Clinical proteomics: from biomarker discovery and cell signaling profiles to individualized personal therapy

Harnessing the potential of reverse-phase protein array technology: Advancing precision oncology strategies

The last few decades have seen remarkable strides in the field of cancer therapy. Precision oncology coupled with comprehensive genomic profiling has become routine clinical practice for solid tumors, the advent of immune checkpoint inhibitors has transformed the landscape of oncology treatment, and the number of cancer drug approvals has continued to increase. Nevertheless, the application of genomics-driven precision oncology has thus far benefited only 10%-20% of cancer patients, leaving the majority without matched treatment options. This limitation underscores the need to explore alternative avenues with regard to selecting patients for targeted therapies. In contrast with genomics-based approaches, proteomics-based strategies offer a more precise understanding of the intricate biological processes driving cancer pathogenesis. This perspective underscores the importance of integrating complementary proteomic analyses into the next phase of precision oncology to establish robust biomarker-drug associations and surmount challenges related to drug resistance. One promising technology in this regard is the reverse-phase protein array (RPPA), which excels in quantitatively detecting protein modifications, even with limited amounts of sample. Its cost-effectiveness and rapid turnaround time further bolster its appeal for application in clinical settings. Here, we review the current status of genomics-driven precision oncology, as well as its limitations, with an emphasis on drug resistance. Subsequently, we explore the application of RPPA technology as a catalyst for advancing precision oncology. Through illustrative examples drawn from clinical trials, we demonstrate its utility for unraveling the molecular mechanisms underlying drug responses and resistance.

ErbB2pY -1248 as a predictive biomarker for Parkinson's disease based on research with RPPA technology and in vivo verification

AIMS

This study aims to reveal a promising biomarker for Parkinson's disease (PD) based on research with reverse phase protein array (RPPA) technology for the first time and in vivo verification, which gains time for early intervention in PD, thus increasing the effectiveness of treatment and reducing disease morbidity.

METHODS AND RESULTS

We employed RPPA technology which can assess both total and post-translationally modified proteins to identify biomarker candidates of PD in a cellular PD model. As a result, the phosphorylation (pY-1248) of the epidermal growth factor receptor (EGFR) ErbB2 is a promising biomarker candidate for PD. In addition, lapatinib, an ErbB2 tyrosine kinase inhibitor, was used to verify this PD biomarker candidate in vivo. We found that lapatinib-attenuated dopaminergic neuron loss and PD-like behavior in the zebrafish PD model. Accordingly, the expression of ErbB2pY-1248 significantly increased in the MPTP-induced mouse PD model. Our results suggest that ErbB2pY-1248 is a predictive biomarker for PD.

CONCLUSIONS

In this study, we found that ErbB2pY-1248 is a predictive biomarker of PD by using RPPA technology and in vivo verification. It offers a new perspective on PD diagnosing and treatment, which will be essential in identifying individuals at risk of PD. In addition, this study provides new ideas for digging into biomarkers of other neurodegenerative diseases.

Quantitative label-free mass spectrometry using contralateral and adjacent breast tissues reveal differentially expressed proteins and their predicted impacts on pathways and cellular functions in breast cancer

Proteins play an essential role in the biological processes associated with cancer. Their altered expression levels can deregulate critical cellular pathways and interactive networks. In this study, the mass spectrometry-based label-free quantification followed by functional annotation was performed to investigate the most significant deregulated proteins among tissues of primary breast tumor (PT) and axillary metastatic lymph node (LN) and corresponding non-tumor tissues contralateral (NCT) and adjacent (ANT) from patients diagnosed with invasive ductal carcinoma. A total of 462 proteins was observed as differentially expressed (DEPs) among the groups analyzed. A high level of similarity was observed in the proteome profile of both non-tumor breast tissues and DEPs (n = 12) were mainly predicted in the RNA metabolism. The DEPs among the malignant and non-tumor breast tissues [n = 396 (PTxNCT) and n = 410 (LNxNCT)] were related to pathways of the LXR/RXR, NO, eNOS, eIF2 and sirtuins, tumor-related functions, fatty acid metabolism and oxidative stress. Remarkable similarity was observed between both malignant tissues, which the DEPs were related to metastatic capabilities. Altogether, our findings revealed differential proteomic profiles that affected cancer associated and interconnected signaling processes. Validation studies are recommended to demonstrate the potential of individual proteins and/or pathways as biological markers in breast cancer. SIGNIFICANCE: The proteomic analysis of this study revealed high similarity in the proteomic profile of the contralateral and adjacent non-tumor breast tissues. Significant differences were identified among the proteome of the malignant and non-tumor tissue groups of the same patients, providing relevant insights into the hallmarks, signaling pathways, biological functions, and interactive protein networks that act during tumorigenesis and breast cancer progression. These proteins are suggested as targets of relevant interest to be explored as potential biological markers related to tumor development and metastatic progression in the breast cancer disease.

