Mass spectrometry-based lipidomics of oral squamous cell carcinoma tissue reveals aberrant cholesterol and glycerophospholipid metabolism - A Pilot study

Immunotherapeutic strategies in head and neck cancer: challenges and opportunities

HNSCC remains a substantial health issue, with treatment options including surgery, radiation, and platinum-based chemotherapy. Unfortunately, despite progress in research, only modest gains have been made in disease control, with existing treatments resulting in significant functional and quality-of-life issues. The introduction of immunotherapy in the treatment of HNSCC has resulted in some improvements in outlook for patients and is now standard of care for populations with both recurrent and metastatic disease. However, despite the early successes, responses to immune checkpoint inhibition (ICI) remain modest to low, approaching 14%-22% objective response rates. Challenges to the effectiveness of ICI and other immunotherapies are complex, including the diverse and dynamic molecular plasticity and heterogeneity of HNSCCs; lack of immunogenic antigens; accumulated suppressive immune populations such as myeloid cells and dysfunctional T cells; nutrient depletion; and metabolic dysregulation in the HNSCC tumor microenvironment. In this Review, we explore the mechanisms responsible for immunotherapy resistance, dissect these challenges, and discuss potential opportunities for overcoming hurdles to the development of successful immunotherapy for HNSCC.

Malignant Transformed and Non-Transformed Oral Leukoplakias Are Metabolically Different

Understanding the early molecular events driving oral carcinogenesis is vital for diagnosing oral squamous cell carcinoma (OSCC) promptly. While metabolic differences between oral leukoplakia (OLK), OSCC, and healthy oral mucosa have been reported, the metabolic changes distinguishing malignant transformed OLKs (MT-OLK) from non-transformed OLKs (NT-OLK) remain unexplored. Here, we examine the metabolomic profiles of 5 cases of MT-OLK and 15 of NT-OLK to identify key predictive molecules using untargeted high-performance liquid chromatography-mass spectrometry. The potentially discriminant compounds were highlighted through a robust statistical analysis workflow, and the dysregulated metabolic pathways were illustrated by enrichment analysis. Seventeen molecular features, primarily lipids-including phospholipids, oxidised lipids, cholesteryl esters, and fatty acids-were identified as discriminants between MT-OLK and NT-OLK across statistical and bioinformatic approaches. Pathway enrichment analysis revealed alterations in lipid metabolism, particularly fatty acid synthesis and degradation, steroid hormone biosynthesis, and glycerophospholipid metabolism. Predictive models showed high accuracy (AUC = 0.88) in distinguishing the two groups. This study suggests that metabolomics has the potential to differentiate between MT-OLK and NT-OLK by identifying candidate biomarkers that may contribute to the understanding of malignant transformation. Validation in larger cohorts is warranted to translate these findings into clinical practice.

Enhanced nano-LC-MS for analyzing dansylated oral cancer tissue metabolome dissolved in solvents with high elution strength

BACKGROUND

Tissue metabolomics analysis, alongside genomics and proteomics, offers crucial insights into the regulatory mechanisms of tumorigenesis. To enhance metabolite detection sensitivity, chemical isotope labeling (CIL) techniques, such as dansylation, have been developed to improve metabolite separation and ionization in mass spectrometry (MS). However, the dissolution of hydrophobic derivatized metabolites in solvents with high acetonitrile content limits the use of liquid chromatography (LC) systems with small-volume reversed-phase (RP) columns. In this study, we established a nano-LC-MS system with an online dilution design to address this issue, enabling sensitive analysis of oral cancer tissue metabolomes.

RESULTS

Our nano-LC system features a flow path design with online sample dilution before an RP trap column and backflushing of the trap column before entering the analytical column. Compared to other nano-LC systems, both with and without online dilution designs, our system demonstrates the superiority of the T-connector-based dilution method. Using only 1/20th of the sample required for popular micro-LC systems, our nano-LC detects a larger number of peak pairs with similar recovery rates for both hydrophilic and hydrophobic metabolites, ensuring unbiased results. Thirty-two matched pairs of oral squamous cell carcinoma (OSCC) tissue samples and adjacent noncancerous tissues (ANTs) underwent high-throughput CIL-metabolome analysis using our nano-LC system. Compared to our previous micro-LC methods, the nano-LC-MS system exhibits enhanced detection sensitivity, significantly reducing sample requirements.

SIGNIFICANCE

Our findings highlight the efficacy of our platform for metabolomic analysis with limited sample amounts. The nano-LC system's ability to analyze samples dissolved in strong eluents suggests potential applications for handling other hydrophobic compounds using RPLC or other separation methods facing similar solvent incompatibility issues. This approach holds promise for identifying novel metabolite biomarkers for oral cancers, advancing our understanding of tumorigenesis, and enhancing clinical applications.

Identification of novel serum lipid metabolism potential markers and metabolic pathways for oral cancer: a population-based study

OBJECTIVE

This study aims to identify potential lipid biomarkers and metabolic pathways associated with oral cancer (OC). Then to establish and evaluate disease classification models capable of distinguishing OC patients from healthy controls.

METHODS

A total of 41 OC patients and 41 controls were recruited from a hospital in Southeast China to examine the serum lipidomics by Ultra-high Performance Liquid Chromatography Q Exactive Mass Spectrometry (UHPLC-QE-MS).

RESULTS

The total serum lipid profile showed that triglycerides accounted for the highest proportion of total metabolites, reaching 35.90% of the total. A total of 74 different metabolites were screened (12 up-regulated and 62 down-regulated), mainly enriched in the glycerophospholipid metabolism pathway. The three most significant changes in lipid metabolites were phosphatidylcholine (PC(18:3e/17:2)), acylcarnitine (ACar(14:2)), and glucuronosyldiacylglycerol (GlcADG(14:1/14:1)). The disease classification model, constructed using a KNN algorithm with 13 metabolites selected through LASSO screening, achieved the best performance, with an AUC of 0.978 (0.955-1.000).

