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Neoantigens are newly formed peptides created from somatic mutations that are capable of inducing tumor-specific T cell recognition. Recently, researchers and clinicians have leveraged next generation sequencing technologies to identify neoantigens and to create personalized immunotherapies for cancer treatment. To create a personalized cancer vaccine, neoantigens must be computationally predicted from matched tumor–normal sequencing data, and then ranked according to their predicted capability in stimulating a T cell response. This candidate neoantigen prediction process involves multiple steps, including somatic mutation identification, HLA typing, peptide processing, and peptide-MHC binding prediction. The general workflow has been utilized for many preclinical and clinical trials, but there is no current consensus approach and few established best practices. In this article, we review recent discoveries, summarize the available computational tools, and provide analysis considerations for each step, including neoantigen prediction, prioritization, delivery, and validation methods. In addition to reviewing the current state of neoantigen analysis, we provide practical guidance, specific recommendations, and extensive discussion of critical concepts and points of confusion in the practice of neoantigen characterization for clinical use. Finally, we outline necessary areas of development, including the need to improve HLA class II typing accuracy, to expand software support for diverse neoantigen sources, and to incorporate clinical response data to improve neoantigen prediction algorithms. The ultimate goal of neoantigen characterization workflows is to create personalized vaccines that improve patient outcomes in diverse cancer types.

Somatic mutations within non-coding regions and even exons may have unidentified regulatory consequences that are often overlooked in analysis workflows. Here we present RegTools ( www.regtools.org ), a computationally efficient, free, and open-source software package designed to integrate somatic variants from genomic data with splice junctions from bulk or single cell transcriptomic data to identify variants that may cause aberrant splicing. We apply RegTools to over 9000 tumor samples with both tumor DNA and RNA sequence data. RegTools discovers 235,778 events where a splice-associated variant significantly increases the splicing of a particular junction, across 158,200 unique variants and 131,212 unique junctions. To characterize these somatic variants and their associated splice isoforms, we annotate them with the Variant Effect Predictor, SpliceAI, and Genotype-Tissue Expression junction counts and compare our results to other tools that integrate genomic and transcriptomic data. While many events are corroborated by the aforementioned tools, the flexibility of RegTools also allows us to identify splice-associated variants in known cancer drivers, such as TP53 , CDKN2A , and B2M , and other genes. Analysing the regulatory consequences of mutations and splice variants at large scale in cancer requires efficient computational tools. Here, the authors develop RegTools, a software package that can identify splice-associated variants from large-scale genomics and transcriptomics data with efficiency and flexibility.

Retinal and choroidal neovascularization (NV) and vascular leakage contribute to visual impairment in several common ocular diseases. The angiopoietin/TIE2 (ANG/TIE2) pathway maintains vascular integrity, and negative regulators of this pathway are potential therapeutic targets for these diseases. Here, we demonstrated that vascular endothelial-protein tyrosine phosphatase (VE-PTP), which negatively regulates TIE2 activation, is upregulated in hypoxic vascular endothelial cells, particularly in retinal NV. Intraocular injection of an anti-VE-PTP antibody previously shown to activate TIE2 suppressed ocular NV. Furthermore, a small-molecule inhibitor of VE-PTP catalytic activity (AKB-9778) activated TIE2, enhanced ANG1-induced TIE2 activation, and stimulated phosphorylation of signaling molecules in the TIE2 pathway, including AKT, eNOS, and ERK. In mouse models of neovascular age-related macular degeneration, AKB-9778 induced phosphorylation of TIE2 and strongly suppressed NV. Ischemia-induced retinal NV, which is relevant to diabetic retinopathy, was accentuated by the induction of ANG2 but inhibited by AKB-9778, even in the presence of high levels of ANG2. AKB-9778 also blocked VEGF-induced leakage from dermal and retinal vessels and prevented exudative retinal detachments in double-transgenic mice with high expression of VEGF in photoreceptors. These data support targeting VE-PTP to stabilize retinal and choroidal blood vessels and suggest that this strategy has potential for patients with a wide variety of retinal and choroidal vascular diseases.

