WO2020105626A1 - Marker for predicting prognosis of pancreatic tumor - Google Patents

Abstract

The present invention addresses the problem of providing a biomarker which enables prediction of the prognosis of a patient with a tumor on the basis of the nature of tumor cells themselves. In the present invention, the prognosis of a pancreatic tumor of a subject is predicted by a method for detecting a marker for predicting the prognosis of a pancreatic tumor, the method comprising the step of detecting adipophilin in pancreatic tumor cells collected from the subject.

Description

Prognostic marker for pancreatic tumor

The present specification discloses a method for detecting a prognostic marker for pancreatic tumor, and a test reagent for detecting a prognostic marker for pancreatic tumor.

Pancreatic cancer has a poor prognosis and a high mortality rate. In order to predict the prognosis of pancreatic cancer, it has been reported that blood CA19-9 concentration, stump state after surgical cancer resection, tumor stage, etc. are used as indicators (Non-Patent Document 1). In recent years, it has been reported that the recurrence classification of National Comprehensive Cancer Network (NCCN) is useful for predicting the prognosis of pancreatic cancer.

However, currently reported prognostic factors for pancreatic cancer are factors that reflect the size of the tumor, residual tumor, etc., and do not reflect the properties of the tumor cells themselves. The malignancy of the tumor cells themselves influences the prognosis of the patient regardless of the size of the tumor, etc. However, at present, the prognosis cannot be predicted based on the malignancy of the tumor cells themselves. An object of the present invention is to provide a biomarker that can predict the prognosis of a patient having the tumor based on the properties of the tumor cell itself.

The present inventor has conducted extensive studies and found that the prognosis of a patient becomes poor when adipophilin is detected in the pancreatic tumor cells of the patient.
The present disclosure includes the following aspects.

Item 1. A method for detecting a prognostic marker for pancreatic tumor, comprising the step of detecting adipophilin in pancreatic tumor cells collected from a subject.
Item 2. Item 2. The detection method according to Item 1, further comprising the step of determining that the prognosis of the subject is poor when adipophilin is detected.
Item 3. Item 3. The detection method according to Item 1 or 2, wherein the prognosis is survival rate.
Item 4. Item 4. The detection method according to any one of Items 1 to 3, wherein detection of adipophilin is performed by immunostaining of a tumor tissue.
Item 5. A method of using adipophilin present in the cells of a pancreatic tumor as a biomarker for predicting the prognosis of a subject having the pancreatic tumor.
Item 6. Adipophilin present in pancreatic tumor cells collected from a subject is a test reagent for detecting as a biomarker for predicting the prognosis of the subject, wherein the test reagent is for detecting adipophilin. A test reagent containing the antibody or nucleic acid of.
Item 7. A prognostic marker of pancreatic tumor consisting of adipophilin.
Item 8. A prognosis predicting apparatus for pancreatic tumor, comprising a processing unit, wherein the processing unit obtains a measurement value of adipophilin in pancreatic tumor cells collected from a subject, and the obtained measurement value is a reference value. Compared, when the acquired measurement value is higher than the reference value, outputs a label indicating that the prognosis of the subject is poor, and / or the acquired measurement value is higher than the reference value. A prognosis prediction apparatus that outputs a label indicating that the subject has a good prognosis when the result is low.

Detecting adipophilin in pancreatic tumors can predict the prognosis of patients with pancreatic tumors.

1 shows an example of a schematic view of a pancreatic tumor prognosis prediction system 1000. An example of the block diagram of the prognosis prediction apparatus 10 of a pancreatic tumor is shown. An example of the operation of the pancreatic tumor prognosis prediction device 10 will be described. The hematoxylin-eosin staining example of the pancreatic cancer cell which has a transparent cytoplasm is shown. The stained image of the immunostaining positive example of adipophyrin of a pancreatic cancer tissue is shown. 2 shows a Kaplan-Meier plot of a pancreatic cancer patient. A shows the overall survival rate (OS) of the adipophilin expression positive group and the adipophilin expression negative group. B shows the recurrence-free survival rate (RFS) of adipophilin expression positive group and adipophilin expression negative group. 2 shows a Kaplan-Meier plot of a colorectal cancer patient.

1. Glossary of Terms Adipophilin is a lipid droplet-related protein that is present on the surface of lipid droplets in the cytoplasm. Adipophilin is also called perilipin 2 and is typically expressed from a gene registered in National Center for Biotechnology Information under Gene ID: 123. The biomarker composed of adipophilin includes a protein expressed from the gene or mRNA. Further, the biomarkers include variants expressed in addition to the proteins or mRNA expressed from the above genes.

Pancreatic tumor is not limited as long as it is a tumor derived from cells present in the pancreas. Pancreatic tumors may include malignant tumors and benign tumors, but may be tumors that have not been determined to be malignant or benign by histological diagnosis or the like. The pancreatic tumor is preferably a malignant tumor. The pancreatic tumor is preferably a cancer or a neuroendocrine tumor. Pancreatic cancer may include pancreatic ductal adenocarcinoma, mucinous cystadenocarcinoma, serous cystadenocarcinoma and the like. Pancreatic ductal adenocarcinoma is preferred. The pancreatic neuroendocrine tumor may include pancreatic neuroendocrine tumor grade 1, pancreatic neuroendocrine tumor grade 2, pancreatic neuroendocrine tumor grade 3, pancreatic neuroendocrine cancer, etc., classified by Ki-67 index. The pancreatic neuroendocrine tumor is preferably pancreatic neuroendocrine tumor grade 2, pancreatic neuroendocrine tumor grade 3, or pancreatic neuroendocrine cancer. The pancreatic tumor may be present in the pancreas, but may also be present in lymph nodes, portal veins, arteries, duodenum, bile ducts, liver, peritoneum, lungs and the like. In addition, the pancreatic tumor may be initial or recurrent. It is preferably the first shot.

