Doxorubicin, a mainstay in Breast and other types of cancer therapy is a wide-spectrum chemotherapeutic agent of the anthracycline class that is associated with cardiotoxicity, hepatic lesions and a number of other side effects. Despite the wide use of Doxorubicin, little research has been done on the metabolomic pathways that it influences. The aim of this study was to analyse the overall metabolite changes in MDA-MB-231 cells in response to Doxorubicin treatment and to identify the impacted metabolomic pathways. A metabolomics analysis of MDA-MB231 cells at 200nM and 1μM Doxorubicin concentrations using UHPLC/MS tandem mass spectrometry `was performed to achieve this goal. The analysis revealed that the change in metabolite abundance was dependent on the dose of Doxorubicin used. However, the relationship between dose and metabolite change was non-linear, the most probable cause for this is treatment emerging resistance. Amino acid metabolism was significantly affected; fatty acid and polyamine metabolism was affected to a lesser extent. Pathway analysis using MetaboAnalyst 5.0 revealed that phenylalanine, tyrosine and tryptophan biosynthesis was the most impacted. The citrate cycle (TCA) and nictotinate/nictotinamide metabolism were affected to lesser degrees. Moreover, the recent advancements in electronic databases and freely available online bioinformatics tools was utilised to conduct a bioinformatics analysis of KPNA2 expression and prognostic value in breast cancer as well as its correlation with the expression of other genes. Data from bcgenex miner demonstrated that KPNA2 mRNA expression was upregulated in hormone receptor negative and HER2+ breast cancers. KMplots revealed that KPNA2 expression is associated with poor prognostic outcome; HER2+ breast cancer demonstrated the worst prognosis in correlation with KPNA2 expression. Furthermore, STRING database revealed a number of KPNA2 functional partners including TPX2 and RCC1 which might offer a more thorough understanding of nuclear transport as well as being novel drug targets for breast cancer therapy.
Doxorubicin, a mainstay in Breast and other types of cancer therapy is a wide-spectrum chemotherapeutic agent of the anthracycline class that is associated with cardiotoxicity, hepatic lesions and a number of other side effects. Despite the wide use of Doxorubicin, little research has been done on the metabolomic pathways that it influences. The aim of this study was to analyse the overall metabolite changes in MDA-MB-231 cells in response to Doxorubicin treatment and to identify the impacted metabolomic pathways. A metabolomics analysis of MDA-MB231 cells at 200nM and 1μM Doxorubicin concentrations using UHPLC/MS tandem mass spectrometry `was performed to achieve this goal. The analysis revealed that the change in metabolite abundance was dependent on the dose of Doxorubicin used. However, the relationship between dose and metabolite change was non-linear, the most probable cause for this is treatment emerging resistance. Amino acid metabolism was significantly affected; fatty acid and polyamine metabolism was affected to a lesser extent. Pathway analysis using MetaboAnalyst 5.0 revealed that phenylalanine, tyrosine and tryptophan biosynthesis was the most impacted. The citrate cycle (TCA) and nictotinate/nictotinamide metabolism were affected to lesser degrees. Moreover, the recent advancements in electronic databases and freely available online bioinformatics tools was utilised to conduct a bioinformatics analysis of KPNA2 expression and prognostic value in breast cancer as well as its correlation with the expression of other genes. Data from bcgenex miner demonstrated that KPNA2 mRNA expression was upregulated in hormone receptor negative and HER2+ breast cancers. KMplots revealed that KPNA2 expression is associated with poor prognostic outcome; HER2+ breast cancer demonstrated the worst prognosis in correlation with KPNA2 expression. Furthermore, STRING database revealed a number of KPNA2 functional partners including TPX2 and RCC1 which might offer a more thorough understanding of nuclear transport as well as being novel drug targets for breast cancer therapy.
Metabolomic analysis of doxorubicin treated breast cancer cells using MS/MS tandem spectrometry
GAAFAR, AHMED MAMDOUH MOUSTAFA KAMAL
2021/2022
Abstract
Doxorubicin, a mainstay in Breast and other types of cancer therapy is a wide-spectrum chemotherapeutic agent of the anthracycline class that is associated with cardiotoxicity, hepatic lesions and a number of other side effects. Despite the wide use of Doxorubicin, little research has been done on the metabolomic pathways that it influences. The aim of this study was to analyse the overall metabolite changes in MDA-MB-231 cells in response to Doxorubicin treatment and to identify the impacted metabolomic pathways. A metabolomics analysis of MDA-MB231 cells at 200nM and 1μM Doxorubicin concentrations using UHPLC/MS tandem mass spectrometry `was performed to achieve this goal. The analysis revealed that the change in metabolite abundance was dependent on the dose of Doxorubicin used. However, the relationship between dose and metabolite change was non-linear, the most probable cause for this is treatment emerging resistance. Amino acid metabolism was significantly affected; fatty acid and polyamine metabolism was affected to a lesser extent. Pathway analysis using MetaboAnalyst 5.0 revealed that phenylalanine, tyrosine and tryptophan biosynthesis was the most impacted. The citrate cycle (TCA) and nictotinate/nictotinamide metabolism were affected to lesser degrees. Moreover, the recent advancements in electronic databases and freely available online bioinformatics tools was utilised to conduct a bioinformatics analysis of KPNA2 expression and prognostic value in breast cancer as well as its correlation with the expression of other genes. Data from bcgenex miner demonstrated that KPNA2 mRNA expression was upregulated in hormone receptor negative and HER2+ breast cancers. KMplots revealed that KPNA2 expression is associated with poor prognostic outcome; HER2+ breast cancer demonstrated the worst prognosis in correlation with KPNA2 expression. Furthermore, STRING database revealed a number of KPNA2 functional partners including TPX2 and RCC1 which might offer a more thorough understanding of nuclear transport as well as being novel drug targets for breast cancer therapy.File | Dimensione | Formato | |
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https://hdl.handle.net/20.500.12608/10168