Exploration of a Robust and Prognostic Immune Related Gene Signature for Cervical Squamous Cell Carcinoma.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:33748188", "kind": "science-record", "revision": 7, "content_hash": "sha256:bdba81ae88d8ac307a8ea8056c4c722467e207cfb00bbc3e15729ef8ea179cb0", "created_at": "2026-11-01T15:41:29Z", "updated_at": "2026-11-01T22:03:22Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Exploration of a Robust and Prognostic Immune Related Gene Signature for Cervical Squamous Cell Carcinoma.", "doi": "10.3389/fmolb.2021.625470", "pmid": "33748188", "authors": ["Zhihua Zuo", "Junjun Xiong", "Chuyi Zeng", "Yao Jiang", "Kang Xiong", "Hualin Tao", "Yongcan Guo"], "journal": "Frontiers in molecular biosciences", "year": 2021, "abstract": "Background: Cervical squamous cell carcinoma (CESC) is one of the most frequent malignancies in women worldwide. The level of immune cell infiltration and immune-related genes (IRGs) can significantly affect the prognosis and immunotherapy of CESC patients. Thus, this study aimed to identify an immune-related prognostic signature for CESC. Methods: TCGA-CESC cohorts, obtained from TCGA database, were divided into the training group and testing group; while GSE44001 dataset from GEO database was viewed as external validation group. ESTIMATE algorithm was applied to evaluate the infiltration levels of immune cells of CESC patients. IRGs were screened out through weighted gene co-expression network analysis (WGCNA). A multi-gene prognostic signature based on IRGs was constructed using LASSO penalized Cox proportional hazards regression, which was validated through Kaplan-Meier, Cox, and receiver operating characteristic curve (ROC) analyses. The abundance of immune cells was calculated using ssGSEA algorithm in the ImmuCellAI database, and the response to immunotherapy was evaluated using immunophenoscore (IPS) analysis and the TIDE algorithm. Results: In TCGA-CESC cohorts, higher levels of immune cell infiltration were closely associated with better prognoses. Moreover, a prognostic signature was constructed using three IRGs. Based on this given signature, Kaplan-Meier analysis suggested the significant differences in overall survival (OS) and the ROC analysis demonstrated its robust predictive potential for CESC prognosis, further confirmed by internal and external validation. Additionally, multivariate Cox analysis revealed that the three IRGs signature served as an independent prognostic factor for CESC. In the three-IRGs signature low-risk group, the infiltrating immune cells (B cells, CD4/8 + T cells, cytotoxic T cells, macrophages and so on) were much more abundant than that in high-risk group. Ultimately, IPS and TIDE analyses showed that low-risk CESC patients appeared to present with a better response to immunotherapy and a better prognosis than high-risk patients. Conclusion: The present prognostic signature based on three IRGs (CD3E, CD3D, LCK) was not only reliable for survival prediction but efficient to predict the clinical response to immunotherapy for CESC patients, which might assist in guiding more precise individual treatment in the future.", "claims": [{"id": "claim-method", "statement": "Moreover, the survival curve was determined using the Kaplan–Meier method in the R survminer package, where the differences between low- and high-risk groups were calculated by the log-rank test.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:33748188", "locator": "sections[8] \"Development and Validation of the Prognostic Signature\" paragraph 2", "quote": "Moreover, the survival curve was determined using the Kaplan–Meier method in the R survminer package, where the differences between low- and high-risk groups were calculated by the log-rank test."}], "state": "complete"}, {"id": "claim-data-access", "statement": "Publicly available datasets were analyzed in this study. 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