High immunogenicity of the human leukocyte antigen peptidomes of melanoma tumor cells

Recent advances in immunopeptidomic-based tumor neoantigen discovery

The role of aberrantly expressed proteins in tumors in driving immune-mediated control of cancer has been well documented for more than five decades. Today, we know that both aberrantly expressed normal proteins as well as mutant proteins (neoantigens) can function as tumor antigens in both humans and mice. Next-generation sequencing (NGS) and high-resolution mass spectrometry (MS) technologies have made significant advances since the early 2010s, enabling detection of rare but clinically relevant neoantigens recognized by T cells. MS profiling of tumor-specific immunopeptidomes remains the most direct method to identify mutant peptides bound to cellular MHC. However, the need for use of large numbers of cells or significant amounts of tumor tissue to achieve neoantigen detection has historically limited the application of MS. Newer, more sensitive MS technologies have recently demonstrated the capacities to detect neoantigens from fewer cells. Here, we highlight recent advancements in immunopeptidomics-based characterization of tumor-specific neoantigens. Various tumor antigen categories and neoantigen identification approaches are also discussed. Furthermore, we summarize recent reports that achieved successful tumor neoantigen detection by MS using a variety of starting materials, MS acquisition modes, and novel ion mobility devices.

Personalized neoantigen viro-immunotherapy platform for triple-negative breast cancer

BACKGROUND

Triple-negative breast cancer (TNBC) corresponds to approximately 20% of all breast tumors, with a high propensity for metastasis and a poor prognosis. Because TNBC displays a high mutational load compared with other breast cancer types, a neoantigen-based immunotherapy strategy could be effective. One major bottleneck in the development of a neoantigen-based vaccine for TNBC is the selection of the best targets, that is, tumor-specific neoantigens which are presented at the surface of tumor cells and capable of eliciting robust immune responses. In this study, we aimed to set up a platform for identification and delivery of immunogenic neoantigens in a vaccine regimen for TNBC using oncolytic vaccinia virus (VV).

METHODS

We used bioinformatic tools and cell-based assays to identify immunogenic neoantigens in TNBC patients' samples, human and murine cell lines. Immunogenicity of the neoantigens was tested in vitro (human) and ex vivo (murine) in T-cell assays. To assess the efficacy of our regimen, we used a preclinical model of TNBC where we treated tumor-bearing mice with neoantigens together with oncolytic VV and evaluated the effect on induction of neoantigen-specific CD8+T cells, tumor growth and survival.

RESULTS

We successfully identified immunogenic neoantigens and generated neoantigen-specific CD8+T cells capable of recognizing a human TNBC cell line expressing the mutated gene. Using a preclinical model of TNBC, we showed that our tumor-specific oncolytic VV was able to change the tumor microenvironment, attracting and maintaining mature cross-presenting CD8α+dendritic cells and effector T-cells. Moreover, when delivered in a prime/boost regimen together with oncolytic VV, long peptides encompassing neoantigens were able to induce neoantigen-specific CD8+T cells, slow tumor growth and increase survival.

CONCLUSIONS

Our study provides a promising approach for the development of neoantigen-based immunotherapies for TNBC. By identifying immunogenic neoantigens and developing a delivery system through tumor-specific oncolytic VV, we have demonstrated that neoantigen-based vaccines could be effective in inducing neoantigen-specific CD8+T cells response with significant impact on tumor growth. Further studies are needed to determine the safety and efficacy of this approach in clinical trials.

Soluble HLA peptidome: A new resource for cancer biomarkers

Using circulating molecular biomarkers to screen for cancer and other debilitating disorders in a high-throughput and low-cost fashion is becoming increasingly attractive in medicine. One major limitation of investigating protein biomarkers in body fluids is that only one-fourth of the entire proteome can be routinely detected in these fluids. In contrast, Human Leukocyte Antigen (HLA) presents peptides from the entire proteome on the cell surface. While peptide-HLA complexes are predominantly membrane-bound, a fraction of HLA molecules is released into body fluids which is referred to as soluble HLAs (sHLAs). As such peptides bound by sHLA molecules represent the entire proteome of their cells/tissues of origin and more importantly, recent advances in mass spectrometry-based technologies have allowed for accurate determination of these peptides. In this perspective, we discuss the current understanding of sHLA-peptide complexes in the context of cancer, and their potential as a novel, relatively untapped repertoire for cancer biomarkers. We also review the currently available tools to detect and quantify these circulating biomarkers, and we discuss the challenges and future perspectives of implementing sHLA biomarkers in a clinical setting.

