Identifying intracellular signaling modules and exploring pathways associated with breast cancer recurrence.
Identifying intracellular signaling modules and exploring pathways associated with breast cancer recurrence.
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DOI：
10.1038/s41598-020-79603-5
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发表时间：
2021-01-11
影响因子：
4.6
通讯作者：
Xuan J
中科院分区：
文献类型：
--
作者：
Chen X;Gu J;Neuwald AF;Hilakivi-Clarke L;Clarke R;Xuan J
探索细胞内信号转导途径的复杂模块化对于理解疾病发展和药物治疗期间的异常细胞反应至关重要。 IMPALA（路径景观的推断模块化）集成了来自高通量基因表达实验和基因组规模知识数据库的信息，以识别异常的路径模块，从而提供强大的采样策略来重建和探索路径景观。 IMPALA 在此确定了与乳腺癌复发和他莫昔芬耐药相关的通路模块。 IMPALA 专注于雌激素受体 (ER) 信号传导，从他莫昔芬治疗的 ER 阳性乳腺癌患者样本的基因表达数据中确定了替代途径。这些通路通常通过 IRS1/2、JAK1、YWHAZ、CSNK2A1、MAPK1 和 HSP90AA1 等细胞质基因相互连接，并显着富含 ErbB、MAPK 和 JAK-STAT 信号传导成分。通路景观的表征揭示了与 ER 信号传导以及细胞周期和细胞凋亡信号传导相关的关键模块。我们使用来自四种不同乳腺癌细胞系的数据验证了 IMPALA 识别的通路模块，包括对他莫昔芬敏感和耐药的模型。结果显示，在短生存期（< 5年）乳腺癌患者中上调的细胞周期/凋亡模块中的大多数基因在耐药细胞系中也过度表达，而转录因子JUN、FOS和STAT3在患者和耐药细胞系中均下调。因此，IMPALA 确定了与他莫昔芬耐药性和乳腺癌复发风险增加相关的途径。 IMPALA 软件包可从 https://dlrl.ece.vt.edu/software/ 获取。
Exploring complex modularization of intracellular signal transduction pathways is critical to understanding aberrant cellular responses during disease development and drug treatment. IMPALA (Inferred Modularization of PAthway LAndscapes) integrates information from high throughput gene expression experiments and genome-scale knowledge databases to identify aberrant pathway modules, thereby providing a powerful sampling strategy to reconstruct and explore pathway landscapes. Here IMPALA identifies pathway modules associated with breast cancer recurrence and Tamoxifen resistance. Focusing on estrogen-receptor (ER) signaling, IMPALA identifies alternative pathways from gene expression data of Tamoxifen treated ER positive breast cancer patient samples. These pathways were often interconnected through cytoplasmic genes such as IRS1/2, JAK1, YWHAZ, CSNK2A1, MAPK1 and HSP90AA1 and significantly enriched with ErbB, MAPK, and JAK-STAT signaling components. Characterization of the pathway landscape revealed key modules associated with ER signaling and with cell cycle and apoptosis signaling. We validated IMPALA-identified pathway modules using data from four different breast cancer cell lines including sensitive and resistant models to Tamoxifen. Results showed that a majority of genes in cell cycle/apoptosis modules that were up-regulated in breast cancer patients with short survivals (< 5 years) were also over-expressed in drug resistant cell lines, whereas the transcription factors JUN, FOS, and STAT3 were down-regulated in both patient and drug resistant cell lines. Hence, IMPALA identified pathways were associated with Tamoxifen resistance and an increased risk of breast cancer recurrence. The IMPALA package is available at https://dlrl.ece.vt.edu/software/.
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