Bilayer Forming Phospholipids as Targets for Cancer Therapy

Elucidating the role of lipid metabolism dysregulation in the transition from oral lichen planus to oral squamous cell carcinoma

BACKGROUND

Oral Lichen Planus (OLP) is a chronic inflammatory disorder that may progress to Oral Squamous Cell Carcinoma (OSCC). Lipid metabolism dysregulation has been implicated in tumor development and immune response modulation. This study aims to explore the role of lipid metabolism, particularly the lipids diacylglycerol (DAG), triacylglycerol (TAG), and phosphatidylcholine (PC), in the progression from OLP to OSCC, and to identify potential therapeutic targets for prevention and treatment.

METHODS

We performed a Mendelian randomization (MR) analysis to investigate the causal relationships between lipid metabolism and the risk of OLP and OSCC. Differential gene expression analysis was conducted to identify key genes related to lipid metabolism. The interactions of lipid species and key genes were examined using drug databases (DrugBank, DGIdb, and TCMSP) to explore potential drug candidates. Enrichment analysis of signaling pathways, including PPAR signaling, was also conducted to understand the underlying mechanisms.

RESULTS

Our MR analysis revealed that DAG exerts a protective effect in OLP (OR < 1), but its role shifts to a risk factor in OSCC (OR > 1), potentially by altering the tumor immune microenvironment. TAG and PI dysregulation also plays a critical role in tumorigenesis. Gene expression analysis identified several key lipid metabolism-related genes, including SLC27A6, FABP3, FABP4, ADIPOQ, and PLIN1, whose expression differed between OLP and OSCC, highlighting their importance in tumor progression. These genes were enriched in the PPAR signaling pathway, suggesting its involvement in tumor growth and immune modulation. Potential drug candidates, such as palm acid (PA), Imatinib, and Curcumin, were identified through drug-repurposing strategies.

CONCLUSION

Lipid metabolism dysregulation plays a crucial role in the progression of OLP to OSCC. Targeting key lipid metabolism pathways and genes, such as DAG, TAG, PI, and the PPAR pathway, may offer promising strategies for early diagnosis and therapeutic intervention. This study provides novel insights into the molecular mechanisms of OLP-to-OSCC progression and suggests potential drug candidates, including natural compounds, for future clinical applications. Further research is needed to validate these findings in clinical settings.

CLINICAL TRIAL NUMBER

Not applicable.

Phospholipid metabolism and drug resistance in cancer

Phospholipids, complex lipids prevalent in the human body, play crucial roles in various pathophysiological processes. Beyond their synthesis and degradation, phospholipids can influence chemoresistance by participating in ferroptosis. Extensive evidence highlights the significant link between tumor drug resistance and phospholipids. Therefore, drugs targeting phospholipid metabolism itself or the synthesis of corresponding composite materials will effectively overcome the difficulties of clinical tumor treatment.

Association of Plasma Lipid Patterns and LDL Cholesterol Levels with Breslow Thickness and Ulceration in Melanoma Patients

Recent evidence has highlighted the critical role of lipids in tumor biology. In this study, we analyzed the plasma lipid profiles of 151 melanoma patients (University of Debrecen, Department of Dermatology, Hungary) to examine the associations between specific lipid species and commonly used LDL-C lipid parameters, as well as the Breslow thickness and ulceration of primary tumors. Our analysis included patients who underwent primary tumor resection, comprising 83 individuals without metastases and 68 with metastases at the time of blood sampling. Lipid profiling was performed using the Lipidyzer™ platform, which targets over 1100 lipid species. Following quality control filtering, 802 lipids were included in the subsequent analyses. Ten lipids were found to have decreased plasma levels, while one lipid exhibited elevated plasma levels, both associated with an increased risk of higher Breslow thickness. Additionally, patients with thicker tumors (≥2 mm) demonstrated significantly higher LDL-C levels after adjusting for age, sex, therapy, and tumor presence (p = 0.032). Using forward stepwise regression, we identified a combination of four lipids-(CE(20:5), LCER(24:1), PE(P18:1/18:1), and LPE(18:2))-that demonstrated the strongest correlation with Breslow depth (AUC = 0.779, as determined by ROC analysis). Additionally, we identified 11 lipids significantly associated with tumor ulceration. Stepwise regression analysis further revealed two lipids (FFA(16:0) and PC(15:0/18:1)) capable of predicting tumor ulceration with an AUC score of 0.740. These findings suggest that individual lipid metabolism may influence tumor thickness and ulceration during the development and progression of primary melanoma.

Unmasking the lipid landscape: carbamazepine induces alterations in Leydig cell lipidome

Leydig cells rely on lipids and fatty acids (FA) for essential functions like maintaining structural integrity, energy metabolism, and steroid hormone synthesis, including testosterone production. Carbamazepine (CBZ), a common anticonvulsant medication, can influence lipid metabolism and profiles, potentially impacting Leydig cell function and testosterone levels. Understanding this interplay is crucial to optimize treatment strategies for individuals requiring CBZ therapy while mitigating any adverse effects on male reproductive health. This study focuses on evaluating the effects of selected CBZ concentrations on the lipid homeostasis of BLTK-1 murine Leydig cells. By employing liquid chromatography-mass spectrometry (LC-MS) and gas chromatography-mass spectrometry (GC-MS), we aimed to uncover the specific changes in lipid profiles induced by CBZ exposure (25 and 200 μM). FA analysis demonstrated a significant decrease in FA 22:6 n-3 with increasing CBZ concentration and an increase in the n-6/n-3 ratio. Furthermore, changes in the lipidome, particularly in lipid species belonging to phosphatidylethanolamine (PE), phosphatidylcholine (PC), phosphatidylglycerol (PG), and sphingomyelin (SM) classes were observed. PE and PC lipid species were significantly elevated in Leydig cells exposed to 200 μM CBZ, whereas PG and SM species were downregulated. CBZ treatment significantly altered the Leydig cell phospholipidome, suggesting specific phospholipids such as PG 40:4, PG 34:1, PC O-32:1, PC 32:2, and PE P-38:6, which exhibited the lowest p-values, as potential biomarkers for clinical assessment of CBZ's impact on Leydig cells. These findings underscore the intricate relationship between CBZ exposure and alterations in lipid profiles, offering potential insights for monitoring and mitigating the drug's effects on male reproductive health.

