Proteomic identification of serum biomarkers for head and neck cancer surveillance

Identification of a serum-based microRNA signature that detects recurrent oral squamous cell carcinoma before it is clinically evident

BACKGROUND

Survival rates for oral squamous cell carcinoma (OSCC) have remained poor for decades, a fact largely attributable to late-stage diagnoses and high recurrence rates. We report analysis of serum miRNA expression in samples from patients with high-risk oral lesions (HRL, including OSCC/carcinoma in situ lesions) and healthy non-cancer controls, with the aim of non-invasively detecting primary or recurrent disease before it is clinically evident.

METHODS

Discovery, test, and validation sets were defined from a total of 468 serum samples (305 HRL and 163 control samples). Samples were analysed using multiple qRT-PCR platforms.

RESULTS

A two-miRNA classifier comprised of miR-125b-5p and miR-342-3p was defined following discovery and test analyses. Analysis in an independent validation cohort reported sensitivity and specificity of ~74% for this classifier. Significantly, when this classifier was applied to serial serum samples taken from patients both before treatment and during post-treatment surveillance, it identified recurrence an average of 15 months prior to clinical presentation.

CONCLUSIONS

These results indicate this serum miRNA classifier is effective as a simple, non-invasive monitoring tool for earlier detection of recurrent disease when lesions are typically smaller and amenable to a wider array of treatment options to improve survival.

Discovery proteomics reveals potential protein signature associated with malignant phenotype acquisition in pleomorphic adenoma

OBJECTIVE

To analyze the proteomic profile of salivary pleomorphic adenoma (PA) and carcinoma ex pleomorphic adenoma (CXPA) samples and correlate them with the malignant transformation of the PA.

MATERIALS AND METHODS

Thirty samples (10 PA, 16 CXPA, and 4 residual PA) were microdissected and submitted to liquid chromatography-tandem mass spectrometry (LC-MS/MS). The proteomic data and protein identification were analyzed through LC-MS/MS spectra using the MaxQuant software.

RESULTS

The proteomic analysis identified and quantified a total of 240 proteins in which 135 were found in PA, residual PA, and CXPA. The shared proteins were divided into six subgroups, and the proteins that showed statistically significant differences (p > 0.05) and fold-change > or <2.5 in one subgroup to another subgroup were included. Seven proteins (Apolipoprotein A-I-APOA1, haptoglobin-HP, protein of the synaptonemal complex 1-SYCP1, anion transport protein of band 3-SLC4A1, subunit μ1 of AP-1 complex-AP1M1, beta subunit of hemoglobin-HBB, and dermcidin-DCD) were classified as potential protein signatures, being HP, AP1M1, and HBB with higher abundance for PA to residual PA, APOA1 with higher abundance for PA to CXPA, SLC4A1 with lower abundance in the PA to CXPA, SYCP1with lower abundance for residual PA to CXPA, and DCD with higher abundance in the CXPA with epithelial differentiation to myoepithelial differentiation.

CONCLUSIONS

In this work, we demonstrated the comparative proteomic profiling of PA, residual PA, and CXPA, and seven were proposed as protein signatures, some of which may be associated with the malignant phenotype acquisition.

High-Multiplex Aptamer-Based Serum Proteomics to Identify Candidate Serum Biomarkers of Oral Squamous Cell Carcinoma

Improved serological biomarkers are needed for the early detection, risk stratification and treatment surveillance of patients with oral squamous cell carcinoma (OSCC). We performed an exploratory study using advanced, highly specific, DNA-aptamer-based serum proteomics (SOMAscan, 1305-plex) to identify distinct proteomic changes in patients with OSCC pre- vs. post-resection and compared to healthy controls. A total of 63 significantly differentially expressed serum proteins (each p < 0.05) were found that could discriminate between OSCC and healthy controls with 100% accuracy. Furthermore, 121 proteins were detected that were significantly altered between pre- and post-resection sera, and 12 OSCC-associated proteins reversed to levels equivalent to healthy controls after resection. Of these, 6 were increased and 6 were decreased relative to healthy controls, highlighting the potential relevance of these proteins as OSCC tumor markers. Pathway analyses revealed potential pathophysiological mechanisms associated with OSCC. Hence, quantitative proteome analysis using SOMAscan technology is promising and may aid in the development of defined serum marker assays to predict tumor occurrence, progression and recurrence in OSCC, and to guide personalized therapies.

DIGE Analysis of Immunodepleted Plasma

This chapter focuses on upstream immunodepletion of high-abundance proteins from plasma samples and subsequent analysis by fluorescence two-dimensional difference gel electrophoresis (2D-DIGE). The abundances of proteins in biofluid proteomes, such as serum, plasma, saliva, and bronchoalveolar lavage fluid (BALF), can exceed ten orders of magnitude. This substantial dynamic range is problematic for the detection of medium and low-abundance proteins by 2D-DIGE analysis. To increase the detection, quantification, and identification of medium-low-abundance proteins, the targeted depletion of known abundant proteins with antibody columns has been successfully employed. From the literature, it is clear that the performance of abundant protein depletion with immunodepletion columns has been successful in broadening the coverage of the biofluid proteome and facilitating the identification of disease-specific biomarkers. The task for a successful biomarker strategy involves the combination of a reproducible and robust fractionation method, coupled with a highly accurate quantitative method, a task that is exemplified by combining both immunodepletion and 2D-DIGE together to discover significant proteins associated with the disease phenotype.

