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.




The Epigenetic Evolution of Glioma Is Determined by the IDH1 Mutation Status and Treatment Regimen.
Authors: Malta T.M. , Sabedot T.S. , Morosini N.S. , Datta I. , Garofano L. , Vallentgoed W. , Varn F.S. , Aldape K. , D'Angelo F. , Bakas S. , et al. .
Source: Cancer Research, 2024-03-04 00:00:00.0; 84(5), p. 741-756.
PMID: 38117484
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Glioma progression is shaped by genetic evolution and microenvironment interactions.
Authors: Varn F.S. , Johnson K.C. , Martinek J. , Huse J.T. , Nasrallah M.P. , Wesseling P. , Cooper L.A.D. , Malta T.M. , Wade T.E. , Sabedot T.S. , et al. .
Source: Cell, 2022-06-09 00:00:00.0; 185(12), p. 2184-2199.e16.
EPub date: 2022-05-31 00:00:00.0.
PMID: 35649412
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Expression and regulatory roles of lncRNAs in G-CIMP-low vs G-CIMP-high Glioma: an in-silico analysis.
Authors: Datta I. , Noushmehr H. , Brodie C. , Poisson L.M. .
Source: Journal Of Translational Medicine, 2021-04-29 00:00:00.0; 19(1), p. 182.
EPub date: 2021-04-29 00:00:00.0.
PMID: 33926464
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DNA Methylation-based Signatures Classify Sporadic Pituitary Tumors According to Clinicopathological Features.
Authors: Mosella M.S. , Sabedot T.S. , Silva T.C. , Malta T.M. , Segato F.D. , Asmaro K.P. , Wells M. , Mukherjee A. , Poisson L.M. , Snyder J. , et al. .
Source: Neuro-oncology, 2021-02-25 00:00:00.0; , .
EPub date: 2021-02-25 00:00:00.0.
PMID: 33631002
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A serum-based DNA methylation assay provides accurate detection of glioma.
Authors: Sabedot T. , Malta T. , Snyder J. , Nelson K. , Wells M. , deCarvalho A. , Mukherjee A. , Chitale D. , Mosella M. , Sokolov A. , et al. .
Source: Neuro-oncology, 2021-02-09 00:00:00.0; , .
EPub date: 2021-02-09 00:00:00.0.
PMID: 33560371
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iGLASS: imaging integration into the Glioma Longitudinal Analysis Consortium.
Authors: Bakas S. , Ormond D.R. , Alfaro-Munoz K.D. , Smits M. , Cooper L.A.D. , Verhaak R. , Poisson L.M. .
Source: Neuro-oncology, 2020-10-14 00:00:00.0; 22(10), p. 1545-1546.
PMID: 32644158
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Prognostic Value of Preoperative MRI Metrics for Diffuse Lower-Grade Glioma Molecular Subtypes.
Authors: Darvishi P. , Batchala P.P. , Patrie J.T. , Poisson L.M. , Lopes M.B. , Jain R. , Fadul C.E. , Schiff D. , Patel S.H. .
Source: Ajnr. American Journal Of Neuroradiology, 2020 05; 41(5), p. 815-821.
EPub date: 2020-04-23 00:00:00.0.
PMID: 32327434
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Developing Real-world Evidence-Ready Datasets: Time for Clinician Engagement.
Authors: Snyder J.M. , Pawloski J.A. , Poisson L.M. .
Source: Current Oncology Reports, 2020-04-16 00:00:00.0; 22(5), p. 45.
EPub date: 2020-04-16 00:00:00.0.
PMID: 32297007
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Longitudinal molecular trajectories of diffuse glioma in adults.
Authors: Barthel F.P. , Johnson K.C. , Varn F.S. , Moskalik A.D. , Tanner G. , Kocakavuk E. , Anderson K.J. , Abiola O. , Aldape K. , Alfaro K.D. , et al. .
Source: Nature, 2019 12; 576(7785), p. 112-120.
EPub date: 2019-11-20 00:00:00.0.
PMID: 31748746
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Identification of subsets of IDH-mutant glioblastomas with distinct epigenetic and copy number alterations and stratified clinical risks.
Authors: Li K.K. , Shi Z.F. , Malta T.M. , Chan A.K. , Cheng S. , Kwan J.S.H. , Yang R.R. , Poon W.S. , Mao Y. , Noushmehr H. , et al. .
Source: Neuro-oncology Advances, 2019 May-Dec; 1(1), p. vdz015.
EPub date: 2019-07-17 00:00:00.0.
PMID: 31667475
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Clinical and research applications of a brain tumor tissue bank in the age of precision medicine.
Authors: Snyder J. , Poisson L.M. , Noushmehr H. , Castro A.V. , deCarvalho A.C. , Robin A. , Mukherjee A. , Lee I. , Walbert T. .
Source: Personalized Medicine, 2019 03; 16(2), p. 145-156.
EPub date: 2019-02-28 00:00:00.0.
PMID: 30816054
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