Identification of Salivary Biomarkers for Oral Cancer Detection with Untargeted and Targeted Quantitative Proteomics Approaches

Lactylome analyses suggest systematic lysine-lactylated substrates in oral squamous cell carcinoma under normoxia and hypoxia

Cancer cells tend to live in hypoxic environment characterized by enhanced glycolysis and accumulation of lactate. Intracellular lactate is shown to drive a novel type of post-translational modification (PTM), lysine lactylation (Kla). Kla has been confirmed to affect the malignant progression of tumors such as hepatocellular carcinoma (HCC) and colon cancer, whereas the global lactylomic profiling of oral squamous cell carcinoma (OSCC) is unclear. Here, the integrative lactylome and proteome analyses by using liquid chromatography-tandem mass spectrometry (LC-MS/MS) identified 1011 Kla sites within 532 proteins and 1197 Kla sites within 608 proteins in SCC25 cells under normoxic and hypoxic environments, respectively. Among these lactylated proteins, histones accounted for only a small fraction, suggesting the presence of Kla modification of OSCC in a large number of non-histone proteins. Notably, Kla preferred to enrich in spliceosome, ribosome and glycolysis/gluconeogenesis pathway in both normoxic and hypoxic cultures. Compared with normoxia, 589 differential proteins with 898 differentially lactylated sites were detected under hypoxia, which were mainly associated with the glycolysis/gluconeogenesis pathway by KEGG analysis. Importantly, we verified the presence of lactylation modification in the spliceosomal proteins hnRNPA1, SF3A1, hnRNPU and SLU7, as well as in glycolytic enzyme PFKP. In addition, the differential alternative splicing analysis described the divergence of pre-mRNA splicing patterns in the presence or absence of sodium lactate and at different oxygen concentrations. Finally, a negative correlation between tissue Kla levels and the prognosis of OSCC patients was revealed by immunohistochemistry. Our study is the first report to elucidate the lactylome and its biological function in OSCC, which deepens our understanding of the mechanisms underlying OSCC progression and provides a novel strategy for targeted therapy for OSCC.

Temporal Assessment of Protein Stability in Dried Blood Spots

The use of protein biomarkers in blood for clinical settings is limited by the cost and accessibility of traditional venipuncture sampling. The dried blood spot (DBS) technique offers a less invasive and more accessible alternative. However, protein stability in DBS has not been well evaluated. Herein, we deployed a quantitative LC-MS/MS system to construct proteomic atlases of whole blood, DBSs, plasma, and blood cells. Approximately 4% of detected proteins' abundance was significantly altered during blood drying into blood spots, with overwhelming disturbances in cytoplasmic fraction. We also reported a novel finding suggesting a decrease in the level of membrane/cytoskeletal proteins (SLC4A1, RHAG, DSC1, DSP, and JUP) and an increase in the level of proteins (ATG3, SEC14L4, and NRBP1) related to intracellular trafficking. Furthermore, we identified 19 temporally dynamic proteins in DBS samples stored at room temperature for up to 6 months. There were three declined cytoskeleton-related proteins (RDX, SH3BGRL3, and MYH9) and four elevated proteins (XPO7, RAN, SLC2A1, and SLC29A1) involved in cytoplasmic transport as representatives. The instability was governed predominantly by hydrophilic proteins and enhanced significantly with an increasing storage time. Our analyses provide comprehensive knowledge of both short- and long-term storage stability of DBS proteins, forming the foundation for the widespread use of DBS in clinical proteomics and other analytical applications.

Fibrinogen and tumors

Elevated plasma fibrinogen (Fg) levels consistently correlate with an unfavorable prognosis in various tumor patient cohorts. Within the tumor microenvironment, aberrant deposition and expression of Fg have been consistently observed, interacting with multiple cellular receptors and thereby accentuating its role as a regulator of inflammatory processes. Specifically, Fg serves to stimulate and recruit immune cells and pro-inflammatory cytokines, thereby contributing to the promotion of tumor progression. Additionally, Fg and its fragments exhibit dichotomous effects on tumor angiogenesis. Notably, Fg also facilitates tumor migration through both platelet-dependent and platelet-independent mechanisms. Recent studies have illuminated several tumor-related signaling pathways influenced by Fg. This review provides a comprehensive summary of the intricate involvement of Fg in tumor biology, elucidating its multifaceted role and the underlying mechanisms.

Nanomaterial Biosensors in Salivary Diagnosis of Oral Cancer: A Scoping Review

Oral cancer is among the highest in the Indian subcontinent. Advanced stages of oral cancer are associated with severe morbidity and higher mortality. Salivary diagnosis is novel and non-invasive. It could be employed on patients even with restricted mouth opening. Hence, an attempt was made to retrieve relevant data regarding this clinically relevant topic.  This article has reviewed metal oxide nanoparticles as a biosensor (BS) in salivary diagnosis for oral cancer. Gold, copper oxide, and carbon nanotubes (CNTs) were used in BS applications. A search from the PUBMED database collection (2004 to 2024) was performed to identify the nanoparticle biomarkers and salivary diagnosis in oral cancer. It revealed 30 articles. All the relevant data was extracted and tabulated in this review. We have discussed the relevance of these BS in salivary diagnosis with their corresponding clinical parameters and sensitivity. We hope that this review summarizes the available literature on this topic and incites dedicated research in prompt and early diagnosis of oral cancer, which directly influences the quality of life outcomes in such patients.

Shaping the future of oral cancer diagnosis: advances in salivary proteomics

INTRODUCTION

Saliva has gained increasing attention in the quest for disease biomarkers. Because it is a biological fluid that can be collected is an easy, painless, and safe way, it has been increasingly studied for the identification of oral cancer biomarkers. This is particularly important because oral cancer is often diagnosed at late stages with a poor prognosis.

AREAS COVERED

The review addresses the evolution of the experimental approaches used in salivary proteomics studies of oral cancer over the years and outlines advantages and pitfalls related to each one. In addition, examines the current landscape of oral cancer biomarker discovery and translation focusing on salivary proteomic studies. This discussion is based on an extensive literature search (PubMed, Scopus and Google Scholar).

EXPERT OPINION

The introduction of mass spectrometry has revolutionized the study of salivary proteomics. In the future, the focus will be on refining existing methods and introducing powerful experimental techniques such as mass spectrometry with selected reaction monitoring, which, despite their effectiveness, are still underutilized due to their high cost. In addition, conducting studies with larger cohorts and establishing standardized protocols for salivary proteomics are key challenges that need to be addressed in the coming years.

Prognostic significance of RKIP, TGM2, and CMTM4 expression in oral squamous cell carcinoma

BACKGROUND

The expression of RKIP, TGM2, and CMTM4 in oral squamous cell carcinoma (OSCC) and normal oral tissues was detected and their correlations were analyzed. The relationships between RKIP, TGM2, and CMTM4 and the clinicopathological parameters and prognosis of patients were analyzed.

METHODS

Seventy cancerous and adjacent normal tissue samples were selected, recorded in the pathology department, and embedded in paraffin. Protein expression was detected by immunohistochemistry. Statistical software (SPSS 25.0, IBM Corporation) was used for the statistical analysis. The chi-squared (χ2) test was used to analyze the expression of RKIP, TGM2, and CMTM4 proteins and their clinicopathological features. Differences in RKIP, TGM2, and CMTM4 protein levels between OSCC and normal tissues were compared using a χ2 test. Survival analysis was performed using the Kaplan-Meier method, and differences between survival curves were determined using the log-rank test. The effects of RKIP, TGM2, and CMTM4 expression on patient prognosis were analyzed using a multivariate Cox proportional hazards regression model. P < .05 was considered statistically significant.

RESULTS

The expression level of RKIP correlated with age and clinical stage (P < .05). TGM2 was associated with clinical stage and lymph node metastasis (P < .05). The expression of CMTM4 increased with a decrease in cancer differentiation. Kaplan-Meier survival analysis suggested that the positive expression of TGM2 and CMTM4 may predict poor prognosis in patients with OSCC. The multivariate Cox proportional hazards regression model suggested that TGM2 could be an independent prognostic factor for patients with OSCC.

