Non-invasive fecal metabonomic detection of colorectal cancer

Progress of gut microbiome and its metabolomics in early screening of colorectal cancer

Gut microbes are widely considered to be closely associated with colorectal cancer (CRC) development. The microbiota is regarded as a potential identifier of CRC, as several studies have found great significant changes in CRC patients' microbiota and metabolic groups. Changes in microbiota, like Fusobacterium nucleatum and Bacteroides fragilis, also alter the metabolic activity of the host, promoting CRC development. In contrast, the metabolome is an intuitive discriminative biomarker as a small molecular bridge to distinguish CRC from healthy individuals due to the direct action of microbes on the host. More diagnostic microbial markers have been found, and the potential discriminatory power of microorganisms in CRC has been investigated through the combined use of biomic genomic metabolomics, bringing new ideas for screening fecal microbial markers. In this paper, we discuss the potential of microorganisms and their metabolites as biomarkers in CRC screening, hoping to provide thoughts and references for non-invasive screening of CRC.

Microbiome and metabolic features of tissues and feces reveal diagnostic biomarkers for colorectal cancer

Microbiome and their metabolites are increasingly being recognized for their role in colorectal cancer (CRC) carcinogenesis. Towards revealing new CRC biomarkers, we compared 16S rRNA gene sequencing and liquid chromatography-mass spectrometry (LC-MS) metabolite analyses in 10 CRC (TCRC) and normal paired tissues (THC) along with 10 matched fecal samples (FCRC) and 10 healthy controls (FHC). The highest microbial phyla abundance from THC and TCRC were Firmicutes, while the dominant phyla from FHC and FCRC were Bacteroidetes, with 72 different microbial genera identified among four groups. No changes in Chao1 indices were detected between tissues or between fecal samples whereas non-metric multidimensional scaling (NMDS) analysis showed distinctive clusters among fecal samples but not tissues. LEfSe analyses indicated Caulobacterales and Brevundimonas were higher in THC than in TCRC, while Burkholderialese, Sutterellaceaed, Tannerellaceaea, and Bacteroidaceae were higher in FHC than in FCRC. Microbial association networks indicated some genera had substantially different correlations. Tissue and fecal analyses indicated lipids and lipid-like molecules were the most abundant metabolites detected in fecal samples. Moreover, partial least squares discriminant analysis (PLS-DA) based on metabolic profiles showed distinct clusters for CRC and normal samples with a total of 102 differential metabolites between THC and TCRC groups and 700 metabolites different between FHC and FCRC groups. However, only Myristic acid was detected amongst all four groups. Highly significant positive correlations were recorded between genus-level microbiome and metabolomics data in tissue and feces. And several metabolites were associated with paired microbes, suggesting a strong microbiota-metabolome coupling, indicating also that part of the CRC metabolomic signature was attributable to microbes. Suggesting utility as potential biomarkers, most such microbiome and metabolites showed directionally consistent changes in CRC patients. Nevertheless, further studies are needed to increase sample sizes towards verifying these findings.

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.

Microbiome-mediated fructose depletion restricts murine gut colonization by vancomycin-resistant Enterococcus

Multidrug-resistant organisms (MDRO) are a major threat to public health. MDRO infections, including those caused by vancomycin-resistant Enterococcus (VRE), frequently begin by colonization of the intestinal tract, a crucial step that is impaired by the intestinal microbiota. However, the specific members of the microbiota that suppress MDRO colonization and the mechanisms of such protection are largely unknown. Here, using metagenomics and mouse models that mimic the patients' exposure to antibiotics, we identified commensal bacteria associated with protection against VRE colonization. We further found a consortium of five strains that was sufficient to restrict VRE gut colonization in antibiotic treated mice. Transcriptomics in combination with targeted metabolomics and in vivo assays indicated that the bacterial consortium inhibits VRE growth through nutrient depletion, specifically by reducing the levels of fructose, a carbohydrate that boosts VRE growth in vivo. Finally, in vivo RNA-seq analysis of each strain of the consortium in combination with ex vivo and in vivo assays demonstrated that a single bacterium (Olsenella sp.) could recapitulate the effect of the consortium. Our results indicate that nutrient depletion by specific commensals can reduce VRE intestinal colonization, which represents a novel non-antibiotic based strategy to prevent infections caused by this multidrug-resistant organism.

Microbiome systems biology advancements for natural well-being

Throughout the years all data from epidemiological, physiological and omics have suggested that the microbial communities play a considerable role in modulating human health. The population of microorganisms residing in the human intestine collectively known as microbiota presents a genetic repertoire that is higher in magnitude than the human genome. They play an essential role in host immunity and neuronal signaling. Rapid enhancement of sequence based screening and development of humanized gnotobiotic model has sparked a great deal of interest among scientists to probe the dynamic interactions of the commensal bacteria. This review focuses on systemic analysis of the gut microbiome to decipher the complexity of the host-microbe intercommunication and gives a special emphasis on the evolution of targeted precision medicine through microbiome engineering. In addition, we have also provided a comprehensive description of how interconnection between metabolism and biochemical reactions in a specific organism can be obtained from a metabolic network or a flux balance analysis and combining multiple datasets helps in the identification of a particular metabolite. The review highlights how genetic modification of the critical components and programming the resident microflora can be employed for targeted precision medicine. Inspite of the ongoing debate on the utility of gut microbiome we have explored on the probable new therapeutic avenues like FMT (Fecal microbiota transplant) can be utilized. This review also recapitulates integrating human-relevant 3D cellular models coupled with computational models and the metadata obtained from interventional and epidemiological studies may decipher the complex interactome of diet-microbiota-disease pathophysiology. In addition, it will also open new avenues for the development of therapeutics derived from microbiome or implementation of personalized nutrition. In addition, the identification of biomarkers can also help towards the development of new diagnostic tools and eventually will lead to strategic management of the disease. Inspite of the ongoing debate on the utility of the gut microbiome we have explored how probable new therapeutic avenues like FMT (Fecal microbiota transplant) can be utilized. This review also summarises integrating human-relevant 3D cellular models coupled with computational models and the metadata obtained from interventional and epidemiological studies may decipher the complex interactome of diet- microbiota-disease pathophysiology. In addition, it will also open new avenues for the development of therapeutics derived from the microbiome or implementation of personalized nutrition. In addition, the identification of biomarkers can also help towards the development of new diagnostic tools and eventually will lead to strategic management of disease.

