Molin Yue, Daniel J Weiner, Kristina M Gaietto, Franziska J Rosser, Christopher M Qoyawayma, Michelle L Manni, Michael M Myerburg, Joseph M Pilewski, Juan C Celedón, Wei Chen, Erick Forno
{"title":"鼻腔上皮细胞转录组学预测对 Elexacaftor/Tezacaftor/Ivacaftor 的临床反应。","authors":"Molin Yue, Daniel J Weiner, Kristina M Gaietto, Franziska J Rosser, Christopher M Qoyawayma, Michelle L Manni, Michael M Myerburg, Joseph M Pilewski, Juan C Celedón, Wei Chen, Erick Forno","doi":"10.1165/rcmb.2024-0103OC","DOIUrl":null,"url":null,"abstract":"<p><p>Elexacaftor/tezacaftor/ivacaftor (ETI) has made a substantial positive impact for people living with CF (pwCF). However, there can be substantial variability in efficacy, and we lack adequate biomarkers to predict individual response. We thus aimed to identify transcriptomic profiles in nasal respiratory epithelium that predict clinical response to ETI treatment. We obtained nasal epithelial samples from pwCF prior to ETI initiation and performed a transcriptome-wide analysis of baseline gene expression to predict changes in FEV<sub>1</sub> (∆FEV<sub>1</sub>), year's best FEV<sub>1</sub> (∆ybFEV<sub>1</sub>), and body mass index (∆BMI). Using the top differentially expressed genes (DEGs), we generated transcriptomic risk scores (TRS) and evaluated their predictive performance. The study included 40 pwCF aged ≥6 years (mean 27.7 [SD=15.1] years; 40% female). After ETI initiation, FEV<sub>1</sub> improved ≥5% in 22 (61.1%) participants and ybFEV<sub>1</sub> improved ≥5% in 19 (50%). TRS were constructed using top over-expressed and under-expressed genes for each. Adding the ∆FEV<sub>1</sub> TRS for to a model with age, sex, and baseline FEV<sub>1</sub> increased the AUC from 0.41 to 0.88; the ∆ybFEV<sub>1</sub> TRS increased the AUC from 0.51 to 0.88; and the ∆BMI TRS increased the AUC from 0.46 to 0.92. Average accuracy was thus ~85% in predicting the response to the three outcomes. Results were similar in models further adjusted for F508del zygosity and previous CFTR modulator use. In conclusion, we identified nasal epithelial transcriptomic profiles that help accurately predict changes in FEV1 and BMI with ETI treatment. These novel TRS could serve as predictive biomarkers for clinical response to modulator treatment in pwCF.</p>","PeriodicalId":7655,"journal":{"name":"American Journal of Respiratory Cell and Molecular Biology","volume":null,"pages":null},"PeriodicalIF":5.9000,"publicationDate":"2024-07-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Nasal Epithelium Transcriptomics Predict Clinical Response to Elexacaftor/Tezacaftor/Ivacaftor.\",\"authors\":\"Molin Yue, Daniel J Weiner, Kristina M Gaietto, Franziska J Rosser, Christopher M Qoyawayma, Michelle L Manni, Michael M Myerburg, Joseph M Pilewski, Juan C Celedón, Wei Chen, Erick Forno\",\"doi\":\"10.1165/rcmb.2024-0103OC\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>Elexacaftor/tezacaftor/ivacaftor (ETI) has made a substantial positive impact for people living with CF (pwCF). However, there can be substantial variability in efficacy, and we lack adequate biomarkers to predict individual response. We thus aimed to identify transcriptomic profiles in nasal respiratory epithelium that predict clinical response to ETI treatment. We obtained nasal epithelial samples from pwCF prior to ETI initiation and performed a transcriptome-wide analysis of baseline gene expression to predict changes in FEV<sub>1</sub> (∆FEV<sub>1</sub>), year's best FEV<sub>1</sub> (∆ybFEV<sub>1</sub>), and body mass index (∆BMI). Using the top differentially expressed genes (DEGs), we generated transcriptomic risk scores (TRS) and evaluated their predictive performance. The study included 40 pwCF aged ≥6 years (mean 27.7 [SD=15.1] years; 40% female). After