SynthesisOncoimmunology2020
Identification of a costimulatory molecule-based signature for predicting prognosis risk and immunotherapy response in patients with lung adenocarcinoma.
Synthesis in Oncoimmunology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 44 papers.
What it found
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Who cites it
44 citing papers in PubMed, 58 citations in OpenAlex.
- Novel lipid metabolism-related gene signature associated with clinical and immune features in lung adenocarcinoma patients experiencing lymph node metastasis.Translational lung cancer research · 2026Article
- Single-cell dissection of pleural and systemic immunity uncovers pathogen-specific immune reprogramming in tuberculosis versus lung adenocarcinoma.Inflammation research : official journal of the European Histamine Research Society ... [et al.] · 2026Article
- Observational
- Aging-related signature stratifies LUAD prognosis and uncovers senescence-induced chemoresistance via NF-κB/RELA activation.Respiratory research · 2025Article
- Osimertinib resistance-based immune prognostic related gene signature in EGFR mutant lung adenocarcinoma, in which PSMD11 promotes tumor progression.Translational lung cancer research · 2025Article
- A novel risk score model incorporating six co-stimulatory molecules for accurate prognosis prediction of laryngeal cancer.Translational cancer research · 2025Article
- SIRT2 as a Potential Biomarker in Lung Adenocarcinoma: Implications for Immune Infiltration.Molecular biotechnology · 2025Article
- A review of enhanced biosignature immunotherapy tools for predicting lung cancer immune phenotypes using deep learning.Discover oncology · 2025Review
- Elevated levels of total cholesterol and high-density lipoprotein cholesterol are associated with better prognosis in patients with lung adenocarcinoma: a retrospective cohort study.Translational cancer research · 2025Article
- Article
- PANoptosis-related genes in the prognosis and immune landscape of hepatocellular carcinoma.Immunologic research · 2025Article
- A tumor-infiltrating B lymphocytes -related index based on machine-learning predicts prognosis and immunotherapy response in lung adenocarcinoma.Frontiers in immunology · 2025Article
- Interpretable artificial intelligence based on immunoregulation-related genes predicts prognosis and immunotherapy response in lung adenocarcinoma.Frontiers in bioinformatics · 2025Article
- Article
- Identification and validation of a costimulatory molecule-related signature to predict the prognosis for uveal melanoma patients.Scientific reports · 2024Article
- Identification of Key Prognostic Alternative Splicing Events of Costimulatory Molecule-Related Genes in Colon Cancer.Combinatorial chemistry & high throughput screening · 2024Article
- Integrating machine learning algorithms and multiple immunohistochemistry validation to unveil novel diagnostic markers based on costimulatory molecules for predicting immune microenvironment status in triple-negative breast cancer.Frontiers in immunology · 2024Article
- C-reactive protein and lactate dehydrogenase serum levels potentially predict the response to checkpoint inhibitors in patients with advanced non-small cell lung cancer.Journal of thoracic disease · 2023Article
- Costimulatory molecule expression profile as a biomarker to predict prognosis and chemotherapy response for patients with small cell lung cancer.Cancer immunology, immunotherapy : CII · 2023Article
- Costimulatory molecule-related lncRNA model as a potential prognostic biomarker in non-small cell lung cancer.Cancer medicine · 2023Article
Corrections and comments
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Authors and funding
9 authors at 2 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Costimulatory molecules play significant roles in mounting anti-tumor immune responses, and antibodies targeting these molecules are recognized as promising adjunctive cancer immunotherapies. Here, we aim to conduct a first full-scale exploration of costimulatory molecules from the B7-CD28 and TNF families in patients with lung adenocarcinoma (LUAD) and generated a costimulatory molecule-based signature (CMS) to predict survival and response to immunotherapy. Methods: We enrolled 1549 LUAD cases across 10 different cohorts and included 502 samples from TCGA for discovery. The validation set included 970 cases from eight different Gene Expression Omnibus (GEO) datasets and 77 frozen tumor tissues with qPCR data. The underlying mechanisms and predictive immunotherapy capabilities of the CMS were also explored. Results: A five gene-based CMS (CD40LG, TNFRSF6B, TNFSF13, TNFRSF13C, and TNFRSF19) was initially constructed using the bioinformatics method from TCGA that classifies cases as high- vs. low-risk groups per OS. Multivariable Cox regression analysis confirmed that the CMS was an independent prognostic factor. As expected, CMS exhibited prognostic significance in the stratified cohorts and different validation cohorts. Additionally, the prognostic meta-analysis revealed that CMS was superior to the previous signature. Samples in high- and low-risk groups exhibited significantly different tumor-infiltrating leukocytes and inflammatory activities. Importantly, we found that the CMS scores were closely related to multiple immunotherapy biomarkers. Conclusion: We conducted the first and most comprehensive costimulatory molecule landscape analysis of patients with LUAD and built a clinically feasible CMS for prognosis and immunotherapy response prediction, which will be helpful for further optimize immunotherapies for cancer.
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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.