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The study of tumour-specific antigens (TSAs) as targets for antitumour therapies has accelerated within the past decade. The most commonly studied class of TSAs are those derived from non-synonymous single-nucleotide variants (SNVs), or SNV neoantigens. However, to increase the repertoire of available therapeutic TSA targets, ‘alternative TSAs’, defined here as high-specificity tumour antigens arising from non-SNV genomic sources, have recently been evaluated. Among these alternative TSAs are antigens derived from mutational frameshifts, splice variants, gene fusions, endogenous retroelements and other processes. Unlike the patient-specific nature of SNV neoantigens, some alternative TSAs may have the advantage of being widely shared by multiple tumours, allowing for universal, off-the-shelf therapies. In this Opinion article, we will outline the biology, available computational tools, preclinical and/or clinical studies and relevant cancers for each alternative TSA class, as well as discuss both current challenges preventing the therapeutic application of alternative TSAs and potential solutions to aid in their clinical translation.

The ability to non-invasively monitor tumor-infiltrating T cells in vivo could provide a powerful tool to visualize and quantify tumor immune infiltrates. For non-invasive evaluations in vivo, an anti-CD3 mAb was modified with desferrioxamine (DFO) and radiolabeled with zirconium-89 (Zr-89 or 89Zr). Radiolabeled 89Zr-DFO-anti-CD3 was tested for T cell detection using positron emission tomography (PET) in both healthy mice and mice bearing syngeneic bladder cancer BBN975. In vivo PET/CT and ex vivo biodistribution demonstrated preferential accumulation and visualization of tracer in the spleen, thymus, lymph nodes, and bone marrow. In tumor bearing mice, 89Zr-DFO-anti-CD3 demonstrated an 11.5-fold increase in tumor-to-blood signal compared to isotype control. Immunological profiling demonstrated no significant change to total T cell count, but observed CD4+ T cell depletion and CD8+ T cell expansion to the central and effector memory. This was very encouraging since a high CD8+ to CD4+ T cell ratio has already been associated with better patient prognosis. Ultimately, this anti-CD3 mAb allowed for in vivo imaging of homeostatic T cell distribution, and more specifically tumor-infiltrating T cells. Future applications of this radiolabeled mAb against CD3 could include prediction and monitoring of patient response to immunotherapy.

Human endogenous retroviruses (hERVs) are remnants of exogenous retroviruses that have integrated into the genome throughout evolution. We developed a computational workflow, hervQuant, which identified more than 3,000 transcriptionally active hERVs within The Cancer Genome Atlas (TCGA) pan-cancer RNA-Seq database. hERV expression was associated with clinical prognosis in several tumor types, most significantly clear cell renal cell carcinoma (ccRCC). We explored two mechanisms by which hERV expression may influence the tumor immune microenvironment in ccRCC: (i) RIG-I-like signaling and (ii) retroviral antigen activation of adaptive immunity. We demonstrated the ability of hERV signatures associated with these immune mechanisms to predict patient survival in ccRCC, independent of clinical staging and molecular subtyping. We identified potential tumor-specific hERV epitopes with evidence of translational activity through the use of a ccRCC ribosome profiling (Ribo-Seq) dataset, validated their ability to bind HLA in vitro, and identified the presence of MHC tetramer-positive T cells against predicted epitopes. hERV sequences identified through this screening approach were significantly more highly expressed in ccRCC tumors responsive to treatment with programmed death receptor 1 (PD-1) inhibition. hervQuant provides insights into the role of hERVs within the tumor immune microenvironment, as well as evidence that hERV expression could serve as a biomarker for patient prognosis and response to immunotherapy.

Background Measures of the adaptive immune response have prognostic and predictive associations in melanoma and other cancer types. Specifically, intratumoral T cell density and function have considerable prognostic and predictive value in skin cutaneous melanoma (SKCM). Less is known about the significance of tumor-infiltrating B cells in SKCM. Our goal was to understand the prognostic and predictive value of B cell phenotypic subsets in SKCM using RNA sequencing. Methods We used our previously published algorithm, V’DJer, to assemble B cell receptor (BCR) repertoires and estimate diversity from short-read RNA sequencing (RNA-seq). We applied machine learning-based cellular phenotype classifiers to measure relative similarity of bulk tumor sample gene expression profiles and different B cell phenotypes. We assessed these aspects of B cell biology in 473 SKCM from the Cancer Genome Atlas Project (TCGA) as well as in RNA-seq data corresponding to tumor samples procured from patients who received CTLA-4 and PD-1 inhibitors for metastatic SKCM. Results We found that the BCR repertoire was associated with different clinical factors, such as tumor tissue site and sex. However, increased clonality of the BCR repertoire was favorably prognostic in SKCM and was prognostic even after first conditioning on various clinical factors. Mutation burden was not correlated with any BCR measurement, and no specific mutation had an altered BCR repertoire. Lack of an assembled BCR in pre-treatment tumor tissues was associated with a lack of anti-tumor response to a CTLA-4 inhibitor in metastatic SKCM. Conclusions These findings suggest an important prognostic and predictive role for B cell characteristics in SKCM. This has implications for melanoma immunobiology and potential development of immunogenomics features to predict survival and response to immunotherapy.

