Welcome to the latest research highlights from the Neuroendocrine Tumor Research Foundation (NETRF). In this blog post, we dive into two new research studies funded by NETRF that enhance our understanding of lung neuroendocrine tumors (NETs) and explore targeted therapies for cancer-associated fibroblasts (CAFs) as an innovative approach for neuroendocrine cancers that do not express somatostatin receptors.
Lung Neuroendocrine Tumors: Refining Classification and Prognosis
Lung NETs, which comprise approximately 2% of lung cancer cases, are classified by the World Health Organization (WHO) into different grades and types based on morphology or how the tumor cells look under the microscope. This includes low-grade or typical carcinoids (TCs) and intermediate-grade or atypical carcinoids (ACs). Particularly, ACs pose a significant challenge due to their more aggressive nature and higher propensity for metastasis and relapse within a decade post-surgery.
Recent NETRF-funded research by Matthieu Foll, PhD at the International Agency for Research on Cancer and his team was published in the journal ESMO Open. The study aims to refine the classification and prognostic predictions of lung NETs to ensure accurate diagnosis and appropriate follow-up, thus sparing patients from the anxiety and costs of unnecessary treatments. The WHO’s inclusion of mitotic figures and necrosis as criteria for distinguishing between TCs and ACs has been somewhat successful. Yet, the subjective nature of these criteria often leads to variability in diagnosis.
The researchers sought to test new markers to see if they improved the accuracy of lung NET diagnosis. This includes markers such as Ki-67, a known proliferation index used to classify other types of NETs, and phospho-histone H3 (PHH3), alongside innovative technologies like whole-slide image (WSI) deep learning analysis to learn if there were previously undiscovered morphological markers of diagnostic significance.
Despite these advances, this study revealed that Ki-67 and PHH3, while useful, do not eliminate the challenges in distinguishing more aggressive ACs from TCs based on morphology alone. The WSI deep learning models did not uncover any new diagnostic markers of value. This important study suggests that we may have reached the limits of what can be done with the diagnostic and prognostic value of morphological classification. Dr. Foll and his team suggest that incorporating molecular markers of disease, such as genetic mutations or gene expression, is essential to make future breakthroughs for improved diagnosis and personalized treatment approaches for patients with lung NETs.
The Promise of Targeted Radiotherapies: Innovations in Cancer-associated Fibroblast Imaging
Shifting focus to another promising area of neuroendocrine cancer research, we explore the development of novel diagnostic and therapeutic strategies targeting cancer-associated fibroblasts (CAFs). CAFs, integral to tumor growth and present in nearly all solid tumors, express the fibroblast activation protein (FAP). Targeting these proteins with radiolabeled inhibitors can allow for both precise imaging and effective treatment, constituting a ‘theranostic’ approach. Neuroendocrine cancer research needs new targets, such as FAP, since not all neuroendocrine cancers express somatostatin receptors, which are the commonly targeted receptors for therapies such as PRRT (e.g., Lutathera® ).
NETRF-funded researcher Benjamin Viglianti, MD, PhD of the University of Michigan, recently published work in the journal Pharmaceuticals outlining a breakthrough in this domain with the development of 18F-FAPI, a new FAP inhibitor linked to the radioisotope fluorine-18. The novelty of this new structure is that it simplifies the molecule by eliminating the traditional linker-chelator complex and directly links the inhibitor with the radioisotope. This reduces its molecular weight, potentially enhancing tumor uptake and imaging clarity. This advancement not only promises improved diagnostics but also paves the way for first-in-human trials, aiming to transform the landscape of targeted radiotherapy in neuroendocrine cancers.
Conclusion
NETRF remains committed to supporting research and meeting unmet needs in the diagnosis and treatment of neuroendocrine cancer. As we dive deeper into these diseases’ molecular underpinnings, we hope to develop more effective, personalized treatment regimens. Integrating morpho-molecular classifications and innovative diagnostic tools like 18F-FAPI represents the future of neuroendocrine cancer treatment, where personalized medicine can lead to better patient outcomes.
~Anna Greene, PhD
Director of Research