Convergence of Technology and Cancer Immunotherapy最新文献

{"title":"Abstract B030: Predicting the response of uveal melanoma to immunotherapy with MRI assessments","authors":"A. Moreira, M. Saake, G. Schuler, L. Heinzerling","doi":"10.1158/2326-6074.CRICIMTEATIAACR18-B030","DOIUrl":"https://doi.org/10.1158/2326-6074.CRICIMTEATIAACR18-B030","url":null,"abstract":"Purpose: Contrary to cutaneous melanoma, uveal melanoma is little responsive to immune checkpoint inhibitors. This is thought to result from a different immunogenicity of these two melanoma variants. We sought to investigate whether imaging properties in magnetic resonance imaging (MRI) were able to predict the response of liver metastases of uveal melanoma to immune checkpoint blockade. Study Design: Pre- and post-therapeutic liver MRIs, including a native T1-weighted fat-saturated FLASH sequence, were analyzed in a population of patients with uveal melanoma, segmenting the metastasis into areas of active tumor, necrosis and edema. Different lesions from all of the patients were investigated and their patterns correlated with response to immunotherapy. Results: Contrary to previous results of other research groups, MRI signal intensity scores in our population could not predict response to immunotherapy. Therefore, we could not validate the MRI assessment as a clinical biomarker. Other parameters need to be integrated in the radiomic signature. Conclusions: Current MRI imaging methods are limited in their ability to predict response of liver metastases of uveal melanoma to immune checkpoint blockade. Advanced MRI imaging methods, more sensitized to different biophysical processes including blood perfusion and tumor metabolism, which can provide more specific information on tissue physiology, should be investigated in the light of emerging immunotherapies for uveal melanoma, such as tumor-infiltrating lymphocytes and recent developments in dendritic cell cancer vaccines. Citation Format: Alvaro Moreira, Marc Saake, Gerold Schuler, Lucie Heinzerling. Predicting the response of uveal melanoma to immunotherapy with MRI assessments [abstract]. In: Proceedings of the Fourth CRI-CIMT-EATI-AACR International Cancer Immunotherapy Conference: Translating Science into Survival; Sept 30-Oct 3, 2018; New York, NY. Philadelphia (PA): AACR; Cancer Immunol Res 2019;7(2 Suppl):Abstract nr B030.","PeriodicalId":352838,"journal":{"name":"Convergence of Technology and Cancer Immunotherapy","volume":"41 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131624885","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Abstract B015: T-cell recognition profiling of CD8+ T-cells in tumor-infiltrating lymphocytes expanded for adoptive cell transfer","authors":"Christina Heeke, Anne-Mette Bjerregaard, A. Bentzen, M. Donia, R. Andersen, M. Svane, S. Hadrup","doi":"10.1158/2326-6074.CRICIMTEATIAACR18-B015","DOIUrl":"https://doi.org/10.1158/2326-6074.CRICIMTEATIAACR18-B015","url":null,"abstract":"Adoptive T-cell therapy (ACT) has proven to be a highly effective therapy option for melanoma and other immunogenic cancer types, however only a subset of 40% of the patients respond. Due to the intensive and costly regimen, it is important to find predictive biomarkers to identify patients that more likely respond to therapy.Melanoma-associated tissue antigens play an important role in melanoma immunotherapy, as they are expressed in the majority of tumors across different patients and can elicit T-cell recognition. Furthermore, such melanoma-associated T-cell responses may serve as a surrogate marker for T-cell reactivity in general and hence potentially also reflect the level of neoepitope reactivity. Several recent reports point towards the importance of mutation-derived neo-epitopes for cancer immunotherapy, as the mutational and putative neoantigen load correlates with therapeutically benefit of immune checkpoint blockade and ACT. In this study, we analyzed the impact of the number and size of T-cell responses against a library of shared antigens and predicted neoantigens to correlate the number of responses with the outcome of the ACT. We screened expanded tumor-infiltrating lymphocytes (TILs) from stage IV melanoma patients within a phase I/II clinical trial of ACT for CD8+ T-cell reactivity. A library of classical melanoma-associated shared antigens as well as a personalized library of predicted neoantigens for each patient was selected. CD8+ T-cell recognition in the TIL product was investigated by use of a novel technology based on DNA-barcode