Mass spectrometry-based clinical proteomics: head-and-neck cancer biomarkers and drug-targets discovery

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.

Amorphous poly-N-vinylcarbazole polymer as a novel matrix for the determination of low molecular weight compounds by MALDI-TOF MS

Traditional matrices for matrix-assisted laser desorption/ionization mass spectrometry (MALDI-TOF MS) are usually crystalline small molecules. The heterogeneous co-crystallization of the analyte and the matrix creates a sweet spot effect and reduces point-to-point reproducibility. In this study, an amorphous poly-N-vinylcarbazole polymer (PVK) was studied as a novel matrix for MALDI-TOF MS to detect various low molecular weight compounds (LMWCs) in the negative ion mode. The PVK achieved excellent matrix action and showed high sensitivity, good salt tolerance, and reproducibility. These results significantly broaden the design rules for new and efficient polymeric MALDI matrices.

Amorphous, highly salt tolerant and stable polymer PVK as a negative ion mode matrix was successfully achieved for the qualitative and quantitative detection of small molecule compounds by MALDI MS.

Fabricated Metal-Organic Frameworks (MOFs) as luminescent and electrochemical biosensors for cancer biomarkers detection

In the health domain, a major challenge is the detection of diseases using rapid and cost-effective techniques. Most of the existing cancer detection methods show poor sensitivity and selectivity and are time consuming with high cost. To overcome this challenge, we analyzed porous fabricated metal-organic frameworks (MOFs) that have better structures and porosities for enhanced biomarker sensing. Here, we summarize the use of fabricated MOF luminescence and electrochemical sensors in devices for cancer biomarker detection. Various strategies of fabrication and the role of fabricated materials in sensing cancer biomarkers have been studied and described. The structural properties, sensing mechanisms, roles of noncovalent interactions, limits of detection, modeling, advantages, and limitations of MOF sensors have been well-discussed. The study presents an innovative technique to detect the cancer biomarkers by the use of luminescence and electrochemical MOF sensors. In addition, the potential association studies have been opening the way for personalized patient treatments and the development of new cancer-detecting devices.

Deep Learning in Head and Neck Tumor Multiomics Diagnosis and Analysis: Review of the Literature

Head and neck tumors are the sixth most common neoplasms. Multiomics integrates multiple dimensions of clinical, pathologic, radiological, and biological data and has the potential for tumor diagnosis and analysis. Deep learning (DL), a type of artificial intelligence (AI), is applied in medical image analysis. Among the DL techniques, the convolution neural network (CNN) is used for image segmentation, detection, and classification and in computer-aided diagnosis. Here, we reviewed multiomics image analysis of head and neck tumors using CNN and other DL neural networks. We also evaluated its application in early tumor detection, classification, prognosis/metastasis prediction, and the signing out of the reports. Finally, we highlighted the challenges and potential of these techniques.

Proteomics-based Predictive Model for the Early Detection of Metastasis and Recurrence in Head and Neck Cancer

BACKGROUND/AIM

Head and neck squamous cell carcinoma (HNSCC) presents high morbidity, an overall poor prognosis and survival, and a compromised quality of life of the survivors. Early tumor detection, prediction of its behavior and prognosis as well as the development of novel therapeutic strategies are urgently needed for a more successful HNSCC management.

MATERIALS AND METHODS

In this study, a proteomics analysis of HNSCC tumor and non-tumor samples was performed and a model to predict the risk of recurrence and metastasis development was built.

RESULTS

This predictive model presented good accuracy (>80%) and comprises as variables the tumor staging along with DHB12, HMGB3 and COBA1 proteins. Differences at the intensity levels of these proteins were correlated with the development of metastasis and recurrence as well as with patient's survival.

CONCLUSION

The translation of proteomic predictive models to routine clinical practice may contribute to a more precise and individualized clinical management of the HNSCC patients, reducing recurrences and improving patients' quality of life. The capability of generalization of this proteomic model to predict the recurrence and metastases development should be evaluated and validated in other HNSCC populations.

