摘要:

The ultimate goal of cancer proteomics is to adapt proteomic technologies for routine use in clinical laboratories for the purpose of diagnostic and prognostic classification of disease states, as well as in evaluating drug toxicity and efficacy. Analysis of tumor-specific proteomic profiles may also allow better understanding of tumor development and the identification of novel targets for cancer therapy. The biological variability among patient samples as well as the huge dynamic range of biomarker concentrations are currently the main challenges facing efforts to deduce diagnostic patterns that are unique to specific disease states. While several strategies exist to address this problem, we focus here on cancer classification using mass spectrometry (MS) for proteomic profiling and biomarker identification. Recent advances in MS technology are starting to enable high-throughput profiling of the protein content of complex samples. For cancer classification, the protein samples from cancer patients and noncancer patients or from different cancer stages are analyzed through MS instruments and the MS patterns are used to build a diagnostic classifier. To illustrate the importance of feature selection in cancer classification, we present a method based on support vector machine-recursive feature elimination (SVM-RFE), demonstrated on two cancer datasets from ovarian and lung cancer.

ISSN:1175-2203    

出版商:ADIS    

年代:2005

数据来源: ADIS

摘要:

Acquired resistance to imatinib mesylate is an increasing and continued challenge in the treatment of BCR-ABL tyrosine kinase positive leukemias as well as gastrointestinal stromal tumors. Stable isotope-based dynamic metabolic profiling (SIDMAP) studies conducted in parallel with the development and clinical testing of imatinib revealed that this targeted drug is most effective in controlling glucose transport, direct glucose oxidation for RNA ribose synthesis in the pentose cycle, as well asde novolong-chain fatty acid synthesis. Thus imatinib deprives transformed cells of the key substrate of macromolecule synthesis, malignant cell proliferation, and growth. Tracer-based magnetic resonance spectroscopy studies revealed a restitution of mitochondrial glucose metabolism and an increased energy state by reversing the Warburg effect, consistent with a subsequent decrease in anaerobic glycolysis. Recentin vitroSIDMAP studies that involved myeloid cells isolated from patients who developed resistance against imatinib indicated that non-oxidative ribose synthesis from glucose and decreased mitochondrial glucose oxidation are reliable metabolic signatures of drug resistance and disease progression. There is also evidence that imatinib-resistant cells utilize alternate substrates for macromolecule synthesis to overcome limited glucose transport controlled by imatinib. The main clinical implications involve early detection of imatinib resistance and the identification of new metabolic enzyme targets with the potential of overcoming drug resistance downstream of the various genetic and BCR-ABL-expression derived mechanisms. Metabolic profiling is an essential tool used to predict, clinically detect, and treat targeted drug resistance. This need arises from the fact that targeted drugs are narrowly conceived against genes and proteins but the metabolic network is inherently complex and flexible to activate alternative macromolecule synthesis pathways that targeted drugs fail to control.

ISSN:1175-2203    

出版商:ADIS    

年代:2005

数据来源: ADIS

摘要:

Pharmacogenomics is defined as research into inherited genetic variations that determine an individual’s response to therapeutic agents. In oncology, pharmacogenomics based on somatic molecular alterations inherited by subsequent cancer cell generations forms the basis of molecular targeting of novel therapeutic agents. What has emerged from clinical experience with such agents is the need for appropriate pharmacodiagnostic approaches to ensure the drugs are correctly targeted. Given the broad range of pharmacogenomic agents currently under evaluation for cancer therapy, it appears that a rapid extension of pharmacodiagnostic profiling will be required in the next 5–10 years, if not sooner. If this is to be successfully achieved, lessons learned in the past, particularly during the development of HER2 (ERBB2) testing for directing trastuzumab therapy in breast cancer, may provide a valuable framework for the development of future pharmacodiagnostic assays system.This article reviews the biological and clinical rationale for targeting breast cancer with trastuzumab and the steps taken to validate and improve pharmacodiagnostic procedures for testing tumor HER2 protein expression andHER2gene amplification. Attention is given to quality assurance and reproducibility of testing approaches and the optimal selection of patients for response to trastuzumab. This approach serves as a paradigm for the future development of pharmacodiagnostic tests in oncology.

ISSN:1175-2203    

出版商:ADIS    

年代:2005

数据来源: ADIS

摘要:

Traditionally, anatomic staging systems have been used to determine predictions of individual patient outcome and, to a lesser extent, guide the choice of treatment in patients with cancer. With new targeted therapies, the role of biomarkers is increasingly promising, suggesting an integrated approach using the genetic make-up of the tumor and the genotype of the patient for treatment selection and patient management. Specifically, biomarkers can aid in patient stratification (risk assessment), treatment response identification (surrogate markers), or in differential diagnosis (identifying individuals who are likely to respond to specific drugs). To be clinically useful, a marker must favorably affect clinical outcomes such as decreased toxicity, increased overall and/or disease-free survival, or improved quality of life.This paper focuses on possible clinical trial designs for assessing the utility of a predictive marker(s) for toxicity or clinical efficacy. We consider the scenario of single and multiple markers as well as present alternative solutions based on the prevalence of a marker. Our designs rest on the assumption that the methods for assessment of the biomarker are established and the initial results show promise with regard to the predictive ability of a marker. Additional research is clearly warranted to achieve the goal of ‘predictive oncology’.

ISSN:1175-2203    

出版商:ADIS    

年代:2005

数据来源: ADIS

摘要:

This is the third paper in a four-part serial review on potential therapeutic targeting of oncogenes. The previous parts described the involvement of oncogenes in different aspects of cancer growth and development, and considered the new technologies responsible for the advancement of oncogene identification, target validation, and drug design. Because of such advances, new specific and more efficient therapeutic agents can be developed for cancer. This part of the review continues the exploration of various oncogenes that we have grouped within seven categories: growth factors, tyrosine kinases, intermediate signaling molecules, transcription factors, cell cycle regulators, DNA damage repair genes, and genes involved in apoptosis. Part one discussed growth factors and tyrosine kinases and part two discussed intermediate signaling molecules. This portion of the review covers transcription factors and the various strategies being used to inhibit their expression or decrease their activities.

ISSN:1175-2203    

出版商:ADIS    

年代:2005

数据来源: ADIS

摘要:

BackgroundCurrent structural genomics projects are being driven by two main goals; to produce a representative set of protein folds that could be used as templates for comparative modeling purposes, and to provide insight into the function of the currently unannotated protein sequences. Such projects may reveal that a newly determined protein structure shares structural similarity with a previously observed structure or that it is a novel fold. The manner in which structure can be used to suggest the function of a protein will depend on the number and diversity of homologous sequences and the extent to which these sequences are functionally characterized.Method and resultsUsing sequence searching methods, we analyzed structural genomics target sequences to ascertain if they were members of functionally characterized protein families, protein families of unknown function, or orphan sequences. This analysis provided an indication of what could be expected to emerge from structural genomics projects. Matches were found to approximately 25% of the current functionally unannotated protein families in the PFAM database (protein families database of alignments and hidden Markov models). The 16% of strict orphan sequences will be the most problematic if their structures reveal novel folds. However, out of the remaining target sequences that match families whose members are largely of unknown function, 28% are particularly interesting in that they are part of protein families with considerable sequence diversity.ConclusionThe determination of a new structure of a member of these families is likely to offer considerable insight into possible functional roles of these proteins even if it is a new fold. Mapping the sequence conservation onto the structure may reveal functionally important residues for further study by experimental methods.

ISSN:1175-2203    

出版商:ADIS    

年代:2005

数据来源: ADIS