Proteomics for Early Detection of Non-Muscle-Invasive Bladder Cancer: Clinically Useful Urine Protein Biomarkers

Bladder cancer is the fourth most common cancer in men, and most cases are non-muscle-invasive. A high recurrence rate is a critical problem in non-muscle-invasive bladder cancer. The availability of few urine tests hinders the effective detection of superficial and small bladder tumors. Cystoscopy is the gold standard for diagnosis; however, it is associated with urinary tract infections, hematuria, and pain. Early detection is imperative, as intervention influences recurrence. Therefore, urinary biomarkers need to be developed to detect these bladder cancers. Recently, several protein candidates in the urine have been identified as biomarkers. In the present narrative review, the current status of the development of urinary protein biomarkers, including FDA-approved biomarkers, is summarized. Additionally, contemporary proteomic technologies, such as antibody-based methods, mass-spectrometry-based methods, and machine-learning-based diagnosis, are reported. Furthermore, new strategies for the rapid and correct profiling of potential biomarkers of bladder cancer in urine are introduced, along with their limitations. The advantages of urinary protein biomarkers and the development of several related technologies are highlighted in this review. Moreover, an in-depth understanding of the scientific background and available protocols in research and clinical applications of the surveillance of non-muscle bladder cancer is provided.

Lipoproteins and cancer: The role of HDL-C, LDL-C, and cholesterol-lowering drugs

Cholesterol is an amphipathic sterol molecule that is vital for maintaining normal physiological homeostasis. It is a relatively complicated molecule with 27 carbons whose synthesis starts with 2-carbon units. This in itself signifies the importance of this molecule. Cholesterol serves as a precursor for vitamin D, bile acids, and hormones, including estrogens, androgens, progestogens, and corticosteroids. Although essential, high cholesterol levels are associated with cardiovascular and kidney diseases and cancer initiation, progression, and metastasis. Although there are some contrary reports, current literature suggests a positive association between serum cholesterol levels and the risk and extent of cancer development. In this review, we first present a brief overview of cholesterol biosynthesis and its transport, then elucidate the role of cholesterol in the progression of some cancers. Suggested mechanisms for cholesterol-mediated cancer progression are plentiful and include the activation of oncogenic signaling pathways and the induction of oxidative stress, among others. The specific roles of the lipoprotein molecules, high-density lipoprotein (HDL) and low-density lipoprotein (LDL), in this pathogenesis, are also reviewed. Finally, we hone on the potential role of some cholesterol-lowering medications in cancer.

Identifying the role of apolipoprotein A-I in prostate cancer

Although localized prostate cancer (PCa) can be cured by prostatectomy and radiotherapy, the development of effective therapeutic approaches for advanced prostate cancer, including castration-resistant PCa (CRPC) and neuroendocrine PCa (NEPC), is lagging far behind. Identifying a novel prognostic and diagnostic biomarker for early diagnosis and intervention is an urgent clinical need. Here, we report that apolipoprotein A-I (ApoA-I), the major component of high-density lipoprotein (HDL), is upregulated in PCa based on both bioinformatics and experimental evidence. The fact that advanced PCa shows strong ApoA-I expression reflects its potential role in driving therapeutic resistance and disease progression by reprogramming the lipid metabolic network of tumor cells. Molecularly, ApoA-I is regulated by MYC, a frequently amplified oncogene in late-stage PCa. Altogether, our findings have revealed a novel indicator to predict prognosis and recurrence, which would benefit patients who are prone to progress to metastasis or even NEPC, which is the lethal subtype of PCa.

Advances in urinary biomarker discovery in urological research

A disease-specific biomarker (or biomarkers) is a characteristic reflecting a pathological condition in human body, which can be used as a diagnostic or prognostic tool for the clinical management. A urine-based biomarker(s) may provide a clinical value as attractive tools for clinicians to utilize in the clinical setting in particular to bladder diseases including bladder cancer and other bladder benign dysfunctions. Urine can be easily obtained by patients with no preparation or painful procedures required from patients' side. Currently advanced omics technologies and computational power identified potential omics-based novel biomarkers. An unbiased profiling based on transcriptomics, proteomics, epigenetics, metabolomics approaches et al. found that expression at RNA, protein, and metabolite levels are linked with specific bladder diseases and outcomes. In this review, we will discuss about the urine-based biomarkers reported by many investigators including us and how these biomarkers can be applied as a diagnostic and prognostic tool in clinical trials and patient care to promote bladder health. Furthermore, we will discuss how these promising biomarkers can be developed into a smart medical device and what we should be cautious about toward being used in real clinical setting.

Apolipoprotein A-I (ApoA-I), Immunity, Inflammation and Cancer

Apolipoprotein A-I (ApoA-I), the major protein component of high-density lipoproteins (HDL) is a multifunctional protein, involved in cholesterol traffic and inflammatory and immune response regulation. Many studies revealing alterations of ApoA-I during the development and progression of various types of cancer suggest that serum ApoA-I levels may represent a useful biomarker contributing to better estimation of cancer risk, early cancer diagnosis, follow up, and prognosis stratification of cancer patients. In addition, recent in vitro and animal studies disclose a more direct, tumor suppressive role of ApoA-I in cancer pathogenesis, which involves anti-inflammatory and immune-modulatory mechanisms. Herein, we review recent epidemiologic, clinicopathologic, and mechanistic studies investigating the role of ApoA-I in cancer biology, which suggest that enhancing the tumor suppressive activity of ApoA-I may contribute to better cancer prevention and treatment.

