CN111321221A - Composition, microarray and computer system for predicting risk of recurrence after surgical resection of local section of rectal cancer - Google Patents
Composition, microarray and computer system for predicting risk of recurrence after surgical resection of local section of rectal cancer Download PDFInfo
- Publication number
- CN111321221A CN111321221A CN201811534784.0A CN201811534784A CN111321221A CN 111321221 A CN111321221 A CN 111321221A CN 201811534784 A CN201811534784 A CN 201811534784A CN 111321221 A CN111321221 A CN 111321221A
- Authority
- CN
- China
- Prior art keywords
- recurrence
- rectal cancer
- risk
- predicting
- microarray
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Granted
Links
Images
Classifications
-
- C—CHEMISTRY; METALLURGY
- C12—BIOCHEMISTRY; BEER; SPIRITS; WINE; VINEGAR; MICROBIOLOGY; ENZYMOLOGY; MUTATION OR GENETIC ENGINEERING
- C12Q—MEASURING OR TESTING PROCESSES INVOLVING ENZYMES, NUCLEIC ACIDS OR MICROORGANISMS; COMPOSITIONS OR TEST PAPERS THEREFOR; PROCESSES OF PREPARING SUCH COMPOSITIONS; CONDITION-RESPONSIVE CONTROL IN MICROBIOLOGICAL OR ENZYMOLOGICAL PROCESSES
- C12Q1/00—Measuring or testing processes involving enzymes, nucleic acids or microorganisms; Compositions therefor; Processes of preparing such compositions
- C12Q1/68—Measuring or testing processes involving enzymes, nucleic acids or microorganisms; Compositions therefor; Processes of preparing such compositions involving nucleic acids
- C12Q1/6876—Nucleic acid products used in the analysis of nucleic acids, e.g. primers or probes
- C12Q1/6883—Nucleic acid products used in the analysis of nucleic acids, e.g. primers or probes for diseases caused by alterations of genetic material
- C12Q1/6886—Nucleic acid products used in the analysis of nucleic acids, e.g. primers or probes for diseases caused by alterations of genetic material for cancer
-
- C—CHEMISTRY; METALLURGY
- C12—BIOCHEMISTRY; BEER; SPIRITS; WINE; VINEGAR; MICROBIOLOGY; ENZYMOLOGY; MUTATION OR GENETIC ENGINEERING
- C12Q—MEASURING OR TESTING PROCESSES INVOLVING ENZYMES, NUCLEIC ACIDS OR MICROORGANISMS; COMPOSITIONS OR TEST PAPERS THEREFOR; PROCESSES OF PREPARING SUCH COMPOSITIONS; CONDITION-RESPONSIVE CONTROL IN MICROBIOLOGICAL OR ENZYMOLOGICAL PROCESSES
- C12Q2600/00—Oligonucleotides characterized by their use
- C12Q2600/118—Prognosis of disease development
-
- C—CHEMISTRY; METALLURGY
- C12—BIOCHEMISTRY; BEER; SPIRITS; WINE; VINEGAR; MICROBIOLOGY; ENZYMOLOGY; MUTATION OR GENETIC ENGINEERING
- C12Q—MEASURING OR TESTING PROCESSES INVOLVING ENZYMES, NUCLEIC ACIDS OR MICROORGANISMS; COMPOSITIONS OR TEST PAPERS THEREFOR; PROCESSES OF PREPARING SUCH COMPOSITIONS; CONDITION-RESPONSIVE CONTROL IN MICROBIOLOGICAL OR ENZYMOLOGICAL PROCESSES
- C12Q2600/00—Oligonucleotides characterized by their use
- C12Q2600/158—Expression markers
Landscapes
- Chemical & Material Sciences (AREA)
- Life Sciences & Earth Sciences (AREA)
- Health & Medical Sciences (AREA)
- Organic Chemistry (AREA)
- Proteomics, Peptides & Aminoacids (AREA)
- Engineering & Computer Science (AREA)
- Immunology (AREA)
- Pathology (AREA)
- Analytical Chemistry (AREA)
- Zoology (AREA)
- Genetics & Genomics (AREA)
- Wood Science & Technology (AREA)
- Physics & Mathematics (AREA)
- Biotechnology (AREA)
- Microbiology (AREA)
- Molecular Biology (AREA)
- Hospice & Palliative Care (AREA)
- Biophysics (AREA)
- Oncology (AREA)
- Biochemistry (AREA)
- Bioinformatics & Cheminformatics (AREA)
- General Engineering & Computer Science (AREA)
- General Health & Medical Sciences (AREA)
- Measuring Or Testing Involving Enzymes Or Micro-Organisms (AREA)
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 rectal cancer postoperative recurrence marker genes aiming at Chinese population, draws out a specific rectal cancer postoperative recurrence evaluation model, customizes the rectal cancer postoperative recurrence marker gene microarray chip according to research results, and is used for clinical diagnosis and evaluation of rectal cancer patients postoperative recurrence evaluation 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 operation.
