Lipids and cancer: Emerging roles in pathogenesis, diagnosis and therapeutic intervention

High expression of SLC27A2 predicts unfavorable prognosis and promotes inhibitory immune infiltration in acute lymphoblastic leukemia

Solute carrier family 27 member 2 (SLC27A2) is involved in fatty acid metabolism in tumors and represents a prospective target for cancer therapy. However, the role and mechanism of action of SLC27A2 in acute lymphoblastic leukemia (ALL) remain unclear. In this study, we aimed to explore the intrinsic associations between SLC27A2 and ALL and evaluate the prognostic significance, biological functions, and correlation with immune infiltration. We used the transcriptome and clinical data from the TARGET dataset. Differentially expressed genes (DEGs) in the SLC27A2 low- and high-expression groups were analyzed for prognostic implications and functional enrichment. Furthermore, we analyzed the relationship between SLC27A2 gene expression and immune cell infiltration using the ESTIMATE method, which was evaluated using the TIGER platform. Finally, we knocked down SLC27A2 in the Jurkat ALL cell line and conducted cell proliferation, western blotting, flow cytometry, and CCK-8 assays to elucidate the biological function of SLC27A2 in ALL. Patients with ALL who have higher expression levels of SLC27A2 have poorer overall survival and event-free survival. According to gene set enrichment analysis, the DEGs were primarily enriched with immune system processes and the PI3K-Akt signaling pathway. There was an inverse relationship between SLC27A2 expression and immune cell invasion, suggesting involvement of the former in tumor immune evasion. In vitro experiments showed that knockdown of SLC27A2 inhibited cell proliferation and protein expression and altered the Akt pathway, with a reduced proportion of B cells. In conclusion, SLC27A2 plays a vital role in the development of ALL.

Should the standard model of cellular energy metabolism be reconsidered? Possible coupling between the pentose phosphate pathway, glycolysis and extra-mitochondrial oxidative phosphorylation

The process of cellular respiration occurs for energy production through catabolic reactions, generally with glucose as the first process step. In the present work, we introduce a novel concept for understanding this process, based on our conclusion that glucose metabolism is coupled to the pentose phosphate pathway (PPP) and extra-mitochondrial oxidative phosphorylation in a closed-loop process. According to the current standard model of glycolysis, glucose is first converted to glucose 6-phosphate (glucose 6-P) and then to fructose 6-phosphate, glyceraldehyde 3-phosphate and pyruvate, which then enters the Krebs cycle in the mitochondria. However, it is more likely that the pyruvate will be converted to lactate. In the PPP, glucose 6-P is branched off from glycolysis and used to produce NADPH and ribulose 5-phosphate (ribulose 5-P). Ribulose 5-P can be converted to fructose 6-P and glyceraldehyde 3-P. In our view, a circular process can take place in which the ribulose 5-P produced by the PPP enters the glycolysis pathway and is then retrogradely converted to glucose 6-P. This process is repeated several times until the complete degradation of glucose 6-P. The role of mitochondria in this process is to degrade lipids by beta-oxidation and produce acetyl-CoA; the function of producing ATP appears to be only secondary. This proposed new concept of cellular bioenergetics allows the resolution of some previously unresolved controversies related to cellular respiration and provides a deeper understanding of metabolic processes in the cell, including new insights into the Warburg effect.

Tanshinone IIA acts as a regulator of lipogenesis to overcome osimertinib acquired resistance in lung cancer

Osimertinib is a novel epidermal growth factor receptor tyrosine kinase inhibitor (EGFR-TKI), acting as the first-line medicine for advanced EGFR-mutated NSCLC. Recently, the acquired resistance to osimertinib brings great challenges to the advanced treatment. Therefore, it is in urgent need to find effective strategy to overcome osimertinib acquired resistance. Here, we demonstrated that SREBP pathway-driven lipogenesis was a key mediator to promote osimertinib acquired resistance, and firstly found Tanshinone IIA (Tan IIA), a natural pharmacologically active constituent isolated from Salvia miltiorrhiza, could overcome osimertinib-acquired resistance in vitro and in vivo via inhibiting SREBP pathway-mediated lipid lipogenesis by using LC-MS based cellular lipidomics analysis, quantitative real-time PCR (qRT-PCR) analysis, western blotting analysis, flow cytometry, small interfering RNAs transfection, and membrane fluidity assay et al. The results showed that SREBP1/2-driven lipogenesis was highly activated in osimertinib acquired resistant NSCLC cells, while knockdown or inhibition of SREBP1/2 could restore the sensitivity of NSCLC to osimertinib via altered the proportion of saturated phospholipids and unsaturated phospholipids in osimertinib acquired-resistant cells. Furthermore, Tanshinone IIA (Tan IIA) could reverse the acquired resistance to osimertinib in lung cancer. Mechanically, Tan IIA inhibited SREBP signaling mediated lipogenesis, changed the profiles of saturated phospholipids and unsaturated phospholipids, and thus promoted osimertinib acquired resistant cancer cells to be attacked by oxidative stress-induced damage and reduce the cell membrane fluidity. The reversal effect of Tan IIA on osimertinib acquired resistant NSCLC cells was also confirmed in vivo, which is helpful for the development of strategies to reverse osimertinib acquired resistance.

Prognostic potential of lipid profiling in cancer patients: a systematic review of mass spectrometry-based studies

Cancer prognosis remains a critical clinical challenge. Lipidomic analysis via mass spectrometry (MS) offers the potential for objective prognostic prediction, leveraging the distinct lipid profiles of cancer patient-derived specimens. This review aims to systematically summarize the application of MS-based lipidomic analysis in prognostic prediction for cancer patients. Our systematic review summarized 38 studies from the past decade that attempted prognostic prediction of cancer patients through lipidomics. Commonly analyzed cancers included colorectal, prostate, and breast cancers. Liquid (serum and urine) and tissue samples were equally used, with liquid chromatography-tandem MS being the most common analytical platform. The most frequently evaluated prognostic outcomes were overall survival, stage, and recurrence. Thirty-eight lipid markers (including phosphatidylcholine, ceramide, triglyceride, lysophosphatidylcholine, sphingomyelin, phosphatidylethanolamine, diacylglycerol, phosphatidic acid, phosphatidylserine, lysophosphatidylethanolamine, lysophosphatidic acid, dihydroceramide, prostaglandin, sphingosine-1-phosphate, phosphatidylinosito, fatty acid, glucosylceramide and lactosylceramide) were identified as prognostic factors, demonstrating potential for clinical application. In conclusion, the potential for developing lipidomics in cancer prognostic prediction was demonstrated. However, the field is still nascent, necessitating future studies for validating and establishing lipid markers as reliable prognostic tools in clinical practice.

Phospholipase PLA2G7 is complementary to GPX4 in mitigating punicic-acid-induced ferroptosis in prostate cancer cells

Ferroptosis is a cell death pathway that can be promoted by peroxidizable polyunsaturated fatty acids in cancer cells. Here, we investigated the mechanisms underlying the toxicity of punicic acid (PunA), an isomer of conjugated linolenic acids (CLnAs) bearing three conjugated double bonds highly prone to peroxidation, on prostate cancer (PCa) cells. PunA induced ferroptosis in PCa cells and triggered massive lipidome remodeling, more strongly in PC3 androgen-negative cells than in androgen-positive cells. The greater sensitivity of androgen-negative cells to PunA was associated with lower expression of glutathione peroxidase 4 (GPX4). We then identified the phospholipase PLA2G7 as a PunA-induced ferroptosis suppressor in PCa cells. Overexpressing PLA2G7 decreased lipid peroxidation levels, suggesting that PLA2G7 hydrolyzes hydroperoxide-containing phospholipids, thus preventing ferroptosis. Importantly, overexpressing both PLA2G7 and GPX4 strongly prevented PunA-induced ferroptosis in androgen-negative PCa cells. This study shows that PLA2G7 acts complementary to GPX4 to protect PCa cells from CLnA-induced ferroptosis.

Spray-Dried Nanolipid Powders for Pulmonary Drug Delivery: A Comprehensive Mini Review

Lung diseases have received great attention in the past years because they contribute approximately one-third of the total global mortality. Pulmonary drug delivery is regarded as one of the most appealing routes to treat lung diseases. It addresses numerous drawbacks linked to traditional dosage forms. It presents notable features, such as, for example, a non-invasive route, localized lung drug delivery, low enzymatic activity, low drug degradation, higher patient compliance, and avoiding first-pass metabolism. Therefore, the pulmonary route is commonly explored for delivering drugs both locally and systemically. Inhalable nanocarrier powders, especially, lipid nanoparticle formulations, including solid-lipid and nanostructured-lipid nanocarriers, are attracting considerable interest in addressing respiratory diseases thanks to their significant advantages, including deep lung deposition, biocompatibility, biodegradability, mucoadhesion, and controlled drug released. Spray drying is a scalable, fast, and commercially viable technique to produce nanolipid powders. This review highlights the ideal criteria for inhalable spray-dried SLN and NLC powders for the pulmonary administration route. Additionally, the most promising inhalation devices, known as dry powder inhalers (DPIs) for the pulmonary delivery of nanolipid powder-based medications, and pulmonary applications of SLN and NLC powders for treating chronic lung conditions, are considered.

