DNA replication licensing proteins: Saints and sinners in cancer

Development of a prognostic model for lung adenocarcinoma polarity-related genes and analysis of immune landscape

Despite the progress made in the management of lung adenocarcinoma (LUAD), the overall prognosis for LUAD individuals remains suboptimal. While the role of cell polarity in tumor invasion and metastasis is well established, its prognostic significance in LUAD is still unknown. Differential analysis was performed on the Cancer Genome Atlas (TCGA)-LUAD and normal lung tissue, and candidate genes were identified by intersecting differentially expressed genes with polarity-related genes (PRGs). A prognostic model was constructed using univariate and multivariate Cox regression and LASSO regression. To enhance the robustness of the analysis, an independent prognostic analysis was conducted by incorporating relevant clinical information. The accuracy and sensitivity of the model were validated using survival analysis and ROC curves. Finally, immune landscape, immune therapy, tumor mutation burden, and drug sensitivity analysis were carried out on high- and low-risk patients. Ten prognostic genes were screened to divide LUAD patients into different risk groups. Survival analysis, ROC curves, and univariate/multivariate Cox regression analyses collectively demonstrated the favorable predictive performance of the model, which could be an independent prognostic factor. The nomogram, in conjunction with the calibration curve, demonstrated the model's compelling predictive capacity in prognosticating the overall survival of LUAD individuals. Low-risk LUAD patients exhibited heightened levels of immune cell infiltration, immune scores, and immune checkpoint expression compared to high-risk individuals. So, they may have a greater likelihood of benefiting from immune therapy. The high-risk group demonstrated a remarkably higher tumor mutation burden (TMB) in contrast with the low-risk group. XAV-939, Fulvestrant, and SR16157 may have potential value in the clinical use of LUAD. We revealed the potential linkage between PRGs and LUAD prognosis, and the application of these prognostic factors in risk stratification and prognosis prediction of LUAD patients may be of great significance.

Fabrication of targeted and pH responsive lysozyme-hyaluronan nanoparticles for 5-fluorouracil and curcumin co-delivery in colorectal cancer therapy

Green nanotechnology is considered a promising method to construct functional materials with significant anticancer activity, while overcoming the shortcomings of traditional synthesis process complexity and high organic solvents consumption. Thus, in this study, we report for the first time the rational design and green synthesis of functionalized 5-fluorouracil and curcumin co-loaded lysozyme-hyaluronan composite colloidal nanoparticles (5-Fu/Cur@LHNPs) for better targeted colorectal cancer therapy with minimized side effects. The functionalized 5-Fu/Cur@LHNPs exhibit stabilized particle size (126.1 nm) with excellent homogeneity (PDI = 0.1), favorable colloidal stabilities, and excellent re-dispersibility. In vitro cell experiments illustrate that the cellular uptake of 5-Fu/Cur@LHNPs was significantly improved and further promoted a higher apoptosis ratio of HCT-116 cells. Compared with the control group, the 5-Fu/Cur@LHNPs formulation group achieved effective inhibition (60.1 %) of colorectal tumor growth. The alcohol-free self-assembly method to construct 5-Fu/Cur@LHNPs is simple and safe for a translational chemotherapy drug, also to promote more robust delivery systems for treating colorectal cancer.

Werner helicase mediates the senescence and cell cycle of leukemia cells by regulating DNA repair pathways

Leukemia is a type of malignant hematological disease that is generally resistant to chemotherapy and has poor therapeutic outcomes. Werner (WRN) DNA helicase, an important member of the RecQ family of helicases, plays an important role in DNA repair and telomere stability maintenance. WRN gene dysfunction leads to premature aging and predisposes humans to various types of cancers. However, the biological function of WRN in cancer remains unknown. In this study, the expression of this RecQ family helicase was investigated in different types of leukemia cells, and the leukemia cell line K562 with high WRN expression was selected to construct a WRN knockdown cell line. The results showed that WRN knockdown inhibited leukemia occurrence and development by regulating the proliferation, cell cycle, differentiation, and aging of cells and other biological processes. The results of transcriptome sequencing revealed that WRN promoted the sensitivity of leukemia cells to the DNA damage inducer Etoposide by regulating cell cycle-related proteins, such as CDC2, cyclin B1, p16, and p21, as well as key proteins in DNA damage repair pathways, such as p53, RAD50, RAD51, and MER11. Our findings show that WRN helicase is a promising potential target for leukemia treatment, providing new ideas for the development of targeted drugs against leukemia.

