Metabotyping of human colorectal cancer using two-dimensional gas chromatography mass spectrometry

Surface-enhanced Raman database of 24 metabolites: Stable measurement of spectra, extraction and analysis of the main features

Surface-enhanced Raman spectroscopy (SERS) has been used in Raman-based metabolomics to provide abundant molecular fingerprint information in situ with extremely high sensitivity, without damaging the sample. However, poor reproducibility, caused by the randomness of the adsorption sites, and the short-range effect of SERS have hindered the development of SERS in metabolomics, resulting in very few SERS reference databases for small-molecule metabolites. In this work, our previously proposed large laser spot-swift mapping SERS method was adopted for the measurement of 24 commercially available metabolite standards, to provide reproducible and reliable references for Raman-based metabolomics study. Among these 24 metabolites, 22 contained no Raman data in PubChem. Other than the SERS spectra data, we extracted and explained the molecular vibration information of these metabolites, and combined with the density functional theory (DFT) calculations, we provided a new possibility for the fast Raman recognition of small-molecule metabolites. Accordingly, a large laser spot-swift mapping SERS database of metabolites in human serum was initially established, which contained not only the original spectral data but also other detailed feature information regarding the Raman peaks. With continuous accumulation, this database could play a promising role in Raman-based metabolomics and other Raman-related research.

Canine detection of chronic wasting disease (CWD) in laboratory and field settings

Chronic wasting disease (CWD) is a fatal transmissible spongiform encephalopathy that affects both free-ranging and farmed cervid species, including mule deer, white-tailed deer, and elk (Odocoileus hemionus, Odocoileus virginianus, and Cervus canadensis). Due to the long incubation period and variability of clinical signs, CWD can expand and spread to new areas before they reach diagnostically detectable levels. Antemortem testing methods currently available can be difficult to obtain and to be applied to the large numbers required for adequate surveillance. However, key volatile biomarkers could be harnessed for non-invasive antemortem surveillance. Detection dogs are the most effective tool currently available for volatile detection; dogs can effectively complete wildlife surveys at rates surpassing that of humans. This study is the first to demonstrate that trained detection dogs can be used as an antemortem test for CWD. First, we trained three dogs to differentiate between CWD-positive and CWD-negative white-tailed deer faeces in a laboratory setting. Dogs spent significantly more time at the positive sample than the negative samples, suggesting that they differentiated between the positive and negative volatile signatures. We then trained the same dogs to search for CWD-positive faecal samples in a more naturalistic field setting. In the field, dogs found 8/11 CWD-positive samples and had an average false detection rate of 13%. These results suggest that dogs can be trained to differentiate CWD-positive faeces from CWD-negative faeces in both laboratory and field settings. Future studies will compare canine accuracy to other antemortem methods, as well as improved canine training methods.

Correlations for untargeted GC × GC-HRTOF-MS metabolomics of colorectal cancer

INTRODUCTION

Modern comprehensive instrumentations provide an unprecedented coverage of complex matrices in the form of high-dimensional, information rich data sets.

OBJECTIVES

In addition to the usual biomarker research that focuses on the detection of the studied condition, we aimed to define a proper strategy to conduct a correlation analysis on an untargeted colorectal cancer case study with a data set of 102 variables corresponding to metabolites obtained from serum samples analyzed with comprehensive two-dimensional gas chromatography coupled to high-resolution time-of-flight mass spectrometry (GC × GC-HRTOF-MS). Indeed, the strength of association existing between the metabolites contains potentially valuable information about the molecular mechanisms involved and the underlying metabolic network associated to a global perturbation, at no additional analytical effort.

METHODS

Following Anscombe's quartet, we took particular attention to four main aspects. First, the presence of non-linear relationships through the comparison of parametric and non-parametric correlation coefficients: Pearson's r, Spearman's rho, Kendall's tau and Goodman-Kruskal's gamma. Second, the visual control of the detected associations through scatterplots and their associated regressions and angles. Third, the effect and handling of atypical samples and values. Fourth, the role of the precision of the data on the attribution of the ranks through the presence of ties.

RESULTS

Kendall's tau was found the method of choice for the data set at hand. Its application highlighted 17 correlations significantly altered in the active state of colorectal cancer (CRC) in comparison to matched healthy controls (HC), from which 10 were specific to this state in comparison to the remission one (R-CRC) investigated on distinct patients. 15 metabolites involved in the correlations of interest, on the 25 unique ones obtained, were annotated (Metabolomics Standards Initiative level 2).

CONCLUSIONS

The metabolites highlighted could be used to better understand the pathology. The systematic investigation of the methodological aspects that we expose allows to implement correlation analysis to various fields and many specific cases.

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.

Dietary Energy Intake and Presence of Aberrant Crypt Foci Are Associated with Phospholipid, Purine, and Taurine Metabolite Abundances in C57BL/6N Mouse Colon

SCOPE

Colon metabolomes associated with high-fat (H) versus energy-restricted (E) diets in early colorectal cancer (CRC) models have never been directly compared. The objectives of this study are to elucidate metabolites associated with diet, aberrant crypt foci (ACF), and diet:ACF interaction, using a lifetime murine model.

METHODS AND RESULTS

Three-week-old mice consumed control (C), E, or H initiation diets for 18 weeks. ACF formation is initiated weeks 16-21 with azoxymethane injections, followed by progression diet crossover (to C, E, or H) through week 60. Colon extracts are analyzed using ultra-high-performance liquid chromatography-high resolution mass spectrometry (UHPLC-HRMS). Metabolites associated with diet, ACF, or diet:ACF are determined using regression models (FDR-adjusted p-value <0.05). No metabolites are significantly associated with initiation diets, but concentrations of acylcarnitines and phospholipids are associated with C, E, and H progression diets. Purines, taurine, and phospholipids are associated with ACF presence. No significant associations between metabolites and diet:ACF interaction are observed.

CONCLUSIONS

These results suggest that recent, rather than early-life, diet is more closely associated with the colon metabolome, particularly lipid metabolism. Results from this study also provide candidate biomarkers of early CRC development and provide support for the importance of early diet on influencing pre-CRC risk.

