Proteomic patterns for early cancer detection

The human volatilome meets cancer diagnostics: past, present, and future of noninvasive applications

BACKGROUND

Cancer is a significant public health problem, causing dozens of millions of deaths annually. New cancer screening programs are urgently needed for early cancer detection, as this approach can improve treatment outcomes and increase patient survival. The search for affordable, noninvasive, and highly accurate cancer detection methods revealed a valuable source of tumor-derived metabolites in the human metabolome through the exploration of volatile organic compounds (VOCs) in noninvasive biofluids.

AIM OF REVIEW

This review discusses volatilomics-based approaches for cancer detection using noninvasive biomatrices (breath, saliva, skin secretions, urine, feces, and earwax). We presented the historical background, the latest approaches, and the required stages for clinical validation of volatilomics-based methods, which are still lacking in terms of making noninvasive methods available and widespread to the population. Furthermore, insights into the usefulness and challenges of volatilomics in clinical implementation steps for each biofluid are highlighted.

KEY SCIENTIFIC CONCEPTS OF REVIEW

We outline the methodologies for using noninvasive biomatrices with up-and-coming clinical applications in cancer diagnostics. Several challenges and advantages associated with the use of each biomatrix are discussed, aiming at encouraging the scientific community to strengthen efforts toward the necessary steps to speed up the clinical translation of volatile-based cancer detection methods, as well as discussing in favor of (i) hybrid applications (i.e., using more than one biomatrix) to describe metabolite modulations that can be "cancer volatile fingerprints" and (ii) in multi-omics approaches integrating genomics, transcriptomics, and proteomics into the volatilomic data, which might be a breakthrough for diagnostic purposes, onco-pathway assessment, and biomarker validations.

MALDI-TOF MS Analysis of Serum Peptidome Patterns in Cervical Cancer

BACKGROUND

Cervical cancer is the fourth most common cancer among females worldwide. Identifying peptide patterns discriminating healthy individuals from those with diseases has gained interest in the early detection of cancers. Our study aimed to determine signature peptide patterns for cervical cancer screening.

METHODS

Our study focused on the serum peptidome analysis of 83 healthy women and 139 patients with cervical cancer. All spectra derived from matrix-assisted laser desorption/ionization time-of-flight mass spectrometry were analyzed using FlexAnalysis 3.0 and ClinProTools 2.2 software.

RESULTS

In the mass range of 1000-10,000 Da, the total average spectra were represented as the signature pattern. Principal component analysis showed that all the groups were separately distributed. Furthermore, the peaks at m/z 1466.91, 1898.01, 3159.09, and 4299.40 significantly differed among the investigated groups (Wilcoxon/Kruskal-Wallis test and ANOVA, p < 0.001).

CONCLUSIONS

Laboratory-based rapid mass spectrometry showed that serum peptidome patterns could serve as diagnostic tools for diagnosing cervical cancer; however, verification through larger cohorts and association with clinical data are required, and the use of externally validated samples, such as patients with other types of cancers, should be investigated to validate the specific peptide patterns.

Evaluation of inflammatory cytokines and oxidative stress markers in prostate cancer patients undergoing curative radiotherapy

Prostate cancer is the second leading cause of cancer-related death in men. The present study was carried out to investigate the radiation response of serum cytokines and oxidative markers to find out if these novel biomarkers have significant applications regarding radiation outcome in prostate cancer patients. Significant elevations of prostatic specific antigen (PSA), asymmetric dimethyl arginine (ADMA) and nitric oxide (NO) were recorded in cancer prostate patients at the time of diagnosis compared to controls. Patients were subjected to radiotherapy post prostatectomy with a total dose of 66 Gy in 33 fractions (5 sessions/week) for 7 weeks. At the end of the seventh week post radiotherapy, ADMA levels were accentuated while the levels of PSA and NO were lower than before therapy. The level of inflammatory cytokines (interleukins IL-4, IL-5 and interferon-gamma) in post radiation therapy patients were significantly elevated compared to both controls and prostate cancer patients. A significant inverse correlation was observed in prostate cancer patients between ADMA and NO. Moreover, a significant inverse correlation in post radiation therapy patients was observed between IL-5 and PSA. These results are highly suggestive that there is a specific cytokine response in patients undergoing curative radiotherapy for prostate cancer.

