Evidence map›Paper›PMID 37406019›Full record

ArticlePloS one2023

Construction and validation of 3-genes hypoxia-related prognostic signature to predict the prognosis and therapeutic response of hepatocellular carcinoma patients.

Yunxun Liu, Bingbing Shen, Ting Huang, Jianguo Wang, Jianxin Jiang

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Article in PloS one, 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

Authors and funding

5 authors.

Yunxun LiuDepartment of Urology, Renmin Hospital of Wuhan University, Wuhan, Hubei, PR China.
Bingbing ShenDepartment of Hepatobiliary Surgery, Renmin Hospital of Wuhan University, Wuhan, Hubei, PR China.
Ting HuangDepartment of Anaesthesiology, Renmin Hospital of Wuhan University, Wuhan, Hubei, PR China.
Jianguo WangDepartment of Hepatobiliary Surgery, Renmin Hospital of Wuhan University, Wuhan, Hubei, PR China.
Jianxin JiangDepartment of Hepatobiliary Surgery, Renmin Hospital of Wuhan University, Wuhan, Hubei, PR China.ORCID 0000-0001-7939-9082

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundPrevious studies have shown that the hypoxia microenvironment significantly impacted tumor progression. However, the clinical prognostic value of hypoxia-related risk signatures and their effects on the tumor microenvironment (TME) in hepatocellular carcinoma (HCC) remains hazy. This study aimed to conduct novel hypoxia-related prognostic signatures and improve HCC prognosis and treatment.

methodsDifferentially expressed hypoxia-related genes (HGs) were identified with the gene set enrichment analysis (GSEA). Univariate Cox regression was utilized to generate the tumor hypoxia-related prognostic signature, which consists of 3 HGs, based on the least absolute shrinkage and selection operator (LASSO) algorithm. Then the risk score for each patient was performed. The prognostic signature's independent prognostic usefulness was confirmed, and systematic analyses were done on the relationships between the prognostic signature and immune cell infiltration, somatic cell mutation, medication sensitivity, and putative immunological checkpoints.

resultsA prognostic risk model of four HGs (FDPS, SRM, and NDRG1) was constructed and validated in the training, testing, and validation datasets. To determine the model's performance in patients with HCC, Kaplan-Meier curves and time-dependent receiver operating characteristic (ROC) curves analysis was implemented. According to immune infiltration analysis, the high-risk group had a significant infiltration of CD4+ T cells, M0 macrophages, and dendritic cells (DCs) than those of the low-risk subtype. In addition, the presence of TP53 mutations in the high-risk group was higher, in which LY317615, PF-562271, Pyrimethamine, and Sunitinib were more sensitive. The CD86, LAIR1, and LGALS9 expression were upregulated in the high-risk subtype.

conclusionsThe hypoxia-related risk signature is a reliable predictive model for better clinical management of HCC patients and offers clinicians a holistic viewpoint when determining the diagnosis and course of HCC treatment.

Indexed as

Carcinoma, HepatocellularLiver NeoplasmsFemaleFetal HypoxiaGenes, RegulatorHumansHypoxiaPrognosisTumor Microenvironment

Identifiers

PMID37406019
PMCPMC10321610

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.