five

Data Sheet 1_Identification of an Ara-C resistance-related gene risk score and the role of S100A4 in AML via NR6A1-dependent activation and p53 regulation.zip

收藏
NIAID Data Ecosystem2026-05-02 收录
下载链接:
https://figshare.com/articles/dataset/Data_Sheet_1_Identification_of_an_Ara-C_resistance-related_gene_risk_score_and_the_role_of_S100A4_in_AML_via_NR6A1-dependent_activation_and_p53_regulation_zip/29312150
下载链接
链接失效反馈
官方服务:
资源简介:
IndroductionAra‐C (cytarabine) resistance remains a significant contributor to the poor clinical outcomes in adult acute myeloid leukemia (AML). However, predicting Ara‐C resistance and developing effective targeted therapies remain challenging. MethodsIn this study, we integrated transcriptional data from Ara‐C‐resistant cell lines in the GEO database and the TCGA‐LAML cohort to establish an Ara‐C resistancerelated gene risk score (ARRGRS). Kaplan‐Meier survival analysis revealed that AML patients with high ARRGRS had significantly worse prognosis compared to those with low ARRGRS in both cohorts. Additionally, ARRGRS effectively predicted chemotherapy response in AML patients across both cohorts. To further elucidate the mechanisms underlying Ara‐C resistance, we constructed Ara‐C‐resistant AML cell lines and validated our findings using qPCR, Western blotting, flow cytometry (FCM), and in vivo experiments. ResultsWe discovered that high expression of S100A4 promotes Ara‐C resistance in AML. Mechanistically, we identified that the transcription factor NR6A1 directly binds to the S100A4 promoter, enhancing its transcriptional activity. Subsequently, S100A4 upregulates p53 expression, thereby promoting AML cell proliferation and resistance to Ara‐C. DiscussionIn summary, our comprehensive investigation of the ARRGRS not only deepens the understanding of Ara‐C resistance mechanisms but also provides promising insights for targeting S100A4 to inhibit tumor growth and overcome chemotherapy resistance in AML.
创建时间:
2025-06-13
二维码
社区交流群
二维码
科研交流群
商业服务