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Neoantigens arising from mutations in tumor DNA provide targets for immune-based therapy. Here, we report the clinical and immune data from a Phase Ib clinical trial of a personalized neoantigen-vaccine NEO-PV-01 in combination with pemetrexed, carboplatin, and pembrolizumab as first-line therapy for advanced non-squamous non-small cell lung cancer (NSCLC). This analysis of 38 patients treated with the regimen demonstrated no treatment-related serious adverse events. Multiple parameters including baseline tumor immune infiltration and on-treatment circulating tumor DNA levels were highly correlated with clinical response. De novo neoantigen-specific CD4

BackgroundThe ongoing COVID-19 pandemic has created an urgency to identify novel vaccine targets for protective immunity against SARS-CoV-2. Early reports identify protective roles for both humoral and cell-mediated immunity for SARS-CoV-2.MethodsWe leveraged our bioinformatics binding prediction tools for human leukocyte antigen (HLA)-I and HLA-II alleles that were developed using mass spectrometry-based profiling of individual HLA-I and HLA-II alleles to predict peptide binding to diverse allele sets. We applied these binding predictors to viral genomes from theCoronaviridaefamily and specifically focused on T cell epitopes from SARS-CoV-2 proteins. We assayed a subset of these epitopes in a T cell induction assay for their ability to elicit CD8+T cell responses.ResultsWe first validated HLA-I and HLA-II predictions onCoronaviridaefamily epitopes deposited in the Virus Pathogen Database and Analysis Resource (ViPR) database. We then utilized our HLA-I and HLA-II predictors to identify 11,897 HLA-I and 8046 HLA-II candidate peptides which were highly ranked for binding across 13 open reading frames (ORFs) of SARS-CoV-2. These peptides are predicted to provide over 99% allele coverage for the US, European, and Asian populations. From our SARS-CoV-2-predicted peptide-HLA-I allele pairs, 374 pairs identically matched what was previously reported in the ViPR database, originating from other coronaviruses with identical sequences. Of these pairs, 333 (89%) had a positive HLA binding assay result, reinforcing the validity of our predictions. We then demonstrated that a subset of these highly predicted epitopes were immunogenic based on their recognition by specific CD8+T cells in healthy human donor peripheral blood mononuclear cells (PBMCs). Finally, we characterized the expression of SARS-CoV-2 proteins in virally infected cells to prioritize those which could be potential targets for T cell immunity.ConclusionsUsing our bioinformatics platform, we identify multiple putative epitopes that are potential targets for CD4+and CD8+T cells, whose HLA binding properties cover nearly the entire population. We also confirm that our binding predictors can predict epitopes eliciting CD8+T cell responses from multiple SARS-CoV-2 proteins. Protein expression and population HLA allele coverage, combined with the ability to identify T cell epitopes, should be considered in SARS-CoV-2 vaccine design strategies and immune monitoring.

Summary T cells use highly diverse receptors (TCRs) to identify tumor cells presenting neoantigens arising from genetic mutations and establish anti-tumor activity. Immunotherapy harnessing neoantigen-specific T cells to target tumors has emerged as a promising clinical approach. To assess whether a comprehensive peripheral mononuclear blood cell analysis predicts responses to a personalized neoantigen cancer vaccine combined with anti-PD-1 therapy, we characterize the TCR repertoires and T and B cell frequencies in 21 patients with metastatic melanoma who received this regimen. TCR-α/β-chain sequencing reveals that prolonged progression-free survival (PFS) is strongly associated with increased clonal baseline TCR repertoires and longitudinal repertoire stability. Furthermore, the frequencies of antigen-experienced T and B cells in the peripheral blood correlate with repertoire characteristics. Analysis of these baseline immune features enables prediction of PFS following treatment. This method offers a pragmatic clinical approach to assess patients’ immune state and to direct therapeutic decision making., Graphical Abstract, Highlights Pre-treatment blood-based factors predict response to immunotherapy TCR repertoire clonality and stability associate with improved clinical outcomes Baseline T and B cell memory phenotypes associate with improved clinical outcomes Combined baseline TCR repertoire and PBMC phenotypes predict immunotherapy response, Poran et al. study peripheral blood cells from metastatic melanoma patients before, during, and after treatment with personalized neoantigen therapy plus anti-PD-1. The combination of T cell receptor repertoire profiling and immunophenotyping of blood cells collected pre-treatment presents a strong predictor for response to treatment in a minimally invasive manner.