Establishment of an early diagnosis model of colon cancerous bowel obstruction based on 1H NMR

Objective

To prospectively establish an early diagnosis model of acute colon cancerous bowel obstruction by applying nuclear magnetic resonance hydrogen spectroscopy(1H NMR) technology based metabolomics methods, combined with machine learning.

Methods

In this study, serum samples of 71 patients with acute bowel obstruction requiring emergency surgery who were admitted to the Emergency Department of Sichuan Provincial People’s Hospital from December 2018 to November 2020 were collected within 2 hours after admission, and NMR spectroscopy data was taken after pretreatment. After postoperative pathological confirmation, they were divided into colon cancerous bowel obstruction (CBO) group and adhesive bowel obstruction (ABO) control group. Used MestReNova software to extract the two sets of spectra bins, and used the MetaboAnalyst5.0 website to perform partial least square discrimination (PLS-DA), combining the human metabolome database (HMDB) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) to find possible different Metabolites and related metabolic pathways.

Results

22 patients were classified as CBO group and 30 were classified as ABO control group. Compared with ABO group, the level of Xanthurenic acid, 3-Hydroxyanthranilic acid, Gentisic acid, Salicyluric acid, Ferulic acid, Kynurenic acid, CDP, Mandelic acid, NADPH, FAD, Phenylpyruvate, Allyl isothiocyanate, and Vanillylmandelic acid increased in the CBO group; while the lecel of L-Tryptophan and Bilirubin decreased. There were significant differences between two groups in the tryptophan metabolism, tyrosine metabolism, glutathione metabolism, phenylalanine metabolism and synthesis pathways of phenylalanine, tyrosine and tryptophan (all P<0.05). Tryptophan metabolism pathway had the greatest impact (Impact = 0.19). The early diagnosis model of colon cancerous bowel was established based on the levels of six metabolites: Xanthurenic acid, 3-Hydroxyanthranilic acid, Gentisic acid, Salicylic acid, Ferulic acid and Kynurenic acid (R2 = 0.995, Q2 = 0.931, RMSE = 0.239, AUC = 0.962).

Conclusion

This study firstly used serum to determine the difference in metabolome between patients with colon cancerous bowel obstruction and those with adhesive bowel obstruction. The study found that the metabolic information carried by the serum was sufficient to discriminate the two groups of patients and provided the theoretical supporting for the future using of the more convenient sample for the differential diagnosis of patients with colon cancerous bowel obstruction. Quantitative experiments on a large number of samples were still needed in the future.

Plasma Metabolomics Analysis of Aspirin Treatment and Risk of Colorectal Adenomas

Despite substantial observational and experimental evidence that aspirin use can provide protection against the development of colorectal neoplasia, our understanding of the molecular mechanisms involved is inadequate and limits our ability to use this drug effectively and safely for chemoprevention. We employed an untargeted plasma metabolomics approach using liquid chromatography with high-resolution mass spectroscopy to explore novel metabolites that may contribute to the chemopreventive effects of aspirin. Associations between levels of metabolic features in plasma and aspirin treatment were investigated among 523 participants in a randomized placebo-controlled clinical trial of two doses of aspirin (81 or 325 mg/day) and were linked to risk of colorectal adenoma occurrence over 3 years of follow-up. Metabolic pathways that were altered with aspirin treatment included linoleate and glycerophospholipid metabolism for the 81-mg dose and carnitine shuttle for both doses. Metabolites whose levels increased with 81 mg/day aspirin treatment and were also associated with decreased risk of adenomas during follow-up included certain forms of lysophosphatidylcholine and lysophosphatidylethanolamine as well as trihydroxyoctadecenoic acid, which is a derivative of linoleic acid and is upstream of cyclooxygenase inhibition by aspirin in the linoleate and arachidonic acid metabolism pathways. In conclusion, our findings regarding lysophospholipids and metabolites in the linoleate metabolism pathway may provide novel insights into the chemopreventive effects of aspirin in the colorectum, although they should be considered hypothesis-generating at this time.

PREVENTION RELEVANCE

This research used metabolomics, an innovative discovery-based approach, to identify molecular changes in human blood that may help to explain how aspirin use reduces the risk of colorectal neoplasia in some individuals. Ultimately, this work could have important implications for optimizing aspirin use in the prevention of colorectal cancer.

Bidirectional effects of intestinal microbiota and antibiotics: a new strategy for colorectal cancer treatment and prevention

PURPOSE

Colorectal cancer (CRC) is the third most common cancer worldwide, and its incidence and mortality rates are increasing every year. The intestinal microbiota has been called the "neglected organ" and there is growing evidence that the intestinal microbiota and its metabolites can be used in combination with immunotherapy, radiotherapy and chemotherapy to greatly enhance the treatment of colorectal cancer and to address some of the side effects and adverse effects of these therapies. Antibiotics have great potential to eliminate harmful microbiota, control infection, and reduce colorectal cancer side effects. However, the use of antibiotics has been a highly controversial issue, and numerous retrospective studies have shown that the use of antibiotics affects the effectiveness of treatment (especially immunotherapy). Understanding the bi-directional role of the gut microbiota and antibiotics will further enhance our research into the diagnosis and treatment of cancer.

