Diagnostic methods for prognosis of non-small-cell lung cancer using RIPK1 SNP

Abstract

The present invention relates to a marker for the diagnosis and prognosis prediction of non-small cell lung cancer (NSCLC) using a single nucleotide polymorphism (SNP) of the RIPK1 gene, a composition for the diagnosis and prognosis prediction of non-small cell lung cancer (NSCLC) using the same, a kit for the diagnosis and prognosis prediction of non-small cell lung cancer (NSCLC), a microarray, and a method for diagnosis and prognosis prediction. Specifically, the technology according to the present invention can enhance the therapeutic effect of non-small cell lung cancer (NSCLC) patients by providing diagnosis and prognosis prediction for patients with NSCLC, specifically by rapidly, simply, and accurately confirming tumor recurrence after curative resection and the effectiveness of adjuvant therapy.

Description

Technology Field

[0001] The present invention relates to a method for diagnosing and predicting the prognosis of non-small cell lung cancer using polymorphisms of RIPK1. Background Technology

[0002] Lung cancer is one of the leading causes of cancer death, accounting for 30% of cancer-related deaths worldwide. More than 75% of all lung cancers are non-small cell lung cancer (NSCLC), with an average 5-year survival rate of 15%.

[0003] These non-small cell lung cancers originate from non-small cells in lung tissue and exhibit various mutations, primarily in cell size and morphology, typically appearing as adenocarcinoma, squamous cell carcinoma, and large cell carcinoma. Treatment methods for the above-mentioned non-small cell lung cancer include radiation therapy, chemotherapy, and targeted therapy. In addition to conventional anticancer drugs, targeted therapy drugs such as crizotinib, gefitinib, and erlotinib are also used.

[0004] As described above, non-small cell lung cancer has a high incidence rate, and with the existence of various treatment methods, there is an increasing demand for methods that can effectively predict the prognosis for each patient. Accordingly, much research has recently been conducted on methods utilizing specific gene mutations in non-small cell lung cancer patients for treatment selection, diagnosis, and prognosis prediction. Methods utilizing these gene mutations can be effectively used to predict the degree of tumor progression or the response to drug therapy, and are evaluated as being relatively simple and highly accurate.

[0005] Meanwhile, although curative lung resection is primarily used for the treatment of the aforementioned non-small cell lung cancer, approximately 30 to 75% of non-small cell lung cancer patients experience local or metastatic recurrence after curative surgery and die from this recurrence. Platinum-based adjuvant chemotherapy has been used as a standard adjuvant therapy since the early 2000s, but it is difficult to see a definite effect on improving survival rates. Although recent advancements in targeted therapy and immunotherapy have improved the survival rate of early-stage non-small cell lung cancer patients, there is an increasing need to improve the survival rate of early-stage non-small cell lung cancer patients by discovering molecular biomarkers that predict tumor recurrence, in addition to developing such effective adjuvant therapies. Furthermore, while the Tumor-Node-Metastasis (TNM) staging system is currently commonly used as an indicator to predict tumor recurrence and the effectiveness of adjuvant therapy following curative resection in non-small cell lung cancer patients, the accuracy of prognosis prediction methods using this staging system is not high because the risk of recurrence and death varies significantly among patients even within the same stage.

[0006] Genetic polymorphism refers to a variation in genotype with a frequency of 1% or more within a population of a species, and can manifest in various forms such as differences in gene sequence, location, or number. Such genetic polymorphisms can be used in genetic diseases and pathology, drug metabolism and response prediction, cancer prognosis prediction, and the selection of personalized treatment methods, and due to their vast potential for application, they are currently being developed in various fields.

[0007] Single Nucleotide Polymorphisms (SNPs) are the most common form of human genetic variation, referring to a change in a single nucleotide sequence within the genome composed of A, T, G, and C. SNPs account for approximately 90% of variations occurring in the human genome, and there may be about one million SNPs in the genome. Since individuals with similar traits or pedigrees share identical or similar SNP patterns, they can be used in clinical settings as indicators to predict an individual's susceptibility to disease, as well as to predict the efficacy and side effects of drugs. Because these SNPs are primarily associated with the onset of disease, individuals with specific SNPs have a higher risk of developing certain diseases. Accordingly, SNPs can be utilized to understand the causes of disease development, develop new treatments, diagnose specific diseases, and predict prognoses.

