
Microarray analysis in glioblastomas is done using either cell lines or patient samples as starting material. A survey of the current literature points to transcript-based microarrays and immunohistochemistry (IHC)-based tissue microarrays as being the preferred methods of choice in cancers of neurological origin. Microarray analysis may be carried out for various purposes including the following: i. To correlate gene expression signatures of glioblastoma cell lines or tumors with response to chemotherapy (DeLay et al., Clin Cancer Res 18(10):2930-2942, 2012). ii. To correlate gene expression patterns with biological features like proliferation or invasiveness of the glioblastoma cells (Jiang et al., PLoS One 8(6):e66008, 2013). iii. To discover new tumor classificatory systems based on gene expression signature, and to correlate therapeutic response and prognosis with these signatures (Huse et al., Annu Rev Med 64(1):59-70, 2013; Verhaak et al., Cancer Cell 17(1):98-110, 2010). While investigators can sometimes use archived tumor gene expression data available from repositories such as the NCBI Gene Expression Omnibus to answer their questions, new arrays must often be run to adequately answer specific questions. Here, we provide a detailed description of microarray methodologies, how to select the appropriate methodology for a given question, and analytical strategies that can be used. Experimental methodology for protein microarrays is outside the scope of this chapter, but basic sample preparation techniques for transcript-based microarrays are included here.
Proteomics, Proteome, 3102 Bioinformatics and Computational Biology (for-2020), Microarray, 0399 Other Chemical Sciences (for), Workflow, Brain Disorders (rcdc), Databases, Genetic, Medicinal and biomolecular chemistry, Gene-expression, 3101 Biochemistry and cell biology (for-2020), Cancer, Developmental Biology (science-metrix), Oligonucleotide Array Sequence Analysis, Cancer (rcdc), Brain Cancer (rcdc), Humans (mesh), Proteomics (mesh), Biological Sciences, Glioblastoma (mesh), 3404 Medicinal and biomolecular chemistry (for-2020), Computational Biology (mesh), Biotechnology, 570, Bioinformatics and Computational Biology, 0601 Biochemistry and Cell Biology (for), 610, Biotechnology (rcdc), Rare Diseases (rcdc), Databases, Oligonucleotide Array Sequence Analysis (mesh), Rare Diseases, Genetic, Genetics, Humans, Software (mesh), Proteome (mesh), Workflow (mesh), 31 Biological Sciences (for-2020), Genetics (rcdc), Gene Expression Profiling, Human Genome, Computational Biology, Cancer (hrcs-hc), Human Genome (rcdc), Gene Expression Profiling (mesh), Brain Disorders, Brain Cancer, Genetic (mesh), Biochemistry and Cell Biology, Other Chemical Sciences, Glioblastoma, Software, Developmental Biology
Proteomics, Proteome, 3102 Bioinformatics and Computational Biology (for-2020), Microarray, 0399 Other Chemical Sciences (for), Workflow, Brain Disorders (rcdc), Databases, Genetic, Medicinal and biomolecular chemistry, Gene-expression, 3101 Biochemistry and cell biology (for-2020), Cancer, Developmental Biology (science-metrix), Oligonucleotide Array Sequence Analysis, Cancer (rcdc), Brain Cancer (rcdc), Humans (mesh), Proteomics (mesh), Biological Sciences, Glioblastoma (mesh), 3404 Medicinal and biomolecular chemistry (for-2020), Computational Biology (mesh), Biotechnology, 570, Bioinformatics and Computational Biology, 0601 Biochemistry and Cell Biology (for), 610, Biotechnology (rcdc), Rare Diseases (rcdc), Databases, Oligonucleotide Array Sequence Analysis (mesh), Rare Diseases, Genetic, Genetics, Humans, Software (mesh), Proteome (mesh), Workflow (mesh), 31 Biological Sciences (for-2020), Genetics (rcdc), Gene Expression Profiling, Human Genome, Computational Biology, Cancer (hrcs-hc), Human Genome (rcdc), Gene Expression Profiling (mesh), Brain Disorders, Brain Cancer, Genetic (mesh), Biochemistry and Cell Biology, Other Chemical Sciences, Glioblastoma, Software, Developmental Biology
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