ReviewInternational journal of molecular sciences2024
Bioinformatics Analysis and Validation of Potential Markers Associated with Prediction and Prognosis of Gastric Cancer.
Review in International journal of molecular sciences, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 49 papers, 1 of them a synthesis that pooled it.
What it found
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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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
49 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Applications and challenges of biomarker-based predictive models in proactive health management.Frontiers in public health · 2025Pooled it
- T‑box transcription factor 15 regulated by methyltransferase‑like 3‑mediated N6‑methyladenosine modification promotes immune escape and progression of gastric cancer by activating matrix metalloproteinase 14 transcription.International journal of oncology · 2026Article
- Gene Variations in RNA Modification Pathway Linked to Poor Survival After Gastric Cancer Surgery.Genes · 2026Article
- Identification of senescence-related genes as diagnostic biomarkers for gastric cancer using bioinformatics and machine learning.Discover oncology · 2026Article
- Integrative immunogenomic and experimental characterization reveals CXCL9, CXCL13, CCL5 and CD74 as key oncogenic drivers in breast cancer.Mammalian genome : official journal of the International Mammalian Genome Society · 2026Article
- RHCG inhibition promotes the sensitivity of PIK3CA-mutant non-small lung cancer to PI3K inhibitor.Histology and histopathology · 2026Article
- ITPG: an immune-related transcriptomic predictive model for gastric cancer prognosis.Translational cancer research · 2026Article
- A Real-Time Online Nomogram Integrating Systemic Inflammatory Response Index and Lactate Dehydrogenase to Predict Pathological Response in Gastric Cancer Patients Receiving Neoadjuvant Chemoimmunotherapy.Cancer management and research · 2026Article
- Development and clinical application of a postoperative complication prognosis prediction model for gastric cancer patients based on automated machine learning with body fat rate.Frontiers in oncology · 2026Article
- Correlation of serum exosomal miR-21 with the risk of gastric cancer onset: its value for early diagnosis.American journal of translational research · 2026Article
- Glycogen metabolic dysfunction in T2DM with MASLD: linking α-hydroxybutyrate to GYS2 downregulation.Frontiers in nutrition · 2026Article
- A risk prediction model for metachronous peritoneal metastasis after radical gastrectomy in gastric cancer based on peripheral blood inflammatory markers and tumor pathological features.American journal of translational research · 2026Article
- Multi-omics integration and Mendelian randomization elucidate the PARP16-UPR axis driving chemoresistancein gastric cancer.Frontiers in oncology · 2026Article
- Article
- Navigating the molecular landscape: integrated multiomics liquid biopsy for biomarker discovery in early detection and monitoring of colorectal cancer.Frontiers in molecular biosciences · 2026Review
- Identification of Potential Biomarkers and Drugs for Papillary Thyroid Carcinoma Using Computational Analysis and Molecular Docking.Current medicinal chemistry · 2026Article
- miR-1343-3p regulating OGDHL/PDHB-pyruvate glucose metabolic reprogramming against gastric cancer cell proliferation.Discover oncology · 2025Article
- Tumor Immune Contexture Model Predicts Prognosis and Immunotherapy Response in Gastric Cancer.The journal of gene medicine · 2025Article
- Machine learning identifies INHBA DPT ADH7 FBP2 and GPR155 as diagnostic biomarkers for gastric cancer.Discover oncology · 2025Article
- Unveiling the role of gastric cancer-associated mesenchymal stem cells and neutrophil extracellular traps through multi-omics analysis.Stem cell research & therapy · 2025Article
Corrections and comments
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Authors and funding
2 authors.
Funding
Abstract
Gastric cancer (GC) is one of the most common cancers worldwide. Most patients are diagnosed at the progressive stage of the disease, and current anticancer drug advancements are still lacking. Therefore, it is crucial to find relevant biomarkers with the accurate prediction of prognoses and good predictive accuracy to select appropriate patients with GC. Recent advances in molecular profiling technologies, including genomics, epigenomics, transcriptomics, proteomics, and metabolomics, have enabled the approach of GC biology at multiple levels of omics interaction networks. Systemic biological analyses, such as computational inference of "big data" and advanced bioinformatic approaches, are emerging to identify the key molecular biomarkers of GC, which would benefit targeted therapies. This review summarizes the current status of how bioinformatics analysis contributes to biomarker discovery for prognosis and prediction of therapeutic efficacy in GC based on a search of the medical literature. We highlight emerging individual multi-omics datasets, such as genomics, epigenomics, transcriptomics, proteomics, and metabolomics, for validating putative markers. Finally, we discuss the current challenges and future perspectives to integrate multi-omics analysis for improving biomarker implementation. The practical integration of bioinformatics analysis and multi-omics datasets under complementary computational analysis is having a great impact on the search for predictive and prognostic biomarkers and may lead to an important revolution in treatment.
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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.