Immunogenicity and therapeutic targeting of a public neoantigen derived from mutated PIK3CA

Regional and intratumoral adoptive T-cell therapy

Adoptive T-cell therapies (ACTs) including tumor-infiltrating lymphocytes and engineered T cells (transgenic T-cell receptor and chimeric antigen receptor T cells), have made an important impact in the field of cancer treatment over the past years. Most of these therapies are typically administered systemically in approaches that facilitate the elimination of hematologic malignancies. Therapeutical efficacy against solid tumors, however, with the exception of tumor-infiltrating lymphocytes against melanoma, remains limited due to several barriers preventing lymphocyte access to the tumor bed. Building upon the experience of regional administration in other immunotherapies, the regional administration of adoptive cell therapies is being assessed to overcome this challenge, granting a first round of access of the transferred T cells to the tumor niche and thereby ensuring their activation and expansion. Intralesional and intracavitary routes of delivery have been tested with promising antitumor objective responses in preclinical and clinical studies. Additionally, several strategies are being developed to further improve T-cell activity after reinfusing them back to the patient such as combinations with other immunotherapy agents or direct engineering of the transferred T cells, achieving long-term immune memory. Clinical trials testing different regional adoptive T-cell therapies are ongoing but some issues related to methodology of administration and correct selection of the target antigen to avoid on-target/off-tumor side-effects need to be further evaluated and improved. Herein, we discuss the current preclinical and clinical landscape of intratumoral and locoregional delivery of adoptive T-cell therapies.

TCR-T cell therapy: current development approaches, preclinical evaluation, and perspectives on regulatory challenges

TCR-T cell therapy represents a promising advancement in adoptive immunotherapy for cancer treatment. Despite its potential, the development and preclinical testing of TCR-T cells face significant challenges. This review provides a structured overview of the key stages in preclinical testing, including in silico, in vitro, and in vivo methods, within the context of the sequential development of novel therapies. This review aimed to systematically outline the processes for evaluating TCR-T cells at each stage: from in silico approaches used to predict target antigens, assess cross-reactivity, and minimize off-target effects, to in vitro assays designed to measure cell functionality, cytotoxicity, and activation. Additionally, the review discusses the limitations of in vivo testing in animal models, particularly in accurately reflecting the human tumor microenvironment and immune responses. Performed analysis emphasizes the importance of these preclinical stages in the safe and effective development of TCR-T cell therapies. While current models provide valuable insights, we identify critical gaps, particularly in in vivo biodistribution and toxicity assessments, and propose the need for enhanced standardization and the development of more representative models. This structured approach aims to improve the predictability and safety of TCR-T cell therapy as it advances towards clinical application.

T cell-redirecting therapies in hematological malignancies: Current developments and novel strategies for improved targeting

T cell-redirecting therapies (TCRTs), such as chimeric antigen receptor (CAR) or T cell receptor (TCR) T cells and T cell engagers, have emerged as a highly effective treatment modality, particularly in the B and plasma cell-malignancy setting. However, many patients fail to achieve deep and durable responses; while the lack of truly unique tumor antigens, and concurrent on-target/off-tumor toxicities, have hindered the development of TCRTs for many other cancers. In this review, we discuss the recent developments in TCRT targets for hematological malignancies, as well as novel targeting strategies that aim to address these, and other, challenges.

Personalized cancer T-cell therapy takes the stage, mirroring vaccine success

Personalized T-cell therapy is emerging as a pivotal treatment of cancer care by tailoring cellular therapies to individual genetic and antigenic profiles, echoing the exciting success of personalized vaccines. We describe here the parallel evolution and analogies of cancer vaccines and T-cell therapies.

Improvement of Tumor Neoantigen Detection by High-Field Asymmetric Waveform Ion Mobility Mass Spectrometry

Cancer neoantigens have been shown to elicit cancer-specific T-cell responses and have garnered much attention for their roles in both spontaneous and therapeutically induced antitumor responses. Mass spectrometry (MS) profiling of tumor immunopeptidomes has been used, in part, to identify MHC-bound mutant neoantigen ligands. However, under standard conditions, MS-based detection of such rare but clinically relevant neoantigens is relatively insensitive, requiring 300 million cells or more. Here, to quantitatively define the minimum detectable amounts of therapeutically relevant MHC-I and MHC-II neoantigen peptides, we analyzed different dilutions of immunopeptidomes isolated from the well-characterized T3 mouse methylcholanthrene (MCA)-induced cell line by MS. Using either data-dependent acquisition or parallel reaction monitoring (PRM), we established the minimum amount of material required to detect the major T3 neoantigens in the presence or absence of high field asymmetric waveform ion mobility spectrometry (FAIMS). This analysis yielded a 14-fold enhancement of sensitivity in detecting the major T3 MHC-I neoantigen (mLama4) with FAIMS-PRM compared with PRM without FAIMS, allowing ex vivo detection of this neoantigen from an individual 100 mg T3 tumor. These findings were then extended to two other independent MCA-sarcoma lines (1956 and F244). This study demonstrates that FAIMS substantially increases the sensitivity of MS-based characterization of validated neoantigens from tumors.

Systematic discovery of neoepitope-HLA pairs for neoantigens shared among patients and tumor types

The broad application of precision cancer immunotherapies is limited by the number of validated neoepitopes that are common among patients or tumor types. To expand the known repertoire of shared neoantigen-human leukocyte antigen (HLA) complexes, we developed a high-throughput platform that coupled an in vitro peptide-HLA binding assay with engineered cellular models expressing individual HLA alleles in combination with a concatenated transgene harboring 47 common cancer neoantigens. From more than 24,000 possible neoepitope-HLA combinations, biochemical and computational assessment yielded 844 unique candidates, of which 86 were verified after immunoprecipitation mass spectrometry analyses of engineered, monoallelic cell lines. To evaluate the potential for immunogenicity, we identified T cell receptors that recognized select neoepitope-HLA pairs and elicited a response after introduction into human T cells. These cellular systems and our data on therapeutically relevant neoepitopes in their HLA contexts will aid researchers studying antigen processing as well as neoepitope targeting therapies.

Public neoantigens in breast cancer immunotherapy (Review)

Among women globally, breast cancer is the most prevalent cancer and the leading cause of cancer‑related death. Interestingly, though genetic mutations contribute to the disease, <15% of women diagnosed with breast cancer have a family history of the disease, suggesting a prevalence of sporadic genetic mutations in breast cancer development. In the rapidly rising field of cancer genomics, neoantigen‑based immunotherapy has come to the fore. The investigation of novel proteins arising from unique somatic mutations or neoantigens have opened a new pathway for both individualized and public cancer treatments. Because they are shared among individuals with similar genetic changes, public neoantigens provide an opportunity for 'off‑the‑shelf' anticancer therapies, potentially extending the benefits to a wider patient group. The present review aimed to highlight the role of shared or public neoantigens as therapeutic targets for patients with breast cancer, emphasizing common hotspot mutations of certain genes identified in breast cancer. The clinical utilization of public neoantigen‑based therapies for breast cancer treatment were also discussed.

Development and Clinical Applications of Therapeutic Cancer Vaccines with Individualized and Shared Neoantigens

Neoantigens, presented as peptides on the surfaces of cancer cells, have recently been proposed as optimal targets for immunotherapy in clinical practice. The promising outcomes of neoantigen-based cancer vaccines have inspired enthusiasm for their broader clinical applications. However, the individualized tumor-specific antigens (TSA) entail considerable costs and time due to the variable immunogenicity and response rates of these neoantigens-based vaccines, influenced by factors such as neoantigen response, vaccine types, and combination therapy. Given the crucial role of neoantigen efficacy, a number of bioinformatics algorithms and pipelines have been developed to improve the accuracy rate of prediction through considering a series of factors involving in HLA-peptide-TCR complex formation, including peptide presentation, HLA-peptide affinity, and TCR recognition. On the other hand, shared neoantigens, originating from driver mutations at hot mutation spots (e.g., KRASG12D), offer a promising and ideal target for the development of therapeutic cancer vaccines. A series of clinical practices have established the efficacy of these vaccines in patients with distinct HLA haplotypes. Moreover, increasing evidence demonstrated that a combination of tumor associated antigens (TAAs) and neoantigens can also improve the prognosis, thus expand the repertoire of shared neoantigens for cancer vaccines. In this review, we provide an overview of the complex process involved in identifying personalized neoantigens, their clinical applications, advances in vaccine technology, and explore the therapeutic potential of shared neoantigen strategies.