Metabolomics reveals that phosphatidylethanolamine can alleviate the toxicity of silica nanoparticles in human lung A549 cells

Silica nanoparticles (SiNPs) are widely utilized in occupational settings where they can cause lung damage through inhalation. The objective of this research was to explore the metabolic markers of SiNPs-induced toxicity on A549 cells by metabolomics and provide a foundation for studying nanoparticle-induced lung toxicity. Metabolomics analysis was employed to analyze the metabolites of SiNPs-treated A549 cells. LASSO regression was applied for selection, and protective measure experiments were conducted to validate the efficacy of selected potential toxicity mitigators. After SiNPs treatment, 23 differential metabolites were identified, including lipids, nucleotides, and organic oxidants. Pathway analysis revealed involvement in various biological processes. LASSO regression further identified six metabolites significantly associated with SiNPs toxicity. Notably, phosphatidylethanolamine (PE (14:1(9Z)/14:0)) showed enrichment in six significant metabolic pathways and with an AUC of 1 in the ROC curve. Protective measure experiments verified its protective effect on A549 cells and demonstrated its considerable inhibition of SiNPs-induced cytotoxicity. This study elucidated SiNPs-induced cytotoxicity on A549 cells and identified PE as a potential toxicity mitigator. These findings contribute to understanding the mechanisms of nanoparticle-induced lung toxicity and inform occupational health preventive strategies.

Network pharmacology and metabolomics elucidate the underlying effects and mechanisms of maackiain against endometrial cancer

Endometrial carcinoma (EC), a prevalent gynecological cancer, is characterized by rising incidence and mortality rates, highlighting the need for novel treatments to improve patient outcomes. Maackiain (MA) is a natural compound isolated from common herbal medicines, that has been reported to have anti-cancer effects. However, the underlying roles and mechanisms concerning EC remain unclear. This study focused on deeply exploring the potential roles and mechanisms of MA against EC by network pharmacology, experimentally validated, metabolomics, and molecular docking. A total of 86 potential targets of MA against EC were identified by network pharmacology. In vitro experiments further confirmed network pharmacology' predictions. In addition to suppressing EC cell proliferation, MA also paused the cell cycle at the G2/M phase in a dose-dependent manner. This effect is accompanied by increased p21 and phospho-p53 expression, as well as reduced expression of CDK1 and CCNB1. Furthermore, cell metabolomics analysis revealed that 285 metabolites were changed after MA administration, which majorly affects glycerophospholipid metabolism, nucleotide metabolism, choline metabolism in cancer, and purine metabolism. Combination network pharmacology, metabolomics, and molecular docking, PLA2G10, PDE4D, and PDE5A were found to be potential targets for therapeutic intervention. These findings underlined that MA has anti-EC potential by modulating multiple targets including PLA2G10, PDE4D, and PDE5A, inhibiting EC cell proliferation, inducing G2/M phase arrest, and causing metabolic shifts. This study provides theoretical support for advanced experimental research on its clinical applications.

Elucidating of the metabolic impact of risperidone on brain microvascular endothelial cells using untargeted metabolomics-based LC-MS

Risperidone is useful for the treatment of schizophrenia symptoms; however, it also has side effects, and an overdose can be harmful. The metabolic effects of risperidone at high therapeutic doses and its metabolites have not been elucidated. Endogenous cellular metabolites may be comprehensively analyzed using untargeted metabolomics-based liquid chromatography-mass spectrometry (LC-MS), which can reveal changes in cell regulation and metabolic pathways. By identifying the metabolites and pathway changes using a nontargeted metabolomics-based LC-MS approach, we aimed to shed light on the potential toxicological effects of high-dose risperidone on brain microvascular endothelial cells (MVECs) associated with the human blood brain barrier. A total of 42 metabolites were selected as significant putative metabolites of the toxicological response of high-dose risperidone in MVECs. Six highly correlated pathways were identified, including those involving diacylglycerol, fatty acid, ceramide, glycerophospholipid, amino acid, and tricarboxylic acid metabolism. We demonstrated that methods focused on metabolomics are useful for identifying metabolites that may be used to clarify the mechanism of drug-induced toxicity.

Identification of Phospholipids Relevant to Cancer Tissue Using Differential Ion Mobility Spectrometry

Phospholipids are the main building components of cell membranes and are also used for cell signaling and as energy storages. Cancer cells alter their lipid metabolism, which ultimately leads to an increase in phospholipids in cancer tissue. Surgical energy instruments use electrical or vibrational energy to heat tissues, which causes intra- and extracellular water to expand rapidly and degrade cell structures, bursting the cells, which causes the formation of a tissue aerosol or smoke depending on the amount of energy used. This gas phase analyte can then be analyzed via gas analysis methods. Differential mobility spectrometry (DMS) is a method that can be used to differentiate malignant tissue from benign tissues in real time via the analysis of surgical smoke produced by energy instruments. Previously, the DMS identification of cancer tissue was based on a 'black box method' by differentiating the 2D dispersion plots of samples. This study sets out to find datapoints from the DMS dispersion plots that represent relevant target molecules. We studied the ability of DMS to differentiate three subclasses of phospholipids (phosphatidylcholine, phosphatidylinositol, and phosphatidylethanolamine) from a control sample using a bovine skeletal muscle matrix with a 5 mg addition of each phospholipid subclass to the sample matrix. We trained binary classifiers using linear discriminant analysis (LDA) and support vector machines (SVM) for sample classification. We were able to identify phosphatidylcholine, -inositol, and -ethanolamine with SVM binary classification accuracies of 91%, 73%, and 66% and with LDA binary classification accuracies of 82%, 74%, and 72%, respectively. Phosphatidylcholine was detected with a reliable classification accuracy, but ion separation setups should be adjusted in future studies to reliably detect other relevant phospholipids such as phosphatidylinositol and phosphatidylethanolamine and improve DMS as a microanalysis method and identify other phospholipids relevant to cancer tissue.

Metabolic Reprogramming of Phospholipid Fatty Acids as a Signature of Lung Cancer Type

Background: Lung cancer is one of the leading causes of cancer-related mortality. Non-small cell lung cancer (NSCLC) and small cell lung cancer (SCLC) differ in aggressiveness, proliferation speed, metastasis propensity, and prognosis. Since tumor cells notably change lipid metabolism, especially phospholipids and fatty acids (FA), this study aimed to identify FA alterations in lung cancer tissues. Methods: Our study included patients with newly diagnosed, histologically confirmed SCLC (n = 27) and NSCLC (n = 37). Samples were collected from both malignant and healthy tissues from each patient, providing they were within subject design. Results: In both NSCLC and SCLC tumor tissues, FA contents were shifted toward pro-inflammatory profiles, with increased levels of some individual n-6 polyunsaturated FA (PUFA), particularly arachidonic acid, and elevated activity of Δ6 desaturase. Compared to healthy counterparts, lower levels of alpha-linolenic acid (18:3n-3) and total saturated FA (SFA) were found in NSCLC, while decreased levels of linoleic acid (18:2n-6) and all individual n-3 FA were found in SCLC tissue in comparison to the healthy tissue control. When mutually compared, SCLC tissue had higher levels of total SFA, especially stearic acid, while higher levels of linoleic acid, total PUFA, and n-3 and n-6 PUFA were detected in NSCLC. Estimated activities of Δ6 desaturase and elongase were higher in SCLC than in NSCLC. Conclusions: Our findings indicate a notable impairment of lipid metabolism in two types of lung cancer tissues. These type-specific alterations may be associated with differences in their progression and also point out different therapeutic targets.

