WO2016136684A1

WO2016136684A1 - Method for assisting in prognostic diagnosis of colorectal cancer, recording medium and determining apparatus

Info

Publication number: WO2016136684A1
Application number: PCT/JP2016/055124
Authority: WO
Inventors: 雄一郎吉田
Original assignee: シスメックス株式会社
Priority date: 2015-02-27
Filing date: 2016-02-22
Publication date: 2016-09-01
Also published as: AU2016224709A1; AU2016224709B2; JP2016158531A; CN107429242A; JP6612509B2; CN107429242B

Abstract

The present invention measures an SCEL gene expression amount in a biological specimen taken from a colorectal cancer patient and assists in the prognostic diagnosis of colorectal cancer on the basis of the measured SCEL gene expression amount.

Description

Method, recording medium and determination device for assisting prognosis of colorectal cancer

The present invention relates to a method for assisting prognosis of colorectal cancer. In particular, the present invention relates to a method, a recording medium, and a determination device for obtaining SCEL gene expression level data for a nucleic acid obtained from a tissue of a colorectal cancer patient and assisting prognosis of the patient's colorectal cancer based on the acquired expression level data. .

Colorectal cancer is a general term for carcinomas that occur in the cecum, colon, and rectum. Like many cancers, early detection is important for the treatment of colorectal cancer. In the treatment of cancer, an anticancer agent having a strong side effect may be used, and in this case, the patient is forced to bear a great burden. In order to reduce such a burden on the patient, it is important for the doctor to select the most appropriate treatment method for the patient, and for this purpose, the doctor accurately determines the progression, malignancy, symptoms, etc. of the patient's cancer. It is necessary to grasp.

Also, accurately predicting the patient's prognosis is important for improving the quality of life (QOL) of the patient's prognosis. In recent years, the appearance of budding has attracted attention as a pathological prognostic factor for colorectal cancer. Non-Patent Document 1 reports that exudation can be useful as a prognostic factor for rectal and colonic mucinous cancers.

In the conventional method described above, since the pathologist performs the observation with a microscope, the diagnosis result becomes subjective. The present inventor has a risk of being overlooked by observation with a microscope, since the oozing is a nest containing 1 to 4 cancer cells. In addition, the prognosis determination by the conventional method has a problem that it is difficult to determine the prognosis because a high level of expertise is required.
An object of the present invention is to provide a more objective colorectal cancer prognosis assistance method, recording medium, and determination apparatus.

As a result of intensive studies to solve the above-mentioned problems, the present inventor found that the expression of the SCEL gene correlates with the presence or absence of excision, and completed the present invention.

According to the present invention, a colorectal cancer comprising the steps of measuring the expression level of the SCEL gene in a biological sample collected from a colorectal cancer patient, and determining the prognosis of colorectal cancer based on the measured expression level. A method is provided to assist in the prognosis of patients.

ADVANTAGE OF THE INVENTION According to this invention, the intermediate information which assists the prognosis diagnosis of colon cancer by doctors etc. can be acquired.

It is the schematic which showed an example of the diagnostic assistance apparatus. It is a block diagram which shows the function structure of the software of a diagnostic assistance apparatus. It is a block diagram which shows the structure of the hardware of a diagnostic assistance apparatus. It is a flowchart which shows an example of operation | movement of a diagnostic assistance apparatus. It is a flowchart which shows an example of operation | movement of a diagnostic assistance apparatus. It is a box-and-whisker diagram showing the correlation between BSS and brewing grade. It is a ROC curve in the case of Example 1 (training set). It is a Kaplan-Meier curve which shows the result of the lifetime comparison of the high risk group (poor prognosis) and the low risk group (good prognosis) in the case of Example 1 (training set). It is a ROC curve in the case of Example 2 (validation set). It is a Kaplan-Meier curve which shows the result of the disease free survival comparison of the high risk group (poor prognosis) and the low risk group (good prognosis) in the case of Example 2 (validation set). 4 is an ROC curve in the case of Example 3. It is a Kaplan-Meier curve which shows the result of the recurrence-free survival comparison of the high risk group (poor prognosis) and the low risk group (good prognosis) in the case of Example 3. 4 is an ROC curve in the case of Example 4. It is a Kaplan-Meier curve which shows the result of the recurrence-free survival rate comparison of the high risk group (poor prognosis) and the low risk group (good prognosis) in the case of Example 4.