The subject is not limited as long as it has a pancreatic tumor.

In the present disclosure, “prognosis” is intended to refer to the subject's outcome. The outcome of the subject is the outcome of the effect of the pancreatic tumor of the subject. The prognosis is preferably survival rate, tumor recurrence rate, presence or absence of metastasis, or tumor grade, more preferably survival rate is overall survival rate, recurrence rate is recurrence-free survival rate, metastasis is It is lymph node metastasis or metastasis to other organs, and the tumor grade is the degree of differentiation. When the pancreatic tumor is pancreatic cancer, it is preferable to evaluate the prognosis based on the survival rate and the recurrence rate of the tumor. The favorable prognosis is intended to mean, for example, that the survival rate at 30 months after diagnosis is 50% or more, preferably the survival rate at 36 months after diagnosis is 40% or more. A poor prognosis is intended to mean, for example, a survival rate after 30 months of diagnosis of less than 50%, preferably a survival rate of 36 months after diagnosis of less than 40%. A favorable prognosis means, for example, a recurrence-free survival rate of 6 months after the diagnosis is 70% or more, preferably a recurrence-free survival rate of 12 months after the diagnosis is 40% or more. A poor prognosis is intended to mean, for example, a recurrence-free survival rate of less than 50% 6 months after the diagnosis, preferably less than 25% of the recurrence-free survival rate 12 months after the diagnosis. In another aspect, a favorable prognosis means, for example, that no metastasis is observed. A poor prognosis is intended to mean, for example, that metastases are observed. In another aspect, a favorable prognosis means, for example, that the tumor is well-differentiated. Poor prognosis means, for example, that the tumor is poorly differentiated.

2. A prognostic marker for pancreatic tumor and a method for detecting the same A certain aspect of the present disclosure relates to a prognostic marker for pancreatic tumor and a method for detecting the same. The detection method comprises detecting adipophilin in pancreatic tumor cells. That is, adipophilin in tumor cells of pancreatic tumor can be used as a biomarker for predicting the prognosis of a subject having the pancreatic tumor.

The detection of adipophilin in pancreatic tumor is not limited as long as it is performed using pancreatic tumor cells or pancreatic tumor tissue collected from a subject. The pancreatic tumor cells or pancreatic tumor tissue can be collected by, for example, surgical excision or biopsy from the primary lesion or metastatic lesion, excision or biopsy under the endoscope, separation from ascites, and the like. The determination as to whether it is a tumor tissue or a normal tissue can be made by macroscopic observation, microscopic observation, or the like. Further, whether or not the tissue is a tumor tissue may be determined by using the cell proliferation ability and the presence of a tumor marker (for example, CA19-9) as an index. When it is determined whether the tissue is a tumor tissue using the cell proliferation ability as an index, for example, the labeling index of BrdU or Ki-67 protein (also referred to as “Ki-67 index”) of the test tissue is compared with that of a normal tissue. When it is high, it can be determined that the test target tissue is highly likely to be a tumor tissue. When a tumor marker is used as an index, it can be determined that a tissue in which the expression of the tumor marker is positive is highly likely to be a tumor tissue.

Pancreatic tumor cells or pancreatic tumor tissue collected from a subject are pretreated according to the method for detecting adipophilin.

Adipophilin in pancreatic tumor can be detected as a protein or mRNA.

As a method for detecting adipophilin as a protein, known methods such as immunostaining and western blotting can be mentioned. As a method for detecting adipophilin as mRNA, known methods such as in situ hybridization, RT-PCR (including quantitative RT-PCR), microarray, RNA-Seq and the like can be mentioned.

When immunostaining or in situ hybridization is performed using pancreatic tumor tissue, as a pretreatment, the pancreatic tumor tissue is fixed with a known fixative such as formalin and paraformaldehyde, and then a paraffin-embedded block is used. Create. Alternatively, the pancreatic tumor tissue is fixed or not fixed, and then embedded in a resin for producing a frozen block such as OCT Compound (registered trademark) to produce a frozen block. Next, the prepared paraffin-embedded block or frozen block is sliced to prepare a tissue section, and subjected to immunostaining or in situ hybridization. Here, the pancreatic tumor tissue embedded in the block may be only a tumor portion, but may include, for example, a normal portion.

When immunostaining or in situ hybridization is performed using pancreatic tumor cells, as a pretreatment, the cells are smeared or collected on a slide glass and fixed with formalin, paraformaldehyde, ethanol, etc.

When adipophilin is detected as a protein by Western blotting, pancreatic tumor cells or pancreatic tumor tissues are lysed with a prescribed lysis buffer as a pretreatment. The sample dissolved in the lysis buffer is used as the test sample.

When adipophilin is detected as mRNA using RT-PCR, microarray, RNA-Seq, etc., total RNA or mRNA is extracted from pancreatic tumor cells or pancreatic tumor tissue as a pretreatment. If necessary, reverse transcription may be performed using the extracted total RNA or mRNA as a template to synthesize complementary DNA (cDNA). Use total RNA, mRNA, or cDNA as the test sample.

The primary antibody for detecting adipophilin by immunostaining or Western blotting is not limited as long as it can detect adipophilin. For example, it is preferable to use an antibody prepared by using the N-terminal peptide of human adipophyrin as an antigen, particularly an antibody prepared by using the peptides of human adipophyrin 5th to 27th as an antigen. Specific examples of the primary antibody include anti-adipophilin mouse monoclonal primary antibody (AP125, Progen Biotechnik) and the like. The primary antibody bound to adipophilin can be detected by the reaction of the enzyme-labeled secondary antibody binding to the primary antibody and the enzyme with the substrate. When immunostaining is performed, the tissue sections may be treated with a proteolytic enzyme such as trypsin after deparaffinization and water immersion treatment, and then immunostaining may be performed.

A method for producing a probe used for in situ hybridization is known. Moreover, you may use a commercially available probe.

