Integrating tumor and stroma to understand and predict treatment response

整合肿瘤和基质以了解和预测治疗反应

• 批准号: 10693943
• 负责人: Naim Ur Rashid
• 金额: $ 92.46万
• 依托单位: UNIV OF NORTH CAROLINA CHAPEL HILL
• 依托单位国家: 美国
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-09-01 至 2027-08-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10693943
• 关键词: Affect; Biological Assay; Biometry; CLIA certified; Cancer Biology; Cell Communication; Cells; Characteristics; Clinic; Clinical; Clinical Trials; Coculture Techniques; Computing Methodologies; Data; Data Set; Desmoplastic; Genes; Heterogeneity; Libraries; Manuscripts; Methods; Modeling; Molecular Profiling; Neoadjuvant Therapy; Outcome; Patient-Focused Outcomes; Patients; Phosphotransferases; Positioning Attribute; Prediction of Response to Therapy; Primary Neoplasm; Proteome; Sampling; Selection for Treatments; Signal Transduction; Systemic Therapy; Testing; Therapeutic; Tumor Subtype; Validation; cell type; clinical application; clinically relevant; early phase trial; immunoregulation; innovation; kinase inhibitor; molecular subtypes; multidisciplinary; neoplastic cell; novel; patient response; predicting response; prognostic; response; standard of care; transcriptome; transcriptome sequencing; treatment effect; treatment response; tumor; tumor heterogeneity; tumor microenvironment; tumor progression

ABSTRACT Through novel deconvolution approaches for bulk RNA sequencing analysis, we identified two tumor-intrinsic subtypes of PDAC (basal and classical) that we have confirmed, are robust, replicable, prognostic and predictive of treatment response. We found that the basal subtype is consistently associated with poor outcome and have shown, through analysis of two clinical trials, that patients with basal subtype tumors do not respond to the 1st-line therapy FOLFIRINOX. These results strongly support the idea that molecular subtypes may be used to select treatment. Given the impact of our tumor-intrinsic subtypes on therapy response, we developed a single sample classifier, PurIST, that is now a CLIA certified assay and being evaluated as an integral marker for treatment selection in a clinical trial. In parallel, we developed a de novo approach, DECODER to deconvolve bulk tumors into compartments that allows us to determine tumor and TME specific characteristics in patients. Using the deconvolution approaches that led us to identify tumor-intrinsic subtypes, we have found two types of PDAC stroma: activated, and normal where patients with activated stroma have shorter survival. We have shown that CAFs are the contributory cells in activated stroma. Patients can be found to have a combination of tumor/stroma subtypes and the combinations have different impacts on outcome, suggesting that it is critically important to understand tumor-stroma interactions and how they affect treatment response. Similarly, we find that i/myCAF may differentially educate basal vs. classical subtype lines Our findings provide strong support for our central hypothesis that CAFs and tumor cells have interactions that together may alter tumor progression and response, making it critical that we understand the heterogeneity of the stroma, and specifically CAFs, their interaction with the tumor, for tumor-stroma context specific treatment response. Our team is uniquely positioned to comprehensively characterize CAF/NAF-tumor heterogeneity and interactions, response to treatment, and develop an integrative CAF-tumor subtype classifier to predict treatment response of patients in standard of care, stroma and immune modulating trials.

摘要 通过用于批量RNA测序分析的新的去卷积方法，我们鉴定了两种肿瘤固有的 我们已经证实的PDAC亚型（基础型和经典型）是稳健的、可复制的、预后性的， 预测治疗反应。我们发现，基底亚型与低血糖相关， 通过对两项临床试验的分析，结果表明，基底亚型肿瘤患者 对一线治疗FOLFIRINOX有反应。这些结果有力地支持了分子亚型 可以用来选择治疗。 考虑到我们的肿瘤内在亚型对治疗反应的影响，我们开发了一个单样本分类器， PurIST，现在是一种经过CLIA认证的检测方法，并被评估为治疗选择的不可或缺的标志物 临床试验。与此同时，我们开发了一种从头开始的方法，DECODER去卷积大块肿瘤， 这使得我们能够确定患者的肿瘤和TME特异性特征。 使用去卷积方法，使我们能够识别肿瘤内在亚型，我们发现了两种类型 PDAC间质：活化，正常，其中具有活化间质的患者具有较短的存活。我们有 显示CAFs是活化基质中的贡献细胞。可以发现患者具有以下组合： 肿瘤/间质亚型和组合对结果有不同的影响，这表明它是至关重要的， 重要的是要了解肿瘤间质的相互作用，以及它们如何影响治疗反应。同样，我们发现 i/myCAF可以区别地培养基础与经典亚型细胞系， 我们的研究结果为我们的中心假设提供了强有力的支持，即CAFs和肿瘤细胞之间存在相互作用， 一起可能改变肿瘤的进展和反应，这使得我们了解肿瘤的异质性变得至关重要。 基质，特别是CAF，它们与肿瘤的相互作用，用于肿瘤-基质环境特异性治疗 反应我们的团队在全面表征CAF/NAF-肿瘤异质性方面具有独特的优势， 相互作用，对治疗的反应，并开发一个综合的CAF肿瘤亚型分类器，以预测 标准治疗、基质和免疫调节试验中患者的治疗反应。