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Anthropogenic emissions of methane (CH4) have made a considerable contribution towards the Earth's changing radiative budget since pre-industrial times. This is because large amounts of methane are emitted from human activities, and the global warming potential of methane is high. The majority of anthropogenic fossil methane emissions to the atmosphere originate from a large number of small (point) sources. Thus, detection and accurate, rapid quantification of such emissions are vital to enable the reduction of emissions to help mitigate future climate change. There exist a number of instruments on satellites that measure radiation at methane-absorbing wavelengths, which have sufficiently high spatial resolution that can be used for detecting plumes of highly spatially localised methane “point sources” (areas on the order of m2 to km2). Searching for methane plumes in methane-sensitive satellite images using classical methods, such as thresholding and clustering, can be useful but is time-consuming and often involves empirical decisions. Here, we develop a deep neural network to identify and quantify methane point source emissions from hyperspectral imagery from the PRecursore IperSpettrale della Missione Applicativa (PRISMA) satellite with 30 m spatial resolution. The moderately high spectral and spatial resolution, as well as considerable global coverage and free access to data, makes PRISMA a good candidate for methane plume detection. The neural network was trained with simulated synthetic methane plumes generated with the large eddy simulation extension of the Weather Research and Forecasting model (WRF-LES), which we embedded into PRISMA images. The deep neural network was successful at locating plumes with a F1 score, precision, and recall of 0.95, 0.96, and 0.92, respectively, and was able to quantify emission rates with a mean error of 24 %. The neural network was furthermore able to locate several plumes in real-world images. We have thus demonstrated that our method can be effective in locating and quantifying methane point source emissions in near-real time from 30 m resolution satellite data, which can aid us in mitigating future climate change.

Contrast media administration has been associated with complications such as nephropathy, cardiovascular morbidity, and neurovascular events, particularly in patients with renal insufficiency. This association has been questioned in recent studies. This review was performed to summarize the most current evidence on contrast induced nephropathy (CIN), contributing factors, and considerations in patients with renal insufficiency. The risk of CIN was over-estimated by the previous studies, due to a lack of control groups or presence of non-randomized control groups, which led to a selection bias. However, the thresholds associated with an increased risk of CIN are controversial and require risk-benefit analysis on an individual basis. Regarding the administration of contrast media (CM) in the emergency setting, the majority of studies suggested that CM exposure does not meaningfully increase the risk of acute kidney injury in critically ill patients (including trauma patients). Several strategies have been suggested to reduce the risk of CIN, including volume expansion to increase renal blood flow, sodium bicarbonate or N-acetylcysteine administration, and use of low-osmolal contrast media in end-stage renal disease.

Methane (CH4) is the second most important anthropogenic greenhouse gas (GHG) in terms of its overall effect on climate radiative forcing. The atmospheric residence time of methane is considerably shorter than that of carbon dioxide, but its warming potential significantly stronger. Methane is produced from natural sources such as wetlands, and as a result of human activities, such as the oil and gas industry. A small number of anomalously large anthropogenic point sources are a major contribution to the total global anthropogenic methane emission budget, thus early detection of such sources has great potential for climate mitigation.Methane satellite observations are now possible from a number of instruments with very high spatial resolution which allow to map methane emission plumes from individual emission sources. In this work, we explore the capabilities of three satellites with different specifications, spatial coverage and spatial resolutions ranging from metres (WorldView-3; multi-spectral) to tens of metres (PRISMA; hyperspectral) to kilometres (TROPOMI; hyperspectral). This leads to different capabilities for detecting and quantifying methane point sources that can complement each other. Thanks to its good coverage, TROPOMI Level 2 XCH4 data (from IUP Bremen) allows to locate areas with methane anomalies which can then be further analysed with targeted PRISMA and WorldView-3 (WV-3) observations to quantify methane emissions from small point sources.In our work, we use a fast data-driven retrieval algorithm to derive methane column enhancements from PRISMA and Worldview-3, combined with a statistical method to identify methane plumes and the well-established Integrated Mass Enhancement (IME) method to derive emission flux rates. We developed a simulation framework to characterise and test our approach. This makes use of synthetic methane plumes generated with the Large Eddy Simulation extension of the Weather Research and Forecasting model (WRF-LES) that have been embedded into WV-3 or PRISMA images. To further advance the plume detection methods and to allow automatisation, we have developed a deep learning model for WV-3 or PRISMA based on the WRF-LES simulations.In this presentation, we will describe and characterise our plume detection method for three satellite systems covering a wide range of spatial resolutions and we will introduce our deep learning approach. Both methods have been applied to case studies with a focus on emissions from coal mining in South Africa and Australia which we will use to discuss and contrast the different methods and satellite systems.

