Abnormal spindle-like microcephaly-associated protein (ASPM) contributes to the progression of Lung Squamous Cell Carcinoma (LSCC) by regulating CDK4

Pan-cancer prognostic model and immune microenvironment analysis of natural killer cell-related genes

Background

Natural killer (NK) cells play a significant role in antitumor immunity and are closely related to tumor prognosis and recurrence. NK cell-based tumor immunotherapy, including immune checkpoint inhibition and CAR-engineered NK cells, is a promising area of research. However, there is a need for better NK cell-related models and associated biomarkers.

Methods

The sequences of NK cell-related genes were obtained from the published NK cell CRISPR/Cas9 library data, and the common genes were selected as NK cell-related genes. The RNA sequencing (RNA-seq) and clinical data of 32 solid tumors from The Cancer Genome Atlas (TCGA) were downloaded from the UCSC Xena database, and the RNA-seq data of normal samples were downloaded from the Genotype-Tissue Expression (GTEx) database. The differentially expressed NK cell-related genes (DENKGs) between the tumor and normal samples were analyzed. The DENKGs related to the prognosis of solid tumors were selected via univariate Cox analysis, and 32 kinds of solid tumor prognostic models were constructed using least absolute shrinkage and selection operator (LASSO) and multivariate Cox analysis. Survival, receiver operating characteristic (ROC), and independent prognostic analyses were employed to test the effectiveness of the model, along with a nomogram model and prediction curve. Differences in the immune pathways and microenvironment cells were analyzed between the high- and low-risk groups identified by the model.

Results

We constructed a pan-cancer prognostic model with 63 NK cell-related genes and further identified DEPDC1 and ASPM as potentially offering new directions in tumor research by literature screening.

Conclusions

In this study, 63 prognostic solid tumor markers were investigated using NK cell-related genes, and for the first time, a pan-cancer prognostic model was constructed to analyze their role in the immune microenvironment, which may contribute new insights into tumor research.

Identification of potential regulatory mechanisms and therapeutic targets for lung cancer

Lung cancer poses a significant health threat globally, especially in regions like India, with 5-year survival rates remain alarmingly low. Our study aimed to uncover key markers for effective treatment and early detection. We identified specific genes related to lung cancer using the BioXpress database and delved into their roles through DAVID enrichment analysis. By employing network theory, we explored the intricate interactions within lung cancer networks, identifying ASPM and MKI67 as crucial regulator genes. Predictions of microRNA and transcription factor interactions provided additional insights. Examining gene expression patterns using GEPIA and KM Plotter revealed the clinical relevance of these key genes. In our pursuit of targeted therapies, Drug Bank pointed to methotrexate as a potential drug for the identified key regulator genes. Confirming this, molecular docking studies through Swiss Dock showed promising binding interactions. To ensure stability, we conducted molecular dynamics simulations using the AMBER 16 suite. In summary, our study pinpoints ASPM and MKI67 as vital regulators in lung cancer networks. The identification of hub genes and functional pathways enhances our understanding of molecular processes, offering potential therapeutic targets. Importantly, methotrexate emerged as a promising drug candidate, supported by robust docking and simulation studies. These findings lay a solid foundation for further experimental validations and hold promise for advancing personalized therapeutic strategies in lung cancer.Communicated by Ramaswamy H. Sarma.

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.

Analysis of the potential relationship between COVID-19 and Behcet's disease using transcriptome data

