AU2016224709A1 - Method for assisting in prognostic diagnosis of colorectal cancer, recording medium and determining device - Google Patents
Method for assisting in prognostic diagnosis of colorectal cancer, recording medium and determining device Download PDFInfo
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- G—PHYSICS
- G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
- G16B—BIOINFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR GENETIC OR PROTEIN-RELATED DATA PROCESSING IN COMPUTATIONAL MOLECULAR BIOLOGY
- G16B25/00—ICT specially adapted for hybridisation; ICT specially adapted for gene or protein expression
- G16B25/10—Gene or protein expression profiling; Expression-ratio estimation or normalisation
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- C—CHEMISTRY; METALLURGY
- C12—BIOCHEMISTRY; BEER; SPIRITS; WINE; VINEGAR; MICROBIOLOGY; ENZYMOLOGY; MUTATION OR GENETIC ENGINEERING
- C12N—MICROORGANISMS OR ENZYMES; COMPOSITIONS THEREOF; PROPAGATING, PRESERVING, OR MAINTAINING MICROORGANISMS; MUTATION OR GENETIC ENGINEERING; CULTURE MEDIA
- C12N15/00—Mutation or genetic engineering; DNA or RNA concerning genetic engineering, vectors, e.g. plasmids, or their isolation, preparation or purification; Use of hosts therefor
- C12N15/09—Recombinant DNA-technology
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- 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
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N33/00—Investigating or analysing materials by specific methods not covered by groups G01N1/00 - G01N31/00
- G01N33/48—Biological material, e.g. blood, urine; Haemocytometers
- G01N33/50—Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing
- G01N33/53—Immunoassay; Biospecific binding assay; Materials therefor
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N33/00—Investigating or analysing materials by specific methods not covered by groups G01N1/00 - G01N31/00
- G01N33/48—Biological material, e.g. blood, urine; Haemocytometers
- G01N33/50—Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing
- G01N33/53—Immunoassay; Biospecific binding assay; Materials therefor
- G01N33/574—Immunoassay; Biospecific binding assay; Materials therefor for cancer
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- G—PHYSICS
- G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
- G16B—BIOINFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR GENETIC OR PROTEIN-RELATED DATA PROCESSING IN COMPUTATIONAL MOLECULAR BIOLOGY
- G16B25/00—ICT specially adapted for hybridisation; ICT specially adapted for gene or protein expression
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
1
DESCRIPTION
TITLE OF INVENTION: METHOD FOR ASSISTING IN PROGNOSTIC DIAGNOSIS OF COLORECTAL CANCER, RECORDING MEDIUM AND DETERMINING DEVICE
TECHNICAL FIELD
[0001]
The present invention relates to a method for assisting in the prognostic diagnosis of colorectal cancer. More specifically, the present invention relates to a method, a recording medium, and a determining device for assisting in the prognostic diagnosis of colorectal cancer in a patient based on expression level data of SCEL gene that are obtained for a nucleic acid obtained from a tissue of a colorectal cancer patient. BACKGROUND ART
[0002]
Colorectal cancer is a generic term for carcinomas occurring in the cecum, colon, and rectum. As with many cancers, early detection is important for the treatment of colorectal cancer. In the treatment of cancer, an anticancer drug having a strong side effect is sometimes used. In such a case, the patient is forced to bear a heavy burden. In order to reduce such burden on the patient, it is important for a doctor to select an optimal treatment method for the patient. For this purpose, the doctor has to accurately grasp the stage of cancer progression, degree of malignancy, symptoms, and the like of the patient.
[0003]
In addition, accurate prediction of a patient’s prognosis is important for improving the quality of life (QOL) of the patient in the prognosis. In recent years, as 2 a pathological prognostic factor of colorectal cancer, presence or absence of budding has been drawing attention. Non Patent Literature 1 reports that budding can be useful as a prognostic factor of mucinous cancers in rectum and colon. CITATIONS LIST Patent Literature [0004]
Non Patent Literature 1: Okuyama T. et al., Budding (sprouting) as a useful prognostic marker in colorectal mucinous carcinoma, Jpn J Clin Oncol, 2002; 32 (10) 412-416 SUMMARY
TECHNICAL PROBLEMS
[0005]
In the above-mentioned conventional method, the diagnosis result is subjective since a pathologist makes the diagnosis through microscopic observation. The present inventor has found a problem that there is a risk of overlook of the budding through microscopic observation since the budding is a nest containing 1 to 4 cancer cells. The inventor has also found a problem that it is difficult to make a prognostic determination because highly specialized knowledge is required for the prognostic determination by the conventional method.
It is an object of the present invention to provide a method, a recording medium, and a determining device for assisting in a more objective prognostic diagnosis of colorectal cancer.
SOLUTIONS TO PROBLEMS
[0006]
As a result of extensive research to solve the above-mentioned problems, the 3 present inventor has found that the expression of SCEL gene correlates with the presence or absence of budding, and completed the present invention.
