Kannan, Nagarajan

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.

The fallopian tubes are critical segments of the female reproductive tract and are essential for transporting gametes and embryos. It creates a conducive environment necessary for successful fertilization, early embryo development, and embryo transport. The cellular composition and function of the fallopian tube are tightly regulated by the sex hormones estradiol and progesterone. Therefore, any pathological/ metabolic condition or exposure to exogenous agents with the potential to alter endocrine levels can have a significant impact on fallopian tube function and health. This review summarizes the effects of medications, infections, pathological conditions, lifestyle choices, and environmental factors that can significantly impact the morphology, histology, cellularity, and functionality of the fallopian tube.

ABSTRACT In our efforts to enhance sensitivity to PARP inhibitors, we identified clofarabine (CLF) as a potential therapy for drug-resistant ovarian cancer and nuclear trafficking of Cathepsin L (CTSL) as a treatment- responsive biomarker. Using PARP inhibitor-sensitive and -resistant OC cell lines, ex vivo cultures of patient-derived ovarian ascites (OVA), primary ovarian tumors, and xenografts (PDX), we found that CLF monotherapy induces nuclear CTSL (nCTSL) in CLF-responsive cells (CLF-r) and sensitizes them to PARP inhibitors olaparib and rucaparib. In CLF non-responsive cells (CLF-nr), a combination of CLF with olaparib is necessary for nCTSL trafficking and synergy. CLF+olaparib synergy was observed in 47% of CLF-r and 24% of CLF-nr OVA samples. Drug-induced nCTSL is crucial for DNA damage response, including cell cycle arrest and apoptosis. Knockdown of CTSL in both CLF-r and CLF-nr cells conferred resistance to the CLF+olaparib combination, emphasizing nCTSL’s role in the DNA damage response pathway (DDR). Mechanistically, CLF facilitates CTSL nuclear import via KPNB1 in CLF-r cells. In CLF-nr cells, both olaparib and CLF are needed to facilitate CTSL nuclear import. Additionally, CLF downregulates the nuclear export protein CRM1 (XPO1) in both cohorts. Interestingly, CLF does not downregulate CRM1 in a subset of OVAs (29%), and they were classified as CLF-resistant (CLF- Res). In these samples, inhibiting CRM1 with KPT8602 restored synergy between CLF and PARP inhibitors. In vivo, CLF-r and CLF-nr PDX models exhibited enhanced DDR, reduced tumor burden, and prolonged survival with the CLF+olaparib combination. These findings suggest the CLF+olaparib combination is a promising therapeutic strategy for drug-resistant OC by inducing DDR through CTSL nuclear localization.

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 Polycystic ovarian syndrome (PCOS) is a complex health condition associated with metabolic disturbances and infertility. Recent data suggest that the prevalence of PCOS is increasing among women globally, although the etiology of these trends is undefined. Consequently, preclinical models that better reflect the biology of PCOS are urgently needed to facilitate research that can lead to the discovery of prevention strategies or improved management. The existing animal models have several limitations as they do not reflect all the PCOS features metabolically and/or phenotypically. Therefore, there is no clear consensus on the use of appropriate animal model and selection of the most appropriate PCOS-inducing agent. To that end, we have established a Swiss albino mouse model of PCOS based on 3 weeks of daily treatment with letrozole (50 μg/day; intraperitoneal) and dehydroepiandrosterone (DHEA, 6 mg/100 g body weight; subcutaneous) in 5-week-old female mice fed on normal or high-fat diet (HFD). Mice were regularly assessed for body weight, blood glucose, and estrous cycle. Three weeks after drug administration, mice were sacrificed and assessed for blood-based metabolic parameters as well as ovarian function. Our results indicate that DHEA combined with HFD produces changes mimicking those of clinical PCOS, including elevated serum testosterone and luteinizing hormone, dyslipidemia, poor ovarian microenvironment, and development of multiple ovarian cysts, recapitulating cardinal features of PCOS. In comparison, normal diet and/or letrozole produced fewer features of PCOS. The data from the experimental models presented here can improve our understanding of PCOS, a growing concern in women’s health.