BackgroundClinical data demonstrates increased antigen presentation diversity is an important factor in determining response rates to checkpoint inhibitors.1 In addition to tumor mutational burden, increased HLA heterozygosity and HLA evolutionary diversity are non-overlapping factors which further diversify the immunopeptidome and improve clinical response to checkpoint therapies.2 3 Endoplasmic reticulum aminopeptidase 1 (ERAP1) is an enzyme that trims peptides loaded into classical and nonclassical MHC Class I molecules.4 5 Ablation of mouse ERAAP modifies the immunopeptidome, resulting in improved immunogenicity, generation of CD8+ T cell responses and tumor growth inhibition.6 7 We report the characterisation of ERAP1 inhibitors in syngeneic tumor models and development of biomarkers to enable translation of this mechanism into the clinic.MethodsHuman and mouse cancer cell lines treated with ERAP1 inhibitors were assessed by immunopeptidomics8 to profile peptide repertoire changes. ERAP1 inhibitor with and without checkpoint inhibition were used to treat syngeneic mouse tumor models, followed by analysing effects on the T cell receptor (TCR) repertoire, RNA sequencing profile, immune cell infiltration and tumor growth inhibition.ResultsExtensive analysis of the immunopeptidomes of diverse cancer cell lines robustly show that ERAP1 inhibition modulates the cancer-related antigen repertoire across diverse ERAP1 and HLA genotypes and cancer-type backgrounds. ERAP1 inhibition drives changes in T cell activation and response, leading to increased T cell infiltration into CT26 syngeneic tumors and alteration of the TCR repertoire at early and late timepoints in tumor growth. Consistent peptide length changes in the immunopeptidome, caused by ERAP1 inhibition, is a proof of mechanism biomarker, whilst tumor immunohistochemisty, TCR repertoire analysis and RNA sequencing are potential proof of principle biomarkers that can all be translated into the clinic. Importantly, the antigen and T cell changes we see following ERAP1 inhibition lead to robust tumor growth inhibition in different syngeneic mouse models when combined with anti-PD-1. We are also exploring the potential of ERAP1 inhibitors to enhance tumour immune responses in combination with additional therapies (e.g. chemotherapy and radiotherapy), across different tumor microenvironments.ConclusionsGrey Wolf Therapeutics ERAP1 inhibitors significantly modify the immunopeptidome and combination with anti PD-1 leads to significant TCR repertoire change, T cell infiltration and tumor growth inhibition in syngeneic mouse tumor models. These data provide the foundation from which we will explore the potential of our first-in-class ERAP1 inhibitor development candidate in the clinic, as well as identifying useful biomarkers to demonstrate desired biological activity.ReferencesRizvi N, Hellmann MD, Snyder A, et al. Mutational landscape determines sensitivity to PD-1 blockade in non–small cell lung cancer. Science 2015;348(6230):124–128.Chowell D, uc G T Morris LGT,2 3, Grigg CM, et al Patient HLA class I genotype influences cancer response to checkpoint blockade immunotherapy. Science 2018;359 (6375):582–587.Chowell D, Chirag Krishna, Federica Pierini, et al Evolutionary divergence of HLA class I genotype impacts efficacy of cancer immunotherapy. Nature Medicine 2019;25(11):1715–1720.Shastri N, Nagarajan N, Lind KC, et al. Monitoring peptide processing for MHC class I molecules in the endoplasmic reticulum. Curr Opin Immunol 2014;26:123–127.Mpakali A, Maben Z, Stern LJ, et al. Molecular pathways for antigenic peptide generation by ER aminopeptidase 1. Mol Immunol 2018;13:50–57.James E, Bailey I, Sugiyarto G, et al. Induction of protective antitumor immunity through attenuation of ERAAP function. J Immunol 2013;190(11):5839–5846.Manguso RT, Pope, HW, MD Zimmer, et al In vivo CRISPR screening identifies Ptpn2 as a cancer immunotherapy target. Nature 2017;547(7664):413–418.Purcell AW, Ramarathinam SH, Ternette N. Mass spectrometry–based identification of MHC-bound peptides for immunopeptidomics. Nat Protoc 2019;14(6):1687–1707.

