ReviewClinical Medicine Insights. Oncology2025
Navigating Cancer Complexity: Integrative Multi-Omics Methodologies for Clinical Insights.
Review in Clinical Medicine Insights. Oncology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.
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
16 citing papers in PubMed.
- Single-cell and spatial RNA sequencing in prostate cancer.Nature reviews. Urology · 2026Review
- Multi-omics integration of proteomics and metabolomics in pediatric health and disease.Communications medicine · 2026Review
- Expression quantitative trait methylation across multiple cancer types with functional and therapeutic characterization using Onco-eQTM.NAR genomics and bioinformatics · 2026Article
- Proteomic Biomarker Discovery in Breast Cancer: Advances, Challenges, and Translational Prospects.Journal of biochemical and molecular toxicology · 2026Review
- Landscape and biogenesis of piRNAs in HBV-associated hepatocarcinogenesis: from repetitive elements to oncogenic circuits.Discover oncology · 2026Review
- 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
- The Role that Biobanks Can Play in Driving Animal-Free Biomedical Research.Expert reviews in molecular medicine · 2026Review
- Mapping research trends in immune cell metabolic reprogramming in breast cancer: a parallel dual-database bibliometric study.Discover oncology · 2026Article
- Integrative transcriptomic and structural modeling reveal CASP1, TLR3, PYCARD, and CD274 as immune-modulatory drivers in breast cancer.Naunyn-Schmiedeberg's archives of pharmacology · 2026Article
- Review
- Transcriptional Profiling Reveals Lineage-Specific Characteristics in ATR/CHK1 Inhibitor-Resistant Endometrial Cancer.Biomolecules · 2026Article
- Tumor-on-chip's alliance with molecular pathology against metastatic disease.Journal of biomedical science · 2026Review
- Integrative network pharmacology, molecular dynamics simulation, and single-cell RNA sequencing strategies reveal the multi-target mechanisms of oridonin against cervical cancer.Frontiers in pharmacology · 2026Article
- Host-microbiome interactions in leukemia: mechanisms, treatment response, and clinical implications.Frontiers in cellular and infection microbiology · 2026Review
- Editorial: Targeted cancer therapy through metabolic pathways.Frontiers in molecular medicine · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Recent advancements in cancer multi-omics have transformed our understanding of cancer biology by integrating genomics, transcriptomics, proteomics, and metabolomics. These integrative approaches have led to the identification of novel biomarkers and therapeutic targets, offering deeper insights into the molecular intricacies of various cancers, including breast, lung, gastric, pancreatic, and glioblastoma. Despite these advances, challenges remain, such as the integration of disparate data types and the interpretation of complex biological interactions. However, developments in proteogenomics and mass spectrometry have enhanced the correlation between molecular profiles and clinical features, refining the prediction of therapeutic responses. Future research in cancer drug discovery is poised to benefit from multi-omics approaches, improving the precision and efficacy of personalized therapies. By developing integrative network-based models, researchers aim to address challenges related to heterogeneity, reproducibility, and data interpretation. A standardized framework for multi-omics data integration could revolutionize cancer research, optimizing the identification of novel drug targets and enhancing our understanding of cancer biology. This complete approach holds the promise of advancing personalized therapies by fully characterizing the molecular landscape of cancer, ultimately improving patient outcomes through more effective and targeted treatment strategies. This narrative review underscores the potential of multi-omics approaches to transform cancer research and improve patient outcomes through more precise and effective treatments.
Indexed as
Identifiers
What Socratic 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 Socratic graph.