RNAi-mediated TCF-3 gene silencing inhibits proliferation of Eca-109 esophageal cancer cells by inducing apoptosis

TCF3 Induces DNMT1 Expression to Regulate Wnt Signaling Pathway in Glioma

The epigenetic alteration is widely understood as the key to cancer initiation. Herein, we intended to clarify the role of transcription factor 3 (TCF3) in the development of glioma and the behind epigenetic mechanism. Through bioinformatics analysis, we identified a TCF3-DNA methyltransferase 1 (DNMT1)-secreted frizzled related protein 1 (SFRP1) axis which was differentially expressed and interacted in gliomas. More specifically, TCF3 activated DNMT1 transcription, and DNMT1 repressed SFRP1 expression. TCF3 and DNMT1 were overexpressed, while SFRP1 was downregulated in glioma. Functionally, TCF3 silencing inhibited cell proliferation and migration, and promoted apoptosis, which were reversed by DNMT1. SFRP1 inhibited the tumor supporting effects of DNMT1 on glioma cells. Moreover, TCF3 downregulation or SFRP1 overexpression inhibited tumorigenesis and enhanced apoptosis of glioma cells, while DNMT1 enhanced tumorigenesis and repressed apoptosis in tumor tissues in vivo. The Wnt pathway was a downstream effector of the TCF3-DNMT1-SFRP1 axis. Collectively, this study determined a novel therapeutic target TCF3 for glioma from the perspective of epigenetic alteration via regulation of SFRP1 expression in a DNMT1-dependent manner.

Logistic regression with adaptive sparse group lasso penalty and its application in acute leukemia diagnosis

Cancer diagnosis based on gene expression profile data has attracted extensive attention in computational biology and medicine. It suffers from three challenges in practical applications: noise, gene grouping, and adaptive gene selection. This paper aims to solve the above problems by developing the logistic regression with adaptive sparse group lasso penalty (LR-ASGL). A noise information processing method for cancer gene expression profile data is first presented via robust principal component analysis. Genes are then divided into groups by performing weighted gene co-expression network analysis on the clean matrix. By approximating the relative value of the noise size, gene reliability criterion and robust evaluation criterion are proposed. Finally, LR-ASGL is presented for simultaneous cancer diagnosis and adaptive gene selection. The performance of the proposed method is compared with the other four methods in three simulation settings: Gaussian noise, uniformly distributed noise, and mixed noise. The acute leukemia data are adopted as an experimental example to demonstrate the advantages of LR-ASGL in prediction and gene selection.

MEX3D is an oncogenic driver in prostate cancer

BACKGROUND

Prostate cancer (PCa) is the most common visceral malignancy and the second leading cause of cancer deaths in US men. The two most common genetic alterations in PCa are expression of the TMPRSS2/ERG (TE) fusion gene and loss of the PTEN tumor suppressor. These genetic alterations act cooperatively to transform prostatic epithelium but the exact mechanisms involved are unclear.

METHODS

Microarray expression analysis of immortalized prostate epithelial cells transformed by loss of PTEN and expression of the TE fusion revealed MEX3D as one of the most highly upregulated genes. MEX3D expression in prostate cancer was examined in patient samples and in silico. In vitro and in vivo studies to characterize the biological impact of MEX3D were carried out. Analysis of the TCGA PanCancer database revealed TCF3 as a major target of MEX3D. The induction of TCF3 by MEX3D was confirmed and the biological impact of TCF3 examined by in vitro studies.

RESULTS

MEX3D is expressed at increased levels in prostate cancer and is increased by decreased PTEN and/or expression of the TE fusion gene and drives soft agar colony formation, invasion and tumor formation in vivo. The known oncogenic transcription factor TCF3 is highly correlated with MEX3D in prostate cancer. MEX3D expression strongly induces TCF3, which promotes soft agar colony formation and invasion in vitro.

CONCLUSIONS

Loss of PTEN and expression of the TE fusion gene in prostate cancer strongly upregulates expression of MEX3D and its target TCF3 and promotes transformation associated phenotypes via this pathway.

Identification of microRNAs as novel biomarkers for esophageal squamous cell carcinoma: a study based on The Cancer Genome Atlas (TCGA) and bioinformatics

BACKGROUND

MicroRNAs (miRNAs) have played important roles in the regulation of gene expression in many cancers, but their roles in esophageal squamous cell carcinoma (ESCC) are still unclear. The aim of this study was to determine the potential ESCC-specific key miRNAs from a large sample dataset in The Cancer Genome Atlas (TCGA).

