Identification and functional characterization of long non-coding RNAs as epigenetic determinants of therapy resistance in BRAF-driven cancers

在包括黑色素瘤(MM)和毛细胞性星形细胞瘤(PA)在内的多种癌症中，BRAF介导的丝裂原活化蛋白激酶(MAPK)通路的激活是致癌的标志。长非编码RNA(LncRNA)作为MAPK通路的调节者，特别是对MAPK抑制的治疗耐药的调节作用仍然知之甚少，但可能成为肿瘤学中一个新的强大靶点。由于许多lncRNAs的表达仅限于特定的发育程序或细胞状态，这些转录本作为预测生物标记物和治疗靶点特别有希望。我们已经成功地建立了一条生物信息学管道，以揭示髓母细胞瘤多组学数据集中的候选LncRNA(突变数据、RNA测序和基因表达谱)。在这里，我们建议识别和功能鉴定在BRAF突变的肿瘤中特异性表达并阻碍对BRAF抑制剂的治疗反应的lncRNAs。我们计划使用我们建立的系统生物学管道来发现与这些lncRNA相关的信号网络。虽然多发性骨髓瘤的突变情况非常复杂，但PA含有非常有限的重复突变，主要发生在BRAF和其他MAPK途径中间体，导致实验分析中的突变噪声要低得多。我们将覆盖来自原始MM和PA样本的依赖于BRAF的lncRNA表达谱。随后，我们将使用功能基因组学方法，根据患者来源的细胞模型和已建立的PA和MM细胞系中候选基因的过度表达或缺失，确定选定的lncRNA候选基因与癌症相关的作用，后者是由PhenoTImE联盟内部的合作提供的。具体地说，我们将揭示BRAF抑制时不同的lncRNA表达，然后调节最有希望的候选lncRNA的表达，以潜在地克服耐药性。使用来自MM和PA患者的临床注释的肿瘤样本，所产生的LncRNA图谱也将被评估其作为治疗预测生物标记物的潜力。最后，我们将利用蛋白质组学数据的系统生物学方法，结合高通量药物筛选，识别和验证与MAPK抑制剂的协同联合治疗，以克服治疗耐药性。我们期望从这些研究中为未来临床试验的设计和建立进一步的翻译生物标记物计划提供直接的翻译理由。临床研究单位PhenoTImE的共同目标是建立一个强大的合作网络的基本基础，该网络具有高度互补性的专业知识，以阐明lncRNAs是BRAF突变肿瘤中MAPK信号的关键调节器。同样，我们将贡献我们的生物信息学专业知识和高通量药物筛选平台，以确保将深刻的生物学见解快速转化为临床应用。

BRAF-mediated activation of the mitogen-activated protein kinase (MAPK) pathway represents an oncogenic hallmark in several cancer types including melanoma (MM) and pilocytic astrocytoma (PA). The contribution of long non-coding RNAs (lncRNA) as regulators of the MAPK pathway and, particularly, of therapy resistance to MAPK inhibition remains poorly understood, but could represent a novel powerful target in oncology. As expression of many lncRNAs is confined to specific developmental programs or cellular states, these transcripts are particularly promising as predictive biomarkers and therapeutic targets. We have successfully established a bioinformatic pipeline to reveal lncRNA candidates in multi-omics datasets in medulloblastomas (mutational data, RNA sequencing and gene expression profiling). Here, we propose to identify and functionally characterize lncRNAs that are specifically expressed in BRAF-mutant tumors and impede the therapeutic response to BRAF inhibitors. We plan to discover the signaling networks that correlate with these lncRNAs using our established systems biology pipeline. While the mutational landscape of MM is highly complex, PA harbors very limited recurrent mutations mostly in BRAF and other MAPK pathway intermediates causing much lower mutational noise in experimental analysis. We will overlay the BRAF-dependent lncRNA expression profiles from primary MM and PA samples. Subsequently, we will determine the cancer-related role of selected lncRNA candidates using functional genomics approaches upon candidate gene overexpression or depletion in patient-derived cell models and established cell lines from PA and MM, the latter being provided by collaborations within the PhenoTImE consortium. Specifically, we will reveal differential lncRNA expression upon BRAF inhibition and then modulate the expression of the most promising lncRNA candidates to potentially overcome drug resistance. Using clinically annotated tumor samples from MM and PA patients, the resulting lncRNA profiles will be also evaluated regarding their potential as predictive biomarkers for therapy. Lastly, we will utilize a systems biology approach for proteogenomic data combined with high-throughput drug screening to identify and validate synergistic combination therapies with MAPK inhibitors to overcome therapy resistance. We expect from these studies straightforward translational rationales for the design of future clinical trials and for the establishment of further translational biomarker programs alongside. The common goals of the Clinical Research Unit PhenoTImE serve as a fundamental basis for a powerful collaborative network with highly complementary expertise to elucidate lncRNAs as crucial modulators of MAPK signaling in BRAF mutant tumors. Likewise, we will contribute our bioinformatic expertise and high-throughput drug screening platform to ensure rapid translation of the profound biological insights into clinical applications.