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

Oral squamous cell carcinoma identification by FTIR spectroscopy of oral biofluids

OBJECTIVES

This case study evaluated the efficacy of mid-infrared spectroscopy on the identification of oral squamous cell carcinoma, following the assessment of unstimulated whole saliva.

STUDY DESIGN AND METHODS

The trial follows a matched case-control design. Saliva samples were characterized through mid-infrared spectroscopy, and chemometric tools were applied to distinguish between case and control participants, further identifying the spectral regions that played a pivotal role in the successful identification of oral squamous cell carcinoma.

RESULTS

Mid-infrared spectroscopy was capable to discriminate between cancer patients and matched controls with 100% of correct predictions. Additionally, the spectral regions mostly contributing to the successful prediction were identified and found to be potentially associated with significant molecular changes crucial to the carcinogenic process.

CONCLUSION

The application of mid-infrared spectroscopy in saliva analysis may be regarded as an innovative, noninvasive, low cost, and sensitive technique contributing to the identification of oral squamous cell carcionma.

Revolutionary Point-of-Care Wearable Diagnostics for Early Disease Detection and Biomarker Discovery through Intelligent Technologies

Early-stage disease detection, particularly in Point-Of-Care (POC) wearable formats, assumes pivotal role in advancing healthcare services and precision-medicine. Public benefits of early detection extend beyond cost-effectively promoting healthcare outcomes, to also include reducing the risk of comorbid diseases. Technological advancements enabling POC biomarker recognition empower discovery of new markers for various health conditions. Integration of POC wearables for biomarker detection with intelligent frameworks represents ground-breaking innovations enabling automation of operations, conducting advanced large-scale data analysis, generating predictive models, and facilitating remote and guided clinical decision-making. These advancements substantially alleviate socioeconomic burdens, creating a paradigm shift in diagnostics, and revolutionizing medical assessments and technology development. This review explores critical topics and recent progress in development of 1) POC systems and wearable solutions for early disease detection and physiological monitoring, as well as 2) discussing current trends in adoption of smart technologies within clinical settings and in developing biological assays, and ultimately 3) exploring utilities of POC systems and smart platforms for biomarker discovery. Additionally, the review explores technology translation from research labs to broader applications. It also addresses associated risks, biases, and challenges of widespread Artificial Intelligence (AI) integration in diagnostics systems, while systematically outlining potential prospects, current challenges, and opportunities.

Soluble CD44 in oral rinses for the early detection of cancer: a prospective cohort study in high-risk individuals

BACKGROUND

There are 54,000 new cases of oral cavity and oropharyngeal cancer in the United States and more than 476,000 worldwide each year. Oral cavity and oropharyngeal squamous cell carcinoma make up most tumors with five-year survival rates of 50% due to prevalence of late-stage diagnoses. Improved methods of early detection in high-risk individuals are urgently needed. We aimed to assess the tumorigenic biomarkers soluble CD44 (solCD44) and total protein (TP) measured using oral rinses as affordable convenient screening tools for cancer detection.

METHODS

In this prospective cohort study, we recruited 150 healthy current or former smokers through a community screening program. Baseline and four annual visits were conducted from March 2011-January 2016 with records followed until August 2020. Participants provided oral rinses, received head and neck exams, and completed questionnaires. SolCD44 and TP levels were measured and compared across groups and time. Participants were placed in the cancer group if malignancy developed in the study period, the suspicious group if physical exams were concerning for premalignant disease or cancer in the head and neck, and the healthy group if there were no suspicious findings. This analysis used two-sample t-test for comparison of means and two-sample Wilcoxon Test for comparison of medians. For subjects with follow-ups, estimated means of biomarkers were obtained from a fitted Repeated Measures Analysis of Variance (RANOVA) model including group, visit, and their interaction. Pairwise comparisons of mean solCD44 were made, including intergroup and intragroup comparison of values at different years.

RESULTS

Most participants were males (58.7%), < 60 years of age. (90.7%), and Black (100%). Baseline mean solCD44 was elevated (2.781 ng/ml) in the cancer group compared to the suspicious group (1.849 ng/ml) and healthy group (1.779 ng/ml).

CONCLUSION

This study supports the feasibility of a CD44-based oral rinse test as an affordable and convenient adjunctive tool for early detection of aerodigestive tract and other cancers in high-risk populations.

Realizing the clinical utility of saliva for monitoring oral diseases

In the era of personalized/precision health care, additional effort is being expended to understand the biology and molecular mechanisms of disease processes. How these mechanisms are affected by individual genetics, environmental exposures, and behavioral choices will encompass an expanding role in the future of optimally preventing and treating diseases. Considering saliva as an important biological fluid for analysis to inform oral disease detection/description continues to expand. This review provides an overview of saliva as a diagnostic fluid and the features of various biomarkers that have been reported. We emphasize the use of salivary biomarkers in periodontitis and transport the reader through extant literature, gaps in knowledge, and a structured approach toward validating and determine the utility of biomarkers in periodontitis. A summation of the findings support the likelihood that a panel of biomarkers including both host molecules and specific microorganisms will be required to most effectively identify risk for early transition to disease, ongoing disease activity, progression, and likelihood of response to standard periodontal therapy. The goals would be to develop predictive algorithms that serve as adjunctive diagnostic tools which provide the clinician and patient important information for making informed clinical decisions.

Identification of a Biomarker Panel from Genome-Wide Methylation to Detect Early HPV-Associated Oropharyngeal Cancer

As oropharyngeal cancer (OPC) associated with human papillomavirus (HPV) increases in men, the need for a screening test to diagnose OPC early is crucial. This study agnostically identified differentially methylated CpG sites to identify additional biomarkers to improve screening for early OPC.DNA was extracted from oral gargles of 89 early cases and 108 frequency matched healthy controls, and processed for genome-wide methylation using the Illumina Infinium MethylationEPIC BeadChip. Selected sites were combined with our prior methylation data in the EPB41L3 gene (CpG sites 438, 427, and 425) and oral HPV16 and HPV18 status were considered as binary variables (positive/negative). Lasso regression identified CpG sites strongly associated with early OPC. ROC curves with AUC were generated. The panel was validated utilizing bootstrap resampling.Machine learning analyses identified 14 markers that are significantly associated with early OPC, including one EPB41L3 CpG site (438) and oral HPV16 status. A final model was trained on all available samples using the discovered panel and was able to predict early OPC compared with controls with an AUC of 0.970 on the training set. In the bootstrap validation sets, the average AUC was 0.935, indicating adequate internal validity.Our data suggest that this panel can detect OPC early, however external validation of this panel is needed. Further refinement of a panel of biomarkers to diagnose OPC earlier is urgently needed to prevent complex treatment of OPC and associated comorbidities, while reducing risk of recurrence.

