Prognostic relevance of topoisomerase II α and minichromosome maintenance protein 6 expression in colorectal cancer

A High MCM6 Proliferative Index in Atypical Meningioma Is Associated with Shorter Progression Free and Overall Survivals

The aim of this study was to evaluate the prognostic value of MCM6, in comparison with Ki-67, in two series of grade 1 and 2 meningiomas, and to evaluate its correlation with methylation classes. The first cohort included 100 benign (grade 1, World Health Organization 2021) meningiomas, and the second 69 atypical meningiomas (grade 2). Immunohistochemical Ki-67 and MCM6 labeling indices (LI) were evaluated independently by two observers. Among the atypical meningiomas, 33 cases were also studied by genome-wide DNA methylation. In grade 2 meningiomas, but not grade 1, both Ki-67 and MCM6 LIs were correlated with PFS (p = 0.004 and p = 0.005, respectively; Cox univariate analyses). Additionally, MCM6 was correlated with overall survival only in univariate analysis. In a multivariate model, including mitotic index, Ki-67, MCM6, age, sex, and the quality of surgical resection, only MCM6 was correlated with PFS (p = 0.046). Additionally, we found a significant correlation between PTEN loss and high MCM6 or Ki-67 LIs. Although no correlation was found with the methylation classes and subtypes returned by the meningioma algorithm MNGv2.4., MCM6 LI was significantly correlated with the methylation of 2 MCM6 gene body loci. In conclusion, MCM6 is a relevant prognostic marker in atypical meningiomas. This reproducible and easy-to-use marker allows the identification of a highly aggressive subtype of proliferative meningiomas, characterized notably by frequent PTEN losses, which was previously reported to be sensitive to histone deacetylase inhibitors.

Identification of a 5-Nutrient Stress-Sensitive Gene Signature to Predict Survival for Colorectal Cancer

Background

The high heterogeneity and the complexity of the tumor microenvironment of colorectal cancer (CRC) have enhanced the difficulty of prognosis prediction based on conventional clinical indicators. Recent studies revealed that tumor cells could overcome various nutritional deficiencies by gene regulation and metabolic remodeling. However, whether differentially expressed genes (DEGs) in CRC cells under kinds of nutrient deficiency could be used to predict prognosis remained unveiled.

Methods

Three datasets (GSE70976, GSE13548, and GSE116087), in which colon cancer cells were, respectively, cultured in serum-free, glucose-free, or glutamine-free medium, were included to delineate the profiles of gene expression by nutrient stress. DEGs were figured out in three datasets, and gene functional analysis was performed. Survival analyses and Cox proportional hazards model were then used to identify nutrient stress sensitive genes in CRC datasets (GSE39582 and TCGA COAD). Then, a 5-gene signature was constructed and the risk scores were also calculated. Survival analyses, cox analyses, and nomogram were applied to predict the prognosis of patients with colorectal cancer. The effectiveness of the risk model was also tested.

Results

A total of 48 genes were found to be dysregulated in serum, glucose, or glutamine-deprived CRC cells, which were mainly enriched in cell cycle and endoplasmic reticulum stress pathways. After further analyses, 5 genes, MCM5, MCM6, CDCA2, GINS2, and SPC25, were identified to be differentially expressed in CRC and be related to prognosis of in CRC datasets. We used the above nutrient stress-sensitive genes to construct a risk scoring model. CRC samples in the datasets were divided into low-risk and high-risk groups. Data showed that higher risk scores were associated with better outcomes and risk scores decreased significantly with tumor procession. Moreover, the risk score could be used to predict the probability of survival based on nomogram.

Conclusions

The 5-nutrient stress-sensitive gene signature could act as an independent biomarker for survival prediction of CRC patients.

The Effects of the Food Additive Titanium Dioxide (E171) on Tumor Formation and Gene Expression in the Colon of a Transgenic Mouse Model for Colorectal Cancer

