Transcript analysis of commercial prostate cancer risk stratification panels in hard-to-predict grade group 2-4 prostate cancers
| Autor: | Carolin Stürenberg, Andrew Erickson, Adrian Malen, Hannu Koistinen, Ian G. Mills, Antti Rannikko, Tuomas Mirtti, Timo-Pekka Lehto |
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| Přispěvatelé: | Department of Pathology, University of Helsinki, Helsinki University Hospital Area, Medicum, Department of Clinical Chemistry and Hematology, HUS Abdominal Center, Faculty Common Matters (Faculty of Biology and Environmental Sciences), Clinicum, Urologian yksikkö, Research Program in Systems Oncology, HUSLAB |
| Jazyk: | angličtina |
| Rok vydání: | 2021 |
| Předmět: |
0301 basic medicine
Oncology Male medicine.medical_specialty Urology medicine.medical_treatment 3122 Cancers Youden's J statistic DNA Mutational Analysis prolaris oncotype DX Risk Assessment 03 medical and health sciences Prostate cancer 0302 clinical medicine gene panel SDG 3 - Good Health and Well-being Prostate Internal medicine medicine Clinical endpoint Biomarkers Tumor Humans Aged Retrospective Studies Prostatectomy medicine.diagnostic_test business.industry Area under the curve Prostatic Neoplasms Retrospective cohort study Middle Aged medicine.disease Prognosis 3. Good health Survival Rate decipher 030104 developmental biology medicine.anatomical_structure 030220 oncology & carcinogenesis biomarker Oncotype DX business |
| Zdroj: | Lehto, T-P K, Stürenberg, C, Malén, A, Erickson, A M, Koistinen, H, Mills, I G, Rannikko, A & Mirtti, T 2021, ' Transcript analysis of commercial prostate cancer risk stratification panels in hard-to-predict grade group 2-4 prostate cancers ', Prostate . https://doi.org/10.1002/pros.24108 |
| Popis: | BACKGROUND: Improved prognostication is needed to minimize overtreatment in grade group (GG) 2-4 prostate cancer. Our aim was to determine, at messenger RNA (mRNA) level, the performance of the genes in the commercial panels Decipher, Oncotype DX, Prolaris, and mutational panel MSK-IMPACT to predict metastasis-free and prostate cancer-specific death (PCSD) in patients with GG 2-4 prostate cancer at radical prostatectomy. METHODS: The retrospective cohort consisted of GG 2-4 patients treated with radical prostatectomy (median follow-up 10.4 years). Seventy-six cases with postoperative metastasis or PCSD and 84 controls with similar clinical baseline risk, but without progression, were analyzed. Index lesion mRNA transcripts were analyzed using NanoString technology. Random forest models were trained using panel gene sets to predict clinical endpoints and area under the curve (AUC), sensitivity, specificity, Youden index, and number needed to diagnose (NND) was measured. Survival probability was assessed with Kaplan-Meier estimator. RESULTS: All gene sets outperformed clinical parameters and predicted metastasis-free and prostate cancer-specific survival. However, there were significant differences between the panels. In metastasis prediction, the genes in Oncotype DX had inferior performance (area under the curve [AUC] = 0.65) compared to other panels (AUC = 0.73-0.74). Decipher, MSK-IMPACT and Prolaris showed similar NND (2.83-3.12) with Oncotype DX having highest NND (4.79). In PCSD prediction, the Prolaris gene set performed worse (AUC = 0.66) than MSK-IMPACT or Decipher (AUC = 0.72). Oncotype DX performed similarly to other panels (AUC = 0.69, p > .05). Oncotype DX demonstrated lowest NND (2.79) compared to other panels (4.22-5.66). CONCLUSION: Transcript analysis of genes included in commercial panels is feasible in survival prediction of GG 2-4 patients after radical prostatectomy and may aid in clinical decision making. There were significant differences between the panels, and overall stronger predictive gene sets are needed. Prospective investigation is warranted in biopsy materials. |
| Databáze: | OpenAIRE |
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