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Development of personalized cancer vaccines based on neoantigens has become a new direction in cancer immunotherapy. Two forms of cancer vaccines have been widely studied: tumor-associated antigen (including proteins, peptides, or tumor lysates)-pulsed dendritic cell (DC) vaccines and protein- or peptide-adjuvant vaccines. However, different immune modalities may produce different therapeutic effects and immune responses when the same antigen is used. Therefore, it is necessary to choose a more effective neoantigen vaccination method. In this study, we compared the differences in immune and anti-tumor effects between neoantigen-pulsed DC vaccines and neoantigen-adjuvant vaccines using murine lung carcinoma (LL2) candidate neoantigens. The enzyme-linked immunospot (ELISPOT) assay showed that 4/6 of the neoantigen-adjuvant vaccines and 6/6 of the neoantigen-pulsed DC vaccines induced strong T-cell immune responses. Also, 2/6 of the neoantigen-adjuvant vaccines and 5/6 of the neoantigen-pulsed DC vaccines exhibited potent anti-tumor effects. The results indicated that the neoantigen-pulsed DC vaccines were superior to the neoantigen-adjuvant vaccines in both activating immune responses and inhibiting tumor growth. Our fundings provide an experimental basis for the selection of immune modalities for the use of neoantigens in individualized tumor immunotherapies.

In cancer, non-synonymous DNA base changes alter protein sequence and produce neoantigens that are detected by the immune system. For immune detection, neoantigens must first be presented on class I or II human leukocyte antigens (HLA) followed by recognition by peptide-specific receptors, exemplified by the T-cell receptor (TCR). Detection of neoantigens represents a unique challenge to the immune system due to their high similarity with endogenous ‘self’ proteins. Here, we review insights into how TCRs detect neoantigens from structural studies and delineate two broad mechanistic categories: 1) recognition of mutated ‘self’ peptides and 2) recognition of novel ‘non-self’ peptides generated through anchor residue modifications. While mutated ‘self’ peptides differ only by a single amino acid from an existing ‘self’ epitope, mutations that form anchor residues generate an entirely new epitope, hitherto unknown to the immune system. We review recent structural studies that highlight these structurally distinct mechanisms and discuss how they may lead to differential anti-tumor immune responses. We discuss how T cells specific for neoantigens derived from anchor mutations can be of high affinity and provide insights to their use in adoptive T cell transfer-based immunotherapy.

Adoptive cell therapy (ACT) is a kind of immunotherapy in which T cells are genetically modified to express a chimeric antigen receptor (CAR) or T cell receptor (TCR), and ACT has made a great difference in treating multiple types of tumors. ACT is not perfect, and it can be followed by severe side effects, which hampers the application of ACT in clinical trials. One of the most promising methods to minimize side effects is to endow adoptive T cells with the ability to target neoantigens, which are specific to tumor cells. With the development of antigen screening technologies, more methods can be applied to discover neoantigens in cancer cells, such as whole-exome sequencing combined with mass spectrometry, neoantigen screening through an inventory-shared neoantigen peptide library, and neoantigen discovery via trogocytosis. In this review, we focus on the side effects of existing antigens and their solutions, illustrate the strategies of finding neoantigens in CAR-T and TCR-T therapies through methods reported by other researchers, and summarize the clinical behavior of these neoantigens.

IntroductionNeoantigen-based immunotherapy has emerged as a promising strategy for improving the life expectancy of cancer patients. This therapeutic approach heavily relies on accurate identification of cancer mutations using DNA sequencing (DNAseq) data. However, current workflows tend to provide a large number of neoantigen candidates, of which only a limited number elicit efficient and immunogenic T-cell responses suitable for downstream clinical evaluation. To overcome this limitation and increase the number of high-quality immunogenic neoantigens, we propose integrating RNA sequencing (RNAseq) data into the mutation identification step in the neoantigen prediction workflow.MethodsIn this study, we characterize the mutation profiles identified from DNAseq and/or RNAseq data in tumor tissues of 25 patients with colorectal cancer (CRC). Immunogenicity was then validated by ELISpot assay using long synthesis peptides (sLP).ResultsWe detected only 22.4% of variants shared between the two methods. In contrast, RNAseq-derived variants displayed unique features of affinity and immunogenicity. We further established that neoantigen candidates identified by RNAseq data significantly increased the number of highly immunogenic neoantigens (confirmed by ELISpot) that would otherwise be overlooked if relying solely on DNAseq data.DiscussionThis integrative approach holds great potential for improving the selection of neoantigens for personalized cancer immunotherapy, ultimately leading to enhanced treatment outcomes and improved survival rates for cancer patients.

