Reduced levels of hydroxylated, polyunsaturated ultra long-chain fatty acids in the serum of colorectal cancer patients: implications for early screening and detection

Lipid biomarkers in colorectal cancer, with particular emphasis on exosomes - current status and future inferences

INTRODUCTION

Colorectal cancer (CRC) is one of the most deadly cancers on a global scale. Diagnosis of CRC is challenging and it is often detected at a late stage. Identification of relevant biomarkers could lead to the development of effective diagnostic methods for CRC.

AREAS COVERED

We reviewed the literature on lipid (including exosomal) biomarkers that have the potential to become common, minimally invasive and effective diagnostic tools for CRC. We showed that differences in lipid levels (single compounds and entire panels) make it possible to classify patients into diseased or healthy groups, determine the stage of CRC, as well as accompanying inflammation and immune reactions associated with tumorigenesis. We also discussed exosomes which are important components of the tumor microenvironment that influence tumor progression and for which only a small number of studies were conducted so far in this area.

EXPERT OPINION

A rapid development in the field of lipid-based biomarkers, including exosomal lipid biomarkers, is expected as growing evidence shows their potential application and good accuracy. However, one of the major issues that needs to be addressed within this topic is to translate findings into a noninvasive and versatile diagnostic test robustly validated in clinical conditions.

A critical appraisal of the role of metabolomics in breast cancer research and diagnostics

Breast cancer (BC) remains the most prevalent cancer among women worldwide, despite significant advancements in its prevention and treatment. The escalating incidence of BC globally necessitates continued research into novel diagnostic and therapeutic strategies. Metabolomics, a burgeoning field, offers a comprehensive analysis of all metabolites within a cell, tissue, system, or organism, providing crucial insights into the dynamic changes occurring during cancer development and progression. This review focuses on the metabolic alterations associated with BC, highlighting the potential of metabolomics in identifying biomarkers for early detection, diagnosis, treatment and prognosis. Metabolomics studies have revealed distinct metabolic signatures in BC, including alterations in lipid metabolism, amino acid metabolism, and energy metabolism. These metabolic changes not only support the rapid proliferation of cancer cells but also influence the tumour microenvironment and therapeutic response. Furthermore, metabolomics holds great promise in personalized medicine, facilitating the development of tailored treatment strategies based on an individual's metabolic profile. By providing a holistic view of the metabolic changes in BC, metabolomics has the potential to revolutionize our understanding of the disease and improve patient outcomes.

Identifying metabolic features of colorectal cancer liability using Mendelian randomization

Background

Recognizing the early signs of cancer risk is vital for informing prevention, early detection, and survival.

Methods

To investigate whether changes in circulating metabolites characterize the early stages of colorectal cancer (CRC) development, we examined the associations between a genetic risk score (GRS) associated with CRC liability (72 single-nucleotide polymorphisms) and 231 circulating metabolites measured by nuclear magnetic resonance spectroscopy in the Avon Longitudinal Study of Parents and Children (N = 6221). Linear regression models were applied to examine the associations between genetic liability to CRC and circulating metabolites measured in the same individuals at age 8 y, 16 y, 18 y, and 25 y.

Results

The GRS for CRC was associated with up to 28% of the circulating metabolites at FDR-P < 0.05 across all time points, particularly with higher fatty acids and very-low- and low-density lipoprotein subclass lipids. Two-sample reverse Mendelian randomization (MR) analyses investigating CRC liability (52,775 cases, 45,940 controls) and metabolites measured in a random subset of UK Biobank participants (N = 118,466, median age 58 y) revealed broadly consistent effect estimates with the GRS analysis. In conventional (forward) MR analyses, genetically predicted polyunsaturated fatty acid concentrations were most strongly associated with higher CRC risk.

Conclusions

These analyses suggest that higher genetic liability to CRC can cause early alterations in systemic metabolism and suggest that fatty acids may play an important role in CRC development.

Funding

This work was supported by the Elizabeth Blackwell Institute for Health Research, University of Bristol, the Wellcome Trust, the Medical Research Council, Diabetes UK, the University of Bristol NIHR Biomedical Research Centre, and Cancer Research UK. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. This work used the computational facilities of the Advanced Computing Research Centre, University of Bristol - http://www.bristol.ac.uk/acrc/.

Epigenetic and metabolic reprogramming in inflammatory bowel diseases: diagnostic and prognostic biomarkers in colorectal cancer

BACKGROUND AND AIM

"Inflammatory bowel disease" (IBD) is a chronic, relapsing inflammatory disease of the intestinal tract that typically begins at a young age and might transit to colorectal cancer (CRC). In this manuscript, we discussed the epigenetic and metabolic change to present a extensive view of IBDs transition to CRC. This study discusses the possible biomarkers for evaluating the condition of IBDs patients, especially before the transition to CRC.

RESEARCH APPROACH

We searched "PubMed" and "Google Scholar" using the keywords from 2000 to 2022.

DISCUSSION

In this manuscript, interesting titles associated with IBD and CRC are discussed to present a broad view regarding the epigenetic and metabolic reprogramming and the biomarkers.

CONCLUSION

Epigenetics can be the main reason in IBD transition to CRC, and Hypermethylation of several genes, such as VIM, OSM4, SEPT9, GATA4 and GATA5, NDRG4, BMP3, ITGA4 and plus hypomethylation of LINE1 can be used in IBD and CRC management. Epigenetic, metabolisms and microbiome-derived biomarkers, such as Linoleic acid and 12 hydroxy 8,10-octadecadienoic acid, Serum M2-pyruvate kinase and Six metabolic genes (NAT2, XDH, GPX3, AKR1C4, SPHK and ADCY5) expression are valuable biomarkers for early detection and transition to CRC condition. Some miRs, such as miR-31, miR-139-5p, miR -155, miR-17, miR-223, miR-370-3p, miR-31, miR -106a, miR -135b and miR-320 can be used as biomarkers to estimate IBD transition to CRC condition.

Serum Lipidomic Screen Identifies Key Metabolites, Pathways, and Disease Classifiers in Crohn's Disease

BACKGROUND

There is an unmet medical need for biomarkers that capture host and environmental contributions in inflammatory bowel diseases (IBDs). This study aimed at testing the potential of circulating lipids as disease classifiers given their major roles in inflammation.

METHODS

We applied a previously validated comprehensive high-resolution liquid chromatography-mass spectrometry-based untargeted lipidomic workflow covering 25 lipid subclasses to serum samples from 100 Crohn's disease (CD) patients and 100 matched control subjects. Findings were replicated and expanded in another 200 CD patients and 200 control subjects. Key metabolites were tested for associations with disease behavior and location, and classification models were built and validated. Their association with disease activity was tested using an independent cohort of 42 CD patients.

RESULTS

We identified >70 metabolites with strong association (P < 1 × 10-4, q < 5 × 10-4) to CD. Highly performing classification models (area under the curve > 0.84-0.97) could be built with as few as 5 to 9 different metabolites, representing 6 major correlated lipid clusters. These classifiers included a phosphatidylethanolamine ether (O-16:0/20:4), a sphingomyelin (d18:1/21:0) and a cholesterol ester (14:1), a very long-chain dicarboxylic acid [28:1(OH)] and sitosterol sulfate. These classifiers and correlated lipids indicate a dysregulated metabolism in host cells, notably in peroxisomes, as well as dysbiosis, oxidative stress, compromised inflammation resolution, or intestinal membrane integrity. A subset of these were associated with disease behavior or location.

CONCLUSIONS

Untargeted lipidomic analyses uncovered perturbations in the circulating human CD lipidome, likely resulting from multiple pathogenic mechanisms. Models using as few as 5 biomarkers had strong disease classifier characteristics, supporting their potential use in diagnosis or prognosis.