Utility of Reverse-Phase Protein Array for Refining Precision Oncology

Despite the early successes of targeted therapies and continuous improvements in next-generation sequencing technology over the last two decades, genomics-driven precision oncology has helped only a minority of cancer patients; thus treatment regimens are still not matched to the vast majority of cancer patients. It has become apparent that genomic profiling in itself is limited with respect to optimal selection of patients for targeted therapy. Proteomics-based approaches (in contrast to genomics-based and transcriptomics-based approaches) capture biological processes (e.g., diversity of protein expression patterns and post-translational modifications) directly contributing to cancer pathogenesis. This encourages incorporation of concordant proteomic analyses into the next stage of precision oncology. Reverse-phase protein array (RPPA) is well suited to pharmacodynamic analysis due to its ability to precisely map signaling status using limited amounts of clinical sample. In addition, the cost-effectiveness and rapid turnaround time of the RPPA platform offer a substantial advantage over existing molecular profiling technologies in a clinical setting. In this chapter, we begin by reviewing the current status of genomics-driven precision oncology, along with its limitations and challenges. Finally, we discuss the utility of RPPA technology as a means of improving precision oncology.

Understanding the Pathological Basis of Neurological Diseases Through Diagnostic Platforms Based on Innovations in Biomedical Engineering: New Concepts and Theranostics Perspectives

The pace of advancement of genomics and proteomics together with the recent understanding of the molecular basis behind rare diseases could lead in the near future to significant advances in the diagnosing and treating of many pathological conditions. Innovative diagnostic platforms based on biomedical engineering (microdialysis and proteomics, biochip analysis, non-invasive impedance spectroscopy, etc.) are introduced at a rapid speed in clinical practice: this article primarily aims to highlight how such platforms will advance our understanding of the pathological basis of neurological diseases. An overview of the clinical challenges and regulatory hurdles facing the introduction of such platforms in clinical practice, as well as their potential impact on patient management, will complement the discussion on foreseeable theranostic perspectives. Indeed, the techniques outlined in this article are revolutionizing how we (1) identify biomarkers that better define the diagnostic criteria of any given disease, (2) develop research models, and (3) exploit the externalities coming from innovative pharmacological protocols (i.e., those based on monoclonal antibodies, nanodrugs, etc.) meant to tackle the molecular cascade so far identified.

New Insights into the Tumor Microenvironment Utilizing Protein Array Technology

The tumor microenvironment (TME) is a considerably heterogeneous niche, which is created by tumor cells, the surrounding tumor stroma, blood vessels, infiltrating immune cells, and a variety of associated stromal cells. Intercellular communication within this niche is driven by soluble proteins synthesized by local tumor and stromal cells and include chemokines, growth factors, interferons, interleukins, and angiogenic factors. The interaction of tumor cells with their microenvironment is essential for tumorigenesis, tumor progression, growth, and metastasis, and resistance to drug therapy. Protein arrays enable the parallel detection of hundreds of proteins in a small amount of biological sample. Recent data have demonstrated that the application of protein arrays may yield valuable information regarding the structure and functional mechanisms of the TME. In this review, we will discuss protein array technologies and their applications in TME analysis to discern pathways involved in promoting the tumorigenic phenotype.

Signaling pathway profiling using reverse-phase protein array and its clinical applications

INTRODUCTION

Increased accessibility to next-generation sequencing within the last decade has led to a paradigm shift in cancer treatment from one-size-fits-all medicine to precision medicine providing therapeutic strategies tailored to the requirements of individual patients. However, the effect of even the most successful agent yet tested is only transient, and durable efficacy has yet to be achieved. Genome- and transcriptome-based approaches cannot fully predict the diversity of protein expression patterns or post-translational modifications that directly contribute to cancer pathogenesis and physiology. This underscores the need for concordant proteomic analysis in the next stage of precision medicine. Areas covered: This review begins with an overview of the recent advances and trends in precision medicine that currently rely on genomics, and highlights the utility of antibody-based reverse-phase protein array (RPPA) technology as a proteomic tool in this context. Expert commentary: RPPA is well suited for pharmacodynamics analysis in view of its ability to precisely map signaling status using limited amounts of clinical samples. In addition, the cost-effectiveness and rapid turn-around time of the RPPA platform offer a substantial advantage over existing molecular profiling technologies in clinical settings.

Studying the effect of microwave heating on the digestion process and identification of proteins

The impact of microwave irradiation on the in-solution digestion processes and the detection limit of proteins are systematically studied. Kinetic processes of many peptides produced through the trypsin digestion of various proteins under microwave heating at 50°C were investigated with MALDI-MS. This study also examines the detection limits and digestion completeness of individual proteins under microwave heating at 50°C and at different time intervals (1, 5 and 30 min) using LC-MS. We conclude that if the peptides without missed cleavage dictate the detection limit, conventional digestion will lead to a better detection limit. The detection limit may not differ between the microwave and conventional heating if the peptides with missed cleavage sites and strong intensity are formed at the very early stage (i.e., less than 1 min) and are not further digested throughout the entire digestion process. The digestion of Escherichia coli lysate was compared under conventional and short time (microwave) conditions. The number of proteins identified under conventional heating exceeded that obtained from microwave heating over heating periods less than 5 min. The overall results show that the microwave-assisted digestion is not complete. Although the sequence coverage might be better, the detection limit might be worse than that under conventional heating.

