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The era of precision medicine has marked a significant shift in cancer care, leading to more personalized treatment plans for patients. In the realm of metastatic colorectal cancer (mCRC), therapies often include monoclonal antibody (mAb) treatments targeting the epidermal growth factor receptor (EGFR). These therapies have shown promise; however, their effectiveness can be significantly impacted by the patient’s genetic makeup, particularly mutations in the RAS family of genes. One such crucial gene is NRAS.
NRAS is a member of the RAS oncoprotein family, which acts as a mitogen-activated protein kinase (MAPK) signaling pathway GTPase downstream of EGFR. Certain mutations in the NRAS gene result in permanent activation of parts of this pathway, rendering anti-EGFR therapies, like cetuximab or panitumumab, ineffective. Therefore, patient stratification based on RAS mutations has become crucial for optimizing treatment outcomes.
Positive identification of NRAS mutations means that anti-EGFR therapies are unlikely to be effective. Early and accurate diagnosis can thus save both time and resources by avoiding ineffective treatments. According to the PRIME study, NRAS mutations were found in approximately 7% of KRAS wild-type mCRC tumors, suggesting that testing for NRAS mutations is essential even if a patient is KRAS wild-type.
The NRAS StripAssay® is an in vitro diagnostic assay based on polymerase chain reaction (PCR) and reverse-hybridization. The process is fairly straightforward and comprises three main steps:
Bound biotinylated sequences are then detected using streptavidin-alkaline phosphatase and color substrates. The assay is designed to cover 22 mutations in the NRAS gene (codon 12, 13, 59, 60, 61, and 146).
Understanding genetic variations in mCRC is critical for the effective use of anti-EGFR mAb therapies. NRAS StripAssay® provides a reliable, precise, and efficient methodology for identifying patients who are unlikely to respond to such therapies, thereby playing a pivotal role in the era of precision medicine. By enabling better patient stratification, this groundbreaking tool allows clinicians to make more informed treatment choices, ultimately leading to better patient outcomes.