CREB1 directly activates the transcription of ribonucleotide reductase small subunit M2 and promotes the aggressiveness of human colorectal cancer

Fang, Zejun; Lin, Aifen; Chen, Jiaoe; Zhang, Xiaomin; Liu, Hong; Li, Hongzhang; Hu, Yifei; Zhang, Xia; Zhang, Jian Gang; Qiu, Lanlan; Mei, Lingming; Shao, Jimin; Chen, Xiang

doi:10.18632/oncotarget.12938

Cited by 24 publications

(18 citation statements)

References 43 publications

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“…RRM2 is important in controlling cellular function in a number of human malignant tumors, including DNA repair, cell proliferation and senescence. Importantly, RRM2 functions as a driver in a variety of tumors, with in vivo and in vitro experiments confirming that knocking down expression using siRNA significantly inhibits tumor cell proliferation (Fang et al, 2016).…”

Section: Discussionmentioning

confidence: 94%

Co-expression Network Analysis Identifies Four Hub Genes Associated With Prognosis in Soft Tissue Sarcoma

et al. 2019

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Background: Soft tissue sarcomas (STS) are heterogeneous tumors derived from mesenchymal cells that differentiate into soft tissues. The prognosis of patients who present with an STS is influenced by the regulation of a complex gene network.Methods: Weighted gene co-expression network analysis (WGCNA) was performed to identify gene modules associated with STS (Samples = 156).Results: Among the 11 modules identified, the black and blue modules were highly correlated with STS. However, using preservation analysis, the black module demonstrated low preservation, therefore the blue module was chosen as the module of interest. Furthermore, a total of 20 network hub genes were identified in the blue module, 12 of which were also hub nodes in the protein-protein interaction network of the module genes. Following additional verification, 4 of 12 genes (RRM2, BUB1B, CENPF, and KIF20A) demonstrated poorer overall survival and disease-free survival rate in the test datasets. In addition, gene set enrichment analysis (GSEA) demonstrated that samples with a high level of blue module eigengene (ME) were enriched in cell cycle and metabolism associated signaling pathways.Conclusion: In summary, co-expression network analysis identified four hub genes associated with prognosis for STS, which may diminish the prognosis by influencing cell cycle and metabolism associated signaling pathways.

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Section: Discussionmentioning

confidence: 94%

Co-expression Network Analysis Identifies Four Hub Genes Associated With Prognosis in Soft Tissue Sarcoma

et al. 2019

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“…Regulation of RRM1 mRNA has been reported to depend on the cell cycle and the transcription factors, NF‐Y and THAP1, 36,37 and RRM1 encodes a protein with a long half‐life. RRM2 transcription is regulated by the transcription factors E2F1, NF‐Y, and CreB1 38,39 . DNA damage by N‐methyl‐N′‐nitro‐N‐nitrosoguanidine treatment has been found to activate the ATR‐CHK2‐E2F3 cascade 40 .…”

Section: Discussionmentioning

confidence: 99%

Combination of hydroxyurea and tranilast suppresses gemcitabine resistance induced by ribonucleotide reductase M1 in gemcitabine‐resistant cells

Shinagawa

Minami

Ishida

et al. 2020

Oral Science International

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Introduction Gemcitabine (GEM; 2′,2′‐difluorodeoxycytidine) is widely used to treat pancreatic, biliary tract, non‐small cell lung, bladder, mammary, and ovarian cancers. Chemoradiotherapy with GEM is a promising treatment for patients with advanced and locally recurrent head and neck cancers, including those with oral cavity cancer. However, the development of GEM resistance limits its use for curative treatment. Overexpression of ribonucleotide reductase (RR) M1 is a major cause of GEM resistance. We previously established RRM1‐mediated GEM‐resistant cell lines (MGEM6 and MGEM8) and showed that the knockdown of RRM1 is a rationale strategy for overcoming GEM resistance. We further investigated the role of RR inhibition in enhancing the effects of GEM. Materials and methods We examined whether the combination treatment of hydroxyurea (HU), 3‐aminopyridine‐2‐carboxaldehyde thiosemicarbazone (3‐AP), and tranilast (TRL) could increase GEM sensitivity using the survival assay of MGEM6, MGEM8, and their parental cells. The effects of these compounds on the expression of RRM1 and RRM2 mRNA and protein were evaluated in the three cell lines by quantitative PCR (polymerase chain reaction) and immunoblotting. Results HU or/and TRL at nontoxic concentrations significantly improved the response of resistant cancer cells to GEM, whereas 3‐AP did not. This may have been because the two agents reduced the ratio of RRM1/RRM2. The three compounds have different effects on the mRNA and protein expression of RRM1 and RRM2. Conclusions The combination of HU and/or TRL with GEM enhances the toxic effect in gemcitabine‐resistant cells induced by RRM1.

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“…In a recent work, IRF1 was upregulated by CD-associated bacteria [ 34 ], so that together with our results, we could suggest an increase of IRF1 activity in situations that promote the disease. There are no previous data on CREB1 in CD, but it has been related to other diseases like human colorectal cancer, where CREB1 acts as a TF for tumor driver RRM2 , or glioblastoma, where CREB1 acts as a mediator of the induction of TGFβ2 [ 35 , 36 ]. This increase in nuclear translocation suggests a role for gliadin in the upregulation of their target genes through TF activation, also in non-celiac individuals.…”

Section: Discussionmentioning

confidence: 99%

Transcription Factor Binding Site Enrichment Analysis in Co-Expression Modules in Celiac Disease

Romero-Garmendia

García-Etxebarria

Hernandez-Vargas

et al. 2018

Genes

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The aim of this study was to construct celiac co-expression patterns at a whole genome level and to identify transcription factors (TFs) that could drive the gliadin-related changes in coordination of gene expression observed in celiac disease (CD). Differential co-expression modules were identified in the acute and chronic responses to gliadin using expression data from a previous microarray study in duodenal biopsies. Transcription factor binding site (TFBS) and Gene Ontology (GO) annotation enrichment analyses were performed in differentially co-expressed genes (DCGs) and selection of candidate regulators was performed. Expression of candidates was measured in clinical samples and the activation of the TFs was further characterized in C2BBe1 cells upon gliadin challenge. Enrichment analyses of the DCGs identified 10 TFs and five were selected for further investigation. Expression changes related to active CD were detected in four TFs, as well as in several of their in silico predicted targets. The activation of TFs was further characterized in C2BBe1 cells upon gliadin challenge, and an increase in nuclear translocation of CAMP Responsive Element Binding Protein 1 (CREB1) and IFN regulatory factor-1 (IRF1) in response to gliadin was observed. Using transcriptome-wide co-expression analyses we are able to propose novel genes involved in CD pathogenesis that respond upon gliadin stimulation, also in non-celiac models.

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CREB1 directly activates the transcription of ribonucleotide reductase small subunit M2 and promotes the aggressiveness of human colorectal cancer

Cited by 24 publications

References 43 publications

Co-expression Network Analysis Identifies Four Hub Genes Associated With Prognosis in Soft Tissue Sarcoma

Co-expression Network Analysis Identifies Four Hub Genes Associated With Prognosis in Soft Tissue Sarcoma

Combination of hydroxyurea and tranilast suppresses gemcitabine resistance induced by ribonucleotide reductase M1 in gemcitabine‐resistant cells

Transcription Factor Binding Site Enrichment Analysis in Co-Expression Modules in Celiac Disease

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