Evidence map›Paper›PMID 41670819›Full record

ArticleClinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico2026

Establishment of insulin resistance-related ten-gene signature in endometrial cancer and identification of ACTL8 as a prognostic and immunological biomarker.

Siyun Lu, Jie Xu, XiaoXiao Sun, Jie Yuan, Jiajing Cheng, Jinlong Qin

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Article in Clinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico, 2026. 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

Authors and funding

6 authors.

Siyun Lu *Department of Gynecology, Shanghai Fourth People's Hospital, Shanghai, 200434, China.
Jie Xu *Department of Gynecology, Shanghai Fourth People's Hospital, Shanghai, 200434, China.
XiaoXiao Sun *Department of Gynecology, Shanghai Fourth People's Hospital, Shanghai, 200434, China.
Jie YuanDepartment of General Surgery, The 980th, Hospital (Bethune International Peace Hospital) of The PLA Joint Logistic Support Force, Shijiazhuang, 050082, China. yuanjie816@126.com.
Jiajing ChengDepartment of Gynecology, Shanghai Fourth People's Hospital, Shanghai, 200434, China. chengjiajing1963@163.com.
Jinlong QinDepartment of Gynecology, Shanghai Fourth People's Hospital, Shanghai, 200434, China. jinqinlong@yeah.net.ORCID http://orcid.org/0009-0005-0284-819X

Funding

Science and Technology Commission of Shanghai Municipality NO.22DZ1202304
6 · The paper itself

Abstract

backgroundEndometrial cancer (EC) is a common gynecological tumor. Insulin resistance (IR) increases the risk of EC. However, the common molecular basis between the two remains unclear. This study aims to screen the common differential expression genes (DEGs) between the two diseases and construct a prognostic risk model.

methodsWe obtained gene expression profiles and clinical information of patients with IR and EC from GEO and TCGA datasets. We performed differential analysis to discover the shared DEGs between IR and EC. Subsequently, the interactions among overlapping DEGs, along with their biological functions and genetic mutations in EC, were comprehensively analyzed via protein-protein interaction (PPI) network, function enrichment analyses, and genetic mutation analyses. Then, machine-learning algorithms were employed to figure out genes significantly associated with survival. For clinical application, we constructed a prognostic risk model and also compared tumor-infiltrating immune cells (TIICs) and genetic mutation between high- and low-risk groups. Finally, we screened one of the most important markers in the prognostic signature to investigate its expression-prognosis pattern, biological function, and underlying mechanism.

resultsOur analysis identified 20 co-upregulated genes and 32 co-downregulated genes of IR and EC. In addition, the two subnetworks and the top 20 top genes were obtained through PPI analysis, while the construction of extracellular matrix and immune response were the most enriched functions of DEGs. Filtered by random forest, gradient boosting machine, and extreme gradient boosting, six upregulated markers (ACTL8, WNT7A, CTSV, MMP9, CNIH2, and PLAUR) and four downregulated markers (COL6A6, MYOC, PHLDB1, and FIBIN), were defined as the characteristic genes for the prognosis of EC patients. The risk prediction model constructed by these ten genes had good predictive value in prognosis of EC patients and was related to immune regulation and genetic mutation. ACTL8 was further studied as the most significant marker among 10-gene signature. The correlation between the upregulation of ACTL8 and the poor prognosis of EC patients suggested its carcinogenic effect, which was correlated to its regulation of cilium movement.

conclusionOur findings suggest that there are common molecular profiles between IR and EC. IR-related prognostic model represents an excellent prognosis predictor and immune-related biomarker, which can be applied to risk stratification and precise treatment of EC patients with IR.

Indexed as

Biomarkers, TumorEndometrial NeoplasmsInsulin ResistanceTranscriptomeFemaleGene Expression ProfilingGene Expression Regulation, NeoplasticHumansLymphocytes, Tumor-InfiltratingMutationPrognosisProtein Interaction MapsBiomarkers, TumorEndometrial cancerGenetic mutationInsulin resistanceMachine learningPrognostic signatureTumor-infiltrating immune cells

Identifiers

PMID41670819
PMCPMC13401548

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