[0008] The RIPK1 (Receptor-interacting protein kinase 1) gene is one of the key regulators of necropsis and is a major factor regulating NF-κB signaling and apoptosis, which promote survival in response to widespread inflammation and apoptosis stimuli in human diseases. While conventional studies have focused primarily on the necropsis-mediating ability of RIPK1, no method has been known to utilize RIPK1 gene polymorphisms for the diagnosis and prognosis prediction of non-small cell lung cancer.

[0009] Accordingly, the inventors performed a Luciferase analysis on the rs17548629 region at the 3'-UTR position of the RIPK1 gene and confirmed that rs17548629 regulates the expression of RIPK1 by regulating the binding of miR-642a-5p. Additionally, analysis of RIPK1 mRNA expression in lung cancer patient tissues revealed that RIPK1 expression and survival rates were high in the rs17548629 T genotype, while RIPK1 expression and survival rates were lower in the C genotype. Accordingly, it was confirmed that the RIPK1 rs17548629 C>T polymorphism can be effectively used for the diagnosis and prognosis prediction of non-small cell lung cancer. Furthermore, the invention was completed by confirming that it can be used as a more accurate biomarker for diagnosis and prognosis prediction in AC (adenocarcinoma), a subtype of non-small cell lung cancer. The problem to be solved

[0010] The objective of the present invention is to provide a polymorphic biomarker of the RIPK1 gene capable of diagnosing and predicting the prognosis of non-small cell lung cancer.

[0011] Another objective of the present invention is to provide a composition for diagnosing and predicting the prognosis of non-small cell lung cancer comprising the marker.

[0012] Another objective of the present invention is to provide a microarray for the diagnosis and prognosis prediction of a non-small cell lung cancer patient comprising the marker.

[0013] Another objective of the present invention is to provide a kit for the diagnosis and prognosis prediction of a non-small cell lung cancer patient comprising the marker.

[0014] Another objective of the present invention is to provide a method for diagnosing and predicting the prognosis of non-small cell lung cancer using polymorphisms of the RIPK1 gene. means of solving the problem

[0015] To achieve the above objective, the present invention provides a polynucleotide for the diagnosis and prognosis prediction of non-small cell lung cancer comprising a nucleotide at a specific position of SEQ ID NO. 1, or a polynucleotide complementary thereto.

[0016] To achieve the above objective, the present invention provides a composition comprising a polynucleotide for the diagnosis and prognosis prediction of non-small cell lung cancer or a polynucleotide complementary thereto, comprising the polynucleotide and a polypeptide encoded by the same.

[0017] In addition, the present invention provides a microarray for the diagnosis and prognosis prediction of non-small cell lung cancer comprising the polynucleotide and the polypeptide encoded by it.

[0018] In addition, the present invention provides a kit for diagnosing and predicting the prognosis of non-small cell lung cancer comprising the microarray.

[0019] In addition, the present invention provides a method for diagnosing and predicting the prognosis of non-small cell lung cancer using the polynucleotide and the polypeptide encoded by it. Effects of the invention

[0020] The present invention confirmed that RIPK1 mRNA expression in non-small cell lung cancer patient tissues is lower when the C genotype is present at the rs17548629 position of the RIPK1 gene, and RIPK1 mRNA expression is higher when the T genotype is present, and accordingly, the RIPK1 rs17548629 C>T polymorphism was discovered as a biomarker for the diagnosis and prognosis prediction of the non-small cell lung cancer.

[0021] Accordingly, the lung cancer prognosis prediction technology using RIPK1 rs17548629 C>T according to the present invention can be easily used to diagnose and evaluate the prognosis of patients with lung cancer, and as a means for selecting and evaluating treatment methods, thereby increasing the survival rate of patients with lung cancer and expanding the scope of application to include the discovery of additional SNP markers. Brief explanation of the drawing

[0022] Figure 1 shows the overall survival and disease-free survival curves according to the RIPK1 rs17548629 C>T genotype for the total patient group (A), lung adenocarcinoma patient group (B), and squamous cell carcinoma patient group (C) (AC: adenocarcinoma, SCC: squamous cell carcinoma, by multivariate Cox proportional hazards model P value). Figure 2 shows the results of the dual luciferase reporter analysis of RIPK1 rs17548629 C>T according to the present invention, and confirms the effect of RIPK1 rs17548629 C>T on the binding of miR-642a. The luciferase activity of the RIPK1 rs17548629 C and T alleles was normalized to pRL-SV40 renilla luciferase activity, and the data are expressed as mean ± SEM (n=8) (NC: negative control). The left plot of Fig. 3 shows the relative mRNA expression levels of RIPK1 according to the RIPK1 rs17548629 C>T genotype (horizontal line inside the box: median), and the right plot shows the Kaplan-Meier plot of overall survival according to the RIPK1 rs17548629 C>T genotype (AC: adenocarcinoma, SCC: squamous cell carcinoma, by log-rank test P value). Specific details for implementing the invention

