Antigen processing and presentation in cancer immunotherapy

Wilms' tumor 1 -targeting cancer vaccine: Recent advancements and future perspectives

This mini-review explores recent advancements in cancer vaccines that target Wilms' tumor (WT1). Phase I/II trials of WT1 peptide vaccines have demonstrated their safety and efficacy against various cancers. Early trials employing HLA class I peptides evolved through their combination with HLA class II peptides, resulting in improved clinical outcomes. Additionally, WT1-targeted dendritic cell vaccines have exhibited favorable results. Studies focusing on hematological malignancies have revealed promising outcomes, including long-term remission and extended survival times. The combination of vaccines with immune checkpoint inhibitors has shown synergistic effects. Current preclinical developments are focused on enhancing the effectiveness of WT1 vaccines, underscoring the necessity for future large-scale Phase III trials to further elucidate their efficacy.

Activation of MAL2 by RAD21 inhibits the expression of MHC-I in immune evasion of endometrial cancer

CD8+ T cells are the primary mediators of anticancer immunity, and modulation of the CD8+ T cell response has been a central focus of immunotherapy to treat cancer. When CD8+ T cells specifically recognize antigenic peptides presented by the MHC-I on tumor cells, they become activated and kill the tumor cells. However, one pivotal mechanism through which tumor cells evade immune surveillance is to reduce their antigen presentation. To identify novel immunotherapeutic targets, we specifically focused on the role of MAL2 in immune evasion in endometrial cancer (EC) and the underlying mechanism. MAL2 was overexpressed in EC tissues and cells and its transcription was enhanced by RAD21. Knockdown of MAL2 or RAD21 inhibited malignant behavior and immune evasion of EC cells by repressing MHC-I expression and the cytotoxic effects of CD8+ cells. Conversely, MAL2 promoted immune evasion of EC cells and tumor growth in mice in the presence of RAD21 knockdown. These results indicate that RAD21 activation of MAL2 inhibits antigen processing and presentation of MHC-I, thereby inducing immune evasion of EC cells. We further suggest that RAD21 and MAL2 may serve as novel targets for EC immunotherapy.

Radioactive Hydroxyapatite Microspheres Empower Sustainable In Situ Tumor Vaccination

Tumor in situ vaccination (ISV) strategies have emerged in clinical trials as promising approaches, involving the release of tumor antigens through local radiotherapy and intratumorally adjuvant injections. However, the current fabrication strategy for achieving a sustainable immune response to ISV remains a pressing challenge. In this study, we present an empowered sustainable ISV method for antitumor therapy using 177Lu-labeled manganese-doped mesoporous hydroxyapatite (177Lu/Mn-HAP) microspheres. The ISV enables the sustained utilization of tumor antigens, leading to the activation of dendritic cells and polarization of macrophages toward the M1 subtype. Consequently, it facilitates the generation of potent CD8+ T-cell responses, enhancing the antitumor effects of internal radiation in both primary and distant tumors. Importantly, this approach achieves complete remission in all tumor-bearing mice and stimulates immune memory to prevent tumor recurrence. Our study highlights a universal and safe ISV strategy capable of inducing potent tumor-specific and sustainable immune response.

First-in-human clinical trial results with ABBV-184, a first-in-class T-cell receptor/anti-CD3 bispecific protein, in adults with previously treated AML or NSCLC

BACKGROUND

ABBV-184, a novel survivin peptide-targeting T-cell receptor (TCR)/anti-CD3 bispecific protein, demonstrated preclinical T-cell activation and cytotoxicity toward HLA-A2:01-positive tumor lines. This first-in-human trial evaluated ABBV-184 monotherapy in patients with acute myeloid leukemia (AML) and non-small cell lung cancer (NSCLC).

RESEARCH DESIGN AND METHODS

This phase 1 multicenter, open-label, dose escalation trial (NCT04272203) enrolled adult patients with relapsed/refractory AML or NSCLC with an HLA-A2:01 restricted genotype. Patients received ABBV-184 at 0.07 ug/kg initially, with 2- to 3-fold dose increases. The primary objective was determining the ABBV-184 recommended phase 2 dose. Secondary objectives included safety, tolerability, pharmacokinetics, and immunogenicity assessments.

RESULTS

Fifteen patients enrolled in the dose escalation (8 AML and 7 NSCLC). ABBV-184 doses ranged from 0.07 mg/kg-0.7 µg/kg, with a half-life of approximately 13-29 hours. Transient cytokine increases were observed at all dose levels, and in patients with NSCLC, transient peripheral blood lymphocyte decreases were observed. The most frequently reported treatment-emergent adverse events (TEAEs) were anemia, diarrhea, and headache. Grade 1-2 infusion-related reaction (IRR) and cytokine release syndrome (CRS) TEAEs were reported.

CONCLUSIONS

ABBV-184 was well tolerated and demonstrated preliminary evidence of CD3 engagement with transient cytokine increases and peripheral lymphocyte decreases.

CLINICAL TRIAL REGISTRATION

NCT04272203.

Targeting CD8+ T cells with natural products for tumor therapy: Revealing insights into the mechanisms

BACKGROUND

Despite significant advances in cancer immunotherapy over the past decades, such as T cell-engaging chimeric antigen receptor (CAR)-T cell therapy and immune checkpoint blockade (ICB), therapeutic failure resulting from various factors remains prevalent. Therefore, developing combinational immunotherapeutic strategies is of great significance for improving the clinical outcome of cancer immunotherapy. Natural products are substances that naturally exist in various living organisms with multiple pharmacological or biological activities, and some of them have been found to have anti-tumor potential. Notably, emerging evidences have suggested that several natural compounds may boost the anti-tumor effects through activating immune response of hosts, in which CD8+ T cells play a pivotal role.

METHODS

The data of this review come from PubMed, Web of Science, Google Scholar, and ClinicalTrials (https://clinicaltrials.gov/) with the keywords "CD8+ T cell", "anti-tumor", "immunity", "signal 1", "signal 2", "signal 3", "natural products", "T cell receptor (TCR)", "co-stimulation", "co-inhibition", "immune checkpoint", "inflammatory cytokine", "hesperidin", "ginsenoside", "quercetin", "curcumin", "apigenin", "dendrobium officinale polysaccharides (DOPS)", "luteolin", "shikonin", "licochalcone A", "erianin", "resveratrol", "procyanidin", "berberine", "usnic acid", "naringenin", "6-gingerol", "ganoderma lucidum polysaccharide (GL-PS)", "neem leaf glycoprotein (NLGP)", "paclitaxel", "source", "pharmacological activities", and "toxicity". These literatures were published between 1993 and 2023.

RESULTS

Natural products have considerable advantages as anti-tumor drugs based on the various species, wide distribution, low price, and few side effects. This review summarized the effects and mechanisms of some natural products that exhibit anti-tumor effects via targeting CD8+ T cells, mainly focused on the three signals that activate CD8+ T cells: TCR, co-stimulation, and inflammatory cytokines.

CONCLUSION

Clarifying the role and underlying mechanism of natural products in cancer immunotherapy may provide more options for combinational treatment strategies and benefit cancer therapy, to shed light on identifying potential natural compounds for improving the clinical outcome in cancer immunotherapy.

Targeting Neoantigens in Pancreatic Ductal Adenocarcinoma

Pancreatic ductal adenocarcinoma (PDAC) is the most common type of pancreatic cancer and is currently the third leading cause of cancer-related death in the United States after lung and colon cancer. PDAC is estimated to be the second leading cause of cancer-related death by 2030. The diagnosis at a late stage is the underlying cause for higher mortality and poor prognosis after surgery. Treatment resistance to chemotherapy and immunotherapy results in recurrence after surgery and poor prognosis. Neoantigen burden and CD8+ T-cell infiltration are associated with clinical outcomes in PDAC and paucity of neoantigen-reactive tumor-infiltrating lymphocytes may be the underlying cause for treatment resistance for immunotherapy. This suggests a need to identify additional neoantigens and therapies targeting these neoantigens to improve clinical outcomes in PDAC. In this review, we focus on describing the pathophysiology, current treatment strategies, and treatment resistance in PDAC followed by the need to target neoantigens in PDAC.