A central composite design-based targeted quercetin nanoliposomal formulation: Optimization and cytotoxic studies on MCF-7 breast cancer cell lines

This study aimed to enhance the efficacy of quercetin (QT) by formulating it into a liposomal drug delivery system utilizing the concept of central composite design. The drug:lipid ratio, cholesterol concentration, and sonication time were selected as independent variables in the study. The vesicle and percentage entrapment efficiency were selected as the dependent variables. Quercetin nanoliposomes (QT-NLs) were prepared via a combination of ethanol injection and thin film hydration. The vesicle size and entrapment efficiency of all formulations were within the ranges of 100 nm and >80 %, respectively. The zeta potential value indicated the stability of the optimized formulation. The contour plots were used to select the desired batch range. SEM studies revealed an imperfect crystalline morphology without any unwanted agglomeration. MTT assays on VERO cell lines indicated the safety of the developed formulation. MTT assays of MCF-7 cells revealed IC50 values of 5.8 μM and 7.9 μM for QT-NLs and QT, respectively. In our study, the optimized formulation exhibited late and early apoptosis and necrosis when used to treat MCF-7 cells. S and G2/M cell cycle phases of MCF-7 cell arrest were confirmed by the cell cycle report. At sub-G0/G1 phase, 2.10 ± 1.1 %; G0/G1 phase, 34.13 ± 1.9 %; S phase, 34.55 ± 0.98 %; and G2/M phase, 26.24 ± 1.7 % of cell arrest were observed. The results demonstrated the effectiveness of the proposed design for the development of corn starch-coated QT-NLs and their activity in breast cancer cell lines.

Esterified styrene-maleic acid copolymer modified silica as mixed-mode polymer-brush stationary phases for chromatographic separation

Styrene-maleic acid (SMA) copolymer has received much attention for its excellent solubilization characteristics. In this work, SMA copolymer brush-based chromatographic stationary phases were exploited and developed for the first time. First, SMA copolymer brush was in situ grown on the surface of spherical silica via living/controlled reversible addition-fragmentation chain transfer (RAFT) polymerization method. Subsequently, as a proof-of-concept demonstration, the copolymer was esterified by diethylene glycol mono-2-ethylhexyl ether (DGME) and 2-(2-ethylhexyloxy) ethanol (EHOE), respectively. The obtained Sil-SMA-DGME and Sil-SMA-EHOE copolymer-brush chromatographic stationary phases were characterized by transmission electron microscopy, Fourier transform infrared spectrometer, X-ray photoelectron spectroscopy, and thermogravimetric analysis, respectively. The chromatographic retention mechanism indicated that both the two packed columns exhibited hydrophilic/reverse mixed-mode retention modes. The maximum column efficiency was up to 71,000 N/m. The chromatographic separation performance evaluation indicated that the novel kind of stationary phases had excellent separation capabilities for hydrophilic, hydrophobic compounds and phospholipid standards. In addition, by combination with mass spectrometry identification, the Sil-SMA-DGME column was further exploited for separation and identification of phospholipids in human lung cancer cells. Totally, 9 classes including 186 phospholipid species were successfully identified. The results demonstrated the promising application prospects of the novel kind of SMA copolymer-brush chromatographic stationary phases.

Spatial Metabolomics Profiling Reveals Curcumin Induces Metabolic Reprogramming in Three-Dimensional Tumor Spheroids

Curcumin is widely recognized for its diverse antitumor properties, ranging from breast cancer to many other types of cancers. However, its role in the tumor microenvironment remains to be elucidated. In this study, we established a 3D tumor spheroids model that can simulate the growth environment of tumor cells and visualized the antitumor metabolic alteration caused by curcumin using mass spectrometry imaging technology. Our results showed that curcumin not only exerts a profound impact on the growth and proliferation of breast cancer cells but in situ multivariate statistical analysis also reveals the significant effect on the overall metabolic profile of tumor spheroids. Meanwhile, our visualization map characterized curcumin metabolic processes of reduction and glucuronidation in tumor spheroids. More importantly, abnormal metabolic pathways related to lipid metabolism and polyamine metabolism were also remodeled at the metabolite and gene levels after curcumin intervention. These insights deepen our comprehension of the regulatory mechanism of curcumin on the tumor metabolic network, furnishing powerful references for antitumor treatment.

Design, Synthesis, Antitumor Activity and NMR-Based Metabolomics of Novel Amino Substituted Tetracyclic Imidazo[4,5-b]Pyridine Derivatives

Newly prepared tetracyclic imidazo[4,5-b]pyridine derivatives were synthesized to study their antiproliferative activity against human cancer cells. Additionally, the structure-activity was studied to confirm the impact of the N atom position in pyridine nuclei as well as the chosen amino side chains on antiproliferative activity. Targeted amino substituted regioisomers were prepared by using uncatalyzed amination from corresponding chloro substituted precursors. The most active compounds 6 a, 8 and 10 showed improved activity in comparison to standard drug etoposide with IC50 values in a nanomolar range of concentration (0.2-0.9 μM). NMR-based metabolomics is a powerful instrument to elucidate activity mechanism of new chemotherapeutics. Multivariate and univariate statistical analysis of metabolic profiles of non-small cell lung cancer cells before and after exposure to 6 a revealed significant changes in metabolism of essential amino acids, glycerophospholipids and oxidative defense. Insight into the changes of metabolic pathways that are heavily involved in cell proliferation and survival provide valuable guidelines for more detailed analysis of activity metabolism and possible targets of this class of bioactive compounds.

