Phenotypic changes associated with DYNACTIN‐2 (DCTN2) over expression characterise SJSA‐1 osteosarcoma cells

Bransfield, Kieran; Askham, Jon M.; Leek, J.P.; Robinson, Philip A.; Mighell, Alan J.

doi:10.1002/mc.20151

Cited by 11 publications

(10 citation statements)

References 43 publications

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“…Overexpression in mammalian cells of one dynactin subunit (dynamitin) disrupts the complex, resulting in the perturbation of mitosis (32). In addition, DCTN2 overexpression disrupt the dynein-dynactin motor, shifting cellular movement and mitosis with predisposition to mitotic block and polyploidy (33). DCTN3 localizes to the centrosomes during interphase and to kinetochores and spindle poles throughout mitosis.…”

Section: Dctn3 and Rhbdd2 As Predictors Or Recurrencementioning

confidence: 99%

Breast Cancer Molecular Signatures as Determined by SAGE: Correlation with Lymph Node Status

Abba

Sun

Hawkins

et al. 2007

Molecular Cancer Research

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Global gene expression measured by DNA microarray platforms have been extensively used to classify breast carcinomas correlating with clinical characteristics, including outcome. We generated a breast cancer Serial Analysis of Gene Expression (SAGE) high-resolution database of f2.7 million tags to perform unsupervised statistical analyses to obtain the molecular classification of breast-invasive ductal carcinomas in correlation with clinicopathologic features. Unsupervised statistical analysis by means of a random forest approach identified two main clusters of breast carcinomas, which differed in their lymph node status (P = 0.01); this suggested that lymph node status leads to globally distinct expression profiles. A total of 245 (55 up-modulated and 190 down-modulated) transcripts were differentially expressed between lymph node (+) and lymph node (À) primary breast tumors (fold change, z2; P < 0.05). Various lymph node (+) up-modulated transcripts were validated in independent sets of human breast tumors by means of real-time reverse transcription-PCR (RT-PCR). We validated significant overexpression of transcripts for HOXC10 (P = 0.001), TPD52L1 (P = 0.007), ZFP36L1 (P = 0.011), PLINP1 (P = 0.013), DCTN3 (P = 0.025), DEK (P = 0.031), and CSNK1D (P = 0.04) in lymph node (+) breast carcinomas. Moreover, the DCTN3 (P = 0.022) and RHBDD2 (P = 0.002) transcripts were confirmed to be overexpressed in tumors that recurred within 6 years of follow-up by real-time RT-PCR. In addition, meta-analysis was used to compare SAGE data associated with lymph node (+) status with publicly available breast cancer DNA microarray data sets. We have generated evidence indicating that the pattern of gene expression in primary breast cancers at the time of surgical removal could discriminate those tumors with lymph node metastatic involvement using SAGE to identify specific transcripts that behave as predictors of recurrence as well. (Mol Cancer Res 2007;5(9):881 -90)

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Section: Dctn3 and Rhbdd2 As Predictors Or Recurrencementioning

confidence: 99%

Breast Cancer Molecular Signatures as Determined by SAGE: Correlation with Lymph Node Status

Abba

Sun

Hawkins

et al. 2007

Molecular Cancer Research

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“…These studies demonstrated that DCTN1 acted as a fusion partner in non-small cell lung cancer (NSCLC), 17 and DCTN2 was up-regulated in the osteosarcoma SJSA-1 cell line. 18 Another study showed that high expression of DCTN4 was significantly related to a favorable prognosis in colon adenocarcinoma (COAD) patients. 19 Moreover, it was reported that the mRNA expressions of down-regulated DCTN1 , DCTN2 , DCTN5 , and the up-regulated DCTN6 were associated with a satisfactory prognosis for cutaneous melanoma.…”

