Multiple biomarker tissue arrays: A computational approach to identifying protein-protein interactions in the EGFR/ERK signalling pathway.

BACKGROUND: Many studies have demonstrated genetic and environmental factors that lead to renal cell carcinoma (RCC) and that occur during a protracted period of tumourigenesis. It appears suitable to identify and characterise potential molecular markers that appear during tumourigenesis and that might provide rapid and effective possibilities for the early detection of RCC. EGFR activation induces cell cycle progression, inhibition of apoptosis and angiogenesis, promotion of invasion/metastasis, and other tumour promoting activities. Over-expression of EGFR is thought to play an important role in tumour initiation and progression of RCC because up-regulation of EGFR has been associated with high grade cancers and a worse prognosis. METHODS: Characterisation of the protein profile interacting with EGFR was performed using the following: an immunohistochemical (IHC) study of EGFR, a comprehensive computational study of EGFR protein-protein interactions, an analysis correlating the expression levels of EGFR with other significant markers in the tumourigenicity of RCC, and finally, an analysis of the utility of EGFR for prognosis in a cohort of patients with renal cell carcinoma. RESULTS: The cases that showed a higher level of this protein fell within the clear cell histological subtype (p = 0.001). The EGFR significance statistic was found with respect to a worse prognosis. In vivo significant correlations were found with PDGFR-ß, Flk-1, Hif1-α, proteins related to differentiation (such as DLL3 and DLL4 ligands), and certain metabolic proteins such as Glut5. In silico significant associations gave us a panel of 32 EGFR-interacting proteins (EIP) using the APID and STRING databases. CONCLUSIONS: This work summarises the multifaceted role of EGFR in the pathology of RCC, and it identifies EIPs that could help to provide mechanistic explanations for the different behaviours observed in tumours.

Expression of Notch1 to -4 and their ligands in renal cell carcinoma: a tissue microarray study.

BACKGROUND: Mutations in signalling pathways essential for embryonic development often lead to tumourigenesis, as is also true for Notch. The aim of this study was to assess the relationship between Notch1 to -4 and their ligands with anatomopathological features of the patients with renal cell carcinoma (RCC). MATERIALS AND METHODS: This study investigated the pattern of protein expression in RCC specimens using tissue microarray technology. A total of 80 paraffin-embedded RCC samples were retrospectively analysed together with ACHN and A.704 cell lines. RESULTS: Notch1 showed significant positive correlation with chromophobe RCC, no broken capsule, Furhman grade I and when the number of nodes involved was small [(N=1); p=0.039, 0.016, 0.037 and 0.001, respectively)]. Notch3 showed higher expression when the tumour was located in the right kidney (p=0.048). CONCLUSION: Notch1 may be useful in the future as a biomarker for the differential diagnosis of different RCC histological subtypes. Notch1 to -3 may also have potential use as a strong prognostic factor.

Relevant Networks involving the p53 Signalling Pathway in Renal Cell Carcinoma.

INTRODUCTION: Renal cell carcinoma is the most common type of kidney cancer. A better understanding of the critical pathways and interactions associated with alterations in renal function and renal tumour properties is required. Our final goal is to combine the knowledge provided by a regulatory network with experimental observations provided by the dataset. METHODS: In this study, a systems biology approach was used, integrating immunohistochemistry protein expression profiles and protein interaction information with the STRING and MeV bioinformatics tools. A group consisting of 80 patients with renal cell carcinoma was studied. The expression of selected markers was assessed using tissue microarray technology on immunohistochemically stained slides. The immunohistochemical data of the molecular factors studied were analysed using a parametric statistical test, Pearson's correlation coefficient test. RESULTS: Bioinformatics analysis of tumour samples resulted in 2 protein networks. The first network consists of proteins involved in the angiogenesis pathway and the apoptosis suppressor, BCL2, and includes both positive and negative correlations. The second network shows a negative interaction between the p53 tumour suppressor protein and the glucose transporter type 4. CONCLUSION: The comprehensive pathway network will help us to realise the cooperative behaviours among pathways. Regulation of metabolic pathways is an important role of p53. The pathway involving the tumour suppressor gene p53 could regulate tumour angiogenesis. Further investigation of the proteins that interact with this pathway in this type of tumour may provide new strategies for cancer therapies to specifically inhibit the molecules that play crucial roles in tumour progression.