JP2014027898A - Method for judging onset risk of hepatocarcinoma - Google Patents

Abstract

PROBLEM TO BE SOLVED: To provide a method for judging recurrence risk of hepatocarcinoma using biomarkers that can accurately judge the recurrence risk of hepatocarcinoma, and to provide a kit for judging the recurrence risk of hepatocarcinoma.SOLUTION: By using 7 genes (CYP2A6, SLC10A1, SLC22A1, ESR1, GLYAT, TSPAN8 and NQO1) as the biomarkers, the recurrence risk of hepatocarcinoma can be judged (predicted) accurately. When 3 biomarker genes (SLC22A1, TSPAN8 and NQO1) selected from 7 biomarker genes are used with further COL15A1 and ABCB6 genes as the biomarkers to carry out discriminant analysis, 88% (sensitivity) of the patients that suffer from recurrence 2 years after the operation are judged as "hepatocarcinoma will recur within 2 years after the surgery", and 100% (specificity) of the patients having no hepatocarcinoma recurrence over 2 years after the operation are judged as "hepatocarcinoma will not recur over 2 years after the operation". Thus the recurrence risk of hepatocarcinoma can be judged with high accuracy.

Description

  The present invention relates to a method for determining the risk of developing hepatocellular carcinoma and a kit for determination.

  In Japan, the number one cause of death is cancer, and countermeasures are the most important from the viewpoint of public health. Hepatocellular carcinoma (HCC, hereinafter sometimes referred to as “HCC”) is one of the most frequent solid cancers in the world, and the death rate from HCC in Japan in 2009 It is reported that it is the third highest among them. HCC is known to develop mainly against chronic hepatitis caused by viral infection and cirrhosis that has progressed from chronic hepatitis, and is positive for hepatitis C virus (HCV) among HCC patients. The proportion of people is about 70%, and the proportion of people who are positive for hepatitis B virus (HBV) is about 20% (Non-patent Document 1). Although the details of the mechanism by which these hepatitis viruses cause HCC have not been clarified, it is thought that hepatocyte canceration occurs in the process in which persistent infection of the virus causes chronic hepatitis, cirrhosis, and the like.

  At present, surgical resection is considered to be effective as an HCC treatment method, but it is known that the recurrence rate after surgery is extremely high and the prognosis is poor (Non-patent Document 2). Intrahepatic recurrence in the early postoperative period (approximately 1 to 2 years) is thought to be due to intrahepatic metastasis caused by portal vein invasion. In addition, since many patients with hepatocellular carcinoma have grounds for viral infection, it is also known that hepatocellular carcinoma recurs due to multicentric carcinogenesis in the later postoperative period (Non-patent Document 3). ). As described above, the treatment of HCC is associated with a high risk of recurrence, and the development of biomarkers for predicting recurrence after surgery is extremely important from the viewpoint of QOL (quality of life) of HCC patients. Is important to.

  So far, gene expression profiles in cancer cells have been constructed from exhaustive analysis such as DNA microarray method, and many genes related to cancer have been identified. Based on this, diagnostic methods such as early detection, classification, and prognosis prediction for cancer have been developed using mRNA expression of a cancer-specific gene as a biomarker. However, what has been put into practical use so far is currently MammaPrint (Agendia), which is approved by the US Food and Drug Administration and predicts the risk of breast cancer recurrence from the expression of 70 genes.

Kiyosawa K. et al., Gastroenterology 127, S17-26 (2004) Makuuchi M. et al., Hepatogastroenterology 45, S1267-1274 (1998) Poon RT. Et al., Cancer 89, 500-507 (2000)

  An object of the present invention is to provide a method for determining the risk of developing hepatocellular carcinoma and a kit for determining the risk of developing hepatocellular carcinoma using a biomarker that can accurately determine the risk of developing hepatocellular carcinoma. It is in.

  In the process of continuing intensive research to solve the above-mentioned problems, the present inventors have searched for biomarker genes using two different analysis methods, the microarray method and the High Coverage Expression Profiling (HiCEP) (registered trademark) method. And after screening for those in which the expression level of the mRNA of the gene is different in the HCC non-relapsed group and the HCC relapsed group within 1 year after the operation, 1806 by the microarray method and the HiCEP method, respectively. Kinds and six kinds of biomarker candidate genes were identified. Furthermore, secondary selection by a significant difference test or the like was performed from these, and quantitative analysis using the real-time PCR method was performed. From the three types of genes (TSPAN8, CYP2A6, and SLC22A1) from the microarray method and the HiCEP method, These three genes (NQO1, SLC10A1, and GLYAT) have been found to be biomarkers that can accurately determine the onset or recurrence risk of HCC (hereinafter sometimes referred to as “HCC biomarkers”).

  Further, when the biomarker was selected using the mRNA expression ratio in the HCC tissue and the surrounding non-cancerous liver tissue as an index, the COL15A1 gene was found as an HCC biomarker. Furthermore, in addition to the above seven genes (TSPAN8, CYP2A6, SLC22A1, NQO1, SLC10A1, GLYAT, and COL15A1), the ABCB6 gene that the present inventors have previously found as a biomarker that can predict the risk of developing hepatocellular carcinoma When a biomarker was selected by paying attention to the transcription factor binding site existing in the upstream sequence of (International Publication No. 2011/122021 pamphlet), the ESR1 gene was found as an HCC biomarker.

  Furthermore, when constructing a diagnostic system that uses the expression of a gene as a biomarker, combining multiple genes is expected to improve diagnostic capabilities. However, a biomarker obtained from a single method is homogeneous in a sense. Therefore, the present inventors considered that there is a limit in improving the diagnostic system even if they are combined. Therefore, in addition to the above 8 types of HCC biomarker genes (TSPAN8, CYP2A6, SLC22A1, NQO1, SLC10A1, GLYAT, ESR1 and COL15A1) obtained by various types of approaches, ABCB6 genes are combined to predict HCC recurrence. Study was carried out. As a result, when discriminant analysis was performed based on the measurement results of the mRNA expression levels of the five genes (TSPAN8, SLC22A1, NQO1, COL15A1, and ABCB6), “ It is 88% (sensitivity) that is judged as “with relapse of HCC within 2 years after”, whereas “within 2 years after operation over 2 years after operation” It is 100% (specificity) that is determined as “no HCC re-occurrence”, and it was confirmed that the risk of HCC onset or recurrence can be determined with high accuracy. The present invention has been completed based on these findings.

