Genomics and proteomics: emerging technologies in clinical cancer research

A comprehensive review on anticancer evaluation techniques

The development of effective anticancer strategies and the improvement of our understanding of cancer need analytical tools. Utilizing a variety of analytical approaches while investigating anti-cancer medicines gives us a thorough understanding of the traits and mechanisms concerned to cancer cells, which enables us to develop potent treatments to combat them. The importance of anticancer research may be attributed to various analytical techniques that contributes to the identification of therapeutic targets and the assessment of medication efficacy, which are crucial things in expanding our understanding of cancer biology. The study looks at methods that are often used in cancer research, including cell viability assays, clonogenic assay, flow cytometry, 2D electrophoresis, microarray, immunofluorescence, western blot caspase activation assay, bioinformatics, etc. The fundamentals, applications, and how each technique analytical advances our understanding of cancer are briefly reviewed.

Role of microRNA dysregulation in childhood acute leukemias: Diagnostics, monitoring and therapeutics: A comprehensive review

MicroRNAs (miRNAs) are short noncoding RNAs that regulate the expression of genes by sequence-specific binding to mRNA to either promote or block its translation; they can also act as tumor suppressors (e.g., let-7b, miR-29a, miR-99, mir-100, miR-155, and miR-181) and/or oncogenes (e.g., miR-29a, miR-125b, miR-143-p3, mir-155, miR-181, miR-183, miR-196b, and miR-223) in childhood acute leukemia (AL). Differentially expressed miRNAs are important factors associated with the initiation and progression of AL. As shown in many studies, they can be used as noninvasive diagnostic and prognostic biomarkers, which are useful in monitoring early stages of AL development or during therapy (e.g., miR-125b, miR-146b, miR-181c, and miR-4786), accurate classification of different cellular or molecular AL subgroups (e.g., let-7b, miR-98, miR-100, miR-128b, and miR-223), and identification and development of new therapeutic agents (e.g., mir-10, miR-125b, miR-203, miR-210, miR-335). Specific miRNA patterns have also been described for commonly used AL therapy drugs (e.g., miR-125b and miR-223 for doxorubicin, miR-335 and miR-1208 for prednisolone, and miR-203 for imatinib), uncovering miRNAs that are associated with treatment response. In the current review, the role of miRNAs in the development, progression, and therapy monitoring of pediatric ALs will be presented and discussed.

Identification of Haptoglobin as a Readout of rhGH Therapy in GH Deficiency

BACKGROUND

GH deficiency (GHD) is characterized by a cluster of cardiovascular risk factors and subtle inflammation. We aimed to demonstrate, through a proteomic approach, molecules directly modulated by GHD and involved in the inflammatory state.

METHODS

Ten children with isolated GHD were studied before and after 1 year of treatment with rhGH and compared with 14 matched controls. A two-dimensional electrophoresis plasma proteomics analysis was performed at baseline and after GH treatment to identify the top molecules modulated by GH. In vitro studies on human hepatoma (HepG2) cells were performed to validate the data.

RESULTS

Twelve of 20 proteomic spots were predicted to be isoforms α and β of haptoglobin (Hp) and confirmed by liquid chromatography tandem mass spectrometry and Western immunoblot analyses. Hp levels were higher in patients with GHD than controls at baseline (P < 0.001) and were reduced following GH treatment (P < 0.01). In HepG2 cells, both GH and IGF-1 were able to downregulate IL-6-induced Hp secretion. Moreover, Hp secretion was restored in pegvisomant-treated HepG2 cells.

CONCLUSIONS

Hp is a molecule acting in the inflammatory state of GHD and a possible biomarker for GH treatment. Nevertheless, the contribution of other factors and the molecular pathways involved in the GH downregulation of Hp remain to be clearly defined.

Volatile Compounds Are Involved in Cellular Crosstalk and Upregulation

Cell-cell cross talk is of great importance in cancer research due to its major role in proliferation, differentiation, migration, and influence on the apoptotic pathway. Different cell-cell communication mechanisms have come mainly from proteomic and genomic approaches. In this paper, a new route is reported for cross talk between cancer cells that occurs, even when they are far away from each other. Single-cell and culture analysis shows that upregulation of cancer cells emits hundreds of volatile organic compounds (VOCs) into their headspace. Part of the VOCs remains without any change, disregarding the biological environment around it. The other part of the VOCs is exchanged between monocultures of the cells as well as between co-cultures of the cells with no physical contact between them, leading to different changes in growth than when left on their own. The chemical nature and composition of these VOCs have been determined and are discussed herein. Cell-to-cell cross talk has the advantage of being suitable for transfer/diffusion over relatively long distances. It would thus be expected to serve as a shuttling pad toward the development of advanced approaches that could enable very early detection of cancer and/or monitoring of metastasis and related cancer therapy.

