ArticleAsian Pacific journal of cancer prevention : APJCP2023
The Mutation Portraits of Oncogenes and Tumor Supressor Genes in Predicting the Overall Survival in Pancreatic Cancer: A Bayesian Network Meta-Analysis.
Article in Asian Pacific journal of cancer prevention : APJCP, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers, 1 of them a synthesis that pooled it.
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3 citing papers in PubMed, 1 synthesis or guideline pooled it, 4 citations in OpenAlex.
- Treatments for rotator cuff calcific tendinitis: a systematic review and network meta-analysis of randomized-controlled trials.EFORT open reviews · 2025Pooled it
- The Effect of Cuproptosis-Related Proteins on Macrophage Polarization in Mesothelioma is Revealed by scRNA-seq.Biological trace element research · 2025Article
- From Sequence to Solution: Intelligent Learning Engine Optimization in Drug Discovery and Protein Analysis.Biotech (Basel (Switzerland)) · 2024Article
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10 authors at 1 institution in 1 country.
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No grant is acknowledged in the PubMed record.
Abstract
introductionIn pancreatic cancer, the carcinogenesis can not be separated from genetics mutations. The portraits of genes alterations majorily including oncogenes (KRAS, HER2, PD-L1) and tumor supressor genes (P53, CDKN2A, SMAD4). Besides being notorious a screening marker, the genetic mutations were related to the prognosis of pancreatic cancer. The aim of this study is to determine the genetic mutations portrait in predicting the overall survival in pancreatic cancer.
methodsThe network meta analysis (NMA) was registered in PROSPERO (CRD42023397976) and conducted in accordance with the PRISMA-P (Preferred Reporting Items for Systematic Review and Meta-Analysis Protocols) in addition of NMA extension guidance. Comprehensive searches were done including all studies which reported the overall survival of pancreatic cancer subjects with KRAS, HER2, PD-L1, P53, CDKN2A, SMAD4. Data were collected and analysis will be done based on Bayesian method, Markov Chain Monte Carlo algorithm, using BUGSnet package in R studio. Transivity was controlled by methods and consistency of the NMA will be fitted by deviance information criterion. Data analysis in NMA were presented in Sucra plot, league table, and forest plot.
resultsTwenty-four studies were included in this NMA with 4613 total subjects. The NMA was conducted in random-effects, consistent, and convergence model. Relative to control, the genetic mutation of SMAD4 (HR 1.84; 95%CI 1.39-2.46), HER2 (HR 1.76; 95%CI 1.14-2.71), and KRAS (HR 1.7; 95%CI 1.19-2.48) were significant to have worse survival. The mutations of PD-L1, P53, and CDKN2A also showed poor survival, but not statistically significant compared to control.
conclusionIn pancreatic cancer, the mutation of SMAD4 predicted the worst overall survival, compared to control, also mutation of HER2, KRAS, PD-L1, P53, and CDKN2A.
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