DNA Replication Licensing Protein MCM10 Promotes Tumor Progression and Is a Novel Prognostic Biomarker and Potential Therapeutic Target in Breast Cancer

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.

Prediction of Endocrine-Disrupting Chemicals Related to Estrogen, Androgen, and Thyroid Hormone (EAT) Modalities Using Transcriptomics Data and Machine Learning

Endocrine-disrupting chemicals (EDCs) are chemicals that can interfere with homeostatic processes. They are a major concern for public health, and they can cause adverse long-term effects such as cancer, intellectual impairment, obesity, diabetes, and male infertility. The endocrine system is a complex machinery, with the estrogen (E), androgen (A), and thyroid hormone (T) modes of action being of major importance. In this context, the availability of in silico models for the rapid detection of hazardous chemicals is an effective contribution to toxicological assessments. We developed Qualitative Gene expression Activity Relationship (QGexAR) models to predict the propensities of chemically induced disruption of EAT modalities. We gathered gene expression profiles from the LINCS database tested on two cell lines, i.e., MCF7 (breast cancer) and A549 (adenocarcinomic human alveolar basal epithelial). We optimized our prediction protocol by testing different feature selection methods and classification algorithms, including CATBoost, XGBoost, Random Forest, SVM, Logistic regression, AutoKeras, TPOT, and deep learning models. For each EAT endpoint, the final prediction was made according to a consensus prediction as a function of the best model obtained for each cell line. With the available data, we were able to develop a predictive model for estrogen receptor and androgen receptor binding and thyroid hormone receptor antagonistic effects with a consensus balanced accuracy on a validation set ranging from 0.725 to 0.840. The importance of each predictive feature was further assessed to identify known genes and suggest new genes potentially involved in the mechanisms of action of EAT perturbation.

Unwinding Helicase MCM Functionality for Diagnosis and Therapeutics of Replication Abnormalities Associated with Cancer: A Review

The minichromosome maintenance (MCM) protein is a component of an active helicase that is essential for the initiation of DNA replication. Dysregulation of MCM functions contribute to abnormal cell proliferation and genomic instability. The interactions of MCM with cellular factors, including Cdc45 and GINS, determine the formation of active helicase and functioning of helicase. The functioning of MCM determines the fate of DNA replication and, thus, genomic integrity. This complex is upregulated in precancerous cells and can act as an important tool for diagnostic applications. The MCM protein complex can be an important broad-spectrum therapeutic target in various cancers. Investigations have supported the potential and applications of MCM in cancer diagnosis and its therapeutics. In this article, we discuss the physiological roles of MCM and its associated factors in DNA replication and cancer pathogenesis.

Activation of Glycolysis by MCM10 Increases Stemness and Paclitaxel Resistance in Gastric Cancer Cells

BACKGROUND/AIMS

Chemotherapy is an essential avenue for curing malignancies; however, tumor cells acquire resistance to chemotherapeutic agents, eventually leading to chemotherapy failure. At present, paclitaxel (PTX) resistance seriously hinders the therapeutic efficacy of gastric cancer (GC). Investigating the molecular mechanism of PTX resistance in GC is critical. This study attempted to delineate the impact of MCM10 on GC resistance to PTX and its mechanism in GC.

MATERIALS AND METHODS

The expression of minichromosome maintenance complex component 10 (MCM10) in GC tissues, its enrichment pathways, and its correlation with glycolysis marker genes and stemness index (mRNAsi) were analyzed in a bioinformatics effort. Real-time quantitative polymerase chain reaction was used to assay the expression of MCM10 in cells. Cell counting kit-8 (CCK-8) was used to analyze cell viability and calculate the 50% inhibitor concentration (IC50) value. Western blot was used to measure the expression of MCM10, Hexokinase 2 (HK2) and stemness-related factors in cells. Sphere-forming assay was performed to study cell sphere-forming ability. Seahorse XF 96 was utilized to measure cell extracellular acidification and oxygen consumption rates. The content of glycolysisrelated products was tested with corresponding kits.

RESULTS

MCM10 was significantly upregulated in GC and enriched in the glycolysis pathway, and it was positively correlated with both glycolysis-related genes and stemness index. High expression of MCM10 increased sphere-forming ability of drug-resistant cells and GC resistance to PTX. The stimulation of PTX resistance and drug-resistant cell stemness in GC by high MCM10 expression was mediated by the glycolysis pathway.

CONCLUSION

MCM10 was upregulated in GC and drove stemness and PTX resistance in GC cells by activating glycolysis. These findings generated new insights into the development of PTX resistance in GC, implicating that targeting MCM10 may be a novel approach to improve GC sensitivity to PTX chemotherapy.

MCM10, a potential diagnostic, immunological, and prognostic biomarker in pan-cancer

Microchromosome maintenance (MCM) proteins are a number of nuclear proteins with significant roles in the development of cancer by influencing the process of cellular DNA replication. Of the MCM protein family, MCM10 is a crucial member that maintains the stability and extension of DNA replication forks during DNA replication and is significantly overexpressed in a variety of cancer tissues, regulating the biological behaviour of cancer cells. But little is understood about MCM10's functional role and regulatory mechanisms in a range of malignancies. We investigate the impact of MCM10 in human cancers by analyzing data from databases like the Gene Expression Profiling Interaction Analysis (GEPIA2), Genotype-Tissue Expression (GTEx) and The Cancer Genome Atlas (TCGA), among others. Possible relationships between MCM10 and clinical staging, diagnosis, prognosis, Mutation burden (TMB), microsatellite instability (MSI), immunological checkpoints, DNA methylation, and tumor stemness were identified. The findings demonstrated that MCM10 expression was elevated in the majority of cancer types and was connected to tumor dryness, immunocytic infiltration, immunological checkpoints, TMB and MSI. Functional enrichment analysis in multiple tumors also identified possible pathways of MCM10 involvement in tumorigenesis. We also discovered promising MCM10-targeting chemotherapeutic drugs. In conclusion, MCM10 may be a desirable pan-cancer biomarker and offer fresh perspectives on cancer therapy.

