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A personalized medicine approach to optimize care for a pediatric cystic fibrosis patient with atypical clinical symptoms
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  • Kavisha Arora,
  • Jesun Lee,
  • Ammar Husami,
  • Weiqiang Zhang,
  • Ferdous Kadri,
  • Sunitha Yarlagadda,
  • Changsuk Moon,
  • Kyu Shik Mun,
  • Kejian Zhang,
  • Yunjie Huang,
  • Pramodha Liyanage,
  • John Brewington,
  • John P. Clancy,
  • Ala Shaikhkhalil,
  • Grace Paul,
  • Anjaparavanda P. Naren
Kavisha Arora
Cedars-Sinai Medical Center
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Jesun Lee
Cedars-Sinai Medical Center
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Ammar Husami
Cincinnati Children's Hospital Medical Center Division of Human Genetics
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Weiqiang Zhang
USDA-ARS Warmwater Aquaculture Research Unit
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Ferdous Kadri
Cedars-Sinai Medical Center
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Sunitha Yarlagadda
Cincinnati Children's Hospital Medical Center Winslow
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Changsuk Moon
Decibel Therapeutics Inc
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Kyu Shik Mun
Cedars-Sinai Medical Center
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Kejian Zhang
Cincinnati Children's Hospital Medical Center Division of Human Genetics
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Yunjie Huang
Indiana University
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Pramodha Liyanage
Cedars-Sinai Medical Center
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John Brewington
Cincinnati Children's Hospital Medical Center Winslow
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John P. Clancy
Cystic Fibrosis Foundation
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Ala Shaikhkhalil
Nationwide Children's Hospital
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Grace Paul
Nationwide Children's Hospital
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Anjaparavanda P. Naren
Cedars-Sinai Medical Center

Corresponding Author:[email protected]

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Abstract

Mutations in the cystic fibrosis (CF) transmembrane conductance regulator (CFTR) gene typically cause severe health complications in multiple organ systems, including the respiratory and gastrointestinal systems. Certain CFTR mutations, however, cause milder clinical phenotypes which may delay confirmatory diagnosis and treatment. Moreover, rare CFTR variants are not studied frequently or approved for genotype specific CFTR modulator therapies, creating further disadvantage. Herein, we describe a personalized medicine approach for a CF patient with three CFTR variants and mild clinical disease to aid in the diagnosis of CF and development of an optimized treatment plan. This strategy relied on the synergistic combination of advanced genetic analyses, patient-derived models of CFTR function and modulation, and personalized clinical care delivery. Whole Exome Sequencing revealed three compound heterozygous CFTR variants: c.2249C>T (p.P750L), c.1408G>A (p.V470M), and c.1251C>A (p.N417K). The CFTR channel function and nature of protein defects for both V470M and N417K mutations are not previously characterized. Patient-derived intestinal organoid models demonstrated residual CFTR channel activity, with improvement in channel function following treatment with the CFTR modulators. / n vitro studies in heterologous model system demonstrated that P750L has the features of Class II CFTR mutations, whereas V470M/N417K exhibited characteristics of Class II, III, and IV mutations, with all three variants responding to the combination modulator therapy of elexacaftor, tezacaftor, and ivacaftor (ETI) and showing functional rescue to near-wild-type CFTR levels. The laboratory data was then utilized to inform patient care, including off-label prescription of ETI. Following 18 months of ETI therapy, significant improvements were noted in key clinical outcomes, including sweat chloride, nutritional parameters, and respiratory and gastrointestinal symptoms. This study demonstrates a personalized medicine approach across clinical and laboratory domains used to care for CF patients with atypical symptoms and/or rare CFTR mutations.
22 Jun 2023Submitted to Pediatric Pulmonology
22 Jun 2023Submission Checks Completed
22 Jun 2023Assigned to Editor
22 Jun 2023Review(s) Completed, Editorial Evaluation Pending
26 Jun 2023Editorial Decision: Revise Minor
08 Aug 20231st Revision Received
08 Aug 2023Assigned to Editor
08 Aug 2023Submission Checks Completed
08 Aug 2023Review(s) Completed, Editorial Evaluation Pending
19 Aug 2023Editorial Decision: Revise Minor
31 Aug 20232nd Revision Received
14 Sep 2023Submission Checks Completed
14 Sep 2023Assigned to Editor
14 Sep 2023Review(s) Completed, Editorial Evaluation Pending
26 Sep 2023Editorial Decision: Accept