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Whole transcriptome analysis identifies differentially regulated networks between osteosarcoma and normal bone samples
Journal article   Peer reviewed

Whole transcriptome analysis identifies differentially regulated networks between osteosarcoma and normal bone samples

X.D. Ho, P. Phung, V.Q. Le, V.H. Nguyen, E. Reimann, E. Prans, G. Kõks, K. Maasalu, N.T.N. Le, L.H. Trinh, …
Experimental Biology and Medicine, Vol.242(18), pp.1802-1811
2017
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Abstract

We performed whole transcriptome analysis of osteosarcoma bone samples. Initially, we sequenced total RNA from 36 fresh-frozen samples (18 tumoral bone samples and 18 non-tumoral paired samples) matching in pairs for each osteosarcoma patient. We also performed independent gene expression analysis of formalin-fixed paraffin-embedded samples to verify the RNAseq results. Formalin-fixed paraffin-embedded samples allowed us to analyze the effect of chemotherapy. Data were analyzed with DESeq2, edgeR and Reactome packages of R. We found 5365 genes expressed differentially between the normal bone and osteosarcoma tissues with an FDR below 0.05, of which 3399 genes were upregulated and 1966 were downregulated. Among those genes, BTNL9, MMP14, ABCA10, ACACB, COL11A1, and PKM2 were expressed differentially with the highest significance between tumor and normal bone. Functional annotation with the reactome identified significant changes in the pathways related to the extracellular matrix degradation and collagen biosynthesis. It was suggested that chemotherapy may induce the modification of ECM with important collagen biosynthesis. Taken together, our results indicate that changes in the degradation of extracellular matrix seem to be an important mechanism of osteosarcoma and efficient chemotherapy induces the genes related to bone formation.

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Collaboration types
Domestic collaboration
International collaboration
Citation topics
1 Clinical & Life Sciences
1.118 Soft Tissue, Bone & Nerve Cancers
1.118.300 Sarcoma Research
Web Of Science research areas
Medicine, Research & Experimental
ESI research areas
Clinical Medicine
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