Metabolomic analysis identifies differentially produced oral metabolites, including the oncometabolite 2-hydroxyglutarate, in patients with head and neck squamous cell carcinoma

The role of salivary metabolomics in chronic periodontitis: bridging oral and systemic diseases

BACKGROUND

Chronic periodontitis is a condition impacting approximately 50% of the world's population. As chronic periodontitis progresses, the bacteria in the oral cavity change resulting in new microbial interactions which in turn influence metabolite production. Chronic periodontitis manifests with inflammation of the periodontal tissues, which is progressively developed due to bacterial infection and prolonged bacterial interaction with the host immune response. The bi-directional relationship between periodontitis and systemic diseases has been reported in many previous studies. Traditional diagnostic methods for chronic periodontitis and systemic diseases such as chronic kidney diseases (CKD) have limitations due to their invasiveness, requiring practised individuals for sample collection, frequent blood collection, and long waiting times for the results. More rapid methods are required to detect such systemic diseases, however, the metabolic profiles of the oral cavity first need to be determined.

AIM OF REVIEW

In this review, we explored metabolomics studies that have investigated salivary metabolic profiles associated with chronic periodontitis and systemic illnesses including CKD, oral cancer, Alzheimer's disease, Parkinsons's disease, and diabetes to highlight the most recent methodologies that have been applied in this field.

KEY SCIENTIFIC CONCEPTS OF THE REVIEW

Of the rapid, high throughput techniques for metabolite profiling, Nuclear magnetic resonance (NMR) spectroscopy was the most applied technique, followed by liquid chromatography-mass spectrometry (LC-MS) and gas chromatography-mass spectrometry (GC-MS). Furthermore, Raman spectroscopy was the most used vibrational spectroscopic technique for comparison of the saliva from periodontitis patients to healthy individuals, whilst Fourier Transform Infra-Red Spectroscopy (FT-IR) was not utilised as much in this field. A recommendation for cultivating periodontal bacteria in a synthetic medium designed to replicate the conditions and composition of saliva in the oral environment is suggested to facilitate the identification of their metabolites. This approach is instrumental in assessing the potential of these metabolites as biomarkers for systemic illnesses.

A simple and effective method for smartphone-based detection of polyamines in oral cancer

Oral cancer accounts for 50%-70% of all cancer-related deaths in India and ranks sixth among the most frequent cancers globally. Roughly 90% of oral malignancies are histologically arise from squamous cells and are therefore called oral squamous cell carcinoma. Organic polycations known as biogenic polyamines, for example, putrescine (Put), spermidine (Spd), and spermine (Spm), are vital for cell proliferation, including gene expression control, regulation of endonuclease-mediated fragmentation of DNA, and DNA damage inhibition. Higher Spm and Spd levels have been identified as cancer biomarkers for detecting tumour development in various cancers. The current study utilises tannic acid, a polyphenolic compound, as a reducing and capping agent to fabricate AuNPs via a one-step microwave-assisted synthesis. The fabricated TA@AuNPs were utilised as a nanoprobe for colourimetric sensing of polyamines in PBS. When TA@AuNPs are added to the polyamine, the amine groups in polyamines interact with the phenolic groups of TA@AuNPs via hydrogen bonding or electrostatic interactions. These interactions cause the aggregation of TA@AuNPs, resulting in a red shift of the Surface Plasmon Resonance band of TA@AuNPs from 530 nm to 560 nm. The nanoprobe was found to be highly specific for Spm at low concentrations. TA@AuNPs were able to detect Spm successfully in artificial saliva samples. On recording the RGB values of the sensing process using a smartphone app, it was found that as the nanoparticles aggregated due to the presence of Spm, the intensity of theR-value decreased, indicating the aggregation of TA@AuNPs due to interaction with the polyamine.

