HGF/MET pathway aberrations as diagnostic, prognostic, and predictive biomarkers in human cancers

gene overexpression, gene amplification, exon 14 skipping and other activating mutations, is almost invariably associated with shorter survival and poor prognosis. Most meta-analyses have been performed in non-small cell lung cancer (NSCLC), breast, head and neck cancers as well as colorectal, gastric, pancreatic and other gastrointestinal cancers. Furthermore, several studies have shown the predictive value of MET biomarkers in the identification of patients who gain the most benefit from HGF/MET targeted therapies administered as single or combination therapies. The highest predictive values have been observed for response to foretinib and savolitinib in renal cancer, as well as tivantinib in NSCLC and colorectal cancer. However, some studies, especially those based on MET expression, have failed to show much value in these stratifications. This may be rooted in lack of standardization of methodologies, in particular in scoring systems applied in immunohistochemistry determinations or absence of oncogenic addiction of cancer cells to the MET pathway, despite detection of overexpression. Measurements of amplification and mutation aberrations are less likely to suffer from these pitfalls. Increased levels of MET soluble ectodomain (sMET) in circulation have also been associated with poor prognosis; however, the evidence is not as strong as it is with tissue-based biomarkers. As a diagnostic biomarker, sMET has shown its value in distinguishing cancer patients from healthy individuals in prostate and bladder cancers and in melanoma. On the other hand, increased circulating HGF has also been presented as a valuable prognostic and diagnostic biomarker in many cancers; however, there is controversy on the predictive value of HGF as a biomarker. Other biomarkers such as circulating tumor DNA (ctDNA) and tumor HGF levels have also been briefly covered. In conclusion, HGF/MET aberrations can provide valuable diagnostic, prognostic and predictive biomarkers and represent vital assets for personalized cancer therapy.