Overexpression of the ASPM gene is associated with aggressiveness and poor outcome in bladder cancer

Elucidating the molecular role of MUC5B in progressive lung adenocarcinoma: Prospects for early diagnosis

Gel-forming mucin MUC5B is significantly deregulated in lung adenocarcinoma (LUAD), however, its role in tumor progression is not yet clearly understood. Here, we used an integrated computational-pipeline-initiated with gene expression analysis followed by network, functional-enrichment, O-linked glycosylation analyses, mutational profiling, and immune cell infiltration estimation to functionally characterize MUC5B gene in LUAD. Thereafter, clinical biomarker validation was supported by the overall survival (OA) and comparative expression profiling across clinical stages using computational algorithms. The gene expression profile of LUAD identified MUC5B to be significantly up-regulated (logFC: 2.36; p-value: 0.01). Network analysis on LUAD interactome screened MUC5B-related genes, having key enrichment in immune suppression and O-linked glycosylation with serine-threonine-rich tandem repeats being highly glycosylated. Furthermore, positive correlation of mutant MUC5B with immune cells in tumor microenvironment (TME) such as cancer-associated fibroblasts and myeloid-derived suppressor cells indicates TME-mediated tumor progression. The positive correlation with immune inhibitors suggested the enhanced tumor proliferation mediated by MUC5B. Structural stability due to genetic alterations identified overall rigid N-H-backbone dynamics (S2 : 0.756), indicating an overall stable mutant protein. Moreover, the low median OA (<50 months) with a hazard ratio of 1.4 and clinical profile of MUC5B gene showed high median expression corresponding to lymph node (N2) and tumor (T3) stages. Our study concludes by highlighting the functional role of O-glycosylated and mutant MUC5B in promoting LUAD by immune suppression. Further, clinical gene expression validation of MUC5B suggests its potential role as a diagnostic biomarker for LUAD metastasis.

Activation of assembly factor for spindle microtubules triggers progression of renal cell carcinoma via Wnt3a pathway

Renal cell carcinoma, shorted as RCC is a well-known urological cancer with high level of morbidity and mortality. Although the regulatory role of the spindle microtubule assembly factor (ASPM) in tumor progression has been established, its relationship to the development of RCC remains unclear. To determine the significance of this gene in RCC, we examined its expression in RCC patients in the TCGA database and compared ASPM level between clinical samples of normal tissues and RCC tissues collected at our center. The prognostic relevance of ASPM was assessed by generating Kaplan-Meier survival curves and log-rank functions. Following alteration of ASPM expression using sh-ASPM or oe-ASPM transfection, RCC cell characteristics were evaluated through CCK-8, Transwell, and colony formation assays. Western blot analysis was conducted to measure levels of genes affected by ASPM, and rescue experiments were performed to explore the involvement of Wnt3a signaling in ASPM-mediated malignancy in RCC. Our findings indicate that ASPM is upregulated in RCC samples, and its levels are associated with the long-term survival of RCC patients. ASPM promotes the migration, proliferation, and invasiveness of RCC cells, and the Wnt3a pathway may be implicated in this process. In conclusion, these results indicate that ASPM contributes to the cancer progression of RCC by targeting the Wnt3a signaling pathway.

Oncogenic ASPM Is a Regulatory Hub of Developmental and Stemness Signaling in Cancers

Despite recent advances in molecularly targeted therapies and immunotherapies, the effective treatment of advanced-stage cancers remains a largely unmet clinical need. Identifying driver mechanisms of cancer aggressiveness can lay the groundwork for the development of breakthrough therapeutic strategies. Assembly factor for spindle microtubules (ASPM) was initially identified as a centrosomal protein that regulates neurogenesis and brain size. Mounting evidence has demonstrated the pleiotropic roles of ASPM in mitosis, cell-cycle progression, and DNA double-strand breaks (DSB) repair. Recently, the exon 18-preserved isoform 1 of ASPM has emerged as a critical regulator of cancer stemness and aggressiveness in various malignant tumor types. Here, we describe the domain compositions of ASPM and its transcript variants and overview their expression patterns and prognostic significance in cancers. A summary is provided of recent progress in the molecular elucidation of ASPM as a regulatory hub of development- and stemness-associated signaling pathways, such as the Wnt, Hedgehog, and Notch pathways, and of DNA DSB repair in cancer cells. The review emphasizes the potential utility of ASPM as a cancer-agnostic and pathway-informed prognostic biomarker and therapeutic target.

Construction of a prediction model for prognosis of bladder cancer based on the expression of ion channel-related genes

OBJECTIVES

To construct a prediction model for the prognosis of bladder cancer patients based on the expression of ion channel-related genes (ICRGs).

METHODS

ICRGs were obtained from the existing researches. The clinical information and the expression of ICRGs mRNA in breast cancer patients were obtained from the Cancer Genome Atlas database. Cox regression analysis, minimum absolute shrinkage and selection operator regression analysis were used to screen breast cancer prognosis related genes, which were verified by immunohistochemistry and qRT-PCR. The risk scoring equation for predicting the prognosis of patients with bladder cancer was constructed, and the patients were divided into high-risk group and low-risk group according to the median risk score. Immune cell infiltration was compared between the two groups. Kaplan-Meier survival curve and receiver operating characteristic (ROC) curve were used to evaluate the accuracy and clinical application value of the risk scoring equation. The factors related to the prognosis of bladder cancer patients were analyzed by univariate and multivariate Cox regression, and a nomogram for predicting the prognosis of bladder cancer patients was constructed.

RESULTS

By comparing the expression levels of ICRGs in bladder cancer tissues and normal bladder tissues, 73 differentially expressed ICRGs were dentified, of which 11 were related to the prognosis of bladder cancer patients. Kaplan-Meier survival curve suggested that the risk score based on these 11 genes was negatively correlated with the prognosis of patients. The area under the ROC curve of the risk score for predicting the prognosis of patients at 1, 3 and 5 year was 0.634, 0.665 and 0.712, respectively. Stratified analysis showed that the ICRGs-based risk score performed well in predicting the prognosis of patients with American Joint Committee on Cancer (AJCC) stage Ⅲ-Ⅳ bladder cancer (P<0.05), while it had a poor value in predicting the prognosis of patients with AJCC stage Ⅰ-Ⅱ (P>0.05). There were significant differences in the infiltration of plasma cells, activated natural killer cells, resting mast cells and M2 macrophages between the high-risk group and the low-risk group. Cox regression analysis showed that risk score, smoking, age and AJCC stage were independently associated with the prognosis of patients with bladder cancer (P<0.05). The nomogram constructed by combining risk score and clinical parameters has high accuracy in predicting the 1, 3 and 5 year overall survival rate of bladder cancer patients.

