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.

The SwissBioisostere database (http://www.swissbioisostere.ch) contains information on molecular replacements and their performance in biochemical assays. It is meant to provide researchers in drug discovery projects with ideas for bioisosteric modifications of their current lead molecule, as well as to give interested scientists access to the details on particular molecular replacements. As of August 2012, the database contains 21,293,355 datapoints corresponding to 5,586,462 unique replacements that have been measured in 35,039 assays against 1948 molecular targets representing 30 target classes. The accessible data were created through detection of matched molecular pairs and mining bioactivity data in the ChEMBL database. The SwissBioisostere database is hosted by the Swiss Institute of Bioinformatics and available via a web-based interface.

Hepatoblastoma is the most common malignant pediatric liver cancer. Histological evaluation of tumor biopsies is used to distinguish among the different subtypes of hepatoblastoma, with fetal and embryonal representing the two main epithelial components. With frequent CTNNB1 mutations, hepatoblastoma is a Wnt/β-catenin-driven malignancy. Considering that Wnt activation has been associated with tumor metabolic reprogramming, we characterized the metabolic profile of cells from hepatoblastoma and compared it to cells from hepatocellular carcinoma. First, we demonstrated that glucose transporter GLUT3 is a direct TCF4/β-catenin target gene. RNA sequencing enabled to identify molecular and metabolic features specific to hepatoblastoma and revealed that several glycolytic enzymes are overexpressed in embryonal-like compared to fetal-like tumor cells. This led us to implement successfully three biomarkers to distinguish embryonal from fetal components by immunohistochemistry from a large panel of human hepatoblastoma samples. Functional analyses demonstrated that embryonal-like hepatoblastoma cells are highly glycolytic and sensitive to hexokinase-1 silencing. Altogether, our findings reveal a new, metabolic classification of human hepatoblastoma, with potential future implications for patients' diagnosis and treatment.

The mechanisms regulating exhaustion of tumor-infiltrating lymphocytes (TIL) and responsiveness to PD-1 blockade remain partly unknown. In human ovarian cancer, we show that tumor-specific CD8+ TIL accumulate in tumor islets, where they engage antigen and upregulate PD-1, which restrains their functions. Intraepithelial PD-1+CD8+ TIL can be, however, polyfunctional. PD-1+ TIL indeed exhibit a continuum of exhaustion states, with variable levels of CD28 costimulation, which is provided by antigen-presenting cells (APC) in intraepithelial tumor myeloid niches. CD28 costimulation is associated with improved effector fitness of exhausted CD8+ TIL and is required for their activation upon PD-1 blockade, which also requires tumor myeloid APC. Exhausted TIL lacking proper CD28 costimulation in situ fail to respond to PD-1 blockade, and their response may be rescued by local CTLA-4 blockade and tumor APC stimulation via CD40L.

Recent evidence suggests that numerous similarities exist between the genomic landscapes of both conjunctival and cutaneous melanoma. Since alterations of several components of the MAP kinases, PI3K/mTOR, and cell cycle pathways have been reported in conjunctival melanoma, we decided to assess the sensitivity of conjunctival melanoma to targeted inhibition mostly of kinase inhibitors. A high content drug screening assay based on automated fluorescence microscopy was performed in three conjunctival melanoma cell lines with different genomic backgrounds with 489 kinase inhibitors and 53 other inhibitors. IC50 and apoptosis induction were respectively assessed for 53 and 48 compounds. The genomic background influenced the response to MAK and PI3K/mTOR inhibition, more specifically cell lines with BRAF V600E mutations were more sensitive to BRAF/MEK inhibition, while CRMM2 bearing the NRASQ61L mutation was more sensitive to PI3k/mTOR inhibition. All cell lines demonstrated sensitivity to cell cycle inhibition, being more pronounced in CRMM2, especially with polo-like inhibitors. Our data also revealed new vulnerabilities to Hsp90 and Src inhibition. This study demonstrates that the genomic background partially influences the response to targeted therapy and uncovers a large panel of potential vulnerabilities in conjunctival melanoma that may expand available options for the management of this tumor.

