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Figure 1.
Expression Profile Similarity in Patient-Matched Breast Cancer Metastases to the Brain
Expression Profile Similarity in Patient-Matched Breast Cancer Metastases to the Brain

A, Unsupervised hierarchical clustering heatmap of 20 patient-matched cases with hormone status (green indicates positive; black, negative), tissue site source or institution (yellow indicates Royal College of Surgeons [RCS], Ireland; purple, University of Pittsburgh [Pitt], United States), and tumor site (blue indicates primary; red, metastasis) of each sample indicated. The asterisks below the plots indicate patient-matched pairs that clustered in the same doublet of a clade in the dendrogram. B, PAM50 intrinsic molecular subtype calls in patient-matched cases (red indicates basal; green, ERBB2/HER2; blue, LumA; yellow, LumB). Discordant pairs are marked with a delta symbol. BP indicates breast primary; BrM, brain metastasis.

Figure 2.
Recurrent Expression Alterations in Breast Cancer Brain Metastases
Recurrent Expression Alterations in Breast Cancer Brain Metastases

A, OncoPrint plot of highly recurrent (>25% of cases) expression alterations in 20 cases, ranked by frequency of alteration by gene. Blue tile represents a greater than 2-fold decrease in the patient-matched brain metastasis relative to the primary, while a red tile represents a greater than 2-fold increase. B, Tile plot visualizing expression alterations in clinically actionable genes. Top panel consists of recurrent increases in expression (light red indicates a >2-fold increase; dark red, >4-fold increase), bottom panel are recurrent decreases in expression (light blue indicates a >2-fold decrease; dark blue, >4-fold decrease) between patient-matched pairs. Pitt indicates University of Pittsburgh; RSC, Royal College of Surgeons.

Figure 3.
ERBB2/HER2 Gains in Breast Cancer Brain Metastases
ERBB2/HER2 Gains in Breast Cancer Brain Metastases

A, Paired ladder plot of ERBB2/HER2 expression in patient-matched cases. Gray dots represent samples with suspected hormone status switching; P values are from Wilcoxon signed-rank tests (primaries vs metastases). B, The top panel shows ERBB2/HER2 alterations (amplification or mutation) in 3135 local tumors and 4130 metastatic tumors, and the bottom panel shows ERBB2/HER2 alterations in local tumors and 167 brain metastases (mets). NS indicates not significant.

