A Software Platform for the Identification of Cell Surface Antigens Using RNA-seq Data

人单克隆抗体是发展最快的治疗方式之一， 超过60种化合物被FDA批准用于治疗感染、自身免疫、慢性炎症 和癌症这些疾病加在一起造成了5000万人死亡 根据世界卫生组织的数据，然而，治疗的出现 预期免疫制剂可显著降低相关的发病率和死亡率， 特别是对于肿瘤疾病。目前，有15种免疫肿瘤学（IO）治疗方法， 商业上可用，并包括一个不断增长的市场，预计到2022年将达到1000亿美元。 IO治疗剂通过选择性结合肿瘤特异性蛋白结构域有效地攻击癌症。 细胞表面，称为肿瘤相关胞外域（TAE）。然而，许多癌症 对可用的IO保持不敏感，因为难以识别有效和安全的TAE。 检测TAE的标准方法成本高、耗时长，而且检测TAE的能力有限。 发现新的目标，需要开发创新技术来规避 这个负担。RNAseq是目前发现新型剪接异构体最有效的方法， 高通量、灵敏和廉价。Envisagenics一直处于RNAseq的最前沿， 自其SpliceCore®平台发布以来，在这里，我们建议 开发一种新型药物发现平台， 具有机器学习算法知识库，能够快速识别异常 使用RNAseq数据的剪接衍生的TAE。在第一阶段SBIR提案中，我们将开发和 在急性髓性白血病的情况下应用SpliceIO，急性髓性白血病是一种对IO特别耐药的癌症， 与剪接错误调节和关键剪接体组分内的突变高度相关。 我们将使用已建立的白血病细胞系和患者源性TAE在体外鉴定和验证TAE。 与纪念斯隆的Omar Abdel-Wahab博士合作进行骨髓穿刺 凯特林癌症中心总的来说，本文概述的目标将使我们能够开发和 验证新型剪接依赖性TAE鉴定平台，以提供新的药物来源 目标，同时大大减少与其开发相关的时间和成本。在 此外，这将使Envisagenics能够为IO共同创造新的合作机会， 与制药公司合作开发。如果成功，该管道可用于识别 用于癌症和炎性疾病患者分层的药物靶标和/或生物标志物， SBIR第二阶段赠款的背景。

Human monoclonal antibodies are among the fastest growing therapeutic modalities, with over sixty compounds approved by FDA to treat infections, autoimmunity, chronic inflammation and cancer. In combination, these diseases are responsible for the deaths of 50 million people annually, according to the World Health Organization. However, the advent of therapeutic immunologics is expected to significantly reduce the associated morbidity and mortality, particularly for oncologic diseases. Currently, 15 immuno-oncologic (IO) treatments are commercially available and comprise a growing market that is expected to reach $100B by 2022. IO therapeutics effectively attack cancer by selectively binding tumor-specific protein domains on the cell surface, referred to as tumor-associated ectodomains (TAEs). However, many cancers remain insensitive to available IO as effective and safe TAEs are difficult to identify. Standard methods to detect TAEs are costly, time-consuming and limited in their ability to discover novel targets, necessitating the development of innovative technologies to circumvent this burden. RNAseq is currently the most effective method to discover novel splicing isoforms, is high-throughput, sensitive and inexpensive. Envisagenics has been at the forefront of RNAseq- based splicing characterization since the release of its SpliceCore® platform. Here, we propose to develop SpliceIO, a novel drug discovery platform that integrates the Envisagenics’ SpliceCore knowledge base with machine learning algorithms to enable rapid identification of aberrant splicing-derived TAEs using RNAseq data. In this Phase I SBIR proposal, we will develop and apply SpliceIO in the context of Acute Myeloid Leukemia, a cancer particularly resistant to IO but highly associated with splicing mis-regulation and mutations within key spliceosome components. We will identify and validate TAEs in vitro using established leukemia cell lines and patient-derived bone marrow aspirates in collaboration with Dr. Omar Abdel-Wahab from Memorial Sloan Kettering Cancer Center. Collectively, the aims outlined herein will allow us to both develop and validate a novel splicing-dependent TAE identification platform to provide new sources of drug targets while dramatically reducing the time and cost associated with their development. In addition, this will allow Envisagenics to create new partnership opportunities for IO co- development with pharmaceutical companies. If successful, this pipeline can be used to identify drug targets and/or biomarkers for patient stratification in cancer and inflammatory diseases in the context of an SBIR Phase II grant.