Commercially available primers can be used for the RT-PCR (the probe may be included in the case of the quantitative RT-PCR). In addition, a commercially available microarray can be used.

For RNA-Seq, the number of reads of adipophilin mRNA can be obtained using a next-generation sequencer (eg, Illumina).

When adipophilin is detected by immunostaining or in situ hybridization, the presence or absence of adipophilin can be detected by observing a tissue sample immunostained or in situ hybridized with a microscope or a slide scanner. Can be detected. When immunostaining or an in situ hybridization signal is confirmed in the tumor cells in the tissue sample, it can be determined (determined) that adipophilin was detected. When even one tumor cell having adipophilin in the cell is detected in the tumor part in the tissue specimen, it is determined that "adipophylline is detected" or "expression of adipophilin is positive" Is also good. Alternatively, for example, when the number of tumor cells existing in a predetermined section of a microscope or a slide scanner is 100%, the number of tumor cells having adipophilin in the cells is 10% or more, preferably 5% or more, Preferably, when 1% or more is present, it may be determined that “adipophilin was detected” or “adipophilin expression is positive”.

When adipophilin is detected by Western blotting, RT-PCR, RNA-Seq, when adipophilin is detected in a sample extracted from tumor cells or tumor tissues, "adipophilin is detected" or " The expression of adipophilin is positive ". Alternatively, a test sample derived from a tumor cell or a tumor tissue is compared with a protein amount of adipophilin derived from a normal cell or a normal tissue, or an mRNA amount of adipophilin, and adipophilin in a test sample derived from a tumor cell or a tumor tissue is compared. Or adipophilin mRNA level is higher than the protein level of adipophilin derived from normal cells or normal tissues, or the adipophilin mRNA level, "adipophilin was detected" or "adipophilin was detected". The expression of filin is positive. " Further, the amount of adipophilin protein in the test sample derived from tumor cells or tumor tissues, or the amount of adipophilin mRNA is similar to the amount of adipophilin protein derived from normal cells or normal tissues, or the amount of adipophilin mRNA. In some cases, it may be determined that "adipophilin is not detected" or "adipophilin expression is negative". Here, “showing a high value” may be, for example, 1.2 times or more, preferably 1.5 times or more, more preferably 2 times or more, and further preferably 5 times or more. The “similar degree” can be, for example, about 0.8 times to 1.1 times. In addition, before comparing the amount of adipophilin protein or the amount of adipophilin mRNA, the protein amount or RNA amount in each test sample was determined by using a housekeeping gene such as GAPDH, β ₂ -microglobulin, or β-actin. The amount of protein or mRNA may be normalized. The amount of protein may be represented by mass or concentration, but may also be represented by the emission intensity of the substrate or the like. The amount of mRNA may be the number of copies of mRNA or the number of reads, but may be represented by fluorescence intensity or the like.

In another embodiment, when the reference value of the amount of adipophilin protein or RNA is determined in advance and the amount of adipophilin protein or RNA in the test sample derived from tumor cells or tumor tissues is higher than the reference value, , "Adipophilin was detected" or "Adipophilin expression is positive". In addition, when the amount of adipophilin protein or RNA in the test sample derived from tumor cells or tumor tissue is lower than the reference value, "no adipophilin is detected" or "expression of adipophilin is negative" You may decide. The reference value is not limited as long as it is a value that can determine whether the amount of adipophilin protein or the amount of adipophilin mRNA is detected or the expression is positive, and can be determined by a known method. ROC (receiver operating characteristic curve) curve, discriminant analysis method, mode method, Kittler method, and a value that can determine whether the amount of adipophilin protein or the amount of adipophilin mRNA is detected or the expression is positive. It can also be determined by the 3σ method, the p-tile method, or the like. Further, as the reference value, sensitivity, specificity, negative predictive value, positive predictive value, first quartile, etc. can be exemplified.

The method for detecting a prognostic marker may further include the step of determining that the subject has a poor prognosis when adipophilin is detected. Alternatively, the method may include a step of determining that the subject has a favorable prognosis when adipophilin is not detected. Further, the method of detecting a prognostic marker may include the step of determining a necessary treatment method depending on whether or not adipophilin is detected in pancreatic tumor cells. For example, if adipophilin is detected, it may be decided to apply radiation therapy and / or adjuvant chemotherapy.

3. Test Reagent Another aspect of the present disclosure relates to a test reagent for detecting adipophilin present in pancreatic tumor cells collected from a subject as a biomarker for predicting the prognosis of the subject.

The test reagent may include a reagent for detecting adipophilin protein and / or a reagent for detecting adipophilin mRNA.

The reagent for detecting adipophilin protein contains at least one antibody (eg, primary antibody) capable of binding to at least a part of the adipophilin protein. As the “antibody”, any of a polyclonal antibody, a monoclonal antibody, and a fragment thereof (eg, Fab, F (ab ′), F (ab) ₂ etc.) can be used. The class and subclass of immunoglobulin is not particularly limited. The antibody may be one screened from an antibody library, or may be a chimeric antibody, scFv, or the like.

Further, the antibody does not necessarily have to be purified, and may be antiserum containing the antibody, ascites, immunoglobulin fraction fractionated from these, or the like.

The antibody contained in the test reagent may be in a dried state or may be dissolved in a buffer such as phosphate buffered saline. Furthermore, the test reagents include stabilizers such as β-mercaptoethanol and DTT; protective agents such as albumin; surfactants such as polyoxyethylene (20) sorbitan monolaurate and polyoxyethylene (10) octylphenyl ether; It may contain at least one preservative such as sodium azide.

The antibody that binds to adipophilin may be labeled with an enzyme or a fluorescent dye. The antibody that binds to adipophilin may be immobilized on a microplate, magnetic beads, or the like.