[0007]
According to the present invention, there is provided a method for assisting in prognostic diagnosis of colorectal cancer, the method including the steps of measuring the expression level of 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.
ADVANTAGEOUS EFFECTS OF INVENTION
[0008]
According to the present invention, it is possible to acquire intermediate information for assisting in the prognostic diagnosis of colorectal cancer by a doctor or the like.
BRIEF DESCRIPTION OF DRAWINGS
[0009]
Fig. 1 is a schematic diagram showing an example of a diagnosis assisting apparatus.
Fig. 2 is a block diagram showing a functional configuration of software of a diagnosis assisting apparatus.
Fig. 3 is a block diagram showing a configuration of hardware of a diagnosis assisting apparatus.
Fig. 4 is a flowchart showing an example of an operation of a diagnosis assisting apparatus.
Fig. 5 is a flowchart showing an example of the operation of the diagnosis assisting apparatus. 4
Fig. 6 is a box-and-whisker plot showing a correlation between a BSS and a budding grade.
Fig. 7 is an ROC curve in a case of Example 1 (training set).
Fig. 8 is a Kaplan-Meier curve showing the results of comparing the survival periods between a high-risk group (poor prognosis) and a low-risk group (good prognosis) in the case of Example 1 (training set).
Fig. 9 is an ROC curve in a case of Example 2 (validation set).
Fig. 10 is a Kaplan-Meier curve showing the results of comparing the disease free survival periods between a high-risk group (poor prognosis) and a low-risk group (good prognosis) in the case of Example 2 (validation set).
Fig. 11 is an ROC curve in a case of Example 3.
Fig. 12 is a Kaplan-Meier curve showing the results of comparing the relapse free survival periods between a high-risk group (poor prognosis) and a low-risk group (good prognosis) in the case of Example 3.
Fig. 13 is an ROC curve in a case of Example 4.
Fig. 14 is a Kaplan-Meier curve showing the results of comparing the relapse free survivals between a high-risk group (poor prognosis) and a low-risk group (good prognosis) in the case of Example 4.
DESCRIPTION OF EMBODIMENTS
[0010]
In the prognostic determination method for colorectal cancer in the present embodiment (hereinafter sometimes referred to as “determination method”), first, a step of measuring the expression level of SCEL gene in a biological sample collected from a colorectal cancer patient is performed.
[0011] 5
The “biological sample” is not particularly limited as long as it contains a nucleic acid (e.g., mRNA) derived from a tumor cell of a colorectal cancer patient.
For example, a clinical specimen can be used. Specific examples of the clinical specimen include tissues, blood, and serum collected by surgery or biopsy. Preferably, the clinical specimen can be a tumor tissue collected by surgery or biopsy, particularly a tissue surrounding the invasive front of cancer.
[0012]
The nucleotide sequence of cDNA of SCEL (sciellin) gene is represented in SEQ ID NO: 1. This nucleotide sequence is publicly known under Accession No. NM 001160706 in the human genome database GenBank.
[0013]
In another embodiment, in the measurement step, the expression level of at least one gene selected from MGAT3 gene, SLC4A11 gene, MSLN gene, FOXC1 gene, RUNX2 gene, and WNT11 gene may be further measured in addition to the expression level of SCEL gene.
[0014]
The nucleotide sequence of cDNA of MGAT3 (mannosyl (beta-l,4-)-glycoprotein beta-1,4-N-acetylglucosaminyltransferase) gene is represented in SEQ ID NO: 2. This nucleotide sequence is publicly known under Accession No. ΝΜ 001098270 in the human genome database GenBank.
[0015]
The nucleotide sequence of cDNA of SLC4A11 (solute carrier family 4, sodium borate transporter, member 11) gene is represented in SEQ ID NO: 3. This nucleotide sequence is publicly known under Accession No. NM 001174089 in the human genome database GenBank. 6 [0016]
The nucleotide sequence of cDNA of MSLN (mesothelin) gene is represented in SEQ ID NO: 4. This nucleotide sequence is publicly known under Accession No. NM 001177355 in the human genome database GenBank.
[0017]
The nucleotide sequence of cDNA of FOXC1 (forkhead box Cl) gene is represented in SEQ ID NO: 5. This nucleotide sequence is publicly known under Accession No. NM 001453 in the human genome database GenBank.
[0018]
The nucleotide sequence of cDNA of RUNX2 (runt-related transcription factor 2) gene is represented in SEQ ID NO: 6. This nucleotide sequence is publicly known under Accession No. NM 001015051 in the human genome database GenBank.
[0019]
The nucleotide sequence of cDNA of WNT11 (wingless-type MMTV integration site family, member 11) gene is represented in SEQ ID NO: 7. This nucleotide sequence is publicly known under Accession No. NM_004626 in the human genome database GenBank.
