The peptide woods are lovely, dark and deep: Hunting for novel cancer antigens.

Harnessing the patient's immune system to control a tumor is a proven avenue for cancer therapy. T cell therapies as well as therapeutic vaccines, which target specific antigens of interest, are being explored as treatments in conjunction with immune checkpoint blockade. For these therapies, selecting the best suited antigens is crucial. Most of the focus has thus far been on neoantigens that arise from tumor-specific somatic mutations. Although there is clear evidence that T-cell responses against mutated neoantigens are protective, the large majority of these mutations are not immunogenic. In addition, most somatic mutations are unique to each individual patient and their targeting requires the development of individualized approaches. Therefore, novel antigen types are needed to broaden the scope of such treatments. We review high throughput approaches for discovering novel tumor antigens and some of the key challenges associated with their detection, and discuss considerations when selecting tumor antigens to target in the clinic.

Graph-pMHC: graph neural network approach to MHC class II peptide presentation and antibody immunogenicity.

Antigen presentation on MHC class II (pMHCII presentation) plays an essential role in the adaptive immune response to extracellular pathogens and cancerous cells. But it can also reduce the efficacy of large-molecule drugs by triggering an anti-drug response. Significant progress has been made in pMHCII presentation modeling due to the collection of large-scale pMHC mass spectrometry datasets (ligandomes) and advances in machine learning. Here, we develop graph-pMHC, a graph neural network approach to predict pMHCII presentation. We derive adjacency matrices for pMHCII using Alphafold2-multimer and address the peptide-MHC binding groove alignment problem with a simple graph enumeration strategy. We demonstrate that graph-pMHC dramatically outperforms methods with suboptimal inductive biases, such as the multilayer-perceptron-based NetMHCIIpan-4.0 (+20.17% absolute average precision). Finally, we create an antibody drug immunogenicity dataset from clinical trial data and develop a method for measuring anti-antibody immunogenicity risk using pMHCII presentation models. Our model increases receiver operating characteristic curve (ROC)-area under the ROC curve (AUC) by 2.57% compared to just filtering peptides by hits in OASis alone for predicting antibody drug immunogenicity.

Chromatin architecture and the generation of antigen receptor diversity.

The adaptive immune system generates a specific response to a vast spectrum of antigens. This remarkable property is achieved by lymphocytes that each express single and unique antigen receptors. During lymphocyte development, antigen receptor coding elements are assembled from widely dispersed gene segments. The assembly of antigen receptors is controlled at multiple levels, including epigenetic marking, nuclear location, and chromatin topology. Here, we review recently uncovered mechanisms that underpin long-range genomic interactions and the generation of antigen receptor diversity.

TGFß attenuates tumour response to PD-L1 blockade by contributing to exclusion of T cells.

Therapeutic antibodies that block the programmed death-1 (PD-1)-programmed death-ligand 1 (PD-L1) pathway can induce robust and durable responses in patients with various cancers, including metastatic urothelial cancer. However, these responses only occur in a subset of patients. Elucidating the determinants of response and resistance is key to improving outcomes and developing new treatment strategies. Here we examined tumours from a large cohort of patients with metastatic urothelial cancer who were treated with an anti-PD-L1 agent (atezolizumab) and identified major determinants of clinical outcome. Response to treatment was associated with CD8+ T-effector cell phenotype and, to an even greater extent, high neoantigen or tumour mutation burden. Lack of response was associated with a signature of transforming growth factor ß (TGFß) signalling in fibroblasts. This occurred particularly in patients with tumours, which showed exclusion of CD8+ T cells from the tumour parenchyma that were instead found in the fibroblast- and collagen-rich peritumoural stroma; a common phenotype among patients with metastatic urothelial cancer. Using a mouse model that recapitulates this immune-excluded phenotype, we found that therapeutic co-administration of TGFß-blocking and anti-PD-L1 antibodies reduced TGFß signalling in stromal cells, facilitated T-cell penetration into the centre of tumours, and provoked vigorous anti-tumour immunity and tumour regression. Integration of these three independent biological features provides the best basis for understanding patient outcome in this setting and suggests that TGFß shapes the tumour microenvironment to restrain anti-tumour immunity by restricting T-cell infiltration.