Canine discrimination of ovarian cancer through volatile organic compounds

Ovarian cancer has a high mortality rate due to its unclear symptomology and the lack of precise early detection tools. If detected in the first stage, over 90% of patients reach remission. As such, developing a reliable method of early detection is crucial in reducing the mortality rate of the disease. One potential method would be to identify specific biomarkers that are unique to ovarian cancer, which could be detected using a blood test. While this can be done using gas chromatography - mass spectrometry (GC-MS), identifying these biomarkers is an enormous task. One way to expedite the process is to utilize trained scent detection canines. In this study, dogs who were previously trained to respond to positive blood samples from ovarian cancer patients were then tested on their ability to recognize samples prepared by micro-preparative gas chromatography (MP-GC) techniques. MP-GC employed a gradient-cooled glass tube connected to the GC outlet to collect GC eluents containing the plasma-derived volatiles in positive blood samples. These post-column fractions were collected at the exit of the GC according to their eluent times (i.e., 0-15 min, 15-25 min and 25-35 min or 0-35 min) and these full or fractional collections were presented to the trained dogs to judge their responses. Dogs' time spent investigating the odor was used as an indication of odor recognition and was significantly longer on the early (0-15 min) and middle (15-25 min) fractions of the ovarian cancer than the late (25-35 min) fraction of plasma odorants or either the negative fractions or distractors odorants. These findings suggest that characteristic odor biomarkers of ovarian cancer for dogs may exist in the relatively small and more volatile compounds. Additionally, variation between dogs suggests that there may be a number of different biomarkers that can be used to identify ovarian cancer.

Surgical Treatment for Colorectal Cancer Partially Restores Gut Microbiome and Metabolome Traits

The gut microbiome and metabolites are associated with CRC progression and carcinogenesis. Postoperative CRC patients are reported to be at an increased CRC risk; however, how gut microbiome and metabolites are related to CRC risk in postoperative patients remains only partially understood.

Comprehensive two-dimensional gas chromatography with mass spectrometry: an advanced bioanalytical technique for clinical metabolomics studies

This review highlights the current state of knowledge in the development of GC × GC-MS for the analysis of clinical metabolites. Selected applications are described as well as our perspectives on current challenges and potential future directions.

Use of plasma-free amino acids as biomarkers for detecting and predicting disease risk

This paper reviews developments regarding the use of plasma-free amino acid (PFAA) profiles as biomarkers for detecting and predicting disease risk. This work was initiated and first published in 2006 and was subsequently developed by Ajinomoto Co., Inc. After commercialization in 2011, PFAA-based tests were adopted in over 1500 clinics and hospitals in Japan, and numerous clinician-led studies have been performed to validate these tests. Evidence is accumulating that PFAA profiles can be used for diabetes prediction and evaluation of frailty; in particular, decreased plasma essential amino acids could contribute to the pathophysiology of severe frailty. Integration of PFAA evaluation as a biomarker and effective essential amino acid supplementation, which improves physical and mental functions in the elderly, could facilitate the development of precision nutrition, including personalized solutions. This present review provides the background for the technology as well as more recent clinical findings, and offers future possibilities regarding the implementation of precision nutrition.

Metabolomics of primary cutaneous melanoma and matched adjacent extratumoral microenvironment

BACKGROUND

Melanoma causes the vast majority of deaths attributable to skin cancer, largely due to its propensity for metastasis. To date, few studies have examined molecular changes between primary cutaneous melanoma and adjacent putatively normal skin. To broaden temporal inferences related to initiation of disease, we performed a metabolomics investigation of primary melanoma and matched extratumoral microenvironment (EM) tissues; and, to make inferences about progressive disease, we also compared unmatched metastatic melanoma tissues to EM tissues.

METHODS

Ultra-high performance liquid chromatography-mass spectrometry-based metabolic profiling was performed on frozen human tissues.

RESULTS

We observed 824 metabolites as differentially abundant among 33 matched tissue samples, and 1,118 metabolites as differentially abundant between metastatic melanoma (n = 46) and EM (n = 34) after false discovery rate (FDR) adjustment (p<0.01). No significant differences in metabolite abundances were noted comparing primary and metastatic melanoma tissues.

CONCLUSIONS

Overall, pathway-based results significantly distinguished melanoma tissues from EM in the metabolism of: ascorbate and aldarate, propanoate, tryptophan, histidine, and pyrimidine. Within pathways, the majority of individual metabolite abundances observed in comparisons of primary melanoma vs. EM and metastatic melanoma vs. EM were directionally consistent. This observed concordance suggests most identified compounds are implicated in the initiation or maintenance of melanoma.

Profiling of polar urine metabolite extracts from Chinese colorectal cancer patients to screen for potential diagnostic and adverse-effect biomarkers

Background: Metabolomics has demonstrated its potential in the early diagnosis, drug safety evaluation and personalized toxicology research of various cancers. Objectives: We aim to screen for potential diagnostic and capecitabine-related adverse effect (CRAE) biomarkers from urinary endogenous metabolites in Chinese colorectal cancer (CRC) patients. Methods: The metabolic profiles of 139 CRC patients and 50 non-neoplastic controls were analyzed using ultra-high-performance liquid chromatography combined with quadrupole time-of-flight mass spectrometry. Results: There were 41 metabolites identified between the CRC patients and the non-neoplastic controls, and 19 metabolites were identified between CRC patients with and without CRAE. Based on these identified metabolites, bioinformatic analysis and prediction model construction were completed. Most of these differential metabolites have important roles in cell proliferation and differentiation and the immune system. Based on binary logistic regression, a CRC prediction model, composed of 3-methylhistidine, N-heptanoylglycine, N1,N12-diacetylspermine and hippurate, was established, with an area under curve (AUC) of 0.980 (95% CI: 0.953-1.000; sensitivity: 94.3%; specificity: 92.0%) in the training set, and an AUC of 0.968 (95% CI: 0.933-1.000; sensitivity: 89.9%; specificity: 92.0%) in the testing set. In addition, methionine and 4-pyridoxic acid can be combined to predict hand foot syndrome, with an AUC of 0.884; ubiquinone-1 and 4-pyridoxic acid can be combined to predict anemia, with an AUC of 0.889; and 5-acetamidovalerate and 3,4-methylenesebacic acid can be combined to predict neutropenia, with an AUC of 0.882. Conclusion: The profiling of urine polar metabolites has great potential in the early detection of CRC and the prediction of CRAE.