Identification of an HLA-A*11:01-restricted neoepitope of mutant PIK3CA and its specific T cell receptors for cancer immunotherapy targeting hotspot driver mutations

Hotspot driver mutations presented by human leukocyte antigens might be recognized by anti-tumor T cells. Based on their advantages of tumor-specificity and immunogenicity, neoantigens derived from hotspot mutations, such as PIK3CAH1047L, may serve as emerging targets for cancer immunotherapies. NetMHCpan V4.1 was utilized for predicting neoepitopes of PIK3CA hotspot mutation. Using in vitro stimulation, antigen-specific T cells targeting the HLA-A*11:01-restricted PIK3CA mutation were isolated from healthy donor-derived peripheral blood mononuclear cells. T cell receptors (TCRs) were cloned using single-cell PCR and sequencing. Their functionality was assessed through T cell activation markers, cytokine production and cytotoxic response to cancer cell lines pulsed with peptides or transduced genes of mutant PIK3CA. Immunogenic mutant antigens from PIK3CA and their corresponding CD8+ T cells were identified. These PIK3CA mutation-specific CD8+ T cells were subsequently enriched, and their TCRs were isolated. The TCR clones exhibited mutation-specific and HLA-restricted reactivity, demonstrating varying degrees of functional avidity. Identified TCR genes were transferred into CD8+ Jurkat cells and primary T cells deficient of endogenous TCRs. TCR-expressing cells demonstrated specific recognition and reactivity against the PIK3CAH1047L peptide presented by HLA-A*11:01-expressing K562 cells. Furthermore, mutation-specific TCR-T cells demonstrated an elevation in cytokine production and profound cytotoxic effects against HLA-A*11:01+ malignant cell lines harboring PIK3CAH1047L. Our data demonstrate the immunogenicity of an HLA-A*11:01-restricted PIK3CA hotspot mutation and its targeting therapeutic potential, together with promising candidates of TCR-T cell therapy.

Neoantigen-specific stimulation of tumor-infiltrating lymphocytes enables effective TCR isolation and expansion while preserving stem-like memory phenotypes

BACKGROUND

Tumor-infiltrating lymphocytes (TILs) targeting neoantigens can effectively treat a selected set of metastatic solid cancers. However, harnessing TILs for cancer treatments remains challenging because neoantigen-reactive T cells are often rare and exhausted, and ex vivo expansion can further reduce their frequencies. This complicates the identification of neoantigen-reactive T-cell receptors (TCRs) and the development of TIL products with high reactivity for patient treatment.

METHODS

We tested whether TILs could be in vitro stimulated against neoantigens to achieve selective expansion of neoantigen-reactive TILs. Given their prevalence, mutant p53 or RAS were studied as models of human neoantigens. An in vitro stimulation method, termed "NeoExpand", was developed to provide neoantigen-specific stimulation to TILs. 25 consecutive patient TILs from tumors harboring p53 or RAS mutations were subjected to NeoExpand.

RESULTS

We show that neoantigenic stimulation achieved selective expansion of neoantigen-reactive TILs and broadened the neoantigen-reactive CD4+ and CD8+ TIL clonal repertoire. This allowed the effective isolation of novel neoantigen-reactive TCRs. Out of the 25 consecutive TIL samples, neoantigenic stimulation enabled the identification of 16 unique reactivities and 42 TCRs, while conventional TIL expansion identified 9 reactivities and 14 TCRs. Single-cell transcriptome analysis revealed that neoantigenic stimulation increased neoantigen-reactive TILs with stem-like memory phenotypes expressing IL-7R, CD62L, and KLF2. Furthermore, neoantigenic stimulation improved the in vivo antitumor efficacy of TILs relative to the conventional OKT3-induced rapid TIL expansion in p53-mutated or KRAS-mutated xenograft mouse models.

CONCLUSIONS

Taken together, neoantigenic stimulation of TILs selectively expands neoantigen-reactive TILs by frequencies and by their clonal repertoire. NeoExpand led to improved phenotypes and functions of neoantigen-reactive TILs. Our data warrant its clinical evaluation.

TRIAL REGISTRATION NUMBER

NCT00068003, NCT01174121, and NCT03412877.

Dynamic allostery in the peptide/MHC complex enables TCR neoantigen selectivity

The inherent cross-reactivity of the T cell receptor (TCR) is balanced by high specificity, which often manifests in confounding ways not easily interpretable from static structures. We show here that TCR discrimination between an HLA-A*03:01 (HLA-A3)-restricted public neoantigen derived from mutant PIK3CA and its wild-type (WT) counterpart emerges from motions within the HLA binding groove that vary with the identity of the peptide's first primary anchor. The motions form a dynamic gate that in the complex with the WT peptide impedes a large conformational change required for TCR binding. The more rigid neoantigen is insusceptible to this limiting dynamic, and with the gate open, is able to transit its central tryptophan residue underneath the peptide backbone to the contralateral side of the HLA-A3 peptide binding groove, facilitating TCR binding. Our findings reveal a novel mechanism driving TCR specificity for a cancer neoantigen that is rooted in the dynamic and allosteric nature of peptide/MHC-I complexes, with implications for resolving long-standing and often confounding questions about the determinants of T cell specificity.

The potential and promise for clinical application of adoptive T cell therapy in cancer

Adoptive cell therapy has revolutionized cancer treatment, especially for hematologic malignancies. T cells are the most extensively utilized cells in adoptive cell therapy. Currently, tumor-infiltrating lymphocytes, T cell receptor-transgenic T cells and chimeric antigen receptor T cells are the three main adoptive T cell therapies. Tumor-infiltrating lymphocytes kill tumors by reinfusing enlarged lymphocytes that naturally target tumor-specific antigens into the patient. T cell receptor-transgenic T cells have the ability to specifically destroy tumor cells via the precise recognition of exogenous T cell receptors with major histocompatibility complex. Chimeric antigen receptor T cells transfer genes with specific antigen recognition structural domains and T cell activation signals into T cells, allowing T cells to attack tumors without the assistance of major histocompatibility complex. Many barriers have been demonstrated to affect the clinical efficacy of adoptive T cell therapy, such as tumor heterogeneity and antigen loss, hard trafficking and infiltration, immunosuppressive tumor microenvironment and T cell exhaustion. Several strategies to improve the efficacy of adoptive T cell therapy have been explored, including multispecific chimeric antigen receptor T cell therapy, combination with immune checkpoint blockade, targeting the immunosuppressive tumor microenvironment, etc. In this review, we will summarize the current status and clinical application, followed by major bottlenecks in adoptive T cell therapy. In addition, we will discuss the promising strategies to improve adoptive T cell therapy. Adoptive T cell therapy will result in even more incredible advancements in solid tumors if the aforementioned problems can be handled.

