A novel human homologue of Escherichia coli, yeast and plant 1-acylglycerol-3-phosphate acyltransferase has been isolated from U937 cell cDNA. Expression of the cloned sequence in 1-acylglycerol-3-phosphate acyltransferase-deficient E. coli resulted in increased incorporation of oleic acid into cellular phospholipids. Membranes made from COS7 cells transfected with the cDNA exhibited higher acyltransferase activity towards a range of donor fatty acyl-CoAs and lysophosphatidic acid. Northern-blot analysis of the cDNA sequence indicated high levels of expression in immune cells and epithelium. Rapid amplification of cDNA ends revealed differentially expressed splice variants, which suggests regulation of the enzyme by alternative splicing. This cDNA therefore represents the first described sequence of a mammalian gene homologous to non-mammalian lysophosphatidic acid acyltransferases.

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Esophageal adenocarcinoma (EAC) is a highly heterogeneous disease, dominated by large-scale genomic rearrangements and copy number alterations. Such characteristics have hampered conventional target-directed drug discovery and personalized medicine strategies, contributing to poor outcomes for patients. We describe the application of a high-content Cell Painting assay to profile the phenotypic response of 19,555 compounds across a panel of six EAC cell lines and two tissue-matched control lines. We built an automated high-content image analysis pipeline to identify compounds that selectively modified the phenotype of EAC cell lines. We further trained a machine-learning model to predict the mechanism of action of EAC selective compounds using phenotypic fingerprints from a library of reference compounds. We identified a number of phenotypic clusters enriched with similar pharmacological classes, including methotrexate and three other antimetabolites that are highly selective for EAC cell lines. We further identify a small number of hits from our diverse chemical library that show potent and selective activity for EAC cell lines and that do not cluster with the reference library of compounds, indicating they may be selectively targeting novel esophageal cancer biology. Overall, our results demonstrate that our EAC phenotypic screening platform can identify existing pharmacologic classes and novel compounds with selective activity for EAC cell phenotypes.