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Functional annotation of up-regulated genes in NSCLC (A); and down-regulated genes in NSCLC compared to control (B). GO, Gene Ontology; BP, Biological Processes; MF, Molecular Function; CC, Cell Component; KEGG, Kyoto Encyclopedia of Genes and Genomes.
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Background: Loss of control on cell division is an important factor for the development of non-small cell lung cancer (NSCLC), however, its molecular mechanism and gene regulatory network are not clearly understood. This study utilized the systems bioinformatics approach to reveal the “driver-network” involve in tumorigenic processes in NSCLC.
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Introduction
In sarcoidosis, peripheral lymphopenia and anergy have been associated with increased inflammation and maladaptive immune activity, likely promoting development of chronic and progressive disease. However, the molecular mechanisms that lead to reduced lymphocyte proportions, particularly CD4+ T-cells, have not been fully elucidated. We...
Citations
... Without loss of generality, we focus on the case where larger values of y correspond to a higher cell division rate (i.e. a higher proliferative potential), and larger values of x correspond to a higher probability for changes in proliferative potential to occur (i.e. a higher evolvability). The variable y could represent the normalised level of expression of a gene that regulates cell division -such as MKI67, BIRC5, CCNB1, CDC20, CEP55, NDC80, TYMS, NUF2, UBE2C, PTTG1, and RRM2 [43,44,45], while the variable x could relate to the degree of variation of the level of expression of such a gene over time and, therefore, could be connected with the normalised level of expression of a gene that controls the expression of genes regulating cell division -such as FOXM1, MYBL2 or TOP2A [44,46]. ...
Evolvability is defined as the ability of a population to generate heritable variation to facilitate its adaptation to new environments or selection pressures. In this article, we consider evolvability as a phenotypic trait subject to evolution and discuss its implications in the adaptation of cell populations. We explore the evolutionary dynamics of an actively proliferating population of cells subject to changes in their proliferative potential and their evolvability using a stochastic individual-based model and its deterministic continuum counterpart through numerical simulations of these models. We find robust adaptive trajectories that rely on cells with high evolvability rapidly exploring the phenotypic landscape and reaching the proliferative potential with the highest fitness. The strength of selection on the proliferative potential, and the cost associated with evolvability, can alter these trajectories such that, if both are sufficiently constraining, highly evolvable populations can become extinct in our individual-based model simulations. We explore the impact of this interaction at various scales, discussing its effects in undisturbed environments and also in disrupted contexts, such as cancer.
... Silencing of HS6ST2 reduces tumorigenesis and metastasis in human pancreatic cancer through Notch-mediated epithelial-mesenchymal transition (EMT) 21 . Moreover, HS6ST2 is elevated in non-small cell lung cancer (NSCLC) 22 , and HS6ST2 overexpression is related with progression of NSCLC 23 . In addition, silencing HS6ST2 decreases the viability of human lung and ovarian cell lines in the presence of a sublethal dose of Taxol 24 . ...
... The significance of HS6ST2 expression and prognosis relevance in different malignancies were first examined. In line with other prior investigations, ours indicated that HS6ST2 was dysregulated in 13 distinct cancer types 14,15,20,22,23 but inconsistent with one study 18 . For instance, HS6ST2 is overexpressed in thyroid cancer, and HS6ST2 overexpression is correlated with the progression of thyroid cancer 14,15 . ...
... Silencing of HS6ST2 reduced the transcriptional activity mediated by Smad2/3/4, thereby inhibiting the production of IL-11 induced by TGF-β, resulting in the inhibition of breast tumor growth 20 . Another study illustrated that HS6ST2 was upregulated in NSCLC 22 and promoted cell development in NSCLC 23 . Our findings in renal clear cell cancer contradict those of earlier studies 17 , which showed that HS6ST2 is a potential prognostic biomarker and that inhibition of HS6ST2 causes decreased migration and invasion of RCC cells 18 . ...
