JP2010107306A - Prognostic prediction method of esophagus cancer - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To provide a method for predicting a prognosis of an esophagus cancer patient, a method for providing information on a selection of a medical treatment, and a reagent for a prognostic prediction of the esophagus cancer patient. <P>SOLUTION: The invention detects an expression of a biomarker within a sample obtained from the esophagus cancer patient and predicts the prognosis of an esophagus cancer from an excess or a decrease in the expression of the biomarker. The biomarker is preferably transglutaminase 3. <P>COPYRIGHT: (C)2010,JPO&INPIT

Description

  The present invention relates to the field of gene medicine related to predicting the prognosis of esophageal cancer patients, and particularly to a prognosis prediction method based on tumor gene expression information. More particularly, the present invention relates to a method for detecting abnormalities in targeted protein or mRNA levels.

  Esophageal cancer is the eighth most common cancer in the world and the sixth cause of death due to cancer (see Non-Patent Documents 1 and 2). Despite the recent development of surgical techniques combining radiotherapy and chemotherapy, early recurrence is not uncommon, especially in advanced cancers that have infiltrated the muscle layer or lymph node metastasis, and the 5-year survival rate is still around 40. % (See Non-Patent Documents 3 to 5). In clinical practice, it has been reported that adjuvant and neoadjuvant chemotherapy for esophageal cancer patients have improved survival (see Non-Patent Document 6). However, many patients in these clinical trials have experienced serious side effects, and there are cases where therapeutic agents have little or no effect on cancer cells. So far, when such a treatment method is applied to all esophageal cancer patients, there has been a problem that unnecessary and harmful combination therapy must be received even for patients who can be completely cured by surgery alone.

  Patients' responses to treatments such as surgery and chemo-radiotherapy, even if they were at the same clinical stage, were widely different and could not be predicted by existing diagnostic methods . One of the obstacles to effective treatment management of esophageal cancer patients is that there is a limit to predicting the course of the disease. For example, in the past, physicians have not been able to select patients who can benefit from more aggressive surgical treatment and / or therapeutic effects such as radiation and chemotherapy. Thus, risk stratification is considered critically important to avoid the possibility of treatment death or prevent further progression of the disease.

  It has been reported that substitution of multiple genes and proteins is involved in esophageal cancer (Non-patent Document 7). These substitutions can be thought of as biomarkers, and may be used to diagnose cancer, track progress, and monitor disease progression and response to treatment. However, many of them have a problem of low sensitivity or high false positive rate. In addition, these biomarkers have been studied for the purpose of mainly serving as an indicator of the presence of cancer, and do not predict the future of cancer, that is, the prognosis. Therefore, there is a need for new cancer prediction methods to optimize treatment strategies and improve clinical outcomes.

Transglutaminase 3 is an enzyme that forms a protein cross-linking bond by binding a protein polyamine, and is known to act in the late stage of the cell coat of the epidermis or hair follicle. In relation to esophageal cancer, there is a report that the level of transglutaminase 3 mRNA is decreased in esophageal cancer tissues (Non-patent Document 8). There is also a report on the relationship between protein level expression of transglutaminase 3 and esophageal cancer (Non-patent Document 9). However, in this report, it has been shown that there is no correlation between lymph node metastasis that can be an indicator of cancer prognosis and the expression of transglutaminase 3, and although transglutaminase 3 is an indicator of the presence of esophageal cancer, It was thought not to be an indicator for prognosis. It should be noted that the citation of the above documents is not intended as an admission that any of the above descriptions is related prior art. The statements regarding the date and content of these documents are based on information available to the applicant and are not endorsed for the accuracy of the date or content of these documents. It is not intended to be limited by any theory or hypothesis described.
Parkin DM, Pisani P, Ferlay J. Estimates of the worldwide incidence of 25 major cancers in 1990.Int J Cancer1999; 80: 827-41. Pisani P, Parkin DM, Bray F, Ferlay J. Estimates of the worldwide mortality from 25 cancers in 1990. Int J Cancer1999; 83: 18-29. Ilson DH. Oesophageal cancer: newdevelopments in systemic therapy.Cancer Treat Rev 2003; 29: 525-32. Enzinger PC, Mayer RJ.Esophageal cancer.N Engl J Med2003; 349: 2241-52. Mariette C, Balon JM, Piessen G, Fabre S, Van Seuningen I, Triboulet JP. Pattern of recurrence following completeresection of esophageal carcinoma and factors predictive of recurrent disease.Cancer 2003; 97: 1616-23. Shinoda M, Hatooka S, Mori S, Mitsudomi T. Clinical aspects of multimodality therapy for resectable locoregionalesophageal cancer. Ann Thorac Cardiovasc Surg 2006; 12: 234-41. Vallbohmer D, Lenz HJ. Predictive and prognostic molecular markers in outcome of esophageal cancer.Dis Esophagus2006; 19: 425-32. Chen et al., Int. J. Cancer: 88, 862-865 (2000) World journal of Gastroenterology: 12 (24) 3929-3932

  The present invention relates to a method for predicting prognosis of esophageal cancer (or a method for providing information for predicting prognosis), a method for providing information for selecting a method for treating an esophageal cancer patient, or a therapeutic agent for esophageal cancer. It is an object of the present invention to provide a screening method and a kit used for the method, and to provide information for selecting a therapeutic strategy that is more beneficial for patients and information useful for new drug development.

  Extensive mRNA expression studies have used gene-based methods to identify gene clusters involved in esophageal carcinogenesis and progression. However, biomarkers that can actually be used for new therapeutic strategies and genes that are molecular targets have not yet been found. From this, it is considered that there is a limit to the search for biomarkers by this method. Proteins contained in cells are functional translations of genes and directly control the malignant phenotype of cancer cells. However, in studies related to measurement of DNA sequence and RNA content, post-translational abnormalities resulting from phosphorylation, glycosylation or proteolysis that occur during cancer progression could not be predicted.

  The present inventors performed two-dimensional electrophoresis on a large number of clinical specimens using a highly sensitive fluorescent dye, and based on the results, integrated proteomic information and clinical pathological information. As a result, transglutaminase 3 was found to be esophageal cancer. We found a strong correlation with the prognosis.

  The method of the present invention comprises detecting the expression of at least one biomarker in a body sample (particularly a biopsy), wherein the expression or expression level of the biomarker is indicative of esophageal cancer prognosis. . An unexpressed or decreased expression of the biomarker of the present invention indicates a poor prognosis of esophageal cancer. Therefore, the method of the present invention can sort esophageal cancer patients into patients with good prognosis and patients with poor prognosis. In addition, since the method of the present invention can select a patient with a good prognosis from patients with esophageal cancer, it is possible to avoid the disadvantages caused by applying unnecessary treatment methods for patients with a good prognosis. At the same time, the method of the present invention can select patients with poor prognosis from patients with esophageal cancer. Therefore, by applying the necessary treatment method to patients with poor prognosis, the progression of disease due to non-treatment can be prevented. It can be avoided. Furthermore, the biomarker of the present invention can be used as an index of the effect of an esophageal cancer therapeutic agent (particularly, a therapeutic agent aimed at improving prognosis). Therefore, the biomarker of the present invention can be used for screening for esophageal cancer therapeutic agents. In addition, the biomarker of the present invention can be used to monitor the pathology and progression of esophageal cancer patients (particularly, the pathology and progression related to prognosis such as metastasis and malignancy).

The present invention relates to a biomarker for predicting the prognosis of esophageal cancer. In certain embodiments, the invention provides a method for predicting prognosis (or providing information for predicting prognosis) in patients with esophageal cancer:
(A) detecting the expression of transglutaminase 3 in a sample from the patient; and
(B) relates to a method comprising associating a measured expression level of transglutaminase 3 with the prognosis of the patient. Preferably, the correlation between the measured expression level of transglutaminase 3 and the prognosis of esophageal cancer indicates that the unexpressed or decreased expression of transglutaminase 3 indicates a poor prognosis of the patient.

