A Novel Prognostic Signature of Immune-Related Long Noncoding RNA Pairs for Tumor-Infiltrating Immune Cells and Drug Susceptibility in Breast Cancer

Prognostic signatures of specific immune-related long noncoding RNAs (irlncRNAs) have been elucidated with the development of immunotherapy for breast cancer, but the heterogeneity of gene expression in different patients still limits their effectiveness. We constructed a new prognostic signature based on the relative expression of differentially expressed irlncRNA (DEirlncRNA) pairs and analyzed its clinical application in 1069 patients from The Cancer Genome Atlas-Breast Cancer (TCGA-BRCA) containing 745 White patients, 180 Black and African American patients, 58 Asian patients, 181 stage I patients, 606 stage II patients, 240 stage III patients, and 20 stage IV patients. Data from TCGA-BRCA and ImmPort were used to screen DEirlncRNAs, and the DEirlncRNA pairs were established by cyclical single comparison of each DEirlncRNA. After the data optimization, we constructed a signature containing 24 DEirlncRNA pairs. Risk groups of this signature were defined using the cutoff value from the 10-year survival receiver operating characteristic curve, and Kaplan-Meier analysis verified its prognostic effectiveness. Furthermore, we confirmed this signature as an independent prognostic factor and confirmed its close association with traditional clinicopathological factors. Moreover, this risk signature was closely related to tumor-infiltrating immune cells and drug susceptibility. In short, we successfully constructed a risk signature of DEirlncRNA pairs, which might provide new insights for breast cancer precision therapy.

Automated summary

A prognostic signature containing 24 DEirlncRNA pairs was successfully constructed and verified for its effectiveness in predicting breast cancer outcomes. The signature was confirmed as an independent prognostic factor closely associated with traditional clinicopathological factors, tumor-infiltrating immune cells, and drug susceptibility. This risk signature may provide new insights for precision therapy in breast cancer.