Immunometabolism at the Nexus of Cancer Therapeutic Efficacy and Resistance

RNA modifications in cellular metabolism: implications for metabolism-targeted therapy and immunotherapy

Cellular metabolism is an intricate network satisfying bioenergetic and biosynthesis requirements of cells. Relevant studies have been constantly making inroads in our understanding of pathophysiology, and inspiring development of therapeutics. As a crucial component of epigenetics at post-transcription level, RNA modification significantly determines RNA fates, further affecting various biological processes and cellular phenotypes. To be noted, immunometabolism defines the metabolic alterations occur on immune cells in different stages and immunological contexts. In this review, we characterize the distribution features, modifying mechanisms and biological functions of 8 RNA modifications, including N6-methyladenosine (m6A), N6,2'-O-dimethyladenosine (m6Am), N1-methyladenosine (m1A), 5-methylcytosine (m5C), N4-acetylcytosine (ac4C), N7-methylguanosine (m7G), Pseudouridine (Ψ), adenosine-to-inosine (A-to-I) editing, which are relatively the most studied types. Then regulatory roles of these RNA modification on metabolism in diverse health and disease contexts are comprehensively described, categorized as glucose, lipid, amino acid, and mitochondrial metabolism. And we highlight the regulation of RNA modifications on immunometabolism, further influencing immune responses. Above all, we provide a thorough discussion about clinical implications of RNA modification in metabolism-targeted therapy and immunotherapy, progression of RNA modification-targeted agents, and its potential in RNA-targeted therapeutics. Eventually, we give legitimate perspectives for future researches in this field from methodological requirements, mechanistic insights, to therapeutic applications.

Advances in tumor immunomodulation based on nanodrug delivery systems

Immunotherapy is a therapeutic approach that employs immunological principles and techniques to enhance and amplify the body's immune response, thereby eradicating tumor cells. Immunotherapy has demonstrated effective antitumor effects on a variety of malignant tumors. However, when applied to humans, many immunotherapy drugs fail to target lesions with precision, leading to an array of adverse immune-related reactions that profoundly limit the clinical application of immunotherapy. Nanodrug delivery systems enable the precise delivery of immunotherapeutic drugs to targeted tissues or specific immune cells, enhancing the immune antitumor effect while reducing the number of adverse reactions. A nanodrug delivery system provides a feasible strategy for activating the antitumor immune response by the following mechanisms: 1) increased targeting and uptake of vaccines by DCs, which enhances the efficacy of the immune response; 2) increased tumor cell immunogenicity; 3) regulation of TAMs and other cells by, for example, regulating the polarization of TAMs and interfering with TAN formation, and ECM remodeling by CAFs; and 4) interference with tumor immune escape signaling pathways, namely, the PD-1/PD-L1, FGL1/LAG-3 and IDO signaling pathways. This paper reviews the progress of nanodrug delivery system research with respect to tumor immunotherapy based on tumor immunomodulation over the last few years, discussing the promising future of these delivery systems under this domain.

Tumor Metabolism-Rewriting Nanomedicines for Cancer Immunotherapy

Cancer immunotherapy has become an established therapeutic paradigm in oncologic therapy, but its therapeutic efficacy remains unsatisfactory in the majority of cancer patients. Accumulating evidence demonstrates that the metabolically hostile tumor microenvironment (TME), characterized by acidity, deprivation of oxygen and nutrients, and accumulation of immunosuppressive metabolites, promotes the dysfunction of tumor-infiltrating immune cells (TIICs) and thereby compromises the effectiveness of immunotherapy. This indicates the potential role of tumor metabolic intervention in the reinvigoration of antitumor immunity. With the merits of multiple drug codelivery, cell and organelle-specific targeting, controlled drug release, and multimodal therapy, tumor metabolism-rewriting nanomedicines have recently emerged as an attractive strategy to strengthen antitumor immune responses. This review summarizes the current progress in the development of multifunctional tumor metabolism-rewriting nanomedicines for evoking antitumor immunity. A special focus is placed on how these nanomedicines reinvigorate innate or adaptive antitumor immunity by regulating glucose metabolism, amino acid metabolism, lipid metabolism, and nucleotide metabolism at the tumor site. Finally, the prospects and challenges in this emerging field are discussed.

