CUX1-Transcriptional Master Regulator of Tumor Progression in Pancreatic Neuroendocrine Tumors

Identification and validation of genes associated with prognosis of cisplatin-resistant ovarian cancer

PURPOSE

To investigate the role of prognostic genes related to cisplatin resistance in ovarian cancer during disease progression.

METHOD

The gene expression profile of the NCI-60 cell line was acquired through comprehensive analysis of the GEO database accession GSE116439. We performed a thorough analysis of gene expression differences in samples from seven individuals exposed to cisplatin concentrations of 0 nM compared to seven samples exposed to 15000 nM over a 24-h period. Key genes were initially identified through LASSO regression, followed by their enrichment through differential gene function analysis (GO) and pathway enrichment analysis (KEGG). Subsequently, a prognostic risk model was established for these key genes. The prognostic model's performance was assessed through K-M survival curves and ROC curves. To examine the variance in immune cell infiltration between the high and low-risk groups, CIBERSORTx analysis was employed. Finally, validation of prognostic gene expression in cisplatin-resistant ovarian cancer was carried out using clinical samples, employing RT-qPCR and Western Blot techniques.

RESULTS

A total of 132 differential genes were found between cisplatin resistance and control group, and 8 key prognostic genes were selected by analysis, namely VPS13B, PLGRKT, CDKAL1, TBC1D22A, TAP1, PPP3CA, CUX1 and PPP1R15A. The efficacy of the risk assessment model derived from prognostic biomarkers, as indicated by favorable performance on both Kaplan-Meier survival curves and ROC curves. Significant variations in the abundance of Macrophages M1, T cells CD4 memory resting, T cells follicular helper, and T cells gamma delta were observed between the high and low-risk groups. To further validate our findings, RT-qPCR and Western Blot analyses were employed, confirming differential expression of the identified eight key genes between the two groups.

CONCLUSION

VPS13B, TBC1D22A, PPP3CA, CUX1 and PPP1R15A were identified as poor prognostic genes of cisplatin resistance in ovarian cancer, while PLGRKT, CDKAL1 and TAP1 were identified as good prognostic genes. This offers a novel perspective for future advancements in ovarian cancer treatment, suggesting potential avenues for the development of new therapeutic targets.

Concomitant inhibition of PI3K/mTOR signaling pathways boosts antiproliferative effects of lanreotide in bronchopulmonary neuroendocrine tumor cells

Introduction: Somatostatin analogues (SSAs) are commonly used in the treatment of hormone hypersecretion in neuroendocrine tumors (NETs), however the extent to which they inhibit proliferation is much discussed. Objective: We studied the antiproliferative effects of novel SSA lanreotide in bronchopulmonary NETs (BP-NETs). We focused on assessing whether pretreating cells with inhibitors for phosphatidylinositol 3-kinase (PI3K) and mammalian target for rapamycin (mTOR) could enhance the antiproliferative effects of lanreotide. Methods: BP-NET cell lines NCI-H720 and NCI-H727 were treated with PI3K inhibitor BYL719 (alpelisib), mTOR inhibitor everolimus and SSA lanreotide to determine the effect on NET differentiation markers, cell survival, proliferation and alterations in cancer-associated pathways. NT-3 cells, previously reported to express somatostatin receptors (SSTRs) natively, were used as control for SSTR expression. Results: SSTR2 was upregulated in NCI-H720 and NT-3 cells upon treatment with BYL719. Additionally, combination treatment consisting of BYL719 and everolimus plus lanreotide tested in NCI-H720 and NCI-H727 led to diminished cell proliferation in a dose-dependent manner. Production of proteins activating cell death mechanisms was also induced. Notably, a multiplexed gene expression analysis performed on NCI-H720 revealed that BYL719 plus lanreotide had a stronger effect on the downregulation of mitogens than lanreotide alone. Discussion/Conclusion: We report a widespread analysis of changes in BP-NET cell lines at the genetic/protein expression level in response to combination of lanreotide with pretreatment consisting of BYL719 and everolimus. Interestingly, SSTR expression reinduction could be exploited in therapeutic and diagnostic applications. The overall results of this study support the evaluation of combination-based therapies using lanreotide in preclinical studies to further increase its antiproliferative effect and ultimately facilitate its use in high-grade tumors.