BackgroundThe ongoing COVID-19 pandemic has created an urgency to identify novel vaccine targets for protective immunity against SARS-CoV-2. Consistent with observations for SARS-CoV, a closely related coronavirus responsible for the 2003 SARS outbreak, early reports identify a protective role for both humoral and cell-mediated immunity for SARS CoV-2.MethodsIn this study, we leveraged HLA-I and HLA-II T cell epitope prediction tools from RECON® (Real-time Epitope Computation for ONcology), our bioinformatic pipeline that was developed using proteomic profiling of individual HLA-I and HLA-II alleles to predict rules for peptide binding to a diverse set of such alleles. We applied these binding predictors to viral genomes from the Coronaviridae family, and specifically to identify SARS-CoV-2 T cell epitopes.ResultsTo test the suitability of these tools to identify viral T cell epitopes, we first validated HLA-I and HLA-II predictions on Coronaviridae family epitopes deposited in the Virus Pathogen Database and Analysis Resource (ViPR) database. We then use our HLA-I and HLA-II predictors to identify 11,776 HLA-I and 7,991 HLA-II candidate binding peptides across all 12 open reading frames (ORFs) of SARS-CoV-2. This extensive list of identified candidate peptides is driven by the length of the ORFs and the significant number of HLA-I and HLA-II alleles that we are able to predict (74 and 83, respectively), providing over 99% coverage for the US, European and Asian populations, for both HLA-I and HLA-II. From our SARS-CoV-2 predicted peptide-HLA-I allele pairs, 368 pairs identically matched previously reported pairs in the ViPR database, originating from other forms of coronaviruses. 320 of these pairs (89.1%) had a positive MHC-binding assay result. This analysis reinforces the validity our predictions.ConclusionsUsing this bioinformatic platform, we identify multiple putative epitopes for CD4+ and CD8+ T cells whose HLA binding properties cover nearly the entire population and thus may be effective when included in prophylactic vaccines against SARS-CoV-2 to induce broad cellular immunity.

Summary Neoantigens arise from mutations in cancer cells and are important targets of T cell-mediated anti-tumor immunity. Here, we report the first open-label, phase Ib clinical trial of a personalized neoantigen-based vaccine, NEO-PV-01, in combination with PD-1 blockade in patients with advanced melanoma, non-small cell lung cancer, or bladder cancer. This analysis of 82 patients demonstrated that the regimen was safe, with no treatment-related serious adverse events observed. De novo neoantigen-specific CD4+ and CD8+ T cell responses were observed post-vaccination in all of the patients. The vaccine-induced T cells had a cytotoxic phenotype and were capable of trafficking to the tumor and mediating cell killing. In addition, epitope spread to neoantigens not included in the vaccine was detected post-vaccination. These data support the safety and immunogenicity of this regimen in patients with advanced solid tumors (Clinicaltrials.gov: NCT02897765).

Summary Oncogenic mutations in KRAS can be recognized by T cells on specific class I human leukocyte antigen (HLA-I) molecules, leading to tumor control. To date, the discovery of T cell targets from KRAS mutations has relied on occasional T cell responses in patient samples or the use of transgenic mice. To overcome these limitations, we have developed a systematic target discovery and validation pipeline. We evaluate the presentation of mutant KRAS peptides on individual HLA-I molecules using targeted mass spectrometry and identify 13 unpublished KRASG12C/D/R/V mutation/HLA-I pairs and nine previously described pairs. We assess immunogenicity, generating T cell responses to nearly all targets. Using cytotoxicity assays, we demonstrate that KRAS-specific T cells and T cell receptors specifically recognize endogenous KRAS mutations. The discovery and validation of T cell targets from KRAS mutations demonstrate the potential for this pipeline to aid the development of immunotherapies for important cancer targets.

Identification of human leukocyte antigen (HLA)-bound peptides by liquid chromatography-tandem mass spectrometry (LC-MS/MS) is poised to provide a deep understanding of rules underlying antigen presentation. However, a key obstacle is the ambiguity that arises from the co-expression of multiple HLA alleles. Here, we have implemented a scalable mono-allelic strategy for profiling the HLA peptidome. By using cell lines expressing a single HLA allele, optimizing immunopurifications, and developing an application-specific spectral search algorithm, we identified thousands of peptides bound to 16 different HLA class I alleles. These data enabled the discovery of subdominant binding motifs and an integrative analysis quantifying the contribution of factors critical to epitope presentation, such as protein cleavage and gene expression. We trained neural-network prediction algorithms with our large dataset (>24,000 peptides) and outperformed algorithms trained on data-sets of peptides with measured affinities. We thus demonstrate a strategy for systematically learning the rules of endogenous antigen presentation.

Summary Increasing evidence indicates CD4+ T cells can recognize cancer-specific antigens and control tumor growth. However, it remains difficult to predict the antigens that will be presented by human leukocyte antigen class II molecules (HLA-II), hindering efforts to optimally target them therapeutically. Obstacles include inaccurate peptide-binding prediction and unsolved complexities of the HLA-II pathway. To address these challenges, we developed an improved technology for discovering HLA-II binding motifs and conducted a comprehensive analysis of tumor ligandomes to learn processing rules relevant in the tumor microenvironment. We profiled >40 HLA-II alleles and showed that binding motifs were highly sensitive to HLA-DM, a peptide-loading chaperone. We also revealed that intratumoral HLA-II presentation was dominated by professional antigen-presenting cells (APCs) rather than cancer cells. Integrating these observations, we developed algorithms that accurately predicted APC ligandomes, including peptides from phagocytosed cancer cells. These tools and biological insights will enable improved HLA-II-directed cancer therapies.

