Prediction of viral spillover risk based on the mass action principle

Infectious zoonotic disease emergence, through spillover events, is of global concern and has the potential to cause significant harm to society, as recently demonstrated by COVID-19. More than 70% of the 400 infectious diseases that emerged in the past five decades have a zoonotic origin, including all recent pandemics. There have been several approaches used to predict the risk of spillover through some of the known or suspected infectious disease emergence drivers, largely using correlative approaches. Here, we predict the spatial distribution of spillover risk by approximating general transmission through animal and human interactions. These mass action interactions are approximated through the multiplication of the spatial distribution of zoonotic virus diversity and human population density. Although our results indicate higher risk in regions along the equator and in Southeast Asia where both virus diversity and human population density are high, it should be noted that this is primarily a conceptual exercise. We compared our spillover risk map to key factors, including the model inputs of zoonotic virus diversity estimate map, human population density map, and the spatial distribution of species richness. Despite the limitations of this approach, this viral spillover map is a step towards developing a more comprehensive spillover risk prediction system to inform global monitoring.

Biodiversity loss reduces global terrestrial carbon storage

Natural ecosystems store large amounts of carbon globally, as organisms absorb carbon from the atmosphere to build large, long-lasting, or slow-decaying structures such as tree bark or root systems. An ecosystem's carbon sequestration potential is tightly linked to its biological diversity. Yet when considering future projections, many carbon sequestration models fail to account for the role biodiversity plays in carbon storage. Here, we assess the consequences of plant biodiversity loss for carbon storage under multiple climate and land-use change scenarios. We link a macroecological model projecting changes in vascular plant richness under different scenarios with empirical data on relationships between biodiversity and biomass. We find that biodiversity declines from climate and land use change could lead to a global loss of between 7.44-103.14 PgC (global sustainability scenario) and 10.87-145.95 PgC (fossil-fueled development scenario). This indicates a self-reinforcing feedback loop, where higher levels of climate change lead to greater biodiversity loss, which in turn leads to greater carbon emissions and ultimately more climate change. Conversely, biodiversity conservation and restoration can help achieve climate change mitigation goals.

The exposure of the world's mountains to global change drivers

Global change affects mountain areas at different levels, with some mountains being more exposed to change in climate or environmental conditions and others acting as local refugia. We quantified the exposure of the world's mountains to three drivers of change, climate, land use, and human population density, using two spatial-temporal metrics (velocity and magnitude of change). We estimated the acceleration of change for these drivers by comparing past (1975-2005) vs. future (2020-2050) exposure, and we also compared exposure in lowlands vs. mountains. We found Africa's tropical mountains facing the highest future exposure to multiple drivers of change, thus requiring targeted adaptation and mitigation strategies to preserve biodiversity. European and North America's mountains, in contrast, experience more limited exposure to global change and could act as local refugia for biodiversity. This knowledge can be used to prioritize local-scale interventions and planning long-term monitoring to reduce the risks faced by mountain biodiversity.

Global trends and scenarios for terrestrial biodiversity and ecosystem services from 1900 to 2050

Based on an extensive model intercomparison, we assessed trends in biodiversity and ecosystem services from historical reconstructions and future scenarios of land-use and climate change. During the 20th century, biodiversity declined globally by 2 to 11%, as estimated by a range of indicators. Provisioning ecosystem services increased several fold, and regulating services decreased moderately. Going forward, policies toward sustainability have the potential to slow biodiversity loss resulting from land-use change and the demand for provisioning services while reducing or reversing declines in regulating services. However, negative impacts on biodiversity due to climate change appear poised to increase, particularly in the higher-emissions scenarios. Our assessment identifies remaining modeling uncertainties but also robustly shows that renewed policy efforts are needed to meet the goals of the Convention on Biological Diversity.

Using social media records to inform conservation planning

Citizen science plays a crucial role in helping monitor biodiversity and inform conservation. With the widespread use of smartphones, many people share biodiversity information on social media, but this information is still not widely used in conservation. Focusing on Bangladesh, a tropical megadiverse and mega-populated country, we examined the importance of social media records in conservation decision-making. We collated species distribution records for birds and butterflies from Facebook and Global Biodiversity Information Facility (GBIF), grouped them into GBIF-only and combined GBIF and Facebook data, and investigated the differences in identifying critical conservation areas. Adding Facebook data to GBIF data improved the accuracy of systematic conservation planning assessments by identifying additional important conservation areas in the northwest, southeast, and central parts of Bangladesh, extending priority conservation areas by 4,000-10,000 km2 . Community efforts are needed to drive the implementation of the ambitious Kunming-Montreal Global Biodiversity Framework targets, especially in megadiverse tropical countries with a lack of reliable and up-to-date species distribution data. We highlight that conservation planning can be enhanced by including available data gathered from social media platforms.

Modelling the probability of meeting IUCN Red List criteria to support reassessments

Comparative extinction risk analysis-which predicts species extinction risk from correlation with traits or geographical characteristics-has gained research attention as a promising tool to support extinction risk assessment in the IUCN Red List of Threatened Species. However, its uptake has been very limited so far, possibly because existing models only predict a species' Red List category, without indicating which Red List criteria may be triggered. This prevents such approaches to be integrated into Red List assessments. We overcome this implementation gap by developing models that predict the probability of species meeting individual Red List criteria. Using data on the world's birds, we evaluated the predictive performance of our criterion-specific models and compared it with the typical criterion-blind modelling approach. We compiled data on biological traits (e.g. range size, clutch size) and external drivers (e.g. change in canopy cover) often associated with extinction risk. For each specific criterion, we modelled the relationship between extinction risk predictors and species' Red List category under that criterion using ordinal regression models. We found criterion-specific models were better at identifying threatened species compared to a criterion-blind model (higher sensitivity), but less good at identifying not threatened species (lower specificity). As expected, different covariates were important for predicting extinction risk under different criteria. Change in annual temperature was important for criteria related to population trends, while high forest dependency was important for criteria related to restricted area of occupancy or small population size. Our criteria-specific method can support Red List assessors by producing outputs that identify species likely to meet specific criteria, and which are the most important predictors. These species can then be prioritised for re-evaluation. We expect this new approach to increase the uptake of extinction risk models in Red List assessments, bridging a long-standing research-implementation gap.

