个性化肿瘤新抗原疫苗中抗原肽预测研究进展

失控的突变导致肿瘤的发生,其中某些非同义突变(错义、移码、融合)多肽,被蛋白酶体降解成短肽后被抗原提呈细胞(antigen-presenting cells,APCs)识别,呈递至引流淋巴结,符合主要组织相容性复合物(major histocompatibility complex,MHC)结合基序的短肽,继而被T细胞表面因子捕获而产生免疫反应,引发肿瘤的消退,我们称之为"新抗原"(neoantigens).这类抗原由于未受胸腺的阴性筛选,被T细胞识别为"异类",不易受免疫耐受机制的影响,从而可作为免疫介导肿瘤治疗的有效靶点.新一代测序技术极大推动了新抗原疫苗的可行性,但从测序识别肿瘤的体细胞突变到TCR (Tcell receptor)识别新抗原产生免疫反应,中间存在着大量的候选假阳性新抗原多肽,这对于针对新抗原而设计疫苗无疑是难以跨越的障碍.一套有效合理的筛选方法,是新抗原疫苗制备过程中不可或缺的一环.然而国内未见相关综述报道,本文调研了目前新抗原免疫治疗过程中的新抗原肽预测及筛选研究进展.     

Personalized neoantigen vaccines: A new approach to cancer immunotherapy

Neoantigens arise from somatic mutations that differ from wild-type antigens and are specific to each individual patient, which provide tumor specific targets for developing personalized cancer vaccines. Decades of work has increasingly shown the potential of targeting neoantigens to generate effective clinical responses. Current clinical trials using neoantigen targeting cancer vaccines, including in combination with checkpoint blockade monoclonal antibodies, have demonstrated potent T-cell responses against those neoantigens accompanied by antitumor effects in patients. Personalized neoantigen vaccines represent a potential new class of cancer immunotherapy.     

TSNAdb: A Database for Tumor-specific Neoantigens from Immunogenomics Data Analysis

Tumor-specific neoantigens have attracted much attention since they can be used as biomarkers to predict therapeutic effects of immune checkpoint blockade therapy and as potential targets for cancer immunotherapy. In this study, we developed a comprehensive tumor-specific neoantigen database (TSNAdb v1.0), based on pan-cancer immunogenomic analyses of somatic mutation data and human leukocyte antigen (HLA) allele information for 16 tumor types with 7748 tumor samples from The Cancer Genome Atlas (TCGA) and The Cancer Immunome Atlas (TCIA). We predicted binding affinities between mutant/wild-type peptides and HLA class I molecules by NetMHCpan v2.8/v4.0, and presented detailed information of 3,707,562/1,146,961 potential neoantigens generated by somatic mutations of all tumor samples. Moreover, we employed recurrent mutations in combination with highly frequent HLA alleles to predict potential shared neoantigens across tumor patients, which would facilitate the discovery of putative targets for neoantigen-based cancer immunotherapy. TSNAdb is freely available at http://biopharm.zju.edu.cn/tsnadb.     

Finding neoepitopes in mouse models of personalized cancer immunotherapy

Background

Cancer immunotherapy uses one’s own immune system to fight cancerous cells. As immune system is hard-wired to distinguish self and non-self, cancer immunotherapy is predicted to target cancerous cells specifically, therefore is less toxic than chemotherapy and radiation therapy, two major treatments for cancer. Cancer immunologists have spent decades to search for the specific targets in cancerous cells.

Methods

Due to the recent advances in high throughput sequencing and bioinformatics, evidence has merged that the neoantigens in cancerous cells are probably the cancer-specific targets that lead to the destruction of cancer.We will review the transplantable murine tumor models for cancer immunotherapy and the bioinformatics tools used to navigate mouse genome to identify tumor-rejecting neoantigens.

Results

Several groups have independently identified point mutations that can be recognized by T cells of host immune system. It is consistent with the note that the formation of peptide-MHC I-TCR complex is critical to activate T cells. Both anchor residue and TCR-facing residue mutations have been reported. While TCR-facing residue mutations may directly activate specific T cells, anchor residue mutations improve the binding of peptides to MHC I molecules, which increases the presentation of peptides and the T cell activation indirectly.

Conclusions

Our work indicates that the affinity of neoepitopes for MHC I is not a predictor for anti-tumor immune responses in mice. Instead differential agretopic index (DAI), the numerical difference of epitope-MHC I affinities between the mutated and un-mutated sequences is a significant predictor. A similar bioinformatics pipeline has been developed to generate personalized vaccines to treat human ovarian cancer in a Phase I clinical trial.

