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

BRAF介导的丝裂原活化蛋白激酶（MAPK）通路的激活代表了几种癌症类型（包括黑色素瘤（MM）和毛细胞星形细胞瘤（PA））的致癌标志。长链非编码RNA（lncRNA）作为MAPK通路的调节剂，特别是对MAPK抑制的治疗抗性的调节剂的贡献仍然知之甚少，但可能代表肿瘤学中的新的强大靶标。由于许多lncRNA的表达局限于特定的发育程序或细胞状态，这些转录物作为预测生物标志物和治疗靶点特别有前途。我们已经成功地建立了一个生物信息学管道，以揭示髓母细胞瘤多组学数据集中的lncRNA候选者（突变数据，RNA测序和基因表达谱）。在这里，我们提出了识别和功能特性lncRNA的BRAF突变体肿瘤中特异性表达，并阻碍BRAF抑制剂的治疗反应。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MM的突变景观是高度复杂的，但PA具有非常有限的复发突变，主要在BRAF和其他MAPK途径中间体中，导致实验分析中的突变噪音低得多。我们将覆盖原发性MM和PA样本的BRAF依赖性lncRNA表达谱。随后，我们将使用功能基因组学方法，在患者来源的细胞模型和来自PA和MM的已建立细胞系中候选基因过表达或缺失时，确定选定lncRNA候选物的癌症相关作用，后者由PhenoTIME联盟内的合作提供。具体来说，我们将揭示BRAF抑制后的差异lncRNA表达，然后调节最有希望的lncRNA候选物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，还将评价所得lncRNA谱作为治疗预测生物标志物的潜力。最后，我们将利用系统生物学方法结合高通量药物筛选的蛋白基因组学数据，以确定和验证与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得到直接的翻译理论基础，用于设计未来的临床试验和建立进一步的翻译生物标志物项目。临床研究单位PhenoTIME的共同目标是作为一个强大的合作网络的基础，具有高度互补的专业知识，以阐明lncRNA作为BRAF突变肿瘤中MAPK信号传导的关键调节剂。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.