Pharmacologic modulation of RNA splicing enhances anti-tumor immunity.

Although mutations in DNA are the best-studied source of neoantigens that determine response to immune checkpoint blockade, alterations in RNA splicing within cancer cells could similarly result in neoepitope production. However, the endogenous antigenicity and clinical potential of such splicing-derived epitopes have not been tested. Here, we demonstrate that pharmacologic modulation of splicing via specific drug classes generates bona fide neoantigens and elicits anti-tumor immunity, augmenting checkpoint immunotherapy. Splicing modulation inhibited tumor growth and enhanced checkpoint blockade in a manner dependent on host T cells and peptides presented on tumor MHC class I. Splicing modulation induced stereotyped splicing changes across tumor types, altering the MHC I-bound immunopeptidome to yield splicing-derived neoepitopes that trigger an anti-tumor T cell response in vivo. These data definitively identify splicing modulation as an untapped source of immunogenic peptides and provide a means to enhance response to checkpoint blockade that is readily translatable to the clinic.

The insulin secretory granule is a hotspot for autoantigen formation in type 1 diabetes.

In type 1 diabetes, the insulin-producing beta cells of the pancreas are destroyed through the activity of autoreactive T cells. In addition to strong and well-documented HLA class II risk haplotypes, type 1 diabetes is associated with noncoding polymorphisms within the insulin gene locus. Furthermore, autoantibody prevalence data and murine studies implicate insulin as a crucial autoantigen for the disease. Studies identify secretory granules, where proinsulin is processed into mature insulin, stored and released in response to glucose stimulation, as a source of antigenic epitopes and neoepitopes. In this review, we integrate established concepts, including the role that susceptible HLA and thymic selection of the T cell repertoire play in setting the stage for autoimmunity, with emerging insights about beta cell and insulin secretory granule biology. In particular, the acidic, peptide-rich environment of secretory granules combined with its array of enzymes generates a distinct proteome that is unique to functional beta cells. These factors converge to generate non-templated peptide sequences that are recognised by autoreactive T cells. Although unanswered questions remain, formation and presentation of these epitopes and the resulting immune responses appear to be key aspects of disease initiation. In addition, these pathways may represent important opportunities for therapeutic intervention.

Mouse brain contains age-dependent extraparenchymal granular structures and astrocytes, both reactive to natural IgM antibodies, linked to the fissura magna.

BACKGROUND: Mouse brains can contain specific polyglucosan aggregates known as Periodic Acid-Schiff (PAS)-granules. Generated in astrocytes, these granules increase with age and exhibit neo-epitopes of carbohydrate nature that are recognized by natural IgM antibodies (IgMs). The existence of neoepitopes on PAS granules suggests the presence of neoepitopes in other brain structures, and this is investigated here. To this end, brain sections from SAMP8 and ICR-CD1 mice were examined at different ages. RESULTS: We have identified two novel structures that, apart from PAS granules, are recognized by natural IgMs. On one side, IgM reactive (IgM+) granular structures which are placed in the longitudinal fissure, the quadrigeminal cistern, and a region that extends from the quadrigeminal cistern to the interpeduncular cistern. This last region, located between the telencephalon and both the mesencephalon and diencephalon, is designated henceforth as the fissura magna, as it is indeed a fissure and the largest in the brain. As all these regions are extraparenchymal (EP), the IgM+ granules found in these zones have been named EP granules. These EP granules are mainly associated with fibroblasts and are not stained with PAS. On the other side, some IgM+ astrocytes have been found in the glia limitans, near the above-mentioned fissures. Remarkably, EP granules are more prevalent at younger ages, while the number of IgM+ astrocytes increases with age, similarly to the already described evolution of PAS granules. CONCLUSIONS: The present work reports the presence of two brain-related structures that, apart from PAS granules, contain neo-epitopes of carbohydrate nature, namely EP granules and IgM+ astrocytes. We suggest that EP granules, associated to fibroblasts, may be part of a physiological function in brain clearance or brain-CSF immune surveillance, while both PAS granules and IgM+ astrocytes may be related to the increasing accumulation of harmful materials that occurs with age and linked to brain protective mechanisms. Moreover, the specific localisation of these EP granules and IgM+ astrocytes suggest the importance of the fissura magna in these brain-related cleaning and immune functions. The overall results reinforce the possible link between the fissura magna and the functioning of the glymphatic system.

Prediction of cancer neoepitopes needs new rules.

