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.
Highlights
Cervical cancer ranks as the fourth most frequent malignancy and the fourth leading cause of cancer-related death in women worldwide, with approximately 570,000 new cases and 311,000 deaths reported by the International Agency for Research on Cancer (IARC) in 2018 alone (Bray et al, 2018)
A total of 291 and 301 CESC samples were enrolled from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) database according to the inclusion criteria, respectively
The ESTIMATE score of each patient, which reflects the landscape of the tumor microenvironment (TME) and overall immune-infiltration degree was calculated with the ESTIMATE algorithm
Summary
Cervical cancer ranks as the fourth most frequent malignancy and the fourth leading cause of cancer-related death in women worldwide, with approximately 570,000 new cases and 311,000 deaths reported by the International Agency for Research on Cancer (IARC) in 2018 alone (Bray et al, 2018). Distinct from traditional treatments, the clinical benefits for immunotherapy patients are achieved by stimulating the persistent antitumor immune response (Kennedy and Salama, 2020), which depends on immunomodulation between the tumor microenvironment (TME) and cancer cells. The mechanism of immune checkpoint blockade (ICB) therapy is to enhance a patient’s anti-tumor immune response by blocking the inhibitory effect of tumor cells on immune cells. In this process, programmed cell death 1 (PD1) and cytotoxic T lymphocyte antigen 4 (CTLA-4) are the most common targets of ICIs, which generally inhibit the activation and amplification of T cells that render the anti-tumor response ineffective. This study aimed to identify an immune-related prognostic signature for CESC
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