METHODS

Integrative bioinformatics analysis was used to identify key ESCC-specific miRNAs related to the ESCC patients' tumor histological grade and lymphatic metastasis from TCGA. Next, these key miRNA potential gene regulatory functions and relationships with ESCC patients' clinical characteristics and overall survival were analyzed. Finally, three key miRNAs were selected randomly and quantificational real-time polymerase chain reaction (qRT-PCR) was used to validate in 51 newly diagnosed ESCC patients' tissues samples (collected from Nov. 2017 to Feb. 2019, in Wuwei, China) whether the bioinformatics analyses results were reliable and valid. Two-tailed Student's t test, Pearson Chi-squared test and Kaplan-Meier survival analysis were used in this study.

RESULTS

Thirty-five ESCC-specific miRNAs from TCGA database were investigated (fold-change > 2.0, P < 0.05), and 28 participated in the miRNAs-mRNAs co-expression network construction, while 17 were related with ESCC patients' tumor histological grade, TNM stage, and lymphatic metastasis (P < 0.05). Meanwhile, six miRNAs (including miR-200b-3p, miR-31-5p, miR-15b-5p, miR-141-3p, miR-135b-5p, and miR-195-5p) were correlated with overall survival of ESCC patients (log-rank, P < 0.05). MiR-135b-5p, miR-15b-5p, and miR-195-5p were selected for verification of the expression levels in 51 ESCC patients' tissue samples by using qRT-PCR. We found that the fold-changes between qRT-PCR and TCGA were completely consistent. The results also suggested that miR-135b-5p, miR-15b-5p, and miR-195-5p were significantly correlated with tumor differentiation degrees (P < 0.05), miR-195-5p was significantly correlated with tumor TNM stage (P < 0.05), and miR-135b-5p was significantly correlated with lymph-node metastasis (P < 0.05). MiR-135b-5p, miR-15b-5p, and miR-195-5p expression levels, ESCC patient clinical features association analysis results and the aforementioned TCGA bioinformatics analyses were similar.

CONCLUSION

This study identified key ESCC-related miRNAs. The key miRNAs are worthy of further investigation as potential novel biomarkers for diagnosis, classification, and prognosis of ESCC.

Increased CDKL3 expression predicts poor prognosis and enhances malignant phenotypes in esophageal squamous cell carcinoma

BACKGROUND

Cyclin-dependent kinase-like 3 (CDKL3) is a putative protein serine kinase and plays an important role in the regulation of cell growth and/or differentiation. However, studies on the function of CDKL3 in esophageal squamous cell carcinoma (ESCC) is limited. In our study, we explored the role and prognosis of CDKL3 in ESCC and underlying mechanism.

MATERIALS AND METHODS

The expression of CDKL3 was investigated by quantitative reverse transcription polymerase chain reaction and immunohistochemical staining. CDKL3 expression was downregulated by the RNAi-mediated knockdown. The functions of CDKL3 on cell growth were assessed by Celigo image cytometry, MTT assay, cell-cycle analysis, Annexin V assay, and caspase-3/7 activity analysis. The effect of CDKL3 on cellular invasive was investigated by the Transwell assay. Pathscan Stress Signaling Antibody Array was used to study the underlying mechanism. Additionally, the association between the survival and CDKL3 expression in ESCC were evaluated based on the TCGA data.

RESULTS

CDKL3 was highly expressed in ESCC tissues and cell lines. TE-1 cells transfected with CDKL3-shRNA-lentivirus significantly decreased CDKL3 expression and resulted in inhibiting cell proliferation, inducing the S-phase cell-cycle arrest, attenuating cellular invasive and increasing cell apoptosis. The expression of pERK1/2, p-Akt, p-Smad2, p-p38 mitogen-activated protein kinase, cleaved caspase-7, and phospho-Chk1 were significantly decreased by CDKL3 knockdown. In addition, high expression of CDKL3 was associated with shorter overall survival.

CONCLUSION

Our findings suggest that higher expression of CDKL3 is correlated with poor prognosis in patients with ESCC and play a vital role in the malignant phenotype of ESCC cell lines, which indicating that CDKL3 may be as a new therapeutic target in ESCC.