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Breast Cancer Res. 2019 Feb 8;21(1):22. doi: 10.1186/s13058-019-1102-7.

Targeted mutation detection in breast cancer using MammaSeq™.

Author information

1
Department of Pharmacology and Chemical Biology, and Human Genetics, UPMC Hillman Cancer Center, Magee-Womens Research Institute, University of Pittsburgh, 204 Craft Avenue, Pittsburgh, PA, 15213, USA.
2
Graduate Program in Integrated Systems Biology, University of Pittsburgh, Pittsburgh, USA.
3
Department of Pathology, Gundersen Health System, La Crosse, WI, USA.
4
Department of Pathology, University of Pittsburgh, Pittsburgh, PA, USA.
5
Department of Medicine, University of Pittsburgh, Pittsburgh, PA, USA.
6
Department of Genetics and Molecular Biology, School of Medicine, University of Medical Sciences, Isfahan, Iran.
7
Department of Pharmacology and Chemical Biology, and Human Genetics, UPMC Hillman Cancer Center, Magee-Womens Research Institute, University of Pittsburgh, 204 Craft Avenue, Pittsburgh, PA, 15213, USA. leeav@upmc.edu.

Abstract

BACKGROUND:

Breast cancer is the most common invasive cancer among women worldwide. Next-generation sequencing (NGS) has revolutionized the study of cancer across research labs around the globe; however, genomic testing in clinical settings remains limited. Advances in sequencing reliability, pipeline analysis, accumulation of relevant data, and the reduction of costs are rapidly increasing the feasibility of NGS-based clinical decision making.

METHODS:

We report the development of MammaSeq, a breast cancer-specific NGS panel, targeting 79 genes and 1369 mutations, optimized for use in primary and metastatic breast cancer. To validate the panel, 46 solid tumors and 14 plasma circulating tumor DNA (ctDNA) samples were sequenced to a mean depth of 2311× and 1820×, respectively. Variants were called using Ion Torrent Suite 4.0 and annotated with cravat CHASM. CNVKit was used to call copy number variants in the solid tumor cohort. The oncoKB Precision Oncology Database was used to identify clinically actionable variants. Droplet digital PCR was used to validate select ctDNA mutations.

RESULTS:

In cohorts of 46 solid tumors and 14 ctDNA samples from patients with advanced breast cancer, we identified 592 and 43 protein-coding mutations. Mutations per sample in the solid tumor cohort ranged from 1 to 128 (median 3), and the ctDNA cohort ranged from 0 to 26 (median 2.5). Copy number analysis in the solid tumor cohort identified 46 amplifications and 35 deletions. We identified 26 clinically actionable variants (levels 1-3) annotated by OncoKB, distributed across 20 out of 46 cases (40%), in the solid tumor cohort. Allele frequencies of ESR1 and FOXA1 mutations correlated with CA.27.29 levels in patient-matched blood draws.

CONCLUSIONS:

In solid tumor biopsies and ctDNA, MammaSeq detects clinically actionable mutations (OncoKB levels 1-3) in 22/46 (48%) solid tumors and in 4/14 (29%) of ctDNA samples. MammaSeq is a targeted panel suitable for clinically actionable mutation detection in breast cancer.

KEYWORDS:

Breast cancer; Clinical utility; Targeted sequencing; Tumor burden; ctDNA

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