1.
Dawood  S, Broglio  K, Esteva  FJ,  et al.  Defining prognosis for women with breast cancer and CNS metastases by HER2 status.  Ann Oncol. 2008;19(7):1242-1248.PubMedGoogle ScholarCrossref
2.
Bachelot  T, Romieu  G, Campone  M,  et al.  Lapatinib plus capecitabine in patients with previously untreated brain metastases from HER2-positive metastatic breast cancer (LANDSCAPE): a single-group phase 2 study.  Lancet Oncol. 2013;14(1):64-71.PubMedGoogle ScholarCrossref
3.
Partridge  AH, Rumble  RB, Carey  LA,  et al.  Chemotherapy and targeted therapy for women with human epidermal growth factor receptor 2–negative (or unknown) advanced breast cancer: American Society of Clinical Oncology Clinical practice guideline.  J Clin Oncol. 2014;32(29):3307-3329.Google ScholarCrossref
4.
Nilsen  G, Liestøl  K, Van Loo  P,  et al.  Copynumber: efficient algorithms for single- and multi-track copy number segmentation.  BMC Genomics. 2012;13(1):591.PubMedGoogle ScholarCrossref
5.
Gendoo  D, Ratanasirigulchai  N, Schröder  M,  et al.  genefu: a package for breast cancer gene expression analysis. https://www.bioconductor.org/packages/devel/bioc/vignettes/genefu/inst/doc/genefu.pdf. Accessed November 7, 2016.
6.
McKenna  A, Hanna  M, Banks  E,  et al.  The Genome Analysis Toolkit: a MapReduce framework for analyzing next-generation DNA sequencing data.  Genome Res. 2010;20(9):1297-1303.PubMedGoogle ScholarCrossref
7.
Talevich  E, Shain  AH, Botton  T, Bastian  BC.  CNVkit: genome-wide copy number detection and visualization from targeted DNA sequencing.  PLoS Comput Biol. 2016;12(4):e1004873.PubMedGoogle ScholarCrossref
8.
Wagner  AH, Coffman  AC, Ainscough  BJ,  et al.  DGIdb 2.0: mining clinically relevant drug-gene interactions.  Nucleic Acids Res. 2016;44(D1):D1036-D1044.PubMedGoogle ScholarCrossref
9.
Brastianos  PK, Carter  SL, Santagata  S,  et al.  Genomic characterization of brain metastases reveals branched evolution and potential therapeutic targets.  Cancer Discov. 2015;5(11):1164-1177.Google ScholarCrossref
10.
Duchnowska  R, Dziadziuszko  R, Trojanowski  T,  et al; Polish Brain Metastasis Consortium.  Conversion of epidermal growth factor receptor 2 and hormone receptor expression in breast cancer metastases to the brain.  Breast Cancer Res. 2012;14(4):R119.PubMedGoogle ScholarCrossref
11.
Thomson  AH, McGrane  J, Mathew  J,  et al.  Changing molecular profile of brain metastases compared with matched breast primary cancers and impact on clinical outcomes.  Br J Cancer. 2016;114(7):793-800.PubMedGoogle ScholarCrossref
12.
Gutierrez  MC, Detre  S, Johnston  S,  et al.  Molecular changes in tamoxifen-resistant breast cancer: relationship between estrogen receptor, HER-2, and p38 mitogen-activated protein kinase.  J Clin Oncol. 2005;23(11):2469-2476.PubMedGoogle ScholarCrossref
13.
Bose  R, Kavuri  SM, Searleman  AC,  et al.  Activating HER2 mutations in HER2 gene amplification negative breast cancer.  Cancer Discov. 2013;3(2):224-237.PubMedGoogle ScholarCrossref
14.
Karantza  V.  Keratins in health and cancer: more than mere epithelial cell markers.  Oncogene. 2011;30(2):127-138.PubMedGoogle ScholarCrossref
15.
Joosse  SA, Hannemann  J, Spötter  J,  et al.  Changes in keratin expression during metastatic progression of breast cancer: impact on the detection of circulating tumor cells.  Clin Cancer Res. 2012;18(4):993-1003.PubMedGoogle ScholarCrossref
16.
Osborne  CK, Schiff  R.  Mechanisms of endocrine resistance in breast cancer.  Annu Rev Med. 2011;62(1):233-247.PubMedGoogle ScholarCrossref
Brief Report
May 2017

Intrinsic Subtype Switching and Acquired ERBB2/HER2 Amplifications and Mutations in Breast Cancer Brain Metastases

Author Affiliations
  • 1Department of Pharmacology and Chemical Biology, University of Pittsburgh, Pittsburgh, Pennsylvania
  • 2Women's Cancer Research Center, University of Pittsburgh Cancer Institute, Pittsburgh, Pennsylvania
  • 3Magee-Women's Research Institute, Magee-Women's Research Hospital of University of Pittsburgh Medical Center, Pittsburgh, Pennsylvania
  • 4Medical Scientist Training Program, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania
  • 5Foundation Medicine, Cambridge, Massachusetts
  • 6Endocrine Oncology Research Group, Department of Surgery, Royal College of Surgeons in Ireland, Dublin, Ireland
  • 7Department of Human Genetics, University of Pittsburgh Graduate School of Public Health, Pittsburgh, Pennsylvania
  • 8Department of Medicine, University of Pittsburgh Medical Center, Pittsburgh, Pennsylvania
  • 9Holden Comprehensive Cancer Center, University of Iowa Hospitals and Clinics, Iowa City
  • 10Department of Pathology, University of Pittsburgh Medical Center, Pittsburgh, Pennsylvania
JAMA Oncol. 2017;3(5):666-671. doi:10.1001/jamaoncol.2016.5630
Key Points

Question  Do brain metastases gain clinically actionable molecular alterations when compared with patient-matched primary breast cancers?