Application of Protein-Protein Interaction Network Analysis in Order to Identify Cervical Cancer miRNA and mRNA Biomarkers

Cervical cancer (CC) is one of the world's most common and severe cancers. This cancer includes two histological types: squamous cell carcinoma (SCC) and adenocarcinoma (ADC). The current study aims at identifying novel potential candidate mRNA and miRNA biomarkers for SCC based on a protein-protein interaction (PPI) and miRNA-mRNA network analysis. The current project utilized a transcriptome profile for normal and SCC samples. First, the PPI network was constructed for the 1335 DEGs, and then, a significant gene module was extracted from the PPI network. Next, a list of miRNAs targeting module's genes was collected from the experimentally validated databases, and a miRNA-mRNA regulatory network was formed. After network analysis, four driver genes were selected from the module's genes including MCM2, MCM10, POLA1, and TONSL and introduced as potential candidate biomarkers for SCC. In addition, two hub miRNAs, including miR-193b-3p and miR-615-3p, were selected from the miRNA-mRNA regulatory network and reported as possible candidate biomarkers. In summary, six potential candidate RNA-based biomarkers consist of four genes containing MCM2, MCM10, POLA1, and TONSL, and two miRNAs containing miR-193b-3p and miR-615-3p are opposed as potential candidate biomarkers for CC.

Aberrant activation of five embryonic stem cell-specific genes robustly predicts a high risk of relapse in breast cancers

BACKGROUND

In breast cancer, as in all cancers, genetic and epigenetic deregulations can result in out-of-context expressions of a set of normally silent tissue-specific genes. The activation of some of these genes in various cancers empowers tumours cells with new properties and drives enhanced proliferation and metastatic activity, leading to a poor survival prognosis.

RESULTS

In this work, we undertook an unprecedented systematic and unbiased analysis of out-of-context activations of a specific set of tissue-specific genes from testis, placenta and embryonic stem cells, not expressed in normal breast tissue as a source of novel prognostic biomarkers. To this end, we combined a strict machine learning framework of transcriptomic data analysis, and successfully created a new robust tool, validated in several independent datasets, which is able to identify patients with a high risk of relapse. This unbiased approach allowed us to identify a panel of five biomarkers, DNMT3B, EXO1, MCM10, CENPF and CENPE, that are robustly and significantly associated with disease-free survival prognosis in breast cancer. Based on these findings, we created a new Gene Expression Classifier (GEC) that stratifies patients. Additionally, thanks to the identified GEC, we were able to paint the specific molecular portraits of the particularly aggressive tumours, which show characteristics of male germ cells, with a particular metabolic gene signature, associated with an enrichment in pro-metastatic and pro-proliferation gene expression.

CONCLUSIONS

The GEC classifier is able to reliably identify patients with a high risk of relapse at early stages of the disease. We especially recommend to use the GEC tool for patients with the luminal-A molecular subtype of breast cancer, generally considered of a favourable disease-free survival prognosis, to detect the fraction of patients undergoing a high risk of relapse.

Whole exon capture sequencing for identifying mutations associated with pulmonary benign metastasising leiomyoma

A woman in her early 20s presented with cough and fever. She had undergone an abdominal myomectomy 3 years ago for uterine leiomyoma. Chest CT and positron emission tomography-CT revealed multiple round nodules in both lungs, suggesting metastatic lesions. A CT-guided lung biopsy was performed, and the tumour was diagnosed as pulmonary benign metastasising leiomyoma (PBML) based on pathological analyses. Whole exon capture sequencing of uterine leiomyoma and PBML sections revealed that 13 genes (MCM10, SLC16A9, RAG1, BAZ1A, NLRP2, TRMT61B, CPXM1, NGLY1, SUCLG2, FAM13A, CAGE1, PHTF2 and ZDHHC2) were concurrently present in the two tumours. The patient was prescribed goserelin injections every 4 weeks. The symptoms improved 2 weeks after starting the treatment. The lung nodules considerably decreased in size after three courses of goserelin treatment. The nodular size continues to decrease with the treatment.

DNA replication: Mechanisms and therapeutic interventions for diseases

Accurate and integral cellular DNA replication is modulated by multiple replication-associated proteins, which is fundamental to preserve genome stability. Furthermore, replication proteins cooperate with multiple DNA damage factors to deal with replication stress through mechanisms beyond their role in replication. Cancer cells with chronic replication stress exhibit aberrant DNA replication and DNA damage response, providing an exploitable therapeutic target in tumors. Numerous evidence has indicated that posttranslational modifications (PTMs) of replication proteins present distinct functions in DNA replication and respond to replication stress. In addition, abundant replication proteins are involved in tumorigenesis and development, which act as diagnostic and prognostic biomarkers in some tumors, implying these proteins act as therapeutic targets in clinical. Replication-target cancer therapy emerges as the times require. In this context, we outline the current investigation of the DNA replication mechanism, and simultaneously enumerate the aberrant expression of replication proteins as hallmark for various diseases, revealing their therapeutic potential for target therapy. Meanwhile, we also discuss current observations that the novel PTM of replication proteins in response to replication stress, which seems to be a promising strategy to eliminate diseases.

