An Innovative Immune Score‐Based Prognostic Nomogram for Patients with Cervical Cancer

Abstract

Background. In the past few years, the immune system and tumor immune microenvironment are becoming increasingly popular as more work has been accomplished in this field. However, nomograms based on immune-related characteristics for prognosis prediction of cervical cancer have not been fully explored to our knowledge. We constructed a novel immune score-based nomogram to predict patients with high risk and poor prognosis. Materials and Methods. 198 patients with cervical cancer from The Cancer Genome Atlas (TCGA) database were included in our study. Immune scores were generated with Estimation of STromal and Immune cells in MAlignant Tumor tissues using Expression data (ESTIMATE) algorithm, and clinic-pathological characteristics were also included for subsequent analysis. Cox proportional hazards regression models were performed for univariate and multivariate analyses to screen the significant factors, and a prognostic nomogram was built. Bootstrap resampling analysis was used for internal validation. The calibration curve and concordance index (C-index) were used to assess the predictive performance of the nomogram. Results. Patients were split into three subgroups based on immune scores. We found that patients with high immune scores conferred significantly better overall survival (OS) compared with those with medium and low immune scores (hazard ratio (HR), 0.305; 95% confidence interval (CI), 0.108-0.869). A nomogram with a C-index of 0.720 had a favorable performance for predicting survival rate for clinical use by combining immune scores with other clinical features. The calibration curves at 3 and 5 years suggested a good consistency between the predicted OS and the actual OS probability. Conclusions. Our work highlights the potential clinical application significance of immune score-based nomogram in predicting the OS of cervical cancer patients.

Immune-Inhibitory Gene Expression is Positively Correlated with Overall Immune Activity and Predicts Increased Survival Probability of Cervical and Head and Neck Cancer Patients

“…The heterogeneic nature of cancers including CESC thus requires methods for tumor stratification for prognostic purposes beyond the classical Tumor/Nodes/Metastasis (TNM) staging system, including the consensus Immunoscore ( Pagès et al, 2018 ; Angell et al, 2020 ). Identification of prognostic immune-related gene signatures and the “Immunophenoscore” facilitated retrospective patient stratification in CESC ( Charoentong et al, 2017 ; Thorsson et al, 2018 ; Yang et al, 2019 ; Nie et al, 2020 ; Qi et al, 2020 ) and will potentially guide immunotherapy selection to increase survival outcomes. However, identification of co-expressed immune networks will help to identify optimal targets for therapy.…”

Exploration of Immunogenic Cell Death-Associated Genes for Predicting Prognosis and Immunological Characteristics in Cervical Squamous Cell Carcinoma

“…Qi for subsequent analysis. Tis nomogram model can efectively predict the clinical outcomes of cervical cancer [37]. However, the correlation between their models and immune infltration was not clearly identifed.…”

Construction of an immune infiltration-associated ceRNA network and prognostic model for low-grade gliomas

“…Elevated immune scores were signi cantly associated with poor prognosis, consistent with the ndings of Chen et al ( 18), which prompted us to explore the potential association between immune scores and OS in LGG patients. Currently, elevated immune-related scores are associated with the survival and prognosis of tumor patients in breast, cervical, and prostate cancers (19)(20)(21)(22). Immune scores play an important role in the staging of various tumors, including colon and gastric cancers (23,24).…”