In a specific embodiment, the present invention is a method for predicting the prognosis of a patient with esophageal cancer or a method for providing information for predicting the prognosis, comprising the following steps:
(A) preparing a sample from the patient;
(B) contacting the sample with at least one antibody or fragment thereof or nucleic acid, wherein the antibody or fragment thereof is an antibody or fragment thereof that specifically binds to transglutaminase 3 protein, and the nucleic acid is trans A nucleic acid that specifically binds to glutaminase 3 mRNA;
(C) measuring the expression level of the transglutaminase 3 protein or mRNA by detecting the binding of the antibody or fragment thereof or the nucleic acid to the transglutaminase 3 protein or mRNA; and
(D) a method of predicting the prognosis of an esophageal cancer patient from the expression level of transglutaminase 3 protein or mRNA, wherein non-expression of transglutaminase 3 protein or decreased expression indicates poor prognosis of the esophageal cancer patient .
In addition, for example, the method for predicting the prognosis of the esophageal cancer patient or the method for providing information for predicting the prognosis of the present invention is an esophageal cancer patient and has lymph node metastasis (preferably 2 or more). In patients with lymph node metastases).

In another aspect, the present invention provides a method for providing information for selecting a method for treating an esophageal cancer patient comprising:
(A) detecting the expression of transglutaminase 3 in a sample from the patient; and
(B) relates to a method comprising associating a measured expression level of transglutaminase 3 with a method of treating the patient. Preferably, in the correlation between the measured expression level of transglutaminase 3 and the method for treating the patient, the non-expression or decrease in the expression of transglutaminase 3 indicates that the patient is a subject for intensive chemotherapy or radiation therapy. Show.
In addition, for example, the method for providing information for selecting a treatment method for an esophageal cancer patient of the present invention is an esophageal cancer patient and has lymph node metastasis (preferably, there are two or more lymph node metastases). ) Can be performed on patients.

In yet another aspect, the invention relates to a method for monitoring esophageal cancer status or progression or a method for providing information for monitoring esophageal cancer status or progression. For example, the present invention is a method for monitoring the state or progression of esophageal cancer or a method for providing information for monitoring the state or progression of esophageal cancer, comprising:
(A) detecting the expression of transglutaminase 3 in a patient-derived sample; and
(B) relates to a method comprising associating a measured expression level of transglutaminase 3 with the state or progression of esophageal cancer of the patient. Preferably, in the association between the measured level of transglutaminase 3 expression and the state or progression of esophageal cancer in the patient, non-expression or decreased expression of transglutaminase 3 is that the patient is in a poor esophageal cancer state. The expression or increase in expression of transglutaminase 3 indicates that the patient's esophageal cancer is in good condition or has not progressed.
In addition, for example, the method for monitoring the state or progression of esophageal cancer or the method for providing information for monitoring the state or progression of esophageal cancer of the present invention is a patient with esophageal cancer and has lymph node metastasis (preferably Can be performed on patients with two or more lymph node metastases).

In another aspect, the present invention relates to a screening method for a therapeutic agent for esophageal cancer. For example, the present invention is a screening method for an esophageal cancer therapeutic drug, which is one method selected from the following (i) to (iii):
(I) The following steps:
(A) adjusting esophageal cancer cells;
(B) contacting the test drug with the esophageal cancer cell;
(B) a step of measuring the amount of mRNA or protein of transglutaminase 3;
(C) calculating the expression level of transglutaminase 3 from the measured value of transglutaminase 3;
(D) comparing the expression level of transglutaminase 3 in esophageal cancer cells not contacted with esophageal cancer cells contacted with the test drug; and
(E) When the expression level of transglutaminase 3 in esophageal cancer cells contacted with the test drug is increased compared to the expression level of transglutaminase 3 in esophageal cancer cells not contacted with the test drug, Determining that there is an effect of improving prognosis of esophageal cancer
A method comprising:
(Ii) The following steps:
(A) adjusting esophageal cancer model cells;
(B) a step of administering a test drug to the model animal;
(C) a step of measuring the amount of mRNA or protein of transglutaminase 3 in the model animal;
(D) calculating the expression level of transglutaminase 3 from the measured value of transglutaminase 3;
(E) comparing the expression level of transglutaminase 3 in an esophageal cancer model animal administered with the test drug and an esophageal cancer model animal not administered;
(F) When the expression level of transglutaminase 3 in the esophageal cancer model animal administered with the test drug is increased compared to the expression level of transglutaminase 3 in the esophageal cancer model animal not administered with the test drug, the test drug Determining that is effective in improving the prognosis of esophageal cancer;
A method comprising: or
(Iii) The following steps:
(A) administering the test drug to an esophageal cancer patient;
(B) measuring the amount of mRNA or protein of transglutaminase 3 in the esophageal cancer patient;
(C) calculating the expression level of transglutaminase 3 from the measured value of transglutaminase 3;
(D) comparing the expression level of transglutaminase 3 in an esophageal cancer patient who has been administered the test drug and an esophageal cancer patient who has not been administered; and
(E) When the expression level of transglutaminase 3 in an esophageal cancer patient administered with the test drug is increased compared to the expression level of transglutaminase 3 in an esophageal cancer patient who has not been administered the test drug, the test drug is Determining that there is an effect of improving the prognosis of cancer;
A method comprising:

  In yet another aspect, the present invention provides information for predicting prognosis of esophageal cancer patients, providing information for selecting a treatment method for esophageal cancer patients, monitoring the state or progression of esophageal cancer, and / or esophagus. The present invention relates to a biomarker for screening cancer drugs. Specifically, the biomarker of the present invention is transglutaminase 3.

Moreover, the present invention provides a kit comprising any one selected from the following (i) to (iii):
(I) an antibody or a fragment thereof that specifically binds to transglutaminase 3 protein;
(Ii) a primer that specifically binds to a part of the transglutaminase 3 gene and a nucleic acid complementary to the transglutaminase 3 gene; or (iii) a sequence complementary to a part of the transglutaminase 3 gene and a part of the quenching probe. And a fluorescent-labeled universal probe having a triple-strand-specific DNA-degrading enzyme and a quenching probe. In yet another aspect, the present invention provides information for predicting prognosis of an esophageal cancer patient (or providing information for predicting prognosis) and selecting a treatment method for an esophageal cancer patient, A kit for monitoring the condition or progression of the disease or screening for an esophageal cancer therapeutic drug, comprising any one selected from the following (i) to (iii):
(I) an antibody or a fragment thereof that specifically binds to transglutaminase 3 protein;
(Ii) a primer that specifically binds to a part of the transglutaminase 3 gene and a nucleic acid complementary to the transglutaminase 3 gene; or (iii) a sequence complementary to a part of the transglutaminase 3 gene and a part of the quenching probe. And a fluorescent-labeled universal probe having a triple-strand-specific DNA-degrading enzyme and a quenching probe.

  The method for predicting the prognosis of the present invention as described above, the method for providing information for predicting the prognosis, the method for providing information for selecting a method for treating an esophageal cancer patient, the state or progression of esophageal cancer The method of monitoring, the method of providing information for monitoring the state or progression of esophageal cancer, or the screening method of therapeutic agents for esophageal cancer can be used in combination with known methods as appropriate. For example, since lymph node metastasis is known to be an important indicator of a patient's prognosis, a step of detecting lymph node metastasis or obtaining information on lymph node metastasis is added to the method of the present invention. In addition, lymph node metastasis and detection of the biomarker of the present invention can be used in combination. Specifically, the detection of lymph node metastasis or information on lymph node metastasis, and a group of patients excluding a patient group in which lymph node metastasis is not present or few (1) and it is clear that the prognosis is good By detecting the biomarker, it is possible to obtain information related to predicting the prognosis of a patient group whose prognosis is not predictable only by lymph node metastasis. In the prognosis prediction method of the present invention, the subject may be a patient with lymph node metastasis (preferably, two or more lymph node metastases are present).

  In the present specification, “esophageal cancer” is not particularly limited as long as it is a cancer existing in the esophagus, and includes squamous cell carcinoma in which mucosal epithelial cells of the esophagus have become cancerous and adenocarcinoma in which the esophageal gland has become cancerous.

