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Project 3: Transcriptomic subtypes, response predictions, and therapy selection

项目 3：转录组亚型、反应预测和治疗选择

基本信息

批准号：
10845920
负责人：
Jen Jen Yeh
金额：
$ 1.51万
依托单位：
UNIV OF NORTH CAROLINA CHAPEL HILL
依托单位国家：
美国
项目类别：
财政年份：
2023
资助国家：
美国
起止时间：
2023-07-01 至 2026-06-30
项目状态：
未结题

来源：
https://reporter.nih.gov/project-details/10845920
关键词：
Aftercare Biological Assay Biopsy CLIA certified Cancerous Cells Cellularity Characteristics Classification Clinic Clinical Clinical Trials Coculture Techniques Computing Methodologies Consensus Data Data Set Desmoplastic Devices Ecosystem Effectiveness Epidermal Growth Factor Receptor Evaluation Fibroblasts Genes Immune Immunooncology Infrastructure KPC model Letters Libraries Light Malignant neoplasm of pancreas Malignant neoplasm of urinary bladder Mass Spectrum Analysis Methodology Methods Neoadjuvant Therapy Normal Cell North Carolina Organoids Outcome Paclitaxel Pancreatic Ductal Adenocarcinoma Patient Selection Patient-Focused Outcomes Patients Pharmacologic Substance Phosphotransferases Physicians Prediction of Response to Therapy Proteins Proteomics Regimen Resistance Risk Role Sampling Selection for Treatments Signal Transduction Therapeutic Treatment outcome Tumor Subtype Universities Validation Wisconsin alternative treatment chemotherapy clinical infrastructure cohort combinatorial differential expression gemcitabine improved outcome inhibitor innovation kinase inhibitor malignant breast neoplasm medical schools molecular subtypes nano-string novel novel strategies pancreatic cancer patients patient derived xenograft model patient subsets precision oncology predicting response programs prospective response therapy resistant transcriptomics treatment response tumor tumor microenvironment

项目摘要

PROJECT 3: ABSTRACT FOLFIRINOX and gemcitabine plus nab-paclitaxel (GnP) have emerged as the first-line treatment for patients with metastatic pancreatic cancer (PDAC). These two regimens have not been compared in the first-line setting, and treatment selection is guided by physician choice. Among patients with metastatic PDAC who do not respond to first-line FOLFIRINOX, a substantial proportion will have a robust response to second-line GnP. This strongly suggests that there may be a subset of patients who may have significant clinical response to GnP but not FOLFIRINOX. Matching patients to the most effective first-line therapy is a critical and unmet need. We have identified molecular subtypes of PDAC that are robust and replicable. Analysis from two clinical trials has shown that the basal subtype does not respond to FOLFIRINOX-based therapies and emphasizes the critical need to identify alternative treatments. Recent results have shown that patients with basal tumors are more responsive to GnP compared to FOLFIRINOX. Based on our findings of subtype associated treatment response, we developed a robust and replicable single-sample classifier (PurIST) that is now a CLIA-approved assay, and will be used this proposal to prospectively evaluate whether the PurIST classifier can be used to direct treatment selection. Leveraging the strength of molecular subtyping expertise at the University of North Carolina at Chapel Hill and the tremendous clinical infrastructure at the Medical College of Wisconsin’s Pancreatic Cancer Program, we propose a clinical trial where PurIST subtyping will be used to direct the initial chemotherapy. To our knowledge this will be the first trial to use molecular subtyping to direct treatment in the neoadjuvant setting. Results from this trial will demonstrate if precision oncology approaches such as PurIST may help direct treatment and improve outcome for patients that may otherwise be less responsive to either FOLFIRINOX or GnP. In parallel, we will determine if specific characteristics in the tumor and tumor microenvironment may predict response to different therapies through innovative computational approaches of cutting edge trials. Finally, through our novel proteomic approaches we have found that basal tumors have differential kinase profiles. We show that effectiveness of kinases inhibitors in PDAC may have been overlooked as ~20% of PDAC patients are basal, and that subtype-specific kinases may be promising targets.

项目三：摘要