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(由申请人提供):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)患者将在五年内死于复发性疾病。辅助化疗对一组切除的l-lll期患者的生存率仅产生适度的改善。发展复发的分子预测因子是至关重要的。在最近的一项研究中,我们对来自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,并确定了由64个基因组成的基因表达特征,该基因高度预测复发。中心假设是,这64个基因签名可以准确预测I期NSCLC患者的生存率。提出了两个目标来检验这一假设。在目标1中,我们将在癌症和白血病组B(CALGB)肺癌研究140202的300例I期NSCLC病例中使用定制设计的阵列验证64基因签名。我们的目标是开发一种诊断基因签名,可以指导这些患者的治疗选择。在目标2中,我们将使用组织微阵列(TMA)方法验证64个基因特征。我们将确定是否可以使用现有的肺癌TMA在蛋白质水平上确认mRNA变化的64个基因签名,我们将评估从CALGB 140202研究的肿瘤组织中创建的新TMA中的64个基因签名的子集。使用新发现的64个基因签名和CALGB肺癌研究(140202)已经开发的独特患者人群,拟议的研究将帮助临床医生选择I期肺癌最有效的治疗方案。肺癌是美国癌症相关死亡的主要原因。近50%的I期和II期NSCLC患者即使手术切除也会死于疾病复发。辅助化疗可提高切除的I-III期NSCLC患者的生存率。目前还没有可靠的临床或分子预测指标来确定那些处于复发性疾病高风险的人。如果发生,可选择该高危亚组进行辅助治疗。未来的辅助治疗研究将集中在这一高危人群。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,我们对来自7项不同肺癌微阵列研究的数据集进行了荟萃分析,以获得与生存期(小于2年和大于5年)相关的差异表达基因(Lu et al. 2006)。我们鉴定了一组64个基因分子标记物,该标记物高度预测哪些I期肺癌患者可能从更积极的治疗中获益。我们的研究表明,64个基因的分子标记集清楚地表明,高风险组和低风险组的总体生存率有显着差异。本提案的目的是系统地验证64基因分子标记集预测I期NSCLC患者的生存。我们提案的一个主要资源是直接和完全获得来自CALGB研究140202的300多个具有相关临床信息的良好表征的人I期肺癌组织。中心假设是64基因分子标记集可以准确预测I期NSCLC患者的生存期。这项建议分为两个具体目标。Aim 1将在来自CALGB肺癌研究(140202)的300多例I期NSCLC患者中使用定制设计的阵列对64基因分子标记集进行验证研究。合格患者的冷冻样本将用于RNA提取和微阵列分析。验证系列中来自相同患者的所有石蜡包埋肿瘤样本将由病理学家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64个基因一式三份。目的2将使用组织芯片(TMAs)验证64基因分子标记集。我们将确定是否可以使用多个独立的肺癌组与TMA方法在蛋白质水平上证实64基因分子标记集基因的mRNA变化。将使用至少两组独立的肺癌(包括CALGAB 140202)和具有来自RPCI的临床结局数据的存档样本进行TMA构建。我们认为,64个基因的分子标记集是有效的,辅助治疗可以选择性地给予那些高风险的复发患者。

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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