| Title |
Expression differences of genes in the PI3K/AKT, WNT/b-catenin, SHH, NOTCH and MAPK signaling pathways in CD34+ hematopoietic cells obtained from chronic phase patients with chronic myeloid leukemia and from healthy controls
|
|---|---|
| Published in |
Clinical and Translational Oncology, September 2017
|
| DOI | 10.1007/s12094-017-1751-x |
| Pubmed ID | |
| Authors |
R. de Cássia Viu Carrara, A. M. Fontes, K. J. Abraham, M. D. Orellana, S. K. Haddad, P. V. B. Palma, R. A. Panepucci, M. A. Zago, D. T. Covas |
| Abstract |
The fusion gene BRC-ABL has an important role to the progression of chronic myeloid leukemia (CML) and several signaling pathways have been characterized as responsible for the terminal blastic phase (BP). However, the initial phase, the chronic phase (CP), is long lasting and there is much yet to be understood about the critical role of BRC-ABL in this phase. This study aims to evaluate transcriptional deregulation in CD34+ hematopoietic cells (CD34+ cells) from patients with untreated newly diagnosed CML compared with CD34+HC from healthy controls. Gene expression profiling in CML-CD34 cells and CD34 cells from healthy controls were used for this purpose with emphasis on five main pathways important for enhanced proliferation/survival, enhanced self-renewal and block of myeloid differentiation. We found 835 genes with changed expression levels (fold change ≥ ±2) in CML-CD34 cells compared with CD34 cells. These include genes belonging to PI3K/AKT, WNT/b-catenin, SHH, NOTCH and MAPK signaling pathways. Four of these pathways converge to MYC activation. We also identified five transcripts upregulated in CD34-CML patients named OSBPL9, MEK2, p90RSK, TCF4 and FZD7 that can be potential biomarkers in CD34-CML-CP. We show several mRNAs up- or downregulated in CD34-CML during the chronic phase. |
X Demographics
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Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 30 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 30 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Master | 6 | 20% |
| Student > Ph. D. Student | 4 | 13% |
| Researcher | 3 | 10% |
| Professor > Associate Professor | 3 | 10% |
| Student > Postgraduate | 2 | 7% |
| Other | 5 | 17% |
| Unknown | 7 | 23% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 9 | 30% |
| Agricultural and Biological Sciences | 6 | 20% |
| Biochemistry, Genetics and Molecular Biology | 4 | 13% |
| Unspecified | 2 | 7% |
| Economics, Econometrics and Finance | 1 | 3% |
| Other | 1 | 3% |
| Unknown | 7 | 23% |
Attention Score in Context
This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 15 September 2017.
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#20,447,499
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Outputs from Clinical and Translational Oncology
#1,022
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Outputs of similar age from Clinical and Translational Oncology
#21
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