Dietary elaidic acid boosts tumoral antigen presentation and cancer immunity via ACSL5

Bacteroides uniformis-generated hexadecanedioic acid ameliorates metabolic-associated fatty liver disease

Gut microbiota exerts a pivotal influence on the development of Metabolic Associated Fatty Liver Disease (MAFLD), although the specific contributions of individual bacterial strains and their metabolites remain poorly defined. We conducted stool shotgun metagenomic sequencing and plasma untargeted metabolomics in a large prospective cohort comprising 120 MAFLD patients and 120 matched healthy controls. The mechanisms and microbial-derived metabolites involved in MAFLD were further investigated through multi-omics analyses in vitro and in vivo. Distinct differences were identified in both the microbial community structure and metabolomic profiles between MAFLD patients and healthy controls. Bacteroides uniformis (B. uniformis) was the most significantly depleted species in MAFLD and negatively correlated with hepatic steatosis and BMI. MAFLD was characterized by marked disruptions in fatty acid and amino acid metabolism. Combined analysis of metabolomic and metagenomic data achieved high diagnostic accuracy for MAFLD and hepatic steatosis severity (AUC = 0.93). Transplantation of fecal microbiota from MAFLD subjects into ABX mice led to the onset of MAFLD-like symptoms, whereas B. uniformis administration alleviate disease progression by inhibiting intestinal fat absorption, FFA from eWAT influx into liver via the gut-liver axis, and IRE1α-XBP1s-mediated flipogenesis and ferroptosis, as confirmed by hepatic transcriptomic and proteomic analyses. Hexadecanedioic acid (HDA), potentially identified as a key metabolite produced by B. uniformis, ameliorated MAFLD symptoms. Mechanistically, B. uniformis-derived HDA also inhibited fat absorption and transported, and entered the liver via the portal vein to suppress IRE1α-XBP1s-mediated flipogenesis and ferroptosis. B. uniformis and its potential putative metabolite HDA may contribute to MAFLD progression modulation, through regulation of the IRE1α-XBP1s axis. This study provides new insights into the gut-liver axis in MAFLD and offers promising therapeutic targets based on specific microbes and their metabolites.

OTUB1 enhances fatty acid oxidation in APAP-induced liver injury by mediating ACSL5 deubiquitination

Overdosing on acetaminophen (APAP) is the primary cause of drug-induced liver injury. Recent studies have demonstrated that dysregulated lipid metabolism, particularly decreased fatty acid oxidation (FAO), is a key contributor to APAP-induced acute liver injury (AILI). OTU domain-containing ubiquitin aldehyde-binding protein 1 (OTUB1), a crucial member of the OTU deubiquitinase family, has been involved in the metabolic progression of multiple diseases. Nevertheless, its involvement in AILI as well as FAO remains unclear. Here, we aimed to elucidate the effects of OTUB1 on the regulation of FAO in AILI. Our investigation revealed decreased OTUB1 expression in AILI. OTUB1 overexpression not only alleviated liver injury but also improved FAO in vivo and in vitro. Conversely, opposite biochemical changes were observed in hepatocytes with OTUB1 knockdown. Mechanistically, long-chain acyl-CoA synthase 5 (ACSL5), which plays a crucial role in regulating FAO, was identified as a novel substrate of OTUB1 in AILI via mass spectrometry analysis. OTUB1 interacts with ACSL5 and promotes its deubiquitination and stability. Moreover, the protective effect of OTUB1 on FAO in AILI occurred via the deubiquitination of ACSL5. Overall, the present study revealed that the OTUB1-ACSL5 axis plays an essential role in regulating FAO during AILI progression and might be a novel target for therapeutic intervention.