Self-supervised learning of T cell receptor sequences exposes core properties for T cell membership

The T cell receptor (TCR) repertoire is an extraordinarily diverse collection of TCRs essential for maintaining the body's homeostasis and response to threats. In this study, we compiled an extensive dataset of more than 4200 bulk TCR repertoire samples, encompassing 221,176,713 sequences, alongside 6,159,652 single-cell TCR sequences from over 400 samples. From this dataset, we then selected a representative subset of 5 million bulk sequences and 4.2 million single-cell sequences to train two specialized Transformer-based language models for bulk (CVC) and single-cell (scCVC) TCR repertoires, respectively. We show that these models successfully capture TCR core qualities, such as sharing, gene composition, and single-cell properties. These qualities are emergent in the encoded TCR latent space and enable classification into TCR-based qualities such as public sequences. These models demonstrate the potential of Transformer-based language models in TCR downstream applications.

Recent Findings on Therapeutic Cancer Vaccines: An Updated Review

Cancer remains one of the global leading causes of death and various vaccines have been developed over the years against it, including cell-based, nucleic acid-based, and viral-based cancer vaccines. Although many vaccines have been effective in in vivo and clinical studies and some have been FDA-approved, there are major limitations to overcome: (1) developing one universal vaccine for a specific cancer is difficult, as tumors with different antigens are different for different individuals, (2) the tumor antigens may be similar to the body's own antigens, and (3) there is the possibility of cancer recurrence. Therefore, developing personalized cancer vaccines with the ability to distinguish between the tumor and the body's antigens is indispensable. This paper provides a comprehensive review of different types of cancer vaccines and highlights important factors necessary for developing efficient cancer vaccines. Moreover, the application of other technologies in cancer therapy is discussed. Finally, several insights and conclusions are presented, such as the possibility of using cold plasma and cancer stem cells in developing future cancer vaccines, to tackle the major limitations in the cancer vaccine developmental process.

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.

Birinapant Reshapes the Tumor Immunopeptidome and Enhances Antigen Presentation

Birinapant, an antagonist of the inhibitor of apoptosis proteins, upregulates MHCs in tumor cells and displays a better tumoricidal effect when used in combination with immune checkpoint inhibitors, indicating that Birinapant may affect the antigen presentation pathway; however, the mechanism remains elusive. Based on high-resolution mass spectrometry and in vitro and in vivo models, we adopted integrated genomics, proteomics, and immunopeptidomics strategies to study the mechanism underlying the regulation of tumor immunity by Birinapant from the perspective of antigen presentation. Firstly, in HT29 and MCF7 cells, Birinapant increased the number and abundance of immunopeptides and source proteins. Secondly, a greater number of cancer/testis antigen peptides with increased abundance and more neoantigens were identified following Birinapant treatment. Moreover, we demonstrate the existence and immunogenicity of a neoantigen derived from insertion/deletion mutation. Thirdly, in HT29 cell-derived xenograft models, Birinapant administration also reshaped the immunopeptidome, and the tumor exhibited better immunogenicity. These data suggest that Birinapant can reshape the tumor immunopeptidome with respect to quality and quantity, which improves the presentation of CTA peptides and neoantigens, thus enhancing the immunogenicity of tumor cells. Such changes may be vital to the effectiveness of combination therapy, which can be further transferred to the clinic or aid in the development of new immunotherapeutic strategies to improve the anti-tumor immune response.

Structural basis for self-discrimination by neoantigen-specific TCRs

T cell receptors (TCR) are pivotal in mediating tumour cell cytolysis via recognition of mutation-derived tumour neoantigens (neoAgs) presented by major histocompatibility class-I (MHC-I). Understanding the factors governing the emergence of neoAg from somatic mutations is a major focus of current research. However, the structural and cellular determinants controlling TCR recognition of neoAgs remain poorly understood. This study describes the multi-level analysis of a model neoAg from the B16F10 murine melanoma, H2-Db/Hsf2 p.K72N68-76, as well as its cognate TCR 47BE7. Through cellular, molecular and structural studies we demonstrate that the p.K72N mutation enhances H2-Db binding, thereby improving cell surface presentation and stabilizing the TCR 47BE7 epitope. Furthermore, TCR 47BE7 exhibited high functional avidity and selectivity, attributable to a broad, stringent, binding interface enabling recognition of native B16F10 despite low antigen density. Our findings provide insight into the generation of anchor-residue modified neoAg, and emphasize the value of molecular and structural investigations of neoAg in diverse MHC-I contexts for advancing the understanding of neoAg immunogenicity.

Incongruity between T cell receptor recognition of breast cancer hotspot mutations ESR1 Y537S and D538G following exogenous peptide loading versus endogenous antigen processing

T cell receptor engineered T cell (TCR T) therapies have shown recent efficacy against certain types of solid metastatic cancers. However, to extend TCR T therapies to treat more patients across additional cancer types, new TCRs recognizing cancer-specific antigen targets are needed. Driver mutations in AKT1, ESR1, PIK3CA, and TP53 are common in patients with metastatic breast cancer (MBC) and if immunogenic could serve as ideal tumor-specific targets for TCR T therapy to treat this disease. Through IFN-γ ELISpot screening of in vitro expanded neopeptide-stimulated T cell lines from healthy donors and MBC patients, we identified reactivity towards 11 of 13 of the mutations. To identify neopeptide-specific TCRs, we then performed single-cell RNA sequencing of one of the T cell lines following neopeptide stimulation. Here, we identified an ESR1 Y537S specific T cell clone, clonotype 16, and an ESR1 Y537S/D538G dual-specific T cell clone, clonotype 21, which were HLA-B*40:02 and HLA-C*01:02 restricted, respectively. TCR Ts expressing these TCRs recognized and killed target cells pulsed with ESR1 neopeptides with minimal activity against ESR1 WT peptide. However, these TCRs failed to recognize target cells expressing endogenous mutant ESR1. To investigate the basis of this lack of recognition we performed immunopeptidomics analysis of a mutant-overexpressing lymphoblastoid cell line and found that the ESR1 Y537S neopeptide was not endogenously processed, despite binding to HLA-B*40:02 when exogenously pulsed onto the target cell. These results indicate that stimulation of T cells that likely derive from the naïve repertoire with pulsed minimal peptides may lead to the expansion of clones that recognize non-processed peptides, and highlights the importance of using methods that selectively expand T cells with specificity for antigens that are efficiently processed and presented.

Challenges in developing personalized neoantigen cancer vaccines

The recent success of cancer immunotherapies has highlighted the benefit of harnessing the immune system for cancer treatment. Vaccines have a long history of promoting immunity to pathogens and, consequently, vaccines targeting cancer neoantigens have been championed as a tool to direct and amplify immune responses against tumours while sparing healthy tissue. In recent years, extensive preclinical research and more than one hundred clinical trials have tested different strategies of neoantigen discovery and vaccine formulations. However, despite the enthusiasm for neoantigen vaccines, proof of unequivocal efficacy has remained beyond reach for the majority of clinical trials. In this Review, we focus on the key obstacles pertaining to vaccine design and tumour environment that remain to be overcome in order to unleash the true potential of neoantigen vaccines in cancer therapy.

Computational immunogenomic approaches to predict response to cancer immunotherapies

Cancer immunogenomics is an emerging field that bridges genomics and immunology. The establishment of large-scale genomic collaborative efforts along with the development of new single-cell transcriptomic techniques and multi-omics approaches have enabled characterization of the mutational and transcriptional profiles of many cancer types and helped to identify clinically actionable alterations as well as predictive and prognostic biomarkers. Researchers have developed computational approaches and machine learning algorithms to accurately obtain clinically useful information from genomic and transcriptomic sequencing data from bulk tissue or single cells and explore tumours and their microenvironment. The rapid growth in sequencing and computational approaches has resulted in the unmet need to understand their true potential and limitations in enabling improvements in the management of patients with cancer who are receiving immunotherapies. In this Review, we describe the computational approaches currently available to analyse bulk tissue and single-cell sequencing data from cancer, stromal and immune cells, as well as how best to select the most appropriate tool to address various clinical questions and, ultimately, improve patient outcomes.