A Low-Rank Representation Method Regularized by Dual-Hypergraph Laplacian for Selecting Differentially Expressed Genes

Differentially expressed genes selection becomes a hotspot and difficulty in recent molecular biology. Low-rank representation (LRR) uniting graph Laplacian regularization has gained good achievement in the above field. However, the co-expression information of data cannot be captured well by graph regularization. Therefore, a novel low-rank representation method regularized by dual-hypergraph Laplacian is proposed to reveal the intrinsic geometrical structures hidden in the samples and genes direction simultaneously, which is called dual-hypergraph Laplacian regularized LRR (DHLRR). Finally, a low-rank matrix and a sparse perturbation matrix can be recovered from genomic data by DHLRR. Based on the sparsity of differentially expressed genes, the sparse disturbance matrix can be applied to extracting differentially expressed genes. In our experiments, two gene analysis tools are used to discuss the experimental results. The results on two real genomic data and an integrated dataset prove that DHLRR is efficient and effective in finding differentially expressed genes.

Combined detection of IL-6 and IL-8 is beneficial to the diagnosis of early stage esophageal squamous cell cancer: a preliminary study based on the screening of serum markers using protein chips

Background

The diagnosis rate of early stage esophageal squamous cell carcinoma (ESCC) is low due to the lack of specific tumor markers. Seeking for these markers is beneficial to improve the early diagnosis rate and the prognosis of patients. This study profiles the differentially expressed proteins of early stage ESCC patients via the AAH-BLG-507 protein chip, which further consolidates the clinical evidence of ESCC diagnosis.

Materials and methods

In this study, 20 serum samples were collected from Taihe Hospital between August 2016 and June 2017. Ten of them carried ESCC, while the rest were healthy controls. To profile the proteins’ expression level, the AAH-BLG-507 protein chip was used, and both highly expressed and lowly expressed proteins were fished out. Meanwhile, their biological roles were examined by using Gene Ontology (GO) database and String database, and they were further verified by ELISA.

Results

Results showed that the expression levels of AXL, ARTN, Ang2, BDNF, BMP7, cripto-1, CCL28, E-selectin, IL-6, IL-8 and SHH in the serum of early ESCC were significantly upregulated (P<0.05), particularly IL-6 and IL-8. The expression levels of TSP1 and MMP-8 were markedly downregulated (P<0.05). Analysis showed that these proteins were mainly involved in angiogenesis, signal transduction, cell proliferation and migration, indicating the close relationship with the development of ESCC.

Conclusion

It suggested that IL-6 and IL-8 proteins could be considered as the markers for ESCC diagnosis.

Emerging proteomics biomarkers and prostate cancer burden in Africa

Various biomarkers have emerged via high throughput omics-based approaches for use in diagnosis, treatment, and monitoring of prostate cancer. Many of these have yet to be demonstrated as having value in routine clinical practice. Moreover, there is a dearth of information on validation of these emerging prostate biomarkers within African cohorts, despite the huge burden and aggressiveness of prostate cancer in men of African descent. This review focusses of the global landmark achievements in prostate cancer proteomics biomarker discovery and the potential for clinical implementation of these biomarkers in Africa. Biomarker validation processes at the preclinical, translational and clinical research level are discussed here, as are the challenges and prospects for the evaluation and use of novel proteomic prostate cancer biomarkers.

Assessment of Sample Preparation Bias in Mass Spectrometry-Based Proteomics

For mass spectrometry-based proteomics, the selected sample preparation strategy is a key determinant for information that will be obtained. However, the corresponding selection is often not based on a fit-for-purpose evaluation. Here we report a comparison of in-gel (IGD), in-solution (ISD), on-filter (OFD), and on-pellet digestion (OPD) workflows on the basis of targeted (QconCAT-multiple reaction monitoring (MRM) method for mitochondrial proteins) and discovery proteomics (data-dependent acquisition, DDA) analyses using three different human head and neck tissues (i.e., nasal polyps, parotid gland, and palatine tonsils). Our study reveals differences between the sample preparation methods, for example, with respect to protein and peptide losses, quantification variability, protocol-induced methionine oxidation, and asparagine/glutamine deamidation as well as identification of cysteine-containing peptides. However, none of the methods performed best for all types of tissues, which argues against the existence of a universal sample preparation method for proteome analysis.

Mass Spectrometry Analyses of Multicellular Tumor Spheroids

Multicellular tumor spheroids (MCTS) are a powerful biological in vitro model, which closely mimics the 3D structure of primary avascularized tumors. Mass spectrometry (MS) has established itself as a powerful analytical tool, not only to better understand and describe the complex structure of MCTS, but also to monitor their response to cancer therapeutics. The first part of this review focuses on traditional mass spectrometry approaches with an emphasis on elucidating the molecular characteristics of these structures. Then the mass spectrometry imaging (MSI) approaches used to obtain spatially defined information from MCTS is described. Finally the analysis of primary spheroids, such as those present in ovarian cancer, and the great potential that mass spectrometry analysis of these structures has for improved understanding of cancer progression and for personalized in vitro therapeutic testing is discussed.