Cutaneous squamous cell carcinoma characterized by MALDI mass spectrometry imaging in combination with machine learning

Cutaneous squamous cell carcinoma (SCC) is an increasingly prevalent global health concern. Current diagnostic and surgical methods are reliable, but they require considerable resources and do not provide metabolomic insight. Matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI) enables detailed, spatially resolved metabolomic analysis of tissue samples. Integrated with machine learning, MALDI-MSI could yield detailed information pertaining to the metabolic alterations characteristic for SCC. These insights have the potential to enhance SCC diagnosis and therapy, improving patient outcomes while tackling the growing disease burden. This study employs MALDI-MSI data, labelled according to histology, to train a supervised machine learning model (logistic regression) for the recognition and delineation of SCC. The model, based on data acquired from discrete tumor sections (n = 25) from a mouse model of SCC, achieved a predictive accuracy of 92.3% during cross-validation on the labelled data. A pathologist unacquainted with the dataset and tasked with evaluating the predictive power of the model in the unlabelled regions, agreed with the model prediction for over 99% of the tissue areas. These findings highlight the potential value of integrating MALDI-MSI with machine learning to characterize and delineate SCC, suggesting a promising direction for the advancement of mass spectrometry techniques in the clinical diagnosis of SCC and related keratinocyte carcinomas.

Longitudinal molecular profiling elucidates immunometabolism dynamics in breast cancer

Although metabolic reprogramming within tumor cells and tumor microenvironment (TME) is well described in breast cancer, little is known about how the interplay of immune state and cancer metabolism evolves during treatment. Here, we characterize the immunometabolic profiles of tumor tissue samples longitudinally collected from individuals with breast cancer before, during and after neoadjuvant chemotherapy (NAC) using proteomics, genomics and histopathology. We show that the pre-, on-treatment and dynamic changes of the immune state, tumor metabolic proteins and tumor cell gene expression profiling-based metabolic phenotype are associated with treatment response. Single-cell/nucleus RNA sequencing revealed distinct tumor and immune cell states in metabolism between cold and hot tumors. Potential drivers of NAC based on above analyses were validated in vitro. In summary, the study shows that the interaction of tumor-intrinsic metabolic states and TME is associated with treatment outcome, supporting the concept of targeting tumor metabolism for immunoregulation.

Metabolic Rewiring in Cancer: Small Molecule Inhibitors in Colorectal Cancer Therapy

Alterations in cellular metabolism, such as dysregulation in glycolysis, lipid metabolism, and glutaminolysis in response to hypoxic and low-nutrient conditions within the tumor microenvironment, are well-recognized hallmarks of cancer. Therefore, understanding the interplay between aerobic glycolysis, lipid metabolism, and glutaminolysis is crucial for developing effective metabolism-based therapies for cancer, particularly in the context of colorectal cancer (CRC). In this regard, the present review explores the complex field of metabolic reprogramming in tumorigenesis and progression, providing insights into the current landscape of small molecule inhibitors targeting tumorigenic metabolic pathways and their implications for CRC treatment.

Role of carboxylesterase and arylacetamide deacetylase in drug metabolism, physiology, and pathology

Carboxylesterases (CES1 and CES2) and arylacetamide deacetylase (AADAC), which are expressed primarily in the liver and/or gastrointestinal tract, hydrolyze drugs containing ester and amide bonds in their chemical structure. These enzymes often catalyze the conversion of prodrugs, including the COVID-19 drugs remdesivir and molnupiravir, to their pharmacologically active forms. Information on the substrate specificity and inhibitory properties of these enzymes, which would be useful for drug development and toxicity avoidance, has accumulated. Recently,in vitroandin vivostudies have shown that these enzymes are involved not only in drug hydrolysis but also in lipid metabolism. CES1 and CES2 are capable of hydrolyzing triacylglycerol, and the deletion of their orthologous genes in mice has been associated with impaired lipid metabolism and hepatic steatosis. Adeno-associated virus-mediated human CES overexpression decreases hepatic triacylglycerol levels and increases fatty acid oxidation in mice. It has also been shown that overexpression of CES enzymes or AADAC in cultured cells suppresses the intracellular accumulation of triacylglycerol. Recent reports indicate that AADAC can be up- or downregulated in tumors of various organs, and its varied expression is associated with poor prognosis in patients with cancer. Thus, CES and AADAC not only determine drug efficacy and toxicity but are also involved in pathophysiology. This review summarizes recent findings on the roles of CES and AADAC in drug metabolism, physiology, and pathology.

Serum Lipidome Profiling Reveals a Distinct Signature of Ovarian Cancer in Korean Women

BACKGROUND

Distinguishing ovarian cancer from other gynecological malignancies is crucial for patient survival yet hindered by non-specific symptoms and limited understanding of ovarian cancer pathogenesis. Accumulating evidence suggests a link between ovarian cancer and deregulated lipid metabolism. Most studies have small sample sizes, especially for early-stage cases, and lack racial/ethnic diversity, necessitating more inclusive research for improved ovarian cancer diagnosis and prevention.

METHODS

Here, we profiled the serum lipidome of 208 ovarian cancer, including 93 early-stage patients with ovarian cancer and 117 nonovarian cancer (other gynecological malignancies) patients of Korean descent. Serum samples were analyzed with a high-coverage liquid chromatography high-resolution mass spectrometry platform, and lipidome alterations were investigated via statistical and machine learning (ML) approaches.

RESULTS

We found that lipidome alterations unique to ovarian cancer were present in Korean women as early as when the cancer is localized, and those changes increase in magnitude as the diseases progresses. Analysis of relative lipid abundances revealed specific patterns for various lipid classes, with most classes showing decreased abundance in ovarian cancer in comparison with other gynecological diseases. ML methods selected a panel of 17 lipids that discriminated ovarian cancer from nonovarian cancer cases with an AUC value of 0.85 for an independent test set.

CONCLUSIONS

This study provides a systemic analysis of lipidome alterations in human ovarian cancer, specifically in Korean women.

IMPACT

Here, we show the potential of circulating lipids in distinguishing ovarian cancer from nonovarian cancer conditions.

Mechanism of fibroblast growth factor 1 regulating fatty liver disorder in mule ducks

Mule ducks tend to accumulate abundant fat in their livers via feeding, which leads to the formation of a fatty liver that is several times larger than a normal liver. However, the mechanism underlying fatty liver formation has not yet been elucidated. Fibroblast growth factor 1 (FGF1), a member of the FGF superfamily, is involved in cellular lipid metabolism and mitosis. This study aims to investigate the regulatory effect of FGF1 on lipid metabolism disorders induced by complex fatty acids in primary mule duck liver cells and elucidate the underlying molecular mechanism. Hepatocytes were induced by adding 1,500:750 µmol/L oleic and palmitic acid concentrations for 36 h, which were stimulated with FGF1 concentrations of 0, 10, 100, and 1000 ng/mL for 12 h. The results showed that FGF1 significantly reduced the hepatic lipid droplet deposition and triglyceride content induced by complex fatty acids; it also reduced oxidative stress; decreased reactive oxygen species fluorescence intensity and malondialdehyde content; upregulated the expression of antioxidant factors nuclear factor erythroid 2 related factor 2 (Nrf2), HO-1, and NQO-1; significantly enhanced liver cell activity; promoted cell cycle progression; inhibited cell apoptosis; upregulated cyclin-dependent kinase 1 (CDK1) and BCL-2 mRNA expression; and downregulated Bax and Caspase-3 expression. In addition, FGF1 promoted AMPK phosphorylation, activated the AMPK pathway, upregulated AMPK gene expression, and downregulated the expression of SREBP1 and ACC1 genes, thereby alleviating excessive fat accumulation in liver cells induced by complex fatty acids. In summary, FGF1 may alleviate lipid metabolism disorders induced by complex fatty acids in primary mule duck liver cells by activating the AMPK signaling pathway.

Identification of Plasma Lipid Alterations Associated with Melanoma Metastasis

The aim of this study was to apply a state-of-the-art quantitative lipidomic profiling platform to uncover lipid alterations predictive of melanoma progression. Our study included 151 melanoma patients; of these, 83 were without metastasis and 68 with metastases. Plasma samples were analyzed using a targeted Lipidyzer™ platform, covering 13 lipid classes and over 1100 lipid species. Following quality control filters, 802 lipid species were included in the subsequent analyses. Total plasma lipid contents were significantly reduced in patients with metastasis. Specifically, levels of two out of the thirteen lipid classes (free fatty acids (FFAs) and lactosylceramides (LCERs)) were significantly decreased in patients with metastasis. Three lipids (CE(12:0), FFA(24:1), and TAG47:2-FA16:1) were identified as more effective predictors of melanoma metastasis than the well-known markers LDH and S100B. Furthermore, the predictive value substantially improved upon combining the lipid markers. We observed an increase in the cumulative levels of five lysophosphatidylcholines (LPC(16:0); LPC(18:0); LPC(18:1); LPC(18:2); LPC(20:4)), each individually associated with an elevated risk of lymph node metastasis but not cutaneous or distant metastasis. Additionally, seventeen lipid molecules were linked to patient survival, four of which (CE(12:0), CE(14:0), CE(15:0), SM(14:0)) overlapped with the lipid panel predicting metastasis. This study represents the first comprehensive investigation of the plasma lipidome of melanoma patients to date. Our findings suggest that plasma lipid profiles may serve as important biomarkers for predicting clinical outcomes of melanoma patients, including the presence of metastasis, and may also serve as indicators of patient survival.

