LENS: Landscape of Effective Neoantigens Software.

MOTIVATION: Elimination of cancer cells by T cells is a critical mechanism of anti-tumor immunity and cancer immunotherapy response. T cells recognize cancer cells by engagement of T cell receptors with peptide epitopes presented by major histocompatibility complex molecules on the cancer cell surface. Peptide epitopes can be derived from antigen proteins coded for by multiple genomic sources. Bioinformatics tools used to identify tumor-specific epitopes via analysis of DNA and RNA-sequencing data have largely focused on epitopes derived from somatic variants, though a smaller number have evaluated potential antigens from other genomic sources. RESULTS: We report here an open-source workflow utilizing the Nextflow DSL2 workflow manager, Landscape of Effective Neoantigens Software (LENS), which predicts tumor-specific and tumor-associated antigens from single nucleotide variants, insertions and deletions, fusion events, splice variants, cancer-testis antigens, overexpressed self-antigens, viruses, and endogenous retroviruses. The primary advantage of LENS is that it expands the breadth of genomic sources of discoverable tumor antigens using genomics data. Other advantages include modularity, extensibility, ease of use, and harmonization of relative expression level and immunogenicity prediction across multiple genomic sources. We present an analysis of 115 acute myeloid leukemia samples to demonstrate the utility of LENS. We expect LENS will be a valuable platform and resource for T cell epitope discovery bioinformatics, especially in cancers with few somatic variants where tumor-specific epitopes from alternative genomic sources are an elevated priority. AVAILABILITY AND IMPLEMENTATION: More information about LENS, including code, workflow documentation, and instructions, can be found at (https://gitlab.com/landscape-of-effective-neoantigens-software).

NeoSplice: a bioinformatics method for prediction of splice variant neoantigens.

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.

Entinostat induces antitumor immune responses through immune editing of tumor neoantigens.

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.

Landscape and selection of vaccine epitopes in SARS-CoV-2.

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.

Clinical Features and Multiplatform Molecular Analysis Assist in Understanding Patient Response to Anti-PD-1/PD-L1 in Renal Cell Carcinoma.

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.

A High-Avidity T-cell Receptor Redirects Natural Killer T-cell Specificity and Outcompetes the Endogenous Invariant T-cell Receptor.

T-cell receptor (TCR) gene transfer redirects T cells to target intracellular antigens. However, the potential autoreactivity generated by TCR mispairing and occurrence of graft-versus-host disease in the allogenic setting due to the retention of native TCRs remain major concerns. Natural killer T cells (NKT) have shown promise as a platform for adoptive T-cell therapy in cancer patients. Here, we showed their utility for TCR gene transfer. We successfully engineered and expanded NKTs expressing a functional TCR (TCR NKTs), showing HLA-restricted antitumor activity in xenogeneic mouse models in the absence of graft-versus-mouse reactions. We found that TCR NKTs downregulated the invariant TCR (iTCR), leading to iTCR+TCR+ and iTCR-TCR+ populations. In-depth analyses of these subsets revealed that in iTCR-TCR+ NKTs, the iTCR, although expressed at the mRNA and protein levels, was retained in the cytoplasm. This effect resulted from a competition for binding to CD3 molecules for cell-surface expression by the transgenic TCR. Overall, our results highlight the feasibility and advantages of using NKTs for TCR expression for adoptive cell immunotherapies. NKT-low intrinsic alloreactivity that associated with the observed iTCR displacement by the engineered TCR represents ideal characteristics for "off-the-shelf" products without further TCR gene editing.

CD28 costimulation drives tumor-infiltrating T cell glycolysis to promote inflammation.

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.

Landscape and Selection of Vaccine Epitopes in SARS-CoV-2.

There is an urgent need for a vaccine with efficacy against SARS-CoV-2. We hypothesize that peptide vaccines containing epitope regions optimized for concurrent B cell, CD4+ T cell, and CD8+ T cell stimulation would drive both humoral and cellular immunity with high specificity, potentially avoiding undesired effects such as antibody-dependent enhancement (ADE). Additionally, such vaccines can be rapidly manufactured in a distributed manner. In this study, we combine computational prediction of T cell epitopes, recently published B cell epitope mapping studies, and epitope accessibility to select candidate peptide vaccines for SARS-CoV-2. We begin with an exploration of the space of possible T cell epitopes in SARS-CoV-2 with interrogation of predicted HLA-I and HLA-II ligands, overlap between predicted ligands, protein source, as well as concurrent human/murine coverage. Beyond MHC affinity, T cell vaccine candidates were further refined by predicted immunogenicity, viral source protein abundance, sequence conservation, coverage of high frequency HLA alleles and co-localization of CD4+ and CD8+ T cell epitopes. B cell epitope regions were chosen from linear epitope mapping studies of convalescent patient serum, followed by filtering to select regions with surface accessibility, high sequence conservation, spatial localization near functional domains of the spike glycoprotein, and avoidance of glycosylation sites. From 58 initial candidates, three B cell epitope regions were identified. By combining these B cell and T cell analyses, as well as a manufacturability heuristic, we propose a set of SARS-CoV-2 vaccine peptides for use in subsequent murine studies and clinical trials.