That is, the present invention provides (1) a decrease in the expression of mRNA or cDNA of one or more genes selected from the genes in [Group A] below, or a decrease in the expression of proteins encoded by them, or a gene in [Group B] The present invention relates to a method for determining the risk of developing hepatocellular carcinoma, which comprises detecting an increase in the expression of mRNA or cDNA of one or more genes selected from
[Group A]
CYP2A6, SLC10A1, SLC22A1, ESR1, GLYAT
[Group B]
TSPAN8, NQO1

Moreover, the present invention is characterized in that (2) the gene is selected from the following [A ′ group] included in [A group] or the following [B ′ group] included in [B group]. The present invention relates to the method described in (1).
[A 'group]
CYP2A6, SLC10A1, SLC22A1, ESR1
[B 'group]
TSPAN8

Further, the present invention provides (3) the method according to (1) above, wherein the gene is ESR1 included in [Group A] or NQO1 included in [Group B], or (4) [ A method according to any one of (1) to (3) above, wherein 4 or more genes are selected from genes in [Group A] and / or [Group B], and (5) at least [ TSPAN8 included in [B group] is selected, the method described in (4) above, (6) CYP2A6, SLC10A1, and GLYAT included in [A group], and included in [B group] In addition to the method according to (4) or (5) above, wherein (7) the gene in [A group] and / or [B group] is selected, and [Group]] detects mRNA or cDNA of gene or protein encoded by them, and / or decreases gene mRNA or cDNA of [D group] or protein encoded by them, and performs discriminant analysis This relates to the method according to any one of (4) to (6) above.
[Group C]
COL15A1
[Group D]
ABCB6

  The present invention also includes (8) SLC22A1 included in [A group], TSPAN8 and NQO1 included in [B group], COL15A1 included in [C group], and ABCB6 included in [D group]. It is related with the method in any one of said (4)-(7) characterized by selecting.

  The determination method of the present invention does not include a diagnostic action by a doctor, and other aspects of the determination method include a method of collecting data for determining (predicting) the risk of developing or recurrent hepatocellular carcinoma. be able to.

The present invention also relates to (9) expression of mRNA or cDNA of one or more genes selected from genes in [Group A] below, or mRNA or cDNA of one or more genes selected from genes in [Group B]. The present invention relates to a kit for determining the risk of developing hepatocellular carcinoma, comprising a primer pair or a probe for detecting expression, or a label thereof.
[Group A]
CYP2A6, SLC10A1, SLC22A1, ESR1, GLYAT
[Group B]
TSPAN8, NQO1

The present invention is also characterized in that (10) the gene is selected from the following [A ′ group] included in [A group] or the following [B ′ group] included in [B group]. The kit according to (9) above.
[A 'group]
CYP2A6, SLC10A1, SLC22A1, ESR1
[B 'group]
TSPAN8

  The present invention also relates to the kit according to (9) above, wherein the gene (11) is ESR1 contained in [Group A] or NQO1 contained in [Group B].

The present invention also relates to (12) an antibody that specifically binds to a protein encoded by one or more genes selected from genes in [Group A] below, or one or more genes selected from genes in [Group B]. The present invention relates to a kit for determining the risk of developing hepatocellular carcinoma, comprising an antibody that specifically binds to a protein encoded by or a label thereof.
[Group A]
CYP2A6, SLC10A1, SLC22A1, ESR1, GLYAT
[Group B]
TSPAN8, NQO1

Moreover, the present invention is characterized in that (13) the gene is selected from the following [A ′ group] included in [A group] or the following [B ′ group] included in [B group]. The kit according to (12) above.
[A 'group]
CYP2A6, SLC10A1, SLC22A1, ESR1
[B 'group]
TSPAN8

  Furthermore, the present invention relates to the kit according to (12) above, wherein the gene (14) is ESR1 contained in [A group] or NQO1 contained in [B group].

  According to the present invention, it is possible to accurately determine (predict) the risk of recurrence of hepatocellular carcinoma after surgery in the treatment of hepatocellular carcinoma, and to determine the postoperative treatment policy for the treatment of hepatocellular carcinoma. . Moreover, according to the present invention, useful information for prevention and early detection of hepatocellular carcinoma can be provided. Furthermore, according to the present invention, it is suggested that DNA methylation in the HCC biomarker gene of the present invention is related to the onset of hepatocellular carcinoma.

It is a figure which shows the result of having analyzed the expression level of mRNA of three types of genes (TSPAN8, CYP2A6, and SLC22A1) by the microarray method (upper stage) and real-time PCR method (lower stage). In the figure, “no recurrence”, “1 to 2 years recurrence”, and “recurrence within 1 year” indicate that there is no recurrence of HCC more than 2 years after surgery, and 1 year after surgery and within 2 years. (1 to 2 years) An HCC re-occurrence group and an HCC re-occurrence group within 1 year after surgery are shown (the same applies to FIGS. 2 and 3). In the figure, “*” indicates a statistically significant difference by the Kruskal Wallis test, and “**” indicates a statistically significant difference (P <0.05) by the Steel test (FIG. The same applies to 2 and 3.) It is a figure which shows the result of having analyzed the expression level of mRNA of three types of genes (NQO1, SLC10A, and GLYAT) by the microarray method (upper part) and the real-time PCR method (lower part). It is a figure which shows the result of having analyzed the expression level of mRNA of ESR1 gene by the microarray method (left figure) and real-time PCR method (right figure). Statistical analysis software IBM SPSS based on the expression levels of mRNAs of nine genes (TSPAN8, CYP2A6, SLC22A1, ESR1, NQO1, SLC10A, GLYAT, COL15A1, and ABCB6) analyzed using real-time PCR It is a figure which shows the result of having performed Receiver Operating Characteristic (ROC) curve analysis using Statics 17.0 (made by IBM), and having evaluated discrimination | determination performance by making the area under a ROC curve (Area) into a parameter | index. In the figure, “Relapse within 1 year” indicates the result of a comparative study between the HCC non-relapsed group within 1 year after surgery and the HCC relapsed group within 1 year after surgery, and “Relapse within 2 years” Shows the result of comparative examination between the HCC non-relapsed group and the HCC re-occurrence group within 2 years after the operation over 2 years after the operation. In the figure, “IHR predictive value” indicates a combination of mRNA expression levels of five types of genes (TSPAN8, SLC22A1, NQO1, COL15A1, and ABCB6). It is a figure which shows the result of having performed the discriminant analysis by the combination of five types of genes (TSPAN8, SLC22A1, NQO1, COL15A1, and ABCB6) based on the result obtained in FIG.

