 3 or more, 4 or more, 5 or more, 10 or more, 15 or more, or 20 or more microRNAs ⁇ .
  • the presence of microRNA showing expression higher than the first threshold indicates that the subject from which the urine is derived may have early cancer.
  • Method. A method for predicting the likelihood that a subject will have early-stage cancer in a subject who has or is suspected of having cancer.
  • MicroRNA according to the method described in [74] above which further satisfies the condition that the expression of microRNA is improved in cancer patients in Tables 4-1 to 4-15 ⁇ independently in each table. It can be 1 or more, 2 or more, 3 or more, 4 or more, 5 or more, 10 or more, 15 or more, or 20 or more microRNAs ⁇ .
  • the presence of microRNA showing expression higher than the first threshold indicates that the subject from which the urine is derived may be gastrointestinal cancer.
  • Method. [83] The subject according to [82] above, wherein the subject having or suspected of having cancer is a subject having or suspected of having gastrointestinal cancer. the method of.
  • microRNA further satisfies the condition that the expression is improved in cancer patients in Tables 4-1 to 4-15 ⁇ in each table, each is independent. It can be 1 or more, 2 or more, 3 or more, 4 or more, 5 or more, 10 or more, 15 or more, or 20 or more microRNAs ⁇ .
  • the presence of microRNA showing expression higher than the first threshold indicates that the subject from which the urine is derived may be hematopoietic cancer.
  • the subject having or suspected of having cancer is a subject having or suspected of having hematopoietic cancer, according to [84] above. the method of. [86] A method for predicting the likelihood that a subject will have early-stage cancer in a subject who has or is suspected of having cancer.
  • MicroRNA according to the method described in [76] above, which further satisfies the condition that the expression of microRNA is improved in cancer patients in Tables 4-1 to 4-15 ⁇ independently in each table. It can be 1 or more, 2 or more, 3 or more, 4 or more, 5 or more, 10 or more, 15 or more, or 20 or more microRNAs ⁇ .
  • the presence of microRNA showing expression higher than the first threshold indicates that the subject from which the urine is derived may be urinary cancer.
  • Method. [87] The method according to [86] above, wherein the subject having or suspected of having cancer is a subject having or suspected of having urinary cancer. .. [88] A method for predicting the likelihood that a subject will have early-stage cancer in a subject who has or is suspected of having cancer.
  • MicroRNA according to the method described in [73] above which further satisfies the condition that the expression of microRNA is reduced in cancer patients in Tables 4-1 to 4-15 ⁇ independently in each table. It can be 1 or more, 2 or more, 3 or more, 4 or more, 5 or more, 10 or more, 15 or more, or 20 or more microRNAs ⁇ .
  • the presence of microRNA showing expression below the first threshold indicates that the subject from which the urine is derived may be cancer.
  • MicroRNA according to the method described in [74] above, which further satisfies the condition that the expression of microRNA is reduced in cancer patients in Tables 4-1 to 4-15 ⁇ independently in each table. It can be 1 or more, 2 or more, 3 or more, 4 or more, 5 or more, 10 or more, 15 or more, or 20 or more microRNAs ⁇ .
  • the presence of microRNAs with lower expression than healthy individuals indicates that the subject from which the urine is derived may be gastrointestinal cancer.
  • Method The subject according to [89] above, wherein the subject having or suspected of having cancer is a subject having or suspected of having gastrointestinal cancer.
  • MicroRNA according to the method described in [75] above, which further satisfies the condition that the expression of microRNA is reduced in cancer patients in Tables 4-1 to 4-15 ⁇ independently in each table. It can be 1 or more, 2 or more, 3 or more, 4 or more, 5 or more, 10 or more, 15 or more, or 20 or more microRNAs ⁇ .
  • the presence of microRNAs with lower expression than healthy individuals indicates that the subject from which the urine is derived may be hematopoietic cancer.
  • microRNA according to the method described in [76] above, which further satisfies the condition that the expression of microRNA is reduced in cancer patients in Tables 4-1 to 4-15 ⁇ independently in each table. It can be 1 or more, 2 or more, 3 or more, 4 or more, 5 or more, 10 or more, 15 or more, or 20 or more microRNAs ⁇ .
  • microRNA showing expression below the second threshold indicates that the subject from which the urine is derived may be urinary cancer.
  • Method. [94] The method according to [93] above, wherein the subject having or suspected of having cancer is a subject having or suspected of having urinary cancer. .. [95] The method according to any one of [81] to [87] above, wherein there are 5 or more types of microRNA showing expression higher than the first threshold value. [96] The method according to any one of [81] to [87] above, wherein the microRNA showing expression higher than the first threshold value is 10 or more, 15 or more, or 20 or more. [97] The method according to any one of [88] to [94] above, wherein there are 5 or more types of microRNA showing expression lower than the second threshold value.
  • the method according to any one of [88] to [94] above, wherein the microRNA exhibiting expression lower than the second threshold value is 10 or more, 15 or more, or 20 or more.
  • the nanowire is a nanowire having a surface of a metal oxide.
  • the nanowire is a nanowire having a surface of zinc oxide.
  • the first threshold is selected from the group consisting of the mean, median, third quartile, first quartile, and lowest of the microRNA levels in the cancer subject group.
  • the threshold value may be different for each microRNA ⁇ .
  • the first threshold is selected from the group consisting of the maximum value, the third quartile, the mean, the median, and the first child quantile of the microRNA level in the non-cancer subject group. Any of the above methods, which is an arbitrary numerical value between the two values ⁇ here, the threshold value may be different for each microRNA ⁇ .
  • the second threshold is selected from the group consisting of the mean, median, third quartile, first quartile, and lowest of the microRNA levels in the cancer subject group. Any of the above methods, which is an arbitrary numerical value between two values (statistical value or index value) ⁇ here, the threshold value may be different for each microRNA ⁇ .
  • a second threshold is selected from the group consisting of the maximum, third quartile, mean, median, and first child quantile of the microRNA level in the non-cancerous subject group. Any of the above methods, which is an arbitrary numerical value between the two values ⁇ here, the threshold value may be different for each microRNA ⁇ .
  • the second threshold is any value (eg, an intermediate value) between the mean in the cancer control group and the mean in healthy individuals.
  • the threshold may be different ⁇ .
  • the first threshold is a value between the mean value of the microRNA level in the cancer control group and the mean value of the microRNA level in the non-cancer control group, in any of the above.
  • the method described ⁇ here, the threshold value may be different for each microRNA ⁇ .
  • the first threshold is an intermediate value between the mean microRNA level in the cancer control group and the microRNA level mean in the non-cancer control group. ⁇ Here, the threshold value may be different for each microRNA ⁇ .
  • the second threshold is a value between the mean value of the microRNA level in the cancer control group and the mean value of the microRNA level in the non-cancer control group, in any of the above.
  • the method described ⁇ here, the threshold value may be different for each microRNA ⁇ .
  • the second threshold is an intermediate value between the mean of the microRNA level in the cancer control group and the mean of the microRNA level in the non-cancer control group. ⁇ Here, the threshold value may be different for each microRNA ⁇ .
  • the first threshold is a value between the mean value of the cancer control group and the third quartile value.
  • the first threshold is a value between the mean value of the cancer control group and the first quartile.
  • the first threshold is a value between the first quartile and the lowest value of the cancer control group.
  • the first threshold is a value between the mean and median of the non-cancerous control group.
  • the first threshold is a value between the mean value of the non-cancer control group and the third quartile value.
  • the first threshold is a value between the mean value of the non-cancerous control group and the first quartile value.
  • the first threshold is a value between the third quartile and the maximum of the non-cancerous control group.
  • the second threshold is a value between the mean and median of the cancer control group.
  • the second threshold is a value between the mean value of the cancer control group and the third quartile.
  • the second threshold is a value between the mean value of the cancer control group and the first quartile.
  • the second threshold is a value between the first quartile and the lowest value of the cancer control group.
  • the second threshold is a value between the mean and median of the non-cancerous control group.
  • the second threshold is a value between the mean value of the non-cancer control group and the third quartile value.
  • the second threshold is a value between the mean value of the non-cancerous control group and the first quartile.
  • the second threshold is a value between the third quartile and the maximum of the non-cancerous control group.
  • FIG. 1 relates to electrostatic recovery of urinary EV by nanowires followed by in situ extraction of EV-encapsulated miRNA.
  • FIG. 1A is a schematic diagram relating to the recovery (capture) of EV in urine and the in situ extraction of EV-encapsulated miRNA using a nanowire-embedded microdevice.
  • FIG. 1B shows the embedded nanowires after pouring, curing and peeling of PDMS, and a schematic diagram of a vertical cross-sectional FESEM image of the embedded nanowires (nanowires shown by rods, PDMS shown by transparent regions) and cut surfaces. A schematic inset diagram at the bottom left showing the image is shown.
  • FIG. 1C is a schematic view showing a cut plane image relating to the growth of nanowires from embedded nanowires (nanowire-embedded PDMS), a schematic insert view in the lower left, and a vertical cut-plane image of the nanowire-embedded PDMS.
  • the scale bar indicates 1 ⁇ m.
  • FIG. 1D shows a schematic view of a cut plane and a schematic inset at the bottom left of adhering to a PDMS substrate with a microfluidic herringbone structure of nanowire-embedded PDMS, and polyether ether ketone (PEEK) for inlet and outlet.
  • PEEK polyether ether ketone
  • FIG. 1E shows a schematic view of the nanowire-embedded device after exposure to lysis buffer and a FESEM image from the top surface of the nanowire-embedded PDMS.
  • the scale bar indicates 1 ⁇ m.
  • FIG. 1F shows a schematic view of nanowires on a Si substrate and a FESEM image from the top surface of the nanowires on a Si substrate after exposure to a lysis buffer.
  • FIG. 2 relates to in situ extraction of miRNA using a nanowire-embedded microfluidic device.
  • FIG. 2A shows a scatter plot of normalized intensities of the nanowire-embedded devices of the present disclosure and miRNAs extracted from EVs recovered by ultracentrifugation.
  • FIG. 2C shows a scatter plot of normalized intensities of miRNAs extracted from EVs recovered by the nanowire-embedded devices of the present disclosure and commercially available kits.
  • FIG. 3 relates to the recovery of EVs on nanowires.
  • FIG. 3 relates to the recovery of EVs on nanowires.
  • FIG. 3A is a schematic diagram relating to the experimental process and the calculation of the recovery efficiency.
  • FIG. 3C shows the flow-through fraction of urine processed by the nanowire-embedded device of the present disclosure and the error bars showing the size distribution of free suspended matter in urine in ultracentrifugated urine. Is shown.
  • FIG. 3D shows a fluorescent (RKH26) labeled EV recovered with nanowires. In the figure, PKH26 labeled EV on nanowires is shown. The scale bar indicates 500 ⁇ m.
  • FIG. 3E shows a FESEM image of nanowires after the introduction of PKH26 labeled EV.
  • FIG. 4 shows the results of in situ extraction of cancer-related miRNAs using nanowire-embedded devices.
  • FIG. 4 shows a heat map of miRNA expression arrays for each of the urine samples of non-cancer donors, lung cancer donors, liver cancer donors, bladder cancer donors and prostate cancer donors. Color gradations are used based on signal intensity to intuitively understand the expression of each miRNA and the comparison between each group. When the logarithmic signal intensity is 5, black; 2 or less is blue; 8 or more is yellow. Each column of the heatmap represents the log signal intensity of the miRNA (specific numbers are shown in data S1).
  • FIG. 5 shows downregulation and overexpression of miRNAs extracted from FIG. 4 between non-cancer donors and donors of various cancers. The extracted miRNAs had a higher logarithmic signal intensity of the second lowest in the other group than the second highest log signal intensity in one group.
  • FIG. 6 shows a schematic diagram of the process of manufacturing nanowires incorporated into PDMS.
  • nanowires are incorporated into PDMS by lithography and PDMS curing process.
  • Components include a Si substrate and OFPR8600 photoresist, Cr layer, nanowires, and PDMS.
  • the si substrate is prepared in FIG.
  • FIG. 6a shows a schematic diagram of the embedded nanowires after pouring, curing and peeling of PDMS.
  • FIG. 6i shows a schematic diagram of the process of growing nanowires from embedded nanowires.
  • FIG. 6j shows a schematic diagram of a process of attaching a nanowire-embedded PDMS substrate to a PDMS substrate having a microfluidic herringbone structure.
  • FIG. 7 relates to the incorporation of nanowires into PDMS.
  • FIG. 7a is a FESEM image from the upper surface of the nanowire. The scale bar is 1 ⁇ m.
  • FIG. 7b shows the diameter distribution of nanowires. The average diameter of the nanowires was 150 nm.
  • FIG. 7c shows the distribution of spaces between nanowires. The space was defined as the shortest distance between the two nanowires and was determined from the SEM image of the cut surface. The average space between the nanowires was 200 nm.
  • FIG. 7 relates to the incorporation of nanowires into PDMS.
  • FIG. 7a is a FESEM image from the upper surface of the nanowire. The scale bar is 1 ⁇ m.
  • FIG. 7b shows the diameter distribution of nanowires. The average
  • 8 relates to a FESEM image of each of a PDMS substrate without nanowires, a PDMS substrate with embedded nanowires, and a PDMS substrate with nanowires and the corresponding EDS element mapping.
  • 8a-c are FESEM images of the vertical cut surfaces of the PDMS substrate without nanowires, the PDMS substrate with embedded nanowires, and the PDMS substrate with nanowires.
  • 8d-f show elemental mappings corresponding to the FESEM images of the cut planes of FIGS. 8a-c.
  • Si and Zn are represented by blue (dark part) and green (the part indicated by the arrowhead and the light part), respectively.
  • FIG. 8e is a FESEM image from the top surface of PDMS with embedded nanowires.
  • FIG. 8h shows the EDS element mapping corresponding to the FESEM image from the top surface of FIG. 8g.
  • Si and Zn are represented by blue and green (bright areas scattered on the gray scale), respectively.
  • FIG. 9 relates to the mechanical stability of incorporated nanowires and non-incorporated nanowires.
  • 9a and 9b are schematic views of nanowires incorporated into PDMS and nanowires on a Si substrate prior to exposure to lysis buffer.
  • Components include nanowires, PDMS, Si substrates, and Cr layers.
  • the non-embedded nanowires were made on a thermal oxidation treated chromium layer on a Si substrate.
  • 9c and 9d are FESEM images from the top surface of the nanowires incorporated into PDMS and the nanowires on the Si substrate, respectively.
  • the scale bar indicates 1 ⁇ m.
  • 9e and 9f are FESEM images from the conditions of nanowires incorporated into PDMS and nanowires on a Si substrate when exposed to lysis buffer, respectively.
  • the scale bar indicates 1 ⁇ m. After exposure to the lysis buffer, the nanowires on the Si substrate were exfoliated, whereas the nanowires incorporated into PDMS were not exfoliated.
  • FIG. 10 shows an example of a urinary miRNA extraction process using a nanowire-embedded device, ultracentrifugation, and a commercially available kit.
  • FIG. 10a shows an experimental procedure for microarray analysis of miRNA expression.
  • FIG. 10b shows an experimental procedure for quantification of small RNA using a Qubit TM microRNA assay kit (Thermo Fisher Scientific). After extracting miRNA by various methods, RNA production and quantification of small RNA were performed.
  • FIG. 10c shows the quantification of small RNA using various methods. Since the Qubit TM microRNA assay kit (Thermo Fisher Scientific) can quantify not only miRNA but also small RNA ( ⁇ 20 nucleotides or base pairs), the concentration of small RNA was set on the Y-axis.
  • FIG. 11 shows EDS element mapping between a FESEM image and a STEM image of a single nanowire. Zn, O, and Al are shown in green, red, and orange, respectively.
  • FIG. 11a shows a nanowire of ZnO alone. The scale bar indicates 500 nm.
  • FIG. 11b shows ZnO / Al 2 O 3 core-shell nanowires. The scale bar indicates 500 nm. In FIG. 11b, it was observed that Al covered the core of Zn.
  • FIG. 11c shows ZnO / Al 2 O 3 core-shell nanowires. The scale bar indicates 100 nm. In FIG.
  • mouse anti-human CD9 antibody (10 ⁇ g / mL, Abcam, Plc.) was introduced into each device, after which the device was allowed to stand for 15 minutes.
  • CD9 is known as a membrane protein expressed on exosomes.
  • each device was washed with PBS and AlexaFluor488-labeled goat polyclonal anti-mouse IgG antibody (5 ⁇ g / mL, Abcam, Plc.) was introduced into each device, after which the device was allowed to stand for 15 minutes. Finally, each device was washed with PBS and the fluorescence intensity was observed with a fluorescence microscope (Olympus, Co. Ltd.).
  • FIG. 13 shows the zeta potential of EV in urine.
  • the zeta potential of EV was measured using a dynamic light scattering device (Zetasizer Nano-ZS, Malvern Instruments, Ltd.).
  • the average zeta potential of EV was -28 mV.
  • FIG. 14 shows the size distribution of EVs recovered by the ultracentrifugation method.
  • FIG. 14 also shows the presence of EV-free miRNA recovered on nanowires.
  • FIG. 14b shows the amount of miRNA recovered and released by quantitative reverse transcription-polymerase chain reaction (qRT-PCR). As EV-free miRNAs, 100 nM miRNAs (sequence: miRNA (sequence, ugcauaguacaaaagugauc) were used. “Untreated” indicates the amount of 100 nM miRNAs. Recovery of microchannels with or without nanowires, respectively. It was 100% and 23%.
  • FIG. 15 shows the size distribution of free suspended matter in urine.
  • FIG. 15a shows data on free suspended matter of untreated urine, the concentration of which was 1.4 ⁇ 10 12 mL -1 .
  • FIG. 15b shows data on free suspended matter in the flow-through fraction of urine treated by a nanowire-embedded device, with a concentration of 2.4 ⁇ 10 10 mL -1 (capture efficiency 99%).
  • FIG. 15c shows data on free suspended matter in the flow-through fraction of urine treated with a nanowire-embedded device without a herringbone structure, with a concentration of 4.3 ⁇ 10 11 mL -1 (capture efficiency: 61%).
  • FIG. 16 Schematic diagram and photograph (A to C) of the current microRNA extraction system, the number of detected miRNAs (D), and the number of miRNAs showing a significant difference between the urine of lung cancer patients and the urine of healthy subjects. (E), patients and healthy subjects were randomly divided into 20 groups, a judgment formula was derived from the results of 19 randomly obtained groups by logistic regression, and the remaining 1 group was predicted for 20 cycles.
  • FIG. 17 shows the relationship between the weighting coefficient (A) and log2 (fluorescence intensity) for miRNA having an absolute value of the weighting coefficient greater than 0.01 in the determination formula obtained in FIG. 16 and the miRNA shown in FIG. 17A.
  • the prepared heat map (B) and the accuracy (correct answer rate), sensitivity (sensitivity), and specificity (specificity) of prediction of lung cancer using all miRNAs, and the absolute value of the weighting coefficient are from 0.05.
  • the accuracy, sensitivity, and specificity (C) of prediction of lung cancer using large miRNA are shown.
  • FIG. 18 Lung Cancer Prediction for Stage I Patients (A and B), Lung Cancer Prediction for Stage II Patients (C and D), Lung Cancer Prediction for Stage III Patients (E and F), and Stage IV
  • the results of lung cancer prediction (G and H) of the patients in Japan are shown.
  • FIG. 19 shows the relationship between the number of miRNAs detected in lung cancer tissue and the urine of lung cancer patients (A), and the intensity of tissue expression of miRNAs having an absolute weighting factor greater than 0.5.
  • FIGGS. 20-1 to 20-217 ROC curves for the prediction of human lung cancer using a single miRNA are shown.
  • FIGGS. 21-1 to 21-78 ROC curves for human breast cancer prediction using a single miRNA are shown. [FIGS.
  • FIG. 22 shows ROC curves for the prediction of human kidney cancer using a single miRNA.
  • FIG. 23-1 to 23-25 ROC curves for the prediction of human leukemia using a single miRNA are shown.
  • FIG. 24-65 FIG. 2 shows ROC curves for the prediction of human lymphoma using a single miRNA.
  • FIG. 25-1 to 25-68 ROC curves for the prediction of human pancreatic cancer using a single miRNA are shown.
  • FIGGS. 26-1 to 26-18 ROC curves for the prediction of human prostate cancer using a single miRNA are shown.
  • FIGGS. 27-1 to 27-49 ROC curves for the prediction of human gastric cancer using a single miRNA are shown. [FIGS.
  • FIG. 29-1 to 29-39 show ROC curves for the prediction of human melanoma using a single miRNA.
  • FIG. 30-1 to 30-28 ROC curves for the prediction of human ovarian cancer using a single miRNA are shown.
  • FIG. 31-1 to Fig. 31-130 ROC curves for prediction of human thyroid cancer using a single miRNA are shown.
  • FIGS. 32-1 to 32-57 ROC curves for the prediction of human cervical cancer using a single miRNA are shown.
  • FIG. 33-1 to Fig. 33-44 ROC curves for the prediction of human rectal colon cancer using a single miRNA are shown.
  • FIG. 34-1 to Fig. 34-84 ROC curves for the prediction of human endometrial cancer using a single miRNA are shown.
  • subject means a subject of urinalysis.
  • the subject can be an animal.
  • the subject may be a reptile, a mammal, or an amphibian.
  • Mammals may be dogs, cats, cows, horses, sheep, pigs, hamsters, mice, squirrels, and primates such as monkeys, gorillas, chimpanzees, bonobos, and humans.
  • the subject can be, in particular, a human.
  • Urine means liquid excrement produced by the kidneys. Urine may be either excreted externally through the urethra or accumulated in the bladder. Urine may be extracted or collected / collected from the body using an extractor such as a syringe. In the present specification, the urine is not particularly limited, but may be, for example, urine of reptiles, mammals, and amphibians. Mammals may be dogs, cats, cows, horses, sheep, pigs, hamsters, mice, squirrels, and primates such as monkeys, gorillas, chimpanzees, bonobos, and humans.
  • the "urine” may be the urine of a healthy subject or a cancer selected from cancers of a particular disease (eg, lung cancer, liver cancer, pancreatic cancer, bladder cancer, and prostate cancer). Etc.), or the urine of a subject suspected of having a specific disease.
  • Urine may be used as a stock solution, or may be a diluted or concentrated liquid of the stock solution.
  • Urine may be a urine sample to which an additive is added.
  • the additive may be, for example, a stabilizer or a pH adjuster added.
  • the "urine” may be frozen urine.
  • microRNA (also referred to as "miRNA”) is a type of non-coding RNA (ncRNA) that is not considered to encode a protein. MicroRNA undergoes processing from its precursor to become a mature product. The matured microRNA is known to have a length of about 20 to 25 bases.
  • Human microRNA is given the name hsa ⁇ In this specification, since all examples measure human microRNA, the notation of hsa is omitted, but the results of human microRNA are disclosed. Has been ⁇ . Precursors are labeled mir and matures are labeled miR. Numbers are assigned in the order in which they are identified, and for similar sequences, a lowercase alphabet is added after the number.
  • microRNA derived from the 5'end is labeled with 5p and is derived from the 3'end. Is attached with 3p. And these symbols and numbers are connected by a hyphen. Mature microRNA can be double-stranded. As used herein, miRNA names are described as explicitly including human miRNAs, with or without has-.
  • extracellular vesicles are vesicles released from cells, those released from cells during the process of apoptosis, and those released from healthy cells. Can be mentioned. Extracellular vesicles are roughly classified into exosomes, microvesicles (MV), and apoptosis bodies according to their size and surface markers. Exosomes typically have a diameter of 40-120 nm and can express one or more or all molecules selected from the group consisting of Alix, Tsg101, CD9, CD63, CD81, and Flotillin.
  • Microvesicles typically have a diameter of 50-1,000 nm and can express one or more or all molecules selected from the group consisting of integrins, selectins, and CD40s.
  • Apoptotic bodies typically have a diameter of 500-2,000 nm and can express one or more molecules selected from the group consisting of Annexin V and phosphatidylserine.
