Identification of phosphatidylcholine and lysophosphatidylcholine as novel biomarkers for cervical cancers in a prospective cohort study

"Find Me" and "Eat Me" signals: tools to drive phagocytic processes for modulating antitumor immunity

Phagocytosis, a vital defense mechanism, involves the recognition and elimination of foreign substances by cells. Phagocytes, such as neutrophils and macrophages, rapidly respond to invaders; macrophages are especially important in later stages of the immune response. They detect "find me" signals to locate apoptotic cells and migrate toward them. Apoptotic cells then send "eat me" signals that are recognized by phagocytes via specific receptors. "Find me" and "eat me" signals can be strategically harnessed to modulate antitumor immunity in support of cancer therapy. These signals, such as calreticulin and phosphatidylserine, mediate potent pro-phagocytic effects, thereby promoting the engulfment of dying cells or their remnants by macrophages, neutrophils, and dendritic cells and inducing tumor cell death. This review summarizes the phagocytic "find me" and "eat me" signals, including their concepts, signaling mechanisms, involved ligands, and functions. Furthermore, we delineate the relationships between "find me" and "eat me" signaling molecules and tumors, especially the roles of these molecules in tumor initiation, progression, diagnosis, and patient prognosis. The interplay of these signals with tumor biology is elucidated, and specific approaches to modulate "find me" and "eat me" signals and enhance antitumor immunity are explored. Additionally, novel therapeutic strategies that combine "find me" and "eat me" signals to better bridge innate and adaptive immunity in the treatment of cancer patients are discussed.

Genetically predicted TWEAK mediates the association between lipidome and Keratinocyte Carcinomas

BACKGROUND

Reports suggest that lipid profiles may be linked to the likelihood of developing skin cancer, yet the exact causal relationship is still unknown.

OBJECTIVE

This study aimed to examine the connection between lipidome and skin cancers, as well as investigate any possible mediators.

METHODS

A two-sample Mendelian randomization (MR) analysis was conducted on 179 lipidomes and each skin cancer based on a genome-wide association study (GWAS), including melanoma, basal cell carcinoma (BCC), and squamous cell carcinoma (SCC). Then, Bayesian weighted MR was performed to verify the analysis results of two-sample MR. Moreover, a two-step MR was employed to investigate the impact of TNF-like weak inducer of apoptosis (TWEAK)-mediated lipidome on skin cancer rates.

RESULTS

MR analysis identified higher genetically predicted phosphatidylcholine (PC) (17:0_18:2) could reduce the risk of skin tumors, including BCC (OR = 0.9149, 95% CI: 0.8667-0.9658), SCC (OR = 0.9343, 95% CI: 0.9087-0.9606) and melanoma (OR = 0.9982, 95% CI: 0.9966-0.9997). The proportion of PC (17:0_18:2) predicted by TWEAK-mediated genetic prediction was 6.6 % in BCC and 7.6% in SCC. The causal relationship between PC (17:0_18:2) and melanoma was not mediated by TWEAK.

CONCLUSION

This study identified a negative causal relationship between PC (17:0_18:2) and keratinocyte carcinomas, a small part of which was mediated by TWEAK, and most of the remaining mediating factors are still unclear. Further research on other risk factors is needed in the future.

High-throughput metabolomics identifies new biomarkers for cervical cancer

BACKGROUND

Cervical cancer (CC) is a danger to women's health, especially in many developing countries. Metabolomics can make the connection between genotypes and phenotypes. It provides a wide spectrum profile of biological processes under pathological or physiological conditions.

METHOD

In this study, we conducted plasma metabolomics of healthy volunteers and CC patients and integratively analyzed them with public CC tissue transcriptomics from Gene Expression Omnibus (GEO).

RESULT

Here, we screened out a panel of 5 metabolites to precisely distinguish CC patients from healthy volunteers. Furthermore, we utilized multi-omics approaches to explore patients with stage I-IIA1 and IIA2-IV4 CC and comprehensively analyzed the dysregulation of genes and metabolites in CC progression. We identified that plasma levels of trimethylamine N-oxide (TMAO) were associated with tumor size and regarded as a risk factor for CC. Moreover, we demonstrated that TMAO could promote HeLa cell proliferation in vitro. In this study, we delineated metabolic profiling in healthy volunteers and CC patients and revealed that TMAO was a potential biomarker to discriminate between I-IIA1 and IIA2-IV patients to indicate CC deterioration.

CONCLUSION

Our study identified a diagnostic model consisting of five metabolites in plasma that can effectively distinguish CC from healthy volunteers. Furthermore, we proposed that TMAO was associated with CC progression and might serve as a potential non-invasive biomarker to predict CC substage.

IMPACT

These findings provided evidence of the important role of metabolic molecules in the progression of cervical cancer disease, as well as their ability as potential biomarkers.

Probing interaction of atherogenic lysophosphatidylcholine with functionalized graphene nanosheets: theoretical modelling and experimental validation

CONTEXT

The potential of graphene derivatives for theranostic applications depends on their compatibility with cellular and biomolecular components. Lysophosphatidylcholine (LPC), a lipid component present in oxidized low-density lipoproteins, microvesicles and free circulation in blood, plays a critical role in the pathophysiology of various diseases. Using density functional theory-based methods, we systematically investigated the interaction of atherogenic LPC molecule with different derivatives of graphene, including pristine graphene, graphene with defect, N-doped graphene, amine-functionalized graphene, various graphene oxides and hydroxylated graphene oxides. We observed that the adsorption of LPC on graphene derivatives is highly selective based on the orientation of the functional groups of LPC interacting with the surface of the derivatives. Hydroxylated graphene oxide exhibited the strongest interaction with LPC with adsorption energy of - 2.1 eV due to the interaction between the hydroxyl group on graphene and the phosphate group of LPC. The presence of aqueous medium further enhanced this interaction indicating favourable adsorption of LPC and graphene oxide in biological systems. Such strong interaction leads to substantial change in the electronic structure of the LPC molecule, which results in the activation of this molecule. In contrast, amine-modified graphene showed the least interaction. These theoretical results are in line with our experimental fluorescence spectroscopic data of LPC/1-anilino-8-napthalene sulfonic acid complex. Our present comprehensive investigation employing both theoretical and experimental methods provides a deeper understanding of graphene-lipid interaction, which holds paramount importance in the design and fabrication of graphene-based nanomaterials for biomedical applications.