labeled MHC multimers, enabling high-throughput screening for >1,000 specific T-cell-populations in a single sample. Specific T-cell responses against shared antigens could be found and verified among the TIL samples. The number of CD8+ T-cells responses against tumor-associated shared antigens does not seem to correlate with progression-free or overall survival in this patient cohort, but further screenings have to be conducted. The analysis of neoantigen-reactive CD8+ T-cells within the TILs is ongoing.Identification of predictive biomarkers is an important step towards higher effectiveness of adoptive cell transfer as immunotherapeutic approach and the recognition pattern of melanoma by CD8+ T-cells associated with favorable clinical outcome provides mechanistic insights important for future developments. Citation Format: Christina Heeke, Anne-Mette Bjerregaard, Amalie Kai Bentzen, Marco Donia, Rikke Andersen, Marie Stentoft Svane, Sine Reker Hadrup. T-cell recognition profiling of CD8+ T-cells in tumor-infiltrating lymphocytes expanded for adoptive cell transfer [abstract]. In: Proceedings of the Fourth CRI-CIMT-EATI-AACR International Cancer Immunotherapy Conference: Translating Science into Survival; Sept 30-Oct 3, 2018; New York, NY. Philadelphia (PA): AACR; Cancer Immunol Res 2019;7(2 Suppl):Abstract nr B015.","PeriodicalId":352838,"journal":{"name":"Convergence of Technology and Cancer Immunotherapy","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130678144","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Abstract B022: Properties of T-cell-recognized neoantigens","authors":"P. Kvistborg, Marit M. van Buuren, Daisy Philips, N. Rooij, A. Velds, S. Behjati, M. Braber, M. Toebes, Lorenzo F. Fanchi, M. Slagter, M. Svane, P. Hwu, J. H. Berg, M. Stratton, C. Blank, J. Haanen, C. Keşmir, T. Schumacher","doi":"10.1158/2326-6074.CRICIMTEATIAACR18-B022","DOIUrl":"https://doi.org/10.1158/2326-6074.CRICIMTEATIAACR18-B022","url":null,"abstract":"Over the past years we have learned that the T-cell-based immune system frequently responds to the neoantigens that arise as a consequence of the accumulated DNA damage causing the malignant transformation. Furthermore, recognition of neoantigens appears an important driver of the clinical activity of both T-cell checkpoint blockade and adoptive T-cell therapy as cancer immunotherapies. From the efforts dissecting the neoantigen-specific T-cell response it has become clear that only a very minor fraction of the accumulated mutations is recognized by the immune system, and the challenge to unravel the neoantigen-specific T-cell response lies in identifying which neoantigens are more likely to be true T-cell epitopes. We have analyzed neoantigen-specific T-cell reactivity in 12 melanoma patients using an in silico epitope prediction pipeline based on RNA expression, predicted HLA binding affinity, proteasomal processing and self-similarity to predict potential neoepitopes. We screened for T-cell recognition of 7000 epitopes from these 12 patients (average ~550 epitopes per patient, range: 96-1902) using our pMHC multimer combinatorial encoding technology and found 19 epitopes to be recognized by T-cells (hits) and 6981 to be “non-hits.” Based on these data we have examined the properties of T-cell recognized neoantigens. An intriguing observation is an enrichment within T-cell recognized epitopes of epitopes with the mutation positioned within the last 4 amino acids (C-terminal end of the peptide) compared to the screened set of epitopes. Fifteen out of 19 hits (approximately 80%) harbored a mutation within the last 4 amino acids of the peptide, whereas within the full set of screen epitopes it is 43%. While it is currently unclear what the reason is for this, this could reflect a biologic importance in T-cell recognition of the C-terminal part of the epitope. Furthermore, RNA expression and predicted binding affinity to HLA are important informative parameters for selecting T-cell recognized epitopes. A striking observation is that predicted binding affinity not only correlates with likelihood of observing a T-cell response but also the magnitude of this T-cell response, suggesting a hierarchy within neoantigens, and that not all neoantigens are of equal immunologic quality. In summary, our findings indicate that T-cell recognized neoantigens may differ from the neoantigen pool not recognized. In particular regarding position of the mutation with the epitope, RNA abundance and predicted HLA binding affinity. Importantly, our data reveal