Proteomics: A new perspective for cancer

In the past decades, several ground breaking discoveries in life science were made. The completion of sequencing the human genome certainly belongs to the key tasks successfully completed, representing a true milestone in the biomedicine. The accomplishment of the complete genome also brings along a new, even more challenging task for scientists: The characterization of the human proteome. Proteomics, the main tool for proteome research, is a relatively new and extremely dynamically evolving branch of science, focused on the evaluation of gene expression at proteome level. Due to the specific properties of proteins, current proteomics deals with different issues, such as protein identification, quantification, characterization of post-translational modification, structure and function elucidation, and description of possible interactions. This field incorporates technologies that can be applied to serum and tissue in order to extract important biological information in the form of biomarkers to aid clinicians and scientists in understanding the dynamic biology of their system of interest, such as a patient with cancer. The present review article provides a detail description of proteomics and its role in cancer research.

Cancer proteomics: many technologies, one goal

A major goal of the National Cancer Institute is to alleviate patient pain, suffering and death associated with cancer by the year 2015. This goal does not insinuate a cure for cancer, but rather the development of diagnostics and therapeutics that will eventually decrease cancer morbidity and mortality. A part of meeting this goal is to leverage the enormous data-gathering capabilities of proteomic technologies to discover disease-specific biomarkers in serum, plasma, urine, tissues and other biologic samples. The rapid advance in available technologies that have been spurred by the -omics era, has enabled biologic samples to be surveyed for biomarkers in ways never before possible. However, it is not yet clear which specific technologies will be the most successful. Therefore, proteomic laboratories within the National Cancer Institute are taking a multipronged approach to identify disease-specific biomarkers. This review discusses some of these approaches in their context of meeting the National Cancer Institute's 2015 goal.

Molecular profiling of cervical neoplasia

Cervical cancer, a potentially preventable disease, remains the second most common malignancy in women worldwide. Human papillomavirus is the single most important etiological agent in cervical cancer, contributing to neoplastic progression through the action of viral oncoproteins, mainly E6 and E7, which interfere with critical cell cycle pathways, p53 and retinoblastoma. However, evidence suggests that human papillomavirus infection alone is insufficient to induce malignant changes and that other host genetic variations are important in the development of cervical cancer. This article will discuss the latest molecular profiling techniques available and review the published literature relating to their role in the diagnosis and management of cervical dysplasia and cancer. It is hoped that these techniques will allow the detection of novel biomarkers at DNA, RNA, microRNA and protein levels, which may ultimately play a role in facilitating early disease diagnosis and in predicting response to therapies, thus allowing the development of personalized treatment strategies.

High throughput profiling of serum phosphoproteins/peptides using the SELDI-TOF-MS platform

Protein phosphorylation is a dynamic post-translational modification that plays a critical role in the regulation of a wide spectrum of biological events and cellular functions including signal transduction, gene expression, cell proliferation, and apoptosis. Determination of the sites and magnitudes of protein phosphorylation has been an essential step in the analysis of the control of many biological systems. A high throughput analysis of phosphorylation of proteins would provide a simple, logical, and useful tool for a functional dissection and prediction of biological functions and signaling pathways in association with these important molecular events. We have developed a functional proteomics technique using the ProteinChip array-based SELDI-TOF-MS analysis for high throughput profiling of phosphoproteins/phosphopeptides in human serum for the early detection and diagnosis as well as for the molecular staging of human cancer. The methodology and experimental approach consists of five steps: (1) generation of a total peptide pool of serum proteins by a global trypsin digestion; (2) rapid isolation of phosphopeptides from the total serum peptide pool by an affinity selection, purification, and enrichment using a novel automated micro-bioprocessing system with phospho-antibody-conjugated paramagnetic beads and a hybrid magnet plate; (3) high throughput phosphopeptide analysis on ProteinChip arrays by automated SELDI-TOF-MS; and (4) bioinformatics and statistical methods for data analysis. This method with appropriate modifications may be equally applicable to serine-, threonine- and tyrosine-phosphorylated proteins and for selectively isolating, profiling, and identifying phosphopeptides present in a highly complex phosphor-peptide mixture prepared from various human specimens such as cells, tissue samples, and serum and other body fluids.