Expression of small leucine-rich extracellular matrix proteoglycans biglycan and lumican reveals oral lichen planus malignant potential

OBJECTIVES

The aim of this study was to examine molecular alterations on the protein level in lesions of oral lichen planus (OLP), oral squamous cell carcinoma (OSCC) and healthy mucosa.

MATERIALS AND METHODS

Global protein profiling methods based on liquid chromatography coupled to mass spectrometry (LC-MS) were used, with a special emphasis on evaluation of deregulated extracellular matrix molecules expression, as well as on analyses of IG2F and IGFR2 expression in healthy mucosa, OLP and OSCC tissues by comparative semi-quantitative immunohistochemistry.

RESULTS

Mass spectrometry-based proteomics profiling of healthy mucosa, OLP and OSCC tissues (and accompanied histologically unaltered tissues, respectively) identified 55 extracellular matrix proteins. Twenty among identified proteins were common to all groups of samples. Expression of small leucine-rich extracellular matrix proteoglycans lumican and biglycan was found both in OSCC and OLP and they were validated by Western blot analysis as putative biomarkers. A significant increase (p < 0.05) of biglycan expression in OLP-AT group was determined in comparison with OLP-T group, while lumican showed significant up-regulation (p < 0.05) in OLP-T and OSCC-T groups vs. adjacent and control tissue groups. Biglycan expression was only determined in OSCC-AT group. Immunohistochemical analysis of IGF2 and IG2FR expression revealed no significant difference among groups of samples.

CONCLUSION/CLINICAL RELEVANCE

Biglycan and lumican were identified as important pathogenesis biomarkers of OLP that point to its malignant potential.

Clinical Significance and Prognostic Value of the Expression of LAMP3 in Oral Squamous Cell Carcinoma

Recent studies demonstrated high expression of lysosome-associated membrane protein 3 (LAMP3) in a variety of malignancies including esophageal squamous cell carcinoma, gastrointestinal cancer, breast cancer, and cervical cancer and its involvement in several biological activities of tumor cells. However, the expression of LAMP3 and its value in oral squamous cell carcinoma (OSCC) remain unclear. In this study, we examined the expression of LAMP3 in OSCC tissue samples and investigated the relationship between LAMP3 and clinical characteristics of patients with OSCC. We examined mRNA and protein levels of LAMP3 in OSCC tissues and neighboring normal tissues using quantitative real-time polymerase chain reaction and immunohistochemistry analyses, respectively. Both the mRNA and protein levels of LAMP3 were significantly higher in OSCC tissues than in adjacent normal tissues. Chi-square analysis showed that the high LAMP3 expression was notably linked to the degree of tumor differentiation and advanced TNM stage. Univariate and multivariate analyses showed that the high LAMP3 expression was an independent prognostic marker in OSCC. Our results suggest that LAMP3 might act as a potential anticancer target and a prognostic marker in patients with OSCC.

End Binding 1 (EB1) overexpression in oral lesions and cancer: A biomarker of tumor progression and poor prognosis

INTRODUCTION

Oral squamous cell carcinoma (OSCC) patients are at high risk of loco-regional recurrence and despite the improvement in treatment strategy, 5-year survival rates are about 50%. Identification of patients at high risk of recurrence may enable rigorous personalized post-treatment management. In an earlier proteomics study we observed overexpression of End Binding Protein (EB1) in OSCC. In the present study we investigated the diagnostic and prognostic significance of alterations in expression of EB1 in oral cancer.

METHODS

In this retrospective study, the expression of EB1 protein was evaluated in 259 OSCCs, 41 dysplasia, 166 hyperplasia and 126 normal tissues using immunohistochemistry and correlated with clinical-pathological parameters and prognosis of OSCC patients over a follow-up period of up to 91months.

RESULTS

Significantly higher expression of cytoplasmic EB1 was observed in hyperplasia [p<0.001, OR=7.2, 95% CI=4.1-12.8], dysplasia (p<0.001, OR=21.8, CI=8.8-50.2) and OSCCs (p<0.001, OR=10.1, CI=5.8-17.4) in comparison with normal mucosa. Univariate analysis revealed cytoplasmic EB1 association with tumor grade, tumor size and recurrence of the disease. Kaplan Meier survival analysis of EB1 expression showed significantly reduced disease free survival (DFS) (p=0.003). Notably, OSCC patients showing cytoplasmic EB1 overexpression demonstrated significantly reduced DFS (p=0.004, HR=2.1).

