Current status of use of high throughput nucleotide sequencing in rheumatology.

OBJECTIVE: Here, we assess the usage of high throughput sequencing (HTS) in rheumatic research and the availability of public HTS data of rheumatic samples. METHODS: We performed a semiautomated literature review on PubMed, consisting of an R-script and manual curation as well as a manual search on the Sequence Read Archive for public available HTS data. RESULTS: Of the 699 identified articles, rheumatoid arthritis (n=182 publications, 26%), systemic lupus erythematous (n=161, 23%) and osteoarthritis (n=152, 22%) are among the rheumatic diseases with the most reported use of HTS assays. The most represented assay is RNA-Seq (n=457, 65%) for the identification of biomarkers in blood or synovial tissue. We also find, that the quality of accompanying clinical characterisation of the sequenced patients differs dramatically and we propose a minimal set of clinical data necessary to accompany rheumatological-relevant HTS data. CONCLUSION: HTS allows the analysis of a broad spectrum of molecular features in many samples at the same time. It offers enormous potential in novel personalised diagnosis and treatment strategies for patients with rheumatic diseases. Being established in cancer research and in the field of Mendelian diseases, rheumatic diseases are about to become the third disease domain for HTS, especially the RNA-Seq assay. However, we need to start a discussion about reporting of clinical characterisation accompany rheumatological-relevant HTS data to make clinical meaningful use of this data.

Correction to: Angiosarcoma patients treated with immune checkpoint inhibitors: a case series of seven patients from a single institution.

Following publication of the original article [1], the authors have reported that the following sentence "While of the same IgG1 class as ipilimumab, preclinical data suggests this molecule may have enhanced activity against T regulatory cells".

TCR Fingerprinting and Off-Target Peptide Identification.

Adoptive T cell therapy using patient T cells redirected to recognize tumor-specific antigens by expressing genetically engineered high-affinity T-cell receptors (TCRs) has therapeutic potential for melanoma and other solid tumors. Clinical trials implementing genetically modified TCRs in melanoma patients have raised concerns regarding off-target toxicities resulting in lethal destruction of healthy tissue, highlighting the urgency of assessing which off-target peptides can be recognized by a TCR. As a model system we used the clinically efficacious NY-ESO-1-specific TCR C259, which recognizes the peptide epitope SLLMWITQC presented by HLA-A*02:01. We investigated which amino acids at each position enable a TCR interaction by sequentially replacing every amino acid position outside of anchor positions 2 and 9 with all 19 possible alternative amino acids, resulting in 134 peptides (133 altered peptides plus epitope peptide). Each peptide was individually evaluated using three different in vitro assays: binding of the NY-ESOc259 TCR to the peptide, peptide-dependent activation of TCR-expressing cells, and killing of peptide-presenting target cells. To represent the TCR recognition kernel, we defined Position Weight Matrices (PWMs) for each assay by assigning normalized measurements to each of the 20 amino acids in each position. To predict potential off-target peptides, we applied a novel algorithm projecting the PWM-defined kernel into the human proteome, scoring NY-ESOc259 TCR recognition of 336,921 predicted human HLA-A*02:01 binding 9-mer peptides. Of the 12 peptides with high predicted score, we confirmed 7 (including NY-ESO-1 antigen SLLMWITQC) strongly activate human primary NY-ESOc259-expressing T cells. These off-target peptides include peptides with up to 7 amino acid changes (of 9 possible), which could not be predicted using the recognition motif as determined by alanine scans. Thus, this replacement scan assay determines the "TCR fingerprint" and, when coupled with the algorithm applied to the database of human 9-mer peptides binding to HLA-A*02:01, enables the identification of potential off-target antigens and the tissues where they are expressed. This platform enables both screening of multiple TCRs to identify the best candidate for clinical development and identification of TCR-specific cross-reactive peptide recognition and constitutes an improved methodology for the identification of potential off-target peptides presented on MHC class I molecules.

Mutation-Derived Neoantigens for Cancer Immunotherapy.

