Identifying Treatment Options using RNA-Based Synthetic Lethality and Rescue

尽管到目前为止，精确肿瘤学已经通过使用基因组生物标记物来预测治疗反应和预测结果来定义，但到目前为止，很大一部分癌症患者仍然没有从这些治疗中受益。批量RNA提取方法的进步使这种“组学”数据在临床上得到了越来越多的应用。Enlight算法，源自Ruppin等人的SELECT。并由Pangea Bied改进，使用完整外显子RNA-seq和合成致命性来优先为患者选择治疗方案。这是一项试验性的单臂开放标签II期试验，使用从FFPE组织中提取的完整外显子RNA-SEQ的光线算法(Pangea Bied)，为参与者确定FDA批准的治疗方法。该项目是一项与皮法蒂玛·卡尔扎伊和几名参与调查人员合作的内部研究。

Although precision oncology has been defined to date by the use of genomic biomarkers for prediction of response to treatment and prognostication of outcomes, a large fraction of patients with cancer still do not benefit from these therapies to date. The advancement of bulk RNA extraction methods allows this "-omics" data to be used increasingly on a clinical basis. The ENLIGHT algorithm, derived from SELECT by Ruppin et al. and advanced by PANGEA Biomed, uses whole-exome RNA-seq and synthetic lethality to prioritize therapeutic options for patients. This is a pilot single-arm open-label phase II trial using the ENLIGHT algorithm (PANGEA Biomed) on whole-exome RNA-seq extracted from FFPE tissue to identify FDA-approved therapies for participants. This project is a collaborative intramural study with PI Fatima Karzai and with several participating investigators.