Optimizing Pancreatic Cancer Management with Next Generation Imaging and Liquid Biopsy

利用下一代成像和液体活检优化胰腺癌治疗

• 批准号: 10584523
• 负责人: Eric Collisson
• 金额: $ 59.83万
• 依托单位: UNIVERSITY OF CALIFORNIA, SAN FRANCISCO
• 依托单位国家: 美国
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-04-01 至 2026-03-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10584523
• 关键词: Biological Markers; Biology; CA-19-9 Antigen; Cancer Etiology; Cessation of life; Clinical; Clinical Management; Data; Detection; Diagnosis; Disease; Drops; Excision; Futility; Future; Goals; Grant; Hybrids; Image; KRAS2 gene; Localized Disease; Magnetic Resonance Imaging; Malignant Neoplasms; Malignant neoplasm of pancreas; Medical Oncologist; Metabolic; Minority; Modeling; Molecular; Monitor; Neoadjuvant Therapy; Neoplasm Metastasis; Operative Surgical Procedures; Pancreatic Ductal Adenocarcinoma; Pathologic; Patient-Focused Outcomes; Patients; Pharmaceutical Preparations; Positioning Attribute; Positron-Emission Tomography; Prediction of Response to Therapy; Recurrence; Regimen; Resectable; Resistance; Staging; Surgeon; Surgical Models; Systemic Therapy; Testing; Therapeutic; Toxic effect; Tumor Markers; United States; Unresectable; X-Ray Computed Tomography; adjudication; biomarker discovery; burden of illness; chemotherapy; cost; data integration; data modeling; effective therapy; evidence base; fluorodeoxyglucose; fluorodeoxyglucose positron emission tomography; genomic biomarker; image reconstruction; improved; improved outcome; ineffective therapies; innovation; liquid biopsy; magnetic resonance imaging biomarker; metabolic imaging; mutant; next generation; personalized decision; precision medicine; prospective; radiologist; response; response biomarker; standard of care; tool; treatment optimization; treatment response; tumor DNA

PROJECT SUMMARY: Pancreatic ductal adenocarcinoma (PDA) will become the 2nd leading cause of cancer deaths in the United States by 2030. Most patients with PDA present with nonresectable/metastatic disease, and systemic chemotherapy is the anchoring treatment in these patients. Surgery is an option in the minority of patients (~30%) who present with localized disease, though most develop early recurrence after a highly morbid surgery due to occult metastases. Therefore, neoadjuvant therapy (NAT) is an emerging standard approach, but is only beneficial if the selected systemic therapy is effective. Indeed, for all patients with PDA, metastatic or otherwise, the duration of effective systemic therapy is the most important factor in their survival. There is a critical unmet need for accurate and timely assessment of treatment response in order to 1) get patients on effective systemic therapy as soon as possible and keep them on it as long as possible, 2) expeditiously discontinue toxic, costly and ineffective therapies, and 3) facilitate evidence-based personalized clinical decisions regarding curative- intent surgery. Current management of PDA relies principally on computed tomography (CT) and tumor markers (CA19-9). However, these tools are not sensitive enough and are too slow for adjudicating benefit in patients with rapidly lethal metastatic disease, and for identifying suitable candidates most likely to benefit from surgery after NAT. We now have cutting-edge tools for more precise quantification of disease burden at the molecular and metabolic levels. We have previously shown that mutant KRAS circulating tumor (ct)DNA can be detected with high sensitivity in PDA, tends to drop rapidly with effective therapy, and may be a more dynamic predictor of therapy response than CA19-9. We have also shown that metabolic imaging with hybrid integrated 18-fluoro- deoxyglucose (FDG) positron emission tomography/magnetic resonance imaging (PET/MRI) improves the detection of subtle metastases that are occult on CT, early response assessment in patients with nonresectable/metastatic PDA, and prediction of pathological response to NAT in patients who undergo resection. Building on these promising results, we hypothesize that the appropriate combination of KRAS ctDNA and PET/MRI biomarkers will enable timely assessment of the clinical utility of therapy in PDA patients. In Aim 1, we will define thresholds for early chemotherapy switch in unresectable/metastatic PDA using dynamic and quantitative changes in KRAS ctDNA and FDG PET/MRI biomarkers for use in future prospective trials. In Aim 2, we will construct, test and validate a model of surgical benefit or futility for patients with potentially resectable PDA using dynamic KRAS ctDNA and FDG PET/MRI response data. Our overarching goal is to integrate reliable biomarkers that can accurately guide therapy and enable precision medicine to improve outcomes of patients with this deadly disease.

