Immuno-Metabolism: The Role of Cancer Niche in Immune Checkpoint Inhibitor Resistance

Immunometabolism in cancer: basic mechanisms and new targeting strategy

Maturing immunometabolic research empowers immune regulation novel approaches. Progressive metabolic adaptation of tumor cells permits a thriving tumor microenvironment (TME) in which immune cells always lose the initial killing capacity, which remains an unsolved dilemma even with the development of immune checkpoint therapies. In recent years, many studies on tumor immunometabolism have been reported. The development of immunometabolism may facilitate anti-tumor immunotherapy from the recurrent crosstalk between metabolism and immunity. Here, we discuss clinical studies of the core signaling pathways of immunometabolism and their inhibitors or agonists, as well as the specific functions of these pathways in regulating immunity and metabolism, and discuss some of the identified immunometabolic checkpoints. Understanding the comprehensive advances in immunometabolism helps to revise the status quo of cancer treatment. An overview of the new landscape of immunometabolism. The PI3K pathway promotes anabolism and inhibits catabolism. The LKB1 pathway inhibits anabolism and promotes catabolism. Overactivation of PI3K/AKT/mTOR pathway and IDO, IL4I1, ACAT, Sirt2, and MTHFD2 promote immunosuppression of TME formation, as evidenced by increased Treg and decreased T-cell proliferation. The LKBI-AMPK pathway promotes the differentiation of naive T cells to effector T cells and memory T cells and promotes anti-tumor immunity in DCs.

Tumor metabolic crosstalk and immunotherapy

Tumor cells must resist the host's immune system while maintaining growth under harsh conditions of acidity and hypoxia, which indicates that tumors are more robust than normal tissue. Immunotherapeutic agents have little effect on solid tumors, mostly because of the tumor density and the difficulty of penetrating deeply into the tissue to achieve the theoretical therapeutic effect. Various therapeutic strategies targeting the tumor microenvironment (TME) have been developed. Immunometabolic disorders play a dominant role in treatment resistance at both the TME and host levels. Understanding immunometabolic factors and their treatment potential may be a way forward for tumor immunotherapy. Here, we summarize the metabolism of substances that affect tumor progression, the crosstalk between the TME and immunosuppression, and some potential tumor-site targets. We also summarize the progress and challenges of tumor immunotherapy.

Targeting YAP1 to improve the efficacy of immune checkpoint inhibitors in liver cancer: mechanism and strategy

Liver cancer is the third leading of tumor death, including hepatocellular carcinoma (HCC) and intrahepatic cholangiocarcinoma (ICC). Immune checkpoint inhibitors (ICIs) are yielding much for sufferers to hope for patients, but only some patients with advanced liver tumor respond. Recent research showed that tumor microenvironment (TME) is critical for the effectiveness of ICIs in advanced liver tumor. Meanwhile, metabolic reprogramming of liver tumor leads to immunosuppression in TME. These suggest that regulating the abnormal metabolism of liver tumor cells and firing up TME to turn "cold tumor" into "hot tumor" are potential strategies to improve the therapeutic effect of ICIs in liver tumor. Previous studies have found that YAP1 is a potential target to improve the efficacy of anti-PD-1 in HCC. Here, we review that YAP1 promotes immunosuppression of TME, mainly due to the overstimulation of cytokines in TME by YAP1. Subsequently, we studied the effects of YAP1 on metabolic reprogramming in liver tumor cells, including glycolysis, gluconeogenesis, lipid metabolism, arachidonic acid metabolism, and amino acid metabolism. Lastly, we summarized the existing drugs targeting YAP1 in the treatment of liver tumor, including some medicines from natural sources, which have the potential to improve the efficacy of ICIs in the treatment of liver tumor. This review contributed to the application of targeted YAP1 for combined therapy with ICIs in liver tumor patients.

