Digital Expression Profiling Identifies <i>RUNX2</i>, <i>CDC5L</i>, <i>MDM2</i>, <i>RECQL4</i>, and <i>CDK4</i> as Potential Predictive Biomarkers for Neo-Adjuvant Chemotherapy Response in Paediatric Osteosarcoma

<div><p>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 <i>RUNX2</i>, the cell cycle regulator <i>CDC5L</i>, the <i>TP53</i> transcriptional inactivator <i>MDM2</i>, the DNA helicase <i>RECQL4</i>, and the cyclin-dependent kinase gene <i>CDK4</i>, 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 (<i>RUNX2</i>, <i>CDC5L</i>, <i>MDM2</i>, <i>RECQL4</i>, and <i>CDK4</i>) in differential response to chemotherapy.</p></div

List of experimental genes and control genes assayed.

<p>Twenty one probes for 17 genes and three controls were assayed for expression in the nanoString code set. Probes for each of the two main promoter regions of <i>RUNX2</i> were constructed.</p

Cluster map constructed using Cluster 3.0, showing the differential expression of the 17 gene set in osteosarcoma biopsy and resection cases in the cohort.

<p>Patients with >90% tumor necrosis in response to chemotherapy (good response) are shown in blue and those with <90% (poor response) are shown in red. Sample numbers 1–36 were analyzed in triplicates whereas samples 41–116 were analysed in duplicates. Detailed data manipulation for the cohort is presented in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0095843#pone.0095843.s004" target="_blank">Table S2B</a>.</p

Mean expression of the most significantly discriminating five genes in the osteosarcoma cohort when poor response (<90% tumor necrosis in response to chemotherapy) was compared to good response (>90% tumor necrosis).

<p>Unpaired Student’s t-test was applied to derive the genes that were differentially expressed in the two groups.</p