A distinct metabolic signature of human colorectal cancer with prognostic potential

Identifying targetable metabolic dependencies across colorectal cancer progression

Colorectal cancer (CRC) is a multi-stage process initiated through the formation of a benign adenoma, progressing to an invasive carcinoma and finally metastatic spread. Tumour cells must adapt their metabolism to support the energetic and biosynthetic demands associated with disease progression. As such, targeting cancer cell metabolism is a promising therapeutic avenue in CRC. However, to identify tractable nodes of metabolic vulnerability specific to CRC stage, we must understand how metabolism changes during CRC development. Here, we use a unique model system - comprising human early adenoma to late adenocarcinoma. We show that adenoma cells transition to elevated glycolysis at the early stages of tumour progression but maintain oxidative metabolism. Progressed adenocarcinoma cells rely more on glutamine-derived carbon to fuel the TCA cycle, whereas glycolysis and TCA cycle activity remain tightly coupled in early adenoma cells. Adenocarcinoma cells are more flexible with respect to fuel source, enabling them to proliferate in nutrient-poor environments. Despite this plasticity, we identify asparagine (ASN) synthesis as a node of metabolic vulnerability in late-stage adenocarcinoma cells. We show that loss of asparagine synthetase (ASNS) blocks their proliferation, whereas early adenoma cells are largely resistant to ASN deprivation. Mechanistically, we show that late-stage adenocarcinoma cells are dependent on ASNS to support mTORC1 signalling and maximal glycolytic and oxidative capacity. Resistance to ASNS loss in early adenoma cells is likely due to a feedback loop, absent in late-stage cells, allowing them to sense and regulate ASN levels and supplement ASN by autophagy. Together, our study defines metabolic changes during CRC development and highlights ASN synthesis as a targetable metabolic vulnerability in later stage disease.

Hypoxia-induced cysteine metabolism reprogramming is crucial for the tumorigenesis of colorectal cancer

Metabolic reprogramming is a hallmark of human cancer, and cancer-specific metabolism provides opportunities for cancer diagnosis, prognosis, and treatment. However, the underlying mechanisms by which metabolic pathways affect the initiation and progression of colorectal cancer (CRC) remain largely unknown. Here, we demonstrate that cysteine is highly enriched in colorectal tumors compared to adjacent non-tumor tissues, thereby promoting tumorigenesis of CRC. Synchronously importing both cysteine and cystine in colorectal cancer cells is necessary to maintain intracellular cysteine levels. Hypoxia-induced reactive oxygen species (ROS) and ER stress regulate the co-upregulation of genes encoding cystine transporters (SLC7A11, SLC3A2) and genes encoding cysteine transporters (SLC1A4, SLC1A5) through the transcription factor ATF4. Furthermore, the metabolic flux from cysteine to reduced glutathione (GSH), which is critical to support CRC growth, is increased due to overexpression of glutathione synthetase GSS in CRC. Depletion of cystine/cysteine by recombinant cyst(e)inase effectively inhibits the growth of colorectal tumors by inducing autophagy in colorectal cancer cells through mTOR-ULK signaling axis. This study demonstrates the underlying mechanisms of cysteine metabolism in tumorigenesis of CRC, and evaluates the potential of cysteine metabolism as a biomarker or a therapeutic target for CRC.

Signals from intestinal microbiota mediate the crosstalk between the lung-gut axis in an influenza infection mouse model

Introduction

Introduction: The influenza virus primarily targets the respiratory tract, yet both the respiratory and intestinal systems suffer damage during infection. The connection between lung and intestinal damage remains unclear.

Methods

Our experiment employs 16S rRNA technology and Liquid Chromatography-Mass Spectrometry (LC-MS) to detect the impact of influenza virus infection on the fecal content and metabolites in mice. Additionally, it investigates the effect of influenza virus infection on intestinal damage and its underlying mechanisms through HE staining, Western blot, Q-PCR, and flow cytometry.

Results

Our study found that influenza virus infection caused significant damage to both the lungs and intestines, with the virus detected exclusively in the lungs. Antibiotic treatment worsened the severity of lung and intestinal damage. Moreover, mRNA levels of Toll-like receptor 7 (TLR7) and Interferon-b (IFN-b) significantly increased in the lungs post-infection. Analysis of intestinal microbiota revealed notable shifts in composition after influenza infection, including increased Enterobacteriaceae and decreased Lactobacillaceae. Conversely, antibiotic treatment reduced microbial diversity, notably affecting Firmicutes, Proteobacteria, and Bacteroidetes. Metabolomics showed altered amino acid metabolism pathways due to influenza infection and antibiotics. Abnormal expression of indoleamine 2,3-dioxygenase 1 (IDO1) in the colon disrupted the balance between helper T17 cells (Th17) and regulatory T cells (Treg cells) in the intestine. Mice infected with the influenza virus and supplemented with tryptophan and Lactobacillus showed reduced lung and intestinal damage, decreased Enterobacteriaceae levels in the intestine, and decreased IDO1 activity.

Discussion

Overall, influenza infection caused damage to lung and intestinal tissues, disrupted intestinal microbiota and metabolites, and affected Th17/Treg balance. Antibiotic treatment exacerbated these effects. Supplementation with tryptophan and Lactobacillus improved lung and intestinal health, highlighting a new understanding of the lung-intestine connection in influenza-induced intestinal disease.

Machine Learning-Based Integrated Multiomics Characterization of Colorectal Cancer Reveals Distinctive Metabolic Signatures

The metabolic signature identification of colorectal cancer is critical for its early diagnosis and therapeutic approaches that will significantly block cancer progression and improve patient survival. Here, we combined an untargeted metabolic analysis strategy based on internal extractive electrospray ionization mass spectrometry and the machine learning approach to analyze metabolites in 173 pairs of cancer samples and matched normal tissue samples to build robust metabolic signature models for diagnostic purposes. Screening and independent validation of metabolic signatures from colorectal cancers via machine learning methods (Logistic Regression_L1 for feature selection and eXtreme Gradient Boosting for classification) was performed to generate a panel of seven signatures with good diagnostic performance (the accuracy of 87.74%, sensitivity of 85.82%, and specificity of 89.66%). Moreover, seven signatures were evaluated according to their ability to distinguish between cancer and normal tissues, with the metabolic molecule PC (30:0) showing good diagnostic performance. In addition, genes associated with PC (30:0) were identified by multiomics analysis (combining metabolic data with transcriptomic data analysis) and our results showed that PC (30:0) could promote the proliferation of colorectal cancer cell SW480, revealing the correlation between genetic changes and metabolic dysregulation in cancer. Overall, our results reveal potential determinants affecting metabolite dysregulation, paving the way for a mechanistic understanding of altered tissue metabolites in colorectal cancer and design interventions for manipulating the levels of circulating metabolites.

Comparative Metabolomics and Transcriptome Studies of Two Forms of Rhododendron chrysanthum Pall. under UV-B Stress

Rhododendron chrysanthum Pall. (R. chrysanthum), a plant with UV-B resistance mechanisms that can adapt to alpine environments, has gained attention as an important plant resource with the ability to cope with UV-B stress. In this experiment, R. chrysanthums derived from the same origin were migrated to different culture environments (artificial climate chamber and intelligent artificial incubator) to obtain two forms of R. chrysanthum. After UV-B irradiation, 404 metabolites and 93,034 unigenes were detected. Twenty-six of these different metabolites were classified as UV-B-responsive metabolites. Glyceric acid is used as a potential UV-B stress biomarker. The domesticated Rhododendron chrysanthum Pall. had high amino acid and SOD contents. The study shows that the domesticated Rhododendron chrysanthum Pall. has significant UV-B resistance. The transcriptomics results show that the trends of DEGs after UV-B radiation were similar for both forms of R. chrysanthum: cellular process and metabolic process accounted for a higher proportion in biological processes, cellular anatomical entity accounted for the highest proportion in the cellular component, and catalytic activity and binding accounted for the highest proportion in the molecular function category. Through comparative study, the forms of metabolites resistant to UV-B stress in plants can be reflected, and UV-B radiation absorption complexes can be screened for application in future specific practices. Moreover, by comparing the differences in response to UV-B stress between the two forms of R. chrysanthum, references can be provided for cultivating domesticated plants with UV-B stress resistance characteristics. Research on the complex mechanism of plant adaptation to UV-B will be aided by these results.

Black raspberry-mediated metabolic changes in patients with familial adenomatous polyposis associated with rectal polyp regression

Familial adenomatous polyposis (FAP) patients face an almost certain 100% risk of developing colorectal cancer, necessitating prophylactic colectomy to prevent disease progression. A crucial goal is to hinder this progression. In a recent clinical trial involving 14 FAP patients, half received 60 g of black raspberry (BRB) powder orally and BRB suppositories at bedtime, while the other half received only BRB suppositories at bedtime over 9 months. This intervention led to a notable reduction in rectal polyps for 11 patients, although 3 showed no response. In this study, we delved into the metabolic changes induced by BRBs in the same patient cohort. Employing mass spectrometry-based non-targeted metabolomics, we analyzed pre- and post-BRB urinary and plasma samples from the 11 responders. The results showed significant alterations in 23 urinary and 6 plasma metabolites, influencing various pathways including polyamine, glutathione metabolism, the tricarboxylic acid cycle, inositol metabolism, and benzoate production. BRBs notably elevated levels of several metabolites associated with these pathways, suggesting a potential mechanism through which BRBs facilitate rectal polyp regression in FAP patients by modulating multiple metabolic pathways. Notably, metabolites derived from BRB polyphenols were significantly increased post-BRB intervention, emphasizing the potential therapeutic value of BRBs in FAP management.

