CN111321221B - Composition, microarray and computer system for predicting risk of recurrence after regional resection of rectal cancer - Google Patents
Composition, microarray and computer system for predicting risk of recurrence after regional resection of rectal cancer Download PDFInfo
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Abstract
The invention discloses a composition, a microarray and a computer system for predicting the risk of recurrence after a local resection surgery for rectal cancer. The invention adopts a microarray chip mode, screens out specific marker genes for postoperative recurrence of rectal cancer aiming at Chinese population, draws out a specific model for evaluating postoperative recurrence of rectal cancer, customizes the microarray chip for the marker genes for postoperative recurrence of rectal cancer according to research results, and is used for clinical diagnosis and evaluation of postoperative recurrence evaluation of rectal cancer patients of Chinese population.
Description
Technical Field
The invention relates to the field of biomedicine, in particular to a composition, a microarray and a computer system for predicting recurrence risk after rectal cancer local resection.
Background
Colorectal cancer (CRC) is a malignant tumor originating from colorectal mucosal epithelium, is the third most common malignant tumor worldwide, and is the fourth most common cause of cancer mortality worldwide. More than 25 million new cases of colorectal cancer and about 14 million death cases are caused each year in China, and the new cases and the death cases account for 20 percent of the colorectal cancer cases in the same period all over the world. Given the low rectal location, the precancerous lesions they can remove are not complete and the risk of disease recurrence is extremely high. Therefore, establishing an effective rectal cancer risk assessment method to reduce the morbidity and mortality of rectal cancer in China is a major clinical problem which is difficult to solve.
The early-middle colorectal cancer patients usually adopt surgical excision of focuses, so that the further development and the spread of tumors are effectively controlled. Colorectal cancer often recurs after two years of operation due to hematogenous metastasis, and postoperative adjuvant chemotherapy aiming at eliminating in vivo minimal residual lesions can reduce the recurrence rate and improve the long-term survival rate of patients. Therefore, postoperative patients need to pay close attention to the metastasis and recurrence of tumors and adopt an effective diagnosis and treatment scheme to prevent and treat the disease progression in time. Common methods of diagnosing rectal cancer include: fecal occult blood test, digital rectal examination, proctoscope, sigmoidoscope, fibrocolonoscope, imaging exam, and detection of CEA carcinoembryonic antigen. These screening methods have their own limitations, low detection sensitivity or not easy frequent detection, etc. In view of the rapid development of current high-throughput detection techniques, studies based on the detection of blood biomarkers are also endless. First, extracorporeal blood tests are safe and minimally invasive. Second, there is no need for dietary restriction, colon cleansing or sedation. Third, sample collection and processing procedures may be easier and more convenient. Furthermore, no microbial community may degrade the biomarker or interfere with the analysis. Therefore, the recurrence risk of the rectal cancer can be predicted in time through peripheral blood detection, and the detection accuracy is improved, so that the life is saved.
The most studied is the methylation of septin9 in the screening and diagnosis of colorectal cancer. The sensitivity of the colorectal cancer screened by septin9 is about 70%, and the specificity is about 90%. However, DNA microarray technology can simultaneously quantify the expression of thousands of genes and can better explore the complex biological mechanisms leading to rectal tumorigenesis and progression than a single gene marker. Reports of the use of DNA microarray technology to identify blood-based gene expression profiles for CRC detection are emerging. Han and colleagues report the colorectal cancer expression characteristics of the 5 gene, the detection sensitivity is 88 percent, and the specificity is 64 percent; marshall et al published colorectal cancer 7 gene expression characteristics, with a detection sensitivity of 72% and a specificity of 70%. Rosenthal et al also reported a panel of 202 genes associated with colorectal cancer expression with a detection sensitivity of 90% and a specificity of 88%.
However, the current research report of colorectal cancer is mainly based on data of European and American populations, and the reported data of Asian populations or Chinese populations is not detailed.
Disclosure of Invention
In view of the current situation, the invention aims at the screening of the relevant postoperative recurrence marker genes of the rectal cancer patients in the Chinese population, establishes a corresponding postoperative recurrence evaluation model and further determines a specific postoperative recurrence detection scheme of the colorectal cancer patients. The present invention has been accomplished at least based on this. Specifically, the present invention includes the following.