Deciphering cervical cancer-associated biomarkers by integrated multi-omics approach

OBJECTIVES

Cervical Squamous Cell Carcinoma (CESC) is one of the most fatal female malignancies, and the underlying molecular mechanisms governing this disease have not been fully explored. In this research, we planned to conduct the analysis of Gene Expression Omnibus (GEO) cervical squamous cell carcinoma microarray datasets by a detailed in silico approach and to explore some novel biomarkers of CESC.

METHODS

The top commonly differentially expressed genes (DEGs) from the GSE138080 and GSE113942 datasets were analyzed by Limma package-based GEO2R tool. The protein-protein interaction (PPI) network of the DEGs was drawn through Search Tool for the Retrieval of Interacting Genes (STRING), and top 6 hub genes were obtained from Cytoscape. Expression analysis and validation of hub genes expression in CESC samples and cell lines were done using UALCAN, OncoDB, GENT2, and HPA. Additionally, cBioPortal, Gene set enrichment analysis (GSEA) tool, Kaplan-Meier (KM) plotter, ShinyGO, and DGIdb databases were also used to check some important values of hub genes in CESC.

RESULTS

Out of 79 DEGs, the minichromosome maintenance complex component 4 (MCM4), nucleolar and spindle-associated protein 1 (NUSAP1), cell division cycle associated 5 (CDCA5), cell division cycle 45 (CDC45), denticleless E3 ubiquitin protein ligase homolog (DTL), and chromatin licensing and DNA replication factor 1 (CDT1) genes were regarded as hub genes in CESC. Further analysis revealed that the expressions of all these hub genes were significantly elevated in CESC cell lines and samples of diverse clinical attributes. In this study, we also documented some important correlations between hub genes and some other diverse measures, including DNA methylation, genetic alterations, and Overall Survival (OS). Last, we also identify hub genes associated ceRNA network and 31 important chemotherapeutic drugs.

CONCLUSION

Through detailed in silico methodology, we identified 6 hub genes, including MCM4, NUSAP1, CDCA5, CDC45, DTL, and CDT1, which are likely to be associated with CESC development and diagnosis.

Identification of Candidate Genes in Breast Cancer Induced by Estrogen Plus Progestogens Using Bioinformatic Analysis

Menopausal hormone therapy (MHT) was widely used to treat menopause-related symptoms in menopausal women. However, MHT therapies were controversial with the increased risk of breast cancer because of different estrogen and progestogen combinations, and the molecular basis behind this phenomenon is currently not understood. To address this issue, we identified differentially expressed genes (DEGs) between the estrogen plus progestogens treatment (EPT) and estrogen treatment (ET) using the Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) data. As a result, a total of 96 upregulated DEGs were first identified. Seven DEGs related to the cell cycle (CCNE2, CDCA5, RAD51, TCF19, KNTC1, MCM10, and NEIL3) were validated by RT-qPCR. Specifically, these seven DEGs were increased in EPT compared to ET (p < 0.05) and had higher expression levels in breast cancer than adjacent normal tissues (p < 0.05). Next, we found that estrogen receptor (ER)-positive breast cancer patients with a higher CNNE2 expression have a shorter overall survival time (p < 0.05), while this effect was not observed in the other six DEGs (p > 0.05). Interestingly, the molecular docking results showed that CCNE2 might bind to 17β-estradiol (−6.791 kcal/mol), progesterone (−6.847 kcal/mol), and medroxyprogesterone acetate (−6.314 kcal/mol) with a relatively strong binding affinity, respectively. Importantly, CNNE2 protein level could be upregulated with EPT and attenuated by estrogen receptor antagonist, acolbifene and had interactions with cancer driver genes (AKT1 and KRAS) and high mutation frequency gene (TP53 and PTEN) in breast cancer patients. In conclusion, the current study showed that CCNE2, CDCA5, RAD51, TCF19, KNTC1, MCM10, and NEIL3 might contribute to EPT-related tumorigenesis in breast cancer, with CCNE2 might be a sensitive risk indicator of breast cancer risk in women using MHT.

Over-Activation of Minichromosome Maintenance Protein 10 Promotes Genomic Instability in Early Stages of Breast Cancer

Genomic instability is considered as one of the key hallmark during cancer development and progression. Cellular mechanisms, such as DNA replication initiation, DNA damage and repair response, apoptosis etc are observed to block progression of genomic instability and thereby induce protective effects against cancer. DNA replication initiation protein MCM10 has been previously observed to have an increased expression in different cancer subtypes. However, MCM10 association with genomic instability, cancer development and its relevant mechanisms remain unknown. Here, using a breast cancer model, we observe a significant association of MCM10 with the degree of clinical aggressiveness in breast cancer patients. By overexpression of MCM10, we observed that MCM10 promotes tumorigenic properties in immortal non-tumorigenic mammary cells by increasing proliferation, shortening the cell cycle, and promoting tumorigenic characters in in-vivo mimicking conditions. Furthermore, overexpression of MCM10 is found to induce accumulation of ssDNA followed by overexpression of ssDNA binding protein RPA2. Mesenchymal markers such as up-regulation of Vimentin, transcription factor Snail and Twist2, and the down-regulation of E-cadherin were observed in MCM10 overexpression cells. Overall, the findings of this study revealed a novel mechanism by which MCM10 promotes genomic instability and breast cancer progression, and effectively differentiates the active degree of breast cancer aggressiveness. Thus, MCM10 has the potential to be a clinically useful biomarker as well as a therapeutic target for future breast cancer treatment.