The reagent for detecting adipophilin protein may be provided as a test kit including a test reagent and a package insert describing a method of using the reagent or a URL of a web page describing the method of using the reagent. When the antibody that binds to adipophilin is an unlabeled primary antibody, the test kit may include a secondary antibody labeled with an enzyme or a fluorescent dye. Furthermore, the test kit may contain a substrate that reacts with the enzyme.

The reagent for detecting adipophilin mRNA contains a nucleic acid that hybridizes with all or part of adipophyrin mRNA or adipophyrin cDNA. The nucleic acid is preferably a nucleic acid for detection (DNA or RNA) having a function as a primer and / or a probe. The length of the nucleic acid for detection is not particularly limited.

If the nucleic acid for detection is a primer used in a PCR reaction, the sequence that hybridizes with adipophilin mRNA or adipophyrin cDNA is preferably 50 mer or less, more preferably 30 mer or less, and further preferably , About 15 to 25 mer. The primer may include a sequence that does not hybridize with adipophilin mRNA or adipophilin cDNA. Further, the primer may be labeled with a fluorescent dye or the like.

Also, in RT-PCR, in addition to the primers, a quantification probe that is decomposed during the PCR reaction, which is used for real-time quantification of PCR products, can be used. The quantification probe is not limited as long as it hybridizes with adipophilin mRNA or adipophilin cDNA. The quantification probe is preferably a nucleic acid of about 5 to 20 mer containing a sequence that hybridizes with adipophilin mRNA or adipophilin cDNA. Further, it is preferable that one end of the quantification probe is labeled with a fluorescent dye, and the other end of the quantification probe is labeled with a quencher of the fluorescent dye.

If the nucleic acid for detection is used as a capture probe in a microarray or the like, the sequence that hybridizes with adipophyrin mRNA or adipophyrin cDNA is preferably about 100 mer, more preferably about 60 mer, More preferably, it is about 20 to 30 mer. The capture probe may include a sequence that does not hybridize with adipophilin mRNA or adipophilin cDNA. Furthermore, the capture probe is preferably immobilized on the chip.

When the nucleic acid for detection is a probe for in situ hybridization, the nucleic acid for detection may be an oligonucleotide having a sequence that hybridizes with adipophyrin mRNA of about 15 to 100 mer, and may be a polynucleotide having a sequence of more than 100 mer. It may be a nucleotide. The polynucleotide may be DNA or RNA. Labeling substances such as digoxigenin and fluorescent dyes can be bound to the probe for in situ hybridization. The probe may contain a sequence that does not hybridize with adipophilin mRNA.

The reagent for detecting adipophilin mRNA may be provided as a test kit including a test reagent and a package insert describing a method of using the reagent or a URL of a web page describing the method of using the reagent. When detecting adipophilin mRNA or adipophilin cDNA by RT-PCR, the test kit contains a nucleic acid amplification reagent (including thermostable DNA including polymerase, buffer, dNTP, etc.), reverse transcriptase, etc. You can leave. The nucleic acid amplification reagent may contain a dye such as SYBER GREEN (registered trademark) if necessary. When adipophilin mRNA or adipophilin cDNA is detected by a microarray, the test kit may include a hybridization buffer, a washing buffer and the like. When detecting adipophyrin mRNA by in situ hybridization, the test kit may include a proteolytic enzyme such as proteinase K, a hybridization buffer, and a washing buffer.

4. Prognosis prediction device for pancreatic tumor 4-1. Configuration of Prognosis Prediction Device for Pancreatic Tumor One embodiment of the present disclosure relates to a prognosis prediction system 1000 for pancreatic tumor and a prognosis prediction device 10 for pancreatic tumor.

FIG. 1 is a schematic view of a prognosis prediction system 1000 for pancreatic tumor. As one aspect, the prognosis prediction system 1000 for pancreatic tumor includes a prognosis prediction device 10 for pancreatic tumor, and an analysis device 5a or an analysis device 5b. May be.

FIG. 2 shows a block diagram of the pancreatic tumor prognosis prediction apparatus 10. The pancreatic tumor prognosis prediction apparatus 10 may be connected to the input unit 111, the output unit 112, and the storage medium 113.

In the pancreatic tumor prognosis prediction device 10, a processing unit 101, a main storage unit 102, a ROM (read only memory) 103, an auxiliary storage unit 104, a communication interface (I / F) 105, and an input interface (I / F). The F) 106, the output interface (I / F) 107, and the media interface (I / F) 108 are connected to each other by a bus 109 so that data communication can be performed therebetween. The main storage unit 102 and the auxiliary storage unit 104 may be collectively referred to as a storage unit. The storage unit stores the measured value and the reference value in a volatile or non-volatile manner.

The processing unit 101 is the CPU of the pancreatic tumor prognosis prediction apparatus 10. The processing unit 101 may be a GPU. The processing unit 101 executes the computer program stored in the auxiliary storage unit 104 or the ROM 103 and processes the acquired data, so that the pancreatic tumor prognosis prediction apparatus 10 functions.

The ROM 103 is composed of a mask ROM, a PROM, an EPROM, an EEPROM, etc., and stores a computer program executed by the processing unit 101 and data used for the computer program. The processing unit 101 may be the MPU 101. The ROM 103 stores a boot program executed by the processing unit 101 when the pancreatic tumor prognosis prediction apparatus 10 is activated, and programs and settings related to the operation of the hardware of the pancreatic tumor prognosis prediction apparatus 10.

The main storage unit 102 is configured by a RAM (Random access memory) such as SRAM or DRAM. The main storage unit 102 is used for reading the computer programs recorded in the ROM 103 and the auxiliary storage unit 104. Further, the main storage unit 102 is used as a work area when the processing unit 101 executes these computer programs.

The auxiliary storage unit 104 includes a hard disk, a semiconductor memory device such as a flash memory, an optical disk, and the like. The auxiliary storage unit 104 stores various computer programs to be executed by the processing unit 101 such as an operating system and application programs, and various setting data used for executing the computer programs. Specifically, the reference value and the like are stored in a nonvolatile manner.

