Evidence map›Paper›PMID 38192999›Full record

ArticleTranslational cancer research2023

Identification of cuproptosis and ferroptosis-related subgroups and development of a signature for predicting prognosis and tumor microenvironment landscape in hepatocellular carcinoma.

Bin-Feng Yang, Qi Ma, Yuan Hui, Xiang-Chun Gao, Da-You Ma, Jing-Xian Li, Zheng-Xue Pei, Bang-Rong Huang

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Article in Translational cancer research, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

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3citing papers in PubMed
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1 · What the graph read from it

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3 · Its place in the literature

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3 citing papers in PubMed.

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4 · The record

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5 · Who and what money

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8 authors.

Bin-Feng Yang *Department of Oncology, Gansu Provincial Hospital of Traditional Chinese Medicine, Lanzhou, China.
Qi Ma *School of Integrative Medicine, Gansu University of Traditional Chinese Medicine, Lanzhou, China.
Yuan Hui *School of Integrative Medicine, Gansu University of Traditional Chinese Medicine, Lanzhou, China.
Xiang-Chun GaoSchool of Integrative Medicine, Gansu University of Traditional Chinese Medicine, Lanzhou, China.
Da-You MaSchool of Integrative Medicine, Gansu University of Traditional Chinese Medicine, Lanzhou, China.
Jing-Xian LiSchool of Integrative Medicine, Gansu University of Traditional Chinese Medicine, Lanzhou, China.
Zheng-Xue PeiDepartment of Integrative Medicine, Gansu Provincial Cancer Hospital, Lanzhou, China.
Bang-Rong HuangDepartment of Oncology, Gansu Provincial Hospital of Traditional Chinese Medicine, Lanzhou, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Ferroptosis and cuproptosis play a crucial role in the progression and dissemination of hepatocellular carcinoma (HCC). The primary objective of this study was to develop a unique scoring system for predicting the prognosis and immunological landscape of HCC based on ferroptosis-related genes (FRGs) and cuproptosis-related genes (CRGs). Methods: As the training cohort, we assembled a novel HCC cohort by merging gene expression data and clinical data from The Cancer Genome Atlas (TCGA) database, and Gene Expression Omnibus (GEO) database. The validation cohort consisted of 230 HCC cases taken from the International Cancer Genome Consortium (ICGC) database. Multiple genomic characteristics, such as tumor mutation burden (TMB), and copy number variations were analyzed concurrently. On the basis of the expression of CRGs and FRGs, patients were classified into cuproptosis and ferroptosis subtypes. Then, we constructed a risk model using least absolute shrinkage and selection operator (LASSO) analysis and Cox regression analysis based on ferroptosis and cuproptosis-related differentially expressed genes (DEGs). Patients were separated into two groups according to median risk score. We compared the immunophenotype, tumor microenvironment (TME), cancer stem cell index, and treatment sensitivity of two groups. Results: Three subtypes of ferroptosis and two subtypes of cuproptosis were identified among the patients. A greater likelihood of survival (P<0.05) was expected for patients in FRGcluster B and CRGcluster B. After that, a confirmed risk signature for ferroptosis and cuproptosis was developed and tested. Patients in the low-risk group had significantly higher survival rates than those in the high-risk group, according to our study (P<0.001). There was also a strong correlation between the signature and other variables including immunophenoscore, TMB, cancer stem cell index, immunological checkpoint genes, and sensitivity to chemotherapeutics. Conclusions: Through this comprehensive research, we identified a unique risk signature associated with HCC patients' treatment status and prognosis. Our findings highlight FRGs' and CRGs' significance in clinical practice and imply ferroptosis and cuproptosis may be therapeutic targets for HCC patients.

Indexed as

cuproptosisFerroptosishepatocellular carcinoma (HCC)prognostic signaturetumor microenvironment landscape (TME landscape)

Identifiers

PMID38192999
PMCPMC10774034

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