Neoantigens: promising targets for cancer therapy

Recent progress in cancer vaccines and nanovaccines

Vaccine science, nanotechnology, and immunotherapy are at the forefront of cancer treatment strategies, each offering significant potential for enhancing tumor-specific immunity and establishing long-lasting immune memory to prevent tumor recurrence. Despite the promise of these personalized and precision-based anti-cancer approaches, challenges such as immunosuppression, suboptimal immune activation, and T-cell exhaustion continue to hinder their effectiveness. The limited clinical success of cancer vaccines often stems from difficulties in identifying effective antigens, efficiently targeting immune cells, lymphoid organs, and the tumor microenvironment, overcoming immune evasion, enhancing immunogenicity, and avoiding lysosomal degradation. However, numerous studies have demonstrated that integrating nanotechnology with immunotherapeutic strategies in vaccine development can overcome these challenges, leading to potent antitumor immune responses and significant progress in the field. This review highlights the critical components of cancer vaccine and nanovaccine strategies for immunomodulatory antitumor therapy. It covers general vaccine strategies, types of vaccines, antigen forms, nanovaccine platforms, challenges faced, potential solutions, and key findings from preclinical and clinical studies, along with future perspectives. To fully unlock the potential of cancer vaccines and nanovaccines, precise immunological monitoring during early-phase trials is essential. This approach will help identify and address obstacles, ultimately expanding the available options for patients who are resistant to conventional cancer immunotherapies.

Emerging role of endogenous peptides encoded by non-coding RNAs in cancer biology

Non-coding RNAs have long been recognized for their regulatory roles in various cellular processes, including cancer development and progression. Recent advancements have shed light on a novel aspect of non-coding RNA biology, revealing their ability to encode endogenous peptides also named micropeptides or microprotein through short open reading frames (sORFs). These small proteins play crucial roles in oncogenic processes, acting as either tumour suppressors or tumour promoters, and hold enormous potential as biomarkers for early diagnosis of cancer and as therapeutic targets. This comprehensive review highlights the state of the art on peptides encoded by long non-coding RNAs (lncRNAs), microRNAs (miRNAs), and circular RNAs (circRNAs), elucidating their regulatory functions and implications in different cancer types, including breast cancer, hepatocellular carcinoma and colorectal cancer. The review also discusses challenges and future directions in the exploration of these emerging players in cancer biology, emphasizing the importance of further investigation for their clinical translation in diagnosis and therapy.

Frontiers in pancreatic cancer on biomarkers, microenvironment, and immunotherapy

Pancreatic cancer remains one of the most challenging malignancies to treat due to its late-stage diagnosis, aggressive progression, and high resistance to existing therapies. This review examines the latest advancements in early detection, and therapeutic strategies, with a focus on emerging biomarkers, tumor microenvironment (TME) modulation, and the integration of artificial intelligence (AI) in data analysis. We highlight promising biomarkers, including microRNAs (miRNAs) and circulating tumor DNA (ctDNA), that offer enhanced sensitivity and specificity for early-stage diagnosis when combined with multi-omics panels. A detailed analysis of the TME reveals how components such as cancer-associated fibroblasts (CAFs), immune cells, and the extracellular matrix (ECM) contribute to therapy resistance by creating immunosuppressive barriers. We also discuss therapeutic interventions that target these TME components, aiming to improve drug delivery and overcome immune evasion. Furthermore, AI-driven analyses are explored for their potential to interpret complex multi-omics data, enabling personalized treatment strategies and real-time monitoring of treatment response. We conclude by identifying key areas for future research, including the clinical validation of biomarkers, regulatory frameworks for AI applications, and equitable access to innovative therapies. This comprehensive approach underscores the need for integrated, personalized strategies to improve outcomes in pancreatic cancer.

Nuclear factor I/B: Duality in action in cancer pathophysiology

The nuclear factor I (NFI) family of transcription factors plays a decisive role in organ development and maturation. Their deregulation has been linked with various diseases, most notably cancer. NFIB stands apart from the other NFI family members given its unique ability to drive both tumor suppressive and oncogenic programs. Thus, the ultimate impact of deregulated NFIB signaling is cancer-specific and strongly influenced by an intricate network of upstream regulators and downstream effectors. Deciphering the events that drive NFIB's paradoxical roles within these networks will enable us to not only understand how this critical transcription factor enacts its dual roles but also drive innovations to help us effectively target NFIB in different cancers. Here, we provide an in-depth review of NFIB. Starting with its defining role in the development of various organs, most notably the central nervous system, we highlight critical signaling pathways and the impact of deregulation on neoplastic transformation, contrasting it with the effect of silencing alone. We then provide examples of its dual roles in various cancers, identifying specific signaling networks associated with oncogenesis versus tumor suppression. We incorporate an example of a cancer type, osteosarcoma, wherein NFIB enacts its dual functions and explore which pathways influence each function. In this manner, we suggest plausible mechanisms for its role-switching from cancers sharing common triggering events in the setting of NFIB deregulation. We also review how NFIB enhances aggressiveness by driving metastasis, stemness, and chemoresistance. We conclude with a discussion on efficacious ways to target NFIB and pose some unanswered questions that may further help solidify our understanding of NFIB and facilitate clinical translation of NFIB targeting.

Adeno-associated viral vectors deliver gene vaccines

Adeno-associated viruses (AAVs) are leading platforms for in vivo delivery of gene therapies, with six licensed AAV-based therapeutics attributed to their non-pathogenic nature, low immunogenicity, and high efficiency. In the realm of gene-based vaccines, one of the most vital therapeutic areas, AAVs are also emerging as promising delivery tools. We scrutinized AAVs, focusing on their virological properties, as well as bioengineering and chemical modifications to demonstrate their significant potential in gene vaccine delivery, and detailing the preparation of AAV particles. Additionally, we summarized the use of AAV vectors in vaccines for both infectious and non-infectious diseases, such as influenza, COVID-19, Alzheimer's disease, and cancer. Furthermore, this review, along with the latest clinical trial updates, provides a comprehensive overview of studies on the potential of using AAV vectors for gene vaccine delivery. It aims to deepen our understanding of the challenges and limitations in nucleic acid delivery and pave the way for future clinical success.

Unlocking cancer vaccine potential: What are the key factors?

Cancer is a global health challenge, with changing demographics and lifestyle factors producing an increasing burden worldwide. Screening advancements are enabling earlier diagnoses, but current cancer immunotherapies only induce remission in a small proportion of patients and come at a high cost. Cancer vaccines may offer a solution to these challenges, but they have been mired by poor results in past decades. Greater understanding of tumor biology, coupled with the success of vaccine technologies during the COVID-19 pandemic, has reinvigorated cancer vaccine development. With the first signs of efficacy being reported, cancer vaccines may be beginning to fulfill their potential. Solid tumors, however, present different hurdles than infectious diseases. Combining insights from previous cancer vaccine clinical development and contemporary knowledge of tumor immunology, we ask: who are the 'right' patients, what are the 'right' targets, and which are the 'right' modalities to maximize the chances of cancer vaccine success?

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.

Immunogenic cell death: A new strategy to enhancing cancer immunotherapy

Immunogenic cell death (ICD) is a distinct type of stress-induced regulated cell death that can lead to adaptive immune responses and the establishment of immunological memory. ICD exhibits both similarities and differences when compared to apoptosis and other non-apoptotic forms of regulated cell death (RCD). The interplay between ICD-mediated immunosurveillance against cancer and the ability of cancer cells to evade ICD influences the host-tumor immunological interaction. Consequently, the restoration of ICD and the development of effective strategies to induce ICD have emerged as crucial considerations in the treatment of cancer within the context of immunotherapy. To enhance comprehension of ICD in the setting of cancer, this paper examines the interconnected responsive pathways associated with ICD, the corresponding biomarkers indicative of ICD, and the mechanisms through which tumors subvert ICD. Additionally, this review explores strategies for reinstating ICD and the therapeutic potential of harnessing ICD in cancer immunotherapy.