Cross-Talks between Raf Kinase Inhibitor Protein and Programmed Cell Death Ligand 1 Expressions in Cancer: Role in Immune Evasion and Therapeutic Implications

Innovations in cancer immunotherapy have resulted in the development of several novel immunotherapeutic strategies that can disrupt immunosuppression. One key advancement lies in immune checkpoint inhibitors (ICIs), which have shown significant clinical efficacy and increased survival rates in patients with various therapy-resistant cancers. This immune intervention consists of monoclonal antibodies directed against inhibitory receptors (e.g., PD-1) on cytotoxic CD8 T cells or against corresponding ligands (e.g., PD-L1/PD-L2) overexpressed on cancer cells and other cells in the tumor microenvironment (TME). However, not all cancer cells respond-there are still poor clinical responses, immune-related adverse effects, adaptive resistance, and vulnerability to ICIs in a subset of patients with cancer. This challenge showcases the heterogeneity of cancer, emphasizing the existence of additional immunoregulatory mechanisms in many patients. Therefore, it is essential to investigate PD-L1's interaction with other oncogenic genes and pathways to further advance targeted therapies and address resistance mechanisms. Accordingly, our aim was to investigate the mechanisms governing PD-L1 expression in tumor cells, given its correlation with immune evasion, to uncover novel mechanisms for decreasing PD-L1 expression and restoring anti-tumor immune responses. Numerous studies have demonstrated that the upregulation of Raf Kinase Inhibitor Protein (RKIP) in many cancers contributes to the suppression of key hyperactive pathways observed in malignant cells, alongside its broadening involvement in immune responses and the modulation of the TME. We, therefore, hypothesized that the role of PD-L1 in cancer immune surveillance may be inversely correlated with the low expression level of the tumor suppressor Raf Kinase Inhibitor Protein (RKIP) expression in cancer cells. This hypothesis was investigated and we found several signaling cross-talk pathways between the regulations of both RKIP and PD-L1 expressions. These pathways and regulatory factors include the MAPK and JAK/STAT pathways, GSK3β, cytokines IFN-γ and IL-1β, Sox2, and transcription factors YY1 and NFκB. The pathways that upregulated PD-L1 were inhibitory for RKIP expression and vice versa. Bioinformatic analyses in various human cancers demonstrated the inverse relationship between PD-L1 and RKIP expressions and their prognostic roles. Therefore, we suspect that the direct upregulation of RKIP and/or the use of targeted RKIP inducers in combination with ICIs could result in a more targeted anti-tumor immune response-addressing the therapeutic challenges related to PD-1/PD-L1 monotherapy alone.

Neoantigen Identification and Dendritic Cell-Based Vaccines for Lung Cancer Immunotherapy

Immunotherapies can treat many cancers, including difficult-to-treat cases such as lung cancer. Due to its tolerability, long-lasting therapeutic responses, and efficacy in a wide spectrum of patients, immunotherapy can also help to treat lung cancer, which has few treatment choices. Tumor-specific antigens (TSAs) for cancer vaccinations and T-cell therapies are difficult to discover. Neoantigens (NeoAgs) from genetic mutations, irregular RNA splicing, protein changes, or viral genetic sequences in tumor cells provide a solution. NeoAgs, unlike TSAs, are non-self and can cause an immunological response. Next-generation sequencing (NGS) and bioinformatics can swiftly detect and forecast tumor-specific NeoAgs. Highly immunogenic NeoAgs provide personalized or generalized cancer immunotherapies. Dendritic cells (DCs), which originate and regulate T-cell responses, are widely studied potential immunotherapeutic therapies for lung cancer and other cancers. DC vaccines are stable, reliable, and safe in clinical trials. The purpose of this article is to evaluate the current status, limitations, and prospective clinical applications of DC vaccines, as well as the identification and selection of major histocompatibility complex (MHC) class I and II genes for NeoAgs. Our goal is to explain DC biology and activate DC manipulation to help researchers create extremely potent cancer vaccines for patients.

Design of Cytotoxic T Cell Epitopes by Machine Learning of Human Degrons

Antigen processing is critical for therapeutic vaccines to generate epitopes for priming cytotoxic T cell responses against cancer and pathogens, but insufficient processing often limits the quantity of epitopes released. We address this challenge using machine learning to ascribe a proteasomal degradation score to epitope sequences. Epitopes with varying scores were translocated into cells using nontoxic anthrax proteins. Epitopes with a low score show pronounced immunogenicity due to antigen processing, but epitopes with a high score show limited immunogenicity. This work sheds light on the sequence-activity relationships between proteasomal degradation and epitope immunogenicity. We anticipate that future efforts to incorporate proteasomal degradation signals into vaccine designs will lead to enhanced cytotoxic T cell priming by these vaccines in clinical settings.

Advances in Therapeutic Cancer Vaccines, Their Obstacles, and Prospects Toward Tumor Immunotherapy

Over the past few decades, cancer immunotherapy has experienced a significant revolution due to the advancements in immune checkpoint inhibitors (ICIs) and adoptive cell therapies (ACTs), along with their regulatory approvals. In recent times, there has been hope in the effectiveness of cancer vaccines for therapy as they have been able to stimulate de novo T-cell reactions against tumor antigens. These tumor antigens include both tumor-associated antigen (TAA) and tumor-specific antigen (TSA). Nevertheless, the constant quest to fully achieve these abilities persists. Therefore, this review offers a broad perspective on the existing status of cancer immunizations. Cancer vaccine design has been revolutionized due to the advancements made in antigen selection, the development of antigen delivery systems, and a deeper understanding of the strategic intricacies involved in effective antigen presentation. In addition, this review addresses the present condition of clinical tests and deliberates on their approaches, with a particular emphasis on the immunogenicity specific to tumors and the evaluation of effectiveness against tumors. Nevertheless, the ongoing clinical endeavors to create cancer vaccines have failed to produce remarkable clinical results as a result of substantial obstacles, such as the suppression of the tumor immune microenvironment, the identification of suitable candidates, the assessment of immune responses, and the acceleration of vaccine production. Hence, there are possibilities for the industry to overcome challenges and enhance patient results in the coming years. This can be achieved by recognizing the intricate nature of clinical issues and continuously working toward surpassing existing limitations.

Low-dose radiation therapy mobilizes antitumor immunity: New findings and future perspectives

Radiotherapy has unique immunostimulatory and immunosuppressive effects. Although high-dose radiotherapy has been found to have systemic antitumor effects, clinically significant abscopal effects were uncommon on the basis of irradiating single lesion. Low-dose radiation therapy (LDRT) emerges as a novel approach to enhance the antitumor immune response due to its role as a leverage to reshape the tumor immune microenvironment (TIME). In this article, from bench to bedside, we reviewed the possible immunomodulatory role of LDRT on TIME and systemic tumor immune environment, and outlined preclinical evidence and clinical application. We also discussed the current challenges when LDRT is used as a combination therapy, including the optimal dose, fraction, frequency, and combination of drugs. The advantage of low toxicity makes LDRT potential to be applied in multiple lesions to amplify antitumor immune response in polymetastatic disease, and its intersection with other disciplines might also make it a direction for radiotherapy-combined modalities.

Comprehensive analysis of the interaction of antigen presentation during anti-tumour immunity and establishment of AIDPS systems in ovarian cancer

There are hundreds of prognostic models for ovarian cancer. These genes are based on different gene classes, and there are many ways to construct the models. Therefore, this paper aims to build the most stable prognostic evaluation system known to date through 101 machine learning strategies. We combined 101 algorithm combinations with 10 machine learning algorithms to create antigen presentation-associated genetic markers (AIDPS) with outstanding precision and steady performance. The inclusive set of algorithms comprises the elastic network (Enet), Ridge, stepwise Cox, Lasso, generalized enhanced regression model (GBM), random survival forest (RSF), supervised principal component (SuperPC), Cox partial least squares regression (plsRcox), survival support vector machine (Survival-SVM). Then, in the train cohort, the prediction model was fitted using a leave-one cross-validation (LOOCV) technique, which involved 101 different possible combinations of prognostic genes. Seven validation data sets (GSE26193, GSE26712, GSE30161, GSE63885, GSE9891, GSE140082 and ICGC_OV_AU) were compared and analysed, and the C-index was calculated. Finally, we collected 32 published ovarian cancer prognostic models (including mRNA and lncRNA). All data sets and prognostic models were subjected to a univariate Cox regression analysis, and the C-index was calculated to demonstrate that the antigen presentation process should be the core criterion for evaluating ovarian cancer prognosis. In a univariate Cox regression analysis, 22 prognostic genes were identified based on the expression profiles of 283 genes involved in antigen presentation and the intersection of genes (p < 0.05). AIDPS were developed by our machine learning-based integration method, which was applied to these 22 genes. One hundred and one prediction models are fitted using the LOOCV framework, and the C-index is calculated for each model across all validation sets. Interestingly, RSF + Lasso was the best model overall since it had the greatest average C-index and the highest C-index of any combination of models tested on the validated data sets. In comparing external cohorts, we found that the C-index correlated AIDPS method using the RSF + Lasso method in 101 prediction models was in contrast to other features. Notably, AIDPS outperformed the vast majority of models across all data sets. Antigen-presenting anti-tumour immune pathways can be used as a representative gene set of ovarian cancer to track the prognosis of patients with cancer. The antigen-presenting model obtained by the RSF + Lasso method has the best C-INDEX, which plays a key role in developing antigen-presenting targeted drugs in ovarian cancer and improving the treatment outcome of patients.

