Low Grade CaP Research Articles

Diagnostic molecular markers predicting aggressive potential in low-grade prostate cancer

Currently, clinicians rely on clinical nomograms to stratify progression risk at the time of diagnosis in patients with prostate cancer (CaP). However, these tools may not accurately distinguish aggressive potential in low-grade CaP. The current study determined the diagnostic potential of 3 molecular markers (ROCK1, RUNX3, and miR-301a) in terms of their ability to identify which low-grade tumors are likely to progress. Real-time PCR and immunohistochemical analysis were used to assess ROCK1, RUNX3, and miR-301a expression profiles in 118 serum and needle biopsy specimens. Expressions of ROCK1 and miR-301a were found to be significantly higher in Gleason 6 and 7 CaP as compared to BPH, while an inverse trend was observed with RUNX3. Further, incorporation of all 3 molecular markers significantly improved clinical nomograms' diagnostic accuracy and correlated with disease progression. Hence, in conclusion, the inclusion of these 3 molecular markers identified aggressive phenotype and predicted disease progression in low-grade CaP tumors at the time of diagnosis.

Bioptic intraprostatic chronic inflammation predicts adverse pathology at radical prostatectomy in patients with low-grade prostate cancer

PurposeTo determine the potential role of bioptic inflammation (Irani score) in predicting adverse pathology (AP) at radical prostatectomy (RP) in patients with low-grade (ISUP Gleason Group [ISUP GG] 1 and 2) prostate cancer (CaP). MethodsAfter institutional review board-approval, we identified patients who underwent prostate biopsy, had bioptic Irani score assessment, were diagnosed with low-grade CaP (ISUP GG 1–2, prostate-specific antigen [PSA] <20 ng/ml), and underwent RP. The impact of standard clinicopathological variables and bioptic Irani Score (G = grade and A = aggressiveness) on AP at RP, defined as stage ≥T3 and/or ISUP GG ≥3, was assessed by univariate and multivariate logistic regression analysis. ResultsA total of 282 patients were eligible for this study. AP at RP occurred in 37 of 214 (17.3%) patients with ISUP GG 1, and 26 of 68 (38.2%) with ISUP GG 2. At univariate analysis, serum PSA, PSA density, bioptic ISUP GG, number of positive cores, total percentage of core involvement and Irani G score emerged as significant risk factors of AP. At multivariate analysis, however, only PSA density, bioptic ISUP GG, total percentage of core, and Irani G score kept statistical significance. The area under the curve for the resulting model was 0.75. ConclusionsThis is the first study demonstrating that low-grade inflammation is associated with a significantly increased risk of AP at RP. These findings would support the concept of prostatic inflammation being inversely correlated with presence and aggressiveness of CaP. Further studies are needed to externally validate the role of this readily available parameter in the decision-making process of patients with low-grade CaP.

Overexpression of periostin in stroma positively associated with aggressive prostate cancer.

BackgroundPeriostin is an important extracellular matrix protein involved in cell development and adhesion. Previously, we identified periostin to be up-regulated in aggressive prostate cancer (CaP) using quantitative glycoproteomics and mass spectrometry. The expression of periostin was further evaluated in primary radical prostatectomy (RP) prostate tumors and adjacent non-tumorous prostate tissues using immunohistochemistry (IHC). Our IHC results revealed a low background periostin levels in the adjacent non-tumorous prostate tissues, but overexpressed periostin levels in the peritumoral stroma of primary CaP tumors.MethodsIn this study, periostin expression in CaP was further examined on multiple tissue microarrays (TMAs), which were conducted in four laboratories. To achieve consistent staining, all TMAs were stained with same protocol and scored by same image computation tool to determine the total periostin staining intensities. The TMAs were further scored by pathologists to characterize the stromal staining and epithelial staining.ResultsThe periostin staining was observed mainly in peritumoral stromal cells and in some cases in tumor epithelial cells though the stronger staining was found in peritumoral stromal cells. Both periostin stromal staining and epithelial staining can differentiate BPH from CaP including low grade CaP (Gleason score ≤6), with significant p-value of 2.2e-16 and 0.001, respectively. Periostin epithelial staining differentiated PIN from low grade CaP (Gleason score ≤6) (p=0.001), while periostin stromal staining differentiated low grade Cap (Gleason score ≤6) from high grade Cap (Gleason score ≤6) (p=1.7e-05). In addition, a positive correlation between total periostin staining and Gleason score was observed (r=0.87, p=0.002).ConclusionsThe results showed that periostin staining was positively correlated with increasing Gleason score and the aggressiveness of prostate disease.