Preparation and Optimization of MiR-375 Nano-Vector Using Two Novel Chitosan-Coated Nano-Structured Lipid Carriers as Gene Therapy for Hepatocellular Carcinoma

Currently, there is still a lack of effective carriers with minimal side effects to deliver therapeutic miRNA. Thus, it is crucial to optimize novel drug delivery systems. MiR-375 has proven superior therapeutic potency in Hepatocellular carcinoma (HCC). The purpose of this study was to fabricate 2 novel and smart nano-carriers for the transportation efficiency of miR-375 in HCC cells and enhance its anti-tumor effects. We established the miR-375 construct through the pEGP- miR expression vector. Two nano-carriers of solid/liquid lipids and chitosan (CS) were strategically selected, prepared by high-speed homogenization, and optimized by varying nano-formulation factors. Thus, the two best nano-formulations were designated as F1 (0.5% CS) and F2 (1.5% CS) and were evaluated for miR-375 conjugation efficiency by gel electrophoresis and nanodrop assessment. Then, physio-chemical characteristics and stability tests for the miR-375 nano-plexes were all studied. Next, its efficiencies as replacement therapy in HepG2 cells have been assessed by fluorescence microscopy, flow cytometry, and cytotoxicity assay. The obtained data showed that two cationic nanostructured solid/liquid lipid carriers (NSLCs); F1 and F2 typically had the best physio-chemical parameters and long-term stability. Moreover, both F1 and F2 could form nano-plexes with the anionic miR-375 construct at weight ratios 250/1 and 50/1 via electrostatic interactions. In addition, these nano-plexes exhibited physical stability after three months and protected miR-375 from degradation in the presence of 50% fetal bovine serum (FBS). Furthermore, both nano-plexes could simultaneously deliver miR-375 into HepG2 cells and they ensure miR re-expression even in the presence of 50% FBS compared to free miR-375 (p-value < 0.001). Moreover, both F1 and F2 alone significantly exhibited minimal cytotoxicity in treated cells. In contrast, the nano-plexes significantly inhibited cell growth compared to free miR-375 or doxorubicin (DOX), respectively. More importantly, F2/miR-375 nano-plex exhibited more anti-proliferative activity in treated cells although its IC50 value was 55 times lower than DOX (p-value < 0.001). Collectively, our findings clearly emphasized the multifunctionality of the two CS-coated NSLCs in terms of their enhanced biocompatibility, biostability, conjugation, and transfection efficiency of therapeutic miR-375. Therefore, the NSLCs/miR-375 nano-plexes could serve as a novel and promising therapeutic strategy for HCC.

Oleoylethanolamide and Palmitoylethanolamide Enhance IFNβ-Induced Apoptosis in Human Neuroblastoma SH-SY5Y Cells

Oleoylethanolamide (OEA) and palmitoylethanolamide (PEA) are endogenous lipids that act as agonists of the peroxisome proliferator-activated receptor α (PPARα). Recently, an interest in the role of these lipids in malignant tumors has emerged. Nevertheless, the effects of OEA and PEA on human neuroblastoma cells are still not documented. Type I interferons (IFNs) are immunomodulatory cytokines endowed with antiviral and anti-proliferative actions and are used in the treatment of various pathologies such as different cancer forms (i.e., non-Hodgkin's lymphoma, melanoma, leukemia), hepatitis B, hepatitis C, multiple sclerosis, and many others. In this study, we investigated the effect of OEA and PEA on human neuroblastoma SH-SY5Y cells treated with IFNβ. We focused on evaluating cell viability, cell proliferation, and cell signaling. Co-exposure to either OEA or PEA along with IFNβ leads to increased apoptotic cell death marked by the cleavage of caspase 3 and poly-(ADP ribose) polymerase (PARP) alongside a decrease in survivin and IKBα levels. Moreover, we found that OEA and PEA did not affect IFNβ signaling through the JAK-STAT pathway and the STAT1-inducible protein kinase R (PKR). OEA and PEA also increased the phosphorylation of p38 MAP kinase and programmed death-ligand 1 (PD-L1) expression both in full cell lysate and surface membranes. Furthermore, GW6471, a PPARα inhibitor, and the genetic silencing of the receptor were shown to lower PD-L1 and cleaved PARP levels. These results reveal the presence of a novel mechanism, independent of the IFNβ-prompted pathway, by which OEA and PEA can directly impair cell survival, proliferation, and clonogenicity through modulating and potentiating the intrinsic apoptotic pathway in human SH-SY5Y cells.

Tumour cell-expressed PD-L1 reprograms lipid metabolism via EGFR/ITGB4/SREBP1c signalling in liver cancer

Background & Aims

The programmed death-ligand 1 (PD-L1) is a major co-inhibitory checkpoint factor that controls T-cell activities in tumours. PD-L1 is expressed on immune cells and tumour cells. Whether tumour cell-expressed PD-L1 affects tumour cells in an immune cell-independent fashion remains largely elusive. In this study, we investigated the significance of tumour cell-expressed PD-L1 with a focus on downstream signals and changes in lipid metabolism.

Methods

Immune-independent functions of PD-L1 in tumour growth were investigated in vitro and in immuno-deficient mice in vivo. The global influence of PD-L1 in targeted/untargeted lipidomic metabolites was studied by comprehensive mass spectrometry-based metabolomic analysis in liver cancer. Effects on lipid metabolism were confirmed by triglyceride and cholesterol assays as well as by Oil Red O staining in liver, pancreatic, breast, and oesophageal squamous cancer. Underlying mechanisms were investigated by real-time quantitative PCR, Western blot analysis, co-immunoprecipitation, pull-down assays, immunofluorescence staining, and RNA sequencing.

Results

PD-L1 enhanced the accumulation of triglycerides, cholesterol, and lipid droplets in tumours. PD-L1 influenced targeted/untargeted lipidomic metabolites in hepatoma, including lipid metabolism, glucose metabolism, amino acid metabolism, nucleotide metabolism, and energy metabolism, suggesting that PD-L1 globally modulates the metabolic reprogramming of tumours. Mechanistically, PD-L1 activated epidermal growth factor receptor (EGFR) and/or integrin β4 (ITGB4) by forming a complex of PD-L1/EGFR/ITGB4 in the cell membrane, prior to activating PI3K/mTOR/SREBP1c signalling, leading to reprogramming of lipid metabolism in tumours. Functionally, PD-L1-mediated lipid metabolism reprogramming supported the tumour growth in vitro and in vivo through EGFR and/or ITGB4 in an immune cell-independent manner.

Conclusions

Our findings on lipogenesis and EGFR activation by tumour cell-expressed PD-L1 suggest that, in addition to its immunostimulatory effects, anti-PD-L1 may restrict lipid metabolism and EGFR/ITGB4 signalling in liver cancer therapy.

Impact and implications

In this study, we present evidence that PD-L1 drives the reprogramming of lipid metabolism in tumours. PD-L1 forms a complex with epidermal growth factor receptor (EGFR) and ITGB4, activating the PI3K/Akt/mTOR/SREBP1c signalling pathway and thereby contributing to lipid metabolism in cancer progression. Our findings offer novel insights into the mechanisms by which PD-L1 initiates the reprogramming of lipid metabolism in tumours. From a clinical perspective, the anti-PD-L1 antibody may alleviate resistance to the anti-EGFR antibody cetuximab and inhibit the reprogramming of lipid metabolism in tumours.

Is STARD3 A New Biomarker for Breast Cancer?

Despite advances in diagnosis and treatment, breast cancer is still one of the three most common cancers in the world and a significant cause of morbidity and mortality. Lipids play a role in many basic physiological pathways in cells, from regulating cell homeostasis to energy expenditure. As in many types of cancer, changes in lipid metabolism and their relationship have been reported in breast cancer. The STARD3 gene encodes a member of the subfamily of lipid trafficking proteins. It is a sterol-binding protein that mediates the transport of cholesterol from the endoplasmic reticulum to endosomes. It has been shown that STARD3 is correlated with human epidermal growth factor receptor 2 (HER2) amplification since it has the same localization as HER2 in the chromosome. In this review, we aimed to emphasize that investigating lipid metabolism together with the STARD3 biomarker has great potential not only for subtype-specific strategies but also for patient-specific strategies.

Causal role of metabolites in non-small cell lung cancer: Mendelian randomization (MR) study

On a global scale, lung cancer(LC) is the most commonly occurring form of cancer. Nonetheless, the process of screening and detecting it in its early stages presents significant challenges. Earlier research endeavors have recognized metabolites as potentially reliable biomarkers for LC. However, the majority of these studies have been limited in scope, featuring inconsistencies in terms of the relationships and levels of association observed.Moreover, there has been a lack of consistency in the types of biological samples utilized in previous studies. Therefore, the main objective of our research was to explore the correlation between metabolites and Non-small cell lung cancer (NSCLC).Thorough two-sample Mendelian randomization (TSMR) analysis, we investigated potential cause-and-effect relationships between 1400 metabolites and the risk of NSCLC.The analysis of TSMR revealed a significant causal impact of 61 metabolites on NSCLC.To ensure the reliability and validity of our findings, we perform FDR correction for P-values by Benjaminiand Hochberg(BH) method, Our results indicate that Oleate/vaccenate (18:1) levels and Caffeine to paraxanthine ratio may be causally associated with an increased risk of NSCLC [Oleate/vaccenate(18:1)levels: OR = 1.171,95%CI: 1.085-1.265, FDR = 0.036; Caffeine to paraxanthine ratio: OR = 1.386, 95%CI:1.191-1.612,FDR = 0.032].