a hierarchy within neoantigens comparable to immunodominance known from viral infections. This hierarchy appears to depend mostly on binding affinity. These observations are likely to be highly relevant when selecting neoantigens for therapeutic manipulation such as vaccines. Citation Format: Pia Kvistborg, Marit M. van Buuren, Daisy Philips, Nienke van Rooij, Arno Velds, Sam Behjati, Marlous van den Braber, Mireil","PeriodicalId":352838,"journal":{"name":"Convergence of Technology and Cancer Immunotherapy","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130880074","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Abstract B047: Next-generation gene expression enables tumor-focused immuno-oncology therapies","authors":"Patrick Stern","doi":"10.1158/2326-6074.CRICIMTEATIAACR18-B047","DOIUrl":"https://doi.org/10.1158/2326-6074.CRICIMTEATIAACR18-B047","url":null,"abstract":"To move cancer immuno-therapies forward, the tumor must participate in treatment. The goal is treatments that provoke tumors to activate cancer-killing immunity, but the basic research technologies to develop these therapies were sorely lacking until now. Our next-generation gene expression system can mimic pharmacologic intervention for any target in growing tumors in mice, enabling high-confidence target assessments before committing to compound development. We have used this technology to understand the mechanisms controlling CTL-activating apoptosis—Immunizing Cell Death (ICD)—and have identified drug-able pathways that will synergize with existing clinical cytotoxic drugs and cause tumors to provoke antitumor immunity. Developed over 8 years at the MIT Koch Institute, our patented Switch expression system is the only “translation control” system and is 1000-times faster than existing “transcription-based” technologies. This speed enables gene expression with drug-like kinetics. More importantly, our novel control enables unmatched drug target assessments by mimicking targeted therapy in growing tumors. Switch is designed to express a first gene and then “switch” for a second gene (e.g., express a kinase and replace with kinase-dead to mimic kinase inhibitors) in growing tumors or in vitro. Switch has been used in 20+ cell lines and transplantable tumor models and is the follow-on to CRISPR-based efforts where the endogenous gene is deleted. Delivered into cancer cells with optimized lentiviral vectors, Switch can replace the CRISPRed genomic target and then cells may be transplanted into mice or grown/ differentiated in vitro. When engineered cells reach the desired point (e.g., a mature tumor), Tamoxifen-CreER recombination causes deletion of the first gene and expression of the second gene. This strategy recapitulates the “logic” of drug treatment—acute functional perturbation of a target protein—and elevates preclinical drug RD Sept 30-Oct 3, 2018; New York, NY. Philadelphia (PA): AACR; Cancer Immunol Res 2019;7(2 Suppl):Abstract nr B047.","PeriodicalId":352838,"journal":{"name":"Convergence of Technology and Cancer Immunotherapy","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117144703","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Abstract B028: Label-free Raman signatures of immune cells: A new tool for artificial intelligence in immunotherapy","authors":"Girish Chundayil Madathil, Raveena Nagareddy, A. Ramkumar, M. Krishnan, V. Harish, A. Ashokan, S. Nair, Manzoor Koyakutty","doi":"10.1158/2326-6074.CRICIMTEATIAACR18-B028","DOIUrl":"https://doi.org/10.1158/2326-6074.CRICIMTEATIAACR18-B028","url":null,"abstract":"In the emerging era of artificial intelligence mediated immune response analysis, post- imunotherapeutic interventions, monitoring of large pool of data related to different types of immune cells is a critical requirement. Several gold standard methodologies such as flow cytometry, cytoTOF, ELISPOT and other immune-imaging techniques are routinely used for quantifying the phenotypic behavior of immune cells. These techniques involve the use of antibodies for specifically labeling each cell types, which makes the procedure expensive and laborious. Here, we are presenting a novel approach for label free detection of various types of immune cells using their inherent vibrational Raman signatures and a method of using the same data for cluster analysis. Raman spectroscopy is a well-established tool that measures the vibrational fingerprints of the analytes. It has been extensively used in biologic research for differentiating cells and tissues based on their Raman spectral