GeMInA, Genomic Metadata for Infectious Agents, a geospatial surveillance pathogen database

The Gemina system (http://gemina.igs.umaryland.edu) identifies, standardizes and integrates the outbreak metadata for the breadth of NIAID category A–C viral and bacterial pathogens, thereby providing an investigative and surveillance tool describing the Who [Host], What [Disease, Symptom], When [Date], Where [Location] and How [Pathogen, Environmental Source, Reservoir, Transmission Method] for each pathogen. The Gemina database will provide a greater understanding of the interactions of viral and bacterial pathogens with their hosts and infectious diseases through in-depth literature text-mining, integrated outbreak metadata, outbreak surveillance tools, extensive ontology development, metadata curation and representative genomic sequence identification and standards development. The Gemina web interface provides metadata selection and retrieval of a pathogen's; Infection Systems (Pathogen, Host, Disease, Transmission Method and Anatomy) and Incidents (Location and Date) along with a hosts Age and Gender. The Gemina system provides an integrated investigative and geospatial surveillance system connecting pathogens, pathogen products and disease anchored on the taxonomic ID of the pathogen and host to identify the breadth of hosts and diseases known for these pathogens, to identify the extent of outbreak locations, and to identify unique genomic regions with the DNA Signature Insignia Detection Tool

31st Annual Meeting and Associated Programs of the Society for Immunotherapy of Cancer (SITC 2016) : part two

Background The immunological escape of tumors represents one of the main ob- stacles to the treatment of malignancies. The blockade of PD-1 or CTLA-4 receptors represented a milestone in the history of immunotherapy. However, immune checkpoint inhibitors seem to be effective in specific cohorts of patients. It has been proposed that their efficacy relies on the presence of an immunological response. Thus, we hypothesized that disruption of the PD-L1/PD-1 axis would synergize with our oncolytic vaccine platform PeptiCRAd. Methods We used murine B16OVA in vivo tumor models and flow cytometry analysis to investigate the immunological background. Results First, we found that high-burden B16OVA tumors were refractory to combination immunotherapy. However, with a more aggressive schedule, tumors with a lower burden were more susceptible to the combination of PeptiCRAd and PD-L1 blockade. The therapy signifi- cantly increased the median survival of mice (Fig. 7). Interestingly, the reduced growth of contralaterally injected B16F10 cells sug- gested the presence of a long lasting immunological memory also against non-targeted antigens. Concerning the functional state of tumor infiltrating lymphocytes (TILs), we found that all the immune therapies would enhance the percentage of activated (PD-1pos TIM- 3neg) T lymphocytes and reduce the amount of exhausted (PD-1pos TIM-3pos) cells compared to placebo. As expected, we found that PeptiCRAd monotherapy could increase the number of antigen spe- cific CD8+ T cells compared to other treatments. However, only the combination with PD-L1 blockade could significantly increase the ra- tio between activated and exhausted pentamer positive cells (p= 0.0058), suggesting that by disrupting the PD-1/PD-L1 axis we could decrease the amount of dysfunctional antigen specific T cells. We ob- served that the anatomical location deeply influenced the state of CD4+ and CD8+ T lymphocytes. In fact, TIM-3 expression was in- creased by 2 fold on TILs compared to splenic and lymphoid T cells. In the CD8+ compartment, the expression of PD-1 on the surface seemed to be restricted to the tumor micro-environment, while CD4 + T cells had a high expression of PD-1 also in lymphoid organs. Interestingly, we found that the levels of PD-1 were significantly higher on CD8+ T cells than on CD4+ T cells into the tumor micro- environment (p < 0.0001). Conclusions In conclusion, we demonstrated that the efficacy of immune check- point inhibitors might be strongly enhanced by their combination with cancer vaccines. PeptiCRAd was able to increase the number of antigen-specific T cells and PD-L1 blockade prevented their exhaus- tion, resulting in long-lasting immunological memory and increased median survival

Abstract 528: Identify and prioritize candidate neoantigens from cancer exome sequencing with unmatched accuracy