METHODS

We searched the "PubMed" database and selected the following keywords "intestinal microbiota, antibiotics, treatment, prevention, colorectal cancer". In this review, we discuss the role of the intestinal microbiota in immunotherapy, radiotherapy, chemotherapy, diagnosis, and prevention of CRC. We also conclude that the intestinal microbiota and antibiotics work together to promote the treatment of CRC through a bidirectional effect.

RESULTS

We found that the intestinal microbiota plays a key role in promoting immunotherapy, chemotherapy, radiotherapy, diagnosis and prevention of CRC. In addition, gut microbiota and antibiotic interactions could be a new strategy for CRC treatment.

CONCLUSION

The bi-directional role of the intestinal microbiota and antibiotics plays a key role in the prevention, diagnosis, and treatment of colorectal cancer.

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.

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

PURPOSE

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

Evaluation of different stool extraction methods for metabolomics measurements in human faecal samples

Background

Metabolomics analysis of human stool samples is of great interest for a broad range of applications in biomedical research including early detection of colorectal neoplasms. However, due to the complexity of metabolites there is no consensus on how to process samples for stool metabolomics measurements to obtain a broad coverage of hydrophilic and hydrophobic substances.

Methods

We used frozen stool samples (50 mg) from healthy study participants. Stool samples were processed after thawing using eight different processing protocols and different solvents (solvents such as phosphate-buffered saline, isopropanol, methanol, ethanol, acetonitrile and solvent mixtures with or without following evaporation and concentration steps). Metabolites were measured afterwards using the MxP Quant 500 kit (Biocrates). The best performing protocol was subsequently applied to compare stool samples of participants with different dietary habits.

Results

In this study, we were able to determine up to 340 metabolites of various chemical classes extracted from stool samples of healthy study participants with eight different protocols. Polar metabolites such as amino acids could be measured with each method while other metabolite classes, particular lipid species (better with isopropanol and ethanol or methanol following a drying step), are more dependent on the solvent or combination of solvents used. Only a small number of triglycerides or acylcarnitines were detected in human faeces. Extraction efficiency was higher for protocols using isopropanol (131 metabolites>limit of detection (LOD)) or those using ethanol or methanol and methyl tert-butyl ether (MTBE) including an evaporation and concentration step (303 and 342 metabolites>LOD, respectively) than for other protocols. We detected significant faecal metabolite differences between vegetarians, semivegetarians and non-vegetarians.

Conclusion

For the evaluation of metabolites in faecal samples, we found protocols using solvents like isopropanol and those using ethanol or methanol, and MTBE including an evaporation and concentration step to be superior regarding the number of detected metabolites of different chemical classes over others tested in this study.

Microbiome-Mediated Immune Signaling in Inflammatory Bowel Disease and Colorectal Cancer: Support From Meta-omics Data

Chronic intestinal inflammation and microbial dysbiosis are hallmarks of colorectal cancer (CRC) and inflammatory bowel diseases (IBD), such as Crohn’s disease and ulcerative colitis. However, the mechanistic relationship between gut dysbiosis and disease has not yet been fully characterized. Although the “trigger” of intestinal inflammation remains unknown, a wealth of evidence supports the role of the gut microbiome as a mutualistic pseudo-organ that significantly influences intestinal homeostasis and is capable of regulating host immunity. In recent years, culture-independent methods for assessing microbial communities as a whole (termed meta-omics) have grown beyond taxonomic identification and genome characterization (metagenomics) into new fields of research that collectively expand our knowledge of microbiomes. Metatranscriptomics, metaproteomics, and metabolomics are meta-omics techniques that aim to describe and quantify the functional activity of the gut microbiome. Uncovering microbial metabolic contributions in the context of IBD and CRC using these approaches provides insight into how the metabolic microenvironment of the GI tract shapes microbial community structure and how the microbiome, in turn, influences the surrounding ecosystem. Immunological studies in germ-free and wild-type mice have described several host-microbiome interactions that may play a role in autoinflammation. Chronic colitis is a precursor to CRC, and changes in the gut microbiome may be an important link triggering the neoplastic process in chronic colitis. In this review, we describe several microbiome-mediated mechanisms of host immune signaling, such as short-chain fatty acid (SCFA) and bile acid metabolism, inflammasome activation, and cytokine regulation in the context of IBD and CRC, and discuss the supporting role for these mechanisms by meta-omics data.

Odors and cancer: Current status and future directions

Cancer is the second leading cause of death in the world. Because tumors detected at early stages are easier to treat, the search for biomarkers-especially non-invasive ones-that allow early detection of malignancies remains a central goal to reduce cancer mortality. Cancer, like other pathologies, often alters body odors, and much has been done by scientists over the last few decades to assess the value of volatile organic compounds (VOCs) as signatures of cancers. We present here a quantitative review of 208 studies carried out between 1984 and 2020 that explore VOCs as potential biomarkers of cancers. We analyzed the main findings of these studies, listing and classifying VOCs related to different cancer types while considering both sampling methods and analysis techniques. Considering this synthesis, we discuss several of the challenges and the most promising prospects of this research direction in the war against cancer.

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

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

Comparing Metabolomics Profiles in Various Types of Liquid Biopsies among Screening Participants with and without Advanced Colorectal Neoplasms

Analysis of metabolomics has been suggested as a promising approach for early detection of colorectal cancer and advanced adenomas. We investigated and compared the metabolomics profile in blood, stool, and urine samples of screening colonoscopy participants and aimed to evaluate differences in metabolite concentrations between people with advanced colorectal neoplasms and those without neoplasms. Various types of bio-samples (plasma, feces, and urine) from 400 participants of screening colonoscopy were investigated using the MxP® Quant 500 kit (Biocrates, Innsbruck, Austria). We detected a broad range of metabolites in blood, stool, and urine samples (504, 331, and 131, respectively). Significant correlations were found between concentrations in blood and stool, blood and urine, and stool and urine for 93, 154, and 102 metabolites, of which 68 (73%), 126 (82%), and 39 (38%) were positive correlations. We found significant differences between participants with and without advanced colorectal neoplasms for concentrations of 123, 49, and 28 metabolites in blood, stool and urine samples, respectively. We detected mostly positive correlations between metabolite concentrations in blood samples and urine or stool samples, and mostly negative correlations between urine and stool samples. Differences between subjects with and without advanced colorectal neoplasms were found for metabolite concentrations in each of the three bio-fluids.

