Biomarkers Identification in the Microenvironment of Oral Squamous Cell Carcinoma: A Systematic Review of Proteomic Studies

An important determinant for oral squamous cell carcinoma (OSCC) onset and outcome is the composition of the tumor microenvironment (TME). Thus, the study of the interactions occurring among cancer cells, immune cells, and cancer-associated fibroblasts within the TME could facilitate the understanding of the mechanisms underlying OSCC development and progression, as well as of its sensitivity or resistance to the therapy. In this context, it must be highlighted that the characterization of TME proteins is enabled by proteomic methodologies, particularly mass spectrometry (MS). Aiming to identify TME protein markers employable for diagnosing and prognosticating OSCC, we have retrieved a total of 119 articles spanning 2001 to 2023, of which 17 have passed the selection process, satisfying all its criteria. We have found a total of 570 proteins detected by MS-based proteomics in the TME of OSCC; among them, 542 are identified by a single study, while 28 are cited by two or more studies. These 28 proteins participate in extracellular matrix remodeling and/or energy metabolism. Here, we propose them as markers that could be used to characterize the TME of OSCC for diagnostic/prognostic purposes. Noteworthy, most of the 28 individuated proteins share one feature: being modulated by the hypoxia that is present in the proliferating OSCC mass.

Recent advances in minimally invasive biomarkers of OSCC: from generalized to personalized approach

Oral cancer is the 6th most common type of cancer worldwide, and oral squamous cell carcinoma (OSCC) accounts for >90% of oral cancers. It is a major health problem, particularly in low- and middle-income countries (LMICs), due to both its high incidence and significant mortality and morbidity. Despite being a global burden, and even with the significant advancement in the management of OSCC, the overall outcome of the disease is still abysmal. With the advent of time, advanced diagnostic and treatment approaches have come into practice, but the burden of the disease has not improved significantly. Major reasons attributed to the poor outcome are delay in diagnosis, locoregional recurrence and resistance to the currently available treatment regimen. In this review, we have highlighted the existing challenges in the diagnosis and have emphasized the advancements in minimally invasive biomarkers. Additionally, the importance of collaborative multidimensional approaches involving clinicians and researchers has been discussed, as well as the need to redefine and establish better utility and management of existing diagnostic and treatment protocols along with the minimally invasive/non-invasive biomarkers.

Artificial intelligence in salivary biomarker discovery and validation for oral diseases

Salivary biomarkers can improve the efficacy, efficiency, and timeliness of oral and maxillofacial disease diagnosis and monitoring. Oral and maxillofacial conditions in which salivary biomarkers have been utilized for disease-related outcomes include periodontal diseases, dental caries, oral cancer, temporomandibular joint dysfunction, and salivary gland diseases. However, given the equivocal accuracy of salivary biomarkers during validation, incorporating contemporary analytical techniques for biomarker selection and operationalization from the abundant multi-omics data available may help improve biomarker performance. Artificial intelligence represents one such advanced approach that may optimize the potential of salivary biomarkers to diagnose and manage oral and maxillofacial diseases. Therefore, this review summarized the role and current application of techniques based on artificial intelligence for salivary biomarker discovery and validation in oral and maxillofacial diseases.

Cystatin SN (CST1) as a Novel Salivary Biomarker of Periodontitis

Identification of biomarkers could help in assessing periodontal health status and monitoring treatment outcomes. Therefore, the aim of this cross-sectional study was to identify potential innovative salivary biomarkers for the diagnosis of periodontitis using an untargeted proteomic approach. Forty-five healthy non-smoker participants diagnosed as having periodontally healthy conditions (H), severe periodontitis (P), and healthy but reduced periodontium after active periodontal treatment (T) were consecutively enrolled (15 per each group) in the study. A higher number of spots were identified in the proteome of unstimulated whole saliva collected from H and T subjects compared with P group, mainly within the range of 8-40 kDa. Protein spots of interest were analysed by MALDI-TOF-MS, allowing the identification of cystatin SN (CST1) isoform, as confirmed by Western blot. CST1 was markedly expressed in the H group, while it was absent in most P samples (p < 0.001). Interestingly, a distinct CST1 expression was observed in saliva from T patients. CST1 was negatively correlated with the percentage of pathological sites (p < 0.001) and was effective in discriminating active periodontitis from healthy periodontal status (whether H or T). Therefore, salivary CST1 may be a promising non-invasive biomarker for periodontal disease diagnosis and monitoring.

Salivary Chemical Barrier Proteins in Oral Squamous Cell Carcinoma-Alterations in the Defense Mechanism of the Oral Cavity

Oral squamous cell carcinoma (OSCC) is one of the most frequent types of head and neck cancer. Despite the genetic and environmental risk factors, OSCC is also associated with microbial infections and/or dysbiosis. The secreted saliva serves as the chemical barrier of the oral cavity and, since OSCC can alter the protein composition of saliva, our aim was to analyze the effect of OSCC on the salivary chemical barrier proteins. Publicly available datasets regarding the analysis of salivary proteins from patients with OSCC and controls were collected and examined in order to identify differentially expressed chemical barrier proteins. Network analysis and gene ontology (GO) classification of the differentially expressed chemical barrier proteins were performed as well. One hundred and twenty-seven proteins showing different expression pattern between the OSCC and control groups were found. Protein-protein interaction networks of up- and down-regulated proteins were constructed and analyzed. The main hub proteins (IL-6, IL-1B, IL-8, TNF, APOA1, APOA2, APOB, APOC3, APOE, and HP) were identified and the enriched GO terms were examined. Our study highlighted the importance of the chemical barrier of saliva in the development of OSCC.

Mass spectrometry-based proteomics as an emerging tool in clinical laboratories

Mass spectrometry (MS)-based proteomics have been increasingly implemented in various disciplines of laboratory medicine to identify and quantify biomolecules in a variety of biological specimens. MS-based proteomics is continuously expanding and widely applied in biomarker discovery for early detection, prognosis and markers for treatment response prediction and monitoring. Furthermore, making these advanced tests more accessible and affordable will have the greatest healthcare benefit.This review article highlights the new paradigms MS-based clinical proteomics has created in microbiology laboratories, cancer research and diagnosis of metabolic disorders. The technique is preferred over conventional methods in disease detection and therapy monitoring for its combined advantages in multiplexing capacity, remarkable analytical specificity and sensitivity and low turnaround time.Despite the achievements in the development and adoption of a number of MS-based clinical proteomics practices, more are expected to undergo transition from bench to bedside in the near future. The review provides insights from early trials and recent progresses (mainly covering literature from the NCBI database) in the application of proteomics in clinical laboratories.

