Clinical lipidomics in understanding of lung cancer: Opportunity and challenge

Alterations of Ceramides, Acylcarnitines, GlyceroLPLs, and Amines in NSCLC Tissues

Abnormal lipid metabolism plays an important role in cancer development. In this study, nontargeted lipidomic study on 230 tissue specimens from 79 nonsmall cell lung cancer (NSCLC) patients was conducted using ultraperformance liquid chromatography-high-resolution mass spectrometry (UPLC-HRMS). Downregulation of sphingosine and medium-long-chain ceramides and short-medium-chain acylcarnitine, upregulation of long-chain acylcarnitine C20:0, and enhanced histamine methylation were revealed in NSCLC tissues. Compared with paired noncancerous tissues, adenocarcinoma (AC) tissues had significantly decreased levels of sphingosine, medium-long-chain ceramides (Cer d18:1/12:0 and Cer d16:1/14:0, Cer d18:0/16:0, Cer d18:1/16:0, Cer d18:2/16:0, Cer d18:2/18:0), short-medium-chain (C2-C16) acylcarnitines, LPC 20:0 and LPC 22:1, and significantly increased levels of the long-chain acylcarnitine C20:0, LPC 16:0, LPC P-16:0, LPC 20:1, LPC 20:2, glyceroPC, LPE 16:0, and LPE 18:2. In squamous cell carcinoma (SCC) tissues, sphingosine, Cer d18:2/16:0 and Cer d18:2/18:0, and short-medium-chain acylcarnitines had significantly lower levels, while long-chain acylcarnitines (C20:0, and C22:0 or C22:0 M), LPC 20:1, LPC 20:2, and N1,N12-diacetylspermine had significantly higher levels compared to controls. In AC and SCC tissues, the levels of LPG 18:0, LPG 18:1, and LPS 18:1 were significantly decreased, while the levels of ceramide-1-phosphate (C1P) d18:0/3:0 or LPE P-16:0, N1-acetylspermidine, and 1-methylhistamine were significantly increased than controls. Furthermore, an orthogonal partial least-squares-discriminant analysis (OPLS-DA) model based on a 4-lipid panel was established, showing good discrimination ability between cancerous and noncancerous tissues.

Blocking ACSL6 Compromises Autophagy via FLI1-Mediated Downregulation of COLs to Radiosensitize Lung Cancer

Lung cancer (LC) is the leading cause of cancer-related mortality worldwide. Radiotherapy is the main component of LC treatment; however, its efficacy is often limited by radioresistance development, resulting in unsatisfactory clinical outcomes. Here, we found that LC radiosensitivity is up-regulated by decreased expression of long-chain acyl-CoA synthase 6 (ACSL6) after irradiation. Deletion of ACSL6 results in significant elevation of Friend leukemia integration 1 transcription factor (FLI1) and a marked decline of collagens (COLs). Blocking of ACSL6 impairs the tumor growth and upregulates FLI1, which reduces the levels of COLs and compromises irradiation-induced autophagy, leading to considerable therapeutic benefits during radiotherapy. Moreover, the direct interaction between ACSL6 and FLI1 and engagement between FLI1 and COLs indicates the involvement of the ACSL6-FLI1-COL axis. Finally, the potently adjusted autophagy flux reduces its otherwise contributive capability in surviving irradiation stress and leads to satisfactory radiosensitization for LC radiotherapy. These results demonstrate that enhanced ACSL6 expression promotes the aggressive performance of irradiated LC through increased FLI1-COL-mediated autophagy flux. Thus, the ACSL6-FLI1-Col-autophagy axis may be targeted to enhance the radiosensitivity of LC and improve the management of LC in radiotherapy.

Uncovering Porphyrin Accumulation in the Tumor Microenvironment

Heme, an iron-containing tetrapyrrole, is essential in almost all organisms. Heme biosynthesis needs to be precisely regulated particularly given the potential cytotoxicity of protoporphyrin IX, the intermediate preceding heme formation. Here, we report on the porphyrin intermediate accumulation within the tumor microenvironment (TME), which we propose to result from dysregulation of heme biosynthesis concomitant with an enhanced cancer survival dependence on mid-step genes, a process we recently termed "Porphyrin Overdrive". Specifically, porphyrins build up in both lung cancer cells and stromal cells in the TME. Within the TME's stromal cells, evidence supports cancer-associated fibroblasts (CAFs) actively producing porphyrins through an imbalanced pathway. Conversely, normal tissues exhibit no porphyrin accumulation, and CAFs deprived of tumor cease porphyrin overproduction, indicating that both cancer and tumor-stromal porphyrin overproduction is confined to the cancer-specific tissue niche. The clinical relevance of our findings is implied by establishing a correlation between imbalanced porphyrin production and overall poorer survival in more aggressive cancers. These findings illuminate the anomalous porphyrin dynamics specifically within the tumor microenvironment, suggesting a potential target for therapeutic intervention.

Phospholipidomics in Clinical Trials for Brain Disorders: Advancing our Understanding and Therapeutic Potentials

Phospholipidomics is a specialized branch of lipidomics that focuses on the characterization and quantification of phospholipids. By using sensitive analytical techniques, phospholipidomics enables researchers to better understand the metabolism and activities of phospholipids in brain disorders such as Alzheimer's and Parkinson's diseases. In the brain, identifying specific phospholipid biomarkers can offer valuable insights into the underlying molecular features and biochemistry of these diseases through a variety of sensitive analytical techniques. Phospholipidomics has emerged as a promising tool in clinical studies, with immense potential to advance our knowledge of neurological diseases and enhance diagnosis and treatment options for patients. In the present review paper, we discussed numerous applications of phospholipidomics tools in clinical studies, with a particular focus on the neurological field. By exploring phospholipids' functions in neurological diseases and the potential of phospholipidomics in clinical research, we provided valuable insights that could aid researchers and clinicians in harnessing the full prospective of this innovative practice and improve patient outcomes by providing more potent treatments for neurological diseases.

Adaptations of membrane trafficking in cancer and tumorigenesis

Membrane trafficking, a fundamental cellular process encompassing the transport of molecules to specific organelles, endocytosis at the plasma membrane and protein secretion, is crucial for cellular homeostasis and signalling. Cancer cells adapt membrane trafficking to enhance their survival and metabolism, and understanding these adaptations is vital for improving patient responses to therapy and identifying therapeutic targets. In this Review, we provide a concise overview of major membrane trafficking pathways and detail adaptations in these pathways, including COPII-dependent endoplasmic reticulum (ER)-to-Golgi vesicle trafficking, COPI-dependent retrograde Golgi-to-ER trafficking and endocytosis, that have been found in cancer. We explore how these adaptations confer growth advantages or resistance to cell death and conclude by discussing the potential for utilising this knowledge in developing new treatment strategies and overcoming drug resistance for cancer patients.

Roles of glutamic pyruvate transaminase 2 in reprogramming of airway epithelial lipidomic and metabolomic profiles after smoking

Metabolic abnormalities represent one of the pathological features of chronic obstructive pulmonary disease (COPD). Glutamic pyruvate transaminase 2 (GPT2) is involved in glutamate metabolism and lipid synthesis pathways, whilst the exact roles of GPT2 in the occurrence and development of COPD remains uncertain. This study aims at investigating how GPT2 and the associated genes modulate smoking-induced airway epithelial metabolism and damage by reprogramming lipid synthesis. The circulating or human airway epithelial metabolomic and lipidomic profiles of COPD patients or cell-lines explored with smoking were assessed to elucidate the pivotal roles of GPT2 in reprogramming processes. We found that GPT2 regulate the reprogramming of lipid metabolisms caused by smoking, especially phosphatidylcholine (PC) and triacylglycerol (TAG), along with changes in the expression of lipid metabolism-associated genes. GPT2 modulated cell sensitivities and survival in response to smoking by enhancing mitochondrial functions and maintaining lipid and energy homeostasis. Our findings provide evidence for the involvement of GPT2 in the reprogramming of airway epithelial lipids following smoking, as well as the molecular mechanisms underlying GPT2-mediated regulation, which may offer an alternative of therapeutic strategies for chronic lung diseases.