Genome-scale modeling predicts metabolic differences between macrophage subtypes in colorectal cancer

Colorectal cancer (CRC) shows high incidence and mortality, partly due to the tumor microenvironment (TME), which is viewed as an active promoter of disease progression. Macrophages are among the most abundant cells in the TME. These immune cells are generally categorized as M1, with inflammatory and anti-cancer properties, or M2, which promote tumor proliferation and survival. Although the M1/M2 subclassification scheme is strongly influenced by metabolism, the metabolic divergence between the subtypes remains poorly understood. Therefore, we generated a suite of computational models that characterize the M1- and M2-specific metabolic states. Our models show key differences between the M1 and M2 metabolic networks and capabilities. We leverage the models to identify metabolic perturbations that cause the metabolic state of M2 macrophages to more closely resemble M1 cells. Overall, this work increases understanding of macrophage metabolism in CRC and elucidates strategies to promote the metabolic state of anti-tumor macrophages.

Tumor microenvironment responsive metal nanoparticles in cancer immunotherapy

Malignant tumors have a unique tumor microenvironment (TME), which includes mild acidity, hypoxia, overexpressed reactive oxygen species (ROS), and high glutathione (GSH) levels, among others. Recently, TME regulation approaches have attracted widespread attention in cancer immunotherapy. Nanoparticles as drug delivery systems have ability to modulate the hydrophilicity of drugs to affect drug uptake and efflux in tumor. Especially, the metal nanoparticles have been extensive applied for tumor immunotherapy due to their unique physical properties and elaborate design. However, the potential deficiencies of metal nanoparticles due to their low biodegradability, toxicity and treatment side effects restrict their clinical application. In this review, we briefly introduce the feature characteristics of the TME and the recent advances in tumor microenvironment responsive metal nanoparticles for tumor immunotherapy. In addition, nanoparticles could be combined with other treatments, such as chemotherapy, radiotherapy and photodynamic therapy also is presented. Finally, the challenges and outlook for improving the antitumor immunotherapy efficiency, side effect and potential risks of metal nanoparticles has been discussed.

Immunometabolic control by Klebsiella pneumoniae

Klebsiella pneumoniae is a common Gram-negative pathogen associated with community-acquired and healthcare-associated infections. Its ability to acquire genetic elements resulted in its rapid development of resistance to virtually all antimicrobial agents. Once infection is established, K. pneumoniae is able to evade the host immune response and perhaps more importantly, undergo metabolic rewiring to optimize its ability to maintain infection. K. pneumoniae lipopolysaccharide and capsular polysaccharide are central factors in the induction and evasion of immune clearance. Less well understood is the importance of immunometabolism, the intersection between cellular metabolism and immune function, in the host response to K. pneumoniae infection. Bacterial metabolism itself is perceived as a metabolic stress to the host, altering the microenvironment at the site of infection. In this review, we will discuss the metabolic responses induced by K. pneumoniae, particularly in response to stimulation with the metabolically active bacteria versus pathogen-associated molecular patterns alone, and their implications in shaping the nature of the immune response and the infection outcome. A better understanding of the immunometabolic response to K. pneumoniae may help identify new targets for therapeutic intervention in the treatment of multidrug-resistant bacterial infections.

Targeting cGAS/STING signaling-mediated myeloid immune cell dysfunction in TIME

Myeloid immune cells (MICs) are potent innate immune cells serving as first responders to invading pathogens and internal changes to cellular homeostasis. Cancer is a stage of altered cellular homeostasis that can originate in response to different pathogens, chemical carcinogens, and internal genetic/epigenetic changes. MICs express several pattern recognition receptors (PRRs) on their membranes, cytosol, and organelles, recognizing systemic, tissue, and organ-specific altered homeostasis. cGAS/STING signaling is a cytosolic PRR system for identifying cytosolic double-stranded DNA (dsDNA) in a sequence-independent but size-dependent manner. The longer the cytosolic dsDNA size, the stronger the cGAS/STING signaling activation with increased type 1 interferon (IFN) and NF-κB-dependent cytokines and chemokines' generation. The present article discusses tumor-supportive changes occurring in the tumor microenvironment (TME) or tumor immune microenvironment (TIME) MICs, specifically emphasizing cGAS/STING signaling-dependent alteration. The article further discusses utilizing MIC-specific cGAS/STING signaling modulation as critical tumor immunotherapy to alter TIME.