PREVENTION RELEVANCE

This study identified biomarkers using genome-wide methylation to create a panel capable of discerning early oropharyngeal cancer (OPC) from those without OPC. Such a biomarker panel would be an effective tool to detect OPC early and prevent complications of treatment associated with later diagnosis.

The emerging role of liquid biopsy in oral squamous cell carcinoma detection: advantages and challenges

INTRODUCTION

Oral Squamous Cell Carcinoma (OSCC), the sixth most widespread malignancy in the world, accounts for 90% of all cases of oral cancer. The primary risk factors are tobacco chewing, alcohol consumption, viral infection, and genetic modifications. OSCC has a high morbidity rate due to the lack of early diagnostic methods. Nowadays, liquid biopsy plays a vital role in the initial diagnosis of oral cancer. ctNAs extracted from saliva and serum/plasma offer meaningful insights into tumor genetics and dynamics. The interplay of these elements in saliva and serum/plasma showcases their significance in advancing noninvasive, effective OSCC detection and monitoring.

AREAS COVERED

This review mainly focused on the role of liquid biopsy as an emerging point in the diagnosis and prognosis of OSCC and the current advancements and challenges associated with liquid biopsy.

EXPERT OPINION

Liquid biopsy is regarded as a new, minimally invasive, real-time monitoring tool for cancer diagnosis and prognosis. Many biomolecules found in bodily fluids, including ctDNA, ctRNA, CTCs, and EVs, are significant biomarkers to identify cancer in its early stages. Despite these groundbreaking strides, challenges persist. Standardization of sample collection, isolation, processing, and detection methods is imperative for ensuring result reproducibility across diverse studies.

Capnocytophaga gingivalis is a potential tumor promotor in oral cancer

OBJECTIVES

To investigate the role of oral microbiome in promoting oral squamous cell carcinoma (OSCC) development.

MATERIALS AND METHODS

We investigated the salivary microbiome of 108 controls and 70 OSCC cases by16S rRNA gene sequencing and detected the fluorescence signal of OSCC-related pathological bacteria by fluorescence in situ hybridization assay (FISH). The invasion and migration assays were used to show the differences of invasive and migrative abilities between control and experimental groups. Quantitative real-time PCR and Western blotting were used to verify the epithelial-to-mesenchymal transition (EMT).

RESULTS

In our study, the overall microbiome abundance and composition were richer in the 108 controls than in the 70 OSCC cases. We demonstrated that Streptococcus, Capnocytophaga, Peptostreptococcus, and Lactobacillus were highly abundant in the saliva of OSCC patients by 16S rDNA sequencing and FISH. Moreover, we found that Capnocytophaga gingivalis (C. gingivalis) was highly presented in OSCC tissues by FISH. We focused on C. gingivalis and found that its supernatant induced OSCC cells to undergo EMT, causing the cells to acquire a mesenchymal phenotype associated with highly invasive and metastatic properties.

CONCLUSION

Taken together, these results indicated that C. gingivalis might invade OSCC tissues and played an important role in OSCC by promoting OSCC invasion and metastasis by inducing EMT. Hence, the role of C. gingivalis in cancer progression revealed a new direction for the research of OSCC.

Leveraging technology-driven strategies to untangle omics big data: circumventing roadblocks in clinical facets of oral cancer

Oral cancer is one of the 19most rapidly progressing cancers associated with significant mortality, owing to its extreme degree of invasiveness and aggressive inclination. The early occurrences of this cancer can be clinically deceiving leading to a poor overall survival rate. The primary concerns from a clinical perspective include delayed diagnosis, rapid disease progression, resistance to various chemotherapeutic regimens, and aggressive metastasis, which collectively pose a substantial threat to prognosis. Conventional clinical practices observed since antiquity no longer offer the best possible options to circumvent these roadblocks. The world of current cancer research has been revolutionized with the advent of state-of-the-art technology-driven strategies that offer a ray of hope in confronting said challenges by highlighting the crucial underlying molecular mechanisms and drivers. In recent years, bioinformatics and Machine Learning (ML) techniques have enhanced the possibility of early detection, evaluation of prognosis, and individualization of therapy. This review elaborates on the application of the aforesaid techniques in unraveling potential hints from omics big data to address the complexities existing in various clinical facets of oral cancer. The first section demonstrates the utilization of omics data and ML to disentangle the impediments related to diagnosis. This includes the application of technology-based strategies to optimize early detection, classification, and staging via uncovering biomarkers and molecular signatures. Furthermore, breakthrough concepts such as salivaomics-driven non-invasive biomarker discovery and omics-complemented surgical interventions are articulated in detail. In the following part, the identification of novel disease-specific targets alongside potential therapeutic agents to confront oral cancer via omics-based methodologies is presented. Additionally, a special emphasis is placed on drug resistance, precision medicine, and drug repurposing. In the final section, we discuss the research approaches oriented toward unveiling the prognostic biomarkers and constructing prediction models to capture the metastatic potential of the tumors. Overall, we intend to provide a bird's eye view of the various omics, bioinformatics, and ML approaches currently being used in oral cancer research through relevant case studies.