Integration of clinical phenoms and metabolomics facilitates precision medicine for lung cancer

Lung cancer is a common malignancy that is frequently associated with systemic metabolic disorders. Early detection is pivotal to survival improvement. Although blood biomarkers have been used in its early diagnosis, missed diagnosis and misdiagnosis still exist due to the heterogeneity of lung cancer. Integration of multiple biomarkers or trans-omics results can improve the accuracy and reliability for lung cancer diagnosis. As metabolic reprogramming is a hallmark of lung cancer, metabolites, specifically lipids might be useful for lung cancer detection, yet systematic characterizations of metabolites in lung cancer are still incipient. The present study profiled the polar metabolome and lipidome in the plasma of lung cancer patients to construct an inclusive metabolomic atlas of lung cancer. A comprehensive analysis of lung cancer was also conducted combining metabolomics with clinical phenotypes. Furthermore, the differences in plasma lipid metabolites were compared and analyzed among different lung cancer subtypes. Alcohols, amides, and peptide metabolites were significantly increased in lung cancer, while carboxylic acids, hydrocarbons, and fatty acids were remarkably decreased. Lipid profiling revealed a significant increase in plasma levels of CER, PE, SM, and TAG in individuals with lung cancer as compared to those in healthy controls. Correlation analysis confirmed the association between a panel of metabolites and TAGs. Clinical trans-omics studies elucidated the complex correlations between lipidomic data and clinical phenotypes. The present study emphasized the clinical importance of lipidomics in lung cancer, which involves the correlation between metabolites and the expressions of other omics, ultimately influencing clinical phenotypes. This novel trans-omics network approach would facilitate the development of precision therapy for lung cancer.

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.

Exploring Optimal Biomarker Sources: A Comparative Analysis of Exosomes and Whole Plasma in Fasting and Non-Fasting Conditions for Liquid Biopsy Applications

The study of liquid biopsy with plasma samples is being conducted to identify biomarkers for clinical use. Exosomes, containing nucleic acids and metabolites, have emerged as possible sources for biomarkers. To evaluate the effectiveness of exosomes over plasma, we analyzed the small non-coding RNAs (sncRNAs) and metabolites extracted from exosomes in comparison to those directly extracted from whole plasma under both fasting and non-fasting conditions. We found that sncRNA profiles were not affected by fasting in either exosome or plasma samples. Our results showed that exosomal sncRNAs were found to have more consistent profiles. The plasma miRNA profiles contained high concentrations of cell-derived miRNAs that were likely due to hemolysis. We determined that certain metabolites in whole plasma exhibited noteworthy concentration shifts in relation to fasting status, while others did not. Here, we propose that (1) fasting is not required for a liquid biopsy study that involves both sncRNA and metabolomic profiling, as long as metabolites that are not influenced by fasting status are selected, and (2) the utilization of exosomal RNAs promotes robust and consistent findings in plasma samples, mitigating the impact of batch effects derived from hemolysis. These findings advance the optimization of liquid biopsy methodologies for clinical applications.

Spatial metabolomics in head and neck tumors: a review

The joint analysis of single-cell transcriptomics, proteomics, lipidomics, metabolomics and spatial metabolomics is continually transforming our understanding of the mechanisms of metabolic reprogramming in tumor cells. Since head and neck tumor is the sixth most common tumor in the world, the study of the metabolic mechanism of its occurrence, development and prognosis is still undeveloped. In the past decade, this field has witnessed tremendous technological revolutions and considerable development that enables major breakthroughs to be made in the study of human tumor metabolism. In this review, a comprehensive comparison of traditional metabolomics and spatial metabolomics has been concluded, and the recent progress and challenges of the application of spatial metabolomics combined multi-omics in the research of metabolic reprogramming in tumors are reviewed. Furthermore, we also highlight the advances of spatial metabolomics in the study of metabolic mechanisms of head and neck tumors, and provide an outlook of its application prospects.

Associations between prefrontal PI (16:0/20:4) lipid, TNC mRNA, and APOA1 protein in schizophrenia: A trans-omics analysis in post-mortem brain

Background

Though various mechanisms have been proposed for the pathophysiology of schizophrenia, the full extent of these mechanisms remains unclear, and little is known about the relationships among them. We carried out trans-omics analyses by comparing the results of the previously reported lipidomics, transcriptomics, and proteomics analyses; all of these studies used common post-mortem brain samples.

Methods

We collected the data from three aforementioned omics studies on 6 common post-mortem samples (3 schizophrenia patients and 3 controls), and analyzed them as a whole group sample. Three correlation analyses were performed for each of the two of three omics studies in these samples. In order to discuss the strength of the correlations in a limited sample size, the p-values of each correlation coefficient were confirmed using the Student's t-test. In addition, partial correlation analysis was also performed for some correlations, to verify the strength of the impact of each factor on the correlations.

Results

The following three factors were strongly correlated with each other: the lipid level of phosphatidylinositol (PI) (16:0/20:4), the amount of TNC mRNA, and the quantitative signal intensity of APOA1 protein. PI (16:0/20:4) and TNC showed a positive correlation, while PI (16:0/20:4) and APOA1, and TNC and APOA1 showed negative correlations. All of these correlations reached at p < 0.01. PI (16:0/20:4) and TNC were decreased in the prefrontal cortex of schizophrenia samples, while APOA1 was increased. Partial correlation analyses among them suggested that PI (16:0/20:4) and TNC have no direct correlation, but their relationships are mediated by APOA1.

Conclusion

The current results suggest that these three factors may provide new clues to elucidate the relationships among the candidate mechanisms of schizophrenia, and support the potential of trans-omics analyses as a new analytical method.

Blood Profiles in the Prediction of Radioiodine Refractory Papillary Thyroid Cancer: A Case-Control Study

Purpose

Although most patients with papillary thyroid cancer can be cured by surgery and I-131 ablation, a small proportion will progress to radioactive iodine refractory (RAIR) thyroid cancer. The prediction of RAIR in its early stages can improve patient prognosis. The aim of this article is to evaluate the blood biomarkers in patients with RAIR and to establish a prediction model.

Patients and Methods

Data collected from patients with thyroid cancer that were enrolled from Jan. 2017 to Dec. 2021 were screened. RAIR was defined based on the criteria in the 2015 American Thyroid Association guidelines. The blood biomarkers from the study participants at three admissions timepoints (surgery and first and secondary I-131 ablations) were compared using both parametric and nonparametric tests to identify predictive factors for RAIR. Binary logistic regression analysis was used to construct a prediction model using parameters associated with surgical procedure decision. The model was then assessed with receiver operating characteristic curves.

Results

Thirty-six patients were included in the data analysis. Sixteen blood variables, including the low density lipoprotein-cholesterol-total cholesterol ratio, neutrophils, thyroglobulins, thyroglobulin antibody, thyroid peroxidase antibody, anion gap, etc., were revealed to be predictors for RAIR. The prediction model, which incorporated two parameters, reached an area under the curve of 0.861 (p<0.001).

Conclusion

Conventional blood biomarkers can be used in the prediction of early-stage RAIR. In addition, a prediction model incorporating multiple biomarkers can improve the predictive accuracy.

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.

Lysophosphatidylcholine inhibits lung cancer cell proliferation by regulating fatty acid metabolism enzyme long-chain acyl-coenzyme A synthase 5

Lung cancer is a widespread malignancy with a high death rate and disorder of lipid metabolism. Lysophosphatidylcholine (lysoPC) has anti-tumour effects, although the underlying mechanism is not entirely known. The purpose of this study aims at defining changes in lysoPC in lung cancer patients, the effects of lysoPC on lung cancer cells and molecular mechanisms. Lung cancer cell sensitivity to lysoPC was evaluated and decisive roles of long-chain acyl-coenzyme A synthase 5 (ACSL5) in lysoPC regulation were defined by comprehensively evaluating transcriptomic changes of ACSL5-downregulated epithelia. ACSL5 over-expressed in ciliated, club and Goblet cells in lung cancer patients, different from other lung diseases. LysoPC inhibited lung cancer cell proliferation, by inducing mitochondrial dysfunction, altering lipid metabolisms, increasing fatty acid oxidation and reprograming ACSL5/phosphoinositide 3-kinase/extracellular signal-regulated kinase-regulated triacylglycerol-lysoPC balance. Thus, this study provides a general new basis for the discovery of reprogramming metabolisms and metabolites as a new strategy of lung cancer precision medicine.

