Comprehensive mapping of somatotroph pituitary neuroendocrine tumour heterogeneity using spatial and single‐cell transcriptomics

Abstract

Abstract Background Pituitary neuroendocrine tumours (PitNETs) are common intracranial tumours that are highly heterogeneous with unpredictable growth patterns. The driver genes and mechanisms that are crucial for tumour progression in somatotroph PitNETs are poorly understood. Methods In this study, we performed integrative spatial transcriptomics (ST) and single‐cell RNA sequencing (scRNA‐seq) analysis on somatotroph tumours and normal pituitary samples to comprehensively characterize the differences in cellular characteristics. Results By analyzing combined copy number variations (CNVs), tumour tissues were divided into two regions, which included the CNVhigh and CNVlow areas. The protumour genes DLK1 and RCN1 were highly expressed in the CNVhigh area, which might be related to tumour progression and could be targeted for precision therapy. We also found that the transforming growth factor beta signalling pathway participated in tumour progression and identified heterogeneity in the expression profiles of key genes. We assessed the intertumoral and intratumoral heterogeneity in somatotroph PitNETs and emphasized the importance of individualized treatment. Conclusion In summary, we visualized the cellular distribution and transcriptional differences in normal pituitary and somatotroph PitNETs by ST and scRNA‐seq for the first time. This study provides a strong theoretical foundation to comprehensively understand the crucial mechanisms involved in tumour progression and develop new strategies to treat somatotroph PitNETs. Key points The first‐ever visualization of cellular distributions in normal and tumor pituitary tissues. The inter‐ and intra‐tumoral transcriptomic heterogeneity of somatotroph PitNETs was comprehensively revealed. Identification of potential protumor factors and critical signaling pathways, opening new avenues for therapeutic intervention.

Keywords

• somatotroph PitNETs
• spatial transcriptomics
• single‐cell RNA sequencing
• tumour heterogeneity