Mutation-derived neoantigens distinguish tumor from normal cells. T cells can sense the HLA-presented mutations, recognize tumor cells as non-self and destroy them. Therapeutically, immunotherapy antibodies can increase the virulence of the immune system by increasing T-cell cytotoxicity targeted toward neoantigens. Neoantigen vaccines act through antigen-presenting cells, such as dendritic cells, to activate patient-endogenous T cells that recognize vaccine-encoded mutations. Infusion of mutation-targeting T cells by adoptive cell therapy (ACT) directly increases the number and frequency of cytotoxic T cells recognizing and killing tumor cells. At the same time, publicly-funded consortia have profiled tumor genomes across many indications, identifying mutations in each tumor. For example, we find basal and HER2 positive tumors contain more mutated proteins and more TP53 mutations than luminal A/B breast tumors. HPV negative tumors have more mutated proteins than HPV positive head and neck tumors and in agreement with the hypothesis that HPV activity interferes with p53 activity, only 14% of the HPV positive mutations have TP53 mutations vs. 86% of the HPV negative tumors. Lung adenocarcinomas in smokers have over four times more mutated proteins relative to those in never smokers (median 248 vs. 61, respectively). With an eye toward immunotherapy applications, we review the spectrum of mutations in multiple indications, show variations in indication sub-types, and examine intra- and inter-indication prevalence of re-occurring mutation neoantigens that could be used for warehouse vaccines and ACT.

Angiosarcoma patients treated with immune checkpoint inhibitors: a case series of seven patients from a single institution.

BACKGROUND: Angiosarcoma is an uncommon endothelial malignancy and a highly aggressive soft tissue sarcoma. Due to its infiltrative nature, successful management of localized angiosarcoma is often challenging. Systemic chemotherapy is used in the metastatic setting and occasionally in patients with high-risk localized disease in neoadjuvant or adjuvant settings. However, responses tend to be short-lived and most patients succumb to metastatic disease. Novel therapies are needed for patients with angiosarcomas. METHODS: We performed a retrospective analysis of patients with locally advanced or metastatic angiosarcoma, who were treated with checkpoint inhibitors at our institution. We collected their clinical information and outcome measurements. In one patient with achieved complete response, we analyzed circulating and infiltrating T cells within peripheral blood and tumor tissue. RESULTS: We have treated seven angiosarcoma (AS) patients with checkpoint inhibitors either in the context of clinical trials or off label [Pembrolizumab + Axitinib (NCT02636725; n = 1), AGEN1884, a CTLA-4 inhibitor (NCT02694822; n = 2), Pembrolizumab (n = 4)]. Five patients had cutaneous angiosarcoma, one primary breast angiosarcoma and one radiation-associated breast angiosarcoma. At 12 weeks, 5/7 patients (71%) had partial response of their lesions either on imaging and/or clinical exam and two (29%) had progressive disease. 6/7 patients are alive to date and, thus far, 3/7 patients (43%) have progressed (median 3.4 months)- one achieved partial response after pembrolizumab was switched to ongoing Nivolumab/Ipilimumab, one died of progressive disease at 31 weeks (primary breast angiosarcoma) and one was placed on pazopanib. One patient had a complete response (CR) following extended treatment with monotherapy AGEN1884. No patient experienced any ≥ grade 2 toxicities. CONCLUSIONS: This case series underscores the value of targeted immunotherapy in treating angiosarcoma. It also identifies genetic heterogeneity of cutaneous angiosarcomas and discusses specific genetic findings that may explain reported benefits from immunotherapy.

Bioinformatic methods for cancer neoantigen prediction.

Tumor cells accumulate aberrations not present in normal cells, leading to presentation of neoantigens on MHC molecules on their surface. These non-self neoantigens distinguish tumor cells from normal cells to the immune system and are thus targets for cancer immunotherapy. The rapid development of molecular profiling platforms, such as next-generation sequencing, has enabled the generation of large datasets characterizing tumor cells. The simultaneous development of algorithms has enabled rapid and accurate processing of these data. Bioinformatic software tools encoding the algorithms can be strung together in a workflow to identify neoantigens. Here, with a focus on high-throughput sequencing, we review state-of-the art bioinformatic tools along with the steps and challenges involved in neoantigen identification and recognition.