  As used herein, “prognosis” means the progression or outcome (eg, the presence or absence of metastasis, life and death, etc.) of esophageal cancer following suppression or reduction of tumor growth by surgical treatment or the like. In this specification, the prognosis is, for example, suppression of tumor growth by surgical treatment or the like, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 15 or 20 years or more after reduction. It may be life or death at this point. Prognosis is predicted by examining transglutaminase 3 (prognostic indicator). The prognosis can be predicted by determining whether or not the prognosis of the patient is good or bad by the presence / absence or increase / decrease of transglutaminase 3, or the probability thereof. In the present specification, the terms “prognosis determination” and “prognosis evaluation” are used as synonyms for prognosis prediction.

  In the present specification, “good prognosis” means suppression of tumor growth by surgical treatment or the like of a patient, and a condition after reduction for a long time (for example, 3, 5, 6, 7, 8, 9, 10, 15, or 20). Year or more) means non-fatal and may mean survival, non-metastasis, non-regression, or non-relapse. For example, good prognosis may mean surviving for at least 3 years, especially at least 5 years (preferably without metastasis or recurrence). In addition, as a favorable prognosis state, the most preferable state is long-term disease-free survival, but in the present invention, good prognosis means that even if some disease such as metastasis is confirmed, its malignancy is low and it can survive A state can also be included.

  In the present specification, “poor prognosis” means that the condition after suppression or reduction of tumor growth by surgical treatment of a patient is fatal for a short period of time (for example, 1, 2, 3, 4, 5 years or less). May mean death, metastasis, regression, or recurrence. For example, poor prognosis may mean relapse, metastasis or death within at least 3 years, in particular at least 5 years.

  Transglutaminase 3 is also known as TGaseE or TGE, and crosslinks structural proteins such as involucrin, loricrin, and small paracrine-rich protein in the final stage of epidermal differentiation. Thus, it is known that it is involved in keratinization in skin keratinocytes. The full-length transglutaminase 3 protein (precursor) is a protein consisting of 693 amino acids (Swiss plot accession No. Q08188). SEQ ID NO: 1 shows the gene sequence of transglutaminase 3, and SEQ ID NO: 2 shows the amino acid sequence of transglutaminase 3.

  The biomarker of the present invention is useful as a prognostic biomarker for esophageal cancer, for which prognosis has not been accurately predicted so far. That is, information for determining the prognosis of esophageal cancer can be obtained by the method of the present invention. In particular, the biomarker of the present invention is an excellent prognostic predictor compared with the wall depth and macroscopic findings of esophageal cancer that have been reported as prognostic predictors. The prognostic predictor of the present invention can provide information for selecting a treatment strategy for esophageal cancer patients, and it is expected that many esophageal cancer patients will benefit.

  Since the biomarker of the present invention serves as an index of prognosis of esophageal cancer patients, a method of providing information for selecting a prognosis prediction method of esophageal cancer, a treatment method of esophageal cancer patients, and a state of esophageal cancer or Can be used in methods of monitoring progress.

The method for providing information for predicting the prognosis of an esophageal cancer patient of the present invention comprises the following steps:
(A) detecting the expression of transglutaminase 3 in a sample from the patient; and
(B) correlating the measured expression level of transglutaminase 3 with the prognosis of the patient, wherein unexpressed or decreased expression of transglutaminase 3 indicates a poor prognosis of the esophageal cancer patient Can do.

More specifically, the method for providing information for predicting the prognosis of an esophageal cancer patient of the present invention comprises the following steps:
(A) preparing a sample from the patient;
(B) contacting the sample with at least one antibody or fragment thereof or nucleic acid, wherein the antibody or fragment thereof is an antibody or fragment thereof that specifically binds to transglutaminase 3 protein, and the nucleic acid is trans A nucleic acid that specifically binds to glutaminase 3 mRNA;
(C) measuring the expression level of the transglutaminase 3 protein or mRNA by detecting the binding of the antibody or fragment thereof or the nucleic acid to the transglutaminase 3 protein or mRNA; and
(D) predicting the prognosis of esophageal cancer patients from the expression level of transglutaminase 3 protein or mRNA, wherein unexpressed or decreased expression of transglutaminase 3 protein indicates poor prognosis of esophageal cancer patients it can.

A method for providing information for selecting a treatment method for an esophageal cancer patient comprises the following steps:
(A) detecting the expression of transglutaminase 3 in a sample from the patient; and
(B) correlating the measured expression level of transglutaminase 3 with the treatment method of the patient, wherein transglutaminase 3 is not expressed or decreased in expression, if the patient is a subject of intensive chemotherapy Can be done by showing that there is.

Furthermore, the method for monitoring the state or progression of esophageal cancer of the present invention comprises the following steps:
(A) detecting the expression of transglutaminase 3 in a patient-derived sample; and
(B) associating the measured level of transglutaminase 3 expression with the state or progression of esophageal cancer of the patient, wherein unexpressed or decreased expression of transglutaminase 3 is a condition of esophageal cancer of the patient Is poor, has progressed, and / or transglutaminase 3 expression or increased expression indicates that the patient's esophageal cancer condition is good or not progressing, It can be carried out.

  In addition, since the biomarker of the present invention serves as an index for prognosis of patients, it can be used as an index for improving prognosis of patients in screening for esophageal cancer therapeutic agents. For example, a test drug is added to esophageal cancer cells, a test drug is administered to an esophageal cancer model animal, or a test drug is administered to an esophageal cancer patient, and the expression level of the biomarker of the present invention is measured after a certain time. Thus, it can be determined whether or not the therapeutic agent improves the prognosis of esophageal cancer. More specifically, a test drug in which transglutaminase 3 is expressed or increased by addition or administration can be selected as a therapeutic drug that improves the prognosis of esophageal cancer. Therefore, the present invention provides a screening method for an esophageal cancer therapeutic agent (or prognosis improving agent).

The screening for the esophageal cancer therapeutic agent of the present invention includes, for example, the following steps:
(A) adjusting esophageal cancer cells;
(B) contacting the test drug with the esophageal cancer cell;
(B) a step of measuring the amount of mRNA or protein of transglutaminase 3;
(C) calculating the expression level of transglutaminase 3 from the measured value of transglutaminase 3;
(D) comparing the expression level of transglutaminase 3 in esophageal cancer cells not contacted with esophageal cancer cells contacted with the test drug; and
(E) When the expression level of transglutaminase 3 in esophageal cancer cells contacted with the test drug is increased compared to the expression level of transglutaminase 3 in esophageal cancer cells not contacted with the test drug, Determining that the prognostic effect of esophageal cancer is improved;
Can be performed.

The screening for the esophageal cancer therapeutic agent of the present invention includes, for example, the following steps:
(A) adjusting esophageal cancer model cells;
(B) a step of administering a test drug to the model animal;
(B) a step of measuring the amount of mRNA or protein of transglutaminase 3 in the model animal;
(C) calculating the expression level of transglutaminase 3 from the measured value of transglutaminase 3;
(D) comparing the expression level of transglutaminase 3 in an esophageal cancer model animal administered with the test drug and an esophageal cancer model animal not administered;
(E) When the expression level of transglutaminase 3 in esophageal cancer cells contacted with the test drug is increased compared to the expression level of transglutaminase 3 in esophageal cancer cells not contacted with the test drug, Determining that the prognostic effect of esophageal cancer is improved;
Can be performed.

The screening for the esophageal cancer therapeutic agent of the present invention includes, for example, the following steps:
(A) administering the test drug to an esophageal cancer patient;
(B) measuring the amount of mRNA or protein of transglutaminase 3 in the esophageal cancer patient;
(C) calculating the expression level of transglutaminase 3 from the measured value of transglutaminase 3;
(D) comparing the expression level of transglutaminase 3 in an esophageal cancer patient who has been administered the test drug and an esophageal cancer patient who has not been administered; and
(E) When the expression level of transglutaminase 3 in an esophageal cancer patient administered with the test drug is increased compared to the expression level of transglutaminase 3 in an esophageal cancer patient who has not been administered the test drug, the test drug is It can be performed by a step of determining that there is an effect of improving the prognosis of cancer.