To investigate the potential role of COVID-19 in relation to Behcet's disease (BD) and to search for relevant biomarkers. We used a bioinformatics approach to download transcriptomic data from peripheral blood mononuclear cells (PBMCs) of COVID-19 patients and PBMCs of BD patients, screened the common differential genes between COVID-19 and BD, performed gene ontology (GO) and pathway analysis, and constructed the protein-protein interaction (PPI) network, screened the hub genes and performed co-expression analysis. In addition, we constructed the genes-transcription factors (TFs)-miRNAs network, the genes-diseases network and the genes-drugs network to gain insight into the interactions between the 2 diseases. We used the RNA-seq dataset from the GEO database (GSE152418, GSE198533). We used cross-analysis to obtain 461 up-regulated common differential genes and 509 down-regulated common differential genes, mapped the PPI network, and used Cytohubba to identify the 15 most strongly associated genes as hub genes (ACTB, BRCA1, RHOA, CCNB1, ASPM, CCNA2, TOP2A, PCNA, AURKA, KIF20A, MAD2L1, MCM4, BUB1, RFC4, and CENPE). We screened for statistically significant hub genes and found that ACTB was in low expression of both BD and COVID-19, and ASPM, CCNA2, CCNB1, and CENPE were in low expression of BD and high expression of COVID-19. GO analysis and pathway analysis was then performed to obtain common pathways and biological response processes, which suggested a common association between BD and COVID-19. The genes-TFs-miRNAs network, genes-diseases network and genes-drugs network also play important roles in the interaction between the 2 diseases. Interaction between COVID-19 and BD exists. ACTB, ASPM, CCNA2, CCNB1, and CENPE as potential biomarkers for 2 diseases.

Development and validation of an epithelial–mesenchymal transition-related gene signature for predicting prognosis

BACKGROUND

Currently, there are many therapeutic methods for lung adenocarcinoma (LUAD), but the 5-year survival rate is still only 15% at later stages. Epithelial– mesenchymal transition (EMT) has been shown to be closely associated with local dissemination and subsequent metastasis of solid tumors. However, the role of EMT in the occurrence and development of LUAD remains unclear.

AIM

To further elucidate the value of EMT-related genes in LUAD prognosis.

METHODS

Univariate, least absolute shrinkage and selection operator, and multivariate Cox regression analyses were applied to establish and validate a new EMT-related gene signature for predicting LUAD prognosis. The risk model was evaluated by Kaplan–Meier survival analysis, principal component analysis, and functional enrichment analysis and was used for nomogram construction. The potential structures of drugs to which LUAD is sensitive were discussed with respect to EMT-related genes in this model.

RESULTS

Thirty-three differentially expressed genes related to EMT were found to be highly associated with overall survival (OS) by using univariate Cox regression analysis (log2FC ≥ 1, false discovery rate < 0.001). A prognostic signature of 7 EMT-associated genes was developed to divide patients into two risk groups by high or low risk scores. Kaplan–Meier survival analysis showed that the OS of patients in the high-risk group was significantly poorer than that of patients in the low-risk group (P < 0.05). Multivariate Cox regression analysis showed that the risk score was an independent risk factor for OS (HR > 1, P < 0.05). The results of receiver operator characteristic curve analysis suggested that the 7-gene signature had a perfect ability to predict prognosis (all area under the curves > 0.5).

CONCLUSION

The EMT-associated gene signature classifier could be used as a feasible indicator for predicting OS.

Weighted Gene Correlation Network Analysis Identifies Specific Functional Modules and Genes in Esophageal Cancer

Objective

Esophageal cancer (ESCA) is one of the most aggressive malignancies globally with an undesirable five-year survival rate. Here, this study was conducted for determining specific functional genes linked with ESCA initiation and progression.

Methods

Gene expression profiling of ESCA was curated from TCGA (containing 160 ESCA and 11 nontumor specimens) and GSE38129 (30 paired ESCA and nontumor tissues) datasets. Differential expression analysis was conducted between ESCA and nontumor tissues with adjusted p value <0.05 and |log2fold-change|>1. Weighted gene coexpression network analysis (WGCNA) was conducted for determining the ESCA-specific coexpression modules and genes. Thereafter, ESCA-specific differentially expressed genes (DEGs) were intersected. Functional enrichment analysis was then presented with clusterProfiler package. Protein-protein interaction was conducted, and hub genes were determined. Association of hub genes with pathological staging was evaluated, and survival analysis was presented among ESCA patients.

Results

This study determined 91 ESCA-specific DEGs following intersection of DEGs and ESCA-specific genes in TCGA and GSE38129 datasets. They were remarkably linked to cell cycle progression and carcinogenic pathways like the p53 signaling pathway, cellular senescence, and apoptosis. Ten ESCA-specific hub genes were determined, containing ASPM, BUB1B, CCNA2, CDC20, CDK1, DLGAP5, KIF11, KIF20 A, TOP2A, and TPX2. They were prominently associated with pathological staging. Among them, KIF11 upregulation was in relation to undesirable prognosis of ESCA patients.

