Genetic polymorphisms in apoptosis-related genes and the prognosis of hepatocellular carcinoma.
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ABSTRACT:
SUBMITTER: Yu GP
PROVIDER: S-EPMC4656746 | biostudies-literature | 2015
REPOSITORIES: biostudies-literature
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Project description:Recent studies have shown that the high incidence and low cure rate of hepatocellular carcinoma (HCC) have not improved significantly. Surgery and liver transplantation are the mainstays of prolonging the survival of HCC patients. However, the surgical resection rate of HCC patients is very low, and even after radical surgical resection, the recurrence rate at 5 years postoperatively remains high and the prognosis is very poor, so more treatment options are urgently needed. Increasing evidence suggests that cellular senescence is not only related to cancer development but may also be one of its primary driving factors. We aimed to establish a prognostic signature of senescence-associated genes to predict the prognosis and therapeutic response of HCC patients. The aim of this study was to develop a risk model associated with cellular senescence and to search for potential strategies to treat HCC. We divided HCC patients into two clusters and identified differentially expressed genes (DEGs) between clusters. In this study, low-risk patients had a better prognosis, higher levels of immune cell infiltration, and better efficacy to fluorouracil, Paclitaxel and Cytarabine chemotherapy compared to high-risk patients. To further identify potential biomarkers for HCC, we further validated the expression levels of the four signature genes in HCC and neighbouring normal tissues by in vitro experiments. In conclusion, we identified and constructed a relevant prognostic signature, which performed well in predicting the survival and treatment response of HCC patients. This helps to differentiate between low-score and high-risk HCC, and the results may contribute to precise treatment protocols in clinical practice.
| S-EPMC10585749 | biostudies-literature
Project description:BackgroundHepatocellular carcinoma (HCC) is closely associated with the immune microenvironment. To identify the effective population before administering treatment, the establishment of prognostic immune biomarkers is crucial for early HCC diagnosis and treatment.ResultsA total of 335 IRGs identified from 788 overlapping IRGs were associated with the survival of HCC. A prognostic immunoscore model was identified. The Kaplan-Meier survival curves and time-dependent ROC analysis revealed a powerful prognostic performance of immunoscore signature via multi validation. Besides, the immunoscore signature exhibited a better predictive power compared to other prognostic signatures. Gene set enrichment analysis showed multiple signaling differences between the high and low immunoscore group. Furthermore, immunoscore was significantly associated with multiple immune cells and immune infiltration in the tumor microenvironment.ConclusionsWe identified the immunoscore as a robust marker for predicting HCC patient survival.MethodsThree sets of immune-related genes (IRGs) were integrated to identify the overlapping IRGs. Weighted gene co-expression network analysis was performed to obtain the survival-related IRGs. Further, the prognostic immunoscore model was constructed via LASSO-penalized Cox regression analysis. Then the prognostic performance of immunoscore was evaluated. In addition, ESTIMATE and CIBERSORT algorithms were applied to explore the relationship between immunoscore and tumor immune microenvironment.
| S-EPMC7834986 | biostudies-literature
Project description:The aim of our study was to determine the impact of genetic polymorphisms in the caspase (CASP) genes on prognosis of hepatocellular carcinoma (HCC). We genotyped 7 potentially functional polymorphisms in CASP3, CASP7, CASP8, CASP9, CASP10 genes in 362 HCC patients of receiving surgical resection of HCC tumor. The associations of genotype and haplotype with overall survival (OS) and disease free survival (DFS) were analyzed by using the Cox proportional hazards model. We found that the CASP9 rs4645981 C allele was significantly associated with positive effect on DFS (P = 0.011 and 0.016 for CT+CC vs. TT in univariate and multivariate analysis, respectively), CT genotype was associated with a better OS of HCC than the TT genotype both in univariate and multivariate analysis (P = 0.048 and 0.041, respectively). Moreover, the CASP3 rs2705897 GT genotype showed marginally significant association with decreased OS and DFS, compared with the GG genotype. One haplotype TT/TG in CASP3 (constructed by rs12108497 T>C and rs2705897 T>G) was significantly associated with decreased OS and DFS, compared to the common haplotype TT/TT both in univariate analysis (P = 0.021 and 0.026, respectively) and multivariate analysis (P = 0.025 and 0.030, respectively). The haplotype GT/GT in CASP9 (constructed by rs4645978 A>G and rs4645981 C>T) was significantly associated with decreased DFS both in univariate and multivariate analysis (P = 0.012 and 0.010, respectively). In conclusion, the CASP9 rs4645981 polymorphism, CASP3 and CASP9 haplotypes may be useful prognosis markers for HCC patients with surgical resection of tumor.