A Comparison of Spatial and Phenotypic Immune Profiles of Pancreatic Ductal Adenocarcinoma and Its Precursor Lesions

Pancreatic ductal adenocarcinoma (PDAC) is a devastating disease with a 5-year survival rate of 12.5%. PDAC predominantly arises from non-cystic pancreatic intraepithelial neoplasia (PanIN) and cystic intraductal papillary mucinous neoplasm (IPMN). We used multiplex immunofluorescence and computational imaging technology to characterize, map, and compare the immune microenvironments (IMEs) of PDAC and its precursor lesions. We demonstrate that the IME of IPMN was abundantly infiltrated with CD8+ T cells and PD-L1-positive antigen-presenting cells (APCs), whereas the IME of PanIN contained fewer CD8+ T cells and fewer PD-L1-positive APCs but elevated numbers of immunosuppressive regulatory T cells (Tregs). Thus, immunosuppression in IPMN and PanIN seems to be mediated by different mechanisms. While immunosuppression in IPMN is facilitated by PD-L1 expression on APCs, Tregs seem to play a key role in PanIN. Our findings suggest potential immunotherapeutic interventions for high-risk precursor lesions, namely, targeting PD-1/PD-L1 in IPMN and CTLA-4-positive Tregs in PanIN to restore immunosurveillance and prevent progression to cancer. Tregs accumulate with malignant transformation, as observed in PDAC, and to a lesser extent in IPMN-associated PDAC (IAPA). High numbers of Tregs in the microenvironment of PDAC went along with a markedly decreased interaction between CD8+ T cells and cancerous epithelial cells (ECs), highlighting the importance of Tregs as key players in immunosuppression in PDAC. We found evidence that a defect in antigen presentation, further aggravated by PD-L1 expression on APC, may contribute to immunosuppression in IAPA, suggesting a role for PD-L1/PD-1 immune checkpoint inhibitors in the treatment of IAPA.

An integrative machine learning model for the identification of tumor T-cell antigens

The escalating global incidence of cancer poses significant health challenges, underscoring the need for innovative and more efficacious treatments. Cancer immunotherapy, a promising approach leveraging the body's immune system against cancer, emerges as a compelling solution. Consequently, the identification and characterization of tumor T-cell antigens (TTCAs) have become pivotal for exploration. In this manuscript, we introduce TTCA-IF, an integrative machine learning-based framework designed for TTCAs identification. TTCA-IF employs ten feature encoding types in conjunction with five conventional machine learning classifiers. To establish a robust foundation, these classifiers are trained, resulting in the creation of 150 baseline models. The outputs from these baseline models are then fed back into the five classifiers, generating their respective meta-models. Through an ensemble approach, the five meta-models are seamlessly integrated to yield the final predictive model, the TTCA-IF model. Our proposed model, TTCA-IF, surpasses both baseline models and existing predictors in performance. In a comparative analysis involving nine novel peptide sequences, TTCA-IF demonstrated exceptional accuracy by correctly identifying 8 out of 9 peptides as TTCAs. As a tool for screening and pinpointing potential TTCAs, we anticipate TTCA-IF to be invaluable in advancing cancer immunotherapy.

The significance of targeting lysosomes in cancer immunotherapy

Lysosomes are intracellular digestive organelles that participate in various physiological and pathological processes, including the regulation of immune checkpoint molecules, immune cell function in the tumor microenvironment, antigen presentation, metabolism, and autophagy. Abnormalities or dysfunction of lysosomes are associated with the occurrence, development, and drug resistance of tumors. Lysosomes play a crucial role and have potential applications in tumor immunotherapy. Targeting lysosomes or harnessing their properties is an effective strategy for tumor immunotherapy. However, the mechanisms and approaches related to lysosomes in tumor immunotherapy are not fully understood at present, and further basic and clinical research is needed to provide better treatment options for cancer patients. This review focuses on the research progress related to lysosomes and tumor immunotherapy in these.

Integrating single-cell and bulk RNA sequencing data unveils antigen presentation and process-related CAFS and establishes a predictive signature in prostate cancer

BACKGROUND

Cancer-associated fibroblasts (CAFs) are heterogeneous and can influence the progression of prostate cancer in multiple ways; however, their capacity to present and process antigens in PRAD has not been investigated. In this study, antigen presentation and process-related CAFs (APPCAFs) were identified using bioinformatics, and the clinical implications of APPCAF-related signatures in PRAD were investigated.

METHODS

SMART technology was used to sequence the transcriptome of primary CAFs isolated from patients undergoing different treatments. Differential expression gene (DEG) screening was conducted. A CD4 + T-cell early activation assay was used to assess the activation degree of CD4 + T cells. The datasets of PRAD were obtained from The Cancer Genome Atlas (TCGA) database and NCBI Gene Expression Omnibus (GEO), and the list of 431 antigen presentation and process-related genes was obtained from the InnateDB database. Subsequently, APP-related CAFs were identified by nonnegative matrix factorization (NMF) based on a single-cell seq (scRNA) matrix. GSVA functional enrichment analyses were performed to depict the biological functions. A risk signature based on APPCAF-related genes (APPCAFRS) was developed by least absolute shrinkage and selection operator (LASSO) regression analysis, and the independence of the risk score as a prognostic factor was evaluated by univariate and multivariate Cox regression analyses. Furthermore, a biochemical recurrence-free survival (BCRFS)-related nomogram was established, and immune-related characteristics were assessed using the ssGSEA function. The immune treatment response in PRAD was further analyzed by the Tumor Immune Dysfunction and Exclusion (TIDE) tool. The expression levels of hub genes in APPCAFRS were verified in cell models.

RESULTS

There were 134 upregulated and 147 downregulated genes, totaling 281 differentially expressed genes among the primary CAFs. The functions and pathways of 147 downregulated DEGs were significantly enriched in antigen processing and presentation processes, MHC class II protein complex and transport vesicle, MHC class II protein complex binding, and intestinal immune network for IgA production. Androgen withdrawal diminished the activation effect of CAFs on T cells. NMF clustering of CAFs was performed by APPRGs, and pseudotime analysis yielded the antigen presentation and process-related CAF subtype CTSK + MRC2 + CAF-C1. CTSK + MRC2 + CAF-C1 cells exhibited ligand‒receptor connections with epithelial cells and T cells. Additionally, we found a strong association between CTSK + MRC2 + CAF-C1 cells and inflammatory CAFs. Through differential gene expression analysis of the CTSK + MRC2 + CAF-C1 and NoneAPP-CAF-C2 subgroups, 55 significant DEGs were identified, namely, APPCAFRGs. Based on the expression profiles of APPCAFRGs, we divided the TCGA-PRAD cohort into two clusters using NMF consistent cluster analysis, with the genetic coefficient serving as the evaluation index. Four APPCAFRGs, THBS2, DPT, COL5A1, and MARCKS, were used to develop a prognostic signature capable of predicting BCR occurrence in PRAD patients. Subsequently, a nomogram with stability and accuracy in predicting BCR was constructed based on Gleason grade (p = n.s.), PSA (p < 0.001), T stage (p < 0.05), and risk score (p < 0.01). The analysis of immune infiltration showed a positive correlation between the abundance of resting memory CD4 + T cells, M1 macrophages, resting dendritic cells, and the risk score. In addition, the mRNA expression levels of THBS2, DPT, COL5A1, and MARCKS in the cell models were consistent with the results of the bioinformatics analysis.

CONCLUSIONS

APPCAFRS based on four potential APPCAFRGs was developed, and their interaction with the immune microenvironment may play a crucial role in the progression to castration resistance of PRAD. This novel approach provides valuable insights into the pathogenesis of PRAD and offers unexplored targets for future research.

It Takes Two to Tango: The Interplay between Prostate Cancer and Its Microenvironment from an Epigenetic Perspective

Prostate cancer is the second most common cancer in men worldwide and is associated with high morbidity and mortality. Consequently, there is an urgent unmet need for novel treatment avenues. In addition to somatic genetic alterations, deviations in the epigenetic landscape of cancer cells and their tumor microenvironment (TME) are critical drivers of prostate cancer initiation and progression. Unlike genomic mutations, epigenetic modifications are potentially reversible. Therefore, the inhibition of aberrant epigenetic modifications represents an attractive and exciting novel treatment strategy for castration-resistant prostate cancer patients. Moreover, drugs targeting the epigenome also exhibit synergistic interactions with conventional therapeutics by directly enhancing their anti-tumorigenic properties by "priming" the tumor and tumor microenvironment to increase drug sensitivity. This review summarizes the major epigenetic alterations in prostate cancer and its TME, and their involvement in prostate tumorigenesis, and discusses the impact of epigenome-targeted therapies.

Protein kinase C delta regulates mononuclear phagocytes and hinders response to immunotherapy in cancer

Mononuclear phagocytes (MPs) play a crucial role in tissue homeostasis; however, MPs also contribute to tumor progression and resistance to immune checkpoint blockade (ICB). Targeting MPs could be an effective strategy to enhance ICB efficacy. We report that protein kinase C delta (PKCδ), a serine/threonine kinase, is abundantly expressed by MPs in human and mouse tumors. PKCδ-/- mice displayed reduced tumor progression compared to wild types, with increased response to anti-PD-1. Tumors from PKCδ-/- mice demonstrated TH1-skewed immune response including increased antigen presentation and T cell activation. Depletion of MPs in vivo altered tumor growth in control but not PKCδ-/- mice. Coinjection of PKCδ-/- M2-like macrophages with cancer cells into wild-type mice markedly delayed tumor growth and significantly increased intratumoral T cell activation compared to PKCδ+/+ controls. PKCδ deficiency reprogrammed MPs by activating type I and type II interferon signaling. Thus, PKCδ might be targeted to reprogram MPs to augment ICB efficacy.