In silico tools for accurate HLA and KIR inference from clinical sequencing data empower immunogenetics on individual-patient and population scales.

Immunogenetic variation in humans is important in research, clinical diagnosis and increasingly a target for therapeutic intervention. Two highly polymorphic loci play critical roles, namely the human leukocyte antigen (HLA) system, which is the human version of the major histocompatibility complex (MHC), and the Killer-cell immunoglobulin-like receptors (KIR) that are relevant for responses of natural killer (NK) and some subsets of T cells. Their accurate classification has typically required the use of dedicated biological specimens and a combination of in vitro and in silico efforts. Increased availability of next generation sequencing data has led to the development of ancillary computational solutions. Here, we report an evaluation of recently published algorithms to computationally infer complex immunogenetic variation in the form of HLA alleles and KIR haplotypes from whole-genome or whole-exome sequencing data. For both HLA allele and KIR gene typing, we identified tools that yielded >97% overall accuracy for four-digit HLA types, and >99% overall accuracy for KIR gene presence, suggesting the readiness of in silico solutions for use in clinical and high-throughput research settings.

The 3D structure of the immunoglobulin heavy-chain locus: implications for long-range genomic interactions.

The immunoglobulin heavy-chain (Igh) locus is organized into distinct regions that contain multiple variable (V(H)), diversity (D(H)), joining (J(H)) and constant (C(H)) coding elements. How the Igh locus is structured in 3D space is unknown. To probe the topography of the Igh locus, spatial distance distributions were determined between 12 genomic markers that span the entire Igh locus. Comparison of the distance distributions to computer simulations of alternative chromatin arrangements predicted that the Igh locus is organized into compartments containing clusters of loops separated by linkers. Trilateration and triple-point angle measurements indicated the mean relative 3D positions of the V(H), D(H), J(H), and C(H) elements, showed compartmentalization and striking conformational changes involving V(H) and D(H)-J(H) elements during early B cell development. In pro-B cells, the entire repertoire of V(H) regions (2 Mbp) appeared to have merged and juxtaposed to the D(H) elements, mechanistically permitting long-range genomic interactions to occur with relatively high frequency.

A global network of transcription factors, involving E2A, EBF1 and Foxo1, that orchestrates B cell fate.

It is now established that the transcription factors E2A, EBF1 and Foxo1 have critical roles in B cell development. Here we show that E2A and EBF1 bound regulatory elements present in the Foxo1 locus. E2A and EBF1, as well as E2A and Foxo1, in turn, were wired together by a vast spectrum of cis-regulatory sequences. These associations were dynamic during developmental progression. Occupancy by the E2A isoform E47 directly resulted in greater abundance, as well as a pattern of monomethylation of histone H3 at lysine 4 (H3K4) across putative enhancer regions. Finally, we divided the pro-B cell epigenome into clusters of loci with occupancy by E2A, EBF and Foxo1. From this analysis we constructed a global network consisting of transcriptional regulators, signaling and survival factors that we propose orchestrates B cell fate.

Multilineage priming of enhancer repertoires precedes commitment to the B and myeloid cell lineages in hematopoietic progenitors.

Recent studies have documented genome-wide binding patterns of transcriptional regulators and their associated epigenetic marks in hematopoietic cell lineages. In order to determine how epigenetic marks are established and maintained during developmental progression, we have generated long-term cultures of hematopoietic progenitors by enforcing the expression of the E-protein antagonist Id2. Hematopoietic progenitors that express Id2 are multipotent and readily differentiate upon withdrawal of Id2 expression into committed B lineage cells, thus indicating a causative role for E2A (Tcf3) in promoting the B cell fate. Genome-wide analyses revealed that a substantial fraction of lymphoid and myeloid enhancers are premarked by the poised or active enhancer mark H3K4me1 in multipotent progenitors. Thus, in hematopoietic progenitors, multilineage priming of enhancer elements precedes commitment to the lymphoid or myeloid cell lineages.

Predicting immunogenic tumour mutations by combining mass spectrometry and exome sequencing.

