WO2019144099A1 - Methods for colon cancer detection and treatment monitoring - Google Patents
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- C12Q2600/00—Oligonucleotides characterized by their use
- C12Q2600/158—Expression markers
Definitions
- the present invention relates to colon cancer detection.
- CRC Colorectal cancer
- CEA carcinoembryonic antigen
- a glycoprotein involved in cell adhesion that is not generally expressed in adult tissues except in heavy smokers. Its specialized sialofucosy lated glycoforms serve as functional colon carcinoma L-selectin and E-selectin ligands, which may play a role in metastatic dissemination of colon carcinoma cells.
- CEA is principally used to monitor colorectal carcinoma treatment, to identify recurrences after surgical resection, for staging or to localize cancer spread through measurement of biological fluids. There are, however, significant limitations. While preoperative CEA levels have shown an association with (disease- free) survival, this was chiefly because it was a surrogate for metastatic presentation.
- the present disclosure provides a method for detecting a colon cancer in a subject in need thereof, comprising: (a) determining the expression level of at least 14 biomarkers from a test sample from the subject by contacting the test sample with a plurality of agents specific to detect the expression of the at least 14 biomarkers, wherein the 14 biomarkers comprise ADRM1, CDK4, COMT, DHCR7, HMOX2, MCM2, PDXK, POP7, SWOP, SNRPA, SORD, STOML2, UMPS, and a housekeeping gene; (b) normalizing the expression level of each of ADRMl, CDK4, COMT, DHCR7, HMOX2, MCM2, PDXK, POP7, SWOP, SNRPA, SORD, STOML2, and UMPS to the expression level of the housekeeping gene, thereby obtaining a normalized expression level of each of
- the present disclosure provides a method for detecting a colon cancer in a subject in need thereof, the method comprising: (a) determining the expression level of at least 14 biomarkers from a test sample from the subject by contacting the test sample with a plurality of agents specific to detect the expression of the at least 14 biomarkers, wherein the 14 biomarkers comprise ADRMl, CDK4, COMT, DHCR7, HMOX2, MCM2, PDXK, POP7, SWOP, SNRPA, SORD, STOMIJ2, UMPS, and a housekeeping gene; (b) normalizing the expression level of each of ADRMl, CDK4, COMT, DHCR7, HMOX2, MCM2, PDXK, POP7, SWOP, SNRPA, SORD, STOML2, and UMPS to the expression level of the housekeeping gene, thereby obtaining a normalized expression level of each of ADRMl, CDK4, COMT, DHCR7, HMOX2, MCM2,
- the present disclosure provides a method for determining whether a colon cancer in a subject is stable or progressive, the method comprising: (a) determining the expression level of at least 14 biomarkers from a test sample from the subject by contacting the test sample with a plurality of agents specific to detect the expression of the at least 14 biomarkers, wherein the 14 biomarkers comprise ADRM1, CDK4, COMT, DHCR7, HMOX2, MCM2, PDXK, POP7, SWOP, SNRPA, SORD, STOML2, UMPS, and a housekeeping gene; (b) normalizing the expression level of each of ADRM1, CDK4, COMT, DHCR7, HMOX2, MCM2, PDXK, POP7, SWOP, SNRPA, SORD, STOML2, and UMPS to the expression level of the housekeeping gene, thereby obtaining a normalized expression level of each of ADRM1, CDK4, COMT, DHCR7, HMOX2, MCM2, PD
- the present disclosure provides a method for determining whether a colon cancer in a subject is stable or progressive, the method comprising: (a) determining the expression level of at least 14 biomarkers from a test sample from the subject by contacting the test sample with a plurality of agents specific to detect the expression of the at least 14 biomarkers, wherein the 14 biomarkers comprise ADRMl, CDK4, COMT, DHCR7, HMOX2, MCM2, PDXK, POP7, SWOP, SNRPA, SORD, STOMI.2, UMPS, and a housekeeping gene; (b) normalizing the expression level of each of ADRMl, CDK4, COMT, DHCR7, HMOX2, MCM2, PDXK, POP7, SWOP, SNRPA, SORD, STOMI.2, and UMPS to the expression level of the housekeeping gene, thereby obtaining a normalized expression level of each of ADRMl, CDK4, COMT, DHCR7, HMOX2,
- a method for determining the completeness of surgery in a subject having a colon cancer comprising: (a) determining the expression level of at least 14 biomarkers from a test sample from the subject after the surgery by contacting the test sample with a plurality of agents specific to detect the expression of the at least 14 biomarkers, wherein the 14 biomarkers comprise ADRM1, CDK4, COMT, DHCR7, HMOX2, MCM2, PDXK, POP7, SIOOP, SNRPA, SORD, STOML2, ZJMPS, and a housekeeping gene; (b) normalizing the expression level of each of ADRMl, CDK4, COMT, DHCR7, HMOX2, MCM2, PDXK, POP7, SIOOP, SNRPA, SORD, STOML2, and ZJMPS to the expression level of the housekeeping gene, thereby obtaining a normalized expression level of each of ADRMl, CDK4, COMT, DHCR7, HMOX2, MCM2, PDXK, P
- the present disclosure provides a method for determining the completeness of surgery in a subject having a colon cancer, the method comprising: (a) determining the expression level of at least 14 biomarkers from a test sample from the subject after the surgery by contacting the test sample with a plurality of agents specific to detect the expression of the at least 14 biomarkers, wherein the 14 biomarkers comprise ADRMl, CDK4, COMT, DHCR7, HMOX2, MCM2, PDXK, POP7, SIOOP, SNRPA, SORD, STOML2, UMPS, and a housekeeping gene; (b) normalizing the expression level of each of ADRMl, CDK4, COMT, DHCR7, HMOX2, MCM2, PDXK, POP7, SIOOP, SNRPA, SORD, STOML2, and UMPS to the expression level of the housekeeping gene, thereby obtaining a normalized expression level of each of ADRMl, CDK4, COMT, DHCR7,
- the present disclosure provides a method comprising: (a) determining the expression level of at least 14 biomarkers from a test sample from a subject by contacting the test sample with a plurality of agents specific to detect the expression of the at least 14 biomarkers, wherein the 14 biomarkers comprise ADRMl, CDK4, COMT, DHCR7, HMOX2, MCM2, PDXK, POP7, SWOP, SNRPA, SORD, STOML2, IMPS, and a housekeeping gene; (b) normalizing the expression level of each of ADBM1, CDK4, COMT, DHCR7, HMOX2, MCM2, PDXK, POP7, SWOP, SNRPA, SORD, STOML2, and UMPS to the expression level of the housekeeping gene, thereby obtaining a normalized expression level of each of ADRMl, CDK4, COMT, DHCR7, HMOX2, MCM2, PDXK, POP7, SWOP, SNRPA, SORD, STOML2, and