CONCLUSIONS

The study shows the potential value of ICRGs in the prognostic risk assessment of bladder cancer patients. The constructed prognostic nomogram based on ICRGs risk score has high accuracy in predicting the prognosis of bladder cancer patients.

The neurological and non-neurological roles of the primary microcephaly-associated protein ASPM

Primary microcephaly (MCPH), is a neurological disorder characterized by small brain size that results in numerous developmental problems, including intellectual disability, motor and speech delays, and seizures. Hitherto, over 30 MCPH causing genes (MCPHs) have been identified. Among these MCPHs, MCPH5, which encodes abnormal spindle-like microcephaly-associated protein (ASPM), is the most frequently mutated gene. ASPM regulates mitotic events, cell proliferation, replication stress response, DNA repair, and tumorigenesis. Moreover, using a data mining approach, we have confirmed that high levels of expression of ASPM correlate with poor prognosis in several types of tumors. Here, we summarize the neurological and non-neurological functions of ASPM and provide insight into its implications for the diagnosis and treatment of MCPH and cancer.

Improvement of variables interpretability in kernel PCA

BACKGROUND

Kernel methods have been proven to be a powerful tool for the integration and analysis of high-throughput technologies generated data. Kernels offer a nonlinear version of any linear algorithm solely based on dot products. The kernelized version of principal component analysis is a valid nonlinear alternative to tackle the nonlinearity of biological sample spaces. This paper proposes a novel methodology to obtain a data-driven feature importance based on the kernel PCA representation of the data.

RESULTS

The proposed method, kernel PCA Interpretable Gradient (KPCA-IG), provides a data-driven feature importance that is computationally fast and based solely on linear algebra calculations. It has been compared with existing methods on three benchmark datasets. The accuracy obtained using KPCA-IG selected features is equal to or greater than the other methods' average. Also, the computational complexity required demonstrates the high efficiency of the method. An exhaustive literature search has been conducted on the selected genes from a publicly available Hepatocellular carcinoma dataset to validate the retained features from a biological point of view. The results once again remark on the appropriateness of the computed ranking.

CONCLUSIONS

The black-box nature of kernel PCA needs new methods to interpret the original features. Our proposed methodology KPCA-IG proved to be a valid alternative to select influential variables in high-dimensional high-throughput datasets, potentially unravelling new biological and medical biomarkers.

Identification of Potential Key Genes Linked to Gender Differences in Bladder Cancer Based on Gene Expression Omnibus (GEO) Database

Background

Growing evidence strongly indicates pivotal roles of gender differences in the occurrence and survival rate of patients with bladder cancer, with a higher incidence in males and poorer prognosis in females. Nevertheless, the molecular basis underlying gender-specific differences in bladder cancer remains unknown. The current study has tried to detect key genes contributing to gender differences in bladder cancer patients.

Materials and Methods

The gene expression profile of GSE13507 was firstly obtained from the Gene Expression Omnibus (GEO) database. Further, differentially expressed genes (DEGs) were screened between males and females using R software. Protein-protein interactive (PPI) network analysis, Kyoto Encyclopedia of Genes and Genomes (KEGG), Gene Ontology (GO), and Kaplan-Meier survival analyses were also performed.

Results

We detected six hub genes contributing to gender differences in bladder cancer patients, containing IGF2, CCL5, ASPM, CDC20, BUB1B, and CCNB1. Our analyses demonstrated that CCNB1 and BUB1B were upregulated in tumor tissues of female subjects with bladder cancer. Other genes, such as IGF2 and CCL5, were associated with a poor outcome in male patients with bladder cancer. Additionally, three signaling pathways (focal adhesion, rheumatoid arthritis, and human T-cell leukemia virus infection) were identified to be differentially downregulated in bladder cancer versus normal samples in both genders.

Conclusion

Our findings suggested that gender differences may modulate the expression of key genes that contributed to bladder cancer occurrence and prognosis.

Screening ANLN and ASPM as bladder urothelial carcinoma-related biomarkers based on weighted gene co-expression network analysis

Introduction: Bladder cancer (BLCA) is one of the most common malignancies in the urinary system with a poor prognosis and high treatment costs. Identifying potential prognostic biomarkers is significant for exploring new therapeutic and predictive targets of BLCA.

Methods: In this study, we screened differentially expressed genes using the GSE37815 dataset. We then performed a weighted gene co‐expression network analysis (WGCNA) to identify the genes correlated with the histologic grade and T stage of BLCA using the GSE32548 dataset. Subsequently, Kaplan Meier survival analysis and Cox regression were used to further identify prognosis‐related hub genes using the datasets GSE13507 and TCGA‐BLCA. Moreover, we detected the expression of the hub genes in 35 paired samples, including BLCA and paracancerous tissue, from the Shantou Central Hospital by qRT‐polymerase chain reaction.

Results: This study showed that Anillin (ANLN) and Abnormal spindle-like microcephaly-associated gene (ASPM) were prognostic biomarkers for BLCA. High expression of ANLN and ASPM was associated with poor overall survival.The qRT‐PCR results revealed that ANLN and ASPM genes were upregulated in BLCA, and there was a correlation between the expression of ANLN and ASPM in cancer tissues and paracancerous tissue. Additionally, the increasing multiples in the ANLN gene was obvious in high-grade BLCA.

Discussion: In summary, this preliminary exploration indicated a correlation between ANLN and ASPM expression. These two genes, serving as the risk factors for BLCA progression, might be promising targets to improve the occurrence and progression of BLCA.

ASPM promotes migration and invasion of anaplastic thyroid carcinoma by stabilizing KIF11

Abnormal spindle-like microcephaly-associated (ASPM) protein is crucial to the mitotic spindle function during cell replication and tumor progression in multiple tumor types. However, the effect of ASPM in anaplastic thyroid carcinoma (ATC) has not yet been understood. The present study is to elucidate the function of ASPM in the migration and invasion of ATC. ASPM expression is incrementally upregulated in ATC tissues and cell lines. Knockout (KO) of ASPM pronouncedly attenuates the migration and invasion of ATC cells. ASPM KO significantly reduces the transcript levels of Vimentin, N-cadherin, and Snail and increases E-cadherin and Occludin, thereby inhibiting epithelial-to-mesenchymal transition (EMT). Mechanistically, ASPM regulates the movement of ATC cells by inhibiting the ubiquitin degradation of KIF11 and thus stabilizing it via direct binding to it. Moreover, xenograft tumors in nude mice proved that KO of ASPM could ameliorate tumorigenesis and tumor growth accompanied by a decreased protein expression of KIF11 and an inhibition of EMT. In conclusion, ASPM is a potentially useful therapeutic target for ATC. Our results also reveal a novel mechanism by which ASPM inhibits the ubiquitin process in KIF11.

