ArticleGenes, chromosomes & cancer2017
Genome-wide copy number variation pattern analysis and a classification signature for non-small cell lung cancer.
Article in Genes, chromosomes & cancer, 2017. 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.
- CNAttention: an attention-based deep multiple-instance method for uncovering copy number aberration signatures across cancers.Briefings in bioinformatics · 2026Article
- Gene amplification in the premalignant stages of non-small cell lung cancer development.Frontiers in oncology · 2026Review
- A fusion-based multiomics classification approach for enhanced gene discovery in non-small cell lung cancer.Bioinformatics advances · 2026Article
- The Added Value of Genome-Wide Copy Numbers to Objectively Resolve Clonality of Multiple Tumors With Pulmonary Involvement and Ambiguous or Inconclusive Mutational Diagnosis.JTO clinical and research reports · 2025Article
- Mitochondrial Ribosomal Protein S17 Silencing Inhibits Proliferation and Invasiveness of Lung Cancer Cells.Journal of cancer prevention · 2025Article
- Article
- Proteogenomic analysis reveals non-small cell lung cancer subtypes predicting chromosome instability, and tumor microenvironment.Nature communications · 2024Article
- DNA variants detected in primary and metastatic lung adenocarcinoma: a case report and review of the literature.Laboratory medicine · 2024Review
- NKX2‑1 copy number alterations are associated with oncogenic, immunological and prognostic remodeling in non‑small cell lung cancer.Oncology letters · 2024Article
- Assessment of MYC and TERT copy number variations in lung cancer using digital PCR.BMC research notes · 2023Article
- Genomic analysis and clinical correlations of non-small cell lung cancer brain metastasis.Nature communications · 2023Article
- Intratumoral Microbiota-Host Interactions Shape the Variability of Lung Adenocarcinoma and Lung Squamous Cell Carcinoma in Recurrence and Metastasis.Microbiology spectrum · 2023Article
- A Genomically and Clinically Annotated Patient-Derived Xenograft Resource for Preclinical Research in Non-Small Cell Lung Cancer.Cancer research · 2022Article
- Machine-Learning-Based Late Fusion on Multi-Omics and Multi-Scale Data for Non-Small-Cell Lung Cancer Diagnosis.Journal of personalized medicine · 2022Article
- High expression of HOXB3 predicts poor prognosis and correlates with tumor immunity in lung adenocarcinoma.Molecular biology reports · 2022Article
- Circular RNA hsa_circ_0008003 facilitates tumorigenesis and development of non-small cell lung carcinoma via modulating miR-488/ZNF281 axis.Journal of cellular and molecular medicine · 2022Article
- MicroRNA-140-3p represses the proliferation, migration, invasion and angiogenesis of lung adenocarcinoma cells via targeting TYMS (thymidylate synthetase).Bioengineered · 2021Article
- ER expression associates with poor prognosis in male lung squamous carcinoma after radical resection.BMC cancer · 2021Article
- Low-Coverage Whole Genome Sequencing of Cell-Free DNA From Immunosuppressed Cancer Patients Enables Tumor Fraction Determination and Reveals Relevant Copy Number Alterations.Frontiers in cell and developmental biology · 2021Article
- Downregulation of mInternational journal of biological sciences · 2021Article
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4 authors.
Funding
Abstract
The accurate classification of non-small cell lung carcinoma (NSCLC) into lung adenocarcinoma (LUAD) and lung squamous cell carcinoma (LUSC) is essential for both clinical practice and lung cancer research. Although the standard WHO diagnosis of NSCLC on biopsy material is rapid and economic, more than 13% of NSCLC tumors in the USA are not further classified. The purpose of this study was to analyze the genome-wide pattern differences in copy number variations (CNVs) and to develop a CNV signature as an adjunct test for the routine histopathologic classification of NSCLCs. We investigated the genome-wide CNV differences between these two tumor types using three independent patient datasets. Approximately half of the genes examined exhibited significant differences between LUAD and LUSC tumors and the corresponding non-malignant tissues. A new classifier was developed to identify signature genes out of 20 000 genes. Thirty-three genes were identified as a CNV signature of NSCLC. Using only their CNV values, the classification model separated the LUADs from the LUSCs with an accuracy of 0.88 and 0.84, respectively, in the training and validation datasets. The same signature also classified NSCLC tumors from their corresponding non-malignant samples with an accuracy of 0.96 and 0.98, respectively. We also compared the CNV patterns of NSCLC tumors with those of histologically similar tumors arising at other sites, such as the breast, head, and neck, and four additional tumors. Of greater importance, the significant differences between these tumors may offer the possibility of identifying the origin of tumors whose origin is unknown.
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