Therapeutic cancer vaccines: advancements, challenges, and prospects

With the development and regulatory approval of immune checkpoint inhibitors and adoptive cell therapies, cancer immunotherapy has undergone a profound transformation over the past decades. Recently, therapeutic cancer vaccines have shown promise by eliciting de novo T cell responses targeting tumor antigens, including tumor-associated antigens and tumor-specific antigens. The objective was to amplify and diversify the intrinsic repertoire of tumor-specific T cells. However, the complete realization of these capabilities remains an ongoing pursuit. Therefore, we provide an overview of the current landscape of cancer vaccines in this review. The range of antigen selection, antigen delivery systems development the strategic nuances underlying effective antigen presentation have pioneered cancer vaccine design. Furthermore, this review addresses the current status of clinical trials and discusses their strategies, focusing on tumor-specific immunogenicity and anti-tumor efficacy assessment. However, current clinical attempts toward developing cancer vaccines have not yielded breakthrough clinical outcomes due to significant challenges, including tumor immune microenvironment suppression, optimal candidate identification, immune response evaluation, and vaccine manufacturing acceleration. Therefore, the field is poised to overcome hurdles and improve patient outcomes in the future by acknowledging these clinical complexities and persistently striving to surmount inherent constraints.

Neddylation Regulation of Immune Responses

Neddylation plays a vital role in post-translational modification, intricately shaping the regulation of diverse biological processes, including those related to cellular immune responses. In fact, neddylation exerts control over both innate and adaptive immune systems via various mechanisms. Specifically, neddylation influences the function and survival of innate immune cells, activation of pattern recognition receptors and GMP-AMP synthase-stimulator of interferon genes pathways, as well as the release of various cytokines in innate immune reactions. Moreover, neddylation also governs the function and survival of antigen-presenting cells, which are crucial for initiating adaptive immune reactions. In addition, neddylation regulates T cell activation, proliferation, differentiation, survival, and their effector functions, thereby ensuring an appropriate adaptive immune response. In this review, we summarize the most recent findings in these aspects and delve into the connection between dysregulated neddylation events and immunological disorders, especially inflammatory diseases. Lastly, we propose future directions and potential treatments for these diseases by targeting neddylation.

Identification of an antigen-presenting cells/T/NK cells-related gene signature to predict prognosis and CTSL to predict immunotherapeutic response for lung adenocarcinoma: an integrated analysis of bulk and single-cell RNA sequencing

BACKGROUND

Antigen-presenting cells (APC)/T/NK cells are key immune cells that play crucial roles in fighting against malignancies including lung adenocarcinoma (LUAD). In this study, we aimed to identify an APC/T/NK cells-related gene signature (ATNKGS) and potential immune cell-related genes (IRGs) to realize risk stratification, prognosis, and immunotherapeutic response prediction for LUAD patients.

METHODS

Based on the univariate Cox regression and the LASSO Cox regression results of 196 APC/T/NK cells-related genes collected from three pathways in the KEGG database, we determined the final genes and established the ATNKGS-related risk model. The single-cell RNA sequencing data were applied for key IRGs identification and investigate their value in immunotherapeutic response prediction. Several GEO datasets and an external immunotherapy cohort from Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, were applied for validation.

RESULTS

In this study, nine independent public datasets including 1108 patients were enrolled. An ATNKGS containing 16 genes for predicting overall survival of LUAD patients was constructed with robust prognostic capability. The ATNKGS high risk group was related to significantly worse OS outcomes than those in the low-risk group, which were verified in TCGA and four GEO datatsets. A nomogram combining the ATNKGS risk score with clinical TNM stage achieved the optimal prediction performance. The single-cell RNA sequencing analysis revealed CTSL as an IRG of macrophage and monocyte. Moreover, though CTSL was an indicator for poor prognosis of LUAD patients, CTSL high expression group was associated with higher ESTIMATEScore, immune checkpoints expression, and lower TIDE score. Several immunotherapeutic cohorts have confirmed the response-predicting significance of CTSL in patients receiving immune checkpoint inhibitor (ICI) treatment.

CONCLUSIONS

Our study provided an insight into the significant role of APC/T/NK cells-related genes in survival risk stratification and CTSL in response prediction of immunotherapy in patients with LUAD.

Clinical Applications of Combined Immunotherapy Approaches in Gastrointestinal Cancer: A Case-Based Review

Malignant neoplasms arising from the gastrointestinal (GI) tract are among the most common types of cancer with high mortality rates. Despite advances in treatment in a small subgroup harboring targetable mutations, the outcome remains poor, accounting for one in three cancer-related deaths observed globally. As a promising therapeutic option in various tumor types, immunotherapy with immune checkpoint inhibitors has also been evaluated in GI cancer, albeit with limited efficacy except for a small subgroup expressing microsatellite instability. In the quest for more effective treatment options, energetic efforts have been placed to evaluate the role of several immunotherapy approaches comprising of cancer vaccines, adoptive cell therapies and immune checkpoint inhibitors. In this review, we report our experience with a personalized dendritic cell cancer vaccine and cytokine-induced killer cell therapy in three patients with GI cancers and summarize current clinical data on combined immunotherapy strategies.

Design of Cytotoxic T Cell Epitopes by Machine Learning of Human Degrons

Antigen processing is critical for producing epitope peptides that are presented by HLA molecules for T cell recognition. Therapeutic vaccines aim to harness these epitopes for priming cytotoxic T cell responses against cancer and pathogens, but insufficient processing often reduces vaccine efficacy through limiting the quantity of epitopes released. Here, we set out to improve antigen processing by harnessing protein degradation signals called degrons from the ubiquitin-proteasome system. We used machine learning to generate a computational model that ascribes a proteasomal degradation score between 0 and 100. Epitope peptides with varying degron activities were synthesized and translocated into cells using nontoxic anthrax proteins: protective antigen (PA) and the N-terminus of lethal factor (LFN). Immunogenicity studies revealed epitope sequences with a low score (<25) show pronounced T-cell activation but epitope sequences with a higher score (>75) provide limited activation. This work sheds light on the sequence-activity relationships between proteasomal degradation and epitope immunogenicity, through conserving the epitope region but varying the flanking sequence. We anticipate that future efforts to incorporate proteasomal degradation signals into vaccine designs will lead to enhanced cytotoxic T cell priming by vaccine therapeutics in clinical settings.

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.

Identification of Colon Immune Cell Marker Genes Using Machine Learning Methods

Immune cell infiltration that occurs at the site of colon tumors influences the course of cancer. Different immune cell compositions in the microenvironment lead to different immune responses and different therapeutic effects. This study analyzed single-cell RNA sequencing data in a normal colon with the aim of screening genetic markers of 25 candidate immune cell types and revealing quantitative differences between them. The dataset contains 25 classes of immune cells, 41,650 cells in total, and each cell is expressed by 22,164 genes at the expression level. They were fed into a machine learning-based stream. The five feature ranking algorithms (last absolute shrinkage and selection operator, light gradient boosting machine, Monte Carlo feature selection, minimum redundancy maximum relevance, and random forest) were first used to analyze the importance of gene features, yielding five feature lists. Then, incremental feature selection and two classification algorithms (decision tree and random forest) were combined to filter the most important genetic markers from each list. For different immune cell subtypes, their marker genes, such as KLRB1 in CD4 T cells, RPL30 in B cell IGA plasma cells, and JCHAIN in IgG producing B cells, were identified. They were confirmed to be differentially expressed in different immune cells and involved in immune processes. In addition, quantitative rules were summarized by using the decision tree algorithm to distinguish candidate immune cell types. These results provide a reference for exploring the cell composition of the colon cancer microenvironment and for clinical immunotherapy.

Antigen presentation in cancer - mechanisms and clinical implications for immunotherapy

Over the past decade, the emergence of effective immunotherapies has revolutionized the clinical management of many types of cancers. However, long-term durable tumour control is only achieved in a fraction of patients who receive these therapies. Understanding the mechanisms underlying clinical response and resistance to treatment is therefore essential to expanding the level of clinical benefit obtained from immunotherapies. In this Review, we describe the molecular mechanisms of antigen processing and presentation in tumours and their clinical consequences. We examine how various aspects of the antigen-presentation machinery (APM) shape tumour immunity. In particular, we discuss genomic variants in HLA alleles and other APM components, highlighting their influence on the immunopeptidomes of both malignant cells and immune cells. Understanding the APM, how it is regulated and how it changes in tumour cells is crucial for determining which patients will respond to immunotherapy and why some patients develop resistance. We focus on recently discovered molecular and genomic alterations that drive the clinical outcomes of patients receiving immune-checkpoint inhibitors. An improved understanding of how these variables mediate tumour-immune interactions is expected to guide the more precise administration of immunotherapies and reveal potentially promising directions for the development of new immunotherapeutic approaches.

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.