METHODS

In this study, we employed the density functional theory-based methods to investigate the electronic and structural properties of graphene derivatives and LPC molecule using the Quantum Espresso package. The exchange-correlation functional was described within generalized gradient approximation (GGA) as parameterized by Perdew, Burke and Ernzerhof (PBE). The valence electrons were represented using plane wave basis sets. `The Grimme's dispersion method was used to include the van der Waals dispersion correction.

Reprogramming of lipid metabolism in hepatocellular carcinoma resulting in downregulation of phosphatidylcholines used as potential markers for diagnosis and prediction

BACKGROUND

Aberrant methylation and metabolic perturbations may deepen our understanding of hepatocarcinogenesis and help identify novel biomarkers for diagnosing hepatocellular carcinoma (HCC). We aimed to develop an HCC model based on a multi-omics.

RESEARCH DESIGN AND METHODS

Four hundred patient samples (200 with HCC and 200 with hepatitis B virus-related liver disease (HBVLD)) were subjected to liquid chromatography-mass spectrometry and multiplex bisulfite sequencing. Integrative analysis of clinical data, CpG data, and metabolome for the 20 complete imputation datasets within a for-loopwas used to identify biomarker.

RESULTS

Totally, 1,140 metabolites were annotated, of which 125 were differentially expressed. Lipid metabolism reprogramming in HCC, resulting in phosphatidylcholines (PC) significantly downregulated, partly due to the altered mitochondrial beta-oxidation of fatty acids with diverse chain lengths. Age, sex, serum-fetoprotein levels, cg05166871,cg14171514, cg18772205, PC (O-16:0/20:3(8Z, 11Z, 14Z)), and PC (16:1(9Z)/P-18:0) were used to develop the HCC model. The model presented a good diagnostic and an acceptable predictive performance. The cumulative incidence of HCC in low- and high-risk groups of HBVLD patients were 1.19% and 21.40%, respectively (p = 0.0039).

CONCLUSIONS

PCs serve as potential plasma biomarkers and help identify patients with HBVLD at risk of HCC who should be screened for early diagnosis and intervention.

Metabolomics of Esophageal Squamous Cell Carcinoma Tissues: Potential Biomarkers for Diagnosis and Promising Targets for Therapy

Background

The incidence of esophageal squamous cell carcinoma in China ranks first in the world. The early diagnosis technology is underdeveloped, and the prognosis is poor, which seriously threatens the quality of life of the Chinese people. Epidemiological findings are related to factors such as diet, living habits, and age. The specific mechanism is not clear yet. Metabolomics is a kind of omics that simultaneously and quantitatively analyzes the comprehensive profile of metabolites in living systems. It has unique advantages in the study of the diagnosis and pathogenesis of tumor-related diseases, especially in the search for biomarkers. Therefore, it is desirable to perform metabolic profiling analysis of cancer tissues through metabolomics to find potential biomarkers for the diagnosis and treatment of esophageal squamous cell carcinoma.

Methods

HPLC-TOF-MS/MS technology and Illumina Hiseq Xten Sequencing was used for the analysis of 210 pairs of matched esophageal squamous cell carcinoma tissues and normal tissues in Zhenjiang City, Jiangsu Province, a high-incidence area of esophageal cancer in China. Bioinformatics analysis was also performed.

Results

Through metabolomic and transcriptomic analysis, this study found that a total of 269 differential metabolites were obtained in esophageal squamous cell carcinoma and normal tissues, and 48 differential metabolic pathways were obtained through KEGG enrichment analysis. After further screening and identification, 12 metabolites with potential biomarkers to differentiate esophageal squamous cell carcinoma from normal tissues were obtained.

Conclusions

From the metabolomic data, 4 unknown compounds were found to be abnormally expressed in esophageal squamous cell carcinoma for the first time, such as 9,10-epoxy-12,15-octadecadienoate; 3 metabolites were found in multiple abnormal expression in another tumor, but upregulation or downregulation was found for the first time in esophageal cancer, such as oleoyl glycine; at the same time, it was further confirmed that five metabolites were abnormally expressed in esophageal squamous cell carcinoma, which was similar to the results of other studies, such as PE.

Shotgun Lipidomics for Differential Diagnosis of HPV-Associated Cervix Transformation

A dramatic increase in cervical diseases associated with human papillomaviruses (HPV) in women of reproductive age has been observed over the past decades. An accurate differential diagnosis of the severity of cervical intraepithelial neoplasia and the choice of the optimal treatment requires the search for effective biomarkers with high diagnostic and prognostic value. The objective of this study was to introduce a method for rapid shotgun lipidomics to differentiate stages of HPV-associated cervix epithelium transformation. Tissue samples from 110 HPV-positive women with cervicitis (n = 30), low-grade squamous intraepithelial lesions (LSIL) (n = 30), high-grade squamous intraepithelial lesions (HSIL) (n = 30), and cervical cancers (n = 20) were obtained. The cervical epithelial tissue lipidome at different stages of cervix neoplastic transformation was studied by a shotgun label-free approach. It is based on electrospray ionization mass spectrometry (ESI-MS) data of a tissue extract. Lipidomic data were processed by the orthogonal projections to latent structures discriminant analysis (OPLS-DA) to build statistical models, differentiating stages of cervix transformation. Significant differences in the lipid profile between the lesion and surrounding tissues were revealed in chronic cervicitis, LSIL, HSIL, and cervical cancer. The lipids specific for HPV-induced cervical transformation mainly belong to glycerophospholipids: phosphatidylcholines, and phosphatidylethanolamines. The developed diagnostic OPLS-DA models were based on 23 marker lipids. More than 90% of these marker lipids positively correlated with the degree of cervix transformation. The algorithm was developed for the management of patients with HPV-associated diseases of the cervix, based on the panel of 23 lipids as a result. ESI-MS analysis of a lipid extract by direct injection through a loop, takes about 25 min (including preparation of the lipid extract), which is significantly less than the time required for the HPV test (several hours for hybrid capture and about an hour for PCR). This makes lipid mass spectrometric analysis a promising method for express diagnostics of HPV-associated neoplastic diseases of the cervix.

