Future of personalized medicine in oncology: a systems biology approach

Overcoming implementation challenges of personalized cancer therapy

Personalized cancer therapy is based on the precept that detailed molecular characterization of the patient's tumour and its microenvironment will enable tailored therapies to improve outcomes and decrease toxicity. The goal of personalized therapy is to target aberrations that drive tumour growth and survival, by administering the right drug combination for the right person. This is becoming increasingly achievable with advances in high-throughput technologies to characterize tumours and the expanding repertoire of molecularly targeted therapies. However, there are numerous challenges that need to be surpassed before delivering on the promise of personalized cancer therapy. These include tumour heterogeneity and molecular evolution, costs and potential morbidity of biopsies, lack of effective drugs against most genomic aberrations, technical limitations of molecular tests, and reimbursement and regulatory hurdles. Critically, the 'hype' surrounding personalized cancer therapy must be tempered with realistic expectations, which, today, encompass increased survival times for only a portion of patients.

Coverage of genomic medicine: information gap between lay public and scientists

The sharing of information between the lay public and medical professionals is crucial to the conduct of personalized medicine using genomic information in the near future. Mass media, such as newspapers, can play an important role in disseminating scientific information. However, studies on the role of newspaper coverage of genome-related articles are highly limited. We investigated the coverage of genomic medicine in five major Japanese newspapers (Asahi, Mainichi, Yomiuri, Sankei, and Nikkei) using Nikkei Telecom and articles in scientific journals in PubMed from 1995 to 2009. The number of genome-related articles in all five newspapers temporarily increased in 2000, and began continuously decreasing thereafter from 2001 to 2009. Conversely, there was a continuous increasing trend in the number of genome-related articles in PubMed during this period. The numbers of genome-related articles among the five major newspapers from 1995 to 2009 were significantly different (P = 0.002). Commentaries, research articles, and articles about companies were the most frequent in 2001 and 2003, when the number of genome-related articles transiently increased in the five newspapers. This study highlights the significant gap between newspaper coverage and scientific articles in scientific journals.

Concomitant targeting of tumor cells and induction of T-cell response synergizes to effectively inhibit trastuzumab-resistant breast cancer

Trastuzumab is an iconic rationally designed targeted therapy for HER2-positive breast cancers. However, the low response rate and development of resistance call for novel approaches for the treatment of patients. Here, we report that concurrent targeting of tumor cells and activation of T cells in the tumor microenvironment results in a synergistic inhibitory effect on tumor growth and overcomes resistance in two distinct PTEN loss-mediated trastuzumab-resistant mammary tumor mouse models. In vivo combination treatment with HER2/Neu antibody and Akt inhibitor triciribine effectively inhibited tumor growth in both models via inhibiting PI3K/AKT and mitogen-activated protein kinase signaling accompanied by increased T-cell infiltration in the tumor microenvironment. We showed that both CD8(+) and CD4(+) T cells were essential to the optimal antitumor effect of this combination treatment in an IFN-γ-dependent manner. Importantly, the antitumor activities of HER2/Neu antibody and triciribine combination treatment were further improved when coinhibitory receptor cytotoxic T-lymphocyte-associated antigen 4 was blocked to enhance the T-cell response. Our data indicate that multitargeted combinatorial therapies targeting tumor cells and concomitantly enhancing T-cell response in the tumor microenvironment could cooperate to exert maximal therapeutic activity, suggesting a promising clinical strategy for treating trastuzumab-resistant breast cancers and other advanced malignancies.

Discrepancies between primary tumor and metastasis: a literature review on clinically established biomarkers

The identification of predictive factors of response is critical for the development and appropriate use of anti-cancer agents. The evaluation of biomarkers is usually performed by analyzing the primary tumor tissues but this approach does not take into account potential discrepancies between primary tumor and secondary lesions. This review proposes to describe currently available data regarding differential expression of established biomarkers between primary tumor and matched metastasis. In light of recent data, the need of iterative biopsies in metastatic setting has been suggested but technical and methodological limits in such analyses should not be ignored and this strategy cannot be definitively validated. Complementary studies are still needed since the question of spatial and temporal variability of biomarkers in solid tumors is clearly a key issue in an era where personalized therapy is strongly advocated by clinicians, researchers and patients.

Major Functional Transcriptome of an Inferred Center Regulator of an ER(-) Breast Cancer Model System

We aimed to find clinically relevant gene activities ruled by the signal transducer and activator of transcription 3 (STAT3) proteins in an ER(-) breast cancer population via network approach. STAT3 is negatively associated with both lymph nodal category and stage. MYC is a component of STAT3 network. MYC and STAT3 may co-regulate gene expressions for Warburg effect, stem cell like phenotype, cell proliferation and angiogenesis. We identified a STAT3 network in silico showing its ability in predicting its target gene expressions primarily for specific tumor subtype, tumor progression, treatment options and prognostic features. The aberrant expressions of MYC and STAT3 are enriched in triple negatives (TN). They promote histological grade, vascularity, metastasis and tumor anti-apoptotic activities. VEGFA, STAT3, FOXM1 and METAP2 are druggable targets. High levels of METAP2, MMP7, IGF2 and IGF2R are unfavorable prognostic factors. STAT3 is an inferred center regulator at early cancer development predominantly in TN.

Molecular oncology and the neoadjuvant setting: the perfect blend for treatment personalization and clinical trial design

Breast cancer is a heterogeneous disease. Predictive molecular markers are crucial in patient management, but the only recommended predictive biomarkers are estrogen and progesterone receptors and HER2. There are many new targeted therapies, and although the target pathway expression is readily analyzed on conventional pathology, the dynamic response cannot be assessed and pathway expression is no guarantee it has a major driver role, even if mutated. Selecting therapies requires considering the patient, the molecular characteristics of the tumor, and the microenvironment of the tumor. Thus, the integration of molecular pathology, imaging, and early tumor biological response to therapy may provide evidence of drug activity and allow more rapid changes of therapy. The adaptive response of the tumor is a key resistance mechanism that can be assessed readily in the neoadjuvant setting. Although there are no markers that meet all surrogacy criteria, their use could provide crucial information on mechanisms of drug sensitivity/resistance. Validation of such markers requires a major emphasis on neoadjuvant trials to relate early-biomarker response to outcome.

