Dataset Information

Genetic variation in the PNPLA3 gene and hepatocellular carcinoma in USA: risk and prognosis prediction.

ABSTRACT: Nonalcoholic fatty liver disease (NAFLD) is an emerging epidemic with high prevalence in Western countries. Genome-wide association studies had reported that a variation in the patatin-like phospholipase domain containing 3 (PNPLA3) gene is associated with high susceptibility to NAFLD. However, the relationship between this variation and hepatocellular carcinoma (HCC) has not been well established. We investigated the impact of PNPLA3 genetic variation (rs738409: C>G) on HCC risk and prognosis in the United States by conducting a case-control study that included 257 newly diagnosed and pathologically confirmed Caucasian patients with HCC (cases) and 494 healthy controls. Multivariate logistics and Cox regression models were used to control for the confounding effects of HCC risk and prognostic factors. We observed higher risk of HCC for subjects with a homozygous GG genotype than for those with CC or CG genotypes, the adjusted odds ratio (OR) was 3.21 (95% confidence interval [CI], 1.68-6.41). We observed risk modification among individuals with diabetes mellitus (OR = 19.11; 95% CI, 5.13-71.20). The PNPLA3 GG genotype was significantly associated with underlying cirrhosis in HCC patients (OR = 2.48; 95% CI, 1.05-5.87). Moreover, GG allele represents an independent risk factor for death. The adjusted hazard ratio of the GG genotype was 2.11 (95% CI, 1.26-3.52) compared with CC and CG genotypes. PNPLA3 genetic variation (rs738409: C>G) may determine individual susceptibility to HCC development and poor prognosis. Further experimental investigations are necessary for thorough assessment of the hepatocarcinogenic role of PNPLA3.

SUBMITTER: Hassan MM

PROVIDER: S-EPMC3808509 | biostudies-literature | 2013 Nov

REPOSITORIES: biostudies-literature

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Genetic variation in the PNPLA3 gene and hepatocellular carcinoma in USA: risk and prognosis prediction.

Hassan Manal M MM Kaseb Ahmed A Etzel Carol J CJ El-Serag Hashem H Spitz Margaret R MR Chang Ping P Hale Katherine S KS Liu Mei M Rashid Asif A Shama Mohamed M Abbruzzese James L JL Loyer Evelyne M EM Kaur Harmeet H Hassabo Hesham M HM Vauthey Jean-Nicolas JN Wray Curtis J CJ Hassan Basmah S BS Patt Yehuda Z YZ Hawk Ernest E Soliman Khalid M KM Li Donghui D

Molecular carcinogenesis 20130615

Nonalcoholic fatty liver disease (NAFLD) is an emerging epidemic with high prevalence in Western countries. Genome-wide association studies had reported that a variation in the patatin-like phospholipase domain containing 3 (PNPLA3) gene is associated with high susceptibility to NAFLD. However, the relationship between this variation and hepatocellular carcinoma (HCC) has not been well established. We investigated the impact of PNPLA3 genetic variation (rs738409: C>G) on HCC risk and prognosis i ...[more]

PMID: 23776098

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Project description:Background:The prognosis of hepatocellular carcinoma (HCC) patients remains poor. Identifying prognostic markers to stratify HCC patients might help to improve their outcomes. Methods:Six 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. Results:A 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. Conclusions:We 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:Hepatocellular carcinoma (HCC), the most frequently occurring type of cancer, is strongly associated with metabolic disorders. In this study, we aimed to characterize the metabolic features of HCC and normal tissue adjacent to the tumor (NAT). By using samples from The Cancer Genome Atlas (TCGA) liver cancer cohort and comparing 85 well-defined metabolic pathways obtained from the Kyoto Encyclopedia of Genes and Genomes (KEGG), 70 and 7 pathways were found to be significantly downregulated and upregulated, respectively, in HCC, revealing that tumor tissue lacks the ability to maintain normal metabolic levels. Through unsupervised hierarchical clustering of metabolic pathways, we found that metabolic heterogeneity correlated with prognosis in HCC samples. Thus, using the least absolute shrinkage and selection operator (LASSO) and filtering independent prognostic genes by the Cox proportional hazards model, a six-gene-based metabolic score model was constructed to enable HCC classification. This model showed that high expression of LDHA and CHAC2 was associated with an unfavorable prognosis but that high ADPGK, GOT2, MTHFS, and FTCD expression was associated with a favorable prognosis. Patients with higher metabolic scores had poor prognoses (p value = 2.19e-11, hazard ratio = 3.767, 95% CI = 2.555-5.555). By associating the score level with clinical features and genomic alterations, it was found that NAT had the lowest metabolic score and HCC with tumor stage III/IV the highest. qRT‒PCR results for HCC patients also revealed that tumor samples had higher score levels than NAT. Regarding genetic alterations, patients with higher metabolic scores had more TP53 gene mutations than those with lower metabolic scores (p value = 8.383e-05). Validation of this metabolic score model was performed using another two independent HCC cohorts from the Gene Expression Omnibus (GEO) repository and other TCGA datasets and achieved good performance, suggesting that this model may be used as a reliable tool for predicting the prognosis of HCC patients.

Dataset Information

Genetic variation in the PNPLA3 gene and hepatocellular carcinoma in USA: risk and prognosis prediction.

Publications

Genetic variation in the PNPLA3 gene and hepatocellular carcinoma in USA: risk and prognosis prediction.

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