MLF1 interacting protein: a potential gene therapy target for human prostate cancer?

Overexpression of MLF1IP promotes colorectal cancer cell proliferation through BRCA1/AKT/p27 signaling pathway

BACKGROUND AND OBJECTIVE

MLF1IP has been correlated with the progression and prognosis of a few tumors. However, the role of MLF1IP in colorectal cancer remains unclear. Here, we examined the expression and function of MLF1IP in colorectal cancer and investigated possible molecular mechanisms.

METHODS

MLF1IP expressions in colorectal cancer tissues and cell lines were detected by quantitative real-time PCR, western blotting, and immunohistochemistry. In vitro and in vivo assays were performed to explore the function and underlying molecular mechanisms of MLF1IP in colorectal cancer.

RESULTS

The expression levels of MLF1IP were significantly up-regulated in colorectal cancer tissues and CRC cell lines (P < 0.05). High expression of MLF1IP was significantly associated with TNM stage, T classification, lymph node involvement, distant metastasis, and poor patient survival (all P < 0.05). Overexpressing MLF1IP promoted while silencing MLF1IP inhibited, the proliferation and clonogenicity of colorectal cancer cells and tumorigenicity in NOD/SCID mice (P < 0.05). In addition, we demonstrated that the pro-proliferative effect of MLF1IP on colorectal cancer cells was associated with mediating the G1-to-S phase transition. MLF1IP knockdown enhanced BRCA1 activity concomitantly with p-AKT downregulation and p27 upregulation, while overexpression of MLF1IP has the opposite effect. Moreover, upregulation of BRCA1 can partially abolish the proliferative activity of MLF1IP.

CONCLUSIONS

These findings suggest that MLF1IP may promote proliferation and tumorigenicity of colorectal cancer cells via BRCA1/AKT/p27 signaling axis, and thereby provides potential targets for colorectal cancer therapy.

Identification of Key Biomarkers and Pathways in Small-Cell Lung Cancer Using Biological Analysis

Background

Small-cell lung cancer (SCLC) is a major cause of carcinoma-related deaths worldwide. The aim of this study was to identify the key biomarkers and pathways in SCLC using biological analysis.

Methods

Key genes involved in the development of SCLC were identified by downloading three datasets from the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) were screened using the GEO2R online analyzer; for the functional annotation and pathway enrichment analysis of genes, Funrich software was used. Construction of protein-to-protein interaction (PPI) networks was accomplished using the Search Tool for the Retrieval of Interacting Genes (STRING), and network visualization and module identification were performed using Cytoscape.

Results

A total of 268 DEGs were ultimately obtained. The enriched functions and pathways of the upregulated DEGs included cell cycle, mitotic, and DNA replication, and the downregulated DEGs were enriched in epithelial-to-mesenchymal transition, serotonin degradation, and noradrenaline. Analysis of significant modules demonstrated that the upregulated genes are primarily concentrated in functions related to cell cycle and DNA replication. Kaplan-Meier analysis of hub genes revealed that they may promote the carcinogenesis and progression of SCLC. The result of ONCOMINE demonstrated that these 10 hub genes were significantly overexpressed in SCLC compared with normal samples.

Conclusion

Identification of the molecular functions and signaling pathways of participating DEGs can deepen the current understanding of the molecular mechanisms of SCLC. The knowledge gained from this work may contribute to the development of treatment options and improve the prognosis of SCLC in the future.

Common and distinct features of potentially predictive biomarkers in small cell lung carcinoma and large cell neuroendocrine carcinoma of the lung by systematic and integrated analysis

BACKGROUND

Large-cell neuroendocrine carcinoma of the lung (LCNEC) and small-cell lung carcinoma (SCLC) are neuroendocrine neoplasms. However, the underlying mechanisms of common and distinct genetic characteristics between LCNEC and SCLC are currently unclear. Herein, protein expression profiles and possible interactions with miRNAs were provided by integrated bioinformatics analysis, in order to explore core genes associated with tumorigenesis and prognosis in SCLC and LCNEC.

