AFF3 is a Prognostic Biomarker Correlated with Immune Infiltrates in Triple-Negative Breast Cancer

Background: Triple-negative breast cancer (TNBC) is an aggressive type of breast cancer that cannot be treated with targeted therapies such as endocrine therapy or anti-HER-2 (anti-human epidermal growth factor receptor 2) therapy. In the growth of tumors, AFF3 (AF4/FMR2 family member 3) plays a critical role. This study aims to examine the prognostic value and immune-related functions of AFF3 in TNBC. Methods: In the Gene Expression Omnibus (GEO) database, differentially expressed genes (DEGs) were identified from three datasets associated with TNBC. Clinicopathologic characteristics, overall survival (OS) data and gene expression data of TNBC patients were acquired from The Cancer Genome Atlas (TCGA). The Kaplan-Meier analyses and proportional hazards model (Cox) regression were used to assess factors associated with OS, including gene expression levels and clinicopathological factors. Gene Ontology, the Kyoto Encyclopedia of Genes and Genomes were performed for the analysis of biological processes associated with DEGs related to TNBC. Gene Set Enrichment Analysis was used to analyze the biological processes associated with AFF3 in TNBC. Twenty-five paired primary TNBC tumor tissues and adjacent non-tumorous tissues were collected from patients at Jiangxi Cancer Hospital (Nanchang, China). Quantitative real-time polymerase chain reaction (qRT-PCR) and western blotting were performed to assess the mRNA and protein expression of AFF3 in these samples. Immune cell infiltration status of 152 TNBC samples was analyzed by CIBERSORT algorithm. Results: Seventy-five DEGs from three TNBC-related gene expression profiles in GEO database. Based on the L1000 fireworks display (L1000FWD) dataset, five small-molecule drugs which were potentially suitable for treating TNBC patients were obtained. Univariate and multivariate Cox analyses revealed that low AFF3 expression in TNBC patients was an independent prognostic factor for poor survival. AFF3 expression was comparatively analyzed in 152 TNBC samples. The CIBERSORT algorithm was used to examine immune cell infiltration in TNBC tumors, which provided useful insights into the interface between the immune system and TNBC. Conclusions: In TNBC, low AFF3 expression might be predictive of poor survival. AFF3 might provide additional insight into therapeutics in TNBC.