Immunotherapy offers a promising novel approach for the treatment of cancer and both adoptive T-cell transfer and immune modulation lead to regression of advanced melanoma. However, the potential synergy between these two strategies remains unclear.

While T cell-based immunotherapies are steadily improving, there are still many patients who progress, despite T cell-infiltrated tumors. Emerging evidence suggests that T cells themselves may provoke immune escape of cancer cells. Here, we describe a well-controlled co-culture system for studying the dynamic T cell - cancer cell interplay, using human melanoma as a model. We explain starting material, controls, and culture parameters to establish reproducible and comparable cultures with highly heterogeneous tumor cells. Low passage melanoma cell lines and melanoma-specific CD8+ T cell clones generated from patient blood were cultured together for up to 3 days. Living melanoma cells were isolated from the co-culture system by fluorescence-activated cell sorting. We demonstrate that the characterization of isolated melanoma cells is feasible using flow cytometry for protein expression analysis as well as an Agilent whole human genome microarray and the NanoString technology for differential gene expression analysis. In addition, we identify five genes (ALG12, GUSB, RPLP0, KRBA2, and ADAT2) that are stably expressed in melanoma cells independent of the presence of T cells or the T cell-derived cytokines IFNγ and TNFα. These genes are essential for correct normalization of gene expression data by NanoString. Further to the characterization of melanoma cells after exposure to CTLs, this experimental system might be suitable to answer a series of questions, including how the affinity of CTLs for their target antigen influences the melanoma cell response and whether CTL-induced gene expression changes in melanoma cells are reversible. Taken together, our human T cell - melanoma cell culture system is well suited to characterize immune-related mechanisms in cancer cells.

Numerous in vitro studies attribute to human TRIM5α some modest anti-HIV-1 activity and human population studies suggest some differential effect of TRIM5α polymorphisms on disease progression. If the activity of TRIM5α were relevant in vivo, it could result in positive selection on the viral capsid. To address this issue, we identified 10 positively selected sites in HIV-1 capsid from multiple viral strains and generated 17 clade B viruses carrying a minor (i.e. low frequency) residue or an alanine at those positions. All recombinant viruses were susceptible to the modest effect of common human TRIM5α and allelic variants R136Q, and H419Y; H43Y and G249D TRIM5α were generally inactive. Increased sensitivity to TRIM5α was observed for some capsid variants, suggesting that minor residues are selected against in human populations. On the other hand, the modest potency of human TRIM5α does not translate in escape mutations in the viral capsid.

Peptide recognition domains and transcription factors play crucial roles in cellular signaling. They bind linear stretches of amino acids or nucleotides, respectively, with high specificity. Experimental techniques that assess the binding specificity of these domains, such as microarrays or phage display, can retrieve thousands of distinct ligands, providing detailed insight into binding specificity. In particular, the advent of next-generation sequencing has recently increased the throughput of such methods by several orders of magnitude. These advances have helped reveal the presence of distinct binding specificity classes that co-exist within a set of ligands interacting with the same target. Here, we introduce a software system called MUSI that can rapidly analyze very large data sets of binding sequences to determine the relevant binding specificity patterns. Our pipeline provides two major advances. First, it can detect previously unrecognized multiple specificity patterns in any data set. Second, it offers integrated processing of very large data sets from next-generation sequencing machines. The results are visualized as multiple sequence logos describing the different binding preferences of the protein under investigation. We demonstrate the performance of MUSI by analyzing recent phage display data for human SH3 domains as well as microarray data for mouse transcription factors.

CD160 is a T cell coinhibitory molecule that interacts with the herpes virus entry mediator (HVEM) on antigen-presenting cells to provide an inhibitory signal to T cells. To date, the structure of CD160 and its complex with HVEM are unknown. Here, we have identified the fragments of CD160 interacting with HVEM using ELISA tests, hydrogen/deuterium studies, affinity chromatography and mass spectrometry (MS). By combining hydrogen/deuterium exchange and mass spectrometry (HDX-MS) we obtained key information about the tertiary structure of CD160, predicting the 3D structure of the CD160-HVEM complex. Our results provide insights into the molecular architecture of this complex, serving as a useful basis for designing inhibitors for future immunotherapies.