A standard approach for including climate change responses in IUCN Red List assessments

The International Union for Conservation of Nature (IUCN) Red List is a central tool for extinction risk monitoring and influences global biodiversity policy and action. But, to be effective, it is crucial that it consistently accounts for each driver of extinction. Climate change is rapidly becoming a key extinction driver, but consideration of climate change information remains challenging for the IUCN. Several methods can be used to predict species' future decline, but they often fail to provide estimates of the symptoms of endangerment used by IUCN. We devised a standardized method to measure climate change impact in terms of change in habitat quality to inform criterion A3 on future population reduction. Using terrestrial nonvolant tetrapods as a case study, we measured this impact as the difference between the current and the future species climatic niche, defined based on current and future bioclimatic variables under alternative model algorithms, dispersal scenarios, emission scenarios, and climate models. Our models identified 171 species (13% out of those analyzed) for which their current red-list category could worsen under criterion A3 if they cannot disperse beyond their current range in the future. Categories for 14 species (1.5%) could worsen if maximum dispersal is possible. Although ours is a simulation exercise and not a formal red-list assessment, our results suggest that considering climate change impacts may reduce misclassification and strengthen consistency and comprehensiveness of IUCN Red List assessments.

Dissimilarity of vertebrate trophic interactions reveals spatial uniqueness but functional redundancy across Europe

Identifying areas that contain species assemblages not found elsewhere in a region is central to conservation planning.1,2 Species assemblages contain networks of species interactions that underpin species dynamics,3,4 ecosystem processes, and contributions to people.5,6,7 Yet the uniqueness of interaction networks in a regional context has rarely been assessed. Here, we estimated the spatial uniqueness of 10,000 terrestrial vertebrate trophic networks across Europe (1,164 species, 50,408 potential interactions8) based on the amount of similarity between all local networks mapped at a 10 km resolution. Our results revealed more unique networks in the Arctic bioregion, but also in southern Europe and isolated islands. We then contrasted the uniqueness of trophic networks with their vulnerability to human footprint and future climate change and measured their coverage within protected areas. This analysis revealed that unique networks situated in southern Europe were particularly exposed to human footprint and that unique networks in the Arctic might be at risk from future climate change. However, considering interaction networks at the level of trophic groups, rather than species, revealed that the general structure of trophic networks was redundant across the continent, in contrast to species' interactions. We argue that proactive European conservation strategies might gain relevance by turning their eyes toward interaction networks that are both unique and vulnerable.

Prioritizing the reassessment of data-deficient species on the IUCN Red List

Despite being central to the implementation of conservation policies, the usefulness of the International Union for Conservation of Nature (IUCN) Red List of Threatened Species is hampered by the 14% of species classified as data-deficient (DD) because information to evaluate these species' extinction risk was lacking when they were last assessed or because assessors did not appropriately account for uncertainty. Robust methods are needed to identify which DD species are more likely to be reclassified in one of the data-sufficient IUCN Red List categories. We devised a reproducible method to help red-list assessors prioritize reassessment of DD species and tested it with 6887 DD species of mammals, reptiles, amphibians, fishes, and Odonata (dragonflies and damselflies). For each DD species in these groups, we calculated its probability of being classified in a data-sufficient category if reassessed today from covariates measuring available knowledge (e.g., number of occurrence records or published articles available), knowledge proxies (e.g., remoteness of the range), and species characteristics (e.g., nocturnality); calculated change in such probability since last assessment from the increase in available knowledge (e.g., new occurrence records); and determined whether the species might qualify as threatened based on recent rate of habitat loss determined from global land-cover maps. We identified 1907 species with a probability of being reassessed in a data-sufficient category of >0.5; 624 species for which this probability increased by >0.25 since last assessment; and 77 species that could be reassessed as near threatened or threatened based on habitat loss. Combining these 3 elements, our results provided a list of species likely to be data-sufficient such that the comprehensiveness and representativeness of the IUCN Red List can be improved.

Elevational homogenization of mountain parasitoids across six decades

Elevational gradients are characterized by strong environmental changes within small geographical distances, providing important insights on the response of biological communities to climate change. Mountain biodiversity is particularly sensitive to climate change, given the limited capacity to colonize new areas and the competition from upshifting lowland species. Knowledge on the impact of climate change on mountain insect communities is patchy, but elevation is known to influence parasitic interactions which control insect communities and functions within ecosystems. We analyzed a European dataset of bristle flies, a parasitoid group which regulates insect herbivory in both managed and natural ecosystems. Our dataset spans six decades and multiple elevational bands, and we found marked elevational homogenization in the host specialization of bristle fly species through time. The proportion of specialized parasitoids has increased by ca. 70% at low elevations, from 17 to 29%, and has decreased by ca. 20% at high elevations, from 48 to 37%. As a result, the strong elevational gradient in bristle fly specialization observed in the 1960s has become much flatter over time. As climate warming is predicted to accelerate, the disappearance of specialized parasitoids from high elevations might become even faster. This parasitoid homogenization can reshape the ecological function of mountain insect communities, increasing the risk of herbivory outbreak at high elevations. Our results add to the mounting evidence that symbiotic species might be especially at risk from climate change: Monitoring the effects of these changes is urgently needed to define effective conservation strategies for mountain biodiversity.

Scenarios of change in the realized climatic niche of mountain carnivores and ungulates

Mountains are among the natural systems most affected by climate change, and mountain mammals are considered particularly imperiled, given their high degree of specialization to narrow tolerance bands of environmental conditions. Climate change mitigation policies, such as the Paris Agreement, are essential to stem climate change impacts on natural systems. But how significant is the Paris Agreement to the survival of mountain mammals? We investigated how alternative emission scenarios may determine change in the realized climatic niche of mountain carnivores and ungulates in 2050. We based our predictions of future change in species niches based on how species have responded to past environmental changes, focusing on the probabilities of niche shrink and niche stability. We found that achieving the Paris Agreement's commitments would substantially reduce climate instability for mountain species. Specifically, limiting global warming to below 1.5°C would reduce the probability of niche shrinkage by 4% compared with a high-emission scenario. Globally, carnivores showed greater niche shrinkage than ungulates, whereas ungulates were more likely to shift their niches (i.e., face a level of climate change that allows adaptation). Twenty-three species threatened by climate change according to the IUCN Red List had greater niche contraction than other species we analyzed (3% higher on average). We therefore argue that climate mitigation policies must be coupled with rapid species-specific conservation intervention and sustainable land-use policies to avoid high risk of loss of already vulnerable species.

