Genomic and proteomic technologies for individualisation and improvement of cancer treatment

Identification of potential key genes and functional role of CENPF in osteosarcoma using bioinformatics and experimental analysis

Osteosarcoma, which arises from bone tissue, is considered to be one of the most common types of cancer in children and teenagers. As the etiology of osteosarcoma has not been fully elucidated, the overall prognosis for patients is generally poor. In recent years, the development of bioinformatical technology has allowed researchers to identify numerous molecular biological characteristics associated with the prognosis of osteosarcoma using online databases. In the present study, Gene Expression Omnibus (GEO) database was used and three microarray datasets were obtained. The GEO2R web tool was utilized and differentially expressed genes (DEGs) in osteosarcoma tissue were identified. Venn analysis was performed to determine the intersection of the DEG profiles. DEGs were analyzed by Gene Ontology function and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis. Protein-protein interactions (PPIs) between these DEGs were analyzed using the Search Tool for the Retrieval of Interacting Genes database, and the PPI network was then visualized using Cytoscape software. The top ten genes were identified based on measurement of degree, density of maximum neighborhood component, maximal clique centrality and mononuclear cell counts in the PPI network, and five overlapping genes [origin recognition complex subunit 6 (ORC6), IGF-binding protein 5 (IGFBP5), minichromosome maintenance 10 replication initiation factor (MCM10), MET proto-oncogene, receptor tyrosine kinase (MET) and centromere protein F (CENPF)] were identified. Additionally, three module networks were analyzed by Molecular Complex Detection (MCODE), and six key genes [ORC6, MCM10, DEP domain containing 1 (DEPDC1), CENPF, TIMELESS interacting protein (TIPIN) and shugoshin 1 (SGOL1)] were screened. Combined with the results from Cytoscape and MCODE, eight hub genes (ORC6, MCM10, DEPDC1, CENPF, TIPIN, SGOL1, MET and IGFBP5) were obtained. Furthermore, Kaplan-Meier plotter survival analysis was used to evaluate the prognostic value of these eight hub genes in patients with osteosarcoma. Oncomine and GEPIA databases were applied to further confirm the expression levels of hub genes in tissue. Finally, the functional roles of the core gene CENPF were investigated using Cell Counting Kit-8, wound healing and Transwell assays, which indicated that CENPF knockdown inhibited the proliferation, migration and invasion of osteosarcoma cells. These results provided potential prognostic markers, as well as a basis for further investigation of the mechanism underlying osteosarcoma.

Discovery and Evaluation of Protein Biomarkers as a Signature of Wellness in Late-Stage Cancer Patients in Early Phase Clinical Trials

TARGET (tumour characterisation to guide experimental targeted therapy) is a cancer precision medicine programme focused on molecular characterisation of patients entering early phase clinical trials. Performance status (PS) measures a patient's ability to perform a variety of activities. However, the quality of present algorithms to assess PS is limited and based on qualitative clinician assessment. Plasma samples from patients enrolled into TARGET were analysed using the mass spectrometry (MS) technique: sequential window acquisition of all theoretical fragment ion spectra (SWATH)-MS. SWATH-MS was used on a discovery cohort of 55 patients to differentiate patients into either a good or poor prognosis by creation of a Wellness Score (WS) that showed stronger prediction of overall survival (p = 0.000551) compared to PS (p = 0.001). WS was then tested against a validation cohort of 77 patients showing significant (p = 0.000451) prediction of overall survival. WS in both sets had receiver operating characteristic curve area under the curve (AUC) values of 0.76 (p = 0.002) and 0.67 (p = 0.011): AUC of PS was 0.70 (p = 0.117) and 0.55 (p = 0.548). These signatures can now be evaluated further in larger patient populations to assess their utility in a clinical setting.

Phosphoproteomic profiling of tumor tissues identifies HSP27 Ser82 phosphorylation as a robust marker of early ischemia

Delays between tissue collection and tissue fixation result in ischemia and ischemia-associated changes in protein phosphorylation levels, which can misguide the examination of signaling pathway status. To identify a biomarker that serves as a reliable indicator of ischemic changes that tumor tissues undergo, we subjected harvested xenograft tumors to room temperature for 0, 2, 10 and 30 minutes before freezing in liquid nitrogen. Multiplex TMT-labeling was conducted to achieve precise quantitation, followed by TiO₂ phosphopeptide enrichment and high resolution mass spectrometry profiling. LC-MS/MS analyses revealed phosphorylation level changes of a number of phosphosites in the ischemic samples. The phosphorylation of one of these sites, S82 of the heat shock protein 27 kDa (HSP27), was especially abundant and consistently upregulated in tissues with delays in freezing as short as 2 minutes. In order to eliminate effects of ischemia, we employed a novel cryogenic biopsy device which begins freezing tissues in situ before they are excised. Using this device, we showed that the upregulation of phosphorylation of S82 on HSP27 was abrogated. We thus demonstrate that our cryogenic biopsy device can eliminate ischemia-induced phosphoproteome alterations, and measurements of S82 on HSP27 can be used as a robust marker of ischemia in tissues.

Electrical nanowell diagnostics sensors for rapid and ultrasensitive detection of prostate-specific antigen

Aim: Alumina nanowell based disposable diagnostic biosensor for detecting and quantifying levels of prostate-specific antigen (PSA) from human serum has been designed, fabricated and tested. Materials & methods: The biosensors were designed by integrating nanoporous alumina membranes onto printed circuit board platforms, resulting in the generation of high-density nanowell arrays with gold base electrodes. The size and density of the nanowells were leveraged toward achieving sieving action for size-based exclusion of nonspecific molecules and size-based confinement of the target PSA molecules. Results & conclusion: We demonstrated PSA detection between 0.01 and 1000 ng/ml and detection and quantification of PSA from a 17 patient cohort validated using the Beckman Access system with >95% correlation.

