Evaluating Ultra-long-Chain Fatty Acids as Biomarkers of Colorectal Cancer Risk

Untargeted plasma metabolomics and risk of colorectal cancer-an analysis nested within a large-scale prospective cohort

BACKGROUND

Colorectal cancer (CRC) is a leading cause of cancer-related death worldwide, but if discovered at an early stage, the survival rate is high. The aim of this study was to identify novel markers predictive of future CRC risk using untargeted metabolomics.

METHODS

This study included prospectively collected plasma samples from 902 CRC cases and 902 matched cancer-free control participants from the population-based Northern Sweden Health and Disease Study (NSHDS), which were obtained up to 26 years prior to CRC diagnosis. Using reverse-phase liquid chromatography-mass spectrometry (LC-MS), data comprising 5015 metabolic features were obtained. Conditional logistic regression was applied to identify potentially important metabolic features associated with CRC risk. In addition, we investigated if previously reported metabolite biomarkers of CRC risk could be validated in this study population.

RESULTS

In the univariable analysis, seven metabolic features were associated with CRC risk (using a false discovery rate cutoff of 0.25). Two of these could be annotated, one as pyroglutamic acid (odds ratio per one standard deviation increase = 0.79, 95% confidence interval, 0.70-0.89) and another as hydroxytigecycline (odds ratio per one standard deviation increase = 0.77, 95% confidence interval, 0.67-0.89). Associations with CRC risk were also found for six previously reported metabolic biomarkers of prevalent and/or incident CRC: sebacic acid (inverse association) and L-tryptophan, 3-hydroxybutyric acid, 9,12,13-TriHOME, valine, and 13-OxoODE (positive associations).

CONCLUSIONS

These findings suggest that although the circulating metabolome may provide new etiological insights into the underlying causes of CRC development, its potential application for the identification of individuals at higher risk of developing CRC is limited.

HSA Adductomics Reveals Sex Differences in NHL Incidence and Possible Involvement of Microbial Translocation

BACKGROUND

The higher incidence of non-Hodgkin lymphoma (NHL) in males is not well understood. Although reactive oxygen species (ROS) have been implicated as causes of NHL, they cannot be measured directly in archived blood.

METHODS

We performed untargeted adductomics of stable ROS adducts in human serum albumin (HSA) from 67 incident NHL cases and 82 matched controls from the European Prospective Investigation into Cancer and Nutrition-Italy cohort. Regression and classification methods were employed to select features associated with NHL in all subjects and in males and females separately.

RESULTS

Sixty seven HSA-adduct features were quantified by liquid chromatography-high-resolution mass spectrometry at Cys34 (n = 55) and Lys525 (n = 12). Three features were selected for association with NHL in all subjects, while seven were selected for males and five for females with minimal overlap. Two selected features were more abundant in cases and seven in controls, suggesting that altered homeostasis of ROS may affect NHL incidence. Heat maps revealed differential clustering of features between sexes, suggesting differences in operative pathways.

CONCLUSIONS

Adduct clusters dominated by Cys34 oxidation products and disulfides further implicate ROS and redox biology in the etiology of NHL. Sex differences in dietary and alcohol consumption also help to explain the limited overlap of feature selection between sexes. Intriguingly, a disulfide of methanethiol from enteric microbial metabolism was more abundant in male cases, thereby implicating microbial translocation as a potential contributor to NHL in males.

IMPACT

Only two of the ROS adducts associated with NHL overlapped between sexes and one adduct implicates microbial translocation as a risk factor.

Risk-Predictive and Diagnostic Biomarkers for Colorectal Cancer; a Systematic Review of Studies Using Pre-Diagnostic Blood Samples Collected in Prospective Cohorts and Screening Settings

This systematic review summarizes the evidence for blood-based colorectal cancer biomarkers from studies conducted in pre-diagnostic, asymptomatic settings. Of 1372 studies initially identified, the final selection included 30 studies from prospective cohorts and 23 studies from general screening settings. Overall, the investigations had high quality but considerable variability in data analysis and presentation of results, and few biomarkers demonstrated a clinically relevant discriminatory ability. One of the most promising biomarkers was the anti-p53 antibody, with consistent findings in one screening cohort and in the 3-4 years prior to diagnosis in two prospective cohort studies. Proteins were the most common type of biomarker assessed, particularly carcinoembryonic antigen (CEA) and C-reactive protein (CRP), with modest results. Other potentially promising biomarkers included proteins, such as AREG, MIC-1/GDF15, LRG1 and FGF-21, metabolites and/or metabolite profiles, non-coding RNAs and DNA methylation, as well as re-purposed routine lab tests, such as ferritin and the triglyceride-glucose index. Biomarker panels generally achieved higher discriminatory performance than single markers. In conclusion, this systematic review highlighted anti-p53 antibodies as a promising blood-based biomarker for use in colorectal cancer screening panels, together with other specific proteins. It also underscores the need for validation of promising biomarkers in independent pre-diagnostic settings.

