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Systems biology-based algorithm discovers new checkpoints of ovarian cancer

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(Vienna, 31 May 2019) A multidisciplinary team made up of MedUni Vienna scientists and international partners developed a new integrative approach to deciphering therapeutic checkpoints in the pathobiology of epithelial ovarian cancer. The team used this algorithm to analyse the sphingolipid/lysophosphatidate system in terms of the local immune response and discovered new "checkpoints", which, in future, could help to provide better patient stratification and the development of new targeted treatment strategies. The study has been published in the Computational and Structural Biotechnology Journal.

"The greatest clinical challenge in treating high-grade serous ovarian cancer is the development of chemotherapy resistance in the majority of patients. Furthermore, ovarian cancer is characterised by strong intertumoural and intratumoural heterogeneity in terms of genetic variability and differences in the underlying inflammatory and immune responses. In contrast to other types of cancer, serous ovarian cancer does not have clear molecular characteristics that allow patients to be stratified for effective application of targeted treatments or immunotherapy interventions," explains Diana Mechtcheriakova from MedUni Vienna’s Institute of Pathophysiology and Allergy Research.

In collaboration with Georg Heinze (Institute of Clinical Biometrics at MedUni Vienna's Center for Medical Statistics, Informatics and Intelligent Systems), Philip Zimmermann (Nebion AG, Zürich, Switzerland) and Markus Jaritz (Research Institute for Molecular Pathology, Vienna BioCenter), her research group has developed and implemented a multi-modular integrative analytical algorithm, MuSiCO (from Multigene Signature to Patient-Oriented Clinical Outcome), which combines the very latest technologies and analytical techniques from the fields of gene expression analysis, statistical predictive modelling, next-generation digital pathology, and systems biology.

In the 5-modular approach, the researchers used a self-created sphingolipid/lysophosphatidate/immune-associated multigene signature for gene expression analysis, thereby demonstrating the applicability of the patient-specific signature-based gene expression profile for identifying new cancer-related checkpoints.

Says project leader Diana Mechtcheriakova: “This study is characterised by a new approach, in that we look at the cancer-related regulatory disturbances of the sphingolipid signaling system in the context of mutual influencing by the lysophosphatidate system and the interrelationship with the local immune response of the tumour." The lead investigator also points out that the outlined integrative strategy builds new bridges between systems biology and systems medicine.

The results obtained show that the sphingolipid/lysophosphatidate system makes an important contribution to the organisation of the local immune response. This gives rise to new patient stratification strategies including dividing them into immunologically enriched and immunologically poor tumour types and the resulting prediction of clinical outcome and treatment response. The study nominates the sphingolipid/lysophosphatidate/immune-associated checkpoints as candidates for the development of new targeted therapeutic approaches and clinical decision-making strategies.

Service: Computational and Structural Biotechnology Journal
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