In a first aspect of the invention, there is provided a composition for predicting the risk of recurrence following a regional rectal cancer resection procedure comprising an oligonucleotide that specifically binds to a partially contiguous sequence of a gene selected from the group consisting of WDR43, RAB31, FASN, TYMS, SNX2, DAP3, MRPS18C, FANCL, cidep, HNRNPH1, and CMSS 1.
In certain embodiments, a contiguous sequence of the invention is a conserved sequence of the corresponding gene.
In certain embodiments, the oligonucleotides of the invention are designed to be capable of fixedly binding to a substrate at one end thereof, and at least part of the sequence is capable of specifically binding to a partially contiguous sequence of a gene selected from the group consisting of WDR43, RAB31, FASN, TYMS, SNX2, DAP3, MRPS18C, FANCL, cidep, HNRNPH1, and CMSS1, thereby enabling capture of the desired gene in the sample.
In a second aspect of the present invention, there is provided a microarray for predicting risk of recurrence after radical rectal cancer resection, comprising the composition of the present invention and a substrate having a surface with a plurality of sites independently disposed from each other.
Preferably, each site has a reactive functional group capable of binding to the oligonucleotide; or each site binds to a separate one of the oligonucleotides.
Preferably, the sites are regularly arranged in such a way that the spacing between adjacent sites is in the range of 0.1-20 μm, the area of each site being less than 1 μm 2 。
Preferably, the oligonucleotide comprises a repeat sequence of a plurality of target regions, and the sequence length of the oligonucleotide is 50-500 nt.
In a third aspect of the present invention, there is provided a computer system for predicting risk of recurrence after a partial resection of rectal cancer, comprising:
a. an input device for receiving object data, wherein the object data comprises gene detection data from a microarray of the invention;
b. a memory having a database for storing at least the genetic testing data;
c. a processor in communication with the memory and configured to:
calculating an evaluation value F (x) by an algorithm model by using the gene detection data; and
d. output means configured to transmit a notification according to a result of the determination of the evaluation value f (x).
Preferably, the algorithm model is:
F(x)＝29.3341-0.7416*WDR43+0.9450*RAB31+2.9083*FASN-0.5904*TYMS-3.0449*SNX2-2.5533*DAP3+3.7309*pt+1.9524*MRPS18C+1.0107*FANCL-6.5343*CIDECP-1.1939*HNRNPH1+0.1941*CMSS1。
preferably, the processor is further configured to: obtaining a value of P (x) by the following formula, and comparing the obtained value of P (x) with a reference value of 0.37, wherein the risk of recurrence after the rectal cancer was judged to be high when P (x) is higher than 0.37, and the risk of recurrence after the rectal cancer was judged to be low when P (x) is lower than or equal to 0.37.
The composition, the microarray and the computer system are developed aiming at the special postoperative recurrence of the Chinese rectal cancer patient population, and can be used for performing model verification on clinical samples of the Chinese rectal cancer patients. The results confirmed that the microarray for postoperative recurrence of rectal cancer of the present invention was used in combination with the postoperative recurrence evaluation model to evaluate postoperative recurrence of rectal cancer, and the postoperative recurrence evaluation thereof had sensitivity of 78% and specificity of 100%.
Drawings
FIG. 1 is a graph of the results of random forest analysis.
Detailed Description
Reference will now be made in detail to various exemplary embodiments of the invention, the detailed description should not be construed as limiting the invention but as a more detailed description of certain aspects, features and embodiments of the invention.
It is to be understood that the terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention. Further, for numerical ranges in this disclosure, it is understood that the upper and lower limits of the range, and each intervening value therebetween, is specifically disclosed. Every smaller range between any stated value or intervening value in a stated range and any other stated or intervening value in a stated range is encompassed within the invention. The upper and lower limits of these smaller ranges may independently be included or excluded in the range.
Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs. Although only preferred methods and materials are described herein, any methods and materials similar or equivalent to those described herein can be used in the practice or testing of the present invention. All documents mentioned in this specification are incorporated by reference herein for the purpose of disclosing and describing the methods and/or materials associated with the documents. In case of conflict with any incorporated document, the present specification will control. Unless otherwise indicated, "%" is percent by weight.
