Impact of <Emphasis Type="Italic">Plasmodium falciparum</Emphasis> infection on haematological parameters in children living in Western Kenya

Background

Malaria is the commonest cause of childhood morbidity in Western Kenya with varied heamatological consequences. The t study sought to elucidate the haemotological changes in children infected with malaria and their impact on improved diagnosis and therapy of childhood malaria.

Methods

Haematological parameters in 961 children, including 523 malaria-infected and 438 non-malaria infected, living in Kisumu West District, an area of malaria holoendemic transmission in Western Kenya were evaluated.

Results

The following parameters were significantly lower in malaria-infected children; platelets, lymphocytes, eosinophils, red blood cell count and haemoglobin (Hb), while absolute monocyte and neutrophil counts, and mean platelet volume (MPV) were higher in comparison to non-malaria infected children. Children with platelet counts of <150,000/uL were 13.8 times (odds ratio) more likely to have malaria. Thrombocytopaenia was present in 49% of malaria-infected children and was associated with high parasitaemia levels, lower age, low Hb levels, increased MPV and platelet aggregate flag. Platelet aggregates were more frequent in malaria-infected children (25% vs. 4%, p<0.0001) and associated with thrombocytopaenia rather than malaria status.

Conclusion

Children infected with Plasmodium falciparum malaria exhibited important changes in some haematological parameters with low platelet count and haemoglobin concentration being the two most important predictors of malaria infection in children in our study area. When used in combination with other clinical and microscopy, these parameters could improve malaria diagnosis in sub-patent cases.

     

<Emphasis Type="Italic">massPix</Emphasis>: an R package for annotation and interpretation of mass spectrometry imaging data for lipidomics

Introduction

Mass spectrometry imaging (MSI) experiments result in complex multi-dimensional datasets, which require specialist data analysis tools.

Objectives

We have developed massPix—an R package for analysing and interpreting data from MSI of lipids in tissue.

Methods

massPix produces single ion images, performs multivariate statistics and provides putative lipid annotations based on accurate mass matching against generated lipid libraries.

Results

Classification of tissue regions with high spectral similarly can be carried out by principal components analysis (PCA) or k-means clustering.

Conclusion

massPix is an open-source tool for the analysis and statistical interpretation of MSI data, and is particularly useful for lipidomics applications.

     

Unbiased lipidomic profiling reveals metabolomic changes during the onset and antipsychotics treatment of schizophrenia disease

Introduction

Schizophrenia (SCH) is one of the most common psychiatric disorders, which involves impairments in motivation and cognition. The pathological mechanisms underlying SCH are still unknown, and no effective therapies can prevent or treat perfectly the cognitive impairments and deficit symptoms caused by SCH.

Objectives

We aimed to find the lipid expression change in plasma that underlie SCH onset and antipsychotics treatment.

Methods

We performed a data independent acquisition-based untargeted lipidomic approach on a quadrupole-time of flight liquid chromatography coupled to mass spectrometry platform. The plasma lipidomic profiles of SCH patients (n?=?20) pre- and post-antipsychotics treatment were acquired as well as healthy controls (n?=?29). Grouped or paired t-test were used to analyze the data.

Results

Over 1000 features were detected by our lipidomic analysis, of which 445 lipids belonging to 17 lipid species were reliably identified by tandem mass spectrometry. After statistical analysis, 47 lipids belonging to 9 lipid species were found to be dysregulated between naive SCH patients and healthy controls, and 50 lipids belonging to 9 lipid species were found to be dysregulated after antipsychotics treatment. These findings include several new SCH-relevant lipid species such as sphingomyelin, acylcarnitine and ceramide. Four types of lipid expression regulative patterns can be concluded from the above mentioned findings, revealing information about mechanism, side-effect and potential target of antipsychotics.

Conclusions

The work presented here have revealed several new lipid species which are significantly dysregulated in SCH disease development or antipsychotics treatment. These lipids provide new evidence for the pathological studies of SCH and new antipsychotics development, or can be considered as potentially candidate biomarkers for further validation.

     

A methodology for elucidating regulatory mechanisms leading to changes in lipid profiles

Introduction

It is difficult to elucidate the metabolic and regulatory factors causing lipidome perturbations.

Objectives

This work simplifies this process.

Methods

A method has been developed to query an online holistic lipid metabolic network (of 7923 metabolites) to extract the pathways that connect the input list of lipids.