Sensitive Immunopeptidomics by Leveraging Available Large-Scale Multi-HLA Spectral Libraries, Data-Independent Acquisition, and MS/MS Prediction

Mass spectrometry (MS) is the state-of-the-art methodology for capturing the breadth and depth of the immunopeptidome across human leukocyte antigen (HLA) allotypes and cell types. The majority of studies in the immunopeptidomics field are discovery driven. Hence, data-dependent tandem MS (MS/MS) acquisition (DDA) is widely used, as it generates high-quality references of peptide fingerprints. However, DDA suffers from the stochastic selection of abundant ions that impairs sensitivity and reproducibility. In contrast, in data-independent acquisition (DIA), the systematic fragmentation and acquisition of all fragment ions within given isolation m/z windows yield a comprehensive map for a given sample. However, many DIA approaches commonly require generating comprehensive DDA-based spectrum libraries, which can become impractical for studying noncanonical and personalized neoantigens. Because the amount of HLA peptides eluted from biological samples such as small tissue biopsies is typically not sufficient for acquiring both meaningful DDA data necessary for generating comprehensive spectral libraries and DIA MS measurements, the implementation of DIA in the immunopeptidomics translational research domain has remained limited. We implemented a DIA immunopeptidomics workflow and assessed its sensitivity and accuracy by matching DIA data against libraries with growing complexity-from sample-specific libraries to libraries combining 2 to 40 different immunopeptidomics samples. Analyzing DIA immunopeptidomics data against a complex multi-HLA spectral library resulted in a two-fold increase in peptide identification compared with sample-specific library and in a three-fold increase compared with DDA measurements, yet with no detrimental effect on the specificity. Furthermore, we demonstrated the implementation of DIA for sensitive personalized neoantigen discovery through the analysis of DIA data with predicted MS/MS spectra of clinically relevant HLA ligands. We conclude that a comprehensive multi-HLA library for DIA approach in combination with MS/MS prediction is highly advantageous for clinical immunopeptidomics, especially when low amounts of biological samples are available.

Analysis of Secondary Structure Biases in Naturally Presented HLA-I Ligands

Recent clinical developments in antitumor immunotherapy involving T-cell related therapeutics have led to a renewed interest for human leukocyte antigen class I (HLA-I) binding peptides, given their potential use as peptide vaccines. Databases of HLA-I binding peptides hold therefore information on therapeutic targets essential for understanding immunity. In this work, we use in depth and accurate HLA-I peptidomics datasets determined by mass-spectrometry (MS) and analyze properties of the HLA-I binding peptides with structure-based computational approaches. HLA-I binding peptides are studied grouping all alleles together or in allotype-specific contexts. We capitalize on the increasing number of structurally determined proteins to (1) map the 3D structure of HLA-I binding peptides into the source proteins for analyzing their secondary structure and solvent accessibility in the protein context, and (2) search for potential differences between these properties in HLA-I binding peptides and in a reference dataset of HLA-I motif-like peptides. This is performed by an in-house developed heuristic search that considers peptides across all the human proteome and converges to a collection of peptides that exhibit exactly the same motif as the HLA-I peptides. Our results, based on 9-mers matched to protein 3D structures, clearly show enriched sampling for HLA-I presentation of helical fragments in the source proteins. This enrichment is significant, as compared to 9-mer HLA-I motif-like peptides, and is not entirely explained by the helical propensity of the preferred residues in the HLA-I motifs. We give possible hypothesis for the secondary structure biases observed in HLA-I peptides. This contribution is of potential interest for researchers working in the field of antigen presentation and proteolysis. This knowledge refines the understanding of the rules governing antigen presentation and could be added to the parameters of the current peptide-MHC class I binding predictors to increase their antigen predictive ability.