CONCLUSION

Combined expression of TGM2 and CMTM4 can be used as an indicator to evaluate the risk of metastasis and prognosis of OSCC.

The human factor H protein family - an update

Complement is an ancient and complex network of the immune system and, as such, it plays vital physiological roles, but it is also involved in numerous pathological processes. The proper regulation of the complement system is important to allow its sufficient and targeted activity without deleterious side-effects. Factor H is a major complement regulator, and together with its splice variant factor H-like protein 1 and the five human factor H-related (FHR) proteins, they have been linked to various diseases. The role of factor H in inhibiting complement activation is well studied, but the function of the FHRs is less characterized. Current evidence supports the main role of the FHRs as enhancers of complement activation and opsonization, i.e., counter-balancing the inhibitory effect of factor H. FHRs emerge as soluble pattern recognition molecules and positive regulators of the complement system. In addition, factor H and some of the FHR proteins were shown to modulate the activity of immune cells, a non-canonical function outside the complement cascade. Recent efforts have intensified to study factor H and the FHRs and develop new tools for the distinction, quantification and functional characterization of members of this protein family. Here, we provide an update and overview on the versatile roles of factor H family proteins, what we know about their biological functions in healthy conditions and in diseases.

Extensive comparison of salivary collection, transportation, preparation, and storage methods: a systematic review

BACKGROUND

Human saliva as a bodily fluid-similar to blood-is utilized for diagnostic purposes. Unlike blood sampling, collecting saliva is non-invasive, inexpensive, and readily accessible. There are no previously published systematic reviews regarding different collection, transportation, preparation, and storage methods for human saliva.

DESIGN

This study has been prepared and organized according to the preferred reporting items for systematic reviews and meta-analyses (PRISMA) 2020 guidelines. This systematic review has been registered at PROSPERO (Registration ID: CRD42023415384). The study question according to the PICO format was as followed: Comparison of the performance (C) of different saliva sampling, handling, transportation, and storage techniques and methods (I) assessed for analyzing stimulated or unstimulated human saliva (P and O). An electronic search was executed in Scopus, Google Scholar, and PubMed.

RESULTS

Twenty-three descriptive human clinical studies published between 1995 and 2022 were included. Eight categories of salivary features and biomarkers were investigated (i.e., salivary flow rate, total saliva quantity, total protein, cortisol, testosterone, DNA quality and quantity, pH and buffering pH). Twenty-two saliva sampling methods/devices were utilized. Passive drooling, Salivette®, and spitting were the most utilized methods. Sampling times with optimum capabilities for cortisol, iodine, and oral cancer metabolites are suggested to be 7:30 AM to 9:00 AM, 10:30 AM to 11:00 AM, and 14:00 PM to 20:00 PM, respectively. There were 6 storage methods. Centrifuging samples and storing them at -70 °C to -80 °C was the most utilized storage method. For DNA quantity and quality, analyzing samples immediately after collection without centrifuging or storage, outperformed centrifuging samples and storing them at -70 °C to -80 °C. Non-coated Salivette® was the most successful method/device for analyzing salivary flow rate.

CONCLUSION

It is highly suggested that scientists take aid from the reported categorized outcomes, and design their study questions based on the current voids for each method/device.

Saliva as a potential non-invasive liquid biopsy for early and easy diagnosis/prognosis of head and neck cancer

Head and neck squamous cell carcinomas (HNSCCs) are the most devastating diseases in India and southeast Asia. It is a preventable and curable disease if detected early. Tobacco and alcohol consumption are the two major risk-factors but infection of high-risk HPVs are also associated with development of predominantly oral and oropharyngeal carcinomas. Interestingly, unlike cervical cancer, HPV-induced HNSCCs show good prognosis and better survival in contrast, majority of tobacco-associated HPV-ve HNSCCs are highly aggressive with poor clinical outcome. Biomarker analysis in circulatory body-fluids for early cancer diagnosis, prognosis and treatment monitoring are becoming important in clinical practice. Early diagnosis using non-invasive saliva for oral or other diseases plays an important role in successful treatment and better prognosis. Saliva mirrors the body's state of health as it comes into direct contact with oral lesions and needs no trained manpower to collect, making it a suitable bio-fluid of choice for screening. Saliva can be used to detect not only virus, bacteria and other biomarkers but variety of molecular and genetic markers for an early detection, treatment and monitoring cancer and other diseases. The performance of saliva-based diagnostics are reported to be highly (≥95 %) sensitive and specific indicating the test's ability to correctly identify true positive or negative cases. This review focuses on the potentials of saliva in the early detection of not only HPV or other pathogens but also identification of highly reliable gene mutations, oral-microbiomes, metabolites, salivary cytokines, non-coding RNAs and exosomal miRNAs. It also discusses the importance of saliva as a reliable, cost-effective and an easy alternative to invasive procedures.

Emerging histological and serological biomarkers in oral squamous cell carcinoma: Applications in diagnosis, prognosis evaluation and personalized therapeutics (Review)

Oral squamous cell carcinoma (OSCC) is the most common malignancy of the oral cavity and accounts for >90% of all oral cancers. Despite advances in diagnostic procedures and therapeutic interventions, overall survival has not improved significantly in recent decades, primarily due to late diagnosis, locoregional recurrence and treatment resistance. Identifying reliable biomarkers for early detection, prognosis evaluation and treatment response prediction is critical for improving clinical outcomes in patients with OSCC. In the present review, the prognostic and predictive utility of circulating biomarkers, such as circulating tumour cells, serological biomarkers and histological and genetic biomarkers, were explored in the context of OSCC. In addition, the potential role of immune checkpoints in the treatment of OSCC was highlighted and the rapidly evolving field of liquid biopsy and its potential to revolutionize diagnosis, prognosis evaluation and treatment were examined. The existing evidence for the clinical utility of these biomarkers was critically evaluated and the challenges and limitations associated with their introduction into routine clinical practice were addressed. In conclusion, the present review highlights the promising role of biomarkers in improving the current understanding of the pathogenesis of OSCC and offers potential avenues for improving patient care through personalized medicine approaches.

Association between salivary proteases and protease inhibitors linked with viral infections and oral inflammatory diseases

INTRODUCTION

Despite the role of transmembrane protease, serine 2 (TMPRSS2) in facilitating the entry of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the primary cause of the global COVID-19 pandemic, the interaction of extracellular and intracellular proteases in this process remains poorly elucidated. Thus, we monitored the salivary expression concentration (SEC) of TMPRSS2 and its inhibitor, alpha-1 antitrypsin (A1AT), and investigated whether oral inflammatory diseases affected the SEC of both proteins.

MATERIALS AND METHODS

We collected saliva samples before and after surgical treatment of inflammatory cystic diseases (radicular and inflammatory dentigerous cysts) in 25 patients. The SEC of TMPRSS2 and A1AT was measured using enzyme-linked immunosorbent assay. SEC in multiple patient status groups and subgroups of each status were investigated. Finally, the correlation between TMPRSS2 and A1AT SEC was analyzed.

RESULTS

The TMPRSS2 and A1AT SEC did not significantly change pre- or post-treatment. The TMPRSS2 SEC was significantly higher before and after treatment in patients aged >50 years, patients with radicular cysts, and patients with the basic disease. A1AT SEC was significantly decreased after treatment in the acute inflammation, large-sized, and patients without basic disease groups. No significant correlation was observed between the SEC of either protein before and after treatment.

DISCUSSION

Individual-specific SEC for TMPRSS2 may be influenced by age, lesion type, and basic disease; however, oral inflammatory diseases may not have a direct effect. Moreover, the extent of oral inflammatory diseases and the presence of basic diseases may be associated with A1AT SEC. Furthermore, the SEC between the two proteins may be independent.