Neoantigen cancer vaccines: a new star on the horizon

Immunotherapy represents a promising strategy for cancer treatment that utilizes immune cells or drugs to activate the patient's own immune system and eliminate cancer cells. One of the most exciting advances within this field is the targeting of neoantigens, which are peptides derived from non-synonymous somatic mutations that are found exclusively within cancer cells and absent in normal cells. Although neoantigen-based therapeutic vaccines have not received approval for standard cancer treatment, early clinical trials have yielded encouraging outcomes as standalone monotherapy or when combined with checkpoint inhibitors. Progress made in high-throughput sequencing and bioinformatics have greatly facilitated the precise and efficient identification of neoantigens. Consequently, personalized neoantigen-based vaccines tailored to each patient have been developed that are capable of eliciting a robust and long-lasting immune response which effectively eliminates tumors and prevents recurrences. This review provides a concise overview consolidating the latest clinical advances in neoantigen-based therapeutic vaccines, and also discusses challenges and future perspectives for this innovative approach, particularly emphasizing the potential of neoantigen-based therapeutic vaccines to enhance clinical efficacy against advanced solid tumors.

Engineered Adoptive T-Cell Therapies for Breast Cancer: Current Progress, Challenges, and Potential

Breast cancer remains a significant health challenge, and novel treatment approaches are critically needed. This review presents an in-depth analysis of engineered adoptive T-cell therapies (E-ACTs), an innovative frontier in cancer immunotherapy, focusing on their application in breast cancer. We explore the evolving landscape of chimeric antigen receptor (CAR) and T-cell receptor (TCR) T-cell therapies, highlighting their potential and challenges in targeting breast cancer. The review addresses key obstacles such as target antigen selection, the complex breast cancer tumor microenvironment, and the persistence of engineered T-cells. We discuss the advances in overcoming these barriers, including strategies to enhance T-cell efficacy. Finally, our comprehensive analysis of the current clinical trials in this area provides insights into the future possibilities and directions of E-ACTs in breast cancer treatment.

How does TCR-T cell therapy exhibit a superior anti-tumor efficacy

TCR-engineered T cells have achieved great progress in solid tumor therapy, some of which have been applicated in clinical trials. Deep knowledge about the current progress of TCR-T in tumor therapy would be beneficial to understand the direction. Here, we classify tumor antigens into tumor-associated antigens, tumor-specific antigens, tumor antigens expressed by oncogenic viruses, and tumor antigens caused by abnormal protein modification; Then we detail the TCR-T cell therapy effects targeting those tumor antigens in clinical or preclinical trials, and propose that neoantigen specific TCR-T cell therapy is expected to be a promising approach for solid tumors; Furthermore, we summarize the optimization strategies, such as tumor microenvironment, TCR pairing and affinity, to improve the therapeutic effect of TCR-T. Overall, this review provides inspiration for the antigen selection and therapy strategies of TCR-T in the future.

Nivolumab plus ipilimumab in advanced salivary gland cancer: a phase 2 trial

Salivary gland cancers (SGCs) are rare, aggressive cancers without effective treatments when metastasized. We conducted a phase 2 trial evaluating nivolumab (nivo, anti-PD-1) and ipilimumab (ipi, anti-CTLA-4) in 64 patients with metastatic SGC enrolled in two histology-based cohorts (32 patients each): adenoid cystic carcinoma (ACC; cohort 1) and other SGCs (cohort 2). The primary efficacy endpoint (≥4 objective responses) was met in cohort 2 (5/32, 16%) but not in cohort 1 (2/32, 6%). Treatment safety/tolerability and progression-free survival (PFS) were secondary endpoints. Treatment-related adverse events grade ≥3 occurred in 24 of 64 (38%) patients across both cohorts, and median PFS was 4.4 months (95% confidence interval (CI): 2.4, 8.3) and 2.2 months (95% CI: 1.8, 5.3) for cohorts 1 and 2, respectively. We present whole-exome, RNA and T cell receptor (TCR) sequencing data from pre-treatment and on-treatment tumors and immune cell flow cytometry and TCR sequencing from peripheral blood at serial timepoints. Responding tumors universally demonstrated clonal expansion of pre-existing T cells and mutational contraction. Responding ACCs harbored neoantigens, including fusion-derived neoepitopes, that induced T cell responses ex vivo. This study shows that nivo+ipi has limited efficacy in ACC, albeit with infrequent, exceptional responses, and that it could be promising for non-ACC SGCs, particularly salivary duct carcinomas. ClinicalTrials.gov identifier: NCT03172624 .

T cell receptor therapeutics: immunological targeting of the intracellular cancer proteome

The T cell receptor (TCR) complex is a naturally occurring antigen sensor that detects, amplifies and coordinates cellular immune responses to epitopes derived from cell surface and intracellular proteins. Thus, TCRs enable the targeting of proteins selectively expressed by cancer cells, including neoantigens, cancer germline antigens and viral oncoproteins. As such, TCRs have provided the basis for an emerging class of oncology therapeutics. Herein, we review the current cancer treatment landscape using TCRs and TCR-like molecules. This includes adoptive cell transfer of T cells expressing endogenous or engineered TCRs, TCR bispecific engagers and antibodies specific for human leukocyte antigen (HLA)-bound peptides (TCR mimics). We discuss the unique complexities associated with the clinical development of these therapeutics, such as HLA restriction, TCR retrieval, potency assessment and the potential for cross-reactivity. In addition, we highlight emerging clinical data that establish the antitumour potential of TCR-based therapies, including tumour-infiltrating lymphocytes, for the treatment of diverse human malignancies. Finally, we explore the future of TCR therapeutics, including emerging genome editing methods to safely enhance potency and strategies to streamline patient identification.

Structural basis for T cell recognition of cancer neoantigens and implications for predicting neoepitope immunogenicity

Adoptive cell therapy (ACT) with tumor-specific T cells has been shown to mediate durable cancer regression. Tumor-specific T cells are also the basis of other therapies, notably cancer vaccines. The main target of tumor-specific T cells are neoantigens resulting from mutations in self-antigens over the course of malignant transformation. The detection of neoantigens presents a major challenge to T cells because of their high structural similarity to self-antigens, and the need to avoid autoimmunity. How different a neoantigen must be from its wild-type parent for it to induce a T cell response is poorly understood. Here we review recent structural and biophysical studies of T cell receptor (TCR) recognition of shared cancer neoantigens derived from oncogenes, including p53R175H, KRASG12D, KRASG12V, HHATp8F, and PIK3CAH1047L. These studies have revealed that, in some cases, the oncogenic mutation improves antigen presentation by strengthening peptide-MHC binding. In other cases, the mutation is detected by direct interactions with TCR, or by energetically driven or other indirect strategies not requiring direct TCR contacts with the mutation. We also review antibodies designed to recognize peptide-MHC on cell surfaces (TCR-mimic antibodies) as an alternative to TCRs for targeting cancer neoantigens. Finally, we review recent computational advances in this area, including efforts to predict neoepitope immunogenicity and how these efforts may be advanced by structural information on peptide-MHC binding and peptide-MHC recognition by TCRs.

Genomic alterations associated with pseudoprogression and hyperprogressive disease during anti-PD1 treatment for advanced non-small-cell lung cancer

Introduction

This study aimed to elucidate the relationship between dynamic genomic mutation alteration and pseudoprogression (PsPD)/hyperprogressive disease (HPD) in immunotherapy-treated advanced non-small-cell lung cancer (NSCLC), to provide clinical evidence for identifying and distinguishing between PsPD and HPD.

Method

Patients with advanced NSCLC who were treated with anti-PD1 were enrolled. Whole blood was collected at baseline and post image progression. Serum was separated and sequenced using 425-panel next-generation sequencing analysis (NGS).

