Centromeric cohesion failure invokes a conserved choreography of chromosomal mis-segregations in pancreatic neuroendocrine tumor

Oncogenic pathway signatures predict the risk of progression and recurrence in well-differentiated pancreatic neuroendocrine tumors

BACKGROUND

Pancreatic neuroendocrine tumors (pNETs) are genomically diverse tumors. The management of newly diagnosed well-differentiated pNETs is limited by a lack of sensitivity of existing biomarkers for prognostication. Our goal was to investigate the potential utility of genetic markers as a predictor of progression-free survival (PFS) and recurrence-free survival (RFS).

METHODS

Whole-exome sequencing of resected well-differentiated, low and intermediate-grade (G1 and G2) pNETs and normal adjacent tissue from patients who underwent resection from 2005 to 2015 was performed. Genetic alterations were classified using pan-genomic and oncogenic pathway classifications. Additional samples with genetic and clinicopathologic data available were obtained from the publicly available International Cancer Genome Consortium (ICGC) database and included in the analysis. The prognostic relevance of these genomic signatures on PFS and RFS was analyzed.

RESULTS

Thirty-one patients who underwent resection for pNET were identified. Genomic analysis of mutational, copy number, cytogenetic, and complex phenomena revealed similar patterns to prior studies of pNETs with relatively few somatic gene mutations but numerous instances of copy number changes. Analysis of genomic and clinicopathologic outcomes using the combined data from our study as well as the ICGC pNET cohort (n = 124 patients) revealed that the recurrent pattern of whole chromosome loss (RPCL) and metastatic disease were independently associated with disease progression. When evaluating patients with local disease at the time of resection, RPCL and alterations in the TGFβ oncogenic pathway were independently associated with the risk of recurrence.

CONCLUSIONS

Well-differentiated pNETs are genomically diverse tumors. Pathway signatures may be prognostic for predicting disease progression and recurrence.

Well-differentiated G1 and G2 pancreatic neuroendocrine tumors: a meta-analysis of published expanded DNA sequencing data

Introduction

Well-differentiated pancreatic neuroendocrine tumors (PNETs) can be non-functional or functional, e.g. insulinoma and glucagonoma. The majority of PNETs are sporadic, but PNETs also occur in hereditary syndromes, primarily multiple endocrine neoplasia type 1 (MEN1). The Knudson hypothesis stated a second, somatic hit in MEN1 as the cause of PNETs of MEN1 syndrome. In the recent years, reports on genetic somatic events in both sporadic and hereditary PNETs have emerged, providing a basis for a more detailed molecular understanding of the pathophysiology. In this systematic review and meta-analysis, we made a collation and statistical analysis of aggregated frequent genetic alterations and potential driver events in human grade G1/G2 PNETs.

Methods

A systematic search was performed in concordance with the Preferred Reporting Items for Systematic Review and Meta-Analyses (PRISMA) reporting guidelines of 2020. A search in Pubmed for published studies using whole exome, whole genome, or targeted gene panel (+400 genes) sequencing of human G1/G2 PNETs was conducted at the 25th of September 2023. Fourteen datasets from published studies were included with data on 221 patients and 225 G1/G2 PNETs, which were divided into sporadic tumors, and hereditary tumors with pre-disposing germline variants, and tumors with unknown germline status. Further, non-functioning and functioning PNETs were distinguished into two groups for pathway evaluation. The collated genetical analyses were conducted using the 'maftools' R-package.

Results

Sporadic PNETs accounted 72.0% (162/225), hereditary PNETs 13.3% (30/225), unknown germline status 14.7% (33/225). The most frequently altered gene was MEN1, with somatic variants and copy number variations in overall 42% (95/225); hereditary PNETs (germline variations in MEN1, VHL, CHEK2, BRCA2, PTEN, CDKN1B, and/or MUTYH) 57% (16/30); sporadic PNETs 36% (58/162); unknown germline status 64% (21/33). The MEN1 point mutations/indels were distributed throughout MEN1. Overall, DAXX (16%, 37/225) and ATRX-variants (12%, 27/225) were also abundant with missense mutations clustered in mutational hotspots associated with histone binding, and translocase activity, respectively. DAXX mutations occurred more frequently in PNETs with MEN1 mutations, p<0.05. While functioning PNETs shared few variated genes, non-functioning PNETs had more recurrent variations in genes associated with the Phosphoinositide 3-kinase, Wnt, NOTCH, and Receptor Tyrosine Kinase-Ras signaling onco-pathways.