features. Since the basic building block molecules of the cells are the same, variations in the spectral features among cells and tissues are minimal. Mathematical tools such as multivariate statistical analysis and machine learning methods are adopted to identify the significant Raman spectral features that cause the variation among groups (DC, macrophage, NK, T-cell, B cell, neutrophils, etc.). In immunology, no studies have been reported so far in understanding and recording the inherent Raman spectral finger prints of all forms of immune cells, both in the naive and active stage. In this study, we have created a spectral database of various immune cells such as T-cells, B cells, NK cells, dendritic cells, macrophages, neutrophils and their signature variations in activated and naive forms. These spectral databases can be used in machine learning algorithms to predict the treatment response in clinical and preclinical settings. Citation Format: Girish Chundayil Madathil, Raveena Nagareddy, Anjana Ramkumar, Manu Krishnan, Vijay Harish, Anusha Ashokan, Shanti Kumar Nair, Manzoor Koyakutty. Label-free Raman signatures of immune cells: A new tool for artificial intelligence in immunotherapy [abstract]. In: Proceedings of the Fourth CRI-CIMT-EATI-AACR International Cancer Immunotherapy Conference: Translating Science into Survival; Sept 30-Oct 3, 2018; New York, NY. Philadelphia (PA): AACR; Cancer Immunol Res 2019;7(2 Suppl):Abstract nr B028.","PeriodicalId":352838,"journal":{"name":"Convergence of Technology and Cancer Immunotherapy","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129055584","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Abstract B008: Treatment of IDO1 and TDO2 positive tumors with a kynurenine-degrading enzyme: A highly differentiated approach from IDO1 inhibition","authors":"S. Coma, Jillian D. Cavanaugh, James Nolan, J. Tchaicha, Karen McGovern, E. Stone, John Blazeck, Candice Lamb, G. Georgiou, M. Manfredi, Michelle J. Zhang","doi":"10.1158/2326-6074.CRICIMTEATIAACR18-B008","DOIUrl":"https://doi.org/10.1158/2326-6074.CRICIMTEATIAACR18-B008","url":null,"abstract":"Despite the sustained clinical benefit demonstrated by immune checkpoint inhibitors, a majority of patients derive minimal or no appreciable benefit, indicating the urgent need to incorporate novel immunomodulatory targets and therapeutic strategies. Indoleamine 2,3-dioxygenase 1 (IDO1) and tryptophan 2,3-dioxygenase 2 (TDO2) catalyze the first and rate-limiting step in the immunosuppressive tryptophan/kynurenine pathway and are both upregulated in a number of tumor types. Although small-molecule IDO1 inhibitors are being clinically evaluated in several tumor types, so far they have not demonstrated significant clinical benefits either as a single agent or in combination with immune checkpoint inhibition. We are developing pegylated kynureninase (Kynase), a kynurenine degrading enzyme, to treat a broader population with IDO1 and/or TDO2 expressing tumors. We believe that a more robust antitumor immune response can be achieved by depleting kynurenine, produced by both IDO1 and TDO2, with Kynase, than by inhibiting only IDO1. The human Kynase (HsKYN) has been successfully engineered to exhibit vastly improved catalytic activity and stability toward kynurenine over the wild-type human enzyme. HsKYN achieved durable and near complete plasma kynurenine depletion in mice, rats and non-human primates. HsKYN demonstrated single agent efficacy in CT26, MC38 and B16-IDO syngeneic mouse models. Tumor gene expression analysis using NanoString revealed that HsKYN treatment upregulated T-cell and NK cell activation signature. More importantly, HsKYN significantly increased the tumor-infiltrating CD8 T-cells and their activation/polyfunctionality, and reduced the Treg population. As a direct comparison, the lead IDO1 inhibitor epacadostat did not impose any meaningful effects on the same immune cell populations. Furthermore, HsKYN showed beneficial combination efficacy with anti-PD-1 that was superior to combined Epacadostat / anti-PD-1. Evidence to date suggest that HsKYN is well tolerated in multiple species. Therefore, immunoprofiling, efficacy and safety results strongly support that Kynase is a more effective therapeutic approach than IDO1 inhibition. HsKYN is moving toward clinical development for treatment of cancers where IDO1 and/or TDO2 pathways play a significant immunosuppressive role. Citation Format: Silvia Coma, Jillian Cavanaugh, James Nolan, Jeremy Tchaicha, Karen McGovern, Everett