CONCLUSION

Lipid metabolic biomarkers identified in this study exhibit potential as candidate biomarkers for OC diagnosis. Further validation through prospective studies is required to confirm their clinical utility in early detection.

Unraveling the genetic and epigenetic landscape governing intramuscular fat deposition in rabbits: Insights and implications

Intramuscular fat (IMF) content is a predominant factor recognized to affect rabbit meat quality, directly impacting flavor, juiciness, and consumer preference. Despite its significance, the major interplay of genetic and epigenetic factors regulating IMF in rabbits remains largely unexplored. This review sheds light on this critical knowledge gap, offering valuable insights and future directions. We delve into the potential role of established candidate genes from other livestock (e.g. PPARγ, FABP4, and SCD) in rabbits, while exploring the identified novel genes of IMF in rabbits. Furthermore, we explored the quantitative trait loci studies in rabbit IMF and genomic selection approaches for improving IMF content in rabbits. Beyond genetics, this review unveils the exciting realm of epigenetic mechanisms modulating IMF deposition. We explored the potential of DNA methylation patterns, histone modifications, and non-coding RNA-mediation as fingerprints for selecting rabbits with desirable IMF levels. Additionally, we explored the possibility of manipulating the epigenetic landscape through nutraceuticals interventions to promote favorable IMF depositions. By comprehensively deciphering the genomic and epigenetic terrain of rabbit intramuscular fat regulation, this study aims to assess the existing knowledge regarding the genetic and epigenetic factors that control the deposition of intramuscular fat in rabbits. By doing so, we identified gaps in the current research, and suggested potential areas for further investigation that would enhance the quality of rabbit meat. This can enable breeders to develop targeted breeding strategies, optimize nutrition, and create innovative interventions to enhance the quality of rabbit meat, meet consumer demands and increase market competitiveness.

Integrating omics data and machine learning techniques for precision detection of oral squamous cell carcinoma: evaluating single biomarkers

Introduction

Early detection of oral squamous cell carcinoma (OSCC) is critical for improving clinical outcomes. Precision diagnostics integrating metabolomics and machine learning offer promising non-invasive solutions for identifying tumor-derived biomarkers.

Methods

We analyzed a multicenter public dataset comprising 61 OSCC patients and 61 healthy controls. Plasma metabolomics data were processed to extract 29 numerical and 47 ratio features. The Extra Trees (ET) algorithm was applied for feature selection, and the TabPFN model was used for classification and prediction.

Results

The model achieved an area under the curve (AUC) of 93% and an overall accuracy of 76.6% when using top-ranked individual biomarkers. Key metabolic features significantly differentiated OSCC patients from healthy controls, providing a detailed metabolic fingerprint of the disease.

Discussion

Our findings demonstrate the utility of integrating omics data with advanced machine learning techniques to develop accurate, non-invasive diagnostic tools for OSCC. The study highlights actionable metabolic signatures that have potential applications in personalized therapeutics and early intervention strategies.

Connecting the dots: investigating the link between environmental, genetic, and epigenetic influences in metabolomic alterations in oral squamous cell carcinoma

Oral squamous cell carcinoma (OSCC) accounts for around 90% of all oral cancers and is the eighth most common cancer worldwide. Despite progress in managing OSCC, the overall prognosis remains poor, with a survival rate of around 50-60%, largely due to tumor size and recurrence. The challenges of late-stage diagnosis and limitations in current methods emphasize the urgent need for less invasive techniques to enable early detection and treatment, crucial for improving outcomes in this aggressive form of oral cancer. Research is currently aimed at unraveling tumor-specific metabolite profiles to identify candidate biomarkers as well as discover underlying pathways involved in the onset and progression of cancer that could be used as new targets for diagnostic and therapeutic purposes. Metabolomics is an advanced technological approach to identify metabolites in different sample types (biological fluids and tissues). Since OSCC promotes metabolic reprogramming influenced by a combination of genetic predisposition and environmental factors, including tobacco and alcohol consumption, and viral infections, the identification of distinct metabolites through screening may aid in the diagnosis of this condition. Moreover, studies have shown the use of metabolites during the catalysis of epigenetic modification, indicating a link between epigenetics and metabolism. In this review, we will focus on the link between environmental, genetic, and epigenetic influences in metabolomic alterations in OSCC. In addition, we will discuss therapeutic targets of tumor metabolism, which may prevent oral tumor growth, metastasis, and drug resistance.

Integrating lipid metabolite analysis with MRI-based transformer and radiomics for early and late stage prediction of oral squamous cell carcinoma

BACKGROUND

Oral Squamous Cell Carcinoma (OSCC) presents significant diagnostic challenges in its early and late stages. This study aims to utilize preoperative MRI and biochemical indicators of OSCC patients to predict the stage of tumors.

METHODS

This study involved 198 patients from two medical centers. A detailed analysis of contrast-enhanced T1-weighted (ceT1W) and T2-weighted (T2W) MRI were conducted, integrating these with biochemical indicators for a comprehensive evaluation. Initially, 42 clinical biochemical indicators were selected for consideration. Through univariate analysis and multivariate analysis, only those indicators with p-values less than 0.05 were retained for model development. To extract imaging features, machine learning algorithms in conjunction with Vision Transformer (ViT) techniques were utilized. These features were integrated with biochemical indicators for predictive modeling. The performance of model was evaluated using the Receiver Operating Characteristic (ROC) curve.

