Knockdown of MCM10 Gene Impairs Glioblastoma Cell Proliferation, Migration and Invasion and the Implications for the Regulation of Tumorigenesis

Multifaceted role of the DNA replication protein MCM10 in maintaining genome stability and its implication in human diseases

MCM10 plays a vital role in genome duplication and is crucial for DNA replication initiation, elongation, and termination. It coordinates several proteins to assemble at the fork, form a functional replisome, trigger origin unwinding, and stabilize the replication bubble. MCM10 overexpression is associated with increased aggressiveness in breast, cervical, and several other cancers. Disruption of MCM10 leads to altered replication timing associated with initiation site gains and losses accompanied by genome instability. Knockdown of MCM10 affects the proliferation and migration of cancer cells, manifested by DNA damage and replication fork arrest, and has recently been shown to be associated with clinical conditions like CNKD and RCM. Loss of MCM10 function is associated with impaired telomerase activity, leading to the accumulation of abnormal replication forks and compromised telomere length. MCM10 interacts with histones, aids in nucleosome assembly, binds BRCA2 to maintain genome integrity during DNA damage, prevents lesion skipping, and inhibits PRIMPOL-mediated repriming. It also interacts with the fork reversal enzyme SMARCAL1 and inhibits fork regression. Additionally, MCM10 undergoes several post-translational modifications and contributes to transcriptional silencing by interacting with the SIR proteins. This review explores the mechanism associated with MCM10's multifaceted role in DNA replication initiation, chromatin organization, transcriptional silencing, replication stress, fork stability, telomere length maintenance, and DNA damage response. Finally, we discuss the role of MCM10 in the early detection of cancer, its prognostic significance, and its potential use in therapeutics for cancer treatment.

Discovery of key molecular signatures for diagnosis and therapies of glioblastoma by combining supervised and unsupervised learning approaches

Glioblastoma (GBM) is the most malignant brain cancer and one of the leading causes of cancer-related death globally. So, identifying potential molecular signatures and associated drug molecules are crucial for diagnosis and therapies of GBM. This study suggested GBM-causing ten key genes (ASPM, CCNB2, CDK1, AURKA, TOP2A, CHEK1, CDCA8, SMC4, MCM10, and RAD51AP1) from nine transcriptomics datasets by combining supervised and unsupervised learning results. Differential expression patterns of key genes (KGs) between GBM and control samples were verified by different independent databases. Gene regulatory network (GRN) detected some important transcriptional and post-transcriptional regulators for KGs. The KGs-set enrichment analysis unveiled some crucial GBM-causing molecular functions, biological processes, cellular components, and pathways. The DNA methylation analysis detected some hypo-methylated CpG sites that might stimulate the GBM development. From the immune infiltration analysis, we found that almost all KGs are associated with different immune cell infiltration levels. Finally, we recommended KGs-guided four repurposable drug molecules (Fluoxetine, Vatalanib, TGX221 and RO3306) against GBM through molecular docking, drug likeness, ADMET analyses and molecular dynamics simulation studies. Thus, the discoveries of this study could serve as valuable resources for wet-lab experiments in order to take a proper treatment plan against GBM.

Minichromosome maintenance protein 10 (mcm10) regulates hematopoietic stem cell emergence in the zebrafish embryo

Hematopoietic stem cells (HSCs) guarantee the continuous supply of all blood lineages during life. In response to stress, HSCs are capable of extensive proliferative expansion, whereas in steady state, HSCs largely remain in a quiescent state to prevent their exhaustion. DNA replication is a very complex process, where many factors need to exert their functions in a perfectly concerted manner. Mini-chromosome-maintenance protein 10 (Mcm10) is an important replication factor, required for proper assembly of the eukaryotic replication fork. In this report, we use zebrafish to study the role of mcm10 during embryonic development, and we show that mcm10 specifically regulates HSC emergence from the hemogenic endothelium. We demonstrate that mcm10-deficient embryos present an accumulation of DNA damages in nascent HSCs, inducing their apoptosis. This phenotype can be rescued by knocking down p53. Taken all together, our results show that mcm10 plays an important role in the emergence of definitive hematopoiesis.

MCM10 as a novel prognostic biomarker and its relevance to immune infiltration in gliomas

BACKGROUND

Gliomas are one of the most common malignancies in the central nervous system (CNS). Members of the minichromosomal maintenance protein (MCM) family play an essential role in diagnosing and prognosis of malignant tumors. MCM10 is found in gliomas, but the prognosis and immune infiltration of gliomas has not been elucidated.

OBJECTIVE

To explore the biological function and immune infiltration of MCM10 in gliomas and provide a reference for the diagnosis, treatment, and prognostic evaluation.

