Prognostic and Predictive Digital Tissue Image Assay for Prostate Cancer

前列腺癌的预后和预测数字组织图像分析

基本信息

批准号：
10697304
负责人：
Shilpa Gupta
金额：
$ 62.76万
依托单位：
EMORY UNIVERSITY
依托单位国家：
美国
项目类别：
财政年份：
2022
资助国家：
美国
起止时间：
2022-09-05 至 2027-08-31
项目状态：
未结题

来源：
https://reporter.nih.gov/project-details/10697304
关键词：
Accounting Adjuvant Therapy African American Androgen Suppression Architecture Biochemical Biological Assay Biological Markers Biopsy Biopsy Specimen Cancer Patient Cell Nucleus Cessation of life Clinic Clinical Clinical Trials Collagen Collagen Fiber Complement Computer software Computers Country Cues Data Dedications Ethnic Population Exhibits Genomics Gland Gleason Grade for Prostate Cancer Goals Guidelines Habitats Image Image-Guided Surgery Malignant Neoplasms Malignant neoplasm of prostate Medical Oncology Modeling Molecular Morbidity - disease rate Morphology National Comprehensive Cancer Network Neoplasm Metastasis Nomograms Nuclear Oncology Operative Surgical Procedures Organ Outcome Paper Pathologic Pathology Patients Pattern Pennsylvania Performance Phenotype Population Prognosis Prostate Cancer therapy Publishing Radiation Radiation Therapy Oncology Group Radiation therapy Radical Prostatectomy Recurrence Recurrent Malignant Neoplasm Risk Risk Reduction Secure Site Slide Specimen Testing Time Tissue imaging Tissues Translating Tumor Tissue Universities Validation Visual advanced disease androgen deprivation therapy cancer recurrence caucasian American chemotherapy companion diagnostics computerized cost diagnostic assay digital digital imaging digital pathology disorder risk effective therapy follow-up genetic testing hazard head-to-head comparison high risk high risk population improved indexing innovation men mortality risk precision medicine precision oncology predictive test prognostic prognostic assays prostate cancer model prostate cancer risk prototype randomized, clinical trials risk minimization success tool treatment guidelines tumor

Accounting Adjuvant Therapy African American Androgen Suppression Architecture Biochemical Biological Assay Biological Markers Biopsy Biopsy Specimen Cancer Patient Cell Nucleus Cessation of life Clinic Clinical Clinical Trials Collagen Collagen Fiber Complement Computer software Computers Country Cues Data Dedications Ethnic Population Exhibits Genomics Gland Gleason Grade for Prostate Cancer Goals Guidelines Habitats Image Image-Guided Surgery Malignant Neoplasms Malignant neoplasm of prostate Medical Oncology Modeling Molecular Morbidity - disease rate Morphology National Comprehensive Cancer Network Neoplasm Metastasis Nomograms Nuclear Oncology Operative Surgical Procedures Organ Outcome Paper Pathologic Pathology Patients Pattern Pennsylvania Performance Phenotype Population Prognosis Prostate Cancer therapy Publishing Radiation Radiation Therapy Oncology Group Radiation therapy Radical Prostatectomy Recurrence Recurrent Malignant Neoplasm Risk Risk Reduction Secure Site Slide Specimen Testing Time Tissue imaging Tissues Translating Tumor Tissue Universities Validation Visual advanced disease androgen deprivation therapy cancer recurrence caucasian American chemotherapy companion diagnostics computerized cost diagnostic assay digital digital imaging digital pathology disorder risk effective therapy follow-up genetic testing hazard head-to-head comparison high risk high risk population improved indexing innovation men mortality risk precision medicine precision oncology predictive test prognostic prognostic assays prostate cancer model prostate cancer risk prototype randomized, clinical trials risk minimization success tool treatment guidelines tumor

