Preclinical Models of Neuroendocrine Neoplasia

GLP-1R agonist promotes proliferation of neuroendocrine neoplasm cells expressing GLP-1 receptors

OBJECTIVES

Semaglutide is a glucagon-like peptide 1 (GLP-1) analog that binds to GLP-1 receptors (GLP-1R) on beta-cells and neuronal cells and is used for treating type 2 diabetes and obesity. Insulin-secreting pancreatic neuroendocrine neoplasms have been reported to express high levels of GLP-1R protein, raising the possibility that GLP-1 receptor agonists could promote tumor growth. Our goal was to quantify GLP-1R expression levels in 6 neuroendocrine neoplasm cellular models and determine their proliferative response to semaglutide treatment.

METHODS

Gene expression of GLP-1R in neuroendocrine neoplasm cells (BON, GOT1, NT-3, NEC913, NEC1452, and NEC1583) was measured by quantitative polymerase chain reaction. Protein expression was determined by immunofluorescent staining and Western blotting. Neuroendocrine neoplasm cells were incubated with semaglutide, and cell growth was measured using a cell viability assay. Mice harboring GOT1 xenografts were treated with semaglutide, and tumor volumes were measured.

RESULTS

BON, NEC1452, and NEC1583 cells expressed significantly lower levels of GLP-1R transcript and protein than GOT1, NT-3, and NEC913 cells. GOT1 and NT-3 showed the highest response to semaglutide treatment, with a 19% and 22% increase in growth. Semaglutide promotes tumor growth in mice with GOT1 xenografts by 72%.

CONCLUSION

The impact of the GLP-1 receptor agonist semaglutide on neuroendocrine cancer growth is understudied. Our data revealed that 50% of neuroendocrine neoplasm cell lines tested expressed GLP-1R, and semaglutide treatment promoted their growth. These results indicate a potential risk in the use of semaglutide in patients with neuroendocrine neoplasms expressing GLP-1R. Investigations into a larger set of neuroendocrine neoplasms would be important because they are highly heterogeneous.

Improving neuroendocrine tumor treatments with mathematical modeling: lessons from other endocrine cancers

Neuroendocrine tumors (NETs) occur sporadically or as part of rare endocrine tumor syndromes (RETSs) such as multiple endocrine neoplasia 1 and von Hippel-Lindau syndromes. Due to their relative rarity and lack of model systems, NETs and RETSs are difficult to study, hindering advancements in therapeutic development. Causal or mechanistic mathematical modeling is widely deployed in disease areas such as breast and prostate cancers, aiding the understanding of observations and streamlining in vitro and in vivo modeling efforts. Mathematical modeling, while not yet widely utilized in NET research, offers an opportunity to accelerate NET research and therapy development. To illustrate this, we highlight examples of how mathematical modeling associated with more common endocrine cancers has been successfully used in the preclinical, translational and clinical settings. We also provide a scope of the limited work that has been done in NETs and map how these techniques can be utilized in NET research to address specific outstanding challenges in the field. Finally, we include practical details such as hardware and data requirements, present advantages and disadvantages of various mathematical modeling approaches and discuss challenges of using mathematical modeling. Through a cross-disciplinary approach, we believe that many currently difficult problems can be made more tractable by applying mathematical modeling and that the field of rare diseases in endocrine oncology is well poised to take advantage of these techniques.

NET Models Meeting 2024 white paper: the current state of neuroendocrine tumour research models and our future aspirations

Current models for the study of neuroendocrine tumours (NETs) are severely limited. While in vitro (e.g. cell lines), ex vivo (e.g. organoids) and in vivo (e.g. mice) models all exist, each has limitations. To address these limitations and collectively identify strategies to move the NET models field forward, we held an inaugural NET models meeting, hosted by our founding group: Dr Lines (Oxford), Prof. Quelle (Iowa), Dr Dayton (Barcelona), Dr Ear (Iowa), Dr Marinoni (Bern) and Dr Guenter (Alabama). This two-day meeting in Oxford (UK) was organised and supported by Bioscientifica Ltd and was solely dedicated to the discussion of NET models. The meeting was attended by ∼30 international researchers (from the UK, EU, Israel, USA and Canada). Plenary talks were given by Prof. Thakker, who summarised NET research over the past few decades, and Dr Schrader, who described the process and pitfalls of generating new cell lines. Eight researchers also presented their work on topics ranging from human cell 3D bioprinting to zebrafish models and included novel ideas and improvements on current concepts. This was followed by an interactive workshop, where discussion topics included a summary of currently available NET models, limitations of these models, barriers to developing new models, and how we can address these issues going forward. This white paper summarises the key points raised in these discussions and the future aspirations of the NET Models Consortium. The next meeting will take place in Oxford (UK) in 2025; contact contact@netcancerfoundation.com for more information.