Higher Plasma Creatinine Is Associated with an Increased Risk of Death in Patients with Non-Metastatic Rectal but Not Colon Cancer: Results from an International Cohort Consortium

Colorectal cancer (CRC) is increasingly recognized as a heterogeneous disease. No studies have prospectively examined associations of blood metabolite concentrations with all-cause mortality in patients with colon and rectal cancer separately. Targeted metabolomics (Biocrates AbsoluteIDQ p180) and pathway analyses (MetaboAnalyst 4.0) were performed on pre-surgery collected plasma from 674 patients with non-metastasized (stage I-III) colon (n = 394) or rectal cancer (n = 283). Metabolomics data and covariate information were received from the international cohort consortium MetaboCCC. Cox proportional hazards models were computed to investigate associations of 148 metabolite levels with all-cause mortality adjusted for age, sex, tumor stage, tumor site (whenever applicable), and cohort; the false discovery rate (FDR) was used to account for multiple testing. A total of 93 patients (14%) were deceased after an average follow-up time of 4.4 years (60 patients with colon cancer and 33 patients with rectal cancer). After FDR adjustment, higher plasma creatinine was associated with a 39% increase in all-cause mortality in patients with rectal cancer. HR: 1.39, 95% CI 1.23-1.72, pFDR = 0.03; but not colon cancer: pFDR = 0.96. Creatinine is a breakdown product of creatine phosphate in muscle and may reflect changes in skeletal muscle mass. The starch and sucrose metabolisms were associated with increased all-cause mortality in colon cancer but not in rectal cancer. Genes in the starch and sucrose metabolism pathways were previously linked to worse clinical outcomes in CRC. In summary, our findings support the hypothesis that colon and rectal cancer have different etiological and clinical outcomes that need to be considered for targeted treatments.

Serum nuclear magnetic resonance metabolomics analysis of human metastatic colorectal cancer: Biomarkers and pathway analysis

We describe the use of nuclear magnetic resonance metabolomics to analyze blood serum samples from healthy individuals (n = 26) and those with metastatic colorectal cancer (CRC; n = 57). The assessment, employing both linear and nonlinear multivariate data analysis techniques, revealed specific metabolite changes associated with metastatic CRC, including increased levels of lactate, glutamate, and pyruvate, and decreased levels of certain amino acids and total fatty acids. Biomarker ratios such as glutamate-to-glutamine and pyruvate-to-alanine were also found to be related to CRC. The study also found that glutamate was linked to progression-free survival and that both glutamate and 3-hydroxybutyrate were risk factors for metastatic CRC. Additionally, gas chromatography coupled to flame-ionization detection was utilized to analyze the fatty acid profile and pathway analysis was performed on the profiled metabolites to understand the metabolic processes involved in CRC. A correlation was also found between the presence of certain metabolites in the blood of CRC patients and certain clinical features.

Metabolomic profiling for the preventive effects of dietary grape pomace against colorectal cancer

Colorectal cancer (CRC) is one of the most common and deadly cancers worldwide. Grape pomace (GP) is a rich source of bioactive compounds with anti-inflammatory, and anticancer effects. We recently found that dietary GP had protective effects against CRC development in the azoxymethane (AOM)/dextran sulfate sodium (DSS) CRC mouse model through suppression of cell proliferation and modulation of DNA methylation. However, the underlying molecular mechanisms associated with changes in metabolites remain unexamined. This study profiled fecal metabolomic changes in a mouse CRC model in response to GP supplementation using gas chromatography-mass spectrometry (GC-MS) based metabolomic analysis. A total of 29 compounds showed significant changes due to GP supplementation, including bile acids, amino acids, fatty acids, phenols/flavonoids, glycerolipids, carbohydrates, organic acids, and others. The major changes in metabolites of feces include increased deoxycholic acid (DCA) and decreased amino acid content. Dietary GP upregulated the expression of farnesoid X receptor (FXR) downstream genes while decreasing fecal urease activity. DNA repair enzyme MutS Homolog 2 (MSH2) was upregulated by GP supplementation. Consistently, γ-H2AX, as a DNA damage marker, decreased in GP supplemented mice. Moreover, MDM2, a protein in the ataxia telangiectasia mutated (ATM) signaling, was decreased by GP supplementation. These data provided valuable metabolic clues for unraveling the protective effects of GP supplementation against CRC development.

Plasma metabolomics for the assessment of the progression of non-small cell lung cancer

Objectives

Non-small cell lung cancer (NSCLC) is a leading type of lung cancer with a high mortality rate worldwide. Although many procedures for the diagnosis and prognosis assessment of lung cancer exist, they are often laborious, expensive, and invasive. This study aimed to develop an ultra-high performance liquid chromatography-tandem mass spectrometry (UPLC–MS/MS)-based analysis method for the plasma biomarkers of NSCLC with the potential to indicate the stages and progression of this malignancy conveniently and reliably.

Methods

A total of 53 patients with NSCLC in early stages (I–III) and advanced stage (IV) were classified into the early and advanced groups based on the tumor node metastasis staging system. A comprehensive metabolomic analysis of plasma from patients with NSCLC was performed via UPLC–MS/MS. Principal component analysis and partial least squares–discriminant analysis were conducted for statistical analysis. Potential biomarkers were evaluated and screened through receiver operating characteristic analyses and correlation analysis. Main differential metabolic pathways were also identified by utilizing metaboanalyst.

Results

A total of 129 differential metabolites were detected in accordance with the criteria of VIP ≥ 1 and a P-value of ≤ 0.05. The receiver operating characteristic curves indicated that 11 of these metabolites have the potential to be promising markers of disease progression. Apparent correlated metabolites were also filtered out. Furthermore, the 11 most predominant metabolic pathways with alterations involved in NSCLC were identified.

Conclusion

Our study focused on the plasma metabolomic changes in patients with NSCLC. These changes may be used for the prediction of the stage and progression of NSCLC. Moreover, we discussed the metabolic pathways wherein the altered metabolites were mainly enriched.

The contribution of the gut-liver axis to the immune signaling pathway of NAFLD

Nonalcoholic fatty liver disease (NAFLD) is the liver manifestation of metabolic syndrome and is the most common chronic liver disease in the world. The pathogenesis of NAFLD has not been fully clarified; it involves metabolic disturbances, inflammation, oxidative stress, and various forms of cell death. The “intestinal-liver axis” theory, developed in recent years, holds that there is a certain relationship between liver disease and the intestinal tract, and changes in intestinal flora are closely involved in the development of NAFLD. Many studies have found that the intestinal flora regulates the pathogenesis of NAFLD by affecting energy metabolism, inducing endotoxemia, producing endogenous ethanol, and regulating bile acid and choline metabolism. In this review, we highlighted the updated discoveries in intestinal flora dysregulation and their link to the pathogenesis mechanism of NAFLD and summarized potential treatments of NAFLD related to the gut microbiome.

Very long chain fatty acids

Very long chain fatty acids (VLCFAs) are important components of various lipid classes in most organisms, from bacteria to higher plants and mammals, including humans. VLCFAs, or very long chain polyunsaturated fatty acids (VLCPUFAs), can be defined as fatty acids with 23 or more carbon atoms in the molecule. The main emphasis in this review is on the analysis of these acids, including obtaining standards from natural sources or their synthesis. Furthermore, the occurrence and analysis of these compounds in both lower (bacteria, invertebrates) and higher organisms (flowering plants or mammals) are discussed in detail. Attention is paid to their biosynthesis, especially the elongation of very long chain fatty acids protein (ELOVL4). This review deals with papers describing these very interesting compounds, whose chemical, biochemical and biological properties have not been fully explored.

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.

