NDRG2 gene expression pattern in ovarian cancer and its specific roles in inhibiting cancer cell proliferation and suppressing cancer cell apoptosis

NDRG2 acts as a negative regulator of the progression of small-cell lung cancer through the modulation of the PTEN-AKT-mTOR signalling cascade

N-myc downstream-regulated gene 2 (NDRG2) has been recognised as a negative regulator of the progression of numerous tumours, yet its specific role in small-cell lung carcinoma (SCLC) is not fully understood. The purpose of the current study was to investigate the biological role and mechanism of NDRG2 in SCLC. Initial investigation using the Gene Expression Omnibus (GEO) dataset revealed marked downregulation of NDRG2 transcripts in SCLC. The decreased abundance of NDRG2 in SCLC was verified by examining clinical specimens. Increasing NDRG2 expression in SCLC cell lines caused significant changes in cell proliferation, cell cycle progression, colony formation, and chemosensitivity. NDRG2 overexpression decreased the levels of phosphorylated PTEN, AKT and mTOR. In PTEN-depleted SCLC cells, the upregulation of NDRG2 did not result in any noticeable impact on AKT or mTOR activation. Additionally, the reactivation of AKT reversed the antitumour effects of NDRG2 in SCLC cells. Notably, increasing NDRG2 expression retarded the growth of SCLC cell-derived xenografts in vivo. In conclusion, NDRG2 serves as an inhibitor of SCLC, and its cancer-inhibiting effects are achieved through the suppression of AKT/mTOR via the activation of PTEN. This work suggests that NDRG2 is a potential druggable target for SCLC treatment.

NDRG2 Promotes Lens Epithelial Cells Senescence via NLRP3/Caspase1-Mediated Pyroptosis

OBJECT

This study aims to investigate the molecular mechanism of NDRG2 (N-myc downstream-regulated gene 2) in the cell senescence of lens endothelial cells.

METHODS

Lens endothelial cells (SRA01/04) were irradiated with UVB at different times. Cell viability was measured by CCK-8 kit and cell cycle was detected by flow cytometry. Cell senescence was detected using SA-β-gal staining. Western blot was utilized to detect the expressions of p53, p21 and NDRG2. TUNEL staining and flow cytometry were used to detect apoptosis and pyroptosis.

RESULTS

UVB-irradiation significantly induces cell senescence and the expression of NDRG2, p53 and p21 in SRA01/04 cells was up-regulated. Down-regulation of NDRG2 inhibited UVB-induced cell senescence, significantly reversed pyroptosis and promoted cell proliferation. UVB-induced pyroptosis is closely related to caspase-1/NLRP3 axis.

CONCLUSION

Our study confirmed downregulation of NDRG2 significantly inhibited UVB radiation-induced cell senescence by regulating caspase-1/NLRP3-mediated pyroptosis.

Targeted Overexpression of NDRG2 using Survivin Promoter Reduces Viability and Invasiveness of A549 Cell Line

Background

Anti-tumor effects of N-myc Downstream Regulated Gene2 (NDRG2) have been demonstrated in many tumors. In the present study, NDRG2 was specifically overexpressed in lung cancer cell line using Survivin Promoter (Sur-P). Then, the effects of NDRG2 overexpression on viability, apoptosis, migration, and invasion of A549 cells were evaluated.

Methods

Recombinant pAdenoVator-Sur-P-NDRG2-IRES-GFP plasmid harboring NDRG2 gene under transcriptional control of Sur-P and mock plasmid were constructed. A549 lung tumor cells and LX-2 cells (non-tumor cell line) were transfected with pAdenoVator-Sur-P-NDRG2-IRES-GFP, pAdenoVator-CMV-NDRG2-IRES-GFP, or mock plasmids. Tumor specificity of Sur-P was evaluated using fluorescent microscopy for GFP expression. The effects of NDRG2 overexpression on cell viability, apoptosis, and migration of A549 cells were measured using MTT, annexinV/7-AAD flow cytometry, and transwell migration assay, respectively. NDRG2 and matrix metalloproteinase-2 (MMP-2) expression were measured using real time-PCR.

Results

pAdenoVator-Sur-P-NDRG2-IRES-GFP transfection resulted in a huge GFP expression in A549 cells, but not in LX-2 cells. The results of real time-PCR analysis also showed that pAdenoVator-Sur-P-NDRG2-IRES-GFP transfection led to an abundant NDRG2 expression in A549 cells. NDRG2 overexpression decreased A549 cell viability through increasing cell apoptosis. In addition, migration, invasion, and MMP-2 expression decreased following NDRG2 overexpression in A549 cells.

Conclusion

The findings indicate that the targeted overexpression of NDRG2 using Sur-P can reduce the viability and invasiveness of A549 cells, suggesting possible benefits of this approach in lung cancer therapy.

The Crosstalk Between Signaling Pathways and Cancer Metabolism in Colorectal Cancer

Colorectal cancer (CRC) is one of the most frequently diagnosed cancers worldwide. Metabolic reprogramming represents an important cancer hallmark in CRC. Reprogramming core metabolic pathways in cancer cells, such as glycolysis, glutaminolysis, oxidative phosphorylation, and lipid metabolism, is essential to increase energy production and biosynthesis of precursors required to support tumor initiation and progression. Accumulating evidence demonstrates that activation of oncogenes and loss of tumor suppressor genes regulate metabolic reprogramming through the downstream signaling pathways. Protein kinases, such as AKT and c-MYC, are the integral components that facilitate the crosstalk between signaling pathways and metabolic pathways in CRC. This review provides an insight into the crosstalk between signaling pathways and metabolic reprogramming in CRC. Targeting CRC metabolism could open a new avenue for developing CRC therapy by discovering metabolic inhibitors and repurposing protein kinase inhibitors/monoclonal antibodies.

Integrated multi-omics analysis of ovarian cancer using variational autoencoders

Cancer is a complex disease that deregulates cellular functions at various molecular levels (e.g., DNA, RNA, and proteins). Integrated multi-omics analysis of data from these levels is necessary to understand the aberrant cellular functions accountable for cancer and its development. In recent years, Deep Learning (DL) approaches have become a useful tool in integrated multi-omics analysis of cancer data. However, high dimensional multi-omics data are generally imbalanced with too many molecular features and relatively few patient samples. This imbalance makes a DL based integrated multi-omics analysis difficult. DL-based dimensionality reduction technique, including variational autoencoder (VAE), is a potential solution to balance high dimensional multi-omics data. However, there are few VAE-based integrated multi-omics analyses, and they are limited to pancancer. In this work, we did an integrated multi-omics analysis of ovarian cancer using the compressed features learned through VAE and an improved version of VAE, namely Maximum Mean Discrepancy VAE (MMD-VAE). First, we designed and developed a DL architecture for VAE and MMD-VAE. Then we used the architecture for mono-omics, integrated di-omics and tri-omics data analysis of ovarian cancer through cancer samples identification, molecular subtypes clustering and classification, and survival analysis. The results show that MMD-VAE and VAE-based compressed features can respectively classify the transcriptional subtypes of the TCGA datasets with an accuracy in the range of 93.2-95.5% and 87.1-95.7%. Also, survival analysis results show that VAE and MMD-VAE based compressed representation of omics data can be used in cancer prognosis. Based on the results, we can conclude that (i) VAE and MMD-VAE outperform existing dimensionality reduction techniques, (ii) integrated multi-omics analyses perform better or similar compared to their mono-omics counterparts, and (iii) MMD-VAE performs better than VAE in most omics dataset.