New omics information for clinical trial utility in the primary setting

Cancer is a complex cellular disease caused by multiple factors via genetic mutations (hereditary or somatic) or environmental factors. The emerging omics technologies, including genomics, epigenomics, transcriptomics, proteomics, metabolomics, and interactomics, are increasingly being used for cancer research and personalized medicine; they have provided new opportunities in the molecular analysis of human cancer with unprecedented speed and detail. The omic approach has brought powerful ability to screen cancer cells at different levels from gene to metabolite and to search for novel drug targets, expounding the drug mechanism of action, identifying adverse effects in unexpected interaction, validating current drug targets, exploring potential applications for novel drugs, and enabling the translation from bench to bedside. As a clinical research tool, the neoadjuvant approach in breast cancer is the perfect setting for individualization of treatment based on clinical, pathological, image-guided, or molecular assessment, based on the omics techniques of tumors during treatment; neoadjuvant treatment offers the ability to discern treatment effect in vivo and may allow smaller trials targeting specific breast cancer subtypes.

The challenge to bring personalized cancer medicine from clinical trials into routine clinical practice: the case of the Institut Gustave Roussy

Research with high throughput technologies has propitiated the segmentation of different types of tumors into very small subgroups characterized by the presence of very rare molecular alterations. The identification of these subgroups and the apparition of new agents targeting these infrequent alterations are already affecting the way in which clinical trials are being conducted with an increased need to identify those patients harboring specific molecular alterations. In this review we describe some of the currently ongoing and future studies at the Institut Gustave Roussy that aim for the identification of potential therapeutic targets for cancer patients with the incorporation of high throughput technologies into daily practice including aCGH, next generation sequencing and the creation of a software that allows for target identification specific for each tumor. The initial intention is to enrich clinical trials with cancer patients carrying certain molecular alterations in order to increase the possibility of demonstrating benefit from a targeted agent. Mid and long term aims are to facilitate and speed up the process of drug development as well as to implement the concept of personalized medicine.

First report of the safety, tolerability, and pharmacokinetics of the Src kinase inhibitor saracatinib (AZD0530) in Japanese patients with advanced solid tumours

BACKGROUND

Saracatinib (AZD0530) is a selective, oral Src inhibitor that has demonstrated antitumour activity in preclinical studies.

METHODS

This open-label, dose-escalation, phase I study evaluated the safety and tolerability of saracatinib in Japanese patients with advanced solid tumours (clinicaltrials.gov NCT00704366). Patients received continuous once-daily oral dosing with saracatinib starting 7 days after a single dose in ascending dose cohorts until dose-limiting toxicity (DLT) or disease progression. Pharmacokinetics and efficacy were also evaluated.

RESULTS

A total of 12 patients received saracatinib at doses of 50 (n = 3), 125 (n = 6), and 175 mg (n = 3). Median durations of exposure were 65, 44, and 16 days in the 50, 125, and 175 mg cohorts, respectively. The most common adverse events were diarrhoea (67 %), nausea (67 %), decreased appetite (58 %), lymphopenia (50 %) and pyrexia (50 %). The most common grade ≥3 adverse events were leukopenia, lymphopenia, neutropenia, and haemoglobin decreased (all 17 %). DLTs occurred in two patients, both in the 175 mg cohort: grade 3 aspartate aminotransferase increased with grade 3 gamma-glutamyltransferase increased (n = 1); and grade 3 hypoxia (n = 1). Following a single dose, saracatinib median t(max) across the doses was 2-4 h, and thereafter plasma concentrations declined in a biphasic manner, with mean terminal half-life of approximately 45 h. Geometric mean saracatinib exposures were 0.8-2.1 times greater than those reported in Caucasian patients. The best response was stable disease (50 mg, n = 2; 125 mg, n = 1).

CONCLUSIONS

Saracatinib was tolerated in Japanese patients with advanced solid tumours at doses up to 125 mg.

Integration of proteomics into systems biology of cancer

Deciphering the complexity and heterogeneity of cancer, benefits from integration of proteomic level data into systems biology efforts. The opportunities available as a result of advances in proteomic technologies, the successes to date, and the challenges involved in integrating diverse datasets are addressed in this review.

Trends in Personalized Therapies in Oncology: The (Venture) Capitalist's Perspective

Oncology is one of the most important fields of personalized medicine as a majority of efforts in this field have recently centered on targeted cancer drug development. New tools are continuously being developed that promise to make cancer treatment more efficacious while causing fewer side effects. Like most industries, the biopharmaceutical industry is also following certain global trends and these are analyzed in this article. As academia and industry are mutually dependent on each other, researchers in the field should be aware of those trends and the immediate consequences for their research. It is important for the future of this field that there is a healthy relationship among all interested parties as the challenges of personalized medicine are becoming ever more complex.

Antibody validation by combining immunohistochemistry and protein extraction from formalin-fixed paraffin-embedded tissues

AIMS

  Personalized cancer treatment strategies depend on comprehensive and detailed characterization of individual human malignancies. Clinical pathology, particularly immunohistochemical evaluation of biomarkers in tissues, is considered to be the approved standard for diagnostic and therapeutic decisions, having a direct influence on patient management and therapy. Although antibody-based approaches are established and integrated successfully into both clinical and research applications, for personalized treatment regimens new demands have been placed on the quality, reproducibility and accuracy of antibody-based assays. To ensure the accuracy of specific antigen detection in immunohistochemistry, we introduce a novel approach for antibody validation.