Review Insights on Salivary Proteomics Biomarkers in Oral Cancer Detection and Diagnosis

Early detection is crucial for the treatment and prognosis of oral cancer, a potentially lethal condition. Tumor markers are abnormal biological byproducts produced by malignant cells that may be found and analyzed in a variety of bodily fluids, including saliva. Early detection and appropriate treatment can increase cure rates to 80-90% and considerably improve quality of life by reducing the need for costly, incapacitating medicines. Salivary diagnostics has drawn the interest of many researchers and has been proven to be an effective tool for both medication monitoring and the diagnosis of several systemic diseases. Since researchers are now searching for biomarkers in saliva, an accessible bodily fluid, for noninvasive diagnosis of oral cancer, measuring tumor markers in saliva is an interesting alternative to blood testing for early identification, post-treatment monitoring, and monitoring high-risk lesions. New molecular markers for oral cancer detection, treatment, and prognosis have been found as a result of developments in the fields of molecular biology and salivary proteomics. The numerous salivary tumor biomarkers and how they relate to oral cancer and pre-cancer are covered in this article. We are optimistic that salivary protein biomarkers may one day be discovered for the clinical detection of oral cancer because of the rapid advancement of proteomic technology.

Mass Spectrometry Contribution to Pediatric Cancers Research

For over four decades, mass spectrometry-based methods have provided a wealth of information relevant to various challenges in the field of cancers research. These challenges included identification and validation of novel biomarkers for various diseases, in particular for various forms of cancer. These biomarkers serve various objectives including monitoring patient response to the various forms of therapy, differentiating subgroups of the same type of cancer, and providing proteomic data to complement datasets generated by genomic, epigenetic, and transcriptomic methods. The same proteomic data can be used to provide prognostic information and could guide scientists and medics to new and innovative targeted therapies The past decade has seen a rapid emergence of epigenetics as a major contributor to carcinogenesis. This development has given a fresh momentum to MS-based proteomics, which demonstrated to be an unrivalled tool for the analyses of protein post-translational modifications associated with chromatin modifications. In particular, high-resolution mass spectrometry has been recently used for systematic quantification of chromatin modifications. Data generated by this approach are central in the search for new therapies for various forms of cancer and will help in attempts to decipher antitumor drug resistance. To appreciate the contribution of mass spectrometry-based proteomics to biomarkers discovery and to our understanding of mechanisms behind the initiation and progression of various forms of cancer, a number of recent investigations are discussed. These investigations also include results provided by two-dimensional gel electrophoresis combined with mass spectrometry.

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.

Saliva diagnostics: emerging techniques and biomarkers for salivaomics in cancer detection

INTRODUCTION

The pursuit of easy-to-use, non-invasive and inexpensive diagnostics is an urgent task for clinicians and scientists. Saliva is an important component of body fluid with regular changes of contents under various pathophysiological conditions, and the biomarkers identified from saliva shows high application potentials and values in disease diagnostics. This review introduces the latest developments in saliva research, with an emphasis on the detection and application of salivary biomarkers in cancer detection.

AREAS COVERED

Detection of disease-specific biomarkers in saliva samples by existing salivaomic methods can be used to diagnose various human pathological conditions and was introduced in details. This review also covers the saliva collection methods, the analytical techniques as well as the corresponding commercial products, with an aim to describe an holistic process for saliva-based diagnostics.

EXPERT OPINION

Saliva, as a non-invasive and collectable body fluid, can reflect the pathophysiological changes of the human body to a certain extent. Identification of reliable saliva biomarkers can provide a convenient way for cancer detection in clinical applications.

Development and validation of machine learning-based risk prediction models of oral squamous cell carcinoma using salivary autoantibody biomarkers

INTRODUCTION

The incidence of oral cavity squamous cell carcinoma (OSCC) continues to rise. OSCC is associated with a low average survival rate, and most patients have a poor disease prognosis because of delayed diagnosis. We used machine learning techniques to predict high-risk cases of OSCC by using salivary autoantibody levels and demographic and behavioral data.

METHODS

We collected the salivary samples of patients recruited from a teaching hospital between September 2008 and December 2012. Ten salivary autoantibodies, sex, age, smoking, alcohol consumption, and betel nut chewing were used to build prediction models for identifying patients with a high risk of OSCC. The machine learning algorithms applied in the study were logistic regression, random forest, support vector machine with the radial basis function kernel, eXtreme Gradient Boosting (XGBoost), and a stacking model. We evaluated the performance of the models by using the area under the receiver operating characteristic curve (AUC), with simulations conducted 100 times.

RESULTS

A total of 337 participants were enrolled in this study. The best predictive model was constructed using a stacking algorithm with original forms of age and logarithmic levels of autoantibodies (AUC = 0.795 ± 0.055). Adding autoantibody levels as a data source significantly improved the prediction capability (from 0.698 ± 0.06 to 0.795 ± 0.055, p < 0.001).

CONCLUSIONS

We successfully established a prediction model for high-risk cases of OSCC. This model can be applied clinically through an online calculator to provide additional personalized information for OSCC diagnosis, thereby reducing the disease morbidity and mortality rates.

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.

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 future of early cancer detection

A proactive approach to detecting cancer at an early stage can make treatments more effective, with fewer side effects and improved long-term survival. However, as detection methods become increasingly sensitive, it can be difficult to distinguish inconsequential changes from lesions that will lead to life-threatening cancer. Progress relies on a detailed understanding of individualized risk, clear delineation of cancer development stages, a range of testing methods with optimal performance characteristics, and robust evaluation of the implications for individuals and society. In the future, advances in sensors, contrast agents, molecular methods, and artificial intelligence will help detect cancer-specific signals in real time. To reduce the burden of cancer on society, risk-based detection and prevention needs to be cost effective and widely accessible.

Finding the combination of multiple biomarkers to diagnose oral squamous cell carcinoma - A data mining approach

Data mining has proven to be a reliable method to analyze and discover useful knowledge about various diseases, including cancer research. In particular, data mining and machine learning algorithms to study oral squamous cell carcinoma (OSCC), the most common form of oral cancer, is a new area of research. This malignant neoplasm can be studied using saliva samples. Saliva is an important biofluid that must be used to verify potential biomarkers associated with oral cancer. In this study, first, we provide an overview of OSSC diagnoses based on machine learning and salivary metabolites. To our knowledge, this is the first study to apply advanced data mining techniques to diagnose OSCC. Then, we give new results of classification and feature selection algorithms used to identify potential salivary biomarkers of OSCC. To accomplish this task, we used the filter feature selection random forest importance algorithm and a wrapper methodology to evaluate the importance of metabolites obtained from gas chromatography mass-spectrometry (GC-MS) in the context of differentiation of OSCC and the control group. Salivary samples (n = 68) were collected for the control group, and the OSCC group were from patients matched for gender, age, and smoking habit. The classification process occurred based on Random Forest (RF) classification algorithm along with 10-cross validation. The results showed that glucuronic acid, maleic acid, and batyl alcohol can classify the samples with an area under the curve (AUC) of 0.91 versus an AUC of 0.76 using all 51 metabolites analyzed. The methodology used in this study can assist healthcare professionals and be adopted to discover diagnostic biomarkers for other diseases.

