Interrelations of Sphingolipid and Lysophosphatidate Signaling with Immune System in Ovarian Cancer
Autor: | Sven Mahner, Elena Ioana Braicu, Diana Mechtcheriakova, Philip Zimmermann, Dan Cacsire Castillo-Tong, Georg Heinze, David N. Brindley, Sandrina Lambrechts, Ignace Vergote, Martina Salzmann, Markus Jaritz, Felicitas Mungenast, Dietmar Pils, Gudrun Hager, Jalid Sehouli, Robert Zeillinger, Anastasia Meshcheryakova, Andrea Wolf, Peter Birner, Martin Svoboda |
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Jazyk: | angličtina |
Rok vydání: | 2019 |
Předmět: |
Patient stratification
Systems biology lcsh:Biotechnology Biophysics Context (language use) Computational biology Biology Sphingolipid/lysophosphatidate system Biochemistry Transcriptome 03 medical and health sciences 0302 clinical medicine Immune system Structural Biology Ovarian carcinoma lcsh:TP248.13-248.65 Patient-specific expression data sets Genetics medicine 030304 developmental biology 0303 health sciences On-site immune response From systems biology to systems medicine medicine.disease Sphingolipid 3. Good health Computer Science Applications Gene expression profiling 030220 oncology & carcinogenesis Ovarian cancer Integrative analysis algorithm Research Article Biotechnology |
Zdroj: | Computational and Structural Biotechnology Journal, Vol 17, Iss, Pp 537-560 (2019) |
Popis: | 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. Keywords: Sphingolipid/lysophosphatidate system, On-site immune response, Patient-specific expression data sets, Integrative analysis algorithm, Patient stratification, From systems biology to systems medicine |
Databáze: | OpenAIRE |
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