Metabolic adaptations of cancer in extreme tumor microenvironments

Nutrient-gene therapy as a strategy to enhance CAR T cell function and overcome barriers in the tumor microenvironment

Cancer immunotherapy is transforming the treatment landscape of both hematological and solid cancers. Although T-cell-based adoptive cell transfer (ACT) therapies have demonstrated initial success, several recurrent obstacles limit their long-term anti-tumor efficacy, including: (1) lack of antigen specificity; (2) poor long-term survival of transplanted T cells in vivo; and (3) a hostile tumor microenvironment (TME). While numerous approaches have been explored to enhance the antigen specificity of Chimeric Antigen Receptor (CAR) T-cell therapies, the field still lacks an effective strategy to optimize the long-term retention and in vivo expansion of engrafted T cells within the TME-a critical factor for the durable efficacy of T-cell-based immunotherapies for both blood and solid cancers. Here, we hypothesize that the success of CAR T-cell therapy can be enhanced by targeting donor T cells' ability to compete with cancer cells for key nutrients, thereby overcoming T-cell exhaustion and sustaining durable anti-tumor function in the TME. To explore this hypothesis, we first provide a comprehensively review of the current understanding of the metabolic interactions (e.g., glucose metabolism) between T cells and tumor cells. To address the challenges, we propose an innovative strategy: utilizing nutrient gene therapy (genetic overexpression of glucose transporter 1, GLUT1) to fortify the metabolic competency of adoptive CAR T-cells, deprive tumors of critical metabolites and ATP, and disrupt the TME. Altogether, our proposed approach combining precision medicine (adoptive CAR T-cell therapy) with tumor metabolism-targeting strategies offers a promising and cost-effective solution to enhance the efficacy and durability of ACT therapies, ultimately improving outcomes for cancer patients.

RNA‑seq analysis of predictive markers associated with glutamine metabolism in thyroid cancer

The incidence of thyroid cancer (TC) increases year by year. It is necessary to construct a prognostic model for risk stratification and management of TC patients. Glutamine metabolism is essential for tumor progression and the tumor microenvironment. The present study aimed to develop a predictive model for TC using a glutamine metabolism gene set. Differentially expressed genes in cells with high glutamine metabolism levels from single cell RNA‑sequencing data were compared with genes differentially expressed between normal and TC tissues from The Cancer Genome Atlas Program data. Through Boruta feature selection methods and multivariate Cox regression, six crucial genes were identified for a risk‑scoring system to develop a prognostic model. The role of each gene was verified in TC cells in vitro. A risk‑scoring system was developed according to the glutamine gene set to forecast the overall survival of TC patients. This risk score could stratify TC patients and minimize unnecessary surgeries and invasive treatments. In addition, signal induced proliferation associated 1 like 2 (SIPA1L2), an important gene in the prognostic model, knockdown in TPC‑1 and BCPAP cell lines enhanced TC cell proliferation, migration and invasion. A risk model was developed based on a glutamine metabolism gene set. The model has reference values for TC stratification.

The Diagnostic Value of Plasma Small Extracellular Vesicle-Derived CAIX Protein in Prostate Cancer and Clinically Significant Prostate Cancer: A Study on Predictive Models

BACKGROUND

Current diagnostic tools are inaccurate and not specific to prostate cancer (PCa) diagnosis. Cancer-derived small extracellular vehicles (sEVs) play a key role in intercellular communication. In this study, we examined the diagnostic value of plasma sEV-derived carbonic anhydrase IX (CAIX) protein for PCa and clinically significant prostate cancer (csPCa) diagnosis and avoiding unnecessary biopsies.

METHODS

Plasma samples (n = 230) were collected from the patients who underwent prostate biopsy with elevated prostate-specific antigen (PSA) levels. sEVs were isolated and characterized, and sEV protein CAIX was measured using an enzyme-linked immunosorbent assay. Independent predictors of csPCa (Gleason score ≥ 7) were identified, and a predictive model was established. A Nomogram for predicting csPCa was developed using data from the training cohort.

