ArticleFrontiers in oncology2021
Somatic Copy Number Alterations in Human Cancers: An Analysis of Publicly Available Data From The Cancer Genome Atlas.
Article in Frontiers in oncology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 34 papers.
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Who cites it
34 citing papers in PubMed, 63 citations in OpenAlex.
- Exploring copy number alterations (CNAs) to gain new insight into SCLC heterogeneity.Molecular biology reports · 2026Review
- Article
- EXaCT-2: an augmented and customizable oncology-focused whole exome sequencing platform.NPJ precision oncology · 2026Article
- CRESCENT: a deep learning framework with multi-scale attention for detecting recurrent copy number alterations.Briefings in bioinformatics · 2026Article
- Extending differential gene expression testing to handle genome aneuploidy in cancer.PLoS computational biology · 2026Article
- Gene amplification in the premalignant stages of non-small cell lung cancer development.Frontiers in oncology · 2026Review
- Complex landscape of somatic copy number alterations in head and neck paragangliomas.Frontiers in endocrinology · 2026Article
- SISTEM: simulation of tumor evolution, metastasis, and DNA-seq data under genotype-driven selection.Bioinformatics (Oxford, England) · 2025Article
- Advances and challenges in circulating tumor DNA-based early detection of lung cancer.Translational cancer research · 2025Review
- Utility of Germline, Somatic and ctDNA Testing in Adults With Cancer.Cancer medicine · 2025Review
- DICE: fast and accurate distance-based reconstruction of single-cell copy number phylogenies.Life science alliance · 2025Article
- Nanopore-based random genomic sampling for intraoperative molecular diagnosis.Genome medicine · 2025Article
- Integrative spatial and genomic analysis of tumor heterogeneity with Tumoroscope.Nature communications · 2024Article
- Article
- The genomic landscape of lung cancer in never-smokers from the Women's Health Initiative.JCI insight · 2024Article
- Tissue of origin detection for cancer tumor using low-depth cfDNA samples through combination of tumor-specific methylation atlas and genome-wide methylation density in graph convolutional neural networks.Journal of translational medicine · 2024Article
- Insights into the Clinical, Biological and Therapeutic Impact of Copy Number Alteration in Cancer.International journal of molecular sciences · 2024Review
- CopyVAE: a variational autoencoder-based approach for copy number variation inference using single-cell transcriptomics.Bioinformatics (Oxford, England) · 2024Article
- High clonal diversity and spatial genetic admixture in early prostate cancer and surrounding normal tissue.Nature communications · 2024Article
- Classification of tumor types using XGBoost machine learning model: a vector space transformation of genomic alterations.Journal of translational medicine · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors at 4 institutions in 3 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Somatic copy number alterations (SCNAs) are a pervasive trait of human cancers that contributes to tumorigenesis by affecting the dosage of multiple genes at the same time. In the past decade, The Cancer Genome Atlas (TCGA) and the International Cancer Genome Consortium (ICGC) initiatives have generated and made publicly available SCNA genomic profiles from thousands of tumor samples across multiple cancer types. Here, we present a comprehensive analysis of 853,218 SCNAs across 10,729 tumor samples belonging to 32 cancer types using TCGA data. We then discuss current models for how SCNAs likely arise during carcinogenesis and how genomic SCNA profiles can inform clinical practice. Lastly, we highlight open questions in the field of cancer-associated SCNAs.
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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.