Precise pathological classification of non-small cell lung adenocarcinoma and squamous carcinoma based on an integrated platform of targeted metabolome and lipidome

Deciphering the lipid-cancer nexus: comprehensive Mendelian randomization analysis of the associations between lipid profiles and digestive system cancer susceptibility

BACKGROUND

Digestive system cancers represent a significant global health challenge and are attributed to a combination of demographic and lifestyle changes. Lipidomics has emerged as a pivotal area in cancer research, suggesting that alterations in lipid metabolism are closely linked to cancer development. However, the causal relationship between specific lipid profiles and digestive system cancer risk remains unclear.

METHODS

Using a two-sample Mendelian randomization (MR) approach, we elucidated the causal relationships between lipidomic profiles and the risk of five types of digestive system cancer: stomach, liver, esophageal, pancreatic, and colorectal cancers. The aim of this study was to investigate the effect impact of developing lipid profiles on the risk of digestive system cancers utilizing data from public databases such as the GWAS Catalog and the UK Biobank. The inverse‒variance weighted (IVW) method and other strict MR methods were used to evaluate the potential causal links. In addition, we performed sensitivity analyses and reverse MR analyses to ensure the robustness of the results.

RESULTS

Significant causal relationships were identified between certain lipidomic traits and the risk of developing digestive system cancers. Elevated sphingomyelin (d40:1) levels were associated with a reduced risk of developing gastric cancer (odds ratio (OR) = 0.68, P < 0.001), while elevated levels of phosphatidylcholine (16:1_20:4) increased the risk of developing esophageal cancer (OR = 1.31, P = 0.02). Conversely, phosphatidylcholine (18:2_0:0) had a protective effect against colorectal cancer (OR = 0.86, P = 0.036). The bidirectional analysis did not suggest reverse causality between cancer risk and lipid levels. Strict MR methods demonstrated the robustness of the above causal relationships.

CONCLUSION

Our findings underscore the significant causal relationships between specific lipidomic traits and the risk of developing various digestive system cancers, highlighting the potential of lipid profiles in informing cancer prevention and treatment strategies. These results reinforce the value of MR in unraveling complex lipid-cancer interactions, offering new avenues for research and clinical application.

Quercetin ameliorates nonalcoholic fatty liver disease (NAFLD) via the promotion of AMPK-mediated hepatic mitophagy

The global incidence of nonalcoholic fatty liver disease (NAFLD) has been surging in recent years, however, no drug is currently approved to treat this disease. Quercetin, a natural flavonoid abundant in plants and fruits, has been reported to alleviate NAFLD, however, the exact molecular mechanism remains unclear. This study aims to further elucidate its potential mechanism of action. The beneficial effects and the underlying mechanism of quercetin in alleviating NAFLD were explored both in vitro and in vivo, by employing chemical inhibitors of autophagosomes (3-methyladenine, 3-MA), autolysosomes (chloroquine, CQ), AMPK (Compound C, CC) and SIRT1 (selisistat, EX-527). The levels of intracellular lipids, reactive oxygen species, mitochondria function, autophagy, and mitophagy were assessed by fluorescent labeling and examined using flow cytometry or confocal microscopy. Key protein expressions of autophagy, mitophagy, and inflammation were also determined. In vivo, quercetin was shown to dose-dependently effectively alleviate NAFLD, but intraperitoneal injection of 3-MA could block the beneficial effects of quercetin on body weight, liver weight, serum ALT/AST, hepatic ROS and inflammation. In vitro, quercetin could reduce intracellular lipids (Nile Red staining) and ROS/DHE accumulation, which could be also blocked by 3-MA or CQ. Furthermore, we found that CC could abrogate the protective effects of quercetin on lipid and ROS accumulation in vitro. Also, CC abolished the proautophagic and anti-inflammatory effects of quercetin, as shown by western blot determination and Lyso-Tracker labeling. Importantly, mitophagy, a specific form of mitochondria-targeted autophagy, was enhanced by quercetin, as demonstrated by PINK1/Parkin protein variation and immunofluorescence colocalization of autophagosomes and mitochondria, which could also be blocked by the intervention of CC. This study demonstrates that quercetin prevents NAFLD through AMPK-mediated mitophagy and suggests that promoting mitophagy via an upregulation of AMPK may be a promising therapeutic strategy against NAFLD.