  • Exosomes can include proteins and nucleic acids (eg, mRNA, miRNA, ncRNA).
  • Microvesicles can include proteins and nucleic acids (eg, mRNA, miRNA, ncRNA).
  • Apoptotic bodies are thought to contain fragmented nuclei and organelles.
  • the term "extract” means an extracted product in which a specific component is more concentrated than before the extraction.
  • the term “urine extract” means an extract from urine in which specific components (particularly microRNA) are more concentrated than in unextracted urine.
  • the urine extract can be an aqueous solution (solution or suspension) or a solid obtained by drying them.
  • the extract from which extracellular vesicles in urine and components other than nucleic acids are substantially removed is sometimes referred to as a purified urine product.
  • the urine extract may contain a surfactant (preferably a nonionic surfactant).
  • the urine extract may contain detergent and debris of extracellular vesicles (eg, exosomes and / or microvesicles).
  • Urine extracts are free or substantially free of one or more selected from the group consisting of detergents and debris of extracellular vesicles (eg, exosomes and / or microvesicles). It may be there.
  • the urine extract may further contain a stabilizer (eg, a nucleic acid stabilizer) and / or a pH regulator (eg, a buffer).
  • the urine extract may contain salt.
  • a urine extract is one or more urine components selected from the group consisting of urine components such as urea, creatinine, uric acid, ammonia, urobilin, riboflavin, urine protein, sugar and urinary hormones (eg, chorionic gonadotropin).
  • the concentration in urine may be 1% or less, 1 ⁇ 10 -1 % or less, 1 ⁇ 10 ⁇ 2 % or less, or 1 ⁇ 10 -3 % or less ⁇ .
  • the pH of the urine extract may be greater than or greater than a value such as 2, 3, 4, or 5.
  • the pH of the urine extract may be less than or less than a value such as 10, 9, 8, 7, 6, or 5.
  • the urine extract comprises microRNA.
  • the urine extract may comprise concentrated microRNA or a group thereof.
  • the urine extract may comprise microRNA extracted by the extraction method described herein.
  • the urine extract may contain at least one or all of the microRNAs listed in data S1 (or Table 3 which discloses data S1).
  • the urine extract is a nanowire having a positively charged surface under the pH environment of urine (eg, ZnO, SiO 2 , Li 2 O, MgO, Al 2 O 3 , CaO, TiO 2 , Mn 2 O 3).
  • urine are brought into contact with each other, and then washed if necessary, and then extracted with a buffer solution containing a nonionic surfactant or the like.
  • the urine extract of the present disclosure Sometimes referred to as "the urine extract of the present disclosure”).
  • the pH of urine can also be adjusted so that the surface charge of the nanowires is positive when the urine is brought into contact with the nanowires (before, after, or during contact).
  • Urine extract is suitable for nucleic acid analysis.
  • in-situ extraction refers to the extraction of small RNA (eg, microRNA) "on the fly” by destroying the EV captured on the nanowire using a nanowire-embedded microfluidic device. Alternatively, it means extracting small RNA (eg, microRNA) captured on the nanowires from the nanowires into a solution.
  • small RNA eg, microRNA
  • microRNA is not encapsulated in extracellular vesicles and that microRNA is extracellular small when used in the context of the presence of microRNA in urine. It means that it exists in a state where it is not associated with vesicles.
  • internal capsule as used in the context of the presence of microRNA in urine means that the microRNA is integrated into the extracellular vesicle (if fully encapsulated). It may be any case where the part is partially contained).
  • nanowire generally means a rod-like structure having a size such as a cross-sectional shape or diameter on the order of nanometers (for example, a diameter of one to several hundred nanometers).
  • the size of the nanowire is not particularly limited, but is, for example, 1 nm, 5 nm, 10 nm, 15 nm, 20 nm, 25 nm, 30 nm, 40 nm, 50 nm, 60 nm, 70 nm, 80 nm, 90 nm, 100 nm, 105 nm, 110 nm, 115 nm, 120 nm, 125 nm, 130 nm.
  • nm 135 nm, 140 nm, 145 nm, 150 nm, 155 nm, 160 nm, 165 nm, 170 nm, 175 nm, 180 nm, 185 nm, 190 nm, 195 nm , 200 nm, 210 nm, 220 nm, 230 nm, 240 nm, 250 nm, 260 nm, 270 nm, 280 nm, 290 nm, 300 nm, 310 nm.
  • the size of the nanowire is also not particularly limited, but for example, 1000 nm, 990 nm, 980 nm, 970 nm, 960 nm, 950 nm, 940 nm, 930 nm, 920 nm, 910 nm, 900 nm, 890 nm, 880 nm, 870 nm, 860 nm, 850 nm, 840 nm, 830 nm, 820 nm.
  • the size of the nanowire is not particularly limited, but may be, for example, any size between the above upper limit value and the lower limit value.
  • the surface area can be increased by using nanowires, which can increase the recovery capacity of EVs.
  • the length of the nanowire is not particularly limited, but is selected from, for example, 500 nm, 600 nm, 700 nm, 800 nm, 900 nm, 1 ⁇ m, 2 ⁇ m, 3 ⁇ m, 4 ⁇ m, 5 ⁇ m, 6 ⁇ m, 7 ⁇ m, 8 ⁇ m, 9 ⁇ m, and 10 ⁇ m 2 It can be any length between the two values.
  • the length and diameter of the nanowires can affect the physical strength and surface area of the nanowires. The length and diameter could be adjusted according to the usage environment.
  • the nanowires are 1 ⁇ m long to 10 ⁇ n long ⁇ eg, 1.5 ⁇ m to 5 ⁇ m and are made of metal oxide ⁇ eg, zinc oxide ⁇ .
  • the term “free” means that, when used in combination with the component described immediately preceding this term, the component is substantially free or absent.
  • substantially free does not exclude the inclusion of the component at a level that cannot be removed in the extract.
  • the present inventors contact nanowires having a positively charged surface (for example, the surface of zinc oxide (ZnO)) in an environment of pH 6 to 8 with the target urine to cause extracellular vesicles in urine.
  • a positively charged surface for example, the surface of zinc oxide (ZnO)
  • ZnO zinc oxide
  • EV and miRNA adsorbed on nanowires can be effectively recovered by a surfactant.
  • an extract of urine containing any one or more of the microRNAs described in data S1 (or Table 3) is provided. According to the present disclosure, an extract of urine containing all the microRNAs described in data S1 (or Table 3) is provided. According to the present disclosure, urine extracts containing any one or more of the microRNAs listed in Table 2 are provided. According to the present disclosure, urine extracts containing all the microRNAs listed in Table 2 are provided. In some embodiments of the present disclosure, a urine extract containing any one or more, or all of the microRNAs described in data S1 (or Table 3), comprises 500 microRNAs (particularly microRNAs present in urine).
  • the urine extract containing any one or more of the microRNAs described in data S1 (or Table 3), or all microRNAs comprises 749 or more types of microRNAs (particularly microRNAs present in urine). It may include 822 or more, or 1111 or more.
  • microRNA present in urine may contain 500 or more, 600 or more, 700 or more, 800 or more, 900 or more, 1000 or more, or 1100 or more.
  • the number of microRNA types contained in urine may be the number of microRNA types actually contained.
  • the number of types of microRNA contained in urine may be defined by the method or technique of detecting microRNA.
  • the number of types of microRNA contained in urine can depend on the detection limit of the method for detecting microRNA.
  • it can be prepared from urine using the nanowire-embedded devices of the present disclosure.
  • the microRNA is 1 or more, 2 or more, 3 or more, 4 or more in the numerical values shown in data S1 (or Table 3) (values converted to log 2 after background intensity is deducted).
  • Micro selected from the group consisting of microRNAs showing 5 or more, 6 or more, 7 or more, 8 or more, 9 or more, 10 or more, 11 or more, 12 or more, 13 or more, 14 or more, 15 or more, and 16 or more. It may contain at least one or all of the RNA.
  • the microRNA is 1 or more and less than 2 and less than 2 or more and less than 3 in the numerical values described in data S1 (or Table 3) (values converted to log 2 after background intensity has been deducted).
  • the above-mentioned numerical value may be a numerical value in a non-cancer donor (for example, a healthy person), a numerical value in a lung cancer patient, a numerical value in a pancreatic cancer patient, and a numerical value in a liver cancer patient.
  • the numerical value can be, for example, a numerical value in a gastrointestinal cancer patient, a numerical value in a hematopoietic cancer patient, and / or a numerical value in a urinary cancer patient. In this aspect, the above numerical value can be a numerical value in all cancer patients.
  • a urine extract containing RNA or all microRNAs is provided.
  • an extract of urine comprising at least one microRNA selected from the group consisting of miR-378a-5p, miR-520c-3p, and miR-526b-3p or all microRNAs.
  • These microRNAs can be detected in the urine of lung cancer patients. Therefore, according to the present disclosure, urine can be the urine of a subject with lung cancer.
  • an extract of urine containing at least one or all microRNAs selected from the group consisting of miR-183-5p, miR-202-5p, and miR-409-5p. ..
  • a urine extract containing at least one or all microRNAs selected from the group consisting of miR-506-3p, miR-520c-3p, miR-1284, miR-1323, and miR-4273 is provided. ..
  • These microRNAs can be detected in the urine of patients with pancreatic cancer. Therefore, according to the present disclosure, urine can be the urine of a subject with pancreatic cancer.
  • a urine extract containing at least one or all microRNAs selected from the group is provided.
  • an extract of urine containing miR-520c-3p is provided. These microRNAs can be detected in the urine of subjects with liver cancer. Therefore, urine can be the urine of a subject with liver cancer.
  • a urine extract containing at least one or all microRNAs selected is provided. According to the present disclosure, it is composed of miR-16-1--3p, miR-23b-3p, miR-28-5p, miR-142-3p, miR-195-3p, miR-299-3p, and miR-4295.
  • a urine extract containing at least one or all microRNAs selected from the group is provided. According to the present disclosure, an extract of urine containing miR-520c-3p is provided. These microRNAs can be detected in embodiments with bladder cancer. Thus, in the present disclosure, urine can be the urine of a subject with bladder cancer.
  • an extract of urine containing at least one or all microRNAs selected from the group consisting of miR-135b-5p, miR-520c-3p, miR-4783-5p, and miR-7849-3p.
  • At least one or all microRNAs selected from the group consisting of miR-28-5p, miR-105-5p, miR-124-3p, miR-151a-5p, and miR-300 are provided.
  • an extract of urine including, is provided.
  • an extract of urine containing at least one or all microRNAs selected from the group consisting of miR-15a-3p and miR-520c-3p.
  • These microRNAs can be detected in embodiments with prostate cancer.
  • urine can be the urine of a subject with prostate cancer.
  • Another aspect of the disclosure provides a method of testing the subject for possible cancer.
  • the methods to test for the possibility of cancer are how to diagnose whether it is cancer, how to obtain preliminary information for diagnosing whether it is cancer, and whether or not cancer cells are present in the subject's body. It can be read as a method for determining cancer cells, a method for detecting cancer cells, a method for predicting the possibility of cancer, or a method for determining the possibility of cancer in a subject, and can be used interchangeably.
  • diagnosis of cancer and anticancer treatment eg, radiation therapy, chemotherapy, immunological therapy
  • the possibility that the subject has cancer can be determined by using the expression level of any of the microRNAs described in the data S1 (or Table 3) in the body fluid sample as an index.
  • an extract of urine containing any one or more of the microRNAs listed in any of Tables 4-1 to 4-15 is provided. According to the present disclosure, an extract of urine containing all the microRNAs listed in any of Tables 4-1 to 4-15 is provided. According to the present disclosure, an extract of urine containing any one or more of the microRNAs listed in any of Tables 4-1 to 4-15 is provided. According to the present disclosure, an extract of urine containing all the microRNAs listed in any of Tables 4-1 to 4-15 is provided.
  • the microRNA can be an increased microRNA in a cancer patient. Thus, in some embodiments, if microRNA is detected in a urine extract, it may indicate that the subject from which the urine is derived has or may have cancer.
  • a method for analyzing urine which comprises obtaining a urine extract.
  • the urine analysis method of the present disclosure may further include extracting microRNA from the urine extract.
  • the method for analyzing urine of the present disclosure may further include measuring the abundance of the microRNA.
  • the particular microRNA can be any one or more of the microRNAs listed in any of Tables 4-1 to 4-15.
  • the specific microRNA is any one or more of the microRNAs listed in any of Tables 4-1 to 4-15 and has a p-value of less than 0.005.
  • the particular microRNA can be any one or more of the microRNAs listed in any of Tables 22-1 to 22-13.
  • the specific microRNA is any one or more of the microRNAs listed in any of Tables 22-1 to 22-13, and the accuracy is more than 50%, 55% or more, 60% or more, 65% or more. , 70% or more, 75% or more, 80% or more, 85% or more, 90% or more, or 95% or more.
  • the particular microRNA can be any one or more microRNAs listed in any of Tables 22-1 and 23-1 to 23-14, preferably 55% or more with an accuracy greater than 50%. , 60% or more, 65% or more, 70% or more, 75% or more, 80% or more, 85% or more, 90% or more, or 95% or more accuracy of microRNA.
  • the particular microRNA can be any one or more microRNAs listed in any of the tables 24-15 to 24-15, greater than 0.5, greater than 0.55, greater than or equal to 0.6, It can be a microRNA exhibiting an accuracy of 0.65 or higher, 0.7 or higher, 0.75 or higher, 0.8 or higher, 0.85 or higher, or 0.9 or higher.
  • the particular microRNA can be any one or more microRNAs listed in any of the tables 25-1 to 25-15, greater than 0.5, greater than 0.55, greater than or equal to 0.6, It can be a microRNA exhibiting an accuracy of 0.65 or higher, 0.7 or higher, 0.75 or higher, 0.8 or higher, 0.85 or higher, or 0.9 or higher.
  • Specific microRNAs are 5 types, 10 types, 15 types, 20 types, 30 types, 40 types, 50 types, 60 types, 70 types, 80 types, 90 types, 100 types, 200 types, 300 types, and 400 types.
  • microRNAs of 1800 types or more, 1900 types or more, 2000 types or more, 2100 types or more, 2200 types or more, 2300 types or more, 2400 types or more, or 2500 types or more.
  • Specific microRNAs can be detected or measured in abundance by a variety of known methods. A particular microRNA can be identified by contacting it with a nucleic acid containing a sequence capable of hybridizing with the microRNA.
  • Nucleic acids containing sequences that are hybridizable with microRNA can be immobilized. Nucleic acids containing sequences that are hybridizable with microRNAs may be immobilized on microarrays. The nucleic acid containing a sequence capable of hybridizing with microRNA may be a probe for RT-PCR.
  • a urine extract comprising any one or more, or all of the microRNAs listed in any of Tables 4-1 to 4-15, is a microRNA (particularly in urine).
  • urine extracts containing any one or more of the microRNAs listed in any of Tables 4-1 to 4-15, or all microRNAs are microRNAs (particularly in urine).
  • Existing microRNA may include more than 50%, more than 60%, more than 70%, more than 80%, more than 90%, or all of the number of types of microRNA listed in each table.
  • a urine extract containing any one or more, or all of the microRNAs listed in Table 1 contains 749 or more, 822 or more microRNAs (particularly microRNAs present in urine), or 1111 or more types can be included.
  • the microRNA can be an increased microRNA in a cancer patient.
  • microRNA is detected in a urine extract, it may indicate that the subject from which the urine is derived has or is likely to have cancer.
  • a urine extract containing any one or more of the microRNAs listed in any of the tables 4-1 to 4-15, or all microRNAs is a microRNA present in the urine.
  • the number of microRNA types contained in urine may be the number of microRNA types actually contained. In some embodiments, the number of types of microRNA contained in urine may be defined by the method or technique of detecting microRNA.
  • the number of types of microRNA contained in urine can depend on the detection limit of the method for detecting microRNA. In some aspects of the disclosure of the present invention, preferably, it can be prepared from urine using the nanowire-embedded devices of the present disclosure.
  • the microRNA is greater than 50%, greater than 55% of the microRNAs listed in Table 4-1 in terms of sensitivity and / or specificity as shown in Table 4-1. MicroRNA exhibiting sensitivity and / or specificity greater than 60%, greater than 65%, greater than 70%, greater than 75%, greater than 80%, greater than 85%, greater than 90%, or greater than 95% It may contain at least one or all of the microRNAs selected from the group consisting of.
  • the microRNA is greater than 50% and less than or equal to 55% of the microRNAs listed in Table 4-1 in terms of sensitivity and / or specificity as shown in Table 4-1. More than 55% and less than 60%, more than 60% and less than 65%, more than 65% and less than 70%, more than 70% and less than 75%, more than 75% and less than 80%, Select from the group consisting of microRNAs exhibiting more than 80% and less than 85%, more than 85% and less than 90%, more than 90% and less than 95%, or more than 95% sensitivity and / or specificity. It may contain at least one or all of the microRNAs to be made.
  • the microRNA can be an increased microRNA in a cancer patient.
  • microRNA is detected in a urine extract, it may indicate that the subject from which the urine is derived has or is likely to have cancer. Whether the expression level of a specific microRNA increases or decreases in a specific cancer as compared with a healthy person is shown in Tables 4-1 to 4-15. It can be confirmed by whether the expression level is increased or decreased.
  • the amount of microRNA contained in the urine extract can be detected by a microarray, or is in a sufficient amount thereof.
  • hsa-let-7a-3p hsa-miR-103a-2-5p, hsa-miR-103a-3p, hsa-miR-105-3p, hsa-miR-106a-3p, hsa- miR-1180-3p, hsa-miR-1185-2-3p, hsa-miR-1193, hsa-miR-127-3p, hsa-miR-1245b-5p, hsa-miR-1247-3p, hsa-miR- 125b-2-3p, hsa-miR-1263, hsa-miR-173g-3p, hsa-miR-129-2-3p, hsa-miR-1293, hsa-miR-1301-5p, hsa-miR-130a- 3p, hsa-miR-130a
  • Urine extracts comprising at least one, two, three, four, five, six, seven, eight, nine, or ten or all microRNAs are provided.
  • the urine extract can be a urine extract of a patient with stage I cancer.
  • a patient with stage I cancer can be a patient with stage I lung cancer.
  • These miRNAs are found in more urine in stage I lung cancer patients than in healthy individuals.
  • the stage can be, for example, by TNM classification. In the TNM classification, the stage judgment is evaluated from the three viewpoints of T: cancer size, N: presence / absence of metastasis to lymph nodes, and M: metastasis to other organs. Cancers can be classified according to the TNM classification.
  • early cancer means a cancer selected from the group consisting of stage I and II cancers.
  • a urine extract containing 10 or all microRNAs is provided.
  • a urine extract containing the microRNA of is provided.
  • the urine extract can be the urine extract of a breast cancer patient. Only one of these microRNAs can predict whether or not the subject from which urine is derived is a breast cancer patient, and a combination of 5 or more, 10 or more, 15 or more, or 20 or more can be used. It is possible to predict whether or not the subject from which urine is derived is a breast cancer patient. Of these microRNAs, microRNAs that can be highly expressed in breast cancer patients can be preferably used for prediction.
  • the urine extract can be a urine extract of a stage I or II breast cancer patient. Only one of these microRNAs can predict whether or not the subject from which urine is derived is a breast cancer patient (particularly stage I or II), with 5 or more, 10 or more, 15 or more, or By combining 20 or more species, it is possible to predict whether or not the subject from which urine is derived is a breast cancer patient (particularly stage I or II). Of these microRNAs, microRNAs that can be highly expressed in breast cancer patients (particularly stage I or II) can be preferably used for prediction.
  • a urine extract comprising species, 8, 9, or 10 or all microRNAs is provided.
  • the urine extract can be an extract of the urine of a stage I breast cancer patient. Only one of these microRNAs can predict whether or not the subject from which urine is derived is a breast cancer patient (particularly stage I), and 5 or more, 10 or more, 15 or more, or 20 types. By combining the above, it is possible to predict whether or not the subject from which urine is derived is a breast cancer patient (particularly stage I). Of these microRNAs, microRNAs that can be highly expressed in breast cancer patients (particularly Stage I) can be preferably used for prediction.
  • the correct answer rate exceeding 0.500 was shown.
  • Urine containing at least one, two, three, four, five, six, seven, eight, nine, or ten or all microRNAs selected from the group consisting of microRNAs. Extracts are provided.
  • the urine extract can be the urine extract of a breast cancer patient. Only one of these microRNAs can predict whether or not the subject from which urine is derived is a breast cancer patient, and a combination of 5 or more, 10 or more, 15 or more, or 20 or more can be used. It is possible to predict whether or not the subject from which urine is derived is a breast cancer patient.
  • microRNAs that can be highly expressed in a breast cancer patient can be preferably used for prediction.
  • accuracy Is greater than 0.5, 0.55 or higher, 0.6 or higher, 0.65 or higher, 0.7 or higher, 0.75 or higher, 0.8 or higher, 0.85 or higher, or 0.9 or higher. obtain.
  • the urine extract can be the urine extract of a breast cancer patient. Only one of these microRNAs can predict whether or not the subject from which urine is derived is a breast cancer patient, and a combination of 5 or more, 10 or more, 15 or more, or 20 or more can be used. It is possible to predict whether or not the subject from which urine is derived is a breast cancer patient.
  • a microRNA that can be highly expressed in a breast cancer patient can be preferably used for prediction.
  • accuracy. Is greater than 0.5, 0.55 or higher, 0.6 or higher, 0.65 or higher, 0.7 or higher, 0.75 or higher, 0.8 or higher, 0.85 or higher, or 0.9 or higher. obtain.
  • At least one, two, three, four, five, six, seven, eight, nine, or one selected from the microRNAs listed in Table 4-3, or A urine extract containing 10 or all microRNAs is provided.
  • Urine extracts comprising one, two, three, four, five, six, seven, eight, nine, or ten or all microRNAs are provided.
  • the urine extract can be an extract of urine from a patient with kidney cancer. Only one of these microRNAs can predict whether or not the subject from which urine is derived is a kidney cancer patient, and a combination of 5 or more, 10 or more, 15 or more, or 20 or more. Therefore, it is possible to predict whether or not the subject from which urine is derived is a kidney cancer patient. Of these microRNAs, microRNAs that can be highly expressed in renal cancer patients can be preferably used for prediction.
  • the urine extract can be a urine extract of a stage I or II kidney cancer patient. Only one of these microRNAs can predict whether or not the subject from which urine is derived is a kidney cancer patient (particularly stage I or II), and 5 or more, 10 or more, 15 or more. , Or a combination of 20 or more, can predict whether or not the subject from which urine is derived is a kidney cancer patient (particularly stage I or II). Of these microRNAs, microRNAs that can be highly expressed in renal cancer patients (particularly stage I or II) can be preferably used for prediction.
  • the urine extract may be a urine extract of a stage I kidney cancer patient.
  • these microRNAs it is possible to predict whether or not the subject from which urine is derived is a kidney cancer patient (particularly stage I), and 5 or more, 10 or more, 15 or more, or By combining 20 or more species, it is possible to predict whether or not the subject from which urine is derived is a kidney cancer patient (particularly stage I).
  • microRNAs that can be highly expressed in renal cancer patients (particularly stage I) can be preferably used for prediction.
  • Urinary extracts containing 6, 7, 8, 9, or 10 or all microRNAs are provided.
  • the urine extract can be an extract of urine from a patient with kidney cancer. Only one of these microRNAs can predict whether or not the subject from which urine is derived is a kidney cancer patient, and a combination of 5 or more, 10 or more, 15 or more, or 20 or more. Therefore, it is possible to predict whether or not the target from which urine is derived is a kidney cancer patient.
  • a microRNA that can be highly expressed in a kidney cancer patient can be preferably used for prediction.
  • the accuracy is greater than 0.5, greater than 0.55, greater than or equal to 0.6, greater than or equal to 0.65, greater than or equal to 0.7, greater than or equal to 0.75, greater than or equal to 0.8, greater than or equal to 0.85, or It can be 0.9 or higher.