Plasma metabolomics, lipidomics and cytokinomics profiling predict disease recurrence in metastatic colorectal cancer patients undergoing liver resection

Purpose

In metastatic colorectal cancer (mCRC) patients (pts), treatment strategies integrating liver resection with induction chemotherapy offer better 5-year survival rates than chemotherapy alone. However, liver resection is a complex and costly procedure, and recurrence occurs in almost 2/3rds of pts, suggesting the need to identify those at higher risk. The aim of this work was to evaluate whether the integration of plasma metabolomics and lipidomics combined with the multiplex analysis of a large panel of plasma cytokines can be used to predict the risk of relapse and other patient outcomes after liver surgery, beyond or in combination with clinical morphovolumetric criteria.

Experimental design

Peripheral blood metabolomics and lipidomics were performed by 600 MHz NMR spectroscopy on plasma from 30 unresectable mCRC pts treated with bevacizumab plus oxaliplatin-based regimens within the Obelics trial (NCT01718873) and subdivided into responder (R) and non-R (NR) according to 1-year disease-free survival (DFS): ≥ 1-year (R, n = 12) and < 1-year (NR, n = 18). A large panel of cytokines, chemokines, and growth factors was evaluated on the same plasma using Luminex xMAP-based multiplex bead-based immunoassay technology. A multiple biomarkers model was built using a support vector machine (SVM) classifier.

Results

Sparse partial least squares discriminant analysis (sPLS-DA) and loading plots obtained by analyzing metabolomics profiles of samples collected at the time of response evaluation when resectability was established showed significantly different levels of metabolites between the two groups. Two metabolites, 3-hydroxybutyrate and histidine, significantly predicted DFS and overall survival. Lipidomics analysis confirmed clear differences between the R and NR pts, indicating a statistically significant increase in lipids (cholesterol, triglycerides and phospholipids) in NR pts, reflecting a nonspecific inflammatory response. Indeed, a significant increase in proinflammatory cytokines was demonstrated in NR pts plasma. Finally, a multiple biomarkers model based on the combination of presurgery plasma levels of 3-hydroxybutyrate, cholesterol, phospholipids, triglycerides and IL-6 was able to correctly classify patients by their DFS with good accuracy.

Conclusion

Overall, this exploratory study suggests the potential of these combined biomarker approaches to predict outcomes in mCRC patients who are candidates for liver metastasis resection after induction treatment for defining personalized management and treatment strategies.

Lipidomics combined with transcriptomic and mass spectrometry imaging analysis of the Asiatic toad (Bufo gargarizans) during metamorphosis and bufadienolide accumulation

Background

To adapt to life on land, Asiatic toads (Bufo gargarizans) must remodel their bodies and refine their chemical defenses in water. The full scope of the mechanisms underlying these processes has yet to be revealed. Bufadienolides (BDs) are chemical defense substances secreted by toads when they are in danger, and they have high medicinal value in treating heart failure, cancer, and hepatitis. However, the artificial breeding of toads to increase BDs has been unsuccessful due to the high mortality of toad larvae during metamorphosis.

Method

Toad larvae at different growth stages were selected to study the changes in the metamorphosis process under the same growth conditions. The differences of tadpoles were explored, including body remodeling, energy metabolism, synthesis and regulation of BDs, through lipidomic technology, transcriptomic technology, and mass spectrometry imaging technology during metamorphosis.

Results

During metamorphosis, tadpoles underwent significant changes in lipid metabolism due to body remodeling to adapt to terrestrial life, which involved ketosis, lipogenesis, cholesterol metabolism, and fatty acid oxidation. The accumulation trend of BDs was observed. “Pentose phosphate pathway” and “Aromatase activity” may be the critical pathway and GO term in BD synthesis, involving 16 genes predominantly expressed in the liver. The involved genes were mainly expressed in the liver, consistent with the synthetic site observed by mass spectrometry imaging.

Conclusion

Together, our findings presented the changes in the toad larvae during metamorphosis and highlighted the accumulation process of BDs as well as the regulatory pathways and synthetic site, providing research and theoretical basis for future development of the toad resources.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13020-022-00676-7.

Selective poly adenylation predicts the efficacy of immunotherapy in patients with lung adenocarcinoma by multiple omics research

The aim of this study was to find the application value of selective polyadenylation in immune cell infiltration, biological transcription function and risk assessment of survival and prognosis in lung adenocarcinoma (LUAD). The processed original mRNA expression data of LUAD were downloaded, and the expression profiles of 594 patient samples were collected. The (APA) events in TCGA-NA-SEQ data were evaluated by polyadenylation site use Index (PDUI) values, and the invasion of stromal cells and immune cells and tumor purity were calculated to group and select the differential genes. Lasso regression and stratified analysis were used to examine the role of risk scores in predicting patient outcomes. The study also used the GDSC database to predict the chemotherapeutic sensitivity of each tumor sample and used a regression method to obtain an IC50 estimate for each specific chemotherapeutic drug treatment. Then CIBERSORT algorithm was used to conduct Spearman correlation analysis, immune regulatory factor analysis and TIDE immune system function analysis for gene expression level and immune cell content. Finally, the Kaplan-Meier curve was used to analyze the correlation between stromal score and the immune score of LUAD. In this study, APA's LUAD risk score prognostic model was constructed. KM survival analysis showed that immune score affected the prognosis of LUAD patients ( P  = 0.027) but the matrix score was not statistically significant ( P  = 0.1). We extracted 108 genes with APA events from 827 different genes and based on PUDI clustering and heat map, the survival rate of patients in the four groups was significantly different ( P  = 0.05). Multiple omics studies showed that risk score was significantly positively correlated with Macrophages M0, T cells Follicular helper, B cells naive and NK cells resting. It is significantly negatively correlated with dendritic cells resting, mast cells resting, monocyte, T cells CD4 memory resting and B cells memory. We further explored the relationship between the expression of immunosuppressor genes and risk score and found that ADORA2A, BTLA, CD160, CD244, CD274, CD96, CSF1R and CTLA4 genes were highly correlated with the risk score. Selective poly adenylation plays an important role in the development and progression of LUAD, immune invasion, tumor cell invasion and metastasis and biological transcription, and affects the survival and prognosis of LUAD patients.

Lipidomics: An excellent tool for chronic disease detection

It has been known as almost all the cells consists a lipid molecule which has a considerable impact in various biological processes. Lipids have been investigated with a potential role for the formation of cellular membrane and thereby maintaining the structural integrity. Omics has placed as a combined technologies utilized for an exploaration of mechanistic actions in several kinds of molecules that make up the cells of an organism. Lipidomics has been recognized as a newly emerged branch of omics technology. This technology has the captivating factors to classify and characterize almost all the cellular lipids with the help of various analytical techniques and computational biological plateform. In lipidomics studies, structural display of several lipid biomarkers could also be analyzed and considered for actual disease diagnosis procedures. This could also replace certain traditional diagnostics method at all over the globe. Our review focuses how important this lipidomics particularly in disease diagnosis and also covers various analytical techniques and computational methods or bioinformatics tools in for the diagnosis of disease. In addtion, we also pinponted the possible role of lipids in several kinds of cellular disorders including cancer, neurodegenerative diseases, cardiovascular diseases, diabetes and obesity in human population. .

Prioritize biologically relevant ions for data-independent acquisition (BRI-DIA) in LC-MS/MS-based lipidomics analysis

INTRODUCTION

Data-dependent acquisition (DDA) is the most commonly used MS/MS scan method for lipidomics analysis on orbitrap-based instrument. However, MS instrument associated software decide the top N precursors for fragmentation, resulting in stochasticity of precursor selection and compromised consistency and reproducibility. We introduce a novel workflow using biologically relevant lipids to construct inclusion list for data-independent acquisition (DIA), named as BRI-DIA workflow.