The mitotic cell cycle-associated nomogram predicts overall survival in lung adenocarcinoma

BACKGROUND

This study aimed to develop a prognostic model for lung adenocarcinoma (LUAD) associated with mitotic cell cycle. The model will predict the probability of survival at different time points and serve as a reference tool to evaluate the effectiveness of LUAD treatment.

METHODS

A cohort of 442 patients with LUAD from the gene expression omnibus (GEO) database was randomly divided into a training group (n = 299) and a validation group (n = 99). The least absolute shrinkage and selection operator (LASSO)-COX algorithm was used to reduce the number of predictors based on the clinicopathological and RNA sequencing data to establish mutant characteristics that could predict patient survival. Additionally, gene ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), gene set variation analysis (GSVA), and gene set enrichment analysis (GSEA) analyses were conducted on the mutant characteristics. The performance of the developed nomogram was evaluated using calibration curves and the C-index.

RESULTS

The mutant characteristics had prognostic value for LUAD and acted as an independent prognostic factor. The mutant characteristics profile derived from the LASSO-COX algorithm demonstrated a significant association with overall survival in patients with LUAD. Functional annotation based on the mutant score, its involvement in the phase transition of the mitotic cell cycle, and its regulatory processes. The nomogram, which combined the mutant score with clinical factors associated with prognosis, showed robust accuracy in both the training and validation groups.

CONCLUSION

This study presents the first individualized model that establishes a mutant score for predicting survival in LUAD. This model can be used as a predictive tool for determining 1-, 2-, 3-, and 5-year survival probabilities in patients with LUAD.

PhenoDriver: interpretable framework for studying personalized phenotype-associated driver genes in breast cancer

Identifying personalized cancer driver genes and further revealing their oncogenic mechanisms is critical for understanding the mechanisms of cell transformation and aiding clinical diagnosis. Almost all existing methods primarily focus on identifying driver genes at the cohort or individual level but fail to further uncover their underlying oncogenic mechanisms. To fill this gap, we present an interpretable framework, PhenoDriver, to identify personalized cancer driver genes, elucidate their roles in cancer development and uncover the association between driver genes and clinical phenotypic alterations. By analyzing 988 breast cancer patients, we demonstrate the outstanding performance of PhenoDriver in identifying breast cancer driver genes at the cohort level compared to other state-of-the-art methods. Otherwise, our PhenoDriver can also effectively identify driver genes with both recurrent and rare mutations in individual patients. We further explore and reveal the oncogenic mechanisms of some known and unknown breast cancer driver genes (e.g. TP53, MAP3K1, HTT, etc.) identified by PhenoDriver, and construct their subnetworks for regulating clinical abnormal phenotypes. Notably, most of our findings are consistent with existing biological knowledge. Based on the personalized driver profiles, we discover two existing and one unreported breast cancer subtypes and uncover their molecular mechanisms. These results intensify our understanding for breast cancer mechanisms, guide therapeutic decisions and assist in the development of targeted anticancer therapies.

De novo MCM6 variants in neurodevelopmental disorders: a recognizable phenotype related to zinc binding residues

The minichromosome maintenance (MCM) complex acts as a DNA helicase during DNA replication, and thereby regulates cell cycle progression and proliferation. In addition, MCM-complex components localize to centrosomes and play an independent role in ciliogenesis. Pathogenic variants in genes coding for MCM components and other DNA replication factors have been linked to growth and developmental disorders as Meier-Gorlin syndrome and Seckel syndrome. Trio exome/genome sequencing identified the same de novo MCM6 missense variant p.(Cys158Tyr) in two unrelated individuals that presented with overlapping phenotypes consisting of intra-uterine growth retardation, short stature, congenital microcephaly, endocrine features, developmental delay and urogenital anomalies. The identified variant affects a zinc binding cysteine in the MCM6 zinc finger signature. This domain, and specifically cysteine residues, are essential for MCM-complex dimerization and the induction of helicase activity, suggesting a deleterious effect of this variant on DNA replication. Fibroblasts derived from the two affected individuals showed defects both in ciliogenesis and cell proliferation. We additionally traced three unrelated individuals with de novo MCM6 variants in the oligonucleotide binding (OB)-fold domain, presenting with variable (neuro)developmental features including autism spectrum disorder, developmental delay, and epilepsy. Taken together, our findings implicate de novo MCM6 variants in neurodevelopmental disorders. The clinical features and functional defects related to the zinc binding residue resemble those observed in syndromes related to other MCM components and DNA replication factors, while de novo OB-fold domain missense variants may be associated with more variable neurodevelopmental phenotypes. These data encourage consideration of MCM6 variants in the diagnostic arsenal of NDD.

