Project title: Spatial transcriptomic profiling of the PanNET tumor microenvironment

Description

Dr. Heaphy, in collaboration with Dr. Ruben Dries (Boston Medical Center), will comprehensively profile PanNETs by integrating spatial transcriptomics with established biomarkers to accurately map these tumors and explore their biological underpinnings.

What critical NET problem/question will researchers try to answer?

While new biomarkers have been identified and validated, these biomarkers only capture the molecular alterations in the cancer cells. Spatial information in the tumor and tumor microenvironment, including the immune cell populations, are still not fully understood. 

Why is this important?

Integrative spatial transcriptomics profiling has the ability to capture patient heterogeneity and provide novel insights to better understand the biology.

What will the researchers do?

The team will uncover the underlying processes driving tumor initiation and progression in PanNETs, using innovative technologies, state-of-the-art research methodologies, and multidisciplinary collaborations between investigators with expertise in molecular cancer biology (Heaphy Lab) and implementation of novel technologies and computational approaches to view multi-cellular ecosystems (Dries Lab).

How might this improve treatment of NETs?

Profiling the tumor microenvironment may reveal the genetic, cellular, and structural components that create an immunosuppressive microenvironment that causes a lack of response to immuno-oncology therapies.

What is the next step?

Documenting the organization and crosstalk of the tumor microenvironment may lead to improved stratification and prediction of how patients might respond to treatment. For example, data from this project will serve as the foundation for improved biomarker stratification and identification of potential novel druggable targets within both the cancer and non-cancer segments of the tumor microenvironment.

Outcomes:

Pancreatic neuroendocrine tumors (PanNETs) are the second most common pancreatic malignancy and arise from the islets of Langerhans. Historically, the prevalence of patients with PanNETs has been low; however, with frequent use of abdominal imaging, the number of patients diagnosed with a PanNET has increased rapidly. The 5-year survival of patients with PanNETs is 54%, but is highly dependent on the presence of metastatic spread to distant organs. For example, patients with localized disease have a reported 5-year survival of 93% as compared to 27% for patients with metastatic disease. In addition, many patients develop infiltrative and widely metastatic neoplasms, while others may present with slow growing, indolent tumors. While new biomarkers have been identified and validated, these biomarkers only capture the molecular alterations in the cancer cells, while spatial information in the tumor and tumor microenvironment (TME), including the immune cell populations, are still not fully understood. Thus, we propose to comprehensively profile PanNETs by integrating spatial transcriptomics with established biomarkers to accurately map the molecularly-defined subgroups of PanNETs and explore their biological underpinnings. To accomplish this, we proposed two aims. In Aim 1, we will perform unbiased spatial transcriptomics profiling of archival PanNETs using the Visium platform from 10X Genomics. PanNETs are spatially characterized by complex cellular architectures and various interactions between cellular and environmental components. We will extract and model how these various spatial features contribute to the subtyping of PanNETs. We will systematically profile archival PanNETs and associate our findings with both histopathological features and clinical outcomes. In Aim 2, we will correlate the tumor and TME spatial transcriptomics profiles with established biomarkers (ALT by telomere-specific FISH and ATRX, DAXX, ARX, and PDX1 by immunohistochemistry) that previously known to identify unique PanNET subtypes. By integrating information from established biomarkers with unbiased spatial transcriptomic information, we will enhance PanNET subtype identification and reveal how specific signaling pathways and biological processes are spatially correlated. Thus, integrative spatial transcriptomics will reflect true patient heterogeneity and provide us with novel insights to better understand the biology and prognostic potential of our previously identified markers. Importantly, these studies may reveal potential novel druggable targets within both the cancer and non-cancer fraction of the TME.

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