alexa Determining the Optimal Numbers of Cores Based on Tissue Microarray Antibody Assessment in Non-Small Cell Lung Cancer | OMICS International | Abstract
ISSN: 1948-5956

Journal of Cancer Science & Therapy
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Research Article

Determining the Optimal Numbers of Cores Based on Tissue Microarray Antibody Assessment in Non-Small Cell Lung Cancer

Jason A. Wampfler1, Marie Christine Aubry2, Ping Yang1*, Darren L. Riehle3, C. Dilara Savci-Heijink3, Sumithra Mandrekar4 and Wilma L. Lingle2

1Department of Health Sciences Research, Mayo Clinic College of Medicine, 200 First Street SW, Rochester, Minnesota, 55905, USA

2Department of Laboratory Medicine and Pathology, Mayo Clinic College of Medicine, 200 First Street SW, Rochester, Minnesota, 55905, USA

3Advanced Genomics Technology Center, Mayo Clinic College of Medicine, 200 First Street SW, Rochester, Minnesota, 55905, USA

4Cancer Center Statistics, Mayo Clinic of College Medicine, 200 First Street SW, Rochester, Minnesota, 55905, USA

*Corresponding Author:
Dr. Ping Yang
Mayo Clinic, 200 First Street SW, Rochester, MN, 55905
Tel: 507-266-5369
Fax: 507-266-2478
E-mail: [email protected]

Received Date: April 23, 2011; Accepted Date: July 20, 2011; Published Date: July 22, 2011

Citation: Wampfler JA, Aubry MC, Yang P, Riehle DL, Savci-Heijink CD (2011) Determining the Optimal Numbers of Cores Based on Tissue Microarray Antibody Assessment in Non-Small Cell Lung Cancer. J Cancer Sci Ther 3:120-124. doi: 10.4172/1948-5956.1000072

Copyright: © 2011 Wampfler JA, et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Abstract

Background: Tissue microarrays (TMAs) have been commonly utilized in translational research to rapidly screen numerous biomarkers in large samples. One major concern has been the adequate assessment of biomarkers affected by within-tumor heterogeneity and by molecular targets. Methods: Our study was designed to answer a fundamental question: How do researchers define the optimal cores to sample when designing a TMA study to minimize sampling bias and core artifact? We compared the staining results from a full-section tissue slide to the virtual TMA and from the actual TMA to the virtual TMA. Results: Three cores were demonstrated as optimal for markers such as TTF-1 and p53, but no optimal core number could be determined for markers such as Ki-67 due to the poor TMA representation of the entire tissue. Conclusion: We propose that before using TMAs to analyze large samples, particularly with significant withinsample heterogeneity, a preliminary investigation using a virtual TMA could help decide target markers to be tested for valid and valued results.

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