Liquid Biopsies in Head and Neck Cancer: Current State and Future Challenges

Head and neck cancers are the seventh most frequent malignancy worldwide, consisting of a heterogeneous group of cancers that develop in the oral cavity, pharynx, and larynx, with head and neck squamous cell carcinoma (HNSCC) being the most common pathology. Due to limitations with screening and physical examination, HNSCC often presents in advanced disease states and is thus associated with poor survival. In this setting, liquid biopsies, or obtaining patient bodily fluid samples for cancer diagnosis and prognosis, may play a dramatic role in optimizing care for HNSCC patients. In recent years, there have been dramatic advancements in investigations focused on optimizing and implementing liquid biopsies in general, and specifically for HNSCC patients. Moving forward, there remain significant challenges in liquid biopsy technological development, as well as opportunities for the development of HNSCC liquid biopsy clinical trials and treatment paradigms. In this review, we discuss the current state of liquid biopsy technologies via circulating tumor cells, circulating tumor DNA and exosomes, approaches in head and neck cancer, challenges to optimization and application of liquid biopsies for clinical study, and future prospects for this field of research as it applies to head and neck cancer.

Serum metabolomics analysis for the progression of esophageal squamous cell carcinoma

BACKGROUND: Previous metabolomics studies have found differences in metabolic characteristics between the healthy and ESCC patients. However, few of these studies concerned the whole process of the progression of ESCC. This study aims to explore serum metabolites associated with the progression of ESCC.

METHODS: Serum samples from 653 participants (305 normal, 77 esophagitis, 228 LGD, and 43 HGD/ESCC) were examined by ultra-high performance liquid chromatography quadruple time-of-flight mass spectrometry (UHPLC-QTOF/MS). Principal component analysis (PCA) was first applied to obtain an overview of the clustering trend for the multidimensional data. Fuzzy c-means (FCM) clustering was then used to screen metabolites with a changing tendency in the progression of ESCC. Univariate ordinal logistic regression analysis and multiple ordinal logistic regression analysis were applied to evaluate the association of metabolites with the risk of ESCC progression, and adjusted for age, gender, BMI, tobacco smoking, and alcohol drinking status.

RESULTS: After FCM clustering analysis, a total of 38 metabolites exhibiting changing tendency among normal, esophagitis, LGD, and HGD/ESCC patients. Final results showed 15 metabolites associated with the progression of ESCC. Ten metabolites (dopamine, L-histidine, 5-hydroxyindoleacetate, L-tryptophan, 2'-O-methylcytidine, PC (14:0/0:0), PC (O-16:1/0:0), PE (18:0/0:0), PC (16:1/0:0), PC (18:2/0:0)) were associated with decreased risk of developing ESCC. Five metabolites (hypoxanthine, inosine, carnitine (14:1), glycochenodeoxycholate, PC (P-18:0/18:3)) were associated with increased risk of developing ESCC.

CONCLUSIONS: These results demonstrated that serum metabolites are associated with the progression of ESCC. These metabolites are capable of potential biomarkers for the risk prediction and early detection of ESCC.

Metabolomics for Diagnosis and Prognosis of Uterine Diseases? A Systematic Review

This systematic review analyses the contribution of metabolomics to the identification of diagnostic and prognostic biomarkers for uterine diseases. These diseases are diagnosed invasively, which entails delayed treatment and a worse clinical outcome. New options for diagnosis and prognosis are needed. PubMed, OVID, and Scopus were searched for research papers on metabolomics in physiological fluids and tissues from patients with uterine diseases. The search identified 484 records. Based on inclusion and exclusion criteria, 44 studies were included into the review. Relevant data were extracted following the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analysis) checklist and quality was assessed using the QUADOMICS tool. The selected metabolomics studies analysed plasma, serum, urine, peritoneal, endometrial, and cervico-vaginal fluid, ectopic/eutopic endometrium, and cervical tissue. In endometriosis, diagnostic models discriminated patients from healthy and infertile controls. In cervical cancer, diagnostic algorithms discriminated patients from controls, patients with good/bad prognosis, and with/without response to chemotherapy. In endometrial cancer, several models stratified patients from controls and recurrent from non-recurrent patients. Metabolomics is valuable for constructing diagnostic models. However, the majority of studies were in the discovery phase and require additional research to select reliable biomarkers for validation and translation into clinical practice. This review identifies bottlenecks that currently prevent the translation of these findings into clinical practice.