Targeting Altered Energy Metabolism in Colorectal Cancer: Oncogenic Reprogramming, the Central Role of the TCA Cycle and Therapeutic Opportunities

Colorectal cancer (CRC) is among the most frequent cancer entities worldwide. Multiple factors are causally associated with CRC development, such as genetic and epigenetic alterations, inflammatory bowel disease, lifestyle and dietary factors. During malignant transformation, the cellular energy metabolism is reprogrammed in order to promote cancer cell growth and proliferation. In this review, we first describe the main alterations of the energy metabolism found in CRC, revealing the critical impact of oncogenic signaling and driver mutations in key metabolic enzymes. Then, the central role of mitochondria and the tricarboxylic acid (TCA) cycle in this process is highlighted, also considering the metabolic crosstalk between tumor and stromal cells in the tumor microenvironment. The identified cancer-specific metabolic transformations provided new therapeutic targets for the development of small molecule inhibitors. Promising agents are in clinical trials and are directed against enzymes of the TCA cycle, including isocitrate dehydrogenase, pyruvate dehydrogenase kinase, pyruvate dehydrogenase complex (PDC) and α-ketoglutarate dehydrogenase (KGDH). Finally, we focus on the α-lipoic acid derivative CPI-613, an inhibitor of both PDC and KGDH, and delineate its anti-tumor effects for targeted therapy.

Multi-omic profiling reveals associations between the gut mucosal microbiome, the metabolome, and host DNA methylation associated gene expression in patients with colorectal cancer

Background

The human gut microbiome plays a critical role in the carcinogenesis of colorectal cancer (CRC). However, a comprehensive analysis of the interaction between the host and microbiome is still lacking.

Results

We found correlations between the change in abundance of microbial taxa, butyrate-related colonic metabolites, and methylation-associated host gene expression in colonic tumour mucosa tissues compared with the adjacent normal mucosa tissues. The increase of genus Fusobacterium abundance was correlated with a decrease in the level of 4-hydroxybutyric acid (4-HB) and expression of immune-related peptidase inhibitor 16 (PI16), Fc Receptor Like A (FCRLA) and Lymphocyte Specific Protein 1 (LSP1). The decrease in the abundance of another potentially 4-HB-associated genus, Prevotella 2, was also found to be correlated with the down-regulated expression of metallothionein 1 M (MT1M). Additionally, the increase of glutamic acid-related family Halomonadaceae was correlated with the decreased expression of reelin (RELN). The decreased abundance of genus Paeniclostridium and genus Enterococcus were correlated with increased lactic acid level, and were also linked to the expression change of Phospholipase C Beta 1 (PLCB1) and Immunoglobulin Superfamily Member 9 (IGSF9) respectively. Interestingly, 4-HB, glutamic acid and lactic acid are all butyrate precursors, which may modify gene expression by epigenetic regulation such as DNA methylation.

Conclusions

Our study identified associations between previously reported CRC-related microbial taxa, butyrate-related metabolites and DNA methylation-associated gene expression in tumour and normal colonic mucosa tissues from CRC patients, which uncovered a possible mechanism of the role of microbiome in the carcinogenesis of CRC. In addition, these findings offer insight into potential new biomarkers, therapeutic and/or prevention strategies for CRC.

Decreased Triacylglycerol Content and Elevated Contents of Cell Membrane Lipids in Colorectal Cancer Tissue: A Lipidomic Study

Recent evidence suggests that lipid composition in cancer tissues may undergo multiple alterations. However, no comprehensive analysis of various lipid groups in colorectal cancer (CRC) tissue has been conducted thus far. To address the problem in question, we determined the contents of triacylglycerols (TG), an energetic substrate, various lipids necessary for cell membrane formation, among them phospholipids (phosphatidylcholine, phosphatidylethanolamine), sphingolipids (sphingomyelin) and cholesterol (free, esterified and total), and fatty acids included in complex lipids. ¹H-nuclear magnetic resonance (¹H-NMR) and gas chromatography-mass spectrometry (GC-MS) were used to analyze the lipid composition of colon cancer tissue and normal large intestinal mucosa from 25 patients. Compared with normal tissue, cancer tissues had significantly lower TG content, along with elevated levels of phospholipids, sphingomyelin, and cholesterol. Moreover, the content of oleic acid, the main component of TG, was decreased in cancer tissues, whereas the levels of saturated fatty acids and polyunsaturated fatty acids (PUFAs), which are principal components of polar lipids, were elevated. These lipidome rearrangements were associated with the overexpression of genes associated with fatty acid oxidation, and the synthesis of phospholipids and cholesterol. These findings suggest that reprogramming of lipid metabolism might occur in CRC tissue, with a shift towards increased utilization of TG for energy production and enhanced synthesis of membrane lipids, necessary for the rapid proliferation of cancer cells.

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 potential of nanoflow liquid chromatography-nano electrospray ionisation-mass spectrometry for global profiling the faecal metabolome

Faeces are comprised of a wide array of metabolites arising from the circulatory system as well as the human microbiome. A global metabolite analysis (metabolomics) of faecal extracts offers the potential to uncover new compounds which may be indicative of the onset of bowel diseases such as colorectal cancer (CRC). To date, faecal metabolomics is still in its infancy and the compounds of low abundance present in faecal extracts poorly characterised. In this study, extracts of faeces from healthy subjects were profiled using a sensitive nanoflow-nanospray LC-MS platform which resulted in highly repeatable peak retention times (<2% CV) and intensities (<15% CV). Analysis of the extracts revealed wide coverage of the faecal metabolome including detection of low abundant signalling compounds such as sex steroids and eicosanoids, alongside highly abundant pharmaceuticals and tetrapyrrole metabolites. A small pilot study investigating differences in metabolomics profiles of faecal samples obtained from 7 CRC, 25 adenomatous polyp and 26 healthy groups revealed that secondary bile acids, conjugated androgens, eicosanoids, phospholipids and an unidentified haem metabolite were potential classes of metabolites that discriminated between the CRC and control sample groups. However, much larger follow up studies are needed to confirm which components of the faecal metabolome are associated with actual CRC disease rather than dietary influences. This study reveals the potential of nanospray-nanoflow LC-MS profiling of faecal samples from large scale cohort studies for uncovering the role of the faecal metabolome in colorectal disease formation.