Response rates to immunotherapies in pancreatic ductal adenocarcinoma (PDAC) patients are low. However, cases with long-term survival have been correlated with both T cell infiltration and quality of neoantigens (i.e., epitopes from mutations presented by Human Leukocyte Antigen (HLA) molecules). It is known that mutations in the KRAS oncogene, which occur in the majority of PDAC patients, can be recognized by T cells as neoantigens on specific HLA molecules and lead to tumor control. KRAS neoantigens may thus be an attractive therapeutic target in a substantial fraction of PDAC patients. In this study, we systematically evaluated a broad range of KRAS neoantigens using an integrated discovery and validation pipeline. To date, the discovery and validation of KRAS neoantigens has mainly relied on the detection of stochastic T cell responses in patient samples or the use of transgenic mouse models. As such, the reported coverage of common HLA alleles is relatively limited. To overcome these issues, we established a systematic pipeline that addresses two fundamental principles: (1) the presentation of the neoantigen on cells with the mutation and (2) ability of the neoantigen to elicit T cell responses. The presentation of potential neoantigens was evaluated by applying a targeted mass spectrometry approach to detect peptides eluted from specific class I HLA molecules isolated from cells harboring a KRAS mutation of interest. T cell responses were elicited to MS-observed peptides using a proprietary in vitro stimulation protocol, after which the T cells can further be used in cytotoxicity assays to orthogonally confirm neoantigen presentation. We substantiated our pipeline using KRAS codon 12 neoantigens reported in the literature (e.g., G12D on HLA-C*08:02), then evaluated novel neoantigens predicted to be presented by common class I HLA molecules in the U.S. population. Through this pipeline, we have increased the number of validated KRAS neoantigens and thus the targetable patient population expected to harbor at least one KRAS neoantigen. A more comprehensive understanding of KRAS neoantigens will help drive focused therapies, such as the development of tumor-specific T cell receptor (TCR) therapies or neoantigen vaccines in appropriate patient populations in PDAC or other indications. Citation Format: Jaewon Choi, Scott P Goulding, Brandon P. Conn, Christopher D. McGann, Jared L. Dietze, Jessica Kohler, Divya R. Lenkala, Antoine Boudot, Daniel A. Rothenberg, Paul J. Turcott, John S. Srouji, Michael S. Rooney, Marit M. van Buuren, Richard B. Gaynor, Jennifer G. Abelin, Terri A. Addona, Vikram R. Juneja. Systematic discovery of KRAS neoantigens [abstract]. In: Proceedings of the AACR Virtual Special Conference on Pancreatic Cancer; 2020 Sep 29-30. Philadelphia (PA): AACR; Cancer Res 2020;80(22 Suppl):Abstract nr PO-015.

The ongoing COVID-19 pandemic has created an urgency to identify novel vaccine targets for protective immunity against SARS-CoV-2. Consistent with observations for the closely related SARS-CoV, early reports identify a protective role for both humoral and cell-mediated immunity for SARS-CoV-2. In this study, we leveraged our bioinformatics binding prediction tools for human leukocyte antigen (HLA)-I and HLA-II alleles that cover nearly the entire population and were developed using mass spectrometry-based profiling of 74 individual HLA-I and 83 individual HLA-II alleles. We applied these binding predictors, initially developed to predict tumor neoantigen presentation, to identify T-cell epitopes from SARS-CoV-2 proteins. To determine the ability of our tools to identify viral T-cell epitopes, we validated HLA-I and HLA-II predictions on Coronaviridae family epitopes deposited in the Virus Pathogen Database and Analysis Resource (ViPR) database. We then applied our HLA-I and HLA-II predictors to 13 open reading frames (ORFs) of SARS-CoV-2 and identified 11,897 HLA-I and 8,046 HLA-II candidate peptides that were highly ranked for binding. From our SARS-CoV-2 predicted peptide-HLA-I allele pairs, 374 pairs identically matched previously reported pairs in the ViPR database, originating from other coronaviruses with homologous sequences. Of these pairs, 333 (89 %) had a positive HLA-binding assay result, reinforcing the validity of our predictions. Furthermore, we assayed a subset of epitopes with highly predicted binding scores for their ability to be recognized by specific CD8+ T cell in human donor PBMCs. These epitopes were chosen from four structural proteins (S, N, M, E) and one nonstructural protein (ORF1ab) from SARS-CoV-2, and epitopes from all five proteins were found to be immunogenic. Finally, it was important to address the expression of SARS-CoV-2 proteins within cells since their subsequent processing is necessary for MHC presentation and the generation of specific epitopes. We utilized publicly available proteomic data to infer the relative expression of SARS-CoV-2 proteins from infected cell lines and determined that the different proteins vary significantly in their expression levels, with the nucleocapsid being the most highly expressed viral protein across these studies. Our predictions identify few epitopes from each SARS-CoV-2 protein, which are predicted to bind multiple HLA-I or HLA-II alleles, potentially covering over 99% of the USA, European, and Asian populations. Finally, using our bioinformatic platform, we identify multiple putative epitopes that are potential targets for CD4+ and CD8+ T cells whose predicted HLA binding properties cover nearly the entire population. We further propose that when considering the protein expression levels of these epitopes and their ability to elicit a T-cell response, these epitopes may be effective when included in vaccines against SARS-CoV-2 to induce broad cellular immunity. Citation Format: Asaf Poran, Dewi Harjanto, Matt Malloy, Christina M. Arieta, Daniel A. Rothenberg, Divya Lenkala, Marit M. van Buuren, Terri A. Addona, Michael S. Rooney, Lakshmi Srinivasan, Richard B. Gaynor. Sequence-based prediction of SARS-CoV-2 vaccine targets using a mass spectrometry-based bioinformatics predictor identifies immunogenic T-cell epitopes [abstract]. In: Proceedings of the AACR Virtual Meeting: COVID-19 and Cancer; 2020 Jul 20-22. Philadelphia (PA): AACR; Clin Cancer Res 2020;26(18_Suppl):Abstract nr S03-02.

