CombiMatrix has completed the clinical validation of the BAC array CGH based clinical microarray tests. ATScan is designed to detect known genomic copy-number variations associated with Autism Spectrum Disorder and this test is now available to physicians and consumers.
CombiMatrix Molecular Diagnostics Launches Microarray Test for Detection of Autism Spectrum Disorder
Prof. David Dandy of Colorado State University chemical and biological engineering has proven that called microarray assays can be used for biomedical disease and drug screening assays could rapidly increase drug discovery,
Although not ready for hospital or office use, microarrays represent a novel miniaturized multi-spot diagnostic format that has huge potential for patient diagnosis if found reliable and approved.
Smaller is often better, according to a new scientific study that appears this week in the Proceedings of the National Academy of Sciences by Professor David Dandy, head of the Department of Chemical and Biological Engineering at Colorado State. Dandy co-wrote the paper with David Grainger, a former chemistry professor at Colorado State who now is chair of the Department of Pharmaceutics & Pharmaceutical Chemistry at the University of Utah.
The study was funded by a multi-year, $2.5 million grant from the National Institutes of Health.
“This work is extremely useful from an industrial perspective,” said Michael Lochhead, chief scientist at Accelr8 Technology Corp., a Denver-based developer of innovative materials and instrumentation for advanced applications in medical instrumentation, basic research, drug discovery, and bio-detection.
The critical importance of this work is illustrated by the fact that, to date, a single microarray-based test has been approved by the FDA for clinical use.
According to Roche, the manufacturer of this diagnostic microarray, “This test analyzes a patient’s Cytochrome P450 2D6 and 2C19 genotypes from genomic DNA extracted from a blood sample. Test results will allow physicians to consider unique genetic information from patients in selecting medications and doses of medications for a wide variety of common conditions such as cardiac diseases, pain and cancer.”
Filed under: clinical diagnostics, clinical microarray, Clinical microarrays, custom microarray, diagnostic microarray, DNA microarray, gene expression, Genomics, microarray, microarray blog, microarray for clinical diagnostics, personalized medicine, Pharmacogenomics, Theranostics | Leave a comment »
Theranostics is the term used to describe the proposed process of diagnostic therapy for individual patients – to test them for possible reaction to taking a new medication and to tailor a treatment for them based on the test results or in plain english Personalized Medicine.
Personalized medicine is the use of detailed information about a patient’s genotype or level of gene expression and a patient’s clinical data in order to select a medication, therapy or preventative measure that is particularly suited to that patient at the time of administration
The test results are used to tailor treatment, usually with a drug that targets a particular gene or protein.
Seen the movie Gattaca it shows glipses of the what to come.
The technology is set to grow by leaps as new companies are introducing new microarray chip which are getting cheaper day by day
Already there are microarraychips approved by FDA for clinical diagnostics
Filed under: bioinformatics, bioinformatics blog, clinical diagnostics, clinical microarray, Clinical microarrays, DNA microarray, drug discoverry, epigenetics, gene expression, genetics, genotyping, microaray blog, microarray, microarray for clinical diagnostics, personalized medicine, Pharmacogenomics, science blog, Theranostics | 1 Comment »
DNA microarray detection of antimicrobial resistance genes in diverse bacteria
Study published at http://cat.inist.fr/?aModele=afficheN&cpsidt=17459830
High throughput genotyping is essential for studying the spread of multiple antimicrobial resistance. A test oligonucleotide microarray designed to detect 94 antimicrobial resistance genes was constructed and successfully used to identify antimicrobial resistance genes in control strains. The microarray was then used to assay 51 distantly related bacteria, including Gram-negative and Gram-positive isolates, resulting in the identification of 61 different antimicrobial resistance genes in these bacteria. These results were consistent with their known gene content and resistance phenotypes. Microarray results were confirmed by polymerase chain reaction and Southern blot analysis. These results demonstrate that this approach could be used to construct a microarray to detect all sequenced antimicrobial resistance genes in nearly all bacteria.
