Single-cell transcriptome and genome analyses of pituitary neuroendocrine tumors.
Ontology highlight
ABSTRACT: Background
Pituitary neuroendocrine tumors (PitNETs) are the second most common intracranial tumor. We lacked a comprehensive understanding of the pathogenesis and heterogeneity of these tumors.Methods
We performed high-precision single-cell RNA sequencing for 2,679 individual cells obtained from 23 surgically resected samples of the major subtypes of PitNETs from 21 patients. We also performed single-cell multi-omics sequencing for 238 cells from 5 patients.Results
Unsupervised clustering analysis distinguished all tumor subtypes, which was in accordance with the classification based on immunohistochemistry and provided additional information. We identified three normal endocrine cell types: somatotrophs, lactotrophs and gonadotrophs. Comparisons of tumor and matched normal cells showed that differentially expressed genes of gonadotroph tumors were predominantly downregulated, while those of somatotroph and lactrotroph tumors were mainly upregulated. We identified novel tumor-related genes, such as AMIGO2, ZFP36, BTG1 and DLG5. Tumors expressing multiple hormone genes showed little transcriptomic heterogeneity. Furthermore, single-cell multi-omics analysis demonstrated that the tumor shad a relatively uniform pattern of genome with slight heterogeneity in copy number variations.Conclusions
Our single-cell transcriptome and single-cell multi-omics analyses provide novel insights into the characteristics and heterogeneity of these complex neoplasms for the identification of biomarkers and therapeutic targets.
SUBMITTER: Cui Y
PROVIDER: S-EPMC8563320 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Abstract Neuroendocrine tumors (NETs) comprise a group of complex heterogeneous and increasingly prevalent neoplasms. They arise from diverse body regions, share derivation from primitive neuronal stem cells, secrete various bioactive peptides and exhibit a wide spectrum of tumor behavior from relatively indolent to rapidly progressive. Pituitary tumors represent 20% of intracranial tumors and share some features of NET histo-pathologic morphology, their excess hormone production and some have proposed re-naming pituitary tumors as PitNETs. However there has been no precise cell type composition comparison at the whole genome level in these two types of tumors. To explore intratumoral heterogeneity at a single cell resolution in pituitary and pancreatic NETs, we employed single cell RNA sequencing (scRNA-seq) to analyze in parallel cell populations from surgically resected pituitary tumors (n=4) and pancreatic NETs (pNET, n=2) using a 10x Genomics platform (v3). Using Cell Ranger pipeline for alignment and mapping, we obtained an average of 8,306±2,519 cells/sample with 1,516±822 genes/cell (mean reads/cell 67.9±30K). Seurat v3 was then used for read pre-filtering, normalization, and cluster identification. We identified 5 genes commonly expressed in both pNET and pituitary tumor populations, namely CALY (clathrin light chain binding GO:0032051), SPINT (peptidase inhibitor activity GO:0030414), CHGB (hormone activity GO:0005179), SCG5 (GTP binding GO:0005525) and SEZ6L2. As proof of their oral epidermal embryonic origin, the commonly expressed genes in 4 pituitary tumor samples include pituitary tissue restricted transcription factors (POU1F1, BEX1/2 GO:0033613), GNAS (G-protein beta/gamma-subunit complex binding GO:0031683), NLRP1 (peptidase activator activity involved in apoptotic process GO:0016505), PTN (protein phosphatase regulator activity GO:0019888) and ATP6V1G1 (ATPase binding GO:0051117). In parallel, 71 genes were present at high levels in pNET and involved in molecular functions such as calcium ion binding (HSPA5; ENPP2; C2CD4B; CALR; HSP90B1 GO:0005509) and endopeptidase inhibitor activity (PCSK1N; WFDC2 GO:0004866). Although our exploratory findings are limited to 6 samples, the robust commonly expressed genes within each tumor type clearly separated pituitary and pancreatic neuroendocrine tumors into distinct entities. We did observe conservation of chromogranins and prohormone convertases in these two tumor types, but it only represented a very small portion of overlap in transcriptome in pNETs. In summary, our findings suggest that pituitary and neuroendocrine tumors have only limited common molecular features, and by and large they stand as separate biologic populations. Our observations may begin to provide insight into the differences in tumor progression that are encountered clinically between pituitary tumors and pancreatic NETs.
