ArticleNucleic acids research2014
Isoform-level gene signature improves prognostic stratification and accurately classifies glioblastoma subtypes.
Article in Nucleic acids research, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 42 papers.
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Who cites it
42 citing papers in PubMed.
- Immune-associated alternative splicing signatures define molecular subtypes in breast cancer.iScience · 2026Article
- Solid Tumors Pan Cancer Transcriptome: Tissue/Cancer specific expression groups at the Isoform-Level.bioRxiv : the preprint server for biology · 2026Article
- Integrating WGCNA and machine learning algorithm to identify ACSM5 as a prognostic biomarker and therapeutic target for predicting immunotherapy efficacy in non-small cell lung cancer.Translational cancer research · 2026Article
- Global profiling of alternative splicing in non-small cell lung cancer reveals novel histological and population differences.Oncogene · 2025Article
- Integrating imaging and genomic data for the discovery of distinct glioblastoma subtypes: a joint learning approach.Scientific reports · 2024Article
- Leveraging multi-omics data to infer regulators of mRNA 3' end processing in glioblastoma.Frontiers in molecular biosciences · 2024Article
- Systemic and local immunosuppression in glioblastoma and its prognostic significance.Frontiers in immunology · 2024Review
- Rapid, High-Throughput Single-Cell Multiplex In Situ Tagging (MIST) Analysis of Immunological Disease with Machine Learning.Analytical chemistry · 2023Article
- Exploring lncRNAs associated with human pancreatic islet cell death induced by transfer of adoptive lymphocytes in a humanized mouse model.Frontiers in endocrinology · 2023Article
- Deep multi-omics integration by learning correlation-maximizing representation identifies prognostically stratified cancer subtypes.Bioinformatics advances · 2023Article
- Glioblastoma Molecular Classification Tool Based on mRNA Analysis: From Wet-Lab to Subtype.International journal of molecular sciences · 2022Article
- IntAPT: integrated assembly of phenotype-specific transcripts from multiple RNA-seq profiles.Bioinformatics (Oxford, England) · 2021Article
- A novel gene signature based on five immune checkpoint genes predicts the survival of glioma.Chinese neurosurgical journal · 2021Article
- Characterization and prognostic significance of alternative splicing events in lower-grade diffuse gliomas.Journal of cellular and molecular medicine · 2020Article
- Identification of Prognostic Signatures of Alternative Splicing in Glioma.Journal of molecular neuroscience : MN · 2020Article
- Systematic profiling of alternative splicing signature reveals prognostic predictor for prostate cancer.Cancer science · 2020Article
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- ShinyButchR: Interactive NMF-based decomposition workflow of genome-scale datasets.Biology methods & protocols · 2020Article
- Immune landscapes associated with different glioblastoma molecular subtypes.Acta neuropathologica communications · 2019Article
Corrections and comments
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Authors and funding
6 authors.
Funding
Abstract
Molecular stratification of tumors is essential for developing personalized therapies. Although patient stratification strategies have been successful; computational methods to accurately translate the gene-signature from high-throughput platform to a clinically adaptable low-dimensional platform are currently lacking. Here, we describe PIGExClass (platform-independent isoform-level gene-expression based classification-system), a novel computational approach to derive and then transfer gene-signatures from one analytical platform to another. We applied PIGExClass to design a reverse transcriptase-quantitative polymerase chain reaction (RT-qPCR) based molecular-subtyping assay for glioblastoma multiforme (GBM), the most aggressive primary brain tumors. Unsupervised clustering of TCGA (the Cancer Genome Altas Consortium) GBM samples, based on isoform-level gene-expression profiles, recaptured the four known molecular subgroups but switched the subtype for 19% of the samples, resulting in significant (P = 0.0103) survival differences among the refined subgroups. PIGExClass derived four-class classifier, which requires only 121 transcript-variants, assigns GBM patients' molecular subtype with 92% accuracy. This classifier was translated to an RT-qPCR assay and validated in an independent cohort of 206 GBM samples. Our results demonstrate the efficacy of PIGExClass in the design of clinically adaptable molecular subtyping assay and have implications for developing robust diagnostic assays for cancer patient stratification.
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