Results

The output enables pathway visualisation and the querying of other databases to identify potential regulators. When used to a study a plasma lipidome dataset of polycystic ovary syndrome, 14 enzymes were identified, of which 3 are linked to ELAVL1—an mRNA stabiliser.

Conclusion

This method provides a simplified approach to identifying potential regulators causing lipid-profile perturbations.

     

Minimal variation of the plasma lipidome after delayed processing of neonatal cord blood

Background

Cord blood lipids are potential disease biomarkers. We aimed to determine if their concentrations were affected by delayed blood processing.

Method

Refrigerated cord blood from six healthy newborns was centrifuged every 12 h for 4 days. Plasma lipids were analysed by liquid chromatography/mass spectroscopy.

Results

Of 262 lipids identified, only eight varied significantly over time. These comprised three dihexosylceramides, two phosphatidylserines and two phosphatidylethanolamines whose relative concentrations increased and one sphingomyelin that decreased.

Conclusion

Delay in separation of plasma from refrigerated cord blood has minimal effect overall on the plasma lipidome.

     

rDolphin: a GUI R package for proficient automatic profiling of 1D <Superscript>1</Superscript>H-NMR spectra of study datasets

Introduction

Adoption of automatic profiling tools for ¹H-NMR-based metabolomic studies still lags behind other approaches in the absence of the flexibility and interactivity necessary to adapt to the properties of study data sets of complex matrices.

Objectives

To provide an open source tool that fully integrates these needs and enables the reproducibility of the profiling process.

Methods

rDolphin incorporates novel techniques to optimize exploratory analysis, metabolite identification, and validation of profiling output quality.

Results

The information and quality achieved in two public datasets of complex matrices are maximized.

Conclusion

rDolphin is an open-source R package (http://github.com/danielcanueto/rDolphin) able to provide the best balance between accuracy, reproducibility and ease of use.

     

Absolute quantitative lipidomics reveals lipidome-wide alterations in aging brain

Introduction

The absolute quantitation of lipids at the lipidome-wide scale is a challenge but plays an important role in the comprehensive study of lipid metabolism.

Objectives

We aim to develop a high-throughput quantitative lipidomics approach to enable the simultaneous identification and absolute quantification of hundreds of lipids in a single experiment. Then, we will systematically characterize lipidome-wide changes in the aging mouse brain and provide a link between aging and disordered lipid homeostasis.

Methods

We created an in-house lipid spectral library, containing 76,361 lipids and 181,300 MS/MS spectra in total, to support accurate lipid identification. Then, we developed a response factor-based approach for the large-scale absolute quantifications of lipids.

Results

Using the lipidomics approach, we absolutely quantified 1212 and 864 lipids in human cells and mouse brains, respectively. The quantification accuracy was validated using the traditional approach with a median relative error of 12.6%. We further characterized the lipidome-wide changes in aging mouse brains, and dramatic changes were observed in both glycerophospholipids and sphingolipids. Sphingolipids with longer acyl chains tend to accumulate in aging brains. Membrane-esterified fatty acids demonstrated diverse changes with aging, while most polyunsaturated fatty acids consistently decreased.

Conclusion

We developed a high-throughput quantitative lipidomics approach and systematically characterized the lipidome-wide changes in aging mouse brains. The results proved a link between aging and disordered lipid homeostasis.

     

Plasma lipidomic profiling in patients with rheumatoid arthritis

Introduction

Rheumatoid arthritis (RA) is linked to increased cardiovascular morbidity and mortality, not completely explained by traditional risk factors. Importantly, the increased risk occurs despite lower levels of total and low-density lipoprotein cholesterol. Whilst systemic inflammation may be a factor, it is possible that changes in individual lipid species contribute to the increased cardiovascular risk.

Objectives

In the present study, we characterized plasma lipidomic profiles in patients with RA in comparison with healthy controls.

Methods

Patients with RA (n = 32) and age- and gender-matched healthy volunteers (n = 84) were recruited. Fasting plasma lipid profiles were measured using electrospray-ionisation tandem mass spectrometry. 24 lipid classes and subclasses were measured.

