George Coukos

The paper applies T-cell receptor sequencing and epitope annotation tools to quality control and immune monitoring of TIL products by identifying tumor-specific clones and screening for off-cancer reactivity.

The paper uses patient-derived explants to study BiTE-driven T cell responses in tumors, identifying the COX/PGE2 axis as a barrier to immune activation and showing COX inhibition enhances anti-tumor effects.

This study introduces iMSEA, a computational framework that identifies metabolic state shifts in BRCA1-deficient cancers using omics data and validates findings with experimental assays.

The paper presents two workflows for analyzing multiplexed imaging data from cancer tissues, applied to over 10,000 samples from 2500 patients, enabling large-scale tumor microenvironment studies.

The paper identifies immune phenotypes and myeloid cell networks in recurrent ovarian cancer that influence prognosis and immune environment reinstatement.

This study shows that PI-103 and samotolisib enhance CRISPR/Cas9-mediated TCR knockin efficiency in human T cells without affecting viability or phenotype.

The paper compares three transcriptomic methods on FFPE tumor samples to assess their ability to detect inter- and intra-patient heterogeneity.

This study shows that low pH impairs CD8+ T cell function by reducing IL-2 responsiveness, disrupting mTORC1 signaling, and altering c-Myc levels and amino acid metabolism.

This study reconstructs the colorectal cancer tumor microenvironment using patient-derived organoids and co-cultures, revealing how stromal cells influence cancer behavior and immune evasion.

This study shows that a variant of IL-2 (IL-2v) induces a stem-like, metabolically active T-cell state with improved therapeutic potential in adoptive cell therapy.

The paper introduces ProjecTILs, a method to project scRNA-seq data onto T cell reference atlases to interpret immune responses and perturbations.

The paper reanalyzes the contribution of proteasomal spliced peptides to the HLA-I ligandome and finds that only 2-4% of the ligandome may be explained by such peptides.

The paper identifies HLA-I binding motifs from peptidomics data to improve neo-antigen predictions and reveals allosteric regulation of HLA specificity.