Prospects and challenges of neoantigen applications in oncology

Neoantigen, unique peptides resulting from tumor-specific mutations, represent a promising frontier in oncology for personalized cancer immunotherapy. Their unique features allow for the development of highly specific and effective cancer treatments, which can potentially overcome the limitations of conventional therapies. This paper explores the current prospects and challenges associated with the application of neoantigens in oncology. We examine the latest advances in neoantigen identification, vaccine development, and adoptive T cell therapy. Additionally, we discuss the obstacles related to neoantigen heterogeneity, immunogenicity prediction, and the tumor microenvironment. Through a comprehensive analysis of current research and clinical trials, this paper aims to provide a detailed overview of how neoantigens could revolutionize cancer treatment and the hurdles that must be overcome to realize their full potential.

The Landmark Series: Cancer Vaccines for Solid Tumors

Immunotherapy has become an integral part of the treatment for solid tumors. Cancer vaccines represent a potentially powerful class of immunotherapeutic agents to drive antitumor immunity. Cancer vaccine development involves selecting immunogenic target antigens expressed by tumor cells that can be effectively delivered for uptake by antigen-presenting cells to generate a robust adaptive immune response against tumor. While numerous cancer vaccines have been shown to produce antigen-specific immune responses, translating promising results of immunogenicity from early-phase trials into durable clinical benefit in larger randomized trials has remained elusive. Recent findings support new enthusiasm for several cancer vaccine approaches for solid tumors. This review will discuss landmark historic clinical trials in cancer vaccine development and strategies to optimize cancer vaccines to achieve improved clinical efficacy.

Comparative proteomic analysis to annotate the structural association of the hypothetical proteins from the conserved domain of P. aeruginosa as novel vaccine candidates

OBJECTIVES

Pseudomonas aeruginosa, identified as an ESKAPE pathogen, contributes to severe clinical diseases worldwide and despite its prevalence an effective vaccine or treatment remains elusive. Numerous computational methods are being employed to target hypothetical proteins (HPs). Presently, no studies have predicted multi-epitope vaccines for these HPs.

RESULTS

Totally, 877 HPs from P. aeruginosa were included in the study and the data showcased here illustrate a methodical approach to prioritize the proteome by employing diverse comparative proteomics. The study employed physicochemical property assessment and conserved domain analysis to identify stable and immunologically pertinent proteins for epitope prediction. The VaxiJen2.0 antigenicity assessment aided in epitope selection, contributing to the foundational steps in vaccine development by predicting T-cell and B-cell epitopes. Potential T and B cell epitopes with high antigenicity, non-toxic categorization, and robust binding affinities were identified in the investigation. The periplasmic HP WP_132813935.1 was predicted as conserved, stable, and soluble. The T-cell peptide RTSMRALAY and the B-cell peptide MPVYLYLM were predicted to be probable non-allergen and demonstrated strong binding with MHC class I allele HLA-C*03:03.

CONCLUSIONS

This research provides a comprehensive approach to predict T and B cell epitopes for conditions associated with P. aeruginosa, offering a candidate pool for tailored vaccine development. However, the efficacy of these epitopes in vaccine development necessitates clinical validation and testing for confirmation.

mRNA cancer vaccines from bench to bedside: a new era in cancer immunotherapy

Harnessing the power of the immune system to target cancer cells is one of the most appealing approaches for cancer therapy. Among these immunotherapies, messenger ribonucleic acid (mRNA) cancer vaccines are worthy of consideration, as they have demonstrated promising results in clinical trials. These vaccines have proven to be safe and well-tolerated. They can be easily mass-produced in a relatively short time and induce a systemic immune response effective against both the primary tumor and metastases. Transcripts encoding immunomodulatory molecules can also be incorporated into the mRNA, enhancing its efficacy. On the other hand, there are some challenges associated with their application, including mRNA instability, insufficient uptake by immune cells, and intrinsic immunogenicity, which can block mRNA translation. Many innovations have been suggested to overcome these obstacles, including structural modification (such as 5' cap modification), optimizing delivery vehicles (especially dendritic cells (DCs) and nanoparticles), and using antigens that can enhance immunogenicity by circumventing tolerance mechanisms. A popular approach is to combine mRNA cancer vaccines with traditional and novel cancer treatments like chemotherapy, radiotherapy, and immune checkpoint blockade (ICB). They are most efficacious when combined with other therapies like ICBs. There is still a long way to go before these vaccines enter the standard of care for cancer patients, but with the incredible pace of development in this field, their clinical application will soon be witnessed. This review highlights the recent advances and challenges of mRNA cancer vaccines. Finally, some of the most prominent clinical applications of these vaccines will be reviewed.

Identification of BRCA new prognostic targets and neoantigen candidates from fusion genes

Cancer-associated gene fusions serve as a potential source of highly immunogenic neoantigens. In this study, we identified fusion proteins from fusion genes and extracted fusion peptides to accurately predict Breast cancer (BRCA) neo-antigen candidates by high-throughput artificial intelligence computation. Firstly, Deepsurv was used to evaluate the prognosis of patients, providing a landscape of prognostic fusion genes in BRCA. Next, AGFusion was utilized to generate full-length fusion protein sequences and annotate functional domains. Advanced neural networks and Transformer-based analyses were implemented to predict the binding of fusion peptides to 112 types of HLA, thereby forming a new immunotherapy candidates' library of BRCA neo-antigens (n = 7791, covering 88.41% of patients). Among them, 15 neo-antigens were validated and factually translated into mass spectrometry data of BRCA patients. Finally, AlphaFold2 was applied to predict the binding sites of these neo-antigens to MHC (HLA) molecules. Notably, we identified a prognostic neoantigen from the TBC1D4-COMMD6 fusion that significantly improves patient prognosis and extensively binds to 16 types of HLA alleles. These highly immunogenic and tumor-specific neoantigens offer emerging targets for personalized cancer immunotherapies and act as prospective predictors for tumor survival prognosis and responses to immune checkpoint therapies.

Development of CAR-T Therapies and Personalized Vaccines for the Treatment of Cholangiocarcinoma: Current Progress, Mechanisms of Action, and Challenges

Cholangiocarcinoma (CCA) is a highly lethal malignancy with rising incidence, high mortality, poor overall survival rates, and limited responsiveness to traditional chemo-radiotherapy. Targeted therapies addressing specific gene mutations have expanded treatment options for some patient populations. The introduction of chimeric antigen receptor-modified T cell (CAR-T) immunotherapy and personalized vaccines have opened up a new avenue for managing various cancers. Considerable efforts have been dedicated to preclinical research and ongoing clinical trials aimed at investigating immunotherapeutic approaches such as CAR-T therapy, vaccines, and antibody-based therapies such as antibody drug conjugates. However, the potential of CAR-T therapy and vaccines in treating advanced unresectable/metastatic CCA remains largely unexplored. This review offers an overview of the current landscape of antibody-based immunotherapy, particularly CAR-T therapy and vaccines in the context of CCA treatment. It outlines a framework for selecting CAR-T and vaccine targets and delves into the biology of promising targetable antigens, as well as potential future therapeutic targets.