METHODS

The MCM10 expression profile and the clinical information database of glioma patients were obtained from the China Glioma Genome Atlas (CGGA) and Cancer Genome Atlas (TCGA) glioma data. We analyzed the MCM10 expression levels in various cancers from The TCGA.RNA sequencing data were analyzed using the R packages to determine differentially expressed genes (DEGs) between high- and low MCM10 expressing GBM tissues from the TCGA-GBM database. The Wilcoxon rank sum test was used to compare MCM10 expression levels in glioma and normal brain tissue. To evaluate the value of MCM10 expressions in the prognosis of glioma patients by the Kaplan-Meier survival analysis, a univariate Cox analysis, multivariate Cox analysis, and a ROC curve analysis were used to analyze the correlation of MCM10 expression and the clinicopathological features of glioma patients using the TCGA database data. Subsequently, a functional enrichment analysis was performed to explore its potential signaling pathways and biological functions. Moreover, a single-sample gene set enrichment analysis was used to assess the extent of immune cell infiltration. Lastly, the authors constructed a nomogram to predict the overall survival rate (OS) of gliomas at 1, 3 and 5 years after diagnosis.

RESULTS

MCM10 is highly expressed in 20 cancer types including gliomas, and MCM10 expression was an independent adverse prognostic factor in glioma patients. Similarly, high expression of MCM10 was associated with advanced age (60 years), increased tumor grade, tumor recurrence or development of a secondary tumor, IDH wild-type, and non-codeletion of 1p19q (p< 0.01). The OS nomogram generated a consistency index of 0.821. The results of Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment and Gene Ontology (GO) functional analysis showed that the cell-cycle-related and tumor-related signaling pathways were significantly enriched in the MCM10 high expression phenotype. Moreover, signaling pathways were significantly enriched in Gene Set Enrichment Analysis (GSEA), including Rho GTPases, M phase, DNA repair, extracellular matrix organization, and nuclear receptors. Furthermore, MCM10 over expression was negatively correlated with the level of immune cell infiltration in natural killer CD56 bright cells, follicular helper T cells, plasmacytoma dendritic cells, and dendritic cells.

CONCLUSION

MCM10 is an independent prognostic index of glioma patients, and the high expression of MCM10 suggests a poor prognosis; MCM10 expression is closely related to the immune cell infiltration of gliomas, and MCM10 may be related to drug resistance and development of gliomas.

Expression Profiles of Long Noncoding RNAs and Messenger RNAs in a Rat Model of Spinal Cord Injury

Spinal cord injury (SCI) is a serious disorder of the central nervous system with a high disability rate. Long noncoding RNAs (lncRNAs) are reported to mediate many biological processes. The aim of this study was to explore lncRNA and mRNA expression profiles and functional networks after SCI. Differentially expressed genes between SCI model rats and sham controls were identified by microarray assays and analyzed by functional enrichment. Key lncRNAs were identified using a support vector machine- (SVM-) recursive feature elimination (RFE) algorithm. A trans and cis regulation model was used to analyze the regulatory relationships between lncRNAs and their targets. An lncRNA-related ceRNA network was established. We identified 5465 differentially expressed lncRNAs (DE lncRNAs) and 8366 differentially expressed mRNAs (DE mRNAs) in the SCI group compared with the sham group (fold change > 2.0, p < 0.05). Four genes were confirmed by qRT-PCR which were consistent with the microarray data. GSEA analysis showed that most marked changes occurred in pathways related to immune inflammation and nerve cell function, including cytokine-cytokine receptor interaction, neuroactive ligand-receptor interaction, and GABAergic synapse. Enrichment analysis identified 30 signaling pathways, including those associated with immune inflammation response. A total of 40 key lncRNAs were identified using the SVM-RFE algorithm. A key lncRNA-mRNAs coexpression network was generated for 230 951 lncRNA-mRNA pairs with half showing positive correlations. Several key DE lncRNAs were predicted to have "cis"- or "trans"-regulated target genes. The transcription factors, Sp1, JUN, and SOX10, may regulate the interaction between XR_001837123.1 and ETS 1. In addition, five pairs of ceRNA regulatory sequences were constructed. Many mRNAs and lncRNAs were found to be dysregulated after SCI. Bioinformatic analysis showed that DE lncRNAs may play crucial roles in SCI. It is anticipated that these findings will provide new insights into the underlying mechanisms and potential therapeutic targets for SCI.

Polyclonal evolution of Fanconi anemia to MDS and AML revealed at single cell resolution

Background

Fanconi anemia (FA) is a rare disease of bone marrow failure. FA patients are prone to develop myelodysplastic syndrome (MDS) and acute myeloid leukemia (AML). However, the molecular clonal evolution of the progression from FA to MDS/AML remains elusive.