High expression of ABCF1 is an independent predictor of poor prognosis in bladder cancer

ABCF1, a member of the ATP-binding cassette (ABC) transporter family, is involved in the malignant progression of tumors. However, the role of ABCF1 in bladder cancer is poorly understood. In our study, we explored the differential expression of ABCF1 in bladder cancer and normal bladder tissues based on bioinformatic analysis and immunohistochemical results. GSEA was performed to ascertain the potential related signaling pathways of ABCF1. The relationship between ABCF1 expression and bladder cancer progression was analyzed using the GSE13507 dataset. In addition, the differential expression of ABCF1 in the cell lines was verified by quantitative real-time polymerase chain reaction (qRT‒PCR) and Western blotting. ABCF1 was upregulated in bladder cancer, and the high expression of ABCF1 was closely related to sex (P = 0.00056), grade (P = 0.00049), T stage (P = 0.00007), and N stage (P = 0.0076). High expression of ABCF1 was correlated with poor overall survival in bladder cancer patients (P < 0.001). In addition, univariate and multivariate Cox regression analyses showed that high ABCF1 expression was an independent factor for poor prognosis in bladder cancer patients. Therefore, ABCF1 expression is closely related to the progression of bladder cancer and can be used as a potential indicator of poor prognosis and a therapeutic target for bladder cancer.

Systemic analysis of the DNA replication regulator origin recognition complex in lung adenocarcinomas identifies prognostic and expression significance

BACKGROUND

DNA replication alteration is a hallmark of patients with lung adenocarcinoma (LUAD) and is frequently observed in LUAD progression. Origin recognition complex (ORC) 1, ORC2, ORC3, ORC4, ORC5, and ORC6 form a replication-initiator complex to mediate DNA replication, which plays a key role in carcinogenesis, while their roles in LUAD remain poorly understood.

METHODS

The mRNA and protein expression of ORCs was confirmed by the GEPIA, HPA, CPTAC, and TCGA databases. The protein-protein interaction network was analyzed by the GeneMANIA database. Functional enrichment was confirmed by the Metascape database. The effects of ORCs on immune infiltration were validated by the TIMER database. The prognostic significance of ORCs in LUAD was confirmed by the KM-plot and GENT2 databases. DNA alteration and protein structure were determined in the cBioProtal and PDB databases. Moreover, the protein expression and prognostic value of ORCs were confirmed in our LUAD data sets by immunohistochemistry (IHC) staining.

RESULTS

ORC mRNA and protein were significantly increased in patients with LUAD compared with corresponding normal tissue samples. The results of IHC staining analysis were similar result to those of the above bioinformatics analysis. Furthermore, ORC1 and ORC6 had significant prognostic values for LUAD patients. Furthermore, the ORC cooperatively promoted LUAD development by driving DNA replication, cellular senescence, and metabolic processes.

CONCLUSION

The ORC, especially ORC1/6, has important prognostic and expression significance for LUAD patients.

High MCM8 expression correlates with unfavorable prognosis and induces immune cell infiltration in hepatocellular carcinoma

BACKGROUND

MCM8 has been reported highly expressed in several human malignancies. However, its role in HCC has not yet been researched.

METHODS

The prognostic significance of MCM8 mRNA expression was analyzed using datasets from TCGA and GEO databases. Immunohistochemistry (IHC) assay was used to detect the MCM8 protein expression in HCC tissues. The Cox regression analysis was employed to determine the independent prognostic value of MCM8. Then, we established a nomogram for OS and RFS prediction based on MCM8 protein expression. We analyzed the DNA methylation and genetic alteration of MCM8 in HCC. Moreover, GO, KEGG and GSEA were utilized to explore the potential biological functions of MCM8. Subsequently, we evaluate the correlations between MCM8 expression and composition of the tumor microenvironment as well as immunocyte infiltration ratio in HCC.

