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An Integrated Approach to Uncover Drivers of Cancer
Open accessAbstract
Systematic characterization of cancer genomes has revealed a staggering number of diverse aberrations that differ among individuals, such that the functional importance and physiological impact of most tumor genetic alterations remain poorly defined. We developed a computational framework that integrates chromosomal copy number and gene expression data for detecting aberrations that promote cancer progression. We demonstrate the utility of this framework using a melanoma data set. Our analysis correctly identified known drivers of melanoma and predicted multiple tumor dependencies. Two dependencies, TBC1D16 and RAB27A, confirmed empirically, suggest that abnormal regulation of protein trafficking contributes to proliferation in melanoma. Together, these results demonstrate the ability of integrative Bayesian approaches to identify candidate drivers with biological, and possibly therapeutic, importance in cancer.
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“Similarly, CONEXIC (Akavia et al., 2010) also uses a BN to integrate gene expression and copy number variation from tumour samples to identify driver mutations.”
From Using machine learning approaches for multi-omics data analysis: A review (2021) · cites this paper as Akavia et al., 2010
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Metadata
- Authors
- Akavia, U. D., Litvin, O., Kim, J., Sanchez-Garcia, F., Kotliar, D., Causton, H. C., Pochanard, P., Mozes, E., Garraway, L. A., & Pe'er, D.
- Affiliations
- Columbia University (US)
- Broad Institute (US)
- Venue
- Cell
- Publisher
- Elsevier BV
- Published
- 2010-12
- Volume
- 143
- Issue
- 6
- Pages
- 1005-1017
- ISSN
- 0092-8674 (ISSN-L)
- PMC
- PMC3013278
- OpenAlex
- W1968667083
- Cited by
- 484
- References
- 129
- Citations by year
- 2026: 5 · 2025: 5 · 2024: 14 · 2023: 21 · 2022: 18 · 2021: 17 · 2020: 30 · 2019: 28 · 2018: 24 · 2017: 33 · 2016: 42 · 2015: 51 · 2014: 47 · 2013: 60 · 2012: 56
- FWCI
- 14.99
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Licence
- Locations
- Cell (publishedVersion)
- PubMed (publishedVersion)
- Europe PMC (PubMed Central) (acceptedVersion)
- PubMed Central (acceptedVersion)
- Funders
- Burroughs Wellcome Fund
- National Institutes of Health (DP2OD002414)
- National Cancer Institute (U54CA121852)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Cancer Research › Cancer Genomics and Diagnostics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Chromatin Remodeling and Cancer
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genomic variations and chromosomal abnormalities
- Keywords
- cancer driver genes, melanoma, chromosomal copy number alterations, gene expression, tumor dependency, Rab27a, protein trafficking, tumor progression, therapeutic target
- MeSH terms
- rab27 GTP-Binding Proteins, Bayes Theorem, Humans, Melanoma, GTPase-Activating Proteins, rab GTP-Binding Proteins, Gene Expression Profiling, Protein Transport, Microphthalmia-Associated Transcription Factor
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