Macrophages at the interface of the co-evolving cancer ecosystem

Macrophages are versatile and heterogeneous innate immune cells undertaking central functions in balancing immune responses and tissue repair to maintain homeostasis. This plasticity, once co-opted by malignant outgrowth, orchestrates manifold reciprocal interactions within the tumor microenvironment, fueling the evolution of the cancer ecosystem. Here, we review the multilayered sources of influence that jointly underpin and longitudinally shape tumor-associated macrophage (TAM) phenotypic states in solid neoplasms. We discuss how, in response to these signals, TAMs steer tumor evolution in the context of natural selection, biological dispersion, and treatment resistance. A number of research frontiers to be tackled are laid down in this review to therapeutically exploit the complex roles of TAMs in cancer. Building upon knowledge obtained from currently applied TAM-targeting strategies and using next generation technologies, we propose conceptual advances and novel therapeutic avenues to rewire TAM multifaceted regulation of the co-evolving cancer ecosystem.

Ensemble-based genome-scale modeling predicts metabolic differences between macrophage subtypes in colorectal cancer

1Colorectal cancer (CRC) shows high incidence and mortality, partly due to the tumor microenvironment, which is viewed as an active promoter of disease progression. Macrophages are among the most abundant cells in the tumor microenvironment. These immune cells are generally categorized as M1, with inflammatory and anti-cancer properties, or M2, which promote tumor proliferation and survival. Although the M1/M2 subclassification scheme is strongly influenced by metabolism, the metabolic divergence between the subtypes remains poorly understood. Therefore, we generated a suite of computational models that characterize the M1- and M2-specific metabolic states. Our models show key differences between the M1 and M2 metabolic networks and capabilities. We leverage the models to identify metabolic perturbations that cause the metabolic state of M2 macrophages to more closely resemble M1 cells. Overall, this work increases understanding of macrophage metabolism in CRC and elucidates strategies to promote the metabolic state of anti-tumor macrophages.

Machine learning methods revealed the roles of immune-metabolism related genes in immune infiltration, stemness, and prognosis of neuroblastoma

BACKGROUND

Immunometabolism plays an important role in neuroblastoma (NB). However, the mechanism of immune-metabolism related genes (IMRGs) in NB remains unclear. This study aimed to explore the effects of IMRGs on the prognosis, immune infiltration and stemness of patients with NB using machine learning methods.

METHODS

R software (v4.2.1) was used to identify the differentially expressed IMRGs, and machine learning algorithm was used to screen the prognostic genes from IMRGs. Then we constructed a prognostic model and calculated the risk scores. The NB patients were grouped according to the prognosis scores. In addition, the genes most associated with the immune infiltration and stemness of NB were analyzed by weighted gene co-expression network analysis (WGCNA).

RESULTS

There were 89 differentially expressed IMRGs between the MYCN amplification and the MYCN non-amplification group, among which CNR1, GNAI1, GLDC and ABCC4 were selected by machine learning algorithm to construct the prognosis model due to their better prediction effect. Both the K-M survival curve and the 5-year Receiver operating characteristic (ROC) curve indicated that the prognosis model could predict the prognosis of NB patients, and there was significant difference in immune infiltration between the two groups according to the median of risk score.

CONCLUSIONS

We verified the effects of IMRGs on the prognosis, immune infiltration and stemness of NB. These findings could provide help for predicting prognosis and developing immunotherapy in NB.

