Integrated Network Analysis Reveals FOXM1 and MYBL2 as Key Regulators of Cell Proliferation in Non-small Cell Lung Cancer

FOXM1 transcriptional regulation

FOXM1 is a key transcriptional regulator involved in various biological processes in mammals, including carbohydrate and lipid metabolism, aging, immune regulation, development, and disease. Early studies have shown that FOXM1 acts as an oncogene by regulating cell proliferation, cell cycle, migration, metastasis, and apoptosis, as well as genes related to diagnosis, treatment, chemotherapy resistance, and prognosis. Researchers are increasingly focusing on FOXM1 functions in tumor microenvironment, epigenetics, and immune infiltration. However, researchers have not comprehensively described FOXM1's involvement in tumor microenvironment shaping, epigenetics, and immune cell infiltration. Here we review the role of FOXM1 in the formation and development of malignant tumors, and we will provide a comprehensive summary of the role of FOXM1 in transcriptional regulation, interacting proteins, tumor microenvironment, epigenetics, and immune infiltration, and suggest areas for further research.

Pancancer analysis of the correlations of HS6ST2 with prognosis, tumor immunity, and drug resistance

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.

Optimal Supervised Reduction of High Dimensional Transcription Data

The plight of navigating high-dimensional transcription datasets remains a persistent problem. This problem is further amplified for complex disorders, such as cancer as these disorders are often multigenic traits with multiple subsets of genes collectively affecting the type, stage, and severity of the trait. We are often faced with a trade off between reducing the dimensionality of our datasets and maintaining the integrity of our data. To accomplish both tasks simultaneously for very high dimensional transcriptome for complex multigenic traits, we propose a new supervised technique, Class Separation Transformation (CST). CST accomplishes both tasks simultaneously by significantly reducing the dimensionality of the input space into a one-dimensional transformed space that provides optimal separation between the differing classes. Furthermore, CST offers an means of explainable ML, as it computes the relative importance of each feature for its contribution to class distinction, which can thus lead to deeper insights and discovery. We compare our method with existing state-of-the-art methods using both real and synthetic datasets, demonstrating that CST is the more accurate, robust, scalable, and computationally advantageous technique relative to existing methods. Code used in this paper is available on https://github.com/richiebailey74/CST.

Glycoprotein M6A upregulation detected by transcriptome analysis controls the proliferation of keloidal fibroblasts

Hypertrophic scars and keloids are fibroproliferative disorders caused by abnormal wound healing. Their exact cause has not been found, but abnormalities during the wound healing process including inflammatory, immune, genetic, and other factors are thought to predispose an individual to excessive scarring. In the present study, we performed transcriptome analysis of established keloid cell lines (KEL FIB), focusing on gene expression analysis and fusion gene detection for the first time. For gene expression analysis, fragments per kilobase per million map read values were calculated, which were validated by real-time PCR and immunohistochemistry. Fusion genes were predicted by transcriptome sequence, and validated by Sanger sequence and G-banding. As a result, GPM6A was shown in the expression analysis to be upregulated in KEL FIB compared with normal fibroblasts. The GPM6A upregulation in KEL FIB was confirmed by real-time PCR, and GPM6A messenger ribonucleic acid expression was consistently significantly elevated in the tissues of hypertrophic scar and keloid compared to normal skin. Immunohistochemistry also revealed that the number of fibroblast-like spindle-shaped cells positive for GPM6A was significantly increased in keloidal tissues. GPM6A inhibition by small interfering ribonucleic acid significantly reduced the number of KEL FIB. On the other hand, although we hypothesized that fusion genes are involved in the pathogenesis of keloids, the transcriptome analysis could not prove the presence of fusion genes in KEL FIB. Taken together, GPM6A upregulation may have an inducible effect on cell proliferation in keloidal fibroblasts. GPM6A can be a novel therapeutic target in hypertrophic scars and keloids. The inflammatory nature may be more prominent in the pathogenesis of keloids, rather than being skin tumors, as proposed by Ogawa et al. Future studies using several cell lines will be required.

Lung Cancer Gene Regulatory Network of Transcription Factors Related to the Hallmarks of Cancer

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.

A Systems Biology and LASSO-Based Approach to Decipher the Transcriptome-Interactome Signature for Predicting Non-Small Cell Lung Cancer

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 (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 assessed 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 0.998, respectively. Furthermore, the performance of the LASSO model was evaluated using three independent NSCLC test 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 was developed to predict NSCLC.

Characterizing and Targeting Genes Regulated by Transcription Factor MYBL2 in Lung Adenocarcinoma Cells

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.

Human alveolar progenitors generate dual lineage bronchioalveolar organoids

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.