Results

NGS revealed that not only single gene mutations were associated with PsPD/HPD before treatment, dynamic monitoring of the whole-blood genome mutation spectrum also varied greatly. Mutational burden, allele frequency%, and relative circulating tumor DNA abundance indicated that the fold change after image progression was much higher in the HPD group.

Discussion

The gene mutation profiles of PsPD and HPD not only differed before treatment, but higher genome mutation spectrum post image progression indicated true disease progression in patients with HPD. This suggests that dynamic whole-genome mutation profile monitoring as NGS can distinguish PsPD from HPD more effectively than single gene detection, providing a novel method for guiding clinical immune treatment.

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.

Coengineering specificity, safety, and function into T cells for cancer immunotherapy

Adoptive T-cell transfer (ACT) therapies, including of tumor infiltrating lymphocytes (TILs) and T cells gene-modified to express either a T cell receptor (TCR) or a chimeric antigen receptor (CAR), have demonstrated clinical efficacy for a proportion of patients and cancer-types. The field of ACT has been driven forward by the clinical success of CD19-CAR therapy against various advanced B-cell malignancies, including curative responses for some leukemia patients. However, relapse remains problematic, in particular for lymphoma. Moreover, for a variety of reasons, relative limited efficacy has been demonstrated for ACT of non-hematological solid tumors. Indeed, in addition to pre-infusion challenges including lymphocyte collection and manufacturing, ACT failure can be attributed to several biological processes post-transfer including, (i) inefficient tumor trafficking, infiltration, expansion and retention, (ii) chronic antigen exposure coupled with insufficient costimulation resulting in T-cell exhaustion, (iii) a range of barriers in the tumor microenvironment (TME) mediated by both tumor cells and suppressive immune infiltrate, (iv) tumor antigen heterogeneity and loss, or down-regulation of antigen presentation machinery, (v) gain of tumor intrinsic mechanisms of resistance such as to apoptosis, and (vi) various forms of toxicity and other adverse events in patients. Affinity-optimized TCRs can improve T-cell function and innovative CAR designs as well as gene-modification strategies can be used to coengineer specificity, safety, and function into T cells. Coengineering strategies can be designed not only to directly support the transferred T cells, but also to block suppressive barriers in the TME and harness endogenous innate and adaptive immunity. Here, we review a selection of the remarkable T-cell coengineering strategies, including of tools, receptors, and gene-cargo, that have been developed in recent years to augment tumor control by ACT, more and more of which are advancing to the clinic.

Challenges and solutions for therapeutic TCR-based agents

Recent development of methods to discover and engineer therapeutic T-cell receptors (TCRs) or antibody mimics of TCRs, and to understand their immunology and pharmacology, lag two decades behind therapeutic antibodies. Yet we have every expectation that TCR-based agents will be similarly important contributors to the treatment of a variety of medical conditions, especially cancers. TCR engineered cells, soluble TCRs and their derivatives, TCR-mimic antibodies, and TCR-based CAR T cells promise the possibility of highly specific drugs that can expand the scope of immunologic agents to recognize intracellular targets, including mutated proteins and undruggable transcription factors, not accessible by traditional antibodies. Hurdles exist regarding discovery, specificity, pharmacokinetics, and best modality of use that will need to be overcome before the full potential of TCR-based agents is achieved. HLA restriction may limit each agent to patient subpopulations and off-target reactivities remain important barriers to widespread development and use of these new agents. In this review we discuss the unique opportunities for these new classes of drugs, describe their unique antigenic targets, compare them to traditional antibody therapeutics and CAR T cells, and review the various obstacles that must be overcome before full application of these drugs can be realized.

Successes and challenges in clinical gene therapy

Despite the ups and downs in the field over three decades, the science of gene therapy has continued to advance and provide enduring treatments for increasing number of diseases. There are active clinical trials approaching a variety of inherited and acquired disorders of different organ systems. Approaches include ex vivo modification of hematologic stem cells (HSC), T lymphocytes and other immune cells, as well as in vivo delivery of genes or gene editing reagents to the relevant target cells by either local or systemic administration. In this article, we highlight success and ongoing challenges in three areas of high activity in gene therapy: inherited blood cell diseases by targeting hematopoietic stem cells, malignant disorders using immune effector cells genetically modified with chimeric antigen receptors, and ophthalmologic, neurologic, and coagulation disorders using in vivo administration of adeno-associated virus (AAV) vectors. In recent years, there have been true cures for many of these diseases, with sustained clinical benefit that exceed those from other medical approaches. Each of these treatments faces ongoing challenges, namely their high one-time costs and the complexity of manufacturing the therapeutic agents, which are biological viruses and cell products, at pharmacologic standards of quality and consistency. New models of reimbursement are needed to make these innovative treatments widely available to patients in need.

Tumor-wide RNA splicing aberrations generate immunogenic public neoantigens

T-cell-mediated immunotherapies are limited by the extent to which cancer-specific antigens are homogenously expressed throughout a tumor. We reasoned that recurrent splicing aberrations in cancer represent a potential source of tumor-wide and public neoantigens, and to test this possibility, we developed a novel pipeline for identifying neojunctions expressed uniformly within a tumor across diverse cancer types. Our analyses revealed multiple neojunctions that recur across patients and either exhibited intratumor heterogeneity or, in some cases, were tumor-wide. We identified CD8+ T-cell clones specific for neoantigens derived from tumor-wide and conserved neojunctions in GNAS and RPL22 , respectively. TCR-engineered CD8 + T-cells targeting these mutations conferred neoantigen-specific tumor cell eradication. Furthermore, we revealed that cancer-specific dysregulation in splicing factor expression leads to recurrent neojunction expression. Together, these data reveal that a subset of neojunctions are both intratumorally conserved and public, providing the molecular basis for novel T-cell-based immunotherapies that address intratumoral heterogeneity.

HLA3DB: comprehensive annotation of peptide/HLA complexes enables blind structure prediction of T cell epitopes

The class I proteins of the major histocompatibility complex (MHC-I) display epitopic peptides derived from endogenous proteins on the cell surface for immune surveillance. Accurate modeling of peptides bound to the human MHC, HLA, has been mired by conformational diversity of the central peptide residues, which are critical for recognition by T cell receptors. Here, analysis of X-ray crystal structures within our curated database (HLA3DB) shows that pHLA complexes encompassing multiple HLA allotypes present a discrete set of peptide backbone conformations. Leveraging these backbones, we employ a regression model trained on terms of a physically relevant energy function to develop a comparative modeling approach for nonamer pHLA structures named RepPred. Our method outperforms the top pHLA modeling approach by up to 19% in structural accuracy, and consistently predicts blind targets not included in our training set. Insights from our work may be applied towards predicting antigen immunogenicity, and receptor cross-reactivity.

Anti-cervical cancer mechanism of bioactive compounds from Alangium platanifolium based on the 'compound-target-disease' network

In this study, we analyzed the chemical compositions of Alangium platanifolium (Sieb. et Zucc.) Harms (AP) using ultraperformance liquid chromatography-quadrupole time-of-flight mass spectrometry (UPLC-Q-TOF-MS) non-targeted plant metabolomics integration MolNetEnhancer strategy. A total of 75 compounds, including flavonoids, alkaloids, terpenes, C21 steroids, among others, were identified by comparing accurate mass-to-charge ratios, MS2 cleavage fragments, retention times, and MolNetenhancer-integrated analytical data, and the cleavage rules of the characteristic compounds were analyzed. A total of 125 potential cervical cancer (CC) therapeutic targets were obtained through Gene Expression Omnibus (GEO) data mining, differential analysis, and database screening. Hub targets were obtained by constructing protein-protein interaction (PPI) networks and CytoNCA topology analysis, including SRC, STAT3, TP53, PIK3R1, MAPK3, and PIK3CA. According to Gene ontology (GO) analysis, AP was primarily against CC by influencing gland development, oxidative stress processes, serine/threonine kinase, and tyrosine kinase activity. Enrichment analysis of the Kyoto Encyclopedia of Genes and Genomes (KEGG) indicated that the PI3K/AKT and MAPK signaling pathways play a crucial role in AP treatment for CC. The compound-target-pathway (C-T-P) network revealed that quercetin, methylprednisolone, and caudatin may play key roles in the treatment of CC. The results of molecular docking revealed that the core compound could bind significantly to the core target. In this study, the compounds in AP were systematically analyzed qualitatively, and the core components, core targets, and mechanisms of action of AP in the treatment of CC were screened through a combination of network pharmacology tools. Providing a scientific reference for the therapeutic material basis and quality control of AP.

