A Systematic Review of the Heterogenous Gene Expression Patterns Associated with Multidrug Chemoresistance in Conventional Osteosarcoma

Abstract

Multidrug chemoresistance (MDR) remains the most significant obstacle to improving survival in osteosarcoma patients. Heterogeneous genetic alterations characterise the tumour microenvironment, and host molecular markers have been associated with MDR. This systematic review examines the genetic alterations of molecular biomarkers associated with multidrug chemotherapy resistance in genome-wide analysis of central high-grade conventional osteosarcoma (COS). We systematically searched MEDLINE, EMBASE, Web of Science, Wiley online library and Scopus. Only human studies involving genome-wide analysis were included, while candidate gene, in vitro and animal studies were excluded. The risk of bias of the studies was assessed using the Newcastle-Ottawa Quality Assessment Scale. The systematic search identified 1355 records. Following the screening, six studies were included in the qualitative analysis. There were 473 differentially expressed genes (DEGs) associated with chemotherapy response in COS. Fifty-seven of those were associated with MDR in osteosarcoma. The heterogeneous gene expressions were related to the mechanism of MDR in osteosarcoma. The mechanisms include drug-related sensitivity genes, bone remodelling and signal transduction. Complex, variable and heterogenous gene expression patterns underpin MDR in osteosarcoma. Further research is needed to identify the most relevant alterations for prognostication and to guide the development of possible therapeutic targets.

Gold nanoparticles attenuate the interferon-γ induced SOCS1 expression and activation of NF-κB p65/50 activity via modulation of microRNA-155-5p in triple-negative breast cancer cells

“…When analyzing miRNAs at the cellular level within tissues, it becomes challenging to distinguish the specific contributions of different cell types to the overall miRNA expression patterns. This tissue heterogeneity can confound the interpretation of cellular-level microRNA analysis; in vivo miRNA analysis may lack spatial resolution ( 64 , 65 ). While it is possible to isolate specific cell populations or use imaging techniques to study miRNA localization, it is often difficult to precisely determine the spatial distribution and activity of miRNAs within tissues ( 66 ).…”