Lucas, P. C. | Search bioRxiv

bioRxiv2018

Targeted mutation detection in breast cancer using MammaSeqTM

BackgroundBreast 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 remain 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.\n\nMethodsWe 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 tumor and 14 plasma circulating-free cfDNA samples were sequenced to a mean depth of 2311X and 1820 X 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. ddPCR was used to validate select cfDNA mutations.\n\nResultsIn cohorts of 46 solid tumors and 14 cfDNA 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 cfDNA 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.\n\nConclusionsIn solid tumors biopsies and cfDNA, MammaSeq detects clinicaly actionable mutations (oncoKB levels 1-3) in 22/46 (48%) solid tumors and in 4/14 (29%) of cfDNA samples. MammaSeq is a targeted panel suitable for clinically actionable mutation detection in breast cancer.

cancer biology↗

bioRxiv2017

Exome-Capture RNA-Sequencing Of Decade-Old Breast Cancers And Matched Decalcified Bone Metastases Identifies Clinically Actionable Targets

Bone metastases (BoM) are a significant cause of morbidity in patients with Estrogen-receptor (ER)-positive breast cancer, yet characterizations of human specimens are limited. In this study, exome-capture RNA-sequencing (ecRNA-seq) on aged (8-12 years), formalin-fixed paraffin-embedded (FFPE) and decalcified cancer specimens was first evaluated. Gene expression values and RNA-seq quality metrics from FFPE or decalcified tumor RNA showed minimal differences when compared to matched flash-frozen or non-decalcified tumors. ecRNA-seq was then applied on a longitudinal collection of 11 primary breast cancers and patient-matched de novo or recurrent BoM. BoMs harbored shifts to more Her2 and LumB PAM50 intrinsic subtypes, temporally influenced expression evolution, recurrently dysregulated prognostic gene sets and altered expression of clinically actionable genes, particularly in the CDK-Rb-E2F and FGFR-signaling pathways. Taken together, this study demonstrates the use of ecRNA-seq on decade-old and decalcified specimens and defines expression-based tumor evolution in long-term, estrogen-deprived metastases that may have immediate clinical implications.\n\nGrant SupportResearch funding for this project was provided in part by a Susan G. Komen Scholar award to AVL and to SO, the Breast Cancer Research Foundation (AVL and SO), the Fashion Footwear Association of New York, the Magee-Womens Research Institute and Foundation, and through a Postdoctoral Fellowship awarded to RJW from the Department of Defense (BC123242). NP was supported by a training grant from the NIH/NIGMS (2T32GM008424-21) and an individual fellowship from the NIH/NCI (5F30CA203095).\n\nConflicts of Interest DisclosureNo relevant conflicts of interest disclosed for this study.\n\nAuthor ContributionsStudy concept and design (NP, RJW, SO, AVL); acquisition, analysis, or interpretation of data (all authors); drafting of the manuscript (NP, RJW, SO, AVL); critical revision of the manuscript for important intellectual content (all authors); administrative, technical, or material support (PCL, AB, RB, KRW, WH, JK, MR, ZF, AMB).

cancer biology↗