Human tumours typically harbour a remarkable number of somatic mutations. If presented on major histocompatibility complex class I molecules (MHCI), peptides containing these mutations could potentially be immunogenic as they should be recognized as 'non-self' neo-antigens by the adaptive immune system. Recent work has confirmed that mutant peptides can serve as T-cell epitopes. However, few mutant epitopes have been described because their discovery required the laborious screening of patient tumour-infiltrating lymphocytes for their ability to recognize antigen libraries constructed following tumour exome sequencing. We sought to simplify the discovery of immunogenic mutant peptides by characterizing their general properties. We developed an approach that combines whole-exome and transcriptome sequencing analysis with mass spectrometry to identify neo-epitopes in two widely used murine tumour models. Of the >1,300 amino acid changes identified, ∼13% were predicted to bind MHCI, a small fraction of which were confirmed by mass spectrometry. The peptides were then structurally modelled bound to MHCI. Mutations that were solvent-exposed and therefore accessible to T-cell antigen receptors were predicted to be immunogenic. Vaccination of mice confirmed the approach, with each predicted immunogenic peptide yielding therapeutically active T-cell responses. The predictions also enabled the generation of peptide-MHCI dextramers that could be used to monitor the kinetics and distribution of the anti-tumour T-cell response before and after vaccination. These findings indicate that a suitable prediction algorithm may provide an approach for the pharmacodynamic monitoring of T-cell responses as well as for the development of personalized vaccines in cancer patients.

Nuclear positioning rather than contraction controls ordered rearrangements of immunoglobulin loci.

Progenitor-B cells recombine their immunoglobulin (Ig) loci to create unique antigen receptors. Despite a common recombination machinery, the Ig heavy and Ig light chain loci rearrange in a stepwise manner. We studied pre-pro-B cells and Rag(-/-) progenitor-B cells to determine whether Ig locus contraction or nuclear positioning is decisive for stepwise rearrangements. We found that both Ig loci were contracted in pro-B and pre-B cells. Igh relocated from the nuclear lamina to central domains only at the pro-B cell stage, whereas, Igκ remained sequestered at the lamina, and only at the pre-B cell stage located to central nuclear domains. Finally, in vitro induced re-positioning of Ig alleles away from the nuclear periphery increased germline transcription of Ig loci in pre-pro-B cells. Thus, Ig locus contraction juxtaposes genomically distant elements to mediate efficient recombination, however, sequential positioning of Ig loci away from the nuclear periphery determines stage-specific accessibility of Ig loci.

Building proteomic tool boxes to monitor MHC class I and class II peptides.

Major histocompatibility complex Class I (MHCI) and Class II (MHCII) presented peptides powerfully modulate T cell immunity and play a vital role in generating effective anti-tumor and anti-viral immune responses in mammals. Characterizing these MHCI or MHCII presented peptides can help generate therapeutic treatments, afford information on T cell mediated biomarkers, provide insight into disease progression, and reduce adverse anti-drug side effects from engineered biotherapeutics. Here, we explore the tools and techniques commonly employed to discover both MHCI- and MHCII-presented peptides. We describe complementary strategies that enhance the characterization of these peptides and the informatics tools employed for both predicting and characterizing MHCI- and MHCII-presented epitopes. The evolution of methodologies for isolating MHC-presented peptides is discussed, as are the mass spectrometric workflows that can be employed for their characterization. We provide a perspective on where this field is headed, and how these tools may be applicable to the discovery and monitoring of epitopes in a variety of scenarios.

The effects of hepatitis B virus integration into the genomes of hepatocellular carcinoma patients.

Hepatitis B virus (HBV) infection is a leading risk factor for hepatocellular carcinoma (HCC). HBV integration into the host genome has been reported, but its scale, impact and contribution to HCC development is not clear. Here, we sequenced the tumor and nontumor genomes (>80× coverage) and transcriptomes of four HCC patients and identified 255 HBV integration sites. Increased sequencing to 240× coverage revealed a proportionally higher number of integration sites. Clonal expansion of HBV-integrated hepatocytes was found specifically in tumor samples. We observe a diverse collection of genomic perturbations near viral integration sites, including direct gene disruption, viral promoter-driven human transcription, viral-human transcript fusion, and DNA copy number alteration. Thus, we report the most comprehensive characterization of HBV integration in hepatocellular carcinoma patients. Such widespread random viral integration will likely increase carcinogenic opportunities in HBV-infected individuals.