DIGE Analysis of Immunodepleted Plasma

This chapter will focus on upstream immunodepletion of high abundant proteins from plasma samples and subsequent analysis by difference gel electrophoresis (DIGE). The abundances of proteins in biofluid proteomes, such as serum, plasma, saliva, and bronchoalveolar lavage fluid (BALF), can exceed 10 orders of magnitude. This substantial dynamic range is problematic for the detection of medium and low abundance proteins by DIGE analysis. To increase the detection, quantification, and identification of medium-low abundant proteins, the targeted depletion of known abundant proteins with antibody columns has been successfully employed. From the literature, it is clear that the performance of abundant protein depletion with immunodepletion columns has been successful in broadening the coverage of the biofluid proteome and facilitating the identification of disease-specific biomarkers. The task for a successful biomarker strategy involves the combination of a reproducible and robust fractionation method, coupled with a highly accurate quantitative method, a task that is exemplified by combining both immunodepletion and DIGE together to discover significant proteins associated with the disease phenotype.

Identification of differentially expressed proteins in retinoblastoma tumors using mass spectrometry-based comparative proteomic approach

In India, retinoblastoma is among the top five childhood cancers. Children mostly present with extraocular extension and high risk features that results in unsatisfactory treatment and low survival rate. In addition, lack of potential therapeutic and prognostic targets is another challenge in the management of retinoblastoma. We studied comparative proteome of retinoblastoma patients (HPV positive and negative (n=4 each) and controls (n=4), in order to identify potential retinoblastoma-specific protein targets. 2D-DIGE coupled MALDI-TOF/TOF mass spectrometry identified 39 unique proteins. Highly deregulated proteins were GFAP,RBP3,APOA1,CRYAA,CRABP1,SAG and TF. Gene ontology (Panther 7.0) revealed majority of proteins to be associated with metabolic processes (26%) and catalytic activity (38%). 8 proteins were significantly upregulated in HPV positive vis-a-vis HPV negative cases. Patient group exhibited 12 upregulated and 18 downregulated proteins compared to controls. Pathway and network analysis (IPA software) revealed CTNNB1 as most significantly regulated signalling pathway in HPV positive than HPV negative retinoblastoma. The trends in transcriptional change of 9 genes were consistent with those at proteomic level. The Western blot analysis confirmed the expression pattern of RBP3,GFAP and CRABP1. We suggest GFAP,RBP3,CRABP1,CRYAAA,APOA1 and SAG as prospective targets that could further be explored as potential candidates in therapy and may further assist in studying the disease mechanism.

SIGNIFICANCE

In this study we evaluated tumor tissue specimens from retinoblastoma patients and identified 39 differentially regulated proteins compared to healthy retina. From these, we propose RBP3, CRABP1, GFAP, CRYAA, APOA1 and SAG as promising proteomic signatures that could further be explored as efficient prognostic and therapeutic targets in retinoblastoma. The present study is not only a contribution to the ongoing endeavour for the discovery of proteomic signatures in retinoblastoma, but, may also act as a starting point for future studies aimed at uncovering novel targets for further therapeutic interventions and improving patient outcomes.

Low expression of angiotensinogen and dipeptidyl peptidase 1 in saliva of patients with proliferative verrucous leukoplakia

AIM

To elucidate the profile of the salivary proteome.

METHODS

Unstimulated whole mouth saliva was collected from 30 volunteers [15 proliferative verrucous leukoplakia (PVL) patients and 15 controls] and proteins were submitted for mass spectrometry-based proteomics using the discovery approach, followed by analyses of variance and logistic regression tests.

RESULTS

A total of two hundred and eighty-three proteins were confidently identified in saliva. By combining two low abundance proteins from the PVL group, angiotensinogen (AGT) and dipeptidyl peptidase 1 (DPP1), a model for group differentiation was built with a concordance index of 94.2%, identifying both proteins as potential etiologic biomarkers for PVL.

CONCLUSION

This study suggests that both AGT and DPP1 may be involved in developmental mechanisms of PVL.

A proteomic approach to compare saliva from individuals with and without oral leukoplakia

BACKGROUND

Oral leukoplakia is the most common potentially malignant disorder in the oral cavity and can precede carcinoma. This study aimed to identify possible oral leukoplakia salivary biomarkers.

METHODS

Unstimulated saliva was collected from participants and protein concentration was determined. Proteins were then precipitated with cold acetone and separated using 2DE over a pH range of 3-10. Spot demarcation and matching were performed and protein identification was done through MS analysis. Oral leukoplakia tissues were submitted to immunohistochemistry analysis for keratin 10 (CK10). A complementary analysis of oral leukoplakias that were not included previously was performed in addition.

RESULTS

226±10 spots were identified in oral leukoplakia 2DE gels, and 262±12 spots were identified in volunteers. Twenty-two spots were highly abundant in oral leukoplakias or not detected in the control group, such as apolipoprotein A1, alpha amylase, cystatins, keratin 10, and lysozyme precursor. All were identified. All oral leukoplakia cases were immunopositive for CK10, mainly in the superficial epithelial layers.

CONCLUSIONS

The 2DE salivary protein profiles of individuals with and without oral leukoplakia were observably different. CK10 appears to be an interesting protein and should be further studied in oral carcinogenesis.