HS6ST2 has ability to encodes a member of the heparan sulfate (HS) sulfotransferase gene family, which catalyze the transfer of sulfate to HS and a crucial regulator of cell growth, differentiation, adhesion, and migration. Although mounting evidence supports a vital role for HS6ST2 in tumorigenesis of some cancers, no pan-cancer analysis of HS6ST2 has been reported. Therefore, we aimed to explore the prognostic value of HS6ST2 in 33 cancer types and investigate its potential immune function. Based on data from The Cancer Genome Atlas, Cancer Cell Lines Encyclopedia, Genotype Tissue Expression, and GSCA, we used a range of bioinformatics approaches to explore the potential carcinogenic role of HS6ST2, analysis of HS6ST2 and prognosis, DNA methylation, RNA methylation, microsatellite instability (MSI), tumor mutation burden (TMB), and immune cell infiltration in different tumors. The results show that HS6ST2 was highly expressed in most cancers but lower in Breast invasive carcinoma, Kidney Chromophobe, Kidney renal clear cell carcinoma, Kidney renal papillary cell carcinoma, and Uterine Corpus Endometrial Carcinoma. Moreover, HS6ST2 is positively or negatively associated with prognosis in different cancers. HS6ST2 expression was not only associated with MSI in 5 cancer types and associated with TMB in 10 cancer types, and it's significantly correlated with DNA methylation in 13 types of cancer, but it's correlated with RNA methylation related genes in most cancer. HS6ST2 expression was correlated with immune cell infiltration, immune-related genes, tumor immune microenvironment, and drug resistance in various cancers. Eventually, HS6ST2 was validated in human lung adenocarcinoma tissues. Our study reveals that HS6ST2 can function as a prognostic marker in various malignant tumors because of its role in tumorigenesis and tumor immunity.
... The gene expression profiles have been extensively used to understand the molecular mechanisms of diseases and to find biomarkers and novel targets [54][55][56][57]. Therefore, the present work analyzed DEGs to understand the biological processes affected in the islets of T2D mice. ...
Type 2 diabetes (T2D) is a major global health problem often caused by the inability of pancreatic islets to compensate for the high insulin demand due to apoptosis. However, the complex mechanisms underlying the activation of apoptosis and its counter process, anti-apoptosis, during T2D remain unclear. In this study, we employed bioinformatics and systems biology approaches to understand the anti-apoptosis-associated gene expression and the biological network in the pancreatic islets of T2D mice. First, gene expression data from four peripheral tissues (islets, liver, muscle and adipose) were used to identify differentially expressed genes (DEGs) in T2D compared to non-T2D mouse strains. Our comparative analysis revealed that Gm2036 is upregulated across all four tissues in T2D and is functionally associated with increased cytosolic Ca²⁺ levels, which may alter the signal transduction pathways controlling metabolic processes. Next, our study focused on islets and performed functional enrichment analysis, which revealed that upregulated genes are significantly associated with sucrose and fructose metabolic processes, as well as negative regulation of neuron apoptosis. Using the Ingenuity Pathway Analysis (IPA) tool of QIAGEN, gene regulatory networks and their biological effects were analyzed, which revealed that glucose is associated with the underlying change in gene expression in the islets of T2D; and an activated gene regulatory network—containing upregulated CCK, ATF3, JUNB, NR4A1, GAST and downregulated DPP4—is possibly inhibiting apoptosis of islets and β-cells in T2D. Our computational-based study has identified a putative regulatory network that may facilitate the survival of pancreatic islets in T2D; however, further validation in a larger sample size is needed. Our results provide valuable insights into the underlying mechanisms of T2D and may offer potential targets for developing more efficacious treatments.
... MYBL2 has been related to the proliferation and migration of NSCLC cells [32], as well as genomic instability in lung adenocarcinoma [33]. MYBL2 and FOXM1 have been identified as the upstream regulators of a local "driver network" related to NSCLC cell proliferation [34]. MYBL2 and FOXM1 were related to cancer-specific enhancers, and its high expression in lung adenocarcinomas has been related to poor patient survival [35]. ...