Proteomics-based identification of spontaneous regression-associated proteins in neuroblastoma

BACKGROUND

Spontaneous regression is usually found in stage 4s neuroblastoma, whereas the elucidation of the underlying molecular mechanism(s) is still limited.

PURPOSE

Our study aims to investigate the pathogenesis of spontaneous regression at the protein level.

METHODS AND MATERIALS

Differential expression of proteins in stage 4s neuroblastoma tissue, in stage 4 neuroblastoma tissue, and in normal adrenal tissue was investigated by use of 2-dimensional difference gel electrophoresis (2D-DIGE).

RESULTS

Twenty-four protein spots were found to have significant changes among the different tissues, in which 16 proteins were identified using matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF-MS). Among these proteins, 7 proteins (RhoGDP-dissociation inhibitor 1, phosphatidylethanolamine-binding protein, prohibitin, etc) were up-regulated and 2 proteins (F-actin capping protein 1 subunit and aldose reductase) were down-regulated in stage 4s neuroblastoma compared with stage 4 neuroblastoma. The differential expression of selected candidate protein (RhoGDP-dissociation inhibitor 1 and CAPZA1) was further validated by western blotting.

CONCLUSION

Some proteins are differentially expressed between stage 4s and stage 4 neuroblastoma tissue, including those associated with differentiation and proliferation as well as apoptosis. RhoGDP-dissociation inhibitor 1 is highly expressed in stage 4s neuroblastoma tissue, whereas CAPZA1 is down-regulated.

Serum biomarkers which correlate with failure to respond to immunotherapy and tumor progression in a murine colorectal cancer model

PURPOSE

To advance our understanding of mechanisms involved in tumor progression/regression, a CT26 colorectal mouse model treated intra-tumorally with DISC-herpes simplex virus as immunotherapy was used in the discovery and validation phases to investigate and ultimately identify biomarkers correlating with the failure to respond to immunotherapy.

EXPERIMENTAL DESIGN

For the discovery phase, serum protein/peptide profiles of a retrospective sample collection (total n=70) were analyzed using MALDI-TOF-MS combined with artificial neural networks. Following identification of the key predictive peptides using ESI-MS/MS, validation of the identified proteins was carried out on serum and tissues collected in an independent sample set (total n=60).

RESULTS

Artificial neural network analysis resulted in four discriminatory peaks with an accuracy of 86%, sensitivity of 90% and specificity of 81% between the progressor/regressor groups. Three of the identified discriminatory markers were upregulated and demonstrated a positive correlation with tumor progression following DISC-herpes simplex virus therapy. Immunovalidation studies corroborated the MALDI-TOF-MS findings. Immunohistochemistry revealed that serum amyloid A-1 and serum amyloid P produced in the liver localized intracellularly in CT26 tumor tissue.

CONCLUSIONS

MALDI-TOF-MS and BI analysis of the serum proteome of tumor-bearer mice undergoing immunotherapy, identified biomarkers associating with "failure to respond" and biological arrays confirmed these findings.

Proteomics and biomarkers for ovarian cancer diagnosis

Ovarian cancer remains a leading cause of death from gynecological malignancy. Early diagnosis is the most important determinant of survival. Current diagnostic tools have had very limited success in early detection. In recent years, the advancing techniques for proteomics have accelerated the discovery of ovarian cancer biomarkers. Numerous proteomics-based molecular biomarkers/panels have been identified and hold great potential for diagnostic applications, but they need further development and validation. This article reviews recently published data on the diagnosis of ovarian cancer with proteomics, including the major proteomics technologies and promising strategies for biomarker discovery and development.

Microbead arrays for the analysis of ErbB receptor tyrosine kinase activation and dimerization in breast cancer cells

