Due to the large number of putative microRNA gene targets predicted by sequence-alignment databases and the relative low accuracy of such predictions which are conducted independently of biological context by design, systematic experimental identification and validation of every functional microRNA target is currently challenging. Consequently, biological studies have yet to identify, on a genome scale, key regulatory networks perturbed by altered microRNA functions in the context of cancer. In this report, we demonstrate for the first time how phenotypic knowledge of inheritable cancer traits and of risk factor loci can be utilized jointly with gene expression analysis to efficiently prioritize deregulated microRNAs for biological characterization. Using this approach we characterize miR-204 as a tumor suppressor microRNA and uncover previously unknown connections between microRNA regulation, network topology, and expression dynamics. Specifically, we validate 18 gene targets of miR-204 that show elevated mRNA expression and are enriched in biological processes associated with tumor progression in squamous cell carcinoma of the head and neck (HNSCC). We further demonstrate the enrichment of bottleneckness, a key molecular network topology, among miR-204 gene targets. Restoration of miR-204 function in HNSCC cell lines inhibits the expression of its functionally related gene targets, leads to the reduced adhesion, migration and invasion in vitro and attenuates experimental lung metastasis in vivo. As importantly, our investigation also provides experimental evidence linking the function of microRNAs that are located in the cancer-associated genomic regions (CAGRs) to the observed predisposition to human cancers. Specifically, we show miR-204 may serve as a tumor suppressor gene at the 9q21.1–22.3 CAGR locus, a well established risk factor locus in head and neck cancers for which tumor suppressor genes have not been identified. This new strategy that integrates expression profiling, genetics and novel computational biology approaches provides for improved efficiency in characterization and modeling of microRNA functions in cancer as compared to the state of art and is applicable to the investigation of microRNA functions in other biological processes and diseases.
Hepatocyte growth factor receptor (HGFR), the product of the MET gene, plays an important role in normal cellular function and oncogenesis. In cancer, HGFR has been implicated in cellular proliferation, cell survival, invasion, cell motility, metastasis and angiogenesis. Activation of HGFR can occur through binding to its ligand, hepatocyte growth factor (HGF), overexpression/amplification, mutation, and/or decreased degradation. Amplification of HGFR can occur de novo or in resistance to therapy. Mutations of HGFR have been described in the tyrosine kinase domain, juxtamembrane domain, or semaphorin domain in a number of tumors. These mutations appear to have gain of function, and also reflect differential sensitivity to therapeutic inhibition. There have been various drugs developed to target HGFR, including antibodies to HGFR/HGF, small-molecule inhibitors against the tyrosine kinase domain of HGFR and downstream targets. Different HGFR inhibitors are currently in clinical trials in lung cancer and a number of solid tumors. Several phase I trials have already been completed, and two specific trials have been reported combining HGFR with epidermal growth factor receptor (EGFR) inhibition in non-small cell lung cancer. In particular, trials involving MetMAb and ARQ197 (tivantinib) have gained interest. Ultimately, as individualized therapies become a reality for cancers, HGFR will be an important molecular target.
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