[0020]
Budding is a nest that contains 1 to 4 cancer cells and is present in the interstitium near the invasive front of cancer. According to the “Clinical Practice Guideline” of the Japan Society of Clinical Oncology, when referring to colorectal cancer, budding is cancer cells that are liberated from a cancer tissue and proliferated, and is known as a risk factor for lymph node metastasis of colorectal cancer. The grade of the budding is evaluated by selecting an area with the most advanced budding, observing the invasive front of cancer development in a field of view of 20 x 10 times, 7 and counting the number of budding foci. An individual with 5 or more counted budding foci (Grades 2 and 3) has a significantly increased lymph node metastasis rate compared to an individual with less than 5 budding foci (Grade 1).
[0021]
The present inventor found for the first time that the expression levels of the above-mentioned seven genes are significantly increased in the invasive front of cancer having the budding. Therefore, the seven genes can serve as useful genetic markers in the prognostic determination of colorectal cancer. Since the gene expression level can be measured and quantified according to a method known to those skilled in the art, measuring the expression levels of these genes enables the objective prognostic determination of colorectal cancer.
[0022] A “gene transcription product” is a product obtained by transcription of a gene. Specific examples of the transcription product include messenger RNA (mRNA) and a precursor of mRNA.
The “gene expression level” refers to the abundance of a gene transcription product or the amount of a substance reflecting the abundance in the biological sample. Therefore, in the present embodiment, the amount of mRNA, or the amount of complementary deoxyribonucleic acid (cDNA) or complementary RNA (cRNA) obtained from mRNA is measured as the gene expression level. Since mRNA is present in a biological sample usually in a trace amount, it is preferred to measure the amount of cDNA or cRNA obtained from the mRNA by reverse transcription and in vitro transcription (IVT).
[0023]
As a method for extracting a gene transcription product from a biological 8 sample, an RNA extraction method known in the art can be mentioned. For example, it is possible to obtain an RNA extract by centrifuging a biological sample to precipitate RNA-containing cells, and disrupting the cells by a physical technique, a chemical technique, or an enzymatic technique to remove the cell debris. The extraction of RNA can also be performed using a commercially available RNA extraction kit or the like.
[0024]
It is also possible to perform a treatment of removing, from the extract of the gene transcription product obtained as described above, a contaminant component derived from a biological sample (for example, globin mRNA when the biological sample is blood) which is preferably not incorporated in the extract at the time of measuring the gene expression level.
[0025]
The method for measuring the gene expression level is not particularly limited as long as it is a quantitative method. For example, the expression level can be measured using a microarray containing DNA, RNA, artificial nucleic acid or the like as a probe (hereinafter sometimes simply referred to as “microarray”) or quantitative PCR (for example, quantitative RT-PCR). In a preferred embodiment, a method using a microarray can be used.
In the case of measuring the gene expression level using a microarray, the expression level of the target gene can be measured, for example, by bringing an extract of a gene transcription product, or cDNA or cRNA prepared from a gene transcription product into contact with a nucleic acid probe of about 20 to 25 mer fixed on a substrate, and confirming the presence or absence of hybridization by measuring the change in indices such as fluorescence, color, and current. 9
The number of required nucleic acid probes used for one gene transcription product is at least one, and a plurality of probes may be used depending on the length and the like of the gene transcription product. A person skilled in the art can appropriately determine the sequence of the probe in accordance with the sequence of the gene transcription product to be measured. For example, in the present embodiment, polynucleotides represented by SEQ ID NOS: 8 to 84 can be used as the probe.
As a method for measuring the gene expression level using a microarray, for example, a GeneChip (registered trademark) system provided by Affymetrix, Inc. can be used.
[0026]
When a microarray is used, the gene transcription product, or cDNA or cRNA thereof may be fragmented to facilitate hybridization with the nucleic acid probe. The fragmentation can be carried out by a method known in the art. For example, the fragmentation can be carried out using a nucleolytic enzyme such as ribonuclease or deoxyribonuclease.
[0027]
The amount of the gene transcription product, or cDNA or cRNA thereof to be brought into contact with a nucleic acid probe in a microarray may be usually about 5 to 20 pg. The contact conditions are usually about 16 hours at 45 °C.
[0028]
The gene transcription product, or cDNA or cRNA thereof that has hybridized by contact with a nucleic acid probe can be detected for the presence or absence of hybridization and the amount of hybridization based on the fluorescent substance, dye, or a change in the amount of current flowing on the microarray due to hybridization. 10
When the hybridization is measured by detection of a fluorescent substance or a dye, it is preferred that the gene transcription product, or cDNA or cRNA thereof is labeled with a labeling substance for detection of a fluorescent substance or a dye. A labeling substance commonly used in the art can be used as the labeling substance. Usually, biotinylated nucleotide or biotinylated ribonucleotide can be mixed as a nucleotide or ribonucleotide substrate when synthesizing cDNA or cRNA to label the obtained cDNA or cRNA with biotin. When cDNA or cRNA is biotin-labeled, avidin or streptavidin, which is a binding partner for biotin, can be bound on the microarray. Hybridization can be detected by binding of avidin or streptavidin to an appropriate fluorescent substance or dye. Examples of the fluorescent substance include fluorescein isothiocyanate (FITC), green fluorescent protein (GFP), luciferin, and phycoerythrin. It is usually convenient to use a commercially available conjugate of phycoerythrin-streptavidin.