Radiomics features analysis of PET images in oropharyngeal and hypopharyngeal cancer

This study used radiomics image analysis to examine the differences of texture feature values extracted from oropharyngeal and hypopharyngeal cancer positron emission tomography (PET) images on various tumor segmentations, and finds the proper and stable feature groups. A total of 80 oropharyngeal and hypopharyngeal cancer cases were retrospectively recruited. Radiomics method was applied to the PET image for the 80 oropharyngeal and hypopharyngeal cancer cases to extract texture features from various defined metabolic volumes. Kruskal-Wallis one-way analysis of variance method was used to test whether feature value difference exists between groups, which were grouped by stage, response to treatment, and recurrence. If there was a significant difference, the corresponding feature cutoff value was applied to the Kaplan-Meier estimator to estimate the survival functions. For the various defined metabolic volumes, there were 16 features that had significant differences between early (T1, T2) and late tumor stages (T3, T4). Five images and 2 textural features were found to be able to predict the tumor response and recurrence, respectively, with the areas under the receiver operating characteristic curves reaching 0.7. The histogram entropy was found to be a good predictor of overall survival (OS) and primary relapse-free survival (PRFS) of oropharyngeal and hypopharyngeal cancer patients. Textural features from PET images provide predictive and prognostic information in tumor staging, tumor response, recurrence, and have the potential to be a prognosticator for OS and PRFS in oropharyngeal and hypopharyngeal cancer.

Profiling Single Cancer Cells with Volatolomics Approach

Single-cell analysis is a rapidly evolving to characterize molecular information at the individual cell level. Here, we present a new approach with the potential to overcome several key challenges facing the currently available techniques. The approach is based on the identification of volatile organic compounds (VOCs), viz. organic compounds having relatively high vapor pressure, emitted to the cell's headspace. This concept is demonstrated using lung cancer cells with various p53 genetic status and normal lung cells. The VOCs were analyzed by gas chromatography combined with mass spectrometry. Among hundreds of detected compounds, 18 VOCs showed significant changes in their concentration levels in tumor cells versus control. The composition of these VOCs was found to depend, also, on the sub-molecular structure of the p53 genetic status. Analyzing the VOCs offers a complementary way of querying the molecular mechanisms of cancer as well as of developing new generation(s) of biomedical approaches for personalized screening and diagnosis.

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Measurement of VOCs was achieved at the single-cell level

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Genetic changes influence the emitted volatiles of single and bulk cancer cells

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Single-cell VOC analysis measures population heterogeneity in initial stage of tumors

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Volatolomics research can promote non-invasive, simple, and cost-effective diagnostics

Proteomics: A new perspective for cancer

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

SWOG S0709: Randomized Phase II Trial of Erlotinib versus Erlotinib Plus Carboplatin/Paclitaxel in Patients with Advanced Non-Small Cell Lung Cancer and Impaired Performance Status as Selected by a Serum Proteomics Assay

INTRODUCTION

Patients with advanced-stage non-small cell lung cancer (NSCLC) and borderline performance status (performance status 2 [PS2]) are often excluded from clinical trials and platinum-based therapy. In light of the potential role for serum proteomics in predicting the benefit of erlotinib beyond that of epidermal growth factor receptor gene (EGFR) mutational status, we conducted a trial in which the Veristrat proteomics assay was used for data enrichment when selecting a cohort of patients with NSCLC and PS2 to receive erlotinib with and without chemotherapy.

METHODS

Patients with metastatic NSCLC, PS2, acceptable end-organ function, and Veristrat-good status were randomly assigned to receive either 150 mg of erlotinib orally daily (arm 1) or 150 mg of erlotinib orally daily on days 2 through16 plus four cycles of carboplatin (area under the curve = 5 on day 1) and paclitaxel (200 mg/m(2) intravenously on day 1) followed by 150 mg of erlotinib orally (arm 2). The arm 2 agents were pharmacodynamically separated to mitigate potential antagonism. The arm with superior observed median progression-free survival (PFS) would be selected for further evaluation, but only if PFS lasted for at least 3 months.