  • the urine extract can be an extract of urine from a patient with kidney cancer. Only one of these microRNAs can predict whether or not the subject from which urine is derived is a kidney cancer patient, and a combination of 5 or more, 10 or more, 15 or more, or 20 or more. Therefore, it is possible to predict whether or not the subject from which urine is derived is a kidney cancer patient.
  • MicroRNA that can be highly expressed in a kidney cancer patient can be preferably used for prediction.
  • the accuracy is accurate. , 0.5 or more, 0.55 or more, 0.6 or more, 0.65 or more, 0.7 or more, 0.75 or more, 0.8 or more, 0.85 or more, or 0.9 or more ..
  • a urine extract containing the microRNA of the above is provided.
  • the urine extract can be the urine extract of a leukemia patient. Only one of these microRNAs can predict whether or not the subject from which urine is derived is a leukemia patient, and a combination of 5 or more, 10 or more, 15 or more, or 20 or more can be used. It is possible to predict whether or not the subject from which urine is derived is a leukemia patient. Of these microRNAs, microRNAs that can be highly expressed in leukemia patients can be preferably used for prediction.
  • Urinary extracts containing 6, 7, 8, 9, or 10 or all microRNAs are provided.
  • the urine extract can be the urine extract of a leukemia patient. Only one of these microRNAs can predict whether or not the subject from which urine is derived is a leukemia patient, and a combination of 5 or more, 10 or more, 15 or more, or 20 or more can be used. It is possible to predict whether or not the subject from which urine is derived is a leukemia patient.
  • microRNAs that can be highly expressed in a leukemia patient can be preferably used for prediction.
  • accuracy Is greater than 0.5, 0.55 or higher, 0.6 or higher, 0.65 or higher, 0.7 or higher, 0.75 or higher, 0.8 or higher, 0.85 or higher, or 0.9 or higher. obtain.
  • Urinary extracts containing 6, 7, 8, 9, or 10 or all microRNAs are provided.
  • the urine extract can be the urine extract of a leukemia patient. Only one of these microRNAs can predict whether or not the subject from which urine is derived is a leukemia patient, and a combination of 5 or more, 10 or more, 15 or more, or 20 or more can be used. It is possible to predict whether or not the subject from which urine is derived is a leukemia patient.
  • microRNAs that can be highly expressed in a leukemia patient can be preferably used for prediction.
  • accuracy Is greater than 0.5, 0.55 or higher, 0.6 or higher, 0.65 or higher, 0.7 or higher, 0.75 or higher, 0.8 or higher, 0.85 or higher, or 0.9 or higher. obtain.
  • a urine extract containing the microRNA of the above is provided.
  • the urine extract can be the urine extract of a lymphoma patient. Only one of these microRNAs can predict whether or not the subject from which urine is derived is a lymphoma patient, and a combination of 5 or more, 10 or more, 15 or more, or 20 or more can be used. It is possible to predict whether or not the subject from which urine is derived is a lymphoma patient. Of these microRNAs, microRNAs that can be highly expressed in lymphoma patients can be preferably used for prediction.
  • Urinary extracts containing at least one, two, three, four, five, six, seven, eight, nine, or ten or all microRNAs are provided.
  • the urine extract can be a urine extract from a stage I or II lymphoma patient. Only one of these microRNAs can predict whether or not the subject from which urine is derived is a lymphoma patient (particularly stage I or II), with 5 or more, 10 or more, 15 or more, or By combining 20 or more species, it is possible to predict whether or not the subject from which urine is derived is a lymphoma patient (particularly stage I or II). Of these microRNAs, microRNAs that can be highly expressed in lymphoma patients (particularly stage I or II) can be preferably used for prediction.
  • the urine extract can be the urine extract of a lymphoma patient. Only one of these microRNAs can predict whether or not the subject from which urine is derived is a lymphoma patient, and a combination of 5 or more, 10 or more, 15 or more, or 20 or more can be used. It is possible to predict whether or not the subject from which urine is derived is a lymphoma patient.
  • a microRNA that can be highly expressed in a lymphoma patient can be preferably used for prediction. Is greater than 0.5, 0.55 or higher, 0.6 or higher, 0.65 or higher, 0.7 or higher, 0.75 or higher, 0.8 or higher, 0.85 or higher, or 0.9 or higher. obtain.
  • Urinary extracts containing 6, 7, 8, 9, or 10 or all microRNAs are provided.
  • the urine extract can be the urine extract of a lymphoma patient. Only one of these microRNAs can predict whether or not the subject from which urine is derived is a lymphoma patient, and a combination of 5 or more, 10 or more, 15 or more, or 20 or more can be used. It is possible to predict whether or not the subject from which urine is derived is a lymphoma patient.
  • a microRNA that can be highly expressed in a lymphoma patient can be preferably used for prediction. Is greater than 0.5, 0.55 or higher, 0.6 or higher, 0.65 or higher, 0.7 or higher, 0.75 or higher, 0.8 or higher, 0.85 or higher, or 0.9 or higher. obtain.
  • the urine extract can be a urine extract of a pancreatic cancer patient. Only one of these microRNAs can predict whether or not the subject from which urine is derived is a pancreatic cancer patient, and a combination of 5 or more, 10 or more, 15 or more, or 20 or more. Therefore, it is possible to predict whether or not the subject from which urine is derived is a pancreatic cancer patient. Of these microRNAs, microRNAs that can be highly expressed in pancreatic cancer patients can be preferably used for prediction.
  • the urine extract can be a urine extract of a stage I or II pancreatic cancer patient. Only one of these microRNAs can predict whether or not the subject from which urine is derived is a pancreatic cancer patient (particularly stage I or II), and 5 or more, 10 or more, 15 or more. , Or a combination of 20 or more, can predict whether the subject from which urine is derived is a pancreatic cancer patient (particularly stage I or II). Of these microRNAs, microRNAs that can be highly expressed in pancreatic cancer patients (particularly stage I or II) can be preferably used for prediction.
  • Urinary extracts comprising at least one, two, three, four, five, six, seven, eight, nine, or ten or all microRNAs selected from are provided.
  • the urine extract can be a urine extract of a stage I pancreatic cancer patient.
  • these microRNAs it is possible to predict whether or not the subject from which urine is derived is a pancreatic cancer patient (particularly stage I), and 5 or more, 10 or more, 15 or more, or By combining 20 or more species, it is possible to predict whether or not the subject from which urine is derived is a pancreatic cancer patient (particularly stage I).
  • microRNAs that can be highly expressed in pancreatic cancer patients (particularly stage I) can be preferably used for prediction.
  • Urinary extracts containing 6, 7, 8, 9, or 10 or all microRNAs are provided.
  • the urine extract can be a urine extract of a pancreatic cancer patient. Only one of these microRNAs can predict whether or not the subject from which urine is derived is a pancreatic cancer patient, and a combination of 5 or more, 10 or more, 15 or more, or 20 or more. Therefore, it is possible to predict whether or not the target from which urine is derived is a pancreatic cancer patient.
  • a microRNA that can be highly expressed in a pancreatic cancer patient can be preferably used for prediction.
  • the accuracy is greater than 0.5, greater than 0.55, greater than or equal to 0.6, greater than or equal to 0.65, greater than or equal to 0.7, greater than or equal to 0.75, greater than or equal to 0.8, greater than or equal to 0.85, or It can be 0.9 or higher.
  • Urinary extracts containing 6, 7, 8, 9, or 10 or all microRNAs are provided.
  • the urine extract can be a urine extract of a pancreatic cancer patient. Only one of these microRNAs can predict whether or not the subject from which urine is derived is a pancreatic cancer patient, and a combination of 5 or more, 10 or more, 15 or more, or 20 or more. Therefore, it is possible to predict whether or not the target from which urine is derived is a pancreatic cancer patient.
  • a microRNA that can be highly expressed in a pancreatic cancer patient can be preferably used for prediction.
  • the accuracy is greater than 0.5, greater than 0.55, greater than or equal to 0.6, greater than or equal to 0.65, greater than or equal to 0.7, greater than or equal to 0.75, greater than or equal to 0.8, greater than or equal to 0.85, or It can be 0.9 or higher.
  • a urine extract containing all microRNAs is provided.
  • Urinary extracts containing 2, 3, 4, 4, 5, 6, 7, 7, 8, 9, or 10 or all microRNAs are provided.
  • the urine extract can be an extract of urine from a prostate cancer patient. Only one of these microRNAs can predict whether or not the subject from which urine is derived is a prostate cancer patient, and a combination of 5 or more, 10 or more, 15 or more, or 20 or more. Therefore, it is possible to predict whether or not the subject from which urine is derived is a prostate cancer patient. Of these microRNAs, microRNAs that can be highly expressed in prostate cancer patients can be preferably used for prediction.
  • the urine extract can be a urine extract of a stage I or II prostate cancer patient. Only one of these microRNAs can predict whether or not the subject from which urine is derived is a prostate cancer patient (particularly stage I or II), and 5 or more, 10 or more, 15 or more. , Or a combination of 20 or more, can predict whether the subject from which urine is derived is a prostate cancer patient (particularly stage I or II). Of these microRNAs, microRNAs that can be highly expressed in prostate cancer patients (particularly stage I or II) can be preferably used for prediction.
  • Urine extracts comprising at least one, two, three, four, five, six, seven, eight, nine, or ten or all microRNAs are provided.
  • the urine extract can be an extract of the urine of a stage I prostate cancer patient. Only one of these microRNAs can predict whether or not the subject from which urine is derived is a prostate cancer patient (particularly stage I), with 5 or more, 10 or more, 15 or more, or By combining 20 or more species, it is possible to predict whether or not the subject from which urine is derived is a prostate cancer patient (particularly stage I). Of these microRNAs, microRNAs that can be highly expressed in prostate cancer patients (particularly Stage I) can be preferably used for prediction.
  • Urinary extracts containing 6, 7, 8, 9, or 10 or all microRNAs are provided.
  • the urine extract can be an extract of urine from a prostate cancer patient. Only one of these microRNAs can predict whether or not the subject from which urine is derived is a prostate cancer patient, and a combination of 5 or more, 10 or more, 15 or more, or 20 or more. Therefore, it is possible to predict whether or not the target from which urine is derived is a prostate cancer patient.
  • a microRNA that can be highly expressed in a prostate cancer patient can be preferably used for prediction.
  • the accuracy is greater than 0.5, greater than 0.55, greater than or equal to 0.6, greater than or equal to 0.65, greater than or equal to 0.7, greater than or equal to 0.75, greater than or equal to 0.8, greater than or equal to 0.85, or It can be 0.9 or higher.
  • Urinary extracts containing 6, 7, 8, 9, or 10 or all microRNAs are provided.
  • the urine extract can be an extract of urine from a prostate cancer patient. Only one of these microRNAs can predict whether or not the subject from which urine is derived is a prostate cancer patient, and a combination of 5 or more, 10 or more, 15 or more, or 20 or more. Therefore, it is possible to predict whether or not the target from which urine is derived is a prostate cancer patient.
  • a microRNA that can be highly expressed in a prostate cancer patient can be preferably used for prediction.
  • the accuracy is greater than 0.5, greater than 0.55, greater than or equal to 0.6, greater than or equal to 0.65, greater than or equal to 0.7, greater than or equal to 0.75, greater than or equal to 0.8, greater than or equal to 0.85, or It can be 0.9 or higher.
  • an extract of urine containing all microRNAs is provided.
  • the urine extract can be the urine extract of a gastric cancer patient. Only one of these microRNAs can predict whether or not the subject from which urine is derived is a gastric cancer patient, and a combination of 5 or more, 10 or more, 15 or more, or 20 or more can be used. It is possible to predict whether or not the subject from which urine is derived is a gastric cancer patient. Of these microRNAs, microRNAs that can be highly expressed in gastric cancer patients can be preferably used for prediction.
  • the urine extract can be a urine extract of a stage I or II gastric cancer patient. Only one of these microRNAs can predict whether or not the subject from which urine is derived is a gastric cancer patient (particularly stage I or II), and 5 or more, 10 or more, 15 or more, or By combining 20 or more species, it is possible to predict whether or not the subject from which urine is derived is a gastric cancer patient (particularly stage I or II). Of these microRNAs, microRNAs that can be highly expressed in gastric cancer patients (particularly stage I or II) can be preferably used for prediction.
  • the urine extract may be a urine extract of a stage I gastric cancer patient. Only one of these microRNAs can predict whether or not the subject from which urine is derived is a gastric cancer patient (particularly stage I), and 5 or more, 10 or more, 15 or more, or 20 types. By combining the above, it is possible to predict whether or not the subject from which urine is derived is a gastric cancer patient (particularly stage I). Of these microRNAs, microRNAs that can be highly expressed in gastric cancer patients (particularly stage I) can be preferably used for prediction.
  • Urinary extracts containing 6, 7, 8, 9, or 10 or all microRNAs are provided.
  • the urine extract can be the urine extract of a gastric cancer patient. Only one of these microRNAs can predict whether or not the subject from which urine is derived is a gastric cancer patient, and a combination of 5 or more, 10 or more, 15 or more, or 20 or more can be used. Therefore, it is possible to predict whether or not the subject from which urine is derived is a gastric cancer patient.
  • a microRNA that can be highly expressed in a gastric cancer patient can be preferably used for prediction.
  • Accuracy exceeds 0.5, 0.55 or more, 0.6 or more, 0.65 or more, 0.7 or more, 0.75 or more, 0.8 or more, 0.85 or more, or 0.9 or more Can be.
  • Urinary extracts containing 6, 7, 8, 9, or 10 or all microRNAs are provided.
  • the urine extract can be the urine extract of a gastric cancer patient. Only one of these microRNAs can predict whether or not the subject from which urine is derived is a gastric cancer patient, and a combination of 5 or more, 10 or more, 15 or more, or 20 or more can be used. It is possible to predict whether or not the subject from which urine is derived is a gastric cancer patient.
  • microRNAs that can be highly expressed in a gastric cancer patient can be preferably used for prediction.
  • accuracy Is greater than 0.5, 0.55 or higher, 0.6 or higher, 0.65 or higher, 0.7 or higher, 0.75 or higher, 0.8 or higher, 0.85 or higher, or 0.9 or higher. obtain.
  • a urine extract containing all microRNAs is provided.
  • the urine extract can be a urine extract of a patient with urothelial cancer. Only one of these microRNAs can predict whether or not the subject from which urine is derived is a patient with urothelial cancer, and 5 or more, 10 or more, 15 or more, or 20 or more. Can be combined to predict whether or not the subject from which urine is derived is a patient with urothelial cancer. Of these microRNAs, microRNAs that can be highly expressed in patients with urothelial cancer can be preferably used for prediction.
  • a urine extract containing 10 or all microRNAs is provided.
  • the urine extract can be a urine extract from a patient with stage I or II urothelial cancer. Only one of these microRNAs can predict whether or not the subject from which urine is derived is a patient with urothelial cancer (particularly stage I or II), and 5 or more, 10 or more, 15 It is possible to predict whether or not the subject from which urine is derived is a patient with urothelial cancer (particularly stage I or II) by combining more than one species or 20 or more species.
  • microRNAs that can be highly expressed in patients with urothelial cancer (particularly stage I or II) can be preferably used for prediction.
  • the urine extract can be a urine extract of a stage I urothelial cancer patient. Only one of these microRNAs can predict whether or not the subject from which urine is derived is a patient with urothelial cancer (particularly stage I), and 5 or more, 10 or more, and 15 or more. , Or a combination of 20 or more, it is possible to predict whether or not the subject from which urine is derived is a patient with urothelial cancer (particularly stage I). Among these microRNAs, microRNAs that can be highly expressed in patients with urothelial cancer (particularly stage I) can be preferably used for prediction.
  • Urinary extracts containing 6, 7, 8, 9, or 10 or all microRNAs are provided.
  • the urine extract can be a urine extract of a patient with urothelial cancer. Only one of these microRNAs can predict whether or not the subject from which urine is derived is a patient with urothelial cancer, and 5 or more, 10 or more, 15 or more, or 20 or more. In combination, it is possible to predict whether or not the subject from which urine is derived is a patient with urothelial cancer.
  • the accuracy is greater than 0.5, 0.55 or higher, 0.6 or higher, 0.65 or higher, 0.7 or higher, 0.75 or higher, 0.8 or higher, It can be 0.85 or higher, or 0.9 or higher.
  • Urinary extracts containing 6, 7, 8, 9, or 10 or all microRNAs are provided.
  • the urine extract can be a urine extract of a patient with urothelial cancer. Only one of these microRNAs can predict whether or not the subject from which urine is derived is a patient with urothelial cancer, and 5 or more, 10 or more, 15 or more, or 20 or more. In combination, it is possible to predict whether or not the subject from which urine is derived is a patient with urothelial cancer.
  • the accuracy is greater than 0.5, 0.55 or higher, 0.6 or higher, 0.65 or higher, 0.7 or higher, 0.75 or higher, 0.8 or higher, It can be 0.85 or higher, or 0.9 or higher.
  • an extract of urine containing all microRNAs is provided.
  • the urine extract can be an extract of urine from a melanoma patient. Only one of these microRNAs can predict whether or not the subject from which urine is derived is a melanoma patient, and a combination of 5 or more, 10 or more, 15 or more, or 20 or more can be used. It is possible to predict whether or not the subject from which urine is derived is a melanoma patient. Of these microRNAs, microRNAs that can be highly expressed in melanoma patients can be preferably used for prediction.
  • the urine extract can be an extract of the urine of a stage I or II melanoma patient. Only one of these microRNAs can predict whether or not the subject from which urine is derived is a melanoma patient (particularly stage I or II), with 5 or more, 10 or more, 15 or more, or By combining 20 or more species, it is possible to predict whether or not the subject from which urine is derived is a melanoma patient (particularly stage I or II). Of these microRNAs, microRNAs that can be highly expressed in melanoma patients (particularly stage I or II) can be preferably used for prediction.
  • the urine extract can be an extract of the urine of a stage I melanoma patient. Only one of these microRNAs can predict whether or not the subject from which urine is derived is a melanoma patient (particularly stage I), and 5 or more, 10 or more, 15 or more, or 20 types. By combining the above, it is possible to predict whether or not the subject from which urine is derived is a melanoma patient (particularly stage I). Of these microRNAs, microRNAs that can be highly expressed in melanoma patients (particularly Stage I) can be preferably used for prediction.
  • Urinary extracts containing 6, 7, 8, 9, or 10 or all microRNAs are provided.
  • the urine extract can be an extract of urine from a melanoma patient. Only one of these microRNAs can predict whether or not the subject from which urine is derived is a melanoma patient, and a combination of 5 or more, 10 or more, 15 or more, or 20 or more can be used. It is possible to predict whether or not the subject from which urine is derived is a melanoma patient.
  • microRNAs that can be highly expressed in a melanoma patient can be preferably used for prediction.
  • accuracy Is greater than 0.5, 0.55 or higher, 0.6 or higher, 0.65 or higher, 0.7 or higher, 0.75 or higher, 0.8 or higher, 0.85 or higher, or 0.9 or higher. obtain.
  • Urinary extracts containing 6, 7, 8, 9, or 10 or all microRNAs are provided.
  • the urine extract can be an extract of urine from a melanoma patient. Only one of these microRNAs can predict whether or not the subject from which urine is derived is a melanoma patient, and a combination of 5 or more, 10 or more, 15 or more, or 20 or more can be used. It is possible to predict whether or not the subject from which urine is derived is a melanoma patient.
  • microRNAs that can be highly expressed in a melanoma patient can be preferably used for prediction.
  • accuracy Is greater than 0.5, 0.55 or higher, 0.6 or higher, 0.65 or higher, 0.7 or higher, 0.75 or higher, 0.8 or higher, 0.85 or higher, or 0.9 or higher. obtain.
  • a urine extract containing all microRNAs is provided.
  • a urine extract containing 10 or all microRNAs is provided.
  • the urine extract can be an extract of urine from a patient with ovarian cancer. Only one of these microRNAs can predict whether or not the subject from which urine is derived is an ovarian cancer patient, and a combination of 5 or more, 10 or more, 15 or more, or 20 or more. Therefore, it is possible to predict whether or not the subject from which urine is derived is an ovarian cancer patient. Of these microRNAs, microRNAs that can be highly expressed in ovarian cancer patients can be preferably used for prediction.
  • the urine extract can be a urine extract of a stage I or II ovarian cancer patient. Only one of these microRNAs can predict whether or not the subject from which urine is derived is an ovarian cancer patient (particularly stage I or II), and 5 or more, 10 or more, 15 or more. , Or a combination of 20 or more, can predict whether the subject from which urine is derived is an ovarian cancer patient (particularly stage I or II). Of these microRNAs, microRNAs that can be highly expressed in ovarian cancer patients (particularly stage I or II) can be preferably used for prediction.
  • hsa-miR-93-5p hsa-miR-210-3p, hsa-miR-221-3p, hsa-miR-27b-3p, hsa-miR-143-3p, hsa-miR- 34b-5p, hsa-miR-130b-3p, hsa-miR-371a-3p, hsa-miR-380-3p, hsa-miR-382-5p, hsa-miR-383-5p, hsa-miR-330- 3p, hsa-miR-369-5p, hsa-miR-431-5p, hsa-miR-452-3p, hsa-miR-485-5p, hsa-miR-518b-3p, hsa-miR-525-3p, hsa-miR-519a
  • Urinary extracts containing 2, 3, 4, 4, 5, 6, 7, 7, 8, 9, or 10 or all microRNAs are provided.
  • the urine extract can be a urine extract of a stage I ovarian cancer patient.
  • these microRNAs it is possible to predict whether or not the subject from which urine is derived is an ovarian cancer patient (particularly stage I), and 5 or more, 10 or more, 15 or more, or By combining 20 or more species, it is possible to predict whether or not the subject from which urine is derived is an ovarian cancer patient (particularly stage I).
  • microRNAs that can be highly expressed in ovarian cancer patients (particularly Stage I) can be preferably used for prediction.
  • Urinary extracts containing 6, 7, 8, 9, or 10 or all microRNAs are provided.
  • the urine extract can be an extract of urine from a patient with ovarian cancer. Only one of these microRNAs can predict whether or not the subject from which urine is derived is an ovarian cancer patient, and a combination of 5 or more, 10 or more, 15 or more, or 20 or more. Therefore, it is possible to predict whether or not the target from which urine is derived is an ovarian cancer patient.
  • a microRNA that can be highly expressed in an ovarian cancer patient can be preferably used for prediction.
  • the accuracy is greater than 0.5, greater than 0.55, greater than or equal to 0.6, greater than or equal to 0.65, greater than or equal to 0.7, greater than or equal to 0.75, greater than or equal to 0.8, greater than or equal to 0.85, or It can be 0.9 or higher.
  • Urinary extracts containing 6, 7, 8, 9, or 10 or all microRNAs are provided.
  • the urine extract can be an extract of urine from a patient with ovarian cancer. Only one of these microRNAs can predict whether or not the subject from which urine is derived is an ovarian cancer patient, and a combination of 5 or more, 10 or more, 15 or more, or 20 or more. Therefore, it is possible to predict whether or not the target from which urine is derived is an ovarian cancer patient.
  • a microRNA that can be highly expressed in an ovarian cancer patient can be preferably used for prediction.
  • the accuracy is greater than 0.5, greater than 0.55, greater than or equal to 0.6, greater than or equal to 0.65, greater than or equal to 0.7, greater than or equal to 0.75, greater than or equal to 0.8, greater than or equal to 0.85, or It can be 0.9 or higher.
  • a urine extract containing all microRNAs is provided.
  • hsa-miR-1292-5p hsa-miR-4521, hsa-miR-451, hsa-miR-8080, hsa-miR-6071, hsa-miR-4691-3p, hsa-miR-127 -5p, hsa-miR-3133, hsa-miR-1914-3p, hsa-miR-6838-5p, hsa-miR-4755-3p, hsa-miR-10526-3p, hsa-miR-551b-5p, hsa -MiR-8078, hsa-miR-181d-3p, hsa-miR-489-5p, hsa-miR-4321, hsa-miR-4280, hsa-miR-605-3p, hsa-miR
  • the urine extract can be a urine extract of a thyroid cancer patient. Only one of these microRNAs can predict whether or not the subject from which urine is derived is a thyroid cancer patient, and a combination of 5 or more, 10 or more, 15 or more, or 20 or more. Therefore, it is possible to predict whether or not the subject from which urine is derived is a thyroid cancer patient. Of these microRNAs, microRNAs that can be highly expressed in thyroid cancer patients can be preferably used for prediction.