Role of PAX6, TRPA1, BCL11B, MCOLN2, CUX1, EMX1 in colorectal cancer and osteosarcoma

Colorectal cancer is a cancer that arises from the abnormal growth of cells in the colon or rectum. Osteosarcoma (OS) is a common primary bone tumor with high degree of malignancy. The configuration files for colorectal cancer dataset GSE142279 and OS datasets GSE197158 and GSE206448 were downloaded from Gene Expression Omnibus database using the platforms GPL20795, GPL20301, and GPL24676. Differentially expressed genes (DEGs) were screened and weighted gene co-expression network analysis (WGCNA) was performed. Construction and analysis of protein-protein interactions (PPI) network. Functional enrichment analysis, gene set enrichment analysis (GSEA) were performed. A heat map of gene expression was drawn. The Comparative Toxicogenomics Database (CTD) was used to find the diseases most associated with the core genes. TargetScan was used to screen miRNAs regulating DEGs. According to the Gene Ontology (GO) analysis, DEGs are mainly enriched in acetylcholine binding receptor activity involved in Wnt signaling pathway, cell polarity pathway, PI3K-Akt signaling pathway, receptor regulator activity, cytokine-cytokine receptor interaction, transcriptional misregulation in cancer, and inflammation-mediated regulation of tryptophan transport. In the Metascape enrichment analysis, GO enrichment items related to the regulation of Wnt signaling pathway, regulation of muscle system process, and regulation of actin filament-based movement. Eight core genes (CUX1, NES, BCL11B, PAX6, EMX1, MCOLN2, TRPA1, TRPC4) were identified. CTD showed that 4 genes (CUX1, EMX1, TRPA1, BCL11B) were associated with colorectal neoplasms, colorectal tumors, colonic diseases, multiple myeloma, OS, and inflammation. PAX6, TRPA1, BCL11B, MCOLN2, CUX1, and EMX1 are highly expressed in colorectal cancer and OS, and the higher the expression level, the worse the prognosis.

Association between DNA Methylation in the Core Promoter Region of the CUT-like Homeobox 1 (CUX1) Gene and Lambskin Pattern in Hu Sheep

CUT-like homeobox 1 (CUX1) has been proven to be a key regulator in sheep hair follicle development. In our previous study, CUX1 was identified as a differential expressed gene between Hu sheep lambskin with small wave patterns (SM) and straight wool patterns (ST); however, the exact molecular mechanism of CUX1 expression has been obscure. As DNA methylation can regulate the gene expression, the potential association between CUX1 core promotor region methylation and lambskin pattern in Hu sheep was explored in the present study. The results show that the core promoter region of CUX1 was present at (-1601-(-1) bp) upstream of the transcription start site. A repressive region (-1151-(-751) bp) was also detected, which had a strong inhibitory effect on CUX1 promoter activity. Bisulfite amplicon sequencing revealed that no significant difference was detected between the methylation levels of CUX1 core promoter region in SM tissues and ST tissues. Although the data demonstrated the differential expression of CUX1 between SM and ST probably has no association with DNA methylation, the identification of the core region and a potential repressive region of CUX1 promoter can enrich the role of CUX1 in Hu sheep hair follicle development.

Aberrant transcription factors in the cancers of the pancreas

Transcription factors (TFs) are essential for proper activation of gene set during the process of organogenesis, differentiation, lineage specificity. Reactivation or dysregulation of TFs regulatory networks could lead to deformation of organs, diseases including various malignancies. Currently, understanding the mechanism of oncogenesis became necessity for the development of targeted therapeutic strategy for different cancer types. It is evident that many TFs go awry in cancers of the pancreas such as pancreatic ductal adenocarcinoma (PDAC) and pancreatic neuroendocrine neoplasms (PanNENs). These mutated or dysregulated TFs abnormally controls various signaling pathways in PDAC and PanNENs including RTK, PI3K-PTEN-AKT-mTOR, JNK, TGF-β/SMAD, WNT/β-catenin, SHH, NOTCH and VEGF which in turn regulate different hallmarks of cancer. Aberrant regulation of such pathways have been linked to the initiation, progression, metastasis, and resistance in pancreatic cancer. As of today, a number of TFs has been identified as crucial regulators of pancreatic cancer and a handful of them shown to have potential as therapeutic targets in pre-clinical and clinical settings. In this review, we have summarized the current knowledge on the role and therapeutic usefulness of TFs in PDAC and PanNENs.

