Systematic identification of cancer pathways and potential drugs for intervention through multi-omics analysis.
1/5 보강
The pathogenesis of cancer is complicated, and different types of cancer often exhibit different gene mutations resulting in different omics profiles.
APA
Xu T, Ngan DK, et al. (2025). Systematic identification of cancer pathways and potential drugs for intervention through multi-omics analysis.. The pharmacogenomics journal, 25(2), 2. https://doi.org/10.1038/s41397-025-00361-6
MLA
Xu T, et al.. "Systematic identification of cancer pathways and potential drugs for intervention through multi-omics analysis.." The pharmacogenomics journal, vol. 25, no. 2, 2025, pp. 2.
PMID
39971899
Abstract
The pathogenesis of cancer is complicated, and different types of cancer often exhibit different gene mutations resulting in different omics profiles. The purpose of this study was to systematically identify cancer-specific biological pathways and potential cancer-targeting drugs. We collectively analyzed the transcriptomics and proteomics data from 16 common types of human cancer to study the mechanism of carcinogenesis and seek potential treatment. Statistical approaches were applied to identify significant molecular targets and pathways related to each cancer type. Potential anti-cancer drugs were subsequently retrieved that can target these pathways. The number of significant pathways linked to each cancer type ranged from four (stomach cancer) to 112 (acute myeloid leukemia), and the number of therapeutic drugs that can target these cancer related pathways, ranged from one (ovarian cancer) to 97 (acute myeloid leukemia and non-small-cell lung carcinoma). As a validation of our method, some of these drugs are FDA approved therapies for their corresponding cancer type. Our findings provide a rich source of testable hypotheses that can be applied to deconvolute the complex underlying mechanisms of human cancer and used to prioritize and repurpose drugs as anti-cancer therapies.
MeSH Terms
Humans; Antineoplastic Agents; Neoplasms; Proteomics; Transcriptome; Gene Expression Profiling; Signal Transduction; Molecular Targeted Therapy; Multiomics
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