Explore the vast range of titles available.

Cancer is thought to arise through the accumulation of genomic aberrations evolving under Darwinian selection. However, it remains unclear when the aberrations associated with metastasis emerge during tumor evolution. Uveal melanoma (UM) is the most common primary eye cancer and frequently leads to metastatic death, which is strongly linked to BAP1 mutations. Accordingly, UM is ideally suited for studying the clonal evolution of metastatic competence. Here we analyze sequencing data from 151 primary UM samples using a customized bioinformatic pipeline, to improve detection of BAP1 mutations and infer the clonal relationships among genomic aberrations. Strikingly, we find BAP1 mutations and other canonical genomic aberrations usually arise in an early punctuated burst, followed by neutral evolution extending to the time of clinical detection. This implies that the metastatic proclivity of UM is “set in stone” early in tumor evolution and may explain why advances in primary treatment have not improved survival. Uveal melanoma (UM), the most common primary eye cancer, is strongly linked to mutations in the tumor suppressor BAP1 . Here, the authors analyze 151 primary UM samples to find that BAP1 and other canonical genomic aberrations arise in an early punctuated burst followed by neutral tumor evolution.

William Harbour, Anne Bowcock and colleagues identify recurrent mutations at codon 625 of SF3B1 in uveal melanomas. These mutations occur in low-grade tumors and are associated with favorable prognosis. Uveal melanoma is the most common primary cancer of the eye and often results in fatal metastasis. Here, we describe mutations occurring exclusively at codon 625 of the SF3B1 gene, encoding splicing factor 3B subunit 1, in low-grade uveal melanomas with good prognosis. Thus, uveal melanoma is among a small group of cancers associated with SF3B1 mutations, and these mutations denote a distinct molecular subset of uveal melanomas.

Pleural mesothelioma is an aggressive malignancy with limited effective therapies. In order to identify therapeutic targets, we integrated SNP genotyping, sequencing and transcriptomics from tumours and low-passage patient-derived cells. Previously unrecognised deletions of SUFU locus (10q24.32), observed in 21% of 118 tumours, resulted in disordered expression of transcripts from Hedgehog pathways and the T-cell synapse including VISTA . Co-deletion of Interferon Type I genes and CDKN2A was present in half of tumours and was a predictor of poor survival. We also found previously unrecognised deletions in RB1 in 26% of cases and show sub-micromolar responses to downstream PLK1, CHEK1 and Aurora Kinase inhibitors in primary mesothelioma cells. Defects in Hippo pathways that included RASSF7 amplification and NF2 or LATS1 /2 mutations were present in 50% of tumours and were accompanied by micromolar responses to the YAP1 inhibitor Verteporfin. Our results suggest new therapeutic avenues in mesothelioma and indicate targets and biomarkers for immunotherapy.

Chimeric antigen receptor (CAR) T cells mediate anti-tumour effects in a small subset of patients with cancer 1 – 3 , but dysfunction due to T cell exhaustion is an important barrier to progress 4 – 6 . To investigate the biology of exhaustion in human T cells expressing CAR receptors, we used a model system with a tonically signaling CAR, which induces hallmark features of exhaustion 6 . Exhaustion was associated with a profound defect in the production of IL-2, along with increased chromatin accessibility of AP-1 transcription factor motifs and overexpression of the bZIP and IRF transcription factors that have been implicated in mediating dysfunction in exhausted T cells 7 – 10 . Here we show that CAR T cells engineered to overexpress the canonical AP-1 factor c-Jun have enhanced expansion potential, increased functional capacity, diminished terminal differentiation and improved anti-tumour potency in five different mouse tumour models in vivo. We conclude that a functional deficiency in c-Jun mediates dysfunction in exhausted human T cells, and that engineering CAR T cells to overexpress c-Jun renders them resistant to exhaustion, thereby addressing a major barrier to progress for this emerging class of therapeutic agents. Chimeric antigen receptor (CAR) T cells engineered to overexpress the canonical AP-1 transcription factor c-Jun are resistant to T cell exhaustion, and provide enhanced therapeutic benefit in mouse tumour models.