SIGNIFICANCE

MS-based proteomics enables large-scale analysis of proteins. Proteomics can provide detailed descriptions of proteomes of cells and tissues, including body fluids, and appears as a powerful tool to study human disorders. Saliva is readily accessible through non invasive collection and can mirror diverse disease states. Saliva from both diseased and healthy subjects can be analyzed through 2DE and differences between groups could be found. Routine immunohistochemistry analysis confirmed one of these findings, with CK10 being positive tissues from individuals with oral leukoplakia. Therefore, the present study allows insights into development of an important potential oral cancer precursor, named oral leukoplakia. However, the results can be extrapolated and tested in other precancer states, such as proliferative verrucous leukoplakia, patients at risk of oral cancer due to lifestyle behavior and/or cancer history in the family or even those who are under surveillance after a treated primary oral cancer.

Evaluation of potential circulating biomarkers for prediction of response to chemoradiation in patients with glioblastoma

Surgery followed by chemoradiation and adjuvant chemotherapy is standard of care for patients with a glioblastoma (GBM). Due to its limited benefit, an upfront method to predict dismal outcome would prevent unnecessary toxic treatment. We searched for a predictive blood derived biomarker in a cohort of 55 patients with GBM. Increasing age (HR 1.03, 95 % CI 1.01–1.06), and postoperative tumor residue (HR 1.07, 95 % CI 1.02–1.15) were independently associated with unfavourable progression free survival (PFS) in these patients. Corticosteroid use before start of chemoradiaton was strongly predictive for outcome (HR 3.26, 95 % CI 1.67–6.39) with a mean PFS and OS in patients using corticosteroids of 7.3 and 14.6 months, versus 16.1 and 21.6 months in patients not using corticosteroids (p = 0.0005, p < 0.0067 respectively). Despite earlier reports, blood concentrations of YKL-40, Fetuin-a and haptoglobin were not predictive for response. In addition, serum peptide profiles, determined by MALDI-TOF mass spectroscopy, were not predictive as well. In conclusion, further biomarker discovery studies are needed to predict treatment outcome for patients with GBM in the near future.

High level of serum apolipoprotein A-I is a favorable prognostic factor for overall survival in esophageal squamous cell carcinoma

Background

Noninvasive prognostic tools for esophageal squamous cell carcinoma (ESCC) are urgently needed. Serum lipids and lipoproteins are used for the prognosis of certain diseases; however, the prognostic value of serum apolipoprotein A-I (ApoA-I) in ESCC has not been described.

Methods

Pre-treatment serum lipids and lipoprotein concentrations (including ApoA-I, Apo-B, HDL-C, LDL-C, TC and TG) were analyzed retrospectively and compared between 210 patients with ESCC and 219 healthy controls. The prognostic significance of serum lipids and lipoproteins was determined by univariate and multivariate Cox hazard models in ESCC.

Results

Clinical characteristics (age, sex, pT status, pN status, pM status, pTNM status, histological differentiation or alcohol index) had no influence on baseline ApoA-I level. Serum ApoA-I, HDL-C, LDL-C, and TC levels were significantly lower and Apo-B was significantly higher in ESCC patients than in normal controls. On univariate analysis, ApoA-I, alcohol index, pT status, pN status and pTNM status were associated with significantly poor survival, and ApoA-I (p = 0.039), alcohol index (p = 0.037) and pTNM status (p = 0.000) were identified as prognostic factors associated with shorter survival in the multivariate analysis.

Conclusions

Overall survival was shorter in ESCC patients with decreased pre-treatment ApoA-I levels. Our findings suggest that serum ApoA-I level should be evaluated as a predictor of survival in patients with ESCC.

Apolipoproteins as Differentiating and Predictive Markers for Assessing Clinical Outcomes in Patients with Small Cell Lung Cancer

PURPOSE

The present study aimed to investigate the value of apolipoproteins, including ApoA-1, ApoC-III, and ApoE, in patients with small cell lung cancer (SCLC) as potential biomarkers for diagnosis, prognosis, and cancer progression.

MATERIALS AND METHODS

Lung samples were collected from 89 patients with SCLC. Nineteen lung samples from non-small cell lung cancer (NSCLC) patients and 12 normal lung tissues were used as controls. Expression profiles of ApoA-1, ApoC-III, and ApoE in different samples were examined using immunohistochemical methods, and the expression levels were correlated with cancer types, treatment, and outcomes using chi-square and Mann-Whitney tests.

RESULTS

Expression of ApoA-1 and ApoC-III in SCLC was significantly different, compared with that in NSCLC and normal lung tissues, and was correlated with recurrence of SCLC. Patients undergoing neoadjuvant chemotherapy before surgery showed significantly reduced expression of ApoA-1 and increased expression of ApoC-III and ApoE. Nevertheless, the expression levels of ApoA-1, ApoC-III, and ApoE were not correlated with SCLC staging.

CONCLUSION

ApoA-1 and ApoC-III may be used as differentiating and predictive markers for SCLC. ApoA-1, ApoC-III, and ApoE may be used to monitor the efficacy of chemotherapy.

