1
|
Guo R, Yu Y, Huang Y, Lin M, Liao Y, Hu Y, Li Q, Peng C, Zhou J. A nomogram model combining ultrasound-based radiomics features and clinicopathological factors to identify germline BRCA1/2 mutation in invasive breast cancer patients. Heliyon 2024; 10:e23383. [PMID: 38169922 PMCID: PMC10758804 DOI: 10.1016/j.heliyon.2023.e23383] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/29/2023] [Revised: 09/18/2023] [Accepted: 12/01/2023] [Indexed: 01/05/2024] Open
Abstract
Objective BRCA1/2 status is a key to personalized therapy for invasive breast cancer patients. This study aimed to explore the association between ultrasound radiomics features and germline BRCA1/2 mutation in patients with invasive breast cancer. Materials and methods In this retrospective study, 100 lesions in 92 BRCA1/2-mutated patients and 390 lesions in 357 non-BRCA1/2-mutated patients were included and randomly assigned as training and validation datasets in a ratio of 7:3. Gray-scale ultrasound images of the largest plane of the lesions were used for feature extraction. Maximum relevance minimum redundancy (mRMR) algorithm and multivariate logistic least absolute shrinkage and selection operator (LASSO) regression were used to select features. The multivariate logistic regression method was used to construct predictive models based on clinicopathological factors, radiomics features, or a combination of them. Results In the clinical model, age at first diagnosis, family history of BRCA1/2-related malignancies, HER2 status, and Ki-67 level were found to be independent predictors for BRCA1/2 mutation. In the radiomics model, 10 significant features were selected from the 1032 radiomics features extracted from US images. The AUCs of the radiomics model were not inferior to those of the clinical model in both training dataset [0.712 (95% CI, 0.647-0.776) vs 0.768 (95% CI, 0.704-0.835); p = 0.429] and validation dataset [0.705 (95% CI, 0.597-0.808) vs 0.723 (95% CI, 0.625-0.828); p = 0.820]. The AUCs of the nomogram model combining clinical and radiomics features were 0.804 (95% CI, 0.748-0.861) in the training dataset and 0.811 (95% CI, 0.724-0.894) in the validation dataset, which were proved significantly higher than those of the clinical model alone by DeLong's test (p = 0.041; p = 0.007). To be noted, the negative predictive values (NPVs) of the nomogram model reached a favorable 0.93 in both datasets. Conclusion This machine nomogram model combining ultrasound-based radiomics and clinical features exhibited a promising performance in identifying germline BRCA1/2 mutation in patients with invasive breast cancer and may help avoid unnecessary gene tests in clinical practice.
Collapse
Affiliation(s)
| | | | - Yini Huang
- Department of Ultrasound, Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, No. 651 Dongfeng Road East, Guangzhou, 510060, PR China
| | - Min Lin
- Department of Ultrasound, Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, No. 651 Dongfeng Road East, Guangzhou, 510060, PR China
| | - Ying Liao
- Department of Ultrasound, Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, No. 651 Dongfeng Road East, Guangzhou, 510060, PR China
| | - Yixin Hu
- Department of Ultrasound, Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, No. 651 Dongfeng Road East, Guangzhou, 510060, PR China
| | - Qing Li
- Department of Ultrasound, Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, No. 651 Dongfeng Road East, Guangzhou, 510060, PR China
| | - Chuan Peng
- Department of Ultrasound, Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, No. 651 Dongfeng Road East, Guangzhou, 510060, PR China
| | - Jianhua Zhou
- Department of Ultrasound, Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, No. 651 Dongfeng Road East, Guangzhou, 510060, PR China
| |
Collapse
|
2
|
Ni M, Wang F, Yang A, Shao Q, Xue C, Xia W, Xu F, Lin X, Huang J, Bi X, Hong R, Chen M, Zheng Q, Jiang K, Xie X, Tang J, Wang X, Yuan Z, Wang S, Shi Y, An X. What is the appropriate genetic testing criteria for breast cancer in the Chinese population?-Analysis of genetic and clinical features from a single cancer center database. Cancer Med 2023. [PMID: 37096751 DOI: 10.1002/cam4.5976] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/12/2022] [Revised: 04/02/2023] [Accepted: 04/09/2023] [Indexed: 04/26/2023] Open
Abstract
BACKGROUND Genetic testing plays an important role in guiding screening, diagnosis, and precision treatment of breast cancer (BC). However, the appropriate genetic testing criteria remain controversial. The current study aims to facilitate the development of suitable strategies by analyzing the germline mutational profiles and clinicopathological features of large-scale Chinese BC patients. METHODS BC patients who had undergone genetic testing at the Sun Yat-sen University Cancer Center (SYSUCC) from September 2014 to March 2022 were retrospectively reviewed. Different screening criteria were applied and compared in the population cohort. RESULTS A total of 1035 BC patients were enrolled, 237 pathogenic or likely pathogenic variants (P/LPV) were identified in 235 patients, including 41 out of 203 (19.6%) patients tested only for BRCA1/2 genes, and 194 out of 832 (23.3%) received 21 genes panel testing. Among the 235 P/LPV carriers, 222 (94.5%) met the NCCN high-risk criteria, and 13 (5.5%) did not. While using Desai's criteria of testing, all females diagnosed with BC by 60 years and NCCN criteria for older patients, 234 (99.6%) met the high-risk standard, and only one did not. The 21 genes panel testing identified 4.9% of non-BRCA P/LPVs and a significantly high rate of variants of uncertain significance (VUSs) (33.9%). The most common non-BRCA P/LPVs were PALB2 (11, 1.3%), TP53 (10, 1.2%), PTEN (3, 0.4%), CHEK2 (3, 0.4%), ATM (3, 0.4%), BARD1 (3, 0.4%), and RAD51C (2, 0.2%). Compared with BRCA1/2 P/LPVs, non-BRCA P/LPVs showed a significantly low incidence of NCCN criteria listed family history, second primary cancer, and different molecular subtypes. CONCLUSIONS Desai's criteria might be a more appropriate genetic testing strategy for Chinese BC patients. Panel testing could identify more non-BRCA P/LPVs than BRCA1/2 testing alone. Compared with BRCA1/2 P/LPVs, non-BRCA P/LPVs exhibited different personal and family histories of cancer and molecular subtype distributions. The optimal genetic testing strategy for BC still needs to be investigated with larger continuous population studies.