Examples of the method for determining the risk of developing hepatocellular carcinoma according to the present invention include, for example, subjects who are uncertain whether hepatocellular carcinoma has developed or subjects who have been treated for hepatocellular carcinoma such as surgery (hepatocellular carcinoma). Decrease in expression of HCC biomarker gene (group) mRNA or its reverse transcript (cDNA) in [Group A], or a protein encoded by the mRNA or cDNA, in a sample for determination collected from a patient) The method is not particularly limited as long as it is a method for detecting a decrease in expression and / or an increase in the expression of mRNA or cDNA of the HCC biomarker gene (s) in [Group B], or an increase in the expression of the protein encoded by the mRNA or cDNA.
The kit for determining the risk of developing hepatocellular carcinoma according to the present invention includes the expression of mRNA or cDNA of the HCC biomarker gene in [Group A] and / or the mRNA of the HCC biomarker gene in [Group B]. Alternatively, a kit comprising a primer pair or probe for detecting the expression of cDNA, or a label thereof (hereinafter referred to as “this kit 1”), or a protein encoded by the HCC biomarker gene in [Group A] above A kit (hereinafter referred to as “this kit 2”) comprising an antibody that specifically binds and / or an antibody that specifically binds to a protein encoded by the HCC biomarker gene in [B group] above, or a label thereof. If there is no particular limitation.
The term “hepatocellular carcinoma onset” in the present invention means that hepatocytes that are not cancerous or hepatocytes in a precancerous state become cancerous, or cancer cells in other organs other than the liver enter the liver. In addition to the new onset of hepatocellular carcinoma, metastasis is the first time cancer has formed in the liver tissue, and in the non-cancerous liver tissue after removal of the cancer part for treatment Also included is the recurrence (recurrence) of hepatocellular carcinoma.

  The determination method of the present invention and the gene in the present kit 1 and the present kit 2 are included in the above [Group A] when determining the risk of developing hepatocellular carcinoma that recurs within 2 years after hepatocellular carcinoma treatment. A gene selected from the above [A 'group] and / or the above [B' group] included in the above [B group] is preferable, and hepatocellular carcinoma that recurs within 1 year after hepatocellular cancer treatment When determining the onset risk, ESR1 included in the [A group] and / or NQO1 included in the [B group] are preferable. Moreover, the risk of developing hepatocellular carcinoma that recurs within 2 years after hepatocellular carcinoma treatment by detecting increased expression of mRNA or cDNA of the COL15A1 gene or the protein encoded by them contained in [Group C] above Can also be determined.

  Examples of the determination sample include non-liquid samples such as tissues, cells, and organs derived from liver tissue, and liquid samples such as blood, serum, and saliva. For example, the liver tissue may be a frozen tissue that has been subjected to a freezing treatment after being collected from a subject, or a pathological tissue that has been subjected to a histopathological treatment. Formalin-fixed tissue, formalin-fixed paraffin-embedded tissue and the like can be exemplified.

In the determination method of the present invention, the expression level of the mRNA or cDNA of the HCC biomarker gene or the expression level of the protein encoded by the mRNA or cDNA in the above [Group A] in the determination sample collected from the subject is The expression level of the mRNA or cDNA of the HCC biomarker gene in the above [Group B] in the determination sample collected from the subject when the expression level is decreased compared to the expression level in the control sample, or the mRNA or If the expression level of the protein encoded by the cDNA is increased compared to the expression level in the control sample, the risk of hepatocellular carcinoma onset (recurrence) in the subject is high, or the prognosis of hepatocellular carcinoma treatment in the subject is high Can be evaluated (predicted) as bad (poor prognosis).
In addition, the expression level of the mRNA or cDNA of the HCC biomarker gene in [Group A] or the expression level of the protein encoded by the mRNA or cDNA in the determination sample collected from the subject is the expression level in the control sample. Or the expression level of mRNA or cDNA of the HCC biomarker gene in the above [Group B] in the determination sample collected from the subject, or the protein encoded by the mRNA or cDNA When the expression level is not increased compared to the expression level in the control sample, the risk of hepatocellular carcinoma onset (recurrence) in the subject is low, or the prognosis of hepatocellular carcinoma treatment in the subject is good (good prognosis) Can be evaluated (predicted).
In addition, the prognosis of hepatocellular carcinoma treatment refers to hepatocellular carcinoma patients who have undergone hepatocellular carcinoma treatment, such as hepatocellular carcinoma patients, hepatocellular carcinoma recurrence patients, hepatocellular carcinoma metastases ( (Subject) 's survival and recovery period after treatment (period in which no recurrence of hepatocellular carcinoma or metastasis to other organs other than the liver is observed).

  Examples of the control sample include tissues, cells, blood, saliva, and the like derived from healthy individuals, as well as tissues, cells, organs that are clearly judged not to be cancerous in light of criteria usually used by those skilled in the art, such as doctors. Examples thereof include non-liquid samples such as blood and liquid samples such as blood and saliva. These control samples are preferably control samples that have been collected and then subjected to the same treatment as the determination sample.

  In the determination method of the present invention, as a method for detecting the decrease or increase in the expression of mRNA or cDNA of a gene, HCC biomarker genes in [Group A] and [Group B] (hereinafter collectively referred to as “this case”). Any method may be used as long as it can specifically detect a part or all of mRNA or cDNA of “HCC biomarker gene”, specifically, total RNA in cells in a determination sample. Extracted / purified, extracted by the Northern blotting method using a probe consisting of a base sequence complementary to the mRNA of the HCC biomarker gene, or extracted / purified by extracting and purifying total RNA in cells in the sample for determination. After synthesizing cDNA using a transcriptase, the cDNA of the HCC biomarker gene is specific. Quantitative PCR methods such as competitive PCR and real-time PCR methods using primer pairs to be amplified, and total RNA in cells in the sample for determination were purified, and cDNA was synthesized using reverse transcriptase After labeling the cDNA with biotin, digoxigenin, etc., and then indirectly labeling the cDNA with an antibody that recognizes avidin or digoxigenin with high affinity for biotin labeled with a fluorescent substance. Detecting by microarray using probe consisting of base sequence complementary to cDNA of HCC biomarker gene immobilized on a support that can be used for hybridization such as glass, silicon, plastic, etc. Purify total RNA in cells in a sample for use and combine cDNA using reverse transcriptase. Then, the cDNA was cleaved with restriction enzymes (MspI, MseI, etc.), adapter sequences were bound, PCR was performed using these as template DNA, and each PCR product was developed by capillary electrophoresis. Examples thereof include a HiCEP method for verifying a peak derived from a PCR product. For example, the mRNA and cDNA sequence information of the HCC biomarker gene is searched from the NCBI (http://www.ncbi.nlm.nih.gov/guide/) database based on the HCC biomarker gene name, for example. Can be obtained.

