Emperumal, Chitra Priya

ABSTRACT The normal adult male breast has not been characterized at single-cell resolution, leaving the cellular basis of male breast cancer (MBC) biology undefined. Here we present an integrated single-cell RNA sequencing atlas of the adult human breast comprising 174,471 cells from 17 donors (3 male, 14 female), including 18,117 male-derived cells. This revealed that the male breast retains all three epithelial populations, basal (BC), luminal progenitor (LP), and luminal committed cells (LC), but with an increase in LC at the expense of BC and LP across all three male donors. Male LC were distinguished from female by elevated ESR1 and PGR mRNA, enrichment of RNA processing and ribosome biogenesis programs, reduced inflammatory cytokine and growth factor signaling, elevated estradiol gene set enrichment scores, and higher inferred activity of developmental patterning transcription factors. This pattern was observed across differential expression, gene ontology, ligand profiling, and regulon-based analyses, and was not restricted to sex chromosome-linked gene expression. This is consistent with the near-universal estrogen receptor (ER) positivity that characterizes MBC clinically. This atlas provides the first cellular and transcriptional reference for the normal male breast and a resource for investigating sex differences in mammary biology, germline susceptibility variant interpretation, and modeling breast malignancies.

e18055 Background: Entrectinib, a TRK kinase inhibitor, has been approved for the treatment of tissue agnostic rare tumors positive for TRK fusions. A very low frequency molecular subset of TRK fusion tumors dubbed as secretory carcinoma (SC) are characterized by organ-agnostic epithelial origin, ETV6-NTRK3 (EN) fusion and distinguishable secretory-type tumor cells. These tumors have been frequently miscategorized as acinic cell carcinoma or adenocarcinoma. A previous mouse study identified EGF dependent epithelial progenitors as putative cell-of-origin for SC. Methods: To test the role of EGFR signaling in EN mediated transformation and therapy resistance, we expressed EN, kinase-dead EN-K380M, and drug-resistant EN-G623R in human epithelial MCF10A cells with EGF-dependent primitive function and investigated their ability to grow in the presence and absence of EGF and/or entrectinib. To understand the significance of findings based on our model, we analyzed a total of 22 ‘rare’ patients from Mayo Clinic Tissue Registry and analyzed TCGA PanCan datasets. Results: We report herein that EGF signaling is essential for normal growth but dispensable during EN driven transformation. Our findings suggest that levels equivalent to circulating EGF (0.5-1ng/ml) is sufficient to drive 100% resistance to entrectinib in vitro. Three different strategies to blockade EGF/EGFR axis including depletion of EGF in culture system, genetic depletion of EGFR using shRNA as well as cetuximab antibody-based EGFR neutralization potentiated oncogene-addiction and hypersensitivity to entrectinib in our models. As predicted, models with G623R mutation in EN was refractory to entrectinib under all experimental conditions. Further omics analysis of TCGA PanCan suggested that EN and EGFR mutations are mutually exclusive and entrectinib-resistant G623R mutation were uncommon. Interestingly, nearly all EN tumors from Mayo Clinic Tissue Registry immunostained weakly or strongly for EGFR and showed perfect concordance with pEGFR suggesting pathway activation. Conclusions: Together, these findings raise an important question whether blockade of ‘wildtype’ EGFR signaling could improve medical intervention in SC patients presenting with wildtype EGFR and no drug-resistant mutation in entrectinib, by improving oncogene-addiction and attendant hypersensitization of transformed cells to entrectinib.

Abstract COVID-19 patients show significant clinical heterogeneity in presentation and outcomes that makes pandemic control and strategy difficult; optimising management requires a systems biology approach of understanding the disease. Here we sought to understand and infer complex system-wide changes in patients infected with coronaviruses (SARS-CoV and SARS-CoV-2; n=38 and 57 samples) at two different disease stages compared with healthy individuals (n=16) and patients with other infections (n=144). We applied inferential statistics/machine-learning approaches (the COVID-engine platform) to RNA profiles derived from peripheral blood mononuclear cells (PBMCs). Compared to healthy individuals, an integrated blood-based gene signatures distinguished acute-like (mimicking coronavirus-infected patients with prolonged hospitalisation) from recovering-like patients. These signatures also hierarchically represented systems-level parameters associated with PBMC including dysregulated cytokines, genes, pathways, networks of pathways/concepts, immune status, and cell types. Proof-of-principle confirmatory observations included PBMC-associated increases in ACE2, cytokine storm-associated IL6, enhanced innate immunity (macrophages and neutrophils), and lower adaptive T and B cell immunity in patients with acute-like disease compared to those with recovery-like disease. Patients in the recovery-like stage had significantly enhanced TNF, IFN-g, anti-viral, HLA-DQA1, and HLA-F gene expression and cytolytic activity, and reduced pro-viral gene expression compared to those in the acute-like stage in PBMC. Besides, PBMC-derived surrogate-based approach revealed overlapping genes associated with comorbidities (associated diabetes), and disease-like symptoms (associated with thromboembolism, pneumonia, lung disease and septicaemia). Overall, our study involving PBMC-based RNA profiling may further help understand complex and variable systems-wide responses displayed by coronavirus-infected patients.