Copolymer Brush-Based Ultralow-Fouling Biorecognition Surface Platform for Food Safety

Functional polymer coatings that combine the ability to resist nonspecific fouling from complex media with high biorecognition element (BRE) immobilization capacity represent an emerging class of new functional materials for a number of bioanalytical and biosensor technologies for medical diagnostics, security, and food safety. Here, we report on a random copolymer brush surface - poly(CBMAA-ran-HPMAA) - providing high BRE immobilization capacity while simultaneously exhibiting ultralow-fouling behavior in complex food media. We demonstrate that both the functionalization and fouling resistance capabilities of such copolymer brushes can be tuned by changing the surface contents of the two monomer units: nonionic N-(2-hydroxypropyl) methacrylamide (HPMAA) and carboxy-functional zwitterionic carboxybetaine methacrylamide (CBMAA). It is demonstrated that the resistance to fouling decreases with the surface content of CBMAA; poly(CBMAA-ran-HPMAA) brushes with CBMAA molar content up to 15 mol % maintain excellent resistance to fouling from a variety of homogenized foods (hamburger, cucumber, milk, and lettuce) even after covalent attachment of BREs to carboxy groups of CBMAA. The poly(CBMAA 15 mol %-ran-HPMAA) brushes functionalized with antibodies are demonstrated to exhibit fouling resistance from food samples by up to 3 orders of magnitude better when compared with the widely used low-fouling carboxy-functional oligo(ethylene glycol) (OEG)-based alkanethiolate self-assembled monolayers (AT SAMs) and, furthermore, by up to 2 orders of magnitude better when compared with the most successful ultralow-fouling biorecognition coatings - poly(carboxybetaine acrylamide), poly(CBAA). When model SPR detections of food-borne bacterial pathogens in homogenized foods are used, it is also demonstrated that the antibody-functionalized poly(CBMAA 15 mol %-ran-HPMAA) brush exhibits superior biorecognition properties over the poly(CBAA).

Proteomics studies in inner ear disorders: pathophysiology and biomarkers

Although proteomics has been exploited in a wide range of diseases for identification of biomarkers and pathophysiological mechanisms, there are still biomedical disciplines such as otology where proteomics platforms are underused due to technical challenges and/or complex features of the disease. Thus, in the past few years, healthcare and scientific agencies have advocated the development and adoption of proteomic technologies in otological research. However, few studies have been conducted and limited literature is available in this area. Here, we present the state of the art of proteomics in otology, discussing the substantial evidence from recent experimental models and clinical studies in inner-ear conditions. We also delineate a series of critical issues including minute size of the inner ear, delicacy and poor accessibility of tissue that researchers face while undertaking otology proteomics research. Furthermore, we provide perspective to enhance the impact and lead to the clinical implementation of these proteomics-based strategies.

Signaling pathway profiling by reverse-phase protein array for personalized cancer medicine

Deregulation of intracellular signaling through accumulation of genetic alterations is a hallmark of cancer. In the past few decades, concerted and systematic efforts have been made to identify key genetic alterations and to develop therapeutic agents targeting active signaling molecules. However, the efficacy of molecular therapeutics often varies among individuals, and precise mapping of active molecules in individual patients is now considered an essential for therapy optimization. Reverse-phase protein array or microarray (RPPA or RPPM) is an emerging antibody-based highly quantitative proteomic technology, especially suitable for profiling of expression and modification of signaling proteins in low abundance. Because the supply of clinical materials is often limited, RPPA technology is highly advantageous for clinical proteomics in view of its high sensitivity as well as accurate quantification. RPPA has now begun to be incorporated into various clinical trials employing molecular-targeted therapeutics. In this article we review and discuss the application of RPPA technology in the fields of basic, preclinical, and clinical research. The RPPA Global Workshop was recently launched to accelerate the exchange of rapidly expanding knowledge of this fascinating technology among academic laboratories and industries worldwide. This article is part of a Special Issue entitled: Medical Proteomics.

Role and challenges of proteomics in pharma and biotech: technical, scientific and commercial perspective

Contemporary proteomics, currently in its exponential growth phase, is a bewildering array of tools. Proteomic methods are the result of a convergence of rapidly improving mass spectrometry technologies, protein chemistry and separation sciences, genomics and bioinformatics. Strides in improving proteomics technologies to map and measure proteomes and subproteomes are being made. However, no single proteomic platform appears ideally suited to address all research needs or accomplish ambitious goals satisfactorily. However, proteomics is in a unique position to contribute to protein discovery and to public health in terms of better biomarkers, diagnostics and treatment of disease. While the potential is great, many challenges and issues remain to be solved. Fundamental issues, such as biological variability, pre-analytic factors and analytical reproducibility, remain to be resolved. Neither an all-genetic approach nor an all-proteomic approach will solve biological complexity. Proteomics will be the foundation for constructing and extracting useful knowledge to pharma and biotech depicted in the following path: data --> structured data --> information --> information architecture --> knowledge --> useful knowledge.

Shotgun-proteomics-based clinical testing for diagnosis and classification of amyloidosis

Shotgun proteomics technology has matured in the research laboratories and is poised to enter clinical laboratories. However, the road to this transition is sprinkled with major technical unknowns such as long-term stability of the platform, reproducibility of the technology and clinical utility over traditional antibody-based platforms. Further, regulatory bodies that oversee the clinical laboratory operations are unfamiliar with this new technology. As a result, diagnostic laboratories have avoided using shotgun proteomics for routine diagnostics. In this perspectives article, we describe the clinical implementation of a shotgun proteomics assay for amyloid subtyping, with a special emphasis on standardizing the platform for better quality control and earning clinical acceptance. This assay is the first shotgun proteomics assay to receive regulatory approval for patient diagnosis. The blueprint of this assay can be utilized to develop novel proteomics assays for detecting numerous other disease pathologies.