Interplay Between EGFR and the Platelet-Activating Factor/PAF Receptor Signaling Axis Mediates Aggressive Behavior of Cervical Cancer

Epidermal growth factor receptor (EGFR) is a receptor tyrosine kinase widely expressed in cervical tumors, being correlated with adverse clinical outcomes. EGFR may be activated by a diversity of mechanisms, including transactivation by G-protein coupled receptors (GPCRs). Studies have also shown that platelet-activating factor (PAF), a pro-inflammatory phospholipid mediator, plays an important role in the cancer progression either by modulating the cancer cells or the tumor microenvironment. Most of the PAF effects seem to be mediated by the interaction with its receptor (PAFR), a member of the GPCRs family. PAFR- and EGFR-evoked signaling pathways contribute to tumor biology; however, the interplay between them remains uninvestigated in cervical cancer. In this study, we employed The Cancer Genome Atlas (TCGA) and cancer cell lines to evaluate possible cooperation between EGFR, PAFR, and lysophosphatidylcholine acyltransferases (LPCATs), enzymes involved in the PAF biosynthesis, in the context of cervical cancer. It was observed a strong positive correlation between the expression of EGFR × PAFR and EGFR × LPCAT2 in 306 cervical cancer samples. The increased expression of LPCAT2 was significantly correlated with poor overall survival. Activation of EGFR upregulated the expression of PAFR and LPCAT2 in a MAPK-dependent fashion. At the same time, PAF showed the ability to transactivate EGFR leading to ERK/MAPK activation, cyclooxygenase-2 (COX-2) induction, and cell migration. The positive crosstalk between the PAF-PAFR axis and EGFR demonstrates a relevant linkage between inflammatory and growth factor signaling in cervical cancer cells. Finally, combined PAFR and EGFR targeting treatment impaired clonogenic capacity and viability of aggressive cervical cancer cells more strongly than each treatment separately. Collectively, we proposed that EGFR, LPCAT2, and PAFR emerge as novel targets for cervical cancer therapy.

Laser-assisted rapid evaporative ionisation mass spectrometry (LA-REIMS) as a metabolomics platform in cervical cancer screening

Background

The introduction of high-risk human papillomavirus (hrHPV) testing as part of primary cervical screening is anticipated to improve sensitivity, but also the number of women who will screen positive. Reflex cytology is the preferred triage test in most settings but has limitations including moderate diagnostic accuracy, lack of automation, inter-observer variability and the need for clinician-collected sample. Novel, objective and cost-effective approaches are needed.

Methods

In this study, we assessed the potential use of an automated metabolomic robotic platform, employing the principle of laser-assisted Rapid Evaporative Ionisation Mass Spectrometry (LA-REIMS) in cervical cancer screening.

Findings

In a population of 130 women, LA-REIMS achieved 94% sensitivity and 83% specificity (AUC: 91.6%) in distinguishing women testing positive (n = 65) or negative (n = 65) for hrHPV. We performed further analysis according to disease severity with LA-REIMS achieving sensitivity and specificity of 91% and 73% respectively (AUC: 86.7%) in discriminating normal from high-grade pre-invasive disease.

Interpretation

This automated high-throughput technology holds promise as a low-cost and rapid test for cervical cancer screening and triage. The use of platforms like LA-REIMS has the potential to further improve the accuracy and efficiency of the current national screening programme.

Funding

Work was funded by the MRC Imperial Confidence in Concept Scheme, Imperial College Healthcare Charity, British Society for Colposcopy and Cervical Pathology, National Research Development and Innovation Office of Hungary, Waters corporation and NIHR BRC.

Lipid and protein tumor markers for head and neck squamous cell carcinoma identified by imaging mass spectrometry

Head and neck squamous cell carcinoma (HNSCC) is the sixth most common cancer worldwide. To improve pre- and post-operative diagnosis and prognosis novel molecular markers are desirable. Here we used MALDI imaging mass spectrometry (IMS) and immunohistochemistry (IHC) to seek tumor specific expression of proteins and lipids in HNSCC samples. Among low molecular weight proteins visualized, S100A8 and S100A9 were found to be expressed in the regions of tumor tissue but not in the surrounding healthy stroma of a post-operative microdissected tissue. Marker potential of S100A8 and S100A9 was confirmed by immunohistochemistry of paraffin-embedded pathological samples. Imaging lipids showed a remarkable depletion of lysophosphatidylcholine species LPC[16:0], LPC[18:2] and, in parallel, accumulation of major glycerophospholipid species PE-P[36:4], PC[32:1], PC[34:1] in neoplastic areas. This was confirmed by shotgun lipidomics of dissected healthy and tumor tissue sections. A combination of the negative (LPC[16:0]) and positive (PC[32:1], PC[34:1]) markers was also applicable to uncover tumorous character of a pre-operative biopsy. Furthermore, marker potential of lysophospholipids was supported by elevated expression levels of the lysophospholipid degrading enzyme lysophospholipase A1 (LYPLA1) in the tumor regions of paraffin-embedded HNSCC samples. Finally, experimental evidence of 3D cell spheroid tests showed that LPC[16:0] facilitates HNSCC invasion, implying that HNSCC progression in vivo may be dependent on lysophospholipid supply. Altogether, a series of novel proteins and lipid species were identified by IMS and IHC screening, which may serve as potential molecular markers for tumor diagnosis, prognosis, and may pave the way to better understand HNSCC pathophyisiology.

Metabolomic Biomarkers in Gynecology: A Treasure Path or a False Path?

Omic-technologies (genomics, transcriptomics, proteomics and metabolomics) have become more important in current medical science. Among them, it is metabolomics that most accurately reflects the minor changes in body functioning, as it focuses on metabolome - the group of the metabolism products, both intermediate and end. Therefore, metabolomics is actively engaged in fundamental and clinical studies and search for potential biomarkers. The biomarker could be used in diagnostics, management and stratification of the patients, as well as in prognosing the outcomes. The good example is gynecology, since many gynecological diseases lack effective biomarkers. In the current review, we aimed to summarize the results of the studies, devoted to the search of potential metabolomic biomarkers for the most common gynecological diseases.