In the colorectal cancer prognosis determination method of the present embodiment (hereinafter sometimes referred to as “determination method”), first, a step of measuring the expression level of the SCEL gene in a biological sample collected from a colorectal cancer patient is performed. .

The “biological sample” is not particularly limited as long as it contains a nucleic acid (eg, mRNA) derived from a tumor cell of a colorectal cancer patient. For example, a clinical sample can be used. Specific examples of the clinical specimen include tissue, blood, serum and the like collected by surgery or biopsy. Preferably, the clinical specimen may be a tumor tissue collected by surgery or biopsy, particularly a tissue around a cancer advanced part.

The nucleotide sequence of the cDNA for the SCEL gene is represented as SEQ ID NO: 1. This base sequence is known under the accession number NM_001160706 in the human genome database GenBank.

In another embodiment, in addition to the SCEL gene, at least one expression level selected from the MGAT3 gene, SLC4A11 gene, MSLN gene, FOXC1 gene, RUNX2 gene and WNT11 gene can be measured in the measurement step.

MGAT3 (mannosyl (beta-1,4-)-glycoprotein beta-1,4-N-acetylglucosaminyltransfer
ase) The cDNA base sequence of the gene is represented as SEQ ID NO: 2. This base sequence is known under the accession number NM_001098270 in the human genome database GenBank.

The nucleotide sequence of cDNA of SLC4A11 (solute carrier family 4, sodium borate transporter, member 11) gene is represented as SEQ ID NO: 3. This base sequence is known under the accession number NM_001174089 in the human genome database GenBank.

The base sequence of cDNA of MSLN (mesothelin) gene is represented as SEQ ID NO: 4. This base sequence is known under the accession number NM_001177355 in the human genome database GenBank.

The base sequence of cDNA of FOXC1 (forkhead box C1) gene is represented as SEQ ID NO: 5. This base sequence is known under the accession number NM_001453 in the human genome database GenBank.

The cDNA base sequence of the RUNX2 (run-related transcription factor 2) gene is represented as SEQ ID NO: 6. This base sequence is known under the accession number NM_001015051 in the human genome database GenBank.

The nucleotide sequence of the cDNA of WNT11 (wingless-type MMTV integration site family, member 11) gene is represented as SEQ ID NO: 7. This base sequence is known under the accession number NM_004626 in the human genome database GenBank.

簇 Exudation is a nest containing 1 to 4 cancer cells present in the stroma near the advanced cancer area. According to the Japanese Cancer Treatment Society's “Cancer Medical Practice Guidelines”, when referring to colorectal cancer, exudation is a growth of cancer cells that have been released from cancer tissue and is known as a risk factor for lymph node metastasis of colorectal cancer. It has been. The grade of exudation is evaluated by selecting the most advanced area of exudation, observing the advanced part of cancer development in a 20 × 10 field of view, and counting the number of exudations. Individuals with 5 or more counts (Grade 2 and 3) have a significantly increased lymph node metastasis rate compared to individuals with less than 4 (Grade 1).

The present inventor has now found for the first time that the expression levels of the above seven genes are significantly increased in advanced cancerous sections with ulcers. Therefore, the above seven genes can be useful gene markers in prognosis determination of colorectal cancer. Since the expression levels of genes can be measured and quantified according to methods known to those skilled in the art, the prognosis of colorectal cancer can be objectively determined by measuring the expression levels of these genes.

A “gene transcription product” is a product obtained by transcription of a gene. Specifically, messenger RNA (mRNA) and a precursor of mRNA are exemplified.
Further, the “gene expression level” refers to the amount of gene transcripts present in the biological sample or the amount of a substance that reflects the gene transcript. Therefore, in this embodiment, the amount of mRNA or the amount of complementary deoxyribonucleic acid (cDNA) or complementary RNA (cRNA) obtained from mRNA can be measured. Usually, since the amount of mRNA in a biological sample is very small, it is preferable to measure the amount of cDNA or cRNA obtained therefrom by reverse transcription and in vitro transcription (IVT).

Examples of a method for extracting a gene transcription product from a biological sample include RNA extraction methods known in the art. For example, a biological sample can be centrifuged to precipitate RNA-containing cells, the cells can be destroyed by physical, chemical, or enzymatic methods, and an RNA extract can be obtained by removing cell debris. it can. RNA extraction can also be performed using a commercially available RNA extraction kit or the like.

