Evidence mapPaperPMID 39556271Full record

ArticleDiscover oncology2024

TMSB4X is a regulator of inflammation-associated ferroptosis, and promotes the proliferation, migration and invasion of hepatocellular carcinoma cells.

Linlin Tang, Yangli Jin, Jinxu Wang, Xiuyan Lu, Mengque Xu, Mingwei Xiang

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Article in Discover oncology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

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4citing 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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4 citing papers in PubMed.

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5 · Who and what money

Authors and funding

6 authors.

Linlin Tang *Department of Gastroenterology, Zhuji People's Hospital, Shaoxing, China.
Yangli Jin *Department of Ultrasound, Ningbo Yinzhou No.2 Hospital, Ningbo, Zhejiang, China.
Jinxu WangIntensive Care Unit, Shouguang Hospital of Traditional Chinese Medicine, Weifang, Shandong, China.
Xiuyan LuDepartment of Gastroenterology, Zhuji People's Hospital, Shaoxing, China.
Mengque XuDepartment of Gastroenterology, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China.
Mingwei XiangGeneral Surgery Ward 4, Qinghai Provincial People's Hospital, Xining, Qinghai, China. Xiao_wei0103@163.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundFerroptosis and inflammation are involved in cancer progression. The aim of this study was to identify inflammation-associated ferroptosis regulators in hepatocellular carcinoma (HCC).

methodsFerrDb database was searched for ferroptosis-related genes. RNA sequencing data and clinicopathologic information of HCC patients were downloaded from the Cancer Genome Atlas (TCGA) database. Weighted gene co-expression network analysis was applied to obtain the genes probably involved in inflammation-associated ferroptosis. Univariate Cox regression analysis was conducted to screen prognostic genes, and 10 machine learning algorithms were combined to find the optimal strategy to evaluate the prognosis of the patients based on the prognosis-related genes. The patients were divided into high risk group and low risk group, and the differentially expressed genes were obtained. Thymosin beta 4 X-linked (TMSB4X) was overexpressed or knocked down in HCC cell lines, and then qPCR, CCK-8, Transwell, flow cytometery assays were performed to detect the change of HCC cells' phenotypes, and Western blot was used to detect the change of ferroptosis markers.

results157 genes related to inflammation and ferroptosis in HCC were obtained by WGCNA. rLasso algorithm, with the highest C-index, screened out 29 hub genes, and this model showed good efficacy to predict the prognosis of HCC patients. The patients in high risk group and low risk groups showed distinct molecular characteristics. TMSB4X was the most important gene which dominated the classification, and it was highly expressed in HCC samples. TMSB4X promoted the viability, migration and invasion, and repressed ferroptosis of HCC cells.

conclusionThe risk model constructed based on the inflammation-associated ferroptosis regulators is effective to predict the clinical outcome of HCC patients. TMSB4X, involved in inflammation-associated ferroptosis, is a potential biomarker and therapeutic target for HCC.

Indexed as

FerroptosisHepatocellular carcinomaInflammationMachine learning

Identifiers

PMID39556271
PMCPMC11573954

What Socratic holds

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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 Socratic graph.