RESULTS

After rigorously screening biochemical indicators, four key markers were selected for the model: cholesterol, triglyceride, very low-density lipoprotein cholesterol and chloride. The model, developed using radiomics and deep learning for feature extraction from ceT1W and T2W images, showed a lower Area Under the Curve (AUC) of 0.85 in the validation cohort when using these imaging modalities alone. However, integrating these biochemical indicators improved the model's performance, increasing the validation cohort AUC to 0.87.

CONCLUSION

In this study, the performance of the model significantly improved following multimodal fusion, outperforming the single-modality approach.

CLINICAL RELEVANCE STATEMENT

This integration of radiomics, ViT models, and lipid metabolite analysis, presents a promising non-invasive technique for predicting the staging of OSCC.

Salivary Metabolites Produced by Oral Microbes in Oral Diseases and Oral Squamous Cell Carcinoma: A Review

In recent years, salivary metabolome studies have provided new biological information and salivary biomarkers to diagnose different diseases at early stages. The saliva in the oral cavity is influenced by many factors that are reflected in the salivary metabolite profile. Oral microbes can alter the salivary metabolite profile and may express oral inflammation or oral diseases. The released microbial metabolites in the saliva represent the altered biochemical pathways in the oral cavity. This review highlights the oral microbial profile and microbial metabolites released in saliva and its use as a diagnostic biofluid for different oral diseases. The importance of salivary metabolites produced by oral microbes as risk factors for oral diseases and their possible relationship in oral carcinogenesis is discussed.

Correlation analysis of plasma lipid profiles and the prognosis of head and neck squamous cell carcinoma

PURPOSE

This study aims to clarify whether blood lipid profiles are indicators of prognosis in patients with head and neck squamous cell carcinoma (HNSCC).

METHODS

This retrospective study included 512 T1/2N0M0 HNSCC patients. The correlation between blood lipid profiles and progression-free survival (PFS) and disease-specific survival (DSS) was analyzed by multivariate analysis. The data from TCGA was also analyzed to investigate the expression levels and prognostic values of different lipoprotein receptors essential for specific lipid uptake.

RESULTS

A high level of low-density lipoprotein cholesterol (LDL-C) indicated better PFS and DSS, and a low level of apolipoprotein A-I (Apo A-I) indicated better PFS, while a high level of apolipoprotein B (Apo B) indicated poorer PFS and DSS. The Apo A-I receptor gene SCARB1 was upregulated and associated with poor survival in HNSCC patients. Activation of SCARB1 was implicated in a series of tumor-promoting pathways. There was no significant correlation between the expression of LDL-C and Apo B-related receptors and prognosis.

CONCLUSION

A high level of LDL-C and a low level of Apo A-I are protective factors for HNSCC, while a high level of Apo B is a risk factor. The upregulation of SCARB1 may participate in the progression of HNSCC.

Advanced progress of spatial metabolomics in head and neck cancer research

Head and neck cancer ranks as the sixth most prevalent malignancy, constituting 5 % of all cancer cases. Its inconspicuous onset often leads to advanced stage diagnoses, prompting the need for early detection to enhance patient prognosis. Currently, research into early diagnostic markers relies predominantly on genomics, proteomics, transcriptomics, and other methods, which, unfortunately, necessitate tumor tissue homogenization, resulting in the loss of temporal and spatial information. Emerging as a recent addition to the omics toolkit, spatial metabolomics stands out. This method conducts in situ mass spectrometry analyses on fresh tissue specimens while effectively preserving their spatiotemporal information. The utilization of spatial metabolomics in life science research offers distinct advantages. This article comprehensively reviews the progress of spatial metabolomics in head and neck cancer research, encompassing insights into cancer cell metabolic reprogramming. Various mass spectrometry imaging techniques, such as secondary ion mass spectrometry, stroma-assisted laser desorption/ionization, and desorption electrospray ionization, enable in situ metabolite analysis for head and neck cancer. Finally, significant emphasis is placed on the application of presently available techniques for early diagnosis, margin assessment, and prognosis of head and neck cancer.

Integrated proteomic and metabolomic analysis of plasma reveals regulatory pathways and key elements in thyroid cancer

Thyroid cancer (TC) is the most common endocrine malignancy with increasing incidence in recent years. Fine-needle aspiration biopsy (FNAB), as a gold standard for the initial evaluation of thyroid nodules, fails to cover all the cytopathologic conditions resulting in overdiagnosis. There is an urgent need for a better classification of thyroid cancer from benign thyroid nodules (BTNs). Here, data independent acquisition (DIA)-based proteomics and untargeted metabolomics in plasma samples of 10 patients with TC and 15 patients with BTNs were performed. Key proteins and metabolites were identified specific to TC, and an independent cohort was used to validate the potential biomarkers using enzyme-linked immunosorbent assay (ELISA). In total, 1429 proteins and 1172 metabolites were identified. Principal component analysis showed a strong overlap at the proteomic level and a significant discrimination at the metabolomic level between the two groups, indicating a more drastic disturbance in the metabolome of thyroid cancer. Integrated analysis of proteomics and metabolomics shows glycerophospholipid metabolism and arachidonic acid metabolism as key regulatory pathways. Furthermore, a multi-omics biomarker panel was developed consisting of LCAT, GPX3 and leukotriene B4. Based on the AUC value for the discovery set, the classification performance was 0.960. The AUC value of the external validation set was 0.930. Altogether, our results will contribute to the clinical application of potential biomarkers in the diagnosis of thyroid cancer.