Proteogenomics offers a novel avenue in neoantigen identification for cancer immunotherapy

Cancer neoantigens are tumor-specific non-synonymous mutant peptides that activate the immune system to produce an anti-tumor response. Personalized cancer vaccines based on neoantigens are currently one of the most promising therapeutic approaches for cancer treatment. By utilizing the unique mutations within each patient's tumor, these vaccines aim to elicit a strong and specific immune response against cancer cells. However, the identification of neoantigens remains challenging due to the low accuracy of current prediction tools and the high false-positive rate of candidate neoantigens. Since the concept of "proteogenomics" emerged in 2004, it has evolved rapidly with the increased sequencing depth of next-generation sequencing technologies and the maturation of mass spectrometry-based proteomics technologies to become a more comprehensive approach to neoantigen identification, allowing the discovery of high-confidence candidate neoantigens. In this review, we summarize the reason why cancer neoantigens have become attractive targets for immunotherapy, the mechanism of cancer vaccines and the advances in cancer immunotherapy. Considerations relevant to the application emerging of proteogenomics technologies for neoantigen identification and challenges in this field are described.

Immunoproteasome Activation Expands the MHC Class I Immunopeptidome, Unmasks Neoantigens, and Enhances T-cell Anti-Myeloma Activity

Proteasomes generate antigenic peptides that are presented on the tumor surface to cytotoxic T-lymphocytes. Immunoproteasomes are highly specialized proteasome variants that are expressed at higher levels in antigen-presenting cells and contain replacements of the three constitutive proteasome catalytic subunits to generate peptides with a hydrophobic C-terminus that fit within the groove of MHC class I (MHC-I) molecules. A hallmark of cancer is the ability to evade immunosurveillance by disrupting the antigen presentation machinery and downregulating MHC-I antigen presentation. High-throughput screening was performed to identify compound A, a novel molecule that selectively increased immunoproteasome activity and expanded the number and diversity of MHC-I-bound peptides presented on multiple myeloma cells. Compound A increased the presentation of individual MHC-I-bound peptides by >100-fold and unmasked tumor-specific neoantigens on myeloma cells. Global proteomic integral stability assays determined that compound A binds to the proteasome structural subunit PSMA1 and promotes association of the proteasome activator PA28α/β (PSME1/PSME2) with immunoproteasomes. CRISPR/Cas9 silencing of PSMA1, PSME1, or PSME2 as well as treatment with immunoproteasome-specific suicide inhibitors abolished the effects of compound A on antigen presentation. Treatment of multiple myeloma cell lines and patient bone marrow-derived CD138+ cells with compound A increased the anti-myeloma activity of allogenic and autologous T cells. Compound A was well-tolerated in vivo and co-treatment with allogeneic T cells reduced the growth of myeloma xenotransplants in NOD/SCID gamma mice. Taken together, our results demonstrate the paradigm shifting impact of immunoproteasome activators to diversify the antigenic landscape, expand the immunopeptidome, potentiate T-cell-directed therapy, and reveal actionable neoantigens for personalized T-cell immunotherapy.

Cancer vaccines: Target antigens, vaccine platforms and preclinical models

This review provides a comprehensive overview of the evolving landscape of cancer vaccines, highlighting their potential to revolutionize tumor prevention. Building on the success of vaccines against virus-related cancers, such as HPV- and HBV-associated cervical and liver cancers, the current challenge is to extend these achievements to the prevention of non-viral tumors and the treatment of preneoplastic or early neoplastic lesions. This review analyzes the critical aspects of preventive anti-cancer vaccination, focusing on the choice of target antigens, the development of effective vaccine platforms and technologies, and the use of various model systems for preclinical testing, from laboratory rodents to companion animals.

Beta-Cell-Derived Extracellular Vesicles: Mediators of Intercellular Communication in the Islet Microenvironment in Type 1 Diabetes

Type 1 diabetes (T1D) is a chronic autoimmune disorder characterised by an autoimmune response specifically mounted against the insulin-producing beta cells. Within the islet, high cellular connectivity and extensive vascularisation facilitate intra-islet communication and direct crosstalk with the surrounding tissues and the immune system. During the development of T1D, cytokines and extracellular vesicles released by beta cells can contribute to the recruitment of immune cells, further amplifying autoimmunity and aggravating beta cell damage and dysfunction. In this review, we will evaluate the role of beta-cell-derived extracellular vesicles as mediators of the autoimmune response and discuss their potential for early diagnosis and new therapeutic strategies in T1D.

Immunotherapy for glioblastoma: current state, challenges, and future perspectives

Glioblastoma (GBM) is an aggressive and lethal type of brain tumor in human adults. The standard of care offers minimal clinical benefit, and most GBM patients experience tumor recurrence after treatment. In recent years, significant advancements have been made in the development of novel immunotherapies or other therapeutic strategies that can overcome immunotherapy resistance in many advanced cancers. However, the benefit of immune-based treatments in GBM is limited because of the unique brain immune profiles, GBM cell heterogeneity, and immunosuppressive tumor microenvironment. In this review, we present a detailed overview of current immunotherapeutic strategies and discuss the challenges and potential molecular mechanisms underlying immunotherapy resistance in GBM. Furthermore, we provide an in-depth discussion regarding the strategies that can overcome immunotherapy resistance in GBM, which will likely require combination therapies.

Enhancing Mass spectrometry-based tumor immunopeptide identification: machine learning filter leveraging HLA binding affinity, aliphatic index and retention time deviation

Accurately identifying neoantigens is crucial for developing effective cancer vaccines and improving tumor immunotherapy. Mass spectrometry-based immunopeptidomics has emerged as a promising approach to identifying human leukocyte antigen (HLA) peptides presented on the surface of cancer cells, but false-positive identifications remain a significant challenge. In this study, liquid chromatography-tandem mass spectrometry-based proteomics and next-generation sequencing were utilized to identify HLA-presenting neoantigenic peptides resulting from non-synonymous single nucleotide variations in tumor tissues from 18 patients with renal cell carcinoma or pancreatic cancer. Machine learning was utilized to evaluate Mascot identifications through the prediction of MS/MS spectral consistency, and four descriptors for each candidate sequence: the max Mascot ion score, predicted HLA binding affinity, aliphatic index and retention time deviation, were selected as important features in filtering out identifications with inadequate fragmentation consistency. This suggests that incorporating rescoring filters based on peptide physicochemical characteristics could enhance the identification rate of MS-based immunopeptidomics compared to the traditional Mascot approach predominantly used for proteomics, indicating the potential for optimizing neoantigen identification pipelines as well as clinical applications.

DIPAN: Detecting personalized intronic polyadenylation derived neoantigens from RNA sequencing data

Intronic polyadenylation (IPA) refers to a particular type of alternative polyadenylation where a gene makes use of a polyadenylation site located within its introns. Aberrant IPA events have been observed in various types of cancer. IPA can produce noncoding transcripts or truncated protein-coding transcripts with altered coding sequences in the resulting protein product. Therefore, IPA events hold the potential to act as a reservoir of tumor neoantigens. Here, we developed a computational method termed DIPAN, which incorporates IPA detection, protein fragmentation, and MHC binding prediction to predict IPA-derived neoantigens. Utilizing RNA-seq from breast cancer cell lines and ovarian cancer clinical samples, we demonstrated the significant contribution of IPA events to the neoantigen repertoire. Through mass spectrometry immunopeptidome analysis, we further illustrated the processing and presentation of IPA-derived neoantigens on the surface of cancer cells. While most IPA-derived neoantigens are sample-specific, shared neoantigens were identified in both cancer cell lines and clinical samples. Furthermore, we demonstrated an association between IPA-derived neoantigen burden and overall survival in cancer patients.