Role of the fatty pancreatic infiltration in pancreatic oncogenesis

Although pancreatic precancerous lesions are known to be related to obesity and fatty pancreatic infiltration, the mechanisms remain unclear. We assessed the role of fatty infiltration in the process of pancreatic oncogenesis and obesity. A combined transcriptomic, lipidomic and pathological approach was used to explore neoplastic transformations. Intralobular (ILF) and extralobular (ELF) lipidomic profiles were analyzed to search for lipids associated with pancreatic intraepithelial neoplasia (PanINs) and obesity; the effect of ILF and ELF on acinar tissue and the histopathological aspects of pancreatic parenchyma changes in obese (OB) and non-obese patients. This study showed that the lipid composition of ILF was different from that of ELF. ILF was related to obesity and ELF-specific lipids were correlated to PanINs. Acinar cells were shown to have different phenotypes depending on the presence and proximity to ILF in OB patients. Several lipid metabolic pathways, oxidative stress and inflammatory pathways were upregulated in acinar tissue during ILF infiltration in OB patients. Early acinar transformations, called acinar nodules (AN) were linked to obesity but not ELF or ILF suggesting that they are the first reversible precancerous pancreatic lesions to occur in OB patients. On the other hand, the number of PanINs was higher in OB patients and was positively correlated to ILF and ELF scores as well as to fibrosis. Our study suggests that two types of fat infiltration must be distinguished, ELF and ILF. ILF plays a major role in acinar modifications and the development of precancerous lesions associated with obesity, while ELF may play a role in the progression of PDAC.

PLA2G4A and ACHE modulate lipid profiles via glycerophospholipid metabolism in platinum-resistant gastric cancer

BACKGROUND

Bioactive lipids involved in the progression of various diseases. Nevertheless, there is still a lack of biomarkers and relative regulatory targets. The lipidomic analysis of the samples from platinum-resistant in gastric cancer patients is expected to help us further improve our understanding of it.

METHODS

We employed LC-MS based untargeted lipidomic analysis to search for potential candidate biomarkers for platinum resistance in GC patients. Partial least squares discriminant analysis (PLS-DA) and variable importance in projection (VIP) analysis were used to identify differential lipids. The possible molecular mechanisms and targets were obtained by metabolite set enrichment analysis and potential gene network screened. Finally, verified them by immunohistochemical of a tissue microarray.

RESULTS

There were 71 differential lipid metabolites identified in GC samples between the chemotherapy-sensitivity group and the chemotherapy resistance group. According to Foldchange (FC) value, VIP value, P values (FC > 2, VIP > 1.5, p < 0.05), a total of 15 potential biomarkers were obtained, including MGDG(43:11)-H, Cer(d18:1/24:0) + HCOO, PI(18:0/18:1)-H, PE(16:1/18:1)-H, PE(36:2) + H, PE(34:2p)-H, Cer(d18:1 + hO/24:0) + HCOO, Cer(d18:1/23:0) + HCOO, PC(34:2e) + H, SM(d34:0) + H, LPC(18:2) + HCOO, PI(18:1/22:5)-H, PG(18:1/18:1)-H, Cer(d18:1/24:0) + H and PC(35:2) + H. Furthermore, we obtained five potential key targets (PLA2G4A, PLA2G3, DGKA, ACHE, and CHKA), and a metabolite-reaction-enzyme-gene interaction network was built to reveal the biological process of how they could disorder the endogenous lipid profile of platinum resistance in GC patients through the glycerophospholipid metabolism pathway. Finally, we further identified PLA2G4A and ACHE as core targets of the process by correlation analysis and tissue microarray immunohistochemical verification.

CONCLUSION

PLA2G4A and ACHE regulated endogenous lipid profile in the platinum resistance in GC patients through the glycerophospholipid metabolism pathway. The screening of lipid biomarkers will facilitate earlier precision medicine interventions for chemotherapy-resistant gastric cancer. The development of therapies targeting PLA2G4A and ACHE could enhance platinum chemotherapy effectiveness.

Advances in mass spectrometry imaging for spatial cancer metabolomics

Mass spectrometry (MS) has become a central technique in cancer research. The ability to analyze various types of biomolecules in complex biological matrices makes it well suited for understanding biochemical alterations associated with disease progression. Different biological samples, including serum, urine, saliva, and tissues have been successfully analyzed using mass spectrometry. In particular, spatial metabolomics using MS imaging (MSI) allows the direct visualization of metabolite distributions in tissues, thus enabling in-depth understanding of cancer-associated biochemical changes within specific structures. In recent years, MSI studies have been increasingly used to uncover metabolic reprogramming associated with cancer development, enabling the discovery of key biomarkers with potential for cancer diagnostics. In this review, we aim to cover the basic principles of MSI experiments for the nonspecialists, including fundamentals, the sample preparation process, the evolution of the mass spectrometry techniques used, and data analysis strategies. We also review MSI advances associated with cancer research in the last 5 years, including spatial lipidomics and glycomics, the adoption of three-dimensional and multimodal imaging MSI approaches, and the implementation of artificial intelligence/machine learning in MSI-based cancer studies. The adoption of MSI in clinical research and for single-cell metabolomics is also discussed. Spatially resolved studies on other small molecule metabolites such as amino acids, polyamines, and nucleotides/nucleosides will not be discussed in the context.

Precise diagnosis and risk stratification of prostate cancer by comprehensive serum metabolic fingerprints: a prediction model study

OBJECTIVES

Prostate cancer (PCa) is one of the most common malignancies in men worldwide and has caused increasing clinical morbidity and mortality, making timely diagnosis and accurate staging crucial. The authors introduced a novel approach based on mass spectrometry for precise diagnosis and stratification of PCa to facilitate clinical decision-making.

METHODS

Matrix-assisted laser desorption ionization time-of-flight (MALDI-TOF) mass spectrometry analysis of trace blood samples was combined with machine learning algorithms to construct diagnostic and stratification models. A total of 367 subjects, comprising 181 with PCa and 186 with non-PCa were enrolled. Additional 60 subjects, comprising 30 with PCa and 30 with non-PCa were enrolled as an external cohort for validation. Subsequent metabolomic analysis was carried out using Autoflex MALDI-TOF, and the mass spectra were introduced into various algorithms to construct different models.

RESULTS

Serum metabolic fingerprints were successfully obtained from 181 patients with PCa and 186 patients with non-PCa. The diagnostic model based on the eight signals demonstrated a remarkable area under curve of 100% and was validated in the external cohort with the area under curve of 87.3%. Fifteen signals were selected for enrichment analysis, revealing the potential metabolic pathways that facilitate tumorigenesis. Furthermore, the stage prediction model with an overall accuracy of 85.9% precisely classified subjects with localized disease and those with metastasis. The risk stratification model, with an overall accuracy of 89.6%, precisely classified the subjects as low-risk and high-risk.

CONCLUSIONS

Our study facilitated the timely diagnosis and risk stratification of PCa and provided new insights into the underlying mechanisms of metabolic alterations in PCa.

Intelligent Delivery Systems in Tumor Metabolism Regulation: Exploring the Path Ahead

Cancer metabolism plays multifaceted roles in the initiation and progression of tumors, and interventions in metabolism are considered fundamental approaches for cancer control. Within the vast metabolic networks of tumors, there exist numerous potential therapeutic targets, intricately interconnected with each other and with signaling networks related to immunity, metastasis, drug resistance, and more. Based on the characteristics of the tumor microenvironment, constructing drug delivery systems for multi-level modulation of the tumor microenvironment is proven as an effective strategy for achieving multidimensional control of cancer. Consequently, this article summarizes several features of tumor metabolism to provide insights into recent advancements in intelligent drug delivery systems for achieving multi-level regulation of the metabolic microenvironment in cancer, with the aim of offering a novel paradigm for cancer treatment.

Spatial MS multiomics on clinical prostate cancer tissues

Mass spectrometry (MS) and MS imaging (MSI) are used extensively for both the spatial and bulk characterization of samples in lipidomics and proteomics workflows. These datasets are typically generated independently due to different requirements for sample preparation. However, modern omics technologies now provide higher sample throughput and deeper molecular coverage, which, in combination with more sophisticated bioinformatic and statistical pipelines, make generating multiomics data from a single sample a reality. In this workflow, we use spatial lipidomics data generated by matrix-assisted laser desorption/ionization MSI (MALDI-MSI) on prostate cancer (PCa) radical prostatectomy cores to guide the definition of tumor and benign tissue regions for laser capture microdissection (LCM) and bottom-up proteomics all on the same sample and using the same mass spectrometer. Accurate region of interest (ROI) mapping was facilitated by the SCiLS region mapper software and dissected regions were analyzed using a dia-PASEF workflow. A total of 5525 unique protein groups were identified from all dissected regions. Lysophosphatidylcholine acyltransferase 1 (LPCAT1), a lipid remodelling enzyme, was significantly enriched in the dissected regions of cancerous epithelium (CE) compared to benign epithelium (BE). The increased abundance of this protein was reflected in the lipidomics data with an increased ion intensity ratio for pairs of phosphatidylcholines (PC) and lysophosphatidylcholines (LPC) in CE compared to BE.