Reverse phase protein arrays: mapping the path towards personalized medicine

Reverse phase protein array (RPPA) technology evolved from the advent of miniaturized immunoassays and gene microarray technology. Reverse phase protein arrays provide either a low throughput or high throughput methodology for quantifying proteins and their post-translationally modified forms in both cellular and non-cellular samples. As the demand for patient tailored therapies increases so does the need for precise and sensitive technology to accurately profile the molecular circuitry driving an individual patient's disease. RPPAs are currently utilized in clinical trials for profiling and comparing the functional state of protein signaling pathways, either temporally within tumors, between patients, or within the same patients before/after treatment. RPPAs are generally employed for quantifying large numbers of samples on one array, under identical experimental conditions. However, the goal of personalized cancer medicine is to design therapies based on the molecular portrait of a patient's tumor, which in turn result in more efficacious treatments with less toxicity. Therefore, RPPAs are also being validated for low throughput assays of individual patient samples. This review explores RPPA technology in the cancer research field, concentrating on its role as a fundamental tool for deciphering protein signaling networks and its emerging role in personalized medicine.

Proteomic strategies for the discovery of novel diagnostic and therapeutic targets for infectious diseases

Viruses have developed numerous and elegant strategies to manipulate the host cell machinery to establish a productive infectious cycle. The interaction of viral proteins with host proteins plays an important role in infection and pathogenesis, often bypassing traditional host defenses such as the interferon response and apoptosis. Host–viral protein interactions can be studied using a variety of proteomic approaches ranging from genetic and biochemical to large‐scale high‐throughput technologies. Protein interactions between host and viral proteins are greatly influenced by host signal transduction pathways. In this review, we will focus on comparing proteomic information obtained through differing technologies and how their integration can be used to determine the functional aspect of the host response to infection. We will briefly review and evaluate techniques employed to elucidate viral–host interactions with a primary focus on Protein Microarrays (PMA) and Mass Spectrometry (MS) as potential tools in the discovery of novel therapeutic targets. As many potential molecular markers and targets are proteins, proteomic profiling is expected to yield both clearer and more direct answers to functional and pharmacologic questions.

Evidence for the importance of personalized molecular profiling in pancreatic cancer

OBJECTIVES

There is a growing body of evidence that targeted gene therapy holds great promise for the future treatment of cancer. A crucial step in this therapy is the accurate identification of appropriate candidate genes/pathways for targeted treatment. One approach is to identify variant genes/pathways that are significantly enriched in groups of afflicted individuals relative to control subjects. However, if there are multiple molecular pathways to the same cancer, the molecular determinants of the disease may be heterogeneous among individuals and possibly go undetected by group analyses.

METHODS

In an effort to explore this question in pancreatic cancer, we compared the most significantly differentially expressed genes/pathways between cancer and control patient samples as determined by group versus personalized analyses.

RESULTS

We found little to no overlap between genes/pathways identified by gene expression profiling using group analyses relative to those identified by personalized analyses.

CONCLUSIONS

Our results indicate that personalized and not group molecular profiling is the most appropriate approach for the identification of putative candidates for targeted gene therapy of pancreatic and perhaps other cancers with heterogeneous molecular etiology.

Recent advances in the identification of genes for human hypertension

It is a well-established fact that genes are involved in the etiology of hypertension. However, identification of the gene variants still remains a challenge. Over the years, different approaches and technologies, including genome-wide scans, case-control association studies, experiments on inbred rodent models and expression profiling, have been utilized to elucidate hypertension susceptibility genes, but so far the results have been equivocal. During the last year, further chromosomal regions harboring blood pressure loci have been identified, and transcriptomics has been applied to aid the identification of disease genes. There are great expectations for the future with regards to further advancements in transcriptomics and proteomics. This review reports primarily on work that has been carried out in the last 12 months in the field, and considers its contribution towards a better understanding of the genetic mechanisms involved in blood pressure regulation and hypertension.

Molecular characterization of photosensitizer-mediated photodynamic therapy by gene expression profiling

Photodynamic therapy (PDT) is a novel cancer treatment based on the tumor-specific accumulation of a photosensitizer followed by irradiation with visible light, which induces selective tumor cell death via production of reactive oxygen species. To elucidate the underlying mechanisms, microarray analysis was used to analyze the changes in gene expression patterns during PDT induced by various photosensitizers. Cancer cells were subjected to four different photosensitizer-mediated PDT and the resulting gene expression profiles were compared. We identified many differentially expressed genes reported previously as well as new genes for which the functionfunctions in PDT are still unclear. Our current results not only advance the general understanding of PDT but also suggest that distinct molecular mechanisms are involved in different photosensitizer-mediated PDT. Elucidating the signaling mechanisms in PDT will provide information to modulate the antitumor effectiveness of PDT using various photosensitizers.

Predictive tests for individualization of pharmacological cancer treatment

BACKGROUND

The selection of cancer drugs for an individual patient is still based mostly on cancer type and stage. Predictive tests are needed to make individualized and more efficient pharmacological cancer treatment possible.

OBJECTIVE

To provide an overview of available, possible future development and principles for development of predictive tests for individualized selection of cancer drugs.

METHODS

Overview of published data.

RESULTS/CONCLUSION

Despite increased knowledge in cancer biology, only limited progress has been made in the development and use of predictive tests. However, rapid progress in this field will be possible using already available and emerging technologies, but requires a paradigm shift in principles for the development and use of cancer drugs. Assessment of drug activity in intact tumor cells and tumor cell gene expression signatures are considered to have greatest potential for the development of versatile predictive tests.

Cancer proteomics

Cancer presents high mortality and morbidity globally, largely due to its complex and heterogenous nature, and lack of biomarkers for early diagnosis. A proteomics study of cancer aims to identify and characterize functional proteins that drive the transformation of malignancy, and to discover biomarkers to detect early-stage cancer, predict prognosis, determine therapy efficacy, identify novel drug targets, and ultimately develop personalized medicine. The various sources of human samples such as cell lines, tissues, and plasma/serum are probed by a plethora of proteomics tools to discover novel biomarkers and elucidate mechanisms of tumorigenesis. Innovative proteomics technologies and strategies have been designed for protein identification, quantitation, fractionation, and enrichment to delve deeper into the oncoproteome. In addition, there is the need for high-throughput methods for biomarker validation, and integration of the various platforms of oncoproteome data to fully comprehend cancer biology.

Personalized medicine: the impact on chemistry

An effective strategy for personalized medicine requires a major conceptual change in the development and application of therapeutics. In this article, we argue that further advances in this field should be made with reference to another conceptual shift, that of network pharmacology. We examine the intersection of personalized medicine and network pharmacology to identify strategies for the development of personalized therapies that are fully informed by network pharmacology concepts. This provides a framework for discussion of the impact personalized medicine will have on chemistry in terms of drug discovery, formulation and delivery, the adaptations and changes in ideology required and the contribution chemistry is already making. New ways of conceptualizing chemistry's relationship with medicine will lead to new approaches to drug discovery and hold promise of delivering safer and more effective therapies.

