Evidence map›Paper›PMID 42226181›Full record

ArticleWorld journal of surgical oncology2026

In silico analysis of driver genes in squamous cell carcinoma of the cervix: insights into their biological functions, prognosis, immune infiltration, and therapy.

Samatha Bhat, Vasudha Devi, Shama Prasada Kabekkodu

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Article in World journal of surgical oncology, 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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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

3 authors.

Samatha BhatDepartment of Biotherapeutics Research, Manipal Academy of Higher Education, Manipal, India.
Vasudha DeviDepartment of Basic Medical Sciences, Manipal Academy of Higher Education, Manipal, India.
Shama Prasada KabekkoduDepartment of Cell and Molecular Biology, Manipal School of Life Sciences, Manipal Academy of Higher Education, Manipal, India. shama.prasada@manipal.edu.ORCID http://orcid.org/0000-0002-4158-3893

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundCervical cancer is the fourth most common cancer affecting the female reproductive system worldwide. Although several studies have reported recurrent mutations in cervical squamous cell carcinoma (SCC), a comprehensive understanding of the clinically relevant driver genes remains limited. Unlike previous single-cohort or frequency-based reports, this study integrates four independent cervical squamous cell carcinoma (SCC) cohorts with network-based analysis, multiendpoint survival assessment, and drug-gene interaction to prioritize functionally and clinically relevant driver hub genes. MATERIALS AND

methodsIn this study, we performed a genomic analysis of a cohort of 4 squamous cell carcinomas of the cervix (SCCs), consisting of 467 samples, to identify driver genes and their clinical significance. Key pathways and biological functions affected were tested by functional enrichment analysis. The Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) and CytoHubba tools were used to construct a protein‒protein interaction network (PPIN) and identify the hub genes. Additional analyses included enrichment assessment of cancer hallmarks, survival evaluation, immune cell infiltration profiling, and drug‒gene interaction studies.

resultsOur analysis revealed 9,749,109 mutations across 44 driver genes. PIK3CA, KMT2C, KMT2D, FBXW7, FAT1, EP300, TP53, NOTCH1, STK11, and CASP8 were the top 10 mutated genes. PIK3CA, NOTCH1, PTEN, KRAS, ERBB2, TP53, ARID1A, EP300, STK11, and FBXW7 emerged as the top 10 hub genes according to the results of the PPIN and Cytohubba analyses. In addition, we observed significant differences in T helper cell type 2, natural killer cell, dendritic cell, and gamma delta T-cell composition in samples with hub gene mutations. Prioritization analysis of drug and hub gene interactions revealed 112 clinically relevant compounds, especially HER2-directed therapies (trastuzumab), PI3K inhibitors (alpelisib), and mTOR inhibitors (everolimus).

conclusionCollectively, our analysis describes the driver genes and mutation characteristics in SCC. The multi-cohort and network-based framework employed in this study identifies candidate hub genes that warrant further clinical investigation in cervical cancer.

Indexed as

Biomarkers, TumorCarcinoma, Squamous CellUterine Cervical NeoplasmsFemaleGene Expression Regulation, NeoplasticGene Regulatory NetworksHumansMutationPrognosisProtein Interaction MapsBiomarkers, TumorCervical cancerDriver genesHub genesImmune infiltrationIn silico analysisMutationsPrognostic marker

Identifiers

PMID42226181
PMCPMC13435706

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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.