Titanium dioxide (TiO2) is present in many different food products as the food additive E171, which is currently scrutinized due to its potential adverse effects, including the stimulation of tumor formation in the gastrointestinal tract. We developed a transgenic mouse model to examine the effects of E171 on colorectal cancer (CRC), using the Cre-LoxP system to create an Apc-gene-knockout model which spontaneously develops colorectal tumors. A pilot study showed that E171 exposed mice developed colorectal adenocarcinomas, which were accompanied by enhanced hyperplasia in epithelial cells, lymphatic nodules at the base of the polyps, and increased tumor size. In the main study, tumor formation was studied following the exposure to 5 mg/kgbw/day of E171 for 9 weeks (Phase I). E171 exposure showed a statistically nonsignificant increase in the number of colorectal tumors in these transgenic mice, as well as a statistically nonsignificant increase in the average number of mice with tumors. Gene expression changes in the colon were analyzed after exposure to 1, 2, and 5 mg/kgbw/day of E171 for 2, 7, 14, and 21 days (Phase II). Whole-genome mRNA analysis revealed the modulation of genes in pathways involved in the regulation of gene expression, cell cycle, post-translational modification, nuclear receptor signaling, and circadian rhythm. The processes associated with these genes might be involved in the enhanced tumor formation and suggest that E171 may contribute to tumor formation and progression by modulation of events related to inflammation, activation of immune responses, cell cycle, and cancer signaling.

Potential molecular target screening and bioinformatics analysis of cholangiocarcinoma based on GEO database

BACKGROUND

Cholangiocarcinoma is a highly malignant tumor with a poor prognosis. Targeted therapy is important for the treatment of cholangiocarcinoma, and it is therefore of great clinical importance to identify novel molecular targets for targeted therapy of this malignancy.

AIM

To identify potential molecular targets for the treatment of cholangiocarcinoma and identify the key genes involved in cholangiocarcinoma by bioinformatics analysis.

METHODS

We downloaded two sets of cholangiocarcinoma expression profile data from GEO database. GEO2R online analysis tool was used to screen differentially expressed genes in cholangiocarcinoma tumor tissues and normal tissues, and we performed GO enrichment analysis, KEGG pathway analysis, and protein interaction network for differentially expressed genes. We used Cytoscape software to calculate key genes. The GEPIA database was used to verify the expression of hub genes in cholangiocarcinoma tissues.

RESULTS

A total of 158 differentially expressed genes were identified. GO enrichment analysis showed that these differential genes were mainly involved in the cellular response to zinc ion, negative regulation of growth, cell adhesion, metabolic process, and protein homotetramerization. They were enriched in exosomes, extracellular spaces, elastic fibers, and organelle membranes. The main molecular functions are related to heparin binding, cysteine-type endopeptidase inhibitor activity, protein homodimerization activity, receptor binding, and pyridoxal phosphate binding. KEGG pathway analysis showed that differential genes are mainly involved in processes such as mineral absorption, carbon and propanoate metabolism, PPAR signaling pathway, and fatty acid degradation. A protein interaction network diagram was constructed based on the String database, and the CytoHubba plug-in of the Cytoscape software was used to calculate the key genes. The key genes were all up-regulated ones. GEPIA analysis verified that the expression of key genes in cholangiocarcinoma tissues was significantly higher than that in normal tissues.

CONCLUSION

In this study, eight key genes related to cholangiocarcinoma were identified, including NUSAP1, TOP2A, RAD51AP1, MCM4, KIAA0101, CDCA5, TYMS, and ZWINT. These genes provide new ideas for in-depth study of the targeted therapy of cholangiocarcinoma, and are expected to become new molecular therapeutic targets.

Comprehensive Bioinformatics Analysis of mRNA Expression Profiles and Identification of a miRNA-mRNA Network Associated with the Pathogenesis of Low-Grade Gliomas

Purpose

Low-grade glioma is the most common type of primary intracranial tumour, and the overall survival of patients with low-grade glioma (LGG) has shown no significant improvement over the past few decades. Therefore, it is crucial to understand the precise molecular mechanisms involved in the carcinogenesis of LGG.

Methods

To investigate the regulatory mechanisms of mRNA–miRNA networks related to LGG, in the present study, a comprehensive analysis of the genomic landscape between low-grade gliomas and normal brain tissues from the GEO and TCGA datasets was first conducted to identify differentially expressed genes (DEGs) and differentially expressed miRNAs in LGG. Following a series of analyses, including WGCNA, GO and KEGG analyses, PPI and key model analyses, and survival analysis of the DEGs with clinical phenotypes, the potential key genes were screened and identified, and the related miRNA–mRNA networks were subsequently constructed through miRWalk 3.0. Finally, the potential miRNA–mRNA networks were further validated in CGGA (Chinese Glioma Genome Atlas) datasets and clinical specimens by qRT-PCR.