The communication I / F 105 includes a serial interface such as USB, IEEE1394, RS-232C, a parallel interface such as SCSI, IDE, and IEEE1284, an analog interface including a D / A converter and an A / D converter, a network interface controller ( Network interface controller (NIC), etc. The communication I / F 105, under the control of the processing unit 101, receives data from the analyzers 5a and 5b or other external devices, and stores information generated or stored by the pancreatic tumor prognosis prediction apparatus 10 as necessary, It is transmitted or displayed to the analyzers 5a, 5b or the outside. The communication I / F 105 may communicate with the analyzers 5a and 5b or other external devices via a network.

The input I / F 106 is composed of, for example, a serial interface such as USB, IEEE 1394, RS-232C, etc., a parallel interface such as SCSI, IDE, IEEE 1284, etc., and an analog interface such as a D / A converter, A / D converter, etc. It The input I / F 106 receives character input, click, voice input, and the like from the input unit 111. The received input content is stored in the main storage unit 102 or the auxiliary storage unit 104.

The input unit 111 includes a touch panel, a keyboard, a mouse, a pen tablet, a microphone, etc., and performs character input or voice input to the pancreatic tumor prognosis prediction device 10. The input unit 111 may be connected from the outside of the pancreatic tumor prognosis prediction apparatus 10 or may be integrated with the pancreatic tumor prognosis prediction apparatus 10.

The output I / F 107 is composed of the same interface as the input I / F 106, for example. The output I / F 107 outputs the information generated by the processing unit 101 to the output unit 112. The output I / F 107 outputs the information generated by the processing unit 101 and stored in the auxiliary storage unit 104 to the output unit 112.

The output unit 112 is composed of, for example, a display, a printer, and the like, and displays the measurement results transmitted from the analyzers 5a and 5b, various operation windows in the pancreatic tumor prognosis prediction device 10, analysis results, and the like.

The media I / F 108 reads out, for example, application software stored in the storage medium 113. The read application software and the like are stored in the main storage unit 102 or the auxiliary storage unit 104. The media I / F 108 also writes the information generated by the processing unit 101 in the storage medium 113. The media I / F 108 writes the information generated by the processing unit 101 and stored in the auxiliary storage unit 104 into the storage medium 113.

The storage medium 113 is composed of a flexible disk, a CD-ROM, a DVD-ROM, or the like. The storage medium 113 is connected to the media I / F 108 by a flexible disk drive, a CD-ROM drive, a DVD-ROM drive, or the like. The storage medium 113 may store an application program or the like for a computer to execute an operation.

The processing unit 101 may acquire application software and various settings necessary for controlling the prognosis prediction device 10 for pancreatic tumor via the network instead of reading from the ROM 103 or the auxiliary storage unit 104. The application program is stored in an auxiliary storage unit of a server computer on a network, and the pancreatic tumor prognosis prediction apparatus 10 accesses the server computer to download the computer program and store it in the ROM 103 or the auxiliary storage unit 104. It is also possible to memorize.

Further, in the ROM 103 or the auxiliary storage unit 104, an operating system that provides a graphical user interface environment such as Windows (registered trademark) manufactured and sold by US Microsoft Co. is installed. The application program according to the second embodiment operates on the operating system. That is, the pancreatic tumor prognosis prediction apparatus 10 may be a personal computer or the like.

The pancreatic tumor prognosis prediction system 1000 does not need to be installed in one place, and the pancreatic tumor prognosis prediction device 10 and the analysis devices 5a and 5b may be arranged in different places and may be connected by a network. The pancreatic tumor prognosis prediction device 10 may be a device that does not require an operator who omits the input unit 111 and the output unit 112.

The analyzer 5a is a device for measuring the amount or concentration of protein, and includes a sample storage space 51, a reaction section 52, and a detection section 53. The cell lysate set in the sample storage 51 is dispensed and incubated in the microplate on which the antigen-capturing antibody is mounted in the reaction section 52. After removing unreacted antigen as needed, the detection antibody is dispensed to the microplate and incubated. After removing unreacted antigen as necessary, a substrate for detecting the detection antibody is dispensed to the microplate, the microplate is moved to the detection unit 53, and the signal generated by the reaction of the substrate is measured. To be done.

Another embodiment of the analysis device 5a is a device for measuring the expression level of mRNA by microarray analysis, in which the reverse transcription reaction product set in the sample storage space 51 is distributed on the microarray chip set in the reaction part 52. After pouring, hybridization and washing, the sample is moved to the detection unit 53 to detect a signal.

Furthermore, another embodiment of the analyzer 5a is a device for measuring the expression level of mRNA by RT-PCR, in which the reverse transcription reaction product set in the sample storage space 51 is placed in the microtube set in the reaction part 52. Dispense, and then a quantitative PCR reagent is dispensed into a microtube. While performing the PCR reaction in the reaction section 52, the detection section 53 detects the signal in the tube.

The analysis device 5b is a device for measuring the expression level of mRNA by the RNA-Seq method, and includes a sequence analysis unit 54. The sample subjected to the reaction for RNA-Seq is set in the sequence analysis unit 54, and the base sequence is analyzed in the sequence analysis unit 54.

The analyzer 5b is a fully automatic Western blotting apparatus for measuring the amount of protein by Western blotting, and includes a chemiluminescence signal detection unit 54. A sample of pancreatic tumor cells or pancreatic tumor tissue lysed with a lysis buffer is set at a predetermined position of an automatic western blotting device, SDS-PAGE, blotting on a membrane, antibody reaction, chemiluminescence, and chemiluminescence signal detection unit Analysis is performed at 54 to quantify the signal intensity.