[0023] The present invention will be described in detail below with reference to embodiments thereof. However, the following embodiments are presented as examples of the present invention and are not intended to limit the present invention, and various modifications and applications are possible within the scope of the claims set forth below and the equivalent scope interpreted therefrom.

[0024] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by those skilled in the art to which this invention pertains. Any method and material similar or equivalent to those described herein may be used in practice to test the invention, but preferred materials and methods are described herein.

[0025] In the present invention, the term “comprising” any component means that, unless specifically stated otherwise, it does not exclude other components but may include additional components.

[0027] The present invention provides a polynucleotide for predicting the prognosis of non-small cell lung cancer or a polynucleotide complementary thereto comprising a nucleotide at a specific position of SEQ ID NO. 1.

[0028] More specifically, the present invention provides a marker for the diagnosis and prognosis prediction of non-small cell lung cancer, comprising: a polynucleotide in which the 104th base of the polynucleotide of SEQ ID NO. 1 is C or T and the polynucleotide is composed of a continuous DNA sequence including said 104th base; or a polynucleotide complementary thereto.

[0029] The present invention provides a composition for diagnosing and predicting the prognosis of non-small cell lung cancer, comprising a preparation capable of detecting an SNP of the 104th base in a polynucleotide consisting of SEQ ID NO. 1.

[0030] The present invention provides a kit for diagnosing and predicting the prognosis of non-small cell lung cancer comprising the above composition.

[0031] The above kit can be used for the diagnosis and prognosis prediction of non-small cell lung cancer by identifying the RIPK1 rs17548629 C>T polymorphism site (SNP) within the 3'-UTR region of the RIPK1 gene, which is a marker for the diagnosis and prognosis prediction of non-small cell lung cancer. The above kit may include a polynucleotide, primer, or probe for identifying the RIPK1 rs17548629 C>T SNP, as well as one or more other component compositions, solutions, or devices suitable for the analysis method.

[0032] Additionally, the above kit may be a kit for the diagnosis and prognosis prediction of non-small cell lung cancer that includes essential elements necessary for performing DNA chip analysis. The DNA chip kit comprises a substrate to which a polynucleotide, primer, or probe specific to the SNP is attached, and the substrate may include a nucleic acid corresponding to a quantitative control gene or a fragment thereof.

[0033] The present invention provides a microarray for the diagnosis and prognosis prediction of non-small cell lung cancer comprising the above composition.

[0034] The above microarray may be composed of a conventional microarray except that it includes the polynucleotide of the present invention.

[0035] The present invention provides a method for diagnosing and predicting the prognosis of non-small cell lung cancer, comprising the step of identifying an SNP of the 104th base in a polynucleotide consisting of SEQ ID NO. 1 from isolated nucleic acids.

[0036] More specifically, the above method for predicting therapeutic effects or prognosis may include the step of identifying the bases of a polymorphic site of a polynucleotide containing an SNP of the 104th base in a polynucleotide consisting of SEQ ID NO. 1 in isolated nucleic acids.

[0037] The RIPK1 rs17548629 C>T of the present invention is the 3'-UTR position of RIPK1, and can change the expression level of RIPK1 by regulating the binding of miR-642a-5p.

[0038] In one embodiment of the present invention, if the genotype of the SNP at the 104th base in the polynucleotide of SEQ ID NO. 1 from the patient's nucleic acid is C, the prognosis for non-small cell lung cancer may be predicted to be poor. On the other hand, if the genotype of the SNP at the 104th base in the polynucleotide of SEQ ID NO. 1 from the patient's nucleic acid is T, the survival rate and disease-free survival rate increase, and the prognosis for non-small cell lung cancer may be predicted to be good. The nucleic acid may be obtained from samples such as tissue, cells, whole blood, serum, plasma, saliva, sputum, cerebrospinal fluid, or urine obtained from these lung cancer patients, and the nucleic acid sample includes DNA, mRNA, or cDNA synthesized from mRNA. Furthermore, the nucleic acid of the lung cancer patient may be obtained by conventional methods and separation methods such as the phenol / chloroform extraction method and the protease K treatment method, and may also be obtained by amplifying the target nucleic acid through PCR and purifying it.

