Genomic Classifiers in Personalized Prostate Cancer Radiation Therapy Approaches: A Systematic Review and Future Perspectives Based on International Consensus

TY - JOUR

T1 - Genomic Classifiers in Personalized Prostate Cancer Radiation Therapy Approaches: A Systematic Review and Future Perspectives Based on International Consensus

AU - Spohn, Simon K B

AU - Draulans, Cédric

AU - Kishan, Amar U

AU - Spratt, Daniel

AU - Ross, Ashley

AU - Maurer, Tobias

AU - Tilki, Derya

AU - Berlin, Alejandro

AU - Blanchard, Pierre

AU - Collins, Sean

AU - Bronsert, Peter

AU - Chen, Ronald

AU - Pra, Alan Dal

AU - de Meerleer, Gert

AU - Eade, Thomas

AU - Haustermans, Karin

AU - Hölscher, Tobias

AU - Höcht, Stefan

AU - Ghadjar, Pirus

AU - Davicioni, Elai

AU - Heck, Matthias

AU - Kerkmeijer, Linda G W

AU - Kirste, Simon

AU - Tselis, Nikolaos

AU - Tran, Phuoc T

AU - Pinkawa, Michael

AU - Pommier, Pascal

AU - Deltas, Constantinos

AU - Schmidt-Hegemann, Nina-Sophie

AU - Wiegel, Thomas

AU - Zilli, Thomas

AU - Tree, Alison C

AU - Qiu, Xuefeng

AU - Murthy, Vedang

AU - Epstein, Jonathan I

AU - Graztke, Christian

AU - Gao, Xin

AU - Grosu, Anca L

AU - Kamran, Sophia C

AU - Zamboglou, Constantinos

N1 - Copyright © 2022. Published by Elsevier Inc.

PY - 2023/7/1

Y1 - 2023/7/1

N2 - Current 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.

AB - Current 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.

U2 - 10.1016/j.ijrobp.2022.12.038

DO - 10.1016/j.ijrobp.2022.12.038

M3 - SCORING: Review article

C2 - 36596346

VL - 116

SP - 503

EP - 520

JO - INT J RADIAT ONCOL

JF - INT J RADIAT ONCOL

SN - 0360-3016

IS - 3

ER -