  • the urine extract can be a urine extract of a stage I or II thyroid cancer patient. Only one of these microRNAs can predict whether or not the subject from which urine is derived is a thyroid cancer patient (particularly stage I or II), and 5 or more, 10 or more, 15 or more. , Or a combination of 20 or more, can predict whether the subject from which urine is derived is a thyroid cancer patient (particularly stage I or II). Of these microRNAs, microRNAs that can be highly expressed in thyroid cancer patients (particularly stage I or II) can be preferably used for prediction.
  • the urine extract may be a urine extract of a stage I thyroid cancer patient. Only one of these microRNAs can predict whether or not the subject from which urine is derived is a thyroid cancer patient (particularly stage I), with 5 or more, 10 or more, 15 or more, or By combining 20 or more species, it is possible to predict whether or not the subject from which urine is derived is a thyroid cancer patient (particularly stage I). Of these microRNAs, microRNAs that can be highly expressed in thyroid cancer patients (particularly Stage I) can be preferably used for prediction.
  • Urinary extracts containing 6, 7, 8, 9, or 10 or all microRNAs are provided.
  • the urine extract can be a urine extract of a thyroid cancer patient. Only one of these microRNAs can predict whether or not the subject from which urine is derived is a thyroid cancer patient, and a combination of 5 or more, 10 or more, 15 or more, or 20 or more. Therefore, it is possible to predict whether or not the subject from which urine is derived is a thyroid cancer patient.
  • a microRNA that can be highly expressed in a thyroid cancer patient can be preferably used for prediction.
  • the accuracy is greater than 0.5, greater than 0.55, greater than or equal to 0.6, greater than or equal to 0.65, greater than or equal to 0.7, greater than or equal to 0.75, greater than or equal to 0.8, greater than or equal to 0.85, or It can be 0.9 or higher.
  • Urinary extracts containing 6, 7, 8, 9, or 10 or all microRNAs are provided.
  • the urine extract can be a urine extract of a thyroid cancer patient. Only one of these microRNAs can predict whether or not the subject from which urine is derived is a thyroid cancer patient, and a combination of 5 or more, 10 or more, 15 or more, or 20 or more. Therefore, it is possible to predict whether or not the subject from which urine is derived is a thyroid cancer patient.
  • a microRNA that can be highly expressed in a thyroid cancer patient can be preferably used for prediction.
  • the accuracy is greater than 0.5, greater than 0.55, greater than or equal to 0.6, greater than or equal to 0.65, greater than or equal to 0.7, greater than or equal to 0.75, greater than or equal to 0.8, greater than or equal to 0.85, or It can be 0.9 or higher.
  • a urine extract containing all microRNAs is provided.
  • Urine extracts comprising 2, 3, 4, 5, 6, 7, 7, 8, 9, or 10 or all microRNAs are provided.
  • the urine extract can be an extract of urine from a patient with cervical cancer.
  • these microRNAs it is possible to predict whether or not the subject from which urine is derived is a patient with cervical cancer. In combination, it is possible to predict whether or not the subject from which urine is derived is a patient with cervical cancer.
  • microRNAs that can be highly expressed in cervical cancer patients can be preferably used for prediction.
  • the urine extract can be a urine extract of a stage I or II cervical cancer patient. Only one of these microRNAs can predict whether or not the subject from which urine is derived is a cervical cancer patient (particularly stage I or II), and 5 or more, 10 or more, 15 types. By combining the above, or a combination of 20 or more, it is possible to predict whether or not the subject from which urine is derived is a cervical cancer patient (particularly stage I or II). Of these microRNAs, microRNAs that can be highly expressed in cervical cancer patients (particularly stage I or II) can be preferably used for prediction.
  • a urine extract containing 10 or all microRNAs is provided.
  • the urine extract can be a urine extract of a stage I cervical cancer patient. Only one of these microRNAs can predict whether or not the subject from which urine is derived is a cervical cancer patient (particularly stage I), and 5 or more, 10 or more, 15 or more, Alternatively, a combination of 20 or more can be used to predict whether or not the subject from which urine is derived is a cervical cancer patient (particularly Stage I). Of these microRNAs, microRNAs that can be highly expressed in cervical cancer patients (particularly stage I) can be preferably used for prediction.
  • the urine extract can be the urine extract of a cervical cancer patient. Only one of these microRNAs can predict whether or not the subject from which urine is derived is a cervical cancer patient, and 5 or more, 10 or more, 15 or more, or 20 or more. In combination, it is possible to predict whether or not the subject from which urine is derived is a cervical cancer patient. Of these microRNAs, a microRNA that can be highly expressed in a cervical cancer patient is preferably used for prediction. In some embodiments, the accuracy is greater than 0.5, 0.55 or greater, 0.6 or greater, 0.65 or greater, 0.7 or greater, 0.75 or greater, 0.8 or greater, 0.85. It can be greater than or equal to or greater than or equal to 0.9.
  • the urine extract can be the urine extract of a cervical cancer patient. Only one of these microRNAs can predict whether or not the subject from which urine is derived is a cervical cancer patient, and 5 or more, 10 or more, 15 or more, or 20 or more. In combination, it is possible to predict whether or not the subject from which urine is derived is a cervical cancer patient. Of these microRNAs, a microRNA that can be highly expressed in a cervical cancer patient is preferably used for prediction. In some embodiments, the accuracy is greater than 0.5, 0.55 or greater, 0.6 or greater, 0.65 or greater, 0.7 or greater, 0.75 or greater, 0.8 or greater, 0.85. It can be greater than or equal to or greater than or equal to 0.9.
  • a urine extract containing all microRNAs is provided.
  • the urine extract can be an extract of urine from a patient with rectal colon cancer. Only one of these microRNAs can predict whether or not the subject from which urine is derived is a patient with rectal colon cancer, and 5 or more, 10 or more, 15 or more, or 20 or more. In combination, it is possible to predict whether or not the subject from which urine is derived is a patient with rectal colon cancer. Of these microRNAs, microRNAs that can be highly expressed in patients with rectal colon cancer can be preferably used for prediction.
  • Urinary extracts containing at least one, two, three, four, five, six, seven, eight, nine, or ten or all microRNAs are provided.
  • the urine extract can be a urine extract of a stage I or II rectal colon cancer patient. Only one of these microRNAs can predict whether or not the subject from which urine is derived is a rectal colon cancer patient (particularly stage I or II), and 5 or more, 10 or more, 15 types. By combining the above, or a combination of 20 or more, it is possible to predict whether or not the subject from which urine is derived is a rectal colon cancer patient (particularly stage I or II). Of these microRNAs, microRNAs that can be highly expressed in patients with rectal colon cancer (particularly stage I or II) can be preferably used for prediction.
  • Urine extracts comprising at least one, two, three, four, five, six, seven, eight, nine, or ten or all microRNAs are provided.
  • the urine extract can be a urine extract of a stage I rectal colon cancer patient. Only one of these microRNAs can predict whether or not the subject from which urine is derived is a rectal colon cancer patient (particularly stage I), and 5 or more, 10 or more, 15 or more, Alternatively, a combination of 20 or more can be used to predict whether or not the subject from which urine is derived is a rectal colon cancer patient (particularly Stage I).
  • microRNAs that can be highly expressed in patients with rectal colon cancer (particularly stage I) can be preferably used for prediction.
  • Urinary extracts containing 6, 7, 8, 9, or 10 or all microRNAs are provided.
  • the urine extract can be an extract of urine from a patient with rectal colon cancer. Only one of these microRNAs can predict whether or not the subject from which urine is derived is a patient with rectal colon cancer, and 5 or more, 10 or more, 15 or more, or 20 or more. In combination, it is possible to predict whether or not the subject from which urine is derived is a rectal colon cancer patient.
  • a microRNA that can be highly expressed in a rectal colon cancer patient is preferably used for prediction.
  • the accuracy is greater than 0.5, 0.55 or greater, 0.6 or greater, 0.65 or greater, 0.7 or greater, 0.75 or greater, 0.8 or greater, 0.85. It can be greater than or equal to or greater than or equal to 0.9.
  • Urinary extracts containing 6, 7, 8, 9, or 10 or all microRNAs are provided.
  • the urine extract can be an extract of urine from a patient with rectal colon cancer. Only one of these microRNAs can predict whether or not the subject from which urine is derived is a patient with rectal colon cancer, and 5 or more, 10 or more, 15 or more, or 20 or more. In combination, it is possible to predict whether or not the subject from which urine is derived is a rectal colon cancer patient.
  • a microRNA that can be highly expressed in a rectal colon cancer patient is preferably used for prediction.
  • the accuracy is greater than 0.5, 0.55 or greater, 0.6 or greater, 0.65 or greater, 0.7 or greater, 0.75 or greater, 0.8 or greater, 0.85. It can be greater than or equal to or greater than or equal to 0.9.
  • a urine extract containing all microRNAs is provided.
  • Urine extracts comprising one, two, three, four, five, six, seven, eight, nine, or ten or all microRNAs are provided.
  • the urine extract can be an extract of urine from a patient with endometrial cancer. Only one of these microRNAs can predict whether or not the subject from which urine is derived is an endometrial cancer patient, and 5 or more, 10 or more, 15 or more, or 20 or more. Can be combined to predict whether or not the subject from which urine is derived is an endometrial cancer patient. Of these microRNAs, microRNAs that can be highly expressed in endometrial cancer patients can be preferably used for prediction.
  • let-7e-5p miR-15a-5p, miR-17-3p, miR-29a-3p, miR-30a-5p, miR-31-5p, miR-29b-3p, miR-196a-5p, miR- 197-3p, miR-198, miR-199a-5p, miR-199a-3p, miR-199b-3p, miR-30d-5p, miR-139-5p, miR-187-3p, miR-199b-5p, miR-214-3p, miR-223-3p, miR-122-5p, miR-124-3p, miR-138-5p, miR-140-5p, miR-141-3p, miR-125a-5p, miR- 134-5p, miR-149-5p, miR-154-3p, miR-184, miR-185-5p, miR-188-5p, miR-206, miR-106b-5p, miR-29c-3p, miR- 34c-5p, miR-299-3p,
  • the urine extract can be a urine extract of a stage I or II endometrial cancer patient. Only one of these microRNAs can predict whether or not the subject from which urine is derived is an endometrial cancer patient (particularly stage I or II), and 5 or more, 10 or more, 15 It is possible to predict whether or not the subject from which urine is derived is an endometrial cancer patient (particularly stage I or II) by combining more than one species or 20 or more species. Of these microRNAs, microRNAs that can be highly expressed in endometrial cancer patients (particularly stage I or II) can be preferably used for prediction.
  • the urine extract can be a urine extract of a stage I endometrial cancer patient. Only one of these microRNAs can predict whether or not the subject from which urine is derived is an endometrial cancer patient (particularly stage I), and 5 or more, 10 or more, 15 or more. , Or a combination of 20 or more, it is possible to predict whether or not the subject from which urine is derived is an endometrial cancer patient (particularly stage I).
  • microRNAs that can be highly expressed in endometrial cancer patients (particularly stage I) can be preferably used for prediction.
  • Urinary extracts containing 6, 7, 8, 9, or 10 or all microRNAs are provided.
  • the urine extract can be an extract of urine from a patient with endometrial cancer. Only one of these microRNAs can predict whether or not the subject from which urine is derived is an endometrial cancer patient, and 5 or more, 10 or more, 15 or more, or 20 or more. Can be combined to predict whether or not the subject from which urine is derived is a patient with endometrial cancer (whether or not it is present.
  • microRNAs a microRNA that can be highly expressed in patients with endometrial cancer is predicted.
  • the accuracy is greater than 0.5, 0.55 or higher, 0.6 or higher, 0.65 or higher, 0.7 or higher, 0.75 or higher, 0.8 or higher, It can be 0.85 or higher, or 0.9 or higher.
  • Urinary extracts containing 6, 7, 8, 9, or 10 or all microRNAs are provided.
  • the urine extract can be an extract of urine from a patient with endometrial cancer. Only one of these microRNAs can predict whether or not the subject from which urine is derived is an endometrial cancer patient, and 5 or more, 10 or more, 15 or more, or 20 or more. Can be combined to predict whether or not the subject from which urine is derived is a patient with endometrial cancer (whether or not it is present.
  • microRNAs a microRNA that can be highly expressed in patients with endometrial cancer is predicted.
  • the accuracy is greater than 0.5, 0.55 or higher, 0.6 or higher, 0.65 or higher, 0.7 or higher, 0.75 or higher, 0.8 or higher, It can be 0.85 or higher, or 0.9 or higher.
  • microRNAs are the microRNAs included in the above table, but are microRNAs in which fluctuations are commonly observed in all cancer types.
  • An extract of urine is provided, including.
  • Urinary extracts containing 4, 5, 6, 7, 8, 9, or 10 or all microRNAs are provided.
  • Urinary extracts containing 6, 7, 8, 9, or 10 or all microRNAs are provided. According to the present disclosure, among the groups (ALL), at least one, two, three, four, five, selected from the group consisting of microRNAs listed in Tables 25-1 to 25-15. Urinary extracts containing 6, 7, 8, 9, or 10 or all microRNAs are provided.
  • the microRNAs listed in Tables 24-1 to 24-15 and the microRNAs listed in Tables 25-1 to 25-15 can have an accuracy greater than 0.500 in the table. According to the present disclosure, it is predicted that the subject from which the urine is derived may be cancer, using whether or not the urine obtained from the subject corresponds to any of the above urine extracts as an index. Can be done.
  • the subject from which the urine is derived is cancer. It can be predicted that there is a possibility.
  • the urine obtained from the subject contains microRNA selected from the above group at a predetermined value (second threshold value) or less, the subject from which the urine is derived may be cancer. It can be predicted that there is sex.
  • a predetermined value (first threshold value or second threshold value) can be set independently for each microRNA.
  • microRNAs are the microRNAs included in the above table, but are microRNAs in which fluctuations are commonly observed in all cancer types.
  • An extract of urine is provided, including.
  • Urinary extracts containing 4, 5, 6, 7, 8, 9, or 10 or all microRNAs are provided.
  • An extract of urine containing species, 5, 6, 7, 8, 9, or 10 or all microRNAs is provided.
  • among the groups (GI) at least 1 type, 2 types, 3 types, 4 types, 5 types, selected from the group consisting of microRNAs shown in Tables 22-1 to 22-13.
  • Urinary extracts containing 6, 7, 8, 9, or 10 or all microRNAs are provided.
  • Urinary extracts containing 6, 7, 8, 9, or 10 or all microRNAs are provided. According to the present disclosure, among the groups (GI), at least one, two, three, four, five, selected from the group consisting of microRNAs listed in Tables 25-1 to 25-15. Urinary extracts containing 6, 7, 8, 9, or 10 or all microRNAs are provided.
  • the microRNAs listed in Tables 24-1 to 24-15 and the microRNAs listed in Tables 25-1 to 25-15 can have an accuracy greater than 0.500 in the table. According to the present disclosure, it is predicted that the subject from which the urine is derived may be cancer, using whether or not the urine obtained from the subject corresponds to any of the above urine extracts as an index. Can be done.
  • the subject from which the urine is derived is cancer. It can be predicted that there is a possibility.
  • the urine obtained from the subject contains microRNA selected from the above group at a predetermined value (second threshold value) or less, the subject from which the urine is derived may be cancer. It can be predicted that there is sex.
  • a predetermined value (first threshold value or second threshold value) can be set independently for each microRNA.
  • microRNAs are the microRNAs included in the above table, but are microRNAs in which fluctuations are commonly observed in all cancer types.
  • An extract of urine is provided, including.
  • Urinary extracts containing 4, 5, 6, 7, 8, 9, or 10 or all microRNAs are provided.
  • Urinary extracts containing 6, 7, 8, 9, or 10 or all microRNAs are provided. According to the present disclosure, at least one, two, three, four, five, selected from the group consisting of microRNAs listed in Tables 25-1 to 25-15, among the groups (Hemo). Urinary extracts containing 6, 7, 8, 9, or 10 or all microRNAs are provided.
  • the microRNAs listed in Tables 24-1 to 24-15 and the microRNAs listed in Tables 25-1 to 25-15 can have an accuracy greater than 0.500 in the table. According to the present disclosure, it is predicted that the subject from which the urine is derived may be cancer, using whether or not the urine obtained from the subject corresponds to any of the above urine extracts as an index. Can be done.
  • the subject from which the urine is derived is cancer. It can be predicted that there is a possibility.
  • the urine obtained from the subject contains microRNA selected from the above group at a predetermined value (second threshold value) or less, the subject from which the urine is derived may be cancer. It can be predicted that there is sex.
  • a predetermined value (first threshold value or second threshold value) can be set independently for each microRNA.
  • let-7b-5p miR-25-3p, miR-28-5p, miR-29a-3p, miR-29b-3p, miR-105-5p, miR-192-5p, miR-196a-5p, miR- 197-3p, miR-198, miR-199a-5p, miR-129-5p, miR-30d-5p, miR-147a, miR-10a-5p, miR-34a-5p, miR-181a-5p, miR- 181b-5p, miR-187-3p, miR-199b-5p, miR-204-5p, miR-210-3p, miR-221-5p, miR-212-3p, miR-214-3p, miR-221- 3p, miR-223-3p, miR-200b-3p, miR-23b-3p, miR-30b-5p, miR-122-5p, miR-124-3p, miR-125b-5p, miR-138
  • microRNAs are the microRNAs included in the above table, but are microRNAs in which fluctuations are commonly observed in all cancer types.
  • An extract of urine is provided, including.
  • Urinary extracts containing 4, 5, 6, 7, 8, 9, or 10 or all microRNAs are provided.
  • Urinary extracts containing 6, 7, 8, 9, or 10 or all microRNAs are provided. According to the present disclosure, at least one, two, three, four, five, selected from the group consisting of microRNAs listed in Tables 25-1 to 25-15, among the groups (Uro). Urinary extracts containing 6, 7, 8, 9, or 10 or all microRNAs are provided.
  • the microRNAs listed in Tables 24-1 to 24-15 and the microRNAs listed in Tables 25-1 to 25-15 can have an accuracy greater than 0.500 in the table. According to the present disclosure, it is predicted that the subject from which the urine is derived may be cancer, using whether or not the urine obtained from the subject corresponds to any of the above urine extracts as an index. Can be done.
  • the subject from which the urine is derived is cancer. It can be predicted that there is a possibility.
  • the urine obtained from the subject contains microRNA selected from the above group at a predetermined value (second threshold value) or less, the subject from which the urine is derived may be cancer. It can be predicted that there is sex.
  • a predetermined value (first threshold value or second threshold value) can be set independently for each microRNA.
  • microRNA that can be highly expressed in cancer patients can be preferably used for prediction.
  • microRNAs that may be underexpressed in cancer patients may be used for prediction.
  • microRNAs that can be highly expressed in cancer patients may be preferably used for prediction, and in addition, microRNAs that can be lowly expressed in cancer patients may be used for prediction. High or low expression is obtained by comparing the relative expression level with the first quartile, mean, median, or third quartile of healthy subjects.
  • Another aspect of the disclosure provides a method of testing the subject for possible cancer.
  • Methods for testing for possible cancer include diagnosing cancer, obtaining preliminary information to diagnose cancer, and whether cancer cells are present in the subject's body. It can be read as a method of determining the possibility of cancer or a method of determining the possibility that the subject has cancer.
  • a definitive diagnosis can be made by a doctor or the like thereafter.
  • the present disclosure provides methods according to the methods of the present disclosure, including diagnosing cancer and providing anti-cancer treatment to a patient diagnosed with cancer.
  • microRNA that can be highly expressed in a cancer patient when it may be indicated that the patient from which the urine is derived has cancer or is likely to have cancer.
  • microRNA that can be underexpressed in a cancer patient when it may be indicated that the patient from which the urine is derived is not cancer or the possibility thereof.
  • the possibility that the subject has cancer can be determined by using the expression level of any of the microRNAs listed in any of Tables 4-1 to 4-15 in the body fluid sample as an index.
  • a body fluid sample means a body fluid obtained from a subject or a sample derived from the body fluid.
  • the body fluid sample may be blood, serum, plasma, lymph, tissue fluid such as interstitial fluid, interstitial fluid, interstitial fluid, etc. , Cerebrospinal fluid (medullary fluid), joint fluid (slip fluid), and aqueous humor (aqueous humor).
  • the body fluid may be digestive juice such as saliva, gastric juice, bile, pancreatic juice, and intestinal juice, and may be sweat, tears, runny nose, urine, semen, vaginal juice, amniotic fluid, and milk.
  • the body fluid may be an animal body fluid or a human body fluid.
  • body fluid samples may be provided.
  • urine or an extract thereof can be preferably used as the body fluid sample.
  • the urine extract can be the urine extract of the present disclosure.
  • an extract of a body fluid sample, particularly an extract of urine may be provided.
  • Body fluids eg, urine
  • the cancer is not particularly limited, but may be, for example, one or more cancers selected from solid cancers, hematopoietic tumors, and the like.
  • cancer include lung cancer, breast cancer, kidney cancer, leukemia, lymphoma, pancreatic cancer, gastric cancer, urinary tract epithelial cancer, thyroid cancer, ovarian cancer, melanoma, liver cancer, bladder cancer, and prostate. Included is one or more selected from the group consisting of cancer, cervical cancer, rectal colon cancer, and endometrial cancer.
  • the possibility that the subject has cancer can be evaluated using the microRNA level of the subject's body fluid sample as an index. For example, for microRNA that showed higher expression in a subject with cancer than in a non-cancer subject in either data S1 (or Table 3) or Tables 4-1 to 4-15, the subject. It can be determined that the subject is likely to have cancer by using the fact that the microRNA level of the body fluid sample is higher than a predetermined value (hereinafter, may be referred to as “threshold value”) as an index.
  • a predetermined value hereinafter, may be referred to as “threshold value”
  • the micro of the body fluid sample of the subject Using the RNA level higher than a predetermined value (hereinafter, sometimes referred to as “threshold value”) as an index, it can be determined that the subject is likely to have cancer. Also, for example, in data S1 (or Table 3), or in any of Tables 4-1 to 4-15, microRNAs (eg, doubled) that showed higher expression in subjects with cancer than in non-cancer subjects.
  • a predetermined value hereinafter, sometimes referred to as “threshold value”
  • the microRNA level of the target body fluid sample is a predetermined value (hereinafter, "threshold value"). It can be determined that the subject is unlikely to have cancer by using a lower value than (sometimes said) as an index.
  • the microRNA level of the target body fluid sample is a predetermined value (hereinafter, may be referred to as "threshold value"). It can be determined that the subject is unlikely to have cancer by using the lower value as an index.
  • the index microRNA is any one or more of Table 3.
  • the cancer can be lung cancer.
  • the cancer can be pancreatic cancer.
  • the cancer can be liver cancer.
  • the cancer can be bladder cancer. In this embodiment, the cancer can be prostate cancer. MicroRNA is a microRNA that exhibits higher expression in a subject with cancer than in a subject with non-cancer. In some embodiments, the index microRNA is any one or more of Table 4-1. In this embodiment, the cancer can be lung cancer. MicroRNA is a microRNA that exhibits higher expression in a subject with cancer than in a subject with non-cancer. In some embodiments, the index microRNA is any one or more of Table 4-2. In this embodiment, the cancer can be breast cancer. MicroRNA is a microRNA that exhibits higher expression in a subject with cancer than in a subject with non-cancer. In some embodiments, the index microRNA is any one or more of Table 4-3.
  • the cancer can be kidney cancer.
  • MicroRNA is a microRNA that exhibits higher expression in a subject with cancer than in a subject with non-cancer.
  • the index microRNA is any one or more of Table 4-4.
  • the cancer can be leukemia.
