MCM7 promotes cancer progression through cyclin D1-dependent signaling and serves as a prognostic marker for patients with hepatocellular carcinoma

Qu, Kai; Wang, Zhixin; Fan, Haining; Li, Juan; Liu, Jie; Li, Pingping; Liang, Zheyong; An, Hongli; Jiang, Yongchao; Lin, Qiushi; Dong, Xiaoqun; Liu, Chang

doi:10.1038/cddis.2016.352

Cited by 89 publications

(75 citation statements)

References 41 publications

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“…Its sensitivity for HCC screening ranges from 41 to 65% at a cutoff of 20 ng/mL [53][54][55][56]. In recent years, various biomarkers have emerged for diagnosing HCC and predicting patient outcome, including glypican 3 and insulin-like growth factor (IGF)II mRNA [57], Keap1 and pNrf2 [58], 3-microRNA and AFP [59], CXCL1 [60], minichromosome maintenance complex -7 [61], and IGF1 receptor [62], among others.…”

Section: Discussionmentioning

confidence: 99%

NLRC and NLRX gene family mRNA expression and prognostic value in hepatocellular carcinoma

et al. 2017

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Nucleotide‐binding oligomerization domain (NOD)‐like receptor (NLR)C and NLRX family proteins play a key role in the innate immune response. The relationship between these proteins and hepatocellular carcinoma (HCC) remains unclear. This study investigated the prognostic significance of NLRC and NLRX family protein levels in HCC patients. Data from 360 HCC patients in The Cancer Genome Atlas database and 231 patients in the Gene Expression Omnibus database were analyzed. Kaplan–Meier analysis and a Cox regression model were used to determine median survival time (MST) and overall and recurrence‐free survival by calculating the hazard ratio (HR) and 95% confidence interval (CI). High NOD2 and low NLRX1 expression in tumor tissue was associated with short MST (P = 0.012 and 0.014, respectively). A joint‐effects analysis of NOD2 and NLRX1 combined revealed that groups III and IV had reduced risk of death from HCC as compared to group I (adjusted P = 0.001, adjusted HR = 0.31, 95% CI = 0.16–0.61 and adjusted P = 0.043, adjusted HR = 0.63, 95%CI = 0.41–0.99, respectively). NOD2 and NLRX1 expression levels are potential prognostic markers in HCC following hepatectomy.

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Section: Discussionmentioning

confidence: 99%

NLRC and NLRX gene family mRNA expression and prognostic value in hepatocellular carcinoma

et al. 2017

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“…Through this mechanism, MCM7 initiates DNA replication, which is a key process in cell cycle progression. (Qu et al 2017) CKS2 is activated by the Wnt/βcatenin signaling pathway and promotes cell proliferation and inhibits apoptosis, which makes the HCC cells more aggressive as its overexpression is more frequently observed in poorly differentiated tumors. (Li et al 2018;Shen et al 2010) KIF23 depletion inhibits tumor formation by inducing apoptosis in certain types of cancer, such as lung adenocarcinomas.…”

Section: Discussionmentioning

confidence: 99%

Peer Review #1 of "Identification of key genes and long non-coding RNA associated ceRNA networks in hepatocellular carcinoma (v0.2)"

