Identification of Serum Markers of Esophageal Adenocarcinoma by Global and Targeted Metabolic Profiling

Metabolomics for searching validated biomarkers in cancer studies: a decade in review

INTRODUCTION

In the dynamic landscape of modern healthcare, the ability to anticipate and diagnose diseases, particularly in cases where early treatment significantly impacts outcomes, is paramount. Cancer, a complex and heterogeneous disease, underscores the critical importance of early diagnosis for patient survival. The integration of metabolomics information has emerged as a crucial tool, complementing the genotype-phenotype landscape and providing insights into active metabolic mechanisms and disease-induced dysregulated pathways.

AREAS COVERED

This review explores a decade of developments in the search for biomarkers validated within the realm of cancer studies. By critically assessing a diverse array of research articles, clinical trials, and studies, this review aims to present an overview of the methodologies employed and the progress achieved in identifying and validating biomarkers in metabolomics results for various cancer types.

EXPERT OPINION

Through an exploration of more than 800 studies, this review has allowed to establish a general idea about state-of-art in the search of biomarkers in metabolomics studies involving cancer which include certain level of results validation. The potential for metabolites as diagnostic markers to reach the clinic and make a real difference in patient health is substantial, but challenges remain to be explored.

HPLC for simultaneous quantification of free mannose and glucose concentrations in serum: use in detection of ovarian cancer

Background: Abnormal levels of monosaccharides in blood have been linked to tumorigenesis. In this study, a novel high-performance liquid chromatography (HPLC) method was established for the simultaneous determination of free mannose and glucose in the serum. Methods: The serum was directly derivatized by 1-phenyl-3-methyl-5-pyrazolone under alkaline conditions using L-rhamnose as an internal standard. The chromatographic separation was then performed on a Poroshell EC-C18 chromatographic column (4.6 × 100 mm, particle size 2.7 μm, Agilent) with gradient elution using NH4Ac-HAc and acetonitrile as the mobile phases. The method was thereafter validated according to international guidelines. The serum samples obtained from 200 healthy individuals and 200 ovarian cancer (OC) patients were analyzed for free mannose and glucose. Results: The method was found to be reproducible for quantification within 20 min and included online sample purification. The method displayed excellent linearity in the concentration range (for mannose: 0.5-500 μg/mL; glucose: 0.5-1500 μg/mL). The precision, recovery, and stability met the FDA bioanalytical method validation acceptance criteria. Overall, the measurement of glucose content by HPLC correlated well with the different enzymatic methods. Ovarian cancer mannose levels in the serum were significantly higher in the advanced stage (61.22 μmol/L, p < 0.0001) than those in healthy volunteers and early-stage patients (44.51 μmol/L versus 50.09 μmol/L, p < 0.0001). The AUC for the ratio of serum free glucose to mannose (G/M) was 0.98 (p < 0.0001), with a sensitivity of 91.46% and a specificity of 98.50%, which served as a biomarker for OC diagnosis. Conclusion: We report a simple, repeatable, and attractive analytical method by HPLC, which can be used for quantitative estimation of free mannose and glucose simultaneously in human serum. Our results indicate that the serum level of mannose could be used as a potential biomarker of ovarian cancer.

Serum metabolite signatures in normal individuals and patients with colorectal adenoma or colorectal cancer using UPLC-MS/MS method

Colorectal cancer (CRC) is one of the main causes of cancer-related deaths worldwide. Sporadic CRC develops from normal mucosa via adenoma to adenocarcinoma, which provides a long screening window for clinical detection. However, early diagnosis of sporadic colorectal adenoma (CRA) and CRC using serum metabolic screening remains unclear. The purpose of this study was to identify some promising signatures for distinguishing the different pathological metabolites of colorectal mucosal malignant transformation. A total of 238 endogenous metabolites were elected. We found that CRA and CRC patients had 72 and 73 different metabolites compared with healthy controls, respectively. There were 20 different metabolites between CRA and CRC patients. The potential metabolites of tumor growth (including patients with CRA and CRC) were found, such as A-d-glucose, D-mannose, N-acetyl-D-glucosamine, L-cystine, Sarcosine, TXB 2, 12-Hete, and chenodeoxycholic acid. Compared with CRA, 3,4,5-trimethoxybenzoic acid was significantly higher in CRC patients. There results prompt us to use the potential serum signatures to screen CRC as the novel strategy. Serum metabolite screening is useful for early detection of mucosal intestinal malignancy. We will further investigate the roles of these promising biomarkers during intestinal tumorigenesis in future. SIGNIFICANCE: CRC is one of the main causes of cancer-related deaths worldwide. Sporadic CRC develops from normal mucosa via adenomas to adenocarcinoma, which provides a long screening window for about 5-10 years. We adopt the metabolic analysis of extensive targeted metabolic technology. The main purpose of the metabolic group analysis is to detect and screen the different metabolites, thereby performing related functional prediction and analysis of the differential metabolites. In our study, 30 samples are selected, divided into 3 groups for metabolic analysis, and 238 metabolites are elected. In 238 metabolites, we find that CRA patients have 72 different metabolites compared with health control. Compared with health control, CRC have 73 different metabolites. Compared with CRA and CRC patients, there are 20 different metabolites. The annotation results of the significantly different metabolites are classified according to the KEGG pathway type. The potential metabolites of tumor growth stage (including patients with CRA and CRC) are found, such as A-d-glucose, D-mannose, N-acetyl-D-glucosamine, L-cystine, sarcosine, TXB 2, 12-Hete and chenodeoxycholic acid. Compared with CRA patients, CRC patients had significantly higher 3,4,5-trimethoxybenzoic acid level. It is prompted to use serum different metabolites to screen CRC to provide new possibilities.

