Predicting Transcriptional and Epigenetic Networks in Cancer from Sequencing Data

无限的复制潜力是癌症的一个关键标志，它严重依赖于端粒的维持。许多 因此，癌症会异常地重新激活端粒酶逆转录酶(TERT)，TERT是端粒酶逆转录酶的催化亚单位 拉长端粒的端粒酶复合体。最近发现，这条通向 研究发现，多发性癌症的永生是通过TERT启动子(TERTp)的两个激活点突变实现的 在50多种不同的癌症类型中，通常频率非常高，例如在胶质母细胞瘤中大约83% (GBM)和71%的黑色素瘤。在之前的资助期间，PI已经确定了分子功能 这些高度重复的突变，表明转录因子(Tf)GABP与突变的TERTp结合 具有精致的特异性，但不是野生型TERTp。TERTp突变在多发性骨髓瘤中的高流行率 癌症类型和GABP对突变型TERTp的选择性招募因此提供了前所未有的 为治疗大量癌症患者提供了机会，对健康细胞的毒性最小。尽管天气晴朗 然而，这个机会的意义，围绕着分子功能和 TERTp突变的调节因子仍然知之甚少，阻碍了有效和安全的研究进展 治疗策略。 我们的长期目标是建立一个严格的计算框架来理解这种反常现象 癌症中的转录和表观遗传网络，并应用由此产生的知识来设计新的 考虑到个别患者的遗传背景并可先验预测的治疗策略 并避免潜在的抗性机制。我们目前的续签提案的目标是发展强大的 将我们关于非编码TERTp突变的知识转化为有效TERTp突变的计算方法 和安全的分子靶标。同时，由此产生的方法将有助于解决几个突出的问题 在转录基因调控领域的挑战，并在癌症基因组学中有广泛的应用。我们 将实现我们的目标我追求以下目标：(1)开发和测试计算框架 用于推断决定平行转录因子的不同和共享结合模式的序列特征；(2) 开发和验证综合工具，以发现基因相互作用的分子基础 胚系变异和致癌突变；(3)开发和应用计算方法来研究 相邻结合基序之间的DNA螺旋相在将ETS因子招募到染色质中的作用；(4)执行 TERTp突变癌细胞中GABPB1L基因敲除效应的系统基因组特征 健康的细胞。 这一提议的结果将为癌症研究提供强大的工具，从而对癌症研究产生广泛的影响 类似性致癌的TFS，并揭示了一种非常有前景的治疗策略的新见解。

Limitless replicative potential is a key hallmark of cancer and critically depends on telomere maintenance. Many cancers thus aberrantly reactivate the telomerase reverse transcriptase (TERT), a catalytic subunit of the telomerase complex that elongates telomere. It has been recently discovered that this common path to immortality in multiple cancers is through two activating point mutations in the TERT promoter (TERTp), found in more than 50 different cancer types, often at strikingly high frequencies, e.g. roughly 83% in glioblastomas (GBM) and 71% in melanomas. In the previous funding period, the PI has identified the molecular function of these highly recurrent mutations, demonstrating that the transcription factor (TF) GABP binds the mutant TERTp with exquisite specificity, but not the wild-type TERTp. The high prevalence of TERTp mutations across multiple cancer types and the selectivity of GABP recruitment to mutant TERTp thus provide an unprecedented opportunity for treating a large number of cancer patients with minimal toxicity to healthy cells. Despite the clear significance of this opportunity, however, several important questions surrounding the molecular functions and modulators of TERTp mutations remain poorly understood, hindering the development of effective and safe therapeutic strategies. Our long-term goal is to establish a rigorous computational framework for understanding the aberrant transcriptional and epigenetic networks in cancers and to apply the resulting knowledge to devise novel therapeutic strategies that account for the genetic background of individual patients and that can a priori predict and avoid potential resistance mechanisms. The objective of our current renewal proposal is to develop powerful computational methods for transforming our knowledge about the non-coding TERTp mutations into an effective and safe molecular target. At the same time, the resulting methods will help resolve several outstanding challenges in the field of transcriptional gene regulation and have broad applications in cancer genomics. We will accomplish our objective my pursuing the following Aims: (1) Develop and test a computational framework for inferring sequence features that determine the distinct and shared binding patterns of paralogous TFs; (2) Develop and validate integrative tools for discovering the molecular basis of genetic interactions between germline variations and oncogenic mutations; (3) Develop and apply computational methods for studying the role of DNA helical phase between adjacent binding motifs in recruiting ETS factors to chromatin; (4) Perform a systematic genomic characterization of the effects of knocking out GABPB1L in TERTp-mutant cancer cells and healthy cells. The results of this proposal will have a broad impact on cancer research by providing powerful tools for studying paralogous oncogenic TFs and revealing novel insights into a highly promising therapeutic strategy.