Immunodominant T-cell epitopes from the SARS-CoV-2 spike antigen reveal robust pre-existing T-cell immunity in unexposed individuals.

The COVID-19 pandemic has revealed a range of disease phenotypes in infected patients with asymptomatic, mild, or severe clinical outcomes, but the mechanisms that determine such variable outcomes remain unresolved. In this study, we identified immunodominant CD8 T-cell epitopes in the spike antigen using a novel TCR-binding algorithm. The predicted epitopes induced robust T-cell activation in unexposed donors demonstrating pre-existing CD4 and CD8 T-cell immunity to SARS-CoV-2 antigen. The T-cell reactivity to the predicted epitopes was higher than the Spike-S1 and S2 peptide pools in the unexposed donors. A key finding of our study is that pre-existing T-cell immunity to SARS-CoV-2 is contributed by TCRs that recognize common viral antigens such as Influenza and CMV, even though the viral epitopes lack sequence identity to the SARS-CoV-2 epitopes. This finding is in contrast to multiple published studies in which pre-existing T-cell immunity is suggested to arise from shared epitopes between SARS-CoV-2 and other common cold-causing coronaviruses. However, our findings suggest that SARS-CoV-2 reactive T-cells are likely to be present in many individuals because of prior exposure to flu and CMV viruses.

Ophthatome™: an integrated knowledgebase of ophthalmic diseases for translating vision research into the clinic.

BACKGROUND: Medical big data analytics has revolutionized the human healthcare system by introducing processes that facilitate rationale clinical decision making, predictive or prognostic modelling of the disease progression and management, disease surveillance, overall impact on public health and research. Although, the electronic medical records (EMR) system is the digital storehouse of rich medical data of a large patient cohort collected over many years, the data lack sufficient structure to be of clinical value for applying deep learning methods and advanced analytics to improve disease management at an individual patient level or for the discipline in general. Ophthatome™ captures data contained in retrospective electronic medical records between September 2012 and January 2018 to facilitate translational vision research through a knowledgebase of ophthalmic diseases. METHODS: The electronic medical records data from Narayana Nethralaya ophthalmic hospital recorded in the MS-SQL database was mapped and programmatically transferred to MySQL. The captured data was manually curated to preserve data integrity and accuracy. The data was stored in MySQL database management system for ease of visualization, advanced search functions and other knowledgebase applications. RESULTS: Ophthatome™ is a comprehensive and accurate knowledgebase of ophthalmic diseases containing curated clinical, treatment and imaging data of 581,466 ophthalmic subjects from the Indian population, recorded between September 2012 and January 2018. Ophthatome™ provides filters and Boolean searches with operators and modifiers that allow selection of specific cohorts covering 524 distinct ophthalmic disease types and 1800 disease sub-types across 35 different anatomical regions of the eye. The availability of longitudinal data for about 300,000 subjects provides additional opportunity to perform clinical research on disease progression and management including drug responses and management outcomes. The knowledgebase captures ophthalmic diseases in a genetically diverse population providing opportunity to study genetic and environmental factors contributing to or influencing ophthalmic diseases. CONCLUSION: Ophthatome™ will accelerate clinical, genomic, pharmacogenomic and advanced translational research in ophthalmology and vision sciences.

Mutational Landscape of Esophageal Squamous Cell Carcinoma in an Indian Cohort.

Esophageal squamous cell carcinoma (ESCC) is the most common histological subtype of esophageal cancer in India. Cigarette smoking and chewing tobacco are known risk factors associated with ESCC. However, genomic alterations associated with ESCC in India are not well-characterized. In this study, we carried out exome sequencing to characterize the mutational landscape of ESCC tumors from subjects with a varied history of tobacco usage. Whole exome sequence analysis of ESCC from an Indian cohort revealed several genes that were mutated or had copy number changes. ESCC from tobacco chewers had a higher frequency of C:G > A:T transversions and 2-fold enrichment for mutation signature 4 compared to smokers and non-users of tobacco. Genes, such as TP53, CSMD3, SYNE1, PIK3CA, and NOTCH1 were found to be frequently mutated in Indian cohort. Mutually exclusive mutation patterns were observed in PIK3CA-NOTCH1, DNAH5-ZFHX4, MUC16-FAT1, and ZFHX4-NOTCH1 gene pairs. Recurrent amplifications were observed in 3q22-3q29, 11q13.3-q13.4, 7q22.1-q31.1, and 8q24 regions. Approximately 53% of tumors had genomic alterations in PIK3CA making this pathway a promising candidate for targeted therapy. In conclusion, we observe enrichment of mutation signature 4 in ESCC tumors from patients with a history of tobacco chewing. This is likely due to direct exposure of esophagus to tobacco carcinogens when it is chewed and swallowed. Genomic alterations were frequently observed in PIK3CA-AKT pathway members independent of the history of tobacco usage. PIK3CA pathway can be potentially targeted in ESCC which currently has no effective targeted therapeutic options.