Metabolic reprogramming by miRNAs in the tumor microenvironment: Focused on immunometabolism

MicroRNAs (miRNAs) are emerging as a significant modulator of immunity, and their abnormal expression/activity has been linked to numerous human disorders, such as cancer. It is now known that miRNAs potentially modulate the production of several metabolic processes in tumor-associated immune cells and indirectly via different metabolic enzymes that affect tumor-associated signaling cascades. For instance, Let-7 has been identified as a crucial modulator for the long-lasting survival of CD8+ T cells (naive phenotypes) in cancer by altering their metabolism. Furthermore, in T cells, it has been found that enhancer of zeste homolog 2 (EZH2) expression is controlled via glycolytic metabolism through miRNAs in patients with ovarian cancer. On the other hand, immunometabolism has shown us that cellular metabolic reactions and processes not only generate ATP and biosynthetic intermediates but also modulate the immune system and inflammatory processes. Based on recent studies, new and encouraging approaches to cancer involving the modification of miRNAs in immune cell metabolism are currently being investigated, providing insight into promising targets for therapeutic strategies based on the pivotal role of immunometabolism in cancer. Throughout this overview, we explore and describe the significance of miRNAs in cancer and immune cell metabolism.

From CD16a Biology to Antibody-Dependent Cell-Mediated Cytotoxicity Improvement

Antibody-dependent cell-mediated cytotoxicity (ADCC) is a potent cytotoxic mechanism that is mainly mediated in humans by natural killer (NK) cells. ADCC mediates the clinical benefit of several widely used cytolytic monoclonal antibodies (mAbs), and increasing its efficacy would improve cancer immunotherapy. CD16a is a receptor for the Fc portion of IgGs and is responsible to trigger NK cell-mediated ADCC. The knowledge of the mechanism of action of CD16a gave rise to several strategies to improve ADCC, by working on either the mAbs or the NK cell. In this review, we give an overview of CD16a biology and describe the latest strategies employed to improve antibody-dependent NK cell cytotoxicity.

The Evasion Mechanisms of Cancer Immunity and Drug Intervention in the Tumor Microenvironment

Recently, in the field of cancer treatment, the paradigm has changed to immunotherapy that activates the immune system to induce cancer attacks. Among them, immune checkpoint inhibitors (ICI) are attracting attention as excellent and continuous clinical results. However, it shows not only limitations such as efficacy only in some patients or some indications, but also side-effects and resistance occur. Therefore, it is necessary to understand the factors of the tumor microenvironment (TME) that affect the efficacy of immunotherapy, that is, the mechanism by which cancer grows while evading or suppressing attacks from the immune system within the TME. Tumors can evade attacks from the immune system through various mechanisms such as restricting antigen recognition, inhibiting the immune system, and inducing T cell exhaustion. In addition, tumors inhibit or evade the immune system by accumulating specific metabolites and signal factors within the TME or limiting the nutrients available to immune cells. In order to overcome the limitations of immunotherapy and develop effective cancer treatments and therapeutic strategies, an approach is needed to understand the functions of cancer and immune cells in an integrated manner based on the TME. In this review, we will examine the effects of the TME on cancer cells and immune cells, especially how cancer cells evade the immune system, and examine anti-cancer strategies based on TME.

The Immunological Contribution of a Novel Metabolism-Related Signature to the Prognosis and Anti-Tumor Immunity in Cervical Cancer

Cervical cancer is the most frequently diagnosed malignancy in the female reproductive system. Conventional stratification of patients based on clinicopathological characters has gradually been outpaced by a molecular profiling strategy. Our study aimed to identify a reliable metabolism-related predictive signature for the prognosis and anti-tumor immunity in cervical cancer. In this study, we extracted five metabolism-related hub genes, including ALOX12B, CA9, FAR2, F5 and TDO2, for the establishment of the risk score model. The Kaplan-Meier curve suggested that patients with a high-risk score apparently had a worse prognosis in the cervical cancer training cohort (TCGA, n = 304, p < 0.0001), validation cohort (GSE44001, n = 300, p = 0.0059) and pan-cancer cohorts (including nine TCGA tumors). Using a gene set enrichment analysis (GSEA), we observed that the model was correlated with various immune-regulation-related pathways. Furthermore, pan-cancer cohorts and immunohistochemical analysis showed that the infiltration of tumor infiltrating lymphocytes (TILs) was lower in the high-score group. Additionally, the model could also predict the prognosis of patients with cervical cancer based on the expression of immune checkpoints (ICPs) in both the discovery and validation cohorts. Our study established and validated a metabolism-related prognostic model, which might improve the accuracy of predicting the clinical outcome of patients with cervical cancer and provide guidance for personalized treatment.

