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Two in silico methodologies were implemented to reveal the molecular signatures of inorganic hydroxyapatite and β-TCP materials from a transcriptome database to compare biomaterials. To test this new methodology, we choose the array E-MTAB-7219, which contains the transcription profile of osteoblastic cell line seeded onto 15 different biomaterials up to 48 hr. The expansive potential of the methodology was tested from the construction of customized signatures. We present, for the first time, a methodology to compare the performance of different biomaterials using the transcriptome profile of the cell through the Gene set variation analysis (GSVA) score. To test this methodology, we implemented two methods based on MSigDB collections, using all the collections and sub-collections except the Hallmark collection, which was used in the second method. The result of this analysis provided an initial understanding of biomaterial grouping based on the cell transcriptional landscape. The comparison using GSVA score combined efforts and expand the potential to compare biomaterials using transcriptome profile. Altogether, our results provide a better understanding of the comparison of different biomaterials and suggest a possibility of the new methodology be applied to the prospection of new biomaterials.
Ferreira et al. (Fri,) studied this question.