RESULTS

MCM8 mRNA and protein were significantly overexpressed in HCC tissues. High MCM8 protein expression was an independent risk factor for OS and RFS of HCC patients. MCM8 expression is altered in 60% of queried HCC patients. In addition, higher methylation of the CpG site cg03098629, cg10518808, and 17230679 correlated with lower MCM8 levels. MCM8 expression correlated with cell cycle and DNA replication signaling. Moreover, MCM8 may be correlated with different compositions of the tumor microenvironment and immunocyte infiltration ratio in HCC.

CONCLUSIONS

MCM8 was highly expressed in HCC tissues and was associated with poor prognosis. Meanwhile, high expression of MCM8 may induce immune cell infiltration and may be a promising prognostic biomarker for HCC.

Unscheduled DNA replication in G1 causes genome instability and damage signatures indicative of replication collisions

DNA replicates once per cell cycle. Interfering with the regulation of DNA replication initiation generates genome instability through over-replication and has been linked to early stages of cancer development. Here, we engineer genetic systems in budding yeast to induce unscheduled replication in a G1-like cell cycle state. Unscheduled G1 replication initiates at canonical S-phase origins. We quantifiy the composition of replisomes in G1- and S-phase and identified firing factors, polymerase α, and histone supply as factors that limit replication outside S-phase. G1 replication per se does not trigger cellular checkpoints. Subsequent replication during S-phase, however, results in over-replication and leads to chromosome breaks and chromosome-wide, strand-biased occurrence of RPA-bound single-stranded DNA, indicating head-to-tail replication collisions as a key mechanism generating genome instability upon G1 replication. Low-level, sporadic induction of G1 replication induces an identical response, indicating findings from synthetic systems are applicable to naturally occurring scenarios of unscheduled replication initiation.

A novel classification of HCC basing on fatty-acid-associated lncRNA

Aberrant long noncoding RNA (lncRNA) expression and fatty acid signaling dysfunction both contribute to hepatocellular carcinoma (HCC) occurrence and development. However, the relationship and interaction mechanism between lncRNAs and fatty acid signaling in HCC remain unclear. Data regarding RNA expression and clinical outcomes for patients with HCC were obtained from The Cancer Genome Atlas (TCGA), HCCDB, and the Gene Expression Omnibus (GEO) databases. Hallmark pathways were identified using the single-sample gene set enrichment analysis (ssGSEA) method. ConsensusClusterPlus was used to establish a consistency matrix for classifying samples into three subtypes. A risk signature was established, and predictive values for key lncRNAs related to prognosis were evaluated using Kaplan-Meier analysis and receiver operating characteristic curves. The ESTIMATE algorithm, MCP-Counter, and ssGSEA were used to evaluate the characteristics of the tumor immune microenvironment. The CTRP2.0 and PRISM were used to analyze drug sensitivity in HCC subtypes. We discovered seven fatty-acid-associated lncRNAs with predictive prognostic capabilities, including TRAF3IP2-AS1, SNHG10, AL157392.2, LINC02641, AL357079.1, AC046134.2, and A1BG-AS. Three subtypes were obtained, which presented with differences in prognosis, clinical information, mutation features, pathway traits, immune characteristics, and drug sensitivity. The seven key lncRNAs identified in this study might serve as promising biomarkers for predicting prognosis in patients with HCC, and the three HCC subtypes classified according to lncRNA expression profiles could improve HCC classification.

A multi-functional role for the MCM8/9 helicase complex in maintaining fork integrity during replication stress

The minichromosome maintenance (MCM) 8/9 helicase is a AAA⁺ complex involved in DNA replication-associated repair. Despite high sequence homology to the MCM2-7 helicase, a precise cellular role for MCM8/9 has remained elusive. We have interrogated the DNA synthesis ability and replication fork stability in cells lacking MCM8 or 9 and find that there is a functional partitioning of MCM8/9 activity between promoting replication fork progression and protecting persistently stalled forks. The helicase function of MCM8/9 aids in normal replication fork progression, but upon persistent stalling, MCM8/9 directs additional downstream stabilizers, including BRCA1 and Rad51, to protect forks from excessive degradation. Loss of MCM8 or 9 slows the overall replication rate and allows for excessive nascent strand degradation, detectable by increased markers of genomic damage. This evidence defines multifunctional roles for MCM8/9 in promoting normal replication fork progression and genome integrity following stress.