Stone, John Blazeck, Candice Lamb, George Georgiou, Mark G Manfredi, Michelle Zhang. Treatment of IDO1 and TDO2 positive tumors with a kynurenine-degrading enzyme: A highly differentiated approach from IDO1 inhibition [abstract]. In: Proceedings of the Fourth CRI-CIMT-EATI-AACR International Cancer Immunotherapy Conference: Translating Science into Survival; Sept 30-Oct 3, 2018; New York, NY. Philadelphia (PA): AACR; Cancer Immunol Res 2019;7(2 Suppl):Abstract nr B008.","PeriodicalId":352838,"journal":{"name":"Convergence of Technology and Cancer Immunotherapy","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116416154","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Abstract B005: Linking transcriptomic and imaging features of the melanoma tumor microenvironment","authors":"Andrew X. Chen, R. Gartrell, D. Marks, Thomas D. Hart, Emanuelle M. Rizk, Anthea Monod, R. Rabadán, Y. Saenger","doi":"10.1158/2326-6074.CRICIMTEATIAACR18-B005","DOIUrl":"https://doi.org/10.1158/2326-6074.CRICIMTEATIAACR18-B005","url":null,"abstract":"Background: While immunotherapy has demonstrated success in melanoma, a deeper understanding of the heterogeneous tumor microenvironment is needed for stratifying patients for treatment. Technologies such as quantitative multiplex immunofluorescence (qmIF) imaging and transcriptomic profiling both have the potential to provide such insights. Using these tools, we had previously shown that immune cellular compositions and bulk gene expression in tumors are each related to patient survival. However, the connection between these modalities and their impact on prognosis is not well-understood. Here, we investigate the link between the microenvironmental composition of immune cells, such as cytotoxic T lymphocytes (CTLs) and macrophages, with observed transcriptomic signatures. Furthermore, we uncover spatial correlations in cellular positioning, which supports a mechanistic basis underlying these relationships. Methods: QmIF imaging was obtained from 104 stage II-III primary melanomas from Columbia University Irving Medical Center (CUIMC), which included staining for CTLs (CD3 and CD8), macrophages (CD68), and tumor cells (SOX10). HLA-DR and Ki67 were also stained in order to assess activation and proliferation of immune and tumor cells. Visualization, cell segmentation, and phenotyping were performed using inForm software within Mantra workstation. Spatial relationships between cells were quantified via the inhomogeneous pair correlation function (PCF), which compares the observed probability of two cell types being separated by a given distance to that expected by chance. Disease-specific survival status was known for 64 patients, while mRNA expression for 63 immune-related genes was obtained via NanoString for 53 patients. We assessed the similarity of each sample’s gene expression profile to the cellular subtype signatures from LM22, the reference standard for CIBERSORT. Results: The proportion of CTLs observed via qmIF was significantly associated with the CD8 T-cell transcriptomic signature (Spearman’s rho = 0.33, p Citation Format: Andrew X. Chen, Robyn Gartrell, Douglas K. Marks, Thomas Hart, Emanuelle Rizk, Anthea Monod, Raul Rabadan, Yvonne Saenger. Linking transcriptomic and imaging features of the melanoma tumor microenvironment [abstract]. In: Proceedings of the Fourth CRI-CIMT-EATI-AACR International Cancer Immunotherapy Conference: Translating Science into Survival; Sept 30-Oct 3, 2018; New York, NY. Philadelphia (PA): AACR; Cancer Immunol Res 2019;7(2 Suppl):Abstract nr B005.","PeriodicalId":352838,"journal":{"name":"Convergence of Technology and Cancer Immunotherapy","volume":"264 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124733141","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Abstract B038: A unified genome-wide analysis of dysfunctional T-cell states in cancer and chronic viral infection","authors":"Y. Pritykin, C. Leslie","doi":"10.1158/2326-6074.CRICIMTEATIAACR18-B038","DOIUrl":"https://doi.org/10.1158/2326-6074.CRICIMTEATIAACR18-B038","url":null,"abstract":"Tumor-specific T-cells that have differentiated into a terminal dysfunctional state exist in the tumor microenvironment. A systematic understanding of the requirements of immunotherapeutic rescue of these cells is critically needed to improve clinical results in patients. Mouse models of chronic infection and cancer have been studied to elucidate biologic mechanisms of persistent antigen stimulation resulting in T-cell dysfunction, or “exhaustion.” Recently, chromatin