An Updated Review of Pro- and Anti-Inflammatory Properties of Plasma Lysophosphatidylcholines in the Vascular System

Lysophosphatidylcholines are a group of bioactive lipids heavily investigated in the context of inflammation and atherosclerosis development. While present in plasma during physiological conditions, their concentration can drastically increase in certain inflammatory states. Lysophosphatidylcholines are widely regarded as potent pro-inflammatory and deleterious mediators, but an increasing number of more recent studies show multiple beneficial properties under various pathological conditions. Many of the discrepancies in the published studies are due to the investigation of different species or mixtures of lysophatidylcholines and the use of supra-physiological concentrations in the absence of serum or other carrier proteins. Furthermore, interpretation of the results is complicated by the rapid metabolism of lysophosphatidylcholine (LPC) in cells and tissues to pro-inflammatory lysophosphatidic acid. Interestingly, most of the recent studies, in contrast to older studies, found lower LPC plasma levels associated with unfavorable disease outcomes. Being the most abundant lysophospholipid in plasma, it is of utmost importance to understand its physiological functions and shed light on the discordant literature connected to its research. LPCs should be recognized as important homeostatic mediators involved in all stages of vascular inflammation. In this review, we want to point out potential pro- and anti-inflammatory activities of lysophospholipids in the vascular system and highlight recent discoveries about the effect of lysophosphatidylcholines on immune cells at the endothelial vascular interface. We will also look at their potential clinical application as biomarkers.

FeOOH@Metal-Organic Framework Core-Satellite Nanocomposites for the Serum Metabolic Fingerprinting of Gynecological Cancers

High-throughput metabolic analysis is of significance in diagnostics, while tedious sample pretreatment has largely hindered its clinic application. Herein, we designed FeOOH@ZIF-8 composites with enhanced ionization efficiency and size-exclusion effect for laser desorption/ionization mass spectrometry (LDI-MS)-based metabolic diagnosis of gynecological cancers. The FeOOH@ZIF-8-assisted LDI-MS achieved rapid, sensitive, and selective metabolic fingerprints of the native serum without any enrichment or purification. Further analysis of extracted serum metabolic fingerprints successfully discriminated patients with gynecological cancers (GCs) from healthy controls and also differentiated three major subtypes of GCs. Given the low cost, high-throughput, and easy operation, our approach brings a new dimension to disease analysis and classification.

The intelligent knife (iKnife) and its intraoperative diagnostic advantage for the treatment of cervical disease

Clearance of surgical margins in early cervical cancer prevents the need for adjuvant chemoradiation and associated morbidity and allows fertility preservation. Clearance of disease is also crucial in the surgical management of local recurrence of cervical tumors with exenterative surgery. In this study intelligent knife technology was able to discriminate healthy from abnormal lesions on the cervix with high accuracy, highlighting the potential to improve intraoperative management of women treated surgically for cervical cancer and, as a result, patient outcomes. While pilot experiments in vivo are encouraging, accuracy remains to be validated in larger patient cohorts. Future studies could also explore whether this technology could be used for management of cervical preinvasive disease.

Clearance of surgical margins in cervical cancer prevents the need for adjuvant chemoradiation and allows fertility preservation. In this study, we determined the capacity of the rapid evaporative ionization mass spectrometry (REIMS), also known as intelligent knife (iKnife), to discriminate between healthy, preinvasive, and invasive cervical tissue. Cervical tissue samples were collected from women with healthy, human papilloma virus (HPV) ± cervical intraepithelial neoplasia (CIN), or cervical cancer. A handheld diathermy device generated surgical aerosol, which was transferred into a mass spectrometer for subsequent chemical analysis. Combination of principal component and linear discriminant analysis and least absolute shrinkage and selection operator was employed to study the spectral differences between groups. Significance of discriminatory m/z features was tested using univariate statistics and tandem MS performed to elucidate the structure of the significant peaks allowing separation of the two classes. We analyzed 87 samples (normal = 16, HPV ± CIN = 50, cancer = 21 patients). The iKnife discriminated with 100% accuracy normal (100%) vs. HPV ± CIN (100%) vs. cancer (100%) when compared to histology as the gold standard. When comparing normal vs. cancer samples, the accuracy was 100% with a sensitivity of 100% (95% CI 83.9 to 100) and specificity 100% (79.4 to 100). Univariate analysis revealed significant MS peaks in the cancer-to-normal separation belonging to various classes of complex lipids. The iKnife discriminates healthy from premalignant and invasive cervical lesions with high accuracy and can improve oncological outcomes and fertility preservation of women treated surgically for cervical cancer. Larger in vivo research cohorts are required to validate these findings.

Deep Metabolomics of a High-Grade Serous Ovarian Cancer Triple-Knockout Mouse Model

High-grade serous carcinoma (HGSC) is the most common and deadliest ovarian cancer (OC) type, accounting for 70-80% of OC deaths. This high mortality is largely due to late diagnosis. Early detection is thus crucial to reduce mortality, yet the tumor pathogenesis of HGSC remains poorly understood, making early detection exceedingly difficult. Faithfully and reliably representing the clinical nature of human HGSC, a recently developed triple-knockout (TKO) mouse model offers a unique opportunity to examine the entire disease spectrum of HGSC. Metabolic alterations were investigated by applying ultra-performance liquid chromatography-mass spectrometry (UPLC-MS) to serum samples collected from these mice at premalignant, early, and advanced stages of HGSC. This comprehensive analysis revealed a panel of 29 serum metabolites that distinguished mice with HGSC from controls and mice with uterine tumors with over 95% accuracy. Meanwhile, our panel could further distinguish early-stage HGSC from controls with 100% accuracy and from advanced-stage HGSC with over 90% accuracy. Important identified metabolites included phospholipids, sphingomyelins, sterols, N-acyltaurine, oligopeptides, bilirubin, 2(3)-hydroxysebacic acids, uridine, N-acetylneuraminic acid, and pyrazine derivatives. Overall, our study provides insights into dysregulated metabolism associated with HGSC development and progression, and serves as a useful guide toward early detection.