Discovering the strength of immunometabolism in cancer therapy: Employing metabolic pathways to enhance immune responses

Immunometabolism, which studies cellular metabolism and immune cell function, is a possible cancer treatment. Metabolic pathways regulate immune cell activation, differentiation, and effector functions, crucial to tumor identification and elimination. Immune evasion and tumor growth can result from tumor microenvironment metabolic dysregulation. These metabolic pathways can boost antitumor immunity. This overview discusses immune cell metabolism, including glycolysis, oxidative phosphorylation, amino acid, and lipid metabolism. Amino acid and lipid metabolic manipulations may improve immune cell activity and antitumor immunity. Combination therapy using immunometabolism-based strategies may enhance therapeutic efficacy. The complexity of the metabolic network, biomarker development, challenges, and future approaches are all covered, along with a summary of case studies demonstrating the effectiveness of immunometabolism-based therapy. Metabolomics, stable isotope tracing, single-cell analysis, and computational modeling are also reviewed for immunometabolism research. Personalized and combination treatments are considered. This review adds to immunometabolism expertise and sheds light on metabolic treatments' ability to boost cancer treatment immunological response. Also, in this review, we discussed the immune response in cancer treatment and altering metabolic pathways to increase the immune response against malignancies.

Unlocking the Potential of Biomarkers for Immune Checkpoint Inhibitors in Cancer Therapy

Immune checkpoint inhibitors (ICIs) are pharmaceutical agents capable of disrupting immune checkpoint signaling, leading to T-cell activation and a robust anti-tumor response [...].

Immunometabolism: a new dimension in immunotherapy resistance

Immune checkpoint inhibitors (ICIs) have demonstrated unparalleled clinical responses and revolutionized the paradigm of tumor treatment, while substantial patients remain unresponsive or develop resistance to ICIs as a single agent, which is traceable to cellular metabolic dysfunction. Although dysregulated metabolism has long been adjudged as a hallmark of tumor, it is now increasingly accepted that metabolic reprogramming is not exclusive to tumor cells but is also characteristic of immunocytes. Correspondingly, people used to pay more attention to the effect of tumor cell metabolism on immunocytes, but in practice immunocytes interact intimately with their own metabolic function in a way that has never been realized before during their activation and differentiation, which opens up a whole new frontier called immunometabolism. The metabolic intervention for tumor-infiltrating immunocytes could offer fresh opportunities to break the resistance and ameliorate existing ICI immunotherapy, whose crux might be to ascertain synergistic combinations of metabolic intervention with ICIs to reap synergic benefits and facilitate an adjusted anti-tumor immune response. Herein, we elaborate potential mechanisms underlying immunotherapy resistance from a novel dimension of metabolic reprogramming in diverse tumor-infiltrating immunocytes, and related metabolic intervention in the hope of offering a reference for targeting metabolic vulnerabilities to circumvent immunotherapeutic resistance.

Targeting inhibition of prognosis-related lipid metabolism genes including CYP19A1 enhances immunotherapeutic response in colon cancer

BACKGROUND

Lipid metabolic reprogramming in colon cancer shows a potential impact on tumor immune microenvironment and is associated with response to immunotherapy. Therefore, this study aimed to develop a lipid metabolism-related prognostic risk score (LMrisk) to provide new biomarkers and combination therapy strategies for colon cancer immunotherapy.

METHODS

Differentially expressed lipid metabolism-related genes (LMGs) including cytochrome P450 (CYP) 19A1 were screened to construct LMrisk in TCGA colon cancer cohort. The LMrisk was then validated in three GEO datasets. The differences of immune cell infiltration and immunotherapy response between LMrisk subgroups were investigated via bioinformatic analysis. These results were comfirmed by in vitro coculture of colon cancer cells with peripheral blood mononuclear cells, human colon cancer tissue microarray analysis, multiplex immunofluorescence staining and mouse xenograft models of colon cancer.

RESULTS

Six LMGs including CYP19A1, ALOXE3, FABP4, LRP2, SLCO1A2 and PPARGC1A were selected to establish the LMrisk. The LMrisk was positively correlated with the abundance of macrophages, carcinoma-associated fibroblasts (CAFs), endothelial cells and the levels of biomarkers for immunotherapeutic response including programmed cell death ligand 1 (PD-L1) expression, tumor mutation burden and microsatellite instability, but negatively correlated with CD8⁺ T cell infiltration levels. CYP19A1 protein expression was an independent prognostic factor, and positively correlated with PD-L1 expression in human colon cancer tissues. Multiplex immunofluorescence analyses revealed that CYP19A1 protein expression was negatively correlated with CD8⁺ T cell infiltration, but positively correlated with the levels of tumor-associated macrophages, CAFs and endothelial cells. Importantly, CYP19A1 inhibition downregulated PD-L1, IL-6 and TGF-β levels through GPR30-AKT signaling, thereby enhancing CD8⁺ T cell-mediated antitumor immune response in vitro co-culture studies. CYP19A1 inhibition by letrozole or siRNA strengthened the anti-tumor immune response of CD8⁺ T cells, induced normalization of tumor blood vessels, and enhanced the efficacy of anti-PD-1 therapy in orthotopic and subcutaneous mouse colon cancer models.