Development of an expert system for the classification of myalgic encephalomyelitis/chronic fatigue syndrome

Myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) is a severe condition with an uncertain origin and a dismal prognosis. There is presently no precise diagnostic test for ME/CFS, and the diagnosis is determined primarily by the presence of certain symptoms. The current study presents an explainable artificial intelligence (XAI) integrated machine learning (ML) framework that identifies and classifies potential metabolic biomarkers of ME/CFS. Metabolomic data from blood samples from 19 controls and 32 ME/CFS patients, all female, who were between age and body mass index (BMI) frequency-matched groups, were used to develop the XAI-based model. The dataset contained 832 metabolites, and after feature selection, the model was developed using only 50 metabolites, meaning less medical knowledge is required, thus reducing diagnostic costs and improving prognostic time. The computational method was developed using six different ML algorithms before and after feature selection. The final classification model was explained using the XAI approach, SHAP. The best-performing classification model (XGBoost) achieved an area under the receiver operating characteristic curve (AUCROC) value of 98.85%. SHAP results showed that decreased levels of alpha-CEHC sulfate, hypoxanthine, and phenylacetylglutamine, as well as increased levels of N-delta-acetylornithine and oleoyl-linoloyl-glycerol (18:1/18:2)[2], increased the risk of ME/CFS. Besides the robustness of the methodology used, the results showed that the combination of ML and XAI could explain the biomarker prediction of ME/CFS and provided a first step toward establishing prognostic models for ME/CFS.

Metabolic Patterns of High-Invasive and Low-Invasive Oral Squamous Cell Carcinoma Cells Using Quantitative Metabolomics and 13C-Glucose Tracing

Most current metabolomics studies of oral squamous cell carcinoma (OSCC) are mainly focused on identifying potential biomarkers for early screening and diagnosis, while few studies have investigated the metabolic profiles promoting metastasis. In this study, we aimed to explore the altered metabolic pathways associated with metastasis of OSCC. Here, we identified four OSCC cell models (CAL27, HN6, HSC-3, SAS) that possess different invasive heterogeneity via the transwell invasion assay and divided them into high-invasive (HN6, SAS) and low-invasive (CAL27, HSC-3) cells. Quantitative analysis and stable isotope tracing using [U-13C6] glucose were performed to detect the altered metabolites in high-invasive OSCC cells, low-invasive OSCC cells and normal human oral keratinocytes (HOK). The metabolic changes in the high-invasive and low-invasive cells included elevated glycolysis, increased fatty acid metabolism and an impaired TCA cycle compared with HOK. Moreover, pathway analysis demonstrated significant differences in fatty acid biosynthesis; arachidonic acid (AA) metabolism; and glycine, serine and threonine metabolism between the high-invasive and low-invasive cells. Furthermore, the high-invasive cells displayed a significant increase in the percentages of 13C-glycine, 13C-palmitate, 13C-stearic acid, 13C-oleic acid, 13C-AA and estimated FADS1/2 activities compared with the low-invasive cells. Overall, this exploratory study suggested that the metabolic differences related to the metastatic phenotypes of OSCC cells were concentrated in glycine metabolism, de novo fatty acid synthesis and polyunsaturated fatty acid (PUFA) metabolism, providing a comprehensive understanding of the metabolic alterations and a basis for studying related molecular mechanisms in metastatic OSCC cells.

Differences in the metabolomic profile of the human palatine tonsil between pediatrics and adults

Palatine tonsils (PT) are B cell-predominant lymphoid organs that provide primary immune responses to airborne and dietary pathogens. Numerous histopathological and immunological studies have been conducted on PT, yet no investigations have been conducted on its metabolic profile. We performed high-resolution magic angle spinning nuclear magnetic resonance spectroscopy-based metabolic profiling in 35 pediatric and 28 adult human palatine tonsillar tissue samples. A total of 36 metabolites were identified, and the levels of 10 metabolites were significantly different depending on age. Among them, partial correlation analysis shows that glucose levels increased with age, whereas glycine, phosphocholine, phosphoethanolamine, and ascorbate levels decreased with age. We confirmed the decrease in immunometabolic activity in adults through metabolomic analysis, which had been anticipated from previous histological and immunological studies on the PT. These results improve our understanding of metabolic changes in the PT with aging and serve as a basis for future tonsil-related metabolomic studies.

