4.5 Article

Evaluating the Potential of Polygenic Risk Score to Improve Colorectal Cancer Screening

期刊

CANCER EPIDEMIOLOGY BIOMARKERS & PREVENTION
卷 31, 期 7, 页码 1305-1312

出版社

AMER ASSOC CANCER RESEARCH
DOI: 10.1158/1055-9965.EPI-22-0042

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资金

  1. Strategic Plan for Health Research and Innovation - PERIS program 2016-2020 (Generalitat de Catalunya) [SLT002/16/00398]
  2. Fondo de Investigacion Sanitaria/FEDER [PI14/00613, PI17/00878, PI17/00092, PI20/00113]
  3. Fundacio La Marato de TV3 [2019-202008]
  4. CERCA Program (Generalitat de Catalunya) [CERCA-2648]
  5. Agencia de Gestio d'Ajuts Universitaris i de Recerca (Generalitat de Catalunya) [GRPRE 2017SGR21, GRC 2017SGR653, GRC 2017SGR735, GRC 2017SGR80, GRC 2017SGR723]
  6. Instituto de Salud Carlos III
  7. CIBEREHD [CB06/04/0016]
  8. Juan de la Cierva postdoctoral contract [FJCI-2017-32593]
  9. COST [CA17118]
  10. Fundacion Cientifica de la Asociacion Espanola contra el Cancer [GCB13131592CAST, GCTRA18022MORE, PRYGN211085CAST]

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This study is the first investigation analyzing polygenic risk score (PRS) in a two-step colorectal cancer screening program. The results showed that PRS could improve the accuracy of current colorectal cancer screening, especially for higher at-risk subgroups. However, the capacity of PRS is limited and should be complemented by additional biomarkers.
Background: Colorectal cancer has high incidence and associ-ated mortality worldwide. Screening programs are recommended for men and women over 50. Intermediate screens such as fecal immunochemical testing (FIT) select patients for colonoscopy with suboptimal sensitivity. Additional biomarkers could improve the current scenario. Methods: We included 2,893 individuals with a positive FIT test. They were classified as cases when a high-risk lesion for colorectal cancer was detected after colonoscopy, whereas the control group comprised individuals with low-risk or no lesions. 65 colorectal cancer risk genetic variants were geno-typed. Polygenic risk score (PRS) and additive models for risk prediction incorporating sex, age, FIT value, and PRS were generated. Results: Risk score was higher in cases compared with controls [per allele OR = 1.04; 95% confidence interval (CI), 1.02-1.06; P < 0.0001]. A 2-fold increase in colorectal cancer risk was observed for subjects in the highest decile of risk alleles (>= 65), compared with those in the first decile (<= 54; OR = 2.22; 95% CI, 1.59-3.12; P < 0.0001). The model combining sex, age, FIT value, and PRS reached the highest accuracy for identifying patients with a high-risk lesion [cross-validated area under the ROC curve (AUROC): 0.64; 95% CI, 0.62-0.66]. Conclusions: This is the first investigation analyzing PRS in a two-step colorectal cancer screening program. PRS could improve current colorectal cancer screening, most likely for higher at-risk subgroups. However, its capacity is limited to predict colorectal cancer risk status and should be complemented by additional biomarkers.Impact: PRS has capacity for risk stratification of colorectal cancer suggesting its potential for optimizing screening strategies alongside with other biomarkers.

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