Guochun Zhang1, Yulei Wang1, Bo Chen1, Liping Guo1,2, Li Cao1, Chongyang Ren1, Lingzhu Wen1, Kai Li1, Minghan Jia1, Cheukfai Li1, Hsiaopei Mok1, Xiaoqing Chen1,2, Guangnan Wei1,3, Jiali Lin1,2, Zhou Zhang4, Ting Hou4, Han Han-Zhang4, Chenglin Liu4, Hao Liu4, Jing Liu4, Charles M Balch5, Funda Meric-Bernstam6, Ning Liao1,2,3. 1. Department of Breast Cancer, Guangdong Provincial People's Hospital & Guangdong Academy of Medical Sciences, Guangzhou 510080, China. 2. The Second School of Clinical Medicine, Southern Medical University, Guangzhou 510000, China. 3. School of Medicine, South China University of Technology, Guangzhou 510000, China. 4. Burning Rock Biotech, Guangzhou 510000, China. 5. Department of Surgical Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA. 6. Departments of Breast Surgical Oncology and Investigational Cancer Therapeutics, Institute of Personalized Cancer Therapeutics, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.
Abstract
BACKGROUND: The complexity of breast cancer at the clinical, morphological and genomic levels has been extensively studied in the western population. However, the mutational genomic profiles in Chinese breast cancer patients have not been explored in any detail. METHODS: We performed targeted sequencing using a panel consisting of 33 breast cancer-related genes to investigate the genomic landscape of 304 consecutive treatment-naïve Chinese breast cancer patients at Guangdong Provincial People's Hospital (GDPH), and further compared the results to those in 453 of Caucasian breast cancer patients from The Cancer Genome Atlas (TCGA). RESULTS: The most frequently mutated gene was TP53 (45%), followed by PIK3CA (44%), GATA3 (18%), MAP3K1 (10%), whereas the copy-number amplifications were frequently observed in genes of ERBB2 (24%), MYC (23%), FGFR1 (13%) and CCND1 (10%). Among the 8 most frequently mutated or amplified genes, at least one driver was identifiable in 87.5% (n=267) of our GDPH cohort, revealing the significant contribution of these known driver genes in the development of Chinese breast cancer. Compared to TCGA data, the median age at diagnosis in our cohort was significantly younger (48 vs. 58 years; P<0.001), while the distribution of estrogen receptor (ER), progesterone receptor (PR) and human epidermal growth factor receptor-2 (HER2) statuses were similar. The largest difference occurred in HR+/HER2- subtype, where 8 of the 10 driver genes compared had statistically significant differences in their frequency, while there were differences in 2 of 10 driver genes among the TNBC and HR+/HER2+ group, but none in the HR-/HER2+ patients in our cohort compared to the TCGA data. Collectively, the most significant genomic difference was a significantly higher prevalence for TP53 and AKT1 in Chinese patients. Additionally, more than half of TP53-mutation HR+/HER2- Chinese patients (~60%) are likely to harbor more severe mutations in TP53, such as nonsense, indels, and splicing mutations. CONCLUSIONS: We elucidated the mutational landscape of cancer genes in Chinese breast cancer and further identified significant genomic differences between Asian and Caucasian patients. These results should improve our understanding of pathogenesis and/or metastatic behavior of breast cancer across races/ethnicities, including a better selection of targeted therapies.
BACKGROUND: The complexity of breast cancer at the clinical, morphological and genomic levels has been extensively studied in the western population. However, the mutational genomic profiles in Chinese breast cancer patients have not been explored in any detail. METHODS: We performed targeted sequencing using a panel consisting of 33 breast cancer-related genes to investigate the genomic landscape of 304 consecutive treatment-naïve Chinese breast cancer patients at Guangdong Provincial People's Hospital (GDPH), and further compared the results to those in 453 of Caucasian breast cancer patients from The Cancer Genome Atlas (TCGA). RESULTS: The most frequently mutated gene was TP53 (45%), followed by PIK3CA (44%), GATA3 (18%), MAP3K1 (10%), whereas the copy-number amplifications were frequently observed in genes of ERBB2 (24%), MYC (23%), FGFR1 (13%) and CCND1 (10%). Among the 8 most frequently mutated or amplified genes, at least one driver was identifiable in 87.5% (n=267) of our GDPH cohort, revealing the significant contribution of these known driver genes in the development of Chinese breast cancer. Compared to TCGA data, the median age at diagnosis in our cohort was significantly younger (48 vs. 58 years; P<0.001), while the distribution of estrogen receptor (ER), progesterone receptor (PR) and human epidermal growth factor receptor-2 (HER2) statuses were similar. The largest difference occurred in HR+/HER2- subtype, where 8 of the 10 driver genes compared had statistically significant differences in their frequency, while there were differences in 2 of 10 driver genes among the TNBC and HR+/HER2+ group, but none in the HR-/HER2+ patients in our cohort compared to the TCGA data. Collectively, the most significant genomic difference was a significantly higher prevalence for TP53 and AKT1 in Chinese patients. Additionally, more than half of TP53-mutation HR+/HER2- Chinese patients (~60%) are likely to harbor more severe mutations in TP53, such as nonsense, indels, and splicing mutations. CONCLUSIONS: We elucidated the mutational landscape of cancer genes in Chinese breast cancer and further identified significant genomic differences between Asian and Caucasian patients. These results should improve our understanding of pathogenesis and/or metastatic behavior of breast cancer across races/ethnicities, including a better selection of targeted therapies.
Entities:
Keywords:
AKT1; Chinese breast cancer; GATA3; Genomic mutation; MAP3K1; PIK3CA; TP53; multi-gene; mutational landscape; next-generation sequencing
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