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Project description:Pituitary neuroendocrine tumors (PitNETs) are common, generally benign tumors with complex clinical characteristics related to hormone hypersecretion and/or growing sellar tumor mass. PitNETs can be classified based on the expression pattern of anterior pituitary hormones and three main transcriptions factors (TF), SF1, PIT1 and TPIT that regulate differentiation of adenohypophysial cells. Here, we have extended this classification based on the global transcriptomics landscape using tumor tissue from a well-defined cohort comprising 51 PitNETs of different clinical and histological types. The molecular profiles were compared with current classification schemes based on immunohistochemistry. Our results identified three main clusters of PitNETs that were aligned with the main pituitary TFs expression patterns. Our analyses enabled further identification of specific genes and expression patterns, including both known and unknown genes, that could distinguish the three different classes of PitNETs. We conclude that the current classification of PitNETs based on the expression of SF1, PIT1 and TPIT reflects three distinct subtypes of PitNETs with different underlying biology and partly independent from the expression of corresponding hormones. The transcriptomic analysis reveals several potentially targetable tumor-driving genes with previously unknown role in pituitary tumorigenesis.
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Project description:BackgroundPituitary neuroendocrine tumors (PitNETs) are one of the most common types of intracranial tumors. Currently, the cellular characteristics of normal pituitary and various other types of PitNETs are still not completely understood.MethodsWe performed single-cell RNA sequencing (scRNA-seq) on 4 normal samples and 24 PitNET samples for comprehensive bioinformatics analysis. Findings regarding the function of PBK in the aggressive tumor cells were validated by siRNA knockdown, overexpression, and transwell experiments.ResultsWe first constructed a reference cell atlas of the human pituitary. Subsequent scRNA-seq analysis of PitNET samples, representing major tumor subtypes, shed light on the intrinsic cellular heterogeneities of the tumor cells and tumor microenvironment (TME). We found that the expression of hormone-encoding genes defined the major variations of the PIT1-lineage tumor cell transcriptomic heterogeneities. A sub-population of TPIT-lineage tumor cells highly expressing GZMK suggested a novel subtype of corticotroph tumors. In immune cells, we found two clusters of tumor-associated macrophages, which were both highly enriched in PitNETs but with distinct functional characteristics. In PitNETs, the stress response pathway was significantly activated in T cells. While a majority of these tumors are benign, our study unveils a common existence of aggressive tumor cells in the studied samples, which highly express a set of malignant signature genes. The following functional experiments confirmed the oncogenic role of selected up-regulated genes. The over-expression of PBK could promote both tumor cell proliferation and migration, and it was also significantly associated with poor prognosis in PitNET patients.ConclusionsOur data and analysis manifested the basic cell types in the normal pituitary and inherent heterogeneity of PitNETs, identified several features of the tumor immune microenvironments, and found a novel epithelial cell sub-population with aggressive signatures across all the studied cases.
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Project description:Background and aimAbout a third of Pituitary Neuroendocrine Tumors (PitNETs) may show aggressive behavior. Many efforts have been performed for identifying possible predictive factors to early determine the future behavior of PitNETs. Programmed cell death ligand 1 (PD-L1) expression was associated with a more aggressive biology in different solid tumors, but its role in PitNET is not well-established yet. Our study aims to analyze PD-L1 expression in a surgical cohort of PitNETs to determine its association with radiological invasion and pathology findings, as well as with long-term recurrence rates.MethodsWe performed a retrospective analysis in a series of 86 PitNETs. Clinical presentation and radiological features of the preoperative period were collected, as well as pathological data and follow-up data. The rate of PD-L1 expression was immunohistochemically evaluated and expressed as a tumor proportion score (TPS). We assessed its relationship with cavernous sinus invasion and Trouillas' classification as primary outcomes. Secondary outcomes included the TPS' relationship with histopathological markers of proliferation, hormonal expression, tumor size and long-term recurrence rates. We calculated the optimal cut-point for the primary outcomes while maximizing the product of the sensitivity and specificity and then we evaluated the significance of secondary outcomes with logistic regression analysis.ResultsEighty-six patients were included in the analysis; 50 cases were non-functional PitNETs. The TPS for PD-L1 showed a highly right-skewed distribution in our sample, as 30.2% of patients scored 0. Using Trouillas' classification, we found that "proliferative" cases have a significantly higher probability to express PD-L1 in more than 30% of tumor cells (OR: 5.78; CI 95%: 1.80-18.4). This same cut-point was also associated with p53 expression. A positive association was found between PD-L1 expression and GH expression (p = 0.001; OR: 5.44; CI 95%: 1.98-14.98), while an inverse relationship was found with FSH/LH expression (p = 0.014; OR = 0.27, CI 95%: 0.10-0.76). No association was found with CS invasion, tumor size, bone erosion or dura invasion. We could not find any association between PD-L1 expression and recurrence.ConclusionsPD-L1 expression was associated with proliferative grades of Trouillas' classification and p53 expression. We also confirmed a higher expression of PD-L1 in somatotroph tumors. Larger studies are necessary to investigate the relationship between PD-L1 expression and aggressive behaviors.
