Introduction Colorectal carcinogenesis is a multistep process which results from alterations in oncogenes and tumour suppressor genes combined with epigenetic events. Our aim is to refine further the clinical and pathological staging of colorectal cancer by identifying biomarkers of late tumour progression. As the tumour evolves it acquires a number of biological characteristics such as continuing proliferation, avoiding apoptosis etc., collectively referred to as the hallmarks of cancer. In this study we conducted a literature search in order to identify the set of proteins associated with these hallmarks in relation to colorectal cancer. From this long list of biomarkers we proceeded to select those which are associated with hallmarks which are expected to be relevant as late events in the multistep process of colorectal carcinogenesis using a computerised protein-protein network analysis approach.
Method We conducted a search in database Embase and Medline until October 2013 using search terms: colorectal cancer (CRC), colorectal neoplasia, metabolic phenotyping and mass spectrometry. Two hundred and thirty seven records were screened from the search for eligibility. Fifty-seven articles were found be studies relevant for gene expression profiles of CRC. Eight articles met inclusion criteria hence included for quantitative synthesis. All the biomarkers identified in this review were divided according to six-predefined hallmarks of cancer progression. We considered the hallmarks of angiogenesis, invasion and metastasis to represent late events and we identified a total of more than 30 associated protein biomarkers. We used the graph web network software to analyse protein – protein interaction among the protein biomarkers representing late hallmarks.
Results 13 Hub protein molecules, which scored more than 90% function in the networks, are mostly ribosomal proteins they are:
RPS 27 A, RPS 15 A, RPS 11, RPS29, RPS 4X, RPS 13, RPS 18, RPS 19, RPS 27, RPL 3L, RPL4, RPS21, UBA52.
6 Hub protein molecules, which scored more than 95% function in the networks, are:
RPS 27A, UBA52, RPS 19, RPS 27, RPL 4, RPS 21.
Conclusion We hypothesise that proteomic analysis of colorectal cancer samples targeting these proteins will provide additional prognostic information and could possibly form the basis of personalised therapy in the future.
Disclosure of interest None Declared.