  The patient-derived sample used in the method of the present invention is not particularly limited as long as it is a sample that can detect the expression of a biomarker. For example, tissue (particularly esophageal cancer tissue), cell, body fluid (for example, Blood, plasma, serum, lymph, urine, serous fluid, cerebrospinal fluid, joint fluid, aqueous humor, tear fluid, saliva, etc.) can be used. In addition, the patient-derived sample used in the method of the present invention may be pretreated prior to the measurement test, or a sample collected from the patient may be used as it is.

The expression of the biomarkers of the invention can be examined at the protein or nucleic acid level. When testing at the protein level, it can be detected using a substance that specifically binds to a biomarker. For example, an immunological test using an antibody or a fragment thereof (for example, ELISA ( Catty, Raykundalia, 1989), radioimmunoassay (Catty,
Murphy, 1989), immunohistochemical staining, western blot, immunoprecipitation, immunofluorescence, flow cytometry). When testing at the nucleic acid level, methods such as hybridization and nucleic acid amplification (for example, ARMS (Amplification Reference Mutation System) method, RT-PCR (Reverse transcriptase-PCR) method, Nested PCR method, dot blot method, etc.). Hybridization method, surface plasmon resonance method (SPR method), PCR-RFLP method, In situ RT-PCR method, PCR-SSO (sequence specific Oligonucleotide) method, PCR-SSP method, AMPFLP (Amplifiable fragment length) -PCR method, PCR-SSCP (single strand con ormation polymorphism) method, Invader (registered trademark) method) are included. The measurement of expression includes measuring the presence / absence of expression, the possibility of detection, the amount of expression or concentration, the presence / absence of overexpression, the presence / absence of decrease in expression, and the like.

When transglutaminase 3 is examined at the protein level, it can be determined by measuring the binding of an antibody recognizing transglutaminase 3 or a fragment thereof and transglutaminase 3 in the sample. Examples of such methods include ELISA (Catty, Raykundalia, 1989), radioimmunoassay (Catty,
Murphy, 1989), immunohistochemical staining, Western blot, immunoprecipitation, immunofluorescence, flow cytometry and the like. As a sample of the diagnostic agent of the present invention, for example, a tissue sample or fluid collected from a subject as a biopsy can be used. The biopsy used is not particularly limited as long as it is an object of the immunological measurement of the present invention. For example, tissue, blood, plasma, serum, lymph, urine, serous fluid, spinal fluid, joint fluid, eye Examples thereof include aqueous humor, tears, saliva, and fractions or processed products thereof, preferably esophageal cancer tissue or blood (including plasma or serum). Analysis by the diagnostic kit of the present invention can be performed qualitatively, quantitatively or semi-quantitatively.

The antibody or fragment thereof that specifically binds to the biomarker of the present invention used in the method of the present invention may be of any structure, size, immunoglobulin class, origin, etc. as long as it binds to the biomarker of the present invention. Further, the antibody or fragment thereof used in the method of the present invention may be monoclonal or polyclonal. An antibody fragment is a part of an antibody (partial fragment) or a peptide containing a part of an antibody, and retains the binding action of the antibody to the antigen. Such antibody fragments include, for example, F (ab ′) ₂ , Fab ′, Fab, single chain Fv (scFv), disulfide bond Fv (dsFv) or a polymer thereof, dimerized V region ( Diabodies) or peptides containing CDRs. Here, CDR refers to Kabat et al. (“Sequences of Proteins of Immunological Interest”, Kabat, E. et al., US Department of Health and Human Services, 1983) or Cho. Biol., 196, 901-917, 1987). The present invention also includes an isolated nucleic acid encoding the amino acid sequence of the antibody or fragment thereof included in the kit of the present invention, a vector including the nucleic acid, and a cell carrying the vector.

  Antibodies can be obtained by methods well known to those skilled in the art. For example, a polypeptide having all or part of transglutaminase 3 or a mammalian cell expression vector incorporating a polynucleotide encoding them is prepared and used as an antigen. After immunizing the animal with this antigen, immune cells obtained from the immunized animal and myeloma cells are fused to obtain a hybridoma, and an antibody is collected from the hybridoma culture. The monoclonal antibody of the biomarker of the present invention can be obtained by subjecting the finally collected antibody to antigen-specific purification using a polypeptide corresponding to the biomarker of the present invention used as an antigen or a part thereof. In the case of producing a polyclonal antibody, an animal is immunized with the same antigen as described above, blood is collected from the immunized animal, serum is separated from the blood, and antigen-specific purification using the antigen is performed on the serum. Can be obtained. Antibody fragments can be obtained by enzymatic treatment of the obtained antibodies or using sequence information of the obtained antibodies.

  Binding of the label to the antibody or fragment thereof can be performed by methods common in the art. For example, when fluorescently labeling a protein or peptide, after washing the protein or peptide with a phosphate buffer, a dye adjusted with DMSO, buffer, etc. is added, mixed, and then allowed to bind at room temperature for 10 minutes. be able to. Moreover, as a commercially available labeling kit, a biotin labeling kit (Biotin Labeling Kit-NH2, Biotin Labeling Kit-SH: Dojindo Laboratories Co., Ltd.), an alkaline phosphatase labeling kit (Alkaline Phosphatase Labeling Kit-NH2, Alkaline Phosphatase Kit) SH: Dojindo Laboratories Co., Ltd.), peroxidase labeling kit (Peroxidase Labeling Kit-NH2, Peroxidase Labeling Kit-NH2: Dojindo Laboratories, Inc.), phycobiliprotein labeling kit (Allophycocyanin Labeling Kit-NH2, Allophycocyan) Labeling Kit-SH, B-Phycoerythrin Labeling Kit-NH2, B-Phycoerythrin Labeling Kit-SH, R-Phycoerythrin Labeling Kit-NH2, R-Phycoerythrin Label Lab. Labeling Kit-NH2, HiLyte Fluor (registered trademark) 555 Labeling Kit-NH2, HiLyte Fluor (registered trademark) 647 Labeling Kit-NH2: Dojin Chemical Laboratory Co., Ltd., DyLight 547, DyLight 647 (Technochemical Co., Ltd.) Trademark) Ale a Fluor (TM) antibody labeling kit, Qdot (TM) antibody labeling kit (Invitrogen), can be labeled using EZ-Label Protein Labeling Kit (Funakoshi Corporation), and the like. In addition, the labeled antibody or a fragment thereof can be detected by using a device suitable for labeling as appropriate.

  When transglutaminase 3 is tested at the mRNA level, it can be based on a known method using PCR using appropriately designed primers. Examples of such methods include ARMS (Amplification Reference Mutation System) method, RT-PCR (Reverse transcriptase-PCR) method, and Nested PCR method. In addition, the amplified nucleic acid is obtained by using a nucleic acid complementary to the nucleic acid, a dot blot hybridization method, a surface plasmon resonance method (SPR method), a PCR-RFLP method, an in situ RT-PCR method, a PCR. -An SSO (sequence specific oligonucleotide) method, a PCR-SSP method, an AMPFLP (Amplifiable fragment length polymorphism) method, an MVR-PCR method, and a PCR-SSCP (single strand conformation method) can be detected. Analysis by the method of the present invention can be performed qualitatively, quantitatively or semi-quantitatively.

For example, the method of the present invention comprises the following steps:
(A) preparing a patient-derived sample;
(B) Amplifying the transglutaminase 3 gene:
(C) detecting the amplification amount of the nucleic acid and measuring the expression level of the transglutaminase 3 gene; and
(D) Predicting the prognosis of the esophageal cancer patient from the expression level of the transglutaminase 3 gene, wherein non-expression of transglutaminase 3 or decreased expression indicates poor prognosis of the esophageal cancer patient .

  The nucleic acid used in the method of the present invention can be obtained by chemical synthesis or by amplifying with a primer designed to amplify the desired nucleic acid by preparing a gene containing the desired nucleic acid from a biological material. . Moreover, the primer used for the method of this invention can be suitably designed by a method well-known to those skilled in the art based on the disclosure of this specification and known information, and can be obtained by chemical synthesis.

