Evidence map›Paper›PMID 40377731›Full record

ArticleDiscover oncology2025

Identification of M0 macrophage associated lipid metabolism genes for prognostic and immunotherapeutic response prediction in hepatocellular carcinoma.

Huanjie Zhou, Ming Lao, Zhengui Liang, Huiliu Zhao, Ying Wang, Qiongqing Huang, Chao Ou

Abstract read
In one paragraph

Article in Discover oncology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

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2citing papers in PubMed
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1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

7 authors.

Huanjie Zhou *Department of Clinical Laboratory, Guangxi Medical University Cancer Hospital, Guangxi Zhuang Autonomous Region, Nanning, 530021, People's Republic of China.
Ming Lao *Department of Clinical Laboratory, Guangxi Medical University Cancer Hospital, Guangxi Zhuang Autonomous Region, Nanning, 530021, People's Republic of China.
Zhengui LiangDepartment of Clinical Laboratory, Guangxi Medical University Cancer Hospital, Guangxi Zhuang Autonomous Region, Nanning, 530021, People's Republic of China.
Huiliu ZhaoDepartment of Clinical Laboratory, Guangxi Medical University Cancer Hospital, Guangxi Zhuang Autonomous Region, Nanning, 530021, People's Republic of China.
Ying WangDepartment of Clinical Laboratory, Guangxi Medical University Cancer Hospital, Guangxi Zhuang Autonomous Region, Nanning, 530021, People's Republic of China.
Qiongqing HuangDepartment of Clinical Laboratory, Guangxi Medical University Cancer Hospital, Guangxi Zhuang Autonomous Region, Nanning, 530021, People's Republic of China.
Chao OuDepartment of Clinical Laboratory, Guangxi Medical University Cancer Hospital, Guangxi Zhuang Autonomous Region, Nanning, 530021, People's Republic of China. ouchaogx@163.com.

Funding

the Key R & D program Natural Science Foundation of Guangxi Province AB19110007the Natural Science Foundation of Guangxi Province 2017GXNSFAA198015the Technology Development and Promotion Foundation of Guangxi Medical and Health Appropriate S2017104
6 · The paper itself

Abstract

purposeLiver cancer prognosis is associated with M0 macrophages and lipid metabolism reprogramming; however, the prognostic role of M0 macrophage-related lipid metabolism genes in hepatocellular carcinoma (HCC) remains unclear.

methodsWe identified 153 lipid metabolism genes associated with M0 macrophage infiltration in HCC from The Cancer Genome Atlas (TCGA) and the Molecular Signatures Database (MSigDB). Prognostic genes were selected, and a model was constructed using least absolute shrinkage and selection operator (LASSO) and Cox regression analyses. The model was validated using the International Cancer Genome Consortium (ICGC) database. We assessed the expression levels of prognostic genes by quantitative real-time polymerase chain reaction (qRT‒PCR).

resultsA prognostic model was developed based on five characteristic genes. Receiver operating characteristic curve analysis demonstrated that the model had good accuracy, with area under the curve values of 0.796, 0.732, and 0.728 for predicting survival at 1, 3, and 5 years, respectively. The high-risk group exhibited increased sensitivity to common chemotherapy drugs, including sorafenib, dasatinib, and 5-fluorouracil, compared with the low-risk group (P < 0.05). Additionally, the high-risk group had significantly more infiltrating M0 macrophages, resting dendritic cells, follicular helper T cells, and regulatory T cells than did the low-risk group (P < 0.05). The qRT‒PCR results confirmed the upregulation of these five characteristic genes in HCC tissues.

conclusionsM0 macrophage-associated lipid metabolism genes may serve as biomarkers for the prognosis of patients with HCC and as targets for immunotherapy.

Indexed as

HCCLipid metabolism genesM0 macrophagesMetabolic reprogramming

Identifiers

PMID40377731
PMCPMC12084471

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