The landscape of T cell antigens for cancer immunotherapy.

The remarkable capacity of immunotherapies to induce durable regression in some patients with metastatic cancer relies heavily on T cell recognition of tumor-presented antigens. As checkpoint-blockade therapy has limited efficacy, tumor antigens have the potential to be exploited for complementary treatments, many of which are already in clinical trials. The surge of interest in this topic has led to the expansion of the tumor antigen landscape with the emergence of new antigen categories. Nonetheless, how different antigens compare in their ability to elicit efficient and safe clinical responses remains largely unknown. Here, we review known cancer peptide antigens, their attributes and the relevant clinical data and discuss future directions.

Combined presentation and immunogenicity analysis reveals a recurrent RAS.Q61K neoantigen in melanoma.

Neoantigens are now recognized drivers of the antitumor immune response. Recurrent neoantigens, shared among groups of patients, have thus become increasingly coveted therapeutic targets. Here, we report on the data-driven identification of a robustly presented, immunogenic neoantigen that is derived from the combination of HLA-A*01:01 and RAS.Q61K. Analysis of large patient cohorts indicated that this combination applies to 3% of patients with melanoma. Using HLA peptidomics, we were able to demonstrate robust endogenous presentation of the neoantigen in 10 tumor samples. We detected specific reactivity to the mutated peptide within tumor-infiltrating lymphocytes (TILs) from 2 unrelated patients, thus confirming its natural immunogenicity. We further investigated the neoantigen-specific clones and their T cell receptors (TCRs) via a combination of TCR sequencing, TCR overexpression, functional assays, and single-cell transcriptomics. Our analysis revealed a diverse repertoire of neoantigen-specific clones with both intra- and interpatient TCR similarities. Moreover, 1 dominant clone proved to cross-react with the highly prevalent RAS.Q61R variant. Transcriptome analysis revealed a high association of TCR clones with specific T cell phenotypes in response to cognate melanoma, with neoantigen-specific cells showing an activated and dysfunctional phenotype. Identification of recurrent neoantigens and their reactive TCRs can promote "off-the-shelf" precision immunotherapies, alleviating limitations of personalized treatments.

Identification of presented SARS-CoV-2 HLA class I and HLA class II peptides using HLA peptidomics.

The human leukocyte antigen (HLA)-bound viral antigens serve as an immunological signature that can be selectively recognized by T cells. As viruses evolve by acquiring mutations, it is essential to identify a range of presented viral antigens. Using HLA peptidomics, we are able to identify severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)-derived peptides presented by highly prevalent HLA class I (HLA-I) molecules by using infected cells as well as overexpression of SARS-CoV-2 genes. We find 26 HLA-I peptides and 36 HLA class II (HLA-II) peptides. Among the identified peptides, some are shared between different cells and some are derived from out-of-frame open reading frames (ORFs). Seven of these peptides were previously shown to be immunogenic, and we identify two additional immunoreactive peptides by using HLA multimer staining. These results may aid the development of the next generation of SARS-CoV-2 vaccines based on presented viral-specific antigens that span several of the viral genes.

Identification of bacteria-derived HLA-bound peptides in melanoma.

A variety of species of bacteria are known to colonize human tumours1-11, proliferate within them and modulate immune function, which ultimately affects the survival of patients with cancer and their responses to treatment12-14. However, it is not known whether antigens derived from intracellular bacteria are presented by the human leukocyte antigen class I and II (HLA-I and HLA-II, respectively) molecules of tumour cells, or whether such antigens elicit a tumour-infiltrating T cell immune response. Here we used 16S rRNA gene sequencing and HLA peptidomics to identify a peptide repertoire derived from intracellular bacteria that was presented on HLA-I and HLA-II molecules in melanoma tumours. Our analysis of 17 melanoma metastases (derived from 9 patients) revealed 248 and 35 unique HLA-I and HLA-II peptides, respectively, that were derived from 41 species of bacteria. We identified recurrent bacterial peptides in tumours from different patients, as well as in different tumours from the same patient. Our study reveals that peptides derived from intracellular bacteria can be presented by tumour cells and elicit immune reactivity, and thus provides insight into a mechanism by which bacteria influence activation of the immune system and responses to therapy.

Immunoproteasome expression is associated with better prognosis and response to checkpoint therapies in melanoma.

Predicting the outcome of immunotherapy treatment in melanoma patients is challenging. Alterations in genes involved in antigen presentation and the interferon gamma (IFNγ) pathway play an important role in the immune response to tumors. We describe here that the overexpression of PSMB8 and PSMB9, two major components of the immunoproteasome, is predictive of better survival and improved response to immune-checkpoint inhibitors of melanoma patients. We study the mechanism underlying this connection by analyzing the antigenic peptide repertoire of cells that overexpress these subunits using HLA peptidomics. We find a higher response of patient-matched tumor infiltrating lymphocytes against antigens diferentially presented after immunoproteasome overexpression. Importantly, we find that PSMB8 and PSMB9 expression levels are much stronger predictors of melanoma patients' immune response to checkpoint inhibitors than the tumors' mutational burden. These results suggest that PSMB8 and PSMB9 expression levels can serve as important biomarkers for stratifying melanoma patients for immune-checkpoint treatment.

