Single-Cell Transcriptome Analysis Revealed Heterogeneity and Identified Novel Therapeutic Targets for Breast Cancer Subtypes

• Published in: Cells (Basel, Switzerland) Vol. 12; no. 8; p. 1182
• Main Authors: Vishnubalaji, Radhakrishnan, Alajez, Nehad M
• Format: Journal Article
• Language: English
• Published: Switzerland MDPI AG 01.04.2023; MDPI
• Subjects: Algorithms; Analysis; Apoptosis; Bioinformatics; Breast cancer; Care and treatment; Cell adhesion; Cell cycle; Cell death; Cell proliferation; Cells; Chaperonin Containing TCP-1 - genetics; Classification; Clustering; Communication; CRISPR; Diagnosis; Discriminant analysis; Epithelial cells; ErbB-2 protein; Estrogen receptors; Gene expression; Gene Expression Profiling; Gene set enrichment analysis; Genetic aspects; Glycolysis; Health aspects; Humans; Information retrieval; Medical prognosis; Mitosis; molecular subtypes; Molecular targeted therapy; Neoplasm Recurrence, Local; Organoids; Patient outcomes; Proteins; single cell analysis; Single-Cell Gene Expression Analysis; Stromal cells; Support vector machines; Survival analysis; Therapeutic applications; Therapeutic targets; TNBC; Transcriptome - genetics; Transcriptomes; Transcriptomics; Triple Negative Breast Neoplasms - pathology; Tumor microenvironment; Tumor Microenvironment - genetics; Tumor suppressor genes; Tumors; Qatar; United States > US; molecular subtypes; breast cancer; therapeutic targets; TNBC; single cell analysis
• ISSN: 2073-4409; 2073-4409
• DOI: 10.3390/cells12081182

Breast cancer (BC) is a heterogeneous disease, which is primarily classified according to hormone receptors and HER2 expression. Despite the many advances in BC diagnosis and management, the identification of novel actionable therapeutic targets expressed by cancerous cells has always been a daunting task due to the large heterogeneity of the disease and the presence of non-cancerous cells (i.e., immune cells and stromal cells) within the tumor microenvironment. In the current study, we employed computational algorithms to decipher the cellular composition of estrogen receptor-positive (ER ), HER2 , ER HER2 , and triple-negative BC (TNBC) subtypes from a total of 49,899 single cells' publicly available transcriptomic data derived from 26 BC patients. Restricting the analysis to EPCAM Lin tumor epithelial cells, we identified the enriched gene sets in each BC molecular subtype. Integration of single-cell transcriptomic with CRISPR-Cas9 functional screen data identified 13 potential therapeutic targets for ER , 44 potential therapeutic targets for HER2 , and 29 potential therapeutic targets for TNBC. Interestingly, several of the identified therapeutic targets outperformed the current standard of care for each BC subtype. Given the aggressive nature and lack of targeted therapies for TNBC, elevated expression of ENO1, FDPS, CCT6A, TUBB2A, and PGK1 predicted worse relapse-free survival (RFS) in basal BC ( = 442), while elevated expression of ENO1, FDPS, CCT6A, and PGK1 was observed in the most aggressive BLIS TNBC subtype. Mechanistically, targeted depletion of ENO1 and FDPS halted TNBC cell proliferation, colony formation, and organoid tumor growth under 3-dimensional conditions and increased cell death, suggesting their potential use as novel therapeutic targets for TNBC. Differential expression and gene set enrichment analysis in TNBC revealed enrichment in the cycle and mitosis functional categories in FDPS , while ENO1 was associated with numerous functional categories, including cell cycle, glycolysis, and ATP metabolic processes. Taken together, our data are the first to unravel the unique gene signatures and to identify novel dependencies and therapeutic vulnerabilities for each BC molecular subtype, thus setting the foundation for the future development of more effective targeted therapies for BC.