Developing a Method to Estimate the Downstream Metabolite Signals from Hyperpolarized [1-13C]Pyruvate

Hyperpolarized carbon-13 MRI has the advantage of allowing the study of glycolytic flow in vivo or in vitro dynamically in real-time. The apparent exchange rate constant of a metabolite dynamic signal reflects the metabolite changes of a disease. Downstream metabolites can have a low signal-to-noise ratio (SNR), causing apparent exchange rate constant inconsistencies. Thus, we developed a method that estimates a more accurate metabolite signal. This method utilizes a kinetic model and background noise to estimate metabolite signals. Simulations and in vitro studies with photon-irradiated and control groups were used to evaluate the procedure. Simulated and in vitro exchange rate constants estimated using our method were compared with the raw signal values. In vitro data were also compared to the Area-Under-Curve (AUC) of the cell medium in ¹³C Nuclear Magnetic Resonance (NMR). In the simulations and in vitro experiments, our technique minimized metabolite signal fluctuations and maintained reliable apparent exchange rate constants. In addition, the apparent exchange rate constants of the metabolites showed differences between the irradiation and control groups after using our method. Comparing the in vitro results obtained using our method and NMR, both solutions showed consistency when uncertainty was considered, demonstrating that our method can accurately measure metabolite signals and show how glycolytic flow changes. The method enhanced the signals of the metabolites and clarified the metabolic phenotyping of tumor cells, which could benefit personalized health care and patient stratification in the future.

Current and Future Biomarkers for Immune Checkpoint Inhibitors in Head and Neck Squamous Cell Carcinoma

With the introduction of immunotherapy, significant improvement has been made in the treatment of head and neck squamous cell carcinoma (HNSCC). However, only a small subset of patients with HNSCC benefit from immunotherapy. The current biomarker, a programmed cell death protein ligand 1 (PD-L1) expression that is widely used in treatment decision making for advanced HNSCC, has only a moderate predictive value. Additionally, PD-L1-based assay has critical inherent limitations due to its highly dynamic nature and lack of standardization. With the advance in molecular techniques and our understanding of biology, more reliable, reproducible, and practical novel biomarkers are being developed. These include but are not limited to neoantigen/mutation characteristics, immune transcriptomes, tumor-infiltrating immune cell composition, cancer epigenomic, proteomics and metabolic characteristics, and plasma-based and organoid assays.

Application of liquid biopsy as multi-functional biomarkers in head and neck cancer

Head and neck squamous cell carcinoma (HNSCC) is a molecularly heterogeneous disease, with a 5-year survival rate that still hovers at ~60% despite recent advancements. The advanced stage upon diagnosis, limited success with effective targeted therapy and lack of reliable biomarkers are among the key factors underlying the marginally improved survival rates over the decades. Prevention, early detection and biomarker-driven treatment adaptation are crucial for timely interventions and improved clinical outcomes. Liquid biopsy, analysis of tumour-specific biomarkers circulating in bodily fluids, is a rapidly evolving field that may play a striking role in optimising patient care. In recent years, significant progress has been made towards advancing liquid biopsies for non-invasive early cancer detection, prognosis, treatment adaptation, monitoring of residual disease and surveillance of recurrence. While these emerging technologies have immense potential to improve patient survival, numerous methodological and biological limitations must be overcome before their implementation into clinical practice. This review outlines the current state of knowledge on various types of liquid biopsies in HNSCC, and their potential applications for diagnosis, prognosis, grading treatment response and post-treatment surveillance. It also discusses challenges associated with the clinical applicability of liquid biopsies and prospects of the optimised approaches in the management of HNSCC.