Diagnostic accuracy of serum biomarkers for head and neck cancer: A systematic review and meta-analysis

Serum biomarkers could be helpful to characterize head and neck squamous cell carcinoma (HNSCC). Thus, the purpose of this systematic review and meta-analysis was to determine the diagnostic capability of serum biomarkers in the assessment of HNSCC patients. Studies were gathered by searching LILACS, PubMed, Science Direct, Scopus and Web of Science up to April 10th, 2015. Studies that focused on serum biomarkers in the diagnosis of HNSCC compared with controls were considered. Sixty-five studies were identified, and the sample size included 9098 subjects. Combined biomarkers demonstrated improved accuracy than those tested individually. Therefore, 12.8% of single and 34.3% of combined indicated that serum biomarkers discriminate patients with HNSCC from controls. The combined biomarkers with better diagnostic capability included Epidermal growth factor receptor (EGFR)+Cyclin D1 and squamous cell cancer-associated antigen (SCCA)+EGFR+Cyclin D1. Beta2-microglobin may also be a promising single biomarker for future studies. Serum biomarkers can be potentially useful in the diagnosis of HNSCC. However, further research is required to validate these biomarkers.

Genomics, microRNA, epigenetics, and proteomics for future diagnosis, treatment and monitoring response in upper GI cancers

One major objective for our evolving understanding in the treatment of cancers will be to address how a combination of diagnosis and treatment strategies can be used to integrate patient and tumor variables with an outcome-oriented approach. Such an approach, in a multimodal therapy setting, could identify those patients (1) who should undergo a defined treatment (personalized therapy) (2) in whom modifications of the multimodal therapy due to observed responses might lead to an improvement of the response and/or prognosis (individualized therapy), (3) who might not benefit from a particular toxic treatment regimen, and (4) who could be identified early on and thereby be spared the morbidity associated with such treatments. These strategies could lead in the direction of precision medicine and there is hope of integrating translational molecular data to improve cancer classifications. In order to achieve these goals, it is necessary to understand the key issues in different aspects of biotechnology to anticipate future directions of personalized and individualized diagnosis and multimodal treatment strategies. Providing an overview of translational data in cancers proved to be a challenge as different methods and techniques used to obtain molecular data are used and studies are based on different tumor entities with different tumor biology and prognoses as well as vastly different therapeutic approaches. The pros and cons of the available methodologies and the potential response data in genomics, microRNA, epigenetics and proteomics with a focus on upper gastrointestinal cancers are considered herein to allow for an understanding of where these technologies stand with respect to cancer diagnosis, prognosis and treatment.

Identification of RAB2A and PRDX1 as the potential biomarkers for oral squamous cell carcinoma using mass spectrometry-based comparative proteomic approach

Despite the recent advances in diagnostic and therapeutic strategies, oral squamous cell carcinoma (OSCC) remains a major health burden. Protein biomarker discovery for early detection will help to improve patient survival rate in OSCC. Mass spectrometry-based proteomics has emerged as an excellent approach for detection of protein biomarkers in various types of cancers. In the current study, we have used 4-Plex isobaric tags for relative and absolute quantitation (iTRAQ)-based shotgun quantitative proteomic approach to identify proteins that are differentially expressed in cancerous tissues compared to normal tissues. The high-resolution mass spectrometric analysis resulted in identifying 2,074 proteins, among which 288 proteins were differentially expressed. Further, it was noticed that 162 proteins were upregulated, while 125 proteins were downregulated in OSCC-derived cancer tissue samples as compared to the adjacent normal tissues. We identified some of the known molecules which were reported earlier in OSCC such as MMP-9 (8.4-fold), ZNF142 (5.6-fold), and S100A7 (3.5-fold). Apart from this, we have also identified some novel signature proteins which have not been reported earlier in OSCC including ras-related protein Rab-2A isoform, RAB2A (4.6-fold), and peroxiredoxin-1, PRDX1 (2.2-fold). The immunohistochemistry-based validation using tissue microarray slides in OSCC revealed overexpression of the RAB2A and PRDX1 gene in 80 and 68 % of the tested clinical cases, respectively. This study will not only serve as a resource of candidate biomarkers but will contribute towards the existing knowledge on the role of the candidate molecules towards disease progression and therapeutic potential.

Serological comparative proteomics analysis of mitochondrial autoantibody-negative and -positive primary biliary cirrhosis

Here, we investigated the pathogenesis of primary biliary cirrhosis (PBC) by using 2D-DIGE to analyze serological differences between anti-mitochondrial antibody (AMA)-positive and -negative PBC patients. The study comprised 30 patients with PBC; 20 AMA-positive and ten AMA-negative patients matched for age, sex, and pathological stage. A screening group (four AMA-positive and four AMA-negative patients) was used for 2D-DIGE. Protein spots that were differently abundant between the two groups were identified via dye intensity and MS. Nine candidate proteins were identified from these spots. Western blotting was used to verify two of the identified proteins, serum amyloid P-component (SAP) and vitronectin (VN). VN levels were significantly higher in the sera of AMA-negative PBC patients (p < 0.01), whereas no significant difference was found between the two groups for SAP. To our knowledge, this is the first study to use serological comparative proteomics to explore differences between AMA-positive and -negative PBC patients. VN levels were higher in AMA-negative PBC patients, and this finding could be related to the more severe bile duct destruction observed in this group.