METHODS

GSE1037 gene expression profiles were obtained from the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) in LCNEC and SCLC, as compared with normal lung tissues, were selected using the GEO2R online analyzer and Venn diagram software. Gene ontology (GO) analysis was performed using Database for Annotation, Visualization and Integrated Discovery. The biological pathway analysis was performed using the FunRich database. Subsequently, a protein-protein interaction (PPI) network of DEGs was generated using Search Tool for the Retrieval of Interacting Genes and displayed via Cytoscape software. The PPI network was analyzed by the Molecular Complex Detection app from Cytoscape, and 16 upregulated hub genes were selected. The Oncomine database was used to detect expression patterns of hub genes for validation. Furthermore, the biological pathways of these 16 hub genes were re-analyzed, and potential interactions between these genes and miRNAs were explored via FunRich.

RESULTS

A total of 384 DEGs were identified. A Venn diagram determined 88 common DEGs. The PPI network was constructed with 48 nodes and 221 protein pairs. Among them, 16 hub genes were extracted, 14 of which were upregulated in SCLC samples, as compared with normal lung specimens, and 10 were correlated with the cell cycle pathway. Furthermore, 57 target miRNAs for 8 hub genes were identified, among which 31 miRNAs were correlated with the progression of carcinoma, drug-resistance, radio-sensitivity, or autophagy in lung cancer.

CONCLUSION

This study provided effective biomarkers and novel therapeutic targets for diagnosis and prognosis of SCLC and LCNEC.

Centromere protein U expression promotes non-small-cell lung cancer cell proliferation through FOXM1 and predicts poor survival

Purpose

Centromere protein U (CENPU) abnormally exhibits high expression in various types of human tumor tissues and participates in tumor progression; however, its expression pattern and biological function in lung cancer have not yet been elucidated. In the present study, we explored the clinical significance and biological function of CENPU in lung cancer.

Materials and methods

The Cancer Genome Atlas (TCGA) data analyses, quantitative real-time PCR (RT-PCR), and Western blotting were performed to quantify CENPU and FOXM1 expression in non-small-cell lung cancer (NSCLC) samples. Survival data were obtained from Kaplan–Meier plotter or PROGgene V2 prognostic database. The function of CENPU in lung cancer cell proliferation was determined using 5-ethynyl-2′-deoxyuridine (EdU), Cell Counting Kit-8 (CCK-8), and cell cycle assays, and the underlying mechanism was determined through bioinformatic analyses and validated by in vitro siRNA or plasmid transfection experiments.

Results

CENPU was abnormally overexpressed in NSCLC samples compared with matched paired normal tissues. Higher expression of CENPU predicted worse overall survival (OS) and relapse-free survival (RFS) in NSCLC patients. Knockdown of CENPU expression by siRNA significantly inhibited proliferation and delayed cell cycle progression of lung cancer cells. To figure out the mechanism, bioinformatic analyses were performed and the results showed that the transcription factor, FOXM1, positively correlated with CENPU. Further in vitro experiments indicated that FOXM1 was the possible downstream transcription factor of CENPU as the knockdown of CENPU led to lower expression of FOXM1 and the overexpression of FOXM1 significantly reversed the inhibition of proliferation caused by CENPU knockdown. Furthermore, FOXM1 was highly expressed in NSCLC. The knockdown of FOXM1 also attenuated proliferation and induced G1 arrest in lung cancer cells.

Conclusion

CENPU was highly expressed in NSCLC tissues, wherein it promoted lung cancer cell proliferation via the transcription factor, FOXM1, which could be a potential target for therapeutic strategies.

Integrated analysis reveals key genes with prognostic value in lung adenocarcinoma

Background

Lung cancer is one of the most common malignant tumors. Despite advances in lung cancer therapies, prognosis of non-small-cell lung cancer is still unfavorable. The aim of this study was to identify the prognostic value of key genes in lung tumorigenesis.

Methods

Differentially expressed genes (DEGs) were screened out by GEO2R from three Gene Expression Omnibus cohorts. Common DEGs were selected for Kyoto Encyclopedia of Genes and Genomes pathway analysis and Gene Ontology enrichment analysis. Protein– protein interaction networks were constructed by the STRING database and visualized by Cytoscape software. Hub genes, filtered from the CytoHubba, were validated using the Gene Expression Profiling Interactive Analysis database, and their genomic alterations were identified by performing the cBioportal. Finally, overall survival analysis of hub genes was performed using Kaplan–Meier Plotter.

