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Clinical application of artificial neural network (ANN) modeling to predict BRCA1/2 germline deleterious variants in Chinese bilateral primary breast cancer patients
BACKGROUND: Bilateral breast cancer (BBC), as well as ovarian cancer, are significantly associated with germline deleterious variants in BRCA1/2, while BRCA1/2 germline deleterious variants carriers can exquisitely benefit from poly (ADP-ribose) polymerase (PARP) inhibitors. However, formal genetic...
Autores principales: | , , , , , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9628090/ https://www.ncbi.nlm.nih.gov/pubmed/36324133 http://dx.doi.org/10.1186/s12885-022-10160-y |
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author | Li, Yan Chen, Lili Lv, Jinxing Chen, Xiaobin Zeng, Bangwei Chen, Minyan Guo, Wenhui Lin, Yuxiang Yu, Liuwen Hou, Jialin Li, Jing Zhou, Peng Zhang, Wenzhe Li, Shengmei Jin, Xuan Cai, Weifeng Zhang, Kun Huang, Yeyuan Wang, Chuan Fu, Fangmeng |
author_facet | Li, Yan Chen, Lili Lv, Jinxing Chen, Xiaobin Zeng, Bangwei Chen, Minyan Guo, Wenhui Lin, Yuxiang Yu, Liuwen Hou, Jialin Li, Jing Zhou, Peng Zhang, Wenzhe Li, Shengmei Jin, Xuan Cai, Weifeng Zhang, Kun Huang, Yeyuan Wang, Chuan Fu, Fangmeng |
author_sort | Li, Yan |
collection | PubMed |
description | BACKGROUND: Bilateral breast cancer (BBC), as well as ovarian cancer, are significantly associated with germline deleterious variants in BRCA1/2, while BRCA1/2 germline deleterious variants carriers can exquisitely benefit from poly (ADP-ribose) polymerase (PARP) inhibitors. However, formal genetic testing could not be carried out for all patients due to extensive use of healthcare resources, which in turn results in high medical costs. To date, existing BRCA1/2 deleterious variants prediction models have been developed in women of European or other descent who are quite genetically different from Asian population. Therefore, there is an urgent clinical need for tools to predict the frequency of BRCA1/2 deleterious variants in Asian BBC patients balancing the increased demand for and cost of cancer genetics services. METHODS: The entire coding region of BRCA1/2 was screened for the presence of germline deleterious variants by the next generation sequencing in 123 Chinese BBC patients. Chi-square test, univariate and multivariate logistic regression were used to assess the relationship between BRCA1/2 germline deleterious variants and clinicopathological characteristics. The R software was utilized to develop artificial neural network (ANN) and nomogram modeling for BRCA1/2 germline deleterious variants prediction. RESULTS: Among 123 BBC patients, we identified a total of 20 deleterious variants in BRCA1 (8; 6.5%) and BRCA2 (12; 9.8%). c.5485del in BRCA1 is novel frameshift deleterious variant. Deleterious variants carriers were younger at first diagnosis (P = 0.0003), with longer interval between two tumors (P = 0.015), at least one medullary carcinoma (P = 0.001), and more likely to be hormone receptor negative (P = 0.006) and HER2 negative (P = 0.001). Area under the receiver operating characteristic curve was 0.903 in ANN and 0.828 in nomogram modeling individually (P = 0.02). CONCLUSION: This study shows the spectrum of the BRCA1/2 germline deleterious variants in Chinese BBC patients and indicates that the ANN can accurately predict BRCA deleterious variants than conventional statistical linear approach, which confirms the BRCA1/2 deleterious variants carriers at the lowest costs without adding any additional examinations. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12885-022-10160-y. |
format | Online Article Text |