Laser ionization mass spectrometry in oral squamous cell carcinoma

Biomarker research in oral squamous cell carcinoma (OSCC) aims for screening/early diagnosis and in predicting its recurrence, metastasis and overall prognosis. This article reviews the current molecular perspectives and diagnosis of oral cancer with proteomics using matrix-assisted laser desorption ionization (MALDI) and surface-enhanced laser desorption ionization (SELDI) mass spectrometry (MS). This method shows higher sensitivity, accuracy, reproducibility and ability to handle complex tissues and biological fluid samples. However, the data interpretation tools of contemporary mass spectrometry still warrant further improvement. Based on the data available with laser-based mass spectrometry, biomarkers of OSCC are classified as (i) diagnosis and prognosis, (ii) secretory, (iii) recurrence and metastasis, and (iv) drug targets. Majority of these biomarkers are involved in cell homeostasis and are either physiologic responders or enzymes. Therefore, proteins directly related to tumorigenesis have more diagnostic value. Salivary secretory markers are another group that offers a favourable and easy strategy for non-invasive screening and early diagnosis in oral cancer. Key molecular inter-related pathways in oral carcinogenesis are also intensely researched with software analysis to facilitate targeted drug therapeutics. The review suggested the need for incorporating 'multiple MS or tandem approaches' and focusing on a 'group of biomarkers' instead of single protein entities, for making early diagnosis and treatment for oral cancer a reality.

Plasma proteomics shows an elevation of the anti-inflammatory protein APOA-IV in chronic equine laminitis

Background

Equine laminitis is a devastating disease that causes severe pain in afflicted horses and places a major economic burden on the horse industry. In acute laminitis, the disintegration of the dermal-epidermal junction can cause the third phalanx to detach from the hoof wall, leaving the horse unable to bear weight on the affected limbs. Horses that survive the acute phase transition into a chronic form of laminitis, which is often termed “founder”. Some evidence suggests that chronic laminar inflammation might be associated with alterations in the endocrine and immune systems. We investigated this broad hypothesis by using DIGE to assess global differences in the plasma proteome between horses with chronic laminitis and controls.

Results

We identified 16 differentially expressed proteins; the majority of these were involved in the interrelated coagulation, clotting, and kininogen cascades. Clinical testing of functional coagulation parameters in foundered horses revealed a slight delay in prothrombin (PT) clotting time, although most other indices were within normal ranges. Upregulation of the intestinal apolipoprotein APOA-IV in horses with chronic laminitis was confirmed by western blot.

Conclusions

Our results support the hypothesis that localized laminar inflammation may be linked to systemic alterations in immune regulation, particularly in the gastrointestinal system. Gastrointestinal inflammation has been implicated in the development of acute laminitis but has not previously been associated with chronic laminitis.

Discovery of potential bladder cancer biomarkers by comparative urine proteomics and analysis

OBJECTIVE

We searched for bladder tumor markers by analyzing urine samples from patients with bladder cancer and from normal controls.

METHODS

Proteins in urine samples of patients with bladder cancer and with normal controls were systematically examined by 2-dimensional electrophoresis combined with matrix-assisted laser desorption ionization time-of-flight mass spectrometry. The expression of the protein apolipoprotein A-I (apoA-I) was confirmed by Western blot analysis and further evaluated.

RESULTS

We successfully obtained the 2-dimensional electrophoresis gel maps of urinary proteins in patients with bladder cancer and in normal controls. Thirty differentially expressed protein spots were successfully matched by matrix-assisted laser desorption ionization time-of-flight mass spectrometry. Combined with the SWISS-PROT database, only 14 proteins (beta-2-microglobulin, fatty acid-binding protein adipocyte, gelsolin, isoform 1 of gelsolin, myoglobin, isoform 2 of fibrinogen alpha chain, apoA-I, prostaglandin D(2) synthase 21 kDa [brain], protein AMBP, transthyretin, keratin type II cytoskeletal 1, type II cytoskeletal 8, putative uncharacterized protein ALB, putative uncharacterized protein MASP2 [fragment]) were identified, including 2 putative proteins. Furthermore, apoA-I was confirmed by Western blot analysis, and the high level of apoA-I was found in urine samples from patients with bladder tumors compared with normal controls.

CONCLUSIONS

Analysis of urinary proteome may be a feasible, noninvasive, and efficient strategy for searching for potential bladder tumor biomarkers. A significant relationship of expressed apoA-I was established between bladder cancer and normal controls. We concluded that 14 differential spots included the apoA-I and would be potential urinary biomarkers for the diagnosis and surveillance of bladder cancer.

Opportunities and challenges facing biomarker development for personalized head and neck cancer treatment

Head and neck oncologists have traditionally relied on clinical tumor features and patient characteristics to guide care of individual patients. As surgical, radiotherapeutic, and systemic treatments have evolved to become more anatomically precise and mechanistically specific, the opportunity for improved cure and functional patient recovery has never been more promising for this historically debilitating cancer. However, personalized treatment must be accompanied by sophisticated patient selection to triage the application of advanced therapies toward ideal patient candidates. In this monograph, we review current progress, investigative themes, and key challenges facing head and neck cancer biomarker development intended to make personalized head and neck cancer treatment a clinical reality.

Salivary Proteomic Signatures of Oral Squamous Cell Carcinoma

Delay in diagnosing oral squamous cell carcinoma (OSCC) can be still identified as a major cause of its high morbidity and mortality. To date, the early diagnosis for OSCC is mainly based on clinical oral examination and there is an urgent need for reliable markers; thus, advancements in molecular technologies has set the stage for investigating new markers, as well as new diagnostic matrices. The aim of the present study is to investigate the presence of proteomic signatures of OSCC in saliva and their use as potential biomarkers for early and non-invasive diagnosis. Saliva from 45 OSCC patients and 30 healthy controls was analysed by SELDI-TOF mass spectrometry and ProteinChip® technology. A supervised multivariate statistical analysis (Classification and Regression Tree - CART) was used to build models for discriminating between OSCC and controls, and between early (ES-OSCC) and late stage (LS-OSCC) cancers. The peptide with 8041 Da mass was 22-fold more expressed in OSCC, thus being a suitable potential biomarker. Classification and regression analysis allowed to build a model that was capable of correctly classifying all cancers and controls in an independent testing set, using the 8041 m/z peak as splitter. Eleven peaks were also differently expressed between ES-OSCCand LS-OSCC, but, basing on these differences, it was not possible to build an algorithm to predict tumour staging. These findings confirm that saliva proteome in OSCC patients is different from healthy controls and these variations might reflect different stages of disease progression and are worthy of further validation as diagnostic and prognostic biomarkers.

