Subpathologies and genomic classifier for treatment individualization of post-prostatectomy radiotherapy

Matthew Ramotar; Melvin L K Chua; Hong Truong; Ali Hosni; Melania Pintilie; Elai Davicioni; Neil E Fleshner; Adam P Dicker; Robert G Bristow; Hansen H He; Theo van der Kwast; Robert B Den; Alejandro Berlin

doi:10.1016/j.urolonc.2021.08.013

Subpathologies and genomic classifier for treatment individualization of post-prostatectomy radiotherapy

Urol Oncol. 2022 Jan;40(1):5.e1-5.e13. doi: 10.1016/j.urolonc.2021.08.013. Epub 2021 Sep 17.

Authors

Affiliations

¹ Department of Radiation Oncology, University of Toronto; Radiation Medicine Program, Princess Margaret Cancer Centre, University Health Network, Toronto, Ontario, Canada.
² Department of Radiation Oncology, University of Toronto; Radiation Medicine Program, Princess Margaret Cancer Centre, University Health Network, Toronto, Ontario, Canada; Divisions of Radiation Oncology and Medical Sciences, National Cancer Centre Singapore, Singapore; Oncology Academic Programme, Duke-NUS Medical School, Singapore.
³ Department of Urology, Sidney Kimmel Medical College, Thomas Jefferson University, Philadelphia, PA.
⁴ Department of Biostatistics, Princess Margaret Cancer Centre, University Health Network, Toronto, Ontario, Canada.
⁵ Decipher Biosciences Inc. San Diego, CA.
⁶ Division of Urology, University of Toronto; Mount Sinai Hospital; Princess Margaret Cancer Centre, Toronto General Hospital, University Health Network, Toronto, Ontario, Canada.
⁷ Department of Radiation Oncology, Sidney Kimmel Medical College, Thomas Jefferson University, Philadelphia, PA.
⁸ Department of Radiation Oncology, University of Toronto; Radiation Medicine Program, Princess Margaret Cancer Centre, University Health Network, Toronto, Ontario, Canada; Manchester Cancer Research Center, Manchester, United Kingdom.
⁹ Princess Margaret Cancer Centre, University Health Network, Toronto, Ontario, Canada; Department of Medical Biophysics, University of Toronto, Toronto, Ontario, Canada.
¹⁰ Laboratory Medicine Program, University Health Network, Toronto, Ontario, Canada.
¹¹ Department of Radiation Oncology, Sidney Kimmel Medical College, Thomas Jefferson University, Philadelphia, PA. Electronic address: robert.den@jefferson.edu.
¹² Department of Radiation Oncology, University of Toronto; Radiation Medicine Program, Princess Margaret Cancer Centre, University Health Network, Toronto, Ontario, Canada; Techna Institute, University Health Network, Toronto, Ontario, Canada. Electronic address: alejandro.berlin@rmp.uhn.ca.

PMID: 34538726
DOI: 10.1016/j.urolonc.2021.08.013

Abstract

Purpose/objective: Risk-stratification for post-prostatectomy radiotherapy (PORT) using conventional clinicopathologic indexes leads to substantial over- and under-treatment. Better patient selection could spare unnecessary toxicities and improve outcomes. We investigated the prognostic utility of unfavorable subpathologies intraductal carcinoma and cribriform architecture (IDC/CA), and a 22-gene Decipher genomic classifier (GC) in prostate cancer (PCa) patients receiving PORT.

Material/methods: A cohort of 302 men who received PORT at 2 academic institutions was pooled. PORT was predominately delivered as salvage (62% of cases); 20% received HT+PORT. Specimens were centrally reviewed for IDC/CA presence. In 104 cases, GC scores were determined. Endpoints were biochemical relapse-free (bRFR) and metastasis-free (mFR) rates.

Results: After a median follow-up of 6.49-years, 135 (45%) and 40 (13%) men experienced biochemical relapse and metastasis, respectively. IDC/CA were identified in 160 (53%) of cases. Men harboring IDC/CA experienced inferior bRFR (HR 2.6, 95%CI 1.8-3.2, P<0.001) and mFR (HR 3.1, 95%CI 1.5-6.4, P = 0.0014). Patients with GC scores, 22 (21%) were stratified low-, 30 (29%) intermediate-, and 52 (50%) high-risk. GC low-risk was associated with superior bRFR (HR 0.25, 95%CI 0.1-0.5, P<0.001) and mFR (HR 0.15, 95%CI 0.03-0.8, P = 0.025). On multivariable analyses, IDC/CA and GC independently predicted for bRFR, corresponding to improved discrimination (C-index = 0.737 (95%CI 0.662-0.813)).

Conclusions: IDC/CA subpathologies and GC predict for biochemical relapse and metastasis beyond conventional clinicopathologic indexes in the PORT setting. Patients harboring IDC/CA are at higher risk of relapse after maximal local therapies, thus warranting consideration for treatment intensification strategies. Conversely, for men with absence of IDC/CA and low GC scores, de-intensification strategies could be explored.

Keywords: Biomarkers; Cancer; Prostate; Prostatectomy; Radiation therapy.

MeSH terms

Adult
Aged
Cohort Studies
Combined Modality Therapy
Genome
Humans
Male
Middle Aged
Postoperative Period
Prognosis
Prostatectomy*
Prostatic Neoplasms / classification*
Prostatic Neoplasms / genetics
Prostatic Neoplasms / radiotherapy*
Prostatic Neoplasms / surgery