CD151 is associated with prostate cancer cell invasion and lymphangiogenesis in vivo

CD151, a member of the tetraspanin family, is associated with regulation of migration of normal and tumour cells via cell surface microdomain formation. CD151 was found in our laboratory to have a prognostic value in prostate cancer and is a promoter of prostate cancer migration and invasion. These roles involve association with integrins on both cell-cell and cell-stroma levels. Furthermore, CD151 plays a role in endothelial cell motility. CD151 expression was examined in three commonly used prostate cancer cell lines. We investigated CD151 expression, angiogenesis (microvessel density; MVD) and lymphangiogenesis (lymphatic vessel density; LVD) in an orthotopic xenograft model of prostate cancer in matched tumours from primary and secondary sites. CD151 was found to be heterogeneously expressed across different prostate cancer cell lines and the levels of CD151 expression were significantly higher in the highly tumorigenic, androgen-insensitive cells PC-3 and DU-145 compared to the androgen-sensitive cell line LNCaP (P<0.05). The majority of in vivo xenografts developed pelvic lymph node metastases. Importantly, primary tumours that developed metastasis had significantly higher CD151 expression and MVD compared to those which did not develop metastasis (P<0.05). We identified, for the first time, that CD151 expression is associated with LVD in prostate cancer. These findings underscore the potential role of CD151 and angiogenesis in the metastatic potential of prostate cancer. CD151 has a prognostic value in this mouse model of prostate cancer and may play a role in lymphangiogenesis. CD151 is likely an important regulator of cancer cell communication with the surrounding microenvironment

Network analysis of an in vitro model of androgen-resistance in prostate cancer

BACKGROUND: The development of androgen resistance is a major limitation to androgen deprivation treatment in prostate cancer. We have developed an in vitro model of androgen-resistance to characterise molecular changes occurring as androgen resistance evolves over time. Our aim is to understand biological network profiles of transcriptomic changes occurring during the transition to androgen-resistance and to validate these changes between our in vitro model and clinical datasets (paired samples before and after androgen-deprivation therapy of patients with advanced prostate cancer). METHODS: We established an androgen-independent subline from LNCaP cells by prolonged exposure to androgen-deprivation. We examined phenotypic profiles and performed RNA-sequencing. The reads generated were compared to human clinical samples and were analysed using differential expression, pathway analysis and protein-protein interaction networks. RESULTS: After 24 weeks of androgen-deprivation, LNCaP cells had increased proliferative and invasive behaviour compared to parental LNCaP, and its growth was no longer responsive to androgen. We identified key genes and pathways that overlap between our cell line and clinical RNA sequencing datasets and analysed the overlapping protein-protein interaction network that shared the same pattern of behaviour in both datasets. Mechanisms bypassing androgen receptor signalling pathways are significantly enriched. Several steroid hormone receptors are differentially expressed in both datasets. In particular, the progesterone receptor is significantly differentially expressed and is part of the interaction network disrupted in both datasets. Other signalling pathways commonly altered in prostate cancer, MAPK and PI3K-Akt pathways, are significantly enriched in both datasets. CONCLUSIONS: The overlap between the human and cell-line differential expression profiles and protein networks was statistically significant showing that the cell-line model reproduces molecular patterns observed in clinical castrate resistant prostate cancer samples, making this cell line a useful tool in understanding castrate resistant prostate cancer. Pathway analysis revealed similar patterns of enriched pathways from differentially expressed genes of both human clinical and cell line datasets. Our analysis revealed several potential mechanisms and network interactions, including cooperative behaviours of other nuclear receptors, in particular the subfamily of steroid hormone receptors such as PGR and alteration to gene expression in both the MAPK and PI3K-Akt signalling pathways

