Current Drug Targets - Volume 13, Issue 12, 2012

The development of commercial reagents designed specifically for use with formalin-fixed paraffin-embedded (FFPE) tissue has unlocked the diagnostic potential of this prolific resource. The availability of archival FFPE tissue and tissue from current patients make it an ideal resource for molecular testing. Despite its stability and ability to preserve morphological information, FFPE provides a number of technical challenges to the study of biomolecules. In particular, the cross-linking and processing present problems in the extraction and isolation of DNA, RNA and protein and affect their use in downstream analysis. Here we will discuss some of the problems of FFPE tissue, how they can be overcome and how FFPE material can be used within clinical molecular diagnostics.

Molecular profiling of cancers can potentially yield novel gene markers of therapeutic prediction, which would aid our ability to tailor targeted therapy regimens specific to each patient. Public data from gene expression profiling may yield clues as to what oncogenic signaling pathways are deregulated in cancers, and what drugs may effectively counteract the aberrant gene regulation patterns observed. Data are also available on panels of cancer cell lines, which have been both profiled at the gene expression level and extensively characterized for drug responses, allowing us to identify geneto- drug correlations. Profiling tumors from patients undergoing adjuvant or neoadjuvant drug treatment can also yield markers of therapeutic response. In this review, we will examine recent studies aimed at our eventually being able to use the molecular profile of a tumor to predict drug response. The profiling data from these studies is publicly available, and can be re-examined by researchers with different questions in mind, offering us a large number of biomarker candidates that could potentially be tested in the clinical setting.

Being a significant health problem that affects patients in various age groups, breast cancer has been extensively studied to date. Recently, molecular breast cancer classification has advanced significantly with the availability of genomic profiling technologies. Proteomic technologies have also advanced from traditional protein assays including enzyme- linked immunosorbent assay, immunoblotting and immunohistochemistry to more comprehensive approaches including mass spectrometry and reverse phase protein lysate arrays (RPPA). The purpose of this manuscript is to review the current protein markers that influence breast cancer prediction and prognosis and to focus on novel advances in proteomic classification of breast cancer.

Basal-like breast tumors and triple negative breast tumors are high-risk breast cancers that typically carry the poorest prognoses compared with HR (Hormone Receptor)-positive tumors and HER2 (Human Epidermal growth factor Receptor 2)-amplified tumors for known therapies. These subsets of breast cancers exhibit aggressive clinical behavior, pushing margins of invasion, poor clinical outcome, and derive limited benefit from current therapy. This clinical situation is contributed and further aggravated by their less known biology, lack of obvious molecular targets, absence of favorable biomarkers, and their limited response to single-drug therapy. In 2010, Oakman et al., remarked that current therapy fails to curtail the innate aggressive behavior of TNBC (Triple Negative Breast Cancer) in the majority of patients. The poor prognosis coupled with a lack of targeted use of therapies is responsible for the high mortality in this subtype. The present review will examine the existing literature and scrutinize the difficulties that have, to date, limited the understanding of the biology of these tumor cells, and provide a rationale for the development of the concept of combining subtype-specific and pathway-specific drug targets for the therapeutic intervention of the disease.

Anti-cancer clinical drug development is currently costly and slow with a high attrition rate. There is thus an urgent and unmet need to integrate pharmacodynamic biomarkers into early phase clinical trials in the framework provided by the “pharmacologic audit trail” in order to overcome this challenge. This review discusses the rationale, advantages and disadvantages, as well as the practical considerations of various tissue-based approaches to perform pharmacodynamic studies in early phase oncology clinical trials using case histories of molecular targeting agents such as PI3K, m-TOR, HSP90, HDAC and PARP inhibitors. These approaches include the use of normal “surrogate” tissues such as peripheral blood mononuclear cells, platelet-rich plasma, plucked hair follicles, skin biopsies, plasma-based endocrine assays, proteomics, metabolomics and circulating endothelial cells. In addition, the review discusses the use of neoplastic tissues including tumor biopsies, circulating tumor DNA and tumor cells and metabolomic approaches. The utilization of these tissues and technology platforms to study biomarkers will help accelerate the development of molecularly targeted agents for the treatment of cancer.