Imaging of Abdominal Aortic Aneurysm: the present and the future

Abdominal Aortic Aneurysm (AAA) is a common, progressive, and potentially lethal vascular disease. A major obstacle in AAA research, as well as patient care, is the lack of technology that enables non-invasive acquisition of molecular/cellular information in the developing AAA. In this review we will briefly summarize the current techniques (e.g. ultrasound, computed tomography, and magnetic resonance imaging) for anatomical imaging of AAA. We also discuss the various functional imaging techniques that have been explored for AAA imaging. In many cases, these anatomical and functional imaging techniques are not sufficient for providing surgeons/clinicians enough information about each individual AAA (e.g. rupture risk) to optimize patient management. Recently, molecular imaging techniques (e.g. optical and radionuclide-based) have been employed to visualize the molecular alterations associated with AAA, which are discussed in this review. Lastly, we try to provide a glance into the future and point out the challenges for AAA imaging. We believe that the future of AAA imaging lies in the combination of anatomical and molecular imaging techniques, which are largely complementary rather than competitive. Ultimately, with the right molecular imaging probe, clinicians will be able to monitor AAA growth and evaluate the risk of rupture accurately, so that the life-saving surgery can be provided to the right patients at the right time. Equally important, the right imaging probe will also allow scientists/clinicians to acquire critical data during AAA development and to more accurately evaluate the efficacy of potential treatments.

Design and development of molecular imaging probes

Molecular imaging, the visualization, characterization and measurement of biological processes at the cellular, subcellular level, or even molecular level in living subjects, has rapidly gained importance in the dawning era of personalized medicine. Molecular imaging takes advantage of the traditional diagnostic imaging techniques and introduces molecular imaging probes to determine the expression of indicative molecular markers at different stages of diseases and disorders. As a key component of molecular imaging, molecular imaging probe must be able to specifically reach the target of interest in vivo while retaining long enough to be detected. A desirable molecular imaging probe with clinical translation potential is expected to have unique characteristics. Therefore, design and development of molecular imaging probe is frequently a challenging endeavor for medicinal chemists. This review summarizes the general principles of molecular imaging probe design and some fundamental strategies of molecular imaging probe development with a number of illustrative examples.

Identification of potential biomarkers for giant cell tumor of bone using comparative proteomics analysis

Giant cell tumor of bone can be locally aggressive and occasionally can metastasize in the lungs. To identify new markers predictive of aggressive behavior, we analyzed five patients who developed lung metastasis and five who remained disease free for a minimum of 5 years. Using two-dimensional electrophoresis, we detected 28 differentially expressed spots. Fourteen spots were identified using mass spectrometry, including seven up-regulated and seven down-regulated in metastatic samples and classified according to functional categories. We then selected five proteins involved in cell cycle or apoptosis. Thioredoxin peroxidase, allograft inflammatory factor 1, and ubiquitin E2N had more than threefold up-regulation; glutathione peroxidase 1 had 1.9-fold up-regulation; and heat shock protein 27 showed down-regulation in metastatic samples with a very low P value. After validation and analysis of protein levels, evaluation of clinical impact was assessed in a much wider cohort of primary archival specimens. Immunodetection showed a higher frequency of thioredoxin peroxidase, allograft inflammatory factor 1, ubiquitin E2N, and glutathione peroxidase 1 overexpression in primary tumors that developed into lung metastases or that locally relapsed than in the disease-free group, with variable stain intensity and distribution. Kaplan-Meier analysis showed that high expression of glutathione peroxidase 1 was strongly related to local recurrence and metastasis, suggesting that its up-regulation may identify a subset of high-risk patients with giant cell tumor prone to receive diverse clinical management.

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.

Development and validation of a prognostic model using blood biomarker information for prediction of survival of non-small-cell lung cancer patients treated with combined chemotherapy and radiation or radiotherapy alone (NCT00181519, NCT00573040, and NCT00572325)

PURPOSE

Currently, prediction of survival for non-small-cell lung cancer patients treated with (chemo)radiotherapy is mainly based on clinical factors. The hypothesis of this prospective study was that blood biomarkers related to hypoxia, inflammation, and tumor load would have an added prognostic value for predicting survival.

METHODS AND MATERIALS

Clinical data and blood samples were collected prospectively (NCT00181519, NCT00573040, and NCT00572325) from 106 inoperable non-small-cell lung cancer patients (Stages I-IIIB), treated with curative intent with radiotherapy alone or combined with chemotherapy. Blood biomarkers, including lactate dehydrogenase, C-reactive protein, osteopontin, carbonic anhydrase IX, interleukin (IL) 6, IL-8, carcinoembryonic antigen (CEA), and cytokeratin fragment 21-1, were measured. A multivariate model, built on a large patient population (N = 322) and externally validated, was used as a baseline model. An extended model was created by selecting additional biomarkers. The model's performance was expressed as the area under the curve (AUC) of the receiver operating characteristic and assessed by use of leave-one-out cross validation as well as a validation cohort (n = 52).

RESULTS

The baseline model consisted of gender, World Health Organization performance status, forced expiratory volume, number of positive lymph node stations, and gross tumor volume and yielded an AUC of 0.72. The extended model included two additional blood biomarkers (CEA and IL-6) and resulted in a leave-one-out AUC of 0.81. The performance of the extended model was significantly better than the clinical model (p = 0.004). The AUC on the validation cohort was 0.66 and 0.76, respectively.

CONCLUSIONS

The performance of the prognostic model for survival improved markedly by adding two blood biomarkers: CEA and IL-6.

