Integrative bulk and single-cell transcriptomic analysis identifies a ferro-aging-related four-gene signature associated with immune remodeling in hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is characterized by a profoundly immunosuppressive tumor microenvironment, which contributes to poor clinical outcomes and limited therapeutic benefit. Ferro-aging has recently emerged as a concept linking iron dysregulation and sustained lipid peroxidation with cellular senescence, but its biological boundaries and relevance to HCC remain unclear. We integrated bulk and single-cell transcriptomic data to characterize ferro-aging-related features in HCC. A four-gene ferro-aging-related prognostic signature consisting of SLC1A5, CTSB, TFRC, and GMFB was developed using the TCGA-LIHC cohort and quantified as the RiskScore. Cross-cohort expression support was assessed in GSE14520 and GSE76427. The RiskScore was exploratorily contextualized against an unsupervised conventional ferroptosis score. Immune-cell composition and inferred cell-cell communication were analyzed, and iLINCS was used for exploratory compound screening based on the SLC1A5-high malignant-cell signature. The four-gene ferro-aging-related RiskScore stratified patients into high- and low-risk groups with moderate prognostic performance. Cross-cohort analysis provided broadly consistent expression support for the selected genes. Exploratory analysis showed different prognostic and immune-association patterns between the supervised RiskScore and the unsupervised ferroptosis score, although these scores are not directly comparable. After FDR correction, high-risk tumors showed increased inhibitory immune-checkpoint expression, higher M0 macrophage proportions, and lower activated NK-cell proportions. Single-cell analysis localized SLC1A5 expression primarily to malignant cells, while CellChat inferred MIF- and SPP1-related communication between malignant and immune populations. iLINCS analysis prioritized hypothesis-generating compounds, including AKT Inhibitor IV, whose reference signatures showed negative connectivity with the SLC1A5-high malignant-cell signature. Ferro-aging-related transcriptional features were associated with prognosis and immune remodeling in HCC. The four-gene prognostic signature provides an exploratory framework for patient stratification, while the single-cell and drug-screening findings remain hypothesis-generating.

Authors

Institutions

Publication Details

Journal
Discover Oncology
Published
2026-10-16
DOI
https://doi.org/10.1007/s12672-026-06120-8
Primary Topic
Ferroptosis and cancer prognosis
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Integrative bulk and single-cell transcriptomic analysis identifies a ferro-aging-related four-gene signature associated with immune remodeling in hepatocellular carcinoma

Rui Hu, Jiahua Yang, Zhiyi Han, Xiaozhou Zhou et al.
Discover Oncology
Ferroptosis and cancer prognosis
article

Integrative bulk and single-cell transcriptomic analysis identifies a ferro-aging-related four-gene signature associated with immune remodeling in hepatocellular carcinoma

Rui Hu, Jiahua Yang, Zhiyi Han, Xiaozhou Zhou, Jiesheng Guo, Qi Huang, Jing Li, Yan Wang
article en

Abstract

Hepatocellular carcinoma (HCC) is characterized by a profoundly immunosuppressive tumor microenvironment, which contributes to poor clinical outcomes and limited therapeutic benefit. Ferro-aging has recently emerged as a concept linking iron dysregulation and sustained lipid peroxidation with cellular senescence, but its biological boundaries and relevance to HCC remain unclear. We integrated bulk and single-cell transcriptomic data to characterize ferro-aging-related features in HCC. A four-gene ferro-aging-related prognostic signature consisting of SLC1A5, CTSB, TFRC, and GMFB was developed using the TCGA-LIHC cohort and quantified as the RiskScore. Cross-cohort expression support was assessed in GSE14520 and GSE76427. The RiskScore was exploratorily contextualized against an unsupervised conventional ferroptosis score. Immune-cell composition and inferred cell-cell communication were analyzed, and iLINCS was used for exploratory compound screening based on the SLC1A5-high malignant-cell signature. The four-gene ferro-aging-related RiskScore stratified patients into high- and low-risk groups with moderate prognostic performance. Cross-cohort analysis provided broadly consistent expression support for the selected genes. Exploratory analysis showed different prognostic and immune-association patterns between the supervised RiskScore and the unsupervised ferroptosis score, although these scores are not directly comparable. After FDR correction, high-risk tumors showed increased inhibitory immune-checkpoint expression, higher M0 macrophage proportions, and lower activated NK-cell proportions. Single-cell analysis localized SLC1A5 expression primarily to malignant cells, while CellChat inferred MIF- and SPP1-related communication between malignant and immune populations. iLINCS analysis prioritized hypothesis-generating compounds, including AKT Inhibitor IV, whose reference signatures showed negative connectivity with the SLC1A5-high malignant-cell signature. Ferro-aging-related transcriptional features were associated with prognosis and immune remodeling in HCC. The four-gene prognostic signature provides an exploratory framework for patient stratification, while the single-cell and drug-screening findings remain hypothesis-generating.

Discover Oncology
Macau University of Science and Technology (MO), Guangzhou University of Chinese Medicine (CN), University of Macau (MO), Shenzhen Pingle Orthopedic Hospital (CN)
Good health and well-being
Openalex Percentile: Top 13%
Ferroptosis and cancer prognosis
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.