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Polymorphisms of HIF1A gene are associated with prognosis of early stage non-small-cell lung cancer patients after surgery.

ABSTRACT: Hypoxia-inducible factor 1α (HIF1α) activates the transcription of genes that are involved in angiogenesis and cell survival. Over-expression of HIF1α caused by intratumoral hypoxia and its genetic alterations are associated with increased mortality in several cancer types including non-small-cell lung cancer (NSCLC). The aim of this study was to investigate the predictive role of single nucleotide polymorphisms (SNPs) in HIF1A gene in NSCLC outcomes. We genotyped two functional SNPs (rs2057482 and rs2301113) in HIF1A gene and assessed their associations with clinicopathological parameters and prognosis of 494 NSCLC patients by Cox proportional hazard model. There was no significant association between the SNPs and clinical outcomes of NSCLC for overall analysis. However, in stratified analysis for NSCLC patients at early stage (I/II), we observed a protective effect conferred by variant genotype of rs2057482 on overall survival (OS) (HR 0.42, 95% CI 0.22-0.80) and recurrence-free survival (RFS) (HR 0.60, 95 % CI 0.36-0.97) in a dominant model. Additionally, multivariate Cox analysis based on dominant model indicated that significant increased death and recurrence risks were observed in patients with early T-stage (T1 and T2) tumors, who carrying variant-containing genotype of rs2301113, as well as in patients without lymph node involvement (N0 stage) for rs2057482. Genetic variations on HIF1A gene are significantly associated with NSCLC outcomes in patients with early stage disease.

SUBMITTER: Liu B

PROVIDER: S-EPMC3971443 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Genetic polymorphisms in glycolytic pathway are associated with the prognosis of patients with early stage non-small cell lung cancer.

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Project description: Not available

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Association between polymorphisms in microRNA target sites and survival in early-stage non-small cell lung cancer.

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| S-EPMC3387223 | biostudies-literature

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Project description:BackgroundEarly-stage non-small cell lung carcinoma (NSCLC) accounts for more than 80% of lung cancer, which is a kind of cancer with high heterogeneity, so the genetic heterogeneity and molecular subtype should be explored.MethodsPartitioning Around Medoid algorithm was used to acquire the molecular subtype for early-stage NSCLC based on prognosis-related mRNAs and methylation sites. Random forest (RF) and support vector machine (SVM) were used to build prediction models for subtypes.ResultsSix prognosis-related subtypes for early-stage NSCLC, including 4 subtypes for lung squamous cell carcinoma (LUSC) and 2 subtypes for lung adenocarcinoma (LUAD), were identified. There were highly expressed and hypermethylated gene regions for LUSC-C1 and LUAD-C2, highly expressed region for LUAD-C1, and hypermethylated regions for LUSC-C3 and LUSC-C4. Molecular subtypes for LUSC were mainly determined by DNA methylation (14 mRNAs and 362 methylation sites). Molecular subtypes for LUAD were determined by both mRNA and DNA methylation information (143 mRNAs and 458 methylation sites). Ten methylation sites were selected as biomarkers for prediction of LUSC-C1 and LUSC-C3, respectively. Nine genes and 1 methylation site were selected as biomarkers for LUAD subtype prediction. These subtypes can be predicted by the selected biomarkers with RF and SVM models.ConclusionsIn conclusion, we proposed a prognosis-related molecular subtype for early-stage NSCLC, which can provide important information for personalized therapy of patients.

| S-EPMC7866742 | biostudies-literature

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