Identification and functional analysis of genes which confer resistance to cisplatin in tumor cells

The efficacy of cisplatin during cancer chemotherapy is often impaired by the emergence of cancer cells which become resistant to chemotherapeutic agents. While various mechanisms have been proposed to explain resistance to cisplatin, the genes involved in this process still remain unclear. By using DNA microarrays, we performed a genome-wide analysis of cisplatin-resistant HeLa cells in order to identify genes involved in resistance. We identified nine genes (NAPA, CITED2, CABIN1, ADM, HIST1H1A, EHD1, MARK2, PTPN21, and MVD), which were consistently upregulated in two cisplatin-resistant HeLa cell lines. The upregulated genes, here referred to as cisplatin resistance genes (CPR), were further analyzed for their ability to modify the response of HEK293 cells to cisplatin. Short-hairpin RNA (shRNA) knockdown of CPR genes, individually or in combination, was shown to sensitize HEK293 cells to cisplatin, but not to vincristine or taxol, suggesting that CPR genes may be involved specifically in cisplatin resistance. Among the treatments performed, shRNA knockdown of NAPA was the most efficient treatment able to sensitize cells to cisplatin. Furthermore, shRNA knockdown of a single CPR gene was sufficient to partially reverse acquired cisplatin resistance in HeLa cells. Sensitization to cisplatin following knockdown of CPR genes was also observed in the tumorigenic cell lines Sk-ov-3, H1155, and CG-1. Based on these results, we propose that the CPR genes identified here may represent potential candidates for novel target therapies aimed at preventing resistance to cisplatin during chemotherapy.

Molecular profiling of signalling pathways in formalin-fixed and paraffin-embedded cancer tissues

In most hospitals word-wide, histopathological cancer diagnosis is currently based on formalin-fixed and paraffin-embedded (FFPE) tissues. In the last few years new approaches and developments in patient-tailored cancer therapy have raised the need to select more precisely those patients, who will respond to personalised treatments. The most efficient way for optimal therapy and patient selection is probably to provide a tumour-specific protein network portrait prior to treatment. The discovery and characterisation of deregulated signalling molecules (e.g. human epidermal growth factor receptor 2, mitogen-activated protein kinases) are very promising candidates for the identification of new suitable therapy targets and for the selection of those patients who will receive the greatest benefit from individualised treatments. The reverse phase protein array (RPPA) is a promising new technology that allows quick, precise and simultaneous analysis of many components of a network. Importantly it requires only limited amounts of routine clinical material (e.g. FFPE biopsies) and can be used for absolute protein measurements. We and other research groups have described successful protein extraction from routine FFPE tissues. In this manuscript we show how these recent developments might facilitate the implementation of RPPA in clinical trials and routine settings.

Future perspective for diagnosis in autoimmune diseases

Human beings have taken successive approaches for the understanding and management of diseases. Initially brewed in supernatural concepts and mystical procedures, a vigorous scientific approach has emerged on the grounds of fundamental disciplines such as anatomy, microbiology, biochemistry, physiology, immunology, pathology, and pharmacology. The resulting integrated knowledge contributed to the current classification of diseases and the way Medicine is carried out today. Despite considerable progress, this approach is rather insufficient when it comes to systemic inflammatory conditions, such as systemic lupus erythematosus, that covers clinical conditions ranging from mild pauci-symptomatic diseases to rapidly fatal conditions. The treatment for such conditions is often insufficient and novel approaches are needed for further progress in these areas of Medicine. A recent breakthrough has been achieved with respect to chronic auto-inflammatory syndromes, in which molecular dissection of underlying gene defects has provided directions for target-oriented therapy. Such approach may be amenable to application in systemic auto-immune diseases with the comprehension that such conditions may be the consequence of interaction of specific environmental stimuli and an array of several and interconnected gene polymorphisms. On the bulk of this transformation, the application of principles of pharmacogenetics may lead the way towards a progressively stronger personalized Medicine.

Cancer systems biology

Cancer is a complex and heterogeneous disease, not only at a genetic and biochemical level, but also at a tissue, organism, and population level. Multiple data streams, from reductionist biochemistry in vitro to high-throughput "-omics" from clinical material, have been generated with the hope that they encode useful information about phenotype and, ultimately, tumour behaviour in response to drugs. While these data stand alone in terms of the biology they represent, there is the enticing prospect that if incorporated into systems biology models, they can help understand complex systems behaviour and provide a predictive framework as an additional tool in understanding how tumours change and respond to treatment over time. Since these biological data are heterogeneous and frequently qualitative rather than quantitative, at the present time a single systems biology approach is unlikely to be effective; instead, different computational and mathematical approaches should be tailored to different types of data, and to each other, in order to test and re-test hypotheses. In time, these models might converge and result in usable tractable models which accurately represent human cancer. Likewise, biologists and clinicians need to understand what the requirements of systems biology are so that compatible data are produced for computational modelling. In this review, we describe some theoretical approaches (data-driven and process-driven) and experimental methodologies which are being used in cancer research and the clinical context where they might be applied.

Institutional shared resources and translational cancer research

The development and maintenance of adequate shared infrastructures is considered a major goal for academic centers promoting translational research programs. Among infrastructures favoring translational research, centralized facilities characterized by shared, multidisciplinary use of expensive laboratory instrumentation, or by complex computer hardware and software and/or by high professional skills are necessary to maintain or improve institutional scientific competitiveness. The success or failure of a shared resource program also depends on the choice of appropriate institutional policies and requires an effective institutional governance regarding decisions on staffing, existence and composition of advisory committees, policies and of defined mechanisms of reporting, budgeting and financial support of each resource. Shared Resources represent a widely diffused model to sustain cancer research; in fact, web sites from an impressive number of research Institutes and Universities in the U.S. contain pages dedicated to the SR that have been established in each Center, making a complete view of the situation impossible. However, a nation-wide overview of how Cancer Centers develop SR programs is available on the web site for NCI-designated Cancer Centers in the U.S., while in Europe, information is available for individual Cancer centers. This article will briefly summarize the institutional policies, the organizational needs, the characteristics, scientific aims, and future developments of SRs necessary to develop effective translational research programs in oncology.

In fact, the physical build-up of SRs per se is not sufficient for the successful translation of biomedical research. Appropriate policies to improve the academic culture in collaboration, the availability of educational programs for translational investigators, the existence of administrative facilitations for translational research and an efficient organization supporting clinical trial recruitment and management represent essential tools, providing solutions to overcome existing barriers in the development of translational research in biomedical research centers.

Fluoroimmunoassays using the NRL array biosensor

Array-based biosensor technology offers the user the ability to detect and quantify multiple targets in multiple samples simultaneously (Analytical Sciences 23:5-10, 2007). The NRL Array Biosensor has been developed with the aim of creating a system for sensitive, rapid, on-site screening for multiple targets of interest. This system is fluorescence-based, using evanescent illumination of a waveguide, and has demonstrated the use of both sandwich and competitive immunoassays for the detection of both high and low molecular weight targets, respectively. The current portable, automated system has demonstrated detection of a wide variety of analytes ranging from simple chemical compounds to entire bacterial cells, with applications in food safety, disease diagnosis, homeland security and environmental monitoring.

