Fatty acid metabolism and cancer development

Chen, Yuanying; Li, Peng

doi:10.1007/s11434-016-1129-4

Cited by 37 publications

(38 citation statements)

References 76 publications

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“…Genetic alterations in cell metabolism may contribute to poor prognosis in human cancers ( 42 ). Lipid metabolism is now considered to have a key role in cancer progression; it has been proposed that increased metabolic flux may serve as substrate source for phospholipid synthesis in the rapid growth stages of cancer ( 43 ).…”

Section: Discussionmentioning

confidence: 99%

Potential candidate treatment agents for targeting of cholangiocarcinoma identified by gene expression profile analysis

et al. 2018

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Cholangiocarcinoma (CCA) remains to be a major health problem in several Asian countries including Thailand. The molecular mechanism of CCA is poorly understood. Early diagnosis is difficult, and at present, no effective therapeutic drug is available. The present study aimed to identify the molecular mechanism of CCA by gene expression profile analysis and to search for current approved drugs which may interact with the upregulated genes in CCA. Gene Expression Omnibus (GEO) was used to analyze the gene expression profiles of CCA patients and normal subjects. Using the Kyoto Encyclopedia of Genes and Genomes (KEGG), gene ontology enrichment analysis was also performed, with the KEGG pathway analysis indicating that pancreatic secretion, protein digestion and absorption, fat digestion and absorption, and glycerolipid metabolism may serve important roles in CCA oncogenesis. The drug signature database (DsigDB) was used to search for US Food and Drug Administration (FDA)-approved drugs potentially capable of reversing the effects of the upregulated gene expression in CCA. A total of 61 antineoplastic and 86 non-antineoplastic drugs were identified. Checkpoint kinase 1 was the most interacting with drug signatures. Many of the targeted protein inhibitors that were identified have been approved by the US-FDA as therapeutic agents for non-antineoplastic diseases, including cimetidine, valproic acid and lovastatin. The current study demonstrated an application for bioinformatics analysis in assessing the potential efficacy of currently approved drugs for novel use. The present results suggest novel indications regarding existing drugs useful for CCA treatment. However, further in vitro and in vivo studies are required to support the current predictions.

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Section: Discussionmentioning

confidence: 99%

Potential candidate treatment agents for targeting of cholangiocarcinoma identified by gene expression profile analysis

et al. 2018

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“…Lipid metabolism has an important role in cancer progression. It has been proposed that increased lipid metabolic flux may serve as the substrate source for phospholipid synthesis in the rapid growth stage of cancer cells ( 27 ). Notably, fatty acid synthase was demonstrated to be necessary during the proliferation of human OSCCs ( 28 ).…”

Section: Discussionmentioning

confidence: 99%

Twenty‑four signature genes predict the prognosis of oral squamous cell carcinoma with high accuracy and repeatability

et al. 2017

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Oral squamous cell carcinoma (OSCC) is the sixth most common type cancer worldwide, with poor prognosis. The present study aimed to identify gene signatures that could classify OSCC and predict prognosis in different stages. A training data set (GSE41613) and two validation data sets (GSE42743 and GSE26549) were acquired from the online Gene Expression Omnibus database. In the training data set, patients were classified based on the tumor-node-metastasis staging system, and subsequently grouped into low stage (L) or high stage (H). Signature genes between L and H stages were selected by disparity index analysis, and classification was performed by the expression of these signature genes. The established classification was compared with the L and H classification, and fivefold cross validation was used to evaluate the stability. Enrichment analysis for the signature genes was implemented by the Database for Annotation, Visualization and Integration Discovery. Two validation data sets were used to determine the precise of classification. Survival analysis was conducted followed each classification using the package ‘survival’ in R software. A set of 24 signature genes was identified based on the classification model with the Fi value of 0.47, which was used to distinguish OSCC samples in two different stages. Overall survival of patients in the H stage was higher than those in the L stage. Signature genes were primarily enriched in ‘ether lipid metabolism’ pathway and biological processes such as ‘positive regulation of adaptive immune response’ and ‘apoptotic cell clearance’. The results provided a novel 24-gene set that may be used as biomarkers to predict OSCC prognosis with high accuracy, which may be used to determine an appropriate treatment program for patients with OSCC in addition to the traditional evaluation index.

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“…Most metabolized cellular FA are either synthesized into neural triglycerides (TAG) for energy storage within LDs or into phospholipids for cell/organelle membrane growth or maintenance. The cellular requirements determine which metabolic pathway is activated (Chen & Li, 2016). During energy surplus FAs are converted into storage fats.…”

Section: Lipid Metabolism and Pcamentioning

confidence: 99%

“…If cellular energy demands are not being met FAs breakdown via ketogenesis as required (Foster & McGarry 1982). If rapid cell growth is ongoing, FA are synthesised into new phospholipid membranes and this process transpires primarily in smooth ER (Chen & Li, 2016). Phospholipid synthesis is either de novo by the Kennedy Pathway or through lipid modification via the Lands Cycle (Pol, Gross, & Parton, 2014;Appendix Figure 1).…”

Section: Lipid Metabolism and Pcamentioning

confidence: 99%

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Identification of response pathways of prostate cancer cell lines in Hans Clevers Media

Hutchinson¹

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Fatty acid metabolism and cancer development

Cited by 37 publications

References 76 publications

Potential candidate treatment agents for targeting of cholangiocarcinoma identified by gene expression profile analysis

Potential candidate treatment agents for targeting of cholangiocarcinoma identified by gene expression profile analysis

Twenty‑four signature genes predict the prognosis of oral squamous cell carcinoma with high accuracy and repeatability

Identification of response pathways of prostate cancer cell lines in Hans Clevers Media

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