Lipid metabolism reprogramming in head and neck cancer

Lipid metabolism reprogramming is one of the most prominent metabolic anomalies in cancer, wherein cancer cells undergo dysregulation of lipid metabolism to acquire adequate energy, cell membrane building blocks, as well as signaling molecules essential for cell proliferation, survival, invasion, and metastasis. These adaptations enable cancer cells to effectively respond to challenges posed by the tumor microenvironment, leading to cancer therapy resistance and poor cancer prognosis. Head and neck cancer, ranking as the seventh most prevalent cancer, exhibits numerous abnormalities in lipid metabolism. Nevertheless, the precise role of lipid metabolic rewiring in head and neck cancer remains unclear. In line with the LIPID MAPS Lipid Classification System and cancer risk factors, the present review delves into the dysregulated molecules and pathways participating in the process of lipid uptake, biosynthesis, transportation, and catabolism. We also present an overview of the latest advancements in understanding alterations in lipid metabolism and how they intersect with the carcinogenesis, development, treatment, and prognosis of head and neck cancer. By shedding light on the significance of metabolic therapy, we aspire to improve the overall prognosis and treatment outcomes of head and neck cancer patients.

Targeting Squalene Epoxidase Confers Metabolic Vulnerability and Overcomes Chemoresistance in HNSCC

Cisplatin resistance poses a substantial hurdle in effectively treating head and neck squamous cell carcinoma (HNSCC). Utilizing multiple tumor models and examining an internal HNSCC cohort, squalene epoxidase (SQLE) is pinpointed as a key driver of chemoresistance and tumorigenesis, operating through a cholesterol-dependent pathway. Comprehensive transcriptomic analysis reveals that SQLE is essential for maintaining c-Myc transcriptional activity by stabilizing the c-Myc protein and averting its ubiquitin-mediated degradation. Mechanistic investigation demonstrates that SQLE inhibition diminishes Akt's binding affinity to lipid rafts via a cholesterol-dependent process, subsequently deactivating lipid raft-localized Akt, reducing GSK-3β phosphorylation at S9, and increasing c-Myc phosphorylation at T58, ultimately leading to c-Myc destabilization. Importantly, employing an Sqle conditional knockout mouse model, SQLE's critical role in HNSCC initiation and progression is established. The preclinical findings demonstrate the potent synergistic effects of combining terbinafine and cisplatin in arresting tumor growth. These discoveries not only provide novel insights into the underlying mechanisms of SQLE-mediated cisplatin resistance and tumorigenesis in HNSCC but also propose a promising therapeutic avenue for HNSCC patients unresponsive to conventional cisplatin-based chemotherapy.

Cholesterol depletion affects caveolin-1 expression, migration and invasion of oral tongue squamous cell carcinoma cell lines

INTRODUCTION

Cholesterol is a key lipid molecule within cell membranes. This is especially true in cavelolas, invaginated membrane nanodomains, which present the protein caveolin-1 (CAV-1). It is important to note that this structure is involved in many cell signalling pathways. Additionally, high cholesterol is seen in different tumor types but little is known in regards to oral tongue squamous cell carcinoma (OTSCC). The aim of this study was to evaluate the influence of cholesterol depletion on primary (SCC-25) and metastatic (HSC-3) OTSCC cell lines.

MATERIALS AND METHODS

Cell membrane fluidity, cell viability, gene and protein expression of CAV-1 and of epithelial-mesenchymal transition (EMT) markers, cell migration in Myogel and invasion-myoma assay were evaluated after cholesterol depletion with methyl-β-cyclodextrin (MβCD - 7.5, 10 or 15 mM) RESULTS: Decreased cell viability and increased membrane fluidity of SCC-25 cells was seen with cholesterol depletion but cell viability was less affected and there was no effect on membrane fluidity in HSC-3. Cholesterol depletion also decreased CAV-1 at 6 h but increased it after 24 h.; both epithelial and mesenchymal EMT genes were upregulated after 6 h, followed by downregulation at 24 h in SCC-25. In HSC-3, CAV-1 was downregulated, and E-cadherin gene (ECAD) was upregulated at 6 h. Only the protein β-catenin in SCC-25 was affected, and cell migration of both cell lines was decreased, affecting SCC-25 more intensely. The invasive capacity within human myoma organotypic model was increased in SCC-25 and decreased in HSC-3.

CONCLUSION

Cholesterol depletion affects CAV-1 and ECAD inversely. This affect also depends on cell type since the invasive capacity was augmented in primary cells while decreased in metastatic cells.

USP28 controls SREBP2 and the mevalonate pathway to drive tumour growth in squamous cancer

SREBP2 is a master regulator of the mevalonate pathway (MVP), a biosynthetic process that drives the synthesis of dolichol, heme A, ubiquinone and cholesterol and also provides substrates for protein prenylation. Here, we identify SREBP2 as a novel substrate for USP28, a deubiquitinating enzyme that is frequently upregulated in squamous cancers. Our results show that silencing of USP28 reduces expression of MVP enzymes and lowers metabolic flux into this pathway. We also show that USP28 binds to mature SREBP2, leading to its deubiquitination and stabilisation. USP28 depletion rendered cancer cells highly sensitive to MVP inhibition by statins, which was rescued by the addition of geranyl-geranyl pyrophosphate. Analysis of human tissue microarrays revealed elevated expression of USP28, SREBP2 and MVP enzymes in lung squamous cell carcinoma (LSCC) compared to lung adenocarcinoma (LADC). Moreover, CRISPR/Cas-mediated deletion of SREBP2 selectively attenuated tumour growth in a KRas/p53/LKB1 mutant mouse model of lung cancer. Finally, we demonstrate that statins synergise with a dual USP28/25 inhibitor to reduce viability of SCC cells. Our findings suggest that combinatorial targeting of MVP and USP28 could be a therapeutic strategy for the treatment of squamous cell carcinomas.