Untargeted metabolomics of newborn dried blood spots reveals sex-specific associations with pediatric acute myeloid leukemia

The etiology of pediatric acute myeloid leukemia (AML) is largely unknown, but evidence for mutations in utero and long latency periods suggests that environmental factors play a role. Therefore, we used untargeted metabolomics of archived newborn dried blood spots (DBS) to investigate neonatal exposures as potential causal risk factors for AML. Untargeted metabolomics profiling was performed on DBS punches from 48 pediatric patients with AML and 46 healthy controls as part of the California Childhood Leukemia Study (CCLS). Because sex disparities are suggested by differences in AML incidence rates, metabolite features associated with AML were identified in analyses stratified by sex. There was no overlap between the 16 predictors of AML in females and 15 predictors in males, suggesting that neonatal metabolomic profiles of pediatric AML risk are sex-specific. In females, four predictors of AML were putatively annotated as ceramides, a class of metabolites that has been linked with cancer cell proliferation. In females, two metabolite predictors of AML were strongly correlated with breastfeeding duration, indicating a possible biological link between this putative protective risk factor and childhood leukemia. In males, a heterogeneous metabolite profile of AML predictors was observed. Replication with larger participant numbers is required to validate findings.

Metabolic Drug Response Phenotyping in Colorectal Cancer Organoids by LC-QTOF-MS

As metabolic rewiring is crucial for cancer cell proliferation, metabolic phenotyping of patient-derived organoids is desirable to identify drug-induced changes and trace metabolic vulnerabilities of tumor subtypes. We established a novel protocol for metabolomic and lipidomic profiling of colorectal cancer organoids by liquid chromatography quadrupole time-of-flight mass spectrometry (LC-QTOF-MS) facing the challenge of capturing metabolic information from a minimal sample amount (<500 cells/injection) in the presence of an extracellular matrix (ECM). The best procedure of the tested protocols included ultrasonic metabolite extraction with acetonitrile/methanol/water (2:2:1, v/v/v) without ECM removal. To eliminate ECM-derived background signals, we implemented a data filtering procedure based on the p-value and fold change cut-offs, which retained features with signal intensities >120% compared to matrix-derived signals present in blank samples. As a proof-of-concept, the method was applied to examine the early metabolic response of colorectal cancer organoids to 5-fluorouracil treatment. Statistical analysis revealed dose-dependent changes in the metabolic profiles of treated organoids including elevated levels of 2′-deoxyuridine, 2′-O-methylcytidine, inosine and 1-methyladenosine and depletion of 2′-deoxyadenosine and specific phospholipids. In accordance with the mechanism of action of 5-fluorouracil, changed metabolites are mainly involved in purine and pyrimidine metabolism. The novel protocol provides a first basis for the assessment of metabolic drug response phenotypes in 3D organoid models.

A conjunctive lipidomic approach reveals plasma ethanolamine plasmalogens and fatty acids as early diagnostic biomarkers for colorectal cancer patients

Background: Colorectal cancer (CRC) represents a third leading cause of cancer-related death worldwide. The reliable diagnostic biomarkers for detecting CRC at early stage is critical for decreasing the mortality.Method: A conjunctive lipidomic approach was employed to investigate the differences in plasma lipid profiles of CRC patients (n = 101) and healthy volunteers (n = 52). Based on UHPLC-Q-TOF MS and UHPLC-QQQ MS platforms, a total of 236 lipids were structurally detected. Multivariate data analysis was conducted for biomarkers discovery.Results: A total of 11 lipid species, including 1 Glycerophosphoethanolamine (PE), 3 ethanolamine plasmalogens (PlsEtn), 1 plasmanyl glycerophosphatidylethanolamine (PE-O), 3 fatty acids (FFA), 1 Fatty acid ester of hydroxyl fatty acid (FAHFA) and 2 Diacylglycerophosphates (PA) were identified to distinguish the CRC patients at early stage from healthy controls. In addition, these potential lipid biomarkers achieved an estimated AUC=0.981 in a validation set for univariate ROC analysis.Conclusion: By combining Q-TOF MS and QQQ MS analysis, the 11 lipids exhibited good performance in differentiating early-stage CRC and healthy control. This study also demonstrated that lipidomics is a powerful tool in discovering new potential biomarkers for cancer diagnosis.