METHODS AND RESULTS

  In a tandem approach we used the same archival tissue of interest for antibody validation by combining extraction of immunoreactive proteins from formalin-fixed, paraffin-embedded tissue with Western blot analysis and immunohistochemistry. This procedure allows for specification of the antigen detected and for localization of the protein in the tissue. Of the 32 antibodies tested used in research and routine diagnostics, 19 showed reliable specificity in both assays.

CONCLUSION

  This study emphasizes the advantage of combining suitable methods to ensure reproducibility and specific antigen detection. Based on our results, we propose a novel step-by-step strategy to validate antibody specificity and reduce variability of immunohistochemical results.

Delivery success rate of engineered nanoparticles in the presence of the protein corona: a systems-level screening

Nanoparticles (NPs) for medical applications are often introduced into the body via intravenous injections, leading to the formation of a protein corona on their surface due to the interaction with blood plasma proteins. Depending on its composition and time evolution, the corona will modify the biological behavior of the particle. For successful delivery and targeting, it is therefore important to assess on a quantitative basis how and to what extent the presence of the corona perturbs the specific interaction of a designed NP with its cellular target. We present a theoretical systems-level analysis, in which peptides have been covalently coupled to the surface of nanoparticles, describing the delivery success rate in varying conditions, with regard to protein composition of the surrounding fluid. Dynamic modeling and parameter sensitivity analysis proved to be useful and computationally affordable tools to aid in the design of NPs with increased success rate probability in a biological context.

FROM THE CLINICAL EDITOR

The formation of a protein corona consisting of blood plasma proteins on the surface of intravenously delivered nanoparticles may modify the biological behavior of the particles. This team of investigators present a theoretical systems-level analysis of this important and often neglected phenomenon.

Preclinical Remodeling of Human Prostate Cancer through the PTEN/AKT Pathway

Knowledge gained from the identification of genetic and epigenetic alterations that contribute to the progression of prostate cancer in humans is now being implemented in the development of functionally relevant translational models. GEM (genetically modified mouse) models are being developed to incorporate the same molecular defects associated with human prostate cancer. Haploinsufficiency is common in prostate cancer and homozygous loss of PTEN is strongly correlated with advanced disease. In this paper, we discuss the evolution of the PTEN knockout mouse and the cooperation between PTEN and other genetic alterations in tumor development and progression. Additionally, we will outline key points that make these models key players in the development of personalized medicine, as potential tools for target and biomarker development and validation as well as models for drug discovery.

Cancer Genomics: Technology, Discovery, and Translation

In recent years, the increasing awareness that somatic mutations and other genetic aberrations drive human malignancies has led us within reach of personalized cancer medicine (PCM). The implementation of PCM is based on the following premises: genetic aberrations exist in human malignancies; a subset of these aberrations drive oncogenesis and tumor biology; these aberrations are actionable (defined as having the potential to affect management recommendations based on diagnostic, prognostic, and/or predictive implications); and there are highly specific anticancer agents available that effectively modulate these targets. This article highlights the technology underlying cancer genomics and examines the early results of genome sequencing and the challenges met in the discovery of new genetic aberrations. Finally, drawing from experiences gained in a feasibility study of somatic mutation genotyping and targeted exome sequencing led by Princess Margaret Hospital–University Health Network and the Ontario Institute for Cancer Research, the processes, challenges, and issues involved in the translation of cancer genomics to the clinic are discussed.

Who benefits from psychosocial interventions in oncology? A systematic review of psychological moderators of treatment outcome

Medical and demographic characteristics and psychological morbidity of individuals with cancer prior to a psychosocial intervention can influence the efficacy of interventions. However, little is known about the moderating role of patients' psychosocial characteristics on intervention effects. This review sought to identify and synthesize the impacts of psychosocial moderators of the effect of psychosocial interventions on the psychological well-being of cancer patients. A systematic review of the published literature was conducted. Databases searched included PsycINFO, PubMed, MEDLINE, Scopus, CINAHL, Web of Science, and Psychology and Behavioural Sciences Collection. Randomized controlled studies examining a moderator effect of patients' psychosocial characteristics other than baseline depression and anxiety levels were included. Of 199 potential papers, a total of 20 studies, involving 3,340 heterogeneous cancer patients are included. Of the 17 potential psychosocial moderators examined in this review, 14 significantly moderated the effects of interventions. Moderators were categorized into personality traits, mental and physical quality of life, social environment, and self-efficacy. Patients with poorer quality of life, interpersonal relationships and sense of control benefitted more from interventions than those who already had adequate resources. Patients with low levels of optimism and neuroticism, high levels of emotional expressiveness, interpersonal sensitivity, and dispositional hypnotizability also showed greater benefits from various interventions. This review adds to the growing literature aimed at personalizing psychosocial cancer treatment by identifying who benefits from which psychosocial interventions.

Basal/HER2 breast carcinomas: integrating molecular taxonomy with cancer stem cell dynamics to predict primary resistance to trastuzumab (Herceptin)

