ArticleiMeta2025
iMLGAM: Integrated Machine Learning and Genetic Algorithm-driven Multiomics analysis for pan-cancer immunotherapy response prediction.
Article in iMeta, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 121 papers, 1 of them a synthesis that pooled it.
What it found
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Who cites it
121 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Efficacy and Safety of EGF/EGFR Vaccines in EGFR-Driven Solid Tumors: A Systematic Review and Meta-Analysis of Controlled and Single-Arm Studies.Cancer medicine · 2025Pooled it
- The immune signatures predict gastric/gastroesophageal junction cancer response to first-line anti-PD-1 blockade or chemotherapy.BMC cancer · 2025Trial
- Review
- Clinical translation of senescence-related pan-cancer multi-omics: tools for assessment and immunotherapy prediction.Cancer gene therapy · 2026Article
- Comprehensive overview of AI methodologies in nano-drug delivery Optimization and Design.NPJ precision oncology · 2026Review
- Applications of Artificial Intelligence in Cancer Diagnosis and Treatment.Cancer medicine · 2026Review
- AI-driven multi-omics deciphering of extrachromosomal circular DNA rescues hidden targets in colorectal cancer.Cell communication and signaling : CCS · 2026Article
- Integrating AI-driven single-cell analysis to decode epithelial heterogeneity: A prognostic signature and translational immunotherapy strategy targetingChinese journal of cancer research = Chung-kuo yen cheng yen chiu · 2026Article
- A new era of precision diagnosis and treatment for lung cancer: artificial intelligence-driven multimodal data integration and clinical applications.Cell death & disease · 2026Review
- Pan-cancer characterization of POSTN and its clinical and microenvironmental associations in ERScientific reports · 2026Article
- Identification of glycolysis -correlative features for predicting prognosis and investigating immune landscape in prostate cancer.BMC cancer · 2026Article
- Integrative analysis of polyamine-associated genes reveals a prognostic and immunological signature in esophageal squamous cell carcinoma.Discover oncology · 2026Article
- Integrative single-cell and machine learning framework reveals prognostic fibroblast subtypes and constructs a fibroblast-related risk signature in lung adenocarcinoma.Scientific reports · 2026Article
- PTGDS is a potential marker for lung adenocarcinoma identified in a pancancer analysis.Scientific reports · 2026Article
- ICIsc: A Deep Learning Framework for Predicting Immune Checkpoint Inhibitor Response by Integrating scRNA-Seq and Protein Language Models.Bioengineering (Basel, Switzerland) · 2026Article
- Single-cell analysis identifies a stemness-associated tumor cell subpopulation and develops a prognostic scoring model in esophageal squamous cell carcinoma.Translational oncology · 2026Article
- Single-cell profiling of bone metastasis ecosystems reveals pivotal role of INSRTranslational oncology · 2026Article
- Multi-omics characterization identifies AHCY as a prognostic biomarker driving immunometabolic reprogramming in bladder cancer.Translational oncology · 2026Article
- Clinical risk prediction in lung adenocarcinoma using MAL gene and tumor microenvironment features.Discover oncology · 2026Article
- Comprehensive pan-cancer analysis of RPRD1B as a promising diagnostic and prognostic biomarker.Discover oncology · 2026Article
61 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
15 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
To address the substantial variability in immune checkpoint blockade (ICB) therapy effectiveness, we developed an innovative R package called integrated Machine Learning and Genetic Algorithm-driven Multiomics analysis (iMLGAM), which establishes a comprehensive scoring system for predicting treatment outcomes through advanced multi-omics data integration. Our research demonstrates that iMLGAM scores exhibit superior predictive performance across independent cohorts, with lower scores correlating significantly with enhanced therapeutic responses and outperforming existing clinical biomarkers. Detailed analysis revealed that tumors with low iMLGAM scores display distinctive immune microenvironment characteristics, including increased immune cell infiltration and amplified antitumor immune responses. Critically, through clustered regularly interspaced short palindromic repeats screening, we identified Centrosomal Protein 55 (
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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.