A proteomic clock for malignant gliomas: The role of the environment in tumorigenesis at the presymptomatic stage
Autoři:
Le Zheng aff001; Yan Zhang aff003; Shiying Hao aff001; Lin Chen aff004; Zhen Sun aff004; Chi Yan aff004; John C. Whitin aff005; Taichang Jang aff006; Milton Merchant aff006; Doff B. McElhinney aff001; Karl G. Sylvester aff004; Harvey J. Cohen aff005; Lawrence Recht aff006; Xiaoming Yao aff002; Xuefeng B. Ling aff002
Působiště autorů:
Department of Cardiothoracic Surgery, Stanford University, Stanford, California, United States of America
aff001; Clinical and Translational Research Program, Betty Irene Moore Children's Heart Center, Lucile Packard Children’s Hospital, Palo Alto, California, United States of America
aff002; Department of Oncology, the First Hospital of Shijiazhuang, Shijiazhuang, Hebei, China
aff003; Department of Surgery, Stanford University School of Medicine, Stanford, California, United States of America
aff004; Department of Pediatrics, Stanford University School of Medicine, Stanford, California, United States of America
aff005; Department of Neurology and Neurological Science, Stanford University School of Medicine, Stanford, California, United States of America
aff006
Vyšlo v časopise:
PLoS ONE 14(10)
Kategorie:
Research Article
doi:
https://doi.org/10.1371/journal.pone.0223558
Souhrn
Malignant gliomas remain incurable with a poor prognosis despite of aggressive treatment. We have been studying the development of brain tumors in a glioma rat model, where rats develop brain tumors after prenatal exposure to ethylnitrosourea (ENU), and there is a sizable interval between when the first pathological changes are noted and tumors become detectable with MRI. Our aim to define a molecular timeline through proteomic profiling of the cerebrospinal fluid (CSF) such that brain tumor commitment can be revealed earlier than at the presymptomatic stage. A comparative proteomic approach was applied to profile CSF collected serially either before, at and after the time MRI becomes positive. Elastic net (EN) based models were developed to infer the timeline of normal or tumor development respectively, mirroring a chronology of precisely timed, “clocked”, adaptations. These CSF changes were later quantified by longitudinal entropy analyses of the EN predictive metric. False discovery rates (FDR) were computed to control the expected proportion of the EN models that are due to multiple hypothesis testing. Our ENU rat brain tumor dating EN model indicated that protein content in CSF is programmed even before tumor MRI detection. The findings of the precisely timed CSF tumor microenvironment changes at presymptomatic stages, deviation from the normal development timeline, may provide the groundwork for the understanding of adaptation of the brain environment in tumorigenesis to devise effective brain tumor management strategies.
Klíčová slova:
Carcinogenesis – Cerebrospinal fluid – Cytopathology – Entropy – Glioma – Magnetic resonance imaging – Proteomes – Proteomics
Zdroje
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Článek vyšel v časopise
PLOS One
2019 Číslo 10
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