The invention is completed on the basis of the results of the intensive research on the population of Chinese rectal cancer patients. In the research, the group-entering population is strictly screened, all the group-entering population are patients after the colorectal cancer stage II, the experimental group population is known to have postoperative recurrence, and the control group-entering population is patients basically having no postoperative recurrence signs. The experimental group was 68 blood samples from patients who had not relapsed after the colorectal cancer stage II, and the control group was 68 blood samples from patients who had not relapsed after the rectal cancer. RNA was extracted and detected on a microarray chip (Affymetrix Gene Chips HG-U133Plus 2.0). Selecting 500 genes related to the pathogenesis of the rectal cancer to carry out random forest method analysis and establish a postoperative recurrence evaluation model; the accuracy of the model is verified by a leave-one-out cross validation (LOOCV) method, and finally, certain expression difference of 11 genes is found in the population with postoperative recurrence and the population without postoperative recurrence of rectal cancer; and 9 patients in the experimental group and the control group are used for blind test to detect the applicability of the data model and the test accuracy. And finally, customizing the technical scheme of the invention.
[ composition for predicting risk of recurrence after partial rectal cancer excision ]
In a first aspect of the invention, there is provided a composition for predicting the risk of recurrence following a regional rectal cancer resection procedure comprising an oligonucleotide that specifically binds to a partially contiguous sequence of a gene selected from the group consisting of WDR43, RAB31, FASN, TYMS, SNX2, DAP3, MRPS18C, FANCL, cidep, HNRNPH1, and CMSS 1.
In the composition of the present invention, WDR43, RAB31, FASN, TYMS, SNX2, DAP3, MRPS18C, FANCL, CIDECP, HNRNPH1, and CMSS1 are referred to as target genes, respectively. The invention can predict the recurrence risk after the rectal cancer local resection operation by using a smaller number of target genes, and has better effect. The present invention can use the at least one target gene, and in order to improve the accuracy of the prediction result, the present invention preferably uses a plurality of target genes, more preferably all of the target genes.
In general, the target gene specific binding to oligonucleotide of at least one, preferably a plurality of. For example, the oligonucleotide that specifically binds to the WDR43 target gene may be a plurality of oligonucleotides that specifically bind to different contiguous sequences of the gene. The continuous sequence herein is preferably a conserved sequence of the gene. Conserved sequences of these genes are known in the art and can be readily determined by general knowledge.
In certain embodiments, the oligonucleotides of the invention are designed to be capable of fixedly binding to a substrate at one end thereof, and at least part of the sequence is capable of specifically binding to a partially contiguous sequence of a gene selected from the group consisting of WDR43, RAB31, FASN, TYMS, SNX2, DAP3, MRPS18C, FANCL, cidep, HNRNPH1, and CMSS1, thereby enabling capture of the desired gene in the sample. The oligonucleotide is now used to capture the target gene. The sequence length of such oligonucleotides is typically 50-500nt, e.g., 60-400nt, 70-300 nt. Also preferably, the oligonucleotides of the invention comprise a plurality (e.g., 5-15) of repeat sequences of the target region, more preferably, a linker sequence between the repeat sequences. In one embodiment, the oligonucleotide comprises 10 repeats with a linker sequence between adjacent repeats of 5-50 nucleotides in length.
[ microarray for predicting recurrence risk after partial rectal cancer excision surgery ]
In a second aspect of the present invention, a microarray, also called "gene chip" or "microarray chip", for predicting the risk of recurrence after local resection of rectal cancer is a miniaturized, high-throughput gene detection and analysis technique, which mainly comprises hybridizing oligonucleotides or probes on the surface of a solid support with fluorescently pre-labeled sample nucleic acids, and detecting and analyzing hybridization signals to obtain the detection result of the sample.
The microarray of the present invention comprises the composition of the first aspect and a substrate, and the composition is described in detail above and will not be described herein. The substrate is described below.
The substrate of the present invention is made of a commonly used material, preferably in a plate shape. The substrate has a plurality of independently disposed sites on its surface. In certain embodiments, each site has a reactive functional group, such as an aldehyde group, that is capable of binding to an oligonucleotide. In certain embodiments, each site of the invention binds to a separate one of the oligonucleotides of the invention, more preferably, one site binds to one oligonucleotide. In the microarray of the present invention, the sites are regularly arranged in such a manner that the interval between adjacent sites is in the range of 0.1 to 20 μm, and the area of each site is less than 1 μm 2 。
The preparation of the microarray of the present invention can be carried out by a known method. In an exemplary method, which includes designing and synthesizing a probe specific to a gene of interest, a microarray for recurrence risk after partial rectal cancer resection is prepared by spotting the dissolved and diluted probe on a well-known commercially available aldehydized substrate using a gene chip spotter.