Designing a ligand for pharmaceutical purposes

BACKGROUND

Drug approval applications to the FDA have shown a remarkably small increment compared with what was expected. In the last few years several efforts have been made to improve the results of rational drug design approaches and in particular to predict inhibitor-target structure and to evaluate the free energy of binding. Virtual database screening, combined with other computational methods, is one of the most promising methods to overcome this key issue.

OBJECTIVE

It is possible to understand how computational medicinal chemistry is changing, improving from its errors and moving towards becoming a more important tool for drug development.

METHODS

Some of the most recent modeling techniques have been presented and in particular the benefits of combining these techniques are highlighted.

RESULTS/CONCLUSION

At present computational chemists can understand the peculiar problems associated with the study of biological systems and on this basis they can choose the right collection of complementary in silico approaches to solve the medicinal chemistry problem in a better manner.

MALDI imaging of post-mortem human spinal cord in amyotrophic lateral sclerosis

Amyotrophic lateral sclerosis (ALS) is a devastating, rapidly progressing disease of the central nervous system that is characterized by motor neuron degeneration in the brainstem and the spinal cord. Matrix-assisted laser desorption/ionization (MALDI) imaging mass spectrometry is an emerging powerful technique that allows for spatially resolved, comprehensive, and specific characterization of molecular species in situ. In this study, we report for the first time the MALDI imaging-based spatial protein profiling and relative quantification of post-mortem human spinal cord samples obtained from ALS patients and controls. In normal spinal cord, protein distribution patterns were well in line with histological features. For example, thymosin beta 4, ubiquitin, histone proteins, acyl-CoA-binding protein, and macrophage inhibitory factor were predominantly localized to the gray matter. Furthermore, unsupervised statistics revealed a significant reduction of two protein species in ALS gray matter. One of these proteins (m/z 8451) corresponds to an endogenous truncated form of ubiquitin (Ubc 1-76), with both C-terminal glycine residues removed (Ubc-T/Ubc 1-74). This region-specific ubiquitin processing suggests a disease-related change in protease activity. These results highlight the importance of MALDI mass spectrometry as a versatile approach to elucidate molecular mechanisms of neurodegenerative diseases.

Proteomic analysis of cerebrospinal fluid in a fulminant case of multiple sclerosis

Multiple Sclerosis (MS) is a chronic disease, but in rare fulminant cases rapid progression may lead to death shortly after diagnosis. Currently there is no diagnostic test to predict disease course. The aim of this study was to identify potential biomarkers/proteins related to rapid progression. We present the case history of a 15-year-old male MS patient. Cerebrospinal fluid (CSF) was taken at diagnosis and at the time of rapid progression leading to the patient’s death. Using isobaric tag labeling and nanoflow liquid chromatography in conjunction with matrix assisted laser desorption/ionization time of flight tandem mass spectrometry we quantitatively analyzed the protein content of two CSF samples from the patient with fulminant MS as well as one relapsing-remitting (RR) MS patient and one control headache patient, whose CSF analysis was normal. Seventy-eight proteins were identified and seven proteins were found to be more abundant in both fulminant MS samples but not in the RR MS sample compared to the control. These proteins are involved in the immune response, blood coagulation, cell proliferation and cell adhesion. In conclusion, in this pilot study we were able to show differences in the CSF proteome of a rapidly progressing MS patient compared to a more typical clinical form of MS and a control subject.

Protein pathway activation mapping reveals molecular networks associated with antiestrogen resistance in breast cancer cell lines

Previously, we have identified a panel of breast cancer antiestrogen resistance (BCAR) genes. Several of these genes have clinical relevance because mRNA or protein levels associate with tamoxifen resistance or tumor aggressiveness. We postulated that changes in activation status of protein signaling networks induced by BCAR genes may provide better insight into the mechanisms underlying antiestrogen resistance. Key signal transduction pathways were analyzed for changes in activation or expression using reverse-phase protein microarrays probed with 78 antibodies against signaling proteins with known roles in tumorigenesis. We used ZR-75-1-derived cell lines transduced with AKT1, AKT2, BCAR1, BCAR3, BCAR4, EGFR, GRB7, HRAS, HRAS(v12) or HEF1 and MCF7-derived cell lines transduced with BCAR3, BCAR4 or EGFR. In the antiestrogen-resistant cell lines, we observed increased phosphorylation of several pathways involved in cell proliferation and survival. All tamoxifen-resistant cell lines contained high levels of phosphorylated AKT and its biochemically linked substrates Forkhead box O1/3. The activation of ERBB2, ERBB3 and the downstream modulators focal adhesion kinase and SHC were activated in cells with overexpression of BCAR4. Remarkable differences were observed for the levels of activated AMPK alpha1, cyclins, STAT5, STAT6, ERK1/2 and BCL2. The comparison of the cell signaling networks in estrogen-dependent and -independent cell lines revealed biochemically linked kinase-substrate markers that comprised systemically activated signaling pathways involved in tamoxifen resistance. Our results show that this model provides insights into the molecular and cellular mechanisms of breast cancer progression and antiestrogen resistance. This knowledge may help the development of novel targeted treatments.

