Bayesian model of signal rewiring reveals mechanisms of gene dysregulation in acquired drug resistance in breast cancer

Small molecule inhibitors, such as lapatinib, are effective against breast cancer in clinical trials, but tumor cells ultimately acquire resistance to the drug. Maintaining sensitization to drug action is essential for durable growth inhibition. Recently, adaptive reprogramming of signaling circuitry has been identified as a major cause of acquired resistance. We developed a computational framework using a Bayesian statistical approach to model signal rewiring in acquired resistance. We used the p1-model to infer potential aberrant gene-pairs with differential posterior probabilities of appearing in resistant-vs-parental networks. Results were obtained using matched gene expression profiles under resistant and parental conditions. Using two lapatinib-treated ErbB2-positive breast cancer cell-lines: SKBR3 and BT474, our method identified similar dysregulated signaling pathways including EGFR-related pathways as well as other receptor-related pathways, many of which were reported previously as compensatory pathways of EGFR-inhibition via signaling cross-talk. A manual literature survey provided strong evidence that aberrant signaling activities in dysregulated pathways are closely related to acquired resistance in EGFR tyrosine kinase inhibitors. Our approach predicted literature-supported dysregulated pathways complementary to both node-centric (SPIA, DAVID, and GATHER) and edge-centric (ESEA and PAGI) methods. Moreover, by proposing a novel pattern of aberrant signaling called V-structures, we observed that genes were dysregulated in resistant-vs-sensitive conditions when they were involved in the switch of dependencies from targeted to bypass signaling events. A literature survey of some important V-structures suggested they play a role in breast cancer metastasis and/or acquired resistance to EGFR-TKIs, where the mRNA changes of TGFBR2, LEF1 and TP53 in resistant-vs-sensitive conditions were related to the dependency switch from targeted to bypass signaling links. Our results suggest many signaling pathway structures are compromised in acquired resistance, and V-structures of aberrant signaling within/among those pathways may provide further insights into the bypass mechanism of targeted inhibition.

小分子抑制剂（small molecule inhibitors）如拉帕替尼（lapatinib）在临床试验中对乳腺癌展现出良好疗效，但肿瘤细胞最终会对该药物产生获得性耐药。维持肿瘤细胞对药物作用的敏感性，是实现持久生长抑制的关键。近年来，信号通路网络的适应性重编程被证实是获得性耐药的主要诱因。本研究开发了一种基于贝叶斯统计方法的计算框架，用于建模获得性耐药过程中的信号重连现象。我们采用p1模型，以耐药细胞与亲本细胞网络中出现的后验概率差异为依据，推断潜在的异常基因对。研究结果基于耐药与亲本状态下的匹配基因表达谱获得。本研究针对两株经拉帕替尼处理的ErbB2阳性乳腺癌细胞系SKBR3与BT474开展分析，所提出的方法识别出了多条失调的信号通路，其中包含表皮生长因子受体（EGFR）相关通路及其他受体相关通路；其中多数通路此前已有报道，属于通过信号串扰介导的EGFR抑制代偿通路。人工文献调研结果提供了强有力的证据：失调通路中的异常信号活性与表皮生长因子受体酪氨酸激酶抑制剂（EGFR-TKIs）类药物的获得性耐药密切相关。本研究方法所预测的、得到文献支持的失调通路，可与以节点为中心的SPIA、DAVID及GATHER方法，以及以边为中心的ESEA与PAGI方法形成互补。此外，本研究提出了一种名为V型结构（V-structures）的新型异常信号模式，研究发现：当基因参与了从靶向信号通路到旁路信号事件的依赖型转换时，其在耐药与敏感细胞状态下会呈现失调特征。针对部分关键V型结构的文献调研显示，这类结构在乳腺癌转移及/或EGFR-TKIs获得性耐药过程中发挥作用；在耐药与敏感细胞状态下，TGFBR2、LEF1及TP53的mRNA表达变化与从靶向信号链路到旁路信号链路的依赖型转换密切相关。本研究结果表明，获得性耐药过程中多条信号通路结构遭到破坏；而这些通路内部及通路间的异常信号V型结构，可为靶向抑制的旁路逃逸机制提供新的研究视角。