The microarray has great advantages in various aspects such as the speed of gene locus detection, the reliability of medium-low expression level detection of target genes and the like, has complete and mature quality control process and analysis means, is quick, simple and convenient, and has high accuracy and sensitivity. Therefore, the method for predicting the recurrence risk after the local rectal cancer resection operation based on the microarray detection technology has good clinical application prospect.
When using microarrays for predicting the risk of recurrence after a partial resection surgery for rectal cancer, the following steps are generally included: (1) extracting total RNA of a sample to be detected, and performing reverse transcription on the total RNA to obtain a product to be hybridized; (2) a step of reacting the product to be hybridized with a microarray under conditions suitable for the reaction; (3) detecting the hybridization signal to obtain gene detection data.
[ computer System ]
In a fourth aspect of the invention, there is provided a computer system for predicting risk of recurrence after radical rectal resection, comprising:
a. an input device for receiving object data, wherein the object data comprises gene detection data from a microarray of the invention;
b. a memory having a database for storing at least the genetic test data;
c. a processor in communication with the memory and configured to:
calculating an evaluation value F (x) by an algorithm model by using the gene detection data; and
d. output means configured to transmit a notification according to a result of the determination of the evaluation value f (x).
In the computer system of the present invention, preferably, the algorithm model is:
F(x)＝29.3341-0.7416*WDR43+0.9450*RAB31+2.9083*FASN-0.5904*TYMS-3.0449*SNX2-2.5533*DAP3+3.7309*pt+1.9524*MRPS18C+1.0107*FANCL-6.5343*CIDECP-1.1939*HNRNPH1+0.1941*CMSS1。
further, a value of p (x) obtained by the following formula, when p (x) is higher than 0.37, the risk of recurrence after rectal cancer was judged to be high, and when p (x) is lower than or equal to 0.37, the risk of recurrence after rectal cancer was judged to be low.
The input device for receiving object data in the computer system of the present invention includes any type of input device. In the present invention, the object data includes at least gene detection data from the microarray of the present invention or obtained based on the microarray. These data include the relative expression levels of the respective target genes, etc.
In the computer system of the present invention, the memory having the database is used for storing at least the above-mentioned gene assaying data. The memory itself is a product commonly used in the art. Preferably, the memory is communicable with the input device, the output device, or the processor, thereby enabling efficient exchange of data between different components. In certain embodiments, the database in memory may be one or more. In the case of multiple databases, the data of each database may be interacted or exchanged, or may be separately interacted or communicated with the processor, thereby ensuring efficient performance of the evaluation. Preferably, the memory has a data management means, thereby efficiently managing various types of different data and improving data utilization efficiency.
In the computer system of the present invention, the processor is in communication with at least the memory and is configured to: the susceptibility index was calculated by an algorithmic model using the gene detection data. Different algorithmic models are of great importance for achieving the objectives of the present invention. Different algorithms yield different results, sometimes not even results. On the basis of a great deal of intensive research, the invention finds that the evaluation value obtained by the algorithm has unexpected sensitivity and accuracy in predicting the recurrence risk after the rectal cancer local resection operation.
Example 1
First, collection of sample
Each patient adopts a PAXgene special RNA blood sample collection tube to collect a blood sample, and RNA extraction is carried out immediately after the sample collection, so that the RNA is prevented from being degraded, and the sample quality is ensured.
Second, extraction of RNA
1. 2.5mL of peripheral blood sample is taken as a blood sample of each patient for RNA extraction, and the extraction kit is MagMAX TM (with the addition of
Blood RNA tube). The operation is carried out according to the kit using instructions strictly;
RNA quality identification: identifying the purity of RNA by using Nanodrop OD260 nm, wherein OD260/280 is required to be 2.0-2.2;
RNA quantification: RNA quantification was performed on an Agilent 2100Bioanalyzer detection instrument using an RNA 6000Nano Lab Chip kit, and the entire procedure was performed exactly as described in the kit instructions.
