Chapter title |
AMLprofiler: A Diagnostic and Prognostic Microarray for Acute Myeloid Leukemia
|
---|---|
Chapter number | 7 |
Book title |
Acute Myeloid Leukemia
|
Published in |
Methods in molecular biology, July 2017
|
DOI | 10.1007/978-1-4939-7142-8_7 |
Pubmed ID | |
Book ISBNs |
978-1-4939-7140-4, 978-1-4939-7142-8
|
Authors |
Alessandrini, Marco, Kappala, Sharon S., Pepper, Michael S., Marco Alessandrini, Sharon S. Kappala, Michael S. Pepper |
Abstract |
Acute myeloid leukemia is characterized by the proliferation and accumulation of immature hematopoietic cells of the myeloid lineage in the bone marrow. The disease is typified by diverse genetic abnormalities and marked heterogeneity both with regard to response to treatment and survival. The AMLprofiler is a qualitative in vitro diagnostic microarray developed by SkylineDx for use with Affymetrix technology. The AMLprofiler makes use of RNA chemistry and incorporates seven separate assays based on three different technologies-cytogenetics, mutation, and expression analysis-to predict post-therapy survival rates in patients with acute myeloid leukemia. The assay has been validated for processing of bone marrow samples from which RNA is isolated within 48 h. The samples are subsequently processed using Affymetrix GeneChip reagent kits and analyzed on the Affymetrix GeneChip 3000Dx v2 system. The scanned AMLprofiler data is sent to a centralized server of SkylineDx via a secured Internet connection, and a diagnostic report is generated within 15 min. We have performed several AMLprofiler assays in our laboratory and found the data generated via this assay to be consistent with standard modalities. |
X Demographics
Geographical breakdown
Country | Count | As % |
---|---|---|
Unknown | 1 | 100% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Members of the public | 1 | 100% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
Unknown | 6 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Professor | 1 | 17% |
Student > Ph. D. Student | 1 | 17% |
Researcher | 1 | 17% |
Student > Master | 1 | 17% |
Unknown | 2 | 33% |
Readers by discipline | Count | As % |
---|---|---|
Biochemistry, Genetics and Molecular Biology | 2 | 33% |
Medicine and Dentistry | 1 | 17% |
Unknown | 3 | 50% |