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Molecular genomic and transcriptomic profiling of familial breast cancer.

ABSTRACT: This SuperSeries is composed of the SubSeries listed below.

ORGANISM(S): Homo sapiens

PROVIDER: GSE54219 | GEO | 2017/01/17

SECONDARY ACCESSION(S): PRJNA235955

REPOSITORIES: GEO

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Molecular genomic and transcriptomic profiling of familial breast cancer.

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Project description:PurposeMetastatic breast cancer (MBC) is not curable and there is a growing interest in personalized therapy options. Here we report molecular profiling of MBC focusing on molecular evolution in actionable alterations.Experimental designSixty-two patients with MBC were included. An analysis of DNA, RNA, and functional proteomics was done, and matched primary and metastatic tumors were compared when feasible.ResultsTargeted exome sequencing of 41 tumors identified common alterations in TP53 (21; 51%) and PIK3CA (20; 49%), as well as alterations in several emerging biomarkers such as NF1 mutations/deletions (6; 15%), PTEN mutations (4; 10%), and ARID1A mutations/deletions (6; 15%). Among 27 hormone receptor-positive patients, we identified MDM2 amplifications (3; 11%), FGFR1 amplifications (5; 19%), ATM mutations (2; 7%), and ESR1 mutations (4; 15%). In 10 patients with matched primary and metastatic tumors that underwent targeted exome sequencing, discordances in actionable alterations were common, including NF1 loss in 3 patients, loss of PIK3CA mutation in 1 patient, and acquired ESR1 mutations in 3 patients. RNA sequencing in matched samples confirmed loss of NF1 expression with genomic NF1 loss. Among 33 patients with matched primary and metastatic samples that underwent RNA profiling, 14 actionable genes were differentially expressed, including antibody-drug conjugate targets LIV-1 and B7-H3.ConclusionsMolecular profiling in MBC reveals multiple common as well as less frequent but potentially actionable alterations. Genomic and transcriptional profiling demonstrates intertumoral heterogeneity and potential evolution of actionable targets with tumor progression. Further work is needed to optimize testing and integrated analysis for treatment selection.

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