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Project description:The most common genetic drivers of pituitary neuroendocrine tumors (PitNETs) lie within mutational hotspots, which are genomic regions where variants tend to cluster. Some of these hotspot defects are unique to PitNETs, while others are associated with additional neoplasms. Hotspot variants in GNAS and USP8 are the most common genetic causes of acromegaly and Cushing's disease, respectively. Although it has been proposed that these genetic defects could define specific clinical phenotypes, results are highly variable among studies. In contrast, DICER1 hotspot variants are associated with a familial syndrome of cancer predisposition, and only exceptionally occur as somatic changes. A small number of non-USP8-driven corticotropinomas are due to somatic hotspot variants in USP48 or BRAF; the latter is a well-known mutational hotspot in cancer. Finally, somatic variants affecting a hotspot in SF3B1 have been associated with multiple cancers and, more recently, with prolactinomas. Since the associations of BRAF, USP48, and SF3B1 hotspot variants with PitNETs are very recent, their effects on clinical phenotypes are still unknown. Further research is required to fully define the role of these genetic defects as disease biomarkers and therapeutic targets.
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Project description:IntroductionAngiotensin-converting enzyme 2 (ACE2) is the receptor of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The effects of SARS-CoV-2 on normal pituitary glands function or pituitary neuroendocrine tumors (PitNETs) have not yet been elucidated. Thus, the present study aimed to investigate the potential risks of SARS-CoV-2 infection on the impairment of pituitary glands and the development of PitNETs.MethodsPitNETs tissues were obtained from 114 patients, and normal pituitary gland tissues were obtained from the autopsy. The mRNA levels of ACE2 and angiotensin II receptor type 1 (AGTR1) were examined by quantitative real-time PCR. Immunohistochemical staining was performed for ACE2 in 69 PitNETs and 3 normal pituitary glands. The primary tumor cells and pituitary cell lines (MMQ, GH3 and AtT-20/D16v-F2) were treated with diminazene aceturate (DIZE), an ACE2 agonist, with various dose regimens. The pituitary hormones between 43 patients with SARS-CoV-2 infection were compared with 45 healthy controls.ResultsPituitary glands and the majority of PitNET tissues showed low/negative ACE2 expression at both the mRNA and protein levels, while AGTR1 showed high expression in normal pituitary and corticotroph adenomas. ACE2 agonist increased the secretion of ACTH in AtT-20/D16v-F2 cells through downregulating AGTR1. The level of serum adrenocorticotropic hormone (ACTH) was significantly increased in COVID-19 patients compared to normal controls (p < 0.001), but was dramatically decreased in critical cases compared to non-critical patients (p = 0.003).ConclusionsThis study revealed a potential impact of SARS-CoV-2 infection on corticotroph cells and adenomas.