Selective inhibition of indoleamine and tryptophan 2,3-dioxygenases: Comparative study on kynurenine pathway in cell lines via LC-MS/MS-based targeted metabolomics

In the last decade, the kynurenine pathway, which is the primary metabolic route for tryptophan (TRP) catabolism, has sparked great interest in the pharmaceutical sciences due to its role in immune regulation and cancer immunoediting. In this context, the development of cell-based assays might represent a tool to: i) characterize the cell secretome according to cell types; ii) gain more insight into the role of kynurenines in different disease scenarios; iii) screen hIDO1 (human indoleamine 2,3-dioxygenase) inhibitors and evaluate their effect on downstream TRP-catabolizing enzymes. This paper reports a validated Liquid Chromatography with tandem mass spectrometry (LC-MS/MS) method to simultaneously quantify TRP, L-kynurenine (KYN), xanthurenic acid (XA), 3-hydroxykynurenine (3OHKYN), kynurenic acid (KA), 3-hydroxyanthranilic acid (3OHAA), anthranilic acid (AA), 5-hydroxytryptamine (serotonin, 5HT) and tryptamine (TRYP) in Dulbecco's Modified Eagle and Eagle's Minimum Essential Media (DMEM and EMEM, respectively). The quantitative method was validated according to FDA, ICH and EMA guidelines, later applied: i) to assess the impact of selective inhibition of hIDO1 or hTDO (human tryptophan 2,3-dioxygenase) on the kynurenine pathway in A375 (melanoma), MDA-MB-231 (breast cancer), and U87 (glioblastoma) cell lines using multivariate analysis (MVA); ii) to determine the IC50 values of both well-known (i.e., epacadostat, linrodostat) and the novel hIDO1 inhibitor (i.e., BL5) in the aforementioned cell lines. The proposed LC-MS/MS method is reliable and robust. Furthermore, it is highly versatile and suitable for applications in the preclinical drug research and in vitro assays.

Amino Acid Profiles in the Biological Fluids and Tumor Tissue of CRC Patients

Amino acids are the building blocks of proteins and essential players in pathways such as the citric acid and urea cycle, purine and pyrimidine biosynthesis, and redox cell signaling. Therefore, it is unsurprising that these molecules have a significant role in cancer metabolism and its metabolic plasticity. As one of the most prevalent malign diseases, colorectal cancer needs biomarkers for its early detection, prognostic, and prediction of response to therapy. However, the available biomarkers for this disease must be more powerful and present several drawbacks, such as high costs and complex laboratory procedures. Metabolomics has gathered substantial attention in the past two decades as a screening platform to study new metabolites, partly due to the development of techniques, such as mass spectrometry or liquid chromatography, which have become standard practice in diagnostic procedures for other diseases. Extensive metabolomic studies have been performed in colorectal cancer (CRC) patients in the past years, and several exciting results concerning amino acid metabolism have been found. This review aims to gather and present findings concerning alterations in the amino acid plasma pool of colorectal cancer patients.

Aspirin and the metabolic hallmark of cancer: novel therapeutic opportunities for colorectal cancer

Aspirin is a well-known nonsteroidal anti-inflammatory drug (NSAID) that has a recognized role in cancer prevention as well as evidence to support its use as an adjuvant for cancer treatment. Importantly there has been an increasing number of studies contributing to the mechanistic understanding of aspirins' anti-tumour effects and these studies continue to inform the potential clinical use of aspirin for both the prevention and treatment of cancer. This review focuses on the emerging role of aspirin as a regulator of metabolic reprogramming, an essential "hallmark of cancer" required to support the increased demand for biosynthetic intermediates needed for sustained proliferation. Cancer cells frequently undergo metabolic rewiring driven by oncogenic pathways such as hypoxia-inducible factor (HIF), wingless-related integration site (Wnt), mammalian target of rapamycin (mTOR), and nuclear factor kappa light chain enhancer of activated B cells (NF-κB), which supports the increased proliferative rate as tumours develop and progress. Reviewed here, cellular metabolic reprogramming has been identified as a key mechanism of action of aspirin and include the regulation of key metabolic drivers, the regulation of enzymes involved in glycolysis and glutaminolysis, and altered nutrient utilisation upon aspirin exposure. Importantly, as aspirin treatment exposes metabolic vulnerabilities in tumour cells, there is an opportunity for the use of aspirin in combination with specific metabolic inhibitors in particular, glutaminase (GLS) inhibitors currently in clinical trials such as telaglenastat (CB-839) and IACS-6274 for the treatment of colorectal and potentially other cancers. The increasing evidence that aspirin impacts metabolism in cancer cells suggests that aspirin could provide a simple, relatively safe, and cost-effective way to target this important hallmark of cancer. Excitingly, this review highlights a potential new role for aspirin in improving the efficacy of a new generation of metabolic inhibitors currently undergoing clinical investigation.

Determination of the Minimum Sample Amount for Capillary Electrophoresis-Fourier Transform Mass Spectrometry (CE-FTMS)-Based Metabolomics of Colorectal Cancer Biopsies

The minimum sample volume for capillary electrophoresis-Fourier transform mass spectrometry (CE-FTMS) useful for analyzing hydrophilic metabolites was investigated using samples obtained from colorectal cancer patients. One, two, five, and ten biopsies were collected from tumor and nontumor parts of the surgically removed specimens from each of the five patients who had undergone colorectal cancer surgery. Metabolomics was performed on the collected samples using CE-FTMS. To determine the minimum number of specimens based on data volume and biological interpretability, we compared the number of annotated metabolites in each sample with different numbers of biopsies and conducted principal component analysis (PCA), hierarchical cluster analysis (HCA), quantitative enrichment analysis (QEA), and random forest analysis (RFA). The number of metabolites detected in one biopsy was significantly lower than those in 2, 5, and 10 biopsies, whereas those detected among 2, 5, and 10 pieces were not significantly different. Moreover, a binary classification model developed by RFA based on 2-biopsy data perfectly distinguished tumor and nontumor samples with 5- and 10-biopsy data. Taken together, two biopsies would be sufficient for CE-FTMS-based metabolomics from a data content and biological interpretability viewpoint, which opens the gate of biopsy metabolomics for practical clinical applications.

Targeting Oncometabolites in Peritoneal Cancers: Preclinical Insights and Therapeutic Strategies

Peritoneal cancers present significant clinical challenges with poor prognosis. Understanding the role of cancer cell metabolism and cancer-promoting metabolites in peritoneal cancers can provide new insights into the mechanisms that drive tumor progression and can identify novel therapeutic targets and biomarkers for early detection, prognosis, and treatment response. Cancer cells dynamically reprogram their metabolism to facilitate tumor growth and overcome metabolic stress, with cancer-promoting metabolites such as kynurenines, lactate, and sphingosine-1-phosphate promoting cell proliferation, angiogenesis, and immune evasion. Targeting cancer-promoting metabolites could also lead to the development of effective combinatorial and adjuvant therapies involving metabolic inhibitors for the treatment of peritoneal cancers. With the observed metabolomic heterogeneity in cancer patients, defining peritoneal cancer metabolome and cancer-promoting metabolites holds great promise for improving outcomes for patients with peritoneal tumors and advancing the field of precision cancer medicine. This review provides an overview of the metabolic signatures of peritoneal cancer cells, explores the role of cancer-promoting metabolites as potential therapeutic targets, and discusses the implications for advancing precision cancer medicine in peritoneal cancers.

iMSEA: A Novel Metabolite Set Enrichment Analysis Strategy to Decipher Drug Interactions

Drug combinations are commonly used to treat various diseases to achieve synergistic therapeutic effects or to alleviate drug resistance. Nevertheless, some drug combinations might lead to adverse effects, and thus, it is crucial to explore the mechanisms of drug interactions before clinical treatment. Generally, drug interactions have been studied using nonclinical pharmacokinetics, toxicology, and pharmacology. Here, we propose a complementary strategy based on metabolomics, which we call interaction metabolite set enrichment analysis, or iMSEA, to decipher drug interactions. First, a digraph-based heterogeneous network model was constructed to model the biological metabolic network based on the Kyoto Encyclopedia of Genes and Genomes (KEGG) database. Second, treatment-specific influences on all detected metabolites were calculated and propagated across the whole network model. Third, pathway activity was defined and enriched to quantify the influence of each treatment on the predefined functional metabolite sets, i.e., metabolic pathways. Finally, drug interactions were identified by comparing the pathway activity enriched by the drug combination treatments and the single drug treatments. A data set consisting of hepatocellular carcinoma (HCC) cells that were treated with oxaliplatin (OXA) and/or vitamin C (VC) was used to illustrate the effectiveness of the iMSEA strategy for evaluation of drug interactions. Performance evaluation using synthetic noise data was also performed to evaluate sensitivities and parameter settings for the iMSEA strategy. The iMSEA strategy highlighted synergistic effects of combined OXA and VC treatments including the alterations in the glycerophospholipid metabolism pathway and glycine, serine, and threonine metabolism pathway. This work provides an alternative method to reveal the mechanisms of drug combinations from the viewpoint of metabolomics.