Identification of troponin I and actin, alpha cardiac muscle 1 as potential biomarkers for hearts of electrically stimulated chickens

Methods

In this study, proteomics methods have been used to study the effects of different currents and voltages used to stun chickens. Protein profiles of chicken hearts were constructed to detect differences in protein expression and modification. The different voltages studied were 10 V, 40 V and 70 V, while the currents examined were 0.25 A, 0.5 A, and 0.75 A. The profiles obtained from these stunning conditions were compared to the non-stunned (0 A, 0 V) sample.

Results

Proteomics analyses using 2D Platinum ImageMaster 6.0 and Matrix-assisted laser desorption/ionization with time-of-flight mass spectrometry (MALDI-TOF) identified troponin I and alpha cardiac muscle actin 1 in the electrically stimulated heart samples. The overexpression of the proteins was further confirmed at the transcriptional level by Real Time PCR.

Conclusion

The results from MALDI-TOF and Real Time PCR agreed; therefore, this method for identifying biomarkers of electrically stimulated chicken hearts provides a novel approach for differentiation the hearts of increased electrically stimulated chickens from those of non-stunned chickens.

Phosphoproteomic analysis of signaling pathways in head and neck squamous cell carcinoma patient samples

Molecular targeted therapy represents a promising new strategy for treating cancers because many small-molecule inhibitors targeting protein kinases have recently become available. Reverse-phase protein microarrays (RPPAs) are a useful platform for identifying dysregulated signaling pathways in tumors and can provide insight into patient-specific differences. In the present study, RPPAs were used to examine 60 protein end points (predominantly phosphoproteins) in matched tumor and nonmalignant biopsy specimens from 23 patients with head and neck squamous cell carcinoma to characterize the cancer phosphoproteome. RPPA identified 18 of 60 analytes globally elevated in tumors versus healthy tissue and 17 of 60 analytes that were decreased. The most significantly elevated analytes in tumor were checkpoint kinase (Chk) 1 serine 345 (S345), Chk 2 S33/35, eukaryotic translation initiation factor 4E-binding protein 1 (4E-BP1) S65, protein kinase C (PKC) ζ/ι threonine 410/412 (T410/T412), LKB1 S334, inhibitor of kappaB alpha (IκB-α) S32, eukaryotic translation initiation factor 4E (eIF4E) S209, Smad2 S465/67, insulin receptor substrate 1 (IRS-1) S612, mitogen-activated ERK kinase 1/2 (MEK1/2) S217/221, and total PKC ι. To our knowledge, this is the first report of elevated PKC ι in head and neck squamous cell carcinoma that may have significance because PKC ι is an oncogene in several other tumor types, including lung cancer. The feasibility of using RPPA for developing theranostic tests to guide personalized therapy is discussed in the context of these data.

Singularity analysis of the AKT signaling pathway reveals connections between cancer and metabolic diseases

Connections between cancer and metabolic diseases may consist in the complex network of interactions among a common set of biomolecules. By applying singularity and bifurcation analysis, the phenotypes constrained by the AKT signaling pathway are identified and mapped onto the parameter space, which include cancer and certain metabolic diseases. By considering physiologic properties (sensitivity, robustness and adaptivity) the AKT pathway must possess in order to efficiently sense growth factors and nutrients, the region of normal responses is located. To optimize these properties, the intracellular concentration of the AKT protein must be sufficiently high to saturate its enzymes; the strength of the positive feedback must be stronger than that of the negative feedback. The analysis illuminates the parameter space and reveals system-level mechanisms in regulating biological functions (cell growth, survival, proliferation and metabolism) and how their deregulation may lead to the development of diseases. The analytical expressions summarize the synergistic interactions among many molecules, which provides valuable insights into therapeutic interventions. In particular, a strategy for overcoming the limitations of mTOR inhibition is proposed for cancer therapy.

Targeted therapies in cancer - challenges and chances offered by newly developed techniques for protein analysis in clinical tissues

In recent years, new anticancer therapies have accompanied the classical approaches of surgery and radio- and chemotherapy. These new forms of treatment aim to inhibit specific molecular targets namely altered or deregulated proteins, which offer the possibility of individualized therapies.The specificity and efficiency of these new approaches, however, bring about a number of challenges. First of all, it is essential to specifically identify and quantify protein targets in tumor tissues for the reasonable use of such targeted therapies. Additionally, it has become even more obvious in recent years that the presence of a target protein is not always sufficient to predict the outcome of targeted therapies. The deregulation of downstream signaling molecules might also play an important role in the success of such therapeutic approaches. For these reasons, the analysis of tumor-specific protein expression profiles prior to therapy has been suggested as the most effective way to predict possible therapeutic results. To further elucidate signaling networks underlying cancer development and to identify new targets, it is necessary to implement tools that allow the rapid, precise, inexpensive and simultaneous analysis of many network components while requiring only a small amount of clinical material.Reverse phase protein microarray (RPPA) is a promising technology that meets these requirements while enabling the quantitative measurement of proteins. Together with recently developed protocols for the extraction of proteins from formalin-fixed, paraffin-embedded (FFPE) tissues, RPPA may provide the means to quantify therapeutic targets and diagnostic markers in the near future and reliably screen for new protein targets.With the possibility to quantitatively analyze DNA, RNA and protein from a single FFPE tissue sample, the methods are available for integrated patient profiling at all levels of gene expression, thus allowing optimal patient stratification for individualized therapies.