Application of mass spectrometry-based MHC immunopeptidome profiling in neoantigen identification for tumor immunotherapy

One of the challenges for cancer vaccine and adoptive T-cell-based immunotherapy is to identify the major histocompatibility complex (MHC)-associated non-self neoantigens recognized by T cells. T cell epitope in silico prediction algorithms have been widely used for neoantigen prediction; nonetheless, this platform lacks the experimental evidence of directly identification of the presented epitopes on cell surface. Currently, mass spectrometry (MS)-based proteomics is an advanced analytical technology for large-scale peptide sequencing, which has become a powerful tool for directly profiling the immunopeptidome presented by MHC molecules. Integrating with next-generation sequencing, proteogenomic analysis provides the "gold standard" for neoantigen identification at protein level. This method discovers the tumor-specific neoantigens derived from somatic mutations, proteasome splicing, noncoding RNA, and post-translational modified antigens. Herein, we review basis of antigen processing and presentation, tumor antigen classification, existing approaches for neoantigen discovery, quantitative proteomics, epitope prediction programs, and advantages and drawbacks of proteomics workflow for MHC immunopeptidome profiling. Furthermore, we summarize 40 recently published reports addressing the fundamental theory, breakthrough and most advanced updates for the mass spectrometry-based neoantigen discovery for cancer immunotherapy.

High-Throughput, Fast, and Sensitive Immunopeptidomics Sample Processing for Mass Spectrometry

Comprehensive knowledge of the HLA class I and class II peptides presented to T cells is crucial for designing innovative therapeutics against cancer and other diseases. So far, methodologies for recovery of HLA class I and II peptides for subsequent mass spectrometry-based analysis have been a major limitation. In this chapter we describe a detailed protocol for a high-throughput, reproducible, and sensitive immunoaffinity-purification of HLA-I and HLA-II peptides from up to 96 samples in a plate format, suitable for tissue samples and cell lines. Our methodology reduces sample handling, has a competitive peptide yield, and can be completed within 5 h. This simplified pipeline is applicable for basic and clinical applications.

Targeting Neoantigens for Personalised Immunotherapy

This review discusses the rapidly evolving field of immunotherapy research, focusing on the types of cancer antigens that can be recognised by the immune system and potential methods by which neoantigens can be exploited clinically to successfully target and clear tumour cells. Recent studies suggest that the likelihood of successful immunotherapeutic targeting of cancer will be reliant on immune response to neoantigens. This type of cancer-specific antigen arises from somatic variants that result in alteration of the expressed protein sequence. Massively parallel sequencing techniques now allow the rapid identification of these genomic mutations, and algorithms can be used to predict those that will be processed by the proteasome, bind to the transporter complex and encode peptides that bind strongly to individual MHC molecules. The emerging data from assessment of the immunogenicity of neoantigens suggests that only a minority of mutations will form targetable epitopes and therefore the potential for immunotherapeutic targeting will be greater in cancers with a higher frequency of protein-altering somatic variants. It is evident that neoantigens contribute to the success of some immunotherapeutic interventions and that there is significant scope for specific targeting of these antigens to develop new treatment approaches.

Identifying neoantigens for use in immunotherapy

This review focuses on the types of cancer antigens that can be recognised by the immune system and form due to alterations in the cancer genome, including cancer testis, overexpressed and neoantigens. Specifically, neoantigens can form when cancer cell-specific mutations occur that result in alterations of the protein from ‘self’. This type of antigen can result in an immune response sufficient to clear tumour cells when activated. Furthermore, studies have reported that the likelihood of successful immunotherapeutic targeting of cancer by many different methods was reliant on immune response to neoantigens. The recent resurgence of interest in the immune response to tumour cells, in conjunction with technological advances, has resulted in a large increase in the predicted, identified and functionally confirmed neoantigens. This growth in identified neoantigen sequences has increased the contents of training sets for algorithms, which in turn improves the prediction of which genetic mutations may form neoantigens. Additionally, algorithms predicting how proteins will be processed into peptide epitopes by the proteasome and which peptides bind to the transporter complex are also improving with this research. Now that large screens of all the tumour-specific protein altering mutations are possible, the emerging data from assessment of the immunogenicity of neoantigens suggest that only a minority of variants will form targetable epitopes. The potential for immunotherapeutic targeting of neoantigens will therefore be greater in cancers with a higher frequency of protein altering somatic variants. There is considerable potential in the use of neoantigens to treat patients, either alone or in combination with other immunotherapies and with continued advancements, these potentials will be realised.