- the present disclosure provides a method for evaluating the response of a subject having a colon cancer to a first therapy, the method comprising: (1) at a first time point: (a) determining the expression level of at least 14 biomarkers from a first test sample from the subject by contacting the first test sample with a plurality of agents specific to detect the expression of the at least 14 biomarkers, wherein the 14 biomarkers comprise ADRMl, CDK4, COMT, DHCR7, HMOX2, MCM2, PDXK, POP7, SWOP, SNRPA, SORD, STOML2, UMPS, and a housekeeping gene; (b) normalizing the expression level of each of ADRMl, CDK4, COMT, DHCR7, HMOX2, MCM2, PDXK, POP7, SWOP, SNRPA, SORD, STOMU, and UMPS to the expression level of the housekeeping gene, thereby obtaining a normalized expression level of each of ADRMl, CDK4, CO
- the present disclosure provides a method for evaluating the response of a subject having a colon cancer to a therapy, the method comprising: (1) at a first time point, performing the following steps that include (a) determining the expression level of at least 14 biomarkers from a first test sample from the subject by contacting the first test sample with a plurality of agents specific to detect the expression of the at least 14 biomarkers, wherein the 14 biomarkers comprise ADRMl, CDK4, COMT, DHCR7, HMOX2, MCM2, PDXK, POP7, SIOOP, SNRPA, SORD, STOML2, UMPS, and a housekeeping gene; (b) normalizing the expression level of each of ADRMl, CDK4, COMT, DHCR7, HMOX2, MCM2, PDXK, POP7, SIOOP, SNRPA, SORD, STOML2, and UMPS to the expression level of the housekeeping gene, thereby obtaining a normalized expression level of each of ADRMl, CDK4, CO
- a method of the present disclosure can further comprise continuing to administer a first therapy to a subject when a second score is significantly decreased as compared to a first score.
- a method of the present disclosure can further comprise discontinuing administration of a first therapy to a subject when a second score is not significantly decreased as compared to a first score.
- a method of the present disclosure can further comprise administering a second therapy to a subject when a second score is not significantly decreased as compared to a first score.
- a second score is significantly decreased as compared to a first score when the second score is at least 25% less than the first score.
- a predetermined cutoff value can be 50% on a scale of 0-100%.
- a predetermined cutoff value can be 60% on a scale of 0-100%.
- a housekeeping gene can be selected from the group consisting of MRPL19, PSMC4, SF3A1, PUM1, ACTB, GAPD, GUSB, RPUQ, TFRC, MORF4L1, 18S, PPIA, PGKl, RPL13A, B2M, YWHAZ, SDHA, and HPRTl.
- the housekeeping gene can be MORF4L1.
- a method of the present disclosure can have a sensitivity greater than 85%. In some aspects, a method of the present disclosure can have a specificity of greater than 85%.
- a biomarker can comprise RNA, cDNA, protein or any combination thereof.
- the RNA can be reverse transcribed to produce cDNA, and the produced cDNA expression level can be detected.
- a biomarker or the expression of a biomarker can be detected by forming a complex between the biomarker and a labeled probe or primer.
- the protein when a biomarker is protein, the protein can be detected by forming a complex between the protein and a labeled antibody.
- the RNA or cDNA when a biomarker is RNA or cDNA, can be detected by forming a complex between the RNA or cDNA and a labeled nucleic acid probe or primer.
- a complex between the RNA or cDNA and the labeled nucleic acid probe or primer can be a hybridization complex.
- a predetermined cutoff value can be derived from a plurality of reference samples obtained from subjects not having or not diagnosed with a neoplastic disease.
- the neoplastic disease can be colon cancer.
- an algorithm can be XGBoost (XGB), Random Forest (RF), glmnet, cforest, Classification and Regression Trees for Machine Learning (CART), treebag, K-Nearest Neighbors (kNN), neural network (nnet), Support Vector Machine radial (SVM-radial), Support Vector Machine linear (SVM-linear), Naive Bayes (NB), multilayer perception (mlp) or any combination thereof.
- the methods of the present disclosure can further comprise administering to a subject a first therapy when a score is equal to or greater than a predetermined cutoff.
- a first time point can be prior to the administration of a first therapy to the subject
- a first time point can be after the administration of the first therapy to the subject
- a therapy can comprise anti-cancer therapy, surgery, chemotherapy, targeted drug therapy, radiation therapy, immunotherapy or any combination thereof.
- surgery can comprise removing a polyp during a colonoscopy, endoscopic mucosal resection, a partial colectomy, an ostomy, removing at least one cancerous lesion from the liver, or any combination thereof.
- chemotherapy can comprise FOLFOX, FOLFIRI, a combination of 5-FU and leucovorin, capecitabine, irinotecan, CapeOx or any combination thereof.
- targeted drug therapy can comprise bevacizumab, cetuximab, panitumumab, regorafenib, a combination of trifluridine and tipiracil, a EGFR TKI inhibitor or any combination thereof.
- anti-cancer therapy can comprise anti-colon cancer therapy.
- immunotherapy can comprise pembrolizumab, nivolumab or a combination of pembrolizumab and nivolumab.
- a test sample can be blood, serum, plasma, neoplastic tissue or any combination thereof.
- a reference sample can be blood, serum, plasma, non-neoplastic tissue or any combination thereof.
- FIGs. 2A-2B are graphs showing receiver operator curve analysis of the test set (FIG. 2A) and independent set (FIG. 2B). Each cohort included 136 cancers and 60 controls. The AUROC in the test set was 0.9 and the Youden J index was 0.71. In the independent set the AUROC was 0.86 with a Youden index of 0.6. Z-statistics ranged 11.2-15.6 and were highly significant (p ⁇ 0.0001). The sensitivity and specificity of the test ranged 85-87.5% and 75-83%, respectively.