In addition, it is also possible to detect a fluorescent substance or a dye of a labeled antibody by bringing an antibody capable of being labeled with avidin or streptavidin into contact with avidin or streptavidin.
[0029]
The gene expression level obtained in this step is not particularly limited as long as it is a value that relatively expresses the abundance of each gene transcription product in the biological sample. In the case of performing the measurement with the above-mentioned microarray, the expression level can be a signal obtained from the microarray based on the fluorescence intensity, color intensity, current amount, and the like.
These signals can be measured using a measuring device for a microarray.
[0030] 11
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 gene expression level or a logarithm thereof with a predetermined reference value. As the gene expression level, a value obtainable by the above-mentioned measurement method 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 gene expression level. When the expression level is measured by quantitative RT-PCR, values such as a PCR cycle number, and an mRNA copy number calculated from the PCR cycle number can be used.
The base of the logarithm of the gene expression level is not particularly limited, and can be 2 or 10.
In the case where the determination step is performed based on the expression levels of a plurality of genes, an average value of the gene expression levels, a median value of the gene expression levels, an average value of logarithms of the gene expression levels, a median value of the logarithms, an average value of values obtained by standardizing the gene expression levels, a median value of the standardized values, and the like can be used. In the comparison step, such value is compared with a predetermined reference value.
When the value is not less than the predetermined reference value, a patient may be determined to have a poor prognosis. When the value is less than the reference value, a patient may be determined to have a good prognosis.
[0031]
The “reference value” can be appropriately set based on accumulated data of gene expression levels. More specifically, the reference value may be a threshold that 12 allows accurate classification into patients with a poor prognosis and patients with a good prognosis. For example, the reference value is a value that is obtained by measuring gene expression levels of a plurality of patients whose prognosis is known, and that enables most accurate classification into a patient group with a poor prognosis and a patient group with a good prognosis. Measuring the gene expression level of a patient whose prognosis is unknown and comparing the gene expression level with the reference value by the method of the present embodiment makes it possible to determine whether the patient has a good prognosis or not.
[0032]
In the present embodiment, the reference value may be a threshold that is obtained based on an ROC curve through an ROC analysis using an average value of logarithms (base = 2) of gene expression levels measured by a microarray for a plurality of specimens. In the present embodiment, when the average value of logarithms (base = 2) of gene expression levels measured by a microarray for specimens derived from an individual as a target of prognostic determination is equal to or more than the above-mentioned threshold, the individual may be determined to have a poor prognosis of colorectal cancer. On the other hand, when the average value is less than the above-mentioned threshold, the individual may be determined to have a good prognosis of colorectal cancer.
[0033]
The present invention also includes a program product for making a computer execute the prognostic determination of colorectal cancer in a patient. Examples of such a program product include a program that can be downloaded via the Internet or the like, and a computer-readable recording medium recording the program therein.
[0034] 13
For example, a program for making a computer execute the following steps can be mentioned: acquiring, from a measuring device, information relating to a gene expression level in a biological sample collected from a colorectal cancer patient; and determining the prognosis of colorectal cancer in the patient based on the acquired information.
[0035]
Hereinafter, one mode of an apparatus suitable for implementing the method of the present embodiment will be described with reference to the drawings. However, the present invention is not limited to this embodiment. Fig. 1 is a schematic diagram showing an example of a diagnosis assisting apparatus used for prognostic determination of colorectal cancer in a patient. A diagnosis assisting apparatus 10 shown in Fig. 1 includes a measuring device 20 and a determining device 30 connected to the measuring device 20.
[0036]
In the present embodiment, the measuring device 20 may be a measuring device for a microarray. The measuring device 20 can acquire the gene expression level itself, and information relating to the gene expression level such as 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 can acquire information relating to the gene expression level in the biological sample, and provide the acquired information to the determining device 30.
[0037]
The determining device 30 includes a computer main body 300, an input unit 301 including a keyboard and a mouse, and a display unit 302 that includes an LCD or a CRT and displays specimen information, a determination result, and the like. The 14 determining device 30 acquires information relating to the expression level of each gene from the measuring device 20. Based on the information, the determining device 30 executes a program for determining the prognosis of colorectal cancer in a subject.
Via the input unit 301, it is possible to enter “perform single-gene determination”, “perform three-gene determination” and the like described later.
Note that the determining device 30 may be a device separate from the measuring device 20 as shown in Fig. 1 or may be a device including the measuring device 20. In the latter case, the determining device 30 may itself be the diagnosis assisting apparatus 10.