HSV-1 alters lipid metabolism and induces lipid droplet accumulation in functionally impaired mouse dendritic cells

Herpes simplex virus type 1 (HSV-1) significantly impairs dendritic cell (DC) function, ultimately eliciting the death of these cells. Here, we sought to assess whether HSV-1 modulates lipid metabolism in mouse DCs as a mechanism of immune evasion. For this, we performed RT-qPCR gene arrays with ingenuity pathway analysis (IPA), RNA sequencing (RNA-seq) and gene set enrichment analysis (GSEA), confocal microscopy, transmission electron microscopy, ultra-high-performance liquid chromatography-quadrupole time-of-flight (UHPLC-QTOF) analysis, pharmacological inhibition of eight lipid-metabolism-related enzymes in HSV-1-infected DCs, co-cultures between virus-specific transgenic CD4+ and CD8+ T cells and HSV-1-infected DCs, and in vivo assays with mice. We found that HSV-1 significantly alters lipid metabolism in DCs and induces lipid droplet (LD) accumulation in these cells. Pharmacological inhibition of two particular lipid metabolism enzymes was found to partially restore DC function. Overall, these results suggest that lipid metabolism plays an important role in the impairment of DC function by HSV-1.

A machine learning-based glycolysis and fatty acid metabolism-related prognostic signature is constructed and identified ACSL5 as a novel marker inhibiting the proliferation of breast cancer

INTRODUCTION

A new perspective on cancer metabolism suggests that it varies by context and is diverse. Cancer metabolism reprogramming can create a heterogeneous microenvironment that affects immune cell infiltration and function, complicating the selection of treatment methods. However, the specifics of this relationship remain unclear in breast cancer. This research aims to explore how glycolysis and fatty acid metabolism (GF) influence the immune microenvironment and their predictive capabilities for immunotherapy responses and overall survival.

METHODS

We at first time identified 602 GF-related genes. Utilizing multiple datasets from various centers and employing 10 different machine learning algorithms, we developed a GF-related signature called GFSscore, driven by artificial intelligence.

RESULTS

The GFSscore served as an independent prognostic indicator and demonstrated greater robustness than other models. Its validity was validated through multiple databases. Our study found that breast cancer patients with a high GFSscore, indicative of a greater tendency towards glycolytic activity, experienced poorer prognosis due to immunosuppression from distinct immune evasion mechanisms. Conversely, those with a low GFSscore, more inclined towards fatty acid metabolism, had better outcomes. Additionally, the GFSscore has the potential to forecast how well a patient might respond to immunotherapy and their susceptibility to chemotherapy medications. Moreover, we found that the overexpressed ACSL5 gene inhibits the proliferation of BRCA through experiments.

CONCLUSIONS

The GFSscore may offer patients personalized therapy by identifying new therapeutic targets for tumors. By understanding the relationship between cancer metabolism and the immune microenvironment, we can better tailor treatments to individual patients.

Deciphering the Transcriptomic Complexity of Yak Skin Across Different Ages and Body Sites

Differences in skin and hair phenotypes between the scapular and ventral regions of yaks (Bos grunniens) are obvious and become more prominent with age. However, the genetic mechanism that causes differences in yak skin at different ages has not been reported. In this study, we investigated the transcriptomic profile of yak skin across different ages (0.5 years, 2.5 years, and 4.5 years) and body sites (scapular and ventral regions). Differential gene expression analysis was initially conducted to explore the transcriptomic differences in skin at different ages and different body sites. Subsequently, weighted gene co-expression network analysis (WGCNA) was employed to analyze the transcriptomic data comprehensively. The results showed that, among all comparison groups, the Y2.5_S vs. Y2.5_V group (regional comparison) exhibited the highest number of DEGs, with 491 genes (179 upregulated and 312 downregulated), followed by the Y2.5_V vs. Y0.5_V group (age comparison), which had 370 DEGs (103 upregulated and 267 downregulated). DEGs such as IGF2BP3, ADCY8, FOSL1, and S100A8 were found in all comparison groups of different ages, and multiple members of the HOX gene family including HOXC10, HOXA9, HOXA6, HOXB9, and HOXB6 were differentially expressed in comparison groups at different sites. Functional enrichment analysis showed that there were more obvious differences in immune function between different ages of skin and more obvious differences in endocrine function between different parts of skin. WGCNA revealed that genes related with immunity such as GLYATL2, ACSL5, and SPDEF were the core genes of the co-expression module associated with the scapula region, and multiple genes related to hair follicle development such as FOXN1, OVOL1, DLX3, HOXC13, and TCHH were found to be the hub genes of the co-expression module associated with the ventral region. Overall, our study provides valuable insights into the transcriptomic complexity of yak skin across different ages and body sites. The differential gene expression patterns and co-expression network modules identified in this study lay the foundation for further research on skin biology and adaptation mechanisms in yaks.