- the AUROC was 0.88, /K0.0001 (FIG. 3B).
- Horizontal lines identify median expression of the normalized 13 gene signature (ColoTest).
- FIGs. 4A-4B are graphs showing decision curve analysis (FIG. 4A) and risk analysis (FIG. 4B) for the ColoTest. This exhibited >50% standardized predictive benefit up to a risk threshold of 80%.
- the probit risk assessment plot identified a ColoTest score >50% was 75% accurate for predicting colon cancer in a blood sample. This was increased to >80% at a ColoTest score >60%.
- FIGs. 6A-6C are graphs showing ColoTest scores in stable and progressive disease. Test scores were not significantly different between those identified as stable and those with progressive disease at the time of assessment (FIG. 6A). Of the 17 with stable disease, 12 exhibited disease progression in the 3 month follow-up. Levels in those who truly had demonstrable stable disease were low (16 ⁇ 10%) (FIG. 6B). In those who did progress in the 3 months levels were not different to those that had progressive disease (73 ⁇ 16% vs. 68 ⁇ 25%). The AUROC for differentiating stable from progressing/progressive disease was 0.97, p ⁇ 0.0001 (FIG. 6C).
- FIG. 7 is a graph showing comparison of AUROC between the ColoTest and CEA for differentiating stable from progressive disease.
- FIG. 8 is a graph showing the effect of treatment on the ColoTest. Levels prior to treatment are elevated (82 ⁇ 9%). In those who responded to therapy with disease stabilization, levels were reduced to 14 ⁇ 7% (*/? ⁇ 0.0001). In those that exhibited disease progression because of treatment failure, levels were elevated (69 ⁇ 21%).
- Colon cancer is cancer of the large intestine (colon). Symptoms of colon cancer include, but are not limited to: (a) a change in bowel habits, (b) rectal bleeding or blood in the stool, (c) persistent abdominal discomfort, such as cramps, gas or pain, (d) a feeling that the bowel doesn't empty completely, (e) weakness or fatigue, and (f) unexplained weight loss.
- the present invention is based on the discovery that the expression levels of
- ADRMl CDK4, COMT, DHCR7, HMOX2, MCM2, PDXK, POP7, SWOP, SNRPA, SORD,
- MORF4L1 are elevated in subjects having colon cancers as compared to healthy subjects.
- the present disclosure provides a method for detecting a colon cancer in a subject in need thereof, the method comprising: (a) determining the expression level of at least
- 14 biomarkers from a test sample from the subject by contacting the test sample with a plurality of agents specific to detect the expression of the at least 14 biomarkers, wherein the 14 biomarkers comprise ADRMl, CDK4, COMT, DHCR7, HMOX2, MCM2, PDXK, POP7, SWOP,
- SNRPA SORD, STOML2, UMPS, and a housekeeping gene; (b) normalizing the expression level of each of ADRMl, CDK4, COMT, DHCR7, HMOX2, MCM2, PDXK, POP7, SWOP, SNRPA,
- step (e) can comprise producing a report, wherein the report identifies the presence of a colon cancer in the subject when the score is equal to or greater than the first predetermined cutoff value or identifies the absence of a colon cancer in the subject when the score is less than the first predetermined cutoff value.
- the preceding method can further comprise administering to the subject a first therapy.
- the preceding method can further comprise administering to the subject a first therapy when the score is equal to or greater than the predetermined cutoff.
- the present disclosure also provides a method for determining whether a colon cancer in a subject is stable or progressive, the method comprising: (a) determining the expression level of at least 14 biomarkers from a test sample from the subject by contacting the test sample with a plurality of agents specific to detect the expression of the at least 14 biomarkers, wherein the 14 biomarkers comprise ADRM1, CDK4, COMT, DHCR7, HMOX2, MCM2, PDXK, POP7, SI OOP, SNRPA, SORD, STOML2, UMPS, and a housekeeping gene; (b) normalizing the expression level of each of ADRMl, CDK4, COMT, DHCR7, HMOX2, MCM2, PDXK, POP7, SI OOP, SNRPA, SORD, STOML2, and UMPS to the expression level of the housekeeping gene, thereby obtaining a normalized expression level of each of ADRMl, CDK4, COMT, DHCR7, HMOX2, MCM2,
- step (e) can comprise producing a report, wherein the report identifies that the colon cancer is progressive when the score is equal to or greater than the second predetermined cutoff value or identifies that the colon cancer is stable when the score is less than the second predetermined cutoff value.
- the preceding method can further comprise administering to the subject a first therapy.
- the preceding method can further comprise administering to the subject a first therapy when the score is equal to or greater than the predetermined cutoff.
- the method further comprises treating the subject with a progressive colon cancer with surgery, chemotherapy, targeted drug therapy, radiation therapy,
- the present disclosure also provides a method for determining the completeness of surgery in a subject having a colon cancer, the method comprising: (a) determining the expression level of at least 14 biomarkers from a test sample from the subject after the surgery by contacting the test sample with a plurality of agents specific to detect the expression of the at least 14 biomarkers, wherein the 14 biomarkers comprise ADRM1, CDK4, COMT, DHCR7, HMOX2, MCM2, PDXK, POP7, S100P, SNRPA, SORD, STOML2, IMPS, and a housekeeping gene; (b) normalizing the expression level of each of ADRMl, CDK4, COMT, DHCR7, HMOX2, MCM2, PDXK, POP7, SI OOP, SNRPA, SORD, STOML2, and UMPS to the expression level of the housekeeping gene, thereby obtaining a normalized expression level of each of ADRMl, CDK4, COMT, DHCR7, HMOX2,
- step (e) can comprise producing a report, wherein the report identifies that the colon cancer is not completely removed when the score is equal to or greater than the first predetermined cutoff value or identifies that the colon cancer is completely removed when the score is less than the first predetermined cutoff value.
- the preceding method can further comprise administering to the subject a first therapy.
- the preceding method can further comprise administering to the subject a first therapy when the score is equal to or greater than the predetermined cutoff.