Receptor tyrosine kinases (RTKs) in the ErbB family (EGFR, ErbB2, ErbB3, and ErbB4) are implicated in a variety of human malignancies. Accordingly, determination of both expression and activation (dimerization/heterodimerization and phosphorylation) of ErbB proteins is critical in defining their functional role in cancer. Efficient and comprehensive methods to study molecular functions of ErbB family of RTKs are needed not only for improvements in diagnostics but also for early screening of targeted drugs (eg, small molecule inhibitors and therapeutic antibodies). We report development of 3 multiplex microbead immunoassays for simultaneous detection of expression, protein-protein interactions, and phosphorylation of these RTKs. These novel multiplex immunoassays were used to study ErbB RTKs under different cell activation conditions in 2 breast cancer cell lines (MDA-MB-453 and MDA-MB-468) and an epidermoid cancer cell line (A431). The results were confirmed by immunoprecipitation/western blot. Importantly, the multiplex immunoassay facilitated time-course studies in these cell lines after cell activation with EGF and neuregulin, revealing the kinetics of phosphorylation of the ErbB family RTKs. This study demonstrates the utility of the Luminex(R) multiplex system as an efficient and comprehensive approach to study different aspects of molecular roles of these RTKs. Importantly, the study provides proof-of-concept for the utility of the multiplex microbead immunoassay approach for potential use in efficient, robust, and rapid screening of drugs, particularly those targeting functional aspects of these potent signaling molecules. In addition, the assays described here may be useful for cancer diagnostics and monitoring efficacy of therapy targeting the ErbB family of RTKs.

The Sod2 mutant mouse as a model for oxidative stress: a functional proteomics perspective

Oxidative stress has been implicated in the pathogenesis of numerous human diseases and disorders, but the mechanistic basis often remains enigmatic. The Sod2 mutant mouse, which is sensitized to mitochondrial stress, is an ideal mutant model for studying the role of oxidative stress in a diverse range of complications arising from mitochondrial dysfunction and diminished antioxidant defense. To fully appreciate the widespread molecular consequences under increased oxidative stress, a systems approach utilizing proteomics is able to provide a global overview of the complex biological changes, which a targeted single biomolecular approach cannot address fully. This review focuses on the applications of mass spectrometry and functional proteomics in the Sod2 mouse. The combinatorial approach provides novel insights into the interplay of chemistry and biology, free radicals and proteins, thereby augmenting our understanding of how redox perturbations influence protein dynamics. Ultimately, this knowledge can lead to the development of free radical-targeted therapies.

Serum biomarker profiling in cancer studies: a question of standardisation?

Companion animals are exposed to similar environmental conditions and carcinogens as humans. In some animal cancers, there also appears to be the same genetic changes associated as in humans. However, little work has been carried out in cancer biomarker identification in animals. The recent dramatic advances in molecular medicine, genomics, proteomics and translational research will allow biomarker identification, which may provide the best strategies for veterinarians and clinicians to combat disease by early diagnosis and administration of effective treatments. Proteomics may have important applications in cancer diagnosis, prognosis and predictive clinical outcome that could directly change clinical practice by affecting critical elemen-ts of care and management. This review summarizes the advances in proteomics that has propelled us to this exciting age of clinical proteomics, and highlights the future work that is required for this to become a reality. In this review, we will discuss the available proteomic technologies and their limitations, and highlight the key areas of research and how they have been used to discover cancer biomarkers. The principles described here are equally applicable to human and animal disease, but implementation of 'omic' technologies requires stringent guidelines for collection of clinical material, the application of analytical techniques and interpretation of the data.

Clinical significance of tumor markers and an emerging perspective on colorectal cancer

Serum carcinoembryonic antigen (CEA) and CA19-9, a carbohydrate antigen recognized by the monoclonal antibody NS19-9, are commonly used as classical tumor markers in colorectal cancer (CRC) clinics. The roles of tumor markers include: (1) diagnostic screening (diagnostic markers); (2) prediction of prognosis after treatment (prognostic markers); and (3) judgment tools for treatment effect (surveillance markers). Tumor markers can be evaluated in serum, stools, or even in tissues depending on the clinical purpose. The American Society for Clinical Oncology recommends that CEA is the only marker of choice for monitoring the response of metastatic disease to systemic therapy at present. In the present paper, we are the first to review the clinical significance of the classical tumor markers CEA and CA19-9 in serum, allowing for our original data, and present our view on the newly emerging biomarkers in CRC. Novel promising biomarkers for diagnostic, prognostic, and surveillance purposes are reviewed and considered, some of which are anticipated for further validation. For diagnostic markers, urine or serum might replace fecal samples in the near future. On the other hand, prognostic or predictive markers for treatment sensitivity may be identified from the molecular profiles of primary cancer tissues. Selection of patients who are sensitive to chemotherapy will reduce the number of patients who undergo harmful chemotherapy with no effectiveness. The optimal tumor markers would be generalized, easy to assess, and accurate, and such markers are eagerly anticipated to enable personalized tailored therapy for CRC patients.