Mannose enhances the radio-sensitivity of esophageal squamous cell carcinoma with low MPI expression by suppressing glycolysis

BACKGROUND

To investigate the effect of mannose on radio-sensitivity of human esophageal squamous cell carcinoma (ESCC) cell line and its possible mechanism.

METHODS

The expression of mannose phosphate isomerase (MPI) in human esophageal cancer cell lines were detected by Western blot. The inhibitory effect of mannose on human esophageal cancer cell lines were observed by MTT assay. Plate clone formation assay was performed to investigate the efficacy of mannose on radio-sensitivity of human esophageal cancer cells. The apoptosis rates of tumor cells treated with mannose and/or radiation therapy was calculated by flow cytometry. Furthermore, we analyzed intracellular metabolites using liquid chromatography mass spectrometry to identify selective sugar metabolites.

RESULTS

MPI expression was various in human esophageal cancer cells. KYSE70 cells was associated with the highest MPI expression whereas KYSE450 cells had the lowest MPI expression level. When administrated with 11.1 mM/L mannose, the same inhibitory effect was observed in both KYSE70 and KYSE450 cell lines. Moreover, the inhibitory effect was significant on KYSE450 cell lines with an increased mannose concentration. The application of 11.1 mM/L mannose could significantly enhance the radio-sensitivity of KYSE450 cell line; and tumor cell apoptosis rate was also increased. However, there was limited efficacy of mannose on the radio-sensitivity and apoptosis rate of KYSE70 cell line. Additionally, intracellular metabolites analyzation revealed that glycolysis could be disturbed by mannose when combined with radiation therapy in esophageal cancer cells.

CONCLUSION

In esophageal cancer cell lines with low MPI expression, the administration of mannose was associated with enhanced radio-sensitivity.

MPI-based bioinformatic analysis and co-inhibitory therapy with mannose for oral squamous cell carcinoma

Mannose induces tumor cell apoptosis and inhibits glucose metabolism by accumulating intracellularly as mannose 6-phosphate while the drug sensitivity of tumors is negatively correlated with mannose phosphate isomerase gene (MPI) expression. In this study, we performed a first attempt to explore the relationship between the targeted gene MPI and immune infiltration and genetic and clinical characteristics of head and neck squamous carcinoma (HNSC) using computational algorithms and bioinformatic analysis, and further to verify the co-inhibition effects of mannose with genotoxicity, immune responses, and microbes dysbiosis in oral squamous cell carcinoma (OSCC) in vitro and in vivo. Our results found that patients with lower MPI expression had higher survival rate. The enhancement of MPI expression was in response to DNA damage gene, and ATM inhibitor was verified as a potential drug with a synergistic effect with mannose on HSC-3. In the HNSC, infiltrated immunocytes CD8⁺ T cell and B cell were the significantly reduced risk cells, while IL-22 and IFN-γ showed negative correlation with MPI. Finally, mannose could reverse immunophenotyping caused by antibiotics in mice, resulting in the decrease of CD8⁺ T cells and increase of myeloid-derived suppressor cells (MDSCs). In conclusion, the MPI gene showed a significant correlation with immune infiltration and genetic and clinical characteristics of HNSC. The treatment of ATM inhibitor, immune regulating cells of CD8⁺ T cells and MDSCs, and oral microbiomes in combination with mannose could exhibit co-inhibitory therapeutic effect for OSCC.