Hybridization of microarray chips
RNA reverse transcription: reverse transcription kit (SuperScript) was used for 50ng of RNA TM IV Reverse Transcriptase, Invitrogen) to obtain cDNA, the whole process being completely operated according to the kit instructions;
and 2, cDNA purification, namely purifying the reverse transcription product by using a QIAquick PCR purification kit.
Ultrasonic disruption of cDNA: the cDNA was adjusted to a concentration of 10 ng/. mu.l and sonicated using a Covaris sonication instrument according to this procedure: : 150bp, 340s.Peak Power 75, Duty Factor10, Cycle 200, Setpoint 20 ℃. The whole process is completely operated according to the usage instruction of the Covaris ultrasonic interruption instrument.
4. Pre-hybridization cDNA preparation for hybridization to microarray chips: biotin labeling of cDNA before hybridization was carried out according to the instructions of microarray chip (GeneChip U133plus2), and chip hybridization was carried out strictly according to the operating specifications of the instructions.
5. And (4) observing results: after the hybridization of the microarray chip was completed, the results were observed using the GeneChip Scanner 3000.
Fourth, data analysis process
1. Sample assignment: the clinical information of each patient is digitally converted, and the conversion relationship between the clinical information of the patient and the number is shown in the following table.
TABLE 1-conversion correspondence table of clinical information and numerical value
| Clinical information | Defining a value |
| relapse | 1 |
| no relapse | 0 |
| distal | 1 |
| proximal | 0 |
| female | 1 |
| male | 0 |
| >45 | 1 |
| <＝45 | 0 |
2. And (3) data analysis: 500 genes related to the pathogenesis of the rectal cancer are selected, the expression result of the 500 genes is analyzed by a random forest method, and the analysis result is shown in figure 1. The results showed that 11 genes (WDR43, RAB31, FASN, TYMS, SNX2, DAP3, MRPS18C, FANCL, cidep, HNRNPH1, CMSS1) showed different expression patterns in patients in the experimental group versus the control group.
3. Establishing a risk assessment equation: establishing a postoperative recurrence evaluation model according to the analysis result of the random forest method: f (x) ═ 29.3341-0.7416 × WDR43+0.9450 × RAB31+2.9083 × FASn-0.5904 × TYMS-3.0449 × SNX2-2.5533 × DAP3+3.7309 × pt +1.9524 × MRPS18C +1.0107 × FACCL-6.5343 × CIDECP-1.1939 hnRNPH1+0.1941 CMSS 1.
Cutoff value setting: and (x) 1/(1+ exp (-F (x))), and comprehensively analyzing the data of 53 samples, setting a proper cutoff value, and considering that the postoperative rectal cancer recurrence risk is high when P (x) > 0.37.
5. The applicability of the data model and the accuracy of the test were tested by blinding 5 patients with postoperative recurrence (samples 6-10) and 5 patients with no evidence of postoperative recurrence (samples 1-5), respectively. The results are shown in Table 1.
TABLE 1
Example 2
Probes are respectively designed aiming at the 11 genes in the example 1, the sequences of the probes are shown as SEQ ID NO:1-33, and the dissolved and diluted probes are sprayed and solidified on a known commercial hydroformylation substrate by a gene chip spotting instrument to prepare the microarray for the recurrence risk after the local excision surgery of the rectal cancer. The specific preparation of the microarray was performed by boao organism ltd.
TABLE 2 Probe information
This example uses 18 clinical samples to test the applicability of microarray chips. See tables 3 and 4 for specific results.