Chrysomycin A Reshapes Metabolism and Increases Oxidative Stress to Hinder Glioblastoma Progression

Glioblastoma represents the predominant and a highly aggressive primary neoplasm of the central nervous system that has an abnormal metabolism. Our previous study showed that chrysomycin A (Chr-A) curbed glioblastoma progression in vitro and in vivo. However, whether Chr-A could inhibit orthotopic glioblastoma and how it reshapes metabolism are still unclear. In this study, Chr-A markedly suppressed the development of intracranial U87 gliomas. The results from airflow-assisted desorption electrospray ionization mass spectrometry imaging (AFADESI-MSI) indicated that Chr-A improved the abnormal metabolism of mice with glioblastoma. Key enzymes including glutaminase (GLS), glutamate dehydrogenases 1 (GDH1), hexokinase 2 (HK2) and glucose-6-phosphate dehydrogenase (G6PD) were regulated by Chr-A. Chr-A further altered the level of nicotinamide adenine dinucleotide phosphate (NADPH), thus causing oxidative stress with the downregulation of Nrf-2 to inhibit glioblastoma. Our study offers a novel perspective for comprehending the anti-glioma mechanism of Chr-A, highlighting its potential as a promising chemotherapeutic agent for glioblastoma.

The associations between dysregulation of human blood metabolites and lung cancer risk: evidence from genetic data

BACKGROUND

Metabolic dysregulation is recognized as a significant hallmark of cancer progression. Although numerous studies have linked specific metabolic pathways to cancer incidence, the causal relationship between blood metabolites and lung cancer risk remains unclear.

METHODS

Genomic data from 29,266 lung cancer patients and 56,450 control individuals from the Transdisciplinary Research in Cancer of the Lung and the International Lung Cancer Consortium (TRICL-ILCCO) were utilized, and findings were replicated using additional data from the FinnGen consortium. The analysis focused on the associations between 486 blood metabolites and the susceptibility to overall lung cancer and its three major clinical subtypes. Various Mendelian randomization methods, including inverse-variance weighting, weighted median estimation, and MR-Egger regression, were employed to ensure the robustness of our findings.

RESULTS

A total of 19 blood metabolites were identified with significant associations with lung cancer risk. Specifically, oleate (OR per SD = 2.56, 95% CI: 1.51 to 4.36), 1-arachidonoylglyceropholine (OR = 1.79, 95% CI: 1.22 to 2.65), and arachidonate (OR = 1.67, 95% CI: 1.16 to 2.40) were associated with a higher risk of lung cancer. Conversely, 1-linoleoylglycerophosphoethanolamine (OR = 0.57, 95% CI: 0.40 to 0.82), ADpSGEGDFXAEGGGVR, a fibrinogen cleavage peptide (OR = 0.60, 95% CI: 0.47 to 0.77), and isovalerylcarnitine (OR = 0.62, 95% CI: 0.49 to 0.78) were associated with a lower risk of lung cancer. Notably, isoleucine (OR = 9.64, 95% CI: 2.55 to 36.38) was associated with a significantly higher risk of lung squamous cell cancer, while acetyl phosphate (OR = 0.11, 95% CI: 0.01 to 0.89) was associated with a significantly lower risk of small cell lung cancer.

CONCLUSION

This study reveals the complex relationships between specific blood metabolites and lung cancer risk, highlighting their potential as biomarkers for lung cancer prevention, screening, and treatment. The findings not only deepen our understanding of the metabolic mechanisms of lung cancer but also provide new insights for future treatment strategies.

Comprehensive lipidomics study of basa catfish and sole fish using ultra-performance liquid chromatography Q-extractive orbitrap mass spectrometry for fish authenticity

The authenticity of fish products has become a widespread issue in markets due to substitution and false labeling. Lipidomics combined with chemometrics enables the fraudulence identification of food through the analysis of a large amount of data. This study utilized ultra-high-performance liquid chromatography (UHPLC)-QE Orbitrap MS technology to comprehensively analyze the lipidomics of commercially available basa catfish and sole fish. In positive and negative ion modes, a total of 779 lipid molecules from 21 lipid subclasses were detected, with phospholipid molecules being the most abundant, followed by glycerides molecules. Significant differences in the lipidome fingerprinting between the two fish species were observed. A total of 165 lipid molecules were screened out as discriminative features to distinguish between basa catfish and sole fish, such as TAG(16:0/16:0/18:1), PC(14:0/22:3), and TAG(16:1/18:1/18:1), etc. This study could provide valuable insights into authenticating aquatic products through comprehensive lipidomics analysis, contributing to quality control and consumer protection in the food industry.

Characterisation of Canine and Feline Breast Tumours, Their Metastases, and Corresponding Primary Cell Lines Using LA-REIMS and DESI-MS Imaging

Breast cancer, a complex disease with a significant prevalence to form metastases, necessitates novel therapeutic strategies to improve treatment outcomes. Here, we present the results of a comparative molecular study of primary breast tumours, their metastases, and the corresponding primary cell lines using Desorption Electrospray Ionisation (DESI) and Laser-Assisted Rapid Evaporative Ionisation Mass Spectrometry (LA-REIMS) imaging. Our results show that ambient ionisation mass spectrometry technology is suitable for rapid characterisation of samples, providing a lipid- and metabolite-rich spectrum within seconds. Our study demonstrates that the lipidomic fingerprint of the primary tumour is not significantly distinguishable from that of its metastasis, in parallel with the similarity observed between their respective primary cell lines. While significant differences were observed between tumours and the corresponding cell lines, distinct lipidomic signatures and several phospholipids such as PA(36:2), PE(36:1), and PE(P-38:4)/PE(O-38:5) for LA-REIMS imaging and PE(P-38:4)/PE(O-38:5), PS(36:1), and PI(38:4) for DESI-MSI were identified in both tumours and cells. We show that the tumours' characteristics can be found in the corresponding primary cell lines, offering a promising avenue for assessing tumour responsiveness to therapeutic interventions. A comparative analysis by DESI-MSI and LA-REIMS imaging revealed complementary information, demonstrating the utility of LA-REIMS in the molecular imaging of cancer.

Plasma Metabolome Signatures to Predict Responsiveness to Neoadjuvant Chemotherapy in Breast Cancer

BACKGROUND

Neoadjuvant chemotherapy (NACT) has arisen as a treatment option for breast cancer (BC). However, the response to NACT is still unpredictable and dependent on cancer subtype. Metabolomics is a tool for predicting biomarkers and chemotherapy response. We used plasma to verify metabolomic alterations in BC before NACT, relating to clinical data.

METHODS

Liquid chromatography coupled to mass spectrometry (LC-MS) was performed on pre-NACT plasma from patients with BC (n = 75). After data filtering, an SVM model for classification was built and validated with 75%/25% of the data, respectively.

RESULTS

The model composed of 19 identified metabolites effectively predicted NACT response for training/validation sets with high sensitivity (95.4%/93.3%), specificity (91.6%/100.0%), and accuracy (94.6%/94.7%). In both sets, the panel correctly classified 95% of resistant and 94% of sensitive females. Most compounds identified by the model were lipids and amino acids and revealed pathway alterations related to chemoresistance.