Continuous lumbar drainage and the postoperative complication rate of open anterior skull base surgery.

OBJECTIVES/HYPOTHESIS: Anterior skull base operations pose the risk for postoperative cerebrospinal fluid (CSF) leak. Routine lumbar continuous drainage catheter (LD) placement is intended to decrease CSF leaks and central nervous system (CNS) complications, but there are no sound evidence-based data on its efficacy. The primary goal of this study was to review CNS complications following anterior open skull base surgery and their association with LD placement. The secondary goal was to define predictors for the development of early CNS complications. STUDY DESIGN: Retrospective case series. METHODS: We conducted a retrospective analysis of all patients who underwent anterior skull base surgery between 2000 and 2016 at the Tel Aviv Sourasky Medical Center, an Israeli tertiary referral center. RESULTS: A total of 226 patients underwent open skull base surgery, of whom 118 had elective perioperative continuous LD insertion and 108 did not. Delayed complications were defined as those occurring more than 30 days after the index operation. Thirty-one (26%) patients in the LD group had early CNS complications compared with only two (1.6%) in the non-LD group, whereas 13 (11%) of the former patients had late CNS complications compared with four (3%) of the latter patients. Early systemic and late wound complications were also significantly more numerous in the LD group. On multivariate analysis, elective LD insertion and intracranial tumor extension were found to be predictors for developing early CNS complications. CONCLUSIONS: The placement of continuous LDs might increase the risk of developing early and late CNS complications after open anterior skull base surgery. LEVEL OF EVIDENCE: 4 Laryngoscope, 128:2702-2706, 2018.

Structure-based in silico identification of ubiquitin-binding domains provides insights into the ALIX-V:ubiquitin complex and retrovirus budding.

The ubiquitylation signal promotes trafficking of endogenous and retroviral transmembrane proteins. The signal is decoded by a large set of ubiquitin (Ub) receptors that tether Ub-binding domains (UBDs) to the trafficking machinery. We developed a structure-based procedure to scan the protein data bank for hidden UBDs. The screen retrieved many of the known UBDs. Intriguingly, new potential UBDs were identified, including the ALIX-V domain. Pull-down, cross-linking and E3-independent ubiquitylation assays biochemically corroborated the in silico findings. Guided by the output model, we designed mutations at the postulated ALIX-V:Ub interface. Biophysical affinity measurements using microscale-thermophoresis of wild-type and mutant proteins revealed some of the interacting residues of the complex. ALIX-V binds mono-Ub with a K(d) of 119 µM. We show that ALIX-V oligomerizes with a Hill coefficient of 5.4 and IC(50) of 27.6 µM and that mono-Ub induces ALIX-V oligomerization. Moreover, we show that ALIX-V preferentially binds K63 di-Ub compared with mono-Ub and K48 di-Ub. Finally, an in vivo functionality assay demonstrates the significance of ALIX-V:Ub interaction in equine infectious anaemia virus budding. These results not only validate the new procedure, but also demonstrate that ALIX-V directly interacts with Ub in vivo and that this interaction can influence retroviral budding.

An integrated suite of fast docking algorithms.

The CAPRI experiment (Critical Assessment of Predicted Interactions) simulates realistic and diverse docking challenges, each case having specific properties that may be exploited by docking algorithms. Motivated by the different CAPRI challenges, we developed and implemented a comprehensive suite of docking algorithms. These were incorporated into a dynamic docking protocol, consisting of four main stages: (1) Biological and bioinformatics research aiming to predict the binding site residues, to define distance constraints between interface atoms and to analyze the flexibility of molecules; (2) Rigid or flexible docking, performed by the PatchDock or FlexDock method, which utilizes the information gathered in the previous step. Symmetric complexes are predicted by the SymmDock method; (3) Flexible refinement and reranking of the rigid docking solution candidates, performed by FiberDock; and finally, (4) clustering and filtering the results based on energy funnels. We analyzed the performance of our docking protocol on a large benchmark and on recent CAPRI targets. The analysis has demonstrated the importance of biological information gathering prior to docking, which significantly increased the docking success rate, and of the refinement and rescoring stage that significantly improved the ranking of the rigid docking solutions. Our failures were mostly a result of mishandling backbone flexibility, inaccurate homology modeling, or incorrect biological assumptions. Most of the methods are available at http://bioinfo3d.cs.tau.ac.il/.