From the extract of the transcription product of the gene obtained as described above, a contaminated component derived from a biological sample that is preferably not mixed at the time of measuring the expression level of the gene (for example, if the biological sample is blood, globin It is also possible to perform treatment for removing mRNA and the like.

The measurement of gene expression level is not particularly limited as long as it is a quantitative method. For example, a microarray using DNA, RNA, artificial nucleic acid or the like as a probe (hereinafter also simply referred to as “microarray”) or quantitative PCR (for example, quantitative RT-PCR) can be used. In a preferred embodiment, a method using a microarray may be used.
When measuring the expression level of a gene using a microarray, for example, a nucleic acid probe of about 20 to 25 mer immobilized on a substrate is used to extract a gene transcript or a cDNA or cRNA prepared from a gene transcript. The expression level of the target gene can be measured by contacting it and measuring the change in indicators such as fluorescence, color development, and current for the presence or absence of hybrid formation.
At least one nucleic acid probe may be used for one gene transcript, and a plurality of probes may be used depending on the length of the gene transcript. The sequence of the probe can be appropriately determined by those skilled in the art according to the sequence of the transcription product of the gene to be measured. For example, in the present embodiment, a polynucleotide represented by SEQ ID NOs: 8-84 can be used as such a probe.
As a method for measuring the expression level of a gene using a microarray, for example, GeneChip (registered trademark) system provided by Affymetrix can be used.

When using a microarray, a gene transcription product or its cDNA or cRNA may be fragmented to facilitate hybridization with a nucleic acid probe. Fragmentation can be performed by methods known in the art. For example, it can be performed using a nucleolytic enzyme such as ribonuclease or deoxyribonuclease.

Transcript or cDNA of gene contacted with nucleic acid probe in microarray
Alternatively, cRNA is usually about 5 to 20 μg. The contact condition is usually 16 hours at 45 ° C.

The gene transcript or its cDNA or cRNA hybridized upon contact with the nucleic acid probe is measured for the presence or absence of the hybridization and the amount of hybridization with the amount of current flowing on the microarray due to the fluorescent substance, dye or hybridization. It can be detected based on a change or the like.
When the formation of a hybrid is measured by detecting a fluorescent substance or a dye, it is preferable that the gene transcription product or its cDNA or cRNA is labeled with a labeling substance for detecting the fluorescent substance or the dye. As such a labeling substance, those usually used in the art can be used. Usually, by mixing biotinylated nucleotides or biotinylated ribonucleotides as a nucleotide or ribonucleotide substrate when synthesizing cDNA or cRNA, the resulting cDNA or cRNA can be labeled with biotin. When the cDNA or cRNA is labeled with biotin, avidin or streptavidin, which is a binding partner for biotin, can bind on the microarray. Hybrid formation can be detected by avidin or streptavidin binding to an appropriate fluorescent substance or dye. Examples of the fluorescent substance include fluorescein isothiocyanate (FITC), green fluorescent protein (GFP), luciferin, phycoerythrin, and the like. Usually, a phycoerythrin-streptavidin conjugate is commercially available, and it is convenient to use it.
Alternatively, a labeled antibody against avidin or streptavidin can be contacted with avidin or streptavidin to detect the fluorescent substance or dye of the labeled antibody.

The expression level of the gene obtained in this step is not particularly limited as long as it is a value that relatively represents the abundance of the transcription product of each gene in the biological sample. When measurement is performed using the above-described microarray, the expression level can be a signal obtained from the microarray based on fluorescence intensity, color intensity, current amount, and the like.
These signals can be measured using a measuring device for microarrays.

Next, in the determination step, the prognosis of colorectal cancer is determined based on the gene expression level obtained in the measurement step. Preferably, the determination step includes a step of comparing the expression level of the gene or its logarithm with a predetermined reference value. As the gene expression level, a value that can be obtained by the measurement method described above can be used as it is. For example, when the expression level is measured with a microarray, the value of the fluorescence intensity can be used as the expression level of the gene. When the expression level is measured by quantitative RT-PCR, values such as the number of PCR cycles and the number of mRNA copies calculated from the number of PCR cycles can be used.
The logarithmic base of the gene expression level is not particularly limited, and 2 or 10 can be used.
When performing the determination step based on the expression level of multiple genes, the average value of the gene expression level, the median value of the gene expression level, the logarithm average value of the gene expression level, the median value of the logarithm, the gene The average value of the standardized expression levels, the median value of the standardized values, and the like can be used. In the comparison step, these values are compared with a predetermined reference value.
If it is greater than or equal to the predetermined reference value, it can be determined that the prognosis is not good. If it is less than the reference value, it can be determined that the prognosis is good.

