Computational analysis of TP53 vs. CTNNB1 mutations in hepatocellular carcinoma suggests distinct cancer subtypes with differential gene expression profiles and chromatin states

Süt, Burcu Biterge

doi:10.1016/j.compbiolchem.2020.107404

Cited by 1 publication

(1 citation statement)

References 40 publications

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“…The gene with the highest mutation rate in C1 was TP53, a tumor suppressor gene whose mutation not only impaired its antitumor activity but also conferred oncogenic properties on the mutated p53 protein [ 41 ]. Mutations in CTNNB1 and TP53 are mutually exclusive and represent two major groups of HCC with distinct phenotypic features: alcohol-induced HCC and HBV-induced HCC [ 42 – 44 ]. The mutation rate of TP53 in C1 was significantly higher than that of CTNNB1 (65 vs 12%), and that of CTNNB1 in C4 was significantly higher than that of TP53 (60 vs 21%).…”

Section: Discussionmentioning

confidence: 99%

A programmed cell death-related gene signature to predict prognosis and therapeutic responses in liver hepatocellular carcinoma

Gu,

Pan,

et al. 2024

Discov Onc

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Background Programmed cell death (PCD) functions critically in cancers and PCD-related genes are associated with tumor microenvironment (TME), prognosis and therapeutic responses of cancer patients. This study stratified hepatocellular carcinoma (HCC) patients and develop a prognostic model for predicting prognosis and therapeutic responses. Methods Consensus clustering analysis was performed to subtype HCC patients in The Cancer Genome Atlas (TCGA) database. Differentially expressed genes (DEGs) among the subtypes were filtered and subjected to the least absolute shrinkage and selection operator (LASSO) regression analysis and univariate Cox regression analysis to filter prognostic genes. A PCD-related prognostic gene signature in TCGA was constructed and validated in ICGC-LIRI-JP and GSE14520 datasets. TME was analyzed using CIBERSORT, MCP-counter, TIMER and EPIC algorithms. Drug sensitivity was predicted by oncoPredict package. Spearman analysis was used to detect correlation. Results Four molecular subtypes were categorized based on PCD-related genes. Subtype C1 showed the poorest prognosis, the most infiltration of Fibroblasts, dentritic cell (DC) and cancer-associated fibroblasts (CAFs), and the highest TIDE score. C4 had a better prognosis survival outcome, and lowest immune cell infiltration. The survival outcomes of C2 and C3 were intermediate. Next, a total of 69 co-DEGs were screened among the four subtypes and subsequently we identified five prognostic genes (MCM2, SPP1, S100A9, MSC and EPO) for developing the prognostic model. High-risk patients not only had unfavorable prognosis, higher clinical stage and grade, and more inflammatory pathway enrichment, but also possessed higher possibility of immune escape and were more sensitive to Cisplatin and 5. Fluorouracil. The robustness of the prognostic model was validated in external datasets. Conclusion This study provides new insights into clinical subtyping and the PCD-related prognostic signature may serve as a useful tool to predict prognosis and guide treatments for patients with HCC.

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Section: Discussionmentioning

confidence: 99%