KRAS mutations predict response to EGFR inhibitors
ABSTRACT Five antiepidermal growth factor receptor therapies have been approved for the treatment of solid tumors. However, response rates are relatively low. Several biomarkers that enrich for patients with tumors most likely to respond to these therapeutic agents have been identified. Mutations in the intermediate signal transduction pathway member KRAS also selects patients with tumors depending on signaling through this pathway. However, because KRAS acts downstream of the EGF receptor, somatic changes in this gene can be used as a marker to exclude patients unlikely to benefit from anti-EGFR therapy. Recent clinical data have provided substantial evidence that KRAS mutational status should be utilized as a diagnostic marker for predicting that response to anti-EGFR therapies in colorectal and non-small cell lung cancer.
- SourceAvailable from: Marie-Claude Gingras
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- "KRAS is a proto-oncogene that, once point mutated and consequently activated , can recruit and activate growth factors and receptor signals for malignant transformation. Epidermal growth factor receptor (EGFR), which promotes the growth of tumor cells, is a direct upstream gene of KRAS . In colon cancer, drugs targeting EGFR will lose efficiency if KRAS is activated. "
ABSTRACT: Pancreatic cancer has the worst five-year survival rate of all malignancies due to its aggressive progression and resistance to therapy. Current therapies are limited to gemcitabine-based chemotherapeutics, surgery, and radiation. The current trend toward "personalized genomic medicine" has the potential to improve the treatment options for pancreatic cancer. Gene identification and genetic alterations like single nucleotide polymorphisms and mutations will allow physicians to predict the efficacy and toxicity of drugs, which could help diagnose pancreatic cancer, guide neoadjuvant or adjuvant treatment, and evaluate patients' prognosis. This article reviews the multifaceted roles of genomics and pharmacogenomics in pancreatic cancer. Copyright © 2015. Published by Elsevier Ireland Ltd.Cancer letters 04/2015; 363(1). DOI:10.1016/j.canlet.2015.04.009 · 5.62 Impact Factor
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- "A subset analysis of patients with NSCLC with KRAS codon 13 mutations suggests that adjuvant chemotherapy may have a deleterious effect in this subgroup, but needs to be further validated (HR – 5.78; 95% CI, 2.06–16.2) (36). In the absence of prospective, large, randomized clinical trials, KRAS mutation status in NSCLC cannot be used as a prognostic nor predictive biomarker for treatment with exception of negative predictive value of KRAS mutations and response to EGFR-TKI (37, 112). "
ABSTRACT: Lung cancer remains the most lethal malignancy in the world. Despite improvements in surgical treatment, systemic therapy, and radiotherapy, the 5-year survival rate for all patients diagnosed with lung cancer remains between 15 and 20%. Newer therapeutic strategies rely on specific molecular alterations, or biomarkers, that provide opportunities for a personalized approach to specific patient populations. Classification of lung cancer is becoming increasingly focused on these biomarkers, which renders the term "non-small cell lung" cancer less clinically useful. Non-small cell lung cancer is now recognized as a complex malignancy and its molecular and genomic diversity allows for patient-centered treatment options. Here, we review advances in targeted treatment of lung adenocarcinoma with respect to five clinically relevant biomarkers - EGFR, ALK, MET, ROS-1, and KRAS.Frontiers in Oncology 08/2014; 4:204. DOI:10.3389/fonc.2014.00204
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- "Mutations in the v-Ki-ras2 Kirsten rat sarcoma viral oncogene homolog (KRAS), most frequently detected in codons 12, 13, and 61, occur in approximately 40% of CRC patients , . KRAS mutations have emerged as the key negative predictive factor for treatment response in patients receiving cetuximab , . "
ABSTRACT: Background: Oncogenic mutational analysis provides predictive guidance for therapeutics such as anti-EGFR antibodies, but it is successful only for a subset of colorectal cancer (CRC) patients. Method: A comprehensive molecular profiling of 120 CRC patients, including 116 primary, 15 liver metastasis, and 1 peritoneal seeding tissue samples was performed to identify the relationship between v-Ki-ras2 Kirsten rat sarcoma viral oncogene homolog (KRAS) WT and mutant CRC tumors and clinical outcomes. This included determination of the protein activation patterns of human epidermal receptor 1 (HER1), HER2, HER3, c-MET, insulin-like growth factor 1 receptor (IGF1R), phosphatidylinositide 3-kinase (PI3K), Src homology 2 domain containing (Shc), protein kinase B (AKT), and extracellular signal-regulated kinase (ERK) kinases using multiplexed collaborative enzyme enhanced reactive (CEER) immunoassay. Results: KRAS WT and mutated CRCs were not different with respect to the expression of the various signaling molecules. Poor prognosis in terms of early relapse (<2 years) and shorter disease-free survival (DFS) correlated with enhanced activation of PI3K signaling relative to the HER kinase pathway signaling, but not with the KRAS mutational status. KRAS WT CRCs were identified as a mixed prognosis population depending on their level of PI3K signaling. KRAS WT CRCs with high HER1/c-MET index ratio demonstrated a better DFS post-surgery. c-MET and IGF1R activities relative to HER axis activity were considerably higher in early relapse CRCs, suggesting a role for these alternative receptor tyrosine kinases (RTKs) in driving high PI3K signaling. Conclusions: The presented data subclassified CRCs based on their activated signaling pathways and identify a role for c-MET and IGF1R-driven PI3K signaling in CRCs, which is superior to KRAS mutational tests alone. The results from this study can be utilized to identify aggressive CRCs, explain failure of currently approved therapeutics in specific CRC subsets, and, most importantly, generate hypotheses for pathway-guided therapeutic strategies that can be tested clinically.PLoS ONE 08/2014; 9(8):e103551. DOI:10.1371/journal.pone.0103551 · 3.23 Impact Factor