  • MicroRNA is a microRNA that exhibits higher expression in a subject with cancer than in a subject with non-cancer.
  • the index microRNA is any one or more of Table 4-5.
  • the cancer can be lymphoma.
  • MicroRNA is a microRNA that exhibits higher expression in a subject with cancer than in a subject with non-cancer.
  • the index microRNA is any one or more of Table 4-6.
  • the cancer can be pancreatic cancer.
  • MicroRNA is a microRNA that exhibits higher expression in a subject with cancer than in a subject with non-cancer.
  • the index microRNA is any one or more of Table 4-7.
  • the cancer can be prostate cancer.
  • MicroRNA is a microRNA that exhibits higher expression in a subject with cancer than in a subject with non-cancer.
  • the index microRNA is any one or more of Table 4-8.
  • the cancer can be gastric cancer.
  • MicroRNA is a microRNA that exhibits higher expression in a subject with cancer than in a subject with non-cancer.
  • the index microRNA is any one or more of Table 4-9.
  • the cancer can be a urothelial cancer.
  • MicroRNA is a microRNA that exhibits higher expression in a subject with cancer than in a subject with non-cancer.
  • the index microRNA is any one or more of Table 4-10.
  • the cancer can be melanoma.
  • MicroRNA is a microRNA that exhibits higher expression in a subject with cancer than in a subject with non-cancer.
  • the index microRNA is any one or more of Table 4-11.
  • the cancer can be ovarian cancer.
  • MicroRNA is a microRNA that exhibits higher expression in a subject with cancer than in a subject with non-cancer.
  • the index microRNA is any one or more of Table 4-12.
  • the cancer can be thyroid cancer.
  • MicroRNA is a microRNA that exhibits higher expression in a subject with cancer than in a subject with non-cancer.
  • the index microRNA is any one or more of Table 4-13.
  • the cancer can be cervical cancer.
  • MicroRNA is a microRNA that exhibits higher expression in a subject with cancer than in a subject with non-cancer.
  • the index microRNA is any one or more of Table 4-14.
  • the cancer can be rectal colon cancer.
  • MicroRNA is a microRNA that exhibits higher expression in a subject with cancer than in a subject with non-cancer.
  • the index microRNA is any one or more of Table 4-15.
  • the cancer can be endometrial cancer.
  • MicroRNA is a microRNA that exhibits higher expression in a subject with cancer than in a subject with non-cancer.
  • the index microRNA is a microRNA having a p-value of less than 0.005 from any of the tables 4-1 to 4-15.
  • MicroRNA is a microRNA that exhibits higher expression in a subject with cancer than in a subject with non-cancer.
  • the index microRNA is the microRNA listed in any of Tables 22-1 and 23-1-23-14.
  • MicroRNA is a microRNA that exhibits higher expression in a subject with cancer than in a subject with non-cancer.
  • the index microRNA is the microRNA set forth in any of Tables 24-1 to 24-15.
  • MicroRNA is a microRNA that exhibits higher expression in a subject with cancer than in a subject with non-cancer.
  • the index microRNA is the microRNA listed in any of Tables 25-1 to 25-15.
  • MicroRNA is a microRNA that exhibits higher expression in a subject with cancer than in a subject with non-cancer.
  • the index microRNA is at least one of the group (ALL).
  • the cancer can be endometrial cancer.
  • MicroRNA is a microRNA that exhibits higher expression in a subject with cancer than in a subject with non-cancer.
  • the index microRNA is at least one of the group (GI).
  • the cancer can be endometrial cancer.
  • MicroRNA is a microRNA that exhibits higher expression in a subject with cancer than in a subject with non-cancer.
  • the index microRNA is at least one of the group (Hemo).
  • the cancer can be endometrial cancer.
  • MicroRNA is a microRNA that exhibits higher expression in a subject with cancer than in a subject with non-cancer.
  • the index microRNA is one or more of the group (Uro).
  • the cancer can be endometrial cancer.
  • MicroRNA is a microRNA that exhibits higher expression in a subject with cancer than in a subject with non-cancer.
  • the number of types of microRNA used as an index is 0 or more, 1 or more, 2 or more, 3 or more, 4 or more, 5 or more, 10 or more, 15 or more, 20 or more for each table. , 30 or more, 40 or more, 50 or more, 60 or more, 70 or more, 80 or more, 100 or more, 200 or more, 300 or more, 400 or more, 500 or more, 600 or more, 700 Species or more, 800 or more, 900 or more, 1000 or more, 2000 or more, 3000 or more, or all ⁇ however, at least one microRNA is used as an index in any one table ⁇ ..
  • the number of types of microRNA used as an index may be more than 50%, 60% or more and 70% or more, 80% or more, 90% or more, or all of the number of types of microRNA listed in each table. ..
  • the predetermined values are not particularly limited, but are, for example, the mean value, the median value, the third quartile value, the first quartile value, and the lowest value of the microRNA level in the target group having cancer. It can be any numerical value between two values (statistical or index values) selected from the group consisting of.
  • the predetermined value is not particularly limited, but is, for example, from the maximum value, the third quartile, the mean value, the median value, and the first child quantile value of the microRNA level in the non-cancer subject group. It can be any number between two values selected from the group of.
  • the predetermined value can be an arbitrary numerical value (for example, an intermediate value) between the average value in the control group having cancer and the average value in a healthy person.
  • the predetermined value can be the first threshold.
  • the first threshold is set for each target microRNA.
  • the predetermined value can be a second threshold.
  • the second threshold is set for each target microRNA.
  • the type of microRNA to be measured and / or the type of microRNA which is an index of the possibility of cancer is, for example, 1 or more, 2 or more, 3 or more, 4 5 or more, 6 or more, 7 or more, 8 or more, 9 or more, 10 or more, 20 or more, 30 or more, 40 or more, 50 or more, 60 or more, 70 or more, 80 or more, 90 or more, 100 or more, 200 or more, 300 or more, 400 or more, 500 or more, 600 or more, 700 or more, 800 or more, 900 or more, 1000 or more, 1100 or more, 1200 or more, 1300 or more, 1400 or more, 1500 or more, 1600 or more, 1700 or more, 1800 or more, 1900 or more , 2000 or more, 2100 or more, 2200 or more, 2300 or more, 2400 or more, or 2500 or more.
  • the type of microRNA to be measured and / or the type of microRNA that is an index of the possibility of cancer is, for example, 2500 or less, 2400 or less, 2300 or less, 2200 or less, 2100 or less.
  • microRNA as an indicator of cancer potential are as disclosed herein.
  • a microarray can be used for the measurement or detection of microRNA.
  • microRNA that showed lower expression in the cancerous subject than in the non-cancerous subject in any of the data S1 (or Table 3) or Tables 4-1 to 4-15.
  • the microRNA level of the body fluid sample of the subject is lower than a predetermined value as an index, it can be determined that the subject is likely to have cancer.
  • the microRNA level of the target body fluid sample is a predetermined value (hereinafter, "" It can be determined that the subject is likely to have cancer by using a value lower than the "threshold value") as an index. Also, for example, for microRNA that showed lower expression in the cancerous subject than in the non-cancerous subject in any of the data S1 (or Table 3) or Tables 4-1 to 4-15.
  • the microRNA level of the body fluid sample of the subject is higher than a predetermined value as an index, it can be determined that the subject is unlikely to have cancer.
  • the microRNA level of the target body fluid sample is a predetermined value (hereinafter, "" It can be determined that the subject is unlikely to have cancer by using a value higher than the "threshold value”) as an index.
  • the index microRNA is any one or more of Table 3.
  • the cancer can be lung cancer.
  • the cancer can be pancreatic cancer.
  • the cancer can be liver cancer.
  • the cancer can be bladder cancer.
  • the cancer can be prostate cancer.
  • MicroRNA is a microRNA that exhibits lower expression in a subject with cancer than in a subject without cancer.
  • the index microRNA is any one or more of Table 4-1.
  • the cancer can be lung cancer.
  • MicroRNA is a microRNA that exhibits lower expression in a subject with cancer than in a subject without cancer.
  • the index microRNA is any one or more of Table 4-2.
  • the cancer can be breast cancer.
  • MicroRNA is a microRNA that exhibits lower expression in a subject with cancer than in a subject without cancer.
  • the index microRNA is any one or more of Table 4-3.
  • the cancer can be kidney cancer.
  • MicroRNA is a microRNA that exhibits lower expression in a subject with cancer than in a subject without cancer.
  • the index microRNA is any one or more of Table 4-4.
  • the cancer can be leukemia.
  • MicroRNA is a microRNA that exhibits lower expression in a subject with cancer than in a subject without cancer.
  • the index microRNA is any one or more of Table 4-5.
  • the cancer can be lymphoma.
  • MicroRNA is a microRNA that exhibits lower expression in a subject with cancer than in a subject without cancer.
  • the index microRNA is any one or more of Table 4-6.
  • the cancer can be pancreatic cancer.
  • MicroRNA is a microRNA that exhibits lower expression in a subject with cancer than in a subject without cancer.
  • the index microRNA is any one or more of Table 4-7.
  • the cancer can be prostate cancer.
  • MicroRNA is a microRNA that exhibits lower expression in a subject with cancer than in a subject without cancer.
  • the index microRNA is any one or more of Table 4-8.
  • the cancer can be gastric cancer.
  • MicroRNAs are microRNAs that exhibit lower expression in non-cancerous subjects than in non-cancerous subjects.
  • the index microRNA is any one or more of Table 4-9.
  • the cancer can be a urothelial cancer.
  • MicroRNA is a microRNA that exhibits lower expression in a subject with cancer than in a subject without cancer.
  • the index microRNA is any one or more of Table 4-10.
  • the cancer can be melanoma.
  • MicroRNA is a microRNA that exhibits lower expression in a subject with cancer than in a subject without cancer.
  • the index microRNA is any one or more of Table 4-11.
  • the cancer can be ovarian cancer.
  • MicroRNA is a microRNA that exhibits lower expression in a subject with cancer than in a subject without cancer.
  • the index microRNA is any one or more of Table 4-12.
  • the cancer can be thyroid cancer.
  • MicroRNA is a microRNA that exhibits lower expression in a subject with cancer than in a subject without cancer.
  • the index microRNA is any one or more of Table 4-13.
  • the cancer can be cervical cancer.
  • MicroRNA is a microRNA that exhibits lower expression in a subject with cancer than in a subject without cancer.
  • the index microRNA is any one or more of Table 4-14.
  • the cancer can be rectal colon cancer.
  • MicroRNA is a microRNA that exhibits lower expression in a subject with cancer than in a subject without cancer.
  • the index microRNA is any one or more of Table 4-15.
  • the cancer can be endometrial cancer.
  • MicroRNA is a microRNA that exhibits lower expression in a subject with cancer than in a subject without cancer.
  • the index microRNA is a microRNA having a p-value of less than 0.005 from any of the tables 4-1 to 4-15.
  • MicroRNA is a microRNA that exhibits lower expression in a subject with cancer than in a subject without cancer.
  • the index microRNA is the microRNA listed in any of Tables 22-1 and 23-1-23-14.
  • MicroRNA is a microRNA that exhibits lower expression in a subject with cancer than in a subject without cancer.
  • the index microRNA is the microRNA set forth in any of Tables 24-1 to 24-15.
  • MicroRNA is a microRNA that exhibits lower expression in a subject with cancer than in a subject without cancer.
  • the index microRNA is the microRNA listed in any of Tables 25-1 to 25-15.
  • MicroRNA is a microRNA that exhibits lower expression in a subject with cancer than in a subject without cancer.
  • the index microRNA is at least one of the group (ALL).
  • the cancer can be endometrial cancer.
  • MicroRNA is a microRNA that exhibits lower expression in a subject with cancer than in a subject without cancer.
  • the index microRNA is at least one of the group (GI).
  • the cancer can be endometrial cancer.
  • MicroRNA is a microRNA that exhibits lower expression in a subject with cancer than in a subject without cancer.
  • the index microRNA is at least one of the group (Hemo).
  • the cancer can be endometrial cancer.
  • MicroRNA is a microRNA that exhibits lower expression in a subject with cancer than in a subject without cancer.
  • the index microRNA is one or more of the group (Uro).
  • the cancer can be endometrial cancer.
  • MicroRNA is a microRNA that exhibits lower expression in a subject with cancer than in a subject without cancer.
  • the number of types of microRNA used as an index is 0 or more, 1 or more, 2 or more, 3 or more, 4 or more, 5 or more, 10 or more, 15 or more, 20 or more for each table. , 30 or more, 40 or more, 50 or more, 60 or more, 70 or more, 80 or more, 100 or more, 200 or more, 300 or more, 400 or more, 500 or more, 600 or more, 700 Species or more, 800 or more, 900 or more, 1000 or more, 2000 or more, or 3000 or more, or all ⁇ provided that at least one microRNA is used as an index in at least one table ⁇ .
  • the number of types of microRNA used as an index may be more than 50%, 60% or more and 70% or more, 80% or more, 90% or more, or all of the number of types of microRNA listed in each table. ..
  • the predetermined values are not particularly limited, but are, for example, the mean value, the median value, the third quartile value, the first quartile value, and the lowest value of the microRNA level in the target group having cancer. It can be any number between two values selected from the group consisting of. Predetermined values can be determined for each type of cancer.
  • the predetermined value is not particularly limited, but is, for example, from the maximum value, the third quartile, the mean value, the median value, and the first child quantile value of the microRNA level in the non-cancer subject group. It can be any number between two values selected from the group of.
  • the present disclosure provides a method for testing a subject for possible lung cancer.
  • a method for examining the possibility that a subject has lung cancer is a subject using any one or more microRNA levels selected from data S1 (or Table 3) in the body fluid sample of the subject as an index.
  • miR-3117-5p, miR-3118, miR-3121-3p, miR-3121-5p, miR-3126-5p, miR-3128, miR-3133 in the body fluid sample of the subject.
  • miR-3134 miR-3136-3p, miR-3136-5p, miR-3139, miR-3142, miR-3143, miR-3145-3p, miR-3163, miR-3166, miR-3167, miR-16- 1-3p, miR-424-3p, miR-519c-5p, miR-525-5p, miR-551b-5p, miR-558, miR-921, miR-942-3p, miR-3126-3p, miR- 3127-5p, miR-3129-5p, miR-3144-5p, miR-3150a-5p, miR-3152-5p, miR-3155a, miR-3157-3p, miR-3159, miR-3165, miR-3678- 3p, miR-4321, miR-4521, miR-4800-3p, miR-4999-5p, miR-5096, miR-5187-5p, miR-6874-5p, miR-3127-3p, miR-3130-5p, miR-3131, miR-3141
  • the present disclosure also consists of a group consisting of miR-3163, miR-16-1--3p, miR-424-3p, miR-558, miR-3127-5p, and miR-4521 in a target body fluid sample.
  • the subject may be tested for lung cancer.
  • microRNA levels are above a given value, it can be determined that the subject may have lung cancer (and / or if it is lower than a given value, the subject may not have lung cancer. Can be determined to have).
  • the subject may have lung cancer (and / or if it is higher than a given value, the subject may be determined not to have lung cancer).
  • the microRNAs in urine which are indicators of lung cancer, are miR-3127-3p, miR-3130-5p, miR-3131, miR-3141, miR-3150b-5p, miR-3151-3p. , MiR-3151-5p, miR-3154, miR-3160-3p, and miR-3160-5p, which may be at least one or all selected from the group.
  • microRNAs in urine which are indicators of lung cancer, are miR-3117-5p, miR-3118, miR-3121-3p, miR-3121-5p, miR-3126-5p, miR-3128, miR-3133, miR-3134, miR-3136-3p, miR-3136-5p, miR-3139, miR-3142, miR-3143, miR-3145-3p, miR-3163, miR-3166, and miR-3167 It can be at least one or all selected from the group consisting of.
  • the present disclosure provides a method for testing the subject for possible pancreatic cancer.
  • a method for testing the possibility of a subject having pancreatic cancer uses any one or more microRNA levels selected from data S1 (or Table 3) in the subject's body fluid sample as an index.
  • the subject can be tested for possible pancreatic cancer.
  • the level of at least one or all microRNAs selected from the group consisting of miR-183-5p, miR-202-5p, and miR-409-5p in the body fluid sample of interest is also indexed.
  • the possibility of pancreatic cancer can be examined. If the level of at least one or all of the microRNAs selected from the group consisting of miR-183-5p, miR-202-5p, and miR-409-5p in the body fluid sample is higher than a predetermined value, the subject concerned. Can be determined to have a possibility of pancreatic cancer (and / or if low, it can be determined that the subject may not have pancreatic cancer).
  • the level of at least one or all microRNAs selected from the group consisting of -506-3p, miR-520c-3p, miR-1284, miR-1323, and miR-4273 is lower than a predetermined value, the subject concerned. Can be determined to have the potential for pancreatic cancer (and / or, if high, the subject may be determined to have non-pancreatic cancer).
  • the microRNAs in urine which are indicators of pancreatic cancer, are miR-372-3p, miR-378b, miR-520b, miR-1266-3p, miR-3605-5p, miR-3612. , MiR-4645-3p, miR-4649-3p, miR-4752, miR-6816-3p, and at least one or all selected from the group consisting of miR-8087.
  • the present disclosure provides a method for testing the subject for possible liver cancer.
  • a method of testing the subject for possible liver cancer is indexed by any one or more microRNA levels selected from data S1 (or Table 3) in the subject's body fluid sample. The subject can be tested for possible liver cancer.
  • the subject is liver cancer
  • the level of miR-520c-3p in the body fluid sample is lower than a predetermined value, it can be determined that the subject has the possibility of liver cancer (and / or if it is higher, the subject has liver. It can be determined that it may not be cancer).
  • the microRNA in urine which is an indicator of liver cancer, can be miR-4521.
  • the present disclosure provides a method for testing a subject for possible bladder cancer.
  • a method for testing a subject for possible bladder cancer is indexed by any one or more microRNA levels selected from data S1 (or Table 3) in the subject's body fluid sample. The subject can be tested for possible bladder cancer.
  • the subject can be tested for possible bladder cancer.
  • the group consists of miR-16-1--3p, miR-23b-3p, miR-28-5p, miR-142-3p, miR-195-3p, miR-299-3p, and miR-4295.
  • the potential of a subject to have bladder cancer can be tested using at least one or all of the selected microRNA levels as indicators.
  • the subject is likely to have bladder cancer (and / or if lower, the subject has a bladder. It can be determined that it may not be).
  • the possibility that the subject has bladder cancer can be examined using the miR-520c-3p level as an index. If the miR-520c-3p level in the body fluid sample is lower than a predetermined value, it can be determined that the subject may have bladder cancer (and / or if it is higher, the subject is not bladder cancer). Can be determined to have potential).
  • the present disclosure provides a method for testing a subject for possible prostate cancer.
  • a method of testing a subject for prostatic cancer is indexed by any one or more microRNA levels selected from data S1 (or Table 3) in the subject's body fluid sample. The subject can be tested for possible prostate cancer.
  • the subject may have prostate cancer using at least one or all microRNA levels selected from the group consisting of miR-135b-5p, miR-520c-3p, miR-4783-5p, and miR-7849-3p as indicators.
  • Sex can be tested.
  • at least one or all microRNA levels selected from the group consisting of miR-28-5p, miR-105-5p, miR-124-3p, miR-151a-5p, and miR-300 are indexed.
  • the subject can be tested for possible prostate cancer.
  • at least one or all microRNA levels selected from the group consisting of miR-28-5p, miR-105-5p, miR-124-3p, miR-151a-5p, and miR-300 If it is higher than a predetermined value, it can be determined that the subject may have prostate cancer (and / or if it is lower, it may be determined that the subject may not have prostate cancer).
  • the possibility of a subject having liver cancer can be examined using at least one or all microRNA levels selected from the group consisting of miR-15a-3p and miR-520c-3p as indicators. If at least one or all of the microRNA levels selected from the group consisting of miR-15a-3p and miR-520c-3p in the body fluid sample are lower than a predetermined value, the subject may have prostate cancer. (And / or, if high, it can be determined that the subject may not have prostate cancer). Also according to the present disclosure, the microRNA in urine that is an indicator of prostate cancer can be miR-4531.
  • the microRNA level of the body fluid sample of the subject is a predetermined value. It can be determined that the target is likely to have cancer by using a value lower than (hereinafter, sometimes referred to as “threshold value”) as an index. Further, for example, in Tables 4-1 to 4-15, for microRNA showing lower expression in a subject with cancer than in a subject without cancer, the microRNA level of the body fluid sample of the subject is a predetermined value. It can be determined that the subject is unlikely to have cancer by using the higher value as an index.
  • the predetermined value is not particularly limited, but is selected from, for example, a group consisting of the average value, the median value, the third quartile value, the first quartile value, and the lowest value of the microRNA level in the target group having cancer. It can be any number between the two values that are made. Further, for example, the predetermined value is not particularly limited, but is, for example, from the maximum value, the third quartile, the mean value, the median value, and the first child quantile value of the microRNA level in the non-cancer subject group. It can be any number between two values selected from the group of. In addition, the predetermined value can be an arbitrary numerical value (for example, an intermediate value) between the average value in the control group having cancer and the average value in a healthy person.
  • the present disclosure provides a method for testing a subject for possible lung cancer.
  • a method for examining the possibility that a subject has lung cancer is that the subject has lung cancer using any one or more microRNA levels selected from Table 4-1 in the body fluid sample of the subject as an index. You can check for certain possibilities.
  • Species, 5, 6, 7, 8, 9, 9, 10 or more, 15 or more, or 20 or more microRNA levels or all microRNA levels may be used as an index for the subject to be lung cancer. Can be inspected.
  • microRNA levels are higher than a given value, it can be determined that the subject may have lung cancer (and / or if it is lower than a given value, the subject may not have lung cancer. Can be determined to have).
  • hsa-miR-4768-3p, hsa-miR-1265, hsa-miR-4321, hsa-miR-4423-5p, hsa-miR-1294, and hsa also in the body fluid sample of interest.
  • the subject may be lung cancer using at least one, two, three, four, or five or more microRNA levels selected from the group consisting of ⁇ miR-4520-3p or all microRNA levels as an index. Sex can be tested.
  • the present disclosure provides a method for testing a subject for possible lung cancer.
  • a method for examining the possibility that a subject has lung cancer is that the subject has lung cancer using any one or more microRNA levels selected from Table 4-1 in the body fluid sample of the subject as an index. You can check for certain possibilities.
  • hsa-miR-147b hsa-miR-3912-5p, hsa-miR-148a-5p, hsa-miR-6773-5p, hsa-miR-3681- in the body fluid sample of the subject.
  • a method for detecting microRNA in a subject's body fluid comprises detecting microRNA or all microRNA by contacting a body fluid sample obtained from a subject with a detection agent for the detected microRNA: hsa-miR-103a-2.
  • the agent for detecting microRNA may be a nucleic acid having a sequence complementary to the microRNA, such as a probe having a sequence complementary to the microRNA and a primer having a sequence complementary to the microRNA. It can be determined that if the expression of microRNA is high, it is likely to be cancer, and if it is low, it is unlikely to be cancer. The magnitude of the expression of microRNA can be determined based on a predetermined value.
  • the plurality of microRNA levels are compared with a predetermined value, respectively.
  • the score obtained by weighting multiple microRNA levels may be compared to a predetermined value obtained by similarly weighting.
  • the number of microRNAs suggesting that they may be cancer is compared to the number of microRNAs suggesting that they may not be cancer. You can decide if you are likely to have it or if you are not likely to have cancer.
  • each microRNA level is normalized and then weighted.
  • normalized numbers can be added or multiplied to score (eg, a Z-score can be obtained).
  • the microRNA score thus obtained may be cancerous in contrast to a similarly obtained predetermined value (ie, a score similarly obtained from a cancer patient or non-cancer subject, etc.). Can be determined whether it is high or likely not to have cancer.
  • the weighting can be positive for a large amount of body fluid sample of a cancer target and negative for a small amount (or vice versa) as compared with a body fluid sample of a non-cancer target.
  • Weighting can also be done by multiplying those with a large difference or correlation between cancerous and non-cancerous subjects by a larger number.
