title: The use of automated quantitative analysis to evaluate epithelial-to-mesenchymal transition associated proteins in clear cell renal cell carcinoma.
abstract: BACKGROUND
  Epithelial-to-mesenchymal transition (EMT) has recently been implicated in the initiation and progression of renal cell carcinoma (RCC). Some mRNA gene expression studies have suggested a link between the EMT phenotype and poorer clinical outcome from RCC. This study evaluated expression of EMT-associated proteins in RCC using in situ automated quantitative analysis immunofluorescence (AQUA) and compared expression levels with clinical outcome.
  
  
  RESULTS
  Unsupervised hierarchical cluster analysis of pre-existing RCC gene expression array data (GSE16449) from 36 patients revealed the presence of an EMT transcriptional signature in RCC [E-cadherin high/SLUG low/SNAIL low]. As automated immunofluorescence technology is dependent on accurate definition of the tumour cells in which measurements take place is critical, extensive optimisation was carried out resulting in a novel pan-cadherin based tumour mask that distinguishes renal cancer cells from stromal components. 61 patients with ccRCC and clinical follow-up were subsequently assessed for expression of EMT-associated proteins (WT1, SNAIL, SLUG, E-cadherin and phospho-β-catenin) on tissue microarrays. Using Kaplan-Meier analysis both SLUG (p = 0.029) and SNAIL (p = 0.024) (log rank Mantel-Cox) were significantly associated with prolonged progression free survival (PFS). Using Cox regression univariate and multivariate analysis none of the biomarkers were significantly correlated with outcome. 14 of the 61 patients expressed the gene expression analysis predicted EMT-protein signature [E-cadherin high/SLUG low/SNAIL low], which was not found to be associated to PFS when measured at the protein level. A combination of high expression of SNAIL and low stage was able to stratify patients with greater significance (p = 0.001) then either variable alone (high SNAIL p = 0.024, low stage p = 0.029).
  
  
  CONCLUSIONS
  AQUA has been shown to have the potential to identify EMT related protein targets in RCC allowing for stratification of patients into high and low risk groups, as well the ability to assess the association of reputed EMT signatures to progression of the disease.
authors.affiliation: Edinburgh Urological Cancer Group, Division of Pathology, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, United Kingdom.
authors.forename: Fiach C
authors.initials: FC
authors.lastname: O'Mahony
authors.forename: Dana
authors.initials: D
authors.lastname: Faratian
authors.forename: James
authors.initials: J
authors.lastname: Varley
authors.forename: Jyoti
authors.initials: J
authors.lastname: Nanda
authors.forename: Marianna
authors.initials: M
authors.lastname: Theodoulou
authors.forename: Antony C P
authors.initials: AC
authors.lastname: Riddick
authors.forename: David J
authors.initials: DJ
authors.lastname: Harrison
authors.forename: Grant D
authors.initials: GD
authors.lastname: Stewart
mesh_terms: D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D000912:Antibodies, Neoplasm / Q000276:immunology; D001331:Automation; D002292:Carcinoma, Renal Cell / Q000235:genetics / Q000276:immunology / Q000378:metabolism* / Q000473:pathology; D016000:Cluster Analysis; D030541:Databases, Genetic; D018572:Disease-Free Survival; D058750:Epithelial-Mesenchymal Transition / Q000235:genetics; D005260:Female; D005455:Fluorescent Antibody Technique / Q000379:methods*; D015972:Gene Expression Regulation, Neoplastic; D006801:Humans; D007680:Kidney Neoplasms / Q000235:genetics / Q000276:immunology / Q000378:metabolism* / Q000473:pathology; D008297:Male; D008875:Middle Aged; D015999:Multivariate Analysis; D009363:Neoplasm Proteins / Q000378:metabolism*; D020411:Oligonucleotide Array Sequence Analysis; D010641:Phenotype; D016016:Proportional Hazards Models; D015203:Reproducibility of Results; D018709:Statistics, Nonparametric
chemical_list: D000912:Antibodies, Neoplasm; D009363:Neoplasm Proteins