Furthermore, in another embodiment, when transglutaminase 3 is examined at the mRNA level, for example, a method known as the Invader® method (eg, Kwiatkowski, RW et al .: “Clinical, genetic, and
pharmacogenetic applications of the Invader assay. "Mol. Diagn., 4:
353-364, 1999).
For example, the method comprises the following steps:
(A) preparing a patient-derived sample;
(B) contacting the sample with the nucleic acid described in the following (i) and (ii) to form a triplex in DNA complementary to the allele probe:
(I) an allele-specific probe comprising a sequence complementary to a part of the transglutaminase 3 gene and a sequence complementary to a part of the quenching probe (flap),
(Ii) an invader probe comprising a sequence complementary to a part of the transglutaminase 3 gene;
(C) A step of bringing the nucleic acid sample obtained in (b) into contact with a triplex-specific DNA-degrading enzyme to release a flap from the nucleic acid that has formed a triplex;
(D) contacting the liberated flap with a fluorescently labeled universal probe each comprising a sequence complementary to the flap and a quenching probe;
(E) contacting the nucleic acid sample obtained in (d) with a triplex-specific DNA-degrading enzyme to release a fluorescent label and causing fluorescence to develop; and
(F) measuring the expression level of the transglutaminase 3 gene by detecting the colored fluorescence;
(G) Predicting the prognosis of the esophageal cancer patient from the measured transglutaminase 3 gene expression level (or providing information for predicting the prognosis), and selecting a treatment method for the esophageal cancer patient Providing information for monitoring the state or progression of esophageal cancer, or screening for esophageal cancer therapeutic agent, wherein transglutaminase 3 is not expressed or decreased in expression, the prognosis or condition of the esophageal cancer patient Indicating deterioration of cancer or progression of cancer.

As used herein, to determine the prognosis of a patient, the term “associate” used in relation to the measured expression level of a biomarker and the prognosis of the patient refers to the presence or level of a biomarker in a subject, Expression levels of biomarkers in patients who have a poor prognosis or who are known to have a poor prognosis, or who have a poor prognosis or who are believed to have a poor prognosis Means to compare. Alternatively, the association may be comparing the presence or level of the biomarker in the subject with the expression level of the biomarker in a healthy person who has not developed esophageal cancer. For example, the target patient's biomarker level is not poor if the patient group has a poor prognosis or is known to have a poor prognosis, and the patient group or prognosis has a poor prognosis. Compared to the level of biomarkers in a group of beliefs or near the level of the biomarkers in patients with a poor prognosis or known to have a poor prognosis When the value belongs to the level value range of the biomarker formed from the level group, the prognosis of the patient can be predicted to be poor. The level of the biomarker in the patient to be compared is determined, for example, by the disclosure of the present invention, by measuring the level of the biomarker in a sample derived from a patient whose prognosis is already known, or other prognostic indicators. You can know by evaluating in combination with the evaluation by. The biomarker levels of the present invention can be used to determine the likelihood that a patient will die, relapse or metastasize. The association between prognostic factors and prognosis can be made by statistical analysis. Statistical significance is determined by comparing two or more populations and determining confidence intervals and / or p-values (Dowdy and Wearden, Statistics for Research, John Wiely & Sons,
NewYord, 1983). The confidence interval of the present invention may be, for example, 90%, 95%, 98%, 99%, 99.5%, 99.9% or 99.99%. The p value of the present invention is, for example, 0.1, 0.05, 0.025, 0.02, 0.01, 0.005, 0.001, 0.0005, 0.0002, or 0.0001. It may be.

  For example, the biomarkers of the invention can be associated with patient prognosis by their presence / absence. As another example, the biomarkers of the invention can be associated with patient prognosis by increasing / decreasing their expression levels. For example, the increase / decrease in the expression level can be indicated by an increase / decrease in the expression level in the esophageal cancer tissue. In this case, a threshold level of the expression level as a prognostic indicator may be set for the biomarker of the present invention, and the biomarker level in the patient-derived sample may be correlated by comparing with the threshold level. Further, the increase / decrease in the expression level can be determined by using the expansion / contraction of the expression region in the esophageal cancer tissue as an index. For example, a threshold level of an expression region as a prognostic indicator may be set for the biomarker of the present invention, and the biomarker level in a patient-derived sample may be correlated by comparing with the threshold level. Such a threshold level is, for example, a sensitivity of 50, 55, 60, 65, 70, 75, 80, 85, 90, 91, 92, 93, 94, 95, 96, 97, or 98% or more. Can be set to The threshold level is 40, 45, 50, 55, 60, 65, 70, 75, 80, 85, 90, 91, 92, 93, 94, 95, 96, 97, or 98%. It can set so that it may become above. For example, regarding the increase / decrease of the expression level, when the expansion / reduction of the expression region in the esophageal cancer tissue is used as an index, the threshold level of the biomarker of the present invention is 1% to 30% (preferably 5% to 15%) ) Between, for example, about 10%. In the above, “about” means ± 10% (preferably ± 1%).

  Prognostic determination means how to predict the course or outcome of a patient's condition and does not mean that the course or outcome of a condition can be predicted with 100% accuracy. The determination of prognosis means whether or not the probability of occurrence of a certain course or outcome is increased, and does not mean that it is likely to occur on the basis of the case where the course or outcome does not occur. That is, a prognostic outcome means that a particular course or outcome is more likely to occur in patients with reduced levels of the biomarker of the present invention compared to patients who do not exhibit such characteristics. To do.

  Esophageal cancer is managed by treatment strategies with surgery, radiation therapy, chemotherapy, or a combination thereof. By using the method and kit of the present invention, it is possible to provide treatment strategy determinants suitable for esophageal cancer patients. In the present invention, “associating” the expression of a biomarker with a treatment method means that the presence or level of the biomarker in a subject is a patient with a poor prognosis or a poor prognosis. Comparison of biomarker expression levels in patients who are not or have a poor prognosis, or patients whose belief is not bad Means that For example, the treatment method may be predetermined in relation to the determined prognosis. Aggressive chemotherapy for high-risk patients has been shown to reduce the risk of return. The method of the present invention distinguishes between patients with a good prognosis and patients with a poor prognosis, requires an aggressive treatment strategy, and has a poor prognosis, such as a higher risk of recurrence compared to a patient with a good prognosis. This is useful when extracting. On the other hand, patients who are determined to have a better prognosis than patients with a poor prognosis can benefit from choosing a more relaxed treatment strategy.

For example, associating biomarker expression with treatment methods is known to indicate the presence or level of biomarkers in subjects, patients with poor prognosis, or poor prognosis, in accordance with the above methods. Compared to the expression level of biomarkers in patients, or patients whose prognosis was not poor or believed to have poor prognosis, patients who were determined to have poor prognosis were eligible for intensive chemotherapy or radiation therapy It may be done to indicate that the patient is a patient who has been determined to have a good prognosis and is not a subject for intensive chemotherapy or radiation therapy. Intensive chemotherapy is a treatment method by increasing the dose, administration frequency, type of administration, etc. of a chemotherapeutic agent (anticancer agent). The intensive chemotherapy or radiation therapy, for example, postoperative 5-FU and the combination of cisplatin (e.g., 5-FU800mg / ^{m 2} was continuous infusion 1-5 days, cisplatin 80 mg / ^{m 2} drilled 3-4 weeks Or postoperative adjuvant chemotherapy or radical chemoradiotherapy, or preoperative cisplatin administration or chemoradiotherapy. Other drugs used for intensive chemotherapy include platinum preparations such as oxaliplatin, carboplatin and nedaplatin; taxane anticancer agents such as Taxol (registered trademark); tyrosine kinases such as gefitinib and erlotinib Inhibitors: anti-EGFR antibodies such as cetuximab, matuzumab, panitumumab and the like.