  • multiple microRNA levels are predicted using predictive models such as logistic regression when examining the likelihood that the subject is cancer or a particular cancer using multiple microRNAs as indicators. You may.
  • the machine-learned computer or artificial intelligence may determine the presence or absence of a disease, identify the disease, or calculate the probability of developing the disease from the level of one or more microRNAs.
  • machine learning or artificial intelligence for example, one or more microRNA levels are trained in association with determining the presence or absence of a disease, identifying a disease, and the probability of developing the disease, thereby causing machine (computer) or artificial intelligence (AI). Can be learned.
  • Seeds 4 kinds, Relationship data between 5 types, 6 types, 7 types, 8 types, 9 types, 10 types or more, 15 types or more, or 20 types or more, or all microRNAs and cancer (vii) hsa-let- 7e-5p, hsa-let-7f-2-3p, hsa-let-7g-3p, hsa-miR-103a-3p, hsa-miR-106b-5p, hsa-miR-107, hsa-miR-10a- 5p, hsa-miR-10b-5p, hsa-miR-1180-5p, hsa-miR-1183, hsa-miR-1200, hsa-miR-1205, hsa-miR-122-3p, hsa-miR-1247- 3p, hsa-miR-1257, hsa-miR-1263, hsa-miR
  • microRNAs 15 or more, or 20 or more microRNAs, or association data of the expression level of all microRNAs with cancer; selected from the group consisting of microRNAs p ⁇ 0.005 or less in Table 4-2.
  • data on the association between the expression levels of 20 or more types of microRNA or all microRNAs and cancer at least one selected from the group consisting of microRNAs having p ⁇ 0.005 or less in Table 4-3. 2, 3 types, 4 types, 5 types, 6 types, 7 types, 8 types, 9 types, 10 types or more, 15 types or more, or 20 types or more of microRNA or the expression level of all microRNAs. Relevance data; at least 1 type, 2 types, 3 types, 4 types, 5 types, 6 types, 7 types, 8 types, 9 types selected from the group consisting of microRNAs shown in Table 22-3.
  • cancer association data at least 1 type, 2 types, 3 types, 4 types, 5 types, 6 types, 7 types, 8 types, selected from the group consisting of microRNAs shown in Table 24-3.
  • RNA expression level and association data with cancer At least 1 type, 2 types, 3 types, 4 types, 5 types, 6 types, 7 types, 8 types, 9 types, 10 types or more, 15 types or more, or 20 types or more of microRNAs or all micros to be selected.
  • RNA expression level and association data with cancer At least 1 type, 2 types, 3 types, 4 types, 5 types, 6 types, 7 types, 8 types, 9 types, 10 types or more, 15 types or more, selected from the group consisting of Table 4-4.
  • data on the association between the expression levels of 20 or more types of microRNA or all microRNAs and cancer at least one selected from the group consisting of microRNAs having p ⁇ 0.005 or less in Table 4-4. 2, 3 types, 4 types, 5 types, 6 types, 7 types, 8 types, 9 types, 10 types or more, 15 types or more, or 20 types or more of microRNA or the expression level of all microRNAs. Relevance data; at least 1 type, 2 types, 3 types, 4 types, 5 types, 6 types, 7 types, 8 types, 9 types selected from the group consisting of microRNAs shown in Table 24-4.
  • microRNAs or all microRNAs and cancer Data on the association between the expression level of 10 or more, 15 or more, or 20 or more microRNAs or all microRNAs and cancer; or selected from the group consisting of microRNAs shown in Table 25-4. At least 1 type, 2 types, 3 types, 4 types, 5 types, 6 types, 7 types, 8 types, 9 types, 10 types or more, 15 types or more, or 20 types or more of microRNA or all microRNAs. Relationship data between expression level and cancer; (Xi) At least 1 type, 2 types, 3 types, 4 types, 5 types, 6 types, 7 types, 8 types, 9 types, 10 types or more selected from the group consisting of microRNAs shown in Table 4-5.
  • microRNAs 15 or more, or 20 or more microRNAs, or association data of the expression level of all microRNAs with cancer; selected from the group consisting of microRNAs p ⁇ 0.005 or less in Table 4-5.
  • microRNAs or the relationship data between the expression levels of all microRNAs and cancer;
  • Xii At least 1 type, 2 types, 3 types, 4 types, 5 types, 6 types, 7 types, 8 types, 9 types, 10 types or more selected from the group consisting of microRNAs shown in Table 4-6. , 15 or more, or 20 or more microRNAs, or association data of the expression level of all microRNAs with cancer; selected from the group consisting of microRNAs p ⁇ 0.005 or less in Table 4-6.
  • At least 1 type, 2 types, 3 types, 4 types, 5 types, 6 types, 7 types, 8 types, 9 types, 10 types or more, 15 types or more, or 20 types or more of microRNA or all microRNAs Relationship data between expression level and cancer; at least 1 type, 2 types, 3 types, and 4 types selected from the group consisting of microRNAs shown in Tables 22-1 to 22-13 in the group (ALL). Relationship data between the expression levels of 5, 6, 7, 8, 9, 9, 10 or more, 15 or more, or 20 or more microRNAs or all microRNAs and cancer; group ( ALL) at least 1 type, 2 types, 3 types, 4 types, 5 types, 6 types, 7 types selected from the group consisting of microRNAs shown in Tables 22-1 and 23-1 to 23-14.
  • microRNAs or association data of the expression level of all microRNAs with cancer At least 1 type, 2 types, 3 types, 4 types, 5 types, 6 types, 7 types, 8 types, 9 types, 10 types or more, 15 types or more selected from the group consisting of the microRNAs described in 24-15.
  • RNA expression level and association data with cancer At least 1 type, 2 types, 3 types, 4 types, 5 types, 6 types, 7 types, 8 types, 9 types, 10 types or more, 15 types or more, or 20 types or more of microRNAs or all micros to be selected.
  • RNA expression level and association data with cancer At least 1 type, 2 types, 3 types, 4 types, 5 types, 6 types, 7 types, 8 types, 9 types, 10 types or more selected from the group consisting of microRNAs described in the (xxiii) group (GI). , 15 or more, or 20 or more microRNAs, or association data of the expression level of all microRNAs with cancer; selected from the group consisting of microRNAs p ⁇ 0.005 or less in the group (GI).
  • At least 1 type, 2 types, 3 types, 4 types, 5 types, 6 types, 7 types, 8 types, 9 types, 10 types or more, 15 types or more, or 20 types or more of microRNA or all microRNAs Relationship data between expression level and cancer; at least 1 type, 2 types, 3 types, and 4 types selected from the group consisting of microRNAs shown in Tables 22-1 to 22-13 in the group (GI). Relationship data between the expression levels of 5, 6, 7, 8, 9, 9, 10 or more, 15 or more, or 20 or more microRNAs or all microRNAs and cancer; group ( At least 1 type, 2 types, 3 types, 4 types, 5 types, 6 types, and 7 types selected from the group consisting of microRNAs shown in Tables 22-1 and 23-1 to 23-14 of GI).
  • Tables 24-1-1 of the group (GI) At least 1 type, 2 types, 3 types, 4 types, 5 types, 6 types, 7 types, 8 types, 9 types, 10 types or more, 15 types or more selected from the group consisting of the microRNAs described in 24-15. , Or the association data between the expression levels of 20 or more types of microRNA or all microRNAs and cancer; or from the group consisting of microRNAs shown in Tables 25-1 to 25-15 of the group (GI).
  • RNA expression level and association data with cancer At least 1 type, 2 types, 3 types, 4 types, 5 types, 6 types, 7 types, 8 types, 9 types, 10 types or more, 15 types or more, or 20 types or more of microRNAs or all micros to be selected.
  • RNA expression level and association data with cancer At least 1 type, 2 types, 3 types, 4 types, 5 types, 6 types, 7 types, 8 types, 9 types, 10 types or more selected from the group consisting of microRNAs described in the (xxx) group (Hemo). , 15 or more, or 20 or more microRNAs, or association data of the expression level of all microRNAs with cancer; selected from the group consisting of microRNAs p ⁇ 0.005 or less in the group (Hemo).
  • At least 1 type, 2 types, 3 types, 4 types, 5 types, 6 types, 7 types, 8 types, 9 types, 10 types or more, 15 types or more, or 20 types or more of microRNA or all microRNAs Relationship data between expression level and cancer; at least 1 type, 2 types, 3 types, and 4 types selected from the group consisting of microRNAs shown in Tables 22-1 to 22-13 in the group (Hemo). Relationship data between the expression levels of 5, 6, 7, 8, 9, 9, 10 or more, 15 or more, or 20 or more microRNAs or all microRNAs and cancer; group ( Hemo), at least 1 type, 2 types, 3 types, 4 types, 5 types, 6 types, 7 types selected from the group consisting of microRNAs shown in Tables 22-1 and 23-1 to 23-14.
  • Tables 24-1-1 of the group (Hemo) At least 1 type, 2 types, 3 types, 4 types, 5 types, 6 types, 7 types, 8 types, 9 types, 10 types or more, 15 types or more selected from the group consisting of the microRNAs described in 24-15. , Or the association data between the expression levels of 20 or more types of microRNA or all microRNAs and cancer; or from the group consisting of microRNAs shown in Tables 25-1 to 25-15 of the group (Hemo).
  • RNA expression level and association data with cancer At least 1 type, 2 types, 3 types, 4 types, 5 types, 6 types, 7 types, 8 types, 9 types, 10 types or more, 15 types or more, or 20 types or more of microRNAs or all micros to be selected.
  • RNA expression level and association data with cancer At least 1 type, 2 types, 3 types, 4 types, 5 types, 6 types, 7 types, 8 types, 9 types, 10 types or more selected from the group consisting of microRNAs described in the (xxv) group (Uro). , 15 or more, or 20 or more microRNAs, or association data of the expression level of all microRNAs with cancer; selected from the group consisting of microRNAs p ⁇ 0.005 or less in the group (Uro).
  • At least 1 type, 2 types, 3 types, 4 types, 5 types, 6 types, 7 types, 8 types, 9 types, 10 types or more, 15 types or more, or 20 types or more of microRNA or all microRNAs Relationship data between expression level and cancer; at least 1 type, 2 types, 3 types, and 4 types selected from the group consisting of microRNAs shown in Tables 22-1 to 22-13 in the group (Uro). Relationship data between the expression levels of 5, 6, 7, 8, 9, 9, 10 or more, 15 or more, or 20 or more microRNAs or all microRNAs and cancer; group ( Of Uro), at least 1 type, 2 types, 3 types, 4 types, 5 types, 6 types, and 7 types selected from the group consisting of microRNAs shown in Tables 22-1 and 23-1 to 23-14.
  • microRNAs or association data of the expression level of all microRNAs with cancer At least 1 type, 2 types, 3 types, 4 types, 5 types, 6 types, 7 types, 8 types, 9 types, 10 types or more, 15 types or more selected from the group consisting of the microRNAs described in 24-15.
  • association data between the expression levels of 20 or more types of microRNA or all microRNAs and cancer or from the group consisting of microRNAs shown in Tables 25-1 to 25-15 of the group (Uro).
  • the learned computer or artificial intelligence is a memory (ROM, RAM, hard disk, magnetic recording medium such as SSD, or the like, and the magnetic) in which one or more data selected from the group consisting of the above (i) to (v) is recorded. It may include a computer including a recording medium) or may be connected to the memory via an electronic communication circuit.
  • the learned computer or artificial intelligence can be further learned by one or more data selected from the group consisting of (i) to (v) above ⁇ in this case, the data used for learning is further added to the memory. May be ⁇ .
  • the learned computer or artificial intelligence can be used to determine the relationship data between the expression level of at least one or all of the microRNAs and cancer, and the expression level of at least one or all of the microRNAs in the body fluid sample of the subject. Based on, the possibility that the subject has cancer can be determined.
  • Computer or artificial intelligence learning with the relevance data uses one or more of the relevance data as teacher data to evaluate the non-evaluated data, eg, the sensitivity and / or specificity of cancer detection. This can be done by repeatedly learning different relevance data until the value exceeds a predetermined value.
  • the predetermined value may vary depending on the sensitivity and / or specificity requirements, for example, 10%, 20%, 30%, 40%, 50%, 60%, 70%, 80%, or 90% or more. can do.
  • increasing sensitivity increases false positives, and decreasing sensitivity increases false negatives. Therefore, the sensitivity is preferably set according to the purpose of the inspection.
  • increasing the specificity increases false negatives, and decreasing sensitivity increases false positives. Therefore, it is desirable to set the specificity according to the purpose of the test.
  • data indicating that the patient may have cancer and / or may not have cancer is transmitted to a medium such as an electronic medium or paper.
  • a medium such as an electronic medium or paper.
  • the output data may be presented to the physician and / or patient (or their family, relatives, etc.) to consider subsequent treatment plans and subsequent further work-up (eg,). , Can be used for inspection selection).
  • anticancer treatments such as chemotherapy, radiation therapy, and surgery (eg, anticancer treatments for specific cancers that are determined to have). Can be treated.
  • microRNA in a subject's urine or urine extract is a method for detecting microRNA in a subject's urine or urine extract.
  • data S1 or Table 3
  • the microRNA detected in this embodiment is, for example, a microRNA showing higher expression in a subject with cancer than in a non-cancer subject (eg, 2-fold or more, 3-fold or more, 4- or more, 5 or more, 6 or more , 7 or more, 8 or more, 9 or more, or 10 or more).
  • microRNAs include miR-3117-5p, miR-3118, miR-3121-3p, miR-3121-5p, miR-3126-5p, miR-3128, miR-3133, miR-3134, and the like. miR-3136-3p, miR-3136-5p, miR-3139, miR-3142, miR-3143, miR-3145-3p, miR-3163, miR-3166, miR-3167, miR-0558, miR-3126- 3p, miR-3129-5p, miR-3144-5p, miR-3150a-5p, miR-3152-5p, miR-3157-3p, miR-3159, miR-4521, miR-0029b-3p, miR-0030b- 3p, miR-0106b-3p, miR-0320c, miR-0494-3p, miR-0566, miR-0572, miR-0645, miR-0939-3p, miR-0943, miR-1972, miR-3129-3
  • a method of detecting microRNA in a subject's urine or urine extract is, for example, a method of detecting one or more selected from a group of microRNAs showing lower expression in 3 subjects with cancer than any of the 3 subjects without cancer. Will be done.
  • the microRNA detected in this embodiment is, for example, a microRNA having a lower expression than any of the three non-cancer subjects in the three cancer subjects (for example, two-fold or more, three-fold or more, four or more). It can be one or more from the group of microRNAs (5 or more, 6 or more, 7 or more, 8 or more, 9 or more, or 10 or more).
  • microRNAs examples include miR-3127-3p, miR-3130-5p, miR-3131, miR-3141, miR-3150b-5p, miR-3151-3p, miR-3151-5p, miR-. 3154, miR-3160-3p, miR-3160-5p, miR-3162-5p, miR-0015b-5p, miR-0034c-5p, miR-0093-5p, miR-0128-2-5p, miR-0135a- 5p, miR-0149-3p, miR-0214-5p, miR-0320a, miR-0339-5p, miR-0365a-5p, miR-0372-3p, miR-0378b, miR-0424-5p, miR-0488- 5p, miR-0998, miR-0512-3p, miR-0512-5p, miR-0580-3p, miR-0670-5p, miR-0671-5p, miR-0758-5p, miR-0933, miRNA
  • the types of microRNA detected and the types of microRNA used as indicators are independently, for example, 1 or more, 2 or more, 3 or more, 4 or more, 5 or more, 6 or more, 7 or more. , 8 or more, 9 or more, 10 or more, 20 or more, 30 or more, 40 or more, 50 or more, 60 or more, 70 or more, 80 or more, 90 or more, 100 or more, 200 or more, 300 or more, 400 or more, 500 or more, 600 700 or more, 800 or more, 900 or more, 1000 or more, 1100 or more, 1200 or more, 1300 or more, 1400 or more, 1500 or more, 1600 or more, 1700 or more, 1800 or more, 1900 or more, 2000 or more, 2100 or more, 2200 or more, It can be 2300 or more, 2400 or more, or 2500 or more.
  • the types of microRNA detected and the types of microRNA used as indicators are independently, for example, 2500 or less, 2400 or less, 2300 or less, 2200 or less, 2100 or less, 2000 or less, 1900 or less. 1800 or less, 1700 or less, 1600 or less, 1500 or less, 1400 or less, 1300 or less, 1200 or less, 1100 or less, 1000 or less, 900 or less, 800 or less, 700 or less, 600 or less, 500 or less, 400 or less, 300 or less, 200 Below, it can be 100 or less, 90 or less, 80 or less, 70 or less, 60 or less, 50 or less, 40 or less, 30 or less, 20 or less, or 10 or less.
  • the type of microRNA detected and the type of microRNA used as an index can be exactly the same, or a portion of the detected microRNA can be used as an index.
  • cancer can be diagnosed as described in the present disclosure using the expression level and presence / absence of the microRNA as an index.
  • Treatments eg, cancer therapies such as chemotherapy, anticancer drug therapy, surgery, immunotherapy, and radiation therapy
  • cancer therapies such as chemotherapy, anticancer drug therapy, surgery, immunotherapy, and radiation therapy
  • MicroRNA is selected from the group consisting of microRNAs shown in (ia) Table 4-2. At least 1 type, 2 types, 3 types, 4 types, 5 types, 6 types, 7 types, 8 types, 9 types. Species, 10 or more, 15 or more, or 20 or more microRNAs or all microRNAs; at least one selected from the group consisting of microRNAs having p ⁇ 0.005 or less in Table 4-2. 2 types, 3 types, 4 types, 5 types, 6 types, 7 types, 8 types, 9 types, 10 types or more, 15 types or more, or 20 types or more of microRNAs or all microRNAs; Table 22-2.
  • RNA or all microRNA At least 1 type, 2 types, 3 types, 4 types, 5 types, 6 types, 7 types, 8 types, 9 types, 10 types or more, 15 types or more, or 20 types or more micros selected from the group consisting of RNA.
  • RNA or all microRNA the subject may be a subject of breast cancer or a subject suspected of having breast cancer;
  • microRNA or all microRNAs at least 1 type, 2 types, 3 types, 4 types selected from the group consisting of microRNAs having p ⁇ 0.005 or less in Table 4-3. 5, 6, 7, 8, 9, 9, 10 or more, 15 or more, or 20 or more microRNAs or all microRNAs; from the group consisting of microRNAs shown in Table 22-3. At least 1 type, 2 types, 3 types, 4 types, 5 types, 6 types, 7 types, 8 types, 9 types, 10 types or more, 15 types or more, or 20 types or more of microRNAs or all micros to be selected.
  • RNA at least 1 type, 2 types, 3 types, 4 types, 5 types, 6 types, 7 types, 8 types, 9 types, 10 types or more, selected from the group consisting of microRNAs shown in Table 23-3. 15 or more, or 20 or more microRNAs or all microRNAs; at least 1 type, 2 types, 3 types, 4 types, 5 types, 6 selected from the group consisting of the microRNAs shown in Table 24-3. Species, 7, 8, 9, 10 or more, 15 or more, or 20 or more microRNAs or all microRNAs; or selected from the group consisting of microRNAs listed in Table 25-3.
  • the subject may be a subject of kidney cancer or a subject suspected of having kidney cancer;
  • microRNAs or all microRNAs from the group consisting of microRNAs shown in Table 24-4. At least 1 type, 2 types, 3 types, 4 types, 5 types, 6 types, 7 types, 8 types, 9 types, 10 types or more, 15 types or more, or 20 types or more of microRNAs or all micros to be selected. RNA; or at least 1 type, 2 types, 3 types, 4 types, 5 types, 6 types, 7 types, 8 types, 9 types, 10 types selected from the group consisting of microRNAs shown in Table 25-4.
  • the subject may be a subject of leukemia or a subject suspected of having leukemia;
  • RNA or all microRNAs At least 1 type, 2 types, 3 types, 4 types, 5 types, 6 types, 7 types, 8 types, 9 types, 10 types or more, 15 types or more, or 20 types or more of microRNAs or all microRNAs; At least 1 type, 2 types, 3 types, 4 types, 5 types, 6 types, 7 types, 8 types, 9 types, 10 types or more, 15 types or more, or 20 types or more micros selected from the group consisting of RNA. RNA or all microRNAs; at least 1 type, 2 types, 3 types, 4 types, 5 types, 6 types, 7 types, 8 types, 9 types selected from the group consisting of microRNAs shown in Table 24-5.
  • microRNAs or all microRNAs or at least one, two, or three selected from the group consisting of microRNAs listed in Table 25-5. 4 types, 5 types, 6 types, 7 types, 8 types, 9 types, 10 types or more, 15 types or more, or 20 types or more of microRNA or all microRNAs;
  • the subject may be a subject with lymphoma or a subject suspected of having lymphoma;
  • Va At least 1 type, 2 types, 3 types, 4 types, 5 types, 6 types, 7 types, 8 types, 9 types, 10 types selected from the group consisting of microRNAs shown in Table 4-6.
  • RNA or all microRNAs at least 1 type, 2 types, 3 types, 4 types, 5 types, 6 types, 7 types, 8 types, 9 types selected from the group consisting of microRNAs shown in Table 23-5. 10 or more, 15 or more, or 20 or more microRNAs or all microRNAs; at least 1 type, 2 types, 3 types, 4 types selected from the group consisting of microRNAs shown in Table 24-6. It consists of 5, 6, 7, 8, 9, 9, 10 or more, 15 or more, or 20 or more microRNAs or all microRNAs; or the microRNAs shown in Table 25-6.
  • the subject may be a subject with pancreatic cancer or a subject suspected of having pancreatic cancer;
  • RNA or all microRNAs At least 1 type, 2 types, 3 types, 4 types, 5 types, 6 types, 7 types, 8 types, 9 types, 10 types or more, 15 types or more, or 20 types or more of microRNAs or all microRNAs; At least 1 type, 2 types, 3 types, 4 types, 5 types, 6 types, 7 types, 8 types, 9 types, 10 types or more, 15 types or more, or 20 types or more micros selected from the group consisting of RNA. RNA or all microRNAs; at least 1 type, 2 types, 3 types, 4 types, 5 types, 6 types, 7 types, 8 types, 9 types selected from the group consisting of microRNAs shown in Table 23-6.
  • microRNAs or all microRNAs 10 or more, 15 or more, or 20 or more microRNAs or all microRNAs; at least 1 type, 2 types, 3 types, 4 types selected from the group consisting of microRNAs shown in Table 24-7. It consists of 5, 6, 7, 8, 9, 9, 10 or more, 15 or more, or 20 or more microRNAs or all microRNAs; or the microRNAs listed in Table 25-7.
  • the subject may be a subject with prostate cancer or a subject suspected of having prostate cancer;
  • RNA or all microRNAs At least 1 type, 2 types, 3 types, 4 types, 5 types, 6 types, 7 types, 8 types, 9 types, 10 types or more, 15 types or more, or 20 types or more of microRNAs or all microRNAs; At least 1 type, 2 types, 3 types, 4 types, 5 types, 6 types, 7 types, 8 types, 9 types, 10 types or more, 15 types or more, or 20 types or more micros selected from the group consisting of RNA. RNA or all microRNAs; at least 1 type, 2 types, 3 types, 4 types, 5 types, 6 types, 7 types, 8 types, 9 types selected from the group consisting of microRNAs shown in Table 23-7.
  • microRNAs or all microRNAs 10 or more, 15 or more, or 20 or more microRNAs or all microRNAs; at least 1 type, 2 types, 3 types, 4 types selected from the group consisting of microRNAs shown in Table 24-8. It consists of 5, 6, 7, 8, 9, 9, 10 or more, 15 or more, or 20 or more microRNAs or all microRNAs; or the microRNAs shown in Table 25-8.