Findings  Overall, 17 of 20 brain metastases in this study retained the PAM50 subtype of the primary tumor; yet, clinically actionable gains are common, with approximately 20% of ERBB2/HER2-negative primary tumors switching to ERBB2/HER2-positive.

Meaning  Breast cancer brain metastases commonly acquire alterations in clinically actionable genes, which has immediate clinical implications and supports comprehensive profiling of metastases to inform clinical care.

Abstract

Importance  Patients with breast cancer (BrCa) brain metastases (BrM) have limited therapeutic options. A better understanding of molecular alterations acquired in BrM could identify clinically actionable metastatic dependencies.

Objective  To determine whether there are intrinsic subtype differences between primary tumors and matched BrM and to uncover BrM-acquired alterations that are clinically actionable.

Design, Setting, and Participants  In total, 20 cases of primary breast cancer tissue and resected BrM (10 estrogen receptor [ER]-negative and 10 ER-positive) from 2 academic institutions were included. Eligible cases in the discovery cohort harbored patient-matched primary breast cancer tissue and resected BrM. Given the rarity of patient-matched samples, no exclusion criteria were enacted. Two validation sequencing cohorts were used—a published data set of 17 patient-matched cases of BrM and a cohort of 7884 BrCa tumors enriched for metastatic samples.

Main Outcomes and Measures  Brain metastases expression changes in 127 genes within BrCa signatures, PAM50 assignments, and ERBB2/HER2 DNA-level gains.

Results  Overall, 17 of 20 BrM retained the PAM50 subtype of the primary BrCa. Despite this concordance, 17 of 20 BrM harbored expression changes (<2-fold or >2-fold) in clinically actionable genes including gains of FGFR4 (n = 6 [30%]), FLT1 (n = 4 [20%]), AURKA (n = 2 [10%]) and loss of ESR1 expression (n = 9 [45%]). The most recurrent expression gain was ERBB2/HER2, which showed a greater than 2-fold expression increase in 7 of 20 BrM (35%). Three of these 7 cases were ERBB2/HER2-negative out of 13 ERBB2/HER2-negative in the primary BrCa cohort and became immunohistochemical positive (3+) in the paired BrM with metastasis-specific amplification of the ERBB2/HER2 locus. In an independent data set, 2 of 9 (22.2%) ERBB2/HER2-negative BrCa switched to ERBB2/HER2-positive with 1 BrM acquiring ERBB2/HER2 amplification and the other showing metastatic enrichment of the activating V777L ERBB2/HER2 mutation. An expanded cohort revealed that ERBB2/HER2 amplification and/or mutation frequency was unchanged between local disease and metastases across all sites; however, a significant enrichment was appreciated for BrM (13% local vs 24% BrM; P < .001).

Conclusions and Relevance  Breast cancer BrM commonly acquire alterations in clinically actionable genes, with metastasis-acquired ERBB2/HER2 alterations in approximately 20% of ERBB2/HER2-negative cases. These observations have immediate clinical implications for patients with ERBB2/HER2–negative breast cancer and support comprehensive profiling of metastases to inform clinical care.

Introduction

Brain metastases (BrM) occur in 10% to 15% of patients with metastatic breast cancer (BrCa) and present a major clinical challenge, highlighted by a poor 8.5-month median overall survival.1 Limited therapeutic options exist for patients with BrM and current management consists of surgical resection, radiation therapy, and chemotherapy. ERBB2/HER2-positive BrM have demonstrated encouraging responses to ERBB2/HER2-targeted therapies in recent clinical trials.2 Unfortunately, in patients with ERBB2/HER2-negative BrM, no targeted therapies have shown even modest benefits.3

In this study, we performed targeted expression profiling on a molecularly diverse cohort of 20 primary breast tumors and their patient-matched BrM to determine transcriptional differences between primary cancers and BrM and to define metastasis-acquired alterations that may be clinically actionable.