id | pubmed-9628090 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-96280902022-11-03 Clinical application of artificial neural network (ANN) modeling to predict BRCA1/2 germline deleterious variants in Chinese bilateral primary breast cancer patients Li, Yan Chen, Lili Lv, Jinxing Chen, Xiaobin Zeng, Bangwei Chen, Minyan Guo, Wenhui Lin, Yuxiang Yu, Liuwen Hou, Jialin Li, Jing Zhou, Peng Zhang, Wenzhe Li, Shengmei Jin, Xuan Cai, Weifeng Zhang, Kun Huang, Yeyuan Wang, Chuan Fu, Fangmeng BMC Cancer Research BACKGROUND: Bilateral breast cancer (BBC), as well as ovarian cancer, are significantly associated with germline deleterious variants in BRCA1/2, while BRCA1/2 germline deleterious variants carriers can exquisitely benefit from poly (ADP-ribose) polymerase (PARP) inhibitors. However, formal genetic testing could not be carried out for all patients due to extensive use of healthcare resources, which in turn results in high medical costs. To date, existing BRCA1/2 deleterious variants prediction models have been developed in women of European or other descent who are quite genetically different from Asian population. Therefore, there is an urgent clinical need for tools to predict the frequency of BRCA1/2 deleterious variants in Asian BBC patients balancing the increased demand for and cost of cancer genetics services. METHODS: The entire coding region of BRCA1/2 was screened for the presence of germline deleterious variants by the next generation sequencing in 123 Chinese BBC patients. Chi-square test, univariate and multivariate logistic regression were used to assess the relationship between BRCA1/2 germline deleterious variants and clinicopathological characteristics. The R software was utilized to develop artificial neural network (ANN) and nomogram modeling for BRCA1/2 germline deleterious variants prediction. RESULTS: Among 123 BBC patients, we identified a total of 20 deleterious variants in BRCA1 (8; 6.5%) and BRCA2 (12; 9.8%). c.5485del in BRCA1 is novel frameshift deleterious variant. Deleterious variants carriers were younger at first diagnosis (P = 0.0003), with longer interval between two tumors (P = 0.015), at least one medullary carcinoma (P = 0.001), and more likely to be hormone receptor negative (P = 0.006) and HER2 negative (P = 0.001). Area under the receiver operating characteristic curve was 0.903 in ANN and 0.828 in nomogram modeling individually (P = 0.02). CONCLUSION: This study shows the spectrum of the BRCA1/2 germline deleterious variants in Chinese BBC patients and indicates that the ANN can accurately predict BRCA deleterious variants than conventional statistical linear approach, which confirms the BRCA1/2 deleterious variants carriers at the lowest costs without adding any additional examinations. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12885-022-10160-y. BioMed Central 2022-11-02 /pmc/articles/PMC9628090/ /pubmed/36324133 http://dx.doi.org/10.1186/s12885-022-10160-y Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Research Li, Yan Chen, Lili Lv, Jinxing Chen, Xiaobin Zeng, Bangwei Chen, Minyan Guo, Wenhui Lin, Yuxiang Yu, Liuwen Hou, Jialin Li, Jing Zhou, Peng Zhang, Wenzhe Li, Shengmei Jin, Xuan Cai, Weifeng Zhang, Kun Huang, Yeyuan Wang, Chuan Fu, Fangmeng Clinical application of artificial neural network (ANN) modeling to predict BRCA1/2 germline deleterious variants in Chinese bilateral primary breast cancer patients |
title | Clinical application of artificial neural network (ANN) modeling to predict BRCA1/2 germline deleterious variants in Chinese bilateral primary breast cancer patients |
title_full | Clinical application of artificial neural network (ANN) modeling to predict BRCA1/2 germline deleterious variants in Chinese bilateral primary breast cancer patients |
title_fullStr | Clinical application of artificial neural network (ANN) modeling to predict BRCA1/2 germline deleterious variants in Chinese bilateral primary breast cancer patients |
title_full_unstemmed | Clinical application of artificial neural network (ANN) modeling to predict BRCA1/2 germline deleterious variants in Chinese bilateral primary breast cancer patients |
title_short | Clinical application of artificial neural network (ANN) modeling to predict BRCA1/2 germline deleterious variants in Chinese bilateral primary breast cancer patients |
title_sort | clinical application of artificial neural network (ann) modeling to predict brca1/2 germline deleterious variants in chinese bilateral primary breast cancer patients |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9628090/ https://www.ncbi.nlm.nih.gov/pubmed/36324133 http://dx.doi.org/10.1186/s12885-022-10160-y |
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