Increasing biodiversity knowledge through social media: A case study from tropical Bangladesh

Citizen science programs are becoming increasingly popular among naturalists but remain heavily biased taxonomically and geographically. However, with the explosive popularity of social media and the near-ubiquitous availability of smartphones, many post wildlife photographs on social media. Here, we illustrate the potential of harvesting these data to enhance our biodiversity understanding using Bangladesh, a tropical biodiverse country, as a case study. We compared biodiversity records extracted from Facebook with those from the Global Biodiversity Information Facility (GBIF), collating geospatial records for 1013 unique species, including 970 species from Facebook and 712 species from GBIF. Although most observation records were biased toward major cities, the Facebook records were more evenly spatially distributed. About 86% of the Threatened species records were from Facebook, whereas the GBIF records were almost entirely Of Least Concern species. To reduce the global biodiversity data shortfall, a key research priority now is the development of mechanisms for extracting and interpreting social media biodiversity data.

Opportunities and challenges for Common Agricultural Policy reform to support the European Green Deal

The Common Agricultural Policy (CAP) is the European Union's main instrument for agricultural planning, with a new reform approved for 2023-2027. The CAP intends to align with the European Green Deal (EGD), a set of policy initiatives underpinning sustainable development and climate neutrality in the European Union (EU), but several flaws cast doubts about the compatibility of the objectives of these 2 policies. We reviewed recent literature on the potential of CAP environmental objectives for integration with the EGD: protection of biodiversity, climate change mitigation and adaptation, and sustainable management of natural resources. The CAP lacks appropriate planning measures, furthering instead risks to biodiversity and ecosystem services driven by landscape and biotic homogenization. Funding allocation mechanisms are not tailored to mitigate agricultural emissions, decreasing the efficiency of climate mitigation actions. The legislation subsidies farmers making extensive use of synthetic inputs without adequately supporting organic production, hindering the transition toward sustainable practices. We recommend proper control mechanisms be introduced in CAP Strategic Plans from each member state to ensure the EU is set on a sustainable production and consumption path. These include proportional assignment of funds to each CAP objective, quantitative targets to set goals and evidence-based interventions, and relevant indicators to facilitate effective monitoring of environmental performance. Both the CAP and the EGD should maintain ambitious environmental commitments in the face of crisis to avoid further degradation of the natural resources on which production systems stand.

Operationalizing One Health: Environmental Solutions for Pandemic Prevention

Human pressure on the environment is increasing the frequency, diversity, and spatial extent of disease outbreaks. Despite international recognition, the interconnection between the health of the environment, animals, and humans has been historically overlooked. Past and current initiatives have often neglected prevention under the One Health preparedness cycle, largely focusing on post-spillover stages. We argue that pandemic prevention initiatives have yet to produce actionable targets and indicators, connected to overarching goals, like it has been done for biodiversity loss and climate change. We show how the Driver-Pressure-State-Impact-Response framework, already employed by the Convention on Biological Diversity, can be repurposed to operationalize pandemic prevention. Global responses for pandemic prevention should strive for complementarity and synergies among initiatives, better articulating prevention under One Health. Without agreed-upon goals underpinning specific targets and interventions, current global efforts are unlikely to function at the speed and scale necessary to decrease the risk of disease outbreaks that might lead to pandemics. Threats to the environment are not always abatable, but decreasing the likelihood that environmental pressure leads to pandemics, and developing strategies to mitigate these impacts, are both attainable goals.

Area of Habitat maps for the world's terrestrial birds and mammals

Area of Habitat (AOH) is "the habitat available to a species, that is, habitat within its range". It complements a geographic range map for a species by showing potential occupancy and reducing commission errors. AOH maps are produced by subtracting areas considered unsuitable for the species from their range map, using information on each species' associations with habitat and elevation. We present AOH maps for 5,481 terrestrial mammal and 10,651 terrestrial bird species (including 1,816 migratory bird species for which we present separate maps for the resident, breeding and non-breeding areas). Our maps have a resolution of 100 m. On average, AOH covered 66 ± 28% of the range maps for mammals and 64 ± 27% for birds. The AOH maps were validated independently, following a novel two-step methodology: a modelling approach to identify outliers and a species-level approach based on point localities. We used AOH maps to produce global maps of the species richness of mammals, birds, globally threatened mammals and globally threatened birds.

Land-use and climate risk assessment for Earth's remaining wilderness

Earth's wilderness areas are reservoirs of genetic information and carbon storage systems, and are vital to reducing extinction risks. Retaining the conservation value of these areas is fundamental to achieving global biodiversity conservation goals; however, climate and land-use risk can undermine their ability to provide these functions. The extent to which wilderness areas are likely to be impacted by these drivers has not previously been quantified. Using climate and land-use change during baseline (1971-2005) and future (2016-2050) periods, we estimate that these stressors within wilderness areas will increase by ca. 60% and 39%, respectively, under a scenario of high emission and land-use change (SSP5-RCP8.5). Nearly half (49%) of all wilderness areas could experience substantial climate change by 2050 under this scenario, potentially limiting their capacity to shelter biodiversity. Notable climate (>5 km year^-1) and land-use (>0.25 km year^-1) changes are expected to occur more rapidly in the unprotected wilderness, including the edges of the Amazonian wilderness, Northern Russia, and Central Africa, which support unique assemblages of species and are critical for the preservation of biodiversity. However, an alternative scenario of sustainable development (SSP1-RCP2.6) would attenuate the projected climate velocity and land-use instability by 54% and 6%, respectively. Mitigating greenhouse gas emissions and preserving the remaining intact natural ecosystems can help fortify these bastions of biodiversity.

Reptile research shows new avenues and old challenges for extinction risk modelling

This Primer explores the implications of a new PLOS Biology study that presents an innovative method for estimating extinction risk in reptile species worldwide; this method represents a promising avenue to support Red List assessment, alongside some well-known challenges.