CONCLUSION

We developed a model for predicting patient response to NACT. These metabolite panels allow clinical gain by building precision medicine strategies based on tumor stratification.

Dissecting causal relationships between gut microbiota, blood metabolites, and glioblastoma multiforme: a two-sample Mendelian randomization study

Background

Given the increasing interest in the role of gut microbiota in glioblastoma multiforme (GBM), our objective was to examine the potential causal relationship between gut microbiota and GBM, as well as the mediating effects of specific metabolites.

Methods

A bidirectional two-sample Mendelian randomization (MR) analysis was conducted to investigate the associations between 196 microbial taxa and GBM. A two-step MR technique was used to identify significant mediators in this relationship. Subsequently, a mediation analysis was performed to explore and quantify the mediating effects of specific metabolites on the causal relationship between gut microbiota and GBM.

Results

Five taxa showed significant associations with GBM. Among them, family Victivallaceae [odds ratio (OR): 1.95; 95% confidence interval (CI): 1.21, 3.13; p = 0.005] and genus Lactococcus (OR: 1.81; 95% CI: 1.04, 3.15; p = 0.036) were positively correlated with the risk of GBM, while phylum Cyanobacteria had a protective effect against GBM (OR: 0.45; 95% CI: 0.22, 0.89; p = 0.021). The mediation analysis revealed that the connections among family Victivallaceae, genus Lactococcus, phylum Cyanobacteria and GBM were mediated by Methyl-4-hydroxybenzoate sulfate, phosphoethanolamine and dehydroepiandrosterone sulfate. Each of these accounted for 7.27, 7.98, and 8.65%, respectively.

Conclusion

Our study provides evidence supporting a potential causal association between certain gut microbiota taxa and GBM. The study highlights the central role of gut microbiota in GBM pathogenesis and their interactions with vital serum metabolites. This paves the way for potential novel therapeutic interventions in GBM management.

Genetically predicted TWEAK mediates the association between lipidome and Keratinocyte Carcinomas

BACKGROUND

Reports suggest that lipid profiles may be linked to the likelihood of developing skin cancer, yet the exact causal relationship is still unknown.

OBJECTIVE

This study aimed to examine the connection between lipidome and skin cancers, as well as investigate any possible mediators.

METHODS

A two-sample Mendelian randomization (MR) analysis was conducted on 179 lipidomes and each skin cancer based on a genome-wide association study (GWAS), including melanoma, basal cell carcinoma (BCC), and squamous cell carcinoma (SCC). Then, Bayesian weighted MR was performed to verify the analysis results of two-sample MR. Moreover, a two-step MR was employed to investigate the impact of TNF-like weak inducer of apoptosis (TWEAK)-mediated lipidome on skin cancer rates.

RESULTS

MR analysis identified higher genetically predicted phosphatidylcholine (PC) (17:0_18:2) could reduce the risk of skin tumors, including BCC (OR = 0.9149, 95% CI: 0.8667-0.9658), SCC (OR = 0.9343, 95% CI: 0.9087-0.9606) and melanoma (OR = 0.9982, 95% CI: 0.9966-0.9997). The proportion of PC (17:0_18:2) predicted by TWEAK-mediated genetic prediction was 6.6 % in BCC and 7.6% in SCC. The causal relationship between PC (17:0_18:2) and melanoma was not mediated by TWEAK.

CONCLUSION

This study identified a negative causal relationship between PC (17:0_18:2) and keratinocyte carcinomas, a small part of which was mediated by TWEAK, and most of the remaining mediating factors are still unclear. Further research on other risk factors is needed in the future.

UHPLC-HRMS-based Multiomics to Explore the Potential Mechanisms and Biomarkers for Colorectal Cancer

BACKGROUND

Understanding the metabolic changes in colorectal cancer (CRC) and exploring potential diagnostic biomarkers is crucial for elucidating its pathogenesis and reducing mortality. Cancer cells are typically derived from cancer tissues and can be easily obtained and cultured. Systematic studies on CRC cells at different stages are still lacking. Additionally, there is a need to validate our previous findings from human serum.

METHODS

Ultrahigh-performance liquid chromatography tandem high-resolution mass spectrometry (UHPLC-HRMS)-based metabolomics and lipidomics were employed to comprehensively measure metabolites and lipids in CRC cells at four different stages and serum samples from normal control (NR) and CRC subjects. Univariate and multivariate statistical analyses were applied to select the differential metabolites and lipids between groups. Biomarkers with good diagnostic efficacy for CRC that existed in both cells and serum were screened by the receiver operating characteristic curve (ROC) analysis. Furthermore, potential biomarkers were validated using metabolite standards.

RESULTS

Metabolite and lipid profiles differed significantly among CRC cells at stages A, B, C, and D. Dysregulation of glycerophospholipid (GPL), fatty acid (FA), and amino acid (AA) metabolism played a crucial role in the CRC progression, particularly GPL metabolism dominated by phosphatidylcholine (PC). A total of 46 differential metabolites and 29 differential lipids common to the four stages of CRC cells were discovered. Eight metabolites showed the same trends in CRC cells and serum from CRC patients compared to the control groups. Among them, palmitoylcarnitine and sphingosine could serve as potential biomarkers with the values of area under the curve (AUC) more than 0.80 in the serum and cells. Their panel exhibited excellent performance in discriminating CRC cells at different stages from normal cells (AUC = 1.00).

CONCLUSIONS

To our knowledge, this is the first research to attempt to validate the results of metabolism studies of serum from CRC patients using cell models. The metabolic disorders of PC, FA, and AA were closely related to the tumorigenesis of CRC, with PC being the more critical factor. The panel composed of palmitoylcarnitine and sphingosine may act as a potential biomarker for the diagnosis of CRC, aiding in its prevention.

A novel insight into cancer therapy: Lipid metabolism in tumor-associated macrophages

The tumor immune microenvironment (TIME) can limit the effectiveness and often leads to significant side effects of conventional cancer therapies. Consequently, there is a growing interest in identifying novel targets to enhance the efficacy of targeted cancer therapy. More research indicates that tumor-associated macrophages (TAMs), originating from peripheral blood monocytes generated from bone marrow myeloid progenitor cells, play a crucial role in the tumor microenvironment (TME) and are closely associated with resistance to traditional cancer therapies. Lipid metabolism alterations have been widely recognized as having a significant impact on tumors and their immune microenvironment. Lipids, lipid derivatives, and key substances in their metabolic pathways can influence the carcinogenesis and progression of cancer cells by modulating the phenotype, function, and activity of TAMs. Therefore, this review focuses on the reprogramming of lipid metabolism in cancer cells and their immune microenvironment, in which the TAMs are especially concentrated. Such changes impact TAMs activation and polarization, thereby affecting the tumor cell response to treatment. Furthermore, the article explores the potential of targeting the lipid metabolism of TAMs as a supplementary approach to conventional cancer therapies. It reviews and evaluates current strategies for enhancing efficacy through TAMs' lipid metabolism and proposes new lipid metabolism targets as potential synergistic options for chemo-radiotherapy and immunotherapy. These efforts aim to stimulate further research in this area.