RESULTS

The trial terminated before the planned accrual of 98 patients for regulatory reasons. A total of 156 patients were screened. Of the 83 (59%) who were classified as Veristrat good, 59 met the trial eligibility criteria and were randomly assigned to one of two arms (33 patients in arm 1 and 26 in arm 2). The patients in arm 2 patients had a higher response rate (23% versus 6%, p = 0.06), disease control rate (77% versus 41%, p = 0.0046), median PFS (4.6 versus 1.6 months, p = 0.06), and median overall survival (11 versus 6 months, p = 0.27). Treatment-related grade 4 adverse events were seen in two patients in arm 1 (thrombosis and hypomagnesemia) and in five patients in arm 2 (neutropenia in five, febrile neutropenia in one, and leukopenia in one).

CONCLUSIONS

In a proteomics-enriched cohort of patients with NSCLC and PS2, pharmacodynamically separated erlotinib plus chemotherapy had better efficacy than did erlotinib alone and surpassed the protocol-specified benchmark of PFS of at least 3 months required for further study.

Laser capture microdissection: Big data from small samples

Any tissue is made up of a heterogeneous mix of spatially distributed cell types. In response to any (patho) physiological cue, responses of each cell type in any given tissue may be unique and cannot be homogenized across cell-types and spatial co-ordinates. For example, in response to myocardial infarction, on one hand myocytes and fibroblasts of the heart tissue respond differently. On the other hand, myocytes in the infarct core respond differently compared to those in the peri-infarct zone. Therefore, isolation of pure targeted cells is an important and essential step for the molecular analysis of cells involved in the progression of disease. Laser capture microdissection (LCM) is powerful to obtain a pure targeted cell subgroup, or even a single cell, quickly and precisely under the microscope, successfully tackling the problem of tissue heterogeneity in molecular analysis. This review presents an overview of LCM technology, the principles, advantages and limitations and its down-stream applications in the fields of proteomics, genomics and transcriptomics. With powerful technologies and appropriate applications, this technique provides unprecedented insights into cell biology from cells grown in their natural tissue habitat as opposed to those cultured in artificial petri dish conditions.

Radiomic feature clusters and prognostic signatures specific for Lung and Head & Neck cancer

Radiomics provides a comprehensive quantification of tumor phenotypes by extracting and mining large number of quantitative image features. To reduce the redundancy and compare the prognostic characteristics of radiomic features across cancer types, we investigated cancer-specific radiomic feature clusters in four independent Lung and Head & Neck (H∓N) cancer cohorts (in total 878 patients). Radiomic features were extracted from the pre-treatment computed tomography (CT) images. Consensus clustering resulted in eleven and thirteen stable radiomic feature clusters for Lung and H & N cancer, respectively. These clusters were validated in independent external validation cohorts using rand statistic (Lung RS = 0.92, p < 0.001, H & N RS = 0.92, p < 0.001). Our analysis indicated both common as well as cancer-specific clustering and clinical associations of radiomic features. Strongest associations with clinical parameters: Prognosis Lung CI = 0.60 ± 0.01, Prognosis H & N CI = 0.68 ± 0.01; Lung histology AUC = 0.56 ± 0.03, Lung stage AUC = 0.61 ± 0.01, H & N HPV AUC = 0.58 ± 0.03, H & N stage AUC = 0.77 ± 0.02. Full utilization of these cancer-specific characteristics of image features may further improve radiomic biomarkers, providing a non-invasive way of quantifying and monitoring tumor phenotypic characteristics in clinical practice.

Identification of chemoresistant factors by protein expression analysis with iTRAQ for head and neck carcinoma

Background:

Cisplatin and other anticancer drugs are important in the treatment of head and neck squamous cell carcinoma; however, some tumours develop drug resistance. If chemoresistance could be determined before treatment, unnecessary drug administration would be avoided. Here, we investigated chemoresistance factors by comprehensive analyses at the protein level.

Methods:

Four human carcinoma cell lines were used: cisplatin-sensitive UM-SCC-23, UM-SCC-23-CDDPR with acquired cisplatin resistance, naturally cisplatin-resistant UM-SCC-81B, and UM-SCC-23/WR with acquired 5-fluorouracil resistance. Extracted proteins were labelled with iTRAQ and analysed by tandem mass spectrometry to identify resistance. Protein expression was confirmed by western blotting and functional analysis was carried out using siRNA.

