Rojas-Salazar Yareli, Gómez-Montañez Emiliano, Rojas-Salazar Jorge, de Anda-Jáuregui Guillermo, Hernández-Lemus Enrique
Computational Genomics Division, National Institute of Genomic Medicine, Mexico City 14610, Mexico.
Center for Complexity Sciences, Universidad Nacional Autónoma de México, Mexico City 04510, Mexico.
Int J Mol Sci. 2024 Nov 29;25(23):12840. doi: 10.3390/ijms252312840.
HER2-positive (HER2+) breast cancer is characterized by the overexpression of the ERBB2 (HER2) gene, which promotes aggressive tumor growth and poor prognosis. Targeting the ERBB2 pathway with single-agent therapies has shown limited efficacy due to resistance mechanisms and the complexity of gene interactions within the tumor microenvironment. This study aims to explore potential drug synergies by analyzing gene-drug interactions and combination therapies that target the ERBB2 pathway in HER2+ breast tumors. Using gene co-expression network analysis, we identified 23 metabolic pathways with significant cross-linking of gene interactions, including those involving EGFR tyrosine kinase inhibitors, PI3K, mTOR, and others. We visualized these interactions using Cytoscape to generate individual and combined drug-gene networks, focusing on frequently used drugs such as Erlotinib, Gefitinib, Lapatinib, and Cetuximab. Individual networks highlighted the direct effects of these drugs on their target genes and neighboring genes within the ERBB2 pathway. Combined drug networks, such as those for Cetuximab with Lapatinib, Cetuximab with Erlotinib, and Erlotinib with Lapatinib, revealed potential synergies that could enhance therapeutic efficacy by simultaneously influencing multiple genes and pathways. Our findings suggest that a network-based approach to analyzing drug combinations provides valuable insights into the molecular mechanisms of HER2+ breast cancer and offers promising strategies for overcoming drug resistance and improving treatment outcomes.
人表皮生长因子受体2阳性（HER2+）乳腺癌的特征是ERBB2（HER2）基因过度表达，这会促进肿瘤的侵袭性生长并导致预后不良。由于耐药机制以及肿瘤微环境内基因相互作用的复杂性，使用单药疗法靶向ERBB2通路的疗效有限。本研究旨在通过分析基因-药物相互作用以及靶向HER2+乳腺肿瘤中ERBB2通路的联合疗法，探索潜在的药物协同作用。通过基因共表达网络分析，我们确定了23条具有显著基因相互作用交联的代谢途径，包括那些涉及表皮生长因子受体酪氨酸激酶抑制剂、磷脂酰肌醇-3激酶（PI3K）、雷帕霉素靶蛋白（mTOR）等的途径。我们使用Cytoscape软件将这些相互作用可视化，以生成单独的和联合的药物-基因网络，重点关注常用药物，如厄洛替尼、吉非替尼、拉帕替尼和西妥昔单抗。单独的网络突出了这些药物对其靶基因以及ERBB2通路内相邻基因的直接作用。联合药物网络，如西妥昔单抗与拉帕替尼、西妥昔单抗与厄洛替尼、厄洛替尼与拉帕替尼的联合网络，揭示了潜在的协同作用，通过同时影响多个基因和途径可以提高治疗效果。我们的研究结果表明，基于网络的方法分析药物组合能够为HER2+乳腺癌的分子机制提供有价值的见解，并为克服耐药性和改善治疗结果提供有前景的策略。