RESULTS

The expression of sEV protein CAIX was significantly higher in both PCa and csPCa compared to benign patients and nonsignificant PCa (nsPCa) (Gleason score < 7, p < 0.001). sEV protein CAIX performed well in distinguishing PCa from benign patients. The predictive model defined by sEV protein CAIX and PSA density (PSAD) demonstrated the highest discriminative ability for csPCa (AUC = 0.895), with diagnostic sensitivity and specificity of 82.5% and 85.8%, respectively. Furthermore, sEV protein CAIX is an effective predictor of 2-year biochemical recurrence (BCR) in PCa patients (p = 0.013), and its high expression is significantly associated with poorer BCR-free survival (p < 0.05).

CONCLUSIONS

Our findings demonstrate the excellent performance of sEV protein CAIX in PCa and csPCa diagnosis. The Nomogram-based csPCa predictive model incorporating sEV protein CAIX and PSAD exhibits strong predictive value. Additionally, assessing plasma sEV protein CAIX expression levels can further aid in evaluating patient prognosis and provide a basis for making effective treatment decisions.

Harnessing the Power of Metabolomics for Precision Oncology: Current Advances and Future Directions

Metabolic reprogramming is a hallmark of cancer, with cancer cells acquiring many unique metabolic traits to support malignant growth, and extensive intra- and inter-tumour metabolic heterogeneity. Understanding these metabolic characteristics presents opportunities in precision medicine for both diagnosis and therapy. However, despite its potential, metabolic phenotyping has lagged behind genetic, transcriptomic, and immunohistochemical profiling in clinical applications. This is partly due to the lack of a single experimental technique capable of profiling the entire metabolome, necessitating the use of multiple technologies and approaches to capture the full range of cancer metabolic plasticity. This review examines the repertoire of tools available for profiling cancer metabolism, demonstrating their applications in preclinical and clinical settings. It also presents case studies illustrating how metabolomic profiling has been integrated with other omics technologies to gain insights into tumour biology and guide treatment strategies. This information aims to assist researchers in selecting the most effective tools for their studies and highlights the importance of combining different metabolic profiling techniques to comprehensively understand tumour metabolism.

Metabolism Meets Translation: Dietary and Metabolic Influences on tRNA Modifications and Codon Biased Translation

Transfer RNA (tRNA) is not merely a passive carrier of amino acids, but an active regulator of mRNA translation controlling codon bias and optimality. The synthesis of various tRNA modifications is regulated by many "writer" enzymes, which utilize substrates from metabolic pathways or dietary sources. Metabolic and bioenergetic pathways, such as one-carbon (1C) metabolism and the tricarboxylic acid (TCA) cycle produce essential substrates for tRNA modifications synthesis, such as S-Adenosyl methionine (SAM), sulfur species, and α-ketoglutarate (α-KG). The activity of these metabolic pathways can directly impact codon decoding and translation via regulating tRNA modifications levels. In this review, we discuss the complex interactions between diet, metabolism, tRNA modifications, and mRNA translation. We discuss how nutrient availability, bioenergetics, and intermediates of metabolic pathways, modulate the tRNA modification landscape to fine-tune protein synthesis. Moreover, we highlight how dysregulation of these metabolic-tRNA interactions contributes to disease pathogenesis, including cancer, metabolic disorders, and neurodegenerative diseases. We also discuss the new emerging field of GlycoRNA biology drawing parallels from glycobiology and metabolic diseases to guide future directions in this area. Throughout our discussion, we highlight the links between specific modifications, their metabolic/dietary precursors, and various diseases, emphasizing the importance of a metabolism-centric tRNA view in understanding many pathologies. Future research should focus on uncovering the interplay between metabolism and tRNA in specific cellular and disease contexts. Addressing these gaps will guide new research into novel disease interventions.

