ArticleFrontiers in cell and developmental biology2021
Prognostic Signature for Lung Adenocarcinoma Patients Based on Cell-Cycle-Related Genes.
Article in Frontiers in cell and developmental biology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.
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Who cites it
15 citing papers in PubMed.
- Single-patient single-cell RNA sequencing reveals neuroendocrine predominance and immunosuppression in small-cell lung cancer.Translational cancer research · 2026Article
- Identification of a Novel Subset of Human Airway Epithelial Basal Stem Cells.International journal of molecular sciences · 2024Article
- Inhibition of LSD1 induces ferroptosis through the ATF4-xCT pathway and shows enhanced anti-tumor effects with ferroptosis inducers in NSCLC.Cell death & disease · 2023Article
- Genome instability-derived genes as a novel prognostic signature for lung adenocarcinoma.Frontiers in cell and developmental biology · 2023Article
- A cell cycle-related lncRNA signature predicts the progression-free interval in papillary thyroid carcinoma.Frontiers in endocrinology · 2023Article
- Hypoxia-associated prognostic markers and competing endogenous RNA coexpression networks in lung adenocarcinoma.Scientific reports · 2022Article
- High-risk early-stage lung adenocarcinoma patients are identified by an immune-related circadian clock gene signature.Journal of thoracic disease · 2022Article
- Aberrant Expression of BUB1B Contributes to the Progression of Thyroid Carcinoma and Predicts Poor Outcomes for Patients.Journal of Cancer · 2022Article
- A more novel and powerful prognostic gene signature of lung adenocarcinoma determined from the immune cell infiltration landscape.Frontiers in surgery · 2022Article
- Integrating cell cycle score for precise risk stratification in ovarian cancer.Frontiers in genetics · 2022Article
- Comprehensive analyses unveil novel genomic and immunological characteristics of micropapillary pattern in lung adenocarcinoma.Frontiers in oncology · 2022Article
- Immune Landscape and Classification in Lung Adenocarcinoma Based on a Novel Cell Cycle Checkpoints Related Signature for Predicting Prognosis and Therapeutic Response.Frontiers in genetics · 2022Article
- Identification of a Six-Gene SLC Family Signature With Prognostic Value in Patients With Lung Adenocarcinoma.Frontiers in cell and developmental biology · 2021Article
- The Addition of Peripheral Blood Inflammatory Indexes to Nomogram Improves the Predictive Accuracy of Survival in Limited-Stage Small Cell Lung Cancer Patients.Frontiers in oncology · 2021Article
- Identification of Prognostic Gene Signatures for Survival of Patients With Phaeochromocytoma, Paraganglioma, and Other Tumor Types.Cancer diagnosis & prognosisArticle
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Authors and funding
6 authors.
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No grant is acknowledged in the PubMed record.
Abstract
objectiveTo screen lung adenocarcinoma (LUAC)-specific cell-cycle-related genes (CCRGs) and develop a prognostic signature for patients with LUAC.
methodsThe GSE68465, GSE42127, and GSE30219 data sets were downloaded from the GEO database. Single-sample gene set enrichment analysis was used to calculate the cell cycle enrichment of each sample in GSE68465 to identify CCRGs in LUAC. The differential CCRGs compared with LUAC data from The Cancer Genome Atlas were determined. The genetic data from GSE68465 were divided into an internal training group and a test group at a ratio of 1:1, and GSE42127 and GSE30219 were defined as external test groups. In addition, we combined LASSO (least absolute shrinkage and selection operator) and Cox regression analysis with the clinical information of the internal training group to construct a CCRG risk scoring model. Samples were divided into high- and low-risk groups according to the resulting risk values, and internal and external test sets were used to prove the validity of the signature. A nomogram evaluation model was used to predict prognosis. The CPTAC and HPA databases were chosen to verify the protein expression of CCRGs.
resultsWe identified 10 LUAC-specific CCRGs (PKMYT1, ETF1, ECT2, BUB1B, RECQL4, TFRC, COCH, TUBB2B, PITX1, and CDC6) and constructed a model using the internal training group. Based on this model, LUAC patients were divided into high- and low-risk groups for further validation. Time-dependent receiver operating characteristic and Cox regression analyses suggested that the signature could precisely predict the prognosis of LUAC patients. Results obtained with CPTAC, HPA, and IHC supported significant dysregulation of these CCRGs in LUAC tissues.
conclusionThis prognostic prediction signature based on CCRGs could help to evaluate the prognosis of LUAC patients. The 10 LUAC-specific CCRGs could be used as prognostic markers of LUAC.
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