Assessing Biological Aggression in Adrenocortical Neoplasia

TERT Copy Number Alterations, Promoter Mutations and Rearrangements in Adrenocortical Carcinomas

Molecular characterization of adrenocortical carcinomas (ACC) by The Cancer Genome Atlas (TCGA) has highlighted a high prevalence of TERT alterations, which are associated with disease progression. Herein, 78 ACC were profiled using a combination of next generation sequencing (n = 76) and FISH (n = 9) to assess for TERT alterations. This data was combined with TCGA dataset (n = 91). A subset of borderline adrenocortical tumors (n = 5) and adrenocortical adenomas (n = 7) were also evaluated. The most common alteration involving the TERT gene involved gains/amplifications, seen in 22.2% (37/167) of cases. In contrast, "hotspot" promoter mutations (C > T promoter mutation at position -124, 7/167 cases, 4.2%) and promoter rearrangements (2/165, 1.2%) were rare. Recurrent co-alterations included 22q copy number losses seen in 24% (9/38) of cases. Although no significant differences were identified in cases with and without TERT alterations pertaining to age at presentation, tumor size, weight, laterality, mitotic index and Ki67 labeling, cases with TERT alterations showed worse outcomes. Metastatic behavior was seen in 70% (28/40) of cases with TERT alterations compared to 51.2% (65/127, p = 0.04) of cases that lacked these alterations. Two (of 5) borderline tumors showed amplifications and no TERT alterations were identified in 7 adenomas. In the borderline group, 0 (of 4) patients with available follow up had adverse outcomes. We found that TERT alterations in ACC predominantly involve gene amplifications, with a smaller subset harboring "hotspot" promoter mutations and rearrangements, and 70% of TERT-altered tumors are associated with metastases. Prospective studies are needed to validate the prognostic impact of these findings.

Immunohistochemical Biomarkers of Adrenal Cortical Neoplasms

Careful morphological evaluation forms the basis of the workup of an adrenal cortical neoplasm. However, the adoption of immunohistochemical biomarkers has added tremendous value to enhance diagnostic accuracy. The authors provide a brief review of immunohistochemical biomarkers that have been used in the confirmation of adrenal cortical origin and in the detection of the source of functional adrenal cortical proliferations, as well as diagnostic, predictive, and prognostic biomarkers of adrenal cortical carcinoma. In addition, a brief section on potential novel theranostic biomarkers in the prediction of treatment response to mitotane and other relevant chemotherapeutic agents is also provided. In the era of precision and personalized medical practice, adoption of combined morphology and immunohistochemistry provides a new approach to the diagnostic workup of adrenal cortical neoplasms, reflecting the evolution of clinical responsibility of pathologists.

An International Ki67 Reproducibility Study in Adrenal Cortical Carcinoma

Despite the established role of Ki67 labeling index in prognostic stratification of adrenocortical carcinomas and its recent integration into treatment flow charts, the reproducibility of the assessment method has not been determined. The aim of this study was to investigate interobserver variability among endocrine pathologists using a web-based virtual microscopy approach. Ki67-stained slides of 76 adrenocortical carcinomas were analyzed independently by 14 observers, each according to their method of preference including eyeballing, formal manual counting, and digital image analysis. The interobserver variation was statistically significant (P<0.001) in the absence of any correlation between the various methods. Subsequently, 61 static images were distributed among 15 observers who were instructed to follow a category-based scoring approach. Low levels of interobserver (F=6.99; Fcrit=1.70; P<0.001) as well as intraobserver concordance (n=11; Cohen κ ranging from -0.057 to 0.361) were detected. To improve harmonization of Ki67 analysis, we tested the utility of an open-source Galaxy virtual machine application, namely Automated Selection of Hotspots, in 61 virtual slides. The software-provided Ki67 values were validated by digital image analysis in identical images, displaying a strong correlation of 0.96 (P<0.0001) and dividing the cases into 3 classes (cutoffs of 0%-15%-30% and/or 0%-10%-20%) with significantly different overall survivals (P<0.05). We conclude that current practices in Ki67 scoring assessment vary greatly, and interobserver variation sets particular limitations to its clinical utility, especially around clinically relevant cutoff values. Novel digital microscopy-enabled methods could provide critical aid in reducing variation, increasing reproducibility, and improving reliability in the clinical setting.