Publisher Correction: Actively personalized vaccination trial for newly diagnosed glioblastoma.

The additional author support information was erroneously omitted from the Supplementary Information. This has been corrected online.

Actively personalized vaccination trial for newly diagnosed glioblastoma.

Patients with glioblastoma currently do not sufficiently benefit from recent breakthroughs in cancer treatment that use checkpoint inhibitors1,2. For treatments using checkpoint inhibitors to be successful, a high mutational load and responses to neoepitopes are thought to be essential3. There is limited intratumoural infiltration of immune cells4 in glioblastoma and these tumours contain only 30-50 non-synonymous mutations5. Exploitation of the full repertoire of tumour antigens-that is, both unmutated antigens and neoepitopes-may offer more effective immunotherapies, especially for tumours with a low mutational load. Here, in the phase I trial GAPVAC-101 of the Glioma Actively Personalized Vaccine Consortium (GAPVAC), we integrated highly individualized vaccinations with both types of tumour antigens into standard care to optimally exploit the limited target space for patients with newly diagnosed glioblastoma. Fifteen patients with glioblastomas positive for human leukocyte antigen (HLA)-A*02:01 or HLA-A*24:02 were treated with a vaccine (APVAC1) derived from a premanufactured library of unmutated antigens followed by treatment with APVAC2, which preferentially targeted neoepitopes. Personalization was based on mutations and analyses of the transcriptomes and immunopeptidomes of the individual tumours. The GAPVAC approach was feasible and vaccines that had poly-ICLC (polyriboinosinic-polyribocytidylic acid-poly-L-lysine carboxymethylcellulose) and granulocyte-macrophage colony-stimulating factor as adjuvants displayed favourable safety and strong immunogenicity. Unmutated APVAC1 antigens elicited sustained responses of central memory CD8+ T cells. APVAC2 induced predominantly CD4+ T cell responses of T helper 1 type against predicted neoepitopes.

Responsiveness to anti-PD-1 and anti-CTLA-4 immune checkpoint blockade in SB28 and GL261 mouse glioma models.

Immune checkpoint blockade (ICB) is currently evaluated in patients with glioblastoma (GBM), based on encouraging clinical data in other cancers, and results from studies with the methylcholanthrene-induced GL261 mouse glioma. In this paper, we describe a novel model faithfully recapitulating some key human GBM characteristics, including low mutational load, a factor reported as a prognostic indicator of ICB response. Consistent with this observation, SB28 is completely resistant to ICB, contrasting with treatment sensitivity of the more highly mutated GL261. Moreover, SB28 shows features of a poorly immunogenic tumor, with low MHC-I expression and modest CD8+ T-cell infiltration, suggesting that it may present similar challenges for immunotherapy as human GBM. Based on these key features for immune reactivity, SB28 may represent a treatment-resistant malignancy likely to mirror responses of many human tumors. We therefore propose that SB28 is a particularly suitable model for optimization of GBM immunotherapy.

In Silico Typing of Classical and Non-classical HLA Alleles from Standard RNA-Seq Reads.

Next-Generation Sequencing (NGS) enables the rapid generation of billions of short nucleic acid sequence fragments (i.e., "sequencing reads"). Especially, the adoption of gene expression profiling using whole transcriptome sequencing (i.e., "RNA-Seq") has been rapid. Here, we describe an in silico method, seq2HLA, that takes standard RNA-Seq reads as input and determines a sample's (classical and non-classical) HLA class I and class II types as well as HLA expression. We demonstrate the application of seq2HLA using publicly available RNA-Seq data from the Burkitt's lymphoma cell line DAUDI and the choriocarcinoma cell line JEG-3.

HLA and proteasome expression body map.

