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.

项目摘要 世界上大多数癌症病例都是在低收入和中等收入国家（LMIC）诊断出来的，在这些国家， 诊断技术有限，存活率低。诊断资源，如流式细胞术， 细胞遗传学和分子组的访问不一致或完全不可用。特别是病理学家 临床医生不能可靠地区分淋巴样白血病和髓样白血病，或对生物风险进行分层，导致 不准确或不完整的诊断和不适当的治疗选择，这有助于降低生存率 rates.通过开发新的技术和计算方法以及在马拉维进行可行性测试， 我们提出了一种新的具有成本效益的测序方法，以改善综合性白血病， LMIC中的诊断。 我们的方法，使用无偏见的牛津纳米孔RNA测序，需要低资本和每个标本的成本。 我们对124例急性白血病患者进行了纳米孔RNA测序， 证明了在一系列输入条件下的高质量RNA转录物。我们开发了一个管道， 分类白血病谱系和核心基因组亚型。我们假设本地实施的基因组 测序，以最小的资本投资和有限的培训，伴随着适当的计算 算法，可以克服急性白血病的诊断缺陷。 在拟议的项目中，我们将证明无偏纳米孔RNA测序作为诊断的可行性。 通过技术和计算实施，在低资源环境下为急性白血病提供一个工具。在马拉维， 我们将培训实验室人员从60例诊断性急性白血病中生成纳米孔RNA测序， 标本我们将开发协议和监管批准，以便将数据存储到安全的云基础中 分析系统，通过不断收集资料，不断改进分类算法 长读RNA测序数据。与此同时，我们将显著扩大我们的纳米孔RNA队列， 北卡罗来纳州大学的测序案例，改进计算算法， 基于纳米孔基因表达谱的亚型，经病理诊断和短读验证 （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 使用无偏纳米孔RNA测序直接鉴定基因组改变，例如融合转录物， 非整倍体和FLT3内部串联重复，这可以允许精确的医学方法。 在整个研究期间，我们将计划与一个多学科小组进行未来的实施研究， 在临床肿瘤学、病理学、基因组学、健康、 经济和执行。我们创新的诊断方法可以提供谱系和基因型 白血病分类在一个单一的成本效益的平台，导致转型的变化，在诊断 LMIC中急性白血病患者的准确性和随后的临床管理。