Tumors are immunogenic and the non-synonymous point mutations harbored by tumors are a source of their immunogenicity. Immunologists have long been enamored by the idea of synthetic peptides corresponding to mutated epitopes (neoepitopes) as specific "vaccines" against tumors presenting those neoepitopes in context of MHC I. Tumors may harbor hundreds of point mutations and it would require effective prediction algorithms to identify candidate neoepitopes capable of eliciting potent tumor-specific CD8+ T cell responses. Our current understanding of MHC I-restricted epitopes come from the observance of CD8+ T cell responses against viral (vaccinia, lymphocytic choriomeningitis etc.) and model (chicken ovalbumin, hen egg lysozyme etc.) antigens. Measurable CD8+ T cell responses elicited by model or viral antigens are always directed against epitopes possessing strong binding affinity for the restricting MHC I alleles. Immense collective effort to develop methodologies combining genomic sequencing, bioinformatics and traditional immunological techniques to identify neoepitopes with strong binding affinity to MHC I has only yielded inaccurate prediction algorithms. Additionally, new evidence has emerged suggesting that neoepitopes, which unlike the epitopes of viral or model antigens have closely resembling wild-type counterparts, may not necessarily demonstrate strong affinity to MHC I. Our bearing need recalibration.

Tumor Antigens beyond the Human Exome.

With the advent of immunotherapeutics, a new era in the combat against cancer has begun. Particularly promising are neo-epitope-targeted therapies as the expression of neo-antigens is tumor-specific. In turn, this allows the selective targeting and killing of cancer cells whilst healthy cells remain largely unaffected. So far, many advances have been made in the development of treatment options which are tailored to the individual neo-epitope repertoire. The next big step is the achievement of efficacious "off-the-shelf" immunotherapies. For this, shared neo-epitopes propose an optimal target. Given the tremendous potential, a thorough understanding of the underlying mechanisms which lead to the formation of neo-antigens is of fundamental importance. Here, we review the various processes which result in the formation of neo-epitopes. Broadly, the origin of neo-epitopes can be categorized into three groups: canonical, noncanonical, and viral neo-epitopes. For the canonical neo-antigens that arise in direct consequence of somatic mutations, we summarize past and recent findings. Beyond that, our main focus is put on the discussion of noncanonical and viral neo-epitopes as we believe that targeting those provides an encouraging perspective to shape the future of cancer immunotherapeutics.

Characteristics of the (Auto)Reactive T Cells in Rheumatoid Arthritis According to the Immune Epitope Database.

T cells are known to be involved in the pathogenesis of rheumatoid arthritis (RA). Accordingly, and to better understand T cells' contribution to RA, a comprehensive review based on an analysis of the Immune Epitope Database (IEDB) was conducted. An immune CD8+ T cell senescence response is reported in RA and inflammatory diseases, which is driven by active viral antigens from latent viruses and cryptic self-apoptotic peptides. RA-associated pro-inflammatory CD4+ T cells are selected by MHC class II and immunodominant peptides, which are derived from molecular chaperones, host extra-cellular and cellular peptides that could be post-translationally modified (PTM), and bacterial cross-reactive peptides. A large panel of techniques have been used to characterize (auto)reactive T cells and RA-associated peptides with regards to their interaction with the MHC and TCR, capacity to enter the docking site of the shared epitope (DRB1-SE), capacity to induce T cell proliferation, capacity to select T cell subsets (Th1/Th17, Treg), and clinical contribution. Among docking DRB1-SE peptides, those with PTM expand autoreactive and high-affinity CD4+ memory T cells in RA patients with an active disease. Considering original therapeutic options in RA, mutated, or altered peptide ligands (APL) have been developed and are tested in clinical trials.

Carbamylation of ß2-glycoprotein I generates new autoantigens for antiphospholipid syndrome: a new tool for diagnosis of 'seronegative' patients.

