ArticleCell reports methods2021
Pan-cancer analysis of pathway-based gene expression pattern at the individual level reveals biomarkers of clinical prognosis.
Article in Cell reports methods, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.
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Who cites it
18 citing papers in PubMed, 28 citations in OpenAlex.
- PhenoMapR: scalable mapping of sample phenotypes to single-cell, spatial, and bulk transcriptomics data.bioRxiv : the preprint server for biology · 2026Article
- Pathway potency in methylation altered network reveals lung cancer branching evolution and hallmarks.iScience · 2026Article
- IBAS: Interaction-bridged association studies discovering novel genes underlying complex traits.PLoS computational biology · 2026Article
- Identification of Clinically Relevant Genes Using Machine Learning Techniques.Methods in molecular biology (Clifton, N.J.) · 2026Article
- A spatially informed matrix normal model for gene co-expression analysis in spatial transcriptomics studies.Nucleic acids research · 2025Article
- Comprehensive analysis of prognosis markers with molecular features derived from pan-cancer whole-genome sequences.Human genomics · 2025Article
- Biological and clinical relevance of correlated expression levels of coding and long noncoding RNAs in HPV16 positive cervical cancers.Human genomics · 2024Article
- Surgical Tumor Resection Deregulates Hallmarks of Cancer in Resected Tissue and the Surrounding Microenvironment.Molecular cancer research : MCR · 2024Article
- Targeting neddylation and sumoylation in chemoresistant triple negative breast cancer.NPJ breast cancer · 2024Article
- Pathway Activation Analysis for Pan-Cancer Personalized Characterization Based on Riemannian Manifold.International journal of molecular sciences · 2024Article
- ssMutPA: single-sample mutation-based pathway analysis approach for cancer precision medicine.GigaScience · 2024Article
- Predictive value analysis of the interaction network of Tks4 scaffold protein in colon cancer.Frontiers in molecular biosciences · 2024Article
- Single sample pathway analysis in metabolomics: performance evaluation and application.BMC bioinformatics · 2022Article
- Molecular Biomarkers in Cancer.Biomolecules · 2022Review
- SWAN pathway-network identification of common aneuploidy-based oncogenic drivers.Nucleic acids research · 2022Article
- Determination of a DNA repair-related gene signature with potential implications for prognosis and therapeutic response in pancreatic adenocarcinoma.Frontiers in oncology · 2022Article
- Molecular Subclassification Based on Crosstalk Analysis Improves Prediction of Prognosis in Colorectal Cancer.Frontiers in genetics · 2021Article
- Autoencoder-Transformed Transcriptome Improves Genotype-Phenotype Association Studies.IEEE transactions on computational biology and bioinformaticsArticle
Corrections and comments
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Authors and funding
7 authors at 2 institutions in 1 country.
Funding
Abstract
Identifying biomarkers to predict the clinical outcomes of individual patients is a fundamental problem in clinical oncology. Multiple single-gene biomarkers have already been identified and used in clinics. However, multiple oncogenes or tumor-suppressor genes are involved during the process of tumorigenesis. Additionally, the efficacy of single-gene biomarkers is limited by the extensively variable expression levels measured by high-throughput assays. In this study, we hypothesize that in individual tumor samples, the disruption of transcription homeostasis in key pathways or gene sets plays an important role in tumorigenesis and has profound implications for the patient's clinical outcome. We devised a computational method named iPath to identify, at the individual-sample level, which pathways or gene sets significantly deviate from their norms. We conducted a pan-cancer analysis and demonstrated that iPath is capable of identifying highly predictive biomarkers for clinical outcomes, including overall survival, tumor subtypes, and tumor-stage classifications.
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Registered trials
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