[Analysis of signalling pathways in formalin-fixed breast cancer tissues]

AIMS

The aim of our study was to develop and optimize methods for relative and absolute protein quantifications in formalin-fixed and paraffin-embedded (FFPE) tissues with special emphasis on HER mediated pathways in breast cancer.

METHODS

Using a recently developed technology for extraction of full-length proteins from FFPE tissues, we evaluated >50 commercial antibodies for specificity using Western blots and protein microarrays. Purified HER receptor proteins were used to determine absolute protein concentrations.

RESULTS

We confirmed specificity of 23 commercially available phosphospecific and non-phosphospecific antibodies using Western blots with protein extracts from cell lines and tissue extracts from breast cancer patients. Spiking known amounts of purified HER receptor proteins in HER receptor negative tissue extracts allowed us to precisely measure abundances of HER-receptors.

CONCLUSIONS

Our results will provide a basis for the development of diagnostic techniques for the quantitative analysis of deregulated HER receptors and downstream signalling proteins in typical clinical tissues.

The promise of bone cancer proteomics

Mass spectrometric analysis of the low-molecular-weight (LMW) range of the serum/plasma proteome is revealing the existence of large numbers of previously unknown peptides and protein fragments, predicted to be derived from circulating low-abundance proteins. While genomics and proteomics are the primary discovery research tool, recent innovations in high-throughput proteomics are now standard practice for biomarker and target discovery. Surface-enhanced laser desorption/ionization time-of-flight (SELDI-TOF) mass spectrometry (MS) is the current mainstay for serum or plasma analysis, although other methods are emerging as alternative high-throughput approaches. From a proteomics perspective, the bone cancers, such as myeloma, breast and prostate cancer bony metastases, and osteosarcoma, are likely among the least studied. As recent advances in proteomic technology have thrust the bone cancer field into the era of proteomics, a review of the current status of the proteome as it relates to the skeletal consequences of malignancy seems reasonable.

Lipoic acid glyco-conjugates, a new class of agents for controlling nonspecific adsorption of blood serum at biointerfaces for biosensor and biomedical applications

The carbohydrate-derived lipoic acid derivatives were studied as protein and cell resistant biomaterials. Six types of carbohydrates were examined for their abilities to reduce nonspecific adsorption of human serum and Hela cell using quartz crystal microbalance. Our data suggested that the structures of carbohydrates play an important role in resisting nonspecific binding. Specifically, the resistance was found to increase in the order lipoic fucose < lipoic mannose < lipoic N-acetyl glucosamine < lipoic glucose < lipoic sialic acid < lipoic galactose, where lipoic galactose derivative resisted most nonspecific adsorption. Furthermore, the combination of lipoic galactose and BSA was the most effective in reducing the adsorption of even undiluted human serum and the attachment of Hela cells while allowing specific binding. Several control experiments have demonstrated that the resistant-ability of mixed lipoic galactose and BSA was comparable to the best known system for decreasing nonspecific adsorption.

Identification, characterization and quantification of specific neuropeptides in rat spinal cord by liquid chromatography electrospray quadrupole ion trap mass spectrometry

Substance P and CGRP play a central role in neuropathic pain development and maintenance. Additionally, dynorphin A is an endogenous ligand of opioid receptors implicated in the modulation of neurotransmitters including neuropeptides, such as substance P and CGRP. This manuscript proposes a method to characterize, identify and quantify substance P, CGRP and dynorphin A in rat spinal cord by HPLC-ESI/MS/MS. Rat spinal cords were collected and homogenized into a TFA solution. Samples were chromatographed using a microbore C(8) 100 x 1 mm column and a 19 min linear gradient (0:100 --> 40:60; ACN:0.2% formic acid in water) at a flow rate of 75 microL/min for a total run time of 32 min. The peptides were identified in rat spinal cord based on full-scan MS/MS spectra. Substance P, CGRP and dynorphin A were predominantly identified by the presence of specific b CID fragments. Extracted ion chromatogram (XIC) suggested selected mass transitions of 674 --> [600 + 254], 952 --> [1215 + 963] and 717 --> [944 + 630] for substance P, CGRP and dynorphin A can be used for isolation and quantitative analysis. A linear regression (weighted 1/x) was used and coefficients of correlations (r) ranging from 0.990 to 0.999 were observed. The precision (%CV) and accuracy (%NOM) observed were 10.9-14.4% and 8.9-14.2%, 8.8-13.0% and 91.0-110.2% and 97.2-107.3% and 91.8-97.3% for substance P, CGRP and dynorphin A respectively. Following the analysis of rat spinal cords, the mean endogenous concentrations were 110.7, 2541 and 779.4 pmol/g for substance P, CGRP and dynorphin A respectively. The results obtained show that the method provides adequate figures of merit to support targeted peptidomic studies aimed to determine neuropeptide regulation in animal neuropathic and chronic pain models.