A Multimodal Meta-Analytical Evidence of Functional and Structural Brain Abnormalities Across Alzheimer's Disease Spectrum

BACKGROUND

Numerous neuroimaging studies have reported that Alzheimer's disease (AD) spectrum have been linked to alterations in intrinsic functional activity and cortical thickness (CT) of some brain areas. However, the findings have been inconsistent and the correlation with the transcriptional profile and neurotransmitter systems remain largely unknown.

METHODS

We conducted a meta-analysis to identify multimodal differences in the amplitude of low-frequency fluctuation (ALFF)/fractional ALFF (fALFF) and CT in patients with AD and preclinical AD compared to healthy controls (HCs), using the Seed-based d Mapping with Permutation of Subject Images software. Transcriptional data were retrieved from the Allen Human Brain Atlas. The atlas-based nuclear imaging-derived neurotransmitter maps were investigated by JuSpace toolbox.

RESULTS

We included 26 ALFF/fALFF studies comprising 884 patients with AD and 1,020 controls, along with 52 studies comprising 2,046 patients with preclinical AD and 2,336 controls. For CT, we included 11 studies comprising 353 patients with AD and 330 controls. Overall, compared to HCs, patients with AD showed decreased ALFF/fALFF in the bilateral posterior cingulate gyrus (PCC)/precuneus and right angular gyrus, as well as increased ALFF/fALFF in the bilateral parahippocampal gyrus (PHG). Patients with peclinical AD showed decreased ALFF/fALFF in the left precuneus. Additionally, patients with AD displayed decreased CT in the bilateral PHG, left PCC, bilateral orbitofrontal cortex, sensorimotor areas and temporal lobe. Furthermore, gene sets related to brain structural and functional changes in AD and preclincal AD were enriched for G protein-coupled receptor signaling pathway, ion gated channel activity, and components of biological membrane. Functional and structural alterations in AD and preclinical AD were spatially associated with dopaminergic, serotonergic, and GABAergic neurotransmitter systems.

CONCLUSIONS

The multimodal meta-analysis demonstrated that patients with AD exhibited convergent functional and structural alterations in the PCC/precuneus and PHG, as well as cortical thinning in the primary sensory and motor areas. Furthermore, patients with preclinical AD showed reduced functional activity in the precuneus. AD and preclinical AD showed genetic modulations/neurotransmitter deficits of brain functional and structural impairments. These findings may provide new insights into the pathophysiology of the AD spectrum.

Deep Characterisation of the sn-Isomer Lipidome Using High-Throughput Data-Independent Acquisition and Ozone-Induced Dissociation

In recent years there has been a significant interest in the development of innovative lipidomics techniques capable of resolving lipid isomers. To date, methods applied to resolving sn-isomers have resolved only a limited number of species. We report a workflow based on ozone-induced dissociation for untargeted characterisation of hundreds of sn-resolved glycerophospholipid isomers from biological extracts in under 20 min, coupled with an automated data analysis pipeline. It provides an order of magnitude increase in the number of sn-isomer pairs identified as compared to previous reports and reveals that sn-isomer populations are tightly regulated and significantly different between cell lines. The sensitivity of this method and potential for de novo molecular discovery is further demonstrated by the identification of unexpected lipids containing ultra-long monounsaturated acyl chains at the sn-1 position.

Plasma free fatty acid levels in cervical cancer: concurrent chemoradiotherapy improves abnormal profile

Background: Epidemiology has demonstrated that plasma free fatty acids (FFAs) can prevent the development of cancer. Our study sought to evaluate the relationship between plasma (FFA) levels and cervical cancer. Methods: In recent years, metabolomics-based approaches have been recognized as an emerging tool, so we examined the plasma FFA profiles of 114 patients with cervical cancer and 151 healthy people using liquid chromatography-tandem mass spectrometry (LC-MS/MS) methods. Results: The data results were analyzed by multifactorial binary logistic regression analysis, and it was found that palmitic acid, docosahexaenoic acid (DHA), and total ω-3 fatty acids were negatively correlated with the risk of cervical cancer; whereas tetracosanoic acid was positively correlated with the risk of cervical cancer (OR, 1.026; 95% CI, 1.013-1.040; p < 0.001). Dynamic follow-up of 40 cervical cancer patients who successfully completed CCRT revealed that most fatty acid levels tended to increase after the end of treatment, except for palmitic and stearic acid levels, which were lower than before treatment. Conclusion: Plasma FFA profiles were altered in cervical cancer patients, which may be related to abnormal fatty acid metabolism in cervical cancer. The described changes in fatty acid profiles during CCRT may be related to the good functioning of CCRT. Further studies on plasma FFA composition and its changes due to CCRT in patients with cervical cancer are warranted.

Cervical Squamous Cell Carcinoma Diagnosis by FTIR Microspectroscopy

Cervical cancer was considered the fourth most common cancer worldwide in 2020. In order to reduce mortality, an early diagnosis of the tumor is required. Currently, this type of cancer occurs mostly in developing countries due to the lack of vaccination and screening against the Human Papillomavirus. Thus, there is an urgent clinical need for new methods aiming at a reliable screening and an early diagnosis of precancerous and cancerous cervical lesions. Vibrational spectroscopy has provided very good results regarding the diagnosis of various tumors, particularly using Fourier transform infrared microspectroscopy, which has proved to be a promising complement to the currently used histopathological methods of cancer diagnosis. This spectroscopic technique was applied to the analysis of cryopreserved human cervical tissue samples, both squamous cell carcinoma (SCC) and non-cancer samples. A dedicated Support Vector Machine classification model was constructed in order to categorize the samples into either normal or malignant and was subsequently validated by cross-validation, with an accuracy higher than 90%.

Global research trends and prospects of cellular metabolism in colorectal cancer

BACKGROUND

An increasing number of studies have focused on the role of cellular metabolism in the development of colorectal cancer (CRC). However, no work is currently available to synthesize the field through bibliometrics.

AIM

To analyze the development in the field of "glucose metabolism" (GM), "amino acid metabolism" (AM), "lipid metabolism" (LM), and "nucleotide metabolism" (NM) in CRC by visualization.

METHODS

Articles within the abovementioned areas of GM, AM, LM and NM in CRC, which were published from January 1, 1991, to December 31, 2022, are retrieved from the Web of Science Core Collection and analyzed by CiteSpace 6.2.R4 and VOSviewer 1.6.19.

RESULTS

The field of LM in CRC presented the largest number of annual publications and the fastest increase in the last decade compared with the other three fields. Meanwhile, China and the United States were two of the most prominent contributors in these four areas. In addition, Gang Wang, Wei Jia, Maria Notarnicola, and Cornelia Ulrich ranked first in publication numbers, while Jing-Yuan Fang, Senji Hirasawa, Wei Jia, and Charles Fuchs were the most cited authors on average in these four fields, respectively. "Gut microbiota" and "epithelial-mesenchymal transition" emerged as the newest burst words in GM, "gut microbiota" was the latest outburst word in AM, "metastasis", "tumor microenvironment", "fatty acid metabolism", and "metabolic reprogramming" were the up-to-date outbreaking words in LM, while "epithelial-mesenchymal transition" and "apoptosis" were the most recently occurring words in NM.

CONCLUSION

Research in "cellular metabolism in CRC" is all the rage at the moment, and researchers are particularly interested in exploring the mechanism to explain the metabolic alterations in CRC. Targeting metabolic vulnerability appears to be a promising direction in CRC therapy.

Real-Time NMR-Based Drug Discovery to Identify Inhibitors against Fatty Acid Synthesis in Living Cancer Cells

Abnormal fatty acid metabolism is recognized as a key driver of tumor development and progression. Although numerous inhibitors have been developed to target this pathway, finding drugs with high specificity that do not disrupt normal cellular metabolism remains a formidable challenge. In this paper, we introduced a novel real-time NMR-based drug screening technique that operates within living cells. This technique provides a direct way to putatively identify molecular targets involved in specific metabolic processes, making it a powerful tool for cell-based drug screening. Using 2-13C acetate as a tracer, combined with 3D cell clusters and a bioreactor system, our approach enables real-time detection of inhibitors that target fatty acid metabolism within living cells. As a result, we successfully demonstrated the initial application of this method in the discovery of traditional Chinese medicines that specifically target fatty acid metabolism. Elucidating the mechanisms behind herbal medicines remains challenging due to the complex nature of their compounds and the presence of multiple targets. Remarkably, our findings demonstrate the significant inhibitory effect of P. cocos on fatty acid synthesis within cells, illustrating the potential of this approach in analyzing fatty acid metabolism events and identifying drug candidates that selectively inhibit fatty acid synthesis at the cellular level. Moreover, this systematic approach represents a valuable strategy for discovering the intricate effects of herbal medicine.

