Background: Gliomas are the most intrinsic type of primary intracranial tumors. The protein encoded by The calponin 3 (CNN3) has been proven to be a member of the calponin family. Its relationships with cervical cancer, colorectal cancer, gastric cancer, and colon cancer have been emphasized by several studies. Our research aims to explore the prognosis value and immunotherapeutic targetability of CNN3 in glioma patients using bioinformatics approach.
Methods: CNN3 expression in glioma was analyzed based on GEO and TCGA datasets. Gene expression profiling with clinical information was employed to investigate the correlation between clinicopathological features of glioma patients and relative CNN3 expression levels. Survival analysis was conducted using Kaplan-Meier analysis and the Cox proportional-hazards regression model. Gene set enrichment analysis was conducted to select the pathways significantly enriched for CNN3 associations. Correlations between inflammatory activities, immune checkpoint molecules and CNN3 were probed by gene set variation analysis, correlograms, and correlation analysis.
Results: CNN3 was enriched in gliomas, and high expression of CNN3 correlated with worse clinicopathological features and prognosis. Associations between CNN3 and several immune-related pathways were confirmed using a bioinformatics approach. Correlation analysis revealed that CNN3 was associated with inflammatory and immune activities, tumor microenvironment, and immune checkpoint molecules.
Conclusion: Our results indicate that high CNN3 expression levels predict poor prognosis, and CNN3 may be a promising immunotherapy target.
Download full-text PDF |
Source |
|---|---|
| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8601287 | PMC |
| http://dx.doi.org/10.1097/MD.0000000000027931 | DOI Listing |
Publication Analysis
Top Keywords
Similar Publications
Proteomic Analysis of Biomarkers Predicting Treatment Response in Patients with Head and Neck Cancers.
Int J Mol Sci
November 2024
Department of Microbial Cellular and Molecular Biology, College of Natural and Computational Sciences, Addis Ababa University, Addis Ababa 9086, Ethiopia.
Head and neck cancers (HNCs) are the sixth most commonly diagnosed cancer and the eighth leading cause of cancer-related mortality worldwide, with squamous cell carcinoma being the most prevalent type. The global incidence of HNCs is steadily increasing, projected to rise by approximately 30% per year by 2030, a trend observed in both developed and undeveloped countries. This study involved serum proteomic profiling to identify predictive clinical biomarkers in cancer patients undergoing chemoradiotherapy (CRT).
View Article and Find Full Text PDFExamining the potential causal relationships among smoking behaviors, blood DNA methylation profiles, and the development of coronary heart disease and myocardial infarction.
Clin Epigenetics
November 2024
Division of Cardiology and Department of Internal Medicine, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, China.
Background: Smoking has been identified as a standalone risk factor for coronary heart disease (CHD) and myocardial infarction (MI), but the precise underlying mechanisms remain incompletely elucidated.
Results: In this study, we conducted a two-sample Mendelian randomization analysis to examine the impact of smoking behaviors (including smoking initiation, age of smoking initiation, cigarettes per day, and smoking cessation) and smoking-related DNA methylation at CpG sites on CHD and MI based on the UK Biobank dataset. Additionally, we included the FinnGen and Biobank Japan datasets as replications and performed a meta-analysis to combine the results from different data sources.
Molecules That Have Rarely Been Studied in Lymphatic Endothelial Cells.
Int J Mol Sci
November 2024
Institute of Anatomy and Cell Biology, University Medical Center Goettingen, Georg-August-University Goettingen, Kreuzbergring 36, 37075 Göttingen, Germany.
A number of standard molecules are used for the molecular and histological characterization of lymphatic endothelial cells (LECs), including lymphatic vessel endothelial hyaluronan receptor 1 (LYVE1), Podoplanin (D2-40), VEGFR3, Prospero homeobox protein 1 (PROX1), and CD31. The number of molecules whose mutations cause lymphatic malformations or primary congenital lymphedema is considerable, but the majority of these diseases have not yet been characterized at the molecular level. Therefore, there is still considerable scope for molecular and functional studies of the lymphatic vasculature.
View Article and Find Full Text PDFEnhanced skin cancer diagnosis through grid search algorithm-optimized deep learning models for skin lesion analysis.
Front Med (Lausanne)
November 2024
Department of Information Systems, College of Computer and Information Sciences, Princess Nourah Bint Abdulrahman University, Riyadh, Saudi Arabia.
Skin cancer is a widespread and perilous disease that necessitates prompt and precise detection for successful treatment. This research introduces a thorough method for identifying skin lesions by utilizing sophisticated deep learning (DL) techniques. The study utilizes three convolutional neural networks (CNNs)-CNN1, CNN2, and CNN3-each assigned to a distinct categorization job.
View Article and Find Full Text PDFDevelopment of a prognostic model incorporating a cuproptosis-related signature and CNN3 as a predictor in childhood acute myelocytic leukemia.
Front Oncol
November 2024
Department of Hematology and Oncology, Shenzhen Children's Hospital, Shenzhen, China.
Background: Childhood acute myeloid leukemia (cAML) is the second most common pediatric blood cancer, with high heterogeneity and poor prognosis. Recent studies have highlighted cuproptosis, a newly discovered form of programmed cell death triggered by the accumulation of intracellular copper ions, as a critical mechanism influencing cancer survival and resistance. Given its emerging role in cancer biology, we investigated cuproptosis-related genes (CRGs) in cAML to explore their potential in prognostic prediction and therapeutic targeting.
View Article and Find Full Text PDFWant AI Summaries of new PubMed Abstracts delivered to your In-box?
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!