Fatty acid metabolism: The crossroads in intestinal homeostasis and tumor

Fatty acids (FAs) have various functions on cell regulation considering their abundant types and metabolic pathways. In addition, the relation between FA and other nutritional metabolism makes their functions more complex. As the first place for diet-derived FA metabolism, intestine is significantly influenced despite lack of clear conclusions due to the inconsistent findings. In this review, we discuss the regulation of fatty acid metabolism on the fate of intestinal stem cells in homeostasis and disorders, and also focus on the intestinal tumor development and treatment from the aspect of gut microbiota-epithelium-immune interaction. We summarize that the balances between FA oxidation and glycolysis, between oxidative phosphorylation and ketogenesis, between catabolism and anabolism, and the specific roles of individual FA types determine the diverse effects of intestinal FA metabolism in different cases. We hope this will inspire further dissection and suggest precise dietary/metabolic intervention for different demands related to intestinal health.

Phytochemical Characterization and Antioxidant Activity of Cajanus cajan Leaf Extracts for Nutraceutical Applications

Cajanus cajan (guandú) is a widely cultivated leguminous plant in Panama; however, its phytochemical composition remains underexplored. Traditionally used in Asia and Africa for its medicinal properties, the plant's bioactive compounds responsible for these benefits have not been fully identified. The phytochemical profile and antioxidant capacity of C. cajan leaf extracts from Panama were characterized, highlighting their potential applications. Ethanolic extracts obtained via ultrasonication were analyzed through phytochemical screening, confirming the presence of alkaloids, tannins, saponins, and steroids. Spectrophotometric analysis revealed high total phenolic (71 mg g-1) and flavonoid (30 mg g-1) contents. Antioxidant assays demonstrated significant 2,2'-azino-bis(3-ethylbenzothiazoline-6-sulfonic acid) radical cation (ABTS+) inhibition and 2,2-diphenyl-1-picrylhydrazyl (DPPH) radical scavenging activity. Gas chromatography-mass spectrometry (GC-MS) analysis identified 35 bioactive compounds in C. cajan leaves for the first time, including lupeol (antimicrobial and antitumor), lupenone (antidiabetic), squalene (antitumor and antioxidant), tocopherol (antioxidant), and β-amyrin (antibacterial and anti-Alzheimer's). These findings expand the known phytochemical profile of C. cajan, supporting its pharmaceutical, nutraceutical, and agro-industrial potential. Moreover, this research provides a foundation for further studies on the plant's bioactive compounds and their applications in human health and sustainable agriculture.

A lipid metabolism related gene signature predicts postoperative recurrence in pancreatic cancer through multicenter cohort validation