OBJECTIVES

To ensure consistent coverage of biologically relevant lipids in LC-MS/MS-based lipidomics analysis.

METHODS

Biologically relevant ion list was constructed based on LIPID MAPS and lipidome atlas in MS-DIAL 4. Lipids were extracted from mouse tissues and used to assess different MS/MS scan workflow (DDA, BRI-DIA, and hybrid mode) on LC-Orbitrap Exploris 480 mass spectrometer.

RESULTS

DDA resulted in more MS/MS events, but the total number of unique lipids identified by three methods (DDA, BRI-DIA, and hybrid MS/MS scan mode) is comparable (580 unique lipids across 44 lipid subclasses in mouse liver). Major cardiolipin molecular species were identified by data generated using BRI-DIA and hybrid methods and allowed calculation of cardiolipin compositions, while identification of the most abundant cardiolipin CL72:8 was missing in data generated using DDA method, leading to wrong calculation of cardiolipin composition.

CONCLUSION

The method of using inclusion list comprised of biologically relevant lipids in DIA MS/MS scan is as efficient as traditional DDA method in profiling lipids, but offers better consistency of lipid identification, compared to DDA method. This study was performed using Orbitrap Exploris 480, and we will further evaluate this workflow on other platforms, and if verified by future work, this biologically relevant ion fragmentation workflow could be routinely used in many studies to improve MS/MS identification capacities.

Integration Profiling Between Plasma Lipidomics, Epstein–Barr Virus and Clinical Phenomes in Nasopharyngeal Carcinoma Patients

Plasma lipidomics has been commonly used for biomarker discovery. Studies in cancer have suggested a significant alteration of circulating metabolite profiles which is correlated with cancer characteristics and treatment outcome. However, the lipidomics characteristics of nasopharyngeal carcinoma (NPC) have rarely been studied. We previously described the phenomenon of lipid droplet accumulation in NPC cells and showed that such accumulation could be regulated by latent infection of Epstein–Barr virus (EBV). Here, we compared the plasma lipidome of NPC patients to that of healthy controls by liquid chromatography-tandem mass spectrometry (LC–MS/MS). We found 19 lipids (e.g., phosphatidylinositols 18:0/20:4 and 18:0/18:2 and free fatty acid 22:6) to be remarkably decreased, whereas 2 lipids (i.e., diacylglycerols 16:0/16:1 and 16:0/20:3) to be increased, in the plasma of NPC patients, compared with controls. Different lipid profiles were also observed between patients with different titers of EBV antibodies (e.g., EA-IgA and VCA-IgA) as well as between patients with and without lymph node or distant organ metastasis. In conclusion, plasma lipidomics might help to differentiate NPC cases from controls, whereas EBV infection might influence the risk and prognosis of NPC through modulating lipid metabolism in both tumor cells and peripheral blood.

The Role of Lipid Metabolism in Gastric Cancer

Gastric cancer has been one of the most common cancers worldwide with extensive metastasis and high mortality. Chemotherapy has been found as a main treatment for metastatic gastric cancer, whereas drug resistance limits the effectiveness of chemotherapy and leads to treatment failure. Chemotherapy resistance in gastric cancer has a complex and multifactorial mechanism, among which lipid metabolism plays a vital role. Increased synthesis of new lipids or uptake of exogenous lipids can facilitate the rapid growth of cancer cells and tumor formation. Lipids form the structural basis of biofilms while serving as signal molecules and energy sources. It is noteworthy that lipid metabolism is capable of inducing drug resistance in gastric cancer cells by reshaping the tumor micro-environment. In this study, new mechanisms of lipid metabolism in gastric cancer and the metabolic pathways correlated with chemotherapy resistance are reviewed. In particular, we discuss the effects of lipid metabolism on autophagy, biomarkers treatment and drug resistance in gastric cancer from the perspective of lipid metabolism. In brief, new insights can be gained into the development of promising therapies through an in-depth investigation of the mechanism of lipid metabolism reprogramming and resensitization to chemotherapy in gastric cancer cells, and scientific treatment can be provided by applying lipid-key enzyme inhibitors as cancer chemical sensitizers in clinical settings.

Regulatory roles of external cholesterol in human airway epithelial mitochondrial function through STARD3 signalling

BACKGROUND

Hypercholesterolemia is found in patients with chronic lung inflammation, during which airway epithelial cells play important roles in maintenance of inflammatory responses to pathogens. The present study aims at molecular mechanisms by which cholesterol changes airway epithelial sensitivity in response to smoking.

METHODS

Human bronchial epithelial cells (HBEs) were stimulated with cigarette smoke extract (CSE) and mice were exposed to CS/lipopolysaccharide (LPS) as models in vitro and in vivo. Severe COPD patients and healthy volunteers were also enrolled and the level of cholesterol in plasma was detected by metabolomics. Filipin III and elisa kits were used to stain free cholesterol. Mitochondrial function was detected by mitotracker green, mitotracker green, and Seahorse. Mitochondrial morphology was detected by high content screening and electron microscopy. The mRNA and protein levels of mitochondrial dynamics-related proteins were detected by RT-qPCR and Western blot,respectively. BODIPY 493/503 was used to stain lipid droplets. Lipidomics was used to detect intracellular lipid components. The mRNA level of interleukin (IL)-6 and IL-8 were detected by RT-qPCR.

RESULTS

We found that the cholesterol overload was associated with chronic obstructive pulmonary disease (COPD) and airway epithelia-driven inflammation, evidenced by hypercholesterolemia in patients with COPD and preclinical models, alteration of lipid metabolism-associated genes in CSE-induced airway epithelia and production of ILs. External cholesterol altered airway epithelial sensitivity of inflammation in response to CSE, through the regulation of STARD3-MFN2 pathway, cholesterol re-distribution, altered transport and accumulation of cholesterol, activities of lipid transport regulators and disorder of mitochondrial function and dynamics. MFN2 down-regulation increased airway epithelial sensitivity and production of ILs after smoking, at least partially by injuring fatty acid oxidation and activating mTOR phosphorylation.

CONCLUSIONS

Our data provide new insights for understanding molecular mechanisms of cholesterol-altered airway epithelial inflammation and for developing diagnostic biomarkers and therapeutic targets to improve patient outcomes.

Tissue Imprinting on 2D Nanoflakes-Capped Silicon Nanowires for Lipidomic Mass Spectrometry Imaging and Cancer Diagnosis

Spatially resolved tissue lipidomics is essential for accurate intraoperative and postoperative cancer diagnosis by revealing molecular information in the tumor microenvironment. Matrix-free laser desorption ionization mass spectrometry imaging (LDI-MSI) is an emerging attractive technology for label-free visualization of metabolites distributions in biological specimens. However, the development of LDI-MSI technology that could conveniently and authentically reveal molecular distribution on tissue samples is still a challenge. Herein, we present a tissue imprinting technology by retaining tissue lipids on 2D nanoflakes-capped silicon nanowires (SiNWs) for further mass spectrometry imaging and cancer diagnosis. The 2D nanoflakes were prepared by liquid exfoliation of molybdenum disulfide (MoS₂) with nitrogen-doped graphene quantum dots (NGQDs), which serve as both intercalation agent and dispersant. The obtained NGQD@MoS₂ nanoflakes were then decorated on the tip of vertical SiNWs, forming a hybrid NGQD@MoS₂/SiNWs nanostructure, which display excellent lipid extraction ability, enhanced LDI efficiency and molecule imaging capability. The peak number and total ion intensity of different lipids species on animal lung tissues obtained by tissue imprinting LDI-MSI on NGQD@MoS₂/SiNWs were ∼4-5 times greater than those on SiNWs substrate. As a proof-of-concept demonstration, the NGQD@MoS₂/SiNWs nanostructure was further applied to visualize phospholipids on sliced non small cell lung cancer (NSCLC) tissue along with the adjacent normal tissue. On the basis of selected feature lipids and machine learning algorithm, a prediction model was constructed to discriminate NSCLC tissues from the adjacent normal tissues with an accuracy of 100% for the discovery cohort and 91.7% for the independent validation cohort.

