Tumor microenvironment metabolites directing T cell differentiation and function

The immunosuppressive landscape in tumor microenvironment

Recent advances in cancer immunotherapy, especially immune checkpoint inhibitors (ICIs), have revolutionized the clinical outcome of many cancer patients. Despite the fact that impressive progress has been made in recent decades, the response rate remains unsatisfactory, and many patients do not benefit from ICIs. Herein, we summarized advanced studies and the latest insights on immune inhibitory factors in the tumor microenvironment. Our in-depth discussion and updated landscape of tumor immunosuppressive microenvironment may provide new strategies for reversing tumor immune evasion, enhancing the efficacy of ICIs therapy, and ultimately achieving a better clinical outcome.

Metabolic waypoints during T cell differentiation

This Review explores the interplay between T cell activation and cell metabolism and highlights how metabolites serve two pivotal functions in shaping the immune response. Traditionally, T cell activation has been characterized by T cell antigen receptor-major histocompatibility complex interaction (signal 1), co-stimulation (signal 2) and cytokine signaling (signal 3). However, recent research has unveiled the critical role of metabolites in this process. Firstly, metabolites act as signal propagators that aid in the transmission of core activation signals, such as specific lipid species that are crucial at the immune synapse. Secondly, metabolites also function as unique signals that influence immune differentiation pathways, such as amino acid-induced mTORC1 signaling. Metabolites also play a substantial role in epigenetic remodeling, by directly modifying histones, altering gene expression and influencing T cell behavior. This Review discusses how T cells integrate nutrient sensing with activating stimuli to shape their differentiation and sensitivity to metabolites. We underscore the integration of immunological and metabolic inputs in T cell function and suggest that metabolite availability is a fundamental determinant of adaptive immune responses.

Metabolic regulation of tumor-associated macrophage heterogeneity: insights into the tumor microenvironment and immunotherapeutic opportunities

Tumor-associated macrophages (TAMs) are a heterogeneous population that play diverse functions in tumors. Their identity is determined not only by intrinsic factors, such as origins and transcription factors, but also by external signals from the tumor microenvironment (TME), such as inflammatory signals and metabolic reprogramming. Metabolic reprogramming has rendered TAM to exhibit a spectrum of activities ranging from pro-tumorigenic to anti-tumorigenic, closely associated with tumor progression and clinical prognosis. This review implicates the diversity of TAM phenotypes and functions, how this heterogeneity has been re-evaluated with the advent of single-cell technologies, and the impact of TME metabolic reprogramming on TAMs. We also review current therapies targeting TAM metabolism and offer new insights for TAM-dependent anti-tumor immunotherapy by focusing on the critical role of different metabolic programs in TAMs.

Imaging and AI based chromatin biomarkers for diagnosis and therapy evaluation from liquid biopsies

Multiple genomic and proteomic studies have suggested that peripheral blood mononuclear cells (PBMCs) respond to tumor secretomes and thus could provide possible avenues for tumor prognosis and treatment evaluation. We hypothesized that the chromatin organization of PBMCs obtained from liquid biopsies, which integrates secretome signals with gene expression programs, provides efficient biomarkers to characterize tumor signals and the efficacy of proton therapy in tumor patients. Here, we show that chromatin imaging of PBMCs combined with machine learning methods provides such robust and predictive chromatin biomarkers. We show that such chromatin biomarkers enable the classification of 10 healthy and 10 pan-tumor patients. Furthermore, we extended our pipeline to assess the tumor types and states of 30 tumor patients undergoing (proton) radiation therapy. We show that our pipeline can thereby accurately distinguish between three tumor groups with up to 89% accuracy and enables the monitoring of the treatment effects. Collectively, we show the potential of chromatin biomarkers for cancer diagnostics and therapy evaluation.

Endothelial-to-mesenchymal transition in tumour progression and its potential roles in tumour therapy

Tumour-associated endothelial cells (TECs) are a critical stromal cell type in the tumour microenvironment and play central roles in tumour angiogenesis. Notably, TECs have phenotypic plasticity, as they have the potential to transdifferentiate into cells with a mesenchymal phenotype through a process termed endothelial-to-mesenchymal transition (EndoMT). Many studies have reported that EndoMT influences multiple malignant biological properties of tumours, such as abnormal angiogenesis and tumour metabolism, growth, metastasis and therapeutic resistance. Thus, the value of targeting EndoMT in tumour treatment has received increased attention. In this review, we comprehensively explore the phenomenon of EndoMT in the tumour microenvironment and identify influencing factors and molecular mechanisms responsible for EndoMT induction. Furthermore, the pathological functions of EndoMT in tumour progression and potential therapeutic strategies for targeting EndoMT in tumour treatment are also discussed to highlight the pivotal roles of EndoMT in tumour progression and therapy.

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.