The transcriptomic analysis of microarray and RNA-Seq datasets followed our own bioinformatic pipeline to identify a transcriptional regulatory network of lung cancer. Twenty-six transcription factors are dysregulated and co-expressed in most of the lung cancer and pulmonary arterial hypertension datasets, which makes them the most frequently dysregulated transcription factors. Co-expression, gene regulatory, coregulatory, and transcriptional regulatory networks, along with fibration symmetries, were constructed to identify common connection patterns, alignments, main regulators, and target genes in order to analyze transcription factor complex formation, as well as its synchronized co-expression patterns in every type of lung cancer. The regulatory function of the most frequently dysregulated transcription factors over lung cancer deregulated genes was validated with ChEA3 enrichment analysis. A Kaplan–Meier plotter analysis linked the dysregulation of the top transcription factors with lung cancer patients’ survival. Our results indicate that lung cancer has unique and common deregulated genes and transcription factors with pulmonary arterial hypertension, co-expressed and regulated in a coordinated and cooperative manner by the transcriptional regulatory network that might be associated with critical biological processes and signaling pathways related to the acquisition of the hallmarks of cancer, making them potentially relevant tumor biomarkers for lung cancer early diagnosis and targets for the development of personalized therapies against lung cancer.
... In the past few decades, studies have used different approaches to identify the genes and mutation signatures underpinning lung cancer, leading to new therapeutic targets for better treatment. A previous study used an integrative systems biology approach and revealed a driver network that promotes cell proliferation in NSCLC, which could be a promising therapeutic target [16]. Interestingly, the study found that the driver network consisted of 26 upregulated genes associated with spindles, kinetochores, nuclear division, chromosome segregation, and the cell cycle G2/M transition and their upstream regulators, FOXM1 and MYBL2 [16]. ...
... A previous study used an integrative systems biology approach and revealed a driver network that promotes cell proliferation in NSCLC, which could be a promising therapeutic target [16]. Interestingly, the study found that the driver network consisted of 26 upregulated genes associated with spindles, kinetochores, nuclear division, chromosome segregation, and the cell cycle G2/M transition and their upstream regulators, FOXM1 and MYBL2 [16]. A recent study used gene expression data from the TGFβ-induced epithelial-mesenchymal transition in NSCLC cells and identified a cluster of differentially expressed genes associated with specific metabolic processes such as glycolysis, pyruvate metabolism, and the tricarboxylic acid cycle [17]. ...
The lack of precise molecular signatures limits the early diagnosis of non-small cell lung cancer (NSCLC). The present study used gene expression data and interaction networks to develop a highly accurate model with the least absolute shrinkage and selection operator (LASSO) for predicting NSCLC. The differentially expressed genes (DEGs) were identified in NSCLC compared with normal tissues using TCGA and GTEx data. A biological network was constructed using DEGs, and the top 20 upregulated and 20 downregulated hub genes were identified. These hub genes were used to identify signature genes with penalized logistic regression using the LASSO to predict NSCLC. Our model’s development involved the following steps: (i) the dataset was divided into 80% for training (TR) and 20% for Testing Dataset 1 (TD1); (ii) a LASSO logistic regression analysis was performed on the TR with 10-fold cross-validation and identified a combination of 17 genes as NSCLC predictors, which were used further for development of the LASSO model. The model’s performance was accessed on the TD1 dataset and achieved an accuracy and an area under the curve of the receiver operating characteristics (AUC-ROC) of 0.986 and 0.999, respectively. Furthermore, the performance of the LASSO model was evaluated using three independent NSCLC datasets (GSE18842, GSE27262, GSE19804) and achieved high accuracy, with an AUC-ROC of >0.99, >0.99, and 0.95, respectively. Based on this study, a web application called NSCLCpred (https://hifzuransari.shinyapps.io/NSCLCpred/) was developed to predict NSCLC.
... In accordance with the previous finding that MYBL2 and FOXM1 control genes expressed in the G2/M phase of the cell cycle [35,36], we found that MYBL2 and FOXM1 regulate genes belonging to the G2/M phase in lung adenocarcinoma cells (Figure 3). For example, we showed that CENPA is one of the key targets of MYBL2 and FOXM1 in lung adenocarcinoma cells (Figure 4). ...
