Computationally Derived Image Signature of Stromal Morphology Is Prognostic of Prostate Cancer Recurrence Following Prostatectomy in African American Patients.

Clinical Cancer Research : an Official Journal of the American Association for Cancer Research
Hersh K BhargavaAnant Madabhushi

Abstract

Between 30%-40% of patients with prostate cancer experience disease recurrence following radical prostatectomy. Existing clinical models for recurrence risk prediction do not account for population-based variation in the tumor phenotype, despite recent evidence suggesting the presence of a unique, more aggressive prostate cancer phenotype in African American (AA) patients. We investigated the capacity of digitally measured, population-specific phenotypes of the intratumoral stroma to create improved models for prediction of recurrence following radical prostatectomy. This study included 334 radical prostatectomy patients subdivided into training (VT, n = 127), validation 1 (V1, n = 62), and validation 2 (V2, n = 145). Hematoxylin and eosin-stained slides from resected prostates were digitized, and 242 quantitative descriptors of the intratumoral stroma were calculated using a computational algorithm. Machine learning and elastic net Cox regression models were constructed using VT to predict biochemical recurrence-free survival based on these features. Performance of these models was assessed using V1 and V2, both overall and in population-specific cohorts. An AA-specific, automated stromal signature, AAstro, was prognostic of r...Continue Reading

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Citations

Sep 4, 2020·Current Opinion in Urology·Victor M SchuettfortShahrokh F Shariat
Feb 17, 2021·Nature Biomedical Engineering·Jonathan T C LiuAnant Madabhushi
Apr 4, 2021·Cancer Discovery·Bhavneet BhinderOlivier Elemento

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