  • the subject may be a subject with gastric cancer or a subject suspected of having gastric cancer;
  • RNA or all microRNAs At least 1 type, 2 types, 3 types, 4 types, 5 types, 6 types, 7 types, 8 types, 9 types, 10 types or more, 15 types or more, or 20 types or more of microRNAs or all microRNAs; At least 1 type, 2 types, 3 types, 4 types, 5 types, 6 types, 7 types, 8 types, 9 types, 10 types or more, 15 types or more, or 20 types or more micros selected from the group consisting of RNA. RNA or all microRNAs; at least 1 type, 2 types, 3 types, 4 types, 5 types, 6 types, 7 types, 8 types, 9 types selected from the group consisting of microRNAs shown in Table 23-8.
  • microRNAs or all microRNAs 10 or more, 15 or more, or 20 or more microRNAs or all microRNAs; at least 1 type, 2 types, 3 types, 4 types selected from the group consisting of microRNAs shown in Table 24-9. It consists of 5, 6, 7, 8, 9, 9, 10 or more, 15 or more, or 20 or more microRNAs or all microRNAs; or the microRNAs listed in Table 25-9.
  • the subject may be a subject with urothelial cancer or a subject suspected of having urothelial cancer;
  • RNA or all microRNAs at least 1 type, 2 types, 3 types, 4 types, 5 types, 6 types, 7 types, 8 types, 9 types selected from the group consisting of microRNAs shown in Table 23-9. 10 or more, 15 or more, or 20 or more microRNAs or all microRNAs; at least 1 type, 2 types, 3 types, 4 types selected from the group consisting of microRNAs shown in Table 24-10. It consists of 5, 6, 7, 8, 9, 9, 10 or more, 15 or more, or 20 or more microRNAs or all microRNAs; or the microRNAs listed in Table 25-10.
  • the subject may be a subject of melanoma or a subject suspected of having melanoma;
  • RNA or all microRNAs At least 1 type, 2 types, 3 types, 4 types, 5 types, 6 types, 7 types, 8 types, 9 types, 10 types or more, 15 types or more, or 20 types or more of microRNAs or all microRNAs; At least 1 type, 2 types, 3 types, 4 types, 5 types, 6 types, 7 types, 8 types, 9 types, 10 types or more, 15 types or more, or 20 types or more micros selected from the group consisting of RNA. RNA or all microRNAs; at least 1 type, 2 types, 3 types, 4 types, 5 types, 6 types, 7 types, 8 types, 9 types selected from the group consisting of microRNAs shown in Table 23-10.
  • microRNAs or all microRNAs 10 or more, 15 or more, or 20 or more microRNAs or all microRNAs; at least 1 type, 2 types, 3 types, 4 types selected from the group consisting of microRNAs shown in Table 24-11. It consists of 5, 6, 7, 8, 9, 9, 10 or more, 15 or more, or 20 or more microRNAs or all microRNAs; or the microRNAs shown in Table 25-11.
  • the subject may be a subject with ovarian cancer or a subject suspected of having ovarian cancer;
  • RNA or all microRNAs At least 1 type, 2 types, 3 types, 4 types, 5 types, 6 types, 7 types, 8 types, 9 types, 10 types or more, 15 types or more, or 20 types or more of microRNAs or all microRNAs; At least 1 type, 2 types, 3 types, 4 types, 5 types, 6 types, 7 types, 8 types, 9 types, 10 types or more, 15 types or more, or 20 types or more micros selected from the group consisting of RNA. RNA or all microRNAs; at least 1 type, 2 types, 3 types, 4 types, 5 types, 6 types, 7 types, 8 types, 9 types selected from the group consisting of microRNAs shown in Table 23-11.
  • microRNAs or all microRNAs 10 or more, 15 or more, or 20 or more microRNAs or all microRNAs; at least 1 type, 2 types, 3 types, 4 types selected from the group consisting of microRNAs shown in Table 24-12. It consists of 5, 6, 7, 8, 9, 9, 10 or more, 15 or more, or 20 or more microRNAs or all microRNAs; or the microRNAs listed in Table 25-12.
  • the subject may be a subject with thyroid cancer or a subject suspected of having thyroid cancer;
  • RNA or all microRNAs At least 1 type, 2 types, 3 types, 4 types, 5 types, 6 types, 7 types, 8 types, 9 types, 10 types or more, 15 types or more, or 20 types or more of microRNAs or all microRNAs; At least 1 type, 2 types, 3 types, 4 types, 5 types, 6 types, 7 types, 8 types, 9 types, 10 types or more, 15 types or more, or 20 types or more micros selected from the group consisting of RNA. RNA or all microRNAs; at least 1 type, 2 types, 3 types, 4 types, 5 types, 6 types, 7 types, 8 types, 9 types selected from the group consisting of microRNAs shown in Table 23-12.
  • microRNAs or all microRNAs 10 or more, 15 or more, or 20 or more microRNAs or all microRNAs; at least 1 type, 2 types, 3 types, 4 types selected from the group consisting of microRNAs shown in Table 24-13. It consists of 5, 6, 7, 8, 9, 9, 10 or more, 15 or more, or 20 or more microRNAs or all microRNAs; or the microRNAs listed in Table 25-13.
  • the subject may be a subject with thyroid cancer or a subject suspected of having thyroid cancer;
  • RNA or all microRNAs At least 1 type, 2 types, 3 types, 4 types, 5 types, 6 types, 7 types, 8 types, 9 types, 10 types or more, 15 types or more, or 20 types or more of microRNAs or all microRNAs; At least 1 type, 2 types, 3 types, 4 types, 5 types, 6 types, 7 types, 8 types, 9 types, 10 types or more, 15 types or more, or 20 types or more micros selected from the group consisting of RNA. RNA or all microRNAs; at least 1 type, 2 types, 3 types, 4 types, 5 types, 6 types, 7 types, 8 types, 9 types selected from the group consisting of microRNAs shown in Table 23-13.
  • microRNAs or all microRNAs 10 or more, 15 or more, or 20 or more microRNAs or all microRNAs; at least 1 type, 2 types, 3 types, 4 types selected from the group consisting of microRNAs shown in Table 24-14. It consists of 5, 6, 7, 8, 9, 9, 10 or more, 15 or more, or 20 or more microRNAs or all microRNAs; or the microRNAs shown in Table 25-14.
  • the microRNA can be selected from the group consisting of microRNAs that show higher expression in the cancerous subject than in the non-cancerous subject. Also in this embodiment, the microRNA can be selected from the group consisting of microRNAs that showed lower expression in the cancerous subject than in the non-cancerous subject.
  • the types of microRNA detected and the types of microRNA used as indicators are independently, for example, 1 or more, 2 or more, 3 or more, 4 or more, 5 or more, 6 or more, 7 or more. , 8 or more, 9 or more, 10 or more, 20 or more, 30 or more, 40 or more, 50 or more, 60 or more, 70 or more, 80 or more, 90 or more, 100 or more, 200 or more, 300 or more, 400 or more, 500 or more, 600 700 or more, 800 or more, 900 or more, 1000 or more, 1100 or more, 1200 or more, 1300 or more, 1400 or more, 1500 or more, 1600 or more, 1700 or more, 1800 or more, 1900 or more, 2000 or more, 2100 or more, 2200 or more, It can be 2300 or more, 2400 or more, or 2500 or more.
  • the types of microRNA detected and the types of microRNA used as indicators are independently, for example, 2500 or less, 2400 or less, 2300 or less, 2200 or less, 2100 or less, 2000 or less, 1900 or less. 1800 or less, 1700 or less, 1600 or less, 1500 or less, 1400 or less, 1300 or less, 1200 or less, 1100 or less, 1000 or less, 900 or less, 800 or less, 700 or less, 600 or less, 500 or less, 400 or less, 300 or less, 200 Below, it can be 100 or less, 90 or less, 80 or less, 70 or less, 60 or less, 50 or less, 40 or less, 30 or less, 20 or less, or 10 or less.
  • the type of microRNA detected and the type of microRNA used as an index can be exactly the same, or a portion of the detected microRNA can be used as an index.
  • cancer can be diagnosed as described in the present disclosure using the expression level and presence / absence of the microRNA as an index.
  • Treatments eg, cancer therapies such as chemotherapy, anticancer drug therapy, surgery, immunotherapy, and radiation therapy
  • cancer therapies such as chemotherapy, anticancer drug therapy, surgery, immunotherapy, and radiation therapy
  • MicroRNA can be present in body fluids in free and / or EV-encapsulated form.
  • microRNA may be present in urine and urine extracts in free form and / or EV (particularly exosomes and / or microvesicles) encapsulated form.
  • the recovery of microRNA can be performed by contacting the body fluid with the nanowires of the nanowire-embedded device of the present disclosure.
  • Recovery of microRNA can be performed under conditions where the nanowires have a positive surface charge.
  • the body fluid may be pH adjusted so that the nanowires have a positive surface charge.
  • the nanowires may be made of a material having a positive surface charge in the body fluid to match the pH of the body fluid.
  • Some aspects of the disclosure include adjusting the pH of the body fluid and bringing the body fluid into contact with the nanowires of the nanowire-embedded device of the present disclosure.
  • the pH of the body fluid can be adjusted before, after, or during contact with the nanowires.
  • the pH of the body fluid may be adjusted to be greater than or greater than a value such as 2, 3, 4, or 5.
  • the pH of the body fluid may be adjusted to be less than or less than a value such as 10, 9, 8, 7, 6, or 5.
  • the pH of urine may be adjusted to 6-8.
  • the body fluid is urine, the pH of which is 6-8 or adjusted to pH 6-8.
  • the nanowires can be zinc oxide nanowires or zinc oxide coated nanowires.
  • the nanowires may substantially grow directly on the substrate (ie, may not be incorporated), and one of them in the substrate.
  • the unit may be incorporated.
  • the material of the substrate is not particularly limited, and polyethylene, polypropylene, polyvinylidene chloride, polyvinylidene chloride, polystyrene, polyvinyl acetate, polytetrafluoroethylene, ABS (acrylonitrile butadiene styrene) resin, AS (acrylonitrile styrene) resin, acrylic tree finger ( Thermoplastic resin such as PMMA); selected from phenolic wood finger, epoxy resin, melamine resin, urea resin, unsaturated polyester resin, alkyd resin, polyurethane, polyimide, silicone rubber, polymethylmethacrylate (PMMA), and polycarbonate (PC). It may be a material to be used.
  • metals and metal oxides such as platinum, aluminum, copper, iron, cobalt, silver, tin, indium, zinc, gallium. , Chromium, and their oxides can be used.
  • the nanowires can be grown from the seed layer and then the substrate material (in liquid form) can be poured onto the nanowires and cured to allow the nanowires to be incorporated into the substrate material. Then, by further growing the nanowires from the nanowires exposed from the substrate, the nanowires incorporated in the substrate can be prepared. When the nanowires are not exposed from the substrate, the nanowires can be exposed by cutting and / or polishing as appropriate.
  • the nanowire-embedded substrate thus obtained can be used as a substrate on which nanowires are immobilized in the device of the present disclosure, has high physicochemical resistance, and can be useful.
  • RNA contained in the captured EV and the small RNA in free form can be obtained by dissociating from the nanowires with a buffer solution.
  • a buffer solution containing a nonionic surfactant can be used.
  • the buffer may contain an inhibitor of RNase.
  • the urine extract containing any one or more or all of the microRNAs in data S1 (or Table 3) and Table 2 may be solution-substituted with a test solution, and the solution of the test solution. It may have a composition.
  • any one, two, three, four, five, six, seven, or eight microRNAs listed in any of the tables 4-1 to 4-15. , 9 kinds, 10 kinds or more, 15 kinds or more, or 20 kinds or more or more, or all of the urine extracts and any of the above urine extracts may be solution-substituted with the test solution. May have a solution composition of.
  • the microRNA can be selected from the group consisting of microRNAs that show higher expression in the cancerous subject than in the non-cancerous subject. Also in this embodiment, the microRNA can be selected from the group consisting of microRNAs that showed lower expression in the cancerous subject than in the non-cancerous subject.
  • the microRNA test solution may have a solution composition suitable for a test for confirming the presence or abundance of ncRNA such as microRNA.
  • Test solutions include, for example, surfactants (eg, nonionic surfactants), salts (eg, sodium, and potassium, etc.), nucleic acid stabilizers (eg, RNA-degrading enzyme inhibitors, etc.), pH adjustments. It may contain one or more selected from the group consisting of agents (eg, buffers) and water.
  • Detection of microRNAs can be performed using miRNA detection methods well known to those of skill in the art, such as quantitative PCR methods, microarrays for miRNA detection, RNA-Seq methods, and multiplex miRNA profiling methods.
  • the urine extract obtained by extracting microRNA with the devices of the present disclosure may contain, for example, more than 500 types of miRNA. Therefore, in order to confirm the expression of all these miRNAs, for example, a microarray for miRNA detection, an RNA-Seq method, a multiplex miRNA profiling method, or the like can be used.
  • a quantitative PCR method, a multiplex miRNA profiling method, or the like can be used to detect one or several of specific miRNAs in the urine extract.
  • RNA sample peaks to a size of 20-30 nucleotides using, for example, methods well known to those skilled in the art or commercially available equipment and kits ⁇ eg, Agilent 2100 Bioanalyzer and RNA LabChip from Agilent Technologies, Inc. ⁇ . The quality of the RNA sample may be confirmed using the appearance as an index.
  • Labeling of miRNA can be performed, for example, by a method well known to those skilled in the art or by using a commercially available kit ⁇ for example, 3D-Gene TM miRNA labeling kit (manufactured by Toray Industries, Inc.) ⁇ . Further, for example, analysis of miRNA by a microarray can be performed using 3D-Gene TM Human / Mouse / Rat / 4animal miRNA Olicochip-4plex manufactured by Toray Co., Ltd. according to the manufacturer's instruction manual for the product. .. These methods allow the detection and quantification of microRNA.
  • microRNAs that showed higher expression in 3 subjects with cancer than in any of the 3 subjects without cancer
  • microRNAs that showed higher expression in cancer subjects than in non-cancer subjects (eg, 2-fold or higher, 3-fold or higher, 4-fold or higher, 5-fold or higher, 6).
  • data S1 (or Table 3) for example, a microarray containing probes for one or more selected from a group of microRNAs that showed lower expression in 3 subjects with cancer than in any of the 3 subjects without cancer;
  • microRNAs eg, 2-fold or higher, 3-fold or higher, 4-fold or higher
  • Microarrays containing probes for one or more of the group of microRNAs (5x or greater, 6x or greater, 7x or greater, 8x or greater, 9x or greater, or 10x or greater) are raised.
  • the types of microRNA detected (that is, the types of probes mounted on the microarray) are, for example, 1 or more, 2 or more, 3 or more, 4 or more, 5 or more, 6 or more, 7 or more, 8 or more.
  • the type of microRNA detected is, for example, 2000 or less, 1900 or less, 1800 or less, 1700 or less, 1600 or less, 1500 or less, 1400 or less, 1300 or less.
  • the probe for microRNA in the microarray can be a nucleic acid and a derivative thereof that can hybridize to the microRNA, and can be appropriately designed by those skilled in the art.
  • the microarray is one or more of Tables 4-1 to 4-15, 22-1 to 22-13, 23-1 to 23-14, 24-1 to 24-15, and 25-1 to 25-15 (1 or more).
  • microRNAs listed in the table may include the microRNAs listed in the table.
  • the number of types of microRNA to be detected by the microarray is 0 or more, 1 or more, 2 or more, 3 or more, 4 or more, 5 or more, 10 or more, 15 or more for each table.
  • microRNA is indicated in at least one table.
  • the number of types of microRNA used as an index may be more than 50%, 60% or more and 70% or more, 80% or more, 90% or more, or all of the number of types of microRNA listed in each table. ..
  • the type of microRNA detected is, for example, 2500 or less, 2400 or less, 2300 or less, 2200 or less, 2100 or less, 2000 or less, 1900 or less, 1800 or less. 1,700 or less, 1600 or less, 1500 or less, 1400 or less, 1300 or less, 1200 or less, 1100 or less, 1000 or less, 900 or less, 800 or less, 700 or less, 600 or less, 500 or less, 400 or less, 300 or less, 200 or less, 100 Below, it can be 90 or less, 80 or less, 70 or less, 60 or less, 50 or less, 40 or less, 30 or less, 20 or less, or 10 or less.
  • the probe for microRNA in the microarray can be a nucleic acid capable of hybridizing to the microRNA and a derivative thereof, and can be appropriately designed by those skilled in the art.
  • Microarrays for detecting microRNAs include hsa-let-7a-3p, hsa-let-7g-5p, hsa-miR-100-3p, hsa-miR-101-3p, hsa-miR-105-.
  • a microarray containing probes for one or more to be made is raised.
  • the types of microRNA detected are, for example, 1 or more, 2 or more, 3 or more, 4 or more, 5 or more, 6 or more, 7 or more, 8 or more.
  • the type of microRNA detected is, for example, 2500 or less, 2400 or less, 2300 or less, 2200 or less, 2100 or less, 2000 or less, 1900 or less, 1800 or less. 1,700 or less, 1600 or less, 1500 or less, 1400 or less, 1300 or less, 1200 or less, 1100 or less, 1000 or less, 900 or less, 800 or less, 700 or less, 600 or less, 500 or less, 400 or less, 300 or less, 200 or less, 100 Below, it can be 90 or less, 80 or less, 70 or less, 60 or less, 50 or less, 40 or less, 30 or less, 20 or less, or 10 or less.
  • the probe for microRNA in the microarray can be a nucleic acid and a derivative thereof that can hybridize to the microRNA, and can be appropriately designed by those skilled in the art.
  • Example 1 Preparation of Nanowires Fixed on Polydimethylsiloxane (PDMS) After cleaning the Si (100) substrate (Advantech Co. Ltd.) (see FIG. 6a), a positive photoresist (OFPR8600 ,, Tokyo Ohka Kogyo) The Si substrate was coated with Co. Ltd.), and then a channel pattern was formed by photoresist (see FIG. 6b). A 140 nm-thick Cr layer (catalyst layer) was deposited on the substrate by sputtering (see FIG. 6b). After removing the photoresist (see FIG. 6d), the Cr layer was thermally oxidized at 400 ° C. for 2 hours.
  • PDMS Polydimethylsiloxane
  • This Cr layer was used as a seed layer for the growth of ZnO nanowires.
  • ZnO nanowires are obtained by immersing the obtained substrate in a mixed solution of 15 mM hexamethylenetetramine (HMTA; Wako Pure Chemical Industries Ltd.) and 15 mM zinc nitrate hexahydrate (Thermo Fisher Scientific Inc.) at 95 ° C. for 3 hours. It was grown by (see FIG. 6e). The nanowires grown on the substrate were washed with Millipore water and air dried overnight in a vacuum desiccator. Then, PDMS (Silpot 184, Dow Corning Corp.) was poured onto the substrate on which the nanowires were grown and cured (see FIG. 6f).
  • HMTA hexamethylenetetramine
  • PDMS Silpot 184, Dow Corning Corp.
  • the nanowires were transferred from the substrate to PDMS.
  • the transferred nanowires are uniformly and deeply embedded in PDMS with a slight exposure of the head (see FIG. 6h) (this embedded state may be referred to herein as "incorporation").
  • Its head provided a growth point for secondary nanowires. Growth of secondary nanowires was performed by immersing the resulting PDMS in a mixed solution of 15 mM HMTA and 15 mM zinc nitrate hexahydrate at 95 ° C. for 3 hours (see FIG. 6i).
  • the PDMS substrate with embedded nanowires After washing the PDMS substrate with embedded nanowires in Millipore water, it is air-dried in a vacuum desiccator, and the diameter of the nanowires and the distance between the nanowires are measured using a field emission scanning electron microscope (FESEM) (SUPRA 40VP, Carl Zeiss). Was measured.
  • FESEM field emission scanning electron microscope
  • Nanowire-embedded microfluidic device capable of in-situ extraction of urinary extracellular vesicle (EV) -encapsulated miRNA
  • the nanowire-embedded microfluidic device for in-situ extraction of urine EV-encapsulated miRNA is a nanowire-embedded PDMS substrate. It was produced by adhering it to a PDMS substrate having a herringbone structure.
  • the herringbone-structured PDMS substrate had microchannels (width, 2 mm; length, 2 cm; and height, 50 ⁇ m) with a herringbone structure with a height of 12 ⁇ m.
  • the surfaces of the nanowire-embedded PDMS substrate and the herringbone-structured PDMS substrate were treated with a plasma etching apparatus (Meiwafosis Co. Ltd.) and adhered.
  • the adhesive device was heated at 180 ° C. for 3 minutes to achieve strong adhesion (see FIG. 6J).
  • PDMS with a herringbone structure was injected with respect to the inlet and outlet in a polyetheretherketone (PEEK) tube [0.5 mm (outer diameter) x 0.26 mm (inner diameter); length 10 cm; Institute of Microchemical Technology Co., Ltd. Ltd. ] Was linked.
  • PEEK polyetheretherketone
  • nanowire-embedded microfluidic device (hereinafter, also simply referred to as “nanowire-embedded device” or “device of the present disclosure”) capable of in situ extraction of the title was obtained.
  • the microfluidic herringbone structure contributed to the improvement of recovery efficiency (see FIG. 15).
  • EDS element mapping of cross-sectional FESEM images The element mapping of PDMS without nanowires, PDMS with embedded nanowires (ie, PDMS with unexposed nanowires), and PDMS with ZnO nanowires is FESEM (JSM-7610F) with EDS function. , Jeol). Acceleration voltage conditions of 5 keV and 30 keV were used for the top view image and the cross-sectional image, respectively. The image was 512 x 384 pixels, with a delay time of 0.1 seconds for each pixel. The images were integrated for 100 cycles. Element mapping images were constructed by selecting peaks of Si K ⁇ (1.739 keV) and Zn L ⁇ (1.012 keV).
  • Elemental mapping of ZnO-Al 2 O 3 core-shell nanowires was performed by FESE M with EDS function under acceleration voltage conditions of 30 keV.
  • STEM scanning transmission electron microscope
  • nanowires are cut from the substrate using a normal cutting sword, collected and placed on a TEM grid (Cu mesh with carbon microgrid, JEOL) by the adhesion method. I changed it.
  • the STEM image was 512 x 384 pixels, and the delay time for each pixel was 0.1 ms. The images were integrated for 100 cycles.
  • Element mapping images were constructed by selecting peaks of Zn K ⁇ (8.63 keV), 0 K ⁇ (0.525 keV), and Al K ⁇ (1.486 keV).
  • the supernatant was removed, 20 mL of phosphate buffered saline (PBS; Thermo Fisher Scientific Inc.) filtered through a 0.22 ⁇ m filter was added to the recovered EV, and the mixture was further ultracentrifuged (70 minutes, 4 ° C.). , 110,000 g). The supernatant was removed, and 20 mL of phosphate buffered saline (PBS; Thermo Fisher Scientific Inc.) filtered through a 0.22 ⁇ m filter was added to the recovered EV, and the third ultracentrifugation (70 minutes, 4). ° C., 110,000 g). Finally, the supernatant was removed and lysis buffer was added to extract the miRNA.
  • PBS phosphate buffered saline
  • EV recovery and extraction of miRNA using a commercially available kit polymer precipitation method
  • Commercially available urine single donor human urine
  • EVs were collected from 1 mL of urine sample according to the manufacturer's instructions for the kit (ExoQuick-TC, System Biosciences Inc.).
  • lysis buffer was added to extract miRNA.
  • Microarray analysis of miRNA expression For the expression profile of miRNA, a 3D-Gene (Toray Industries) human miRNA chip manufactured by Toray Industries, Inc. was used. The miRNA extracted with the lysis buffer was purified using SeraMir Exosome RNA Purification Col-umn Kit (System Biosciences Inc.) according to the manufacturer's instruction manual. 15 ⁇ L of purified miRNA was added to 3D-Gene Human miRNA Oligo chip ver. Analysis was performed for miRNA profiling using 21 (Toray Industries). In microarray analysis of miRNA expression, each signal intensity corresponds to a type of miRNA. The expression level of each miRNA is expressed as the signal intensity (without background) of all miRNAs on each microarray.