OBJECTIVES: Antiphospholipid syndrome (APS) is a prothrombotic condition defined by recurrent thrombosis, pregnancy complications and circulating antiphospholipid antibodies (aPL), including anti-ß2-glycoprotein I (ß2-GPI). In clinical practice it is possible to find patients with APS persistently negative for the aPL tests according to Sydney criteria ('seronegative APS', SN-APS). Recently, several autoimmune responses have been described as a consequence of post-translational modifications of their target autoantigens. This study was undertaken to test carbamylated-ß2-GPI (Carb-ß2-GPI) as a new autoantigen of APS. METHODS: ß2-GPI was carbamylated by potassium cyanate and used to investigate its effect on monocyte-derived dendritic cell (moDC) phenotype and function. Sera from 114 SN-APS patients, 60 APS, 20 patients with RA, 20 non-APS thrombosis and 50 healthy donors were analysed for anti-Carb-ß2-GPI by ELISA. RESULTS: Carb-ß2-GPI is able to activate moDCs, inducing upregulation of CD80, CD86 and CD40, activation of extracellular signal-regulated kinase, p38 mitogen-activated protein kinase and nuclear factor-κB, and IL-12p70 release. Serological results showed that both 37/114 SN-APS (32.46%) and 23/60 APS (38.33%) patients resulted positive for anti-Carb-ß2-GPI. Interestingly, SN-APS patients who tested positive for anti-Carb-ß2-GPI showed a higher prevalence of thrombocytopenia (P = 0.04, likelihood positive ratio of 3.9). CONCLUSION: Data obtained from both functional tests on moDCs and immunological approaches prompted identification of Carb-ß2-GPI as a 'new' antigenic target in APS. In particular, anti-Carb-ß2-GPI revealed a potential usefulness in identification of a significant proportion of SN-APS patients. Moreover, since patients who tested positive for anti-Carb-ß2-GPI reported a high risk of thrombocytopenia, this test may be considered a suitable approach in the clinical evaluation of SN-APS.

Impact of tumor heterogeneity and microenvironment in identifying neoantigens in a patient with ovarian cancer.

Identification of neoepitopes as tumor-specific targets remains challenging, especially for cancers with low mutational burden, such as ovarian cancer. To identify mutated human leukocyte antigen (HLA) ligands as potential targets for immunotherapy in ovarian cancer, we combined mass spectrometry analysis of the major histocompatibility complex (MHC) class I peptidomes of ovarian cancer cells with parallel sequencing of whole exome and RNA in a patient with high-grade serous ovarian cancer. Four of six predicted mutated epitopes capable of binding to HLA-A*02:01 induced peptide-specific T cell responses in blood from healthy donors. In contrast, all six peptides failed to induce autologous peptide-specific response by T cells in peripheral blood or tumor-infiltrating lymphocytes from ascites of the patient. Surprisingly, T cell responses against a low-affinity p53-mutant Y220C epitope were consistently detected in the patient with either unprimed or in vitro peptide-stimulated T cells even though the patient's primary tumor did not bear this mutation. Our results demonstrated that tumor heterogeneity and distinct immune microenvironments within a patient should be taken into consideration for identification of immunogenic neoantigens. T cell responses to a driver gene-derived p53 Y220C mutation in ovarian cancer warrant further study.

Simplified Monopalmitoyl Toll-like Receptor 2 Ligand Mini-UPam for Self-Adjuvanting Neoantigen-Based Synthetic Cancer Vaccines.

Synthetic vaccines, based on antigenic peptides that comprise MHC-I and MHC-II T-cell epitopes expressed by tumors, show great promise for the immunotherapy of cancer. For optimal immunogenicity, the synthetic peptides (SPs) should be adjuvanted with suitable immunostimulatory additives. Previously, we have shown that improved immunogenicity in vivo is obtained with vaccine modalities in which an SP is covalently connected to an adjuvanting moiety, typically a ligand to Toll-like receptor 2 (TLR2). SPs were covalently attached to UPam, which is a derivative of the classic TLR2 ligand Pam3 CysSK4 . A disadvantage of the triply palmitoylated UPam is its high lipophilicity, which precludes universal adoption of this adjuvant for covalent modification of various antigenic peptides as it renders the synthetic vaccine insoluble in several cases. Here, we report a novel conjugatable TLR2 ligand, mini-UPam, which contains only one palmitoyl chain, rather than three, and therefore has less impact on the solubility and other physicochemical properties of a synthetic peptide. In this study, we used SPs that contain the clinically relevant neoepitopes identified in a melanoma patient who completely recovered after T-cell therapy. Homogeneous mini-UPam-SP conjugates have been prepared in good yields by stepwise solid-phase synthesis that employed a mini-UPam building block pre-prepared in solution and the standard set of Fmoc-amino acids. The immunogenicity of the novel mini-UPam-SP conjugates was demonstrated by using the cancer patient's T-cells.