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.

Salivary Proteomics Identifies Transthyretin as a Biomarker of Early Dementia Conversion

Background:

Alzheimer’s disease (AD) remains to date an incurable disease with a long asymptomatic phase. Early diagnosis in peripheral biofluids has emerged as key for identifying subjects at risk and developing therapeutics and preventative approaches.

Objective:

We apply proteomics discovery to identify salivary diagnostic biomarkers for AD, which are suitable for self-sampling and longitudinal biomonitoring during aging.

Methods:

57 participants were recruited for the study and were categorized into Cognitively normal (CNh) (n = 19), mild cognitive impaired (MCI) (n = 21), and Alzheimer’s disease (AD) (n = 17). On a subset of subjects, 3 CNh and 3 mild AD, shot-gun filter aided sample preparation (FASP) proteomics and liquid chromatography mass spectroscopy (LC-MS/MS) was employed in saliva and cerebrospinal fluid (CSF) to identify neural-derived proteins. The protein level of salivary Transthyretin (TTR) was validated using western blot analysis across groups.

Results:

We found that 19.8% of the proteins in saliva are shared with CSF. When we compared the saliva and CSF proteome, 24 hits were decreased with only one protein expressed more. Among the differentially expressed proteins, TTR with reported function in amyloid misfolding, shows a significant drop in AD samples, confirmed by western blot showing a 0.5-fold reduction in MCI and AD compared to CNh.

Conclusion:

A reduction in salivary TTR appears with the onset of cognitive symptoms. More in general, the proteomic profiling of saliva shows a plethora of biomarkers worth pursuing as non-invasive hallmarks of dementia in the preclinical stage.

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.

HBFP: a new repository for human body fluid proteome

Body fluid proteome has been intensively studied as a primary source for disease biomarker discovery. Using advanced proteomics technologies, early research success has resulted in increasingly accumulated proteins detected in different body fluids, among which many are promising biomarkers. However, despite a handful of small-scale and specific data resources, current research is clearly lacking effort compiling published body fluid proteins into a centralized and sustainable repository that can provide users with systematic analytic tools. In this study, we developed a new database of human body fluid proteome (HBFP) that focuses on experimentally validated proteome in 17 types of human body fluids. The current database archives 11 827 unique proteins reported by 164 scientific publications, with a maximal false discovery rate of 0.01 on both the peptide and protein levels since 2001, and enables users to query, analyze and download protein entries with respect to each body fluid. Three unique features of this new system include the following: (i) the protein annotation page includes detailed abundance information based on relative qualitative measures of peptides reported in the original references, (ii) a new score is calculated on each reported protein to indicate the discovery confidence and (iii) HBFP catalogs 7354 proteins with at least two non-nested uniquely mapping peptides of nine amino acids according to the Human Proteome Project Data Interpretation Guidelines, while the remaining 4473 proteins have more than two unique peptides without given sequence information. As an important resource for human protein secretome, we anticipate that this new HBFP database can be a powerful tool that facilitates research in clinical proteomics and biomarker discovery.

Database URL:https://bmbl.bmi.osumc.edu/HBFP/

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.

Salivary diagnosis of oral cancers by salivary samples: a systematic literature review

The aim of this article is to carry out a systematic analysis of the literature concerning the diagnosis of oral cancers by salivary samples. Different biomarkers, produced by the tumor itself or by its environment, show significant variations in their concentration at the salivary level, correlated or not at the blood or tissue level. After studying 239 articles, we included 36 in this analysis. This allowed us to extract 46 potential molecules for salivary diagnostics. Only 26 demonstrated a good level of evidence. 8 clusters have also been proposed for better specificity and sensitivity. To date, the protocols of the studies carried out do not allow to affirm that one or more biomarkers are effective for a salivary diagnosis of oral cancers. Part of the results contradict or sometimes lack precision. In addition, the studies included here do not have a good methodological quality and do not always take into account other factors influencing the concentrations (systemic diseases, age, sex, tobacco, alcohol, etc.). Additional studies are still necessary, notably with larger groups of patients, representative of the general population and standardization of the protocols for the study and quantification of biomarkers.

Protein and Microbial Biomarkers in Sputum Discern Acute and Latent Tuberculosis in Investigation of Pastoral Ethiopian Cohort

Differential diagnosis of tuberculosis (TB) and latent TB infection (LTBI) remains a public health priority in high TB burden countries. Pulmonary TB is diagnosed by sputum smear microscopy, chest X-rays, and PCR tests for distinct Mycobacterium tuberculosis (Mtb) genes. Clinical tests to diagnose LTBI rely on immune cell stimulation in blood plasma with TB-specific antigens followed by measurements of interferon-γ concentrations. The latter is an important cytokine for cellular immune responses against Mtb in infected lung tissues. Sputum smear microscopy and chest X-rays are not sufficiently sensitive while both PCR and interferon-γ release assays are expensive. Alternative biomarkers for the development of diagnostic tests to discern TB disease states are desirable. This study's objective was to discover sputum diagnostic biomarker candidates from the analysis of samples from 161 human subjects including TB patients, individuals with LTBI, negative community controls (NCC) from the province South Omo, a pastoral region in Ethiopia. We analyzed 16S rRNA gene-based bacterial taxonomies and proteomic profiles. The sputum microbiota did not reveal statistically significant differences in α-diversity comparing the cohorts. The genus Mycobacterium, representing Mtb, was only identified for the TB group which also featured reduced abundance of the genus Rothia in comparison with the LTBI and NCC groups. Rothia is a respiratory tract commensal and may be sensitive to the inflammatory milieu generated by infection with Mtb. Proteomic data supported innate immune responses against the pathogen in subjects with pulmonary TB. Ferritin, an iron storage protein released by damaged host cells, was markedly increased in abundance in TB sputum compared to the LTBI and NCC groups, along with the α-1-acid glycoproteins ORM1 and ORM2. These proteins are acute phase reactants and inhibit excessive neutrophil activation. Proteomic data highlight the effector roles of neutrophils in the anti-Mtb response which was not observed for LTBI cases. Less abundant in the sputum of the LTBI group, compared to the NCC group, were two immunomodulatory proteins, mitochondrial TSPO and the extracellular ribonuclease T2. If validated, these proteins are of interest as new biomarkers for diagnosis of LTBI.

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.