Identifying Functions of Proteins in Mice With Functional Embedding Features

In current biology, exploring the biological functions of proteins is important. Given the large number of proteins in some organisms, exploring their functions one by one through traditional experiments is impossible. Therefore, developing quick and reliable methods for identifying protein functions is necessary. Considerable accumulation of protein knowledge and recent developments on computer science provide an alternative way to complete this task, that is, designing computational methods. Several efforts have been made in this field. Most previous methods have adopted the protein sequence features or directly used the linkage from a protein–protein interaction (PPI) network. In this study, we proposed some novel multi-label classifiers, which adopted new embedding features to represent proteins. These features were derived from functional domains and a PPI network via word embedding and network embedding, respectively. The minimum redundancy maximum relevance method was used to assess the features, generating a feature list. Incremental feature selection, incorporating RAndom k-labELsets to construct multi-label classifiers, used such list to construct two optimum classifiers, corresponding to two key measurements: accuracy and exact match. These two classifiers had good performance, and they were superior to classifiers that used features extracted by traditional methods.

New insights into phenotypic heterogeneity for the distinct lipid accumulation of Schizochytrium sp. H016

BACKGROUND

Schizochytrium sp. is a marine heterotrophic protist and an important sustainable resource for high value-added docosahexaenoic acid in the future. The production of different phenotypes during the continuous subculture of Schizochytrium sp. results in a serious reduction in lipid yield and complicates the used of this strain in scientific research and industrial production. Hence, obtaining an improved understanding of the phenotypic differences and molecular mechanisms underlying the cell-to-cell heterogeneity of Schizochytrium sp. is necessary.

RESULTS

After continuous culture passage, Schizochytrium sp. H016 differentiated into two subpopulations with different morphologies and showed decreased capacity for lipid production. The presence of cell subpopulations with degraded lipid droplets led to a substantial decrease in overall lipid yield. Here, a rapid screening strategy based on fluorescence-activated cell sorting was proposed to classify and isolate subpopulations quickly in accordance with their lipid-producing capability. The final biomass and lipid yield of the subpopulation with high cell lipid content (i.e., H016-H) were 38.83 and 17.22 g/L, respectively, which were 2.07- and 5.38-fold higher than those of the subpopulation with low lipid content (i.e., H016-L), respectively. Subsequently, time‑resolved transcriptome analysis was performed to elucidate the mechanism of phenotypic heterogeneity in different subpopulations. Results showed that the expression of genes related to the cell cycle and lipid degradation was significantly upregulated in H016-L, whereas the metabolic pathways related to fatty acid synthesis and glyceride accumulation were remarkably upregulated in H016-H.

CONCLUSION

This study innovatively used flow cytometry combined with transcriptome technology to provide new insights into the phenotypic heterogeneity of different cell subpopulations of Schizochytrium sp. Furthermore, these results lay a strong foundation for guiding the breeding of oleaginous microorganisms with high lipid contents.

Identification of protein functions in mouse with a label space partition method

Protein is very important for almost all living creatures because it participates in most complicated and essential biological processes. Determining the functions of given proteins is one of the most essential problems in protein science. Such determination can be conducted through traditional experiments. However, the experimental methods are always time-consuming and of high costs. In recent years, computational methods give useful aids for identification of protein functions. This study presented a new multi-label classifier for identifying functions of mouse proteins. Due to the number of functional types, which were termed as labels in the classification procedure, a label space partition method was employed to divide labels into some partitions. On each partition, a multi-label classifier was constructed. The classifiers based on all partitions were integrated in the proposed classifier. The cross-validation results proved that the proposed classifier was of good performance. Classifiers with label partition were superior to those without label partition or with random label partition.

