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Abstract

Developmental Biology

Methods to Enable Spatial Transcriptomics of Bone Tissues

Published: May 3rd, 2024

DOI:

10.3791/66850

1Department of Periodontics and Preventive Dentistry, University of Pittsburgh School of Dental Medicine, 2Center for Craniofacial Regeneration, University of Pittsburgh School of Dental Medicine, 3UPMC Presbyterian, 4UPMC Shadyside, 5Musculoskeletal Oncology Laboratory, Department of Orthopaedic Surgery, University of Pittsburgh, 6UPMC Hillman Cancer Center, 7Departments of Anatomic Pathology and General Surgical Oncology, University of Pittsburgh, 8Department of Medicine, University of Pittsburgh School of Medicine, 9University of Pittsburgh UPMC Hillman Cancer Center, 10McGowan Institute for Regenerative Medicine, University of Pittsburgh

Abstract

Understanding the relationship between the cells and their location within each tissue is critical to uncover the biological processes associated with normal development and disease pathology. Spatial transcriptomics is a powerful method that enables the analysis of the whole transcriptome within tissue samples, thus providing information about the cellular gene expression and the histological context in which the cells reside. While this method has been extensively utilized for many soft tissues, its application for the analyses of hard tissues such as bone has been challenging. The major challenge resides in the inability to preserve good quality RNA and tissue morphology while processing the hard tissue samples for sectioning. Therefore, a method is described here to process freshly obtained bone tissue samples to effectively generate spatial transcriptomics data. The method allows for the decalcification of the samples, granting successful tissue sections with preserved morphological details while avoiding RNA degradation. In addition, detailed guidelines are provided for samples that were previously paraffin-embedded, without demineralization, such as samples collected from tissue banks. Using these guidelines, high-quality spatial transcriptomics data generated from tissue bank samples of primary tumor and lung metastasis of bone osteosarcoma are shown.

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Keywords Spatial Transcriptomics

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