Practical approaches to proteomic biomarkers within prostate cancer radiotherapy trials

INTRODUCTION

Proteomic biomarkers may be useful for monitoring therapeutic response and to triage cancer patients to best therapy.

OBJECTIVES

In this review, we highlight the importance of specimen acquisition, preparation and analysis in radiotherapy proteomic studies. We also discuss practical approaches for the design and execution of clinical proteomic studies using our recent experience based on specimens accrued during prostate cancer radiation therapy.

DISCUSSION AND CONCLUSIONS

Numerous proteomic methods are being employed, including high-throughput mass spectrometry and immunoassays, and using solid tissues, blood and urine for analysis. Given the potential complexity of cytokine and other protein responses, there is a need to assess proteomic signatures within serial samples as longitudinal studies during a course of fractionated radiotherapy (RT).

Proteomic strategies in bladder cancer: From tissue to fluid and back

We have applied protein expression profiling technologies in combination with immunohistochemistry, using fresh tissue and urine samples, to assess bladder cancer heterogeneity and prognosis as well as to generate protein markers for tumor progression and early diagnosis of the disease. Here, we review some selected lines of investigation and approaches undertaken by our laboratory, drawing on more than 15 years of experience in bladder cancer proteomics, to highlight a number of issues that may be useful for researchers entering the field. In particular, we address the identification of markers for bladder cancer progression and exemplify the potential of gel-based proteomic profiling of urine samples for the early detection of urothelial carcinomas. In addition, we provide a brief description of a novel and highly promising source of biomarkers, the tumor interstitial fluid (TIF) that perfuses the tumor microenvironment.

From the genome to the proteome--biomarkers in colorectal cancer

BACKGROUND AND AIMS

Colorectal cancer is the second leading cause of cancer-related death. Current clinical practice in colorectal cancer screening (fecal occult blood test, FOBT; colonoscopy) has contributed to a reduction of mortality. However, despite these screening programs, about 70% of carcinomas are detected at advanced tumor stages (UICC III/IV) presenting poor patient prognosis. Thus, innovative tools and methodologies for early cancer detection can directly result in improving patient survival rates.

PATIENTS/METHODS

Biomedical research has advanced rapidly in recent years with the availability of technologies such as global gene and protein expression profiling. Comprehensive tumor profiling has become a field of intensive research aiming at identifying biomarkers relevant for improved diagnostics and therapeutics.

RESULTS

In this paper, we report a comprehensive review of genomic, transcriptomic, and proteomic approaches for biomarker identification in tissue and blood with a main emphasis on two-dimensional gel-electrophoresis (2-DE) and mass spectrometry analyses.

CONCLUSION

Proteomics-based technologies enable to distinguish the healthy patient from the tumor patient with high sensitivity and specificity and could greatly improve common classification systems and diagnostics. However, this progress has not yet been transferred from bench to bedside but could open the door to a more accurate and target specific personalized medicine with improved patient survival.

Epithelial ovarian cancer: disease etiology, treatment, detection, and investigational gene, metabolite, and protein biomarkers

Cancer research in recent years has immensely benefited from the development of novel technologies that enable scientists to perform detailed investigations of genomes, transcriptomes, proteomes, and metabolomes. This has invariably furthered knowledge of tumorigenesis and etiology of cancer. The resulting information can, in the foreseeable future, effect a significant change in the pace of cancer research, thereby producing improvements in patient care. Ovarian cancer in particular has received the interest of the scientific community, being the most frequent cause of death from gynecological cancers, characterized by few early symptoms, diagnosis at an advanced stage, as well as poor prognosis. Ovarian cancer is a malignancy in which normal ovarian cells begin to grow in an uncontrolled, abnormal manner and produce tumors in one or both ovaries. Epithelial cancers, the most common ovarian cancers (>80%), develop from cells lining the ovarian surface. Most ovarian cancer research is primarily focused on the early detection and treatment of epithelial ovarian cancer, the more common ovarian malignancy. This review offers an introduction to ovarian cancer, with particular emphasis on human epithelial ovarian cancer. Current methods of detection and therapy are discussed. A survey of promising new protein, gene, and metabolite biomarkers on the horizon is provided. Future prospects for improved diagnosis are offered.