[0039] Confirmation of the SNP genotype of the present invention can be performed by known methods such as sequencing analysis, sequencing analysis using an automated DNA sequencer, pyrosequencing, hybridization by microarray, PCR-RELP (restriction fragment length polymorphism), PCR-SSCP (single strand conformation polymorphism), PCR-SSO (specific sequence oligonucleotide), ASO (allele specific oligonucleotide) hybridization combining PCR-SSO and dot hybridization, TaqManPCR, MALDI-TOF / MS, RCA (rolling circle amplification), HRM (high resolution melting) method, primer extension method, Southern blot hybridization method, dot hybridization method, etc.

[0040] The results of the SNP polymorphisms of the present invention can be statistically processed using statistical analysis methods commonly used in the art, for example, by using variables such as continuous variables, categorical variables, odds ratios, and 95% confidence intervals obtained through Student's t-test, Chi-square test, linear regression line analysis, and multiple logistic regression analysis.

[0041] “RIPK1” of the present invention is an abbreviation for “Receptor-interacting protein kinase 1,” and the “RIPK1 gene” of the present invention encodes a member of the receptor-interacting protein (RIP) family of serine / threonine protein kinases, and the encoded protein plays a role in regulating inflammation and apoptosis as part of tissue damage, pathogen recognition, and developmental regulation. Diseases associated with the RIPK1 gene include Immunodeficiency 57 With Autoinflammation and Autoinflammation With Episodic Fever and Lymphadenopathy, and the activation of RIPK1 is regulated by complex ubiquitination modifications and interactions with various DD-containing proteins, including TRADD, FADD, and TNFR1, as well as itself. Furthermore, together with RIPK3, RIPK1 plays an essential role in necrosis and inflammation, which are cell necrosis pathways. Previous studies have shown that inhibiting RIPK1 kinase activity can protect against loss of cell viability caused by stressors in preclinical models, due to RIPK1's ability to regulate neuronal apoptosis. Accordingly, research is currently underway regarding the use of such RIPK1 inhibitors for the treatment of single-gene and multi-gene autoimmunities, inflammatory, neurodegenerative, ischemic, and acute conditions such as sepsis; however, there is no known application of RIPK1 polymorphisms for the diagnosis and prognosis prediction of non-small cell lung cancer. RIPK1 mutations may be associated with the risk and prognosis of various types of cancer, including lung cancer, and abnormal expression of the RIPK1 gene may be associated with resistance to chemotherapy or radiotherapy and malignant prognosis in various types of cancer.

[0042] The polymorphic region of RIPK1 used in the present invention can be indicated as “RIPK1 rs17548629 C>T”.

[0043] The polynucleotide or its complementary polynucleotide according to the present invention is a polymorphic sequence. A polymorphic sequence refers to a sequence that includes a polymorphic site exhibiting a single nucleotide polymorphism within a nucleotide sequence. A polymorphic site refers to a site within a polymorphic sequence where a single nucleotide polymorphism occurs.

[0044] The present invention confirmed that RIPK1 rs17548629 C>T is a biomarker capable of predicting the prognosis of non-small cell lung cancer in 674 patients with non-small cell lung cancer.

[0045] More specifically, the present invention confirmed that it is possible to predict the therapeutic effect or prognosis of non-small cell lung cancer (NSCLC) using RIPK1 rs17548629 C>T.

[0046] In this invention, the term “polymorphism” refers to the case where two or more alleles exist at a single gene locus, and among the polymorphic regions, a single nucleotide polymorphism (SNP) is defined as a region where only a single nucleotide differs from person to person.

[0047] In this invention, the term “genotype” refers to a specific allele of a particular gene in a sample of cells or tissues.

[0048] In the present invention, the term “allele” refers to multiple types of a single gene located at the same locus on homologous chromosomes. The said alleles can be used to express polymorphism; for example, an SNP has two types of alleles.

[0049] In this invention, the term “prognosis” refers to the course of a disease, such as lung cancer, including onset, recurrence, metastatic spread, and drug resistance, as well as lung cancer-induced death or the possibility of progression, and whether a cure is achieved.