Results:

Thirteen multiple-drug resistance proteins were identified, as well as seven proteins with specific resistance to cisplatin, including α-enolase. Differential expression of these proteins in cisplatin-resistant and -sensitive cell lines was confirmed by western blotting. Functional analysis for α-enolase by siRNA showed that cisplatin sensitivity significantly was increased in UM-SCC-81B and slightly in UM-SCC-23-CDDPR but not in UM-SCC-23/WR cells.

Conclusions:

We identified proteins thought to mediate anticancer drug resistance using recent proteome technology and identified α-enolase as a true cisplatin chemoresistance factor. Such proteins could be used as biomarkers for anticancer agent resistance and as targets of cancer therapy.

Ezrin expression and cell survival regulation in colorectal cancer

Colorectal cancer (CRC) is the second largest cause of cancer deaths in the United States. A key barrier that prevents better outcomes for this type of cancer as well as other solid tumors is the lack of effective therapies against the metastatic disease. Thus there is an urgent need to fill this gap in cancer therapy. We utilized a 2D-DIGE proteomics approach to identify and characterize proteins that are differentially regulated between primary colon tumor and liver metastatic deposits of the IGF1R-dependent GEO human CRC xenograft, orthotopically implanted in athymic nude mice that may serve as potential therapeutic targets against CRC metastasis. We observed increased expression of ezrin in liver metastasis in comparison to the primary colonic tumor. Increased ezrin expression was further confirmed by western blot and microarray analyses. Ezrin, a cytoskeletal protein belonging to Ezrin-Radixin-Moesin (ERM) family plays important roles in cell motility, invasion and metastasis. However, its exact function in colorectal cancer is not well characterized. Establishment of advanced GEO cell lines with enhanced liver-metastasizing ability showed a significant increase in ezrin expression in liver metastasis. Increased phosphorylation of ezrin at the T567 site (termed here as p-ezrin T567) was observed in liver metastasis. IHC studies of human CRC patient specimens showed an increased expression of p-ezrin T567 in liver metastasis compared to the primary tumors of the same patient. Ezrin modulation by siRNA, inhibitors and T567A/D point mutations significantly downregulated inhibitors of apoptosis (IAP) proteins XIAP and survivin that have been linked to increased aberrant cell survival and metastasis and increased cell death. Inhibition of the IGF1R signaling pathway by humanized recombinant IGF1R monoclonal antibody MK-0646 in athymic mouse subcutaneous xenografts resulted in inhibition of p-ezrin T567 indicating ezrin signaling is downstream of the IGF1R signaling pathway. We identified increased expression of p-ezrin T567 in CRC liver metastasis in both orthotopically implanted GEO tumors as well as human patient specimens. We report for the first time that p-ezrin T567 is downstream of the IGF1R signaling and demonstrate that ezrin regulates cell survival through survivin/XIAP modulation.

Use of pharmacokinetic/pharmacodynamic biomarkers to support rational cancer drug development

The process of drug development in oncology has struggled to alter at a pace in keeping with the rapid discovery and testing of agents that act on a wide variety of molecular targets. The rational development of such agents requires an understanding of drug effect(s) on their purported target. It is likely that testing these drugs in a framework designed to examine cytotoxic agents will fail to establish their full potential. We discuss how data gained from biomarker investigation might impact on drug development and provide examples that highlight the development, validation and use of pharmacokinetic, and especially pharmacodynamic biomarkers as drug development moves from the laboratory into clinical testing. The challenges of performing assays to satisfy regulatory requirements have been the subject of much debate. We recommend the implementation of appropriate, fit-for-purpose biomarkers in clinical trials of all new cancer drugs.

Application of genomic and proteomic technologies in biomarker discovery

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

Spatial mapping by imaging mass spectrometry offers advancements for rapid definition of human skin proteomic signatures

Investigations into the human skin proteome by classical analytical procedures have not addressed spatial molecular distributions in whole-skin biopsies. The aim of this study was to develop methods for the detection of protein signatures and their spatial disposition in human skin using advanced molecular imaging technology based on mass spectrometry technologies. This technology allows for the generation of protein images at specific molecular weight values without the use of antibody while maintaining tissue architecture. Two experimental approaches were employed: MALDI-MS profiling, where mass spectra were taken from discrete locations based on histology, and MALDI-IMS imaging, where complete molecular images were obtained at various MW values. In addition, proteins were identified by in situ tryptic digestion, sequence analysis of the fragment peptides and protein database searching. We have detected patterns of protein differences that exist between epidermis and dermis as well as subtle regional differences between the papillary and reticular dermis. Furthermore, we were able to detect proteins that are constitutive features of human skin as well as those associated with unique markers of individual variability.