Integrated genomic analysis reveals mutated ELF3 as a potential gallbladder cancer vaccine candidate.

Gallbladder cancer (GBC) is an aggressive gastrointestinal malignancy with no approved targeted therapy. Here, we analyze exomes (n = 160), transcriptomes (n = 115), and low pass whole genomes (n = 146) from 167 gallbladder cancers (GBCs) from patients in Korea, India and Chile. In addition, we also sequence samples from 39 GBC high-risk patients and detect evidence of early cancer-related genomic lesions. Among the several significantly mutated genes not previously linked to GBC are ETS domain genes ELF3 and EHF, CTNNB1, APC, NSD1, KAT8, STK11 and NFE2L2. A majority of ELF3 alterations are frame-shift mutations that result in several cancer-specific neoantigens that activate T-cells indicating that they are cancer vaccine candidates. In addition, we identify recurrent alterations in KEAP1/NFE2L2 and WNT pathway in GBC. Taken together, these define multiple targetable therapeutic interventions opportunities for GBC treatment and management.

A Synthetic DNA, Multi-Neoantigen Vaccine Drives Predominately MHC Class I CD8+ T-cell Responses, Impacting Tumor Challenge.

T-cell recognition of cancer neoantigens is important for effective immune-checkpoint blockade therapy, and an increasing interest exists in developing personalized tumor neoantigen vaccines. Previous studies utilizing RNA and long-peptide neoantigen vaccines in preclinical and early-phase clinical studies have shown immune responses predominantly driven by MHC class II CD4+ T cells. Here, we report on a preclinical study utilizing a DNA vaccine platform to target tumor neoantigens. We showed that optimized strings of tumor neoantigens, when delivered by potent electroporation-mediated DNA delivery, were immunogenic and generated predominantly MHC class I-restricted, CD8+ T-cell responses. High MHC class I affinity was associated specifically with immunogenic CD8+ T-cell epitopes. These DNA neoantigen vaccines induced a therapeutic antitumor response in vivo, and neoantigen-specific T cells expanded from immunized mice directly killed tumor cells ex vivo These data illustrate a unique advantage of this DNA platform to drive CD8+ T-cell immunity for neoantigen immunotherapy.

A neoepitope derived from a novel human germline APC gene mutation in familial adenomatous polyposis shows selective immunogenicity.

Familial adenomatous polyposis (FAP) is an inherited condition arising from genetic defects in the Adenomatous polyposis coli (APC) gene. Carriers with mutations in the APC gene develop polyps in the colon and rectum which if not managed, transition into colon cancer. In this study, we identified a novel germline mutation in the APC gene in members of an FAP-affected (Familial adenomatous polyposis) family. This unique heterozygous variant (c.735_736insT; p.Ser246PhefsTer6) was identified in ten out of twenty six family members, ranging in age from 6 to 60 years. Polyps were detected in six of the ten individuals (35-60 years) carrying this mutation. The remaining four members (6-23 years) remain polyp free. A significant fraction of FAP affected individuals eventually develop colon cancer and therapeutic interventions to prevent cancer progression remain elusive. To address this issue, we sought to determine if peptides derived from the novel APC mutation could induce a cytotoxic T cell response, thereby qualifying them as vaccine candidates. Peptides harboring the variant amino acids were first interrogated in silico for their immunogenicity using a proprietary neoepitope prioritization pipeline, OncoPeptVAC. A single 9-mer peptide was predicted to be immunogenic. Remarkably, CD8+ T cells isolated from either an FAP+/ APCmut individual, or from a FAP-/ APCmut individual, failed to respond to the peptide, whereas those from either an unaffected family member (FAP-/ APCwt) or from healthy unrelated donors, showed a robust response, suggesting that CD8+ T cells from individuals carrying this germline APC mutation have been tolerized to the mutation. Furthermore, experimental testing of six additional reported APC gene mutation-derived peptides revealed one of the six to be immunogenic. While not all APC mutant peptides are inmmunogenic, a few qualify as vaccine candidates offering novel treatment opportunities to patients with somatic APC gene mutations to delay/treat colorectal cancer.

A cancer vaccine approach for personalized treatment of Lynch Syndrome.

