Use of Quantitative RT-PCR for Staging Esophageal Cancer

使用定量 RT-PCR 对食管癌进行分期

基本信息

项目摘要

DESCRIPTION (provided by applicant): In the USA, the incidence of esophageal adenocarcinoma has risen more than 350% since 1974 while long-term survival rates have remained at 10-15%. Current staging methods are inadequate for predicting survival in this disease, as evidenced by the fact that even patients with early stage, potentially resectable tumors frequently recur and die. Since treatment options are based on pathologic stage, clinicians need improved staging methods to assist in appropriate treatment planning for these patients. Our previously published reports indicate that disease recurrence and poor survival in esophageal cancer patients may be predicted, in part, by the presence of occult metastases to lymph nodes. Recently however, Beer et al. reported in Nature Medicine that gene expression patterns in primary tumors can predict outcome in stage I lung cancer patients. In addition, three new reports in Nature Genetics and The Lancet and Cancer Cell demonstrate that the propensity to metastasize may actually be encoded in the gene expression patterns of primary tumors. Furthermore, the Lancet study by Huang et al. identified separate gene sets that seem to predict lymph node metastasis and overall recurrence in breast cancer patients. These interrelated events would thus appear to be the result of distinct biological processes that can be detected by analysis of the primary tumor. It is our hypothesis that gene expression patterns in the primary tumor determine metastatic potential and probability of survival for patients with esophageal adenocarcinoma. Subsequently, we believe that microarray analysis of esophageal tumors will allow us to identify sets of genes that correlate with both metastasis and survival. Given the correlation between lymph node status and survival in esophageal cancer, we also hypothesize that gene expression analysis and occult disease detection approaches will identify overlapping sets of patients at high risk for recurrence. In this proposal, we intend to explore the relationship between data obtained from microarray analysis of the primary tumors and analysis of occult lymph node involvement. We believe that the combination of this comprehensive molecular staging will allow us to significantly improve upon the current staging of esophageal adenocarcinoma. In addition, we believe that this research will answer some very interesting questions about tumor biology and metastasis in esophageal cancer.
描述(由申请人提供):在美国,自1974年以来,食管腺癌的发病率上升了350%以上,而长期生存率保持在10-15%。目前的分期方法不足以预测这种疾病的生存,事实证明,即使是早期、可能切除的肿瘤患者也经常复发和死亡。由于治疗方案是基于病理分期的,临床医生需要改进分期方法,以帮助这些患者制定适当的治疗计划。我们之前发表的报告表明,食管癌患者的疾病复发和低生存率可能部分地通过淋巴结隐匿转移的存在来预测。然而,最近Beer等人在《自然医学》杂志上报道,原发肿瘤中的基因表达模式可以预测I期肺癌患者的预后。此外,《自然遗传学》、《柳叶刀》和《癌症细胞》上的三篇新报告表明,转移倾向实际上可能被编码在原发肿瘤的基因表达模式中。此外,Huang等人在《柳叶刀》上发表的研究发现,不同的基因组似乎可以预测乳腺癌患者的淋巴结转移和总体复发。因此,这些相互关联的事件似乎是不同的生物学过程的结果,可以通过分析原发肿瘤来检测。我们的假设是,原发肿瘤的基因表达模式决定了食管腺癌患者的转移潜力和生存概率。随后,我们相信食道肿瘤的微阵列分析将使我们能够识别与转移和生存相关的一系列基因。考虑到食管癌患者的淋巴结状态与生存之间的相关性,我们还假设基因表达分析和隐匿性疾病检测方法将识别重叠的高复发风险患者。在本提案中,我们打算探讨从原发肿瘤的微阵列分析中获得的数据与隐性淋巴结受累分析之间的关系。我们相信,这种综合分子分期的结合将使我们能够显著改善目前食管腺癌的分期。此外,我们相信这项研究将回答一些关于食管癌肿瘤生物学和转移的非常有趣的问题。

