Bone

The results presented in this manuscript are based on the data presented here.

Selective inhibition of progesterone receptor in osteochondral progenitor cells, but not in mature chondrocytes, modulated subchondral bone structures

The shared data was for the paper “A Novel Mechanical Parameter to Quantify the Microarchitecture Effect on Apparent Modulus of Trabecular Bone: A Computational Analysis of Ineffective Bone Mass”. “Segment” refers to the lumbar vertebral level and the number in parentheses is the T-score. “VOI” means the volume of interests. “E(MPa)” is the apparent modulus of trabecular bone computed from micro finite element analysis. “# elements” refers to the number of elements in the micro finite element model. “BV/TV” is the bone volume fraction, computed as bone volume divided by total volume. “E*(GPa)” is the normalized apparent modulus of trabecular bone, computed to be E/(BV/TV). “LSVMR” denotes the low von Mises stress ratio and is computed as the ratio of the number of elements with von Mises stress less than 59 MPa to the total number of elements. “SMI” is the structural model index calculated using the software CTAn (Version 1.14.4.1, Bruker).

The data is about the canonical Wnt signaling pathway indicators DKK1, GSK3beta, beta catenin, and the osteogenic differentiation indicators COL1A1 and BALP in the Chinese population.

This is the Raw Data Files of the sequencing data. And the original datas about the Differentially_Expressed_miRNAs, GO Analysis Results (miRNA Targets),miRNA_Targets_Prediction,novel_miRNAs_predicted_by_miRDeep2, and Pathway Analysis Results (miRNA Targets).

Raw Data and Model-Averaged Neural Network for the prediction of breast cancer bone metastasis development in a rat model. Required software: R or R-Studio.

Osteosarcoma is an aggressive tumor of the bone that primarily affects young adults and adolescents largely characterized by genomic chaos and heterogeneity. While inactivation of tumor protein p53 (TP53) is nearly universal, other high frequency mutations or structural variations have not been identified. Despite this genomic heterogeneity, key conserved transcriptional programs associated with survival have been identified across human, canine and induced murine osteosarcoma. The epigenomic landscape, including DNA methylation, plays a key role in establishing transcriptional programs in all cell types. The role of epigenetic dysregulation has been studied in a variety of cancers, but has yet to be explored at scale in osteosarcoma. Genome-wide DNA methylation patterns were examined in 24 human and 44 canine osteosarcoma samples identifying groups of highly correlated DNA methylation marks in human and canine osteosarcoma samples. We also link specific DNA methylation patterns to key transcriptional programs in both human and canine osteosarcoma. Building on previous work, we built a DNA methylation-based measure for the presence and abundance of various immune cell types in osteosarcoma. Finally, we determined that the underlying state of the tumor, and not changes in cell composition, were the main driver of differences in DNA methylation across the human and canine samples. In addition to the canine BAM files made available on the ICDC, raw sequencing data for human and canine is available in the Sequence Read Archive (SRA) and can be accessed through BioProject accession PRJNA629591.

Related Article: Ignacy Cukrowski, Ljiljana Popović, Werner Barnard, Sylvia O. Paul, Petrus H. van Rooyen, David C. Liles|2007|BONE|41|668|doi:10.1016/j.bone.2007.05.008