Network analysis of an in vitro model of androgen-resistance in prostate cancer

BACKGROUND: The development of androgen resistance is a major limitation to androgen deprivation treatment in prostate cancer. We have developed an in vitro model of androgen-resistance to characterise molecular changes occurring as androgen resistance evolves over time. Our aim is to understand biological network profiles of transcriptomic changes occurring during the transition to androgen-resistance and to validate these changes between our in vitro model and clinical datasets (paired samples before and after androgen-deprivation therapy of patients with advanced prostate cancer). METHODS: We established an androgen-independent subline from LNCaP cells by prolonged exposure to androgen-deprivation. We examined phenotypic profiles and performed RNA-sequencing. The reads generated were compared to human clinical samples and were analysed using differential expression, pathway analysis and protein-protein interaction networks. RESULTS: After 24 weeks of androgen-deprivation, LNCaP cells had increased proliferative and invasive behaviour compared to parental LNCaP, and its growth was no longer responsive to androgen. We identified key genes and pathways that overlap between our cell line and clinical RNA sequencing datasets and analysed the overlapping protein-protein interaction network that shared the same pattern of behaviour in both datasets. Mechanisms bypassing androgen receptor signalling pathways are significantly enriched. Several steroid hormone receptors are differentially expressed in both datasets. In particular, the progesterone receptor is significantly differentially expressed and is part of the interaction network disrupted in both datasets. Other signalling pathways commonly altered in prostate cancer, MAPK and PI3K-Akt pathways, are significantly enriched in both datasets. CONCLUSIONS: The overlap between the human and cell-line differential expression profiles and protein networks was statistically significant showing that the cell-line model reproduces molecular patterns observed in clinical castrate resistant prostate cancer samples, making this cell line a useful tool in understanding castrate resistant prostate cancer. Pathway analysis revealed similar patterns of enriched pathways from differentially expressed genes of both human clinical and cell line datasets. Our analysis revealed several potential mechanisms and network interactions, including cooperative behaviours of other nuclear receptors, in particular the subfamily of steroid hormone receptors such as PGR and alteration to gene expression in both the MAPK and PI3K-Akt signalling pathways. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12885-015-1884-7) contains supplementary material, which is available to authorized users

Abstract B1-40: Biological network analysis using an in vitro model of androgen-resistance in prostate cancer

Abstract The development of androgen resistance is a major limitation to androgen deprivation treatment in prostate cancer (PCa). We have developed an in vitro model of androgen-resistance using the androgen sensitive cell line LNCaP to characterize the phenotypic and transcriptomic changes occurring as androgen resistance develops. Our aim is to understand biological network profiles of transcriptomic changes during the transition to androgen-resistance and to validate these changes between our in vitro model and previously published clinical datasets (paired samples before and after androgen-deprivation therapy of patients with advanced PCa) (1). Methods: PCa cells, LNCaP, expressing mutated AR which are androgen-dependent (2,3), are used in the development of an androgen-resistant subline. Subline cells were established by prolonged cultures in media + 10% CS-FBS to mimic the clinical course of PCa. Cell proliferation, cell motility and invasion, morphology, AR expression were examined. RNA-sequencing was performed using the parental LNCaP cells and an androgen-resistant subline (LNCaP-AI) established by chronic exposure to the androgen-deprivation. Reads from cells and clinical samples (1), pre- vs. post-treatment, were processed through the same standard pipeline and quality control. Data outputs were analysed as differential expression [DEG] (EdgeR) (4) and top scoring protein-protein interaction (PPI) networks [PINA2 (5) and BioNet (6)]. Data outputs from the cell line model and clinical samples were compared. Results: LNCaP cells initially showed poor growth after prolonged exposure to androgen-deprived conditions but later adapted and started to grow well. After 24 weeks of androgen-deprivation, LNCaP-AI's growth was no longer responsive to addition of androgen [0.1 - 10 nM]. AR expression was not different in LNCaP and LNCaP-AI (P&amp;gt;0.05). LNCaP-AI cells had increased proliferation and cell invasion compared to LNCaP. We identified key genes that overlap between our cell line and clinical RNAseq (1) datasets and analyzed the overlapping PPI network that showed the same pattern of behavior in both datasets. The network revealed several potential mechanisms and gene interactions that warrant further investigation, including cooperative behaviors of other nuclear receptors, TP63 mediated signalling pathway and Aryl hydrocarbon receptor transcriptional pathway. Conclusion: Cell line model of androgen-resistance will be used for further longitudinal study of the mechanism of castrate resistant prostate cancer (CRPC). Our approach allows for better characterization of biological processes of CRPC. Knowledge of the genetic profiles during transition to androgen resistance will improve our understanding of this common clinical scenario and may lead to biomarker discovery. References: 1. Rajan P, Sudbery IM, Villasevil ME, Mui E, Fleming J, Davis M, et al. Next-generation sequencing of advanced prostate cancer treated with androgen-deprivation therapy. Eur Urol 2013;66(1):32-9. 2. Marques RB, van Weerden WM, Erkens-Schulze S, de Ridder CM, Bangma CH, Trapman J, et al. The human PC346 xenograft and cell line panel: A model system for prostate cancer progression. Eur Urol 2006;49(2):245-57. 3. Pienta KJ, Bradley D. Mechanisms underlying the development of androgen-independent prostate cancer. Clin Cancer Res 2006;12(6):1665-71. 4. Robinson MD, McCarthy DJ, Smyth GK. edgeR: a Bioconductor package for differential expression analysis of digital gene expression data. Bioinformatics 2010;26(1):139-40. 5. Cowley MJ, Pinese M, Kassahn KS, Waddell N, Pearson JV, Grimmond SM, et al. PINA v2.0: mining interactome modules. Nucleic Acids Res 2012;40(Database issue):D862-5. 6. Beisser D, Klau GW, Dandekar T, Müller T, Dittrich M. BioNet: an R-Package for the functional analysis of biological networks. Bioinformatics 2010;26(8):1129-30. Citation Format: Sujitra Detchokul, Aparna Elangovan, Melissa J. Davis, Geoff Macintyre, Edmund J. Crampin, Albert G. Frauman. Biological network analysis using an in vitro model of androgen-resistance in prostate cancer. [abstract]. In: Proceedings of the AACR Special Conference on Computational and Systems Biology of Cancer; Feb 8-11 2015; San Francisco, CA. Philadelphia (PA): AACR; Cancer Res 2015;75(22 Suppl 2):Abstract nr B1-40.</jats:p

