Basement Membrane-Related Long Non-Coding RNA Signature Predicts the Prognosis of Breast Cancer

In this study, it was reported that basement membrane-associated long non-coding ribonucleic acid predicts prognosis and effectively enhances the individualized treatment of breast cancer by effectively identifying hot and cold tumors. Breast cancer transcriptional sequencing data were downloaded from The Cancer Genome Atlas and searched for prognostic long non-coding ribonucleic acids associated with basement membrane by univariate Cox regression and co-expression analysis. The least absolute shrinkage and selection operator analysis was employed to investigate the long non-coding ribonucleic acid prognostic model that is related to the basement membrane. Then, the following analyses were used to validate and evaluate the model, including univariate Cox regression, Kaplan-Meier analysis, multivariate Cox regression, receiver operating characteristic curve, calibration curves and nomogram. Immunoassay, principal component analysis, immunocytometric analysis and half-maximal inhibitory concentration analysis were conducted on the risk groups. To distinguish cold and hot tumors in terms of drug immunotherapy sensitivity, all inflammation-related long non-coding ribonucleic acids were divided into two groups. A model containing 4 basement membrane -related long non-coding ribonucleic acids was developed in this study. The area under the receiver operating characteristic curve was 0.742, 0.759 and 0.840 for 1, 2 and 3 y, respectively. High-risk patients were associated with tumor invasion and immunity and had a high immune infiltration status. Immune cells and checkpoints were infiltrated and activated in the high-risk group. Hot and cold tumors could be effectively distinguished by tumor clusters. Among the two clusters, cluster 2 was identified as hot tumors, which indicated that they were more sensitive to immunotherapeutic agents. This study provides evidence to support the hypothesis that basement membrane-related long non-coding ribonucleic acids can accurately predict patient prognosis and differentiate between hot and cold tumors. As a result, individualized immunotherapy for breast cancer patients will be improved and patients will have access to new treatment options.