In this work, we aim to recover the information at 15 m spatial resolution from Landsat 5 TM (L5 TM) data with 30 m spatial resolution using a super-resolution deep learning model. The model is designed to predict a pan-sharpened Landsat 7 ETM+ (L7 ETM+) image at 15 m resolution from a L5 TM image at 30 m spatial resolution. For the model training, we used images of L5 TM and L7 ETM+ from the same region and at a time interval of acquisition < 10 days. Our results show that the model achieves to improve the spatial resolution of the L5 TM even with a modest sample for training, constituted only of 4225 couples of L5 TM and L7 ETM+ images of size 128 ×128 pixels from the Landsat tile 216068. We also found that L5 TM emulated reflectance values at 15 m spatial resolution were more comparable to the values and ranges of L7 ETM+ reflectance than the original L5 TM reflectance. With an improved dataset for training, this model could be used to produce a dataset of images spatially and radiometrically harmonized of L5 TM and L7 ETM+ at 15 m spatial resolution.

The prompt and accurate detection of laser strikes is increasingly important to the survivability of military assets in modern warfare as offensive and defensive laser weapon systems have become more widely implemented. Current laser detection systems on military assets can compromise an asset’s low observability features. This paper presents an addressed detection system based on an array of thermoelectric generators (TEGs) that can be integrated into the skin of an asset. An irradiated TEG harvests the incident energy of a high energy laser (HEL) strike to power a sensor node that transmits an address, via a wireless medium, to a reader in order to indicate which TEG within the array is being irradiated. The wireless sensor node consists of an ultralow voltage step-up converter and microcontroller and a low power RF link.

The magnetic susceptibility of pyrolytic graphite (PyG) is temperature dependent. Under an external magnetic field, a levitated PyG sample with a localized temperature change experiences unequal diamagnetic forces. In this paper, we present a study of the macroscale optomechanical displacement of a levitated PyG sample by using a laser source to locally increase the temperature. Dynamic finite-element method simulations show that a localized increase in the sample temperature, simulating a laser source, decreases the diamagnetic force in that local area, leading to the displacement of the PyG sample in the plane of the permanent magnet array. Experimental setups built using different laser sources and samples confirm the range of applicability of the actuation phenomenon to different conditions. An additional setup without moving parts reduced the likelihood by which airflow could have caused the displacement, as we suspect happened in the previous studies.

The antigen processing machinery of a cell shapes the repertoire of peptides presented for immune recognition on the cell surface. Human leukocyte antigen class I (HLA-I) molecules present peptides that are recognised by both CD8+ T cells and NK cells, and these complexes play a vital role in the recognition and eradication of malignant cells. During direct presentation, the endoplasmic reticulum aminopeptidase 1 (ERAP1) enzyme processes a subset of HLA-I ligand precursors which are translocated into the endoplasmic reticulum (ER) following intracellular proteasomal degradation. Here, we show that inhibition of ERAP1 with highly potent and selective small molecule inhibitors drives significant qualitative and quantitative changes in the HLA-I-restricted immunopeptidome, resulting in the generation of altered and novel peptides from tumour-associated antigens that are then presented on HLA-I molecules. A major consequence of inhibiting the processing of precursor ligands by ERAP1 within the ER of cancer cells was not only the generation of unique peptides which were not detectable under baseline conditions, but a shift in the peptide length distribution towards longer HLA-I-restricted peptides. Importantly, we demonstrate that the degree of bias towards longer HLA-I-bound ligands uniquely presented following ERAP1 inhibition was governed by both ERAP1 and HLA-I haplotypes. Such dramatic changes in the peptide repertoire presented for immune recognition have the potential to enhance anti-tumoural immunogenicity through T cell recognition of a novel cancer immunopeptidome, and, in addition to global shifts in the peptide length distributions, unique peptides presented for immune recognition during ERAP1 inhibition may be used as biomarkers for monitoring activity of this novel therapeutic approach in the clinic. Citation Format: Wayne Paes, Andrew Leishman, Kate Anderton, Hanqing Liao, Isaac Woodhouse, Robert Parker, Annalisa Nicastri, Peter Joyce, Nicola Ternette. First-in-class inhibitors of ERAP1 alter the HLA-I-restricted cancer immunopeptidome leading to the generation of novel peptides presented for immune recognition [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 4153.