Advances in vaccine development for cancer prevention and treatment in Lynch Syndrome

Lynch Syndrome (LS) is one of the most common hereditary cancer syndromes, and is caused by mutations in one of the four DNA mismatch repair (MMR) genes, namely MLH1, MSH2, MSH6 and PMS2. Tumors developed by LS carriers display high levels of microsatellite instability, which leads to the accumulation of large numbers of mutations, among which frameshift insertion/deletions (indels) within microsatellite (MS) loci are the most common. As a result, MMR-deficient (MMRd) cells generate increased rates of tumor-specific neoantigens (neoAgs) that can be recognized by the immune system to activate cancer cell killing. In this context, LS is an ideal disease to leverage immune-interception strategies. Therefore, the identification of these neoAgs is an ongoing effort for the development of LS cancer preventive vaccines. In this review, we summarize the computational methods used for in silico neoAg prediction, including their challenges, and the experimental techniques used for in vitro validation of their immunogenicity. In addition, we outline results from past and on-going vaccine clinical trials and highlight avenues for improvement and future directions.

A T cell receptor targeting a recurrent driver mutation in FLT3 mediates elimination of primary human acute myeloid leukemia in vivo

Acute myeloid leukemia (AML), the most frequent leukemia in adults, is driven by recurrent somatically acquired genetic lesions in a restricted number of genes. Treatment with tyrosine kinase inhibitors has demonstrated that targeting of prevalent FMS-related receptor tyrosine kinase 3 (FLT3) gain-of-function mutations can provide significant survival benefits for patients, although the efficacy of FLT3 inhibitors in eliminating FLT3-mutated clones is variable. We identified a T cell receptor (TCR) reactive to the recurrent D835Y driver mutation in the FLT3 tyrosine kinase domain (TCRFLT3D/Y). TCRFLT3D/Y-redirected T cells selectively eliminated primary human AML cells harboring the FLT3D835Y mutation in vitro and in vivo. TCRFLT3D/Y cells rejected both CD34+ and CD34- AML in mice engrafted with primary leukemia from patients, reaching minimal residual disease-negative levels, and eliminated primary CD34+ AML leukemia-propagating cells in vivo. Thus, T cells targeting a single shared mutation can provide efficient immunotherapy toward selective elimination of clonally involved primary AML cells in vivo.

MSI-XGNN: an explainable GNN computational framework integrating transcription- and methylation-level biomarkers for microsatellite instability detection

Microsatellite instability (MSI) is a hypermutator phenotype caused by DNA mismatch repair deficiency. MSI has been reported in various human cancers, particularly colorectal, gastric and endometrial cancers. MSI is a promising biomarker for cancer prognosis and immune checkpoint blockade immunotherapy. Several computational methods have been developed for MSI detection using DNA- or RNA-based approaches based on next-generation sequencing. Epigenetic mechanisms, such as DNA methylation, regulate gene expression and play critical roles in the development and progression of cancer. We here developed MSI-XGNN, a new computational framework for predicting MSI status using bulk RNA-sequencing and DNA methylation data. MSI-XGNN is an explainable deep learning model that combines a graph neural network (GNN) model to extract features from the gene-methylation probe network with a CatBoost model to classify MSI status. MSI-XGNN, which requires tumor-only samples, exhibited comparable performance with two well-known methods that require tumor-normal paired sequencing data, MSIsensor and MANTIS and better performance than several other tools. MSI-XGNN also showed good generalizability on independent validation datasets. MSI-XGNN identified six MSI markers consisting of four methylation probes (EPM2AIP1|MLH1:cg14598950, EPM2AIP1|MLH1:cg27331401, LNP1:cg05428436 and TSC22D2:cg15048832) and two genes (RPL22L1 and MSH4) constituting the optimal feature subset. All six markers were significantly associated with beneficial tumor microenvironment characteristics for immunotherapy, such as tumor mutation burden, neoantigens and immune checkpoint molecules such as programmed cell death-1 and cytotoxic T-lymphocyte antigen-4. Overall, our study provides a powerful and explainable deep learning model for predicting MSI status and identifying MSI markers that can potentially be used for clinical MSI evaluation.

Neoantigen identification: Technological advances and challenges

Neoantigens have emerged as promising targets for cutting-edge immunotherapies, such as cancer vaccines and adoptive cell therapy. These neoantigens are unique to tumors and arise exclusively from somatic mutations or non-genomic aberrations in tumor proteins. They encompass a wide range of alterations, including genomic mutations, post-transcriptomic variants, and viral oncoproteins. With the advancements in technology, the identification of immunogenic neoantigens has seen rapid progress, raising new opportunities for enhancing their clinical significance. Prediction of neoantigens necessitates the acquisition of high-quality samples and sequencing data, followed by mutation calling. Subsequently, the pipeline involves integrating various tools that can predict the expression, processing, binding, and recognition potential of neoantigens. However, the continuous improvement of computational tools is constrained by the availability of datasets which contain validated immunogenic neoantigens. This review article aims to provide a comprehensive summary of the current knowledge as well as limitations in neoantigen prediction and validation. Additionally, it delves into the origin and biological role of neoantigens, offering a deeper understanding of their significance in the field of cancer immunotherapy. This article thus seeks to contribute to the ongoing efforts to harness neoantigens as powerful weapons in the fight against cancer.

Association of HLA-A, B, and C alleles and cancer susceptibility in 179 solid malignancies

BACKGROUND

The major histocompatibility complex (MHC) genes are known to be capable of influencing the susceptibility of many cancers. All mammalian cells, including cancer cells, express MHC class I molecules consisting of human leukocyte antigens (HLA) A, B, and C. The tumor susceptibility of HLA-A, B, and C alleles has not been studied extensively in solid tumors.

METHODS

HLA-A, B, and C genotypes of 179 solid tumors were collected from Caris Comprehensive Tumor Profiling reports, including 45 GU, 44 GI, 28 pancreaticobiliary, 21 thoracic, 15 breast, 13 Gyn, among others. The tumors were mainly from Caucasians (82%). The HLA allele frequencies in the tumors were compared to those of respective ethnic populations in the US National Marrow Donor Program (NMDP) database. Fisher's exact tests were performed, adjusted P values were calculated using Benjamini-Hochberg's method for false discovery rate (FDR), and Prevalence ratios (PRs) were calculated to quantify associations.

RESULTS

Twenty-one alleles were not listed in the NMDP. Among them, A*11:303 alone was present in 11 carcinomas, and B*08:222 was seen in 4 tumors. Among the alleles listed in the NMDP, C*08:02, B*14:02, A*03:02, and B*44:06 were significantly associated with tumors in Caucasian Americans (PR: 2.50-170), while B*44:02 appeared protective (PR: 0.36). Alleles with less significant associations were listed.

CONCLUSIONS

From the HLA-A, B, and C data of the 179 tumors, we identified several susceptible alleles and one protective allele. Of interest, 21 alleles were not listed in the NMDP. The limited cases prevented our analysis from identifying cancer-susceptible alleles in other races.

