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

• Published in: Molecular systems biology Vol. 17; no. 3; pp. e9526 - n/a
• Main Authors: Jaiswal, Alok, Gautam, Prson, Pietilä, Elina A, Timonen, Sanna, Nordström, Nora, Akimov, Yevhen, Sipari, Nina, Tanoli, Ziaurrehman, Fleischer, Thomas, Lehti, Kaisa, Wennerberg, Krister, Aittokallio, Tero
• Format: Journal Article
• Language: English
• Published: London Nature Publishing Group UK 01.03.2021; EMBO Press; John Wiley and Sons Inc; Springer Nature
• Subjects: Biotechnology; Breast cancer; Cancer; cancer driver; CRISPR; Data analysis; Data integration; Data processing; Datasets; EMBO03; EMBO22; EMBO24; Endometrial cancer; Endometrium; Gene expression; Genomes; Genomics; Laboratories; Meta-analysis; multi‐omics data; Mutation; Phosphorylation; Protein expression; Proteins; PTEN protein; Reproducibility; synthetic lethality; Tumor cell lines; Tumor suppressor genes; Tumors; cancer driver; data integration; reproducibility; multi‐omics data; synthetic lethality; multi-omics data
• ISSN: 1744-4292; 1744-4292
• DOI: 10.15252/msb.20209526

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. SYNOPSIS CLIP is a multi‐modal data integration approach that integrates cancer cell line omics data from multiple studies and identifies robust cancer cell line‐specific genes. As an example, CLIP identifies ECHDC1 as a novel breast tumor suppressor. The study presents a meta‐analysis of 53 multi‐modal molecular profiles composed of nine types of omics data generated in 12 labs for 2,018 cancer cell lines. The reproducibility of molecular profiles varies by data modality. CLIP is a non‐parametric data integration framework that enables systematic multi‐modal meta‐analysis by accounting for reproducibility estimates specific to each modality. CLIP identified known cancer drivers and a novel breast tumor suppressor, ECHDC1, and indicated novel synthetic lethal partners of cancer driver genes. Graphical Abstract CLIP is a multi‐modal data integration approach that integrates cancer cell line omics data from multiple studies and identifies robust cancer cell line‐specific genes. As an example, CLIP identifies ECHDC1 as a novel breast tumor suppressor.