Zhong Shen, Börgeling Yvonne, Zardo Patrick, Jonigk Danny, Borlak Jürgen
Centre for Pharmacology and Toxicology, Hannover Medical School, Hannover, Germany.
Institute of Virology, University of Münster, Münster, Germany.
Clin Transl Med. 2025 Mar;15(3):e70177. doi: 10.1002/ctm2.70177.
Basic research identified oncogenic driver mutations in lung cancer (LC). However, <10% of patients carry driver mutations. Thus, most patients are not recommended for first-line kinase inhibitor (KI)-based therapies. Through enabling technologies and bioinformatics, we gained deep insight into patient-specific signalling networks which permitted novel KI-based treatment options in LC.
We performed molecular pathology, transcriptomics and miRNA profiling across 95 well-characterized LC patients. We confirmed results based on cross-linked immunoprecipitation-sequencing data, and used N = 524 adeno- and 497 squamous cell carcinomas as validation sets. We employed the PamGene platform to identify aberrant kinases, validated the results by evaluating independent siRNA and CRISPR-mediated mRNA knockdown studies in human LC cell lines.
Transcriptomics revealed 439, 1240, 383 and 320 significantly upregulated genes, respectively, for adeno-, squamous, neuroendocrine and metastatic cases, and there are 1092, 1477, 609 and 1267 downregulated DEGs. Based on gene enrichment analysis and experimentally validated miRNA-gene interactions, we constructed regulatory networks specific for adeno-, squamous, neuroendocrine and metastatic LC. Molecular profiling discovered 137 significantly upregulated kinases (range 2-26-fold) of which 65 and 72, respectively, are tyrosine and serine-threonine kinases while 6 kinases carry driver mutations. Meanwhile, there are 21 kinases commonly upregulated irrespective of the histological type of LC. Bioinformatics decoded networks in which kinases function as master regulators. Typically, the networks consisted of 14, 9, 16 and 19 highly regulated kinases in adeno-, squamous, neuroendocrine and metastatic LC. Inhibition of kinases which function as master regulators disrupted the signalling networks, and their gene knock-down studies confirmed inhibition of cell proliferation in a panel of human LC cell lines. Additionally, the proposed molecular profiling enables KI-based therapies in patients with acquired drug resistance.
Our study broadens the perspective of KI-based therapies in LC, and we propose a framework to overcome acquired drug resistance.
基础研究已确定肺癌（LC）中的致癌驱动基因突变。然而，携带驱动基因突变的患者不到10%。因此，大多数患者不建议接受一线基于激酶抑制剂（KI）的治疗。通过使能技术和生物信息学，我们深入了解了患者特异性信号网络，这为LC中基于KI的新治疗选择提供了可能。
我们对95例特征明确的LC患者进行了分子病理学、转录组学和miRNA分析。我们基于交联免疫沉淀测序数据确认了结果，并使用524例腺癌和497例鳞状细胞癌作为验证集。我们采用PamGene平台鉴定异常激酶，并通过评估人LC细胞系中独立的siRNA和CRISPR介导的mRNA敲低研究来验证结果。
转录组学显示，腺癌、鳞状、神经内分泌和转移病例分别有439、1240、383和320个基因显著上调，以及1092、1477、609和1267个下调的差异表达基因。基于基因富集分析和实验验证的miRNA-基因相互作用，我们构建了腺癌、鳞状、神经内分泌和转移LC特异性的调控网络。分子分析发现137个显著上调的激酶（范围为2至26倍），其中分别有65个和72个是酪氨酸激酶和丝氨酸-苏氨酸激酶，同时有6个激酶携带驱动基因突变。此外，无论LC的组织学类型如何，有21个激酶普遍上调。生物信息学解码了激酶作为主要调节因子发挥作用的网络。通常，这些网络在腺癌、鳞状、神经内分泌和转移LC中分别由14、9、16和19个高度调控的激酶组成。抑制作为主要调节因子的激酶会破坏信号网络，并且它们的基因敲低研究证实了在一组人LC细胞系中细胞增殖受到抑制。此外，所提出的分子分析能够为获得性耐药患者提供基于KI的治疗。
我们的研究拓宽了LC中基于KI治疗的视野，并且我们提出了一个克服获得性耐药的框架。
