AZD7507

The failure to predict kidney toxicity of new chemical entities early in the development process before they reach humans remains a critical issue. Here, we used primary human kidney cells and applied a systems biology approach that combines multidimensional datasets and machine learning to identify biomarkers that not only predict nephrotoxic compounds but also provide hints toward their mechanism of toxicity. Gene expression and high-content imaging-derived phenotypical data from 46 diverse kidney toxicants were analyzed using Random Forest machine learning. Imaging features capturing changes in cell morphology and nucleus texture along with mRNA levels of HMOX1 and SQSTM1 were identified as the most powerful predictors of toxicity. These biomarkers were validated by their ability to accurately predict kidney toxicity of four out of six candidate therapeutics that exhibited toxicity only in late stage preclinical/clinical studies. Network analysis of similarities in toxic phenotypes was performed based on live-cell high-content image analysis at seven time points. Using compounds with known mechanism as reference, we could infer potential mechanisms of toxicity of candidate therapeutics. In summary, we report an approach to generate a multidimensional biomarker panel for mechanistic de-risking and prediction of kidney toxicity in in vitro for new therapeutic candidates and chemical entities.

Pancreatic ductal adenocarcinoma (PDAC) is resistant to most therapies including single-agent immunotherapy and has a dense desmoplastic stroma, and most patients present with advanced metastatic disease. We reveal that macrophages are the dominant leukocyte population both in human PDAC stroma and autochthonous models, with an important functional contribution to the squamous subtype of human PDAC. We targeted macrophages in a genetic PDAC model using AZD7507, a potent selective inhibitor of CSF1R. AZD7507 caused shrinkage of established tumors and increased mouse survival in this difficult-to-treat model. Malignant cell proliferation diminished, with increased cell death and an enhanced T cell immune response. Loss of macrophages rewired other features of the TME, with global changes in gene expression akin to switching PDAC subtypes. These changes were markedly different to those elicited when neutrophils were targeted via CXCR2. These results suggest targeting the myeloid cell axis may be particularly efficacious in PDAC, especially with CSF1R inhibitors.