Plurihormonal PIT-1-Positive Pituitary Adenomas: A Systematic Review and Single-Center Series

Transcription Factor Immunohistochemistry in the Classification of Pituitary Neuroendocrine Tumor/Adenoma: Proposal in a Limited-Resource Setting

CONTEXT.—

Pituitary neuroendocrine tumors/adenomas are common intracranial tumors that require accurate subtyping because each tumor differs in its biologic behavior and response to treatment. Pituitary-specific transcription factors allow for improved lineage identification and diagnosis of newly introduced variants.

OBJECTIVE.—

To assess the usefulness of transcription factors and design a limited panel of immunostains for classification of pituitary neuroendocrine tumors/adenoma.

DESIGN.—

A total of 356 tumors were classified as per expression of pituitary hormones and transcription factors T-box family member TBX19 (TPIT), pituitary-specific POU-class homeodomain (PIT1), and steroidogenic factor-1 (SF-1). The resultant classification was correlated with patients' clinical and biochemical features. The performance and relevance of individual immunostains were analyzed.

RESULTS.—

Reclassification of 34.8% (124 of 356) of pituitary neuroendocrine tumors/adenoma was done after application of transcription factors. The highest agreement with final diagnosis was seen using a combination of hormone and transcription factors. SF-1 had higher sensitivity, specificity, and predictive value compared with follicle-stimulating hormone and luteinizing hormone. On the other hand, TPIT and PIT1 had similar performance and Allred scores compared with their respective hormones.

CONCLUSIONS.—

SF-1 and PIT1 should be included in the routine panel for guiding the classification. PIT1 positivity needs to be followed by hormone immunohistochemistry, especially in nonfunctional cases. TPIT and adrenocorticotropin can be used interchangeably as per availability of the lab.

Pathogenesis, clinical features, and treatment of plurihormonal pituitary adenoma

Plurihormonal pituitary adenoma (PPA) is a type of pituitary tumor capable of producing two or more hormones and usually presents as an aggressive, large adenoma. As yet, its pathogenesis remains unclear. This is the first study to systematically summarize the underlying pathogenesis of PPA. The pathogenesis is related to plurihormonal primordial stem cells, co-transcription factors, hormone co-expression, differential gene expression, and cell transdifferentiation. We conducted a literature review of PPA and analyzed its clinical characteristics. We found that the average age of patients with PPA was approximately 40 years, and most showed only one clinical symptom. The most common manifestation was acromegaly. Currently, PPA is treated with surgical resection. However, recent studies suggest that immunotherapy may be a potentially effective treatment.

Digital image analysis allows objective stratification of patients with silent PIT1-lineage pituitary neuroendocrine tumors

Studies describing the clinical presentation and prognosis of patients with silent PIT1 (pituitary specific transcription factor)-lineage pituitary neuroendocrine tumors (PitNETs) are rare. We identified patients with positive PIT1 tumor staining but without evidence of hormone hypersecretion at a tertiary center. Clusters were obtained according to cell morphology and immunostaining from each patient's digitally segmented whole slide image. We compared the clinical presentations, radiological features, and prognoses of the different clusters. We identified 146 patients (68 male, 42.9 ± 14.1 years old) with silent PIT1-lineage PitNETs. Morphology clustering suggested that tumors with large nuclei and apparent eccentricity were associated with a higher proportion of aggressiveness and a higher hazard of recurrence [hazard ratio (HR): 2.64, (95% CI, 1.06-6.55), p = 0.037]. Immunohistochemical clustering suggested that tumors with thyroid stimulating hormone (TSH) staining or all negative PIT1-lineage hormones were associated with a higher proportion of aggressiveness and a higher risk of recurrence [HR: 12.4, (95% CI, 1.60-93.5), p = 0.015]. We obtained three-tier risk profiles by combining morphological and immunohistochemical clustering. Patients with the high-risk profile presented the highest recurrence rate compared with those in the medium-risk and low-risk profiles [HR: 3.54, (95% CI, 1.40-8.93), p = 0.002]. In conclusion, digital image analysis based on cell morphology and immunohistochemical staining allows objective stratification of patients with silent PIT1-lineage tumors. Typical morphological characteristics of high-risk tumors are large tumor nuclei and high eccentricity, and typical immunostaining characteristics are TSH staining or negative staining for all PIT1-lineage hormones.

Prognostic Factors for Recurrence in Pituitary Adenomas: Recent Progress and Future Directions

Pituitary adenomas (PAs) are benign lesions; nonetheless, some PAs exhibit aggressive behaviors, which lead to recurrence. The impact of pituitary dysfunction, invasion-related risks, and other complications considerably affect the quality of life of patients with recurrent PAs. Reliable prognostic factors are needed for recurrent PAs but require confirmation. This review summarizes research progress on two aspects—namely, the clinical and biological factors (biomarkers) for recurrent PAs. Postoperative residue, age, immunohistological subtypes, invasion, tumor size, hormone levels, and postoperative radiotherapy can predict the risk of recurrence in patients with PAs. Additionally, biomarkers such as Ki-67, p53, cadherin, pituitary tumor transforming gene, matrix metalloproteinase-9, epidermal growth factor receptor, fascin actin-bundling protein 1, cyclooxygenase-2, and some miRNAs and lncRNAs may be utilized as valuable tools for predicting PA recurrence. As no single marker can independently predict PA recurrence, we introduce an array of comprehensive models and grading methods, including multiple prognostic factors, to predict the prognosis of PAs, which have shown good effectiveness and would be beneficial for predicting PA recurrence.