Evaluation of Metabolomics as Diagnostic Targets in Oral Squamous Cell Carcinoma: A Systematic Review

In recent years, high-throughput technologies have facilitated the widespread use of metabolomics to identify biomarkers and targets for oral squamous cell carcinoma (OSCC). As a result, the primary goal of this systematic review is to identify and evaluate metabolite biomarkers and their pathways for OSCC that featured consistently across studies despite methodological variations. Six electronic databases (Medline, Cochrane, Web of Science, CINAHL, ProQuest, and Embase) were reviewed for the longitudinal studies involving OSCC patients and metabolic marker analysis (in accordance with PRISMA 2020). The studies included ranged from the inception of metabolomics in OSCC (i.e., 1 January 2007) to 30 April 2023. The included studies were then assessed for their quality using the modified version of NIH quality assessment tool and QUADOMICS. Thirteen studies were included after screening 2285 studies. The majority of the studies were from South Asian regions, and metabolites were most frequently derived from saliva. Amino acids accounted for more than quarter of the detected metabolites, with glutamate and methionine being the most prominent. The top dysregulated metabolites indicated dysregulation of six significantly enriched pathways including aminoacyl-tRNA biosynthesis, glutathione metabolism and arginine biosynthesis with the false discovery rate (FDR) <0.05. Finally, this review highlights the potential of metabolomics for early diagnosis and therapeutic targeting of OSCC. However, larger studies and standardized protocols are needed to validate these findings and make them a clinical reality.

Biomarkers as Biomedical Bioindicators: Approaches and Techniques for the Detection, Analysis, and Validation of Novel Biomarkers of Diseases

A biomarker is any measurable biological moiety that can be assessed and measured as a potential index of either normal or abnormal pathophysiology or pharmacological responses to some treatment regimen. Every tissue in the body has a distinct biomolecular make-up, which is known as its biomarkers, which possess particular features, viz., the levels or activities (the ability of a gene or protein to carry out a particular body function) of a gene, protein, or other biomolecules. A biomarker refers to some feature that can be objectively quantified by various biochemical samples and evaluates the exposure of an organism to normal or pathological procedures or their response to some drug interventions. An in-depth and comprehensive realization of the significance of these biomarkers becomes quite important for the efficient diagnosis of diseases and for providing the appropriate directions in case of multiple drug choices being presently available, which can benefit any patient. Presently, advancements in omics technologies have opened up new possibilities to obtain novel biomarkers of different types, employing genomic strategies, epigenetics, metabolomics, transcriptomics, lipid-based analysis, protein studies, etc. Particular biomarkers for specific diseases, their prognostic capabilities, and responses to therapeutic paradigms have been applied for screening of various normal healthy, as well as diseased, tissue or serum samples, and act as appreciable tools in pharmacology and therapeutics, etc. In this review, we have summarized various biomarker types, their classification, and monitoring and detection methods and strategies. Various analytical techniques and approaches of biomarkers have also been described along with various clinically applicable biomarker sensing techniques which have been developed in the recent past. A section has also been dedicated to the latest trends in the formulation and designing of nanotechnology-based biomarker sensing and detection developments in this field.

Salivary Interleukin Levels in Oral Squamous Cell Carcinoma and Oral Epithelial Dysplasia: Findings from a Sri Lankan Study

The incidence of oral squamous cell carcinoma (OSCC), and its precursor, oral epithelial dysplasia (OED), is on the rise, especially in South Asia. OSCC is the leading cancer in males in Sri Lanka, with >80% diagnosed at advanced clinical stages. Early detection is paramount to improve patient outcome, and saliva testing is a promising non-invasive tool. The aim of this study was to assess salivary interleukins (lL1β, IL6, and IL8) in OSCC, OED and disease-free controls in a Sri Lankan study cohort. A case-control study with OSCC (n = 37), OED (n = 30) patients and disease-free controls (n = 30) was conducted. Salivary lL1β, IL6, and IL8 were quantified using enzyme-linked immuno-sorbent assay. Comparisons between different diagnostic groups and potential correlations to risk factors were assessed. Salivary levels for the three tested interleukins increased from disease-free controls through OED, and were highest in OSCC samples. Furthermore, the levels of IL1β, IL6, and IL8 increased progressively with OED grade. The discrimination between patients (OSCC and OED) and controls, as assessed by AUC of receiver operating characteristic curves, was 0.9 for IL8 (p = 0.0001) and 0.8 for IL6 (p = 0.0001), while IL1β differentiated OSCC from controls (AUC 0.7, p = 0.006). No significant associations were found between salivary interleukin levels and smoking, alcohol, and betel quid risk factors. Our findings suggest that salivary IL1β, IL6, and IL8 are associated with disease severity of OED, and are potential biomarkers for predicting disease progression in OED, and the screening of OSCC.

Salivary Biomarkers in Oral Squamous Cell Carcinoma: A Proteomic Overview

BACKGROUND

Oral squamous cell carcinoma (OSCC) is one of the most frequent cancers worldwide. Endoscopic methods may be useful in the evaluation of oral injuries even though the diagnostic gold standard is a biopsy. Targeted screenings could be considered the best way to prevent the occurrence of oral cancer. Aimed to elucidate the potential identification of specific biomarkers of OSCC, the use of saliva is convenient and noninvasive. Many studies reported more than a hundred putative saliva biomarkers for OSCC, and proteogenomic approaches were fundamental to disclosing this issue.

METHODS

Relevant literature published in the last few years was systematically searched on PubMed and we focused on articles about the use and study of salivary biomarkers in the diagnostics of head and neck cancer (n = 110). Thereafter, we performed a selection focusing on diagnosis with salivary proteomics in OSCC (n = 8).

RESULTS

Saliva proteomics can be a source of biomarkers for OSCC. We reviewed literature of biomarker proteins in saliva that could also be evaluated as probable targets for non-invasive screening of oral neoplasm such as cytokines, matrix metalloproteinases, and acute-phase response proteins.

CONCLUSIONS

The measurement of salivary biomarkers is a highly hopeful technique for the diagnosis of OSCC. Proteogenomic approaches could permit an accurate and early diagnosis of OSCC. This review seeks to generate an up-to-date view on translational OSCC issues by raising awareness of researchers, physicians, and surgeons. Renewed clinical studies, which will validate the sensitivity and specificity of salivary biomarkers, are necessary to translate these results into possible strategies for early diagnosis of OSCC, thus improving patient outcomes.

