Predictive Molecular Markers of Response to Epidermal Growth Factor Receptor(EGFR) Family-Targeted Therapies

Sarah      Barton; Naureen      Starling; Charles      Swanton

doi:10.2174/156800910793357925

Abstract

Constitutive activation of the EGFR/RAS/PI3K cell-signaling pathway that may occur through molecular aberrations in core pathway components occurs in many solid tumours, including colorectal cancer(CRC), non-small-cell lung cancer(NSCLC) and breast cancer. Predictive biomarkers of response to therapeutics targeting this pathway are necessary to select patients more likely to respond, and importantly, to avoid treating patients likely to suffer a worse outcome with therapy compared to standard of care. Determination of EGFR by immunohistochemistry(IHC) is not strongly predictive of response to EGFR-targeted therapy in CRC and NSCLC. EGFR gene mutations in the tyrosine kinase(TK) domain are predictive of response to EGFR tyrosine kinase inhibitors(TKIs) in NSCLC, and the acquisition of a point mutation in an amino acid in an adjacent area, T790M, is predictive of resistance. However, novel irreversible EGFR inhibitors such as BIBW-2992 and HKI-272 may retain activity in tumours with T790M mutations. It is well established in CRC that mutations in KRAS are predictive of resistance to EGFR pathway inhibition, and may predict for a poorer outcome with therapy. Other potentially useful biomarkers of resistance to EGFR-targeted therapy in the process of clinical validation include mutations in BRAF, PTEN loss and PIK3CA mutations, nuclear factor-kappa beta(NF-KB) pathway activity, and expression of alternative EGFR ligands. Functional genomics elucidation of drug resistance pathways using RNA interference(RNAi) techniques may provide novel therapeutic approaches in disease resistant to EGFR pathway targeting and accelerate predictive biomarker development.

Keywords: Predictive molecular markers, epidermal growth factor receptor(EGFR), RAS, phosphoinositide 3-kinase(PI3K), response, resistance, targeted therapy, biomarker.