CONCLUSION

A risk model based on lipid metabolism-related genes may predict prognosis and immunotherapeutic response in colon cancer. CYP19A1-catalyzed estrogen biosynthesis promotes vascular abnormality and inhibits CD8⁺ T cell function through the upregulation of PD-L1, IL-6 and TGF-β via GPR30-AKT signaling. CYP19A1 inhibition combined with PD-1 blockade represents a promising therapeutic strategy for colon cancer immunotherapy.

Prognostic value of inflammatory and nutritional indexes among advanced NSCLC patients receiving PD-1 inhibitor therapy

Though immunotherapy has to some extent improved the prognosis of patients with advanced non-small cell lung cancer (NSCLC), only a few patients benefit. Furthermore, immunotherapy efficacy is affected by inflammatory and nutritional status of patients. To investigate whether dynamics of inflammatory and nutritional indexes were associated with prognosis, 223 patients were analysed retrospectively. The inflammatory indexes of interest were neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR) and systemic immune-inflammation index (SII) while prognostic nutritional index (PNI) and the haemoglobin, albumin, lymphocyte and platelet (HALP) score were considered as nutritional indexes. Patients were divided into high and low groups or into 'increase' and 'decrease' groups based on pre-treatment cut-off values and index dynamics after 6-week follow-up respectively. High pre-treatment PLR (OR = 2.612) and increase in NLR during follow-up (OR = 2.516) were significantly associated with lower objective response rates. Using multivariable analysis, high pre-treatment PLR (HR, 2.319) and increase in SII (HR, 1.731) predicted shorter progression-free survival, while high pre-treatment NLR (HR, 1.635), increase in NLR (HR, 1.663) and PLR (HR, 1.691) and decrease in PNI (HR, 0.611) predicted worse overall survival. The nomogram's C-index in inside validation was 0.718 (95% CI: 0.670-0.766). Our results indicated both nutritional and inflammatory indexes are associated with survival outcomes. Inflammatory indexes were additionally linked to treatment response. Index dynamics are better predictors than baseline values in predicting survival in advanced NSCLC patients receiving PD-1 inhibitor combined with chemotherapy as first-line.

Long-chain polyunsaturated lipids associated with responsiveness to anti-PD-1 therapy are colocalized with immune infiltrates in the tumor microenvironment

The programmed cell death protein-1 (PD-1) is highly expressed on the surface of antigen-specific exhausted T cells and, upon interaction with its ligand PD-L1, can result in inhibition of the immune response. Anti-PD-1 treatment has been shown to extend survival and result in durable responses in several cancers, yet only a subset of patients benefit from this therapy. Despite the implication of metabolic alteration following cancer immunotherapy, mechanistic associations between antitumor responses and metabolic changes remain unclear. Here, we used desorption electrospray ionization mass spectrometry imaging to examine the lipid profiles of tumor tissue from three syngeneic murine models with varying treatment sensitivity at the baseline and at three time points post-anti-PD-1 therapy. These imaging experiments revealed specific alterations in the lipid profiles associated with the degree of response to treatment and allowed us to identify a significant increase of long-chain polyunsaturated lipids within responsive tumors following anti-PD-1 therapy. Immunofluorescence imaging of tumor tissues also demonstrated that the altered lipid profile associated with treatment response is localized to dense regions of tumor immune infiltrates. Overall, these results indicate that effective anti-PD-1 therapy modulates lipid metabolism in tumor immune infiltrates, and we thereby propose that further investigation of the related immune-metabolic pathways may be useful for better understanding success and failure of anti-PD-1 therapy.

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.

