ALBERT

Description: Question: How many vegetation plot observations (relevés) are available in electronic databases, how are they geographically distributed, what are their properties and how might they be discovered and located for research and application? Location: Global. Methods: We compiled the Global Index of Vegetation-Plot Databases (GIVD; http://www.givd.info ), an Internet resource aimed at registering metadata on existing vegetation databases. For inclusion, databases need to (i) contain temporally and spatially explicit species co-occurrence data and (ii) be accessible to the scientific public. This paper summarizes structure and data quality of databases registered in GIVD as of 30 December 2010. Results: On the given date, 132 databases containing more than 2.4 million non-overlapping plots had been registered in GIVD. The majority of these data were in European databases (83 databases, 1.6 million plots), whereas other continents were represented by substantially less (North America 15, Asia 13, Africa nine, South America seven, Australasia two, multi-continental three). The oldest plot observation was 1864, but most plots were recorded after 1970. Most plots reported vegetation on areas of 1 to 1000 m 2 ; some also stored time-series and nested-plot data. Apart from geographic reference (required for inclusion), most frequent information was on altitude (71%), slope aspect and inclination (58%) and land use (38%), but rarely soil properties (〈7%). Conclusions: The vegetation plot data in GIVD constitute a major resource for biodiversity research, both through the large number of species occurrence records and storage of species co-occurrence information at a small scale, combined with structural and plot-based environmental data. We identify shortcomings in available data that need to be addressed through sampling under-represented geographic regions, providing better incentives for data collection and sharing, developing user-friendly database exchange standards, as well as tools to analyse and remove confounding effects of sampling biases. The increased availability of data sets conferred by registration in GIVD offers significant opportunities for large-scale studies in community ecology, macroecology and global change research.

Description: Introduction: Peptide-basedcancer vaccines targeting tumor-associated antigens comprised of synthetic peptides have shown promising clinical results and have progressed to Phase III clinical testing in several tumor entities, including colorectal carcinoma (CRC). As of yet, these vaccines have typically been limited to HLA-A*02 positive patients, which means that more than half of the patient pool will not be eligible for those treatment strategies. The development of novel strategies for vaccine design, which are applicable to a larger fraction of potential patients, is therefore required. CRC seems to be particularly suitable for antigen-specific immunotherapy as it is among those cancers with highest rates of genetic mutations leading to alterations in protein metabolism. In this study, we aimed to identify HLA class I and II tumor-associated antigens from CRC covering the most frequent HLA-allotypes, in order to develop a peptide warehouse containing HLA-specific peptide panels that can be compiled in a patient-individualized manner, according to the respective patient's HLA-typing. Methods: The HLA presented immunopeptidome of 30 primary CRC samples and matched autologous non-malignant colon tissue was analyzed after HLA-immunoprecipitation by uHPLC tandem mass spectrometry. Identified source proteins and peptides were cross-evaluated with an in-house database of ligandome data derived from different benign tissues to preclude off-tumor presentation of HLA-ligands in order to to prevent any possible induction of autoimmunity by antigen-specific T cells against these ligands. Furthermore, we evaluated pre-existing antigen-specific T cell responses against these novel CRC-associated peptides in a cohort of 25 CRC patients. Results: About 17,000 MHC class I presented peptides could be identified on CRC and were cross-evaluated with our in-house database containing 39,000 MHC class I peptides presented on non-malignant tissue. The ligands identified were derived from 7,500 unique tumor-associated proteins and from 11,500 tumor-exclusive source proteins, respectively. Moreover, about 2,000 different MHC class II presented peptides from more than 1,600 source proteins were identified on CRC tissue. Interestingly, MHC class II peptides could contain shorter amino-acid sequences which - after further proteasomal degradation - might also bind to MHC class I molecules. For clinical applicability, we prioritized the identified ligands according to their frequencies of presentation and detectability on CRC. For representation in the HLA-specific peptide sets, a cutoff expression on at least 25% of allotype-matched tumors was required. This guided the assembly of a peptide vaccine warehouse consisting of 40 highly specific CRC-associated HLA ligands. Therefore, this selected set of HLA-specific peptides allows vaccination against CRC for about 95% of Caucasian patients. So far, we detected specific T cell reactivity against two peptides (detection of 10-fold and 17-fold increase of IFNγ-producing T cells representing spots as compared to background in enzyme linked immunospot assays - ELISPOT) in CRC patients. Conclusions: We here provide for the first time a comprehensive evaluation of HLA-ligandomes in CRC across the most frequent Caucasian HLA-alleles. We developed a HLA-allotype specific warehouse of newly identified CRC associated HLA-ligands, which can be individually assembled according to patient specific HLA-alleles. This approach expands the applicability of peptide-based cancer vaccines to literally every CRC patient. Disclosures No relevant conflicts of interest to declare.