BackgroundThe assessment of tumor neoantigen burden has been shown to outperform tumor mutational burden in predicting patient response to checkpoint inhibitor immunotherapy by better capturing the biological mechanism underlying response.1. However, immune recognition of neoantigens by T-cells requires more than antigen presentation, which has been the focus of tumor neoantigen burden assessment to date. Here, we extend the existing SHERPA® MHC-presentation framework.2 To include a model for the prediction of neoantigen immunogenicity.MethodsFor feature engineering, training and validation, we utilized two datasets containing peptides experimentally validated for immunogenicity. The first dataset, curated by Schmidt et al.,3 aggregates experiments from 17 different sources, identifying 1282 immunogenic peptides across 67 MHC alleles. While the diversity of this dataset enables generalizability, a lack of associated sequencing data limits the features that can be investigated. The second dataset, curated by the TESLA consortium, contains 37 immunogenic peptides across 13 MHC alleles and patient-specific exome and transcriptome sequencing data, broadening the potential feature landscape.4 Using both datasets, we developed and validated features associated with antigen availability, processing, presentation and recognition. To inform the assessment of antigen availability, we measured gene expression level and variant allele fraction. We built a cleavage probability predictor from immunopeptidomics data for antigen processing, while SHERPA MHC binding probability was used to quantify antigen presentation. Finally, we included measures to predict T-cell recognition based on antigen hydrophobicity, agreotopicity, dissimilarity to self antigens and similarity to known foreign antigens. We utilized a two-tiered machine learning model that selectively learns the weights of features from the dataset that is most informative and least biased.ResultsThe Schmidt et al. dataset was used in the first tier of the model to develop an immunogenicity score using peptide-derived features. The first tier score distinguished immunogenic peptides with an area under the precision recall curve (AUPRC) of 0.74, far greater than SHERPA or NetMHCpan-4.1 alone (0.48 and 0.39 respectively). The second tier of the model was trained on the TESLA dataset and used the first tier score as a feature along with other patient-specific features. Cross validation yielded a 37% fold increase in AUPRC over the method developed by the TESLA consortium.ConclusionsBy combining antigen presentation and T-cell recognition features in a two-tiered model, we can better predict immunogenic neoantigens and make progress towards using neoantigens as biomarkers to assess checkpoint inhibitor efficacy.ReferencesAbbott, C.W. et al. Prediction of Immunotherapy Response in Melanoma through Combined Modeling of Neoantigen Burden and Immune-Related Resistance Mechanisms. Clin Cancer Res. 2021; 27(15):4265–4276.Pyke, R.M. et al. Precision Neoantigen Discovery Using Large-scale Immunopeptidomes and Composite Modeling of MHC Peptide Presentation. Mol Cell Proteomics. 2021;20:100111.Schmidt, J. et al. Prediction of neo-epitope immunogenicity reveals TCR recognition determinants and provides insight into immunoediting. Cell Rep Med. 2021;2(2):100194.Wells, D. et al. Key Parameters of Tumor Epitope Immunogenicity Revealed Through a Consortium Approach Improves Neoantigen Prediction. Cell. 2020 Oct 29;183(3):818–834.e13.

Uveal melanoma (UM) is the most common cancer of the adult eye which can manifest as a highly aggressive form approximately half of the time. Here a comprehensive landscape of genetic alterations in UMs is described. It was identified by integrating copy number alterations (CNAs), and transcriptomic and whole exome sequencing data from 207 primary UMs. Focal copy number analysis with the GISTIC algorithm refined the boundaries of chromosomal segments with chromosomal gains or losses and candidate cancer genes within these segments were identified. Chromosome 8q24.3 was the region most frequently amplified in UMs, being detected in 72% of tumours. A comparison of focal copy gains and losses with that described by a pan-cancer study revealed Plectin 1 as a candidate gene within the 8q24.3 amplicon. Integration of copy number and transcriptomic data also revealed enrichment of genes within pathways leading to activation of NF-kappa B, WNT signaling and RNA splicing. Using a complementary bioinformatics approach, additional novel mutations in known dominant UM driver genes (GNAQ, GNA11, BAP1, SF3B1, EIFIAX and CYSLTR2) were identified and an accurate estimate of the frequencies of mutations in each gene were obtained. Finally, integration of data obtained from CNAs with mutational and transcriptome data reveled homozygous deletions, protein damaging mutations and gene fusions that targeted chromatin modifiers, and specifically genes encoding components of the human SWItch/Sucrose NonFermentable (SWI/SNF) chromatin remodeling complex. Genes from the BAF complex (ARID1A and ARID1B) and the PBAF complex (PHF10) were subjected to functional loss through CNAs, gene fusions and mutations. Two of these chromatin modifiers (ARID1B and PHF10) map to chromosome 6q whose loss is associated with metastasis in a subset of UMs, and an ARID1B fusion is found in a tumour with a BAP1 mutation that subsequently underwent metastasis. In conclusion, this study provides a comprehensive overview of the landscape of genomic alterations in UM, identifying candidate genes in regions of CNAs and providing further insights into the altered pathways of tumour development and progression.

CAR T cells mediate antitumor effects in a small subset of cancer patients, but dysfunction due to T cell exhaustion is an important barrier to progress. To investigate the biology of exhaustion in human T cells expressing CAR receptors, we used a model system employing a tonically signaling CAR, which induces hallmarks of exhaustion described in other settings. Exhaustion was associated with a profound defect in IL-2 production alongside increased chromatin accessibility of AP-1 transcription factor motifs, and overexpression of numerous bZIP and IRF transcription factors that have been implicated in inhibitory activity. Here we demonstrate that engineering CAR T cells to overexpress c-Jun, a canonical AP-1 factor, enhanced expansion potential, increased functional capacity, diminished terminal differentiation and improved antitumor potency in numerous in vivo tumor models. We conclude that a functional deficiency in c-Jun mediates dysfunction in exhausted human T cells and that engineering CAR T cells to overexpress c-Jun renders them exhaustion-resistant, thereby addressing a major barrier to progress for this emerging class of therapeutics.

T cell exhaustion limits immune responses against cancer and is a major cause of resistance to CAR- T cell therapeutics. Using a model wherein tonic CAR signaling induces hallmark features of exhaustion, we employed a drug-regulatable CAR to test the impact of transient cessation of receptor signaling (i.e. \"rest\") on the development and maintenance of exhaustion. Induction of rest in exhausting or already-exhausted CAR-T cells resulted in acquisition of a memory-like phenotype, improved anti-tumor functionality, and wholescale transcriptional and epigenetic reprogramming. Similar results were achieved with the Src kinase inhibitor dasatinib, which reversibly suppresses CAR signaling. The degree of functional reinvigoration was proportional to the duration of rest and was associated with expression of transcription factors TCF1 and LEF1. This work demonstrates that transient cessation of CAR-T cell signaling can enhance anti-tumor potency by preventing or reversing exhaustion and challenges the paradigm that exhaustion is an epigenetically fixed state.