BACKGROUND: The presentation of HLA peptide complexes to T cells is a highly regulated and tissue specific process involving multiple transcriptionally controlled cellular components. The extensive polymorphism of HLA genes and the complex composition of the proteasome make it difficult to map their expression profiles across tissues. METHODS: Here we applied a tailored gene quantification pipeline to 4323 publicly available RNA-Seq datasets representing 55 normal tissues and cell types to examine expression profiles of (classical and non-classical) HLA class I, class II and proteasomal genes. RESULTS: We generated the first comprehensive expression atlas of antigen presenting-related genes across 56 normal tissues and cell types, including immune cells, pancreatic islets, platelets and hematopoietic stem cells. We found a surprisingly heterogeneous HLA expression pattern with up to 100-fold difference in intra-tissue median HLA abundances. Cells of the immune system and lymphatic organs expressed the highest levels of classical HLA class I (HLA-A,-B,-C), class II (HLA-DQA1,-DQB1,-DPA1,-DPB1,-DRA,-DRB1) and non-classical HLA class I (HLA-E,-F) molecules, whereas retina, brain, muscle, megakaryocytes and erythroblasts showed the lowest abundance. In contrast, we identified a distinct and highly tissue-restricted expression pattern of the non-classical class I gene HLA-G in placenta, pancreatic islets, pituitary gland and testis. While the constitutive proteasome showed relatively constant expression across all tissues, we found the immunoproteasome to be enriched in lymphatic organs and almost absent in immune privileged tissues. CONCLUSIONS: Here, we not only provide a reference catalog of tissue and cell type specific HLA expression, but also highlight extremely variable expression of the basic components of antigen processing and presentation in different cell types. Our findings indicate that low expression of classical HLA class I molecules together with lack of immunoproteasome components as well as upregulation of HLA-G may be of key relevance to maintain tolerance in immune privileged tissues.

The SysteMHC Atlas project.

Mass spectrometry (MS)-based immunopeptidomics investigates the repertoire of peptides presented at the cell surface by major histocompatibility complex (MHC) molecules. The broad clinical relevance of MHC-associated peptides, e.g. in precision medicine, provides a strong rationale for the large-scale generation of immunopeptidomic datasets and recent developments in MS-based peptide analysis technologies now support the generation of the required data. Importantly, the availability of diverse immunopeptidomic datasets has resulted in an increasing need to standardize, store and exchange this type of data to enable better collaborations among researchers, to advance the field more efficiently and to establish quality measures required for the meaningful comparison of datasets. Here we present the SysteMHC Atlas (https://systemhcatlas.org), a public database that aims at collecting, organizing, sharing, visualizing and exploring immunopeptidomic data generated by MS. The Atlas includes raw mass spectrometer output files collected from several laboratories around the globe, a catalog of context-specific datasets of MHC class I and class II peptides, standardized MHC allele-specific peptide spectral libraries consisting of consensus spectra calculated from repeat measurements of the same peptide sequence, and links to other proteomics and immunology databases. The SysteMHC Atlas project was created and will be further expanded using a uniform and open computational pipeline that controls the quality of peptide identifications and peptide annotations. Thus, the SysteMHC Atlas disseminates quality controlled immunopeptidomic information to the public domain and serves as a community resource toward the generation of a high-quality comprehensive map of the human immunopeptidome and the support of consistent measurement of immunopeptidomic sample cohorts.

Establishing a library of resources to help people understand key concepts in assessing treatment claims-The "Critical thinking and Appraisal Resource Library" (CARL).