Cell cycle-related genes associate with sensitivity to hydrogen peroxide-induced toxicity

Reactive oxygen species (ROS) such as hydrogen peroxide (H2O2) are well-described agents in physiology and pathology. Chronic inflammation causes incessant H2O2 generation associated with disease occurrences such as diabetes, autoimmunity, and cancer. In cancer, conditioning of the tumor microenvironment, e.g., hypoxia and ROS generation, has been associated with disease outcomes and therapeutic efficacy. Many reports have investigated the roles of the action of H2O2 across many cell lines and disease models. The genes predisposing tumor cell lines to H2O2-mediated demise are less deciphered, however. To this end, we performed in-house transcriptional profiling of 35 cell lines and simultaneously investigated each cell line's H2O2 inhibitory concentration (IC25) based on metabolic activity. More than 100-fold differences were observed between the most resistant and sensitive cell lines. Correlation and gene ontology pathway analysis identified a rigid association with genes intertwined in cell cycle progression and proliferation, as such functional categories dominated the top ten significant processes. The ten most substantially correlating genes (Spearman r > 0.70 or < -0.70) were validated using qPCR, showing complete congruency with microarray analysis findings. Western blotting confirmed the correlation of cell cycle-related proteins negatively correlating with H2O2 IC25. Top genes related to ROS production or antioxidant defense were only modest in correlation (Spearman r > 0.40 or < -0.40). In conclusion, our in-house transcriptomic correlation analysis revealed a set of cell cycle-associated genes associated with a priori resistance or sensitivity to H2O2-induced cellular demise with the detailed and causative roles of individual genes remaining unclear.

Gene-Level Germline Contributions to Clinical Risk of Recurrence Scores in Black and White Patients with Breast Cancer

Continuous risk of recurrence scores (CRS) based on tumor gene expression are vital prognostic tools for breast cancer. Studies have shown that Black women (BW) have higher CRS than White women (WW). Although systemic injustices contribute substantially to breast cancer disparities, evidence of biological and germline contributions is emerging. In this study, we investigated germline genetic associations with CRS and CRS disparity using approaches modeled after transcriptome-wide association studies (TWAS). In the Carolina Breast Cancer Study, using race-specific predictive models of tumor expression from germline genetics, we performed race-stratified (N = 1,043 WW, 1,083 BW) linear regressions of three CRS (ROR-S: PAM50 subtype score; proliferation score; ROR-P: ROR-S plus proliferation score) on imputed tumor genetically regulated tumor expression (GReX). Bayesian multivariate regression and adaptive shrinkage tested GReX-prioritized genes for associations with tumor PAM50 expression and subtype to elucidate patterns of germline regulation underlying GReX-CRS associations. At FDR-adjusted P < 0.10, 7 and 1 GReX prioritized genes among WW and BW, respectively. Among WW, CRS were positively associated with MCM10, FAM64A, CCNB2, and MMP1 GReX and negatively associated with VAV3, PCSK6, and GNG11 GReX. Among BW, higher MMP1 GReX predicted lower proliferation score and ROR-P. GReX-prioritized gene and PAM50 tumor expression associations highlighted potential mechanisms for GReX-prioritized gene to CRS associations. Among patients with breast cancer, differential germline associations with CRS were found by race, underscoring the need for larger, diverse datasets in molecular studies of breast cancer. These findings also suggest possible germline trans-regulation of PAM50 tumor expression, with potential implications for CRS interpretation in clinical settings. SIGNIFICANCE: This study identifies race-specific genetic associations with breast cancer risk of recurrence scores and suggests mediation of these associations by PAM50 subtype and expression, with implications for clinical interpretation of these scores.

DNA Replication Licensing Factors: Novel Targets for Cancer Therapy via Inhibiting the Stemness of Cancer Cells

The replication licensing factors strictly regulate the DNA replication origin licensing process to guarantee the stability of the genome. Numerous experimental studies have recently demonstrated that the replication licensing factors as oncogenes are essential for the occurrence and development of cancers. Drug resistance, being one of the main characteristics of cancer stem cells, can cause a high recurrence rate and a low survival rate in patients with different cancers. However, the function of the replication licensing factors in cancer stemness remains unclear. The following article highlights the most recent research on DNA replication origin licensing factors in cancer and their function in anti-cancer drug resistance. Moreover, this article proposes a new perspective that replication licensing factors as chemotherapy shield affect anti-cancer drug resistance by promoting the stemness of cancer cells.

