Knapp, David J. H. F.

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.

T cells show tremendous efficacy as cellular therapeutics. However, obtaining primary T cells from human donors is expensive and variable. Pluripotent stem cells (PSCs) have the potential to provide a renewable source of T cells, but differentiating PSCs into hematopoietic progenitors with T cell potential remains an important challenge. Here, we report an efficient serum- and feeder-free system for differentiating human PSCs into hematopoietic progenitors and T cells. This fully defined approach allowed us to study the impact of individual proteins on blood emergence and differentiation. Providing DLL4 and VCAM1 during the endothelial-to-hematopoietic transition enhanced downstream progenitor T cell output by ~80-fold. These two proteins synergized to activate notch signaling in nascent hematopoietic stem and progenitor cells, and VCAM1 additionally promoted an inflammatory transcriptional program. We also established optimized medium formulations that enabled efficient and chemically defined maturation of functional CD8αβ + , CD4 − , CD3 + , TCRαβ + T cells with a diverse TCR repertoire.

Abstract A problematic feature of many human cancers is a lack of understanding of mechanisms controlling organ-specific patterns of metastasis, despite recent progress in identifying many mutations and transcriptional programs shown to confer this potential. To address this gap, we developed a methodology that enables different aspects of the metastatic process to be comprehensively characterized at a clonal resolution. Our approach exploits the application of a computational pipeline to analyze and visualize clonal data obtained from transplant experiments in which a cellular DNA barcoding strategy is used to distinguish the separate clonal contributions of two or more competing cell populations. To illustrate the power of this methodology, we demonstrate its ability to discriminate the metastatic behavior in immunodeficient mice of a well-established human metastatic cancer cell line and its co-transplanted LRRC15 knockdown derivative. We also show how the use of machine learning to quantify clone-initiating cell (CIC) numbers and their subsequent metastatic progeny generated in different sites can reveal previously unknown relationships between different cellular genotypes and their initial sites of implantation with their subsequent respective dissemination patterns. These findings underscore the potential of such combined genomic and computational methodologies to identify new clonally-relevant drivers of site-specific patterns of metastasis.

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.