Collapse
Affiliation(s)
- Mengqian Ni
- State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center, Guangzhou, China
- Department of Medical Oncology, Sun Yat-sen University Cancer Center, Guangzhou, China
| | - Fang Wang
- State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center, Guangzhou, China
- Department of Molecular Diagnostics, Sun Yat-sen University Cancer Center, Guangzhou, China
| | - Anli Yang
- State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center, Guangzhou, China
- Department of Breast Oncology, Sun Yat-sen University Cancer Center, Guangzhou, China
| | - Qiong Shao
- State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center, Guangzhou, China
- Department of Molecular Diagnostics, Sun Yat-sen University Cancer Center, Guangzhou, China
| | - Cong Xue
- State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center, Guangzhou, China
- Department of Medical Oncology, Sun Yat-sen University Cancer Center, Guangzhou, China
| | - Wen Xia
- State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center, Guangzhou, China
- Department of Medical Oncology, Sun Yat-sen University Cancer Center, Guangzhou, China
| | - Fei Xu
- State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center, Guangzhou, China
- Department of Medical Oncology, Sun Yat-sen University Cancer Center, Guangzhou, China
| | - Xi Lin
- State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center, Guangzhou, China
- Department of Ultrasound, Sun Yat-sen University Cancer Center, Guangzhou, China
| | - Jiajia Huang
- State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center, Guangzhou, China
- Department of Medical Oncology, Sun Yat-sen University Cancer Center, Guangzhou, China
| | - Xiwen Bi
- State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center, Guangzhou, China
- Department of Medical Oncology, Sun Yat-sen University Cancer Center, Guangzhou, China
| | - Ruoxi Hong
- State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center, Guangzhou, China
- Department of Medical Oncology, Sun Yat-sen University Cancer Center, Guangzhou, China
| | - Meiting Chen
- State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center, Guangzhou, China
- Department of Medical Oncology, Sun Yat-sen University Cancer Center, Guangzhou, China
| | - Qiufan Zheng
- State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center, Guangzhou, China
- Department of Medical Oncology, Sun Yat-sen University Cancer Center, Guangzhou, China
| | - Kuikui Jiang
- State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center, Guangzhou, China
- Department of Medical Oncology, Sun Yat-sen University Cancer Center, Guangzhou, China
| | - Xinhua Xie
- State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center, Guangzhou, China
- Department of Breast Oncology, Sun Yat-sen University Cancer Center, Guangzhou, China
| | - Jun Tang
- State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center, Guangzhou, China
- Department of Breast Oncology, Sun Yat-sen University Cancer Center, Guangzhou, China
| | - Xi Wang
- State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center, Guangzhou, China
- Department of Breast Oncology, Sun Yat-sen University Cancer Center, Guangzhou, China
| | - Zhongyu Yuan
- State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center, Guangzhou, China
- Department of Medical Oncology, Sun Yat-sen University Cancer Center, Guangzhou, China
| | - Shusen Wang
- State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center, Guangzhou, China
- Department of Medical Oncology, Sun Yat-sen University Cancer Center, Guangzhou, China
| | - Yanxia Shi
- State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center, Guangzhou, China
- Department of Medical Oncology, Sun Yat-sen University Cancer Center, Guangzhou, China
| | - Xin An
- State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center, Guangzhou, China
- Department of Medical Oncology, Sun Yat-sen University Cancer Center, Guangzhou, China
| |
Collapse
|
3
|
Lu B, Natarajan E, Balaji Raghavendran HR, Markandan UD. Molecular Classification, Treatment, and Genetic Biomarkers in Triple-Negative Breast Cancer: A Review. Technol Cancer Res Treat 2023; 22:15330338221145246. [PMID: 36601658 PMCID: PMC9829998 DOI: 10.1177/15330338221145246] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/06/2023] Open
Abstract
Breast cancer is the most common malignancy and the second most common cause of cancer-related mortality in women. Triple-negative breast cancers do not express estrogen receptors, progesterone receptors, or human epidermal growth factor receptor 2 and have a higher recurrence rate, greater metastatic potential, and lower overall survival rate than those of other breast cancers. Treatment of triple-negative breast cancer is challenging; molecular-targeted therapies are largely ineffective and there is no standard treatment. In this review, we evaluate current attempts to classify triple-negative breast cancers based on their molecular features. We also describe promising treatment methods with different advantages and discuss genetic biomarkers and other prediction tools. Accurate molecular classification of triple-negative breast cancers is critical for patient risk categorization, treatment decisions, and surveillance. This review offers new ideas for more effective treatment of triple-negative breast cancer and identifies novel targets for drug development.
