Dataset Information

Association of twelve polymorphisms in three onco-lncRNA genes with hepatocellular cancer risk and prognosis: A case-control study.

ABSTRACT:

Aim

To evaluate the association of 12 tag single nucleotide polymorphisms (tagSNPs) in three onco-long non-coding RNA (lncRNA) genes (HOTTIP, CCAT2, MALAT1) with the risk and prognosis of hepatocellular cancer (HCC).

Methods

Twelve tagSNPs covering the three onco-lncRNAs were genotyped by the KASP method in a total of 1338 samples, including 521 HCC patients and frequency-matched 817 controls. The samples were obtained from an unrelated Chinese population at the First Hospital of China Medical University from 2012-2015. The expression quantitative trait loci (eQTL) analyses were conducted to explore further the potential function of the promising SNPs.

Results

Three SNPs in HOTTIP, one promoter SNP in MALAT1, and one haplotype of HOTTIP were associated with HCC risk. The HOTTIP rs17501292, rs2067087, and rs17427960 SNPs were increased to 1.55-, 1.20-, and 1.18-fold HCC risk under allelic models (P = 0.012, 0.017 and 0.049, respectively). MALAT1 rs4102217 SNP was increased to a 1.32-fold HCC risk under dominant models (P = 0.028). In addition, the two-way interaction of HOTTIP rs17501292-MALAT1 rs619586 polymorphisms showed a decreased effect on HCC risk (P_interaction = 0.028, OR = 0.30) and epistasis with each other. HOTTIP rs3807598 variant genotype showed significantly longer survival time in HBV negative subgroup (P = 0.049, HR = 0.12), and MALAT1 rs591291 showed significantly better prognosis in female and HBV negative subgroups (P = 0.022, HR = 0.37; P = 0.042, HR = 0.25, respectively). In the study, no significant effect was observed in eQTL analysis.

Conclusion

Specific lncRNA (HOTTIP and MALAT1) SNPs have potential to be biomarkers for HCC risk and prognosis.

SUBMITTER: Wang BG

PROVIDER: S-EPMC6010940 | biostudies-literature | 2018 Jun

REPOSITORIES: biostudies-literature

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Publications

Association of twelve polymorphisms in three onco-lncRNA genes with hepatocellular cancer risk and prognosis: A case-control study.

Wang Ben-Gang BG Xu Qian Q Lv Zhi Z Fang Xin-Xin XX Ding Han-Xi HX Wen Jing J Yuan Yuan Y

World journal of gastroenterology 20180601 23

<h4>Aim</h4>To evaluate the association of 12 tag single nucleotide polymorphisms (tagSNPs) in three onco-long non-coding RNA (lncRNA) genes (<i>HOTTIP</i>, <i>CCAT2</i>, <i>MALAT1</i>) with the risk and prognosis of hepatocellular cancer (HCC).<h4>Methods</h4>Twelve tagSNPs covering the three onco-lncRNAs were genotyped by the KASP method in a total of 1338 samples, including 521 HCC patients and frequency-matched 817 controls. The samples were obtained from an unrelated Chinese population at t ...[more]

