| Title |
Identification of histological markers for malignant glioma by genome-wide expression analysis: dynein, α-PIX and sorcin
|
|---|---|
| Published in |
Acta Neuropathologica, November 2005
|
| DOI | 10.1007/s00401-005-1085-6 |
| Pubmed ID | |
| Authors |
Takashi Yokota, Jun Kouno, Koji Adachi, Hiroshi Takahashi, Akira Teramoto, Koshi Matsumoto, Yuichi Sugisaki, Masamitsu Onda, Tatsuhiko Tsunoda |
| Abstract |
Glioblastoma multiforme (GBM), the most malignant class of glial neoplasm (grade IV in WHO criteria), carries the worst clinical prognosis among primary brain tumors in adults. To identify a set of genes involved in the tumorigenesis of GBM, we evaluated expression profiles of GBM tissues from 11 patients using a cDNA microarray representing 25,344 human genes. By comparing the profiles with those of normal brain tissue, we identified a number of differentially expressed genes: 54 with increased expression and 45 with reduced expression in GBMs. Semi-quantitative RT-PCR experiments with 6 of those genes confirmed higher expression of DNCH2, ARHGEF6, NPM1 and SRI and lower expression of NRGN and TM4SF2 in GBM tumors. Immunohistochemical staining for 3 of the respective gene products, dynein (product of DNCH2), alpha-PIX (product of ARHGEF6), and sorcin (product of SRI) indicated that this technique might be useful for histological grading of glial tumors. To establish criteria for this diagnostic approach, we scored glial tumor tissues of different histological grades according to the staining results; the scores were significantly higher in anaplastic astrocytomas and GBMs than in diffuse astrocytomas or normal brain tissues. These findings indicated that levels of these three proteins might serve as histological markers for malignant glioma classification. |
Mendeley readers
The data shown below were compiled from readership statistics for 22 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Belgium | 1 | 5% |
| Brazil | 1 | 5% |
| Unknown | 20 | 91% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 4 | 18% |
| Professor | 3 | 14% |
| Student > Doctoral Student | 2 | 9% |
| Student > Postgraduate | 2 | 9% |
| Professor > Associate Professor | 2 | 9% |
| Other | 4 | 18% |
| Unknown | 5 | 23% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 6 | 27% |
| Biochemistry, Genetics and Molecular Biology | 3 | 14% |
| Agricultural and Biological Sciences | 3 | 14% |
| Computer Science | 2 | 9% |
| Engineering | 2 | 9% |
| Other | 2 | 9% |
| Unknown | 4 | 18% |
Attention Score in Context
This research output has an Altmetric Attention Score of 3. 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 14 July 2018.
All research outputs
#8,882,501
of 26,017,215 outputs
Outputs from Acta Neuropathologica
#1,585
of 2,635 outputs
Outputs of similar age
#43,448
of 164,403 outputs
Outputs of similar age from Acta Neuropathologica
#3
of 4 outputs
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