Plasmalogen Deficiency and Overactive Fatty Acid Elongation Biomarkers in Serum of Breast Cancer Patients Pre- and Post-Surgery-New Insights on Diagnosis, Risk Assessment, and Disease Mechanisms

Simple Summary

Breast cancer (BC) is the most commonly diagnosed cancer in women. Mammography and ultrasonography are commonly used for BC screening; however, they are associated with problems such as inconvenience, radiation exposure, and dependence on the skill level of operators. To overcome this problem, we performed a comprehensive lipid metabolomic analysis of serum using high-resolution accurate mass spectrometry from two case-control studies that included non-BC, BC subjects pre-surgery and BC subjects one-month post-surgery to determine if the metabolic signatures of over-active fatty acid elongation and other lipid changes could be detected in BC vs. non-BC subjects. The ratios of the linoleic acid to the oleic acid which were evaluated in multiple lipid pools were lower in pre-surgery BC subjects, however, these ratios increased at post-surgery and were no longer different from non-BC subjects. On the other hand, the ethanolamine plasmalogen levels were lower in pre-surgery BC subjects and were not recovered by surgical removal. These do not appear to be caused by BC tumor activity and may be pre-existent and a possible risk factor for BC. In this study, we have identified several lipid metabolic systems that detect both BC risk and BC activity.

Abstract

The polyunsaturated fatty acid (PUFA) elongase, ELOVL5, is upregulated in breast cancer (BC) vs. adjacent normal tissue. We performed a comprehensive lipid metabolomic analysis of serum using high-resolution accurate mass spectrometry from two case-control studies that included non-BC, BC subjects pre-surgery, and BC subjects one-month post-surgery to determine if the metabolic signatures of over-active fatty acid elongation and other lipid changes could be detected in BC vs. non-BC subjects: study 1 (n = 48: non-BC, n = 69: pre-surgery BC); study 2 (blinded validation: n = 121: non-BC, n = 62: pre-surgery BC, n = 31: one month post-surgery). The ratio of the ELOVL5 precursor, linoleic acid (18:2) to a non-ELOVL5 precursor, oleic acid (18:1) was evaluated in multiple lipid pools (phosphatidylethanolamine (PtdEtn), phosphatidylcholine (PtdCho), lyso-PtdCho, and free fatty acids). This ratio was lower in pre-surgery BC subjects in all pools in both studies (p < 0.001). At one-month post-surgery, the 18:2/18:1 ratios increased vs. pre-surgery and were no longer different from non-BC subjects (p > 0.05 expect for lyso-PtdCho). In contrast to the elongation biomarkers, docosahexaenoic acid (22:6n-3) containing ethanolamine plasmalogen (EtnPls) species were observed to be further decreased in BC subjects one-month post-surgery vs. pre-surgery levels (p < 0.001). These results are consistent with the hypothesis that ELOVL5 is upregulated in BC tissue, which would result in the selective depletion of 18:2 vs. 18:1 containing lipid species. Surgical removal of the tumor removes the overactive ELOVL5 effect on serum lipids. In contrast, the low EtnPls levels do not appear to be caused by BC tumor activity and may be pre-existent and a possible risk factor for BC. These results indicate that it may be possible to screen for both breast cancer risk and breast cancer activity using a simple blood test.

Molecular Characterization of Advanced Colorectal Cancer Using Serum Proteomics and Metabolomics

Colorectal cancer (CRC) is a growing public health concern due to its high mortality rate. Currently, there is a lack of valid diagnostic biomarkers and few therapeutic strategies are available for CRC treatment, especially for advanced CRC whose underlying pathogenic mechanisms remain poorly understood. In the present study, we investigated the serum samples from 20 patients with stage III or IV advanced CRC using data-independent acquisition (DIA)-based proteomics and ultra-performance liquid chromatography coupled to time-of-flight tandem mass spectrometry (UPLC-TOF-MS/MS) metabolomics techniques. Overall, 551 proteins and 719 metabolites were identified. Hierarchical clustering analysis revealed that the serum proteomes of advanced CRC are more diversified than the metabolomes. Ten biochemical pathways associated with cancer cell metabolism were enriched in the detected proteins and metabolites, including glycolysis/gluconeogenesis, biosynthesis of amino acids, glutathione metabolism, and arachidonic acid metabolism, etc. A protein-protein interaction network in advanced CRC serum was constructed with 80 proteins and 21 related metabolites. Correlation analysis revealed conserved roles of lipids and lipid-like molecules in a regulatory network of advanced CRC. Three metabolites (hydroquinone, leucenol and sphingomyelin) and two proteins (coagulation factor XIII A chain and plasma kallikrein) were selected to be potential biomarkers for advanced CRC, which are positively and significantly correlated with CEA and/or CA 19-9. Altogether, the results expanded our understanding of the physiopathology of advanced CRC and discovered novel potential biomarkers for further validation and application to improve the diagnosis and monitoring of advanced CRC.

Identifying Novel Biomarkers Ready for Evaluation in Low-Prevalence Populations for the Early Detection of Lower Gastrointestinal Cancers: A Systematic Review and Meta-Analysis

INTRODUCTION

Lower gastrointestinal (GI) cancers are a major cause of cancer deaths worldwide. Prognosis improves with earlier diagnosis, and non-invasive biomarkers have the potential to aid with early detection. Substantial investment has been made into the development of biomarkers; however, studies are often carried out in specialist settings and few have been evaluated for low-prevalence populations.

METHODS

We aimed to identify novel biomarkers for the detection of lower GI cancers that have the potential to be evaluated for use in primary care. MEDLINE, Embase, Emcare and Web of Science were systematically searched for studies published in English from January 2000 to October 2019. Reference lists of included studies were also assessed. Studies had to report on measures of diagnostic performance for biomarkers (single or in panels) used to detect colorectal or anal cancers. We included all designs and excluded studies with fewer than 50 cases/controls. Data were extracted from published studies on types of biomarkers, populations and outcomes. Narrative synthesis was used, and measures of specificity and sensitivity were meta-analysed where possible.

RESULTS

We identified 142 studies reporting on biomarkers for lower GI cancers, for 24,844 cases and 45,374 controls. A total of 378 unique biomarkers were identified. Heterogeneity of study design, population type and sample source precluded meta-analysis for all markers except methylated septin 9 (mSEPT9) and pyruvate kinase type tumour M2 (TuM2-PK). The estimated sensitivity and specificity of mSEPT9 was 80.6% (95% CI 76.6-84.0%) and 88.0% (95% CI 79.1-93.4%) respectively; TuM2-PK had an estimated sensitivity of 81.6% (95% CI 75.2-86.6%) and specificity of 80.1% (95% CI 76.7-83.0%).

CONCLUSION

Two novel biomarkers (mSEPT9 and TuM2-PK) were identified from the literature with potential for use in lower-prevalence populations. Further research is needed to validate these biomarkers in primary care for screening and assessment of symptomatic patients.

Colorectal cancer screening and diagnosis: omics-based technologies for development of a non-invasive blood-based method

Introduction: Colorectal cancer (CRC) is one of the most important health problems in the Western world. In order to reduce the burden of the disease, two strategies are proposed: screening and prompt detection in symptomatic patients. Although diagnosis and prevention are mainly based on colonoscopy, fecal hemoglobin detection has been widely implemented as a noninvasive strategy. Various studies aiming to discover blood-based biomarkers have recently emerged.Areas covered: The burgeoning omics field provides diverse high-throughput approaches for CRC blood-based biomarker discovery. In this review, we appraise the most robust and commonly used technologies within the fields of genomics, transcriptomics, epigenomics, proteomics, and metabolomics, together with their targeted validation approaches. We summarize the transference process from the discovery phase until clinical translation. Finally, we review the best candidate biomarkers and their potential clinical applicability.Expert opinion: Some available biomarkers are promising, especially in the field of epigenomics: DNA methylation and microRNA. Transference requires the joint collaboration of basic researchers, intellectual property experts, technology transfer officers and clinicians. Blood-based biomarkers will be selected not only based on their diagnostic accuracy and cost but also on their reliability, applicability to clinical analysis laboratories and their acceptance by the population.