Predicting Antigen Presentation-What Could We Learn From a Million Peptides?

Antigen presentation lies at the heart of immune recognition of infected or malignant cells. For this reason, important efforts have been made to predict which peptides are more likely to bind and be presented by the human leukocyte antigen (HLA) complex at the surface of cells. These predictions have become even more important with the advent of next-generation sequencing technologies that enable researchers and clinicians to rapidly determine the sequences of pathogens (and their multiple variants) or identify non-synonymous genetic alterations in cancer cells. Here, we review recent advances in predicting HLA binding and antigen presentation in human cells. We argue that the very large amount of high-quality mass spectrometry data of eluted (mainly self) HLA ligands generated in the last few years provides unprecedented opportunities to improve our ability to predict antigen presentation and learn new properties of HLA molecules, as demonstrated in many recent studies of naturally presented HLA-I ligands. Although major challenges still lie on the road toward the ultimate goal of predicting immunogenicity, these experimental and computational developments will facilitate screening of putative epitopes, which may eventually help decipher the rules governing T cell recognition.

Impact of Leishmania donovani infection on the HLA I self peptide repertoire of human macrophages

Macrophages are specialized antigen-presenting cells that process and present self-antigens for induction of tolerance, and foreign antigens to initiate T cell-mediated immunity. Despite this, Leishmania donovani (LD) are able to parasitize the macrophages and persist. The impact of this parasitizing and persistence on antigen processing and presentation by macrophages remains poorly defined. To gain insight into this, we analyzed by liquid chromatography tandem mass spectrometry (LC-MS/MS) and compared the HLA-I self-peptidomes, proteasome compositions, HLA expression and activation states of non-infected and LD-infected THP1-derived macrophages. We found that, though both HLA-I peptidomes were dominated by nonapeptides, they were heterogeneous and individualized, with differences in HLA binding affinities and anchor residues. Non-infected and LD-infected THP1-derived macrophages were able to sample peptides from source proteins of almost all subcellular locations and involved in various cellular functions, but in different proportions. In the infected macrophages, there was increased sampling of plasma membrane and extracellular proteins, and those involved in immune responses, cell communication/signal transduction and metabolism/energy pathways, and decreased sampling of nuclear and cytoplasmic proteins and those involved in protein metabolism, RNA binding and cell growth and/or maintenance. Though the activation state of infected macrophages was unchanged, their proteasome composition was altered.

Personal history of infections and immunotherapy: Unexpected links and possible therapeutic opportunities

The recent breakthroughs in the understanding of tumor immune biology have given rise to a new generation of immunotherapies, harnessing the immune system to eliminate tumors. As the typology and frequency of encountered infections are susceptible to shape the immune system, it could also impact the efficiency of immunotherapy. In this review, we report evidences for an indirect link between personal history of infection and different strategies of immunotherapy. In the current context of interest rise for personalized medicine, we discuss the potential medical applications of considering personal history of infection to design immunotherapeutic strategies.

The Role of Mass Spectrometry and Proteogenomics in the Advancement of HLA Epitope Prediction

A challenge in developing personalized cancer immunotherapies is the prediction of putative cancer-specific antigens. Currently, predictive algorithms are used to infer binding of peptides to human leukocyte antigen (HLA) heterodimers to aid in the selection of putative epitope targets. One drawback of current epitope prediction algorithms is that they are trained on datasets containing biochemical HLA-peptide binding data that may not completely capture the rules associated with endogenous processing and presentation. The field of MS has made great improvements in instrumentation speed and sensitivity, chromatographic resolution, and proteogenomic database search strategies to facilitate the identification of HLA-ligands from a variety of cell types and tumor tissues. As such, these advances have enabled MS profiling of HLA-binding peptides to be a tractable, orthogonal approach to lower throughput biochemical assays for generating comprehensive datasets to train epitope prediction algorithms. In this review, we will highlight the progress made in the field of HLA-ligand profiling enabled by MS and its impact on current and future epitope prediction strategies.