Cancer immune escape: the role of antigen presentation machinery

The mechanisms of antigen processing and presentation play a crucial role in the recognition and targeting of cancer cells by the immune system. Cancer cells can evade the immune system by downregulating or losing the expression of the proteins recognized by the immune cells as antigens, creating an immunosuppressive microenvironment, and altering their ability to process and present antigens. This review focuses on the mechanisms of cancer immune evasion with a specific emphasis on the role of antigen presentation machinery. The study of the immunopeptidome, or peptidomics, has provided insights into the mechanisms of cancer immune evasion and has potential applications in cancer diagnosis and treatment. Additionally, manipulating the epigenetic landscape of cancer cells plays a critical role in suppressing the immune response against cancer. Targeting these mechanisms through the use of HDACis, DNMTis, and combination therapies has the potential to improve the efficacy of cancer immunotherapy. However, further research is needed to fully understand the mechanisms of action and optimal use of these therapies in the clinical setting.

β2-microglobulin and colorectal cancer among inpatients: a case-control study

Β2-microglobulin (β2-M) is associated with various malignancies. However, the relationship between β2-M and colorectal cancer (CRC) remains unclear. We explored the association between β2-M and CRC among inpatients who underwent colonoscopy and explored factors that may modify the association. All consecutive inpatients who underwent colonoscopy were enrolled in a tertiary hospital between April 2015 and June 2022. Inpatients with initial CRC or normal colonoscopies were considered eligible as cases or controls, respectively. Baseline characteristics and laboratory indicators of the participants were collected from electronic medical records. Logistic regression analysis, smooth curve fitting, sensitivity analysis, and subgroup analysis were conducted in the present study. After adjusting for baseline clinical characteristics and laboratory parameters, β2-M was positively associated with CRC (odds ratio [OR] 1.32; 95% confidence interval [CI] 1.11-1.58) among inpatients. When the β2-M level was assigned as tertiles, participants in the highest tertile presented with a higher risk of CRC (OR 2.33; 95% CI 1.57-3.48). A positive linear association was observed between β2-M and CRC with smooth curve fitting. In particular, it may be of great importance to monitor β2-M levels for predicting CRC patients.

Multiplexed Immunofluorescence Imaging Reveals an Immune-Rich Tumor Microenvironment in Mucinous Rectal Cancer Characterized by Increased Lymphocyte Infiltration and Enhanced Programmed Cell Death Protein 1 Expression

BACKGROUND

Mucinous rectal cancer is associated with a higher incidence of microsatellite instability and a poorer response to neoadjuvant chemoradiotherapy compared to other subtypes of rectal adenocarcinoma. Immune checkpoint inhibitors are an emerging family of anticancer therapeutics associated with highly variable outcomes in colorectal cancer. Although the immune landscape of mucinous rectal cancer has not been fully explored, the presence of mucin is thought to act as a barrier preventing immune-cell infiltration.

OBJECTIVE

The aim of this study was to determine the immune properties of mucinous rectal cancer and investigate the degree of lymphocyte infiltration in this cohort.

DESIGN

This is a retrospective cohort study that involved multiplexed immunofluorescence staining of tumor microarrays.

SETTINGS

Samples originated from a single university teaching hospital.

PATIENTS

Our cohort included 15 cases of mucinous and 43 cases of nonmucinous rectal cancer.

MAIN OUTCOME MEASURES

Immune cells were classified and quantified. Immune-cell counts were compared between mucinous and nonmucinous cohorts. Immune marker expression within tumor epithelial tissue was evaluated to determine the degree of lymphocyte infiltration.

RESULTS

Cytotoxic ( p = 0.022) and regulatory T cells ( p = 0.010) were found to be overrepresented in the mucinous cohort compared to the nonmucinous group. Programmed cell death protein 1 expression was also found to be significantly greater in the mucinous group ( p = 0.001). CD3 ( p = 0.001) and CD8 ( p = 0.054) expressions within the tumor epithelium were also higher in the mucinous group, suggesting adequate immune infiltration despite the presence of mucin. In our analysis, microsatellite instability status was not a predictor of immune marker expression.

LIMITATIONS

The relatively small size of the cohort.

CONCLUSIONS

Mucinous rectal cancer is associated with an immune-rich tumor microenvironment, which was not associated with microsatellite instability status. See Video Abstract at http://links.lww.com/DCR/C65 .

IMGENES DE INMUNOFLUORESCENCIA MULTIPLEXADAS REVELAN UN MICROAMBIENTE TUMORAL RICO EN INMUNIDAD EN EL CNCER RECTAL MUCINOSO CARACTERIZADO POR UNA MAYOR INFILTRACIN DE LINFOCITOS Y UNA EXPRESIN MEJORADA DE PD

ANTECEDENTES:El cáncer rectal mucinoso se asocia con una mayor incidencia de inestabilidad de microsatélites y una peor respuesta a la quimiorradioterapia neoadyuvante en comparación con otros subtipos de adenocarcinoma rectal. Los inhibidores de puntos de control inmunitarios son una familia emergente de tratamientos contra el cáncer asociados con resultados muy variables en el cáncer colorrectal. Aunque el panorama inmunitario del cáncer rectal mucinoso no se ha explorado completamente, se cree que la presencia de mucina actúa como una barrera que previene la infiltración de células inmunitarias.OBJETIVO:El objetivo de este estudio fue determinar las propiedades inmunes del cáncer de recto mucinoso e investigar el grado de infiltración de linfocitos en esta cohorte.DISEÑO:Este es un estudio de cohorte retrospectivo que involucró la tinción de inmunofluorescencia multiplexada de micromatrices tumorales.AJUSTES:Las muestras se originaron en un solo hospital docente universitario.PACIENTES:Nuestra cohorte incluyó 15 casos de cáncer de recto mucinoso y 43 casos de cáncer de recto no mucinosoPRINCIPALES MEDIDAS DE RESULTADO:Las células inmunitarias se clasificaron y cuantificaron. Se compararon los recuentos de células inmunitarias entre cohortes mucinosas y no mucinosas. Se evaluó la expresión del marcador inmunitario dentro del tejido epitelial tumoral para determinar el grado de infiltración de linfocitos.RESULTADOS:Se encontró que las células T citotóxicas ( p = 0,022) y reguladoras ( p = 0,010) estaban sobrerrepresentadas en la cohorte mucinosa en comparación con el grupo no mucinoso. También se encontró que la expresión de PD-1 era significativamente mayor en el grupo mucinoso ( p = 0,001). La expresión de CD3 ( p = 0,001) y CD8 ( p = 0,054) dentro del epitelio tumoral también fue mayor en el grupo mucinoso, lo que sugiere una infiltración inmunitaria adecuada a pesar de la presencia de mucina. En nuestro análisis, no se encontró que el estado de inestabilidad de los microsatélites sea un predictor de la expresión del marcador inmunitario.LIMITACIONES:El tamaño relativamente pequeño de la cohorte.CONCLUSIONES:El cáncer rectal mucinoso se asocia con un microambiente tumoral rico en inmunidad, que no se asoció con el estado de inestabilidad de microsatélites. Consulte el Video del Resumen en http://links.lww.com/DCR/C65 . (Traducción- Dr. Yesenia Rojas-Khalil ).

A novel glycolysis-related gene signature for predicting the prognosis of multiple myeloma

Background: Metabolic reprogramming is an important hallmark of cancer. Glycolysis provides the conditions on which multiple myeloma (MM) thrives. Due to MM's great heterogeneity and incurability, risk assessment and treatment choices are still difficult. Method: We constructed a glycolysis-related prognostic model by Least absolute shrinkage and selection operator (LASSO) Cox regression analysis. It was validated in two independent external cohorts, cell lines, and our clinical specimens. The model was also explored for its biological properties, immune microenvironment, and therapeutic response including immunotherapy. Finally, multiple metrics were combined to construct a nomogram to assist in personalized prediction of survival outcomes. Results: A wide range of variants and heterogeneous expression profiles of glycolysis-related genes were observed in MM. The prognostic model behaved well in differentiating between populations with various prognoses and proved to be an independent prognostic factor. This prognostic signature closely coordinated with multiple malignant features such as high-risk clinical features, immune dysfunction, stem cell-like features, cancer-related pathways, which was associated with the survival outcomes of MM. In terms of treatment, the high-risk group showed resistance to conventional drugs such as bortezomib, doxorubicin and immunotherapy. The joint scores generated by the nomogram showed higher clinical benefit than other clinical indicators. The in vitro experiments with cell lines and clinical subjects further provided convincing evidence for our study. Conclusion: We developed and validated the utility of the MM glycolysis-related prognostic model, which provides a new direction for prognosis assessment, treatment options for MM patients.