Targeted protein quantitation in human body fluids by mass spectrometry

Human body fluids (biofluids) contain various proteins, some of which reflect individuals' physiological conditions or predict diseases. Therefore, the analysis of biofluids can provide substantial information on novel biomarkers for clinical diagnosis and prognosis. In the past decades, mass spectrometry (MS)-based technologies have been developed as proteomic strategies not only for the identification of protein biomarkers but also for biomarker verification/validation in body fluids for clinical applications. The main advantage of targeted MS-based methodologies is the accurate and specific simultaneous quantitation of multiple biomarkers with high sensitivity. Here, we review MS-based methodologies that are currently used for the targeted quantitation of protein components in human body fluids, especially in plasma, urine, cerebrospinal fluid, and saliva. In addition, the currently used MS-based methodologies are summarized with a specific focus on applicable clinical sample types, MS configurations, and acquisition modes.

Saliva biomarkers in oral disease

Saliva is a versatile biofluid that contains a wide variety of biomarkers reflecting both physiologic and pathophysiologic states. Saliva collection is noninvasive and highly applicable for tests requiring serial sampling. Furthermore, advances in test accuracy, sensitivity and precision for saliva has improved diagnostic performance as well as the identification of novel markers especially in oral disease processes. These include dental caries, periodontitis, oral squamous cell carcinoma (OSCC) and Sjögren's syndrome (SS). Numerous growth factors, enzymes, interleukins and cytokines have been identified and are the subject of much research investigation. This review highlights current procedures for successful determination of saliva biomarkers including preanalytical factors associated with sampling, storage and pretreatment as well as subsequent analysis. Moreover, it provides an overview of the diagnostic applications of these salivary biomarkers in common oral diseases.

A new method for oral cancer biomarkers detection with a non-invasive cyto-salivary sampling and rapid-highly sensitive ELISA immunoassay: a pilot study in humans

Introduction

Oral squamous cell carcinoma (OSCC) accounts for approximately 90% of oral malignancies and has a 5-year mortality rate close to 50%. A consistent part (70%) of all oral cancers is diagnosed at an advanced stage since available screening techniques are ineffective. Therefore, it would be urgent to improve them. The diagnostic gold standard is tissue biopsy with histological and immunohistochemical assessment. This method presents some limitations. Biopsy is invasive and the histopathological evaluation is semi-quantitative, and the absolute abundance of the target cannot be reliably determined. In addition, tissue is highly processed and may lead to loss of information of the natural state. The search for classical and new clinical biomarkers on fragments of tissue/cells collected with a cytobrush is a highly hopeful technique for early detection and diagnosis of OSCC, because of its non-invasive sampling and easy collection method.

Methods

Here we analyzed cytobrush biopsies samples collected from the oral cavity of 15 patients with already diagnosed OSCC by applying an innovative high-sensitivity ELISA technique, in order to verify if this approach may provide useful information for detection, diagnosis, and prognosis of OSCC. To this end, we selected six biomarkers, already used in clinical practice for the diagnosis of OSCC (EGFR, Ki67, p53) or selected based on recent scientific and clinical data which indicate their presence or over-expression in cells undergoing transformation and their role as possible molecular targets in immunecheckpoints blockade therapies (PD-L1, HLA-E, B7-H6).

Results

The selected tumor biomarkers were highly expressed in the tumor core, while were virtually negative in healthy tissue collected from the same patients. These differences were highly statistically significant and consistent with those obtained using the gold standard test clearly indicating that the proposed approach, i.e. analysis of biomarkers by a custom ELISA technique, is strongly reliable.

Discussion

These preliminary data suggest that this non-invasive rapid phenotyping technique could be useful as a screening tool for phenotyping oral lesions and support clinical practice by precise indications on the characteristics of the lesion, also with a view to the application of new anti-tumor treatments, such as immunotherapy, aimed at OSCC patients.

Proteomic Characterization of SAS Cell-Derived Extracellular Vesicles in Relation to Both BPA and Neutron Irradiation Doses

Boron neutron capture therapy (BNCT) is a selective radiotherapy based on nuclear reaction that occurs when ¹⁰B atoms accumulated in cancer cells are irradiated by thermal neutrons, triggering a nuclear fission response leading to cell death. Despite its growing importance in cancer treatment, molecular characterization of its effects is still lacking. In this context, proteomics investigation can be useful to study BNCT effect and identify potential biomarkers. Hence, we performed proteomic analysis with nanoLC-MS/MS (liquid chromatography coupled to tandem mass spectrometry) on extracellular vesicles (EVs) isolated from SAS cultures treated or not with ¹⁰B-boronophenylalanine (BPA) and different doses of neutron irradiation, to study the cellular response related to both boron administration and neutrons action. Despite the interference of fetal bovine serum in the medium, we were able to stratify BPA- and BPA+ conditions and to identify EVs-derived proteins characterizing pathways potentially related to a BNCT effect such as apoptosis, DNA repair and inflammatory response. In particular, KLF11, SERPINA1 and SERPINF2 were up-regulated in BPA+, while POLE and SERPINC1 were up-regulated in BPA-. These results provide the first proteomic investigation of EVs treated with BNCT in different conditions and highlight the potentiality of proteomics for improving biomarkers identification and mechanisms understanding of BNCT.

Proteomic and phosphoproteomic landscape of salivary extracellular vesicles to assess OSCC therapeutical outcomes

Circulating extracellular vesicles (EVs) have emerged as an appealing source for surrogates to evaluate the disease status. Herein, we present a novel proteomic strategy to identify proteins and phosphoproteins from salivary EVs to distinguish oral squamous cell carcinoma (OSCC) patients from healthy individuals and explore the feasibility to evaluate therapeutical outcomes. Bi-functionalized magnetic beads (BiMBs) with Ti (IV) ions and a lipid analog, 1,2-Distearoyl-3-sn-glycerophosphoethanolamine (DSPE) are developed to efficiently isolate EVs from small volume of saliva. In the discovery stage, label-free proteomics and phosphoproteomics quantification showed 315 upregulated proteins and 132 upregulated phosphoproteins in OSCC patients among more than 2500 EV proteins and 1000 EV phosphoproteins, respectively. We further applied targeted proteomics by coupling parallel reaction monitoring with parallel accumulation-serial fragmentation (prm-PASEF) to measure panels of proteins and phosphoproteins from salivary EVs collected before and after surgical resection. A panel of three total proteins and three phosphoproteins, most of which have previously been associated with OSCC and other cancer types, show sensitive response to the therapy in individual patients. Our study presents a novel strategy to the discovery of effective biomarkers for non-invasive assessment of OSCC surgical outcomes with small amount of saliva.

Saliva - a new opportunity for fluid biopsy

Saliva is a complex biological fluid with a variety of biomolecules, such as DNA, RNA, proteins, metabolites and microbiota, which can be used for the screening and diagnosis of many diseases. In addition, saliva has the characteristics of simple collection, non-invasive and convenient storage, which gives it the potential to replace blood as a new main body of fluid biopsy, and it is an excellent biological diagnostic fluid. This review integrates recent studies and summarizes the research contents of salivaomics and the research progress of saliva in early diagnosis of oral and systemic diseases. This review aims to explore the value and prospect of saliva diagnosis in clinical application.

Understanding metabolic alterations after SARS-CoV-2 infection: insights from the patients' oral microenvironmental metabolites

BACKGROUND

Coronavirus disease 2019 is a type of acute infectious pneumonia and frequently confused with influenza since the initial symptoms. When the virus colonized the patient's mouth, it will cause changes of the oral microenvironment. However, few studies on the alterations of metabolism of the oral microenvironment affected by SARS-CoV-2 infection have been reported. In this study, we explored metabolic alterations of oral microenvironment after SARS-CoV-2 infection.

METHODS

Untargeted metabolomics (UPLC-MS) was used to investigate the metabolic changes between oral secretion samples of 25 COVID-19 and 30 control participants. To obtain the specific metabolic changes of COVID-19, we selected 25 influenza patients to exclude the metabolic changes caused by the stress response of the immune system to the virus. Multivariate analysis (PCA and PLS-DA plots) and univariate analysis (students' t-test) were used to compare the differences between COVID-19 patients and the controls. Online hiplot tool was used to perform heatmap analysis. Metabolic pathway analysis was conducted by using the MetaboAnalyst 5.0 web application.

