Modeling neurofibromatosis-1 disease heterogeneity to optimize risk assessment and treatment - Project Summary As we envision employing personalized approaches in medical practice, it is important to define the genomic, cellular, and molecular etiologies that underlie disease pathogenesis and determine how these determinants are modified by intrinsic and extrinsic influences (risk factors). This challenge is nicely illustrated by Neurofibromatosis type 1 (NF1), a rare neurogenetic condition caused by germline mutations in the NF1 gene. The hallmark of NF1 is extreme clinical heterogeneity, where children are prone to the development of a wide variety of neurological problems, including cognitive and behavioral problems (neurodevelopmental deficits; NDDs) and low-grade brain tumors (low-grade gliomas; LGGs). While making the diagnosis of NF1 in a child is usually straightforward, it is currently not possible to predict what medical problems will develop in any given child, how their disease will progress, and what therapies will be most effective. Moreover, our current therapies are effective for only a subset of patients, exhibit variable non-sustained responses, and sometimes result in accelerated growth following treatment cessation. We theorize that these disappointing outcomes reflect the use of a reductionist approach, in which a single cell type (e.g., neuron, cancer cell) or signaling pathway (e.g., MEK or mTOR activation) is targeted, largely ignoring the fact that these medical features result from the interactions of numerous distinct cell types (e.g., tumor cells, neurons, T cells, microglia) each with unique signaling pathway dependencies and tissue-level cellular and molecular interdependencies. Based on observations made possible by the flexibility of our prior R35 Research Program Award (RPA), we now hypothesize that these medical problems should be conceptualized as systems biology abnormalities in which risk factors (disease modifiers) converge on the specific multicellular circuits that drive and maintain these clinical phenotypes. For this new RPA, we propose to deploy a more holistic and integrated approach to elucidate the multicellular circuits that underlie the development and progression of NF1-associated LGG and NDD, the two most common nervous system problems in children with NF1. Leveraging patient-derived and CRISPR-engineered human iPSCs, patient-derived primary LGG cell lines, mice with patient-derived germline NF1 gene mutations, cell type-specific Nf1 conditional knockout strains, and multi-omic bioinformatic analysis approaches, we aim to (1) mechanistically define the cellular and molecular interdependences that underlie NF1 LGG and NDD pathobiology and (2) determine how these multicellular circuits are modified by risk factors to create the clinical heterogeneity that characterizes NF1. The overall mission of this project is to establish the etiologic bases for NF1 clinical variability and create a blueprint for other similar neurogenetic disorders affecting children and adults.