High rates of inherent primary resistance to the humanized monoclonal antibody trastuzumab (Herceptin) are frequent among HER2 gene-amplified breast carcinomas in both metastatic and adjuvant settings. The clinical efficacy of trastuzumab is highly correlated with its ability to specifically and efficiently target HER2-driven populations of breast cancer stem cells (CSCs). Intriguingly, many of the possible mechanisms by which cancer cells escape trastuzumab involve many of the same biomarkers that have been implicated in the biology of CS-like tumor-initiating cells. In the traditional, one-way hierarchy of CSCs in which all cancer cells descend from special self-renewing CSCs, HER2-positive CSCs can occur solely by self-renewal. Therefore, by targeting CSC self-renewal and resistance, trastuzumab is expected to induce tumor shrinkage and further reduce breast cancer recurrence rates when used alongside traditional therapies. In a new, alternate model, more differentiated non-stem cancer cells can revert to trastuzumab-refractory, CS-like cells via the activation of intrinsic or microenvironmental paths-to-stemness, such as the epithelial-to-mesenchymal transition (EMT). Alternatively, stochastic transitions of trastuzumab-responsive CSCs might also give rise to non-CSC cellular states that lack major attributes of CSCs and, therefore, can remain "hidden" from trastuzumab activity. Here, we hypothesize that a better understanding of the CSC/non-CSC social structure within HER2-overexpressing breast carcinomas is critical for trastuzumab-based treatment decisions in the clinic. First, we decipher the biological significance of CSC features and the EMT on the molecular effects and efficacy of trastuzumab in HER2-positive breast cancer cells. Second, we reinterpret the genetic heterogeneity that differentiates trastuzumab-responders from non-responders in terms of CSC cellular states. Finally, we propose that novel predictive approaches aimed at better forecasting early tumor responses to trastuzumab should identify biological determinants that causally underlie the intrinsic flexibility of HER2-positive CSCs to "enter" into or "exit" from trastuzumab-sensitive states. An accurate integration of CSC cellular states and EMT-related biomarkers with the currently available breast cancer molecular taxonomy may significantly improve our ability to make a priori decisions about whether patients belonging to HER2 subtypes differentially enriched with a "mesenchymal transition signature" (e.g., luminal/HER2 vs. basal/HER2) would distinctly benefit from trastuzumab-based therapy ab initio.

Systems biology data analysis methodology in pharmacogenomics

Pharmacogenetics aims to elucidate the genetic factors underlying the individual's response to pharmacotherapy. Coupled with the recent (and ongoing) progress in high-throughput genotyping, sequencing and other genomic technologies, pharmacogenetics is rapidly transforming into pharmacogenomics, while pursuing the primary goals of identifying and studying the genetic contribution to drug therapy response and adverse effects, and existing drug characterization and new drug discovery. Accomplishment of both of these goals hinges on gaining a better understanding of the underlying biological systems; however, reverse-engineering biological system models from the massive datasets generated by the large-scale genetic epidemiology studies presents a formidable data analysis challenge. In this article, we review the recent progress made in developing such data analysis methodology within the paradigm of systems biology research that broadly aims to gain a 'holistic', or 'mechanistic' understanding of biological systems by attempting to capture the entirety of interactions between the components (genetic and otherwise) of the system.

Association of the 5-HTT gene-linked promoter region (5-HTTLPR) polymorphism with psychiatric disorders: review of psychopathology and pharmacotherapy

Serotonin (5-HT) regulates important biological and psychological processes including mood, and may be associated with the development of several psychiatric disorders. An association between psychopathology and genes that regulate 5-HT neurotransmission is a robust area of research. Identification of the genes responsible for the predisposition, development, and pharmacological response of various psychiatric disorders is crucial to the advancement of our understanding of their underlying neurobiology. This review highlights research investigating 5-HT transporter (5-HTTLPR) polymorphism, because studies investigating the impact of the 5-HTTLPR polymorphism have demonstrated significant associations with many psychiatric disorders. Decreased transcriptional activity of the S allele ("risk allele") may be associated with a heightened amygdala response leading to anxiety-related personality traits, major depressive disorder, suicide attempts, and bipolar disorder. By contrast, increased transcriptional activity of the L allele is considered protective for depression but is also associated with completed suicide, nicotine dependence, and attention deficit hyperactivity disorder. For some disorders, such as post-traumatic stress disorder and major depressive disorder, the research suggests that treatment response may vary by allele (such as an enhanced response to serotonin specific reuptake inhibitors in patients with major depressive disorder and post-traumatic stress disorder with L alleles), and for alcohol dependence, the association and treatment for S or L alleles may vary with alcoholic subtype. While some studies suggest that 5-HTTLPR polymorphism can moderate the response to pharmacotherapy, the association between 5-HTTLPR alleles and therapeutic outcomes is inconsistent. The discovery of triallelic 5-HTTLPR alleles (L(A)/L(G)/S) may help to explain some of the conflicting results of many past association studies, while concurrently providing more meaningful data in the future. Studies assessing 5-HTTLPR as the solitary genetic factor contributing to the etiology of psychiatric disorders continue to face the challenges of statistically small effect sizes and limited replication.

Proteomics and biomarkers in clinical trials for drug development

Proteomics allows characterization of protein structure and function, protein-protein interactions, and peptide modifications. It has given us insight into the perturbations of signaling pathways within tumor cells and has improved the discovery of new therapeutic targets and possible indicators of response to and duration of therapy. The discovery, verification, and validation of novel biomarkers are critical in streamlining clinical development of targeted compounds, and directing rational treatments for patients whose tumors are dependent upon select signaling pathways. Studies are now underway in many diseases to examine the immune or inflammatory proteome, vascular proteome, cancer or disease proteome, and other subsets of the specific pathology microenvironment. Successful assay verification and biological validation of such biomarkers will speed development of potential agents to targetable dominant pathways and lead to selection of individuals most likely to benefit. Reconsideration of analytical and clinical trials methods for acquisition, examination, and translation of proteomics data must occur before we march further into future of drug development.

A new frontier in personalized cancer therapy: mapping molecular changes

Mutations in the genome of a normal cell can affect the function of its many genes and pathways. These alterations could eventually transform the cell from a normal to a malignant state by allowing an uncontrolled proliferation of the cell and formation of a cancer tumor. Each tumor in an individual patient can have hundreds of mutated genes and perturbed pathways. Cancers clinically presenting as the same type or subtype could potentially be very different at the molecular level and thus behave differently in response to therapy. The challenge is to distinguish the key mutations driving the cancer from the background of mutational noise and find ways to effectively target them. The promise is that such a molecular approach to classifying cancer will lead to better diagnostic, prognostic and personalized treatment strategies. This article provides an overview of advances in the molecular characterization of cancers and their applications in therapy.

