Precision Approaches to Treat Mantle Cell Lymphoma: Integrating Multi-omics Based Models

项目摘要 套细胞淋巴瘤（MCL）是一种罕见的，不可治愈的形式，非霍奇金淋巴瘤，这是倾向于 治疗抗性和复发。虽然罕见，但MCL在临床和遗传上都是异质性的， 由多个子类型表示。目前尚不清楚各种基因组特征如何影响临床 MCL的病程以及这些生物学方面如何导致治疗耐药性和疾病进展。它 由于MCL的罕见性和缺乏代表性，很难研究其分子特征。 癌症基因组图谱（TCGA）。此外，目前整合组学也具有挑战性。 由于来自测序和不清楚的生物学特性的大量数据， 以及单一突变和转录特征的临床相关性。研究这些也很困难 特征与人口统计学特征和其他相关的个体特征相结合。 在拟议的论文研究项目的F99阶段，冬青山将采用新颖的分析和 在MCL患者的合并分析中整合多组学数据集的计算方法。这些分析 将包括基因组学、转录组学、表观基因组学和临床疾病组学的特征。特征选择 并将酌情使用可变的减少技术。这些子分析将识别生物学 关联并生成复合变量，这些复合变量将用于单变量和多变量模型， 检查MCL的临床结果，包括药物反应和生存率。 拟议活动的KOO阶段将包括进一步调查MCL和其他癌症， 从论文项目中获得的知识（F99）。还将使用在F99阶段获得的见解 开发靶向分析，简化MCL的突变或转录谱， 有效的应用程序。系列组学测量将被整合到相关的基因组学研究中， 精密医学试验，包括液体活检或循环肿瘤DNA（ctDNA）测序。 拟议的努力将产生对浓缩和翻译数据从组学研究到 临床空间希望这项研究的结果将为适用于精准医学试验的方法提供信息 并帮助实现我们的长期目标，为癌症患者提供个性化治疗。

Project Summary Mantle cell lymphoma (MCL) is a rare, incurable form of non Hodgkin lymphoma which is disposed to therapeutic resistance and relapse. Though rare, MCL is both clinically and genetically heterogenous and represented by multiple subtypes. It is presently unknown how various genomic features impact the clinical course of MCL and how these biological aspects contribute to treatment resistance and disease progression. It is difficult to study the molecular features of MCL due to its rarity and lack of representation in accessible databases like the cancer genome atlas (TCGA). Additionally, it is currently challenging to integrate -omics features in precision medicine initiatives due to the vast size of data from sequencing and unclear biological and clinical relevance of singular mutational and transcriptional features. It is also difficult to study these features in combination with demographic and other relevant individual features. In the F99 phase of the proposed dissertation research project, Holly Hill will employ novel analytical and computational methods to integrate multi-omics datasets in a pooled analysis of MCL patients. These analyses will include genomics, transcriptomics, epigenomics and features of the clinical exposome. Feature selection and variable reduction techniques will be used as appropriate. These sub-analyses will identify biological correlates and generate composite variables which will be used in univariate and multivariate models to examine clinical outcomes in MCL including drug response and survival. The KOO phase of the proposed activities will include further investigations into MCL and other cancers utilizing knowledge gained from the dissertation project (F99). Insights acquired during the F99 phase will also be used to develop targeted assays that simplify the mutational or transcriptional profiles of MCL into clinically useful and valid applications. Serial -omics measurements will be integrated into correlative genomics studies and precision medicine trials which will include sequencing from liquid biopsies or circulating tumor DNA (ctDNA). The proposed efforts will produce insights into condensing and translating data from -omics studies into the clinical space. It is hoped that the findings of this study will inform methods suitable for precision medicine trials and help achieve our long-term objective to personalize therapeutics for individual cancer patients.