A genomic approach to identify molecular pathways associated with chemotherapy resistance

Resistance to chemotherapy in cancer is common. As gene expression profiling has been shown to anticipate chemotherapeutic resistance, we sought to identify cellular pathways associated with resistance to facilitate effective combination therapy. Gene set enrichment analysis was used to associate pathways with resistance in two data sets: the NCI-60 cancer cell lines deemed sensitive and resistant to specific chemotherapeutic agents (Adriamycin, cyclophosphamide, docetaxel, etoposide, 5-fluorouracil, paclitaxel, and topotecan) and a series of 40 lung cancer cell lines for which sensitivity to cisplatin and docetaxel was determined. Candidate pathways were further screened in silico using the Connectivity Map. The lead candidate pathway was functionally validated in vitro. Gene set enrichment analysis associated the matrix metalloproteinase, p53, methionine metabolism, and free pathways with cytotoxic resistance in the NCI-60 cell lines across multiple agents, but no gene set was common to all drugs. Analysis of the lung cancer cell lines identified the bcl-2 pathway to be associated with cisplatin resistance and the AKT pathway enriched in cisplatin- and docetaxel-resistant cell lines. Results from Connectivity Map supported an association between phosphatidylinositol 3-kinase/AKT and docetaxel resistance but did not support the association with cisplatin. Targeted inhibition of the phosphatidylinositol 3-kinase/AKT pathway with LY294002, in combination with docetaxel, resulted in a synergistic effect in previously docetaxel-resistant cell lines but not with cisplatin. These results support the use of a genomic approach to identify drug-specific targets associated with the development of chemotherapy resistance and underscore the importance of disease context in identifying these pathways.

Targeting the human cancer pathway protein interaction network by structural genomics

Structural genomics provides an important approach for characterizing and understanding systems biology. As a step toward better integrating protein three-dimensional (3D) structural information in cancer systems biology, we have constructed a Human Cancer Pathway Protein Interaction Network (HCPIN) by analysis of several classical cancer-associated signaling pathways and their physical protein-protein interactions. Many well known cancer-associated proteins play central roles as "hubs" or "bottlenecks" in the HCPIN. At least half of HCPIN proteins are either directly associated with or interact with multiple signaling pathways. Although some 45% of residues in these proteins are in sequence segments that meet criteria sufficient for approximate homology modeling (Basic Local Alignment Search Tool (BLAST) E-value <10(-6)), only approximately 20% of residues in these proteins are structurally covered using high accuracy homology modeling criteria (i.e. BLAST E-value <10(-6) and at least 80% sequence identity) or by actual experimental structures. The HCPIN Website provides a comprehensive description of this biomedically important multipathway network together with experimental and homology models of HCPIN proteins useful for cancer biology research. To complement and enrich cancer systems biology, the Northeast Structural Genomics Consortium is targeting >1000 human proteins and protein domains from the HCPIN for sample production and 3D structure determination. The long range goal of this effort is to provide a comprehensive 3D structure-function database for human cancer-associated proteins and protein complexes in the context of their interaction networks. The network-based target selection (BioNet) approach described here is an example of a general strategy for targeting co-functioning proteins by structural genomics projects.

Guided protein extraction from formalin-fixed tissues for quantitative multiplex analysis avoids detrimental effects of histological stains

Formalin fixed and paraffin embedded (FFPE) tissues are the basis for histopathological diagnosis of many diseases around the world. For translational research and routine diagnostics, protein analysis from FFPE tissues is very important. We evaluated the potential influence of six histological stains, including hematoxylin (Mayer and Gill), fast red, light green, methyl blue and toluidine blue, for yield, electrophoretic mobility in 1-D gels, and immunoreactivity of proteins isolated from formalin-fixed breast cancer tissues. Proteins extracted from stained FFPE tissues using a recently established technique were compared with proteins obtained from the same tissues but without prior histological staining. Western blot and quantitative protein lysate microarray analysis demonstrated that histological staining can result in decreased protein yield but may not have much influence on immunoreactivity and electrophoretic mobility. Interestingly, not all staining protocols tested are compatible with subsequent protein analysis. The commonly used hematoxylin staining was found to be suitable for multiplexed quantitative protein measurement technologies although protein extraction was less efficient. For best results we suggest a guided protein extraction method, in which an adjacent hematoxylin/eosin-stained tissue section is used to control dissection of an unstained specimen for subsequent protein extraction and quantification for research and diagnosis.

Proteins, drug targets and the mechanisms they control: the simple truth about complex networks

Realizing the promise of molecularly targeted inhibitors for cancer therapy will require a new level of knowledge about how a drug target is wired into the control circuitry of a complex cellular network. Here we review general homeostatic principles of cellular networks that enable the cell to be resilient in the face of molecular perturbations, while at the same time being sensitive to subtle input signals. Insights into such mechanisms may facilitate the development of combination therapies that take advantage of the cellular control circuitry, with the aim of achieving higher efficacy at a lower drug dosage and with a reduced probability of drug-resistance development.

Gene expression assays

The study of the profile of gene expression in a cell or tissue at a particular moment gives an insight into the plans of the cell for protein synthesis. Recent technological advances make it possible to analyze the expression of the entire genome in a single experiment. These "gene expression assays" complement or replace previous assays which measured the gene expression of only one gene, or a select group of genes. Within this chapter we outline the development of the gene expression assay and provide examples of the wide range of disciplines in which it is used. An overview of the current technologies is given, and includes an introduction to laser capture microdissection and linear amplification of RNA, both of which have extended the application of gene expression assays. Illustrative examples in the field of cancer and neuroscience highlight the scientific achievements. This technology has made in understanding the pathogenesis of diseases, including breast cancer, Huntington's disease, and schizophrenia. With recent advances including exon arrays to investigate alternative splicing, tiling arrays to investigate novel transcription start sites, and on-chip chromatin immunoprecipitation to investigate DNA-protein interactions, the future of gene expression assays is set to further our understanding of the complexities of gene expression.