The effects of anti-lung cancer in nude mice by a fully human single-chain antibody against associated antigen Ts7TMR between A549 cells and Trichinella spiralis

Lung cancer is a dangerous disease that is lacking in an ideal therapy. Here, we evaluated the anti-lung cancer effect in nude mice of a fully human single-chain antibody (scFv) against the associated antigen 7 transmembrane receptor (Ts7TMR), which is also called G protein-coupled receptor, between A549 cells and Trichinella spiralis (T. spiralis). Our data showed that anti-Ts7TMR scFv could inhibit lung cancer growth in a dose-dependent manner, with a tumour inhibition rate of 59.1%. HE staining did not reveal any obvious tissue damage. Mechanistically, immunohistochemical staining revealed that the scFv down-regulated the expression of PCNA and VEGF in tumour tissues. Overall, this study found that anti-Ts7TMR scFv could inhibit A549 lung cancer growth by suppressing cell proliferation and angiogenesis, which may provide a new strategy for treating lung cancer.

T cell landscape in the microenvironment of human solid tumors

T cells are the main effectors involved in anti-tumor immunity, mediating most of the adaptive response towards cancer. After priming in lymph nodes, tumor antigens-specific naïve T lymphocytes proliferate and differentiate into effector CD4+ and CD8+ T cells that migrate from periphery into tumor sites aiming to eliminate cancer cells. Then while most effector T cells die, a small fraction persists and recirculates as long-lived memory T cells which generate enhanced immune responses when re-encountering the same antigen. A number of T (and non-T) cell subsets, stably resides in non-lymphoid peripheral tissues and may provide rapid immune response independently of T cells recruited from blood, against the reemergence of cancer cells. When tumor grows, however, tumor cells have evaded immune surveillance of effector cells (NK and CTL cells) which are exhausted, thus favoring the local expansion of T (and non-T) regulatory cells. In this review, the current knowledge of features of T cells present in the tumor microenvironment (TME) of solid adult and pediatric tumors, the mechanisms upregulating immune-checkpoint molecules and transcriptional and epigenetic landscapes leading to dysfunction and exhaustion of T effector cells are reviewed. The interaction of T cells with cancer- or TME non-neoplastic cells and their secreted molecules shape the T cell profile compromising the intrinsic plasticity of T cells and, therefore, favoring immune evasion. In this phase regulatory T cells contribute to maintain a high immunosuppressive TME thus facilitating tumor cell proliferation and metastatic spread. Despite the advancements of cancer immunotherapy, many tumors are unresponsive to immune checkpoint inhibitors, or therapeutical vaccines or CAR T cell-based adoptive therapy: some novel strategies to improve these T cell-based treatments are lastly proposed.

Combinational CAR T-cell therapy for solid tumors: Requisites, rationales, and trials

Chimeric antigen receptor (CAR) T-cell therapy has achieved potent antitumor efficacy in hematological malignancies; however, because of limitations in CAR T-cell recruitment, infiltration, activation, and functional persistence in the tumor, its efficacy in solid tumors has been suboptimal. To overcome these challenges, combinational strategies that include chemotherapy, radiation therapy, or immune checkpoint inhibitor agent therapy with CAR T-cell therapy are being investigated. The established functional characteristics of the abovementioned therapies provide a rationale for the use of a combinational approach with CAR T cells. Chemotherapy reshapes the peritumoral stroma, decreases the immunosuppressive cell population, and promotes a proinflammatory milieu, all of which allow for increased recruitment, infiltration, and accumulation of CAR T cells. Radiation therapy promotes a chemokine gradient, which augments tumor infiltration by CAR T cells and further increases expression of tumor-associated antigens, allowing for increased activation of CAR T cells. Immune checkpoint inhibitor agent therapy inactivates T-cell exhaustion pathways-most notably, the PD1/PDL1 pathway-thereby improving the functional persistence of CAR T cells and promoting endogenous immunity. In this review, we discuss the requisites and rationales for combinational therapy, and we review 25 ongoing phase I and II clinical trials, of which 4 use chemotherapy, 3 use radiation therapy, 11 use immunotherapy, and 7 use another agent. While safety, efficacy, and improved outcomes are the primary goals of these ongoing studies, the knowledge gained from them will help pave the way for subsequent studies focused on optimizing combinational regimens and identifying predictive biomarkers.

Cellular MSI-H score: a robust predictive biomarker for immunotherapy response and survival in gastrointestinal cancer

Microsatellite instability-high (MSI-H) is a critical biomarker for immunotherapy, yet primary resistance remains a significant challenge. Current MSI-H detection methods evaluate the proportion of MSI-H loci, termed molecular MSI-H score, which can be affected by intratumoral heterogeneity (ITH). To address this limitation, we propose evaluating MSI-H at the cellular level to improve the prediction of immunotherapy outcomes. Using bulk tissue (TCGA-CRC) and cell line (CCLE-CRC) datasets, we identified genes highly expressed in MSI-H and MSS samples. These signatures were applied to a single-cell RNA sequencing (scCRC) dataset for enrichment analysis, enabling classification of tumor cells into MSI-H, MSS, and microsatellite dual (MSD) clusters using a Gaussian finite mixture model. Validation showed that MSI-H and MSS enrichment scores were higher in mismatch repair-deficient (MMRd) and mismatch repair-proficient (MMRp) patients, respectively. Functional enrichment analysis revealed that MSI-H cells were associated with pathways such as carboxylic acid catabolism, inflammatory responses, and IL-6/JAK2/STAT3 signaling. We developed a cellular MSI-H signature using genes specifically expressed in the MSI-H cell cluster and transformed the scCRC dataset into a cell-type-specific pseudobulk expression matrix. Using this matrix as a reference, we performed reference-based deconvolution on TCGA-CRC data. We defined the deconvolution score of MSI-H cell as cellular MSI-H score. This score strongly correlated with the molecular MSI-H score (R = 0.55, P < 0.001) and showed modest correlations with macrophage (MoMac, R = 0.14) and CD8+ T-cell (R = 0.11). To investigate its potential for clinical application, we applied the cellular MSI-H signature to the BJ-cohort, comprising 97 immunotherapy-treated gastrointestinal patients sequenced with a 395-gene panel. The cellular MSI-H score was significantly higher in responders (P = 0.002), positively correlated with tumor reduction percentage (R = 0.29, P = 0.006), and associated with improved progression-free survival (PFS) (HR: 0.00, 95% CI: 0.00-0.31, P = 0.021). In summary, the cellular MSI-H score reflects the MSI-H cell level within a tumor and demonstrates superior accuracy compared to molecular MSI-H status in predicting immunotherapy response and PFS. This underscores its potential as a more robust biomarker for guiding immunotherapy decisions.

Nanopore approaches for single-molecule temporal omics: promises and challenges

The great molecular heterogeneity within single cells demands omics analysis from a single-molecule perspective. Moreover, considering the perpetual metabolism and communication within cells, it is essential to determine the time-series changes of the molecular library, rather than obtaining data at only one time point. Thus, there is an urgent need to develop a single-molecule strategy for this omics analysis to elucidate the biosystem heterogeneity and temporal dynamics. In this Perspective, we explore the potential application of nanopores for single-molecule temporal omics to characterize individual molecules beyond mass, in both a single-molecule and high-throughput manner. Accordingly, recent advances in nanopores available for single-molecule temporal omics are reviewed from the view of single-molecule mass identification, revealing single-molecule heterogeneity and illustrating temporal evolution. Furthermore, we discuss the primary challenges associated with using nanopores for single-molecule temporal omics in complex biological samples, and present the potential strategies and notes to respond to these challenges.