Screening of radiation gastrointestinal injury biomarkers in rat plasma by high-coverage targeted lipidomics

INTRODUCTION

In the event of radiological accidents and cancer radiotherapies in clinic, the gastrointestinal (GI) system is vulnerable to ionizing radiation and shows GI injury. Accessible biomarkers may provide means to predict, evaluate, and treat GI tissue damage. The current study investigated radiation GI injury biomarkers in rat plasma.

MATERIAL AND METHODS

High-coverage targeted lipidomics was employed to profile lipidome perturbations at 72 h after 0, 1, 2, 3, 5 and 8 Gy (⁶⁰Co γ-rays at 1 Gy/min) total-body irradiation in male rat jejunum. The results were correlated with previous plasma screening outcomes.

RESULTS

In total, 93 differential metabolites and 28 linear dose-responsive metabolites were screened in the jejunum. Moreover, 52 lipid species with significant differences both in jejunum and plasma were obtained. Three lipid species with linear dose-response relationship both in jejunum and plasma were put forth, which exhibited good to excellent sensitivity and specificity in triaging different exposure levels.

DISCUSSION

The linear dose-effect relationship of lipid metabolites in the jejunum and the triage performance of radiation GI injury biomarkers in plasma were studied for the first time.

CONCLUSION

The present study can provide insights into expanded biomarkers of IR-mediated GI injury and minimally invasive assays for evaluation.

Circulating Tumor-Macrophage Fusion Cells and Circulating Tumor Cells Complement Non-Small-Cell Lung Cancer Screening in Patients With Suspicious Lung-RADS 4 Nodules

PURPOSE

Low-dose computed tomography (LDCT) screening of high-risk patients decreases lung cancer-related mortality. However, high false-positive rates associated with LDCT result in unnecessary interventions. To distinguish non-small-cell lung cancer (NSCLC) from benign nodules, in the present study, we integrated cellular liquid biomarkers in patients with suspicious lung nodules (lung cancer screening reporting and data system [Lung-RADS] 4).

METHODS

Prospectively, 7.5 mL of blood was collected from 221 individuals (training set: 90 nonscreened NSCLC patients, 74 high-risk screening patients with no/benign nodules [Lung-RADS 1-3], and 20 never smokers; validation set: 37 patients with suspicious nodules [Lung-RADS 4]). Circulating tumor cells (CTCs), CTC clusters, and tumor-macrophage fusion (TMF) cells were identified by blinded analyses. Screening patients underwent a median of two LDCTs (range, 1-4) with a median surveillance time of 30 (range, 11-50) months.

RESULTS

In the validation set of 37 Lung-RADS 4 patients, all circulating cellular biomarker counts (P < .005; Wilcoxon test) and positivity rates were significantly higher in 23 biopsy-proven NSCLC patients (CTCs: 23 of 23 [100%], CTC clusters: 6 of 23 [26.1%], and TMF cells: 15 of 23 [65.2%]) than in 14 patients with biopsy-proven benign nodules (6 of 14 [42.9%], 0 of 14 [0%], and 2 of 14 [14.3%]). On the basis of cutoff values from the training set, logistic regression with receiver operating characteristic and area under the curve analyses demonstrated that CTCs (sensitivity: 0.870, specificity: 1.0, and area under the curve: 0.989) and TMF cells (0.652; 0.880; 0.790) complement LDCT in diagnosing NSCLC in Lung-RADS 4 patients.

CONCLUSION

Cellular liquid biomarkers have a potential to complement LDCT interpretation of suspicious Lung-RADS 4 nodules to distinguish NSCLC from benign lung nodules. A future prospective, large-scale, multicenter clinical trial should validate the role of cellular liquid biomarkers in improving diagnostic accuracy in high-risk patients with Lung-RADS 4 nodules.

Liu Shen Capsule Alters Airway Microbiota Composition and Metabolite Profiles in Healthy Humans

Alteration in airway microbiota composition and perturbations in microbe-metabolites interactions have been proposed as markers of many diseases. Liu Shen (LS) capsule, a traditional Chinese medicine, was proved as favorable in treating respiratory diseases. However, the effects of the LS capsule in terms of regulating human microorganisms and metabolite profiles are not well known. This study aimed to define and compare the respiratory microbiota composition and circulating and fecal metabolite profiles before and after LS capsule administration. A total of 30 healthy volunteers were recruited. The pharyngeal swab samples were collected for 16S rRNA gene sequencing. The serum and fecal samples were collected to analyze the non-targeted ultra-performance liquid chromatography–tandem mass spectrometry metabolomics. The airway microbial compositions were profoundly altered after LS capsule administration, as evidenced by increased microbial diversity and altered microbial taxa distribution. The increasing abundance of bacterial Bifidobacteria, and Lactobacillus characterized the after-administration groups, and the increasing of abundance bacterial Proteobacteria, Veillonella, Prevotella, Neisseria, and Actinomyces characterized the before-administration groups. Significant discriminations were observed in both serum and fecal metabolic profiles between the before- and after-administration groups. A total number of 134 and 71 significant HMDB taxonomic metabolites including glycerophospholipids, fatty acyls, and prenol lipids in the serum and fecal samples were identified respectively between the before- and after-administration groups. The integrated analysis showed that some altered airway microbiota phylum, such as Bacteroidetes and Proteobacteria, significantly correlated with metabolites in serum and fecal. Hence, our study reported the alternations in the composition and functions of the airway microbial community and the changes in circulating and fecal metabolite profiles after LS capsule administration in healthy humans, thus providing a novel insight into the mechanisms underlying the role of LS capsule treating and preventing related diseases.

Mechanistic insight into sevoflurane-associated developmental neurotoxicity

With the development of technology, more infants receive general anesthesia for surgery, other interventions, or clinical examination at an early stage after birth. However, whether general anesthetics can affect the function and structure of the developing infant brain remains an important, complex, and controversial issue. Sevoflurane is the most-used anesthetic in infants, but this drug is potentially neurotoxic. Short or single exposure to sevoflurane has a weak effect on cognitive function, while long or repeated exposure to general anesthetics may cause cognitive dysfunction. This review focuses on the mechanisms by which sevoflurane exposure during development may induce long-lasting undesirable effects on the brain. We review neural cell death, neural cell damage, impaired assembly and plasticity of neural circuits, tau phosphorylation, and neuroendocrine effects as important mechanisms for sevoflurane-induced developmental neurotoxicity. More advanced technologies and methods should be applied to determine the underlying mechanism(s) and guide prevention and treatment of sevoflurane-induced neurotoxicity.

1. We discuss the mechanisms underlying sevoflurane-induced developmental neurotoxicity from five perspectives: neural cell death, neural cell damage, assembly and plasticity of neural circuits, tau phosphorylation, and neuroendocrine effects. 2. Tau phosphorylation, IL-6, and mitochondrial dysfunction could interact with each other to cause a nerve damage loop. 3. miRNAs and lncRNAs are associated with sevoflurane-induced neurotoxicity.

Clinical challenges of tissue preparation for spatial transcriptome

Spatial transcriptomics is considered as an important part of spatiotemporal molecular images to bridge molecular information with clinical images. Of those potentials and opportunities, the excellent quality of human sample preparation and handling will ensure the precise and reliable information generated from clinical spatial transcriptome. The present study aims at defining potential factors that might influence the quality of spatial transcriptomics in lung cancer, para-cancer, or normal tissues, pathological images of sections and the RNA integrity before spatial transcriptome sequencing. We categorised potential influencing factors from clinical aspects, including patient selection, pathological definition, surgical types, sample harvest, temporary preservation conditions and solutions, frozen approaches, transport and storage conditions and duration. We emphasis on the relationship between the combination of histological scores with RNA integrity number (RIN) and the unique molecular identifier (UMI), which is determines the quality of of spatial transcriptomics; however, we did not find significantly relevance between them. Our results showed that isolated times and dry conditions of sample are critical for the UMI and the quality of spatial transcriptomic samples. Thus, clinical procedures of sample preparation should be furthermore optimised and standardised as new standards of operation performance for clinical spatial transcriptome. Our data suggested that the temporary preservation time and condition of samples at operation room should be within 30 min and in 'dry' status. The direct cryo-preservation within OCT media for human lung sample is recommended. Thus, we believe that clinical spatial transcriptome will be a decisive approach and bridge in the development of spatiotemporal molecular images and provide new insights for understanding molecular mechanisms of diseases at multi-orientations.