New advances in molecular approaches to head and neck squamous cell carcinoma

Head and neck squamous cell cancer is the sixth most common cancer in the world. Despite advances in combined modality therapy, poor outcomes continue to be observed in the form of locoregional recurrence, metastasis, and development of second primary tumors. As tumors vary in their molecular and genetic etiology and because often there is already deregulation at the molecular level in otherwise histopathologically normal tissue, risk stratification using clinical and pathologic criteria alone has proved to be inadequate. In this article, the reader will gain an appreciation for the current advances in biomarker discovery using advanced technology and data interpretation in microarray analysis and proteomics. In addition, other molecular targets, aside from epidermal growth factor receptor, are discussed in the context of their promising role in predicting recurrence, response to therapy, survival, and overall prognosis.

Mass spectrometry of peptides and proteins from human blood

It is difficult to convey the accelerating rate and growing importance of mass spectrometry applications to human blood proteins and peptides. Mass spectrometry can rapidly detect and identify the ionizable peptides from the proteins in a simple mixture and reveal many of their post-translational modifications. However, blood is a complex mixture that may contain many proteins first expressed in cells and tissues. The complete analysis of blood proteins is a daunting task that will rely on a wide range of disciplines from physics, chemistry, biochemistry, genetics, electromagnetic instrumentation, mathematics and computation. Therefore the comprehensive discovery and analysis of blood proteins will rank among the great technical challenges and require the cumulative sum of many of mankind's scientific achievements together. A variety of methods have been used to fractionate, analyze and identify proteins from blood, each yielding a small piece of the whole and throwing the great size of the task into sharp relief. The approaches attempted to date clearly indicate that enumerating the proteins and peptides of blood can be accomplished. There is no doubt that the mass spectrometry of blood will be crucial to the discovery and analysis of proteins, enzyme activities, and post-translational processes that underlay the mechanisms of disease. At present both discovery and quantification of proteins from blood are commonly reaching sensitivities of ∼1 ng/mL.

Discrimination of grade 2 and 3 cervical intraepithelial neoplasia by means of analysis of water soluble proteins recovered from cervical biopsies

Background

Cervical intraepithelial neoplasia (CIN) grades 2 and 3 are usually grouped and treated in the same way as "high grade", in spite of their different risk to cancer progression and spontaneous regression rates. CIN2-3 is usually diagnosed in formaldehyde-fixed paraffin embedded (FFPE) punch biopsies. This procedure virtually eliminates the availability of water-soluble proteins which could have diagnostic and prognostic value.

Aim

To investigate whether a water-soluble protein-saving biopsy processing method followed by a proteomic analysis of supernatant samples using LC-MS/MS (LTQ Orbitrap) can be used to distinguish between CIN2 and CIN3.

Methods

Fresh cervical punch biopsies from 20 women were incubated in RPMI1640 medium for 24 hours at 4°C for protein extraction and subsequently subjected to standard FFPE processing. P16 and Ki67-supported histologic consensus review CIN grade (CIN2, n = 10, CIN3, n = 10) was assessed by independent gynecological pathologists. The biopsy supernatants were depleted of 7 high abundance proteins prior to uni-dimensional LC-MS/MS analysis for protein identifications.

Results

The age of the patients ranged from 25-40 years (median 29.7), and mean protein concentration was 0.81 mg/ml (range 0.55 - 1.14). After application of multistep identification criteria, 114 proteins were identified, including proteins like vimentin, actin, transthyretin, apolipoprotein A-1, Heat Shock protein beta 1, vitamin D binding protein and different cytokeratins. The identified proteins are annotated to metabolic processes (36%), signal transduction (27%), cell cycle processes (15%) and trafficking/transport (9%). Using binary logistic regression, Cytokeratin 2 was found to have the strongest independent discriminatory power resulting in 90% overall correct classification.

Conclusions

114 proteins were identified in supernatants from fresh cervical biopsies and many differed between CIN2 and 3. Cytokeratin 2 is the strongest discriminator with 90% overall correct classifications.

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.