RESULTS

PLS-DA plots showed significant separation of COVID-19 patients and the controls. A total of 45 differential metabolites between COVID-19 and control group were identified. Among them, 35 metabolites were defined as SARS-CoV-2 specific differential metabolites. Especially, the levels of cis-5,8,11,14,17-eicosapentaenoic acid and hexanoic acid changed dramatically based on the FC values. Pathway enrichment found the most significant pathways were tyrosine-related metabolism. Further, we found 10 differential metabolites caused by the virus indicating the body's metabolism changes after viral stimulation. Moreover, adenine and adenosine were defined as influenza virus-specific differential metabolites.

CONCLUSIONS

This study revealed that 35 metabolites and tyrosine-related metabolism pathways were significantly changed after SARS-CoV-2 infection. The metabolic alterations of oral microenvironment in COVID-19 provided new insights into its molecular mechanisms for research and prognostic treatment.

Promising applications of human-derived saliva biomarker testing in clinical diagnostics

Saliva testing is a vital method for clinical applications, for its noninvasive features, richness in substances, and the huge amount. Due to its direct anatomical connection with oral, digestive, and endocrine systems, clinical usage of saliva testing for these diseases is promising. Furthermore, for other diseases that seeming to have no correlations with saliva, such as neurodegenerative diseases and psychological diseases, researchers also reckon saliva informative. Tremendous papers are being produced in this field. Updated summaries of recent literature give newcomers a shortcut to have a grasp of this topic. Here, we focused on recent research about saliva biomarkers that are derived from humans, not from other organisms. The review mostly addresses the proceedings from 2016 to 2022, to shed light on the promising usage of saliva testing in clinical diagnostics. We recap the recent advances following the category of different types of biomarkers, such as intracellular DNA, RNA, proteins and intercellular exosomes, cell-free DNA, to give a comprehensive impression of saliva biomarker testing.

Towards multiomic analysis of oral mucosal pathologies

Oral mucosal pathologies comprise an array of diseases with worldwide prevalence and medical relevance. Affecting a confined space with crucial physiological and social functions, oral pathologies can be mutilating and drastically reduce quality of life. Despite their relevance, treatment for these diseases is often far from curative and remains vastly understudied. While multiple factors are involved in the pathogenesis of oral mucosal pathologies, the host's immune system plays a major role in the development, maintenance, and resolution of these diseases. Consequently, a precise understanding of immunological mechanisms implicated in oral mucosal pathologies is critical (1) to identify accurate, mechanistic biomarkers of clinical outcomes; (2) to develop targeted immunotherapeutic strategies; and (3) to individualize prevention and treatment approaches. Here, we review key elements of the immune system's role in oral mucosal pathologies that hold promise to overcome limitations in current diagnostic and therapeutic approaches. We emphasize recent and ongoing multiomic and single-cell approaches that enable an integrative view of these pathophysiological processes and thereby provide unifying and clinically relevant biological signatures.

The Use of Salivary Levels of Matrix Metalloproteinases as an Adjuvant Method in the Early Diagnosis of Oral Squamous Cell Carcinoma: A Narrative Literature Review

Oral squamous cell carcinoma (OSCC) is an aggressive malignancy with increased mortality, in which the early diagnosis is the most important step in increasing patients' survival rate. Extensive research has evaluated the role of saliva as a source of diagnostic biomarkers, among which matrix metalloproteinases (MMPs) have shown a valuable potential for detecting even early stages of OSCC. The aim of this review was to present recent clinical data regarding the significance of salivary MMPs in the detection of early malignant transformation of the oral mucosa. A narrative review was conducted on articles published in PubMed, Cochrane Library, Web of Science, EBSCO and SciELO databases, using specific terms. Our search revealed that MMP-1, MMP-2, MMP-3, MMP-8, MMP-9, MMP-10, MMP-12 and MMP-13 had significantly higher levels in saliva from patients with OSCC compared to controls. However, the strength of evidence is limited, as most information regarding their use as adjuvant diagnostic tools for OSCC comes from studies with a low number of participants, variable methodologies for saliva sampling and diagnostic assays, and insufficient adjustment for all covariates. MMP-1, MMP-3 and MMP-9 were considered the most promising candidates for salivary diagnosis of OSCC, but larger studies are needed in order to validate their clinical application.

Development of a salivary autoantibody biomarker panel for diagnosis of oral cavity squamous cell carcinoma

Oral cavity squamous cell carcinoma (OSCC) is a destructive disease with increasing incidence. OSCC is usually diagnosed at an advanced stage, which leads to poor outcomes of OSCC patients. Currently, there is a lack of biomarkers with sufficient effectiveness in early diagnosis of OSCC. To ameliorate OSCC screening, we evaluated the performances of salivary autoantibodies (auto-Abs) to nine proteins (ANXA2, CA2, ISG15, KNG1, MMP1, MMP3, PRDX2, SPARC, and HSPA5) as OSCC biomarkers. A multiplexed immunoassay using a fluorescence bead-based suspension array system was established for simultaneous assessment of the salivary levels of the above nine auto-Abs and a known OSCC-associated auto-Ab, anti-p53. Compared to healthy individuals (n = 140), the salivary levels of nine auto-Abs were significantly elevated in OSCC patients (n = 160). Notably, the salivary levels of the 10 auto-Abs in the early-stage OSCC patients (n = 102) were higher than that in the healthy group. Most importantly, utilizing a marker panel consisting of anti-MMP3, anti-PRDX2, anti-SPARC, and anti-HSPA5 for detection of early-stage OSCC achieved a sensitivity of 63.8% with a specificity of 90%. Collectively, herein we established a multiplex auto-Ab platform for OSCC screening, and demonstrated a four-auto-Ab panel which shows clinical applicability for early diagnosis of OSCC.

Liquid Biopsy and Circulating Biomarkers for the Diagnosis of Precancerous and Cancerous Oral Lesions

Oral cancer is one of the most common malignancies worldwide, accounting for 2% of all cases annually and 1.8% of all cancer deaths. To date, tissue biopsy and histopathological analyses are the gold standard methods for the diagnosis of oral cancers. However, oral cancer is generally diagnosed at advanced stages with a consequent poor 5-year survival (~50%) due to limited screening programs and inefficient physical examination strategies. To address these limitations, liquid biopsy is recently emerging as a novel minimally invasive tool for the early identification of tumors as well as for the evaluation of tumor heterogeneity and prognosis of patients. Several studies have demonstrated that liquid biopsy in oral cancer could be useful for the detection of circulating biomarkers including circulating tumor DNA (ctDNA), microRNAs (miRNAs), proteins, and exosomes, thus improving diagnostic strategies and paving the way to personalized medicine. However, the application of liquid biopsy in oral cancer is still limited and further studies are needed to better clarify its clinical impact. The present manuscript aims to provide an updated overview of the potential use of liquid biopsy as an additional tool for the management of oral lesions by describing the available methodologies and the most promising biomarkers.

The metabolomic landscape plays a critical role in glioma oncogenesis

Cancer cells depend on metabolic reprogramming for survival, undergoing profound shifts in nutrient sensing, nutrient uptake and flux through anabolic pathways, in order to drive nucleotide, lipid, and protein synthesis and provide key intermediates needed for those pathways. Although metabolic enzymes themselves can be mutated, including to generate oncometabolites, this is a relatively rare event in cancer. Usually, gene amplification, overexpression, and/or downstream signal transduction upregulate rate‐limiting metabolic enzymes and limit feedback loops, to drive persistent tumor growth. Recent molecular‐genetic advances have revealed discrete links between oncogenotypes and the resultant metabolic phenotypes. However, more comprehensive approaches are needed to unravel the dynamic spatio‐temporal regulatory map of enzymes and metabolites that enable cancer cells to adapt to their microenvironment to maximize tumor growth. Proteomic and metabolomic analyses are powerful tools for analyzing a repertoire of metabolic enzymes as well as intermediary metabolites, and in conjunction with other omics approaches could provide critical information in this regard. Here, we provide an overview of cancer metabolism, especially from an omics perspective and with a particular focus on the genomically well characterized malignant brain tumor, glioblastoma. We further discuss how metabolomics could be leveraged to improve the management of patients, by linking cancer cell genotype, epigenotype, and phenotype through metabolic reprogramming.