Advances in CAR-T therapy for central nervous system tumors

The application of chimeric antigen receptor T-cell therapy in central nervous system tumors has significantly advanced; however, challenges pertaining to the blood-brain barrier, immunosuppressive microenvironment, and antigenic heterogeneity continue to be encountered, unlike its success in hematological malignancies such as acute lymphoblastic leukemia and diffuse large B-cell lymphomas. This review examined the research progress of chimeric antigen receptor T-cell therapy in gliomas, medulloblastomas, and lymphohematopoietic tumors of the central nervous system, focusing on chimeric antigen receptor T-cells targeting antigens such as EGFRvIII, HER2, B7H3, GD2, and CD19 in preclinical and clinical studies. It synthesized current research findings to offer valuable insights for future chimeric antigen receptor T-cell therapeutic strategies for central nervous system tumors and advance the development and application of this therapeutic modality in this domain.

Harnessing Artificial Intelligence for the Detection and Management of Colorectal Cancer Treatment

Currently, eight million people in the United States suffer from cancer and it is a major global health concern. Early detection and interventions are urgently needed for all cancers, including colorectal cancer. Colorectal cancer is the third most common type of cancer worldwide. Based on the diagnostic efforts to general awareness and lifestyle choices, it is understandable why colorectal cancer is so prevalent today. There is a notable lack of awareness concerning the impact of this cancer and its connection to lifestyle elements, as well as people sometimes mistaking symptoms for a different gastrointestinal condition. Artificial intelligence (AI) may assist in the early detection of all cancers, including colorectal cancer. The usage of AI has exponentially grown in healthcare through extensive research, and since clinical implementation, it has succeeded in improving patient lifestyles, modernizing diagnostic processes, and innovating current treatment strategies. Numerous challenges arise for patients with colorectal cancer and oncologists alike during treatment. For initial screening phases, conventional methods often result in misdiagnosis. Moreover, after detection, determining the course of which colorectal cancer can sometimes contribute to treatment delays. This article touches on recent advancements in AI and its clinical application while shedding light on why this disease is so common today.

Prevalence and prognostic value of PD-L1 expression and tumor mutational burden in persistent, recurrent, or metastatic cervical cancer

OBJECTIVE

To evaluate the prevalence and prognostic role of programmed death ligand 1 (PD-L1) expression and tumor mutational burden (TMB) in patients with non-immunotherapy-treated advanced cervical cancer.

METHODS

Clinical data were retrospectively collected from medical records between January 1, 2008, and December 31, 2016, at Asan Medical Center (Korea); archived tumor samples were assessed for PD-L1 expression (combined positive score [CPS] ≥1) and TMB (≥175 mutations/exome). Overall survival (OS) was defined as time from advanced diagnosis or initiation of first-line or second-line systemic therapy until death/last follow-up. The association of OS with PD-L1 expression and TMB were analyzed using the log-rank test and Cox proportional hazards model adjusted for covariates.

RESULTS

Of 267 patients, 76.0% had squamous cell carcinoma (SCC), 24.0% had adenocarcinoma (AC)/adenosquamous carcinoma (ASC), 64.4% had PD-L1 CPS ≥1, and 32.6% had TMB ≥175 mutations/exome. PD-L1 CPS ≥1 and TMB ≥175 mutations/exome were more prevalent in SCC than in AC/ASC (73.9% and 37.2% vs. 34.4% and 17.7%). There was no association between OS and PD-L1 expression (CPS ≥1 vs. <1: adjusted hazard ratio [HR]=1.14; 95% confidence interval [CI]=0.84-1.53 from advanced diagnosis); OS trended shorter for the subgroup with TMB ≥175 versus <175 mutations/exome (adjusted HR=1.29; 95% CI=0.95-1.75).

CONCLUSION

Retrospective analysis of non-immunotherapy-treated patients with advanced cervical cancer demonstrated a higher prevalence of PD-L1 CPS ≥1 and TMB ≥175 mutations/exome in SCC versus AC/ASC. PD-L1 CPS ≥1 was not associated with OS; TMB ≥175 mutations/exome showed a trend toward shorter OS. Additional studies are needed to confirm these findings.

Increases in 4-Acetaminobutyric Acid Generated by Phosphomevalonate Kinase Suppress CD8+ T Cell Activation and Allow Tumor Immune Escape

Certain metabolites in the tumor microenvironment (TME) can alter innate immunity. Here, it is shown how phosphomevalonate kinase (PMVK) allows hepatocellular carcinoma (HCC) cells to overcome the anti-tumor immunity mediated by CD8+ T cells. In HCCs, depletion of PMVK is required to facilitate CD8+ T cell activation and their subsequent suppression of tumor growth. Mechanistically, PMVK phosphorylates and stabilizes glutamate decarboxylase 1 (GAD1), thus increasing the synthesis of γ-aminobutyric acid (GABA), which normally functions as a neurotransmitter. However, PMVK also recruits acetyl-CoA acetyltransferase 1 (ACAT1) and allows it to convert GABA, to 4-acetaminobutyric acid (4-Ac-GABA), which is released into the TME. There, 4-Ac-GABA activates the GABAA receptor (GABAAR) on CD8+ T cells, which inhibits AKT1 signaling. This in turn suppresses CD8+ T cell activation, intratumoral infiltration, and the anti-tumor response. Inhibiting PMVK or GABAAR in HCC mouse models overcomes resistance to anti-PD-1 immune checkpoint therapy. These findings reveal non-canonical and cooperative functions among the key metabolic enzymes PMVK, GAD1, and ACAT1 that reprogram glutamine metabolism to synthesize a potent CD8+ T cell inhibitor 4-Ac-GABA. Blocking 4-Ac-GABA signaling in CD8+ T cells, particularly when combined with immune checkpoint inhibition, potentially represents a new and potent form of immunotherapy.

Epstein Barr virus: A cellular hijacker in cancer

Numerous studies have demonstrated the importance of the Epstein-Barr Virus (EBV), which was initially identified in 1964 while studying Burkitt's lymphoma, in the development of a number of cancers, including nasopharyngeal carcinoma, Hodgkin's lymphoma, Burkitt's lymphoma, and EBV-associated gastric carcinoma. Gammaherpesvirus EBV is extremely common; by adulthood, over 90 % of people worldwide have been infected. Usually, the virus causes a permanent latent infection in B cells, epithelial cells, and NK/T cells. It then contributes to oncogenesis by inhibiting apoptosis and promoting unchecked cell proliferation through its latent proteins, which include EBNA-1, LMP1, and LMP2A. Tumor progression further accelerated by EBV's capacity to transition between latent and lytic phases, especially in cases of nasopharyngeal carcinoma. Although our understanding of the molecular underpinnings of EBV has advanced, there are still difficulties in identifying latent infections and creating targeted therapeutics. To tackle EBV-associated malignancies, current research efforts are concentrated on developing vaccines, developing better diagnostic tools, and developing targeted treatments. In order to improve treatment approaches and lower the incidence of EBV-related cancers worldwide, more research into the relationship between EBV and immune evasion and cancer formation is necessary.

Extracellular vesicle-based anti-HOXB7 CD8+ T cell-specific vaccination strengthens antitumor effects induced by vaccination against Her2/neu

We previously developed an innovative strategy to induce CD8+ T lymphocyte-immunity through in vivo engineering of extracellular vesicles (EVs). This approach relies on intramuscular injection of DNA expressing antigens of interest fused at a biologically-inactive HIV-1 Nef protein mutant (Nefmut). Nefmut is very efficiently incorporated into EVs, thus conveying large amounts of fusion proteins into EVs released by transfected cells. This platform proved successful against highly immunogenic tumor-specific antigens. Here, we tested whether antigen-specific CD8+ T cell immune responses induced by engineered EVs can counteract the growth of tumors expressing two "self" tumor-associated antigens (TAAs): HOXB7 and Her2/neu. FVB/N mice were injected with DNA vectors expressing Nefmut fused to HOXB7 or Her2/neu, singly and in combination, before subcutaneous implantation of breast carcinoma cells co-expressing HOXB7 and Her2/neu. All mice immunized with the combination vaccine remained tumor-free, whereas groups vaccinated with single Nefmut-fused antigens were only partly protected, with stronger antitumor effects in Her2/neu-immunized mice. Double-vaccinated mice also controlled tumor growth upon a later tumor cell re-challenge. Importantly, co-vaccination also contained tumors in a therapeutic immunization setting. These results showed the efficacy of EV-based vaccination against two TAAs, and represent the first demonstration that HOXB7 may be targeted in multi-antigen immunotherapy strategies.