[0038]
Fig. 2 is a block diagram showing software of the computer main body 300 of the determining device 30 in functional blocks. As shown 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 communicably connected to the measuring device 20 via a network. Into the determination unit 324, information necessary for the prognostic determination of colorectal cancer, specifically, information on whether or not to perform single-gene determination, and/or whether or not to perform three-gene determination can be entered via the input unit 301.
[0039]
The acquisition unit 321 acquires information provided from the measuring device 20. The storage unit 322 stores a reference value necessary for the determination, and formulae and processing programs for calculating the gene expression level. The calculation unit 323 calculates the gene expression level according to the stored formulae using the information acquired by the acquisition unit 15 321. The determination unit 324 determines whether or not the gene expression level acquired by the acquisition unit 321 or calculated by the calculation unit 323 is not less than 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 a prognostic determination result of colorectal cancer in a subject.
[0040]
Fig. 3 is a block diagram showing a hardware configuration of the computer main body 300 shown in Fig. 2. 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. The CPU 310, the ROM 311, the RAM 312, the hard disk 313, the input/output interface 314, the reading device 315, the communication interface 316, and the image output interface 317 are connected by a bus 318 so that they are capable of data communication.
[0041]
The CPU 310 can execute a program stored in the ROM 311 and a program loaded in the RAM 312. When the CPU 310 executes the programs, the functions shown in Fig. 2 are executed. In this manner, the determining device 30 functions as a determining device for determining the prognosis of colorectal cancer in a subject.
[0042]
The ROM 311 may be a mask ROM, a PROM, an EPROM, an EEPROM, or the like. In the ROM 311, the program executed by the CPU 310 and data used for the program are recorded as described above.
[0043] 16
The RAM 312 may be an SRAM, a DRAM, or the like. The RAM 312 is used for reading out the programs recorded in the ROM 311 and the hard disk 313.
The RAM 312 is also used as a work area of the CPU 310 when these programs are executed.
[0044]
In the hard disk 313, an operating system and programs such as an application program (a program for prognostic determination of colorectal cancer in a subject) to be executed by the CPU 310, and data used for executing the programs are installed.
[0045]
The reading device 315 may be a flexible disk drive, a CD-ROM drive, a DVD-ROM drive, or the like. The reading device 315 can read out a program or data recorded in a portable recording medium 40.
[0046]
The input/output interface 314 includes, for example, a serial interface such as USB, IEEE 1394, or RS-232C, a parallel interface such as SCSI, IDE, or IEEE 1284, and an analog interface including a D/A converter, an A/D converter, and the like. To the input/output interface 314, the input unit 301 such as a keyboard and a mouse is connected. An operator can enter various commands into the computer main body 300 via the input unit 301.
[0047]
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 through the communication interface 316.
[0048]
The image output interface 317 is connected to the display unit 302 including 17 an LCD, a CRT, or the like. As a result, the display unit 302 can output a video signal corresponding to the image data provided by the CPU 310. The display unit 302 displays an image (screen) according to the input video signal.
[0049]
Next, the processing procedure for prognostic determination of colorectal cancer in a subject by the diagnosis assisting apparatus 10 will be described.
Fig. 4 is an example of a flowchart of prognostic determination of colorectal cancer. Herein, an example will be described about a case where the fluorescence intensity is calculated from the fluorescence information obtained using a biological sample derived from a subject, the gene expression level is calculated from the obtained fluorescence intensity, and a determination is made as to whether or not the obtained expression level is not less than a reference value. However, the present invention is not limited to this embodiment alone.
[0050]
First, in step S1 -1, the acquisition unit 321 of the diagnosis assisting apparatus 10 acquires fluorescence information relating to the expression level of the SCEL gene, MGAT3 gene, SLC4A11 gene, MSLN gene, FOXC1 gene, RUNX2 gene, and/or WNT11 gene from the measuring device 20.
[0051]
Next, in step SI-2, the calculation unit 323 calculates the fluorescence intensity from the acquired fluorescence information and transmits the fluorescence intensity information to the storage unit 322. In step S1-3, the calculation unit 323 calculates the gene expression level according to the stored formula based on the stored fluorescence intensity.
[0052] 18
Then, in step SI-4, the determination unit 324 determines whether or not the expression level calculated in step SI-3 is not less than the reference value stored in the storage unit 322. When the expression level is not less than the reference value, the routine proceeds to step SI-5. Then, the determination unit 324 transmits a determination result indicating that the subject has a poor prognosis of colorectal cancer to the output unit 325. On the other hand, when the expression level is less than the reference value, the routine proceeds to step SI-6. Then, the determination unit 324 transmits a determination result indicating that the subject has a good prognosis of colorectal cancer to the output unit 325.
