ArticleJournal of personalized medicine2021
Comprehensive Profiling of Genomic and Transcriptomic Differences between Risk Groups of Lung Adenocarcinoma and Lung Squamous Cell Carcinoma.
Article in Journal of personalized medicine, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers.
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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
23 citing papers in PubMed, 30 citations in OpenAlex.
- Integrative Analysis UncoversCurrent issues in molecular biology · 2026Article
- Analysis ofInternational journal of molecular sciences · 2026Article
- Data-driven universal insights into tumorigenesis via hallmark networks.NPJ systems biology and applications · 2025Article
- RNA-seq and bulk RNA-seq data analysis of cancer-related fibroblasts (CAF) in LUAD to construct a CAF-based risk signature.Scientific reports · 2024Article
- Clinically relevant stratification of lung squamous carcinoma patients based on ubiquitinated proteasome genes for 3P medical approach.The EPMA journal · 2024Article
- OVOL2 induces autophagy-mediated epithelial-mesenchymal transition by the ERK1/2 MAPK signaling in lung adenocarcinoma.iScience · 2024Article
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- Forkhead box N1 is possibly a novel biomarker and prognostic indicator for patients with squamous cell lung carcinoma.International journal of medical sciences · 2024Article
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- Comparative Transcriptome Profiles of Human HaCaT Cells in Response toLife (Basel, Switzerland) · 2023Article
- Prognostic Significance of Iron Metabolism Related Genes in Human Lung Adenocarcinoma.Cancer management and research · 2023Article
- Evaluating the Expression and Prognostic Value of Genes Encoding Microtubule-Associated Proteins in Lung Cancer.International journal of molecular sciences · 2022Article
- The identification of hub biomarkers and pathways in lung cancer and prognostic evaluation.Translational cancer research · 2022Article
- AC099850.3/NCAPG Axis Predicts Poor Prognosis and is Associated with Resistance to EGFR Tyrosine-Kinase Inhibitors in Lung Adenocarcinoma.International journal of general medicine · 2022Article
- KDM6A missense variants hamper H3 histone demethylation in lung squamous cell carcinoma.Computational and structural biotechnology journal · 2022Article
- M6A-Related Bioinformatics Analysis Reveals a New Prognostic Risk Signature in Cutaneous Malignant Melanoma.Disease markers · 2022Article
- An integrated model ofAnnals of translational medicine · 2021Article
- Risk Score Generated from CT-Based Radiomics Signatures for Overall Survival Prediction in Non-Small Cell Lung Cancer.Cancers · 2021Article
- Recent Developments in Cancer Systems Biology: Lessons Learned and Future Directions.Journal of personalized medicine · 2021Article
- Predictive Value of Max's Giant Associated Protein Mutation in Outcomes of Lung Adenocarcinoma Patients Treated With Immune Checkpoint Inhibitors.Frontiers in cell and developmental biology · 2021Article
Corrections and comments
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Authors and funding
2 authors at 1 institution in 1 country.
Funding
Abstract
Lung cancer is the second most frequently diagnosed cancer type and responsible for the highest number of cancer deaths worldwide. Lung adenocarcinoma (LUAD) and lung squamous cell carcinoma (LUSC) are subtypes of non-small-cell lung cancer which has the highest frequency of lung cancer cases. We aimed to analyze genomic and transcriptomic variations including simple nucleotide variations (SNVs), copy number variations (CNVs) and differential expressed genes (DEGs) in order to find key genes and pathways for diagnostic and prognostic prediction for lung adenocarcinoma and lung squamous cell carcinoma. We performed a univariate Cox model and then lasso-regularized Cox model with leave-one-out cross-validation using The Cancer Genome Atlas (TCGA) gene expression data in tumor samples. We generated 35- and 33-gene signatures for prognostic risk prediction based on the overall survival time of the patients with LUAD and LUSC, respectively. When we clustered patients into high- and low-risk groups, the survival analysis showed highly significant results with high prediction power for both training and test datasets. Then, we characterized the differences including significant SNVs, CNVs, DEGs, active subnetworks, and the pathways. We described the results for the risk groups and cancer subtypes separately to identify specific genomic alterations between both high-risk groups and cancer subtypes. Both LUAD and LUSC high-risk groups have more downregulated immune pathways and upregulated metabolic pathways. On the other hand, low-risk groups have both up- and downregulated genes on cancer-related pathways. Both LUAD and LUSC have important gene alterations such as CDKN2A and CDKN2B deletions with different frequencies. SOX2 amplification occurs in LUSC and PSMD4 amplification in LUAD. EGFR and KRAS mutations are mutually exclusive in LUAD samples. EGFR, MGA, SMARCA4, ATM, RBM10, and KDM5C genes are mutated only in LUAD but not in LUSC. CDKN2A, PTEN, and HRAS genes are mutated only in LUSC samples. The low-risk groups of both LUAD and LUSC tend to have a higher number of SNVs, CNVs, and DEGs. The signature genes and altered genes have the potential to be used as diagnostic and prognostic biomarkers for personalized oncology.
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