Multi-modal meta-analysis of cancer cell line omics profiles identifies ECHDC1 as a novel breast tumor suppressor

Alok Jaiswal*, Prson Gautam, Elina A. Pietilä, Sanna Timonen, Nora Nordström, Yevhen Akimov, Nina Sipari, Ziaurrehman Tanoli, Thomas Fleischer, Kaisa Lehti, Krister Wennerberg, Tero Aittokallio

*Corresponding author af dette arbejde

Publikation: Bidrag til tidsskriftTidsskriftartikelForskningpeer review

6 Citationer (Scopus)
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Abstract

Molecular and functional profiling of cancer cell lines is subject to laboratory-specific experimental practices and data analysis protocols. The current challenge therefore is how to make an integrated use of the omics profiles of cancer cell lines for reliable biological discoveries. Here, we carried out a systematic analysis of nine types of data modalities using meta-analysis of 53 omics studies across 12 research laboratories for 2,018 cell lines. To account for a relatively low consistency observed for certain data modalities, we developed a robust data integration approach that identifies reproducible signals shared among multiple data modalities and studies. We demonstrated the power of the integrative analyses by identifying a novel driver gene, ECHDC1, with tumor suppressive role validated both in breast cancer cells and patient tumors. The multi-modal meta-analysis approach also identified synthetic lethal partners of cancer drivers, including a co-dependency of PTEN deficient endometrial cancer cells on RNA helicases.

OriginalsprogEngelsk
Artikelnummere9526
TidsskriftMolecular Systems Biology
Vol/bind17
Udgave nummer3
Sider (fra-til)1-25
ISSN1744-4292
DOI
StatusUdgivet - 2021

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