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An Immune-Related Gene Panel for Preoperative Lymph Node Status Evaluation in Advanced Gastric Cancer
Background and Aim: Gastric cancer (GC) is the common leading cause of cancer-related death worldwide. Immune-related genes (IRGs) may potentially predict lymph node metastasis (LNM). We aimed to develop a preoperative model to predict LNM based on these IRGs. Methods: In this paper, we compared and...
Autores principales: | , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Hindawi
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7789469/ https://www.ncbi.nlm.nih.gov/pubmed/33490257 http://dx.doi.org/10.1155/2020/8450656 |
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author | Yang, Yuan Zheng, Ya Zhang, Hongling Miao, Yandong Wu, Guozhi Zhou, Lingshan Wang, Haoying Ji, Rui Guo, Qinghong Chen, Zhaofeng Wang, Jiangtao Wang, Yuping Zhou, Yongning |
author_facet | Yang, Yuan Zheng, Ya Zhang, Hongling Miao, Yandong Wu, Guozhi Zhou, Lingshan Wang, Haoying Ji, Rui Guo, Qinghong Chen, Zhaofeng Wang, Jiangtao Wang, Yuping Zhou, Yongning |
author_sort | Yang, Yuan |
collection | PubMed |
description | Background and Aim: Gastric cancer (GC) is the common leading cause of cancer-related death worldwide. Immune-related genes (IRGs) may potentially predict lymph node metastasis (LNM). We aimed to develop a preoperative model to predict LNM based on these IRGs. Methods: In this paper, we compared and evaluated three machine learning models to predict LNM based on publicly available gene expression data from TCGA-STAD. The Pearson correlation coefficient (PCC) method was utilized to feature selection according to its relationships with LN status. The performance of the model was assessed using the area under the curve (AUC) and F1 score. Results: The Naive Bayesian model showed better performance and was constructed based on 26 selected gene features, with AUCs of 0.741 in the training set and 0.688 in the test set. The F1 score in the training set and test set was 0.652 and 0.597, respectively. Furthermore, Naive Bayesian model based on 26 IRGs is the first diagnostic tool for the identification of LNM in advanced GC. Conclusion: These results indicate that our new methods have the value of auxiliary diagnosis with promising clinical potential. |
format | Online Article Text |
id | pubmed-7789469 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Hindawi |
record_format | MEDLINE/PubMed |
spelling | pubmed-77894692021-01-22 An Immune-Related Gene Panel for Preoperative Lymph Node Status Evaluation in Advanced Gastric Cancer Yang, Yuan Zheng, Ya Zhang, Hongling Miao, Yandong Wu, Guozhi Zhou, Lingshan Wang, Haoying Ji, Rui Guo, Qinghong Chen, Zhaofeng Wang, Jiangtao Wang, Yuping Zhou, Yongning Biomed Res Int Research Article Background and Aim: Gastric cancer (GC) is the common leading cause of cancer-related death worldwide. Immune-related genes (IRGs) may potentially predict lymph node metastasis (LNM). We aimed to develop a preoperative model to predict LNM based on these IRGs. Methods: In this paper, we compared and evaluated three machine learning models to predict LNM based on publicly available gene expression data from TCGA-STAD. The Pearson correlation coefficient (PCC) method was utilized to feature selection according to its relationships with LN status. The performance of the model was assessed using the area under the curve (AUC) and F1 score. Results: The Naive Bayesian model showed better performance and was constructed based on 26 selected gene features, with AUCs of 0.741 in the training set and 0.688 in the test set. The F1 score in the training set and test set was 0.652 and 0.597, respectively. Furthermore, Naive Bayesian model based on 26 IRGs is the first diagnostic tool for the identification of LNM in advanced GC. Conclusion: These results indicate that our new methods have the value of auxiliary diagnosis with promising clinical potential. Hindawi 2020-12-07 /pmc/articles/PMC7789469/ /pubmed/33490257 http://dx.doi.org/10.1155/2020/8450656 Text en Copyright © 2020 Yuan Yang et al. https://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research Article Yang, Yuan Zheng, Ya Zhang, Hongling Miao, Yandong Wu, Guozhi Zhou, Lingshan Wang, Haoying Ji, Rui Guo, Qinghong Chen, Zhaofeng Wang, Jiangtao Wang, Yuping Zhou, Yongning An Immune-Related Gene Panel for Preoperative Lymph Node Status Evaluation in Advanced Gastric Cancer |
title | An Immune-Related Gene Panel for Preoperative Lymph Node Status Evaluation in Advanced Gastric Cancer |
title_full | An Immune-Related Gene Panel for Preoperative Lymph Node Status Evaluation in Advanced Gastric Cancer |
title_fullStr | An Immune-Related Gene Panel for Preoperative Lymph Node Status Evaluation in Advanced Gastric Cancer |
title_full_unstemmed | An Immune-Related Gene Panel for Preoperative Lymph Node Status Evaluation in Advanced Gastric Cancer |
title_short | An Immune-Related Gene Panel for Preoperative Lymph Node Status Evaluation in Advanced Gastric Cancer |
title_sort | immune-related gene panel for preoperative lymph node status evaluation in advanced gastric cancer |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7789469/ https://www.ncbi.nlm.nih.gov/pubmed/33490257 http://dx.doi.org/10.1155/2020/8450656 |
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