Desorption electrospray ionization and matrix-assisted laser desorption/ionization as imaging approaches for biological samples analysis

The imaging of biological tissues can offer valuable information about the sample composition, which improves the understanding of analyte distribution in such complex samples. Different approaches using mass spectrometry imaging (MSI), also known as imaging mass spectrometry (IMS), enabled the visualization of the distribution of numerous metabolites, drugs, lipids, and glycans in biological samples. The high sensitivity and multiple analyte evaluation/visualization in a single sample provided by MSI methods lead to various advantages and overcome drawbacks of classical microscopy techniques. In this context, the application of MSI methods, such as desorption electrospray ionization-MSI (DESI-MSI) and matrix-assisted laser desorption/ionization-MSI (MALDI-MSI), has significantly contributed to this field. This review discusses the evaluation of exogenous and endogenous molecules in biological samples using DESI and MALDI imaging. It offers rare technical insights not commonly found in the literature (scanning speed and geometric parameters), making it a comprehensive guide for applying these techniques step-by-step. Furthermore, we provide an in-depth discussion of recent research findings on using these methods to study biological tissues.

A novel anoikis-related gene prognostic signature and its correlation with the immune microenvironment in colorectal cancer

Background: Anoikis is a type of apoptosis associated with cell detachment. Resistance to anoikis is a focal point of tumor metastasis. This study aimed to explore the relationship among anoikis-related genes (ARGs), immune infiltration, and prognosis in colorectal cancer (CRC). Methods: The transcriptome profile and clinical data on patients with CRC were retrieved from The Cancer Genome Atlas and Gene Expression Omnibus databases. Patients were divided into two clusters based on the expression of ARGs. Differences between the two ARG molecular subtypes were analyzed in terms of prognosis, functional enrichment, gene mutation frequency, and immune cell infiltration. An ARG-related prognostic signature for predicting overall survival in patients with CRC was developed and validated using absolute value convergence and selection operator (LASSO) regression analysis. The correlation between the signature risk score and clinicopathological features, immune cell infiltration, immune typing, and immunotherapy response was analyzed. The risk score combined with clinicopathological characteristics was used to construct a nomogram to assess CRC patients' prognosis. Results: Overall, 151 ARGs were differentially expressed in CRC. Two ARG subtypes, namely, ARG-high and ARG-low groups, were identified and correlated with CRC prognosis. The gene mutation frequency and immune, stromal, and ESTIMATE scores of the ARG-high group were higher than those of the ARG-low group. Moreover, CD8, natural killer cells, M1 macrophages, human leukocyte antigen (HLA), and immune checkpoint-related genes were significantly increased in the ARG-high group. An optimized 25-gene CRC prognostic signature was successfully constructed, and its prognostic predictive ability was validated. The high-risk score was correlated with T, N, M, and TNM stages. Risk scores were negatively correlated with dendritic cells, eosinophils, and CD4 cells, and significantly positively correlated with regulatory T cells. Patients in the high-risk group were more likely to exhibit immune unresponsiveness. Finally, the nomogram model was constructed and showed good prognostic predictive power. Conclusion: ARGs are associated with clinicopathological features and the prognosis of CRC, and play important roles in the immune microenvironment. Herein, we underpinned the usefulness of ARGs in CRC to develop more effective immunotherapy techniques.

How cancer hijacks the body's homeostasis through the neuroendocrine system

During oncogenesis, cancer not only escapes the body's regulatory mechanisms, but also gains the ability to affect local and systemic homeostasis. Specifically, tumors produce cytokines, immune mediators, classical neurotransmitters, hypothalamic and pituitary hormones, biogenic amines, melatonin, and glucocorticoids, as demonstrated in human and animal models of cancer. The tumor, through the release of these neurohormonal and immune mediators, can control the main neuroendocrine centers such as the hypothalamus, pituitary, adrenals, and thyroid to modulate body homeostasis through central regulatory axes. We hypothesize that the tumor-derived catecholamines, serotonin, melatonin, neuropeptides, and other neurotransmitters can affect body and brain functions. Bidirectional communication between local autonomic and sensory nerves and the tumor, with putative effects on the brain, is also envisioned. Overall, we propose that cancers can take control of the central neuroendocrine and immune systems to reset the body homeostasis in a mode favoring its expansion at the expense of the host.