Clinical significance and effect of lncRNA BBOX1-AS1 on the proliferation and migration of lung squamous cell carcinoma

Long non-coding RNAs (lncRNAs) have a role in the occurrence and development of lung squamous cell carcinoma (LUSC). lncRNA γ-butyrobetaine hydroxylase 1 (BBOX1)-antisense 1 (AS1) may contribute to disease development. However, there are no studies on the role of BBOX1-AS1 in LUSC to date. In the present study, an in-house gene microarray analysis was performed to detect the differentially expressed lncRNAs and mRNAs between three pairs of LUSC and normal lung tissues. Only one lncRNA, BBOX1-AS1, was differentially expressed in the in-house microarray and The Cancer Genome Atlas (TCGA), Gene Expression Omnibus (GEO) and ArrayExpress databases. Reverse transcription-quantitative PCR (RT-qPCR) was then performed and the original RNA-sequencing data from the TCGA, GEO and ArrayExpress datasets were used to determine the expression and clinical value of BBOX1-AS1 in LUSC. In addition, a Cell Counting Kit-8 assay, cell cycle analysis and scratch assay were performed to explore whether BBOX1-AS1 expression affected the proliferation and migration of LUSC cells in vitro. The results of the RT-qPCR analysis and data obtained from the TCGA database, GEO datasets, in-house gene microarray and standard mean deviation analysis all supported the upregulated expression level of BBOX1-AS1 in LUSC. Furthermore, silencing of BBOX1-AS1 inhibited the proliferation and migration of LUSC cells according to in vitro assays. In addition, the cells were arrested in S-phase after knockdown of BBOX1-AS1. In conclusion, the expression level of BBOX1-AS1 was upregulated in LUSC tissues. BBOX1-AS1 may exert an oncogenic effect on LUSC by regulating various biological functions. However, additional functional experiments should be performed to verify the exact mechanism.

ZWINT is a Promising Therapeutic Biomarker Associated with the Immune Microenvironment of Hepatocellular Carcinoma

Background

The prognosis of patients with advanced hepatocellular carcinoma (HCC) is still poor, effective therapeutic targets are needed. ZW10 interacting kinetochore protein (Zwint) is an essential component of the mitotic spindle checkpoint and is upregulated in cancers. Disappointing, the role of ZWINT in HCC has not been fully illuminated.

Methods

Multiple tools, including TIMER2.0, Oncomine, GEPIA2, UALCAN, LinkedOmics, Kaplan-Meier Plotter, cBioPortal, and MethSurv, etc. were applied to comprehensively analyze the expression, genetic alternations, clinicopathological relevance, prognostic value, and DNA methylation of ZWINT, along with its correlations with immune infiltration in HCC. Besides, gene set enrichment analysis (GSEA) and protein-protein interaction (PPI) analysis were performed for the correlated genes of ZWINT, closely interconnected clusters and hub proteins in the PPI network were discovered to learn the underlying biological mechanisms.

Results

We found ZWINT was significantly upregulated in diverse cancers including HCC, compared with the corresponding normal controls. ZWINT upregulation was significantly associated with unfavorable clinicopathological features and survivals of HCC patients. Genetic alternations of ZWINT frequently occurred, which were linked to worse outcomes of HCC patients. The results of GSEA displayed ZWINT and its correlated genes might be components of condensed chromosomes and spindles, which participated in biological processes and signaling pathways involving DNA replication, cytokinesis, and cell cycle checkpoint, etc. Three highly interconnected clusters and 10 hub proteins were identified from the PPI network constructed with the correlated genes of ZWINT. Moreover, ZWINT expression was found positively correlated with infiltration levels of various immune cells, especially myeloid-derived suppressor cells.

Conclusion

This study demonstrated ZWINT might be a promising unfavorable prognostic biomarker and a therapeutic target of HCC, which could regulate HCC progression through cell division and immunosuppression.

Identification of hub genes in colorectal cancer based on weighted gene co-expression network analysis and clinical data from The Cancer Genome Atlas