Advances in the Diagnosis, Monitoring, and Progression of Oral Cancer through Saliva: An Update

The early detection of cancer, and in particular oral cancer, has been a priority objective of study in recent years. Saliva has been proposed as an easy-to-obtain means of providing the necessary information to diagnose malignant lesions in the oral cavity, since it can be obtained very easily and completely noninvasively. There are a number of molecules, known as biomarkers, which may be involved in the malignant transformation of oral lesions, and which have different natures. The involvement of proteins (“proteomics”), metabolites (“metabolomics”), and even certain genes in the structural changes of altered tissue has been investigated in order to establish validated parameters for the early diagnosis of oral cancer. In addition, the development of new analytical assay methods that can reduce costs and obtain better results in terms of sensitivity and specificity has been a key point in recent research in this field. Even though there are numerous biomarkers with results showing high sensitivity and specificity, there is still a need for more studies, with a larger sample and with analytical methods that can constitute a real advance in time and cost. Although salivary biomarkers are a promising new diagnostic tool for oral cancer, for the moment they do not replace biopsy as the “gold standard”.

The genomic and proteomic landscape in oral lichen planus versus oral squamous cell carcinoma: a scoping review

BACKGROUND

Oral lichen planus (OLP), a World Health Organization (WHO)-classified oral potentially malignant condition, confers a 1% risk of transformation to oral squamous cell carcinoma (OSCC). There does not appear to be a consensus understanding of the underlying molecular events. This scoping review aimed to identify critical molecular pathways and highlight gaps in existing knowledge on malignant transformation in OLP.

METHODS

Following Preferred Reporting Items for Systematic Reviews and Meta-Analysis Protocols (PRISMA-P) guidelines, a comprehensive literature search and methodical screening identified 61 relevant studies detailing molecular differences between OLP and OSCC.

RESULTS

Molecular changes shared between OLP and OSCC included those affecting cellular proliferation (altered p53 expression, hypermethylation of p16/CDKN2A, MYC gains, increased ki-67), apoptosis (increased bcl-2 and survivin expression), extracellular matrix (ECM) remodeling (increased matrix metalloproteinase [MMP] expression), and transcriptional control (altered bmi1 and microRNA [miRNA] expression). In addition, some molecular alterations accumulated incrementally from control to OLP to OSCC or were present in higher-risk erosive variants of OLP or transformed OLP. Few studies included rigorous diagnostic inclusion criteria or unbiased discovery methods.

CONCLUSIONS

Results of this review support the potentially malignant nature of OLP and imply that molecular events associated with malignant transformation may be heterogeneous. In addition, findings in this review highlight the need for additional studies using rigorous diagnostic inclusion criteria and unbiased discovery methods to further understand this process.

Breast cancer in the era of integrating “Omics” approaches

Worldwide, breast cancer is the leading cause of cancer-related deaths in women. Breast cancer is a heterogeneous disease characterized by different clinical outcomes in terms of pathological features, response to therapies, and long-term patient survival. Thus, the heterogeneity found in this cancer led to the concept that breast cancer is not a single disease, being very heterogeneous both at the molecular and clinical level, and rather represents a group of distinct neoplastic diseases of the breast and its cells. Indubitably, in the past decades we witnessed a significant development of innovative therapeutic approaches, including targeted and immunotherapies, leading to impressive results in terms of increased survival for breast cancer patients. However, these multimodal treatments fail to prevent recurrence and metastasis. Therefore, it is urgent to improve our understanding of breast tumor and metastasis biology. Over the past few years, high-throughput “omics” technologies through the identification of novel biomarkers and molecular profiling have shown their great potential in generating new insights in the study of breast cancer, also improving diagnosis, prognosis and prediction of response to treatment. In this review, we discuss how the implementation of “omics” strategies and their integration may lead to a better comprehension of the mechanisms underlying breast cancer. In particular, with the aim to investigate the correlation between different “omics” datasets and to define the new important key pathway and upstream regulators in breast cancer, we applied a new integrative meta-analysis method to combine the results obtained from genomics, proteomics and metabolomics approaches in different revised studies.

The analysis of metabolomics and transcriptomics data in head and neck squamous cell carcinoma

OBJECTIVE

Studies have shown that cancer progression of head and neck squamous cell carcinoma (HNSCC) is related with metabolic alterations. The aim of this study is to identify the clinical roles of metabolic alterations in HNSCC.

MATERIALS AND METHODS

Metabolism-related genes associated with HNSCC were searched in public databases. A predictive and efficacious LASSO model was fabricated to optimize the diagnosis that was based on these genes. Meantime, Ultra-Performance Liquid Chromatography-Quadrupole/Orbitrap High Resolution Mass Spectrometry (UHPLC-Q-Orbitrap HRMS) was used to compare patients with HNSCC (n=73) with healthy controls (HC) (n=51) for serum metabolites. Potential biomarkers and alterations in serum metabolites were analysed and evaluated using t-test analysis, principal component analysis and orthogonal partial least square discrimination analysis (OPLS-DA).

RESULTS

Overall, 21 differential metabolites were probed in serum, of which 8 metabolites had potential for clinical uses. Transcriptome analysis showed that 4 genes in the constructed LASSO model were found to be associated with 7 differential metabolites. Metabolic pathway analysis by MetaboAnalyst showed that the biomarkers that were related with HNSCC were closely related to 4 metabolism pathways (p<0.05).

CONCLUSION

To conclude, future research on HNSCC should be directed toward multi-omics to provide treatment, intervention, or diagnosis of the disease.