- the present disclosure also provides a method comprising: (a) determining the expression level of at least 14 biomarkers from a test sample from a subject by contacting the test sample with a plurality of agents specific to detect the expression of the at least 14 biomarkers, wherein the 14 biomarkers comprise ADRMl, CDK4, COMT, DHCR7, HMOX2, MCM2, PDXK, POP7, SWOP, SNRPA, SORD, STOML2, UMPS, and a housekeeping gene; (b) normalizing the expression level of each of ADRMl, CDK4, COMT, DHCR7, HMOX2, MCM2, PDXK, POP7, SI OOP, SNRPA, SORD, STOML2, and UMPS to the expression level of the housekeeping
- the response of a subject having a colon cancer to a therapy can also be evaluated by comparing the scores determined by the same algorithm at different time points of the therapy.
- the first time point can be prior to or after the administration of the therapy to the subject; the second time point is after the first time point and after the administration of the therapy to the subject.
- a first score is generated at the first time point, and a second score is generated at the second time point.
- the second score is significantly decreased as compared to the first score, the subject is considered to be responsive to the therapy.
- the present disclosure provides a method for evaluating the response of a subject having a colon cancer to a first therapy, the method comprising: (1 ) at a first time point:
- DHCR7, HMOX2, MCM2, PDXK, POP7, SWOP, SNRPA, SORD, STOML2, and UMPS to the expression level of the housekeeping gene, thereby obtaining a normalized expression level of each of ADRMl, CDK4, COMT, DHCR7, HMOX2, MCM2, PDXK, POP7, SWOP, SNRPA,
- each normalized expression level into an algorithm to generate a first score; (2) at a second time point, wherein the second time point is after the first time point and after the administration of the therapy to the subject: (a) determining the expression level of at least 14 biomarkers from a second test sample from the subject by contacting the second test sample with a plurality of agents specific to detect the expression of the at least 14 biomarkers, wherein the 14 biomarkers comprise ADRMl, CDK4, COMT, DHCR7, HMOX2, MCM2, PDXK, POP7, SIOOP, SNRPA, SORD, STOML2, UMPS, and the housekeeping gene; (b) normalizing the expression level of each of ADRMl, CDK4, COMT, DHCR7, HMOX2, MCM2, PDXK, POP7, SIOOP, SNRPA, SORD, STOML2, and UMPS to the expression level of the housekeeping gene, thereby obtaining
- step (4) can comprise producing a report, wherein the report identifies that the subject is responsive to the first therapy when the second score is significantly decreased as compared to the first score or identifies that the subject is not responsive to the first therapy when the second score is not significantly decreased as compared to the first score.
- the second score is significantly decreased as compared to the first score when the second score is at least about 10% less than the first score, or at least about 20% less than the first score, or at least about 25% less than the first score, at least about 40% less than the first score, at least about 50% less than the first score, or at least about 60% less than the first score, or at least about 70% less than the first score, or at least about 75% less than the first score, or at least about 80% less than the first score, or at least about 90% less than the first score, or at least about 95% less than the first score or at least about 95% less than the first score.
- a first time point can be prior to the administration of a first therapy to the subject
- a first time point can be after the administration of a first therapy to the subject.
- the preceding method can further comprise continuing to administer the first therapy to the subject when the second score is significantly decreased as compared to the first score.
- the preceding method can further comprise discontinuing administration of the first therapy to the subject when the second score is not significantly decreased as compared to the first score.
- the preceding method can further comprise administering a second therapy to the subject when the second score is not significantly decreased as compared to the first score.
- a predetermined cutoff value can be about 50% on a scale of 0-100%.
- a predetermined cutoff value can be about 60% on a scale of 0-100%.
- a predetermine cutoff value can be about 10%, or about 20%, or about 30%, or about 40%, or about 70%, or about 80%, or about 90% on a scale of 0-100%.
- a test sample can be any biological fluid obtained from the subject.
- a test sample can be blood, serum, plasma, neoplastic tissue or any combination thereof.
- the test sample is blood.
- the test sample is serum.
- the test sample is plasma.
- a housekeeping gene can comprise, but is not limited to, MRPL19, PSMC4, SF3A1, PIJM1, ACTB, GAPD, GUSB, RPIJ>0, TFRC, MORF4L1, 18S, PPIA, PGK1, RPL13A, B2M, YWHAZ, SDHA, and HPRTl.
- the housekeeping gene is MORF4L1.
- the methods of the present disclosure can have a sensitivity of at least about 50%, or at least about 60%, or at least about 70%, or at least about 75%, or at least about 80%, or at least about 85%, or at least about 90%, or at least about 95%, or at least about 99%.
- the methods of the present disclosure can have a sensitivity of greater than about 50%, or greater than about 60%, or greater than about 70%, or greater than about 75%, or greater than about 80%, or greater than about 85%, or greater than about 90%, or greater than about 95%, or greater than about 99%.
- the methods of the present disclosure can have a specificity of at least about 50%, or at least about 60%, or at least about 70%, or at least about 75%, or at least about 80%, or at least about 85%, or at least about 90%, or at least about 95%, or at least about 99%.
- the methods of the present disclosure can have a specificity of greater than about 50%, or greater than about 60%, or greater than about 70%, or greater than about 75%, or greater than about 80%, or greater than about 85%, or greater than about 90%, or greater than about 95%, or greater than about 99%.
- the methods of the present disclosure can have an accuracy of at least about 50%, or at least about 60%, or at least about 70%, or at least about 75%, or at least about 80%, or at least about 85%, or at least about 90%, or at least about 95%, or at least about 99%.
- the methods of the present disclosure can have an accuracy of greater than about 50%, or greater than about 60%, or greater than about 70%, or greater than about 75%, or greater than about 80%, or greater than about 85%, or greater than about 90%, or greater than about 95%, or greater than about 99%.
- a predetermined cutoff value can be derived from a plurality of reference samples obtained from subjects not having or not diagnosed with a neoplastic disease.
- the neoplastic disease can be colon cancer.
- the plurality of reference samples can comprise about 2-500, 2-200, 10-100, or 20-80 reference samples. Each reference sample produces a score using the algorithm, and the first predetermined cutoff value can be an arithmetic mean of these scores.
