GENOMIC HARBINGERS OF BRAIN METASTASIS IN NON SMALL CELL LUNG CANCER

描述（由申请人提供）：尽管全身治疗取得了进展，脑转移仍然是非小细胞肺癌（NSCLC）患者死亡的重要原因。近50%的NSCLC患者在病程中会发生脑转移。尽管已经确定了许多与实体瘤转移相关的生物学途径和过程，但这些进展仍然没有产生用于预测原发性NSCLC转移行为的稳健生物标志物。我们假设原发性NSCLC肿瘤细胞亚群通过基因组和表观基因组改变的多步骤过程演变，导致转移性细胞表型。虽然最终的功能结果可能是相同的，但患者之间甚至同一患者中肿瘤细胞之间发生的确切改变可能是高度不同的，从而解释了为什么单个基因生物标志物或相关基因表达特征在所有情况下都不能充分预测。在这项提案中，我们计划利用“下一代”测序（NGS）技术进行外显子组和RNA同步测序，对患者匹配的原发性NSCLC和脑转移瘤细胞群的基因组进行全面而集中的比较分析。一个明智选择的约75例腺癌患者的人群将用于发现集，并将包括成对的原发性肿瘤和脑转移病例以及成对的原发性肿瘤和晚期淋巴结转移病例，用于比较目的。我们将鉴定在转移性肿瘤细胞群中富集并在患者中复发的基因组和基因表达改变。而不是专注于单个基因，我们将确定已知有助于转移表型的途径的关键基因组调节因子的协同和互补改变。对于第一个目标中确定的基因组和基因表达改变，我们将构建一个基于风险的模型，该模型将在一个独立的回顾性队列中使用靶向“深度”测序进行验证，该队列包括300例原发性NSCLC腺癌患者，这些患者最终有或没有脑转移。该提案将利用一个相对较大且经过细化的患者队列来研究NSCLC（脑转移）中的特定和临床相关表型，并将应用一种创新的基于生物学的风险模型方法来确定一组更稳健的生物标志物，以预测NSCLC患者的脑转移行为。这种预测因子的可用性将使NSCLC患者的治疗更加个性化，并最终降低与治疗和疾病进展相关的发病率和死亡率。

DESCRIPTION (provided by applicant): Despite advances in systemic therapy, brain metastases remain a significant cause of mortality in non-small cell lung cancer (NSCLC) patients. Nearly 50% of patients with NSCLC will develop brain metastases during the course of their disease. Although many of the biological pathways and processes associated with solid tumor metastasis have been defined, these advances have still not led to robust biomarkers for predicting metastatic behavior in primary NSCLC. We hypothesize that subpopulations of primary NSCLC tumor cells evolve through a multistep process of genomic and epigenomic alterations that result in a metastatic cell phenotype. While the end functional consequence may be the same, the exact alterations that occur between patients and perhaps even between tumor cells in the same patient are likely to be highly varied, thus explaining why single gene biomarkers or correlative gene expression signatures are not sufficiently predictive in all cases. In this proposal, we plan to leverage 'next generation' sequencing (NGS) technologies for simultaneous exome and RNA sequencing to perform a comprehensive yet focused comparative analysis of the genomes of patient-matched primary NSCLC and brain metastatic tumor cell populations. A judiciously selected population of approximately 75 patients with adenocarcinoma will be used for a discovery set and will include paired primary tumor and brain metastasis cases as well as paired primary tumor and late stage lymph node metastasis cases for comparative purposes. We will identify both genomic and gene expression alterations that are enriched in metastatic tumor cell populations and recurrent across patients. Rather than focusing on individual genes, we will identify both synergistic and complementary alterations in key genomic regulators of pathways known to contribute to the metastatic phenotype. For those genomic and gene expression alterations identified in this first aim, we will construct a risk-based model that will be validated using targeted, 'deep' sequencing in an independent, retrospective cohort of 300 primary NSCLC adenocarcinomas from patients with and without the eventual development of brain metastases. This proposal will utilize both a relatively large and refined cohort of patients to study a specific and clinically relevant phenotype in NSCLC (brain metastasis) and will apply an innovative, biologically based risk model approach to identify a more robust set of biomarkers to predict brain metastatic behavior in NSCLC patients. The availability of such a predictor will allow for more personalized therapies for NSCLC patients and ultimately reduce the morbidity and mortality associated with treatment and disease progression.