The needle in the haystack: application of breast fine-needle aspirate samples to quantitative protein microarray technology

BACKGROUND

There is an unmet clinical need for economic, minimally invasive procedures that use a limited number of cells for the molecular profiling of tumors in individual patients. Reverse-phase protein microarray (RPPM) technology has been applied successfully to the quantitative analysis of breast, ovarian, prostate, and colorectal cancers using frozen surgical specimens.

METHODS

For this report, the authors investigated the novel use of RPPM technology for the analysis of both archival cytology aspirate smears and frozen fine-needle aspiration (FNA) samples. RPPMs were printed with 63 breast FNA samples that were obtained before, during, and after treatment from 21 patients who were enrolled in a Phase II trial of neoadjuvant capecitabine and docetaxel therapy for breast cancer.

RESULTS

Based on an MCF7 cell line model of breast adenocarcinoma, the sensitivity of the RPPM detection method was in the femtomolar range with a coefficient of variance <13.5% for the most dilute sample. Assay linearity was noted from 1.0 microg/microL to 7.8 ng/microL total protein/array spot (R(2) = 0.9887) for a membrane receptor protein (epidermal growth factor receptor; R(2) = 0.9935).

CONCLUSIONS

The results from this study indicated that low-abundance analytes and phosphorylated and nonphosphorylated proteins in specimens that consist of a few thousand cells obtained through FNA can be quantified with RPPM technology. The ability to monitor the in vivo state of cell-signaling proteins before and after treatment potentially will augment the ability to design individualized therapy regimens through the mapping of aberrant cell-signaling phenotypes. The mapping of these protein pathways will further the development of rational drug targets.

Quantitative fluorescence imaging analysis for cancer biomarker discovery: application to beta-catenin in archived prostate specimens

The surprising disparity between the number of protein-encoding genes ( approximately 30,000) in the human genome and the number of proteins ( approximately 300,000) in the human proteome has inspired the development of translational proteomics aimed at protein expression profiling of disease states. Translational proteomics, which offers the promise of early disease detection and individualized therapy, requires new methods for the analysis of clinical specimens. We have developed quantitative fluorescence imaging analysis (QFIA) for accurate, reproducible quantification of proteins in slide-mounted tissues. The method has been validated for the analysis of beta-catenin in archived prostate specimens fixed in formalin. QFIA takes advantage of the linearity of fluorescence antibody signaling for tissue epitope content, a feature validated for beta-catenin in methacarn-fixed prostate specimens analyzed by reverse-phase protein array analysis and QFIA (r = 0.97). QFIA of beta-catenin in formaldehyde-fixed tissues correlated directly with beta-catenin content (r = 0.86). Application of QFIA in a cross-sectional study of biopsies from 42 prostate cancer (PC) cases and 42 matched controls identified beta-catenin as a potential field marker for PC. Receiver operating characteristic plots revealed that beta-catenin expression in the normal-appearing acini of cancerous glands identified 42% (95% confidence intervals, 26-57%) of cancer cases, with 88% (95% confidence intervals, 80-96%) specificity. The marker may contribute to a PC biomarker panel. In conclusion, we report the development and validation of a new method for fluorescence quantification of proteins in archived tissues and its application to archived specimens for an evaluation of beta-catenin expression as a biomarker for PC.

A systems biology approach to the pathogenesis of obesity-related nonalcoholic fatty liver disease using reverse phase protein microarrays for multiplexed cell signaling analysis

Nonalcoholic fatty liver disease (NAFLD) is a common cause of chronic liver disease. Omental adipose tissue, a biologically active organ secreting adipokines and cytokines, may play a role in the development of NAFLD. We tested this hypothesis with reverse-phase protein microarrays (RPA) for multiplexed cell signaling analysis of adipose tissue from patients with NAFLD. Omental adipose tissue was obtained from 99 obese patients. Liver biopsies obtained at the time of surgery were all read by the same hepatopathologist. Adipose tissue was exposed to rapid pressure cycles to extract protein lysates. RPA was used to investigate intracellular signaling. Analysis of 54 different kinase substrates and cell signaling endpoints showed that an insulin signaling pathway is deranged in different locations in NAFLD patients. Furthermore, components of insulin receptor-mediated signaling differentiate most of the conditions on the NAFLD spectrum. For example, PKA (protein kinase A) and AKT/mTOR (protein kinase B/mammalian target of rapamycin) pathway derangement accurately discriminates patients with NASH from those with the non-progressive forms of NAFLD. PKC (protein kinase C) delta, AKT, and SHC phosphorylation changes occur in patients with simple steatosis. Amounts of the FKHR (forkhead factor Foxo1)phosphorylated at S256 residue were significantly correlated with AST/ALT ratio in all morbidly obese patients. Furthermore, amounts of cleaved caspase 9 and pp90RSK S380 were positively correlated in patients with NASH. Specific insulin pathway signaling events are altered in the adipose tissue of patients with NASH compared with patients with nonprogressive forms of NAFLD.

CONCLUSION

These findings provide evidence for the role of omental fat in the pathogenesis, and potentially, the progression of NAFLD.

A novel approach for identification of tumor-associated antigens expressed on the surface of tumor cells

To improve tumor targeting in a subset of patients, where tumor cells do not express the well-known tumor antigens widely used in immunotherapy, we have developed a novel biotechnological tool. It is useful for tumors of various origins for the identification of tumor-associated proteins, which are differentially expressed in tumor cells with respect to normal tissue, and exposed on the cell surface. For this purpose, a combination of techniques, such as "suppression subtractive hybridization" and "transmembrane trapping," was employed. In applying this novel approach to breast cancer, we identified a large panel of cDNA fragments encoding for the well-known tumor-associated surface antigens, such as erb-B2, erbB3 and the urokinase receptor and, more importantly, for several clones overexpressed in breast cancer, whose cDNA fragments match the sequences of hypothetical transmembrane proteins with unknown function. The latter may represent novel tumor-specific targets.

MicroRNA profiles and initiation, diagnosis and treatment of cancers in digestive organs

MicroRNA (miRNA) is a kind of small non-coding RNA containin 21 to 23 nucleotides in length that down-regulates gene expression during various crucial cell processes such as development, proliferation, differentiation and apoptosis. Recent studies supported an important role of miRNA in the initiation and progression of human malignancies. Some miRNAs may function as oncogenes or tumor suppressors. It is found that several miRNAs are directly involved in human cancers of digestive organs, including liver, colon, stomach, pancreas and bile duct. In addition, miRNA expression profiling of tumors in digestive organs has identified signatures associated with diagnosis, staging, progression, prognosis and response to treatment. Profiling has also been exploited to identify miRNA genes that might represent downstream targets of activated oncogenic pathways, or target protein coding genes involved in cancer. Moveover, miRNA-mediated therapy may be a powerful tool for cancer prevention and therapy.