The development of immune checkpoint inhibitors (ICIs) has revolutionized cancer therapy but only a fraction of patients benefits from this therapy. Model-informed drug development can be used to assess prognostic and predictive clinical factors or biomarkers associated with treatment response. Most pharmacometric models have thus far been developed using data from randomized clinical trials, and further studies are needed to translate their findings into the real-world setting. We developed a tumor growth inhibition model based on real-world clinical and imaging data in a population of 91 advanced melanoma patients receiving ICIs (i.e., ipilimumab, nivolumab, and pembrolizumab). Drug effect was modeled as an ON/OFF treatment effect, with a tumor killing rate constant identical for the three drugs. Significant and clinically relevant covariate effects of albumin, neutrophil to lymphocyte ratio, and Eastern Cooperative Oncology Group (ECOG) performance status were identified on the baseline tumor volume parameter, as well as NRAS mutation on tumor growth rate constant using standard pharmacometric approaches. In a population subgroup (n = 38), we had the opportunity to conduct an exploratory analysis of image-based covariates (i.e., radiomics features), by combining machine learning and conventional pharmacometric covariate selection approaches. Overall, we demonstrated an innovative pipeline for longitudinal analyses of clinical and imaging RWD with a high-dimensional covariate selection method that enabled the identification of factors associated with tumor dynamics. This study also provides a proof of concept for using radiomics features as model covariates.

Specific metabolic pathways are activated by different nutrients to adapt the organism to available resources. Although essential, these mechanisms are incompletely defined. Here, we report that medium-chain fatty acids contained in coconut oil, a major source of dietary fat, induce the liver ω-oxidation genes Cyp4a10 and Cyp4a14 to increase the production of dicarboxylic fatty acids. Furthermore, these activate all ω- and β-oxidation pathways through peroxisome proliferator activated receptor (PPAR) α and PPARγ, an activation loop normally kept under control by dicarboxylic fatty acid degradation by the peroxisomal enzyme L-PBE. Indeed, L-pbe(-/-) mice fed coconut oil overaccumulate dicarboxylic fatty acids, which activate all fatty acid oxidation pathways and lead to liver inflammation, fibrosis, and death. Thus, the correct homeostasis of dicarboxylic fatty acids is a means to regulate the efficient utilization of ingested medium-chain fatty acids, and its deregulation exemplifies the intricate relationship between impaired metabolism and inflammation.

Molecular docking is a computational approach for predicting the most probable position of ligands in the binding sites of macromolecules and constitutes the cornerstone of structure-based computer-aided drug design. Here, we present a new algorithm called Attracting Cavities that allows molecular docking to be performed by simple energy minimizations only. The approach consists in transiently replacing the rough potential energy hypersurface of the protein by a smooth attracting potential driving the ligands into protein cavities. The actual protein energy landscape is reintroduced in a second step to refine the ligand position. The scoring function of Attracting Cavities is based on the CHARMM force field and the FACTS solvation model. The approach was tested on the 85 experimental ligand-protein structures included in the Astex diverse set and achieved a success rate of 80% in reproducing the experimental binding mode starting from a completely randomized ligand conformer. The algorithm thus compares favorably with current state-of-the-art docking programs.

To be effective as a drug, a potent molecule must reach its target in the body in sufficient concentration, and stay there in a bioactive form long enough for the expected biologic events to occur. Drug development involves assessment of absorption, distribution, metabolism and excretion (ADME) increasingly earlier in the discovery process, at a stage when considered compounds are numerous but access to the physical samples is limited. In that context, computer models constitute valid alternatives to experiments. Here, we present the new SwissADME web tool that gives free access to a pool of fast yet robust predictive models for physicochemical properties, pharmacokinetics, drug-likeness and medicinal chemistry friendliness, among which in-house proficient methods such as the BOILED-Egg, iLOGP and Bioavailability Radar. Easy efficient input and interpretation are ensured thanks to a user-friendly interface through the login-free website http://www.swissadme.ch. Specialists, but also nonexpert in cheminformatics or computational chemistry can predict rapidly key parameters for a collection of molecules to support their drug discovery endeavours.

APOBEC3G (apolipoprotein B mRNA-editing enzyme, catalytic polypeptide-like 3G) has antiretroviral activity associated with the hypermutation of viral DNA through cytosine deamination. APOBEC3G has two cytosine deaminase (CDA) domains; the catalytically inactive amino-terminal domain of APOBEC3G (N-CDA) carries the Vif interaction domain. There is no 3-D structure of APOBEC3G solved by X-ray or nuclear magnetic resonance.

Homology modeling is the most commonly used technique to build a three-dimensional model for a protein sequence. It heavily relies on the quality of the sequence alignment between the protein to model and related proteins with a known three dimensional structure. Alignment quality can be assessed according to the physico-chemical properties of the three dimensional models it produces. In this work, we introduce fifteen predictors designed to evaluate the properties of the models obtained for various alignments. They consist of an energy value obtained from different force fields (CHARMM, ProsaII or ANOLEA) computed on residue selected around misaligned regions. These predictors were evaluated on ten challenging test cases. For each target, all possible ungapped alignments are generated and their corresponding models are computed and evaluated. The best predictor, retrieving the structural alignment for 9 out of 10 test cases, is based on the ANOLEA atomistic mean force potential and takes into account residues around misaligned secondary structure elements. The performance of the other predictors is significantly lower. This work shows that substantial improvement in local alignments can be obtained by careful assessment of the local structure of the resulting models.