Colorectal cancer (CRC) is one of the most common tumors worldwide and is associated with high mortality. Here we performed bioinformatics analysis, which we validated using immunohistochemistry in order to search for hub genes that might serve as biomarkers or therapeutic targets in CRC. Based on data from The Cancer Genome Atlas (TCGA), we identified 4832 genes differentially expressed between CRC and normal samples (1562 up-regulated and 3270 down-regulated in CRC). Gene ontology (GO) analysis showed that up-regulated genes were enriched mainly in organelle fission, cell cycle regulation, and DNA replication; down-regulated genes were enriched primarily in the regulation of ion transmembrane transport and ion homeostasis. Weighted gene co-expression network analysis (WGCNA) identified eight gene modules that were associated with clinical characteristics of CRC patients, including brown and blue modules that were associated with cancer onset. Analysis of the latter two hub modules revealed the following six hub genes: adhesion G protein-coupled receptor B3 (BAI3, also known as ADGRB3), cyclin F (CCNF), cytoskeleton-associated protein 2 like (CKAP2L), diaphanous-related formin 3 (DIAPH3), oxysterol binding protein-like 3 (OSBPL3), and RERG-like protein (RERGL). Expression levels of these hub genes were associated with prognosis, based on Kaplan–Meier survival analysis of data from the Gene Expression Profiling Interactive Analysis database. Immunohistochemistry of CRC tumor tissues confirmed that OSBPL3 is up-regulated in CRC. Our findings suggest that CCNF, DIAPH3, OSBPL3, and RERGL may be useful as therapeutic targets against CRC. BAI3 and CKAP2L may be novel biomarkers of the disease.

Genotoxic stress response: What is the role of cytoplasmic mRNA fate?

Genotoxic stress leads to DNA damage which can be detrimental to the cell. A well-orchestrated cellular response is mounted to manage and repair the genotoxic stress-induced DNA damage. Our understanding of genotoxic stress response is derived mainly from studies focused on transcription, mRNA splicing, and protein turnover. Surprisingly not as much is understood about the role of mRNA translation and decay in genotoxic stress response. This is despite the fact that regulation of gene expression at the level of mRNA translation and decay plays a critical role in a myriad of cellular processes. This review aims to summarize some of the known findings of the role of mRNA translation and decay by focusing on two categories of examples. We discuss examples of mRNA whose fates are regulated in the cytoplasm and RNA-binding proteins that regulate mRNA fates in response to genotoxic stress.

Systematic expression analysis of the CELSR family reveals the importance of CELSR3 in human lung adenocarcinoma

Cadherin EGF LAG seven‐pass G‐type receptors (CELSRs) are involved in the progression of various types of cancer. CELSR3, a crucial signalling molecule in the WNT/PCP pathway, is believed to be associated with tumorigenesis and metastasis. However, its role in lung adenocarcinoma (LUAD) remains unclear. In this paper, we analysed the expression of CELSR family members using the Oncomine, GEPIA and UALCAN databases. We used a Kaplan‐Meier plotter to assess the effect of CELSRs on tumour prognosis. Next, gene ontology (GO), KEGG pathway, miRNA target, kinase target and transcription factor‐target enrichment were analysed by GSEA. Simultaneously, we conducted functional assays including cell viability, colony formation and transwell assays, to determine the oncogenic role of CELSR3 in LUAD. Finally, we used the TIMER and TISIDB databases to analyse the correlation between CELSR3 and immune infiltration and the potential chemokine receptor axis causing immune cell expression. High expression of CELSR3 is in LUAD predicts poor prognosis and early progression of the tumour. KEGG and GO enrichment analysis revealed the functional relationship between CELSR3 and cell adhesion, the cell cycle, and DNA replication. Down‐regulation of CELSR3 suppressed cell proliferation to a significant extent, in addition to inhibiting invasion and migration in LUAD cells. Finally, CELSR3 expression was significantly correlated with the infiltration level of CD8+T cells through the CCL17/CCR4 axis in LUAD. These results indicate that CELSR3 can serve as a prognostic biomarker for determining prognosis and immune infiltration in LUAD.

Enhanced Expression of CNTD2/CCNP Predicts Poor Prognosis in Bladder Cancer Based on the GSE13507

