Clinical application of artificial neural network (ANN) modeling to predict BRCA1/2 germline deleterious variants in Chinese bilateral primary breast cancer patients
Abstract 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...
| Main Authors: | , , , , , , , , , , , , , , , , , , , |
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| Format: | Article |
| Language: | English |
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BMC
2022-11-01
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| Series: | BMC Cancer |
| Subjects: | |
| Online Access: | https://doi.org/10.1186/s12885-022-10160-y |
| _version_ | 1811328828142780416 |
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| author | Yan Li Lili Chen Jinxing Lv Xiaobin Chen Bangwei Zeng Minyan Chen Wenhui Guo Yuxiang Lin Liuwen Yu Jialin Hou Jing Li Peng Zhou Wenzhe Zhang Shengmei Li Xuan Jin Weifeng Cai Kun Zhang Yeyuan Huang Chuan Wang Fangmeng Fu |
| author_facet | Yan Li Lili Chen Jinxing Lv Xiaobin Chen Bangwei Zeng Minyan Chen Wenhui Guo Yuxiang Lin Liuwen Yu Jialin Hou Jing Li Peng Zhou Wenzhe Zhang Shengmei Li Xuan Jin Weifeng Cai Kun Zhang Yeyuan Huang Chuan Wang Fangmeng Fu |
| author_sort | Yan Li |
| collection | DOAJ |
| description | Abstract 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. |
| first_indexed | 2024-04-13T15:32:54Z |
| format | Article |
| id | doaj.art-3009d9014e65498893c439c5b72ad88b |
| institution | Directory Open Access Journal |
| issn | 1471-2407 |
| language | English |
| last_indexed | 2024-04-13T15:32:54Z |
| publishDate | 2022-11-01 |
| publisher | BMC |
| record_format | Article |
| series | BMC Cancer |
| spelling | doaj.art-3009d9014e65498893c439c5b72ad88b2022-12-22T02:41:20ZengBMCBMC Cancer1471-24072022-11-0122111110.1186/s12885-022-10160-yClinical application of artificial neural network (ANN) modeling to predict BRCA1/2 germline deleterious variants in Chinese bilateral primary breast cancer patientsYan Li0Lili Chen1Jinxing Lv2Xiaobin Chen3Bangwei Zeng4Minyan Chen5Wenhui Guo6Yuxiang Lin7Liuwen Yu8Jialin Hou9Jing Li10Peng Zhou11Wenzhe Zhang12Shengmei Li13Xuan Jin14Weifeng Cai15Kun Zhang16Yeyuan Huang17Chuan Wang18Fangmeng Fu19Department of Breast Surgery, Fujian Medical University Union HospitalDepartment of Breast Surgery, Fujian Medical University Union HospitalDepartment of Breast Surgery, Fujian Medical University Union HospitalDepartment of Breast Surgery, Fujian Medical University Union HospitalNosocomial Infection Control Branch, Fujian Medical University Union HospitalDepartment of Breast Surgery, Fujian Medical University Union HospitalDepartment of Breast Surgery, Fujian Medical University Union HospitalDepartment of Breast Surgery, Fujian Medical University Union HospitalDepartment of Breast Surgery, Fujian Medical University Union HospitalDepartment of Breast Surgery, Fujian Medical University Union HospitalDepartment of Breast Surgery, Fujian Medical University Union HospitalDepartment of Breast Surgery, Fujian Medical University Union HospitalDepartment of Breast Surgery, Fujian Medical University Union HospitalDepartment of Breast Surgery, Fujian Medical University Union HospitalDepartment of Breast Surgery, Fujian Medical University Union HospitalDepartment of Breast Surgery, Fujian Medical University Union HospitalDepartment of Breast Surgery, Fujian Medical University Union HospitalFujian Medical UniversityDepartment of Breast Surgery, Fujian Medical University Union HospitalDepartment of Breast Surgery, Fujian Medical University Union HospitalAbstract 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.https://doi.org/10.1186/s12885-022-10160-yBilateral breast cancerBRCA1BRCA2Germline deleterious variantArtificial neural network |
| spellingShingle | Yan Li Lili Chen Jinxing Lv Xiaobin Chen Bangwei Zeng Minyan Chen Wenhui Guo Yuxiang Lin Liuwen Yu Jialin Hou Jing Li Peng Zhou Wenzhe Zhang Shengmei Li Xuan Jin Weifeng Cai Kun Zhang Yeyuan Huang Chuan Wang Fangmeng Fu Clinical application of artificial neural network (ANN) modeling to predict BRCA1/2 germline deleterious variants in Chinese bilateral primary breast cancer patients BMC Cancer Bilateral breast cancer BRCA1 BRCA2 Germline deleterious variant Artificial neural network |
| 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 | Bilateral breast cancer BRCA1 BRCA2 Germline deleterious variant Artificial neural network |
| url | https://doi.org/10.1186/s12885-022-10160-y |
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