Developing Bioinformatic and Microfluidic Single Cell Methods for Studying Intratumoral Heterogeneity in Acute Myeloid Leukemia

开发生物信息学和微流体单细胞方法来研究急性髓系白血病的瘤内异质性

• 批准号: 10308466
• 负责人: Daniel T Chiu
• 金额: $ 13.46万
• 依托单位: FRED HUTCHINSON CANCER RESEARCH CENTER
• 依托单位国家: 美国
• 财政年份: 2018
• 资助国家: 美国
• 起止时间: 2018-12-10 至 2022-03-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10308466
• 关键词: Acute Disease; Acute Myelocytic Leukemia; Address; Alternative Therapies; Big Data; Bioinformatics; Biological; Biological Models; Cancer Patient; Cells; Chemoresistance; Chronic; Clinical; Clinical Research; Clinical Trials; Clonal Evolution; Clonality; Complementary DNA; Complex; DNA; DNA sequencing; Data; Data Analyses; Data Commons; Data Set; Development; Disease; Frequencies; Gene Expression; Gene Frequency; Generations; Genetic; Genetic Transcription; Genetic Variation; Genomic Data Commons; Genotype; Heterogeneity; Human; Individual; Laboratories; Laboratory Research; Large-Scale Sequencing; Link; Malignant Neoplasms; Methods; Microfluidic Microchips; Microfluidics; Minority; Modeling; Molecular Biology; Monitor; Mutation; Outcome; Patients; Phenotype; Play; Process; Recurrent disease; Reporting; Research; Research Personnel; Resistance; Role; Sampling; Specimen; Statistical Models; Structure; System; Techniques; Technology; Therapeutic; Work; base; cancer therapy; cancer type; chemotherapy; clinically actionable; cohort; cost; data harmonization; data modeling; genetic analysis; genetic variant; improved; leukemia; metagenome; mutant; neoplastic cell; novel; single cell analysis; single-cell RNA sequencing; therapy design; tool; transcriptome; transcriptomics; translational genomics; tumor; tumor heterogeneity

PROJECT SUMMARY/ABSTRACT It has been hypothesized that chemotherapy resistance reflects selection for a mutant clone of tumor cells that is intrinsically resistant to chemotherapy due to its unique genetics. However, recent reports demonstrate only a weak correlation between acute myeloid leukemia genotype and chemotherapy resistance. As an alternative, we propose that intratumoral heterogeneity (ITH, i.e. clonal diversity) may be a predictor of chemotherapy resistance. While one might hypothesize that increased levels of ITH relates to less tractable disease, little data is available that definitively links ITH with outcome, let alone a relationship between the presence of genetic diversity and gene expression or other phenotypic changes. While the role of clonal evolution during leukemia development and therapy has been a focus for a number of avenues of research, the ability to deduce the clonal composition of individual samples has been limited by the use of data from bulk tumor samples. Many of the genetic assessments of clonality performed on cancer specimens will require the final description of clonality to be informed by single cell data rather than solely relying on computational deconvolution of the clonal structure. Unfortunately, despite sequencing cost reductions, the challenge of generating statistically meaningful data from single cells makes most techniques not cost effective or flat out uninformative for this purpose. Beyond the costs, the enormous technical and computational challenges that exist for generating and analyzing the data limit single cell analysis to research laboratories often not involved with clinical research. Refining the technical ability to derive accurate data at the bulk and single cell levels, appropriately process and interpret these data, and apply this approach to larger cohorts of patients are crucial next steps for making relevant biological conclusions from ITH analyses. We aim to address this challenge by combining bulk- level ITH deconvolution with single cell targeted genetic analysis using our novel microfluidic chip, and extending this technique to include downstream transcriptomic assessments. The ability to identify genetic diversity, track it through therapy, and connect this diversity with corresponding gene expression changes would all provide a substantial improvement in our clinical understanding of the role of ITH in cancer therapy. With the possibility to more directly query the genetic variability and possible transcriptomic implications of this in both model systems as well as in primary human specimens, we can more clearly understand what role intratumoral heterogeneity plays in human malignancy. Alternative therapies designed to level the evolutionary playing field for all clones and reduce their frequency to a manageable level, could essentially transform an acute disease to a chronic one. This possibility would be a valuable new clinical option for especially toxic, or poorly tolerated therapies designed to abolish all clones that often result in more aggressive relapsed disease.

项目摘要/摘要 据推测，化学疗法抗性反映了肿瘤突变克隆的选择 由于其独特的遗传学而对化学疗法具有本质上具有抗性的细胞。但是，最近的报告 仅证明急性髓性白血病基因型和耐化学疗法抗性之间的相关性较弱。 作为替代方案，我们建议肿瘤内异质性（即克隆多样性）可能是预测指标 化学疗法抗性。虽然可以假设ITH的水平增加与较少的障碍有关 疾病，几乎没有可用的数据将ITH与结果联系起来，更不用说 遗传多样性和基因表达或其他表型变化的存在。 尽管克隆进化在白血病发展和治疗过程中的作用一直是 研究途径的数量，推断单个样本的克隆组成的能力已经 受大量肿瘤样品的数据使用的限制。对克隆性的许多遗传评估 癌症标本将需要对克隆性的最终描述，而不仅仅是单细胞数据的信息 依靠克隆结构的计算反卷积。不幸的是，尽管成本进行了测序 减少，从单细胞中生成统计有意义的数据的挑战使大多数技术不是 为此目的，具有成本效益或不明智的态度。超越成本，巨大的技术和 生成和分析数据限制单细胞分析的计算挑战 实验室通常不参与临床研究。 完善适当的批量和单细胞水平的准确数据的技术能力，适当地 处理和解释这些数据，并将这种方法应用于较大的患者队列是至关重要的下一步 从ITH分析得出相关的生物学结论。我们旨在通过结合批量来应对这一挑战。 使用我们的新型微流体芯片进行单细胞靶向遗传分析，并延伸 该技术包括下游转录组评估。识别遗传多样性，跟踪的能力 它通过治疗，并将这种多样性与相应的基因表达变化联系起来，都将提供 我们对ITH在癌症治疗中的作用的临床理解的实质性改善。有可能 在两个模型系统中，更直接地查询遗传变异性和可能的​​转录组含义 以及在主要人类标本中，我们可以更清楚地了解肿瘤内异质性的作用 扮演人类恶性肿瘤。旨在将所有克隆的进化竞争环境均设置为替代疗法 并将其频率降低到可管理的水平，从本质上可以将急性疾病转化为慢性病 一。对于特别有毒或耐受性不佳的疗法，这种可能性将是一个有价值的新临床选择 旨在废除通常会导致更具侵略性复发疾病的所有克隆。