Synergistic effects of methyl 2-cyano-3,11-dioxo-18beta-olean-1,-12-dien-30-oate and erlotinib on erlotinib-resistant non-small cell lung cancer cells

Non-small cell lung cancer (NSCLC) is often characterized by an underlying mutation in the epidermal growth factor receptor (EGFR), contributing to aggressive metastatic disease. Methyl 2-cyano-3,11-dioxo-18beta-olean-1,12-dien-30-oate (CDODA-Me), a glycyrrhetinic acid derivative, reportedly improves the therapeutic response to erlotinib (ERL), an EGFR tyrosine kinase inhibitor. In the present study, we performed a series of studies to demonstrate the efficacy of CDODA-Me (2 μM) in sensitizing HCC827R (ERL-resistant) cells to ERL. Herein, we first established the selectivity of ERL-induced drug resistance in the HCC827R cells, which was sensitized when ERL was combined with CDODA-Me (2 μM), shifting the IC50 from 23.48 μM to 5.46 μM. Subsequently, whole transcriptomic microarray expression data demonstrated that the combination of ERL + CDODA-Me elicited 210 downregulated genes (0.44% of the whole transcriptome (WT)) and 174 upregulated genes (0.36% of the WT), of which approximately 80% were unique to the ERL + CDODA-Me group. Synergistic effects centered on losses to cell cycle progression transcripts, a reduction of minichromosome maintenance complex components (MCM2-7), all key components of the Cdc45·MCM2-7GINS (CMG) complex, and replicative helicases; these effects were tantamount to the upregulation of processes associated with the nuclear factor erythroid 2 like 2 translational response to oxidative stress, including sulfiredoxin 1, heme oxygenase 1, and stress-induced growth inhibitor 1. Collectively, these findings indicate that the synergistic therapeutic effects of ERL + CDODA-Me on resistant NSCLC cells are mediated via the inhibition of mitosis and induction of oxidative stress.

CDT1 Is a Novel Prognostic and Predictive Biomarkers for Hepatocellular Carcinoma

Objective

Hepatocellular carcinoma (HCC) is one of the most common malignant tumors endangering human health and life in the 21st century. Chromatin licensing and DNA replication factor 1 (CDT1) is an important regulator of DNA replication licensing, which is essential for initiation of DNA replication. CDT1 overexpression in several human cancers reportedly leads to abnormal cell replication, activates DNA damage checkpoints, and predisposes malignant transformation. However, the abnormal expression of CDT1 in HCC and its diagnostic and prognostic value remains to be elucidated.

Methods

TCGA, ONCOMINE, UALCAN, HCCDB, HPA, Kaplan-Meier plotter, STRING, GEPIA, GeneMANIA, and TIMER were conducted for bioinformatics analysis. CDT1 protein expression was evaluated by immunohistochemistry in HCC tissues through a tissue microarray. qRT-PCR, western blot and a cohort of functional experiments were performed for in vitro validation.

Results

In this study, we discovered remarkably upregulated transcription of CDT1 in HCC samples relative to normal liver samples through bioinformatic analysis, which was further verified in clinical tissue microarray samples and in vitro experiments. Moreover, the transcriptional level of CDT1 in HCC samples was positively associated with clinical parameters such as clinical tumor stage. Survival, logistic regression, and Cox regression analyses revealed the significant clinical prognostic value of CDT1 expression in HCC. The receiver operating characteristic curve and nomogram analysis results demonstrated the strong predictive ability of CDT1 in HCC. Kyoto Encyclopedia of Genes and Genomes and gene set enrichment analyses indicated that CDT1 was mainly associated with the cell cycle, DNA repair, and DNA replication. We further demonstrated the significant correlation between CDT1 and minichromosome maintenance (MCM) family genes, revealing abnormal expression and prognostic significance of MCMs in HCC. Immune infiltration analysis indicated that CDT1 was significantly associated with immune cell subsets and affected the survival of HCC patients. Finally, knockdown of CDT1 decreased, whereas overexpression of CDT1 promoted the proliferation, migration, invasion of HCC cells in vitro.

Conclusions

Our study findings demonstrate the potential diagnostic and prognostic significance of CDT1 expression in HCC, and elucidate the potential molecular mechanism underlying its role in promoting the occurrence and development of liver cancer. These results may provide new opportunities and research paths for targeted therapies in HCC.

Prognostic significance and function of MCM10 in human hepatocellular carcinoma

Aim: To investigate the role of MCM10, a conserved replication factor, in hepatocellular carcinoma (HCC). Methods: We used data from 364 HCC patients in the Cancer Genome Atlas database and conducted in vitro experiments to confirm the role of MCM10. Results: High MCM10 expression correlated with poor HCC patient outcome and was an independent prognosticator for HCC. Time-dependent receiver operating characteristic curve analysis found that the sequential trend of MCM10 for survival was not inferior to that of the tumor node metastasis stage. The MCM10 model had a higher C-index than the non-MCM10 model, indicating that incorporating MCM10 into a multivariate model improves the model's prognostic accuracy for HCC. Genetic alterations of MCM10 prominently correlated with an unfavorable HCC outcome. Conclusion: Our findings strongly suggest using the MCM10 gene as a prognostic indicator in HCC.

Aberrant MCM10 SUMOylation induces genomic instability mediated by a genetic variant associated with survival of esophageal squamous cell carcinoma

BACKGROUND

Esophageal squamous cell carcinoma (ESCC) is one of the common gastrointestinal malignancy with an inferior prognosis outcome. DNA replication licensing aberration induced by dysregulation of minichromosome maintenance proteins (MCMs) causes genomic instability and cancer metastasis. SUMOylation modification plays a pivotal role in regulation of genomic integrity, while its dysregulation fueled by preexisting germline variants in cancers remains poorly understood.