Targeted metabolomic profiling as a tool for diagnostics of patients with non-small-cell lung cancer

Lung cancer is referred to as the second most common cancer worldwide and is mainly associated with complex diagnostics and the absence of personalized therapy. Metabolomics may provide significant insights into the improvement of lung cancer diagnostics through identification of the specific biomarkers or biomarker panels that characterize the pathological state of the patient. We performed targeted metabolomic profiling of plasma samples from individuals with non-small cell lung cancer (NSLC, n = 100) and individuals without any cancer or chronic pathologies (n = 100) to identify the relationship between plasma endogenous metabolites and NSLC by means of modern comprehensive bioinformatics tools, including univariate analysis, multivariate analysis, partial correlation network analysis and machine learning. Through the comparison of metabolomic profiles of patients with NSCLC and noncancer individuals, we identified significant alterations in the concentration levels of metabolites mainly related to tryptophan metabolism, the TCA cycle, the urea cycle and lipid metabolism. Additionally, partial correlation network analysis revealed new ratios of the metabolites that significantly distinguished the considered groups of participants. Using the identified significantly altered metabolites and their ratios, we developed a machine learning classification model with an ROC AUC value equal to 0.96. The developed machine learning lung cancer model may serve as a prototype of the approach for the in-time diagnostics of lung cancer that in the future may be introduced in routine clinical use. Overall, we have demonstrated that the combination of metabolomics and up-to-date bioinformatics can be used as a potential tool for proper diagnostics of patients with NSCLC.

Highly Selective, Single-Tube Colorimetric Assay for Detection of Multiple Mutations in the Epidermal Growth Factor Receptor Gene

Many closed-tube methods are designed to detect DNA biomarkers. However, the utility of biomarkers such as a DNA mutation related to personalized medicine is limited as the operation of expensive detection instruments requires well-trained technicians. Therefore, we developed a simple and cheap colorimetric assay based on aggregation of silica-gold nanoparticle-modified probes, with linking probes, to detect mutations. This method consists of target amplification, sequence identification, and aggregation of the silica-gold nanoparticle-modified probes. All reactions are controlled by one individual and proceed sequentially, in a single tube, with no manual intervention. Approximately 10 copies of target DNA were detected with this assay, using 12 hot-spot mutations in exon 19 of EGFR gene as the example. In artificial samples, 0.1% mutant DNA can be distinguished from wild-type genomic DNA. The technology was tested on 104 clinical samples, which included 29 samples that were positive for an exon 19 deletion. The data were consistent with amplification refractory mutation system PCR, with the exception of one weakly positive sample, which was confirmed to be positive by digital PCR. The limit of detection of this colorimetric assay was verified to be better than that of amplification refractory mutation system PCR, and it provides a tool to discriminate multiple mutations in EGFR gene in clinical samples.

Small molecule metabolites: discovery of biomarkers and therapeutic targets

Metabolic abnormalities lead to the dysfunction of metabolic pathways and metabolite accumulation or deficiency which is well-recognized hallmarks of diseases. Metabolite signatures that have close proximity to subject's phenotypic informative dimension, are useful for predicting diagnosis and prognosis of diseases as well as monitoring treatments. The lack of early biomarkers could lead to poor diagnosis and serious outcomes. Therefore, noninvasive diagnosis and monitoring methods with high specificity and selectivity are desperately needed. Small molecule metabolites-based metabolomics has become a specialized tool for metabolic biomarker and pathway analysis, for revealing possible mechanisms of human various diseases and deciphering therapeutic potentials. It could help identify functional biomarkers related to phenotypic variation and delineate biochemical pathways changes as early indicators of pathological dysfunction and damage prior to disease development. Recently, scientists have established a large number of metabolic profiles to reveal the underlying mechanisms and metabolic networks for therapeutic target exploration in biomedicine. This review summarized the metabolic analysis on the potential value of small-molecule candidate metabolites as biomarkers with clinical events, which may lead to better diagnosis, prognosis, drug screening and treatment. We also discuss challenges that need to be addressed to fuel the next wave of breakthroughs.

