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Investigation of metabolic features of glioblastoma tissue and the peritumoral environment using targeted metabolomics screening by LC-MS/MS and gene network analysis. / Basov, N. v.; Adamovskaya, A. v.; Rogachev, A. d. и др.

в: Вавиловский журнал генетики и селекции, Том 28, № 8, 2024, стр. 882-896.

Результаты исследований: Научные публикации в периодических изданиях › статья › Рецензирование

Harvard

Basov, NV, Adamovskaya, AV, Rogachev, AD, Gaisler, EV, Demenkov, PS, Ivanisenko, TV, Venzel, AS, Mishinov, SV, Stupak, VV, Cheresiz, SV, Oleshko, OS, Butikova, EA, Osechkova, AE, Sotnikova, YS, Patrushev, YV, Pozdnyakov, AS, Lavrik, IN, Ivanisenko, VA & Pokrovsky, AG 2024, 'Investigation of metabolic features of glioblastoma tissue and the peritumoral environment using targeted metabolomics screening by LC-MS/MS and gene network analysis', Вавиловский журнал генетики и селекции, Том. 28, № 8, стр. 882-896. https://doi.org/10.18699/vjgb-24-96

APA

Basov, N. V., Adamovskaya, A. V., Rogachev, A. D., Gaisler, E. V., Demenkov, P. S., Ivanisenko, T. V., Venzel, A. S., Mishinov, S. V., Stupak, V. V., Cheresiz, S. V., Oleshko, O. S., Butikova, E. A., Osechkova, A. E., Sotnikova, Y. S., Patrushev, Y. V., Pozdnyakov, A. S., Lavrik, I. N., Ivanisenko, V. A., & Pokrovsky, A. G. (2024). Investigation of metabolic features of glioblastoma tissue and the peritumoral environment using targeted metabolomics screening by LC-MS/MS and gene network analysis. Вавиловский журнал генетики и селекции, 28(8), 882-896. https://doi.org/10.18699/vjgb-24-96

Vancouver

Basov NV, Adamovskaya AV, Rogachev AD, Gaisler EV, Demenkov PS, Ivanisenko TV и др. Investigation of metabolic features of glioblastoma tissue and the peritumoral environment using targeted metabolomics screening by LC-MS/MS and gene network analysis. Вавиловский журнал генетики и селекции. 2024;28(8):882-896. doi: 10.18699/vjgb-24-96

Author

Basov, N. v. ; Adamovskaya, A. v. ; Rogachev, A. d. и др. / Investigation of metabolic features of glioblastoma tissue and the peritumoral environment using targeted metabolomics screening by LC-MS/MS and gene network analysis. в: Вавиловский журнал генетики и селекции. 2024 ; Том 28, № 8. стр. 882-896.

BibTeX

@article{10e074233b6547bab149c66bbcaabbdc,
title = "Investigation of metabolic features of glioblastoma tissue and the peritumoral environment using targeted metabolomics screening by LC-MS/MS and gene network analysis",
abstract = "The metabolomic profiles of glioblastoma and surrounding brain tissue, comprising 17 glioblastoma samples and 15 peritumoral tissue samples, were thoroughly analyzed in this investigation. The LC-MS/MS method was used to analyze over 400 metabolites, revealing significant variations in metabolite content between tumor and peritumoral tissues. Statistical analyses, including the Mann–Whitney and Cucconi tests, identified several metabolites, particularly ceramides, that showed significant differences between glioblastoma and peritumoral tissues. Pathway analysis using the KEGG database, conducted with MetaboAnalyst 6.0, revealed a statistically significant overrepresentation of sphingolipid metabolism, suggesting a critical role of these lipid molecules in glioblastoma pathogenesis. Using computational systems biology and artificial intelligence methods implemented in a cognitive platform, ANDSystem, molecular genetic regulatory pathways were reconstructed to describe potential mechanisms underlying the dysfunction of sphingolipid metabolism enzymes. These reconstructed pathways were integrated into a regulatory gene network comprising 15 genes, 329 proteins, and 389 interactions. Notably, 119 out of the 294 proteins regulating the key enzymes of sphingolipid metabolism were associated with glioblastoma. Analysis of the overrepresentation of Gene Ontology biological processes revealed the statistical significance of 184 processes, including apoptosis, the NF-kB signaling pathway, proliferation, migration, angiogenesis, and pyroptosis, many of which play an important role in oncogenesis. The findings of this study emphasize the pivotal role of sphingolipid metabolism in glioblastoma development and open new prospects for therapeutic approaches modulating this metabolism.",
author = "Basov, {N. v.} and Adamovskaya, {A. v.} and Rogachev, {A. d.} and Gaisler, {E. v.} and Demenkov, {P. s.} and Ivanisenko, {T. v.} and Venzel, {A. s.} and Mishinov, {S. v.} and Stupak, {V. v.} and Cheresiz, {S. v.} and Oleshko, {O. s.} and Butikova, {E. a.} and Osechkova, {A. e.} and Sotnikova, {Yu. s.} and Patrushev, {Y. v.} and Pozdnyakov, {A. s.} and Lavrik, {I. n.} and Ivanisenko, {V. a.} and Pokrovsky, {A. g.}",
note = "The production of monolithic columns for LC was made possible by the financial support of the FWUR-2024-0032 project. The selection and preparation of samples and their subsequent analysis by LC-MS/MS were supported by the funds of the state task No. FSUS-2020-0035. The bioinformatics analysis was funded by the budget project FWNR-2022-0020.",
year = "2024",
doi = "10.18699/vjgb-24-96",
language = "English",
volume = "28",
pages = "882--896",
journal = "Вавиловский журнал генетики и селекции",
issn = "2500-0462",
publisher = "Institute of Cytology and Genetics of Siberian Branch of the Russian Academy of Sciences",
number = "8",

}

RIS

TY - JOUR

T1 - Investigation of metabolic features of glioblastoma tissue and the peritumoral environment using targeted metabolomics screening by LC-MS/MS and gene network analysis

AU - Basov, N. v.