Imaging and 'omic' methods for the molecular diagnosis of cancer

Molecular imaging methods can noninvasively detect specific biological processes that are aberrant in cancer, including upregulated glycolytic metabolism, increased cellular proliferation and altered receptor expression. PET using the glucose analogue 18F-fluoro-2-deoxyglucose, which detects the increased glucose uptake that is a characteristic of tumor cells, has been widely used in the clinic to detect tumors and their responses to treatment; however, there are many new PET tracers being developed for a wide range of biological targets. Magnetic resonance spectroscopy (MRS), which can be used to detect cellular metabolites, can also provide prognostic information, particularly in brain, breast and prostate cancers. An emerging technique, which by hyperpolarizing 13C-labeled cell substrates dramatically enhances their sensitivity to detection, could further extend the use of MRS in molecular imaging in the clinic. Molecular diagnostics applied to serum samples or tumor samples obtained by biopsy, can measure changes at the individual cell level and the underlying changes in gene or protein expression. DNA microarrays enable high-throughput gene-expression profiling, while mass spectrometry can detect thousands of proteins that may be used in the future as biomarkers of cancer. Probing molecular changes will aid not only cancer diagnosis, but also provide tumor grading, based on gene-expression analysis and imaging measurements of cell proliferation and changes in metabolism; staging, based on imaging of metastatic spread and elevation of protein biomarkers; and the detection of therapeutic response, using serial molecular imaging measurements or monitoring of serum markers. The present article provides a summary of the molecular diagnostic methods that are currently being trialed in the clinic.

Mass spectrometry-based proteomics and its potential use in haematological research

In the last decade proteomics has made great progress reaching throughput and comprehensiveness comparable to genomics technologies. Mass spectrometry plays a key role in proteomics and has become an indispensable method for molecular and cellular biology because many cellular changes in response to internal or external stimuli can only be detected at the proteome level. Furthermore, different from genomics which depends on the availability of DNA or RNA, proteomics is not restricted to cellular samples, but also allows the analysis of biological fluids like serum, plasma or urine. This article provides an overview of the recent developments in proteomics techniques useful for haematological research.

Cytokines and cytokine profiles in human autoimmune diseases and animal models of autoimmunity

The precise pathomechanisms of human autoimmune diseases are still poorly understood. However, a deepened understanding of these is urgently needed to improve disease prevention and early detection and guide more specific treatment approaches. In recent years, many new genes and signalling pathways involved in autoimmunity with often overlapping patterns between different disease entities have been detected. Major contributions were made by experiments using DNA microarray technology, which has been used for the analysis of gene expression patterns in chronic inflammatory and autoimmune diseases, among which were rheumatoid arthritis, systemic lupus erythematosus, psoriasis, systemic sclerosis, multiple sclerosis, and type-1 diabetes. In systemic lupus erythematosus, a so-called interferon signature has been identified. In psoriasis, researchers found a particular immune signalling cluster. Moreover the identification of a new subset of inflammatory T cells, so-called Th17 T cells, secreting interleukin (IL)-17 as one of their major cytokines and the identification of the IL-23/IL-17 axis of inflammation regulation, have significantly improved our understanding of autoimmune diseases. Since a plethora of new treatment approaches using antibodies or small molecule inhibitors specifically targeting cytokines, cellular receptors, or signalling mechanisms has emerged in recent years, more individualized treatment for affected patients may be within reach in the future.

Postal survey of physicians and laboratories: practices and perceptions of molecular oncology testing

Background

Molecular oncology testing (MOT) to detect genomic alterations underlying cancer holds promise for improved cancer care. Yet knowledge limitations regarding the delivery of testing services may constrain the translation of scientific advancements into effective health care.

Methods

We conducted a cross-sectional, self-administered, postal survey of active cancer physicians in Ontario, Canada (N = 611) likely to order MOT, and cancer laboratories (N = 99) likely to refer (i.e., referring laboratories) or conduct (i.e., testing laboratories) MOT in 2006, to assess respondents' perceptions of the importance and accessibility of MOT and their preparedness to provide it.

