Abstract
Semiquantitative reactive stromal grading has been shown to be a predictor of biochemical recurrence and prostate cancer (PCa) specific death. It has been extensively validated. In this study we tested novel technologies to introduce quantitative measures of host response, in particular collagen content and stromal cellularity. We use 3 large retrospective cohorts, the Baylor College of Medicine cohort, the Brady cohort and the Pound cohort. Slides were stained and digitized using image deconvolution and analyzed using image segmentation and image analyses. PicroSirius red stain histochemical stains were used for collagen quantification. Area of cancer and stroma were measured independently, without regard to quality of stroma. Cellularity, in each compartment, was measured using image deconvolution, image segmentation and image analysis. Two biomarkers were tested in 3 independent cohorts with two endpoints, biochemical recurrence and prostate cancer specific death. Stromal cellularity (qCollCell) and stromal collagen area (qCollArea) are independently predictive biochemical recurrence in the Hopkins Brady cohort, particularly in Gleason 6–7 patients. Multivariate analysis demonstrated that increased stroma cellularity (qCollCell) was a significant predictor of PCa specific death, when compared to an established model of PCa, in the Baylor cohort. Stromal collagen (qCollArea) independently predicts PCa-specific death in the Hopkins Pound cohort. The introduction of a computerized quantitative test of the host response increases the probability that this test will be reproducible in other cohorts. The ability to improve prediction of prostate cancer specific death might lie in the study of the host and its response.
Original language | English (US) |
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Pages (from-to) | 1-7 |
Number of pages | 7 |
Journal | Human Pathology |
Volume | 144 |
Early online date | Dec 28 2023 |
DOIs | |
State | Published - Feb 2024 |
Keywords
- Collagen
- Host response
- Prediction
- Prostate cancer
- Reactive stroma
ASJC Scopus subject areas
- Pathology and Forensic Medicine