Prostate Needle Biopsies: Impact of Preanalytical Procurement and Processing Variables on the Detection of Gene Expression Signatures of Prostate Cancer Aggressiveness

前列腺针活检：分析前采购和处理变量对前列腺癌侵袭性基因表达特征检测的影响

• 批准号: 10649631
• 负责人: SANDRA M GASTON
• 金额: $ 34.41万
• 依托单位: UNIVERSITY OF MIAMI SCHOOL OF MEDICINE
• 依托单位国家: 美国
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-06-17 至 2027-05-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10649631
• 关键词: Address; Affect; Biological Assay; Biological Sciences; Biopsy; Biopsy Specimen; Categories; Characteristics; Classification; Clinical Trials; Combined Modality Therapy; Core Biopsy; Data; Detection; Disease; Distant Metastasis; Early Detection Research Network; Fixatives; Formalin; Freezing; Gene Expression; Gene Expression Profile; Gene Expression Profiling; Genes; Gleason Grade for Prostate Cancer; Goals; Habitats; Human; Image; Image Analysis; Lesion; Location; Magnetic Resonance Imaging; Malignant Neoplasms; Malignant neoplasm of prostate; Measures; Membrane; Methods; Modality; Modeling; Molecular; National Comprehensive Cancer Network; Needle biopsy procedure; Needles; Paraffin Embedding; Paraffin Tissue; Pathologic; Patients; Pattern; Positioning Attribute; Printing; Probability; Procedures; Prostate; Prostatectomy; Prostatic Neoplasms; Protocols documentation; Pyroxylin; Quantitative Reverse Transcriptase PCR; RNA; Reader; Recommendation; Regional Disease; Reporting; Reproducibility; Risk; Risk Assessment; Sampling; Sampling Errors; Specimen Handling; Standardization; Stratification; System; Techniques; Temperature; Testing; Time; Tissue Fixation; Tissue Procurements; Tissue Sample; Tissues; Touch sensation; Transcript; Tumor Volume; Uncertainty; Work; analytical method; clinical imaging; clinical practice; experience; genomic signature; high risk; imaging system; imprint; improved; large datasets; magnetic resonance imaging biomarker; men; participant enrollment; patient derived xenograft model; portability; predictive signature; preservation; prognostic; prognostic signature; prostate biopsy; prostate cancer model; prostate cancer risk; quantitative imaging; radiomics; risk selection; sample fixation; standard of care; tissue processing; transcriptome sequencing; transcriptomics; tumor heterogeneity

PROJECT SUMMARY Prostate cancer risk assessment governs decisions across a spectrum of local-regional disease from whether to biopsy to whether to intensify treatment using multimodality therapy. RNA transcript-based signatures have rapidly been incorporated into such determinations, along with Gleason Score (now termed Grade Group or GG). The significance of the proposed work is that there is a pressing need for optimization and standardization of preanalytic conditions for determination of highest GG and expression of Prostate Transcripts of Aggressiveness (PTAs), especially when working with biopsy biospecimens. These preanalytic variables extend from tissue procurement to preservation of transcript marker integrity such that appropriate risk is assigned for each patient. Obtaining prostate biopsies with multiparametric (mp) MRI-guidance has rapidly gained acceptance but there is little information about how prostate mpMRI contributes to the preanalytic variables that must be recognized and managed in clinical trials and clinical practice. There are considerable variances in the location and number of prostate biopsies collected and in the handling of the tissue from fixation to embedding to processing for testing of PTAs. As transcriptomic tests become more incorporated into clinical trials and practice, the tolerance of an assay for routinely encountered preanalytic variables must be considered in the formalization of standard operating procedures (SOPs). We will evaluate mpMRI targeted prostate biopsy specimens obtained from patients enrolled in five existing clinical trials in which the MR images are interpreted using both the standard-of- care reporting system for prostate (PIRADSv2.1) and a more advanced, automated, and portable quantitative mpMRI pixel by pixel-based scoring system termed the “Habitat Risk Score” (HRS). While PIRADS provides a critically important framework for prostate mpMRI image acquisition and interpretation, it is limited by reader subjectivity and variability in defining biopsy regions. In this project the impact of refined prostate biopsy procurement is paired with delineation of tissue processing variables for the classification of the most aggressive prostate cancer attributes defined by GG and PTAs. The Decipher Genomic Classifier (GC) score is representative of PTAs incorporated into signatures and is routinely used in clinical practice, is included in current NCCN recommendations, and is part of a combined GG/GC risk model (Spratt model). Our proof-of-principal studies on the impact of preanalytic variables examine highest GG and GC score, as well as effects on >400 PTAs. We hypothesize that mpMRI HRS directed tissue procurement will result in tissue more representative of prostate cancer risk, as determined by combined GG/GC score, as compared to tissue procurement directed by mpMRI PIRADS suspicion scores (Aim 1), that GG/Decipher GC risk will be adequately defined by 2 cores, as compared to 4 (Aim 2) and that the definition of preanalytic processing variables and revised analytic methods will result in improved integrity of PTAs (Aim 3).

项目概要 前列腺癌风险评估控制着一系列局部区域疾病的决策，从是否 活检以决定是否使用基于 RNA 转录的特征强化治疗。 已与格里森评分（现称为等级组或 GG）一起迅速纳入此类测定中。 这项工作的意义在于迫切需要优化和标准化 用于确定最高 GG 和攻击性前列腺转录本表达的分析前条件 （PTAs），特别是在处理活检生物样本时，这些分析前变量从组织延伸出来。 采购以保存转录标记的完整性，以便为每个患者分配适当的风险。 利用多参数 (mp) MRI 引导进行前列腺活检已迅速获得认可，但仍存在一些问题 关于前列腺 mpMRI 如何影响必须识别和分析的预分析变量的信息很少 临床试验和临床实践中的管理地点和数量存在很大差异。 收集前列腺活检并处理组织，从固定到包埋再到测试处理 随着转录组测试越来越多地融入临床试验和实践， 在标准的形式化中必须考虑对常规遇到的分析前变量的测定 我们将评估从获得的 mpMRI 靶向前列腺活检标本。 患者参加了五项现有的临床试验，其中使用两种标准来解释 MR 图像： 前列腺护理报告系统 (PIRADSv2.1) 和更先进、自动化、便携式定量 mpMRI 基于像素的评分系统称为“栖息地风险评分”(HRS)，而 PIRADS 则提供了一个评分系统。 对于前列腺 mpMRI 图像采集和解释至关重要的框架，它受到读者的限制 在该项目中，精细化前列腺活检的影响具有主观性和可变性。 采购与组织加工变量的描述相结合，以对最具侵略性的产品进行分类 由 GG 和 PTA 定义的前列腺癌属性是 Decipher 基因组分类器 (GC) 评分。 纳入签名并在临床实践中常规使用的 PTA 的代表，包含在当前的 NCCN 建议，并且是组合 GG/GC 风险模型（Spratt 模型）的一部分。 关于分析前变量影响的研究检查了最高 GG 和 GC 分数，以及对 >400 的影响 我们追求 mpMRI HRS 指导的组织采购将使组织更具代表性。 前列腺癌风险，由 GG/GC 综合评分确定，与由 GG/GC 指导的组织采购相比 mpMRI PIRADS 怀疑评分（目标 1），GG/Decipher GC 风险将由 2 个核心充分定义，如 与 4（目标 2）相比，分析前处理变量的定义和修订的分析方法 将提高 PTA 的完整性（目标 3）。