Secretome-based identification and characterization of potential biomarkers in thyroid cancer

In search of thyroid cancer biomarkers, proteins secreted by thyroid cancer cell lines, papillary-derived TPC-1 and anaplastic-derived CAL62, were analyzed using liquid chromatography-tandem mass spectrometry. Of 46 high-confidence identifications, 6 proteins were considered for verification in thyroid cancer patients' tissue and blood. The localization of two proteins, nucleolin and prothymosin-α (PTMA), was confirmed in TPC-1 and CAL62 cells by confocal microscopy and immunohistochemically in xenografts of TPC-1 cells in NOD/SCID/γ mice and human thyroid cancers (48 tissues). Increased nuclear and cytoplasmic expression of PTMA was observed in anaplastic compared to papillary and poorly differentiated carcinomas. Nuclear expression of nucleolin was observed in all subtypes of thyroid carcinomas, along with faint cytoplasmic expression in anaplastic cancers. Importantly, PTMA, nucleolin, clusterin, cysteine-rich angiogenic inducer 61, enolase 1, and biotinidase were detected in thyroid cancer patients' sera, warranting future analysis to confirm their potential as blood-based thyroid cancer markers. In conclusion, we demonstrated the potential of secretome analysis of thyroid cancer cell lines to identify novel proteins that can be independently verified in cell lines, xenografts, tumor tissues, and blood samples of thyroid cancer patients. These observations support their potential utility as minimally invasive biomarkers for thyroid carcinomas and their application in management of these diseases upon future validation.

Discovery of novel bladder cancer biomarkers by comparative urine proteomics using iTRAQ technology

A urine sample preparation workflow for the iTRAQ (isobaric tag for relative and absolute quantitation) technique was established. The reproducibility of this platform was evaluated and applied to discover proteins with differential levels between pooled urine samples from nontumor controls and three bladder cancer patient subgroups with different grades/stages (a total of 14 controls and 23 cancer cases in two multiplex iTRAQ runs). Combining the results of two independent clinical sample sets, a total of 638 urine proteins were identified. Among them, 55 proteins consistently showed >2-fold differences in both sample sets. Western blot analyses of individual urine samples confirmed that the levels of apolipoprotein A-I (APOA1), apolipoprotein A-II, heparin cofactor 2 precursor and peroxiredoxin-2 were significantly elevated in bladder cancer urine specimens (n = 25-74). Finally, we quantified APOA1 in a number of urine samples using a commercial ELISA and confirmed again its potential value for diagnosis (n = 126, 94.6% sensitivity and 92.0% specificity at a cutoff value of 11.16 ng/mL) and early detection (n = 71, 83.8% sensitivity and 94.0% specificity). Collectively, our results provide the first iTRAQ-based quantitative profile of bladder cancer urine proteins and represent a valuable resource for the discovery of bladder cancer markers.

Sample size and statistical power considerations in high-dimensionality data settings: a comparative study of classification algorithms

BACKGROUND

data generated using 'omics' technologies are characterized by high dimensionality, where the number of features measured per subject vastly exceeds the number of subjects in the study. In this paper, we consider issues relevant in the design of biomedical studies in which the goal is the discovery of a subset of features and an associated algorithm that can predict a binary outcome, such as disease status. We compare the performance of four commonly used classifiers (K-Nearest Neighbors, Prediction Analysis for Microarrays, Random Forests and Support Vector Machines) in high-dimensionality data settings. We evaluate the effects of varying levels of signal-to-noise ratio in the dataset, imbalance in class distribution and choice of metric for quantifying performance of the classifier. To guide study design, we present a summary of the key characteristics of 'omics' data profiled in several human or animal model experiments utilizing high-content mass spectrometry and multiplexed immunoassay based techniques.

RESULTS

the analysis of data from seven 'omics' studies revealed that the average magnitude of effect size observed in human studies was markedly lower when compared to that in animal studies. The data measured in human studies were characterized by higher biological variation and the presence of outliers. The results from simulation studies indicated that the classifier Prediction Analysis for Microarrays (PAM) had the highest power when the class conditional feature distributions were Gaussian and outcome distributions were balanced. Random Forests was optimal when feature distributions were skewed and when class distributions were unbalanced. We provide a free open-source R statistical software library (MVpower) that implements the simulation strategy proposed in this paper.

CONCLUSION

no single classifier had optimal performance under all settings. Simulation studies provide useful guidance for the design of biomedical studies involving high-dimensionality data.

Precipitation and selective extraction of human serum endogenous peptides with analysis by quadrupole time-of-flight mass spectrometry reveals posttranslational modifications and low-abundance peptides

The endogenous peptides of human serum may have regulatory functions, have been associated with physiological states, and their modifications may reveal some mechanisms of disease. In order to correlate levels of specific peptides with disease alongside internal standards, the polypeptides must first be reliably extracted and identified. Endogenous blood peptides can be effectively enriched by precipitation of the serum with organic solvents followed by selective extraction of peptides using aqueous solutions modified with organic solvents. Polypeptides on filter paper were assayed with Coomasie brilliant blue binding. The polypeptides were resolved by detergent tricine polyacrylamide electrophoresis and visualized by diamine silver staining. Peptides in the extracts were collected by C18 and analyzed by matrix-assisted laser desorption/ionization and liquid chromatography-electrospray ionization-tandem mass spectrometry (MS/MS) quadrupole time-of-flight MS/MS. Peptides were resolved as multiple isotopic peaks in MS mode with mass deviation of 0.1 Da or less and similar accuracy for fragments. The sensitivity of MS and MS/MS analysis was estimated to be in the picomolar range or less. The peptide composition of the extracts was dependent on solvent formulation. Multiple peptides from apolipoproteins, complement proteins, coagulation factors, and many others were identified by X!Tandem with high mass accuracy of peptide ions and fragments from collision-induced dissociation. Many previously unreported posttranslational modifications of peptides including phosphorylations, oxidations, glycosylations, and others were detected with high mass accuracy and may be of clinical importance. About 4,630 redundant peptides were identified with 99% confidence separately, and together some 1,251 distinct proteins were identified with 99% confidence or greater using the Paragon algorithm.