Targeted sequencing of cell-free DNA for monitoring of prostate cancer progression

用于监测前列腺癌进展的游离 DNA 靶向测序

• 批准号: 10313093
• 负责人: Jace Webster
• 金额: $ 3.2万
• 依托单位: WASHINGTON UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-09-01 至 2024-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10313093
• 关键词: Address; Affect; African American; Androgen Receptor; BRCA2 gene; Bioinformatics; Biological Assay; Biological Markers; Biopsy; Blood; Cancer Biology; Cancer Patient; Castration; Caucasians; Cells; Cellular Assay; Clinical; Computer software; Copy Number Polymorphism; Country; Custom; DNA analysis; DNA sequencing; Data; Development; Diagnosis; Disease; Disease Progression; Disease Resistance; Enhancers; Environment; Ethnic Origin; Exhibits; Genes; Genetic; Genomics; Goals; Human; Impairment; Knowledge; Malignant neoplasm of prostate; Mentorship; Metastatic Prostate Cancer; Metastatic to; Methods; Molecular; Monitor; Mutate; Mutation; Neoplasm Circulating Cells; Neoplasm Metastasis; Newly Diagnosed; Outcome; Paper; Patient Care; Patients; Performance; Pharmaceutical Preparations; Population; Publications; Publishing; RNA Splicing; Refractory; Reproducibility; Research; Research Personnel; Resistance; Running; Sampling; Single Nucleotide Polymorphism; Software Tools; Standardization; Stratification; Structure; TP53 gene; Testing; Time; Training; Tumor Biology; Underrepresented Populations; Universities; Validation; Variant; Washington; Work; abiraterone; androgen deprivation therapy; anticancer research; base; bioinformatics tool; career; castration resistant prostate cancer; cell free DNA; chemotherapy; clinical application; clinical translation; clinically relevant; cohort; density; effective therapy; exome sequencing; gene panel; genome sequencing; high risk; improved; individualized medicine; liquid biopsy; men; molecular marker; non-invasive monitor; open source; patient stratification; programs; prospective; prostate cancer progression; skills; software development; standard care; standard of care; targeted sequencing; taxane; tool; transcriptome sequencing; translational impact; user-friendly; variant detection; whole genome

PROJECT SUMMARY / ABSTRACT Prostate cancer (PCa) results in more than 160,000 diagnoses in the US each year with essentially all patients eventually progressing to metastatic castration-resistant prostate cancer (mCRPC), the more lethal form of the disease. Early stratification of mCRPC patients is critical since 20-40% exhibit primary resistance to first-line treatments and those with resistance have a median survival of only 5.5 months. The standard-of-care circulating tumor cell assay (monitoring the AR-V7 splice variant) highlights the potential for a non-invasive method for monitoring PCa disease progression, but it gives 80-90% of patients a false-negative and has only ~3% sensitivity when used pre-treatment. The long-term objective of this proposal is to investigate the potential of a cell-free DNA (cfDNA)-based assay for mCRPC patient stratification to improve upon the current standard-of-care. To address this, the current proposal leverages our published cfDNA assay that monitors the recently discovered tandem duplication of an enhancer region upstream of the androgen receptor (AR), additional AR mutations, and 83 additional genes commonly mutated in mCRPC. Our gene panel and cfDNA analysis method (EnhanceAR-Seq) outperformed the current standard-of-care in a prospectively collected cohort of mCRPC patients. While this highlights the clinical utility of monitoring SVs non-invasively, no automated pipelines exist for SV calling using targeted cfDNA assays. Copy number variation (CNV) and SV analysis of cfDNA using a targeted sequencing approach requires specific considerations not accounted for in traditional pipelines, such as the influence of probe density on read depth. This in turn results in researchers developing custom scripts and parameters for running multiple tools for analysis of different variant classes (SV, CNV, single nucleotide variants) and ultimately impairing the reproducibility of clinically relevant work. This serves as a strong rationale for the following aims to (1) develop a standardized and robust unified pipeline for somatic variant calling of all classes using cfDNA and (2) assess the clinical utility of EnhanceAR-Seq across (a) an independent validation mCRPC patient cohort, (b) across ethnicities and (c) in an earlier clinical setting. The research will be completed with mentorship from Dr. Christopher Maher and through the Human and Statistical Genetics program at Washington University, one of the top ranked genetics programs in the country. The Maher lab is an ideal environment for this project given their extensive bioinformatics, software development, structural variation, genomics, and prostate cancer biology expertise. Training will focus on (1) developing computational skills through software development and the application of bioinformatics tools, (2) improving knowledge of translational tumor biology, and (3) professional development, all of which will support the goal of a career in cancer research. This study will have an overall impact on the field by providing a standardized and reproducible method for variant calling with cfDNA in a non-invasive assay, which will be broadly applicable beyond PCa. Long term, this research has enormous potential for clinical translation by improving PCa patient care.

前列腺癌（PCa）在美国导致超过160，000例诊断 基本上所有患者最终进展为转移性去势抵抗性前列腺癌 （mCRPC），更致命的疾病形式。mCRPC患者的早期分层至关重要，因为20-40% 对一线治疗表现出原发性耐药，耐药者的中位生存期仅为5.5 个月标准治疗循环肿瘤细胞测定（监测AR-V7剪接变体）突出了 潜在的非侵入性方法监测PCa疾病进展，但它给80-90%的患者， 假阴性，并且在治疗前使用时仅具有~3%的灵敏度。本提案的长期目标 研究基于无细胞DNA（cfDNA）的检测方法用于mCRPC患者分层的潜力， 在目前的护理标准。为了解决这一问题，目前的提案利用了我们发表的cfDNA测定法。 它监测最近发现的雄激素上游增强子区域的串联重复， 受体（AR）、其他AR突变和mCRPC中常见的83种其他基因突变。我们的基因组 和cfDNA分析方法（EnhanceAR-Seq）在前瞻性研究中优于当前的护理标准。 收集的mCRPC患者队列。虽然这突出了无创监测SV的临床实用性，但 存在使用靶向cfDNA测定的SV调用的自动化流水线。拷贝数变异（CNV）和SV 使用靶向测序方法的cfDNA分析需要特定的考虑因素，这些考虑因素在本发明中没有考虑。 传统的流水线，如探针密度对读取深度的影响。这反过来又导致研究人员 开发用于运行多个工具以分析不同变体类的定制脚本和参数（SV， CNV，单核苷酸变异），并最终损害临床相关工作的再现性。这 为以下目标提供了强有力的理由：（1）开发一个标准化和强大的统一管道， 使用cfDNA的所有类别的体细胞变体识别和（2）评估EnhanceAR-Seq在以下方面的临床效用： 独立验证mCRPC患者队列，（B）跨种族和（c）早期临床环境。的 研究将在克里斯托弗·马赫博士的指导下完成，并通过人类和统计学 华盛顿大学的遗传学项目，全国排名最高的遗传学项目之一。马赫 实验室是这个项目的理想环境，因为他们广泛的生物信息学，软件开发，结构 变异、基因组学和前列腺癌生物学专业知识。培训将侧重于（1）开发计算 通过软件开发和生物信息学工具的应用提高技能，（2） 翻译肿瘤生物学，（3）专业发展，所有这些都将支持职业生涯的目标， 癌症研究。这项研究将通过提供一个标准化的和可重复的 在非侵入性测定中使用cfDNA进行变体识别的方法，其将广泛适用于PCa之外。 从长远来看，这项研究通过改善PCa患者护理而具有巨大的临床转化潜力。