Meta-analysis of fecal metagenomes reveals global microbial signatures that are specific for colorectal cancer

Association studies have linked microbiome alterations with many human diseases. However, they have not always reported consistent results, thereby necessitating cross-study comparisons. Here, a meta-analysis of eight geographically and technically diverse fecal shotgun metagenomic studies of colorectal cancer (CRC, n = 768), which was controlled for several confounders, identified a core set of 29 species significantly enriched in CRC metagenomes (false discovery rate (FDR) < 1 × 10^-5). CRC signatures derived from single studies maintained their accuracy in other studies. By training on multiple studies, we improved detection accuracy and disease specificity for CRC. Functional analysis of CRC metagenomes revealed enriched protein and mucin catabolism genes and depleted carbohydrate degradation genes. Moreover, we inferred elevated production of secondary bile acids from CRC metagenomes, suggesting a metabolic link between cancer-associated gut microbes and a fat- and meat-rich diet. Through extensive validations, this meta-analysis firmly establishes globally generalizable, predictive taxonomic and functional microbiome CRC signatures as a basis for future diagnostics.

An update on the role of gut microbiota in chronic inflammatory diseases, and potential therapeutic targets

The human microbiome plays a critical role in human health, having metabolic, protective, and trophic functions, depending upon its' exact composition. This composition is affected by a number of factors, including the genetic background of the individual, early life factors (including method of birth, length of breastfeeding) and nature of the diet and other environmental exposures (including cigarette smoking) and general life habits. It plays a key role in the control of inflammation, and in turn, its' composition is significantly influenced by inflammation. Areas covered: We consider metabolic, protective, and trophic functions of the microbiome and influences through the lifespan from post-partum effects, to diet later in life in healthy older adults, the effects of aging on both its' composition, and influence on health and potential therapeutic targets that may have anti-inflammatory effects. Expert commentary: The future will see the growth of more effective therapies targeting the microbiome particularly with respect to the use of specific nutrients and diets personalized to the individual.

A Metabolomics Pilot Study on Desmoid Tumors and Novel Drug Candidates

Desmoid tumors (aggressive fibromatosis) are locally invasive soft tissue tumors that lack the ability to metastasize. There are no directed therapies or standard treatment plan, and chemotherapeutics, radiation, and surgery often have temporary effects. The majority of desmoid tumors are related to T41A and S45F mutations of the beta-catenin encoding gene (CTNNB1). Using broad spectrum metabolomics, differences were investigated between paired normal fibroblast and desmoid tumor cells from affected patients. There were differences identified, also, in the metabolomics profiles associated with the two beta-catenin mutations, T41A and S45F. Ongoing drug screening has identified currently available compounds which inhibited desmoid tumor cellular growth by more than 50% but did not affect normal fibroblast proliferation. Two drugs were investigated in this study, and Dasatinib and FAK Inhibitor 14 treatments resulted in unique metabolomics profiles for the normal fibroblast and desmoid tumor cells, in addition to the T41A and S45F. The biochemical pathways that differentiated the cell lines were aminoacyl-tRNA biosynthesis in mitochondria and cytoplasm and signal transduction amino acid-dependent mTORC1 activation. This study provides preliminary understanding of the metabolic differences of paired normal and desmoid tumors cells, their response to desmoid tumor therapeutics, and new pathways to target for therapy.

Discovery of potential biomarkers in human melanoma cells with different metastatic potential by metabolic and lipidomic profiling

Malignant melanoma, characterized by its ability to metastasize to other organs, is responsible for 90% of skin cancer mortality. To investigate alterations in the cellular metabolome and lipidome related to melanoma metastasis, gas chromatography-mass spectrometry (GC-MS) and direct infusion-mass spectrometry (DI-MS)-based metabolic and lipidomic profiling were performed on extracts of normal human melanocyte (HEMn-LP), low metastatic melanoma (A375, G361), and highly metastatic melanoma (A2058, SK-MEL-28) cell lines. In this study, metabolomic analysis identified aminomalonic acid as a novel potential biomarker to discriminate between different stages of melanoma metastasis. Uptake and release of major metabolites as hallmarks of cancer were also measured between high and low metastatic melanoma cells. Lipid analysis showed a progressive increase in phosphatidylinositol (PI) species with saturated and monounsaturated fatty acyl chains, including 16:0/18:0, 16:0/18:1, 18:0/18:0, and 18:0/18:1, with increasing metastatic potential of melanoma cells, defining these lipids as possible biomarkers. In addition, a partial-least-squares projection to latent structure regression (PLSR) model for the prediction of metastatic properties of melanoma was established, and central metabolic and lipidomic pathways involved in the increased motility and metastatic potential of melanoma cells were identified as therapeutic targets. These results could be used to diagnose and control of melanoma metastasis.

Rapid differentiating colorectal cancer and colorectal polyp using dried blood spot mass spectrometry metabolomic approach

Colorectal cancer (CRC) is the third leading causes of cancer mortality, and the early-stage detection could significantly enhance survival rates. Cancer influences the important metabolic pathways and the changes in metabolite levels had been used in many studies as the potential biomarkers. This study is aimed at screening metabolite biomarkers with CRC diagnosis potentials. The direct infusion mass spectrometry (MS) metabolomic analysis based on dried blood spot was used to distinguish CRC from polyp. The target metabolites were composed of 23 amino acids and 26 acylcarnitines. The 21 metabolites in blood were selected via multivariate analysis. A regression model was established based on parameters C16, Arg, C4/C8, C5/C3, Val, Phe/Tyr, Ala, C4/C3. Tenfold cross validation (CV) method was used to test this model and showed sensitivity of 81.18% and specificity of 83.95%. The metabolomic analysis is a practicable method for CRC detection. The use of direct MS analysis in metabolite screening could be finished in several minutes and served as a higher-throughput method to distinguish CRC and polyps. © 2017 IUBMB Life, 69(5):347-354, 2017.