Results

54% of physicians, 63% of testing laboratories and 60% of referring laboratories responded. Most perceived MOT to be important for treatment, diagnosis or prognosis now, and in 5 years (61% – 100%). Yet only 45% of physicians, 59% of testing labs and 53% of referring labs agreed that patients in their region were receiving MOT that is indicated as a standard of care. Physicians and laboratories perceived various barriers to providing MOT, including, among 70% of physicians, a lack of clear guidelines regarding clinical indications, and among laboratories, a lack of funding (73% – 100%). Testing laboratories were confident of their ability to determine whether and which MOT was indicated (77% and 82% respectively), and perceived that key elements of formal and continuing education were helpful (75% – 100%). By contrast, minorities of physicians were confident of their ability to assess whether and which MOT was indicated (46% and 34% respectively), and while majorities considered various continuing educational resources helpful (68% – 75%), only minorities considered key elements of formal education helpful in preparing for MOT (17% – 43%).

Conclusion

Physicians and laboratory professionals were enthusiastic about the value of MOT for cancer care but most did not believe patients were gaining adequate access to clinically necessary testing. Further, our results suggest that many were ill equipped as individual stakeholders, or as a coordinated system of referral and interpretation, to provide MOT. These challenges should inspire educational, training and other interventions to ensure that developments in molecular oncology can result in optimal cancer care.

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.

Development and external validation of prognostic model for 2-year survival of non-small-cell lung cancer patients treated with chemoradiotherapy

PURPOSE

Radiotherapy, combined with chemotherapy, is the treatment of choice for a large group of non-small-cell lung cancer (NSCLC) patients. Recent developments in the treatment of these patients have led to improved survival. However, the clinical TNM stage is highly inaccurate for the prediction of survival, and alternatives are lacking. The objective of this study was to develop and validate a prediction model for survival of NSCLC patients, treated with chemoradiotherapy.

PATIENTS AND METHODS

The clinical data from 377 consecutive inoperable NSCLC patients, Stage I-IIIB, treated radically with chemoradiotherapy were collected. A prognostic model for 2-year survival was developed, using 2-norm support vector machines. The performance of the model was expressed as the area under the curve of the receiver operating characteristic and assessed using leave-one-out cross-validation, as well as two external data sets.

RESULTS

The final multivariate model consisted of gender, World Health Organization performance status, forced expiratory volume in 1 s, number of positive lymph node stations, and gross tumor volume. The area under the curve, assessed by leave-one-out cross-validation, was 0.74, and application of the model to the external data sets yielded an area under the curve of 0.75 and 0.76. A high- and low-risk group could be clearly identified using a risk score based on the model.

CONCLUSION

The multivariate model performed very well and was able to accurately predict the 2-year survival of NSCLC patients treated with chemoradiotherapy. The model could support clinicians in the treatment decision-making process.

The use of gene array technology and proteomics in the search of new targets of diseases for therapeutics

The advent of functional genomics has been greatly broadening our view and accelerating our way in numerous medical research fields. The complete genomic data acquired from the human genome project and the desperate clinical need of comprehensive analytical tools to study complex diseases, has allowed rapid evolution of genomic and proteomic technologies, speeding the rate and number of discoveries in new biomarkers. By jointly using genomics, proteomics and bioinformatics there is a great potential to make considerable contribution to biomarker identification and to revolutionize both the development of new therapies and drug development process.

Genomic analysis of epithelial ovarian cancer

Ovarian cancer is a major health problem for women in the United States. Despite evidence of considerable heterogeneity, most cases of ovarian cancer are treated in a similar fashion. The molecular basis for the clinicopathologic characteristics of these tumors remains poorly defined. Whole genome expression profiling is a genomic tool, which can identify dysregulated genes and uncover unique sub-classes of tumors. The application of this technology to ovarian cancer has provided a solid molecular basis for differences in histology and grade of ovarian tumors. Differentially expressed genes identified pathways implicated in cell proliferation, invasion, motility, chromosomal instability, and gene silencing and provided new insights into the origin and potential treatment of these cancers. The added knowledge provided by global gene expression profiling should allow for a more rational treatment of ovarian cancers. These techniques are leading to a paradigm shift from empirical treatment to an individually tailored approach. This review summarizes the new genomic data on epithelial ovarian cancers of different histology and grade and the impact it will have on our understanding and treatment of this disease.

