Novel immune-related genes in the tumor microenvironment with prognostic value in breast cancer

Abstract

Background Breast cancer is one of the most frequently diagnosed cancers among women worldwide. Alterations in the tumor microenvironment (TME) have been increasingly recognized as key in the development and progression of breast cancer in recent years. To deeply comprehend the gene expression profiling of the TME and identify immunological targets, as well as determine the relationship between gene expression and different prognoses is highly critical. Methods The stromal/immune scores of breast cancer patients from The Cancer Genome Atlas (TCGA) were employed to comprehensively evaluate the TME. Then, TME characteristics were assessed, overlapping genes of the top 3 Gene Ontology (GO) terms and upregulated differentially expressed genes (DEGs) were analyzed. Finally, through combined analyses of overall survival, time-dependent receiver operating characteristic (ROC), and protein-protein interaction (PPI) network, novel immune related genes with good prognosis were screened and validated in both TCGA and GEO database. Results Although the TME did not correlate with the stages of breast cancer, it was closely associated with the subtypes of breast cancer and gene mutations (CDH1, TP53 and PTEN), and had immunological characteristics. Based on GO functional enrichment analysis, the upregulated genes from the high vs low immune score groups were mainly involved in T cell activation, the external side of the plasma membrane, and receptor ligand activity. The top GO terms of the upregulated DEGs from the high vs low immune score groups exhibited better prognosis in breast cancer; 15 of them were related to good prognosis in breast cancer, especially CD226 and KLRC4-KLRK1. Conclusions High CD226 and KLRC4-KLRK1 expression levels were identified and validated to correlate with better overall survival in specific stages or subtypes of breast cancer. CD226, KLRC4-KLRK1 and other new targets seem to be promising avenues for promoting antitumor targeted immunotherapy in breast cancer.

Identifying tumour microenvironment-related signature that correlates with prognosis and immunotherapy response in breast cancer

“…Consistent with our results, oncogene TP53 mutation is a known detrimental prognostic factor in breast cancer patients and MAP3K1 mutations are relevant to shorter survival in metastatic breast cancer 40 , 41 . Our findings are consistent with previous studies showing that TP53 and MAP3K1 mutations revealed a highly increased risk of breast cancer 42 . In the low-risk score group, the mutation frequency of CDH1 (P < 0.001) is significantly upregulated when comparing with the high-risk group.…”

“…In the low-risk score group, the mutation frequency of CDH1 (P < 0.001) is significantly upregulated when comparing with the high-risk group. CDH1 mutated patients exhibited higher immune scores than wild-type patients in breast cancer, which supports our results that the TME of breast cancers correlates with CDH1 mutations 42 . Importantly, the mutation frequencies of 92.4% mutated genes were not high in the BRCA samples (mutation rate < 5%; mean mutation rate = 2.5%), but they showed significantly different mutation frequencies between the high and low risk score groups.…”

An Aging-Related Gene Signature-Based Model for Risk Stratification and Prognosis Prediction in Breast Cancer

“…With the advancement of freely available public TCGA and GEO databases, risk prognostic models for BC combining RNA sequencing data and clinicopathological factors have been rapidly established. 4,27 However, most models are limited to factors such as ferroptosis, energy metabolism, autography, immune infiltration, and long non-coding RNAs, [28][29][30][31][32] and few have been clinically extended. In addition, there are few specific studies about the prognostic role of the ARG risk signatures in BC.…”

Genetic Heterogeneity, Tumor Microenvironment and Immunotherapy in Triple-Negative Breast Cancer

“…In addition to more conventional intracellular markers, tumor-microenvironment markers, such as the level of hypoxia or pH, can be utilized for TNBC diagnosis and predication of model of tumor growth and spread. The specific formation of the tumor microenvironment is associated with abnormalities in expression of various immune-related genes [ 91 , 92 , 93 , 94 ]. Hypoxia, which is typical of fast-growing breast tumors, is linked to metabolic reprogramming, stem cell signatures, angiogenesis, extracellular matrix organization, and cancer cell metastasis [ 95 , 96 , 97 ].…”