8DEstablishment and validation of a hypoxia-related signature predicting prognosis in hepatocellular carcinoma.
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ABSTRACT:
SUBMITTER: Cai C
PROVIDER: S-EPMC8667367 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Hepatocellular carcinoma (HCC) has emerged as a primary health problem and threat to global mortality, especially in China. Since pyroptosis as a new field for HCC prognosis is not well studied, it is important to open a specific prognostic model. In this study, consensus clustering method for 42 pyroptosis-related genes to classify 374 HCC patients in the TCGA database. After cox regression analysis of the differentially expressed genes between the two clusters, LASSO-Cox analysis was then performed to construct a pyroptosis-related prognostic model with 11 genes including MMP1, KPNA2, LPCAT1, NEIL3, CDCA8, SLC2A1, PSRC1, CBX2, HAVCR1, G6PD, MEX3A. The ICGC dataset was served as the validation cohort. Patients in the high-risk group had significantly lower overall survival (OS) rates than those in the low-risk group (p < 0.05). COX regression analysis showed that our model could be used as an independent prognostic factor to predict prognosis of patients and was significantly correlated with clinicopathological characteristics. Nomogram showing the stability of the model predicting the 1, 3, 5 year survival probability of patients. In addition, based on the risk model, ssGSEA analysis revealed significant differences in the level of immune cell infiltration and activation of immune-related functional pathways between high and low-risk groups, and patients with the high-risk score may benefit more from treatment with immune checkpoint inhibitors. Furthermore, patients in the high-risk group were more tend to develop chemoresistance. Overall, we identified a novel pyroptosis-related risk signature for prognosis prediction in HCC patients and revealed the overall immune response intensity of the tumor microenvironment. All these findings make the pyroptosis signature shed light upon a latent therapeutic strategy aimed at the treatment and prevention of cancers.
| S-EPMC8818951 | biostudies-literature
Project description:BackgroundHypoxia and angiogenesis, as prominent characteristics of malignant tumors, are implicated in the progression of hepatocellular carcinoma (HCC). However, the role of hypoxia in the angiogenesis of liver cancer is unclear. Therefore, we explored the regulatory mechanisms of hypoxia-related angiogenic genes (HRAGs) and the relationship between these genes and the prognosis of HCC.MethodsThe transcriptomic and clinical data of HCC samples were downloaded from public datasets, followed by identification of hypoxia- and angiogenesis-related genes in the database. A gene signature model was constructed based on univariate and multivariate Cox regression analyses, and validated in independent cohorts. Kaplan-Meier survival and time-dependent receiver operating characteristic (ROC) curves were generated to evaluate the model's predictive capability. Gene set enrichment analysis (GSEA) was performed to explore signaling pathways regulated by the gene signature. Furthermore, the relationships among gene signature, immune status, and response to anti-angiogenesis agents and immune checkpoint blockade (ICB) were analyzed.ResultsThe prognostic model was based on three HRAGs (ANGPT2, SERPINE1 and SPP1). The model accurately predicted that low-risk patients would have longer overall survival than high-risk patients, consistent with findings in other cohorts. GSEA indicated that high-risk group membership was significantly associated with hypoxia, angiogenesis, the epithelial-mesenchymal transition, and activity in immune-related pathways. The high-risk group also had more immunosuppressive cells and higher expression of immune checkpoints such as PD-1 and PD-L1. Conversely, the low-risk group had a better response to anti-angiogenesis and ICB therapy.ConclusionsThe gene signature based on HRAGs was predictive of prognosis and provided an immunological perspective that will facilitate the development of personalized therapies.
| S-EPMC9468769 | biostudies-literature
Project description:BackgroundHypoxia plays an indispensable role in the development of hepatocellular carcinoma (HCC). However, there are few studies on the application of hypoxia molecules in the prognosis predicting of HCC. We aim to identify the hypoxia-related genes in HCC and construct reliable models for diagnosis, prognosis and recurrence of HCC patients as well as exploring the potential mechanism.MethodsDifferentially expressed genes (DEGs) analysis was performed using The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) database and four clusters were determined by a consistent clustering analysis. Three DEGs closely related to overall survival (OS) were identified using Cox regression and LASSO analysis. Then the hypoxia-related signature was developed and validated in TCGA and International Cancer Genome Consortium (ICGC) database. The Gene Set Enrichment Analysis (GSEA) was performed to explore signaling pathways regulated by the signature. CIBERSORT was used for estimating the fractions of immune cell types.ResultsA total of 397 hypoxia-related DEGs in HCC were detected and three genes (PDSS1, CDCA8 and SLC7A11) among them were selected to construct a prognosis, recurrence and diagnosis model. Then patients were divided into high- and low-risk groups. Our hypoxia-related signature was significantly associated with worse prognosis and higher recurrence rate. The diagnostic model also accurately distinguished HCC from normal samples and nodules. Furthermore, the hypoxia-related signature could positively regulate immune response. Meanwhile, the high-risk group had higher fractions of macrophages, B memory cells and follicle-helper T cells, and exhibited higher expression of immunocheckpoints such as PD1and PDL1.ConclusionsAltogether, our study showed that hypoxia-related signature is a potential biomarker for diagnosis, prognosis and recurrence of HCC, and it provided an immunological perspective for developing personalized therapies.
