Targeting Mechanistic Subtypes of Neoplastic Disease

 描述（由申请人提供）：驱动癌症发生和进展的遗传病变的多样性是极端的。在很大程度上，这种邪恶的复杂性是肿瘤疾病逃避目前最有效治疗的能力的原因。针对这一难题，提出了“个性化医疗”，作为一种针对特定肿瘤遗传和表观遗传特征的癌症治疗机制。然而，由于缺乏可用的药物， 将治疗方案与合适的患者联系起来的困难。挑战在于确定真实的干预靶点，以开发适当多样化的治疗队列，以应对疾病异质性以及指定对这些治疗有反应的患者人群的分子招募生物标志物。我们正在解决这一挑战，通过对癌基因表达和肿瘤演变引起的条件性脆弱性的集中调查。为了实现这一目标，我们在一个大型的、完全分子注释的细胞系组中使用平行的遗传和化学扰动构建了癌症干预发现管道，这些细胞系代表了国家和国际癌症基因组测序工作在肺癌中检测到的体细胞病变。我们发现，目前的一线靶向治疗与有效分层反应患者所需的入组生物标志物一起在该小组中是可验证的。重要的是，我们发现，新的遗传和化学脆弱性可以被揭示出来，这些脆弱性与肺癌患者的复发性突变有关，而这些突变目前还不能“采取行动”。我们正在利用这种方法来1）解析机制性肺癌亚型，2）通过强大的分子鉴别器制定与这些亚型相关的新干预靶点和化学探针。

 DESCRIPTION (provided by applicant): Diversity in the genetic lesions that drive cancer initiation and progression is extreme. This nefarious complexity is, in large measure, responsible for the capacity of neoplastic disease to evade current best efforts for effective therapy. "Personalized medicine" has been proposed in response to this conundrum as a mechanism to tailor cancer treatment to a specific tumor's genetic and epigenetic characteristics. However, selection of appropriate treatment is dramatically limited by the paucity of available drugs and by the difficulty of linking treatment options to the appropriate patients. The challenge is to identiy authentic intervention targets for development of an appropriately diverse cohort of therapies to contend with disease heterogeneity together with molecular enrollment biomarkers that specify patient populations responsive to those therapies. We are addressing this challenge by a focused investigation of conditional vulnerabilities that arise as a consequence of oncogene expression and tumor evolution. To accomplish this, we have constructed a cancer intervention discovery pipeline using parallel genetic and chemical perturbations within a large, fully molecularly annotated, panel of cell lines representative of the somatic lesions detected in lung cancer by national and international cancer genome sequencing efforts. We have found that current first line targeted therapies are discoverable within this panel together with the enrollment biomarkers required to effectively stratify responsive patients. Importantly, we have found that new genetic and chemical vulnerabilities can be revealed that are linked to recurrent mutations in lung cancer patients that are not currently "actionable". We are leveraging this approach to 1) parse mechanistic lung cancer subtypes and 2) elaborate new intervention targets and chemical probes that are linked to those subtypes by robust molecular discriminators.