Differentiation Unclean and Cleaned Edible Bird’s Nest using Multivariate Analysis of Amino Acid Composition Data

Edible Bird’s Nest (EBN) has been used as a health modulator for many centuries. Nutrient degradation in EBN always happen during cleaning process due to many factors such as temperature and long soaking time in water. The present study attempts to find the difference between unclean and cleaned EBN in their amino acid composition. A total of 65 EBN samples were collected directly from swiftlet premises in 13 states of Malaysia to ensure the coverage of geographical location differences. A standardized cleaning method had been adapted from the industry to clean the collected EBN sample in the lab. Then it was analysed for amino acids composition. After that OPLS-DA multivariate model was used to discriminate the unclean and cleaned EBN on 18 types of amino acids composition. The model was robust with classification and predictive ability of 76.1% and 64.5%, respectively. The model was further validated with sample blind test and 100% of the sample was accurately fall into their respective cluster, unclean and cleaned EBN. The findings suggest that three major amino acids with the highest VIP value were Aspartic acid, Methionine and Glutamic acid and proposed as the marker for discriminating the unclean and cleaned EBN.

A Review of GC-Based Analysis of Non-Invasive Biomarkers of Colorectal Cancer and Related Pathways

Colorectal cancer (CRC) is the third most commonly diagnosed cancer in the world. In Europe, it is the second most common cause of cancer-related deaths. With the advent of metabolomics approaches, studies regarding the investigation of metabolite profiles related to CRC have been conducted, aiming to serve as a tool for early diagnosis. In order to provide further information about the current status of this field of research, 21 studies were systematically reviewed, regarding their main findings and analytical aspects. A special focus was given to the employment of matrices obtained non-invasively and the use of gas chromatography as the analytical platform. The relationship between the reported volatile and non-volatile biomarkers and CRC-related metabolic alterations was also explored, demonstrating that many of these metabolites are connected with biochemical pathways proven to be involved in carcinogenesis. The most commonly reported CRC indicators were hydrocarbons, aldehydes, amino acids and short-chain fatty acids. These potential biomarkers can be associated with both human and bacterial pathways and the analysis based on such species has the potential to be applied in the clinical practice as a low-cost screening method.

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.

Simultaneous Determination of 34 Amino Acids in Tumor Tissues from Colorectal Cancer Patients Based on the Targeted UHPLC-MS/MS Method

A targeted ultrahigh-performance liquid chromatography-tandem mass spectrometry (UHPLC-MS/MS) method was established and validated for the simultaneous determination of 34 amino acids in tissue samples from colorectal cancer (CRC) patients. The chromatographic separation was achieved on an Agilent ZORBAX SB-C₁₈ column (3.0 × 150 mm, 5 μm) with a binary gradient elution system (A, 0.02% heptafluorobutyric acid and 0.2% formic acid in water, v/v; B, methanol). The run time was 10 min. The multiple reaction monitoring mode was chosen with an electrospray ionization source operating in the positive ionization mode for data acquisition. The linear correlation coefficients were >0.99 for all the analytes in their corresponding calibration ranges. The sample was pretreated based on tissue homogenate and protein precipitation with a 100 mg aliquot sample. The average recovery and matrix effect for 34 amino acids and 3 internal standards were 39.00%∼146.95% and 49.45%∼173.63%, respectively. The intra- and interday accuracy for all the analytes ranged from -13.52% to 14.21% (RSD ≤8.57%) and from -14.52% to 12.59% (RSD ≤10.31%), respectively. Deviations of stability under different conditions were within ±15% for all the analytes. This method was applied to simultaneous quantification of 34 amino acids in tissue samples from 94 CRC patients.

Metabolomics Analysis of Aspirin's Effects in Human Colon Tissue and Associations with Adenoma Risk

Although substantial evidence supports aspirin's efficacy in colorectal cancer chemoprevention, key molecular mechanisms are uncertain. An untargeted metabolomics approach with high-resolution mass spectrometry was used to elucidate metabolic effects of aspirin treatment in human colon tissue. We measured 10,269 metabolic features in normal mucosal biopsies collected at colonoscopy after approximately 3 years of randomized treatment with placebo, 81 or 325 mg/day aspirin from 325 participants in the Aspirin/Folate Polyp Prevention Study. Linear regression was used to identify aspirin-associated metabolic features and network analysis was used to identify pathways and predict metabolite identities. Poisson regression was used to examine metabolic features associations with colorectal adenoma risk. We detected 471 aspirin-associated metabolic features. Aside from the carnitine shuttle, aspirin-associated metabolic pathways were largely distinct for 81 mg aspirin (e.g., pyrimidine metabolism) and 325 mg (e.g., arachidonic acid metabolism). Among aspirin-associated metabolic features, we discovered three that were associated with adenoma risk and could contribute to the chemopreventive effect of aspirin treatment, and which have also previously been associated with colorectal cancer: creatinine, glycerol 3-phosphate, and linoleate. The last two of these are in the glycerophospholipid metabolism pathway, which was associated with 81 mg aspirin treatment and provides precursors for the synthesis of eicosanoids from arachidonic acid upstream of cyclooxygenase inhibition by aspirin. Conversely, carnitine shuttle metabolites were increased with aspirin treatment and associated with increased adenoma risk. Thus, our untargeted metabolomics approach has identified novel metabolites and pathways that may underlie the effects of aspirin during early colorectal carcinogenesis.

