Development of chemoresistance is a persistent problem during cancer treatment. Long non-coding RNAs (LncRNAs) are currently emerging as an integral functional component of the human genome and as critical regulators of cancer development and progression. In the present study, we investigated the role and molecular mechanism of H19 lncRNA in chemoresistance development by using doxorubicin (Dox) resistance in breast cancer cells as a model system. lncRNA expression was significantly increased in anthracycline-treated and Dox-resistant MCF-7 breast cancer cells. This H19 overexpression was contributed to cancer cell resistance to anthracyclines and paclitaxel as knockdown of lncRNA by a specific shRNA in Dox-resistant cells significantly improved the cell sensitivity to anthracyclines and paclitaxel. Furthermore, gene expression profiling analysis revealed that a total of 192 genes were associated with H19-mediated Dox resistance. These genes were enriched in multiple KEGG pathways that are related to chemoresistance. Using genetic and pharmacological approaches, we demonstrated that MDR1 and MRP4 were major effectors of H19-regulated Dox resistance in breast cancer cells as MDR1 and MRP4 expression was markedly elevated in Dox-resistant cells while dramatically reduced when H19 was knocked down. Moreover, we found that CUL4A, an ubiquitin ligase component, was a critical factor bridging H19 lncRNA to MDR1 expression, and a high tumor CUL4A expression was associated with low survival in breast cancer patients treated with chemotherapy. These data suggest that H19 lncRNA plays a leading role in breast cancer chemoresistance, mediated mainly through a --/ pathway.
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http://dx.doi.org/10.18632/oncotarget.21121 | DOI Listing |
Sci Rep
December 2024
Department of Clinical Pharmacy, Baoshan Hospital Affiliated to, Shanghai University of Traditional Chinese Medicine, Shanghai, China.
This study investigates the potential treatment of breast cancer utilizing Gentiana robusta King ex Hook. f. (QJ) through an integrated approach involving network pharmacology, molecular docking, and molecular dynamics simulation.
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December 2024
Department of Breast Surgery, Second Affiliated Hospital of Dalian Medical University, No. 467 Zhongshan Road, Shahekou District, Dalian, China.
Early prediction of patient responses to neoadjuvant chemotherapy (NACT) is essential for the precision treatment of early breast cancer (EBC). Therefore, this study aims to noninvasively and early predict pathological complete response (pCR). We used dynamic ultrasound (US) imaging changes acquired during NACT, along with clinicopathological features, to create a nomogram and construct a machine learning model.
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