Animal and Cell Culture Models of PPGLs - Achievements and Limitations

Research on rare tumors heavily relies on suitable models for basic and translational research. Paragangliomas (PPGL) are rare neuroendocrine tumors (NET), developing from adrenal (pheochromocytoma, PCC) or extra-adrenal (PGL) chromaffin cells, with an annual incidence of 2-8 cases per million. While most PPGL cases exhibit slow growth and are primarily treated with surgery, limited systemic treatment options are available for unresectable or metastatic tumors. Scarcity of appropriate models has hindered PPGL research, preventing the translation of omics knowledge into drug and therapy development. Human PPGL cell lines are not available, and few animal models accurately replicate the disease's genetic and phenotypic characteristics. This review provides an overview of laboratory models for PPGLs, spanning cellular, tissue, organ, and organism levels. We discuss their features, advantages, and potential contributions to diagnostics and therapeutics. Interestingly, it appears that in the PPGL field, disease models already successfully implemented in other cancers have not been fully explored.

Therapeutic Potential of P110 Peptide: New Insights into Treatment of Alzheimer's Disease

Mitochondrial degeneration in various neurodegenerative diseases, specifically in Alzheimer's disease, involves excessive mitochondrial fission and reduced fusion, leading to cell damage. P110 is a seven-amino acid peptide that restores mitochondrial dynamics by acting as an inhibitor of mitochondrial fission. However, the role of P110 as a neuroprotective agent in AD remains unclear. Therefore, we performed cell culture studies to evaluate the neuroprotective effect of P110 on amyloid-β accumulation and mitochondrial functioning. Human SH-SY5Y neuronal cells were incubated with 1 µM and 10 µM of P110, and Real-Time PCR and Western blot analysis were done to quantify the expression of genes pertaining to AD and neuronal health. Exposure of SH-SY5Y cells to P110 significantly increased APP mRNA levels at 1 µM, while BACE1 mRNA levels were increased at both 1 µM and 10 µM. However, protein levels of both APP and BACE1 were significantly reduced at 10 µM of P110. Further, P110 treatment significantly increased ADAM10 and Klotho protein levels at 10 µM. In addition, P110 exposure significantly increased active mitochondria and reduced ROS in live SH-SY5Y cells at both 1 µM and 10 µM concentrations. Taken together, our results indicate that P110 might be useful in attenuating amyloid-β generation and improving neuronal health by maintaining mitochondrial function in neurons.

PET/CT and Conventional Imaging for the Assessment of Neuroendocrine Prostate Cancer: A Systematic Review

BACKGROUND

Neuroendocrine prostate cancer (NEPC) is a rare neoplasm, and the role of both conventional imaging (CI) and positron emission tomography/computed tomography (PET/CT) for its assessment has not been clearly evaluated and demonstrated. The aim of this systematic review was to analyze the diagnostic performances of these imaging modalities in this setting.

METHODS

A wide literature search of the PubMed/MEDLINE, Scopus, and Web of Science databases was made to find relevant published articles about the role of CI and PET/CT for the evaluation of NEPC.

RESULTS

13 studies were included in the systematic review. PET/CT imaging with different radiopharmaceuticals has been evaluated in many studies (10) compared to CI (3 studies), which has only a limited role in NEPC. Focusing on PET/CT, a study used [18F]FDG, labeled somatostatin analogs were used in 5 cases, a study used [68Ga]Ga-FAPI-04, [68Ga]Ga-PSMA-11 was evaluated in a single case, and two works used different tracers.

CONCLUSION

Published data on the role of PET/CT for the assessment of NEPC are limited. At present, it is still uncertain which tracer performs best, and although [18F]FDG has been evaluated and seems to offer some advantages in availability and clinical staging, other tracers may be more useful to understand tumor biology or identify targets for subsequent radioligand therapy. Further research is therefore desirable. In contrast, data are still limited to draw a final conclusion on the role and the specific characteristics of CI in this rare form of neoplasm, and therefore, more studies are needed in this setting.

ATR inhibition augments the efficacy of lurbinectedin in small-cell lung cancer

Small-cell lung cancer (SCLC) is the most lethal type of lung cancer. Specifically, MYC-driven non-neuroendocrine SCLC is particularly resistant to standard therapies. Lurbinectedin was recently approved for the treatment of relapsed SCLC, but combinatorial approaches are needed to increase the depth and duration of responses to lurbinectedin. Using high-throughput screens, we found inhibitors of ataxia telangiectasia mutated and rad3 related (ATR) as the most effective agents for augmenting lurbinectedin efficacy. First-in-class ATR inhibitor berzosertib synergized with lurbinectedin in multiple SCLC cell lines, organoid, and in vivo models. Mechanistically, ATR inhibition abrogated S-phase arrest induced by lurbinectedin and forced cell cycle progression causing mitotic catastrophe and cell death. High CDKN1A/p21 expression was associated with decreased synergy due to G1 arrest, while increased levels of ERCC5/XPG were predictive of increased combination efficacy. Importantly, MYC-driven non-neuroendocrine tumors which are resistant to first-line therapies show reduced CDKN1A/p21 expression and increased ERCC5/XPG indicating they are primed for response to lurbinectedin-berzosertib combination. The combination is being assessed in a clinical trial NCT04802174.