AU - Adamovskaya, A. v.

AU - Rogachev, A. d.

AU - Gaisler, E. v.

AU - Demenkov, P. s.

AU - Ivanisenko, T. v.

AU - Venzel, A. s.

AU - Mishinov, S. v.

AU - Stupak, V. v.

AU - Cheresiz, S. v.

AU - Oleshko, O. s.

AU - Butikova, E. a.

AU - Osechkova, A. e.

AU - Sotnikova, Yu. s.

AU - Patrushev, Y. v.

AU - Pozdnyakov, A. s.

AU - Lavrik, I. n.

AU - Ivanisenko, V. a.

AU - Pokrovsky, A. g.

N1 - The production of monolithic columns for LC was made possible by the financial support of the FWUR-2024-0032 project. The selection and preparation of samples and their subsequent analysis by LC-MS/MS were supported by the funds of the state task No. FSUS-2020-0035. The bioinformatics analysis was funded by the budget project FWNR-2022-0020.

PY - 2024

Y1 - 2024

N2 - The metabolomic profiles of glioblastoma and surrounding brain tissue, comprising 17 glioblastoma samples and 15 peritumoral tissue samples, were thoroughly analyzed in this investigation. The LC-MS/MS method was used to analyze over 400 metabolites, revealing significant variations in metabolite content between tumor and peritumoral tissues. Statistical analyses, including the Mann–Whitney and Cucconi tests, identified several metabolites, particularly ceramides, that showed significant differences between glioblastoma and peritumoral tissues. Pathway analysis using the KEGG database, conducted with MetaboAnalyst 6.0, revealed a statistically significant overrepresentation of sphingolipid metabolism, suggesting a critical role of these lipid molecules in glioblastoma pathogenesis. Using computational systems biology and artificial intelligence methods implemented in a cognitive platform, ANDSystem, molecular genetic regulatory pathways were reconstructed to describe potential mechanisms underlying the dysfunction of sphingolipid metabolism enzymes. These reconstructed pathways were integrated into a regulatory gene network comprising 15 genes, 329 proteins, and 389 interactions. Notably, 119 out of the 294 proteins regulating the key enzymes of sphingolipid metabolism were associated with glioblastoma. Analysis of the overrepresentation of Gene Ontology biological processes revealed the statistical significance of 184 processes, including apoptosis, the NF-kB signaling pathway, proliferation, migration, angiogenesis, and pyroptosis, many of which play an important role in oncogenesis. The findings of this study emphasize the pivotal role of sphingolipid metabolism in glioblastoma development and open new prospects for therapeutic approaches modulating this metabolism.

AB - The metabolomic profiles of glioblastoma and surrounding brain tissue, comprising 17 glioblastoma samples and 15 peritumoral tissue samples, were thoroughly analyzed in this investigation. The LC-MS/MS method was used to analyze over 400 metabolites, revealing significant variations in metabolite content between tumor and peritumoral tissues. Statistical analyses, including the Mann–Whitney and Cucconi tests, identified several metabolites, particularly ceramides, that showed significant differences between glioblastoma and peritumoral tissues. Pathway analysis using the KEGG database, conducted with MetaboAnalyst 6.0, revealed a statistically significant overrepresentation of sphingolipid metabolism, suggesting a critical role of these lipid molecules in glioblastoma pathogenesis. Using computational systems biology and artificial intelligence methods implemented in a cognitive platform, ANDSystem, molecular genetic regulatory pathways were reconstructed to describe potential mechanisms underlying the dysfunction of sphingolipid metabolism enzymes. These reconstructed pathways were integrated into a regulatory gene network comprising 15 genes, 329 proteins, and 389 interactions. Notably, 119 out of the 294 proteins regulating the key enzymes of sphingolipid metabolism were associated with glioblastoma. Analysis of the overrepresentation of Gene Ontology biological processes revealed the statistical significance of 184 processes, including apoptosis, the NF-kB signaling pathway, proliferation, migration, angiogenesis, and pyroptosis, many of which play an important role in oncogenesis. The findings of this study emphasize the pivotal role of sphingolipid metabolism in glioblastoma development and open new prospects for therapeutic approaches modulating this metabolism.

UR - https://www.scopus.com/record/display.uri?eid=2-s2.0-85217256182&origin=inward&txGid=d1f9d0d96c12354dbc550bbeec7dbd72

U2 - 10.18699/vjgb-24-96

DO - 10.18699/vjgb-24-96

M3 - Article

C2 - 39944803

VL - 28

SP - 882

EP - 896

JO - Вавиловский журнал генетики и селекции

JF - Вавиловский журнал генетики и селекции

SN - 2500-0462

IS - 8

ER -

ID: 64716249