Modern Diagnosis of Early Esophageal Cancer: From Blood Biomarkers to Advanced Endoscopy and Artificial Intelligence

Simple Summary

Esophageal cancer (EC) has a poor prognosis when the diagnosis is delayed, but curative treatment is possible if the diagnosis is timely. The disease subtly progresses before symptoms prompt patients to seek medical attention. Effective pre-symptomatic screening strategies may improve the outcome of the disease. Recent evidence provided insights into early diagnosis of EC via blood tests, advanced endoscopic imaging, and artificial intelligence. Accordingly, we reviewed available strategies to diagnose early EC.

Abstract

Esophageal cancer (EC) is the seventh most common cancer and the sixth cause of cancer death worldwide. Histologically, esophageal squamous cell carcinoma (ESCC) and esophageal adenocarcinoma (EAC) account for up to 90% and 20% of all ECs, respectively. Clinical symptoms such as dysphagia, odynophagia, and bolus impaction occur late in the natural history of the disease, and the diagnosis is often delayed. The prognosis of ESCC and EAC is poor in advanced stages, being survival rates less than 20% at five years. However, when the diagnosis is achieved early, curative treatment is possible, and survival exceeds 80%. For these reasons, mass screening strategies for EC are highly desirable, and several options are currently under investigation. Blood biomarkers offer an inexpensive, non-invasive screening strategy for cancers, and novel technologies have allowed the identification of candidate markers for EC. The esophagus is easily accessible via endoscopy, and endoscopic imaging represents the gold standard for cancer surveillance. However, lesion recognition during endoscopic procedures is hampered by interobserver variability. To fill this gap, artificial intelligence (AI) has recently been explored and provided encouraging results. In this review, we provide a summary of currently available options to achieve early diagnosis of EC, focusing on blood biomarkers, advanced endoscopy, and AI.

Efficacy of Analytical Technologies in Metabolomics Studies of the Gastrointestinal Cancers

According to the reports of the World Health Organization and the International Agency for Research on Cancer, cancer is the second leading cause of human death worldwide. However, early-stage detection of cancers can efficiently enhance the chance of therapy and saving lives. Metabolomics strategies apply a variety of approaches to discover new potential diagnoses, prognoses, and/or therapeutic biomarkers of various diseases. Metabolomics aims to identify and measure different low-molecular-weight biomolecules in physiological environments. In these studies, special metabolites are extracted from biological samples and identified using analytical techniques. Afterward, using data processing programs discovering significantly associated biomarkers is pursued. In the present review, we aimed to discuss recently reported analytical approaches on the metabolomics studies of gastrointestinal cancers including gastric, colorectal, and esophageal cancers. The gas- and liquid-chromatography with different detectors have been shown that are the main analytical techniques and for metabolites quantification, nuclear magnetic resonance has been utilized as a master method.

A Transcriptional Regulatory Loop of Master Regulator Transcription Factors, PPARG, and Fatty Acid Synthesis Promotes Esophageal Adenocarcinoma

Although obesity is one of the strongest risk factors for esophageal adenocarcinoma, the molecular mechanisms underlying this association remain unclear. We recently identified four esophageal adenocarcinoma-specific master regulator transcription factors (MRTF) ELF3, KLF5, GATA6, and EHF. In this study, gene-set enrichment analysis of both esophageal adenocarcinoma patient samples and cell line models unbiasedly underscores fatty acid synthesis as the central pathway downstream of three MRTFs (ELF3, KLF5, GATA6). Further characterizations unexpectedly identified a transcriptional feedback loop between MRTF and fatty acid synthesis, which mutually activated each other through the nuclear receptor, PPARG. MRTFs cooperatively promoted PPARG transcription by directly regulating its promoter and a distal esophageal adenocarcinoma-specific enhancer, leading to PPARG overexpression in esophageal adenocarcinoma. PPARG was also elevated in Barrett's esophagus, a recognized precursor to esophageal adenocarcinoma, implying that PPARG might play a role in the intestinal metaplasia of esophageal squamous epithelium. Upregulation of PPARG increased de novo synthesis of fatty acids, phospholipids, and sphingolipids as revealed by mass spectrometry-based lipidomics. Moreover, ChIP-seq, 4C-seq, and a high-fat diet murine model together characterized a novel, noncanonical, and cancer-specific function of PPARG in esophageal adenocarcinoma. PPARG directly regulated the ELF3 super-enhancer, subsequently activating the transcription of other MRTFs through an interconnected regulatory circuitry. Together, elucidation of this novel transcriptional feedback loop of MRTF/PPARG/fatty acid synthesis advances our understanding of the mechanistic foundation for epigenomic dysregulation and metabolic alterations in esophageal adenocarcinoma. More importantly, this work identifies a potential avenue for prevention and early intervention of esophageal adenocarcinoma by blocking this feedback loop. SIGNIFICANCE: These findings elucidate a transcriptional feedback loop linking epigenomic dysregulation and metabolic alterations in esophageal adenocarcinoma, indicating that blocking this feedback loop could be a potential therapeutic strategy in high-risk individuals.