The T cell receptor β chain repertoire of tumor infiltrating lymphocytes improves neoantigen prediction and prioritization

In the realm of cancer immunotherapy, the meticulous selection of neoantigens plays a fundamental role in enhancing personalized treatments. Traditionally, this selection process has heavily relied on predicting the binding of peptides to human leukocyte antigens (pHLA). Nevertheless, this approach often overlooks the dynamic interaction between tumor cells and the immune system. In response to this limitation, we have developed an innovative prediction algorithm rooted in machine learning, integrating T cell receptor β chain (TCRβ) profiling data from colorectal cancer (CRC) patients for a more precise neoantigen prioritization. TCRβ sequencing was conducted to profile the TCR repertoire of tumor-infiltrating lymphocytes (TILs) from 28 CRC patients. The data unveiled both intra-tumor and inter-patient heterogeneity in the TCRβ repertoires of CRC patients, likely resulting from the stochastic utilization of V and J segments in response to neoantigens. Our novel combined model integrates pHLA binding information with pHLA-TCR binding to prioritize neoantigens, resulting in heightened specificity and sensitivity compared to models using individual features alone. The efficacy of our proposed model was corroborated through ELISpot assays on long peptides, performed on four CRC patients. These assays demonstrated that neoantigen candidates prioritized by our combined model outperformed predictions made by the established tool NetMHCpan. This comprehensive assessment underscores the significance of integrating pHLA binding with pHLA-TCR binding analysis for more effective immunotherapeutic strategies.

Seeing the Future of Lung Cancer Vaccination

It has been nearly fifteen years since the Food and Drug Administration (FDA) approved the first therapeutic cancer vaccine for solid tumors, namely Sipuleucel-T (Provenge®), marking a significant milestone in the treatment of metastatic castration-resistant prostate cancer [...].

The Impact of COVID-19 on RNA Therapeutics: A Surge in Lipid Nanoparticles and Alternative Delivery Systems

The COVID-19 pandemic has significantly accelerated progress in RNA-based therapeutics, particularly through the successful development and global rollout of mRNA vaccines. This review delves into the transformative impact of the pandemic on RNA therapeutics, with a strong focus on lipid nanoparticles (LNPs) as a pivotal delivery platform. LNPs have proven to be critical in enhancing the stability, bioavailability, and targeted delivery of mRNA, facilitating the unprecedented success of vaccines like those developed by Pfizer-BioNTech and Moderna. Beyond vaccines, LNP technology is being explored for broader therapeutic applications, including treatments for cancer, rare genetic disorders, and infectious diseases. This review also discusses emerging RNA delivery systems, such as polymeric nanoparticles and viral vectors, which offer alternative strategies to overcome existing challenges related to stability, immune responses, and tissue-specific targeting. Additionally, we examine the pandemic's influence on regulatory processes, including the fast-tracked approvals for RNA therapies, and the surge in research funding that has spurred further innovation in the field. Public acceptance of RNA-based treatments has also grown, laying the groundwork for future developments in personalized medicine. By providing an in-depth analysis of these advancements, this review highlights the long-term impact of COVID-19 on the evolution of RNA therapeutics and the future of precision drug delivery technologies.

Tumour Immunotherapy and Applications of Immunological Products: A Review of Literature

Malignant tumors, characterized by uncontrolled cell proliferation, are a leading global health challenge, responsible for over 9.7 million deaths in 2022, with new cases expected to rise to 35 million annually by 2050. Immunotherapy is preferred to other cancer therapies, offering precise targeting of malignant cells while simultaneously strengthening the immune system's complex responses. Advances in this novel field of science have been closely linked to a deeper knowledge of tumor biology, particularly the intricate interplay between tumor cells, the immune system, and the tumor microenvironment (TME), which are central to cancer progression and immune evasion. This review offers a comprehensive analysis of the molecular mechanisms that govern these interactions, emphasizing their critical role in the development of effective immunotherapeutic products. We critically evaluate the current immunotherapy approaches, including cancer vaccines, adoptive T cell therapies, and cytokine-based treatments, highlighting their efficacy and safety. We also explore the latest advancements in combination therapies, which synergistically integrate multiple immunotherapeutic strategies to overcome resistance and enhance therapeutic outcomes. This review offers key insights into the future of cancer immunotherapy with a focus on advancing more effective and personalized treatment strategies.

Vax-Innate: improving therapeutic cancer vaccines by modulating T cells and the tumour microenvironment

T cells have a critical role in mediating antitumour immunity. The success of immune checkpoint inhibitors (ICIs) for cancer treatment highlights how enhancing endogenous T cell responses can mediate tumour regression. However, mortality remains high for many cancers, especially in the metastatic setting. Based on advances in the genetic characterization of tumours and identification of tumour-specific antigens, individualized therapeutic cancer vaccines targeting mutated tumour antigens (neoantigens) are being developed to generate tumour-specific T cells for improved therapeutic responses. Early clinical trials using individualized neoantigen vaccines for patients with advanced disease had limited clinical efficacy despite demonstrated induction of T cell responses. Therefore, enhancing T cell activity by improving the magnitude, quality and breadth of T cell responses following vaccination is one current goal for improving outcome against metastatic tumours. Another major consideration is how T cells can be further optimized to function within the tumour microenvironment (TME). In this Perspective, we focus on neoantigen vaccines and propose a new approach, termed Vax-Innate, in which vaccination through intravenous delivery or in combination with tumour-targeting immune modulators may improve antitumour efficacy by simultaneously increasing the magnitude, quality and breadth of T cells while transforming the TME into a largely immunostimulatory environment for T cells.

Status Quo in the Liposome-Based Therapeutic Strategies Against Glioblastoma: "Targeting the Tumor and Tumor Microenvironment"

Glioblastoma is the most aggressive and fatal brain cancer, characterized by a high growth rate, invasiveness, and treatment resistance. The presence of the blood-brain barrier (BBB) and blood-brain tumor barrier (BBTB) poses a challenging task for chemotherapeutics, resulting in low efficacy, bioavailability, and increased dose-associated side effects. Despite the rigorous treatment strategies, including surgical resection, radiotherapy, and adjuvant chemotherapy with temozolomide, overall survival remains poor. The failure of current chemotherapeutics and other treatment regimens in glioblastoma necessitates the development of new drug delivery methodologies to precisely and efficiently target glioblastoma. Nanoparticle-based drug delivery systems offer a better therapeutic option in glioblastoma, considering their small size, ease of diffusion, and ability to cross the BBB. Liposomes are a specific category of nanoparticles made up of fatty acids. Furthermore, liposomes can be surface-modified to target a particular receptor and are nontoxic. This review discusses various methods of liposome modification for active/directed targeting and various liposome-based therapeutic approaches in the delivery of current chemotherapeutic drugs and nucleic acids in targeting the glioblastoma and tumor microenvironment.