Reprogramming of lipid metabolism in the tumor microenvironment: a strategy for tumor immunotherapy

Lipid metabolism in cancer cells has garnered increasing attention in recent decades. Cancer cells thrive in hypoxic conditions, nutrient deficiency, and oxidative stress and cannot be separated from alterations in lipid metabolism. Therefore, cancer cells exhibit increased lipid metabolism, lipid uptake, lipogenesis and storage to adapt to a progressively challenging environment, which contribute to their rapid growth. Lipids aid cancer cell activation. Cancer cells absorb lipids with the help of transporter and translocase proteins to obtain energy. Abnormal levels of a series of lipid synthases contribute to the over-accumulation of lipids in the tumor microenvironment (TME). Lipid reprogramming plays an essential role in the TME. Lipids are closely linked to several immune cells and their phenotypic transformation. The reprogramming of tumor lipid metabolism further promotes immunosuppression, which leads to immune escape. This event significantly affects the progression, treatment, recurrence, and metastasis of cancer. Therefore, the present review describes alterations in the lipid metabolism of immune cells in the TME and examines the connection between lipid metabolism and immunotherapy.

Association of serum lipids and abnormal lipid score with cancer risk: a population-based prospective study

BACKGROUND

Serum lipid levels are associated with cancer risk. However, there still have uncertainties about the single and combined effects of low lipid levels on cancer risk.

METHODS

A prospective cohort study of 33,773 adults in Shanghai between 2016 and 2017 was conducted. Total cholesterol (TC), triglycerides (TG), low-density lipoprotein cholesterol (LDL-C), and high-density lipoprotein cholesterol (HDL-C) levels were measured. Cox proportional hazard models were used to assess the association of single and combined lipids with overall, lung, colon, rectal, thyroid gland, stomach, and female breast cancers. The effect of the combination of abnormal lipid score and lifestyle on cancer was also estimated.

RESULTS

A total of 926 incident cancer cases were identified. In the RCS analysis, hazard ratios (HRs) of overall cancer for individuals with TC < 5.18 mmol/L or with LDL-C < 3.40 mmol/L were higher. Low TC was associated with higher colorectal cancer risk (HR [95% CI] = 1.76 [1.09-2.84]) and low HDL-C increased thyroid cancer risk by 90%. Abnormal lipid score was linearly and positively associated with cancer risk, and smokers with high abnormal lipid scores had a higher cancer risk, compared to non-smokers with low abnormal lipid scores (P < 0.05).

CONCLUSIONS

Low TC levels were associated with an increased risk of overall and colorectal cancer. More attention should be paid to participants with high abnormal lipid scores and unhealthy lifestyles who may have a higher risk of developing cancer. Determining the specific and comprehensive lipid combinations that affect tumorigenesis remains a valuable challenge.

Enzymatic production process of capric acid-rich structured lipids: Development of formulation as a new therapeutic approach

The present work reports an optimization of the synthesis of MLM-type (medium, long, medium) structured lipids (SL) through an acidolysis reaction of grape seed oil with capric acid catalyzed by Rhizopus oryzae lipase immobilized. At first, tests were carried out by preparing the biocatalysts using enzyme loadings (0.15 to 1 g of enzymatic powder) for each gram of support. Enzyme loading was used 0.3 g of enzymatic powder, and hydrolytic activity of 1860 ± 23.4 IU/g was reached. Optimized conditions determined by the Central Composite Rotatable Design (CCRD) revealed that the acidolysis reaction reached approximately 59 % incorporation degree (%ID) after 24 h, in addition to the fact that the biocatalyst could maintain the incorporation degree in five consecutive cycles. From this high incorporation degree, cell viability assays were performed with murine fibroblast cell lines and human cervical adenocarcinoma cell lines. Concerning the cytotoxicity assays, the concentration of MLM-SL to 1.75 and 2 % v/v were able to induce cell death in 56 % and 64 % of adenocarcinoma cells, respectively. Human cervical adenocarcinoma cells showed greater sensitivity to the induction of cell death when using emulsions with MLM-SL > 1.75 % v/v compared to emulsions with lower content indicating a potential for combating carcinogenic cells.

Identification of pre-diagnostic lipid sets associated with liver cancer risk using untargeted lipidomics and chemical set analysis: A nested case-control study within the ATBC cohort

In pre-disposed individuals, a reprogramming of the hepatic lipid metabolism may support liver cancer initiation. We conducted a high-resolution mass spectrometry based untargeted lipidomics analysis of pre-diagnostic serum samples from a nested case-control study (219 liver cancer cases and 219 controls) within the Alpha-Tocopherol, Beta-Carotene Cancer Prevention (ATBC) Study. Out of 462 annotated lipids, 158 (34.2%) were associated with liver cancer risk in a conditional logistic regression analysis at a false discovery rate (FDR) <0.05. A chemical set enrichment analysis (ChemRICH) and co-regulatory set analysis suggested that 22/28 lipid classes and 47/83 correlation modules were significantly associated with liver cancer risk (FDR <0.05). Strong positive associations were observed for monounsaturated fatty acids (MUFA), triacylglycerols (TAGs) and phosphatidylcholines (PCs) having MUFA acyl chains. Negative associations were observed for sphingolipids (ceramides and sphingomyelins), lysophosphatidylcholines, cholesterol esters and polyunsaturated fatty acids (PUFA) containing TAGs and PCs. Stearoyl-CoA desaturase enzyme 1 (SCD1), a rate limiting enzyme in fatty acid metabolism and ceramidases seems to be critical in this reprogramming. In conclusion, our study reports pre-diagnostic lipid changes that provide novel insights into hepatic lipid metabolism reprogramming may contribute to a pro-cell growth and anti-apoptotic tissue environment and, in turn, support liver cancer initiation.

Proteomic-based stratification of intermediate-risk prostate cancer patients

Gleason grading is an important prognostic indicator for prostate adenocarcinoma and is crucial for patient treatment decisions. However, intermediate-risk patients diagnosed in the Gleason grade group (GG) 2 and GG3 can harbour either aggressive or non-aggressive disease, resulting in under- or overtreatment of a significant number of patients. Here, we performed proteomic, differential expression, machine learning, and survival analyses for 1,348 matched tumour and benign sample runs from 278 patients. Three proteins (F5, TMEM126B, and EARS2) were identified as candidate biomarkers in patients with biochemical recurrence. Multivariate Cox regression yielded 18 proteins, from which a risk score was constructed to dichotomize prostate cancer patients into low- and high-risk groups. This 18-protein signature is prognostic for the risk of biochemical recurrence and completely independent of the intermediate GG. Our results suggest that markers generated by computational proteomic profiling have the potential for clinical applications including integration into prostate cancer management.

Genes and Pathways Involved in the Progression of Malignant Pleural Mesothelioma: A Meta-analysis of Genome-Wide Expression Studies

Malignant pleural mesothelioma (MPM) is a rare and aggressive neoplasm of the pleural tissue that lines the lungs and is mainly associated with long latency from asbestos exposure. This tumor has no effective therapeutic opportunities nowadays and has a very low five-year survival rate. In this sense, identifying molecular events that trigger the development and progression of this tumor is highly important to establish new and potentially effective treatments. We conducted a meta-analysis of genome-wide expression studies publicly available at the Gene Expression Omnibus (GEO) and ArrayExpress databases. The differentially expressed genes (DEGs) were identified, and we performed functional enrichment analysis and protein-protein interaction networks (PPINs) to gain insight into the biological mechanisms underlying these genes. Additionally, we constructed survival prediction models for selected DEGs and predicted the minimum drug inhibition concentration of anticancer drugs for MPM. In total, 115 MPM tumor transcriptomes and 26 pleural tissue controls were analyzed. We identified 1046 upregulated DEGs in the MPM samples. Cellular signaling categories in tumor samples were associated with the TNF, PI3K-Akt, and AMPK pathways. The inflammatory response, regulation of cell migration, and regulation of angiogenesis were overrepresented biological processes. Expression of SOX17 and TACC1 were associated with reduced survival rates. This meta-analysis identified a list of DEGs in MPM tumors, cancer-related signaling pathways, and biological processes that were overrepresented in MPM samples. Some therapeutic targets to treat MPM are suggested, and the prognostic potential of key genes is shown.

CD36: The Bridge between Lipids and Tumors

It has been found that the development of some cancers can be attributed to obesity, which is associated with the excessive intake of lipids. Cancer cells undergo metabolic reprogramming, shifting from utilizing glucose to fatty acids (FAs) for energy. CD36, a lipid transporter, is highly expressed in certain kinds of cancer cells. High expressions of CD36 in tumor cells triggers FA uptake and lipid accumulation, promoting rapid tumor growth and initiating metastasis. Meanwhile, immune cells in the tumor microenvironment overexpress CD36 and undergo metabolic reprogramming. CD36-mediated FA uptake leads to lipid accumulation and has immunosuppressive effects. This paper reviews the types of FAs associated with cancer, high expressions of CD36 that promote cancer development and progression, effects of CD36 on different immune cells in the tumor microenvironment, and the current status of CD36 as a therapeutic target for the treatment of tumors with high CD36 expression.