... We also found that cyclin B1 (CCNB1) is regulated by MYBL2 and FOXM1 (Figure 4), and overexpression of CCNB1 is associated with poor survival of lung adenocarcinoma patients (Supplementary Figure S1). CCNB1 was reported as one of the driver genes for lung cancer from the bioinformatic meta-analysis of gene expression data of non-small cell lung cancer with protein-protein interaction data [35]. CCNB1 interacts with CDK1 to form a complex that phosphorylates their substrates and promotes the G2/M transition in the cell cycle. ...
Overexpression of MYBL2 is associated with poor survival of lung adenocarcinoma patients, but the molecular mechanism by which it regulates transcription and carcinogenesis has not yet been elucidated. In this study, we performed ChIP-seq using an MYBL2-targeted antibody and discovered that MYBL2 primarily binds to the promoters of highly expressed genes in lung adenocarcinoma cells. Using a knockdown experiment of MYBL2 and global transcriptome profiling, we identified that over a thousand genes are dysregulated by MYBL2, and MYBL2 acts as a transcriptional activator in lung adenocarcinoma cells. Moreover, we revealed that the binding sites of FOXM1 are largely shared with MYBL2 binding sites, and genes involved in cell cycle phase transitions are regulated by these transcription factors. We furthermore investigated the effect of a previously reported FOXM1 inhibitor, FDI-6, in lung adenocarcinoma cells. We demonstrated that FDI-6 decreases the proliferation of lung adenocarcinoma cells and inhibits the activities of FOXM1 as well as MYBL2. Moreover, we found that genes involved in cell death and cell cycle are inhibited by FDI-6. Overall, our findings suggest that MYBL2 and FOXM1 activate cell cycle genes together, acting as oncogenic transcription factors in lung adenocarcinoma cells, and they are potential treatment targets for the disease.
... Cluster 11 is found to be characterized by the activation of the MYBL2 network with notable enrichment also in the RARB pathway. As regulators of cell proliferation, FOXM1 and MYBL2 have been previously described as key players in the development of small lung cancer 30 . Thus, this data is suggestive of a putative involvement of these networks in regeneration and differentiation processes in adult lung. ...
Mechanisms of epithelial renewal in the alveolar compartment remain incompletely understood. To this end, we aimed to characterize alveolar progenitors. Single-cell RNA-sequencing (scRNA-seq) analysis of the HTII-280 ⁺ /EpCAM ⁺ population from adult human lung revealed subclusters enriched for adult stem cell signature (ASCS) genes. We found that alveolar progenitors in organoid culture in vitro show phenotypic lineage plasticity as they can yield alveolar or bronchial cell-type progeny. The direction of the differentiation is dependent on the presence of the GSK-3β inhibitor, CHIR99021. By RNA-seq profiling of GSK-3β knockdown organoids we identified additional candidate target genes of the inhibitor, among others FOXM1 and EGF . This gives evidence of Wnt pathway independent regulatory mechanisms of alveolar specification. Following influenza A virus (IAV) infection organoids showed a similar response as lung tissue explants which confirms their suitability for studies of sequelae of pathogen-host interaction.
... [32] Another in-silico study by gene network analysis showed that FOXM1 and MYBL2 play a vital role in cancer cell growth and proliferation. [33] In gastric adenocarcinoma, it was found that high expression of MYBL2 causes cancer cells to differentiate and invade lymph nodes, the inhibition of which can be a binding antitumor effect [ Figure 4e]. [34] The next step is to identify drug agents that are able to inhibit or reduce the expression of mentioned genes that have an influential role in attenuating cancer stem cells. ...
Background and aim:
Glioblastoma multiform (GBM) is considered as one of the malignant brain tumors that affect a wide range of people every year. Cancer stem cells, as essential factors, are resistant to chemotherapy drugs and complicate treatments. Therefore, finding critical molecular pathways in GBM-derived stem cells, and selecting the appropriate drug agents can prove more effective treatment approaches for GBM.
Method:
In this study, using RNA-Seq data, we performed continuous bioinformatics analyses and examined the up-and down-regulated genes from GBM-derived stem cells samples. Afterward, we separated the signaling pathways using the KEGG database and measured the protein interactions with the STRING database. Then, using the Drug matrix database, we nominated drugs that could affect these genes.