Urinary fatty acid biomarkers for prostate cancer detection

The lack of accuracy in the current prostate specific antigen (PSA) test for prostate cancer (PCa) screening causes around 60-75% of unnecessary prostate biopsies. Therefore, alternative diagnostic methods that have better accuracy and can prevent over-diagnosis of PCa are needed. Researchers have examined various potential biomarkers for PCa, and of those fatty acids (FAs) markers have received special attention due to their role in cancer metabolomics. It has been noted that PCa metabolism prefers FAs over glucose substrates for continued rapid proliferation. Hence, we proposed using a urinary FAs based model as a non-invasive alternative for PCa detection. Urine samples collected from 334 biopsy-designated PCa positive and 232 biopsy-designated PCa negative subjects were analyzed for FAs and lipid related compounds by stir bar sorptive extraction coupled with gas chromatography/mass spectrometry (SBSE-GC/MS). The dataset was split into the training (70%) and testing (30%) sets to develop and validate logit models and repeated for 100 runs of random data partitioning. Over the 100 runs, we confirmed the stability of the models and obtained optimal tuning parameters for developing the final FA based model. A PSA model using the values of the patients' PSA test results was constructed with the same cohort for the purpose of comparing the performances of the FA model against PSA test. The FA final model selected 20 FAs and rendered an AUC of 0.71 (95% CI = 0.67-0.75, sensitivity = 0.48, and specificity = 0.83). In comparison, the PSA model performed with an AUC of 0.51 (95% CI = 0.46-0.66, sensitivity = 0.44, and specificity = 0.71). The study supports the potential use of urinary FAs as a stable and non-invasive alternative test for PCa diagnosis.

Bioactive Functions of Lipids in the Milk Fat Globule Membrane: A Comprehensive Review

The milk fat globule membrane (MFGM) is a complex tri-layer membrane that wraps droplets of lipids in milk. In recent years, it has attracted widespread attention due to its excellent bioactive functions and nutritional value. MFGM contains a diverse array of bioactive lipids, including cholesterol, phospholipids, and sphingolipids, which play pivotal roles in mediating the bioactivity of the MFGM. We sequentially summarize the main lipid types in the MFGM in this comprehensive review and outline the characterization methods used to employ them. In this comprehensive review, we sequentially describe the types of major lipids found in the MFGM and outline the characterization methods employed to study them. Additionally, we compare the structural disparities among glycerophospholipids, sphingolipids, and gangliosides, while introducing the formation of lipid rafts facilitated by cholesterol. The focus of this review revolves around an extensive evaluation of the current research on lipid isolates from the MFGM, as well as products containing MFGM lipids, with respect to their impact on human health. Notably, we emphasize the clinical trials encompassing a large number of participants. The summarized bioactive functions of MFGM lipids encompass the regulation of human growth and development, influence on intestinal health, inhibition of cholesterol absorption, enhancement of exercise capacity, and anticancer effects. By offering a comprehensive overview, the aim of this review is to provide valuable insights into the diverse biologically active functions exhibited by lipids in the MFGM.

Lipidomics Profiling Reveals Serum Phospholipids Associated with Albuminuria in Early Type 2 Diabetic Kidney Disease

Early screening and administration of DKD are beneficial for renal outcomes of type 2 diabetic patients. However, the current early diagnosis using the albuminuria/creatine ratio (ACR) contains limitations. This study aimed to compare serum lipidome variation between type 2 diabetes and early DKD patients with increased albuminuria through an untargeted lipidomics method to explore the potential lipid biomarkers for DKD identification. 92 type 2 diabetic patients were enrolled and divided into two groups: DM group (ACR < 3 mg/mmol, n = 49) and early DKD group (3 mg/mmol ≤ ACR < 30 mg/mmol, n = 43). Fasting serum was analyzed through an ultraperformance liquid mass spectrometry tandem chromatography system (LC-MS). Orthogonal partial least-squares discriminant analysis (OPLS-DA) and univariate and multivariate analysis were performed to filter differentially depressed lipids. Receiver operating characteristic (ROC) curves were used to estimate the diagnostic capability of potential lipid biomarkers. We found that serum phospholipids including phosphatidylserine (PS), sphingomyelin (SM), and phosphatidylcholine (PC) were significantly upregulated in the DKD group and were highly correlated with the ACR. In addition, a panel of two phospholipids including PS(27:0)-H and PS(30:2e)-H showed good performance to help clinical lipids in early DKD identification, which increased the area under the curve (AUC) from 0.568 to 0.954. The study exhibited the serum lipidome variation in early DKD patients, and the increased phospholipids might participate in the development of albuminuria. The panel of PS(27:0)-H and PS(30:2e)-H could be a potential biomarker for DKD diagnosis.

Discovery of lipid profiles in plasma-derived extracellular vesicles as biomarkers for breast cancer diagnosis

Lipids are a major component of extracellular vesicles; however, their significance in tumorigenesis and progression has not been well elucidated. As we previously found that lipid profiles drastically changed in breast tumors upon progression, we hypothesized that lipid profiles of plasma-derived extracellular vesicles could be utilized as breast cancer biomarkers. Here, we adopted modified sucrose cushion ultracentrifugation to isolate plasma-derived extracellular vesicles from breast cancer (n = 105), benign (n = 11), and healthy individuals (n = 43) in two independent cohorts (n = 126 and n = 33) and conducted targeted lipidomic analysis. We established a breast cancer diagnostic model comprising three lipids that showed favorable performance with the area under the receiver operating characteristic curve of 0.759, 0.743, and 0.804 in the training, internal validation, and external test sets, respectively. Moreover, we identified several lipids that could effectively discriminate breast cancer progression and subtypes: phosphatidylethanolamines and phosphatidylserines were relatively higher in Stage III, whereas phosphatidylcholines and sphingomyelins were higher in Stage IV; phosphatidylcholines and ceramides were correspondingly concentrated in HER2-positive patients, while lysophosphatidylcholines and polyunsaturated triglycerides were concentrated in the triple-negative breast cancer subtype. Lipid profiling of plasma-derived extracellular vesicles is a non-invasive and promising approach for diagnosing, staging, and subtyping breast cancer.