Identification of Possible Salivary Metabolic Biomarkers and Altered Metabolic Pathways in South American Patients Diagnosed with Oral Squamous Cell Carcinoma

Oral squamous cell carcinoma (OSCC) represents 90% of oral malignant neoplasms. The search for specific biomarkers for OSCC is a very active field of research contributing to establishing early diagnostic methods and unraveling underlying pathogenic mechanisms. In this work we investigated the salivary metabolites and the metabolic pathways of OSCC aiming find possible biomarkers. Salivary metabolites samples from 27 OSCC patients and 41 control individuals were compared through a gas chromatography coupled to a mass spectrometer (GC-MS) technique. Our results allowed identification of pathways of the malate-aspartate shuttle, the beta-alanine metabolism, and the Warburg effect. The possible salivary biomarkers were identified using the area under receiver-operating curve (AUC) criterion. Twenty-four metabolites were identified with AUC > 0.8. Using the threshold of AUC = 0.9 we find malic acid, maltose, protocatechuic acid, lactose, 2-ketoadipic, and catechol metabolites expressed. We notice that this is the first report of salivary metabolome in South American oral cancer patients, to the best of our knowledge. Our findings regarding these metabolic changes are important in discovering salivary biomarkers of OSCC patients. However, additional work needs to be performed considering larger populations to validate our results.

Chromatographic methods coupled to mass spectrometry for the determination of oncometabolites in biological samples-A review

It is now well-established that dysregulation of the tricarboxylic acid (TCA) cycle enzymes succinate dehydrogenase, fumarate hydratase, and isocitrate dehydrogenase leads to the abnormal cellular accumulation of succinate, fumarate, and 2-hydroxyglutarate, respectively, which contribute to the formation and malignant progression of numerous types of cancers. Thus, these metabolites, called oncometabolites, could potentially be useful as tumour-specific biomarkers and as therapeutic targets. For this reason, the development of analytical methodologies for the accurate identification and determination of their levels in biological matrices is an important task in the field of cancer research. Currently, hyphenated gas chromatography-mass spectrometry (GC-MS) and liquid chromatography-mass spectrometry (LC-MS) techniques are the most powerful analytical tools in what concerns high sensitivity and selectivity to achieve such difficult task. In this review, we first provide a brief description of the biological formation of oncometabolites and their oncogenic properties, and then we present an overview and critical assessment of the GC-MS and LC-MS based analytical approaches that are reported in the literature for the determination of oncometabolites in biological samples, such as biofluids, cells, and tissues. Advantages and drawbacks of these approaches will be comparatively discussed. We believe that the present review represents the first attempt to summarize the applications of these hyphenated techniques in the context of oncometabolite analysis, which may be useful to new and existing researchers in this field.

Metabolomics of Oral/Head and Neck Cancer

Oral/head and neck cancer is the sixth most common human malignancies in the world. Despite the treatment advances in surgery, chemotherapy, and radiotherapy, the patient survival has not been significantly improved in the past several decades. As a new methodological approach, metabolomics may help reveal the metabolic reprogramming mechanisms underlying head and neck cancer cell proliferation, invasion, and metastasis and may be used to identify metabolite biomarkers for clinical applications of the disease. In this chapter, we briefly review recent metabolomic applications in head and neck cancer.

Targeted Metabolomics Identifies Plasma Biomarkers in Mice with Metabolically Heterogeneous Melanoma Xenografts

Melanomas are genetically and metabolically heterogeneous, which influences therapeutic efficacy and contributes to the development of treatment resistance in patients with metastatic disease. Metabolite phenotyping helps to better understand complex metabolic diseases, such as melanoma, and facilitates the development of novel therapies. Our aim was to characterize the tumor and plasma metabolomes of mice bearing genetically different melanoma xenografts. We engrafted the human melanoma cell lines A375 (BRAF mutant), WM47 (BRAF mutant), WM3000 (NRAS mutant), and WM3311 (BRAF, NRAS, NF1 triple-wildtype) and performed a broad-spectrum targeted metabolomics analysis of tumor and plasma samples obtained from melanoma-bearing mice as well as plasma samples from healthy control mice. Differences in ceramide and phosphatidylcholine species were observed between melanoma subtypes irrespective of the genetic driver mutation. Furthermore, beta-alanine metabolism differed between melanoma subtypes and was significantly enriched in plasma from melanoma-bearing mice compared to healthy mice. Moreover, we identified beta-alanine, p-cresol sulfate, sarcosine, tiglylcarnitine, two dihexosylceramides, and one phosphatidylcholine as potential melanoma biomarkers in plasma. The present data reflect the metabolic heterogeneity of melanomas but also suggest a diagnostic biomarker signature for melanoma screening.