Background Neoantigen-targeting therapies including personalized vaccines have shown promise in the treatment of cancers, particularly when used in combination with checkpoint blockade therapy. At least 100 clinical trials involving these therapies have been initiated globally. Accurate identification and prioritization of neoantigens is crucial for designing these trials, predicting treatment response, and understanding mechanisms of resistance. With the advent of massively parallel DNA and RNA sequencing technologies, it is now possible to computationally predict neoantigens based on patient-specific variant information. However, numerous factors must be considered when prioritizing neoantigens for use in personalized therapies. Complexities such as alternative transcript annotations, various binding, presentation and immunogenicity prediction algorithms, and variable peptide lengths/registers all potentially impact the neoantigen selection process. There has been a rapid development of computational tools that attempt to account for these complexities. While these tools generate numerous algorithmic predictions for neoantigen characterization, results from these pipelines are difficult to navigate and require extensive knowledge of the underlying tools for accurate interpretation. This often leads to over-simplification of pipeline outputs to make them tractable, for example, limiting prediction to a single RNA isoform or only summarizing the top ranked of many possible peptide candidates. In addition to variant detection, gene expression, and predicted peptide binding affinities, recent studies have also demonstrated the importance of mutation location, allele-specific anchor locations, and variation of T-cell response to long versus short peptides. Due to the intricate nature and number of salient neoantigen features, presenting all relevant information to facilitate candidate selection for downstream applications is a difficult challenge that current tools fail to address. Results We have created pVACview, the first interactive tool designed to aid in the prioritization and selection of neoantigen candidates for personalized neoantigen therapies including cancer vaccines. pVACview has a user-friendly and intuitive interface where users can upload, explore, select, and export their neoantigen candidates. The tool allows users to visualize candidates at multiple levels of detail including variant, transcript, peptide, and algorithm prediction information. Conclusions pVACview will allow researchers to analyze and prioritize neoantigen candidates with greater efficiency and accuracy in basic and translational settings. The application is available as part of the pVACtools software at pvactools.org and as an online server at pvacview.org.

The pandemic influenza A (H1N1) pdm09 virus, avian influenza A (H5N1) virus, and influenza A (H7N9) virus induced severe morbidity and mortality throughout the world. Previous studies suggested a close association between the interferon-induced transmembrane protein-3 (IFITM3) genetic variant rs12252 and influenza. Here, we explored the correlation between the rs12252 and influenza susceptibility and severity using meta-analysis. Relevant studies published before May 22, 2014 were retrieved from PubMed, ISI web of knowledge, EBSCO, and Cochrane central register of controlled trials databases. Association between rs12252 and influenza susceptibility and severity were determined using statistical analysis of odds ratios (ORs). A total of four studies consisting of 445 cases and 4180 controls were included in our analysis. Generally, there is increased risk of influenza in subjects carrying rs12252 in the recessive model (CC vs. CT+TT: OR = 2.35, 95% CI: 1.49-3.70, P<0.001), the dominant model (CC+CT vs. TT: OR=1.60, 95% CI: 1.18-2.22, P=0.003), the homozygote comparison (CC vs. TT: OR=4.11, 95% CI: 2.15-7.84, P<0.001), and the allele contrast (C vs. T: OR=1.67, 95% CI: 1.32-2.13, P<0.001). Stratification analysis of ethnicity and severity revealed a significant increase in influenza susceptibility by IFITM3-SNP rs12252 among both Asian and Caucasian population. SNP rs12252 shows significant impact on severe infections (P<0.05), but not on mild influenza. Besides, our result also associated rs12252 with influenza severity (severe vs. mild: OR=2.37, 95% CI: 1.32-4.25, P=0.004), (severe vs. control: OR=2.70, 95% CI: 1.85-3.94, P<0.001). Our meta-analysis suggests a significant association between a minor IFITM3 allele (SNP rs12252-C) with severe influenza susceptibility, but not in mild influenza subjects, in both UK Caucasians and Han Chinese population. The rs12252-C allele causes a 23.7% higher chance of infection and also constitutes a risk factor for more severe influenza.

