Validation of tumor protein marker quantification by two independent automated immunofluorescence image analysis platforms.
Protein marker levels in formalin-fixed, paraffin-embedded tissue sections traditionally have been assayed by chromogenic immunohistochemistry and evaluated visually by pathologists. Pathologist scoring of chromogen staining intensity is subjective and generates low-resolution ordinal or nominal data rather than continuous data. Emerging digital pathology platforms now allow quantification of chromogen or fluorescence signals by computer-assisted image analysis, providing continuous immunohistochemistry values. Fluorescence immunohistochemistry offers greater dynamic signal range than chromogen immunohistochemistry, and combined with image analysis holds the promise of enhanced sensitivity and analytic resolution, and consequently more robust quantification. However, commercial fluorescence scanners and image analysis software differ in features and capabilities, and claims of objective quantitative immunohistochemistry are difficult to validate as pathologist scoring is subjective and there is no accepted gold standard. Here we provide the first side-by-side validation of two technologically distinct commercial fluorescence immunohistochemistry analysis platforms. We document highly consistent results by (1) concordance analysis of fluorescence immunohistochemistry values and (2) agreement in outcome predictions both for objective, data-driven cutpoint dichotomization with Kaplan-Meier analyses or employment of continuous marker values to compute receiver-operating curves. The two platforms examined rely on distinct fluorescence immunohistochemistry imaging hardware, microscopy vs line scanning, and functionally distinct image analysis software. Fluorescence immunohistochemistry values for nuclear-localized and tyrosine-phosphorylated Stat5a/b computed by each platform on a cohort of 323 breast cancer cases revealed high concordance after linear calibration, a finding confirmed on an independent 382 case cohort, with concordance correlation coefficients >0.98. Data-driven optimal cutpoints for outcome prediction by either platform were reciprocally applicable to the data derived by the alternate platform, identifying patients with low Nuc-pYStat5 at ~3.5-fold increased risk of disease progression. Our analyses identified two highly concordant fluorescence immunohistochemistry platforms that may serve as benchmarks for testing of other platforms, and low interoperator variability supports the implementation of objective tumor marker quantification in pathology laboratories.
Department of Pathology, Medical College of Wisconsin, Milwaukee, WI, USA.
Amy R
AR
Peck
Department of Pathology, Medical College of Wisconsin, Milwaukee, WI, USA.
Melanie A
MA
Girondo
Department of Pathology, Medical College of Wisconsin, Milwaukee, WI, USA.
Chengbao
C
Liu
John P. Murtha Cancer Center, Walter Reed National Military Medical Center, Bethesda, MD, USA.
Albert J
AJ
Kovatich
John P. Murtha Cancer Center, Walter Reed National Military Medical Center, Bethesda, MD, USA.
Jeffrey A
JA
Hooke
John P. Murtha Cancer Center, Walter Reed National Military Medical Center, Bethesda, MD, USA.
Craig D
CD
Shriver
Chan Soon-Shiong Institute of Molecular Medicine at Windber, Windber, PA, USA.
Hai
H
Hu
Department of Medical Oncology, Thomas Jefferson University, Philadelphia, PA, USA.
Edith P
EP
Mitchell
Division of Biostatistics, Thomas Jefferson University, Philadelphia, PA, USA.
Boris
B
Freydin
Duke Cancer Institute, Department of Biostatistics and Bioinformatics, Duke University, Durham, NC, USA.
Terry
T
Hyslop
Division of Biostatistics, Thomas Jefferson University, Philadelphia, PA, USA.
Inna
I
Chervoneva
Department of Pathology, Medical College of Wisconsin, Milwaukee, WI, USA.
Hallgeir
H
Rui
D014408:Biomarkers, Tumor / Q000032:analysis*; D001943:Breast Neoplasms / Q000378:metabolism*; D005260:Female; D005455:Fluorescent Antibody Technique / Q000379:methods*; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D015203:Reproducibility of Results
D014408:Biomarkers, Tumor