Inadequate tissue mineralization promotes cancer cell attachment

Selection of lncRNAs That Influence the Prognosis of Osteosarcoma Based on Copy Number Variation Data

Osteosarcoma is the most common primary malignancy in the musculoskeletal system. It is reported that copy number variation- (CNV-) derived lncRNAs contribute to the progression of osteosarcoma. However, whether CNV-derived lncRNAs affect the prognosis of osteosarcoma remains unclear. Here, we obtained osteosarcoma-related CNV data and gene expression profiles from The Cancer Genome Atlas (TCGA) database. CNV landscape analysis indicated that copy number amplification of lncRNAs was more frequent than deletion in osteosarcoma samples. Thirty-four CNV-lncRNAs with DNA-CNV frequencies greater than 30% and their corresponding 294 mRNAs were identified. Gene Ontology (GO) and Kyoto Encyclopedia of Gene and Genome (KEGG) pathway enrichment analyses revealed that these mRNAs were mainly enriched in olfaction, olfactory receptor activity, and olfactory transduction processes. Furthermore, we predicted that a total of 23 genes were cis-regulated by 16 CNV-lncRNAs, while 30 transcription factors (TFs) were trans-regulated by 5 CNV-lncRNAs. Through $t$ -tests, univariate Cox regression analysis, and the least absolute shrinkage and selection operator (LASSO), we constructed a CNV-related risk model including 3 lncRNAs (AC129492.1, PSMB1, and AC037459.4). The Kaplan-Meier (K-M) curves indicated that patients with high-risk scores showed poor prognoses. The areas under the receiver operating characteristic (ROC) curves (AUC) for predicting 3-, 5-, and 7-year overall survival (OS) were greater than 0.7, showing a satisfactory predictive efficiency. Gene set enrichment analysis (GSEA) revealed that the prognostic signature was intimately linked to skeletal system development, immune regulation, and inflammatory response. Collectively, our study developed a novel 3-CNV-lncRNA prognostic signature that would provide theoretical guidance for the clinical prognostic management of osteosarcoma.

In vitro engineering of a bone metastases model allows for study of the effects of antiandrogen therapies in advanced prostate cancer

While androgen-targeted therapies are routinely used in advanced prostate cancer (PCa), their effect is poorly understood in treating bone metastatic lesions and ultimately results in the development of metastatic castrate resistant prostate cancer (mCRPC). Here, we used an all-human microtissue-engineered model of mineralized metastatic tissue combining human osteoprogenitor cells, 3D printing and prostate cancer cells, to assess the effects of the antiandrogens, bicalutamide, and enzalutamide in this microenvironment. We demonstrate that cancer/bone stroma interactions and antiandrogens drive cancer progression in a mineralized microenvironment. Probing the bone microenvironment with enzalutamide led to stronger cancer cell adaptive responses and osteomimicry than bicalutamide. Enzalutamide presented with better treatment response, in line with enzalutamide delaying time to bone-related events and enzalutamide extending survival in mCRPC. The all-human microtissue-engineered model of mineralized metastatic tissue presented here represents a substantial advance to dissect the role of the bone tumor microenvironment and responses to therapies for mCPRC.