TAPIR: a T-cell receptor language model for predicting rare and novel targets

T-cell receptors (TCRs) are involved in most human diseases, but linking their sequences with their targets remains an unsolved grand challenge in the field. In this study, we present TAPIR (T-cell receptor and Peptide Interaction Recognizer), a T-cell receptor (TCR) language model that predicts TCR-target interactions, with a focus on novel and rare targets. TAPIR employs deep convolutional neural network (CNN) encoders to process TCR and target sequences across flexible representations (e.g., beta-chain only, unknown MHC allele, etc.) and learns patterns of interactivity via several training tasks. This flexibility allows TAPIR to train on more than 50k either paired (alpha and beta chain) or unpaired TCRs (just alpha or beta chain) from public and proprietary databases against 1933 unique targets. TAPIR demonstrates state-of-the-art performance when predicting TCR interactivity against common benchmark targets and is the first method to demonstrate strong performance when predicting TCR interactivity against novel targets, where no examples are provided in training. TAPIR is also capable of predicting TCR interaction against MHC alleles in the absence of target information. Leveraging these capabilities, we apply TAPIR to cancer patient TCR repertoires and identify and validate a novel and potent anti-cancer T-cell receptor against a shared cancer neoantigen target (PIK3CA H1047L). We further show how TAPIR, when extended with a generative neural network, is capable of directly designing T-cell receptor sequences that interact with a target of interest.

Identification of neoepitope reactive T-cell receptors guided by HLA-A*03:01 and HLA-A*11:01 immunopeptidomics

BACKGROUND

Tumor-specific mutated proteins can create immunogenic non-self, mutation-containing 'neoepitopes' that are attractive targets for adoptive T-cell therapies. To avoid the complexity of defining patient-specific, private neoepitopes, there has been major interest in targeting common shared mutations in driver genes using off-the-shelf T-cell receptors (TCRs) engineered into autologous lymphocytes. However, identifying the precise naturally processed neoepitopes to pursue is a complex and challenging process. One method to definitively demonstrate whether an epitope is presented at the cell surface is to elute peptides bound to a specific major histocompatibility complex (MHC) allele and analyze them by mass spectrometry (MS). These MS data can then be prospectively applied to isolate TCRs specific to the neoepitope.

METHODS

We created mono-allelic cell lines expressing one class I HLA allele and one common mutated oncogene in order to eliminate HLA deconvolution requirements and increase the signal of recovered peptides. MHC-bound peptides on the surface of these cell lines were immunoprecipitated, purified, and analyzed using liquid chromatography-tandem mass spectrometry, producing a list of mutation-containing minimal epitopes. To validate the immunogenicity of these neoepitopes, HLA-transgenic mice were vaccinated using the minimal peptides identified by MS in order to generate neoepitope-reactive TCRs. Specificity of these candidate TCRs was confirmed by peptide titration and recognition of transduced targets.

RESULTS

We identified precise neoepitopes derived from mutated isoforms of KRAS, EGFR, BRAF, and PIK3CA presented by HLA-A*03:01 and/or HLA-A*11:01 across multiple biological replicates. From our MS data, we were able to successfully isolate murine TCRs that specifically recognize four HLA-A*11:01 restricted neoepitopes (KRAS G13D, PIK3CA E545K, EGFR L858R and BRAF V600E) and three HLA-A*03:01 restricted neoepitopes (KRAS G12V, EGFR L858R and BRAF V600E).

CONCLUSIONS

Our data show that an MS approach can be used to demonstrate which shared oncogene-derived neoepitopes are processed and presented by common HLA alleles, and those MS data can rapidly be used to develop TCRs against these common tumor-specific antigens. Although further characterization of these neoepitope-specific murine TCRs is required, ultimately, they have the potential to be used clinically for adoptive cell therapy.

Genome Editing in Engineered T Cells for Cancer Immunotherapy

Advanced gene transfer technologies and profound immunological insights have enabled substantial increases in the efficacy of anticancer adoptive cellular therapy (ACT). In recent years, the U.S. Food and Drug Administration and European Medicines Agency have approved six engineered T cell therapeutic products, all chimeric antigen receptor-engineered T cells directed against B cell malignancies. Despite encouraging clinical results, engineered T cell therapy is still constrained by challenges, which could be addressed by genome editing. As RNA-guided Clustered Regularly Interspaced Short Palindromic Repeats technology passes its 10-year anniversary, we review emerging applications of genome editing approaches designed to (1) overcome resistance to therapy, including cancer immune evasion mechanisms; (2) avoid unwanted immune reactions related to allogeneic T cell products; (3) increase fitness, expansion capacity, persistence, and potency of engineered T cells, while preserving their safety profile; and (4) improve the ability of therapeutic cells to resist immunosuppressive signals active in the tumor microenvironment. Overall, these innovative approaches should widen the safe and effective use of ACT to larger number of patients affected by cancer.

The screening, identification, design and clinical application of tumor-specific neoantigens for TCR-T cells

Recent advances in neoantigen research have accelerated the development of tumor immunotherapies, including adoptive cell therapies (ACTs), cancer vaccines and antibody-based therapies, particularly for solid tumors. With the development of next-generation sequencing and bioinformatics technology, the rapid identification and prediction of tumor-specific antigens (TSAs) has become possible. Compared with tumor-associated antigens (TAAs), highly immunogenic TSAs provide new targets for personalized tumor immunotherapy and can be used as prospective indicators for predicting tumor patient survival, prognosis, and immune checkpoint blockade response. Here, the identification and characterization of neoantigens and the clinical application of neoantigen-based TCR-T immunotherapy strategies are summarized, and the current status, inherent challenges, and clinical translational potential of these strategies are discussed.

Generation of novel complete HLA class I monoallelic cell lines used in an MHC stabilization assay for neoantigen evaluation

Immunogenic neoantigens derived from somatic mutations in cancer have been identified through clinical studies with the cloning of tumor-infiltrating T cells, and cancer driver gene mutation-derived epitopes have been reported; however, these are rare. At present, the validation of epitopes predicted in silico is difficult as human T-cell clonal diversity cannot be reproduced in vitro or in experimental animal models. To confirm the epitope peptides presented by human leukocyte antigen (HLA) class I molecules predicted in silico, biochemical methods such as major histocompatibility complex (MHC) stabilization assays and mass spectrometry-mediated identification have been developed based on HLA-A*02:01 monoallelic T2 cells and HLA-C*01:02 monoallelic LCL721.221 cells. Therefore, in the present study, to prevent confusion due to peptide cross-presentation among HLA molecules, HLA class I monoallelic B-cell clones were generated from the TISI cell line by knocking out HLA-ABC and TAP2, and knocking in HLA alleles. To explore cancer driver mutations as potential targets for immunotherapy, exome sequencing data from 5,143 patients with cancer enrolled in a comprehensive genome analysis project at the Shizuoka Cancer Center were used to identify somatic amino acid substituted mutations and the 50 most frequent mutations in five genes, TP53, EGFR, PIK3CA, KRAS and BRAF, were identified. Using NetMHC4.1, the present study predicted whether epitopes derived from these mutations are presented on major HLA-ABC alleles in Japanese individuals and synthesized 138 peptides for MHC stabilization assays. The authors also attempted to examine the candidate epitopes at physiological temperatures by using antibody clone G46-2.6, which can detect HLA-ABC, independent of β2-microglobulin association. In the assays, although the peptide-induced HLA expression levels were associated with the predicted affinities, the respective HLA alleles exhibited varying degrees of responsiveness, and unexpectedly, p53-mutant epitopes with predicted weak affinities exhibited strong responses. These results suggested that MHC stabilization assays using completely monoallelic HLA-expressing B-cell lines are useful for evaluating the presentation of neoantigen epitopes.