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Project description:The purpose of this study was to analyze the impact of copy number variations (CNV) on sporadic pituitary neuroendocrine tumors (PitNETs) prognosis, to identify specific prognosis markers according to the known clinico-pathological classification. CGH array analysis was performed on 195 fresh-frozen PitNETs (56 gonadotroph, 11 immunonegative, 56 somatotroph, 39 lactotroph and 33 corticotroph), with 5 years post-surgery follow-up (124 recurrences), classified according to the five-tiered grading classification (invasion, Ki-67, mitotic index and p53 positivity). Effect of alterations on recurrence was studied using logistic regression models. Transcriptomic analysis of 32 lactotroph tumors was performed. The quantity of CNV was dependent on tumor type: higher in lactotroph (median(min-max) = 38% (0-97) of probes) compared to corticotroph (11% (0-77)), somatotroph (5% (0-99)), gonadotroph (0% (0-10)) and immunonegative tumors (0% (0-17). It was not predictive of recurrence in the whole cohort. In lactotroph tumors, genome instability, especially quantity of gains, significantly predicted recurrence independently of invasion and proliferation (p-value = 0.02, OR = 1.2). However, no specific CNV was found as a prognostic marker. Transcriptomic analysis of the genes included in the CNV and associated with prognosis didn't show significantly overrepresented pathway. In somatotroph and corticotroph tumors, USP8 and GNAS mutations were not associated with genome disruption or recurrence respectively. To conclude, CGH array analysis showed genome instability was dependent on PitNET type. Lactotroph tumors were highly altered and the quantity of altered genome was associated with poorer prognosis though the mechanism is unclear, whereas gonadotroph and immunonegative tumors showed the same 'quiet' profile, leaving the mechanism underlying tumorigenesis open to question.
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Project description:Adenohypophyseal tumors, which were recently renamed pituitary neuroendocrine tumors (PitNET), are mostly benign, but may present various behaviors: invasive, "aggressive" and malignant with metastases. They are classified into seven morphofunctional types and three lineages: lactotroph, somatotroph and thyrotroph (PIT1 lineage), corticotroph (TPIT lineage) or gonadotroph (SF1 lineage), null cell or immunonegative tumor and plurihormonal tumors. The WHO 2017 classification suggested that subtypes, such as male lactotroph, silent corticotroph and Crooke cell, sparsely granulated somatotroph, and silent plurihormonal PIT1 positive tumors, should be considered as "high risk" tumors. However, the prognostic impact of these subtypes and of each morphologic type remains controversial. In contrast, the French five-tiered classification, taking into account the invasion, the immuno-histochemical (IHC) type, and the proliferative markers (Ki-67 index, mitotic count, p53 positivity), has a prognostic value validated by statistical analysis in 4 independent cohorts. A standardized report for the diagnosis of pituitary tumors, integrating all these parameters, has been proposed by the European Pituitary Pathology Group (EPPG). In 2020, the pituitary pathologist must be considered as a member of the multidisciplinary pituitary team. The pathological diagnosis may help the clinician to adapt the post-operative management, including appropriate follow-up and early recognition and treatment of potentially aggressive forms.
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Project description:Somatic genetic alterations in pituitary neuroendocrine tumors (PitNET) tissues have been identified in several studies, but detection of overlapping somatic PitNET candidate genes is rare. We sequenced and by employing multiple data analysis methods studied the exomes of 15 PitNET patients to improve discovery of novel factors involved in PitNET development. PitNET patients were recruited to the study before PitNET removal surgery. For each patient, two samples for DNA extraction were acquired: venous blood and PitNET tissue. Exome sequencing was performed using Illumina NexSeq 500 sequencer and data analyzed using two separate workflows and variant calling algorithms: GATK and Strelka2. A combination of two data analysis pipelines discovered 144 PitNET specific somatic variants (mean = 9.6, range 0-19 per PitNET) of which all were SNVs. Also, we detected previously known GNAS PitNET mutation and identified somatic variants in 11 genes, which have contained somatic variants in previous WES and WGS studies of PitNETs. Noteworthy, this is the third study detecting somatic variants in gene RYR1 in the exomes of PitNETs. In conclusion, we have identified two novel PitNET candidate genes (AC002519.6 and AHNAK) with recurrent somatic variants in our PitNET cohort and found 13 genes overlapping from previous PitNET studies that contain somatic variants. Our study demonstrated that the use of multiple sequencing data analysis pipelines can provide more accurate identification of somatic variants in PitNETs.
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