2019

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Background. Hepatocellular carcinoma (HCC) is one of the leading causes of cancerrelated deaths worldwide. Although multiple efforts have been made to understand the development of HCC, morbidity and mortality rates remain high. In this study, we aimed to discover the mRNAs and long non-coding RNAs (lncRNAs) that contribute to the progression of HCC. We constructed a lncRNA-related competitive endogenous RNA (ceRNA) network to elucidate the molecular regulatory mechanism underlying HCC. Methods. A microarray dataset (GSE54238) containing information about both mRNAs and lncRNAs was downloaded from the GEO database. Differentially expressed genes (DEGs) and lncRNAs (DElncRNAs) in tumor tissues and non-cancerous tissues were identified using the limma package of the R software. The miRNAs that are targeted by DElncRNAs were predicted using miRcode, while the target mRNAs of miRNAs were retrieved from miRDB, miRTarBas, and TargetScan. Functional annotation and pathway enrichment of DEGs were performed using the EnrichNet website. We constructed a protein-protein interaction (PPI) network of DEGs using STRING, and identified the hub genes using Cytoscape. Survival analysis of the hub genes and DElncRNAs was performed using the GEPIA database. The expression of molecules with prognostic values was validated on the UALCAN database. The hepatic expression of hub genes was examined using The Human Protein Atlas. The hub genes and DElncRNAs with prognostic values as well as the predictive miRNAs were selected to construct the ceRNA networks. Results. We found that 10 hub genes (KPNA2, MCM7, CKS2, KIF23, HMGB2, ZWINT, E2F1, MCM4, H2AFX, and EZH2) and four lncRNAs (FAM182B, SNHG6, SNHG1, and SNHG3) with prognostic values were overexpressed in the hepatic tumor samples. We also constructed a network containing 10 lncRNA-miRNA-mRNA pathways, which might be responsible for

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“…DNA replication is a central process in cell proliferation, while aberrant DNA replication is a driving force of oncogenesis. It has been reported that overexpressed MCM7 is associated with a poor prognosis of HCC patients, and MCM7 promotes HCC cell proliferation via upregulating MAPK-cyclin D1 pathway both in vitro and in vivo 32 . In addition, the hallmark MYC targets proteins, and the cell cycle checkpoint proteins involved in G2/M transitions, are also among the upregulated protein networks.…”

Section: Differentially Regulated Proteins Characterized In the Hcc Cmentioning

confidence: 99%

Identification of protein abundance changes in biopsy-level hepatocellular carcinoma tissues using PCT-SWATH

Zhu

et al. 2018

Preprint

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and Tiannan Guo (guotiannan@wias.org.cn) Zhu, et al. Proteomics in Pathology: PCT-SWATH analysis of Hepatocellular carcinoma 2 / 26 2 AbstractIn this study, we optimized the pressure-cycling technology (PCT) and SWATH mass spectrometry workflow to analyze biopsy-level tissue samples (2 mg wet weight) from 19 hepatocellular carcinoma (HCC) patients. Using OpenSWATH and pan-human spectral library, we quantified 11,787 proteotypic peptides from 2,579 SwissProt proteins in 76 HCC tissue samples within about 9 working days (from receiving tissue to SWATH data). The coefficient of variation (CV) of peptide yield using PCT was 32.9%, and the R 2 of peptide quantification was 0.9729. We identified protein changes in malignant tissues compared to matched control samples in HCC patients, and further stratified patient samples into groups with high α-fetoprotein (AFP) expression or HBV infection. In aggregate, the data identified 23 upregulated pathways and 13 ones. We observed enhanced biomolecule synthesis and suppressed small molecular metabolism in liver tumor tissues. 16 proteins of high documented relevance to HCC are highlighted in our data. We also identified changes of virus-infection-related proteins including PKM, CTPS1 and ALDOB in the HBV + HCC subcohort. In conclusion, we demonstrate the practicality of performing proteomic analysis of biopsy-level tissue samples with PCT-SWATH methodology with moderate effort and within a relatively short timeframe. Zhu, et al. Proteomics in Pathology: PCT-SWATH analysis of Hepatocellular carcinoma 3 / 26

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MCM7 promotes cancer progression through cyclin D1-dependent signaling and serves as a prognostic marker for patients with hepatocellular carcinoma

Cited by 89 publications

References 41 publications

NLRC and NLRX gene family mRNA expression and prognostic value in hepatocellular carcinoma

NLRC and NLRX gene family mRNA expression and prognostic value in hepatocellular carcinoma

Peer Review #1 of "Identification of key genes and long non-coding RNA associated ceRNA networks in hepatocellular carcinoma (v0.2)"

Identification of protein abundance changes in biopsy-level hepatocellular carcinoma tissues using PCT-SWATH

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