Data mining and manual curation of published microarray datasets to establish a multi-gene panel for prediction of liver metastasis

Liver metastasis is associated with frequent occurrence and poor prognosis in patients with more common neoplastic diseases such as colorectal, breast, pancreas and lung. The poor 5-year survival rate can be attributed to factors such as aggressiveness of the disease, late diagnosis, resistance to therapy and low therapeutic response. These failures are associated with the complexity of the multifaceted metastatic process and the molecular mechanism underlying this cascade still remains unclear. Moreover, this complex cascade is driven by the acquisition of genetic and/or epigenetic alterations within tumor cells and also the co-option of non-neoplastic stromal cells, which together provide early metastatic cells, the traits needed to generate macroscopic metastases. Therefore, considering the heterogeneity of various mutations in tumorigenesis and understanding the nature of genes involved in the metastatic disease has become an utmost priority. In spite of numerous efforts being made to elucidate molecular and cellular mechanisms underlying tumorigenesis, cancer metastases still poses a threat to the modern world. Specific markers have been investigated in the hope of developing a deeper understanding of their role in liver metastases and developing newer therapeutic strategies. Thus, this review encompasses the functional relevance of almost all the biomarkers established to date with a special emphasis on a common 13-gene signature pattern specific for liver metastasis and their potential role in early prediction of metastatic event for improving the diagnosis, prognosis and treatment of patients with hepatic metastasis

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