Postoperative recurrence of pancreatic adenocarcinoma (PAAD) remains a major challenge. This study aims to establish and validate a lipid metabolism-related prognostic model to predict recurrence in PAAD patients. The TCGA-PAAD database was used to establish a training cohort, which was validated using the ICGC database and multiple center cohorts. A prognostic model based on LASSO Cox regression and a nomogram was developed and further validated. Among 196 lipid metabolism-related genes, four were selected for the prognostic model. Patients were stratified into high- and low-risk groups based on the risk score. Univariate and multivariate Cox regression analyses showed that tumor site, T stage, N stage, M stage, and risk score were significantly associated with progression-free interval (PFI). High-risk patients had worse PFI, overall survival (OS), and disease-specific survival (DSS) (all P < 0.05). Time-dependent ROC and decision curve analyses confirmed the superior diagnostic capacity of the nomogram. GSEA revealed enrichment in G2M checkpoint, glycolysis, estrogen response, and hypoxia pathways for the high-risk group. Additionally, high-risk scores correlated with poor immune infiltration, gene mutations, and tumor mutational burden (TMB). Single-cell analysis suggested that risk genes interact with various cell types to promote PAAD progression. A novel lipid metabolism-related prognostic model was developed and validated to predict recurrence and survival in PAAD patients, with strong accuracy and stability.

A gene-based predictive model for lymph node metastasis in cervical cancer: superior performance over imaging techniques

OBJECTIVE

Lymph node metastasis (LNM) critically impacts the prognosis and treatment decisions of cervical cancer patients. The accuracy and sensitivity of current imaging techniques, such as CT and MRI, are limited in assessing lymph node status. This study aims to develop a more accurate and efficient method for predicting LNM.

METHODS

Three independent cohorts were merged and divided into training and internal validation groups, with our cohort and those from other centers serving as external validation. A predictive model for LNM in cervical cancer was established using the LASSO regression and multivariate logistic regression. The diagnostic performance of the predictive model was compared with that of CT/MRI in terms of accuracy, sensitivity, specificity, and AUC.

RESULTS

Using RNA-seq data, four independent predictive genes (MAPT, EPB41L1, ACSL5, and PRPF4B) were identified through LASSO regression and multivariate logistic regression, and a predictive model was constructed to calculate the LNM risk score. Compared with CT/MRI, the model demonstrated higher diagnostic efficiency, with an accuracy of 0.840 and sensitivity of 0.804, compared to CT/MRI's accuracy of 0.713 and sensitivity of 0.587. The predictive model corrected 81% of misdiagnoses by CT/MRI, demonstrating significant improvements in accuracy and sensitivity.

CONCLUSION

The predictive model developed in this study, based on gene expression data, significantly improves the preoperative assessment accuracy of LNM in cervical cancer. Compared to traditional imaging techniques, this model shows superior sensitivity and accuracy. This study provides a robust foundation for developing precise diagnostic tools, paving the way for future clinical applications in individualized treatment planning.

Metabolites and metabolic pathway reactions links to sensitization of immunotherapy in pan-cancer

Metabolic features are crucial in tumor immune interactions, but their relationship with antitumor immune responses is not yet fully understood. This study used Mendelian randomization analysis to identify the causal relationships between blood metabolites and immune cells and to evaluate the effects of metabolic pathways and reactions on antitumor immune responses in various cancers. Levels of 156 metabolites exhibited significant associations with selected immune cells. Metabolic enrichment analysis indicated laurate, propionyl-carnitine, carnitine and l-acetylcarnitine are enriched in fatty acid (FA) metabolism pathways. These enriched pathways are significantly correlated to CD8+ T cell function signatures in tumor environment and favor better prognostic outcomes. Metabolic reactions contributing to better immunotherapy responses were identified and used to establish the immuno-metabolic reaction score (IMRS). IMRS were significantly correlated to CD8+ T cell infiltration levels and CD8+ T cell signature scores in either 10× Visium spatial transcriptomic or RNA-seq samples. Finally, IMRS could significantly predict favorable survival outcomes in different cancer patients treated with immunotherapy. Our study revealed a link between certain metabolites and their related metabolic pathways to tumor immune landscape and immune functions. These results could promote the accurate stratification of patients before treatment and improve the efficacy of immunotherapy.