Integrating Two-Dimensional Gas and Liquid Chromatography-Mass Spectrometry for Untargeted Colorectal Cancer Metabolomics: A Proof-of-Principle Study

Untargeted metabolomics is expected to lead to a better mechanistic understanding of diseases and thus applications of precision medicine and personalized intervention. To further increase metabolite coverage and achieve high accuracy of metabolite quantification, the present proof-of-principle study was to explore the applicability of integration of two-dimensional gas and liquid chromatography-mass spectrometry (GC × GC-MS and 2DLC-MS) platforms to characterizing circulating polar metabolome extracted from plasma collected from 29 individuals with colorectal cancer in comparison with 29 who remained cancer-free. After adjustment of multiple comparisons, 20 metabolites were found to be up-regulated and 8 metabolites were found to be down-regulated, which pointed to the dysregulation in energy metabolism and protein synthesis. While integrating the GC × GC-MS and 2DLC-MS data can dramatically increase the metabolite coverage, this study had a limitation in analyzing the non-polar metabolites. Given the small sample size, these results need to be validated with a larger sample size and with samples collected prior to diagnostic and treatment. Nevertheless, this proof-of-principle study demonstrates the potential applicability of integration of these advanced analytical platforms to improve discrimination between colorectal cancer cases and controls based on metabolite profiles in future studies.

Profiling of serum metabolites in advanced colon cancer using liquid chromatography-mass spectrometry

Lymph node metastasis remains a key factor that affects the prognosis of patients with colon cancer. The aim of the present study was to identify and evaluate serum metabolites as biomarkers for the detection of tumor lymph node metastasis and the prediction of patient survival. The present study analyzed the metabolites in the serum of patients with advanced colon cancer both with and without lymph node metastasis. Blood samples from 104 patients with stage T3 colon cancer were collected and analyzed using liquid chromatography-mass spectrometry. The metabolites were structurally confirmed with data from the Human Metabolome Database. The association between the serum metabolites and the clinicopathological characteristics and survival time of patients from the present study was analyzed. Overall, 227 different metabolites were identified in the serum of patients with stage T3 colon cancer with or without lymph node metastasis. Furthermore, 17 of these metabolites may potentially distinguish those patients with lymph node metastasis from those patients without. In addition, five factors, including abscisic acid, calcitroic acid and glucosylsphingosine presence in the serum, age and sex, were identified as independent predictors for lymph node metastasis (P<0.05). Furthermore, three factors, including abscisic acid, calcitroic acid and glucosylsphingosine presence in the serum were independent predictors for patient survival (P<0.05). In conclusion, the serum levels of abscisic acid, calcitroic-acid and glucosylsphingosine may be considered as potential biomarkers to predict the occurrence of lymph node metastasis and the survival time of patients with colon cancer.

Research Note: Metabolic changes and physiological responses of broilers in the final stage of growth exposed to different environmental temperatures

There is no information regarding the influence of heat stress (HS) on host metabolic profile. In this study, we investigated the effects of different environmental temperatures on oxidative status, hormone levels, HS indicators, and plasma metabolites in broilers. A total of 1,680 yellow-feather broilers (28 D old) were randomly allotted to 4 groups with 6 replicates. The broilers (29–57 D old) were maintained in thermostatic rooms (20°C, 25°C, 28°C, and 30°C) for 28 consecutive days. The results showed that the plasma cortisol and adrenocorticotropic hormone levels and creatine kinase and lactate dehydrogenase activities gradually increased when the temperature increased from 20°C to 30°C. However, the insulin-like growth factor-І level decreased gradually. Furthermore, heat shock protein 70 expression significantly increased in the liver and breast muscle (P < 0.01). As the temperature increased, the total anti-oxidant capacity in the plasma and liver gradually decreased, whereas the malondialdehyde level increased. The activity of plasma glutathione peroxidase and total superoxide dismutase in the liver showed a similar increasing trend (P < 0.01). In addition, 15 metabolites were identified at higher (P < 0.05) levels, whereas 2 metabolites were identified at lower (P < 0.05) levels in the 30°C treatment group than those in the 25°C treatment group. Most of these potentially diagnostic biomarkers are involved in carbohydrate, amino acid, lipid, or gut microbiome-derived metabolism, indicating that HS affected the metabolic pathways in broilers. Six candidate metabolites (tartronic acid, l-bethreine, tartaric acid, allose, glutaric acid, and neohesperidin) were selected as biomarkers, as they showed high sensitivity, specificity, and accuracy in diagnosing broilers under HS (P < 0.01). In conclusion, in the final stage of growth, we identified 6 plasma differential metabolites as potential biomarkers of HS-induced metabolic disorders in yellow-feathered broilers. This work offers new insights into the metabolic alterations of broilers exposed to HS and provides a new perspective for further study.

Metabolic phenotyping to monitor chronic enteritis canceration

INTRODUCTION

Colorectal cancer (CRC) remains an incurable disease. Previous metabolomic studies show that metabolic signatures in plasma distinguish CRC patients from healthy controls. Chronic enteritis (CE) represents a risk factor for CRC, with a 20 fold greater incidence than in healthy individuals. However, no studies have performed metabolomic profiling to investigate CRC biomarkers in CE.

OBJECTIVE

Our aims were to identify metabolomic signatures in CRC and CE and to search for blood-derived metabolite biomarkers distinguishing CRC from CE, especially early-stage biomarkers.

METHODS

In this case-control study, 612 subjects were prospectively recruited between May 2015 and May 2016, and including 539 CRC patients (stage I, 102 cases; stage II, 259 cases; stage III, 178 cases) and 73 CE patients. Untargeted metabolomics was performed to identify CRC-related metabolic signatures in CE.

RESULTS

Five pathways were significantly enriched based on 153 differential metabolites between CRC and CE. 16 biomarkers were identified for diagnosis of CRC from CE and for guiding CRC staging. The AUC value for CRC diagnosis in the external validation set was 0.85. Good diagnostic performances were also achieved for early-stage CRC (stage I and stage II), with an AUC value of 0.84. The biomarker panel could also stage CRC patients, with an AUC of 0.72 distinguishing stage I from stage II CRC and AUC of 0.74 distinguishing stage II from stage III CRC.

CONCLUSIONS

The identified metabolic biomarkers exhibit promising properties for CRC monitoring in CE patients and are superior to commonly used clinical biomarkers (CEA and CA19-9).

Biomarkers for detecting colorectal cancer non-invasively: DNA, RNA or proteins?

Colorectal cancer (CRC) is a global problem affecting millions of people worldwide. This disease is unique because of its slow progress that makes it preventable and often curable. CRC symptoms usually emerge only at advanced stages of the disease, consequently its early detection can be achieved only through active population screening, which markedly reduces mortality due to this cancer. CRC screening tests that employ non-invasively detectable biomarkers are currently being actively developed and, in most cases, samples of either stool or blood are used. However, alternative biological substances that can be collected non-invasively (colorectal mucus, urine, saliva, exhaled air) have now emerged as new sources of diagnostic biomarkers. The main categories of currently explored CRC biomarkers are: (1) Proteins (comprising widely used haemoglobin); (2) DNA (including mutations and methylation markers); (3) RNA (in particular microRNAs); (4) Low molecular weight metabolites (comprising volatile organic compounds) detectable by metabolomic techniques; and (5) Shifts in gut microbiome composition. Numerous tests for early CRC detection employing such non-invasive biomarkers have been proposed and clinically studied. While some of these studies generated promising early results, very few of the proposed tests have been transformed into clinically validated diagnostic/screening techniques. Such DNA-based tests as Food and Drug Administration-approved multitarget stool test (marketed as Cologuard®) or blood test for methylated septin 9 (marketed as Epi proColon® 2.0 CE) show good diagnostic performance but remain too expensive and technically complex to become effective CRC screening tools. It can be concluded that, despite its deficiencies, the protein (haemoglobin) detection-based faecal immunochemical test (FIT) today presents the most cost-effective option for non-invasive CRC screening. The combination of non-invasive FIT and confirmatory invasive colonoscopy is the current strategy of choice for CRC screening. However, continuing intense research in the area promises the emergence of new superior non-invasive CRC screening tests that will allow the development of improved disease prevention strategies.