Comparison of one-phase and two-phase extraction methods for porcine tissue lipidomics applying a fast and reliable tentative annotation workflow

Lipidomics has great potential for the discovery of biomarkers, elucidation of metabolic processes and identifying dysregulations in complex biological systems. Concerning biofluids like plasma or cerebrospinal fluid, several studies for the comparison of lipid extraction solvents have already been conducted. With respect to tissues, which can differ significantly in terms of dry matter content and composition, only few studies are available. The proper selection of an extraction method that covers the complexity and individuality of different tissues is challenging. The goal of this work was to provide a systematic overview on the potential of different extraction methods for a broad applicability. This study covers six different extraction procedures and four different reconstitution solvents applied to ten different porcine tissues. To get an overview of the individual lipid profiles, a workflow was developed for a fast and reliable tentative lipid annotation. Therefore, several machine learning tools were utilized, like the prediction of collision cross sections to support the tentative lipid identification in case of untargeted lipidomics. In terms of data evaluation, unsupervised (e.g. principal component analysis) and supervised (e.g. partial least square - discriminant analysis) methods were applied to visualize and subsequently interpret all generated information. Furthermore, the influence of the tissue composition on the extraction performance was investigated. It could be shown that the ten porcine tissues can be distinguished based on their lipid profile with the applied workflow and that the methyl-tert-butyl ether (MTBE) based extraction method (two-phase) showed the best overall performance for the 16 examined lipid species. With this method the highest number of features (428 in lung tissue) could be annotated. Upcoming one-phase extractions also showed a high potential concerning total number of extracted lipids. Methanol/MTBE/chloroform (MMC) extracted slightly less lipids (393 in lung and liver) than MTBE but turned out to be the best one-phase extraction method. Additionally, the numbers of extracted lipids obtained by isopropanol/water 90:10 (IPA90) (399 in stomach) and by isopropanol/methanol/chloroform (IMC) (395 in stomach) were similar to those of the modified Folch method (402 in stomach). One-phase extractions can therefore clearly be seen as preferable when a high throughput is needed.

Exploring Serum NMR-Based Metabolomic Fingerprint of Colorectal Cancer Patients: Effects of Surgery and Possible Associations with Cancer Relapse

Background: Colorectal cancer (CRC) is the fourth most commonly diagnosed and third most deadly cancer worldwide. Surgery is the main treatment option for early disease; however, a relevant proportion of CRC patients relapse. Here, variations among preoperative and postoperative serum metabolomic fingerprint of CRC patients were studied, and possible associations between metabolic variations and cancer relapse were explored. Methods: A total of 41 patients with stage I-III CRC, planned for radical resection, were enrolled. Serum samples, collected preoperatively (t0) and 4–6 weeks after surgery before the start of any treatment (t1), were analyzed via NMR spectroscopy. NMR data were analyzed using multivariate and univariate statistical approaches. Results: Serum metabolomic fingerprints show differential clustering between t0 and t1 (82–85% accuracy). Pyruvate, HDL-related parameters, acetone, and 3-hydroxybutyrate appear to be the major players in this discrimination. Eight out of the 41 CRC patients enrolled developed cancer relapse. Postoperative, relapsed patients show an increase of pyruvate and HDL-related parameters, and a decrease of Apo-A1 Apo-B100 ratio and VLDL-related parameters. Conclusions: Surgery significantly alters the metabolomic fingerprint of CRC patients. Some metabolic changes seem to be associated with the development of cancer relapse. These data, if validated in a larger cohort, open new possibilities for risk stratification in patients with early-stage CRC.

Revealing potential lipid biomarkers in clear cell renal cell carcinoma using targeted quantitative lipidomics

BACKGROUND

The high drug resistance and metabolic reprogramming of clear cell renal cell carcinoma (ccRCC) are considered responsible for poor prognosis. In-depth research at multiple levels is urgently warranted to illustrate the lipid composition, distribution, and metabolic pathways of clinical ccRCC specimens.

METHODS

In this project, a leading-edge targeted quantitative lipidomic study was conducted using 10 pairs of cancerous and adjacent normal tissues obtained from ccRCC patients. Accurate lipid quantification was performed according to a linear equation calculated using internal standards. Qualitative and quantitative analyses of lipids were performed with multiple reaction monitoring analysis based on ultra-performance liquid chromatography (UPLC) and mass spectrometry (MS). Additionally, a multivariate statistical analysis was performed using data obtained on lipids.

RESULTS

A total of 28 lipid classes were identified. Among them, the most abundant were triacylglycerol (TG), diacylglycerol (DG), phosphatidylcholine (PC), and phosphatidylethanolamine (PE). Cholesteryl ester (CE) was the lipid exhibiting the most considerable difference between normal samples and tumor samples. Lipid content, chain length, and chain unsaturation of acylcarnitine (CAR), CE, and DG were found to be significantly increased. Based on screening for variable importance in projection scores ≥1, as well as fold change limits between 0.5 and 2, 160 differentially expressed lipids were identified. CE was found to be the most significantly upregulated lipid, while TG was observed to be the most significantly downregulated lipid.

CONCLUSION

Based on the absolute quantitative analysis of lipids in ccRCC specimens, it was observed that the content and change trends varied in different lipid classes. Upregulation of CAR, CE, and DG was observed, and analysis of changes in the distribution helped clarify the causes of lipid accumulation in ccRCC and possible carcinogenic molecular mechanisms. The results and methods described herein provide a comprehensive analysis of ccRCC lipid metabolism and lay a theoretical foundation for cancer treatment.

New focuses on roles of communications between endoplasmic reticulum and mitochondria in identification of biomarkers and targets

The communication between endoplasmic reticulum (ER) and mitochondria (Mt) plays important roles in maintenance of intra- and extra-cellular microenvironment, metabolisms, signaling activities and cell-cell communication. The present review aims to overview the advanced understanding about roles of ER-Mt structural contacts, molecular interactions and chemical exchanges, signal transmissions and inter-organelle regulations in ER-Mt communication. We address how the ER-Mt communication contributes to the regulation of lipid, amino acid and glucose metabolisms by enzymes, transporters and regulators in the process of biosynthesis. We specially emphasize the importance of deep understanding about molecular mechanisms of ER-Mt communication for identification and development of biology-specific, disease-specific and metabolism-specific biomarkers and therapeutic targets for human diseases. The inhibitors and modulators of the ER-Mt communication are categorized according to therapeutic targets. Rapid development of biotechnologies will provide new insights for spatiotemporally understanding the molecular mechanisms of ER-Mt communication.

Dysregulation of cholesterol homeostasis in human lung cancer tissue and tumour-associated macrophages

Background

Based on reports on elevated cholesterol levels in cancer cells, strategies to lower cholesterol synthesis have been suggested as an antitumour strategy. However, cholesterol depletion has also been shown to induce tumour-promoting actions in tumour-associated macrophages (TAMs).

Methods

We performed lipidomic and transcriptomic analyses of human lung cancer material. To assess whether the TAM phenotype is shaped by secreted factors produced by tumour cells, primary human monocyte-derived macrophages were polarized towards a TAM-like phenotype using tumour cell-conditioned medium.

Findings

Lipidomic analysis of lung adenocarcinoma (n=29) and adjacent non-tumour tissues (n=22) revealed a significant accumulation of free cholesterol and cholesteryl esters within the tumour tissue. In contrast, cholesterol levels were reduced in TAMs isolated from lung adenocarcinoma tissues when compared with alveolar macrophages (AMs) obtained from adjacent non-tumour tissues. Bulk-RNA-Seq revealed that genes involved in cholesterol biosynthesis and metabolism were downregulated in TAMs, while cholesterol efflux transporters were upregulated. In vitro polarized TAM-like macrophages showed an attenuated lipogenic gene expression signature and exhibited lower cholesterol levels compared with non-polarized macrophages. A genome-wide comparison by bulk RNA-Seq confirmed a high similarity of ex vivo TAMs and in vitro TAM-like macrophages. Modulation of intracellular cholesterol levels by either starving, cholesterol depletion, or efflux transporter inhibition indicated that cholesterol distinctly shapes macrophage gene expression.