Artificial intelligence-assisted selection and efficacy prediction of antineoplastic strategies for precision cancer therapy

The rapid development of artificial intelligence (AI) technologies in the context of the vast amount of collectable data obtained from high-throughput sequencing has led to an unprecedented understanding of cancer and accelerated the advent of a new era of clinical oncology with a tone of precision treatment and personalized medicine. However, the gains achieved by a variety of AI models in clinical oncology practice are far from what one would expect, and in particular, there are still many uncertainties in the selection of clinical treatment options that pose significant challenges to the application of AI in clinical oncology. In this review, we summarize emerging approaches, relevant datasets and open-source software of AI and show how to integrate them to address problems from clinical oncology and cancer research. We focus on the principles and procedures for identifying different antitumor strategies with the assistance of AI, including targeted cancer therapy, conventional cancer therapy, and cancer immunotherapy. In addition, we also highlight the current challenges and directions of AI in clinical oncology translation. Overall, we hope this article will provide researchers and clinicians with a deeper understanding of the role and implications of AI in precision cancer therapy, and help AI move more quickly into accepted cancer guidelines.

Cancer Immunology: Immune Escape of Tumors-Expression and Regulation of HLA Class I Molecules and Its Role in Immunotherapies

The addition of "avoiding immune destruction" to the hallmarks of cancer demonstrated the importance of cancer immunology and in particular the role of immune surveillance and escape from malignancies. However, the underlying mechanisms contributing to immune impairment and immune responses are diverse. Loss or reduced expression of the HLA class I molecules are major characteristics of human cancers resulting in an impaired recognition of tumor cells by CD8 + cytotoxic T lymphocytes. This is of clinical relevance and associated with worse patients outcome and limited efficacy of T-cell-based immunotherapies. Here, we summarize the role of HLA class I antigens in cancers by focusing on the underlying molecular mechanisms responsible for HLA class I defects, which are caused by either structural alterations or deregulation at the transcriptional, posttranscriptional, and posttranslational levels. In addition, the influence of HLA class I abnormalities to adaptive and acquired immunotherapy resistances will be described. The in-depth knowledge of the different strategies of malignancies leading to HLA class I defects can be applied to design more effective cancer immunotherapies.

Integrated multi-omics approach to distinct molecular characterization and classification of early-onset colorectal cancer

Incidence of early-onset colorectal cancer (EOCRC), defined by a diagnosed age under 50 years, is increasing, but its heterogeneous etiologies that differ from general CRC remain undetermined. We initially characterize the genome, epigenome, transcriptome, and proteome of tumors from 79 patients in a Chinese CRC cohort. Data for an additional 126 EOCRC subjects are obtained from the International Cancer Genome Consortium Chinese cohort and The Cancer Genome Atlas European cohort. We observe that early-onset tumors have a high tumor mutation burden; increased DNA repair features by mutational signature 3 and multi-layer pathway enrichments; strong perturbations at effects of DNA methylation and somatic copy-number alteration on gene expression; and upregulated immune infiltration as hot tumors underlying immunophenotypes. Notably, LMTK3 exhibits ancestral mutation disparity, potentially being a functional modulator and biomarker that drives molecular alterations in EOCRC development and immunotherapies. This integrative omics study provides valuable knowledge for precision oncology of CRC.

CTLs, NK cells and NK-derived EVs against breast cancer

Patients with advanced stage breast cancer need novel therapies. New potential treatments have been developed, such as adoptive cellular therapies and alternative cell-free immunotherapies. The goal of this study was to assess the cytotoxicity of three of the patient-derived immune components, CTLs, NK cells and NK-derived EVs, and evaluate the potential for the development of novel therapy against breast cancer. CTLs were activated against MUC-1 antigen. The in vitro cytotoxic activity of three components was assessed with flow cytometry and in vivo study revealed the efficacy of adoptive cell therapy. Overall, CTLs exhibited the highest cytotoxicity against spheroids of MCF7 breast adenocarcinoma, reaching in all cases higher than double the percentage of NK cells' cytotoxicity. NK-derived EVs exhibited the lowest effect against MCF7 spheroids comparing to the two cell populations. MUC-1 specific CTLs were evaluated with adoptive cell therapy mice study and appeared to be well tolerable and moderately efficacious. More studies need to be performed with CTLs to evaluate safety and efficacy in order to assess their clinical potential, while NK cells and NK-derived EVs are promising candidates that require more experiments to enhance their cytotoxicity.

Next-generation antigen-presenting cell immune therapeutics for gliomas

Antigen presentation machinery and professional antigen-presenting cells (APCs) are fundamental for an efficacious immune response against cancers, especially in the context of T cell-centric immunotherapy. Dendritic cells (DCs), the gold standard APCs, play a crucial role in initiating and maintaining a productive antigen-specific adaptive immunity. In recent decades, ex vivo-differentiated DCs from circulating CD14+ monocytes have become the reference for APC-based immunotherapy. DCs loaded with tumor-associated antigens, synthetic peptides, or RNA activate T cells with antitumor properties. This strategy has paved the way for the development of alternative antigen-presenting vaccination strategies, such as monocytes, B cells, and artificial APCs, that have shown effective therapeutic outcomes in preclinical cancer models. The search for alternative APC platforms was initiated by the overall limited clinical impact of DC vaccines, especially in indications such as gliomas, a primary brain tumor known for resistance to any immune intervention. In this Review, we navigate the APC immune therapeutics' past, present, and future in the context of primary brain tumors.

Human γδ T cells induce CD8+ T cell antitumor responses via antigen-presenting effect through HSP90-MyD88-mediated activation of JNK

Human Vγ9Vδ2 T cells have attracted considerable attention as novel alternative antigen-presenting cells (APCs) with the potential to replace dendritic cells in antitumor immunotherapy owing to their high proliferative capacity and low cost. However, the utility of γδ T cells as APCs to induce CD8⁺ T cell-mediated antitumor immune response, as well as the mechanism by which they perform APC functions, remains unexplored. In this study, we found that activated Vγ9Vδ2 T cells were capable of inducing robust CD8⁺ T cell responses in osteosarcoma cells. Activated γδ T cells also effectively suppressed osteosarcoma growth by priming CD8⁺ T cells in xenograft animal models. Mechanistically, we further revealed that activated γδ T cells exhibited increased HSP90 production, which fed back to upregulate MyD88, followed by JNK activation and a subsequent improvement in CCL5 secretion, leading to enhanced CD8⁺ T cell cross-priming. Thus, our study suggests that Vγ9Vδ2 T cells represent a promising alternative APC for the development of γδ T cell-based tumor immunotherapy.

Neoantigens: promising targets for cancer therapy

Recent advances in neoantigen research have accelerated the development and regulatory approval of tumor immunotherapies, including cancer vaccines, adoptive cell therapy and antibody-based therapies, especially for solid tumors. Neoantigens are newly formed antigens generated by tumor cells as a result of various tumor-specific alterations, such as genomic mutation, dysregulated RNA splicing, disordered post-translational modification, and integrated viral open reading frames. Neoantigens are recognized as non-self and trigger an immune response that is not subject to central and peripheral tolerance. The quick identification and prediction of tumor-specific neoantigens have been made possible by the advanced development of next-generation sequencing and bioinformatic technologies. Compared to tumor-associated antigens, the highly immunogenic and tumor-specific neoantigens provide emerging targets for personalized cancer immunotherapies, and serve as prospective predictors for tumor survival prognosis and immune checkpoint blockade responses. The development of cancer therapies will be aided by understanding the mechanism underlying neoantigen-induced anti-tumor immune response and by streamlining the process of neoantigen-based immunotherapies. This review provides an overview on the identification and characterization of neoantigens and outlines the clinical applications of prospective immunotherapeutic strategies based on neoantigens. We also explore their current status, inherent challenges, and clinical translation potential.

An original cuproptosis-related genes signature effectively influences the prognosis and immune status of head and neck squamous cell carcinoma

Background: Recently, a non-apoptotic cell death pathway that is dependent on the presence of copper ions was proposed, named as cuproptosis. Cuproptosis have been found to have a strong association with the clinical progression and prognosis of several cancers. Head and neck squamous cell carcinoma (HNSC) are among the most common malignant tumors, with a 5-year relative survival rate ranging between 40% and 50%. The underlying mechanisms and clinical significance of cuproptosis-related genes (CRGs) in HNSC progression have not been clarified. Methods: In this study, expression pattern, biological functions, Immunohistochemistry (IHC), gene variants and immune status were analyzed to investigate the effects of CRGs on HNSC progression. Moreover, a 12-CRGs signature and nomogram were also constructed for prognosis prediction of HNSC. Results: The results revealed that some CRGs were dysregulated, had somatic mutations, and CNV in HNSC tissues. Among them, ISCA2 was found to be upregulated in HNSC and was strongly correlated with the overall survival (OS) of HNSC patients (HR = 1.13 [1.01-1.26], p-value = 0.0331). Functionally, CRGs was mainly associated with the TCA cycle, cell cycle, iron-sulfur cluster assembly, p53 signaling pathway, chemical carcinogenesis, and carbon metabolism in cancer. A 12-CRGs signature for predicting the OS was constructed which included, CAT, MTFR1L, OXA1L, POLE, NTHL1, DNA2, ATP7B, ISCA2, GLRX5, NDUFA1, and NDUFB2. This signature showed good prediction performance on the OS (HR = 5.3 [3.4-8.2], p-value = 3.4e-13) and disease-specific survival (HR = 6.4 [3.6-11], p-value = 2.4e-10). Furthermore, 12-CRGs signature significantly suppressed the activation of CD4⁺ T cells and antigen processing and presentation. Finally, a nomogram based on a 12-CRGs signature and clinical features was constructed which showed a significantly adverse effect on OS (HR = 1.061 [1.042-1.081], p-value = 1.6e-10) of HNSC patients. Conclusion: This study reveals the association of CRGs with the progression of HNSC based on multi-omics analysis. The study of CRGs is expected to improve clinical diagnosis, immunotherapeutic responsiveness and prognosis prediction of HNSC.

