ArticleFrontiers in oncology2021
Integrated Analysis of Cell Cycle-Related and Immunity-Related Biomarker Signatures to Improve the Prognosis Prediction of Lung Adenocarcinoma.
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 18 papers.
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18 citing papers in PubMed, 21 citations in OpenAlex.
- Machine learning-based multi-omic analysis identifies CEP55, DLGAP5, and EZH2 as regulated cell death biomarkers linked to immunotherapy resistance in hepatocellular carcinoma.Naunyn-Schmiedeberg's archives of pharmacology · 2026Article
- Multi-Omics reveals SPP1 + malignant and CXCR4Discover oncology · 2026Article
- Identification of Shared Pathways and Molecules Between Type 2 Diabetes and Lung Adenocarcinoma and the Impact of High Glucose Environment on Lung Adenocarcinoma.International journal of endocrinology · 2025Article
- A Multi-Faceted Approach to Explore the Role of Inflammatory CAFs, Providing Prognostic Value and Therapeutic Implications in Lung Adenocarcinoma.International journal of genomics · 2025Article
- Osteosarcoma-Associated Immune Genes as Potential Immunotherapy and Prognosis Biomarkers.Biochemical genetics · 2024Article
- Elevated RACGAP1 Expression Enhances Malignant Potential in Lung Adenocarcinoma and Serves as a Prognostic Factor.Journal of Cancer · 2024Article
- S100A6 is a potential diagnostic and prognostic biomarker for human glioma.Oncology letters · 2023Article
- SUMOylation patterns and signature characterize the tumor microenvironment and predict prognosis in lung adenocarcinoma.Frontiers in cell and developmental biology · 2023Article
- Integrated single-cell and transcriptome sequencing analyses develops a metastasis-based risk score system for prognosis and immunotherapy response in uveal melanoma.Frontiers in pharmacology · 2023Article
- A cell cycle-related lncRNA signature predicts the progression-free interval in papillary thyroid carcinoma.Frontiers in endocrinology · 2023Article
- Pan-cancer analysis of UBE2T with a focus on prognostic and immunological roles in lung adenocarcinoma.Respiratory research · 2022Article
- Analysis of immune related gene expression profiles and immune cell components in patients with Barrett esophagus.Scientific reports · 2022Article
- A Cell Cycle-Related 13-mRNA Signature to Predict Prognosis in Hepatocellular Carcinoma.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
- Pancancer Analysis of RevealedDisease markers · 2022Article
- A more novel and powerful prognostic gene signature of lung adenocarcinoma determined from the immune cell infiltration landscape.Frontiers in surgery · 2022Article
- Construction of a ferroptosis scoring system and identification of LINC01572 as a novel ferroptosis suppressor in lung adenocarcinoma.Frontiers in pharmacology · 2022Article
- Identification of the Shared Gene Signatures and Biological Mechanism in Type 2 Diabetes and Pancreatic Cancer.Frontiers in endocrinology · 2022Article
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Authors and funding
7 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundLung adenocarcinoma (LUAD) is a leading malignancy and has a poor prognosis over the decades. LUAD is characterized by dysregulation of cell cycle. Immunotherapy has emerged as an ideal option for treating LUAD. Nevertheless, optimal biomarkers to predict outcomes of immunotherapy is still ill-defined and little is known about the interaction of cell cycle-related genes (CCRGs) and immunity-related genes (IRGs).
methodsWe downloaded gene expression and clinical data from TCGA and GEO database. LASSO regression and Cox regression were used to construct a differentially expressed CCRGs and IRGs signature. We used Kaplan-Meier analysis to compare survival of LUAD patients. We constructed a nomogram to predict the survival and calibration curves were used to evaluate the accuracy.
resultsA total of 61 differentially expressed CCRGs and IRGs were screened out. We constructed a new risk model based on 8 genes, including ACVR1B, BIRC5, NR2E1, INSR, TGFA, BMP7, CD28, NUDT6. Subgroup analysis revealed the risk model accurately predicted the overall survival in LUAD patients with different clinical features and was correlated with immune cells infiltration. A nomogram based on the risk model exhibited excellent performance in survival prediction of LUAD.
conclusionsThe 8 gene survival signature and nomogram in our study are effective and have potential clinical application to predict prognosis of LUAD.
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