  In the method for monitoring the state or progression of esophageal cancer of the present invention, the association between the measured expression level of transglutaminase 3 and the state or progression of esophageal cancer of the patient may be performed according to the association with the prognosis. it can. In the method for monitoring the state or progression of esophageal cancer of the present invention, the level of a biomarker can be used to determine a change in the likelihood that a patient will die, relapse, or metastasize. In particular, changes in the prognosis of a patient can be known by measuring biomarkers over time. Such monitoring is preferably performed regularly, for example, once a week, once every two weeks, once a month, once in February, once in March, once in June. It can be performed once a year, once every two years, once every three years, once every five years, or once every ten years, and can be set appropriately according to the patient's progress. it can.

  In one embodiment, the kit of the present invention comprises an antibody that specifically binds to transglutaminase 3 or a fragment thereof, or a nucleic acid that specifically binds to transglutaminase 3 mRNA or a part thereof. For example, the kit of the present invention may be an ELISA (Catty, Raykundalia, 1989) or an immunochromatography kit. In another embodiment, the kit of the present invention comprises a primer that specifically binds to a portion of the transglutaminase 3 gene or mRNA. For example, the kit of the present invention may be a kit for RT-PCR. An antibody or a fragment thereof that specifically binds to transglutaminase 3 included in the kit of the present invention, or a nucleic acid that specifically binds to transglutaminase 3 mRNA or a part thereof can be obtained by the method described above.

  In one embodiment, the prediction kit described herein can be a kit suitable for the Invader® method. For example, the prediction kit of the present invention comprises a sequence complementary to a part of the transglutaminase 3 gene, a sequence complementary to a part of the quenching probe (flap), and a sequence complementary to a part of the transglutaminase 3 gene. A fluorescently labeled universal probe comprising an invader probe, a triplex-specific DNA-degrading enzyme, and a quenching probe can be provided. The flap is preferably different between each allele-specific probe. As the fluorescent label, a probe known to those skilled in the art can be appropriately selected, and it is preferable that the fluorescent label is different among the fluorescent labeled universal probes. For example, FAM and VIC can be used as fluorescent labels.

  Hereinafter, examples will be shown to describe the present invention in more detail, but the present invention is not limited to these examples. It should be noted that all documents cited throughout this application are incorporated herein by reference in their entirety.

1. Patient and clinical information To standardize the clinical background, the patient group has a pathologically T3N0-1M0 tumor, has not received pre- or post-operative chemotherapy or radiation therapy, and is newly The subjects were patients diagnosed with squamous cell carcinoma of the thoracic esophagus and observed for at least 5 years after surgery. Tumor cells and adjacent normal mucosal cells were collected from 80 of the 500 cases resected between 1998 and 2002 at the National Cancer Center. Two or three tissue fragments in an amount of 10 mm ³ or less were obtained from each case. Corresponding normal mucosal tissue was obtained in the same manner. The excised tissue was snap frozen in liquid nitrogen and stored at −80 ° C. until used for measurement. This study has been approved by the Ethics Committee of the National Cancer Center, and written informed consent has been obtained from patients. Lymph node metastasis was observed in 63 cases (78%). Table 1 shows the relationship between the number of lymph node metastases and the prognosis. Moreover, the survival curve with respect to the number of lymph node metastasis is shown in FIG. These results confirmed that there was a correlation between lymph node metastasis and patient prognosis.

2.2 Protein expression profiling with D-DAGE First, identify protein spots associated with postoperative prognosis by comparing protein expression profiles with 2D-DAGE for two groups of patients with very different survival times did. Of these, one group is a good prognosis group consisting of 37 patients who have not had any signs of disease for 5 years, and the other group is a prognosis consisting of 28 patients who have died from the disease within 2 years. It is a bad group.

2-1. Laser microdissection and protein extraction Non-tumor cells were removed using laser microdissection and only tumor cell populations were collected and used for later proteomic analysis (Kondo T, Hirohashi S. Application of high sensitive fluorescent dyes ( (Non-Prototype 29: CyDye DIGE Fluor Saturation Dies) to laser microdetection and two-dimensional differential gel electrophoresis (2D-DIGE) for cancer proteomics. That is, this method was performed by the following steps. Frozen samples are embedded in OCT compound (Sakura Finetech Japan Co., Ltd.), 8 μm sections are prepared using cryostat (Leica CM3050S, Leica Microsystems Co., Ltd.), and hematoxylin and eosin staining are performed for pathological diagnosis. Went. An adjacent section having a thickness of 8 μm was placed on a thin polyethylene film pretreated with a tissue adhesive solution (0.1% poly-L-lysine, Sigma-Aldrich). Tissue fragments were always stained with Mayer Hematoxylin. All staining steps were performed on ice. The Meyer's hematoxylin stained fragment was used for laser microdissection (Leica Laser Microdissection version 3.1.0.0, Leica Microsystems). Recovery of tumor cells from non-necrotic tissue was performed using a pulsed ultraviolet laser beam while avoiding contamination of infiltrated inflammatory cells, stromal cells and vascular components into the sample. Relatively morphologically normal esophageal epithelial specimens present at least 5 cm away from the cancer tissue were collected from 53 of 58 patients. Since eosin staining hinders 2D-DIGE, the fragments stained with hematoxylin and eosin were used to confirm the diagnosis, and the remaining fragments were stained with hematoxylin alone for proteomic analysis. A protein corresponding to a 1 mm ² microdissection region recovered from hematoxylin stained tissue during microdissection was used for each 2D-DIGE gel.

2-2.2 Preparation of D-PAGE fluorescently labeled protein samples and acquisition of images Microdissected tissues were immediately treated with urea lysis buffer (6M urea, 2M thiourea, 3% CHAPS, and 1% Triton X-100). . 1 mm ² was used as the range of microdissected tissue per 2D-DIGE gel. Protein labeling was performed according to a previously reported method (Kondo T, Hirohashi S. Application of high energic di energic di s er w er di s er ed s ero s e s e n e n e n e n e n e n e n e n e n e n e n e n e n e n e n e n e n e n e n e n e n e n e n e n e n e n e n e n e n e n e n e n? cancer protocols. Nat Protoc 2006; 1: 2940-56). That is, this method was performed by the following steps. A 3 mm ² microdissected tissue was cultured in 50 mL of 40 mM Tris-HCl (pH 8.0) urea lysis buffer. Thereafter, the protein specimen was reduced by treatment in 8 nmol tris- (2-carboxyethyl) phosphine hydrochloride (TCEP; Sigma-Aldrich) at 37 ° C. for 60 minutes, and 12 nmol Cy5 (CyDye DIGE Fluor saturation dye, GE Healthcare). A fluorescent label was applied by treating at 37 ° C. for 30 minutes using Bioscience. The labeling reaction was terminated by adding urea dissolution buffer containing DTT and Pharmalyte (pH 4-7, GE Healthcare Biosciences) to a final concentration of 65 mM and 2.0%, respectively. All individual protein specimens were mixed as internal standard specimens and labeled with Cy3 fluorescent staining (GE Healthcare Bioscience). After completion of the labeling reaction, each Cy5-labeled sample corresponding to the 1 mm ² laser microscopic cutting region is mixed with an equal amount of Cy3-labeled internal standard sample, and 35 mM DTT and 1.0% Pharmalyte (GE Healthcare Bioscience) Co., Ltd.)-Containing urea dissolution buffer was added so that the final amount per sample was 420 mL.

  Fluorescence-labeled two-dimensional differential electrophoresis (2 Dimensional Difference Gel Electrophoresis: 2D-DIGE) was performed by a method well known to those skilled in the art. Separation in the first dimension was performed using an immobilized pH gradient polyacrylamide gel (IPG (immobilized pH gradient) Dry Strip, GE Healthcare Bioscience) having a length of 24 cm and a pI range of 4 to 7. Separation in the second dimension was performed using SDS-PAGE using a 38 cm long large format gel (Biocraft Co., Ltd.). The gel was scanned at the appropriate wavelength using a laser scanner (Tyhoon Trio, GE Healthcare Bioscience). Using two-dimensional electrophoresis analysis software (Progenesis PG240, Nonlinear dynamics Ltd.), the Cy5 image intensity was normalized by the Cy3 image intensity in the same gel for all spots. The difference was corrected. The reproducibility of the system was verified by comparing protein profiles obtained from two separate separations on the same sample.