Identification of vital modules and genes associated with heart failure based on weighted gene coexpression network analysis

Aims

Heart failure (HF) is a chronic heart disease with a high incidence and mortality. Due to the regulatory complexity of gene coexpression networks, the underlying hub genes regulation in HF remain incompletely appreciated. We aimed to explore potential key modules and genes for HF using weighted gene coexpression network analysis (WGCNA).

Methods and results

The expression profiles by high throughput sequencing of heart tissues samples from HF and non‐HF samples were obtained from the Gene Expression Omnibus database. Differentially expressed genes (DEGs) between HF and non‐HF samples were firstly identified. Then, a coexpression network was constructed to identify key modules and potential hub genes. The biological functions of potential hub genes were analysed by Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analyses. Finally, a protein–protein interaction (PPI) network was constructed using the STRING online tool. A total of 135 DEGs (133 up‐regulated and 2 down‐regulated DEGs) between HF and non‐HF samples were identified in the GSE135055 and GSE123976 datasets. Moreover, a total of 38 modules were screened based on WGCNA in the GSE135055 dataset, and six potential hub genes (UCK2, ASB1, CCNI, CUX1, IRX6, and STX16) were screened from the key module by setting the gene significance over 0.2 and the module membership over 0.8. Furthermore, 78 potential hub genes were obtained by taking the intersection of the 135 DEGs and all genes in the key module, and enrichment analysis revealed that they were mainly involved in the MAPK and PI3K‐AKT signalling pathways. Finally, in a PPI network constructed with the 78 potential hub genes, CUX1 and ASB1 were identified as hub genes in HF because they were also identified as potential hub genes in the WGCNA.

Conclusions

To the best of our knowledge, our study is the first to employ WGCNA to identify the key module and hub genes for HF. Our study identified a module and two genes that might play important roles in HF, which may provide potential biomarkers for the diagnosis of HF and improve our knowledge of the molecular mechanisms underlying HF.

CUX1 Facilitates the Development of Oncogenic Properties Via Activating Wnt/β-Catenin Signaling Pathway in Glioma

Background: Homeobox cut like 1 (CUX1), which often presents aberrated expression in many cancer cells, exerts a crucial role in tumorigenesis. Evidence describing CUX1 in gliomagenesis is scarce, and the effects of CUX1 on the Wnt/β-catenin pathway have not been reported. Our study aimed to explore the biological functions and molecular mechanisms involved in CUX1 activity in glioma.

Methods: Datasets for bioinformatics analysis were obtained from the GEO, TCGA, CGGA, GTEX and CCLE databases. qRT-PCR, western blotting (WB), and immunohistochemistry (IHC) assays were used to investigate the expression patterns of CUX1 among glioma and brain tissues. CUX1 knockdown and overexpression vectors were transfected into glioma cell lines, the CCK-8, clone formation assay, wound healing, Transwell assay, and flow cytometry were performed to detect changes in cell viability, invasiveness, and the cell cycle. WB and immunofluorescence (IF) assays were used to explore changes in cell cycle-related and Wnt/β-catenin signaling protein levels.

Results: Overexpression of CUX1 was identified in glioma tissues, and especially in glioblastoma (GBM), when compared to normal controls and correlated with poor prognosis. In comparison with untreated cells, TJ905 glioma cells overexpressing CUX1 showed higher proliferation and invasion abilities and S phase cell-cycle arrest, while the knockdown of CUX1 suppressed cell invasive ability and induced G1 phase arrest. Active Wnt/β-catenin signaling was enriched and clustered in a CUX1-associated GSEA/GSVA analysis. IF and WB assays indicated that CUX1 regulated the distribution of Axin2/β-catenin in glioma cells and regulated the expression of proteins downstream of the Wnt/β-catenin signaling pathway, suggesting that CUX1 served as an upstream positive regulator of the Wnt/β-catenin pathway. Finally, the knockdown of Axin2 or β-catenin could reverse the tumor-promoting effects caused by CUX1 overexpression, suggesting that CUX1 induced gliomagenesis and malignant phenotype by activating the Wnt/β-catenin signaling pathway.

Conclusion: Our data suggested that the transcription factor CUX1 could be a novel therapeutic target for glioma with gene therapy.