Differentially expressed discriminative genes and significant meta-hub genes based key genes identification for hepatocellular carcinoma using statistical machine learning

Hepatocellular carcinoma (HCC) is the most common lethal malignancy of the liver worldwide. Thus, it is important to dig the key genes for uncovering the molecular mechanisms and to improve diagnostic and therapeutic options for HCC. This study aimed to encompass a set of statistical and machine learning computational approaches for identifying the key candidate genes for HCC. Three microarray datasets were used in this work, which were downloaded from the Gene Expression Omnibus Database. At first, normalization and differentially expressed genes (DEGs) identification were performed using limma for each dataset. Then, support vector machine (SVM) was implemented to determine the differentially expressed discriminative genes (DEDGs) from DEGs of each dataset and select overlapping DEDGs genes among identified three sets of DEDGs. Enrichment analysis was performed on common DEDGs using DAVID. A protein-protein interaction (PPI) network was constructed using STRING and the central hub genes were identified depending on the degree, maximum neighborhood component (MNC), maximal clique centrality (MCC), centralities of closeness, and betweenness criteria using CytoHubba. Simultaneously, significant modules were selected using MCODE scores and identified their associated genes from the PPI networks. Moreover, metadata were created by listing all hub genes from previous studies and identified significant meta-hub genes whose occurrence frequency was greater than 3 among previous studies. Finally, six key candidate genes (TOP2A, CDC20, ASPM, PRC1, NUSAP1, and UBE2C) were determined by intersecting shared genes among central hub genes, hub module genes, and significant meta-hub genes. Two independent test datasets (GSE76427 and TCGA-LIHC) were utilized to validate these key candidate genes using the area under the curve. Moreover, the prognostic potential of these six key candidate genes was also evaluated on the TCGA-LIHC cohort using survival analysis.

Identification of Potential Biomarkers for Pan-Cancer Diagnosis and Prognosis Through the Integration of Large-Scale Transcriptomic Data

Cancer is one of the leading causes of death worldwide, bringing a significant burden to human health and society. Accurate cancer diagnosis and biomarkers that can be used as robust therapeutic targets are of great importance as they facilitate early and effective therapies. Shared etiology among cancers suggests the existence of pan-cancer biomarkers, performance of which could benefit from the large sample size and the heterogeneity of the studied patients. In this study, we conducted a systematic RNA-seq study of 9,213 tumors and 723 para-cancerous tissue samples of 28 solid tumors from the Cancer Genome Atlas (TCGA) database, and 7,008 normal tissue samples from the Genotype-Tissue Expression (GTEx) database. By differential gene expression analysis, we identified 214 up-regulated and 186 downregulated differentially expressed genes (DEGs) in more than 80% of the studied tumors, respectively, and obtained 20 highly linked up- and downregulated hub genes from them. These markers have rarely been reported in multiple tumors simultaneously. We further constructed pan-cancer diagnostic models to classify tumors and para-cancerous tissues using 10 up-regulated hub genes with an AUC of 0.894. Survival analysis revealed that these hub genes were significantly associated with the overall survival of cancer patients. In addition, drug sensitivity predictions for these hub genes in a variety of tumors obtained several broad-spectrum anti-cancer drugs targeting pan-cancer. Furthermore, we predicted immunotherapy sensitivity for cancers based on tumor mutational burden (TMB) and the expression of immune checkpoint genes (ICGs), providing a theoretical basis for the treatment of tumors. In summary, we identified a set of biomarkers that were differentially expressed in multiple types of cancers, and these biomarkers can be potentially used for diagnosis and used as therapeutic targets.

ASPM Is a Prognostic Biomarker and Correlates With Immune Infiltration in Kidney Renal Clear Cell Carcinoma and Liver Hepatocellular Carcinoma

Background

Abnormal spindle microtubule assembly (ASPM) is a centrosomal protein and that is related to a poor clinical prognosis and recurrence. However, the relationship between ASPM expression, tumor immunity, and the prognosis of different cancers remains unclear.

Methods

ASPM expression and its influence on tumor prognosis were analyzed using the Tumor Immune Estimation Resource (TIMER), UALCAN, OncoLnc, and Gene Expression Profiling Interactive Analysis (GEPIA) databases. The relationship between ASPM expression and tumor immunity was analyzed using the TIMER and GEPIA databases, and the results were further verified using qPCR, western blot, and multiplex quantitative immuno fluorescence.

Results

The results showed that ASPM expression was significantly higher in most cancer tissues than in corresponding normal tissues, including kidney renal clear cell carcinoma (KIRC), kidney renal papillary cell carcinoma (KIRP), liver hepatocellular carcinoma (LIHC), lung adenocarcinoma (LUAD), pancreatic adenocarcinoma (PAAD), and breast invasive carcinoma (BRCA). ASPM expression was significantly higher in late-stage cancers than in early-stages cancers (e.g., KIRC, KIRP, LIHC, LUAD, and BRCA; p < 0.05), demonstrating a possible role of ASPM in cancer progression and invasion. Moreover, our data showed that high ASPM expression was associated with poor overall survival, and disease-specific survival in KIRC and LIHC (p < 0.05). Besides, Cox hazard regression analysis results showed that ASPM may be an independent prognostic factor for KIRC and LIHC. ASPM expression showed a strong correlation with tumor-infiltrating B cells, CD8⁺ T cells, and M2 macrophages in KIRC and LIHC.

Conclusions

These findings demonstrate that the high expression of ASPM indicates poor prognosis as well as increased levels of immune cell infiltration in KIRC and LIHC. ASPM expression may serve as a novel prognostic biomarker for both the clinical outcome and immune cell infiltration in KIRC and LIHC.

Abnormal spindle-like microcephaly-associated protein promotes proliferation by regulating cell cycle in epithelial ovarian cancer

BACKGROUND

Epithelial ovarian cancer (EOC) ranks first for female gynecological tumor-related deaths. Due to the limited efficacy of traditional chemotherapy strategies, potential therapeutic targets are urgently needed. Previous studies have reported a relationship between abnormal spindle-like microcephaly-associated protein (ASPM) and ovarian cancer based on immunohistochemistry (IHC) and bioinformatics analysis. However, the potential role of ASPM in the proliferation of ovarian cancer cells and its molecular mechanism remain to be elucidated. Therefore, we aimed to further investigate the potential role of ASPM and its underlying mechanism in EOC using integrated online databases, clinical samples, and cell models.