Proteomic profiling in extracellular vesicles for cancer detection and monitoring

Extracellular vesicles (EVs) are nanometer-size lipid vesicles released by cells, which play essential biological functions in intercellular communication. Increasing evidence indicates that EVs participate in cancer development, including invasion, migration, metastasis, and cancer immune modulation. One of the key mechanisms is that EVs affect different cells in the tumor microenvironment through surface-anchor proteins and protein cargos. Moreover, proteins specifically expressed in tumor-derived EVs can be applied in cancer diagnosis and monitoring. Besides, the EV proteome also helps to understand drug resistance in cancers and to guide clinical medication. With the development of mass spectrometry and array-based multi-protein detection, the research of EV proteomics has entered a new era. The high-throughput parallel proteomic profiling based on these new platforms allows us to study the impact of EV proteome on cancer progression more comprehensively and to describe the proteomic landscape in cancers with more details. In this article, we review the role and function of different types of EVs in cancer progression. More importantly, we summarize the proteomic profiling of EVs based on different methods and the application of EV proteome in cancer detection and monitoring.

Profiling of extracellular vesicles in oral cancer, from transcriptomics to proteomics

Oral cancers occurring in different subsites can have distinct etiologies' and are a significant problem worldwide. In general, the incidence of oral cancers has declined over the last decade due to improvements in modifiable risk factors (tobacco and alcohol consumption). However, recent data suggest that the incidence of squamous cell carcinomas in the oral tongue and oropharynx are increasing. Human papilloma virus (HPV) is an important risk factor for oropharyngeal cancer and is associated with better treatment responses when compared with HPV-unrelated oropharyngeal cancer. Regardless of the subsite, there are no clinically available biomarkers for the early detection of these cancers and many are detected at an advanced stage and are associated with poor 5-year survival rates. Tumor tissue and serial needle biopsies are used to diagnose and prognosticate oral cancers but have important limitations. Besides being invasive and physically painful, these types of biopsies offer a limited view of a complex tumor due to inter- and intra-tumoral heterogeneity and a dynamic tumor microenvironment. Liquid biopsies offer a promising and alternative way to measure disease in real-time. Extracellular vesicles (EVs) are small particles that are secreted by all cells types and can be readily isolated from a wide range of biofluids. EVs are structurally stable and can horizontally transfer bioactive molecules to distant sites throughout the body in concentrated forms that exceed what can be delivered in a soluble format. As EVs represent their cell of origin, biofluid derived EVs are heterogeneous and are comprised of a complex repertoire of host- and cancer-derived particles. This review article has focused on studies that have used transcriptomics and proteomics to explore the function and clinical significance of EVs in oral cavity and oropharyngeal cancers.

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.

Association of chronic periodontitis and type 2 diabetes mellitus with salivary Del-1 and IL-17 levels

PURPOSE

Chronic periodontitis (CP) and Type 2 diabetes mellitus (T2DM) are chronic diseases affecting the humans and have interrelationship in their pathogenesis. Monitoring the progress with biomarker in these disease is important from treatment outcome point of view. We investigated the association of salivary developmental endothelial locus-1 (Del-1) and interleukin-17 (IL-17) levels in CP and T2DM.

METHODS

Saliva was collected from 17 healthy and 68 patients (divided into 4 groups based on presence or absence of CP and T2DM). Periodontal parameters were recorded at the time of visit. Del-1 and IL-17 levels in unstimulated salivary samples were determined using enzyme-linked immunosorbent assay.

RESULTS

Study found the lower levels of salivary Del-1 and higher levels of IL-17 in CP (2.23 ± 2.10 ng/mL, 56.54 ± 19.79 ng/mL), CCDM ((1.97 ± 1.36 ng/mL, 74.74 ± 17.79 ng/mL) and CUDM (1.02 ± 0.52 ng/mL, 63.84 ± 24.72 ng/mL) as compared to healthy individuals (6.54 ± 2.07; 24.47 ± 8.23 ng/mL) (p < 0.001). Del-1 and IL-17 levels were correlating with inflammatory state in CP and presence of T2DM aggravate the severity of disease in CP. An inverse correlation between salivary Del-1 & IL-17 levels was also seen. Furthermore, we also observed that the combination of T2DM and CP (CCDM and CUDM) increases the salivary IL-17 levels and decreases Del-1 levels.

CONCLUSIONS

There is an upregulation of salivary IL-17 and downregulation of salivary Del-1 with increase in severity of periodontal disease as well as T2DM. Furthermore, the presence of T2DM in chronic periodontitis patients can aggravate the inflammation related periodontal destruction.

In-gel digestion coupled with mass spectrometry (GeLC-MS/MS)-based salivary proteomic profiling of canine oral tumors

BACKGROUND

Various types of oral tumors, either benign or malignant, are commonly found in dogs. Since saliva directly contacts the tumors and saliva collection is non-invasive, easily accessible and cost effective, salivary biomarkers are practical to be used for the diagnosis and/or prognosis of these diseases. However, there is limited knowledge of protein expression in saliva for canine oral tumors. The present study aimed to investigate novel biomarkers from the salivary proteome of dogs with early- and late-stage oral melanoma (EOM and LOM, respectively), oral squamous cell carcinoma (OSCC), benign oral tumors (BN), and periodontitis and healthy controls (CP), using an in-gel digestion coupled with mass spectrometry (GeLC-MS/MS). The relationships between protein candidates and chemotherapy drugs were explored and the expression of potential biomarkers in saliva and tissues was verified by western blot analysis.

RESULTS

For saliva samples, increased expression of protein tyrosine phosphatase non-receptor type 5 (PTPN5) was shown in all tumor groups compared with the CP group. Marked expression of PTPN5 was also observed in LOM and OSCC compared with that in BN and EOM. In addition, tumor protein p53 (p53), which appeared in the PTPN5-drug interactions, was exhibited to be expressed in all tumor groups compared with that in the CP group. For tissue samples, increased expression of p53 was shown in LOM compared with the control group.

CONCLUSION

PTPN5 and p53 were proposed to be potential salivary biomarkers of canine oral tumors.

Recent advances in mass spectrometry based clinical proteomics: applications to cancer research

Cancer biomarkers have transformed current practices in the oncology clinic. Continued discovery and validation are crucial for improving early diagnosis, risk stratification, and monitoring patient response to treatment. Profiling of the tumour genome and transcriptome are now established tools for the discovery of novel biomarkers, but alterations in proteome expression are more likely to reflect changes in tumour pathophysiology. In the past, clinical diagnostics have strongly relied on antibody-based detection strategies, but these methods carry certain limitations. Mass spectrometry (MS) is a powerful method that enables increasingly comprehensive insights into changes of the proteome to advance personalized medicine. In this review, recent improvements in MS-based clinical proteomics are highlighted with a focus on oncology. We will provide a detailed overview of clinically relevant samples types, as well as, consideration for sample preparation methods, protein quantitation strategies, MS configurations, and data analysis pipelines currently available to researchers. Critical consideration of each step is necessary to address the pressing clinical questions that advance cancer patient diagnosis and prognosis. While the majority of studies focus on the discovery of clinically-relevant biomarkers, there is a growing demand for rigorous biomarker validation. These studies focus on high-throughput targeted MS assays and multi-centre studies with standardized protocols. Additionally, improvements in MS sensitivity are opening the door to new classes of tumour-specific proteoforms including post-translational modifications and variants originating from genomic aberrations. Overlaying proteomic data to complement genomic and transcriptomic datasets forges the growing field of proteogenomics, which shows great potential to improve our understanding of cancer biology. Overall, these advancements not only solidify MS-based clinical proteomics' integral position in cancer research, but also accelerate the shift towards becoming a regular component of routine analysis and clinical practice.