Interacting Genetic Lesions of Melanoma in the Tumor Microenvironment: Defining a Viable Therapy.

Melanoma is the most aggressive form of skin cancer with an estimated 106,110 newly diagnosed cases in the United States of America in 2021 leading to an approximated 7180 melanoma-induced deaths. Cancer typically arises from an accumulation of somatic mutations and can be associated with mutagenic or carcinogenic exposure. A key characteristic of melanoma is the extensive somatic mutation rate of 16.8 mutations/Mb, which is largely attributed to UV exposure. Bearing the highest mutational load, many of them occur in key driver pathways, most commonly the BRAFV600E in the mitogen-activated protein kinase (MAPK) pathway. This driver mutation is targeted clinically with FDA-approved therapies using small molecule inhibitors of oncogenic BRAFV600E and MEK, which has greatly expanded therapeutic intervention following a melanoma diagnosis. Up until 2011, therapeutic options for metastatic melanoma were limited, and treatment typically fell under the spectrum of surgery, radiotherapy, and chemotherapy.Attributed to the extensive mutation rate, as well as having the highest number of neoepitopes, melanoma is deemed to be extremely immunogenic. However, despite this highly immunogenic nature, melanoma is notorious for inducing an immunosuppressive microenvironment which can be relieved by checkpoint inhibitor therapy. The two molecules currently approved clinically are ipilimumab and nivolumab, which target the molecules CTLA-4 and PD-1, respectively.A plethora of immunomodulatory molecules exist, many with redundant functions. Additionally, these molecules are expressed not only by immune cells but also by tumor cells within the tumor microenvironment. Tumor profiling of these cell surface checkpoint molecules is necessary to optimize a clinical response. The presence of immunomodulatory molecules in melanoma, using data from The Cancer Genome Atlas and validation of expression in two model systems, human melanoma tissues and patient-derived melanoma cells, revealed that the expression levels of B and T lymphocyte attenuator (BTLA), TIM1, and CD226, concurrently with the BRAFV600E mutation status, significantly dictated overall survival in melanoma patients. These molecules, along with herpesvirus entry mediator (HVEM) and CD160, two molecules that are a part of the HVEM/BTLA/CD160 axis, had a higher expression in human melanoma tissues when compared to normal skin melanocytes and have unique roles to play in T cell activation. New links are being uncovered between the expression of immunomodulatory molecules and the BRAFV600E genetic lesion in melanoma. Small molecule inhibitors of the MAPK pathway regulate the surface expression of this multifaceted molecule, making BTLA a promising target for immuno-oncology to be targeted in combination with small molecule inhibitors, potentially alleviating T regulatory cell activation and improving patient prognosis.

Improved Prediction of MHC II Antigen Presentation through Integration and Motif Deconvolution of Mass Spectrometry MHC Eluted Ligand Data.

Major histocompatibility complex II (MHC II) molecules play a vital role in the onset and control of cellular immunity. In a highly selective process, MHC II presents peptides derived from exogenous antigens on the surface of antigen-presenting cells for T cell scrutiny. Understanding the rules defining this presentation holds critical insights into the regulation and potential manipulation of the cellular immune system. Here, we apply the NNAlign_MA machine learning framework to analyze and integrate large-scale eluted MHC II ligand mass spectrometry (MS) data sets to advance prediction of CD4+ epitopes. NNAlign_MA allows integration of mixed data types, handling ligands with multiple potential allele annotations, encoding of ligand context, leveraging information between data sets, and has pan-specific power allowing accurate predictions outside the set of molecules included in the training data. Applying this framework, we identified accurate binding motifs of more than 50 MHC class II molecules described by MS data, particularly expanding coverage for DP and DQ beyond that obtained using current MS motif deconvolution techniques. Furthermore, in large-scale benchmarking, the final model termed NetMHCIIpan-4.0 demonstrated improved performance beyond current state-of-the-art predictors for ligand and CD4+ T cell epitope prediction. These results suggest that NNAlign_MA and NetMHCIIpan-4.0 are powerful tools for analysis of immunopeptidome MS data, prediction of T cell epitopes, and development of personalized immunotherapies.

New therapeutic and diagnostic opportunities for injured tissue-specific targeting of complement inhibitors and imaging modalities.

