| Title |
Digital Expression Profiling Identifies RUNX2, CDC5L, MDM2, RECQL4, and CDK4 as Potential Predictive Biomarkers for Neo-Adjuvant Chemotherapy Response in Paediatric Osteosarcoma
|
|---|---|
| Published in |
PLOS ONE, May 2014
|
| DOI | 10.1371/journal.pone.0095843 |
| Pubmed ID | |
| Authors |
Jeffrey W. Martin, Susan Chilton-MacNeill, Madhuri Koti, Andre J. van Wijnen, Jeremy A. Squire, Maria Zielenska |
| Abstract |
Osteosarcoma is the most common malignancy of bone, and occurs most frequently in children and adolescents. Currently, the most reliable technique for determining a patients' prognosis is measurement of histopathologic tumor necrosis following pre-operative neo-adjuvant chemotherapy. Unfavourable prognosis is indicated by less than 90% estimated necrosis of the tumor. Neither genetic testing nor molecular biomarkers for diagnosis and prognosis have been described for osteosarcomas. We used the novel nanoString mRNA digital expression analysis system to analyse gene expression in 32 patients with sporadic paediatric osteosarcoma. This system used specific molecular barcodes to quantify expression of a set of 17 genes associated with osteosarcoma tumorigenesis. Five genes, from this panel, which encoded the bone differentiation regulator RUNX2, the cell cycle regulator CDC5L, the TP53 transcriptional inactivator MDM2, the DNA helicase RECQL4, and the cyclin-dependent kinase gene CDK4, were differentially expressed in tumors that responded poorly to neo-adjuvant chemotherapy. Analysis of the signalling relationships of these genes, as well as other expression markers of osteosarcoma, indicated that gene networks linked to RB1, TP53, PI3K, PTEN/Akt, myc and RECQL4 are associated with osteosarcoma. The discovery of these networks provides a basis for further experimental studies of role of the five genes (RUNX2, CDC5L, MDM2, RECQL4, and CDK4) in differential response to chemotherapy. |
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Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Practitioners (doctors, other healthcare professionals) | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 69 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Japan | 1 | 1% |
| Singapore | 1 | 1% |
| Switzerland | 1 | 1% |
| Brazil | 1 | 1% |
| Unknown | 65 | 94% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 12 | 17% |
| Researcher | 11 | 16% |
| Student > Master | 9 | 13% |
| Student > Bachelor | 6 | 9% |
| Other | 5 | 7% |
| Other | 9 | 13% |
| Unknown | 17 | 25% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 19 | 28% |
| Biochemistry, Genetics and Molecular Biology | 14 | 20% |
| Agricultural and Biological Sciences | 12 | 17% |
| Unspecified | 1 | 1% |
| Environmental Science | 1 | 1% |
| Other | 2 | 3% |
| Unknown | 20 | 29% |