Decision tree modeling predicts effects of inhibiting contractility signaling on cell motility

BACKGROUND

Computational models of cell signaling networks typically are aimed at capturing dynamics of molecular components to derive quantitative insights from prior experimental data, and to make predictions concerning altered dynamics under different conditions. However, signaling network models have rarely been used to predict how cell phenotypic behaviors result from the integrated operation of these networks. We recently developed a decision tree model for how EGF-induced fibroblast cell motility across two-dimensional fibronectin-coated surfaces depends on the integrated activation status of five key signaling nodes, including a proximal regulator of transcellular contractile force generation, MLC (myosin light chain) [Hautaniemi et al, Bioinformatics 21: 2027 {2005}], but we have not previously attempted predictions of new experimental effects from this model.

RESULTS

In this new work, we construct an improved decision tree model for the combined influence of EGF and fibronectin on fibroblast cell migration based on a wider spectrum of experimental protein signaling and cell motility measurements, and directly test a significant and non-intuitive a priori prediction for the outcome of a targeted molecular intervention into the signaling network: that partially reducing activation of MLC would increase cell motility on moderately adhesive surfaces. This prediction was indeed confirmed experimentally: partial inhibition of the activating MLC kinase (MLCK) upstream using the pharmacologic agent ML-7 resulted in increased motility of NR6 fibroblasts. We further extended this exciting finding by showing that partial reduction of MLC activation similarly enhanced the transmigration of the human breast carcinoma cell line MDA-213 through a Matrigel barrier.

CONCLUSION

These findings specifically highlight a central regulatory role for transcellular contractility in governing cell motility, while at the same time demonstrating the value of a decision tree approach to a systems "signal-response" model in discerning non-intuitive behavior arising from integrated operation a cell signaling network.

Enantiomeric separation and determination of absolute stereochemistry of asymmetric molecules in drug discovery—Building chiral technology toolboxes

The application of Chiral Technology, or the (extensive) use of techniques or tools for the determination of absolute stereochemistry and the enantiomeric or chiral separation of racemic small molecule potential lead compounds, has been critical to successfully discovering and developing chiral drugs in the pharmaceutical industry. This has been due to the rapid increase over the past 10-15 years in potential drug candidates containing one or more asymmetric centers. Based on the experiences of one pharmaceutical company, a summary of the establishment of a Chiral Technology toolbox, including the implementation of known tools as well as the design, development, and implementation of new Chiral Technology tools, is provided.

A Simple Parallel Analytical Method of Prenatal Screening

Protein microarray has progressed rapidly in the past few years, but it is still hard to popularize it in many developing countries or small hospitals owing to the technical expertise required in practice. We developed a cheap and easy-to-use protein microarray based on dot immunogold filtration assay for parallel analysis of ToRCH-related antibodies including Toxoplasma gondii, rubella virus, cytomegalovirus and herpes simplex virus type 1 and 2 in sera of pregnant women. It does not require any expensive instruments and the assay results can be clearly recognized by the naked eye. We analyzed 186 random sera of outpatients at the gynecological department with our microarray and commercial ELISA kit, and the results showed there was no significant difference between the two detection methods. Validated by clinical application, the microarray is easy to use and has a unique advantage in cost and time. It is more suitable for mass prenatal screening or epidemiological screening than the ELISA format.

Technology insight: pharmacoproteomics for cancer--promises of patient-tailored medicine using protein microarrays

Patient-tailored medicine can be defined as the selection of specific therapeutics to treat disease in a particular individual based on genetic, genomic or proteomic information. While individualized treatments have been used in medicine for years, advances in cancer treatment have now generated a need to more precisely define and identify those patients who will derive the most benefit from new-targeted agents. Cellular signaling pathways are a protein-based network, and the intended drug effect is to disrupt aberrant protein phosphorylation-based enzymatic activity and epigenetic phenomena. Pharmacoproteomics, or the tailoring of therapy based on proteomic knowledge, will begin to take a central role in this process. A new type of protein array platform, the reverse-phase protein microarray, shows potential for providing detailed information about the state of the cellular 'circuitry' from small samples such as patient biopsy specimens. Measurements of hundreds of specific phosphorylated proteins that span large classes of important signaling pathways can be obtained at once from only a few thousand cells. Clinical implementation of these new proteomic tools to aid the clinical, medical and surgical oncologist in making decisions about patient care will now require thoughtful communication between practicing clinicians and research scientists.

Genomic profiling in clinical oncology. The predictive value of genomic information in cancer management

Genomic profiling is a significant addition to the clinician's armamentarium, enabling more specific diagnosis and targeted treatment of a wide range of diseases, including cancer. Although not yet widely used in a clinical setting, the new technology is providing detailed information about the particular genes expressed in malignant tissues. The predictive value of this information has been demonstrated in small clinical trials. The results of these and other groundbreaking studies are briefly reviewed.

The characterization of the invasion phenotype of uveal melanoma tumour cells shows the presence of MUC18 and HMG-1 metastasis markers and leads to the identification of DJ-1 as a potential serum biomarker

Uveal malignant melanoma (UM) is the most frequent primary intraocular tumour in adult humans. Because the survival rate of patients with UM has changed little in the past few decades, a better understanding of the molecular events governing UM development and the identification of markers indicating the potential for metastasis at the time of diagnosis are necessary to design improved and more specific treatments. In this study, we investigated UM tumour development by comparing two recently established UM cultures with different invasion potential by two-dimensional gel electrophoresis. Protein features expressed differentially were identified by mass spectrometric analysis. Potential markers were assayed in both cultures and in long-term established UM cell lines (UW-1, OCM-1, SP6.5 and 92.1) by Western blotting and their role in invasion analysed using Matrigel membranes. Comparative analysis revealed that UM cultures with low- and high-grade invasion potential differ in their cellular metabolism and, more interestingly, in several cancer-associated proteins, including those implicated in cell adhesion and migration, proliferation and various oncogenes. Our data indicate a correlation between MUC18 and HMG-1 expression and the invasiveness of UM cells. We also demonstrate the expression and secretion of DJ-1 oncoprotein by UM cells. We suggest a possible role for MUC18 and HMG-1 proteins in UM cell invasion. The secretion of DJ-1 by UM cells, and the ability to detect this protein in UM patients' sera implicate it as a potential noninvasive biomarker for this malignancy.