Vegetation growth in northern high‐latitudes during springtime is strongly temperature limited, and thus anomalously warm springs are expected to result in an increased drawdown of carbon dioxide (CO2). However, a recent analysis of the relationship between spring temperature anomalies and atmospheric CO2 anomalies at Point Barrow, Alaska, suggests that the link between spring carbon uptake by northern ecosystems and temperature anomalies has been weakening over recent decades due to a diminishing control of temperature on plant productivity. Upon further analysis, covering the 1982‐2015 period, we found no significant change in the relationship between spring vegetation productivity derived from remote sensing data and air temperature. We showed that a reduction in spatial coherence of temperature anomalies, alongside a significant sensitivity to atmospheric transport, is likely responsible for the apparent weakening. Our results, therefore, suggest that spring temperature remains as an important control of northern high‐latitude CO2 uptake.

Background:Small bowel obstruction (SBO) accounts for 15% of abdominal pain complaints referred to emergency departments and imposes significant financial burdens on the healthcare system. The most common symptom and sign of SBO is the absence of stool or flatus passsage and abdominal distension, respectively. Patients who do not demonstrate severe clinical or imaging findings are typically treated with conservative approaches. Patients with clinical signs of sepsis or physical findings of peritonitis are often instantly transferred to the operating room without supplementary imaging assessment. However, in cases where symptoms are non-specific or physical examination is challenging, such as in cases with loss of consciousness, the diagnosis can be complicated. This paper discusses the key findings identifiable on Computed Tomography (CT) which are vital for the emergent triage, proper treatment and appropriate decision making in patients with suspected SBO.Method:Narrative review of the literature.Results:CT plays a key role in emergent triage, proper treatment and decision making and provides high sensitivity, specificity, and accuracy in the detection of early-stage obstruction and acute intestinal vascular compromise. CT can also differentiate between various etiologies of SBO entity which is considered an important criterion in the triage of patients into surgical vs. non-surgical treatment.Conclusion:There Key CT findings which may suggest a need for surgical treatment include mesenteric edema, lack of the small-bowel feces, bowel wall thickening, fat stranding in the mesentery, and intraperitoneal fluid which are predictive of urgent surgical exploration.

Detection of high-energy laser strikes is key to the survivability of military assets in future warfare. The introduction of laser weapon systems demands the capability to quickly detect these strikes without disrupting the stealth capability of military craft with active sensing technologies. We explored the use of thermoelectric generators (TEGs) as self-powered passive sensors to detect such strikes. Experiments were conducted using lasers of various power ratings, wavelengths, and beam sizes to strike 2 × 2 cm2 commercially available TEGs arranged in different configurations. Open-circuit voltage and short-circuit current responses of TEGs struck with 808-, 1070-, and 1980-nm lasers at irradiance levels between 8.5 and 509.3 W / cm2 and spot sizes between 2 and 8 mm are compared. TEG surface temperatures indicate that the sensor can survive temperatures nearing 400°C. TEG open-circuit voltage magnitudes correlate more strongly with net incident laser power than with specific irradiance levels, and linearity is limited by Seebeck coefficient variation with temperature. Open-circuit voltage responses are characterized by 10% to 90% rise times of ∼2 to 10 s despite surface temperatures not reaching equilibrium. With open-circuit voltage as the sensing parameter, detection thresholds three times above the standard deviation noise level can be exceeded within 300 ms of the start of a laser strike with irradiance levels of ∼200 W / cm2. Potential harvested power levels as high as 16 mW are estimated based on measured electrical responses. A multiphysics finite-element model corresponding to the experiments was developed to further optimization of a lightweight, low-profile TEG sensor for detection of high-energy laser strikes.