TABLE 3-9 results of 11 Gene microarray chip application of non-recurrent samples after rectal cancer surgery
| Name of Gene | Sample 1 | Sample 2 | |
Sample No. 4 | |
|
|
Sample 8 | Sample 9 |
| HNRNPH1 | 6.26 | 5.56 | 5.86 | 6.36 | 6.50 | 7.74 | 6.41 | 6.66 | 6.74 |
| SNX2 | 6.86 | 7.04 | 7.20 | 6.85 | 7.22 | 7.41 | 7.03 | 7.33 | 7.36 |
| FASN | 5.54 | 6.24 | 6.86 | 6.15 | 6.31 | 6.75 | 6.25 | 6.05 | 5.66 |
| WDR43 | 6.72 | 6.65 | 6.82 | 6.58 | 6.79 | 7.21 | 6.69 | 7.00 | 6.64 |
| DAP3 | 8.24 | 8.44 | 8.58 | 8.26 | 8.98 | 8.82 | 8.56 | 8.92 | 9.06 |
| RAB31 | 9.28 | 8.76 | 8.51 | 6.61 | 7.47 | 7.30 | 8.16 | 7.50 | 7.62 |
| MRPS18C | 3.44 | 3.92 | 3.82 | 4.04 | 4.27 | 3.96 | 3.76 | 4.39 | 4.21 |
| FANCL | 6.23 | 6.22 | 6.38 | 7.07 | 7.29 | 6.99 | 7.06 | 7.16 | 7.61 |
| CMSS1 | 7.23 | 7.54 | 7.29 | 7.42 | 7.83 | 7.36 | 8.01 | 8.44 | 7.21 |
| TYMS | 6.54 | 6.01 | 5.88 | 6.95 | 7.60 | 8.81 | 5.88 | 7.04 | 6.41 |
| CIDECP | 3.76 | 3.91 | 3.89 | 4.06 | 4.15 | 3.96 | 3.89 | 3.99 | 4.11 |
| |
3 | 3 | 3 | 3 | 3 | 4 | 3 | 3 | 3 |
| F(x) | -2.986 | -1.288 | -0.944 | -3.877 | -6.144 | -3.767 | -2.351 | -5.844 | -7.666 |
| P value | 0.048 | 0.216 | 0.280 | 0.020 | 0.002 | 0.023 | 0.087 | 0.003 | 0.000 |
| Predict | N | N | N | N | N | N | N | N | N |
| Clinical | N | N | N | N | N | N | N | N | N |
TABLE 4-9 application results of 11 gene microarray chips of postoperative recurrence samples of rectal cancer
It will be apparent to those skilled in the art that various modifications and variations can be made in the specific embodiments of the present disclosure without departing from the scope or spirit of the disclosure. Other embodiments will be apparent to those skilled in the art from consideration of the specification. The specification and examples are exemplary only.
SEQUENCE LISTING
<110> tumor hospital of Chinese academy of medical sciences
Yuanma Gene Technology (Beijing) Co., Ltd.
<120> composition, microarray and computer system for predicting risk of recurrence after radical resection of rectal cancer
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catttacagt taccgatgaa cctgtctata ttgacttaac tttgtcagaa aacaaagaag 60
agcctgtcaa gttggc 76
<210> 12
<211> 74
<212> DNA
<213> Artificial sequence
<400> 12
ggaaaggcaa gaagtcaaca ccaaaaccca tccctattct agctgctggt ttttgctcag 60
acaaaatgtc attg 74
<210> 13
<211> 76
<212> DNA
<213> Artificial sequence
<400> 13
aattcctgac ctcaagtgat ctgcccacct tgacctccca aagtgctggg attacagtgc 60
aaggatgatg ctgaaa 76
<210> 14
<211> 76
<212> DNA
<213> Artificial sequence
<400> 14
tggaattcag catgtcaaaa ttcacagctg gctgggcaca gtggctcatg cctgtaatcc 60
cagcactttg gaagcc 76
<210> 15
<211> 77
<212> DNA
<213> Artificial sequence
<400> 15
caggagtttg caaccagcct gggcaacatg gtgaaaacct gtctctacta aaaatacaaa 60
aattagccgg gcacggt 77
<210> 16
<211> 76
<212> DNA
<213> Artificial sequence
<400> 16
ctgccagggc ttatattagg gggtgattct taaaggacat taggattggt gctcagaaat 60
ggttaatcat gctgtg 76
<210> 17
<211> 74
<212> DNA
<213> Artificial sequence
<400> 17
tgctagccag ggccagctgg taccttcttt gccatgagca ttcaagggac ggctaacctt 60
tattgacaat ctat 74
<210> 18
<211> 76
<212> DNA
<213> Artificial sequence
<400> 18
atcgcaaaag tcaggaaaga ggttgtgagc tgattggatt aaagacctgg cacttcagta 60
actcagcacg cttcca 76
<210> 19
<211> 75
<212> DNA
<213> Artificial sequence