Methods

Eligible BrCa cases harbored paired formalin-fixed, paraffin-embedded tissue from primary BrCa and resected BrM (eTable 1 in Supplement 1). Two independent data sets reinforced findings—17 patient-matched BrCa cases of whole-exome sequencing data4 and targeted sequencing from 7884 BrCa tumors enriched for metastases. This study was approved by the institutional review boards of both participating institutions.

NanoString expression counts for target genes were generated from tumor RNA extracts. Hierarchical clusters, PAM50/Oncotype DX assignments,5 and fold-change expression values between patient-matched tumors (eFigure 1 in Supplement 1) were called using normalized expression counts.

Standard clinical ERBB2/HER2 and estrogen receptor (ER) immunohistochemistry (IHC) analyses were performed. DNA from case Pitt_62 was extracted and analyzed for ERBB2 gains using a single-nucleotide polymorphism–based microarray. Metastasis-specific ERBB2/HER2 copy number alteration and single-nucleotide variation (SNV) gains in whole-exome sequencing were interrogated with CNVkit and GATK.6,7 To test for site-specific enrichment of ERBB2/HER2 amplifications and SNVs in metastases, we analyzed FoundationOne (Foundation Medicine) targeted sequencing data.

More detailed methods can be found in Supplement 1, and more detailed results, including unprocessed raw count data, can be found in Supplement 2.

Results

To determine the transcriptional similarity between primary tumors and patient-matched BrM, we performed unsupervised hierarchical clustering on normalized gene expression values. This produced 3 major clades broadly classified as ER-positive, ERBB2/HER2-positive, and ER-negative (Figure 1A). Overall, 12 of 20 (65%) patient-matched pairs clustered within a single doublet clade. PAM50 assignments were concordant in 17 of 20 pairs (Figure 1B). OncotypeDX (Genomic Health) scores were also largely unchanged between primary and metastatic tumors, retaining their clinical risk score in 15 of 20 cases (eTable 2 in Supplement 1).

Despite a large degree of similarity between patient-matched pairs, 100 genes were recurrently altered (eFigure 2A in Supplement 1); 55 genes harbored 2-fold expression gains and/or losses in at least 25% of cases (Figure 2A). The most recurrently down-regulated genes were cytokeratins—KRT17 in 14 of 20 pairs, KRT5 and KRT14 in 15 pairs (eFigure 2B in Supplement 1). The most recurrently up-regulated genes were RAB6B and GRB7 (eFigure 2B in Supplement 1).

Ten genes in the panel are defined as clinically actionable,8 and all but 3 cases had at least 1 gene with a BrM-specific change (Figure 2B). ERBB2/HER2 was the most recurrent alteration showing at least a 2-fold expression increase in 35% of BrM. Notably, 3 cases were classified as ERBB2/HER2-negative in the primary tumor. FGFR4 showed increased expression in 30% of BrM, with 3 cases showing a greater than 4-fold increase. Other recurrent gains included FLT1, AURKA, and EGFR. The most recurrently down-regulated gene was ESR1, showing a 2-fold expression decrease in 4 samples and a greater than 4-fold decrease in 5 samples. Two samples with the greatest fold-change in ESR1 switched expression from ER-positive to ER-negative levels, with 1 case showing substantial protein level changes (eFigure 3A and B in Supplement 1).

ERBB2/HER2 IHC was performed in 3 ERBB2/HER2-negative samples with the greatest mRNA gains in ERBB2/HER2 (Figure 3A). All 3 tumors showed clinical ERBB2/HER2-status switching via IHC scores—RCS_4 and RCS_6; 1+ in primary, 3+ in BrM (data not shown), Pitt_62; 0 in primary, 3+ in BrM (eFigure 4A in Supplement 1). Single-nucleotide polymorphism array copy number alteration analysis revealed that ERBB2/HER2 status switching is driven by canonical amplification of the ERBB2/HER2 locus (eFigure 4B in Supplement 1).

