MP35-09 COMBINATION OF NF-κB/P65 NUCLEAR LOCALIZATION AND GLAND MORPHOLOGIC FEATURES IS PREDICTIVE OF BIOCHEMICAL RECURRENCE

Abstract

You have accessJournal of UrologyProstate Cancer: Markers I1 Apr 2018MP35-09 COMBINATION OF NF-κB/P65 NUCLEAR LOCALIZATION AND GLAND MORPHOLOGIC FEATURES IS PREDICTIVE OF BIOCHEMICAL RECURRENCE Patrick Leo, Eswar Shankar, Robin Elliott, Andrew Janowczyk, Nafiseh Janaki, Gregory MacLennan, Anant Madabhushi, and Sanjay Gupta Patrick LeoPatrick Leo More articles by this author , Eswar ShankarEswar Shankar More articles by this author , Robin ElliottRobin Elliott More articles by this author , Andrew JanowczykAndrew Janowczyk More articles by this author , Nafiseh JanakiNafiseh Janaki More articles by this author , Gregory MacLennanGregory MacLennan More articles by this author , Anant MadabhushiAnant Madabhushi More articles by this author , and Sanjay GuptaSanjay Gupta More articles by this author View All Author Informationhttps://doi.org/10.1016/j.juro.2018.02.1122AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookTwitterLinked InEmail INTRODUCTION AND OBJECTIVES In prostate cancer, clinical management decisions are often based on risk determination with major uncertainty since limited tools are available to understand the risk of disease progression and guide the treatment decision process. Utilizing a combination of quantitative histomorphometric (QH) and biomarker expression features from prostate tissue specimens, we sought to fuse structural and molecular markers to better characterize disease progression and improve prediction of biochemical recurrence (BCR). METHODS Radical prostatectomy specimens (n=23) were used of which 8 were extracted from patients who experienced BCR (PSA > 0.2 ng/ml) within two years of surgery. Digitized H&E slides were annotated for a representative cancerous region, glands were automatically segmented, and 216 features of gland architecture, shape, and orientation disorder were extracted. Nuclei were automatically segmented from NF-κB/p65 stained slides. Based on digitally calculated stain optical density, every nuclei pixel was classified as either negative or weakly, moderately, or strongly positive for NF-κB. We first used the H&E features alone in leave-one-out cross validation with a naive Bayes classifier, using the top two features by t-test in every fold, to obtain a recurrence probability for each patient. We repeated that experiment with the NF-κB/p65 features. We then multiplied together patients’ posterior class probabilities from each model for a final probability. In every fold a probability threshold was identified from the training set to classify patients as BCR or non-BCR. RESULTS The three most predictive H&E features were all gland orientation disorder features. The top NF-κB feature was percentage of nuclei pixels positive for staining (Figure 1). Accuracy was 78% with H&E features alone, 74% with NF-κB features alone, and 87% in the aggregate model. CONCLUSIONS Our results suggest that fusing nuclei NF-κB/p65 and gland morphology information allows for functional and morphologic characterization of prostate cancer, potentially allowing for improved risk characterization and prognosis prediction. © 2018FiguresReferencesRelatedDetails Volume 199Issue 4SApril 2018Page: e450 Advertisement Copyright & Permissions© 2018MetricsAuthor Information Patrick Leo More articles by this author Eswar Shankar More articles by this author Robin Elliott More articles by this author Andrew Janowczyk More articles by this author Nafiseh Janaki More articles by this author Gregory MacLennan More articles by this author Anant Madabhushi More articles by this author Sanjay Gupta More articles by this author Expand All Advertisement Advertisement PDF downloadLoading ...