Predicting the response of advanced cervical and ovarian tumors to therapy

The management of advanced cervical and ovarian cancers remains a significant challenge as many women fail to respond to recommended therapy, resulting in disease progression and ultimately patient death. Because of tumor heterogeneity, it is rare for all cancers of a particular type to respond to a specific therapy; and, as a result, many patients receive treatment from which they derive little or no benefit, leading to increased morbidity and undue costs. A marker that could rapidly predict or forecast disease outcome would clearly be beneficial in allowing the administration of a tailored regime for each patient while reducing toxicity and cost. Traditional prognostic factors of tumor size, grade, and stage are not ideal for predicting patient outcome, whereas the use of in vitro assays to detect chemosensitivity or resistance has not yet translated into routine clinical practice. Similarly, biomarkers and tumor markers vary in their predictive ability. DNA array technology offers great promise in predicting the response to therapy based on gene expression profiles, and can allow for targeted therapies against specific molecular alterations that cause disease. Imaging techniques, particularly those with the ability to characterize biological tissues and provide functional, structural, and molecular information, have the potential to noninvasively integrate physical and metabolic information. These include F-18-fluorodeoxyglucose positron emission tomography, dynamic contrast-enhanced magnetic resonance imaging, and diffusion weighted magnetic resonance imaging, all techniques that attempt to evaluate and predict therapy response and so influence clinical outcome. This review examines different methods of predicting the response to treatment in advanced cervical and ovarian tumors.

TARGET AUDIENCE

Obstetricians & Gynecologists, Family Physicians.

LEARNING OBJECTIVES

After completion of this article, the reader should be able to describe why prediction of response to therapy for cervical and ovarian cancers is important, describe obstacles to use of in vitro assays to predict outcomes for therapy for ovarian and cervical cancers, and explain potentially new predictive markers.

Increase in serum haptoglobin and apolipoprotein M in patients with obstructive sleep apnoea

Obstructive sleep apnoea (OSA) is a common syndrome, which is associated with a number of medical problems that impact morbidity and mortality. Although the precise mechanisms that underlie these associations are not fully understood, previous studies have suggested that patients with OSA show elevations of several biomarkers that are associated with cardiovascular risk. This study was undertaken to identify serum proteins associated with OSA by using a proteomics technique and to examine changes in identified protein levels after continuous positive airway pressure treatment. The study participants consisted of 40 male patients (aged 40-49 years) with severe OSA and 34 male control subjects matched for age and body mass index. All subjects underwent polysomnography. Using a proteomics approach, we identified nine proteins that were differentially expressed in patients with severe OSA and controls. Three of these nine proteins, haptoglobin, paraoxonase-1 and apolipoprotein M, were quantified by using enzyme-linked immunosorbent assays, kinetic assays and by using Western blotting. Multiple regression analysis showed that haptoglobin and apolipoprotein M levels are independently related to apnoea-hypopnoea index (P < 0.01). A further study is required to determine the nature of associations between these identified proteins and OSA in a large population.

Blood-related proteomics

Blood-related proteomics is an emerging field, recently gaining momentum. Indeed, a wealth of data is now available and a plethora of groups has contributed to add pieces to the jigsaw puzzle of protein complexity within plasma and blood cells. In this review article we purported to sail across the mare magnum of the actual knowledge in this research endeavour. The main strides in proteomic investigations on red blood cells, platelets, plasma and white blood cells are hereby presented in a chronological order. Moreover, a glance is given at prospective studies which promise to shift the focus of attention from the end product to its provider, the donor, in a sort of Kantian "Copernican revolution". A well-rounded portrait of the usefulness of proteomics in blood-related research is accurately given. In particular, proteomic tools could be adopted to follow the main steps of the blood-banking production processes (a comparison of collection methods, pathogen inactivation techniques, storage protocols). Thus proteomics has been recently transformed from a mere basic-research extremely-expensive toy into a dramatically-sensitive and efficient eye-lens to either delve into the depths of the molecular mechanisms of blood and blood components or to establish quality parameters in the blood-banking production chain totally anew.

Proteomic signatures of epidermal growth factor receptor and survival signal pathways correspond to gefitinib sensitivity in head and neck cancer

PURPOSE

Gefitinib targeting of the epidermal growth factor receptor (EGFR) has shown limited activity in clinical trials of head and neck squamous cell carcinoma (HNSCC). To investigate the underlying molecular mechanism, the proteomic signatures and responses of EGFR and downstream signals have been studied in a panel of HNSCC cell lines and tumor specimens pre- and post-gefitinib treatment.

EXPERIMENTAL DESIGN

The IC(50) of gefitinib for HNSCC cell lines were determined using 3-(4,5-dmethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide proliferation assay. The effects of gefitinib on activation of EGFR and downstream signaling molecules were determined by Western blot, ELISA, and reverse-phase protein microarray (RPMA). The biomarkers involved in the signaling pathways were examined in HNSCC tumor specimens from patients in a phase I gefitinib trial.

