Reichelt Paula, Bernhart Stephan, Wilke Franziska, Schwind Sebastian, Cross Michael, Platzbecker Uwe, Behre Gerhard
Department of Hematology, Cell Therapy, Hemostaseology and Infectiology, University Hospital Leipzig, 04103 Leipzig, Germany.
Interdisciplinary Center for Bioinformatics, Leipzig University, 04107 Leipzig, Germany.
Cancers (Basel). 2023 Oct 21;15(20):5086. doi: 10.3390/cancers15205086.
Resistance to chemotherapy is ultimately responsible for the majority of AML-related deaths, making the identification of resistance pathways a high priority. Transcriptomics approaches can be used to identify genes regulated at the level of transcription or mRNA stability but miss microRNA-mediated changes in translation, which are known to play a role in chemo-resistance. To address this, we compared miRNA profiles in paired chemo-sensitive and chemo-resistant subclones of HL60 cells and used a bioinformatics approach to predict affected pathways. From a total of 38 KEGG pathways implicated, TGF-β/activin family signaling was selected for further study. Chemo-resistant HL60 cells showed an increased TGF-β response but were not rendered chemo-sensitive by specific inhibitors. Differential pathway expression in primary AML samples was then investigated at the RNA level using publically available gene expression data in the TGCA database and by longitudinal analysis of pre- and post-resistance samples available from a limited number of patients. This confirmed differential expression and activity of the TGF-β family signaling pathway upon relapse and revealed that the expression of TGF-β and activin signaling genes at diagnosis was associated with overall survival. Our focus on a matched pair of cytarabine sensitive and resistant sublines to identify miRNAs that are associated specifically with resistance, coupled with the use of pathway analysis to rank predicted targets, has thus identified the activin/TGF-β signaling cascade as a potential target for overcoming resistance in AML.
化疗耐药最终导致了大多数与急性髓系白血病（AML）相关的死亡，因此确定耐药途径成为当务之急。转录组学方法可用于识别在转录或mRNA稳定性水平上受到调控的基因，但会遗漏微小RNA介导的翻译变化，而这些变化已知在化疗耐药中起作用。为了解决这个问题，我们比较了HL60细胞化疗敏感和化疗耐药配对亚克隆中的微小RNA谱，并使用生物信息学方法预测受影响的途径。在总共涉及的38条京都基因与基因组百科全书（KEGG）途径中，选择了转化生长因子-β（TGF-β）/激活素家族信号传导进行进一步研究。化疗耐药的HL60细胞显示出TGF-β反应增加，但特异性抑制剂并未使其对化疗敏感。然后，利用TGCA数据库中公开可用的基因表达数据，并通过对有限数量患者的耐药前后样本进行纵向分析，在RNA水平上研究原发性AML样本中的差异途径表达。这证实了复发时TGF-β家族信号传导途径的差异表达和活性，并揭示了诊断时TGF-β和激活素信号基因的表达与总生存期相关。我们专注于一对阿糖胞苷敏感和耐药的亚系，以识别与耐药特异性相关的微小RNA，并结合使用途径分析对预测靶点进行排名，从而确定激活素/TGF-β信号级联作为克服AML耐药的潜在靶点。