Lipidome Analysis of Oropharyngeal Tumor Tissues Using Nanosecond Infrared Laser (NIRL) Tissue Sampling and Subsequent Mass Spectrometry

Ultrashort pulse infrared lasers can simultaneously sample and homogenize biological tissue using desorption by impulsive vibrational excitation (DIVE). With growing attention on alterations in lipid metabolism in malignant disease, mass spectrometry (MS)-based lipidomic analysis has become an emerging topic in cancer research. In this pilot study, we investigated the feasibility of tissue sampling with a nanosecond infrared laser (NIRL) for the subsequent lipidomic analysis of oropharyngeal tissues, and its potential to discriminate oropharyngeal squamous cell carcinoma (OPSCC) from non-tumorous oropharyngeal tissue. Eleven fresh frozen oropharyngeal tissue samples were ablated. The produced aerosols were collected by a glass fiber filter, and the lipidomes were analyzed with mass spectrometry. Data was evaluated by principal component analysis and Welch's t-tests. Lipid profiles comprised 13 lipid classes and up to 755 lipid species. We found significant inter- and intrapatient alterations in lipid profiles for tumor and non-tumor samples (p-value < 0.05, two-fold difference). Thus, NIRL tissue sampling with consecutive MS lipidomic analysis is a feasible and promising approach for the differentiation of OPSCC and non-tumorous oropharyngeal tissue and may provide new insights into lipid composition alterations in OPSCC.

Cholesterol Is a Regulator of CAV1 Localization and Cell Migration in Oral Squamous Cell Carcinoma

Cholesterol plays an important role in cancer progression, as it is utilized in membrane biogenesis and cell signaling. Cholesterol-lowering drugs have exhibited tumor-suppressive effects in oral squamous cell carcinoma (OSCC), suggesting that cholesterol is also essential in OSCC pathogenesis. However, the direct effects of cholesterol on OSCC cells remain unclear. Here, we investigated the role of cholesterol in OSCC with respect to caveolin-1 (CAV1), a cholesterol-binding protein involved in intracellular cholesterol transport. Cholesterol levels in OSCC cell lines were depleted using methyl-β-cyclodextrin and increased using the methyl-β-cyclodextrin-cholesterol complex. Functional analysis was performed using timelapse imaging, and CAV1 expression in cholesterol-manipulated cells was investigated using immunofluorescence and immunoblotting assays. CAV1 immunohistochemistry was performed on surgical OSCC samples. We observed that cholesterol addition induced polarized cell morphology, along with CAV1 localization at the trailing edge, and promoted cell migration. Moreover, CAV1 was upregulated in the lipid rafts and formed aggregates in the plasma membrane in cholesterol-added cells. High membranous CAV1 expression in tissue specimens was associated with OSCC recurrence. Therefore, cholesterol promotes the migration of OSCC cells by regulating cell polarity and CAV1 localization to the lipid raft. Furthermore, membranous CAV1 expression is a potential prognostic marker for OSCC patients.

Prognosis-related molecular subtyping in head and neck squamous cell carcinoma patients based on glycolytic/cholesterogenic gene data

BACKGROUND

Head and neck squamous cell carcinoma (HNSCC) remains an unmet medical challenge. Metabolic reprogramming is a hallmark of diverse cancers, including HNSCC.

METHODS

We investigated the metabolic profile in HNSCC by using The Cancer Genome Atlas (TCGA) (n = 481) and Gene Expression Omnibus (GEO) (n = 97) databases. The metabolic stratification of HNSCC samples was identified by using unsupervised k-means clustering. We analyzed the correlations of the metabolic subtypes in HNSCC with featured genomic alterations and known HNSCC subtypes. We further validated the metabolism-related subtypes based on features of ENO1, PFKFB3, NSDHL and SQLE expression in HNSCC by Immunohistochemistry. In addition, genomic characteristics of tumor metabolism that varied among different cancer types were confirmed.

RESULTS

Based on the median expression of coexpressed cholesterogenic and glycolytic genes, HNSCC subtypes were identified, including glycolytic, cholesterogenic, quiescent and mixed subtypes. The quiescent subtype was associated with the longest survival and was distributed in stage I and G1 HNSCC. Mutation analysis of HNSCC genes indicated that TP53 has the highest mutation frequency. The CDKN2A mutation frequency has the most significant differences amongst these four subtypes. There is good overlap between our metabolic subtypes and the HNSCC subtype.

CONCLUSION

The four metabolic subtypes were successfully determined in HNSCC. Compared to the quiescent subtype, glycolytic, cholesterogenic and mixed subtypes had significantly worse outcome, which might offer guidelines for developing a novel treatment strategy for HNSCC.

An Investigation of the Prognostic Role of Genes Related to Lipid Metabolism in Head and Neck Squamous Cell Carcinoma

Head and neck squamous cell carcinoma (HNSCC) has become a prevalent malignancy, and its incidence and mortality rate are increasing worldwide. Accumulating evidence has indicated that lipid metabolism-related genes (LMRGs) are involved in the occurrence and development of HNSCC. This study investigated the latent association of lipid metabolism with HNSCC and established a prognostic signature based on LMRGs. A prognostic risk model composed of eight differentially expressed LMRGs (PHYH, CYP4F8, INMT, ELOVL6, PLPP3, BCHE, TPTE, and STAR) was constructed through The Cancer Genome Atlas database. Then, ELOVL6 expression was validated in oral squamous cell carcinoma (OSCC), which is a common type of HNSCC, by immunohistochemical analysis. ELOVL6 expression in the OSCC II/III group was significantly higher than that in the other three groups (normal, dysplasia, and OSCC I), and OSCC patients with high ELOVL6 expression had poorer survival than those with low ELOVL6 expression. In summary, the LMRG-based prognostic feature had prognostic predictive capacity. ELOVL6 may be a potential prognostic factor for HNSCC patients.