Molecular Biomarkers of Colorectal Cancer and Cancer Disparities: Current Status and Perspective

This review provides updates on the efforts for the development of prognostic and predictive markers in colorectal cancer based on the race/ethnicity of patients. Since the clinical consequences of genetic and molecular alterations differ with patient race and ethnicity, the usefulness of these molecular alterations as biomarkers needs to be evaluated in different racial/ethnic groups. To accomplish personalized patient care, a combined analysis of multiple molecular alterations in DNA, RNA, microRNAs (miRNAs), metabolites, and proteins in a single test is required to assess disease status in a precise way. Therefore, a special emphasis is placed on issues related to utility of recently identified genetic and molecular alterations in genes, miRNAs, and various "-omes" (e.g., proteomes, kinomes, metabolomes, exomes, methylomes) as candidate molecular markers to determine cancer progression (disease recurrence/relapse and metastasis) and to assess the efficacy of therapy in colorectal cancer in relation to patient race and ethnicity. This review will be useful for oncologists, pathologists, and basic and translational researchers.

A validated metabolomic signature for colorectal cancer: exploration of the clinical value of metabolomics

Background:

Timely diagnosis and classification of colorectal cancer (CRC) are hindered by unsatisfactory clinical assays. Our aim was to construct a blood-based biomarker series using a single assay, suitable for CRC detection, prognostication and staging.

Methods:

Serum metabolomic profiles of adenoma (N=31), various stages of CRC (N=320) and healthy matched controls (N=254) were analysed by gas chromatography-mass spectrometry (GC-MS). A diagnostic model for CRC was derived by orthogonal partial least squares-discriminant analysis (OPLS-DA) on a training set, and then validated on an independent data set. Metabolomic models suitable for identifying adenoma, poor prognosis stage II CRC and discriminating various stages were generated.

Results:

A diagnostic signature for CRC with remarkable multivariate performance (R²Y=0.46, Q²Y=0.39) was constructed, and then validated (sensitivity 85% specificity 86%). Area under the receiver-operating characteristic curve was 0.91 (95% CI, 0.87–0.96). Adenomas were also detectable (R²Y=0.35, Q²Y=0.26, internal AUROC=0.81, 95% CI, 0.70–0.92). Also of particular interest, we identified models that stratified stage II by prognosis, and classified cases by stage.

Conclusions:

Using a single assay system, a suite of CRC biomarkers based on circulating metabolites enables early detection, prognostication and preliminary staging information. External population-based studies are required to evaluate the repeatability of our findings and to assess the clinical benefits of these biomarkers.

Changes in urinary metabolic profiles of colorectal cancer patients enrolled in a prospective cohort study (ColoCare)

INTRODUCTION

Metabolomics is a valuable tool for biomarker screening of colorectal cancer (CRC). In this study, we profiled the urinary metabolomes of patients enrolled in a prospective patient cohort (ColoCare). We aimed to describe changes in the metabolome in the longer clinical follow-up and describe initial predictors as candidate markers with possibly prognostic significance.

METHODS

In total, 199 urine samples from CRC patients pre-surgery (n=97), 1-8 days post-surgery (n=12) and then after 6 and 12 months (n=52 and 38, respectively) were analyzed using both GC-MS and ¹H-NMR. Both datasets were analyzed separately with built in uni- and multivariate analyses of Metaboanalyst 2.0. Furthermore, adjusted linear mixed effects regression models were constructed.

RESULTS

Many concentrations of the metabolites derived from the gut microbiome were affected by CRC surgery, presumably indicating a tumor-induced shift in bacterial species. Associations of the microbial metabolites with disease stage indicate an important role of the gut microbiome in CRC.We were able to differentiate the metabolite profiles of CRC patients prior to surgery from those at any post-surgery timepoint using a multivariate model containing 20 marker metabolites (AUCROC=0.89; 95% CI:0.84-0.95).

CONCLUSION

To the best of our knowledge, this is one of the first metabolomic studies to follow CRC patients in a prospective setting with repeated urine sampling over time. We were able to confirm markers initially identified in case-control studies and pin point metabolites which may serve as candidates for prognostic biomarkers of CRC.

Investigation of Host-Gut Microbiota Modulation of Therapeutic Outcome

A broader understanding of factors underlying interindividual variation in pharmacotherapy is important for our pursuit of "personalized medicine." Based on knowledge gleaned from the investigation of human genetics, drug-metabolizing enzymes, and transporters, clinicians and pharmacists are able to tailor pharmacotherapies according to the genotype of patients. However, human host factors only form part of the equation that accounts for heterogeneity in therapeutic outcome. Notably, the gut microbiota possesses wide-ranging metabolic activities that expand the metabolic functions of the human host beyond that encoded by the human genome. In this review, we first illustrate the mechanisms in which gut microbes modulate pharmacokinetics and therapeutic outcome. Second, we discuss the application of metabonomics in deciphering the complex host-gut microbiota interaction in pharmacotherapy. Third, we highlight an integrative approach with particular mention of the investigation of gut microbiota using culture-based and culture-independent techniques to complement the investigation of the host-gut microbiota axes in pharmaceutical research.

Analytical protocols based on LC-MS, GC-MS and CE-MS for nontargeted metabolomics of biological tissues

Invasive, site-specific metabolite information could be better obtained from tissues. Hence, highly sensitive mass spectrometry-based metabolomics coupled with separation techniques are increasingly in demand in clinical research for tissue metabolomics application. Applying these techniques to nontargeted tissue metabolomics provides identification of distinct metabolites. These findings could help us to understand alterations at the molecular level, which can also be applied in clinical practice as screening markers for early disease diagnosis. However, tissues as solid and heterogeneous samples pose an additional analytical challenge that should be considered in obtaining broad, reproducible and representative analytical profiles. This manuscript summarizes the state of the art in tissue (human and animal) treatment (quenching, homogenization and extraction) for nontargeted metabolomics with mass spectrometry.