Combination of Baseline and Variation of Prognostic Nutritional Index Enhances the Survival Predictive Value of Patients With Advanced Non-Small Cell Lung Cancer Treated With Programmed Cell Death Protein 1 Inhibitor

BACKGROUND

Low baseline prognostic nutritional index (PNI) scores are associated with poor survival for various malignancies; however, they vary based on the cohort and time resulting in inaccurate results. We determined the predictive value of the PNI score variations in addition to the baseline PNI scores for patients with advanced non-small cell lung cancer (NSCLC) who received programmed cell death protein 1 (PD-1) inhibitor.

METHODS

We retrospectively analysed 115 patients with advanced NSCLC who received PD-1 inhibitor. The median follow-up period was 28 months. Patients were clustered into four groups based on the combined PNI scores (combination of baseline and variation of PNI scores): ΔPNI-L-L, ΔPNI-L-H, ΔPNI-H-L, and ΔPNI-H-H subgroups. For instance, if PNI scores of patients with high baseline PNI score increased from baseline to 6 weeks after treatment, they were included in the ΔPNI-H-H subgroup. Cox regression models were used to identify the factors associated with survival.

RESULTS

The baseline PNI score was only related to the overall survival (OS) (P = .026), and not to the overall response rate (ORR) (P = .299) and progression-free survival (PFS) (P = .207). The ORR was associated with the combined PNI scores (P = .017). A multivariable Cox regression analysis confirmed that the combined PNI scores were independent factors for PFS (ΔPNI-L-H, 12 months, hazard ratio [HR] = 0.449, P = .009; ΔPNI-H-L, 14 months, HR = 0.500, P = .019; and ΔPNI-H-H, 17 months, HR = 0.390, P = .012; vs ΔPNI-L-L, 8 months) and OS (ΔPNI-L-H, 27 months, HR = 0.403, P = .019; ΔPNI-H-L, 28 months, HR = 0.369, P = .010; and ΔPNI-H-H, not reached, HR = 0.087, P = .002; vs ΔPNI-L-L, 15 months).

CONCLUSIONS

Patients with high baseline PNI and increased PNI score had the better survival outcome. On dynamic monitoring and comprehensive assessment, the combined PNI scores significantly enhanced the survival predictive ability of patients with NSCLC treated with PD-1 inhibitor.

Clinical applications of plasma proteomics and peptidomics: Towards precision medicine

In the context of precision medicine, disease treatment requires individualized strategies based on the underlying molecular characteristics to overcome therapeutic challenges posed by heterogeneity. For this purpose, it is essential to develop new biomarkers to diagnose, stratify, or possibly prevent diseases. Plasma is an available source of biomarkers that greatly reflects the physiological and pathological conditions of the body. An increasing number of studies are focusing on proteins and peptides, including many involving the Human Proteome Project (HPP) of the Human Proteome Organization (HUPO), and proteomics and peptidomics techniques are emerging as critical tools for developing novel precision medicine preventative measures. Excitingly, the emerging plasma proteomics and peptidomics toolbox exhibits a huge potential for studying pathogenesis of diseases (e.g., COVID-19 and cancer), identifying valuable biomarkers and improving clinical management. However, the enormous complexity and wide dynamic range of plasma proteins makes plasma proteome profiling challenging. Herein, we summarize the recent advances in plasma proteomics and peptidomics with a focus on their emerging roles in COVID-19 and cancer research, aiming to emphasize the significance of plasma proteomics and peptidomics in clinical applications and precision medicine.

Immune checkpoint proteins: Signaling mechanisms and molecular interactions in cancer immunotherapy

Immune checkpoint proteins (ICP) are currently one of the most novel and promising areas of immune-oncology research. This novel way of targeting tumor cells has shown favorable success over the past few years with some FDA approvals such as Ipilimumab, Nivolumab, Pembrolizumab etc. Currently, more than 3000 clinical trials of immunotherapeutic agents are ongoing with majority being ICPs. However, as the number of trials increase so do the challenges. Some challenges such as adverse side effects, non-specific binding on healthy tissues and absence of response in some subset populations are critical obstacles. For a safe and effective further therapeutic development of molecules targeting ICPs, understanding their mechanism at molecular level is crucial. Since ICPs are mostly membrane bound receptors, a number of downstream signaling pathways divaricate following ligand-receptor binding. Most ICPs are expressed on more than one type of immune cell populations. Further, the expression varies within a cell type. This naturally varied expression pattern adds to the difficulty of targeting specific effector immune cell types against cancer. Hence, understanding the expression pattern and cellular mechanism helps lay out the possible effect of any immunotherapy. In this review, we discuss the signaling mechanism, expression pattern among various immune cells and molecular interactions derived using interaction database analysis (BioGRID).