Filed under: bacteria, bioinformatics, bioinformatics blog, clinical diagnostics, clinical microarray, Clinical microarrays, custom microarray, DNA, DNA microarray, drug resistance, epigenetics, gene expression, genetics, genotyping, microaray blog, microarray, microarray analysis, microarray analysis software, microarray for clinical diagnostics, Oligo, Pharmacogenomics, RNA microarray | 1 Comment »
Two critical characteristics of breast cancer that are important to treatment can be identified by measuring gene expression in the tumor, a research team led by scientists at The University of Texas M. D. Anderson Cancer Center reports in Lancet Oncology online.
Researchers developed and validated a new genomic microarray test that identifies whether a tumor’s growth is fueled by the female hormone estrogen and the role of a growth factor receptor known as HER-2 that makes a tumor vulnerable to a specific drug.
“This is one important step towards personalized diagnosis and treatment planning based on an integrated genomic test of an individual tumor,” said senior author W. Fraser Symmans, M.D., associate professor in the M. D. Anderson Department of Pathology.
The Lancet Oncology paper results are the latest in an effort by the research team to develop a single test to quickly and efficiently determine the characteristics and vulnerabilities of a patient’s breast cancer and ultimately to guide treatment.
About 70 percent of breast cancers are estrogen-receptor positive and another 15 to 25 percent are human epidermal growth factor receptor-2 (HER-2) positive. Each receptor status requires different types of treatment.
“This moves us closer to developing an integrated single genomic test that could estimate the risk of cancer relapse after surgery, determine the ER and HER2 receptor status, and also gauge the sensitivity of the tumor to hormone therapy and chemotherapy,” says Lajos Pusztai, M.D., Ph.D., associate professor in the M. D. Anderson Department of Breast Medical Oncology, and team leader with Symmans.
Last fall, the group published a study showing that a genomic microarray test can also predict a patient’s response to chemotherapy. They also presented a paper in December showing that another genomic index predicts how an ER-positive patient will respond to hormonal therapy.
The study was funded by the National Cancer Institute, the Breast Cancer Research Foundation and the Goodwin Foundation.
Co-authors with Symmans and Pusztai are: first author Yun Gong, M.D., and Nour Sneige, M.D., of the M. D. Anderson Department of Pathology; Kai Yan, Keith Anderson, and Kenneth Hess, of the M. D. Anderson Department of Biostatistics; Feng Lin, M.D., Vicente Valero, M.D., Daniel Booser, M.D., Jaime Mejia, M.D., and Gabriel Hortobagyi, M.D., of the M. D. Anderson Department of Breast Medical Oncology; Christos Sotiriou, M.D., Ph.D., Institut Jules Bordet, Brussels, Belgium; Fabrice Andre, M.D., of Institut Gustave Roussy, Villejuif, France; Frankie Holmes, M.D., John Pippen Jr., M.D., and Svetislava Vukelja, M.D., of U.S. Oncology-Texas Oncology; Henry Gomez, M.D., of the Instituto Nacional de Enfermedades Neoplasicas, Lima, Peru; and Luis Barajas, M.D., Departmento de Ginecologia Oncologica, Instituto Mexicano del Seguro Social, Guadalajara, Mexico.
Contact: Scott Merville
University of Texas M. D. Anderson Cancer Center
Filed under: Affymetrix, bioinformatics, bioinformatics blog, bioinformatics software, cancer, cancer microarray, clinical diagnostics, clinical microarray, Clinical microarrays, custom microarray, DNA, DNA microarray, drug development, drug discoverry, drug resistance, gene expression, genetics, genotyping, microaray blog, microarray, microarray analysis, microarray for clinical diagnostics, personalized medicine, Pharmacogenomics | 3 Comments »
New non-parametric analyis algorithm for Detecting Differentially Expressed Genes with Replicated Microarray Data
Previous nonparametric statistical methods on constructing the test and null statistics require having at least 4 arrays under each condition. In this paper, we provide an improved method of constructing the test and null statistics which only requires 2 arrays under one condition if the number of arrays under the other condition is at least 3. The conventional testing method defines the rejection region by controlling the probability of Type I error. In this paper, we propose to determine the critical values (or the cut-off points) of the rejection region by directly controlling the false discovery rate. Simulations were carried out to compare the performance of our proposed method with several existing methods. Finally, our proposed method is applied to the rat data of Pan et al. (2003). It is seen from both simulations and the rat data that our method has lower false discovery rates than those from the significance analysis of microarray (SAM) method of Tusher et al. (2001) and the mixture model method (MMM)of Pan et al. (2003).
study published by
Shunpu Zhang (2006) “An Improved Nonparametric Approach for Detecting Differentially Expressed Genes with Replicated Microarray Data,” Statistical Applications in Genetics and Molecular Biology: Vol. 5 : Iss. 1, Article 30.