While tumor-reactive CD4+ T cells have been associated with effective immunotherapy responses, accurate prediction of MHC class II-restricted ligands remains a challenge, limiting our ability to harness CD4+ immunity for cancer therapy. To this end, we have developed a state-of-the-art MHC class II binding predictor, neonmhc2, trained on HLA-II ligands identified from mass spectrometry (MS) of cell lines engineered to express a single affinity-tagged HLA-II allele. Over 60 HLA-II alleles have been characterized to date. We demonstrate that neonmhc2 outperforms NetMHCIIpan, the current benchmark for class II prediction, in distinguishing 1) HLA-II ligands presented in cell lines and tissues, and critically, 2) immunogenic CD4+ epitopes identified with tetramer-guided epitope mapping. Furthermore, we show that numerous neoantigen peptides that were ranked highly by neonmhc2 but poorly by NetMHCIIpan were immunogenic in an ex vivo induction. We next studied HLA-II antigen processing in order to further boost our ability to predict CD4+ epitopes. We determined a gene-level bias by comparing transcript expression and gene length to the frequency of observations in MS, finding that secreted genes are over-represented in HLA-II ligandomes from tissues. We built numerous primary sequence-based processability predictors trained on MS data, but only achieved significant prediction improvement when using the simple feature of determining if a candidate peptide contained sequence that overlapped a previously observed HLA-II ligand. By combining neonmhc2 binding prediction, transcript expression, gene bias, and the overlap feature in an integrated presentation predictor, we were able to achieve up to a 61-fold increase in ability to predict HLA-II peptides presented from tissue MS data over NetMHCIIpan alone. We also sought to understand which cells are presenting HLA-II ligands in the tumor microenvironment to elucidate the presentation pathway most relevant to immunotherapy. By leveraging publicly available RNA-seq (bulk and single cell), we found that professional antigen-presenting cells rather than tumor cells are primarily responsible for HLA-II presentation. We developed a novel SILAC-based MS workflow to directly interrogate peptides derived from phagocytosed tumor cells that are presented by dendritic cells. The experiment revealed that mitochondrial genes are preferentially presented from phagocytosed cells. In conclusion, by integrating proteomics and genomics data at large scale, we have defined new rules for understanding HLA-II processing and presentation, particularly in the context of the tumor microenvironment. This work should enhance our ability to predict CD4+ epitopes for immunotherapy. Citation Format: Dewi Harjanto, Jennifer G. Abelin, Matthew Malloy, Prerna Suri, Tyler Colson, Scott P. Goulding, Amanda L. Creech, Lia R. Serrano, Gibbs Nasir, Yusuf Nasrullah, Christopher D. McGann, Diana Velez, Ying S. Ting, Asaf Poran, Daniel A. Rothenberg, Sagar Chhangawala, Alex Rubinsteyn, Jeff Hammerbacher, Richard B. Gaynor, Edward F. Fritsch, Rob C. Oslund, Dominik Barthelme, Terri A. Addona, Christina M. Arieta, Michael S. Rooney. Enhanced HLA-II epitope prediction for immunotherapy with novel proteomics and genomics approaches [abstract]. In: Proceedings of the AACR Special Conference on Tumor Immunology and Immunotherapy; 2019 Nov 17-20; Boston, MA. Philadelphia (PA): AACR; Cancer Immunol Res 2020;8(3 Suppl):Abstract nr B23.

Detection of somatic mutations in human leukocyte antigen (HLA) genes using whole-exome sequencing (WES) is hampered by the high polymorphism of the HLA loci, which prevents alignment of sequencing reads to the human reference genome. We describe a computational pipeline that enables accurate inference of germline alleles of class I HLA-A, B and C genes and subsequent detection of mutations in these genes using the inferred alleles as a reference. Analysis of WES data from 7,930 pairs of tumor and healthy tissue from the same patient revealed 298 nonsilent HLA mutations in tumors from 266 patients. These 298 mutations are enriched for likely functional mutations, including putative loss-of-function events. Recurrence of mutations suggested that these 'hotspot' sites were positively selected. Cancers with recurrent somatic HLA mutations were associated with upregulation of signatures of cytolytic activity characteristic of tumor infiltration by effector lymphocytes, supporting immune evasion by altered HLA function as a contributory mechanism in cancer.

