- by RCG
- 1 octobre 2021
We are excited to share the latest work from our MESOMICS project in which we disentangle the molecular, clinical and morphological heterogeneity of malignant pleural mesothelioma (MPM) using deep integrative omics analyses: https://biorxiv.org/cgi/content/short/2021.09.27.461908v1.
MPM is a rare aggressive cancer associated with asbestos exposure. In the past decade, knowledge on the molecular profile of MPM has rapidly expanded but surprisingly little progress has been made in its clinical management. Thanks to the French MESOBANK biorepository, we have assembled the largest series of whole-genome sequencing (WGS) data to date, along with transcriptomic and epigenomic data, including 13 patients with two tumoral regions to study intra-tumor heterogeneity. Using multi-omic factor analysis, we demonstrate that heterogeneity arises from four sources of variation: tumor cell morphology, ploidy, adaptive immune response, and CpG island methylator phenotype. Previous studies focused on describing only the tumor cell morphology factor because genomic events have not been fully described and there is a lack of comprehensive integrative analyses examining how molecular features affecting multiple omic layers interact. The novel WGS data allowed for the first time a detailed characterization of the multiple mutational processes shaping MPM tumors, including Whole Genome duplication events, chromothripsis, extrachromosomal DNA, recurrent structural variants, and novel driver genes. To understand how these mutational processes shape the observed phenotypes, we characterized their impact through the lens of multi-task theory and demonstrate that these genomic events push MPM tumors toward specialized phenotypes at early stages of tumor development. Finally, we show how these new sources of variation help understand the heterogeneity of the clinical behavior of MPM and drug responses measured in cell lines.
As always we are strongly committed to make our research as open as possible, as soon as possible. Data is available on EGAarchive, bioinformatics pipelines powered by nextflowio and Docker are available on our github page https://github.com/IARCbioinfo/.