The Distinctive Serum Metabolomes of Gastric, Esophageal and Colorectal Cancers

Simple Summary

Cancer of the stomach, esophagus and colon are often fatal. Ways are being sought to establish patient-friendly screening tests that would allow these cancers to be detected earlier. Examination of the metabolomics results of cancer patient’s serum for certain metabolites unique for a particular cancer was the goal of this review. From studies conducted within the past five years several metabolites were found to be changed in cancer compared to non-cancer patients for each of the three cancers. Further confirmation of what was discovered in this review coupled with establishment of standard protocols may allow for cancer screening on patient blood samples to become routine clinical tests.

Abstract

Three of the most lethal cancers in the world are the gastrointestinal cancers—gastric (GC), esophageal (EC) and colorectal cancer (CRC)—which are ranked as third, sixth and fourth in cancer deaths globally. Early detection of these cancers is difficult, and a quest is currently on to find non-invasive screening tests to detect these cancers. The reprogramming of energy metabolism is a hallmark of cancer, notably, an increased dependence on aerobic glycolysis which is often referred to as the Warburg effect. This metabolic change results in a unique metabolic profile that distinguishes cancer cells from normal cells. Serum metabolomics analyses allow one to measure the end products of both host and microbiota metabolism present at the time of sample collection. It is a non-invasive procedure requiring only blood collection which encourages greater patient compliance to have more frequent screenings for cancer. In the following review we will examine some of the most current serum metabolomics studies in order to compare their results and test a hypothesis that different tumors, notably, from EC, GC and CRC, have distinguishing serum metabolite profiles.

Metabolomics studies in gastrointestinal cancer: a systematic review

Introduction: This systemic review provides an overview of metabolic perturbations and possible mechanisms in gastrointestinal cancer. The authors discuss emerging challenges of technical and clinical applications.Areas covered: In this systemic review, the authors summarized the currently available results of metabolomic biomarkers linked to GI cancer, and discussed the altered metabolism pathways including carbohydrate metabolism, amino acid metabolism, lipids, and nucleotide metabolism and other metabolisms. Furthermore, future efforts need to adhere to normalize analysis procedures, validate with the larger cohort and utilize multiple-omics technologies. The search was conducted in PubMed with the following search terms (biomarker, gastrointestinal cancer, colorectal cancer, and esophageal cancer) from 2013 to 2019.Expert opinion: This systemic review summarized the currently available results of metabolomic biomarkers linked to gastrointestinal cancer, and discussed the altered metabolism pathways. The authors believe that metabolomics will benefit deeper understandings of the pathogenic mechanism, discovery of biomarkers and aid the search for drug targets as we move toward the era of personalized medicine. Personalized medication for tumors can improve the curative effect, avoid side effects and medical resource waste. As a promisingtool, metabolomics that targets the entire cancer-specific metabolite network should be applied more widely in cancer research.

Prospective serum metabolomic profiling of lethal prostate cancer

Impaired metabolism may play an important role in the pathogenesis of lethal prostate cancer, yet there is a paucity of evidence regarding the association. We conducted a large prospective serum metabolomic analysis of lethal prostate cancer in 523 cases and 523 matched controls nested within the Alpha-Tocopherol, Beta-Carotene Cancer Prevention (ATBC) Study. Median time from baseline fasting serum collection to prostate cancer death was 18 years (maximum 30 years). We identified 860 known biochemicals through an ultrahigh-performance LC-MS/MS platform. Conditional logistic regression models estimated odds ratios (OR) and 95% confidence intervals of risk associated with 1-standard deviation (s.d.) increases in log-metabolite signals. We identified 34 metabolites associated with lethal prostate cancer with a false discovery rate (FDR) < 0.15. Notably, higher serum thioproline, and thioproline combined with two other cysteine-related amino acids and redox metabolites, cystine and cysteine, were associated with reduced risk (1-s.d. OR = 0.75 and 0.71, respectively; p ≤ 8.2 × 10-5 ). By contrast, the dipeptide leucylglycine (OR = 1.36, p = 8.2 × 10-5 ), and three gamma-glutamyl amino acids (OR = 1.28-1.30, p ≤ 4.6 × 10-4 ) were associated with increased risk of lethal prostate cancer. Cases with metastatic disease at diagnosis (n = 179) showed elevated risk for several lipids, including especially the ketone body 3-hydroxybutyrate (BHBA), acyl carnitines, and dicarboxylic fatty acids (1.37 ≤ OR ≤ 1.49, FDR < 0.15). These findings provide a prospective metabolomic profile of lethal prostate cancer characterized by altered biochemicals in the redox, dipeptide, pyrimidine, and gamma-glutamyl amino acid pathways, whereas ketone bodies and fatty acids were associated specifically with metastatic disease.

