Identification and validation of stemness-associated hub genes in cervical cancer: a bioinformatics and experimental study.

Authors

Shama Prasada Kabekkodu, Alfa Florence Rodrigues, Pratheeksha Hebbar, Samatha Bhat

Published in

World journal of surgical oncology. Jun 27, 2026. Epub Jun 27, 2026.

Abstract

Cancer stem cells (CSCs) are a subpopulation with self-renewal and differentiation capacity that drive the progression, recurrence, and therapeutic resistance of patients with cervical cancer (CC). However, the complete set of genes that maintain stemness in CC remains incompletely defined. We aimed to identify key stemness-related genes and evaluate their prognostic utility, immune associations, and drug sensitivity. Through literature mining and CellMarker 2.0, we identified 1345 stemness-associated genes that overlapped with differentially expressed genes (DEGs) from the TCGA-CESC dataset (log2FC > 2, p < 0.05), yielding 216 stemness-related DEGs. A protein-protein interaction network (STRING) and CytoHubba (MCC algorithm) revealed ten hub genes (HGs): CCNB1, CCNA2, BUB1B, UBE2C, KIF11, CCNB2, KIF23, CDC20, CDC6, and FOXM1. Gene ontology and KEGG analyses revealed predominant enrichment in cell cycle progression. Cox regression and Kaplan‒Meier analyses identified BUB1B, CCNA2, CDC20, FOXM1, and KIF23 as risk factors for poor overall survival, with KIF11 emerging as an independent prognostic factor. HGs overexpression significantly correlated with altered infiltration of 15 immune cell types, including negative associations with CD8 + T and NK cells. We identified 661 unique drugs/chemicals targeting these HGs, including FDA-approved repurposed agents. Experimental validation via RT‒PCR confirmed significant overexpression of FOXM1 and KIF11 in CC tissues and cell lines compared with normal samples. These stemness-associated HGs, particularly FOXM1 and KIF11, may serve as potential prognostic biomarkers and therapeutic targets, warranting further investigation of stemness-driven CC progression.

PMID:
42365339
Bibliographic data and abstract were imported from PubMed on 28 Jun 2026.

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