Oncometabolite L-2-hydroxyglurate directly induces vasculogenic mimicry through PHLDB2 in renal cell carcinoma

Metabolism reprograming is a hallmark of cancer and plays an important role in tumor progression. The aberrant metabolism in renal cell carcinoma (RCC) leads to accumulation of the oncometabolite l‐2‐hydroxyglurate (L‐2HG). L‐2HG has been reported to inhibit the activity of some α‐ketoglutarate‐dependent dioxygenases such as TET enzymes, which mediate epigenetic alteration, including DNA and histone demethylation. However, the detailed functions of L‐2HG in renal cell carcinoma have not been investigated thoroughly. In our study, we found that L‐2HG was significantly elevated in tumor tissues compared to adjacent tissues. Furthermore, we demonstrated that L‐2HG promoted vasculogenic mimicry (VM) in renal cancer cell lines through reducing the expression of PHLDB2. A mechanism study revealed that activation of the ERK1/2 pathway was involved in L‐2HG‐induced VM formation. In conclusion, these findings highlighted the pathogenic link between L‐2HG and VM and suggested a novel therapeutic target for RCC.

What's new?

Metabolic reprograming, a hallmark of cancer, influences tumor progression. In the case of renal cell carcinoma (RCC) specifically, progression appears to be facilitated by the oncometabolite L‐2‐hydroxyglurate (L‐2HG), though underlying mechanisms remain enigmatic. Here, the authors investigated the ability of L‐2HG in RCC to promote vasculogenic mimicry (VM), in which aggressive cancer cells form vessel‐like networks that support tumor growth. Analyses of RCC patient tissues revealed elevated L‐2HG levels, wherein tumor cells with greater L‐2HG levels exhibited more VM structures. TCGA data and high‐throughput sequencing analyses further show that L‐2HG contributes to VM formation via reduction of PHLDB2 levels.

Hypoxic Transformation of Immune Cell Metabolism Within the Microenvironment of Oral Cancers

Oral squamous cell carcinoma (OSCC) includes tumors of the lips, tongue, gingivobuccal complex, and floor of the mouth. Prognosis for OSCC is highly heterogeneous, with overall 5-year survival of ~50%, but median survival of just 8-10 months for patients with locoregional recurrence or metastatic disease. A key feature of OSCC is microenvironmental oxygen depletion due to rapid growth of constituent tumor cells, which triggers hypoxia-associated signaling events and metabolic adaptations that influence subsequent tumor progression. Better understanding of leukocyte responses to tissue hypoxia and onco-metabolite expression under low-oxygen conditions will therefore be essential to develop more effective methods of diagnosing and treating patients with OSCC. This review assesses recent literature on metabolic reprogramming, redox homeostasis, and associated signaling pathways that mediate crosstalk of OSCC with immune cells in the hypoxic tumor microenvironment. The likely functional consequences of this metabolic interface between oxygen-starved OSCC and infiltrating leukocytes are also discussed. The hypoxic microenvironment of OSCC modifies redox signaling and alters the metabolic profile of tumor-infiltrating immune cells. Improved understanding of heterotypic interactions between host leukocytes, tumor cells, and hypoxia-induced onco-metabolites will inform the development of novel theranostic strategies for OSCC.

Prognostic Role of Serum Amino Acids in Head and Neck Cancer

Introduction

Serum amino acid (AA) profiles represent a valuable tool in the metabolic assessment of cancer patients; still, information on the AA pattern in head and neck cancer (HNC) patients is insufficient. The aim of the study was to assess whether serum AA levels were associated with the stage of neoplastic disease and prognosis in primary HNC patients.

Methods

Two hundred and two primary HNC patients were included in the study. Thirty-one AAs and derivatives were measured in serum through an ultraperformance liquid chromatography-mass spectrometry (UPLC-MS). The association between AA concentrations and the stage (advanced versus early) of HNC was estimated using a multivariable logistic regression model. A multivariable Cox regression model was used to evaluate the prognostic significance of each AA.