An Integrated Multi-Disciplinary Perspectivefor Addressing Challenges of the Human Gut Microbiome

Our understanding of the human gut microbiome has grown exponentially. Advances in genome sequencing technologies and metagenomics analysis have enabled researchers to study microbial communities and their potential function within the context of a range of human gut related diseases and disorders. However, up until recently, much of this research has focused on characterizing the gut microbiological community structure and understanding its potential through system wide (meta) genomic and transcriptomic-based studies. Thus far, the functional output of these microbiomes, in terms of protein and metabolite expression, and within the broader context of host-gut microbiome interactions, has been limited. Furthermore, these studies highlight our need to address the issues of individual variation, and of samples as proxies. Here we provide a perspective review of the recent literature that focuses on the challenges of exploring the human gut microbiome, with a strong focus on an integrated perspective applied to these themes. In doing so, we contextualize the experimental and technical challenges of undertaking such studies and provide a framework for capitalizing on the breadth of insight such approaches afford. An integrated perspective of the human gut microbiome and the linkages to human health will pave the way forward for delivering against the objectives of precision medicine, which is targeted to specific individuals and addresses the issues and mechanisms in situ.

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).

Metaproteomic and Metabolomic Approaches for Characterizing the Gut Microbiome

The gut microbiome has been shown to play a significant role in human healthy and diseased states. The dynamic signaling that occurs between the host and microbiome is critical for the maintenance of host homeostasis. Analyzing the human microbiome with metaproteomics, metabolomics, and integrative multi-omics analyses can provide significant information on markers for healthy and diseased states, allowing for the eventual creation of microbiome-targeted treatments for diseases associated with dysbiosis. Metaproteomics enables functional activity information to be gained from the microbiome samples, while metabolomics provides insight into the overall metabolic states affecting/representing the host-microbiome interactions. Combining these functional -omic platforms together with microbiome composition profiling allows for a holistic overview on the functional and metabolic state of the microbiome and its influence on human health. Here the benefits of metaproteomics, metabolomics, and the integrative multi-omic approaches to investigating the gut microbiome in the context of human health and diseases are reviewed.

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.

Microbiome and colorectal cancer: Roles in carcinogenesis and clinical potential

The gastrointestinal tract harbors most of the microbiota associated with humans. In recent years, there has been a surge of interest in assessing the relationships between the gut microbiota and several gut alterations, including colorectal cancer. Changes in the gut microbiota in patients suffering colorectal cancer suggest a possible role of host-microbe interactions in the origin and development of this malignancy and, at the same time, open the door for novel ways of preventing, diagnosing, or treating this disease. In this review we survey current knowledge on the healthy microbiome of the gut and how it is altered in colorectal cancer and other related disease conditions. In describing past studies we will critically assess technical limitations of different approaches and point to existing challenges in microbiome research. We will have a special focus on host-microbiome interaction mechanisms that may be important to explain how dysbiosis can lead to chronic inflammation and drive processes that influence carcinogenesis and tumor progression in colon cancer. Finally, we will discuss the potential of recent developments of novel microbiota-based therapeutics and diagnostic tools for colorectal cancer.

Metabolomics Profiling on Different Stages of Colorectal Cancer: A Systematic Review

Colorectal cancer (CRC) is one of the leading causes of cancer-related deaths worldwide. Early diagnosis and accurate staging of the disease is vital to improve the prognosis. Metabolomics has been used to identify changes in metabolite profiles in the different stages of cancer in order to introduce new non-invasive molecular tools for staging. In this systematic review, we aim to identify the common metabolite changes in human biological samples and the dominant metabolic pathways associated with CRC progression. A broad systematic search was carried out from selected databases. Four reviewers screened and reviewed the titles, abstracts, and full-text articles according to the inclusion and exclusion criteria. Quality assessment was conducted on the eight articles which met the criteria. Data showed that the metabolites involved with redox status, energy metabolism and intermediates of amino acids, choline and nucleotides metabolism were the most affected during CRC progression. However, there were differences in the levels of individual metabolites detected between the studies, and this might be due to the study population, sample preparation, analytical platforms used and statistical tools. In conclusion, this systematic review highlights the changes in metabolites from early to late stages of CRC. Moreover, biomarkers for prognosis are important to reduce CRC-related mortality.

Metabolite quantification of faecal extracts from colorectal cancer patients and healthy controls

Colorectal cancer (CRC), a primary cause of morbidity and mortality worldwide is expected to rise in the coming years. A better understanding of the metabolic changes taking place during the disease progression is needed for effective improvements of screening strategies and treatments. In the present study, Nuclear Magnetic Resonance (NMR) metabolomics was used to quantify the absolute concentrations of metabolites in faecal extracts from two cohorts of CRC patients and healthy controls. The quantification of over 80 compounds revealed that patients with CRC had increased faecal concentrations of branched chain fatty acids (BCFA), isovalerate and isobutyrate plus valerate and phenylacetate but diminished concentrations of amino acids, sugars, methanol and bile acids (deoxycholate, lithodeoxycholate and cholate). These results suggest that alterations in microbial activity and composition could have triggered an increase in utilisation of host intestinal slough cells and mucins and led to an increase in BCFA, valerate and phenylacetate. Concurrently, a general reduction in the microbial metabolic function may have led to reduced levels of other components (amino acids, sugars and bile acids) normally produced under healthy conditions. This study provides a thorough listing of the most abundant compounds found in human faecal waters and presents a template for absolute quantification of metabolites. The production of BCFA and phenylacetate in colonic carcinogenesis warrants further investigations.