Negative selection in tumor genome evolution acts on essential cellular functions and the immunopeptidome

Background

Natural selection shapes cancer genomes. Previous studies used signatures of positive selection to identify genes driving malignant transformation. However, the contribution of negative selection against somatic mutations that affect essential tumor functions or specific domains remains a controversial topic.

Results

Here, we analyze 7546 individual exomes from 26 tumor types from TCGA data to explore the portion of the cancer exome under negative selection. Although we find most of the genes neutrally evolving in a pan-cancer framework, we identify essential cancer genes and immune-exposed protein regions under significant negative selection. Moreover, our simulations suggest that the amount of negative selection is underestimated. We therefore choose an empirical approach to identify genes, functions, and protein regions under negative selection. We find that expression and mutation status of negatively selected genes is indicative of patient survival. Processes that are most strongly conserved are those that play fundamental cellular roles such as protein synthesis, glucose metabolism, and molecular transport. Intriguingly, we observe strong signals of selection in the immunopeptidome and proteins controlling peptide exposition, highlighting the importance of immune surveillance evasion. Additionally, tumor type-specific immune activity correlates with the strength of negative selection on human epitopes.

Conclusions

In summary, our results show that negative selection is a hallmark of cell essentiality and immune response in cancer. The functional domains identified could be exploited therapeutically, ultimately allowing for the development of novel cancer treatments.

Electronic supplementary material

The online version of this article (10.1186/s13059-018-1434-0) contains supplementary material, which is available to authorized users.

Current Strategies to Enhance Anti-Tumour Immunity

The interaction of the immune system with cancer is complex, but new approaches are resulting in exciting therapeutic benefits. In order to enhance the immune response to cancer, immune therapies seek to either induce high avidity immune responses to tumour specific antigens or to convert the tumour to a more pro-inflammatory microenvironment. Strategies, including vaccination, oncolytic viruses, and adoptive cell transfer all seek to induce anti-tumour immunity. To overcome the suppressive tumour microenvironment checkpoint inhibitors and modulators of regulatory cell populations have been investigated. This review summarizes the recent advances in immune therapies and discusses the importance of combination therapies in the treatment of cancers.

MHC class I loaded ligands from breast cancer cell lines: A potential HLA-I-typed antigen collection

To build a catalog of peptides presented by breast cancer cells, we undertook systematic MHC class I immunoprecipitation followed by elution of MHC class I-loaded peptides in breast cancer cells. We determined the sequence of 3196 MHC class I ligands representing 1921 proteins from a panel of 20 breast cancer cell lines. After removing duplicate peptides, i.e., the same peptide eluted from more than one cell line, the total number of unique peptides was 2740. Of the unique peptides eluted, more than 1750 had been previously identified, and of these, sixteen have been shown to be immunogenic. Importantly, half of these immunogenic peptides were shared between different breast cancer cell lines. MHC class I binding probability was used to plot the distribution of the eluted peptides in accordance with the binding score for each breast cancer cell line. We also determined that the tested breast cancer cells presented 89 mutation-containing peptides and peptides derived from aberrantly translated genes, 7 of which were shared between four or two different cell lines. Overall, the high throughput identification of MHC class I-loaded peptides is an effective strategy for systematic characterization of cancer peptides, and could be employed for design of multi-peptide anticancer vaccines.

SIGNIFICANCE

By employing proteomic analyses of eluted peptides from breast cancer cells, the current study has built an initial HLA-I-typed antigen collection for breast cancer research. It was also determined that immunogenic epitopes can be identified using established cell lines and that shared immunogenic peptides can be found in different cancer types such as breast cancer and leukemia. Importantly, out of 3196 eluted peptides that included duplicate peptides in different cells 89 peptides either contained mutation in their sequence or were derived from aberrant translation suggesting that mutation-containing epitopes are on the order of 2-3% in breast cancer cells. Finally, our results suggest that interfering with MHC class I function is one of the mechanisms of how tumor cells escape immune system attack.