Results

Patients with RA had normal total, low-density lipoprotein and high-density lipoprotein cholesterol, but higher triglycerides than controls. Five lipid classes (dihydroceramides, alkylphosphatidylethanolamine, alkenylphosphatidylethanolamine, lysophosphatidylinositol, phosphatidylserine) differed between patients with RA and controls. Then we measured 36 lipid species within these 5 classes and found that 11 lipid species were different between patients with RA and controls. Three lipid classes (dihydroceramides, lysophosphatidylinositol, phosphatidylserine) and 10 lipid species remained significantly associated with RA after adjusting for age, sex, body mass index, current smoking, systolic blood pressure and anti-hypertensive treatment in a binary logistic regression model.

Conclusion

This study has identified lipid alterations in RA. These alterations of lipids warrant further investigation as they may be associated with accelerated atherosclerosis and joint inflammation in patient with RA.

     

Ultra high performance liquid chromatography–high resolution mass spectrometry plasma lipidomics can distinguish between canine breeds despite uncontrolled environmental variability and non-standardized diets

Introduction and objectives

The purpose of this study was to use high accurate mass metabolomic profiling to investigate differences within a phenotypically diverse canine population, with breed-related morphological, physiological and behavioural differences. Previously, using a broad metabolite fingerprinting approach, lipids appear to dominate inter- and intra- breed discrimination. The purpose here was to use Ultra High Performance Liquid Chromatography–High Resolution Mass Spectrometry (UHPLC–HRMS) to identify in more detail, inter-breed signatures in plasma lipidomic profiles of home-based, client-owned dogs maintained on different diets and fed according to their owners’ feeding regimens.

Methods

Nine dog breeds were recruited in this study (Beagle, Chihuahua, Cocker Spaniel, Dachshund, Golden Retriever, Greyhound, German Shepherd, Labrador Retriever and Maltese: 7–12 dogs per breed). Metabolite profiling on a MTBE lipid extract of fasted plasma was performed using UHPLC-HRMS.

Results

Multivariate modelling and classification indicated that the main source of lipidome variance was between the three breeds Chihuahua, Dachshund and Greyhound and the other six breeds, however some intra-breed variance was evident in Labrador Retrievers. Metabolites associated with dietary intake impacted on breed-associated variance and following filtering of these signals out of the data-set unique inter-breed lipidome differences for Chihuahua, Golden Retriever and Greyhound were identified.

Conclusion

By using a phenotypically diverse home-based canine population, we were able to show that high accurate mass lipidomics can enable identification of metabolites in the first pass plasma profile, capturing distinct metabolomic variability associated with genetic differences, despite environmental and dietary variability.

     

A relative quantitative positive/negative ion switching method for untargeted lipidomics via high resolution LC-MS/MS from any biological source

Introduction

Advances in high-resolution mass spectrometry have created renewed interest for studying global lipid biochemistry in disease and biological systems.

Objectives

Here, we present an untargeted 30 min. LC-MS/MS platform that utilizes positive/negative polarity switching to perform unbiased data dependent acquisitions (DDA) via higher energy collisional dissociation (HCD) fragmentation to profile more than 1000–1500 lipid ions mainly from methyl-tert-butyl ether (MTBE) or chloroform:methanol extractions.

Methods

The platform uses C₁₈ reversed-phase chromatography coupled to a hybrid QExactive Plus/HF Orbitrap mass spectrometer and the entire procedure takes?~10 h from lipid extraction to identification/quantification for a data set containing 12 samples (~4 h for a single sample). Lipids are identified by both accurate precursor ion mass and fragmentation features and quantified using LipidSearch and Elements software.

Results

Using this approach, we are able to profile intact lipid ions from up to 18 different main lipid classes and 66 subclasses. We show several studies from different biological sources, including cultured cancer cells, resected tissues from mice such as lung and breast tumors and biological fluids such as plasma and urine.

Conclusions

Using mouse embryonic fibroblasts, we showed that TSC2^?/? KD significantly abrogates lipid biosynthesis and that rapamycin can rescue triglyceride (TG) lipids and we show that SREBP^?/? shuts down lipid biosynthesis significantly via mTORC1 signaling pathways. We show that in mouse EGFR driven lung tumors, a large number of TGs and phosphatidylmethanol (PMe) lipids are elevated while some phospholipids (PLs) show some of the largest decrease in lipid levels from ~?2000 identified lipid ions. In addition, we identified more than 1500 unique lipid species from human blood plasma.

     

Annotation of the human cerebrospinal fluid lipidome using high resolution mass spectrometry and a dedicated data processing workflow

Introduction

Due to its proximity with the brain, cerebrospinal fluid (CSF) could be a medium of choice for the discovery of biomarkers of neurological and psychiatric diseases using untargeted analytical approaches.