<400> 19
attgaaaaac ctcacctact ctcgcgggtc ctcagcgttc tcctgcggaa cctttgaacg 60
gggtactcga gccca 75
<210> 20
<211> 75
<212> DNA
<213> Artificial sequence
<400> 20
aatataagta tgcctggtta agatatcttc cctttgtaga aatgttacat tgggatggat 60
agtggtgctg tcaca 75
<210> 21
<211> 76
<212> DNA
<213> Artificial sequence
<400> 21
gtcttttaca tgaagagatg atttacacct aatagacatt gaatatgata gacatacatg 60
tatatatgta tcagtt 76
<210> 22
<211> 74
<212> DNA
<213> Artificial sequence
<400> 22
ttaggatagt gttgcctgaa gatttacaac tgaagaatgc aagattatta tgtagttggc 60
agctgagaac aata 74
<210> 23
<211> 73
<212> DNA
<213> Artificial sequence
<400> 23
cttagtggat accatcgaat agtacaacag agaatgcagc actctcctga tctaatgagc 60
tttatgatgg agt 73
<210> 24
<211> 74
<212> DNA
<213> Artificial sequence
<400> 24
tgaagatgct tttggaagtt gccttaaaga atagacaaga gctgtatgca ctacctcctc 60
ctccccagtt ctac 74
<210> 25
<211> 75
<212> DNA
<213> Artificial sequence
<400> 25
gaataccacc aagaccagga aaagaagaaa gaagaaaatt actgatgttc ttgcaaaatc 60
agaaccaaaa ccagg 75
<210> 26
<211> 75
<212> DNA
<213> Artificial sequence
<400> 26
gttacctgaa gacctacaga agctgatgaa ggactattat agcagcagac gcttggtgat 60
tgaattagaa gaact 75
<210> 27
<211> 71
<212> DNA
<213> Artificial sequence
<400> 27
gaacctgcca gactcctgtt tcctcaaggc caatgatttg actcacagtc tttcctcata 60
cctaaaagaa a 71
<210> 28
<211> 74
<212> DNA
<213> Artificial sequence
<400> 28
attccctctg ctgacaacca aacgtgtgtt ctggaagggt gttttggagg agttgctgtg 60
gtttatcaag ggat 74
<210> 29
<211> 74
<212> DNA
<213> Artificial sequence
<400> 29
tgctaaagag ctgtcttcca agggagtgaa aatctgggat gccaatggat cccgagactt 60
tttggacagc ctgg 74
<210> 30
<211> 76
<212> DNA
<213> Artificial sequence
<400> 30
cttgggccca gtttatggct tccagtggag gcattttggg gcagaataca gagatatgga 60
atcagattat tcagga 76
<210> 31
<211> 70
<212> DNA
<213> Artificial sequence
<400> 31
cccatcgtta tcactcttcg tagacatgat ccgccactac gtgtccatcc tgctggagag 60
cgacaagaag 70
<210> 32
<211> 70
<212> DNA
<213> Artificial sequence
<400> 32
ctcacccagg aacaagtatc tgacagggga cgaggcaccc acagtccctc tcccataagc 60
ctgccaagaa 70
<210> 33
<211> 71
<212> DNA
<213> Artificial sequence
<400> 33
gattgatgtg gcccgtgtaa cctttgacct gtacaagctg aacccacagg acttcattgg 60
ctgcctgaac a 71
Claims (6)
1. For predicting ChineseComposition for the risk of recurrence after radical resection of rectal cancer in a population, consisting of a peptide binding specifically toWDR43、RAB31、FASN、TYMS、SNX2、DAP3、MRPS18C、FANCL、CIDECP、HNRNPH1AndCMSS1the oligonucleotide of partial continuous sequence of gene, wherein the sequence of the oligonucleotide is shown in SEQ ID NO 1-33.
2. The composition for predicting the risk of recurrence after regional rectal cancer resection in the chinese population according to claim 1, wherein the oligonucleotide is designed to have one end thereof fixedly bound to a substrate and at least a part of the sequence thereof specifically bound toWDR43、RAB31、FASN、TYMS、SNX2、DAP3、MRPS18C、FANCL、CIDECP、HNRNPH1AndCMSS1a partially contiguous sequence of genes, thereby enabling capture of a desired gene in a sample.
3. A microarray for predicting the risk of recurrence after radical resection of rectal cancer in a chinese population comprising the composition of claim 1 or 2 and a substrate having a surface with a plurality of sites disposed independently of each other.