LC/MS-Based Polar Metabolite Profiling Identified Unique Biomarker Signatures for Cervical Cancer and Cervical Intraepithelial Neoplasia Using Global and Targeted Metabolomics

Cervical cancer remains one of the most prevalent cancers among females worldwide. Therefore, it is important to discover new biomarkers for early diagnosis of cervical intraepithelial neoplasia (CIN) and cervical cancer, preferably non-invasive ones. In the present study, we aimed to identify unique metabolic signatures for CINs and cervical cancers using global and targeted metabolomic profiling. Plasma samples (69 normal, 55 CIN1, 42 CIN2/3, and 60 cervical cancer) were examined by ultra-performance liquid chromatography-quadrupole-time-of-flight mass spectrometry (UPLC-QTOF-MS) coupled with multivariate statistical analysis. Metabolic pathways were analyzed using the integrated web-based tool MetaboAnalyst. A multivariate logistic regression analysis was conducted to evaluate the combined association of metabolites and human papillomavirus (HPV) status with the risk of cervical carcinogenesis. A total of 28 metabolites exhibiting discriminating levels among normal, CIN, and cervical cancer patients (Kruskal–Wallis test p < 0.05) were identified in the global profiling analysis. The pathway analysis showed significantly altered alanine, aspartate, and glutamate metabolic pathways (FDR p-value < 0.05) in both the discovery and validation phases. Seven metabolites (AMP, aspartate, glutamate, hypoxanthine, lactate, proline, and pyroglutamate) were discriminated between CINs and cervical cancer versus normal (area under the curve (AUC) value > 0.8). The levels of these metabolites were significantly high in patients versus normal (p < 0.0001) and were associated with increased risk of developing CIN2/3 and cervical cancer. Additionally, elevated levels of the seven metabolites combined with positive HPV status were correlated with substantial risk of cancer progression. These results demonstrated that metabolomics profiling is capable of distinguishing CINs and cervical cancers from normal and highlighted potential biomarkers for the early detection of cervical carcinogenesis.

Recent Advances on the Molecular Mechanism of Cervical Carcinogenesis Based on Systems Biology Technologies

Cervical cancer is one of the common malignancies in women worldwide. Exploration of pathogenesis and molecular mechanism of cervical cancer is pivotal for development of effective treatment for this disease. Recently, systems biology approaches based on high-throughput technologies have been carried out to investigate the expression of some genes and proteins in genomics, transcriptomics, proteomics, and metabonomics of cervical cancer. Compared with traditional methods，systems biology technology has been shown to provide large of information regarding prognostic biomarkers and therapeutic targets for cervical cancer. These molecular signatures from system biology technology could be useful to understand the molecular mechanisms of cervical cancer development and progression, and help physicians to design targeted therapeutic strategies for patients with cervical cancer.

Similarities in Blood Mononuclear Cell Membrane Phospholipid Profiles During Malignancy

Phospholipids (PLs), key elements of cellular membranes, are regulated reciprocally with membrane proteins and can act as sensors for alterations in physiological or pathological states of cells including initiation and development of cancer. On the other hand, peripheral blood mononuclear cells (MNCs) play an important role in antitumor immune response by reacting to cancerous modifications in distant organs. In the current study, we tested the hypothesis that tumor initiation and development are reflected in the alteration pattern of the MNC PL component. We analyzed MNC membrane PL fractions in samples from healthy individuals and from patients with diverse types of cancers to reveal possible alterations induced by malignancy. Compared to healthy controls, the cancer samples demonstrated shifts in several membrane PL profiles. In particular, when analyzing cancer data pooled together, there were significantly higher levels in lysophosphatidylcholine, phosphatidylcholine, and phosphatidylethanolamine fractions, and significantly lower quantities in phosphatidylinositol, phosphatidylserine, and phosphatidic acid fractions in cancer samples compared to controls. The levels of sphingomyelins and diphosphatidylglycerols were relatively unaffected. Most of the differences in PLs were sustained during the analysis of individual cancers such as breast cancer and chronic lymphocytic leukemia. Our findings suggest the presence of a common pattern of changes in MNC PLs during malignancy.

Plasma metabonomics investigation reveals involvement of fatty acid oxidation in hematotoxicity in Chinese benzene-exposed workers with low white blood cell count

Benzene is an environmental and occupational contaminant. Health hazards associated with occupational benzene exposure is a major public health problem in China. In this study, we analyzed metabolite profiles among plasma samples collected from benzene-exposed workers with low white blood cell count (BLWs) and healthy controls using high-performance liquid chromatography-time-of-flight mass spectrometry. To screen potential benzene hematotoxicity biomarkers and metabolic pathways, principal component analysis was used to examine metabolite profile changes in plasma samples. The alterations in fatty acid oxidation (FAO) pathway were consistent with our previous findings in a mouse model; hence, two key genes were selected and verified in WBC samples. A total of nine identified metabolites were significantly changed in BLWs, which were involved in glutathione metabolism, porphyrin metabolism, lipid metabolism pathway, and FAO metabolism. Furthermore, compared with healthy controls, the mRNA expressions of carnitine acyltransferase (CRAT) and ACADVL were significantly increased in BLWs. Particularly, WBC counts was negatively correlated with the expression of AVADVL in BLWs. These aberrant metabolites could act as potential biomarkers for benzene hematotoxicity. In addition, fatty acid oxidation pathway may play a critical role in the development of hematotoxicity caused by benzene.

Individualized metabolic profiling stratifies pancreatic and biliary tract cancer: a useful tool for innovative screening programs and predictive strategies in healthcare

BACKGROUND

Pancreatic cancer (PC) and biliary tract cancer (BTC) are highly aggressive cancers, characterized by their rarity, difficulty in diagnosis, and overall poor prognosis. Diagnosis of PC and BTC is complex and is made using a combination of appropriate clinical suspicion, imaging and endoscopic techniques, and cytopathological examination. However, the late-stage detection and poor prognosis of this tumor have led to an urgent need for biomarkers for early and/or predictive diagnosis and improved personalized treatments.