Lipid alterations play a role in the integration of PD-1/PD-L1 inhibitors and anlotinib for the treatment of advanced non-small-cell lung cancer

BACKGROUND

Studies have shown that integrating anlotinib with programmed death 1 (PD-1)/programmed death-ligand 1 (PD-L1) inhibitors enhances survival rates among progressive non-small-cell lung cancer (NSCLC) patients lacking driver mutations. However, not all individuals experience clinical benefits from this therapy. As a result, it is critical to investigate the factors that contribute to the inconsistent response of patients. Recent investigations have emphasized the importance of lipid metabolic reprogramming in the development and progression of NSCLC.

METHODS

The objective of this investigation was to examine the correlation between lipid variations and observed treatment outcomes in advanced NSCLC patients who were administered PD-1/PD-L1 inhibitors alongside anlotinib. A cohort composed of 30 individuals diagnosed with advanced NSCLC without any driver mutations was divided into three distinct groups based on the clinical response to the combination treatment, namely, a group exhibiting partial responses, a group manifesting progressive disease, and a group demonstrating stable disease. The lipid composition of patients in these groups was assessed both before and after treatment.

RESULTS

Significant differences in lipid composition among the three groups were observed. Further analysis revealed 19 differential lipids, including 2 phosphatidylglycerols and 17 phosphoinositides.

CONCLUSION

This preliminary study aimed to explore the specific impact of anlotinib in combination with PD-1/PD-L1 inhibitors on lipid metabolism in patients with advanced NSCLC. By investigating the effects of using both anlotinib and PD-1/PD-L1 inhibitors, this study enhances our understanding of lipid metabolism in lung cancer treatment. The findings from this research provide valuable insights into potential therapeutic approaches and the identification of new therapeutic biomarkers.

Obesity, Dietary Fats, and Gastrointestinal Cancer Risk-Potential Mechanisms Relating to Lipid Metabolism and Inflammation

Obesity is a major driving factor in the incidence, progression, and poor treatment response in gastrointestinal cancers. Herein, we conducted a comprehensive analysis of the impact of obesity and its resulting metabolic perturbations across four gastrointestinal cancer types, namely, oesophageal, gastric, liver, and colorectal cancer. Importantly, not all obese phenotypes are equal. Obese adipose tissue heterogeneity depends on the location, structure, cellular profile (including resident immune cell populations), and dietary fatty acid intake. We discuss whether adipose heterogeneity impacts the tumorigenic environment. Dietary fat quality, in particular saturated fatty acids, promotes a hypertrophic, pro-inflammatory adipose profile, in contrast to monounsaturated fatty acids, resulting in a hyperplastic, less inflammatory adipose phenotype. The purpose of this review is to examine the impact of obesity, including dietary fat quality, on adipose tissue biology and oncogenesis, specifically focusing on lipid metabolism and inflammatory mechanisms. This is achieved with a particular focus on gastrointestinal cancers as exemplar models of obesity-associated cancers.

Radiotherapy-Triggered In Situ Tumor Vaccination Boosts Checkpoint Blockaded Immune Response via Antigen-Capturing Nanoadjuvants

In situ vaccination (ISV) formed with the aid of intratumorally injected adjuvants has shed bright light on enhancing the abscopal therapeutic effects of radiotherapy. However, the limited availability of antigens resulting from the radiotherapy-induced immunogenic cell death largely hampers the clinical outcome of ISV. To maximally utilize the radiotherapy-induced antigen, we herein developed a strategy by capturing the radiotherapy-induced antigen in situ with a nanoadjuvant comprised of CpG-loaded Fe3O4 nanoparticles. The highly efficient click reaction between the maleimide residue on the nanoadjuvant and sulfhydryl group on the antigen maximized the bioavailability of autoantigens and CpG adjuvant in vivo. Importantly, combined immune checkpoint blockade can reverse T cell exhaustion after treatment with radiotherapy-induced ISV, thereby largely suppressing the treated and distant tumor. Mechanistically, metabolomics reveals the intratumorally injected nanoadjuvants disrupt redox homeostasis in the tumor microenvironment, further inducing tumor ferroptosis after radiotherapy. Overall, the current study highlights the immense potential of the innovative antigen-capturing nanoadjuvants for synergistically enhancing the antitumor effect.

Ultrahigh resolution lipid mass spectrometry imaging of high-grade serous ovarian cancer mouse models

No effective screening tools for ovarian cancer (OC) exist, making it one of the deadliest cancers among women. Considering that little is known about the detailed progression and metastasis mechanism of OC at a molecular level, it is crucial to gain more insights into how metabolic and signaling alterations accompany its development. Herein, we present a comprehensive study using ultra-high-resolution Fourier transform ion cyclotron resonance matrix-assisted laser desorption/ionization (MALDI) mass spectrometry imaging (MSI) to investigate the spatial distribution and alterations of lipids in ovarian tissues collected from double knockout (n = 4) and triple mutant mouse models (n = 4) of high-grade serous ovarian cancer (HGSOC). Lipids belonging to a total of 15 different classes were annotated and their abundance changes were compared to those in healthy mouse reproductive tissue (n = 4), mapping onto major lipid pathways involved in OC progression. From intermediate-stage OC to advanced HGSC, we provide direct visualization of lipid distributions and their biological links to inflammatory response, cellular stress, cell proliferation, and other processes. We also show the ability to distinguish tumors at different stages from healthy tissues via a number of highly specific lipid biomarkers, providing targets for future panels that could be useful in diagnosis.

Lipid metabolism in the immune niche of tumor-prone liver microenvironment

The liver is a common primary site not only for tumorigenesis, but also for cancer metastasis. Advanced cancer patients with liver metastases also show reduced response rates and survival benefits when treated with immune checkpoint inhibitors. Accumulating evidence has highlighted the importance of the liver immune microenvironment in determining tumorigenesis, metastasis-organotropism, and immunotherapy resistance. Various immune cells such as T cells, natural killer and natural killer T cells, macrophages and dendritic cells, and stromal cells including liver sinusoidal endothelial cells, Kupffer cells, hepatic stellate cells, and hepatocytes are implicated in contributing to the immune niche of tumor-prone liver microenvironment. In parallel, as the major organ for lipid metabolism, the increased abundance of lipids and their metabolites is linked to processes crucial for nonalcoholic fatty liver disease and related liver cancer development. Furthermore, the proliferation, differentiation, and functions of hepatic immune and stromal cells are also reported to be regulated by lipid metabolism. Therefore, targeting lipid metabolism may hold great potential to reprogram the immunosuppressive liver microenvironment and synergistically enhance the immunotherapy efficacy in the circumstance of liver metastasis. In this review, we describe how the hepatic microenvironment adapts to the lipid metabolic alterations in pathologic conditions like nonalcoholic fatty liver disease. We also illustrate how these immunometabolic alterations promote the development of liver cancers and immunotherapy resistance. Finally, we discuss the current therapeutic options and hypothetic combination immunotherapies for the treatment of advanced liver cancers.

Immune, metabolic landscapes of prognostic signatures for lung adenocarcinoma based on a novel deep learning framework

Lung adenocarcinoma (LUAD) is a malignant tumor with high lethality, and the aim of this study was to identify promising biomarkers for LUAD. Using the TCGA-LUAD dataset as a discovery cohort, a novel joint framework VAEjMLP based on variational autoencoder (VAE) and multilayer perceptron (MLP) was proposed. And the Shapley Additive Explanations (SHAP) method was introduced to evaluate the contribution of feature genes to the classification decision, which helped us to develop a biologically meaningful biomarker potential scoring algorithm. Nineteen potential biomarkers for LUAD were identified, which were involved in the regulation of immune and metabolic functions in LUAD. A prognostic risk model for LUAD was constructed by the biomarkers HLA-DRB1, SCGB1A1, and HLA-DRB5 screened by Cox regression analysis, dividing the patients into high-risk and low-risk groups. The prognostic risk model was validated with external datasets. The low-risk group was characterized by enrichment of immune pathways and higher immune infiltration compared to the high-risk group. While, the high-risk group was accompanied by an increase in metabolic pathway activity. There were significant differences between the high- and low-risk groups in metabolic reprogramming of aerobic glycolysis, amino acids, and lipids, as well as in angiogenic activity, epithelial-mesenchymal transition, tumorigenic cytokines, and inflammatory response. Furthermore, high-risk patients were more sensitive to Afatinib, Gefitinib, and Gemcitabine as predicted by the pRRophetic algorithm. This study provides prognostic signatures capable of revealing the immune and metabolic landscapes for LUAD, and may shed light on the identification of other cancer biomarkers.

Advanced progress of spatial metabolomics in head and neck cancer research

Head and neck cancer ranks as the sixth most prevalent malignancy, constituting 5 % of all cancer cases. Its inconspicuous onset often leads to advanced stage diagnoses, prompting the need for early detection to enhance patient prognosis. Currently, research into early diagnostic markers relies predominantly on genomics, proteomics, transcriptomics, and other methods, which, unfortunately, necessitate tumor tissue homogenization, resulting in the loss of temporal and spatial information. Emerging as a recent addition to the omics toolkit, spatial metabolomics stands out. This method conducts in situ mass spectrometry analyses on fresh tissue specimens while effectively preserving their spatiotemporal information. The utilization of spatial metabolomics in life science research offers distinct advantages. This article comprehensively reviews the progress of spatial metabolomics in head and neck cancer research, encompassing insights into cancer cell metabolic reprogramming. Various mass spectrometry imaging techniques, such as secondary ion mass spectrometry, stroma-assisted laser desorption/ionization, and desorption electrospray ionization, enable in situ metabolite analysis for head and neck cancer. Finally, significant emphasis is placed on the application of presently available techniques for early diagnosis, margin assessment, and prognosis of head and neck cancer.

