# Rational optimization of combinatorial therapies for the treatment of rare cystic fibrosis variants

> **NIH NIH R01** · PURDUE UNIVERSITY · 2024 · $678,226

## Abstract

Abstract
Cystic fibrosis (CF) is a lethal genetic disease that currently affects ~100,000 people worldwide. CF is caused
by a spectrum of loss-of-function mutations that compromise the biogenesis and/ or function of the cystic fibrosis
transmembrane conductance regulator (CFTR) ion channel, most of which enhance its misfolding and
degradation. Recent drug discovery efforts have yielded a suite of approved small molecule “correctors” that
enhance the expression of misfolded CFTR variants and “potentiators” that restore conductance to CFTR
variants with defective gating. Combinations of these molecules have recently revolutionized the treatment of
the ~90% of CF patients bearing at least one copy of the well-studied ΔF508 CFTR variant, which is highly
penetrant among Caucasians. However, the efficacy of current combinatorial therapies varies widely among the
~10% of patients bearing diverse combinations of rare, uncharacterized CF variants with divergent
pharmacological properties (“theratype”). Efforts to expand the labels of current therapeutics and maximize the
number of treatable CF genotypes, in particular amongst non-white populations, are constrained by the large
number of CF variants and the limited throughput of current methods. Identifying rare CF variants that respond
to therapeutic cocktails is likely to become even more challenging as new correctors and/ or potentiators gain
approval. Addressing this challenge requires new techniques that enable efficient biochemical and/ or
pharmacological profiling of rare CF variants. In the following, we propose to address this challenge with a unique
fusion of emerging genetic, biochemical, and computational methods. We show how deep mutational scanning
(DMS) can be used to compare the effects of correctors on the expression of hundreds of variants in parallel.
Our preliminary findings provide an unprecedented glimpse of the divergent theratypes of CF variants while
identifying numerous variants with unique biochemical and/ or pharmacological properties. We first propose to
expand on these investigations in order to measure the response of the complete set of CFTR2 missense
variants to a panel of structurally diverse corrector molecules. We will then characterize the interactomes of
variants with distinct corrector responses to identify CFTR interactions that antagonize the effects of these small
molecules. We will then fuse CRISPR/ Cas9 technology with DMS to determine how these interactions impact
the spectrum of CF variant theratypes. Using state-of-the-art structural modeling approaches, we will then
identify structural defects in the CFTR protein that are associated with the formation of antagonistic interactions
and deviations in CFTR variant theratype. We will then utilize machine learning to classify CF variants based on
their observed pharmacological properties. Finally, we will assess the effects of approved correctors on the
functional properties of previously uncharacterized variants u...

## Key facts

- **NIH application ID:** 10913607
- **Project number:** 5R01HL167046-02
- **Recipient organization:** PURDUE UNIVERSITY
- **Principal Investigator:** Lars Plate
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $678,226
- **Award type:** 5
- **Project period:** 2023-09-01 → 2027-05-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10913607

## Citation

> US National Institutes of Health, RePORTER application 10913607, Rational optimization of combinatorial therapies for the treatment of rare cystic fibrosis variants (5R01HL167046-02). Retrieved via MORVS 2026-10-25 from https://api.morvs.ai/grant/nih/10913607. Licensed CC0.

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