ArticlePloS one2012
Integrative subtype discovery in glioblastoma using iCluster.
Article in PloS one, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 128 papers.
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.
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Who cites it
128 citing papers in PubMed.
- CSIE: cancer subtyping via inference and ensemble.Briefings in bioinformatics · 2026Article
- DBSCAN applied to EHRs data from patients with glioblastoma clusters patients based on cytosolic Hsp70 protein, sex, and brain subventricular zone.BioData mining · 2026Article
- Integrative Analysis of Multimodal Omics Data.Annual review of statistics and its application · 2026Article
- MetaPaCS: A Novel Meta-Learning Framework for Pancreatic Cancer Subtype Identification.bioRxiv : the preprint server for biology · 2026Article
- Integrative multi-omics and network biology in cardiovascular disease: a systems-level framework for translational discovery.Frontiers in systems biology · 2026Review
- MOTLAB: A Weighted Multi-Omics Transfer Learning Approach to Mitigate Breast Cancer Racial Disparities.bioRxiv : the preprint server for biology · 2025Article
- panomiX: Investigating mechanisms of trait emergence through multi-omics data integration.Plant phenomics (Washington, D.C.) · 2025Article
- DSCC: disease subtyping using spectral clustering and community detection from consensus networks.Briefings in bioinformatics · 2025Article
- Artificial Intelligence-Driven Multi-Omics Approaches in Glioblastoma.International journal of molecular sciences · 2025Review
- A Comprehensive Review of Deep Learning Applications with Multi-Omics Data in Cancer Research.Genes · 2025Review
- A comprehensive review of cancer survival prediction using multi-omics integration and clinical variables.Briefings in bioinformatics · 2025Review
- Heterogeneous Clustering of Multiomics Data for Breast Cancer Subgroup Classification and Detection.International journal of molecular sciences · 2025Article
- Multi-tissue metabolomics analysis reveals susceptible factors for chemotherapy-induced hepatotoxicity in colorectal cancer patients.Frontiers in pharmacology · 2025Article
- Article
- Unlocking the power of multi-institutional data: Integrating and harmonizing genomic data across institutions.Biometrics · 2024Article
- Bayesian Simultaneous Factorization and Prediction Using Multi-Omic Data.Computational statistics & data analysis · 2024Article
- scMNMF: a novel method for single-cell multi-omics clustering based on matrix factorization.Briefings in bioinformatics · 2024Article
- Integrating imaging and genomic data for the discovery of distinct glioblastoma subtypes: a joint learning approach.Scientific reports · 2024Article
- An extension of latent unknown clustering integrating multi-omics data (LUCID) incorporating incomplete omics data.Bioinformatics advances · 2024Article
- Pinpointing the integration of artificial intelligence in liver cancer immune microenvironment.Frontiers in immunology · 2024Review
68 more citing papers are in PubMed but not listed here.
Corrections and comments
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Authors and funding
8 authors.
Funding
Abstract
Large-scale cancer genome projects, such as the Cancer Genome Atlas (TCGA) project, are comprehensive molecular characterization efforts to accelerate our understanding of cancer biology and the discovery of new therapeutic targets. The accumulating wealth of multidimensional data provides a new paradigm for important research problems including cancer subtype discovery. The current standard approach relies on separate clustering analyses followed by manual integration. Results can be highly data type dependent, restricting the ability to discover new insights from multidimensional data. In this study, we present an integrative subtype analysis of the TCGA glioblastoma (GBM) data set. Our analysis revealed new insights through integrated subtype characterization. We found three distinct integrated tumor subtypes. Subtype 1 lacks the classical GBM events of chr 7 gain and chr 10 loss. This subclass is enriched for the G-CIMP phenotype and shows hypermethylation of genes involved in brain development and neuronal differentiation. The tumors in this subclass display a Proneural expression profile. Subtype 2 is characterized by a near complete association with EGFR amplification, overrepresentation of promoter methylation of homeobox and G-protein signaling genes, and a Classical expression profile. Subtype 3 is characterized by NF1 and PTEN alterations and exhibits a Mesenchymal-like expression profile. The data analysis workflow we propose provides a unified and computationally scalable framework to harness the full potential of large-scale integrated cancer genomic data for integrative subtype discovery.
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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.