Lynch syndrome (LS) is a cancer predisposition disorder wherein patients have a 70-80% lifetime risk of developing colorectal cancers (CRC). Finding germline mutations in predisposing genes allows for risk assessment of CRC development. Here we report a germline heterozygous frame-shift mutation in the mismatch repair MLH1 gene which was identified in members of two unrelated LS families. Since defects in DNA mismatch repair genes generate frame-shift mutations giving rise to highly immunogenic neoepitopes, we postulated that vaccination with these mutant peptide antigens could offer promising treatment options to LS patients. To this end we performed whole-exome and RNA seq analysis on the blood and tumour samples from an LS-CRC patient, and used our proprietary neoepitope prioritization pipeline OncoPeptVAC to select peptides, and confirm their immunogenicity in an ex vivo CD8+ T cell activation assay. Three neoepitopes derived from the tumour of this patient elicited a potent CD8+ T cell response. Furthermore, analysis of the tumour-associated immune infiltrate revealed CD8+ T cells expressing low levels of activation markers, suggesting mechanisms of immune suppression at play in this relapsed tumour. Taken together, our study paves the way towards development of a cancer vaccine to treat or delay the onset/relapse of LS-CRC.

A Computational Approach Identifies Immunogenic Features of Prognosis in Human Cancers.

A large number of tumor intrinsic and extrinsic factors determine long-term survival in human cancers. In this study, we stratified 9120 tumors from 33 cancers with respect to their immune cell content and identified immunogenomic features associated with long-term survival. Our analysis demonstrates that tumors infiltrated by CD8+ T cells expressing higher levels of activation marker (PD1hi) along with TCR signaling genes and cytolytic T cell markers (IL2hi/TNF-αhi/IFN-γhi/GZMA-Bhi) extend survival, whereas survival benefit was absent for tumors infiltrated by anergic and hyperexhausted CD8+ T cells characterized by high expression of CTLA-4, TIM3, LAG3, and genes linked to PI3K signaling pathway. The computational approach of using robust and highly specific gene expression signatures to deconvolute the tumor microenvironment has important clinical applications, such as selecting patients who will benefit from checkpoint inhibitor treatment.

Comprehensive genomic analysis of malignant pleural mesothelioma identifies recurrent mutations, gene fusions and splicing alterations.

We analyzed transcriptomes (n = 211), whole exomes (n = 99) and targeted exomes (n = 103) from 216 malignant pleural mesothelioma (MPM) tumors. Using RNA-seq data, we identified four distinct molecular subtypes: sarcomatoid, epithelioid, biphasic-epithelioid (biphasic-E) and biphasic-sarcomatoid (biphasic-S). Through exome analysis, we found BAP1, NF2, TP53, SETD2, DDX3X, ULK2, RYR2, CFAP45, SETDB1 and DDX51 to be significantly mutated (q-score ≥ 0.8) in MPMs. We identified recurrent mutations in several genes, including SF3B1 (∼2%; 4/216) and TRAF7 (∼2%; 5/216). SF3B1-mutant samples showed a splicing profile distinct from that of wild-type tumors. TRAF7 alterations occurred primarily in the WD40 domain and were, except in one case, mutually exclusive with NF2 alterations. We found recurrent gene fusions and splice alterations to be frequent mechanisms for inactivation of NF2, BAP1 and SETD2. Through integrated analyses, we identified alterations in Hippo, mTOR, histone methylation, RNA helicase and p53 signaling pathways in MPMs.

Evolution of targeted therapies in cancer: opportunities and challenges in the clinic.

Targeted therapies have changed the course of cancer treatment in recent years. By reducing toxicity and improving outcome, these new generations of precision medicines have extended patient lives beyond what could be achieved by the use of nontargeted therapies. In the last 2 years, several new molecular entities targeting signaling proteins and immune pathways have gone through successful clinical development resulting in their approval. These new targeted therapies require patient selection and the discovery of biomarkers of response. This review discusses the evolution of targeted therapies in cancer and challenges in translating the concepts into clinical practice.

Regulation of Macrophage Polarization by RON Receptor Tyrosine Kinase Signaling.

The M1 and M2 states of macrophage polarization are the two extremes of a physiologic/phenotypic continuum that is dynamically influenced by environmental signals. The M1/M2 paradigm is an excellent framework to understand and appreciate some of the diverse functions that macrophages perform. Molecular analysis of mouse and human macrophages indicated that they gain M1 and M2-related functions after encountering specific ligands in the tissue environment. In this perspective, I discuss the function of recepteur d'origine nantais (RON) receptor tyrosine kinase in regulating the M2-like state of macrophage activation Besides decreasing pro-inflammatory cytokine production in response to toll-like receptor-4 activation, macrophage-stimulating protein strongly suppresses nitric oxide synthase and at the same time upregulates arginase, which is the rate limiting enzyme in the ornithine biosynthesis pathway. Interestingly, RON signaling preserved some of the characteristics of the M1 state, while still promoting the hallmarks of M2 polarization. Therefore, therapeutic modulation of RON activity can shift the activation state of macrophages between acute and chronic inflammatory states.