FoxM1 Regulates Proliferation and Apoptosis of Human Neuroblastoma Cell through PI3K/AKT Pathway

Aim: This study investigated the effect of FoxM1 on the biological behavior of neuroblastoma (NB) cells in vitro and the association between FoxM1 and PI3K/AKT pathways in NB cell lines. Materials and methods: Recombinant plasmid pcDNA3.1 (+)-FoxM1 and FoxM1-specific small interfering RNA (siRNA) were transfected into IMR-32 cells by liposome transfection. The expression of FoxM1, AKT and PI3K were determined by qRT-PCR and western blotting. The effect of FoxM1 and PI3K/AKT pathways on the cell cycles and apoptosis were analyzed by flow cytometry. Cell viability and proliferation ability were assessed by CCK8 and colony formation assay. Results: Knockdown of FoxM1 promoted NB cell apoptosis and G1-phase cell cycle arrest significantly, increased the expression of apoptosis-related proteins, and suppressed the phospho-activation of PI3K and AKT. Over-expression of FoxM1 had the opposite effects. Conclusion: FoxM1 knockdown inhibited NB cell proliferation and induced apoptosis through inhibiting activation of PI3K and AKT.

BARD1 mystery: tumor suppressors are cancer susceptibility genes

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.

Expression pattern and prognostic significance of CDKs in breast cancer: An integrated bioinformatic study

BACKGROUND: Globally, breast cancer (BC) has become one of the most prevalent malignancies and the leading cause of tumor-related deaths among women. Dysregulation of the cell cycle is a well-known hallmark of cancer development and metastasis. CDKs are essential components of the cell-cycle regulatory system with aberrant expression in a variety of cancers, including BC. In the development of targeted cancer treatment, reestablishing the regulation of the cell cycle by modulation of CDKs has emerged as a promising approach. METHODS: Herein, we used a bioinformatic approach to assess the expression pattern, prognostic and diagnostic importance, and clinical relevance of CDKs in BC. Additionally, we conducted a functional enrichment analysis of deregulated CDKs using the STRING and KEGG databases to delineate the role of CDKs in breast tumorigenesis. RESULTS: Gene expression analysis revealed substantial deregulation of CDKs in BC, with CDK1, CDK11A, and CDK18 showing a fold change of >± 1.5. Also, metastatic tumors showed high expression of CDK1 in the single cell RNA sequencing analysis of primary and metastatic breast tumors. Additionally, it was found that dysregulated CDK expression affects overall survival (OS) and relapse-free survival (RFS) of BC patients. CONCLUSION: The study’s multimodal analytical methodologies imply that modulating CDKs for BC treatment is a promising approach.

Development and Validation of a Novel Stemness-Index-Related Long Noncoding RNA Signature for Breast Cancer Based on Weighted Gene Co-Expression Network Analysis

Background: Breast cancer (BC) is a major leading cause of woman deaths worldwide. Increasing evidence has revealed that stemness features are related to the prognosis and progression of tumors. Nevertheless, the roles of stemness-index-related long noncoding RNAs (lncRNAs) in BC remain unclear.

Methods: Differentially expressed stemness-index-related lncRNAs between BC and normal samples in The Cancer Genome Atlas database were screened based on weighted gene co-expression network analysis and differential analysis. Univariate Cox and least absolute shrinkage and selection operator regression analyses were performed to identify prognostic lncRNAs and construct a stemness-index-related lncRNA signature. Time-dependent receiver operating characteristic curves were plotted to evaluate the predictive capability of the stemness-index-related lncRNA signature. Moreover, correlation analysis and functional enrichment analyses were conducted to investigate the stemness-index-related lncRNA signature-related biological function. Finally, a quantitative real-time polymerase chain reaction was used to detect the expression levels of lncRNAs.

Results: A total of 73 differentially expressed stemness-index-related lncRNAs were identified. Next, FAM83H-AS1, HID1-AS1, HOXB-AS1, RP11-1070N10.3, RP11-1100L3.8, and RP11-696F12.1 were used to construct a stemness-index-related lncRNA signature, and receiver operating characteristic curves indicated that stemness-index-related lncRNA signature could predict the prognosis of BC well. Moreover, functional enrichment analysis suggested that differentially expressed genes between the high-risk group and low-risk group were mainly involved in immune-related biological processes and pathways. Furthermore, functional enrichment analysis of lncRNA-related protein-coding genes revealed that FAM83H-AS1, HID1-AS1, HOXB-AS1, RP11-1070N10.3, RP11-1100L3.8, and RP11-696F12.1 were associated with neuroactive ligand–receptor interaction, AMPK signaling pathway, PPAR signaling pathway, and cGMP-PKG signaling pathway. Finally, quantitative real-time polymerase chain reaction revealed that FAM83H-AS1, HID1-AS1, RP11-1100L3.8, and RP11-696F12.1 might be used as the potential diagnostic biomarkers of BC.

Conclusion: The stemness-index-related lncRNA signature based on FAM83H-AS1, HID1-AS1, HOXB-AS1, RP11-1070N10.3, RP11-1100L3.8, and RP11-696F12.1 could be used as an independent predictor for the survival of BC, and FAM83H-AS1, HID1-AS1, RP11-1100L3.8, and RP11-696F12.1 might be used as the diagnostic markers of BC.

