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Hoffman, K. S.

Publications and source records attributed to Hoffman, K. S..

2 recordsLinked to original sources

NRF2 translation block by inhibition of cap-dependent initiation sensitizes lymphoma cells to ferroptosis and CAR-T immunotherapy

Cancers coopt stress-response pathways to drive oncogenesis, dodge immune surveillance, and resist cytotoxic therapies. Several of these provide protection from ferroptosis, iron-mediated oxidative cell death. Here, we found dramatic sensitization to ferroptosis upon disruption of cap-dependent translation in diffuse large B-cell lymphoma (DLBCL). Specifically, rocaglate inhibitors of the eIF4A1 RNA helicase synergized with pharmacologic ferroptosis inducers, driven by a collapse of glutathione production that protects polyunsaturated fatty acids from ferroptotic oxidation. These effects occur despite initial up-regulation of specific protective factors. We find lost translation of NRF2, oncogenic master regulator of antioxidant gene-expression, is a key consequence of eIF4A1 inhibition. In vivo, combination of the clinical rocaglate zotatifin with a pharmacologically optimized ferroptosis inducer eradicated DLBCL patient derived xenografts. Moreover, we found zotatifin pre-exposure sensitized DLBCL to CD19-directed chimeric antigen receptor (CAR-19) T cells. Translational disruption therefore provides new opportunities to leverage therapeutic impacts of ferroptosis inducers including cytotoxic immunotherapies. SignificanceWe find translational disruption sensitizes lymphomas to ferroptosis, enhancing efficacy of CAR-T cells and multiple drugs. NRF2 loss mediates these effects, informing promising new therapeutic combinations. Multiple cancers exploit NRF2 to resist a wide variety treatments. These results expand therapeutic implications from its loss downstream of eIF4A1 inhibition.

cancer biology↗

A Facile Immunopeptidomics Workflow for Capturing the HLA-I Ligandome with PEAKS XPro

Identifying antigens displayed specifically on tumour cell surfaces by human leukocyte antigen (HLA) proteins is important for the development of immunotherapies and cancer vaccines. The difficulty in capturing an HLA ligandome stems from the fact that many HLA ligands are derived from splicing events or contain mutations, hindering their identification in a standard database search. To address this challenge, we developed an immunopeptidomics workflow with PEAKS XPro that uses de novo sequencing to uncover such peptides and identifies mutations for neoantigen discovery. We demonstrate the utility of this workflow by re-analyzing HLA-I ligandome datasets and reveal a vast diversity in peptide sequences among clones derived from a colorectal cancer tumour. Over 8000 peptides predicted to bind HLA-I molecules were identified by de novo sequencing only (not found in the UniProt database) and make up over 50% of identified peptides from each sample. Lastly, tumour-specific mutations and consensus sequence motif characteristics are defined. This workflow is widely applicable to any immunopeptidomic mass spectrometry dataset and does not require custom database generation for neoantigen discovery.

bioinformatics↗