Background: Prostate cancer remains the second most common cause of male cancer death in Australia, and this has been increasingly linked to metastatic disease status. Tumour cell migration is required throughout multiple steps of the metastatic cascade. Yet, which molecular key players drive tumour spread and metastatic potential in prostate cancer is not fully understood.
Methods: Prostate cancer cell lines LNCaP and PC-3, which differ in their androgen sensitivity and tumorigenicity, were used as minimally and highly metastatic cancer cell models. RNA was extracted from these models and cDNA generated through reverse transcription. PCR arrays (n=3 per model) were performed to analyse differential gene expression of 84 cell motility genes (plus six reference genes) in the highly metastatic vs. minimally metastatic prostate cancer model. Quality control checked for PCR array reproducibility, reverse transcription control, and genomic DNA contamination control.
Results: The top motility genes that were significantly more highly expressed in the highly metastatic cancer model (PC-3) compared to the minimally metastatic model (LNCaP) were CAV1, FGF2, ITGB2, MET, MMP14, PLD1, RAC2, RND3, TGFB1 and VIM (p values < 0.001). Interestingly, expression of MMP14, Matrix metalloproteinase-14, a transmembrane, zinc metalloprotease capable of degrading the extracellular matrix, was higher than the expression of other proteases from that family (MMP2 and MMP9), in both models, suggestive of the importance of MMP14 in the migration of prostate cancer cells. In contrast, expression of cell motility genes IGF1, PTEN, and STAT3 were lost in the highly metastatic cancer model (PC-3) compared to the minimally metastatic model (LNCaP).
Conclusion: By advancing the understanding of differential expression of cell motility genes in prostate cancer, the project has the potential to contribute to our understanding of the mechanisms of prostate cancer progression, development of alternative therapeutic targets, and identification of novel prognostic markers.