Methods

Herein, we performed a comprehensive genomic analysis using an FA patient (P1001) sample that transformed to MDS and subsequently AML, together with other three FA patient samples at the MDS stage.

Results

Our finding showed the existence of polyclonal pattern in these cases at MDS stage. The clonal evolution analysis of FA case (P1001) showed the mutations of UBASH3A, SF3B1, RUNX1 and ASXL1 gradually appeared at the later stage of MDS, while the IDH2 alteration become the dominant clone at the leukemia stage. Moreover, single-cell sequencing analyses further demonstrated a polyclonal pattern was present at either MDS or AML stages, whereas IDH2 mutated cell clones appeared only at the leukemia stage.

Conclusions

We thus propose a clonal evolution model from FA to MDS and AML for this patient. The results of our study on the clonal evolution and mutated genes of the progression of FA to AML are conducive to understanding the progression of the disease that still perplexes us.

Supplementary Information

The online version contains supplementary material available at 10.1186/s40164-022-00319-5.

MCM10 is a Prognostic Biomarker and Correlated With Immune Checkpoints in Ovarian Cancer

Background: Microchromosome maintenance protein 10 (MCM10) is required for DNA replication in all eukaryotes, and it plays a key role in the development of many types of malignancies. However, we currently still do not know the relationship between MCM10 and ovarian cancer (OV) prognosis and immune checkpoints.

Methods: The Gene Expression Profiling Interactive Analysis and Tumor Immunology Estimation Resource (TIMER) databases were used to investigate MCM10 expression in Fan cancer. The Kaplan-Meier Plotter and PrognoScan were used to assess the relationship between MCM10 and OV prognosis. The LinkedOmics database was used to analyze the MCM10 co-expression network and explore GO term annotation and the KEGG pathway. The relationship between MCM10 expression and immune infiltration in OV was investigated using the Tumor Immunology Estimation Resource database. cBioPortal database was used to explore the relationship between MCM10 expression and 25 immune checkpoints. Finally, quantitative real-time polymerase chain reaction (qRT-PCR) was performed to detect MCM10 expression. The prognosis was also analyzed by distinguishing between high and low expression groups based on median expression values.

Results: The results of the three data sets (220,651_s_at, 222,962_s_at and 223,570_at) in KM Plotter all indicated that the overall survivalof the high MCM10 expression group was lower than that of the low expression group OV, and the results of GSE9891 also reached the same conclusion. The expression level of MCM10 was negatively correlated with B cells and CD8+T cells, and positively correlated with CD4+T Cells and Macrophages. GO term annotation and KEGG pathway analysis showed that the co-expressed genes of MCM10 were mainly enriched in cell cycle and DNA replication. The alterations in MCM10 coexisted statistically with the immune checkpoints CTLA4, TNFSF4, TNFSF18, CD80, ICOSLG, LILRB1 and CD200. PCR results displayed that MCM10 was highly expressed in OV tissues, and the increased expression of MCM10 was significantly associated with poor overall survival.

Conclusion: These results demonstrated that high expression of MCM10 was associated with poor prognosis in OV and correlated with immune checkpoints.

Integrative Analysis of Minichromosome Maintenance Proteins and Their Prognostic Significance in Melanoma

Background

Minichromosome maintenance (MCM) is known for participating in cell cycle progression, as well as DNA replication. While the diverse expression patterns and prognostic values of MCMs in melanoma still remained unclear.

Methods

In the present study, the transcriptional and clinical profiles of MCMs were explored in patients with melanoma from multiple databases, including GEO, TCGA, ONCOMINE, GEPIA, UALCAN, cBioPortal, and TIMER databases.

Results

We found that the elevated expressions of MCM2–6 and MCM10 were significantly expressed in melanoma compared to normal skin. High mRNA levels of MCM4, MCM5, and MCM10 were closely related to worse prognosis in patients with melanoma. GSEA showed hallmark pathways were most involved in mTORC1 signaling, G2M checkpoint, E2F targets, and mitotic spindle. Furthermore, we found potential correlations between the MCM expression and the immune cell infiltration, including B cells, CD4+ T cells, CD8+ T cells, neutrophils, macrophages, and dendritic cells.

Conclusion

Upregulated MCM gene expression in melanoma probably played a crucial part in the development and progression of melanoma. The upregulated MCM4/5/10 expressions could be used as potential prognostic markers to improve the poor outcome and prognostic accuracy in patients with melanoma. Our study might shed light on the selection of prognostic biomarkers as well as the underlying molecular pathogenesis of melanoma.