Objectives

This study explored the CSF lipidome in order to generate a robust mass spectral database using an untargeted lipidomic approach.

Methods

Cerebrospinal fluid samples from 45 individuals were analyzed by liquid chromatography coupled to high-resolution mass spectrometry method (LC-HRMS). A dedicated data processing workflow was implemented using XCMS software and adapted filters to select reliable features. In addition, an automatic annotation using an in silico lipid database and several MS/MS experiments were performed to identify CSF lipid species.

Results

Using this complete workflow, 771 analytically relevant monoisotopic lipid species corresponding to 550 unique lipids which represent five major lipid families (i.e., free fatty acids, sphingolipids, glycerophospholipids, glycerolipids, and sterol lipids) were detected and annotated. In addition, MS/MS experiments enabled to improve the annotation of 304 lipid species. Thanks to LC-HRMS, it was possible to discriminate between isobaric and also isomeric lipid species; and interestingly, our study showed that isobaric ions represent about 50 % of the total annotated lipid species in the human CSF.

Conclusion

This work provides an extensive LC/HRMS database of the human CSF lipidome which constitutes a relevant foundation for future studies aimed at finding biomarkers of neurological disorders.

     

A comparison of human serum and plasma metabolites using untargeted <Superscript>1</Superscript>H NMR spectroscopy and UPLC-MS

Introduction

Differences in the metabolite profiles between serum and plasma are incompletely understood.

Objectives

To evaluate metabolic profile differences between serum and plasma and among plasma sample subtypes.

Methods

We analyzed serum, platelet rich plasma (PRP), platelet poor plasma (PPP), and platelet free plasma (PFP), collected from 8 non-fasting apparently healthy women, using untargeted standard 1D and CPMG ¹H NMR and reverse phase and hydrophilic (HILIC) UPLC-MS. Differences between metabolic profiles were evaluated using validated principal component and orthogonal partial least squares discriminant analysis.

Results

Explorative analysis showed the main source of variation among samples was due to inter-individual differences with no grouping by sample type. After correcting for inter-individual differences, lipoproteins, lipids in VLDL/LDL, lactate, glutamine, and glucose were found to discriminate serum from plasma in NMR analyses. In UPLC-MS analyses, lysophosphatidylethanolamine (lysoPE)(18:0) and lysophosphatidic acid(20:0) were higher in serum, and phosphatidylcholines (PC)(16:1/18:2, 20:3/18:0, O-20:0/22:4), lysoPC(16:0), PE(O-18:2/20:4), sphingomyelin(18:0/22:0), and linoleic acid were lower. In plasma subtype analyses, isoleucine, leucine, valine, phenylalanine, glutamate, and pyruvate were higher among PRP samples compared with PPP and PFP by NMR while lipids in VLDL/LDL, citrate, and glutamine were lower. By UPLC-MS, PE(18:0/18:2) and PC(P-16:0/20:4) were higher in PRP compared with PFP samples.

Conclusions

Correction for inter-individual variation was required to detect metabolite differences between serum and plasma. Our results suggest the potential importance of inter-individual effects and sample type on the results from serum and plasma metabolic phenotyping studies.

     

A lipidomic and metabolomic serum signature from nonhuman primates exposed to ionizing radiation

Introduction

Due to dangers associated with potential accidents from nuclear energy and terrorist threats, there is a need for high-throughput biodosimetry to rapidly assess individual doses of radiation exposure. Lipidomics and metabolomics are becoming common tools for determining global signatures after disease or other physical insult and provide a “snapshot” of potential cellular damage.

Objectives

The current study assesses changes in the nonhuman primate (NHP) serum lipidome and metabolome 7 days following exposure to ionizing radiation (IR).

Methods

Serum sample lipids and metabolites were extracted using a biphasic liquid–liquid extraction and analyzed by ultra performance liquid chromatography quadrupole time-of-flight mass spectrometry. Global radiation signatures were acquired in data-independent mode.

Results

Radiation exposure caused significant perturbations in lipid metabolism, affecting all major lipid species, including free fatty acids, glycerolipids, glycerophospholipids and esterified sterols. In particular, we observed a significant increase in the levels of polyunsaturated fatty acids (PUFA)-containing lipids in the serum of NHPs exposed to 10 Gy radiation, suggesting a primary role played by PUFAs in the physiological response to IR. Metabolomics profiling indicated an increase in the levels of amino acids, carnitine, and purine metabolites in the serum of NHPs exposed to 10 Gy radiation, suggesting perturbations to protein digestion/absorption, biological oxidations, and fatty acid β-oxidation.