Pan-cancer analysis of ASB3 and the potential clinical implications for immune microenvironment of glioblastoma multiforme

Background

Ankyrin repeat and SOCS Box containing 3 (ASB3) is an E3 ubiquitin ligase. It has been reported to regulate the progression of some cancers, but no systematic pan-cancer analysis has been conducted to explore its function in prognosis and immune microenvironment.

Method

In this study, mRNA expression data were downloaded from TCGA and GTEx database. Next generation sequencing data from 14 glioblastoma multiforme (GBM) samples by neurosurgical resection were used as validation dataset. Multiple bioinformatics methods (ssGSEA, Kaplan-Meier, Cox regression analysis, GSEA and online tools) were applied to explore ASB3 expression, gene activity, prognosis of patients in various cancers, and its correlation with clinical information, immune microenvironment and pertinent signal pathways in GBM. The biological function of ASB3 in tumor-infiltrating lymphocytes (TILs) was verified using an animal model.

Results

We found that ASB3 was aberrant expressed in a variety of tumors, especially in GBM, and significantly correlated with the prognosis of cancer patients. The level of ASB3 was related to the TMB, MSI and immune cell infiltration in some cancer types. ASB3 had a negative association with immune infiltration and TME, including regulatory T cells (Tregs), cancer-associated fibroblasts, immunosuppressors and related signaling pathways in GBM. ASB3 overexpression reduced the proportion of Tregs in TILs. GSEA and PPI analysis also showed negative correlation between ASB3 expression and oncogenetic signaling pathways in GBM.

Conclusion

A comprehensive pan-cancer analysis of ASB3 showed its potential function as a biomarker of cancer prognosis and effective prediction of immunotherapy response. This study not only enriches the understanding of the biological function of ASB3 in pan-cancer, especially in GBM immunity, but also provides a new reference for the personalized immunotherapy of GBM.

KLF15 suppresses tumor growth and metastasis in Triple-Negative Breast Cancer by downregulating CCL2 and CCL7

Kruppel like factor 15 (KLF15), a transcriptional factor belonging to the Kruppel-like factor (KLF) family of genes, has recently been reported as a tumor suppressor gene in breast cancer. However, the specific mechanisms by which KLF15 inhibits BrCa have not been elucidated. Here we investigated the role and mechanism of KLF15 in triple-negative breast cancer (TNBC). KLF15 expression and methylation were detected by RT-qPCR, RT-PCR and methylation-specific PCR in breast cancer cell lines and tissues. The effects of KLF15 on TNBC cell functions were examined via various cellular function assays. The specific anti-tumor mechanisms of KLF15 were further investigated by RNA sequence, RT-qPCR, Western blotting, luciferase assay, ChIP, and bioinformatics analysis. As the results showed that KLF15 is significantly downregulated in breast cancer cell lines and tissues, which promoter methylation of KLF15 partially contributes to. Exogenous expression of KLF15 induced apoptosis and G2/M phase cell cycle arrest, suppressed cell proliferation, metastasis and in vivo tumorigenesis of TNBC cells. Mechanism studies revealed that KLF15 targeted and downregulated C-C motif chemokine ligand 2 (CCL2) and CCL7. Moreover, transcriptome and metabolome analysis revealed that KLF15 is involved in key anti-tumor regulatory and metabolic pathways in TNBC. In conclusion, KLF15 suppresses cell growth and metastasis in TNBC by downregulating CCL2 and CCL7. KLF15 may be a prognostic biomarker in TNBC.

Single-Cell Sequencing Analysis Identified ASTN2 as a Migration Biomarker in Adult Glioblastoma

Glioblastoma is the most common and aggressive primary central nervous system malignant tumors. With the development of targeted sequencing and proteomic profiling technology, some new tumor types have been established and a series of novel molecular markers have also been identified. The 2021 updated World Health Organization classification of central nervous system tumors first mentioned the classification of adult glioma and pediatric glioma based on the molecular diagnosis. Thus, we used single-cell RNA sequencing analysis to explore the diversity and similarities in the occurrence and development of adult and pediatric types. ASTN2, which primarily encodes astrotactin, has been reported to be dysregulated in various neurodevelopmental disorders. Although some studies have demonstrated that ASTN2 plays an important role in glial-guided neuronal migration, there are no studies about its impact on glioblastoma cell migration. Subsequent single-cell RNA sequencing revealed ASTN2 to be a hub gene of a cell cluster which had a poor effect on clinical prognosis. Eventually, a western blot assay and a wound-healing assay first confirmed that ASTN2 expression in glioblastoma cell lines is higher than that in normal human astrocytes and affects the migration ability of glioblastoma cells, making it a potential therapeutic target.

Comprehensive analysis of the immune implication of FABP4 in colon adenocarcinoma

Background

Fatty acid-binding protein 4 (FABP4) has been reported to be associated with tumor progress and poor prognosis in various cancers. However, the relationship between FABP4 expression and tumor immunity in colon adenocarcinoma (COAD) is still poorly understood.

Methods

FABP4 mRNA expression was analyzed using The Cancer Genome Atlas (TCGA)-COAD data. FABP4 protein staining was performed by immunohistochemistry (IHC) staining in our 10 paired COAD samples and corresponding adjacent noncancerous tissues. The association between FABP4 and immune cell infiltration was evaluated by Tumor Immune Estimation Resource (TIMER) database. FABP4 coexpressed genes were identified based on Cancer Cell Line Encyclopedia (CCLE) database, which were employed for further enrichment analysis. FABP4 related immunomodulators was identified by Tumor and Immune System Interaction Database (TISIDB) database, and a prognostic risk signature was constructed based on FABP4-related immunomodulators using stepwise Cox regression analysis. A nomogram consists of FABP4 related immunomodulators signature and clinical parameters was developed to predict the overall survival (OS).

Results

In TCGA data, we found that the decreased FABP4 mRNA expression in COAD samples compared with normal samples, and low FABP4 mRNA expression was associated with B cells, CD4+ T cells, CD8+ T cells, myeloid dendritic cells, macrophages, and neutrophils. In our 10 paired samples, the protein levels of COAD were lower in all COAD tissues than in their adjacent noncancerous tissues. Functional enrichment analysis revealed that FABP4 coexpressed genes were mostly enriched in immune-related pathways. Based on 54 FABP4-related immunomodulators, a 2-gene FABP4-related prognostic risk signature was developed, and the signature stratified the patients into the high-risk and low-risk groups with statistically different survival outcomes. The Nomogram consists of the prognostic signature and clinical parameters had a certain predictability for prognosis of COAD patients.

Conclusion

These findings suggest that FABP4 is associated with 2-gene immune signature which also correlate with the prognosis of COAD patients.

Comprehensive Analysis of the Immune Implication of AKAP12 in Stomach Adenocarcinoma

A kinase anchor protein 12 (AKAP12) as a tumor suppressor in various cancers has been extensively studied and confirmed. However, its immune implication in stomach adenocarcinoma (STAD) remains uncertain. Here, using The Cancer Genome Atlas (TCGA), Human Protein Atlas (HPA), Tumor Immune Estimation Resource (TIMER), Cancer Cell Line Encyclopedia (CCLE), integrated repository portal for tumor-immune system interactions (TISIDB), and Search Tool for the Retrieval of Interaction Gene/Proteins (STRING) database, we systematically analyzed the immune correlation of AKAP12 from three aspects including immune infiltration cells, immune-related pathways, and immunomodulators and developed a AKAP12-related 4-gene signature for prognosis prediction. Our results showed that AKAP12 mRNA and protein levels were downregulated in STAD patients, and its expression was positively related to CD4+ T cells and macrophages. In addition, the immune cell infiltration levels were associated with AKAP12 gene copy number deletion in STAD. Based on CCLE database, we found that AKAP12 coexpressed genes were enriched in several immune- and cancer-related pathways, which was further validated by Gene Set Enrichment Analysis (GSEA). Moreover, we identified 46 immunomodulators that were significantly related to AKAP12 expression using TISIDB database, and these immunomodulators were involved in immune-related pathways including Th17 cell differentiation and natural killer cell-mediated cytotoxicity. Additionally, based on the 46 AKAP12-related immunomodulators, a 4-gene risk prediction signature was developed using the Cox regression model. The risk signature was identified as an independent prognostic factor, which can accurately predict the prognosis of patients with STAD, showing good predictive performance. Furthermore, we constructed a prognostic nomogram and calibration to predict and assess patient survival probabilities by integrating the risk score and other clinical factors. In conclusion, our study provides strong evidence that AKAP12 is closely related to tumor immunity in STAD from three aspects: immune infiltration cells, immune pathways, and immunomodulators. More importantly, the AKAP12-related prognostic signature may have a good application prospect for clinical practice.