SummaryHow the genomic landscape of a tumor shapes and is shaped by anti-tumor immunity has not been systematically explored. Using large-scale genomic data sets of solid tissue tumor biopsies, we quantified the cytolytic activity of the local immune infiltrate and identified associated properties across 18 tumor types. The number of predicted MHC Class I-associated neoantigens was correlated with cytolytic activity and was lower than expected in colorectal and other tumors, suggesting immune-mediated elimination. We identified recurrently mutated genes that showed positive association with cytolytic activity, including beta-2-microglobulin (B2M), HLA-A, -B and -C and Caspase 8 (CASP8), highlighting loss of antigen presentation and blockade of extrinsic apoptosis as key strategies of resistance to cytolytic activity. Genetic amplifications were also associated with high cytolytic activity, including immunosuppressive factors such as PDL1/2 and ALOX12B/15B. Our genetic findings thus provide evidence for immunoediting in tumors and uncover mechanisms of tumor-intrinsic resistance to cytolytic activity.

Treatment with immune checkpoint blockade (CPB) therapies often leads to prolonged responses in patients with metastatic melanoma, but the common mechanisms of primary and acquired resistance to these agents remain incompletely characterized and have yet to be validated in large cohorts. By analyzing longitudinal tumor biopsies from 17 metastatic melanoma patients treated with CPB therapies, we observed point mutations, deletions or loss of heterozygosity (LOH) in beta-2-microglobulin (B2M), an essential component of MHC class I antigen presentation, in 29.4% of patients with progressing disease. In two independent cohorts of melanoma patients treated with anti-CTLA4 and anti-PD1, respectively, we find that B2M LOH is enriched threefold in non-responders (~30%) compared to responders (~10%) and associated with poorer overall survival. Loss of both copies of B2M is found only in non-responders. B2M loss is likely a common mechanism of resistance to therapies targeting CTLA4 or PD1., Resistance to immune-checkpoint blockade often occurs in treated patients. Here, the authors demonstrate that B2M loss is a mechanism of primary and acquired resistance to therapies targeting CTLA4 or PD-1 in melanoma patients.

Background: Neoantigens arise from DNA mutations in cancer cells and are important targets for T cell mediated anti-tumor immunity. NEO-PV-01 is a personal neoantigen vaccine of up to 20 peptides designed based on a patient’s neoantigen and HLA profile that is directed at inducing tumor-specific T cell responses to neoantigens. Here, we report relationships between baseline tumor characteristics, immune response and clinical outcome for NT-001, a Phase 1b study of NEO-PV-01 + adjuvant in combination with nivolumab in either first or later line therapy for patients with metastatic melanoma, bladder and non-small cell lung cancer (NCT02897765). This analysis is focused on the melanoma cohort. Methods: Serial blood and tumor biopsies were scheduled for collection: i) prior to treatment, ii) after 12 weeks of nivolumab monotherapy and iii) after completion of NEO-PV-01 vaccination. Baseline features and immune responses in tumor cells were characterized by immunohistochemistry for multiple immune and tumor markers, gene expression, whole exome and TCR sequencing. Antigen-specific responses by IFNγ ELISpot, intracellular cytokine staining, multi-parameter surface and functional phenotyping by FACS and the presence of cytolytic properties were monitored in serial peripheral blood samples. Durability of immune responses up to 104 weeks post start of treatment will be measured. Results: A cohort of 10 melanoma patients demonstrated CD4 and CD8 T cell responses against 56% of vaccine peptides that were detected primarily in the post-vaccination samples as measured by IFNγ ELISpot. Analysis of additional patients is ongoing. T cell responses were neoantigen-specific for most peptides tested (86%; 12/14). Vaccine-induced immune responses were durable in patients who reached the week 52 treatment timepoint. Most T cell responses were polyfunctional, as evident by secretion of multiple cytokines, exhibited a memory and effector memory phenotype and were cytolytic. Epitope spreading, defined as post-vaccination T cell responses to neoantigens not included in the vaccine, was observed in multiple melanoma patients analyzed and evaluated for association with post vaccine clinical responses. Further, multi-platform assessments of immune and molecular responses including gene expression and TCR repertoire analysis demonstrate extensive responses in patients continuing study past 52 weeks. Additional correlates of clinical outcomes with molecular and immunologic responses will be presented. Conclusions: Treatment with NEO-PV-01 + adjuvant in combination with nivolumab induced broad de novo neoantigen-specific immune responses in metastatic melanoma. Immune responses were specific and correlations with clinical outcomes will be discussed. Citation Format: Siwen Hu-Lieskovan, Patrick A. Ott, Aung Naing, Rana H. Besada, Samantha J. Gates, Victoria R. Kohler, Riley R. Curran, Meghan E. Bushway, Julian Scherer, Kristen N. Balogh, Tracey E. Sciuto, Ying S. Ting, Michael S. Rooney, Dewi Harjanto, Zhengping Huang, Yuting Huang, Yvonne Ware, April Lamb, Lisa D. Cleary, Melissa A. Moles, Richard B. Gaynor, Matthew J. Goldstein, Les H. Brail, Joel Greshock, Lakshmi Srinivasan. The personalized vaccine, NEO-PV-01 with anti-PD1, induces neoantigen-specific de novo immune responses in patients with advanced metastatic melanoma: Association with clinical outcomes [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 942.