Results

In our results, six hub genes, MELK, NCAPG, KIF4A, NUSAP1, CEP55, and TOP2A, were ultimately identified. Two regulatory pathways, miR-495-3p-TOP2A and miR-1224-3p-MELK, that regulate the pathogenesis of LGG were ultimately identified. Furthermore, the expression of miR-495-3p-TOP2A and miR-1224-3p-MELK in solid tissues was validated by qRT-PCR.

Conclusion

Our study identified hub genes and related miRNA–mRNA regulatory pathways that contribute to the carcinogenesis of LGG, which may help us reveal the mechanisms underlying the development of LGG.

High MCM6 Expression as a Potential Prognostic Marker in Clear-cell Renal Cell Carcinoma

AIM

Minichromosome maintenance (MCM) proteins are involved in initiation of DNA replication and cell-cycle progression. Loss of MCM function results in genomic instability and causes carcinogenesis. Among MCM genes, the role and prognostic value of MCM6 expression in clear-cell renal cell carcinoma (ccRCC) has not been elucidated.

MATERIALS AND METHODS

We assessed the mRNA expression level of MCM6 using the Gene Expression Profiling Interactive Analysis database and investigated MCM6 protein expression by immunohistochemistry in 238 ccRCC cases.

RESULTS

High MCM6 expression was significantly associated with increasing tumor size, pT, stage, tumor necrosis, and metastasis. Furthermore, high MCM6 expression was significantly associated with shorter overall and disease-free survival, and was an independent unfavorable prognostic marker. Regarding patients with metastasis, high MCM6-expressing ccRCC conferred significantly shorter survival than for those with low expression.

CONCLUSION

A high MCM6 expression level may be a promising biomarker to predict tumor progression, metastasis, and survival in patients with ccRCC.

The DNA replication regulator MCM6: An emerging cancer biomarker and target

MCM6 is a significant DNA replication regulator that plays a crucial role in sustaining the cell cycle. In many cancer cells, MCM6 expression is enhanced. For example, persistently increased expression of MCM6 promotes the formation, development and progression of hepatocellular carcinoma (HCC). Up- and down-regulation studies have indicated that MCM6 regulates cell cycle, proliferation, metastasis, immune response and the maintenance of the DNA replication system. MCM6 can also regulate downstream signaling such as MEK/ERK thus promoting carcinogenesis. Accordingly, MCM6 may represent a sensitive and specific biomarker to predict adverse progression and poor outcome. Furthermore, inhibition of MCM6 may be an effective cancer treatment. The present review summarizes the latest results on the inactivating and activating functions of MCM6, underlining its function in carcinogenesis. Further studies of the carcinogenic functions of MCM6 may provide novel insight into cancer biology and shed light on new approaches for cancer diagnosis and treatment.

Identification of the DNA Replication Regulator MCM Complex Expression and Prognostic Significance in Hepatic Carcinoma

BACKGROUND

The microliposome maintenance (MCM) complex, MCM2-7, is revealed to be involved in multiple cellular processes and plays a key role in the development and progression of human cancers. However, the MCM complex remains poorly elaborated in hepatic carcinoma (HCC).

METHODS

In the study, we found the mRNA and protein level by bioinformatics. We also explored the prognostic value, genetic alteration, interaction network, and functional enrichment of MCM2-7. The MCM expression and correlation among these MCMs in HCC cell lines were identified by western blot.

RESULTS

MCM2-7 was significantly increased in HCC tissues compared to normal liver tissues. The high level of MCM2-7 had a positive correlation with poor prognosis. However, MCM2-7 alterations were not correlated with poor OS. MCMs were both increased in HCC cell lines compared to the normal hepatocyte cell line. Furthermore, the positive correlation was found among MCMs in HCC cell lines.

CONCLUSIONS

The MCM complex was increased in HCC tissues and cell lines and negatively correlated with prognosis, which might be important biomarkers for HCC.

MCM family in gastrointestinal cancer and other malignancies: From functional characterization to clinical implication

Despite the recent advances in cancer research and treatment, gastrointestinal (GI) cancers remain the most common deadly disease worldwide. The aberrant DNA replication serves as a major source of genomic instability and enhances cell proliferation that contributes to tumor initiation and progression. Minichromosome maintenance family (MCMs) is a well-recognized group of proteins responsible for DNA synthesis. Recent studies suggested that dysregulated MCMs lead to tumor initiation, progression, and chemoresistance via modulating cell cycle and DNA replication stress. Their underlying mechanisms in various cancer types have been gradually identified. Furthermore, multiple studies have investigated the association between MCMs expression and clinicopathological features of cancer patients, implying that MCMs might serve as prominent prognostic biomarkers for GI cancers. This review summarizes the current knowledge on the oncogenic role of MCM proteins and highlights their clinical implications in various malignancies, especially in GI cancers. Targeting MCMs might shed light on the potential for identifying novel therapeutic strategies.