METHODS

We used online databases (Gene Expression Profiling Interactive Analysis, Cbioportal and Kaplan-Meier Plotter) to analyze differential ASPM expression in ovarian carcinoma and explore its prognostic value in ovarian cancer (OvCa) patients. Immunohistochemistry staining based on a clinical tissue microarray (TMA) comprised 75 cases of EOC tissue and 5 cases of adjacent normal ovary tissue was used to detect the ASPM expression and analyze the relationship between ASPM expression and EOC characteristics. Various cell function experiments related to tumorigenesis were performed including the CCK8 assay, 5-ethynyl-2'-deoxyuridine (EdU), colony formation assay and Transwell assay in EOC cell models (A2780 and OVCAR3) with knocked down ASPM by small interfering RNA (siRNA) to observe its role. Finally, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment was conducted to determine the signaling pathways in which ASPM was involved in the pathogenesis of ovarian cancer. Analysis of cell cycle distribution using flow cytometry was further performed to verify the pathways.

RESULTS

The expression profile based on data from The Cancer Genome Atlas (TCGA) database confirmed ASPM expression in EOC was higher compared with normal tissue, and further analysis suggested that higher expression was correlated with worse patient prognosis. Immunohistochemical analysis further indicated that ASPM was highly expressed in OvCa tissues and associated with a higher pathological stage, grade, and positive lymphatic metastasis. Cell models with knocked down ASPM by small interfering RNA (siRNA) significantly inhibited proliferation and migration. KEGG pathway enrichment and cell cycle analysis showed that ASPM silencing could inhibit ovarian cancer cell proliferation via synthesis (S) phase arrest.

CONCLUSIONS

Our study confirmed that ASPM promoted proliferation and caused S phase arrest in EOC cells. ASPM may become a potential molecular marker for early screening and a valuable therapeutic target in EOC.

KEYWORDS

Abnormal spindle-like microcephaly-associated protein (ASPM); epithelial ovarian cancer (EOC); prognosis; proliferation.

Identification of hub genes and pathways in bladder cancer using bioinformatics analysis

Bladder cancer (BC) is the most common malignant tumor of urinary tract system. The aim of this study was to investigate the genetic signatures of bladder cancer (BC) and identify its potential molecular mechanisms. The gene expression profiles of GSE3167 (50 samples, including 41BC and 9 non-cancerous urothelial cells) was downloaded from the GEO database. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes pathway (KEGG) were performed to identify enriched pathways, and a protein-protein interaction (PPI) network was used to identify hub genes and for module analysis. Moreover, we conducted expression and survival analyses to screen and validate hub genes. In total, 1528 DEGs were identified in bladder cancer (BC), including 1212 up-regulated genes and 316 down-regulated genes. Up-regulated differentially expressed genes (DEGs) were significantly enriched in negative regulation of macromolecule metabolic process, macromolecule catabolic process, proteolysis and regulation of cell death, while the down-regulated differentially expressed genes (DEGs) were mainly involved in cell surface receptor linked signal transduction, ion transport, cell-cell signaling and defense response. The top 10 hub genes with the highest degrees were selected from the PPI network. These genes included HSP90AA1, MYH11, MYL9, CNN1, ACTC1, RAN, ENO1, HNRNPC, ACTG2 and YWHAZ. From sub-networks, we found these genes were involved in the proteasome, pathways in cancer and cell cycle. Hence, the identified DEGs and hub genes may be beneficial to elucidate the mechanisms underlying BC.

Overexpression of abnormal spindle-like microcephaly-associated (ASPM) increases tumor aggressiveness and predicts poor outcome in patients with lung adenocarcinoma

Background

Cumulative evidence points to abnormal spindle-like microcephaly-associated (ASPM) protein being overexpressed in various cancers, and the aberrant expression of ASPM has been shown to promote cancer tumorigenicity and progression. However, its role and clinical significance in lung adenocarcinoma (LUAD) remains unclear. This study aimed to determine the expression patterns of ASPM and its clinical significance in LUAD.

Methods

In total, 4 original worldwide LUAD microarray mRNA expression datasets (N=1,116) with clinical and follow-up annotations were downloaded from The Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO) databases. The expression of ASPM protein in LUAD patients was detected by immunohistochemistry. Survival analysis and Cox regression analysis were used to examine the prognostic value of ASPM expression. Gene set enrichment analysis (GSEA) was performed to investigate the relationship between ASPM and LUAD.

Results

Dataset analyses and immunohistochemistry revealed that ASPM expression was significantly higher in the LUAD tissues compared with normal lung tissues, especially in the advanced tumor stage. Additionally, overexpression of ASPM was significantly correlated with shorter overall survival (OS) and relapse-free survival (RFS) in LUAD. Univariate and multivariate Cox regression analyses revealed that the overexpression of ASPM was a potential independent predictor of poor OS and RFS. However, ASPM overexpression was not significantly associated with predicting OS in lung squamous cell carcinoma. GSEA analysis demonstrated that ASPM was significantly enriched in the cell cycle, DNA replication, homologous recombination, RNA degradation, mismatch repair, and p53 signaling pathways.

Conclusions

These findings demonstrate the important role of ASPM in the tumorigenesis and progression of LUAD.

Identification of key genes and carcinogenic pathways in hepatitis B virus-associated hepatocellular carcinoma through bioinformatics analysis

Backgrounds/Aims

Mechanisms for the development of hepatocellular carcinoma (HCC) in hepatitis B virus (HBV)-infected patients remain unclear. The aim of the present study was to identify genes and pathways involved in the development of HBV-associated HCC.

Methods

The GSE121248 gene dataset, which included 70 HCCs and 37 adjacent liver tissues, was downloaded from the Gene Expression Omnibus database. Differentially expressed genes (DEGs) in HCCs and adjacent liver tissues were identified. Gene ontology and Kyoto Encyclopedia of Genes and Genome pathway enrichment analyses were then performed.

Results

Of 134 DEGs identified, 34 were up-regulated and 100 were down-regulated in HCCs. The 34 up-regulated DEGs were mainly involved in nuclear division, organelle fission, spindle and midbody formation, histone kinase activity, and p53 signaling pathway, whereas the 100 down-regulated DEGs were involved in steroid and hormone metabolism, collagen-coated extracellular matrix, oxidoreductase activity, and activity on paired donors, including incorporation or reduction of molecular oxygen, monooxygenase activity, and retinol metabolism. Analyses of protein-protein interaction networks with a high degree of connectivity identified significant modules containing 14 hub genes, including ANLN, ASPM, BUB1B, CCNB1, CDK1, CDKN3, ECT2, HMMR, NEK2, PBK, PRC1, RACGAP1, RRM2, and TOP2A, which were mainly associated with nuclear division, organelle fission, spindle formation, protein serine/threonine kinase activity, p53 signaling pathway, and cell cycle.