Evaluation of platelet indices as diagnostic biomarkers for colorectal cancer

Altered platelet indices, including platelet count (PC), mean platelet volume (MPV), platelet distribution width (PDW), and plateletcrit (PCT), have been found in various cancer types. This study aimed to evaluate the role of platelet indices as potential biomarkers for the diagnosis of colorectal cancer (CRC), and to assess the association between platelet indices and CRC clinicopathological characteristics. The study included 783 subjects with CRC, 463 subjects with colorectal adenomas (CA), and 689 control subjects from June 2015 to October 2017. All participants' clinicopathological characteristics were collected and analyzed. Here, we found that PC, MPV and PCT levels in CRC patients were significantly higher than those in CA patients and healthy participants (p < 0.001); however, PDW level in CRC patients was significantly higher than that in healthy participants while lower than that in CA patients. Receiver-operating characteristic (ROC) analysis indicated that combined detection of PCT and CEA appears to be a more effective marker to distinguish CRC patients from CA patients, with 70% sensitivity and 83% specificity. Among CRC patients, PC and PCT levels were associated with TNM stages and tumor size; MPV and PCT levels were associated with vascular invasion. Our findings suggest that altered PC, MPV and PCT levels might serve as potential biomarkers for the diagnosis and prognosis of CRC.

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.

Microbial markers in colorectal cancer detection and/or prognosis

Colorectal cancer (CRC) is the second leading cause of cancer worldwide. CRC is still associated with a poor prognosis among patients with advanced disease. On the contrary, due to its slow progression from detectable precancerous lesions, the prognosis for patients with early stages of CRC is encouraging. While most robust methods are invasive and costly, actual patient-friendly screening methods for CRC suffer of lack of sensitivity and specificity. Therefore, the development of sensitive, non-invasive and cost-effective methods for CRC detection and prognosis are necessary for increasing the chances of a cure. Beyond its beneficial functions for the host, increasing evidence suggests that the intestinal microbiota is a key factor associated with carcinogenesis. Many clinical studies have reported a disruption in the gut microbiota balance and an alteration in the faecal metabolome of CRC patients, suggesting the potential use of a microbial-based test as a non-invasive diagnostic and/or prognostic tool for CRC screening. This review aims to discuss the microbial signatures associated with CRC known to date, including dysbiosis and faecal metabolome alterations, and the potential use of microbial variation markers for non-invasive early diagnosis and/or prognostic assessment of CRC and advanced adenomas. We will finally discuss the possible use of these markers as predicators for treatment response and their limitations.

Aptamers: novelty tools for cancer biology

Although the term ‘cancer’ was still over two thousand years away of being coined, the first known cases of the disease date back to about 3000BC, in ancient Egypt. Five thousand years later, still lacking a cure, it has become one of the leading causes of death, killing over half a dozen million people yearly. So far, monoclonal antibodies are the most successful immune-therapy tools when it comes to fighting cancer. The number of clinical trials that use them has been increasing steadily during the past few years, especially since the Food and Drug Administration greenlit the use of the first immune-checkpoint blockade antibodies. However, albeit successful, this approach does come with the cost of auto-inflammatory toxicity. Taking this into account, the development of new therapeutic reagents with low toxicity becomes evident, particularly ones acting in tandem with the tools currently at our disposal. Ever since its discovery in the early nineties, aptamer technology has been used for a wide range of diagnostic and therapeutic applications. With similar properties to those of monoclonal antibodies, such as high-specificity of recognition and high-affinity binding, and the advantages of being developed using in vitro selection procedures, aptamers quickly became convenient building blocks for the generation of multifunctional constructs. In this review, we discuss the steps involved in the in vitro selection process that leads to functional aptamers - known as Systematic Evolution of Ligands by Exponential Enrichment - as well as the most recent applications of this technology in diagnostic and treatment of oncological illnesses. Moreover, we also suggest ways to improve such use.

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.

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.

Gut microbiome in chronic kidney disease: challenges and opportunities

More than 100 trillion microbial cells that reside in the human gut heavily influence nutrition, metabolism, and immune function of the host. Gut dysbiosis, seen commonly in patients with chronic kidney disease (CKD), results from qualitative and quantitative changes in host microbiome profile and disruption of gut barrier function. Alterations in gut microbiota and a myriad of host responses have been implicated in progression of CKD, increased cardiovascular risk, uremic toxicity, and inflammation. We present a discussion of dysbiosis, various uremic toxins produced from dysbiotic gut microbiome, and their roles in CKD progression and complications. We also review the gut microbiome in renal transplant, highlighting the role of commensal microbes in alteration of immune responses to transplantation, and conclude with therapeutic interventions that aim to restore intestinal dysbiosis.

Fecal Metabolome in Hmga1 Transgenic Mice with Polyposis: Evidence for Potential Screen for Early Detection of Precursor Lesions in Colorectal Cancer

Because colorectal cancer (CRC) remains a leading cause of cancer mortality worldwide, more accessible screening tests are urgently needed to identify early stage lesions. We hypothesized that highly sensitive, metabolic profile analysis of stool samples will identify metabolites associated with early stage lesions and could serve as a noninvasive screening test. We therefore applied traveling wave ion mobility mass spectrometry (TWIMMS) coupled with ultraperformance liquid chromatography (UPLC) to investigate metabolic aberrations in stool samples in a transgenic model of premalignant polyposis aberrantly expressing the gene encoding the high mobility group A (Hmga1) chromatin remodeling protein. Here, we report for the first time that the fecal metabolome of Hmga1 mice is distinct from that of control mice and includes metabolites previously identified in human CRC. Significant alterations were observed in fatty acid metabolites and metabolites associated with bile acids (hypoxanthine xanthine, taurine) in Hmga1 mice compared to controls. Surprisingly, a marked increase in the levels of distinctive short, arginine-enriched, tetra-peptide fragments was observed in the transgenic mice. Together these findings suggest that specific metabolites are associated with Hmga1-induced polyposis and abnormal proliferation in intestinal epithelium. Although further studies are needed, these data provide a compelling rationale to develop fecal metabolomic analysis as a noninvasive screening tool to detect early precursor lesions to CRC in humans.