Minichromosome maintenance 6 complex component identified by bioinformatics analysis and experimental validation in esophageal squamous cell carcinoma

Esophageal squamous cell carcinoma (ESCC), the main subtype of esophageal cancer (EC), is a common lethal type of cancer with a high mortality rate. The aim of the present study was to select key relevant genes and identify potential mechanisms involved in the development of ESCC based on bioinformatics analysis. Minichromosome maintenance 6 complex component (MCM6) has been identified to be upregulated in multiple malignancies; however, its contributions to ESCC remain unclear. For the purposes of the present study, four datasets were downloaded from the Gene Expression Omnibus (GSE63941, GSE26886, GSE17351 and GSE77861), and the intersection of the differentially expressed genes was obtained using a Venn diagram. The protein‑protein interaction was then constructed, and the modules were verified by Cytoscape, in which the key genes have a high connectivity degree with other genes. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway were subsequently filtered out to analyze the development of ESCC. MCM6, an upregulated gene, was selected and connected with most of the other genes, for further research validation. The expression levels of MCM6 were then assessed using the Oncomine, GEPIA and UALCAN databases and validated in both ESCC tissues samples and cell lines by immunohistochemistry and RT‑qPCR. Cell counting kit‑8 (CCK‑8), flow cytometry, wound healing and Transwell assays were used to determine the proliferation, apoptosis, cell cycle, migration and invasion of ESCC cells. A total of 24 genes were identified by a series of bioinformatics analyses and the results revealed that the genes were associated with DNA replication and cell cycle. Experimental validation revealed that MCM6 expression was significantly elevated in both ESCC tissues and cell lines. The results were consistent with those of bioinformatics analysis. Furthermore, the knockdown of MCM6 inhibited cell proliferation, migration and invasion and promoted cell apoptosis, and made cells arrested in S stage. In summary, the findings of bioinformatics analysis provided a novel hypothesis for ESCC progression. In particular, the aberrantly elevated expression of MCM6 is a potential biomarker for ESCC diagnosis and treatment.

Bioinformatics Analysis of Prognostic miRNA Signature and Potential Critical Genes in Colon Cancer

This study aims to lay a foundation for studying the regulation of microRNAs (miRNAs) in colon cancer by applying bioinformatics methods to identify miRNAs and their potential critical target genes associated with colon cancer and prognosis. Data of differentially expressed miRNAs (DEMs) and genes (DEGs) downloaded from two independent databases (TCGA and GEO) and analyzed by R software resulted in 472 DEMs and 565 DEGs in colon cancers, respectively. Next, we developed an 8-miRNA (hsa-mir-6854, hsa-mir-4437, hsa-mir-216a, hsa-mir-3677, hsa-mir-887, hsa-mir-4999, hsa-mir-34b, and hsa-mir-3189) prognostic signature for patients with colon cancer by Cox proportional hazards regression analysis. To predict the target genes of these miRNAs, we used TargetScan and miRDB. The intersection of DEGs with the target genes predicted for these eight miRNAs retrieved 112 consensus genes. GO and KEGG pathway enrichment analyses showed these 112 genes were mainly involved in protein binding, one-carbon metabolic process, nitrogen metabolism, proteoglycans in cancer, and chemokine signaling pathways. The protein-protein interaction network of the consensus genes, constructed using the STRING database and imported into Cytoscape, identified 14 critical genes in the pathogenesis of colon cancer (CEP55, DTL, FANCI, HMMR, KIF15, MCM6, MKI67, NCAPG2, NEK2, RACGAP1, RRM2, TOP2A, UBE2C, and ZWILCH). Finally, we verified the critical genes by weighted gene co-expression network analysis (WGCNA) of the GEO data, and further mined the core genes involved in colon cancer. In summary, this study identified an 8-miRNA model that can effectively predict the prognosis of colon cancer patients and 14 critical genes with vital roles in colon cancer carcinogenesis. Our findings contribute new ideas for elucidating the molecular mechanisms of colon cancer carcinogenesis and provide new therapeutic targets and biomarkers for future treatment and prognosis.