Conclusions

This study identified key genes and carcinogenic pathways that play essential roles in the development of HBV-associated HCC. This may provide important information for the development of diagnostic and therapeutic targets for HCC.

Changes in Protein Structural Motifs upon Post-Translational Modification in Kidney Cancer

Post-translational modification (PTM) leads to conformational changes in protein structure, modulates the biological function of proteins, and, consequently, changes the signature of metabolic transformations and the immune response in the body. Common PTMs are reversible and serve as a mechanism for modulating metabolic trans-formations in cells. It is likely that dysregulation of post-translational cellular signaling leads to abnormal proliferation and oncogenesis. We examined protein PTMs in the blood samples from patients with kidney cancer. Conformational changes in proteins after modification were analyzed. The proteins were analyzed using ultra-high resolution HPLC-MS/MS and structural analysis was performed with the AMBER and GROMACS software packages. Fifteen proteins containing PTMs were identified in blood samples from patients with kidney cancer. For proteins with PDB structures, a comparative analysis of the structural changes accompanying the modifications was performed. Results revealed that PTMs are localized in stable and compact space protein globule motifs that are exposed to a solvent. The phenomenon of modification is accompanied, as a rule, by an increase in the area available for the solvent of the modified amino acid residue and its active environment.

ASPM combined with KIF11 promotes the malignant progression of hepatocellular carcinoma via the Wnt/β-catenin signaling pathway

To investigate the molecular mechanism of assembly factor for spindle microtubules (ASPM) in the regulation of the malignant progression of hepatocellular carcinoma (HCC), bioinformatics analysis was utilized to analyze the role of ASPM in the malignant progression of HCC and its potential interaction with the kinesin family member 11 (KIF11) gene. The expression levels of ASPM and KIF11 were detected by reverse transcription-quantitative PCR and western blotting. Following knockdown of ASPM expression, Cell Counting Kit-8/colony formation assays were performed to detect cell viability and proliferation. Wound healing and Transwell assays were employed to detect cell migration and invasion. Additionally, a co-immunoprecipitation (CO-IP) assay was used to detect whether there was an interaction between ASPM and KIF11. KIF11 overexpression was performed to verify if ASPM exerted its effects via KIF11. ASPM was highly expressed in HCC tissues and cells, and was closely associated with a poor prognosis of patients with HCC. Interference with ASPM expression markedly inhibited the viability, proliferation, invasion and migration of HCC cells. Using a CO-IP assay, it was revealed that there was an interaction between ASPM and KIF11. Rescue experiments subsequently revealed the regulatory effects of ASPM on the activity, proliferation, invasion and migration of HCC cells via KIF11. Finally, western blot analysis demonstrated that ASPM in combination with KIF11 promoted the malignant progression of HCC by regulating the activity of the Wnt/β-catenin signaling pathway. Therefore, the present study demonstrated that ASPM may interact with KIF11 in HCC cells to promote the malignant progression of HCC via the Wnt/β-catenin signaling pathway.

Construction of a novel mRNA-signature prediction model for prognosis of bladder cancer based on a statistical analysis

Background

Bladder cancer (BC) is a common malignancy neoplasm diagnosed in advanced stages in most cases. It is crucial to screen ideal biomarkers and construct a more accurate prognostic model than conventional clinical parameters. The aim of this research was to develop and validate an mRNA-based signature for predicting the prognosis of patients with bladder cancer.

Methods

The RNA-seq data was downloaded from the Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO). Differentially expressed genes (DEGs) were screened in three datasets, and prognostic genes were identified from the training set of TCGA dataset. The common genes between DEGs and prognostic genes were narrowed down to six genes via Least Absolute Shrinkage and Selection Operator (LASSO) regression, and stepwise multivariate Cox regression. Then the gene-based risk score was calculated via Cox coefficient. Time-dependent receiver operating characteristic (ROC) and Kaplan-Meier (KM) survival analysis were used to assess the prognostic power of risk score. Multivariate Cox regression analysis was applied to construct a nomogram. Decision curve analysis (DCA), calibration curves, and time-dependent ROC were performed to assess the nomogram. Finally, functional enrichment of candidate genes was conducted to explore the potential biological pathways of candidate genes.

Results

SORBS2, GPC2, SETBP1, FGF11, APOL1, and H1–2 were screened to be correlated with the prognosis of BC patients. A nomogram was constructed based on the risk score, pathological stage, and age. Then, the calibration plots for the 1-, 3-, 5-year OS were predicted well in entire TCGA-BLCA patients. Decision curve analysis (DCA) indicated that the clinical value of the nomogram was higher than the stage model and TNM model in predicting overall survival analysis. The time-dependent ROC curves indicated that the nomogram had higher predictive accuracy than the stage model and risk score model. The AUC of nomogram time-dependent ROC was 0.763, 0.805, and 0.806 for 1-year, 3-year, and 5-year, respectively. Functional enrichment analysis of candidate genes suggested several pathways and mechanisms related to cancer.

Conclusions

In this research, we developed an mRNA-based signature that incorporated clinical prognostic parameters to predict BC patient prognosis well, which may provide a novel prognosis assessment tool for clinical practice and explore several potential novel biomarkers related to the prognosis of patients with BC.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12885-021-08611-z.

ASPM promotes homologous recombination-mediated DNA repair by safeguarding BRCA1 stability

DNA double-strand break (DSB) repair by homologous recombination (HR) is essential for ensuring genome stability. Abnormal spindle-like microcephaly-associated (ASPM) gene encodes a spindle protein that is commonly implicated in primary microcephaly. We found that ASPM is recruited to sites of DNA damage in a PARP2-dependent manner. ASPM interacts with BRCA1 and its E3 ligase HERC2, preventing HERC2 from accessing to BRCA1 and ensuring BRCA1 stability. Inhibition of ASPM expression promotes HERC2-mediated BRCA1 degradation, compromises HR repair efficiency and chromosome stability, and sensitizes cancer cells to ionizing radiation. Moreover, we observed a synergistic effect between ASPM and PARP inhibition in killing cancer cells. This research has uncovered a novel function for ASPM in facilitating HR-mediated repair of DSBs by ensuring BRCA1 stability. ASPM might constitute a promising target for synthetic lethality-based cancer therapy.