Identification of Diagnostic Metabolic Signatures in Thyroid Tumors Using Mass Spectrometry Imaging

"Gray zone" thyroid follicular tumors are difficult to diagnose, especially when distinguishing between benign follicular thyroid adenoma (FTA) and malignant carcinoma (FTC). Thus, proper classification of thyroid follicular diseases may improve clinical prognosis. In this study, the diagnostic performance of metabolite enzymes was evaluated using imaging mass spectrometry to distinguish FTA from FTC and determine the association between metabolite enzyme expression with thyroid follicular borderline tumor diagnosis. Air flow-assisted desorption electrospray ionization mass spectrometry imaging (AFAIDESI-MSI) was used to build a classification model for thyroid follicular tumor characteristics among 24 samples. We analyzed metabolic enzyme marker expression in an independent validation set of 133 cases and further evaluated the potential biological behavior of 19 thyroid borderline lesions. Phospholipids and fatty acids (FAs) were more abundant in FTA than FTC (p < 0.001). The metabolic enzyme panel, which included FA synthase and Ca2+-independent PLA2, was further validated in follicular thyroid tumors. The marker combination showed optimal performance in the validation group (area under the ROC, sensitivity, and specificity: 73.6%, 82.1%, and 60.6%, respectively). The findings indicate that AFAIDESI-MSI, in combination with low metabolic enzyme expression, could play a role in the diagnosis of thyroid follicular borderline tumors for strict follow-up.

Metabolic Profiles Point Out Metabolic Pathways Pivotal in Two Glioblastoma (GBM) Cell Lines, U251 and U-87MG

Glioblastoma (GBM) is the most lethal central nervous system (CNS) tumor, mainly due to its high heterogeneity, invasiveness, and proliferation rate. These tumors remain a therapeutic challenge, and there are still some gaps in the GBM biology literature. Despite the significant amount of knowledge produced by research on cancer metabolism, its implementation in cancer treatment has been limited. In this study, we explored transcriptomics data from the TCGA database to provide new insights for future definition of metabolism-related patterns useful for clinical applications. Moreover, we investigated the impact of key metabolites (glucose, lactate, glutamine, and glutamate) in the gene expression and metabolic profile of two GBM cell lines, U251 and U-87MG, together with the impact of these organic compounds on malignancy cell features. GBM cell lines were able to adapt to the exposure to each tested organic compound. Both cell lines fulfilled glycolysis in the presence of glucose and were able to produce and consume lactate. Glutamine dependency was also highlighted, and glutamine and glutamate availability favored biosynthesis observed by the increase in the expression of genes involved in fatty acid (FA) synthesis. These findings are relevant and point out metabolic pathways to be targeted in GBM and also reinforce that patients' metabolic profiling can be useful in terms of personalized medicine.

Machine Learning Reveals Lipidome Remodeling Dynamics in a Mouse Model of Ovarian Cancer

Ovarian cancer (OC) is one of the deadliest cancers affecting the female reproductive system. It may present little or no symptoms at the early stages and typically unspecific symptoms at later stages. High-grade serous ovarian cancer (HGSC) is the subtype responsible for most ovarian cancer deaths. However, very little is known about the metabolic course of this disease, particularly in its early stages. In this longitudinal study, we examined the temporal course of serum lipidome changes using a robust HGSC mouse model and machine learning data analysis. Early progression of HGSC was marked by increased levels of phosphatidylcholines and phosphatidylethanolamines. In contrast, later stages featured more diverse lipid alterations, including fatty acids and their derivatives, triglycerides, ceramides, hexosylceramides, sphingomyelins, lysophosphatidylcholines, and phosphatidylinositols. These alterations underscored unique perturbations in cell membrane stability, proliferation, and survival during cancer development and progression, offering potential targets for early detection and prognosis of human ovarian cancer.

Effect of Short-Chain Fatty Acids and Polyunsaturated Fatty Acids on Metabolites in H460 Lung Cancer Cells

Lung cancer is the most common primary malignant lung tumor. However, the etiology of lung cancer is still unclear. Fatty acids include short-chain fatty acids (SCFAs) and polyunsaturated fatty acids (PUFAs) as essential components of lipids. SCFAs can enter the nucleus of cancer cells, inhibit histone deacetylase activity, and upregulate histone acetylation and crotonylation. Meanwhile, PUFAs can inhibit lung cancer cells. Moreover, they also play an essential role in inhibiting migration and invasion. However, the mechanisms and different effects of SCFAs and PUFAs on lung cancer remain unclear. Sodium acetate, butyrate, linoleic acid, and linolenic acid were selected to treat H460 lung cancer cells. Through untargeted metabonomics, it was observed that the differential metabolites were concentrated in energy metabolites, phospholipids, and bile acids. Then, targeted metabonomics was conducted for these three target types. Three LC-MS/MS methods were established for 71 compounds, including energy metabolites, phospholipids, and bile acids. The subsequent methodology validation results were used to verify the validity of the method. The targeted metabonomics results show that, in H460 lung cancer cells incubated with linolenic acid and linoleic acid, while the content of PCs increased significantly, the content of Lyso PCs decreased significantly. This demonstrates that there are significant changes in LCAT content before and after administration. Through subsequent WB and RT-PCR experiments, the result was verified. We demonstrated a substantial metabolic disparity between the dosing and control groups, further verifying the reliability of the method.

Hypoxia increases cellular levels of phosphatidic acid and lysophospholipids in undifferentiated Caco-2 cells

Cancer cells are known to survive in a hypoxic microenvironment by altering their lipid metabolism as well as their energy metabolism. In this study, Caco-2 cells derived from human colon cancer, were found to have elevated intracellular levels of phosphatidic acid and its lysoform, lysophosphatidic acid (LPA), under hypoxic conditions. Our results suggested that the elevation of LPA in Caco-2 cells was mainly due to the combined increases in cellular levels of lysophosphatidylcholine and lysophosphatidylethanolamine by phospholipase A₂ and subsequent hydrolysis to LPA by lysophospholipase D. We detected the Ca²⁺ -stimulated choline-producing activities toward exogenous lysophosphatidylcholines in whole Caco-2 cell homogenates, indicating their involvement in the LPA production in intact Caco-2 cells.