  As data analysis before processing, log 2 conversion of intensity data itself obtained in each experiment was performed and converted into Z score to standardize intensity data distribution. Hierarchical cluster analysis was performed on the standardized data using the Euclidean distance and UPGMA method, and the overall characteristics of the proteome were confirmed. In order to identify spots showing different expression between the two groups, a Z-test was performed for each spot. The resulting p-value list contained some false positives due to multiple tests. Therefore, using the Benjamini-Hochberg method (Benjamini, Y., and Hochberg, Y., Journal of the Royal Statistical Society. Series B (Methodological), Vol. A false discovery rate (FDR) was evaluated, and as a result, spots with an FDR of less than 0.05 were selected. In comparison between normal tissue and tumor, in addition to the above FDR standard, a spot having a group average expression ratio of at least 4 times or more was selected.

  By 2D-DIGE, an expression profile of 3623 protein spots per sample was obtained. Based on the overall similarity of protein expression, specimens were divided into two groups: tumor tissue and normal epithelial tissue. There were a number of differences between tumors and normal tissues. Of the 200 protein spots that clearly showed significant differences between tissues (FDR <0.001 and the difference is more than 4-fold), 33 spots are clearly up-regulated in tumor tissue and the other 167 spots Decreased expression. These 200 protein spots were identified by mass spectral analysis.

2-3. Protein Identification by Mass Spectrometry Protein identification by in-gel digestion and mass spectrometry was performed according to the inventors' previous report (Kondo T, Hirohashi S. Application of high fluoresient dyes (CyDye Fluors DF). laser microdetection and two-dimensional difference gel electrophoresis (2D-DIGE) for cancer protocols. Nat Protoc 2006; 1: 2940-56). That is, this method was performed by the following steps. The target protein spot was collected on a 96-well PCR plate using an automatic spot collection device (ProHunter, ASONE Corporation). The gel plug was washed three times with methanol, ammonium carbonate and acenotryl, dried, and then treated with TPCK-treated trypsin overnight. Peptides were extracted from the gel by treating the gel with acetonitrile. The tryptic peptide obtained by in-gel digestion was subjected to analysis by nanoscale microcapillary RP LC-ESI MS / MS. Paradigm MS4 HPLC Dual Solvent Delivery System for Microflow HPLC (Michrom BioResource), HTS PAL Autosampler (CTC Analytics), and Finigan LTQ Linear IT Mass Spectrometer with Nano-ESI (NSI) Source (AMR Corporation) Using a meter (ThermoElectron), protein identification was performed (Kondo T, Hiroshi S. Application of high sensitive fluorscent dyes (Cydie DIGE Fluorescent Strain). gel electrophoresis (2D-DIGE) for cancer protocols. Nat Protoc 2006; 1: 2940-56). The digested peptide mixture was separated on a microcapillary RP Magic C18 column (3 mm, 200 A, 5060.2 mm id; Michrom). The peptide is buffer A (2% acetonitrile (v / v) containing 10 to 80% linear gradient buffer B (acetonitrile containing 10% water (v / v) and 0.1% formic acid (v / v)). And 0.1% formic acid (v / v) -containing water) for 10 minutes.

  The eluate from the HPLC was put into a mass spectrometer through a NSI needle at a rate of 1.0 to 1.2 mL / min (FortisTip, Omniseparo Appropriate School). The capillary was heated to 200 ° C. with a voltage of 1.8 kV. Sheath and auxiliary gas were not used. The mass spectrometer is set to a data-dependent acquisition mode, so that mass range acquisition at m / z 450-1800 automatically switches to MS / MS acquisition under the automatic control of Xcalibur software (version 2.0, ThermoElectron). did. The results of all MS scans were obtained by MS / MS test with the activation amplitude parameter set to 35% and the separation width m / Z 2.0 for the three ions most abundantly detected in the survey scan. Data was acquired with a dynamic mass exclusion window with an exclusion period of 30 seconds and exclusion mass widths of -1.0 and +2.0 Da.

  The obtained data was obtained in dta format (peak list file) using ExtractMS software version 2.11 (ThermoElectron) provided with the instrument, with a peptide mass range of 450 to 600 Da and MS / MS minimum peak of 25. Converted and MASCOT® search was performed. MASCOT® (version 2.1, Matrix Science Inc.) search is a sequence in the non-overlapping protein sequence database of Swiss plot (Sprot — 47.8 fasta file, 12867 sequence) and NCBI (NCBInr — 20050422 fasta file, 131447 sequence) Of these, the homosapiens subset was performed. The following search parameters were used for all MASCOT® searches: allowance for missing two trypsin digests, variable modification of methionine residues (oxidation, +16 Da), and ± 2.0 Da in MS data And ± 1.0 Da in the MS / MS data was taken as the maximum error tolerance. Proteins containing two or more well-matched peptides with characteristic sequences (p <0.05, under the search parameters in this experiment, a MASCOT ion score of 34 or higher for the Swiss plot database and for the NCBI database And the reliability of protein identification was evaluated. In addition, the MS / MS spectrum of the identified peptides was examined manually.

  In tumor specimens, the good prognosis and poor prognosis groups were not classified into groups based on the overall protein expression image of the specimen. Also, no spots showing significantly different intensities between these two groups were found. Therefore, we hierarchized patients by lymph node metastasis. According to the number of lymph node metastasis, which is an important clinical prognostic predictor, all 25 patients with no or only one lymph node metastasis were included in the good prognosis group. Since these patients can predict their prognosis based on clinical information alone, the analysis was limited to patients with two or more lymph node metastases. Of the 34 patients in the good prognosis group, 9 had 2 or more lymph node metastases, and all 24 patients in the poor prognosis group had 2 or more lymph node metastases. The relationship between lymph node metastasis and prognosis is as shown in Table 1 above. A comparison of the spots of the good prognosis group and the poor prognosis group for a total of 33 patients having two or more lymph node metastases, the 22 protein spots are significantly different between the two groups showing different prognosis It was found to show strength (FDR <0.05). The positions of 22 spots are shown in FIG.

  Protein identification by mass spectrum found that 22 protein spots were associated with 18 different gene products. Of the 18 identified proteins, the transglutaminase 3 (TGM3) spot appeared three times in the 22 protein spot list, revealing that expression was reduced in the poor prognosis group.

2-4. Pathway analysis Pathway analysis of protein expression patterns was performed using the MetaCore software analysis tool (GeneGo, Inc). MetaCore uses a proteome data set to identify networks based on a manually managed database containing known intermolecular interactions, functions, and disease interactions. The pathway was identified by the possibility that a random set of proteins as large as the input list could accidentally generate a specific mapping.

  In the pathway analysis using the metacore, 17 out of 18 proteins were incorporated into the pathway analysis diagram. According to it, STAT1, p53, and HNF4 seemed to be important proteins on the pathway. TGM3 was directly regulated by an important transcription factor, Sp1, located downstream of STAT1, p53. From this, TGM3 is considered to be an important gene product for life phenomena. The results of pathway analysis are shown in FIG.

3. Immunohistochemical staining and tissue array To assess the results of 2D-DIGE, immunohistochemical staining was performed on 15 patients with intermediate prognosis. Using a Dako REAL EnVision Detection System (DAKO), immunohistochemical staining of transglutaminase 3 was performed on methanol-fixed paraffin-embedded tissue fragments according to the manufacturer's instructions. In order to recover antigenicity, the fragment was deparaffinized, dehydrated, and then treated with 3 mL / L H ₂ O ₂ -containing methanol for 30 minutes to remove and block endogenous peroxidase activity. Fragments were autoclaved for 10 minutes at 121 ° C. in 10 mM citrate buffer (pH 6.0). As the first antibody, a rabbit polyclonal, mono-specific anti-transglutaminase 3 antibody (HPA004728, Atlas antibodies) was used at a 1: 100 dilution. Staining was a blinded method used in clinical data and was observed by two separate observers. Transglutaminase 3 staining was observed in tumor cytoplasm and part of the cell nucleus as well as in normal esophageal epithelium. Normal esophageal epithelium used as an internal standard was positive for staining. Cases in which 10% or more of the tumor cells were positive for staining with anti-transglutaminase 3 antibody were positive for transglutaminase 3, and cases in which the number of transglutaminase positive tumor cells was 10% or less were negative for transglutaminase 3. When tumors were of histologically different grades, staining assessment was performed on the main segmented areas. The tissue array contained 59 normal tissues and 323 tumor tissues.