- Each reference sample can be blood, serum, plasma, or non-neoplastic tissue. In some aspects, each reference sample is blood. In some aspects, each reference sample is of the same type as the test sample.
- Each of the biomarkers disclosed herein may have one or more transcript variants.
- the methods disclosed herein can measure the expression level of any one of the transcript variants for each biomarker.
- the expression level can be measured in a number of ways, including, but not limited to: measuring the mRNA encoded by the selected genes; measuring the amount of protein encoded by the selected genes; and measuring the activity of the protein encoded by the selected genes.
- a biomarker can be RNA, cDNA, protein or any combination thereof.
- the biomarker is RNA
- the RNA can be reverse transcribed to produce cDNA (such as by RT-PCR), and the produced cDNA expression level can be detected.
- the expression level of a biomarker can be detected by forming a complex between the biomarker and a labeled probe or primer.
- the biomarker is RNA or cDNA
- the RNA or cDNA can be detected by forming a complex between the RNA or cDNA and a labeled nucleic acid probe or primer.
- the complex between the RNA or cDNA and the labeled nucleic acid probe or primer can be a hybridization complex.
- gene expression can be detected by microarray analysis. Differential gene expression can also be identified, or confirmed using the microarray technique. Thus, the expression profile biomarkers can be measured in either fresh or fixed tissue, using microarray technology.
- polynucleotide sequences of interest including cDNAs and oligonucleotides
- the arrayed sequences are then hybridized with specific DNA probes from cells or tissues of interest.
- the source of mRNA typically is total RNA isolated from a biological sample, and corresponding normal tissues or cell lines may be used to determine differential expression.
- PCR amplified inserts of cDNA clones are applied to a substrate in a dense array.
- at least 10,000 nucleotide sequences are applied to the substrate.
- the microarrayed genes, immobilized on the microchip at 10,000 elements each, are suitable for hybridization under stringent conditions.
- Fluorescently labeled cDNA probes may be generated through incorporation of fluorescent nucleotides by reverse transcription of RNA extracted from tissues of interest. Labeled cDNA probes applied to the chip hybridize with specificity to each spot of DNA on the array. After stringent washing to remove non-specifically bound probes, the microarray chip is scanned by a device such as, confocal laser microscopy or by another detection method, such as a CCD camera. Quantitation of
- the biomarkers can be detected in a biological sample using qRT-PCR.
- the first step in gene expression profiling by RT-PCR is extracting RNA from a biological sample followed by the reverse transcription of the RNA template into cDNA and amplification by a PCR reaction.
- the reverse transcription reaction step is generally primed using specific primers, random hexamers, or oligo-dT primers, depending on the goal of expression profiling.
- the two commonly used reverse transcriptases are avilo myeloblastosis virus reverse transcriptase (AMV-RT) and Moloney murine leukemia virus reverse transcriptase (MLV-RT).
- the protein when the biomarker is a protein, the protein can be detected by forming a complex between the protein and a labeled antibody.
- the label can be any label for example a fluorescent label, chemiluminescence label, radioactive label, etc.
- Exemplary methods for protein detection include, but are not limited to, enzyme immunoassay (EI A), radioimmunoassay (RIA), Western blot analysis and enzyme linked immunoabsorbant assay (ELISA).
- EI A enzyme immunoassay
- RIA radioimmunoassay
- ELISA enzyme linked immunoabsorbant assay
- the biomarker can be detected in an ELISA, in which the biomarker antibody is bound to a solid phase and an enzyme-antibody conjugate is employed to detect and/or quantify biomarker present in a sample.
- a western blot assay can be used in which solubilized and separated biomarker is bound to nitrocellulose paper. The combination of a highly specific, stable liquid conjugate with
- the methods described herein can have a specificity, sensitivity, and/or accuracy of at least 75%, 80%, 85%, 90%, 91%, 92%, 93%, 94%, 95%, 96%, 97%, 98%, or 99%.
- a labeled probe, a labeled primer, a labeled antibody or a labeled nucleic acid can comprise a fluorescent label.
- the algorithm analyzes the data (i.e., expression levels) and then assigns a score.
- the algorithm can be a machine-learning algorithm.
- Exemplary algorithms that can be used in the methods disclosed herein can include, but are not limited to, XGBoost (XGB), Random Forest (RF), glmnet, cforest, Classification and Regression Trees for Machine Learning (CART), treebag, K-Nearest Neighbors (kNN), neural network (nnet), Support Vector Machine radial (SVM-radial), Support Vector Machine linear (SVM- linear), Naive Bayes (NB), multilayer perceptron (mlp) or any combination thereof.
- the algorithm can be XGB (also called XGBoost).
- XGB is an implementation of gradient boosted decision trees designed for speed and performance.
- a therapy can comprise anticancer therapy, surgery, chemotherapy, targeted drug therapy, radiation therapy, immunotherapy, or any combination thereof.
- surgery can comprise removing a polyp during a colonoscopy, endoscopic mucosal resection, a partial colectomy, an ostomy, removing at least one cancerous lesion from the liver, or any combination thereof.
- anti-cancer therapy can comprise anti-colon cancer therapy.
- chemotherapy can comprise FOLFOX, FOLFIRI, a combination of 5-FU and leucovorin, capecitabine, irinotecan, CapeOx or any combination thereof.
- targeted drug therapy can comprise bevacizumab, cetuximab, panitumumab, regorafenib, a combination of trifluridine and tipiracil, an EGFR TKI inhibitor or any combination thereof.
- immunotherapy can comprise pembrolizumab, nivolumab or a combination of pembrolizumab and nivolumab.
- a minimally invasive approach to surgery can be used to remove the cancer.
- the polyp can be removed during a colonoscopy.
- Endoscopic mucosal resection can be performed to remove larger polyps.
- Polyps that cannot be removed during a colonoscopy may be removed using laparoscopic surgery.
- partial colectomy can be performed to remove the part of the colon that contains the cancer, along with a margin of normal tissue on either side of the cancer.
- an ostomy can be performed to create an opening in the wall of the abdomen from a portion of the remaining bowel for the elimination of stool into a bag that fits securely over the opening. Lymph node removal can also be performed.