Detection of Nail Oncometabolite SAICAR in Oral Cancer Patients and Its Molecular Interactions with PKM2 Enzyme

Oncometabolites are known to drive metabolic adaptations in oral cancer. Several oncometabolites are known to be shared between cancer cells and non-cancer cells including microbiotas to modulate the tumor microenvironment. Among potential oncometabolites, succinylaminoimidazolecarboxamide ribose5′-phosphate (SAICAR) supports the growth and invasiveness of cancer cells by pyruvate kinase M2 (PKM2) enzyme in a glucose starved tumor microenvironment. There is a significant gap that shows the detection of SAICAR in biological samples including nails of oral cancer patients. Metabolite identification of SAICAR was investigated in the nails of oral cancer patients using novel vertical tube gel electrophoresis (VTGE) and LC-HRMS. Further molecular docking and molecular dynamics simulations (MDS) were employed to determine the nature of molecular interactions of SAICAR (CHEBI ID:18319) with PKM2 (PDB ID: 4G1N). Molecular docking of SAICAR (CHEBI ID:18319) was performed against pyruvate kinase M2 (PDB ID: 4G1N). Data suggest the presence of oncometabolite SAICAR in nails of oral cancer. Molecular docking of SAICAR with PKM2 showed appreciable binding affinity (−8.0 kcal/mol) with residues including ASP407, THR405, GLU410, ARG443, GLY321, ARG436, HIS439, LYS266, and TYR466. Furthermore, MDS confirmed the specific binding of SAICAR within the activator site of PKM2 and the stability of SAICAR and PKM2 molecular interactions. In conclusion, SAICAR is a promising oncometabolite biomarker present in the nails of oral cancer patients. A significant activation potential of SAICAR exists with the PKM2 enzyme.

Diagnostic salivary biomarkers in oral cancer and oral potentially malignant disorders and their relationships to risk factors - A systematic review

INTRODUCTION

Oral squamous cell carcinoma (OSCC) and oral potentially malignant disorders (OPMD) are a significant health burden globally. Smoking, alcohol, and betel quid are the main risk factors. Lack of screening methods has been highlighted as a significant challenge in management. Salivary biomarkers are proposed as noninvasive diagnostic tools. The aim of this systematic review was to study salivary biomarkers reported in OSCC and OPMD. Specific objectives were to select a salivary biomarker panel suitable for early detection of OSCC and OPMD and to assess relationships between salivary biomarkers and risk factors.

METHODS

Electronic literature search was conducted in academic databases (Scopus, Medline, Embase and Web of Science) without any restrictions. Following calibration, two blinded reviewers screened the studies and extracted data. A risk of bias assessment was conducted using Newcastle Ottawa scale. 295 studies were included with descriptive data analysis.

EXPERT OPINION

A salivary biomarker panel including Interleukin (IL) 1β, IL6, and IL8 was selected for OSCC and OPMD. Reported relationships between salivary biomarkers and risk factors are discussed and research gaps are highlighted. Future research should be directed to assess potential salivary biomarkers and their relationships to risk factors in order to understand the biomarker's role in disease initiation.

Precision Medicine Gains Momentum: Novel 3D Models and Stem Cell-Based Approaches in Head and Neck Cancer

Despite the current progress in the development of new concepts of precision medicine for head and neck squamous cell carcinoma (HNSCC), in particular targeted therapies and immune checkpoint inhibition (CPI), overall survival rates have not improved during the last decades. This is, on the one hand, caused by the fact that a significant number of patients presents with late stage disease at the time of diagnosis, on the other hand HNSCC frequently develop therapeutic resistance. Distinct intratumoral and intertumoral heterogeneity is one of the strongest features in HNSCC and has hindered both the identification of specific biomarkers and the establishment of targeted therapies for this disease so far. To date, there is a paucity of reliable preclinical models, particularly those that can predict responses to immune CPI, as these models require an intact tumor microenvironment (TME). The "ideal" preclinical cancer model is supposed to take both the TME as well as tumor heterogeneity into account. Although HNSCC patients are frequently studied in clinical trials, there is a lack of reliable prognostic biomarkers allowing a better stratification of individuals who might benefit from new concepts of targeted or immunotherapeutic strategies. Emerging evidence indicates that cancer stem cells (CSCs) are highly tumorigenic. Through the process of stemness, epithelial cells acquire an invasive phenotype contributing to metastasis and recurrence. Specific markers for CSC such as CD133 and CD44 expression and ALDH activity help to identify CSC in HNSCC. For the majority of patients, allocation of treatment regimens is simply based on histological diagnosis and on tumor location and disease staging (clinical risk assessments) rather than on specific or individual tumor biology. Hence there is an urgent need for tools to stratify HNSCC patients and pave the way for personalized therapeutic options. This work reviews the current literature on novel approaches in implementing three-dimensional (3D) HNSCC in vitro and in vivo tumor models in the clinical daily routine. Stem-cell based assays will be particularly discussed. Those models are highly anticipated to serve as a preclinical prediction platform for the evaluation of stable biomarkers and for therapeutic efficacy testing.

Feasibility of a Portable Electronic Nose for Detection of Oral Squamous Cell Carcinoma in Sudan

BACKGROUND

Oral squamous cell carcinoma (OSCC) is increasing at an alarming rate particularly in low-income countries. This urges for research into noninvasive, user-friendly diagnostic tools that can be used in limited-resource settings. This study aims to test and validate the feasibility of e-nose technology for detecting OSCC in the limited-resource settings of the Sudanese population.

METHODS

Two e-nose devices (Aeonose™, eNose Company, Zutphen, The Netherlands) were used to collect breath samples from OSCC (n = 49) and control (n = 35) patients. Patients were divided into a training group for building an artificial neural network (ANN) model and a blinded control group for model validation. The Statistical Package for the Social Sciences (SPSS) software was used for the analysis of baseline characteristics and regression. Aethena proprietary software was used for data analysis using artificial neural networks based on patterns of volatile organic compounds.

RESULTS

A diagnostic accuracy of 81% was observed, with 88% sensitivity and 71% specificity.

CONCLUSIONS

This study demonstrates that e-nose is an efficient tool for OSCC detection in limited-resource settings, where it offers a valuable cost-effective strategy to tackle the burden posed by OSCC.

An integrated approach for identification of a panel of candidate genes arbitrated for invasion and metastasis in oral squamous cell carcinoma

Oral squamous cell carcinoma (OSCC) is known for its aggressiveness associated with poor prognosis. The molecular mechanisms underlying the invasion and metastasis are still poorly understood. An improved understanding of these mechanisms shall precede the development of new diagnostic tools and targeted therapies. We report an integrated approach using bioinformatics to predict candidate genes, coupled with proteomics and immunohistochemistry for validating their presence and involvement in OSCC pathways heralding invasion and metastasis. Four genes POSTN, TNC, CAV1 and FSCN1 were identified. A protein–protein interaction network analysis teamed with pathway analysis led us to propose the role of the identified genes in invasion and metastasis in OSCC. Further analyses of archived FFPE blocks of various grades of oral cancer was carried out using TMT-based mass spectrometry and immunohistochemistry. Results of this study expressed a strong communiqué and interrelationship between these candidate genes. This study emphasizes the significance of a molecular biomarker panel as a diagnostic tool and its correlation with the invasion and metastatic pathway of OSCC. An insight into the probable association of CAF's and these biomarkers in the evolution and malignant transformation of OSCC further magnifies the molecular-biological spectrum of OSCC tumour microenvironment.