The analysis devices 5a and 5b are connected to the pancreatic tumor prognosis prediction device 10 by wire or wirelessly. The analyzer 5a A / D-converts the measured value of the protein or the measured value of the mRNA, and sends it to the pancreatic tumor prognosis prediction apparatus 10 as digital data. Similarly, the analyzer 5b A / D-converts the measured value of mRNA, and transmits it to the pancreatic tumor prognosis prediction device 10 as digital data. As a result, the pancreatic tumor prognosis prediction apparatus 10 can acquire the measured value of protein or the measured value of mRNA as digital data that can be processed.

4-2. Operation of Pancreatic Tumor Prognosis Prediction Device FIG. 3 shows an example of a flowchart of an operation example of the pancreatic tumor prognosis prediction device 10.

The processing unit 101 of the pancreatic tumor prognosis prediction apparatus 10 starts the process for predicting the prognosis of the pancreatic tumor of the subject when the operator inputs the process start from the input unit 111. In step S11, the processing unit 101 determines the protein amount of adipophilin in the pancreatic tumor cells collected from the subject from the analyzer 5a or the analyzer 5b, the amount of adipophilin mRNA, or a value reflecting the amount of adipophilin. Is obtained as the measurement value of. Alternatively, the operator inputs from the input unit 111 whether the expression of adipophilin by immunostaining or in situ hybridization is positive or negative (or whether or not adipophilin is detected), and the processing unit 101 The input may be obtained as a measurement of adipophilin.

Next, in step S12, the processing unit 101 compares the reference value of adipophyrin stored in the storage unit with the measurement value acquired in step S11.

When the acquired measurement value is higher than the reference value in step S13, the processing unit 101 proceeds to step S14 (YES), determines that the prognosis of the subject is poor, and determines the determination result. The indicated label is output to the output unit 112 (step S16). Further, in step S13, when the obtained measured value is lower than the reference value, the process proceeds to step S15 (NO), it is determined that the prognosis of the subject is good, and a label indicating the determination result is output by the output unit 112. (Step S16). If the prognosis is determined to be poor, the label includes information indicating "poor prognosis" or "indicative of poor prognosis." If the prognosis is determined to be good, the label includes information indicating "good prognosis" or "indicative of good prognosis." The information may be a mark such as X, O, exclamation mark, or the like.

For details on the standard value, comparison method, and method for determining whether the measured value is higher or lower than the standard value, see 2. Is incorporated herein by reference.

4-3. Prognosis Prediction Program This embodiment includes a computer program for causing a computer to execute the processes of steps S11 to S16, and for predicting the prognosis of a pancreatic tumor.
Further, an embodiment of the present embodiment relates to a program product such as a storage medium that stores the computer program. That is, the computer program can be stored in a hard disk, a semiconductor memory device such as a flash memory, or a storage medium such as an optical disk. The recording format of the program in the storage medium is not limited as long as the training device 200A can read the program. The recording on the storage medium is preferably non-volatile.

5. Treatment Method for Pancreatic Cancer In the present disclosure, the treatment method can be determined depending on whether the expression of adipophilin in the tumor tissue is positive or negative. For example, when adipophilin expression is positive in a biopsy test before surgery, it is preferable to perform chemotherapy and / or radiation therapy before performing tumor removal surgery. The chemotherapy and / or radiation therapy is preferably performed even when the tumor is determined to be surgically resectable. In chemotherapy, at least one selected from the group consisting of fluorouracil, levofolinate, irinotecan, oxaliplatin, gemcitabine, and nabupaclitaxel can be used as the anticancer agent. Further, chemotherapy using fluorouracil, levofolinate, irinotecan, and oxaliplatin, chemotherapy using gemcitabine and nabupaclitaxel, and the like may be performed.

Also, if adipophilin expression is negative in the preoperative biopsy test etc., tumor removal surgery may be performed without preoperative chemotherapy.

The present disclosure will be described in more detail below with reference to examples, but the present disclosure should not be construed as being limited to the examples.

This study was conducted with the approval of the Ethics Committee of Kansai Medical University, a school corporation based on the Declaration of Helsinki.

I. Example 1
1. Patient selection From January 2008 to December 2015, 213 patients who underwent surgical resection for ductal adenocarcinoma of the pancreas (PDAC) at the Kansai Medical University Hospital and who continued to be examined were selected. Patients who died of other causes or complications (19) and patients who were unable to follow up their clinical course within 24 months (13) were excluded from the study.

Finally, we examined 181 patients whose tumor residual rate was R0 or R1.

2. Histological examination The surgically excised tissue sample was fixed with formalin to prepare a tissue specimen. The tissue specimen was prepared by embedding all fixed tissue samples in paraffin, preparing thin-sectioned sections, and performing hematoxylin-eosin staining. The prepared tissue sample was examined microscopically and histologically classified (grading) based on World Health Organization Classification 2010, and tumor tissues were classified into well-differentiated adenocarcinoma, moderately differentiated adenocarcinoma, and poorly differentiated adenocarcinoma. .. Tumor cells having a clear cytoplasm have been reported to have high reactivity with anti-adipophilin antibodies in immunostaining. Based on this finding, whether or not the cytoplasm of the tumor cells was transparent was also evaluated in the observation of the tissue specimen.

Tumor staging was performed on all patients based on TNM clinical staging 8th edition (Union for International Cancer Control).

3. Tissue microarray For each patient's tissue, select the most morphologically characteristic cancerous part in the tissue sample stained with hematoxylin-eosin and select two tissue masses (diameter 2 mm) from the paraffin-embedded block. Was punched. The punched tissue mass was further arranged and embedded in a paraffin block and sliced to prepare a tissue section.