Despite substantial opportunity and commercial interest in developing drugs that modulate the complement system in a broad range of non-orphan indications, several obstacles remain to be overcome. Among these issues is the biophysical nature of complement proteins, whose circulating levels are typically very high and whose turnover rates are relatively rapid, especially in the setting of chronic inflammatory conditions. This situation necessitates the use of very high levels of therapeutic compounds in order to achieve both multi-pathway and multiple effector mechanism inhibition. In addition, one must avoid infectious complications or the systemic impairment of the other important physiological functions of complement. Herein we focus on the development of a novel therapeutic strategy based on injured tissue-specific targeting of complement inhibitors using the antigen-combining domains of a small subset of natural IgM antibodies, which as endogenous antibodies specifically recognize sites of local damage across a broad range of tissues and locally activate complement C3, resulting in C3 fragment covalent fixation. Because the use of such recombinant tissue-targeting inhibitors precludes the utility of measuring systemic levels of complement biomarkers or function, since a goal of this targeting strategy is to leave those processes intact and unimpeded, we also briefly describe a new method designed to quantitatively measure using imaging modalities the inhibition of generation of fixed C3 fragments at sites of inflammation/injury. In addition to the ability to determine whether complement activation is locally constrained with the use of inhibitors, there is also a broader application of this imaging approach to inflammatory and autoimmune diseases characterized by local complement activation.

MHCquant: Automated and Reproducible Data Analysis for Immunopeptidomics.

Personalized multipeptide vaccines are currently being discussed intensively for tumor immunotherapy. In order to identify epitopes-short, immunogenic peptides-suitable for eliciting a tumor-specific immune response, human leukocyte antigen-presented peptides are isolated by immunoaffinity purification from cancer tissue samples and analyzed by liquid chromatography-coupled tandem mass spectrometry (LC-MS/MS). Here, we present MHCquant, a fully automated, portable computational pipeline able to process LC-MS/MS data automatically and generate annotated, false discovery rate-controlled lists of (neo-)epitopes with associated relative quantification information. We could show that MHCquant achieves higher sensitivity than established methods. While obtaining the highest number of unique peptides, the rate of predicted MHC binders remains still comparable to other tools. Reprocessing of the data from a previously published study resulted in the identification of several neoepitopes not detected by previously applied methods. MHCquant integrates tailor-made pipeline components with existing open-source software into a coherent processing workflow. Container-based virtualization permits execution of this workflow without complex software installation, execution on cluster/cloud infrastructures, and full reproducibility of the results. Integration with the data analysis workbench KNIME enables easy mining of large-scale immunopeptidomics data sets. MHCquant is available as open-source software along with accompanying documentation on our website at https://www.openms.de/mhcquant/ .

Neoepitopes: a new take on beta cell autoimmunity in type 1 diabetes.

Type 1 diabetes is an autoimmune disease caused by T cell-mediated destruction of pancreatic insulin-producing beta cells. The epitopes recognised by pathogenic T cells in human type 1 diabetes are poorly defined; however, a growing body of evidence suggests that T cell responses against neoepitopes contribute to beta cell destruction in type 1 diabetes. Neoepitopes are formed when self-proteins undergo post-translational modification to create a new epitope that is recognised by T- or B cells. Here we review the role of human T cell responses against neoepitopes in the immune pathogenesis of type 1 diabetes. Specifically, we review the different approaches to identifying neoepitopes relevant to human type 1 diabetes and outline several advances in this field that have occurred over the past few years. We also discuss the application of neoepitopes to the development of antigen-specific therapies for type 1 diabetes and the unresolved challenges that need to be overcome before the full repertoire of neoepitopes recognised by pathogenic human T cells in type 1 diabetes can be determined. This information may then be used to develop antigen-specific therapies for type 1 diabetes and assays to monitor changes in pathogenic, beta cell-specific T cell responses.

A Targeted LC-MS Strategy for Low-Abundant HLA Class-I-Presented Peptide Detection Identifies Novel Human Papillomavirus T-Cell Epitopes.