Results

At the multivariable logistic regression analysis, increased levels of alpha-aminobutyric acid, aminoadipic acid, histidine, proline, and tryptophan were associated with a reduced risk of advanced stage HNC, while high levels of beta-alanine, beta-aminobutyric acid, ethanolamine, glycine, isoleucine, 4-hydroxyproline, and phenylalanine were associated with an increased risk of advanced stage HNC. Furthermore, at multivariate analysis, increased levels of alpha-aminobutyric acid were associated with increased overall survival (OS), while high levels of arginine, ethanolamine, glycine, histidine, isoleucine, 4-hydroxyproline, leucine, lysine, 3-methylhistidine, phenylalanine, and serine were associated with decreased OS.

Conclusions

Our study suggests that AA levels are associated with the stage of disease and prognosis in patients with HNC. More study is necessary to evaluate if serum AA levels may be considered a hallmark of HNC and prove to be clinically useful markers of disease status and prognosis in HNC patients.

Oncometabolites in renal cancer

The study of cancer metabolism has evolved vastly beyond the remit of tumour proliferation and survival with the identification of the role of 'oncometabolites' in tumorigenesis. Simply defined, oncometabolites are conventional metabolites that, when aberrantly accumulated, have pro-oncogenic functions. Their discovery has led researchers to revisit the Warburg hypothesis, first postulated in the 1950s, of aberrant metabolism as an aetiological determinant of cancer. As such, the identification of oncometabolites and their utilization in diagnostics and prognostics, as novel therapeutic targets and as biomarkers of disease, are areas of considerable interest in oncology. To date, fumarate, succinate, L-2-hydroxyglutarate (L-2-HG) and D-2-hydroxyglutarate (D-2-HG) have been characterized as bona fide oncometabolites. Extensive metabolic reprogramming occurs during tumour initiation and progression in renal cell carcinoma (RCC) and three oncometabolites - fumarate, succinate and L-2-HG - have been implicated in this disease process. All of these oncometabolites inhibit a superfamily of enzymes known as α-ketoglutarate-dependent dioxygenases, leading to epigenetic dysregulation and induction of pseudohypoxic phenotypes, and also have specific pro-oncogenic capabilities. Oncometabolites could potentially be exploited for the development of novel targeted therapies and as biomarkers of disease.

Metabolic Biomarkers of Squamous Cell Carcinoma of the Aerodigestive Tract: A Systematic Review and Quality Assessment

Introduction. Aerodigestive squamous cell carcinomas (ASCC) constitute a major source of global cancer deaths. Patients typically present with advanced, incurable disease, so new means of detecting early disease are a research priority. Metabolite quantitation is amenable to point-of-care analysis and can be performed in ASCC surrogates such as breath and saliva. The purpose of this systematic review is to summarise progress of ASCC metabolomic studies, with an emphasis on the critical appraisal of methodological quality and reporting.

METHOD

A systematic online literature search was performed to identify studies reporting metabolic biomarkers of ASCC. This review was conducted in accordance with the recommendations of the Cochrane Library and MOOSE guidelines.

RESULTS

Thirty studies comprising 2117 patients were included in the review. All publications represented phase-I biomarker discovery studies, and none validated their findings in an independent cohort. There was heterogeneity in study design and methodological and reporting quality. Sensitivities and specificities were higher in oesophageal and head and neck squamous cell carcinomas compared to those in lung squamous cell carcinoma. The metabolic phenotypes of these cancers were similar, as was the kinetics of metabolite groups when comparing blood, tissue, and breath/saliva concentrations. Deregulation of amino acid metabolism was the most frequently reported theme.

CONCLUSION

Metabolite analysis has shown promising diagnostic performance, especially for oesophageal and head and neck ASCC subtypes, which are phenotypically similar. However, shortcomings in study design have led to inconsistencies between studies. To support future studies and ultimately clinical adoption, these limitations are discussed.