Proteomics in neurosciences

This review provides an outline of the most important proteomic applications in the study of neurodegenerative disorders including Alzheimer's (AD), Parkinson's (PD), Huntington's (HD), and prion diseases, and also discusses advances in cancer and addiction. One of the scopes is to illustrate the potential of proteomics in the biomarkers discovery of these diseases. Finally, this article comments the advantages and drawbacks of the most commonly used techniques and methods for samples preparation.

Biomarkers and diagnosis; protein biomarkers in serum of pediatric patients with severe traumatic brain injury identified by ICAT-LC-MS/MS

This report is a feasibility study on the utility of gel-free proteomics in identifying peripheral biomarkers of brain injury. The study was performed in six pediatric patients admitted to the intensive care unit for severe traumatic brain injury (TBI). Serum samples collected at admission (less than 8 h after injury) were used for determining the levels of S100beta by enzyme-linked immunosorbent assay (ELISA) and for proteomics analyses. Serum samples were depleted of high abundant albumin and immunoglobulin, and were compared to a pooled reference from several healthy individuals. After labeling and separation on an ionic column, six different serum fractions were analyzed using Isotope-Coded Affinity Tag (ICAT), followed by tandem mass spectrometry (MS/MS) protein sequencing and identification. Ninety-five unique, differentially expressed proteins were identified, including several with a likely brain origin. Several proteins with pattern similarity to S100beta identified by hierarchical clustering could be considered for evaluation in a larger patient sample as potential peripheral markers of TBI.

European Organisation for Research and Treatment of Cancer (EORTC) Pathobiology Group standard operating procedure for the preparation of human tumour tissue extracts suited for the quantitative analysis of tissue-associated biomarkers

With the new concept of 'individualized treatment and targeted therapies', tumour tissue-associated biomarkers have been given a new role in selection of cancer patients for treatment and in cancer patient management. Tumour biomarkers can give support to cancer patient stratification and risk assessment, treatment response identification, or to identifying those patients who are expected to respond to certain anticancer drugs. As the field of tumour-associated biomarkers has expanded rapidly over the last years, it has become increasingly apparent that a strong need exists to establish guidelines on how to easily disintegrate the tumour tissue for assessment of the presence of tumour tissue-associated biomarkers. Several mechanical tissue (cell) disruption techniques exist, ranging from bead mill homogenisation and freeze-fracturing through to blade or pestle-type homogenisation, to grinding and ultrasonics. Still, only a few directives have been given on how fresh-frozen tumour tissues should be processed for the extraction and determination of tumour biomarkers. The PathoBiology Group of the European Organisation for Research and Treatment of Cancer therefore has devised a standard operating procedure for the standardised preparation of human tumour tissue extracts which is designed for the quantitative analysis of tumour tissue-associated biomarkers. The easy to follow technical steps involved require 50-300 mg of deep-frozen cancer tissue placed into small size (1.2 ml) cryogenic tubes. These are placed into the shaking flask of a Mikro-Dismembrator S machine (bead mill) to pulverise the tumour tissue in the capped tubes in the deep-frozen state by use of a stainless steel ball, all within 30 s of exposure. RNA is isolated from the pulverised tissue following standard procedures. Proteins are extracted from the still frozen pulverised tissue by addition of Tris-buffered saline to obtain the cytosol fraction of the tumour or by the Tris buffer supplemented with the non-ionic detergent Triton X-100, and, after high-speed centrifugation, are found in the tissue supernatant. The resulting tissue cell debris sediment is a rich source of genomic DNA.

Proteomic Analysis of Colorectal Cancer Reveals Alterations in Metabolic Pathways

Colorectal cancer is the second leading killer cancer worldwide and presently the most common cancer among males in Singapore. The study aimed to detect changes of protein profiles associated with the process of colorectal tumorigenesis to identify specific protein markers for early colorectal cancer detection and diagnosis or as potential therapeutic targets. Seven pairs of colorectal cancer tissues and adjacent normal mucosa were examined by two-dimensional gel electrophoresis at basic pH range (pH 7-10). Intensity changes of 34 spots were detected with statistical significance. 16 of the 34 spots were identified by MALDI-TOF/TOF tandem mass spectrometry. Changes in protein expression levels revealed a significantly enhanced glycolytic pathway (Warburg effect), a decreased gluconeogenesis, a suppressed glucuronic acid pathway, and an impaired tricarboxylic acid cycle. Observed changes in protein abundance were verified by two-dimensional DIGE. These changes reveal an underlying mechanism of colorectal tumorigenesis in which the roles of impaired tricarboxylic acid cycle and the Warburg effect may be critical.