The potential role of P.gingivalis in gastrointestinal cancer: a mini review

Bacterial infection may be involved in the entire process of tissue carcinogenesis by directly or indirectly affecting the occurrence and development of tumors. Porphyromonas gingivalis (P.gingivalis) is an important pathogen causing periodontitis. Periodontitis may promote the occurrence of various tumors. Gastrointestinal tumors are common malignant tumors with high morbidity, high mortality, and low early diagnosis rate. With the rapid development of molecularbiotechnology, the role of P.gingivalis in digestive tract tumors has been increasingly explored. This article reviews the correlation between P.gingivalis and gastrointestinal cancer and the pathogenesis of the latter. The relationship among P.gingivalis, periodontal disease, and digestive tract tumors must be clarifiedthrough a multi-center, prospective, large-scale study.

Etiology, cancer stem cells and potential diagnostic biomarkers for esophageal cancer

Esophageal cancer (EC) has been a leading cause of cancer death worldwide in part due to late detection and lack of precision treatment. EC includes two major malignancies, esophageal squamous cell carcinoma (ESCC) and esophageal adenocarcinoma (EAC). Recent studies reveal that ESCC and EAC have distinct cell of origin and contain cancer stem cells (also known as tumor initiating cells) expressing different cell surface markers. These biomarkers have potentially important values for both early detection and finding effective therapy. In this review we summarize the updated findings for cell of origin and provide an overview of cancer cell biomarkers that have been tested for ESCC and EAC. In addition, we also discuss recent progress in the study of molecular mechanisms leading to these malignancies.

Quantification of d-mannose in plasma: Development and validation of a reliable and accurate HPLC-MS-MS method

The present paper describes the development and the validation process - in compliance with the EMA guidelines - of a method based on tandem mass spectrometry coupled to liquid chromatography for the accurate quantification of mannose in human plasma samples. The quick sample preparation procedure, simplified by the absence of any derivatization step, makes the assay suitable for routine use in a clinical chemistry laboratory. The method validation yielded satisfactory selectivity, with a good separation of mannose from its epimers (glucose and galactose), linearity over the whole concentration range of interest (0.31-40 μg/mL), reproducibility with RSD <10%, and accuracy in the range 96-104%. Instrumental LLOD (0.31 μg/mL) and LLOQ (1.25 μg/mL) were good enough to detect endogenous plasma mannose levels and in agreement with recent data from the literature. Sensitivity was affected by a 5-fold dilution factor, which, if necessary, can be reduced. The method robustness was proven in >600 injections, most of them being of plasma samples, used also to assess the reference ranges in healthy subjects (9.93 ± 3.37 μg/mL) and type 2 diabetic patients (23.47 ± 6.19 μg/mL).

1H-NMR spectroscopy identifies potential biomarkers in serum metabolomic signatures for early stage esophageal squamous cell carcinoma

BACKGROUND

Esophageal squamous cell carcinoma (ESCC) is one of the most prevalent types of upper gastrointestinal malignancies. Here, we used ¹H nuclear magnetic resonance spectroscopy (¹H-NMR) to identify potential serum biomarkers in patients with early stage ESCC.

METHODS

Sixty-five serum samples from early stage ESCC patients (n = 25) and healthy controls (n = 40) were analysed using ¹H-NMR spectroscopy. We distinguished between different metabolites through principal component analysis, partial least squares-discriminant analysis, and orthogonal partial least squares-discriminant analysis (OPLS-DA) using SIMCA-P+ version 14.0 software. Receiver operating characteristic (ROC) analysis was conducted to verify potential biomarkers.

RESULTS

Using OPLS-DA, 31 altered serum metabolites were successfully identified between the groups. Based on the area under the ROC curve (AUROC), and the biomarker panel with AUROC of 0.969, six serum metabolites (α-glucose, choline, glutamine, glutamate, valine, and dihydrothymine) were selected as potential biomarkers for early stage ESCC. Dihydrothymine particularly was selected as a new feasible biomarker associated with tumor occurrence.