| S-EPMC5409165 | biostudies-literature
Project description:Predicting the prognosis of hepatocellular carcinoma (HCC) is a major medical challenge and of guiding significance for treatment. This study explored the actual relevance of RNA expression in predicting HCC prognosis. Cox's multiple regression was used to establish a risk score staging classification and to predict the HCC patients' prognosis on the basis of data in the Cancer Genome Atlas (TCGA). We screened seven gene biomarkers related to the prognosis of HCC from the perspective of oxidative stress, including Alpha-Enolase 1(ENO1), N-myc downstream-regulated gene 1 (NDRG1), nucleophosmin (NPM1), metallothionein-3, H2A histone family member X, Thioredoxin reductase 1 (TXNRD1) and interleukin 33 (IL-33). Among them we measured the expression of ENO1, NGDP1, NPM1, TXNRD1 and IL-33 to investigate the reliability of the multi-index prediction. The first four markers' expressions increased successively in the paracellular tissues, the hepatocellular carcinoma samples (from patients with better prognosis) and the hepatocellular carcinoma samples (from patients with poor prognosis), while IL-33 showed the opposite trend. The seven genes increased the sensitivity and specificity of the predictive model, resulting in a significant increase in overall confidence. Compared with the patients with higher-risk scores, the survival rates with lower-risk scores are significantly increased. Risk score is more accurate in predicting the prognosis HCC patients than other clinical factors. In conclusion, we use the Cox regression model to identify seven oxidative stress-related genes, investigate the reliability of the multi-index prediction, and develop a risk staging model for predicting the prognosis of HCC patients and guiding precise treatment strategy.
| S-EPMC10781471 | biostudies-literature
Project description:BackgroundDysregulation of the balance between proliferation and apoptosis is the basis for human hepatocarcinogenesis. In many malignant tumors, such as hepatocellular carcinoma (HCC), there is a correlation between apoptotic dysregulation and poor prognosis. However, the prognostic values of apoptosis-related genes (ARGs) in HCC have not been elucidated.MethodsTo screen for differentially expressed ARGs, the expression levels of 161 ARGs from The Cancer Genome Atlas (TCGA) database ( https://cancergenome.nih.gov/ ) were analyzed. Gene Ontology (GO) enrichment and the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses were performed to evaluate the underlying molecular mechanisms of differentially expressed ARGs in HCC. The prognostic values of ARGs were established using Cox regression, and subsequently, a prognostic risk model for scoring patients was developed. Kaplan-Meier (K-M) and receiver operating characteristic (ROC) curves were plotted to determine the prognostic value of the model.ResultsCompared with normal tissues, 43 highly upregulated and 8 downregulated ARGs in HCC tissues were screened. GO analysis results revealed that these 51 genes are indeed related to the apoptosis function. KEGG analysis revealed that these 51 genes were correlated with MAPK, P53, TNF, and PI3K-AKT signaling pathways, while Cox regression revealed that 5 ARGs (PPP2R5B, SQSTM1, TOP2A, BMF, and LGALS3) were associated with prognosis and were, therefore, obtained to develop the prognostic model. Based on the median risk scores, patients were categorized into high-risk and low-risk groups. Patients in the low-risk groups exhibited significantly elevated 2-year or 5-year survival probabilities (p < 0.0001). The risk model had a better clinical potency than the other clinical characteristics, with the area under the ROC curve (AUC = 0.741). The prognosis of HCC patients was established from a plotted nomogram.ConclusionBased on the differential expression of ARGs, we established a novel risk model for predicting HCC prognosis. This model can also be used to inform the individualized treatment of HCC patients.
