Targeted Therapies for Prostate Cancer

Let’s Go 3D! New Generation of Models for Evaluating Drug Response and Resistance in Prostate Cancer

Prostate cancer (PC) is the third most frequently diagnosed cancer worldwide and the second most frequent in men. Several risk factors can contribute to the development of PC, and those include age, family history, and specific genetic mutations. So far, drug testing in PC, as well as in cancer research in general, has been performed on 2D cell cultures. This is mainly because of the vast benefits these models provide, including simplicity and cost effectiveness. However, it is now known that these models are exposed to much higher stiffness; lose physiological extracellular matrix on artificial plastic surfaces; and show changes in differentiation, polarization, and cell–cell communication. This leads to the loss of crucial cellular signaling pathways and changes in cell responses to stimuli when compared to in vivo conditions. Here, we emphasize the importance of a diverse collection of 3D PC models and their benefits over 2D models in drug discovery and screening from the studies done so far, outlining their benefits and limitations. We highlight the differences between the diverse types of 3D models, with the focus on tumor–stroma interactions, cell populations, and extracellular matrix composition, and we summarize various standard and novel therapies tested on 3D models of PC for the purpose of raising awareness of the possibilities for a personalized approach in PC therapy.

Bone Progenitors Pull the Strings on the Early Metabolic Rewiring Occurring in Prostate Cancer Cells

Metastatic prostate cancer (PCa) cells soiling in the bone require a metabolic adaptation. Here, we identified the metabolic genes fueling the seeding of PCa in the bone niche. Using a transwell co-culture system of PCa (PC3) and bone progenitor cells (MC3T3 or Raw264.7), we assessed the transcriptome of PC3 cells modulated by soluble factors released from bone precursors. In a Principal Component Analysis using transcriptomic data from human PCa samples (GSE74685), the altered metabolic genes found in vitro were able to stratify PCa patients in two defined groups: primary PCa and bone metastasis, confirmed by an unsupervised clustering analysis. Thus, the early transcriptional metabolic profile triggered in the in vitro model has a clinical correlate in human bone metastatic samples. Further, the expression levels of five metabolic genes (VDR, PPARA, SLC16A1, GPX1 and PAPSS2) were independent risk-predictors of death in the SU2C-PCF dataset and a risk score model built using this lipid-associated signature was able to discriminate a subgroup of bone metastatic PCa patients with a 23-fold higher risk of death. This signature was validated in a PDX pre-clinical model when comparing MDA-PCa-183 growing intrafemorally vs. subcutaneously, and appears to be under the regulatory control of the Protein Kinase A (PKA) signaling pathway. Secretome analyses of conditioned media showcased fibronectin and type-1 collagen as critical bone-secreted factors that could regulate tumoral PKA. Overall, we identified a novel lipid gene signature, driving PCa aggressive metastatic disease pointing to PKA as a potential hub to halt progression.

COPB2 Is Upregulated in Prostate Cancer and Regulates PC-3 Cell Proliferation, Cell Cycle, and Apoptosis

BACKGROUND AND AIMS

Transport of membranes and proteins in eukaryotic cells is mediated by vesicular carriers. Coatomer complex I (COPI)-coated vesicles are involved in the transport between endoplasmic reticulum (ER) and Golgi complex. Several studies indicated that some subunits of COPI were correlated with the cell proliferation of malignant tumors. The present study focused on the function of coatomer protein complex subunit β 2 (COPB2), one of seven proteins in COPI, in prostate cancer (PCa).

METHODS

COPB2 gene expression was first analyzed by immunohistochemistry (IHC) in 15 paired PCa and carcinoma adjacent normal tissue from patients. To investigate the role of COPB2 in PCa, we used lentivirus-mediated small interfering RNA (siRNA) to knockdown COPB2 expression in human PCa cell line PC-3 and assessed it by RT-qPCR. Cellomics ArrayScan VTI imaging and colony formation were conducted to evaluate cell proliferation. Cell cycle phase arrest and apoptosis were assayed by flow cytometry.

RESULTS

COPB2 gene was upregulated in the PCa tissue. Cell proliferation was significantly inhibited in COPB2-silenced PC-3 cells using both Cellomics ArrayScan VTI imaging and colony formation assays. S-phase cell counts were significantly decreased; G1- and G2-phase cell counts were significantly increased in COPB2-siRNA group than the control group. Apoptosis was significantly increased in COPB2-siRNA cells.

CONCLUSIONS

COPB2 significantly promoted PC-3 cell proliferation and colony formation through the cell cycle and apoptosis pathway. Moreover, COPB2 showed a clinical correlation and may serve as a biomarker for the detection for PCa.