Serum Starvation Enhances the Antitumor Activity of Natural Matrices: Insights into Bioactive Molecules from Dromedary Urine Extracts

Natural matrices have historically been a cornerstone in drug discovery, offering a rich source of structurally diverse and biologically active compounds. However, research on natural products often faces significant challenges due to the complexity of natural matrices, such as urine, and the limitations of bioactivity assessment assays. To ensure reliable insights, it is crucial to optimize experimental conditions to reveal the bioactive potential of samples, thereby improving the validity of statistical analyses. Approaches in metabolomics further strengthen this process by identifying and focusing on the most promising compounds within natural matrices, enhancing the precision of bioactive metabolite prioritization. In this study, we assessed the bioactivity of 17 dromedary urine samples on human renal cells under serum-reduced conditions (1%FBS) in order to minimize possible FBS-derived interfering factors. Using viability assays and Annexin V/PI staining, we found that the tumor renal cell lines Caki-1 and RCC-Shaw were more sensitive to the cytotoxic effects of the small molecules present in dromedary urine compared to non-tumor HK-2 cells. Employing NMR metabolomics analysis combined with detected in vitro activity, our statistical model highlights the presence of bioactive compounds in dromedary urine, such as azelaic acid and phenylacetyl glycine, underscoring its potential as a sustainable source of bioactive molecules within the framework of green chemistry and circular economy initiatives.

Metabolic crossroads: unravelling immune cell dynamics in gastrointestinal cancer drug resistance

Metabolic reprogramming within the tumor microenvironment (TME) plays a critical role in driving drug resistance in gastrointestinal cancers (GI), particularly through the pathways of fatty acid oxidation and glycolysis. Cancer cells often rewire their metabolism to sustain growth and reshape the TME, creating conditions such as nutrient depletion, hypoxia, and acidity that impair antitumor immune responses. Immune cells within the TME also undergo metabolic alterations, frequently adopting immunosuppressive phenotypes that promote tumor progression and reduce the efficacy of therapies. The competition for essential nutrients, particularly glucose, between cancer and immune cells compromises the antitumor functions of effector immune cells, such as T cells. Additionally, metabolic by-products like lactate and kynurenine further suppress immune activity and promote immunosuppressive populations, including regulatory T cells and M2 macrophages. Targeting metabolic pathways such as fatty acid oxidation and glycolysis presents new opportunities to overcome drug resistance and improve therapeutic outcomes in GI cancers. Modulating these key pathways has the potential to reinvigorate exhausted immune cells, shift immunosuppressive cells toward antitumor phenotypes, and enhance the effectiveness of immunotherapies and other treatments. Future strategies will require continued research into TME metabolism, the development of novel metabolic inhibitors, and clinical trials evaluating combination therapies. Identifying and validating metabolic biomarkers will also be crucial for patient stratification and treatment monitoring. Insights into metabolic reprogramming in GI cancers may have broader implications across multiple cancer types, offering new avenues for improving cancer treatment.

Metabolic reprogramming and therapeutic resistance in primary and metastatic breast cancer

Metabolic alterations, a hallmark of cancer, enable tumor cells to adapt to their environment by modulating glucose, lipid, and amino acid metabolism, which fuels rapid growth and contributes to treatment resistance. In primary breast cancer, metabolic shifts such as the Warburg effect and enhanced lipid synthesis are closely linked to chemotherapy failure. Similarly, metastatic lesions often display distinct metabolic profiles that not only sustain tumor growth but also confer resistance to targeted therapies and immunotherapies. The review emphasizes two major aspects: the mechanisms driving metabolic resistance in both primary and metastatic breast cancer, and how the unique metabolic environments in metastatic sites further complicate treatment. By targeting distinct metabolic vulnerabilities at both the primary and metastatic stages, new strategies could improve the efficacy of existing therapies and provide better outcomes for breast cancer patients.

CRYAB Promotes Colorectal Cancer Progression by Inhibiting Ferroptosis Through Blocking TRIM55-Mediated β-Catenin Ubiquitination and Degradation

BACKGROUND

α-Crystallin B (CRYAB) is a chaperone member of the HSPs family that protects proteins with which it interacts from degradation. This study aims to investigate the effect of CRYAB on the progression of colorectal cancer (CRC) and its underlying mechanism.

METHODS

CRYAB expression was evaluated in CRC tissues. Cell growth was tested by CCK-8 kit. Lipid reactive oxygen species (ROS) assays, lipid peroxidation assays, glutathione assays were used to assess the degree of cellular lipid peroxidation of CRC cells. The potential signal pathways of CRYAB were analyzed and verified by Western blot (WB) and immunoprecipitation (Co-IP).