WORKING HYPOTHESIS

There are two hypotheses for focusing on low-mass metabolites in the blood. First, valuable information can be obtained from the masses and relative amounts of such metabolites, which present as low-mass ions (LMIs) in mass spectra. Second, metabolic profiling of individuals may provide important information regarding biological changes in disease states that is useful for the early diagnosis of PC and BTC.

MATERIALS AND METHODS

To assess whether profiling metabolites in serum can serve as a non-invasive screening tool for PC and BTC, 320 serum samples were obtained from patients with PC (n = 51), BTC (n = 39), colorectal cancer (CRC) (n = 100), and ovarian cancer (OVC) (n = 30), and from healthy control subjects (control) (n = 100). We obtained information on the relative amounts of metabolites, as LMIs, via triple time-of-flight mass spectrometry. All data were analyzed according to the peak area ratios of discriminative LMIs.

RESULTS AND CONCLUSIONS

The levels of the 14 discriminative LMIs were higher in the PC and BTC groups than in the control, CRC and OVC groups, but only two LMIs discriminated between PC and BTC: lysophosphatidylcholine (LysoPC) (16:0) and LysoPC(20:4). The levels of these two LysoPCs were also slightly lower in the PC/BTC/CRC/OVC groups compared with the control group. Taken together, the data showed that metabolic profiling can precisely denote the status of cancer, and, thus, could be useful for screening. This study not only details efficient methods to identify discriminative LMIs for cancer screening but also provides an example of metabolic profiling for distinguishing PC from BTC. Furthermore, the two metabolites [LysoPC(16:0), LysoPC(20:4)] shown to discriminate these diseases are potentially useful when combined with other, previously identified protein or metabolic biomarkers for predictive, preventive and personalized medical approach.

Evaluation of the mRNA expression levels of integrins α3, α5, β1 and β6 as tumor biomarkers of oral squamous cell carcinoma

Integrin signaling may modulate several different functions involved in cell migration, invasion, proliferation and motility, and is a potential candidate biomarker for oral cancer. In the present study, a total of four integrin genes were evaluated as potential biomarkers of oral squamous cell carcinoma (OSCC). Gene expression was determined using the reverse transcription-quantitative polymerase chain reaction in 55 OSCC and 55 matched normal oral tissues. The performance of individual and combined biomarkers was analyzed by receiver operating characteristic (ROC) analysis based on the relative mRNA expression (OSCC vs. matched oral tissue from the tumor-free margin), which was calculated using the ΔΔCq value (ΔCq of OSCC-ΔCq of oral tissue from the tumor-free margin of the same patient). In the individual ROC analysis, the areas under the ROC curve (AUCs) of relative mRNA expression (ΔΔCq) of integrin subunit α3 (ITGA3), integrin subunit α5 (ITGA5), integrin subunit β1 (ITGB1) and integrin subunit β6 (ITGB6) in all tumor locations were 0.724, 0.698, 0.640 and 0.657, respectively. For locations 2 (tongue/mouth part) and 3 (edentulous ridge), their individual AUC values were 0.840, 0.765, 0.725 and 0.763, respectively. In the cumulative ROC analysis, ITGA3, ITGA5 and ITGB1 genes exhibited the highest combined AUC values (0.809 and 0.871 for all locations and locations 2 and 3 combined, respectively) compared with other biomarker combinations. In conclusion, the results of the present study identified that higher mRNA expressions of ITGA3, ITGA5, ITGB1 and ITGB6 genes are suitable for OSCC diagnosis biomarkers. Cumulative ROC analysis indicated an improved overall performance compared with the best individual integrin biomarker of OSCC.

Molecular Signatures of High-Grade Cervical Lesions

Cervical cancer is the fourth most common neoplasia in women and the infection with human papilloma virus (HPV) is its necessary cause. Screening methods, currently based on cytology and HPV DNA tests, display low specificity/sensitivity, reducing the efficacy of cervical cancer screening programs. Herein, molecular signatures of cervical cytologic specimens revealed by liquid chromatography-mass spectrometry (LC-MS), were tested in their ability to provide a metabolomic screening for cervical cancer. These molecules were tested whether they could clinically differentiate insignificant HPV infections from precancerous lesions. For that, high-grade squamous intraepithelial lesions (HSIL)-related metabolites were compared to those of no cervical lesions in women with and without HPV infection. Samples were collected from women diagnosed with normal cervix (N = 40) and from those detected with HSIL from cytology and colposcopy (N = 40). Liquid-based cytology diagnosis, DNA HPV-detection test, and LC-MS analysis were carried out for all the samples. The same sample, in a customized collection medium, could be used for all the diagnostic techniques employed here. The metabolomic profile of cervical cancer provided by LC-MS was found to indicate unique molecular signatures for HSIL, being two ceramides and a sphingosine metabolite. These molecules occurred independently of women’s HPV status and could be related to the pre-neoplastic phenotype. Statistical models based on such findings could correctly discriminate and classify HSIL and no cervical lesion women. The results showcase the potential of LC-MS as an emerging technology for clinical use in cervical cancer screening, although further validation with a larger sample set is still necessary.