Lipid biomarkers that reflect postoperative recurrence risk in lung cancer patients who smoke: a case-control study

BACKGROUND

The risk of postoperative recurrence is higher in lung cancer patients who smoke than non-smokers. However, objective evaluation of the postoperative recurrence risk is difficult using conventional pathological prognostic factors because of their lack of reproducibility. Consequently, novel objective biomarkers that reflect postoperative risk in lung cancer patients who smoke must be identified. Because cigarette smoking and oncogenesis alter lipid metabolism in lung tissue, we hypothesized that the lipid profiles in lung cancer tissues are influenced by cigarette smoking and can reflect the postoperative recurrence risk in smoking lung cancer patients. This study aimed to identify lipid biomarkers that reflect the smoking status and the postoperative recurrence risk.

METHODS

Primary tumor tissues of lung adenocarcinoma (ADC) (n = 26) and squamous cell carcinoma (SQCC) (n = 18) obtained from surgery were assigned to subgroups according to the patient's smoking status. The ADC cohort was divided into never smoker and smoker groups, while the SQCC cohort was divided into moderate smoker and heavy smoker groups. Extracted lipids from the tumor tissues were subjected to liquid chromatography-tandem mass spectrometry analysis. Lipids that were influenced by smoking status and reflected postoperative recurrence and pathological prognostic factors were screened.

RESULTS

Two and 12 lipid peaks in the ADC and SQCC cohorts showed a significant positive correlation with the Brinkman index, respectively. Among them, in the ADC cohort, a higher lipid level consisted of three phosphatidylcholine (PC) isomers, PC (14:0_18:2), PC (16:1_16:1), and PC (16:0_16:2), was associated with a shorter recurrence free period (RFP) and a greater likelihoods of progressed T-factor (≥ pT2) and pleural invasion. In the SQCC cohort, a lower m/z 736.5276 level was associated with shorter RFP and greater likelihood of recurrence.

CONCLUSIONS

From our data, we propose three PC isomers, PC (14:0_18:2), PC (16:1_16:1), and PC (16:0_16:2), and a lipid peak of m/z 736.5276 as novel candidate biomarkers for postoperative recurrence risk in lung ADC and SQCC patients who are smokers.

Metabolic rewiring in MYC-driven medulloblastoma by BET-bromodomain inhibition

Medulloblastoma (MB) is the most common malignant brain tumour in children. High-risk MB patients harbouring MYC amplification or overexpression exhibit a very poor prognosis. Aberrant activation of MYC markedly reprograms cell metabolism to sustain tumorigenesis, yet how metabolism is dysregulated in MYC-driven MB is not well understood. Growing evidence unveiled the potential of BET-bromodomain inhibitors (BETis) as next generation agents for treating MYC-driven MB, but whether and how BETis may affect tumour cell metabolism to exert their anticancer activities remains unknown. In this study, we explore the metabolic features characterising MYC-driven MB and examine how these are altered by BET-bromodomain inhibition. To this end, we employed an NMR-based metabolomics approach applied to the MYC-driven MB D283 and D458 cell lines before and after the treatment with the BETi OTX-015. We found that OTX-015 triggers a metabolic shift in both cell lines resulting in increased levels of myo-inositol, glycerophosphocholine, UDP-N-acetylglucosamine, glycine, serine, pantothenate and phosphocholine. Moreover, we show that OTX-015 alters ascorbate and aldarate metabolism, inositol phosphate metabolism, phosphatidylinositol signalling system, glycerophospholipid metabolism, ether lipid metabolism, aminoacyl-tRNA biosynthesis, and glycine, serine and threonine metabolism pathways in both cell lines. These insights provide a metabolic characterisation of MYC-driven childhood MB cell lines, which could pave the way for the discovery of novel druggable pathways. Importantly, these findings will also contribute to understand the downstream effects of BETis on MYC-driven MB, potentially aiding the development of new therapeutic strategies to combat medulloblastoma.

Chronic restraint stress promotes the tumorigenic potential of oral squamous cell carcinoma cells by reprogramming fatty acid metabolism via CXCL3 mediated Wnt/β-catenin pathway

Chronic stress promotes tumor progression and may harm homeostasis of energy metabolism by disrupting key metabolic processes. Recently, emerging evidence that chemokines CXCL3 as a novel adipokine plays a new role in lipid metabolism and various human malignancies. However, the role and mechanism of the CXCL3 in oral squamous cell carcinoma (OSCC) progression and reprogramming lipid metabolism induced by chronic restraint stress is unclear. The analysis of transcriptome sequencing, LC-MS, GC-MS, CCK8, cell apoptosis assays, cell cycle analysis, qRT-PCR, ELISA, western blotting, immunofluorescence, immunohistochemistry, RNA interference and lentivirus transfection and a xenograft tumor growth and chronic restraint stress model were used to investigate the role of CXCL3 in the regulation of lipid metabolism and OSCC and explore the underlying molecular mechanisms. We showed that CXCL3 plays a critical role in in fatty acid de novo synthesis and tumor growth induced by chronic restraint stress. We demonstrated that chronic restraint stress promoted lipid accumulation, OSCC growth and metastasis in a mouse xenograft model. CXCL3 knockdown and FH535, an inhibitor of Wnt/β-catenin pathway, could attenuate fatty acid de novo synthesis, cell proliferation and epithelial-mesenchymal transition induced by chronic restraint stress in OSCC cells. Our findings demonstrate that chronic restraint stress promotes the proliferation and metastasis of OSCC by reprogramming fatty acid metabolism via CXCL3 mediated Wnt/β-catenin pathway. Our study provides novel insights to help understand the underlying mechanisms of CXCL3 in OSCC progression induced by chronic restraint stress.