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. In China, more than 25 million new cases of colorectal cancer and about 14 million death cases are caused every year, 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 disease progression in time. Common methods of diagnosing rectal cancer include: fecal occult blood test, digital rectal examination, proctoscope, sigmoidoscope, fibrocolonoscope, imaging examination, 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 method for screening and diagnosing colorectal cancer is the methylation of septin 9. The research proves that the sensitivity of the septin9 for screening the colorectal cancer 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 signatures for CRC detection are endless. 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 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 screens the related postoperative recurrence marker genes of the rectal cancer patients in Chinese population, establishes a corresponding postoperative recurrence evaluation model and further customizes a specific postoperative recurrence detection scheme of the colorectal cancer patients in Chinese population. 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 surgical resection locally of rectal cancer 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 a sample.
In a second aspect of the present invention, there is provided a microarray for predicting risk of recurrence after a partial resection surgery for rectal cancer, 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 respective one of the oligonucleotides.
Preferably, 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 μm2。
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 surgery for 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 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).
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 P (x) value by the following formula, and comparing the obtained P (x) value with a reference value of 0.37, judging that the risk of recurrence after the rectal cancer partial resection surgery is high when P (x) is higher than 0.37, and judging that the risk of recurrence after the rectal cancer partial resection surgery is 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 the Chinese colorectal 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. Finally, the technical scheme of the invention is customized.
[ composition for predicting the risk of recurrence after partial rectal cancer excision surgery ]
In a first aspect of the invention, there is provided a composition for predicting the risk of recurrence following surgical resection locally of rectal cancer 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 fewer 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 number of oligonucleotides that specifically bind to the same target gene is at least one, and preferably a plurality. 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 a 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 resection of rectal cancer ]
In a second aspect of the present invention, a microarray, also called "gene chip" or "microarray chip", for predicting the risk of recurrence after a local resection operation for 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 fluorescent 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 above in detail 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, each site is 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 μm2。
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 specific probe for a gene of interest, spotting the dissolved and diluted probe on a well-known commercially available aldehydized substrate by a gene chip spotter, and preparing a microarray for risk of recurrence after a local resection surgery for rectal cancer.
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 flow 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 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 a partial resection surgery for 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 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, the p (x) value obtained by the following formula is used to judge that the risk of recurrence after the rectal cancer partial resection surgery is high when p (x) is higher than 0.37, and low when p (x) is lower than or equal to 0.37.
In the computer system of the present invention, the input means for receiving object data includes any form of input means. 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 and sometimes even no results. Based on 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 MagMAXTM(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: 50ng of RNA was reverse transcription kit (SuperScript)TMIV ReverseTranscriptase, Invitrogen) to obtain cDNA, and the whole process is completely operated according to the kit instruction;
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 a 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 numbers 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 probes which are dissolved and diluted are sprayed and solidified on a known commercial aldehyde substrate by a gene chip sample applicator to prepare a microarray for the recurrence risk after the local resection operation 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 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 chip for recurrence samples after rectal cancer surgery
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 medical science institute
