Colorectal Cancer Molecular Subtype Assay Development and Validation

结直肠癌分子亚型检测的开发和验证

• 批准号: 9789655
• 负责人: Scott Kopetz
• 金额: $ 16.37万
• 依托单位: UNIVERSITY OF TX MD ANDERSON CAN CTR
• 依托单位国家: 美国
• 财政年份: 2018
• 资助国家: 美国
• 起止时间: 2018-09-21 至 2020-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9789655
• 关键词: Address; Advisory Committees; Age; Behavior; Benefits and Risks; Biological Assay; Biological Markers; Biology; CLIA certified; Cancer and Leukemia Group B; Cessation of life; Cetuximab; Characteristics; Classification; Clinic; Clinical; Clinical Chemistry; Clinical Trials; Collaborations; Colon Adenocarcinoma; Colon Carcinoma; Colorectal Cancer; Conflict (Psychology); Consensus; Custom; DNA; Data; Development; Discrimination; Disease; Enrollment; Ensure; Formalin; Freezing; Future; Gene Expression; Gene Expression Profile; Generations; Genetic Transcription; Goals; Grant; Immune; Individual; Infiltration; Institution; International; Knowledge; Laboratories; Machine Learning; Measures; Mesenchymal; Metabolic; Methods; Modeling; Molecular; Mutation; National Surgical Adjuvant Breast and Bowel Project; Outcome; Paraffin Embedding; Pathologic; Patients; Pattern; Performance; Prevalence; Primary Neoplasm; Procedures; Prognostic Marker; Prospective Studies; Publishing; Quality Control; RNA; Randomized; Randomized Controlled Clinical Trials; Reproducibility; Research; Research Personnel; Risk; Risk Factors; Sampling; Series; Southwest Oncology Group; Specimen; Subgroup; System; Testing; Therapeutic; Tissue Embedding; Transforming Growth Factor beta; Tumor Biology; Validation; assay development; base; bevacizumab; chemotherapy; clinical biomarkers; cohort; colon cancer patients; drug development; genetic signature; hazard; high risk; improved; innovation; insight; irinotecan; molecular subtypes; nano-string; novel; novel therapeutics; outcome forecast; oxaliplatin; phase 3 study; predicting response; prognostic; prognostic assays; prognostic signature; prognostic value; standard of care; tool; tumor; tumor behavior

ABSTRACT Stage III colorectal cancer (CRC) demonstrates substantial variability in tumor biology and clinical outcomes and there is a need to understand prognosis for patients in order to gauge risk benefit for chemotherapy and intensity of chemotherapy administration. These features are not well recapitulated by the current biomarkers in use in the clinic, majority of them are DNA based mutation assays. RNA expression patterns have been described by various investigators and may more fully recapitulate tumor biology. The clinical utility of these findings have been limited by the apparent conflicting subgrouping efforts and lack of a validated gene expression signature as a clinical grade assay applicable on formalin fixed paraffin embedded (FFPE) tissue. In our international collaboration with several academic leaders who have previously published in this field, we have identified a robust consensus subgroup classification based on clustering approaches independent of clinical outcomes. Remarkably, this classification system, termed consensus molecular subtypes (CMS), identified 4 subgroups that provide novel insights into the classification of CRC. One subgroup with mesenchymal, TGF-β, and angiogenic features (CMS4) is associated with a hazard ratio for death of 2.26 (95% CI of 1.41 to 3.61, P=.001), significantly higher than other subgroups, in a multivariate model inclusive of current clinical and pathologic risk factors and genetic signature (Oncotype Dx). We hypothesize that a gene expression signature classifier can be developed and validated for determining the CMS in FFPE tissues, and that this classifier can be implemented to improve prognostication of stage III CRC by classifying them in CMS 4 vs. other subtypes. We have developed a support-vector-machine classifier with very high accuracy for classification based on an Affymetrix array from fresh frozen specimens. We have demonstrated good classification accuracy (>90%) using customized Nanostring codesets on FFPE tumor samples of 85 patients with stage III CRC. We have also demonstrated good technical reproducibility in six of those 85 samples. In this application, we will transfer the assay using the Nanostring Codeset to fresh frozen (FF) and FFPE using a set of paired samples, while maintaining classifier performance. We will then pursue technical and analytic validation of the assay, including precision in repeatability, reproducibility between sample types, inter- lab reproducibility, and impact of RNA quality/quantity. In the UH3 portion of the grant, we will clinically validate the prognostic utility of the gene expression signature assay in single-institution cohort, and then in a completed prospective study of FOLFOX chemotherapy (NRG/NSABPC-08), in a CLIA certified laboratory. Additional data will be used in predicting response to various standard of care therapeutics, which represents a series of future potential applications of the assay. By utilizing an assay developed to classify CRC by its tumor biology, we anticipate development of an enduring tool that will be of greater use than traditional fit-for-purpose tests.

抽象的 III 期结直肠癌 (CRC) 表现出肿瘤生物学和临床结果的显着差异， 需要了解患者的预后，以评估化疗的风险益处和强度 化疗给药。目前使用的生物标志物并没有很好地概括这些特征 临床上，大多数是基于 DNA 的突变检测。 RNA 表达模式已被描述为 各种研究人员可能会更全面地概括肿瘤生物学。这些发现的临床效用 受到明显相互冲突的亚组工作和缺乏经过验证的基因表达特征的限制 作为适用于福尔马林固定石蜡包埋 (FFPE) 组织的临床级测定。在我们的国际 与之前在该领域发表过文章的几位学术领袖合作，我们确定了 基于独立于临床的聚类方法的稳健共识亚组分类 结果。值得注意的是，这个分类系统被称为共有分子亚型 (CMS)，确定了 4 为 CRC 分类提供新颖见解的子组。一个亚组具有间充质、TGF-β、 血管生成特征 (CMS4) 与死亡风险比 2.26 相关（95% CI 为 1.41 至 3.61， P=.001），在包含当前临床和临床数据的多变量模型中显着高于其他亚组 病理危险因素和遗传特征（Oncotype Dx）。我们假设基因表达 可以开发和验证特征分类器来确定 FFPE 组织中的 CMS，并且 该分类器可以通过将 III 期 CRC 分类为 CMS 4 与其他亚型。我们开发了一种具有非常高准确度的支持向量机分类器 基于 Affymetrix 阵列对新鲜冷冻标本进行分类。我们已经表现出了良好的 在 85 个 FFPE 肿瘤样本上使用定制的 Nanostring 代码集进行分类准确率 (>90%) III 期 CRC 患者。我们还在这 85 个项目中的 6 个项目中展示了良好的技术重现性 样品。在此应用中，我们将使用 Nanostring 代码集将检测转移到新鲜冷冻 (FF) 和 FFPE 使用一组配对样本，同时保持分类器性​​能。然后我们将追求技术和 测定的分析验证，包括重复性的精确性、样品类型之间的再现性、 实验室重现性以及 RNA 质量/数量的影响。在拨款的 UH3 部分中，我们将进行临床验证 基因表达特征测定在单一机构队列中的预后效用，然后在完整的 在 CLIA 认证的实验室中进行的 FOLFOX 化疗 (NRG/NSABPC-08) 前瞻性研究。附加数据 将用于预测对各种标准护理疗法的反应，这代表了一系列未来 该测定的潜在应用。通过利用一种根据肿瘤生物学特性对 CRC 进行分类的检测方法， 我们预计将开发出一种比传统的专用工具更有用的持久工具 测试。