Role of lncRNA FAM83H antisense RNA1 (FAM83H-AS1) in the progression of non-small cell lung cancer by regulating the miR-545-3p/heparan sulfate 6-O-sulfotransferase (HS6ST2) axis

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.

The role of Wnt pathway antagonists in early-stage lung adenocarcinoma

PURPOSE

We aimed to examine the expression levels of the genes encoding adenomatous polyposis coli (APC) 1, APC-2, Dickkopf related protein (DKK)-1, DKK-3, secreted frizzled-related protein (SFRP)-2, SFRP-4, and SFRP-5, which play roles in the Wnt signaling pathway, in lung adenocarcinoma and adjacent normal lung tissues and to evaluate their relationships with clinicopathologic factors.

MATERIALS AND METHODS

The expression levels of genes in formalin-fixed paraffin-embedded samples of tumor tissue and adjacent intact lung tissue from 57 patients who underwent surgery for lung adenocarcinoma between 2011 and 2018 were determined by real-time PCR analysis.

RESULTS

The expression levels of the DKK-1 in tumor tissue, especially in stage I-II tumor tissue, were significantly suppressed compared to those in normal tissue (p < 0.025). Whereas DKK-1 expression was suppressed in the tumor tissue of patients with early-stage lung adenocarcinoma, expression of the SFRP-5 in these patients was significantly higher in tumor tissue than in normal tissue (p < 0.039).

CONCLUSION

In our study, opposing regulation was found between the SFRP-5 and DKK-1, which are known to be extracellular antagonists of the Wnt signaling pathway. The SFRP-5 was found to have an oncogenic role in adenocarcinoma development. Studies of the opposing regulation between these genes in early-stage lung adenocarcinoma may shed light on the mechanisms associated with the development of carcinogenesis. The relationships or interactions of these genes may serve as potential therapeutic targets.

MYBL2 Gene Polymorphism Is Associated With Acute Lymphoblastic Leukemia Susceptibility in Children

Purpose

Although MYBL2 had been validated to participate in multiple cancers including leukemia, the role of MYBL2 polymorphisms in acute lymphoblastic leukemia (ALL) was still not clear. In this study, we aimed to evaluate the association between MYBL2 single nucleotide polymorphisms (SNPs) and ALL risk in children.

Methods

A total of 687 pediatric ALL cases and 971 cancer-free controls from two hospitals in South China were recruited. A case-control study by genotyping three SNPs in the MYBL2 gene (rs285162 C>T, rs285207 A>C, and rs2070235 A>G) was conducted. The associations were assessed by odds ratios (ORs) with corresponding 95% confidence intervals (CIs). Subgroup and stratification analyses were conducted to explore the association of rs285207 with ALL risk in terms of age, sex, immunophenotype, risk level, and other clinical characteristics. The false-positive report probability (FPRP) analysis was performed to verify each significant finding. Functional analysis in silico was used to evaluate the probability that rs285207 might influence the regulation of MYBL2 .

Results

Our study demonstrated that rs285207 was related to a decreased ALL risk (adjusted OR = 0.78; 95% CI = 0.63-0.97, P = 0.022) in the dominant model. The associations of rs285207 with ALL risk appeared stronger in patients with pre B ALL (adjusted OR=0.56; 95% CI=0.38-0.84, P=0.004), with normal diploid (adjusted OR=0.73; 95% CI=0.57-0.95, P=0.017), with low risk (adjusted OR=0.68; 95% CI=0.49-0.94, P=0.021), with lower WBC (adjusted OR=0.62; 95% CI=0.43-0.87, P=0.007) or lower platelet level (adjusted OR=0.76; 95% CI=0.59-0.96, P=0.023). With FPRP analysis, the significant association between the rs285207 polymorphism and decreased ALL risk was still noteworthy (FPRP=0.128). Functional analysis showed that IKZF1 bound to DNA motif overlapping rs285207 and had a higher preference for the risk allele A. As for rs285162 C>T and rs2070235 A>G, no significant was found between them and ALL risk.

Conclusion

In this study, we revealed that rs285207 polymorphism decreased the ALL risk in children, and rs285207 might alter the binding to IKZF1, which indicated that the MYBL2 gene polymorphism might be a potential biomarker of childhood ALL.

Ferroptosis-Related Gene Signature and Patterns of Immune Infiltration Predict the Overall Survival in Patients With Lung Adenocarcinoma

Background: Lung adenocarcinoma (LUAD) is a malignant tumor with high heterogeneity and poor prognosis. Ferroptosis, a form of regulated cell-death–related iron, has been proven to trigger inflammation-associated immunosuppression in the tumor microenvironment, which promotes tumor growth. Therefore, the clinical prognostic value of ferroptosis-related genes in LUAD needs to be further explored.

