Germline mutations in CDKN2A, encoding the tumor suppressor p16, are responsible for a large proportion of familial melanoma cases and also increase risk of pancreatic cancer. We identified four families through pancreatic cancer probands that were affected by both cancers. These families bore a germline missense variant of CDKN2A (47T>G), encoding a p16-L16R mutant protein associated with high cancer occurrence.
View Article and Find Full Text PDFThe Hedgehog-regulated transcription factors GLI1 and GLI2 play overlapping roles in development and disease; however, the mechanisms underlying their interplay remain elusive. We report for the first time that GLI1 and GLI2 physically and functionally interact in cancer cells. GLI1 and GLI2 were shown to co-immunoprecipitate in PANC1 pancreatic cancer cells and RMS13 rhabdomyosarcoma cells.
View Article and Find Full Text PDFThe expression of the extracellular sulfatase SULF2 has been associated with increased hepatocellular carcinoma (HCC) growth and poor patient survival. However, the molecular mechanisms underlying SULF2-associated tumor growth remain unclear. To address this gap, here we developed a transgenic mouse overexpressing in hepatocytes under the control of the transthyretin promoter.
View Article and Find Full Text PDFAutophagy has been shown to be a key cellular event controlling tumor growth in different neoplasms including hepatocellular carcinoma (HCC). Although this biological role of autophagy has been clearly established, the mechanism underlying its regulation remains elusive. Here, we demonstrate a role of sulfatase 2 (SULF2), a 6-O-endosulfatase modulating various growth factors and cytokine-related signaling pathways controlling tumor cell proliferation and survival, in the regulation of autophagy in HCC cells.
View Article and Find Full Text PDFPurpose: Genomic testing has increased the quantity of information available to oncologists. Unfortunately, many identified sequence alterations are variants of unknown significance (VUSs), which thus limit the clinician's ability to use these findings to inform treatment. We applied a combination of in silico prediction and molecular modeling tools and laboratory techniques to rapidly define actionable VUSs.
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