Deciphering the prognostic significance of anoikis-related lncRNAs in invasive breast cancer: from comprehensive bioinformatics analysis to functional experimental validation.

Abstract

The global prevalence of breast cancer necessitates the development of innovative prognostic markers and therapeutic strategies. This study investigated the prognostic implications of anoikis-related long non-coding RNAs (ARLs) in invasive breast cancer (IBC), which is an area that has not been extensively explored. By integrating the RNA sequence transcriptome and clinical data from The Cancer Genome Atlas (TCGA) database and employing advanced regression analyses, we devised a novel prognostic model based on ARL scores. ARL scores correlated with diverse clinicopathological parameters, cellular pathways, distinct mutation patterns, and immune responses, thereby affecting both immune cell infiltration and anticipated responses to chemotherapy and immunotherapy. Additionally, the overexpression of a specific lncRNA, AL133467.1, significantly impeded the proliferation and migration, as well as possibly the anoikis resistance of breast cancer cells. These findings highlight the potential of the ARL signature as a robust prognostic tool and a promising basis for personalized IBC treatment strategies.