Method: In this study, we downloaded the mRNA expression profiles and corresponding clinical data of LUAD patients from the Cancer Genome Atlas database. The least absolute shrinkage and selection operator (LASSO) Cox regression model was utilized to construct ferroptosis-related gene signature. Based on these, we established the nomograms for prognosis prediction and validated the model in the GSE72094 dataset. The cell type was identified using the CIBERSORT algorithm for estimating relative subsets of RNA transcripts, which was then used to screen significant tumor immune-infiltrating cells associated with the LUAD prognosis prediction model. Subsequently, we applied co-expression analysis to reveal the relationship between ferroptosis-related genes and significant immune cells.

Results: The univariate COX regression analysis showed that 20 genes were associated with the overall survival (OS) as prognostic differentially expressed genes (DEGs) (FDR <0.05). Patients were divided into two risk groups using a 13-gene signature, with the high-risk group having a significantly worse OS than their low-risk counterparts (p < 0.001). We used receiver operating characteristic (ROC) curve analysis to confirm the predictive capacity of the signature. Besides, we identified seven pairs of ferroptosis-related genes and tumor-infiltrating immune cells associated with the prognosis of LUAD patients.

Conclusion: In this study, we construct a ferroptosis-related gene signature that can be used for prognostic prediction in LUAD. In addition, we reveal a potential connection between ferroptosis and tumor-infiltrating immune cells.

Analyzing the characteristics of immune cell infiltration in lung adenocarcinoma via bioinformatics to predict the effect of immunotherapy

Recent studies have shown that tumor immune cell infiltration (ICI) is associated with immunotherapy sensitivity and the prognosis of lung adenocarcinoma (LUAD). However, the immunoinfiltrative landscape of LUAD has not been elucidated. We propose two computational algorithms to unravel the ICI landscape to evaluate the efficacy of immunotherapy in LUAD patients. The raw data of LUAD patients from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases were analyzed. After merging these datasets and removing the batch differences, we used the Cell-type Identification By Estimating Relative Subsets Of RNA Transcripts (CIBERSORT) algorithm to obtain the immune cell content of all the samples. The unsupervised consistency clustering algorithm was used to analyze the ICI subtypes, and three subgroups were obtained. In addition, the unsupervised consistency clustering algorithm was used to analyze the differentially expressed genes (DEGs) of the ICI subtypes and obtain three ICI gene clusters. Finally, the ICI score was determined by using principal component analysis (PCA) for the gene signature. The ICI score of LUAD patients ranged from - 32.26 to 12.89 and represents the prognosis and the response to immunotherapy. High ICI scores were characterized by the T cell receptor signaling pathway, B cell receptor signaling pathway, and natural killer cell-mediated cytotoxicity, suggesting that some immune cells were activated and had increased activity, which may be the cause of the better prognosis for patients with high ICI scores. Additionally, patients with higher ICI scores showed a significant immune therapeutic advantage and clinical benefit. This study shows that the ICI score may be a potent prognostic biomarker and predictor of therapy with immune checkpoint inhibitors.

A Computational Approach Identified Andrographolide as a Potential Drug for Suppressing COVID-19-Induced Cytokine Storm

BACKGROUND

The newly identified betacoronavirus SARS-CoV-2 is the causative pathogen of the coronavirus disease of 2019 (COVID-19) that killed more than 3.5 million people till now. The cytokine storm induced in severe COVID-19 patients causes hyper-inflammation, is the primary reason for respiratory and multi-organ failure and fatality. This work uses a rational computational strategy to identify the existing drug molecules to target host pathways to reduce the cytokine storm.

RESULTS

We used a "host response signature network" consist of 36 genes induced by SARS-CoV-2 infection and associated with cytokine storm. In order to attenuate the cytokine storm, potential drug molecules were searched against "host response signature network". Our study identified that drug molecule andrographolide, naturally present in a medicinal plant Andrographis paniculata, has the potential to bind with crucial proteins to block the TNF-induced NFkB1 signaling pathway responsible for cytokine storm in COVID-19 patients. The molecular docking method showed the binding of andrographolide with TNF and covalent binding with NFkB1 proteins of the TNF signaling pathway.

CONCLUSION

We used a rational computational approach to repurpose existing drugs targeting host immunomodulating pathways. Our study suggests that andrographolide could bind with TNF and NFkB1 proteins, block TNF-induced cytokine storm in COVID-19 patients, and warrant further experimental validation.

A systematic dissection of the epigenomic heterogeneity of lung adenocarcinoma reveals two different subclasses with distinct prognosis and core regulatory networks

BACKGROUND

Lung adenocarcinoma (LUAD) is a highly malignant and heterogeneous tumor that involves various oncogenic genetic alterations. Epigenetic processes play important roles in lung cancer development. However, the variation in enhancer and super-enhancer landscapes of LUAD patients remains largely unknown. To provide an in-depth understanding of the epigenomic heterogeneity of LUAD, we investigate the H3K27ac histone modification profiles of tumors and adjacent normal lung tissues from 42 LUAD patients and explore the role of epigenetic alterations in LUAD progression.