     

Mathematical model of a personalized neoantigen cancer vaccine and the human immune system

Cancer vaccines are an important component of the cancer immunotherapy toolkit enhancing immune response to malignant cells by activating CD4⁺ and CD8⁺ T cells. Multiple successful clinical applications of cancer vaccines have shown good safety and efficacy. Despite the notable progress, significant challenges remain in obtaining consistent immune responses across heterogeneous patient populations, as well as various cancers. We present a mechanistic mathematical model describing key interactions of a personalized neoantigen cancer vaccine with an individual patient’s immune system. Specifically, the model considers the vaccine concentration of tumor-specific antigen peptides and adjuvant, the patient’s major histocompatibility complexes I and II copy numbers, tumor size, T cells, and antigen presenting cells. We parametrized the model using patient-specific data from a clinical study in which individualized cancer vaccines were used to treat six melanoma patients. Model simulations predicted both immune responses, represented by T cell counts, to the vaccine as well as clinical outcome (determined as change of tumor size). This model, although complex, can be used to describe, simulate, and predict the behavior of the human immune system to a personalized cancer vaccine.     

Low immunogenicity of common cancer hot spot mutations resulting in false immunogenic selection signals

Cancer is driven by somatic mutations that result in a cellular fitness advantage. This selective advantage is expected to be counterbalanced by the immune system when these driver mutations simultaneously lead to the generation of neoantigens, novel peptides that are presented at the cancer cell membrane via HLA molecules from the MHC complex. The presentability of these peptides is determined by a patient’s MHC genotype and it has been suggested that this results in MHC genotype-specific restrictions of the oncogenic mutational landscape. Here, we generated a set of virtual patients, each with an identical and prototypical MHC genotype, and show that the earlier reported HLA affinity differences between observed and unobserved mutations are unrelated to MHC genotype variation. We demonstrate how these differences are secondary to high frequencies of 13 hot spot driver mutations in 6 different genes. Several oncogenic mechanisms were identified that lower the peptides’ HLA affinity, including phospho-mimicking substitutions in BRAF, destabilizing tyrosine mutations in TP53 and glycine-rich mutational contexts in the GTP-binding KRAS domain. In line with our earlier findings, our results emphasize that HLA affinity predictions are easily misinterpreted when studying immunogenic selection processes.     

UV‐induced somatic mutations elicit a functional T cell response in the YUMMER1.7 mouse melanoma model

Human melanomas exhibit relatively high somatic mutation burden compared to other malignancies. These somatic mutations may produce neoantigens that are recognized by the immune system, leading to an antitumor response. By irradiating a parental mouse melanoma cell line carrying three driver mutations with UVB and expanding a single‐cell clone, we generated a mutagenized model that exhibits high somatic mutation burden. When inoculated at low cell numbers in immunocompetent C57BL/6J mice, YUMMER1.7 (Yale University Mouse Melanoma Exposed to Radiation) regresses after a brief period of growth. This regression phenotype is dependent on T cells as YUMMER1.7 tumors grow significantly faster in immunodeficient Rag1^?/? mice and C57BL/6J mice depleted of CD4 and CD8 T cells. Interestingly, regression can be overcome by injecting higher cell numbers of YUMMER1.7, which results in tumors that grow without effective rejection. Mice that have previously rejected YUMMER1.7 tumors develop immunity against higher doses of YUMMER1.7 tumor challenge. In addition, escaping YUMMER1.7 tumors are sensitive to anti‐CTLA‐4 and anti‐PD‐1 therapy, establishing a new model for the evaluation of immune checkpoint inhibition and antitumor immune responses.     

The thin red line between the immune system and cancer evolution

The cancer immunoediting theory describes the dual ability of endogenous antitumor immunity to inhibit or promote progressing cancers. Tumor-specific neoantigens arising from somatic mutations serve as targets for the endogenous T-cell-mediated antitumor immunity and therefore possess a crucial role for tumor development. Additionally, targeting these molecules is conceptually appealing because neoantigens are not expressed in healthy tissue and therefore confer less toxicity and greater specificity when used in therapeutic interventions. Moreover, intratumor neo-antigenic heterogeneity is believed to play a pivotal role in the activation of adaptive immunity and in the efficacy of immunotherapies that are based on immune checkpoint inhibition. In this respect, mutual interactions between tumor cells and immune lymphocytes regulate the levels of antitumor immunity, but also shape tumor heterogeneity through the selective outgrowth of tumor subclones. Therefore, the exploration of the mechanistic pathways and the identification of the genomic aberrations underlying the clonal evolution of tumors is considered mandatory for improving the clinical outcomes of therapies, as it will assist in the selection of the appropriate therapeutic decisions so as to delay, avoid, or overcome resistance through the identification of the most effective therapeutic strategies.     

