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

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    Authors
    Franco, N. R.
    Massi, M. C.
    Ieva, F.
    Manzoni, A.
    Paganoni, A. M.
    Zunino, P.
    Veldeman, L.
    Ost, P.
    Fonteyne, V.
    Talbot, C. J.
    Rattay, T.
    Webb, A.
    Johnson, K.
    Lambrecht, M.
    Haustermans, K.
    De Meerleer, G.
    De Ruysscher, D
    Vanneste, B.
    Van Limbergen, E.
    Choudhury, Ananya
    Elliott, Rebecca M
    Sperk, E.
    Veldwijk, M. R.
    Herskind, C.
    Avuzzi, B.
    Noris Chiorda, B.
    Valdagni, R.
    Azria, D.
    Farcy-Jacquet, M. P.
    Brengues, M.
    Rosenstein, B. S.
    Stock, R. G.
    Vega, A.
    Aguado-Barrera, M. E.
    Sosa-Fajardo, P.
    Dunning, A. M.
    Fachal, L.
    Kerns, S. L.
    Payne, D.
    Chang-Claude, J.
    Seibold, P.
    West, Catharine M L
    Rancati, T.
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    Affiliation
    MOX, Department of Mathematics, Politecnico di Milano, Italy.
    Issue Date
    2021
    
    Metadata
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    Abstract
    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.
    Citation
    Franco NR, Massi MC, Ieva F, Manzoni A, Paganoni AM, Zunino P, et al. Development of a method for generating SNP interaction-aware polygenic risk scores for radiotherapy toxicity. Radiotherapy and Oncology. 2021 Jun;159:241–8.
    Journal
    Radiotherapy and Oncology
    URI
    http://hdl.handle.net/10541/623975
    DOI
    10.1016/j.radonc.2021.03.024
    PubMed ID
    33838170
    Additional Links
    https://dx.doi.org/10.1016/j.radonc.2021.03.024
    Type
    Article
    Language
    en
    ae974a485f413a2113503eed53cd6c53
    10.1016/j.radonc.2021.03.024
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