RESULTS

A high intertumoral epigenetic heterogeneity is observed across the LUAD H3K27ac profiles. We quantitatively model the intertumoral variability of H3K27ac levels at proximal gene promoters and distal enhancers and propose a new epigenetic classification of LUAD patients. Our classification defines two LUAD subgroups which are highly related to histological subtypes. Group II patients have significantly worse prognosis than group I, which is further confirmed in the public TCGA-LUAD cohort. Differential RNA-seq analysis between group I and group II groups reveals that those genes upregulated in group II group tend to promote cell proliferation and induce cell de-differentiation. We construct the gene co-expression networks and identify group-specific core regulators. Most of these core regulators are linked with group-specific regulatory elements, such as super-enhancers. We further show that CLU is regulated by 3 group I-specific core regulators and works as a novel tumor suppressor in LUAD.

CONCLUSIONS

Our study systematically characterizes the epigenetic alterations during LUAD progression and provides a new classification model that is helpful for predicting patient prognosis.

MYB oncoproteins: emerging players and potential therapeutic targets in human cancer

MYB transcription factors are highly conserved from plants to vertebrates, indicating that their functions embrace fundamental mechanisms in the biology of cells and organisms. In humans, the MYB gene family is composed of three members: MYB, MYBL1 and MYBL2, encoding the transcription factors MYB, MYBL1, and MYBL2 (also known as c-MYB, A-MYB, and B-MYB), respectively. A truncated version of MYB, the prototype member of the MYB family, was originally identified as the product of the retroviral oncogene v-myb, which causes leukaemia in birds. This led to the hypothesis that aberrant activation of vertebrate MYB could also cause cancer. Despite more than three decades have elapsed since the isolation of v-myb, only recently investigators were able to detect MYB genes rearrangements and mutations, smoking gun evidence of the involvement of MYB family members in human cancer. In this review, we will highlight studies linking the activity of MYB family members to human malignancies and experimental therapeutic interventions tailored for MYB-expressing cancers.

Knowledge-Guided "Community Network" Analysis Reveals the Functional Modules and Candidate Targets in Non-Small-Cell Lung Cancer

Non-small-cell lung cancer (NSCLC) represents a heterogeneous group of malignancies that are the leading cause of cancer-related death worldwide. Although many NSCLC-related genes and pathways have been identified, there remains an urgent need to mechanistically understand how these genes and pathways drive NSCLC. Here, we propose a knowledge-guided and network-based integration method, called the node and edge Prioritization-based Community Analysis, to identify functional modules and their candidate targets in NSCLC. The protein–protein interaction network was prioritized by performing a random walk with restart algorithm based on NSCLC seed genes and the integrating edge weights, and then a “community network” was constructed by combining Girvan–Newman and Label Propagation algorithms. This systems biology analysis revealed that the CCNB1-mediated network in the largest community provides a modular biomarker, the second community serves as a drug regulatory module, and the two are connected by some contextual signaling motifs. Moreover, integrating structural information into the signaling network suggested novel protein–protein interactions with therapeutic significance, such as interactions between GNG11 and CXCR2, CXCL3, and PPBP. This study provides new mechanistic insights into the landscape of cellular functions in the context of modular networks and will help in developing therapeutic targets for NSCLC.

CircRNA ZNF609 Knockdown Represses the Development of Non-Small Cell Lung Cancer via miR-623/FOXM1 Axis

Background

The dysregulated circular RNAs (circRNAs) are relevant to the development of non-small cell lung cancer (NSCLC). Nevertheless, the function and mechanism of circRNA zinc finger protein 609 (circZNF609) in NSCLC development remain uncertain.

Methods

Sixty-two NSCLC patients were recruited. circZNF609, microRNA-623 (miR-623) and forkhead box M1 (FOXM1) abundances were measured via quantitative reverse transcription polymerase chain reaction or Western blot. Cell viability, apoptosis, migration and invasion were analyzed via cell counting kit-8 (CCK8), flow cytometry, caspase3 activity, transwell assay and Western blot. The interaction between miR-623 and circZNF609 or FOXM1 was analyzed via dual-luciferase reporter analysis, RNA immunoprecipitation and pull-down. The function of circZNF609 on cell growth in vivo was tested via xenograft model.

Results

circZNF609 abundance was enhanced in NSCLC tissues and cells. High expression of circZNF609 indicated the lower overall survival. circZNF609 interference restrained cell viability, migration and invasion and increased apoptosis. miR-623 was targeted via circZNF609. FOXM1 was targeted via miR-623 and regulated via circZNF609. miR-623 knockdown or FOXM1 overexpression mitigated the role of circZNF609 silence in NSCLC development. circZNF609 knockdown decreased NSCLC xenograft tumor growth.