- an operation to relieve a blockage of the colon or other conditions can also be performed. In specific cases where the cancer has spread only to the liver, surgery to remove the cancerous lesion from the liver can be performed.
- chemotherapies either the FOLFOX (5-FU, leucovorin, and oxaliplatin) or CapeOx (capecitabine and oxaliplatin) regimens are used most often, but some patients may get 5-FU with leucovorin or capecitabine alone based on their age and health needs.
- Irinotecan can also be used as a chemotherapeutic agent for treating a colon cancer.
- Targeted drug therapies target specific malfunctions that allow cancer cells to grow. These therapies include, but are not limited to, bevacizumab, cetuximab, panitumumab, ramucirumab, regorafenib, ziv-aflibercept, a combination of trifluridine and tipiracil, and an EGFR TKI inhibitor.
- Immunotherapies for colon cancer include, but are not limited to, pembrolizumab (Keytruda®) and nivolumab (Opdivo®).
- nucleic acid molecule As used herein, the terms “polynucleotide” and “nucleic acid molecule” are used interchangeably to mean a polymeric form of nucleotides of at least 10 bases or base pairs in length, either ribonucleotides or deoxynucleotides or a modified form of either type of nucleotide, and is meant to include single and double stranded forms of DNA.
- a nucleic acid molecule or nucleic acid sequence that serves as a probe in a microarray analysis preferably comprises a chain of nucleotides, more preferably DNA and/or RNA.
- nucleic acid molecule or nucleic acid sequence comprises other kinds of nucleic acid structures such a for instance a DNA/RNA helix, peptide nucleic acid (PNA), locked nucleic acid (LNA) and/or a ribozyme.
- PNA peptide nucleic acid
- LNA locked nucleic acid
- nucleic acid molecule also encompasses a chain comprising non-natural nucleotides, modified nucleotides and/or non-nucleotide building blocks which exhibit the same function as natural nucleotides.
- hybridize As used herein, the terms “hybridize,” “hybridizing”, “hybridizes,” and the like, used in the context of polynucleotides, are meant to refer to conventional hybridization conditions, such as hybridization in 50% formamide/6XSSC/0.1% SDS/100 ⁇ g/ml ssDNA, in which temperatures for hybridization are above 37 degrees centigrade and temperatures for washing in 0.1
- XSSC/0.1% SDS are above 55 degrees C, and preferably to stringent hybridization conditions.
- normalization refers to the expression of a differential value in terms of a standard value to adjust for effects which arise from technical variation due to sample handling, sample preparation, and measurement methods rather than biological variation of biomarker concentration in a sample.
- the absolute value for the expression of the protein can be expressed in terms of an absolute value for the expression of a standard protein that is substantially constant in expression.
- diagnosis also encompass the terms “prognosis” and “prognostics”, respectively, as well as the applications of such procedures over two or more time points to monitor the diagnosis and/or prognosis over time, and statistical modeling based thereupon.
- diagnosis includes: a. prediction (determining if a patient will likely develop aggressive disease (hyperproliferative/invasive)), b. prognosis (predicting whether a patient will likely have a better or worse outcome at a pre-selected time in the future), c.
- therapy selection d. therapeutic drug monitoring, and e. relapse monitoring.
- TP true positives
- TN true negatives
- FP false negatives
- FN false negatives
- biological sample refers to any sample of biological origin potentially containing one or more biomarkers.
- biological samples include tissue, organs, or bodily fluids such as whole blood, plasma, serum, tissue, lavage or any other specimen used for detection of disease.
- a subject refers to a mammal, preferably a human.
- a subject can have at least one colon cancer symptom.
- a subject can have a predisposition or familial history for developing a colon cancer.
- a subject can also have been previously diagnosed with a colon cancer and is tested for cancer recurrence.
- Treating" or “treatment” as used herein with regard to a condition may refer to preventing the condition, slowing the onset or rate of development of the condition, reducing the risk of developing the condition, preventing or delaying the development of symptoms associated with the condition, reducing or ending symptoms associated with the condition, generating a complete or partial regression of the condition, or some combination thereof.
- Biomarker levels may change due to treatment of the disease.
- the changes in biomarker levels may be measured by the present disclosure. Changes in biomarker levels may be used to monitor the progression of disease or therapy.
- "Altered”, “changed” or “significantly different” refer to a detectable change or difference from a reasonably comparable state, profile, measurement, or the like. Such changes may be all or none. They may be incremental and need not be linear. They may be by orders of magnitude.
- a change may be an increase or decrease by 5%, 10%, 20%,30%, 40%, 50%, 60%, 70%, 80%, 90%, 95%, 99%, 100%, or more, or any value in between 0% and 100%.
- the change may be 1-fold, 1.5- fold, 2-fold, 3 -fold, 4-fold, 5-fold or more, or any values in between 1-fold and five-fold.
- the change may be statistically significant with a p value of 0.1, 0.05, 0.001, or 0.0001.
- stable disease refers to a diagnosis for the presence of a colon cancer, however the colon cancer has been treated and remains in a stable condition, i.e. one that that is not progressive, as determined by imaging data and/or best clinical judgment.
- progressive disease refers to a diagnosis for the presence of a highly active state of a colon cancer, i.e. one has not been treated and is not stable or has been treated and has not responded to therapy, or has been treated and active disease remains, as determined by imaging data and/or best clinical judgment.
- neoplastic disease refers to any abnormal growth of cells or tissues being either benign (non-cancerous) or malignant (cancerous).
- the neoplastic disease can be a colon cancer.
- Neoplastic tissue refers to a mass of cells that grow abnormally.
- non-neoplastic tissue refers to a mass of cells that grow normally.
- immunotherapy can refer to activating immunotherapy or suppressing immunotherapy.
- activating immunotherapy refers to the use of a therapeutic agent that induces, enhances, or promotes an immune response, including, e.g., a T cell response
- suppressing immunotherapy refers to the use of a therapeutic agent that interferes with, suppresses, or inhibits an immune response, including, e.g., a T cell response.
- Activating immunotherapy may comprise the use of checkpoint inhibitors.
- Activating immunotherapy may comprise administering to a subject a therapeutic agent that activates a stimulatory checkpoint molecule.
- Stimulatory checkpoint molecules include, but are not limited to, CD27, CD28, CD40, CD122, CD137, OX40, (HTR and ICOS.