Although immune-checkpoint inhibitors (ICIs) have been a remarkable advancement in bladder cancer treatment, the response rate to single-agent ICIs remains suboptimal. There has been substantial interest in the use of epigenetic agents to enhance ICI efficacy, although precisely how these agents potentiate ICI response has not been fully elucidated. We identified entinostat, a selective HDAC1/3 inhibitor, as a potent antitumor agent in our immune-competent bladder cancer mouse models (BBN963 and BBN966). We demonstrate that entinostat selectively promoted immune editing of tumor neoantigens, effectively remodeling the tumor immune microenvironment, resulting in a robust antitumor response that was cell autonomous, dependent upon antigen presentation, and associated with increased numbers of neoantigen-specific T cells. Finally, combination treatment with anti-PD-1 and entinostat led to complete responses and conferred long-term immunologic memory. Our work defines a tumor cell-autonomous mechanism of action for entinostat and a strong preclinical rationale for the combined use of entinostat and PD-1 blockade in bladder cancer.

BP180, also termed collagen XVII, is a hemidesmosomal transmembrane glycoprotein expressed in basal keratinocytes, and functions as a cell–matrix adhesion molecule in the dermal–epidermal junction of the skin. Its function, other than cell–matrix adhesion, remains unclear. We generated a mouse strain with BP180 dysfunction (termed ∆NC16A ), which develops spontaneous skin inflammation accompanied by an influx of myeloid derived suppressor cells (MDSCs). We used the B16 mouse melanoma model to demonstrate that BP180 dysfunction in either skin or basal keratinocytes promotes MDSC influx into skin and tumor progression. MDSC depletion reduced tumor progression in ∆NC16A mice, demonstrating a critical role for BP180 dysfunction-driven MDSCs in melanoma progression. This study provides the first direct evidence that BP180, a cell–cell matrix adhesion molecule, possesses antitumor function through modulating infiltration of MDSCs. Basal keratinocytes actively participate in skin microenvironment changes caused by BP180 dysfunction. ∆NC16A mice could be a new animal model to study the melanoma microenvironment.

Background Early in the pandemic, we designed a SARS-CoV-2 peptide vaccine containing epitope regions optimized for concurrent B cell, CD4 + T cell, and CD8 + T cell stimulation. The rationale for this design was to drive both humoral and cellular immunity with high specificity while avoiding undesired effects such as antibody-dependent enhancement (ADE). Methods We explored the set of computationally predicted SARS-CoV-2 HLA-I and HLA-II ligands, examining protein source, concurrent human/murine coverage, and population coverage. Beyond MHC affinity, T cell vaccine candidates were further refined by predicted immunogenicity, sequence conservation, source protein abundance, and coverage of high frequency HLA alleles. B cell epitope regions were chosen from linear epitope mapping studies of convalescent patient serum, followed by filtering for surface accessibility, sequence conservation, spatial localization near functional domains of the spike glycoprotein, and avoidance of glycosylation sites. Results From 58 initial candidates, three B cell epitope regions were identified. From 3730 (MHC-I) and 5045 (MHC-II) candidate ligands, 292 CD8 + and 284 CD4 + T cell epitopes were identified. By combining these B cell and T cell analyses, as well as a manufacturability heuristic, we proposed a set of 22 SARS-CoV-2 vaccine peptides for use in subsequent murine studies. We curated a dataset of ~ 1000 observed T cell epitopes from convalescent COVID-19 patients across eight studies, showing 8/15 recurrent epitope regions to overlap with at least one of our candidate peptides. Of the 22 candidate vaccine peptides, 16 (n = 10 T cell epitope optimized; n = 6 B cell epitope optimized) were manually selected to decrease their degree of sequence overlap and then synthesized. The immunogenicity of the synthesized vaccine peptides was validated using ELISpot and ELISA following murine vaccination. Strong T cell responses were observed in 7/10 T cell epitope optimized peptides following vaccination. Humoral responses were deficient, likely due to the unrestricted conformational space inhabited by linear vaccine peptides. Conclusions Overall, we find our selection process and vaccine formulation to be appropriate for identifying T cell epitopes and eliciting T cell responses against those epitopes. Further studies are needed to optimize prediction and induction of B cell responses, as well as study the protective capacity of predicted T and B cell epitopes.

