Orchestrating and sharing large multimodal data for transparent and reproducible research

Reproducibility is essential to open science, as there is limited relevance for findings that can not be reproduced by independent research groups, regardless of its validity. It is therefore crucial for scientists to describe their experiments in sufficient detail so they can be reproduced, scrutinized, challenged, and built upon. However, the intrinsic complexity and continuous growth of biomedical data makes it increasingly difficult to process, analyze, and share with the community in a FAIR (findable, accessible, interoperable, and reusable) manner. To overcome these issues, we created a cloud-based platform called ORCESTRA ( orcestra.ca ), which provides a flexible framework for the reproducible processing of multimodal biomedical data. It enables processing of clinical, genomic and perturbation profiles of cancer samples through automated processing pipelines that are user-customizable. ORCESTRA creates integrated and fully documented data objects with persistent identifiers (DOI) and manages multiple dataset versions, which can be shared for future studies.

Big data-based identification of methylated genes associated with drug resistance and prognosis in ovarian cancer

It is imperative to further the understanding of the drug resistance mechanisms of ovarian cancer (OC) and to identify useful biological markers for prognosis prediction.Cormine, cBioportal, and The Cancer Genome Atlas databases were used to search microarray data of gene methylation related to OC, drug resistance in OC, and prognosis, and to analyze methylated genes potentially inducing the drug resistance in OC. Fifty-five DNA-methylated genes significantly associated with drug resistance in OC were screened, and the regulatory mechanisms underlying changes in methylation levels of these genes were systematically integrated.Enrichment and annotation of biological processes indicated that most of the above DNA-methylated genes were significantly associated with cell proliferation and cell cycle. In addition, pathway enrichment demonstrated that the above DNA-methylated genes were significantly associated with PI3K-AKT and P53 signaling pathways. Among the 55 genes, 4 were significantly associated with OC prognostic disease-free survival, namely bromodomain containing 4, PDZ domain containing 1 (PDZK1), phosphatase and tensin homolog, and TNF receptor superfamily member 10c; 5 were significantly related to overall survival, namely bromodomain containing 4, PDZK1, PIK3C2B, Rh associated glycoprotein, and DYRK; among them, the degree of methylation of TNF receptor superfamily member 10c, PDZK1, and Rh associated glycoprotein genes was significantly correlated with mRNA expression. Furthermore, PDZK1, Rh associated glycoprotein, and TNF receptor superfamily member 10c genes showed significant hypomethylation in drug-resistance tissues of OC, and their mRNAs had significantly high expression.The association between the methylation of these 55 genes and OC and drug resistance in OC, in addition to bioinformatics analyses clarify the important mechanisms of gene methylation in the development, progression, and drug resistance of OC.