Tumor mutation burden in connection with immune-related survival in uterine corpus endometrial carcinoma

• Published in: Cancer cell international 2021-01, Vol.21 (1), p.80-80, Article 80
• Main Authors: Zhao, Ling, Fu, Xueshu, Han, Xiling, Yu, Yanjun, Ye, Yaping, Gao, Jun
• Format: Article
• Language: English
• Subjects: Age; Cancer therapies; Carcinoma; CD4 antigen; CD8 antigen; Cell survival; Chemotherapy; Endocrine therapy; Endometrial cancer; Endometrial carcinoma; Endometrium; Fibroblast growth factor 20; Gene expression; Genomes; Glial fibrillary acidic protein; Immune-related survival; Immunotherapy; Infiltration; Leukocytes (neutrophilic); Lymphocytes; Lymphocytes T; Macrophages; Malignancy; Medical prognosis; Metastases; Metastasis; Mutation; Nomograms; Primary Research; Protein interaction; Proteins; Radiation therapy; Regression analysis; Software; Survival analysis; TCGA; Tumor mutation burden; Uterine cancer; Uterus
• ISSN: 1475-2867; 1475-2867
• DOI: 10.1186/s12935-021-01774-6

UCEC is the most common gynecological malignancy in many countries, and its mechanism of occurrence and development is related to tumor mutation burden (TMB) and immune cell infiltration. Therefore, it is necessary to systematically explore the TMB-related gene profile in immune cells to improve the prognosis of UCEC. We integrated TMB-related genes with basic clinical information of UCEC patients based on TCGA dataset. Differentially expressed genes (DEGs) were selected through differential expression screening, PPI, and enrichment analysis. Additionally, we analyzed the components of immune cell infiltration of the DEGs to obtain the differential immunity-related genes. A single factor and multifactor Cox regression analyses were conducted to establish new prognostic indicators of OS and DFS based on TMB-related immune genes. To further study the correlation between survival and immune cell infiltration, a Cox model based on these immune infiltration compositions was built. Using the clinical variables, we established nomograms for OS and DFS. 393 DEGs were significantly associated with clinical outcomes and the immune component in patients with UCEC. Gene Ontology (GO) and Kyoto Encyclopedia of Genes, Genomes (KEGG) pathway and protein-protein interaction network (PPI) analyses revealed the role of these genes and information on related pathways. Then, two prognostic models were established based on the differential immune genes for OS (GFAP and MX2) and DFS (MX2, GFAP, IGHM, FGF20, and TRAV21). In DFS, the differential immune genes were related to CD4+ T cell, CD8+ T cell, macrophage, and neutrophil (all P