Collapse
Affiliation(s)
- Boya Lu
- Department of Mechanical Engineering, Faculty of Engineering,
Technology and Built Environment, UCSI University,
Kuala Lumpur, Malaysia,Boya Lu, MD, Department of Mechanical
Engineering, Faculty of Engineering, Technology and Built Environment, UCSI
University, No 1, Jalan Menara Gading, UCSI Heights (Taman Connaught), Cheras,
56000, Kuala Lumpur, Malaysia.
| | - Elango Natarajan
- Department of Mechanical Engineering, Faculty of Engineering,
Technology and Built Environment, UCSI University,
Kuala Lumpur, Malaysia
| | - Hanumantha Rao Balaji Raghavendran
- Faculty of Clinical Research, Central Research Facility, Sri
Ramachandra Institute of Higher Education and Research, Chennai, Tamil Nadu,
India
| | | |
Collapse
|
4
|
Lei H, Zhang M, Zhang L, Hemminki K, Wang XJ, Chen T. Overview on population screening for carriers with germline BRCA mutation in China. Front Oncol 2022; 12:1002360. [PMID: 36439508 PMCID: PMC9682265 DOI: 10.3389/fonc.2022.1002360] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/25/2022] [Accepted: 10/24/2022] [Indexed: 12/01/2023] Open
Abstract
Carriers with BRCA1/2 germline pathogenic variants are associated with a high risk of breast and ovarian cancers (also pancreatic and prostate cancers). While the spectrum on germline BRCA mutations among the Chinese population shows ethnic specificity, the identification of carriers with germline BRCA mutation before cancer onset is the most effective approach to protect them. This review focused on the current status of BRCA1/2 screening, the surveillance and prevention measures, and discussed the issues and potential impact of BRCA1/2 population screening in China. We conducted literature research on databases PubMed and Google Scholar, as well as Chinese databases CNKI and Wangfang Med Online database (up to 31 March 2022). Latest publications on germline BRCA1/2 prevalence, spectrum, genetic screening as well as carrier counseling, surveillance and prevention were captured where available. While overall 15,256 records were retrieved, 72 publications using germline BRCA1/2 testing were finally retained for further analyses. Germline BRCA1/2 mutations are common in Chinese patients with hereditary breast, ovarian, prostate and pancreatic cancers. Within previous studies, a unique BRCA mutation spectrum in China was revealed. Next-generation sequencing panel was considered as the most common method for BRCA1/2 screening. Regular surveillance and preventive surgeries were tailored to carriers with mutated-BRCA1/2. We recommend that all Chinese diagnosed with breast, ovarian, pancreatic or prostate cancers and also healthy family members, shall undergo BRCA1/2 gene test to provide risk assessment. Subsequently, timely preventive measures for mutation carriers are recommended after authentic genetic counseling.