Niraparib restricts intraperitoneal metastases of ovarian cancer by eliciting CD36-dependent ferroptosis

Ovarian cancer (OC) is prone to peritoneum or omentum dissemination, thus giving rise to the formidable challenge of unresectable surgery and a dismal survival rate. Although niraparib holds a pivotal role in the maintenance treatment of OC, its effect on suppressing metastases during primary intervention remains enigmatic. Recently, we initiated a prospective clinical study (NCT04507841) in order to evaluate the therapeutic efficacy of neoadjuvant niraparib monotherapy for advanced OC with homologous recombination deficiency. An analysis of patient tumor burden before and after the niraparib challenge showed a remarkable vulnerability of OC intraperitoneal metastases to niraparib exposure. This killing capacity of niraparib was closely associated with the accumulation of fatty acids within the abdomen, which was confirmed by the increased susceptibility of tumor cells to niraparib treatment in the presence of fatty acids. In the context of abundant fatty acids, niraparib elevated intracellular levels of fatty acids and lipid peroxidation, leading to subsequent tumor cell ferroptosis in a p53 and BRCA-independent manner. Notably, under niraparib exposure, a critical fatty acid transporter CD36 was dramatically upregulated in tumors, facilitating excessive uptake of fatty acids. Pharmacological inhibition of either ferroptosis or CD36 impaired the anti-tumor activity of niraparib both in vitro and in murine intraperitoneal ID8 tumor models. Our findings demonstrate ferroptosis as a novel mechanism underlying the regression of OC metastases induced by niraparib, thereby offering tantalizing prospects for the frontline application of this agent in the management of OC.

Emerging insights into the impact of systemic metabolic changes on tumor-immune interactions

Tumors are inherently embedded in systemic physiology, which contributes metabolites, signaling molecules, and immune cells to the tumor microenvironment. As a result, any systemic change to host metabolism can impact tumor progression and response to therapy. In this review, we explore how factors that affect metabolic health, such as diet, obesity, and exercise, influence the interplay between cancer and immune cells that reside within tumors. We also examine how metabolic diseases influence cancer progression, metastasis, and treatment. Finally, we consider how metabolic interventions can be deployed to improve immunotherapy. The overall goal is to highlight how metabolic heterogeneity in the human population shapes the immune response to cancer.

Bioinformatics insights into ACSL1 and ACSL5: prognostic and immune roles in low-grade glioma

BACKGROUND

Fatty acid metabolism disruptions affect low-grade gliomas (LGGs), with glioma cells depending on fatty acids for survival. Targeting fatty acid oxidation through the acyl-coenzyme A synthetase long-chain (ACSL) family could alleviate glioma growth and improve prognosis management. However, the integration of ACSLs for analyzing their relationship with LGGs remains unexplored.

METHODS

We collected RNA expression data of ACSLs for LGGs from TCGA, GTEx, CGGA, and GEO datasets and validated the prognostic significance of gene expression in 37 glioma samples. DNA methylation data from UCSC Xena and promoter methylation levels via MEXPRESS were analyzed. Functional enrichments of co-expressed ACSLs genes were conducted using Gene Ontology, Kyoto Encyclopedia of Genes and Genomes, and Gene Set Enrichment Analysis. Protein-protein interaction networks were established via GeneMANIA, and cBioPortal assessed somatic mutations and copy number variations of ACSLs in LGGs. TIMER and TISIDB databases investigated the correlation between ACSLs expression and immune infiltration and checkpoint genes. Hazard ratios (HR) with 95% confidence intervals (95% CI) were computed, and net reclassification index and integrated discrimination improvement were estimated to evaluate the predictive capability of the prognosis model.