Discussion

The somatic genetic alterations in G1/G2 PNETs are diverse, but with distinct differences between sporadic vs. hereditary, and functional vs. non-functional PNETs. Increased understanding of the genetic alterations may lead to identification of more drivers and driver hotspots in the tumorigenesis in well-differentiated PNETs, potentially giving a basis for the identification of new drug targets. (Funded by Novo Nordisk Foundation, grant number NNF19OC0057915).

Multiregion WES of metastatic pancreatic neuroendocrine tumors revealed heterogeneity in genomic alterations, immune microenvironment and evolutionary patterns

Pancreatic neuroendocrine tumors (PanNETs), though uncommon, have a high likelihood of spreading to other body parts. Previously, the genetic diversity and evolutionary patterns in metastatic PanNETs were not well understood. To investigate this, we performed multiregion sampling whole-exome sequencing (MRS-WES) on samples from 10 patients who had not received prior treatment for metastatic PanNETs. This included 29 primary tumor samples, 31 lymph node metastases, and 15 liver metastases. We used the MSK-MET dataset for survival analysis and validation of our findings. Our research indicates that mutations in the MEN1/DAXX genes might trigger the early stages of PanNET development. We categorized the patients based on the presence (MEN1/DAXXmut, n = 7) or absence (MEN1/DAXXwild, n = 3) of these mutations. Notable differences were observed between the two groups in terms of genetic alterations and clinically relevant mutations, confirmed using the MSK-MET dataset. Notably, patients with mutations in MEN1/DAXX/ATRX genes had a significantly longer median overall survival compared to those without these mutations (median not reached vs. 43.63 months, p = 0.047). Multiplex immunohistochemistry (mIHC) analysis showed a more prominent immunosuppressive environment in metastatic tumors, especially in patients with MEN1/DAXX mutations. These findings imply that MEN1/DAXX mutations lead PanNETs through a unique evolutionary path. The disease's progression pattern indicates that PanNETs can spread early, even before clinical detection, highlighting the importance of identifying biomarkers related to metastasis to guide personalized treatment strategies.

DAXX promotes centromeric stability independently of ATRX by preventing the accumulation of R-loop-induced DNA double-stranded breaks

Maintaining chromatin integrity at the repetitive non-coding DNA sequences underlying centromeres is crucial to prevent replicative stress, DNA breaks and genomic instability. The concerted action of transcriptional repressors, chromatin remodelling complexes and epigenetic factors controls transcription and chromatin structure in these regions. The histone chaperone complex ATRX/DAXX is involved in the establishment and maintenance of centromeric chromatin through the deposition of the histone variant H3.3. ATRX and DAXX have also evolved mutually-independent functions in transcription and chromatin dynamics. Here, using paediatric glioma and pancreatic neuroendocrine tumor cell lines, we identify a novel ATRX-independent function for DAXX in promoting genome stability by preventing transcription-associated R-loop accumulation and DNA double-strand break formation at centromeres. This function of DAXX required its interaction with histone H3.3 but was independent of H3.3 deposition and did not reflect a role in the repression of centromeric transcription. DAXX depletion mobilized BRCA1 at centromeres, in line with BRCA1 role in counteracting centromeric R-loop accumulation. Our results provide novel insights into the mechanisms protecting the human genome from chromosomal instability, as well as potential perspectives in the treatment of cancers with DAXX alterations.

Alternative lengthening of telomeres: mechanism and the pathogenesis of cancer

Telomere maintenance and elongation allows cells to gain replicative immortality and evade cellular senescence during cancer development. While most cancers use telomerase to maintain telomere lengths, a subset of cancers engage the alternative lengthening of telomeres (ALT) pathway for telomere maintenance. ALT is present in 5%-10% of all cancers, although the prevalence is dramatically higher in certain cancer types, including complex karyotype sarcomas, isocitrate dehydrogenase-mutant astrocytoma (WHO grade II-IV), pancreatic neuroendocrine tumours, neuroblastoma and chromophobe hepatocellular carcinomas. ALT is maintained through a homology-directed DNA repair mechanism. Resembling break-induced replication, this aberrant process results in dramatic cell-to-cell telomere length heterogeneity, widespread chromosomal instability and chronic replication stress. Additionally, ALT-positive cancers frequently harbour inactivating mutations in either chromatin remodelling proteins (ATRX, DAXX and H3F3A) or DNA damage repair factors (SMARCAL1 and SLX4IP). ALT can readily be detected in tissue by assessing the presence of unique molecular characteristics, such as large ultrabright nuclear telomeric foci or partially single-stranded telomeric DNA circles (C-circles). Importantly, ALT has been validated as a robust diagnostic and prognostic biomarker for certain cancer types and may even be exploited as a therapeutic target via small molecular inhibitors and/or synthetic lethality approaches.