Effective oxygen metabolism-based prognostic signature for colorectal cancer

Backgroud

Oxygen metabolism is an important factor affecting the development of tumors, but its roles and clinical value in Colorectal cancer are not clear. We developed an oxygen metabolism (OM) based prognostic risk model for colorectal cancer and explored the role of OM genes in cancer.

Methods

Gene expression and clinical data obtained from The Cancer Genome Atlas, Clinical Proteomic Tumor Analysis Consortium databases were consider as discovery and validation cohort, respectively. The prognostic model based on differently expressed OM genes between tumor and GTEx normal colorectal tissues were constructed in discovery cohort and validated in validation cohort. The Cox proportional hazards analysis was used to test clinical independent. Upstream and downstream regulatory relationships and interaction molecules are used to clarify the roles of prognostic OM genes in colorectal cancer.

Results

A total of 72 common differently expressed OM genes were detected in the discovery and validation set. A five-OM gene prognostic model including LRT2, ATP6V0E2, ODC1, SEL1L3 and VDR was established and validated. Risk score determined by the model was an independent prognostic according to routine clinical factors. Besides, the role of prognostic OM genes involves transcriptional regulation of MYC and STAT3, and downstream cell stress and inflammatory response pathways.

Conclusions

We developed a five-OM gene prognostic model and study the unique roles of oxygen metabolism in of colorectal cancer.

Analyses of regulatory network and discovery of potential biomarkers for Korean rockfish (Sebastes schlegelii) in responses to starvation stress through transcriptome and metabolome

Whether in aquaculture or in nature, starvation stress limits the growth of fish. The purpose of the study was to clarify the detailed molecular mechanisms underlying starvation stress in Korean rockfish (Sebastes schlegelii) through liver transcriptome and metabolome analysis. Transcriptome results showed that liver genes associated with cell cycle and fatty acid synthesis were down-regulated, whereas those related to fatty acid decomposition were up-regulated in the experimental group (EG; starved for 72 days) compared to the control group (CG; feeding). Metabolomic results showed that there were significant differences in the levels of metabolites related to nucleotide metabolism and energy metabolism, such as purine metabolism, histidine metabolism and oxidative phosphorylation. Five fatty acids (C22:6n-3; C22:5n-3; C20:5n-3; C20:4n-3; C18:3n-6) were selected as possible biomarkers of starvation stress from the differential metabolites of metabolome. Subsequently, correlation between these differential genes of lipid metabolism and cell cycle and differential metabolites were analyzed, and observed that these five fatty acids were significantly correlated with the differential genes. These results provide new clues for understanding the role of fatty acid metabolism and cell cycle in fish under starvation stress. It also provides a reference for promoting the biomarker identification of starvation stress and stress tolerance breeding research.

Reduced expression of alanyl aminopeptidase is a robust biomarker of non-familial adenomatous polyposis and non-hereditary nonpolyposis colorectal cancer syndrome early-onset colorectal cancer

BACKGROUND

Early-onset colorectal cancer (EOCRC) has been increasing in incidence worldwide but its genomic pathogenesis is mostly undetermined. This study aimed to identify robust EOCRC-specific gene expression patterns in non-familial adenomatous polyposis (FAP) and non-hereditary nonpolyposis colorectal cancer syndrome (HNPCC) EOCRC.

METHOD

We first performed gene expression profiling analysis using RNA sequencing of discovery cohort comprised of 49 EOCRC (age <50) and 50 late-onset colorectal cancer (LOCRC) (age >70) specimens. To obtain robust gene expression data from this analysis, we validated differentially expressed genes (DEGs) through TCGA cohort (EOCRC:59 samples, LOCRC:229 samples) and our validation cohort (EOCRC:72 samples, LOCRC:43 samples) using real-time RT-PCR. After the validation of DEGs, we validated the selected gene at protein levels using Western blotting. To identify whether genomic methylation regulates the expression of a particular gene, we selected methylation sites using The Cancer Genome Atlas (TCGA) datasets and validated them by pyrosequencing in our validation cohort.

RESULTS

The EOCRC patients included in this study had significantly more prominent family history of cancer than the LOCRC patients (23 [46.9%] vs. 13 [26%], p = 0.050). Alanyl aminopeptidase (ANPEP) was significantly downregulated in the EOCRC tissues (FC = 1.78, p = 0.0007) and was also commonly downregulated in the TCGA cohort (FC = -1.08, p = 0.0021). Moreover, the ANPEP mRNA and protein expression levels were significantly downregulated in the EOCRC tissues of our validation cohort (p = 0.037 and 0.027). In comparisons of the normal and tumor tissues in public datasets, the ANPEP level was significantly lower in the tumor tissue in the TCGA dataset (p < 2.2 × 10^-16 ) and GSE196006 dataset (p = 0.0005). Furthermore, the ANPEP expression level did not show a decreasing tendency at a young age in the normal colon tissue of the GTEx dataset. Lastly, the hypermethylation of cg26222247 in ANPEP was identified to be weakly associated with reduced ANPEP expression in our EOCRC cohort.

CONCLUSION

The reduced expression of ANPEP was identified as a novel biomarker of non-FAP and non-HNPCC EOCRC.

Gut microbiota-mediated nucleotide synthesis attenuates the response to neoadjuvant chemoradiotherapy in rectal cancer

Preoperative neoadjuvant chemoradiotherapy (nCRT) is a standard treatment for locally advanced rectal cancer (LARC) patients, yet little is known about the mediators underlying the heterogeneous patient response. In this longitudinal study, we performed 16S rRNA sequencing on 353 fecal specimens and find reduced microbial diversity after nCRT. Multi-omics data integration reveals that Bacteroides vulgatus-mediated nucleotide biosynthesis associates with nCRT resistance in LARC patients, and nonresponsive tumors are characterized by the upregulation of genes related to DNA repair and nucleoside transport. Nucleosides supplementation or B. vulgatus gavage protects cancer cells from the 5-fluorouracil or irradiation treatment. An analysis of 2,205 serum samples from 735 patients suggests that uric acid is a potential prognosis marker for LARC patients receiving nCRT. Our data unravel the role of intestinal microbiota-mediated nucleotide biosynthesis in the response of rectal tumors to nCRT, and highlight the importance of deciphering the cross-talk between cancer cells and gut microorganisms during cancer therapies.

Metabolite profiling analysis of hepatitis B virus-induced liver cirrhosis patients with minimal hepatic encephalopathy using gas chromatography-time-of-flight mass spectrometry and ultra-performance liquid chromatography-quadrupole-time-of-flight mass spectrometry

This study used gas chromatography-time-of-flight mass spectrometry (GC-TOFMS) and ultra-performance liquid chromatography-quadrupole TOFMS (UPLC-QTOFMS) metabonomic analytical techniques in combination with bioinformatics and pattern recognition analysis methods to analyze the serum metabolite profiling of hepatitis B virus (HBV)-induced liver cirrhosis patients with minimal hepatic encephalopathy (MHE), to find the specific biomarkers of MHE, to reveal the pathogenesis of MHE, and to determine a promising approach for early diagnosis of MHE. Serum samples of 100 normal controls (NC group), 29 HBV-induced liver cirrhosis patients with MHE (MHE group), and 24 HBV-induced liver cirrhosis patients without MHE [comprising 12 cases of compensated cirrhosis (CS group) and 12 cases of decompensated cirrhosis (DS group)] were collected and employed into GC-TOFMS and UPLC-QTOFMS platforms for serum metabolite detection; the outcome data were then analyzed using principal component analysis and orthogonal partial least squares-discriminant analysis (OPLS-DA). There were no significant differential metabolites between the NC group and the CS group. A series of key differential metabolites were detected. According to the variable influence in projection values and P-values, 60 small-molecule metabolites were considered to be dysregulated in the MHE group (compared to the NC group); 27 of these 60 dysregulated differential metabolites were considered to be the potential biomarkers (see Table 4, marked in bold); 66 small-molecule metabolites were considered to be dysregulated in the DS group (compared to the NC group); 34 of these 66 dysregulated differential metabolites were considered to be the potential biomarkers (see Table 5, marked in bold). According to the fold-change values, 9 of these 27 metabolites, namely valine, oxalic acid, erythro-sphingosine, 4,7,10,13,16,19-docosahexaenoic acid, isoleucine, allo-isoleucine, thyroxine, rac-octanoyl carnitine, and tocopherol (vitamin E), were downregulated in the MHE group (compared to the NC group); the other 18, namely adenine, glycochenodeoxycholic acid, fucose, allothreonine, glycohyocholic acid, glycoursodeoxycholic acid, tyrosine, taurocheno-deoxycholate, phenylalanine, 2-hydroxy-3-methyl-butanoic acid, hydroxyacetic acid, taurocholate, sorbitol, rhamnose, tauroursodeoxycholate, tolbutamide, pyroglutamic acid, and malic acid, were upregulated; 6 of these 34 metabolites were downregulated in the DS group (compared to the NC group), and the other 28 were upregulated, as shown in Table 5. (a) GC-TOFMS and UPLC-QTOFMS metabonomic analytical platforms can detect a range of metabolites in the serum; this might be of great help to study the pathogenesis of MHE and may provide a new approach for the early diagnosis of MHE. (b) Metabonomics analysis in combination with pattern recognition analysis might have great potential to distinguish the HBV-induced liver cirrhosis patients who have MHE from the normal healthy population and HBV-induced liver cirrhosis patients without MHE.

