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.

项目概要： 胰腺导管腺癌（PDA）将成为癌症死亡的第二大原因， 美国到2030年。大多数PDA患者存在不可切除/转移性疾病，并且全身 化疗是这些患者的固定治疗。手术是少数患者的一种选择（约30%） 虽然大多数人在高度病态的手术后会出现早期复发， 隐匿性转移因此，新辅助治疗（NAT）是一种新兴的标准方法，但仅限于 如果选择的系统治疗有效，则是有益的。事实上，对于所有患有PDA的患者，转移性或其他， 有效的系统治疗的持续时间是影响其生存的最重要因素。有一个关键的未满足的 需要准确和及时评估治疗反应，以1）使患者接受有效的系统性治疗 尽快治疗，并保持尽可能长的时间，2）迅速停止有毒，昂贵的 和无效的治疗，3）促进基于证据的个性化临床决策， 意图手术目前PDA的治疗主要依赖于计算机断层扫描（CT）和肿瘤标记物 （CA 19 -9）。然而，这些工具不够灵敏，并且对于裁定患者的益处来说太慢 快速致命的转移性疾病，并确定最有可能从手术中受益的合适候选人 我们现在有了尖端的工具，可以在分子水平上更精确地量化疾病负担。 和代谢水平。我们以前已经证明，突变KRAS循环肿瘤（ct）DNA可以检测到， 在PDA中具有高敏感性，在有效的治疗下倾向于迅速下降，并且可能是一个更动态的预测因子 比CA 19 -9的治疗反应。我们还表明，代谢成像与混合集成18-氟- 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上隐匿的微小转移， 不可切除/转移性PDA，并预测接受NAT的患者对NAT的病理反应 切除术基于这些有希望的结果，我们假设KRAS ctDNA的适当组合 PET/MRI生物标记物将能够及时评估PDA患者治疗的临床效用。在Aim中 1，我们将使用动态和 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。在Aim中 2，我们将构建，测试和验证一个模型，手术受益或无效的患者可能切除 使用动态KRAS ctDNA和FDG PET/MRI响应数据的PDA。我们的首要目标是整合可靠的 生物标志物，可以准确指导治疗，并使精准医疗，以改善患者的结果 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