RESULTS

In vitro, gefitinib inhibited cell proliferation with differing IC(50), and suppressed activation of EGFR and downstream signaling molecules protein kinase B (AKT), extracellular signal-regulated kinase 1/2, signal transducer and activator of transcription 3 (STAT3), and nuclear factor kappaB. The drug sensitivity was statistically correlated with activation of phosphorylated AKT (p-AKT) and phosphorylated STAT3 (p-STAT3) detected by ELISA, and consistent with results measured by RPMA. In patient samples, a broad suppression of activation of EGFR and downstream signaling molecules was observed in a molecular responder patient, in contrast to a lack of inhibition or increased activation of biomarkers in different pathways in nonresponder patients.

CONCLUSIONS

Gefitinib sensitivity is correlated with p-AKT and p-STAT3 activation in HNSCC cell lines and tumor specimens. p-AKT and p-STAT3 could serve as potentially useful biomarkers and drug targets for further development of novel therapeutic agents for HNSCC.

The current state of proteomics in GI oncology

Proteomics refers to the study of the entire set of proteins in a given cell or tissue. With the extensive development of protein separation, mass spectrometry, and bioinformatics technologies, clinical proteomics has shown its potential as a powerful approach for biomarker discovery, particularly in the area of oncology. More than 130 exploratory studies have defined candidate markers in serum, gastrointestinal (GI) fluids, or cancer tissue. In this article, we introduce the commonly adopted proteomic technologies and describe results of a comprehensive review of studies that have applied these technologies to GI oncology, with a particular emphasis on developments in the last 3 years. We discuss reasons why the more than 130 studies to date have had little discernible clinical impact, and we outline steps that may allow proteomics to realize its promise for early detection of disease, monitoring of disease recurrence, and identification of targets for individualized therapy.

Comparative study of SPR and ELISA methods based on analysis of CD166/ALCAM levels in cancer and control human sera

Surface plasmon resonance (SPR), as a label free method for analysis of various analytes, has significantly advanced in recent years. However, assessment of the performance of SPR compared to label-based immunoassays such as the commonly used multiplexed enzyme-linked immunosorbent assay (ELISA) is limited, particularly for applications involving complex media. In this work, an optimized SPR assay was implemented and its performance compared with an ELISA assay for CD166/activated cell leukocyte adhesion molecule (ALCAM), as candidate pancreatic cancer marker, based on direct and amplified detection in buffer and in human serum samples from healthy individuals and subjects with cancer. ALCAM antibody was immobilized on the surface of a four-channel SPR sensor via physical adsorption onto charged amine-terminated alkanethiolates to mimic the ELISA plate surface. Excellent correlations between SPR and ELISA results were achieved in buffer and in human serum. SPR detected the target protein with a similar sensitivity to sandwich ELISA, with a detection limit below ng/mL. The detection time, sample consumption, throughput, signal referencing, and surface blocking and washing for detection in human serum were evaluated. It is demonstrated that SPR can distinguish between ALCAM levels in cancer and control sera using direct detection without the need for additional amplification steps.

Applications of protein microarrays for biomarker discovery

The search for new biomarkers for diagnosis, prognosis, and therapeutic monitoring of diseases continues in earnest despite dwindling success at finding novel reliable markers. Some of the current markers in clinical use do not provide optimal sensitivity and specificity, with the prostate cancer antigen (PSA) being one of many such examples. The emergence of proteomic techniques and systems approaches to study disease pathophysiology has rekindled the quest for new biomarkers. In particular the use of protein microarrays has surged as a powerful tool for large-scale testing of biological samples. Approximately half the reports on protein microarrays have been published in the last two years especially in the area of biomarker discovery. In this review, we will discuss the application of protein microarray technologies that offer unique opportunities to find novel biomarkers.

The Role of the NF-kappaB Transcriptome and Proteome as Biomarkers in Human Head and Neck Squamous Cell Carcinomas

NF-kappaB is a family of signal activated transcription factors comprised of hetero- or homo-dimers from 5 different subunits, NF-kappaB1, NF-kappaB2, RELA, cREL and RELB. NF-kappaBs normally are transiently activated in response to infection or injury, but in cancers are aberrantly activated, regulating a transcriptome of hundreds of genes and corresponding proteome that promote pathogenesis and therapeutic resistance. In head and neck squamous cell carcinomas, an important role of NF-kappaB in regulation of the altered transcriptome and proteome has been established, providing a catalog of activating and target genes and proteins that may be useful as biomarkers of alterations in this pathway for this and other cancers. An emerging appreciation that NF-kappaB and other signal pathways form an altered regulatory network highlights the need to use biomarkers and combine targeted agents for personalized therapy of cancer.

Advances in tumor-related molecular phenotypes and personalized therapy

Malignant tumor impairs human's health severely. Although progresses have been made in tumor's etiology, clinical management of tumor is still confronted by challenges. The standard treatments against tumor, including surgery, chemotherapy and radiotherapy, are not effective for all patients. The clinicians often feel confused while selecting appropriate therapeutic pattern and judging patients' prognosis. The clinical outcome of target-protein-based cancer therapy revealed that personalized molecular signature determined individualized curative effect. Effective management of tumor needs patient-tailored design. The so-called "omic" researches accelerate the studies in specific molecule phenotype of tumor cells, and the personalized therapy against such individualized malignant phenotype will represent the future direction in tumor treatment.