Systematic Review: Contribution of the Gut Microbiome to the Volatile Metabolic Fingerprint of Colorectal Neoplasia

Colorectal cancer (CRC) has been associated with changes in volatile metabolic profiles in several human biological matrices. This enables its non-invasive detection, but the origin of these volatile organic compounds (VOCs) and their relation to the gut microbiome are not yet fully understood. This systematic review provides an overview of the current understanding of this topic. A systematic search using PubMed, Embase, Medline, Cochrane Library, and the Web of Science according to PRISMA guidelines resulted in seventy-one included studies. In addition, a systematic search was conducted that identified five systematic reviews from which CRC-associated gut microbiota data were extracted. The included studies analyzed VOCs in feces, urine, breath, blood, tissue, and saliva. Eight studies performed microbiota analysis in addition to VOC analysis. The most frequently reported dysregulations over all matrices included short-chain fatty acids, amino acids, proteolytic fermentation products, and products related to the tricarboxylic acid cycle and Warburg metabolism. Many of these dysregulations could be related to the shifts in CRC-associated microbiota, and thus the gut microbiota presumably contributes to the metabolic fingerprint of VOC in CRC. Future research involving VOCs analysis should include simultaneous gut microbiota analysis.

Targeting cancer-specific metabolic pathways for developing novel cancer therapeutics

Cancer is a heterogeneous disease characterized by various genetic and phenotypic aberrations. Cancer cells undergo genetic modifications that promote their proliferation, survival, and dissemination as the disease progresses. The unabated proliferation of cancer cells incurs an enormous energy demand that is supplied by metabolic reprogramming. Cancer cells undergo metabolic alterations to provide for increased energy and metabolite requirement; these alterations also help drive the tumor progression. Dysregulation in glucose uptake and increased lactate production via "aerobic glycolysis" were described more than 100 years ago, and since then, the metabolic signature of various cancers has been extensively studied. However, the extensive research in this field has failed to translate into significant therapeutic intervention, except for treating childhood-ALL with amino acid metabolism inhibitor L-asparaginase. Despite the growing understanding of novel metabolic alterations in tumors, the therapeutic targeting of these tumor-specific dysregulations has largely been ineffective in clinical trials. This chapter discusses the major pathways involved in the metabolism of glucose, amino acids, and lipids and highlights the inter-twined nature of metabolic aberrations that promote tumorigenesis in different types of cancer. Finally, we summarise the therapeutic interventions which can be used as a combinational therapy to target metabolic dysregulations that are unique or common in blood, breast, colorectal, lung, and prostate cancer.

UV-B Irradiation to Amino Acids and Carbohydrate Metabolism in Rhododendron chrysanthum Leaves by Coupling Deep Transcriptome and Metabolome Analysis

Under natural environmental conditions, excess UV-B stress can cause serious injuries to plants. However, domestication conditions may allow the plant to better cope with the upcoming UV-B stress. The leaves of Rhododendron chrysanthum are an evergreen plant that grows at low temperatures and high altitudes in the Changbai Mountains, where the harsh ecological environment gives it different UV resistance properties. Metabolites in R. chrysanthum have a significant impact on UV-B resistance, but there are few studies on the dynamics of their material composition and gene expression levels. We used a combination of gas chromatography time-of-flight mass spectrometry and transcriptomics to analyze domesticated and undomesticated R. chrysanthum under UV-B radiation. A total of 404 metabolites were identified, of which amino acids were significantly higher and carbohydrates were significantly lower in domesticated R. chrysanthum. Transcript profiles throughout R. chrysanthum under UV-B were constructed and analyzed, with an emphasis on sugar and amino acid metabolism. The transcript levels of genes associated with sucrose and starch metabolism during UV-B resistance in R. chrysanthum showed a consistent trend with metabolite content, while amino acid metabolism was the opposite. We used metabolomics and transcriptomics approaches to obtain dynamic changes in metabolite and gene levels during UV-B resistance in R. chrysanthum. These results will provide some insights to elucidate the molecular mechanisms of UV tolerance in plants.

Metabolomic profiling of bovine leucocytes transformed by Theileria annulata under BW720c treatment

Background

When Theileria annulata infects host cells, it undertakes unlimited proliferation as tumor cells. Although the transformed cells will recover their limited reproductive characteristics and enter the apoptosis process after treatment with buparvaquone (BW720c), the metabolites and metabolic pathways involved are not clear.

Methods

The transformed cells of T. annulata were used as experimental materials, and the buparvaquone treatment group and DMSO control group were used. Qualitative and quantitative analysis was undertaken of 36 cell samples based on the LC–QTOF platform in positive and negative ion modes. The metabolites of the cell samples after 72 h of drug treatment were analyzed, as were the different metabolites and metabolic pathways involved in the BW720c treatment. Finally, the differential metabolites and metabolic pathways in the transformed cells were found.

Results

A total of 1425 metabolites were detected in the negative ion mode and 1298 metabolites were detected in the positive ion mode. After drug treatment for 24 h, 48 h, and 72 h, there were 56, 162, and 243 differential metabolites in negative ion mode, and 35, 121, and 177 differential metabolites in positive ion mode, respectively. These differential metabolites are mainly concentrated on various essential amino acids.

Conclusion

BW720c treatment induces metabolic disturbances in T. annulata-infected cells by regulating the metabolism of leucine, arginine, and l-carnitine, and induces host cell apoptosis.

Graphical abstract

Supplementary Information

The online version contains supplementary material available at 10.1186/s13071-022-05450-0.

Integrated Analysis of Colorectal Cancer Reveals Cross-Cohort Gut Microbial Signatures and Associated Serum Metabolites

BACKGROUND & AIMS

Studies have reported abnormal gut microbiota or circulating metabolome associated with colorectal cancer (CRC), but it remains a challenge to capture the CRC-relevant features consistent across geographic regions. This is particularly the problem for metabolic traits of CRC because the analyses generally use different platforms and laboratory methods, which poses a barrier to cross-dataset examination. In light of this, we sought to elucidate the microbial and metabolic signatures of CRC with broad population relevance.

METHODS

In this integrated metagenomic (healthy controls [HC], n = 91; colorectal adenoma [CRA], n = 63; CRC, n = 71) and metabolomic (HC, n = 34; CRA, n = 31; CRC, n = 35) analysis, CRC-associated features and microbe-metabolite correlations were first identified from a Shanghai cohort. A gut microbial panel was trained in the in-house cohort and cross-validated in 7 published metagenomic datasets of CRC. The in-house metabolic connections to the cross-cohort microbial signatures were used as evidence to infer serum metabolites with potentially external relevance. In addition, a combined microbe-metabolite panel was produced for diagnosing CRC or adenoma.

RESULTS

CRC-associated alterations were identified in the gut microbiome and serum metabolome. A composite microbe-metabolite diagnostic panel was developed and yielded an area under the curve of 0.912 for adenoma and 0.994 for CRC. We showed that many CRC-associated metabolites were linked to cross-cohort gut microbiome signatures of the disease, including CRC-enriched leucylalanine, serotonin, and imidazole propionate; and CRC-depleted perfluorooctane sulfonate, 2-linoleoylglycerol (18:2), and sphingadienine.

CONCLUSIONS

We generated cross-cohort metagenomic signatures of CRC, some of which linked to in-house CRC-associated serum metabolites. The microbial and metabolic shifts may have wide population relevance.

Neurotransmitter signaling: a new frontier in colorectal cancer biology and treatment

The brain-gut axis, a bidirectional network between the central and enteric nervous system, plays a critical role in modulating the gastrointestinal tract function and homeostasis. Recently, increasing evidence suggests that neuronal signaling molecules can promote gastrointestinal cancers, however, the mechanisms remain unclear. Aberrant expression of neurotransmitter signaling genes in colorectal cancer supports the role of neurotransmitters to stimulate tumor growth and metastatic spread by promoting cell proliferation, migration, invasion, and angiogenesis. In addition, neurotransmitters can interact with immune and endothelial cells in the tumor microenvironment to promote inflammation and tumor progression. As such, pharmacological targeting of neurotransmitter signaling represent a promising novel anticancer approach. Here, we present an overview of the current evidence supporting the role of neurotransmitters in colorectal cancer biology and treatment.

