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.

摘要 III期结直肠癌（CRC）在肿瘤生物学和临床结局方面表现出很大的变异性， 有必要了解患者的预后，以衡量化疗的风险和强度 化疗管理。这些特征不能很好地被目前在生物医学中使用的生物标志物概括。 在临床上，它们中的大多数是基于DNA的突变测定。RNA表达模式已被描述为 不同的研究人员，并可能更全面地概括肿瘤生物学。这些发现的临床效用 由于明显的亚组划分工作的冲突和缺乏有效的基因表达标记， 作为适用于福尔马林固定石蜡包埋（FFPE）组织的临床级试验。在我们的国际 与之前在该领域发表过文章的几位学术领导者合作，我们确定了一个 基于独立于临床的聚类方法的鲁棒一致性亚组分类 结果。值得注意的是，这个分类系统，称为共识分子亚型（CMS），确定了4个 亚组，为CRC的分类提供了新的见解。一个亚组有间质细胞，TGF-β， 和血管生成特征（CMS4）与死亡风险比为2.26（95%CI为1.41至3.61， P =.001），显著高于其他亚组，在多变量模型中，包括当前临床和 病理风险因素和遗传标记（Oncotype Dx）。我们假设一个基因表达 可以开发和验证特征分类器以确定FFPE组织中的CMS，并且 该分类器可以被实现为通过将它们分类为 CMS 4与其他亚型。我们已经开发了一个支持向量机分类器，具有非常高的精度， 基于来自新鲜冷冻标本的Affyellow阵列的分类。我们展示了良好的 使用定制的Nanostring代码集对85例FFPE肿瘤样本进行分类准确率（> 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再现性 样品在本申请中，我们将使用Nanostring Codeset将测定转移至新鲜冷冻（FF）， FFPE使用一组配对样本，同时保持分类器性能。然后，我们将寻求技术和 测定的分析验证，包括重复性精密度、样品类型之间的重现性、样品间的 实验室再现性和RNA质量/数量的影响。在赠款的UH3部分，我们将在临床上验证 基因表达特征检测在单机构队列中的预后效用，然后在一个完整的 在CLIA认证实验室进行的FOLFOX化疗（NRG/NSABPC-08）的前瞻性研究。附加数据 将用于预测对各种护理治疗标准的反应，这代表了一系列未来的 分析的潜在应用。通过利用开发用于根据其肿瘤生物学对CRC进行分类的测定， 我们预计会开发出一种持久的工具，它将比传统的适用于目的的工具有更大的用途 试验.