Neoantigen sequestrated autophagosomes as therapeutic cancer vaccines

Neoantigens serve as ideal personalized cancer vaccines because of their high immunogenicity, ability to evade central thymic tolerance, and minimal risk of eliciting autoimmune responses. Herein, we describe a genetically engineered autophagosome-based neoantigen vaccine (APNV) in combination with an immune checkpoint inhibitor (anti-PD-1 antibody) for cancer immunotherapy. The APNV was derived from engineered NIH 3T3 cells, which co-express melanoma neoantigens and autophagosome maker microtubule-associated proteins 1 A/1B light chain 3B (LC3), from which the LC3-labeled neoantigen-autophagosomes were isolated. These purified autophagosomes, in conjunction with vaccine adjuvants high-mobility group box 1 (HMGB1) and granulocyte-macrophage colony-stimulating factor (GM-CSF), were integrated into a hydrogel to create an APNV. The APNV effectively activated dendritic cells both in vitro and in vivo. Moreover, APNV, in combination with checkpoint blockade therapy, significantly hampered post-surgical tumor recurrence in a subcutaneous melanoma tumor model and effectively impeded metastatic progression in a melanoma lung metastasis model. This APNV may be conducive to making personalized therapeutic neoantigen vaccines for cancer immunotherapy.

Cold and hot tumors: from molecular mechanisms to targeted therapy

Immunotherapy has made significant strides in cancer treatment, particularly through immune checkpoint blockade (ICB), which has shown notable clinical benefits across various tumor types. Despite the transformative impact of ICB treatment in cancer therapy, only a minority of patients exhibit a positive response to it. In patients with solid tumors, those who respond well to ICB treatment typically demonstrate an active immune profile referred to as the "hot" (immune-inflamed) phenotype. On the other hand, non-responsive patients may exhibit a distinct "cold" (immune-desert) phenotype, differing from the features of "hot" tumors. Additionally, there is a more nuanced "excluded" immune phenotype, positioned between the "cold" and "hot" categories, known as the immune "excluded" type. Effective differentiation between "cold" and "hot" tumors, and understanding tumor intrinsic factors, immune characteristics, TME, and external factors are critical for predicting tumor response and treatment results. It is widely accepted that ICB therapy exerts a more profound effect on "hot" tumors, with limited efficacy against "cold" or "altered" tumors, necessitating combinations with other therapeutic modalities to enhance immune cell infiltration into tumor tissue and convert "cold" or "altered" tumors into "hot" ones. Therefore, aligning with the traits of "cold" and "hot" tumors, this review systematically delineates the respective immune characteristics, influencing factors, and extensively discusses varied treatment approaches and drug targets based on "cold" and "hot" tumors to assess clinical efficacy.

ImmuneApp for HLA-I epitope prediction and immunopeptidome analysis

Advances in mass spectrometry accelerates the characterization of HLA ligandome, necessitating the development of efficient methods for immunopeptidomics analysis and (neo)antigen prediction. We develop ImmuneApp, an interpretable deep learning framework trained on extensive HLA ligand datasets, which improves the prediction of HLA-I epitopes, prioritizes neoepitopes, and enhances immunopeptidomics deconvolution. ImmuneApp extracts informative embeddings and identifies key residues for pHLA binding. We also present a more accurate model-based deconvolution approach and systematically analyzed 216 multi-allelic immunopeptidomics samples, identifying 835,551 ligands restricted to over 100 HLA-I alleles. Our investigation reveals the effectiveness of the composite model, denoted as ImmuneApp-MA, which integrates mono- and multi-allelic data to enhance predictive performance. Leveraging ImmuneApp-MA as a pre-trained model, we built ImmuneApp-Neo, an immunogenicity predictor that outperforms existing methods for prioritizing immunogenic neoepitope. ImmuneApp demonstrates its utility across various immunopeptidomics datasets, which will promote the discovery of novel neoantigens and the development of new immunotherapies.

Lipopolyplex-formulated mRNA cancer vaccine elicits strong neoantigen-specific T cell responses and antitumor activity

mRNA neoantigen cancer vaccine inducing neoantigen-specific T cell responses holds great promise for cancer immunotherapy; however, its clinical translation remains challenging because of suboptimal neoantigen prediction accuracy and low delivery efficiency, which compromise the in vivo therapeutic efficacy. We present a lipopolyplex (LPP)-formulated mRNA cancer vaccine encoding tandem neoantigens as a cancer therapeutic regimen. The LPP-formulated mRNA vaccines elicited robust neoantigen-specific CD8+ T cell responses in three syngeneic murine tumor models (CT26, MC38, and B16F10) to suppress tumor growth. Prophylactic cancer vaccine treatment completely prevented tumor development, and long-lasting memory T cells protected mice from tumor cell rechallenge. Combining the vaccine with immune checkpoint inhibitor further boosted the antitumor activity. Of note, LPP-based personalized cancer vaccine was administered in two cancer patients and induced meaningful neoantigen-specific T cell and clinical responses. In conclusion, we demonstrated that the LPP-based mRNA vaccine can elicit strong antitumor immune responses, and the results support further clinical evaluation of the therapeutic mRNA cancer vaccine.

The Immune Microenvironment in Prostate Cancer: A Comprehensive Review

BACKGROUND

Prostate cancer (PCa) is a malignancy with significant immunosuppressive properties and limited immune activation. This immunosuppression is linked to reduced cytotoxic T cell activity, impaired antigen presentation, and elevated levels of immunosuppressive cytokines and immune checkpoint molecules. Studies demonstrate that cytotoxic CD8+ T cell infiltration correlates with improved survival, while increased regulatory T cells (Tregs) and tumor-associated macrophages (TAMs) are associated with worse outcomes and therapeutic resistance. Th1 cells are beneficial, whereas Th17 cells, producing interleukin-17 (IL-17), contribute to tumor progression. Tumor-associated neutrophils (TANs) and immune checkpoint molecules, such as PD-1/PD-L1 and T cell immunoglobulin-3 (TIM-3) are also linked to advanced stages of PCa. Chemotherapy holds promise in converting the "cold" tumor microenvironment (TME) to a "hot" one by depleting immunosuppressive cells and enhancing tumor immunogenicity.

SUMMARY

This comprehensive review examines the immune microenvironment in PCa, focusing on the intricate interactions between immune and tumor cells in the TME. It highlights how TAMs, Tregs, cytotoxic T cells, and other immune cell types contribute to tumor progression or suppression and how PCa's low immunogenicity complicates immunotherapy.

KEY MESSAGES

The infiltration of cytotoxic CD8+ T cells and Th1 cells correlates with better outcomes, while elevated T regs and TAMs promote tumor growth, metastasis, and resistance. TANs and natural killer (NK) cells exhibit dual roles, with higher NK cell levels linked to better prognoses. Immune checkpoint molecules like PD-1, PD-L1, and TIM-3 are associated with advanced disease. Chemotherapy can improve tumor immunogenicity by depleting T regs and myeloid-derived suppressor cells, offering therapeutic promise.

mRNA-Based Cancer Vaccines: Advancements and Prospects

The success of mRNA COVID-19 vaccines has reinvigorated research and interest in mRNA-based cancer vaccines. Despite promising results in clinical trials, therapeutic mRNA-based cancer vaccines have not yet been approved for human use. These vaccines are designed to trigger tumor regression, establish enduring antitumor memory, and mitigate adverse reactions. However, challenges such as tumor-induced immunosuppression and immunoresistance significantly hinder their application. Here, we provide an overview of the recent advances of neoantigen discovery and delivery systems for mRNA vaccines, focusing on improving clinical efficacy. Additionally, we summarize the recent clinical advances involving mRNA cancer vaccines and discuss prospective strategies for overcoming immuneresistance.