[0053]
Finally, in step SI-7, the output unit 325 outputs the prognostic determination result of colorectal cancer in the subject and causes the display unit 302 to display the result. In this manner, the diagnosis assisting apparatus 10 can provide a doctor or the like with information that assists in diagnosing whether the subject has a good prognosis of colorectal cancer or not.
[0054]
In the present embodiment, the gene used for the prognostic determination may be only the SCEL gene, or two or more genes including the SCEL gene and at least one additional gene selected from the MGAT3 gene, SLC4A11 gene, MSLN gene, FOXC1 gene, RUNX2 gene, and WNT11 gene.
[0055]
Further, in another embodiment, it is also possible to enable a user to select a gene to be used for prognostic determination. Such a processing procedure will be described with reference to Fig. 5 as an example. In this embodiment, a user can select whether to use only the SCEL gene (single-gene determination), use the SCEL gene, 19 MGAT3 gene, and SLC4A11 gene (three-gene determination), or use the SCEL gene, MGAT3 gene, SLC4A11 gene, MSLN gene, FOXC1 gene, RUNX2 gene, and WNT11 gene (seven-gene determination).
[0056]
First, in step S2-1, when an operator enters “perform single-gene determination” via the input unit 301, the routine proceeds to S2-3. Then, the acquisition unit 321 of the determining device 30 acquires fluorescence information relating to the expression level of the SCEL gene from the measuring device 20 (single-gene determination).
[0057]
On the other hand, when an operator does not enter “perform single-gene determination” via the input unit, the routine proceeds to S2-2. Then, in step S2-2, when the operator enters “perform three-gene determination” via the input unit 301, the routine proceeds to S2-4. Then, the acquisition unit 321 of the diagnosis assisting apparatus 10 acquires fluorescence information relating to the expression levels of the SCEL gene, MGAT3 gene, and SLC4A11 gene from the measuring device 20 (three-gene determination).
[0058]
When the operator does not enter “perform three-gene determination” in step S2-2, the routine proceeds to S2-5. Then, the acquisition unit 321 of the diagnosis assisting apparatus 10 acquires fluorescence information relating to the expression levels of the SCEL gene, MGAT3 gene, SLC4A11 gene, MSLN gene, FOXC1 gene, RUNX2 gene, and WNT11 gene from the measuring device 20 (seven-gene determination).
[0059] 20
Next, in step S2-6, the calculation unit 323 calculates the fluorescence intensity from the acquired fluorescence information and transmits the fluorescence intensity information 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.
[0060]
Then, in step S2-8, the determination unit 324 determines whether or not the expression level calculated in step S2-7 is not less than the reference value stored in the storage unit 322. When the expression level is not less than the reference value, the routine proceeds to step S2-9. Then, the determination unit 324 transmits a determination result indicating that the subject has a poor prognosis of colorectal cancer 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 subject has a good prognosis of colorectal cancer to the output unit 325.
[0061]
Finally, in step S2-11, the output unit 325 outputs the prognostic determination result of colorectal cancer in the subject and causes the display unit 302 to display the result. In this manner, the diagnosis assisting apparatus 10 can provide a doctor or the like with information that assists in diagnosing whether the subject has a good prognosis of colorectal cancer or not.
[0062]
The present invention also includes a determining device suitable for prognostic determination of colorectal cancer in a subject.
[0063] 21
It should be noted that the storage unit 322 records therein a program for making the determining device 30 execute the following steps: acquiring, from a measuring device, information relating to a gene expression level in a biological sample collected from a colorectal cancer patient; and determining the prognosis of colorectal cancer in the patient based on the acquired information.
[0064]
In the present embodiment, it is possible to acquire information on the gene expression level measured by the microarray, and determine the prognosis of colorectal cancer in a subject based on the acquired information. For example, it is possible to provide a determination result that the subject has a good/poor prognosis of colorectal cancer. By providing the above-mentioned determination result to a doctor or the like, it is possible to assist in diagnosis by a doctor or the like about the prognosis of colorectal cancer.
EXAMPLES
[0065]
Example 1: Prognostic determination of colorectal cancer using seven genes (training set) (1) Search for markers
Budding markers were searched according to the following procedure. Specifically, first, with respect to each two positions in total in the invasive front and the base part of three colorectal cancer tissue specimens in which budding is observed, (1) 23,509 genes were selected, the genes had an average expression value as measured by a microarray (manufactured by Affymetrix, Inc.) of 200 or more. Then, (2) 73 genes were selected, the genes had a minimal expression ratio between the invasive front and the base part in the three specimens of 2 or more (genes whose expression 22 level in the invasive front with budding was about 2-fold that in the base part). Then, (3) 34 genes were selected, the genes had an expression ratio between the invasive front and the whole tissues of 1 or more (genes whose expression level in the invasive front with budding was higher than that in the whole tissue).