  In the determination method of the present invention, as a method for detecting a decrease or increase in protein expression, a part of a protein encoded by mRNA or cDNA of the HCC biomarker gene (hereinafter referred to as “the HCC biomarker protein”) or Any method can be used as long as it can specifically detect the whole, specifically, an immunological assay using an antibody that specifically recognizes the HCC biomarker protein, or the HCC A mass spectrometry method for detecting a peptide constituting a biomarker protein can be mentioned. The amino acid sequence information of the present HCC biomarker protein can be obtained by searching the NCBI (http://www.ncbi.nlm.nih.gov/guide/) database based on the HCC biomarker gene name, for example. Can be obtained.

Preferable examples of the immunological measurement method include immunohistochemical staining method, ELISA method, EIA method, RIA method, Western blotting method and the like. In addition, the mass spectrometry is a peptide sample obtained by converting a peptide sample into gaseous ions using an ion source (ionization), and ionizing the sample by moving in a vacuum using electromagnetic force or by a time-of-flight difference. Is a measurement method using a mass spectrometer that can be separated and detected in accordance with the mass-to-charge ratio. The ionization method using an ion source includes the EI method, the CI method, the FD method, the FAB method, and the MALDI method. A method such as the ESI method can be selected as appropriate, and the method of separating the ionized peptide sample in the analysis unit includes a magnetic deflection type, a quadrupole type, an ion trap type, and a time of flight (TOF) type. A separation method such as a Fourier transform ion cyclotron resonance type can be selected as appropriate. Further, tandem mass spectrometry (MS / MS) or triple quadrupole mass spectrometry combining two or more mass spectrometry methods can be used. Moreover, the peptide which comprises this HCC biomarker protein can be isolate | separated and refined | purified by a liquid chromatograph (LC) or HPLC, and it can be set as a sample. Moreover, a detection part and a data processing method can also be selected suitably. In addition, when detecting and quantifying the peptide constituting the HCC biomarker protein by mass spectrometry using mass spectrometry, a peptide consisting of the same amino acid sequence as that peptide and labeled with a stable isotope with a known concentration is used. Can be an internal standard. As such a stable isotope labeled peptide, one or more of the amino acids in the peptide constituting the present HCC biomarker protein to be detected contains any one or more of ¹⁵ N, ¹³ C, ¹⁸ O, and ² H. In the case of a labeled peptide, the type, position, number, and the like of amino acids can be appropriately selected. Such a stable isotope-labeled peptide can be obtained by the F-moc method (Amblard., Et al.) Using an amino acid labeled with a stable isotope. al. Methods Mol Biol. 298: 3-24 (2005)) or the like, iTRAQ (registered trademark) reagent, ICAT (registered trademark) reagent, ICPL (registered trademark) reagent, It can also be prepared using a labeling reagent such as an NBS (registered trademark) reagent.

  In order to increase the accuracy of the determination method of the present invention, it is preferable to perform discriminant analysis from the genes in the above [A group] and [B group]. If it can discriminate the onset risk, it will not restrict | limit, For example, 2 or more, 3 or more, 4 or more etc. can be mentioned, Especially 4 or more can be illustrated suitably. Further, in addition to the genes in [Group A] and [Group B], the expression of mRNA or cDNA of the gene in [Group C] or the protein encoded by them, and the gene in [Group D] Discriminant analysis may be carried out by detecting a decrease in the expression of mRNA or cDNA or the protein encoded by them. When performing discriminant analysis, the number and type of genes to be selected are sensitivity (probability that can be discriminated as a positive test [with or without hepatocellular carcinoma] in true hepatocellular carcinoma onset or recurrence group) and specificity. (Probability of discriminating negative test [no hepatocellular carcinoma onset or no recurrence] in true healthy subjects or no hepatocellular carcinoma recurrence group) and / or positive predictive value (positive test [onset hepatocellular carcinoma] Or in the case of recurrence] group, the probability of being a true hepatocellular carcinoma patient or a recurrence patient) and a negative predictive value (negative test [distinguished from the occurrence or recurrence of hepatocellular carcinoma] group). Or the probability of being non-recurrent hepatocellular carcinoma), and the sensitivity and / or specificity may be at least 50%, preferably at least 78%, more preferably At least 88% Preferably at least 92%, most preferably 100%, the positive predictive value and / or negative predictive value may be at least 50%, preferably at least 78%, more preferably at least 88%. %, More preferably at least 92%, and most preferably 100%. In addition, the sensitivity (%) is expressed by the formula “([number of test positive persons in true hepatocellular carcinoma onset or recurrence group] / [number of true hepatocellular carcinoma onset or recurrence]) × 100”. Specificity (%) can be calculated by inputting the formula “([number of true healthy individuals or non-relapsed group, number of test negatives] / [number of true healthy or non-relapsed persons] ]) × 100 ”, and the positive predictive value (%) is calculated by the formula“ ([number of true hepatocellular carcinoma onset or relapse among test positive group] / [Negative test number]) × 100 ”can be calculated by inputting the negative predictive value (%) of the formula“ ([test negative group of true healthy or non-relapsed people]. Number] / [number of test negatives]) × 100 ”.