Functional Genomics Assistant (FUGA): a toolbox for the analysis of complex biological networks

Background

Cellular constituents such as proteins, DNA, and RNA form a complex web of interactions that regulate biochemical homeostasis and determine the dynamic cellular response to external stimuli. It follows that detailed understanding of these patterns is critical for the assessment of fundamental processes in cell biology and pathology. Representation and analysis of cellular constituents through network principles is a promising and popular analytical avenue towards a deeper understanding of molecular mechanisms in a system-wide context.

Findings

We present Functional Genomics Assistant (FUGA) - an extensible and portable MATLAB toolbox for the inference of biological relationships, graph topology analysis, random network simulation, network clustering, and functional enrichment statistics. In contrast to conventional differential expression analysis of individual genes, FUGA offers a framework for the study of system-wide properties of biological networks and highlights putative molecular targets using concepts of systems biology.

Conclusion

FUGA offers a simple and customizable framework for network analysis in a variety of systems biology applications. It is freely available for individual or academic use at http://code.google.com/p/fuga.

Pharmacogenetics of new analgesics

Patient phenotypes in pharmacological pain treatment varies between individuals, which could be partly assigned to their genotypes regarding the targets of classical analgesics (OPRM1, PTGS2) or associated signalling pathways (KCNJ6). Translational and genetic research have identified new targets, for which new analgesics are being developed. This addresses voltage-gated sodium, calcium and potassium channels, for which SCN9A, CACNA1B, KCNQ2 and KCNQ3, respectively, are primary gene candidates because they code for the subunits of the respective channels targeted by analgesics currently in clinical development. Mutations in voltage gated transient receptor potential (TRPV) channels are known from genetic pain research and may modulate the effects of analgesics under development targeting TRPV1 or TRPV3. To this add ligand-gated ion channels including nicotinic acetylcholine receptors, ionotropic glutamate-gated receptors and ATP-gated purinergic P2X receptors with most important subunits coded by CHRNA4, GRIN2B and P2RX7. Among G protein coupled receptors, δ-opioid receptors (coded by OPRD1), cannabinoid receptors (CNR1 and CNR2), metabotropic glutamate receptors (mGluR5 coded by GRM5), bradykinin B(1) (BDKRB1) and 5-HT(1A) (HTR1A) receptors are targeted by new analgesic substances. Finally, nerve growth factor (NGFB), its tyrosine kinase receptor (NTRK1) and the fatty acid amide hydrolase (FAAH) have become targets of interest. For most of these genes, functional variants have been associated with neuro-psychiatric disorders and not yet with analgesia. However, research on the genetic modulation of pain has already identified variants in these genes, relative to pain, which may facilitate the pharmacogenetic assessments of new analgesics. The increased number of candidate pharmacogenetic modulators of analgesic actions may open opportunities for the broader clinical implementation of genotyping information.

Personalized medicine: progress and promise

Personalized medicine is a broad and rapidly advancing field of health care that is informed by each person's unique clinical, genetic, genomic, and environmental information. Personalized medicine depends on multidisciplinary health care teams and integrated technologies (e.g., clinical decision support) to utilize our molecular understanding of disease in order to optimize preventive health care strategies. Human genome information now allows providers to create optimized care plans at every stage of a disease, shifting the focus from reactive to preventive health care. The further integration of personalized medicine into the clinical workflow requires overcoming several barriers in education, accessibility, regulation, and reimbursement. This review focuses on providing a comprehensive understanding of personalized medicine, from scientific discovery at the laboratory bench to integration of these novel ways of understanding human biology at the bedside.

Advances in proteomic strategies toward the early detection of lung cancer

Since the advent of the new proteomics era more than a decade ago, large-scale studies of protein profiling have been exploited to identify the distinctive molecular signatures in a wide array of biological systems spanning areas of basic biological research, various disease states, and biomarker discovery directed toward therapeutic applications. Recent advances in protein separation and identification techniques have significantly improved proteomics approaches, leading to enhancement of the depth and breadth of proteome coverage. Proteomic signatures specific for invasive lung cancer and preinvasive lesions have begun to emerge. In this review we provide a critical assessment of the state of recent advances in proteomic approaches and the biological lessons they have yielded, with specific emphasis on the discovery of biomarker signatures for the early detection of lung cancer.

Clinical trials of antioxidants as cancer prevention agents: past, present, and future

The purpose of this review is to summarize the most important human clinical trials of antioxidants as cancer prevention agents conducted to date, provide an overview of currently ongoing studies, and discuss future steps needed to advance research in this field. To date there have been several large (at least 7000 participants) trials testing the efficacy of antioxidant supplements in preventing cancer. The specific agents (diet-derived direct antioxidants and essential components of antioxidant enzymes) tested in those trials included β-carotene, vitamin E, vitamin C, selenium, retinol, zinc, riboflavin, and molybdenum. None of the completed trials produced convincing evidence to justify the use of traditional antioxidant-related vitamins or minerals for cancer prevention. Our search of ongoing trials identified six projects at various stages of completion. Five of those six trials use selenium as the intervention of interest delivered either alone or in combination with other agents. The lack of success to date can be explained by a variety of factors that need to be considered in the next generation research. These factors include lack of good biological rationale for selecting specific agents of interest; limited number of agents tested to date; use of pharmacological, rather than dietary, doses; and insufficient duration of intervention and follow-up. The latter consideration underscores the need for alternative endpoints that are associated with increased risk of neoplasia (i.e., biomarkers of risk), but are detectable prior to tumor occurrence. Although dietary antioxidants are a large and diverse group of compounds, only a small proportion of candidate agents have been tested. In summary, the strategy of focusing on large high-budget studies using cancer incidence as the endpoint and testing a relatively limited number of antioxidant agents has been largely unsuccessful. This lack of success in previous trials should not preclude us from seeking novel ways of preventing cancer by modulating oxidative balance. On the contrary, the well demonstrated mechanistic link between excessive oxidative stress and carcinogenesis underscores the need for new studies. It appears that future large-scale projects should be preceded by smaller, shorter, less expensive biomarker-based studies that can serve as a link from mechanistic and observational research to human cancer prevention trials. These relatively inexpensive studies would provide human experimental evidence for the likely efficacy, optimum dose, and long-term safety of the intervention of interest that would then guide the design of safe, more definitive large-scale trials.