[0066]
Then, (4) using 85 specimens of colorectal cancer tissues including the above-mentioned three specimens, through a T test between 26 specimens positive for budding (Grade 3) and 44 negative specimens (Grade 1), seven genes with significant differences (p < 0.05) and whose expression was elevated in the budding-positive specimens were selected from the above-mentioned 34 genes. The selected seven genes and the IDs of the probe sets used for measuring the expression levels of the genes are shown in Table 1 below. In addition, the nucleotide sequences of the probes (all antisense strands) are represented by SEQ ID NOS: 8 to 84.
[0067] [Table 1]
Gene symbol Gene name cDNA SEQ ID NO: Probe set ID Sequence ID No. of probe included in probe set SCEL sciellin 1 206884 s at 8-18 MGAT3 mannosyl (beta-1,4-)-glycoprotein beta-1,4-N-acetylglucosaminyltransferase 2 209764 at 19-29 SLC4A11 solute carrier family 4, sodium borate transporter, member 11 3 223748 at 30-40 MSLN mesothelin 4 204885 s at 41 -51 FOXC1 forkhead box Cl 5 1553613 s at 52-62 RUNX2 runt-related transcription factor 2 6 232231 at 63-73 WNT11 wingless-type MMTV integration site family, member 11 7 206737_at 74-84 [0068] A correlation between the average value of logarithms (base = 2) of the 23 expression level calculated above (hereinafter referred to as Budding Signature Score (BSS); the specific calculation formula is shown below) and the budding grade by a pathological diagnosis is shown in Fig. 6. Herein, the budding grade was determined as defined in [Grade of budding] in the Clinical Practice Guideline of the Japan Society of Clinical Oncology. That is, an area with the most advanced budding in the specimen was selected, the invasive front of cancer development was observed in a field of view of 20 x 10 times, and the number of budding foci were counted. Based on the result, when the number of budding foci was 0 to 4, the area was classified as Grade 1, when the number was 5 to 9, the area was classified as Grade 2, and when the number was 10 or more, the area was classified as Grade 3. From Fig. 6, it was found that the BSS increases as the budding grade increases. That is, the higher the budding grade is, the more genes are expressed.
[0069] [Mathematical Expression 1]
Budding Signature Score = [Log2 (signal value of DN A chip of MSLN gene) + Log2 (signal value of DN A chip of SCEL gene) +
Log2 (signal value of DN A chip of RUNX2 gene) + Log2 (signal value of DNA chip of FOXC1 gene) + Log2 (signal value of DNA chip of MGAT3 gene) + Log2 (signal value of DNA chip of SLC4A11 gene) + Log2 (signal value of DNA chip of WNT11 gene)]/7 [0070] (2) Prognostic determination
An ROC analysis was performed on the 85 specimens using the BSS value calculated as described above, and a threshold was set. The results are shown in Fig. 7. In the ROC curve of Fig. 7, the threshold (8.436) was set to the value at which the sensitivity and specificity were the highest (the value corresponds to the point closest to 24 (sensitivity, specificity) = (1, 1) on the ROC curve). The area under the curve (AUC) was 0.602.
[0071]
Subsequently, the survival periods were compared between the specimens having a BSS not less than the threshold and the specimens having a BSS less than the threshold. The results are shown in Fig. 8. As shown in Fig. 8, a significant difference (p = 0.0479) was observed from the viewpoint of survival probability (probability) between the specimens having a BSS not less than the threshold and the specimens having a BSS less than the threshold. As described above, it was suggested that it is possible to determine whether a colorectal cancer patient has a high-risk prognosis or a low-risk prognosis based on the expression levels of seven genes, that is, the SCEL gene, MGAT3 gene, SLC4A11 gene, MSLN gene, FOXC1 gene, RUNX2 gene, and WNT11 gene.
[0072]
Example 2: Prognostic determination of colorectal cancer using seven genes (validation set)
The usefulness of the seven genes as colorectal cancer prognostic markers was further validated using published gene expression level data of colorectal cancer. The used data were GSE39582 (461 specimens) of Gene Expression Omnibus (GEO) (http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE39582). a public database.
The ROC analysis was performed in the same manner as in Example 1, and a threshold (7.686, AUC = 0.5752) was set. The survival periods were compared between the specimens having a BSS not less than the threshold and the specimens having a BSS less than the threshold. The results are shown in Figs. 9 and 10. As shown in Fig. 10, a significant difference (p = 0.000473) was observed from the 25 viewpoint of disease free survival between the specimens having a BSS not less than the threshold and the specimens having a BSS less than the threshold. This result reproduces the result of Example 1. Therefore, it was confirmed that the above-mentioned seven genes are useful as prognostic markers for colorectal cancer.
