Hypoxia, a driver of tumor growth and metastasis, regulates angiogenic pathways that are targets for vessel normalization and ovarian cancer management. However, toxicities and resistance to anti-angiogenics can limit their use making identification of new targets vital. Inhibin, a heteromeric TGFβ ligand, is a contextual regulator of tumor progression acting as an early tumor suppressor, yet also an established biomarker for ovarian cancers. Here, we find that hypoxia increases inhibin levels in ovarian cancer cell lines, xenograft tumors, and patients. Inhibin is regulated primarily through HIF-1, shifting the balance under hypoxia from activins to inhibins. Hypoxia regulated inhibin promotes tumor growth, endothelial cell invasion and permeability. Targeting inhibin in vivo through knockdown and anti-inhibin strategies robustly reduces permeability in vivo and alters the balance of pro and anti-angiogenic mechanisms resulting in vascular normalization. Mechanistically, inhibin regulates permeability by increasing VE-cadherin internalization via ACVRL1 and CD105, a receptor complex that we find to be stabilized directly by inhibin. Our findings demonstrate direct roles for inhibins in vascular normalization via TGF-β receptors providing new insights into the therapeutic significance of inhibins as a strategy to normalize the tumor vasculature in ovarian cancer.

Dissemination is an essential early step in metastasis but its molecular basis remains incompletely understood. To define the essential targetable effectors of this process, we developed a 3D mammary epithelial culture model, in which dissemination is induced by overexpression of the transcription factor Twist1. Transcriptomic analysis and ChIP-PCR together demonstrated that protein kinase D1 (Prkd1) is a direct transcriptional target of Twist1 and is not expressed in the normal mammary epithelium. Pharmacologic and genetic inhibition of Prkd1 in the Twist1induced dissemination model demonstrated that Prkd1 was required for cells to initiate extracellular matrix (ECM)-directed protrusions, release from the epithelium, and migrate through the ECM. Antibody-based protein profiling revealed that Prkd1 induced broad phosphorylation changes, including an inactivating phosphorylation of b-catenin and two microtubule depolymerizing phosphorylations of Tau, potentially explaining the release of cell-cell contacts and persistent activation of Prkd1. In patients with breast cancer, TWIST1 and PRKD1 expression correlated with metastatic recurrence, particularly in basal breast cancer. Prkd1 knockdown was sufficient to block dissemination of both murine and human mammary tumor organoids. Finally, Prkd1 knockdown in vivo blocked primary tumor invasion and distant metastasis in a mouse model of basal breast cancer. Collectively, these data identify Prkd1 as a novel and targetable signaling node downstream of Twist1 that is required for epithelial invasion and dissemination.

Summary Organoid model systems recapitulate key features of mammalian tissues and enable high throughput experiments. However, the impact of these experiments may be limited by manual, non-standardized, static or qualitative phenotypic analysis. OrgDyn is an open-source and modular pipeline to quantify organoid shape dynamics using a combination of feature- and model-based approaches on time series of 2D organoid contour images. Our pipeline consists of (i) geometrical and signal processing feature extraction, (ii) dimensionality reduction to differentiate dynamical paths, (iii) time series clustering to identify coherent groups of organoids and (iv) dynamical modeling using point distribution models to explain temporal shape variation. OrgDyn can characterize, cluster and model differences among unique dynamical paths that define diverse final shapes, thus enabling quantitative analysis of the molecular basis of tissue development and disease. Availability and Implementation https://github.com/zakih/organoidDynamics (BSD 3-Clause License). Supplementary information Supplementary data are available at Bioinformatics online.

Inhibins and activins are dimeric ligands belonging to the TGFβ superfamily with emergent roles in cancer. Inhibins contain an α-subunit (INHA) and a β-subunit (either INHBA or INHBB), while activins are mainly homodimers of either βA (INHBA) or βB (INHBB) subunits. Inhibins are biomarkers in a subset of cancers and utilize the coreceptors betaglycan (TGFBR3) and endoglin (ENG) for physiological or pathological outcomes. Given the array of prior reports on inhibin, activin and the coreceptors in cancer, this study aims to provide a comprehensive analysis, assessing their functional prognostic potential in cancer using a bioinformatics approach. We identify cancer cell lines and cancer types most dependent and impacted, which included p53 mutated breast and ovarian cancers and lung adenocarcinomas. Moreover, INHA itself was dependent on TGFBR3 and ENG/CD105 in multiple cancer types. INHA, INHBA, TGFBR3, and ENG also predicted patients’ response to anthracycline and taxane therapy in luminal A breast cancers. We also obtained a gene signature model that could accurately classify 96.7% of the cases based on outcomes. Lastly, we cross-compared gene correlations revealing INHA dependency to TGFBR3 or ENG influencing different pathways themselves. These results suggest that inhibins are particularly important in a subset of cancers depending on the coreceptor TGFBR3 and ENG and are of substantial prognostic value, thereby warranting further investigation.