RESULTS

CRYAB expression was elevated in CRC tissues and exhibited sensitivity and specificity in predicting CRC. Functionally, knockdown of CRYAB induced ferroptosis in CRC cells. Mechanistically, CRYAB binding prevented from β-catenin interacting with TRIM55, leading to an increase in β-catenin protein stability, which desensitized CRC cells to ferroptosis and ultimately accelerated cancer progression.

CONCLUSIONS

Targeting CRYAB might be a promising strategy to enhance ferroptosis and improve the efficacy of CRC therapy.

Inorganic Nanoparticle Functionalization Strategies in Immunotherapeutic Applications

Nanotechnology has been increasingly utilized in anticancer treatment owing to its ability of engineering functional nanocarriers that enhance therapeutic effectiveness while minimizing adverse effects. Inorganic nanoparticles (INPs) are prevalent nanocarriers to be customized for a wide range of anticancer applications, including theranostics, imaging, targeted drug delivery, and therapeutics, because they are advantageous for their superior biocompatibility, unique optical properties, and capacity of being modified via versatile surface functionalization strategies. In the past decades, the high adaptation of INPs in this emerging immunotherapeutic field makes them good carrier options for tumor immunotherapy and combination immunotherapy. Tumor immunotherapy requires targeted delivery of immunomodulating therapeutics to tumor locations or immunological organs to provoke immune cells and induce tumor-specific immune response while regulating immune homeostasis, particularly switching the tumor immunosuppressive microenvironment. This review explores various INP designs and formulations, and their employment in tumor immunotherapy and combination immunotherapy. We also introduce detailed demonstrations of utilizing surface engineering tactics to create multifunctional INPs. The generated INPs demonstrate the abilities of stimulating and enhancing the immune response, specific targeting, and regulating cancer cells, immune cells, and their resident microenvironment, sometimes along with imaging and tracking capabilities, implying their potential in multitasking immunotherapy. Furthermore, we discuss the promises of INP-based combination immunotherapy in tumor treatments.

Modifications of Nanobubble Therapy for Cancer Treatment

Cancer development is related to genetic mutations in primary cells, where 5-10% of all cancers are derived from acquired genetic defects, most of which are a consequence of the environment and lifestyle. As it turns out, over half of cancer deaths are due to the generation of drug resistance. The local delivery of chemotherapeutic drugs may reduce their toxicity by increasing their therapeutic dose at targeted sites and by decreasing the plasma levels of circulating drugs. Nanobubbles have attracted much attention as an effective drug distribution system due to their non-invasiveness and targetability. This review aims to present the characteristics of nanobubble systems and their efficacy within the biomedical field with special emphasis on cancer treatment. In vivo and in vitro studies on cancer confirm nanobubbles' ability and good blood capillary perfusion; however, there is a need to define their safety and side effects in clinical trials.

Lymph node metastasis regulation by peritumoral tonsillar tissue mitochondria-related pathway activation in oropharyngeal cancer

Immune-related gene expression profiles of peritumoral tonsillar tissues are modified by oropharyngeal cancer (OPC) nodal status. This study explored immunometabolism and immune cell count alterations in peritumoral tonsillar tissue according to OPC nodal status. Microarray data analysis of 27 peritumoral tonsillar tissue samples, using a newly generated mitochondrial metabolism-related gene set comprised of 948 genes, detected 228 differentially expressed genes (DEGs) (206 up- and 22 downregulated) in metastasis-negative cases compared to metastasis-positive ones. REACTOME pathway analysis of the 206 upregulated genes revealed the Toll-like receptor 4 cascade were most enriched. Immune cell proportion analysis using the CIBERSORTx algorithm revealed a significantly higher rate of naïve B cells, but lower rates of regulatory T cells and resting natural killer cells in metastasis-negative cases. Digital spatial profiling of the 6 OPC tissues detected 9 DEGs in the lymphoid regions, in contrast, no DEGs were identified in tumor regions according to nodal status. Cancer cell nests and pair matched normal epithelia mitochondrial DNA (mtDNA) from 5 OPC tissues were analyzed by next generation sequencing for variant detection. However, no significant mtDNA variation was found. This study identified mitochondria-related immune cell transcriptional programs and immune cell profiles associated with OPC lymphatic spread in peritumoral tonsil tissue, further evaluation of which will elucidate targetable immune mechanisms associated with OPC lymphatic dissemination.