CONCLUSION

EB1 overexpression is an early event in oral tumorigenesis and cytoplasmic EB1 accumulation is associated with poor prognosis and tumor recurrence in OSCC patients.

M2 isoform of pyruvate kinase (PKM2) is upregulated in Kazakh's ESCC and promotes proliferation and migration of ESCC cells

The objectives of the present study are to explore role of pyruvate kinase isoenzyme type M2 (PKM2) in progression of Kazakh's esophageal squamous cell carcinoma (ESCC) in Xinjiang, China, and to clarify mechanism of PKM2 in malignant phenotype. PKM2 expression was examined using immunohistochemistry (IHC) in 101 matched pairs of ESCC and normal adjacent tissues (NATs) and using enzyme-linked immunosorbent assay (ELISA) in 35 serum samples of Kazakh's ESCC and 8 serum samples of healthy subjects. To investigate mechanism, small interfering RNA (siRNA)-PKM2 was transfected into ESCC cells. Cell migration and invasion were evaluated by wound healing and Transwell assays. Apoptosis and cell cycle were analyzed by flow cytometry (FCM). PKM2 expression was significantly higher in ESCC tissues (77.2 %, 78/101) compared with matched NAT (P = 0.003) and also higher in serum samples of Kazakh's ESCC patients (78.84 ng/mL) compared with healthy subjects (13.55 ng/mL) (P = 0.001). Patients with overexpression of PKM2 had a poor prognosis (P = 0.032). After knockdown of PKM2, cell proliferation, migration, and invasion were significantly reduced (P = 0.001), apoptosis increased (P = 0.001), and cell cycle was arrested at G1 phase. PKM2 overexpression was significantly correlated with the worse outcome of Kazakh's ESCC. Furthermore, PKM2 was involved in progression of ESCC by promoting proliferation and suppressing apoptosis, accelerating invasion, and influencing cell cycle. PKM2 could be a potential biomarker for molecular classification of ESCC.

Silencing of high-mobility group box 2 (HMGB2) modulates cisplatin and 5-fluorouracil sensitivity in head and neck squamous cell carcinoma

Dysregulation of protein expression is associated with most diseases including cancer. MS-based proteomic analysis is widely employed as a tool to study protein dysregulation in cancers. Proteins that are differentially expressed in head and neck squamous cell carcinoma (HNSCC) cell lines compared to the normal oral cell line could serve as biomarkers for patient stratification. To understand the proteomic complexity in HNSCC, we carried out iTRAQ-based MS analysis on a panel of HNSCC cell lines in addition to a normal oral keratinocyte cell line. LC-MS/MS analysis of total proteome of the HNSCC cell lines led to the identification of 3263 proteins, of which 185 proteins were overexpressed and 190 proteins were downregulated more than twofold in at least two of the three HNSCC cell lines studied. Among the overexpressed proteins, 23 proteins were related to DNA replication and repair. These included high-mobility group box 2 (HMGB2) protein, which was overexpressed in all three HNSCC lines studied. Overexpression of HMGB2 has been reported in various cancers, yet its role in HNSCC remains unclear. Immunohistochemical labeling of HMGB2 in a panel of HNSCC tumors using tissue microarrays revealed overexpression in 77% (54 of 70) of tumors. The HMGB proteins are known to bind to DNA structure resulting from cisplatin-DNA adducts and affect the chemosensitivity of cells. We observed that siRNA-mediated silencing of HMGB2 increased the sensitivity of the HNSCC cell lines to cisplatin and 5-FU. We hypothesize that targeting HMGB2 could enhance the efficacy of existing chemotherapeutic regimens for treatment of HNSCC. All MS data have been deposited in the ProteomeXchange with identifier PXD000737 (http://proteomecentral.proteomexchange.org/dataset/PXD000737).