Despite the promising therapeutic effects of immune checkpoint blockade (ICB), most patients with solid tumors treated with anti-PD-1/PD-L1 monotherapy do not achieve objective responses, with most tumor regressions being partial rather than complete. It is hypothesized that the absence of pre-existing antitumor immunity and/or the presence of additional tumor immune suppressive factors at the tumor microenvironment are responsible for such therapeutic failures. It is therefore clear that in order to fully exploit the potential of PD-1 blockade therapy, antitumor immune response should be amplified, while tumor immune suppression should be further attenuated. Cancer vaccines may prime patients for treatments with ICB by inducing effective anti-tumor immunity, especially in patients lacking tumor-infiltrating T-cells. These "non-inflamed" non-permissive tumors that are resistant to ICB could be rendered sensitive and transformed into "inflamed" tumor by vaccination. In this article we describe a clinical study where we use pancreatic cancer as a model, and we hypothesize that effective vaccination in pancreatic cancer patients, along with interventions that can reprogram important immunosuppressive factors in the tumor microenvironment, can enhance tumor immune recognition, thus enhancing response to PD-1/PD-L1 blockade. We incorporate into the schedule of standard of care (SOC) chemotherapy adjuvant setting a vaccine platform comprised of autologous dendritic cells loaded with personalized neoantigen peptides (PEP-DC) identified through our own proteo-genomics antigen discovery pipeline. Furthermore, we add nivolumab, an antibody against PD-1, to boost and maintain the vaccine's effect. We also demonstrate the feasibility of identifying personalized neoantigens in three pancreatic ductal adenocarcinoma (PDAC) patients, and we describe their optimal incorporation into long peptides for manufacturing into vaccine products. We finally discuss the advantages as well as the scientific and logistic challenges of such an exploratory vaccine clinical trial, and we highlight its novelty.

The efficacy of T cells depends on their functional avidity, i. e., the strength of T cell interaction with cells presenting cognate antigen. The overall T cell response is composed of multiple T cell clonotypes, involving different T cell receptors and variable levels of functional avidity. Recently, it has been proposed that the presence of low avidity tumor antigen-specific CD8 T cells hinder their high avidity counterparts to protect from tumor growth. Here we analyzed human cytotoxic CD8 T cells specific for the melanoma antigen Melan-A/MART-1. We found that the presence of low avidity T cells did not result in reduced cytotoxicity of tumor cells, nor reduced cytokine production, by high avidity T cells. In vivo in NSG-HLA-A2 mice, the anti-tumor effect of high avidity T cells was similar in presence or absence of low avidity T cells. These data indicate that low avidity T cells are not hindering anti-tumor T cell responses, a finding that is reassuring because low avidity T cells are an integrated part of natural T cell responses.

Immune cells infiltrating tumors can have important impact on tumor progression and response to therapy. We present an efficient algorithm to simultaneously estimate the fraction of cancer and immune cell types from bulk tumor gene expression data. Our method integrates novel gene expression profiles from each major non-malignant cell type found in tumors, renormalization based on cell-type-specific mRNA content, and the ability to consider uncharacterized and possibly highly variable cell types. Feasibility is demonstrated by validation with flow cytometry, immunohistochemistry and single-cell RNA-Seq analyses of human melanoma and colorectal tumor specimens. Altogether, our work not only improves accuracy but also broadens the scope of absolute cell fraction predictions from tumor gene expression data, and provides a unique novel experimental benchmark for immunogenomics analyses in cancer research (http://epic.gfellerlab.org).

The remarkable clinical efficacy of the immune checkpoint blockade therapies has motivated researchers to discover immunogenic epitopes and exploit them for personalized vaccines. Human leukocyte antigen (HLA)-binding peptides derived from processing and presentation of mutated proteins are one of the leading targets for T-cell recognition of cancer cells. Currently, most studies attempt to identify neoantigens based on predicted affinity to HLA molecules, but the performance of such prediction algorithms is rather poor for rare HLA class I alleles and for HLA class II. Direct identification of neoantigens by mass spectrometry (MS) is becoming feasible; however, it is not yet applicable to most patients and lacks sensitivity. In an attempt to capitalize on existing immunopeptidomics data and extract information that could complement HLA-binding prediction, we first compiled a large HLA class I and class II immunopeptidomics database across dozens of cell types and HLA allotypes and detected hotspots that are subsequences of proteins frequently presented. About 3% of the peptidome was detected in both class I and class II. Based on the gene ontology of their source proteins and the peptide's length, we propose that their processing may partake by the cellular class II presentation machinery. Our database captures the global nature of the in vivo peptidome averaged over many HLA alleles, and therefore, reflects the propensity of peptides to be presented on HLA complexes, which is complementary to the existing neoantigen prediction features such as binding affinity and stability or RNA abundance. We further introduce two immunopeptidomics MS-based features to guide prioritization of neoantigens: the number of peptides matching a protein in our database and the overlap of the predicted wild-type peptide with other peptides in our database. We show as a proof of concept that our immunopeptidomics MS-based features improved neoantigen prioritization by up to 50%. Overall, our work shows that, in addition to providing huge training data to improve the HLA binding prediction, immunopeptidomics also captures other aspects of the natural in vivo presentation that significantly improve prediction of clinically relevant neoantigens.