PMID: 29930469

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Project description:BackgroundThe prognosis of hepatocellular carcinoma (HCC) patients remains poor. Identifying prognostic markers to stratify HCC patients might help to improve their outcomes.MethodsSix gene expression profiles (GSE121248, GSE84402, GSE65372, GSE51401, GSE45267 and GSE14520) were obtained for differentially expressed genes (DEGs) analysis between HCC tissues and non-tumor tissues. To identify the prognostic genes and establish risk score model, univariable Cox regression survival analysis and Lasso-penalized Cox regression analysis were performed based on the integrated DEGs by robust rank aggregation method. Then Kaplan-Meier and time-dependent receiver operating characteristic (ROC) curves were generated to validate the prognostic performance of risk score in training datasets and validation datasets. Multivariable Cox regression analysis was used to identify independent prognostic factors in liver cancer. A prognostic nomogram was constructed based on The Cancer Genome Atlas (TCGA) dataset. Finally, the correlation between DNA methylation and prognosis-related genes was analyzed.ResultsA twelve-gene signature including SPP1, KIF20A, HMMR, TPX2, LAPTM4B, TTK, MAGEA6, ANX10, LECT2, CYP2C9, RDH16 and LCAT was identified, and risk score was calculated by corresponding coefficients. The risk score model showed a strong diagnosis performance to distinguish HCC from normal samples. The HCC patients were stratified into high-risk and low-risk group based on the cutoff value of risk score. The Kaplan-Meier survival curves revealed significantly favorable overall survival in groups with lower risk score (P < 0.0001). Time-dependent ROC analysis showed well prognostic performance of the twelve-gene signature, which was comparable or superior to AJCC stage at predicting 1-, 3-, and 5-year overall survival. In addition, the twelve-gene signature was independent with other clinical factors and performed better in predicting overall survival after combining with age and AJCC stage by nomogram. Moreover, most of the prognostic twelve genes were negatively correlated with DNA methylation in HCC tissues, which SPP1 and LCAT were identified as the DNA methylation-driven genes.ConclusionsWe identified a twelve-gene signature as a robust marker with great potential for clinical application in risk stratification and overall survival prediction in HCC patients.

Project description:Background: Coronary artery disease (CAD) is one of the main fatal diseases all over the world. CAD is a complex disease, which has multiple risk factors mechanisms. In recent years, genome-wide association study (GWAS) had revealed single nucleotide polymorphism genes (SNPs) which were closely related with CAD risks. The relationship between long non-coding RNA (lncRNA) MALAT1 (metastasis-associated lung adenocarcinoma transcript 1) and CAD risk is largely unknown. To our knowledge, this is the first study which demonstrated the interaction effects of SNP-SNP and SNP-environment with CAD risk. In general, our case-control study is to detect the association between MALAT1 (rs619586, rs4102217) SNPs and CAD risk. Methods: Three hundred and sixty-five CAD patients and three hundred and eighty-four matched control participants blood samples were collected in Liaoning province, China. Two polymorphisms (rs619586, rs4102217) in lncRNA MALAT1 were genotyped by KASP platform. Results: In a stratified analysis, we found that non-drinkers with GC genotype and the recessive model of rs4102217 had higher CAD risk (P=0.010, odds ratio (OR): 1.96, 95% confidence interval (CI) = 1.17-3.28; P=0.026, OR: 1.73, 95% CI = 1.07-2.79) and diabetes mellitus (DM) history group (P=0.010, OR: 4.07, 95% CI = 1.41-11.81; P=0.019, OR: 3.29, 95% CI = 1.22-8.88). In SNP-SNP interactions analysis between MALAT1 and CAD risk, we found rs4102217 had an increase in smokers (GG: OR: 2.04, 95% CI = 1.42-2.92; CC+GC: OR: 2.64, 95% CI = 1.64-4.26) and a decrease in drinkers (CC+GC: OR: 0.33, 95% CI = 0.20-0.55). Smokers with MALAT1 rs619586 AA genotype (OR: 2.20, 95% CI = 1.57-3.07) and GG+AG genotype (OR: 2.11, 95% CI = 1.17-3.81) had a higher risk of CAD. Moreover, drinkers with AA genotype (OR: 0.22, 95% CI = 0.10-0.48) and GG+AG genotype (OR: 0.38, 95% CI = 0.22-0.65) had a lower risk of CAD. According to the MDR software, MALAT1 rs4102217 polymorphism-smoking-drinking was the best interaction model, which has higher risk of CAD (Testing Bal.ACC. = 0.6979). Conclusion: Our study demonstrated that the GC genotype and the recessive model of rs4102217 potentially increased CAD risk in some specific group.

Dataset Information

Association of twelve polymorphisms in three onco-lncRNA genes with hepatocellular cancer risk and prognosis: A case-control study.

Aim

Methods

Results

Conclusion

Publications

Association of twelve polymorphisms in three onco-lncRNA genes with hepatocellular cancer risk and prognosis: A case-control study.

Similar Datasets

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