Micro-scale strategy to detect spermine and spermidine by MALDI-TOF MS in foods and identification of apoptosis-related proteins by nano-flow UPLC-MS/MS after treatment with spermine and spermidine

Spermine and spermidine are multiple-nitrogen compounds found in many foods. Both compounds are essential for cell growth and human health. This study established a simple and fast method of detecting spermine and spermidine in food samples by matrix-assisted laser desorption/ionization combined with time-of-flight mass spectrometry (MALDI-TOF MS). After a simple sample preparation procedure, spermine and spermidine were directly detected by MALDI-TOF MS with no additional purification procedure. The calibration curves for spermine and spermidine ranged from 0.1 to 10 μg/mL. In intra- and inter-batch assays of three different concentrations of spermine and spermidine, all relative standard deviations and relative errors were below 18.9%. These experimental results confirmed the practicability and effectiveness of the proposed MALDI-TOF MS method for fast determination of spermine and spermidine in food samples. Furthermore, since spermine and spermidine have important roles in apoptosis, up-regulation and down-regulation of spermine and spermidine during apoptosis were analyzed. After treating NRK-52E cells with spermine and spermidine, the cells were lysed, and cell proteins were collected, and digested. Apoptosis-related proteins were then identified by tandem MS.

Streamlining bottom-up protein identification based on selective ultraviolet photodissociation (UVPD) of chromophore-tagged histidine- and tyrosine-containing peptides

We report a fast and highly efficient diazonium reaction that couples a nitroazobenzene chromophore to tyrosine and histidine residues, thus endowing peptides with high photoabsorption cross sections at 351 nm in the gas phase. Only the tagged peptides undergo ultraviolet photodissociation (UVPD) at 351 nm, as demonstrated for several Tyr- and His-containing peptides from protein digests. Additional selectivity is achieved by the integration of the UVPD-MS method with an in silico database search restricted to Tyr- and His-containing peptides. A modified MassMatrix algorithm condenses analysis by filtering the input database file to include Tyr/His-containing peptides only, thus reducing the search space and increasing confidence. In summary, derivatization of specific amino acid residues in conjunction with selective activation of the derivatized peptides provides a streamlined approach to shotgun proteomics.

Alkylated trihydroxyacetophenone as a MALDI matrix for hydrophobic peptides

Hydrophobic peptides are difficult to detect in matrix-assisted laser desorption/ionization mass spectrometry (MALDI-MS), because of the hydrophilic properties of conventional matrices and the low affinity for hydrophobic peptides. Recently, we reported on alkylated dihydroxybenzoic acid (ADHB) as a matrix additive for hydrophobic peptides; however, the peptides were detected in the rim of the matrix-analyte dried spot. Here, we report on a novel matrix, alkylated trihydroxyacetophenone (ATHAP), which is a 2,4,6-trihydroxyacetophenone derivative incorporating a hydrophobic alkyl chain on the acetyl group and thus is expected to have an affinity for hydrophobic peptides. ATHAP increased the sensitivity of hydrophobic peptides 10-fold compared with α-cyano-4-hydroxycinnamic acid (CHCA), in which the detection of hydrophilic peptides was suppressed. The peptides were detected throughout the entire matrix-analyte dried spot using ATHAP, overcoming the difficulty of finding a "sweet spot" when using ADHB. In addition, ATHAP functioned alone as a matrix, unlike ADHB as an additive. In phosphorylase b digests analysis, hydrophobic peptides, which were not detected with CHCA for 1 pmol, were detected with this matrix, confirming that ATHAP led to increased sequence coverage and may extend the range of target analytes in MALDI-MS.

Proteomics: methodologies and applications to the study of human diseases

Proteomic approach has allowed large-scale studies of protein expression in different tissues and body fluids in discrete conditions and/or time points. Recent advances of methodologies in this field have opened new opportunities to obtain relevant information on normal and abnormal processes occurring in the human body. In the current report, the main proteomics techniques and their application to human disease study are reviewed.

Comparative proteomics, network analysis and post-translational modification identification reveal differential profiles of plasma Con A-bound glycoprotein biomarkers in gastric cancer

