Guiding immunotherapy combinations: Who gets what?

Although PD-1 and CTLA-4 inhibitors have proven successful in a range of malignancies, there are subsets of patients that do not respond to these agents due to upregulation of adaptive and innate resistance mechanisms by the tumor and its surrounding microenvironment. As new immunotherapeutic strategies are developed, there is a need for rational implementation of novel immunotherapy combinations that target complementary mechanisms of immunotherapy resistance intrinsic to each patient and tumor type. In this short review, we cover mechanisms by which tumors evade the immune system, as well as summarize available clinical data on emerging therapeutic agents that target these defense mechanisms. Rational implementation of combination immunotherapy targeting patient- and malignancy-specific immune evasion mechanisms may thus lead to enhanced response rates and allow immunotherapy to be effective even in tumors that are historically considered poorly responsive to immunotherapy.

Tumor cells endowed with professional antigen-presenting cell functions prime PBLs to generate antitumor CTLs

Intrinsic genetic instability of tumor cells leads to continuous production of mutated proteins referred to as tumor-specific neoantigens. Generally, they are recognized as nonself products by the host immune system. However, an effective adaptive response clearing neoantigen-expressing cells is lost in tumor diseases. Most advanced therapeutic strategies aim at inducing neoantigen-specific immune activation through personalized approaches. They include tumor cell exome sequencing, human leukocyte antigen (HLA) typing, synthesis, and injection of peptides/RNA with adjuvants. Here, we propose an innovative method to induce a CD8⁺ T cytotoxic lymphocyte (CTL) immune response against tumor neoantigens bypassing the steps needed in current therapeutic strategies of personalized vaccination. We assumed that tumor cells can be the most efficient and precise factory of major histocompatibility complex (MHC) class I-associated, tumor neoantigen-derived peptides. Hence, endowing tumor cells with professional antigen-presenting functions would prime CD8⁺ T lymphocytes towards a response against nonself tumor antigens. To explore this possibility, both adenocarcinoma and melanoma human cells were engineered to express both CD80 and CD86 costimulatory molecules. HLA-matched lymphocytes were then primed through cocultivation with the engineered tumor cells. The generation of tumor-specific CD8⁺ T lymphocytes was tested through the combined analysis of cell activation markers, formation of immunologic synapses, generation of tumor antigen-specific CD8⁺ T lymphocytes, and cytotoxic activity. Our data consistently indicate that tumor cells endowed with professional antigen-presenting functions can generate an effective tumor-specific CTL immune response. This finding may open avenues towards the development of innovative antitumor immunotherapies. KEY MESSAGES: We established a novel method to induce antitumor CTLs without a need to identify TAAs and/or tumor neoantigens. This strategy relies on transducing tumor cells with a retroviral vector expressing both CD80 and CD86. In this way, tumor cells prime naïve CD8⁺ T lymphocytes in a way that CTLs killing the same tumor cells are generated. These findings open the way towards preclinical assays in the perspective to introduce this antitumor immunotherapy strategy in clinic.

DeepTAP: An RNN-based method of TAP-binding peptide prediction in the selection of tumor neoantigens

The transport of peptides from the cytoplasm to the endoplasmic reticulum (ER) by transporters associated with antigen processing (TAP) is a critical step in the intracellular presentation of cytotoxic T lymphocyte (CTL) epitopes. The development and application of computational methods, especially deep learning methods and new neural network strategies that can automatically learn feature representations with limited knowledge, provide an opportunity to develop fast and efficient methods to identify TAP-binding peptides. Herein, this study presents a comprehensive analysis of TAP-binding peptide sequences to derive TAP-binding motifs and preferences for N-terminal and C-terminal amino acids. A novel recurrent neural network (RNN)-based method called DeepTAP, using bidirectional gated recurrent unit (BiGRU), was developed for the accurate prediction of TAP-binding peptides. Our results demonstrated that DeepTAP achieves an optimal balance between prediction precision and false positives, outperforming other baseline models. Furthermore, DeepTAP significantly improves the prediction accuracy of high-confidence neoantigens, especially the top-ranked ones, making it a valuable tool for researchers studying antigen presentation processes and T-cell epitope screening. DeepTAP is freely available at https://github.com/zjupgx/deeptap and https://pgx.zju.edu.cn/deeptap.

Individualized tumor-reactive T cells exhibit a potent anti-tumor response in prostate cancer

BACKGROUND

Cellular immunotherapy exhibits promise in treating blood tumors. However, its application for solid tumors is impeded by their heterogeneity and complex microenvironments. The development of individualized multitarget therapy may be the key to overcoming the challenge of tumor heterogeneity.

METHODS

To generate tumor-reactive T cells, we modified the conditional reprogramming primary cell culture method by to establish a primary prostate cancer cell culture approach, refer to as eCR (enhanced conditional reprogramming). Then, Tumor tissue-derived primary cells were physically lysed and loaded into dendric cells, which, in turn, were co-cultured with peripheral blood T cells to induced individualized tumor-reactive T cells.

