Key result
Stromal periostin expression correlates with aggressive prostate cancer features, and circulating periostin and sparc levels improve prediction of disease reclassification in active surveillance.
Why the study?
Reactive stroma fosters aggressive prostate cancer, suggesting reactive stroma-based biomarkers could potentially improve the early detection of aggressive disease and disease classification.
Does the assessment of periostin and sparc biomarkers improve risk assessment and predict disease reclassification in patients with prostate cancer?
Cohort
Does the assessment of periostin and sparc biomarkers improve risk assessment and predict disease reclassification in patients with prostate cancer?
Answers are grounded in this paper and cite their sources.
Circulating molecular biomarkers of prostate cancer stroma, specifically periostin and sparc, may refine risk assessment and predict the reclassification of patients on active surveillance.
Prostate cancer (PCa) ranges from indolent to aggressive tumors that may rapidly progress and metastasize. The switch to aggressive PCa is fostered by reactive stroma infiltrating tumor foci. Therefore, reactive stroma-based biomarkers may potentially improve the early detection of aggressive PCa, ameliorating disease classification. Gene expression profiles of PCa reactive fibroblasts highlighted the up-regulation of genes related to stroma deposition, including periostin and sparc. Here, the potential of periostin as a stromal biomarker has been investigated on PCa prostatectomies by immunohistochemistry. Moreover, circulating levels of periostin and sparc have been assessed in a low-risk PCa patient cohort enrolled in active surveillance (AS) by ELISA. We found that periostin is mainly expressed in the peritumoral stroma of prostatectomies, and its stromal expression correlates with PCa grade and aggressive disease features, such as the cribriform growth. Moreover, stromal periostin staining is associated with a shorter biochemical recurrence-free survival of PCa patients. Interestingly, the integration of periostin and sparc circulating levels into a model based on standard clinico-pathological variables improves its performance in predicting disease reclassification of AS patients. In this study, we provide the first evidence that circulating molecular biomarkers of PCa stroma may refine risk assessment and predict the reclassification of AS patients.
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Doldi et al. (2022) conducted a cohort in Prostate cancer. Periostin and sparc expression/circulating levels was evaluated on Disease reclassification and biochemical recurrence-free survival. Stromal periostin expression correlates with aggressive prostate cancer features, and circulating periostin and sparc levels improve prediction of disease reclassification in active surveillance.
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