4). Statistical analysis For 76 cases of esophageal cancer patients, a hierarchical cluster approach was performed using Expressionist software (Gendata).
Statistical calculation was performed using Stat View Version 5.0 statistical package (SAS Institute Inc,). Survival was defined as from the time of diagnosis to the last follow-up (or death). Survival was assessed by the Kaplan-Meier methodology. The relationship between survival and other variables was examined by a categorical log rank test and a continuous variable score test based on Cox's proportional hazards analysis. The multivariate model was fitted with significant variables at the univariate level using Cox regression. Based on the change in the survival curve, a cutoff value for the prognostic variable was determined.

  A survival curve for transglutaminase 3 prepared by the Kaplan-Meier method is shown in FIG. The presence or absence of expression of transglutaminase 3 showed a statistically significant numerical value (P = 0.0033).

  From the above results, transglutaminase 3 obtained by this study is useful as a prognostic biomarker at the time of esophageal cancer diagnosis, and whether or not these biomarkers are expressed in biopsy tissues at the time of esophageal cancer diagnosis or By measuring the expression level, the prognosis of patients with esophageal cancer can be predicted, and an appropriate treatment method can be selected. In esophageal cancer, a biopsy is always performed for diagnostic purposes, so the biopsy material used in this test can be collected without placing a new burden on the patient.

  The prognostic predictor (transglutaminase 3) at the time of diagnosis of esophageal cancer of the present invention is useful as a marker for predicting the prognosis of an esophageal cancer patient and selecting an appropriate treatment method. Since such a biomarker (or clinical test) has never existed, it is expected that many esophageal cancer patients will benefit from the present invention.

Fig. 5 shows the survival curve of esophageal cancer versus the number of lymph node metastases. The vertical axis represents the survival rate and the horizontal axis represents the postoperative period. Comparison of spots in esophageal cancer with good prognosis and esophageal cancer with poor prognosis is shown. The vertical axis represents the molecular weight, and the horizontal axis represents the isoelectric point. Those marked in the figure represent spots showing significantly different intensities between the two groups showing different prognoses. It is a figure which shows the result of a pathway analysis. The survival curve of an esophageal cancer with respect to transglutaminase expression level is shown. The vertical axis represents the survival rate and the horizontal axis represents the postoperative period.

Claims (10)

A method for providing information for predicting the prognosis of an esophageal cancer patient:
(A) detecting the expression of transglutaminase 3 in a sample from the patient; and
(B) A method comprising associating the measured expression level of transglutaminase 3 with the prognosis of the patient.   The method according to claim 1, wherein in the association between the measured expression level of transglutaminase 3 and the prognosis of esophageal cancer, unexpressed or decreased expression of transglutaminase 3 indicates a poor prognosis of the patient.   The method according to claim 1 or 2, wherein the detection of expression of transglutaminase 3 comprises performing immunological analysis, nucleic acid hybridization, or quantitative RT-PCR.   The method according to any one of claims 1 to 3, wherein the patient-derived sample is cancer tissue collected from an esophageal cancer patient. A method for providing information for predicting the prognosis of a patient with esophageal cancer comprising the following steps:
(A) preparing a sample from the patient;
(B) contacting the sample with at least one antibody or fragment thereof or nucleic acid, wherein the antibody or fragment thereof is an antibody or fragment thereof that specifically binds to transglutaminase 3 protein, and the nucleic acid is trans A nucleic acid that specifically binds to glutaminase 3 mRNA;
(C) measuring the expression level of the transglutaminase 3 protein or mRNA by detecting the binding of the antibody or fragment thereof or the nucleic acid to the transglutaminase 3 protein or mRNA; and
(D) A method comprising predicting the prognosis of an esophageal cancer patient from the expression level of transglutaminase 3 protein or mRNA, wherein unexpressed or decreased expression of transglutaminase 3 protein indicates poor prognosis of the esophageal cancer patient. A method for providing information for selecting a treatment method for an esophageal cancer patient,
(A) detecting the expression of transglutaminase 3 in a sample from the patient; and
(B) A method comprising associating a measured expression level of transglutaminase 3 with a method for treating the patient.   In the association between the measured expression level of transglutaminase 3 and the method of treating the patient, non-expression or decreased expression of transglutaminase 3 indicates that the patient is a patient subject to intensive chemotherapy. The method described. A method of monitoring esophageal cancer status or progression comprising:
(A) detecting the expression of transglutaminase 3 in a patient-derived sample; and
(B) associating the measured level of transglutaminase 3 expression with the state or progression of esophageal cancer of the patient, wherein unexpressed or decreased expression of transglutaminase 3 is a condition of esophageal cancer of the patient Is poor, has progressed, and / or the expression or increased expression of transglutaminase 3 indicates that the patient's esophageal cancer condition is good or not progressing. Including methods. A method for screening an esophageal cancer therapeutic agent, which is selected from the following (i) to (iii):
(I) The following steps:
(A) adjusting esophageal cancer cells;
(B) contacting the test drug with the esophageal cancer cell;
(B) a step of measuring the amount of mRNA or protein of transglutaminase 3;
(C) calculating the expression level of transglutaminase 3 from the measured value of transglutaminase 3;
(D) comparing the expression level of transglutaminase 3 in esophageal cancer cells not contacted with esophageal cancer cells contacted with the test drug; and
(E) When the expression level of transglutaminase 3 in esophageal cancer cells contacted with the test drug is increased compared to the expression level of transglutaminase 3 in esophageal cancer cells not contacted with the test drug, Determining that there is an effect of improving the prognosis of esophageal cancer,
A method comprising:
(Ii) The following steps:
(A) adjusting esophageal cancer model cells;
(B) a step of administering a test drug to the model animal;
(C) a step of measuring the amount of mRNA or protein of transglutaminase 3 in the model animal;
(D) calculating the expression level of transglutaminase 3 from the measured value of transglutaminase 3;
(E) comparing the expression level of transglutaminase 3 in an esophageal cancer model animal administered with the test drug and an esophageal cancer model animal not administered;
(F) When the expression level of transglutaminase 3 in the esophageal cancer model animal administered with the test drug is increased compared to the expression level of transglutaminase 3 in the esophageal cancer model animal not administered with the test drug, the test drug Determining that is effective in improving the prognosis of esophageal cancer;
A method comprising: or
(Iii) The following steps:
(A) administering the test drug to an esophageal cancer patient;
(B) measuring the amount of mRNA or protein of transglutaminase 3 in the esophageal cancer patient;
(C) calculating the expression level of transglutaminase 3 from the measured value of transglutaminase 3;
(D) comparing the expression level of transglutaminase 3 in an esophageal cancer patient who has been administered the test drug and an esophageal cancer patient who has not been administered; and
(E) When the expression level of transglutaminase 3 in an esophageal cancer patient administered with the test drug is increased compared to the expression level of transglutaminase 3 in an esophageal cancer patient who has not been administered the test drug, the test drug is Determining that there is an effect of improving the prognosis of cancer;
Including methods. A kit for predicting the prognosis of an esophageal cancer patient, a kit for providing information for selecting a treatment method for an esophageal cancer patient, or a screening kit for a therapeutic drug for esophageal cancer, comprising the following (i) to A kit comprising any one selected from (iii):
(I) an antibody or a fragment thereof that specifically binds to transglutaminase 3 protein;
(Ii) a primer that specifically binds to a part of the transglutaminase 3 gene and a nucleic acid complementary to the transglutaminase 3 gene; or (iii) a sequence complementary to a part of the transglutaminase 3 gene and a part of the quenching probe. A fluorescent label-labeled universal probe comprising: a flap having a sequence complementary to γ, an invader probe comprising a sequence complementary to a part of the transglutaminase 3 gene, a triplex-specific DNA degrading enzyme, and a quenching probe.