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ASPM is recruited to sites of DNA damage in a PARP2-dependent manner.

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ASPM promotes DSB-end resection to facilitate HR repair.

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ASPM prevents HERC2 from accessing to BRCA1 and ensuring BRCA1 stability.

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Inhibition of ASPM sensitizes cancer cells to ionizing radiation and PARP inhibitor.

A multi-mode Wnt- and stemness-regulatory module dictated by FOXM1 and ASPM isoform I in gastric cancer

BACKGROUND

Gastric cancer (GC) is the third leading cause of cancer mortality globally and a molecularly heterogeneous disease. Identifying the driver pathways in GC progression is crucial to improving the clinical outcome. Recent studies identified ASPM (abnormal spindle-like microcephaly-associated) and FOXM1 (Forkhead box protein M1) as novel Wnt and cancer stem cell (CSC) regulators; their pathogenetic roles and potential crosstalks in GC remain unclarified.

METHODS

The expression patterns of ASPM isoforms and FOXM1 were profiled in normal gastric epithelial and GC tissues. The functional roles of ASPM and FOXM1 in Wnt activity, cancer stemness and GC progression, and the underlying signaling processes were investigated.

RESULTS

Approximately one third of GC cells upregulate the expression of ASPM isoform I (ASPMiI) in their cytoplasm; the tumors with a high ASPMiI positive score (≥ 10%) are associated with a poor prognosis of the patients. Mechanistically, the molecular interplay among FOXM1, ASPMiI and DVL3 was found to converge on β-catenin to control the Wnt activity and the stemness property of GC cells. This multi-mode Wnt-regulatory module serves to reinforce Wnt signals in CSCs by transcriptional regulation (FOXM1-ASPM), protein-protein interactions (ASPMiI-DVL3-β-catenin), and nuclear translocation (FOXM1-β-catenin).

CONCLUSIONS

This study illuminates a novel Wnt- and stemness-regulatory mechanism in GC cells and identifies a novel subset of FOXM1^highASPMiI^high GC with potential to guide Wnt- and stemness-related diagnostics and therapies.

Oncogenic role of abnormal spindle‑like microcephaly‑associated protein in lung adenocarcinoma

Lung adenocarcinoma (LUAD) is a common malignant cancer worldwide. It is urgent to explore its underlying molecular mechanism and identify novel diagnostic biomarkers. Abnormal spindle-like microcephaly (ASPM) has recently received considerable attention due to its function in tumor progression. However, its role in LUAD is unclear. The present study aimed to explore the clinical role of ASPM in LUAD. Seven pairs of LUAD and adjacent normal tissues were collected to identify potential LUAD biomarkers using transcriptome sequencing. The association between ASPM expression and LUAD progression was evaluated using bioinformatics analysis and data obtained from clinical specimens. Using small interfering RNA technology, the function of ASPM was analyzed in the LUAD H1299 and A549 cell lines. Transcriptional profiling of ASPM-deficient H1299 cells was then performed to determine the downstream targets of ASPM. Using databases and clinical specimens, it was revealed that ASPM expression was frequently elevated in LUAD tissues, and this upregulation was highly associated with LUAD progression. ASPM served as an oncogenic regulator of LUAD cell proliferation and metastasis. Mechanistically, ASPM facilitated epithelial-mesenchymal transition (EMT) via the PI3K/AKT signaling pathway and 740 Y-P, an activator of this pathway, restored the migratory ability of ASPM-knockdown LUAD cells. The current study identified ASPM as an independent prognostic biomarker of LUAD that served an important oncogenic role in regulating LUAD cell metastasis by promoting EMT via the PI3K/AKT signaling pathway. Targeting ASPM may therefore be a therapeutic strategy for treating LUAD.

Abnormal spindle-like microcephaly-associated (ASPM) gene expression in posterior fossa brain tumors of childhood and adolescence

PURPOSE

In neurogenesis, ASPM (abnormal spindle-like microcephaly-associated) gene is expressed mainly in the ventricular zone of posterior fossa and is the major determinant in the cerebral cortex. Besides its role in embryonic development, ASPM overexpression promotes tumor growth, including central nervous system (CNS) tumors. This study aims to investigate ASPM expression levels in most frequent posterior fossa brain tumors of childhood and adolescence: medulloblastoma (MB), ependymoma (EPN), and astrocytoma (AS), correlating them with clinicopathological characteristics and tumor solid portion size.

METHODS

Quantitative reverse transcription (qRT-PCR) is used to quantify ASPM mRNA levels in 80 pre-treatment tumor samples: 28 MB, 22 EPN, and 30 AS. The tumor solid portion size was determined by IOP-GRAACC Diagnostic Imaging Center. We correlated these findings with clinicopathological characteristics and tumor solid portion size.

RESULTS

Our results demonstrated that ASPM gene was overexpressed in MB (p = 0.007) and EPN (p = 0.0260) samples. ASPM high expression was significantly associated to MB samples from patients with worse overall survival (p = 0.0123) and death due to disease progression (p = 0.0039). Interestingly, two patients with AS progressed toward higher grade showed ASPM overexpression (p = 0.0046). No correlation was found between the tumor solid portion size and ASPM expression levels in MB (p = 0.1154 and r = - 0.4825) and EPN (p = 0.1108 and r = - 0.3495) samples.

CONCLUSION

Taking in account that ASPM gene has several functions to support cell proliferation, as mitotic defects and premature differentiation, we suggest that its overexpression, presumably, plays a critical role in disease progression of posterior fossa brain tumors of childhood and adolescence.