- Therapeutic agents that activate a stimulatory checkpoint molecule include, but are not limited to, MEDI0562, TGN1412, CDX-1127, lipocalin.
- antibody herein is used in the broadest sense and encompasses various antibody structures, including but not limited to monoclonal antibodies, polyclonal antibodies, multispecific antibodies (e.g., bispecific antibodies), and antibody fragments so long as they exhibit the desired antigen-binding activity.
- An antibody that binds to a target refers to an antibody that is capable of binding the target with sufficient affinity such that the antibody is useful as a diagnostic and/or therapeutic agent in targeting the target
- the extent of binding of an anti-target antibody to an unrelated, non-target protein is less than about 10% of the binding of the antibody to target as measured, e.g., by a radioimmunoassay (RIA) or biacore assay.
- RIA radioimmunoassay
- an antibody that binds to a target has a dissociation constant (Kd) of ⁇ 1 ⁇ , ⁇ 100 nM, ⁇ 10 nM, ⁇ 1 nM, ⁇ 0.1 nM, ⁇ 0.01 nM, or ⁇ 0.001 nM (e.g. 108 M or less, e.g. from 108 M to 1013 M, e.g., from 109 M to 1013 M).
- Kd dissociation constant
- an anti-target antibody binds to an epitope of a target that is conserved among different species.
- a “blocking antibody” or an “antagonist antibody” is one that partially or fully blocks, inhibits, interferes, or neutralizes a normal biological activity of the antigen it binds.
- an antagonist antibody may block signaling through an immune cell receptor (e.g., a T cell receptor) so as to restore a functional response by T cells (e.g., proliferation, cytokine production, target cell killing) from a dysfunctional state to antigen stimulation.
- an immune cell receptor e.g., a T cell receptor
- an "agonist antibody” or “activating antibody” is one that mimics, promotes, stimulates, or enhances a normal biological activity of the antigen it binds.
- Agonist antibodies can also enhance or initiate signaling by the antigen to which it binds.
- agonist antibodies cause or activate signaling without the presence of the natural ligand.
- an agonist antibody may increase memory T cell proliferation, increase cytokine production by memory T cells, inhibit regulatory T cell function, and/or inhibit regulatory T cell suppression of effector T cell function, such as effector T cell proliferation and/or cytokine production.
- an "antibody fragment” refers to a molecule other than an intact antibody that comprises a portion of an intact antibody that binds the antigen to which the intact antibody binds.
- Administering chemotherapy to a subject can comprise administering a therapeutically effective dose of at least one chemotherapeutic agent.
- Chemotherapeutic agents include, but are not limited to, 13-cis-Retinoic Acid, 2-CdA, 2-Chlorodeoxyadenosine, 5-Azacitidine, 5-
- Fluorouracil 5-FU, 6-Mercaptopurine, 6-MP, 6-TG, 6-Thioguanine, Abemaciclib, Abiraterone acetate, Abraxane, Accutane, Actinomycin-D, Adcetris, Ado-Trastuzumab Emtansine,
- Carfilzomib Carmustine, Carmustine Wafer, Casodex, CCI-779, Ccnu, Cddp, Ceenu, Ceritinib,
- Cerubidine cetuximab, Chlorambucil, Cisplatin, Citrovorum Factor, Cladribine, Clofarabine,
- Cyclophosphamide Cyramza, Cytadren, Cytarabine, Cytarabine Liposomal, Cytosar-U,
- Etoposide Etoposide Phosphate, Eulexin, Everolimus, Evista, Exemestane, Fareston, Farydak,
- Faslodex Femara, Filgrastim, Firmagon, Floxuridine, Fludara, Fludarabine, Fluoroplex,
- Fluorouracil Fluorouracil (cream), Fluoxymesterone, Flutamide, Folinic Acid, Foloryn, Fudr, Fulvestrant, G-Csf, Gazyva, Gefitinib, Gemcitabine, Gemtuzumab ozogamicin, Gemzar, Gilotrif,
- Gleevec Gleostine, Gliadel Wafer, Gm-Csf, Goserelin, Granix, Granulocyte - Colony
- Stimulating Factor Granulocyte Macrophage Colony Stimulating Factor, Halaven, Halotestin,
- Iclusig Idamycin, Idarubicin, Idelalisib, Idhifa, Ifex, IFN-alpha, Ifosfamide, IL-11, JL-2,
- Leukeran Leukine, Leuprolide, Leurocristine, Leustatin, Liposomal Ara-C, Liquid Pred,
- Methotrexate Methotrexate Sodium, Methylprednisolone, Meticorten, Midostaurin, Mitomycin,
- Mitomycin-C Mitoxantrone, M-Prednisol, MTC, MTX, Mustargen, Mustine, Mutamycin,
- Neulasta Neumega, Neupogen, Nexavar, Nilandron, Nilotinib, Nilutamide, Ninlaro, Nipent,
- Niraparib Nitrogen Mustard, Nivolumab, Nolvadex, Novantrone, Nplate, Obinutuzumab,
- Octreotide Octreotide Acetate, Odomzo, Ofatumumab, Olaparib, Olaratumab, Omacetaxine,
- Pomalidomide Pomalys ⁇ Ponatinib, Portrazza, Pralatrexate, Prednisolone, Prednisone, Prelone,
- Procarbazine Procrit, Proleukin, Prolia, Prolifeprospan 20 with Carmustine Implant, Promacta,
- Clinical benefit can be measured by assessing various endpoints, e.g., inhibition, to some extent, of disease progression, including slowing down and complete arrest; reduction in the number of disease episodes and/or symptoms; reduction in lesion size; inhibition (i.e., reduction, slowing down or complete stopping) of disease cell infiltration into adjacent peripheral organs and/or tissues; inhibition (i.e.