Identification of Metabolism-Associated Biomarkers for Early and Precise Diagnosis of Oral Squamous Cell Carcinoma

The 5-year survival rate for oral squamous cell carcinoma (OSCC), one of the most common head and neck cancers, has not improved in the last 20 years. Poor prognosis of OSCC is the result of failure in early and precise diagnosis. Metabolic reprogramming, including the alteration of the uptake and utilisation of glucose, amino acids and lipids, is an important feature of OSCC and can be used to identify its biomarkers for early and precise diagnosis. In this review, we summarise how recent findings of rewired metabolic networks in OSCC have facilitated early and precise diagnosis of OSCC.

In Vivo Metabolic Analysis of the Anticancer Effects of Plasma-Activated Saline in Three Tumor Animal Models

In recent years, the emerging technology of cold atmospheric pressure plasma (CAP) has grown rapidly along with the many medical applications of cold plasma (e.g., cancer, skin disease, tissue repair, etc.). Plasma-activated liquids (e.g., culture media, water, or normal saline, previously exposed to plasma) are being studied as cancer treatments, and due to their advantages, many researchers prefer plasma-activated liquids as an alternative to CAP in the treatment of cancer. In this study, we showed that plasma-activated-saline (PAS) treatment significantly inhibited tumor growth, as compared with saline, in melanoma, and a low-pH environment had little effect on tumor growth in vivo. In addition, based on an ultra-high-performance liquid tandem chromatography-quadrupole time-of-flight mass spectrometry (UHPLC-QTOF-MS) analysis of tumor cell metabolism, the glycerophospholipid metabolic pathway was the most susceptible metabolic pathway to PAS treatment in melanoma in vitro and in vivo. Furthermore, PAS also inhibited cell proliferation in vivo in oral tongue squamous-cell cancer and non-small-cell lung cancer. There were few toxic side effects in the three animal models, and the treatment was deemed safe to use. In the future, plasma-activated liquids may serve as a potential therapeutic approach in the treatment of cancer.

Inflammation Status and Body Composition Predict Two-Year Mortality of Patients with Locally Advanced Head and Neck Squamous Cell Carcinoma under Provision of Recommended Energy Intake during Concurrent Chemoradiotherapy

Only few prospective cohort trials have evaluated the risk factors for the 2-year mortality rate between two patient subgroups with locally advanced head and neck squamous cell carcinoma (LAHNSCC): oral cavity cancer with adjuvant concurrent chemoradiotherapy (CCRT) (OCC) and non-oral cavity cancer with primary CCRT (NOCC), under the recommended calorie intake and investigated the interplay among calorie supply, nutrition–inflammation biomarkers (NIBs), and total body composition change (TBC), as assessed using dual-energy X-ray absorptiometry (DXA). Patients with LAHNSCC who consumed at least 25 kcal/kg/day during CCRT were prospectively recruited. Clinicopathological variables, blood NIBs, CCRT-related factors, and TBC data before and after treatment were collected. Factor analysis was performed to reduce the number of anthropometric and DXA-derived measurements. Cox proportional hazards models were used for analysis. We enrolled 123 patients with LAHNSCC (69 with OCC and 54 with NOCC). The mean daily calorie intake correlated with the treatment interval changes in total body muscle and fat. Patients consuming ≥30 kcal/kg/day had lower pretreatment levels but exhibited fewer treatment interval changes in anthropometric and DXA measurements than patients consuming <30 kcal/kg/day. In the multivariate analysis of the 2-year mortality rate, the prognostic influence of the recommended calorie intake could not be confirmed, but different risk factors (performance status, pretreatment platelet-to-lymphocyte ratio, and treatment interval body muscle changes in patients with OCC; age, pretreatment neutrophil-to-lymphocyte ratio, and body fat storage in patients with NOCC) showed independent effects. Therefore, the inflammation status and body composition, but not the recommended calorie supply, contribute to the 2-year mortality rate for patients with LAHNSCC receiving CCRT.

Tissue-based metabolomics reveals metabolic signatures and major metabolic pathways of gastric cancer with help of transcriptomic data from TCGA

PURPOSE

The aim of the present study was to screen differential metabolites of gastric cancer (GC) and identify the key metabolic pathways of GC.

METHODS

GC (n=28) and matched paracancerous (PC) tissues were collected, and LC-MS/MS analysis were performed to detect metabolites of GC and PC tissues. Metabolite pathways based on differential metabolites were enriched by MetaboAnalyst, and genes related to metabolite pathways were identified using the KEGGREST function of the R software package. Transcriptomics data from The Cancer Genome Atlas (TCGA) was analyzed to obtain differentially expressed genes (DEGs) of GC. Overlapping genes were acquired from metabonimics and transcriptomics data. Pathway enrichment analysis was performed using String. The protein expression of genes was validated by the Human Protein Atlas (HPA) database.

RESULTS

A total of 325 key metabolites were identified, 111 of which were differentially expressed between the GC and PC groups. Seven metabolite pathways enriched by MetaboAnalyst were chosen, and 361 genes were identified by KEGGREST. A total of 2831 DEGs were identified from the TCGA cohort. Of these, 1317 were down-regulated, and 1636 were up-regulated. Twenty-two overlapping genes were identified between genes related to metabolism and DEGs. Glycerophospholipid (GPL) metabolism is likely associated with GC, of which AGPAT9 and ETNPPL showed lower expressed in GC tissues.

CONCLUSIONS

We investigated the tissue-based metabolomics profile of GC, and several differential metabolites were identified. GPL metabolism may affect on progression of GC.