Conclusion

circZNF609 knockdown repressed NSCLC development via regulating miR-623 and FOXM1.

A Comprehensive Analysis of cis-Acting RNA Elements in the SARS-CoV-2 Genome by a Bioinformatics Approach

The emergence of a new coronavirus (CoV), severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), responsible for severe respiratory disease in humans termed coronavirus disease of 2019 (COVID-19), became a new global threat for health and the economy. The SARS-CoV-2 genome is about a 29,800-nucleotide-long plus-strand RNA that can form functionally important secondary and higher-order structures called cis-acting RNA elements. These elements can interact with viral proteins, host proteins, or other RNAs and be involved in regulating translation and replication processes of the viral genome and encapsidation of the virus. However, the cis-acting RNA elements and their biological roles in SARS-CoV-2 as well as their comparative analysis in the closely related viral genome have not been well explored, which is very important to understand the molecular mechanism of viral infection and pathogenies. In this study, we used a bioinformatics approach to identify the cis-acting RNA elements in the SARS-CoV-2 genome. Initially, we aligned the full genomic sequence of six different CoVs, and a phylogenetic analysis was performed to understand their evolutionary relationship. Next, we predicted the cis-acting RNA elements in the SARS-CoV-2 genome using the structRNAfinder tool. Then, we annotated the location of these cis-acting RNA elements in different genomic regions of SARS-CoV-2. After that, we analyzed the sequence conservation patterns of each cis-acting RNA element among the six CoVs. Finally, the presence of cis-acting RNA elements across different CoV genomes and their comparative analysis was performed. Our study identified 12 important cis-acting RNA elements in the SARS-CoV-2 genome; among them, Corona_FSE, Corona_pk3, and s2m are highly conserved across most of the studied CoVs, and Thr_leader, MAT2A_D, and MS2 are uniquely present in SARS-CoV-2. These RNA structure elements can be involved in viral translation, replication, and encapsidation and, therefore, can be potential targets for better treatment of COVID-19. It is imperative to further characterize these cis-acting RNA elements experimentally for a better mechanistic understanding of SARS-CoV-2 infection and therapeutic intervention.

A Network-Based Analysis Reveals the Mechanism Underlying Vitamin D in Suppressing Cytokine Storm and Virus in SARS-CoV-2 Infection

Background

SARS-CoV-2 causes ongoing pandemic coronavirus disease of 2019 (COVID-19), infects the cells of the lower respiratory tract that leads to a cytokine storm in a significant number of patients resulting in severe pneumonia, shortness of breathing, respiratory and organ failure. Extensive studies suggested the role of Vitamin D in suppressing cytokine storm in COVID-19 and reducing viral infection; however, the precise molecular mechanism is not clearly known. In this work, bioinformatics and systems biology approaches were used to understand SARS-CoV-2 induced cytokine pathways and the potential mechanism of Vitamin D in suppressing cytokine storm and enhancing antiviral response.

Results

This study used transcriptome data and identified 108 differentially expressed host genes (DEHGs) in SARS-CoV-2 infected normal human bronchial epithelial (NHBE) cells compared to control. Then, the DEHGs was integrated with the human protein-protein interaction data to generate a SARS-CoV-2 induced host gene regulatory network (SiHgrn). Analysis of SiHgrn identified a sub-network "Cluster 1" with the highest MCODE score, 31 up-regulated genes, and predominantly associated immune and inflammatory response. Interestingly, the iRegulone tool identified that "Cluster 1" is under the regulation of transcription factors STAT1, STAT2, STAT3, POU2F2, and NFkB1, collectively referred to as "host response signature network". Functional enrichment analysis with NDEx revealed that the "host response signature network" is predominantly associated with critical pathways, including "cytokines and inflammatory response", "non-genomic action of Vitamin D", "the human immune response to tuberculosis", and "lung fibrosis". Finally, in-depth analysis and literature mining revealed that Vitamin D binds with its receptor and could work through two different pathways: (i) it inhibits the expression of pro-inflammatory cytokines through blocking the TNF induced NFkB1 signaling pathway; and (ii) it initiates the expression of interferon-stimulating genes (ISGs) for antiviral defense program through activating the IFN-α induced Jak-STAT signaling pathway.

Conclusion

This comprehensive study identified the pathways associated with cytokine storm in SARS-CoV-2 infection. The proposed underlying mechanism of Vitamin D could be promising in suppressing the cytokine storm and inducing a robust antiviral response in severe COVID-19 patients. The finding in this study urgently needs further experimental validations for the suitability of Vitamin D in combination with IFN-α to control severe COVID-19.

