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The Mutation Portraits of Oncogenes and Tumor Supressor Genes in Predicting the Overall Survival in Pancreatic Cancer: A Bayesian Network Meta-Analysis

INTRODUCTION: In 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 w...

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Autores principales: Aryanti, Citra, Uwuratuw, Julianus Aboyaman, Labeda, Ibrahim, Raharjo, Warsinggih, Lusikooy, Ronald Erasio, Abdul Rauf, Murny, Mappincara, Andi, Sampetoding, Samuel, Kusuma, M. Ihwan, Syarifuddin, Erwin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: West Asia Organization for Cancer Prevention 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10685232/
https://www.ncbi.nlm.nih.gov/pubmed/37642079
http://dx.doi.org/10.31557/APJCP.2023.24.8.2895
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author Aryanti, Citra
Uwuratuw, Julianus Aboyaman
Labeda, Ibrahim
Raharjo, Warsinggih
Lusikooy, Ronald Erasio
Abdul Rauf, Murny
Mappincara, Andi
Sampetoding, Samuel
Kusuma, M. Ihwan
Syarifuddin, Erwin
author_facet Aryanti, Citra
Uwuratuw, Julianus Aboyaman
Labeda, Ibrahim
Raharjo, Warsinggih
Lusikooy, Ronald Erasio
Abdul Rauf, Murny
Mappincara, Andi
Sampetoding, Samuel
Kusuma, M. Ihwan
Syarifuddin, Erwin
author_sort Aryanti, Citra
collection PubMed
description INTRODUCTION: In 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. METHODS: The 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. RESULTS: Twenty-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. CONCLUSION: In 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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spelling pubmed-106852322023-11-30 The Mutation Portraits of Oncogenes and Tumor Supressor Genes in Predicting the Overall Survival in Pancreatic Cancer: A Bayesian Network Meta-Analysis Aryanti, Citra Uwuratuw, Julianus Aboyaman Labeda, Ibrahim Raharjo, Warsinggih Lusikooy, Ronald Erasio Abdul Rauf, Murny Mappincara, Andi Sampetoding, Samuel Kusuma, M. Ihwan Syarifuddin, Erwin Asian Pac J Cancer Prev Research Article INTRODUCTION: In 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. METHODS: The 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. RESULTS: Twenty-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. CONCLUSION: In pancreatic cancer, the mutation of SMAD4 predicted the worst overall survival, compared to control, also mutation of HER2, KRAS, PD-L1, P53, and CDKN2A. West Asia Organization for Cancer Prevention 2023 /pmc/articles/PMC10685232/ /pubmed/37642079 http://dx.doi.org/10.31557/APJCP.2023.24.8.2895 Text en https://creativecommons.org/licenses/by-nc/4.0/This work is licensed under a Creative Commons Attribution-Non Commercial 4.0 International License. (https://creativecommons.org/licenses/by-nc/4.0/)
spellingShingle Research Article
Aryanti, Citra
Uwuratuw, Julianus Aboyaman
Labeda, Ibrahim
Raharjo, Warsinggih
Lusikooy, Ronald Erasio
Abdul Rauf, Murny
Mappincara, Andi
Sampetoding, Samuel
Kusuma, M. Ihwan
Syarifuddin, Erwin
The Mutation Portraits of Oncogenes and Tumor Supressor Genes in Predicting the Overall Survival in Pancreatic Cancer: A Bayesian Network Meta-Analysis
title The Mutation Portraits of Oncogenes and Tumor Supressor Genes in Predicting the Overall Survival in Pancreatic Cancer: A Bayesian Network Meta-Analysis
title_full The Mutation Portraits of Oncogenes and Tumor Supressor Genes in Predicting the Overall Survival in Pancreatic Cancer: A Bayesian Network Meta-Analysis
title_fullStr The Mutation Portraits of Oncogenes and Tumor Supressor Genes in Predicting the Overall Survival in Pancreatic Cancer: A Bayesian Network Meta-Analysis
title_full_unstemmed The Mutation Portraits of Oncogenes and Tumor Supressor Genes in Predicting the Overall Survival in Pancreatic Cancer: A Bayesian Network Meta-Analysis
title_short The Mutation Portraits of Oncogenes and Tumor Supressor Genes in Predicting the Overall Survival in Pancreatic Cancer: A Bayesian Network Meta-Analysis
title_sort mutation portraits of oncogenes and tumor supressor genes in predicting the overall survival in pancreatic cancer: a bayesian network meta-analysis
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10685232/
https://www.ncbi.nlm.nih.gov/pubmed/37642079
http://dx.doi.org/10.31557/APJCP.2023.24.8.2895
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