  In the determination method of the present invention, when performing discriminant analysis, it is preferable to select at least TSPAN8 included in [B group], and as a combination of genes when selecting at least TSPAN8 included in [B group], For example, a combination of CYP2A6, ESR1, and GLYAT included in [A group] and TSPAN8 included in [B group], CYP2A6, SLC10A1, and GLYAT included in [A group], and [B group] A combination with TSPAN8 included, a combination of CYP2A6, SLC10A1 and GLYAT included in [A group] and a TSPAN8 included in [B group], SLC10A1 and GLYAT included in [A group], [ TSPA included in Group B] 8 and NQO1, combinations of CYP2A6, SLC10A1, ESR1, and GLYAT included in [A group] and TSPAN8 included in [B group], CYP2A6, SLC10A1, included in [A group], And GLYAT and TSPAN8 and NQO1 included in [B group], SLC22A1 included in [A group], TSPAN8 and NQO1 included in [B group], and [C group] A combination of COL15A1 and ABCB6 included in [D group], SLC10A1 and SLC22A1 included in [A group], TSPAN8 and NQO1 included in [B group], and COL15A1 included in [C group] And included in [Group D] Combination with ABCB6, SLC22A1 and GLYAT included in [A group], TSPAN8 and NQO1 included in [B group], COL15A1 included in [C group], and ABCB6 included in [D group] , SLC10A1, SLC22A1 and GLYAT included in [A group], TSPAN8 included in [B group], COL15A1 included in [C group], and ABCB6 included in [D group] Combinations of CYP2A6, SLC10A1, SLC22A1, and GLYAT included in [A group], TSPAN8 and NQO1 included in [B group], and COL15A1 included in [C group], [A group] Included in CYP2A6, SL Combinations of C10A1 and SLC22A1, TSPAN8 and NQO1 included in [B group], COL15A1 included in [C group], and ABCB6 included in [D group], and CYP2A6 included in [A group] , SLC10A1, SLC22A1, and GLYAT, a combination of TSPAN8 included in [B group], COL15A1 included in [C group], ABCB6 included in [D group], and SLC10A1 included in [A group] , SLC22A1 and GLYAT, TSPAN8 and NQO1 included in [B group], COL15A1 included in [C group], and ABCB6 included in [D group], and included in [A group] CYP2A6, SLC10A1 Combinations of SLC22A1, ESR1, and GLYAT, TSPAN8 included in [B group], COL15A1 included in [C group], and ABCB6 included in [D group], CYP2A6, SLC10A1 included in [A group] , SLC22A1 and GLYAT, TSPAN8 and NQO1 included in [B group], COL15A1 included in [C group], and ABCB6 included in [D group], and included in [A group] Examples include combinations of CYP2A6, SLC10A1, SLC22A1, ESR1 and GLYAT, TSPAN8 and NQO1 included in [B group], COL15A1 included in [C group], and ABCB6 included in [D group]. Can Among these, combinations of CYP2A6, SLC10A1, and GLYAT included in [A group] and TSPAN8 included in [B group], SLC22A1 included in [A group], and [B group] A combination of TSPAN8 and NQO1, COL15A1 included in [C group], and ABCB6 included in [D group] is preferable.

  As the discriminant analysis, based on the data of whether advance which sample (detection sample) belongs to one which group is (healthy person or hepatocellular carcinoma recurrence-free group or hepatocellular carcinoma onset or hepatocellular carcinoma recurrence group) Any method that determines a function (discriminant function) that discriminates which group a sample that does not know which group belongs to is not limited. Among the discriminant functions, as a linear discriminant function, for example, a discriminant function based on a hyperplane or a straight line As a nonlinear discriminant function, for example, a discriminant function based on a Mahalanobis 氾 distance by a hypersurface or curve can be cited.

  The primer pair in the present kit 1 is a primer pair that can be annealed with a part of the upstream and downstream sequences of the cDNA of the present HCC biomarker gene. The length of the cDNA to be amplified can be appropriately selected in consideration of the amplification efficiency and specificity of the DNA. For example, 15 to 30 bases can be selected as the length of the primer sequence, and 50 to 300 bases can be selected as the length of the cDNA to be amplified.

  The probe in the present kit 1 is a probe that hybridizes with part or all of the mRNA or cDNA of the present HCC biomarker gene. The length of the probe, the site that hybridizes with the splicing variant, etc. It can be appropriately selected in consideration of efficiency and specificity.

The antibody in the present kit 2 may be a monoclonal antibody, a polyclonal antibody, a human antibody, a chimeric antibody, a humanized antibody or the like, and among these, F (ab ′) ₂ , Fab, diabody, Antibody fragments comprising a part of an antibody such as Fv, ScFv, Sc (Fv) ₂ are also included. In addition, the present kit 2 includes a secondary antibody conjugated with a labeling substance such as a fluorescent substance or an enzyme for detecting the antibody in the present kit 2 bound to an amino acid residue of the present HCC biomarker protein. In addition, at least one kind of antibody that reacts with an epitope different from the antibody in the present kit 2 can be included. Further, the present kit 2 may further include a buffer solution, a pH adjuster, a reaction container and the like according to necessity and purpose.

Examples of the labeling substance in the primer pair and the probe in the present kit 1 and the labeled product of the antibody in the present kit 2 include biotin, green fluorescent protein (GFP), horseradish peroxidase (HRP), ³² P can be specifically mentioned.

  EXAMPLES Hereinafter, although an Example demonstrates this invention more concretely, the technical scope of this invention is not limited to these illustrations.

1. Screening of candidate genes involved in HCC re-emergence using microarray method 1-1 cDNA isolation method Five hepatoma samples from the HCC re-occurrence group within 1 year after surgery were used for TRIzol Reagent (Life Technologies) and PureLink Micro-to-Midi Total RNA Purification Kit (Life Technologies) were used to purify total RNA, and then cDNA was synthesized using PrimeScript RT reagent Kit (TaKaRa Bio). In addition, cDNA synthesized from 5 liver tissue samples derived from the HCC non-relapsed group more than 2 years after the operation was used as a control.

1-2 Microarray Method cDNA synthesized by the method described in Example 1-1 “1-1 cDNA isolation method” was fluorescently labeled with Cy3 using DNA Labeling Kits (Roche Applied Science). Subsequently, the fluorescently labeled cDNA was hybridized to Human Gene Expression 4x72K Arrays (Roche). Hybridization was performed using Hybridization Kits (Roche Applied Science) and NimbleGen Hybridization Systems (Roche Applied Science) at 42 ° C. for 16 hours. Scanning of the fluorescent signal was performed using GenePix 4000B (manufactured by Molecular Devices), and image analysis of the acquired fluorescent signal was performed using NimbleScan Software (manufactured by Roche Applied Science). Subsequent statistical analysis was performed using GeneSpring GX (manufactured by Agilent Technologies). Based on the selection criteria (Fold-change> 2.0, P value <0.05), candidate genes involved in HCC re-emergence were identified. P values were calculated by asymptotically calculated unpaired t-test and Benjamini-Hochberg FDR multiple-testing correction.

1-3 Results Compared with the HCC non-relapsed group more than 2 years after the operation, 1806 genes (increase or decrease in the fluorescence signal in the HCC re-occurrence group within 1 year after the operation) 830 types; increase in expression level, 976 types; decrease in expression level). Among these, 45 genes (24 types; increased expression level, 21 types; decreased expression level) could be identified as genes satisfying the above selection criteria, and such genes were designated as candidate genes involved in HCC re-emergence.