Abstract Somatic, nonsynonymous genetic alterations present in cancer can lead to the formation of novel protein sequences and thus production of immunogenic “non-self” neoantigens. Some of those neoantigens will be processed, presented on MHC molecules, and induce tumor-specific T cell responses. Because neoantigens play central roles in the cancer-immunity cycle, it is critical to identify the most potent immunogenic neoantigens effectively and accurately. Combining PGDx's highly accurate cancer exome analyses (CancerXome™) with in silico neoantigen prediction, we have launched ImmunoSelect-R™ that identifies and prioritizes the most relevant mutation-derived neoantigens. To ensure detection of true somatic mutations and prevent false positive mutations from confounding neoantigen identification, ImmunoSelect utilizes CancerXome that delivers unparalleled cancer whole exome sequencing accuracy, achieving 95% sensitivity and 97% positive predictive value at 10% mutant allele frequency with 150x coverage. ImmunoSelect also provides accurate HLA typing from whole exome sequencing with &amp;gt;99.9% sensitivity and specificity. Once exome-based mutations and novel open-reading-frames are identified and HLA genotypes defined, ImmunoSelect utilizes state of art bioinformatics pipelines for prediction and prioritization of the most relevant neoantigens. When applied to a set of experimentally validated neoantigens, ImmunoSelect identified 18 out of 19 of them as being strong neoantigen candidates, suggesting a sensitivity of greater than 90%. Moreover, ImmunoSelect consistently ranked experimentally validated neoantigens within top 20% of all neoantigen candidates derived from whole exome sequencing. In summary, ImmunoSelect is able to identify and prioritize candidate neoantigens from cancer exome sequencing results effectively and accurately, enabling personalized cancer vaccine development, adoptive T-cell transfer, and prediction of response to checkpoint inhibitors Citation Format: James White, Sam Angiuoli, Mark Sausen, Sian Jones, Lisa Kann, Manish Shukla, Maria Sevdali, Victor Velculescu, Luis Diaz, Theresa Zhang. Identify and prioritize candidate neoantigens from cancer exome sequencing with unmatched accuracy. [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr 528.</jats:p

Abstract A039: Accurate identification and prioritization of candidate neoantigens from cancer exome sequencing

Abstract Somatic, nonsynonymous genetic alterations present in cancer can lead to the formation of novel protein sequences and thus production of immunogenic “non-self” neoantigens. Those neoantigens with sufficient expression will be processed and presented on MHC molecules, subsequently inducing a tumor-specific T cell response. Emerging data from clinical studies suggest that neoantigen load and composition is associated with the efficacy of some immunotherapies. As neoantigens play central a role in the cancer-immunity cycle, it is critical to identify the most potent immunogenic neoantigens effectively and accurately. Here we have leveraged highly accurate cancer whole exome (WES) analyses from FFPE tumor tissue with a state-of-the-art analysis protocol to identify and prioritize candidate neoantigens most likely to promote an immune response. ImmunoSelect-R utilizes somatic variants from WES to ensure detection of true somatic peptides and minimize false positives, and provides accurate HLA typing from whole exome sequencing data with &amp;gt;99.9% sensitivity and specificity. When applied to a set of experimentally validated neoantigens, ImmunoSelect correctly classified 18 out of 19 as strong neoantigen candidates, suggesting a sensitivity of greater than 90%. Moreover, in a small set of 10 patients, ImmunoSelect consistently ranked experimentally validated neoantigens within top 20% of all neoantigen candidates derived from whole exome sequencing. In summary, ImmunoSelect is able to identify and prioritize candidate neoantigens from cancer exome sequencing results effectively and accurately, enabling personalized cancer vaccine development, adoptive T-cell transfer, and prediction of response to checkpoint inhibitors Citation Format: James White, John Simmons, Sam Angiuoli, Mark Sausen, Sian Jones, Lisa Kann, Manish Shukla, Maria Sevdali, Victor Velculescu, Luis Diaz, Theresa Zhang. Accurate identification and prioritization of candidate neoantigens from cancer exome sequencing [abstract]. In: Proceedings of the Second CRI-CIMT-EATI-AACR International Cancer Immunotherapy Conference: Translating Science into Survival; 2016 Sept 25-28; New York, NY. Philadelphia (PA): AACR; Cancer Immunol Res 2016;4(11 Suppl):Abstract nr A039.</jats:p

Abstract 604: Accurate identification and prioritization of candidate neoantigens from integrated cancer exome and transcriptome sequencing of FFPE samples