The minimum land area requiring conservation attention to safeguard biodiversity

Ambitious conservation efforts are needed to stop the global biodiversity crisis. In this study, we estimate the minimum land area to secure important biodiversity areas, ecologically intact areas, and optimal locations for representation of species ranges and ecoregions. We discover that at least 64 million square kilometers (44% of terrestrial area) would require conservation attention (ranging from protected areas to land-use policies) to meet this goal. More than 1.8 billion people live on these lands, so responses that promote autonomy, self-determination, equity, and sustainable management for safeguarding biodiversity are essential. Spatially explicit land-use scenarios suggest that 1.3 million square kilometers of this land is at risk of being converted for intensive human land uses by 2030, which requires immediate attention. However, a sevenfold difference exists between the amount of habitat converted in optimistic and pessimistic land-use scenarios, highlighting an opportunity to avert this crisis. Appropriate targets in the Post-2020 Global Biodiversity Framework to encourage conservation of the identified land would contribute substantially to safeguarding biodiversity.

Translating habitat class to land cover to map area of habitat of terrestrial vertebrates

Area of habitat (AOH) is defined as the "habitat available to a species, that is, habitat within its range" and is calculated by subtracting areas of unsuitable land cover and elevation from the range. The International Union for the Conservation of Nature (IUCN) Habitats Classification Scheme provides information on species habitat associations, and typically unvalidated expert opinion is used to match habitat to land-cover classes, which generates a source of uncertainty in AOH maps. We developed a data-driven method to translate IUCN habitat classes to land cover based on point locality data for 6986 species of terrestrial mammals, birds, amphibians, and reptiles. We extracted the land-cover class at each point locality and matched it to the IUCN habitat class or classes assigned to each species occurring there. Then, we modeled each land-cover class as a function of IUCN habitat with (SSG, using) logistic regression models. The resulting odds ratios were used to assess the strength of the association between each habitat and land-cover class. We then compared the performance of our data-driven model with those from a published translation table based on expert knowledge. We calculated the association between habitat classes and land-cover classes as a continuous variable, but to map AOH as binary presence or absence, it was necessary to apply a threshold of association. This threshold can be chosen by the user according to the required balance between omission and commission errors. Some habitats (e.g., forest and desert) were assigned to land-cover classes with more confidence than others (e.g., wetlands and artificial). The data-driven translation model and expert knowledge performed equally well, but the model provided greater standardization, objectivity, and repeatability. Furthermore, our approach allowed greater flexibility in the use of the results and uncertainty to be quantified. Our model can be modified for regional examinations and different taxonomic groups.

Matrix condition mediates the effects of habitat fragmentation on species extinction risk

Habitat loss is the leading cause of the global decline in biodiversity, but the influence of human pressure within the matrix surrounding habitat fragments remains poorly understood. Here, we measure the relationship between fragmentation (the degree of fragmentation and the degree of patch isolation), matrix condition (measured as the extent of high human footprint levels), and the change in extinction risk of 4,426 terrestrial mammals. We find that the degree of fragmentation is strongly associated with changes in extinction risk, with higher predictive importance than life-history traits and human pressure variables. Importantly, we discover that fragmentation and the matrix condition are stronger predictors of risk than habitat loss and habitat amount. Moreover, the importance of fragmentation increases with an increasing deterioration of the matrix condition. These findings suggest that restoration of the habitat matrix may be an important conservation action for mitigating the negative effects of fragmentation on biodiversity.

The influence of human pressure within the matrix surrounding habitat fragments remains poorly understood. This study measures the relationship between habitat fragmentation, matrix condition and the change in extinction risk of 4,426 terrestrial mammals, finding that fragmentation and matrix condition are stronger predictors of risk than habitat loss and habitat amount.

Areas of global importance for conserving terrestrial biodiversity, carbon and water

To meet the ambitious objectives of biodiversity and climate conventions, the international community requires clarity on how these objectives can be operationalized spatially and how multiple targets can be pursued concurrently. To support goal setting and the implementation of international strategies and action plans, spatial guidance is needed to identify which land areas have the potential to generate the greatest synergies between conserving biodiversity and nature's contributions to people. Here we present results from a joint optimization that minimizes the number of threatened species, maximizes carbon retention and water quality regulation, and ranks terrestrial conservation priorities globally. We found that selecting the top-ranked 30% and 50% of terrestrial land area would conserve respectively 60.7% and 85.3% of the estimated total carbon stock and 66% and 89.8% of all clean water, in addition to meeting conservation targets for 57.9% and 79% of all species considered. Our data and prioritization further suggest that adequately conserving all species considered (vertebrates and plants) would require giving conservation attention to ~70% of the terrestrial land surface. If priority was given to biodiversity only, managing 30% of optimally located land area for conservation may be sufficient to meet conservation targets for 81.3% of the terrestrial plant and vertebrate species considered. Our results provide a global assessment of where land could be optimally managed for conservation. We discuss how such a spatial prioritization framework can support the implementation of the biodiversity and climate conventions.

Abstract 1493: Discovery and CAR T targeting of lineage-restricted neuroblastoma oncoproteins

Background: The MHC presents a snapshot of the intracellular proteome for surveillance by T cells, including peptides from mutated proteins (neoantigens) and nonmutated but aberrantly expressed proteins. Though peptides derived from nonmutated oncoproteins may be presented on MHC, self-antigens are not normally immunogenic to native T cells. Neuroblastoma presents a unique combination of challenges in identifying and targeting tumor-specific antigens: low mutational burden and low MHC expression.

Methods and Results: Using an immunogenomic and immunopeptidomics approach in 16 human neuroblastoma samples, we identified 265 novel antigens presented on MHC and prioritized 6 (including the PHOX2B master regulator) as lead preclinical candidates based on: 1) binding affinity to common HLA alleles, 2) extent of differential gene expression, 3) lack of MHC presentation in healthy tissue, 4) biological relevance to neuroblastoma, and 5) recurrence across multiple tumors. We validated PHOX2B binding to the predicted HLA allele A24 using crystallography of the refolded peptide-MHC (pMHC) complex, and confirmed the peptide sequence using LC/MS/MS of the synthetic peptide. Upon antigen validation, we engineered CAR receptors to induce immunogenicity to self-antigens. Phage display libraries were used to pan for tumor-specific scFv's, using predicted cross-reactive pMHCs as decoys, generating candidate scFv's that were cloned into CAR constructs. We developed an algorithm to predict cross-reactivity against normal tissue pMHCs and screened CARs for cross-reactivity, prioritizing constructs with high tumor antigen affinity and low cross-reactivity. Lead CARs demonstrate complete elimination of tumor cells in less than 24 hours using 1:1 E:T ratios in neuroblastoma cells, and not in other cancer lines expressing HLA-A24 but not PHOX2B, demonstrating highly specific and potent killing. Robust CAR killing was induced by pulsing HLA-A24+/PHOX2B- melanoma cells with PHOX2B peptide but not with potential cross-reactive peptides. Finally, two lead CAR constructs induced complete regression of established neuroblastoma HLA-A24+ SKNAS xenografts, with additional murine trials ongoing.