BackgroundLoss of donor-mediated immune antitumor activity after allogeneic hematopoietic stem-cell transplantation (HSCT) permits relapse of hematologic cancers. We hypothesized that immune checkpoint blockade established by targeting cytotoxic T-lymphocyte-associated protein 4 with ipilimumab could restore antitumor reactivity through a graft-versus-tumor effect.MethodsWe conducted a phase 1/1b multicenter, investigator-initiated study to determine the safety and efficacy of ipilimumab in patients with relapsed hematologic cancer after allogeneic HSCT. Patients received induction therapy with ipilimumab at a dose of 3 or 10 mg per kilogram of body weight every 3 weeks for a total of 4 doses, with additional doses every 12 weeks for up to 60 weeks in patients who had a clinical benefit.ResultsA total of 28 patients were enrolled. Immune-related adverse events, including one death, were observed in 6 patients (21%), and graft-versus-host disease (GVHD) that precluded further administration of ipilimumab was observed in 4 patients (14%). No responses that met formal response criteria occurred in patients who received a dose of 3 mg per kilogram. Among 22 patients who received a dose of 10 mg per kilogram, 5 (23%) had a complete response, 2 (9%) had a partial response, and 6 (27%) had decreased tumor burden. Complete responses occurred in 4 patients with extramedullary acute myeloid leukemia and 1 patient with the myelodysplastic syndrome developing into acute myeloid leukemia. Four patients had a durable response for more than 1 year. Responses were associated with in situ infiltration of cytotoxic CD8+ T cells, decreased activation of regulatory T cells, and expansion of subpopulations of effector T cells in the blood.ConclusionsOur early-phase data showed that administration of ipilimumab was feasible in patients with recurrent hematologic cancers after allogeneic HSCT, although immune-mediated toxic effects and GVHD occurred. Durable responses were observed in association with several histologic subtypes of these cancers, including extramedullary acute myeloid leukemia. (Funded by the National Institutes of Health and others; ClinicalTrials.gov number, NCT01822509.).

Background Sources of air pollution in developing country cities include transportation and industrial pollution, biomass and coal fuel use, and resuspended dust from unpaved roads. Objectives Our goal was to understand within-neighborhood spatial variability of particulate matter (PM) in communities of varying socioeconomic status (SES) in Accra, Ghana, and to quantify the effects of nearby sources on local PM concentration. Methods We conducted 1 week of morning and afternoon mobile and stationary air pollution measurements in four study neighborhoods. PM with aerodynamic diameters ≤ 2.5 μm (PM2.5) and ≤ 10 μm (PM10) was measured continuously, with matched global positioning system coordinates; detailed data on local sources were collected at periodic stops. The effects of nearby sources on local PM were estimated using linear mixed-effects models. Results In our measurement campaign, the geometric means of PM2.5 and PM10 along the mobile monitoring path were 21 and 49 μg/m3, respectively, in the neighborhood with highest SES and 39 and 96 μg/m3, respectively, in the neighborhood with lowest SES and highest population density. PM2.5 and PM10 were as high as 200 and 400 μg/m3, respectively, in some segments of the path. After adjusting for other factors, the factors that had the largest effects on local PM pollution were nearby wood and charcoal stoves, congested and heavy traffic, loose dirt road surface, and trash burning. Conclusions Biomass fuels, transportation, and unpaved roads may be important determinants of local PM variation in Accra neighborhoods. If confirmed by additional or supporting data, the results demonstrate the need for effective and equitable interventions and policies that reduce the impacts of traffic and biomass pollution.

A challenge in developing personalized cancer immunotherapies is the prediction of putative cancer‐specific antigens. Currently, predictive algorithms are used to infer binding of peptides to human leukocyte antigen (HLA) heterodimers to aid in the selection of putative epitope targets. One drawback of current epitope prediction algorithms is that they are trained on datasets containing biochemical HLA‐peptide binding data that may not completely capture the rules associated with endogenous processing and presentation. The field of MS has made great improvements in instrumentation speed and sensitivity, chromatographic resolution, and proteogenomic database search strategies to facilitate the identification of HLA‐ligands from a variety of cell types and tumor tissues. As such, these advances have enabled MS profiling of HLA‐binding peptides to be a tractable, orthogonal approach to lower throughput biochemical assays for generating comprehensive datasets to train epitope prediction algorithms. In this review, we will highlight the progress made in the field of HLA‐ligand profiling enabled by MS and its impact on current and future epitope prediction strategies.