In the study, we used Con A affinity chromatography, 1-D gel electrophoresis, and nano-LC-MS/MS to screen biomarker candidates in plasma samples obtained from 30 patients with gastric cancer and 30 healthy volunteers. First, we pooled plasma samples matched by age and sex. We identified 17 differentially expressed Con A-bound glycoproteins, including 10 upregulated proteins and 7 downregulated proteins; these differences were significant (Student's t-test, p-value<0.05). Furthermore, 2 of the upregulated proteins displayed expression levels that were increased by 2-fold or more in gastric cancer samples when compared with normal control samples. These proteins included leucine-rich alpha-2-glycoprotein (LRG1) and inter-alpha-trypsin inhibitor heavy chain H3 (ITIH3), and the expression levels were validated by Western blot analysis. Pathway and network analysis of the differentially expressed proteins by Ingenuity Pathway Analysis revealed vital canonical pathways involving acute phase response signaling, the complement system, LXR/RXR activation, hematopoiesis from pluripotent stem cells, and primary immunodeficiency signaling. Our results suggest that Con A-bound LRG1 and ITIH3 may not be practically applicable as a robust biomarker for the early detection of gastric cancer. Additionally, three novel PTMs in ITIH3 were identified and include hexose-N-acetyl-hexosamine at asparagine-(41), trimethylation at aspartic acid-(290), and flavin adenine dinucleotide at histidine-(335).

BIOLOGICAL SIGNIFICANCE

Our study was to describe a combinatorial approach of Con A affinity chromatography, 1-D SDS-PAGE, and nano-LC/MS/MS that provides a label-free, comparative glycoproteomic quantification strategy for the investigation of glycoprotein profiles in plasma from gastric cancer patients versus healthy volunteers and to identify glycoprotein biomarkers for the early clinical detection of gastric cancer. Three novel PTMs, HexHexNAc, trimethylation and FAD, in Con A-bound ITIH3 were identified and built in molecular modeling. The aspartic acid-(290) trimethylation site was located in a metal ion-dependent adhesion site (MIDAS motif; (290)-DXSXS…T…D-(313)) that may influence important function for binding protein ligands.

Mass spectrometry-based proteomics: the road to lung cancer biomarker discovery

Lung cancer is the leading cause of cancer death in men and women in Western nations, and is among the deadliest cancers with a 5-year survival rate of 15%. The high mortality caused by lung cancer is attributable to a late-stage diagnosis and the lack of effective treatments. So, it is crucial to identify new biomarkers that could function not only to detect lung cancer at an early stage but also to shed light on the molecular mechanisms that underlie cancer development and serve as the basis for the development of novel therapeutic strategies. Considering that DNA-based biomarkers for lung cancer showed inadequate sensitivity, specificity, and reproducibility, proteomics could represent a better tool for the identification of useful biomarkers and therapeutic targets for this cancer type. Among the proteomics technologies, the most powerful tool is mass spectrometry. In this review, we describe studies that use mass spectrometry-based proteomics technologies to analyze tumor proteins and peptides, which might represent new diagnostic, prognostic, and predictive markers for lung cancer. We focus in particular on those findings that hold promise to impact significantly on the clinical management of this disease.

SILAC in biomarker discovery

Stable isotope labeling with amino acids in cell culture (SILAC) has become an extremely valuable tool in quantitative proteomics and in biomarker discovery. Incorporation of SILAC labels occurs when cells are passaged multiple times in media where the endogenous amino acids are replaced with the heavy isotope ones. During a typical experiment, cells from heavy and light strains are combined in equal ratios and all steps of protein extraction and digestion occur on these cells together, minimizing the number of external variables introduced during sample processing. Potential biomarkers are revealed during liquid chromatography-tandem mass spectrometry analysis by peptides that differ considerably in intensity between the two strains as revealed by the mass shift from the incorporated SILAC label. The protocol presented here describes how to perform a typical experiment using the SILAC technology for the search for biomarkers as revealed by differences in protein expression levels, as well as by phosphorylation, a common posttranslational modification.

Salivary proteomics in biomedical research

Proteins that are important indicators of physiological or pathological states, can provide information for the identification of early and differential markers for disease. Saliva, contains an abundance of proteins, offers an easy, inexpensive, safe, and non-invasive approach for disease detection, and possesses a high potential to revolutionize the diagnostics. Discovery of salivary biomarkers could be used to scrutinize health and disease surveillance. The impact of human saliva proteome analysis in the search for clinically relevant disease biomarkers will be realized through advances made using proteomic technologies. The advancements of emerging proteomic techniques have benefited biomarker research to the point where saliva is now recognized as an excellent diagnostic medium for the detection of disease. This review presents an overview of the value of saliva as a credible diagnostic tool and we aim to summarize the proteomic technologies currently used for global analysis of saliva proteins and to elaborate on the application of saliva proteomics to the discovery of disease biomarkers, and discuss some of the critical challenges and perspectives in this field.