RESULTS

Independent prognostic factors for overall survival included age, gender, tumor grade, MGMT promoter status, ACSL1, ACSL3, ACSL5, and ACSL6 expression levels. High ACSL1 (HR = 2.352, 95%CI: 1.647-3.359, P = 9.00E-06), ACSL3 (HR = 2.367, 95%CI: 1.547-3.624, P = 2.92E-04) and ACSL5 (HR = 2.329, 95%CI: 1.611-3.367, P = 2.80E-05) expression correlated with poor prognosis, while increased ACSL6 (HR = 0.449, 95%CI: 0.290-0.696, P = 1.02E-03) expression related to better survival rates. Furthermore, these associations were also confirmed in the validation datasets and our external cohort. Negative correlation between ACSL1 and ACSL3 gene expression and methylation was found. Functional enrichment analyses highlighted the roles of ACSL1 and ACSL5 in glioma mechanisms and immune function, with significant associations between somatic CNVs and immune cell infiltration.

CONCLUSIONS

ACSL1 and ACSL5 exhibit prognostic significance in gliomas and influence tumor immunity and immune cell migration, providing valuable insights into LGG prognosis and therapeutic targets.

Microbiome and metabolome analysis in smoking and non-smoking pancreatic ductal adenocarcinoma patients

BACKGROUND

Smoking is a significant risk factor for pancreatic ductal adenocarcinoma (PDAC). This study aimed to investigate the effects of smoking on the pancreatic microbiome and metabolome in resectable and unresectable male PDAC patients.

METHODS

The pancreatic tissue samples were collected from resectable PDACs via surgery and unresectable PDACs via endoscopic ultrasound fine needle aspiration (EUS-FNA). Surgical samples obtained from 10 smoking and 6 non-smoking PDACs were measured by 16S ribosomal RNA (16S rRNA) gene sequencing and liquid chromatography-mass spectrometry (LC/MS). Fine needle aspiration (FNA) samples obtained from 20 smoking and 14 non-smoking PDACs were measured by 16S rRNA gene sequencing.

RESULTS

From resectable to unresectable patients, the dominant genus in the pancreas changed from Achromobacter to Delftia. Smoking further altered the abundance of specific bacteria, mainly manifested as an increase of Slackia in surgical tumor tissue of the smoking group, and an enrichment of Aggregatibacter and Peptococcus in FNA samples of the smoking group. In tumor tissue, smoking caused an enrichment of the cancer-promoting cAMP signaling pathway and L-lactic acid. In paracancerous tissue, smoking also induced a detrimental disturbance in the pancreatic microbiome and metabolome, including an enrichment of Veillonella, Novosphingobium, Deinococcus, and 3-hydroxybutanoic acid, and a reduction of linoleic acid. Besides, the cancer-promoting L-lactic acid was negatively correlated with Faecalibacterium in tumor tissue based on the correlation analysis.

CONCLUSION

There were differences in the pancreatic microbiome of PDAC patients at different stages, and smoking can further disrupt the pancreatic microbiome and metabolism in PDAC.

Eating for immunity: how diet shapes our defenses

Emerging studies on the diet-immune axis have uncovered novel dietary immune regulators and identified crucial targets and pathways mediating the crosstalk between specific dietary components and diverse immune cell populations. Here, we discuss the recent discovery and mechanisms by which diet-derived components, such as vitamins, amino acids, fatty acids, and antioxidants, could impact immune cell metabolism, alter signaling pathways, and reprogram the overall cellular responses. We also note crucial considerations that need to be tackled to make these findings clinically relevant, acknowledging that our current understanding often relies on simplified models that may not adequately represent the intricate network of factors influencing the diet-immune axis at the whole organism level. Overall, our growing understanding of how diet shapes our defenses underscores the importance of lifestyle choices and illuminates the potential to fine-tune immune responses through targeted nutritional strategies, thereby fortifying the immune system and bolstering our defenses against diseases.

