DNA repair biomarker for lung cancer risk and its correlation with airway cells gene expression

Tamar Paz-Elizur, Yael Leitner-Dagan, Kerstin B. Meyer, Barak Markus, Federico M. Giorgi, Martin O'Reilly, Hyunjin Kim, Yentl Evgy, Ronen Fluss, Laurence S. Freedman, Robert C. Rintoul, Bruce Ponder, Zvi Livneh

Research output: Contribution to journalArticlepeer-review

7 Scopus citations


Background: Improving lung cancer risk assessment is required because current early-detection screening criteria miss most cases. We therefore examined the utility for lung cancer risk assessment of a DNA Repair score obtained from OGG1, MPG, and APE1 blood tests. In addition, we examined the relationship between the level of DNA repair and global gene expression. Methods: We conducted a blinded case-control study with 150 non-small cell lung cancer case patients and 143 control individuals. DNA Repair activity was measured in peripheral blood mononuclear cells, and the transcriptome of nasal and bronchial cells was determined by RNA sequencing. A combined DNA Repair score was formed using logistic regression, and its correlation with disease was assessed using cross-validation; correlation of expression to DNA Repair was analyzed using Gene Ontology enrichment. Results: DNA Repair score was lower in case patients than in control individuals, regardless of the case's disease stage. Individuals at the lowest tertile of DNA Repair score had an increased risk of lung cancer compared to individuals at the highest tertile, with an odds ratio (OR) of 7.2 (95% confidence interval [CI] = 3.0 to 17.5; P <.001), and independent of smoking. Receiver operating characteristic analysis yielded an area under the curve of 0.89 (95% CI = 0.82 to 0.93). Remarkably, low DNA Repair score correlated with a broad upregulation of gene expression of immune pathways in patients but not in control individuals. Conclusions: The DNA Repair score, previously shown to be a lung cancer risk factor in the Israeli population, was validated in this independent study as a mechanism-based cancer risk biomarker and can substantially improve current lung cancer risk prediction, assisting prevention and early detection by computed tomography scanning.

Original languageEnglish
Article numberpkz067
JournalJNCI Cancer Spectrum
Issue number1
StatePublished - 1 Feb 2020
Externally publishedYes

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© The Author(s) 2020. Published by Oxford University Press.


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