Results:
The first 20 pathways on tumorigenesis and 41 up-regulated and 73 down-regulated genes were selected. These genes were most active in the pathways involved in cell division, metabolism, cytoskeleton, cell adhesion molecules, and extracellular space. We then examined the candidate genes and the approach of the drugs that target these genes. Chlorambucil, cyclosporine A, doxorubicin, and etoposide were selected as the drug agents.
Conclusion:
Using integrated bioinformatics analyses, it was found that prominent genes in the cell cycle and cytoskeletal pathways are more expressed in cancer stem cells and that Chlorambucil, cyclosporine A, doxorubicin, and etoposide can be effective compounds to attenuate these cells.
... Herin, we attempted to take the advanteges of using various computational methodological approaches and powerfull bioinformatics tools to construct our study. This approach is well recognized [83][84][85] and provides decent insight and understanding of the biological role of BARD1 in breast cancer evolution. ...
The full-length BRCA1-associated RING domain 1 (BARD1) gene encodes a 777-aa protein. BARD1 displays a dual role in cancer development and progression as it acts as a tumor suppressor and an oncogene. Structurally, BARD1 has homologous domains to BRCA1 that aid their heterodimer interaction to inhibit the progression of different cancers such as breast and ovarian cancers following the BRCA1-dependant pathway. In addition, BARD1 was shown to be involved in other pathways that are involved in tumor suppression (BRCA1-independent pathway) such as the TP53-dependent apoptotic signaling pathway. However, there are abundant BARD1 isoforms exist that are different from the full-length BARD1 due to nonsense and frameshift mutations, or deletions were found to be associated with susceptibility to various cancers including neuroblastoma, lung, breast, and cervical cancers. This article reviews the spectrum of BARD1 full-length genes and its different isoforms and their anticipated associated risk. Additionally, the study also highlights the role of BARD1 as an oncogene in breast cancer patients and its potential uses as a prognostic/diagnostic biomarker and as a therapeutic target for cancer susceptibility testing and treatment.
... Heparan sulfate 6-O-sulfotransferase (HS6ST) is involved in various biological processes [29,30]. Specifically, HS6ST2 is involved in the pathogenesis of malignant tumors and up regulated in different tumor types, such as thyroid [31,32], colorectal [33], and lung cancers [33,34]. ...
... Emerging evidence suggests that HS6ST2 is involved in biological functions of cancer cells [30,[57][58][59][60][61]. Also, HS6ST2 has been found to be overexpressed in lung cancer and is identified as an inferior prognosticator [34]. However, HS6ST2 expression, regulation, and clinical significance in lung cancer have not yet been elucidated. ...
Long non-coding RNAs (lncRNAs) are crucial regulators of cancer pathogenesis and are potentially useful diagnostic and prognostic biomarker tools. FAM83H antisense RNA1 (FAM83H-AS1) has been reported to be a vital regulator of different cancers; however, little attention has been paid to its significance in lung cancer. Non-tumorigenic lung cell line BEAS-2B and adenocarcinoma lung cancer cell lines NCI-H1299 and HCC827 were used in the present study. In addition, RNA immunoprecipitation, Western blotting, quantitative reverse transcription-PCR (qRT-PCR), and luciferase reporter assays were used to dissect the role of FAM83H-AS1 in lung cancer progression. The results revealed that FAM83H-AS1 is highly expressed in lung cancer tissues, and its knockdown inhibits lung cancer cell invasion and proliferation reducing tumor growth in vivo. Besides, we found that FAM83H-AS1 targets miR-545-3p, and a negative correlation exists between their expression in lung cancer tissues. Simultaneously, miR-545-3p negatively regulates heparan sulfate 6-O-sulfotransferase (HS6ST2). Moreover, inhibition of miR-545-3p promoted HS6ST2 protein expression and lung cancer cell invasion. FAM83H-AS1 favors non-small cell lung cancer by targeting the miR-545-3p/HS6ST2 axis, supporting the possibility of developing FAM83H-AS1 as a target for NSCLC intervention.