Pembrolizumab is an immune checkpoint inhibitor against programmed cell death protein-1 (PD-1) approved for therapy in metastatic melanoma. PD-1 expression is associated with a diminished functionality in HIV-1 specific-CD8+ T cells. It is thought that PD-1 blockade could contribute to reinvigorate antiviral immunity and reduce the HIV-1 reservoir.

Recent clinical developments in antitumor immunotherapy involving T-cell related therapeutics have led to a renewed interest for human leukocyte antigen class I (HLA-I) binding peptides, given their potential use as peptide vaccines. Databases of HLA-I binding peptides hold therefore information on therapeutic targets essential for understanding immunity. In this work, we use in depth and accurate HLA-I peptidomics datasets determined by mass-spectrometry (MS) and analyze properties of the HLA-I binding peptides with structure-based computational approaches. HLA-I binding peptides are studied grouping all alleles together or in allotype-specific contexts. We capitalize on the increasing number of structurally determined proteins to (1) map the 3D structure of HLA-I binding peptides into the source proteins for analyzing their secondary structure and solvent accessibility in the protein context, and (2) search for potential differences between these properties in HLA-I binding peptides and in a reference dataset of HLA-I motif-like peptides. This is performed by an in-house developed heuristic search that considers peptides across all the human proteome and converges to a collection of peptides that exhibit exactly the same motif as the HLA-I peptides. Our results, based on 9-mers matched to protein 3D structures, clearly show enriched sampling for HLA-I presentation of helical fragments in the source proteins. This enrichment is significant, as compared to 9-mer HLA-I motif-like peptides, and is not entirely explained by the helical propensity of the preferred residues in the HLA-I motifs. We give possible hypothesis for the secondary structure biases observed in HLA-I peptides. This contribution is of potential interest for researchers working in the field of antigen presentation and proteolysis. This knowledge refines the understanding of the rules governing antigen presentation and could be added to the parameters of the current peptide-MHC class I binding predictors to increase their antigen predictive ability.

Patient derived organoids (PDOs) can be established from colorectal cancers (CRCs) as in vitro models to interrogate cancer biology and its clinical relevance. We applied mass spectrometry (MS) immunopeptidomics to investigate neoantigen presentation and whether this can be augmented through interferon gamma (IFNγ) or MEK-inhibitor treatment.

The maintenance of homeostasis in the gut is a major challenge for the immune system. Here we demonstrate that the transcription factor MAF plays a central role in T cells for the prevention of gastro-intestinal inflammation. Conditional knock out mice lacking Maf in all T cells developed spontaneous late-onset colitis, correlating with a decrease of FOXP3+RORγt+ T cells proportion, dampened IL-10 production in the colon and an increase of inflammatory TH17 cells. Strikingly, FOXP3+ specific conditional knock out mice for MAF did not develop colitis and demonstrated normal levels of IL-10 in their colon, despite the incapacity of regulatory T cells lacking MAF to suppress colon inflammation in Rag1-/- mice transferred with naïve CD4+ T cells. We showed that one of the cellular sources of IL-10 in the colon of these mice are TH17 cells. Thus, MAF is critically involved in the maintenance of the gut homeostasis by regulating the balance between Treg and TH17 cells either at the level of their differentiation or through the modulation of their functions.

Liquid biopsies allow monitoring of cancer progression and detection of relapse, but reliable biomarkers in melanoma are lacking. Because secreted factors preferentially drain to lymphatic vessels before dilution in the blood, we hypothesized that lymph should be vastly enriched in cancer biomarkers. We characterized postoperative lymphatic exudate and plasma of metastatic melanoma patients after lymphadenectomy and found a dramatic enrichment in lymphatic exudate of tumor-derived factors and especially extracellular vesicles containing melanoma-associated proteins and miRNAs, with unique protein signatures reflecting early versus advanced metastatic spread. Furthermore, lymphatic exudate was enriched in memory T cells, including tumor-reactive CD137+ and stem cell-like types. In mice, lymph vessels were the major route of extracellular vesicle transport from tumors to the systemic circulation. We suggest that lymphatic exudate provides a rich source of tumor-derived factors for enabling the discovery of novel biomarkers that may reflect disease stage and therapeutic response.