Additional file 1: of Network analysis of an in vitro model of androgen-resistance in prostate cancer

Table S1.  Top 15 pathways for the human differentially expressed genes. Table S2. Top 15 pathways for the cell line deferentially expressed genes. Figure S1. Differencially expressed cell line genes overlaid on KEGG hsa04010 MAPK signaling pathway. Figure S2. Differentially expressed cell line genes overlaid on KEGG hsa04151 PI3K-Akt signaling pathway-Homo sapiens (human). Figure S3. Differentially expressed human tumour genes overlaid on KEGG hsa04010 MAPK signaling pathway. Figure S4. Differentially expressed human tumour genes overlaid on KEGG hsa04151 PI3K-Akt signaling pathway-Homo sapiens (human). (PDF 460 kb

Abstract 469: CD151 and cell motility in prostate cancer

Abstract Prostate cancer (PCa) is one of the leading causes of cancer death in men. CD151 is a member of the tetraspanin family and is associated with regulation of migration of normal and tumour cells via cell surface microdomain formation. Previous studies from our laboratory revealed that expression of CD151 differs across histological grades of PCa and high levels of expression are linked to shorter survival, independent of Gleason score1. In vitro motility assays of human PCa cell lines suggest CD151 is a motility promoter2. We have sought to develop a number of CD151 inhibitors and examine their ability to modulate prostate cancer motility and metastasis. The human PCa cell line, LNCaP (low endogenous level of CD151), transfected with CD151 shows increased motility and invasion compared to control LNCaP, whilst CD151 siRNA knock-down (KD) of PC-3 cells (high endogenous level of CD151), reduces motility compared to control PC-3. We have conducted in silico screening with compounds predicted to bind a model of the large extracellular domain (EC2) of CD151 and found that a number of these small molecules possess bioactivity in vitro and in vivo in inhibiting prostate cancer motility and progression. LNCaP growth and migration was confirmed by stimulating with 1 and 10 nM DHT at 24 hrs in charcoal stripped FBS. It was found that cell proliferation and motility of LNCaP cells was significantly increased after stimulation by 10 nM DHT at 24 hrs (p&amp;lt;0.01) and 48hrs (p&amp;lt;0.01), whilst DHT had minimal effect on control PC-3 and DU-145 cells. We have also analyzed a set of whole genome microarray expression data from PCa cell lines PC-3 and CD151 KD PC-3, and identified differentially expressed genes linked to CD151. Significant changes were seen in 172 genes after CD151 KD in PC-3 cells. We examined the protein interaction networks of our differentially expressed genes using Cytoscape3. Functional network analysis revealed high level of connectivity surrounding genes involved in transcriptional regulation, microtubule-based movement and protein folding and complex formation. CD151 is an important promoter of cell migration and metastatic disease in PCa and may serve as a target for a novel class of anti-metastatic therapeutic agents. A systems biology approach allows for improved mechanistic interpretation of biological data and may facilitate identification of other therapeutic targets. 1 Ang J et al. Cancer Epidemiol Biomarkers &amp; Prevention (2004) 13: 1717-21 2 Ang J et al. Oncology Reports (2010) 24(6): 1593-1597 3 Shannon P et al. Genome research (2003) 13: 2498-2504 Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 103rd Annual Meeting of the American Association for Cancer Research; 2012 Mar 31-Apr 4; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2012;72(8 Suppl):Abstract nr 469. doi:1538-7445.AM2012-469</jats:p