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Genetically engineered mouse models of NF1 haploinsufficiency and NF1-associated lesions have
contributed significantly to our understanding of the cells of origin of certain tumors and to translational
research underpinning the development of MEK inhibitors for treating NF1-associated plexiform
neurofibromas [5,11-13] . Nevertheless, significant gaps persist in NF1 preclinical modeling, a view shared by
leading investigators in the field, due to challenges such as phenotypic variability, limited reproducibility,
and inconsistencies across laboratories regarding available expertise and experimental setups.

The recognition that genetically identical siblings may manifest different disease symptoms and have
different disease etiologies underscores the need for more information-rich models that link etiology and
symptoms to the underlying molecular pathophysiology. Consequently, there is a need for next-generation
models that enable quantitative evaluation of NF1 loss in specific cell lineages and their role in the
development of various NF1 manifestations. This could help determine appropriate time points and target
cell populations for intervention.

Recent advances in understanding the intracellular developmental programs that drive organ formation
from stem cells have enabled the growth of human tissue systems derived from patient biopsies or stem
cells [14-16] . These systems, known as “organoids”, uniquely recapitulate three-dimensional tissue architecture
and cell-cell interactions, which are often lost in traditional two-dimensional cultures or some animal
models. This feature is particularly valuable for studying NF1-associated cellular heterogeneity,
microenvironmental signaling, and the developmental dynamics of NF1-deficient cells. Organoid models
are suitable for gene editing, enabling the precise recreation of NF1 gene mutations specific to individual
patients [17-20] . The continued advances in the field of organoids can significantly enhance NF1 gene therapy
efforts, as they more accurately replicate the features of human NF1 disease, providing a more faithful
system to study NF1 biology. Additionally, organoids or “mini organs” offer a powerful platform for the
discovery and preclinical evaluation of gene therapy approaches and other new therapeutic strategies [21-23] .
We regard next-generation organoid systems as additions that can enrich the existing NF1 model repertoire
. While it is currently unclear whether organoids derived from patient biopsies will provide the
information-rich discovery system to better understand NF1 heterogeneity, the development of such
information-rich model systems closer to human physiology is critical for moving the NF1 gene therapy
field forward. While NF1 organoids are currently and may remain inadequate for studying behavioral
manifestations of the disorder, they may, over time, prove valuable for dissecting the molecular mechanisms
underlying NF1-related tumors and cognitive dysfunction. They could help clarify the network-level defects
resulting from diminished neurofibromin and ultimately serve as complementary, human-based platforms
for testing gene-delivery strategies and engineering specific cell fates in both the peripheral and central
nervous systems.

In September 2023, the Gilbert Family Foundation announced its commitment to build a bricks and mortar
research institute focused on finding improved treatments and cures for NF1. The institute, named the
“Nick Gilbert Neurofibromatosis Research Institute” or “NGNRI”, will serve as a central forum to unite
efforts across the community of NF1 researchers and patient initiatives and to further develop key enabling
[24]
technologies such as the organoid technologies previously mentioned .
Advancing novel NF1 therapeutic approaches
The majority of NF1 gene therapy research aims to develop gene- or RNA-based corrective therapies to
address the cellular disruptions caused by the loss of neurofibromin function across multiple body systems.
Realizing the potential of NF1 gene therapy requires addressing key gaps: determining optimal timing and
targets for therapy, developing robust assays, and improving preclinical models (as outlined in Sections 1