Novel Sequencing Based Diagnostics for Leukemia in Low Resource Settings

资源匮乏环境下基于测序的新型白血病诊断

• 批准号: 10357301
• 负责人: Thomas Blick Alexander
• 金额: $ 21.81万
• 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: 2022-07-01 至 2024-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10357301
• 关键词: Acute leukemia; Affect; Aneuploidy; B-Cell Acute Lymphoblastic Leukemia; Base Pairing; Bioinformatics; Biological; Biological Assay; Biology; Cancer Center; Cancer Diagnostics; Capital; Child; Classification; Clinical; Clinical Management; Clinical Oncology; Clinical Research; Collaborations; Collection; Computational algorithm; Computing Methodologies; Core-Binding Factor; Country; Cytogenetics; DNA Sequence Alteration; Data; Deposition; Development; Diagnosis; Diagnostic; ETV6 gene; Economics; Ensure; Environment; FLT3 gene; Flow Cytometry; Fluorescent in Situ Hybridization; Gene Expression; Gene Expression Profile; Gene Expression Profiling; Genomics; Genotype; Goals; Gold; Immunohistochemistry; Income; Infrastructure; International; Investments; Lymphoid; Maintenance; Malawi; Malignant Childhood Neoplasm; Malignant Neoplasms; Methods; Molecular; Mutation; Myeloid Leukemia; North Carolina; Oncology; Pathologic; Pathologist; Pathology; Patients; Protocols documentation; RNA; RUNX1 gene; Research; Resource-limited setting; Resources; Risk; Sampling; Secure; Selection for Treatments; Site; Specimen; Survival Rate; Systems Analysis; Technology; Training; Transcript; Universities; Validation; accurate diagnostics; anticancer research; base; cancer care; cancer diagnosis; care delivery; classification algorithm; clinical diagnosis; clinical sequencing; clinically actionable; cloud based; cohort; computational pipelines; computerized data processing; cost; cost effective; data management; data submission; diagnostic accuracy; diagnostic strategy; diagnostic technologies; diagnostic tool; effective therapy; feasibility testing; flexibility; future implementation; health economics; implementation research; implementation study; improved; infrastructure development; innovation; laboratory experience; leukemia; low and middle-income countries; molecular pathology; multidisciplinary; nanopore; novel; pediatric acute leukemia; peer; pilot test; precision medicine; prospective; response; tissue processing; tool; transcriptome sequencing

Project Summary Most cases of cancer worldwide are diagnosed in low and middle income countries (LMIC), where access to diagnostic technologies is limited and survival rates are low. Diagnostic resources such as flow cytometry, cytogenetics, and molecular panels are inconsistently accessible or wholly unavailable. Specifically, pathologists and clinicians cannot reliably differentiate lymphoid- from myeloid leukemia, or stratify biologic risk, leading to inaccurate or incomplete diagnosis and inappropriate treatment selection, which contributes to lower survival rates. Through development of new technical and computational approaches and feasibility testing in Malawi, we propose to advance a novel cost-effective sequencing approach to improve comprehensive leukemia diagnosis in LMICs. Our approach, using unbiased Oxford Nanopore RNA sequencing, requires low capital and per specimen costs. We have performed nanopore RNA sequencing for gene expression analysis on 124 cases of acute leukemia, demonstrating high quality RNA transcripts across a range of input conditions. We developed a pipeline that classifies leukemia lineage and core genomic subtypes. We hypothesize that locally implemented genomic sequencing, with minimal capital investment and limited training, accompanied by appropriate computational algorithms, can overcome diagnostic deficiencies for acute leukemia. In the proposed project, we will demonstrate feasibility of unbiased nanopore RNA sequencing as a diagnostic tool for acute leukemia in a low resource setting through technical and computational implementation. In Malawi, we will train laboratory personal to generate nanopore RNA sequencing from sixty diagnostic acute leukemia specimens. We will develop protocols and regulatory approvals for deposition of data into a secure cloud base system for analysis, which will allow iterative improvement of classification algorithms through ongoing collection of long-read RNA sequencing data. In parallel, we will significantly expand our cohort of nanopore RNA sequencing cases at the University of North Carolina, improving computational algorithms to classify genomic subtypes based upon nanopore gene expression profiling, validated with pathologic diagnosis and short read (eg. Illumina) sequencing data. We will develop computational pipelines and explore sequencing depth required using unbiased nanopore RNA sequencing to directly identify genomic alterations, such as fusion transcripts, aneuploidy, and FLT3 internal tandem duplications, which could allow for precision medicine approaches. Throughout this research period, we will plan for a future implementation study with a multidisciplinary group of domestic and international collaborators with expertise in clinical oncology, pathology, genomics, health economics, and implementation. Our innovative diagnostic approach could provide lineage and genotype leukemia classification on a single cost-effective platform, leading to transformational change in the diagnostic accuracy and subsequent clinical management of patients with acute leukemia in LMICs.

项目概要 全球大多数癌症病例都是在低收入和中等收入国家 (LMIC) 诊断的，这些国家可以获得 诊断技术有限，存活率低。诊断资源，例如流式细胞仪、 细胞遗传学和分子面板的访问不一致或完全不可用。具体而言，病理学家 临床医生无法可靠地区分淋巴细胞白血病和粒细胞白血病，或对生物学风险进行分层，从而导致 不准确或不完整的诊断以及不适当的治疗选择，导致生存率降低 费率。通过在马拉维开发新技术和计算方法并进行可行性测试， 我们建议推进一种新颖的、具有成本效益的测序方法来改善全面的白血病 中低收入国家的诊断。 我们的方法使用无偏见的 Oxford Nanopore RNA 测序，需要较低的资本和每个样本的成本。 我们对124例急性白血病进行了纳米孔RNA测序进行基因表达分析， 在一系列输入条件下展示高质量的 RNA 转录本。我们开发了一条管道 对白血病谱系和核心基因组亚型进行分类。我们假设本地实施的基因组 测序，以最少的资本投资和有限的培训，并伴随适当的计算 算法，可以克服急性白血病的诊断缺陷。 在拟议的项目中，我们将展示无偏纳米孔 RNA 测序作为诊断方法的可行性 通过技术和计算实施在资源匮乏的情况下治疗急性白血病的工具。在马拉维， 我们将培训实验室人员对 60 个诊断性急性白血病进行纳米孔 RNA 测序 标本。我们将开发协议和监管批准，将数据存储到安全的云基础中 分析系统，这将允许通过持续收集迭代改进分类算法 长读RNA测序数据。与此同时，我们将显着扩大我们的纳米孔 RNA 队列 北卡罗来纳大学的测序案例，改进了基因组分类的计算算法 基于纳米孔基因表达谱的亚型，通过病理诊断和短读进行验证 （例如 Illumina）测序数据。我们将开发计算管道并探索所需的测序深度 使用无偏差的纳米孔 RNA 测序直接识别基因组改变，例如融合转录本， 非整倍体和 FLT3 内部串联重复，这可以实现精准医学方法。 在整个研究期间，我们将计划与多学科小组一起进行未来的实施研究 拥有临床肿瘤学、病理学、基因组学、健康专业知识的国内外合作者 经济和实施。我们的创新诊断方法可以提供谱系和基因型 在一个具有成本效益的平台上进行白血病分类，导致诊断的变革 中低收入国家急性白血病患者的准确性和后续临床管理。