  • Signal intensities were standardized throughout the comparison of expression levels between miRNAs in the same urine miRNA sample by extraction with a nanowire-incorporated device and centrifugation or extraction with a commercially available kit. Scatter plots were created for those that were standardized throughout and showed an intensity of 10 or greater (intensity by extraction with a nanowire-embedded device / intensity by ultracentrifugation or extraction with a commercially available kit). Therefore, each point on the scatter plot is a standardized intensity. For comparison of expression levels between miRNAs in the same urine miRNA sample by extraction with a nanowire-incorporated device and centrifugation or extraction with a commercially available kit, signal intensities were log 2 converted.
  • the EV zeta potential was measured using a dynamic light scatterer (Zetasizer Nano ZS, Malvern Instruments Ltd.).
  • Size distribution and concentration of free suspended matter in urine The size distribution and concentration of free suspended matter in urine were measured using a nanoparticle analyzing system (NanoSight ,, Malvern Instruments Ltd.). The concentrations of free suspended matter in urine in the flow-through fraction of urine treated with the nanowire-embedded device in untreated urine and in urine after ultracentrifugation were 2.6 ⁇ 10 12 ml -1 , 5. It was 8 ⁇ 10 9 ml -1 and 3.5 ⁇ 10 9 ml -1 . The size distribution and concentration of free suspended matter in urine were measured using a nanoparticle detector (qNano ,, Meiwafosis Co.
  • NP100 Meiwafosis Co. Ltd.
  • concentrations of free suspended matter in urine in untreated urine, in the flow-through fraction of urine treated with the nanowire-embedded device, and in urine after ultracentrifugation were 1.4 x 10 12 ml -1 , 2. It was 4 ⁇ 10 10 ml -1 and 2.5 ⁇ 10 10 ml -1 .
  • Millipore water 240 ⁇ L
  • 5 mg of PKH26 was added to 1.5 ⁇ 10 8 ml -1 EV.
  • the PKH26 labeled EV was introduced into the nanowire-embedded device at a flow rate of 10 ⁇ l / min using a syringe pump, and then Millipore water was introduced into the nanowire-embedded device at the same flow rate to unrecovered EV (bonded to nanowires). EV) that was not removed was removed. Finally, the fluorescence of EV was observed using a fluorescence microscope (AZ100 ,, Nikon Corp.). Then, the nanowire-embedded device was peeled off, and the nanowire from which the EV was recovered was observed using FESEM (SUPRA 40VP, Carl Zeiss).
  • Detection of Membrane Protein After introducing EV into the nanowire embedded device, PBS was introduced to remove unrecovered EV. Then, a 1% bovine serum albumin (BSA) solution (Kirkegard & Tories Labora-tries Inc.) was introduced into the device and allowed to stand for 15 minutes. The device was washed with PBS and subjected to Alexa Fluor 488-labeled mouse anti-human CD63 monoclonal antibody (10 ⁇ g / ml; Santa Cruz Biotechnology Inc.) or mouse anti-human CD81 monoclonal antibody (10 ⁇ g / ml; Abcam PLC). And allowed to stand for 15 minutes.
  • BSA bovine serum albumin
  • an Alexa Fluor 488-labeled goat anti-mouse IgG polyclonal antibody was introduced into the device as a secondary antibody, and then allowed to stand for 15 minutes. Finally, the device was washed with PBS and the fluorescence intensity was observed under a fluorescence microscope (Olympus Co. Ltd.). PBS was used instead of EV samples to obtain background values. For detection using a 96-well plate (Nunc Co. Ltd.), EV samples were injected into the holes in the plate and allowed to stand for 6 hours, after which the holes were washed with PBS. A 1% BSA solution was introduced into the hole of the plate and allowed to stand for 90 minutes.
  • the holes were washed with PBS, and Alexa Fluor 488-labeled mouse anti-human CD63 monoclonal antibody (10 ⁇ g / ml) or mouse anti-human CD81 antibody (10 ⁇ g / ml) was introduced into the holes of the plate and allowed to stand for 45 minutes.
  • an Alexa Fluor 488-labeled goat anti-mouse IgG polyclonal antibody (5 ⁇ g / ml) was introduced into the hole of the plate as a secondary antibody for 45 minutes thereafter. It was left still.
  • the holes in the plate were washed with PBS, and the fluorescence intensity was observed using a plate reader (POLARstar OPTIMA, BMG Labtech Japan Ltd.). PBS was used instead of EV samples to obtain background values.
  • Preparation of core-shell nanowires of ZnO-Al 2 O 3 After preparation of ZnO nanowires, the nanowires were coated using an atomic layer deposition device (Savannah G2, Ultratech Inc.). The lamination of Al 2 O 3 was carried out by repeating a cycle of flowing trimethylaluminum and H 2 O precursor into a chamber containing nanowires in an atomic layer deposition apparatus and reacting them at 150 ° C. for 100 cycles.
  • a 1 ml urine sample was introduced into the nanowire-embedded device using a syringe pump at a flow rate of 50 ⁇ l / min. Extraction of miRNA from EVs recovered on nanowires was performed in situ by introducing lysis buffer into the device at a flow rate of 50 ml / min using a syringe pump.
  • Nanowires incorporated into microfluidic substrates were developed to establish a methodology for recovering EV-encapsulated miRNAs. These nanowires serve as a solid phase for electrostatic recovery of EVs and subsequently play an important role in the in situ extraction of EV-encapsulated miRNAs (see FIG. 1A).
  • Nanowire-embedded PDMS substrate The nanowire-embedded PDMS substrate was produced by four steps (see Reference 40 and FIG. 6). In the first step, nanowires were grown from the thermally oxidized chromium layer on the Si substrate; in the second step, uncured PDMS was poured onto the growing nanowires; in the third step. , PDMS with nanowires was cured and stripped to give PDMS with embedded nanowires (see FIG. 1B); in a fourth step, nanowires were grown from the embedded nanowires (see FIG. 1C). It is called a nanowire-embedded PDMS substrate obtained here.
  • a field emission scanning electron microscope (FESEM) image of the vertical cross section of the embedded nanowire shows that the nanowire is uniformly and deeply embedded in the PDMS with a slight exposure of its head (see FIG. 1B).
  • the head provided a growth starting point for secondary nanowires (see FIGS. 1C and 7).
  • Element mapping by energy dispersive X-ray analysis (EDS) of cross-sectional FESEM image of PDMS without nanowires was compared with nanowire-embedded PDMS (see FIG. 8) and confirmed that ZnO nanowires were embedded in PDMS in nanowire-embedded PDMS. did.
  • the bone structure ensures good convection and dispersion of the solution) (see Ref. 41) (see FIG. 1D).
  • a nanowire-embedded device that extracts EV-encapsulating miRNA in urine adheres a nanowire-embedded PDMS substrate to a PDMS substrate with a microfluidic herringbone structure to introduce and recover urine samples of polyetheretherketone (PEEK). It was completed by connecting to a tube (see FIG. 1D).
  • the nanowires incorporated into the PDMS substrate showed mechanical stability against exposure to lysis buffer and were able to prevent the nanowires from peeling off the substrate, which would occur for nanowires not incorporated into PDMS. (See FIGS. 1E and F, and FIG. 9).
  • Microarray analysis of miRNA expression In microarray analysis of miRNA expression (2565 types), extraction by a nanowire embedded device has a great variety compared to extraction by a conventional ultracentrifugation method or a polymer precipitation method using a commercially available kit. It has been shown that it is possible to extract species (about 1,000 species) (see FIGS. 2 and 10A). Completion of EV-encapsulated miRNA in urine within 40 minutes (20 minutes for adsorption and 20 minutes for extraction) requires the introduction of a urine sample (1 ml) into the device followed by the introduction of lysis buffer (1 ml). Demonstrated by.
  • the expression levels of miRNA extracted with the nanowire-embedded devices of the present disclosure are higher than those obtained by ultracentrifugation. Scatter plots and histograms showed that it was much higher (see Figures 2A and B). Generally speaking, since 20 times or more of the amount of urine was used, the amount of miRNA obtained by the ultracentrifugation method should be higher than the amount of miRNA obtained by the device of the present disclosure. Was the opposite. Compared to the ultracentrifugation method, the device of the present disclosure resulted in a five-fold higher amount of miRNA (see FIG.
  • the types of miRNA that could be extracted were also diverse (the amount of miRNA extracted by the device of the present disclosure). : 749, 822, types: 1,111 types; amount of miRNA extracted by centrifugation: 171 261 types, types: 352 types) (see FIG. 2B).
  • the amount of miRNA extracted using the devices of the present disclosure was the amount of miRNA obtained by the kit, even though the volume of urine sample consumed was the same. Much higher than (see Figures 2C and D). Compared with the above kit, the device of the present disclosure resulted in a four-fold higher amount of miRNA (see FIG.
  • the devices of the present disclosure have miRNA extraction efficiency (see FIGS. 2), extraction time (see FIGS. 10A and B), and extraction of small RNAs as compared to conventional methods (ultracentrifugation and polymer precipitation). It was concluded that it was excellent in terms of efficiency (see FIG. 10C).
  • the fluorescence intensity of EV in urine collected on nanowires (or wells on 96-well plates) indicates that only nanowires can recover these membrane proteins. Shown (see FIG. 3E). This indicates that EVs can be efficiently recovered on nanowires in the devices of the present disclosure.
  • a ZnO-Al 2 O 3 core-shell nanowire was prepared in which the ZnO core was completely coated with an Al 2 O 3 layer having a thickness of 10 nm (see FIG. 11).
  • the core-shell nanowires of ZnO-Al 2 O 3 are charge-neutral (slightly positive or slightly negative) at pH 6-8, since the isoelectric point of Al 2 O 3 is about 7.5. ) (See Documents 45 and 46). Therefore, by using ZnO-Al 2 O 3 core-shell nanowires, it was confirmed whether the charged state on the surface of the nanowires had a predominant effect on the recovery of EV (see FIG. 12). Since ZnO nanowires have an isoelectric point of ZnO of about 9.5, they have a positively charged surface at pH 6 to 8, whereas EV in urine has a negatively charged surface at pH 6 to 8. It can be understood that ZnO nanowires enable efficient EV recovery (see Documents 47 and 48). From these results, it was further clarified that ZnO nanowires can recover free suspended matter of urine having a diameter up to 200 nm such as EV with a recovery efficiency of 99% or more.
  • EVs when EVs are recovered by the ultracentrifugation method, many of the EVs may fuse and disintegrate by being pressed against the inner wall of the ultracentrifugation tube, and in this process, miRNA contained in the microvesicles may be present. It may be released to the surrounding area.
  • the mechanism of EV recovery by ultracentrifugation is based on the balance between the force and density applied to the recovered object. Therefore, the experimental conditions of ultracentrifugation are not considered suitable for recovery of released miRNAs.
  • the mechanism of EV recovery by nanowires is thought to be based on the electrostatic interaction between positively charged nanowires and negatively charged objects, which allows nanowires to recover exosomes and microvesicles. It is thought that it can be done. Further, since nucleic acids such as miRNA have a surface property of being negatively charged at pH 6 to 8, it is considered that EV-free miRNA (free miRNA) can be recovered by nanowires. However, recovery of free miRNA is considered impossible by ultracentrifugation or polymer precipitation. In addition, the recovery efficiency of miRNA from nanowires by introducing a lysis buffer was almost 100% (see FIG. 14B).
  • Nanowires with positively charged surfaces will provide significant benefits in recovering negatively charged substances in urine such as exosomes, microvesicles, and free miRNAs.
  • the ultracentrifugation method Considering characteristics such as recovery efficiency, selectivity of the obtained product, and ability to recover urinary miRNA (see Table 1), the ultracentrifugation method has high recovery efficiency and high selectivity of the obtained product (exosomes only).
  • the devices of the present disclosure have high recovery efficiency, low selectivity (extensive recovery of exosomes, microvesicles, and free miRNAs), and high recovery capacity, whereas the recovery capacity is low.
  • kits that use the polymer precipitation method are half-finished in these properties.
  • the protamine precipitation method for EVs is achieved by incubating with protamine / polyethylene glycol overnight at 4 ° C. (similar to ExoQuick), such an EV charge-based isolation method (similar to ExoQuick).
  • the extraction of EV-encapsulated miRNAs by the devices of the present disclosure only requires 40 minutes at room temperature (20 minutes for recovery or adsorption and 20 minutes for extraction). There is.
  • EVs with the devices of the present disclosure are compared to charge-based isolation techniques for free nucleic acids using chitosan polymers with amine groups that produce positively charged surfaces below pH 6.3 (see Ref. 50).
  • Extraction of encapsulated miRNA has the advantage that the nanowires are guaranteed to be positively charged in urine at pH 6-8. And from these findings, the recovery of EVs (and free miRNAs) by electrostatic interaction with ZnO nanowires and the mechanical stability of the nanowires incorporated into PDMS during application of the lysis buffer are important mechanisms. , It is expected that early diagnosis of diseases and timely health diagnosis will be possible based on the analysis of urinary miRNA.
  • miRNAs were extracted from urine samples of cancer patient donors and healthy subjects (non-cancer donors) using the devices of the present disclosure and compared on a heat map. As shown in FIG. 4, the presence of various miRNAs whose expression levels change in relation to cancer could be observed. Comparison of cancer patient donors with non-cancer donors revealed cancer-related decreased and increased miRNAs in the urine (see Figures 5 and 2). Heatmaps suggest that decreasing miRNAs and increasing miRNAs are new indicators of cancer, and that combinations of these can be new indicators of cancer.
  • the miRNAs extracted by the devices of the present disclosure included two groups of miRNAs: a group of miRNAs of unknown physiological function and a group of miRNAs of which physiological functions were reported.
  • the group of miRNAs of unknown physiological function can be broadly divided into two subgroups: cancer-related miRNAs and free miRNA-derived artifacts.
  • diseases such as miR-520c-3p (a tumor suppressor and miRNA that was reduced in urine from all cancer patients).
  • miRNAs that positively correlate with the outcome of see Documents 53 to 57
  • miR-16-1--3p miRNAs that suppress the invasion and metastasis of gastric cancer cells and are derived from liver cancer patients and bladder cancer patients. It was roughly divided into a group of miRNAs showing an anti-intuitive correlation between functions such as (miRNAs overexpressed in urine) and diseases (see Reference 60). In the counter-intuitive case, three possibilities were considered: the first possibility is the patient's corresponding risk; the second possibility is the miRNA and cancer type in this study. The relationship with is not covered; a third possibility is that miRNAs are attributed to artifacts.
  • Example 2 Further analysis Urine was collected from 100 patients including various human cancer patients of stages I to IV and 100 healthy subjects, and microRNA was extracted from the urine by the same method as in Example 1. .. There are 100 human cancer patients, including lung cancer, breast cancer, kidney cancer, leukemia, lymphoma, pancreatic cancer, prostate cancer, gastric cancer, urinary epithelial cancer, melanoma, ovarian cancer, and thyroid cancer. Inclusive. Urine was collected from each patient and microRNA was extracted from the urine by the same method as in Example 1.
  • the stages of lung cancer patients were as follows. Number of lung cancer patients by stage Stage IA: 10 Stage IB: 14 Stage II: 18 Stage III: 41 Stage IV: 15 Unknown: 2 Obtain log2 (fluorescence intensity) from the fluorescence intensity of each miRNA and obtain a histogram. It was created. The results were as shown in FIG. 16D. Histograms were created by dividing the miRNAs detected in all 200 samples and the miRNAs detected in any one or more of the samples. Next, a pie chart was created for the urine of lung cancer patients and the urine of healthy subjects based on the p-value in the Student's t-test. The results were as shown in FIG. 16E.
  • miRNAs having an absolute value of the weighting coefficient larger than 0.01 were extracted, and the relationship between the weighting coefficient and the miRNA was illustrated.
  • the results were as shown in FIG. 17A.
  • miR-4520-3p, miR-1250-5p, miR-6070, miR-4453, miR-449c-5p, miR-4307, miR-106a-3p, miR-4311, miR-1265, and miR-6828-5p was identified as a particularly strong factor associated with lung cancer with a weighting factor greater than 0.5.
  • miR-630, miR-6387-3p, miR624-3p, miR-642a-5p, miR339-5p, miR452-3p, miR-30e-3p, miR-938, and miR-20a-3p are weighting coefficients.
  • a heat map was prepared from the relationship between log2 (fluorescence intensity) and miRNA shown in FIG. 17A above. The heat map obtained was as shown in FIG. 17B.
  • patients and healthy subjects were randomly divided into 20 groups, and a judgment formula was derived by logistic regression (using the expression level of total miRNA) from the results of 19 randomly obtained groups, and the remaining 1 group.
  • a judgment formula was created in the same manner as above using patients other than stage II and healthy subjects as teacher data, the stage II patients were predicted, and the Cancer risk value and the ROC curve based on the value were derived. The results were as shown in FIGS. 18D and C, respectively.
  • a judgment formula was created in the same manner as above using patients other than stage III and healthy subjects as teacher data, and patients in stage III were predicted, and the Cancer risk value and the ROC curve based on the value were derived. The results were as shown in FIGS. 18F and E, respectively.
  • FIG. 19A shows the number of miRNAs detected in each of the lung cancer tissues and the urine of lung cancer patients for each sample.
  • FIG. 19A also shows the number of miRNAs detected in both lung cancer tissue and in the urine of lung cancer patients.
  • FIG. 19B is data comparing log2 (fluorescence intensity) of 19 miRNAs in which the absolute value of the weighting coefficient exceeds 0.5 between tissue and urine.
  • Table 4-1 it is clear that the expression level of each microRNA is statistically significantly different from that of the urine of healthy subjects of lung cancer patients.
  • Table 4-1 it was predicted whether the target from which urine was derived was a healthy lung cancer patient.
  • the median value between the average mRNA level in the urine of lung cancer patients and the average mRNA level in the urine of healthy subjects was used as a threshold value.
  • Table 4-1 it was possible to predict lung cancer patients with high sensitivity or high specificity even using a single miRNA.
  • Student's t-test was performed between breast cancer patients and healthy subjects, and the group of microRNAs with p ⁇ 0.05 is shown in Table 4-2.
  • Student's t-test was performed on renal patients and healthy subjects, and the group of microRNAs with p ⁇ 0.05 is shown in Table 4-3.
  • Student's t-test was performed on leukemia patients and healthy subjects, and the group of microRNAs with p ⁇ 0.05 is shown in Table 4-4.
  • Student's t-test was performed on lymphoma patients and healthy subjects, and the group of microRNAs with p ⁇ 0.05 is shown in Table 4-5.
  • Student's t-test was performed between pancreatic cancer patients and healthy subjects, and the group of microRNAs with p ⁇ 0.05 is shown in Table 4-6.
  • Student's t-test was performed on prostate cancer patients and healthy subjects, and the group of microRNAs with p ⁇ 0.05 is shown in Table 4-7. Student's t-test was performed between gastric cancer patients and healthy subjects, and the group of microRNAs with p ⁇ 0.05 is shown in Table 4-8. Student's t-test was performed between patients with urothelial cancer and healthy subjects, and the group of microRNAs with p ⁇ 0.05 is shown in Table 4-9. Student's t-test was performed on melanoma patients and healthy subjects, and the group of microRNAs with p ⁇ 0.05 is shown in Table 4-10.
  • a Studct t-test was performed on ovarian cancer patients and healthy subjects, and the group of microRNAs with p ⁇ 0.05 is shown in Table 4-11. Student's t-test was performed on thyroid cancer patients and healthy subjects, and the group of microRNAs with p ⁇ 0.05 is shown in Table 4-12. Student's t-test was performed on cervical cancer patients and healthy subjects, and the group of microRNAs with p ⁇ 0.05 is shown in Table 4-13. Student's t-test was performed between patients with rectal colon cancer and healthy subjects, and the group of microRNAs with p ⁇ 0.05 is shown in Table 4-14. Student's t-test was performed between endometrial cancer patients and healthy subjects, and the group of microRNAs with p ⁇ 0.05 is shown in Table 4-15.
  • accuracy represents (TP + TN) / (TP + FP + TN + TP); precision represents TP / (TP + FP); reccall represents TP / (TP + FN); TP represents true positive; TN represents true negative. FP represents a false positive; FN represents a false negative.
  • the F value is the harmonic mean of precision and recall.
  • Tables 5-1 and 6-1, 7-1, 8-1, 9-1, 10-1, 11-1, 12-1, 13-1, 14-1, 15-1, 16-1, 17 The analysis results of the results shown in -1, 18-1, and 19-1 are shown in Tables 5-2, 6-2, 7-2, 8-2, 9-2, 10-2, and 11-2, respectively. , 12-2, 13-2, 14-2, 15-2, 16-2, 17-2, 18-2, and 19-2. Tables 5-2, 6-2, 7-2, 8-2, 9-2, 10-2, 11-2, 12-2, 13-2, 14-2, 15-2, and 16-2. As shown, analysis with 5 or more miRNAs showed high accuracy, recall, and precision in all cases, except in exceptional cases.
  • Tables 5-2, 6-2, 7-2, 8-2, 9-2, 10-2, 11-2, 12-2, 13-2, 14-2, 15-2, 16-2 , 17-2, 18-2, and 19-2, analysis with 10, 15, and 20 randomly selected miRNAs further determines its accuracy, recall, and precision. Improved. As described above, various cancer patients can be predicted by randomly selecting and combining 5 or more, preferably 10 or more, of the miRNAs shown in any of the tables 4-1 to 4-15. Was something that could be done.
  • miRNAs that can predict each of the stage I and II patients.
  • the accuracy was 50 in the prediction of stage I and II patients using the expression level using a single miRNA as an index.
  • the miRNA that was% or more and its accuracy were determined.
  • the predictions for various stage I cancer patients were as shown in Tables 22-1 to 22-13.
  • the predictions for stage II lung cancer patients were as shown in Table 23-1.
  • the predicted results of stage I and II cancer patients are shown in Tables 23-2 to 23-14.
  • the ROC curve by simple cutoff was obtained, and the true positive rate, false positive rate, cutoff value at that time, and AUC value were obtained.
  • the results were as shown in Tables 25-1 to 25-15.
  • the ROC curve by logistic regression was obtained for the expression level of a single miRNA, and the true positive rate, false positive rate, cutoff value at that time, and AUC value were obtained.
  • the results were as shown in Tables 24-1 to 24-15. Based on these results, the miRNAs disclosed in these tables could be used alone for evaluation to predict cancer patients.
  • Tricarico A. et al. Corbeli, L. et al. Annatarone, S.A. Pinach, S.A. Grimaldi, G.M. Bruno, D.M. Cimino, D.I. Taberna, M. et al. C. Deregibus, M. et al. P. Rastaldi, P.M. C. Perin, G.M. Gruden, Urinary exosomal microRNAs in incipient diabetic nephropathy. PLOS ONE 8, e73798 (2013). 29. C. They, S.A. Amigorena, G.M. Raposo, A. et al.
  • MicroRNA-378-5p suppresses cell proliferation and apoptosis in apoptosis in colorectal cancer cells by targeting BRAF. Cancer Cell Int. 15, 40 (2015). 53. H. -L. Miao, C.I. -J. Lei, Z. -D. Qiu, Z. -K. Liu, R.M. Li, S. -T. Bao, M.M. -Y. Li, MicroRNA-520c-3p inhibits hepatocellular carcinoma cell proliferation and innovation invasion of cell apoptosis by tricging. Hepatol. Res. 44,338-348 (2014). 54. S. Lu, Q. Zhu, Y. Zhang, W. et al.
  • miRNA-558 promotes gastric cancer promotion throut teaching Smad4-mediated repression of heparanase expression. Cell Death Dis. 7, e2382 (2016). 63. Y. Sun, C.I. Chen, P. et al. Zhang, H. et al. Xie, L. et al. Hou, Z. Hui, Y. Xu, Q. Du, X. Zhou, B. Su, W. Gao, Reduced miR-3127-5p expression promotion NSCLC promotion / invasion and properties to dasatinib sensitivity via the c-Abl / Ras / Sci. Rep. 4,6527 (2014). 64. Y. Fang, J. et al.
  • Zhao miR-337 regulates the proliferation and invasion in pancreatic ductal adenocarcinoma by targeting HOXB7.

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