Secreted protein markers in oral squamous cell carcinoma (OSCC)

Background

Oral squamous cell carcinoma (OSCC) is a main cause of oral cancer mortality and morbidity in central south Asia. To improve the clinical outcome of OSCC patients, detection markers are needed, which are preferably non-invasive and thus independent of a tissue biopsy.

Methods

In the present study, we aimed to identify robust candidate protein biomarkers for non-invasive OSCC diagnosis. To this end, we measured the global protein profiles of OSCC tissue lysates to matched normal adjacent mucosa samples (n = 14) and the secretomes of nine HNSCC cell lines using LC–MS/MS-based proteomics.

Results

A total of 5123 tissue proteins were identified, of which 205 were robustly up- regulated (p-value < 0.01, fold change > + 2) in OSCC-tissues compared to normal adjacent tissues. The biological process “Secretion” was highly enriched in this set of proteins. Other upregulated biological pathways included “Unfolded Protein Response”, “Spliceosomal complex assembly”, “Protein localization to endosome” and “Interferon Gamma Response”. Transcription factor analysis implicated Creb3L1, ESRRA, YY, ELF2, STAT1 and XBP as potential regulators. Of the 205 upregulated tissue proteins, 132 were identified in the cancer cell line secretomes, underscoring their potential use as non-invasive biofluid markers. To further prioritize our candidate markers for non-invasive OSCC detection, we integrated our data with public biofluid datasets including OSCC saliva, yielding 25 candidate markers for further study.

Conclusions

We identified several key proteins and processes that are associated with OSCC tissues, underscoring the importance of altered secretion. Cancer-associated OSCC secretome proteins present in saliva have potential to be used as novel non-invasive biomarkers for the diagnosis of OSCC.

Graphical Abstract

Supplementary Information

The online version contains supplementary material available at 10.1186/s12014-022-09341-5.

Metabolomic Analysis Reveals Potential Biomarkers and the Underlying Pathogenesis Involved in Mycoplasma Pneumoniae Pneumonia

Although previous studies have reported the use of metabolomics for infectious diseases, little is known about the potential function of plasma metabolites in children infected with Mycoplasma pneumoniae (MP). Here, a combination of liquid chromatography-quadrupole time-of-flight mass spectrometry and random forest-based classification model was used to provide a broader range of applications in MP diagnosis. In the training cohort, plasma from 63 MP pneumonia children (MPPs), 37 healthy controls (HC) and 29 infectious disease controls (IDC) was collected. After multivariate analyses, 357 metabolites were identified to be differentially expressed among MPP, HC and IDC groups, and 3 metabolites (568.5661, 459.3493 and 411.3208) had high diagnostic values. In an independent cohort with 57 blinded subjects, samples were successfully classified into different groups, demonstrating the reliability of these biomarkers for distinguishing MPPs from controls. A metabolomic signature analysis identified major classes of glycerophospholipids, sphingolipids and fatty acyls were increased in MPPs. These markedly altered metabolites are mainly involved in glycerophospholipid and sphingolipid metabolism. As the ubiquitous building blocks of eukaryotic cell membranes, dysregulated lipid metabolism indicates damage of the cellular membrane and the activation of immunity in MPPs. Moreover, lipid metabolites, differentially expressed between severe and mild MPPs, were correlated with the markers of extrapulmonary complications, suggesting that they may be involved in MPP disease severity. These findings may offer new insights into biomarker selection and the pathogenesis of MPP in children.

Identification of maternal serum biomarkers for prenatal diagnosis of nonsyndromic orofacial clefts

Nonsyndromic orofacial clefts (NSOFCs) are the most common congenital defects in the oral and maxillofacial regions. It is mainly diagnosed prenatally through fetal ultrasonography. However, the accuracy of ultrasonography for NSOFC is unreliable. Maternal serological screening is a noninvasive method for the diagnosis of fetal malformations. In our study, we sought to identify specific biomarkers in maternal serum for predicting NSOFC prenatally. We quantified the alterations in maternal serum protein profiles between 20 pregnant women with NSOFC fetuses and 20 pregnant women with healthy fetuses by using isobaric tags for relative and absolute quantitation-based mass spectrometry (MS). The serum levels of 75 elevated and 50 decreased proteins in the NSOFC group were detected. Twenty-eight candidate biomarkers were selected for further confirmation by multiple reaction monitoring-MS; of these, 16 proteins were found to be significantly different. More importantly, the levels of three proteins (APOA, HPT, and CRP) were verified by ELISAs to be obviously altered in serum from pregnancies carrying fetuses with NSOFC. Our results indicate that analysis of the maternal serum proteome is a feasible strategy for biomarker discovery of NSOFC, and APOA, HPT, and CRP proteins are potential serum biomarkers for prenatal diagnosis of NSOFC.

Advancements in diagnostic techniques for oral cancer detection

Oral malignancy is among the highest prevalent malignancies all over the world. In comparison to systemic malignancies such as lung cancer and colon cancer, they are frequently overlooked by the general public. Nevertheless, they can be exceedingly lethal if left ignored, regardless at the early stage of the condition. Dentists are the finest qualified healthcare specialists in this sector and are responsible for detecting benign and potentially malignant oral conditions such as oral cancers. Oral carcinoma's high prevalence and delayed appearance are serious international medical concerns. Early detection and management of oral carcinoma are the key goals of the World Health Organization (WHO). The identification of key clinical manifestations during the preliminary oral examination can enhance the patient's likelihood of living. Unfortunately, the conventional technology's practical value is limited by a number of drawbacks. Current advancements in optical scanning techniques, such as tissue-fluorescence imaging and optical coherence tomography, have proven to be quite effective. In particular, nanoparticle-based immunosensors, genomics, and salivary biomarkers, epigenetics and microarray have all received a lot of attention. Raising awareness about frequent dental examinations and using noninvasive, effective, and cost-effective screening tools would improve initial stage detection of oral carcinoma and improve patients' longevity.

Label-free quantitation of the changes in salivary proteome associated with the chronic consumption of the betel nut (Areca catechu)

Areca nut or betel nut chewing is most frequently used in Pakistan and is associated with a high risk for oral cancer. Until now, however, there has not been any research conducted on the long-term effect(s) of betel nut chewing on the saliva proteome. In the present study, initially, the changes in the saliva proteome associated with betel nut chewing were investigated. Secondly, the analysis was focused on the changes in salivary proteome with respect to prolonged usage of betel nuts. After extraction, the saliva proteins were digested into peptides and these were subsequently analyzed using mass spectrometry. Data are available via ProteomeXchange with identifier PXD029768. Label-free quantitation of saliva samples revealed a total of 12 proteins that were differentially expressed between betel nut addicts (BNAs), and the control group. The study groups were further divided into three subgroups, the BNA-1, BNA-2, and BNA-3 groups, with respect to the extent of consumption of betel nuts in terms of years. The data analysis revealed a more detailed profiling of proteins expressed after five, ten, and more than ten years of betel nut consumption. A total of 30, 17, and 22 proteins were found to be differentially expressed when divided into the BNA-1, BNA-2, and BNA-3 groups. The present study shows that the chronic usage of betel nuts leads to the expression of proteins, such as SPARC1, profilin, and SBSN, which are known to be involved in head and neck cancers.

A systematic review of proteomic biomarkers in oral squamous cell cancer

BACKGROUND

Head and neck squamous cell cancer (HNSCC) is the most common cancer associated with chewing tobacco, in the world. As this is divided in to sites and subsites, it does not make it to top 10 cancers. The most common subsite is the oral cancer. At the time of diagnosis, more than 50% of patients with oral squamous cell cancers (OSCC) had advanced disease, indicating the lack of availability of early detection and risk assessment biomarkers. The new protein biomarker development and discovery will aid in early diagnosis and treatment which lead to targeted treatment and ultimately a good prognosis.

METHODS

This systematic review was performed as per PRISMA guidelines. All relevant studies assessing characteristics of oral cancer and proteomics were considered for analysis. Only human studies published in English were included, and abstracts, incomplete articles, and cell line or animal studies were excluded.

RESULTS

A total of 308 articles were found, of which 112 were found to be relevant after exclusion. The present review focuses on techniques of cancer proteomics and discovery of biomarkers using these techniques. The signature of protein expression may be used to predict drug response and clinical course of disease and could be used to individualize therapy with such knowledge.

