Abstract P4-09-01: Clinical sequencing characterizes the genomic landscape and actionable mutations of Chinese breast cancer
Authors: Guan-Tian Lang, Jin-Xiu Shi, Yi-Zhou Jiang, Xiao-Guang Li, Yu-Chen Pei, Fang-Lin Zhang, Chen-Hui Zhang, Ding Ma, Yi Xiao, Ke-Da Yu, Peng-Chen Hu, Ming-Liang Jin, Hai Wang, Yun-Song Yang, Xuan Luo, Qi Hong, Feng Qiao, Wei-Li Sun, Meng-Zhu Xue, Shi-Ping Li, A-Yong Cao, Zhong-Hua Wang, Jia-Xin Zhang, Gen-Hong Di, Peng Wang, Da-Qiang Li, Xin Hu, Wei Huang, Zhi-Ming Shao
Journal: Cancer Research (2020)

Abstract Here, we prospectively collected what is currently the largest Chinese breast cancer cohort of 1,143 patients for clinical sequencing and performed integrated analysis of their clinical and genomic characteristics. All samples were collected via needle biopsy. A custom-designed genetic panel was used in this study. The panel was a hybridization capture-based assay, including 484 genes that are targets of approved and experimental therapies as well as frequently mutated genes in breast cancer. The panel was designed for detecting mutations and small insertions and deletions. The highest prevalence of breast cancer-related variations observed in our Chinese cohort was TP53 mutations (53%), followed by PIK3CA (19%), NF1 (10%), GATA3 (9%) and KMT2C (9%) mutations. The hotspot mutations (with frequencies higher than 2%) in Chinese breast cancer included PIK3CA p. H1047R (10%), AKT1 p. E17K (4%), KMT2C p. K2797fs (2%) and TP53 p. R248Q (2%). PIK3CA and AKT1 mutations were found to be especially enriched in the Luminal (HER2-) subtype, NF1 and ERBB2 mutations were enriched in Luminal (HER2+) subtype, and PTEN mutations were enriched in triple negative breast cancer. In addition, there was significant disparity of mutation load among the different subtypes, suggesting a high mutation load in triple negative breast cancer. We further investigated the differences in mutational features between the Chinese cohort and foreign published cohorts, especially the TCGA and MSKCC breast cancer datasets, and revealed the distinction mainly existed in breast cancer of the HR+/HER2- subtype, while the other subtypes showed a similar mutation prevalence. We evaluated 9 canonical signaling pathways with frequent oncogenic alterations. The pathways that we analyzed included the cell cycle signaling, Hippo signaling, Notch signaling, PI-3-Kinase (PI3K) signaling, β-catenin/Wnt signaling, receptor-tyrosine (RTK)/RAS/MAP-Kinase (RTK-RAS) signaling, p53 signaling, TGF-β signaling and Myc signaling pathways. Alterations in the RTK-RAS pathway were exclusive to those in the PI3K pathway in hormone receptor (HR)-positive breast cancer and co-occurred with those in the Notch pathway in human epidermal growth factor receptor-2 (HER2)-positive, HR- and HER2-positive breast cancer. PI3K signaling pathway mutations were identified as a driving factor, and our finding revealed the competitively oncogenic role of mutations in the RTK-RAS pathway, especially in the HR+/HER2- subtype. Furthermore, we identified mutations in the P53 (53% versus 31%, p &amp;lt; 0.001), RTK-RAS (31% versus 18%, p &amp;lt; 0.001), Notch (17% versus 11%, p &amp;lt; 0.001), WNT (7% versus 1%, p &amp;lt; 0.001) and Hippo (2% versus 0%, p &amp;lt; 0.001) pathways that were more prevalent in our Chinese cohort than in the Caucasian cohort. We further explored the potential actionable targets in Chinese patients with breast cancer who might benefit from our sequencing. The OncoKB classification system was used to stratify levels of genomic biomarkers in the different subtypes. Over 32% of breast cancer patients could be genomically matched to at least one actionable biomarker. Notably, NF1 and NOTCH1 mutations were markedly enriched in Chinese patients, suggesting the potential for novel treatment strategies for breast cancer. Taken together, our study comprehensively revealed the characteristics of mutations in Chinese breast cancer, improving our understanding of the mutational diversity among different molecular subtypes, identifying potential treatment biomarkers and leading to systematic genomic studies and novel clinical trials. Citation Format: Guan-Tian Lang, Jin-Xiu Shi, Yi-Zhou Jiang, Xiao-Guang Li, Yu-Chen Pei, Fang-Lin Zhang, Chen-Hui Zhang, Ding Ma, Yi Xiao, Ke-Da Yu, Peng-Chen Hu, Ming-Liang Jin, Hai Wang, Yun-Song Yang, Xuan Luo, Qi Hong, Feng Qiao, Wei-Li Sun, Meng-Zhu Xue, Shi-Ping Li, A-Yong Cao, Zhong-Hua Wang, Jia-Xin Zhang, Gen-Hong Di, Peng Wang, Da-Qiang Li, Xin Hu, Wei Huang, Zhi-Ming Shao. Clinical sequencing characterizes the genomic landscape and actionable mutations of Chinese breast cancer [abstract]. In: Proceedings of the 2019 San Antonio Breast Cancer Symposium; 2019 Dec 10-14; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2020;80(4 Suppl):Abstract nr P4-09-01.