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. 2021 Jan 14;57(1):2002682.
doi: 10.1183/13993003.02682-2020. Print 2021 Jan.

Validation of Lung EpiCheck, a novel methylation-based blood assay, for the detection of lung cancer in European and Chinese high-risk individuals

Mina Gaga  1 , Joanna Chorostowska-Wynimko  2 , Ildikó Horváth  3 , Martin C Tammemagi  4 , David Shitrit  5 , Vered H Eisenberg  6 , Hao Liang  7 , David Stav  8 , Dan Levy Faber  9   10 , Maarten Jansen  11 , Yael Raviv  12 , Vasileios Panagoulias  13 , Piotr Rudzinski  2 , Gabriel Izbicki  14 , Ohad Ronen  15 , Adiv Goldhaber  16 , Rawia Moalem  17 , Nadir Arber  18 , Ilana Haas  19 , Qinghua Zhou  7
Affiliations

Validation of Lung EpiCheck, a novel methylation-based blood assay, for the detection of lung cancer in European and Chinese high-risk individuals

Mina Gaga et al. Eur Respir J. .

Abstract

Aim: Lung cancer screening reduces mortality. We aim to validate the performance of Lung EpiCheck, a six-marker panel methylation-based plasma test, in the detection of lung cancer in European and Chinese samples.

Methods: A case-control European training set (n=102 lung cancer cases, n=265 controls) was used to define the panel and algorithm. Two cut-offs were selected, low cut-off (LCO) for high sensitivity and high cut-off (HCO) for high specificity. The performance was validated in case-control European and Chinese validation sets (cases/controls 179/137 and 30/15, respectively).

Results: The European and Chinese validation sets achieved AUCs of 0.882 and 0.899, respectively. The sensitivities/specificities with LCO were 87.2%/64.2% and 76.7%/93.3%, and with HCO they were 74.3%/90.5% and 56.7%/100.0%, respectively. Stage I nonsmall cell lung cancer (NSCLC) sensitivity in European and Chinese samples with LCO was 78.4% and 70.0% and with HCO was 62.2% and 30.0%, respectively. Small cell lung cancer (SCLC) was represented only in the European set and sensitivities with LCO and HCO were 100.0% and 93.3%, respectively. In multivariable analyses of the European validation set, the assay's ability to predict lung cancer was independent of established risk factors (age, smoking, COPD), and overall AUC was 0.942.

Conclusions: Lung EpiCheck demonstrated strong performance in lung cancer prediction in case-control European and Chinese samples, detecting high proportions of early-stage NSCLC and SCLC and significantly improving predictive accuracy when added to established risk factors. Prospective studies are required to confirm these findings. Utilising such a simple and inexpensive blood test has the potential to improve compliance and broaden access to screening for at-risk populations.

Trial registration: ClinicalTrials.gov NCT02373917.

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Conflict of interest statement

Conflict of interest: M. Gaga has nothing to disclose. Conflict of interest: J. Chorostowska-Wynimko reports grants, personal fees and non-financial support from Grifols, AstraZeneca, Pfizer, CSL Behring and CelonPharma, grants and personal fees from Boehringer Ingelheim, personal fees and non-financial support from MSD and BMS, personal fees from Amgen, GSK, Novartis, Chiesi, Roche and Lekam, outside the submitted work. Conflict of interest: I. Horváth reports personal fees from AstraZeneca, Novartis, CSL Behring, Boehringer Ingelheim, GSK and Berlin-Chemie, outside the submitted work. Conflict of interest: M.C. Tammemagi has served as consultant to Johnson & Johnson/Janssen, Medial EarlySign, Nucleix, bioAffinity Technologies and AstraZeneca. Conflict of interest: D. Shitrit has nothing to disclose. Conflict of interest: V.H. Eisenberg has nothing to disclose. Conflict of interest: H. Liang has nothing to disclose. Conflict of interest: D. Stav has nothing to disclose. Conflict of interest: D. Levy Faber has nothing to disclose. Conflict of interest: M. Jansen has nothing to disclose. Conflict of interest: Y. Raviv has nothing to disclose. Conflict of interest: V. Panagoulias has nothing to disclose. Conflict of interest: P. Rudzinski has nothing to disclose. Conflict of interest: G. Izbicki has nothing to disclose. Conflict of interest: O. Ronen has nothing to disclose. Conflict of interest: A. Goldhaber has nothing to disclose. Conflict of interest: R. Moalem has nothing to disclose. Conflict of interest: N. Arber has nothing to disclose. Conflict of interest: I. Haas has nothing to disclose. Conflict of interest: Q. Zhou has nothing to disclose.

Figures

FIGURE 1
FIGURE 1
Receiver operating characteristic curves for a) training set; b) European validation set; c) Chinese validation set. AUC: area under the curve.
FIGURE 2
FIGURE 2
Multivariable logistic regression of factors potentially impacting Lung EpiCheck positive result, by cut-off: a) low cut-off EpiScore ≥60; b) high cut-off EpiScore ≥70. This analysis included only patients with history of smoking and full smoking data, n=242 (n=106 cases, n=136 controls). Risk factors included age, pack-years and quit years as continuous measures; sex (female versus male), smoking status (former versus current smoker), COPD (yes versus no), and group (cases versus controls). For current smokers, quit years were counted as 0.
FIGURE 3
FIGURE 3
Multivariable logistic regression analysis of predictive factors for lung cancer. This analysis included only patients with history of smoking and full smoking data, n=242 (n=106 cases, n=136 controls). Risk factors: age, pack-years, quit years (continuous), sex (male/female), smoking status (current/past), COPD (yes/no). For current smokers, quit years were counted as 0. AUC: area under the curve.
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