학술논문

Development and validation of a quantitative reactive stroma biomarker (qRS) for prostate cancer prognosis
Document Type
article
Source
Subject
Biomedical and Clinical Sciences
Clinical Sciences
Oncology and Carcinogenesis
Urologic Diseases
Cancer
Aging
Prostate Cancer
Detection
screening and diagnosis
4.2 Evaluation of markers and technologies
4.1 Discovery and preclinical testing of markers and technologies
Biomarkers
Tumor
Humans
Male
Neoplasm Recurrence
Local
Prognosis
Prostate
Prostate-Specific Antigen
Prostatectomy
Prostatic Neoplasms
Retrospective Studies
Stroma
Host response
Biomarker
Pathology
Clinical sciences
Language
Abstract
To develop and validate a new tissue-based biomarker that improves prediction of outcomes in localized prostate cancer by quantifying the host response to tumor. We use digital image analysis and machine learning to develop a biomarker of the prostate stroma called quantitative reactive stroma (qRS). qRS is a measure of percentage tumor area with a distinct, reactive stromal architecture. Kaplan Meier analysis was used to determine survival in a large retrospective cohort of radical prostatectomy samples. qRS was validated in two additional, distinct cohorts that include international cases and tissue from both radical prostatectomy and biopsy specimens. In the developmental cohort (Baylor College of Medicine, n = 482), patients whose tumor had qRS > 34% had increased risk of prostate cancer-specific death (HR 2.94; p = 0.039). This result was replicated in two validation cohorts, where patients with qRS > 34% had increased risk of prostate cancer-specific death (MEDVAMC; n = 332; HR 2.64; p = 0.02) and also biochemical recurrence (Canary; n = 988; HR 1.51; p = 0.001). By multivariate analysis, these associations were shown to hold independent predictive value when compared to currently used clinicopathologic factors including Gleason score and PSA. qRS is a new, validated biomarker that predicts prostate cancer death and biochemical recurrence across three distinct cohorts. It measures host-response rather than tumor-based characteristics, and provides information not represented by standard prognostic measurements.