Interpretation

Our data show an opposite dysregulation of cholesterol homeostasis in tumour tissue vs. TAMs. Polarization of in vitro differentiated macrophages by tumour cell-conditioned medium recapitulates key features of ex vivo TAMs.

CD44-Targeted and Enzyme-Responsive Photo-Cross-Linked Nanogels with Enhanced Stability for In Vivo Protein Delivery

One of the biggest challenges of the protein delivery system is to realize stable and high protein encapsulation efficiency in blood circulation and rapid release of protein in the targeted tumor cells. To overcome these hurdles, we fabricated enzyme-responsive photo-cross-linked nanogels (EPNGs) through UV-triggered chemical cross-linking of cinnamyloxy groups in the side chain of PEGylation hyaluronic acid (HA) for CD44-targeted transport of cytochrome c (CC). The EPNGs showed high loading efficiency and excellent stability in different biological media. Notably, CC leakage effectively suppressed under physiological conditions but accelerated release in the presence of hyaluronidase, an overexpressed enzyme in tumor cells. Moreover, thiazolylblue tetrazolium bromide (MTT) results indicated that the vacant EPNGs showed excellent nontoxicity, while CC-loaded EPNGs exhibited higher killing efficiency to CD44-positive A549 cells than to CD44-negative HepG2 cells and free CC. Confocal images confirmed that CC-loaded EPNGs could effectively be internalized by CD44-mediated endocytosis pathway and rapidly escape from the endo/lysosomal compartment. Human lung tumor-bearing mice imaging assays further revealed that CC-loaded EPNGs actively target tumor locations. Remarkably, CC-loaded EPNGs also exhibited enhanced antitumor activity with negligible systemic toxicity. These results implied that these EPNGs have appeared as stable and promising nanocarriers for tumor-targeting protein delivery.

Precision Oncology via NMR-Based Metabolomics: A Review on Breast Cancer

Precision oncology is an emerging approach in cancer care. It aims at selecting the optimal therapy for the right patient by considering each patient’s unique disease and individual health status. In the last years, it has become evident that breast cancer is an extremely heterogeneous disease, and therefore, patients need to be appropriately stratified to maximize survival and quality of life. Gene-expression tools have already positively assisted clinical decision making by estimating the risk of recurrence and the potential benefit from adjuvant chemotherapy. However, these approaches need refinement to further reduce the proportion of patients potentially exposed to unnecessary chemotherapy. Nuclear magnetic resonance (NMR) metabolomics has demonstrated to be an optimal approach for cancer research and has provided significant results in BC, in particular for prognostic and stratification purposes. In this review, we give an update on the status of NMR-based metabolomic studies for the biochemical characterization and stratification of breast cancer patients using different biospecimens (breast tissue, blood serum/plasma, and urine).

E3 ubiquitin ligase PJA1 regulates lung adenocarcinoma apoptosis and invasion through promoting FOXR2 degradation

Among all lung cancer cases, lung adenocarcinoma (LAC) represents nearly 40% and remains the leading cause of cancer deaths worldwide. Although the combination therapy of surgical treatment with radiotherapy, chemotherapy, and immunotherapy, has been used to treat LAC, unfortunately, high recurrence rates and poor survival remain. Therefore, novel prognostic markers and new targets for molecular targeted therapy in LAC is urgently needed. Fork-head box R2 (FOXR2) plays a key role in a wide range of cellular processes, including cellular proliferation, invasion, differentiation, and apoptosis, and it has been reported to be implicated in progression of LAC, thus inhibition of FOXR2 may be a novel targeting therapy for lung cancer. This current study found that E3 ligase PJA1 regulates ubiquitin-mediated degradation of FOXR2 and predicts good outcome of patients with LAC. In addition, it was showed force expression of PJA1 significantly inhibited LAC cells invasion and induced apoptosis in vitro through inactivating Wnt/β-catenin signaling pathway. In short, our findings reveal that PJA1 could be a potential diagnostic and prognostic biomarkers and the PJA1- FOXR2 axis could be served as a promising target for LAC therapy.

Combining Field-Enabled Capillary Vibrating Sharp-Edge Spray Ionization with Microflow Liquid Chromatography and Mass Spectrometry to Enhance 'Omics Analyses

Field-enabled capillary vibrating sharp-edge spray ionization (cVSSI) has been combined with high-flow liquid chromatography (LC) and mass spectrometry (MS) to establish current ionization capabilities for metabolomics and proteomics investigations. Comparisons are made between experiments employing cVSSI and a heated electrospray ionization probe representing the state-of-the-art in microflow LC-MS methods for 'omics studies. For metabolomics standards, cVSSI is shown to provide an ionization enhancement by factors of 4 ± 2 for both negative and positive ion mode analyses. For chymotryptic peptides, cVSSI is shown to provide an ionization enhancement by factors of 5 ± 2 and 2 ± 1 for negative and positive ion mode analyses, respectively. Slightly broader high-performance liquid chromatography peaks are observed in the cVSSI datasets, and several studies suggest that this results from a slightly decreased post-split flow rate. This may result from partial obstruction of the pulled-tip emitter over time. Such a challenge can be remedied with the use of LC pumps that operate in the 10 to 100 μL·min-1 flow regime. At this early stage, the proof-of-principle studies already show ion signal advantages over state-of-the-art electrospray ionization (ESI) for a wide variety of analytes in both positive and negative ion mode. Overall, this represents a ∼20-50-fold improvement over the first demonstration of LC-MS analyses by voltage-free cVSSI. Separate comparisons of the ion abundances of compounds eluting under identical solvent conditions reveal ionization efficiency differences between cVSSI and ESI and may suggest varied contributions to ionization from different physicochemical properties of the compounds. Future investigations of parameters that could further increase ionization gains in negative and positive ion mode analyses with the use of cVSSI are briefly presented.

Metabolomic/lipidomic profiling of COVID-19 and individual response to tocilizumab

The current pandemic emergence of novel coronavirus disease (COVID-19) poses a relevant threat to global health. SARS-CoV-2 infection is characterized by a wide range of clinical manifestations, ranging from absence of symptoms to severe forms that need intensive care treatment. Here, plasma-EDTA samples of 30 patients compared with age- and sex-matched controls were analyzed via untargeted nuclear magnetic resonance (NMR)-based metabolomics and lipidomics. With the same approach, the effect of tocilizumab administration was evaluated in a subset of patients. Despite the heterogeneity of the clinical symptoms, COVID-19 patients are characterized by common plasma metabolomic and lipidomic signatures (91.7% and 87.5% accuracy, respectively, when compared to controls). Tocilizumab treatment resulted in at least partial reversion of the metabolic alterations due to SARS-CoV-2 infection. In conclusion, NMR-based metabolomic and lipidomic profiling provides novel insights into the pathophysiological mechanism of human response to SARS-CoV-2 infection and to monitor treatment outcomes.

The current COVID-19 pandemic caused by severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) is markedly affecting the world population. Here we report about the small-molecule profile of patients hospitalized during the first wave of the COVID-19 pandemic in Florence (Italy). Using magnetic resonance spectroscopy, we showed that the infection induces profound changes in the metabolome. The analysis of the specific metabolite changes and correlations with clinical data enabled the identification of potential biochemical determinants of the disease fingerprint. We also followed how metabolic alterations revert towards those of the control group upon treatment with tocilizumab, a recombinant humanized monoclonal antibody against the interleukin-6 receptor. These results open up possibilities for the monitoring of novel patients and their individual response to treatment.

