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.

项目总结/摘要 有人假设化疗耐药性反映了对肿瘤突变克隆的选择 由于其独特的遗传学特性，这种细胞对化疗具有内在抗性。然而，最近的报告 急性髓细胞白血病基因型与化疗耐药之间的相关性很弱。 作为一种替代，我们提出肿瘤内异质性（ITH，即克隆多样性）可能是一个预测因子， 化疗耐药性虽然人们可能会假设，ITH水平的增加与不太容易处理的 疾病，很少有数据可以明确地将ITH与结果联系起来，更不用说 存在遗传多样性和基因表达或其他表型变化。 虽然克隆进化在白血病发展和治疗中的作用已经成为一个焦点， 许多研究途径，推断单个样品的克隆组成的能力已经被证明是可行的。 受来自大量肿瘤样品的数据的使用的限制。许多克隆性的遗传评估是在 癌症标本将需要通过单细胞数据而不是单独地对克隆性进行最终描述 依赖于克隆结构的计算解卷积。不幸的是，尽管测序成本 减少，从单细胞产生统计学上有意义的数据的挑战使得大多数技术不 成本效益或单位出无信息为这一目的。除了成本，巨大的技术和 产生和分析数据的计算挑战限制了单细胞分析的研究， 实验室通常不参与临床研究。 完善技术能力，以适当地在原液和单细胞水平上获得准确数据 处理和解释这些数据，并将这种方法应用于更大的患者队列是至关重要的下一步， 从ITH分析中得出相关的生物学结论。我们的目标是通过结合散装- 水平ITH去卷积与单细胞靶向遗传分析，使用我们的新型微流控芯片，并扩展 该技术包括下游转录组学评估。识别遗传多样性、追踪 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， 我们对ITH在癌症治疗中的作用的临床理解有了实质性的提高。有可能 更直接地查询遗传变异性和这两个模型系统中可能的转录组学含义 以及在原发性人类标本中，我们可以更清楚地了解肿瘤内异质性的作用 在人类恶性肿瘤中发挥作用。替代疗法旨在为所有克隆人提供平等的进化竞争环境 并将其频率降低到可管理的水平，可以从根本上将急性疾病转化为慢性疾病， 一个.这种可能性将是一个有价值的新的临床选择，特别是毒性，或耐受性差的治疗 旨在消除所有克隆，往往导致更积极的复发性疾病。