High-risk neuroblastomas show a paucity of recurrent somatic mutations at diagnosis. As a result, the molecular basis for this aggressive phenotype remains elusive. Recent progress in regulatory network analysis helped us elucidate disease-driving mechanisms downstream of genomic alterations, including recurrent chromosomal alterations. Our analysis identified three molecular subtypes of high-risk neuroblastomas, consistent with chromosomal alterations, and identified subtype-specific master regulator (MR) proteins that were conserved across independent cohorts. A 10–protein transcriptional module – centered around a TEAD4 ↔ MYCN positive-feedback loop – emerged as the regulatory driver of the high-risk subtype associated with MYCN amplification. Silencing of either gene collapsed MYCN-amplified (MYCNAmp) neuroblastoma transcriptional hallmarks and abrogated viability in vitro and in vivo. Consistently, TEAD4 emerged as a robust prognostic marker of poor survival, with activity independent of the canonical Hippo pathway transcriptional co-activators, YAP and TAZ. These results suggest novel therapeutic strategies for the large subset of MYCN deregulated neuroblastomas.
The majority of oncogenic drivers are intracellular proteins, thus constraining their immunotherapeutic targeting to mutated peptides (neoantigens) presented by individual human leukocyte antigen (HLA) allotypes1. However, most cancers have a modest mutational burden that is insufficient to generate responses using neoantigen-based therapies2,3. Neuroblastoma is a paediatric cancer that harbours few mutations and is instead driven by epigenetically deregulated transcriptional networks4. Here we show that the neuroblastoma immunopeptidome is enriched with peptides derived from proteins that are essential for tumourigenesis and focus on targeting the unmutated peptide QYNPIRTTF, discovered on HLA-A*24:02, which is derived from the neuroblastoma dependency gene and master transcriptional regulator PHOX2B. To target QYNPIRTTF, we developed peptide-centric chimeric antigen receptors (CARs) using a counter-panning strategy with predicted potentially cross-reactive peptides. We further hypothesized that peptide-centric CARs could recognize peptides on additional HLA allotypes when presented in a similar manner. Informed by computational modelling, we showed that PHOX2B peptide-centric CARs also recognize QYNPIRTTF presented by HLA-A*23:01 and the highly divergent HLA-B*14:02. Finally, we demonstrated potent and specific killing of neuroblastoma cells expressing these HLAs in vitro and complete tumour regression in mice. These data suggest that peptide-centric CARs have the potential to vastly expand the pool of immunotherapeutic targets to include non-immunogenic intracellular oncoproteins and widen the population of patients who would benefit from such therapy by breaking conventional HLA restriction.
Highlights d Selecting optimal epitopes is essential for vaccine safety and efficacy d We report 65 vaccine peptides predicted to drive long-term immunity in most people d Epitopes contain domains conserved in 15 coronaviruses and newly evolved SARS2 regions d Epitopes can be used to generate B and/or T cell vaccines (RNA and DNA)
Inconsistent detection of plant-based dietary small RNAs in circulation has thwarted the use of dietary RNA therapeutics. Here we demonstrate mice consuming diets rich in vegetables displayed enhanced serum levels of the plant specific small RNA MIR2911. Differential centrifugation, size-exclusion chromatography, and proteinase K treatment of plant extracts suggest this RNA resides within a proteinase K-sensitive complex. Plant derived MIR2911 was more bioavailable than the synthetic RNA. Furthermore, MIR2911 exhibited unusual digestive stability compared with other synthetic plant microRNAs. The characteristics of circulating MIR2911 were also unusual as it was not associated with exosomes and fractionated as a soluble complex that was insensitive to proteinase K treatment, consistent with MIR2911 being stabilized by modifications conferred by the host. These results indicate that intrinsic stability and plant-based modifications orchestrate consumer uptake of this anomalous plant based small RNA and invite revisiting plant-based microRNA therapeutic approaches.