The “reference value” can be set as appropriate based on the accumulation of gene expression level data. Specifically, it may be a threshold that can accurately classify a patient with a poor prognosis and a patient with a good prognosis. For example, the reference value is a value that can measure the gene expression levels of a plurality of patients whose prognosis is known and classify the patient group with a poor prognosis and the patient group with a good prognosis with the highest accuracy. By measuring the gene expression level of a patient whose prognosis is unknown by the method of this embodiment and comparing it with a reference value, it can be determined whether the prognosis is good or not.

In this embodiment, the reference value is set based on the ROC curve obtained by performing ROC analysis using the average value of the logarithm (base = 2) of the gene expression level measured by the microarray for a plurality of specimens. Threshold. In this embodiment, when the average value of the logarithm (base = 2) of the expression level of a gene measured by a microarray for a specimen derived from an individual subject to prognosis determination is the above threshold, colon cancer of the individual It can be determined that the prognosis is not good. On the other hand, when it is less than the above-mentioned threshold, it can be determined that the prognosis of the individual's colon cancer is good.

The present invention also includes a program product for causing a computer to execute prognosis determination of colorectal cancer in a patient. Examples of such a program product include a program that can be downloaded via the Internet, a computer-readable recording medium that records the program, and the like.

For example, the program for making a computer perform the following processes is illustrated.
A step of acquiring information relating to the expression level of a gene in a biological sample collected from a colorectal cancer patient from a measurement device; a step of determining a prognosis of the colorectal cancer of the patient based on the acquired information.

Hereinafter, an embodiment of an apparatus suitable for carrying out the method of this embodiment will be described with reference to the drawings. However, the present invention is not limited only to this embodiment. FIG. 1 is a schematic diagram showing an example of a diagnostic assistance device used for prognosis determination of colorectal cancer in a patient. The diagnostic auxiliary device 10 shown in FIG. 1 includes a measuring device 20 and a determination device 30 connected to the measuring device 20.

In the present embodiment, the measuring device 20 may be a microarray measuring device. The measuring device 20 can acquire information related to the expression level of the gene itself, such as the expression level of the gene itself and the fluorescence hue and fluorescence intensity of the microarray. When a biological sample collected from a colorectal cancer patient is set in the measuring device 20, the measuring device 20 acquires information related to the gene expression level in the biological sample, and provides the obtained information to the determination device 30. Can do.

The determination apparatus 30 includes a computer main body 300, an input unit 301 including a keyboard and a mouse, and a display unit 302 including an LCD and a CRT for displaying sample information and determination results. The determination device 30 acquires information related to the expression level of each gene from the measurement device 20. And the determination apparatus 30 runs the program which determines the prognosis of a subject's colon cancer based on such information. From the input unit 301, “to perform 1 gene determination”, “to perform 3 gene determination”, etc., which will be described later, can be input.
The determination device 30 may be a device separate from the measurement device 20 as illustrated in FIG. 1, or may be a device that includes the measurement device 20. In the latter case, the determination device 30 may be the diagnostic auxiliary device 10 by itself.

FIG. 2 is a block diagram showing software of the computer main body 300 of the determination apparatus 30 as functional blocks. As illustrated in FIG. 2, the computer includes an acquisition unit 321, a storage unit 322, a calculation unit 323, a determination unit 324, and an output unit 325. The acquisition unit 321 is connected to the measurement apparatus 20 via a network so that communication is possible. The determination unit 324 includes information necessary for performing a prognosis determination of colorectal cancer via the input unit 301, specifically, information regarding whether or not to perform 1 gene determination and / or whether or not to perform 3 gene determination. Information can be entered.

