ArticleHuman genomics2024
Prioritization of therapeutic targets for cancers using integrative multi-omics analysis.
Article in Human genomics, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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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.
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Who cites it
7 citing papers in PubMed, 5 citations in OpenAlex.
- Integration of Multi-Omics Data To Understand the Multifaceted Role of RAMP1 across Different Cancer Types.Cell biochemistry and biophysics · 2026Review
- Integration of aged brain multi-omics reveals cross-system mechanisms underlying Alzheimer's disease heterogeneity.Cell reports · 2026Article
- Deep Generative AI for Multi-Target Therapeutic Design: Toward Self-Improving Drug Discovery Framework.International journal of molecular sciences · 2025Review
- Integration of aged brain multi-omics reveals cross-system mechanisms underlying Alzheimer's disease heterogeneity.bioRxiv : the preprint server for biology · 2025Article
- Article
- Review
- Mechanisms and technologies in cancer epigenetics.Frontiers in oncology · 2024Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
11 authors at 3 institutions in 1 country.
Funding
Abstract
backgroundThe integration of transcriptomic, proteomic, druggable genetic and metabolomic association studies facilitated a comprehensive investigation of molecular features and shared pathways for cancers' development and progression.
methodsComprehensive approaches consisting of transcriptome-wide association studies (TWAS), proteome-wide association studies (PWAS), summary-data-based Mendelian randomization (SMR) and MR were performed to identify genes significantly associated with cancers. The results identified in above analyzes were subsequently involved in phenotype scanning and enrichment analyzes to explore the possible health effects and shared pathways. Additionally, we also conducted MR analysis to investigate metabolic pathways related to cancers.
resultsTotally 24 genes (18 transcriptomic, 1 proteomic and 5 druggable genetic) showed significant associations with cancers risk. All genes identified in multiple methods were mainly enriched in nuclear factor erythroid 2-related factor 2 (NRF2) pathway. Additionally, biosynthesis of ubiquinol and urate were found to play an important role in gastrointestinal tumors.
conclusionsA set of putatively causal genes and pathways relevant to cancers were identified in this study, shedding light on the shared biological processes for tumorigenesis and providing compelling genetic evidence to prioritize anti-cancer drugs development.
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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.