A review of sensors for classification and subtype discrimination of cancer: Insights into circulating tumor cells and tumor-derived extracellular vesicles

Liquid biopsy can reflect the state of tumors in vivo non-invasively, thus providing a strong basis for the early diagnosis, individualized treatment monitoring and prognosis of tumors. Circulating tumor cells (CTCs) and tumor-derived extracellular vesicles (tdEVs) contain information-rich components, such as nucleic acids and proteins, and they are essential markers for liquid biopsies. Their capture and analysis are of great importance for the study of disease occurrence and development and, consequently, have been the subject of many reviews. However, both CTCs and tdEVs carry the biological characteristics of their original tissue, and few reviews have focused on their function in the staging and classification of cancer. In this review, we focus on state-of-the-art sensors based on the simultaneous detection of multiple biomarkers within CTCs and tdEVs, with clinical applications centered on cancer classification and subtyping. We also provide a thorough discussion of the current challenges and prospects for novel sensors with the ultimate goal of cancer classification and staging. It is hoped that these most advanced technologies will bring new insights into the clinical practice of cancer screening and diagnosis.

The important role of glycerophospholipid metabolism in the protective effects of polyphenol-enriched Tartary buckwheat extract against alcoholic liver disease

Alcoholic liver disease (ALD) is a mounting public health problem with significant medical, economic and social burdens. Tartary buckwheat (F. tataricum (L.) Gaertn, bitter buckwheat) is a kind of healthy and nutritious food, which has been demonstrated to protect against ALD, but the underlying mechanism has not been fully studied. Herein, we aimed to elucidate the beneficial effects of Tartary buckwheat extract (mainly composed of polyphenols including rutin, quercetin, kaempferol and kaempferol-3-O-rutinoside) in terms of lipid metabolism with the aid of lipidomic analysis. In our study, we employed C57BL/6J mice and a Lieber-DeCarli alcohol liquid diet to construct an ALD model and found that Tartary buckwheat extract was able to prevent ALD-induced histopathological lesions, liver injury and abnormal plasma lipid levels. These beneficial effects might be attributed to the regulation of energy metabolism-related genes (SIRT1, LKB1 and AMPK), lipid synthesis-related genes (ACC, SREBP1c and HMGR) and lipid oxidation-related genes (PPARα, CPT1 and CPT2). In addition, lipidomic profiling and KEGG pathway analysis showed that glycerophospholipid metabolism contributed the most to elucidating the regulatory mechanism of Tartary buckwheat extract. In specific, chronic ethanol intake reduced the level of phosphatidylcholines (PC) and increased the level of phosphatidylethanolamines (PE) in the liver, resulting in a decrease in the PC/PE ratio, which could be all significantly restored by Tartary buckwheat extract intervention, indicating that the Tartary buckwheat extract might regulate PC/PE homeostasis to exert its lipid-lowering effect. Overall, we demonstrated that Tartary buckwheat extract could prevent ALD by modulating hepatic glycerophospholipid metabolism, providing the theoretical basis for its further exploitation as a medical plant or nutritional food.

Luteolin alleviates methionine-choline-deficient diet-induced non-alcoholic steatohepatitis by modulating host serum metabolome and gut microbiome

Background and purpose

Previous studies have indicated the protective effects of luteolin against non-alcoholic steatohepatitis (NASH), but the definite underlying mechanism still remains unclear. This study aimed to explore the metabolomic and metagenomic signatures of NASH with luteolin supplementation.