CONCLUSIONS

Prospective use of these markers in the clinical setting will enable early detection, prediction of response to treatment, improvement in treatment selection, and early detection of tumor recurrence for disease monitoring. However, most of these markers for OSCC are yet to be validated.

Identification and validation of potential novel biomarkers for oral squamous cell carcinoma

Our study aimed to explore potential new diagnostic biomarkers in patients with oral squamous cell carcinoma (OSCC) to find new target molecules involved in the progression of OSCC. Potential novel biomarkers of OSCC were identified using a protein microarray assay. Compared with the healthy control group, there were five proteins (I309, GDF15, AXL, MMP3, and CTACK) in the serum of in situ oral cancer group. However, there were four differentially expressed proteins (MCSF, I309, MMP3, and CTACK) in the serum of the OSCC group. Receiver operating characteristic (ROC) curve analysis results suggested that these six proteins (I309, GDF15, AXL, MMP3, CTACK, and MCSF) had diagnostic value for OSCC. Based on The Cancer Genome Atlas (TCGA) database, we found that only GDF15 expression was associated with the prognosis of OSCC. Subsequently, we verified the expression levels of six proteins in HSC-3 and HaCaT cells, and the results showed that the level of these six proteins was significantly higher in HSC-3 cells than in normal HaCaT cells. Similarly, in the OSCC nude mouse model, the expression levels of these proteins were significantly upregulated in OSCC tumor tissue compared to the normal tissue. GDF15, MMP3, AXL, MCSF, I309, and CTACK may be used as biomarkers for OSCC diagnosis and provide a novel study direction for the treatment of OSCC.

The role of proteomics in the multiplexed analysis of gene alterations in human cancer

INTRODUCTION

Proteomics has played a pivotal role in identifying proteins perturbed in disease conditions when compared with healthy samples. Study of dysregulated proteins aids in identifying diagnostic markers and potential therapeutic targets. Cancer is an outcome of interplay of several such disarrayed proteins and molecular pathways which perturb cellular homeostasis, resulting in transformation. In this review, we discuss various facets of proteomic approaches, including tools and technological advancements, aiding in understanding differentially expressed molecules and signaling mechanisms.

AREAS COVERED

In this review, we have taken the approach of documenting the different methods of proteomic studies, ranging from labeling techniques, data analysis methods, and the nature of molecule detected. We summarize each technique and provide a glimpse of cancer research carried out using them, highlighting the advantages and drawbacks in comparison with others. Literature search using online resources, such as PubMed and Google Scholar were carried out for this approach.

EXPERT OPINION

Technological advancements in proteomics studies have come a long way from the study of two-dimensional mapping of proteins separated on gels in the early 1970s. Higher precision in molecular identification and quantification (high throughput), and greater number of samples analyzed have been the focus of researchers.

Dark Side of Cancer Therapy: Cancer Treatment-Induced Cardiopulmonary Inflammation, Fibrosis, and Immune Modulation

Advancements in cancer therapy increased the cancer free survival rates and reduced the malignant related deaths. Therapeutic options for patients with thoracic cancers include surgical intervention and the application of chemotherapy with ionizing radiation. Despite these advances, cancer therapy-related cardiopulmonary dysfunction (CTRCPD) is one of the most undesirable side effects of cancer therapy and leads to limitations to cancer treatment. Chemoradiation therapy or immunotherapy promote acute and chronic cardiopulmonary damage by inducing reactive oxygen species, DNA damage, inflammation, fibrosis, deregulation of cellular immunity, cardiopulmonary failure, and non-malignant related deaths among cancer-free patients who received cancer therapy. CTRCPD is a complex entity with multiple factors involved in this pathogenesis. Although the mechanisms of cancer therapy-induced toxicities are multifactorial, damage to the cardiac and pulmonary tissue as well as subsequent fibrosis and organ failure seem to be the underlying events. The available biomarkers and treatment options are not sufficient and efficient to detect cancer therapy-induced early asymptomatic cell fate cardiopulmonary toxicity. Therefore, application of cutting-edge multi-omics technology, such us whole-exome sequencing, DNA methylation, whole-genome sequencing, metabolomics, protein mass spectrometry and single cell transcriptomics, and 10 X spatial genomics, are warranted to identify early and late toxicity, inflammation-induced carcinogenesis response biomarkers, and cancer relapse response biomarkers. In this review, we summarize the current state of knowledge on cancer therapy-induced cardiopulmonary complications and our current understanding of the pathological and molecular consequences of cancer therapy-induced cardiopulmonary fibrosis, inflammation, immune suppression, and tumor recurrence, and possible treatment options for cancer therapy-induced cardiopulmonary toxicity.

The role of SPP1 as a prognostic biomarker and therapeutic target in head and neck squamous cell carcinoma

Head and neck squamous cell carcinoma (HNSCC) is one of the most common malignancies and has a low 5-year survival rate. Mounting evidence suggests that oral potentially malignant disorders, such as oral leukoplakia (OLK), may progress to HNSCC. Given that OLK and HNSCC are often insidious and asymptomatic, the identification of markers of OLK malignant transformation and therapeutic targets in HNSCC is critical. Using various online tools and publicly available gene expression datasets, the secreted phosphoprotein 1 gene (SPP1) was identified as a significant differentially expressed gene among OLK, HNSCC, and non-cancerous tissues. SPP1 mRNA levels were elevated in HNSCC tissues and were associated with cancer stage, tumor grade, and human papillomavirus infection status. High SPP1 mRNA levels were correlated with poor overall survival of HNSCC patients. In contrast, SPP1 mutations were not significantly associated with overall survival, although their frequency in HNSCC was very low (0.6%). Furthermore, SPP1 expression levels in HNSCC were positively correlated with the infiltration of CD4⁺ cells, macrophages, neutrophils, and dendritic cells. The study results suggest that SPP1 may represent a diagnostic and prognostic biomarker, as well as a potential therapeutic target in HNSCC.

SecProCT: In Silico Prediction of Human Secretory Proteins Based on Capsule Network and Transformer

Identifying secretory proteins from blood, saliva or other body fluids has become an effective method of diagnosing diseases. Existing secretory protein prediction methods are mainly based on conventional machine learning algorithms and are highly dependent on the feature set from the protein. In this article, we propose a deep learning model based on the capsule network and transformer architecture, SecProCT, to predict secretory proteins using only amino acid sequences. The proposed model was validated using cross-validation and achieved 0.921 and 0.892 accuracy for predicting blood-secretory proteins and saliva-secretory proteins, respectively. Meanwhile, the proposed model was validated on an independent test set and achieved 0.917 and 0.905 accuracy for predicting blood-secretory proteins and saliva-secretory proteins, respectively, which are better than conventional machine learning methods and other deep learning methods for biological sequence analysis. The main contributions of this article are as follows: (1) a deep learning model based on a capsule network and transformer architecture is proposed for predicting secretory proteins. The results of this model are better than the those of existing conventional machine learning methods and deep learning methods for biological sequence analysis; (2) only amino acid sequences are used in the proposed model, which overcomes the high dependence of existing methods on the annotated protein features; (3) the proposed model can accurately predict most experimentally verified secretory proteins and cancer protein biomarkers in blood and saliva.

Saliva, a bodily fluid with recognized and potential diagnostic applications

Human whole saliva is a bodily fluid that can be obtained easily by noninvasive techniques. Specimens can be collected by the patient also at home in order to monitor health status and variations of several analytes of clinical interest. The contributions to whole saliva include secretions from salivary glands and, among others, from the gingival crevicular fluid that derives from the epithelial mucosa. Therefore, saliva is currently a relevant diagnostic fluid for many substances, including steroids, nonpeptide hormones, therapeutic drugs, and drugs of abuse. This review at first briefly describes the different contributions to whole saliva. A section illustrates the procedures for the collection, handling, and storage of salivary specimens. Another section describes the present use of whole saliva for diagnostic purposes and its specific utilization for the diagnosis of several local and systemic diseases. The final sections illustrate the future opportunities offered by various not conventional techniques with a focus on the most recent –omic investigations. It describes the various issues that have to be taken into account to avoid false positives and negatives, such as the strength of the experimental plan, the adequacy of the number of samples under study, and the proper choice of controls.