Conclusion: Neuroblastomas present a unique ligandome, including a significant number of antigens derived from lineage-restricted oncoproteins. We demonstrate proof-of-concept using scFv-based CARs to target the previously undruggable PHOX2B transcription factor in in vitro and in vivo studies. These data provide a basis for targeting non-immunogenic lineage-restricted oncoproteins using CAR T cells in neuroblastoma and other human cancers.

Citation Format: Mark Yarmarkovich, John M. Warrington, Quinlen F. Marshall, Helena Shen, Wei Li, Matt Beasley, Moreno Di Marco, Stefan Stevanovic, Nikolaos G. Sgourakis, Dimiter Dimitrov, Peter Smith, John M. Maris. Discovery and CAR T targeting of lineage-restricted neuroblastoma oncoproteins [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 1493.

COMBINE: a coalesced mammal database of intrinsic and extrinsic traits

The use of species' traits in macroecological analyses has gained popularity in the last decade, becoming an important tool to understand global biodiversity patterns. Currently, trait data can be found across a wide variety of data sets included in websites, articles, and books, each one with its own taxonomic classification, set of traits, and data management methodology. Mammals, in particular, are among the most studied taxa, with large sources of trait information readily available. To facilitate the use of these data, we did an extensive review of published mammal trait data sources between 1999 and May 2020 and produced COMBINE: a COalesced Mammal dataBase of INtrinsic and Extrinsic traits. Our aim was to create a taxonomically integrated database of mammal traits that maximized trait number and coverage without compromising data quality. COMBINE contains information on 54 traits for 6,234 extant and recently extinct mammal species, including information on morphology, reproduction, diet, biogeography, life habit, phenology, behavior, home range, and density. Additionally, we calculated other relevant traits such as habitat and altitudinal breadths for all species and dispersal for terrestrial non-volant species. All data are compatible with the taxonomies of the IUCN Red List v. 2020-2 and PHYLACINE v. 1.2. Missing data were adequately flagged and imputed for non-biogeographical traits with 20% or more data available. We obtained full data sets for 21 traits such as female maturity, litter size, maximum longevity, trophic level, and dispersal, providing imputation performance statistics for all. This data set will be especially useful for those interested in including species' traits in large-scale ecological and conservation analyses. There are no copyright or proprietary restrictions; we request citation of this publication and all relevant underlying data sources (found in Data S1: trait_data_sources.csv), upon using these data.

Effects of spatial autocorrelation and sampling design on estimates of protected area effectiveness

Estimating the effectiveness of protected areas (PAs) in reducing deforestation is useful to support decisions on whether to invest in better management of areas already protected or to create new ones. Statistical matching is commonly used to assess this effectiveness, but spatial autocorrelation and regional differences in protection effectiveness are frequently overlooked. Using Colombia as a case study, we employed statistical matching to account for confounding factors in park location and accounted for for spatial autocorrelation to determine statistical significance. We compared the performance of different matching procedures-ways of generating matching pairs at different scales-in estimating PA effectiveness. Differences in matching procedures affected covariate similarity between matched pairs (balance) and estimates of PA effectiveness in reducing deforestation. Independent matching yielded the greatest balance. On average 95% of variables in each region were balanced with independent matching, whereas 33% of variables were balanced when using the method that performed worst. The best estimates suggested that average deforestation inside protected areas in Colombia was 40% lower than in matched sites. Protection significantly reduced deforestation, but PA effectiveness differed among regions. Protected areas in Caribe were the most effective, whereas those in Orinoco and Pacific were least effective. Our results demonstrate that accounting for spatial autocorrelation and using independent matching for each subset of data is needed to infer the effectiveness of protection in reducing deforestation. Not accounting for spatial autocorrelation can distort the assessment of protection effectiveness, increasing type I and II errors and inflating effect size. Our method allowed improved estimates of protection effectiveness across scales and under different conditions and can be applied to other regions to effectively assess PA performance.

Global correlates of range contractions and expansions in terrestrial mammals

Understanding changes in species distributions is essential to disentangle the mechanisms that drive their responses to anthropogenic habitat modification. Here we analyse the past (1970s) and current (2017) distribution of 204 species of terrestrial non-volant mammals to identify drivers of recent contraction and expansion in their range. We find 106 species lost part of their past range, and 40 of them declined by >50%. The key correlates of this contraction are large body mass, increase in air temperature, loss of natural land, and high human population density. At the same time, 44 species have some expansion in their range, which correlates with small body size, generalist diet, and high reproductive rates. Our findings clearly show that human activity and life history interact to influence range changes in mammals. While the former plays a major role in determining contraction in species’ distribution, the latter is important for both contraction and expansion.

Understanding why many species ranges are contracting while others are stable or expanding is important to inform conservation in an increasingly human-modified world. Here, Pacifici and colleagues investigate changes in the ranges of 204 mammals, showing that human factors mostly explain range contractions while life history explains both contraction and expansion.

Reconciling global priorities for conserving biodiversity habitat

Degradation and loss of natural habitat is the major driver of the current global biodiversity crisis. Most habitat conservation efforts to date have targeted small areas of highly threatened habitat, but emerging debate suggests that retaining large intact natural systems may be just as important. We reconcile these perspectives by integrating fine-resolution global data on habitat condition and species assemblage turnover to identify Earth's high-value biodiversity habitat. These are areas in better condition than most other locations predicted to have once supported a similar assemblage of species and are found within both intact regions and human-dominated landscapes. However, only 18.6% of this high-value habitat is currently protected globally. Averting permanent biodiversity loss requires clear, spatially explicit targets for retaining these unprotected high-value habitats.

Integrative -omics and HLA-ligandomics analysis to identify novel drug targets for ccRCC immunotherapy

Background

Clear cell renal cell carcinoma (ccRCC) is the dominant subtype of renal cancer. With currently available therapies, cure of advanced and metastatic ccRCC is achieved only in rare cases. Here, we developed a workflow integrating different -omics technologies to identify ccRCC-specific HLA-presented peptides as potential drug targets for ccRCC immunotherapy.

