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GSVA score reveals molecular signatures from transcriptomes for biomaterials comparison
Marcel R Ferreira1, Gerson A Santos1, Carlos A Biagi2
1Laboratory of Bioassays and Cellular Dynamics, Department of Chemistry and Biochemistry, Institute of Biosciences, São Paulo State University, UNESP, Botucatu, São Paulo, Brazil.
Journal of Biomedical Materials Research. Part A
|August 22, 2020
Summary
This study introduces a novel in silico method using transcriptome data to compare biomaterials like hydroxyapatite and β-TCP. The approach reveals molecular signatures, aiding in the selection and development of new biomaterials.
Area of Science:
- Biomaterials Science
- Computational Biology
- Transcriptomics
Background:
- Comparing biomaterial performance is crucial for regenerative medicine and tissue engineering.
- Existing methods often lack detailed molecular insights into cellular responses.
- Transcriptome data offers a rich source for understanding cellular interactions with biomaterials.
Purpose of the Study:
- To develop and validate an in silico methodology for comparing inorganic hydroxyapatite and beta-tricalcium phosphate (β-TCP) biomaterials.
- To utilize transcriptome profiles of osteoblastic cells for assessing biomaterial performance.
- To establish a novel approach for biomaterial discovery and characterization.
Main Methods:
- Implementation of two in silico methodologies using transcriptome databases.
- Analysis of the E-MTAB-7219 dataset, including osteoblastic cells on 15 different biomaterials.
- Application of Gene Set Variation Analysis (GSVA) scores with MSigDB collections to derive molecular signatures.
Main Results:
- Successfully generated molecular signatures for hydroxyapatite and β-TCP biomaterials.
- Demonstrated the ability to group biomaterials based on cellular transcriptional landscapes.
- Validated the GSVA score approach for comparing biomaterial performance using transcriptome data.
Conclusions:
- The developed in silico methodology provides a robust framework for comparing biomaterials.
- Transcriptome profiling combined with GSVA offers a powerful tool for understanding cellular responses to biomaterials.
- This approach can significantly aid in the prospection and development of novel biomaterials.