Background Clinical data demonstrates increased antigen presentation diversity is a key factor in determining response rates to checkpoint inhibitors.1 In addition to tumour mutational burden/microsatellite instability, increased HLA heterozygosity and HLA evolutionary diversity are non-overlapping factors recently identified to further diversify the immunopeptidome and improve clinical response to checkpoint therapies.2 3 Endoplasmic reticulum aminopeptidase 1 (ERAP1) is an enzyme that trims peptides loaded into classical and nonclassical class I MHC molecules.4 5 Ablation of mouse ERAAP modifies the immunopeptidome, resulting in improved immunogenicity, generation of CD8 T cell responses and tumor growth inhibition.6 7 Recently identified selective small molecules potently inhibit ERAP1 across key species and haplotypes.8 We report the further profiling of lead candidate ERAP1 inhibitors in human primary T cell in vitro assays and in vivo tumor models in mice. Methods Human cancer cell lines treated with ERAP1 inhibitors in vitro or in vivo in xenograft mouse models were assessed by immunopeptidomics9 to profile peptide repertoire changes. Novel or upregulated peptides were also tested in human immunogenicity assays. FACS analysis of T cells stimulated with Tyrosinase mRNA transfected human dendritic cells ± ERAP1 inhibition was to assess T cell repertoire changes. ERAP1 inhibitor and anti PD-1 mAb combination was assessed in syngeneic mouse tumor models to investigate tumour growth inhibition and PD end-points (e.g. IHC). Results Analysis of human cervical, lung, colorectal and melanoma cell lines carrying distinct HLA haplotypes demonstrates a consistent and profound effect of ERAP1 inhibition on the immunopeptidome. Novel and upregulated cancer associated antigens identified in association with multiple different HLA-A and B alleles stimulate IFNγ production in primary naive human T cell immunogenicity assays. The impact of ERAP1 inhibition on the T cell repertoire to the melanoma antigen tyrosinase is ongoing. The combination of ERAP1 inhibitor and anti PD-1 mAb led to significant tumor growth inhibition in the CT26 syngeneic mouse tumor model that correlated with increased infiltration of T cells to the tumor. Further PD end-points to be analysed include immune gene array and TCR Vbeta repertoire. Conclusions Grey Wolf ERAP1 inhibitors significantly modify the immunopeptidome both in vitro and in vivo across a broad range of HLA and tumor types. Combination of these inhibitors with anti PD-1 leads to significant T cell infiltration and tumor growth inhibition. Thus, ERAP1 mediated modulation of the immunopeptidome has the potential to drive anti tumor T cell responses and be a transformative immunotherapy. References Rizvi N, Hellmann MD, Snyder A, et al. Mutational landscape determines sensitivity to PD-1 blockade in non–small cell lung cancer. Science. 2015;348(6230):124–128. Chowell D, Morris LGT, Grigg CM, et al. Patient HLA class I genotype influences cancer response to checkpoint blockade immunotherapy. Science 2018;359 (6375):582–587. Chowell D, Krishna C, Pierini F, et al. Evolutionary divergence of HLA class I genotype impacts efficacy of cancer immunotherapy. Nature Medicine 2019;25(11):1715–1720. Shastri N, Nagarajan N, Lind KC, et al. Monitoring peptide processing for MHC class I molecules in the endoplasmic reticulum. Curr Opin Immunol 2014; 26:123–127. Mpakali A, Maben Z, Stern LJ, et al. Molecular pathways for antigenic peptide generation by ER aminopeptidase 1. Mol Immunol 2018; 13:50–57. James E, Bailey I, Sugiyarto G, et al. Induction of protective antitumor immunity through attenuation of ERAAP function. J Immunol 2013;190(11):5839–5846. Manguso RT, Pope HW, Zimmer MD, et al. In vivo CRISPR screening identifies Ptpn2 as a cancer immunotherapy target. Nature 2017;547(7664):413–418. Leonard, H Remtulla A, Poynton F, et al. AACR Annual Meeting 2020. Purcell AW, Ramarathinam SH, Ternette N. Mass spectrometry–based identification of MHC-bound peptides for immunopeptidomics. Nat Protoc 2019;14(6):1687–1707.

Land vegetation growth in the northern high latitudes (north of 50˚N) is strongly temperature limited, thus anomalously warm years are expected to result in an increased drawdown of Carbon Dioxide (CO2) and vice versa. Piao et al (2017) concluded in an analysis of climate and CO2 data from Point Barrow, Alaska that there was a weakening response of northern high latitude spring carbon uptake to temperature anomalies over the last 40 years. They proposed that this is due to a weakening control of temperature on productivity. We have analysed northern high latitude climate and remote sensing vegetation indices, as well as atmospheric CO2 data at Point Barrow, with atmospheric transport analyses of the footprint seen at Barrow. Our results show no large-scale significant change in the spring NDVI-temperature relationship inside the footprint of Barrow, and across the high northern latitudes as a whole. This casts doubt on the assertion that the changing relationship between CO2 uptake and temperature is driven by a change in vegetation response to temperature. We thus tested several alternative mechanisms that could explain the apparent weakening, including a change in interannual variability of atmospheric transport (i.e. the footprint seen by Barrow) and the spatial agreement of temperature anomalies. We find that the heterogeneity of temperature anomalies increased over time, whereas there is no significant change in interannual variation in the footprint seen by Barrow. These results offer an additional explanation for the apparent decrease in spring temperature sensitivity of northern high latitude CO2 uptake.