项目摘要： 胰腺导管腺癌（PDA）将成为癌症死亡的第二大原因 到2030年，美国。大多数PDA患者患有不可切除/转移性疾病和全身性疾病 化学疗法是这些患者的锚定治疗。手术是少数患者的一种选择（〜30％） 谁出现局部疾病，尽管大多数因高度病态手术而导致的早期复发 神秘转移。因此，新辅助治疗（NAT）是一种新兴的标准方法，但仅是 如果选定的全身疗法有效，则有益。确实，对于所有患有PDA，转移性或其他患者的患者 有效的全身疗法的持续时间是它们生存的最重要因素。有一个关键的未安装 需要准确，及时评估治疗反应以使其对1）让患者进行有效的全身性 尽快治疗，并尽可能长时间地保持治疗，2）迅速停止有毒，昂贵的 和无效的疗法，以及3）促进有关治疗性的基于证据的个性化临床决策 意图手术。 PDA的当前管理主要依赖于计算机断层扫描（CT）和肿瘤标记 （CA19-9）。但是，这些工具不够敏感，并且太慢，无法裁定患者的益处 患有快速致命的转移性疾病，并确定最有可能受益于手术的合适候选者 纳特之后。现在，我们拥有尖端的工具，可以更精确地量化分子的疾病负担 和代谢水平。我们以前已经表明，可以检测到突变的KRAS循环肿瘤（CT）DNA 在PDA中具有高灵敏度，倾向于通过有效的治疗迅速下降，并且可能是一个更具动态的预测指标 治疗反应比CA19-9。我们还表明，与杂种综合18-氟的代谢成像 - 脱氧葡萄糖（FDG）正电子发射断层扫描/磁共振成像（PET/MRI）改善了 检测CT上神秘的微妙转移酶，患者的早期反应评估 不可切除/转移性PDA，以及接受病理对NAT的病理反应的预测 切除。在这些有希望的结果的基础上，我们假设Kras ctDNA的适当组合 PET/MRI生物标志物将及时评估PDA患者治疗的临床实用性。目标 1，我们将使用动态和动态定义无法切除/转移性PDA的早期化学疗法开关的阈值 KRAS CTDNA和FDG PET/MRI生物标志物的定量变化用于未来的前瞻性试验。目标 2，我们将为具有可切除的患者构建，测试和验证手术益处或徒劳的模型 PDA使用动态KRAS CTDNA和FDG PET/MRI响应数据。我们的总体目标是整合可靠的 可以准确指导治疗并使精确药物改善患者预后的生物标志物 这种致命的疾病。

项目成果

Assessing the robustness of a machine-learning model for early detection of pancreatic adenocarcinoma (PDA): evaluating resilience to variations in image acquisition and radiomics workflow using image perturbation methods.

评估用于早期检测胰腺腺癌 (PDA) 的机器学习模型的稳健性：使用图像扰动方法评估对图像采集和放射组学工作流程变化的恢复能力。

• DOI: 10.1007/s00261-023-04127-1
• 发表时间: 2024
• 期刊: Abdominal radiology (New York)
• 作者: Mukherjee,Sovanlal;Korfiatis,Panagiotis;Patnam,NandakumarG;Trivedi,KamaxiH;Karbhari,Aashna;Suman,Garima;Fletcher,JoelG;Goenka,AjitH
• 通讯作者: Goenka,AjitH

Radiomics for Detection of Pancreas Adenocarcinoma on CT Scans: Impact of Biliary Stents.

CT 扫描检测胰腺腺癌的放射组学：胆管支架的影响。

• DOI: 10.1148/rycan.210081
• 发表时间: 2022
• 期刊: Radiology. Imaging cancer
• 作者: Suman,Garima;Patra,Anurima;Mukherjee,Sovanlal;Korffiatis,Panagiotis;Goenka,AjitH
• 通讯作者: Goenka,AjitH

Radiomics-based machine learning (ML) classifier for detection of type 2 diabetes on standard-of-care abdomen CTs: a proof-of-concept study.

基于放射组学的机器学习 (ML) 分类器，用于在标准护理腹部 CT 上检测 2 型糖尿病：一项概念验证研究。

• DOI: 10.1007/s00261-022-03668-1
• 发表时间: 2022
• 期刊: Abdominal radiology (New York)
• 作者: Wright,DarrylE;Mukherjee,Sovanlal;Patra,Anurima;Khasawneh,Hala;Korfiatis,Panagiotis;Suman,Garima;Chari,SureshT;Kudva,YogishC;Kline,TimothyL;Goenka,AjitH
• 通讯作者: Goenka,AjitH