The acquisition unit 321 acquires information provided from the measurement device 20. The storage unit 322 stores a reference value necessary for determination, an expression for calculating the gene expression level, a processing program, and the like. The calculation unit 323 uses the information acquired by the acquisition unit 321 to calculate the gene expression level according to the stored formula. The determination unit 324 determines whether the gene expression level acquired by the acquisition unit 321 or the gene expression level calculated by the calculation unit 323 is greater than or equal to the reference value stored in the storage unit 322. The output unit 325 outputs the determination result by the determination unit 324 to the display unit 302 as the prognosis determination result of the colorectal cancer of the subject.

FIG. 3 is a block diagram showing a hardware configuration of the computer main body 300 shown in FIG. As shown in FIG. 3, the computer main body 300 includes a CPU (Central Processing Unit) 310, a ROM (Read Only Memory) 311, a RAM (Random Access Memory) 312, a hard disk 313, an input / output interface 314, A reading device 315, a communication interface 316, and an image output interface 317 are provided. CPU 310, ROM 311, RAM 312, hard disk 313, input / output interface 314, reading device 315, communication interface 316, and image output interface 317 are connected by a bus 318 so that data communication is possible.

The CPU 310 can execute a program stored in the ROM 311 and a program loaded in the RAM 312. Each function shown in FIG. 2 is executed by the CPU 310 executing the program. Thereby, the determination apparatus 30 functions as a determination apparatus for determining the prognosis of the colorectal cancer of the subject.

The ROM 311 is configured by a mask ROM, PROM, EPROM, EEPROM, or the like. The ROM 311 records a program executed by the CPU 310 and data used for the program as described above.

The RAM 312 is configured by SRAM, DRAM, or the like. The RAM 312 is used for reading programs recorded in the ROM 311 and the hard disk 313. The RAM 312 is also used as a work area for the CPU 310 when executing these programs.

The hard disk 313 is installed with an operating system to be executed by the CPU 310, a program such as an application program (a program for determining the prognosis of colorectal cancer in a subject), and data used for executing the program.

The reading device 315 includes a flexible disk drive, a CD-ROM drive, a DVD-ROM drive, and the like. The reading device 315 can read a program or data recorded on the portable recording medium 40.

The input / output interface 314 includes, for example, a serial interface such as USB, IEEE 1394, RS-232C, a parallel interface such as SCSI, IDE, IEEE 1284, and an analog interface including a D / A converter, an A / D converter, and the like. It is configured. An input unit 301 such as a keyboard and a mouse is connected to the input / output interface 314. The operator can input various commands to the computer main body 300 through the input unit 301.

The communication interface 316 is, for example, an Ethernet (registered trademark) interface. The computer main body 300 can also transmit print data to a printer or the like via the communication interface 316.

The image output interface 317 is connected to a display unit 302 configured with an LCD, a CRT, or the like. Accordingly, the display unit 302 can output a video signal corresponding to the image data given from the CPU 310. The display unit 302 displays an image (screen) according to the input video signal.

Next, a processing procedure for determining the prognosis of the colorectal cancer of the subject by the diagnosis assisting apparatus 10 will be described.
FIG. 4 is an example of a flowchart for determining the prognosis of colorectal cancer. Here, the fluorescence intensity is calculated from fluorescence information obtained using a biological sample derived from a subject, the gene expression level is calculated from the obtained fluorescence intensity, and the obtained expression level is equal to or greater than a reference value. The case where it is determined whether or not will be described as an example. However, the present invention is not limited only to this embodiment.

First, in step S1-1, the acquisition unit 321 of the diagnostic auxiliary device 10 receives fluorescence information related to the expression levels of the SCEL gene, MGAT3 gene, SLC4A11 gene, MSLN gene, FOXC1 gene, RUNX2 gene, and WNT11 gene from the measurement device 20. To get.

Next, in step S1-2, the calculation unit 323 calculates the fluorescence intensity from the acquired fluorescence information and transmits it to the storage unit 322. In step S1-3, the calculation unit 323 calculates the expression level of the gene according to the stored formula based on the stored fluorescence intensity.

Thereafter, in step S1-4, the determination unit 324 determines whether or not the expression level calculated in step S1-3 is greater than or equal to the reference value stored in the storage unit 322. Here, when the expression level is not less than the reference value, the routine proceeds to step S1-5. Then, the determination unit 324 transmits a determination result indicating that the prognosis of the subject's colorectal cancer is not good to the output unit 325. On the other hand, when the expression level is less than the reference value, the routine proceeds to step S1-6. Then, the determination unit 324 transmits a determination result indicating that the prognosis of the subject's colorectal cancer is good to the output unit 325.

