Challenges and solutions for therapeutic TCR-based agents.

Recent development of methods to discover and engineer therapeutic T-cell receptors (TCRs) or antibody mimics of TCRs, and to understand their immunology and pharmacology, lag two decades behind therapeutic antibodies. Yet we have every expectation that TCR-based agents will be similarly important contributors to the treatment of a variety of medical conditions, especially cancers. TCR engineered cells, soluble TCRs and their derivatives, TCR-mimic antibodies, and TCR-based CAR T cells promise the possibility of highly specific drugs that can expand the scope of immunologic agents to recognize intracellular targets, including mutated proteins and undruggable transcription factors, not accessible by traditional antibodies. Hurdles exist regarding discovery, specificity, pharmacokinetics, and best modality of use that will need to be overcome before the full potential of TCR-based agents is achieved. HLA restriction may limit each agent to patient subpopulations and off-target reactivities remain important barriers to widespread development and use of these new agents. In this review we discuss the unique opportunities for these new classes of drugs, describe their unique antigenic targets, compare them to traditional antibody therapeutics and CAR T cells, and review the various obstacles that must be overcome before full application of these drugs can be realized.

A TCR mimic CAR T cell specific for NDC80 is broadly reactive with solid tumors and hematologic malignancies.

Target identification for chimeric antigen receptor (CAR) T-cell therapies remains challenging due to the limited repertoire of tumor-specific surface proteins. Intracellular proteins presented in the context of cell surface HLA provide a wide pool of potential antigens targetable through T-cell receptor mimic antibodies. Mass spectrometry (MS) of HLA ligands from 8 hematologic and nonhematologic cancer cell lines identified a shared, non-immunogenic, HLA-A*02-restricted ligand (ALNEQIARL) derived from the kinetochore-associated NDC80 gene. CAR T cells directed against the ALNEQIARL:HLA-A*02 complex exhibited high sensitivity and specificity for recognition and killing of multiple cancer types, especially those of hematologic origin, and were efficacious in mouse models against a human leukemia and a solid tumor. In contrast, no toxicities toward resting or activated healthy leukocytes as well as hematopoietic stem cells were observed. This shows how MS can inform the design of broadly reactive therapeutic T-cell receptor mimic CAR T-cell therapies that can target multiple cancer types currently not druggable by small molecules, conventional CAR T cells, T cells, or antibodies.

Integrative Proteogenomics Using ProteomeGenerator2.

Recent advances in nucleic acid sequencing now permit rapid and genome-scale analysis of genetic variation and transcription, enabling population-scale studies of human biology, disease, and diverse organisms. Likewise, advances in mass spectrometry proteomics now permit highly sensitive and accurate studies of protein expression at the whole proteome-scale. However, most proteomic studies rely on consensus databases to match spectra to peptide and protein sequences, and thus remain limited to the analysis of canonical protein sequences. Here, we develop ProteomeGenerator2 (PG2), based on the scalable and modular ProteomeGenerator framework. PG2 integrates genome and transcriptome sequencing to incorporate protein variants containing amino acid substitutions, insertions, and deletions, as well as noncanonical reading frames, exons, and other variants caused by genomic and transcriptomic variation. We benchmarked PG2 using synthetic data and genomic, transcriptomic, and proteomic analysis of human leukemia cells. PG2 can be integrated with current and emerging sequencing technologies, assemblers, variant callers, and mass spectral analysis algorithms, and is available open-source from https://github.com/kentsisresearchgroup/ProteomeGenerator2.

Integrative proteogenomics using ProteomeGenerator2.

