Next-Generation FemtoQuest™ system enables dual-analyte ultrasensitive quantitation of active and total HGF in melanoma plasma samples

Hepatic growth factor (HGF) binds to the HGF receptor tyrosine kinase, also known as c-Met. Autophosphorylation of the HGF receptor leads to recruitment and activation of multiple downstream signaling molecules involved in MAPK, Akt/PI3K, STAT and NF-kB pathways. Activation of HGF receptor by HGF can lead to cell growth, cell motility, angiogenesis and cell survival. Upregulation of this pathway can lead to tumorigenesis of different types of cancer. Various approaches to inhibiting this HGF/c-Met axis have been explored, including c-Met neutralizing antibodies and small molecule inhibitors without much success. It is critical to understand the mechanisms of the HGF/c-Met axis to facilitate novel therapies. It is important to differentiate between the active versus total HGF concentration in the blood. Pro-HGF peptide is secreted by liver cells into extracellular matrix, where it can be cleaved by proteases into alpha and beta subunits, which form the active tetramer of 2 alpha and 2 beta subunits. It is the active form of HGF that binds and activate c-Met. We developed an ultrasensitive immunoassay platform utilizing SMC ® technology to address the challenge of quantifying low-abundance proteins in blood. Our next-generation FemtoQuest™ system enables detection of two analytes in a single assay well, maximizing sample efficiency. For this study, we developed a novel 2-plex immunoassay that can detect active HGF and total HGF (active HGF plus pro-HGF) simultaneously in a single well. This kit was able to achieve the sensitivity needed to quantitate both apparently healthy and melanoma plasma samples. Statistical difference for both Active HGF and Total HGF were observed in healthy versus melanoma samples. This high sensitivity immunoassay kit can differentiate between active HGF versus total HGF and allow measurement of low abundance proteins, demonstrating the platform's capability to detect differential HGF expression patterns in cancer samples.