Conclusions

This is the first report to determine changes in the global NHP serum lipidome and metabolome following radiation exposure and provides information for developing metabolomic biomarker panels in human-based biodosimetry.

     

Lipid phenotyping of lung epithelial lining fluid in healthy human volunteers

Background

Lung epithelial lining fluid (ELF)—sampled through sputum induction—is a medium rich in cells, proteins and lipids. However, despite its key role in maintaining lung function, homeostasis and defences, the composition and biology of ELF, especially in respect of lipids, remain incompletely understood.

Objectives

To characterise the induced sputum lipidome of healthy adult individuals, and to examine associations between different ELF lipid phenotypes and the demographic characteristics within the study cohort.

Methods

Induced sputum samples were obtained from 41 healthy non-smoking adults, and their lipid compositions analysed using a combination of untargeted shotgun and liquid chromatography mass spectrometry methods. Topological data analysis (TDA) was used to group subjects with comparable sputum lipidomes in order to identify distinct ELF phenotypes.

Results

The induced sputum lipidome was diverse, comprising a range of different molecular classes, including at least 75 glycerophospholipids, 13 sphingolipids, 5 sterol lipids and 12 neutral glycerolipids. TDA identified two distinct phenotypes differentiated by a higher total lipid content and specific enrichments of diacyl-glycerophosphocholines, -inositols and -glycerols in one group, with enrichments of sterols, glycolipids and sphingolipids in the other. Subjects presenting the lipid-rich ELF phenotype also had significantly higher BMI, but did not differ in respect of other demographic characteristics such as age or gender.

Conclusions

We provide the first evidence that the ELF lipidome varies significantly between healthy individuals and propose that such differences are related to weight status, highlighting the potential impact of (over)nutrition on lung lipid metabolism.

     

Atorvastatin prevents <Emphasis Type="Italic">Plasmodium falciparum</Emphasis> cytoadherence and endothelial damage

Background

The adhesion of Plasmodium falciparum parasitized red blood cell (PRBC) to human endothelial cells (EC) induces inflammatory processes, coagulation cascades, oxidative stress and apoptosis. These pathological processes are suspected to be responsible for the blood-brain-barrier and other organs' endothelial dysfunctions observed in fatal cases of malaria. Atorvastatin, a drug that belongs to the lowering cholesterol molecule family of statins, has been shown to ameliorate endothelial functions and is widely used in patients with cardiovascular disorders.

Methods

The effect of this compound on PRBC induced endothelial impairments was assessed using endothelial co-culture models.

Results

Atorvastatin pre-treatment of EC was found to reduce the expression of adhesion molecules and P. falciparum cytoadherence, to protect cells against PRBC-induced apoptosis and to enhance endothelial monolayer integrity during co-incubation with parasites.

Conclusions

These results might suggest a potential interest use of atorvastatin as a protective treatment to interfere with the pathophysiological cascades leading to severe malaria.

     

Plasma lipidomics identifies novel biomarkers in patients with hepatitis B virus-related acute-on-chronic liver failure

Introduction

Acute-on-chronic liver failure (ACLF) is a fatal syndrome that presents with acute deterioration of liver function in chronic hepatitis B virus (HBV) patients. However, reliable diagnostic and prognostic biomarkers are scarce.

Objectives

The aim of this study to identify lipid species associated with HBV infection as well as novel lipid biomarkers for HBV-ACLF.

Methods

High performance liquid chromatography–tandem mass spectrometry was used for targeted lipidomic analyses of 147 lipid species. Fasting-state plasma samples from 74 HBV-ACLF patients, 86 HBV-non-ACLF patients [30 HBV-immune tolerant (HBV-IT) and 56 chronic hepatitis B] and 20 healthy controls. Univariate and multivariate analyses examined changes in lipid species among patient groups.