| S-EPMC7487492 | biostudies-literature
Project description:AimImmunotherapy is currently being explored as a potential treatment for hepatocellular carcinoma (HCC). This study investigated the prognostic value of immune-related long non-coding RNAs (lncRNAs) in patients with HCC.MethodsThe Wilcoxon test was used to compare differentially expressed lncRNAs between HCC tissue and non-tumor tissue. Moreover, co-expression analysis was used to determine immune-related lncRNA. Univariate cox regression analysis and the least absolute shrinkage and selection operator (LASSO) regression were used to identify immune-related prognostic lncRNA. The immune risk score was calculated by the sum of the product from each lncRNA expression and its coefficient. Furthermore, the prognostic significance of the lncRNA signature was determined in the training group, testing group, and the entire group. A prognostic nomogram was established by integrating immune risk score and clinicopathological features.ResultsPRRT3-AS1 and AL031985.3 were identified as immune-related prognostic lncRNAs in HCC patients. HCC patients were divided into high and low-risk groups based on the optimal cutoff value of risk score in the training group. The prognosis of HCC patients in the high-risk group was worse compared with the low-risk group. Besides, the immune-related lncRNA score was regarded as an independent risk factor for the prognosis of HCC patients. The predictive nomogram showed satisfactory discrimination and consistency. Gene enrichment analysis results indicated that the high-risk group was associated with immune-related signaling pathways.ConclusionThis study screened a 2-lncRNA signature and constructed a nomogram to predict the survival of HCC patients, thereby provided guidelines for undertaking medical decisions.
| S-EPMC7500314 | biostudies-literature
Project description:PurposeAutophagy is a lysosomal degradation pathway that is essential for maintaining the homeostasis of the intracellular environment. Mounting evidence indicates that autophagy plays an essential role in the occurrence and development of hepatocellular cancer (HCC). This research is aimed at exploring the prognostic value of autophagy-related genes (ARGs) in HCC patients.MethodsThe Wilcoxon test was used to identify differentially expressed ARGs in The Cancer Genome Atlas (TCGA) HCC cohort. Then, the TCGA cohort was randomly divided into training and testing groups. Cox and LASSO regression models were used to screen for autophagy-related genes that affect overall survival (OS) in the TCGA training group. Based on the coefficient of risk genes, we constructed an autophagy-related gene signature for predicting the prognosis of HCC patients. Finally, we validated the prognostic significance of autophagy-related gene signature using the TCGA testing group and three external datasets.ResultsATG10, BIRC5, GAPDH, and TMEM74 are risk genes for OS. According to the optimal cutoff value of risk score in each HCC dataset, HCC patients can divide into high- and low-risk groups. ARG risk score can significantly distinguish HCC patients with different survival outcomes. Meanwhile, the ARG risk score is independently correlated with OS in multiple HCC cohorts.ConclusionsThe autophagy-related risk score can effectively screen high-risk HCC patients and provide guidance for clinical prevention and treatment of HCC.
| S-EPMC8568514 | biostudies-literature
Project description:Background: Hepatocellular carcinoma often results in late-stage diagnosis, leading to decreased treatment success. To improve prognosis, this study integrates cuproptosis with immune risk scoring models for HCC patients. Method: We identified differentially expressed genes connected to cuproptosis and immune responses using Pearson correlation. A risk signature was then constructed via LASSO regression, and its robustness was validated in the International Cancer Genome Consortium dataset. Additionally, qPCR confirmed findings in tumor and normal tissues. Results: Eight genes emerged as key prognostic markers from the 110 differentially expressed genes linked to cuproptosis and immunity. A risk-scoring model was developed using gene expression, effectively categorizing patients into low- or high-risk groups. Validated in the ICGC dataset, high-risk patients had significantly reduced survival times. Multivariate Cox regression affirmed the risk signature's independent predictive capability. A clinical nomogram based on the risk signature was generated. Notably, low-risk patients might benefit more from immune checkpoint inhibitors. qPCR and western blotting results substantiated our bioinformatics findings. Conclusions: The genetic risk signature linked to cuproptosis and immunity holds potential as a vital prognostic biomarker for Hepatocellular carcinoma, providing avenues for tailored therapeutic strategies.