Methods

We analyzed HLA-presented peptides by MS-based ligandomics of 55 ccRCC tumors (cohort 1), paired non-tumor renal tissues, and 158 benign tissues from other organs. Pathways enriched in ccRCC compared to its cell type of origin were identified by transcriptome and gene set enrichment analyses in 51 tumor tissues of the same cohort. To retrieve a list of candidate targets with involvement in ccRCC pathogenesis, ccRCC-specific pathway genes were intersected with the source genes of tumor-exclusive peptides. The candidates were validated in an independent cohort from The Cancer Genome Atlas (TCGA KIRC, n = 452). DNA methylation (TCGA KIRC, n = 273), somatic mutations (TCGA KIRC, n = 392), and gene ontology (GO) and correlations with tumor metabolites (cohort 1, n = 30) and immune-oncological markers (cohort 1, n = 37) were analyzed to characterize regulatory and functional involvements. CD8⁺ T cell priming assays were used to identify immunogenic peptides. The candidate gene EGLN3 was functionally investigated in cell culture.

Results

A total of 34,226 HLA class I- and 19,325 class II-presented peptides were identified in ccRCC tissue, of which 443 class I and 203 class II peptides were ccRCC-specific and presented in ≥ 3 tumors. One hundred eighty-five of the 499 corresponding source genes were involved in pathways activated by ccRCC tumors. After validation in the independent cohort from TCGA, 113 final candidate genes remained. Candidates were involved in extracellular matrix organization, hypoxic signaling, immune processes, and others. Nine of the 12 peptides assessed by immunogenicity analysis were able to activate naïve CD8⁺ T cells, including peptides derived from EGLN3. Functional analysis of EGLN3 revealed possible tumor-promoting functions.

Conclusions

Integration of HLA ligandomics, transcriptomics, genetic, and epigenetic data leads to the identification of novel functionally relevant therapeutic targets for ccRCC immunotherapy. Validation of the identified targets is recommended to expand the treatment landscape of ccRCC.

A new synthetic toll-like receptor 1/2 ligand is an efficient adjuvant for peptide vaccination in a human volunteer

BACKGROUND

We previously showed that the bacterial lipopeptide Pam₃Cys-Ser-Ser, meanwhile established as a toll-like receptor (TLR) 1/2 ligand, acts as a strong adjuvant for the induction of virus specific CD8⁺ T cells in mice, when covalently coupled to a synthetic peptide.

CASE PRESENTATION

We now designed a new water-soluble synthetic Pam₃Cys-derivative, named XS15 and characterized it in vitro by a TLR2 NF-κB luciferase reporter assay. Further, the capacity of XS15 to activate immune cells and stimulate peptide-specific CD8⁺ T and NK cells by 6-sulfo LacNAc⁺ monocytes was assessed by flow cytometry as well as cytokine induction using immunoassays. The induction of a functional immune response after vaccination of a volunteer with viral peptides was assessed by ELISpot assay and flow cytometry in peripheral blood cells and infiltrating cells at the vaccination site, as well as by immunohistochemistry and imaging. XS15 induced strong ex vivo CD8⁺ and T_H1 CD4⁺ responses in a human volunteer upon a single injection of XS15 mixed to uncoupled peptides in a water-in-oil emulsion (Montanide™ ISA51 VG). A granuloma formed locally at the injection site containing highly activated functional CD4⁺ and CD8⁺ effector memory T cells. The total number of vaccine peptide-specific functional T cells was experimentally assessed and estimated to be 3.0 × 10⁵ in the granuloma and 20.5 × 10⁶ in peripheral blood.

CONCLUSION

Thus, in one volunteer we show a granuloma forming by peptides combined with an efficient adjuvant in a water-in-oil-emulsion, inducing antigen specific T cells detectable in circulation and at the vaccination site, after one single vaccination only. The ex vivo T cell responses in peripheral blood were detectable for more than one year and could be strongly boosted by a second vaccination. Hence, XS15 is a promising adjuvant candidate for peptide vaccination, in particular for tumor peptide vaccines in a personalized setting.

Projecting impacts of global climate and land-use scenarios on plant biodiversity using compositional-turnover modelling

Nations have committed to ambitious conservation targets in response to accelerating rates of global biodiversity loss. Anticipating future impacts is essential to inform policy decisions for achieving these targets, but predictions need to be of sufficiently high spatial resolution to forecast the local effects of global change. As part of the intercomparison of biodiversity and ecosystem services models of the Intergovernmental Science-Policy Platform on Biodiversity and Ecosystem Services, we present a fine-resolution assessment of trends in the persistence of global plant biodiversity. We coupled generalized dissimilarity models, fitted to >52 million records of >254 thousand plant species, with the species-area relationship, to estimate the effect of land-use and climate change on global biodiversity persistence. We estimated that the number of plant species committed to extinction over the long term has increased by 60% globally between 1900 and 2015 (from ~10,000 to ~16,000). This number is projected to decrease slightly by 2050 under the most optimistic scenario of land-use change and to substantially increase (to ~18,000) under the most pessimistic scenario. This means that, in the absence of climate change, scenarios of sustainable socio-economic development can potentially bring extinction risk back to pre-2000 levels. Alarmingly, under all scenarios, the additional impact from climate change might largely surpass that of land-use change. In this case, the estimated number of species committed to extinction increases by 3.7-4.5 times compared to land-use-only projections. African regions (especially central and southern) are expected to suffer some of the highest impacts into the future, while biodiversity decline in Southeast Asia (which has previously been among the highest globally) is projected to slow down. Our results suggest that environmentally sustainable land-use planning alone might not be sufficient to prevent potentially dramatic biodiversity loss, unless a stabilization of climate to pre-industrial times is observed.