Identification of Cuproptosis-Associated Prognostic Gene Expression Signatures from 20 Tumor Types

We investigated the mRNA expression of 124 cuproptosis-associated genes in 7489 biopsies from 20 different tumor types of The Cancer Genome Atlas (TCGA). The KM plotter algorithm has been used to calculate Kaplan-Meier statistics and false discovery rate (FDR) corrections. Interaction networks have been generated using Ingenuity Pathway Analysis (IPA). High mRNA expression of 63 out of 124 genes significantly correlated with shorter survival times of cancer patients across all 20 tumor types. IPA analyses revealed that their gene products were interconnected in canonical pathways (e.g., cancer, cell death, cell cycle, cell signaling). Four tumor entities showed a higher accumulation of genes than the other cancer types, i.e., renal clear cell carcinoma (n = 21), renal papillary carcinoma (n = 13), kidney hepatocellular carcinoma (n = 13), and lung adenocarcinoma (n = 9). These gene clusters may serve as prognostic signatures for patient survival. These signatures were also of prognostic value for tumors with high mutational rates and neoantigen loads. Cuproptosis is of prognostic significance for the survival of cancer patients. The identification of specific gene signatures deserves further exploration for their clinical utility in routine diagnostics.

Tumor immunogenicity regulates host immune responses, and conventional dendritic cell type 2 uptakes the majority of tumor antigens in an orthotopic lung cancer model

Human lung cancer carries high genetic alterations, expressing high tumor-specific neoantigens. Although orthotopic murine lung cancer models recapitulate many characteristics of human lung cancers, genetically engineered mouse models have fewer somatic mutations than human lung cancer, resulting in scarce immune cell infiltration and deficient immune responses. The endogenous mouse lung cancer model driven by Kras mutation and Trp53 deletion (KP model) has minimal immune infiltration because of a scarcity of neoantigens. Fine-tuning tumor antigenicity to trigger the appropriate level of antitumor immunity would be key to investigating immune responses against human lung cancer. We engineered the KP model to express antigens of OVA peptides (minOVA) as neoantigens along with ZsGreen, a traceable fluorescent conjugate. The KP model expressing minOVA exhibited stronger immunogenicity with higher immune cell infiltration comprised of CD8+ T cells and CD11c+ dendritic cells (DCs). Consequently, the KP model expressing minOVA exhibits suppressed tumor growth compared to its origin. We further analyzed tumor-infiltrated DCs. The majority of ZsGreen conjugated with minOVA was observed in the conventional type 2 DCs (cDC2), whereas cDC1 has minimal. These data indicate that tumor immunogenicity regulates host immune responses, and tumor neoantigen is mostly recognized by cDC2 cells, which may play a critical role in initiating antitumor immune responses in an orthotopic murine lung cancer model.

Applications of cell therapy in the treatment of virus-associated cancers

A diverse range of viruses have well-established roles as the primary driver of oncogenesis in various haematological malignancies and solid tumours. Indeed, estimates suggest that approximately 1.5 million patients annually are diagnosed with virus-related cancers. The predominant human oncoviruses include Epstein-Barr virus (EBV), Kaposi sarcoma-associated herpesvirus (KSHV), hepatitis B and C viruses (HBV and HCV), human papillomavirus (HPV), human T-lymphotropic virus type 1 (HTLV1), and Merkel cell polyomavirus (MCPyV). In addition, although not inherently oncogenic, human immunodeficiency virus (HIV) is associated with immunosuppression that contributes to the development of AIDS-defining cancers (specifically, Kaposi sarcoma, aggressive B cell non-Hodgkin lymphoma and cervical cancer). Given that an adaptive T cell-mediated immune response is crucial for the control of viral infections, increasing research is being focused on evaluating virus-specific T cell therapies for the treatment of virus-associated cancers. In this Review, we briefly outline the roles of viruses in the pathogenesis of these malignancies before describing progress to date in the field of virus-specific T cell therapy and evaluating the potential utility of these therapies to treat or possibly even prevent virus-related malignancies.

NeoDesign: a computational tool for optimal selection of polyvalent neoantigen combinations

MOTIVATION

Tumor polyvalent neoantigen mRNA vaccines are gaining prominence in immunotherapy. The design of sequences in vaccine development is crucial for enhancing both the immunogenicity and safety of vaccines. However, a major challenge lies in selecting the optimal sequences from the large pools generated by multiple peptide combinations and synonymous codons.

RESULTS

We introduce NeoDesign, a computational tool designed to tackle the challenge of sequence design. NeoDesign comprises four modules: Library Construction, Optimal Path Filtering, Linker Addition, and λ-Evaluation. It aims to identify the optimal protein sequence for tumor polyvalent neoantigen vaccines by minimizing linker usage, avoiding unexpected neoantigens and functional domains, and simplifying the structure. It also provides a preference scheme to balance mRNA stability and protein expression when designing mRNA sequences for the optimal protein sequence. This tool can potentially improve the sequence design of tumor polyvalent neoantigen mRNA vaccines, thereby significantly advancing immunotherapy strategies.

AVAILABILITY AND IMPLEMENTATION

NeoDesign is freely available on https://github.com/HuangLab-Fudan/neoDesign and https://figshare.com/projects/NeoDesign/221704.

Enhancing cell-based therapies with synthetic gene circuits responsive to molecular stimuli

Synthetic biology aims to contribute to the development of next-generation patient-specific cell-based therapies for chronic diseases especially through the construction of sophisticated synthetic gene switches to enhance the safety and spatiotemporal controllability of engineered cells. Indeed, switches that sense and process specific cues, which may be either externally administered triggers or endogenous disease-associated molecules, have emerged as powerful tools for programming and fine-tuning therapeutic outputs. Living engineered cells, often referred to as designer cells, incorporating such switches are delivered to patients either as encapsulated cell implants or by infusion, as in the case of the clinically approved CAR-T cell therapies. Here, we review recent developments in synthetic gene switches responsive to molecular stimuli, spanning regulatory mechanisms acting at the transcriptional, translational, and posttranslational levels. We also discuss current challenges facing clinical translation of cell-based therapies employing these devices.

Clinical efficacy and immune response of neoadjuvant camrelizumab plus chemotherapy in resectable locally advanced oesophageal squamous cell carcinoma: a phase 2 trial

BACKGROUND

Neoadjuvant immunotherapy is under intensive investigation for esophageal squamous cell carcinoma (ESCC). This study assesses the efficacy and immune response of neoadjuvant immunochemotherapy (nICT) in ESCC.

METHODS

In this phase II trial (ChiCTR2100045722), locally advanced ESCC patients receiving nICT were enrolled. The primary endpoint was the pathological complete response (pCR) rate. Multiplexed immunofluorescence, RNA-seq and TCR-seq were conducted to explore the immune response underlying nICT.

RESULTS

Totally 42 patients were enrolled, achieving a 27.0% pCR rate. The 1-year, 2-year DFS and OS rates were 89.2%, 64.4% and 97.3%, 89.2%, respectively. RNA-seq analysis highlighted T-cell activation as the most significantly enriched pathway. The tumour immune microenvironment (TIME) was characterised by high CD4, CD8, Foxp3, and PD-L1 levels, associating with better pathological regression (TRS0/1). TIME was categorised into immune-infiltrating, immune-tolerant, and immune-desert types. Notably, the immune-infiltrating type and tertiary lymphoid structures correlated with improved outcomes. In the context of nICT, TIM-3 negatively influenced treatment efficacy, while elevated TIGIT/PD-1 expression post-nICT correlated positively with CD8+ T cell levels. TCR-seq identified three TCR rearrangements, underscoring the specificity of T-cell responses.

CONCLUSIONS

Neoadjuvant camrelizumab plus chemotherapy is effective for locally advanced, resectable ESCC, eliciting profound immune response that closely associated with clinical outcomes.