Genome and transcriptome sequencing of lung cancers reveal diverse mutational and splicing events.

Lung cancer is a highly heterogeneous disease in terms of both underlying genetic lesions and response to therapeutic treatments. We performed deep whole-genome sequencing and transcriptome sequencing on 19 lung cancer cell lines and three lung tumor/normal pairs. Overall, our data show that cell line models exhibit similar mutation spectra to human tumor samples. Smoker and never-smoker cancer samples exhibit distinguishable patterns of mutations. A number of epigenetic regulators, including KDM6A, ASH1L, SMARCA4, and ATAD2, are frequently altered by mutations or copy number changes. A systematic survey of splice-site mutations identified 106 splice site mutations associated with cancer specific aberrant splicing, including mutations in several known cancer-related genes. RAC1b, an isoform of the RAC1 GTPase that includes one additional exon, was found to be preferentially up-regulated in lung cancer. We further show that its expression is significantly associated with sensitivity to a MAP2K (MEK) inhibitor PD-0325901. Taken together, these data present a comprehensive genomic landscape of a large number of lung cancer samples and further demonstrate that cancer-specific alternative splicing is a widespread phenomenon that has potential utility as therapeutic biomarkers. The detailed characterizations of the lung cancer cell lines also provide genomic context to the vast amount of experimental data gathered for these lines over the decades, and represent highly valuable resources for cancer biology.

Pattern recognition receptor agonists in pathogen vaccines mediate antitumor T-cell cross-priming.

BACKGROUND: Cancer immunotherapies are generally effective in patients whose tumors contain a priori primed T-cells reactive to tumor antigens (TA). One approach to prime TA-reactive T-cells is to administer immunostimulatory molecules, cells, or pathogens directly to the tumor site, that is, in situ vaccination (ISV). We recently described an ISV using Flt3L to expand and recruit dendritic cells (DC), radiotherapy to load DC with TA, and pattern recognition receptor agonists (PRRa) to activate TA-loaded DC. While ISV trials using synthetic PRRa have yielded systemic tumor regressions, the optimal method to activate DCs is unknown. METHODS: To discover optimal DC activators and increase access to clinical grade reagents, we assessed whether viral or bacterial components found in common pathogen vaccines are an effective source of natural PRRa (naPRRa). Using deep profiling (155-metric) of naPRRa immunomodulatory effects and gene editing of specific PRR, we defined specific signatures and molecular mechanisms by which naPRRa potentiate T-cell priming. RESULTS: We observed that vaccine naPRRa can be even more potent in activating Flt3L-expanded murine and human DCs than synthetic PRRa, promoting cross-priming of TA-reactive T-cells. We developed a mechanistically diverse naPRRa combination (BCG, PedvaxHIB, Rabies) and noted more potent T-cell cross-priming than with any single naPRRa. The naPRRa triplet-as part of Flt3L-primed ISV-induced greater intratumoral CD8 T-cell infiltration, T-cells reactive to a newly defined tumorous neoantigen, durable tumor regressions. CONCLUSIONS: This work provides rationale for the translation of pathogen vaccines as FDA-approved clinical-grade DC activators which could be exploited as immune-stimulants for early phase trials.

Tumor-intrinsic expression of the autophagy gene Atg16l1 suppresses anti-tumor immunity in colorectal cancer.