Available at: http://www.bepress.com/sagmb/vol5/iss1/art30
Filed under: bioinformatics, bioinformatics blog, bioinformatics software, bioinformatis software, Clinical microarrays, custom microarray, DNA microarray, gene expression, genetics, genotyping, microaray blog, microarray, microarray analysis, microarray analysis software, microarray software, RNA microarray, science blog | Leave a comment »
NYIT Professor Discovers Next Generation of DNA and RNA Microarrays brings hopes of personalized medicine
A novel invention developed by a scientist from New York Institute of Technology (NYIT) could revolutionize biological and clinical research and may lead to treatments for cancer, AIDS, Alzheimer’s, diabetes, and genetic and infectious diseases.
The invention allows the immobilisation of intact. double-stranded, multi-stranded or alternative DNA or RNA and has the potential to revolutionise biological and clinical research by allowing scientists to duplicate the cell environment and experiment with human, bacterial and viral genes.
Since the discovery of DNA, biologists have worked to unlock the secrets of the human cell.
Scientist Dr. Claude E. Gagna, Ph.D., an associate professor at NYIT’s School of Health Professions, Behavioral and Life Sciences, discovered how to immobilize intact double-stranded (ds-), multi-stranded or alternative DNA and RNA on one microarray. This immobilization allows scientists to duplicate the environment of a cell, and study, examine and experiment with human, bacterial and viral genes. This invention provides the methodology to analyze more than 150,000 non-denatured genes.
The “Gagna/NYIT Multi-Stranded and Alternative DNA, RNA and Plasmid Microarray,” has been patented (#6,936,461) in the United States and is pending in Europe and Asia. Gagna’s discovery will help scientists understand how transitions in DNA structure regulate gene expression (B-DNA to Z-DNA), and how DNA-protein, and DNA-drug interactions regulate genes. The breakthrough can aid in genetic screening, clinical diagnosis, forensics, DNA synthesis-sequencing and biodefense.
This will help pharmaceutical companies produce new classes of drugs that target genes, with fewer side effects,” Dr Gagna continued.
“It will lower the cost and increase the speed of drug discovery, saving millions of dollars.”
Since the invention of the DNA microarray in 1991, the technology has become one of the most powerful research tools for drug discovery research allowing scientist to perform thousands of experiments with incredible accuracy and speed. According to MarketResearch.com sales of DNA microarrays are expected to be higher than $5.3bn (€ bn) by 2009.
The technology hinges around a novel surface that increases the adherence of DNA to the microarray so that any type of nucleic acid can be anchored, unlike conventional arrays that allow only single-stranded DNA to be immobilised.
Additionally, Gagna has developed a novel surface that increases the adherence of the DNA to the microarray so that any type of nucleic acid can be anchored. Unlike conventional microarrays, which immobilize single-stranded DNA, scientists will now be able to “secure intact, non-denatured, unaltered ds-DNA, triplex-, quadruplex-, or pentaplex DNA onto the microarray,” says Gagna. “With this technology, one day we will have tailor-made molecular medicine for patients.”
“With this technology, one day we will have tailor-made molecular medicine for patients,” said Dr Gagna.
and sure the news site are buzzing with the discovery
read more about the research and the original article details at
Filed under: Affymetrix, biodefense, bioinformatics, cancer, cancer microarray, clinical diagnostics, clinical microarray, Clinical microarrays, custom microarray, DNA microarray, drug development, drug discoverry, gene expression, genetics, genotyping, microarray, microarray analysis, microarray for clinical diagnostics, Next Generation of DNA and RNA Microarrays, personalized medicine, Pharmacogenomics, RNA microarray | 3 Comments »