Immune evasion may facilitate hematologic relapse after allogeneic hematopoietic stem cell transplantation (allo-SCT). We recently demonstrated that CTLA4 blockade with ipilimumab reinvigorates a graft-versus-leukemia effect to induce complete remissions of acute myeloid leukemia (AML) relapsing after allo-SCT. Here, we hypothesized that immune subpopulation dynamics and activation states inferred from in situ gene expression changes within the leukemic microenvironment are informative of clinical outcome. We undertook an in situ transcriptomic characterization of paired, pre/post ipilimumab leukemic biopsies from five samples with relapsed, extramedullary AML. We performed a response-to-treatment expression analysis for each patient and found three immune patterns corresponding to three clinical response patterns following ipilimumab (durable response, relapse, and primary resistance). Durable responses were characterized by a diverse infiltration of activated cytotoxic T lymphocytes, B cells, and macrophages. In contrast, primary resistance was associated with both marked infiltration of CD8 T cells deficient in T-cell receptor signaling, activation, or cytolytic activity and absent infiltration of other immune effectors. Interestingly, the sample with transient response and eventual relapse demonstrated pre- and post-treatment immunologically “inflamed” states that were strongly downregulated during clinical relapse. In situ gene expression analyses of leukemic biopsies before and after ipilimumab therapy suggest that specific patterns of immune population dynamics and activation states underlie diverse clinical outcomes. Citation Format: Pavan Bachireddy, Matthew S. Davids, Michael S. Rooney, Michaela Bowden, Chensheng W. Zhou, Scott J. Rodig, Vincent Ho, Joseph Antin, John Koreth, Edwin Alyea, Robert J. Soiffer, Catherine J. Wu. In situ immune expression signatures before and after ipilimumab therapy for relapsed acute myeloid leukemia after allogeneic stem cell transplantation [abstract]. In: Proceedings of the Second AACR Conference on Hematologic Malignancies: Translating Discoveries to Novel Therapies; May 6-9, 2017; Boston, MA. Philadelphia (PA): AACR; Clin Cancer Res 2017;23(24_Suppl):Abstract nr 17.

How the immune system readies for battle Although gene expression is tightly controlled at both the RNA and protein levels, the quantitative contribution of each step, especially during dynamic responses, remains largely unknown. Indeed, there has been much debate whether changes in RNA level contribute substantially to protein-level regulation. Jovanovic et al. built a genome-scale model of the temporal dynamics of differential protein expression during the stimulation of immunological dendritic cells (see the Perspective by Li and Biggin). Newly stimulated functions involved the up-regulation of specific RNAs and concomitant increases in the levels of the proteins they encode, whereas housekeeping functions were regulated posttranscriptionally at the protein level. Science , this issue 10.1126/science.1259038 ; see also p. 1066

Personalized neoantigen therapies for cancer require accurate epitope selection. However, most Class I prediction algorithms in common use today are based on biochemical binding assays that are difficult to scale and do not address processing steps upstream of peptide-MHC binding. Here we present an alternative approach based on the LC-MS/MS identification of MHC Class I-bound peptides. While MS-based profiling is not new, we optimized the system for rule learning by focusing on cell lines expressing only a single HLA-A or HLA-B allele and by collecting parallel transcriptomic and proteomic measurements. Identifying over 24,000 peptides across 16 individual alleles, we were able to discover novel binding motifs, which were validated biochemically, and develop novel neural network algorithms. Furthermore, we systematically interrogated processing rules - discovering a novel motif conserved across multiple cell types - and developed a principled framework for integrating epitope cleavability, expression, and MHC binding potential into an overall ranking. Validating on external datasets, we saw a doubling in positive predictive value with respect to standard approaches. We thus demonstrate a scalable strategy for systematically learning the rules of endogenous antigen presentation that can be deployed for the optimal selection of patient-specific cancer neoantigens. Citation Format: Michael S. Rooney, Jenn Abelin, Siranush Sarkizova, Derin Keskin, Christine Hartigan, Wandi Zhang, John Sidney, William Lane, Jonathan Stevens, Guang L. Zhang, Karl Clauser, Nir Hacohen, Steve Carr, Cathy Wu. Next-generation epitope prediction using mass spectrometry and integrative genomics [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr LB-179. doi:10.1158/1538-7445.AM2017-LB-179

Cancer mutations yield neo-antigens, which are instrumental to immune-mediated recognition and control of cancer. Vaccine-based therapies targeting neo-antigens will require accurate prediction of which mutations yield peptides presented on polymorphic HLA class I. While in vitro methods have produced increasingly accurate predictors of peptide:MHC binding, there remains a need to define rules for endogenous antigen presentation. Here, we use rapid, high-resolution liquid chromatography mass spectrometry (LC-MS/MS) to identify >24,000 peptides associated with 16 HLA alleles in B cell lines that each express a single HLA allele. The elution of peptides from single HLA alleles allowed us to develop improved rules for endogenous peptide presentation based on the physicochemical properties of binding peptides, patterns of peptide cleavage and abundance of cognate transcripts. Finally, we trained models that integrated MS-derived peptide data and gene expression and demonstrate improved prediction of endogenous peptide presentation in independent datasets. Our strategy thus improves the performance of current predictive algorithms and provides a rapid and scalable method to generate rules for the massive and diverse set of human HLA alleles. Citation Format: Michael S. Rooney, Jennifer G. Abelin, Derin B. Keskin, Siranush Sarkizova, Christina Hartigan, Wandi Zhang, John Sidney, Jonathan Stevens, William J. Lane, Guang L. Zhang, Karl R. Clauser, Nir Hacohen, Steven A. Carr, Catherine J. Wu. High-throughput profiling of HLA allele-specific peptides by MS for improved epitope prediction [abstract]. In: Proceedings of the Second CRI-CIMT-EATI-AACR International Cancer Immunotherapy Conference: Translating Science into Survival; 2016 Sept 25-28; New York, NY. Philadelphia (PA): AACR; Cancer Immunol Res 2016;4(11 Suppl):Abstract nr B089.