Metabolic-Dysregulation-Based iEESI-MS Reveals Potential Biomarkers Associated with Early-Stage and Progressive Colorectal Cancer

The application of rapid and accurate diagnostic methods can improve colorectal cancer (CRC) survival rates dramatically. Here, we used a non-targeted metabolic analysis strategy based on internal extractive electrospray ionization mass spectrometry (iEESI-MS) to detect metabolite ions associated with the progression of CRC from 172 tissues (45 stage I/II CRC, 41 stage III/IV CRC, and 86 well-matched normal tissues). A support vector machine (SVM) model based on 10 differential metabolite ions for differentiating early-stage CRC from normal tissues was built with a good prediction accuracy of 92.6%. The biomarker panel consisting of lysophosphatidylcholine (LPC) (18:0) has good diagnostic potential in differentiating early-stage CRC from advanced-stage CRC. We showed that the down-regulation of LPC (18:0) in tumor tissues is associated with CRC progression and related to the regulation of the epidermal growth factor receptor. Pathway analysis showed that metabolic pathways in CRC are related to glycerophospholipid metabolism and purine metabolism. In conclusion, we built an SVM model with good performance to distinguish between early-stage CRC and normal groups based on iEESI-MS and found that LPC (18:0) is associated with the progression of CRC.

The role of gut microbiota in the development of colorectal cancer: a review

PURPOSE

Colorectal cancer (CRC) is the cancer of the colon and rectum. Recent research has found a link between CRC and human gut microbiota. This review explores the effect of gut microbiota on colorectal carcinogenesis and the development of chemoresistance.

METHODS

A literature overview was performed to identify the gut microbiota species that showed altered abundance in CRC patients and the mechanisms by which some of them aid in the development of chemoresistance.

RESULTS

Types of gut microbiota present and methods of analyzing them were discussed. We observed that numerous microbiota showed altered abundance in CRC patients and could act as a biomarker for CRC diagnosis and treatment. Further, it was demonstrated that microbes also have a role in the development of chemoresistance by mechanisms like immune system activation, drug modification, and autophagy modulation. Finally, the key issue of the growing global problem of antimicrobial resistance and its relationship with CRC was highlighted.

CONCLUSION

This review discussed the role of gut microbiota dysbiosis on colorectal cancer progression and the development of chemoresistance.

Loss of PFKFB4 induces cell cycle arrest and glucose metabolism inhibition by inactivating MEK/ERK/c-Myc pathway in cervical cancer cells

6-Phosphofructo-2-kinase/fructose-2,6-biphosphatase 4 (PFKFB4) was reported to be necessary for tumour growth in several cancers. However, the function of PFKFB4 in cervical cancer has not been clearly elucidated. Bioinformatics analysis was applied to detect the expression of PFKFB4 in cervical cancer and the association with survival prognosis. The effect of PFKFB4 on cervical cancer cells growth, cycle, invasion, migration and glucose metabolism was investigated by loss-of-function approaches in vitro. The association between PFKFB4 and MEK/ERK/c-Myc pathway was identified by western blot assay. We found that PFKFB4 was highly expressed in cervical cancer samples and its overexpression led to a poor prognosis of cervical cancer patients. Knock down of PFKFB4 reduced cell growth, blocked cell cycle, inhibited cell invasion and migration, and blocked glucose metabolism in cervical cancer cells. Our findings afforded a theoretical basis for further research on the treatment of cervical cancer based on the control of PFKFB4 expression. Impact StatementWhat is already known on this subject? PFKFB4 was overexpressed in several kinds of cancers and its requirement for tumour growth has been confirmed in cancers such as glioma and breast cancer. However, the function of PFKFB4 in cervical cancer cells has not been clearly elucidated. A bioinformatics study showed that PFKFB4 was a member of a six-gene signature associated with glycolysis to predict the prognosis of patients with cervical cancer. However, the relationship between PFKFB4 and glucose metabolism in cervical cancer has not been revealed.What do the results of this study add? Our results showed that PFKFB4 was highly expressed in cervical cancer samples and its overexpression led to a poor prognosis of cervical cancer patients. Moreover, the administration of si-PFKFB4 significantly reduced cell growth ability, blocked cell cycle, restrained the mobility and suppressed the glucose metabolism in cervical cancer cells partially by inactivating MEK/ERK/c-Myc pathway.What are the implications of these findings for clinical practice and/or further research? Our findings afforded a theoretical basis for further research on the treatment of cervical cancer based on the control of PFKFB4 expression.

Distinct Urinary Metabolic Biomarkers of Human Colorectal Cancer

Colorectal cancer (CRC) is one of the most commonly diagnosed cancers with high mortality rate due to its poor diagnosis in the early stage. Here, we report a urinary metabolomic study on a cohort of CRC patients (n =67) and healthy controls (n =21) using ultraperformance liquid chromatography triple quadrupole mass spectrometry. Pathway analysis showed that a series of pathways that belong to amino acid metabolism, carbohydrate metabolism, and lipid metabolism were dysregulated, for instance the glycine, serine and threonine metabolism, alanine, aspartate and glutamate metabolism, glyoxylate and dicarboxylate metabolism, glycolysis, and TCA cycle. A total of 48 differential metabolites were identified in CRC compared to controls. A panel of 12 biomarkers composed of chenodeoxycholic acid, vanillic acid, adenosine monophosphate, glycolic acid, histidine, azelaic acid, hydroxypropionic acid, glycine, 3,4-dihydroxymandelic acid, 4-hydroxybenzoic acid, oxoglutaric acid, and homocitrulline were identified by Random Forest (RF), Support Vector Machine (SVM), and Boruta analysis classification model and validated by Gradient Boosting (GB), Logistic Regression (LR), and Random Forest diagnostic model, which were able to discriminate CRC subjects from healthy controls. These urinary metabolic biomarkers provided a novel and promising molecular approach for the early diagnosis of CRC.

Serum metabolomic profiling for patients with adenocarcinoma of the esophagogastric junction

INTRODUCTION

The incidence of adenocarcinoma in the esophagogastric junction (AEG) has increased in the recent years. AEG is reported to have a worse prognosis compared with tumor confined to the stomach (non-AEG). Although the metabolic changes of non-AEG have been investigated in extensive studies, little effort focused on the metabolic profiling of AEG serum.

OBJECTIVES

Here we report an untargeted gas chromatography-mass spectrometry (GC-MS) method to explore the abnormal metabolism underlying AEG.

METHODS

GC-MS-based untargeted metabolomics approach combined with multivariate statistical analyses were used to study the metabolic profiling of serum samples from AEG patients (n = 70), non-AEG patients (n = 70) and health controls (n = 71).

RESULTS

A novel serum metabolic profiling of 18 metabolites from patients of AEG and non-AEG was indicated, in comparison with health controls. Moreover, AEG and non-AEG were also well-classified with 9 distinguishing metabolites including hypoxanthine, alanine, proline, pyroglutamate, glycine, lactate, succinic acid, glutamate and kynurenine, which produced a discriminatory model with an area under the Receiver Operating Characteristic (ROC) curve of 0.852, suggesting a distinct metabolic signature of AEG. Importantly, lactate and glutamate disclosed outcome-prediction values by multivariate cox-proportional hazard model and Kaplan-Meier method based on follow-up information for 2-5 years.

CONCLUSION

This is the first metabolomics study to identify serum metabolic signature of AEG. The distinguishing metabolites show a promising application on clinical diagnose and outcome prediction, and allow us to unveil several key metabolic variations coexisting in AEG, which may aid to understand the underlying metabolic mechanisms.

Lipid metabolic reprogramming by hypoxia-inducible factor-1 in the hypoxic tumour microenvironment

Cancer cells rewire metabolic processes to adapt to the nutrient- and oxygen-deprived tumour microenvironment, thereby promoting their proliferation and metastasis. Previous research has shown that modifying glucose metabolism, the Warburg effect, makes glycolytic cancer cells more invasive and aggressive. Lipid metabolism has also been receiving attention because lipids function as energy sources and signalling molecules. Because obesity is a risk factor for various cancer types, targeting lipid metabolism may be a promising cancer therapy. Here, we review the lipid metabolic reprogramming in cancer cells mediated by hypoxia-inducible factor-1 (HIF-1). HIF-1 is the master transcription factor for tumour growth and metastasis by transactivating genes related to proliferation, survival, angiogenesis, invasion, and metabolism. The glucose metabolic shift (the Warburg effect) is mediated by HIF-1. Recent research on HIF-1-related lipid metabolic reprogramming in cancer has confirmed that HIF-1 also modifies lipid accumulation, β-oxidation, and lipolysis in cancer, triggering its progression. Therefore, targeting lipid metabolic alterations by HIF-1 has therapeutic potential for cancer. We summarize the role of the lipid metabolic shift mediated by HIF-1 in cancer and its putative applications for cancer therapy.

