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Quantifying Estrogen and Progesterone Receptor Expression in Breast Cancer by Digital Imaging

Monika K. Szeszel, Cameron L. Crisman, Lauren Crow, Steven McMullen, Jacqueline M. Major, Loki Natarajan, Abu Saquib, James R. Feramisco and Linda M. Wasserman

Department of Medicine (JRF,LMW), the Department of Family and Preventive Medicine (JMM,LN), the Rebecca and John Moores University of California, San Diego, Cancer Center (MKS,LC,SM,JMM,LN,AS,JRF,LMW), and San Diego Supercomputer Center (CLC), University of California, San Diego, La Jolla, California; and San Diego State University, San Diego, California (AS)

Correspondence to: Linda M. Wasserman, MD, PhD, University of California, San Diego, 9500 Gilman Drive, La Jolla, CA 92093. E-mail: lwasserman{at}ucsd.edu

Developments in digital imaging and fluorescent microscopy provide a new method and opportunities for quantification of protein expression in human tissue. Archived collections of paraffin-embedded tumors can be used to study the relationship between quantitative differences in protein expression in tumors and patient outcome. In this report we describe the use of a DeltaVision Restoration deconvolution microscope, combined with fluorescent immunohistochemistry, to obtain reproducible and quantitative estimates of protein expression in a formalin-fixed paraffin-embedded tissue. As proof of principle, we used antibodies to the estrogen and progesterone receptors in a hormone receptor–positive breast cancer specimen. We provide guidelines for control of day-to-day variability in camera and microscope performance to ensure that image acquisition leads to reproducible quantitative estimates of protein expression. We show that background autofluorescence related to formalin fixation can be controlled and that for proteins that are expressed in nearly every cell, multiplexing two primary antibodies on the same slide does not significantly affect the results obtained. We demonstrate that for proteins whose expression varies markedly from cell to cell, data reproducibility, as assessed by imaging successive tissue sections, is more difficult to determine.

(J Histochem Cytochem 53:753–762, 2005)

Key Words: digital imaging • estrogen receptor • progesterone receptor • protein quantification

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