Human papillomavirus type 33 E7 peptides presented by HLA-DR*0402 to tumor-infiltrating T cells in cervical cancer

Several characteristics make human papillomavirus (HPV) amenable to vaccination. Anti-HPV-directed vaccines are based on the observation that HPV E6 and E7 oncoproteins are constitutively expressed in HPV-positive cervical cancer and may serve as tumor rejection antigens. Five HPV types (16, 18, 31, 33, and 45) account for 80% of cervical cancer. Until now, the type of immune response capable of mediating an effective antitumor response has not been defined. In order to define the anticancer-directed immune response in situ, we characterized CD4(+) and CD8(+) sorted T cells from peripheral blood lymphocytes, freshly harvested tumor tissue, and tumor-infiltrating lymphocytes (TIL) from a patient with cervical cancer. The HLA-DR-restricted CD4(+) T-cell receptor VB16-, VA10-, VA21-, and VA22-positive CD4(+) T-cell line derived from TIL recognizes autologous HLA-DR*0402(+) (HPV33(+)) cervical cancer cells, as determined by gamma interferon secretion. Testing of different peptides spanning the E7 gene revealed that the HPV33(73-87) peptide ASDLRTIQQLLMGTV represents the immunodominant epitope which can also be presented by the DR*0401 allele to TIL. Such major histocompatibility complex class II-presented peptides represent attractive candidates to augment T-cell responses directed against autologous tumor cells.     

Human growth hormone presented by K14hGH-transgenic skin grafts induces a strong immune response but no graft rejection

Although immune responses leading to rejection of transplantable tumours have been well studied, requirements for epithelial tumour rejection are unclear. Here, we use human growth hormone (hGH) expressed in epithelial cells (skin keratinocytes) as a model neo-self antigen to investigate the consequences of antigen presentation from epithelial cells. Mice transgenic for hGH driven from the keratin 14 promoter express hGH in skin keratinocytes. This hGH-transgenic skin is not rejected by syngeneic non-transgenic recipients, although an antibody response to hGH develops in grafted animals. Systemic immunization of graft recipients with hGH peptides, or local administration of stimulatory anti-CD40 antibody, induces temporary macroscopic graft inflammation, and an obvious dermal infiltrate of inflammatory cells, but not graft rejection. These results suggest that a neo-self antigen expressed in somatic cells in skin can induce an immune response that can be enhanced further by induction of specific immunity systemically or non-specific immunity locally. However, immune responses do not always lead to rejection, despite induction of local inflammatory changes. Therefore, in vitro immune responses and in vivo delayed type hypersensitivity are not surrogate markers for immune responses effective against epithelial cells expressing neoantigens.     

Highly potent mRNA based cancer vaccines represent an attractive platform for combination therapies supporting an improved therapeutic effect

Direct vaccination with mRNA encoding tumor antigens is a novel and promising approach in cancer immunotherapy. CureVac's mRNA vaccines contain free and protamine-complexed mRNA. Such two-component mRNA vaccines support both antigen expression and immune stimulation. These self-adjuvanting RNA vaccines, administered intradermally without any additional adjuvant, induce a comprehensive balanced immune response, comprising antigen specific CD4+ T cells, CD8+ T cells and B cells. The balanced immune response results in a strong anti-tumor effect and complete protection against antigen positive tumor cells. This tumor inhibition elicited by mRNA vaccines is a result of the concerted action of different players. After just two intradermal vaccinations, we observe multiple changes at the tumor site, including the up-regulation of many genes connected to T and natural killer cell activation, as well as genes responsible for improved infiltration of immune cells into the tumor via chemotaxis. The two-component mRNA vaccines induce a very fast and boostable immune response. Therefore, the vaccination schedules can be adjusted to suit the clinical situation. Moreover, by combining the mRNA vaccines with therapies in clinical use (chemotherapy or anti-CTLA-4 antibody therapy), an even more effective anti-tumor response can be elicited. The first clinical data obtained from two separate Phase I/IIa trials conducted in PCA (prostate cancer) and NSCLC (non-small cell lung carcinoma) patients have shown that the two-component mRNA vaccines are safe, well tolerated and highly immunogenic in humans.     

