Publication:
Genomic classifiers in personalized prostate cancer radiation therapy approaches: a systematic review and future perspectives based on international consensus

dc.contributor.coauthorSpohn, Simon K.B.
dc.contributor.coauthorDraulans, Cedric
dc.contributor.coauthorKishan, Amar U.
dc.contributor.coauthorSpratt, Daniel
dc.contributor.coauthorRoss, Ashley
dc.contributor.coauthorMaurer, Tobias
dc.contributor.coauthorBerlin, Alejandro
dc.contributor.coauthorBlanchard, Pierre
dc.contributor.coauthorCollins, Sean
dc.contributor.coauthorBronsert, Peter
dc.contributor.coauthorChen, Ronald
dc.contributor.coauthorPra, Alan Dal
dc.contributor.coauthorde Meerleer, Gert
dc.contributor.coauthorEade, Thomas
dc.contributor.coauthorHaustermans, Karin
dc.contributor.coauthorHölscher, Tobias
dc.contributor.coauthorHöcht, Stefan
dc.contributor.coauthorGhadjar, Pirus
dc.contributor.coauthorDavicioni, Elai
dc.contributor.coauthorHeck, Matthias
dc.contributor.coauthorKerkmeijer, Linda G.W.
dc.contributor.coauthorKirste, Simon
dc.contributor.coauthorTselis, Nikolaos
dc.contributor.coauthorTran, Phuoc T.
dc.contributor.coauthorPinkawa, Michael
dc.contributor.coauthorPommier, Pascal
dc.contributor.coauthorDeltas, Constantinos
dc.contributor.coauthorSchmidt-Hegemann, Nina-Sophie
dc.contributor.coauthorWiegel, Thomas
dc.contributor.coauthorZilli, Thomas
dc.contributor.coauthorTree, Alison C.
dc.contributor.coauthorQiu, Xuefeng
dc.contributor.coauthorMurthy, Vedang
dc.contributor.coauthorEpstein, Jonathan I.
dc.contributor.coauthorGraztke, Christian
dc.contributor.coauthorGao, Xin
dc.contributor.coauthorGrosu, Anca L.
dc.contributor.coauthorKamran, Sophia C.
dc.contributor.coauthorZamboglou, Constantinos
dc.contributor.kuauthorTilki, Derya
dc.contributor.kuprofileOther
dc.contributor.schoolcollegeinstituteSchool of Medicine
dc.contributor.unitKoç University Hospital
dc.contributor.yokidN/A
dc.date.accessioned2024-11-09T23:08:01Z
dc.date.issued2023
dc.description.abstractCurrent risk-stratification systems for prostate cancer (PCa) do not sufficiently reflect the disease heterogeneity. Genomic classifiers (GC) enable improved risk stratification after surgery, but less data exist for patients treated with definitive radiation therapy (RT) or RT in oligo-/metastatic disease stages. To guide future perspectives of GCs for RT, we conducted (1) a systematic review on the evidence of GCs for patients treated with RT and (2) a survey of experts using the Delphi method, addressing the role of GCs in personalized treatments to identify relevant fields of future clinical and translational research. We performed a systematic review and screened ongoing clinical trials on ClinicalTrials.gov. Based on these results, a multidisciplinary international team of experts received an adapted Delphi method survey. Thirty-one and 30 experts answered round 1 and round 2, respectively. Questions with ≥75% agreement were considered relevant and included in the qualitative synthesis. Evidence for GCs as predictive biomarkers is mainly available to the postoperative RT setting. Validation of GCs as prognostic markers in the definitive RT setting is emerging. Experts used GCs in patients with PCa with extensive metastases (30%), in postoperative settings (27%), and in newly diagnosed PCa (23%). Forty-seven percent of experts do not currently use GCs in clinical practice. Expert consensus demonstrates that GCs are promising tools to improve risk-stratification in primary and oligo-/metastatic patients in addition to existing classifications. Experts were convinced that GCs might guide treatment decisions in terms of RT-field definition and intensification/deintensification in various disease stages. This work confirms the value of GCs and the promising evidence of GC utility in the setting of RT. Additional studies of GCs as prognostic biomarkers are anticipated and form the basis for future studies addressing predictive capabilities of GCs to optimize RT and systemic therapy. The expert consensus points out future directions for GC research in the management of PCa.
dc.description.indexedbyScopus
dc.description.indexedbyPubMed
dc.description.indexedbyWoS
dc.description.openaccessYES
dc.description.publisherscopeInternational
dc.identifier.doi10.1016/j.ijrobp.2022.12.038
dc.identifier.issn0360-3016
dc.identifier.linkhttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85147803881&doi=10.1016%2fj.ijrobp.2022.12.038&partnerID=40&md5=1a5d5a570afaff4ef69f6dac08443cf4
dc.identifier.quartileQ1
dc.identifier.scopus2-s2.0-85147803881
dc.identifier.urihttps://hdl.handle.net/20.500.14288/9248
dc.identifier.wos1055271300001
dc.keywordsBiomarkers
dc.keywordsClinical research
dc.keywordsDecision making
dc.keywordsDisease control
dc.keywordsDiseases
dc.keywordsGenes
dc.keywordsGenome
dc.keywordsPatient monitoring
dc.keywordsUrology
dc.languageEnglish
dc.publisherElsevier Ltd
dc.sourceInternational Journal of Radiation Oncology Biology Physics
dc.subjectCancer
dc.subjectGene fusion
dc.subjectAprotinin
dc.titleGenomic classifiers in personalized prostate cancer radiation therapy approaches: a systematic review and future perspectives based on international consensus
dc.typeReview
dspace.entity.typePublication
local.contributor.authorid0000-0001-7033-1380
local.contributor.kuauthorTilki, Derya

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