GENOMIC HARBINGERS OF BRAIN METASTASIS IN NON SMALL CELL LUNG CANCER

非小细胞肺癌脑转移的基因组先兆

• 批准号: 9288141
• 负责人: Ramaswamy Govindan
• 金额: $ 31.64万
• 依托单位: WASHINGTON UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2014
• 资助国家: 美国
• 起止时间: 2014-07-01 至 2019-05-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9288141
• 关键词: Adenocarcinoma; Behavior; Biological; Biological Assay; Biological Markers; Biology; Biopsy; Brain; Cancer Patient; Cells; Clinical; Collaborations; Comparative Genomic Analysis; Complex; DNA Sequence Alteration; Data; Data Set; Development; Disease; Disease Progression; Evolution; Excision; Gene Expression Alteration; Gene Expression Profile; Genes; Genetic; Genetic Transcription; Genomics; Immunohistochemistry; Individual; Linear Regressions; Lung Adenocarcinoma; Metastatic Neoplasm to Lymph Nodes; Metastatic malignant neoplasm to brain; Metastatic to; Modeling; Morbidity - disease rate; Neoplasm Metastasis; Network-based; Non-Small-Cell Lung Carcinoma; Operative Surgical Procedures; Pathologic; Pathway interactions; Patients; Pattern; Phenotype; Population; Primary Neoplasm; Process; Recurrence; Retrospective cohort; Risk; Sampling; Solid Neoplasm; Somatic Mutation; Specific qualifier value; Specimen; Systemic Therapy; Technology; Testing; Therapeutic; Transcript; Validation; base; cancer gene expression; clinical biomarkers; clinical phenotype; clinically relevant; clinically significant; cohort; comparative; deep sequencing; epigenomics; exome sequencing; follow-up; gene interaction; genetic variant; genome analysis; genomic biomarker; genomic data; improved; innovation; lymph nodes; mortality; neoplastic cell; network models; next generation sequencing; novel; patient subsets; personalized medicine; predictive marker; predictive modeling; prospective; public health relevance; transcriptome; transcriptome sequencing; tumor

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.

描述（由申请人提供）：尽管全身治疗取得了进展，但脑转移仍然是非小细胞肺癌（NSCLC）患者死亡的重要原因。近50%的非小细胞肺癌患者在病程中会发生脑转移。尽管许多与实体瘤转移相关的生物学途径和过程已经被定义，但这些进展仍然没有导致预测原发性非小细胞肺癌转移行为的强大生物标志物。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进化，从而导致转移细胞表型。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的肿瘤细胞之间发生的确切改变可能是高度不同的，因此解释了为什么单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。在本提案中，我们计划利用“下一代”测序（NGS）技术同时进行外显子组和RNA测序，对患者匹配的原发性NSCLC和脑转移性肿瘤细胞群的基因组进行全面而集中的比较分析。经过审慎选择的大约75名腺癌患者将被用于发现组，包括配对原发肿瘤和脑转移病例，以及配对原发肿瘤和晚期淋巴结转移病例，以进行比较。我们将确定在转移性肿瘤细胞群和复发患者中富集的基因组和基因表达改变。而不是专注于单个基因，我们将确定在已知的促进转移表型通路的关键基因组调节因子中的协同和互补改变。对于在第一个目标中发现的那些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”测序来验证300例原发性非小细胞肺癌腺癌，这些患者来自有或没有最终发展为脑转移的患者。该提案将利用相对较大且精细的患者队列来研究非小细胞肺癌（脑转移）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可靠的生物标志物来预测非小细胞肺癌患者的脑转移行为。这种预测因子的可用性将允许对NSCLC患者进行更个性化的治疗，并最终降低与治疗和疾病进展相关的发病率和死亡率。