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Unlike classical RAS genes, oncogenic mutations on RRAS2 are seldomly found in human cancer. By contrast, RRAS2 is frequently found overexpressed in a number of human tumors, including B and T cell lymphomas, breast, gastric, head and neck cancers. In this regard, we have recently shown that overexpression of wild-type RRAS2 drives the formation of both chronic lymphocytic leukemia (CLL) and breast cancer in mice. In support for the relevance of overexpression of wild type RRAS2 in human cancer, we have found that RRAS2 expression is influenced by the presence of a specific single nucleotide polymorphism (SNP) located in the 3'-untranslated region (UTR) of the RRAS2 mRNA. Perhaps more importantly, the presence of the alternate C, rather than the G allele, at the RRAS2 SNP designated as rs8570 is also associated with worse patient prognosis in CLL. This indicates that the detection of this SNP allelic variants can be informative to predict RRAS2 expression levels and disease long-term evolution in patients. Here, we describe a polymerase chain reaction (PCR)-based method that facilitates the rapid and easy determination of G and C allelic variants of the SNP. Using this approach, we confirm that the C allelic variant is associated with higher expression levels of RRAS2 transcripts and poor patient prognosis. However, we have also found that expression of the C allelic variants correlates with better response to ibrutinib, a Bruton kinase inhibitor commonly used in CLL treatments. This suggests that this method for detecting the RRAS2 rs8570 SNP might be a useful as a tool to predict both patient prognosis and response to targeted therapy in CLL.

cancers

An Optimized Single Nucleotide Polymorphism-Based Detection Method Suggests That Allelic Variants in the 3’ Untranslated Region of RRAS2 Correlate with Treatment Response in Chronic Lymphocytic Leukemia Patients