The Breast Cancer Single-Cell Atlas: Defining cellular heterogeneity within model cell lines and primary tumors to inform disease subtype, stemness, and treatment options.

PURPOSE: Breast Cancer (BC) is the most diagnosed cancer in women; however, through significant research, relative survival rates have significantly improved. Despite progress, there remains a gap in our understanding of BC subtypes and personalized treatments. This manuscript characterized cellular heterogeneity in BC cell lines through scRNAseq to resolve variability in subtyping, disease modeling potential, and therapeutic targeting predictions. METHODS: We generated a Breast Cancer Single-Cell Cell Line Atlas (BSCLA) to help inform future BC research. We sequenced over 36,195 cells composed of 13 cell lines spanning the spectrum of clinical BC subtypes and leveraged publicly available data comprising 39,214 cells from 26 primary tumors. RESULTS: Unsupervised clustering identified 49 subpopulations within the cell line dataset. We resolve ambiguity in subtype annotation comparing expression of Estrogen Receptor, Progesterone Receptor, and Human Epidermal Growth Factor Receptor 2 genes. Gene correlations with disease subtype highlighted S100A7 and MUCL1 overexpression in HER2 + cells as possible cell motility and localization drivers. We also present genes driving populational drifts to generate novel gene vectors characterizing each subpopulation. A global Cancer Stem Cell (CSC) scoring vector was used to identify stemness potential for subpopulations and model multi-potency. Finally, we overlay the BSCLA dataset with FDA-approved targets to identify to predict the efficacy of subpopulation-specific therapies. CONCLUSION: The BSCLA defines the heterogeneity within BC cell lines, enhancing our overall understanding of BC cellular diversity to guide future BC research, including model cell line selection, unintended sample source effects, stemness factors between cell lines, and cell type-specific treatment response.

Network-based assessment of HDAC6 activity predicts preclinical and clinical responses to the HDAC6 inhibitor ricolinostat in breast cancer.

Inhibiting individual histone deacetylase (HDAC) is emerging as well-tolerated anticancer strategy compared with pan-HDAC inhibitors. Through preclinical studies, we demonstrated that the sensitivity to the leading HDAC6 inhibitor (HDAC6i) ricolinstat can be predicted by a computational network-based algorithm (HDAC6 score). Analysis of ~3,000 human breast cancers (BCs) showed that ~30% of them could benefice from HDAC6i therapy. Thus, we designed a phase 1b dose-escalation clinical trial to evaluate the activity of ricolinostat plus nab-paclitaxel in patients with metastatic BC (MBC) (NCT02632071). Study results showed that the two agents can be safely combined, that clinical activity is identified in patients with HR+/HER2- disease and that the HDAC6 score has potential as predictive biomarker. Analysis of other tumor types also identified multiple cohorts with predicted sensitivity to HDAC6i's. Mechanistically, we have linked the anticancer activity of HDAC6i's to their ability to induce c-Myc hyperacetylation (ac-K148) promoting its proteasome-mediated degradation in sensitive cancer cells.

In vitro modeling of hepatocellular carcinoma molecular subtypes for anti-cancer drug assessment.

Tractable experimental model that accounts for inter-tumor molecular heterogeneity is a key element of anti-cancer drug development. Hepatocellular carcinoma is known to exhibit highly heterogeneous molecular aberrations across the tumors, including somatic genetic and epigenetic alterations. Previous studies showed that molecular tumor subtypes determined by transcriptome, as a comprehensive functional readout, are reproducibly observed across global patient populations irrespective of geographic and etiological variations. Here we demonstrate that transcriptomic hepatocellular carcinoma subtypes, S1 and S2, determined by our previous transcriptome meta-analysis of multiple clinical hepatocellular carcinoma cohorts, are presented in a panel of hepatoma cell lines widely used by the research community. Interestingly, cell line that resembles gene expression pattern of S3 subtype, representing less aggressive tumors, was not identified in the panel. MYC pathway-activated S2-like cell lines showed higher sensitivity to a small molecule BET bromodomain inhibitor, (+)-JQ1, which has anti-MYC activity. These results support the use of hepatoma cell lines as models to evaluate molecular subtype-specific drug response, which is expected to lead to development of tailored, precision care of the patients with hepatocellular carcinoma.

miR-424(322)/503 is a breast cancer tumor suppressor whose loss promotes resistance to chemotherapy.

The female mammary gland is a very dynamic organ that undergoes continuous tissue remodeling during adulthood. Although it is well established that the number of menstrual cycles and pregnancy (in this case transiently) increase the risk of breast cancer, the reasons are unclear. Growing clinical and experimental evidence indicates that improper involution plays a role in the development of this malignancy. Recently, we described the miR-424(322)/503 cluster as an important regulator of mammary epithelial involution after pregnancy. Here, through the analysis of ∼3000 primary tumors, we show that miR-424(322)/503 is commonly lost in a subset of aggressive breast cancers and describe the genetic aberrations that inactivate its expression. Furthermore, through the use of a knockout mouse model, we demonstrate for the first time that loss of miR-424(322)/503 promotes breast tumorigenesis in vivo. Remarkably, we found that loss of miR-424(322)/503 promotes chemoresistance due to the up-regulation of two of its targets: BCL-2 and insulin-like growth factor-1 receptor (IGF1R). Importantly, targeted therapies blocking the aberrant activity of these targets restore sensitivity to chemotherapy. Overall, our studies reveal miR-424(322)/503 as a tumor suppressor in breast cancer and provide a link between mammary epithelial involution, tumorigenesis, and the phenomenon of chemoresistance.

Antimitotic activity of DY131 and the estrogen-related receptor beta 2 (ERRß2) splice variant in breast cancer.

Breast cancer remains a leading cause of cancer-related death in women, and triple negative breast cancer (TNBC) lacks clinically actionable therapeutic targets. Death in mitosis is a tumor suppressive mechanism that occurs in cancer cells experiencing a defective M phase. The orphan estrogen-related receptor beta (ERRß) is a key reprogramming factor in murine embryonic and induced pluripotent stem cells. In primates, ERRß is alternatively spliced to produce several receptor isoforms. In cellular models of glioblastoma, short form (ERRßsf) and beta2 (ERRß2) splice variants differentially regulate cell cycle progression in response to the synthetic agonist DY131, with ERRß2 driving arrest in G2/M.The goals of the present study are to determine the cellular function(s) of ligand-activated ERRß splice variants in breast cancer and evaluate the potential of DY131 to serve as an antimitotic agent, particularly in TNBC. DY131 inhibits growth in a diverse panel of breast cancer cell lines, causing cell death that involves the p38 stress kinase pathway and a bimodal cell cycle arrest. ERRß2 facilitates the block in G2/M, and DY131 delays progression from prophase to anaphase. Finally, ERRß2 localizes to centrosomes and DY131 causes mitotic spindle defects. Targeting ERRß2 may therefore be a promising therapeutic strategy in breast cancer.