Integrative prediction models for metastasis risk in colon cancer

结肠癌转移风险的综合预测模型

• 批准号: 8706083
• 负责人: Robert Daniel Beauchamp
• 金额: $ 44.89万
• 依托单位: VANDERBILT UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2012
• 资助国家: 美国
• 起止时间: 2012-08-01 至 2017-05-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8706083
• 关键词: Adjuvant; Adjuvant Chemotherapy; Biological Assay; Biological Preservation; Biology; Blinded; Cancer Patient; Clinical; Clinical Trials; Collaborations; Colon Carcinoma; Colorectal Cancer; Data; Development; Elements; Evaluation; Formalin; Gene Expression; Gene Expression Profile; Genes; Genome; Goals; Human Resources; Individual; Investments; Lead; Medicine; Methods; Modeling; Molecular; Morbidity - disease rate; Mus; Mutation; Neoplasm Metastasis; Operative Surgical Procedures; Outcome; Pathologic; Patient Selection; Patients; Phase; RNA; Recurrence; Reproducibility; Research; Risk; Sensitivity and Specificity; Somatic Mutation; Specimen; Staging; Standardization; Systemic Therapy; Testing; Time; Tissue Banks; Tissues; Translating; base; cancer care; cancer cell; cancer prevention; cancer therapy; clinical application; clinical risk; cohort; comparative effectiveness; cost; design; disorder later incidence prevention; evidence base; head-to-head comparison; high risk; improved; mortality; novel; nuclease; outcome forecast; prospective; research clinical testing; response; sample fixation; standard care; tool

DESCRIPTION (provided by applicant): While adjuvant chemotherapy for stage III colon cancer results in an overall survival benefit, 42 to 44% of stage III patients will not recur in five years even without adjuvant treatment. Conversely, clinical trials have failed to demonstrate an overall benefit of adjuvant chemotherapy for stage II colon cancer; however, a subset of high-risk patients may benefit from adjuvant treatment. Thus, an accurate and reliable method of determining risk of recurrence, and corresponding likelihood of benefit of systemic therapy, is greatly needed. We have recently developed a novel gene expression signature ("34-gene signature") based on the metastatic biology of mouse colon cancer cells, capable of segregating colon cancer patient groups into low and high risk of recurrence. A gene signature such as this may allow for more appropriate selection of patients to receive or not receive adjuvant chemotherapy, thus enabling those phase III patients at low risk to avoid the potential morbidity, occasional mortality, and definite financial expense of systemic therapy, while improving the survival of phase II patients. To accurately identify personal risk, clinical, demographic, pathologic, and somatic mutation data all must be incorporated with gene expression; to incorporate these various data, we propose to conduct research to develop an integrative metastatic risk prediction model that allows for integration of diverse types of data. We will validate the predictive power of this model and, over the next five years, explore platforms to apply this tool prospectively as an approach to guide treatment decisions in colon cancer patients. This focused study will translate our molecular findings to clinical application in a relatively short time, in advance of clinical trials. The long-term goal for this proposal is to develop a clinically useful metastasis score from diverse type of data that can be applied to stage II and III colon cancer patients for the purpose of reducing mortality, morbidity, and the cost associated with colon cancer and colon cancer treatment. To this end, our specific aims are as follows: 1) develop an integrative metastasis risk prediction model for colon cancer; 2) determine the optimum platform for the 34-gene metastasis score clinical test; and 3) test the optimized prognosis signature in a blinded fashion on archival tissue, to determine the robustness of the test and whether the metastasis risk score should be advanced to a prospective clinical trial to predict outcomes in stage II and III patients.

描述（由申请人提供）：虽然 III 期结肠癌的辅助化疗可带来总体生存获益，但即使不进行辅助治疗，42% 至 44% 的 III 期患者也不会在五年内复发。相反，临床试验未能证明辅助化疗对 II 期结肠癌的总体益处；然而，一部分高危患者可能会受益于辅助治疗。因此，非常需要一种准确可靠的方法来确定复发风险以及相应的全身治疗获益的可能性。 我们最近根据小鼠结肠癌细胞的转移生物学开发了一种新的基因表达特征（“34 基因特征”），能够将结肠癌患者群体分为低复发风险和高复发风险。诸如此类的基因特征可能允许更合适地选择接受或不接受辅助化疗的患者，从而使那些低风险的 III 期患者能够避免潜在的发病率、偶发性死亡和全身治疗的明确财务费用，同时改善II 期患者的生存情况。 为了准确识别个人风险，临床、人口统计、病理和体细胞突变数据都必须与基因表达结合起来；为了整合这些不同的数据，我们建议进行研究以开发一个综合的转移风险预测模型，该模型可以整合不同类型的数据。我们将验证该模型的预测能力，并在未来五年内探索前瞻性地应用该工具的平台，作为指导结肠癌患者治疗决策的方法。这项重点研究将在临床试验之前在相对较短的时间内将我们的分子发现转化为临床应用。 该提案的长期目标是从不同类型的数据中开发出一种临床上有用的转移评分，可应用于 II 期和 III 期结肠癌患者，以降低死亡率、发病率以及与结肠癌相关的成本，结肠癌治疗。为此，我们的具体目标如下：1）建立结肠癌综合转移风险预测模型； 2）确定34基因转移评分临床试验的最佳平台； 3) 在档案组织上以盲法测试优化的预后特征，以确定测试的稳健性以及转移风险评分是否应推进前瞻性临床试验以预测 II 期和 III 期患者的结果。