The proteomics big challenge for biomarkers and new drug-targets discovery

In the modern process of drug discovery, clinical, functional and chemical proteomics can converge and integrate synergies. Functional proteomics explores and elucidates the components of pathways and their interactions which, when deregulated, lead to a disease condition. This knowledge allows the design of strategies to target multiple pathways with combinations of pathway-specific drugs, which might increase chances of success and reduce the occurrence of drug resistance. Chemical proteomics, by analyzing the drug interactome, strongly contributes to accelerate the process of new druggable targets discovery. In the research area of clinical proteomics, proteome and peptidome mass spectrometry-profiling of human bodily fluid (plasma, serum, urine and so on), as well as of tissue and of cells, represents a promising tool for novel biomarker and eventually new druggable targets discovery. In the present review we provide a survey of current strategies of functional, chemical and clinical proteomics. Major issues will be presented for proteomic technologies used for the discovery of biomarkers for early disease diagnosis and identification of new drug targets.

Potentially novel candidate biomarkers for head and neck squamous cell carcinoma identified using an integrated cell line-based discovery strategy

Head and neck squamous cell carcinomas (HNSCC) can arise from the oral cavity, oropharynx, larynx or hypopharynx, and is the sixth leading cancer by incidence worldwide. The 5-year survival rate of HNSCC patients remains static at 40-60%. Hence, biomarkers which can improve detection of HNSCC or early recurrences should improve clinical outcome. Mass spectrometry-based proteomics methods have emerged as promising approaches for biomarker discovery. As one approach, mass-spectrometric identification of proteins shed or secreted from cancer cells can contribute to the identification of potential biomarkers for HNSCC and our understanding of tumor behavior. In the current study, mass spectrometry-based proteomic profiling was performed on the conditioned media (i.e. secretome) of head and neck cancer (HNC) cell lines (FaDu, UTSCC8 and UTSCC42a) in addition to gene expression microarrays to identify over-expressed transcripts in the HNSCC cells in comparison to a normal control cell line. This integrated data set was systematically mined using publicly available resources (Human Protein Atlas and published proteomic/transcriptomic data) to prioritize putative candidates for validation. Subsequently, quantitative real-time PCR (qRT-PCR), Western blotting, immunohistochemistry (IHC), and ELISAs were performed to verify selected markers. Our integrated analyses identified 90 putative protein biomarkers that were secreted or shed to the extracellular space and over-expressed in HNSCC cell lines, relative to controls. Subsequently, the over-expression of five markers was verified in vitro at the transcriptional and translational levels using qRT-PCR and Western blotting, respectively. IHC-based validation conducted in two independent cohorts comprising of 40 and 39 HNSCC biopsies revealed that high tumor expression of PLAU, IGFBP7, MMP14 and THBS1 were associated with inferior disease-free survival, and increased risk of disease progression or relapse. Furthermore, as demonstrated using ELISAs, circulating levels of PLAU and IGFBP7 were significantly higher in the plasma of HNSCC patients compared with healthy individuals.

Recent advances in biomarkers and potential targeted therapies in head and neck squamous cell carcinoma

Head and neck squamous cell carcinoma (HNSCC) is a devastating tumor of the upper aerodigestive tract with no significant change in treatment modality or improvement in survival over the last several decades. Biomarkers are important biological molecules that can be utilized in tumor detection, prognosis, and as targeted therapies. There are several important biomarkers and potential targets in the forefront, including biomarkers of tumorigenesis, signal transduction molecules, proteins involved in angiogenesis, and oncogenic viruses. The clinical applications of these biomarkers are in various states from in vitro and in vivo models, phase II and III clinical trials, to accepted modes of treatment in patients with HNSCC. Given the potential improvement in prognosis that biomarkers and their targeted therapies may have on the treatment of HNSCC, their investigation is both important and essential.

Application of genomic and proteomic technologies in biomarker discovery

Sequencing of the human genome was completed in 2001. Building on the technology and experience of whole-exome sequencing, numerous cancer genomes have been sequenced, including head and neck squamous cell carcinoma (HNSCC) in 2011. Although DNA sequencing data reveals a complex genome with numerous mutations, the biologic interaction and clinical significance of the overall genetic aberrations are largely unknown. Comprehensive analyses of the tumors using genomics and proteomics beyond sequencing data can potentially accelerate the rate and number of biomarker discoveries to improve biology-driven classification of tumors for prognosis and patient selection for a specific therapy. In this review, we will summarize the current genomic and proteomic technologies, general biomarker-discovery paradigms using the technology and published data in HNSCC-including potential clinical applications and limitations.

