Proteogenomic Predictors of Recurrence in Non-small Cell Lung Cancer

项目摘要/ABSTARCT 肺癌是全球癌症相关死亡的主要原因。近三分之一的非小细胞白血病患者 肺癌(NSCLC)存在潜在的早期可切除的NSCLC。尽管完全切除了， 大约50%的II和III期NSCLC患者复发并死于转移性NSCLC。没有 预测早期非小细胞肺癌预后不良的可靠生物标志物。分子靶向治疗和 针对程序性死亡-1(PD-1)或程序性死亡配体-1(PD-L1)的免疫检查点阻断 显著改善了转移性非小细胞肺癌患者的预后，这些药物现在 在标准治疗后进行早期肺癌的临床试验。美国国家癌症研究所 (NCI)启动了一项雄心勃勃的多中心研究，即辅助肺癌浓缩标记物 鉴定和测序(炼金术师)，筛查近8000名完全切除的非小细胞肺癌患者 识别具有表皮生长因子受体(EGFR)酪氨酸激酶(TK)激活突变的人 和间变性淋巴瘤激酶(ALK)中的重排，以研究厄洛替尼和克里佐替尼的作用， 分别进行了分析。那些缺乏EGFR突变或ALK重排的肿瘤患者被提供参与 PD-1抑制剂尼伏卢单抗对照观察的随机试验。炼金术士基因组学 工作组正计划研究近2000年来肿瘤的全部基因组、外显子和转录本 没有参与干预试验的患者(炼金术师筛选研究)和所有登记的患者 在三个炼金术士的治疗试验中。这套试验使用使用基因组分析产生的数据 为探索癌症蛋白质组在预测患者预后中的作用提供了一个独特的机会 手术切除的非小细胞肺癌。我们建议建立一个蛋白质基因组翻译研究中心(PTRC)来研究 由华盛顿大学医学院联合领导的切除早期非小细胞肺癌的蛋白质基因组学改变 医学(WUSM)和布罗德研究所以及与NCI资助的国家 临床试验网络(NCTN)支持炼金术师的临床试验套件。我们的首要目标是 将基于质谱学的全局和靶向蛋白质组学分析应用于患者来源的切除肿瘤 利用体细胞癌基因组和转录组改进预测生物标志物的材料和 临床特点。这些发现将被转化为有针对性的检测，以预测复发 在治疗之后。由于炼金术师Crizotinib的研究仍在进行中，招募的人数相对较少 与其他研究相比，我们不会将这些样本包括在这项建议中。这样做的三个目的 项目是开发预后评估工具来预测接受切除治疗的非小细胞肺癌患者的复发 使用标准铂双联化疗(AIM 1)、标准铂双联化疗和nivolumab (目标2)，和标准铂双联化疗和厄洛替尼(目标3)使用蛋白质组学。

PROJECT SUMMARY/ABSTARCT Lung cancer is a leading cause of cancer-related death globally. Nearly a third of patients with non-small cell lung cancer (NSCLC) present with potentially resectable early-stage NSCLC. Despite complete resection, approximately 50% of patients with stage II and III NSCLC recur and die from metastatic NSCLC. There are no reliable biomarkers to predict poor outcomes in early-stage NSCLC. Molecularly targeted therapies and immune checkpoint blockade targeting programmed death-1 (PD-1) or programmed death ligand-1 (PD-L1) have significantly improved the outcomes of patients with metastatic NSCLC, and these agents are now undergoing clinical trials in early-stage lung cancer following standard therapy. The National Cancer Institute (NCI) has launched an ambitious multicenter study, the Adjuvant Lung Cancer Enrichment Marker Identification and Sequencing (ALCHEMIST), to screen nearly 8000 patients with completely resected NSCLC to identify those with activating mutations in the epidermal growth factor receptor (EGFR) tyrosine kinase (TK) and rearrangements in anaplastic lymphoma kinase (ALK) to investigate the role of erlotinib and crizotinib, respectively. Those with tumors lacking EGFR mutation or ALK rearrangement were offered participation in a randomized trial comparing nivolumab, an inhibitor of PD-1 to observation. The ALCHEMIST Genomics Working Group is planning to study the tumor whole genomes, exomes, and transcriptomes from nearly 2000 patients who did not participate in the intervention trials (ALCHEMIST Screening Study) and all those enrolled in the three ALCHEMIST therapeutic trials. This suite of trials with data generated using genomic analyses provides a unique opportunity to explore the role of the cancer proteome in predicting outcomes in patients with resected NSCLC. We propose a Proteogenomic Translational Research Center (PTRC) to study the proteogenomic alterations in resected early-stage NSCLC co-led by the Washington University School of Medicine (WUSM) and the Broad Institute along with investigators affiliated with the NCI-funded National Clinical Trials Network (NCTN) supporting the ALCHEMIST suite of clinical trials. Our overarching objective is to apply mass spectrometry-based global and targeted proteomic analyses to patient-derived resected tumor material to improve upon the predictive biomarkers using somatic cancer genome and transcriptome and clinical characteristics. These discoveries will be translated into targeted assays to predict recurrence following therapy. Since the ALCHEMIST Crizotinib study is still ongoing and has enrolled relatively fewer patients compared to other studies, we will not include those samples in this proposal. The three aims of this project are to develop prognostic assessment tools to predict relapse in patients with resected NSCLC treated with standard platinum doublet chemotherapy (aim 1), standard platinum doublet chemotherapy and nivolumab (aim 2), and standard platinum doublet chemotherapy and erlotinib (aim 3) using proteogenomics.