Attenuating Metabolic Competition of Tumor Cells for Favoring the Nutritional Demand of Immune Cells by a Branched Polymeric Drug Delivery System

Tumor cells are dominant in the nutritional competition in the tumor microenvironment, and their metabolic abnormalities often lead to microenvironmental acidosis and nutrient deprivation, thereby impairing the function of immune cells and diminishing the antitumor therapeutic effect. Herein, a branched polymeric conjugate and its efficacy in attenuating the metabolic competition of tumor cells are reported. Compared with the control nanoparticles prepared from its linear counterpart, the branched-conjugate-based nanoparticles can more efficiently accumulate in the tumor tissue and interfere with the metabolic processes of tumor cells to increase the concentration of essential nutrients and reduce the level of immunosuppressive metabolites in the TME, thus creating a favorable environment for infiltrated immune cells. Its combined treatment with an immune checkpoint inhibitor (ICI) achieves an enhanced antitumor effect. The work presents a promising approach for targeting metabolic competition in the TME to enhance the chemo-immunotherapeutic effect against cancers.

Role of DEK in carcinogenesis, diagnosis, prognosis, and therapeutic outcome of breast cancer: An evidence-based clinical review

Breast cancer is a significantly burdening women's cancer with limited diagnostic modalities. DEK is a novel biomarker overexpressed in breast cancers, currently exhaustively researched for its diagnosis and prognosis. Search for relevant meta-analyses, cohorts, and experimental studies in the last fifteen years was done in five large scientific databases. Non-English, non-full text articles or unrelated studies were excluded. Thirteen articles discussed the potential of DEK to estimate breast cancer characteristics, treatment outcomes, and prognosis. This proto-oncogene plays a role in breast carcinogenesis, increasing tumour proliferation and invasion, preventing apoptosis, and creating an immunodeficient tumour milieu with M2 tumour-associated macrophages. DEK is also associated with worse clinicopathological features and survival in breast cancer patients. Using a Kaplan-Meier plotter data analysis, DEK expression predicts worse overall survival (HR 1.24, 95%CI: 1.01-1.52, p = 0.039), comparable to other biomarkers. DEK is a promising novel biomarker requiring further research to determine its bedside applications.

Research progress on tumor hypoxia-associative nanomedicine

Hypoxia at the solid tumor site is generally related to the unrestricted proliferation and metabolism of cancerous cells, which can cause tumor metastasis and aggravate tumor progression. Besides, hypoxia plays a substantial role in tumor treatment, and it is one of the main reasons that malignant tumors are difficult to cure and have a poor prognosis. On account of the tumor specific hypoxic environment, many hypoxia-associative nanomedicine have been proposed for tumor treatment. Considering the enhanced targeting effect, designing hypoxia-associative nanomedicine can not only minimize the adverse effects of drugs on normal tissues, but also achieve targeted therapy at the lesion site. Mostly, there can be three strategies for the treatment of hypoxic tumor, including improvement of hypoxic environment, hypoxia responsive drug release and hypoxia activated prodrug. The review describes the design principle and applications of tumor hypoxia-associative nanomedicine in recent years, and also explores its development trends in solid tumor treatment. Moreover, this review presents the current limitations of tumor hypoxia-associative nanomedicine in chemotherapy, radiotherapy, photodynamic therapy, sonodynamic therapy and immunotherapy, which may provide a reference for clinic translation of tumor hypoxia-associative nanomedicine.

NMR-based metabolomic analysis identifies RON-DEK-β-catenin dependent metabolic pathways and a gene signature that stratifies breast cancer patient survival

BACKGROUND

Advances in detection techniques and treatment have increased the diagnosis of breast cancer at early stages; however, recurrence occurs in all breast cancer subtypes, and both recurrent and de novo metastasis are typically treatment resistant. A growing body of evidence supports the notion that metabolic plasticity drives cancer recurrence. RON and DEK are proteins that promote cancer metastasis and synergize mechanistically to activate β-catenin, but the metabolic consequences are unknown.

METHODS

To ascertain RON-DEK-β-catenin dependent metabolic pathways, we utilized an NMR-based metabolomics approach to determine steady state levels of metabolites. We also interrogated altered metabolic pathway gene expression for prognostic capacity in breast cancer patient relapse-free and distant metastasis-free survival and discover a metabolic signature that is likely associated with recurrence.

RESULTS

RON-DEK-β-catenin loss showed a consistent metabolite regulation of succinate and phosphocreatine. Consistent metabolite alterations between RON and DEK loss (but not β-catenin) were found in media glucose consumption, lactate secretion, acetate secretion, and intracellular glutamine and glutathione levels. Consistent metabolite alterations between RON and β-catenin loss (and not DEK) were found only in intracellular lactate levels. Further pathway hits include β-catenin include glycolysis, glycosylation, TCA cycle/anaplerosis, NAD+ production, and creatine dynamics. Genes in these pathways epistatic to RON-DEK-β-catenin were used to define a gene signature that prognosticates breast cancer patient survival and response to chemotherapy.

CONCLUSIONS

The RON-DEK-β-catenin axis regulates the numerous metabolic pathways with significant associations to breast cancer patient outcomes.