Drug delivery for metabolism targeted cancer immunotherapy

Drug delivery vehicles have made a great impact on cancer immunotherapies in clinics and pre-clinical research. Notably, the science of delivery of cancer vaccines and immunotherapeutics, modulating immune cell functions has inspired development of several successful companies and clinical products. Interestingly, these drug delivery modalities not only modulate the function of immune cells (often quantified at the mRNA and protein levels), but also modulate the metabolism of these cells. Specifically, cancer immunotherapy often leads to activation of different immune cells such as dendritic cells, macrophages and T cells, which is driven by energy metabolism of these cells. Recently, there has been a great excitement about interventions that can directly modulate the energy metabolism of these immune cells and thus affect their function and in turn lead to a robust cancer immune response. Here we review few strategies that have been tested in clinic and pre-clinical research for generating effective metabolism-associated cancer therapies and immunotherapies.

Influence of T Cell-Mediated Immune Surveillance on Somatic Mutation Occurrences in Melanoma

Background

Neoantigens are presented on the cancer cell surface by peptide-restricted human leukocyte antigen (HLA) proteins and can subsequently activate cognate T cells. It has been hypothesized that the observed somatic mutations in tumors are shaped by immunosurveillance.

Methods

We investigated all somatic mutations identified in The Cancer Genome Atlas (TCGA) Skin Cutaneous Melanoma (SKCM) samples. By applying a computational algorithm, we calculated the binding affinity of the resulting neo-peptides and their corresponding wild-type peptides with the major histocompatibility complex (MHC) Class I complex. We then examined the relationship between binding affinity alterations and mutation frequency.

Results

Our results show that neoantigens derived from recurrent mutations tend to have lower binding affinities with the MHC Class I complex compared to peptides from non-recurrent mutations. Tumor samples harboring recurrent SKCM mutations exhibited lower immune infiltration levels, indicating a relatively colder immune microenvironment.

Conclusions

These results suggested that the occurrences of somatic mutations in melanoma have been shaped by immunosurveillance. Mutations that lead to neoantigens with high MHC class I binding affinity are more likely to be eliminated and thus are less likely to be present in tumors.

CD8+ T Cell-Based Molecular Classification With Heterogeneous Immunogenomic Landscapes and Clinical Significance of Clear Cell Renal Cell Carcinoma

The tumor microenvironment (TME) exerts a high impact on tumor biology and immunotherapy. The heterogeneous phenotypes and the clinical significance of CD8⁺ T cells in TME have not been fully elucidated. Here, a comprehensive immunogenomic analysis based on multi-omics data was performed to investigate the clinical significance and tumor heterogeneity between CD8⁺ T cell-related molecular clusters. We identified two distinct molecular clusters of ccRCC (C1 and C2) in TCGA and validated in E-MTAB-1980 cohorts. The C1 cluster was characterized by unfavorable prognosis, increased expression levels of CD8⁺ T cell exhaustion markers, high immune infiltration levels as well as more immune escape mechanisms. The C2 cluster was featured by favorable prognosis, elevated expression levels of CD8⁺ T cell effector markers, low load of copy number loss and low frequency of 9p21.3 deletion. Moreover, the effect of molecular classifications on Nivolumab therapeutic efficacy in the CheckMate 025 cohort was examined, and the C2 cluster exhibited a better prognosis. Taken together, we determine two CD8⁺ T cell-related molecular clusters in ccRCC, and provide new insights for evaluating the functions of CD8⁺ T cells. Our molecular classification is a potential strategy for prognostic prediction and immunotherapeutic guidance for ccRCC patients.