BACKGROUND: People are frequently confronted with untrustworthy claims about the effects of treatments. Uncritical acceptance of these claims can lead to poor, and sometimes dangerous, treatment decisions, and wasted time and money. Resources to help people learn to think critically about treatment claims are scarce, and they are widely scattered. Furthermore, very few learning-resources have been assessed to see if they improve knowledge and behavior. OBJECTIVES: Our objectives were to develop the Critical thinking and Appraisal Resource Library (CARL). This library was to be in the form of a database containing learning resources for those who are responsible for encouraging critical thinking about treatment claims, and was to be made available online. We wished to include resources for groups we identified as 'intermediaries' of knowledge, i.e. teachers of schoolchildren, undergraduates and graduates, for example those teaching evidence-based medicine, or those communicating treatment claims to the public. In selecting resources, we wished to draw particular attention to those resources that had been formally evaluated, for example, by the creators of the resource or independent research groups. METHODS: CARL was populated with learning-resources identified from a variety of sources-two previously developed but unmaintained inventories; systematic reviews of learning-interventions; online and database searches; and recommendations by members of the project group and its advisors. The learning-resources in CARL were organised by 'Key Concepts' needed to judge the trustworthiness of treatment claims, and were made available online by the James Lind Initiative in Testing Treatments interactive (TTi) English (www.testingtreatments.org/category/learning-resources).TTi English also incorporated the database of Key Concepts and the Claim Evaluation Tools developed through the Informed Healthcare Choices (IHC) project (informedhealthchoices.org). RESULTS: We have created a database of resources called CARL, which currently contains over 500 open-access learning-resources in a variety of formats: text, audio, video, webpages, cartoons, and lesson materials. These are aimed primarily at 'Intermediaries', that is, 'teachers', 'communicators', 'advisors', 'researchers', as well as for independent 'learners'. The resources included in CARL are currently accessible at www.testingtreatments.org/category/learning-resources. CONCLUSIONS: We hope that ready access to CARL will help to promote the critical thinking about treatment claims, needed to help improve healthcare choices.

PDE2A2 regulates mitochondria morphology and apoptotic cell death via local modulation of cAMP/PKA signalling.

cAMP/PKA signalling is compartmentalised with tight spatial and temporal control of signal propagation underpinning specificity of response. The cAMP-degrading enzymes, phosphodiesterases (PDEs), localise to specific subcellular domains within which they control local cAMP levels and are key regulators of signal compartmentalisation. Several components of the cAMP/PKA cascade are located to different mitochondrial sub-compartments, suggesting the presence of multiple cAMP/PKA signalling domains within the organelle. The function and regulation of these domains remain largely unknown. Here, we describe a novel cAMP/PKA signalling domain localised at mitochondrial membranes and regulated by PDE2A2. Using pharmacological and genetic approaches combined with real-time FRET imaging and high resolution microscopy, we demonstrate that in rat cardiac myocytes and other cell types mitochondrial PDE2A2 regulates local cAMP levels and PKA-dependent phosphorylation of Drp1. We further demonstrate that inhibition of PDE2A, by enhancing the hormone-dependent cAMP response locally, affects mitochondria dynamics and protects from apoptotic cell death.

TCLP: an online cancer cell line catalogue integrating HLA type, predicted neo-epitopes, virus and gene expression.

Human cancer cell lines are an important resource for research and drug development. However, the available annotations of cell lines are sparse, incomplete, and distributed in multiple repositories. Re-analyzing publicly available raw RNA-Seq data, we determined the human leukocyte antigen (HLA) type and abundance, identified expressed viruses and calculated gene expression of 1,082 cancer cell lines. Using the determined HLA types, public databases of cell line mutations, and existing HLA binding prediction algorithms, we predicted antigenic mutations in each cell line. We integrated the results into a comprehensive knowledgebase. Using the Django web framework, we provide an interactive user interface with advanced search capabilities to find and explore cell lines and an application programming interface to extract cell line information. The portal is available at http://celllines.tron-mainz.de.

In Silico HLA Typing Using Standard RNA-Seq Sequence Reads.

Next-generation sequencing (NGS) enables high-throughput transcriptome profiling using the RNA-Seq assay, resulting in billions of short sequence reads. Worldwide adoption has been rapid: many laboratories worldwide generate transcriptome sequence reads daily. Here, we describe methods for obtaining a sample's human leukocyte antigen (HLA) class I and II types and HLA expression using standard NGS RNA-Seq sequence reads. We demonstrate the application using our algorithm, seq2HLA, and a publicly available RNA-Seq dataset from the Burkitt lymphoma cell line Raji.

Mutant MHC class II epitopes drive therapeutic immune responses to cancer.