Finally, in step S1-7, the output unit 325 outputs the prognosis determination result of the subject's colorectal cancer and causes the display unit 302 to display the result. Thereby, the diagnostic assistance apparatus 10 can provide a doctor or the like with information that assists in diagnosing whether the prognosis of the colorectal cancer of the subject is good or not.

In this embodiment, the gene used for prognosis determination may be only the SCEL gene, or at least one gene selected from the MGAT3 gene, SLC4A11 gene, MSLN gene, FOXC1 gene, RUNX2 gene and WNT11 gene is further added. There may be two or more.

In another embodiment, the user may be able to select a gene used for prognosis determination. Such a processing procedure will be described with reference to FIG. Here, whether to use only SCEL gene (1 gene determination), SCEL gene, MGAT3 gene and SLC4A11 gene (3 gene determination), or SCEL gene, MGAT3 gene, SLC4A11 gene, MSLN gene, FOXC1 gene, RUNX2 The user can select whether to use the gene and WNT11 gene (7 gene determination).

First, in step S2-1, when “input one gene determination” is input from the input unit 301, the routine proceeds to S2-3. And the acquisition part 321 of the determination apparatus 30 acquires the fluorescence information relevant to the expression level of a SCEL gene from the measuring apparatus 20 (1 gene determination).

On the other hand, if “one gene determination” is not input, the routine proceeds to S2-2. In step S2-2, if “input 3 genes is determined” is input from the input unit 301, the routine proceeds to S2-4. Thereafter, the acquisition unit 321 of the diagnostic auxiliary device 10 acquires fluorescence information related to the current amounts of the SCEL gene, the MGAT3 gene, and the SLC4A11 gene from the measurement device 20 (three-gene determination).

In step S2-2, if “3 gene determination” is not input, the routine proceeds to S2-5. And the acquisition part 321 of the diagnostic assistance apparatus 10 acquires the fluorescence information relevant to the expression level of SCEL gene, MGAT3 gene, SLC4A11 gene, MSLN gene, FOXC1 gene, RUNX2 gene, and WNT11 gene from the measuring apparatus 20 (7 genes). Judgment).

Next, in step S2-6, the calculation unit 323 calculates the fluorescence intensity from the acquired fluorescence information, and transmits it to the storage unit 322. In step S2-7, the calculation unit 323 calculates the gene expression level according to the stored formula based on the stored fluorescence intensity.

Thereafter, in step S2-8, the determination unit 324 determines whether or not the expression level calculated in step S2-7 is greater than or equal to the reference value stored in the storage unit 322. If the expression level is greater than or equal to the reference value, the routine proceeds to step S2-9. Then, the determination unit 324 transmits a determination result indicating that the prognosis of the subject's colorectal cancer is not good to the output unit 325. On the other hand, when the expression level is less than the reference value, the routine proceeds to step S2-10. Then, the determination unit 324 transmits a determination result indicating that the prognosis of the subject's colorectal cancer is good to the output unit 325.

Finally, in step S2-11, the output unit 325 outputs the prognosis determination result of the colorectal cancer of the subject and displays it on the display unit 302. Thereby, the diagnostic assistance apparatus 10 can provide a doctor or the like with information that assists in diagnosing whether the prognosis of the colorectal cancer of the subject is good or not.

The present invention also includes a determination apparatus suitable for determining the prognosis of colorectal cancer in a subject.

The storage unit 322 records a program for causing the determination device 30 to execute the following steps: Acquires information related to the gene expression level in a biological sample collected from a colorectal cancer patient from the measurement device. A step of determining a prognosis of the colorectal cancer of the patient based on the acquired information.

In the present embodiment, information on the expression level of the gene measured by the microarray is acquired, and the prognosis of the colorectal cancer of the subject can be determined based on the acquired information. For example, it is possible to provide a determination result that the prognosis of the colorectal cancer of the subject is good or not good. By providing the determination result to a doctor or the like, diagnosis by a doctor or the like regarding the prognosis of colorectal cancer can be assisted.

