Taking systems biology to ovarian cancer
A study published in Computational and Structural Biotechnology Journal and conducted by Anastasia Meshcheryakova from the Systems Biology and Pathophysiology Group of Diana Mechtcheriakova together with colleagues from the Medical University of Vienna and the multidisciplinary team of international experts made an effort to look from another angle on potential therapeutic checkpoints for epithelial ovarian cancer and propose that assessment of the sphingolipid and lysophosphatidate systems in conjunction with the local immune response may lead to novel stratifying and targeting strategies. This offers the power for improving the efficacy of existing therapies and possibly immunotherapies.
The major clinical challenge of high-grade serous ovarian cancer is an ultimate development of progressive resistance to chemotherapy in the majority of patients. A further distinctive cornerstone is the high inter- and intra-tumoral genetic, inflammatory, and immune heterogeneity. In contrast to other cancer types, there is a lack of clear molecular criteria to stratify (group) the patients for effective application of molecular-targeted agents, including immunotherapeutic interventions.
Diana Mechtcheriakova, Head Molecular Systems Biology and Pathophysiology Group, the project leader: “In this study, we provide a novel approach to this challenge based on the understanding of the dysregulation of the sphingolipid signaling system that occurs in cancer, its crosstalk with the lysophosphatidate system, and the interrelation with the local tumor immune microenvironment. And yet, at the same time, we consider that the complexity of the sphingolipid system multiplied by the heterogeneity of tumor necessitates the implementation of integrative, systems biology-based approaches for analysis and for obtaining a comprehensive picture.”
The authors implemented a multi-modular integrative approach, recently developed by Diana Mechtcheriakova’s research group (Department of Pathophysiology and Allergy Research, Center of Pathophysiology, Infectiology and Immunology, Medical University of Vienna) in collaboration with Georg Heinze (Section for Clinical Biometrics, Center for Medical Statistics, Informatics, and Intelligent Systems, Medical University of Vienna), Philip Zimmermann (Nebion AG, Zürich, Switzerland), and Markus Jaritz (Research Institute of Molecular Pathology, Vienna Biocenter). The algorithm was named as MuSiCO/from Multigene Signature to Patient-Orientated Clinical Outcome. This innovative approach consolidates the latest accomplishments in gene expression profiling, prognostic/predictive modeling, next generation digital pathology, and systems biology.
The authors applied the self-created sphingolipid/lysophosphatidate/immune-associated multigene signature within the integrative 5-modular MuSiCO algorithm and demonstrated the applicability of the patient-specific, signature-derived gene expression data sets for identification of novel sphingolipid/lysophosphatidate/immune-related, disease-relevant aberrations and checkpoints. The comprehensiveness of analysis was herein strengthened by inclusion of next generation digital pathology/digital imaging module and by a compendium-wide analysis for assessment of specificity of the herein defined transcriptional profile across the signature genes.
The results and new algorithm provide unique knowledge about the complex expression patterns of sphingolipid-related genes as well as relationships among sphingolipid-, lysophosphatidate-, and immune-related genes. The data presented in this study indicate that the features of the program established by the local sphingolipid/lysophosphatidate machinery give an important impact to the organization of the ovarian cancer microenvironment by way of shaping immune infiltrates. Important follow-up is that the acquired information delivers novel patient-stratification strategies for differentiating between immunologically enriched/immune high and immunologically poor/immune low tumor types and for predicting the clinical outcomes of survival and drug resistance. The study identifies sphingolipid/lysophosphatidate/immune-associated checkpoints as candidates for development of novel targeting and clinical decision-making strategies.
Meshcheryakova A, Svoboda M, Jaritz M, Mungenast F, Salzmann M, Pils D, Castillo-Tong DC, Hager G, Wolf A, Braicu EI, Sehouli J, Lambrechts S, Vergote I, Mahner S, Birner P, Zimmermann P, Brindley DN, Heinze G, Zeillinger R, Mechtcheriakova D. Interrelations of sphingolipid and lysophosphatidate signaling with immune system in ovarian cancer. Comput Struct Biotechnol J 2019, 17: 537-560. DOI:10.1016/j.csbj.2019.04.004
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