accessibility imprinting has been associated with T-cells falling back into the dysfunctional state after temporary rescue by checkpoint blockade, suggesting epigenetic mechanisms in control of T-cell dysfunction. However, comprehensive characterization of T-cell dysfunction across models based on their epigenetic and transcriptional profiles is lacking.We collected 106 chromatin accessibility (ATAC-seq) samples and 87 gene expression (RNA-seq) samples from seven recent publications. We analyzed these data by first applying batch effect correction using generalized linear modeling. This enabled mapping profiles of chromatin accessibility peaks in gene promoters and enhancers from different studies into the same space. We observed that epigenetic profiles of dysfunctional tumor-infiltrating T-cells and dysfunctional T-cells in chronic viral infection were, surprisingly, extremely similar. Furthermore, a recently characterized discrete distinction between epigenetic profiles of early (day 7-8) and late (day 28-35) dysfunction in the tumor was recapitulated in the model of chronic infection. Overall we observed across mouse models that T-cells committed to becoming dysfunctional early after an immune challenge, rather than first mounting and then loosing an effector response. These observations were also largely recapitulated in gene expression analysis. Differentially expressed genes with massive differential accessibility of their promoter and enhancer peaks during development of dysfunction, observed consistently across models, including transcription factors (TF) well studied in immunity such as Tcf7, Lef1, Satb1, Ikzf2, Tox, are good candidates for further targeted analysis.We then turned to TF binding analysis. We associated absolute levels of chromatin accessibility in peaks of each sample with TF binding (predicted by motif analysis) using regularized negative binomial regression with cross-validation. We estimated the effect of each TF in each sample, which allowed us to map chromatin accessibility profiles into the TF activity space of much lower dimensionality. This mapping largely preserved the hierarchy of relative similarities between samples. We identified key TFs whose binding was associated with open or closed chromatin in functional and dysfunctional cell states. For example, not surprisingly, binding of well known effector factors Eomes and Batf was associated with closed chromatin in naive cells and open chromatin in effector cells. Strikingly, the strongest associa","PeriodicalId":352838,"journal":{"name":"Convergence of Technology and Cancer Immunotherapy","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117271454","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Abstract B001: Generation of ImmTACTM molecules: Engineering high-affinity soluble T-cell receptors for the treatment of cancer","authors":"Izabela Bombik, A. Bortoluzzi, N. Mai, A. Preston, A. Vuidepot, B. Jakobsen, N. Liddy","doi":"10.1158/2326-6074.CRICIMTEATIAACR18-B001","DOIUrl":"https://doi.org/10.1158/2326-6074.CRICIMTEATIAACR18-B001","url":null,"abstract":"Immunotherapeutic strategies are centered on harnessing the human immune system to recognise and destroy cancer cells. At Immunocore, we have developed bi-specific Immune-mobilising monoclonal TCRs Against Cancer (ImmTAC) molecules comprising a soluble TCR fused to an anti-CD3 effector function that redirect T-cells to destroy cancer cells. The TCR-targeting domain overcomes a key limitation of traditional antibody-based therapies by targeting short peptide fragments derived from intracellularly processed proteins presented on the cell surface by human leukocyte antigens (HLAs), offering up to nine-fold more potential targets than are accessible to antibodies. To mediate efficient T-cell-mediated tumor clearance, ImmTAC molecules are engineered to overcome the weak affinities of natural TCRs imposed by thymic selection through a complex multistep engineering process described herein.T-cell clones recognising in-house validated cancer-specific peptides are isolated and affinity-enhanced up to a million fold by introducing mutations to the complementarity determining regions, resulting in picomolar affinity TCRs capable of recognizing exceptionally low numbers of target on the cancer cell surface. The TCR is fused to an anti-CD3 scFv to generate an ImmTAC molecule and is made soluble through the inclusion of a non-native disulphide bond. The efficacy and specificity of the ImmTAC molecule is scrutinized using a range of cellular and