Background This proof-of-concept retrospective case study investigated whether patient-reported outcomes (PRO) instruments, designed to capture symptomatic adverse event data, could identity a known exposure–response (ER) relationship for safety characterized in an original FDA analysis of an approved anti-cancer agent. PRO instruments have been designed to uniquely quantify the tolerability aspects of exposure-associated symptomatic adverse events. We explored whether standard ER analyses of clinician-reported safety data for symptomatic adverse events could be complemented by ER analysis using PRO data that capture and quantify the tolerability aspects of these same symptomatic adverse events. Methods Exposure-associated adverse event data for diarrhea were analyzed in parallel in 120 patients enrolled in a clinical trial using physician reported Common Terminology Criteria for Adverse Events (CTCAE) and patient-reported symptomatic adverse event data captured by the National Cancer Institute’s (NCI) PRO Common Terminology Criteria for Adverse Events (PRO-CTCAE) instrument. Comparative ER analyses of diarrhea were conducted using the same dataset. Results from the CTCAE and PRO-CTCAE ER analyses were assessed for consistency with the ER relationship for diarrhea established in the original NDA using a 750-patient dataset. The analysis was limited to the 120-patient subset with parallel CTCAE and PRO-CTCAE assessments. Results Within the same 120-patient dataset, ER analysis using dense, longitudinal PRO-CTCAE-derived data was sensitive to identify the known ER relationship for diarrhea, whereas the standard CTCAE based ER analysis was not. Conclusions ER analysis using PRO assessed symptomatic adverse event data may be a sensitive tool to complement traditional ER analysis. Improved identification of relationships for safety, by including quantification of the tolerability aspect of symptomatic adverse events using PRO instruments, may be useful to improve the sensitivity of exposure response analysis to support early clinical trial dosage optimization strategies, where decision making occurs within limited small patient datasets.

To investigate clinical features of infantile hypertrophic pyloric stenosis (IHPS) in Chinese Han population. Three hundred and sixteen hospitalized patients with IHPS from January 1998 to February 2010 were retrospectively reviewed, and data including patient's sex, onset age, other coexisting congenital defects, pyloric circular muscle thickness evaluated by ultrasonograph, serum electrolytes concentration, and results of arterial blood gas analysis on admission were collected. The patients were divided into two groups: the duration between first onset and admission less than or equal to 10 days (early onset group), and more than 10 days (late onset group). The results of arterial blood gas and serum electrolyte concentration were compared between the two groups. There were 271 males and 45 females in 316 patients; the onset age ranged between 1 and 351 (26.5±26.6) days. The birth weight ranged between 1.6 and 4.5 (3.23±0.44) kilograms; coexisting congenital defects were found in 65 cases (20.6%). Pyloric circular muscle thickness was 4-8 (5.4±1.0) millimetres (mm). For the early onset group, the rates of hypokalemia, hypochloraemia and hypercapnia were significantly lower than those in the late onset group (18.67% VS 50%, P<0.0001; 46.03% VS 71.01%, P = 0.003; 56.58% VS 83.44%, P = 2.17×10(-5); respectively). The symptom duration in Chinese Han population was longer than that in other populations. And as the prolongation of symptom duration, the incidence of acid-base imbalance increased significantly. Infants with persistent vomiting at the age of 3∼5 weeks after birth should be considered IHPS, and go to hospital as soon as possible in order to reduce the incidence of hypokalemia, hypochloraemia and hypercapnia, and avoid deterioration.

Neoantigens are peptides derived from non-synonymous mutations presented by human leukocyte antigens (HLAs), which are recognized by antitumour T cells 1 – 14 . The large HLA allele diversity and limiting clinical samples have restricted the study of the landscape of neoantigen-targeted T cell responses in patients over their treatment course. Here we applied recently developed technologies 15 – 17 to capture neoantigen-specific T cells from blood and tumours from patients with metastatic melanoma with or without response to anti-programmed death receptor 1 (PD-1) immunotherapy. We generated personalized libraries of neoantigen–HLA capture reagents to single-cell isolate the T cells and clone their T cell receptors (neoTCRs). Multiple T cells with different neoTCR sequences (T cell clonotypes) recognized a limited number of mutations in samples from seven patients with long-lasting clinical responses. These neoTCR clonotypes were recurrently detected over time in the blood and tumour. Samples from four patients with no response to anti-PD-1 also demonstrated neoantigen-specific T cell responses in the blood and tumour to a restricted number of mutations with lower TCR polyclonality and were not recurrently detected in sequential samples. Reconstitution of the neoTCRs in donor T cells using non-viral CRISPR–Cas9 gene editing demonstrated specific recognition and cytotoxicity to patient-matched melanoma cell lines. Thus, effective anti-PD-1 immunotherapy is associated with the presence of polyclonal CD8 + T cells in the tumour and blood specific for a limited number of immunodominant mutations, which are recurrently recognized over time. Effective anti-PD-1 immunotherapy is associated with the presence of polyclonal CD8 + T cells in the tumour and blood specific for a limited number of immunodominant mutations, which are recurrently recognized over time.

