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• Research Paper Volume 13, Issue 13 pp 17734-17767

  Clinical significance and prognostic role of an immune-related gene signature in gastric adenocarcinoma

  Relevance score: 12.159791

  Rui Mao, Kehao Liu, Nana Zhao, Pengsen Guo, Yingxin Wu, Zheng Wang, Yanjun Liu, Tongtong Zhang

  Keywords: gastric adenocarcinoma, qRT-PCR, prognosis, immune signature, tumor microenvironment

  Published in Aging on July 11, 2021

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  Limited progress has been made in the treatment of gastric adenocarcinoma (GAC) in recent years, but the potential of immunotherapy in GAC is worthy of consideration. The purpose of this study was to develop a reliable, personalized signature based on immune genes to predict the prognosis of GAC. Here, we identified two groups of patients with significantly different prognoses by performing unsupervised clustering analysis of The Cancer Genome Atlas (TCGA) database based on 881 immune genes. The immune signature was constructed with a training set composed of 350 GAC samples from the TCGA and subsequently validated with 431 samples from GSE84437, 432 samples from GSE26253, and 145 GAC samples from real-time quantitative reverse transcription polymerase chain reaction data. This classification system can also be used to predict prognosis in different clinical subgroups. Further analysis suggested that high-risk patients were characterized by low immune scores, distinctive immune cell proportions, different immune checkpoint profiles, and a low tumor mutational burden. Ultimately, the signature was identified as an independent prognostic factor. In general, the signature can accurately predict recurrence and overall survival in patients with GAC and may serve as a powerful prognostic tool to further optimize cancer immunotherapy.

• Research Paper Volume 12, Issue 21 pp 22233-22252

  Development and validation of a novel prognostic signature in gastric adenocarcinoma

  Relevance score: 10.30615

  Rui Mao, Zheng Wang, Yuanchuan Zhang, YuanYuan Chen, Qian Liu, Tongtong Zhang, Yanjun Liu

  Keywords: gastric adenocarcinoma, qRT-PCR, competing endogenous RNA network, weighted gene coexpression network analysis

  Published in Aging on November 8, 2020

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  Competing endogenous RNA networks have attracted increasing attention in gastric adenocarcinoma (GA). The current study aimed to explore ceRNA-based prognostic biomarkers for GA. RNA expression profiles were downloaded from TCGA and GEO databases. A ceRNA network was constructed based on the most relevant modules in the weighted gene coexpression network analysis. Kaplan-Meier (KM) survival analysis revealed prognosis-related RNAs, which were subjected to the multivariate Cox regression analysis. The predictive accuracy and discriminative ability of the signature were determined by KM analyses, receiver operating characteristic curves and area under the curve values. Ultimately, we constructed a ceRNA network consisting of 55 lncRNAs, 17 miRNAs and 73 mRNAs. Survival analyses revealed 3 lncRNAs (LINC01106, FOXD2-AS1, and AC103702.2) and 3 mRNAs (CCDC34, ORC6, and SOX4) as crucial prognostic factors; these factors were then used to construct a survival specific ceRNA network. Patients with high risk scores exhibited significantly worse overall survival than patients with low risk scores, and the AUC for 5-year survival was 0.801. A total of 112 GA specimens and the GSE84437 dataset were used to successfully validate the robustness of our signature by qRT-PCR. In summary, we developed a prognostic signature for GA, that shows better accuracy than the traditional TNM pathological staging system.