Results

From three datasets, 169 DEGs (70 upregulated and 99 downregulated) were identified. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway analyses showed that upregulated DEGs were significantly enriched in cell cycle, p53 pathway, and extracellular matrix–receptor interactions; the downregulated DEGs were significantly enriched in PPAR pathway and tyrosine metabolism. The protein–protein interaction network consisted of 71 nodes and 305 edges, including 49 upregulated and 22 downregulated genes. The hub genes, including AURKB, BUB1B, KIF2C, HMMR, CENPF, and CENPU, were overexpressed compared with the normal group by Gene Expression Profiling Interactive Analysis analysis, and associated with reduced overall survival in lung cancer patients. In the genomic alterations analysis, two hotspot mutations (S2021C/F and E314K/V) were identified in Pfam protein domains.

Conclusion

DEGs, including AURKB, BUB1B, KIF2C, HMMR, CENPF, and CENPU, might be potential biomarkers for the prognosis and treatment of lung adenocarcinoma.

The effect of centromere protein U silencing by lentiviral mediated RNA interference on the proliferation and apoptosis of breast cancer

Centromere protein U (CENPU) is a novel transcriptional repressor that is associated with different types of cancer. However, its function in breast cancer is poorly understood. In the present study, it was identified that CENPU was highly expressed in breast cancer tissues compared with expression in normal breast tissues (P=0.001). Furthermore, the CENPU mRNA level in tumors was often elevated, compared with the matched adjacent normal breast cancer tissue specimens in the dataset from The Cancer Genome Atlas database (n=106; P<0.001). To understand the function of CENPU in human breast carcinogenesis, its effects on the proliferation, apoptosis and cell cycle progression of MDA-MB-231 cells were examined using the lentiviral-mediated CENPU knockdown approach. The RNA and protein expression levels in the transfected cells were monitored using reverse transcription-quantitative polymerase chain reaction and western blotting, respectively. The mRNA and protein expression levels of the CENPU gene were significantly lower in the CENPU-shRNA transfected cells than in the control (P<0.01), indicating successful gene expression knockdown. Post-transfection, cell counting and MTT analysis revealed that the proliferation activity was significantly suppressed in CENPU knockdown cells relative to the control (P<0.01). Additionally, fluorescence activated cell sorting analysis revealed that the (G2+S) phase fraction was significantly declined in CENPU knockdown cells relative to the control; while the G1 phase fraction was significantly increased (P<0.01) and the percentage of the apoptotic cells was significantly increased (P<0.01). In conclusion, downregulation of CENPU gene expression may inhibit cell proliferation and cell cycle progression, and increase the apoptosis of the breast cancer cells. These results suggested a possible function of this protein in breast cancer pathogenesis and prognosis.

Centromere protein U is a potential target for gene therapy of human bladder cancer

To investigate the role of centromere protein U (CENPU) in human bladder cancer (BCa), CENPU gene expression was evaluated in human BCa tissues. We used real-time quantitative PCR (qPCR) and found that CENPU gene expression in human BCa tissues was higher compared to that observed in cancer-adjacent normal tissues. High CENPU expression was found to be strongly correlated with tumor size and TNM stage. Kaplan-Meier survival analysis indicated that high CENPU levels were associated with reduced survival. We used a lentivirus to silence endogenous CENPU gene expression in the BCa T24 cell line. CENPU knockdown was confirmed by qPCR. Cellomic imaging and BrdU assays showed that cell proliferation was significantly reduced in the CENPU-silenced cells compared to that noted in the control cells. Flow cytometry revealed that in the CENPU-silenced cells the cell cycle was arrested at the G1 phase relative to that in the control cells. In addition, apoptosis was significantly increased in the CENPU-silenced cells. Giemsa staining showed that CENPU-silenced cells, compared to control cells, displayed a significantly lower number of cell colonies. The genome-wide effect of CENPU knockdown showed that a total of 1,274 differentially expressed genes was found, including 809 downregulated genes and 465 upregulated genes. Network analysis by Ingenuity Pathway Analysis (IPA) resulted in 25 distinct signaling pathways, including the top-ranked network: ‘Cellular compromise, organismal injury and abnormalities, skeletal and muscular disorders’. In-depth IPA analysis revealed that CENPU was associated with the HMGB1 signaling pathway. qPCR and western blot analysis demonstrated that in the HMGB1 signaling pathway, CENPU knockdown downregulated expression levels of ILB, CXCL8, RAC1 and IL1A. In conclusion, our data may provide a potential pathway signature for therapeutic targets with which to treat BCa.