ArticleGenome biology2022
Identifying common transcriptome signatures of cancer by interpreting deep learning models.
Article in Genome biology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers.
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Who cites it
24 citing papers in PubMed, 37 citations in OpenAlex.
- In silico generation of gene expression profiles using diffusion models.BMC bioinformatics · 2026Article
- Integrative interpretable learning reveals shared patterns of epitranscriptomic regulation across multiple cancer types.BMC biology · 2026Article
- Organism-Specific Sequence Motifs Link Ribosomal RNAs to Brain Disorders.Molecular biology and evolution · 2025Article
- Transcriptional patterns of cancer-related genes in primary and metastatic tumours revealed by machine learning.BMC biology · 2025Article
- Challenges in AI-driven Biomedical Multimodal Data Fusion and Analysis.Genomics, proteomics & bioinformatics · 2025Review
- Comparative RNA-Seq Analysis of Colon Spheroids and Patient-derived Tissues Identifies Non-Canonical Transcript Isoforms of Protein-Coding Genes Implicated in Colon Carcinogenesis.Cancer informatics · 2025Article
- Interpretable deep cross networks unveiled common signatures of dysregulated epitranscriptomes across 12 cancer types.Molecular therapy. Nucleic acids · 2024Article
- Article
- Gene choice in cancer cells is exclusive in ion transport but concurrent in DNA replication.Computational and structural biotechnology journal · 2024Article
- Human lncRNAs harbor conserved modules embedded in different sequence contexts.Non-coding RNA research · 2024Article
- Genomic strategies for drug repurposing.Journal of the Egyptian National Cancer Institute · 2024Review
- Advanced Prediction of Hepatic Oncogenic Transformation in HBV Patients via RNA-Seq Data Analysis and Deep Learning Techniques.International journal of molecular sciences · 2024Article
- A Comparison of Tools That Identify Tumor Cells by Inferring Copy Number Variations from Single-Cell Experiments in Pancreatic Ductal Adenocarcinoma.Biomedicines · 2024Article
- Designing interpretable deep learning applications for functional genomics: a quantitative analysis.Briefings in bioinformatics · 2024Review
- Pathologic features of brain hemorrhage after radiation treatment: case series with somatic mutation analysis.Journal of stroke and cerebrovascular diseases : the official journal of National Stroke Association · 2024Article
- Genomic Profiling and Molecular Characterisation of Metastatic Urothelial Carcinoma.Medicina (Kaunas, Lithuania) · 2024Review
- MAJIQlopedia: an encyclopedia of RNA splicing variations in human tissues and cancer.Nucleic acids research · 2024Article
- Immune, metabolic landscapes of prognostic signatures for lung adenocarcinoma based on a novel deep learning framework.Scientific reports · 2024Article
- Multi-omics based artificial intelligence for cancer research.Advances in cancer research · 2024Review
- Novel research and future prospects of artificial intelligence in cancer diagnosis and treatment.Journal of hematology & oncology · 2023Review
Corrections and comments
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Authors and funding
6 authors at 4 institutions in 1 country.
Funding
Abstract
backgroundCancer is a set of diseases characterized by unchecked cell proliferation and invasion of surrounding tissues. The many genes that have been genetically associated with cancer or shown to directly contribute to oncogenesis vary widely between tumor types, but common gene signatures that relate to core cancer pathways have also been identified. It is not clear, however, whether there exist additional sets of genes or transcriptomic features that are less well known in cancer biology but that are also commonly deregulated across several cancer types.
resultsHere, we agnostically identify transcriptomic features that are commonly shared between cancer types using 13,461 RNA-seq samples from 19 normal tissue types and 18 solid tumor types to train three feed-forward neural networks, based either on protein-coding gene expression, lncRNA expression, or splice junction use, to distinguish between normal and tumor samples. All three models recognize transcriptome signatures that are consistent across tumors. Analysis of attribution values extracted from our models reveals that genes that are commonly altered in cancer by expression or splicing variations are under strong evolutionary and selective constraints. Importantly, we find that genes composing our cancer transcriptome signatures are not frequently affected by mutations or genomic alterations and that their functions differ widely from the genes genetically associated with cancer.
conclusionsOur results highlighted that deregulation of RNA-processing genes and aberrant splicing are pervasive features on which core cancer pathways might converge across a large array of solid tumor types.
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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.