Section: Introductionmentioning

confidence: 99%

Study on the Prognostic Values of Dynactin Genes in Low-Grade Glioma

Chen

et al. 2021

Technol Cancer Res Treat

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Objective: This present study aims to investigate the potential prognostic values of dynactin genes ( DCTN) for predicting the overall survival (OS) in low-grade glioma (LGG) patients. Methods: The DCTN mRNA expression data were downloaded from The Cancer Genome Atlas database containing 518 patients with LGG. The Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analyses for DCTN genes were performed by using Database for Annotation, Visualization, and Integrated Discovery platform, and their enrichment results were verified by using the Biological Networks Gene Ontology tool. Next, the correlations between DCTN genes and LGG were identified by Pearson correlation coefficient analysis. The OS was estimated by Kaplan-Meier survival analysis. The cBio Cancer Genomics Portal was used to analyze the mutations of DCTN genes and their effects on the prognosis of LGG. The correlation between the abundance of immune infiltration and tumor purity of DCTN genes were predicted by The Tumor Immune Estimation Resource. Results: Our research showed that the mRNA expression of DCTN4 in tumor tissues was much higher ( P < 0.01) than that in normal tissues. Meanwhile, there was a certain correlation between the DCTN genes. Survival analysis showed that the high expression of DCTN1, DCTN3, DCTN4, DCTN6, and their co-expression were significantly correlated with favorable OS in LGG patients ( P < 0.05). In DCTN2, a high mutation rate was observed. Further research showed that the genetic alteration in DCTN genes was related to a poor OS and progression-free survival of LGG patients. The expression of DCTN genes had a certain correlation with immune infiltrating cells. Conclusion: Our study showed that the high expressions of DCTN1, DCTN3, DCTN4, and DCTN6 were associated with a favorable OS of LGG patients, indicating that these DCTN genes are potential biomarkers for evaluating the prognosis of LGG patients.

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“… 30 DCTN2 was observed to be over expressed in SJSA-1 osteosarcoma cells. 31 Nevertheless, the correlation between DCTN4 and cancer was not stated. Here, we have employed statistics from TCGA on expression and medical data in COAD to investigate correlations between DCTN gene family expression levels and prognosis and to identify biomarkers that can be used for prognosis and diagnosis in patients with COAD.…”

Section: Discussionmentioning

confidence: 99%

Distinct prognostic value of dynactin subunit 4 (DCTN4) and diagnostic value of DCTN1, DCTN2, and DCTN4 in colon adenocarcinoma

Wang¹,

Wang²,

Zhang³

et al. 2018

CMAR

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BackgroundColon adenocarcinoma (COAD) is ranked as the third most commonly diagnosed cancer in both women and men, and it is the most frequently occurring malignant tumor. Dynactin is a protein compound based on multiple subunits, including dynactin 1–6 (DCTN1–6), in most categories of cytoplasmic dynein performance in eukaryotes. Nevertheless, correlations between the DCTN family and the prognosis and diagnosis of COAD remain unidentified.MethodsStatistics for DCTN mRNA expression in patients with COAD were acquired from The Cancer Genome Atlas. Kaplan–Meier analyses and a Cox regression model were applied to determine overall survival, with computation of HRs and 95% CIs. Several online data portals were used to assess the biological process, and pathway examination was performed using the Kyoto Encyclopedia of Genes and Genomes to predict the biological functionality of DCTN genes.ResultsWe found that high expression of DCTN4 was linked with satisfactory results for overall survival (P=0.042, HR=0.650, 95% CI 0.429–0.985). The expression of DCTN1, DATN2, and DCTN4 was closely correlated with the frequency of colon tumors (P<0.001, area under the curve [AUC]=0.8811, 95% CI 0.8311–0.9312; P<0.001, AUC=0.870, 96% CI 0.833–0.9071; and P=0.0051, AUC=0.6317, 95% CI 0.5725–0.6908, respectively). In the enrichment examination, the level of gene expression was related to the cell cycle, cell apoptosis, and the cell metastasis pathway.ConclusionThe expression levels of DCTN1, DCTN2, and DCTN4 could allow differentiation between cancer-bearing tissues and paracancerous tissue. These genes can be applied as biomarkers to predict the prognosis and diagnosis of COAD.

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Phenotypic changes associated with DYNACTIN‐2 (DCTN2) over expression characterise SJSA‐1 osteosarcoma cells

Cited by 11 publications

References 43 publications

Breast Cancer Molecular Signatures as Determined by SAGE: Correlation with Lymph Node Status

Breast Cancer Molecular Signatures as Determined by SAGE: Correlation with Lymph Node Status

Study on the Prognostic Values of Dynactin Genes in Low-Grade Glioma

Distinct prognostic value of dynactin subunit 4 (DCTN4) and diagnostic value of DCTN1, DCTN2, and DCTN4 in colon adenocarcinoma

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