Current state of our knowledge on brain tumor epidemiology

The overall incidence of brain tumors for benign and malignant tumors combined is 18.71 per 100,000 person-years; 11.52 per 100,000 person-years for benign tumors and 7.19 per 100,000 person-years for malignant tumors. Incidence, response to treatment, and survival after diagnosis vary greatly by age at diagnosis, histologic type of tumor, and degree of neurologic compromise. The only established environmental risk factor for brain tumors is ionizing radiation exposure. Exposure to radiofrequency electromagnetic fields via cell phone use has gained a lot of attention as a potential risk factor for brain tumor development. However, studies have been inconsistent and inconclusive due to systematic differences in study designs and difficulty of accurately measuring cell phone use. Recently studies of genetic risk factors for brain tumors have expanded to genome-wide association studies. In addition, genome-wide studies of somatic genetic changes in tumors show correlation with clinical outcomes.

The Role of Proteomics in the Diagnosis and Treatment of Women's Cancers: Current Trends in Technology and Future Opportunities

Technological and scientific innovations over the last decade have greatly contributed to improved diagnostics, predictive models, and prognosis among cancers affecting women. In fact, an explosion of information in these areas has almost assured future generations that outcomes in cancer will continue to improve. Herein we discuss the current status of breast, cervical, and ovarian cancers as it relates to screening, disease diagnosis, and treatment options. Among the differences in these cancers, it is striking that breast cancer has multiple predictive tests based upon tumor biomarkers and sophisticated, individualized options for prescription therapeutics while ovarian cancer lacks these tools. In addition, cervical cancer leads the way in innovative, cancer-preventative vaccines and multiple screening options to prevent disease progression. For each of these malignancies, emerging proteomic technologies based upon mass spectrometry, stable isotope labeling with amino acids, high-throughput ELISA, tissue or protein microarray techniques, and click chemistry in the pursuit of activity-based profiling can pioneer the next generation of discovery. We will discuss six of the latest techniques to understand proteomics in cancer and highlight research utilizing these techniques with the goal of improvement in the management of women's cancers.

Heat map visualization of complex environmental and biomarker measurements

Over the past decade, the assessment of human systems interactions with the environment has permeated all phases of environmental and public health research. We are invoking lessons learned from the broad discipline of Systems Biology research that focuses primarily on molecular and cellular networks and adapting these concepts to Systems Exposure Science which focuses on interpreting the linkage from environmental measurements and biomonitoring to the expression of biological parameters. A primary tool of systems biology is the visualization of complex genomic and proteomic data using "heat maps" which are rectangular color coded arrays indicating the intensity (or amount) of the dependent variable. Heat maps are flexible in that both the x-axis and y-axis can be arranged to explore a particular hypothesis and allow a fast overview of data with a third quantitative dimension captured as different colors. We are now adapting these tools for interpreting cumulative and aggregate environmental exposure measurements as well as the results from human biomonitoring of biological media including blood, breath and urine. This article uses existing EPA measurements of environmental and biomarker concentrations of polycyclic aromatic hydrocarbons (PAHs) to demonstrate the value of the heat map approach for hypothesis development and to link back to stochastic and mixed effects models that were originally used to assess study results.

A novel network profiling analysis reveals system changes in epithelial-mesenchymal transition

Patient-specific analysis of molecular networks is a promising strategy for making individual risk predictions and treatment decisions in cancer therapy. Although systems biology allows the gene network of a cell to be reconstructed from clinical gene expression data, traditional methods, such as Bayesian networks, only provide an averaged network for all samples. Therefore, these methods cannot reveal patient-specific differences in molecular networks during cancer progression. In this study, we developed a novel statistical method called NetworkProfiler, which infers patient-specific gene regulatory networks for a specific clinical characteristic, such as cancer progression, from gene expression data of cancer patients. We applied NetworkProfiler to microarray gene expression data from 762 cancer cell lines and extracted the system changes that were related to the epithelial-mesenchymal transition (EMT). Out of 1732 possible regulators of E-cadherin, a cell adhesion molecule that modulates the EMT, NetworkProfiler, identified 25 candidate regulators, of which about half have been experimentally verified in the literature. In addition, we used NetworkProfiler to predict EMT-dependent master regulators that enhanced cell adhesion, migration, invasion, and metastasis. In order to further evaluate the performance of NetworkProfiler, we selected Krueppel-like factor 5 (KLF5) from a list of the remaining candidate regulators of E-cadherin and conducted in vitro validation experiments. As a result, we found that knockdown of KLF5 by siRNA significantly decreased E-cadherin expression and induced morphological changes characteristic of EMT. In addition, in vitro experiments of a novel candidate EMT-related microRNA, miR-100, confirmed the involvement of miR-100 in several EMT-related aspects, which was consistent with the predictions obtained by NetworkProfiler.

Uptake of KRAS mutation testing in patients with metastatic colorectal cancer in Europe, Latin America and Asia

The mutation status of the KRAS gene in the tumors of patients with metastatic colorectal cancer (mCRC) is a predictive biomarker for the efficacy of epidermal growth factor receptor monoclonal antibody therapy. The establishment of KRAS mutation testing in this setting represents a significant change to standard diagnostic procedures and a major advance in the personalization of cancer care. Against a changing regulatory background, three cross-sectional surveys of physicians in 14 countries in Europe, Latin America and Asia were conducted in 2008, 2009, and 2010 to investigate the uptake and outcome of KRAS testing for patients with mCRC. Physicians in each year answered questions on four patients (last patient seen and last seen in first-, second- and third-line settings). Fieldwork was carried out February-May 2008, January-April 2009, and January-April 2010. Data from 3,819, 3,740 and 3,820 anonymized, uncoded patient records were collated. The frequency of KRAS testing in patients with mCRC increased from 3% in 2008 to 47% in 2009 and 69% in 2010. The 2010 survey revealed that test results were available within 15 days for 82%, 51% and 98% of the 1679, 679, and 261 tested patients in the European, Latin American and Asian regions, respectively. Cetuximab was the most commonly administered targeted agent in tested patients with KRAS wild-type mCRC (798/1607 patients; 50%) and bevacizumab was the most commonly administered targeted agent in tested patients with KRAS mutant tumors (396/893; 44% overall). In conclusion, KRAS testing is now widely established as a routine diagnostic procedure for patients with mCRC and is used increasingly to guide treatment selection.

