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Genetic landscape of breast cancer and mutation tracking with circulating tumor DNA in Chinese women

Considerable efforts have been devoted to exploring the breast cancer mutational landscape to understand its genetic complexity. However, no studies have yet comprehensively elucidated the molecular characterization of breast tumors in Chinese women. This study aimed to determine the potential clini...

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Detalles Bibliográficos
Autores principales: Wang, Yinghao, Lin, Lizhi, Li, Linhong, Wen, Jialiang, Chi, Yili, Hao, Rutian, Dai, Xuanxuan, Chen, Yizuo, Huang, Duping, Zhou, Yili, You, Jie, Ye, Zhiqiang, Chen, Hao, Jin, Lingli, Chen, Danxiang, Yang, Fan, Xia, Erjie, Ma, Xueyan, Guo, Fengyu, Tong, Yunguang, Zheng, Min, Wang, Ouchen
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Impact Journals 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8109076/
https://www.ncbi.nlm.nih.gov/pubmed/33893247
http://dx.doi.org/10.18632/aging.202888
Descripción
Sumario:Considerable efforts have been devoted to exploring the breast cancer mutational landscape to understand its genetic complexity. However, no studies have yet comprehensively elucidated the molecular characterization of breast tumors in Chinese women. This study aimed to determine the potential clinical utility of peripheral blood assessment for circulating tumor-derived DNA (ctDNA) and comprehensively characterize the female Chinese population’s genetic mutational spectrum. We used Omi-Seq to create cancer profiles of 273 patients enrolled at The First Affiliated Hospital of Wenzhou Medical University. The gene landscape results indicate PIK3CA and TP53 as the most frequently detected genes, followed by ERBB2, in Chinese breast cancer patients. The accuracy of ERBB2 copy number variations in tissue/formalin-fixed and paraffin-embedded samples was 95% with 86% sensitivity and 99% specificity. Moreover, mutation numbers varied between different molecular cell-free DNA subtypes, with the basal-like patients harboring a higher number of variants than the luminal patients. Furthermore, ratio changes in the max ctDNA allele fraction highly correlated with clinical response measurements, including cancer relapse and metastasis. Our data demonstrate that ctDNA characterization using the Omi-Seq platform can extend the capacity of personalized clinical cancer management.