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Novel tumor sampling strategies to enable microarray gene expression signatures in breast cancer: a study to determine feasibility and reproducibility in the context of clinical care

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Abstract

Feasibility and reproducibility of microarray biomarkers in clinical settings are doubted because of reliance on fresh frozen tissue. We sought to develop and validate a paradigm of frozen tissue collection from early breast tumors to enable use of microarray in oncology practice. Frozen core needle biopsies (CNBx) were collected from 150 clinical stage I patients during image-guided diagnostic biopsy and/or surgery. Histology and tumor content from frozen cores were compared to diagnostic specimens. Twenty-eight patients had microarray analysis to examine accuracy and reproducibility of predictive gene signatures developed for estrogen receptor (ER) and HER2. One hundred twenty-seven (85%) of 150 patients had at least one frozen core containing cancer suitable for microarray analysis. Larger tumor size, ex vivo biopsy, and use of a new specimen device increased the likelihood of obtaining adequate specimens. Sufficient quality RNA was obtained from 90% of tumor cores. Microarray signatures predicting ER and HER2 expression were developed in training sets of up to 363 surgical samples and were applied to microarray data obtained from core samples collected in clinical settings. In these samples, prediction of ER and HER2 expression achieved a sensitivity/specificity of 94%/100%, and 82%/72%, respectively. Predictions were reproducible in 83–100% of paired samples. Frozen CNBx can be readily obtained from most breast cancers without interfering with pathologic evaluation in routine clinical settings. Collection of tumor tissue at diagnostic biopsy and/or at surgery from lumpectomy specimens using image guidance resulted in sufficient samples for array analysis from over 90% of patients. Sampling of breast cancer for microarray data is reproducible and feasible in clinical practice and can yield signatures predictive of multiple breast cancer phenotypes.

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Acknowledgments

The authors thank Mike West, PhD, for discussion of data normalization and statistical approaches to microarray data used in this project. We also acknowledge Andrea Richardson, MD, PhD, and J. Dirk Iglehart, MD for microarray data sharing as part of an NIH breast cancer inter-SPORE collaboration between Duke University and the Dana Farber Cancer Center.

Conflict of interest statement

Duke University has been issued a USA patent (7,172,558 B2) for the tissue sampling device. Dr. Olson is founder of Core Prognostex, Inc. a company that has developed and markets tissue collection protocols and kits for correlative studies in oncology clinical trials. This company had no involvement in this study.

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Authors and Affiliations

  1. Department of Surgery, Duke University Medical Center, Durham, NC, 27710, USA

    Christopher L. Tebbit, Brian R. Untch, Jeffrey R. Marks & John A. Olson Jr.

  2. Institute of Genome Sciences and Policy, Duke University, Durham, NC, USA

    Jun Zhai, Holly K. Dressman, Joseph R. Nevins & John A. Olson Jr.

  3. Department of Medicine, Washington University School of Medicine, St Louis, MO, USA

    Matthew J. Ellis

  4. Department of Pathology, Duke University Medical Center, Durham, NC, USA

    Rex C. Bentley

  5. Department of Radiology, Duke University Medical Center, Durham, NC, USA

    Jay A. Baker

  6. Department of Medicine, Duke University School of Medicine, Durham, NC, 27710, USA

    Paul K. Marcom

Authors
  1. Christopher L. Tebbit
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  2. Jun Zhai
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  3. Brian R. Untch
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  4. Matthew J. Ellis
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  5. Holly K. Dressman
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  6. Rex C. Bentley
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  7. Jay A. Baker
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  9. Joseph R. Nevins
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  10. Jeffrey R. Marks
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  11. John A. Olson Jr.
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Corresponding author

Correspondence to John A. Olson Jr..

Additional information

Supported by the Clinical Investigator and James Ewing Oncology Fellowship Awards from the Society of Surgical Oncology (JAO), NIH K23 CA106595 (JAO), R21 CA108707 (JAO), NIH T32 CA93245-01 (CLT), and the Duke/DFCC breast SPOREs.

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Tebbit, C.L., Zhai, J., Untch, B.R. et al. Novel tumor sampling strategies to enable microarray gene expression signatures in breast cancer: a study to determine feasibility and reproducibility in the context of clinical care. Breast Cancer Res Treat 118, 635–643 (2009). https://doi.org/10.1007/s10549-008-0301-1

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  • DOI: https://doi.org/10.1007/s10549-008-0301-1

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