Mapping kinase domain resistance mechanisms for the MET receptor tyrosine kinase via deep mutational scanning.

Mutations in the kinase and juxtamembrane domains of the MET Receptor Tyrosine Kinase are responsible for oncogenesis in various cancers and can drive resistance to MET-directed treatments. Determining the most effective inhibitor for each mutational profile is a major challenge for MET-driven cancer treatment in precision medicine. Here, we used a deep mutational scan (DMS) of ~5,764 MET kinase domain variants to profile the growth of each mutation against a panel of 11 inhibitors that are reported to target the MET kinase domain. We identified common resistance sites across type I, type II, and type I ½ inhibitors, unveiled unique resistance and sensitizing mutations for each inhibitor, and validated non-cross-resistant sensitivities for type I and type II inhibitor pairs. We augment a protein language model with biophysical and chemical features to improve the predictive performance for inhibitor-treated datasets. Together, our study demonstrates a pooled experimental pipeline for identifying resistance mutations, provides a reference dictionary for mutations that are sensitized to specific therapies, and offers insights for future drug development.

An evolved AAV variant enables efficient genetic engineering of murine T cells.

Precise targeting of large transgenes to T cells using homology-directed repair has been transformative for adoptive cell therapies and T cell biology. Delivery of DNA templates via adeno-associated virus (AAV) has greatly improved knockin efficiencies, but the tropism of current AAV serotypes restricts their use to human T cells employed in immunodeficient mouse models. To enable targeted knockins in murine T cells, we evolved Ark313, a synthetic AAV that exhibits high transduction efficiency in murine T cells. We performed a genome-wide knockout screen and identified QA2 as an essential factor for Ark313 infection. We demonstrate that Ark313 can be used for nucleofection-free DNA delivery, CRISPR-Cas9-mediated knockouts, and targeted integration of large transgenes. Ark313 enables preclinical modeling of Trac-targeted CAR-T and transgenic TCR-T cells in immunocompetent models. Efficient gene targeting in murine T cells holds great potential for improved cell therapies and opens avenues in experimental T cell immunology.

Intron retention is a source of neoepitopes in cancer.

We present an in silico approach to identifying neoepitopes derived from intron retention events in tumor transcriptomes. Using mass spectrometry immunopeptidome analysis, we show that retained intron neoepitopes are processed and presented on MHC I on the surface of cancer cell lines. RNA-derived neoepitopes should be considered for prospective personalized cancer vaccine development.