METHODS

Firstly, we conducted two-stage survival analysis consisting of an exome-wide association study in 904 ESCC samples and another independent 503 ESCC samples. Then, multipronged functional experiments were performed to illuminate the potential biological mechanisms underlying the promising variants, and MCM10 influences the ESCC progression. Finally, we tested the effects of MCM10 inhibitors on ESCC cells.

RESULTS

A germline variant rs2274110 located at the exon 15 of MCM10 was identified to be significantly associated with the prognosis of ESCC patients. Individuals carrying rs2274110-AA genotypes confer a poor survival (hazard ratio = 1.61, 95% confidence interval = 1.35-1.93, p = 1.35 × 10-7 ), compared with subjects carrying rs2274110-AG/GG genotypes. Furthermore, we interestingly found that the variant can increase SUMOylation levels at K669 site (Lys[K]699Arg[R]) of MCM10 protein mediated by SUMO2/3 enzymes, which resulted in an aberrant overexpression of MCM10. Mechanistically, aberrant overexpression of MCM10 facilitated the proliferation and metastasis abilities of ESCC cells in vitro and in vivo by inducing DNA over-replication and genomic instability, providing functional evidence to support our population finding that high expression of MCM10 is extensively presented in tumor tissues of ESCC and correlated with inferior survival outcomes of multiple cancer types, including ESCC. Finally, MCM10 inhibitors Suramin and its analogues were revealed to effectively block the metastasis of ESCC cells.

CONCLUSIONS

These findings not only demonstrate a potential biological mechanism between aberrant SUMOylation, genomic instability and cancer metastasis, but also provide a promising biomarker aiding in stratifying ESCC individuals with different prognosis, as well as a potential therapeutic target MCM10.

High expression of MCM10 is predictive of poor outcomes in lung adenocarcinoma

Backgrounds

Lung adenocarcinoma is a complex disease that results in over 1.8 million deaths a year. Recent advancements in treating and managing lung adenocarcinoma have led to modest decreases in associated mortality rates, owing in part to the multifactorial etiology of the disease. Novel prognostic biomarkers are needed to accurately stage the disease and act as the basis of adjuvant treatments.

Material and Methods

The microarray datasets GSE75037, GSE31210 and GSE32863 were downloaded from the Gene Expression Omnibus (GEO) database to identify prognostic biomarkers for lung adenocarcinoma and therapy. The differentially expressed genes (DEGs) were identified by GEO2R. Functional and pathway enrichment analysis were performed by Kyoto Encyclopedia of Genes and Genomes and Gene Ontology (GO). Validation was performed based on 72 pairs of lung adenocarcinoma and adjacent normal lung tissues.

Results

Results showed that the DEGs were mainly focused on cell cycle and DNA replication initiation. Forty-one hub genes were identified and further analyzed by CytoScape. Here, we provide evidence which suggests MCM10 is a potential target with prognostic, diagnostic and therapeutic value. We base this on an integrated approach of comprehensive bioinformatics analysis and in vitro validation using the A549 lung adenocarcinoma cell line. We show that MCM10 overexpression correlates with a poor prognosis, while silencing of this gene decreases aberrant growth by 2-fold. Finally, evaluation of 72 clinical biopsy samples suggests that overexpression of MCM10 in the lung adenocarcinoma highly correlates with larger tumor size. Together, this work suggests that MCM10 may be a clinically relevant gene with both predictive and therapeutic value in lung adenocarcinoma.

MCM10 compensates for Myc-induced DNA replication stress in breast cancer stem-like cells

Cancer stem-like cells (CSCs) induce drug resistance and recurrence of tumors when they experience DNA replication stress. However, the mechanisms underlying DNA replication stress in CSCs and its compensation remain unclear. Here, we demonstrate that upregulated c-Myc expression induces stronger DNA replication stress in patient-derived breast CSCs than in differentiated cancer cells. Our results suggest critical roles for mini-chromosome maintenance protein 10 (MCM10), a firing (activating) factor of DNA replication origins, to compensate for DNA replication stress in CSCs. MCM10 expression is upregulated in CSCs and is maintained by c-Myc. c-Myc-dependent collisions between RNA transcription and DNA replication machinery may occur in nuclei, thereby causing DNA replication stress. MCM10 may activate dormant replication origins close to these collisions to ensure the progression of replication. Moreover, patient-derived breast CSCs were found to be dependent on MCM10 for their maintenance, even after enrichment for CSCs that were resistant to paclitaxel, the standard chemotherapeutic agent. Further, MCM10 depletion decreased the growth of cancer cells, but not of normal cells. Therefore, MCM10 may robustly compensate for DNA replication stress and facilitate genome duplication in cancer cells in the S-phase, which is more pronounced in CSCs. Overall, we provide a preclinical rationale to target the c-Myc-MCM10 axis for preventing drug resistance and recurrence of tumors.