Given that 3 of 13 ERBB2/HER2-negative tumors showed ERBB2/HER2 gains, we then examined ERBB2/HER2 amplification and SNVs in an independent whole-exome sequencing cohort (n = 17; 9 ERBB2/HER2-negative and 8 ERBB2/HER2-positive) of patient-matched cases (dbGaP phs000730.v1.p).9 One ERBB2/HER2-negative case (Broad_PB0150) showed a metastasis-specific copy number gain in ERBB2/HER2, which was consistent with the case switching to ERBB2/HER2-positive clinically in the BrM (eFigure 5 in Supplement 1). Another case (Broad_PB0049) switched from ERBB2/HER2-negative to ERBB2/HER2-positive clinically, but no metastasis-specific copy number alteration gain was appreciated within ERBB2/HER2; however, an enrichment—from an allele frequency of 39% to 69%—of a somatic V777L activating mutation in the metastasis was identified (eFigure 5 in Supplement 1).

To generalize these observations and test whether ERBB2/HER2 gains are enriched in BrM, we analyzed a cohort of 7884 breast cancers (7265 with unambiguous tissue site information) representing 3135 cases of local disease and 4130 cases of metastases for amplifications and/or SNV in ERBB2/HER2. Comparing all local and metastatic tumors from all sites (Figure 3B) showed no significant difference; however, there was a strong and significant enrichment of ERBB2/HER2 alterations specifically in brain metastases (24%) compared with local disease (13%) (Fisher exact P < .001) (Figure 3B).

Discussion

The brain is a common and catastrophic site of metastasis for patients with breast cancer and an understanding of metastasis-acquired alterations is limited. In this study, we found that patient-matched primary BrCa and BrM have similar intrinsic subtypes; however, when examining on a gene level, clinically actionable alterations were identified in all but 3 pairs.

The most recurrent gain in BrM was ERBB2/HER2, which showed expression increases in 7 of 20 (35%) of BrM and changes from ERBB2/HER2-negative to ERBB2/HER2-positive levels. Duchnowska et al10 and Thomson et al11 reported ERBB2/HER2-negative to ERBB2/HER2-positive switching frequencies of 16% and 18% respectively in BrM via IHC. Gutierrez et al12 reported an ERBB2/HER2-switching frequency of 11% in tamoxifen-resistant tumors, and notably, 6 of 7 cases with ERBB2/HER2 expression gains were ER-positive.12 Our analysis of ERBB2/HER2-switching samples reinforces these observations and shows expression gains are partially driven by classical amplification of the ERBB2 locus. Interestingly, the ERBB2/HER2-switching Broad_PB0049 case showed no copy number gains specific to the BrM, yet harbored an enrichment of the activating V777L ERBB2/HER2 mutation,13 suggesting another DNA-level mechanism of ERBB2/HER2 gain in BrM.

Novel recurrent targetable alterations beyond ERBB2/HER2 were also discovered, including expression increases in FGFR4 (30% of pairs), FLT2 (20%), AURKA (10%) and EGFR (10%). Each one of these targets have clinical trials ongoing and our results suggest that trial eligibility requiring expression of these markers (NCT02325739) should assess metastatic tumors if available, especially given greater than 4-fold mRNA expression gains over primary tumors in patient-matched metastases. A limitation of this study, however, is the small number of patient-matched pairs.

Significant loss of gene expression from the primary to metastatic lesions was also observed. The most recurrent expression losses involved cytokeratins. Cytokeratins have shown a complex role in oncogenesis and breast cancer metastasis, with loss of cytokeratin expression being a hallmark of epithelial-mesenchymal transition and metastasis.14,15 Intermediate steps of metastasis—such as processes taking place within circulating tumor cells—may be masked in our paired analyses. The most recurrently lost clinically actionable gene was ESR1. Importantly, loss of ER expression is an established mediator of therapy resistance.16

Conclusions

Breast cancer BrM are remarkably similar transcriptionally to patient-matched primary tumors; yet, recurrent expression changes in clinically actionable genes are common. Given this evolution, metastasis-acquired features should inform targeted therapy selection and trial eligibilities in advanced cancer settings. Furthermore, approximately 20% of ERBB2/HER2-negative patients with BrCa show copy number alteration and/or SNV gains in ERBB2/HER2 across multiple cohorts, which warrants immediate clinical attention as many of these patients will not be provided ERBB2/HER2-targeted therapies.

