Chemosensitivity of gastric cancer: analysis of key pathogenic transcription factors

Weng, Jianze; Wu, Aixiang; Ying, Jingwen

doi:10.21037/jgo-22-274

Cited by 6 publications

(4 citation statements)

References 20 publications

(29 reference statements)

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“…As a transcriptional factor, FOXM1 plays multiple roles in tumorigenesis and development, such as promoting cell differentiation and proliferation, facilitating tumor metastasis, and invasion [ 39 ]. In addition, higher FOXM1 expression predicted less response of GC patients to cisplatin [ 40 ]. Consistent with other studies, the mRNA level of FOXM1 is significantly ( p = 0.0105 and p = 0.0013) higher in cisplatin resistant GC cells ( Figure 4 A).…”

Section: Resultsmentioning

confidence: 99%

“…The function of FOXM1 in determining sensitivity of cancer cells to chemotherapy drugs has also been reported [ 45 ]. In gastric cancer patients, overexpression of FOXM1 was related to cisplatin resistance, and depletion of FOXM1 improved this resistance [ 40 , 46 ]. FOXM1 was found to be up-regulated in cisplatin resistant GC cells, and KIAA1429 depletion significantly decreased FOXM1 expression.…”

Section: Discussionmentioning

confidence: 99%

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m6A Methyltransferase KIAA1429 Regulates the Cisplatin Sensitivity of Gastric Cancer Cells via Stabilizing FOXM1 mRNA

Zhu

Zhou

Chen

et al. 2022

Cancers

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Although cisplatin is frequently used to treat gastric cancer, the resistance is the main obstacle for effective treatment. mRNA modification, N6-methyladenosine (m6A), is involved in the tumorigenesis of many types of cancer. As one of the largest m6A methyltransferase complex components, KIAA1429 bridges the catalytic m6A methyltransferase components, such as METTL3. In gastric cancer, KIAA1429 was reported to promote cell proliferation. However, whether KIAA1429 is involved in the resistance of gastric cancer to cisplatin remains unclear. Here, we generated cisplatin resistant gastric cancer cell lines, and compared the m6A content between resistant cells and wild type cells. The m6A content as well as KIAA1429 expression are higher in resistant cells. Interestingly, the expression of KIAA1429 was significantly increased after cisplatin treatment. We then used shRNA to knockdown KIAA1429 and found that resistant cells responded more to cisplatin treatment after KIAA1429 depletion, while overexpression of KIAA1429 decreased the sensitivity. Moreover, we identified a putative p65 binding site on the promoter area of KIAA1429 and ChIP assay confirmed the binding. p65 depletion decreased the expression of KIAA1429. YTHDF1 is the most abundant m6A “reader” that interacts with m6A modified mRNA. Mechanistically, YTHDF1 was recruited to the 3′-untranslated Region (3′-UTR) of transcriptional factor, FOXM1 by KIAA1429 and stabilized FOXM1 mRNA. More importantly, KIAA1429 knockdown increased the sensitivity of resistant cells to cisplatin in vivo. In conclusion, our results demonstrated that KIAA1429 facilitated cisplatin resistance by stabilizing FOXM1 mRNA in gastric cancer cells.

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Section: Resultsmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

m6A Methyltransferase KIAA1429 Regulates the Cisplatin Sensitivity of Gastric Cancer Cells via Stabilizing FOXM1 mRNA

Zhu

Zhou

Chen

et al. 2022

Cancers

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“…MYBL2 maintains normal cell cycle progression and is a risk predictor for gastric cancer. MYBL2 leads to metastatic recrudescence and poor prognosis in prostate cancer patients [29,30]. The same, Zhang et al pointed out that MYBL2 is a key downstream factor that promotes the progression of glioma, and is related to the clinical stage and overall survival of patients [31].…”