A systems approach to clinical oncology: focus on breast cancer

During the past decade, genomic microarrays have been applied with some success to the molecular profiling of breast tumours, which has resulted in a much more detailed classification scheme as well as in the identification of potential gene signature sets. These gene sets have been applied to both the prognosis and prediction of outcome to treatment and have performed better than the current clinical criteria. One of the main limitations of microarray analysis, however, is that frozen tumour samples are required for the assay. This imposes severe limitations on access to samples and precludes large scale validation studies from being conducted. Quantitative reverse transcriptase polymerase chain reaction (qRT-PCR), on the other hand, can be used with degraded RNAs derived from formalin-fixed paraffin-embedded (FFPE) tumour samples, the most important and abundant source of clinical material available. More recently, the novel DASL (cDNA-mediated Annealing, Selection, extension and Ligation) assay has been developed as a high throughput gene expression profiling system specifically designed for use with FFPE tumour tissue samples.However, we do not believe that genomics is adequate as a sole prognostic and predictive platform in breast cancer. The key proteins driving oncogenesis, for example, can undergo post-translational modifications; moreover, if we are ever to move individualization of therapy into the practical world of blood-based assays, serum proteomics becomes critical. Proteomic platforms, including tissue micro-arrays (TMA) and protein chip arrays, in conjunction with surface-enhanced laser desorption ionization time-of-flight mass spectrometry (SELDI-TOF/MS), have been the technologies most widely applied to the characterization of tumours and serum from breast cancer patients, with still limited but encouraging results. This review will focus on these genomic and proteomic platforms, with an emphasis placed on the utilization of FFPE tumour tissue samples and serum, as they have been applied to the study of breast cancer for the discovery of gene signatures and biomarkers for the early diagnosis, prognosis and prediction of treatment outcome. The ultimate goal is to be able to apply a systems biology approach to the information gleaned from the combination of these techniques in order to select the best treatment strategy, monitor its effectiveness and make changes as rapidly as possible where needed to achieve the optimal therapeutic results for the patient.

Multiplex Analysis of Intracellular Signaling Pathways in Lymphoid Cells by Microbead Suspension Arrays

Phosphorylation analysis of signaling proteins is key for examining intracellular signaling pathways. Conventional biochemical approaches, e.g. immunoprecipitation, Western blot, and ELISA, have played a major role in elucidation of individual signaling events. However, these methods are laborious, time-consuming, and difficult to adapt for high throughput analysis. A multiplex approach to measure phosphorylation state of multiple signaling proteins simultaneously would significantly enhance the efficiency and scope of signaling pathway analysis for mechanistic studies and clinical application. This report describes a novel multiplex microbead suspension array approach to examine phosphoproteomic profiles in lymphoid cells. In the Jurkat T-cell leukemia line, the multiplex assay enabled targeted investigation of phosphorylation kinetics of signal transduction from receptor proximal events (tyrosine phosphoproteins CD3, Lck, Zap-70, and linker for T-cell activation) to cytosolic events (serine/threonine phosphoproteins Erk and Akt) to transcription factors (serine/threonine phosphorylated Rsk, cyclic AMP-response element-binding protein, and STAT3). To broaden the application of the multiplex analysis, signaling pathways were also studied in B-cell lymphoid tumor lines that included chronic lymphocytic leukemia lines. In these cell lines, multiplex suspension array enabled phosphoproteomic analysis of signaling cascade mediated by Syk, a homolog of Zap-70. Results obtained by multiplex analysis were confirmed by immunoprecipitation and Western blot methods. The examples of T-cell and B-cell signaling pathway analyses in this report demonstrate the utility of the multiplex suspension arrays to investigate phosphorylation dynamics and kinetics of several signaling proteins simultaneously in signal transduction pathways.