Identification of MHC class II-restricted tumor antigens recognized by CD4+ T cells

CD4+ T cells play a central role in orchestrating host immune responses against cancer as well as autoimmune and infectious diseases. Identification of major histocompatibility complex (MHC) class II-restricted helper T peptides is important for development of effective vaccines. The lack of effective methods to identify such T-cell peptides is a major hurdle in the use of antigen-specific CD4+ T cells in cancer vaccines. Here we describe a genetic targeting expression system for cloning genes encoding for MHC class II-restricted tumor antigens recognized by tumor-reactive CD4+ T cells. Helper T peptides are subsequently identified by using synthetic peptides to test their ability to stimulate CD4+ T cells.     

Shared immunoproteome for ovarian cancer diagnostics and immunotherapy: potential theranostic approach to cancer

Elimination of cancer through early detection and treatment is the ultimate goal of cancer research and is especially critical for ovarian and other forms of cancer typically diagnosed at very late stages that have very poor response rates. Proteomics has opened new avenues for the discovery of diagnostic and therapeutic targets. Immunoproteomics, which defines the subset of proteins involved in the immune response, holds considerable promise for providing a better understanding of the early-stage immune response to cancer as well as important insights into antigens that may be suitable for immunotherapy. Early administration of immunotherapeutic vaccines can potentially have profound effects on prevention of metastasis and may potentially cure through efficient and complete tumor elimination. We developed a mass-spectrometry-based method to identify novel autoantibody-based serum biomarkers for the early diagnosis of ovarian cancer that uses native tumor-associated proteins immunoprecipitated by autoantibodies from sera obtained from cancer patients and from cancer-free controls to identify autoantibody signatures that occur at high frequency only in cancer patient sera. Interestingly, we identified a subset of more than 50 autoantigens that were also processed and presented by MHC class I molecules on the surfaces of ovarian cancer cells and thus were common to the two immunological processes of humoral and cell-mediated immunity. These shared autoantigens were highly representative of families of proteins with roles in key processes in carcinogenesis and metastasis, such as cell cycle regulation, cell proliferation, apoptosis, tumor suppression, and cell adhesion. Autoantibodies appearing at the early stages of cancer suggest that this detectable immune response to the developing tumor can be exploited as early-stage biomarkers for the development of ovarian cancer diagnostics. Correspondingly, because the T-cell immune response depends on MHC class I processing and presentation of peptides, proteins that go through this pathway are potential candidates for the development of immunotherapeutics designed to activate a T-cell immune response to cancer. To the best of our knowledge, this is the first comprehensive study that identifies and categorizes proteins that are involved in both humoral and cell-mediated immunity against ovarian cancer, and it may have broad implications for the discovery and selection of theranostic molecular targets for cancer therapeutics and diagnostics in general.     

Antigen loading of DCs with irradiated apoptotic tumor cells induces improved anti-tumor immunity compared to other approaches

Dendritic cells (DCs) serve as central regulators of adaptive immunity by presenting antigens and providing necessary co-signals. Environmental information received by the DCs determines the co-signals delivered to the responding adaptive cells and, ultimately, the outcome of the interaction. DCs loaded with relevant antigens have been used as therapeutic cellular vaccines, but the optimal antigen loading method has not been determined. We compared different methods to load class I and class II epitopes from the male antigenic complex, HY, onto DCs for the potency of the immune response induced in vivo. Co-incubation of female DCs with HY peptides, RNA or cell lysate from HY expressing tumor induced immune responses equivalent to male DCs. In contrast, female DCs incubated with irradiated, apoptotic HY expressing tumor cells (or male B cells) generated a stronger immune response than male DCs or female DCs loaded using any of the other methods. DC loading with apoptotic tumor resulted in complete protection against high dose HY-expressing tumor challenge whereas 100% lethality was observed in groups receiving DCs that were loaded with peptides, RNA, or lysate. We conclude that signals provided to the DCs by apoptotic cells substantially augment the potency of DC vaccines.     

TCR hypervariable regions expressed by T cells that respond to effective tumor vaccines

A major goal of immunotherapy for cancer is the activation of T cell responses against tumor-associated antigens (TAAs). One important strategy for improving antitumor immunity is vaccination with peptide variants of TAAs. Understanding the mechanisms underlying the expansion of T cells that respond to the native tumor antigen is an important step in developing effective peptide-variant vaccines. Using an immunogenic mouse colon cancer model, we compare the binding properties and the TCR genes expressed by T cells elicited by peptide variants that elicit variable antitumor immunity directly ex vivo. The steady-state affinity of the natural tumor antigen for the T cells responding to effective peptide vaccines was higher relative to ineffective peptides, consistent with their improved function. Ex vivo analysis showed that T cells responding to the effective peptides expressed a CDR3β motif, which was also shared by T cells responding to the natural antigen and not those responding to the less effective peptide vaccines. Importantly, these data demonstrate that peptide vaccines can expand T cells that naturally respond to tumor antigens, resulting in more effective antitumor immunity. Future immunotherapies may require similar stringent analysis of the responding T cells to select optimal peptides as vaccine candidates.     