Validation of Salivary Markers, IL-1β, IL-8 and Lgals3bp for Detection of Oral Squamous Cell Carcinoma in an Indian Population

Early detection and easier follow-up of oral squamous cell carcinoma (OSCC) would significantly improve the morbidity and mortality associated with it. With newer technologies, it has become possible to validate cancer biomarkers in saliva with high sensitivity and specificity. There is however a need to further validate these biomarkers in cohorts of different ethnic groups. Our objective was to validate previously evaluated salivary biomarkers in Indian population. The study enrolled 117 patients. These were grouped into subcatergories of 31 early (TNMstage I-II) and 27 late-stage OSCC (TNM stage III-IV), 30 PMOD and 29 post-treatment patients. There were 42 control subjects. We evaluated 3 protein markers, IL-1β, IL-8 and LGALS3BP using ELISA, from unstimulated saliva samples. Statistical analysis was done to calculate p-value, ROC, AUC, sensitivity, and specificity. Protein markers IL-1β and IL-8 were significantly elevated (p < 0.05) in OSCC patients. Though the markers could not discriminate PMOD and post-treatment subjects from controls, they proved to be significantly discriminatory between OSCC and controls. Both these markers were especially strong discriminators of late stage OSCC (stage III-IV). IL-1β had the most statistically significant discriminative power (AUC = 0.9017) in late-stage OSCC followed by IL-8 (AUC = 0.7619). Although LGALS3BP was not found to be significantly elevated in late stage OSCC patients, but it was a significant discriminator of early stage OSCC (stage I-II) with p-value = 0.0008 and AUC = 0.7296. These salivary biomarkers have been discovered and validated in other ethnic groups earlier. Hence, the fact that these markers were discriminatory in Indian population too, strengthens the possibility of using these salivary biomarkers as screening tools in different ethnic cohorts. Such trials would potentiate use of a non-invasive tool, like saliva for diagnosis and follow-up of oral cancer.

Profiling of subcellular EGFR interactome reveals hnRNP A3 modulates nuclear EGFR localization

The aberrant subcellular translocation and distribution of epidermal growth factor receptor (EGFR) represent a major yet currently underappreciated cancer development mechanism in non-small cell lung cancer (NSCLC). In this study, we investigated the subcellular interactome of EGFR by using a spectral counting-based approach combined with liquid chromatography–tandem mass spectrometry to understand the associated protein networks involved in the tumorigenesis of NSCLC. A total of 54, 77, and 63 EGFR-interacting proteins were identified specifically in the cytosolic, mitochondrial, and nuclear fractions from a NSCLC cell line, respectively. Pathway analyses of these proteins using the KEGG database shown that the EGFR-interacting proteins of the cytosol and nucleus are involved in the ribosome and spliceosome pathways, respectively, while those of the mitochondria are involved in metabolizing propanoate, fatty acid, valine, leucine, and isoleucine. A selected nuclear EGFR-interacting protein, hnRNP A3, was found to modulate the accumulation of nuclear EGFR. Downregulation of hnRNP A3 reduced the nuclear accumulation of EGFR, and this was accompanied by reduced tumor growth ability in vitro and in vivo. These results indicate that variations in the subcellular translocation and distribution of EGFR within NSCLC cells could affect tumor progression.

Impacts of RETN genetic polymorphism on breast cancer development

The adipokine resistin is linked with obesity, inflammation and various cancers, including breast cancer. This study sought to determine whether certain polymorphisms in the gene encoding resistin, RETN, increase the risk of breast cancer susceptibility. We analyzed levels of resistin expression in breast cancer tissue and samples from The Cancer Genome Atlas database. We also examined associations between four RETN single nucleotide polymorphisms (SNPs; rs3745367, rs7408174, rs1862513 and rs3219175) and breast cancer susceptibility in 515 patients with breast cancer and 541 healthy women without cancer. Compared with wild-type (GG) carriers, those carrying the AG genotype of the RETN SNP rs3219175 and those carrying at least one A allele in the SNP rs3219175 had a higher chance of developing breast cancer (adjusted odds ratio, AOR: 1.295, 95% confidence intervals, CI: 1.065-1.575 and 2.202, 1.701-2.243, respectively). When clinical aspects and the RETN SNP rs7408174 were examined in the breast cancer cohort, the CT genotype was linked to late-stage disease, while women with luminal A disease and at least one C allele were likely to progress to stage III/IV disease and to develop highly pathological grade III disease. Moreover, resistin-positive individuals were at greater risk than resistin-negative individuals for developing pathological grade III disease (OR: 5.020; 95% CI: 1.380-18.259). This study details risk associations between resistin and RETN SNPs in breast cancer susceptibility in Chinese Han women.

Saliva proteomics updates in biomedicine

In the years of personalized (or precision) medicine the 'omics' methodologies in biomedical sciences-genomics, transcriptomics, proteomics and metabolomics-are helping researchers to detect quantifiable biological characteristics, or biomarkers, that will best define the human physiology and pathologies. Proteomics use high throughput and high efficiency approaches with the support of bioinformatic tools in order to identify and quantify the total protein content of cells, tissues or biological fluids. Saliva receives a lot of attention as a rich biological specimen that offers a number of practical and physiological advantages over blood and other biological fluids in monitoring human health. The aim of this review is to present the latest advances in saliva proteomics for biomedicine.