项目成果

期刊论文数量(16)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
Esophagectomy for T1 esophageal cancer: outcomes in 100 patients and implications for endoscopic therapy.
  • DOI:
    10.1016/j.athoracsur.2008.12.060
  • 发表时间:
    2009-04
  • 期刊:
  • 影响因子:
    4.6
  • 作者:
    Pennathur, Arjun;Farkas, Andrew;Krasinskas, Alyssa M.;Ferson, Peter F.;Gooding, William E.;Michael, K. Gibson;Schuchert, Matthew J.;Landreneau, Rodney J.;Luketich, James D.
  • 通讯作者:
    Luketich, James D.
Molecular staging of lymph nodes from patients with esophageal adenocarcinoma.
食管腺癌患者淋巴结的分子分期。
The "best operation" for esophageal cancer?
  • DOI:
    10.1016/j.athoracsur.2010.03.068
  • 发表时间:
    2010-06
  • 期刊:
  • 影响因子:
    4.6
  • 作者:
    Pennathur, Arjun;Zhang, Jie;Chen, Haiquan;Luketich, James D.
  • 通讯作者:
    Luketich, James D.
Rapid, quantitative reverse transcriptase-polymerase chain reaction: application to intraoperative molecular detection of occult metastases in esophageal cancer.
快速定量逆转录聚合酶链式反应:在食管癌隐匿性转移的术中分子检测中的应用。
Gene expression profiles in esophageal adenocarcinoma predict survival after resection.
食管腺癌的基因表达谱可预测切除后的生存率。
  • DOI:
    10.1016/j.jtcvs.2012.10.031
  • 发表时间:
    2013
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Pennathur,Arjun;Xi,Liqiang;Litle,VirginiaR;Gooding,WilliamE;Krasinskas,Alyssa;Landreneau,RodneyJ;Godfrey,TonyE;Luketich,JamesD
  • 通讯作者:
    Luketich,JamesD
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JAMES D LUKETICH其他文献

JAMES D LUKETICH的其他文献

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{{ truncateString('JAMES D LUKETICH', 18)}}的其他基金

Cardiothoracic Surgery Research Training Program
心胸外科研究培训计划
  • 批准号:
    10532792
  • 财政年份:
    2021
  • 资助金额:
    $ 27.12万
  • 项目类别:
Cardiothoracic Surgery Research Training Program
心胸外科研究培训计划
  • 批准号:
    10332894
  • 财政年份:
    2021
  • 资助金额:
    $ 27.12万
  • 项目类别:
Use of Quantitative RT-PCR for Staging Esophageal Cancer
使用定量 RT-PCR 对食管癌进行分期
  • 批准号:
    6919048
  • 财政年份:
    2001
  • 资助金额:
    $ 27.12万
  • 项目类别:
Use of Quantitative RT-PCR for Staging Esophageal Cancer
使用定量 RT-PCR 对食管癌进行分期
  • 批准号:
    7380032
  • 财政年份:
    2001
  • 资助金额:
    $ 27.12万
  • 项目类别:
Use of Quantitative RT-PCR for Staging Esophageal Cancer
使用定量 RT-PCR 对食管癌进行分期
  • 批准号:
    7215585
  • 财政年份:
    2001
  • 资助金额:
    $ 27.12万
  • 项目类别:
Use of Quantitative RT PCR for Staging Esophageal Cancer
使用定量 RT PCR 对食管癌进行分期
  • 批准号:
    6699653
  • 财政年份:
    2001
  • 资助金额:
    $ 27.12万
  • 项目类别:
Use of Quantitative RT PCR for Staging Esophageal Cancer
使用定量 RT PCR 对食管癌进行分期
  • 批准号:
    6865028
  • 财政年份:
    2001
  • 资助金额:
    $ 27.12万
  • 项目类别:
Use of Quantitative RT-PCR for Staging Esophageal Cancer
使用定量 RT-PCR 对食管癌进行分期
  • 批准号:
    7060850
  • 财政年份:
    2001
  • 资助金额:
    $ 27.12万
  • 项目类别:
Use of Quantitative RT PCR for Staging Esophageal Cancer
使用定量 RT PCR 对食管癌进行分期
  • 批准号:
    6514992
  • 财政年份:
    2001
  • 资助金额:
    $ 27.12万
  • 项目类别:
Use of Quantitative RT PCR for Staging Esophageal Cancer
使用定量 RT PCR 对食管癌进行分期
  • 批准号:
    6322120
  • 财政年份:
    2001
  • 资助金额:
    $ 27.12万
  • 项目类别:

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