Serum Cyr61 as a potential biomarker for diagnosis of colorectal cancer

PURPOSE

To determine the sensitivity and specificity of serum Cyr61 as a potential biomarker for the diagnosis of colorectal cancer (CRC) and to assess the association between serum Cyr61 level and CRC clinicopathological status.

METHODS

We used an enzyme-linked immunosorbent assay to measure serum Cyr61 in patients with CRC, patients with colorectal adenomas, and healthy controls. We also analyzed the relationship between serum Cyr61 and clinicopathological features of CRC patients. The levels of serum carcinoembryonic antigen (CEA) and carbohydrate antigen 19-9 (CA19-9) were quantified using the Roche Cobas 6000 Analyzer. The sensitivity and specificity of Cyr61, CEA, CA19-9 and CEA + CA19-9 were evaluated by receiver operating characteristic (ROC) analysis.

RESULTS

The serum level of Cyr61 was significantly increased in CRC patients compared with colorectal adenoma patients and healthy controls (p < 0.001). Furthermore, the area under the ROC curve for Cyr61 was 0.935 (95 % confidence interval 0.902-0.968), higher than that for CEA + CA19-9 (0.827, 95 % confidence interval: 0.783-0.871). Use of a Cyr61 cutoff value of 92.0 pg/mL allowed distinguishing CRC patients and healthy controls with a sensitivity of 83 % and a specificity of 97 %. Among CRC patients, an elevated level of serum Cyr61 was significantly associated with more advanced TNM stage (p < 0.0042), lymph node metastasis (p < 0.0088), and vascular invasion (p = 0.0027).

CONCLUSION

Cyr61 has potential as a serum biomarker for the diagnosis of CRC and for assessment of the clinicopathological status of CRC.

Noninvasive metabolic profiling for painless diagnosis of human diseases and disorders

Metabolic profiling provides a powerful diagnostic tool complementary to genomics and proteomics. The pain, discomfort and probable iatrogenic injury associated with invasive or minimally invasive diagnostic methods, render them unsuitable in terms of patient compliance and participation. Metabolic profiling of biomatrices like urine, breath, saliva, sweat and feces, which can be collected in a painless manner, could be used for noninvasive diagnosis. This review article covers the noninvasive metabolic profiling studies that have exhibited diagnostic potential for diseases and disorders. Their potential applications are evident in different forms of cancer, metabolic disorders, infectious diseases, neurodegenerative disorders, rheumatic diseases and pulmonary diseases. Large scale clinical validation of such diagnostic methods is necessary in future.

Metabolomics and metabolic pathway networks from human colorectal cancers, adjacent mucosa, and stool

Background

Colorectal cancers (CRC) are associated with perturbations in cellular amino acids, nucleotides, pentose-phosphate pathway carbohydrates, and glycolytic, gluconeogenic, and tricarboxylic acid intermediates. A non-targeted global metabolome approach was utilized for exploring human CRC, adjacent mucosa, and stool. In this pilot study, we identified metabolite profile differences between CRC and adjacent mucosa from patients undergoing colonic resection. Metabolic pathway analyses further revealed relationships between complex networks of metabolites.

Methods

Seventeen CRC patients participated in this pilot study and provided CRC, adjacent mucosa ~10 cm proximal to the tumor, and stool. Metabolomes were analyzed by gas chromatography-mass spectrometry (GC/MS) and ultra-performance liquid chromatography-mass spectrometry (UPLC-MS/MS). All of the library standard identifications were confirmed and further analyzed via MetaboLync^TM for metabolic network interactions.

Results

There were a total of 728 distinct metabolites identified from colonic tissue and stool matrices. Nineteen metabolites significantly distinguished CRC from adjacent mucosa in our patient-matched cohort. Glucose-6-phosphate and fructose-6-phosphate demonstrated 0.64-fold and 0.75-fold lower expression in CRC compared to mucosa, respectively, whereas isobar: betaine aldehyde, N-methyldiethanolamine, and adenylosuccinate had 2.68-fold and 1.88-fold higher relative abundance in CRC. Eleven of the 19 metabolites had not previously been reported for CRC relevance. Metabolic pathway analysis revealed significant perturbations of short-chain fatty acid metabolism, fructose, mannose, and galactose metabolism, and glycolytic, gluconeogenic, and pyruvate metabolism. In comparison to the 500 stool metabolites identified from human CRC patients, only 215 of those stool metabolites were also detected in tissue. This CRC and stool metabolome investigation identified novel metabolites that may serve as key small molecules in CRC pathogenesis, confirmed the results from previously reported CRC metabolome studies, and showed networks for metabolic pathway aberrations. In addition, we found differences between the CRC and stool metabolomes.

Conclusions

Stool metabolite profiles were limited for direct associations with CRC and adjacent mucosa, yet metabolic pathways were conserved across both matrices. Larger patient-matched CRC, adjacent non-cancerous colonic mucosa, and stool cohort studies for metabolite profiling are needed to validate these small molecule differences and metabolic pathway aberrations for clinical application to CRC control, treatment, and prevention.

Electronic supplementary material

The online version of this article (doi:10.1186/s40170-016-0151-y) contains supplementary material, which is available to authorized users.