For rational design of therapeutic vaccines, detailed knowledge about target epitopes that are endogenously processed and truly presented on infected or transformed cells is essential. Many potential target epitopes (viral or mutation-derived), are presented at low abundance. Therefore, direct detection of these peptides remains a challenge. This study presents a method for the isolation and LC-MS3 -based targeted detection of low-abundant human leukocyte antigen (HLA) class-I-presented peptides from transformed cells. Human papillomavirus (HPV) was used as a model system, as the HPV oncoproteins E6 and E7 are attractive therapeutic vaccination targets and expressed in all transformed cells, but present at low abundance due to viral immune evasion mechanisms. The presented approach included preselection of target antigen-derived peptides by in silico predictions and in vitro binding assays. The peptide purification process was tailored to minimize contaminants after immunoprecipitation of HLA-peptide complexes, while keeping high isolation yields of low-abundant target peptides. The subsequent targeted LC-MS3 detection allowed for increased sensitivity, which resulted in successful detection of the known HLA-A2-restricted epitope E711-19 and ten additional E7-derived peptides on the surface of HPV16-transformed cells. T-cell reactivity was shown for all the 11 detected peptides in ELISpot assays, which shows that detection by our approach has high predictive value for immunogenicity. The presented strategy is suitable for validating even low-abundant candidate epitopes to be true immunotherapy targets.

CD11c+ MHCIIlo GM-CSF-bone marrow-derived dendritic cells act as antigen donor cells and as antigen presenting cells in neoepitope-elicited tumor immunity against a mouse fibrosarcoma.

Dendritic cells play a critical role in initiating T-cell responses. In spite of this recognition, they have not been used widely as adjuvants, nor is the mechanism of their adjuvanticity fully understood. Here, using a mutated neoepitope of a mouse fibrosarcoma as the antigen, and tumor rejection as the end point, we show that dendritic cells but not macrophages possess superior adjuvanticity. Several types of dendritic cells, such as bone marrow-derived dendritic cells (GM-CSF cultured or FLT3-ligand induced) or monocyte-derived ones, are powerful adjuvants, although GM-CSF-cultured cells show the highest activity. Among these, the CD11c+ MHCIIlo sub-set, distinguishable by a distinct transcriptional profile including a higher expression of heat shock protein receptors CD91 and LOX1, mannose receptors and TLRs, is significantly superior to the CD11c+ MHCIIhi sub-set. Finally, dendritic cells exert their adjuvanticity by acting as both antigen donor cells (i.e., antigen reservoirs) as well as antigen presenting cells.

Lost in the crowd: identifying targetable MHC class I neoepitopes for cancer immunotherapy.

INTRODUCTION: The recent development of checkpoint blockade immunotherapy for cancer has led to impressive clinical results across multiple tumor types. There is mounting evidence that immune recognition of tumor derived MHC class I (MHC-I) restricted epitopes bearing cancer specific mutations and alterations is a crucial mechanism in successfully triggering immune-mediated tumor rejection. Therapeutic targeting of these cancer specific epitopes (neoepitopes) is emerging as a promising opportunity for the generation of personalized cancer vaccines and adoptive T cell therapies. However, one major obstacle limiting the broader application of neoepitope based therapies is the difficulty of selecting highly immunogenic neoepitopes among the wide array of presented non-immunogenic HLA ligands derived from self-proteins. Areas covered: In this review, we present an overview of the MHC-I processing and presentation pathway, as well as highlight key areas that contribute to the complexity of the associated MHC-I peptidome. We cover recent technological advances that simplify and optimize the identification of targetable neoepitopes for cancer immunotherapeutic applications. Expert commentary: Recent advances in computational modeling, bioinformatics, and mass spectrometry are unlocking the underlying mechanisms governing antigen processing and presentation of tumor-derived neoepitopes.

Assessment of extracellular matrix-related biomarkers in patients with lower extremity artery disease.

BACKGROUND: The prevalence of lower extremity artery disease (LEAD) is high (20%-25%) in the population older than 65 years, but patients are seldom identified until the disease is advanced. Circulating markers of disease activity might provide patients with a key opportunity for timely treatment. We tested the hypothesis that measuring blood-specific fragments generated during degradation of the extracellular matrix (ECM) could provide further insight into the pathophysiologic mechanism of arterial remodeling. METHODS: The protein profile of diseased arteries from patients undergoing infrainguinal limb revascularization was assessed by a liquid chromatography and tandem mass spectrometry, nontargeted proteomic approach. The information retrieved was the basis for measurement of neoepitope fragments of ECM proteins in the blood of 195 consecutive patients with LEAD by specific enzyme-linked immunosorbent assays. RESULTS: Histologic and proteomic analyses confirmed the structural disorganization of affected arteries. Fourteen of 81 proteins were identified as differentially expressed in diseased arteries with respect to healthy tissues. Most of them were related to ECM components, and the difference in expression was used in multivariate analyses to establish that severe arterial lesions in LEAD patients have a specific proteome. Analysis of neoepitope fragments in blood revealed that fragments of versican and collagen type IV, alone or in combination, segregated patients with mild to moderate symptoms (intermittent claudication, Fontaine I-II) from those with severe LEAD (critical limb ischemia, Fontaine III-IV). CONCLUSIONS: We propose noninvasive candidate biomarkers with the ability to be clinically useful across the LEAD spectrum.

