4.5 Article

Steroidogenic Factor 1, Pit-1, and Adrenocorticotropic Hormone A Rational Starting Place for the Immunohistochemical Characterization of Pituitary Adenoma

Journal

ARCHIVES OF PATHOLOGY & LABORATORY MEDICINE
Volume 141, Issue 1, Pages 104-112

Publisher

COLL AMER PATHOLOGISTS
DOI: 10.5858/arpa.2016-0082-OA

Keywords

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Funding

  1. Allina Health Center for Healthcare Innovation (Minneapolis, Minnesota)
  2. Abbott Northwestern Hospital Foundation (Minneapolis, Minnesota)

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Context.-Pituitary adenoma classification is complex, and diagnostic strategies vary greatly from laboratory to laboratory. No optimal diagnostic algorithm has been defined. Objective.-To develop a panel of immunohistochemical (IHC) stains that provides the optimal combination of cost, accuracy, and ease of use. Design.-We examined 136 pituitary adenomas with stains of steroidogenic factor 1 (SF-1), Pit-1, anterior pituitary hormones, cytokeratin CAM5.2, and alpha subunit of human chorionic gonadotropin. Immunohistochemical staining was scored using the Allred system. Adenomas were assigned to a gold standard class based on IHC results and available clinical and serologic information. Correlation and cluster analyses were used to develop an algorithm for parsimoniously classifying adenomas. Results.-The algorithm entailed a 1- or 2-step process: (1) a screening step consisting of IHC stains for SF-1, Pit-1, and adrenocorticotropic hormone; and (2) when screening IHC pattern and clinical history were not clearly gonadotrophic (SF-1 positive only), corticotrophic (adrenocorticotropic hormone positive only), or IHC null cell (negative-screening IHC), we subsequently used IHC for prolactin, growth hormone, thyroid-stimulating hormone, and cytokeratin CAM5.2. Conclusions.-Comparison between diagnoses generated by our algorithm and the gold standard diagnoses showed excellent agreement. When compared with a commonly used panel using 6 IHC for anterior pituitary hormones plus IHC for a low-molecular-weight cytokeratin in certain tumors, our algorithm uses approximately one-third fewer IHC stains and detects gonadotroph adenomas with greater sensitivity.

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