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

Minichromosome maintenance 10 (MCM10) plays an important role in DNA replication and is expressed in a variety of tumors, including glioma. However, its role and mechanism in glioma remain elusive. The purpose of this study was to examine the molecular function of MCM10 in glioblastoma cell lines in vitro and to further investigate the molecular mechanisms in the network mediated by MCM10. Cell proliferation, invasion, and migration were investigated in the absence of MCM10 mediated by RNA interference (RNAi) in U87 and U251 cell lines. Microarray data were obtained from U87 cells infected with a lentivirus expressing a small interfering RNA (siRNA) targeting MCM10, and ingenuity pathway analysis (IPA) was performed. Molecular signaling pathways, gene functions, and upstream and downstream regulatory genes and networks were analyzed. MCM10 was positively stained in human glioblastoma multiforme (GBM) samples according to immunohistochemistry. Silencing MCM10 in U87 and U251 cells significantly reduced cell proliferation, migration, and invasion. In U87 cells transfected with MCM10, 274 genes were significantly upregulated, while 313 genes were downregulated. IPA revealed that MCM10 is involved in the IGF-1 signaling pathway, and calcitriol appears to be a significant upstream regulator of MCM10. Other factors, such as TWIST1 and Stat3, also interact within the MCM10-mediated network. Our data indicate that MCM10 is involved in the regulation of GBM in vitro and may provide more evidence for understanding the molecular mechanisms of this fatal disease.

Network-based integration method for potential breast cancer gene identification

Breast cancer is the most common female death-causing cancer worldwide. A network-based integration method was proposed to identify potential breast cancer genes. First, genes were prioritized using a gene prioritization algorithm by the strategy of disease risks transferred between genes in a network with weighted vertexes and edges. Our prioritization algorithm was effectives and robust for top-ranked seed gene number and higher area under the curve values compared to ToppGene and ToppNet. Then, 20 potential breast cancer genes were identified as common genes of the top 50 candidate genes for their robustness in multiple prioritizations. These genes could accurately classify tumor and normal samples of all and paired sample sets and three independent datasets. Of potential breast cancer genes, 18 were verified by literature and 2 were novel genes that need further study. This study would contribute to the understanding of the genetic architecture for the diagnosis and treatment of breast cancer.

Predictive early gene signature during mouse Bhas 42 cell transformation induced by synthetic amorphous silica nanoparticles

Synthetic amorphous silica nanoparticles (SAS) are used widely in industrial applications. These nanoparticles are not classified for their carcinogenicity in humans. However, some data still demonstrate a potential carcinogenic risk of these compounds in humans. The Bhas 42 cell line was developed to screen chemicals, as tumor-initiators or -promoters according to their ability to trigger cell-to-cell transformation, in a cell transformation assay. In the present study, we performed unsupervised transcriptomic analysis after exposure of Bhas 42 cells to NM-203 SAS as well as to positive (Min-U-Sil 5® crystalline silica microparticles, and 12-O-tetradecanoylphorbol-13-acetate) and negative (diatomaceous earth) control compounds. We identified a common gene signature for 21 genes involved in the early stage of the SAS- Min-U-Sil 5®- or TPA-induced cell transformation. These genes were related to cell proliferation (over expression) and cell adhesion (under expression). Among them, 12 were selected on the basis of their potential impact on cell transformation. RT-qPCR and western blotting were used to confirm the transcriptomic data. Moreover, similar gene alterations were found when Bhas 42 cells were treated with two other transforming SAS. In conclusion, the results obtained in the current study highlight a 12-gene signature that could be considered as a potential early "bio-marker" of cell transformation induced by SAS and perhaps other chemicals.

Toward a holistic view of multiscale breast cancer molecular biomarkers

Powered by rapid technology developments, biomarkers become increasingly diverse, including those detected at genomic, transcriptomic, proteomic, metabolomic and cellular levels. While diverse sets of biomarkers have been utilized in breast cancer predisposition, diagnosis, prognosis, treatment and management, recent additions derived from lincRNA, circular RNA, circulating DNA together with its methylated and hydroxymethylated forms and immune signatures are likely to further transform clinical practice. Here, we take breast cancer as an example of heterogeneous diseases that require many informed decisions from treatment to care to review the huge variety of biomarkers. By assessing the advantages and limitations of modern biomarkers in diverse use scenarios, this article outlines the prospects and challenges of releasing complimentary advantages by augmentation of multiscale molecular biomarkers.

The anti-parasitic agent suramin and several of its analogues are inhibitors of the DNA binding protein Mcm10

Minichromosome maintenance protein 10 (Mcm10) is essential for DNA unwinding by the replisome during S phase. It is emerging as a promising anti-cancer target as MCM10 expression correlates with tumour progression and poor clinical outcomes. Here we used a competition-based fluorescence polarization (FP) high-throughput screening (HTS) strategy to identify compounds that inhibit Mcm10 from binding to DNA. Of the five active compounds identified, only the anti-parasitic agent suramin exhibited a dose-dependent decrease in replication products in an in vitro replication assay. Structure–activity relationship evaluation identified several suramin analogues that inhibited ssDNA binding by the human Mcm10 internal domain and full-length Xenopus Mcm10, including analogues that are selective for Mcm10 over human RPA. Binding of suramin analogues to Mcm10 was confirmed by surface plasmon resonance (SPR). SPR and FP affinity determinations were highly correlated, with a similar rank between affinity and potency for killing colon cancer cells. Suramin analogue NF157 had the highest human Mcm10 binding affinity (FP K_i 170 nM, SPR K_D 460 nM) and cell activity (IC₅₀ 38 µM). Suramin and its analogues are the first identified inhibitors of Mcm10 and probably block DNA binding by mimicking the DNA sugar phosphate backbone due to their extended, polysulfated anionic structures.

