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Prioritizing key synergistic circulating microRNAs for the early diagnosis of biliary tract cancer
Biliary tract cancer (BTC) is a highly aggressive malignant tumor. Serum microRNAs (ser-miRNAs) serve as noninvasive biomarkers to identify high risk individuals, thereby facilitating the design of precision therapies. The study is to prioritize key synergistic ser-miRNAs for the diagnosis of early...
Autores principales: | , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9582275/ https://www.ncbi.nlm.nih.gov/pubmed/36276146 http://dx.doi.org/10.3389/fonc.2022.968412 |
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author | Su, Fei Gao, Ziyu Liu, Yueyang Zhou, Guiqin Gao, Wei Deng, Chao Liu, Yuyu Zhang, Yihao Ma, Xiaoyan Wang, Yongxia Guan, Lili Zhang, Yafang Liu, Baoquan |
author_facet | Su, Fei Gao, Ziyu Liu, Yueyang Zhou, Guiqin Gao, Wei Deng, Chao Liu, Yuyu Zhang, Yihao Ma, Xiaoyan Wang, Yongxia Guan, Lili Zhang, Yafang Liu, Baoquan |
author_sort | Su, Fei |
collection | PubMed |
description | Biliary tract cancer (BTC) is a highly aggressive malignant tumor. Serum microRNAs (ser-miRNAs) serve as noninvasive biomarkers to identify high risk individuals, thereby facilitating the design of precision therapies. The study is to prioritize key synergistic ser-miRNAs for the diagnosis of early BTC. Sampling technology, significant analysis of microarrays, Pearson Correlation Coefficients, t-test, decision tree, and entropy weight were integrated to develop a global optimization algorithm of decision forest. The source code is available at https://github.com/SuFei-lab/GOADF.git. Four key synergistic ser-miRNAs were prioritized and the synergistic classification performance was better than the single miRNA’ s. In the internal feature evaluation dataset, the area under the receiver operating characteristic curve (AUC) for each single miRNA was 0.8413 (hsa-let-7c-5p), 0.7143 (hsa-miR-16-5p), 0.8571 (hsa-miR-17-5p), and 0.9365 (hsa-miR-26a-5p), respectively, whereas the synergistic AUC value increased to 1.0000. In the internal test dataset, the single AUC was 0.6500, 0.5125, 0.6750, and 0.7500, whereas the synergistic AUC increased to 0.8375. In the independent test dataset, the single AUC was 0.7280, 0.8313, 0.8957, and 0.8303, and the synergistic AUC was 0.9110 for discriminating between BTC patients and healthy controls. The AUC for discriminating BTC from pancreatic cancer was 0.9000. Hsa-miR-26a-5p was a predictor of prognosis, patients with high expression had shorter survival than those with low expression. In conclusion, hsa-let-7c-5p, hsa-miR-16-5p, hsa-miR-17-5p, and hsa-miR-26a-5p may act as key synergistic biomarkers and provide important molecular mechanisms that contribute to pathogenesis of BTC. |
format | Online Article Text |
id | pubmed-9582275 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-95822752022-10-21 Prioritizing key synergistic circulating microRNAs for the early diagnosis of biliary tract cancer Su, Fei Gao, Ziyu Liu, Yueyang Zhou, Guiqin Gao, Wei Deng, Chao Liu, Yuyu Zhang, Yihao Ma, Xiaoyan Wang, Yongxia Guan, Lili Zhang, Yafang Liu, Baoquan Front Oncol Oncology Biliary tract cancer (BTC) is a highly aggressive malignant tumor. Serum microRNAs (ser-miRNAs) serve as noninvasive biomarkers to identify high risk individuals, thereby facilitating the design of precision therapies. The study is to prioritize key synergistic ser-miRNAs for the diagnosis of early BTC. Sampling technology, significant analysis of microarrays, Pearson Correlation Coefficients, t-test, decision tree, and entropy weight were integrated to develop a global optimization algorithm of decision forest. The source code is available at https://github.com/SuFei-lab/GOADF.git. Four key synergistic ser-miRNAs were prioritized and the synergistic classification performance was better than the single miRNA’ s. In the internal feature evaluation dataset, the area under the receiver operating characteristic curve (AUC) for each single miRNA was 0.8413 (hsa-let-7c-5p), 0.7143 (hsa-miR-16-5p), 0.8571 (hsa-miR-17-5p), and 0.9365 (hsa-miR-26a-5p), respectively, whereas the synergistic AUC value increased to 1.0000. In the internal test dataset, the single AUC was 0.6500, 0.5125, 0.6750, and 0.7500, whereas the synergistic AUC increased to 0.8375. In the independent test dataset, the single AUC was 0.7280, 0.8313, 0.8957, and 0.8303, and the synergistic AUC was 0.9110 for discriminating between BTC patients and healthy controls. The AUC for discriminating BTC from pancreatic cancer was 0.9000. Hsa-miR-26a-5p was a predictor of prognosis, patients with high expression had shorter survival than those with low expression. In conclusion, hsa-let-7c-5p, hsa-miR-16-5p, hsa-miR-17-5p, and hsa-miR-26a-5p may act as key synergistic biomarkers and provide important molecular mechanisms that contribute to pathogenesis of BTC. Frontiers Media S.A. 2022-10-06 /pmc/articles/PMC9582275/ /pubmed/36276146 http://dx.doi.org/10.3389/fonc.2022.968412 Text en Copyright © 2022 Su, Gao, Liu, Zhou, Gao, Deng, Liu, Zhang, Ma, Wang, Guan, Zhang and Liu https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Oncology Su, Fei Gao, Ziyu Liu, Yueyang Zhou, Guiqin Gao, Wei Deng, Chao Liu, Yuyu Zhang, Yihao Ma, Xiaoyan Wang, Yongxia Guan, Lili Zhang, Yafang Liu, Baoquan Prioritizing key synergistic circulating microRNAs for the early diagnosis of biliary tract cancer |
title | Prioritizing key synergistic circulating microRNAs for the early diagnosis of biliary tract cancer |
title_full | Prioritizing key synergistic circulating microRNAs for the early diagnosis of biliary tract cancer |
title_fullStr | Prioritizing key synergistic circulating microRNAs for the early diagnosis of biliary tract cancer |
title_full_unstemmed | Prioritizing key synergistic circulating microRNAs for the early diagnosis of biliary tract cancer |
title_short | Prioritizing key synergistic circulating microRNAs for the early diagnosis of biliary tract cancer |
title_sort | prioritizing key synergistic circulating micrornas for the early diagnosis of biliary tract cancer |
topic | Oncology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9582275/ https://www.ncbi.nlm.nih.gov/pubmed/36276146 http://dx.doi.org/10.3389/fonc.2022.968412 |
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