Metabolomic Pathway Activity with Genomic Single-Nucleotide Polymorphisms Associated with Colorectal Cancer Recurrence and 5-Year Overall Survival

PURPOSE

Metabolomic analysis in colorectal cancer (CRC) is an emerging research area with both prognostic and therapeutic targeting potential. We aimed to identify metabolomic pathway activity prognostic for CRC recurrence and overall survival and cross-reference such metabolomic data with prognostic genomic single-nucleotide polymorphisms (SNPs).

METHODS

A systematic search of PubMed, Embase and Cochrane Library was performed for studies reporting prognostic metabolomic pathway activity in CRC in keeping with PRISMA guidelines. The QUADOMICS tool was used to assess study quality. MetaboAnalyst software (version4.0) was used to map metabolites that were associated with recurrence and survival in CRC to recognise metabolic pathways and identify genomic SNPs associated with CRC prognosis, referencing the following databases: Human Metabolome Database (HMDB), the Small Molecule Pathway Database (SMPDB), PubChem and Kyoto Encyclopaedia of Genes and Genomes (KEGG) Pathway Database.

RESULTS

Nine studies met the inclusion criteria, reporting on 1117 patients. Increased metabolic activity in the urea cycle (p = 0.002, FDR = 0.198), ammonia recycling (p = 0.004, FDR = 0.359) and glycine and serine metabolism (p = 0.004, FDR = 0.374) was prognostic of CRC recurrence. Increased activity in aspartate metabolism (p < 0.001, FDR = 0.079) and ammonia recycling (p = 0.004, FDR = 0.345) was prognostic of survival. Eight resulting SNPs were prognostic for CRC recurrence (rs2194980, rs1392880, rs2567397, rs715, rs169712, rs2300701, rs313408, rs7018169) and three for survival (rs2194980, rs169712, rs12106698) of which two overlapped with recurrence (rs2194980, rs169712).

CONCLUSIONS

With a caveat on study heterogeneity, specific metabolites and metabolic pathway activity appear evident in the setting of poor prognostic colorectal cancers and such metabolic signatures are associated with specific genomic SNPs.

Integrated hepatic single-cell RNA sequencing and untargeted metabolomics reveals the immune and metabolic modulation of Qing-Fei-Pai-Du decoction in mice with coronavirus-induced pneumonia

BACKGROUND

Although Qing-Fei-Pai-Du decoction (QFPDD) is extensively used clinically to treat COVID-19 patients, the mechanism by which it modulates the immunological and metabolic functions of liver tissue remains unknown.

PURPOSE

The purpose of this study is to investigate the mechanism of action of QFPDD in the treatment of mice with coronavirus-induced pneumonia by combining integrated hepatic single-cell RNA sequencing and untargeted metabolomics.

METHODS

We developed a human coronavirus pneumonia model in BALB/c mice by infecting them with human coronavirus HCoV-229E with stimulating them with cold-damp environment. We initially assessed the status of inflammation and immunity in model mice treated with or without QFPDD by detecting peripheral blood lymphocytes and inflammatory cytokines. Then, single-cell RNA sequencing and untargeted metabolomics were performed on mouse liver tissue.

RESULTS

HCoV-229E infection in combination with exposure to a cold-damp environment significantly decreased the percentage of peripheral blood lymphocytes (CD4+ and CD8+ T cells, B cells) in mice, which was enhanced by QFPDD therapy. Meanwhile, the levels of inflammatory cytokines such as IL-6, TNF-α, and IFN-γ were significantly increased in mouse models but significantly decreased by QFPDD treatment. Single-cell RNA sequencing analysis showed that QFPDD could attenuate disease-associated alterations in gene expression, core transcriptional regulatory networks, and cell-type composition. Computational predictions indicated that QFPDD rectified the observed aberrant patterns of cell-cell communication. Additionally, the metabolic profiles of liver tissue in the Model group were distinct from mice in the Control group, and QFPDD significantly regulated hepatic purine metabolism.

CONCLUSION

To the best of our knowledge, this study is the first to integrate hepatic single-cell RNA sequencing and untargeted metabolomics into a TCM formula and these valuable findings indicate that QFPDD can improve immune function and reduce liver injury and inflammation.

Oleanolic acid blocks the purine salvage pathway for cancer therapy by inactivating SOD1 and stimulating lysosomal proteolysis

Metabolic reprogramming is a core hallmark of cancer and is key for tumorigenesis and tumor progression. Investigation of metabolic perturbation by anti-cancer compounds would allow a thorough understanding of the underlying mechanisms of these agents and identification of new anti-cancer targets. Here, we demonstrated that the administration of oleanolic acid (OA) rapidly altered cancer metabolism, particularly suppressing the purine salvage pathway (PSP). PSP restoration significantly opposed OA-induced DNA replication and cell proliferation arrest, underscoring the importance of this pathway for the anti-cancer activity of OA. Hypoxanthine-guanine phosphoribosyltransferase (HGPRT) and 5′-nucleotidase (5′-NT), two metabolic enzymes essential for PSP activity, were promptly degraded by OA via the lysosome pathway. Mechanistically, OA selectively targeted superoxide dismutase 1 (SOD1) and yielded reactive oxygen species (ROS) to activate the AMP-activated protein kinase (AMPK)/mammalian target of rapamycin complex 1 (mTORC1)/macroautophagy pathway, thus eliciting lysosomal degradation of HGPRT and 5′-NT. Furthermore, we found that the PSP was overactivated in human lung and breast cancers, with a negative correlation with patient survival. The results of this study elucidated a new anti-cancer mechanism of OA by restraining the PSP via the SOD1/ROS/AMPK/mTORC1/macroautophagy/lysosomal pathway. We also identified the PSP as a new target for cancer treatment and highlighted OA as a potential therapeutic agent for cancers with high PSP activity.

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.

Biomarkers for the prediction of esophageal cancer neoadjuvant chemoradiotherapy response: A systemic review

Neoadjuvant chemoradiotherapy followed by surgery has been established as the standard treatment for locally advanced esophageal cancer. For patients with complete regression after neoadjuvant chemotherapy, active surveillance rather than planned surgery has been proposed as an organ preservation strategy. Reliable biomarkers to predict chemoradiation response is needed. We first summarized the previous reports of biomarkers with the potential to predict the treatment response of esophageal cancer neoadjuvant chemoradiotherapy. These traditional biomarkers are classified into three groups: genetic biomarkers, RNA biomarkers, and protein biomarkers. We then summarized some special types of biomarkers, including metabolites biomarkers, immune and tumor microenvironment biomarkers, and microbiome biomarkers.

The Bio-Persistence of Reversible Inflammatory, Histological Changes and Metabolic Profile Alterations in Rat Livers after Silver/Gold Nanorod Administration

As a widely applied nanomaterial, silver nanomaterials (AgNMs) have increased public concern about their potential adverse biological effects. However, there are few related researches on the long-term toxicity, especially on the reversibility of AgNMs in vivo. In the current study, this issue was tackled by exploring liver damage after an intravenous injection of silver nanorods with golden cores (Au@AgNRs) and its potential recovery in a relatively long term (8 w). After the administration of Au@AgNRs into rats, Ag was found to be rapidly cleared from blood within 10 min and mainly accumulated in liver as well as spleen until 8 w. All detected parameters almost displayed a two-stage response to Au@AgNRs administration, including biological markers, histological changes and metabolic variations. For the short-term (2 w) responses, some toxicological parameters (hematological changes, cytokines, liver damages etc.) significantly changed compared to control and AuNRs group. However, after a 6-week recovery, all abovementioned changes mostly returned to the normal levels in the Au@AgNRs group. These indicated that after a lengthy period, acute bioeffects elicited by AgNMs could be followed by the adaptive recovery, which will provide a novel and valuable toxicity mechanism of AgNMs for potential biomedical applications of AgNMs.

Metabolic programming of Rhododendron chrysanthum leaves following exposure to UVB irradiation

Excessive UVB reaching the earth is a cause for concern. To decipher the mechanism concerning UVB resistance of plants, we studied the effects of UVB radiation on photosynthesis and metabolic profiling of Rhododendron chrysanthum Pall. by applying 2.3Wm-2 of UVB radiation for 2days. Results showed that maximum quantum yield of PSII (Fv/Fm) and effective quantum yield of PSII (φPSII) decreased by 7.95% and 8.36%, respectively, following UVB exposure. Twenty five known metabolites were identified as most important by two different methods, including univariate and multivariate statistical analyses. Treatment of R. chrysanthum with UVB increased the abundance of flavonoids, organic acids, and amino acids by 62%, 22%, and 5%, respectively. UVB irradiation also induced about 1.18-fold increase in 11 top-ranked metabolites identified: five organic acids (d-2,3-dihydroxypropanoic acid, maleic acid, glyceric acid, fumaric acid and suberic acid), four amino acids (l-norleucine, 3-oxoalanine, l-serine and glycine), and two fatty acids (pelargonic acid and myristoleic acid). In addition, UVB irradiation increased the intermediate products of arginine biosynthesis and the TCA cycle. Taken together, the accumulation of flavonoids, organic acids, amino acids and fatty acids, accompanied by enhancement of TCA cycle and arginine biosynthesis, may protect R. chrysanthum plants against UVB deleterious effects.

