The pituitary is the master gland of the endocrine system, which plays an important role in metabolic regulation, stress response, reproduction, and other physiological processes. It is mainly composed of five hormone cells including growth hormone (GH)-releasing cells (somatotrophs), prolactin (PRL)-releasing cells (lactotrophs), thyrotropin (TSH)-releasing cells (thyrotrophs), adrenocorticotropic hormone (ACTH)-releasing cells (corticotrophs) and gonadotropin (Gn)–releasing cells (gonadotrophs). Each cell type can form tumors, collectively called pituitary neuroendocrine tumors (PitNETs), also known as pituitary adenomas traditionally. PitNETs are the second most common intracranial tumors, accounting for about 10%~16% of intracranial tumors. Genomics studies have found that GNAS mutations affect 40-60% of somatotroph adenomas, and USP8 mutations affect 40-60% of corticotroph adenomas, while no gene mutations can be detected in 60% of PitNETs, which makes their tumor pathogenesis unknown.

 

Which genes are abnormally expressed in PitNET cells? This issue is not well solved by traditional bulk transcriptomics. This is because in normal pituitary tissues, five types of hormone cells are mixed with each other, and the bulk transcriptomics actually detects the ‘average’ of hormone cells. Due to the lack of normal controls, PitNET-related genes are not accurately identified. In addition, whether there is intratumoral cell heterogeneity in multihormonal and invasive PitNETs is unclear.

On April 28, 2021, Professor Fuchou Tang and Associate Research Scientist Lu Wen of Biomedical Pioneering Innovation Center (BIOPIC) of Peking University, in collaboration with Professor Dabiao Zhou of Neurosurgery Department of Beijing Tiantan Hospital, published an article entitled “ Single-cell Transcriptome and Genome Analyses of Pituitary Neuroendocrine Tumors ” online in Neuro-oncology . The study performed single-cell transcriptome sequencing on 23 pituitary tumor samples from 21 patients (2679 cells), and single-cell multi-omics sequencing (238 cells) on 5 of them (Figure 1), providing new insights into the above issues. The main findings of this research include:

Figure 1. Clinical information for pituitary tumor patients.

 

1) By unsupervised clustering of single-cell transcriptomes, this study distinguishes all of three pituitary tumor subtypes (Figure 2), which is consistent with the clinical diagnosis based on immunohistochemistry. Single-cell transcriptome sequencing also provides some interesting findings. For example, one tumor (P11) expresses both T-PIT (TBX19) and SF-1 (NR5A1), which are master transcription factors for corticotroph cells and gonadotroph cells respectively. The tumor cell cluster of P11 is embedded in the linear space between the T-PIT and the SF-1 lineage, which indicates that it is in an intermediate state between two subtypes. Another case (P14) is clinically diagnosed as a null-cell tumor, but clustered with gonadotroph tumor cells, suggesting that those tumor cells may origin from gonadotroph cells.

 

Figure 2. All tumor cells and their key transcription factors expression mapped in the principal component analysis (PCA) space.

 

2) The authors have characterized three types of normal pituitary hormone-releasing cells: somatotrophs, lactotrophs, and gonadotrophs, obtaining the single-cell transcriptome data of human adult pituitary hormone-releasing cells for the first time. Compared them with corresponding tumor cells, this study comprehensively identifies differentially expressed genes (DEGs) of somatotroph adenomas, gonadotroph adenomas, and prolactinomas versus normal controls (Figure 3A-D). The differentially expressed genes of somatotroph tumors are mainly up-regulated (76.1%, 283/372), while DEGs of gonadotroph tumors are predominantly down-regulated (84.3%, 542/643). The positive enrichment of secretion-related genes such as SCG3 in somatotroph tumors may be related with their hyperfunction of secretion. While the negative enrichment of hormone-releasing related genes in gonadotroph tumors including LHB and GNRHR reflects functional silence of this tumor subtype. Meanwhile, down-regulation of cell cycle related genes like CDKN2A points to mechanism of cell proliferation dysregulation of the tumors. It is noteworthy that many novel tumor-related genes are identified, e.g. AMIGO2, which is markedly upregulated in the somatotroph and gonadotroph tumors (Figure 3E).

Figure 3. (A-C) Differentially expressed genes of PitNETs versus normal controls in corresponding lineages, (D) and gene ontology enrichment analysis. (E) Expression levels of PitNET related genes among all patients.

 

3) In multihormonal PitNETs, single-cell transcriptome analyses show that multiple hormone-related genes and transcription factors are co-expressed in single cells. No clear intratumoral heterogeneity is found in most invasive tumors (Figure 4).

 

Figure 4. The expression of hormone-related genes in PIT-1 and multihormonal PitNETs at the single-cell level.

 

4) Single-cell multi-omics analysis shows that the copy number variations (CNV) pattern is generally similar among single cells in tumors even with genomic disruption, consistent with the notion of monoclonal origin of PitNETs (Figure 5A). On the other hand, the authors also identify slight intratumoral CNV heterogeneity, which may indicate slow tumor evolution (Figure 5B).

 

Figure 5. PitNET CNV patterns in the single-cell level for P20 (A) and P21 (B).

In conclusion, this study is the first to conduct a comprehensive analysis of PitNETs in the single-cell transcriptome and genome level, which analyzes the intertumoral and intratumoral heterogeneity, and identifies new tumor-related genes for PitNETs. It serves as an invaluable resource for the identification of diagnostic biomarkers and therapeutic targets for PitNETs.

 

Dr. Yueli Cui, doctoral candidate Zhenhuan Jiang, postdoctor Shu Zhang from Biomedical Pioneering Innovation Center of Peking University, and doctoral candidate Chao Li from Beijing Tiantan Hospital are the co-first authors of this article. Professor Fuchou Tang and Associate Research Scientist Lu Wen of Beijing Advanced Innovation Center for Genomics, Biomedical Pioneering Innovation Center, School of Life Sciences of Peking University, and Professor Dabiao Zhou of Neurosurgery Department of Beijing Tiantan Hospital are the co-corresponding authors. This research project was supported by the National Natural Science Foundation of China and the Beijing Advanced Innovation Center for Genomics.

 

Link： https://academic.oup.com/neuro-oncology/advance-article/doi/10.1093/neuonc/noab102/6256973