A novel prognostic framework for HBV-infected hepatocellular carcinoma: insights from ferroptosis and iron metabolism proteomics DOI Creative Commons
Zhiwei Cheng, Yongyong Ren, Xinbo Wang

et al.

Briefings in Bioinformatics, Journal Year: 2025, Volume and Issue: 26(3)

Published: May 1, 2025

Abstract Effective classification methods and prognostic models enable more accurate treatment of hepatocellular carcinoma (HCC) patients. However, the weak correlation between RNA protein data has limited clinical utility previous RNA-based for HCC. In this work, we constructed a novel framework HCC patients using seven differentially expressed proteins associated with ferroptosis iron metabolism. Furthermore, model robustly classifies into three clinically relevant risk groups. Significant differences in overall survival, age, tumor differentiation, microvascular invasion, distant metastasis, alpha-fetoprotein levels were observed among Based on known biological pathways, explored potential mechanisms underlying inconsistent differential expression patterns FTH1 (Ferritin heavy chain 1) mRNA protein. Our findings demonstrated that tissues promote liver cancer progression by downregulating expression, rather than upregulating ultimately leading to poor prognosis. Subsequently, based score size, developed nomogram predicting prognosis patients, which superior predictive performance both training validation cohorts (C-index: 0.774; AUC 1–5 years: 0.783–0.964). Additionally, our adverse high-risk was closely correlated tissues, alterations metabolism, changes immune microenvironment. conclusion, offer insights tools effective potentially enhancing decision-making outcomes.

Language: Английский

A novel prognostic framework for HBV-infected hepatocellular carcinoma: insights from ferroptosis and iron metabolism proteomics DOI Creative Commons
Zhiwei Cheng, Yongyong Ren, Xinbo Wang

et al.

Briefings in Bioinformatics, Journal Year: 2025, Volume and Issue: 26(3)

Published: May 1, 2025

Abstract Effective classification methods and prognostic models enable more accurate treatment of hepatocellular carcinoma (HCC) patients. However, the weak correlation between RNA protein data has limited clinical utility previous RNA-based for HCC. In this work, we constructed a novel framework HCC patients using seven differentially expressed proteins associated with ferroptosis iron metabolism. Furthermore, model robustly classifies into three clinically relevant risk groups. Significant differences in overall survival, age, tumor differentiation, microvascular invasion, distant metastasis, alpha-fetoprotein levels were observed among Based on known biological pathways, explored potential mechanisms underlying inconsistent differential expression patterns FTH1 (Ferritin heavy chain 1) mRNA protein. Our findings demonstrated that tissues promote liver cancer progression by downregulating expression, rather than upregulating ultimately leading to poor prognosis. Subsequently, based score size, developed nomogram predicting prognosis patients, which superior predictive performance both training validation cohorts (C-index: 0.774; AUC 1–5 years: 0.783–0.964). Additionally, our adverse high-risk was closely correlated tissues, alterations metabolism, changes immune microenvironment. conclusion, offer insights tools effective potentially enhancing decision-making outcomes.

Language: Английский

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