SELDI-TOF-MS proteomics of breast cancer

The detection, diagnosis, and management of breast cancer rely on an integrated approach using clinical history, physical examination, imaging, and histopathology. The discovery and validation of novel biomarkers will aid the physician in more effectively achieving this integration. This review discusses efforts in surface-enhanced laser desorption/ionization (SELDI)-based proteomics to address various clinical questions surrounding breast cancer, including diagnosis, monitoring, and stratification for treatment. Emphasis is placed on examining how study design and execution influence the discovery and validation process, which is critical to the proper development of potential clinical tests.

Proteome profile of the MCF7 cancer cell line: a mass spectrometric evaluation

The development of novel proteomic technologies that will enable the discovery of disease specific biomarkers is essential in the clinical setting to facilitate early diagnosis and increase survivability rates. We are reporting a shotgun two-dimensional (2D) strong cationic exchange/reversed-phase liquid chromatography/electrospray ionization tandem mass spectrometry (SCX/RPLC/ESI-MS/MS) protocol for the analysis of proteomic constituents in cancerous cells. The MCF7 breast cancer cell line was chosen as a model system. A series of optimization steps were performed to improve the LC/MS experimental setup, sample preparation, data acquisition and database search protocols, and a data filtering strategy was developed to enable confident identification of a large number of proteins and potential biomarkers. This research has resulted in the identification of >2000 proteins using multiple filtering and p-value sorting. Approximately 1600-1900 proteins had p < 0.001, and, of these, approximately 60% were matched by >or=2 unique peptides. Alternatively, >99% of the proteins identified by >or=2 unique peptides had p < 0.001. When searching the data against a reversed database of proteins, the rate of false positive identifications was 0.1% at the peptide level and 0.4% at the protein level. The typical reproducibility in detecting overlapping proteins across replicate runs exceeded 90% for proteins matched by >or=2 unique peptides. According to their biological function, approximately 200 proteins were involved in cancer-relevant cellular processes, and over 25 proteins were previously described in the literature as putative cancer biomarkers, as they were found to be differentially expressed between normal and cancerous cell states. Among these, biomarkers such PCNA, cathepsin D, E-cadherin, 14-3-3-sigma, antigen Ki-67, TP53RK, and calreticulin were identified. These data were generated by subjecting to MS analysis approximately 42 microg of sample, analyzing 16 SCX peptide fractions, and interpreting approximately 55,000 MS2 spectra. Total MS time required for analysis was 40 h.

The role of proteomics in the diagnosis and treatment of ovarian cancer

Ovarian cancer is the leading cause of gynecologic cancer death in the Western world and more than 70% of patients are diagnosed with advanced stage disease. The high mortality rate is due to the difficulty in the early detection of ovarian cancer. Current screening strategies lack the necessary sensitivity and specificity to reliably and accurately diagnose affected women, prompting investigators to seek alternative means of analysis found in protein pathways and networks. Proteomics seeks to advance the understanding of how proteins interact in cancer and may provide a mechanism for early stage diagnosis. The proteomic techniques of laser capture microdissection, mass spectrometry and tissue lysate arrays have led to the discovery of new biomarkers and the identification, development and approval of a number of targeted therapeutic agents. Following validation through clinical trials, the application of these techniques will contribute to the changing paradigm of cancer detection and treatment toward personalized medicine.

Killing time for cancer cells

As the signalling pathways that control cellular proliferation and death are unravelled, a range of targets have emerged as candidates for molecular cancer therapy. For their survival, cancer cells depend on a few highly activated signalling pathways; inhibition of these pathways has a strong apoptotic effect and can lead to tumour regression. But drugs that exploit this weakness, such as imatinib, have not cured patients: withdrawal of the drug leads to disease recurrence, and sustained treatment leads to the emergence of drug-resistant clones. Can cancer be cured, or will it have to be controlled as a chronic disease?

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Biomarkers: mining the biofluid proteome

Proteomics has brought with it the hope of identifying novel biomarkers for diseases such as cancer. This hope is built on the ability of proteomic technologies, such as mass spectrometry (MS), to identify hundreds of proteins in complex biofluids such as plasma and serum. There are many factors that make this research very challenging beginning with the lack of standardization of sample collection and continuing through the entire analytical process. Fortunately the advances made in the characterization of biofluids using proteomic techniques have been rapid and suggest that these mainly discovery driven approaches will lead to the development of highly specific platforms for diagnosing diseases and monitoring responses to different treatments in the near future.