Evidence map›Paper›PMID 41123823›Full record

ArticleDiscover oncology2025

Amino acid metabolism-related LncRNAs as prognostic biomarkers and predictors of immunotherapy response in hepatocellular carcinoma.

Jiaxing Zhang, Xiaojing Zhu, Long Hu, Liyue Yu, Yan Xu

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Article in Discover oncology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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5 · Who and what money

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5 authors.

Jiaxing ZhangCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin, 150081, China.
Xiaojing ZhuCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin, 150081, China.
Long HuXJTLU Wisdom Lake Academy of Pharmacy, Xi'an Jiaotong-Liverpool University, Suzhou, 215123, Jiangsu, China.
Liyue YuXJTLU Wisdom Lake Academy of Pharmacy, Xi'an Jiaotong-Liverpool University, Suzhou, 215123, Jiangsu, China.
Yan XuCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin, 150081, China. xuyan@ems.hrbmu.edu.cn.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundHCC has a high mortality rate among common malignancies. Finding the pathway that is involved with HCC is the main challenge in targeting metabolism for cancer therapy.

methodsBased on transcription data from the TCGA database, Univariate Cox analysis, LASSO, and Multivariate Cox analysis were used to identify hub AAM-related lncRNAs and construct a risk model. Then K-M survival analysis, time-dependent ROC curve analysis, genetic alterations, functional enrichment, immune infiltration status, and immunotherapy response were conducted. Finally, the effect of the characteristic gene AL590681.1 across different HCC cell lines was assessed.

results24 lncRNAs were involved in AAM and prognostic factors, and 4 lncRNAs were in our risk model. Patients in the high-risk group had a lower OS rate than patients in the low-risk group. The high-risk group had more immunosuppressive immune cells infiltrating and expressing CD276, CTLA4 and TIGIT. Patients in the high-risk group could had better survival prospects with an anti-PD1 treatment. Finally, the key gene AL590681.1 was overexpressed in various HCC cell lines and could enhance HCC cell activity.

conclusionWe developed a novel risk model for HCC patients with AAM-related lncRNAs, which could help predict the prognosis and response to immunotherapy.

Indexed as

Amino acid metabolismHepatocellular carcinomaImmunotherapy responseLncRNA signature

Identifiers

PMID41123823
PMCPMC12545943

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