Host genetic background impacts modulation of the TLR4 pathway by RON in tissue-associated macrophages.

Toll-like receptors (TLRs) enable metazoans to mount effective innate immune responses to microbial and viral pathogens, as well as to endogenous host-derived ligands. It is understood that genetic background of the host can influence TLR responsiveness, altering susceptibility to pathogen infection, autoimmunity and cancer. Macrophage stimulatory protein (MSP), which activates the receptor tyrosine kinase recepteur d'origine nantais (RON), promotes key macrophage functions such as motility and phagocytic activity. MSP also acts via RON to modulate signaling by TLR4, which recognizes a range of pathogen or endogenous host-derived molecules. Here, we show that RON exerts divergent control over TLR4 activity in macrophages from different mouse genetic backgrounds. RON potently modulated the TLR4 response in macrophages from M2-prone FVB mice, as compared with M1-skewed C57Bl6 mice. Moreover, global expression analysis revealed that RON suppresses the TLR4-dependent type-I interferon gene signature only in FVB macrophages. This leads to attenuated production of the potent inflammatory mediator, tumor necrosis factor-α. Eliminating RON kinase activity markedly decreased carcinogen-mediated tumorigenesis in M2/Th2-biased FVB mice. We propose that host genetic background influences RON function, thereby contributing to the variability in TLR4 responsiveness in rodents and, potentially, in humans. These findings provide novel insight into the complex interplay between genetic context and immune function.

Functional consequences of the macrophage stimulating protein 689C inflammatory bowel disease risk allele.

BACKGROUND: Macrophage stimulating protein (MSP) is a serum growth factor that binds to and activates the receptor tyrosine kinase, Recepteur d'Origine Nantais (RON). A non-synonymous coding variant in MSP (689C) has been associated with genetic susceptibility to both Crohn's disease and ulcerative colitis, two major types of inflammatory bowel disease (IBD) characterized by chronic inflammation of the digestive tract. We investigated the consequences of this polymorphism for MSP-RON pathway activity and IBD pathogenesis. METHODS: RON expression patterns were examined on mouse and human cells and tissues under normal and disease conditions to identify cell types regulated by MSP-RON. Recombinant MSP variants were tested for their ability to bind and stimulate RON and undergo proteolytic activation. MSP concentrations were quantified in the serum of individuals carrying the MSP 689R and 689C alleles. RESULTS: In intestinal tissue, RON was primarily expressed by epithelial cells under normal and disease conditions. The 689C polymorphism had no impact on the ability of MSP to bind to or signal through RON. In a cohort of normal individuals and IBD patients, carriers of the 689C polymorphism had lower concentrations of MSP in their serum. CONCLUSIONS: By reducing the quantities of circulating MSP, the 689C polymorphism, or a variant in linkage disequilibrium with this polymorphism, may impact RON ligand availability and thus receptor activity. Given the known functions of RON in regulating wound healing and our analysis of RON expression patterns in human intestinal tissue, these data suggest that decreased RON activity may impact the efficiency of epithelial repair and thus underlie the increased IBD susceptibility associated with the MSP 689C allele.

Proteolytic activation of pro-macrophage-stimulating protein by hepsin.

Macrophage-stimulating protein (MSP) is a plasminogen-related growth factor and ligand for the receptor tyrosine kinase RON. The MSP/RON system promotes wound healing and invasive tumor growth and suppresses proinflammatory immune response. MSP binding to RON requires proteolytic conversion of the inactive single-chain form (pro-MSP) into the disulfide-linked α/ß heterodimer. The pro-MSP cleavage sequence (Ser-Lys-Leu-Arg(483)↓Val(484)) closely matches the substrate recognition sequences of hepsin, a type II transmembrane serine protease, that is overexpressed in several cancers. Here, we show that recombinant hepsin cleaves pro-MSP at the consensus site Arg(483)-Val(484) with superior efficiency compared with the known activators MT-SP1 and hepatocyte growth factor activator (HGFA). At least 50% of pro-MSP was processed within 1 hour at a hepsin concentration of 2.4 nmol/L and at a molar enzyme to substrate ratio of 1:500. An uncleavable single-chain variant of MSP weakly bound to a RON-Fc fusion protein, whereas hepsin-cleaved MSP bound with a K(D) of 10.3 nmol/L, suggesting that the high-affinity binding site in MSP ß-chain was properly formed. LNCaP prostate cancer cells overexpressing hepsin on the cell surface efficiently activated pro-MSP, which was blocked by a specific anti-hepsin antibody. Incubation of pro-MSP with hepsin led to robust RON-mediated phosphorylation of mitogen-activated protein kinase, ribosomal S6 protein, and Akt in human A2780 ovarian carcinoma cells stably expressing RON protein. In macrophages, pro-MSP with hepsin induced chemotaxis and attenuated lipopolysaccharide-dependent production of nitric oxide. These findings suggest that the MSP/RON signaling pathway may be regulated by hepsin in tissue homeostasis and in disease pathologies, such as in cancer and immune disorders.