[0050] For the purposes of the present invention, the “prognosis” may refer to the risk of recurrence, course, or survival prognosis of non-small cell lung cancer after curative resection.

[0051] In the present invention, the term “prediction” may refer to whether and / or the possibility that a patient will survive for a specific period without cancer recurrence due to said treatment, such as chemotherapy, by responding favorably or unfavorably to said treatment. In the present invention, it may refer to determining whether there is a possibility that a patient will develop lung cancer, and whether and / or the possibility that the patient will survive after treatment by responding favorably or unfavorably to said chemotherapy.

[0052] In the present invention, the terms "cancer," "tumor," or "malignant" may generally refer to a physiological condition of a mammal characterized by uncontrolled cell growth.

[0053] In the present invention, the term "marker for predicting the survival prognosis of a lung cancer patient" refers to a polymorphic marker capable of predicting the risk of developing lung cancer, whether the developed lung cancer has been cured, or its course, and preferably refers to the nucleotide described above. Furthermore, the patient may refer to a patient for determining the risk of developing lung cancer or a patient who has surgically resected lung cancer, particularly lung cancer. The patient who has surgically resected lung cancer may preferably refer to a patient who has surgically resected lung cancer such as non-small cell lung cancer, squamous cell carcinoma, adenocarcinoma, or large cell carcinoma, and more preferably, may refer to a patient who has surgically resected non-small cell lung cancer.

[0055] The present invention will be explained in more detail below through examples.

[0056] However, the following examples are intended only to clearly illustrate the technical features of the present invention, and the scope of protection of the present invention is not limited by the following examples.

[0057] In addition, the following examples were approved by the Institutional Review Boards of Kyungpook National University Hospital and Chonnam National University Hospital, and were conducted in accordance with the research protocols approved by the Institutional Review Boards of both hospitals.

[0059] <Example 1> Selection of Research Subjects

[0060] The patient group used in this study consisted of a total of 674 Korean patients, comprising 337 from Kyungpook National University Hospital and 337 from Chonnam National University Hospital. The patients were diagnosed with non-small cell lung cancer of stage 1, 2, or 2IA pathologically, and underwent curative resection at Kyungpook National University Hospital from April 2000 to June 2010 and at Chonnam National University Hospital from January 2005 to August 2012. No other chemotherapy or radiation therapy was administered prior to the surgery.

[0062] <Example 2> Discovery of SNPs Related to Non-Small Cell Lung Cancer

[0063] To select gene polymorphisms associated with non-small cell lung cancer, the patient group from Example 1 was selected as the study subjects, and the NCBI SNP database (https: / / www.ncbi.nlm.nih.gov / snp) was utilized. Using the FuncPred utility for functional SNP prediction and the TagSNP utility for selecting unbalanced tag SNPs on the SNPinfo web server (https: / / snpinfo.niehs.nih.gov / ), strong unbalanced (LD) ( Except for those with > 0.8, 15 SNPs with a non-recurrence frequency of 0.1 or higher were selected based on HapMap JPT data, and accordingly, 3 SNPs were selected from the MLKL gene, 5 from the RIPK1 gene, and 7 from the RIPK3 gene.

[0064] Subsequently, the 15 SNPs mentioned above were genotyped using the iPLEX Assay and MassARRAY system (Agena Bioscience, San Diego, California, USA).

[0065] As a result, among the 15 SNPs mentioned above, 5 SNPs (P<0.05) that were out of Hardy-Weinberg equilibrium were excluded, and 10 additional SNPs were analyzed, and among them, SNPs that showed a significant association with the survival rate of non-small cell lung cancer patients who underwent curative resection were selected.

[0067] <Example 3> Analysis of Target Gene Expression Levels of RIPK1 rs17548629 C>T

[0068] <3.1> Luciferase Activity Analysis and Confirmation of mRNA Expression Levels via Quantitative Reverse Transcription Polymerase Chain Reaction (qRT-PCR)

[0069] Luciferase analysis was performed to determine whether RIPK1 rs17548629 C>T, an SNP that showed a significant association with the survival rate of non-small cell lung cancer patients selected in Example 2, affects the expression of the RIPK1 gene by regulating the binding of miR-642a.