Tumour-specific mutations are ideal targets for cancer immunotherapy as they lack expression in healthy tissues and can potentially be recognized as neo-antigens by the mature T-cell repertoire. Their systematic targeting by vaccine approaches, however, has been hampered by the fact that every patient's tumour possesses a unique set of mutations ('the mutanome') that must first be identified. Recently, we proposed a personalized immunotherapy approach to target the full spectrum of a patient's individual tumour-specific mutations. Here we show in three independent murine tumour models that a considerable fraction of non-synonymous cancer mutations is immunogenic and that, unexpectedly, the majority of the immunogenic mutanome is recognized by CD4(+) T cells. Vaccination with such CD4(+) immunogenic mutations confers strong antitumour activity. Encouraged by these findings, we established a process by which mutations identified by exome sequencing could be selected as vaccine targets solely through bioinformatic prioritization on the basis of their expression levels and major histocompatibility complex (MHC) class II-binding capacity for rapid production as synthetic poly-neo-epitope messenger RNA vaccines. We show that vaccination with such polytope mRNA vaccines induces potent tumour control and complete rejection of established aggressively growing tumours in mice. Moreover, we demonstrate that CD4(+) T cell neo-epitope vaccination reshapes the tumour microenvironment and induces cytotoxic T lymphocyte responses against an independent immunodominant antigen in mice, indicating orchestration of antigen spread. Finally, we demonstrate an abundance of mutations predicted to bind to MHC class II in human cancers as well by employing the same predictive algorithm on corresponding human cancer types. Thus, the tailored immunotherapy approach introduced here may be regarded as a universally applicable blueprint for comprehensive exploitation of the substantial neo-epitope target repertoire of cancers, enabling the effective targeting of every patient's tumour with vaccines produced 'just in time'.

Mutated tumor alleles are expressed according to their DNA frequency.

The transcription of tumor mutations from DNA into RNA has implications for biology, epigenetics and clinical practice. It is not clear if mutations are in general transcribed and, if so, at what proportion to the wild-type allele. Here, we examined the correlation between DNA mutation allele frequency and RNA mutation allele frequency. We sequenced the exome and transcriptome of tumor cell lines with large copy number variations, identified heterozygous single nucleotide mutations and absolute DNA copy number, and determined the corresponding DNA and RNA mutation allele fraction. We found that 99% of the DNA mutations in expressed genes are expressed as RNA. Moreover, we found a high correlation between the DNA and RNA mutation allele frequency. Exceptions are mutations that cause premature termination codons and therefore activate nonsense-mediated decay. Beyond this, we did not find evidence of any wide-scale mechanism, such as allele-specific epigenetic silencing, preferentially promoting mutated or wild-type alleles. In conclusion, our data strongly suggest that genes are equally transcribed from all alleles, mutated and wild-type, and thus transcribed in proportion to their DNA allele frequency.

Immunomic, genomic and transcriptomic characterization of CT26 colorectal carcinoma.

BACKGROUND: Tumor models are critical for our understanding of cancer and the development of cancer therapeutics. Here, we present an integrated map of the genome, transcriptome and immunome of an epithelial mouse tumor, the CT26 colon carcinoma cell line. RESULTS: We found that Kras is homozygously mutated at p.G12D, Apc and Tp53 are not mutated, and Cdkn2a is homozygously deleted. Proliferation and stem-cell markers, including Top2a, Birc5 (Survivin), Cldn6 and Mki67, are highly expressed while differentiation and top-crypt markers Muc2, Ms4a8a (MS4A8B) and Epcam are not. Myc, Trp53 (tp53), Mdm2, Hif1a, and Nras are highly expressed while Egfr and Flt1 are not. MHC class I but not MHC class II is expressed. Several known cancer-testis antigens are expressed, including Atad2, Cep55, and Pbk. The highest expressed gene is a mutated form of the mouse tumor antigen gp70. Of the 1,688 non-synonymous point variations, 154 are both in expressed genes and in peptides predicted to bind MHC and thus potential targets for immunotherapy development. Based on its molecular signature, we predicted that CT26 is refractory to anti-EGFR mAbs and sensitive to MEK and MET inhibitors, as have been previously reported. CONCLUSIONS: CT26 cells share molecular features with aggressive, undifferentiated, refractory human colorectal carcinoma cells. As CT26 is one of the most extensively used syngeneic mouse tumor models, our data provide a map for the rationale design of mode-of-action studies for pre-clinical evaluation of targeted- and immunotherapies.