Computational model of EGFR and IGF1R pathways in lung cancer: a Systems Biology approach for Translational Oncology

In this paper we propose a Systems Biology approach to understand the molecular biology of the Epidermal Growth Factor Receptor (EGFR, also known as ErbB1/HER1) and type 1 Insulin-like Growth Factor (IGF1R) pathways in non-small cell lung cancer (NSCLC). This approach, combined with Translational Oncology methodologies, is used to address the experimental evidence of a close relationship among EGFR and IGF1R protein expression, by immunohistochemistry (IHC) and gene amplification, by in situ hybridization (FISH) and the corresponding ability to develop a more aggressive behavior. We develop a detailed in silico model, based on ordinary differential equations, of the pathways and study the dynamic implications of receptor alterations on the time behavior of the MAPK cascade down to ERK, which in turn governs proliferation and cell migration. In addition, an extensive sensitivity analysis of the proposed model is carried out and a simplified model is proposed which allows us to infer a similar relationship among EGFR and IGF1R activities and disease outcome.

An integrated genomic approach to the assessment and treatment of acute myeloid leukemia

Traditionally, new scientific advances have been applied quickly to the leukemias based on the ease with which relatively pure samples of malignant cells can be obtained. Currently, our arsenal of approaches used to characterize an individual's acute myeloid leukemia (AML) combines hematopathologic evaluation, flow cytometry, cytogenetic analysis, and molecular studies focused on a few key genes. The advent of high-throughput methods capable of full-genome evaluation presents new options for a revolutionary change in the way we diagnose, characterize, and treat AML. Next-generation DNA sequencing techniques allow full sequencing of a cancer genome or transcriptome, with the hope that this will be affordable for routine clinical care within the decade. Microarray-based testing will define gene and miRNA expression, DNA methylation patterns, chromosomal imbalances, and predisposition to disease and chemosensitivity. The vision for the future entails an integrated and automated approach to these analyses, bringing the possibility of formulating an individualized treatment plan within days of a patient's initial presentation. With these expectations comes the hope that such an approach will lead to decreased toxicities and prolonged survival for patients.

Molecular profiling of cancer--the future of personalized cancer medicine: a primer on cancer biology and the tools necessary to bring molecular testing to the clinic

Cancers arise as a result of an accumulation of genetic aberrations that are either acquired or inborn. Virtually every cancer has its unique set of molecular changes. Technologies have been developed to study cancers and derive molecular characteristics that increasingly have implications for clinical care. Indeed, the identification of key genetic aberrations (molecular drivers) may ultimately translate into dramatic benefit for patients through the development of highly targeted therapies. With the increasing availability of newer, more powerful, and cheaper technologies such as multiplex mutational screening, next generation sequencing, array-based approaches that can determine gene copy numbers, methylation, expression, and others, as well as more sophisticated interpretation of high-throughput molecular information using bioinformatics tools like signatures and predictive algorithms, cancers will routinely be characterized in the near future. This review examines the background information and technologies that clinicians and physician-scientists will need to interpret in order to develop better, personalized treatment strategies.

What can molecular pathology contribute to the management of renal cell carcinoma?

The incidence of renal cell carcinoma (RCC) is increasing and outcomes remain poor. One-third of patients with localized disease will relapse, and 5-year survival for patients with metastatic disease is less than 10%. No molecular test is currently available to identify which patients who have undergone 'curative' surgery will relapse, and which patients will respond to targeted therapy. Some well characterized biochemical pathways, such as those associated with von Hippel-Lindau disease, are aberrantly regulated in RCC and are associated with histological subtype, but the understanding of these pathways contributes little to the clinical management of patients with RCC. Gene expression and sequencing studies have increased our understanding of the genetic basis of the disease but have failed to establish any unified classification to improve molecular stratification or to predict which patients are likely to relapse or respond to targeted therapy. Instead, they have served to highlight that RCC is heterogeneous at histological, morphological, and molecular levels, and that novel approaches are required to resolve the complexity of RCC prognostication and prediction of treatment response.

Personalized therapy for urothelial cancer: review of the clinical evidence

Despite a detailed understanding of the molecular aberrations driving the development of urothelial cancers, this knowledge has not translated into advances for the treatment of this disease. Urothelial cancers are chemosensitive, and platinum-based combination chemotherapy remains the standard of care for advanced disease, as well as neoadjuvant and adjuvant therapy for locally advanced disease. However, nearly half of patients who undergo resection of locally advanced urothelial cancer will relapse and eventually develop platinum-resistant disease. Clinical trials of targeted agents against angiogenesis and growth factors, as well as novel chemotheraputics, have generally been unsuccessful in urothelial cancers. Improvements in the theraputic arsenal for urothelial cancer depend upon identification of new targets and strategies to overcome platinum resistance.

The impact of next-generation sequencing on genomics

This article reviews basic concepts, general applications, and the potential impact of next-generation sequencing (NGS) technologies on genomics, with particular reference to currently available and possible future platforms and bioinformatics. NGS technologies have demonstrated the capacity to sequence DNA at unprecedented speed, thereby enabling previously unimaginable scientific achievements and novel biological applications. But, the massive data produced by NGS also presents a significant challenge for data storage, analyses, and management solutions. Advanced bioinformatic tools are essential for the successful application of NGS technology. As evidenced throughout this review, NGS technologies will have a striking impact on genomic research and the entire biological field. With its ability to tackle the unsolved challenges unconquered by previous genomic technologies, NGS is likely to unravel the complexity of the human genome in terms of genetic variations, some of which may be confined to susceptible loci for some common human conditions. The impact of NGS technologies on genomics will be far reaching and likely change the field for years to come.