Nanoparticle-Based Drug Delivery Systems Targeting Tumor Microenvironment for Cancer Immunotherapy Resistance: Current Advances and Applications

Cancer immunotherapy has shown impressive anti-tumor activity in patients with advanced and early-stage malignant tumors, thus improving long-term survival. However, current cancer immunotherapy is limited by barriers such as low tumor specificity, poor response rate, and systemic toxicities, which result in the development of primary, adaptive, or acquired resistance. Immunotherapy resistance has complex mechanisms that depend on the interaction between tumor cells and the tumor microenvironment (TME). Therefore, targeting TME has recently received attention as a feasibility strategy for re-sensitizing resistant neoplastic niches to existing cancer immunotherapy. With the development of nanotechnology, nanoplatforms possess outstanding features, including high loading capacity, tunable porosity, and specific targeting to the desired locus. Therefore, nanoplatforms can significantly improve the effectiveness of immunotherapy while reducing its toxic and side effects on non-target cells that receive intense attention in cancer immunotherapy. This review explores the mechanisms of tumor microenvironment reprogramming in immunotherapy resistance, including TAMs, CAFs, vasculature, and hypoxia. We also examined whether the application of nano-drugs combined with current regimens is improving immunotherapy clinical outcomes in solid tumors.

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.

Impact of cancer metabolism on therapy resistance - Clinical implications

Despite an increasing arsenal of anticancer therapies, many patients continue to have poor outcomes due to the therapeutic failures and tumor relapses. Indeed, the clinical efficacy of anticancer therapies is markedly limited by intrinsic and/or acquired resistance mechanisms that can occur in any tumor type and with any treatment. Thus, there is an urgent clinical need to implement fundamental changes in the tumor treatment paradigm by the development of new experimental strategies that can help to predict the occurrence of clinical drug resistance and to identify alternative therapeutic options. Apart from mutation-driven resistance mechanisms, tumor microenvironment (TME) conditions generate an intratumoral phenotypic heterogeneity that supports disease progression and dismal outcomes. Tumor cell metabolism is a prototypical example of dynamic, heterogeneous, and adaptive phenotypic trait, resulting from the combination of intrinsic [(epi)genetic changes, tissue of origin and differentiation dependency] and extrinsic (oxygen and nutrient availability, metabolic interactions within the TME) factors, enabling cancer cells to survive, metastasize and develop resistance to anticancer therapies. In this review, we summarize the current knowledge regarding metabolism-based mechanisms conferring adaptive resistance to chemo-, radio-and immunotherapies as well as targeted therapies. Furthermore, we report the role of TME-mediated intratumoral metabolic heterogeneity in therapy resistance and how adaptations in amino acid, glucose, and lipid metabolism support the growth of therapy-resistant cancers and/or cellular subpopulations. We also report the intricate interplay between tumor signaling and metabolic pathways in cancer cells and discuss how manipulating key metabolic enzymes and/or providing dietary changes may help to eradicate relapse-sustaining cancer cells. Finally, in the current era of personalized medicine, we describe the strategies that may be applied to implement metabolic profiling for tumor imaging, biomarker identification, selection of tailored treatments and monitoring therapy response during the clinical management of cancer patients.

Immunometabolism Modulation in Therapy

The study of cancer biology should be based around a comprehensive vision of the entire tumor ecosystem, considering the functional, bioenergetic and metabolic state of tumor cells and those of their microenvironment, and placing particular importance on immune system cells. Enhanced understanding of the molecular bases that give rise to alterations of pathways related to tumor development can open up new therapeutic intervention opportunities, such as metabolic regulation applied to immunotherapy. This review outlines the role of various oncometabolites and immunometabolites, such as TCA intermediates, in shaping pro/anti-inflammatory activity of immune cells such as MDSCs, T lymphocytes, TAMs and DCs in cancer. We also discuss the extraordinary plasticity of the immune response and its implication in immunotherapy efficacy, and highlight different therapeutic intervention possibilities based on controlling the balanced systems of specific metabolites with antagonistic functions.