2. Identification of candidate genes involved in re-emergence of HCC using HiCEP method 2-1 HiCEP method cDNA isolated by the method described in the section of “1-1-1 cDNA isolation method” in Example 1 above was used. The HiCEP method was performed according to the method described in the literature (Fukumura R et al., Nucleic Acids Res. 2003. 31: e94.). That is, after cleaving the cDNA with two types of restriction enzymes (MspI and MseI), the adapter sequence was bound. PCR was performed using “256 primer sets” using these as template DNA, each PCR product was developed by capillary electrophoresis, and the resulting PCR product-derived peak was verified. After screening the peaks based on the selection criteria (Fold-change> 5.0, Higher peak height> 1500), the PCR product from the peak was sequenced, and it was revealed that the PCR product was mRNA. Were identified as candidate genes involved in HCC re-emergence.

2-2 Results More than 2 years postoperatively compared with the non-relapsed HCC group within 1 year postoperatively, the increase or decrease in fluorescence signal in the HCC relapsed group, that is, the increase or decrease in expression level (Fold-change> 2.0, Higher peak It was confirmed that there were 2858 PCR products (height> 100) (1390 types; increased expression level, 1468 types; decreased expression level). Of these, 28 PCR products (15 types; increased expression level, 13 types; decreased expression level) are shown as PCR products that satisfy the above selection criteria (Fold-change> 5.0, Higher peak height> 1500). It was done. Of these, when 15 types of PCR products were sequenced, it was revealed that 6 types were derived from mRNA, and genes derived from these 6 types of PCR products were used as candidate genes involved in HCC re-onset.

3. Identification of genes involved in HCC re-emergence using real-time PCR method 3-1 Real-time PCR method The 45 types of candidate genes involved in HCC re-emergence identified by the method in Example 1 above, and the method in Example 2 above. For the 6 types of candidate genes involved in the re-emergence of HCC screened, the expression level of mRNA was quantified by analysis using a real-time PCR method. Specifically, using the cDNA isolated by the method described in the section “1-1-1 cDNA Isolation” as a template DNA, Universal ProbeLibrary Set, Human (Roche Applied Science), LightCycler 480 Probe Master A real-time PCR method was performed using Roche Applied Science (manufactured by Roche Applied Science) and LightCycler480 System II (manufactured by Roche Applied Science), and the number of PCR cycles (threshold cycle; Ct value) in which the PCR product was a constant amount was measured. As a control, the relative amount of the PCR product, that is, the relative amount of mRNA was calculated by the comparative Ct method (ΔΔCt method) based on the Ct value obtained by performing real-time PCR using cDNA derived from non-cancerous part as template DNA. .

3-2 Results As a result of the analysis by the real-time PCR method, 3 types of genes (TSPAN8, CYP2A6, and SLC22A1) among 45 types of candidate genes involved in HCC re-emergence screened by the microarray method described in Example 1 above were found. In the analysis by the real-time PCR method, the detection level was particularly high, and it became clear that there was a statistically significant difference in the expression level over 2 years after the operation compared with the non-relapsed HCC group. In addition, samples different from those used in Example 1 (6 samples and 7 samples, respectively) are selected from the HCC re-occurrence group within 1 year after the operation and the HCC non-re-occurrence group exceeding 2 years after the operation, and cDNA is selected. After the isolation, the microarray method (the upper part of FIG. 1) and the real-time PCR method (the lower part of FIG. 1) were performed. Similarly, the expression level of TSPAN8 gene mRNA in the HCC relapse group within one year after the operation More than 2 years later, compared to the non-relapsed group of HCC (left figure in FIG. 1), the expression levels of CYP2A6 and SLC22A1 gene mRNA in the relapsed group of HCC within 1 year after the operation More than 2 years later, there was a decrease compared to the HCC non-relapsed group (the central and right diagrams in FIG. 1 respectively), and there was a statistically significant difference between the two groups (P <0.05). . Furthermore, when examined using 11 specimens derived from the HCC relapse group 1 to 2 years after the operation, the expression levels of the above three genes exceeded 1 year after the operation compared to the HCC non-relapse group 1 Increased (TSPAN8) or decreased (CYP2A6 and SLC22A1) in the 2-year relapse group, and a statistically significant difference was observed in the expression levels of the three genes between the two groups (P <0.05). (FIG. 1). From these results, it was possible to identify three types of genes (TSPAN8, CYP2A6, and SLC22A1) as genes involved in HCC re-emergence.

  As a result of analysis by the real-time PCR method, three types of genes (NQO1, SLC10A1, and GLYAT) among the six types of candidate genes involved in the re-emergence of HCC screened by the HiCEP method described in Example 2 above are real-time PCR. In the analysis by the method, the detection level was particularly high, and it became clear that there was a statistically significant difference in the expression level over 2 years after the operation compared with the non-relapsed HCC group. In addition, samples different from those used in Example 1 (6 samples and 7 samples, respectively) are selected from the HCC re-occurrence group within 1 year after the operation and the HCC non-re-occurrence group exceeding 2 years after the operation, and cDNA is selected. After isolation, the microarray method and real-time PCR method were performed. Similarly, the expression level of NQO1 gene mRNA in the HCC relapse group within 1 year after the operation exceeded 2 years after the operation, and no HCC re-occurred. Compared to the group (left figure in FIG. 2), the expression levels of SLC10A1 and GLYAT gene mRNA in the HCC re-occurrence group within 1 year after the operation exceeded 2 years after the operation and no HCC re-occurred. Compared with the group, it decreased (the center figure of FIG. 2, and the right figure, respectively), and the statistically significant difference was recognized by these expression levels between both groups (P <0.05). Furthermore, when a comparative study was performed using the 1- to 2-year-relapsed group after surgery, the expression levels of the above three genes exceeded the 2-year postoperative period compared to the HCC-free group for 1 to 2 years after the surgery. Increased (NQO1) or decreased (SLC10A1 and GLYAT) in the relapsed group, and a statistically significant difference was observed in the expression level of the SLC10A1 gene between the two groups (P <0.05) (FIG. 2) . From these results, three types of genes (NQO1, SLC10A1, and GLYAT) could be identified as genes involved in HCC re-emergence.

