“Genetic Profiling of Breast Cancer using cDNA Microarray.” (original) (raw)
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Genomics in breast cancer?therapeutic implications
Nature Clinical Practice Oncology, 2005
The introduction of DNA microarray techniques has had dramatic implications on cancer research, allowing researchers to analyze expression of multiple genes in concert and relate the findings to clinical parameters. The main discoveries in breast cancer, as well as in other malignancies, have so far been with respect to two key issues. First, individual tumors arising from the same organ may be grouped into distinct classes based on their gene expression profiles, independent of stage and grade. Second, the biologic relevance of such classification is corroborated by significant prognostic impact. We review how the use of microarray technologies can provide unique possibilities to explore the mechanisms of tumor behavior in vivo that will allow evaluation of prognosis and, potentially, drug resistance. However, in spite of recent advances, we are not yet at a stage where the use of these techniques should be implemented for routine clinical use, whether to define prognostic factors or to predict sensitivity to therapy.
Genomic approaches in the management and treatment of breast cancer
British Journal of Cancer, 2005
Breast cancer is the most common malignancy afflicting women from Western cultures. It has been estimated that approximately 211 000 women will be diagnosed with breast cancer in 2003 in the United States alone, and each year over 40 000 women will die of this disease. Developments in breast cancer molecular and cellular biology research have brought us closer to understanding the genetic basis of this disease. Unfortunately, this information has not yet been incorporated into the routine diagnosis and treatment of breast cancer in the clinic. Recent advancements in microarray technology hold the promise of further increasing our understanding of the complexity and heterogeneity of this disease, and providing new avenues for the prognostication and prediction of breast cancer outcomes. The most recent application of microarray genomic technologies to studying breast cancer will be the focus of this review.
New concepts in breast cancer genomics and genetics
Massively parallel DNA and RNA sequencing approaches have generated data on thousands of breast cancer genomes. In this review, we consider progress largely from the perspective of new concepts and hypotheses raised so far. These include challenges to the multistep model of breast carcinogenesis and the discovery of new defects in DNA repair through sequence analysis. Issues for functional genomics include the development of strategies to differentiate between mutations that are likely to drive carcinogenesis and bystander background mutations, as well as the importance of mechanistic studies that examine the role of mutations in genes with roles in splicing, histone methylation, and long non-coding RNA function. The application of genome-annotated patient-derived breast cancer xenografts as a potentially more reliable preclinical model is also discussed. Finally, we address the challenge of extracting medical value from genomic data. A weakness of many datasets is inadequate clinical annotation, which hampers the establishment of links between the mutation spectra and the efficacy of drugs or disease phenotypes. Tools such as dGene and the DGIdb are being developed to identify possible druggable mutations, but these programs are a work in progress since extensive molecular pharmacology is required to develop successful ‘genome-forward’ clinical trials. Examples are emerging, however, including targeting HER2 in HER2 mutant breast cancer and mutant ESR1 in ESR1 endocrine refractory luminal-type breast cancer. Finally, the integration of DNA- and RNA-based sequencing studies with mass spectrometry-based peptide sequencing and an unbiased determination of post-translational modifications promises a more complete view of the biochemistry of breast cancer cells and points toward a new discovery horizon in our understanding of the pathophysiology of this complex disease.
Microarrays in breast cancer research and clinical practice–the future lies ahead
2006
Molecular profiling for classification and prognostic purposes has demonstrated that the genetic signatures of tumors contain information regarding biological properties as well as clinical behavior. This review highlights the progress that has been made in the field of gene expression profiling of human breast cancer. Breast cancer has become one of the most intensely studied human malignancies in the genomic era; several hundred papers over the last few years have investigated various clinical and biological aspects of human breast cancer using high-throughput molecular profiling techniques. Given the grossly heterogeneous nature of the disease and the lack of robust conventional markers for disease prediction, prognosis, and response to treatment, the notion that a transcriptional profile comprising multiple genes, rather than any single gene or other parameter, will be more predictive of tumor behavior is both appealing and reasonable. Promising results have emerged from these studies, correlating gene expression profiles with prognosis, recurrence, metastatic potential, therapeutic response, as well as biological and functional aspects of the disease. Clearly, the integration of genomic approaches into the clinic lies in the near future, but prospective studies based on larger patient cohorts representing the whole spectrum of breast cancer, oncogenic pathway-based studies, attendant care in bioinformatic analyses and validation studies are needed before the full promise of gene expression profiling can be realized in the clinical setting.
Cancer research, 2005
Genomic imbalances in 31 formalin-fixed and paraffin-embedded primary tumors of advanced breast cancer were analyzed by microarray-based comparative genomic hybridization (matrix-CGH). A DNA chip was designed comprising 422 mapped genomic sequences including 47 proto-oncogenes, 15 tumor suppressor genes, as well as frequently imbalanced chromosomal regions. Analysis of the data was challenging due to the impaired quality of DNA prepared from paraffin-embedded samples. Nevertheless, using a method for the statistical evaluation of the balanced state for each individual experiment, we were able to reveal imbalances with high significance, which were in good concordance with previous data collected by chromosomal CGH from the same patients. Owing to the improved resolution of matrix-CGH, genomic imbalances could be narrowed down to the level of individual bacterial artificial chromosome and P1-derived artificial chromosome clones. On average 37 gains and 13 losses per tumor cell genome...
The genetics of breast cancer: risk factors for disease
The Application of Clinical Genetics, 2011
The genetic factors known to be involved in breast cancer risk comprise about 30 genes. These include the high-penetrance early-onset breast cancer genes, BRCA1 and BRCA2, a number of rare cancer syndrome genes, and rare genes with more moderate penetrance. A larger group of common variants has more recently been identified through genome-wide association studies. Quite a number of these common variants are mapped to genomic regions without being firmly associated with specific genes. It is thought that most of these variants have gene regulatory functions, but their precise roles in disease susceptibility are not well understood. Common variants account for only a small percentage of the risk of disease because they have low penetrance. Collectively, the breast cancer genes identified to date contribute only ∼30% of the familial risk. Therefore, there is much interest in accounting for the missing heritability, and possible sources include loss of information through ignoring phenotype heterogeneity (disease subtypes have genetic differences), gene-gene and gene-environment interaction, and rarer forms of variation. Identification of these rarer variations in coding regions is now feasible and cost effective through exome sequencing, which has already identified high-penetrance variants for some rare diseases. Targeting more 'extreme' breast cancer phenotypes, particularly cases with early-onset disease, a strong family history (not accounted for by BRCA mutations), and with specific tumor subtypes, provides a route to progress using next-generation sequencing methods.