Example 1: Determination of prognosis of colorectal cancer using 7 genes (training set)
(1) Search for marker Search for the marker was performed according to the following procedure. Specifically, first, for each of a total of 2 sites of advanced and basal portions of 3 specimens of colorectal cancer tissue in which exudation is observed, (1) the average expression value in microarray (Affymetrix) measurement is 200 or more 23,509 A gene was selected. Next, (2) 73 genes whose minimum expression ratio between the advanced part and the basal part in 2 specimens is 2 or more (the gene with the expression in the advanced part where there is squeezing is about twice as much as the expression level) Selected. After that, (3) 34 genes whose expression ratio between the advanced part and the whole tissue was 1 or more (the gene with the expression level in the advanced part where the outbreak was larger than the whole tissue) were selected.

(4) Using 85 colorectal cancer tissue samples including the above three samples, out of the above 34 genes, positive samples (grade 3): 26 cases and negative samples (grade 1): 44 cases In the T test, 7 genes that had a significant difference (p <0.05) and increased expression in the positive specimen were selected. Table 7 below shows the IDs of the seven selected genes and the probe sets used to measure their expression levels. In addition, the base sequence of each probe (both are antisense strands) is represented by SEQ ID NOs: 8-84.

Figure shows the correlation between the average value of the logarithm (base = 2) of the expression level calculated above (hereinafter referred to as Budding Signature Score; BSS; the specific calculation formula is shown below) and the leach grade by pathological diagnosis It is shown in FIG. Here, the exudation grade was determined as defined in [Grade of Exudation] in the Cancer Treatment Guidelines of the Japanese Cancer Treatment Society. In other words, after selecting the region with the highest degree of exudation in the specimen, if the number of exudates is counted as a result of observing the advanced part of cancer growth in a 20x10 field of view and counting the number of exudates, Grade 1, Grade 2 when 5-9, Grade 3 when 10 or more. From FIG. 6, it was found that BSS increases as the leach grade increases. That is, it was found that the higher the leach grade, the more genes were expressed.

(2) Prognosis determination ROC analysis was performed on 85 samples using the BSS value calculated above, and a threshold value was set. The results are shown in FIG. The value (corresponding to the point closest to (sensitivity, specificity) = (1,1) on the ROC curve) on the ROC curve in the ROC curve of FIG. 7 was set as the threshold (8.436). The area under the curve (AUC) was 0.602.

Next, the survival time was compared between a specimen showing BSS above the threshold and a specimen showing BSS below the threshold. The results are shown in FIG. As shown in FIG. 8, there is a significant difference (p = 0.0479) between the specimen showing BSS above the threshold and the specimen showing BSS below the threshold from the viewpoint of probability.
Was recognized. Based on the above, the prognosis of colorectal cancer patients is high-risk or low-risk based on the expression levels of seven genes: SCEL gene, MGAT3 gene, SLC4A11 gene, MSLN gene, FOXC1 gene, RUNX2 gene and WNT11 gene It was suggested that it can be determined whether there is any.

Example 2: Colorectal cancer prognosis using 7 genes (validation set)
The usefulness of the above seven genes as a colorectal cancer prognostic marker was further verified by using publicly available colorectal cancer gene expression data. GE39582 (461 samples) of Gene Expression Omunibus (GEO) which is a public database was used ( http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE39582 ).
ROC analysis was performed in the same manner as in Example 1, threshold values (7.686, AUC = 0.5752) were set, and the survival times were compared between samples showing BSS above the threshold and samples showing BSS below the threshold. The results are shown in FIGS. As shown in FIG. 10, there is a significant difference (p = 0) between the specimen showing BSS above the threshold and the specimen showing BSS below the threshold from the viewpoint of disease-free survival (Disease Free Survival).
.000473) was observed. This result reproduces the result of Example 1. Therefore, it was confirmed that the above seven genes are useful as prognostic markers for colorectal cancer.

Example 3 Prognosis Determination of Colorectal Cancer Using 3 Genes The present inventor conducted experiments similar to Example 2 using the same database as Example 2 for 3 genes of SCEL gene, MGAT3 gene and SLC4A11 gene. It was. Specifically, ROC analysis was performed in the same manner as in Example 2, a threshold value (6.112, AUC = 0.5828) was set, and a specific formula for calculating BSS above the above threshold (in the case of 3-gene measurement, BSS) And the specimen showing BSS less than the above threshold were compared for relapse-free survival (rfs delay, days). The result is shown in FIG.
And 12. As shown in FIG. 12, a significant difference (p = 0.000684) was observed from the viewpoint of viability between the specimen showing BSS above the threshold and the specimen showing BSS below the threshold. Therefore, it was shown that the prognosis of colorectal cancer can be determined based on the expression levels of the above three genes.

