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Grant Details

Grant Number: 5U01CA235510-04 Interpret this number
Primary Investigator: Weinstein, John
Organization: University Of Tx Md Anderson Can Ctr
Project Title: Computational Tools for Analysis and Visualization of Quality Control Issues in Metabolomic Data
Fiscal Year: 2021


Abstract

* * * Abstract * * * In omic studies of all types (e.g., genomic, transcriptomic, proteomic, metabolomic), technical batch effects pose a fundamental challenge to quality control and reproducibility. The possibilities for serious error are greatly magnified in metabolomics, however, due to a range of possible platform, operator, instrument, and environmental factors that can cause batch (or trend) effects. Hence, there is a need for routine surveillance and correction of batch effects within and across metabolomics laboratories and technological platforms. Accordingly, we propose here to develop the MetaBatch algorithms, computational tool, and web portal. For development of MetaBatch, we will leverage our experience in developing MBatch, a tool that became indispensible for quality-control of data in all 33 projects of The Cancer Genome Atlas (TCGA) program. Our first aim is to translate the successful quality control model from TCGA to metabolomics by customizing and extending the MBatch pipeline for detection, quantitation, diagnosis, interpretation, and correction of batch and trend effects. The second aim is to develop and incorporate innovative metabolomics-specific algorithms, including major visualization resources such as our interactive Next-Generation Clustered Heat Maps. The third aim is to distribute MetaBatch to the research community as open-source software and in cloud-based and Galaxy versions. The fourth aim is to provide plug-in capability for integration of MetaBatch with other metabolomic resources, prominently including Metabolomics Workbench (in collaboration with Dr. Shankar Subramaniam) and others developed within the Common Fund Metabolomics Program. Our fifth aim is to promote MetaBatch actively and interact extensively with other Consortium members and the metabolomics research community. With active support from MD Anderson Faculty and Academic Development, we will provide documentation, tutorials, videos, demonstrations, and training to accelerate use and to solicit feedback on limitations, possible improvements, and additional modules that would be useful in real-world workflows. We bring a variety of assets to the project, including: the MBatch resource as a starting point for software development; multidisciplinary expertise in bioinformatics, biostatistics, software engineering, biology, and clinical medicine; PIs with a combined 21 years of experience in molecular profiling studies of clinical disease (in a consortial context); international leadership in batch effects analysis; a software engineering team with a track record of producing high-end, highly visual bioinformatics packages and websites; a team of 20 Analysts whose expertise can be called on; extensive computing resources, including one of the most powerful academically based machines in the world; strong institutional support; and close working relationships with first-class basic, translational, and clinical researchers throughout MD Anderson, one of the foremost cancer centers in the country. Our bottom-line mission will be to aid the research community's effort to improve rigor and reproducibility in metabolomics for scientific understanding and to alleviate disease. !



Publications

Targeting MYC-enhanced glycolysis for the treatment of small cell lung cancer.
Authors: Cargill K.R. , Stewart C.A. , Park E.M. , Ramkumar K. , Gay C.M. , Cardnell R.J. , Wang Q. , Diao L. , Shen L. , Fan Y.H. , et al. .
Source: Cancer & metabolism, 2021-09-23; 9(1), p. 33.
EPub date: 2021-09-23.
PMID: 34556188
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Compound NSC84167 selectively targets NRF2-activated pancreatic cancer by inhibiting asparagine synthesis pathway.
Authors: Dai B. , Augustine J.J. , Kang Y. , Roife D. , Li X. , Deng J. , Tan L. , Rusling L.A. , Weinstein J.N. , Lorenzi P.L. , et al. .
Source: Cell death & disease, 2021-07-10; 12(7), p. 693.
EPub date: 2021-07-10.
PMID: 34247201
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Development of a rational strategy for integration of lactate dehydrogenase A suppression into therapeutic algorithms for head and neck cancer.
Authors: Chen Y. , Maniakas A. , Tan L. , Cui M. , Le X. , Niedzielski J.S. , Michel K.A. , Harlan C.J. , Lu W. , Henderson Y.C. , et al. .
Source: British journal of cancer, 2021 May; 124(10), p. 1670-1679.
EPub date: 2021-03-19.
PMID: 33742144
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The Glutaminase Inhibitor CB-839 (Telaglenastat) Enhances the Antimelanoma Activity of T-Cell-Mediated Immunotherapies.
Authors: Varghese S. , Pramanik S. , Williams L.J. , Hodges H.R. , Hudgens C.W. , Fischer G.M. , Luo C.K. , Knighton B. , Tan L. , Lorenzi P.L. , et al. .
Source: Molecular cancer therapeutics, 2021 03; 20(3), p. 500-511.
EPub date: 2020-12-23.
PMID: 33361272
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A role for neuroimmune signaling in a rat model of Gulf War Illness-related pain.
Authors: Lacagnina M.J. , Li J. , Lorca S. , Rice K.C. , Sullivan K. , O'Callaghan J.P. , Grace P.M. .
Source: Brain, behavior, and immunity, 2021 01; 91, p. 418-428.
EPub date: 2020-10-27.
PMID: 33127584
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Bexarotene normalizes chemotherapy-induced myelin decompaction and reverses cognitive and sensorimotor deficits in mice.
Authors: Chiang A.C.A. , Seua A.V. , Singhmar P. , Arroyo L.D. , Mahalingam R. , Hu J. , Kavelaars A. , Heijnen C.J. .
Source: Acta neuropathologica communications, 2020-11-12; 8(1), p. 193.
EPub date: 2020-11-12.
PMID: 33183353
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Epigenetic Reprogramming of Cancer-Associated Fibroblasts Deregulates Glucose Metabolism and Facilitates Progression of Breast Cancer.
Authors: Becker L.M. , O'Connell J.T. , Vo A.P. , Cain M.P. , Tampe D. , Bizarro L. , Sugimoto H. , McGow A.K. , Asara J.M. , Lovisa S. , et al. .
Source: Cell reports, 2020-06-02; 31(9), p. 107701.
PMID: 32492417
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Mass spectrometry-based stable-isotope tracing uncovers metabolic alterations in pyruvate kinase-deficient Aedes aegypti mosquitoes.
Authors: Petchampai N. , Isoe J. , Horvath T.D. , Dagan S. , Tan L. , Lorenzi P.L. , Hawke D.H. , Scaraffia P.Y. .
Source: Insect biochemistry and molecular biology, 2020 06; 121, p. 103366.
EPub date: 2020-04-07.
PMID: 32276114
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SAMMI: a semi-automated tool for the visualization of metabolic networks.
Authors: Schultz A. , Akbani R. .
Source: Bioinformatics (Oxford, England), 2020-04-15; 36(8), p. 2616-2617.
PMID: 31851289
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Glutaminase Activity of L-Asparaginase Contributes to Durable Preclinical Activity against Acute Lymphoblastic Leukemia.
Authors: Chan W.K. , Horvath T.D. , Tan L. , Link T. , Harutyunyan K.G. , Pontikos M.A. , Anishkin A. , Du D. , Martin L.A. , Yin E. , et al. .
Source: Molecular cancer therapeutics, 2019 09; 18(9), p. 1587-1592.
EPub date: 2019-06-17.
PMID: 31209181
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