Neoantigens are novel peptide sequences resulting from sources such as somatic mutations in tumors. Upon loading onto major histocompatibility complex (MHC) molecules, they can trigger recognition by T cells. Neoantigen targeting therapies including personalized vaccines have shown promise in the treatment of cancers, particularly when used in combination with checkpoint blockade therapy. Thus, accurate identification and prioritization of neoantigens is critical for conducting neoantigen-based clinical trials, predicting treatment response, and understanding mechanisms of resistance. With the advent of whole exome and RNA sequencing technologies, researchers and clinicians are now able to computationally predict neoantigens based on patient-specific mutation information. However, numerous factors must be considered when prioritizing neoantigens for use in personalized therapies, including but not limited to binding affinity, mutation location, mutant allele expression, allele-specific anchor locations. Complexities such as alternative transcript annotations, multiple algorithm prediction scores and variable peptide lengths/registers all potentially impact the neoantigen selection process. While there has been a rapid development of computational tools that attempt to account for these complexities, such as pVACtools, there remains considerable room for improvement of both the underlying algorithms as well as how the data is integrated and visualized. To help address these issues, Chapter 2 of this thesis describes a computational pipeline for predicting allele-specific anchor locations. We computationally predicted anchor positions for different peptide lengths for 328 common HLA alleles and identified unique anchoring patterns among them. Analysis of 923 tumor samples shows that 6-38% of neoantigen candidates are potentially misclassified and can be rescued using allele-specific knowledge of anchor positions. A subset of anchor results was orthogonally validated using protein crystallography structures and representative anchor trends were experimentally validated using peptide-MHC stability assays and competition binding assays. Chapter 3 of this thesis describes pVACview, a novel interactive tool designed to aid in the prioritization and selection of neoantigen candidates for personalized neoantigen therapies including cancer vaccines. While computational pipelines generate numerous algorithmic predictions for neoantigen characterization, results from these pipelines are difficult to navigate and require extensive knowledge of the underlying tools for accurate interpretation. pVACview has a user-friendly and intuitive interface where users can upload, explore, select and export their neoantigen candidates. The tool allows users to visualize candidates across three different levels, including variant, transcript and peptide information for prioritization with greater efficiency and accuracy. It is also available as part of the pVACtools pipeline. To account for the different levels of complexity discussed in Chapters 2 and 3, Chapter 4 describes an ongoing effort to generate a standardized dataset of neoantigen features using experimentally validated neoantigens collected from publications. By acquiring raw sequencing datasets and running them through a formalized pipeline, we aim to generate a comprehensive collection of neoantigen features for future training and testing of various machine learning models. Overall, these chapters describe various efforts to improve current algorithms and methods pertaining to the identification, prioritization and selection process of neoantigen candidates. We hope our findings will help formalize, streamline and improve the identification process for relevant clinical studies involving personalized cancer vaccines.

Purpose The purpose of this study was to determine the therapeutic effect and mechanism of AAV-MnSOD by intravitreal injection on diabetic retinopathy (DRP) and the metabolic memory phenomenon. Methods The effect of hyperglycemia and metabolic memory on the thickness of basement membrane, ratio of pericyte area and cross-sectional area of capillary vessels in the nerve fiber layer and outer plexiform layer; retinal capillary cell apoptosis; number of acellular capillaries and activities of retinal MnSOD and catalase were examined and compared with intravitreal injection of AAV-MnSOD by transmission electron microscopy, TUNEL assay, ELISA, and immunohistochemistry. Results Hyperglycemia increased the thickness of capillary basement membranes in the nerve fiber layer and outer plexiform layer, decreased the ratio of pericyte area and cross-sectional area of capillary vessels, increased numbers of acellular capillaries and apoptosis of retinal capillary cells, and decreased activities of retinal MnSOD and catalase. Termination of hyperglycemia cannot reverse pathological changes listed above. Intra-vitreal injection of AAV-MnSOD dramatically elevated the level and activities of retinal MnSOD and catalase, and effectively prevented the progression of DRP and the metabolic memory phenomenon. Conclusions Increasing reactive oxygen species concentration and continuous decreasing of antioxidant enzyme activity play important roles in DRP and the metabolic memory phenomenon. AAV-MnSOD gene therapy provides a promising strategy to inhibit this blinding disease.