Pituitary adenomas evade apoptosis via noxa deregulation in Cushing's disease

Spatial Transcriptomic Analysis of Pituitary Corticotroph Tumors

Context

Spatial transcriptomic (ST) analysis of tumors provides a novel approach to studying gene expression along with the localization of tumor cells in their environment to uncover spatial interactions.

Design

We present ST analysis of corticotroph pituitary neuroendocrine tumors (PitNETs) from formalin-fixed, paraffin-embedded tissues. ST data were compared to immunohistochemistry results. Gene expression profiles were reviewed for cluster annotations, and differentially expressed genes were used for pathway analysis.

Results

Seven tumors were used for ST analysis. In situ annotation of tumor tissue was inferred from the gene expression profiles and was in concordance with the annotation made by a pathologist. Furthermore, relative gene expression in the tumor corresponded to common protein staining used in the evaluation of PitNETs, such as reticulin and Ki-67 index. Finally, we identified intratumor heterogeneity; clusters within the same tumor may present with different transcriptomic profiles, unveiling potential intratumor cell variability.

Conclusion

Together, our results provide the first attempt to clarify the spatial cell profile in PitNETs.

Association between Intracellular Calcium Signaling and Tumor Recurrence in Human Non-Functioning Pituitary Adenomas

Clinically non-functioning pituitary adenomas (CNFPAs) are the second most frequent sellar tumor among studies on community-dwelling adults. They are characterized by the absence of hormonal hypersecretion syndrome, and patients present with compressive symptoms, such as a headache and visual field defects. Immunohistochemically, most CNFPAs are of gonadotrope differentiation, with only a few of them being truly null cell adenomas. Although these tumors express receptors for one or more hypothalamic releasing hormones, to what extent this has an impact on the biological and clinical behavior of these neoplasms remains to be defined. In this research, we evaluated the basal and hypothalamic secretagogue-stimulated intracellular calcium mobilization in 13 CNFPAs, trying to correlate this response to the phenotypic features of the patients. Our results indicate that the recurrence of a CNFPA correlates positively with cellular responsiveness, as measured by spontaneous intracellular calcium activity and the ability to respond to multiple hypothalamic secretagogues. We conclude that this finding may be a useful tool for predicting the clinicopathologic behavior of CNFPAs, by testing the variation of cellular responsiveness to hypothalamic secretagogues.

Spatial Transcriptomic Analysis of Pituitary Corticotroph Tumors Unveils Intratumor Heterogeneity

Spatial transcriptomic (ST) analysis of tumors provides a novel approach on studying gene expression along with the localization of tumor cells in their environment to uncover spatial interactions. Herein, we present ST analysis of corticotroph pituitary neuroendocrine tumors (PitNETs) from formalin-fixed, paraffin-embedded (FFPE) tissues. We report that the in situ annotation of tumor tissue can be inferred from the gene expression profiles and is in concordance with the annotation made by a pathologist. Furthermore, relative gene expression in the tumor corresponds to common protein staining used in the evaluation of PitNETs, such as reticulin and Ki-67 index. Finally, we identify intratumor heterogeneity; clusters within the same tumor may present with different secretory capacity and transcriptomic profiles, unveiling potential intratumor cell variability with possible therapeutic interest. Together, our results provide the first attempt to clarify the spatial cell profile in PitNETs.

Single-cell sequencing identifies differentiation-related markers for molecular classification and recurrence prediction of PitNET

Pituitary neuroendocrine tumor (PitNET) is one of the most common intracranial tumors with variable recurrence rate. Currently, the recurrence prediction is unsatisfying and can be improved by understanding the cellular origins and differentiation status. Here, to comprehensively reveal the origin of PitNET, we perform comparative analysis of single-cell RNA sequencing data from 3 anterior pituitary glands and 21 PitNETs. We identify distinct genes representing major subtypes of well and poorly differentiated PitNETs in each lineage. To further verify the predictive value of differentiation biomarkers, we include an independent cohort of 800 patients with an average follow-up of 7.2 years. In both PIT1 and TPIT lineages, poorly differentiated groups show significantly higher recurrence rates while well-differentiated groups show higher recurrence rates in SF1 lineage. Our findings reveal the possible origin and differentiation status of PitNET based on which new differentiation classification is proposed and verified to predict tumor recurrence.

Transcriptomic Profiles of Normal Pituitary Cells and Pituitary Neuroendocrine Tumor Cells

The pituitary gland is one of the most cellularly diverse regions of the brain. Recent advancements in transcriptomic biology, such as single-cell RNA sequencing, bring an unprecedented glimpse into the molecular composition of the pituitary, both in its normal physiological state and in disease. Deciphering the normal pituitary transcriptomic signatures provides a better insight into the ontological origin and development of five types of endocrine cells, a process involving complex cascades of transcription factors that are still being established. In parallel with these observations about normal pituitary development, recent transcriptomic findings on pituitary neuroendocrine tumors (PitNETs) demonstrate both preservations and changes in transcription factor expression patterns compared to those seen during gland development. Furthermore, recent studies also identify differentially expressed genes that drive various tumor behaviors, including hormone hypersecretion and tumor aggression. Understanding the comprehensive multiomic profiles of PitNETs is essential in developing molecular profile-based therapies for PitNETs not curable with current treatment modalities and could eventually help align PitNETs with the breakthroughs being made in applying precision medicine to other tumors.