Population-level distribution and putative immunogenicity of cancer neoepitopes.

BACKGROUND: Tumor neoantigens are drivers of cancer immunotherapy response; however, current prediction tools produce many candidates requiring further prioritization. Additional filtration criteria and population-level understanding may assist with prioritization. Herein, we show neoepitope immunogenicity is related to measures of peptide novelty and report population-level behavior of these and other metrics. METHODS: We propose four peptide novelty metrics to refine predicted neoantigenicity: tumor vs. paired normal peptide binding affinity difference, tumor vs. paired normal peptide sequence similarity, tumor vs. closest human peptide sequence similarity, and tumor vs. closest microbial peptide sequence similarity. We apply these metrics to neoepitopes predicted from somatic missense mutations in The Cancer Genome Atlas (TCGA) and a cohort of melanoma patients, and to a group of peptides with neoepitope-specific immune response data using an extension of pVAC-Seq (Hundal et al., pVAC-Seq: a genome-guided in silico approach to identifying tumor neoantigens. Genome Med 8:11, 2016). RESULTS: We show neoepitope burden varies across TCGA diseases and HLA alleles, with surprisingly low repetition of neoepitope sequences across patients or neoepitope preferences among sets of HLA alleles. Only 20.3% of predicted neoepitopes across TCGA patients displayed novel binding change based on our binding affinity difference criteria. Similarity of amino acid sequence was typically high between paired tumor-normal epitopes, but in 24.6% of cases, neoepitopes were more similar to other human peptides, or bacterial (56.8% of cases) or viral peptides (15.5% of cases), than their paired normal counterparts. Applied to peptides with neoepitope-specific immune response, a linear model incorporating neoepitope binding affinity, protein sequence similarity between neoepitopes and their closest viral peptides, and paired binding affinity difference was able to predict immunogenicity (AUROC = 0.66). CONCLUSIONS: Our proposed prioritization criteria emphasize neoepitope novelty and refine patient neoepitope predictions for focus on biologically meaningful candidate neoantigens. We have demonstrated that neoepitopes should be considered not only with respect to their paired normal epitope, but to the entire human proteome, and bacterial and viral peptides, with potential implications for neoepitope immunogenicity and personalized vaccines for cancer treatment. We conclude that putative neoantigens are highly variable across individuals as a function of cancer genetics and personalized HLA repertoire, while the overall behavior of filtration criteria reflects predictable patterns.

Methylation-Based Classification of Cervical Squamous Cell Carcinoma into Two New Subclasses Differing in Immune-Related Gene Expression.

Cervical cancer is traditionally classified into two major histological subtypes, cervical squamous cell carcinoma (CSCC) and cervical adenocarcinoma (CA). However, heterogeneity exists among patients, comprising possible subpopulations with distinct molecular profiles. We applied consensus clustering to 307 methylation samples with cervical cancer from The Cancer Genome Atlas (TCGA). Fisher's exact test was used to perform transcription factors (TFs) and genomic region enrichment. Gene expression profiles were downloaded from TCGA to assess expression differences. Immune cell fraction was calculated to quantify the immune cells infiltration. Putative neo-epitopes were predicted from somatic mutations. Three subclasses were identified: Class 1 correlating with the CA subtype and Classes 2 and 3 dividing the CSCC subtype into two subclasses. We found the hypomethylated probes in Class 3 exhibited strong enrichment in promoter region as compared with Class 2. Five TFs significantly enriched in the hypomethylated promoters and their highly expressed target genes in Class 3 functionally involved in the immune pathway. Gene function analysis revealed that immune-related genes were significantly increased in Class 3, and a higher level of immune cell infiltration was estimated. High expression of 24 immune genes exhibited a better overall survival and correlated with neo-epitope burden. Additionally, we found only two immune-related driver genes, CARD11 and JAK3, to be significantly increased in Class 3. Our analyses provide a classification of the largest CSCC subtype into two new subclasses, revealing they harbored differences in immune-related gene expression.