medRxivGenetic & Genomic MedicinePreprint
CFTR structures bound to ETI components predict rare mutation response to modulator combinations
Noemie StanleighiD, Michal GuriD, Michal ShteinbergiD, Aryeh M. Weiss, Naama Sebbag-Sznajder, Deborah Duran, Myriam GrunewaldiD, Liron Birimberg‐SchwartziD, Ronen Bar‐YosephiD, Jeffrey Matthijn BeekmaniD, Eitan KeremiD, Michael A. WilschanskiiD, Batsheva KeremiD
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Abstract
BackgroundCFTR protein structures bound to each of Elexacaftor/Tezacaftor/Ivacaftor (ETI) were recently established. We aimed to use this data to predict and assess responses to ETI and each of its components in intestinal organoids derived from patients carrying rare CFTR mutations, not yet approved for ETI, based on their mutation location within the CFTR structure. MethodsOrganoids were generated from six patients carrying the Q1100P and/or K163E alleles, not receiving ETI. Measurements of the response to ETI or combination of its components were performed in 3D-organoids by forskolin-induced swelling (FIS) and in 2D-monolayers by short-circuit currents (Isc). Based on these results, patients initiated off-label ETI treatment. Clinical data before and after treatment were collected. ResultsVX-445 binds amino acids flanking Q1100P and VX-661 binds near the TM2-ICL1 boundary, where K163E is located. Thus, each modulator was predicted to contribute to the correction of one mutation. Functional measurements (FIS and Isc) indeed showed that Q1100P responded to VX-445 alone, and K163E to VX-661 alone. Unexpectedly, VX-445 had a dramatic effect on K163E function. Both mutations achieved clinically significant CFTR activity levels with VX-661+VX-445, without benefit from VX-770. Following these results ETI was initiated, resulting in significant and sustained clinical improvements, in all patients, in lung function (FEV1, LCI), BMI and sweat chloride. ConclusionThese results suggest that our structural approach can help predict response to the available modulators in patients carrying rare CFTR mutations. Furthermore, this approach allows for patient-specific optimization of modulator combinations, minimizing unnecessary exposure to ineffective treatments.
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