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项目摘要

PROJECT SUMMARY: There were >34,000 PCa-related deaths in 2020 in the US alone. Definitive treatment includes Radical prostatectomy (RP) or radiotherapy (RT) with long term androgen-suppression therapy (ADT). These have been shown to be effective treatments for organ-confined PCa and have been demonstrated to reduce the risk of death from PCa. In 38-52% of cases, however, advanced disease with potentially poor prognosis is found on tissue pathology. A number of recent clinical trials have shown the benefit of adjuvant therapy in select PCa patients post-RP or RT. However, it is critical to identify those PCa patients who following definitive therapy (surgery or radiation) are at high-risk for recurrence or metastasis and thus will benefit from adjuvant therapy versus patients who will not and hence may be spared the morbidity and cost of therapy. Recognizing the significance of this unmet clinical need, in 2018 the NCCN guidelines for PCa were modified to include the Decipher Score, a prognostic molecular gene-based test to identify the likelihood of metastasis following surgery. We have developed our own "Integrated Risk Score" (IRiS) image classifier that (npj Precison Onc, In Press14) combines computer extracted morphologic glandular features from H&E tissue slides of the tumor. IRiS stratified PCa patients (N>900, 6 sites) based on their time to biochemical recurrence (BCR) into low- and high-risk groups (p<0.001; HR=2.44). Further, IRiS when combined with pre-op PSA and Gleason grade outperformed Decipher in predicting BCR in N=173 patients (p<0.001; HR=3.23 vs HR=2.76). In this R01, we will validate IRiS as (1) prognostic of BCR and risk of metastasis as well as (2) predictive of the added benefit of additional chemotherapy following definitive therapy (surgery or radiation) in PCa. In a recent paper in Clin Cancer Res, we identified IRiS specific prognostic features for African American (AA) men with PCa. We will build on these findings to develop population specific IRiS models for PCa. We will also further optimize IRiS by including (1) features of stromal and cribriform morphology, (2) develop population specific IRiS models for different ethnic groups, and (3) complement IRiS with clinico-pathological features. To validate IRiS as predictive of benefit of adjuvant therapy, we need access to randomized clinical trial tissue slide images involving PCa patients treated with definitive therapy alone (surgery or ADT+radiation) and definitive therapy+ adj. chemo. The STAMPEDE and RTOG-0521 trials fit these criteria; we have secured approval to access tissue slide images from these trials. To make the tool widely available, IRiS will be integrated into PathPresenter, a digital pathology viewer and management platform currently in use in 178 countries. This partnership will combine expertise in (a) computational pathology of the Madabhushi group, (2) clinical, pathological and biomarker expertise of PCa from the University of Pennsylvania (Drs. Priti Lal) and (3) GU medical oncology expertise from the Cleveland Clinic (Dr Shilpa Gupta) to translate IRiS as the first tissue non- destructive prognostic and predictive Affordable Precision Medicine (APM) solution for PCa.

项目摘要：仅在美国，就在2020年就有34,000例与PCA有关的死亡。确定的治疗包括长期雄激素抑制疗法（ADT）的根治性前列腺切除术（RP）或放射治疗（RT）。这些已显示为有效的器官PCA处理，并已证明降低PCA死亡的风险。然而，在38-52％的病例中，晚期疾病可能很差在组织病理学上发现了预后。许多最近的临床试验显示了辅助的好处 RT或RT后精选PCA患者的治疗。但是，确定那些关注的PCA患者至关重要确定治疗（手术或辐射）处于高危或转移的高风险中，因此将从中受益辅助治疗与不会的患者，因此可能会保留治疗的发病率和成本。认识到这种未满足的临床需求的重要性，2018年NCCN PCA指南是修改以包括编译分数，这是一种基于预后的分子基因测试，以识别手术后转移。我们已经开发了自己的“综合风险评分”（IRIS）图像分类器（NPJ proceson onc，in Press14）结合了来自H＆E组织的计算机提取的形态腺特征肿瘤的幻灯片。虹膜根据生化复发时间分层PCA患者（n> 900，6个地点）（BCR）分为低风险组（P <0.001； HR = 2.44）。此外，当与PRE-OP PSA结合时，虹膜和格里森等级在预测n = 173例患者的BCR方面的表现优于解密（p <0.001; hr = 3.23 vs hr = 2.76）。在此R01中，我们将验证IRIS为（1）BCR的预后和转移风险以及（2）预测在确定治疗后（手术或辐射）在 PCA。在最近在Clin Cancer Res的论文中，我们确定了非裔美国人的虹膜特定预后特征（aa）患有PCA的男人。我们将以这些发现为基础，以开发PCA的特定人群IRIS模型。我们将还包括（1）基质和丝布状形态的特征，进一步优化虹膜，（2）发展种群不同种族的特定虹膜模型，以及（3）虹膜与临床病理学特征相辅相成。到验证虹膜可以预测辅助治疗的益处，我们需要进入随机临床试验载玻片涉及单独治疗的PCA患者（手术或ADT+辐射）和确定性的图像治疗+调整化学疗法。 Stampede和RTOG-0521试验符合这些标准；我们已获得批准从这些试验中访问组织滑动图像。为了使工具广泛可用，虹膜将集成到 PathPresenter是目前在178个国家 /地区使用的数字病理观众和管理平台。这伙伴关系将在（a）Madabhushi集团的计算病理学中结合专业知识，（2）临床，宾夕法尼亚大学PCA的病理和生物标志物专业知识（Priti Lal博士）和（3）GU 来自克利夫兰诊所（Shilpa Gupta博士）的医学肿瘤学专业知识将Iris翻译为第一个组织非组织 PCA的破坏性预后和预测性负担得起的精确药物（APM）解决方案。