Alternative tumour-specific antigens.

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.

Prognostic value of B cells in cutaneous melanoma.

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.

The dysfunction of BP180/collagen XVII in keratinocytes promotes melanoma progression.

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.

Machine-Learning Prediction of Tumor Antigen Immunogenicity in the Selection of Therapeutic Epitopes.

Current tumor neoantigen calling algorithms primarily rely on epitope/major histocompatibility complex (MHC) binding affinity predictions to rank and select for potential epitope targets. These algorithms do not predict for epitope immunogenicity using approaches modeled from tumor-specific antigen data. Here, we describe peptide-intrinsic biochemical features associated with neoantigen and minor histocompatibility mismatch antigen immunogenicity and present a gradient boosting algorithm for predicting tumor antigen immunogenicity. This algorithm was validated in two murine tumor models and demonstrated the capacity to select for therapeutically active antigens. Immune correlates of neoantigen immunogenicity were studied in a pan-cancer data set from The Cancer Genome Atlas and demonstrated an association between expression of immunogenic neoantigens and immunity in colon and lung adenocarcinomas. Lastly, we present evidence for expression of an out-of-frame neoantigen that was capable of driving antitumor cytotoxic T-cell responses. With the growing clinical importance of tumor vaccine therapies, our approach may allow for better selection of therapeutically relevant tumor-specific antigens, including nonclassic out-of-frame antigens capable of driving antitumor immunity.

CD30-Redirected Chimeric Antigen Receptor T Cells Target CD30+ and CD30- Embryonal Carcinoma via Antigen-Dependent and Fas/FasL Interactions.

Tumor antigen heterogeneity limits success of chimeric antigen receptor (CAR) T-cell therapies. Embryonal carcinomas (EC) and mixed testicular germ cell tumors (TGCT) containing EC, which are the most aggressive TGCT subtypes, are useful for dissecting this issue as ECs express the CD30 antigen but also contain CD30-/dim cells. We found that CD30-redirected CAR T cells (CD30.CAR T cells) exhibit antitumor activity in vitro against the human EC cell lines Tera-1, Tera-2, and NCCIT and putative EC stem cells identified by Hoechst dye staining. Cytolytic activity of CD30.CAR T cells was complemented by their sustained proliferation and proinflammatory cytokine production. CD30.CAR T cells also demonstrated antitumor activity in an in vivo xenograft NOD/SCID/γcnull (NSG) mouse model of metastatic EC. We observed that CD30.CAR T cells, while targeting CD30+ EC tumor cells through the CAR (i.e., antigen-dependent targeting), also eliminated surrounding CD30- EC cells in an antigen-independent manner, via a cell-cell contact-dependent Fas/FasL interaction. In addition, ectopic Fas (CD95) expression in CD30+ Fas- EC was sufficient to improve CD30.CAR T-cell antitumor activity. Overall, these data suggest that CD30.CAR T cells might be useful as an immunotherapy for ECs. Additionally, Fas/FasL interaction between tumor cells and CAR T cells can be exploited to reduce tumor escape due to heterogeneous antigen expression or to improve CAR T-cell antitumor activity. Cancer Immunol Res; 6(10); 1274-87. ©2018 AACR.

Immuno-PET imaging of tumor-infiltrating lymphocytes using zirconium-89 radiolabeled anti-CD3 antibody in immune-competent mice bearing syngeneic tumors.

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.

A Dual Immunotherapy Nanoparticle Improves T-Cell Activation and Cancer Immunotherapy.