Fourier Transform Infrared Spectroscopy in Oral Cancer Diagnosis

Oral cancer is one of the most common cancers worldwide. Despite easy access to the oral cavity and significant advances in treatment, the morbidity and mortality rates for oral cancer patients are still very high, mainly due to late-stage diagnosis when treatment is less successful. Oral cancer has also been found to be the most expensive cancer to treat in the United States. Early diagnosis of oral cancer can significantly improve patient survival rate and reduce medical costs. There is an urgent unmet need for an accurate and sensitive molecular-based diagnostic tool for early oral cancer detection. Fourier transform infrared spectroscopy has gained increasing attention in cancer research due to its ability to elucidate qualitative and quantitative information of biochemical content and molecular-level structural changes in complex biological systems. The diagnosis of a disease is based on biochemical changes underlying the disease pathology rather than morphological changes of the tissue. It is a versatile method that can work with tissues, cells, or body fluids. In this review article, we aim to summarize the studies of infrared spectroscopy in oral cancer research and detection. It provides early evidence to support the potential application of infrared spectroscopy as a diagnostic tool for oral potentially malignant and malignant lesions. The challenges and opportunities in clinical translation are also discussed.

Potential Metabolic Biomarkers for Early Detection of Oral Lichen Planus, a Precancerous Lesion

Background: Oral lichen planus (OLP) is a T-cell-mediated chronic inflammatory disorder and precancerous oral lesion with high incidence. The current diagnostic method of OLP is very limited and metabolomics may provide a new approach for quantitative evaluation.

Methods: The Ultra-Performance Liquid Chromatography-Quadrupole/Orbitrap High Resolution Mass Spectrometry (UHPLC-Q-Orbitrap HRMS) was applied to analyze the change of metabolites in serum of patients with OLP. A total of 115 OLP patients and 124 healthy controls were assigned to either a training set (n = 160) or a test set (n = 79). The potential biomarkers and the change of serum metabolites were profiled and evaluated by multivariate analysis.

Results: Totally, 23 differential metabolites were identified in the training set between OLP group and healthy group. Three prominent metabolites in receiver operating characteristic (ROC) were selected as a panel to distinguish OLP or healthy individuals in the test set, and the diagnostic accuracy was 86.1%.

Conclusions: This study established a new method for the early detection of OLP by analyzing serum metabolomics using UHPLC-Q-Orbitrap HRMS, which will help in understanding the pathological processes of OLP and identifying precancerous lesions in oral cavity.

Metabolic Profiles of Whole Serum and Serum-Derived Exosomes Are Different in Head and Neck Cancer Patients Treated by Radiotherapy

BACKGROUND

In general, the serum metabolome reflects the patient's body response to both disease state and implemented treatment. Though serum-derived exosomes are an emerging type of liquid biopsy, the metabolite content of these vesicles remains under researched. The aim of this pilot study was to compare the metabolite profiles of the whole serum and serum-derived exosomes in the context of differences between cancer patients and healthy controls as well as patients' response to radiotherapy (RT).

METHODS

Serum samples were collected from 10 healthy volunteers and 10 patients with head and neck cancer before and after RT. Metabolites extracted from serum and exosomes were analyzed by the gas chromatography-mass spectrometry (GC-MS).

RESULTS

An untargeted GC-MS-based approach identified 182 and 46 metabolites in serum and exosomes, respectively. Metabolites that differentiated cancer and control samples, either serum or exosomes, were associated with energy metabolism. Serum metabolites affected by RT were associated with the metabolism of amino acids, sugars, lipids, and nucleotides.

CONCLUSIONS

cancer-related features of energy metabolism could be detected in both types of specimens. On the other hand, in contrast to RT-induced changes observed in serum metabolome, this pilot study did not reveal a specific radiation-related pattern of exosome metabolites.

Diagnostic and Prognostic Value of Salivary Biochemical Markers in Oral Squamous Cell Carcinoma

The purpose of the work is a comprehensive assessment of biochemical saliva markers for the diagnosis and prognosis of oral cancer. The group of patients included 68 patients with oral squamous cell carcinoma, 50 with non-cancerous diseases of the oral cavity, and 114 healthy volunteers. Before the start of treatment, 23 biochemical parameters of saliva were determined. Participants were monitored for six years to assess survival rates. The statistical analysis was performed by means of Statistica 10.0 and R package. A complex of metabolic changes occurring in saliva in oral cancer is described. It was shown that none of the studied parameters could be used to diagnose oral cancer in an independent variant; the use of combinations of parameters is more informative. The high prognostic value of the content of malondialdehyde (MDA) and the Na/K-ratio in saliva before treatment was established. Thus, the content of MDA ˂ 7.34 nmol/mL and the Na/K-ratio > 1.09 c.u. is a prognostically unfavorable factor (HR = 7.88, 95% CI 1.10-54.62, p = 0.01876), which may be useful for optimizing the treatment of patients with oral cancer. It has been shown that saliva has great potential for the development of diagnostic and prognostic tests for oral cancer.

[Standardized and individualized diagnosis and treatment of oral squamous cell carcinoma: opportunities and challenges]

How to improve the effects of treatment on patients with oral squamous cell carcinoma (OSCC) has always been the focus of clinical and basic studies. The standardized diagnosis and treatment of malignant tumors aim to improve the effects of treatment, and individualized treatment based on standardized diagnosis and treatment may further improve these effects. On the basis of the existing guidelines for the diagnosis and treatment of patients with OSCC, this study explored the opportunities and challenges of standardized and individualized diagnosis and treatment of OSCC. These challenges and opportunities were related to the updates of clinical and pathological staging system, surgical margins, and neck dissection in patients with OSCC at early stage and preoperative induction therapy and postoperative adjuvant treatment in patients with advanced OSCC. This study also shared ideas on clinical studies of OSCC to optimize the existing treatment schemes, improve the treatment effects, and enhance the guidelines.

