QUANTITATIVE DETECTION OF CLINICALLY ACTIONABLE MUTATIONS IN LUNG CANCER

描述（由申请人提供）：现有的化疗在大多数非小细胞肺癌（NSCLC）患者中仅能提高4%-15%的生存率。鉴于目前治疗的有限成功，非常需要改善这些患者的结局。迄今为止，全面的基因组研究表明，肺肿瘤在患者之间存在显著差异。另一方面，最近使用靶向肺癌特定分子的药物，以及认识到肺肿瘤的基因组成可以预测患者对这些药物的反应，被认为是过去三十年来肺癌治疗中最引人注目的进展之一。该提案的假设是，使用“下一代”测序技术，对基因突变进行集中和敏感的分析，这些基因是目前可用治疗药物的已知靶点，将确定NSCLC患者，这些患者将是新临床试验的理想候选人。为了验证这一假设，我们将使用基于捕获的“下一代”测序测定法对大约48个基因的外显子和周围序列进行“深度”测序，这些基因是目前可用试剂的已知靶标。将对常规固定的手术病理学标本的DNA进行检测，以证明实际的临床实用性。基于一个精心挑选的，高度注释的400例早期NSCLC患者的队列，本研究产生的肿瘤DNA序列数据将使我们能够解决几个重要的实际问题，将这种方法转化为临床诊断工具。首先，基于灵敏度水平的大幅提高（1,500倍测序覆盖率），我们将确定早期基因组变异（单核苷酸取代，小插入/缺失和扩增）的总体频率。 晚期NSCLC。其次，我们将定量评估患者之间突变等位基因频率的变异性（“突变负荷”），并寻求与其他临床或病理参数（如临床复发或肿瘤组织学特征）的相关性。最后，我们将研究特定基因组变异与用于分类的传统临床和病理参数之间的潜在相关性。使用一种新的注释生物标本资源和一种创新的技术方法，这项工作将测试对NSCLC患者进行前瞻性定量突变分析以进行“个性化”治疗选择的临床相关性。

DESCRIPTION (provided by applicant): Existing chemotherapy improves survival by only 4%-15% in most patients with non-small cell lung cancer (NSCLC). There is a tremendous need to improve the outcomes in these patients given the limited success of current therapies. To date, comprehensive genomic studies have shown that lung tumors are remarkably diverse between patients. On the other hand, the recent use of agents that target specific molecules in lung cancer and the realization that the genetic makeup of a lung tumor can predict how patients will respond to each of these drugs has been considered one of the most dramatic advances in lung cancer treatment over the past three decades. The hypothesis of this proposal is that, using 'next-generation' sequencing technology, a focused and sensitive analysis of mutations in genes which are already known targets of currently available therapeutic agents will identify NSCLC patients who would be ideal candidates for novel clinical trials. To test this hypothesis, we will use a capture-based, 'next-generation' sequencing assay to perform 'deep' sequencing of the exons and surrounding sequence of approximately 48 genes that are the known targets of currently available agents. The assay will be performed on DNA from routinely fixed surgical pathology specimens to demonstrate practical clinical utility. Based on a carefully selected, highly annotated cohort of 400, early stage NSCLC patients, tumor DNA sequence data generated from this study will allow us to address several practical questions important for translating this approach into a clinical diagnostic tool. First, based on a vastly increased levelof sensitivity (1,500-fold sequencing coverage), we will determine the overall frequency of genomic variants (single nucleotide substitutions, small insertions/deletions, and amplifications) in early stage NSCLC. Second, we will quantitatively assess the variability of mutated allele frequency ('mutation burden') between patients and seek correlations with other clinical or pathological parameters such as clinical relapse or tumor histological features. Finally, we will examine potential correlations between specific genomic variants and traditional clinical and pathological parameters used for classification. Using both a novel annotated bio specimen resource and an innovative technical approach, this work will test the clinical relevance of performing prospective, quantitative mutation profiling on NSCLC patients for 'personalized' treatment selection.