RESULTS

Our improved culture method could use a small amount of fresh or frozen tumor specimens (including biopsy specimens), which can be amplified in vitro while maintaining their original characteristics, without contamination by heterologous antigens. Furthermore, a series of in vitro and in vivo experiments revealed these tumor-reactive T cells exhibited specific and effective killing of tumor cells through their ability to recognize neoantigens in cancer.

CONCLUSION

In this study, we developed a protocol for the generation of tumor-responsive T cells based on autologous tumor antigens in patients with prostate cancer. This platform is characterized by its multitargeted, individualized, affordability, and minimal adverse effects, holding significant promise in the treatment of prostate cancer as well as other solid tumors.

Relevance of mutation-derived neoantigens and non-classical antigens for anticancer therapies

Efficacy of cancer immunotherapies relies on correct recognition of tumor antigens by lymphocytes, eliciting thus functional responses capable of eliminating tumor cells. Therefore, important efforts have been carried out in antigen identification, with the aim of understanding mechanisms of response to immunotherapy and to design safer and more efficient strategies. In addition to classical tumor-associated antigens identified during the last decades, implementation of next-generation sequencing methodologies is enabling the identification of neoantigens (neoAgs) arising from mutations, leading to the development of new neoAg-directed therapies. Moreover, there are numerous non-classical tumor antigens originated from other sources and identified by new methodologies. Here, we review the relevance of neoAgs in different immunotherapies and the results obtained by applying neoAg-based strategies. In addition, the different types of non-classical tumor antigens and the best approaches for their identification are described. This will help to increase the spectrum of targetable molecules useful in cancer immunotherapies.

Characterizing and forecasting neoantigens-resulting from MUC mutations in COAD

BACKGROUND

The treatment for colon adenocarcinoma (COAD) faces challenges in terms of immunotherapy effectiveness due to multiple factors. Because of the high tumor specificity and immunogenicity, neoantigen has been considered a pivotal target for cancer immunotherapy. Therefore, this study aims to identify and predict the potential tumor antigens of MUC somatic mutations (MUCmut) in COAD.

METHODS

Three databases of TCGA, TIMER2.0, and cBioPortal were used for a detailed evaluation of the association between MUCmut and multi-factors like tumor mutation burden (TMB), microsatellite instability (MSI), prognosis, and the tumor microenvironment within the context of total 2242 COAD patients. Next, TSNAdb and the differential agretopicity index (DAI) were utilized to predict high-confidence neopeptides for MUCmut based on 531 COAD patients' genomic information. DAI was calculated by subtraction of its predicted HLA binding affinity of the MUCmut peptide from the corresponding wild-type peptide.

RESULTS

The top six mutation frequencies (14 to 2.9%) were from MUC16, MUC17, MUC5B, MUC2, MUC4 and MUC6. COAD patients with MUC16 and MUC4 mutations had longer DFS and PFS. However, patients with MUC13 and MUC20 mutations had shorter OS. Patients with the mutation of MUC16, MUC5B, MUC2, MUC4, and MUC6 exhibited higher TMB and MSI. Moreover, these mutations from the MUC family were associated with the infiltration of diverse lymphocyte cells and the expression of immune checkpoint genes. Through TSNAdb 1.0/NetMHCpan v2.8, 452 single nucleotide variants (SNVs) of MUCmut peptides were identified. Moreover, through TSNAdb2.0/NetMHCpan v4.0, 57 SNVs, 1 Q-frame shift (TS), and 157 short insertions/deletions (INDELs) of MUCmut were identified. Finally, 10 high-confidence neopeptides of MUCmut were predicted by DAI.

CONCLUSIONS

Together, our findings establish the immunogenicity and therapeutic potential of mutant MUC family-derived neoantigens. Through combining the tools of TSNAdb and DAI, a group of novel MUCmut neoantigens were identified as potential targets for immunotherapy.

NitraTh epitope-based neoantigen vaccines for effective tumor immunotherapy

Neoantigen vaccines represent an emerging and promising strategy in the field of tumor immunotherapy. Despite their potential, designing an effective neoantigen vaccine remains a challenge due to the current limitations in predicting CD4+ T cell epitopes with high accuracy. Here, we introduce a novel approach to neoantigen vaccine design that does not rely on computational prediction of CD4+ T cell epitopes. Utilizing nitrated helper T cell epitope containing p-nitrophenylalanine, termed "NitraTh epitope," we have successfully engineered a series of tumor neoantigen vaccines capable of eliciting robust neoantigen-specific immune responses. With the help of NitraTh epitope, even mutations with low predicted affinity for MHC class I molecules were successfully induced to elicit neoantigen-specific responses. In H22 cell allograft and patient-derived xenograft (PDX) liver cancer mouse models, the NitraTh epitope-based neoantigen vaccines significantly suppressed tumor progression. More strikingly, through single-cell sequencing we found that the NitraTh epitope-based neoantigen vaccines regulate macrophage reprogramming and modulate macrophages to decrease the levels of the immunosuppressive molecule prostaglandin E2 (PGE2), which in turn reshapes the tumor immunosuppressive microenvironment. In summary, NitraTh epitope-based neoantigen vaccines possess the dual effects of potently activating neoantigen-specific immunity and alleviating immunosuppression, potentially providing a new paradigm for the design of tumor neoantigen vaccines.