4.7 Article

Development of a method for generating SNP interaction-aware polygenic risk scores for radiotherapy toxicity

期刊

RADIOTHERAPY AND ONCOLOGY
卷 159, 期 -, 页码 241-248

出版社

ELSEVIER IRELAND LTD
DOI: 10.1016/j.radonc.2021.03.024

关键词

Prostate cancer; Radiotherapy; Late toxicity; Genetic risk factors; SNPs; Epistasis

资金

  1. European Union [601826]
  2. ERA-NET ERA PerMed/FRRB grant [ERAPERMED2018244]
  3. ERA-NET ERA PerMed/BMBF [01KU1912]
  4. NIHR Manchester Biomedical Research Center, UK
  5. European Union's Horizon 2020 Research and Innovation Programme under Marie SklodowskaCurie [656144]
  6. Fondazione Italo Monzino
  7. Spanish Instituto de Salud Carlos III (ISCIII) funding, an initiative of the Spanish Ministry of Economy and Innovation
  8. European Regional Development FEDER Funds [INT15/00070, INT16/00154, INT17/00133, INT20/00071, PI19/01424, PI16/00046, PI13/02030, PI10/00164]
  9. Autonomous Government of Galicia (Consolidation and structuring program) [IN607B]
  10. National Institute of Health Research (NIHR) Doctoral Research Fellowship [DRF 201407079]
  11. National Cancer Institute (NCI) [K07CA187546]
  12. [INCa_Inserm_DGOS_12553]
  13. Marie Curie Actions (MSCA) [656144] Funding Source: Marie Curie Actions (MSCA)

向作者/读者索取更多资源

The study aimed to investigate the impact of single nucleotide polymorphism interactions on the risk of toxicity in prostate cancer patients receiving radiotherapy. A novel method for polygenic risk score incorporating SNP-SNP interactions was proposed and found to outperform traditional approaches in discriminating patients with toxicity.
Aim: To identify the effect of single nucleotide polymorphism (SNP) interactions on the risk of toxicity following radiotherapy (RT) for prostate cancer (PCa) and propose a new method for polygenic risk score incorporating SNP-SNP interactions (PRSi). Materials and methods: Analysis included the REQUITE PCa cohort that received external beam RT and was followed for 2 years. Late toxicity endpoints were: rectal bleeding, urinary frequency, haematuria, nocturia, decreased urinary stream. Among 43 literature-identified SNPs, the 30% most strongly associated with each toxicity were tested. SNP-SNP combinations (named SNP-allele sets) seen in >= 10% of the cohort were condensed into risk (RS) and protection (PS) scores, respectively indicating increased or decreased toxicity risk. Performance of RS and PS was evaluated by logistic regression. RS and PS were then combined into a single PRSi evaluated by area under the receiver operating characteristic curve (AUC). Results: Among 1,387 analysed patients, toxicity rates were 11.7% (rectal bleeding), 4.0% (urinary frequency), 5.5% (haematuria), 7.8% (nocturia) and 17.1% (decreased urinary stream). RS and PS combined 8 to 15 different SNP-allele sets, depending on the toxicity endpoint. Distributions of PRSi differed significantly in patients with/without toxicity with AUCs ranging from 0.61 to 0.78. PRSi was better than the classical summed PRS, particularly for the urinary frequency, haematuria and decreased urinary stream endpoints. Conclusions: Our method incorporates SNP-SNP interactions when calculating PRS for radiotherapy toxicity. Our approach is better than classical summation in discriminating patients with toxicity and should enable incorporating genetic information to improve normal tissue complication probability models. (C) 2021 The Authors. Published by Elsevier B.V.

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