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Grant Details

Grant Number: 5R01CA222146-05 Interpret this number
Primary Investigator: Poisson, Laila
Organization: Henry Ford Health System
Project Title: Molecular and Clinical Evaluation of the Glioma Patient Experience to Anticipate Modern Outcomes and Guide Patient Care
Fiscal Year: 2022


Project Summary Landmark papers published recently by us, and others, mark the new era of molecular diagnoses and precision therapy for glioma. In the summer of 2016, the World Health Organization (WHO) published updated diagnosis criteria for glioma that include molecular markers, taking a first step toward a molecularly precise diagnosis. It is our long-term goal to capitalize on the longitudinal resources of brain tumor banks to rapidly assess molecular hypotheses for prognosis and treatment of glioma. With the significant contribution of 240 cases from Henry Ford Hospital (HFH), an effort to molecularly and clinically profile glioma was started by The Cancer Genome Atlas (TCGA) project. Capitalizing on our clinically annotated brain tumor bank at HFH, we will focus on therapeutic outcomes, recurrent disease, and extended survival, which were not captured in the TCGA project. For this work, we have constructed an interdisciplinary team of collaborators, with clinical and informatics expertise, to profile an additional 340 glioma cases (WHO grade II-IV). In total, we will assess 700 tumor specimens (FFPE/frozen) from the HFH tumor bank (2001-present), representing both primary and matched progressive disease (Aim 1). Molecular data will be generated by exome sequencing to assess DNA sequence and copy number variants, targeted Sanger sequencing to profile the TERT promoter, and DNA methylation array assays to profile the methylome. Clinical annotation from our tumor bank, including long-term follow-up and therapy regimens, will be added to each of the 550 profiled glioma cases. The resulting comprehensively-annotated tumor bank will be an invaluable resource for queries of clinical-molecular associations and the progression of disease, made available to researchers at HFH and beyond. In this proposal we use our database to address two analytical aims: (Aim 2) to carefully design statistical models of prognosis and therapy response among modern diagnosis classes using retrospective records; (Aim 3) to identify genomic differences, per patient, arising over the course of treatment and progression, which we expect will impact therapy decisions and inform standard treatments strategies. As part of the third aim, we will also explore the genomic patterns and clinical response of patients with exceptional survival, which may indicate differential molecular diagnosis or suggest therapeutic avenues for extending survival in others.


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