Salivary Metabolomics: From Diagnostic Biomarker Discovery to Investigating Biological Function

Metabolomic profiling of biofluids, e.g., urine, plasma, has generated vast and ever-increasing amounts of knowledge over the last few decades. Paradoxically, metabolomic analysis of saliva, the most readily-available human biofluid, has lagged. This review explores the history of saliva-based metabolomics and summarizes current knowledge of salivary metabolomics. Current applications of salivary metabolomics have largely focused on diagnostic biomarker discovery and the diagnostic value of the current literature base is explored. There is also a small, albeit promising, literature base concerning the use of salivary metabolomics in monitoring athletic performance. Functional roles of salivary metabolites remain largely unexplored. Areas of emerging knowledge include the role of oral host-microbiome interactions in shaping the salivary metabolite profile and the potential roles of salivary metabolites in oral physiology, e.g., in taste perception. Discussion of future research directions describes the need to begin acquiring a greater knowledge of the function of salivary metabolites, a current research direction in the field of the gut metabolome. The role of saliva as an easily obtainable, information-rich fluid that could complement other gastrointestinal fluids in the exploration of the gut metabolome is emphasized.

The Microbiome of Temporal Arteries

Objective

A role for microorganisms in giant cell arteritis (GCA) has long been suspected. We describe the microbiomes of temporal arteries from patients with GCA and controls.

Methods

Temporal artery biopsies from patients suspected to have GCA were collected under aseptic conditions and snap-frozen. Fluorescence in situ hybridization (FISH) and long-read 16S rRNA-gene sequencing was used to examine microbiomes of temporal arteries. Taxonomic classification of bacterial sequences was performed to the genus level and relative abundances were calculated. Microbiome differential abundances were analyzed by principal coordinate analysis (PCoA) with comparative Unifrac distances and predicted functional profiling using PICRUSt.

Results

Forty-seven patients, including 9 with biopsy-positive GCA, 15 with biopsy-negative GCA and 23 controls without GCA, were enrolled. FISH for bacterial DNA revealed signal in the arterial media. Beta, but not alpha, diversity differed between GCA and control temporal arteries (P = 0.042). Importantly, there were no significant differences between biopsy-positive and biopsy-negative GCA (P > 0.99). The largest differential abundances seen between GCA and non-GCA temporal arteries included Proteobacteria (P), Bifidobacterium (g), Parasutterella (g), and Granulicatella (g) [Log 2-fold change ≥ 4].

Conclusion

Temporal arteries are not sterile, but rather are inhabited by a community of bacteria. We have demonstrated that there are microbiomic differences between GCA and non-GCA temporal arteries, but not between biopsy-positive and biopsy-negative GCA.

Metabolomics study of oral cancers

BACKGROUND

Oral cancer is one of the most frequently occurring cancers. Metabolic reprogramming is an important hallmark of cancer. Metabolomics characterizes all the small molecules in a biological sample, and a complete set of small molecules in such sample is referred as metabolome. Nuclear magnetic resonance spectroscopy and mass spectrometry are two widely used techniques in metabolomics studies. Increasing evidence demonstrates that metabolomics techniques can be used to explore the metabolic signatures in oral cancer. Elucidation of metabolic alterations in oral cancer is also important for the understanding of its pathological mechanisms.

AIM OF REVIEW

In this paper, we summarize the latest progress of metabolomics study in oral cancer and provide the suggestions for the future studies.

KEY SCIENTIFIC CONCEPTS OF REVIEW

The metabolomics studies in saliva, serum, and tumor tissues revealed the existence of metabolic signatures in bio-fluids and tissues of oral cancer, and several tumor-specific metabolites identified in individual study could discriminate oral cancer from healthy controls or precancerous lesions, which are potential biomarkers for the screening or early diagnosis of oral cancer. Metabolomics study of oral cancers in the future should aim to establish a routine procedure with high sensitivity, profile intracellular metabolites to find out the metabolic characteristics of tumor cells, and investigate the mechanism behind metabolomic alterations and the metabolic response of cancer cells to chemotherapy.