Metabolic reprogramming dictates the fate and function of stimulated T cells, yet these pathways can be suppressed in T cells in tumor microenvironments. We previously showed that glycolytic and mitochondrial adaptations directly contribute to reducing the effector function of renal cell carcinoma (RCC) CD8+ tumor-infiltrating lymphocytes (TILs). Here we define the role of these metabolic pathways in the activation and effector functions of CD8+ RCC TILs. CD28 costimulation plays a key role in augmenting T cell activation and metabolism, and is antagonized by the inhibitory and checkpoint immunotherapy receptors CTLA4 and PD-1. While RCC CD8+ TILs were activated at a low level when stimulated through the T cell receptor alone, addition of CD28 costimulation greatly enhanced activation, function, and proliferation. CD28 costimulation reprogrammed RCC CD8+ TIL metabolism with increased glycolysis and mitochondrial oxidative metabolism, possibly through upregulation of GLUT3. Mitochondria also fused to a greater degree, with higher membrane potential and overall mass. These phenotypes were dependent on glucose metabolism, as the glycolytic inhibitor 2-deoxyglucose both prevented changes to mitochondria and suppressed RCC CD8+ TIL activation and function. These data show that CD28 costimulation can restore RCC CD8+ TIL metabolism and function through rescue of T cell glycolysis that supports mitochondrial mass and activity.

Motivation Splice variant neoantigens are a potential source of tumor-specific antigen (TSA) that are shared between patients in a variety of cancers, including acute myeloid leukemia. Current tools for genomic prediction of splice variant neoantigens demonstrate promise. However, many tools have not been well validated with simulated and/or wet lab approaches, with no studies published that have presented a targeted immunopeptidome mass spectrometry approach designed specifically for identification of predicted splice variant neoantigens. Results In this study, we describe NeoSplice, a novel computational method for splice variant neoantigen prediction based on (i) prediction of tumor-specific k-mers from RNA-seq data, (ii) alignment of differentially expressed k-mers to the splice graph and (iii) inference of the variant transcript with MHC binding prediction. NeoSplice demonstrates high sensitivity and precision (>80% on average across all splice variant classes) through in silico simulated RNA-seq data. Through mass spectrometry analysis of the immunopeptidome of the K562.A2 cell line compared against a synthetic peptide reference of predicted splice variant neoantigens, we validated 4 of 37 predicted antigens corresponding to 3 of 17 unique splice junctions. Lastly, we provide a comparison of NeoSplice against other splice variant prediction tools described in the literature. NeoSplice provides a well-validated platform for prediction of TSA vaccine targets for future cancer antigen vaccine studies to evaluate the clinical efficacy of splice variant neoantigens. Availability and implementation https://github.com/Benjamin-Vincent-Lab/NeoSplice Supplementary information Supplementary data are available at Bioinformatics Advances online.

Predicting response to ICI therapy among patients with renal cell carcinoma (RCC) has been uniquely challenging. We analyzed patient characteristics and clinical correlates from a retrospective single-site cohort of advanced RCC patients receiving anti-PD-1/PD-L1 monotherapy (N = 97), as well as molecular parameters in a subset of patients, including multiplexed immunofluorescence (mIF), whole exome sequencing (WES), T cell receptor (TCR) sequencing, and RNA sequencing (RNA-seq). Clinical factors such as the development of immune-related adverse events (odds ratio (OR) = 2.50, 95% confidence interval (CI) = 1.05–5.91) and immunological prognostic parameters, including a higher percentage of circulating lymphocytes (23.4% vs. 17.4%, p = 0.0015) and a lower percentage of circulating neutrophils (61.8% vs. 68.5%, p = 0.0045), correlated with response. Previously identified gene expression signatures representing pathways of angiogenesis, myeloid inflammation, T effector presence, and clear cell signatures also correlated with response. High PD-L1 expression (>10% cells) as well as low TCR diversity (≤644 clonotypes) were associated with improved progression-free survival (PFS). We corroborate previously published findings and provide preliminary evidence of T cell clonality impacting the outcome of RCC patients. To further biomarker development in RCC, future studies will benefit from integrated analysis of multiple molecular platforms and prospective validation.