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.
Subject(s)
Bone Neoplasms , Bone and Bones , Transcriptome , Humans , Transcriptome/genetics , Bone and Bones/metabolism , Bone Neoplasms/genetics , Bone Neoplasms/pathology , Bone Neoplasms/metabolism , Osteosarcoma/genetics , Osteosarcoma/pathology , Osteosarcoma/metabolism , Gene Expression Profiling/methods , Paraffin Embedding/methods , Lung Neoplasms/genetics , Lung Neoplasms/pathology , Lung Neoplasms/metabolismABSTRACT
AIMS: Leiomyosarcomas (LMSs) occur in various tissues and harbour potential for metastases. The genomic landscape of LMS is poorly understood. In an effort to improve understanding of the LMS genome, we analysed 11 LMSs of somatic soft tissue including matching tissue of normal phenotype. METHODS: DNA derived from microdissected tumour domains and matching normal tissue underwent amplicon sequencing of 409 tumour suppressors and oncogenes using the Ion Torrent Comprehensive Cancer Panel. RESULTS: Genomic changes were heterogeneous with few recurrent abnormalities detected. Coding variants were identified in genes involved in signal transduction, transcriptional regulation and DNA repair. There were variants in several genes related to angiogenesis and GPR124 variants (TEM5) were confirmed by immunohistochemical analysis of a LMS tissue microarray. Surprisingly, there were shared coding variants in tumour and corresponding normal tissue. CONCLUSIONS: LMSs are a very heterogeneous population lacking recurrent somatic abnormalities. The presence of damaging mutations in normal tissue may reflect either a germline predisposition or field effect rather than tissue contamination. Hopeful therapeutic targets appear to be those related to AKT/MTOR pathway.