Integrative Single-Cell Transcriptomics and Co-Expression Network Analysis Identify SIMALR as a Prognostic Immune-Related LncRNA in Breast Cancer: In Silico Analysis and Validation

Abstract Purpose This study aimed to identify and characterize irLncRNAs associated with prognosis and immune modulation in breast cancer. Methods We integrated single-cell RNA sequencing hdWGCNA and bulk RNA-seq differential expression analysis results to identify candidate irLncRNAs. The top candidate, SIMALR, was further investigated using immune, survival, mutation analysis, and GSEA. RT-qPCR validation was performed on patient tissues. Results SIMALR was linked to favorable survival and enriched in immune pathways, including T-cell receptor signaling, Natural Killer (NK) cell cytotoxicity, and antigen processing. Pearson analysis showed co-expression of SIMALR-related genes (CD8A, CD4, TNF, LCP2, ITGB2) in key immune populations. SIMALR expression correlated with recruitment of M1 macrophages, CD8 + T cells, and memory CD4 + T cells. Mutation profiling associated SIMALR with alterations in TP53 and other cancer-related genes. RT-qPCR confirmed higher SIMALR expression in tumors. Discussion SIMALR may contribute to anti-tumor immunity, highlighting its potential as a promising biomarker and therapeutic target in breast cancer. Clinical significance Breast cancer remains a significant cause of mortality in women, and its heterogeneity complicates prognosis and treatment. Therefore, discovering novel biomarkers could improve therapeutic decisions. This study explored SIMALR, a LncRNA that contributes to cancer-associated fibroblast activity. By combining hdWGCNA network analysis, RNA-Seq data analysis, and RT-qPCR validation in tissues, we found that SIMALR expression correlates with immune cell recruitment and survival outcomes. These findings highlight its potential as a clinically relevant biomarker for determining prognosis and targeted therapeutic strategies in breast cancer.