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, Joanna Chorostowska-Wynimko, Ildikó Horváth, Martin C Tammemagi, David Shitrit, Vered H Eisenberg, Hao Liang, David Stav, Dan Levy Faber, Maarten Jansen, Yael Raviv, Vasileios Panagoulias, Piotr Rudzinski, Gabriel Izbicki, Ohad Ronen, Adiv Goldhaber, Rawia Moalem, Nadir Arber, Ilana Haas, Qinghua Zhou, Mina Gaga, Joanna Chorostowska-Wynimko, Ildikó Horváth, Martin C Tammemagi, David Shitrit, Vered H Eisenberg, Hao Liang, David Stav, Dan Levy Faber, Maarten Jansen, Yael Raviv, Vasileios Panagoulias, Piotr Rudzinski, Gabriel Izbicki, Ohad Ronen, Adiv Goldhaber, Rawia Moalem, Nadir Arber, Ilana Haas, Qinghua Zhou

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.

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.

Copyright ©ERS 2021.

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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