Experimental approach

Mice were fed with a methionine–choline-deficient (MCD) diet containing 0.05% luteolin for 6 weeks. NASH severity was determined based on the liver histological observations, serum and hepatic biochemical measurements. Targeted metabolomics was conducted to identify differential metabolites in mice serum. 16S rRNA sequencing was conducted to assess the gut microbiota composition and function in mice colon.

Results

In detail, luteolin treatment significantly alleviated MCD diet-induced hepatic lipid deposition, liver function damage, and oxidative stress. Targeted plasma metabolomics revealed that 5-hydroxyindole, LPE (0:0/22:5), indole 3-phosphate, and N-phenylacetylphenylalanine were remarkably elevated, and homogentisic acid, thiamine, KN-93, PC (16:1e/8, 9-EpETE), carnitine C9:1-OH, FFA (18:4) and carnitine C8:1 were significantly decreased in NASH group as compared to normal group, which could be profoundly reversed after luteolin treatment. 16S rRNA sequencing indicated that luteolin supplementation significantly increased Erysipelatoclostridium and Pseudomonas as well as decreased Faecalibaculum at genus level. Most importantly, a negative association between thiamine and Faecalibaculum was observed based on Spearman's correlation analysis, which may play an important role in the preventive effects of luteolin against NASH.

Conclusion

Collectively, luteolin may alleviate the NASH by modulating serum metabolome and gut microbiome, which supports its use as a dietary supplement for NASH prevention.

Improved profiling of low molecular weight serum proteome for gastric carcinoma by data-independent acquisition

Low molecular weight proteins (LMWPs) in the bloodstream participate in various biological processes and are closely associated with disease status, whereas identification of serous LMWPs remains a great technical challenge due to the wide dynamic range of protein components. In this study, we constructed an integrated LMWP library by combining the LMWPs obtained by three enrichment methods (50% ACN, 20% ACN + 20 mM ABC, and 30 kDa) and their fractions identified by the data-dependent acquisition method. With this newly constructed library, we comprehensively profiled LMWPs in serum using data-independent acquisition and reliably achieved quantitative results for 75% serous LMWPs. When applying this strategy to quantify LMWPs in human serum samples, we could identify 405 proteins on average per sample, of which 136 proteins were with a MW less than 30 kDa and 293 proteins were with a MW less than 65 kDa. Of note, pre- and post-operative gastric carcinoma (GC) patients showed differentially expressed serous LWMPs, which was also different from the pattern of LWMP expression in healthy controls. In conclusion, our results showed that LMWPs could efficiently distinguish GC patients from healthy controls as well as between pre- and post-operative statuses, and more importantly, our newly developed LMWP profiling platform could be used to discover candidate LMWP biomarkers for disease diagnosis and status monitoring.

Tris (2-chloroethyl) phosphate (TCEP) induces obesity and hepatic steatosis via FXR-mediated lipid accumulation in mice: Long-term exposure as a potential risk for metabolic diseases

Tris (2-chloroethyl) phosphate (TCEP) is the most commonly detective organophosphate flame retardant in surroundings. TCEP is also evidenced as endocrine disrupting chemicals and has potential adverse effects on metabolic diseases. In this study, we hypothesized that metabolic diseases are adverse outcomes of TCEP exposure. Adult ICR mice was daily treated with TCEP (20 mg/kg and 60 mg/kg, higher than expected level in people) by gavage administration for 9 weeks. The results demonstrate that TCEP promoted body weight gain, hypertriglyceridemia, and hepatic steatosis, consistent with upregulation of hepatic lipogenesis-related gene expression. Moreover, TCEP altered the levels of several hepatic metabolites, especially bile acids and downregulated bile acid synthesis pathways. Intriguingly, we found a marked downregulation of the bile acid nuclear reporter, FXR, in TCEP-exposed livers. Mechanistically, TCEP directly interacted with FXR at Lys335 and Lys336. Further studies in this work elucidate the mechanisms of long-term TCEP exposure on hepatic steatosis and obesity in mice via FXR-mediated lipid accumulation. Our results provide insight into the possibility of intermediate TCEP exposure in causing metabolic diseases.