Advances in genomic and proteomic studies of non-small-cell lung cancer: clinical and translational research perspective

Recent years have brought tremendous progress in the development of genomic and proteomic platforms to study cancer biology. Tests based on these platforms are helpful in early diagnosis, prognosis, and prediction of treatment benefit. Molecular studies performed on minimally invasive material (plasma, sputum) from individuals participating in longitudinal or case-control studies have approximately 70%-90% sensitivity and specificity to detect lung cancer. In operable non-small-cell lung cancer, genomic and proteomic studies yield better prognostic information than pathologic staging. There are several examples of successful identification of predictive assays for benefit from chemotherapy (ERCC1, RRM1, p27Kip1, and p53 expression) or targeted therapies (epidermal growth factor receptor [EGFR] gene copy number, EGFR activating mutations, EGFR protein expression, serum proteomic profile). These markers should be prospectively tested in clinical studies before they can be routinely used in the clinic.

Screening for specific biomarkers in serum for diagnosis of primary biliary cirrhosis using proteomic fingerprint technology

AIM: To screen for the potential protein biomarkers in serum for the diagnosis of primary biliary cirrhosis (PBC) using proteomic fingerprint technology.

METHODS: Proteomic fingerprint technology combining magnetic beads with MALDI-TOF-MS was used to profile and compare the serum proteins from 44 patients with PBC, 32 patients with other hepatic diseases and 43 healthy blood donors. Proteomic patterns associated with PBC were identified by Biomarker Patterns Software. Model of biomarkers was constructed and evaluated using the Biomarker Patterns Software.

RESULTS: A total of 69 discriminating m/z peaks were identified that were related to PBC (P < 0.05). The model of biomarkers constructed by the Biomarker Patterns Software based on the four biomarkers (3445, 4260, 8133 and 16290) generated excellent separation between the PBC and control groups. The sensitivity was 93.3% and the specificity was 95.1%. Blind test data indicated a sensitivity of 92.9% and a specificity of 82.4%.

CONCLUSION: Biomarkers for PBC can be discovered in serum by MALDI-TOF-MS combining the use of magnetic beads. The pattern of combined markers provides a powerful and reliable diagnostic method for PBC with a high sensitivity and specificity.

Connecting chemosensitivity, gene expression and disease

Omics-based investigations offer potentially powerful readouts that might be useful for probing the underlying biology of normal and diseased states, identifying novel therapeutic targets and proposing relevant markers for designing treatment strategies. A vital component of these investigations involves a systematic analysis of gene expression and chemosensitivity data in the context of disease states and small molecule probes into the function of targets responsible for a disease phenotype. Systematic analysis of chemical and pharmacogenetics data offers a possible means to identify novel, small-molecule, potentially therapeutic, agents that affect the phenotype of a particular target. Elegantly simple in concept, the covariation of genetic and chemosensitivity readouts provide a hypothetical link for relating compounds through genomic expression profiles to underlying biology.

Strategic plans to promote head and neck cancer translational research within the radiation therapy oncology group: a report from the translational research program

Head and neck cancer is the fifth most common cancer in the United States, with an overall survival rate of approximately 40-50%. In an effort to improve patient outcomes, research efforts designed to maximize benefit and reduce toxicities of therapy are in progress. Basic research in cancer biology has accelerated this endeavor and provided preclinical data and technology to support clinically relevant advances in early detection, prognostic and predictive biomarkers. Recent completion of the Human Genome Project has promoted the rapid development of novel "omics" technologies that allow more broad based study from a systems biology perspective. However, clinically relevant application of resultant gene signatures to clinical trials within cooperative groups has advanced slowly. In light of the large numbers of variables intrinsic to biomarker studies, validation of preliminary data for clinical implementation presents a significant challenge and may only be realized with large trials that involve significant patient numbers. The Radiation Therapy Oncology Group (RTOG) Head and Neck Cancer Translational Research Program recognizes this problem and brings together three unique features to facilitate this research: (1) availability of large numbers of clinical specimens from homogeneously treated patients through multi-institutional clinical trials; (2) a team of physicians, scientists, and staff focused on patient-oriented head-and-neck cancer research with the common goal of improving cancer care; and (3) a funding mechanism through the RTOG Seed Grant Program. In this position paper we outline strategic plans to further promote translational research within the framework of the RTOG.