Cargando…

Immune Cell Infiltration and Relevant Gene Signatures in the Tumor Microenvironment that Significantly Associates With the Prognosis of Patients With Breast Cancer

Breast cancer is the most common malignancy and the leading cause of cancer-related deaths in women. Recent studies have investigated the prognostic value of the tumor microenvironment (TME)-related genes in breast cancer. The purpose of this research is to identify the immune-associated prognostic...

Descripción completa

Detalles Bibliográficos
Autores principales: Xu, Qiang, Yan, Xinghe, Han, Zhezhu, Jin, Xiuying, Jin, Yongmin, Sun, Honghua, Liang, Junhua, Zhang, Songnan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8905140/
https://www.ncbi.nlm.nih.gov/pubmed/35281270
http://dx.doi.org/10.3389/fmolb.2022.823911
Descripción
Sumario:Breast cancer is the most common malignancy and the leading cause of cancer-related deaths in women. Recent studies have investigated the prognostic value of the tumor microenvironment (TME)-related genes in breast cancer. The purpose of this research is to identify the immune-associated prognostic signature for breast cancer evaluate the probability of their prognostic value and compare the current staging system. In this study, we comprehensively evaluated the infiltration patterns of TME in 1,077 breast cancer patients downloaded from TCGA by applying the ssGSEA method to the transcriptome of these patients. Thus, generated two groups of immune cell infiltration. Based on two groups of low infiltration and high infiltration immune cell groups, 983 common differentially expressed genes were found using the limma algorithm. In addition, studying potential mechanisms, the GSEA method was used to indicate some pathways with remarkable enrichment in two clusters of immune cell infiltration. Finally, the seven immune-associated hub genes with survival as prognostic signatures were identified by using univariate Cox, survival, and LASSO analyses and constructed a TME score. The prognostic value of the TME score was self-validated in the TCGA cohort and further validated in an external independent set from METABRIC and GEO database by time-dependent survival receiver operation. Univariate and multivariate analyses of clinicopathological characteristics indicated that the TME score was an independent prognostic factor. In conclusion, the proposed TME score model should be considered as a prognostic factor, similar to the current TNM stage, and the seven immune-related genes can be a valuable potential biomarker for breast cancer.