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Meshcheryakova, Anastasia; Svoboda, Martin; Jaritz, Markus; Mungenast, Felicitas; Salzmann, Martina; Pils, Dietmar; Castillo-Tong, Dan Cacsire; Hager, Gudrun; Wolf, Andrea; Braicu, Elena Ioana; Sehouli, Jalid; Lambrechts, Sandrina; Vergote, Ignace; Mahner, Sven; Birner, Peter; Zimmermann, Philip; Brindley, David N.; Heinze, Georg; Zeillinger, Robert and Mechtcheriakova, Diana (2019): Interrelations of Sphingolipid and Lysophosphatidate Signaling with Immune System in Ovarian Cancer. In: Computational and Structural Biotechnology Journal, Vol. 17: pp. 537-560

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The sphingolipid and lysophosphatidate regulatory networks impact diverse mechanisms attributed to cancer cells and the tumor immune microenvironment. Deciphering the complexity demands implementation of a holistic approach combined with higher-resolution techniques. We implemented a multi-modular integrative approach consolidating the latest accomplishments in gene expression profiling, prognostic/predictive modeling, next generation digital pathology, and systems biology for epithelial ovarian cancer. We assessed patient-specific transcriptional profiles using the sphingolipid/lysophosphatidate/immune-associated signature. This revealed novel sphingolipid/lysophosphatidate-immune gene-gene associations and distinguished tumor subtypes with immune high/low context. These were characterized by robust differences in sphingolipid-/lysophosphatidate-related checkpoints and the drug response. The analysis also nominates novel survival models for stratification of patients with CD68, LPAR3, .SMPD1 , PPAP2B, and SMPD2 emerging as the most prognostically important genes. Alignment of proprietary data with curated transcriptomic data from public databases across a variety of malignancies (over 600 categories;over 21,000 arrays) showed specificity for ovarian carcinoma. Our systems approach identified novel sphingolipid-lysophosphatidate-immune checkpoints and networks underlying tumor immune heterogeneity and disease outcomes. This holds great promise for delivering novel stratifying and targeting strategies. (C) 2019 The Authors. Published by Elsevier B.V. on behalf of Research Network of Computational and Structural Biotechnology.

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