Publications by authors named "R L Eoff"

In some organisms, the replication of G-quadruplex (G4) structures is supported by the Rev1 DNA polymerase. We previously showed that residues in the insert-2 motif of human Rev1 (hRev1) increased the affinity of the enzyme for G4 DNA and mediated suppression of mutagenic replication near G4 motifs. We have now investigated the conservation of G4-selective properties in Rev1 from other species.

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Glioblastoma (GBM) remains the most frequently diagnosed primary malignant brain cancer in adults. Despite recent progress in understanding the biology of GBM, the clinical outcome for patients remains poor, with a median survival of approximately one year after diagnosis. One factor contributing to failure in clinical trials is the fact that traditional models used in GBM drug discovery poorly recapitulate patient tumors.

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Li Fraumeni syndrome (LFS) is a hereditary cancer predisposition syndrome caused by germline mutations in TP53. TP53 is the most common mutated gene in human cancer, occurring in 30-50% of glioblastomas (GBM). Here, we highlight a precision medicine platform to identify potential targets for a GBM patient with LFS.

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The lipid peroxidation product malondialdehyde and the DNA peroxidation product base-propenal react with dG to generate the exocyclic adduct, MdG. This mutagenic lesion has been found in human genomic and mitochondrial DNA. MdG in genomic DNA is enzymatically oxidized to 6-oxo-MdG, a lesion of currently unknown mutagenic potential.

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Article Synopsis
  • Glioblastoma (GBM) is a challenging cancer known for its treatment resistance and invasive behavior, leading to recurrence after surgery.
  • Researchers screened 22 anti-invasive compounds on GBM cell spheroids to find effective treatments, focusing on their toxicity and ability to inhibit invasion.
  • The study highlighted the importance of using both established cell lines and patient-derived organoids to assess treatment efficacy, finding that outcomes can vary significantly due to tumor heterogeneity, suggesting these models might inform personalized cancer therapies.
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