[0073]
Example 3: Prognostic determination of colorectal cancer using three genes The present inventor conducted the same experiment as in Example 2 using the same database as in Example 2 on the three genes of the SCEL gene, MGAT3 gene, and SLC4A11 gene. Specifically, the ROC analysis was performed in the same manner as in Example 2, and a threshold (6.112, AUC = 0.5828) was set. The relapse free survival periods (r.f.s. delay, number of days) were compared between the specimens having a BSS not less than the threshold (the specific calculation formula of the BSS in the case of three-gene measurement is shown below) and the specimens having a BSS less than the threshold. The results are shown in Figs. 11 and 12. As shown in Fig. 12, a significant difference (p = 0.000684) was observed from the viewpoint of survival probability between the specimens having a BSS not less than the threshold and the specimens having a BSS less than the threshold. Therefore, it was shown that the prognosis of colorectal cancer can be determined based on the expression levels of the above-mentioned three genes.
[0074] [Mathematical Expression 2]
Budding Signature Score = [Log2 (signal value of DNA chip of SCEL gene) + Log2 (signal value of DNA chip of MGAT3 gene) + Log2 (signal value of DNA chip of SLC4A11 gene)]/3 [0075] 26
Example 4: Prognostic determination of colorectal cancer using SCEL gene Whether or not the prognostic determination of colorectal cancer can be made based on the expression level of the SCEL gene was validated. That is, the same experiment as in Example 2 was conducted on the SCEL gene using the same database as in Example 2. Specifically, the ROC analysis was performed in the same manner as in Example 2, and a threshold (5.300, AUC = 0.6003) was set. The relapse free survival periods (number of days) were compared between the specimens having a BSS not less than the threshold (the specific calculation formula of the BSS in the case of one-gene measurement is shown below) and the specimens having a BSS less than the threshold. The results are shown in Figs. 13 and 14. As shown in Fig. 14, a significant difference (p = 0.000702) was observed from the viewpoint of survival probability between the specimens having a BSS not less than the threshold and the specimens having a BSS less than the threshold. Therefore, it was shown that the prognosis of colorectal cancer can be determined based on the expression level of the SCEL gene.
[0076] [Mathematical Expression 3]
Budding Signature Score = Log2 (signal value of DNA chip of SCEL gene)
REFERENCE SIGNS LIST
[0077] 10 Diagnosis assisting apparatus 20 Measuring device 30 Determining device 40 Recording medium 27
Computer main body
Input unit
Display unit
CPU
ROM
RAM
Hard disk
Input/output interface Reading device Communication interface Image output interface Bus
Acquisition unit Storage unit Calculation unit Determination unit Output unit
Claims (9)
1. A method for assisting in prognostic diagnosis of colorectal cancer, the method comprising the steps of: measuring an expression level of SCEL gene in a biological sample collected from a colorectal cancer patient, and determining a prognosis of colorectal cancer based on the expression level.
2. The method according to claim 1, wherein in the determination step, the expression level or a logarithm thereof is compared with a predetermined reference value, and when the expression level or a logarithm thereof is not less than the reference value, the patient is determined to have a poor prognosis, whereas when the expression level or a logarithm thereof is less than the reference value, the patient is determined to have a good prognosis.
3. The method according to claim 1, wherein in the measurement step, an 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, and in the determination step, the prognosis of colorectal cancer is determined based on the gene expression levels measured in the measurement step.
4. The method according to claim 1, wherein in the measurement step, expression levels of MGAT3 gene and SLC4A11 gene are further measured, and in the determination step, the prognosis of colorectal cancer is determined based on the gene expression levels measured in the measurement step.
5. The method according to claim 4, wherein in the measurement step, an expression level of MSLN gene, an expression level of FOXC1 gene, an expression level of RUNX2 gene, and an expression level of WNT11 gene are further measured, and in the determination step, the prognosis of colorectal cancer is determined based on the gene expression levels measured in the measurement step.
6. The method according to claim 1, wherein in the determination step, a logarithm of the gene expression level measured in the measurement step is calculated, the logarithm is compared with a predetermined reference value, and when the logarithm is not less than the reference value, the patient is determined to have a poor prognosis, whereas when the logarithm is less than the reference value, the patient is determined to have a good prognosis.
7. The method according to any one of claims 3 to 5, wherein in the determination step, an average value of the gene expression levels measured in the measurement step or a logarithm of the average value is calculated, the average value or the logarithm is compared with a predetermined reference value, and when the average value or the logarithm is not less than the reference value, the patient is determined to have a poor prognosis, whereas when the average value or the logarithm is less than the reference value, the patient is determined to have a good prognosis.
8. A computer program for making a computer execute the steps of: acquiring, from a measuring device, information relating to an expression level of SCEL gene in a biological sample collected from a colorectal cancer patient, and determining a prognosis of colorectal cancer in the patient based on the acquired information.
9. A determining device for determining a prognosis of colorectal cancer, comprising at least a computer including a processor and a memory, wherein the memory records therein a program for making the computer execute the steps of: acquiring, from a measuring device, information relating to an expression level of SCEL gene in a biological sample collected from a colorectal cancer patient, and determining a prognosis of colorectal cancer in the patient based on the acquired information.
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