A lncRNA HAR1B has a potential as a predictive marker for pazopanib therapy in patients with sarcoma

Bone and soft tissue sarcomas are rare and highly heterogeneous mesenchymal malignancies. Their rarity makes it difficult to acquire clinical data of patients with specific histological subtypes of sarcoma from large clinical trials. The diagnoses and treatment of sarcomas need to be further developed. We show that a long non-coding RNA (lncRNA) HAR1B may serve as predictive biomarkers for pazopanib treatment in bone and soft tissue sarcomas. Multiplex real-time reverse transcription polymerase chain reaction and microarray analyses revealed that HAR1B and HOTAIR were differentially expressed in pazopanib-sensitive cells and responders. We further clarified this mechanism by showing that siRNA-knockdown of HAR1B led to an increased resistance to pazopanib in sarcoma cell lines. Gene expression profiles related to pazopanib sensitivity included cellular molecular pathways, including genes involved in von-Willebrand factor-related signaling. Our study demonstrates that lncRNA HAR1B expression affects cellular sensitivity to pazopanib in sarcoma cell lines and in patients with sarcoma. We collected 16 different bone and soft tissue sarcoma cell lines (cell lines) consisting of various tissue types. MTT assays using pazopanib against these cell lines were conducted to classify the cell lines into pazopanib effective (pazopanib-sensitive group) and ineffective (pazopanib-resistant group). The expression profiles of 90 lncRNAs known to be associated with cancer and stem cells in these cell lines were analyzed by multiplex qPCR to extract lncRNAs with differential expression between the two groups. 23 Tissues from patients with bone and soft tissue sarcoma who had been previously treated with pazopanib (patient tissues) were classified into two groups based on the therapeutic effect of pazopanib (responder group (R) and non-responder group (NR)). Patient tissues were subjected to comprehensive expression analysis by microarray targeting lncRNA as well as mRNA, and lncRNAs differentially expressed between the two groups were extracted. Among the lncRNAs also targeted in cell lines, candidate lncRNAs with similar expression differences also in patient tissues were extracted. Comprehensive gene and lncRNA expression analysis was also conducted in the cell lines using the same microarrays. Combined with the results from patient tissues, gene ontology (GO) analysis, and functional cluster analysis of genes and lncRNAs that showed common expression trends between pazopanib effective group and pazopanib ineffective group were performed. We examined which genes and lncRNAs were differentially expressed in the pazopanib-effective group in both cell lines and patient tissues.