Description: Background: Immunotherapy with checkpoint-inhibitors has shown spectacular results in the treatment of certain cancer types including microsatellite instable colorectal cancer (CRC). Applicability is believed to be dependent on the number of potential neo-epitopes derived from genetic mutations that are presented on cancer cells. In case of most microsatellite-stable CRC however, clinical responses to immune checkpoint blockade are so far disappointing. Therefore, we analyzed the non-mutant HLA immunopeptidome of CRC in order to provide an extensive dataset for the development of immunotherapeutic strategies in this very common malignancy. Methods: Tissue specimens from 35 primary CRC and corresponding non-malignant colon were analyzed after HLA immunoprecipitation by uHPLC tandem mass spectrometry. Maximally attainable quantities of source proteins (MAQS) expectable in HLA-ligandomes were estimated by regression analyses. Identified peptides and source proteins were annotated for their pathway association using the Kyoto Encyclopedia of Genes and Genomes (KEGG) and the protein analysis through evolutionary relationships (PANTHER). HLA-ligands and source proteins were further analyzed semi-quantitatively assessing significant modulations on CRC tissue compared to adjacent benign colon, with particular focus on specific alterations observed exclusively in CRC tissue. Immunogenicity of the identified HLA-ligands (prioritized ligands for the 8 most frequent HLA-alleles HLA A*01, A*02, A*03, A*24, B*07, B*08, B*44, C*07) was evaluated in peripheral blood mononuclear cells (PBMC) from 50 additional CRC patients and 120 healthy controls (15 each for the 8 most frequent HLA-types) using ELISpot and flow cytometry. Results: For MHC class I, peptides from 7684 source proteins (81% MAQS) were identified on CRC, as well as peptides from 6312 source proteins on (non-malignant) colon tissue (79% MAQS). For MHC class II, peptides from 1602 source proteins (63% MAQS) were identified, as well as peptides from 3835 source proteins on non-malignant colon tissue (75% MAQS). HLA-ligands and their respective source proteins were compared on tissue level (CRC vs. adjacent benign tissue), as well as against a database of 100 non-malignant human tissues of different origin in order to identify ligands and source proteins exclusively presented on CRC tissue. Implementing KEGG and PANTHER pathway analysis, overrepresented source proteins within MHC class I and II restricted ligands could be assigned to classical tumorigenesis pathways like WNT- and integrin signaling, as well as to the p53 signaling pathway. HLA ligands were further semi-quantitatively analyzed comparing tumor and autologous adjacent colon tissue leading to the exclusive identification of 1364 up-modulated and 1070 down-modulated source proteins in CRC tissue. Notably, 3 source proteins (represented by 10 HLA-ligands) showing significant up-modulation and frequent tumor-exclusive detection of derived HLA-ligands (in ≥3 CRC) were identified (LAMC-2, SLC52A2, SULF-1). For MHC class II, a single up-modulated source protein with exclusive detection in ≥2 CRC tissues (IL6R) was identified. Further analyses of HLA class I restricted peptides (n=359) derived from simultaneously up- and down-modulated source proteins revealed that the respective modulation was mainly a peptide sequence specific feature (31/359 (8.6%) peptides with up- and down-modulation). Preexisting T cell responses were observed against one tumor-exclusive up-modulated peptide (SULF-1) in CRC patients and 3 HLA restricted peptides established as immunogenic epitopes in CRC patients (TACC2, TNS4, IGHG2), as well as 2 additional HLA-restricted peptides confirmed as epitopes in healthy controls (GLA, ESRRA). Conclusions: We provide the first comprehensive analysis of the HLA immunopeptidome in a solid cancer (CRC). We observed that the presented ligandome can reflect tumor-specific alterations in protein metabolism. Moreover, tumor-exclusive up- and down-modulation of HLA-peptides was mainly sequence-specific, suggesting a differential posttranslational regulation of HLA-restricted peptides in CRC. The described approach for identification of relevant antigens might also enable patient-specific immunotherapeutic approaches in CRC patients. Disclosures Kowalewski: Immatics Biotechnologies GmbH: Employment. Bernhardt:DECODON: Employment.