4). Identification of genes involved in HCC re-emergence focusing on genes showing HCC tissue-specific expression In Examples 1-3 above, candidate genes involved in HCC re-emergence were screened and identified from HCC re-emerged specimens. In this example, candidate genes involved in the onset of HCC were identified from among genes showing HCC tissue-specific expression, from which an attempt was made to identify a gene involved in the reoccurrence of HCC. First, cDNA was synthesized by the method described in the section of “1-1-1 cDNA isolation method” in the above Examples using hepatocellular carcinoma tissue samples derived from 5 specimens of HCC development. In addition, cDNA synthesized from a peripheral non-cancer liver tissue sample derived from the 5 HCC-onset specimens was used as a control. Using cDNA, microarray analysis was performed by the method described in the item “1-2 microarray method” of Example 1 above, and candidate genes involved in the onset of HCC were screened. As a result, 41 types of genes could be screened as candidate genes involved in HCC development. Among these 41 types of genes, 5 types were identified as genes involved in the onset of HCC by the real-time PCR method according to the method described in Example 3 above, and the expression level of the COL15A1 gene, which is one of them, in the HCC tissue is: More than 2 years after surgery, the HCC non-relapsed group was 10.4 times the expression level in the peripheral non-cancerous liver tissue, whereas the HCC relapsed group within 1 year after surgery When compared with the expression level in cancer liver tissue, it was found to be 3.2 times. That is, it is shown that the elevated level of COL15A1 gene expression in HCC tissues is significantly lower in the HCC re-occurrence group within 1 year after the operation than in the HCC re-occurrence group over 2 years after the operation. It was done. From this result, COL15A1 could be identified as a gene involved in HCC re-emergence.

5. Identification of genes involved in HCC re-emergence focusing on transcriptional regulatory factors In Examples 1 and 2 above, candidate genes involved in HCC re-emergence were screened by exhaustive analysis using the microarray method or HiCEP method. By the microarray method and HiCEP method of Examples 1 to 4 above, the expression level increased or decreased in the HCC re-occurrence group within 1 year after the operation compared to the HCC non-re-occurrence group after 2 years after the operation. In addition to the seven types of genes (TSPAN8, CYP2A6, SLC22A1, NQO1, SLC10A1, GLYAT, and COL15A1), the ABCB6 gene that the present inventors have previously found as a biomarker that can predict the risk of developing hepatocellular carcinoma Upstream sequence (5 kb upstream from the translation start point to 0.5 kb downstream from the translation start point) Focusing on the transcription factor binding site present in the sequence (including the region), an attempt was made to screen candidate genes involved in HCC re-emergence. First, the presence or absence of a transcription factor binding site was analyzed using the MATCH and p-MATCH programs, and 40 transcription factor binding sites were revealed. Whether or not there is an increase or decrease in mRNA expression level in the HCC relapse group within 1 year after surgery compared to the HCC non-relapse group for more than 2 years after surgery for the transcription factor binding to the transcription factor binding site This was verified by microarray method and real-time PCR method. The microarray method is performed based on the selection criteria (Fold-change> 1.2) using the method described in the item “1-2 microarray method” in Example 1 above, and the real-time PCR method is the same as that in the above example. 3. The method described in the item “3-1 Real-time PCR method” was performed.

  Among the transcription factors, 21 types of candidate genes involved in HCC re-emergence satisfying the selection criteria (Fold-change> 1.2) could be identified. The mRNA expression levels of these 21 types of genes were confirmed by real-time PCR. As a result, the level of ESR1 gene detection was particularly high, and the expression level was statistically higher than the HCC non-relapsed group over 2 years after surgery. It became clear that there was a significant difference. In addition, samples different from those used in Example 1 (6 samples and 7 samples, respectively) are selected from the HCC re-occurrence group within 1 year after the operation and the HCC non-re-occurrence group exceeding 2 years after the operation, and cDNA is selected. After the isolation, the microarray method (left diagram in FIG. 3) and the real-time PCR method (right diagram in FIG. 3) were performed. Similarly, the expression of mRNA of the ESR1 gene in the HCC relapse group within one year after surgery The amount decreased over 2 years after the operation compared with the non-relapsed HCC group, and a statistically significant difference was observed between the two groups (P <0.05). (Figure 3). Furthermore, when a comparative study was conducted using the 1- to 2-year-relapsed group after surgery, the expression level of the ESR1 gene exceeded the 2-year post-surgery group compared to the HCC-non-relapsed group for 1 to 2 years after the surgery. (Fig. 3). From these results, ESR1 could be identified as a gene involved in HCC re-emergence.

6). Examination of HCC recurrence prediction using 8 identified genes 6-1 Comparison study between HCC non-relapsed group over 1 year after operation and HCC re-emerged group within 1 year after operation, and 2 after operation Comparative study between HCC non-relapsed group over 2 years and HCC onset group within 2 years after surgery In the above Examples 1-5, 8 genes (TSPAN8, CYP2A6, SLC22A1, ESR1, NQO1 that can predict relapse of HCC) , SLC10A1, GLYAT, and COL15A1) mRNA expression levels in the HCC non-relapsed group and the HCC re-occurrence group within 2 years after surgery, or 2 years after surgery However, in this example, the HCC non-relapsed group (postoperative 2) exceeded 1 year after the operation. Over-year HCC non-relapsed group + operation 1- to 2-year re-onset group) and HCC re-onset group within 1 year after surgery, and HCC re-onset group within 2 years after surgery and HCC re-onset group within 2 years after surgery ( A comparative study was conducted between the HCC re-occurrence group within 1 year after the operation and the 1-2 year re-occurrence group after the operation) (FIG. 4). As a control, ABCB6 gene (International Publication No. 2011/122021 pamphlet) which is a biomarker for predicting recurrence of hepatocellular carcinoma previously identified by the inventors was used. A comparative study was performed based on the results obtained by the real-time PCR method of Example 3 above. Among the above 8 genes and the control ABCB6 gene, the HCC non-relapsed group and 1 year after the operation exceeded 1 year. There were three statistically significant differences in the expression level (expression level ratio [mRNA expression level in HCC / expression level in surrounding non-cancerous liver tissue]) among HCC relapsed groups (ESR1) [P value = 0.023, AUC value = 0.815], NQO1 [P value = 0.033, AUC value = 0.796], and ABCB6 [P value = 0.009, AUC value = 0.861] In addition, there were 6 (TSPAN8 [P value) that had a statistically significant difference in the expression level between the HCC non-relapsed group and the HCC-onset group within 2 years beyond 2 years after surgery. = 0.033, AUC value = 0.782], YP2A6 [P value = 0.001, AUC value = 0.933], SLC22A1 [P value = 0.008, AUC value = 0.849], ESR1 [P value = 0.008, AUC value = 0.849] SLC10A1 [P value = 0.007, AUC value = 0.857], and COL15A1 [P value = 0.177, AUC value = 0.815]) (FIG. 4). As a result, three genes (ESR1, NQO1, and ABCB6) are useful as biomarkers for predicting the reoccurrence of HCC within one year after surgery, and six genes (TSPAN8, CYP2A6, SLC22A1, ESR1) , SLC10A1 and COL15A1) have been shown to be useful as biomarkers for predicting relapse of HCC within 2 years after surgery. In particular, the ESR1 gene has been shown to be useful as a biomarker for predicting relapse of HCC both within 1 year after surgery and within 2 years after surgery.