4. The microarray for predicting the risk of recurrence after radical rectal cancer resection surgery in a Chinese population according to claim 3, wherein each site has a reactive functional group capable of binding to the oligonucleotide; or each site binds to a separate one of the oligonucleotides.
5. The microarray for predicting the risk of recurrence after regional rectal cancer resection in the Chinese population according to claim 3 or 4, wherein the sites are regularly arranged in such a way that the interval between adjacent sites is in the range of 0.1-20 μm, and the area of each site is less than 1 μm 2 。
6. A computer system for predicting risk of recurrence after radical resection surgery of rectal cancer in a chinese population, comprising:
a. an input device for receiving subject data, wherein the subject data comprises genetic test data from a microarray according to any one of claims 3-5;
b. a memory having a database for storing at least the genetic test data;
c. a processor in communication with the memory and configured to:
calculating an evaluation value F (x) by an algorithm model by using the gene detection data; and
d. output means configured to transmit a notification according to a result of the determination of the evaluation value f (x);
wherein the algorithm model is:
F(x)=29.3341-0.7416 * WDR43+0.9450 * RAB31+2.9083 * FASN-0.5904 * TYMS-3.0449 * SNX2-2.5533 * DAP3+3.7309 * pt+1.9524 * MRPS18C+1.0107 * FANCL-6.5343 * CIDECP-1.1939 * HNRNPH1+0.1941 * CMSS1；
the processor is further configured to: obtaining a P (x) value by:
P(x)＝1/(1+exp(-F(x)))，
and comparing the obtained P (x) value with a reference value of 0.37, determining that the risk of recurrence after the rectal cancer resection is high when P (x) is higher than 0.37, and determining that the risk of recurrence after the rectal cancer resection is low when P (x) is lower than or equal to 0.37.
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| CN101389957A (en) * | 2005-12-23 | 2009-03-18 | 环太平洋生物技术有限公司 | Prognosis prediction for colorectal cancer |
| EP2092086A2 (en) * | 2006-11-02 | 2009-08-26 | Signature Diagnostics AG | Prognostic marker for predicting the five-year progression-free survival of patients with colorectal carcinoma based on expression profiles of biological samples |
| CN103403187A (en) * | 2011-01-18 | 2013-11-20 | 艾沃锐斯特基因有限公司 | Prognostic signature for colorectal cancer recurrence |
| CN104031915A (en) * | 2014-06-17 | 2014-09-10 | 复旦大学附属肿瘤医院 | Gene segments for prognosis of colorectal cancers and application of gene segments |
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| DE102006035388A1 (en) * | 2006-11-02 | 2008-05-15 | Signature Diagnostics Ag | Prognostic markers for the classification of colon carcinomas based on expression profiles of biological samples |
| WO2012031008A2 (en) * | 2010-08-31 | 2012-03-08 | The General Hospital Corporation | Cancer-related biological materials in microvesicles |
| US20120238464A1 (en) * | 2011-03-18 | 2012-09-20 | Baylor Research Institute | Biomarkers for Predicting the Recurrence of Colorectal Cancer Metastasis |
| WO2015017537A2 (en) * | 2013-07-30 | 2015-02-05 | H. Lee Moffitt Cancer Center And Research Institute, Inc. | Colorectal cancer recurrence gene expression signature |
| SG2013079173A (en) * | 2013-10-18 | 2015-05-28 | Agency Science Tech & Res | Sense-antisense gene pairs for patient stratification, prognosis, and therapeutic biomarkers identification |
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| CN101389957A (en) * | 2005-12-23 | 2009-03-18 | 环太平洋生物技术有限公司 | Prognosis prediction for colorectal cancer |
| EP2092086A2 (en) * | 2006-11-02 | 2009-08-26 | Signature Diagnostics AG | Prognostic marker for predicting the five-year progression-free survival of patients with colorectal carcinoma based on expression profiles of biological samples |
| CN103403187A (en) * | 2011-01-18 | 2013-11-20 | 艾沃锐斯特基因有限公司 | Prognostic signature for colorectal cancer recurrence |
| CN104031915A (en) * | 2014-06-17 | 2014-09-10 | 复旦大学附属肿瘤医院 | Gene segments for prognosis of colorectal cancers and application of gene segments |
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