GeCo++: a C++ library for genomic features computation and annotation in the presence of variants

We propose a C++ class library developed to the purpose of making the implementation of sequence analysis algorithms easier and faster when genomic annotations and variations need to be considered. The library provides a class hierarchy to seamlessly bind together annotations of genomic elements to sequences and to algorithm results; it allows to evaluate the effect of mutations/variations in terms of both element position shifts and of algorithm results, limiting recalculation to the minimum. Particular care has been posed to keep memory and time overhead into acceptable limits.

AVAILABILITY AND IMPLEMENTATION

A complete tutorial as well as a detailed doxygen generated documentation and source code is freely available at http://bioinformatics.emedea.it/geco, under the GPL license. The library was written in standard ISO C++, and does not depend on external libraries.

The cetuximab experience: developing predictive biomarkers in oncology

The anti-EGF receptor monoclonal antibody cetuximab provides a case study for the development of predictive biomarkers in oncology. The identification and validation of KRAS mutation status as a predictor of lack of benefit from cetuximab in metastatic colorectal cancer provides an important first step. However, KRAS mutation status does not appear to be predictive of cetuximab benefit in advanced non-small-cell lung cancer, illustrating the necessity for separate biomarker validation to occur across tumor types. Numerous candidate biomarkers have been suggested based on noncontrolled exploratory analyses, but they require validation in sufficiently sized controlled studies. Key pending issues include distinguishing markers predictive of treatment benefit from those prognostic of disease outcome, selecting the best specimen for analysis (determining the tissue type and collection site, as well as the sample matrix type); and optimizing and standardizing assay technology and scoring systems, particularly for markers expressed over a continuous dynamic range.

Engineering building blocks for self-assembling protein nanoparticles

Like natural viruses, manmade protein cages for drug delivery are to be ideally formed by repetitive subunits with self-assembling properties, mimicking viral functions and molecular organization. Naturally formed nanostructures (such as viruses, flagella or simpler protein oligomers) can be engineered to acquire specific traits of interest in biomedicine, for instance through the addition of cell targeting agents for desired biodistribution and specific delivery of associated drugs. However, fully artificial constructs would be highly desirable regarding finest tuning and adaptation to precise therapeutic purposes. Although engineering of protein assembling is still in its infancy, arising principles and promising strategies of protein manipulation point out the rational construction of nanoscale protein cages as a feasible concept, reachable through conventional recombinant DNA technologies and microbial protein production.

Personalizing cancer treatment in the age of global genomic analyses: PALB2 gene mutations and the response to DNA damaging agents in pancreatic cancer

Metastasis and drug resistance are the major causes of mortality in patients with pancreatic cancer. Once developed, the progression of pancreatic cancer metastasis is virtually unstoppable with current therapies. Here, we report the remarkable clinical outcome of a patient with advanced, gemcitabine-resistant, pancreatic cancer who was later treated with DNA damaging agents, on the basis of the observation of significant activity of this class of drugs against a personalized xenograft generated from the patient's surgically resected tumor. Mitomycin C treatment, selected on the basis of its robust preclinical activity in a personalized xenograft generated from the patient's tumor, resulted in long-lasting (36+ months) tumor response. Global genomic sequencing revealed biallelic inactivation of the gene encoding PalB2 protein in this patient's cancer; the mutation is predicted to disrupt BRCA1 and BRCA2 interactions critical to DNA double-strand break repair. This work suggests that inactivation of the PALB2 gene is a determinant of response to DNA damage in pancreatic cancer and a new target for personalizing cancer treatment. Integrating personalized xenografts with unbiased exomic sequencing led to customized therapy, tailored to the genetic environment of the patient's tumor, and identification of a new biomarker of drug response in a lethal cancer.

Inactivation of FBXW7/hCDC4-β expression by promoter hypermethylation is associated with favorable prognosis in primary breast cancer

INTRODUCTION

Mutational inactivation of the FBXW7/hCDC4 tumor suppressor gene (TSG) is common in many cancer types, but infrequent in breast cancers. This study investigates the presence and impact of FBXW7/hCDC4 promoter methylation in breast cancer.

METHODS

FBXW7/hCDC4-β expression and promoter methylation was assessed in 161 tumors from two independent breast cancer cohorts. Associations between methylation status and clinicopathologic characteristics were assessed by Fisher's exact test. Survival was analyzed using the Kaplan-Meier method in addition to modeling the risk by use of a multivariate proportional hazard (Cox) model adjusting for possible confounders of survival.

RESULTS

Methylation of the promoter and loss of mRNA expression was found both in cell lines and primary tumors (43% and 51%, respectively). Using Cox modeling, a trend was found towards decreased hazard ratio (HR) for death in women with methylation of FBXW7/hCDC4-β in both cohorts (HR 0.53 (95% CI 0.23 to 1.23) and HR 0.50 (95% CI 0.23 to 1.08), respectively), despite an association between methylation and high-grade tumors (P = 0.017). Interestingly, in subgroups of patients whose tumors are p53 mutated or lymph-node positive, promoter methylation identified patients with significantly improved survival (P = 0.048 and P = 0.017, respectively).

CONCLUSIONS

We demonstrate an alternative mechanism for inactivation of the TSG FBXW7/hCDC4, namely promoter specific methylation. Importantly, in breast cancer, methylation of FBXW7/hCDC4-β is related to favorable prognosis despite its association with poorly differentiated tumors. Future work may define whether FBXW7/hCDC4 methylation is a biomarker of the response to chemotherapy and a target for epigenetic modulation therapy.