Evidence map›Paper›PMID 38988938›Full record

ArticleTranslational cancer research2024

Construction and validation of a prognostic and therapeutic cuproptosis- and immune-related gene signature in hepatocellular carcinoma.

Qianqian Cheng, Wei Wang, Zhenyu Lv, Wenbin Ji, Jing Liu, Xueli Zhou, Yan Yang

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Article in Translational cancer research, 2024. 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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7 authors.

Qianqian Cheng *Department of Medical Oncology, The First Affiliated Hospital of Bengbu Medical University, Bengbu, China.
Wei Wang *Department of Medical Oncology, The First Affiliated Hospital of Bengbu Medical University, Bengbu, China.
Zhenyu LvDepartment of Medical Oncology, The First Affiliated Hospital of Bengbu Medical University, Bengbu, China.
Wenbin JiDepartment of Medical Oncology, The First Affiliated Hospital of Bengbu Medical University, Bengbu, China.
Jing LiuDepartment of Medical Oncology, The First Affiliated Hospital of Bengbu Medical University, Bengbu, China.
Xueli ZhouDepartment of Medical Oncology, The First Affiliated Hospital of Bengbu Medical University, Bengbu, China.
Yan YangDepartment of Medical Oncology, The First Affiliated Hospital of Bengbu Medical University, Bengbu, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Abnormal accumulation of copper could induce cell death and tumor growth, and affect tumor immune escape by regulating programmed cell death ligand 1 (PD-L1) expression. This study aims to establish and verify a risk signature based on cuproptosis- and immune-related genes (CIRGs) for hepatocellular carcinoma (HCC) management. Methods: HCC RNA-seq and clinical data were obtained from open databases. Least absolute shrinkage and selection operator (LASSO) and Cox regression analyses were utilized to screen CIRGs and develop a risk signature. The signature's value for clinical applications, functional enrichment, tumor mutation burden (TMB), and immune profile analyses were investigated systematically. Results: A risk signature was developed utilizing seven CIRGs, and it performed well in predicting the prognosis of HCC patients in both the training and external validation cohorts. The model's risk score was discovered to be related to important clinical features. Top 15 mutated genes in HCC were significantly different among different risk groups. High-risk patients showed higher TMB, and high TMB was closely identified with a poorer prognosis. Immune profile analyses showed that immune infiltration level was higher in low-risk patients than high-risk patients, and the level of immune checkpoint genes expression varied significantly between patients in two different risk groups. Low-risk patients responded well to immunotherapy treatment, whereas high-risk patients were more sensitive to sorafenib, doxorubicin, gemcitabine and AKT (also known as protein kinase B) inhibitors. Conclusions: The established risk signature based on CIRGs can not only well predict the prognosis of HCC patients but is also promising in evaluating TMB and treatment response to immunotherapy, targeted therapy and chemotherapy, which has the potential to assist in the clinical management of HCC.

Indexed as

Cuproptosishepatocellular carcinoma (HCC)immune-related genes (IRGs)prognosistreatment response

Identifiers

PMID38988938
PMCPMC11231767

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