Proteomic Profiling of Paired Interstitial Fluids Reveals Dysregulated Pathways and Salivary NID1 as a Biomarker of Oral Cavity Squamous Cell Carcinoma

Patients with oral cavity squamous cell carcinoma (OSCC) are frequently first diagnosed at an advanced stage, leading to poor prognosis and high mortality rates. Early detection of OSCC using body fluid-accessible biomarkers may improve the prognosis and survival rate of OSCC patients. As tumor interstitial fluid is a proximal fluid enriched with cancer-related proteins, it is a useful reservoir suitable for the discovery of cancer biomarkers and dysregulated biological pathways in tumor microenvironments. Thus, paired interstitial fluids of tumor (TIF) and adjacent noncancerous (NIF) tissues from 10 OSCC patients were harvested and analyzed using one-dimensional gel electrophoresis coupled with liquid chromatography-tandem mass spectrometry (GeLC-MS/MS). Using label-free spectral counting-based quantification, 113 proteins were found to be up-regulated in the TIFs compared with the NIFs. The gene set enrichment analysis (GSEA) revealed that the differentially expressed TIF proteins were highly associated with aminoacyl tRNA biosynthesis pathway. The elevated levels of 4 proteins (IARS, KARS, WARS, and YARS) involved in the aminoacyl tRNA biosynthesis were verified in the OSCC tissues with immunohistochemistry (IHC). In addition, nidogen-1 (NID1) was selected for verification as an OSCC biomarker. Salivary level of NID1 in OSCC patients (n = 48) was significantly higher than that in the healthy individuals (n = 51) and subjects with oral potentially malignant disorder (OPMD; n = 53). IHC analysis showed that NID1 level in OSCC tissues was increased compared with adjacent noncancerous epithelium (n = 222). Importantly, the elevated NID1 level was correlated with the advanced stages of OSCC, as well as the poor survival of OSCC patients. Collectively, the results suggested that TIF analysis facilitates understanding of the OSCC microenvironment and that salivary NID1 may be a useful biomarker for OSCC.

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

Oral cavity squamous cell carcinoma (OSCC) is one of the most common cancers worldwide. In Taiwan, OSCC is the fifth leading cause of cancer-related mortality and leads to 2800 deaths per year. The poor outcome of OSCC patients is principally ascribed to the fact that this disease is often advanced at the time of diagnosis, suggesting that early detection of OSCC is urgently needed. Analysis of cancer-related body fluids is one promising approach to identify biomarker candidates of cancers. To identify OSCC biomarkers, salivary proteomes of OSCC patients, individuals with oral potentially malignant disorders (OPMDs), and healthy volunteers were comparatively profiled with isobaric tags for relative and absolute quantitation (iTRAQ)-based mass spectrometry (MS). The salivary levels of 67 and 18 proteins in the OSCC group are elevated and decreased compared with that in the noncancerous group (OPMD and healthy groups), respectively. The candidate biomarkers were further selected using the multiple reaction monitoring (MRM)-MS and validated with the immunoassays. More importantly, the higher salivary level of three proteins, complement factor H (CFH), fibrinogen alpha chain (FGA), and alpha-1-antitrypsin (SERPINA1) was correlated with advanced stages of OSCC. Our results indicate that analysis of salivary proteome is a feasible strategy for biomarker discovery, and the three proteins are potential salivary markers for OSCC diagnosis.

Clinical validity of saliva and novel technology for cancer detection

Cancer, a local disease at an early stage, systemically evolves as it progresses by triggering alterations in surrounding microenvironment, disturbing immune surveillance and further disseminating its molecular contents into circulation. This pathogenic characteristic of cancer makes the use of biofluids such as blood/serum/plasma, urine, tear and cerebrospinal fluids credible surrogates harboring tumor tissue-derived molecular alterations for the detection of cancer. Most importantly, a number of recent reports have credentialed the clinical validity of saliva for the detection of systemic diseases including cancers. In this review, we discussed the validity of saliva as credible biofluid and clinical sample type for the detection of cancers. We have presented the molecular constituents of saliva that could mirror the systemic status of our body and recent findings of salivaomics associated with cancers. Recently, liquid biopsy to detect cancer-derived circulating tumor DNA has emerged as a credible cancer-detection tool with potential benefits in screening, diagnosis and also risk management of cancers. We have further presented the clinical validity of saliva for liquid biopsy of cancers and a new technology platform based on electrochemical detection of cancer-derived ctDNA in saliva with superior sensitivity and point-of-care potential. The clinical utilities of saliva for the detection of cancers have been evidenced, but biological underpinning on the existence of molecular signatures of cancer-origin in saliva, such as via exosomal distribution, should be addressed in detail.

Salivary proteomics of canine oral tumors using MALDI-TOF mass spectrometry and LC-tandem mass spectrometry

Canine oral tumors are relatively common neoplasms in dogs. For disease monitoring and early diagnosis, salivary biomarkers are appropriate because saliva collection is non-invasive and requires no professional skills. In the era of omics, matrix-assisted laser desorption/ionization with time-of-flight mass spectrometry (MALDI-TOF MS) coupled with liquid chromatography-tandem MS (LC-MS/MS) are suitable to identify potential disease-associated peptides and proteins. The present study aimed to use MALDI-TOF MS and LC-MS/MS to search for particular peptide mass fingerprints (PMFs) and conceivable biomarkers in saliva of dogs with early- and late-stage oral melanoma (EOM and LOM, respectively), oral squamous cell carcinoma (OSCC), benign oral tumors (BN), and periodontitis and healthy controls (CP). Pooled saliva samples in each group were used to be representative of population change. Unique PMFs were obtained and specific peptide fragments were sequenced by LC-MS/MS and BLAST-searched with mammalian protein databases. Seven peptide fragments appeared in the tumor groups (EOM, LOM, OSCC and BN) at 1096, 1208, 1322, 1794, 1864, 2354 and 2483 Da, two peptide fragments appeared in the LOM and OSCC groups at 2450 and 3492 Da, and in the CP controls at 2544 and 3026 Da. Also, protein–chemotherapy drug interaction networks were exhibited. Using western blot analysis, the expression of sentrin-specific protease 7 (SENP7), a peptide fragment at 1096 Da, in OSCC was significantly increased, as was the expression of TLR4, a peptide fragment at 3492 Da, in LOM and OSCC, compared with the CP group. The expression of nuclear factor kappa B (NF-κB), a TLR4 partner, was notably increased in OSCC compared with CP, BN and EOM. The expression was also enhanced in LOM compared with EOM. Expressed protein sequences from western blots were verified by LC-MS/MS. Western blots were then performed with individual samples in each group. The results showed the elevated expression of TLR4 in LOM and OSCC, compared with that in CP and BN, the increased expression of NF-κB in LOM and OSCC, compared with CP and in LOM compared with BN, and the enhanced expression of SENP7 in LOM and OSCC, compared with that in CP and BN. In conclusion, discrete clusters of EOM, LOM, OSCC, BN and CP groups and potential protein candidates associated with the diseases were demonstrated by salivary proteomics. Western blot analysis verified SENP7, TLR4 and NF-κB as potential salivary biomarkers of canine oral tumors.

Prediction of lymph node metastasis in oral squamous cell carcinoma based on protein profile

OBJECTIVE

Lymph node metastasis leads to high mortality rates of oral squamous cell carcinoma (OSCC). However, it is still controversial to define clinically negative neck (cN0) and positive neck (cN1-3).

