Molecular Characterization of Stage I Lung Cancer

I 期肺癌的分子特征

基本信息

  • 批准号:
    7466801
  • 负责人:
  • 金额:
    $ 34.05万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
  • 财政年份:
    2008
  • 资助国家:
    美国
  • 起止时间:
    2008-06-17 至 2011-03-31
  • 项目状态:
    已结题

项目摘要

DESCRIPTION (provided by applicant): Lung cancer is the leading cause of cancer related deaths in the United States. Despite undergoing curative surgery, a majority of patients with resected (Stage I -III) non-small cell lung cancer (NSCLC) will die from recurrent disease within five years. Adjuvant chemotherapy in an unselected group of patients with resected stage l-lll produces only modest improvement in survival. It is critical to develop molecular predictors for recurrence. In a recent study, we applied a meta-analysis of data sets from seven different microarray studies on lung cancer for differentially expressed genes related to survival and identified a gene expression signature consisting of 64 genes that is highly predictive of recurrence. The central hypothesis is that this 64-gene signature can accurately predict survival of patients with stage I NSCLC. Two aims are proposed to test this hypothesis. In Aim 1, we will validate the 64-gene signature using a custom-designed array in 300 stage I NSCLC cases from the Cancer and Leukemia Group B (CALGB) lung cancer study 140202. The goal is to develop a diagnostic gene signature that can guide the treatment options for these patients. In Aim 2, we will validate the 64-gene signature using the Tissue Microarray (TMA) approach. We will determine whether the 64-gene signature of mRNA changes can be confirmed on the protein level using existing lung cancer TMA, and we will evaluate a subset of the 64-gene signature in a new TMA created from tumor tissues from the CALGB 140202 study. Using the newly identified 64-gene signature and the unique patient populations already developed by the CALGB lung cancer study (140202), the proposed studies will help clinicians in selecting the most effective treatment options for stage I lung cancer. Lung cancer is the leading cause of cancer related death in the United States. Nearly 50% of patients with stage I and II NSCLC will die from recurrent disease despite surgical resection. Adjuvant chemotherapy improves survival in patients with resected stage I-III NSCLC. There are no reliable clinical or molecular predictors for identifying those at high risk for developing recurrent disease. If developed, this high risk subgroup could be selected for adjuvant therapy. Future studies on adjuvant therapy would then focus on this high risk group. Conversely, the low risk group can be spared the side effects of adjuvant therapy. In a recent study, we applied a meta-analysis of data sets from seven different microarray studies on lung cancer for differentially expressed genes related to survival (less than 2 years and greater than 5 years) (Lu et al. 2006). We identified a 64 gene - molecular marker set that is highly predictive of which stage I lung cancer patients may benefit from more aggressive therapy. Our study has shown that the 64-gene molecular marker set clearly demonstrated that the high and low-risk groups are significantly different in their overall survival. The objective of this proposal is to systematically validate the 64-gene molecular marker set to predicting survival of patients with stage I NSCLC. One major resource for our proposal is direct and full access to more than 300 well- characterized human stage I lung cancer tissues from CALGB study 140202 with relevant clinical information. The central hypothesis is that the 64-gene molecular marker set can accurately predict survival of patients with stage I NSCLC. This proposal is organized into two specific aims. Aim 1 will conduct a validation study of the 64-gene molecular marker set using a custom-designed array in more than 300 stage I NSCLC from the CALGB lung cancer study (140202). Frozen samples from eligible patients will be used for RNA extraction and microarray analysis. All paraffin-embedded tumor samples from the same patients in the validation series will be examined by a pathologist to verify histopathology. Microarray analysis will be performed using a custom-designed array with the 64 genes in triplicate. Aim 2 will validate the 64-gene molecular marker set using Tissue Microarrays (TMAs). We will determine whether mRNA changes of the 64-gene molecular marker set genes can be confirmed on the protein level using multiple independent sets of lung cancer with a TMA approach. At least two independent sets of lung cancer including CALGAB 140202, and archival samples with clinical outcome data from RPCI will be used for TMA construction. We believe that the 64-gene molecular marker set are validated, adjuvant therapy could be selectively administered to those patients at high risk for relapse.
描述(申请人提供):肺癌是美国癌症相关死亡的主要原因。尽管接受了根治性手术,但大多数切除(I-III期)非小细胞肺癌(NSCLC)的患者将在五年内死于复发疾病。在L-111期切除患者中,辅助化疗仅能轻微改善患者的存活率。发展复发的分子预测是至关重要的。在最近的一项研究中,我们对来自七个不同肺癌微阵列研究的数据集进行了荟萃分析,以寻找与生存相关的差异表达基因,并确定了由基因组成的高度预测复发的基因表达特征。中心假设是这种基因标记可以准确地预测I期非小细胞肺癌患者的生存。为了检验这一假设,本文提出了两个目标。在目标1中,我们将使用定制设计的阵列在来自癌症和白血病B组肺癌研究140202的300例I期非小细胞肺癌病例中验证基因签名。我们的目标是开发一种诊断基因特征,以指导这些患者的治疗选择。在目标2中,我们将使用组织芯片方法验证基因的签名。我们将确定是否可以利用现有的肺癌TMA在蛋白质水平上证实基因标记的mrna变化,我们将评估从CALGB 140202研究的肿瘤组织创建的新TMA中基因标记的一个子集。利用新发现的基因标记和CALGB肺癌研究(140202)已经开发的独特患者群体,拟议的研究将帮助临床医生选择最有效的I期肺癌治疗方案。肺癌是美国癌症相关死亡的主要原因。尽管手术切除,近50%的I期和II期非小细胞肺癌患者仍将死于复发。辅助化疗可提高I-III期非小细胞肺癌切除患者的存活率。没有可靠的临床或分子预测指标来识别那些发展为复发疾病的高危人群。如果得到发展,这一高危亚群可以选择进行辅助治疗。未来关于辅助治疗的研究将集中在这一高危群体。相反,低风险组可以避免辅助治疗的副作用。在最近的一项研究中,我们对7个不同的肺癌微阵列研究的数据集进行了荟萃分析,以寻找与生存相关的差异表达基因(小于2年和大于5年)(Lu等人。2006)。我们确定了一组基因-分子标记物,该标记物可以高度预测I期肺癌患者可能从更积极的治疗中受益。我们的研究表明,基因的分子标记集清楚地表明,高危和低危人群在总体生存方面存在显著差异。本研究的目的是系统验证基因分子标记集预测I期非小细胞肺癌患者生存的有效性。我们建议的一个主要资源是直接和全面地获取来自CALGB研究140202的300多个具有良好特征的人类I期肺癌组织和相关的临床信息。中心假设是基因分子标记集可以准确预测I期非小细胞肺癌患者的生存。这项提议被组织成两个具体目标。目的1将在CALGB肺癌研究(140202)的300多个I期非小细胞肺癌中使用定制设计的阵列对基因分子标记集进行验证研究。来自符合条件的患者的冷冻样本将用于RNA提取和微阵列分析。来自验证系列中相同患者的所有石蜡包埋肿瘤样本将由病理学家进行检查,以验证组织病理学。微阵列分析将使用定制设计的阵列进行,其中基因一式三份。目的2利用组织芯片(TMA)验证基因分子标记集。我们将用TMA方法确定是否可以用多个独立的肺癌组在蛋白质水平上证实基因分子标记集基因的mR NA变化。至少两组独立的肺癌,包括CALGAB 140202,以及来自RPCI临床结果数据的档案样本将被用于TMA构建。我们认为基因分子标记集是有效的,可以选择性地对复发高危患者进行辅助治疗。