Exploring the Molecular Mechanism of the Drug-Treated Breast Cancer Based on Gene Expression Microarray

: Breast cancer (BRCA) remains the leading cause of cancer morbidity and mortality worldwide. In the present study, we identified novel biomarkers expressed during estradiol and tamoxifen treatment of BRCA. The microarray dataset of E-MTAB-4975 from Array Express database was downloaded, and the differential expressed genes (DEGs) between estradiol-treated BRCA sample and tamoxifen-treated BRCA sample were identified by limma package. The pathway and gene ontology (GO) enrichment analysis, construction of protein-protein interaction (PPI) network, module analysis, construction of target genes-miRNA interaction network and target genes-transcription factor (TF) interaction network were performed using bioinformatics tools. The expression, prognostic values, and mutation of hub genes were validated by SurvExpress database, cBioPortal, and human protein atlas (HPA) database. A total of 856 genes (421 up-regulated genes and 435 down-regulated genes) were identified in T47D (overexpressing Split Ends (SPEN) + estradiol) samples compared to T47D (overexpressing Split Ends (SPEN) + tamoxifen) samples. Pathway and GO enrichment analysis revealed that the DEGs were mainly enriched in response to lysine degradation II (pipecolate pathway), cholesterol biosynthesis pathway, cell cycle pathway, and response to cytokine pathway. DEGs (MCM2, TCF4, OLR1, HSPA5, MAP1LC3B, SQSTM1, NEU1, HIST1H1B, RAD51, RFC3, MCM10, ISG15, TNFRSF10B, GBP2, IGFBP5, SOD2, DHF and MT1H) , which were significantly up- and down-regulated in estradiol and tamoxifen-treated BRCA samples, were selected as hub genes according to the results of protein-protein interaction (PPI) network, module analysis, target genes-miRNA interaction network and target genes-TF interaction network analysis. The SurvExpress database, cBioPortal, and Human Protein Atlas (HPA) database further confirmed that patients with higher expression levels of these hub genes experienced a shorter overall survival. A comprehensive bioinformatics analysis was performed, and potential therapeutic applications of estradiol and tamoxifen were predicted in BRCA samples. The data may unravel the future molecular mechanisms of BRCA.

Co-expression network analysis identified candidate biomarkers in association with progression and prognosis of breast cancer

PURPOSE

Breast cancer is one of the most common malignancies among females, and its prognosis is affected by a complex network of gene interactions. Weighted gene co-expression network analysis was used to construct free-scale gene co-expression networks and to identify potential biomarkers for breast cancer progression.

METHODS

The gene expression profiles of GSE42568 were downloaded from the Gene Expression Omnibus database. RNA-sequencing data and clinical information of breast cancer from TCGA were used for validation.

RESULTS

A total of ten modules were established by the average linkage hierarchical clustering. We identified 58 network hub genes in the significant module (R² = 0.44) and 6 hub genes (AGO2, CDC20, CDCA5, MCM10, MYBL2, and TTK), which were significantly correlated with prognosis. Receiver-operating characteristic curve validated that the mRNA levels of these six genes exhibited excellent diagnostic efficiency in the test data set of GSE42568. RNA-sequencing data from TCGA showed that the expression levels of these six genes were higher in triple-negative tumors. One-way ANOVA suggested that these six genes were upregulated at more advanced stages. The results of independent sample t test indicated that MCM10 and TTK were associated with tumor size, and that AGO2, CDC20, CDCA5, MCM10, and MYBL2 were overexpressed in lymph-node positive breast cancer.

CONCLUSIONS

AGO2, CDC20, CDCA5, MCM10, MYBL2, and TTK were identified as candidate biomarkers for further basic and clinical research on breast cancer based on co-expression analysis.

DNA replication licensing proteins: Saints and sinners in cancer

DNA replication is all-or-none process in the cell, meaning, once the DNA replication begins it proceeds to completion. Hence, to achieve maximum control of DNA replication, eukaryotic cells employ a multi-subunit initiator protein complex known as "pre-replication complex or DNA replication licensing complex (DNA replication LC). This complex involves multiple proteins which are origin-recognition complex family proteins, cell division cycle-6, chromatin licensing and DNA replication factor 1, and minichromosome maintenance family proteins. Higher-expression of DNA replication LC proteins appears to be an early event during development of cancer since it has been a common hallmark observed in a wide variety of cancers such as oesophageal, laryngeal, pulmonary, mammary, colorectal, renal, urothelial etc. However, the exact mechanisms leading to the abnormally high expression of DNA replication LC have not been clearly deciphered. Increased expression of DNA replication LC leads to licensing and/or firing of multiple origins thereby inducing replication stress and genomic instability. Therapeutic approaches where the reduction in the activity of DNA replication LC was achieved either by siRNA or shRNA techniques, have shown increased sensitivity of cancer cell lines towards the anti-cancer drugs such as cisplatin, 5-Fluorouracil, hydroxyurea etc. Thus, the expression level of DNA replication LC within the cell determines a cell's fate thereby creating a paradox where DNA replication LC acts as both "Saint" and "Sinner". With a potential to increase sensitivity to chemotherapy drugs, DNA replication LC proteins have prospective clinical importance in fighting cancer. Hence, in this review, we will shed light on importance of DNA replication LC with an aim to use DNA replication LC in diagnosis and prognosis of cancer in patients as well as possible therapeutic targets for cancer therapy.