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Targeted next-generation sequencing detects a high frequency of potentially actionable mutations in metastatic breast cancers.
Exp Mol Pathol 2016; 100(3):421-5EM

Abstract

BACKGROUND

Metastatic breast cancer is a genetically heterogeneous disease and effective therapies for advanced stage disease are limited.

METHODS

In this study, distant metastases of 22 formalin-fixed, paraffin-embedded (FFPE) breast cancer samples were sequenced using the Ion Torrent PGM and the 50 gene AmpliSeq Cancer Hotspot Panel v2 from 10ng of extracted DNA using 318 chips. Data analysis was performed with the Ion Torrent Variant Caller Plugin (hg19) and Golden Helix's SVS software for annotation and prediction of the significance of the variants.

RESULTS

All patients were female with a median age of 61years (range 37-85years). Metastatic sites included liver (n=6, 27%), skin (n=5, 23%), brain (n=4, 18%), lymph node (n=3, 14%), lung (n=2, 9%), retroperitoneum (n=1, 4.5%), and colon (n=1, 4.5%). Overall, 28 variants in 11 genes were observed. Five (23%) samples showed no alterations and 17 (77%) showed at least one potentially biologically significant variant (BSV) defined as having FDA-approved drugs or clinical trials evaluating their significance. BSVs included mutations in the following genes: TP53 (n=8), APC (n=4), PIK3CA (n=5), MET (n=2), ERBB2 (n=2), AKT1 (n=1), CDKN2A (n=1), KRAS (n=1), and FGFR3 (n=1).

CONCLUSIONS

Potentially actionable mutations were identified in the majority of breast cancer metastases. Evaluating metastatic breast tumors using a NGS approach provides a better understanding of the mechanisms behind tumor progression and evolution and also identifies additional potentially beneficial therapeutic targets for patient management or eligibility for clinical trials.

Authors+Show Affiliations

Department of Pathology and Laboratory Medicine, Dartmouth-Hitchcock Medical Center, 1 Medical Center Drive, Lebanon, NH 03766, United States.Department of Pathology and Laboratory Medicine, Dartmouth-Hitchcock Medical Center, 1 Medical Center Drive, Lebanon, NH 03766, United States.Department of Pathology and Laboratory Medicine, Dartmouth-Hitchcock Medical Center, 1 Medical Center Drive, Lebanon, NH 03766, United States.Department of Pathology and Laboratory Medicine, Dartmouth-Hitchcock Medical Center, 1 Medical Center Drive, Lebanon, NH 03766, United States.Department of Pharmacology & Toxicology, Dartmouth-Hitchcock Medical Center, 1 Medical Center Drive, Lebanon, NH 03766, United States.Department of Hematology-Oncology, Dartmouth-Hitchcock Medical Center, 1 Medical Center Drive, Lebanon, NH 03766, United States.Department of Pathology and Laboratory Medicine, Dartmouth-Hitchcock Medical Center, 1 Medical Center Drive, Lebanon, NH 03766, United States.Department of Pathology and Laboratory Medicine, Dartmouth-Hitchcock Medical Center, 1 Medical Center Drive, Lebanon, NH 03766, United States. Electronic address: Laura.J.Tafe@hitchcock.org.

Pub Type(s)

Journal Article
Research Support, Non-U.S. Gov't

Language

eng

PubMed ID

27095739

Citation

Muller, Kristen E., et al. "Targeted Next-generation Sequencing Detects a High Frequency of Potentially Actionable Mutations in Metastatic Breast Cancers." Experimental and Molecular Pathology, vol. 100, no. 3, 2016, pp. 421-5.
Muller KE, Marotti JD, de Abreu FB, et al. Targeted next-generation sequencing detects a high frequency of potentially actionable mutations in metastatic breast cancers. Exp Mol Pathol. 2016;100(3):421-5.
Muller, K. E., Marotti, J. D., de Abreu, F. B., Peterson, J. D., Miller, T. W., Chamberlin, M. D., ... Tafe, L. J. (2016). Targeted next-generation sequencing detects a high frequency of potentially actionable mutations in metastatic breast cancers. Experimental and Molecular Pathology, 100(3), pp. 421-5. doi:10.1016/j.yexmp.2016.04.002.
Muller KE, et al. Targeted Next-generation Sequencing Detects a High Frequency of Potentially Actionable Mutations in Metastatic Breast Cancers. Exp Mol Pathol. 2016;100(3):421-5. PubMed PMID: 27095739.
* Article titles in AMA citation format should be in sentence-case
TY - JOUR T1 - Targeted next-generation sequencing detects a high frequency of potentially actionable mutations in metastatic breast cancers. AU - Muller,Kristen E, AU - Marotti,Jonathan D, AU - de Abreu,Francine B, AU - Peterson,Jason D, AU - Miller,Todd W, AU - Chamberlin,Mary D, AU - Tsongalis,Gregory J, AU - Tafe,Laura J, Y1 - 2016/04/16/ PY - 2016/04/08/received PY - 2016/04/12/accepted PY - 2016/4/21/entrez PY - 2016/4/21/pubmed PY - 2017/6/14/medline KW - Breast cancer KW - Metastatic cancer KW - Next-generation sequencing KW - Somatic mutations KW - Targeted therapy SP - 421 EP - 5 JF - Experimental and molecular pathology JO - Exp. Mol. Pathol. VL - 100 IS - 3 N2 - BACKGROUND: Metastatic breast cancer is a genetically heterogeneous disease and effective therapies for advanced stage disease are limited. METHODS: In this study, distant metastases of 22 formalin-fixed, paraffin-embedded (FFPE) breast cancer samples were sequenced using the Ion Torrent PGM and the 50 gene AmpliSeq Cancer Hotspot Panel v2 from 10ng of extracted DNA using 318 chips. Data analysis was performed with the Ion Torrent Variant Caller Plugin (hg19) and Golden Helix's SVS software for annotation and prediction of the significance of the variants. RESULTS: All patients were female with a median age of 61years (range 37-85years). Metastatic sites included liver (n=6, 27%), skin (n=5, 23%), brain (n=4, 18%), lymph node (n=3, 14%), lung (n=2, 9%), retroperitoneum (n=1, 4.5%), and colon (n=1, 4.5%). Overall, 28 variants in 11 genes were observed. Five (23%) samples showed no alterations and 17 (77%) showed at least one potentially biologically significant variant (BSV) defined as having FDA-approved drugs or clinical trials evaluating their significance. BSVs included mutations in the following genes: TP53 (n=8), APC (n=4), PIK3CA (n=5), MET (n=2), ERBB2 (n=2), AKT1 (n=1), CDKN2A (n=1), KRAS (n=1), and FGFR3 (n=1). CONCLUSIONS: Potentially actionable mutations were identified in the majority of breast cancer metastases. Evaluating metastatic breast tumors using a NGS approach provides a better understanding of the mechanisms behind tumor progression and evolution and also identifies additional potentially beneficial therapeutic targets for patient management or eligibility for clinical trials. SN - 1096-0945 UR - https://www.unboundmedicine.com/medline/citation/27095739/Targeted_next_generation_sequencing_detects_a_high_frequency_of_potentially_actionable_mutations_in_metastatic_breast_cancers_ L2 - https://linkinghub.elsevier.com/retrieve/pii/S0014-4800(16)30037-5 DB - PRIME DP - Unbound Medicine ER -