Abstract
PurposeMolecular characterization of prostate cancer, including The Cancer Genome Atlas, has revealed distinct subtypes with underlying genomic alterations. One of these core subtypes, SPOP (speckle-type POZ protein) mutant prostate cancer, has previously only been identifiable via DNA sequencing, which has made the impact on prognosis and routinely used risk stratification parameters unclear.MethodsWe have developed a novel gene expression signature, classifier (Subclass Predictor Based on Transcriptional Data), and decision tree to predict the SPOP mutant subclass from RNA gene expression data and classify common prostate cancer molecular subtypes. We then validated and further interrogated the association of prostate cancer molecular subtypes with pathologic and clinical outcomes in retrospective and prospective cohorts of 8,158 patients.ResultsThe subclass predictor based on transcriptional data model showed high sensitivity and specificity in multiple cohorts across both RNA sequencing and microarray...
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CITATION STYLE
Liu, D., Takhar, M., Alshalalfa, M., Erho, N., Shoag, J., Jenkins, R. B., … Barbieri, C. E. (2018). Impact of the SPOP Mutant Subtype on the Interpretation of Clinical Parameters in Prostate Cancer. JCO Precision Oncology, (2), 1–13. https://doi.org/10.1200/po.18.00036
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