Mass spectrometric analysis of the HLA class I peptidome of melanoma cell lines as a promising tool for the identification of putative tumor-associated HLA epitopes

Melanoma is one of the most immunogenic tumors, and extensive lists of potential tumor rejection antigens have been collected during the last decades. By isolating human leukocyte antigen (HLA) class I complexes from five melanoma cell lines (FM-82, FM-93/2, Mel-624, MeWo and SK-Mel-5) and sequencing HLA-eluted peptides by mass spectrometry, we identified over 10,000 unique peptides with high confidence. The majority of the peptides were 8-11 amino acids in length and were predicted to bind to the respective HLA alleles. Over 250 epitopes, corresponding to previously described tumor-associated antigens, were identified, suggesting that HLA peptidome analysis may facilitate the characterization of putative tumor rejection antigens. MeWo and SK-Mel-5 cell lines were further interrogated for neo-epitopes, revealing one peptide from MeWo cells carrying an amino acid mutation. We also observed a remarkable overlap between A*03:01 peptides eluted from Mel-624 cells and A*03:01 peptides recovered from soluble HLA complexes purified from two melanoma patients, shedding light on the similarity of the HLA peptidome in cell lines and in patient-derived material. The reliable characterization of the HLA class I peptidome in melanoma promises to facilitate the identification of tumor rejection antigens and the development of immunotherapeutic strategies.

Diverse HLA-I Peptide Repertoires of the APC Lines MUTZ3-Derived Immature and Mature Dendritic Cells and THP1-Derived Macrophages

Dendritic cells (DCs) and macrophages are specialized APCs that process and present self-Ags for induction of tolerance and foreign Ags to initiate T cell-mediated immunity. Related to differentiation states they have specific phenotypes and functions. However, the impact of these differentiations on Ag processing and presentation remains poorly defined. To gain insight into this, we analyzed and compared the HLA-I peptidomes of MUTZ3-derived human immature and mature DC lines and THP1-derived macrophages by liquid chromatography tandem mass spectrometry. We found that the HLA-I peptidomes were heterogeneous and individualized and were dominated by nonapeptides with similar HLA-I binding affinities and anchor residues. MUTZ3-derived DCs and THP1-derived macrophages were able to sample peptides from source proteins of almost all subcellular locations and were involved in various cellular functions in similar proportion, with preference to proteins involved in cell communication, signal transduction, protein metabolism, and transcription factor/regulator activity.

Mass spectrometry-based antigen discovery for cancer immunotherapy

The antigenic landscape of tumors is distinct from healthy cells and has been the rationale behind a variety of vaccination trials. Typically the target tumor-associated antigens have been of self origin and have rarely induced effective anti-tumor responses. Recent data show that activation of the immune system by immune checkpoint blocking therapies leads to tumor rejection and that recognition of mutated antigens, known as 'neo-antigens' plays a key role. Discovery of neo-antigens relies mainly on prediction-based interrogation of the 'mutanome' using genomic information as input, followed by T-cell screening. Recent breakthroughs in mass spectrometry (MS) based immunopeptidomics have allowed the discovery of very large pools of naturally presented peptides, among them neo-epitopes. This review highlights the current progress related to neo-antigens discovery with emphasis on prediction algorithms and MS as well as the synergy of the two methodologies and how they can be exploited to develop effective personalized immunotherapy.

Implications of Lymphatic Transport to Lymph Nodes in Immunity and Immunotherapy

Adaptive immune response consists of many highly regulated, multistep cascades that protect against infection while preserving the health of autologous tissue. The proper initiation, maintenance, and resolution of such responses require the precise coordination of molecular and cellular signaling over multiple time and length scales orchestrated by lymphatic transport. In order to investigate these functions and manipulate them for therapy, a comprehensive understanding of how lymphatics influence immune physiology is needed. This review presents the current mechanistic understanding of the role of the lymphatic vasculature in regulating biomolecule and cellular transport from the interstitium, peripheral tissue immune surveillance, the lymph node stroma and microvasculature, and circulating lymphocyte homing to lymph nodes. This review also discusses the ramifications of lymphatic transport in immunity as well as tolerance and concludes with examples of how lymphatic-mediated targeting of lymph nodes has been exploited for immunotherapy applications.

