Non-functioning gonadotroph (NFG) tumors are the most common type of non-functioning pituitary adenomas and can cause significant symptoms due to mass effect. However, the molecular programs underlying NFG tumor growth and their relationship to the normal anterior pituitary gland (APG) are poorly understood. To gain a deeper understanding of NFG tumor biology in the context of the normal APG, we performed single-cell/nucleus RNA-sequencing on 21 NFG tumors and 8 APG samples in human, generating the largest transcriptomic dataset of its kind. Single-cell/nucleus sequencing yielded 77,342, cells from APG samples and 152,649 cells from NFG tumor samples. Differential expression analysis within the APG identified novel marker genes of each neuroendocrine cell type and defined distinct transcriptional signatures of anterior and posterior pituitary stem cell populations. Comparison with tumor transcriptomes revealed that NFG tumor cells most closely resemble gonadotrophs, while also showing significant enrichment of thyrotroph and somatotroph markers. Notably, there was no significant overlap with stem cell markers, suggesting that NFG tumors most likely originate from differentiated gonadotrophs but can take on transcriptional characteristics of other neuroendocrine cell types. Pseudobulk profiling of NFG tumor cells demonstrated that tumor volume is significantly positively correlated with 83 genes including known oncogenes CAD, BRF2, and SOX12, along with 16 zinc finger transcription factors. Lastly, analysis of the tumor microenvironment revealed proportional increases in myeloid, endothelial, and mural cell populations in tumor samples compared to APG samples and highlighted cross talk between tumor and endothelial, mesenchymal, and immune populations via VEGF, PDGF, and MIF signaling pathways respectively. This study identifies novel transcriptomic signatures determining cell type identity in both APG neuroendocrine and NFG tumor cells. Our findings elucidate molecular programs driving NFG lineage infidelity and tumor growth, highlighting candidate predictors of patient outcomes and potential targets for therapeutic intervention.
Dennis, E., Kim, G. D., Zhou, Y., Pereira, C. A., Zhang, Q., Chang, Y. R., Zee, G. v. d., Mullem, I. v., Tsytsykova, A., Conner, E., Tieu, E., Soberman, R., Miller, K. K., Jones, P. S., Petti, A. A.
Advertisement
Stats
- Recommendations n/a n/a positive of 0 vote(s)
- Views 0
- Comments 0