ETI initiation, FEV<sub>1</sub> improved ≥5% in 22 (61.1%) participants and ybFEV<sub>1</sub> improved ≥5% in 19 (50%). TRS were constructed using top over-expressed and under-expressed genes for each. Adding the ∆FEV<sub>1</sub> TRS for to a model with age, sex, and baseline FEV<sub>1</sub> increased the AUC from 0.41 to 0.88; the ∆ybFEV<sub>1</sub> TRS increased the AUC from 0.51 to 0.88; and the ∆BMI TRS increased the AUC from 0.46 to 0.92. Average accuracy was thus ~85% in predicting the response to the three outcomes. Results were similar in models further adjusted for F508del zygosity and previous CFTR modulator use. In conclusion, we identified nasal epithelial transcriptomic profiles that help accurately predict changes in FEV1 and BMI with ETI treatment. These novel TRS could serve as predictive biomarkers for clinical response to modulator treatment in pwCF.</p>\",\"PeriodicalId\":7655,\"journal\":{\"name\":\"American Journal of Respiratory Cell and Molecular Biology\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":5.9000,\"publicationDate\":\"2024-07-19\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"American Journal of Respiratory Cell and Molecular Biology\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1165/rcmb.2024-0103OC\",\"RegionNum\":2,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"BIOCHEMISTRY & MOLECULAR BIOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"American Journal of Respiratory Cell and Molecular Biology","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1165/rcmb.2024-0103OC","RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"BIOCHEMISTRY & MOLECULAR BIOLOGY","Score":null,"Total":0}
Nasal Epithelium Transcriptomics Predict Clinical Response to Elexacaftor/Tezacaftor/Ivacaftor.
Elexacaftor/tezacaftor/ivacaftor (ETI) has made a substantial positive impact for people living with CF (pwCF). However, there can be substantial variability in efficacy, and we lack adequate biomarkers to predict individual response. We thus aimed to identify transcriptomic profiles in nasal respiratory epithelium that predict clinical response to ETI treatment. We obtained nasal epithelial samples from pwCF prior to ETI initiation and performed a transcriptome-wide analysis of baseline gene expression to predict changes in FEV1 (∆FEV1), year's best FEV1 (∆ybFEV1), and body mass index (∆BMI). Using the top differentially expressed genes (DEGs), we generated transcriptomic risk scores (TRS) and evaluated their predictive performance. The study included 40 pwCF aged ≥6 years (mean 27.7 [SD=15.1] years; 40% female). After ETI initiation, FEV1 improved ≥5% in 22 (61.1%) participants and ybFEV1 improved ≥5% in 19 (50%). TRS were constructed using top over-expressed and under-expressed genes for each. Adding the ∆FEV1 TRS for to a model with age, sex, and baseline FEV1 increased the AUC from 0.41 to 0.88; the ∆ybFEV1 TRS increased the AUC from 0.51 to 0.88; and the ∆BMI TRS increased the AUC from 0.46 to 0.92. Average accuracy was thus ~85% in predicting the response to the three outcomes. Results were similar in models further adjusted for F508del zygosity and previous CFTR modulator use. In conclusion, we identified nasal epithelial transcriptomic profiles that help accurately predict changes in FEV1 and BMI with ETI treatment. These novel TRS could serve as predictive biomarkers for clinical response to modulator treatment in pwCF.
期刊介绍:
The American Journal of Respiratory Cell and Molecular Biology publishes papers that report significant and original observations in the area of pulmonary biology. The focus of the Journal includes, but is not limited to, cellular, biochemical, molecular, developmental, genetic, and immunologic studies of lung cells and molecules.