6-2 Discriminant Analysis When discriminant analysis was performed based on the results obtained in FIG. 4, a linear discriminant (Y = −0.288 × [TSPAN8 mRNA expression level] + 0.266 × [SLC22A1 mRNA expression level) was obtained. ] + (− 0.125) × [NQO1 mRNA expression level] + 0.511 × [COL15A1 mRNA expression level] + 0.379 × [ABCB6 mRNA expression level] +0.059) Can be sought. If a discrimination score of 0 or more exceeds 2 years after surgery without HCC re-occurrence, and a discrimination score of less than 0 indicates HCC re-occurrence within 2 years after surgery, 17 samples of true HCC re-occurrence within 2 years after surgery Among them, 15 specimens (sensitivity score: 88%) were judged as “re-onset of HCC within 2 years after surgery” according to this discriminant formula, whereas 2 years after true surgery It was 7 specimens (specificity: 100%) that were judged as “no HCC recurrence more than 2 years after surgery” in 7 specimens with no relapse (FIG. 5). In addition, the positive predictive value (probability of true HCC re-occurrence within 2 years after operation in the group with positive test [identified as having re-occurrence of HCC within 2 years after operation) is 100%. The negative predictive value (the probability of being true in the negative test [determined as having no reoccurrence of HCC beyond 2 years after surgery] group) was 78% (FIG. 5). From the above results, when discriminant analysis is performed based on the results of measuring the mRNA expression level of five genes (TSPAN8, SLC22A1, NQO1, COL15A1, and ABCB6) among the above eight genes that can predict HCC relapse. Both sensitivity and specificity were high, and it became clear that the reoccurrence of HCC within 2 years after surgery can be accurately predicted. It has also been revealed that these five genes are useful as biomarkers for predicting HCC relapse within 2 years after surgery. (Refer to "IHR predictive value" in FIG. 4) (P value <0.001, AUC value = 0.983).

  Furthermore, when the combination pattern of genes that can accurately predict the reoccurrence of HCC within 2 years after the operation was verified, combinations other than the combinations shown in FIGS. 4 and 5 described above can predict the reoccurrence of HCC with high accuracy. It became clear (Tables 1 and 2). For example, when discriminant analysis is performed based on the results of measuring mRNA expression levels of four genes (CYP2A6, SLC10A1, GLYAT, and TSPAN8), both sensitivity (82%) and specificity (100%) are high. It became clear that the relapse of HCC within 2 years later can be accurately predicted (AUC value≈0.99). Furthermore, it was confirmed that it is necessary to select at least the TSPAN8 gene and perform discriminant analysis in order to accurately predict the re-occurrence of HCC within 2 years after surgery.

  According to the present invention, since the risk of recurrence of hepatocellular carcinoma can be predicted, a postoperative treatment policy can be determined. In addition, it is expected to extend the survival and recovery period after surgery.

Claims (14)

Decrease in expression of mRNA or cDNA of one or more genes selected from genes in [Group A] below, or decrease in expression of protein encoded by them, or mRNA of one or more genes selected from genes in [Group B] Alternatively, a method for determining the risk of developing hepatocellular carcinoma, comprising detecting an increase in expression of cDNA or a protein encoded by the cDNA.
[Group A]
CYP2A6, SLC10A1, SLC22A1, ESR1, GLYAT
[Group B]
TSPAN8, NQO1 The method according to claim 1, wherein the gene is selected from the following [A 'group] included in [A group] or the following [B' group] included in [B group].
[A 'group]
CYP2A6, SLC10A1, SLC22A1, ESR1
[B 'group]
TSPAN8   The method according to claim 1, wherein the gene is ESR1 included in [Group A] or NQO1 included in [Group B].   The method according to claim 1, wherein discriminant analysis is performed by selecting four or more genes from [A group] and / or [B group].   5. The method according to claim 4, wherein TSPAN8 included in at least [B group] is selected.   The method according to claim 4 or 5, wherein CYP2A6, SLC10A1, and GLYAT included in [A group] and TSPAN8 included in [B group] are selected. In addition to the genes in [Group A] and / or [Group B], the expression of mRNA or cDNA of the gene in [Group C] below, or the protein encoded by them, and / or in [Group D] The method according to any one of claims 4 to 6, wherein a decrease in expression of mRNA or cDNA of the gene or a protein encoded by the gene is detected and discriminant analysis is performed.
[Group C]
COL15A1
[Group D]
ABCB6   The SLC 22A1 included in [A group], TSPAN8 and NQO1 included in [B group], COL15A1 included in [C group], and ABCB6 included in [D group] are selected. Item 8. The method according to any one of Items 4 to 7. Primer pairs for detecting the expression of mRNA or cDNA of one or more genes selected from the genes in [Group A] below, or the expression of mRNA or cDNA of one or more genes selected from the genes in [Group B] Alternatively, a kit for determining the risk of developing hepatocellular carcinoma, comprising a probe or a labeled product thereof.
[Group A]
CYP2A6, SLC10A1, SLC22A1, ESR1, GLYAT
[Group B]
TSPAN8, NQO1 The kit according to claim 9, wherein the gene is selected from the following [A 'group] included in [A group] or the following [B' group] included in [B group].
[A 'group]
CYP2A6, SLC10A1, SLC22A1, ESR1
[B 'group]
TSPAN8   The kit according to claim 9, wherein the gene is ESR1 included in [Group A] or NQO1 included in [Group B]. An antibody that specifically binds to a protein encoded by one or more genes selected from the genes in [Group A] below, or a protein encoded by one or more genes selected from the genes in [Group B] A kit for determining the risk of developing hepatocellular carcinoma, comprising a binding antibody or a label thereof.
[Group A]
CYP2A6, SLC10A1, SLC22A1, ESR1, GLYAT
[Group B]
TSPAN8, NQO1 The kit according to claim 12, wherein the gene is selected from the following [A 'group] included in [A group] or the following [B' group] included in [B group].
[A 'group]
CYP2A6, SLC10A1, SLC22A1, ESR1
[B 'group]
TSPAN8   The kit according to claim 12, wherein the gene is ESR1 included in [Group A] or NQO1 included in [Group B].