Cys34 Adductomics Links Colorectal Cancer with the Gut Microbiota and Redox Biology

Chronic inflammation is an established risk factor for colorectal cancer. To study reactive products of gut inflammation and redox signaling on colorectal cancer development, we used untargeted adductomics to detect adduct features in prediagnostic serum from the EPIC Italy cohort. We focused on modifications to Cys34 in human serum albumin, which is responsible for scavenging small reactive electrophiles that might initiate cancers. Employing a combination of statistical methods, we selected seven Cys34 adducts associated with colorectal cancer, as well as body mass index (BMI; a well-known risk factor). Five adducts were more abundant in colorectal cancer cases than controls and clustered with each other, suggesting a common pathway. Because two of these adducts were Cys34 modifications by methanethiol, a microbial-human cometabolite, and crotonaldehyde, a product of lipid peroxidation, these findings further implicate infiltration of gut microbes into the intestinal mucosa and the corresponding inflammatory response as causes of colorectal cancer. The other two associated adducts were Cys34 disulfides of homocysteine that were less abundant in colorectal cancer cases than controls and may implicate homocysteine metabolism as another causal pathway. The selected adducts and BMI ranked higher as potentially causal factors than variables previously associated with colorectal cancer (smoking, alcohol consumption, physical activity, and total meat consumption). Regressions of case-control differences in adduct levels on days to diagnosis showed no statistical evidence that disease progression, rather than causal factors at recruitment, contributed to the observed differences. These findings support the hypothesis that infiltration of gut microbes into the intestinal mucosa and the resulting inflammation are causal factors for colorectal cancer. SIGNIFICANCE: Infiltration of gut microbes into the intestinal mucosa and the resulting inflammation are causal factors for colorectal cancer.

Filtering procedures for untargeted LC-MS metabolomics data

Background

Untargeted metabolomics datasets contain large proportions of uninformative features that can impede subsequent statistical analysis such as biomarker discovery and metabolic pathway analysis. Thus, there is a need for versatile and data-adaptive methods for filtering data prior to investigating the underlying biological phenomena. Here, we propose a data-adaptive pipeline for filtering metabolomics data that are generated by liquid chromatography-mass spectrometry (LC-MS) platforms. Our data-adaptive pipeline includes novel methods for filtering features based on blank samples, proportions of missing values, and estimated intra-class correlation coefficients.

Results

Using metabolomics datasets that were generated in our laboratory from samples of human blood, as well as two public LC-MS datasets, we compared our data-adaptive filtering method with traditional methods that rely on non-method specific thresholds. The data-adaptive approach outperformed traditional approaches in terms of removing noisy features and retaining high quality, biologically informative ones. The R code for running the data-adaptive filtering method is provided at https://github.com/courtneyschiffman/Metabolomics-Filtering.

Conclusions

Our proposed data-adaptive filtering pipeline is intuitive and effectively removes uninformative features from untargeted metabolomics datasets. It is particularly relevant for interrogation of biological phenomena in data derived from complex matrices associated with biospecimens.

Electronic supplementary material

The online version of this article (10.1186/s12859-019-2871-9) contains supplementary material, which is available to authorized users.

Changes in lipids composition and metabolism in colorectal cancer: a review

Altered metabolism of lipids is currently considered a hallmark characteristic of many malignancies, including colorectal cancer (CRC). Lipids are a large group of metabolites that differ in terms of their fatty acid composition. This review summarizes recent evidence, documenting many alterations in the content and composition of fatty acids, polar lipids, oxylipins and triacylglycerols in CRC patients' sera, tumor tissues and adipose tissue. Some of altered lipid molecules may be potential biomarkers of CRC risk, development and progression. Owing to a significant role of many lipids in cancer cell metabolism, some of lipid metabolism pathways may also constitute specific targets for anti-CRC therapy.

Untargeted lipidomic features associated with colorectal cancer in a prospective cohort

BACKGROUND

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

Redefining environmental exposure for disease etiology

Etiological studies of human exposures to environmental factors typically rely on low-throughput methods that target only a few hundred chemicals or mixtures. In this Perspectives article, I outline how environmental exposure can be defined by the blood exposome—the totality of chemicals circulating in blood. The blood exposome consists of chemicals derived from both endogenous and exogenous sources. Endogenous chemicals are represented by the human proteome and metabolome, which establish homeostatic networks of functional molecules. Exogenous chemicals arise from diet, vitamins, drugs, pathogens, microbiota, pollution, and lifestyle factors, and can be measured in blood as subsets of the proteome, metabolome, metals, macromolecular adducts, and foreign DNA and RNA. To conduct ‘exposome-wide association studies’, blood samples should be obtained prospectively from subjects—preferably at critical stages of life—and then analyzed in incident disease cases and matched controls to find discriminating exposures. Results from recent metabolomic investigations of archived blood illustrate our ability to discover potentially causal exposures with current technologies.