title: Network analysis of an in vitro model of androgen-resistance in prostate cancer.
abstract: 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.
authors.affiliation: Clinical Pharmacology and Therapeutics, Department of Medicine, The University of Melbourne, Austin Health, Heidelberg, VIC, Australia. sdet@unimelb.edu.au.
authors.forename: Sujitra
authors.initials: S
authors.lastname: Detchokul
authors.affiliation: Systems Biology Laboratory, Melbourne School of Engineering, The University of Melbourne, Parkville, VIC, Australia. aparnae@student.unimelb.edu.au.
authors.forename: Aparna
authors.initials: A
authors.lastname: Elangovan
authors.affiliation: Systems Biology Laboratory, Melbourne School of Engineering, The University of Melbourne, Parkville, VIC, Australia. edmund.crampin@unimelb.edu.au.|School of Mathematics & Statistics, The University of Melbourne, Parkville, VIC, Australia. edmund.crampin@unimelb.edu.au.|School of Medicine, University of Melbourne, Parkville, VIC, Australia. edmund.crampin@unimelb.edu.au.|ARC Centre of Excellence in Convergent Bio-Nano Science and Technology, The University of Melbourne, Parkville, VIC, Australia. edmund.crampin@unimelb.edu.au.
authors.forename: Edmund J
authors.initials: EJ
authors.lastname: Crampin
authors.affiliation: Systems Biology Laboratory, Melbourne School of Engineering, The University of Melbourne, Parkville, VIC, Australia. melissa.davis@unimelb.edu.au.
authors.forename: Melissa J
authors.initials: MJ
authors.lastname: Davis
authors.affiliation: Clinical Pharmacology and Therapeutics, Department of Medicine, The University of Melbourne, Austin Health, Heidelberg, VIC, Australia. albertf@unimelb.edu.au.
authors.forename: Albert G
authors.initials: AG
authors.lastname: Frauman
mesh_terms: D000728:Androgens / Q000378:metabolism / Q000627:therapeutic use*; D045744:Cell Line, Tumor; D002465:Cell Movement / Q000235:genetics; D049109:Cell Proliferation / Q000235:genetics; D002470:Cell Survival / Q000235:genetics; D015972:Gene Expression Regulation, Neoplastic; D059014:High-Throughput Nucleotide Sequencing; D006801:Humans; D008297:Male; D020929:Mitogen-Activated Protein Kinase Kinases / Q000235:genetics; D009363:Neoplasm Proteins / Q000096:biosynthesis; D019869:Phosphatidylinositol 3-Kinases / Q000235:genetics; D064129:Prostatic Neoplasms, Castration-Resistant / Q000188:drug therapy / Q000235:genetics* / Q000473:pathology; D060066:Protein Interaction Maps / Q000235:genetics*; D011944:Receptors, Androgen / Q000096:biosynthesis* / Q000378:metabolism; D011980:Receptors, Progesterone / Q000096:biosynthesis* / Q000378:metabolism; D015398:Signal Transduction / Q000235:genetics
chemical_list: D000728:Androgens; D009363:Neoplasm Proteins; D011944:Receptors, Androgen; D011980:Receptors, Progesterone; D019869:Phosphatidylinositol 3-Kinases; D020929:Mitogen-Activated Protein Kinase Kinases