The Landscape of Lipid Metabolism in Lung Cancer: The Role of Structural Profiling

The aim of this study was to explore the relationship between lipids with different structural features and lung cancer (LC) risk and identify prospective biomarkers of LC. Univariate and multivariate analysis methods were used to screen for differential lipids, and two machine learning methods were used to define combined lipid biomarkers. A lipid score (LS) based on lipid biomarkers was calculated, and a mediation analysis was performed. A total of 605 lipid species spanning 20 individual lipid classes were identified in the plasma lipidome. Higher carbon atoms with dihydroceramide (DCER), phosphatidylethanolamine (PE), and phosphoinositols (PI) presented a significant negative correlation with LC. Point estimates revealed the inverse associated with LC for the n-3 PUFA score. Ten lipids were identified as markers with an area under the curve (AUC) value of 0.947 (95%, CI: 0.879-0.989). In this study, we summarized the potential relationship between lipid molecules with different structural features and LC risk, identified a panel of LC biomarkers, and demonstrated that the n-3 PUFA of the acyl chain of lipids was a protective factor for LC.

Computational and experimental therapeutic efficacy analysis of andrographolide phospholipid complex self-assembled nanoparticles against Neuro2a cells

BACKGROUND

Neuroblastoma is one of the most common malignancies in childhood, accounts for approximately 7% of all malignancies. Andrographolide (AN) inhibits cancer cells progression via multiple pathways like cell cycle arrest, mitochondrial apoptosis, NF-κβ inhibition, and antiangiogenesis mechanism. Despite multiple advantages, application of AN is very limited due to its low aqueous solubility (6.39 ± 0.47 μg/mL), high lipophilicity (log P ∼ 2.632 ± 0.135), and reduced stability owing to pH sensitive lactone ring.

OBJECTIVES AND RESULTS

In present investigation, a molecular complex of AN with soya-L-α-phosphatidyl choline (SPC) was synthesized as ANSPC and characterized by FT-IR and¹H NMR spectroscopy. Spectral and molecular simulation techniques confirmed the intermolecular interactions between the 14-OH group of AN and the N⁺(CH₃)₃part of SPC. In addition, molecular dynamics (MD) simulation was used to determine the degree of interaction between various proteins such as TNF-α, caspase-3, and Bcl-2. Later, ANSPC complex was transformed in to self-assembled soft nanoparticles of size 201.8 ± 1.48 nm with PDI of 0.092 ± 0.004 and zeta potential of -21.7 ± 0.85 mV. The IC50 offree AN (8.319 μg/mL) and the self-assembled soft ANSPC nanoparticles (3.406 μg/mL ∼ 1.2 μg of AN) against Neuro2a cells was estimated with significant (P < 0.05) difference. Interestingly, the self-assembled soft ANSPC nanoparticles showed better endocytosis compared to free AN in Neuro2a cells. In-vitrobiological assays confirmed that self-assembled soft ANSPC nanoparticles induces apoptosis in Neuro2a cells by declining the MMP (Δψm) and increasing the ROS generation.

CONCLUSION

Self-assembled soft ANSPC nanoparticles warrant further in-depth antitumor study in xenograft model of neuroblastoma to establish the anticancer potential.

Postoperative Metabolic Phenoreversion in Clear Cell Renal Cell Carcinoma

The ultimate goal of surgical treatment in cancer is to remove the tumor mass for restoring a healthy state. A 16-lipid panel that discriminated healthy controls from clear cell renal cell carcinoma (ccRCC) patients in a prior study was evaluated in the present work in paired-serum samples collected from patients (n = 41) before and after nephrectomy. Changes in the lipid and metabolite fingerprints from ccRCC patients were investigated and compared with fingerprints from healthy individuals obtained by means of ultra-performance liquid chromatography-high-resolution mass spectrometry. The lipid panel differentiated phenotypes associated with metabolic restoration after surgery, representing a serum signature of phenoreversion to a healthy metabolic state. In particular, PC 16:0/0:0, PC 18:2/18:2, and linoleic acid allowed discriminating serum samples from ccRCC patients with poor prognosis from those with an improved outcome during the follow-up period. Ratios of PC 16:0/0:0 and PC 18:2/18:2 with linoleic acid levels may contribute as prognostic tools to support decision-making during the patient follow-up care. The preliminary character of these results should be validated with larger cohorts, including subjects with different ethnicities, life style, and diets. MetaboLights study references: MTBLS1839, MTBLS3838, and MTBLS4629.

Machine Learning Reveals Lipidome Remodeling Dynamics in a Mouse Model of Ovarian Cancer

Ovarian cancer (OC) is one of the deadliest cancers affecting the female reproductive system. It may present little or no symptoms at the early stages, and typically unspecific symptoms at later stages. High-grade serous ovarian cancer (HGSC) is the subtype responsible for most ovarian cancer deaths. However, very little is known about the metabolic course of this disease, particularly in its early stages. In this longitudinal study, we examined the temporal course of serum lipidome changes using a robust HGSC mouse model and machine learning data analysis. Early progression of HGSC was marked by increased levels of phosphatidylcholines and phosphatidylethanolamines. In contrast, later stages featured more diverse lipids alterations, including fatty acids and their derivatives, triglycerides, ceramides, hexosylceramides, sphingomyelins, lysophosphatidylcholines, and phosphatidylinositols. These alterations underscored unique perturbations in cell membrane stability, proliferation, and survival during cancer development and progression, offering potential targets for early detection and prognosis of human ovarian cancer.

Teaser

Time-resolved lipidome remodeling in an ovarian cancer model is studied through lipidomics and machine learning.

Rapid Evaporative Ionization Mass Spectrometry-Based Lipidomics for Identification of Canine Mammary Pathology

The present work proposes the use of a fast analytical platform for the mass spectrometric (MS) profiling of canine mammary tissues in their native form for the building of a predictive statistical model. The latter could be used as a novel diagnostic tool for the real-time identification of different cellular alterations in order to improve tissue resection during veterinary surgery, as previously validated in human oncology. Specifically, Rapid Evaporative Ionization Mass Spectrometry (REIMS) coupled with surgical electrocautery (intelligent knife—iKnife) was used to collect MS data from histologically processed mammary samples, classified into healthy, hyperplastic/dysplastic, mastitis and tumors. Differences in the lipid composition enabled tissue discrimination with an accuracy greater than 90%. The recognition capability of REIMS was tested on unknown mammary samples, and all of them were correctly identified with a correctness score of 98–100%. Triglyceride identification was increased in healthy mammary tissues, while the abundance of phospholipids was observed in altered tissues, reflecting morpho-functional changes in cell membranes, and oxidized species were also tentatively identified as discriminant features. The obtained lipidomic profiles represented unique fingerprints of the samples, suggesting that the iKnife technique is capable of differentiating mammary tissues following chemical changes in cellular metabolism.