Genome-Scale Modeling of NADPH-Driven β-Lapachone Sensitization in Head and Neck Squamous Cell Carcinoma

AIMS

The purpose of this study was to investigate differential nicotinamide adenine dinucleotide phosphate, reduced (NADPH) production between radiation-sensitive and -resistant head and neck squamous cell carcinoma (HNSCC) cell lines and whether these differences are predictive of sensitivity to the chemotherapeutic β-lapachone.

RESULTS

We have developed a novel human genome-scale metabolic modeling platform that combines transcriptomic, kinetic, thermodynamic, and metabolite concentration data. Upon incorporation of this information into cell line-specific models, we observed that the radiation-resistant HNSCC model redistributed flux through several major NADPH-producing reactions. Upon RNA interference of canonical NADPH-producing genes, the metabolic network can further reroute flux through alternate NADPH biosynthesis pathways in a cell line-specific manner. Model predictions of perturbations in cellular NADPH production after gene knockdown match well with experimentally verified effects of β-lapachone treatment on NADPH/NADP⁺ ratio and cell viability. This computational approach accurately predicts HNSCC-specific oxidoreductase genes that differentially affect cell viability between radiation-responsive and radiation-resistant cancer cells upon β-lapachone treatment.

INNOVATION

Quantitative genome-scale metabolic models that incorporate multiple levels of biological data are applied to provide accurate predictions of responses to a NADPH-dependent redox cycling chemotherapeutic drug under a variety of perturbations.

CONCLUSION

Our modeling approach suggests differences in metabolism and β-lapachone redox cycling that underlie phenotypic differences in radiation-sensitive and -resistant cancer cells. This approach can be extended to investigate the synergistic action of NAD(P)H: quinone oxidoreductase 1 bioactivatable drugs and radiation therapy. Antioxid. Redox Signal. 29, 937-952.

"Omics" in oral cancer: New approaches for biomarker discovery

OBJECTIVES

In this review paper, we explored the application of "omics" approaches in the study of oral cancer (OC). It will provide a better understanding of how "omics" approaches may lead to novel biomarker molecules or molecular signatures with potential value in clinical practice. A future direction of "omics"-driven research in OC is also discussed.

METHODS

Studies on "omics"-based approaches [genomics/proteomics/transcriptomics/metabolomics] were investigated for differentiating oral squamous cell carcinoma,oral sub-mucous fibrosis, oral leukoplakia, oral lichen planus, oral erythroplakia from normal cases. Electronic databases viz., PubMed, Springer, and Google Scholar were searched.

RESULTS

One eighty-one studies were included in this review. The review shows that the fields of genomics, transcriptomics, proteomics, and metabolomics-based marker identification have implemented advanced tools to screen early changes in DNA, RNA, protein, and metabolite expression in OC population.

CONCLUSIONS

It may be concluded that despite advances in OC therapy, symptomatic presentation occurs at an advanced stage, where various curative treatment options become very limited. A molecular level study is essential for detecting an OC biomarker at an early stage. Modern "Omics" strategies can potentially make a major contribution to meet this need.

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.

GC-MS based metabolomics used for the identification of cancer volatile organic compounds as biomarkers

A biomarker can be a metabolite, coming from a metabolic pathway or cell process, which might be employed in the diagnostic of diseases, predict patient response towards chemical therapies and/or monitor disease recurrences. Biomarkers, e.g. aldehydes or hydrocarbons, are often identified from different body fluids such as blood, urine, serum, saliva or from various tissues samples, and their concentration can vary from one sample to the other. However, the detection and the action of these biomarkers for diseases is a complicated process. Cancer is one of the main cause of death worldwide. The main characteristic of cancerous tumor is the uncontrolled growing of cells inside the organism. Likely, these uncontrolled growths are as consequence changes in the metabolism that could be analytically monitored. Depending on where the cancer cells are located, they provide different characteristics profiles. These profiles as fingerprints are used for differentiation in a comparison to normal cells. This critical study aimed at highlighting the latest progress in this area, especially in the employment of gas chromatography for the monitoring of volatile organic compounds (VOCs) and the identification of possible molecules used as biomarkers for cancer therapy.