• Research Paper Volume 12, Issue 20 pp 20778-20800

  Identification of a nomogram based on an 8-lncRNA signature as a novel diagnostic biomarker for head and neck squamous cell carcinoma

  Relevance score: 11.292799

  Rui Mao, Yuanyuan Chen, Lei Xiong, Yanjun Liu, Tongtong Zhang

  Keywords: head and neck squamous carcinoma, long noncoding RNAs, prognosis, bioinformatics, qRT-PCR

  Published in Aging on October 22, 2020

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  Long noncoding RNAs (lncRNAs) have been proposed as diagnostic or prognostic biomarkers of head and neck squamous carcinoma (HNSCC). The current study aimed to develop a lncRNA-based prognostic nomogram for HNSCC. LncRNA expression profiles were downloaded from The Cancer Genome Atlas (TCGA) database. After the reannotation of lncRNAs, the differential analysis identified 253 significantly differentially expressed lncRNAs in training set TCGA-HNSC (n = 300). The prognostic value of each lncRNA was first estimated in univariate Cox analysis, and 41 lncRNAs with P < 0.05 were selected as seed lncRNAs for Cox LASSO regression, which identified 11 lncRNAs. Multivariate Cox analysis was used to establish an 8-lncRNA signature with prognostic value. Patients in the high-signature score group exhibited a significantly worse overall survival (OS) than those in the low-signature score group, and the area under the receiver operating characteristic (ROC) curve for 3-year survival was 0.74. Multivariable Cox regression analysis among the clinical characteristics and signature scores suggested that the signature is an independent prognostic factor. The internal validation cohort, external validation cohort, and 102 HNSCC specimens quantified by qRT-PCR successfully validate the robustness of our nomogram.

• Research Paper Volume 12, Issue 17 pp 17634-17646

  DUSP4 directly deubiquitinates and stabilizes Smad4 protein, promoting proliferation and metastasis of colorectal cancer cells

  Relevance score: 15.353783

  Weifeng Xu, Beibei Chen, Dianshan Ke, Xiaobing Chen

  Keywords: DUSP4, Smad4, colorectal cancer, EMT, qRT-PCR

  Published in Aging on September 7, 2020

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  Colorectal cancer is a common health-threatening tumor within the gastrointestinal tract. The aim of this study was to test the biological role of DUSP4 in colorectal cancer cells. In our study, DUSP4 overexpression-treated HCT116 cells and DUSP4 knockdown-treated SW480 cells were selected to perform study. Quantitative real-time PCR test (qRT-PCR) and western blot were used to detect DUSP4 abundance in clinical tissues and six cell lines, as well as ubiquitin-related Smad4 degradation. Western blot, migration and invasion. were used to assess the relationships between DUSP4 and Smad4. Higher DUSP4 expression of functional significance was observed in colorectal cancer tissues and cells. The results showed that both treatments could affect the proliferation, colony formation, migration, invasion of tumor cells, and the expression of epithelial mesenchymal transformation (EMT)-associated biomarkers. Moreover, in colorectal cancer cells, DUSP4 could promote the Smad4 degradation by regulating ubiquitin-related Smad4 degradation, and promote the cell proliferation, migration and invasion by regulating Smad4 degradation via Smad4 gene. Meanwhile, DUSP4 can directly deubiquitinate and stabilize Smad4 protein, hence further promote proliferation and metastasis of colorectal cancer cells.

  

  DUSP4 gene was highly expressed in colorectal cancer tissues. (A) mRNA abundance analysis of DUSP4 gene in GEPIA database. (B) mRNA abundance analysis of DUSP4 gene in oncomine. (C) Western blot analysis of normal tissues and colorectal cancer tissues. N: normal tissues; T: tumor tissues. GAPDH was employed as an internal reference. (D) qRT-PCR analysis of DUSP4 mRNA abundance in four colorectal cancer tissues and the paired normal tissues. (E and F) Immunohistochemical analysis of normal tissues and colorectal cancer tissues. *P<0.05. ***P<0.001.

  
  
  

  

  DUSP4 promoted metastasis and proliferation of colorectal cancer cells in vitro. (A) Western blot analysis of DUSP4 expression in FHC, LOVO, SW480, SW620, HCT116, and DLD1. (B) qRT-PCR analysis of DUSP4 expression in FHC, LOVO, SW480, SW620, HCT116, and DLD1. (C) Knockdown treatment of three designed siRNAs in SW480 cells. (D) DUSP4 protein expression of DUSP4 knockdown-treated SW480 cells and DUSP4 overexpression-treated HCT116 cells. (E) Cell proliferation analysis of DUSP4 knockdown-treated SW480 cells. (F) Cell proliferation analysis of DUSP4 overexpression-treated HCT116 cells. (G) Colony formation analysis of DUSP4 knockdown-treated SW480 cells and DUSP4 overexpression-treated HCT116 cells. (H) Western blot analysis of cell proliferation-related biomarkers expression in DUSP4 knockdown-treated SW480 cells and DUSP4 overexpression-treated HCT116 cells. **P<0.01, ***P<0.001.