Metabolic models predict bacterial passengers in colorectal cancer

BACKGROUND

Colorectal cancer (CRC) is a complex multifactorial disease. Increasing evidence suggests that the microbiome is involved in different stages of CRC initiation and progression. Beyond specific pro-oncogenic mechanisms found in pathogens, metagenomic studies indicate the existence of a microbiome signature, where particular bacterial taxa are enriched in the metagenomes of CRC patients. Here, we investigate to what extent the abundance of bacterial taxa in CRC metagenomes can be explained by the growth advantage resulting from the presence of specific CRC metabolites in the tumor microenvironment.

METHODS

We composed lists of metabolites and bacteria that are enriched on CRC samples by reviewing metabolomics experimental literature and integrating data from metagenomic case-control studies. We computationally evaluated the growth effect of CRC enriched metabolites on over 1500 genome-based metabolic models of human microbiome bacteria. We integrated the metabolomics data and the mechanistic models by using scores that quantify the response of bacterial biomass production to CRC-enriched metabolites and used these scores to rank bacteria as potential CRC passengers.

RESULTS

We found that metabolic networks of bacteria that are significantly enriched in CRC metagenomic samples either depend on metabolites that are more abundant in CRC samples or specifically benefit from these metabolites for biomass production. This suggests that metabolic alterations in the cancer environment are a major component shaping the CRC microbiome.

CONCLUSION

Here, we show with in sillico models that supplementing the intestinal environment with CRC metabolites specifically predicts the outgrowth of CRC-associated bacteria. We thus mechanistically explain why a range of CRC passenger bacteria are associated with CRC, enhancing our understanding of this disease. Our methods are applicable to other microbial communities, since it allows the systematic investigation of how shifts in the microbiome can be explained from changes in the metabolome.

The Translational Status of Cancer Liquid Biopsies

Abstract

Precision oncology aims to tailor clinical decisions specifically to patients with the objective of improving treatment outcomes. This can be achieved by leveraging omics information for accurate molecular characterization of tumors. Tumor tissue biopsies are currently the main source of information for molecular profiling. However, biopsies are invasive and limited in resolving spatiotemporal heterogeneity in tumor tissues. Alternative non-invasive liquid biopsies can exploit patient’s body fluids to access multiple layers of tumor-specific biological information (genomes, epigenomes, transcriptomes, proteomes, metabolomes, circulating tumor cells, and exosomes). Analysis and integration of these large and diverse datasets using statistical and machine learning approaches can yield important insights into tumor biology and lead to discovery of new diagnostic, predictive, and prognostic biomarkers. Translation of these new diagnostic tools into standard clinical practice could transform oncology, as demonstrated by a number of liquid biopsy assays already entering clinical use. In this review, we highlight successes and challenges facing the rapidly evolving field of cancer biomarker research.

Lay Summary

Precision oncology aims to tailor clinical decisions specifically to patients with the objective of improving treatment outcomes. The discovery of biomarkers for precision oncology has been accelerated by high-throughput experimental and computational methods, which can inform fine-grained characterization of tumors for clinical decision-making. Moreover, advances in the liquid biopsy field allow non-invasive sampling of patient’s body fluids with the aim of analyzing circulating biomarkers, obviating the need for invasive tumor tissue biopsies. In this review, we highlight successes and challenges facing the rapidly evolving field of liquid biopsy cancer biomarker research.

Plasma metabolites associated with colorectal cancer: A discovery-replication strategy

Colorectal cancer is known to arise from multiple tumorigenic pathways; however, the underlying mechanisms remain not completely understood. Metabolomics is becoming an increasingly popular tool in assessing biological processes. Previous metabolomics research focusing on colorectal cancer is limited by sample size and did not replicate findings in independent study populations to verify robustness of reported findings. Here, we performed a ultrahigh performance liquid chromatography-quadrupole time-of-flight mass spectrometry (UHPLC-QTOF-MS) screening on EDTA plasma from 268 colorectal cancer patients and 353 controls using independent discovery and replication sets from two European cohorts (ColoCare Study: n = 180 patients/n = 153 controls; the Colorectal Cancer Study of Austria (CORSA) n = 88 patients/n = 200 controls), aiming to identify circulating plasma metabolites associated with colorectal cancer and to improve knowledge regarding colorectal cancer etiology. Multiple logistic regression models were used to test the association between disease state and metabolic features. Statistically significant associated features in the discovery set were taken forward and tested in the replication set to assure robustness of our findings. All models were adjusted for sex, age, BMI and smoking status and corrected for multiple testing using False Discovery Rate. Demographic and clinical data were abstracted from questionnaires and medical records.

Current state and future direction of screening tool for colorectal cancer

As the second-most-common cause of cancer death, colorectal cancer (CRC) has been recognized as one of the biggest health concerns in advanced countries. The 5-year survival rate for patients with early-stage CRC is significantly better than that for patients with CRC detected at a late stage. The primary target for CRC screening and prevention is advanced neoplasia, which includes both CRC itself, as well as benign but histologically advanced adenomas that are at increased risk for progression to malignancy. Prevention of CRC through detection of advanced adenomas is important. It is, therefore, necessary to develop more efficient detection methods to enable earlier detection and therefore better prognosis. Although a number of CRC diagnostic methods are currently used for early detection, including stool-based tests, traditional colonoscopy, etc., they have not shown optimal results due to several limitations. Hence, development of more reliable screening methods is required in order to detect the disease at an early stage. New screening tools also need to be able to accurately diagnose CRC and advanced adenoma, help guide treatment, and predict the prognosis along with being relatively simple and non-invasive. As part of such efforts, many proposals for the early detection of colorectal neoplasms have been introduced. For example, metabolomics, referring to the scientific study of the metabolism of living organisms, has been shown to be a possible approach for discovering CRC-related biomarkers. In addition, a growing number of high-performance screening methodologies could facilitate biomarker identification. In the present, evidence-based review, the authors summarize the current state as recognized by the recent guideline recommendation from the American Cancer Society, US Preventive Services Task Force and the United States Multi-Society Task Force and discuss future direction of screening tools for colorectal cancer. Further, we highlight the most interesting publications on new screening tools, like molecular biomarkers and metabolomics, and discuss these in detail.

High-Throughput Metabolomics Based on Direct Mass Spectrometry Analysis in Biomedical Research

Metabolomics based on direct mass spectrometry analysis shows a great potential in biomedical research because of its high-throughput screening capability and wide metabolome coverage. This chapter contains detailed protocols to perform comprehensive metabolomic fingerprinting of multiple biological samples (serum, plasma, urine, brain, liver, spleen, thymus) by using complementary analytical platforms. The most important issues to be considered are discussed, including sample treatment, metabolomic analysis, raw data preprocessing, and data analysis.

Reduced Plasma Levels of Very-Long-Chain Dicarboxylic Acid 28:4 in Italian and Brazilian Colorectal Cancer Patient Cohorts

BACKGROUND

There are currently no blood-based biomarkers for early diagnosis of colorectal cancer. Previous research has suggested that very-long-chain dicarboxylic acid (VLCDCA) 28:4 might be such a biomarker.