A synthetic DNA template for fast manufacturing of versatile single epitope mRNA

A flexible, affordable, and rapid vaccine platform is necessary to unlock the potential of personalized cancer vaccines in order to achieve full clinical efficiency. mRNA cancer vaccine manufacture relies on the rigid sequence design of multiepitope constructs produced by laborious bacterial cloning and time-consuming plasmid preparation. Here, we introduce a synthetic DNA template (SDT) assembly process, which allows cost- and time-efficient manufacturing of single (neo)epitope mRNA. We benchmarked SDT-derived mRNA against mRNA derived from a plasmid DNA template (PDT), showing that monocyte-derived dendritic cells (moDCs) electroporated with SDT-mRNA or PDT-mRNA, encoding HLA-I- or HLA-II-restricted (neo)epitopes, equally activated T cells that were modified to express the cognate T cell receptors. Furthermore, we validated the SDT-mRNA platform for neoepitope immunogenicity screening using the characterized HLA-A2-restricted neoepitope DHX40B and four new candidate HLA-A2-restricted melanoma neoepitopes. Finally, we compared SDT-mRNA with PDT-mRNA for vaccine development purposes. moDCs electroporated with mRNA encoding the HLA-A2-restricted, mutated Melan-A/Mart-1 epitope together with TriMix mRNA-generated high levels of functional Melan-A/Mart-1-specific CD8⁺ T cells. In conclusion, SDT single epitope mRNA can be manufactured in a more flexible, cost-efficient, and time-efficient way compared with PDT-mRNA, allowing prompt neoepitope immunogenicity screening, and might be exploited for the development of personalized cancer vaccines.

Construction of a novel necroptosis-related lncRNA signature for prognosis prediction in esophageal cancer

Background

Esophageal cancer (EC), one highly malignant gastrointestinal cancer, is the 6th leading cause of cancer-related deaths worldwide. Necroptosis and long non-coding RNA (lncRNA) play important roles in the occurrence and development of EC, but the research on the role of necroptosis-related lncRNA in EC is not conclusive. This study aims to use bioinformatics to investigate the prognostic value of necroptosis-related lncRNA in EC.

Methods

Transcriptome data containing EC and normal samples, and clinical information were obtained from the Cancer Genome Atlas database. 102 necroptosis-related genes were obtained from Kanehisa Laboratories. Necroptosis-related lncRNAs were screened out via univariate, multivariate Cox and the least absolute shrinkage and selection operator regression analyses to construct the risk predictive model. The reliability of the risk model was evaluated mainly through quantitative real-time PCR (qRT-PCR), the receiver operating characteristic (ROC) curves and the constructed nomogram. KEGG pathways were explored in the high- and low-risk groups of EC patients via gene set enrichment analyses (GSEA) software. Immune microenvironment and potential therapeutic agents in risk groups were also analyzed.

Results

A 6 necroptosis-related lncRNAs risk model composed of AC022211.2, Z94721.1, AC007991.2, SAMD12-AS1, AL035461.2 and AC051619.4 was established to predict the prognosis level of EC patients. qRT-PCR analysis showed upregulated Z94721.1 and AL035461.2 mRNA levels and downregulated AC051619.4 mRNA level in EC tissues compared with normal tissues. According to clinical characteristics, the patients in the high-risk group had a shorter overall survival than the low-risk group. The ROC curve and nomogram confirmed this model as one independent and predominant predictor. GSEA analysis showed metabolic and immune-related pathways enriched in the risk model. Most of the immune cells and immune checkpoints were positively correlated with the risk model, mainly active in the high-risk group. For the prediction of potential therapeutic drugs, 16 compounds in the high-risk group and 2 compounds in the low-risk group exhibited higher sensitivity.

Conclusions

Our results supported the necroptosis-related lncRNA signature could independently predict prognosis of EC patients, and provided theoretical basis for improving the clinical treatment of EC.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12876-022-02421-8.

Promoting the formation of Pi-stacking interaction to improve CTL cells activation between modified peptide and HLA

OBJECTIVE

This study aims to investigate the use of single residue substitution to promote the formation of pi-stacking interactions between peptides and Human leukocyte antigen (HLA)-A*2402 molecules to improve the affinity of peptides and HLA molecules, as well as the level of cytotoxic T lymphocyte (CTL) cells activated by peptides-HLA (p-HLA) complex.

METHODS

Molecular docking and molecular dynamics simulation were used to simulate and analyze the interactions and binding free energies between HLA-A*2402-restricted antigen peptides and HLA molecules, before and after the single residue substitution. HLA-A*2402 restricted antigen peptides before and after the single residue replacement were loaded into dendritic cells (DCs) in vitro, and further Enzyme-Linked ImmunoSpot (ELispot) test was carried out to evaluate the effect of modified antigen peptides on the immune activation of CTL cells.

RESULT

After replacing the antigen peptides with a single residue, some of them could promote the formation of pi-stacking interaction. The binding free energy between the modified antigen peptides and HLA-A*2402, as well as the level of immune activation of CTL cells were mostly higher than before, especially after the replacement of the 9th residue of the polypeptide, such as C9F and C9W. There was a significant negative correlation between the level of activated CTL cells by modified antigen peptides and the total interaction amount of hydrogen bonds and salt bridges.

CONCLUSION

Promoting the formation of pi-stacking interaction between antigen peptides and HLA-A*2402 molecules could increase the total binding free energy of p-HLA complex and the level of CTL cells activation. In addition, the amount of hydrogen bonds and salt bridges between peptides and HLA could reduce the level of immune activation. All the characteristics above can improve the immunogenicities of the weak antigens.

Dendritic cells can prime anti-tumor CD8+ T cell responses through major histocompatibility complex cross-dressing

Antigen cross-presentation, wherein dendritic cells (DCs) present exogenous antigen on major histocompatibility class I (MHC-I) molecules, is considered the primary mechanism by which DCs initiate tumor-specific CD8+ T cell responses. Here, we demonstrate that MHC-I cross-dressing, an antigen presentation pathway in which DCs acquire and display intact tumor-derived peptide:MHC-I molecules, is also important in orchestrating anti-tumor immunity. Cancer cell MHC-I expression was required for optimal CD8+ T cell activation in two subcutaneous tumor models. In vivo acquisition of tumor-derived peptide:MHC-I molecules by DCs was sufficient to induce antigen-specific CD8+ T cell priming. Transfer of tumor-derived human leukocyte antigen (HLA) molecules to myeloid cells was detected in vitro and in human tumor xenografts. In conclusion, MHC-I cross-dressing is crucial for anti-tumor CD8+ T cell priming by DCs. In addition to quantitatively enhancing tumor antigen presentation, MHC cross-dressing might also enable DCs to more faithfully and efficiently mirror the cancer cell peptidome.

Adoptive Cellular Transfer Immunotherapies for Cancer

Patients with cancer require efficient treatment approaches as the mortality rate due to their disease is high. Conventional therapies, like chemotherapy and radiation, have severe side effects. Drug discovery is focusing on the development of alternative strategies that could have beneficial effects to the patients. Cellular therapies are potential therapeutics, and the generation of new products is growing fast. The concept involves the isolation of immune cells, ex vivo activation and reinfusion into the patient. The goal is to boost the immune cells to fight cancer cells. Different immune cells can be used, including dendritic cells, T cells, NK cells, macrophages and B lymphocytes. Some products have already gained FDA approval, while many more are currently in clinical trials. Research is focusing on the improvement of the function of the cells that may require genetic modification or combination with other therapies. Finally, it is crucial to develop novel technologies that could be used in monitoring of the immune profile of patients that have received a cellular therapy to assess the efficacy of the treatment.

A 16-gene signature associated with homologous recombination deficiency for prognosis prediction in patients with triple-negative breast cancer

Homologous recombination deficiency (HRD) commonly occurs in breast cancer, which is the second cause of cancer death in women with a high rate of relapse and poor outcomes. Triple-negative breast cancer (TNBC) is the most aggressive subtype of breast cancer. Thus, we aim to develop a prognostic signature based on HRD expecting to help improve outcomes in TNBC. The Cancer Genome Atlas (TCGA)–TNBC cohort was divided into the training set and the testing set randomly. Sixteen genes were filtered from the prognostic HRD-associated genes to establish a prognostic model in the training set. Patients were divided into high-risk and low-risk groups based on the median value of the risk score. Prognosis analysis showed that the high-risk group was associated with a worse prognosis in the training set, the testing set, the entire TCGA–TNBC cohort, and the METABRIC–TNBC cohort. The time-dependent receiver operating characteristic curve showed that our model had very good accuracy in the prediction of 1–5-year overall survival in the TCGA–TNBC cohort. Besides, a comparison of the area under curve value and C-index between our model and four published models showed that our model had the best predictive efficiency compared to other models. Subsequently, a nomogram was established. Finally, our finding also indicated that our model was associated with immunoregulation in TNBC and had the potential to be the target for TNBC treatment. Therefore, our findings not only provided a new strategy in the personalized prognosis management of TNBC but also offered new insight into precision treatment in TNBC.