The Evolutionary History of Metastatic Pancreatic Neuroendocrine Tumours Reveals a Therapy Driven Route to High-Grade Transformation

Tumour evolution with acquisition of more aggressive disease characteristics is a hallmark of disseminated cancer. Metastatic pancreatic neuroendocrine tumours (PanNETs) in particular, show frequent progression from a low/intermediate to a high-grade disease. To understand the molecular mechanisms underlying this phenomenon, we performed multi-omics analysis of 32 longitudinal samples from six metastatic PanNET patients. Following MEN1 inactivation, PanNETs exhibit genetic heterogeneity on both spatial and temporal dimensions with parallel and convergent tumuor evolution involving the ATRX/DAXX and mTOR pathways. Following alkylating chemotherapy treatment, some PanNETs develop mismatch repair deficiency and acquire a hypermutator phenotype. This DNA hypermutation phenotype was only found in cases that also showed transformation into a high-grade PanNET. Overall, our findings contribute to broaden the understanding of metastatic PanNET, and suggests that therapy driven disease evolution is an important hallmark of this disease.

Identifying target ion channel-related genes to construct a diagnosis model for insulinoma

Background: Insulinoma is the most common functional pancreatic neuroendocrine tumor (PNET) with abnormal insulin hypersecretion. The etiopathogenesis of insulinoma remains indefinable. Based on multiple bioinformatics methods and machine learning algorithms, this study proposed exploring the molecular mechanism from ion channel-related genes to establish a genetic diagnosis model for insulinoma. Methods: The mRNA expression profile dataset of GSE73338 was applied to the analysis, which contains 17 insulinoma samples, 63 nonfunctional PNET (NFPNET) samples, and four normal islet samples. Differently expressed ion channel-related genes (DEICRGs) enrichment analyses were performed. We utilized the protein-protein interaction (PPI) analysis and machine learning of LASSO and support vector machine-recursive feature elimination (SVM-RFE) to identify the target genes. Based on these target genes, a nomogram diagnostic model was constructed and verified by a receiver operating characteristic (ROC) curve. Moreover, immune infiltration analysis, single-gene gene set enrichment analysis (GSEA), and gene set variation analysis (GSVA) were executed. Finally, a drug-gene interaction network was constructed. Results: We identified 29 DEICRGs, and enrichment analyses indicated they were primarily enriched in ion transport, cellular ion homeostasis, pancreatic secretion, and lysosome. Moreover, the PPI network and machine learning recognized three target genes (MCOLN1, ATP6V0E1, and ATP4A). Based on these target genes, we constructed an efficiently predictable diagnosis model for identifying insulinomas with a nomogram and validated it with the ROC curve (AUC = 0.801, 95% CI 0.674-0.898). Then, single-gene GSEA analysis revealed that these target genes had a significantly positive correlation with insulin secretion and lysosome. In contrast, the TGF-beta signaling pathway was negatively associated with them. Furthermore, statistically significant discrepancies in immune infiltration were revealed. Conclusion: We identified three ion channel-related genes and constructed an efficiently predictable diagnosis model to offer a novel approach for diagnosing insulinoma.

Prognostic and Predictive Biomarkers for Pancreatic Neuroendocrine Tumors

Pancreatic neuroendocrine tumors (PanNETs) represent a clinically challenging disease because these tumors vary in clinical presentation, natural history, and prognosis. Novel prognostic biomarkers are needed to improve patient stratification and treatment options. Several putative prognostic and/or predictive biomarkers (eg, alternative lengthening of telomeres, alpha-thalassemia/mental retardation, X-linked (ATRX)/Death Domain Associated Protein (DAXX) loss) have been independently validated. Additionally, recent transcriptomic and epigenetic studies focusing on endocrine differentiation have identified PanNET subtypes that display similarities to either α-cells or β-cells and differ in clinical outcomes. Thus, future prospective studies that incorporate genomic and epigenetic biomarkers are warranted and have translational potential for individualized therapeutic and surveillance strategies.