METHODS

Using high-resolution mass spectrometry, we analyzed VLCDCA 28:4 in the plasma of colorectal cancer patients in Italian [n = 62] and Brazilian [n = 52] cohorts. Additionally, we investigated individuals diagnosed with familial adenomatous polyposis (FAP; n = 27), one of the most important clinical forms of inherited susceptibility to colorectal cancer. Results: Decrements in plasma levels of VLCDCA 28:4 were monitored in colorectal cancer patients. These decreases were independent of the stage of tumor development and the individual's age. However, no decrements in VLCDCA 28:4 were monitored in FAP patients.

CONCLUSIONS

The plasma levels of VLCDCA 28:4 represent a potential biomarker of sporadic colorectal cancer. In addition, it is possible that resupply of this anti-inflammatory lipid may represent a new therapeutic strategy for CRC and inflammatory disorders.

Endogenous Anti-Inflammatory Very-Long-Chain Dicarboxylic Acids: Potential Chemopreventive Lipids

In a paradigm shift, cancer research efforts are being dedicated to the discovery of chemopreventive agents. The goal of this approach is to delay or prevent the progression of augmented cell division to established cancer. Research has focused on dietary supplements, drugs, and endogenous lipids that possess anti-inflammatory properties. We undertook a lipidomics analysis of potential endogenous anti-inflammatory/anti-proliferative lipids in human plasma. We performed high-resolution mass spectrometric lipidomics analyses of plasma samples from controls and patients with colorectal, kidney, pancreatic, glioblastoma, and breast cancers. We present evidence that endogenous very-long-chain dicarboxylic acids (VLCDCA) are anti-inflammatory lipids that possess chemopreventative properties. In a family of VLCDCAs, we characterized VLCDCA 28:4, which is decreased in the plasma of patients with colorectal, kidney, and pancreatic cancers. The structure of this biomarker was validated by derivatization strategies, synthesis of the analytical standard, and tandem mass spectrometry. Our data suggest that VLCDCA 28:4 may be a useful blood biomarker for a number of cancers and that resupplying this lipid, via a prodrug for example, may offer a new anti-inflammatory therapeutic strategy for delaying or preventing the progression of cancer and other inflammatory diseases.

Untargeted lipidomic features associated with colorectal cancer in a prospective cohort

BACKGROUND

Epidemiologists are beginning to employ metabolomics and lipidomics with archived blood from incident cases and controls to discover causes of cancer. Although several such studies have focused on colorectal cancer (CRC), they all followed targeted or semi-targeted designs that limited their ability to find discriminating molecules and pathways related to the causes of CRC.

METHODS

Using an untargeted design, we measured lipophilic metabolites in prediagnostic serum from 66 CRC patients and 66 matched controls from the European Prospective Investigation into Cancer and Nutrition (Turin, Italy). Samples were analyzed by liquid chromatography-high-resolution mass spectrometry (LC-MS), resulting in 8690 features for statistical analysis.

RESULTS

Rather than the usual multiple-hypothesis-testing approach, we based variable selection on an ensemble of regression methods, which found nine features to be associated with case-control status. We then regressed each selected feature on time-to-diagnosis to determine whether the feature was likely to be either a potentially causal biomarker or a reactive product of disease progression (reverse causality).

CONCLUSIONS

Of the nine selected LC-MS features, four appear to be involved in CRC etiology and merit further investigation in prospective studies of CRC. Four other features appear to be related to progression of the disease (reverse causality), and may represent biomarkers of value for early detection of CRC.

Alteration of Serum Free Fatty Acids are Indicators for Progression of Pre-leukaemia Diseases to Leukaemia

Acute Leukaemia (AL) is a neoplasm of WBCs (white blood cells). Being an important class of metabolites, alteration in free fatty acids (FFAs) levels play a key role in cancer development and progression. As they involve in cell signaling, maintain membrane integrity, regulate homeostasis and effect cell and tissue functions. Considering this fact, a comprehensive analysis of FFAs was conducted to monitor their alteration in AL, pre-leukaemic diseases and healthy control. Fifteen FFAs were analyzed in 179 serum samples of myelodysplastic syndrome (MDS), aplastic anemia (APA), acute lymphoblastic leukaemia (ALL), acute myeloid leukaemia (AML) and healthy control using gas chromatography-multiple reaction monitoring-mass spectrometry (GC-MRM-MS). A multivariate statistical method of random forest (RF) was employed for chemometric analysis. Serum level of two FFAs including C18:0 and C14:0 were found discriminative among all five groups, and between ALL and AML, respectively. Moreover, C14:0 was identified as differentiated FFAs for systematic progression of pre-leukaemic conditions towards AML. C16:0 came as discriminated FFAs between APA and MDS/AML. Over all it was identified that FFAs profile not only become altered in leukaemia but also in pre-leukaemic diseases.

Targeted UPLC-MS Metabolic Analysis of Human Faeces Reveals Novel Low-Invasive Candidate Markers for Colorectal Cancer

Low invasive tests with high sensitivity for colorectal cancer and advanced precancerous lesions will increase adherence rates, and improve clinical outcomes. We have performed an ultra-performance liquid chromatography/time-of-flight mass spectrometry (UPLC-(TOF) MS)-based metabolomics study to identify faecal biomarkers for the detection of patients with advanced neoplasia. A cohort of 80 patients with advanced neoplasia (40 advanced adenomas and 40 colorectal cancers) and 49 healthy subjects were analysed in the study. We evaluated the faecal levels of 105 metabolites including glycerolipids, glycerophospholipids, sterol lipids and sphingolipids. We found 18 metabolites that were significantly altered in patients with advanced neoplasia compared to controls. The combinations of seven metabolites including ChoE(18:1), ChoE(18:2), ChoE(20:4), PE(16:0/18:1), SM(d18:1/23:0), SM(42:3) and TG(54:1), discriminated advanced neoplasia patients from healthy controls. These seven metabolites were employed to construct a predictive model that provides an area under the curve (AUC) median value of 0.821. The inclusion of faecal haemoglobin concentration in the metabolomics signature improved the predictive model to an AUC of 0.885. In silico gene expression analysis of tumour tissue supports our results and puts the differentially expressed metabolites into biological context, showing that glycerolipids and sphingolipids metabolism and GPI-anchor biosynthesis pathways may play a role in tumour progression.

Metabolomics Biomarkers for Detection of Colorectal Neoplasms: A Systematic Review

BACKGROUND

Several approaches have been suggested to be useful in the early detection of colorectal neoplasms. Since metabolites are closely related to the phenotype and are available from different human bio-fluids, metabolomics are candidates for non-invasive early detection of colorectal neoplasms.

OBJECTIVES

We aimed to summarize current knowledge on performance characteristics of metabolomics biomarkers that are potentially applicable in a screening setting for the early detection of colorectal neoplasms.

DESIGN

We conducted a systematic literature search in PubMed and Web of Science and searched for biomarkers for the early detection of colorectal neoplasms in easy-to-collect human bio-fluids. Information on study design and performance characteristics for diagnostic accuracy was extracted.

RESULTS

Finally, we included 41 studies in our analysis investigating biomarkers in different bio-fluids (blood, urine, and feces). Although single metabolites mostly had limited ability to distinguish people with and without colorectal neoplasms, promising results were reported for metabolite panels, especially amino acid panels in blood samples, as well as nucleosides in urine samples in several studies. However, validation of the results is limited.

CONCLUSIONS

Panels of metabolites consisting of amino acids in blood and nucleosides in urinary samples might be useful biomarkers for early detection of advanced colorectal neoplasms. However, to make metabolomic biomarkers clinically applicable, future research in larger studies and external validation of the results is required.