A multi-omics study delineates new molecular features and therapeutic targets for esophageal squamous cell carcinoma

Esophageal squamous cell carcinoma (ESCC) is a major histological subtype of esophageal cancer with inferior prognosis. Here, we conducted comprehensive transcriptomic, proteomic, phosphoproteomic, and metabolomic characterization of human, treatment-naive ESCC and paired normal adjacent tissues (cohort 1, n = 24) in an effort to identify new molecular vulnerabilities for ESCC and potential therapeutic targets. Integrative analysis revealed a small group of genes that were related to the active posttranscriptional and posttranslational regulation of ESCC. By using proteomic, phosphoproteomic, and metabolomic data, networks of ESCC-related signaling and metabolic pathways that were closely linked to cancer etiology were unraveled. Notably, integrative analysis of proteomic and phosphoproteomic data pinpointed that certain pathways involved in RNA transcription, processing, and metabolism were stimulated in ESCC. Importantly, proteins with close linkage to ESCC prognosis were identified. By enrolling an ESCC patient cohort 2 (n = 41), three top-ranked prognostic proteins X-prolyl aminopeptidase 3 (XPNPEP3), bromodomain PHD finger transcription factor (BPTF), and fibrillarin (FBL) were verified to have increased expression in ESCC. Among these prognostic proteins, only FBL, a well-known nucleolar methyltransferase, was essential for ESCC cell growth in vitro and in vivo. Furthermore, a validation study using an ESCC patient cohort 3 (n = 100) demonstrated that high FBL expression predicted unfavorable patient survival. Finally, common cancer/testis antigens and established cancer drivers and kinases, all of which could direct therapeutic decisions, were characterized. Collectively, our multi-omics analyses delineated new molecular features associated with ESCC pathobiology involving epigenetic, posttranscriptional, posttranslational, and metabolic characteristics, and unveiled new molecular vulnerabilities with therapeutic potential for ESCC.

Integrative Metabolomic and Lipidomic Profiling of Lung Squamous Cell Carcinoma for Characterization of Metabolites and Intact Lipid Species Related to the Metastatic Potential

SQCC is a major type of NSCLC, which is a major cause of cancer-related deaths, and there were no reports regarding the prediction of metastatic potential of lung SQCC by metabolomic and lipidomic profiling. In this study, metabolomic and lipidomic profiling of lung SQCC were performed to predict its metastatic potential and to suggest potential therapeutic targets for the inhibition of lung SQCC metastasis. Human bronchial epithelial cells and four lung SQCC cell lines with different metastatic potentials were analyzed using gas chromatography-mass spectrometry and direct infusion-mass spectrometry. Based on the obtained metabolic and lipidomic profiles, we constructed models to predict the metastatic potential of lung SQCC; glycerol, putrescine, β-alanine, hypoxanthine, inosine, myo-inositol, phosphatidylinositol (PI) 18:1/18:1, and PI 18:1/20:4 were suggested as characteristic metabolites and intact lipid species associated with lung SQCC metastatic potential. In this study, we established predictive models for the metastatic potential of lung SQCC; furthermore, we identified metabolites and intact lipid species relevant to lung SQCC metastatic potential that may serve as potential therapeutic targets for the inhibition of lung SQCC metastasis.

Integration of global metabolomics and lipidomics approaches reveals the molecular mechanisms and the potential biomarkers for postoperative recurrence in early-stage cholangiocarcinoma

Background

Cholangiocarcioma (CCA) treatment is challenging because most of the patients are diagnosed when the disease is advanced, and cancer recurrence is the main problem after treatment, leading to low survival rates. Therefore, our understanding of the mechanism underlying CCA recurrence is essential in order to prevent CCA recurrence and improve patient outcomes.

Methods

We performed ¹H-NMR and UPLC-MS-based metabolomics on the CCA serum. The differential metabolites were further analyzed using pathway analysis and potential biomarker identification.

Results

At an early stage, the metabolites involved in energy metabolisms, such as pyruvate metabolism, and the TCA cycle, are downregulated, while most lipids, including TGs, PCs, PEs, and PAs, are upregulated in recurrence patients. This metabolic feature has been described in cancer stem-like cell (CSC) metabolism. In addition, the CSC markers CD44v6 and CD44v8-10 are associated with CD36 (a protein involved in lipid uptake) as well as with recurrence-free survival. We also found that citrate, sarcosine, succinate, creatine, creatinine and pyruvate, and TGs have good predictive values for CCA recurrence.

Conclusion

Our study demonstrates the possible molecular mechanisms underlying CCA recurrence, and these may associate with the existence of CSCs. The metabolic change involved in the recurrence pathway might be used to determine biomarkers for predicting CCA recurrence.

Supplementary Information

The online version contains supplementary material available at 10.1186/s40170-021-00266-5.

Systems-level biomarkers identification and drug repositioning in colorectal cancer

Colorectal cancer (CRC) is the most commonly diagnosed fatal cancer in both women and men worldwide. CRC ranked second in mortality and third in incidence in 2020. It is difficult to diagnose CRC at an early stage as there are no clinical symptoms. Despite advances in molecular biology, only a limited number of biomarkers have been translated into routine clinical practice to predict risk, prognosis and response to treatment. In the last decades, systems biology approaches at the omics level have gained importance. Over the years, several biomarkers for CRC have been discovered in terms of disease diagnosis and prognosis. On the other hand, a few drugs are being developed and used in clinics for the treatment of CRC. However, the development of new drugs is very costly and time-consuming as the research and development takes about 10 years and more than $1 billion. Therefore, drug repositioning (DR) could save time and money by establishing new indications for existing drugs. In this review, we aim to provide an overview of biomarkers for the diagnosis and prognosis of CRC from the systems biology perspective and insights into DR approaches for the prevention or treatment of CRC.

Application of metabolomics in clinical and laboratory gastrointestinal oncology

Metabolites are versatile bioactive molecules. They are not only the substrates and/or the products of enzymatic reactions but also act as the regulators in the systemic metabolism. Metabolomics is a high-throughput analytical strategy to qualify or quantify as many metabolites as possible in the metabolomes. It is an indispensable part of systems biology. The leading techniques in this field are mainly based on mass spectrometry and nuclear magnetic resonance spectroscopy. The metabolomic analysis has gained wide use in bioscience fields. In the tumor research arena, metabolomics can be employed to identify biomarkers for prediction, diagnosis, and prognosis. Chemotherapeutic effect evaluation and personalized medicine decision-making can also benefit from metabolomic analysis of patient biofluid or biopsy samples. Many cell-level studies can help in disease exploration. In this review, the basic features and principles of varied metabolomic analysis are introduced. The value of metabolomics in clinical and laboratory gastrointestinal cancer studies is discussed, especially for mass spectrometry applications. Besides, combined use of metabolomics and other tools to solve problems in cancer practice is briefly illustrated. In summary, metabolomics paves a new way to explore cancerous diseases in the light of small molecules.

A Serum Metabolomics Classifier Derived from Elderly Patients with Metastatic Colorectal Cancer Predicts Relapse in the Adjuvant Setting

Simple Summary

Around 30–40% of patients with early stage colorectal cancer (eCRC) experience relapse after surgery. Current recommendations for adjuvant therapy are based on suboptimal risk-stratification tools. In elderly patients, risk of relapse assessment is particularly important to ultimately avoid unnecessary chemotherapy-related toxicity in this frailer population. Serum metabolomics via NMR spectroscopy may improve risk stratification by identifying patients with residual micrometastases after surgery and thus at higher risk of relapse. We evaluated the serum metabolomic fingerprints of 94 elderly patients with eCRC (65 relapse free and 29 relapsed), and of 75 elderly patients with metastatic disease. Metabolomics efficiently discriminated patients with relapse-free eCRC from those with metastatic disease, correctly predicting relapse in 69% of relapsed eCRC patients. The metabolomic score was strongly and independently associated with prognosis. Our data suggest metabolomics as a valid addition to standard tools to refine risk stratification for eCRC and warrant further investigation.

Abstract

Adjuvant treatment for patients with early stage colorectal cancer (eCRC) is currently based on suboptimal risk stratification, especially for elderly patients. Metabolomics may improve the identification of patients with residual micrometastases after surgery. In this retrospective study, we hypothesized that metabolomic fingerprinting could improve risk stratification in patients with eCRC. Serum samples obtained after surgery from 94 elderly patients with eCRC (65 relapse free and 29 relapsed, after 5-years median follow up), and from 75 elderly patients with metastatic colorectal cancer (mCRC) obtained before a new line of chemotherapy, were retrospectively analyzed via proton nuclear magnetic resonance spectroscopy. The prognostic role of metabolomics in patients with eCRC was assessed using Kaplan–Meier curves. PCA-CA-kNN could discriminate the metabolomic fingerprint of patients with relapse-free eCRC and mCRC (70.0% accuracy using NOESY spectra). This model was used to classify the samples of patients with relapsed eCRC: 69% of eCRC patients with relapse were predicted as metastatic. The metabolomic classification was strongly associated with prognosis (p-value 0.0005, HR 3.64), independently of tumor stage. In conclusion, metabolomics could be an innovative tool to refine risk stratification in elderly patients with eCRC. Based on these results, a prospective trial aimed at improving risk stratification by metabolomic fingerprinting (LIBIMET) is ongoing.