Perspectives in Immunotherapy: meeting report from Immunotherapy Bridge (Naples, November 30th-December 1st, 2022)

The discovery and development of novel treatments that harness the patient's immune system and prevent immune escape has dramatically improved outcomes for patients across cancer types. However, not all patients respond to immunotherapy, acquired resistance remains a challenge, and responses are poor in certain tumors which are considered to be immunologically cold. This has led to the need for new immunotherapy-based approaches, including adoptive cell transfer (ACT), therapeutic vaccines, and novel immune checkpoint inhibitors. These new approaches are focused on patients with an inadequate response to current treatments, with emerging evidence of improved responses in various cancers with new immunotherapy agents, often in combinations with existing agents. The use of cell therapies, drivers of immune response, and trends in immunotherapy were the focus of the Immunotherapy Bridge (November 30th-December 1st, 2022), organized by the Fondazione Melanoma Onlus, Naples, Italy, in collaboration with the Society for Immunotherapy of Cancer.

The landscape of T cell antigens for cancer immunotherapy

The remarkable capacity of immunotherapies to induce durable regression in some patients with metastatic cancer relies heavily on T cell recognition of tumor-presented antigens. As checkpoint-blockade therapy has limited efficacy, tumor antigens have the potential to be exploited for complementary treatments, many of which are already in clinical trials. The surge of interest in this topic has led to the expansion of the tumor antigen landscape with the emergence of new antigen categories. Nonetheless, how different antigens compare in their ability to elicit efficient and safe clinical responses remains largely unknown. Here, we review known cancer peptide antigens, their attributes and the relevant clinical data and discuss future directions.

Dynamics and specificities of T cells in cancer immunotherapy

Recent advances in cancer immunotherapy - ranging from immune-checkpoint blockade therapy to adoptive cellular therapy and vaccines - have revolutionized cancer treatment paradigms, yet the variability in clinical responses to these agents has motivated intense interest in understanding how the T cell landscape evolves with respect to response to immune intervention. Over the past decade, the advent of multidimensional single-cell technologies has provided the unprecedented ability to dissect the constellation of cell states of lymphocytes within a tumour microenvironment. In particular, the rapidly expanding capacity to definitively link intratumoural phenotypes with the antigen specificity of T cells provided by T cell receptors (TCRs) has now made it possible to focus on investigating the properties of T cells with tumour-specific reactivity. Moreover, the assessment of TCR clonality has enabled a molecular approach to track the trajectories, clonal dynamics and phenotypic changes of antitumour T cells over the course of immunotherapeutic intervention. Here, we review the current knowledge on the cellular states and antigen specificities of antitumour T cells and examine how fine characterization of T cell dynamics in patients has provided meaningful insights into the mechanisms underlying effective cancer immunotherapy. We highlight those T cell subsets associated with productive T cell responses and discuss how diverse immunotherapies might leverage the pre-existing tumour-reactive T cell pool or instruct de novo generation of antitumour specificities. Future studies aimed at elucidating the factors associated with the elicitation of productive antitumour T cell immunity are anticipated to instruct the design of more efficacious treatment strategies.

TCR sequencing and cloning methods for repertoire analysis and isolation of tumor-reactive TCRs

T cell receptor (TCR) technologies, including repertoire analyses and T cell engineering, are increasingly important in the clinical management of cellular immunity in cancer, transplantation, and other immune diseases. However, sensitive and reliable methods for repertoire analyses and TCR cloning are still lacking. Here, we report on SEQTR, a high-throughput approach to analyze human and mouse repertoires that is more sensitive, reproducible, and accurate as compared with commonly used assays, and thus more reliably captures the complexity of blood and tumor TCR repertoires. We also present a TCR cloning strategy to specifically amplify TCRs from T cell populations. Positioned downstream of single-cell or bulk TCR sequencing, it allows time- and cost-effective discovery, cloning, screening, and engineering of tumor-specific TCRs. Together, these methods will accelerate TCR repertoire analyses in discovery, translational, and clinical settings and permit fast TCR engineering for cellular therapies.

Highlights into historical and current immune interventions for cancer

Immunotherapy is an additional pillar when combined with traditional standards of care such as chemotherapy, radiotherapy, and surgery for cancer patients. It has revolutionized cancer treatment and rejuvenated the field of tumor immunology. Several types of immunotherapies, including adoptive cellular therapy (ACT) and checkpoint inhibitors (CPIs), can induce durable clinical responses. However, their efficacies vary, and only subsets of cancer patients benefit from their use. In this review, we address three goals: to provide insight into the history of these approaches, broaden our understanding of immune interventions, and discuss current and future approaches. We highlight how cancer immunotherapy has evolved and discuss how personalization of immune intervention may address present limitations. Cancer immunotherapy is considered a recent medical achievement and in 2013 was selected as the "Breakthrough of the Year" by Science. While the breadth of immunotherapeutics has been rapidly expanding, to include the use of chimeric antigen receptor (CAR) T-cell therapy and immune checkpoint inhibitor (ICI) therapy, immunotherapy dates back over 3000 years. The expansive history of immunotherapy, and related observations, have resulted in several approved immune therapeutics beyond the recent emphasis on CAR-T and ICI therapies. In addition to other classical forms of immune intervention, including human papillomavirus (HPV), hepatitis B, and the Mycobacterium bovis Bacillus Calmette-Guérin (BCG) tuberculosis vaccines, immunotherapies have had a broad and durable impact on cancer therapy and prevention. One classic example of immunotherapy was identified in 1976 with the use of intravesical administration of BCG in patients with bladder cancer; resulting in a 70 % eradication rate and is now standard of care. However, a greater impact from the use of immunotherapy is documented by the prevention of HPV infections that are responsible for 98 % of cervical cancer cases. In 2020, the World Health Organization (WHO) estimated that 341,831 women died from cervical cancer [1]. However, administration of a single dose of a bivalent HPV vaccine was shown to be 97.5 % effective in preventing HPV infections. These vaccines not only prevent cervical squamous cell carcinoma and adenocarcinoma, but also oropharyngeal, anal, vulvar, vaginal, and penile squamous cell carcinomas. The breadth, response and durability of these vaccines can be contrasted with CAR-T-cell therapies, which have significant barriers to their widespread use including logistics, manufacturing limitations, toxicity concerns, financial burden and lasting remissions observed in only 30 to 40 % of responding patients. Another, recent immunotherapy focus are ICIs. ICIs are a class of antibodies that can increase the immune responses against cancer cells in patients. However, ICIs are only effective against tumors with a high mutational burden and are associated with a broad spectrum of toxicities requiring interruption of administration and/or administration corticosteroids; both of which limit immune therapy. In summary, immune therapeutics have a broad impact worldwide, utilizing numerous mechanisms of action and when considered in their totality are more effective against a broader range of tumors than initially considered. These new cancer interventions have tremendous potential notability when multiple mechanisms of immune intervention are combined as well as with standard of care modalities.

HLA3DB: comprehensive annotation of peptide/HLA complexes enables blind structure prediction of T cell epitopes

The class I proteins of the major histocompatibility complex (MHC-I) display epitopic peptides derived from endogenous proteins on the cell surface for immune surveillance. Accurate modeling of peptide/HLA (pHLA, the human MHC) structures has been mired by conformational diversity of the central peptide residues, which are critical for recognition by T cell receptors. Here, analysis of X-ray crystal structures within a curated database (HLA3DB) shows that pHLA complexes encompassing multiple HLA allotypes present a discrete set of peptide backbone conformations. Leveraging these representative backbones, we employ a regression model trained on terms of a physically relevant energy function to develop a comparative modeling approach for nonamer peptide/HLA structures named RepPred. Our method outperforms the top pHLA modeling approach by up to 19% in terms of structural accuracy, and consistently predicts blind targets not included in our training set. Insights from our work provide a framework for linking conformational diversity with antigen immunogenicity and receptor cross-reactivity.