LncRNAs-circRNAs as Rising Epigenetic Binary Superstars in Regulating Lipid Metabolic Reprogramming of Cancers

As one of novel hallmarks of cancer, lipid metabolic reprogramming has recently been becoming fascinating and widely studied. Lipid metabolic reprogramming in cancer is shown to support carcinogenesis, progression, distal metastasis, and chemotherapy resistance by generating ATP, biosynthesizing macromolecules, and maintaining appropriate redox status. Notably, increasing evidence confirms that lipid metabolic reprogramming is under the control of dysregulated non-coding RNAs in cancer, especially lncRNAs and circRNAs. This review highlights the present research findings on the aberrantly expressed lncRNAs and circRNAs involved in the lipid metabolic reprogramming of cancer. Emphasis is placed on their regulatory targets in lipid metabolic reprogramming and associated mechanisms, including the clinical relevance in cancer through lipid metabolism modulation. Such insights will be pivotal in identifying new theranostic targets and treatment strategies for cancer patients afflicted with lipid metabolic reprogramming.

Prognostic Value of Fatty Acid Metabolism-related Genes in Patients with Bladder Cancer

INTRODUCTION

This study aimed to explore the expression profiles of fatty acid metabolism- related genes (FAMRGs) in patients with bladder cancer (BLCA).

METHODS

The corresponding clinicopathological features of BLCA patients and RNA sequencing data were downloaded from TCGA and GSE13507. Univariate Cox regression was used to determine the prognostic value of FRGS in BLCA patients. LASSO regression analysis was then performed to select potential risk genes and eliminate genes that might overfit the model. Based on the independent prognostication-related FRGs, the nomogram survival model was established using the root mean square value of the R packet to predict the 1-year, 3-year, and 5-year survival rates of BLCA patients. By determining the area under the curve (AUC) value, the time-dependent receiver operating characteristic curve (ROC) was used to evaluate the prognostic efficiency of our model.

RESULTS

A total of 243 DEFRGs were identified. Twenty FRGs were found to be related to the prognosis of BLCA in the TCGA database. Survival curves showed that high-risk patients had significantly shorter OS than low-risk cases (p < 0.001). The AUC of risk was 0.784, which was superior to age, sex, and stage, suggesting that the risk score was more favorable in predicting OS than traditional pathologic prognostic factors. The AUC was 0.757 at 1 year, 0.732 at 3 years, and 0.733 at 5 year-OS.

CONCLUSION

In this study, we demonstrated that a FAMRG prognosis biomarker is associated with the tumor immune microenvironment in patients with BLCA.

Toward Omics-Scale Quantitative Mass Spectrometry Imaging of Lipids in Brain Tissue Using a Multiclass Internal Standard Mixture

Mass spectrometry imaging (MSI) has accelerated our understanding of lipid metabolism and spatial distribution in tissues and cells. However, few MSI studies have approached lipid imaging quantitatively and those that have focused on a single lipid class. We overcome this limitation by using a multiclass internal standard (IS) mixture sprayed homogeneously over the tissue surface with concentrations that reflect those of endogenous lipids. This enabled quantitative MSI (Q-MSI) of 13 lipid classes and subclasses representing almost 200 sum-composition lipid species using both MALDI (negative ion mode) and MALDI-2 (positive ion mode) and pixel-wise normalization of each lipid species in a manner analogous to that widely used in shotgun lipidomics. The Q-MSI approach covered 3 orders of magnitude in dynamic range (lipid concentrations reported in pmol/mm2) and revealed subtle changes in distribution compared to data without normalization. The robustness of the method was evaluated by repeating experiments in two laboratories using both timsTOF and Orbitrap mass spectrometers with an ∼4-fold difference in mass resolution power. There was a strong overall correlation in the Q-MSI results obtained by using the two approaches. Outliers were mostly rationalized by isobaric interferences or the higher sensitivity of one instrument for a particular lipid species. These data provide insight into how the mass resolving power can affect Q-MSI data. This approach opens up the possibility of performing large-scale Q-MSI studies across numerous lipid classes and subclasses and revealing how absolute lipid concentrations vary throughout and between biological tissues.

Interfacial Electromigration for Analysis of Biofluid Lipids in Small Volumes

Lipids are important biomarkers within the field of disease diagnostics and can serve as indicators of disease progression and predictors of treatment effectiveness. Although lipids can provide important insight into how diseases initiate and progress, mass spectrometric methods for lipid characterization and profiling are limited due to lipid structural diversity, particularly the presence of various lipid isomers. Moreover, the difficulty of handling small-volume samples exacerbates the intricacies of biological analyses. In this work, we have developed a strategy that electromigrates a thin film of a small-volume biological sample directly to the air-liquid interface formed at the tip of a theta capillary. Importantly, we seamlessly integrated in situ biological lipid extraction with accelerated chemical derivatization, enabled by the air-liquid interface, and conducted isomeric structural characterization within a unified platform utilizing theta capillary nanoelectrospray ionization mass spectrometry, all tailored for small-volume sample analysis. We applied this unified platform to the analysis of lipids from small-volume human plasma and Alzheimer's disease mouse serum samples. Accelerated electro-epoxidation of unsaturated lipids at the interface allowed us to characterize lipid double-bond positional isomers. The unique application of electromigration of a thin film to the air-liquid interface in combination with accelerated interfacial reactions holds great potential in small-volume sample analysis for disease diagnosis and prevention.

Metabolomic profile of acute myeloid leukaemia parallels of prognosis and response to therapy

The heterogeneity of acute myeloid leukemia (AML), a complex hematological malignancy, is caused by mutations in myeloid cells affecting their differentiation and proliferation. Thus, various cytogenetic alterations in AML cells may be characterized by a unique metabolome and require different treatment approaches. In this study, we performed untargeted metabolomics to assess metabolomics differences between AML patients and healthy controls, AML patients with different treatment outcomes, AML patients in different risk groups based on the 2017 European LeukemiaNet (ELN) recommendations for the diagnosis and management of AML, AML patients with and without FLT3-ITD mutation, and a comparison between patients with FLT3-ITD, CBF-AML (Core binding factor acute myelogenous leukemia), and MLL AML (mixed-lineage leukemia gene) in comparison to control subjects. Analyses were performed in serum samples using liquid chromatography coupled with mass spectrometry (LC-MS). The obtained metabolomics profiles exhibited many alterations in glycerophospholipid and sphingolipid metabolism and allowed us to propose biomarkers based on each of the above assessments as an aid for diagnosis and eventual classification, allowing physicians to choose the best-suited treatment approach. These results highlight the application of LC-MS-based metabolomics of serum samples as an aid in diagnostics and a potential minimally invasive prognostic tool for identifying various cytogenetic and treatment outcomes of AML.

Discovery of a novel lipid metabolism-related gene signature to predict outcomes and the tumor immune microenvironment in gastric cancer by integrated analysis of single-cell and bulk RNA sequencing

Gastric cancer (GC) is a pressing global clinical issue, with few treatment options and a poor prognosis. The onset and spread of stomach cancer are significantly influenced by changes in lipid metabolism-related pathways. This study aimed to discover a predictive signature for GC using lipid metabolism-related genes (LMRGs) and examine its correlation with the tumor immune microenvironment (TIME). Transcriptome data and clinical information from patients with GC were collected from the TCGA and GEO databases. Data from GC samples were analyzed using both bulk RNA-seq and single-cell sequencing of RNA (scRNA-seq). To identify survival-related differentially expressed LMRGs (DE-LMRGs), differential expression and prognosis studies were carried out. We built a predictive signature using LASSO regression and tested it on the TCGA and GSE84437 datasets. In addition, the correlation of the prognostic signature with the TIME was comprehensively analyzed. In this study, we identified 258 DE-LMRGs in GC and further screened seven survival-related DE-LMRGs. The results of scRNA-seq identified 688 differentially expressed genes (DEGs) between the three branches. Two critical genes (GPX3 and NNMT) were identified using the above two gene groups. In addition, a predictive risk score that relies on GPX3 and NNMT was developed. Survival studies in both the TCGA and GEO datasets revealed that patients categorized to be at low danger had a significantly greater prognosis than those identified to be at high danger. Additionally, by employing calibration plots based on TCGA data, the study demonstrated the substantial predictive capacity of a prognostic nomogram, which incorporated a risk score along with various clinical factors. Within the high-risk group, there was a noticeable abundance of active natural killer (NK) cells, quiescent monocytes, macrophages, mast cells, and activated CD4 + T cells. In summary, a two-gene signature and a predictive nomogram have been developed, offering accurate prognostic predictions for general survival in GC patients. These findings have the potential to assist healthcare professionals in making informed medical decisions and providing personalized treatment approaches.