Geographic distribution ranges of terrestrial mammal species in the 1970s

Here we provide geographic distribution ranges for 205 species of terrestrial non-volant mammals in the 1970s. We selected terrestrial non-volant mammals because they are among the most studied groups, have greater availability of historical distribution data for the 1970s decade, and also show the largest range contractions compared to other taxonomic groups. Species belong to 52 families and 16 orders. Range maps were extracted from scientific literature including published papers, books, and action plans. For Australian species, due to the absence of published maps, we collated occurrence data from individual data sets (maintained by museums and government agencies) and converted these into polygonal range maps. Taxonomic and geographic biases towards more studied (charismatic) species are inevitably present. Among the most abundant orders, the highest percentage representation is for Carnivora (55 species, corresponding to 21% of species in the order), Cetartiodactyla (24 species, 10% of the order), and Perissodactyla (six species, 38% of the order). In contrast, the percentage representation is low for Rodentia (66 species, 3% of species in the order), Primates (19 species, 4%), and Eulipotyphla (6 species, 1%). The proportional representation of less speciose orders is highly variable. The data set offers the opportunity to measure the recent (1970-2019) change in the distribution of terrestrial mammal species, and test ecological and biogeographical hypotheses about such change. It also allows us to identify areas where changes in species distribution were largest. No copyright or proprietary restrictions are associated with the use of this data set other than citation of this Data Paper.

Hotspots of human impact on threatened terrestrial vertebrates

Conserving threatened species requires identifying where across their range they are being impacted by threats, yet this remains unresolved across most of Earth. Here, we present a global analysis of cumulative human impacts on threatened species by using a spatial framework that jointly considers the co-occurrence of eight threatening processes and the distribution of 5,457 terrestrial vertebrates. We show that impacts to species are widespread, occurring across 84% of Earth's surface, and identify hotspots of impacted species richness and coolspots of unimpacted species richness. Almost one-quarter of assessed species are impacted across >90% of their distribution, and approximately 7% are impacted across their entire range. These results foreshadow localised extirpations and potential extinctions without conservation action. The spatial framework developed here offers a tool for defining strategies to directly mitigate the threats driving species' declines, providing essential information for future national and global conservation agendas.

Identification of MHC Ligands and Establishing MHC Class I Peptide Motifs

MHC class I peptide motifs are used on a regular basis to identify and predict MHC class I ligands and CD8⁺ T cell epitopes. This approach is above all an invaluable tool for the identification of disease-associated epitopes ranging from pathogen associated epitopes, tumor associated natural and neoepitopes to autoimmune disease associated epitopes. As a matter of fact, the vast majority of T cell epitopes discovered during the past two decades was identified by means of epitope prediction and MHC ligand identification. Here we describe the steps which are necessary to identify MHC epitopes from monoallelic and multiallelic cells and establish MHC class I peptide motifs to compose a reliable scoring matrix for epitope prediction. As an example, the ligands of monoallelic C1R cells and multiallelic peripheral blood mononuclear cell tissue will be identified and a scoring matrix for the prediction of HLA-C*01:02-presented T cell epitopes will be developed.

Abstract 5687: Integrative -omics analysis to identify drug targets for ccRCC immunotherapy

Background

Clear cell renal cell carcinoma (ccRCC) is the dominant subtype of renal cancer and frequently diagnosed at advanced disease stages. Cure of advanced and metastatic ccRCC is achieved only in rare cases with currently available therapies, consisting of tyrosine kinase and mTOR inhibitors, due to intrinsic or acquired resistance mechanisms. We developed a workflow to identify potential drug targets involved in ccRCC pathogenesis for immunotherapeutic approaches and combinatorial treatment strategies.

Methods

We analyzed frequent ccRCC-specific peptides by HLA ligandomics of 55 ccRCC tumors, paired non-tumor tissues and 158 other benign tissues from various organs. To extract cellular pathways with enrichment in ccRCC compared to the S3 region of kidney proximal tubules, which represents the region of ccRCC origin, we performed transcriptome and gene set enrichment analyses in 51 of the 55 tumor tissues of our study cohort and in a microdissected sample of the S3 region (S3-transcriptome data taken from Cheval et al., PloS One 2012). ccRCC-specific pathway genes were intersected with the tumor-exclusive peptide source genes from the HLA ligandome analysis to retrieve a list of candidate target genes. By integrating gene expression data of an independent ccRCC cohort from the Cancer Genome Atlas (TCGA KIRC, n=452), the candidates were validated on the level of individual gene expression and pathway enrichment. Integration of DNA methylation (TCGA KIRC, n=273) and somatic mutation data (TCGA KIRC, n=392) was used to refine the candidate list.

Results

Of the frequent ccRCC-specific HLA class I and II peptide source genes, 203 were involved in ccRCC-enriched pathways in both cohorts. 136 of the genes passed the selection criteria of minimal expression in tumors (> 7.2 log2 FPKM-UQ) and induction compared to paired non-tumor tissues. 89 of the candidate targets were affected by somatic point mutations in one up to eight patients, potentially giving rise to patient-specific neo-epitopes. 110 of the candidate genes displayed altered DNA methylation patterns in tumors compared to non-tumor tissues, offering the possibility of epigenetic targeting.

Conclusion

The presented workflow, integrating HLA ligandomics, transcriptomics and genomics, yields a list of genes with frequent ccRCC-specific HLA-presented peptides that could be targeted in immunotherapeutic approaches, such as ccRCC-directed peptide vaccines. Moreover, the selected genes are involved in ccRCC-enriched cellular pathways and might therefore be important factors of ccRCC pathogenesis, potentially restraining rapid resistance development when they are used as drug targets. The list represents a pre-selection of potential drug targets for novel immunotherapeutic and combinatorial therapy approaches, which need to be further evaluated.

Citation Format: Anna Reustle, Moreno Di Marco, Florian Büttner, Stefan Winter, Siarhei Kandabarau, Daniel Kowalewski, Linus Backert, Steffen Rausch, Joerg Hennenlotter, Marcus Scharpf, Falko Fend, Arnulf Stenzl, Jens Bedke, Stefan Stevanovic, Matthias Schwab, Elke Schaeffeler. Integrative -omics analysis to identify drug targets for ccRCC immunotherapy [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 5687.

Global mismatch of policy and research on drivers of biodiversity loss

The United Nations 2030 Agenda for Sustainable Development calls for urgent actions to reduce global biodiversity loss. Here, we synthesize >44,000 articles published in the past decade to assess the research focus on global drivers of loss. Relative research efforts on different drivers are not well aligned with their assessed impact, and multiple driver interactions are hardly considered. Research on drivers of biodiversity loss needs urgent realignment to match predicted severity and inform policy goals.