Abstract Abundant fibrotic stroma is a typical feature of most solid tumors, and stromal activation promotes oncogenesis, therapy resistance, and metastatic dissemination of cancer cells. Therefore, targeting the tumor stroma in combination with standard-of-care therapies has become a promising therapeutic strategy in recent years. The leucine-rich repeat-containing protein 15 (LRRC15) is involved in cell–cell and cell–matrix interactions and came into focus as a promising anticancer target owing to its overexpression in mesenchymal-derived tumors such as sarcoma, glioblastoma, and melanoma and in cancer-associated fibroblasts in the microenvironment of breast, head and neck, lung, and pancreatic tumors. Effective targeting of LRRC15 using specific antibody–drug conjugates (ADC) has the potential to improve the outcome of patients with LRRC15-positive (LRRC15+) cancers of mesenchymal origin or stromal desmoplasia. Moreover, LRRC15 expression may serve as a predictive biomarker that could be utilized in the preclinical assessment of cancer patients to support personalized clinical outcomes. This review focuses on the role of LRRC15 in cancer, including clinical trials involving LRRC15-targeted therapies, such as the ABBV-085 ADC for patients with LRRC15+ tumors. This review spans perceived knowledge gaps and highlights the clinical avenues that need to be explored to provide better therapeutic outcomes in patients.

Abstract Dissemination of ovarian cancer cells can lead to inoperable metastatic lesions in the bowel and omentum that cause patient death. Here we show that LRRC15, a type-I 15-leucine–rich repeat-containing membrane protein, highly overexpressed in ovarian cancer bowel metastases compared with matched primary tumors and acts as a potent promoter of omental metastasis. Complementary models of ovarian cancer demonstrated that LRRC15 expression leads to inhibition of anoikis-induced cell death and promotes adhesion and invasion through matrices that mimic omentum. Mechanistically, LRRC15 interacted with β1-integrin to stimulate activation of focal adhesion kinase (FAK) signaling. As a therapeutic proof of concept, targeting LRRC15 with the specific antibody–drug conjugate ABBV-085 in both early and late metastatic ovarian cancer cell line xenograft models prevented metastatic dissemination, and these results were corroborated in metastatic patient-derived ovarian cancer xenograft models. Furthermore, treatment of 3D-spheroid cultures of LRRC15-positive patient-derived ascites with ABBV-085 reduced cell viability. Overall, these data uncover a role for LRRC15 in promoting ovarian cancer metastasis and suggest a novel and promising therapy to target ovarian cancer metastases. Significance: This study identifies that LRRC15 activates β1-integrin/FAK signaling to promote ovarian cancer metastasis and shows that the LRRC15-targeted antibody–drug conjugate ABBV-085 suppresses ovarian cancer metastasis in preclinical models.

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.

AbstractSynthetic progestogens (progestins) have been linked to increased breast cancer risk; however, the role of endogenous progesterone in breast physiology and carcinogenesis is less clearly defined. Mechanistic studies using cell culture, tissue culture, and preclinical models implicate progesterone in breast carcinogenesis. In contrast, limited epidemiologic data generally do not show an association of circulating progesterone levels with risk, and it is unclear whether this reflects methodologic limitations or a truly null relationship. Challenges related to defining the role of progesterone in breast physiology and neoplasia include: complex interactions with estrogens and other hormones (eg, androgens, prolactin, etc.), accounting for timing of blood collections for hormone measurements among cycling women, and limitations of assays to measure progesterone metabolites in blood and progesterone receptor isotypes (PRs) in tissues. Separating the individual effects of estrogens and progesterone is further complicated by the partial dependence of PR transcription on estrogen receptor (ER)α-mediated transcriptional events; indeed, interpreting the integrated interaction of the hormones may be more essential than isolating independent effects. Further, many of the actions of both estrogens and progesterone, particularly in “normal” breast tissues, are driven by paracrine mechanisms in which ligand binding to receptor-positive cells evokes secretion of factors that influence cell division of neighboring receptor-negative cells. Accordingly, blood and tissue levels may differ, and the latter are challenging to measure. Given conflicting data related to the potential role of progesterone in breast cancer etiology and interest in blocking progesterone action to prevent or treat breast cancer, we provide a review of the evidence that links progesterone to breast cancer risk and suggest future directions for filling current gaps in our knowledge.