ArticleCurrent gene therapy2026
Identifying Key Epigenetic Modification-Related Genes for Cervical Squamous Cell Carcinoma and Endocervical Adenocarcinoma and Cellular Validation.
Article in Current gene therapy, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
2 citing papers in PubMed.
- FAM83D facilitates EMT and metastasis of cervical cancer via interaction with GSK3β and inactivation of GSK3β/stabilization of Snail signaling.Biology direct · 2026Article
- Development and Validation of a Prognostic Model for Cervical Cancer Based onInternational journal of women's health · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
Abstract
introductionCervical Squamous Cell Carcinoma and Endocervical Adenocarcinoma (CESC) is a highly prevalent female malignancy. As the epigenomic characteristics of immune cells and cancer cells can serve as predictive indicators for the response to cancer immunotherapy, analysis of epigenetically modified genes (EpiGenes) could contribute to CESC treatment.
methodsThe ssGSEA algorithm was employed to compute EpiGenes scores. Core genes that exhibited significant module association and a close correlation with EpiGenes scores were identified via the WGCNA package. Univariate Cox proportional hazards regression was performed on the core genes using the survival package, followed by gene set reduction via LASSO Cox regression. Ultimately, key genes were determined through multivariate Cox regression to establish a RiskScore model. Further, the optimal risk cutoff was determined using the survminer package to stratify CESC patients into high- and low-risk subgroups. For enrichment analysis, clusterProfiler and GSEA were utilized. Immune infiltration across risk groups was evaluated via ssGSEA, the MCPcounter algorithm, and the ESTIMATE algorithm. TIDE was employed to compare immunotherapeutic responses between the risk groups, while the pRRophetic software was utilized to predict patients' chemotherapeutic drug sensitivity. The biomarkers identified were validated by performing in vitro experiments.
resultsDISCUSSION: Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis revealed that module genes are significantly enriched in cell cycle regulatory pathways, and these genes, in conjunction with Human Papillomavirus (HPV) infection-induced cell cycle dysregulation, jointly participate in CESC pathogenesis, providing a mechanistic basis for understanding the disease.
conclusionThis study provided novel theoretical evidence for immunotherapy and chemotherapy selection in the management of CESC.
Indexed as
Identifiers
41293945What OpenQuestion holds
Registered trials
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.