| S-EPMC10937287 | biostudies-literature
Project description:Background: Hepatocellular Carcinoma (HCC) is an aggressive tumor with an inferior prognosis. Necroptosis is a new form of programmed death that plays a dual effect on the tumor. However, the role of necroptosis-related genes(NRGs) in HCC remains unknown. Methods: All datasets were downloaded from publicly available databases. The consensus clustering analysis was used to classify patients into different subtypes based on NRGs. The Least Absolute Shrinkage and Selection Operator (LASSO) Cox regression were used to develop a prognostic signature. Tumor Immune Dysfunction and Exclusion (TIDE) was used to predict immunotherapy response. Results: The genetic and transcriptional changes of NRGs were observed in HCC. Patients were classified into three clusters based on differentially expressed NRGs, of which Cluster-3 had the worst prognosis and the highest immune infiltration. The prognostic signature was developed based on 8-NRGs, which have shown excellent prognostic performance. The high-risk group in the signature presented significantly higher immune infiltration, such as aDCs, iDCs, macrophages, and Treg, compared to the low-risk group. TMB and immune checkpoints were also higher in the high-risk group. Moreover, a lower TIDE score was observed in the high-risk group, indicating the patients with high risk-score may be suitable for immunotherapy. Via the dataset of IMvigor210, we found a higher risk score in the immunotherapy response group. Conclusion: We developed a new necroptosis-related signature for predicting prognosis with the potential to predict immunotherapy for HCC patients.
| S-EPMC9484537 | biostudies-literature
Project description:PurposeTranscatheter arterial chemoembolization (TACE) is commonly used in the treatment of hepatocellular carcinoma (HCC). However, not all patients respond to this treatment. TACE typically leads to hypoxia in the tumor microenvironment. Therefore, we aimed to construct a prognostic model based on hypoxia-related differentially expressed microRNA (miRNAs) in hepatocellular carcinoma (HCC) and to investigate the potential target mRNAs for predicting TACE response.MethodsThe hypoxia-related miRNAs (HRMs) were identified in liver cancer cells, then global test was performed to further select the miRNAs which were associated with recurrence and vascular invasion. A prognostic model was constructed based on multivariate Cox regression analysis; qRT-PCR analysis was used to validate the differentially expressed miRNAs in HCC cell lines under hypoxic condition. We further identified the putative target genes of the miRNAs and investigate the relationship between the target genes and TACE response, immune cells infiltration.ResultsWe established a HRMs prognostic model for HCC patients, containing two miRNAs (miR-638, miR-501-5p), the patients with high-HRMs score showed worse survival in discovery and validation cohort; qRT-PCR analysis confirmed that these two miRNAs are up-regulated in hepatoma cells under hypoxic condition. Furthermore, four putative target genes of these two miRNAs were identified (ADH1B, CTH, FTCD, RCL1), which were significantly associated with TACE response, immune score, immunosuppressive immune cells infiltration, PDCD1 and CTLA4.ConclusionThe HCC-HRMs signature may be utilized as a promising prognostic factor and may have implications for guiding TACE and immune therapy.
| S-EPMC10944249 | biostudies-literature
Project description:Hepatocellular carcinoma (HCC) is the most common form of liver cancer with limited therapeutic options and low survival rate. The hypoxic microenvironment plays a vital role in progression, metabolism, and prognosis of malignancies. Therefore, this study aims to develop and validate a hypoxia gene signature for risk stratification and prognosis prediction of HCC patients. The Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium (ICGC) databases were used as a training cohort, and one Gene Expression Omnibus database (GSE14520) was served as an external validation cohort. Our results showed that eight hypoxia-related genes (HRGs) were identified by the least absolute shrinkage and selection operator analysis to develop the hypoxia gene signature and demarcated HCC patients into the high- and low-risk groups. In TCGA, ICGC, and GSE14520 datasets, patients in the high-risk group had worse overall survival outcomes than those in the low-risk group (all log-rank P < 0.001). Besides, the risk score derived from the hypoxia gene signature could serve as an independent prognostic factor for HCC patients in the three independent datasets. Finally, a nomogram including the gene signature and tumor-node-metastasis stage was constructed to serve clinical practice. In the present study, a novel hypoxia signature risk model could reflect individual risk classification and provide therapeutic targets for patients with HCC. The prognostic nomogram may help predict individualized survival.
| S-EPMC8236897 | biostudies-literature
Project description: Not available
| S-EPMC11020806 | biostudies-literature