Recent advances in nucleic acid sequencing now permit rapid and genome-scale analysis of genetic variation and transcription, enabling population-scale studies of human biology, disease, and diverse organisms. Likewise, advances in mass spectrometry proteomics now permit highly sensitive and accurate studies of protein expression at the whole proteome-scale. However, most proteomic studies rely on consensus databases to match spectra to peptide and proteins sequences, and thus remain limited to the analysis of canonical protein sequences. Here, we develop ProteomeGenerator2 (PG2), based on the scalable and modular ProteomeGenerator framework. PG2 integrates genome and transcriptome sequencing to incorporate protein variants containing amino acid substitutions, insertions, and deletions, as well as non-canonical reading frames, exons, and other variants caused by genomic and transcriptomic variation. We benchmarked PG2 using synthetic data and genomic, transcriptomic, and proteomic analysis of human leukemia cells. PG2 can be integrated with current and emerging sequencing technologies, assemblers, variant callers, and mass spectral analysis algorithms, and is available open-source from https://github.com/kentsisresearchgroup/ProteomeGenerator2 .

Unmasking the suppressed immunopeptidome of EZH2-mutated diffuse large B-cell lymphomas through combination drug treatment.

Exploring the repertoire of peptides presented on major histocompatibility complexes (MHCs) helps identify targets for immunotherapy in many hematologic malignancies. However, there is a paucity of such data for diffuse large B-cell lymphomas (DLBCLs), which might be explained by the profound downregulation of MHC expression in many DLBCLs, and in particular in the enhancer of zeste homolog 2 (EZH2)-mutated subgroup. Epigenetic drug treatment, especially in the context of interferon-γ (IFN-γ), restored MHC expression in DLBCL. In DLBCL, peptides presented on MHCs were identified via mass spectrometry after treatment with tazemetostat or decitabine alone or in combination with IFN-γ. Such treatment synergistically increased the expression of MHC class I surface proteins up to 50-fold and the expression of class II surface proteins up to threefold. Peptides presented on MHCs increased to a similar extent for both class I and class II MHCs. Overall, these treatments restored the diversity of the immunopeptidome to levels described in healthy B cells for 2 of 3 cell lines and allowed the systematic search for new targets for immunotherapy. Consequently, we identified multiple MHC ligands from the regulator of G protein signaling 13 (RGS13) and E2F transcription factor 8 (E2F8) on different MHC alleles, none of which have been described in healthy tissues and therefore represent tumor-specific MHC ligands that are unmasked only after drug treatment. Overall, our results show that EZH2 inhibition in combination with decitabine and IFN-γ can expand the repertoire of MHC ligands presented on DLBCLs by revealing suppressed epitopes, thus allowing the systematic analysis and identification of new potential immunotherapy targets.

Low-dose CDK4/6 inhibitors induce presentation of pathway specific MHC ligands as potential targets for cancer immunotherapy.

Cyclin dependent kinase 4/6 inhibitors (CDK4/6i) lead to cell-cycle arrest but also trigger T cell-mediated immunity, which might be mediated by changes in human leukocyte antigen (HLA) ligands. We investigated the effects of CDK4/6i, abemaciclib and palbociclib, on the immunopeptidome at nontoxic levels in breast cancer cell lines by biochemical identification of HLA ligands followed by network analyses. This treatment led to upregulation of HLA and revealed hundreds of induced HLA ligands in breast cancer cell lines. These new ligands were significantly enriched for peptides derived from proteins involved in the "G1/S phase transition of cell cycle" including HLA ligands from CDK4/6, Cyclin D1 and the 26S regulatory proteasomal subunit 4 (PSMC1). Interestingly, peptides from proteins targeted by abemaciclib and palbociclib, were predicted to be the most likely to induce a T cell response. In strong contrast, peptides induced by solely one of the drugs had a lower T cell recognition score compared to the DMSO control suggesting that the observed effect is class dependent. This general hypothesis was exemplified by a peptide from PSMC1 which was among the HLA ligands with highest prediction scores and which elicited a T cell response in healthy donors. Overall, these data demonstrate that CDK4/6i treatment gives rise to drug-induced HLA ligands from G1/S phase transition, that have the highest chance for being recognized by T cells, thus providing evidence that inhibition of a distinct cellular process leads to increased presentation of the involved proteins that may be targeted by immunotherapeutic agents.

Diurnal variations in the expression of core-clock genes correlate with resting muscle properties and predict fluctuations in exercise performance across the day.