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Article Information

Corresponding Author: Adrian V. Lee, PhD, Magee Women’s Research Institute, University of Pittsburgh Medical Center, 204 Craft Ave, Rm A412, Pittsburgh, PA 15213 (leeav@upmc.edu).

Correction: This article was corrected to add the missing Supplement 2 on January 5, 2017.

Accepted for Publication: October 17, 2016.

Published Online: December 7, 2016. doi:10.1001/jamaoncol.2016.5630

Author Contributions: Dr Lee had full access to all the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.

Concept and design: Priedigkeit, Basudan, Leone, Puhalla, Davidson, Oesterreich, Brufsky, Young, Lee.

Acquisition, analysis, or interpretation of data: Priedigkeit, Hartmaier, Chen, Vareslija, Watters, Thomas, Leone, Lucas, Bhargava, Hamilton, Chmielecki, Puhalla, Brufsky, Young, Lee.

Drafting of the manuscript: Priedigkeit, Hamilton, Brufsky, Lee.

Critical revision of the manuscript for important intellectual content: Priedigkeit, Hartmaier, Chen, Vareslija, Basudan, Watters, Thomas, Leone, Lucas, Bhargava, Chmielecki, Puhalla, Davidson, Oesterreich, Brufsky, Young, Lee.

Statistical analysis: Priedigkeit, Hartmaier, Lee.

Obtained funding: Oesterreich, Brufsky, Lee.

Administrative, technical, or material support: Priedigkeit, Hartmaier, Vareslija, Basudan, Watters, Leone, Lucas, Oesterreich, Brufsky, Lee.

Supervision: Thomas, Bhargava, Oesterreich, Brufsky, Young, Lee.

Other: Davidson.

Conflict of Interest Disclosures: Dr Hartmaier is an employee of, owns stock in, and receives royalties from Foundation Medicine Inc and has received honoraria from Biorad Laboratories. Dr Lucas owns stock in AMGen. Dr Chmielecki is an employee of, owns stock in, and receives royalties from Foundation Medicine Inc. Dr Puhalla serves an advisory and/or consulting role to Celldex, MedImmune, and Pfizer and has research funding from Abbvie, Novartis, Lilly, Pfizer, Incyte and Covance/Bayer. Dr Young has 2 patents unrelated to this work with no royalties received (PCT/IE2009/000015/US 8501483 B2, PCT/EP2012/071864/WO2013064699 A1). No other conflicts are reported.

Funding/Support: This work was supported in part by funds from the Breast Cancer Research Foundation (Drs Lee, Oesterreich, and Davidson), National Cancer Institute of the National Institutes of Health(NIH) (grant P30CA047904), Fashion Footwear Association of New York (FFANY), the Shear Family Foundation, and Magee-Womens Research Institute and Foundation. Drs Lee and Oesterreich are recipients of Scientific Advisory Council awards from Susan G. Komen for the Cure, and Dr Lee is a Hillman Foundation Fellow. Mr Priedigkeit was supported by a training grant from the NIH National Institute of General Medical Sciences (grant 2T32GM008424-21) and an individual fellowship from the NIH National Cancer Institute (grant 5F30CA203095). Drs Young and Vareslija are supported by the Irish Cancer Society Collaborative Cancer Research Centre grant, BREAST-PREDICT (CCRC13GAL).

Role of the Funder/Sponsor: Funding sources had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.

Previous Presentation: A portion of this research was presented at the 2016 San Antonio Breast Cancer Symposium; December 6-10, 2016; San Antonio, Texas.

Additional Contributions: This project used the University of Pittsburgh HSCRF Genomics Research Core single-nucleotide polymorphism array services and the UPCI Tissue and Research Pathology Services that is supported in part by award P30CA047904. We thank the UPMC Cancer Registry for clinical abstraction.