METHODS

We retrieved candidate biomarkers identified by proteomic analysis in OSCC from published works of literature. In training stage, immunohistochemistry (IHC) analysis was used to determine the expression of proteins and logistic regression models with stepwise variable selection were used to identify potential factors that might affect lymph node metastasis and life status. Furthermore, the prediction model was validated in validating stage.

RESULTS

We screened eight highly expressed proteins related to lymph node metastasis in OSCC and found that the expression levels of SOD2, BST2, CAD, ITGB6, and PRDX4 were significantly elevated in patients with lymph node metastasis compared to the patients without lymph node metastasis. Furthermore, in training and validating stages, the prediction model base on the combination of CAD, SOD2 expression levels, and histopathologic grade was developed and validated in patients with OSCC.

CONCLUSIONS

Our findings showed that the developed model well predicts the lymph node metastasis and life status in patients with OSCC, independent of TNM stage.

Sulfate-based lipids: Analysis of healthy human fluids and cell extracts

Sulfate-based lipids (SL) have been proposed as players in inflammation, immunity and infection. In spite of the many biochemical processes linked to SL, analysis on this class of lipids has only focused on specific SL sub-classes in individual fluids or cells leaving a range of additional SL in other biological samples unaccounted for. This study describes the mass spectrometry screening of SL in lipid extracts of human fluids (saliva, plasma, urine, seminal fluid) and primary human cells (RBC, neutrophils, fibroblasts and skin epidermal) using targeted precursor ion scanning (PIS) approach. The PIS 97 mass spectra reveal a wide diversity of SL including steroid sulfates, sulfoglycolipids and other unidentified SL, as well as metabolites such as taurines, sulfated polyphenols and hypurate conjugates. Semi-quantification of SL revealed that plasma exhibited the highest content of SL whereas seminal fluid and epithelial cells contained the highest sulphur to phosphorous (S/P) ratio. The complexity of biofluids and cells sulfateome presented in this study highlight the importance of expanding the panel of synthetic sulfate-based lipid standards. Also, the heterogenous distribution of SL provides evidence for the interplay of sulfotransferases/sulfatases, opening new avenues for biomarker discovery in oral health, cardiovascular, fertility and dermatology research areas.

Resistin facilitates VEGF-A-dependent angiogenesis by inhibiting miR-16-5p in human chondrosarcoma cells

Resistin is an adipokine that is associated with obesity, inflammation, and various cancers. Chondrosarcomas are primary malignant bone tumors that have a poor prognosis. VEGF-A is a critical angiogenic factor that is known to promote angiogenesis and metastasis in chondrosarcoma. It is unknown as to whether resistin affects human chondrosarcoma angiogenesis. In this study, we show how resistin promotes VEGF-A expression and subsequently induces angiogenesis of endothelial progenitor cells (EPCs). Resistin treatment activated the phosphatidylinositol-3-kinase (PI3K) and Akt signaling pathways, while PI3K and Akt inhibitors or siRNA diminished resistin-induced VEGF-A expression. In vitro and in vivo studies revealed the downregulation of micro RNA (miR)-16-5p in resistin-induced VEGF-A expression and EPCs angiogenesis. We also found a positive correlation between resistin and VEGF-A expression, and a negative correlation between resistin and VEGF-A with miR-16-5p in chondrosarcoma patients. These findings reveal that resistin facilitates VEGF-A expression and angiogenesis through the inhibition of miR-16-5p expression via PI3K/Akt signaling cascades. Resistin may be a promising target in chondrosarcoma angiogenesis.

Proteome Analyses Reveal Positive Association of COL2A1, MPO, TYMS, and IGFBP5 with Canine Mammary Gland Malignancy

PURPOSE

To identify aberrantly expressed proteins contributing to pathogenesis of canine mammary tumors (CMTs) which are the most prevalent neoplasms in female dogs and include different types.

EXPERIMENTAL DESIGN

Frozen tissue specimens of normal mammary gland (n = 7), lobular hyperplasia (n = 6), simple carcinoma (n = 6), and complex carcinoma (n = 6) are collected from 11 CMT cases. Tissue homogenates are comparatively analyzed by the isobaric tags for relative and absolute quantification (iTRAQ) combined with LC-MS/MS to identify proteins differentially expressed in different-type CMT tissues.

RESULTS

Among 3795 proteins identified and quantified among all groups, 133, 127, and 98 proteins are particularly overexpressed in simple carcinoma, complex carcinoma, and both types, respectively, compared with normal and hyperplastic tissues. Moreover, collagen type II alpha 1 chain (COL2A), myeloperoxidase (MPO), thymidylate synthetase (TYMS), and insulin-like growth factor-binding protein 5 (IGFBP5) are validated to be highly expressed in different-type CMT tissues using immunoblotting and immunohistochemistry. Notably, COL2A1 and IGFBP5 levels are correlated with clinical stages.

CONCLUSIONS AND CLINICAL RELEVANCE

COL2A1, MPO, TYMS, and IGFBP5 protein levels are positively associated with CMT development. Data expedite further investigations to improve treatment regimens for CMT.

Salivary protease spectrum biomarkers of oral cancer

Proteases are important molecules that are involved in many physiological and pathological processes of the human body, such as growth, apoptosis and metastasis cancer cells. They are potential targets in cancer diagnosis and biotherapy. In this study, we analyzed the salivary protease spectrum of patients with oral squamous cell carcinoma (OSCC), oral benign masses and chronic periodontitis, as well as that of health, using human protease array kits, enzyme-linked immunosorbent assay, western blot and immunofluorescence. The salivary protease spectrum was found to be associated with oral diseases. For example, the saliva of patients with OSCC contained increased numbers of proteases than those of other oral diseases and health. The levels of matrix metalloproteinase (MMP)-1, MMP-2, MMP-10, MMP-12, A disintegrin and metalloprotease (ADAM)9, A disintegrin and metalloprotease with thrombospondin type 13 motifs (ADAMST13), cathepsin V and kallikrein 5 in the saliva of patients with OSCC were significantly increased compared with those of other groups. Taking MMP-1, cathepsin V, kallikrein 5 and ADAM9 as biomarkers of OSCC, cutoff values were199, 11.34, 9.29 and 202.55 pg·mL-1, respectively. From the area under the curve, sensitivity and specificity, the combination of cathepsin V/kallikrein5/ADAM9 was an optimal biomarker for diagnosing OSCC. Thus, analysis of the salivary protease spectrum may be an innovative and cost-efficient approach to evaluating the health status of the oral cavity. Specifically, increases in cathepsin V, kallikrein 5 and ADAM9 may be useful biomarkers in the screening and diagnosis of OSCC.