Investigating the pathogenic SNPs in BLM helicase and their biological consequences by computational approach

The BLM helicase protein plays a vital role in DNA replication and the maintenance of genomic integrity. Variation in the BLM helicase gene resulted in defects in the DNA repair mechanism and was reported to be associated with Bloom syndrome (BS) and cancer. Despite extensive investigation of helicase proteins in humans, no attempt has previously been made to comprehensively analyse the single nucleotide polymorphism (SNPs) of the BLM gene. In this study, a comprehensive analysis of SNPs on the BLM gene was performed to identify, characterize and validate the pathogenic SNPs using computational approaches. We obtained SNP data from the dbSNP database version 150 and mapped these data to the genomic coordinates of the "NM_000057.3" transcript expressing BLM helicase (P54132). There were 607 SNPs mapped to missense, 29 SNPs mapped to nonsense, and 19 SNPs mapped to 3'-UTR regions. Initially, we used many consensus tools of SIFT, PROVEAN, Condel, and PolyPhen-2, which together increased the accuracy of prediction and identified 18 highly pathogenic non-synonymous SNPs (nsSNPs) out of 607 SNPs. Subsequently, these 18 high-confidence pathogenic nsSNPs were analysed for BLM protein stability, structure-function relationships and disease associations using various bioinformatics tools. These 18 mutants of the BLM protein along with the native protein were further investigated using molecular dynamics simulations to examine the structural consequences of the mutations, which might reveal their malfunction and contribution to disease. In addition, 28 SNPs were predicted as "stop gained" nonsense SNPs and one SNP was predicted as "start lost". Two SNPs in the 3'UTR were found to abolish miRNA binding and thus may enhance the expression of BLM. Interestingly, we found that BLM mRNA overexpression is associated with different types of cancers. Further investigation showed that the dysregulation of BLM is associated with poor overall survival (OS) for lung and gastric cancer patients and hence led to the conclusion that BLM has the potential to be used as an important prognostic marker for the detection of lung and gastric cancer.

Global targetome analysis reveals critical role of miR-29a in pancreatic stellate cell mediated regulation of PDAC tumor microenvironment

BACKGROUND

Pancreatic ductal adenocarcinoma (PDAC) is one of the most aggressive forms of malignancies with a nearly equal incidence and mortality rates in patients. Pancreatic stellate cells (PSCs) are critical players in PDAC microenvironment to promote the aggressiveness and pathogenesis of the disease. Dysregulation of microRNAs (miRNAs) have been shown to play a significant role in progression of PDAC. Earlier, we observed a PSC-specific downregulation of miR-29a in PDAC pancreas, however, the mechanism of action of the molecule in PSCs is still to be elucidated. The current study aims to clarify the regulation of miR-29a in PSCs and identifies functionally important downstream targets that contribute to tumorigenic activities during PDAC progression.

METHODS

In this study, using RNAseq approach, we performed transcriptome analysis of paired miR-29a overexpressing and control human PSCs (hPSCs). Enrichment analysis was performed with the identified differentially expressed genes (DEGs). miR-29a targets in the dataset were identified, which were utilized to create network interactions. Western blots were performed with the top miR-29a candidate targets in hPSCs transfected with miR-29a mimic or scramble control.

RESULTS

RNAseq analysis identified 202 differentially expressed genes, which included 19 downregulated direct miR-29a targets. Translational repression of eight key pro-tumorigenic and -fibrotic targets namely IGF-1, COL5A3, CLDN1, E2F7, MYBL2, ITGA6 and ADAMTS2 by miR-29a was observed in PSCs. Using pathway analysis, we find that miR-29a modulates effectors of IGF-1-p53 signaling in PSCs that may hinder carcinogenesis. We further observe a regulatory role of the molecule in pathways associated with PDAC ECM remodeling and tumor-stromal crosstalk, such as INS/IGF-1, RAS/MAPK, laminin interactions and collagen biosynthesis.

CONCLUSIONS

Together, our study presents a comprehensive understanding of miR-29a regulation of PSCs, and identifies essential pathways associated with PSC-mediated PDAC pathogenesis. The findings suggest an anti-tumorigenic role of miR-29a in the context of PSC-cancer cell crosstalk and advocates for the potential of the molecule in PDAC targeted therapies.