Models including plasma levels of sphingomyelins and phosphatidylcholines as diagnostic and prognostic biomarkers of endometrial cancer

In endometrial cancer, biomarkers for preoperative identification of patients with low risk for disease progression would enable stratification according to the extent of surgery needed, and would avoid the complications that can be associated with radical surgery. A panel of proteins, amino acids, enzymes, and miRNA has been investigated as potential biomarkers for endometrial cancer. At the time of the manuscript submission targeted metabolomics/lipidomics approaches have not been applied to biomarker research in endometrial cancer. Using electrospray ionization-tandem mass spectrometry we quantified 163 metabolites in 126 plasma samples (61 patients with endometrial cancer, 65 control patients). Three single phosphatidylcholines were identified with significantly decreased levels in patients with endometrial cancer. A diagnostic model was defined as the ratio between acylcarnitine C16 and phosphatidylcholine PCae C40:1, the ratio between proline and tyrosine, and the ratio between the two phosphatidylcholines PCaa C42:0 and PCae C44:5; which provided sensitivity of 85.25%, specificity of 69.23%, and AUC of 0.837. Addition of smoking status further improved the constructed diagnostic model (AUC = 0.855). The presence of the major prognostic factors of deep myometrial invasion and lymphovascular invasion were also associated with altered metabolite concentrations. A prognostic model for deep myometrial invasion included the ratio between two hydroxysphingomyelins SMOH C14:1 and SMOH C24:1, and the ratio between two phosphatidylcholines PCaa C40:2 and PCaa C42:6, which provided sensitivity of 81.25%, specificity of 86.36%, and AUC of 0.857. The model for lymphovascular invasion included the ratio between two phosphatidylcholines PCaa C34:4 and PCae C38:3, and the ratio between acylcarnitine C16:2 and phosphatidylcholine PCaa C38:1, which provided sensitivity of 88.89%, specificity of 84.31%, and AUC of 0.935.

Activation of choline kinase drives aberrant choline metabolism in esophageal squamous cell carcinomas

Esophageal squamous cell carcinoma (ESCC) is a major health threat worldwide. Research focused on molecular events associated with ESCC carcinogenesis for diagnosis, treatment and prevention is needed. Our goal is to discover novel biomarkers and investigate the underlying molecular mechanisms of ESCC progression by employing a global metabolomic approach. Sera from 34 ESCC patients and 32 age and sex matched healthy controls were profiled using two-dimensional liquid chromatography-mass spectrometry (2D LC-MS). We identified 120 differential metabolites in ESCC patient serums compared to healthy controls. Several amino acids, serine, arginine, lysine and histidine were significantly changed in ESCC patients. Most importantly, we found dysregulated lipid metabolism as an important characteristic in ESCC patients. Several free fat acids (FFA) and carnitines were found down-regulated in ESCC patients. Choline was significantly increased and phosphatidylcholines (PC) were significantly decreased in ESCC serum. The high expression of choline and low expression of total PC in patient serum were associated with the high expression of choline kinase (Chok) and activated Kennedy pathway in ESCC cells. Chok expression can serve as a significant biomarker for ESCC prognosis. In conclusion, metabolite profiles in the ESCC patient serum were significantly different from those in the healthy controls. Phosphatidylcholines and Chok, the key enzyme in the PC metabolism pathway, may serve as novel biomarkers for ESCC.

Lipidomics in translational research and the clinical significance of lipid-based biomarkers

Lipidomics is a rapidly developing field of study that focuses on the identification and quantitation of various lipid species in the lipidome. Lipidomics has now emerged in the forefront of scientific research due to the importance of lipids in metabolism, cancer, and disease. Using both targeted and untargeted mass spectrometry as a tool for analysis, progress in the field has rapidly progressed in the last decade. Having the ability to assess these small molecules in vivo has led to better understanding of several lipid-driven mechanisms and the identification of lipid-based biomarkers in neurodegenerative disease, cancer, sepsis, wound healing, and pre-eclampsia. Biomarker identification and mechanistic understanding of specific lipid pathways linked to a disease's pathologies can form the foundation in the development of novel therapeutics in hopes of curing human disease.

Plasma lipid profiling and diagnostic biomarkers for oral squamous cell carcinoma

Biological requirements for tumor cell proliferation include the sustained increase of structural, energetic, signal transduction and biosynthetic precursors. Because lipids participate in membrane construction, energy storage, and cell signaling. We hypothesized that the differences in lipids between malignant carcinoma and normal controls could be reflected in the bio-fluids. A total of 100 pre-operative plasma samples were collected from 50 oral squamous cell carcinoma (OSCC), 50 normal patients and characterize by lipid profiling using ultra performance liquid chromatography/electro spray ionization mass spectrometry (UPLC-MS). The lipid profiles of the OSCC and control samples as well as the different stages were compared. Differentially expressed lipids were categorized as glycerophospholipids and sphingolipids. All glycerophospholipids were decreased, especially phosphatidylcholine and phosphoethanolamine plasmalogens, whereas sphingolipids were increased in the OSCC patients compared to the controls. We further identified 12 staging related lipids, which could be utilized to discriminate early stage patients from advanced stage patients. In the future, the differential lipids may provide biologists with additional information regarding lipid metabolism and guide clinicians in making individualized therapeutic decisions if these results are confirmed in a larger study.

A Comprehensive Analysis of Metabolomics and Transcriptomics in Cervical Cancer

Cervical cancer (CC) still remains a common and deadly malignancy among females in developing countries. More accurate and reliable diagnostic methods/biomarkers should be discovered. In this study, we performed a comprehensive analysis of metabolomics (285 samples) and transcriptomics (52 samples) on the potential diagnostic implication and metabolic characteristic description in cervical cancer. Sixty-two metabolites were different between CC and normal controls (NOR), in which 5 metabolites (bilirubin, LysoPC(17:0), n-oleoyl threonine, 12-hydroxydodecanoic acid and tetracosahexaenoic acid) were selected as candidate biomarkers for CC. The AUC value, sensitivity (SE), and specificity (SP) of these 5 biomarkers were 0.99, 0.98 and 0.99, respectively. We further analysed the genes in 7 significantly enriched pathways, of which 117 genes, that were expressed differentially, were mainly involved in catalytic activity. Finally, a fully connected network of metabolites and genes in these pathways was built, which can increase the credibility of our selected metabolites. In conclusion, our biomarkers from metabolomics could set a path for CC diagnosis and screening. Our results also showed that variables of both transcriptomics and metabolomics were associated with CC.