Sources of air pollution in developing country cities include transportation and industrial pollution, biomass fuel use, and re-suspended dust from unpaved roads. We examined the spatial patterns of particulate matter (PM) and its sources in four neighborhoods of varying socioeconomic status (SES) in Accra. PM data were from 1 week of morning and afternoon mobile and stationary air pollution measurements in each of the study neighborhoods. PM(2.5) and PM(10) were measured continuously, with matched GPS coordinates. Data on biomass fuel use were from the Ghana 2000 population and housing census and from a census of wood and charcoal stoves along the mobile monitoring paths. We analyzed the associations of PM with sources using a mixed-effects regression model accounting for temporal and spatial autocorrelation. After adjusting for other factors, the density of wood stoves, fish smoking, and trash burning along the mobile monitoring path as well as road capacity and surface were associated with higher PM(2.5). Road capacity and road surface variables were also associated with PM(10), but the association with biomass sources was weak or absent. While wood stoves and fish smoking were significant sources of air pollution, addressing them would require financial and physical access to alternative fuels for low-income households and communities.

Between 1982 and 1986 intravenous digital subtraction arteriography was used to evaluate vascular grafts in 97 patients (54 males, 43 females). Indications included recurrent symptoms, absent or diminished pulses, a drop in Doppler pressure measurements, and clinical uncertainty with respect to graft patency. Problems identified included graft stenosis, stenosis of the anastomosis or its distal vessels, false aneurysm, arteriovenous fistula and emboli. Forty-eight operations were carried out following intravenous digital subtraction arteriography, and radiographic findings were verified surgically. Twice, intravenous digital subtraction arteriography did not show significant graft findings which were discovered at surgery. Thus intravenous digital subtraction arteriography showed a sensitivity of 95.8% and specificity of 100%. Complications following intravenous digital subtraction arteriography were: two patients developed urticaria, and one superficial thrombophlebitis. There were no cases of pulmonary edema or death. In conclusion intravenous digital subtraction arteriography is very useful in the diagnosis of graft-related problems if done on a selective basis looking at graft and anastomosis site only. Intravenous digital subtraction arteriography is done on an outpatient basis, has high sensitivity and specificity, good patient acceptance, is safe, fast and is less expensive than conventional arteriography.

T fasteners were used successfully to allow placement of primary feeding jejunostomies in 4 patients who had previously undergone surgical gastrojejunostomy.

We report aortic rupture secondary to pseudoaneurysm formation following a subintimal injection of contrast.

Cells control dynamic transitions in transcript levels by regulating transcription, processing, and/or degradation through an integrated regulatory strategy. Here, we combine RNA metabolic labeling, rRNA-depleted RNA-seq, and DRiLL, a novel computational framework, to quantify the level; editing sites; and transcription, processing, and degradation rates of each transcript at a splice junction resolution during the LPS response of mouse dendritic cells. Four key regulatory strategies, dominated by RNA transcription changes, generate most temporal gene expression patterns. Noncanonical strategies that also employ dynamic posttranscriptional regulation control only a minority of genes, but provide unique signal processing features. We validate Tristetraprolin (TTP) as a major regulator of RNA degradation in one noncanonical strategy. Applying DRiLL to the regulation of noncoding RNAs and to zebrafish embryogenesis demonstrates its broad utility. Our study provides a new quantitative approach to discover transcriptional and posttranscriptional events that control dynamic changes in transcript levels using RNA sequencing data., National Human Genome Research Institute (U.S.) (Centers for Excellence in Genomics Science 1P50HG006193-01), Howard Hughes Medical Institute, National Institutes of Health (U.S.) (Pioneer Award), Massachusetts Institute of Technology. William Asbjornsen Albert Memorial Fellowship, Xerox Fellowship Program

Summary: Deficiencies in DNA-degrading nucleases lead to accumulation of self DNA and induction of autoimmunity in mice and in monogenic and polygenic human diseases. However, the sources of DNA and the mechanisms that trigger immunity remain unclear. We analyzed mice deficient for the lysosomal nuclease Dnase2a and observed elevated levels of undegraded DNA in both phagocytic and nonphagocytic cells. In nonphagocytic cells, the excess DNA originated from damaged DNA in the nucleus based on colocalization studies, live-cell imaging, and exacerbation by DNA-damaging agents. Removal of damaged DNA by Dnase2a required nuclear export and autophagy-mediated delivery of the DNA to lysosomes. Finally, DNA was found to accumulate in Dnase2a−/− or autophagy-deficient cells and induce inflammation via the Sting cytosolic DNA-sensing pathway. Our results reveal a cell-autonomous process for removal of damaged nuclear DNA with implications for conditions with elevated DNA damage, such as inflammation, cancer, and chemotherapy. : Deficiencies in DNA nucleases can lead to the accumulation of self DNA, activation of innate immunity, and development of autoimmune disease. The source of immunostimulatory DNA is not known in most cases. Lan et al. now find that damaged nuclear DNA accumulates outside the nucleus and stimulates Sting-dependent DNA-sensing when mice lack a lysosomal nuclease, Dnase2a. The results support a model in which damaged chromosomal DNA is normally exported from the nucleus and cleared by autophagy.