Applications of Lipidomics in Tumor Diagnosis and Therapy

Lipids have many critical biological functions in cancer. There are characteristic changes of lipid metabolism and metabolites in different physiological and pathological processes. Lipidomics is an emerging discipline of metabolomics for systematic analysis of lipids in organisms, tissues, or cells and the molecules that interact with them. With the development of new analytical techniques, especially the application and development of mass spectrometry techniques, the determination of lipids can be carried out quickly and accurately and has a high throughput. A large number of studies have shown that abnormal lipid metabolism is closely related to the occurrence and development of tumors. The application of lipidomics technology can reveal changes in lipids and relative abnormal metabolic pathways associated with tumors. Moreover, it shows a wide range of application prospects in the identification of tumor lipid biomarkers, early tumor diagnosis, and the discovery of antitumor drug targets. This chapter mainly introduces the application and development direction of lipidomics in the diagnosis and therapy of different tumors.

Roles of Lipid Profiles in Human Non-Small Cell Lung Cancer

Aims: This review aims to identify lipid biomarkers of non-small cell lung cancer (NSCLC) in human tissue samples and discuss the roles of lipids in tissue molecular identification, the discovery of potential biomarkers, and surgical margin assessment. Methods: A review of the literature focused on lipid-related research using mass spectrometry (MS) techniques in human NSCLC tissues from January 1, 2015, to November 20, 2020, was conducted. The quality of included studies was assessed using the QUADAS-2 tool. Results: Twelve studies met the inclusion criteria and were included in the review. The risk of bias was unclear in the majority of the studies. The contents of lipids including fatty acids, phosphatidyl choline, phosphatidyl ethanolamine, phosphatidyl inositol, cardiolipin, phosphatidyl serine, phosphatidyl glycerol, ceramide, lysophosphatidylethanolamine, lysophosphatidylcholine, and lysophosphatidylglycerol differed significantly between cancer and healthy tissues. The sensitivity or specificity of the discrimination model was reported in 8 studies, and the sensitivity and specificity varied among the reported methods. The lipid profiles differed between adenocarcinoma and squamous cell carcinoma NSCLC subtypes. Conclusion: In preclinical studies, MS analysis and multiple discrimination models can be combined to distinguish NSCLC tissues from healthy tissues based on lipid profiles, which provides a new opportunity to evaluate the surgical margin and cancer subtype intraoperatively. Future studies should provide guidance for selecting patients and discrimination models to develop an improved method for clinical application.

Monoacylglycerol Lipase Knockdown Inhibits Cell Proliferation and Metastasis in Lung Adenocarcinoma

Abnormal metabolism is one of the hallmarks of cancer cells. Monoacylglycerol lipase (MGLL), a key enzyme in lipid metabolism, has emerged as an important regulator of tumor progression. In this study, we aimed to characterize the role of MGLL in the development of lung adenocarcinoma (LUAD). To this end, we used tissue microarrays to evaluate the expression of MGLL in LUAD tissue and assessed whether the levels of this protein are correlated with clinicopathological characteristics of LUAD. We found that the expression of MGLL is higher in LUAD samples than that in adjacent non-tumor tissues. In addition, elevated MGLL expression was found to be associated with advanced tumor progression and poor prognosis in LUAD patients. Functional studies further demonstrated that stable short hairpin RNA (shRNA)-mediated knockdown of MGLL inhibits tumor proliferation and metastasis, both in vitro and in vivo, and mechanistically, our data indicate that MGLL regulates Cyclin D1 and Cyclin B1 in LUAD cells. Moreover, we found that knockdown of MGLL suppresses the expression of matrix metalloproteinase 14 (MMP14) in A549 and H322 cells, and in clinical samples, expression of MMP14 is significantly correlated with MGLL expression. Taken together, our results indicate that MGLL plays an oncogenic role in LUAD progression and metastasis and may serve as a potential biomarker for disease prognosis and as a target for the development of personalized therapies.

Trans-omic profiling between clinical phenoms and lipidomes among patients with different subtypes of lung cancer

Lung cancer has high mortality, often accompanied with systemic metabolic disorders. The present study aimed at defining values of trans-nodules cross-clinical phenomic and lipidomic network layers in patients with adenocarcinoma (ADC), squamous cell carcinomas, or small cell lung cancer (SCLC). We measured plasma lipidomic profiles of lung cancer patients and found that altered lipid panels and concentrations varied among lung cancer subtypes, genders, ages, stages, metastatic status, nutritional status, and clinical phenome severity. It was shown that phosphatidylethanolamine elements (36:2, 18:0/18:2, and 18:1/18:1) were SCLC specific, whereas lysophosphatidylcholine (20:1 and 22:0 sn-position-1) and phosphatidylcholine (19:0/19:0 and 19:0/21:2) were ADC specific. There were statistically more lipids declined in male, <60 ages, late stage, metastasis, or body mass index < 22 . Clinical trans-omics analyses demonstrated that one phenome in lung cancer subtypes might be generated from multiple metabolic pathways and metabolites, whereas a metabolic pathway and metabolite could contribute to different phenomes among subtypes, although those needed to be furthermore confirmed by bigger studies including larger population of patients in multicenters. Thus, our data suggested that trans-omic profiles between clinical phenomes and lipidomes might have the value to uncover the heterogeneity of lipid metabolism among lung cancer subtypes and to screen out phenome-based lipid panels as subtype-specific biomarkers.

ISG15 induces ESRP1 to inhibit lung adenocarcinoma progression

Our previous work demonstrated that Epithelial Splicing Regulatory Protein 1 (ESRP1) could inhibit the progression of lung adenocarcinoma (ADC). When ESRP1 was upregulated, the interferon (IFN) pathway was activated and Interferon-stimulated gene 15 (ISG15) expression increased exponentially in our microarray result. In this study, we aim to explore the function of ISG15 and its interactions with ESRP1 and to provide new insights for ADC treatment. ISG15 expression in lung ADC tissues was determined by immunohistochemistry (IHC) staining. The effect of ISG15 on lung ADC progression was examined by in vitro and in vivo assays. The mechanism of action on ESRP1 regulating ISG15 was investigated using Western blotting, RT-qPCR, immunofluorescence staining, chromatin immunoprecipitation, and a dual luciferase reporter system. The ISGylation between ISG15 and ESRP1 was detected by co-immunoprecipitation. Patients with high ISG15 expression were associated with higher survival rates, especially those with ISG15 expression in the nucleus. In vitro and in vivo experiments showed that upregulation of ISG15 inhibited EMT in lung ADC. ESRP1 upregulated the expression of ISG15 through CREB with enriched ISG15 in the nucleus. Importantly, ISG15 promoted ISGylation of ESRP1 and slowed the degradation of ESRP1, which demonstrated that ESRP1 and ISG15 formed a positive feedback loop and jointly suppressed EMT of lung ADC. In conclusion, ISG15 serves as an independent prognostic marker for long-term survival in lung ADC patients. We have revealed the protective effect of ISG15 against lung ADC progression and the combinatorial benefit of ISG15 and ESRP1 on inhibiting EMT. These findings suggest that reconstituting ISG15 and ESRP1 may have the potential for treating lung ADC.

Roles of acyl-CoA synthetase long-chain family member 5 and colony stimulating factor 2 in inhibition of palmitic or stearic acids in lung cancer cell proliferation and metabolism

Lung cancer is a heterogeneous and complex disease with the highest incidence and mortality rate. The present study aims at defining the lung cancer phenome specificity of lipidomic profiles, screening target lipid-dependent transcriptional alternations, identifying target lipid-associated target genes, and exploring molecular mechanisms. Lung cancer-specific and lung cancer subtype-specific target lipids palmitic acid (C16:0) and stearic acid (C18:0) were found as target lipids by integrating clinical phenomics, lipidomics, and transcriptomics and exhibited antiproliferative effects in sensitive cells. The metabolism-associated gene ACSL5 or inflammation-associated gene CCL3 was identified in lung adenocarcinoma or small lung cancer cells, respectively. C16:0 or C18:0 could upregulate ACSL5 or CSF2 expression in a time- and dose-dependent pattern, and the deletion of both genes led to the insensitivity of cells. Target lipids increased the expression of PDK4 gene in different patterns and inhibited cell proliferation through alterations of intracellular energy. Thus, our data provide a new strategy to investigate the trans-points between clinical and phenomics and lipidomics and target lipid-associated molecular mechanisms to benefit from the discovery of new therapies.