多组学整合建模解析曲妥珠单抗耐药性机理的方法学研究

HER2阳性乳腺癌耐药性研究是乳腺癌治疗领域的重要问题之一，多数HER2阳性乳腺癌患者在使用曲妥珠单抗治疗的过程中出现原发或继发耐药现象，但具体机制不详，越来越多的实验证据表明曲妥珠单抗耐药和甲基化，组蛋白修饰，转录调控，非编码RNA等多因素有关，这些调节因子构成了耐药机理相关的复杂多维调节网络，高通量测序技术为这些因子与曲妥珠单抗耐药的关联提供了不同维度的数据支撑，如何整合这些数据系统解析曲妥珠单抗的耐药的关键驱动模块和调节因子是急需解决的临床科学问题，但目前尚缺少有效的计算模型整合不同层次的数据来绘制曲妥珠单抗耐药的立体多维网络。本研究在组学整合建模的工作基础上拟用多维组学数据构建曲妥珠单抗耐药的多层次网络，从多维网络中探测并量化耐药性协同驱动模块和关键靶点，从不同因子协同调控的层次上揭示耐药性产生的分子机理，并量化这些调控机制，为HER2阳性乳腺癌治疗提供新的靶点或组合用药指导。

Human Epidermal Receptor 2 (HER2) positive breast cancer (HER2+ BC) is the most aggressive subtype, with poor prognosis and high recurrence rate, which accounts for 20~30% breast cancer patients and places large economic burden on health care system. Monoclonal antibody Trastuzumab is considered as frontline therapy for HER2+ BC patients. After treatment, Most of patients with HER2+ BC show primary resistance to Trastuzumab and progress to metastasis and recurrence. The quickly emerged intrinsic and acquired resistances to Trastuzumab sharply shorten the duration of drug action. However, the knowledge on the hidden hierarchical mechanism responsible for the resistance remains limited. Thus, it is necessary to decode the underlying mechanism that could circumvent the drug resistance. More and more published evidence indicated that the resistance mechanisms might be regulated by multi-level regulators, such as histone modifications, transcription factors (TFs), miRNAs, post-translational modification et al. all these regulators and their binding or targeting genes could be orchestrated as hierarchical regulatory structures, New technologies given the data support to measure the disturb in the resistant-cells, To avoid incompletely understanding the resistance mechanisms, here we will design a mathematic model to construct the hierarchical regulatory network and by modeling analysis of the above ChIP-seq, gene expression, miRNA expression and protein protein interaction data to quantify the potential mechanisms of resistance to Trastuzumab hidden in the hierarchical regulatory structures