Collapse
Affiliation(s)
- Huijun Lei
- Department of Cancer Prevention/Zhejiang Cancer Institute, Cancer Hospital of the University of Chinese Academy of Sciences (Zhejiang Cancer Hospital), Hangzhou, China
- Institute of Basic Medicine and Cancer (IBMC), Chinese Academy of Sciences, Hangzhou, China
| | - Min Zhang
- School of Public Health, Hangzhou Medical College, Hangzhou, Zhejiang, China
| | - Luyao Zhang
- Department of Cancer Epidemiology and Prevention, Henan Engineering Research Center of Cancer Prevention and Control, Henan International Joint Laboratory of Cancer Prevention, The Affiliated Cancer Hospital of Zhengzhou University, Henan Cancer Hospital, Zhengzhou, China
| | - Kari Hemminki
- Biomedical Center, Faculty of Medicine, Charles University in Pilsen, Pilsen, Czechia
- Division of Cancer Epidemiology, German Cancer Research Center Deutsches Krebsforschungszentrum (DKFZ), Im Neuenheimer Feld, Heidelberg, Germany
| | - Xiao-jia Wang
- Institute of Basic Medicine and Cancer (IBMC), Chinese Academy of Sciences, Hangzhou, China
- Department of Breast Medical Oncology, Cancer Hospital of the University of Chinese Academy of Sciences (Zhejiang Cancer Hospital), Hangzhou, China
| | - Tianhui Chen
- Department of Cancer Prevention/Zhejiang Cancer Institute, Cancer Hospital of the University of Chinese Academy of Sciences (Zhejiang Cancer Hospital), Hangzhou, China
- Institute of Basic Medicine and Cancer (IBMC), Chinese Academy of Sciences, Hangzhou, China
- Department of Preventive Medicine, School of Medicine, Ningbo University, Ningbo, China
| |
Collapse
|
5
|
Hua D, Tian Q, Wang X, Bei T, Cui L, Zhang B, Bao C, Bai Y, Zhao X, Yuan P. Next-generation sequencing based detection of BRCA1 and BRCA2 large genomic rearrangements in Chinese cancer patients. Front Oncol 2022; 12:898916. [PMID: 36147908 PMCID: PMC9487528 DOI: 10.3389/fonc.2022.898916] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/18/2022] [Accepted: 08/08/2022] [Indexed: 11/17/2022] Open
Abstract
BRCA1/2 mutation is a biomarker for guiding multiple solid tumor treatment. However, the prevalence of BRCA1/2 large genomic rearrangements (LGRs) in Chinese cancer patients has not been well revealed partially due to technical difficulties in LGR detection. This study utilized next-generation sequencing (NGS) to analyze the BRCA1/2 mutation profile, including LGR, in 56126 Chinese cancer patients. We also reported that two ovarian and breast cancer patients with NGS-determined BRCA1/2 LGR benefited from PARP inhibitors (PARPi). DNA sequencing identified BRCA1/2 variants (including LGR, pathogenic and likely-pathogenic variants) in 2108 individuals. Seventy patients were discovered to harbor germline LGRs in BRCA1 and 14 had germline LGRs in BRCA2. Among the LGRs detected, exon 1-2 deletion was the predominant LGR (14/70) in BRCA1, and exon 22-24 deletion was the most frequent LGR (3/14) in BRCA2. Notably, the BRCA1 exon 7 deletion was a novel LGR and was identified in six patients, suggesting a specific LGR in Chinese cancer patients. The prevalence analysis of BRCA1 and BRCA2 LGRs across multiple cancers revealed that BRCA1 LGR more frequently occurred in ovarian cancer (1.31%, 33/2526), and BRCA2 LGR was more commonly seen in cholangiocarcinoma (0.47%, 2/425). Two ovarian and breast cancer patients with BRCA1/2 LGR benefited from PARPi therapy. This is the first study to reveal the BRCA1/2 LGR profile of a Chinese pan-cancer cohort by using an NGS-based assay. Two breast and ovarian cancer patients harboring NGS-determined BRCA1/2 LGR benefited from PARPi, indicating that NGS-based detection of BRCA1/2 LGR has the potential to guide PARPi treatment.
Collapse
Affiliation(s)
- Dingchao Hua
- Department of Medical Affairs, 3D Medicines Inc., Shanghai, China
| | - Qiuhong Tian
- Department of Medical Oncology, First Affiliated Hospital of Nanchang University, Nanchang, China
| | - Xue Wang
- National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Ting Bei
- Department of Medical Affairs, 3D Medicines Inc., Shanghai, China
| | - Lina Cui
- Department of Medical Affairs, 3D Medicines Inc., Shanghai, China
| | - Bei Zhang
- Department of Medical Affairs, 3D Medicines Inc., Shanghai, China
| | - Celimuge Bao
- Department of Medical Affairs, 3D Medicines Inc., Shanghai, China
| | - Yuezong Bai
- Department of Gastrointestinal Oncology, Key Laboratory of Carcinogenesis and Translational Research, Ministry of Education, Peking University Cancer Hospital & Institute, Beijing, China
| | - Xiaochen Zhao
- Department of Medical Affairs, 3D Medicines Inc., Shanghai, China
- *Correspondence: Xiaochen Zhao, ; Peng Yuan,
| | - Peng Yuan
- National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
- *Correspondence: Xiaochen Zhao, ; Peng Yuan,
| |
Collapse
|