Predicting the pathological response to neoadjuvant chemoradiation using untargeted metabolomics in locally advanced rectal cancer

PURPOSE

The present study aimed to identify a panel of potential metabolite biomarkers to predict tumor response to neoadjuvant chemo-radiation therapy (NCRT) in locally advanced rectal cancer (LARC).

EXPERIMENTAL DESIGN

Liquid chromatography-mass spectrometry (LC-MS)-based untargeted metabolomics was used to profile human serum samples (n = 106) from LARC patients treated with NCRT. The samples were collected from Fudan University Shanghai Cancer Center (FUSCC) from July 2014 to January 2016. Statistical methods, such as partial least squares (PLS) and Wilcoxon rank-sum test, were used to identify discriminative metabolites between NCRT-sensitive and NCRT-resistant patients according to their tumor regression grade (TRG). This trial is registered with Clinical Trials.gov, number NCT03149978.

RESULTS

A panel of metabolites was selected as potential predictive biomarkers of pathological response to NCRT. A total of 4810 metabolic peaks were detected, and 57 significantly dysregulated peaks were identified. These 57 metabolic peaks were used to differentiate patients using PLS in a dataset containing NCRT-sensitive (n = 56) and NCRT-resistant (n = 49) patients. The combination of 57 metabolic peaks had AUC values of 0.88, 0.81 and 0.84 in the prediction models using PLS, random forest, and support vector machine, respectively, suggesting that metabolomics has the potential ability to predict responses to NCRT. Furthermore, 15 metabolite biomarkers were identified and used to construct a logistic regression model and explore dysregulated metabolic pathways using untargeted metabolic profiling and data mining approaches.

CONCLUSIONS

A panel of metabolites has been identified to facilitate the prediction of tumor response to NCRT in LARC, which is promising for the generation of personalized treatment strategies for LARC patients.

Metabolomics for biomarker discovery in the diagnosis, prognosis, survival and recurrence of colorectal cancer: a systematic review

Colorectal cancer (CRC) remains an incurable disease. There are no effective noninvasive techniques that have achieved colorectal cancer (CRC) diagnosis, prognosis, survival and recurrence in clinic. To investigate colorectal cancer metabolism, we perform an electronic literature search, from 1998 to January 2016, for studies evaluating the metabolomic profile of patients with CRC regarding the diagnosis, recurrence, prognosis/survival, and systematically review the twenty-three literatures included. QUADOMICS tool was used to assess the quality of them. We highlighted the metabolism perturbations based on metabolites and pathway. Metabolites related to cellular respiration, carbohydrate, lipid, protein and nucleotide metabolism were significantly altered in CRC. Altered metabolites were also related to prognosis, survival and recurrence of CRC. This review could represent the most comprehensive information and summary about CRC metabolism to date. It certificates that metabolomics had great potential on both discovering clinical biomarkers and elucidating previously unknown mechanisms of CRC pathogenesis.

A quantitative multimodal metabolomic assay for colorectal cancer

Background

Early diagnosis of colorectal cancer (CRC) simplifies treatment and improves treatment outcomes. We previously described a diagnostic metabolomic biomarker derived from semi-quantitative gas chromatography-mass spectrometry. Our objective was to determine whether a quantitative assay of additional metabolomic features, including parts of the lipidome could enhance diagnostic power; and whether there was an advantage to deriving a combined diagnostic signature with a broader metabolomic representation.

Methods

The well-characterized Biocrates P150 kit was used to quantify 163 metabolites in patients with CRC (N = 62), adenoma (N = 31), and age- and gender-matched disease-free controls (N = 81). Metabolites included in the analysis included phosphatidylcholines, sphingomyelins, acylcarnitines, and amino acids. Using a training set of 32 CRC and 21 disease-free controls, a multivariate metabolomic orthogonal partial least squares (OPLS) classifier was developed. An independent set of 28 CRC and 20 matched healthy controls was used for validation. Features characterizing 31 colorectal adenomas from their healthy matched controls were also explored, and a multivariate OPLS classifier for colorectal adenoma could be proposed.

Results

The metabolomic profile that distinguished CRC from controls consisted of 48 metabolites (R²Y = 0.83, Q²Y = 0.75, CV-ANOVA p-value < 0.00001). In this quantitative assay, the coefficient of variance for each metabolite was <10%, and this dramatically enhanced the separation of these groups. Independent validation resulted in AUROC of 0.98 (95% CI, 0.93–1.00) and sensitivity and specificity of 93% and 95%. Similarly, we were able to distinguish adenoma from controls (R²Y = 0.30, Q²Y = 0.20, CV-ANOVA p-value = 0.01; internal AUROC = 0.82 (95% CI, 0.72–0.93)). When combined with the previously generated GC-MS signatures for CRC and adenoma, the candidate biomarker performance improved slightly.

Conclusion

The diagnostic power for metabolomic tests for colorectal neoplasia can be improved by utilizing a multimodal approach and combining metabolites from diverse chemical classes. In addition, quantification of metabolites enhances separation of disease-specific metabolomic profiles. Our future efforts will be focused on developing a quantitative assay for the metabolites comprising the optimal diagnostic biomarker.

Electronic supplementary material

The online version of this article (10.1186/s12885-017-3923-z) contains supplementary material, which is available to authorized users.

Colorectal Cancer Detection Using Targeted LC-MS Metabolic Profiling

Colorectal cancer (CRC) is one of the most commonly diagnosed malignancies and causes of cancer death. While the mortality rates from CRC have steadily declined, 50,000 individuals in the USA (and many times this number worldwide) still succumb to this illness every year. Early detection of CRC is the most critical need for improving 5-year survival and cure rates. Currently available CRC diagnostic techniques often miss early stage disease such that only 40% of newly diagnosed CRC patients are treated for local disease, Therefore, development of new screening methods that are highly sensitive, specific, noninvasive and easily accessible are critically desired for the early diagnosis and significant reduction in death rate from CRC. In this chapter we describe a targeted LC-MS based metabolic profiling approach used for the discovery of CRC metabolite biomarker candidates, based on highly reproducible hydrophilic interaction liquid chromatography coupled to triple-quadrupole mass spectrometry (HILIC-LC-QQQ-MS). A partial least squares-discriminant analysis (PLS-DA) model was able to differentiate CRC patients from both healthy controls and polyp patients, as well as to distinguish CRC patients based on the cancer stage.

Altered metabolite levels and correlations in patients with colorectal cancer and polyps detected using seemingly unrelated regression analysis

Introduction

Metabolomics technologies enable the identification of putative biomarkers for numerous diseases; however, the influence of confounding factors on metabolite levels poses a major challenge in moving forward with such metabolites for pre-clinical or clinical applications.

Objectives

To address this challenge, we analyzed metabolomics data from a colorectal cancer (CRC) study, and used seemingly unrelated regression (SUR) to account for the effects of confounding factors including gender, BMI, age, alcohol use, and smoking.

Methods

A SUR model based on 113 serum metabolites quantified using targeted mass spectrometry, identified 20 metabolites that differentiated CRC patients (n = 36), patients with polyp (n = 39), and healthy subjects (n = 83). Models built using different groups of biologically related metabolites achieved improved differentiation and were significant for 26 out of 29 groups. Furthermore, the networks of correlated metabolites constructed for all groups of metabolites using the ParCorA algorithm, before or after application of the SUR model, showed significant alterations for CRC and polyp patients relative to healthy controls.

Results

The results showed that demographic covariates, such as gender, BMI, BMI2, and smoking status, exhibit significant confounding effects on metabolite levels, which can be modeled effectively.

Conclusion

These results not only provide new insights into addressing the major issue of confounding effects in metabolomics analysis, but also shed light on issues related to establishing reliable biomarkers and the biological connections between them in a complex disease.