Multidimensional gas chromatography methods for bioanalytical research

Multidimensional gas chromatography (MDGC) methods are high-resolution volatile chemical separation techniques, and comprise classical heart-cutting MDGC and its more recent incarnation, comprehensive 2D GC. Although available for a long period, MDGC approaches are still not widely practiced in the field of bioanalysis, possibly reflecting the general preference for regular GC versus MDGC approaches. With the recent introduction of ‘-omic’ techniques that emphasize global nontargeted profiling of metabolites within living systems, it is evident that MDGC is gaining momentum as a separation tool, since it offers very high resolution. By untangling metabolites within highly complex biological matrices, and expanding the metabolic coverage, MDGC plays a frontline role in ‘-omics’ based studies. This review highlights state-of-the-art MDGC approaches, and summarizes the recent developments in bioanalytics.

Metabonomics of human colorectal cancer: new approaches for early diagnosis and biomarker discovery

Colorectal cancer (CRC) is one of the most common cancers in the world, having both high prevalence and mortality. It is usually diagnosed at advanced stages due to the limitations of current screening methods used in the clinic. There is an urgent need to develop new biomarkers and modalities to detect, diagnose, and monitor the disease. Metabonomics, an approach that involves the comprehensive profiling of the full complement of endogenous metabolites in a biological system, has demonstrated its great potential for use in the early diagnosis and personalized treatment of various cancers including CRC. By applying advanced analytical techniques and bioinformatics tools, the metabolome is mined for biomarkers that are associated with carcinogenesis and prognosis. This review provides an overview of the metabonomics workflow and studies, with a focus on recent advances and findings in biomarker discovery for the early diagnosis and prognosis of CRC.

Metabolomics for biomarker discovery in gastroenterological cancer

The study of the omics cascade, which involves comprehensive investigations based on genomics, transcriptomics, proteomics, metabolomics, etc., has developed rapidly and now plays an important role in life science research. Among such analyses, metabolome analysis, in which the concentrations of low molecular weight metabolites are comprehensively analyzed, has rapidly developed along with improvements in analytical technology, and hence, has been applied to a variety of research fields including the clinical, cell biology, and plant/food science fields. The metabolome represents the endpoint of the omics cascade and is also the closest point in the cascade to the phenotype. Moreover, it is affected by variations in not only the expression but also the enzymatic activity of several proteins. Therefore, metabolome analysis can be a useful approach for finding effective diagnostic markers and examining unknown pathological conditions. The number of studies involving metabolome analysis has recently been increasing year-on-year. Here, we describe the findings of studies that used metabolome analysis to attempt to discover biomarker candidates for gastroenterological cancer and discuss metabolome analysis-based disease diagnosis.

Development and validation of a highly sensitive urine-based test to identify patients with colonic adenomatous polyps

Objectives:

Adenomatous polyps are precursors of colorectal cancer; their detection and removal is the goal of colon cancer screening programs. However, fecal-based methods identify patients with adenomatous polyps with low levels of sensitivity. The aim or this study was to develop a highly accurate, prototypic, proof-of-concept, spot urine-based diagnostic test using metabolomic technology to distinguish persons with adenomatous polyps from those without polyps.

Methods:

Prospective urine and stool samples were collected from 876 participants undergoing colonoscopy examination in a colon cancer screening program, from April 2008 to October 2009 at the University of Alberta. Colonoscopy reference standard identified 633 participants with no colonic polyps and 243 with colonic adenomatous polyps. One-dimensional nuclear magnetic resonance spectra of urine metabolites were analyzed to define a diagnostic metabolomic profile for colonic adenomas. A urine metabolomic diagnostic test for colonic adenomatous polyps was established using 67% of the samples (un-blinded training set) and validated using the other 33% of the samples (blinded testing set). The urine metabolomic diagnostic test's specificity and sensitivity were compared with those of fecal-based tests.

Results:

Using a two-component, orthogonal, partial least-squares model of the metabolomic profile, the un-blinded training set identified patients with colonic adenomatous polyps with 88.9% sensitivity and 50.2% specificity. Validation using the blinded testing set confirmed sensitivity and specificity values of 82.7% and 51.2%, respectively. Sensitivities of fecal-based tests to identify colonic adenomas ranged from 2.5 to 11.9%.

Conclusions:

We describe a proof-of-concept spot urine-based metabolomic diagnostic test that identifies patients with colonic adenomatous polyps with a greater level of sensitivity (83%) than fecal-based tests.

Metabolome analysis for discovering biomarkers of gastroenterological cancer

Improvements in analytical technologies have made it possible to rapidly determine the concentrations of thousands of metabolites in any biological sample, which has resulted in metabolome analysis being applied to various types of research, such as clinical, cell biology, and plant/food science studies. The metabolome represents all of the end products and by-products of the numerous complex metabolic pathways operating in a biological system. Thus, metabolome analysis allows one to survey the global changes in an organism's metabolic profile and gain a holistic understanding of the changes that occur in organisms during various biological processes, e.g., during disease development. In clinical metabolomic studies, there is a strong possibility that differences in the metabolic profiles of human specimens reflect disease-specific states. Recently, metabolome analysis of biofluids, e.g., blood, urine, or saliva, has been increasingly used for biomarker discovery and disease diagnosis. Mass spectrometry-based techniques have been extensively used for metabolome analysis because they exhibit high selectivity and sensitivity during the identification and quantification of metabolites. Here, we describe metabolome analysis using liquid chromatography-mass spectrometry, gas chromatography-mass spectrometry, and capillary electrophoresis-mass spectrometry. Furthermore, the findings of studies that attempted to discover biomarkers of gastroenterological cancer are also outlined. Finally, we discuss metabolome analysis-based disease diagnosis.