Exploration of peptides bound to MHC class I molecules in melanoma

Advancements in high-resolution HPLC and mass spectrometry have reinvigorated the application of this technology to identify peptides eluted from immunopurified MHC class I molecules. Three melanoma cell lines were assessed using w6/32 isolation, peptide elution and HPLC purification; peptides were identified by mass spectrometry. A total of 13,829 peptides were identified; 83-87% of these were 8-11 mers. Only approximately 15% have been described before. Subcellular locations of the source proteins showed even sampling; mRNA expression and total protein length were predictive of the number of peptides detected from a single protein. HLA-type binding prediction for 10,078 9/10 mer peptides assigned 88-95% to a patient-specific HLA subtype, revealing a disparity in strength of predicted binding. HLA-B*27-specific isolation successfully identified some peptides not found using w6/32. Sixty peptides were selected for immune screening, based on source protein and predicted HLA binding; no new peptides recognized by antimelanoma T cells were discovered. Additionally, mass spectrometry was unable to identify several epitopes targeted ex vivo by one patient's T cells.

Influenza virus infection elicits protective antibodies and T cells specific for host cell antigens also expressed as tumor-associated antigens: a new view of cancer immunosurveillance

Most tumor-associated antigens (TAA) are self-molecules that are abnormally expressed in cancer cells and become targets of antitumor immune responses. Antibodies and T cells specific for some TAAs have been found in healthy individuals and are associated with lowered lifetime risk for developing cancer. Lower risk for cancer has also been associated with a history of febrile viral diseases. We hypothesized that virus infections could lead to transient expression of abnormal forms of self-molecules, some of which are TAAs; facilitated by the adjuvant effects of infection and inflammation, these molecules could elicit specific antibodies, T cells, and lasting immune memory simultaneously with immunity against viral antigens. Such infection-induced immune memory for TAA would be expected to provide life-long immune surveillance of cancer. Using influenza virus infection in mice as a model system, we tested this hypothesis and demonstrated that influenza-experienced mice control 3LL mouse lung tumor challenge better than infection-naive control mice. Using 2D-difference gel electrophoresis and mass spectrometry, we identified numerous molecules, some of which are known TAAs, on the 3LL tumor cells recognized by antibodies elicited by two successive influenza infections. We studied in detail immune responses against glyceraldehyde-3-phosphate dehydrogenase (GAPDH), histone H4, HSP90, malate dehydrogenase 2, and annexin A2, all of which were overexpressed in influenza-infected lungs and in tumor cells. Finally, we show that immune responses generated through vaccination against peptides derived from these antigens correlated with improved tumor control.

Targeting the tumor-draining lymph node with adjuvanted nanoparticles reshapes the anti-tumor immune response

Accumulating evidence implicates the tumor-draining lymph node (TDLN) in tumor-induced immune escape, as it drains regulatory molecules and leukocytes from the tumor microenvironment. We asked whether targeted delivery of adjuvant to the TDLN, presumably already bathed in tumor antigens, could promote anti-tumor immunity and hinder tumor growth. To this end, we used 30 nm polymeric nanoparticles (NPs) that effectively target dendritic cells (DCs, CD11c(+)) within the lymph node (LN) after intradermal administration. These NPs accumulated within the TDLN when administered in the limb ipsilateral (i.l.) to the tumor or in the non-TDLN when administered in the contralateral (c.l.) limb. Incorporating the adjuvants CpG or paclitaxel into the NPs (CpG-NP and PXL-NP) induced DC maturation in vitro. When administered daily i.l. and thus targeting the TDLN of a B16-F10 melanoma, adjuvanted NPs induced DC maturation within the TDLN and reshaped the CD4(+) T cell distribution within the tumor towards a Th1 (CXCR3(+)) phenotype. Importantly, this also led to an increase in the frequency of antigen-specific CD8(+) T cells within the tumor. This correlated with slowed tumor growth, in contrast to unhindered tumor growth after c.l. delivery of adjuvanted NPs (targeting a non-TDLN) or i.l. delivery of free adjuvant. CpG-NP treatment in the i.l. limb also was associated with an increase in CD8(+)/CD4(+) T cell ratios and frequencies of activated (CD25(+)) CD8(+) T cells within the TDLN whereas PXL-NP treatment reduced the frequency of regulatory T (FoxP3(+) CD4(+)) cells in the TDLN. Together, these data implicate the TDLN as a delivery target for adjuvant therapy of solid tumors.