Shen Zhong, Yvonne Börgeling, Patrick Zardo, Danny Jonigk, Jürgen Borlak
{"title":"综合转录组，miRNA和kinome分析确定了个性化肺癌治疗的新治疗选择","authors":"Shen Zhong, Yvonne Börgeling, Patrick Zardo, Danny Jonigk, Jürgen Borlak","doi":"10.1002/ctm2.70177","DOIUrl":null,"url":null,"abstract":"<div>\n \n \n <section>\n \n <h3> Background</h3>\n \n <p>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.</p>\n </section>\n \n <section>\n \n <h3> Methods</h3>\n \n <p>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 <i>N</i> = 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.</p>\n </section>\n \n <section>\n \n <h3> Results</h3>\n \n <p>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.</p>\n </section>\n \n <section>\n \n <h3> Conclusions</h3>\n \n <p>Our study broadens the perspective of KI-based therapies in LC, and we propose a framework to overcome acquired drug resistance.</p>\n </section>\n </div>","PeriodicalId":10189,"journal":{"name":"Clinical and Translational Medicine","volume":"15 3","pages":""},"PeriodicalIF":6.8000,"publicationDate":"2025-02-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/ctm2.70177","citationCount":"0","resultStr":"{\"title\":\"Comprehensive transcriptome, miRNA and kinome profiling identifies new treatment options for personalized lung cancer therapy\",\"authors\":\"Shen Zhong, Yvonne Börgeling, Patrick Zardo, Danny Jonigk, Jürgen Borlak\",\"doi\":\"10.1002/ctm2.70177\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div>\\n \\n \\n <section>\\n \\n <h3> Background</h3>\\n \\n <p>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.</p>\\n </section>\\n \\n <section>\\n \\n <h3> Methods</h3>\\n \\n <p>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 <i>N</i> = 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.</p>\\n </section>\\n \\n <section>\\n \\n <h3> Results</h3>\\n \\n <p>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. 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Comprehensive transcriptome, miRNA and kinome profiling identifies new treatment options for personalized lung cancer therapy
Background
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.
Methods
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.
Results
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.
Conclusions
Our study broadens the perspective of KI-based therapies in LC, and we propose a framework to overcome acquired drug resistance.
期刊介绍：
Clinical and Translational Medicine (CTM) is an international, peer-reviewed, open-access journal dedicated to accelerating the translation of preclinical research into clinical applications and fostering communication between basic and clinical scientists. It highlights the clinical potential and application of various fields including biotechnologies, biomaterials, bioengineering, biomarkers, molecular medicine, omics science, bioinformatics, immunology, molecular imaging, drug discovery, regulation, and health policy. With a focus on the bench-to-bedside approach, CTM prioritizes studies and clinical observations that generate hypotheses relevant to patients and diseases, guiding investigations in cellular and molecular medicine. The journal encourages submissions from clinicians, researchers, policymakers, and industry professionals.
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