Clinical Proteomics of Biofluids in Haematological Malignancies

Since the emergence of high-throughput proteomic techniques and advances in clinical technologies, there has been a steady rise in the number of cancer-associated diagnostic, prognostic, and predictive biomarkers being identified and translated into clinical use. The characterisation of biofluids has become a core objective for many proteomic researchers in order to detect disease-associated protein biomarkers in a minimally invasive manner. The proteomes of biofluids, including serum, saliva, cerebrospinal fluid, and urine, are highly dynamic with protein abundance fluctuating depending on the physiological and/or pathophysiological context. Improvements in mass-spectrometric technologies have facilitated the in-depth characterisation of biofluid proteomes which are now considered hosts of a wide array of clinically relevant biomarkers. Promising efforts are being made in the field of biomarker diagnostics for haematologic malignancies. Several serum and urine-based biomarkers such as free light chains, β-microglobulin, and lactate dehydrogenase are quantified as part of the clinical assessment of haematological malignancies. However, novel, minimally invasive proteomic markers are required to aid diagnosis and prognosis and to monitor therapeutic response and minimal residual disease. This review focuses on biofluids as a promising source of proteomic biomarkers in haematologic malignancies and a key component of future diagnostic, prognostic, and disease-monitoring applications.

Salivary Cytokines as Biomarkers for Oral Squamous Cell Carcinoma: A Systematic Review

The prognosis of patients with oral squamous carcinoma (OSCC) largely depends on the stage at diagnosis, the 5-year survival rate being approximately 30% for advanced tumors. Early diagnosis, including the detection of lesions at risk for malignant transformation, is crucial for limiting the need for extensive surgery and for improving disease-free survival. Saliva has gained popularity as a readily available source of biomarkers (including cytokines) useful for diagnosing specific oral and systemic conditions. Particularly, the close interaction between oral dysplastic/neoplastic cells and saliva makes such fluid an ideal candidate for the development of non-invasive and highly accurate diagnostic tests. The present review has been designed to answer the question: "Is there evidence to support the role of specific salivary cytokines in the diagnosis of OSCC?" We retrieved 27 observational studies satisfying the inclusion and exclusion criteria. Among the most frequent cytokines investigated as candidates for OSCC biomarkers, IL-6, IL-8, TNF-α are present at higher concentration in the saliva of OSCC patients than in healthy controls and may therefore serve as basis for the development of rapid tests for early diagnosis of oral cancer.

Down-Regulation of an Autophagy-Related Gene SERPINA1 as a Superior Prognosis Biomarker Associates with Relapse and Distant Metastasis in Colon Adenocarcinoma

Background

The relapse and distant metastasis in colon adenocarcinoma (COAD) patients with a poor prognosis. Autophagy has gained increasing attention recently.

Methods

This study utilized univariate Cox analysis from the TCGA database to obtain 10 prognostic autophagy-related genes (ARGs). GO and KEGG functional annotation analysis suggested that the ARGs were significantly enriched in tumor metabolic processes. We verified the autophagy-related genes screened by TCGA clinical data. Then, we compared the expression of SERPINA1 in primary and metastatic tumor cells in the GEO database, and finally verified the relationship between SERPINA1 protein expression and prognosis with the CPTAC database.

Results

The ROC curves showed SERPINA1 had robust prediction capability in judging the prognosis and disease process compared with the other 4 ARGs and risk score in COAD. Clinical relationship analysis further indicated SERPINA1 was related to TMN stage, clinical-stage, OS, RFS, and DMFS in COAD. Besides, survival analysis presented that higher expression of SERPINA1 was significantly associated with the longer OS, RFS, or DMFS. Moreover, SERPINA1 protein was validated to be associated with OS, RFS, and DMFS through our own IHC and CPTAC database. Finally, we exploratoryly combined the SERPINA1 mRNA and SERPINA1 protein as a new index for prognostics.

Conclusion

This new combined index showed the highest prognostic value for OS, RFS, and DMFS, and had the potential to become a practical biomarker for prognosis.

Identification of Salivary Proteomic Biomarkers for Oral Cancer Screening

BACKGROUND/AIM

The current study aimed to identify biomarkers for differentiating between patients with oral cancer (OC) and healthy controls (HCs) on the basis of the comprehensive proteomic analyses of saliva samples by using liquid chromatography-mass spectrometry (LC-MS/MS).

PATIENTS AND METHODS

Unstimulated saliva samples were collected from 39 patients with OC and from 31 HCs. Proteins in the saliva were comprehensively analyzed using LC-MS/MS. To differentiate between patients with OC and HCs, a multiple logistic regression model was developed for evaluating the discriminatory ability of a combination of multiple markers.

RESULTS

A total of 23 proteins were significantly differentially expressed between the patients with OC and the HCs. Six out of the 23 proteins, namely α-2-macroglobulin-like protein 1, cornulin, hemoglobin subunit β, Ig k chain V-II region Vk167, kininogen-1 and transmembrane protease serine 11D, were selected using the forward-selection method and applied to the multiple logistic regression model. The area under the curve for discriminating between patients with OC and HCs was 0.957 when the combination of the six metabolites was used (95% confidence interval=0.915-0.998; p<0.001). Furthermore, these candidate proteins did not show a stage-specific difference.

CONCLUSION

The results of the current study showed that six salivary proteins are potential non-invasive biomarkers for OC screening.

Proteomic approaches to assist in diagnosis and prognosis of oral cancer

Introduction: Oral squamous cell carcinoma (OSCC) ranks among the top 10 leading causes of cancer worldwide, with 5-year survival rate of about 50%, high lymph node metastasis, and relapse rates. The OSCC diagnosis, prognosis, and treatment are mostly based on the clinical TNM classification. There is an urgent need for the discovery of biomarkers and therapeutic targets to assist in the clinical decision-making process.Areas covered: We summarize proteomic studies of the OSCC tumor, immune microenvironment, potential liquid biopsy sites, and post-translational modifications trying to retrieve information in the discovery and verification or (pre)validation phases. The search strategy was based on the combination of MeSH terms and expert refinement.Expert opinion: Untargeted combined with targeted proteomics are strategies that provide reliable and reproducible quantitation of proteins and are the methods of choice of many groups worldwide. Undoubtedly, proteomics has been contributing to the understanding of OSCC progression and uncovers potential candidates as biomarker or therapeutic targets. Nevertheless, none of these targets are available in the clinical practice yet. The scientific community needs to overcome the limitations by investing in robust experimental designs to strengthen the value of the findings, leveraging the translation of knowledge, and further supporting clinical decisions.

Identification of Hub Genes Associated With Melanoma Development by Comprehensive Bioinformatics Analysis

Introduction

This study aimed to identify important genes associated with melanoma to further develop new target gene therapies and analyze their significance concerning prognosis.

Materials and methods

Gene expression data for melanoma and normal tissue were downloaded from three databases. Differentially co-expressed genes were identified by WGCNA and DEGs analysis. These genes were subjected to GO, and KEGG enrichment analysis and construction of the PPI visualized with Cytoscape and screened for the top 10 Hub genes using CytoHubba. We validated the Hub gene's protein levels with an immunohistochemical assay to confirm the accuracy of our analysis.

Results

A total of 435 differentially co-expressed genes were obtained. Survival curves showed that high expression of FOXM1,\ EXO1, KIF20A, TPX2, and CDC20 in melanoma patients with 5 of the top 10 hub genes was associated with reduced overall survival (OS). Immunohistochemistry showed that all five genes were expressed at higher protein levels in melanoma than in paracancerous tissues.

Conclusion

FOXM1, EXO1, KIF20A, TPX2, and CDC20 are prognosis-associated core genes of melanoma, and their high expression correlates with the low prognosis of melanoma patients and can be used as biomarkers for melanoma diagnosis, treatment, and prognosis prediction.