| S-EPMC7955636 | biostudies-literature
Project description:Circadian dysregulation can be involved in the development of malignant tumors, though its relationship with the progression of hepatocellular carcinoma is not yet fully understood. We identified genes related to circadian rhythms from the Cancer Genome Atlas (TCGA), measured gene expression, and conducted genomic difference analysis to construct a circadian rhythm-related signature. The resulting prognosis model proved to be an effective biomarker, as demonstrated by Kaplan-Meier survival analysis for both the training (n = 370, P = 2.687e-10) and external validation cohorts (n = 230, P = 1.45e-02). Further, we found that patients considered ‘high risk’, with an associated poor prognosis, displayed elevated levels of immune checkpoint genes and immune filtration. We also conducted functional enrichment, which indicated that the risk model showed a significant positive correlation with certain malignant phenotypes, including G2M checkpoint, MYC targets, and the MTORC1 signaling pathway. In summary, we identified a novel circadian rhythm-related signature allowing assessment of prognosis for hepatocellular carcinoma patients, and further can be used to predict immune infiltration sensitivity.
| S-EPMC9691441 | biostudies-literature
Project description:CD35, an important molecule implicated in inflammation and immunity, is reportedly associated with several cancers. However, very few studies have investigated the relationship between CD35 polymorphisms and hepatocellular carcinoma (HCC). The current study was conducted to investigate the association between tag SNPs in CD35 and HCC susceptibility and postoperative recurrence, in an attempt to elucidate the gene-environment interactions in HCC. A total of 1233 Chinese Han people, including 647 healthy controls and 586 HCC cases, were sampled in this study. Six Tag SNPs (rs10494885, rs2296160, rs3737002, rs3849266, rs669117, and rs7525160) of CD35 were selected using the HaploView 4.2 program and genotyped by matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-TOF-MS). Overall, the mutation genotypes CC/CG of CD35 rs7525160 significantly increased the risk of HCC. Stratification analysis indicated that CD35 rs7525160 CC/CG genotypes increased HCC risk in patients younger than 65 years and were closely related to the pathological type of poor prognosis of HCC. Cox proportional hazard ratio model analysis revealed that the rs7525160 CC/CG genotype remains a significant independent risk factor for postoperative recurrence of HCC. In conclusion, CD35 rs7525160 polymorphism may contribute to the susceptibility and prognosis of HCC in the Chinese Han population.
| S-EPMC8374953 | biostudies-literature
Project description:BackgroundDysregulation of autophagy is important in the pathogenesis of many diseases, including cancer. Several aspects of the biological role of autophagy are however still unclear and the relationship between apoptosis and autophagy, particularly in the liver has yet to be thoroughly explored. In this study we evaluated the expression of Beclin 1 (one of the main autophagocytic agents, which bridges autophagy, apoptosis and both differentiation), and both pro- (Bad, Bax) and anti-apoptotic (Bcl-2, Bcl-xL) factors in liver samples from patients with different stages of liver disease.MethodsThe study concerned 93 patients from 49 cases of chronic hepatitis (CH) (30 HCV and 19 HBV-related), 13 of cirrhosis (CIRR) (10 HCV and 3 HBV-related), 21 of hepatocellular carcinoma (both HCC and peritumoral tissues [PHCC]), and 10 controls (CONTR). Real-time PCR and Western blotting were used to measure mRNA and protein expression levels.ResultsBeclin 1 mRNA levels were lower in HCC than in CH (P = 0.010) or CIRR (P = 0.011), and so were the Bcl-xL transcripts (P < 0.0001). Bad mRNA levels were higher in CH and CIRR than in CONTR, while Bax transcripts were increased in all tissues (P = 0.036). PHCC expressed the highest Bcl-2 mRNA levels. HBV-related CH tissues showed significantly higher Bcl-xL and Bad mRNA levels than HCV-related CH (P = 0.003 and P = 0.016, respectively).ConclusionsHigh Beclin 1, Bcl-xL and Bad levels in CH and CIRR tissues suggest an interaction between autophagy and apoptosis in the early and intermediate stages of viral hepatitis. In HCC these processes seem to be downregulated, probably enabling the survival and growth of neoplastic hepatocytes.