Identification of core genes in the progression of endometrial cancer and cancer cell-derived exosomes by an integrative analysis

Endometrial cancer is one of the most prevalent tumors of the female reproductive system causing serious health effects to women worldwide. Although numerous studies, including analysis of gene expression profile and cellular microenvironment have been reported in this field, pathogenesis of this disease remains unclear. In this study, we performed a system bioinformatics analysis of endometrial cancer using the Gene Expression Omnibus (GEO) datasets (GSE17025, GSE63678, and GSE115810) to identify the core genes. In addition, exosomes derived from endometrial cancer cells were also isolated and identified. First, we analyzed the differentially expressed genes (DEGs) between endometrial cancer tissues and normal tissues in clinic samples. We found that HAND2-AS1, PEG3, OGN, SFRP4, and OSR2 were co-expressed across all 3 datasets. Pathways analysis showed that several pathways associated with endometrial cancer, including "p53 signaling pathway", "Glutathione metabolism", "Cell cycle", and etc. Next, we selected DEGs with highly significant fold change and co-expressed across the 3 datasets and validated them in the TCGA database using Gene Expression Profiling Interactive Analysis (GEPIA). Finally, we performed a survival analysis and identified four genes (TOP2A, ASPM, EFEMP1, and FOXL2) that play key roles in endometrial cancer. We found up-regulation of TOP2A and ASPM in endometrial cancer tissues or cells, while EFEMP1 and FOXL2 were down-regulated. Furthermore, we isolated exosomes from the culturing supernatants of endometrial cancer cells (Ishikawa and HEC-1-A) and found that miR-133a, which regulates expression of FOXL2, were present in exosomes and that they could be delivered to normal endometrial cells. The common DEGs, pathways, and exosomal miRNAs identified in this study might play an important role in progression as well as diagnosis of endometrial cancer. In conclusion, our results provide insights into the pathogenesis and risk assessment of endometrial cancer. Even so, further studies are required to elucidate on the precise mechanism of action of these genes in endometrial cancer.

[Expression of ASPM in Lung Adenocarcinoma and Its Relationship with Development and Prognosis]

BACKGROUND

Previous studies have shown that ASPM is a tumorigenesis associated protein, mutations in ASPM can lead to MCPH. This study mainly explores the relationship between the ASPM expression of lung adenocarcinoma and the development and prognosis of lung cancer. The aim of this study was to investigate the relationship between the expression of abnormal spindle-like microcephaly-associated protein (ASPM) in lung adenocarcinoma and the development and prognosis in lung cancer.

METHODS

A total of 90 cases of lung adenocarcinoma tissue specimens and 90 cases of benign pulmonary lesions were collected, the expression of ASPM was detected by immunohistochemical technique, and the expression of ASPM in 12 pairs of tissues was detected by real-time quantity polymerase chain reaction and western blot.

RESULTS

(1) The expression of ASPM in the tissue specimens of benign pulmonary lesions was negative while the expression level of ASPM in lung adenocarcinoma was significantly higher than lung tissue of benign pulmonary lesions (P<0.05). (2) The expression level of ASPM has no remarkable difference in lung adenocarcinoma with lymph node development and the lung cancer without lymph node development, there was no statistically significant (P<0.05). (3) The ASPM expression level in the tumor's size ≥4 cm was significantly higher than than of the size<4 cm (P<0.05). (4) Hierarchical analysis results show that T stage is related to ASPM expression level (P<0.05). (5) The high expression level of ASPM in lung adenocarcinoma was significantly positively correlated with the poor prognosis (P<0.05).

CONCLUSIONS

(1) The expression level of ASPM in lung cancer is obviously increased and closely related to the progress of lung adenocarcinoma. (2) The expression level of ASPM in lung adenocarcinoma was significantly positively correlated with poor prognosis (P<0.05). (3) Detection of the expression level of ASPM in lung adenocarcinoma help to predict the prognosis of lung adenocarcinoma in advance.

Evaluation of ASPM and TEF Gene Expressions as Potential Biomarkers for Bladder Cancer

Bladder cancer is one of the most predominant tumors of the genitourinary tract. In addition to pathological findings, the molecular modifications that might affect tumorigenesis and tumor outcome should be considered when treating bladder cancer. Accordingly, we aimed to investigate the expression levels of both the ASPM and TEF genes in bladder cancer tissues and their value in disease prognosis. The expression levels of the ASPM and TEF genes were analyzed by quantitative real-time PCR (qRT-PCR) in 90 bladder cancer tissue specimens and 90 specimens of normal urinary bladder tissue taken away from the tumor site. The upregulation of ASPM expression and the downregulation of TEF expression were observed in bladder cancer tissues compared to adjacent normal tissues, and these levels were correlated with high-grade tumors, advanced stage disease and the presence of metastasis. Both genes had the ability to predict metastatic association with sensitivity (84.62%) and specificity (68.42%; *P < 0.001) for the ASPM gene and for the TEF gene with sensitivity (80.77%) and specificity (78.95%; *P < 0.001). Additionally, Kaplan-Meier survival analysis indicated that elevated ASPM expression levels and reduced TEF expression levels significantly correlated with decreased overall survival and progression-free survival. The current analysis concludes that ASPM and TEF expressions might be used as potential biomarkers in bladder cancer patients.

The Yin and Yang of Autosomal Recessive Primary Microcephaly Genes: Insights from Neurogenesis and Carcinogenesis

The stem cells of neurogenesis and carcinogenesis share many properties, including proliferative rate, an extensive replicative potential, the potential to generate different cell types of a given tissue, and an ability to independently migrate to a damaged area. This is also evidenced by the common molecular principles regulating key processes associated with cell division and apoptosis. Autosomal recessive primary microcephaly (MCPH) is a neurogenic mitotic disorder that is characterized by decreased brain size and mental retardation. Until now, a total of 25 genes have been identified that are known to be associated with MCPH. The inactivation (yin) of most MCPH genes leads to neurogenesis defects, while the upregulation (yang) of some MCPH genes is associated with different kinds of carcinogenesis. Here, we try to summarize the roles of MCPH genes in these two diseases and explore the underlying mechanisms, which will help us to explore new, attractive approaches to targeting tumor cells that are resistant to the current therapies.

Comprehensive Analysis of Differential Gene Expression to Identify Common Gene Signatures in Multiple Cancers

Background

With the development of research on cancer genomics and microenvironment, a new era of oncology focusing on the complicated gene regulation of pan-cancer research and cancer immunotherapy is emerging. This study aimed to identify the common gene expression characteristics of multiple cancers – lung cancer, liver cancer, kidney cancer, cervical cancer, and breast cancer – and the potential therapeutic targets in public databases.

Material/Methods

Gene expression analysis of GSE42568, GSE19188, GSE121248, GSE63514, and GSE66272 in the GEO database of multitype cancers revealed differentially expressed genes (DEGs). Then, GO analysis, KEGG function, and path enrichment analyses were performed. Hub-genes were identified by using the degree of association of protein interaction networks. Moreover, the expression of hub-genes in cancers was verified, and hub-gene-related survival analysis was conducted. Finally, infiltration levels of tumor immune cells with related genes were explored.

Results

We found 12 cross DEGs in the 5 databases (screening conditions: “adj p<0.05” and “logFC>2 or logFC<–2”). The biological processes of DEGs were mainly concentrated in cell division, regulation of chromosome segregation, nuclear division, cell cycle checkpoint, and mitotic nuclear division. Furthermore, 10 hub-genes were obtained using Cytoscape: TOP2A, ECT2, RRM2, ANLN, NEK2, ASPM, BUB1B, CDK1, DTL, and PRC1. The high expression levels of the 10 genes were associated with the poor survival of these multiple cancers, as well as ASPM, may be associated with immune cell infiltration.