Proteomics biomarkers for solid tumors: Current status and future prospects

Cancer is a heterogeneous multifactorial disease, which continues to be one of the main causes of death worldwide. Despite the extensive efforts for establishing accurate diagnostic assays and efficient therapeutic schemes, disease prevalence is on the rise, in part, however, also due to improved early detection. For years, studies were focused on genomics and transcriptomics, aiming at the discovery of new tests with diagnostic or prognostic potential. However, cancer phenotypic characteristics seem most likely to be a direct reflection of changes in protein metabolism and function, which are also the targets of most drugs. Investigations at the protein level are therefore advantageous particularly in the case of in-depth characterization of tumor progression and invasiveness. Innovative high-throughput proteomic technologies are available to accurately evaluate cancer formation and progression and to investigate the functional role of key proteins in cancer. Employing these new highly sensitive proteomic technologies, cancer biomarkers may be detectable that contribute to diagnosis and guide curative treatment when still possible. In this review, the recent advances in proteomic biomarker research in cancer are outlined, with special emphasis placed on the identification of diagnostic and prognostic biomarkers for solid tumors. In view of the increasing number of screening programs and clinical trials investigating new treatment options, we discuss the molecular connections of the biomarkers as well as their potential as clinically useful tools for diagnosis, risk stratification and therapy monitoring of solid tumors.

Fabrication of hydrophilic multilayer magnetic probe for salivary glycopeptidome analysis

Variations in salivary components are closely associated with the predisposition and state of disease, the abnormal changes of salivary glycopeptidome are usually discovered as perilous singals of serious disease. Therefore, the monitoring and analyzing of salivary glycopeptidome are of even more overriding importance. In this work, a low-cost layer-by-layer assembly strategy was adopted to fabricate a hydrophilic multilayer magnetic probe (dubbed Mag-m-G6P) for salivary glycopeptidome analysis. The successful construction of multilayer structure not only guaranteed the good dispersal of probe by protecting magnetic core from itself aggregation tendency, but also endowed the probe with multiple advantages including the good hydrophilicity, uniform mesopore size and strong magnetic responsiveness, etc. As expected, with the optimized experimental conditions, the multifunctional probe showed high enrichemnt sensitivity, unbiased enrichment ability, excellent size-exclusion ability and reusability and so on in the process of standard sample analysis. At last, the Mag-m-G6P was successfully applied to salivary glycopeptidome analysis on further combination with LC-MS/MS analysis, a total of 53 endogenous glycopeptides were identified from human saliva.

Proteome characterization in various biological fluids of Trypanosoma brucei gambiense-infected subjects

Human African trypanosomiasis (HAT) is a neglected tropical disease that is endemic in sub-Saharan Africa. Control of the disease has been recently improved by better screening and treatment strategies, and the disease is on the WHO list of possible elimination. However, some physiopathological aspects of the disease transmission and progression remain unclear. We propose a new proteomic approach to identify new targets and thus possible new biomarkers of the disease. We also focused our attention on fluids classically associated with HAT (serum and cerebrospinal fluid (CSF)) and on the more easily accessible biological fluids urine and saliva. Liquid chromatography-tandem mass spectrometry (LC-MS/MS) established the proteomic profile of patients with early and late stage disease. The serum, CSF, urine and saliva of 3 uninfected controls, 3 early stage patients and 4 late stage patients were analyzed. Among proteins identified, in CSF, urine and saliva, respectively, 37, 8 and 24 proteins were differentially expressed and showed particular interest with regards to their function. The most promising proteins (Neogenin, Neuroserpin, secretogranin 2 in CSF; moesin in urine and intelectin 2 in saliva) were quantified by enzyme-linked immunosorbent assay in a confirmatory cohort of 14 uninfected controls, 23 patients with early stage disease and 43 patients with late stage disease. The potential of two proteins, neuroserpin and moesin, with the latter present in urine, were further characterized. Our results showed the potential of proteomic analysis to discover new biomarkers and provide the basis of the establishment of a new proteomic catalogue applied to HAT-infected subjects and controls. SIGNIFICANCE: Sleeping sickness, also called Human African Trypanosomiasis (HAT), is a parasitic infection caused by a parasitic protozoan, Trypanosoma brucei gambiense or T. b. rhodesiense which are transmitted via an infected tsetse fly: Glossina. For both, the haemolymphatic stage (or first stage) signs and symptoms are intermittent fever, lymphadenopathy, hepatosplenomegaly, headaches, pruritus, and for T. b. rhodesiense infection a chancre is often formed at the bite site. Meningoencephalitic stage (or second stage) occurs when parasites invade the CNS, it is characterised by neurological signs and symptoms such as altered gait, tremors, neuropathy, somnolence which can lead to coma and death if untreated. first stage of the disease is characterizing by fevers, headaches, itchiness, and joint pains and progressive lethargy corresponding to the second stage with confusion, poor coordination, numbness and trouble sleeping. Actually, diagnosing HAT requires specialized expertise and significant resources such as well-equipped health centers and qualified staff. Such resources are lacking in many endemic areas that are often in rural locales, so many individuals with HAT die before the diagnosis is established. In this study, we analysed by mass spectrometry the entire proteome of serum, CSF, urine and saliva samples from infected and non-infected Angolan individuals to define new biomarkers of the disease. This work of proteomics analysis is a preliminary stage to the characterization of the whole proteome, of these 4 biological fluids, of HAT patients. We have identified 69 new biomarkers. Five of them have been thoroughly investigated by ELISA quantification. Neuroserpine and Moesin are respectively promising new biomarkers in CSF and urine's patient for a better diagnosis.

Association of Resistin Gene Polymorphisms with Oral Squamous Cell Carcinoma Progression and Development

Oral squamous cell carcinoma (OSCC) accounts for over 90% of malignant neoplasms of the mouth. In Taiwan, OSCC is the fourth most common male cancer and the fourth leading cause of male cancer death. Resistin (RETN) is an adipokine that is associated with obesity, inflammation, and various cancers. Here, we examine the association between four single nucleotide polymorphisms (SNPs) of the RETN gene (rs3745367, rs7408174, rs1862513, and rs3219175) and OSCC susceptibility as well as clinical outcomes in 935 patients with OSCC and in 1200 cancer-free healthy controls. We found that, in 1465 smokers, RETN polymorphisms carriers with the betel-nut chewing habit had a 6.708–10.882-fold greater risk of having OSCC compared to RETN wild-type carriers without the betel-nut chewing habit. Patients with OSCC who had A/A homozygous of RETN rs3219175 polymorphism showed a high risk for an advanced tumor size (> T2), compared to those patients with G/G homozygotes. In addition, A/T/G/G haplotype significantly increased the risks for OSCC by 1.376-fold. This study is the first to examine the risk factors associated with RETN SNPs in OSCC progression and development in Taiwan.