Microsatellite-stable colorectal cancer (MSS-CRC) is highly refractory to immunotherapy. Understanding tumor-intrinsic determinants of immunotherapy resistance is critical to improve MSS-CRC patient outcomes. Here, we demonstrate that high tumor expression of the core autophagy gene ATG16L1 is associated with poor clinical response to anti-PD-L1 therapy in KRAS-mutant tumors from IMblaze370 (NCT02788279), a large phase III clinical trial of atezolizumab (anti-PD-L1) in advanced metastatic MSS-CRC. Deletion of Atg16l1 in engineered murine colon cancer organoids inhibits tumor growth in primary (colon) and metastatic (liver and lung) niches in syngeneic female hosts, primarily due to increased sensitivity to IFN-γ-mediated immune pressure. ATG16L1 deficiency enhances programmed cell death of colon cancer organoids induced by IFN-γ and TNF, thus increasing their sensitivity to host immunity. In parallel, ATG16L1 deficiency reduces tumor stem-like populations in vivo independently of adaptive immune pressure. This work reveals autophagy as a clinically relevant mechanism of immune evasion and tumor fitness in MSS-CRC and provides a rationale for autophagy inhibition to boost immunotherapy responses in the clinic.

Complementary proteomic tools for the dissection of apoptotic proteolysis events.

Proteolysis is a key regulatory event that controls intracellular and extracellular signaling through irreversible changes in a protein's structure that greatly alters its function. Here we describe a platform for profiling caspase substrates which encompasses two highly complementary proteomic techniques--the first is a differential gel based approach termed Global Analyzer of SILAC-derived Substrates of Proteolysis (GASSP) and the second involves affinity enrichment of peptides containing a C-terminal aspartic acid residue. In combination, these techniques have enabled the profiling of a large cellular pool of apoptotic-mediated proteolytic events across a wide dynamic range. By applying this integrated proteomic work flow to analyze proteolytic events resulting from the induction of intrinsic apoptosis in Jurkat cells via etoposide treatment, 3346 proteins were quantified, of which 360 proteins were identified as etoposide-induced proteolytic substrates, including 160 previously assigned caspase substrates. In addition to global profiling, a targeted approach using BAX HCT116 isogenic cell lines was utilized to dissect pre- and post-mitochondrial extrinsic apoptotic cleavage events. By employing apoptotic activation with a pro-apoptotic receptor agonist (PARA), a limited set of apoptotic substrates including known caspase substrates such as BH3 interacting-domain death agonist (BID) and Poly (ADP-ribose) polymerase (PARP)-1, and novel substrates such as Basic Transcription Factor 3, TRK-fused gene protein (TFG), and p62/Sequestosome were also identified.

Expanding cross-presenting dendritic cells enhances oncolytic virotherapy and is critical for long-term anti-tumor immunity.

Immunotherapies directly enhancing anti-tumor CD8+ T cell responses have yielded measurable but limited success, highlighting the need for alternatives. Anti-tumor T cell responses critically depend on antigen presenting dendritic cells (DC), and enhancing mobilization, antigen loading and activation of these cells represent an attractive possibility to potentiate T cell based therapies. Here we show that expansion of DCs by Flt3L administration impacts in situ vaccination with oncolytic Newcastle Disease Virus (NDV). Mechanistically, NDV activates DCs and sensitizes them to dying tumor cells through upregulation of dead-cell receptors and synergizes with Flt3L to promote anti-tumor CD8+ T cell cross-priming. In vivo, Flt3L-NDV in situ vaccination induces parallel amplification of virus- and tumor-specific T cells, including CD8+ T cells reactive to newly-described neoepitopes, promoting long-term tumor control. Cross-presenting conventional Type 1 DCs are indispensable for the anti-tumor, but not anti-viral, T cell response, and type I IFN-dependent CD4+ Th1 effector cells contribute to optimal anti-tumor immunity. These data demonstrate that mobilizing DCs to increase tumor antigen cross-presentation improves oncolytic virotherapy and that neoepitope-specific T cells can be induced without individualized, ex vivo manufactured vaccines.

Antigen presentation in cancer: insights into tumour immunogenicity and immune evasion.