Conclusions

Analysis of the common DEGs of multiple cancers showed that 10 hub-genes, especially ASPM and CDK1, can become potential therapeutic targets. This study can serve as a reference to understand the characteristics of different cancers, design basket clinical trials, and create personalized treatments.

Screening and Identification of Key Biomarkers for Bladder Cancer: A Study Based on TCGA and GEO Data

Bladder cancer (BLCA) is a common malignant cancer, and it is the most common genitourinary cancer in the world. The recurrence rate is the highest of all cancers, and the treatment of BLCA has only slightly improved over the past 30 years. Genetic and environmental factors play an important role in the development and progression of BLCA. However, the mechanism of cancer development remains to be proven. Therefore, the identification of potential oncogenes is urgent for developing new therapeutic directions and designing novel biomarkers for the diagnosis and prognosis of BLCA. Based on this need, we screened overlapping differentially expressed genes (DEG) from the GSE7476, GSE13507, and TCGA BLCA datasets. To identify the central genes from these DEGs, we performed a protein-protein interaction network analysis. To investigate the role of DEGs and the underlying mechanisms in BLCA, we performed Gene Ontology (GO) and Kyoto Gene and Genomic Encyclopedia (KEGG) analysis; we identified the hub genes via different evaluation methods in cytoHubba and then selected the target genes by performing survival analysis. Finally, the relationship between these target genes and tumour immunity was analysed to explore the roles of these genes. In summary, our current studies indicate that both cell division cycle 20 (CDC20) and abnormal spindle microtubule assembly (ASPM) genes are potential prognostic biomarkers for BLCA. It may also be a potential immunotherapeutic target with future clinical significance.

Comprehensive analysis of DNA methylation and gene expression profiles in cholangiocarcinoma

BACKGROUND

The incidence of cholangiocarcinoma (CCA) has risen in recent years, and it has become a significant health burden worldwide. However, the mechanisms underlying tumorigenesis and progression of this disease remain largely unknown. An increasing number of studies have demonstrated crucial biological functions of epigenetic modifications, especially DNA methylation, in CCA. The present study aimed to identify and analyze methylation-regulated differentially expressed genes (MeDEGs) involved in CCA tumorigenesis and progression by bioinformatics analysis.

METHODS

The gene expression profiling dataset (GSE119336) and gene methylation profiling dataset (GSE38860) were obtained from the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) and differentially methylated genes (DMGs) were identified using the limma packages of R and GEO2R, respectively. The MeDEGs were obtained by overlapping the DEGs and DMGs. Functional enrichment analyses of these genes were then carried out. Protein-protein interaction (PPI) networks were constructed using STRING and visualized in Cytoscape to determine hub genes. Finally, the results were verified based on The Cancer Genome Atlas (TCGA) database.

RESULTS

We identified 98 hypermethylated, downregulated genes and 93 hypomethylated, upregulated genes after overlapping the DEGs and DMGs. These genes were mainly enriched in the biological processes of the cell cycle, nuclear division, xenobiotic metabolism, drug catabolism, and negative regulation of proteolysis. The top nine hub genes of the PPI network were F2, AHSG, RRM2, AURKB, CCNA2, TOP2A, BIRC5, PLK1, and ASPM. Moreover, the expression and methylation status of the hub genes were significantly altered in TCGA.

CONCLUSIONS

Our study identified novel methylation-regulated differentially expressed genes (MeDEGs) and explored their related pathways and functions in CCA, which may provide novel insights into a further understanding of methylation-mediated regulatory mechanisms in CCA.

Bioinformatics Analysis Identified Key Molecular Changes in Bladder Cancer Development and Recurrence

Background and Objectives: Bladder cancer (BC) is a complex tumor associated with high recurrence and mortality. To discover key molecular changes in BC, we analyzed next-generation sequencing data of BC and surrounding tissue samples from clinical specimens. Methods. Gene expression profiling datasets of bladder cancer were analyzed online. The Database for Annotation, Visualization, and Integrated Discovery (DAVID, https://david.ncifcrf.gov/) was used to perform Gene Ontology (GO) functional and KEGG pathway enrichment analyses. Molecular Complex Detection (MCODE) in Cytoscape software (Cytoscape_v3.6.1) was applied to identify hub genes. Protein expression and survival data were downloaded from OncoLnc (http://www.oncolnc.org/). Gene expression data were obtained from the ONCOMINE website (https://www.oncomine.org/). Results. We identified 4211 differentially expressed genes (DEGs) by analysis of surrounding tissue vs. cancer tissue (SC analysis) and 410 DEGs by analysis of cancer tissue vs. recurrent tissue cluster (CR analysis). GO function analysis revealed enrichment of DEGs in genes related to the cytoplasm and nucleoplasm for both clusters, and KEGG pathway analysis showed enrichment of DEGs in the PI3K-Akt signaling pathway. We defined the 20 genes with the highest degree of connectivity as the hub genes. Cox regression revealed CCNB1, ESPL1, CENPM, BLM, and ASPM were related to overall survival. The expression levels of CCNB1, ESPL1, CENPM, BLM, and ASPM were 4.795-, 5.028-, 8.691-, 2.083-, and 3.725-fold higher in BC than the levels in normal tissues, respectively. Conclusions. The results suggested that the functions of CCNB1, ESPL1, CENPM, BLM, and ASPM may contribute to BC development and the functions of CCNB1, ESPL1, CENPM, and BLM may also contribute to BC recurrence.

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

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.

Methods: A meta-analysis of gene expression data of NSCLC was integrated with protein-protein interaction (PPI) data to construct an NSCLC network. MCODE and iRegulone were used to identify the local clusters and its upstream transcription regulators involve in NSCLC. Pair-wise gene expression correlation was performed using GEPIA. The survival analysis was performed by the Kaplan-Meier plot.

Results: This study identified a local “driver-network” with highest MCODE score having 26 up-regulated genes involved in the process of cell proliferation in NSCLC. Interestingly, the “driver-network” is under the regulation of TFs FOXM1 and MYBL2 as well as miRNAs. Furthermore, the overexpression of member genes in “driver-network” and the TFs are associated with poor overall survival (OS) in NSCLC patients.

Conclusion: This study identified a local “driver-network” and its upstream regulators responsible for the cell proliferation in NSCLC, which could be promising biomarkers and therapeutic targets for NSCLC treatment.