Improving response prediction to neoadjuvant therapy in pancreatic cancer

改善胰腺癌新辅助治疗的反应预测

• 批准号: 10784272
• 负责人: Harshabad Singh
• 金额: $ 28.86万
• 依托单位: DANA-FARBER CANCER INST
• 依托单位国家: 美国
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-09-15 至 2028-08-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10784272
• 关键词: Adjuvant Chemotherapy; Admixture; Adoption; Award; Basal Cell; Biological Assay; Biological Specimen Banks; Biopsy; Blood; CA-19-9 Antigen; CDKN2A gene; Cancer Biology; Cell Fraction; Cells; Chemoresistance; Chemotherapy-Oncologic Procedure; Clinical; Clinical Trials; Dana-Farber Cancer Institute; Development; Diagnosis; Diagnostic; Disease; Early identification; Enhancers; Epigenetic Process; Evolution; Excision; Exhibits; Exposure to; Fluorouracil; Gene Expression; Gene Mutation; Genes; Genetic; Genetic Transcription; Goals; Heterogeneity; Histones; Immunofluorescence Immunologic; Incidence; Individual; Institution; International; KRAS2 gene; Laboratories; Lead; MADH4 gene; Malignant neoplasm of pancreas; Measures; Mentors; Methods; Molecular; Mutation; Neoadjuvant Therapy; Operative Surgical Procedures; Outcome; Paclitaxel; Pancreas; Pathologic; Patient Monitoring; Patient-Focused Outcomes; Patients; Pattern; Phenotype; Physicians; Postoperative Period; Prediction of Response to Therapy; Prior Chemotherapy; Recurrence; Regimen; Research; Resistance; Resistance profile; Resources; Risk; Screening for cancer; Selection for Treatments; Sensitivity and Specificity; Specificity; Specimen; TP53 gene; Technology; Time; Training Programs; Tumor Burden; Tumor Markers; Tumor Tissue; Work; biobank; biomarker selection; cancer diagnosis; career; chemotherapy; cohort; digital; experience; gemcitabine; high risk; imaging modality; improved; ineffective therapies; irinotecan; mortality; multiplexed imaging; nano-string; neoplastic cell; novel; novel marker; outcome prediction; oxaliplatin; pancreatic cancer patients; pancreatic neoplasm; predicting response; predictive marker; prognostic; programs; protein biomarkers; radiological imaging; response; response biomarker; single cell analysis; therapy resistant; transcriptome; transcriptomics; treatment response; trend; triple-negative invasive breast carcinoma; tumor; tumor DNA; tumor diagnostic

PROJECT SUMMARY Localized pancreatic cancers (PC) are rising in incidence and this trend is expected to continue due to increased use of imaging modalities and focused programs on early cancer detection. Although potentially curable, long terms outcomes for localized PC remain poor. This is due to early micrometastatic spread and risk of systemic recurrence which has been reduced with use of systemic chemotherapy. In addition, use of chemotherapy prior to surgery lowers rates of positive margins and these collective observations have led to the adoption of neoadjuvant chemotherapy (NAC), i.e. prior to surgical resection, for majority of patients. NAC extends for multiple months (4-6 months) making real time assessment of response critical. However, this remains a big clinical challenge as pancreatic tumors don’t change much in size with NAC and use of tumor markers is marred by lack of specificity. Pathologic response to NAC on surgical resection specimens is highly prognostic, yet its molecular predictors remain poorly understood. Transcriptional subtypes of PC include classical and basal subtypes; the latter resembles triple negative breast cancer, displays chemotherapy resistance, and is enriched in metastatic disease. Single cell analysis of pancreatic tumors reveals extensive heterogeneity between classical and basal subtypes as well cells with co-expression of both features. In Aim 1, we use our institutional cohort of 174 patients who underwent pancreatic tumor resection after receiving NAC to identify predictors of pathologic treatment response using pre- treatment tumor specimens. We will investigate the classico-basal cell state heterogeneity using a validated multiplex immunofluorescence panel on initial diagnostic biopsies to understand differences in cell state between tumors which exhibit major response vs. no pathologic response. To identify novel predictive transcriptional states beyond classical-basal subtyping we will perform digital spatial profiling using the Nanostring GeoMx platform. In Aim 2, we propose investigating the utility of highly sensitive ctDNA assays to track changes in tumor burden and cell state during NAC. We expect differential ctDNA dynamics during NAC to predict outcomes. In addition using novel ctDNA based epigenetic assays we will assess whether tumoral cell state evolves during emergence of therapeutic resistance to more basal type. This work will lead to identification of novel predictive biomarkers which can help physicians identify high risk cases which are unlikely to respond to traditional NAC or identify early treatment resistance in real time and facilitate earlier switch to alternative chemotherapy or consideration of clinical trials leading to an improvement in outcomes for patients with localized PC. The proposed research will be performed at Dana-Farber Cancer Institute, under the guidance of Drs. Brian Wolpin and Andrew Aguirre. Both are recognized international leaders in PC biology. Importantly, this research strategy is one part of a comprehensive training program to support my transition to an independent research career in translational cancer biology. My scientific advisors (Drs. Myles Brown, Ryan Corcoran, and Eliezer Van Allen) are distinguished experts with experience highly relevant to the proposed research. My long-term goal is to lead an independent academic research group, focused on deciphering the novel biomarkers and mechanisms underlying therapy resistance in PC. The K08 award will provide pivotal protected time for continued mentored research and enable a successful transition to independence.