CONCLUSIONS

¹H-NMR spectroscopy may be a useful tumour detection approach in identifying useful metabolic ESCC biomarkers for early diagnosis and in the exploration of the molecular pathogenesis of ESCC.

Exploring potential biomarkers of early stage esophageal squamous cell carcinoma in pre- and post-operative serum metabolomic fingerprint spectrum using 1H-NMR method

Esophageal squamous cell carcinoma (ESCC) is one of the most prevalent types of upper gastrointestinal malignancy. Here, we used ¹H nuclear magnetic resonance spectroscopy (¹H-NMR) to identify potential pre- and post-operative serum biomarkers in patients with early stage ESCC using metabolomic fingerprint spectrum. Serum samples from preoperative patients with ESCC (ESCC, n = 25), postoperative patients with ESCC (PO, n = 24), and controls (n = 40) were analysed using ¹H-NMR spectroscopy. Using orthogonal partial least squares-discriminant analysis, 31 altered serum metabolites were successfully identified among the three groups. These metabolites are indicative of the changes that occur with glycometabolism, the metabolism of fatty acids, amino acids, choline, ketone bodies, nucleotides, and lipids. Based on receiver operating characteristic (ROC) curve analysis and a biomarker panel with an area under the curve (AUC) of 0.969, six serum metabolites (α-glucose, choline, glutamine, glutamate, valine, and dihydrothymine) were selected as potential diagnostic biomarkers for early stage ESCC. Additionally, four potential PO biomarkers (α-glucose, pyruvate, glutamate, and valine) with an AUC of 0.985 were selected to distinguish ESCC and PO. Many metabolites trended towards normalisation in PO patients, with only choline remaining high with an AUC of 0.858, suggesting that it may be a valuable potential biomarker for neoplasm progression, recurrence, chemoradiotherapy, and prognosis. ¹H-NMR spectroscopy may be a useful tumour detection approach in the early diagnosis of ESCC. These results also indicate that it is useful to differentiate pre- and post-operative ESCC, evaluate surgery therapeutic responses, and monitor postoperative chemoradiotherapy.

A review of validated biomarkers obtained through metabolomics

INTRODUCTION

Studying changes in the whole set of small molecules, final products of biochemical reactions in living systems or metabolites, is extremely appealing because they represent the best approach to identifying what occurs in an organism when samples are collected. However, their usefulness as potential biomarkers is limited by discoveries obtained in small groups without proper validation or even confirmation of the chemical structure. Areas covered: During the past 5 years, more than 900 papers have been published on metabolomics for biomarker discovery, but the numbers are much lower when some criteria of validation are applied. In total, 102 papers have been included in this review. The most frequent disease areas in which these markers have been discovered include the following: cancer, diabetes, and related diseases and neurodegenerative, cardiovascular, autoimmune, liver, and kidney diseases. Expert commentary: Metabolomics has been demonstrated as rapidly growing due to the improvements in instrumentation, mainly mass spectrometry, and data mining software. For application in the clinic, the results should be validated in different stages, from analytical validation to validation in independent sets of samples, using thousands of samples from different sources.

Circulating metabolite profiles to predict overall survival in advanced non-small cell lung cancer patients receiving first-line chemotherapy

OBJECTIVES

The prognosis for advanced-stage non-small cell lung cancer (NSCLC) is usually poor. However, survival may be variable and difficult to predict. In the current study, we aimed to identify circulating metabolites as potential predictive biomarkers for overall survival of advanced-stage (III/IV) NSCLC patients treated with first-line platinum-based chemotherapy.

MATERIALS AND METHODS

Using two-stage study design, we performed global metabolomic profiling in blood of 220 advanced-stage NSCLC patients, including 110 with poor survival and 110 with good survival. Metabolomic profiling was conducted using Metabolon platform. The association of each metabolite with survival was assessed by Cox proportional hazard regression model with adjustment for covariates.

RESULTS AND CONCLUSION

We found levels of 4 metabolites, caffeine, paraxanthine, stachydrine, and methyl glucopyranoside (alpha+beta), differed significantly between NSCLC patients with poor and good survival in both discovery and validation phases (P<0.05). Interestingly, majority of the identified metabolites are involved in caffeine metabolism, and 2 metabolites are related to coffee intake. In fact, caffeine metabolism pathway was the only significant pathway identified which significantly differed between NSCLC patients with poor and good survival (P=1.48E-07) in the pathway analysis. We also found 4 metabolites whose levels were significantly associated with good survival in both discovery and validation phases. Strong cumulative effects on overall survival were observed for these 4 metabolites. In conclusion, we identified a panel of metabolites including metabolites in caffeine metabolism pathway that may predict survival outcome in advanced-stage NSCLC patients. The identified small metabolites may be useful biomarker candidates to help identify patients who may benefit from platinum-based chemotherapy.

