Functionalized Silica Nanoparticles: Development of a Combined PET and TAT Theranostic Agent for NETs

Year: 2019
Institution: The University of Utah
Country: United States
State: UT
Award Type: Collaborative
NET Type: Multiple
Science Type: Basic

Description

Chan will use a model with a deleted MEN1 gene in the pancreas to study the early development of neuroendocrine cells and how they progress to tumor development. He and his team will study various cell populations in pancreatic NETs, the tumor’s microenvironment, and gene expression changes.

What question will the researchers try to answer?

Pancreatic neuroendocrine tumors (pNETs) are heterogeneous, with MEN1 being the most frequently mutated gene. However, it is not fully understood how the loss of MEN1 leads to tumor development, the tumor cell of origin, or the microenvironment of the tumor.

Why is this important?

Investigating single cells in pNETs will improve our understanding of tumor heterogeneity and the cells of origin. Understanding the gene expression changes that promote growth or development in pNETs will require comparing these tumors to their normal cell of origin.

What will researchers do?

Using an animal model in which MEN1 is deleted in the pancreas, they will use single-cell genomic technologies to study the changes in cell populations and their gene expressions in both early and late stages of pNET development, a process that is not otherwise possible to study in human cells. These findings will be compared to human pNETs that will also be investigated using single-cell approaches.

How might this improve the treatment of NETs?

The findings from this study will reveal the cell types in the pancreas that initiate tumor development, what gene expression changes may drive tumor development, and how the tumor microenvironment changes, which may help identify novel targets for the treatment of pNETs.

What is the next step?

The findings from this study will inform future research on how pNETs develop and may provide new biomarkers or target candidates for the diagnosis, prognosis, or treatment of pNETs.