Glycosylation is an important post-translational modification during protein production in eukaryotic cells, and it is essential for protein structure, stability, half-life, and biological functions. In this study, we produced various monoclonal antibody (mAb) glycoforms from Chinese hamster ovary (CHO) cells, including the natively glycosylated antibody, the enriched G0 form, the deglycosylated form, the afucosylated form, and the high mannose form, and we compared their intrinsic properties, side-by-side, through biophysical and biochemical approaches. Spectroscopic analysis indicates no measureable secondary or tertiary structural changes after in vitro or in vivo modification of the glycosylation pattern. Thermal unfolding experiments show that the high mannose and deglycosylated forms have reduced thermal stability of the CH2 domain compared with the other tested glycoforms. We also observed that the individual domain's thermal stability could be pH dependent. Proteolysis analysis indicates that glycosylation plays an important role in stabilizing mAbs against proteases. The stability of antibody glycoforms at the storage condition (2-8 °C) and at accelerated conditions (30 and 40 °C) was evaluated, and the results indicate that glycosylation patterns do not substantially affect the storage stability of the antibody we studied.
Peptide exchange technologies are essential for the generation of pMHC-multimer libraries used to probe diverse, polyclonal TCR repertoires in various settings. Here, using the molecular chaperone TAPBPR, we develop a robust method for the capture of stable, empty MHC-I molecules comprising murine H2 and human HLA alleles, which can be readily tetramerized and loaded with peptides of choice in a high-throughput manner. Alternatively, catalytic amounts of TAPBPR can be used to exchange placeholder peptides with high affinity peptides of interest. Using the same system, we describe high throughput assays to validate binding of multiple candidate peptides on empty MHC-I/TAPBPR complexes. Combined with tetramer-barcoding via a multi-modal cellular indexing technology, ECCITE-seq, our approach allows a combined analysis of TCR repertoires and other T cell transcription profiles together with their cognate antigen specificities in a single experiment. The new approach allows TCR/ pMHC interactions to be interrogated easily at large scale.
The identification of recurrent human leukocyte antigen (HLA) neoepitopes driving T cell responses against tumors poses a significant bottleneck in the development of approaches for precision cancer therapeutics. Here, we employ a bioinformatics method, Prediction of T Cell Epitopes for Cancer Therapy, to analyze sequencing data from neuroblastoma patients and identify a recurrent anaplastic lymphoma kinase mutation (ALK R1275Q) that leads to two high affinity neoepitopes when expressed in complex with common HLA alleles. Analysis of the X-ray structures of the two peptides bound to HLA-B*15:01 reveals drastically different conformations with measurable changes in the stability of the protein complexes, while the self-epitope is excluded from binding due to steric hindrance in the MHC groove. To evaluate the range of HLA alleles that could display the ALK neoepitopes, we used structure-based Rosetta comparative modeling calculations, which accurately predict several additional high affinity interactions and compare our results with commonly used prediction tools. Subsequent determination of the X-ray structure of an HLA-A*01:01 bound neoepitope validates atomic features seen in our Rosetta models with respect to key residues relevant for MHC stability and T cell receptor recognition. Finally, MHC tetramer staining of peripheral blood mononuclear cells from HLA-matched donors shows that the two neoepitopes are recognized by CD8+ T cells. This work provides a rational approach toward high-throughput identification and further optimization of putative neoantigen/HLA targets with desired recognition features for cancer immunotherapy.
Despite recent advances in cancer immunotherapy, the process of immunoediting early in tumorigenesis remains obscure. Here, we employ a mathematical model that utilizes the Cancer Genome Atlas (TCGA) data to elucidate the contribution of individual mutations and HLA alleles to the immunoediting process. We find that common cancer mutations including BRAF-V600E and KRAS-G12D are predicted to bind none of the common HLA alleles, and are thus "immunogenically silent" in the human population. We identify regions of proteins that are not presented by HLA at a population scale, coinciding with frequently mutated hotspots in cancer, and other protein regions broadly presented across the population in which few mutations occur. We also find that 9/29 common HLA alleles contribute disproportionately to the immunoediting of early oncogenic mutations. These data provide insights into immune evasion of common driver mutations and a molecular basis for the association of particular HLA genotypes with cancer susceptibility.
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