Extraction of high-integrity RNA suitable for microarray gene expression analysis from long-term stored human thyroid tissues

INTRODUCTION

Isolation of high-quality RNA from fresh-frozen thyroid tissues stored for more than a decade would open novel options for gene expression profiling. Herein, we describe successful extraction of high-integrity RNA from human thyroid tissues that were stored for more than a decade.

METHODS

Seventy-nine samples (15 goitres, 20 follicular adenomas, 30 papillary carcinomas, 14 follicular carcinomas) that were shock-frozen in isopentane and stored for a median of 11 years (range 1-16 years) were processed using standard precipitation and column filtration techniques. RNA integrity was assessed by electrophoresis using the RNA integrity number (RIN) algorithm and by gene expression profiling determining the 3'/5' ratio of the glyceraldehyde-3-phosphate dehydrogenase (GAPDH) gene and the percentage of transcripts detected on the Affymetrix U133 2.0 human genome GeneChip.

RESULTS

The median RNA yield was 1.9 microg/mg tissue (papillary carcinoma 2.1 microg/mg, range 0.2-7.2 microg/mg; follicular carcinoma 2.4 microg/mg, range 0.2-3.2 microg/mg; goitre 1.4 microg/mg, range 0.1-5.4 microg/mg; follicular adenoma 1.6 microg/mg, range 0.1-6.2 microg/mg; p = 0.46) with an 8.6 (7.3-9.8) median RIN. The median GAPDH gene 3'/5' ratio was 1.43 (1.34-1.52) and the median percentage of present calls was 48.1% (42.7-52.0%).

CONCLUSIONS

Age and entity independent RNA suitable for expression profiling can be extracted from long-term stored fresh-frozen human thyroid tissues.

Proteomic analysis in cancer research: potential application in clinical use

The ultimate goal of cancer proteomics is to adapt proteomic technologies for routine use in clinical laboratories for the purpose of diagnostic and prognostic classification of disease states, as well as in evaluating drug toxicity and efficacy. The novel technologies allows researchers to facilitate the comprehensive analyses of genomes, transcriptomes, and proteomes in health and disease. The information that is expected from such technologies may soon exert a dramatic change in cancer research and impact dramatically on the care of cancer patients. Analysis of tumor-specific proteomic profiles may also allow better understanding of tumor development and the identification of novel targets for cancer therapy. The localization of gene products, which is often difficult to deduce from the sequence, can be determined experimentally. Mechanisms, such as regulation of protein function by proteolysis, recycling, and isolation in cell compartments, affect gene products, not genes. Finally, protein-protein interactions and the molecular composition of cellular structures can be determined only at the protein level. The biological variability among patient samples as well as the great dynamic range of biomarker concentrations are currently the main challenges facing efforts to deduce diagnostic patterns that are unique to specific disease states. While several strategies exist to address this problem, we have tried to offer a wide perspective about the current possibilities.

Determination of sequential mutation accumulation in pancreas and bile duct brushing cytology

Neoplastic progression is characterized by clonal expansion of tumor cells associated with accumulation of mutational damage. The timing of mutation acquisition could be of value in distinguishing preneoplastic conditions from early and advanced cancer as well as characterizing tumor aggressiveness and treatment response. Using quantitative methods applied to microdissected cell clusters selected according to cytomorphologic features, we sought to demonstrate the feasibility and efficacy for determining the time and course of mutation accumulation in pancreatobiliary cytology specimens. In all, 40 pancreatic duct and 21 biliary brushing cytology specimens were retrieved from the cytology database. Xylene-resistant markings were placed on the slide underside and coverslips removed. Clusters of benign, atypical and malignant cells were manually microdissected and DNA extracted. Mutations (allelic imbalance) (loss of heterozygosity) were quantitatively determined for a broad panel of 15 markers (1p, 3p, 5q, 9p, 10q, 17p, 17q, 21q, 22q) as well as point mutation in K-ras-2 using PCR/capillary electrophoresis. Time course was based on earlier mutations having a higher proportion of mutant DNA for a particular marker. The descending frequency of detectable mutational involvement in pancreatic cytology was K-ras-2 point mutation (58%), 3p25-26 and 17q21 (35%), 5q23 (33%), 1p36 (28%), followed by the remaining molecular markers. The descending frequency of mutational content in bile duct cytology was 17p13, 1p36, 3p25-26, and 5q23 followed by remaining molecular markers. K-ras-2 point mutation was not seen in bile duct specimens. While there was overlap in the spectrum of mutational markers in pancreatic duct and biliary brushing cytology, the temporal profile was significantly different (P<0.001). Pancreatic and biliary neoplasia progression involves distinct subset of accumulated defined mutations. Determination of timing of the mutational damage in cytologic material could be incorporated in the work-up and help in making a more definitive diagnosis of malignancy in pancreatobiliary cytology specimens.

Mechanisms of Disease: preclinical reports of antineoplastic synergistic action of bisphosphonates

For patients with malignant bone disease, bisphosphonate therapy is the standard treatment. Preclinical and preliminary clinical data suggest that bisphosphonates have direct or indirect antitumor effects: they affect growth-factor release, cancer-cell adhesion, invasion and viability, angiogenesis, and apoptosis of cancer cells. These effects might be enhanced through co-administration with chemotherapy agents, biological agents, or both. We survey the biochemical pathways and molecular targets of bisphosphonates, and discuss the molecular mechanisms of these antitumor effects, as well as the documented antineoplastic preclinical effects of bisphosphonates used in combination with cytotoxic and biological drugs. Moreover, the positive interactions between bisphosphonates and farnesyltransferase inhibitors, KIT receptor tyrosine kinase inhibitors (e.g. imatinib mesylate) and cyclo-oxygenase-2 inhibitors are discussed in relation to their potential synergistic and additive effects. We briefly discuss identification of new molecular targets of bisphosphonates from genomic and proteomic analysis, and highlight the cellular consequences of drug-related enzyme inhibition.