Abstract Precise identification and characterization of candidate neoantigens is important for the development of effective cancer vaccines, adoptive T-cell transfer, and prediction of response to checkpoint inhibitors. The candidate tumor neoantigens are actionable only when expressed, however, current prediction methods lack the capacity to evaluate neoantigen expression. Sequencing both DNA and RNA from a patient’s tumor tissue enables identification of mutations and evaluation of their expression leading to accurate identification of putative neoantigens. The purpose of this study was to develop and validate a methodology for co-extraction and sequencing of DNA and RNA from formalin-fixed paraffin-embedded (FFPE) samples to enable a robust neoantigen prediction protocol that integrates whole exome and transcriptome data to identify and prioritize tumor neoantigens for application in immuno-oncology research and clinical trials. In order to prepare high-quality sequencing libraries from FFPE specimens, the tissue was macrodissected to enrich for tumor-specific material, and improve the overall accuracy of next-generation sequencing for detection of somatic alterations. Total DNA and RNA was co-extracted and purified. The DNA was used to prepare whole exome sequencing (WES) libraries, while the co-extracted RNA was ribosome-depleted, and reverse-transcribed to prepare RNA sequencing (RNAseq) libraries. The WES and RNAseq data was then analyzed using a multi-algorithm HLA typing and neoantigen prediction protocol (ImmunoSelect-RTM). ImmunoSelect-R evaluates somatic genomic alterations identified from WES of tumor and matched normal tissue to ensure appropriate prediction of candidate neoantigens. The process of neoantigen prediction was then refined by integration of patient tumor-matched RNAseq data, which allowed for removal of non-expressed putative neoantigens. To further validate the approach, we applied the methodology to a set of experimentally validated neoantigens. In this setting, ImmunoSelect-R correctly classified 18 out of 19 as strong neoantigen candidates, suggesting a sensitivity of greater than 90%. Moreover, in a set of 10 patients, ImmunoSelect-R consistently ranked experimentally validated neoantigens within the top 20% of all neoantigen candidates derived from whole exome sequencing. In summary, our combined tissue processing, macrodissection, co-extraction, and neoantigen prediction methodology is able to identify and prioritize candidate neoantigens. Our approach is unique in combining high-fidelity sequencing (WES) and expression (RNAseq) data to accurately inform the selection of actionable tumor neoantigens for immuno-oncology applications. Citation Format: Marián Novak, Sam Angiuoli, Luis A. Diaz, Andrew Georgiadis, Sian Jones, Peter R. Loverso, Sonya Parpart-Li, Maria Sevdali, Victor E. Velculescu, Ellen L. Verner, James White, Theresa Zhang, Mark Sausen. Accurate identification and prioritization of candidate neoantigens from integrated cancer exome and transcriptome sequencing of FFPE samples [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 604. doi:10.1158/1538-7445.AM2017-604</jats:p

Noninvasive Detection of Microsatellite Instability and High Tumor Mutation Burden in Cancer Patients Treated with PD-1 Blockade

Abstract Purpose: Microsatellite instability (MSI) and high tumor mutation burden (TMB-High) are promising pan-tumor biomarkers used to select patients for treatment with immune checkpoint blockade; however, real-time sequencing of unresectable or metastatic solid tumors is often challenging. We report a noninvasive approach for detection of MSI and TMB-High in the circulation of patients. Experimental Design: We developed an approach that utilized a hybrid-capture–based 98-kb pan-cancer gene panel, including targeted microsatellite regions. A multifactorial error correction method and a novel peak-finding algorithm were established to identify rare MSI frameshift alleles in cell-free DNA (cfDNA). Results: Through analysis of cfDNA derived from a combination of healthy donors and patients with metastatic cancer, the error correction and peak-finding approaches produced a specificity of &amp;gt;99% (n = 163) and sensitivities of 78% (n = 23) and 67% (n = 15), respectively, for MSI and TMB-High. For patients treated with PD-1 blockade, we demonstrated that MSI and TMB-High in pretreatment plasma predicted progression-free survival (hazard ratios: 0.21 and 0.23, P = 0.001 and 0.003, respectively). In addition, we analyzed cfDNA from longitudinally collected plasma samples obtained during therapy to identify patients who achieved durable response to PD-1 blockade. Conclusions: These analyses demonstrate the feasibility of noninvasive pan-cancer screening and monitoring of patients who exhibit MSI or TMB-High and have a high likelihood of responding to immune checkpoint blockade. See related commentary by Wang and Ajani, p. 6887 </jats:sec

Meeting report: the fourth Genomics Standards Consortium Workshop

This meeting report summarizes the proceedings of the “eGenomics: Cataloguing our Complete Genome Collection IV” workshop held June 6–8, 2007, at the National Institute for Environmental eScience (NIEeS), Cambridge, United Kingdom. This fourth workshop of the Genomic Standards Consortium (GSC) was a mix of short presentations, strategy discussions, and technical sessions. Speakers provided progress reports on the development of the “Minimum Information about a Genome Sequence” (MIGS) specification and the closely integrated “Minimum Information about a Metagenome Sequence” (MIMS) specification. The key outcome of the workshop was consensus on the next version of the MIGS/MIMS specification (v1.2). This drove further definition and restructuring of the MIGS/MIMS XML schema (syntax). With respect to semantics, a term vetting group was established to ensure that terms are properly defined and submitted to the appropriate ontology projects. Perhaps the single most important outcome of the workshop was a proposal to move beyond the concept of “minimum” to create a far richer XML schema that would define a “Genomic Contextual Data Markup Language” (GCDML) suitable for wider semantic integration across databases. GCDML will contain not only curated information (e.g., compliant with MIGS/MIMS), but also be extended to include a variety of data processing and calculations. Further information about the Genomic Standards Consortium and its range of activities can be found at http://gensc.or