Pan-cancer analysis of the prognostic and immunological role of ANLN: An onco-immunological biomarker

Anillin actin-binding protein (ANLN) is crucially involved in cell proliferation and migration. Moreover, ANLN is significantly in tumor progression in several types of human malignant tumors; however, it remains unclear whether ANLN acts through common molecular pathways within different tumor microenvironments, pathogeneses, prognoses and immunotherapy contexts. Therefore, this study aimed to perform bioinformatics analysis to examine the correlation of ANLN with tumor immune infiltration, immune evasion, tumor progression, immunotherapy, and tumor prognosis. We observed increased ANLN expression in multiple tumors, which could be involved in tumor cell proliferation, migration, infiltration, and prognosis. The level of ANLN methylation and genetic alteration was associated with prognosis in numerous tumors. ANLN facilitates tumor immune evasion through different mechanisms, which involve T-cell exclusion in different cancer types and tumor-infiltrating immune cells in colon adenocarcinoma, kidney renal clear cell carcinoma, liver hepatocellular carcinoma, and prostate adenocarcinoma. Additionally, ANLN is correlated with immune or chemotherapeutic outcomes in malignant cancers. Notably, ANLN expression may be a predictive biomarker for the response to immune checkpoint inhibitors. Taken together, our findings suggest that ANLN can be used as an onco-immunological biomarker and could serve as a hallmark for tumor screening, prognosis, individualized treatment design, and follow-up.

A Metabolic Gene Signature to Predict Breast Cancer Prognosis

Background: The existing metabolic gene signatures for predicting breast cancer outcomes only focus on gene expression data without considering clinical characteristics. Therefore, this study aimed to establish a predictive risk model combining metabolic enzyme genes and clinicopathological characteristics to predict the overall survival in patients with breast cancer.

Methods: Transcriptomics and corresponding clinical data for patients with breast cancer were downloaded from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. Differentially expressed metabolic genes between tumors and normal tissues were identified in the TCGA dataset (training dataset). A prognostic model was then built using univariate and multifactorial Cox proportional hazards regression analyses in the training dataset. The capability of the predictive model was then assessed using the receiver operating characteristic in both datasets. Pathway enrichment analysis and immune cell infiltration were performed using Kyoto Encyclopedia of Genes and Genomes (KEGG)/Gene Ontology (GO) enrichment and CIBERSORT algorithm, respectively.

Results: In breast cancer and normal tissues, 212 metabolic enzyme genes were differentially expressed. The predictive model included four factors: age, stage, and expression of SLC35A2 and PLA2G10. Patients with breast cancer were classified into high- and low-risk groups based on the model; the high-risk group had a significantly poorer overall survival rate than the low-risk group. Furthermore, the two risk groups showed different activation of pathways and alterations in the properties of tumor microenvironment-infiltrating immune cells.

Conclusion: We developed a powerful model to predict prognosis in patients with breast cancer by combining the gene expression of metabolic enzymes with clinicopathological characteristics.

Lipid Metabolism Regulation Based on Nanotechnology for Enhancement of Tumor Immunity

The hallmarks of cancer include dysregulated metabolism and immune evasion. As a basic way of metabolism, lipid metabolism is reprogrammed for the rapid energy and nutrient supply in the occurrence and development of tumors. Lipid metabolism alterations that occur in the tumor microenvironment (TME) affect the antitumor responses of immune cells and cause immune evasion. Therefore, targeting lipid metabolism in the TME for enhancing the antitumor effect of immune cells is a promising direction for cancer treatment. Cancer nanomedicine has great potential in regulating tumor metabolism and tumor immunity. This review summarizes the nanotechnology-based strategies for lipid metabolism regulation in the TME for enhanced anticancer immune responses.

Cancer immunoediting hypothesis: history, clinical implications and controversies

The main function of the immune system is to protect against infectious pathogens and to ensure tissue homeostasis. The latter function includes preventing autoimmune reactions, tolerizing cells to nonpathogenic environmental microorganisms, and eliminating apoptotic/damaged, transformed, or neoplastic cells. The process of carcinogenesis and tumor development and the role of the immune system in inhibiting progression of cancer have been the subject of intense research since the end of the 20^th century and resulted in formulation of the cancer immunoediting hypothesis. The hypothesis postulates three steps in oncogenesis: 1) elimination - corresponding to immunosurveillance, 2) equilibrium in which the growth of transformed or neoplastic cells is efficiently controlled by immune effector mechanisms, and 3) escape in which cancer progresses due to an ineffective antitumor response. In parallel, a new field of science - immune-oncology - has arisen. Attempts are also being made to quantify intra-tumoral and peritumoral T cell infiltrations and to define optimal immunological parameters for prognostic/predictive purposes in several types of cancer. The knowledge of relationships between the tumor and the immune system has been and is practically exploited therapeutically in the clinic to treat cancer. Immunotherapy is a standard or supplementary treatment in various types of cancer.