molecular assays. The potential application of the ImmTAC platform is exemplified by the expanding portfolio of ImmTAC molecules targeting diverse disease indications. Our lead candidate, IMCgp100, recognizes the melanoma-associated gp100 peptide and is in pivotal trials for the treatment of patients with metastatic uveal melanoma. Citation Format: Izabela Bombik, Alessio Bortoluzzi, Nicole Mai, Andrew Preston, Annelise Vuidepot, Bent K. Jakobsen, Nathaniel Liddy. Generation of ImmTACTM molecules: Engineering high-affinity soluble T-cell receptors for the treatment of cancer [abstract]. In: Proceedings of the Fourth CRI-CIMT-EATI-AACR International Cancer Immunotherapy Conference: Translating Science into Survival; Sept 30-Oct 3, 2018; New York, NY. Philadelphia (PA): AACR; Cancer Immunol Res 2019;7(2 Suppl):Abstract nr B001.","PeriodicalId":352838,"journal":{"name":"Convergence of Technology and Cancer Immunotherapy","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131242812","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Abstract PR14: Identification of specificity TCR groups of tumor antigen specific T-cells","authors":"Liang-en Chen, Chunlin Wang, Mark M. Davis","doi":"10.1158/2326-6074.CRICIMTEATIAACR18-PR14","DOIUrl":"https://doi.org/10.1158/2326-6074.CRICIMTEATIAACR18-PR14","url":null,"abstract":"A major breakthrough in the treatment of advanced melanoma has been the development and FDA approval of immune checkpoint inhibitors. Approximately 20% of the patients who received anti-CTLA-4 or anti-PD-1 therapy have long-term remissions. At the core of the clinical success lies the fact that cancer patients bear T lymphocytes that recognize tumor-specific antigens. It has been proposed that efficacy of immune checkpoint inhibitors is attributable, at least in part, to diversification of T-cell receptor (TCR) repertoire in peripheral circulation. However, current TCR repertoire analyses mostly rely on counting unique TCR sequences, which does not consider the degenerate nature of TCR recognition, that is, many different TCRs can recognize the same antigen peptide and the same TCR can recognize different antigen peptides. This will create roadblocks to identify recurrent TCR clones that likely recognize the same clinically relevant tumor antigen. To understand how TCR sequences encode its specificity, our lab sequenced several thousands of TCRs from T-cells enriched by peptide-major histocompatibility complex multimer (pMHC)-guided cell sorting. We established a TCR repertoire database that contains our own sequences and published TCRs with known specificity. We used this database as the training dataset for a machine learning algorithm that classified TCRs (mainly TCR beta) based on their similarity and specificity. Although the orginal algorithm—termed Grouping of lymphocyte interactions by paratope hotspots(GLIPH)—was proficient in identifying TCR clusters in a small dataset such as those generated by single-cell TCR sequences, it failed to perform reliably when applied to larger data set generated by high-throughput bulk TCR beta sequences. Most importantly, the reference sequences used by GLIPH 1.0 are insufficient when the targeted TCR dataset is much larger. The new version of GLIPH (GLIPH 2.0) was significantly improved in performance and reliability. As a proof of concept, we applied GLIPH 2.0 to TCR-sequences generated from peripheral T-cells of a cohort of melanoma patients. Each of these patients received one infusion of poly-clonal CTLs specific for HLA-A2/MART1. These autologous MART-specific CTLs were generated by priming with MART1 peptide-pulsed dendritic cells and enriched by pMHC-tetramer-guided cell sorting. MART1 peptide stimulation promotes expansion of CTLs based on TCR clonality. However, the overlap of sequences among these polyclonal CTLs is marginal. These TCR sequences were then analyzed by GLIPH and we found that MART1-specific CTLs showed significant enrichment of CDR3 motifs. As a control, we analyzed peripheral TCR repertoire from a group HLA-A2+ healthy donors and found no significant convergence in TCR sequences. This proves that GLIPH 2.0 can reliably identify TCR convergence and antigen specificity CD3 motifs from large-scale TCR beta repertoires. This algorithm can further facilitate the identification of rec","PeriodicalId":352838,"journal":{"name":"Convergence of Technology and Cancer Immunotherapy","volume":"79 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133947258","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}