4. Immunostaining Immunostaining was performed using an automatic staining device (Discovery, Roche Diagnostics, Basel, Switzerland) according to the protocol attached to the device. Anti-adipophilin mouse monoclonal primary antibody (AP125, Progen Biotechnik, Heidelberg, Germany) was used as a primary antibody for staining adipophilin. A peroxidase-labeled anti-mouse immunoglobulin antibody was used as a secondary antibody, and diaminobenzidine (DAB) was used for color development. The sebaceous glands of the skin were used as a positive control. The expression of adipophilin was determined to be "positive" when the number of tumor cells showing granular and / or spherical expression in the cells was 5% or more of the whole tumor tissue. Further, when one or more of the two cell masses collected in the same patient became positive, it was determined that the tumor of that patient was positive for adipophilin expression.

5. Statistical analysis For statistical analysis, JMP Start Statistics version 14 (Statistical Discovery Software; SAS Institute, Cary, NC, USA) was used. The chi-square test was performed between the adipophyrin expression positive group and the adipophilin expression negative group. All patients were followed up for at least 2 years and until 16 March 2018. Overall survival (OS) and recurrence-free survival (RFS) rates were evaluated by the Kaplan-Meier method. The significant difference between the adipophilin expression positive group and the adipophilin expression negative group was determined by the log-rank test. When p value <0.05, it was judged that there was a significant difference. The continuous variables of tumor diameter and CA19-9 level were binarized by the cutoff value obtained based on the ROC (Receiver Operatorating Characteristic) curve. Risk factors for OS and recurrence rate (within 6 months) were determined by logistic regression analysis, which is a multivariate analysis, and expressed by hazard ratio, 95% confidence interval, and p-value. Significant factors determined by univariate analysis to identify important independent factors were further evaluated by multivariate logistic regression analysis.

6. Result 6-1. Clinicopathological Features Table 1 shows the clinicopathologic features of the patients. Of the 181 patients studied, 74 were female and 107 were male. The age of patients who underwent tumor resection surgery was 36 to 86 years, with a median of 68 years. The follow-up period was 25 to 115 months with a median of 48 months. 122 patients (67.4%) died of pancreatic ductal adenocarcinoma. Recurrence was observed in 126 (69.6%) patients. In 117 cases, a tumor was present in the head of the pancreas, and in 64 cases, a tumor was present in the body or tail of the pancreas. Based on the National Comprehensive Cancer Network (NCCN) resectable classification, 134 cases were classified as resectable (R), 43 cases were resectable boundaries (BR), and 4 cases were unresectable (UR). .. By tumor residual classification, 150 patients were classified as R0 and 31 as R1. According to the clinical staging by TNM classification, the number of patients classified into pT1b, pT1c, pT2, pT3 and pT4 was 1, 10, 105, 63 and 2, respectively. Lymph node metastases were found in 133 (73.5%) patients. The patient stages were IA (5), IB (36), IIA (7), IIB (69), III (63), and IV (1). Preoperative chemotherapy (neoadjuvant chemotherapy) was given to 69 (38.1%) patients.

Histologically, 42 (23.2%) were classified as well-differentiated adenocarcinoma, 115 (63.5%) were classified as moderately differentiated adenocarcinoma, and 24 (13.3%) were poorly differentiated adenocarcinoma. Classified as cancer. Tumor cells having a transparent cytoplasm as shown in FIG. 4 were found in 44 (24.3%) cases.

6-2. Expression of adipophilin Expression of adipophilin was observed in 51 (28.2%) cases. FIG. 5 shows an example of dyeing. In most cases, adipophilin showed a globular staining morphology in the nucleus. Table 1 shows the clinicopathologic characteristics of the cases with positive expression of adipophilin and those with negative expression of adipophilin. Positive adipophilin expression was significantly associated with poorly differentiated adenocarcinoma (p = 0.0012). The positive expression of adipophilin was also significantly associated with the high preoperative CA19-9 level (p = 0.0016). In addition, adipophilin expression-positive patients were more likely to be classified as tumor residual rate R1 than adipophilin-negative patients (27.5% vs. 13.1%, p = 0.028).

On the other hand, no positive relationship between adipophilin expression and tumor size, clinical staging, or lymph node metastasis was observed (p values are p = 0.052, p = 0.23, p = 0.57). Moreover, no association was observed between adipophilin expression and the appearance of tumor cells with a clear cytoplasm (p = 0.59).

6-3. Prognostic significance of adipophilin expression We examined the relationship between the presence or absence of adipophilin expression and the survival rate of patients.
FIG. 6A shows survival time (OS) curves of adipophilin expression-positive patients and adipophilin expression-negative patients. FIG. 6B shows recurrence-free survival (RFS) curves of adipophilin expression-positive patients and adipophilin expression-negative patients. Patients with positive adipophilin expression had significantly lower survival rates for both OS and RFS (OS: p = 0.0007, RFS: p = 0.0022) compared to patients with negative adipophilin expression. The median survival of patients with negative adipophilin expression was 31.5 months, while the median survival of patients with positive adipophilin expression was 16 months. In addition, the median recurrence-free survival rate for patients with negative adipophilin expression was 12 months, whereas the median recurrence-free survival rate for patients with positive adipophilin expression was 6.5 months.

Table 2 shows the results of univariate analysis and multivariate analysis of various factors in OS.

In univariate Cox regression analysis, adipophilin expression may be used as a prognostic predictor, preoperative albumin concentration (<3.8g / dL), CA19-9 concentration (> 186U / mL), treatable with NCCN BR or UR in sex classification, larger tumor size (> 32 mm), III or IV in staging, R1 in tumor residual rate, and similar to the application of adjuvant chemotherapy It was shown to be a dominant poor prognostic factor. Furthermore, in multivariate analysis, adipophilin expression showed a hazard ratio of 1.64, 95% confidence interval 1.14-2.34, and p = 0.0084. On the other hand, in the multivariate analysis, the association between OS and belonging to BR or UR in the therapeutic possibility classification by NCCN showed hazard ratio 1.64, 95% confidence interval 1.13-2.34, p = 0.0088. The association between OS and high concentration of preoperative CA19-9 was hazard ratio 1.48, 95% confidence interval 1.05-2.07, p = 0.026. The association between OS and application of adjuvant chemotherapy was a hazard ratio of 0.45, 95% confidence interval of 0.29-0.73, and p == 0.0018. That is, it was shown that the expression of adipophilin was more strongly associated with OS in the hazard ratio or p-value than that of factors other than the expression of adipophilin. From this result, it was shown that adipophilin expression is an important factor and an independent factor in OS of pancreatic cancer patients. In addition, adipophilin expression is more closely associated with preoperative CA19-9 concentration, which is used as a prognostic marker for pancreatic cancer, and OS in pancreatic cancer patients than in clinical staging. It has been shown to be an important marker for prediction.