Global and targeted serum metabolic profiling of colorectal cancer progression

BACKGROUND

Patients with colorectal adenoma polyps (PLPs) are at higher risk for developing colorectal cancer (CRC). However, the development of improved and robust biomarkers to enable the screening, surveillance, and early detection of PLPs and CRC continues to be a challenge. The aim of this study was to identify biomarkers of progression to CRC through metabolomic profiling of human serum samples with a multistage approach.

METHODS

Metabolomic profiling was conducted with the Metabolon platform for 30 CRC patients, 30 PLP patients, and 30 control subjects, and this was followed by the targeted validation of the top metabolites in an additional set of 50 CRC patients, 50 PLP patients, and 50 controls with liquid chromatography-tandem mass spectrometry. Unconditional multivariate logistic regression models, adjusted for covariates, were used to evaluate associations with PLP and CRC risk.

RESULTS

For the discovery phase, 404 serum metabolites were detected, with 50 metabolites showing differential levels between CRC patients, PLP patients, and controls (P for trend < .05). After validation, the 3 top metabolites (xanthine, hypoxanthine, and d-mannose) were validated: lower levels of xanthine and hypoxanthine and higher levels of d-mannose were found in PLP and CRC cases versus controls. A further exploratory analysis of metabolic pathways revealed key roles for the urea cycle and caffeine metabolism associated with PLP and CRC risk. In addition, a joint effect of the top metabolites with smoking and a significant interaction with the body mass index were observed. An analysis of the ratio of hypoxanthine levels to xanthine levels indicated an association with CRC progression.

CONCLUSIONS

These results suggest the potential utility of circulating metabolites as novel biomarkers for the early detection of CRC. Cancer 2017;123:4066-74. © 2017 American Cancer Society.

Investigations in the possibility of early detection of colorectal cancer by gas chromatography/triple-quadrupole mass spectrometry

In developed countries, the number of patients with colorectal cancer has been increasing, and colorectal cancer is one of the most common causes of cancer death. To improve the quality of life of colorectal cancer patients, it is necessary to establish novel screening methods that would allow early detection of colorectal cancer. We performed metabolome analysis of a plasma sample set from 282 stage 0/I/II colorectal cancer patients and 291 healthy volunteers using gas chromatography/triple-quadrupole mass spectrometry in an attempt to identify metabolite biomarkers of stage 0/I/II colorectal cancer. The colorectal cancer patients included patients with stage 0 (N=79), I (N=80), and II (N=123) in whom invasion and metastasis were absent. Our analytical system detected 64 metabolites in the plasma samples, and the levels of 29 metabolites differed significantly (Bonferroni-corrected p=0.000781) between the patients and healthy volunteers. Based on these results, a multiple logistic regression analysis of various metabolite biomarkers was carried out, and a stage 0/I/II colorectal cancer prediction model was established. The area under the curve, sensitivity, and specificity values of this model for detecting stage 0/I/II colorectal cancer were 0.996, 99.3%, and 93.8%, respectively. The model's sensitivity and specificity values for each disease stage were >90%, and surprisingly, its sensitivity for stage 0, specificity for stage 0, and sensitivity for stage II disease were all 100%. Our predictive model can aid early detection of colorectal cancer and has potential as a novel screening test for cases of colorectal cancer that do not involve lymph node or distant metastasis.

Downregulation of serum metabolite GTA-446 as a novel potential marker for early detection of colorectal cancer

BACKGROUND

We previously reported that GTA-446 may be a useful biomarker for early detection of colorectal cancer. In the present study, we confirmed the clinical feasibility of GTA-446 as a screening tool for colorectal cancer with a novel measurement system developed for clinical use. We also improved sensitivity by analysing GTA-446 levels according to gender.

METHODS

Serum samples were collected from 225 colorectal cancer patients and 916 healthy volunteers to measure GTA-446 levels by flow injection analysis-mass spectrometry.

RESULTS

GTA-446 levels were downregulated in colorectal cancer patients compared with the healthy volunteers, and in females compared with the males in both groups. Receiver operating characteristic curve analysis revealed an optimal cut-off of 2.72 μmol l^-1 in males and 1.87 μmol l^-1 in females, with a large area under the curve of 0.89-0.93. The sensitivity and specificity were 90.4% and 84.9% for males, 85.2% and 80.5% for females, and 83.3% and 84.8% for all subjects, respectively.

CONCLUSIONS

GTA-446 is a clinically relevant biomarker for colorectal cancer with high sensitivity when analysed by gender. Thus, GTA-446 is a promising tool for primary colorectal cancer screening to identify populations at a higher risk of colorectal cancer, with an emphasis on early detection.

Identification of differential metabolic characteristics between tumor and normal tissue from colorectal cancer patients by gas chromatography-mass spectrometry

Colorectal cancer (CRC) is one of the most common human malignancies and encompasses cancers of the colon and rectum. Although the gold-standard colonoscopy screening method is effective in detecting CRC, this method is invasive and can result in severe complications for patients. The purpose of this study was to determine differences in metabolites between CRC and matched adjacent nontumor tissues from CRC patients, to identify potential biomarkers that may be informative and developed screening methods. Metabolomic analysis was performed on clinically localized CRC tissue and matched adjacent nontumor tissue from 20 CRC patients. Unsupervised analysis, supervised analysis, univariate analysis and pathway analysis were used to identify potential metabolic biomarkers of CRC. The levels of 25 metabolites in CRC tissues were significantly altered compared with the matched adjacent nontumor tissues. Four metabolites (lactic acid, alanine, phosphate and aspartic acid) demonstrated good area under the curve of receiver-operator characteristic with acceptable sensitivities and specificities, indicating their potential as important biomarkers for CRC. Alterations of amino acid metabolism and enhanced glycolysis may be major factors in the development and progression of CRC. Lactic acid, alanine, phosphate, and aspartic acid could be effective diagnostic indicators for CRC.

Metabolomics for the masses: The future of metabolomics in a personalized world

Current clinical practices focus on a small number of biochemical directly related to the pathophysiology with patients and thus only describe a very limited metabolome of a patient and fail to consider the interations of these small molecules. This lack of extended information may prevent clinicians from making the best possible therapeutic interventions in sufficient time to improve patient care. Various post-genomics '('omic)' approaches have been used for therapeutic interventions previously. Metabolomics now a well-established'omics approach, has been widely adopted as a novel approach for biomarker discovery and in tandem with genomics (especially SNPs and GWAS) has the potential for providing systemic understanding of the underlying causes of pathology. In this review, we discuss the relevance of metabolomics approaches in clinical sciences and its potential for biomarker discovery which may help guide clinical interventions. Although a powerful and potentially high throughput approach for biomarker discovery at the molecular level, true translation of metabolomics into clinics is an extremely slow process. Quicker adaptation of biomarkers discovered using metabolomics can be possible with novel portable and wearable technologies aided by clever data mining, as well as deep learning and artificial intelligence; we shall also discuss this with an eye to the future of precision medicine where metabolomics can be delivered to the masses.

Direct infusion mass spectrometry for metabolomic phenotyping of diseases

Metabolomics based on direct mass spectrometry (MS) analysis, either by direct infusion or flow injection of crude sample extracts, shows a great potential for metabolic fingerprinting because of its high-throughput screening capability, wide metabolite coverage and reduced time of analysis. Considering that numerous metabolic pathways are significantly perturbed during the initiation and progression of diseases, these metabolomic tools can be used to get a deeper understanding about disease pathogenesis and discover potential biomarkers for early diagnosis. In this work, we describe the most common metabolomic platforms used in biomedical research, with special focus on strategies based on direct MS analysis. Then, a comprehensive review on the application of direct MS fingerprinting in clinical issues is provided.

Technological advances in current metabolomics and its application in tradition Chinese medicine

During the last few years, many metabolomics technologies have been established in biomedical research for analyzing the changes of metabolite levels.