Details

Autor(en) / Beteiligte

• Arnau-Collell, Coral
• Díez-Villanueva, Anna
• Bellosillo, Beatriz
• Augé, Josep M
• Muñoz, Jenifer
• Guinó, Elisabet
• Moreira, Leticia
• Serradesanferm, Anna
• Pozo, Àngels
• Torà-Rocamora, Isabel
• Bonjoch, Laia
• Ibañez-Sanz, Gemma
• Obon-Santacana, Mireia
• Moratalla-Navarro, Ferran
• Sanz-Pamplona, Rebeca
• Márquez Márquez, Carmen
• Rueda Miret, Rebeca
• Pérez Berbegal, Rocio
• Piquer Velasco, Gabriel
• Hernández Rodríguez, Cristina
• Grau, Jaume
• Castells, Antoni
• Borràs, Josep M
• Bessa, Xavier
• Moreno, Victor
• Castellví-Bel, Sergi

Titel

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

Ist Teil von

• Cancer epidemiology, biomarkers & prevention, 2022-07, Vol.31 (7), p.1305-1312

Ort / Verlag

United States: American Association for Cancer Research

Erscheinungsjahr

2022

Link zum Volltext

Quelle

Electronic Journals Library

Beschreibungen/Notizen

• Colorectal cancer has high incidence and associated 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. 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 genotyped. Polygenic risk score (PRS) and additive models for risk prediction incorporating sex, age, FIT value, and PRS were generated. 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]. 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. PRS has capacity for risk stratification of colorectal cancer suggesting its potential for optimizing screening strategies alongside with other biomarkers.