Soaring cases of coronavirus disease (COVID-19) are pummeling the global health system. Overwhelmed health facilities have endeavored to mitigate the pandemic, but mortality of COVID-19 continues to increase. Here, we present a mortality risk prediction model for COVID-19 (MRPMC) that uses patients’ clinical data on admission to stratify patients by mortality risk, which enables prediction of physiological deterioration and death up to 20 days in advance. This ensemble model is built using four machine learning methods including Logistic Regression, Support Vector Machine, Gradient Boosted Decision Tree, and Neural Network. We validate MRPMC in an internal validation cohort and two external validation cohorts, where it achieves an AUC of 0.9621 (95% CI: 0.9464–0.9778), 0.9760 (0.9613–0.9906), and 0.9246 (0.8763–0.9729), respectively. This model enables expeditious and accurate mortality risk stratification of patients with COVID-19, and potentially facilitates more responsive health systems that are conducive to high risk COVID-19 patients.

High-grade serous ovarian cancer (HGSOC) is hallmarked by early onset of peritoneal dissemination, which distinguishes it from low-grade serous ovarian cancer (LGSOC). Here, we describe the aggressive nature of HGSOC ascitic tumor cells (ATCs) characterized by integrin α5^high (ITGA5^high) ATCs, which are prone to forming heterotypic spheroids with fibroblasts. We term these aggregates as metastatic units (MUs) in HGSOC for their advantageous metastatic capacity and active involvement in early peritoneal dissemination. Intriguingly, fibroblasts inside MUs support ATC survival and guide their peritoneal invasion before becoming essential components of the tumor stroma in newly formed metastases. Cancer-associated fibroblasts (CAFs) recruit ITGA5^high ATCs to form MUs, which further sustain ATC ITGA5 expression by EGF secretion. Notably, LGSOC is largely devoid of CAFs and the resultant MUs, which might explain its metastatic delay. These findings identify a specialized MU architecture that amplifies the tumor–stroma interaction and promotes transcoelomic metastasis in HGSOC, providing the basis for stromal fibroblast-oriented interventions in hampering OC peritoneal propagation.

Macrophages play diverse roles in development, homeostasis, and immunity. Accordingly, the dysfunction of macrophages is involved in the occurrence and progression of various diseases, such as coronavirus disease 2019 and atherosclerosis. The protective or pathogenic effect that macrophages exert in different conditions largely depends on their functional plasticity, which is regulated via signal transduction such as Janus kinase–signal transducer and activator of transcription, Wnt and Notch pathways, stimulated by environmental cues. Over the past few decades, the molecular mechanisms of signaling pathways in macrophages have been gradually elucidated, providing more alternative therapeutic targets for diseases treatment. Here, we provide an overview of the basic physiology of macrophages and expound the regulatory pathways within them. We also address the crucial role macrophages play in the pathogenesis of diseases, including autoimmune, neurodegenerative, metabolic, infectious diseases, and cancer, with a focus on advances in macrophage‐targeted strategies exploring modulation of components and regulators of signaling pathways. Last, we discuss the challenges and possible solutions of macrophage‐targeted therapy in clinical applications. We hope that this comprehensive review will provide directions for further research on therapeutic strategies targeting macrophage signaling pathways, which are promising to improve the efficacy of disease treatment.

TGF1 in fibroblasts-derived exosomes promotes epithelial-mesenchymal transition of ovarian cancer cells TGFβ1 in fibroblasts-derived exosomes promotes epithelial-mesenchymal transition of ovarian cancer cells