Project title: Developmental Lineages and Microenvironmental Heterogeneity in PNETs

Description

Hwang and his team will optimize two high-resolution techniques they developed to leverage single-nucleus RNA sequencing and digital spatial profiling data in order to gain novel insights into the diverse pathways by which pancreatic NETS develop, self-organize and respond to environmental stresses, including treatment.

What question will the researchers try to answer?

A clinically-relevant molecular classification for pancreatic NETs (pNETS) to predict patient outcomes and guide therapeutic decision-making has been elusive. The reason for this is, in part, because prior studies have primarily looked at the entire tumor in aggregate, leading to an unknown mixture of cancer cells, immune cells, and other components of connective tissue. By separately dissecting out the properties and behaviors of each cell type in the complex tumor ecosystem, as well as preserving the spatial relationships among different cell types, he will identify critical features, multicellular communities, and intercellular interactions that underlie specific molecular subtypes and mediate therapeutic resistance.

Why is this important?

Some pNETs secrete excess hormones and are termed “functional” whereas others do not and are referred to as “non-functional.” The clinical behavior of pNETs varies widely but approximately half of cases of pNETs progress to metastases and cancer-related death after surgery. Having a reliable way to predict and therapeutically target this clinical heterogeneity is therefore critical to improving patient outcomes.

What will researchers do?

Their team will optimize innovative technologies such as single-nucleus RNA sequencing and spatially-resolved proteotranscriptomics for pNETs and then apply them to a diverse cohort of tumors (e.g., primary vs. metastasis, functional vs. non-functional, treated vs. untreated).

How might this improve the treatment of NETs?

The insights gained from this study will provide a molecular blueprint to enhance prognosis and therapeutic strategies in pNETs, ultimately leading to improved clinical outcomes for patients. 

What is the next step?

This study will highlight the molecular features, multicellular communities, and intercellular interactions that underlie the poorest prognostic subtypes and treatment-resistant phenotypes in pNETs. Next steps include validating these specific findings through targeted panels applied to a large independent validation cohort as well as identifying key regulators of these critical subtypes/phenotypes and testing novel therapeutic strategies in preclinical models.

Outcomes:

Pancreatic neuroendocrine tumors (PNET) are a diverse group of malignancies derived from endocrine cells in the pancreatic islets. While most PNETs are considered indolent, about 35% of patients develop metastases; however, at present, there is no molecular basis of risk-stratifying and identifying patients likely to develop progressive disease and there are limited treatment options for patients with metastatic disease. Thus, we profiled the genes of tens of thousands of cells from 15 independent PNET tumors to take a closer look at the different types of malignant PNET cells and interactions between these cells and the microenvironment. From analyzing this data, we identified different types of malignant cells in PNET and the underlying regulatory proteins that may be driving these cell states. By correlating these different types of malignant cells with clinical outcomes in larger cohorts, we can identify genes expressed by malignant neuroendocrine cells that may drive tumor progression and potentially serve as therapeutic targets. Next, we identified a potential mechanism by which certain types of malignant cells interact with macrophages, a type of immune cell, via glutamate signaling to promote an immunosuppressive environment favorable to PNET growth and proliferation. Though previous studies have shown that intratumoral macrophages in PNETs are associated with worse clinical outcomes, our findings are the first to our knowledge to suggest a potential mechanism by which metabolism of glutamate both maintains an immunosuppressive environment by macrophages and promotes proliferation of malignant cells. By validating this signaling interaction, we may be able to develop therapeutics that modulate glutamate metabolism in macrophages to promote an antitumoral immune response against PNET. Ultimately, the goal of this pilot project was to determine features of malignant cells and the tumor microenvironment that promote tumor invasion and disease progression in PNET, with the goal of understanding molecular mechanisms of progression that can be targeted to prevent metastasis and improve clinical outcomes.

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