Dataset of Two-Dimensional Gel Electrophoresis Images of Acute Myeloid Leukemia Patients before and after Induction Therapy

Data

卷:6

Jeanette Prada-Arismendy¹  LuisaF. Restrepo¹  Sarah Röthlisberger¹  Erwing Castillo²  Edilson Delgado-Trejos³  JuanE. Urrea³  MariaC. Torres-Madronero⁴  ManuelM. Goez⁴ 

[1] Biomedical Research and Innovation Group (GI2B), Instituto Tecnologico Metropolitano ITM, 76A354 Medellin, Colombia;

[2] Hematology and Oncology Unit, Hospital Manuel Uribe Angel, 38S57 Envigado, Colombia;

[3] Measurement Analysis and Decision-Making Support Laboratory (AMYSOD Lab), Quality, Metrology and Production (CM&P) Research Group, Instituto Tecnologico Metropolitano (ITM), 76A354 Medellin, Colombia;

[4] Smart Machines and Pattern Recognition (MIRP) Research Group, Instituto Tecnologico Metropolitano ITM, 76A354 Medellin, Colombia;

关键词: acute myeloid leukemia;    image preprocessing;    proteomics;    two-dimensional gel electrophoresis;   

DOI  :  10.3390/data6020020

来源: DOAJ

【 摘 要 】

Acute myeloid leukemia (AML) is a malignant disorder of the hematopoietic stem and progenitor cells, which results in the build-up of immature blasts in the bone marrow and eventually in the peripheral blood of affected patients. Accurately assessing a patient´s prognosis is very important for clinical management of the disease, which is why there are several prognostic factors such as age, performance status at diagnosis, platelet count, serum creatinine and albumin that are taken into account by the clinician when deciding the course of treatment. However, proteomic changes related to treatment response in this patient group have not been widely explored. Here, we make available a set of 22 two-dimensional gel electrophoresis (2DGE) images obtained from the peripheral blood samples of 11 patients with AML, taken at the time of diagnosis and after induction therapy (approximately 21–28 days after starting treatment). The same set of 2DGE images is also made available after a preprocessing stage (an additional 22 2DGE pre-processed images), which was performed using algorithms developed in Python, in order to improve the visualization of characteristic spots and facilitate proteomic analysis of this type of images.

【 授权许可】

Unknown