SynthesisMolecular systems biology2021
Multi-modal meta-analysis of cancer cell line omics profiles identifies ECHDC1 as a novel breast tumor suppressor.
Synthesis in Molecular systems biology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers, 1 of them a synthesis that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
14 citing papers in PubMed, 1 synthesis or guideline pooled it, 18 citations in OpenAlex.
- Multi-modal meta-analysis of cancer cell line omics profiles identifies ECHDC1 as a novel breast tumor suppressor.Molecular systems biology · 2021Pooled it
- GEMap: A comprehensive gene essentiality map for drug discovery.Acta pharmaceutica Sinica. B · 2026Article
- Laser Desorption-Rapid Evaporative Ionization Mass Spectrometry (LD-REIMS): A New Tool for the High-Throughput Metabolomic and Lipidomic Profiling of Live Cells.Analytical chemistry · 2025Article
- Mapping the rapid growth of multi-omics in tumor immunotherapy: Bibliometric evidence of technology convergence and paradigm shifts.Human vaccines & immunotherapeutics · 2025Article
- Largest-Scale Genomic Resource Reconstructing the Genetic Origin, Population Structure, and Biological Adaptations of the Hui People.Molecular biology and evolution · 2025Article
- Article
- Systematic identification of cancer pathways and potential drugs for intervention through multi-omics analysis.The pharmacogenomics journal · 2025Article
- Lactylation Modification as a Promoter of Bladder Cancer: Insights from Multi-Omics Analysis.Current issues in molecular biology · 2024Article
- Alternative splicing of transposable elements in human breast cancer.bioRxiv : the preprint server for biology · 2024Article
- Statistical integration of multi-omics and drug screening data from cell lines.PLoS computational biology · 2024Article
- Bipartite network models to design combination therapies in acute myeloid leukaemia.Nature communications · 2022Article
- Machine learning for multi-omics data integration in cancer.iScience · 2022Review
- The impact of violating the independence assumption in meta-analysis on biomarker discovery.Frontiers in genetics · 2022Article
- Integrative OMICS Data-Driven Procedure Using a Derivatized Meta-Analysis Approach.Frontiers in genetics · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
12 authors at 3 institutions in 4 countries.
Funding
No grant is acknowledged in the PubMed record.
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.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.