In recent decades, adoptive cell transfer and checkpoint blockade therapies have revolutionized immunotherapeutic approaches to cancer treatment. Advances in whole exome/genome sequencing and bioinformatic detection of tumour-specific genetic variations and the amino acid sequence alterations they induce have revealed that T cell mediated anti-tumour immunity is substantially directed at mutated peptide sequences, and the identification and therapeutic targeting of patient-specific mutated peptide antigens now represents an exciting and rapidly progressing frontier of personalized medicine in the treatment of cancer. This review outlines the historical identification and validation of mutated peptide neoantigens as a target of the immune system, and the technical development of bioinformatic and experimental strategies for detecting, confirming and prioritizing both patient-specific or “private” and frequently occurring, shared “public” neoantigenic targets. Further, we examine the range of therapeutic modalities that have demonstrated preclinical and clinical anti-tumour efficacy through specifically targeting neoantigens, including adoptive T cell transfer, checkpoint blockade and neoantigen vaccination.

Current success of immunotherapy in cancer has drawn attention to the subsets of T H cells in the tumor which are critical for activation of anti-tumor response either directly by themselves or by stimulating cytotoxic T cell activity. However, presence of immunosuppressive pro-tumorigenic T H subsets in the tumor milieu further contributes to the complexity of regulation of T H cell-mediated immune response. In this review, we present an overview of the multifaceted positive and negative effects of T H cells, with an emphasis on regulation of different T H cell subtypes by various immune cells, and how a delicate balance of contradictory signals can influence overall success of cancer immunotherapy. We focus on the regulatory network that encompasses dendritic cell-induced activation of CD4 + T H 1 cells and subsequent priming of CD8 + cytotoxic T cells, along with intersecting anti-inflammatory and pro-tumorigenic T H 2 cell activity. We further discuss how other tumor infiltrating immune cells such as immunostimulatory T H 9 and T fh cells, immunosuppressive T reg cells, and the duality of T H 17 function contribute to tip the balance of anti- vs pro-tumorigenic T H responses in the tumor. We highlight the developing knowledge of CD4 + T H 1 immune response against neoantigens/oncodrivers, impact of current immunotherapy strategies on CD4 + T H 1 immunity, and how opposing action of T H cell subtypes can be explored further to amplify immunotherapy success in patients. Understanding the nuances of CD4 + T H cells regulation and the molecular framework undergirding the balancing act between anti- vs pro-tumorigenic T H subtypes is critical for rational designing of immunotherapies that can bypass therapeutic escape to maximize the potential of immunotherapy.

Cancer immunotherapy works by stimulating and strengthening the body’s anti-tumor immune response to eliminate cancer cells. Over the past few decades, immunotherapy has shown remarkable efficacy in the treatment of cancer, particularly the success of immune checkpoint blockade targeting CTLA-4, PD-1 and PDL1, which has led to a breakthrough in tumor immunotherapy. Tumor neoantigens, a new approach to tumor immunotherapy, include antigens produced by tumor viruses integrated into the genome and antigens produced by mutant proteins, which are abundantly expressed only in tumor cells and have strong immunogenicity and tumor heterogeneity. A growing number of studies have highlighted the relationship between neoantigens and T cells’ recognition of cancer cells. Vaccines developed against neoantigens are now being used in clinical trials in various solid tumors. In this review, we summarized the latest advances in the classification of immunotherapy and the process of classification, identification and synthesis of tumor-specific neoantigens, as well as their role in current cancer immunotherapy. Finally, the application prospects and existing problems of neoantigens were discussed.

Hepatocellular carcinoma (HCC) is a major health concern worldwide, with limited therapeutic options and poor prognosis. In recent years, immunotherapies such as immune checkpoint inhibitors (ICIs) have made great progress in the systemic treatment of HCC. The combination treatments based on ICIs have been the major trend in this area. Recently, dual immune checkpoint blockade with durvalumab plus tremelimumab has also emerged as an effective treatment for advanced HCC. However, the majority of HCC patients obtain limited benefits. Understanding the immunological rationale and exploring novel ways to improve the efficacy of immunotherapy has drawn much attention. In this review, we summarize the latest progress in this area, the ongoing clinical trials of immune-based combination therapies, as well as novel immunotherapy strategies such as chimeric antigen receptor T cells, personalized neoantigen vaccines, oncolytic viruses, and bispecific antibodies.

Neoantigens play important roles in cancer immunotherapy. Current methods used for neoantigen prediction focus on the binding between human leukocyte antigens (HLAs) and peptides, which is insufficient for high-confidence neoantigen prediction. In this study, we apply deep learning techniques to predict neoantigens considering both the possibility of HLA-peptide binding (binding model) and the potential immunogenicity (immunogenicity model) of the peptide-HLA complex (pHLA). The binding model achieves comparable performance with other well-acknowledged tools on the latest Immune Epitope Database (IEDB) benchmark datasets and an independent mass spectrometry (MS) dataset. The immunogenicity model could significantly improve the prediction precision of neoantigens. The further application of our method to the mutations with pre-existing T-cell responses indicating its feasibility in clinical application. DeepHLApan is freely available at https://github.com/jiujiezz/deephlapan and http://biopharm.zju.edu.cn/deephlapan.