The Role of T-box Transcription Factor in a Pituitary Adenoma Diagnostic Algorithm.

* Context.--We previously examined pituitary adenomas with immunohistochemical (IHC) stains for steroidogenic factor 1, Pit-1, anterior pituitary hormones, cytokeratin CAM 5.2, and the a-subunit of human chorionic gonadotropin and found that a screening panel comprising stains for steroidogenic fact...

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Publicado en:Archives of Pathology & Laboratory Medicine Vol. 145; no. 5; pp. 592 - 599
Autores principales: McDonald, William C., McDonald, Kelsey N., Helmer, Jordan A., Ho, Bridget, Wang, Amber, Banerji, Nilanjana
Formato: pictorial research tables/charts Journal Article
Publicado: College of American Pathologists May2021
Acceso en línea:Ver este registro en EBSCOhost
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      dt: May2021
      vid: 145
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      pub: College of American Pathologists
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        atl: The Role of T-box Transcription Factor in a Pituitary Adenoma Diagnostic Algorithm.
      aug:
        au:
          McDonald, William C.
          McDonald, Kelsey N.
          Helmer, Jordan A.
          Ho, Bridget
          Wang, Amber
          Banerji, Nilanjana
        affil: Department of Pathology and Laboratory Medicine, Allina Health Laboratories, Minneapolis, Minnesota
      sug:
        subj:
          Adenoma, Pituitary Diagnosis
          Algorithms
          Transcription Factors Metabolism
          Immunohistochemistry
          Staining and Labeling
          Adenoma, Pituitary Classification
          Cancer Screening Methods
          Human
          Cancer Patients
          Cancer Care Facilities
          Tissue Array Analysis
          Serologic Tests
          Correlational Studies
          Cluster Analysis
          Descriptive Statistics
          Sensitivity and Specificity
          Predictive Value of Tests
      ab: * Context.--We previously examined pituitary adenomas with immunohistochemical (IHC) stains for steroidogenic factor 1, Pit-1, anterior pituitary hormones, cytokeratin CAM 5.2, and the a-subunit of human chorionic gonadotropin and found that a screening panel comprising stains for steroidogenic factor 1, Pit-1, and adrenocorticotropic hormone successfully classified most cases and reduced the overall number of stains required. Objectives.--To examine the potential role of IHC stain for T-box transcription factor (Tpit) in the classification of our series of pituitary adenomas and to update our screening panel as necessary. Design.--We collected 157 pituitary adenomas from 2 institutions and included these in tissue microarrays. Immunostains for Tpit were scored in a blinded fashion using the Allred system. Adenomas were assigned to a gold standard class based on IHC pattern followed by application of available clinical and serologic information. Test characteristics were calculated. Correlation analyses, cluster analyses, and classification tree analyses were used to see whether IHC staining patterns reliably reflected adenoma class. Results.--Of the cases collected, 147 (93.6%) had sufficient material for Tpit analysis. IHC stain for Tpit identified 8 null cell adenomas (all nonfunctioning clinically) as silent corticotrophs; Tpit stains showed better sensitivity, specificity, positive predictive value, and negative predictive value than IHC for adrenocorticotropic hormone and cytokeratin CAM 5.2. Correlation analyses continued to show the expected relationships among IHC stains. Cluster analyses showed grouping of adenomas into clinically consistent groups. Classification tree analysis underscored the central role of transcription factor IHC stains, including Tpit, in adenoma classification. Conclusions.--Substitution of Tpit stain for the adrenocorticotropic hormone stain improves our prior algorithm by reducing the number of false-negatives and falsepositives. As a result, fewer adenomas are classified as null cell adenoma, and more adenomas are classified as silent corticotroph adenoma.
      pubtype: Academic Journal
      doctype:
        pictorial
        research
        tables/charts
        Journal Article
      ougenre: Article
    language: English
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