Integrated non-targeted lipidomics and metabolomics analyses for fluctuations of neonicotinoids imidacloprid and acetamiprid on Neuro-2a cells

Neonicotinoid insecticides are widely used for pest control. However, they are highly water-soluble and easily ingested by organisms, posing potential health risks. In this study, cytotoxicity evaluations of imidacloprid and acetamiprid were conducted in Neuro-2a cells by obtaining their half maximal inhibitory concentration (IC₅₀ values) (1152.1 and 936.5 μM, respectively). The toxic effects at the IC₁₀ and IC₂₀ on cell metabolism were determined by integrated non-targeted lipidomics and metabolomics analyses. Changes in the concentration of acetamiprid caused the most drastic perturbations of metabolism in Neuro-2a cells. Altogether, the detected lipids were mainly attributed to triglyceride, phosphatidylcholine (PC), and diglyceride. These three categories of lipids accounted for more than 67% of the sum in Neuro-2a cells. A total of 14 lipids and other 40 metabolites were screened as differential metabolites based on multivariate data analysis, and PCs were most frequently observed with a proportion of 25.9%. The results demonstrated that lipid metabolism should be paid considerable attention after imidacloprid and acetamiprid exposure. Pathway analysis showed that the metabolisms of glycerophospholipid, sphingolipid, and glutathione were the dominant pathways that were interfered. The present study is the first to investigate the cellular toxic mechanisms after separate imidacloprid and acetamiprid exposure by using lipidomics and metabolomics simultaneously. This research also provides novel insights into the evaluation of the ecological risk of imidacloprid and acetamiprid and contribute to the study of toxicity mechanism of these neonicotinoid insecticides to animals and humans in the future.

High SQLE Expression and Gene Amplification Correlates with Poor Prognosis in Head and Neck Squamous Cell Carcinoma

Objective

Squalene epoxidase (SQLE) is considered a metabolic oncogene, but its biological function and prognostic value in head and neck squamous cell carcinoma (HNSCC) remain unclear. We aimed to evaluate the role of SQLE in the occurrence and development of HNSCC through bioinformatics analysis, and validation experiments.

Methods

Transcriptomic, genomic, and clinical data from The Cancer Genome Atlas were used for pan-cancer analysis. SQLE expression in HNSCC was evaluated using Gene Expression Omnibus datasets and immunohistochemistry. The biological significance of SQLE in the tumor microenvironment (TME) of HNSCC was determined using TISCH, HuRI, LinkedOmics, and TIMER 2.0. The prognostic value of SQLE in HNSCC was analyzed using univariate Cox regression and Kaplan–Meier survival curves. Effect of SQLE on the Cal27 HNSCC cell line was evaluated using cell counting kit 8, wound healing, and EdU assays.

Results

SQLE was overexpressed and amplified in various cancers, including HNSCC. High SQLE expression promoted cell proliferation, associated with T stage in HNSCC patients. Copy number amplification and DNA demethylation contributed to high SQLE expression in HNSCC, which was associated with poor prognosis. SQLE was related to HNSCC TME, and its mRNA expression/copy number alterations were negatively correlated with the infiltration of CD8+ T cells, follicular helper T cells, and regulatory T cell infiltration and mast cell activation and positively correlated with the infiltration of M0 macrophages and resting mast cells in HNSCC.

Conclusion

SQLE was identified as a prognostic biomarker and a potential pharmaceutical target for HNSCC.

Mass spectrometry in the lipid study of cancer

Introduction: Cancer is a heterogeneous disease that exploits various metabolic pathways to meet the demand for increased energy and structural components. Lipids are biomolecules that play essential roles as high energy sources, mediators, and structural components of biological membranes. Accumulating evidence has established that altered lipid metabolism is a hallmark of cancer.Areas covered: Mass spectrometry (MS) is a label-free analytical tool that can simultaneously identify and quantify hundreds of analytes. To date, comprehensive lipid studies exclusively rely on this technique. Here, we reviewed the use of MS in the study of lipids in various cancers and discuss its instrumental limitations and challenges.Expert opinion: MS and MS imaging have significantly contributed to revealing altered lipid metabolism in a variety of cancers. Currently, a single MS approach cannot profile the entire lipidome because of its lack of sensitivity and specificity for all lipid classes. For the metabolic pathway investigation, lipid study requires the integration of MS with other molecular approaches. Future developments regarding the high spatial resolution, mass resolution, and sensitivity of MS instruments are warranted.

Prognostic value of lipid metabolism-related genes in head and neck squamous cell carcinoma

BACKGROUND

Altered lipid metabolism is involved in the development of many tumors. However, the role of dissimilar lipid metabolism in head and neck squamous cell carcinoma (HNSCC) is not fully established.

AIMS

Here, we sought to determine the prognostic value of lipid metabolism-related genes in HNSCC.

METHODS

RNA-seq data and clinical features of 545 HNSCC cases were obtained from The Cancer Genome Atlas database. A regulatory network of transcription factors-lipid metabolism genes and a risk prognostic model of lipid metabolism-related genes was developed using bioinformatics and Cox regression modeling. We used tumor immune estimation resource to analyze immune cell infiltration in patients with HNSCC based on the prognostic index (PI) of lipid metabolism-related genes.

RESULTS

A total of 136 differentially expressed lipid metabolism genes were identified. Of these, 23 are related to prognosis. In addition to predicting HNSCC prognosis, 11 lipid metabolism-related genes (ARSI, CYP27B1, CYP2D6, DGKG, DHCR7, LPIN1, PHYH, PIP5K1B, PLA2G2D, RDH16, and TRIB3) also affect HNSCC clinical features (stage, gender, and pathological stage). The PI of lipid metabolism-related genes embodied the state of HNSCC tumor immune microenvironment.