Integrative Computational and Transcriptional Analysis of NF-κB and HIF-1α Modulation Following Doxorubicin Treatment in Triple-Negative Breast Cancer Cells

整合计算和转录分析阿霉素治疗后三阴性乳腺癌细胞中NF-κB和HIF-1α的调控

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Abstract

PURPOSE: Triple-negative breast cancer (TNBC) is an aggressive breast cancer subtype with limited targeted treatment options. Doxorubicin remains a cornerstone of TNBC treatment; however, its molecular effects beyond canonical cytotoxic mechanisms are not fully characterized. This study aimed to explore NF-κB- and HIF-1α-related transcriptional responses associated with doxorubicin treatment in TNBC cells using an integrative computational and experimental approach, in line with global cancer research priorities supporting Sustainable Development Goal (SDG) 3: Good Health and Well-Being. METHODS: Network pharmacology analysis, molecular docking, and molecular dynamics simulations were employed to explore potential pathway-level associations of doxorubicin with NF-κB and HIF-1α-related signaling. In vitro validation was performed using MTT cytotoxicity assays in MDA-MB-231 cells cultured in DMEM and RPMI-1640 media. Half-maximal inhibitory concentrations (IC(5) (0)) were determined using four-parameter logistic regression. Transcriptional responses of NF-κB and HIF-1α were evaluated by RT-qPCR under normoxic conditions. RESULTS: Computational analyses suggested potential associations between doxorubicin and components of NF-κB and HIF-1α-related signaling pathways. In vitro assays demonstrated concentration-dependent cytotoxicity, with IC(5) (0) values of 2.34 µM (95% CI: 2.11-2.74) in DMEM and 1.07 µM (95% CI: 0.92-1.32 µM) in RPMI-1640. RT-qPCR analysis revealed downregulation of NF-κB and HIF-1α mRNA expression following doxorubicin treatment. These findings indicate transcriptional modulation associated with doxorubicin exposure, without establishing functional pathway inhibition. CONCLUSION: This study provides transcriptional-level evidence suggesting the involvement of NF-κB- and HIF-1α-related pathways in the cellular response of TNBC cells to doxorubicin treatment. By integrating computational predictions with early experimental validation, the findings generate biologically plausible hypotheses for further mechanistic and functional investigations, contributing to foundational cancer research efforts aligned with SDG 3 (Good Health and Well-Being).

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