Identification of Candidate Genes Associated with Breast Cancer Prognosis

Breast cancer (BC) is the most malignant tumor in women. The molecular mechanisms underlying tumorigenesis still need to be further elucidated. It is necessary to investigate novel candidate genes involved in breast cancer progression and prognosis. In this study, we commit to explore candidate genes that associate with prognosis and therapy in BC by a comprehensive bioinformatic analysis. Four GEO datasets (GSE5764, GSE7904, GSE20711, and GSE29431) and the BC-related transcriptome data in TCGA database were downloaded and used to identify the differently expressed genes (DEGs). The function of DEGs was analyzed by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways enrichment analysis. The protein-protein interaction (PPI) network of DEGs was constructed to identify hub genes. Prognostic candidate genes were identified through survival analysis. In addition, potential therapeutic targets were identified by constructed gene-drug interaction network through Comparative Toxicogenomics Database. A total of 547 DEGs (302 up and 245 down) were identified. Three core-subnetwork and 25 hub genes were identified in PPI network. Seven genes (namely COL12A1, QPRT, MRPL13, KRT14, KRT15, LAMB3, and MYBPC1) were identified as crucial prognostic candidate genes, which significantly associated with breast cancer overall survival. Furthermore, two representative candidate genes (COL12A1 and LAMB3) were optionally chosen for verification by reverse transcription and quantitative real-time polymerase chain reaction (RT-PCR). What's more, the gene-drugs interaction analysis indicates several antitumor drugs that could affect the expression of these prognostic markers, such as doxorubicin, cisplatin, and tamoxifen. These results identified seven crucial candidate genes that may serve as prognosis biomarkers and novel therapeutic targets of breast cancer, which may facilitate further understanding the molecular pathogenesis and providing potential therapeutic strategies for BC.

Bioinformatics Analysis Reveals Biomarkers With Cancer Stem Cell Characteristics in Lung Squamous Cell Carcinoma

Background

Tumor stem cells play important roles in the survival, proliferation, metastasis and recurrence of tumors. We aimed to identify new prognostic biomarkers for lung squamous cell carcinoma (LUSC) based on the cancer stem cell theory.

Methods

RNA-seq data and relevant clinical information were downloaded from The Cancer Genome Atlas (TCGA) database. Weighted gene coexpression network analysis (WGCNA) was applied to identify significant modules and hub genes, and prognostic signatures were constructed with the prognostic hub genes.

Results

LUSC patients in the TCGA database have higher mRNA expression-based stemness index (mRNAsi) in tumor tissue than in adjacent normal tissue. In addition, some clinical features and outcomes were highly correlated with the mRNAsi. WGCNA revealed that the pink and yellow modules were the most significant modules related to the mRNAsi; the top 10 hub genes in the pink module were enriched mostly in epidermal development, the secretory granule membrane, receptor regulator activity and the cytokine-cytokine receptor interaction. The protein–protein interaction (PPI) network revealed that the top 10 hub genes were significantly correlated with each other at the transcriptional level. In addition, the top 10 hub genes were all highly expressed in LUSC, and some were differentially expressed in different TNM stages. Regarding the survival analysis, the nomogram of a prognostic signature with three hub genes showed high predictive value.

Conclusion

mRNAsi-related hub genes could be a potential biomarker of LUSC.

Overexpression of MYBL2 promotes proliferation and migration of non-small-cell lung cancer via upregulating NCAPH

MYB Proto-Oncogene Like 2 (MYBL2) is a highly conserved member of the Myb family of transcription factors and plays a critical role in regulating cell proliferation and survival. Here we show that overexpression of MYBL2 is frequently observed in lung adenocarcinoma (LUAD) and significantly correlates with advanced stage and poor patient survival. Knockdown of MYBL2 induced apoptosis in lung cancer cells and resulted in significant inhibition of cell proliferation, migration, and invasion. Notably, we identified Non-SMC Condensin I Complex Subunit H (NCAPH) gene as a direct target of MYBL2. NCAPH expression is highly correlated with that of MYBL2 in LUAD cases and is tightly affected by MYBL2 knockdown or overexpression in vitro. Chromatin immunoprecipitation (ChIP) assays also showed that MYBL2 directly binds to the transcription start site (TSS) of NCAPH. Moreover, we provided evidence that NCAPH functions as an oncogene in lung cancer and overexpression of NCAPH could partially rescue cell death and migration blockage induced by MYBL2 knockdown. Together, these results suggest that overexpression of MYBL2 promotes proliferation and migration of lung cancer cells via upregulating NCAPH, establishing their roles as novel prognostic biomarkers as well as potential therapeutic targets for the disease.

Screening and identification of genes associated with cell proliferation in cholangiocarcinoma

Cholangiocarcinoma (CCA), an aggressive tumor with poor prognosis, is a malignant cancer with increasing incidence and mortality rates. It is important to survey crucial genes in CCA to find and design potential drug targets, especially for those genes associated with cell proliferation that is a key biological process in tumorgenesis. Herein, we surveyed genes associated with cell proliferation via a comprehensive pan-cancer analysis. Candidate genes were further analyzed using multiple approaches, including cross-analysis from diverse molecular levels, examination of potential function and interactions, and additional experimental validation. We primarily screened 15 potential genes based on 11 validated genes, and these 26 genes were further examined to delineate their biological functions and potential roles in cancer treatment. Several of them were involved synthetically lethal genetic interactions, especially for RECQL4, TOP2A, MKI67 and ASPM, indicating their potential roles in drug design and cancer treatment. Further experimental validation indicated that some genes were significantly upregulated in several cancer cell lines, implying their important roles in tumorigenesis. Our study identifies some genes associated with cell proliferation, which may be potential future targets in molecular targeted therapy.