Table 3 shows the results of univariate analysis and multivariate analysis of various factors in RFS.
Adipophilin expression was also an important and independent factor in early recurrence in patients with ductal adenocarcinoma of the pancreas (hazard ratio 2.43; 95% confidence interval 1.08-5.19; p = 0.030). Therefore, adipophilin expression was shown to be an important factor and an independent factor in predicting early recurrence in patients with ductal adenocarcinoma of the pancreas. The preoperative CA19-9 concentration was also 2.37; 95% confidence interval 1.09-5.43; p = 0.030, but the hazard ratio was higher when adipophilin was expressed.

From this, it was also shown that adipophilin expression is a predictive marker for early recurrence in pancreatic cancer patients.

These results indicate that adipophilin expression is highly associated with overall-term survival rate and recurrence-free survival rate as compared with other prognostic markers, and is superior as a prognostic marker for pancreatic tumors. It was

In addition, no association was found between adipophilin expression and recurrence probability classification, tumor size, or clinical staging, while the recurrence-free survival rate of adipophilin-positive patients was adipophilin-negative. The cells that express adipophilin itself have a high recurrence rate and the prognosis of the patient, because it is worse than that of the patient and there is a relationship between highly differentiated poorly differentiated adenocarcinoma and the expression of adipophilin. It was considered to be a highly malignant cell that has a poor maturity.

II. Example 2
Pancreatic neuroendocrine tumor (PNET) and pancreatic neuroendocrine cancer (PNEC) are classified into PNET grade 1 (PNET G1), PNET grade 2 (PNET G1) by classification using the positive ratio of cell proliferation markers such as Ki-67 index and mitotic figures. It is classified into PNET G2), PNET grade 3 (PNET G3) and PNEC.

Therefore, we investigated the relationship between the expression of adipophilin in PNET and PNEC and its malignancy.

1. Patients and Evaluation Method From January 2007 to December 2017, 15 patients with PNET G1 and 10 patients with PNET G2 who underwent surgical resection of pancreatic neuroendocrine tumors at the Kansai Medical University Hospital Was picked up and examined. We also examined 3 PNEC patients.

Staining and evaluation of adipophilin were performed in the same manner as in Example 1.

2. Results The number of patients judged to be positive for adipophilin staining was 3 for PNET G1 patients, 4 for PNET G2 patients, and 3 for PNEC patients. Comparing the number of adipophilin-positive patients between grades, (PNET G1) vs (PNET G2 + PNEC) was p = 0.06, (PNET G1 + PNET G2) vs PNEC was p = 0.014, and adipophilin-positive patients were NET G2 It was shown that the above cases tended to be common.

Also, when comparing the presence or absence of lymph node metastasis, as shown in Table 4, it was shown that there were many adipophilin-positive cases among the cases in which lymph node metastasis was soluble.

From these results, it was shown that adipophilin well reflects the malignancy of pancreatic tumors and is useful as a prognostic marker for pancreatic tumor patients.

III. Comparative Example Whether or not adipophilin was correlated with the prognosis of colorectal cancer was examined. Paraffin-embedded tumor tissue of 165 colorectal cancer patients (95 men, 70 women) who underwent surgery at Kansai Medical University Hospital between January 2014 and December 2014 was examined. Patient ages ranged from 33 to 99 years with a median of 78 years.

Adipophilin was stained by the same method as in Example 1, and when the number of tumor cells showing granular and / or spherical expression in the cells was 50% or more of the whole tumor tissue, the expression of adipophilin was " "Positive" was determined. However, as shown in FIG. 7, no correlation was observed between the expression of adipophilin and the survival rate (p = 0.21).

101 Processing Unit 10 Prognosis Prediction Device

Claims (8)

1. A method for detecting a prognostic marker for pancreatic tumor, comprising the step of detecting adipophilin in pancreatic tumor cells collected from a subject.
2. The detection method according to claim 1, further comprising a step of determining that the prognosis of the subject is poor when adipophilin is detected.
3. The detection method according to claim 1, wherein the prognosis is survival rate.
4. The detection method according to any one of claims 1 to 3, wherein the detection of adipophilin is performed by immunostaining of a tumor tissue.
5. A method of using adipophilin present in the cells of a pancreatic tumor as a biomarker for predicting the prognosis of a subject having the pancreatic tumor.
6. Adipophilin present in pancreatic tumor cells collected from a subject is a test reagent for detecting as a biomarker for predicting the prognosis of the subject, wherein the test reagent is for detecting adipophilin. The test reagent, which comprises the antibody or nucleic acid of.
7. A prognostic marker of pancreatic tumor consisting of adipophilin.
8. A prognosis prediction apparatus for pancreatic tumor, comprising a processing unit,
   The processing unit is
   Obtaining the measured value of adipophilin in pancreatic tumor cells collected from the subject,
   Compare the acquired measurement value with the reference value,
   When the obtained measurement value is higher than the reference value, a label indicating that the prognosis of the subject is poor is output, and / or the obtained measurement value is lower than the reference value. , Outputting a label indicating that the prognosis of the subject is good,
   Prognosis prediction device.

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