项目概要 局部胰腺癌 (PC) 的发病率正在上升，并且由于使用更多的药物，预计这一趋势将持续下去 早期癌症检测的成像方式和重点计划虽然可能治愈，但长期结果。 这是由于早期微转移扩散和全身复发的风险。 使用全身化疗可降低阳性率。此外，手术前使用化疗可降低阳性率。 边缘和这些集体观察导致采用新辅助化疗（NAC），即在手术之前 对于大多数患者来说，NAC 会延长数月（4-6 个月），从而实时评估反应。 然而，这仍然是一个巨大的临床挑战，因为胰腺肿瘤的大小不会因 NAC 和使用而发生太大变化。 肿瘤标志物的检测因缺乏特异性而受到损害，手术切除标本上的 NAC 病理反应非常严重。 PC 的转录亚型包括经典亚型和亚型。 后者类似于三阴性乳腺癌，表现出基础化疗耐药性，并且富含 胰腺肿瘤的单细胞分析揭示了经典肿瘤和基础肿瘤之间的广泛异质性。 在目标 1 中，我们使用了由 174 名患者组成的机构队列。 接受 NAC 后进行胰腺肿瘤切除术，以使用预 我们将使用经过验证的多重方法研究经典基底细胞状态异质性。 初始诊断活检的免疫荧光小组，以了解肿瘤之间细胞状态的差异，这些差异表现出 主要反应与无病理反应以确定经典基础之外的新预测转录状态。 在目标 2 中，我们将使用 Nanostring GeoMx 平台执行数字空间分析。 研究高灵敏度 ctDNA 检测在 NAC 期间追踪肿瘤负荷和细胞状态变化的用途。 期望 NAC 期间的差异 ctDNA 动态来预测结果。此外，还使用基于新型 ctDNA 的表观遗传学。 我们将评估肿瘤细胞状态在出现对更多基础类型的治疗耐药性期间是否发生变化。 这项工作将导致识别新的预测生物标志物，这可以帮助医生识别高风险病例，这些病例是 不太可能对传统 NAC 产生反应或实时识别早期治疗耐药性并促进早期转用 替代化疗或考虑临床试验可改善患者的预后 拟议的研究将在 Brian 博士的指导下在 Dana-Farber 癌症研究所进行。 Wolpin 和 Andrew Aguirre 都是 PC 生物学领域公认的国际领导者。 综合培训计划的一部分，以支持我过渡到转化领域的独立研究职业 我的科学顾问（Myles Brown、Ryan Corcoran 和 Eliezer Van Allen 博士）是杰出的专家。 具有与拟议研究高度相关的经验。我的长期目标是领导独立的学术研究。 小组，专注于破译 PC 治疗耐药性的新型生物标志物和机制。 将为继续指导研究提供关键的受保护时间，并实现向独立的成功过渡。