[0070] Synthesize RIPK1 3'-UTR sequences containing rs17548629C or rs17548629T from human genomic DNA by PCR, and psiCHECK TM psiCHECK containing rs17548629 C>T after cloning to -2 vector (Promega, Madison, WI, USA) TM-2- RIPK1 constructs were generated and co-infected H1299 and A549 cell lines with miR-642a-5p. Cells were obtained 48 hours after infection, and their lysates were prepared using the Dual-Luciferase® Reporter Assay System (Promega). Luciferase activity was measured using a Synergy HTX Multi-Mode Microplate Reader (BioTek Instruments, Winooski, VT, USA). The Luciferase activity was normalized to pRL-SV40 Renila Luciferase activity.

[0071] As shown in Figure 2, Renila Luciferase activity was significantly increased in the RIPK1 rs17548629 T allele compared to the RIPK1 rs17548629 C allele, confirming that rs17548629 C>T in the 3'-UTR of RIPK1 regulates the binding of miR-642a and reduces RIPK1 expression.

[0073] <3.2> Genotype Analysis Using TaqMan

[0074] The genotype of RIPK1 rs17548629 C>T was analyzed using TaqMan analysis (Thermo Fisher Scientific, Foster City, CA, USA) for 253 patients with RIPK1 mRNA expression data determined by qRT-PCR.

[0075] Through this, as shown in Figure 3, it was confirmed that the mRNA expression level of RIPK1 has a significant positive correlation with the C-to-T change of RIPK1 rs17548629 (Ptrend = 5x10⁻⁵ and 0.01, respectively). In addition, subgroup analysis confirmed that the association between genotype and expression level is significant in adenocarcinoma (Ptrend = 2x10⁻⁵ and 0.002, respectively).

Claims

Claim 1 A marker composition for the diagnosis and prognosis prediction of a patient with non-small cell lung cancer (NSCLC) who has undergone curative resection, comprising a sequence of nucleotides including the 104th nucleotide of the rs17548629 polynucleotide of SEQ ID NO. 1, which constitutes a part of the RIPK1 gene. Claim 2 A marker composition for the diagnosis and prognosis prediction of a non-small cell lung cancer (NSCLC) patient who has undergone curative resection, wherein, in claim 1, the continuous base is 1 to 100 continuous bases. Claim 3 A composition for the diagnosis and prognosis prediction of a patient with non-small cell lung cancer (NSCLC) who has undergone curative resection, comprising a preparation capable of detecting an SNP of the 104th base in a polynucleotide consisting of SEQ ID NO.

1. Claim 4 A composition for the diagnosis and prognosis prediction of a non-small cell lung cancer (NSCLC) patient who has undergone curative resection, wherein, in claim 3, the preparation capable of detecting the SNP is a primer capable of amplifying a polynucleotide composed of 1 to 100 consecutive bases including an SNP of the 104th base in the polynucleotide of SEQ ID NO. 1, or a polynucleotide complementary thereof. Claim 5 A composition for the diagnosis and prognosis prediction of a non-small cell lung cancer (NSCLC) patient who has undergone curative resection, wherein, in paragraph 4, the non-small cell lung cancer (NSCLC) is lung adenocarcinoma. Claim 6 delete Claim 7 A microarray for the diagnosis and prognosis prediction of a non-small cell lung cancer (NSCLC) patient who has undergone curative resection, comprising a polynucleotide according to claim 1 or 2, a polypeptide encoded by the same, or its cDNA. Claim 8 A kit for the diagnosis and prognosis prediction of non-small cell lung cancer (NSCLC) patients who have undergone curative resection, comprising the microarray of claim 7. Claim 9 A method for providing information necessary for the diagnosis and prognosis prediction of non-small cell lung cancer (NSCLC) after curative resection, comprising the step of identifying the 104th base type of the rs17548629 polynucleotide of SEQ ID NO. 1, which constitutes a part of the RIPK1 gene, from an isolated nucleic acid sample. Claim 10 A method for providing information necessary for the diagnosis and prognosis prediction of non-small cell lung cancer (NSCLC) after curative resection, wherein, in claim 9, if the base at the SNP position corresponding to the 104th nucleotide of SEQ ID NO. 1 is identified as T, the prognosis of non-small cell lung cancer (NSCLC) after curative resection is predicted to be superior compared to the C base of the alternative allele. Claim 11 A method for providing information necessary for the diagnosis and prognosis prediction of non-small cell lung cancer (NSCLC) after curative resection, wherein, in claim 9, the non-small cell lung cancer (NSCLC) is lung adenocarcinoma.

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