Generation of an in vitro 3D PDAC stroma rich spheroid model

Pancreatic ductal adenocarcinoma (PDAC) is characterized by a prominent desmoplastic/stromal reaction, which contributes to the poor clinical outcome of this disease. Therefore, greater understanding of the stroma development and tumor-stroma interactions is highly required. Pancreatic stellate cells (PSC) are myofibroblast-like cells that located in exocrine areas of the pancreas, which as a result of inflammation produced by PDAC migrate and accumulate in the tumor mass, secreting extracellular matrix components and producing the dense PDAC stroma. Currently, only a few orthotopic or ectopic animal tumor models, where PDAC cells are injected into the pancreas or subcutaneous tissue layer, or genetically engineered animals offer tumors that encompass some stromal component. Herein, we report generation of a simple 3D PDAC in vitro micro-tumor model without an addition of external extracellular matrix, which encompasses a rich, dense and active stromal compartment. We have achieved this in vitro model by incorporating PSCs into 3D PDAC cell culture using a modified hanging drop method. It is now known that PSCs are the principal source of fibrosis in the stroma and interact closely with cancer cells to create a tumor facilitatory environment that stimulates local and distant tumor growth. The 3D micro-stroma models are highly reproducible with excellent uniformity, which can be used for PDAC-stroma interaction analysis and high throughput automated drug-screening assays. Additionally, the increased expression of collagenous regions means that molecular based perfusion and cytostaticity of gemcitabine is decreased in our Pancreatic adenocarcinoma stroma spheroids (PDAC-SS) model when compared to spheroids grown without PSCs. We believe this model will allow an improved knowledge of PDAC biology and has the potential to provide an insight into pathways that may be therapeutically targeted to inhibit PSC activation, thereby inhibiting the development of fibrosis in PDAC and interrupting PSC-PDAC cell interactions so as to inhibit cancer progression

Cytoplasmic Accumulation of Glycogen Synthase Kinase-3 beta Is Associated with Aggressive Clinicopathological Features in Human Prostate Cancer

Background: Activation of glycogen synthase kinase-3 (GSK-3) is involved in the regulation of cell growth, differentiation, mobility, proliferation and survival. However, its clinicopathologic significance remains unclear in prostate cancer (PCa). Materials and Methods: A tissue microarray was produced from 640 samples. Sections were immunostained with an antibody against the non-phosphorylated form of GSK-3(GSK-3 beta) and were digitized. Spearman correlation test was processed for correlations between GSK-3 and biological and clinicopathological variables. The prognostic value of GSK-3 beta was analyzed by Cox Regression model. Results: Cytoplasmic GSK-3 beta was higher in PCa than in normal prostate (mean expression index 4.55 vs. 3.50, p<0.0001). Conversely, nuclear expression was higher in normal prostate than that in PCa (3.38 vs. 2.04, p<0.0001). Cytoplasmic levels of GSK-3 beta were correlated with clinical stage (rho=0.095, p=0.0337), lymph node metastasis (rho=0.116, p=0.0096), extracapsular extension (rho=0.092, p=0.0392), and Gleason score (rho=0.167, p=0.0002). Increased cytoplasmic GSK-3 beta expression was correlated with high Ki-67 labeling index (rho=0.319, p<0.0001), low apoptotic index by TUNEL (rho=-0.118, p=0.0134), high levels of androgen receptor (rho=0.292, p<0.0001) and p-Akt (rho=0.396, p<0.0001). Patients with higher cytoplasmic levels of GSK-3 beta had a twofold risk of biochemical recurrence-free survival compared to those with lower levels of GSK-3 beta [HR 1.934 (1.020-3.667), p=0.043]. Conclusion: Cytoplasmic accumulation of GSK-3 beta is potentially associated with a pro-survival mechanism that promotes PCa development and progression

Prognostic Value of Akt-1 in Human Prostate Cancer: A Computerized Quantitative Assessment with Quantum Dot Technology

Abstract Background: Akt/protein kinase B signaling pathway has been implicated in tumorigenesis and progression. Previous studies showed the predictive potential of p-Akt-1, but total Akt-1 could provide more reliable information. We used image deconvolution, nanotechnology (quantum dots), and image analysis to improve Akt-1 quantification. Design: This tissue microarray study included 840 radical prostatectomy cases. Slides were incubated with primary antibody against nonphosphorylated Akt-1 (Akt-1) followed by biotinylated secondary antibody and then by Qdot655 streptavidin conjugate. Slides were imaged under fluorescence microscopy and spectral deconvolution (Nuance) and quantified using plug-in image analysis software. Average intensity of Akt-1 signal was measured and subject to statistical analysis. Multivariate analysis (Cox regression) was applied to assess the prognostic value of Akt-1 for biochemical recurrence and prostate cancer-specific death. Akt-1 expression was also examined for correlations with Ki-67 index and apoptotic index in our database. Result: Akt-1 was inversely correlated with apoptotic index (ρ = −0.203; P = 0.004) but not with Ki-67 index. The correlation between Akt and p-Akt is significant but weak (P = 0.0496; R2 = 0.118). On multivariate analysis Akt-1 was independently predictive of biochemical recurrence [hazard ratio, 2.863 (95% confidence interval, 1.127-7.271); P = 0.0270]. Akt-1 level is also predictive of prostate cancer-specific death (P = 0.0376). Conclusion: High levels of Akt-1, assessed by quantum dots, deconvolution imaging, and image analysis, are associated with a higher risk of biochemical recurrence and prostate cancer-specific death.</jats:p

Moving Beyond Gleason Scoring

Context.—The combination of grading and staging is the basis of current standard of care for prediction for most cancers. D. F. Gleason created the current prostate cancer (PCa) grading system. This system has been modified several times. Molecular data have been added. Currently, all grading systems are cancer-cell based.Objective.—To review the literature available on host response measures as reactive stroma grading and stromogenic carcinoma, and their predictive ability for PCa biochemical recurrence and PCa-specific death.Data Sources.—Our own experience has shown that reactive stroma grading and the subsequently binarized system (stromogenic carcinoma) can independently predict biochemical recurrence and/or PCa-specific death, particularly in patients with a Gleason score of 6 or 7. Stromogenic carcinoma has been validated by 4 other independent groups in at least 3 continents.Conclusions.—Broders grading and Dukes staging have been combined to form the most powerful prognostic tools in standard of care. The time has come for us to incorporate measures of host response (stromogenic carcinoma) into the arsenal of elements we use to predict cancer survival, without abandoning what we know works. These data also suggest that our current definition of PCa might need some revision.</jats:sec

Development and validation of a quantitative reactive stroma biomarker (qRS) for prostate cancer prognosis

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&nbsp;=&nbsp;482), patients whose tumor had qRS &gt; 34% had increased risk of prostate cancer-specific death (HR 2.94; p&nbsp;=&nbsp;0.039). This result was replicated in two validation cohorts, where patients with qRS &gt; 34% had increased risk of prostate cancer-specific death (MEDVAMC; n&nbsp;=&nbsp;332; HR 2.64; p&nbsp;=&nbsp;0.02) and also biochemical recurrence (Canary; n&nbsp;=&nbsp;988; HR 1.51; p&nbsp;=&nbsp;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