项目成果

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MING YOU其他文献

MING YOU的其他文献

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{{ truncateString('MING YOU', 18)}}的其他基金

IGF::OT::IGF LUNG CANCER CHEMOPREVENTION BY MICRORNA DELIVERY
通过 MICRORNA 递送进行 IGF::OT::IGF 肺癌化学预防
  • 批准号:
    9356882
  • 财政年份:
    2016
  • 资助金额:
    $ 34.05万
  • 项目类别:
TARGETED, LABEL-FREE PROTEOMIC ANALYSIS OF URINE IN A RAT BLADDER CANCER MODEL
对大鼠膀胱癌模型中的尿液进行有针对性的、无标记的蛋白质组学分析
  • 批准号:
    8361368
  • 财政年份:
    2011
  • 资助金额:
    $ 34.05万
  • 项目类别:
TARGETED, LABEL-FREE PROTEOMIC ANALYSIS OF URINE IN A RAT BLADDER CANCER MODEL
对大鼠膀胱癌模型中的尿液进行有针对性的、无标记的蛋白质组学分析
  • 批准号:
    8168722
  • 财政年份:
    2010
  • 资助金额:
    $ 34.05万
  • 项目类别:
Chemoprevention of lung cancer with red ginseng extracts
红参提取物对肺癌的化学预防
  • 批准号:
    8324234
  • 财政年份:
    2009
  • 资助金额:
    $ 34.05万
  • 项目类别:
TARGETED, LABEL-FREE PROTEOMIC ANALYSIS OF URINE IN A RAT BLADDER CANCER MODEL
对大鼠膀胱癌模型中的尿液进行有针对性的、无标记的蛋白质组学分析
  • 批准号:
    7953950
  • 财政年份:
    2009
  • 资助金额:
    $ 34.05万
  • 项目类别:
Chemoprevention of lung cancer with red ginseng extracts
红参提取物对肺癌的化学预防
  • 批准号:
    8133545
  • 财政年份:
    2009
  • 资助金额:
    $ 34.05万
  • 项目类别:
Chemoprevention of lung cancer with red ginseng extracts
红参提取物对肺癌的化学预防
  • 批准号:
    7936365
  • 财政年份:
    2009
  • 资助金额:
    $ 34.05万
  • 项目类别:
Chemoprevention of lung cancer with red ginseng extracts
红参提取物对肺癌的化学预防
  • 批准号:
    7777978
  • 财政年份:
    2009
  • 资助金额:
    $ 34.05万
  • 项目类别:
Molecular Characterization of Stage I Lung Cancer
I 期肺癌的分子特征
  • 批准号:
    7790523
  • 财政年份:
    2008
  • 资助金额:
    $ 34.05万
  • 项目类别:
Molecular Characterization of Stage I Lung Cancer
I 期肺癌的分子特征
  • 批准号:
    7640610
  • 财政年份:
    2008
  • 资助金额:
    $ 34.05万
  • 项目类别:

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用于辅助化疗筛选的显微结直肠癌肝转移 3D 工程模型
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