Screening of important metabolites and KRAS genotypes in colon cancer using secondary ion mass spectrometry

Time-of-flight secondary ion mass spectrometry (TOF-SIMS) is an imaging-based analytical technique that can characterize the surfaces of biomaterials. We used TOF-SIMS to identify important metabolites and oncogenic KRAS mutation expressed in human colorectal cancer (CRC). We obtained 540 TOF-SIMS spectra from 180 tissue samples by scanning cryo-sections and selected discriminatory molecules using the support vector machine (SVM) algorithm. Each TOF-SIMS spectrum contained nearly 860,000 ion profiles and hundreds of spectra were analyzed; therefore, reducing the dimensionality of the original data was necessary. We performed principal component analysis after preprocessing the spectral data, and the principal components (20) of each spectrum were used as the inputs of the SVM algorithm using the R package. The performance of the algorithm was evaluated using the receiver operating characteristic (ROC) area under the curve (AUC) (0.9297). Spectral peaks (m/z) corresponding to discriminatory molecules used to classify normal and tumor samples were selected according to p-value and were assigned to arginine, α-tocopherol, and fragments of glycerophosphocholine. Pathway analysis using these discriminatory molecules showed that they were involved in gastrointestinal disease and organismal abnormalities. In addition, spectra were classified according to the expression of KRAS somatic mutation, with 0.9921 AUC. Taken together, TOF-SIMS efficiently and simultaneously screened metabolite biomarkers and performed KRAS genotyping. In addition, a machine learning algorithm was provided as a diagnostic tool applied to spectral data acquired from clinical samples prepared as frozen tissue slides, which are commonly used in a variety of biomedical tests.

Lipid profiling of mouse intestinal organoids for studying APC mutations

Inactivating mutations including both germline and somatic mutations in the adenomatous polyposis coli (APC) gene drives most familial and sporadic colorectal cancers. Understanding the metabolic implications of this mutation will aid to establish its wider impact on cellular behaviour and potentially inform clinical decisions. However, to date, alterations in lipid metabolism induced by APC mutations remain unclear. Intestinal organoids have gained widespread popularity in studying colorectal cancer and chemotherapies, because their 3D structure more accurately mimics an in vivo environment. Here, we aimed to investigate intra-cellular lipid disturbances induced by APC gene mutations in intestinal organoids using a reversed-phase ultra-high-performance liquid chromatography mass spectrometry (RP-UHPLC-MS)-based lipid profiling method. Lipids of the organoids grown from either wild-type (WT) or mice with APC mutations (Lgr5-EGFP-IRES-CreERT2Apcfl/fl) were extracted and analysed using RP-UHPLC-MS. Levels of phospholipids (e.g. PC(16:0/16:0), PC(18:1/20:0), PC(38:0), PC(18:1/22:1)), ceramides (e.g. Cer(d18:0/22:0), Cer(d42:0), Cer(d18:1/24:1)) and hexosylceramides (e.g. HexCer(d18:1/16:0), HexCer(d18:1/22:0)) were higher in Apcfl/fl organoids, whereas levels of sphingomyelins (e.g. SM(d18:1/14:0), SM(d18:1/16:0)) were lower compared with WT. These observations indicate that cellular metabolism of sphingomyelin was up-regulated, resulting in the cellular accumulation of ceramides and production of HexCer due to the absence of Apcfl/fl in the organoids. Our observations demonstrated lipid profiling of organoids and provided an enhanced insight into the effects of the APC mutations on lipid metabolism, making for a valuable addition to screening options of the organoid lipidome.

Lipidomic Signatures for Colorectal Cancer Diagnosis and Progression Using UPLC-QTOF-ESI+MS

Metabolomics coupled with bioinformatics may identify relevant biomolecules such as putative biomarkers of specific metabolic pathways related to colorectal diagnosis, classification and prognosis. This study performed an integrated metabolomic profiling of blood serum from 25 colorectal cancer (CRC) cases previously classified (Stage I to IV) compared with 16 controls (disease-free, non-CRC patients), using high-performance liquid chromatography and mass spectrometry (UPLC-QTOF-ESI⁺ MS). More than 400 metabolites were separated and identified, then all data were processed by the advanced Metaboanalyst 5.0 online software, using multi- and univariate analysis, including specificity/sensitivity relationships (area under the curve (AUC) values), enrichment and pathway analysis, identifying the specific pathways affected by cancer progression in the different stages. Several sub-classes of lipids including phosphatidylglycerols (phosphatidylcholines (PCs), phosphatidylethanolamines (PEs) and PAs), fatty acids and sterol esters as well as ceramides confirmed the “lipogenic phenotype” specific to CRC development, namely the upregulated lipogenesis associated with tumor progression. Both multivariate and univariate bioinformatics confirmed the relevance of some putative lipid biomarkers to be responsible for the altered metabolic pathways in colorectal cancer.

Understanding cell-cell communication and signaling in the colorectal cancer microenvironment

Carcinomas are complex heterocellular systems containing epithelial cancer cells, stromal fibroblasts, and multiple immune cell-types. Cell-cell communication between these tumor microenvironments (TME) and cells drives cancer progression and influences response to existing therapies. In order to provide better treatments for patients, we must understand how various cell-types collaborate within the TME to drive cancer and consider the multiple signals present between and within different cancer types. To investigate how tissues function, we need a model to measure both how signals are transferred between cells and how that information is processed within cells. The interplay of collaboration between different cell-types requires cell-cell communication. This article aims to review the current in vitro and in vivo mono-cellular and multi-cellular cultures models of colorectal cancer (CRC), and to explore how they can be used for single-cell multi-omics approaches for isolating multiple types of molecules from a single-cell required for cell-cell communication to distinguish cancer cells from normal cells. Integrating the existing single-cell signaling measurements and models, and through understanding the cell identity and how different cell types communicate, will help predict drug sensitivities in tumor cells and between- and within-patients responses.

Molecular-Based Score inspired on metabolic signature improves prognostic stratification for myelodysplastic syndrome

Deregulated cellular energetics is formally incorporated as an emerging hallmark of cancer, however little is known about its processes in myelodysplastic syndromes (MDS). Using transcriptomic data of CD34+ cells from 159 MDS patients and 17 healthy donors, we selected 37 genes involved in cellular energetics and interrogated about its clinical and prognostic functions. Based on the low expression of ACLY, ANPEP, and PANK1, as well as high expression of PKM and SLC25A5, we constructed our Molecular-Based Score (MBS), that efficiently discriminated patients at three risks groups: favourable risk (n = 28; 3-year overall survival (OS): 100%); intermediate (n = 60; 76% [62-93%]) and adverse (n = 71; 35% [17-61%]). Adverse MBS risk was independently associated with inferior OS (HR = 10.1 [95% CI 1.26-81]; P = 0.029) in multivariable analysis using age, gender and the revised international prognostic score system as confounders. Transcriptional signature revealed that Favourable- and intermediate-risk patients presented enriched molecular programs related to mature myeloid progenitors, cell cycle progression, and oxidative phosphorylation, indicating that this cells differs in their origin, metabolic state, and cell cycle regulation, in comparison to the adverse-risk. Our study provides the first evidence that cellular energetics is transcriptionally deregulated in MDS CD34+ cells and establishes a new useful prognostic score based on the expression of five genes.

Non-Coding and Regulatory RNAs as Epigenetic Remodelers of Fatty Acid Homeostasis in Cancer

Cancer cells commonly display metabolic fluctuations. Together with the Warburg effect and the increased glutaminolysis, alterations in lipid metabolism homeostasis have been recognized as a hallmark of cancer. Highly proliferative cancer cells upregulate de novo synthesis of fatty acids (FAs) which are required to support tumor progression by exerting multiple roles including structural cell membrane composition, regulators of the intracellular redox homeostasis, ATP synthesis, intracellular cell signaling molecules, and extracellular mediators of the tumor microenvironment. Epigenetic modifications have been shown to play a crucial role in human development, but also in the initiation and progression of complex diseases. The study of epigenetic processes could help to design new integral strategies for the prevention and treatment of metabolic disorders including cancer. Herein, we first describe the main altered intracellular fatty acid processes to support cancer initiation and progression. Next, we focus on the most important regulatory and non-coding RNAs (small noncoding RNA-sncRNAs-long non-coding RNAs-lncRNAs-and other regulatory RNAs) which may target the altered fatty acids pathway in cancer.