Literature DB >> 34973010

Systems Approaches in the Common Metabolomics in Acute Lymphoblastic Leukemia and Rhabdomyosarcoma Cells: A Computational Approach.

Tselios C1, Apostolos Zaravinos2, Athanasios N Tsartsalis3, Anna Tagka4, Athanasios Kotoulas5, Styliani A Geronikolou6, Maria Braoudaki7, George I Lambrou8.   

Abstract

Acute lymphoblastic leukemia is the most common childhood malignancy. Rhabdomyosarcoma, on the other hand, is a rare type of malignancy which belongs to the primitive neuroectodermal family of tumors. The aim of the present study was to use computational methods in order to examine the similarities and differences of the two different tumors using two cell lines as a model, the T-cell acute lymphoblastic leukemia CCRF-CEM and rhabdomyosarcoma TE-671, and, in particular, similarities of the metabolic pathways utilized by two different cell types in vitro. Both cell lines were studied using microarray technology. Differential expression profile has revealed genes with similar expression, suggesting that there are common mechanisms between the two cell types, where some of these mechanisms are preserved from their ancestor embryonic cells. Expression of identified species was modeled using known functions, in order to find common patterns in metabolism-related mechanisms. Species expression manifested very interesting dynamics, and we were able to model the system with elliptical/helical functions. We discuss the results of our analysis in the context of the commonly occurring genes between the two cell lines and the respective participating pathways as far as extracellular signaling and cell cycle regulation/proliferation are concerned. In the present study, we have developed a methodology, which was able to unravel some of the underlying dynamics of the metabolism-related species of two different cell types. Such approaches could prove useful in understanding the mechanisms of tumor ontogenesis, progression, and proliferation.
© 2021. The Author(s), under exclusive license to Springer Nature Switzerland AG.

Entities:  

Keywords:  CCRF-CEM; Leukemia; Metabolomics; Microarrays; Rhabdomyosarcoma; TE_671

Mesh:

Year:  2021        PMID: 34973010     DOI: 10.1007/978-3-030-78775-2_8

Source DB:  PubMed          Journal:  Adv Exp Med Biol        ISSN: 0065-2598            Impact factor:   2.622


  13 in total

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  1 in total

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