The CD8 T cell response to the HLA-A2-restricted epitope LLWNGPMAV (LLW) of the non-structural protein 4b of Yellow Fever Virus (YFV) is remarkably immunodominant, highly prevalent and powerful in YFV-vaccinated humans. Here we used a combinatorial peptide library screening in the context of an A2/LLW-specific CD8 T cell clone to identify a superagonist that features a methionine to isoleucine substitution at position 7. Based on in silico modeling, the functional enhancement of this LLW-7I mutation was associated with alterations in the structural dynamics of the peptide in the major histocompatibility complex (pMHC) binding with the T cell receptor (TCR). While the TCR off-rate of LLW-7I pMHC is comparable to the wild type peptide, the rigidity of the 7I peptide seems to confer less entropy loss upon TCR binding. This LLW-7I superagonist is an example of improved functionality in human CD8 T cells associated with optimized ligand rigidity for TCR binding and not with changes in TCR:pMHC off-rate kinetics.

The understanding of the role of B cells in patients with solid tumors remains insufficient. We found that circulating B cells produced TNFα and/or IL-6, associated with unresponsiveness and poor overall survival of melanoma patients treated with anti-CTLA4 antibody. Transcriptome analysis of B cells from melanoma metastases showed enriched expression of inflammatory response genes. Publicly available single B cell data from the tumor microenvironment revealed a negative correlation between TNFα expression and response to immune checkpoint blockade. These findings suggest that B cells contribute to tumor growth via the production of inflammatory cytokines. Possibly, these B cells are different from tertiary lymphoid structure-associated B cells, which have been described to correlate with favorable clinical outcome of cancer patients. Further studies are required to identify and characterize B cell subsets and their functions promoting or counteracting tumor growth, with the aim to identify biomarkers and novel treatment targets.

SARS-CoV-2 caused one of the most devastating pandemics in the recent history of mankind. Due to various countermeasures, including lock-downs, wearing masks, and increased hygiene, the virus has been controlled in some parts of the world. More recently, the availability of vaccines, based on RNA or adenoviruses, has greatly added to our ability to keep the virus at bay; again, however, in some parts of the world only. While available vaccines are effective, it would be desirable to also have more classical vaccines at hand for the future. Key feature of vaccines for long-term control of SARS-CoV-2 would be inexpensive production at large scale, ability to make multiple booster injections, and long-term stability at 4℃.

Chimeric antigen receptor (CAR) T cell therapy targeting B cell maturation antigen (BCMA) on multiple myeloma (MM) produces fast but not long-lasting responses. Reasons for treatment failure are poorly understood. CARs simultaneously targeting two antigens may represent an alternative. Here, we (1) designed and characterized novel A proliferation inducing ligand (APRIL) based dual-antigen targeting CARs, and (2) investigated mechanisms of resistance to CAR T cells with three different BCMA-binding moieties (APRIL, single-chain-variable-fragment, heavy-chain-only).

Personalized cancer vaccines hold promises for future cancer therapy. Targeting neoantigens is perceived as more beneficial compared to germline, non-mutated antigens. However, it is a practical challenge to identify and vaccinate patients with neoantigens. Here we asked whether two neoantigens are sufficient, and whether the addition of germline antigens would enhance the therapeutic efficacy. We developed and used a personalized cancer nano-vaccine platform based on virus-like particles loaded with toll-like receptor ligands. We generated three sets of multi-target vaccines (MTV) to immunize against the aggressive B16F10 murine melanoma: one set based on germline epitopes (GL-MTV) identified by immunopeptidomics, another set based on mutated epitopes (Mutated-MTV) predicted by whole exome sequencing and a last set combines both germline and mutated epitopes (Mix-MTV). Our results demonstrate that both germline and mutated epitopes induced protection but the best therapeutic effect was achieved with the combination of both. Our platform is based on Cu-free click chemistry used for peptide-VLP coupling, thus enabling bedside production of a personalized cancer vaccine, ready for clinical translation.

The roles of NK cells in human melanoma remain only partially understood. We characterized NK cells from peripheral blood ex vivo by flow cytometry obtained from late stage (III/IV) melanoma patients. Interestingly, we found that the abundance of CD56bright NK cells negatively correlate with overall patient survival, together with distant metastases, in a multivariate cox regression analysis. The patients' CD56bright NK cells showed upregulation of CD11a, CD38 and CD95 as compared to healthy controls, pointing to an activated phenotype as well as a possible immune regulatory role in melanoma patients. After stimulation in vitro, CD56bright NK cells produced less TNFα and GMCSF in patients than controls. Furthermore, IFNγ production by the CD56bright NK cells correlated inversely with overall survival. Our results highlight that abundance and function of CD56bright NK cells are associated with melanoma patient survival, emphasizing the potential of NK cell subsets for biomarker discovery and future therapeutic targeting.