Immune checkpoint blockade, which blocks inhibitory signals of T cell activation, has shown tremendous success in treating cancer, although success still remains limited to a fraction of patients. To date, clinically effective CD8+ T cell responses appear to target predominantly antigens derived from tumour-specific mutations that accumulate in cancer, also called neoantigens. Tumour antigens are displayed on the surface of cells by class I human leukocyte antigens (HLA-I). To elicit an effective antitumour response, antigen presentation has to be successful at two distinct events: first, cancer antigens have to be taken up by dendritic cells (DCs) and cross-presented for CD8+ T cell priming. Second, the antigens have to be directly presented by the tumour for recognition by primed CD8+ T cells and killing. Tumours exploit multiple escape mechanisms to evade immune recognition at both of these steps. Here, we review the tumour-derived factors modulating DC function, and we summarize evidence of immune evasion by means of quantitative modulation or qualitative alteration of the antigen repertoire presented on tumours. These mechanisms include modulation of antigen expression, HLA-I surface levels, alterations in the antigen processing and presentation machinery in tumour cells. Lastly, as complete abrogation of antigen presentation can lead to natural killer (NK) cell-mediated tumour killing, we also discuss how tumours can harbour antigen presentation defects and still evade NK cell recognition.

An Integrated Genomic, Proteomic, and Immunopeptidomic Approach to Discover Treatment-Induced Neoantigens.

All nucleated mammalian cells express major histocompatibility complex (MHC) proteins that present peptides on cell surfaces for immune surveillance. These MHC-presented peptides (pMHC) are necessary for directing T-cell responses against cells harboring non-self antigens derived from pathogens or from somatic mutations. Alterations in tumor-specific antigen repertoires - particularly novel MHC presentation of mutation-bearing peptides (neoantigens) - can be potent targets of anti-tumor immune responses. Here we employed an integrated genomic and proteomic antigen discovery strategy aimed at measuring how interferon gamma (IFN-γ) alters antigen presentation, using a human lymphoma cell line, GRANTA-519. IFN-γ treatment resulted in 126 differentially expressed proteins (2% of all quantified proteins), which included components of antigen presentation machinery and interferon signaling pathways, and MHC molecules themselves. In addition, several proteasome subunits were found to be modulated, consistent with previous reports of immunoproteasome induction by IFN-γ exposure. This finding suggests that a modest proteomic response to IFN-γ could create larger alteration to cells' antigen/epitope repertoires. Accordingly, MHC immunoprecipitation followed by mass spectrometric analysis of eluted peptide repertoires revealed exclusive signatures of IFN-γ induction, with 951 unique peptides reproducibly presented by MHC-I and 582 presented by MHC-II. Furthermore, an additional set of pMHCs including several candidate neoantigens, distinguished control and the IFN-γ samples by their altered relative abundances. Accordingly, we developed a classification system to distinguish peptides which are differentially presented due to altered expression from novel peptides resulting from changes in antigen processing. Taken together, these data demonstrate that IFN-γ can re-shape antigen repertoires by identity and by abundance. Extending this approach to models with greater clinical relevance could help develop strategies by which immunopeptide repertoires are intentionally reshaped to improve endogenous or vaccine-induced anti-tumor immune responses and potentially anti-viral immune responses.

Molecular determinants of response to PD-L1 blockade across tumor types.

Immune checkpoint inhibitors targeting the PD-1/PD-L1 axis lead to durable clinical responses in subsets of cancer patients across multiple indications, including non-small cell lung cancer (NSCLC), urothelial carcinoma (UC) and renal cell carcinoma (RCC). Herein, we complement PD-L1 immunohistochemistry (IHC) and tumor mutation burden (TMB) with RNA-seq in 366 patients to identify unifying and indication-specific molecular profiles that can predict response to checkpoint blockade across these tumor types. Multiple machine learning approaches failed to identify a baseline transcriptional signature highly predictive of response across these indications. Signatures described previously for immune checkpoint inhibitors also failed to validate. At the pathway level, significant heterogeneity is observed between indications, in particular within the PD-L1+ tumors. mUC and NSCLC are molecularly aligned, with cell cycle and DNA damage repair genes associated with response in PD-L1- tumors. At the gene level, the CDK4/6 inhibitor CDKN2A is identified as a significant transcriptional correlate of response, highlighting the association of non-immune pathways to the outcome of checkpoint blockade. This cross-indication analysis reveals molecular heterogeneity between mUC, NSCLC and RCC tumors, suggesting that indication-specific molecular approaches should be prioritized to formulate treatment strategies.