References
1.
Dawood  S, Broglio  K, Esteva  FJ,  et al.  Defining prognosis for women with breast cancer and CNS metastases by HER2 status.  Ann Oncol. 2008;19(7):1242-1248.PubMedGoogle ScholarCrossref
2.
Bachelot  T, Romieu  G, Campone  M,  et al.  Lapatinib plus capecitabine in patients with previously untreated brain metastases from HER2-positive metastatic breast cancer (LANDSCAPE): a single-group phase 2 study.  Lancet Oncol. 2013;14(1):64-71.PubMedGoogle ScholarCrossref
3.
Partridge  AH, Rumble  RB, Carey  LA,  et al.  Chemotherapy and targeted therapy for women with human epidermal growth factor receptor 2–negative (or unknown) advanced breast cancer: American Society of Clinical Oncology Clinical practice guideline.  J Clin Oncol. 2014;32(29):3307-3329.Google ScholarCrossref
4.
Nilsen  G, Liestøl  K, Van Loo  P,  et al.  Copynumber: efficient algorithms for single- and multi-track copy number segmentation.  BMC Genomics. 2012;13(1):591.PubMedGoogle ScholarCrossref
5.
Gendoo  D, Ratanasirigulchai  N, Schröder  M,  et al.  genefu: a package for breast cancer gene expression analysis. https://www.bioconductor.org/packages/devel/bioc/vignettes/genefu/inst/doc/genefu.pdf. Accessed November 7, 2016.
6.
McKenna  A, Hanna  M, Banks  E,  et al.  The Genome Analysis Toolkit: a MapReduce framework for analyzing next-generation DNA sequencing data.  Genome Res. 2010;20(9):1297-1303.PubMedGoogle ScholarCrossref
7.
Talevich  E, Shain  AH, Botton  T, Bastian  BC.  CNVkit: genome-wide copy number detection and visualization from targeted DNA sequencing.  PLoS Comput Biol. 2016;12(4):e1004873.PubMedGoogle ScholarCrossref
8.
Wagner  AH, Coffman  AC, Ainscough  BJ,  et al.  DGIdb 2.0: mining clinically relevant drug-gene interactions.  Nucleic Acids Res. 2016;44(D1):D1036-D1044.PubMedGoogle ScholarCrossref
9.
Brastianos  PK, Carter  SL, Santagata  S,  et al.  Genomic characterization of brain metastases reveals branched evolution and potential therapeutic targets.  Cancer Discov. 2015;5(11):1164-1177.Google ScholarCrossref
10.
Duchnowska  R, Dziadziuszko  R, Trojanowski  T,  et al; Polish Brain Metastasis Consortium.  Conversion of epidermal growth factor receptor 2 and hormone receptor expression in breast cancer metastases to the brain.  Breast Cancer Res. 2012;14(4):R119.PubMedGoogle ScholarCrossref
11.
Thomson  AH, McGrane  J, Mathew  J,  et al.  Changing molecular profile of brain metastases compared with matched breast primary cancers and impact on clinical outcomes.  Br J Cancer. 2016;114(7):793-800.PubMedGoogle ScholarCrossref
12.
Gutierrez  MC, Detre  S, Johnston  S,  et al.  Molecular changes in tamoxifen-resistant breast cancer: relationship between estrogen receptor, HER-2, and p38 mitogen-activated protein kinase.  J Clin Oncol. 2005;23(11):2469-2476.PubMedGoogle ScholarCrossref
13.
Bose  R, Kavuri  SM, Searleman  AC,  et al.  Activating HER2 mutations in HER2 gene amplification negative breast cancer.  Cancer Discov. 2013;3(2):224-237.PubMedGoogle ScholarCrossref
14.
Karantza  V.  Keratins in health and cancer: more than mere epithelial cell markers.  Oncogene. 2011;30(2):127-138.PubMedGoogle ScholarCrossref
15.
Joosse  SA, Hannemann  J, Spötter  J,  et al.  Changes in keratin expression during metastatic progression of breast cancer: impact on the detection of circulating tumor cells.  Clin Cancer Res. 2012;18(4):993-1003.PubMedGoogle ScholarCrossref
16.
Osborne  CK, Schiff  R.  Mechanisms of endocrine resistance in breast cancer.  Annu Rev Med. 2011;62(1):233-247.PubMedGoogle ScholarCrossref
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