Distinct involvement of the Gab1 and Grb2 adaptor proteins in signal transduction by the related receptor tyrosine kinases RON and MET.

Although the signal transduction mechanisms of the receptor tyrosine kinase MET are well defined, less is known about its close relative RON. MET initiates intracellular signaling by autophosphorylation on specific cytoplasmic tyrosines that form docking sites for the adaptor proteins Grb2 and Gab1. Grb2 binds directly and is essential for all of the biological activities of MET. Gab1 docks either directly or indirectly via Grb2 and controls only a subset of MET functions. Because MET and RON possess similar adaptor binding sites, it was anticipated that their adaptor interactions would be conserved. Here we show that in contrast to MET, RON relies primarily on Gab1 for signal transmission. Surprisingly, disruption of the Grb2 docking site of RON or Grb2 depletion augments activity, whereas enhancement of Grb2 binding attenuates Gab1 recruitment and signaling. Hence, RON and MET differ in their adaptor interactions; furthermore, Grb2 performs a novel antagonistic role in the context of RON signaling.

PADGE: analysis of heterogeneous patterns of differential gene expression.

UNLABELLED: We have devised a novel analysis approach, percentile analysis for differential gene expression (PADGE), for identifying genes differentially expressed between two groups of heterogeneous samples. PADGE was designed to compare expression profiles of sample subgroups at a series of percentile cutoffs and to examine the trend of relative expression between sample groups as expression level increases. Simulation studies showed that PADGE has more statistical power than t-statistics, cancer outlier profile analysis (COPA) (Tomlins SA, Rhodes DR, Perner S, Dhanasekaran SM, Mehra R, Sun XW, Varambally S, Cao X, Tchinda J, Kuefer R, Lee C, Montie JE, Shah RB, Pienta KJ, Rubin MA, Chinnaiyan AM. Science 310: 644-648, 2005), and kurtosis (Teschendorff AE, Naderi A, Barbosa-Morais NL, Caldas C. Bioinformatics 22: 2269-2275, 2006). Application of PADGE to microarray data sets in tumor tissues demonstrated its utility in prioritizing cancer genes encoding potential therapeutic targets or diagnostic markers. A web application was developed for researchers to analyze a large gene expression data set from heterogeneous biological samples and identify differentially expressed genes between subsets of sample classes using PADGE and other available approaches. AVAILABILITY: http://www.cgl.ucsf.edu/Research/genentech/padge/.

Protein-interaction mapping in search of effective drug targets.

Signaling complexes and networks are being intensely studied in an attempt to discover pathways that are amenable to therapeutic intervention. A challenge in this search is to understand the effect that the modulation of a target will have on the overall function of a cell and its surrounding neighbors. Protein-interaction mapping reveals relationships between proteins and their impact on cellular processes and is being used more widely in our understanding of disease mechanisms and their treatment. The review discusses challenges and breakthroughs in this new and evolving area and its impact on medicine.

Gaining confidence in high-throughput protein interaction networks.

Although genome-scale technologies have benefited from statistical measures of data quality, extracting biologically relevant pathways from high-throughput proteomics data remains a challenge. Here we develop a quantitative method for evaluating proteomics data. We present a logistic regression approach that uses statistical and topological descriptors to predict the biological relevance of protein-protein interactions obtained from high-throughput screens for yeast. Other sources of information, including mRNA expression, genetic interactions and database annotations, are subsequently used to validate the model predictions without bias or cross-pollution. Novel topological statistics show hierarchical organization of the network of high-confidence interactions: protein complex interactions extend one to two links, and genetic interactions represent an even finer scale of organization. Knowledge of the maximum number of links that indicates a significant correlation between protein pairs (correlation distance) enables the integrated analysis of proteomics data with data from genetics and gene expression. The type of analysis presented will be essential for analyzing the growing amount of genomic and proteomics data in model organisms and humans.