Results

The HBV-ACLF and HBV-non-ACLF groups had distinctly different lipid profiles, while the HC and HBV-IT groups had similar lipid profiles. Further, lysophosphatidylcholine (LPC) 22:6, cholesterol ester (CE) 22:6, CE 20:4, CE 18:2 and CE 18:1 could be used as potential biomarkers for the early prediction of ACLF. Meanwhile, univariate and multivariate analyses identified CE 20:4, LPC 16:0, LPC 18:0, phosphatidylcholine (PC) 40:6 and PC 32:0 as putative diagnostic biomarkers of HBV-ACLF. Moreover, LPC 16:0 and LPC 18:0 were significantly associated with model for end stage liver disease (MELD) scores, and the two lipid species combined with MELD score had significant capability to predict the 6-month mortality.

Conclusions

Our study revealed that lipid metabolism disorders were significantly associated with the severity of liver inflammatory injury rather than HBV infection in patients with chronic HBV infection, and specific lipid species could be used as potentially biomarkers for diagnosis and prognosis in HBV-ACLF.

     

Metabolic response of porcine colon explants to in vitro infection by <Emphasis Type="Italic">Brachyspira hyodysenteriae</Emphasis>: a leap into disease pathophysiology

Introduction

Swine dysentery caused by Brachyspira hyodysenteriae is a production limiting disease in pig farming. Currently antimicrobial therapy is the only treatment and control method available.

Objective

The aim of this study was to characterize the metabolic response of porcine colon explants to infection by B. hyodysenteriae.

Methods

Porcine colon explants exposed to B. hyodysenteriae were analyzed for histopathological, metabolic and pro-inflammatory gene expression changes.

Results

Significant epithelial necrosis, increased levels of l-citrulline and IL-1α were observed on explants infected with B. hyodysenteriae.

Conclusions

The spirochete induces necrosis in vitro likely through an inflammatory process mediated by IL-1α and NO.

     

<Superscript>1</Superscript>H NMR metabolic profiling of gastric cancer patients with lymph node metastasis

Introduction

Gastric cancer (GC) is a malignant tumor worldwide. As primary pathway for metastasis, the lymphatic system is an important prognostic factor for GC patients. Although the metabolic changes of gastric cancer have been investigated in extensive studies, little effort focused on the metabolic profiling of lymph node metastasis (LNM)-positive or negative GC patients.

Objectives

We performed ¹H NMR spectrum of GC tissue samples with and without LNM to identify novel potential metabolic biomarkers in the process of LNM of GC.

Methods

¹H NMR-based untargeted metabolomics approach combined with multivariate statistical analyses were used to study the metabolic profiling of tissue samples from LNM-positive GC patients (n?=?40), LNM-negative GC patients (n?=?40) and normal controls (n?=?40).

Results

There was a clear separation between GC patients and normal controls, and 33 differential metabolites were identified in the study. Moreover, GC patients were also well-classified according to LNM-positive or negative. Totally eight distinguishing metabolites were selected in the metabolic profiling of GC patients with LNM-positive or negative, suggesting the metabolic dysfunction in the process of LNM. According to further validation and analysis, especially BCAAs metabolism (leucine, isoleucine, valine), GSH and betaine may be as potential factors of diagnose and prognosis of GC patients with or without LNM.

Conclusion

To our knowledge, this is the first metabolomics study focusing on LNM of GC. The identified distinguishing metabolites showed a promising application on clinical diagnose and therapy prediction, and understanding the mechanism underlying the carcinogenesis, invasion and metastasis of GC.

     

Metabolomics approach for predicting response to neoadjuvant chemotherapy for colorectal cancer

Introduction

Colorectal cancer (CRC) is a clinically heterogeneous disease, which necessitates a variety of treatments and leads to different outcomes. Only some CRC patients will benefit from neoadjuvant chemotherapy (NACT).

Objectives

An accurate prediction of response to NACT in CRC patients would greatly facilitate optimal personalized management, which could improve their long-term survival and clinical outcomes.

Methods

In this study, plasma metabolite profiling was performed to identify potential biomarker candidates that can predict response to NACT for CRC. Metabolic profiles of plasma from non-response (n?=?30) and response (n?=?27) patients to NACT were studied using UHPLC–quadruple time-of-flight)/mass spectrometry analyses and statistical analysis methods.

Results

The concentrations of nine metabolites were significantly different when comparing response to NACT. The area under the receiver operating characteristic curve value of the potential biomarkers was up to 0.83 discriminating the non-response and response group to NACT, superior to the clinical parameters (carcinoembryonic antigen and carbohydrate antigen 199).

Conclusion

These results show promise for larger studies that could result in more personalized treatment protocols for CRC patients.