The extent and predictability of the biodiversity-carbon correlation

Protecting biomass carbon stocks to mitigate climate change has direct implications for biodiversity conservation. Yet, evidence that a positive association exists between carbon density and species richness is contrasting. Here, we test how this association varies (1) across spatial extents and (2) as a function of how strongly carbon and species richness depend on environmental variables. We found the correlation weakens when moving from larger extents, e.g. realms, to narrower extents, e.g. ecoregions. For ecoregions, a positive correlation emerges when both species richness and carbon density vary as functions of the same environmental variables (climate, soil, elevation). In 20% of tropical ecoregions, there are opportunities to pursue carbon conservation with direct biodiversity co-benefits, while other ecoregions require careful planning for both species and carbon to avoid potentially perverse outcomes. The broad assumption of a linear relationship between carbon and biodiversity can lead to undesired outcomes.

Global hotspots and correlates of emerging zoonotic diseases

Zoonoses originating from wildlife represent a significant threat to global health, security and economic growth, and combatting their emergence is a public health priority. However, our understanding of the mechanisms underlying their emergence remains rudimentary. Here we update a global database of emerging infectious disease (EID) events, create a novel measure of reporting effort, and fit boosted regression tree models to analyze the demographic, environmental and biological correlates of their occurrence. After accounting for reporting effort, we show that zoonotic EID risk is elevated in forested tropical regions experiencing land-use changes and where wildlife biodiversity (mammal species richness) is high. We present a new global hotspot map of spatial variation in our zoonotic EID risk index, and partial dependence plots illustrating relationships between events and predictors. Our results may help to improve surveillance and long-term EID monitoring programs, and design field experiments to test underlying mechanisms of zoonotic disease emergence.

Unveiling the Peptide Motifs of HLA-C and HLA-G from Naturally Presented Peptides and Generation of Binding Prediction Matrices

The classical HLA-C and the nonclassical HLA-E and HLA-G molecules play important roles both in the innate and adaptive immune system. Starting already during embryogenesis and continuing throughout our lives, these three Ags exert major functions in immune tolerance, defense against infections, and anticancer immune responses. Despite these important roles, identification and characterization of the peptides presented by these molecules has been lacking behind the more abundant HLA-A and HLA-B gene products. In this study, we elucidated the peptide specificities of these HLA molecules using a comprehensive analysis of naturally presented peptides. To that end, the 15 most frequently expressed HLA-C alleles as well as HLA-E*01:01 and HLA-G*01:01 were transfected into lymphoblastoid C1R cells expressing low endogenous HLA. Identification of naturally presented peptides was performed by immunoprecipitation of HLA and subsequent analysis of HLA-bound peptides by liquid chromatographic tandem mass spectrometry. Peptide motifs of HLA-C unveil anchors in position 2 or 3 with high variances between allotypes, and a less variable anchor at the C-terminal end. The previously reported small ligand repertoire of HLA-E was confirmed within our analysis, and we could show that HLA-G combines a large ligand repertoire with distinct features anchoring peptides at positions 3 and 9, supported by an auxiliary anchor in position 1 and preferred residues in positions 2 and 7. The wealth of HLA ligands resulted in prediction matrices for octa-, nona-, and decamers. Matrices were validated in terms of their binding prediction and compared with the latest NetMHC prediction algorithm NetMHCpan-3.0, which demonstrated their predictive power.

Abstract 5824: MHC class I immunogenicity and novel tumor antigen discovery in neuroblastoma

Background: Neuroblastoma is a childhood tumor characterized by relatively few somatic mutations and low MHC expression, which has thus far largely precluded it from investigation using adoptive immunotherapy.

Methods: We characterized MHC-presented antigens in 8 patient derived xenograft (PDX) tumors using LC/MS/MS immunopeptidomics. We developed a method to identify antigens derived from differentially expressed proteins by combining RNA-seq data from 153 neuroblastoma and 1641 healthy tissues, and ligandomic data from 190 healthy tissues. We also performed functional characterization on the ability HLA-A2 neuroblastoma lines to elicit a T-cell response using CEF1 antigen-specific T-cell hyrbidoma when challenged with flu virus, and performed bioinformatic analysis of the TME.

Results: From 8 PDX tumors, we identified a total of 14119 MHC-presented antigens. Interestingly, we observed antigens from all tumors which stained negative for MHC by IHC, suggesting that antigens can be identified from tumors below the detection limits of the standard staining protocols. We first searched the ligandome dataset for all possible neoantigens of 8-14aa arising from known mutations. Not having found any mutated neoantigens, we developed a method to search for tumor antigens derived neuroblastoma-specific proteins. We discovered 83 MHC ligands that derive from neuroblastoma-specific proteins, which we expect to be promising targets for adoptive T-cell therapy. We also found a number of recurrent antigens across tumor samples, suggesting that the proteins from which these antigens derive could be used in HLA-agnostic tumors vaccines.

To test whether the MHC expression in neuroblastoma is sufficient to induce a T-cell response, we characterized the ability of neuroblastoma cells to elicit a CD8 response to CEF1 antigen. We demonstrate that despite low MHC expression in all lines tested, 4/7 lines are able to induce a robust T-cell response to flu antigen greater than HLA-A2 melanoma cells (>20pg/mL IL-2 release in all responsive lines).

We also characterized immune activity in patient tumors using Granzyme A (GZMA) and Perforin (PRF1) as surrogates for T-cell activity. We observed a strong correlation between known T-cell-recruiting cytokines (particularly CXCL5/9/10) and GZMA/PRF1 (p=2.51x10-35), providing further evidence that T-cells are active in the tumor microenvironment despite low MHC expression on tumor cells.

Conclusions: We identify neuroblastoma-specific MHC class I antigens in each of the 8 PDX tumors we tested, yielding a total of 83 novel antigens. We conclude that neuroblastoma tumors harbor promising tumor-specific targets for immunotherapy despite low rates of somatic mutation and low MHC expression, and that at least a subset of these tumors are able to induce a robust response using antigen-specific T-cell hybridomas. We also describe methods of identifying tumor-specific MHC antigens in other tumors with low mutational burden.

Note: This abstract was not presented at the meeting.

Citation Format: Mark Yarmarkovich, Moreno Di Marco, Olivia Padovan, Jenna Lobby, Laurence Eisenlohr, Dimitrios Monos, Stefan Stevanovic, John M. Maris. MHC class I immunogenicity and novel tumor antigen discovery in neuroblastoma [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 5824. doi:10.1158/1538-7445.AM2017-5824