Abstract
Uterine Corpus Endometrial Carcinoma (UCEC) is the most common gynecological cancer. Here, we have investigated the significance of immune-related genes in predicting the prognosis and response of UCEC patients to immunotherapy and chemotherapy. Based on the Cancer Genome Atlas (TCGA) database, the single-sample gene-set enrichment analysis (ssGSEA) scores was utilized to obtain enrichment of 29 immune signatures. Univariate, multivariate Cox regression and least absolute shrinkage and selection operator (LASSO) regression analyses were performed to generate an immune-related prognostic signature (IRPS). The biological functions of IRPS-associated genes were evaluated using GSEA, Tumor Immune Estimation Resource (TIMER) Database analysis, Mutation analysis, Immunophenoscore (IPS) analysis, Gene Expression Profiling Interactive Analysis (GEPIA), Genomics of Drug Sensitivity in Cancer (GDSC) and Immune Cell Abundance Identifier (ImmuCellAI). Potential small molecule drugs for UCEC were predicted using the connectivity map (Cmap). The mRNA and protein expression levels of IRPS-associated genes were tested via quantitative real-time PCR (qPCR) and immunohistology. Two immune-related genes (CCL13 and KLRC1) were identified to construct the IRPS. Both genes were related to the prognosis of UCEC patients (P < 0.05). The IRPS could distinguish patients with different prognosis and was closely associated with the infiltration of several types of immune cells. Our findings showed that patients with low IRPS benefited more from immunotherapy and developed stronger response to several chemotherapies, which was also confirmed by the results of ImmuCellAI. Finally, we identified three small molecular drugs that might improve the prognosis of patients with high IRPS. IRPS can be utilized to predict the prognosis of UCEC patients and provide valuable information about their therapeutic response to immunotherapy and chemotherapy.
Highlights
MATERIALS AND METHODSUterine Corpus Endometrial Carcinoma (UCEC) is the most common gynecological cancer
With the help of the singlesample gene-set enrichment analysis (ssGSEA) scores of 29 immune signatures and R package “hclust”, we divided the patients into three clusters according to immune infiltration: Immunity High (Immunity_H), Immunity Medium (Immunity_M), and Immunity Low (Immunity_L)
In this research, we developed a model for predicting the survival and therapeutic response of UCEC patients using two immune-related genes
Summary
Uterine Corpus Endometrial Carcinoma (UCEC) is the most common gynecological cancer. In 2018, 382,069 new cases and 89,929 deaths were reported worldwide (Bray et al, 2018). We identified two immune-related genes, their different expression levels have significant prognostic value, and developed a model for predicting the survival and therapeutic response of UCEC patients. The risk score for patients in training set, testing set and total set was calculated using the following equation: CCL13 in UCEC and evaluated their correlation with the infiltration of immune cells. Based on IRPS, patients were divided into different groups, the different expression genes with a fold change (FC) > 1 and an adjusted P-value < 0.05 were identified using R package “limma”. To further verify the correlation of KLRC1 and CCL13 expression with immune cells markers, the Gene Expression Profiling Interactive Analysis (GEPIA) database was employed. Two-side statistical analyses were performed and samples with P-value < 0.05 were considered statistically significant
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