Proteomic-based stratification of intermediate-risk prostate cancer patients

Author:

Zhong QingORCID,Rui Sun,Aref Adel T.,Noor ZainabORCID,Anees Asim,Zhu Yi,Lucas Natasha,Poulos Rebecca C.,Lyu Mengge,Zhu Tiansheng,Wang Bo,Chen Guo-Bo,Wang Yingrui,Ding Xuan,Rutishauser Dorothea,Rupp Niels J.,Rueschoff Jan H.,Poyet Cédric,Hermanns Thomas,Fankhauser Christian,Martínez María Rodríguez,Shao Wenguang,Buljan Marija,Neumann Janis Frederick,Beyer Andreas,Hains Peter G.,Reddel Roger R.,Robinson Phillip J.,Aebersold Ruedi,Guo Tiannan,Wild Peter J.

Abstract

ABSTRACTGleason grading is an important prognostic indicator for prostate adenocarcinoma and is crucial for patient treatment decisions. However, intermediate-risk patients diagnosed in Gleason Grade Groups (GG) 2 and GG3 can harbour either aggressive or non-aggressive disease, resulting in under- or over-treatment of a significant number of patients. Here, we performed proteomic, differential expression, machine learning, and survival analyses for 1,348 matched tumour and benign sample runs from 278 patients. Three proteins (F5, TMEM126B and EARS2) were identified as candidate biomarkers in patients with biochemical recurrence. Multivariate Cox regression yielded 18 proteins, from which a risk score was constructed to dichotomise prostate cancer patients into low- and high-risk groups. This 18-protein signature is prognostic for the risk of biochemical recurrence and completely independent of the intermediate GG. Our results suggest that markers generated by computational proteomic profiling have the potential for clinical applications including integration into prostate cancer management.

Publisher

Cold Spring Harbor Laboratory

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