Example 4: Prognosis determination of colorectal cancer using SCEL gene Based on the expression level of SCEL gene, it was verified whether or not prognosis determination of colorectal cancer could be performed. That is, for the SCEL gene, the same experiment as in Example 2 was performed using the same database as in Example 2. Specifically, ROC analysis is performed in the same manner as in Example 2, a threshold value (5.300, AUC = 0.6003) is set, and a specific calculation formula of BSS (BSS in the case of 3-gene measurement) equal to or higher than the above threshold value is as follows. The relapse-free survival period (in days) was compared between a sample showing (shown in (1)) and a sample showing BSS less than the above threshold. The results are shown in FIGS. As shown in FIG. 14, a significant difference (p = 0.00702) was observed from the viewpoint of viability between the specimen showing BSS above the threshold and the specimen showing BSS below the threshold. Therefore, it was shown that the prognosis of colorectal cancer can be determined based on the expression level of the SCEL gene.

DESCRIPTION OF SYMBOLS 10 Diagnosis assistance apparatus 20 Measuring apparatus 30 Judgment apparatus 40 Recording medium 300 Computer main body 301 Input part 302 Display part 310 CPU
311 ROM
312 RAM
313 Hard disk 314 Input / output interface 315 Reading device 316 Communication interface 317 Image output interface 318 Bus 321 Acquisition unit 322 Storage unit 323 Calculation unit 324 Determination unit 325 Output unit

Claims

A method for assisting in prognosis of colorectal cancer, comprising: measuring an expression level of a SCEL gene in a biological sample collected from a colorectal cancer patient; and determining a prognosis of colorectal cancer based on the expression level. .
In the determination step,
Compare the expression level or its logarithm with a predetermined reference value,
The prognosis is determined to be poor when the expression level or logarithm thereof is equal to or greater than the reference value, and the prognosis is determined to be favorable when the expression level or logarithm thereof is less than the reference value. the method of.
In the measurement step, the expression level of at least one gene selected from the group consisting of MGAT3 gene, SLC4A11 gene, MSLN gene, FOXC1 gene, RUNX2 gene and WNT11 gene is further measured,
The method according to claim 1, wherein in the determination step, the prognosis of colorectal cancer is determined based on the expression level of the gene measured in the measurement step.
In the measurement step, the expression level of MGAT3 gene and SLC4A11 gene is further measured,
The method according to claim 1, wherein in the determination step, the prognosis of colorectal cancer is determined based on the expression level of the gene measured in the measurement step.
In the measurement step, the expression level of MSLN gene, the expression level of FOXC1 gene, the expression level of RUNX2 gene and the expression level of WNT11 gene are further measured,
The method according to claim 4, wherein in the determination step, the prognosis of colorectal cancer is determined based on the expression level of the gene measured in the measurement step.
In the determination step,
Calculate the logarithm of the expression level of the gene measured in the measurement step,
Comparing the logarithm with a predetermined reference value;
The method according to claim 1, wherein if the logarithm is equal to or greater than the reference value, it is determined that the prognosis is not good, and if the logarithm is less than the reference value, it is determined that the prognosis is good.
In the determination step,
Calculate the average value or the logarithm of the expression level of the gene measured in the measurement step,
Comparing the average value or logarithm with a predetermined reference value;
The prognosis is determined to be poor when the average value or logarithm is equal to or greater than the reference value, and the prognosis is determined to be good when the average value or logarithm is less than the reference value. The method according to claim 1.
On the computer,
A step of acquiring information related to the expression level of the SCEL gene in a biological sample collected from a colorectal cancer patient from a measuring device;
Determining the prognosis of the colorectal cancer of the patient based on the acquired information;
The computer-readable recording medium which recorded the program for performing this.
At least a computer including a processor and memory;
In the memory,
A step of acquiring information related to the expression level of the SCEL gene in a biological sample collected from a colorectal cancer patient from a measuring device;
Determining the prognosis of the colorectal cancer of the patient based on the acquired information;
A determination apparatus for determining a prognosis of colorectal cancer in which a program for causing the computer to execute is recorded.