Multi-kernel graph embedding for detection, Gleason grading of prostate cancer via MRI/MRS

Even though 1 in 6 men in the US, in their lifetime are expected to be diagnosed with prostate cancer (CaP), only 1 in 37 is expected to die on account of it. Consequently, among many men diagnosed with CaP, there has been a recent trend to resort to active surveillance (wait and watch) if diagnosed with a lower Gleason score on biopsy, as opposed to seeking immediate treatment. Some researchers have recently identified imaging markers for low and high grade CaP on multi-parametric (MP) magnetic resonance (MR) imaging (such as T2 weighted MR imaging (T2w MRI) and MR spectroscopy (MRS)). In this paper, we present a novel computerized decision support system (DSS), called Semi Supervised Multi Kernel Graph Embedding (SeSMiK-GE), that quantitatively combines structural, and metabolic imaging data for distinguishing (a) benign versus cancerous, and (b) high- versus low-Gleason grade CaP regions from in vivo MP-MRI. A total of 29 1.5Tesla endorectal pre-operative in vivo MP MRI (T2w MRI, MRS) studies from patients undergoing radical prostatectomy were considered in this study. Ground truth for evaluation of the SeSMiK-GE classifier was obtained via annotation of disease extent on the pre-operative imaging by visually correlating the MRI to the ex vivo whole mount histologic specimens. The SeSMiK-GE framework comprises of three main modules: (1) multi-kernel learning, (2) semi-supervised learning, and (3) dimensionality reduction, which are leveraged for the construction of an integrated low dimensional representation of the different imaging and non-imaging MRI protocols. Hierarchical classifiers for diagnosis and Gleason grading of CaP are then constructed within this unified low dimensional representation. Step 1 of the hierarchical classifier employs a random forest classifier in conjunction with the SeSMiK-GE based data representation and a probabilistic pairwise Markov Random Field algorithm (which allows for imposition of local spatial constraints) to yield a voxel based classification of CaP presence. The CaP region of interest identified in Step 1 is then subsequently classified as either high or low Gleason grade CaP in Step 2. Comparing SeSMiK-GE with unimodal T2w MRI, MRS classifiers and a commonly used feature concatenation (COD) strategy, yielded areas (AUC) under the receiver operative curve (ROC) of (a) 0.89±0.09 (SeSMiK), 0.54±0.18 (T2w MRI), 0.61±0.20 (MRS), and 0.64±0.23 (COD) for distinguishing benign from CaP regions, and (b) 0.84±0.07 (SeSMiK),0.54±0.13 (MRI), 0.59±0.19 (MRS), and 0.62±0.18 (COD) for distinguishing high and low grade CaP using a leave one out cross-validation strategy, all evaluations being performed on a per voxel basis. Our results suggest that following further rigorous validation, SeSMiK-GE could be developed into a powerful diagnostic and prognostic tool for detection and grading of CaP in vivo and in helping to determine the appropriate treatment option. Identifying low grade disease in vivo might allow CaP patients to opt for active surveillance rather than immediately opt for aggressive therapy such as radical prostatectomy.

Clusterin (SGP-2, ApoJ) expression is downregulated in low- and high-grade human prostate cancer.

Clusterin is overexpressed during tissue and cell involution and downregulated in proliferating cells. Its role in cell survival, cell death and neoplastic transformation remains debated. We studied the expression and distribution of clusterin mRNA and protein in human prostate carcinoma (CaP) specimens of different degrees of malignancy. Fresh CaP specimens were obtained from 25 patients subjected to long-term androgen ablation before surgery. Clusterin expression was studied by Northern and Western analysis, in situ hybridization and immunohistochemistry, in comparison with Gas1 and histone H3 mRNA (markers of cell quiescence and S phase of the cell cycle, respectively). Clusterin is downregulated in CaP in comparison with matched benign controls. In low-grade CaP, clusterin colocalized with Gas1 to the stromal compartment, and in some glands, the basal lamina was heavily stained. In high-grade CaP clusterin stained the remnants of stromal matrix while histone H3 localized to cancer cells, which were very rarely clusterin positive. High clusterin expression was found in the branches of a nerve infiltrated by tumor. The periglandular clusterin expression found in low-grade CaP could result from induction of quiescence and/or apoptosis of prostatic fibroblasts lining those glands in which tumor invasion is at an initial stage, involving basal lamina. In advanced CaP, the staining of the remnants of the extracellular matrix suggests a role for clusterin in the process of dismantling the stromal organization caused by cancer progression.