Meta-code Gene science and technology (Beijing) Ltd
<120> composition, microarray and computer system for predicting risk of recurrence after partial resection surgery for rectal cancer
<130>BHBP180164
<160>33
<170>PatentIn version 3.3
<210>1
<211>75
<212>DNA
<213> Artificial sequence
<400>1
acaagggacc ttatttaggt tgcgcaggcg cccgctggcc atttcgtctt agccacgcag 60
aagtcgcgtg tctag 75
<210>2
<211>75
<212>DNA
<213> Artificial sequence
<400>2
gtgagtcgcg gtgggtcctc gcttgcagtt cagcgaccac gtttgtttcg acgccggacc 60
gcgtaagaga cgatg 75
<210>3
<211>77
<212>DNA
<213> Artificial sequence
<400>3
cgacgccgga ccgcgtaaga gacgatgatg ttgggcacgg aaggtggaga gggattcgtg 60
gtgaaggtcc ggggctt 77
<210>4
<211>80
<212>DNA
<213> Artificial sequence
<400>4
tgagcgaaga tggcggccga gagggaacct cctccgctgg gggacgggaa gcccaccgac 60
tttgaggatc tggaggacgg 80
<210>5
<211>79
<212>DNA
<213> Artificial sequence
<400>5
agaccgcgtc gctgcgggtg ctgcgctgcg tagctgccgc gcgtctcacc tttcccctgc 60
cccgacttgt ccctcccca 79
<210>6
<211>74
<212>DNA
<213> Artificial sequence
<400>6
ctcaggagag cagcctgcgg cccgcgggtg ccgacctaat cctcagaggg gccagaaccg 60
aaccgagcat tgca 74
<210>7
<211>75
<212>DNA
<213> Artificial sequence
<400>7
agggtgtggt ggccgtcctg ctgaccaaga agtccctggc ccggcgggtg tacgccacca 60
tcctgaacgc cggca 75
<210>8
<211>76
<212>DNA
<213> Artificial sequence
<400>8
atggcatcac ccgagccctg tgcgccaccc gccaggagcc gctgctcatc ggctccacca 60
agtccaacat ggggca 76
<210>9
<211>76
<212>DNA
<213> Artificial sequence
<400>9
tcccagcgct gttggatggg cggctgcagg tggtggacca gcccctgccc gtccgtggcg 60
caacgtgggc atcaac 76
<210>10
<211>75
<212>DNA
<213> Artificial sequence
<400>10
atgagagcca gccctttgat ggaattacag gtctttattt cttatctgga gcagtacatg 60
accggttact taatg 75
<210>11
<211>76
<212>DNA
<213> Artificial sequence
<400>11
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 (10)
1. A composition for predicting the risk of recurrence following surgical resection locally of rectal cancer 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.
2. The composition for predicting the risk of recurrence after surgical resection of a regional resection of rectal cancer according to claim 1, wherein the contiguous sequence is a conserved sequence of the corresponding gene.
3. The composition for predicting the risk of recurrence after a partial rectal cancer resection surgery according to claim 1, wherein the oligonucleotide is designed to be capable of fixedly binding one end thereof to a substrate and at least part of the sequence is capable of specifically binding to a partially continuous 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 a desired gene in a sample.
4. A microarray for predicting the risk of recurrence after a surgical resection of a local section of rectal cancer, comprising the composition according to any one of claims 1 to 3 and a substrate having a surface with a plurality of sites disposed independently of each other.
5. The microarray for predicting the risk of recurrence after a partial resection surgery for rectal cancer according to claim 4, wherein each of the sites has a reactive functional group capable of binding to the oligonucleotide; or each site binds to a respective one of the oligonucleotides.
6. The microarray for predicting the risk of recurrence after partial resection of rectal cancer according to claim 4 or 5, wherein the sites are regularly arranged in such a manner 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 μm2。
7. The microarray for predicting the risk of recurrence after surgical resection of a regional section of rectal cancer according to claim 4 or 5, wherein the oligonucleotide comprises a repetitive sequence of a plurality of target regions, and the sequence length of the oligonucleotide is 50-500 nt.
8. A computer system for predicting risk of recurrence following a partial resection surgery for rectal cancer, 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 4-7;
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).
9. The computer system for predicting the risk of recurrence after a partial resection surgery for rectal cancer according to claim 8, wherein the algorithmic 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。
10. the computer system for predicting risk of recurrence following a partial resection surgery for rectal cancer according to claim 9, wherein the processor is further configured to: obtaining a P (x) value by the following formula, and comparing the obtained P (x) value with a reference value of 0.37, judging that the risk of recurrence after the rectal cancer partial resection surgery is high when P (x) is higher than 0.37, and judging that the risk of recurrence after the rectal cancer partial resection surgery is low when P (x) is lower than or equal to 0.37.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201811534784.0A CN111321221B (en) | 2018-12-14 | 2018-12-14 | Composition, microarray and computer system for predicting risk of recurrence after regional resection of rectal cancer |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201811534784.0A CN111321221B (en) | 2018-12-14 | 2018-12-14 | Composition, microarray and computer system for predicting risk of recurrence after regional resection of rectal cancer |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN111321221A true CN111321221A (en) | 2020-06-23 |
| CN111321221B CN111321221B (en) | 2022-09-23 |
Family
ID=71163380