Immune Alterations with Aging: Mechanisms and Intervention Strategies

Aging is the result of a complex interplay of physical, environmental, and social factors, leading to an increased prevalence of chronic age-related diseases that burden health and social care systems. As the global population ages, it is crucial to understand the aged immune system, which undergoes declines in both innate and adaptive immunity. This immune decline exacerbates the aging process, creating a feedback loop that accelerates the onset of diseases, including infectious diseases, autoimmune disorders, and cancer. Intervention strategies, including dietary adjustments, pharmacological treatments, and immunomodulatory therapies, represent promising approaches to counteract immunosenescence. These interventions aim to enhance immune function by improving the activity and interactions of aging-affected immune cells, or by modulating inflammatory responses through the suppression of excessive cytokine secretion and inflammatory pathway activation. Such strategies have the potential to restore immune homeostasis and mitigate age-related inflammation, thus reducing the risk of chronic diseases linked to aging. In summary, this review provides insights into the effects and underlying mechanisms of immunosenescence, as well as its potential interventions, with particular emphasis on the relationship between aging, immunity, and nutritional factors.

Targeting ACSLs to modulate ferroptosis and cancer immunity

Five acyl-CoA synthetase long-chain family members (ACSLs) are responsible for catalyzing diverse long-chain fatty acids (LCFAs) into LCFA-acyl-coenzyme A (CoA) for their subsequent metabolism, including fatty acid oxidation (FAO), lipid synthesis, and protein acylation. In this review, we focus on ACSLs and their LCFA substrates and introduce their involvement in regulation of cancer proliferation, metastasis, and therapeutic resistance. Along with the recognition of the decisive role of ACSL4 in ferroptosis - an immunogenic cell death (ICD) initiated by lipid peroxidation - we review the functions of ACSLs on regulating ferroptosis sensitivity. Last, we discuss the current understanding of ACSL on the antitumor immune response. We emphasize the necessity to explore the functions of immune cells expressing ACSLs for developing novel strategies to augment immunotherapy by targeting ACSL.

NPM1 inhibits tumoral antigen presentation to promote immune evasion and tumor progression

BACKGROUND

Tumor cells develop multiple mechanisms to facilitate their immune evasion. Identifying tumor-intrinsic factors that support immune evasion may provide new strategies for cancer immunotherapy. We aimed to explore the function and the mechanism of the tumor-intrinsic factor NPM1, a multifunctional nucleolar phosphoprotein, in cancer immune evasion and progression.

METHODS

The roles of NPM1 in tumor progression and tumor microenvironment (TME) reprogramming were examined by subcutaneous inoculation of Npm1-deficient tumor cells into syngeneic mice, and then explored by CyTOF, flow cytometry, immunohistochemistry staining, and RNA-seq. The in-vitro T-cell killing of OVA-presenting tumor cells by OT-1 transgenic T cells was observed. The interaction of NPM1 and IRF1 was verified by Co-IP. The regulation of NPM1 in IRF1 DNA binding to Nlrc5, Ciita promoter was determined by dual-luciferase reporter assay and ChIP-qPCR.

RESULTS

High levels of NPM1 expression predict low survival rates in various human tumors. Loss of NPM1 inhibited tumor progression and enhanced the survival of tumor-bearing mice. Npm1-deficient tumors showed increased CD8+ T cell infiltration and activation alongside the reduced presence of immunosuppressive cells. Npm1 deficiency increased MHC-I and MHC-II molecules and specific T-cell killing. Mechanistically, NPM1 associates with the transcription factor IRF1 and then sequesters IRF1 from binding to the Nlrc5 and Ciita promoters to suppress IRF1-mediated expression of MHC-I and MHC-II molecules in tumor cells.

CONCLUSIONS

Tumor-intrinsic NPM1 promotes tumor immune evasion via suppressing IRF1-mediated antigen presentation to impair tumor immunogenicity and reprogram the immunosuppressive TME. Our study identifies NPM1 as a potential target for improving cancer immunotherapy.