Global and targeted serum metabolic profiling of colorectal cancer progression

BACKGROUND

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

Applications of Metabolomics in Cancer Studies

Since the start of metabolomics as a field of research, the number of studies related to cancer has grown to such an extent that cancer metabolomics now represents its own discipline. In this chapter, the applications of metabolomics in cancer studies are explored. Different approaches and analytical platforms can be employed for the analysis of samples depending on the goal of the study and the aspects of the cancer metabolome being investigated. Analyses have concerned a range of cancers including lung, colorectal, bladder, breast, gastric, oesophageal and thyroid, amongst others. Developments in these strategies and methodologies that have been applied are discussed, in addition to exemplifying the use of cancer metabolomics in the discovery of biomarkers and in the assessment of therapy (both pharmaceutical and nutraceutical). Finally, the application of cancer metabolomics in personalised medicine is presented.

Candidate serum metabolite biomarkers for differentiating gastroesophageal reflux disease, Barrett's esophagus, and high-grade dysplasia/esophageal adenocarcinoma

INTRODUCTION/OBJECTIVES

Incidence of esophageal adenocarcinoma (EA), an often fatal cancer, has increased sharply over recent decades. Several important risk factors (reflux, obesity, smoking) have been identified for EA and its precursor, Barrett's esophagus (BE), but a key challenge remains identifying individuals at highest risk, since most with reflux do not develop BE, and most with BE do not progress to cancer. Metabolomics represents an emerging approach for identifying novel biomarkers associated with cancer development.

METHODS

We used targeted liquid chromatography-mass spectrometry (LC-MS) to profile 57 metabolites in 322 serum specimens derived from individuals with gastroesophageal reflux disease (GERD), BE, high-grade dysplasia (HGD), or EA, drawn from two well-annotated epidemiologic parent studies.

RESULTS

Multiple metabolites differed significantly (P<0.05) between BE versus GERD (n=9), and between HGD/EA versus BE (n=4). Several top candidates (FDR q≤0.15), including urate, homocysteine, and 3-nitrotyrosine, are linked to inflammatory processes, which may contribute to BE/EA pathogenesis. Multivariate modeling achieved moderate discrimination between HGD/EA and BE (AUC=0.75), with less pronounced separation for BE versus GERD (AUC=0.64).

CONCLUSION

Serum metabolite differences can be detected between individuals with GERD versus BE, and between those with BE versus HGD/EA, and may help differentiate patients at different stages of progression to EA.

Metabolomic Evidence for a Field Effect in Histologically Normal and Metaplastic Tissues in Patients with Esophageal Adenocarcinoma

Patients with Barrett's esophagus (BO) are at increased risk of developing esophageal adenocarcinoma (EAC). Most Barrett's patients, however, do not develop EAC, and there is a need for markers that can identify those most at risk. This study aimed to see if a metabolic signature associated with the development of EAC existed. For this, tissue extracts from patients with EAC, BO, and normal esophagus were analyzed using ¹H nuclear magnetic resonance. Where possible, adjacent histologically normal tissues were sampled in those with EAC and BO. The study included 46 patients with EAC, 7 patients with BO, and 68 controls who underwent endoscopy for dyspeptic symptoms with normal appearances. Within the cancer cohort, 9 patients had nonneoplastic Barrett's adjacent to the cancer suitable for biopsy. It was possible to distinguish between histologically normal, BO, and EAC tissue in EAC patients [area under the receiver operator curve (AUROC) 1.00, 0.86, and 0.91] and between histologically benign BO in the presence and absence of EAC (AUROC 0.79). In both these cases, sample numbers limited the power of the models. Comparison of histologically normal tissue proximal to EAC versus that from controls (AUROC 1.00) suggests a strong field effect which may develop prior to overt EAC and hence be useful for identifying patients at high risk of developing EAC. Excellent sensitivity and specificity were found for this model to distinguish histologically normal squamous esophageal mucosa in EAC patients and healthy controls, with 8 metabolites being very significantly altered. This may have potential diagnostic value if a molecular signature can detect tissue from which neoplasms subsequently arise.

