ReviewMolecules and cells2021
Integrative Multi-Omics Approaches in Cancer Research: From Biological Networks to Clinical Subtypes.
Review in Molecules and cells, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 120 papers, 1 of them a synthesis that pooled it.
What it found
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Who cites it
120 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Machine learning-based analysis of cancer cell-derived vesicular proteins revealed significant tumor-specificity and predictive potential of extracellular vesicles for cell invasion and proliferation - A meta-analysis.Cell communication and signaling : CCS · 2023Pooled it
- Beyond chemotherapy: The rise of nucleic acid nanoformulations in personalized lung cancer therapy.Cancer pathogenesis and therapy · 2026Review
- Spatially organized regulated cell death-immune coupling in solid tumors: integrating spatial omics with actionable regulated cell death biology.Molecular cancer · 2026Review
- Transcriptomic and epigenomic insights into ovarian cancer: a bioinformatics perspective - a narrative review.Annals of medicine and surgery (2012) · 2026Article
- Africa's emerging role in precision oncology: translational insights from the harnessing functional genomics in cancer research conference, Windhoek, 23-26 September 2025.BMC proceedings · 2026Article
- SOPA and SIMPA: normalized single-sample integrated multiomics pathway analysis of tumor heterogeneity in solid cancers.Briefings in bioinformatics · 2026Article
- Molecules of lung cancer - fusion alterations in nonsmall cell lung cancer: biology and diagnostic considerations.Breathe (Sheffield, England) · 2026Review
- Proteomic stratification reveals immune metabolic heterogeneity in lung adenocarcinoma.Discover oncology · 2026Article
- Leveraging single-cell and spatial omics for brain tumour insights to improve therapeutic strategies.Molecular brain · 2026Review
- Article
- Data harmonization processes of cancer data into the observational medical outcomes partnership common data model.Scientific reports · 2026Article
- Integrating multi-omics data for next-generation cancer research and precision medicine.Clinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico · 2026Review
- Venous Thromboembolism and Gut Dysbiosis: Mechanistic Links Between Endotoxemia, Microbial Metabolites, and Thromboinflammation.Nutrients · 2026Review
- Low GBX2 expression is associated with histological type B thymoma: a multi-omics analysis.Discover oncology · 2026Article
- Detection of known gene fusions in cancer cell lines using whole-genome bisulfite sequencing data.Scientific reports · 2026Article
- Early Cancer Detection: What's Going on and What's Next.MedComm · 2026Review
- Robust graph structure learning to improve multi-omics cancer subtype classification.BMC bioinformatics · 2026Article
- ITGA8 suppresses proliferation and metastasis of lung adenocarcinoma through the inhibition of glycolysis.Scientific reports · 2026Article
- Multi-omics integration in deciphering non-small cell lung cancer drug resistance: current status, challenges, and future prospects.Hereditas · 2026Review
- Integrative Multiomics and Drug Sensitivity Profiling Reveal Potential Biomarkers and Therapeutic Strategies in Pediatric Solid Tumors.Cancer research · 2026Article
60 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Multi-omics approaches are novel frameworks that integrate multiple omics datasets generated from the same patients to better understand the molecular and clinical features of cancers. A wide range of emerging omics and multi-view clustering algorithms now provide unprecedented opportunities to further classify cancers into subtypes, improve the survival prediction and therapeutic outcome of these subtypes, and understand key pathophysiological processes through different molecular layers. In this review, we overview the concept and rationale of multi-omics approaches in cancer research. We also introduce recent advances in the development of multi-omics algorithms and integration methods for multiple-layered datasets from cancer patients. Finally, we summarize the latest findings from large-scale multi-omics studies of various cancers and their implications for patient subtyping and drug 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.