Oncotarget

Research Papers:

Programmed death-ligand 1 expression by digital image analysis advances thyroid cancer diagnosis among encapsulated follicular lesions

Anne M.-Y. Hsieh, Olena Polyakova, Guodong Fu, Ronald S. Chazen, Christina MacMillan, Ian J. Witterick, Ranju Ralhan and Paul G. Walfish _

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Oncotarget. 2018; 9:19767-19782. https://doi.org/10.18632/oncotarget.24833

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Abstract

Anne M.-Y. Hsieh1, Olena Polyakova1, Guodong Fu1, Ronald S. Chazen1, Christina MacMillan3,4, Ian J. Witterick1,2,5, Ranju Ralhan1,3,4,5 and Paul G. Walfish1,2,3,4,5,6

1Alex and Simona Shnaider Research Laboratory in Molecular Oncology, Sinai Health System, Toronto, ON, Canada

2Joseph and Mildred Sonshine Family Centre for Head and Neck Diseases, Sinai Health System, Toronto, Ontario, Canada

3Department of Pathology and Laboratory Medicine, Sinai Health System, Toronto, Ontario, Canada

4Laboratory Medicine and Pathobiology, University of Toronto, Toronto, Ontario, Canada

5Department of Otolaryngology-Head and Neck Surgery, Sinai Health System, Toronto, Ontario, Canada

6Department of Medicine, Endocrine Division, Sinai Health System and University of Toronto Medical School, Toronto, Ontario, Canada

Correspondence to:

Paul G. Walfish, email: [email protected]

Keywords: thyroid cancer; digital image analysis; programmed death-ligand 1; invasion; protein biomarker

Received: October 06, 2017     Accepted: February 24, 2018     Published: April 13, 2018

ABSTRACT

Recognition of noninvasive follicular thyroid neoplasms with papillary-like nuclear features (NIFTP) that distinguishes them from invasive malignant encapsulated follicular variant of papillary thyroid carcinoma (EFVPTC) can prevent overtreatment of NIFTP patients. We and others have previously reported that programmed death-ligand 1 (PD-L1) is a useful biomarker in thyroid tumors; however, all reports to date have relied on manual scoring that is time consuming as well as subject to individual bias. Consequently, we developed a digital image analysis (DIA) protocol for cytoplasmic and membranous stain quantitation (ThyApp) and evaluated three tumor sampling methods [Systemic Uniform Random Sampling, hotspot nucleus, and hotspot nucleus/3,3′-Diaminobenzidine (DAB)]. A patient cohort of 153 cases consisting of 48 NIFTP, 44 EFVPTC, 26 benign nodules and 35 encapsulated follicular lesions/neoplasms with lymphocytic thyroiditis (LT) was studied. ThyApp quantitation of PD-L1 expression revealed a significant difference between invasive EFVPTC and NIFTP; but none between NIFTP and benign nodules. ThyApp integrated with hotspot nucleus tumor sampling method demonstrated to be most clinically relevant, consumed least processing time, and eliminated interobserver variance. In conclusion, the fully automatic DIA algorithm developed using a histomorphological approach objectively quantitated PD-L1 expression in encapsulated thyroid neoplasms and outperformed manual scoring in reproducibility and higher efficiency.


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