Systems Modeling of Tumor Heterogeneity and Therapy Response in Colorectal Cancer

结直肠癌肿瘤异质性和治疗反应的系统建模

• 批准号: 9922114
• 负责人: Fiona Ginty
• 金额: $ 55.63万
• 依托单位: GENERAL ELECTRIC GLOBAL RESEARCH CTR
• 依托单位国家: 美国
• 财政年份: 2017
• 资助国家: 美国
• 起止时间: 2017-06-01 至 2022-05-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9922114
• 关键词: Algorithms; Alternative Therapies; Ants; Apoptosis; Area; BRAF gene; Biological Markers; Biological Models; Cell Line; Cell model; Cells; Cessation of life; Chemotherapy-Oncologic Procedure; Clinical; Clinical Markers; Clinical Trials; Collaborations; Colorectal Cancer; Competence; Complex; Data; Diagnostic; Disease; Disease Resistance; Distal; Drug resistance; Endothelial Cells; Epithelial Cells; Fluorouracil; Funding; Funding Agency; Heterogeneity; Image; Imaging technology; Immune; Immunocompetence; In Vitro; Incidence; International; Intervention; Investigation; Ireland; KRAS2 gene; Letters; Location; Measurement; Measures; Memorial Sloan-Kettering Cancer Center; Metabolism; Methods; Modeling; Molecular Genetics; Monitor; Multi-Drug Resistance; Northern Ireland; Oncologist; Outcome; Pathway interactions; Patient-Focused Outcomes; Patients; Pattern Recognition; Performance; Prognostic Marker; Proteins; Randomized Clinical Trials; Randomized Controlled Trials; Recommendation; Recurrence; Research; Resistance; Resistance profile; Resolution; Risk; Sampling; Spatial Distribution; Surgeon; Systems Biology; TP53 gene; Tissues; United States; United States National Institutes of Health; Universities; Validation; Vision; Work; base; cancer diagnosis; cancer recurrence; cancer stem cell; cell stroma; cellular imaging; chemotherapy; cohort; college; colon cancer patients; cytotoxicity; determinants of treatment resistance; drug testing; endothelial stem cell; genotoxicity; improved; insight; lymph nodes; molecular subtypes; mortality; multiplexed imaging; negative affect; neoplastic cell; novel; novel therapeutics; outcome forecast; patient subsets; predictive marker; predictive modeling; predictive signature; prognostic; programs; rectal; response; single cell analysis; stem; stem cells; targeted treatment; tumor; tumor heterogeneity; tumor microenvironment

PROJECT SUMMARY/ABSTRACT Colorectal cancer (CRC) has one of the highest worldwide incidence (>1.3 million new cases) and mortality rates (~610,000 deaths annually). Genotoxic chemotherapy in stage II and III confers minimal treatment benefit (im- proved survival in 3-4% stage II patients and 15-20% patients in stage III), and predictive markers for therapy response are lacking. CRC patients would strongly benefit from novel prognostic and predictive biomarkers that identify patients who will not benefit from 5-FU-based chemotherapy, redirecting them towards targeted or novel interventions and intensified disease monitoring. One of the challenges in implementing such a biomarker approach is that CRC is a highly heterogeneous disease, with evidence for multiple subtypes emerging. The pur- ported causes of chemotherapy resistance are complex and multi-factorial, including dysfunctional apoptosis pathways, immune cell cytotoxicity (in turn, negatively affecting apoptosis and reducing immune-competency) and presence of cancer stem cells (and expression of multi-drug resistance proteins). The numbers, spatial dis- tribution and pathway status of these cells in the tumor and stromal area (and their heterogeneity) is an import- ant consideration, but the significance is not understood. The central hypothesis under investigation in this pro- posal is that modeling of apoptosis pathways at a cellular level and integration with tumor heterogeneity mark- ers in stage II and III CRC patient samples will better predict chemotherapy response, compared to standard biomarkers and treatment algorithms. While the immediate application would be for stage II patients, the re- sults will provide much needed new mechanistic insights into stage III outcomes and diagnostic opportunities for new therapies. We will use a novel single cell imaging technology to profile up to 50 proteins in a single tis- sue micro array (TMA) sections and quantify cellular and spatial distribution in tumor and stromal regions. in >1500 stage II and III CRC patients. These proteins will represent the apoptosis pathway, tumor microenviron- ment, stem cells, stroma and epithelial cells and be quantified at single cell level. Established models will be used to convert single cell apoptosis data into apoptosis competency scores. Heterogeneity in cellular apoptosis will be correlated with recurrence risk in treated and untreated patients. Tumor microenviroment measures (stroma, immune, endothelial), stem cells and available molecular subtype data will be combined with apoptosis scores to further elucidate therapy response. We will validate significant predictive biomarkers in a randomized controlled trial with chemotherapy treated and untreated patients. Finally, in a subset of patients with available cell lines, we will experimentally investigate mechanisms of drug resistance and test whether novel apoptosis- inducing therapies could potentially provide an alternative to chemotherapy. Predictive biomarkers in CRC could potentially save hundreds of thousands of patients per year from treatments with limited benefit and pro- vide oncologists with greater ability to direct patients towards other therapies.