OBJECTIVES: In this study, we investigated daily fluctuations in molecular (gene expression) and physiological (biomechanical muscle properties) features in human peripheral cells and their correlation with exercise performance. METHODS: 21 healthy participants (13 men and 8 women) took part in three test series: for the molecular analysis, 15 participants provided hair, blood or saliva time-course sampling for the rhythmicity analysis of core-clock gene expression via RT-PCR. For the exercise tests, 16 participants conducted strength and endurance exercises at different times of the day (9h, 12h, 15h and 18h). Myotonometry was carried out using a digital palpation device (MyotonPRO), five muscles were measured in 11 participants. A computational analysis was performed to relate core-clock gene expression, resting muscle tone and exercise performance. RESULTS: Core-clock genes show daily fluctuations in expression in all biological samples tested for all participants. Exercise performance peaks in the late afternoon (15-18 hours for both men and women) and shows variations in performance, depending on the type of exercise (eg, strength vs endurance). Muscle tone varies across the day and higher muscle tone correlates with better performance. Molecular daily profiles correlate with daily variation in exercise performance. CONCLUSION: Training programmes can profit from these findings to increase efficiency and fine-tune timing of training sessions based on the individual molecular data. Our results can benefit both professional athletes, where a fraction of seconds may allow for a gold medal, and rehabilitation in clinical settings to increase therapy efficacy and reduce recovery times.

An input-controlled model system for identification of MHC bound peptides enabling laboratory comparisons of immunopeptidome experiments.

Characterization of MHC-bound peptides by mass spectrometry (MS) is an essential technique for immunologic studies. Many efforts have been made to quantify the number of MHC-presented ligands by MS and to define the limits of detection of a specific MHC ligand. However, these experiments are often complex and comparisons across different laboratories are challenging. Therefore, we compared and orthogonally validated quantitation of peptide:MHC complexes by radioimmunoassay and flow cytometry using TCR mimic antibodies in three model systems to establish a method to control the experimental input of peptide MHC:complexes for MS analysis. Following isolation of MHC-bound peptides we identified and quantified an MHC ligand of interest with high correlation to the initial input. We found that the diversity of the presented ligandome, as well as the peptide sequence itself affected the detection of the target peptide. Furthermore, results were applicable from these model systems to unmodified cell lines with a tight correlation between HLA-A*02 complex input and the number of identified HLA-A*02 ligands. Overall, this framework provides an easily accessible experimental setup that offers the opportunity to control the peptide:MHC input and in this way compare immunopeptidome experiments not only within but also between laboratories, independent of their experimental approach. SIGNIFICANCE: Although immunopeptidomics is an essential tool for the characterization of MHCbound peptides on the cell surface, there are no easily applicable established protocols available that allow comparison of immunopeptidome experiments across laboratories. Here, we demonstrate that controlling the peptide:MHC input for immunopurification and LC-MS/MS experiments by flow cytometry in pre-defined model systems allows the generation of qualitative and quantitative data that can easily be compared between investigators, independently of their methods for MHC ligand isolation for MS.

Solving an MHC allele-specific bias in the reported immunopeptidome.

Identification of MHC class I-bound peptides by immunopurification of MHC complexes and subsequent analysis by mass spectrometry is crucial for understanding T cell immunology and immunotherapy. Investigation of the steps for the MHC ligand isolation process revealed biases in widely used isolation techniques toward peptides of lower hydrophobicity. As MHC ligand hydrophobicity correlates positively with immunogenicity, identification of more hydrophobic MHC ligands could potentially lead to more effective isolation of immunogenic peptides as targets for immunotherapies. We solved this problem by use of higher concentrations of acetonitrile for the separation of MHC ligands and their respective complexes. This increased overall MHC ligand identifications by 2-fold, increased detection of cancer germline antigen-derived peptides by 50%, and resulted in profound variations in isolation efficacy between different MHC alleles correlating with the hydrophobicity of their anchor residues. Overall, these insights enabled a more complete view of the immunopeptidome and overcame a systematic underrepresentation of these critical MHC ligands of high hydrophobicity.