Combination immunotherapy has recently emerged as a powerful cancer treatment strategy. A promising treatment approach utilizes coadministration of antagonistic antibodies to block checkpoint inhibitor receptors, such as antiprogrammed cell death-1 (aPD1), alongside agonistic antibodies to activate costimulatory receptors, such as antitumor necrosis factor receptor superfamily member 4 (aOX40). Optimal T-cell activation is achieved when both immunomodulatory agents simultaneously engage T-cells and promote synergistic proactivation signaling. However, standard administration of these therapeutics as free antibodies results in suboptimal T-cell binding events, with only a subset of the T-cells binding to both aPD1 and aOX40. Here, it is shown that precise spatiotemporal codelivery of aPD1 and aOX40 using nanoparticles (NP) (dual immunotherapy nanoparticles, DINP) results in improved T-cell activation, enhanced therapeutic efficacy, and increased immunological memory. It is demonstrated that DINP elicits higher rates of T-cell activation in vitro than free antibodies. Importantly, it is demonstrated in two tumor models that combination immunotherapy administered in the form of DINP is more effective than the same regimen administered as free antibodies. This work demonstrates a novel strategy to improve combination immunotherapy using nanotechnology.

Endogenous retrovirus expression is associated with response to immune checkpoint blockade in clear cell renal cell carcinoma.

Although a subset of clear cell renal cell carcinoma (ccRCC) patients respond to immune checkpoint blockade (ICB), predictors of response remain uncertain. We investigated whether abnormal expression of endogenous retroviruses (ERVs) in tumors is associated with local immune checkpoint activation (ICA) and response to ICB. Twenty potentially immunogenic ERVs (πERVs) were identified in ccRCC in The Cancer Genome Atlas data set, and tumors were stratified into 3 groups based on their expression levels. πERV-high ccRCC tumors showed increased immune infiltration, checkpoint pathway upregulation, and higher CD8+ T cell fraction in infiltrating leukocytes compared with πERV-low ccRCC tumors. Similar results were observed in ER+/HER2- breast, colon, and head and neck squamous cell cancers. ERV expression correlated with expression of genes associated with histone methylation and chromatin regulation, and πERV-high ccRCC was enriched in BAP1 mutant tumors. ERV3-2 expression correlated with ICA in 11 solid cancers, including the 4 named above. In a small retrospective cohort of 24 metastatic ccRCC patients treated with single-agent PD-1/PD-L1 blockade, ERV3-2 expression in tumors was significantly higher in responders compared with nonresponders. Thus, abnormal expression of πERVs is associated with ICA in several solid cancers, including ccRCC, and ERV3-2 expression is associated with response to ICB in ccRCC.

Molecular Subtype-Specific Immunocompetent Models of High-Grade Urothelial Carcinoma Reveal Differential Neoantigen Expression and Response to Immunotherapy.

High-grade urothelial cancer contains intrinsic molecular subtypes that exhibit differences in underlying tumor biology and can be divided into luminal-like and basal-like subtypes. We describe here the first subtype-specific murine models of bladder cancer and show that Upk3a-CreERT2; Trp53L/L; PtenL/L; Rosa26LSL-Luc (UPPL, luminal-like) and BBN (basal-like) tumors are more faithful to human bladder cancer than the widely used MB49 cells. Following engraftment into immunocompetent C57BL/6 mice, BBN tumors were more responsive to PD-1 inhibition than UPPL tumors. Responding tumors within the BBN model showed differences in immune microenvironment composition, including increased ratios of CD8+:CD4+ and memory:regulatory T cells. Finally, we predicted and confirmed immunogenicity of tumor neoantigens in each model. These UPPL and BBN models will be a valuable resource for future studies examining bladder cancer biology and immunotherapy.Significance: This work establishes human-relevant mouse models of bladder cancer. Cancer Res; 78(14); 3954-68. ©2018 AACR.

Endogenous retroviral signatures predict immunotherapy response in clear cell renal cell carcinoma.

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.

The Cancer Genome Atlas Comprehensive Molecular Characterization of Renal Cell Carcinoma.

Renal cell carcinoma (RCC) is not a single disease, but several histologically defined cancers with different genetic drivers, clinical courses, and therapeutic responses. The current study evaluated 843 RCC from the three major histologic subtypes, including 488 clear cell RCC, 274 papillary RCC, and 81 chromophobe RCC. Comprehensive genomic and phenotypic analysis of the RCC subtypes reveals distinctive features of each subtype that provide the foundation for the development of subtype-specific therapeutic and management strategies for patients affected with these cancers. Somatic alteration of BAP1, PBRM1, and PTEN and altered metabolic pathways correlated with subtype-specific decreased survival, while CDKN2A alteration, increased DNA hypermethylation, and increases in the immune-related Th2 gene expression signature correlated with decreased survival within all major histologic subtypes. CIMP-RCC demonstrated an increased immune signature, and a uniform and distinct metabolic expression pattern identified a subset of metabolically divergent (MD) ChRCC that associated with extremely poor survival.