Animal models of human cancer have evolved in attempts to capture the complexity of the human disease. They encompass two broad types of model, namely those in which the tumor arises in situ and those in which cancer cells or tissue are transplanted. Currently human tumor xenografts are the most widely used model to help predict antitumor efficacy in a preclinical setting and xenograft results for certain disease types such as ovarian cancer and non-small cell lung cancer correlate well with clinical activity if the models are used under appropriate conditions. The genetically engineered mouse (GEM) models allow study of the effects of targeted inhibitors against defined molecular targets. These are becoming increasingly sophisticated to recapitulate the progression of tissue-specific molecular changes found within individual cancers. Non-germline GEM models possess the ability to study the impact of specific cancer genes without some of the limitations inherent in traditional GEM models. While rodents, particularly mice, have been the animal host most frequently used, there is increasing recognition of the value of using larger species especially dogs in the veterinary oncology setting. These have successfully modelled aspects of selected human cancers such as osteosarcoma, GIST and prostate cancer. Individually, these models have relative strengths and weaknesses in mimicking the human disease and appropriately reflecting its cellular and molecular pathology. This review will seek to address where these models can be best used to help predict response to therapeutics.

Neurodegenerative diseases are increasing in prevalence in many countries as the average age of their populations increases, since many of these disorders occur more frequently in elderly individuals, placing an increasing burden on healthcare resources. Most neurodegenerative disorders are associated with accumulations of abnormal proteins in the central nervous system (CNS), which result in neuronal degeneration and ultimately neuronal death. Recent developments in molecular pathology and genetics have allowed the identification of the abnormal proteins involved in many neurodegenerative disorders and the genes that encode these proteins. This has led to a fuller understanding of the mechanisms of many of these diseases, but this has not so far been accompanied by major improvements in diagnostic tests or treatments for these disorders. Prion diseases are rare neurodegenerative disorders that are associated with the accumulation of a misfolded host protein, the prion protein, in the CNS. Prion diseases have been considered as a paradigm for protein misfolding diseases, but there are significant differences between prion diseases and other neurodegenerative disorders, not least in the transmissible nature of prion diseases. In this review we give an overview of the wide range of neurodegenerative diseases that affect humans, and compare the molecular pathology of prion diseases with other neurodegenerative diseases. The concept of proteinopathy as a common mechanism in neurodegenerative disorders is explored, and we highlight the improvements in diagnosis and management required to improve our treatment of these devastating conditions.

Computer simulation can be used to inform in vivo and in vitro experimentation, enabling rapid, low-cost hypothesis generation and directing experimental design in order to test those hypotheses. In this way, in silico models become a scientific instrument for investigation, and so should be developed to high standards, be carefully calibrated and their findings presented in such that they may be reproduced. Here, we outline a framework that supports developing simulations as scientific instruments, and we select cancer systems biology as an exemplar domain, with a particular focus on cellular signalling models. We consider the challenges of lack of data, incomplete knowledge and modelling in the context of a rapidly changing knowledge base. Our framework comprises a process to clearly separate scientific and engineering concerns in model and simulation development, and an argumentation approach to documenting models for rigorous way of recording assumptions and knowledge gaps. We propose interactive, dynamic visualisation tools to enable the biological community to interact with cellular signalling models directly for experimental design. There is a mismatch in scale between these cellular models and tissue structures that are affected by tumours, and bridging this gap requires substantial computational resource. We present concurrent programming as a technology to link scales without losing important details through model simplification. We discuss the value of combining this technology, interactive visualisation, argumentation and model separation to support development of multi-scale models that represent biologically plausible cells arranged in biologically plausible structures that model cell behaviour, interactions and response to therapeutic interventions.

Pneumocystis pneumonia (PCP) remains a leading opportunistic infection in patients with weakened immune systems. The fungus causing the infection belongs to the genus, Pneumocystis, and its members are found in a large variety of mammals. Adaptation to the lung environment of a host with an intact immune system has been a key to its successful survival. Unfortunately, the metabolic strategies used by these fungi to grow and survive in this context are largely unknown. There were considerable impediments to standard approaches for investigation of this unique pathogen, the most problematic being the lack of a long term in vitro culture system. The absence of an ex vivo cultivation method remains today, and many fundamental scientific questions about the basic biology, metabolism, and life cycle of Pneumocystis are unanswered. Recent progress in sequencing of the Pneumocystis carinii genome, a species infecting rats, permitted a more informative search for genes and biological pathways within this pathogen that are known to be targets for existing antifungal agents. In this work, we review the classes of antifungal drugs with respect to their potential applicability to the treatment of PCP. Classes covered in the review are the azoles, polyenes, allylamines, and echinocandins. Factors limiting the use of standard antifungal treatments and the currently available alternatives (trimethoprim-sulfamethoxazole, atovaquone, and pentamidine) are discussed. A summary of genomic sequences within Pneumocystis carinii associated with the corresponding targeted biological pathways is provided. All sequences are available via the Pneumocystis Genome Project at http://pgp.cchmc.org/.