FAST-FNA immune cell profiling in HNSCC

HNSCC 中的 FAST-FNA 免疫细胞分析

基本信息

批准号：
10154199
负责人：
Sara Isabel Pai
金额：
$ 67.07万
依托单位：
MASSACHUSETTS GENERAL HOSPITAL
依托单位国家：
美国
项目类别：
财政年份：
2021
资助国家：
美国
起止时间：
2021-01-26 至 2025-12-31
项目状态：
未结题

来源：
https://reporter.nih.gov/project-details/10154199
关键词：
Address Antibodies Archives Artificial Intelligence B-Lymphocytes Biological Markers Biopsy Biopsy Specimen Cells Chemistry Clinical Clinical Laboratory Improvement Amendments Clinical assessments Consumption Core Biopsy Diagnostic Emerging Technologies Engineering Evaluation Evolution Fine needle aspiration biopsy Fresh Tissue Goals Head and Neck Squamous Cell Carcinoma Human Image Guided Biopsy Immune Immune response Immunotherapeutic agent Immunotherapy Laboratories Malignant Neoplasms Methods Modification Morbidity - disease rate Needles Pathologist Patients Physiologic Monitoring Quality Control Recurrence Research Sampling Sedation procedure Site Specimen Stains System T-Lymphocyte Technology Testing Time Tissue Harvesting Tissues Training Translating Treatment Efficacy Treatment Protocols Tumor-infiltrating immune cells United States Food and Drug Administration Validation anti-PD-1 base biomarker discovery biomarker validation cancer cell chemotherapy clinical application clinical predictors companion diagnostics cost experimental study innovation molecular marker mouse model novel predictive marker programmed cell death ligand 1 response response biomarker therapy outcome tumor tumor microenvironment

项目摘要

Currently, the single best predictive biomarker of response to anti-PD1 monotherapy is PD-L1 expression as assessed by immunohistochemical staining of archived or fresh tissue. Current workflows for PD-L1 assessment in tissue are labor and time consuming, are not infallible (inconclusive results in a fraction of image guided biopsies) and are associated with morbidity and are thus rarely performed serially. Rapid on site assessment of cellular, rather than tissue, specimens obtained through fine needle aspiration (FNA) could not only circumvent these bottlenecks but also enable more comprehensive and serial profiling of the tumor microenvironment to obtain the most up-to-date information of a rapidly changing microenvironment during tumor evolution and therapy. The goal of this project is to further develop and validate the new FAST-FNA technology for rapid biomarker discovery and validation in HNSCCs. There are two main aims. In aim 1 we will develop and validate existing and new biomarkers in FNA samples of HNSCC patients (n=100). Specifically we will I) develop and validate new predictive immunotherapeutic biomarkers and ii to determine how well the new FAST-FNA scores correlate with the CPS scores of PD-L1. The goal of the second aim is to translate the above FAST-FNA technology to serial FNA analyses in HNSCC patients receiving anti-PD1 immunotherapy (with or without chemotherapy; n=100). FNA sampling will be performed pre- and on-treatment in order to capture changes in the tumor microenvironment. As the HNSCC field shifts toward increased biomarker testing, we find an unmet clinical need to develop advanced cellular diagnostics in HNSCCs, which will facilitate rapid biomarker analysis, guide therapies and provide “real time” assessment of clinical response.

目前，抗 PD1 单一疗法反应的单一最佳预测生物标志物是 PD-L1 表达：通过存档或新鲜组织的免疫组织化学染色来评估 PD-L1 的当前工作流程。组织评估既费力又费时，而且并非绝对可靠（只有一小部分的结果是不确定的）图像引导活检），并且与发病率相关，因此很少在现场连续进行。通过细针抽吸 (FNA) 获得的标本无法评估细胞而非组织不仅可以规避这些瓶颈，还可以对肿瘤进行更全面和连续的分析微环境，以获得快速变化的微环境的最新信息该项目的目标是进一步开发和验证新的 FAST-FNA。 HNSCC 中快速生物标志物发现和验证的技术在目标 1 中，我们有两个主要目标。在 HNSCC 患者 (n=100) 的 FNA 样本中开发和现有验证和新的生物标志物。 I) 开发和验证新的预测性免疫治疗生物标志物，并 ii 确定新的免疫治疗生物标志物的效果如何 FAST-FNA 分数与 PD-L1 的 CPS 分数相关。第二个目标是转化 FAST-FNA 分数。上述 FAST-FNA 技术对接受抗 PD1 免疫治疗的 HNSCC 患者进行系列 FNA 分析（有或没有化疗；n=100）将在治疗前和治疗中进行 FNA 采样，以便随着 HNSCC 领域转向增加的生物标志物，捕获肿瘤微环境的变化。测试中，我们发现在 HNSCC 中开发先进的细胞诊断技术尚未得到满足的临床需求，这将促进快速生物标志物分析、指导治疗并提供临床反应的“实时”评估。