Development of a method for generating SNP interaction-aware polygenic risk scores for radiotherapy toxicity. (June 2021)
- Record Type:
- Journal Article
- Title:
- Development of a method for generating SNP interaction-aware polygenic risk scores for radiotherapy toxicity. (June 2021)
- Main Title:
- Development of a method for generating SNP interaction-aware polygenic risk scores for radiotherapy toxicity
- Authors:
- Franco, Nicola Rares
Massi, Michela Carlotta
Ieva, Francesca
Manzoni, Andrea
Paganoni, Anna Maria
Zunino, Paolo
Veldeman, Liv
Ost, Piet
Fonteyne, Valérie
Talbot, Christopher J.
Rattay, Tim
Webb, Adam
Johnson, Kerstie
Lambrecht, Maarten
Haustermans, Karin
De Meerleer, Gert
de Ruysscher, Dirk
Vanneste, Ben
Van Limbergen, Evert
Choudhury, Ananya
Elliott, Rebecca M.
Sperk, Elena
Veldwijk, Marlon R.
Herskind, Carsten
Avuzzi, Barbara
Noris Chiorda, Barbara
Valdagni, Riccardo
Azria, David
Farcy-Jacquet, Marie-Pierre
Brengues, Muriel
Rosenstein, Barry S.
Stock, Richard G.
Vega, Ana
Aguado-Barrera, Miguel E.
Sosa-Fajardo, Paloma
Dunning, Alison M.
Fachal, Laura
Kerns, Sarah L.
Payne, Debbie
Chang-Claude, Jenny
Seibold, Petra
West, Catharine M.L.
Rancati, Tiziana
Lievens, Yolande
van Eijkeren, Marc
Monten, Christel
De Neve, Wilfried
Peeters, Stephanie
Weltens, Caroline
Defraene, Gilles
van Limberghen, Erik
Briers, Erik
Bourgier, Celine
Draghici, Roxana
Bons, Francoise
Blaschke, Thomas
Weiß, Christian
Helmbold, Irmgard
Weißenberger, Christian
Stegmaier, Petra
Claßen, Johannes
Giesche, Ulrich
Sautter-Bihl, Marie-Luise
Neu, Burkhard
Schnabel, Thomas
Ehmann, Michael
Gauter-Fleckenstein, Benjamin
Schäfer, Jörg
Giandini, Tommaso
Franceschini, Marzia
Sangalli, Claudia
Morlino, Sara
Lozza, Laura
De Santis, Maria C.
Pietro, Gabriele
Delmastro, Elena
Garibaldi, Elisabetta
Cicchetti, Alessandro
Piqué-Leiva, Bibiana
Molla, Meritxel
Giraldo, Alexandra
Ramos, Monica
Lobato-Busto, Ramon
Torrado Moya, Laura
Dominguez-Rios, Isabel
Fajardo-Paneque, Irene
Calvo-Crespo, Patricia
Carballo, Ana
Peleteiro, Paula
Olivia-Fuentes-Rios,
Gomez-Caamano, Antonio
Harrop, Victoria
Payne, Debbie
Keni, Manjusha
Symonds, Paul R.
Lavers, Samuel
Wright, Simon
Thiagarajan, Sridhar
Aznar-Garcia, Luis
Kancherla, Kiran
Kent, Christopher
Vasanthan, Subramaniam
Appleton, Donna
Kaushik, Monika
Kenny, Frances
Khout, Hazem
Krupa, Jaroslaw
Lambert, Kelly V.
Pilgrim, Simon
Shokuhi, Sheila
Valassiadou, Kalliope
Bioangiu, Ion
Sampson, Kufre
Osman, Ahmed
Faivre-Finn, Corinne
Foweraker, Karen
Pascoe, Abigail
Esler, Claire P.
Ward, Tim
Higginson, Daniel S.
Green, Sheryl
… (more) - Abstract:
- Highlights: Epistasis aware polygenic risk scores (PRSs) can predict late radiotherapy toxicity. SNP-SNP interactions can be summarized to foster interpretability. Allele combinations may be more informative with respect to single genetic variants. Our interaction-aware score outperforms classical PRSs. 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 15Highlights: Epistasis aware polygenic risk scores (PRSs) can predict late radiotherapy toxicity. SNP-SNP interactions can be summarized to foster interpretability. Allele combinations may be more informative with respect to single genetic variants. Our interaction-aware score outperforms classical PRSs. 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. … (more)
- Is Part Of:
- Radiotherapy and oncology. Volume 159(2021)
- Journal:
- Radiotherapy and oncology
- Issue:
- Volume 159(2021)
- Issue Display:
- Volume 159, Issue 2021 (2021)
- Year:
- 2021
- Volume:
- 159
- Issue:
- 2021
- Issue Sort Value:
- 2021-0159-2021-0000
- Page Start:
- 241
- Page End:
- 248
- Publication Date:
- 2021-06
- Subjects:
- Prostate cancer -- Radiotherapy -- Late toxicity -- Genetic risk factors -- SNPs -- Epistasis
Oncology -- Periodicals
Radiotherapy -- Periodicals
Tumors -- Periodicals
Medical Oncology -- Periodicals
Neoplasms -- radiotherapy -- Periodicals
Radiotherapy -- Periodicals
Radiothérapie -- Périodiques
Cancérologie -- Périodiques
Tumeurs -- Périodiques
Electronic journals
616.9940642 - Journal URLs:
- http://www.sciencedirect.com/science/journal/01678140 ↗
http://www.clinicalkey.com/dura/browse/journalIssue/01678140 ↗
http://www.clinicalkey.com.au/dura/browse/journalIssue/01678140 ↗
http://www.estro.org/ ↗
http://www.elsevier.com/journals ↗
http://www.journals.elsevier.com/radiotherapy-and-oncology/ ↗ - DOI:
- 10.1016/j.radonc.2021.03.024 ↗
- Languages:
- English
- ISSNs:
- 0167-8140
- Deposit Type:
- Legaldeposit
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