CENP-A is a potential prognostic biomarker and correlated with immune infiltration levels in glioma patients

Background: Centromeric protein A (CENP-A), an essential protein involved in chromosomal segregation during cell division, is associated with several cancer types. However, its role in gliomas remains unclear. This study examined the clinical and prognostic significance of CENP-A in gliomas.

Methods: Data of patients with glioma were collected from the Cancer Genome Atlas. Logistic regression, the Kruskal–Wallis test, and the Wilcoxon signed-rank test were performed to assess the relationship between CENP-A expression and clinicopathological parameters. The Cox regression model and Kaplan–Meier curve were used to analyze the association between CENP-A and survival outcomes. A prognostic nomogram was constructed based on Cox multivariate analysis. Gene set enrichment analysis (GSEA) was conducted to identify key CENP-A-related pathways and biological processes.

Results:CENP-A was upregulated in glioma samples. Increased CENP-A levels were significantly associated with the world health organization (WHO) grade [Odds ratio (OR) = 49.88 (23.52–129.06) for grade 4 vs. grades 2 and 3], primary therapy outcome [OR = 2.44 (1.64–3.68) for progressive disease (PD) and stable disease (SD) vs. partial response (PR) and complete response (CR)], isocitrate dehydrogenase (IDH) status [OR = 13.76 (9.25–20.96) for wild-type vs. mutant], 1p/19q co-deletion [OR = 5.91 (3.95–9.06) for no codeletion vs. co-deletion], and age [OR = 4.02 (2.68–6.18) for > 60 vs. ≤ 60]. Elevated CENP-A expression was correlated with shorter overall survival in both univariate [hazard ratio (HR): 5.422; 95% confidence interval (CI): 4.044–7.271; p < 0.001] and multivariate analyses (HR: 1.967; 95% CI: 1.280–3.025; p < 0.002). GSEA showed enrichment of numerous cell cycle-and tumor-related pathways in the CENP-A high expression phenotype. The calibration plot and C-index indicated the favorable performance of our nomogram for prognostic prediction in patients with glioma.

Conclusion: We propose a role for CENP-A in glioma progression and its potential as a biomarker for glioma diagnosis and prognosis.

Recurrent Loss of Heterozygosity in Pancreatic Neuroendocrine Tumors

Chromosomal aneuploidies are prognostic markers across a wide variety of tumor types, and recent literature suggests that pancreatic neuroendocrine tumors are no different. In this study 214 patients with grade 1, 2, or 3 pancreatic neuroendocrine tumors had their tissue examined for chromosomal copy number alterations using next-generation sequencing. Univariate and multivariate statistical analyses were performed with all-cause mortality and disease-specific mortality as the end comparators. As such, the cohort stratified into 3 different clinically relevant chromosomal subgroups: an indolent subgroup characterized by loss of chromosome 11 in relative isolation, an aggressive subgroup characterized by losses of chromosomes 1, 2, 3, 6, 10, 11, 16, and 22 and with no loss of chromosomes 4, 5, 7, 12, 14, 17, 19, and 20, and finally a heterogeneous third group with a subset of cases that behave even more aggressively than the aforementioned.

RSF1 in cancer: interactions and functions

RSF1, remodelling and spacing factor 1, is an important interphase centromere protein and is overexpressed in many types of cancers and correlated with poor overall survival. RSF1 has functions mainly in maintaining chromosome stability, facilitating DNA repair, maintaining the protein homeostasis of RSF1 and suppressing the transcription of some oncogenes when RSF1 protein is expressed at an optimal level; however, RSF1 overexpression facilitates drug resistance and cell cycle checkpoint inhibition to prompt cancer proliferation and survival. The RSF1 expression level and gene background are crucial for RSF1 functions, which may explain why RSF1 has different functions in different cancer types. This review summarizes the functional domains of RSF1, the overexpression status of RSF1 and SNF2H in cancer based on the TCGA and GTE_X databases, the cancer-related functions of RSF1 in interacting with H2Aub, HDAC1, CENP-A, PLK1, ATM, CENP-S, SNF2H, HB_X, BubR1, cyclin E1, CBP and NF-κB and the potential clinical value of RSF1, which will lay a theoretical foundation for the structural biology study of RSF1 and application of RSF1 inhibitors, truncated RSF1 proteins and SNF2H inhibitors in the treatment of RSF1-overexpressing tumours.