Section: Discussionmentioning

confidence: 99%

Predicted of seven hub genes of drug resistance in glioma

WEN,

LI,

LEI

et al. 2023

Preprint

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Drug resistance is the main cause of glioma recrudescence and death. But its etiology and pathogenesis are still unclear. There is an urgent need to develop a new prognostic and therapeutic method to assess patient survival and reduce mortality. The Cancer Genome Atlas (TCGA) database was used to identify differentially expressed genes(DEGs) between glioblastoma(GBM) and normal. The samples were divided into cluster 1 and cluster 2 subtypes to explore tumor drug resistance according to their IC50 value of drugs for GBM in the GDSC database. The 7 genes were designated as core molecules, which were significantly correlated with immune checkpoints. The dataset CGGA-693 validated that the survival rate of patients in the high-risk group was significantly lower than that in the low-risk group. Moreover, the hub genes were significantly correlated with age, Neoplasm Histologic Grade, IDH status, MGMT status, ATRX status, and BCR status. And the expression level of 7 genes was significantly associated with the grade of glioma, except CAMK2A. RT-PCR revealed that MYBL2, CDC45, CENPA, and E2F7 were upregulated while ATP2B3, KCNJ9, and OPALIN were downregulated in patients. These results demonstrate that the risk model can effectively predict and differentiate the survival and treatment outcomes of glioma patients. MYBL2, CDC45, CENPA, E2F7, ATP2B3, KCNJ9, and OPALIN are expected to be reliable molecular targets and prognostic biomarkers for drug-resistant gliomas.

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“…Moreover, high RXRG mRNA expression was signi cantly correlated with better tumour characteristics and longer progression-free survival for breast cancer patients(Joseph et al 2019). It has also been shown that RXRG can improve the prognosis of patients with gastric cancer(Weng et al 2022). GO and KEGG analyses were performed to reveal the function of potential targets in the treatment of NSCLC.…”

mentioning

confidence: 99%

Elucidation of the mechanisms of α-linolenic acid and its derivative in the treatment of non-small cell lung cancer using network pharmacology

Meng,

Liu,

Shao

et al. 2023

Preprint

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Purpose α-Linolenic acid (ALA) and its derivative docosahexaenoic acid (DHA) have been reported to play an anticancer role in multiple types of cancer. However, their molecular targets in treating non-small cell lung cancer (NSCLC) have not been investigated. Methods The common target genes of NSCLC, ALA and DHA were obtained by intersections between disease and drug databases. The common targets were imported into the STRING database to build a PPI network. The hub genes were selected in Cytoscape. GO and KEGG analyses were performed to reveal the function of potential targets, and the prognosis of hub genes was obtained by KM analysis. Moreover, molecular docking of target molecules and ligands was carried out using AuToDock software to select the ligand‒receptor with the lowest binding energy for molecular dynamics simulation. Results A total of 8357 targets of NSCLC, 15 targets of ALA and DHA, 12 common targets of diseases and drugs, and 9 targets of PPI interactions were obtained. The Kaplan‒Meier plotter showed that the mRNA expression of the 3 hub genes was significantly associated with overall survival (OS) and first progression survival (FPS) in NSCLC patients. These results showed good binding between the drug components and the hub targets. Molecular docking and molecular dynamics simulations demonstrated that the binding of RXRA and DHA tends to be stable. Conclusions In this study, we investigated the basic pharmacological effects of ALA and DHA in treating NSCLC and concluded that ALA and DHA have multitarget and multipathway actions in the treatment of NSCLC.

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Chemosensitivity of gastric cancer: analysis of key pathogenic transcription factors

Cited by 6 publications

References 20 publications

m6A Methyltransferase KIAA1429 Regulates the Cisplatin Sensitivity of Gastric Cancer Cells via Stabilizing FOXM1 mRNA

m6A Methyltransferase KIAA1429 Regulates the Cisplatin Sensitivity of Gastric Cancer Cells via Stabilizing FOXM1 mRNA

Predicted of seven hub genes of drug resistance in glioma

Elucidation of the mechanisms of α-linolenic acid and its derivative in the treatment of non-small cell lung cancer using network pharmacology

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