项目摘要/摘要 结直肠癌（CRC）是全球发病率最高（> 130万例新病例）和死亡率之一 （每年约610,000人死亡）。 II和III期间的遗传毒性化学疗法赋予了最小的治疗益处（IM- 在第三阶段的3-4％II期患者和15-20％的患者中证明了生存率），治疗的预测标记 缺乏反应。 CRC患者将大力受益于新颖的预后和预测性生物标志物 确定不会从基于5-FU的化学疗法中受益的患者，将其重定向到针对性或 新颖的干预措施和加强疾病监测。实施这种生物标志物的挑战之一 方法是CRC是一种高度异质性疾病，有多种亚型出现的证据。 pur- 化学疗法耐药性的移植原因是复杂且多因素的，包括功能失调的凋亡 途径，免疫细胞细胞毒性（反过来对凋亡产生负面影响并降低免疫能力） 癌症干细胞的存在（以及多药耐药蛋白的表达）。数字，空间差异 这些细胞在肿瘤和基质区域（及其异质性）中的贡献和途径状态是进口 蚂蚁的考虑，但意义尚不理解。在研究中所研究的中心假设 posal是在细胞水平上对凋亡途径的建模，并与肿瘤异质性标记的整合 与标准相比 生物标志物和治疗算法。虽然立即适用于第二期患者，但 Sults将为III期成果和诊断机会提供急需的新机械见解 用于新疗法。我们将使用一种新型的单细胞成像技术在单个Tis-中介绍多达50种蛋白质 SUE微阵列（TMA）切片，并量化肿瘤和基质区域中的细胞和空间分布。在 > 1500阶段II和III CRC患者。这些蛋白质将代表凋亡途径，肿瘤微环体 - 摄入，干细胞，基质和上皮细胞，并在单细胞水平上进行定量。建立的模型将是 用于将单细胞凋亡数据转换为凋亡能力得分。细胞凋亡的异质性 将与经过治疗和未经治疗的患者的复发风险相关。肿瘤微病措施 （基质，免疫，内皮），干细胞和可用的分子亚型数据将与凋亡结合 得分以进一步阐明治疗反应。我们将验证随机的显着预测生物标志物 接受化疗治疗和未经治疗的患者对照试验。最后，在一部分患者中 细胞系，我们将通过实验研究耐药性的机制，并测试新的细胞凋亡 - 诱导疗法可能有可能提供化学疗法的替代方法。 CRC中的预测生物标志物 每年有可能使数十万患者免于受益和利益有限的治疗 视频肿瘤学家可以更大的能力将患者引向其他疗法。