Dataset Information

A multi-omics-based investigation of the immunological and prognostic impact of necroptosis-related genes in patients with hepatocellular carcinoma.

ABSTRACT:

Background

Hepatocellular carcinoma (HCC) is the most common histological subtype of liver cancer and the third leading cause of death from cancer globally. Recent studies suggested cell death is also a key regulator of tumour progression. The purpose of this study was to generate a new predictive signature for HCC patients based on a complete analysis of necroptosis-associated genes.

Methods

We extracted the mRNA expression profiles of HCC patients from the TCGA and ICGC databases and their clinical data. In addition, we used the IMvigor210 cohort to validate our model molecule's ability to predict the effect of immunotherapy. In the TCGA cohort, a seven-gene risk-prognostic model was constructed using univariate cox-Lasoo regression. External validation was conducted using the ICGC cohort. The ssGSEA algorithm is used to determine the degree of immune function response. The CMAP databases are used for chemotherapy drug analysis and screening for drugs that reduce the expression of high-risk genes. The cbioportal database was used to explore mutations in model genes.

Results

Survival analysis shows shorter survival for high-risk patients. Immune function analysis revealed significant differences in the activity of immune pathways between risk subgroups. Varied risk scores result in dramatically diverse immune infiltration and tumour growth, as well as significantly different chemotherapeutic sensitivity. In addition, Apigenin and LY-294002 reduced the expression of high-risk genes, while Arecoline had the opposite effect. In the immunotherapy IMvigor210 cohort, risk scores were significantly different between the objective responder and non-responder groups. By comparing the models constructed with published literature, it is suggested that our model has better predictive power.

Conclusions

We created a new prognostic signature of necroptosis-related genes that can be used as potential prognostic biomarkers to guide effective personalized therapy for hepatocellular carcinoma patients.

SUBMITTER: Yang H

PROVIDER: S-EPMC8993599 | biostudies-literature | 2022 Apr

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

A multi-omics-based investigation of the immunological and prognostic impact of necroptosis-related genes in patients with hepatocellular carcinoma.

Yang Hang H Jiang QiNian Q

Journal of clinical laboratory analysis 20220315 4

<h4>Background</h4>Hepatocellular carcinoma (HCC) is the most common histological subtype of liver cancer and the third leading cause of death from cancer globally. Recent studies suggested cell death is also a key regulator of tumour progression. The purpose of this study was to generate a new predictive signature for HCC patients based on a complete analysis of necroptosis-associated genes.<h4>Methods</h4>We extracted the mRNA expression profiles of HCC patients from the TCGA and ICGC database ...[more]

PMID: 35293027

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Project description:Oxeiptosis is a recently discovered caspase-independent, non-inflammatory programmed cell death modality. Current studies suggest that oxeiptosis has crucial effects on biological processes in a variety of diseases. However, the mechanism of oxeiptosis in hepatocellular carcinoma (HCC) remains unclear and no relevant studies have been published. Therefore, this study is intended to investigate the mechanism and prognostic role of oxeiptosis-related genes in HCC. We explored the mechanisms and molecular phenotypes underlying the role of oxeiptosis in HCC through multi-omics analysis. Firstly, we obtained RNA-sequencing and clinical data from public database and divided the samples into trial and validation cohorts in subsequent analyses. We then screened oxeiptosis core genes (OCGs) and screened prognosis-related genes. Based on different molecular markers, we identified the molecular phenotypes of HCC, and the potential OCGs molecular mechanisms were explored. Subsequently, we construct a prognostic prediction system for HCC. Finally, we analyzed the tumor microenvironment and the immune escape phenomenon. We screened a total of 69 OCGs, most of which were prognostic risk factors for HCC. A majority of OCGs were enriched in cell cycle regulation and mitotic processes, which were related to both tumor cell proliferation and death. We identified 2 different molecular typing options with significant differences in prognosis, function, and signaling pathway enrichment between different molecular subtypes. The prognostic prediction model combined with molecular phenotypes and had a good predictive effect. Finally, we found CD4 + T-cell exhaustion in samples with specific molecular phenotypes. Through multi-omics analysis of OCGs, we not only revealed the possible molecular mechanisms of OCGs in HCC but also provided a prognostic prediction system for clinical application through molecular typing and risk scoring model. Meanwhile, we found immune escape mechanisms in HCC.

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Dataset Information

A multi-omics-based investigation of the immunological and prognostic impact of necroptosis-related genes in patients with hepatocellular carcinoma.

Background

Methods

Results

Conclusions

Publications

A multi-omics-based investigation of the immunological and prognostic impact of necroptosis-related genes in patients with hepatocellular carcinoma.

Similar Datasets

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