LC-MS/MS determination of d-mannose in human serum as a potential cancer biomarker

Several metabolites in human serum have been identified as potential cancer biomarkers for early detection. This study focuses on the LC-MS/MS method development and validation of d-mannose in human serum. Surrogate blank serum, coupled with stable isotope d-mannose-¹³C₆, as internal standard, was used for generating standard curves ranging from 1 to 50μg/mL. Separation was achieved by an Agilent 1200 series HPLC equipped with a SUPELCOGELTM Pb, 6% Crosslinked column with HPLC water as a mobile phase at flow rate of 0.5mL/min at 80°C. Mass detection was performed under negative ionization electrospray. Inter- and intra-day accuracy and precision were <2%. The extraction recovery and matrix effect were 104.1%-105.5% and 97.0%-100.0%, respectively. This method was successfully applied for the quantification of d-mannose in the serum samples of 320 esophageal cancer patients and 323 healthy volunteers. We report a simple, specific and reproducible LC-MS/MS method for the quantification of d-mannose in human serum as a potential cancer biomarker.

Global metabolomics reveals potential urinary biomarkers of esophageal squamous cell carcinoma for diagnosis and staging

We performed a metabolomics study using liquid chromatography-mass spectrometry (LC-MS) combined with multivariate data analysis (MVDA) to discriminate global urine profiles in urine samples from esophageal squamous cell carcinoma (ESCC) patients and healthy controls (NC). Our work evaluated the feasibility of employing urine metabolomics for the diagnosis and staging of ESCC. The satisfactory classification between the healthy controls and ESCC patients was obtained using the MVDA model, and obvious classification of early-stage and advanced-stage patients was also observed. The results suggest that the combination of LC-MS analysis and MVDA may have potential applications for ESCC diagnosis and staging. We then conducted LC-MS/MS experiments to identify the potential biomarkers with large contributions to the discrimination. A total of 83 potential diagnostic biomarkers for ESCC were screened out, and 19 potential biomarkers were identified; the variations between the differences in staging using these potential biomarkers were further analyzed. These biomarkers may not be unique to ESCCs, but instead result from any malignant disease. To further elucidate the pathophysiology of ESCC, we studied related metabolic pathways and found that ESCC is associated with perturbations of fatty acid β-oxidation and the metabolism of amino acids, purines, and pyrimidines.

Pancreatic cancer screening using a multiplatform human serum metabolomics system

Aim: To examine a novel screening method for pancreatic cancer involving gas chromatography/mass spectrometry and liquid chromatography/mass spectrometry-based metabolomics analysis. Materials & methods: Sera from pancreatic cancer patients (n = 59) and healthy volunteers (n = 59) were allocated to the training set or validation set. Serum metabolome analysis was carried out using our multiplatform metabolomics system. A diagnostic model was constructed using a two-phase screening method that was newly advocated. Results: When the training set was used, the constructed diagnostic model exhibited high sensitivity (100%) and specificity (80%) for pancreatic cancer. When the validation set was used, the model displayed high sensitivity (84.1%) and specificity (84.1%). Conclusion: We successfully developed a diagnostic model for pancreatic cancer using a multiplatform serum metabolomics system.

Dietary fat overcomes the protective activity of thrombospondin-1 signaling in the Apc(Min/+) model of colon cancer

Thrombospondin 1 is a glycoprotein that regulates cellular phenotype through interactions with its cellular receptors and extracellular matrix-binding partners. Thrombospondin 1 locally regulates angiogenesis and inflammatory responses that contribute to colorectal carcinogenesis in Apc^Min/+ mice. The ability of thrombospondin 1 to regulate responses of cells and tissues to a variety of stresses suggested that loss of thrombospondin 1 may also have broader systemic effects on metabolism to modulate carcinogenesis. Apc^Min/+:Thbs1^−/− mice exhibited decreased survival and higher tumor multiplicities in the small and large intestine relative to Apc^Min/+ mice when fed a low (5%) fat western diet. However, the protective effect of endogenous thrombospondin 1 was lost when the mice were fed a western diet containing 21% fat. Biochemical profiles of liver tissue identified systemic metabolic changes accompanying the effects of thrombospondin 1 and dietary lipid intake on tumorigenesis. A high-fat western diet differentially regulated elements of amino acid, energy and lipid metabolism in Apc^Min/+:Thbs1^−/− mice relative to Apc^Min/+:Thbs1^+/+mice. Metabolic changes in ketone body and tricarboxylic acid cycle intermediates indicate functional interactions between Apc and thrombospondin 1 signaling that control mitochondrial function. The cumulative diet-dependent differential changes observed in Apc^Min/+:Thbs1^−/− versus Apc^Min/+ mice include altered amino acid and lipid metabolism, mitochondrial dysfunction, eicosanoids and ketone body formation. This metabolic profile suggests that the protective role of thrombospondin 1 to decrease adenoma formation in Apc^Min/+ mice results in part from improved mitochondrial function.