Serum amyloid a protein in clinical cancer diagnosis

The serum amyloid A (SAA) protein is an acute phase protein that is synthesized under the regulation of inflammatory cytokines during both acute and chronic inflammation. It is suggested that the SAA increases correlate with many types of carcinogenesis and neoplastic diseases. Th changes in SAA in serum could therefore indicate the progress and malignancy of the disease, as well as the host responses. The present paper reviewed the rationale of using SAA as potential cancer biomarker in clinical diagnosis, including the contribution and involvement of SAA in cancer growth and development. Then we discussed the current applications of SAA in diagnosis and tracing of different types of cancers. Finally the proteomics techniques, especially the SELDI-TOF MS to identify SAA in serum from patients were appreciated as an important manner in clinical diagnosis.

Clinicopathological pattern and Annexin A2 and Cdc42 status in patients presenting with differentiation and lymphnode metastasis of esophageal squamous cell carcinomas

Annexin A2 and Cdc42 were identified by 2-dimensional electrophoresis (2-DE) and MALDI-TOF-MS between esophageal squamous cell carcinomas (ESCC) and corresponding normal esophagus mucosa in our previous study. To assess clinico-pathological pattern and Annexin A2 and Cdc42 status with respect to cell differentiation and lymphnode metastasis in patients with ESCC. The expression of Annexin A2 and Cdc42 in 22 pairs of fresh ESCC and matched tissues were detected by qRT-PCR and western blot, respectively. And it was further confirmed by immunohistochemistry with 175 pairs of formalin-fixed, paraffin-embedded ESCC. Results showed that Annexin A2 expression was significantly down-regulated, and Cdc42 was up-regulated in ESCC compared to matched control on both mRNA and protein level (P < 0.05), which was in accordance with our previous results on proteomics data. Additionally, Annexin A2 and Cdc42 expression was significantly correlated with lymphoid node metastasis (P < 0.05) and pathological differentiation (P < 0.05). Taken together, we proposed that the aberrant expression of Annexin A2 and Cdc42 played a role in carcinogenesis, differentiation and metastasis of ESCC, which implied its potential target for clinical biomarkers in differentiation and lymph node metastasis.

Identification of proteins secreted by head and neck cancer cell lines using LC-MS/MS: Strategy for discovery of candidate serological biomarkers

In search of blood-based biomarkers that would enhance the ability to diagnose head and neck/oral squamous cell carcinoma (HNOSCC) in early stages or predict its prognosis, we analyzed the HNOSCC secretome (ensemble of proteins secreted and/or shed from the tumor cells) for potential biomarkers using proteomic technologies. LC-MS/MS was used to identify proteins in the conditioned media of four HNOSCC cell lines (SCC4, HSC2, SCC38, and AMOSIII); 140 unique proteins were identified on the basis of 5% global false discovery rate, 122 of which were secretory proteins, with 29 being previously reported to be overexpressed in HNOSCC in comparison to normal head and neck tissues. Of these, five proteins including α-enolase, peptidyl prolyl isomerase A/cyclophilin A, 14-3-3 ζ, heterogeneous ribonucleoprotein K, and 14-3-3 σ were detected in the sera of HNOSCC patients by Western blot analysis. Our study provides the evidence that analysis of head and neck cancer cells' secretome is a viable strategy for identifying candidate serological biomarkers for HNOSCC. In future, these biomarkers may be useful in predicting the likelihood of transformation of oral pre-malignant lesions, prognosis of HNOSCC patients and evaluate response to therapy using minimally invasive tests.

The cetuximab experience: developing predictive biomarkers in oncology

The anti-EGF receptor monoclonal antibody cetuximab provides a case study for the development of predictive biomarkers in oncology. The identification and validation of KRAS mutation status as a predictor of lack of benefit from cetuximab in metastatic colorectal cancer provides an important first step. However, KRAS mutation status does not appear to be predictive of cetuximab benefit in advanced non-small-cell lung cancer, illustrating the necessity for separate biomarker validation to occur across tumor types. Numerous candidate biomarkers have been suggested based on noncontrolled exploratory analyses, but they require validation in sufficiently sized controlled studies. Key pending issues include distinguishing markers predictive of treatment benefit from those prognostic of disease outcome, selecting the best specimen for analysis (determining the tissue type and collection site, as well as the sample matrix type); and optimizing and standardizing assay technology and scoring systems, particularly for markers expressed over a continuous dynamic range.