Bladder cancer is one of the most common urogenital malignancies in the world, and there are no adequate prognostic indicators. CNTD2 is one of the atypical cyclins, which may be related to the cell cycle and even the development of cancers. Early studies have shown that CNTD2 is closely related to the occurrence and development of many malignant tumors. However, the mechanism of CNTD2 in bladder cancer has not been reported. In our research, we explored the different expressions of CNTD2 between 411 bladder cancers and 19 normal bladder tissues based on the TCGA dataset. CNTD2-related signaling pathways were identified through the GSEA. We analyzed the associations of CNTD2 expression and bladder cancer progression and survival using GSE13507. Compared with 19 cases of normal bladder tissue, CNTD2 gene expression was increased in 411 cases of bladder cancer. The high expression of CNTD2 strongly correlated with grade (P < 0.0001), T classification (P = 0.0001), N classification (P = 0.00011), M classification (P = 0.044), age (P = 0.027), and gender (P = 0.0012). Bladder cancer patients with high CNTD2 expression had shorter overall survival (P < 0.001). In the meantime, univariate and multivariate analyses showed that the increased expression of CNTD2 was an independent factor for poor prognosis in bladder cancer patients (P < 0.001 and P < 0.001, respectively). CNTD2 expression is closely related to bladder cancer progression, and the high expression of CNTD2 may be an adverse biomarker in bladder cancer patients.

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.

Structural basis of DNA replication origin recognition by human Orc6 protein binding with DNA

The six-subunit origin recognition complex (ORC), a DNA replication initiator, defines the localization of the origins of replication in eukaryotes. The Orc6 subunit is the smallest and the least conserved among ORC subunits. It is required for DNA replication and essential for viability in all species. Orc6 in metazoans carries a structural homology with transcription factor TFIIB and can bind DNA on its own. Here, we report a solution structure of the full-length human Orc6 (HsOrc6) alone and in a complex with DNA. We further showed that human Orc6 is composed of three independent domains: N-terminal, middle and C-terminal (HsOrc6-N, HsOrc6-M and HsOrc6-C). We also identified a distinct DNA-binding domain of human Orc6, named as HsOrc6-DBD. The detailed analysis of the structure revealed novel amino acid clusters important for the interaction with DNA. Alterations of these amino acids abolish DNA-binding ability of Orc6 and result in reduced levels of DNA replication. We propose that Orc6 is a DNA-binding subunit of human/metazoan ORC and may play roles in targeting, positioning and assembling the functional ORC at the origins.

Changes in the Expression of Pre-Replicative Complex Genes in hTERT and ALT Pediatric Brain Tumors

Background: The up-regulation of a telomere maintenance mechanism (TMM) is a common feature of cancer cells and a hallmark of cancer. Routine methods for detecting TMMs in tumor samples are still missing, whereas telomerase targeting treatments are becoming available. In paediatric cancers, alternative lengthening of telomeres (ALT) is found in a subset of sarcomas and malignant brain tumors. ALT is a non-canonical mechanism of telomere maintenance developed by cancer cells with no-functional telomerase. Methods: To identify drivers and/or markers of ALT, we performed a differential gene expression analysis between two zebrafish models of juvenile brain tumors, that differ only for the telomere maintenance mechanism adopted by tumor cells: one is ALT while the other is telomerase-dependent. Results: Comparative analysis of gene expression identified five genes of the pre-replicative complex, ORC4, ORC6, MCM2, CDC45 and RPA3 as upregulated in ALT. We searched for a correlation between telomerase levels and expression of the pre-replicative complex genes in a cohort of paediatric brain cancers and identified a counter-correlation between telomerase expression and the genes of the pre-replicative complex. Moreover, the analysis of ALT markers in a group of 20 patients confirmed the association between ALT and increased RPA and decreased H3K9_me3 localization at telomeres. Conclusions: Our study suggests that telomere maintenance mechanisms may act as a driver of telomeric DNA replication and chromatin status in brain cancers and identifies markers of ALT that could be exploited for precise prognostic and therapeutic purposes.

MCMs in Cancer: Prognostic Potential and Mechanisms

Enabling replicative immortality and uncontrolled cell cycle are hallmarks of cancer cells. Minichromosome maintenance proteins (MCMs) exhibit helicase activity in replication initiation and play vital roles in controlling replication times within a cell cycle. Overexpressed MCMs are detected in various cancerous tissues and cancer cell lines. Previous studies have proposed MCMs as promising proliferation markers in cancers, while the prognostic values remain controversial and the underlying mechanisms remain unascertained. This review provides an overview of the significant findings regarding the cellular and tumorigenic functions of the MCM family. Besides, current evidence of the prognostic roles of MCMs is retrospectively reviewed. This work also offers insight into the mechanisms of MCMs prompting carcinogenesis and adverse prognosis, providing information for future research. Finally, MCMs in liver cancer are specifically discussed, and future perspectives are provided.