Purpose The purpose of this paper is to assess the advantages and disadvantages of the use of spit guards by police forces in the UK and to make recommendations regarding an evidence-based approach to decisions related to the use of such equipment. Design/methodology/approach The paper is based upon an examination of a range of primary source material, secondary sources and grey literature. Findings Although the use of spit guards can be justified by factors that include the need to protect police officers from contracting serious infectious diseases, there are a number of problems that concern ethical policing and human rights. Concerns arise when spit guards are deployed against vulnerable individuals, are used offensively rather than defensively and when such equipment is deployed disproportionately against persons from Black and Minority Ethnic (BME) communities. Additionally, the image of the police may suffer if spit guards are accompanied by the use of excessive force which may be perceived as an abuse of police power. Practical implications The paper makes recommendations that a comprehensive evidence base is required to assist practitioners to make informed decisions regarding the deployment of spit guards. This evidence base should include the extent to which officers are spat at, medical evidence relating to spitting and the transmission of serious diseases, the views of the public concerning the deployment of spit guards and estimations as to whether such equipment will deter spitting by suspects of crime. Originality/value This paper provides an original academic contribution to the ongoing debate on the use of spit guards within policing. In particular, it brings together a wide range of material that relates to this topic and presents it as a coherent set of arguments located in a single source.

Clinical data demonstrates increased antigen presentation diversity is an important factor in determining response rates to checkpoint inhibitors. In addition to tumor mutational burden, increased HLA heterozygosity and HLA evolutionary diversity are non-overlapping factors which further diversify the immunopeptidome and improve clinical response to checkpoint therapies. Endoplasmic reticulum aminopeptidase 1 (ERAP1) is an enzyme that trims peptides loaded into classical and nonclassical MHC Class I molecules. Human genome-wide association studies have identified single nucleotide polymorphisms within ERAP1 that are associated with immune-related diseases, such as ankylosing spondylitis, providing human genetic validation for ERAP1's role in human disease and antigen presentation. Further, ablation of mouse ERAAP modifies the immunopeptidome, resulting in improved immunogenicity, generation of CD8+ T cell responses and tumor growth inhibition. Grey Wolf Therapeutics have developed highly potent and selective ERAP1 inhibitors. These inhibitors demonstrate significant modulation of the cancer-related antigen repertoire across diverse ERAP1 and HLA genotypes and cancer-type backgrounds, both in vitro and in vivo. These changes in the antigen repertoire drive changes in T cell activation and response, leading to increased T cell infiltration into CT26 syngeneic tumors and T cell receptor (TCR) diversification when combined with anti-PD-1. We have identified immune related markers that are modulated following ERAP1 inhibition in syngeneic tumor models which have the potential to be used as biomarkers. Importantly, ERAP1 inhibitor induced immunopeptidome and T cell changes lead to significant tumor growth inhibition in syngeneic mouse models when combined with anti-PD-1. In parallel, we have demonstrated the ability of ERAP1 inhibitor induced novel cancer associated antigens to stimulate human CD8+ T cell responses. Extensive assessment of the potential of ERAP1 inhibitors to enhance tumor immune responses in combination with additional therapies (e.g. chemotherapy and radiotherapy), across different tumor microenvironments, is ongoing. These data provide the foundation from which we plan to explore the potential of our first-in-class ERAP1 inhibitor development candidate in the clinic. Citation Format: Andrew Leishman, Fergus Poynton, Nicola Ternette, Elisa Lori, Camila de Almeida, Henry Leonard, Emma Reeves, Edd James, Kristopher Clark, Carmen Tong, Jason Shiers, Martin Quibell, Peter Ian Joyce. First in class inhibitors of ERAP1 have the potential to be a transformative immunotherapy in oncology [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 1715.