Determination of somatic and cancer stem cell self-renewing symmetric division rate using sphere assays

Representing a renewable source for cell replacement, neural stem cells have received substantial attention in recent years. The neurosphere assay represents a method to detect the presence of neural stem cells, however owing to a deficiency of specific and definitive markers to identify them, their quantification and the rate they expand is still indefinite. Here we propose a mathematical interpretation of the neurosphere assay allowing actual measurement of neural stem cell symmetric division frequency. The algorithm of the modeling demonstrates a direct correlation between the overall cell fold expansion over time measured in the sphere assay and the rate stem cells expand via symmetric division. The model offers a methodology to evaluate specifically the effect of diseases and treatments on neural stem cell activity and function. Not only providing new insights in the evaluation of the kinetic features of neural stem cells, our modeling further contemplates cancer biology as cancer stem-like cells have been suggested to maintain tumor growth as somatic stem cells maintain tissue homeostasis. Indeed, tumor stem cell's resistance to therapy makes these cells a necessary target for effective treatment. The neurosphere assay mathematical model presented here allows the assessment of the rate malignant stem-like cells expand via symmetric division and the evaluation of the effects of therapeutics on the self-renewal and proliferative activity of this clinically relevant population that drive tumor growth and recurrence.     

The sentinel within: exploiting the immune system for cancer biomarkers

The release of proteins from tumors triggers an immune response in cancer patients. These tumor antigens arise from several mechanisms including tumor-specific alterations in protein expression, mutation, folding, degradation, or intracellular localization. Responses to most tumor antigens are rarely observed in healthy individuals, making the response itself a biomarker that betrays the presence of underlying cancer. Antibody immune responses show promise as clinical biomarkers because antibodies have long half-lives in serum, are easy to measure, and are stable in blood samples. However, our understanding of the specificity and the impact of the immune response in early stages of cancer is limited. The immune response to cancer, whether endogenous or driven by vaccines, involves highly specific T lymphocytes (which target tumor-derived peptides bound to self-MHC proteins) and B lymphocytes (which generate antibodies to tumor-derived proteins). T cell target antigens have been identified either by expression cloning from tumor cDNA libraries, or by prediction based on patterns of antigen expression ("reverse immunology"). B cell targets have been similarly identified using the antibodies in patient sera to screen cDNA libraries derived from tumor cell lines. This review focuses on the application of recent advances in proteomics for the identification of tumor antigens. These advances are opening the door for targeted vaccine development, and for using immune response signatures as biomarkers for cancer diagnosis and monitoring.     

A prostate cancer vaccine comprising whole cells secreting IL-7, effective against subcutaneous challenge,requires local GM-CSF for intra-prostatic efficacy

A panel of cytokine-secreting RM-9 prostate cancer cells were tested as whole cell vaccines to determine their capacity to evoke an anti-prostate cancer immune response. In our model, vaccines secreting mGM-CSF or mIL-7 resulted in the highest increase in circulating T lymphocytes after vaccination, prolonged survival and, in a proportion of animals, tumor-free survival. Anti-tumor effects were more evident after a subcutaneous RM-9 challenge than after an intraprostatic challenge. However, when the RM-9/mGM-CSF cell line was used as intraprostatic tumor challenge, protection after RM-9/mIL-7 vaccination was restored.     

Personalized peptide vaccination: a new approach for advanced cancer as therapeutic cancer vaccine

Since both tumor cells and host immune cell repertoires are diverse and heterogeneous, immune responses against tumor-associated antigens should differ substantially among individual cancer patients. Selection of suitable peptide vaccines for individual patients based on the preexisting host immunity before vaccination could induce potent anti-tumor responses that provide clinical benefit to cancer patients. We have developed a novel immunotherapeutic approach of personalized peptide vaccination (PPV) in which a maximum of four human leukocyte antigen (HLA) class IA-matched peptides are selected for vaccination among pooled peptides on the basis of both HLA class IA type and the preexisting host immunity before vaccination. In this review, we discuss our recent results of preclinical and clinical studies of PPV for various types of advanced cancer.