Aldosterone-Regulating Receptors and Aldosterone-Driver Somatic Mutations.

Background: Somatic gene mutations that facilitate inappropriate intracellular calcium entrance have been identified in most aldosterone-producing adenomas (APAs). Studies suggest that angiotensin II and adrenocorticotropic hormone (ACTH) augment aldosterone production from APAs. Little is known, however, regarding possible variations in response to hormonal stimuli between APAs with different aldosterone-driver mutations. Objective: To analyze the transcript expression of type 1 angiotensin II receptors (AGTR1), ACTH receptors (MC2R), and melanocortin 2 receptor accessory protein (MRAP) in APAs with known aldosterone-driver somatic mutations. Methods: RNA was isolated from APAs with mutations in: KCNJ5 (n = 14), ATP1A1 (n = 14), CACNA1D (n = 14), and ATP2B3 (n = 5), and from normal adjacent adrenal tissue (n = 45). Transcript expression of MC2R, MRAP, AGTR1, aldosterone synthase (CYP11B2), 17α-hydroxylase/17,20-lyase (CYP17A1), and 11ß-hydroxylase (CYP11B1) were quantified using quantitative RT-PCR and normalized to ß-actin. Results: Compared to adjacent normal adrenal tissue, APAs had higher transcript levels of CYP11B2 (2,216.4 [1,112.0, 2,813.5]-fold, p < 0.001), MC2R (2.88 [2.00, 4.52]-fold, p < 0.001), and AGTR1 (1.80 [1.02, 2.80]-fold, p < 0.001]), and lower transcript levels of MRAP, CYP17A1, and CYP11B1 (0.28-0.36, p < 0.001 for all). MC2R and CYP11B2 transcripts were lower in APAs with KCNJ5 vs. other mutations (p < 0.01 for both). MC2R expression correlated positively with that of AGTR1 in APAs harboring KCNJ5 and CACNA1D mutations, and with MRAP expression in APAs harboring ATPase mutations. Conclusions: While MC2R and AGTR1 are expressed in all APAs, differences were observed based on the underlying aldosterone-driver somatic mutations. In tandem, our findings suggest that APAs with ATPase-mutations are more responsive to ACTH than KCNJ5-mutated APAs.

Targeted RNA sequencing of adrenal zones using immunohistochemistry-guided capture of formalin-fixed paraffin-embedded tissue.

Adequate access to fresh or frozen normal adrenal tissue has been a primary limitation to the enhanced characterization of the adrenal zones via RNA sequencing (RNAseq). Herein, we describe the application of targeted RNAseq to formalin-fixed paraffin-embedded (FFPE) normal adrenal gland specimens. Immunohistochemistry (IHC) was used to visualize and guide the capture of the adrenocortical zones and medulla. Following IHC-based tissue capture and isolation of RNA, high-throughput targeted RNAseq highlighted clear transcriptomic differences and identified differentially expressed genes among the adrenal zones. Our data demonstrate the ability to capture FFPE adrenal zone tissue for targeted transcriptomic analyses. Future comparison of normal adrenal zones will improve our understanding of transcriptomic patterns and help identify potential novel pathways controlling zone-specific steroid production.

Targeted RNAseq of Formalin-Fixed Paraffin-Embedded Tissue to Differentiate Among Benign and Malignant Adrenal Cortical Tumors.

Lack of routine fresh or frozen tissue is a barrier to widespread transcriptomic analysis of adrenal cortical tumors and an impediment to translational research in endocrinology and endocrine oncology. Our group has previously pioneered the use of targeted amplicon-based next-generation sequencing for archival formalin-fixed paraffin-embedded (FFPE) adrenal tissue specimens to characterize the spectrum of somatic mutations in various forms of primary aldosteronism. Herein, we developed and validated a novel 194-amplicon targeted next-generation RNA sequencing (RNAseq) assay for transcriptomic analysis of adrenal tumors using clinical-grade FFPE specimens. Targeted RNAseq-derived expression values for 27 adrenal cortical tumors, including aldosterone-producing adenomas (APA; n=8), cortisol-producing adenomas (CPA; n=11), and adrenal cortical carcinomas (ACC; n=8), highlighted known differentially-expressed genes (DEGs; i. e., CYP11B2, IGF2, etc.) and tumor type-specific transcriptional modules (i. e., high cell cycle/proliferation transcript expression in ACC, etc.), and a subset of DEGs was validated orthogonally using quantitative reverse transcription PCR (qRT-PCR). Finally, unsupervised hierarchical clustering using a subset of high-confidence DEGs revealed three discrete clusters representing APA, CPA, and ACC tumors with corresponding unique gene expression signatures, suggesting potential clinical utility for a transcriptomic-based approach to tumor classification. Overall, these data support the use of targeted amplicon-based RNAseq for comprehensive transcriptomic profiling of archival FFPE adrenal tumor material and indicate that this approach may facilitate important translational research opportunities for the study of these tumors.