NMR-based fecal metabolomics fingerprinting as predictors of earlier diagnosis in patients with colorectal cancer

Colorectal cancer (CRC) is a growing cause of mortality in developing countries, warranting investigation into its earlier detection for optimal disease management. A metabolomics based approach provides potential for noninvasive identification of biomarkers of colorectal carcinogenesis, as well as dissection of molecular pathways of pathophysiological conditions. Here, proton nuclear magnetic resonance spectroscopy (1HNMR) -based metabolomic approach was used to profile fecal metabolites of 68 CRC patients (stage I/II=20; stage III=25 and stage IV=23) and 32 healthy controls (HC). Pattern recognition through principal component analysis (PCA) and orthogonal partial least squares-discriminant analysis (OPLS-DA) was applied on 1H-NMR processed data for dimension reduction. OPLS-DA revealed that each stage of CRC could be clearly distinguished from HC based on their metabolomic profiles. Successive analyses identified distinct disturbances to fecal metabolites of CRC patients at various stages, compared with those in cancer free controls, including reduced levels of acetate, butyrate, propionate, glucose, glutamine, and elevated quantities of succinate, proline, alanine, dimethylglycine, valine, glutamate, leucine, isoleucine and lactate. These altered fecal metabolites potentially involved in the disruption of normal bacterial ecology, malabsorption of nutrients, increased glycolysis and glutaminolysis. Our findings revealed that the fecal metabolic profiles of healthy controls can be distinguished from CRC patients, even in the early stage (stage I/II), highlighting the potential utility of NMR-based fecal metabolomics fingerprinting as predictors of earlier diagnosis in CRC patients.

(1)H NMR Spectroscopy of Fecal Extracts Enables Detection of Advanced Colorectal Neoplasia

Colorectal cancer (CRC) is a growing cause of mortality in developing countries, warranting investigation into its etiopathogenesis and earlier diagnosis. Here, we investigated the fecal metabolic phenotype of patients with advanced colorectal neoplasia and controls using (1)H-nuclear magnetic resonance (NMR) spectroscopy and multivariate modeling. The fecal microbiota composition was assessed by quantitative real-time PCR as well as Wif-1 methylation levels in stools, serum, and urine and correlated to the metabolic profile of each patient. The predictivity of the model was 0.507 (Q(2)Y), and the explained variance was 0.755 (R(2)Y). Patients with advanced colorectal neoplasia demonstrated increased fecal concentrations of four short-chain fatty acids (valerate, acetate, propionate, and butyrate) and decreased signals relating to β-glucose, glutamine, and glutamate. The predictive accuracy of the multivariate (1)H NMR model was higher than that of the guaiac-fecal occult blood test and the Wif-1 methylation test for predicting advanced colorectal neoplasia. Correlation analysis between fecal metabolites and bacterial profiles revealed strong associations between Faecalibacterium prausnitzii and Clostridium leptum species with short-chain fatty acids concentration and inverse correlation between Faecalibacterium prausnitzii and glucose. These preliminary results suggest that fecal metabonomics may potentially have a future role in a noninvasive colorectal screening program and may contribute to our understanding of the role of these dysregulated molecules in the cross-talk between the host and its bacterial microbiota.

The promise of metabolic phenotyping in gastroenterology and hepatology

Disease risk and treatment response are determined, at the individual level, by a complex history of genetic and environmental interactions, including those with our endogenous microbiomes. Personalized health care requires a deep understanding of patient biology that can now be measured using a range of '-omics' technologies. Patient stratification involves the identification of genetic and/or phenotypic disease subclasses that require different therapeutic strategies. Stratified medicine approaches to disease diagnosis, prognosis and therapeutic response monitoring herald a new dimension in patient care. Here, we explore the potential value of metabolic profiling as applied to unmet clinical needs in gastroenterology and hepatology. We describe potential applications in a number of diseases, with emphasis on large-scale population studies as well as metabolic profiling on the individual level, using spectrometric and imaging technologies that will leverage the discovery of mechanistic information and deliver novel health care solutions to improve clinical pathway management.

Application of metagenomics in the human gut microbiome

There are more than 1000 microbial species living in the complex human intestine. The gut microbial community plays an important role in protecting the host against pathogenic microbes, modulating immunity, regulating metabolic processes, and is even regarded as an endocrine organ. However, traditional culture methods are very limited for identifying microbes. With the application of molecular biologic technology in the field of the intestinal microbiome, especially metagenomic sequencing of the next-generation sequencing technology, progress has been made in the study of the human intestinal microbiome. Metagenomics can be used to study intestinal microbiome diversity and dysbiosis, as well as its relationship to health and disease. Moreover, functional metagenomics can identify novel functional genes, microbial pathways, antibiotic resistance genes, functional dysbiosis of the intestinal microbiome, and determine interactions and co-evolution between microbiota and host, though there are still some limitations. Metatranscriptomics, metaproteomics and metabolomics represent enormous complements to the understanding of the human gut microbiome. This review aims to demonstrate that metagenomics can be a powerful tool in studying the human gut microbiome with encouraging prospects. The limitations of metagenomics to be overcome are also discussed. Metatranscriptomics, metaproteomics and metabolomics in relation to the study of the human gut microbiome are also briefly discussed.

Emerging field of metabolomics: big promise for cancer biomarker identification and drug discovery

Most cancers are lethal and metabolic alterations are considered a hallmark of this deadly disease. Genomics and proteomics have contributed vastly to understand cancer biology. Still there are missing links as downstream to them molecular divergence occurs. Metabolomics, the omic science that furnishes a dynamic portrait of metabolic profile is expected to bridge these gaps and boost cancer research. Metabolites being the end products are more stable than mRNAs or proteins. Previous studies have shown the efficacy of metabolomics in identifying biomarkers associated with diagnosis, prognosis and treatment of cancer. Metabolites are highly informative about the functional status of the biological system, owing to their proximity to organismal phenotypes. Scores of publications have reported about high-throughput data generation by cutting-edge analytic platforms (mass spectrometry and nuclear magnetic resonance). Further sophisticated statistical softwares (chemometrics) have enabled meaningful information extraction from the metabolomic data. Metabolomics studies have demonstrated the perturbation in glycolysis, tricarboxylic acid cycle, choline and fatty acid metabolism as traits of cancer cells. This review discusses the latest progress in this field, the future trends and the deficiencies to be surmounted for optimally implementation in oncology. The authors scoured through the most recent, high-impact papers archived in Pubmed, ScienceDirect, Wiley and Springer databases to compile this review to pique the interest of researchers towards cancer metabolomics.