Non-invasive fecal metabonomic detection of colorectal cancer

Colorectal cancer (CRC) is a major cause of mortality in many developed countries. Effective screening strategies were called for to facilitate timely detection and to promote a better clinical outcome. In this study, the role of fecal metabonomics in the non-invasive detection of CRC was investigated. Gas chromatography/time-of-flight mass spectrometry (GC/TOFMS) was utilized for the metabolic profiling of feces obtained from 11 CRC patients and 10 healthy subjects. Concurrently, matched tumor and normal mucosae surgically excised from CRC patients were profiled. CRC patients were differentiated clearly from healthy subjects based on their fecal metabonomic profiles (orthogonal partial least squares discriminant analysis [OPLS-DA], 1 predictive and 3 Y-orthogonal components, R (2)X = 0.373, R (2)Y = 0.995, Q (2) [cumulative] = 0.215). The robustness of the OPLS-DA model was demonstrated by an area of 1 under the receiver operator characteristic curve. OPLS-DA revealed fecal marker metabolites (e.g., fructose, linoleic acid, and nicotinic acid) that provided novel insights into the tumorigenesis of CRC. Interestingly, a disparate set of CRC-related metabolic aberrations occurred at the tissue level, implying the contribution of processes beyond the direct shedding of tumor cells to the fecal metabotype. In summary, this work established proof-of-principle for GC/TOFMS-based fecal metabonomic detection of CRC and offered new perspectives on the underlying mechanisms.

Metabolomics in diagnosis and biomarker discovery of colorectal cancer

Colorectal cancer (CRC), a major public health concern, is the second leading cause of cancer death in developed countries. There is a need for better preventive strategies to improve the patient outcome that is substantially influenced by cancer stage at the time of diagnosis. Patients with early stage colorectal have a significant higher 5-year survival rates compared to patients diagnosed at late stage. Although traditional colonoscopy remains the effective means to diagnose CRC, this approach generally suffers from poor patient compliance. Thus, it is important to develop more effective methods for early diagnosis of this disease process, also there is an urgent need for biomarkers to diagnose CRC, assess disease severity, and prognosticate course. Increasing availability of high-throughput methodologies open up new possibilities for screening new potential candidates for identifying biomarkers. Fortunately, metabolomics, the study of all metabolites produced in the body, considered most closely related to a patient's phenotype, can provide clinically useful biomarkers applied in CRC, and may now open new avenues for diagnostics. It has a largely untapped potential in the field of oncology, through the analysis of the cancer metabolome to identify marker metabolites defined here as surrogate indicators of physiological or pathophysiological states. In this review we take a closer look at the metabolomics used within the field of colorectal cancer. Further, we highlight the most interesting metabolomics publications and discuss these in detail; additional studies are mentioned as a reference for the interested reader.

A machine-learned predictor of colonic polyps based on urinary metabolomics

We report an automated diagnostic test that uses the NMR spectrum of a single spot urine sample to accurately distinguish patients who require a colonoscopy from those who do not. Moreover, our approach can be adjusted to tradeoff between sensitivity and specificity. We developed our system using a group of 988 patients (633 normal and 355 who required colonoscopy) who were all at average or above-average risk for developing colorectal cancer. We obtained a metabolic profile of each subject, based on the urine samples collected from these subjects, analyzed via ¹H-NMR and quantified using targeted profiling. Each subject then underwent a colonoscopy, the gold standard to determine whether he/she actually had an adenomatous polyp, a precursor to colorectal cancer. The metabolic profiles, colonoscopy outcomes, and medical histories were then analysed using machine learning to create a classifier that could predict whether a future patient requires a colonoscopy. Our empirical studies show that this classifier has a sensitivity of 64% and a specificity of 65% and, unlike the current fecal tests, allows the administrators of the test to adjust the tradeoff between the two.

Blood volatile compounds as biomarkers for colorectal cancer

Many recent studies have focused on the connection between the composition of specific volatile organic compounds (VOCs) in exhaled breath and various forms of cancer. However, the composition of exhaled breath is affected by many factors, such as lung disease, smoking, and diet. VOCs are released into the bloodstream before they are exhaled; therefore, the analysis of VOCs in blood will provide more accurate results than the analysis of VOCs in exhaled breath. Blood were collected from 16 colorectal cancer patients and 20 healthy controls, then solid phase microextraction-chromatography-mass spectrometry (SPME-GC-MS) was used to analysis the exhaled volatile organic compounds (VOCs). The statistical methods principal component analysis (PCA) and partial least-squares discriminant analysis (PLSDA) were performed to deal with the final dates. Three metabolic biomarkers were found at significantly lower levels in the group of CRC patients than in the normal control group (P<0.01): phenyl methylcarbamate, ethylhexanol, and 6-t-butyl-2,2,9,9-tetramethyl-3,5-decadien-7-yne. In addition, significantly higher levels of 1,1,4,4-tetramethyl-2,5-dimethylene-cyclohexane were found in the group of CRC patients than in the normal control group (P<0.05). Compared with healthy individuals, patients with colorectal adenocarcinoma exhibited a distinct blood metabolic profile with respect to VOCs. The analysis of blood VOCs appears to have potential clinical applications for CRC screening.

Review of mass spectrometry-based metabolomics in cancer research

Metabolomics, the systematic investigation of all metabolites present within a biologic system, is used in biomarker development for many human diseases, including cancer. In this review, we investigate the current role of mass spectrometry-based metabolomics in cancer research. A literature review was carried out within the databases PubMed, Embase, and Web of Knowledge. We included 106 studies reporting on 21 different types of cancer in 7 different sample types. Metabolomics in cancer research is most often used for case-control comparisons. Secondary applications include translational areas, such as patient prognosis, therapy control and tumor classification, or grading. Metabolomics is at a developmental stage with respect to epidemiology, with the majority of studies including less than 100 patients. Standardization is required especially concerning sample preparation and data analysis. In the second part of this review, we reconstructed a metabolic network of patients with cancer by quantitatively extracting all reports of altered metabolites: Alterations in energy metabolism, membrane, and fatty acid synthesis emerged, with tryptophan levels changed most frequently in various cancers. Metabolomics has the potential to evolve into a standard tool for future applications in epidemiology and translational cancer research, but further, large-scale studies including prospective validation are needed.