Spatiotemporal metabolomic approaches to the cancer-immunity panorama: a methodological perspective

Metabolic reprogramming drives the development of an immunosuppressive tumor microenvironment (TME) through various pathways, contributing to cancer progression and reducing the effectiveness of anticancer immunotherapy. However, our understanding of the metabolic landscape within the tumor-immune context has been limited by conventional metabolic measurements, which have not provided comprehensive insights into the spatiotemporal heterogeneity of metabolism within TME. The emergence of single-cell, spatial, and in vivo metabolomic technologies has now enabled detailed and unbiased analysis, revealing unprecedented spatiotemporal heterogeneity that is particularly valuable in the field of cancer immunology. This review summarizes the methodologies of metabolomics and metabolic regulomics that can be applied to the study of cancer-immunity across single-cell, spatial, and in vivo dimensions, and systematically assesses their benefits and limitations.

Acyl-CoA Synthetase Long-Chain Isoenzymes in Kidney Diseases: Mechanistic Insights and Therapeutic Implications

Long-chain acyl-CoA synthetases (ACSLs) are pivotal enzymes in fatty acid metabolism, essential for maintaining cellular homeostasis and energy production. Recent research has uncovered their significant involvement in the pathophysiology of various kidney diseases, including acute kidney injury (AKI), chronic kidney disease (CKD), diabetic kidney disease (DKD), and renal cell carcinoma (RCC). While ACSL1, ACSL3, ACSL4, and ACSL5 have been extensively studied for their roles in processes such as ferroptosis, lipid peroxidation, renal fibrosis, epithelial-mesenchymal transition, and tumor progression, the role of ACSL6 in kidney diseases remain largely unexplored. Notably, these isoenzymes exhibit distinct functions in different kidney diseases. Therefore, to provide a comprehensive understanding of their involvement, this review highlights the molecular pathways influenced by ACSLs and their roles in modulating cell death, inflammation, and fibrosis during kidney disease progression. By examining these mechanisms in detail, this review underscores the potential of ACSLs as biomarkers and therapeutic targets, advocating for further research to elucidate the precise roles of individual ACSL isoenzymes in kidney disease progression. Understanding these mechanisms opens new avenues for developing targeted interventions and improving therapeutic outcomes for patients with kidney diseases.

Deciphering fatty acid biosynthesis-driven molecular subtypes in pancreatic ductal adenocarcinoma with prognostic insights

PURPOSE

Pancreatic ductal adenocarcinoma (PDAC) poses a significant challenge due to its high heterogeneity and aggressiveness. Recognizing the urgency to delineate molecular subtypes, our study focused on the emerging field of lipid metabolism remodeling in PDAC, particularly exploring the prognostic potential and molecular classification associated with fatty acid biosynthesis.

METHODS

Gene set variation analysis (GSVA) and single-sample gene set enrichment analysis (ssGSEA) were performed to evaluate the dysregulation of lipid metabolism in PDAC. Univariate cox analysis and the LASSO module were used to build a prognostic risk score signature. The distinction of gene expression in different risk groups was explored by the Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis and Weighted Gene Co-expression Network Analysis (WGCNA). The biological function of Acyl-CoA Synthetase Long Chain Family Member 5 (ACSL5), a pivotal gene within 7-hub gene signature panel, was validated through in vitro assays.

RESULTS

Our study identified a 7-hub gene signature associated with fatty acid biosynthesis-related genes (FRGs), providing a robust tool for prognosis prediction. The high-FRGs score group displayed a poorer prognosis, decreased immune cell infiltration, and a higher tumor mutation burden. Interestingly, this group exhibited enhanced responsiveness to various compounds according to the Genomics of Drug Sensitivity in Cancer (GDSC) database. Notably, ACSL5 was upregulated in PDAC and essential for tumor progression.

CONCLUSION

In conclusion, our research defined two novel fatty acid biosynthesis-based subtypes in PDAC, characterized by distinct transcriptional profiles. These subtypes not only served as prognostic indicator, but also offered valuable insights into their metastatic propensity and therapeutic potential.