- cancer refers to or describe the physiological condition in mammals that is typically characterized by unregulated cell growth. Included in this definition are benign and malignant cancers. Examples of cancer include but are not limited to, carcinoma, lymphoma, blastema, sarcoma, and leukemia. More particular examples of such cancers include adrenocortical carcinoma, bladder urothelial carcinoma, breast invasive carcinoma, cervical squamous cell carcinoma, endocervical adenocarcinoma, cholangiocarcinoma, colon
- adenocarcinoma lymphoid neoplasm diffuse large B-cell lymphoma, esophageal carcinoma, glioblastoma multiforme, head and neck squamous cell carcinoma, kidney chromophobe, kidney renal clear cell carcinoma, kidney renal papillary cell carcinoma, acute myeloid leukemia, brain lower grade glioma, liver hepatocellular carcinoma, lung adenocarcinoma, lung squamous cell carcinoma, mesothelioma, ovarian serous cystadenocarcinoma, pancreatic adenocarcinoma, pheochromocytoma, paraganglioma, prostate adenocarcinoma, rectum adenocarcinoma, sarcoma, skin cutaneous melanoma, stomach adenocarcinoma, testicular germ cell tumors, thyroid carcinoma, thymoma, uterine carcinosarcoma, uve
- neuroendocrine cancer non-small cell lung cancer (NSCLC), small cell lung cancer, thyroid cancer, endometrial cancer, biliary cancer, esophageal cancer, anal cancer, salivary, cancer, vulvar cancer or cervical cancer.
- NSCLC non-small cell lung cancer
- small cell lung cancer thyroid cancer
- endometrial cancer biliary cancer
- esophageal cancer anal cancer
- salivary cancer
- vulvar cancer vulvar cancer or cervical cancer.
- tumor refers to all neoplastic cell growth and proliferation, whether malignant or benign, and all pre- cancerous and cancerous cells and tissues.
- cancer refers to all neoplastic cell growth and proliferation, whether malignant or benign, and all pre- cancerous and cancerous cells and tissues.
- the score exhibited an area under the curve (AUC) of 0.90 (training) and 0.86 (test set).
- the metrics are: sensitivity: 85.3-87.5% and specificity: 75-83.3%.
- a decision curve analysis was used to quantify the clinical benefit of the diagnostic test (FIGs. 4A-4B).
- the ColoTest exhibited >50% standardized predictive benefit up to a risk threshold of 80%.
- the probit risk assessment plot identified a ColoTest score >50% was 75% accurate for predicting colon cancer in a blood sample. This was increased to >80% at a ColoTest score >60%. The tool can therefore accurately differentiate between controls and colon cancer disease.
- ROC analysis identified the ColoTest had an AUC: 0.97 for differentiating stable from progressive disease.
- the z-statistic for differentiating controls was 20.6.
- Further evaluation of this cohort identified that patients who exhibited disease progression despite therapy exhibited higher scores than those responding to therapy (FIG. 8).
- Therapies included bevacizumab, chemotherapy and EGFR TKI inhibitors. The tool can therefore accurately identify treatment failure in colon cancer disease.
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Priority Applications (13)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| DK19703616.3T DK3743534T3 (da) | 2018-01-22 | 2019-01-22 | Fremgangsmåde til påvisning af coloncancer og behandlingsovervågning |
| ES19703616T ES2917629T3 (es) | 2018-01-22 | 2019-01-22 | Métodos para la detección del cáncer de colon y monitorización del tratamiento |
| PL19703616.3T PL3743534T3 (pl) | 2018-01-22 | 2019-01-22 | Sposoby wykrywania nowotworu okrężnicy i monitorowania leczenia |
| AU2019209436A AU2019209436B2 (en) | 2018-01-22 | 2019-01-22 | Methods for colon cancer detection and treatment monitoring |
| MX2020007771A MX2020007771A (es) | 2018-01-22 | 2019-01-22 | Metodos para la supervision de la deteccion y el tratamiento de cancer de colon. |
| BR112020014737-0A BR112020014737A2 (pt) | 2018-01-22 | 2019-01-22 | Métodos para detecção e tratamento do câncer de cólon com monitoramento |
| SG11202006974WA SG11202006974WA (en) | 2018-01-22 | 2019-01-22 | Methods for colon cancer detection and treatment monitoring |
| EP19703616.3A EP3743534B1 (en) | 2018-01-22 | 2019-01-22 | Methods for colon cancer detection and treatment monitoring |
| CA3088754A CA3088754A1 (en) | 2018-01-22 | 2019-01-22 | Methods for colon cancer detection and treatment monitoring |
| IL276089A IL276089B2 (en) | 2018-01-22 | 2019-01-22 | Methods for colon cancer detection and treatment monitoring |
| CN201980020784.5A CN112004945B (zh) | 2018-01-22 | 2019-01-22 | 用于结肠癌检测和治疗监控的方法 |
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| WO2021072035A1 (en) | 2019-10-10 | 2021-04-15 | Liquid Biopsy Research LLC | Compositions, methods and kits for biological sample and rna stabilization |
| US12305240B2 (en) | 2018-01-22 | 2025-05-20 | Liquid Biopsy Research LLC | Methods for colon cancer detection and treatment |
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| US11809379B2 (en) * | 2019-11-19 | 2023-11-07 | International Business Machines Corporation | Storage tiering for deduplicated storage environments |
| CN111157745A (zh) * | 2020-01-17 | 2020-05-15 | 上海交通大学 | 人snrpa蛋白在肺癌复发或转移监测中的用途 |
| CN115475247B (zh) * | 2021-06-16 | 2024-02-20 | 厦门大学 | β2-微球蛋白或其抑制剂的制药用途 |
| KR102823777B1 (ko) * | 2021-10-15 | 2025-06-23 | 한국과학기술원 | 인공지능을 이용하여 유전체 염기서열로 질환 진단 및 예측 방법, 그 시스템 |
| CN113921079B (zh) * | 2021-12-06 | 2022-03-18 | 四川省肿瘤医院 | 基于免疫相关基因的msi预测模型构建方法 |
| CN121137146B (zh) * | 2025-07-28 | 2026-04-07 | 首钢医院有限公司 | 检测基因组合物的试剂在制备预测结直肠癌患者远端切缘长度的产品中的应用 |
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
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| US12305240B2 (en) | 2018-01-22 | 2025-05-20 | Liquid Biopsy Research LLC | Methods for colon cancer detection and treatment |
| WO2021072035A1 (en) | 2019-10-10 | 2021-04-15 | Liquid Biopsy Research LLC | Compositions, methods and kits for biological sample and rna stabilization |
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