The haem enzyme indoleamine 2,3-dioxygenase 1 (IDO1) catalyses the rate-limiting step in the kynurenine pathway of tryptophan metabolism and plays an essential role in immunity, neuronal function, and ageing. Expression of IDO1 in cancer cells results in the suppression of an immune response, and therefore IDO1 inhibitors have been developed for use in anti-cancer immunotherapy. Here, we report an extension of our previously described highly efficient haem-binding 1,2,3-triazole and 1,2,4-triazole inhibitor series, the best compound having both enzymatic and cellular IC50 values of 34 nM. We provide enzymatic inhibition data for almost 100 new compounds and X-ray diffraction data for one compound in complex with IDO1. Structural and computational studies explain the dramatic drop in activity upon extension to pocket B, which has been observed in diverse haem-binding inhibitor scaffolds. Our data provides important insights for future IDO1 inhibitor design.

Acral melanoma is a rare melanoma subtype with poor prognosis. Importantly, these patients were not identified as a specific subgroup in the landmark melanoma trials involving ipilimumab and the anti-programmed cell death protein-1 (PD-1) agents nivolumab and pembrolizumab. There is therefore an absence of prospective clinical trial evidence regarding the efficacy of checkpoint inhibitors (CPIs) in this population. Acral melanoma has lower tumor mutation burden (TMB) than other cutaneous sites, and primary site is associated with differences in TMB. However the impact of this on the effectiveness of immune CPIs is unknown. We examined the efficacy of CPIs in acral melanoma, including by primary site.

The use of electronic patient-reported outcome (ePRO) data in routine care has been tied to direct patient benefits such as improved quality of care and symptom control and even overall survival. The modes of action behind such benefits are seldom described in detail. Here, we describe the development of a model of care leveraging ePRO data to monitor and manage symptoms of patients treated with immune checkpoint inhibitors.

Persistent viruses are kept in check by specific lymphocytes. The clonal T cell receptor (TCR) repertoire against Epstein-Barr virus (EBV), once established following primary infection, exhibits a robust stability over time. However, the determinants contributing to this long-term persistence are still poorly characterized. Taking advantage of an in vivo clinical setting where lymphocyte homeostasis was transiently perturbed, we studied EBV antigen-specific CD8 T cells before and after non-myeloablative lympho-depleting chemotherapy of melanoma patients. Despite more advanced T cell differentiation, patients T cells showed clonal composition comparable to healthy individuals, sharing a preference for TRBV20 and TRBV29 gene segment usage and several co-dominant public TCR clonotypes. Moreover, our data revealed the presence of relatively few dominant EBV antigen-specific T cell clonotypes, which mostly persisted following transient lympho-depletion (TLD) and lymphocyte recovery, likely related to absence of EBV reactivation and de novo T cell priming in these patients. Interestingly, persisting clonotypes frequently co-expressed memory/homing-associated genes (CD27, IL7R, EOMES, CD62L/SELL and CCR5) supporting the notion that they are particularly important for long-lasting CD8 T cell responses. Nevertheless, the clonal composition of EBV-specific CD8 T cells was preserved over time with the presence of the same dominant clonotypes after non-myeloablative chemotherapy. The observed clonotype persistence demonstrates high robustness of CD8 T cell homeostasis and reconstitution.

Optimal vaccine strategies must be identified for improving T-cell vaccination against infectious and malignant diseases. MelQbG10 is a virus-like nano-particle loaded with A-type CpG-oligonucleotides (CpG-ODN) and coupled to peptide(16-35) derived from Melan-A/MART-1. In this phase IIa clinical study, four groups of stage III-IV melanoma patients were vaccinated with MelQbG10, given (i) with IFA (Montanide) s.c.; (ii) with IFA s.c. and topical Imiquimod; (iii) i.d. with topical Imiquimod; or (iv) as intralymph node injection. In total, 16/21 (76%) patients generated ex vivo detectable Melan-A/MART-1-specific T-cell responses. T-cell frequencies were significantly higher when IFA was used as adjuvant, resulting in detectable T-cell responses in all (11/11) patients, with predominant generation of effector-memory-phenotype cells. In turn, Imiquimod induced higher proportions of central-memory-phenotype cells and increased percentages of CD127(+) (IL-7R) T cells. Direct injection of MelQbG10 into lymph nodes resulted in lower T-cell frequencies, associated with lower proportions of memory and effector-phenotype T cells. Swelling of vaccine site draining lymph nodes, and increased glucose uptake at PET/CT was observed in 13/15 (87%) of evaluable patients, reflecting vaccine triggered immune reactions in lymph nodes. We conclude that the simultaneous use of both Imiquimod and CpG-ODN induced combined memory and effector CD8(+) T-cell responses.

