Regenerative proliferation capacity and poor differentiation are histological features usually linked to poor prognosis in head and neck squamous cell carcinoma (hnSCC). However, the pathways that regulate them remain ill-characterized. Here, we show that those traits can be triggered by the RHO GTPase activator VAV2 in keratinocytes present in the skin and oral mucosa. VAV2 is also required to maintain those traits in hnSCC patient-derived cells. This function, which is both catalysis- and RHO GTPase-dependent, is mediated by c-Myc- and YAP/TAZ-dependent transcriptomal programs associated with regenerative proliferation and cell undifferentiation, respectively. High levels of VAV2 transcripts and VAV2-regulated gene signatures are both associated with poor hnSCC patient prognosis. These results unveil a druggable pathway linked to the malignancy of specific SCC subtypes.
With the advent of OMICs technologies, both individual research groups and consortia have spear-headed the characterization of human samples of multiple pathophysiologic origins, resulting in thousands of archived genomes and transcriptomes. Although a variety of web tools are now available to extract information from OMICs data, their utility has been limited by the capacity of nonbioinformatician researchers to exploit the information. To address this problem, we have developed CANCERTOOL, a web-based interface that aims to overcome the major limitations of public transcriptomics dataset analysis for highly prevalent types of cancer (breast, prostate, lung, and colorectal). CANCERTOOL provides rapid and comprehensive visualization of gene expression data for the gene(s) of interest in well-annotated cancer datasets. This visualization is accompanied by generation of reports customized to the interest of the researcher (e.g., editable figures, detailed statistical analyses, and access to raw data for reanalysis). It also carries out gene-to-gene correlations in multiple datasets at the same time or using preset patient groups. Finally, this new tool solves the time-consuming task of performing functional enrichment analysis with gene sets of interest using up to 11 different databases at the same time. Collectively, CANCERTOOL represents a simple and freely accessible interface to interrogate well-annotated datasets and obtain publishable representations that can contribute to refinement and guidance of cancer-related investigations at all levels of hypotheses and design. In order to facilitate access of research groups without bioinformatics support to public transcriptomics data, we have developed a free online tool with an easy-to-use interface that allows researchers to obtain quality information in a readily publishable format. .
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