Publications by authors named "G Canettieri"

The transcription factor GLI1 is the main and final effector of the Hedgehog signaling pathway, which is involved in embryonic development, cell proliferation and stemness. Whether activated through canonical or non-canonical mechanisms, GLI1 aberrant activity is associated with Hedgehog-dependent cancers, including medulloblastoma, as well as other tumoral contexts. Notwithstanding a growing body of evidence, which have highlighted the potential role of post translational modifications of GLI1, the complex mechanisms modulating GLI1 stability and activity have not been fully elucidated.

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The potential as a cancer therapeutic target of the recently reported hotspot binding region close to Lys508 of the β-catenin armadillo repeat domain was not exhaustively explored. In order to get more insight, we synthesized novel -(heterocyclylphenyl)benzenesulfonamides -. The new compounds significantly inhibited Wnt-dependent transcription as well as SW480 and HCT116 cancer cell proliferation.

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Lipid nanoparticles (LNPs) play a crucial role in addressing genetic disorders, and cancer, and combating pandemics such as COVID-19 and its variants. Yet, the ability of LNPs to effectively encapsulate large-size DNA molecules remains elusive. This is a significant limitation, as the successful delivery of large-size DNA holds immense potential for gene therapy.

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The MYC oncogene is frequently overexpressed in tumors and inhibition of its translation is considered an attractive therapeutic opportunity. Despite numerous reports proposing an internal ribosome entry site (IRES) within the MYC Upstream Region (MYC UR) to sustain MYC translation during cellular stress or chemotherapy, conflicting evidence remains regarding the validity of such a mechanism. Through comprehensive investigations in MYC-driven Colorectal Cancer (CRC) and Burkitt Lymphoma (BL) cells, we demonstrate that MYC UR does not facilitate cap-independent translation, but instead orchestrates resistance to PI3K inhibitors.

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Single Molecule Localisation Microscopy (SMLM) is becoming a widely used technique in cell biology. After processing the images, the molecular localisations are typically stored in a table as xy (or xyz) coordinates, with additional information, such as number of photons, etc. This set of coordinates can be used to generate an image to visualise the molecular distribution, for example, a 2D or 3D histogram of localisations.

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