TCRep 3D is an automated systematic approach for TCR-peptide-MHC class I structure prediction, based on homology and ab initio modeling. It has been considerably generalized from former studies to be applicable to large repertoires of TCR. First, the location of the complementary determining regions of the target sequences are automatically identified by a sequence alignment strategy against a database of TCR Vα and Vβ chains. A structure-based alignment ensures automated identification of CDR3 loops. The CDR are then modeled in the environment of the complex, in an ab initio approach based on a simulated annealing protocol. During this step, dihedral restraints are applied to drive the CDR1 and CDR2 loops towards their canonical conformations, described by Al-Lazikani et. al. We developed a new automated algorithm that determines additional restraints to iteratively converge towards TCR conformations making frequent hydrogen bonds with the pMHC. We demonstrated that our approach outperforms popular scoring methods (Anolea, Dope and Modeller) in predicting relevant CDR conformations. Finally, this modeling approach has been successfully applied to experimentally determined sequences of TCR that recognize the NY-ESO-1 cancer testis antigen. This analysis revealed a mechanism of selection of TCR through the presence of a single conserved amino acid in all CDR3β sequences. The important structural modifications predicted in silico and the associated dramatic loss of experimental binding affinity upon mutation of this amino acid show the good correspondence between the predicted structures and their biological activities. To our knowledge, this is the first systematic approach that was developed for large TCR repertoire structural modeling.

The cross-recognition of peptides by cytotoxic T lymphocytes is a key element in immunology and in particular in peptide based immunotherapy. Here we develop three-dimensional (3D) quantitative structure-activity relationships (QSARs) to predict cross-recognition by Melan-A-specific cytotoxic T lymphocytes of peptides bound to HLA A*0201 (hereafter referred to as HLA A2). First, we predict the structure of a set of self- and pathogen-derived peptides bound to HLA A2 using a previously developed ab initio structure prediction approach [Fagerberg et al., J. Mol. Biol., 521-46 (2006)]. Second, shape and electrostatic energy calculations are performed on a 3D grid to produce similarity matrices which are combined with a genetic neural network method [So et al., J. Med. Chem., 4347-59 (1997)] to generate 3D-QSAR models. The models are extensively validated using several different approaches. During the model generation, the leave-one-out cross-validated correlation coefficient (q (2)) is used as the fitness criterion and all obtained models are evaluated based on their q (2) values. Moreover, the best model obtained for a partitioned data set is evaluated by its correlation coefficient (r = 0.92 for the external test set). The physical relevance of all models is tested using a functional dependence analysis and the robustness of the models obtained for the entire data set is confirmed using y-randomization. Finally, the validated models are tested for their utility in the setting of rational peptide design: their ability to discriminate between peptides that only contain side chain substitutions in a single secondary anchor position is evaluated. In addition, the predicted cross-recognition of the mono-substituted peptides is confirmed experimentally in chromium-release assays. These results underline the utility of 3D-QSARs in peptide mimetic design and suggest that the properties of the unbound epitope are sufficient to capture most of the information to determine the cross-recognition.

Immune checkpoint inhibitor (ICI)-related myocarditis is a rare but potentially fatal adverse event that can occur following ICI exposure. Early diagnosis and treatment are key to improve patient outcomes. Somatostatin receptor-based positron emission tomography-CT (PET/CT) showed promising results for the assessment of myocardial inflammation, yet information regarding its value for the diagnosis of ICI-related myocarditis, especially at the early stage, is limited. Thus, we investigated the value of 68Ga-DOTA(0)-Phe(1)-Tyr(3)-octreotide (68Ga-DOTATOC) PET/CT for the early detection and diagnosis of ICI-related myocarditis.

How targeted therapies and immunotherapies shape tumors, and thereby influence subsequent therapeutic responses, is poorly understood. In the present study, we show, in melanoma patients and mouse models, that when tumors relapse after targeted therapy with MAPK pathway inhibitors, they are cross-resistant to immunotherapies, despite the different modes of action of these therapies. We find that cross-resistance is mediated by a cancer cell-instructed, immunosuppressive tumor microenvironment that lacks functional CD103+ dendritic cells, precluding an effective T cell response. Restoring the numbers and functionality of CD103+ dendritic cells can re-sensitize cross-resistant tumors to immunotherapy. Cross-resistance does not arise from selective pressure of an immune response during evolution of resistance, but from the MAPK pathway, which not only is reactivated, but also exhibits an increased transcriptional output that drives immune evasion. Our work provides mechanistic evidence for cross-resistance between two unrelated therapies, and a scientific rationale for treating patients with immunotherapy before they acquire resistance to targeted therapy.