| S-EPMC3449193 | biostudies-literature
Project description:Hepatocellular carcinoma (HCC) is one of the main causes of cancer deaths globally. Immunotherapy is becoming increasingly important in the cure of advanced HCC. Thus it is essential to identify biomarkers for treatment response and prognosis prediction. We searched publicly available databases and retrieved 465 samples of genes from The Cancer Genome Atlas (TCGA) database and 115 tumor samples from Gene Expression Omnibus (GEO). Meanwhile, we used the ImmPort database to determine the immune-related genes as well. Weighted gene correlation network analysis, Cox regression analysis and least absolute shrinkage and selection operator (LASSO) analysis were used to identify the key immune related genes (IRGs) which are closely related to prognosis. Gene set enrichment analysis (GSEA) was implemented to explore the difference of Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway between Immune high- and low-risk score groups. Finally, we made a prognostic nomogram including Immune-Risk score and other clinicopathologic factors. A total of 318 genes from prognosis related modules were identified through weighted gene co-expression network analysis (WGCNA). 46 genes were strongly linked to prognosis after univariate Cox analysis. We constructed a seven genes prognostic signature which showed powerful prediction ability in both training cohort and testing cohort. 16 significant KEGG pathways were identified between high- and low- risk score groups using GSEA analysis. This study identified and verified seven immune-related prognostic biomarkers for the patients with HCC, which have potential value for immune modulatory and therapeutic targets.
| S-EPMC8139963 | biostudies-literature
Project description:BackgroundUnderstanding the interplay between disulfidptosis, ferroptosis, and hepatocellular carcinoma (HCC) could provide valuable insights into the pathogenesis of HCC and potentially identify novel therapeutic targets for the treatment of this deadly disease. This study aimed to identify a prognostic signature for HCC by examining the differential expression of genes related to disulfidptosis and ferroptosis (DRG-FRG), and to assess its clinical applicability.MethodsBy integrating 23 disulfidptosis and 259 ferroptosis related genes with HCC messenger RNA (mRNA) expression data from The Cancer Genome Atlas (TCGA), differentially expressed DRG-FRG genes were identified. From these, 11 DRG-FRG genes were selected to construct a risk signature model using least absolute shrinkage and selection operator regression analyses. The prognostic performance of this model was evaluated by Kaplan-Meier survival analysis and time-dependent receiver operating characteristic (ROC) analysis. Subsequently, a nomogram was built by combining the signature with clinical variables. To further delve into the underlying mechanisms, we performed bioinformatics analysis using a variety of databases.ResultsA prognostic signature based on 11 DRG-FRG genes effectively categorized HCC patients into high- and low-risk groups, showing a significant survival difference. Even after considering clinical variables, this signature remained an independent prognostic factor. Furthermore, the signature played a role in various critical biological processes and pathways that drive HCC progression. Potential therapeutic benefits could be derived from small molecule drugs targeting NQO1 and SLC7A11. Interestingly, the high-risk group exhibited resistance to several chemotherapeutic drugs, yet showed sensitivity to others when contrasted with the low-risk group. Lastly, the DRG-FRG genes signature had a strong correlation with the tumor immune microenvironment, marked by an elevated expression of immune checkpoint molecules in the high-risk group.ConclusionsThe signature based on 11 DRG-FRG genes stands out as a promising prognostic biomarker for HCC. Beyond its predictive value, it sheds light on the intricate crosstalk between DRG-FRG genes and HCC. Importantly, these findings could pave the way for enhanced prognostic prediction, informed treatment decisions, and the advancement of immunotherapy for HCC patients.
| S-EPMC10928605 | biostudies-literature