Literature DB >> 31352515

Long noncoding RNA CASC2 promotes paclitaxel resistance in breast cancer through regulation of miR-18a-5p/CDK19.

Pengfei Zheng1, Liangpeng Dong1, Bin Zhang2, Jinfang Dai3, Yifu Zhang1, Yanan Wang4, Shuang Qin5.   

Abstract

Breast cancer is one of the most prevalent cancers in women. Chemoresistance is a major obstacle for the treatment of breast cancer. We investigated the role of long noncoding RNA (lncRNA) cancer susceptibility candidate 2 (CASC2) in paclitaxel (PTX) resistance in breast cancer. CASC2 expression was increased in PTX-resistant clinical samples and cell lines. PTX induced CASC2 expression in a concentration-dependent manner. Downregulation of CASC2 increased PTX toxicity and decreased IC50 value, while upregulation of CASC2 decreased PTX toxicity and increased IC50 value in MCF-7/PTX and MDA-MB-231/PTX cells. Moreover, downregulation of CASC2 decreased tumor growth in xenograft mice implanted with MCF-7/PTX cells. miR-18a-5p possessed a putative binding site in 3'-UTR of CASC2 and cyclin-dependent kinase 19 (CDK19). In PTX-resistant breast cancer cells, miR-18a-5p expression was decreased. CASC2 and miR-18a-5p could negatively regulate the expression of each other. CDK19 expression could be negatively regulated by miR-18a-5p, but positively regulated by CASC2. miR-18a-5p mimics or downregulation of CDK19 decreased tumor growth in xenograft mice implanted with MCF-7/PTX cells. In summary, we identified that CASC2 activated PTX resistance in breast cancer through regulation of miR-18a-5p/CDK19. We highlight the importance of CASC2/miR-18a-5p/CDK19 axis in the chemoresistance of breast cancer and provide potential targets for the improving chemotherapy of breast cancer.

Entities:  

Keywords:  Breast cancer; CASC2; CDK19; Chemoresistance; miR-18a-5p

Year:  2019        PMID: 31352515     DOI: 10.1007/s00418-019-01794-4

Source DB:  PubMed          Journal:  Histochem Cell Biol        ISSN: 0948-6143            Impact factor:   4.304


  31 in total

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  17 in total

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10.  Multivariate transcriptome analysis identifies networks and key drivers of chronic lymphocytic leukemia relapse risk and patient survival.

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