  
  
  

  

  Regulation of USP4 on colorectal cancer cell migration and invasion. (A) Cell scratch test of DUSP4 knockdown-treated SW480 cells. (B) Cell scratch test of DUSP4 overexpression-treated HCT116 cells. (C and D) Cell migration and invasion analysis of DUSP4 knockdown-treated SW480 cells and DUSP4 overexpression-treated HCT116 cells, respectively. (E) Western blot analysis of EMT-related biomarkers expression in DUSP4 knockdown-treated SW480 cells and DUSP4 overexpression-treated HCT116 cells. (F) qRT-PCR analysis of EMT-related biomarkers expression in DUSP4 knockdown-treated SW480 cells and DUSP4 overexpression-treated HCT116 cells. **P<0.01, ***P<0.001.

  
  
  

  

  DUSP4 down-regulated Smad4 gene expression. (A) Western blot analysis of Smad4 protein expression in DUSP4 knockdown-treated SW480 cells and DUSP4 overexpression-treated HCT116 cells. (B) qRT-PCR analysis of Smad4 mRNA expression in DUSP4 knockdown-treated SW480 cells and DUSP4 overexpression-treated HCT116 cells. (C) Correlation analysis of DUSP4 protein and Smad4 protein in clinical samples. (D) Correlation analysis of DUSP4 mRNA and Smad4 mRNA in clinical samples. (E) Relationship analysis of DUSP4 and Smad4 in HEK293T cells which was transfected with DUSP4 and Smad4. (F–H) Relative Smad4 protein expressions in DUSP4 knockdown-treated SW480 cells and DUSP4 overexpression-treated HCT116 cells with cyclohexane (CHX) treatment at different time points. **P<0.01, ***P<0.001.

  
  
  

  

  DUSP4 regulated Smad4 expression through ubiquitination. (A) Western blot analysis of DUSP4 and Smad4 expression in DUSP4 overexpression-treated HCT116 cells with CQ and MG132 treatment at different time points. (B) CO-IP analysis of DUSP4 and Smad in SW480 cells. (C) Forward and reverse CO-IP analysis of DUSP4 and Smad in SW480 cells and HCT116 cells. (D) Immunocolocalization analysis of DUSP4 and Smad in SW480 cells and HCT116 cells. (E) Ubiquitination test of DUSP4 and Smad in HCT116 cells. (F) Ubiquitination test of DUSP4 and Smad in SW480 cells. Scale bar: 5 μm.

  
  
  

  

  Rescue experiment. (A) CCK8 analysis of DUSP4 knockdown-treated SW480 cells and DUSP4 overexpression-treated HCT116 cells that had been treated with Smad 4 knockdown and overexpression treatments. (B) Western blot and qRT-PCR analysis of Cyclin D and PCNA expression in USP4 knockdown-treated SW480 cells and DUSP4 overexpression-treated HCT116 cells that had been treated with Smad 4 knockdown and overexpression treatments. (C and D) Migration and invasion analysis of DUSP4 knockdown-treated SW480 cells that had been treated with Smad4 overexpression treatment. (E and F) Migration and invasion analysis of DUSP4 overexpression-treated HCT116 cells that had been treated with Smad 4 knockdown treatment. (G and H) qRT-PCR analysis of EMT related biomarkers in DUSP4 knockdown-treated SW480 cells and DUSP4 overexpression-treated HCT116 cells that had been treated with Smad 4 knockdown and overexpression treatments. **P<0.01, ***P<0.001.