Molecular alterations in oral cancer using high-throughput proteomic analysis of formalin-fixed paraffin-embedded tissue

Loss of cell differentiation is a hallmark for the progression of oral squamous cell carcinoma (OSCC). Archival Formalin-Fixed Paraffin-Embedded (FFPE) tissues constitute a valuable resource for studying the differentiation of OSCC and can offer valuable insights into the process of tumor progression. In the current study, we performed LC-MS/MS-based quantitative proteomics of FFPE specimens from pathologically-confirmed well-differentiated, moderately-differentiated, and poorly-differentiated OSCC cases. The data were analyzed in four technical replicates, resulting in the identification of 2376 proteins. Of these, 141 and 109 were differentially expressed in moderately-differentiated and poorly differentiated OSCC cases, respectively, compared to well-differentiated OSCC. The data revealed significant metabolic reprogramming with respect to lipid metabolism and glycolysis with proteins belonging to both these processes downregulated in moderately-differentiated OSCC when compared to well-differentiated OSCC. Signaling pathway analysis indicated the alteration of extracellular matrix organization, muscle contraction, and glucose metabolism pathways across tumor grades. The extracellular matrix organization pathway was upregulated in moderately-differentiated OSCC and downregulated in poorly differentiated OSCC, compared to well-differentiated OSCC. PADI4, an epigenetic enzyme transcriptional regulator, and its transcriptional target HIST1H1B were both found to be upregulated in moderately differentiated and poorly differentiated OSCC, indicating epigenetic events underlying tumor differentiation. In conclusion, the findings support the advantage of using high-resolution mass spectrometry-based FFPE archival blocks for clinical and translational research. The candidate signaling pathways identified in the study could be used to develop potential therapeutic targets for OSCC.

A Meta-Analysis of Proteomic Blood Markers of Colorectal Cancer

BACKGROUND

Early diagnosis will significantly improve the survival rate of colorectal cancer (CRC); however, the existing methods for CRC screening were either invasive or inefficient. There is an emergency need for novel markers in CRC's early diagnosis. Serum proteomics has gained great potential in discovering novel markers, providing markers that reflect the early stage of cancer and prognosis prediction of CRC. In this paper, the results of proteomics of CRC studies were summarized through a meta-analysis in order to obtain the diagnostic efficiency of novel markers.

METHODS

A systematic search on bibliographic databases was performed to collect the studies that explore blood-based markers for CRC applying proteomics. The detection and validation methods, as well as the specificity and sensitivity of the biomarkers in these studies, were evaluated. Newcastle- Ottawa Scale (NOS) case-control studies version was used for quality assessment of included studies.

RESULTS

Thirty-four studies were selected from 751 studies, in which markers detected by proteomics were summarized. In total, fifty-nine proteins were classified according to their biological function. The sensitivity, specificity, or AUC varied among these markers. Among them, Mammalian STE20-like protein kinase 1/ Serine threonine kinase 4 (MST1/STK4), S100 calcium-binding protein A9 (S100A9), and Tissue inhibitor of metalloproteinases 1 (TIMP1) were suitable for effect sizes merging, and their diagnostic efficiencies were recalculated after merging. MST1/STK4 obtained a sensitivity of 68% and a specificity of 78%. S100A9 achieved a sensitivity of 72%, a specificity of 83%, and an AUC of 0.88. TIMP1 obtained a sensitivity of 42%, a specificity of 88%, and an AUC of 0.71.

CONCLUSION

MST1/STK4, S100A9, and TIMP1 showed excellent performance for CRC detection. Several other markers also presented optimized diagnostic efficacy for CRC early detection, but further verification is still needed before they are suitable for clinical use. The discovering of more efficient markers will benefit CRC treatment.

Molecular alterations in oral cancer between tobacco chewers and smokers using serum proteomics

BACKGROUND

Tobacco exposure (through smoking or chewing) is one of the predominant risk factors associated with the development of oral squamous cell carcinoma (OSCC). Despite the growing number of patients diagnosed with OSCC, there are few circulating biomarkers for identifying individuals at a higher risk of developing the disease. Successful identification of candidate molecular markers for risk assessment could aid in the early detection of oral lesions and potentially be used for community screening of high-risk populations.

OBJECTIVE

Identification of differentially expressed proteins in the serum of oral cancer patients which can serve as biomarkers for the diagnosis of the onset of oral cancer among tobacco users.

METHODS

We employed a tandem mass tag (TMT)-based quantitative proteomics approach to study alterations in the serum proteomes of OSCC patients based on their tobacco exposure habits (chewing and smoking) compared to healthy individuals with no history of using any form of tobacco or any symptoms of the disease.

RESULTS

Mass spectrometry-based analysis resulted in the identification of distinct signatures in the serum of OSCC patients who either chewed or smoked tobacco. Pathway analysis revealed opposing effects of dysregulated proteins enriched in the complement-coagulation signaling cascades with a high expression of the Serpin family of proteins observed in OSCC patients who chewed tobacco compared to healthy individuals whereas these proteins showed decreased levels in OSCC patients who smoked. ELISA-based validation further confirmed our findings revealing higher expression of SERPINA6 and SERPINF1 across serum of OSCC patients who chewed tobacco compared to healthy individuals.

CONCLUSIONS

This study serves as a benchmark for the identification of serum-based protein markers that may aid in the identification of high-risk patients who either chew tobacco or smoke tobacco.

Salivary biomarkers in oral squamous cell carcinoma

In disease diagnostics and health surveillance, the use of saliva has potential because its collection is convenient and noninvasive. Over the past two decades, the development of salivary utilization for the early detection of cancer, especially oral cavity and oropharynx cancer has gained the interest of the researcher and clinician. Until recently, the oral cavity and oropharynx cancers are still having a five-year survival rate of 62%, one of the lowest in all major human cancers. More than 90% of oral cancers are oral squamous cell carcinoma (OSCC). Despite the ease of accessing the oral cavity in clinical examination, most OSCC lesions are not diagnosed in the early stage, which is suggested to be the main cause of the low survival rate. Many studies have been performed and reported more than 100 potential saliva biomarkers for OSCC. However, there are still obstacles in figuring out the reliable OSCC salivary biomarkers and the clinical application of the early diagnosis protocol. The current review article discusses the emerging issues and is hoped to raise awareness of this topic in both researchers and clinicians. We also suggested the potential salivary biomarkers that are reliable, specific, and sensitive for the early detection of OSCC.

CapsNet-SSP: multilane capsule network for predicting human saliva-secretory proteins

Background

Compared with disease biomarkers in blood and urine, biomarkers in saliva have distinct advantages in clinical tests, as they can be conveniently examined through noninvasive sample collection. Therefore, identifying human saliva-secretory proteins and further detecting protein biomarkers in saliva have significant value in clinical medicine. There are only a few methods for predicting saliva-secretory proteins based on conventional machine learning algorithms, and all are highly dependent on annotated protein features. Unlike conventional machine learning algorithms, deep learning algorithms can automatically learn feature representations from input data and thus hold promise for predicting saliva-secretory proteins.

Results

We present a novel end-to-end deep learning model based on multilane capsule network (CapsNet) with differently sized convolution kernels to identify saliva-secretory proteins only from sequence information. The proposed model CapsNet-SSP outperforms existing methods based on conventional machine learning algorithms. Furthermore, the model performs better than other state-of-the-art deep learning architectures mostly used to analyze biological sequences. In addition, we further validate the effectiveness of CapsNet-SSP by comparison with human saliva-secretory proteins from existing studies and known salivary protein biomarkers of cancer.

Conclusions

The main contributions of this study are as follows: (1) an end-to-end model based on CapsNet is proposed to identify saliva-secretory proteins from the sequence information; (2) the proposed model achieves better performance and outperforms existing models; and (3) the saliva-secretory proteins predicted by our model are statistically significant compared with existing cancer biomarkers in saliva. In addition, a web server of CapsNet-SSP is developed for saliva-secretory protein identification, and it can be accessed at the following URL: http://www.csbg-jlu.info/CapsNet-SSP/. We believe that our model and web server will be useful for biomedical researchers who are interested in finding salivary protein biomarkers, especially when they have identified candidate proteins for analyzing diseased tissues near or distal to salivary glands using transcriptome or proteomics.