CE-MS based on moving reaction boundary method for urinary metabolomic analysis of gastric cancer patients

There is still a lack of satisfactory tumor markers for gastric cancer (GasC). This study is aimed at optimizing parameters in CE-MS based on moving reaction boundary (MRB) so as to improve its sensitivity and stability, and at searching for potential tumor markers of GasC in patients' urine samples via MRB-CE-MS. In this study, several parameters of MRB-CE-MS were investigated and optimized in order to gain optimal stability, sensitivity, and specificity, and was afterwards evaluated as valid. Subsequently, urine samples from GasC patients and control subjects were subjected to MRB-CE-MS analysis under optimized conditions, which successfully distinguished GasC patients from controls, as well as early-stage patients from advanced stage patients. Differentiation performance was evaluated by area under the curve, which showed fine differential value between GasC patients and controls, as well as between early and advanced stage patients (area under the curve value 1.0 and 0.847, respectively). In conclusion, this study established a set of feasible and useful methodology in searching potential tumor markers in urine samples from GasC patients. Moreover, several amino acids have been recognized as potential tumor markers that deserve further investigation.

Metabolomic profiling in colorectal cancer: opportunities for personalized medicine

Colorectal cancer (CRC) is one of the most common types of cancer in the world, with high prevalence and mortality. Understanding the alterations of cancer metabolism and identifying reliable biomarkers would facilitate the development of novel technologies of CRC screening and early diagnosis, as well as new approaches to providing personalized medicine. Metabolomics, as an emerging molecular phenotyping approach, provides a clinical platform technology with an unprecedented amount of metabolic readout information, which is ideal for theranostic biomarker discovery. Metabolic signatures can link the unique pathophysiological states of patients to personalized health monitoring and intervention strategies. This article presents an overview of the metabolomic studies of CRC with a focus on recent advances in the biomarker discovery in serum, urine, fecal water and tissue samples for cancer diagnosis. The development and application of metabolomics towards personalized medicine, including early diagnosis, cancer staging, treatment and drug discovery are also discussed.

Global gas chromatography/time-of-flight mass spectrometry (GC/TOFMS)-based metabonomic profiling of lyophilized human feces

Gas chromatography mass spectrometry (GC/MS)-based fecal metabonomics represents a powerful systems biology approach for elucidating metabolic biomarkers of lower gastrointestinal tract (GIT) diseases. Unlike metabolic profiling of fecal water, the profiling of complete fecal material remains under-explored. Here, a gas chromatography/time-of-flight mass spectrometry (GC/TOFMS) method was developed and validated for the global metabonomic profiling of human feces. Fecal and fecal water metabotypes were also profiled and compared. Additionally, the unclear influence of blood in stool on the fecal metabotype was investigated unprecedentedly. Eighty milligram of lyophilized feces was ultrasonicated with 1mL of methanol:water (8:2) for 30min, followed by centrifugation, drying of supernatant, oximation and trimethylsilylation for 45min. Lyophilized feces demonstrated a more comprehensive metabolic coverage than fecal water, based on the number of chromatographic peaks. Principal component analysis (PCA) indicated occult blood (1mgHb/g feces) exerted a negligible effect on the fecal metabotype. Conversely, a unique metabotype related to feces spiked with gross blood (100mgHb/g feces) was revealed (PCA, R(2)X=0.837, Q(2)=0.794), confirming the potential confounding effect of gross GIT bleeding on the fecal metabotype. This pertinent finding highlights the importance of prudent interpretation of fecal metabonomic data, particularly in GIT diseases where bleeding is prevalent.

Urinary metabotyping of bladder cancer using two-dimensional gas chromatography time-of-flight mass spectrometry

Cystoscopy is the gold standard clinical diagnosis of human bladder cancer (BC). As cystoscopy is expensive and invasive, it compromises patients' compliance toward surveillance screening and challenges the detection of recurrent BC. Therefore, the development of a noninvasive method for the diagnosis and surveillance of BC and the elucidation of BC progression become pertinent. In this study, urine samples from 38 BC patients and 61 non-BC controls were subjected to urinary metabotyping using two-dimensional gas chromatography time-of-flight mass spectrometry (GC×GC-TOFMS). Subsequent to data preprocessing and chemometric analysis, the orthogonal partial least-squares discriminant analysis (OPLS-DA, R2X=0.278, R2Y=0.904 and Q2Y (cumulative)=0.398) model was validated using permutation tests and receiver operating characteristic (ROC) analysis. Marker metabolites were further screened from the OPLS-DA model using statistical tests. GC×GC-TOFMS urinary metabotyping demonstrated 100% specificity and 71% sensitivity in detecting BC, while 100% specificity and 46% sensitivity were observed via cytology. In addition, the model revealed 46 metabolites that characterize human BC. Among the perturbed metabolic pathways, our clinical finding on the alteration of the tryptophan-quinolinic metabolic axis in BC suggested the potential roles of kynurenine in the malignancy and therapy of BC. In conclusion, global urinary metabotyping holds potential for the noninvasive diagnosis and surveillance of BC in clinics. In addition, perturbed metabolic pathways gleaned from urinary metabotyping shed new and established insights on the biology of human BC.

Probiotics in colorectal cancer (CRC) with emphasis on mechanisms of action and current perspectives

Colorectal cancer (CRC) is the third most common form of cancer. Diverse therapies such as chemotherapy, immunotherapy and radiation have shown beneficial effects, but are limited because of their safety and toxicity. Probiotic formulations have shown great promise in CRC as preventive and early stage therapeutics. This review highlights the importance of a balanced intestinal microbiota and summarizes the recent developments in probiotics for treating CRC. Specifically, this report describes evidence of the role of probiotics in modulating the microbiota, in improving the physico-chemical conditions of the gut and in reducing oxidative stress. It also discusses the mechanisms of probiotics in inhibiting tumour progression, in producing anticancer compounds and in modulating the host immune response. Even though some of these effects were observed in several clinical trials, when probiotic formulations were used as a supplement to CRC therapies, the application of probiotics as biotherapeutics against CRC still needs further investigation.