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201811534784.0A Active CN111321221B (en) | 2018-12-14 | 2018-12-14 | Composition, microarray and computer system for predicting risk of recurrence after regional resection of rectal cancer |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN111321221B (en) |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114591956A (en) * | 2022-03-03 | 2022-06-07 | 中山大学附属第一医院 | Application of WDR43 antisense nucleotide in preparing medicine for inhibiting intestinal cancer cell proliferation and transfer |
Citations (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| 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 |
| US20090269775A1 (en) * | 2006-11-02 | 2009-10-29 | Signature Diagnostics Ag | Prognostic markers for classifying colorectal carcinoma on the basis of expression profiles of biological samples |
| US20120238464A1 (en) * | 2011-03-18 | 2012-09-20 | Baylor Research Institute | Biomarkers for Predicting the Recurrence of Colorectal Cancer Metastasis |
| 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 |
| US20140045915A1 (en) * | 2010-08-31 | 2014-02-13 | The General Hospital Corporation | Cancer-related biological materials in microvesicles |
| 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 |
| US20160208333A1 (en) * | 2013-07-30 | 2016-07-21 | H. Lee Moffitt Cancer Center And Research Institute, Inc. | Colorectal cancer recurrence gene expression signature |
| US20160259883A1 (en) * | 2013-10-18 | 2016-09-08 | Agency For Science, Technology And Research | Sense-antisense gene pairs for patient stratification, prognosis, and therapeutic biomarkers identification |
-
2018
- 2018-12-14 CN CN201811534784.0A patent/CN111321221B/en active Active
Patent Citations (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| 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 |
| US20090269775A1 (en) * | 2006-11-02 | 2009-10-29 | Signature Diagnostics Ag | Prognostic markers for classifying colorectal carcinoma on the basis of expression profiles of biological samples |
| US20140045915A1 (en) * | 2010-08-31 | 2014-02-13 | The General Hospital Corporation | Cancer-related biological materials in microvesicles |
| 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 |
| US20120238464A1 (en) * | 2011-03-18 | 2012-09-20 | Baylor Research Institute | Biomarkers for Predicting the Recurrence of Colorectal Cancer Metastasis |
| US20160208333A1 (en) * | 2013-07-30 | 2016-07-21 | H. Lee Moffitt Cancer Center And Research Institute, Inc. | Colorectal cancer recurrence gene expression signature |
| US20160259883A1 (en) * | 2013-10-18 | 2016-09-08 | Agency For Science, Technology And Research | Sense-antisense gene pairs for patient stratification, prognosis, and therapeutic biomarkers identification |
| 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 |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114591956A (en) * | 2022-03-03 | 2022-06-07 | 中山大学附属第一医院 | Application of WDR43 antisense nucleotide in preparing medicine for inhibiting intestinal cancer cell proliferation and transfer |
Also Published As
| Publication number | Publication date |
|---|---|
| CN111321221B (en) | 2022-09-23 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| JP2002528097A5 (en) | ||
| JP2022531637A (en) | DNA methylation biomarker for early detection of cervical cancer | |
| KR102067607B1 (en) | Application of Y Chromosome Methylation Site as a Prognostic Cancer Diagnostic Marker | |
| JP2010527577A (en) | Detection method | |
| AU2019301959B2 (en) | DNA methylation markers for noninvasive detection of cancer and uses thereof | |
| CN108277283B (en) | Application of lncRNA combination in preparation of product for predicting renal clear cell carcinoma prognosis and molecular targeted drug treatment sensitivity | |
| JP2009148269A (en) | Method for detecting minute amount of gastric cancer cell | |
| KR20200035427A (en) | Augmentation of cancer screening using cell-free viral nucleic acids | |
| CN102782151A (en) | Circulating miRNA as non-invasive markers for diagnosis and staging in prostate cancer | |
| JP2020519296A (en) | DNA methylation and mutation analysis method for bladder cancer monitoring | |
| TWI408235B (en) | Gene marker and method for detection of oral cancer | |
| CN115896281A (en) | Methylated biomarker, kit and application | |
| JP4317854B2 (en) | Detection method of trace gastric cancer cells | |
| CN111321221B (en) | Composition, microarray and computer system for predicting risk of recurrence after regional resection of rectal cancer | |
| US20180371553A1 (en) | Methods and compositions for the analysis of cancer biomarkers | |
| CN105779580A (en) | Methods and markers for assessing risk of developing colorectal cancer | |
| JP2016508375A (en) | Methods and tools for diagnosis and prognosis of genitourinary cancer | |
| WO2019245587A1 (en) | Methods and compositions for the analysis of cancer biomarkers | |
| US20150329911A1 (en) | Nucleic acid biomarkers for prostate cancer | |
| WO2017167034A1 (en) | Bladder cancer detection method and kit | |
| US11542559B2 (en) | Methylation-based biomarkers in breast cancer screening, diagnosis, or prognosis | |
| CN111321220A (en) | Composition, microarray and computer system for detecting sensitivity of radiotherapy and chemotherapy of rectal cancer | |
| WO2007145325A1 (en) | Test method for malt lymphoma and kit therefor | |
| CN115927607B (en) | Application of biomarker in gastric cancer diagnosis | |
| US11807908B2 (en) | Genetic markers used for identifying benign and malignant pulmonary micro-nodules and the application thereof |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |