Disruption of Circadian Clock Induces Abnormal Mammary Morphology and Aggressive Basal Tumorigenesis by Enhancing LILRB4 Signaling.

Epidemiological studies have shown that circadian rhythm disruption (CRD) is associated with the risk of breast cancer. However, the role of CRD in mammary gland morphology and aggressive basal mammary tumorigenesis and the molecular mechanisms underlying CRD and cancer risk remain unknown. To investigate the effect of CRD on aggressive tumorigenesis, a genetically engineered mouse model that recapitulates the human basal type of breast cancer was used for this study. The effect of CRD on mammary gland morphology was investigated using wild-type mice model. The impact of CRD on the tumor microenvironment was investigated using the tumors from LD12:12 and CRD mice via scRNA seq. ScRNA seq was substantiated by multiplexing immunostaining, flow cytometry, and realtime PCR. The effect of LILRB4 immunotherapy on CRD-induced tumorigenesis was also investigated. Here we identified the impact of CRD on basal tumorigenesis and mammary gland morphology and identified the role of LILRB4 on CRD-induced lung metastasis. We found that chronic CRD disrupted mouse mammary gland morphology and increased tumor burden, and lung metastasis and induced an immunosuppressive tumor microenvironment by enhancing LILRB4a expression. Moreover, CRD increased the M2-macrophage and regulatory T-cell populations but decreased the M1-macrophage populations. Furthermore, targeted immunotherapy against LILRB4 reduced CRD-induced immunosuppressive microenvironment and lung metastasis. These findings identify and implicate LILRB4a as a link between CRD and aggressive mammary tumorigenesis. This study also establishes the potential role of the targeted LILRB4a immunotherapy as an inhibitor of CRD-induced lung metastasis.

Joint Bayesian estimation of cell dependence and gene associations in spatially resolved transcriptomic data.

Recent technologies such as spatial transcriptomics, enable the measurement of gene expressions at the single-cell level along with the spatial locations of these cells in the tissue. Spatial clustering of the cells provides valuable insights into the understanding of the functional organization of the tissue. However, most such clustering methods involve some dimension reduction that leads to a loss of the inherent dependency structure among genes at any spatial location in the tissue. This destroys valuable insights of gene co-expression patterns apart from possibly impacting spatial clustering performance. In spatial transcriptomics, the matrix-variate gene expression data, along with spatial coordinates of the single cells, provides information on both gene expression dependencies and cell spatial dependencies through its row and column covariances. In this work, we propose a joint Bayesian approach to simultaneously estimate these gene and spatial cell correlations. These estimates provide data summaries for downstream analyses. We illustrate our method with simulations and analysis of several real spatial transcriptomic datasets. Our work elucidates gene co-expression networks as well as clear spatial clustering patterns of the cells. Furthermore, our analysis reveals that downstream spatial-differential analysis may aid in the discovery of unknown cell types from known marker genes.

Initiation of sacubitril/valsartan shortly after hospitalisation for acutely decompensated heart failure in patients with newly diagnosed (de novo) heart failure: a subgroup analysis of the TRANSITION study.

AIMS: Sacubitril/valsartan has shown efficacy and tolerability in patients with heart failure (HF) and reduced ejection fraction (HFrEF) in the ambulatory setting (PARADIGM-HF), and following stabilisation of acutely decompensated HF (ADHF) (PIONEER-HF and TRANSITION). However, data are lacking for the initiation of sacubitril/valsartan in newly diagnosed (de novo) HFrEF. Here, we assess the tolerability of initiating sacubitril/valsartan following ADHF in TRANSITION subgroups of patients with a de novo vs. prior diagnosis of HFrEF. METHODS AND RESULTS: TRANSITION randomised 1002 patients to pre- and post-discharge initiation of sacubitril/valsartan (analysis set n = 991, following exclusions for mis-randomisation). In this post-hoc analysis, tolerability to sacubitril/valsartan [proportion of patients achieving target dose (97/103 mg b.i.d.) at 10 weeks post-randomisation], adverse events (AEs) and serious AEs (SAEs) were compared in de novo (n = 286) and prior HFrEF (n = 705) subgroups. More de novo than prior HFrEF patients achieved target dose at Week 10 (56% vs. 45%; relative risk ratio 1.30, 95% confidence interval 1.12-1.52, P < 0.001), and fewer had SAEs and permanent treatment discontinuations. Initiation of sacubitril/valsartan did not prevent the concomitant initiation and up-titration of guideline-directed HF therapies. De novo patients showed faster and greater decreases in N-terminal pro-B-type natriuretic peptide and high-sensitivity troponin-T, and lower rates of HF and all-cause rehospitalisation vs. prior HFrEF. CONCLUSIONS: After ADHF, first-line initiation of sacubitril/valsartan in de novo HFrEF, alongside the initiation of other guideline-directed therapies, is feasible and is associated with a better risk-benefit profile than in patients with prior HFrEF. Early intervention with sacubitril/valsartan may be considered to delay disease progression in patients with de novo HFrEF. CLINICAL TRIAL REGISTRATION: ClinicalTrials.gov, NCT02661217.