Analysis of octamer-binding transcription factor-4 expression in oral leukoplakia

Background:

Oral potentially malignant disorders have a risk for malignant transformation but are difficult to reliably identify and predict which patients are at the risk for malignant transformation. OCT4 has been hypothesized to play a key oncogenic driver in a variety of solid tumors. A deeper understanding of the aberrant molecular pathways which lead to carcinogenesis needs to be identified by the potential markers.

Aims:

To assess the OCT4 stemness factor in oral leukoplakia for its potential risk to malignant transformation.

Settings and Design:

20 cases of oral leukoplakia were obtained from archives at Oral Cancer Research & Coordinating center (OCRCC) Malaysia Subjects and Methods: 20 cases of oral leukoplakia were assessed by OCT4 immunohistochemically. Oral squamous cell carcinoma was used as a control.

Result:

no expression of OCT 4 was observed in any cases of oral leukoplakia.

Conclusion:

The molecular mechanisms of Oct4 regulation and in particular of its switch on and off in tissues depends upon its microenvironment, which makes it challenging in fundamental and applied research fields of regenerative medicine and cancer therapy. It's better that patients should undergo multiple biopsies for the early detection of malignant transformation with close follow-up during the first two to three years, a large amount of work remains to be done with multi-marker panel investigation, as cure rates have remained constant over three decades.

Predicted yeast interactome and network-based interpretation of transcriptionally changed genes

Saccharomyces cerevisiae, budding yeast, is a widely used model organism and research tool in genetics studies. Many efforts have been directed at constructing a high-quality comprehensive molecular interaction network to elucidate the design logic of the gene circuitries in this classic model organism. In this work, we present the yeast interactome resource (YIR), which includes 22,238 putative functional gene interactions inferred from functional gene association data integrated from 10 databases focusing on diverse functional perspectives. These putative functional gene interactions are expected to cover 18.84% of yeast protein interactions, and 38.49% may represent protein interactions. Based on the YIR, a gene set linkage analysis (GSLA) web tool was developed to annotate the potential functional impacts of a set of transcriptionally changed genes. In a case study, we show that the YIR/GSLA system produced more extensive and concise annotations compared with widely used gene set annotation tools, including PANTHER and DAVID. Both YIR and GSLA are accessible through the website http://yeast.biomedtzc.cn.

Oral squamous cell carcinoma diagnosed from saliva metabolic profiling

Saliva is a noninvasive biofluid that can contain metabolite signatures of oral squamous cell carcinoma (OSCC). Conductive polymer spray ionization mass spectrometry (CPSI-MS) is employed to record a wide range of metabolite species within a few seconds, making this technique appealing as a point-of-care method for the early detection of OSCC. Saliva samples from 373 volunteers, 124 who are healthy, 124 who have premalignant lesions, and 125 who are OSCC patients, were collected for discovering and validating dysregulated metabolites and determining altered metabolic pathways. Metabolite markers were reconfirmed at the primary tissue level by desorption electrospray ionization MS imaging (DESI-MSI), demonstrating the reliability of diagnoses based on saliva metabolomics. With the aid of machine learning (ML), OSCC and premalignant lesions can be distinguished from the normal physical condition in real time with an accuracy of 86.7%, on a person by person basis. These results suggest that the combination of CPSI-MS and ML is a feasible tool for accurate, automated diagnosis of OSCC in clinical practice.

Vibrational Spectroscopy Fingerprinting in Medicine: from Molecular to Clinical Practice

In the last two decades, Fourier Transform Infrared (FTIR) and Raman spectroscopies turn out to be valuable tools, capable of providing fingerprint-type information on the composition and structural conformation of specific molecular species. Vibrational spectroscopy's multiple features, namely highly sensitive to changes at the molecular level, noninvasive, nondestructive, reagent-free, and waste-free analysis, illustrate the potential in biomedical field. In light of this, the current work features recent data and major trends in spectroscopic analyses going from in vivo measurements up to ex vivo extracted and processed materials. The ability to offer insights into the structural variations underpinning pathogenesis of diseases could provide a platform for disease diagnosis and therapy effectiveness evaluation as a future standard clinical tool.

Integrative transcriptomics, proteomics, and metabolomics data analysis exploring the injury mechanism of ricin on human lung epithelial cells

Ricin (RT) is a plant toxin belonging to the family of type II ribosome-inactivating protein with high bioterrorism potential. Aerosol RT exposure is the most lethal route, but its mechanism of injury needs further investigation. In the present study, we performed a comprehensive transcriptomics, proteomics and metabolomics analysis on the potential mechanism of injury caused by RT on human lung epithelial cells. In total, 5872 genes, 187 proteins, and 143 metabolites were shown to be significantly changed in human lung epithelial cells after RT treatment. Molecular function, pathway, and network analyses, the genes and proteins regulated in RT-treated cells were mainly attributed to fatty acid metabolism, arginine and proline metabolism and ubiquitin-mediated proteolysis pathway. Furthermore, a comprehensive analysis of transcripts, proteins, and metabolites was performed. The results revealed the correlated genes, proteins, and metabolic pathways regulated in metabolic pathways, amino acid metabolism, transcription and energy metabolism. These genes, proteins, and metabolites involved in these dis-regulated pathways may provide a more targeted and credible direction to study the mechanism of RT injury on human lung epithelial cells. This study provides large-scale omics data that can be used to develop a new strategy for the prevention, rapid diagnosis, and treatment of RT poisoning, especially of RT aerosol.

