Literature DB >> 23998518

Rapid diagnosis and prognosis of de novo acute myeloid leukemia by serum metabonomic analysis.

Yihuang Wang1, Limin Zhang, Wen-Lian Chen, Jing-Han Wang, Ning Li, Jun-Min Li, Jian-Qing Mi, Wei-Na Zhang, Yang Li, Song-Fang Wu, Jie Jin, Yun-Gui Wang, He Huang, Zhu Chen, Sai-Juan Chen, Huiru Tang.   

Abstract

Acute myeloid leukemia (AML) is a life-threatening hematological disease. Novel diagnostic and prognostic markers will be essential for new therapeutics and for significantly improving the disease prognosis. To characterize the metabolic features associated with AML and search for potential diagnostic and prognostic methods, here we analyzed the phenotypic characteristics of serum metabolite composition (metabonome) in a cohort of 183 patients with de novo acute myeloid leukemia together with 232 age- and gender-matched healthy controls using (1)H NMR spectroscopy in conjunction with multivariate data analysis. We observed significant serum metabonomic differences between AML patients and healthy controls and between AML patients with favorable and intermediate cytogenetic risks. Such differences were highlighted by systems differentiations in multiple metabolic pathways including glycolysis/gluconeogenesis, TCA cycle, biosynthesis of proteins and lipoproteins, and metabolism of fatty acids and cell membrane components, especially choline and its phosphorylated derivatives. This demonstrated the NMR-based metabonomics as a rapid and less invasive method for potential AML diagnosis and prognosis. The serum metabolic phenotypes observed here indicated that integration of metabonomics with other techniques will be useful for better understanding the biochemistry of pathogenesis and progression of leukemia.

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Year:  2013        PMID: 23998518     DOI: 10.1021/pr400403p

Source DB:  PubMed          Journal:  J Proteome Res        ISSN: 1535-3893            Impact factor:   4.466


  33 in total

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Journal:  Cell Mol Life Sci       Date:  2017-03-20       Impact factor: 9.261

2.  The differential activation of metabolic pathways in leukemic cells depending on their genotype and micro-environmental stress.

Authors:  Caroline Lo Presti; Florence Fauvelle; Julie Mondet; Pascal Mossuz
Journal:  Metabolomics       Date:  2020-01-10       Impact factor: 4.290

3.  The metabolic reprogramming in acute myeloid leukemia patients depends on their genotype and is a prognostic marker.

Authors:  Caroline Lo Presti; Florence Fauvelle; Marie-Christine Jacob; Julie Mondet; Pascal Mossuz
Journal:  Blood Adv       Date:  2021-01-12

4.  Control of hepatic gluconeogenesis by the promyelocytic leukemia zinc finger protein.

Authors:  Siyu Chen; Jinchun Qian; Xiaoli Shi; Tingting Gao; Tingming Liang; Chang Liu
Journal:  Mol Endocrinol       Date:  2014-12

5.  Synergistic cell death in FLT3-ITD positive acute myeloid leukemia by combined treatment with metformin and 6-benzylthioinosine.

Authors:  Himalee S Sabnis; Heath L Bradley; Shweta Tripathi; Wen-Mei Yu; William Tse; Cheng-Kui Qu; Kevin D Bunting
Journal:  Leuk Res       Date:  2016-10-05       Impact factor: 3.156

6.  Metabolomics of neonatal blood spots reveal distinct phenotypes of pediatric acute lymphoblastic leukemia and potential effects of early-life nutrition.

Authors:  Lauren M Petrick; Courtney Schiffman; William M B Edmands; Yukiko Yano; Kelsi Perttula; Todd Whitehead; Catherine Metayer; Craig E Wheelock; Manish Arora; Hasmik Grigoryan; Henrik Carlsson; Sandrine Dudoit; Stephen M Rappaport
Journal:  Cancer Lett       Date:  2019-03-20       Impact factor: 8.679

7.  Increase in serum choline levels predicts for improved progression-free survival (PFS) in patients with advanced cancers receiving pembrolizumab.

Authors:  Geoffrey Alan Watson; Enrique Sanz-Garcia; Lillian L Siu; Eric Chen; Wen-Jiang Zhang; Zhihui Amy Liu; Sy Cindy Yang; Ben Wang; Shaofeng Liu; Shawn Kubli; Hal Berman; Thomas Pfister; Sofia Genta; Anna Spreafico; Aaron R Hansen; Philippe L Bedard; Stephanie Lheureux; Albiruni Abdul Razak; Dave Cescon; Marcus O Butler; Wei Xu; Tak W Mak
Journal:  J Immunother Cancer       Date:  2022-06       Impact factor: 12.469

8.  Serum Metabolomics Coupling With Clinical Laboratory Indicators Reveal Taxonomic Features of Leukemia.

Authors:  Hao- Xiong; Hui-Tao Zhang; Hong-Wen Xiao; Chun-Lan Huang; Mei-Zhou Huang
Journal:  Front Pharmacol       Date:  2022-05-26       Impact factor: 5.988

9.  Reactive Oxygen Species Drive Proliferation in Acute Myeloid Leukemia via the Glycolytic Regulator PFKFB3.

Authors:  Andrew J Robinson; Goitseone L Hopkins; Namrata Rastogi; Marie Hodges; Michelle Doyle; Sara Davies; Paul S Hole; Nader Omidvar; Richard L Darley; Alex Tonks
Journal:  Cancer Res       Date:  2019-12-20       Impact factor: 12.701

10.  Cellular Metabolomics Profiles Associated With Drug Chemosensitivity in AML.

Authors:  Bradley Stockard; Neha Bhise; Miyoung Shin; Joy Guingab-Cagmat; Timothy J Garrett; Stanley Pounds; Jatinder K Lamba
Journal:  Front Oncol       Date:  2021-06-10       Impact factor: 6.244

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