Assessing Lung Cancer Absolute Risk Trajectory Based on a Polygenic Risk Model



Hung, Rayjean J, Warkentin, Matthew T, Brhane, Yonathan, Chatterjee, Nilanjan, Christiani, David C, Landi, Maria Teresa, Caporaso, Neil E, Liu, Geoffrey, Johansson, Mattias, Albanes, Demetrius
et al (show 19 more authors) (2021) Assessing Lung Cancer Absolute Risk Trajectory Based on a Polygenic Risk Model. CANCER RESEARCH, 81 (6). pp. 1607-1615.

[img] Text
PRS lung cancer prediction_CR_REV10_Clean_Editor.pdf - Author Accepted Manuscript

Download (494kB) | Preview

Abstract

Lung cancer is the leading cause of cancer-related death globally. An improved risk stratification strategy can increase efficiency of low-dose CT (LDCT) screening. Here we assessed whether individual's genetic background has clinical utility for risk stratification in the context of LDCT screening. On the basis of 13,119 patients with lung cancer and 10,008 controls with European ancestry in the International Lung Cancer Consortium, we constructed a polygenic risk score (PRS) via 10-fold cross-validation with regularized penalized regression. The performance of risk model integrating PRS, including calibration and ability to discriminate, was assessed using UK Biobank data (<i>N</i> = 335,931). Absolute risk was estimated on the basis of age-specific lung cancer incidence and all-cause mortality as competing risk. To evaluate its potential clinical utility, the PRS distribution was simulated in the National Lung Screening Trial (<i>N</i> = 50,772 participants). The lung cancer ORs for individuals at the top decile of the PRS distribution versus those at bottom 10% was 2.39 [95% confidence interval (CI) = 1.92-3.00; <i>P</i> = 1.80 × 10<sup>-14</sup>] in the validation set (<i>P</i> <sub>trend</sub> = 5.26 × 10<sup>-20</sup>). The OR per SD of PRS increase was 1.26 (95% CI = 1.20-1.32; <i>P</i> = 9.69 × 10<sup>-23</sup>) for overall lung cancer risk in the validation set. When considering absolute risks, individuals at different PRS deciles showed differential trajectories of 5-year and cumulative absolute risk. The age reaching the LDCT screening recommendation threshold can vary by 4 to 8 years, depending on the individual's genetic background, smoking status, and family history. Collectively, these results suggest that individual's genetic background may inform the optimal lung cancer LDCT screening strategy. SIGNIFICANCE: Three large-scale datasets reveal that, after accounting for risk factors, an individual's genetics can affect their lung cancer risk trajectory, thus may inform the optimal timing for LDCT screening.

Item Type: Article
Uncontrolled Keywords: Lung, Humans, Lung Neoplasms, Pulmonary Disease, Chronic Obstructive, Genetic Predisposition to Disease, Tomography, X-Ray Computed, Mass Screening, Medical History Taking, Oligonucleotide Array Sequence Analysis, Incidence, Risk Assessment, Risk Factors, Case-Control Studies, Smoking, Age Factors, Multifactorial Inheritance, Models, Genetic, Adult, Aged, Middle Aged, Female, Male, Practice Guidelines as Topic, Early Detection of Cancer, Genome-Wide Association Study, Machine Learning, Biomarkers, Tumor, United Kingdom
Divisions: Faculty of Health and Life Sciences
Faculty of Health and Life Sciences > Institute of Systems, Molecular and Integrative Biology
Depositing User: Symplectic Admin
Date Deposited: 26 Mar 2021 08:02
Last Modified: 18 Jan 2023 22:54
DOI: 10.1158/0008-5472.CAN-20-1237
Related URLs:
URI: https://livrepository.liverpool.ac.uk/id/eprint/3118164