Systems Biology Approaches and Precision Oral Health: A Circadian Clock Perspective

A vast majority of the pathophysiological and metabolic processes in humans are temporally controlled by a master circadian clock located centrally in the hypothalamic suprachiasmatic nucleus of the brain, as well as by specialized peripheral oscillators located in other body tissues. This circadian clock system generates a rhythmical diurnal transcriptional-translational cycle in clock genes and protein expression and activities regulating numerous downstream target genes. Clock genes as key regulators of physiological function and dysfunction of the circadian clock have been linked to various diseases and multiple morbidities. Emerging omics technologies permits largescale multi-dimensional investigations of the molecular landscape of a given disease and the comprehensive characterization of its underlying cellular components (e.g., proteins, genes, lipids, metabolites), their mechanism of actions, functional networks and regulatory systems. Ultimately, they can be used to better understand disease and interpatient heterogeneity, individual profile, identify personalized targetable key molecules and pathways, discover novel biomarkers and genetic alterations, which collectively can allow for a better patient stratification into clinically relevant subgroups to improve disease prediction and prevention, early diagnostic, clinical outcomes, therapeutic benefits, patient's quality of life and survival. The use of “omics” technologies has allowed for recent breakthroughs in several scientific domains, including in the field of circadian clock biology. Although studies have explored the role of clock genes using circadiOmics (which integrates circadian omics, such as genomics, transcriptomics, proteomics and metabolomics) in human disease, no such studies have investigated the implications of circadian disruption in oral, head and neck pathologies using multi-omics approaches and linking the omics data to patient-specific circadian profiles. There is a burgeoning body of evidence that circadian clock controls the development and homeostasis of oral and maxillofacial structures, such as salivary glands, teeth and oral epithelium. Hence, in the current era of precision medicine and dentistry and patient-centered health care, it is becoming evident that a multi-omics approach is needed to improve our understanding of the role of circadian clock-controlled key players in the regulation of head and neck pathologies. This review discusses current knowledge on the role of the circadian clock and the contribution of omics-based approaches toward a novel precision health era for diagnosing and treating head and neck pathologies, with an emphasis on oral, head and neck cancer and Sjögren's syndrome.

Evaluation of oxidative stress and the microenvironment in oral submucous fibrosis

BACKGROUND

Oral Submucous fibrosis (OSF) is a chronic inflammatory mucosal disease of unknown etiology. Statistics show cases of OSF which has a high rate of overall prevalence and increase the chance of malignant transformation. As we know malignant cells is situated in a very complex microenvironment with altered metabolic pathway including intermediates which participate in oxidative stress process which enhances metabolic rewiring and promotes tumor progression. This study aims to evaluate the tumor microenvironment and their role in metabolic reprogramming.

METHODS

This study was conducted on the serum sample of OSF (n = 20) compared to the healthy group (n = 20) using ELISA. The serum levels of intermediate by-products of metabolic pathway and oxidative stress induced biomolecular damage products were determined. The sensitivity of results was analyzed by correlating it with markers of metabolic status (Glucose, Total cholesterol, Total protein).

RESULTS

Metabolic pathway intermediates molecules like Fatty Acids (FAA), Ascorbic acid, Citrate, Oxaloacetate (OAA), levels were significantly high in the serum of OSF cases. This indicated that intermediates act as a metabolic switch that drives cells to adapt malignant transformation pathway. Markers related to oxidative DNA damage (8-hydroxy-2' -deoxyguanosine), Oxidative lipid peroxidation (8-epi-Prostaglandin F2α), and Protein carbonyl were significantly up-regulated. This significant increase in oxidative stress marker revealed the reprogramming of the metabolic pathway for fulfilling the nutritional requirement of cancer cells. A further significant correlation was observed with metabolic products confirmed altered metabolic status.

CONCLUSION

Our findings could identify the differentiating intermediate pathway metabolites and oxidative damage to biomolecules that are leading to rewiring of metabolism in the OSF group. Findings described in the study can be helpful to explain further the molecular aspects that lead to the progression of OSF towards carcinogenesis.

Salivary markers of hepato-metabolic comorbidities in pediatric obesity

BACKGROUND

The pediatric obesity epidemic calls for the noninvasive detection of individuals at higher risk of complications.

AIMS

To investigate the diagnostic role of combined salivary uric acid (UA), glucose and insulin levels to screen noninvasively for metabolic syndrome (MetS) and nonalcoholic fatty liver disease.

METHODS

Medical history, clinical, anthropometric, and laboratory data including serum triglyceride, glucose, insulin, HOMA, HDL-cholesterol, and UA levels of 23 obese children (15 with [St+] and 8 without [St-] ultrasonographic hepatic steatosis) and 18 normal weight controls were considered.

RESULTS

Serum and salivary UA (p < 0.05; R² = 0.51), insulin (p < 0.0001; R² = 0.79), and HOMA (p < 0.0001; R² = 0.79) levels were significantly correlated; however their values tended to be only slightly higher in the obese patients, predominately in [St+], than in the controls. Notably, UA and insulin levels in both fluids increased in parallel to the number of MetS components. After conversion of the z-logit function including salivary/anthropometric parameters in a stepwise logistic regression analysis, a factor of 0.5 allowed for predicting hepatic steatosis with high sensitivity, specificity, and total accuracy.

CONCLUSIONS

Salivary testing together with selected anthropometric parameters helps to identify noninvasively obese children with hepatic steatosis and/or having MetS components.

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.

Effect of storage conditions on salivary polyamines quantified via liquid chromatography-mass spectrometry

Salivary polyamines are potential non-invasive tools for screening various types of cancers. For clinical use, the reproducibility of these metabolites should be evaluated under various storage conditions, including duration and temperature, to establish standard operating protocols. Polyamines and amino acids in unstimulated whole saliva were quantified via liquid chromatography-mass spectrometry. Concentrations of time course samples were analysed after short-term storage for up to 240 min and long-term storage for up to 8 days under various storage conditions. As expected, storage at the lowest temperature (-18 °C) exerted the least pronounced effects on the quantified values in both tests. At a higher temperature, polyamines were more stable than amino acids, as evident from polyamine profiling. Addition of ethanol significantly stabilized polyamine profiles even at a higher temperature. Comparative processing of saliva revealed a minor effect of the solvent, whereas drying had a more prominent effect on polyamine profiles. Computational analyses evaluated the ability of polyamines to discriminate pancreatic cancer from controls. Repeated noise added tests were designed on the basis of the results of the storage tests; these analyses confirmed that the discriminative abilities were robust. These data contribute to the standardization of salivary storage conditions, thereby highlighting the clinical utility of saliva.