Conclusion

Collectively, we determined ESCA-specific coexpression modules and hub genes, which offered the foundation for future research concerning the mechanistic basis of ESCA.

ASPM Promotes the Progression of Anaplastic Thyroid Carcinomas by Regulating the Wnt/β-Catenin Signaling Pathway

BACKGROUND

Abnormal spindle-like microcephaly-associated protein (ASPM) is closely correlated with several malignant tumors, whereas little is known about the role of ASPM in anaplastic thyroid cancer (ATC). Herein, we sought to investigate whether ASPM is involved in the pathogenesis of ATC and the underlying mechanisms.

METHODS

The data from two data sets (GSE76039 and GSE33630) were extracted and analyzed for the expression of ASPM, followed by a further validation in collected ATC patients using quantitative real-time polymerase chain reaction (qRT-PCR) and western blotting. The effect of ASPM on cell proliferation, migration, invasion, and cell cycle was explored in ATC cell lines by in vitro inhibition of ASPM, while ASPM-mediated tumorigenicity was investigated in a xenograft tumor model. The involvement of Wnt/β-catenin signaling pathway was also investigated.

RESULTS

ASPM was overexpressed in ATC patients and cell lines. In vitro knockdown of ASPM inhibited the proliferation, migration, and invasion capabilities of ATC cells and induced cell cycle arrest. Wnt/β-catenin signaling was suppressed in response to ASPM inhibition, while rescue of β-catenin expression restored the impaired biological functions of ATC cells. In vivo transplantation of ASPM-knockdown cells inhibited the growth of tumors.

CONCLUSIONS

Upregulation of ASPM promotes the malignant properties of ATC cells and contributes to tumorigenesis through the Wnt/β-catenin signaling pathway.

ASPM facilitates colorectal cancer cells migration and invasion by enhancing β-catenin expression and nuclear translocation

Increased abnormal spindle-like microcephaly (ASPM) expression has been linked to clinical stage and poor prognosis in cancers, but the molecular mechanisms by which ASPM promotes cell metastasis in colorectal cancer (CRC) has not been identified. This study showed that the abilities of cell migration, invasion, and epithelial-mesenchymal transition (EMT) were attenuated in ASPM-deficient CRC cell lines. Furthermore, we reported that attenuation of ASPM expression inhibited CRC cell metastasis in vivo. Additionally, the expression of ASPM was positively correlated with β-catenin level in CRC tissues. Mechanistically, ASPM can upregulate β-catenin transcription by stimulating the β-catenin promoter and enhancing the nuclear translocation of β-catenin in CRC cells, which leads to the activation of the Wnt/β-catenin pathway. Finally, we showed that ASPM effectively induced CRC cell migration and invasion in a β-catenin-dependent manner.

Identification of potential biomarkers associated with immune infiltration in papillary renal cell carcinoma

Background

Immunotherapeutic approaches have recently emerged as effective treatment regimens against various types of cancer. However, the immune‐mediated mechanisms surrounding papillary renal cell carcinoma (pRCC) remain unclear. This study aimed to investigate the tumor microenvironment (TME) and identify the potential immune‐related biomarkers for pRCC.

Methods

The CIBERSORT algorithm was used to calculate the abundance ratio of immune cells in each pRCC samples. Univariate Cox analysis was used to select the prognostic‐related tumor‐infiltrating immune cells (TIICs). Multivariate Cox regression analysis was performed to develop a signature based on the selected prognostic‐related TIICs. Then, these pRCC samples were divided into low‐ and high‐risk groups according to the obtained signature. Analyses using Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and Gene Set Enrichment Analysis (GSEA) were performed to investigate the biological function of the DEGs (differentially expressed genes) between the high‐ and low‐risk groups. The hub genes were identified using a weighted gene co‐expression network analysis (WGCNA) and a protein‐protein interaction (PPI) analysis. The hub genes were subsequently validated by multiple clinical traits and databases.

Results

According to our analyses, nine immune cells play a vital role in the TME of pRCC. Our analyses also obtained nine potential immune‐related biomarkers for pRCC, including TOP2A, BUB1B, BUB1, TPX2, PBK, CEP55, ASPM, RRM2, and CENPF.

Conclusion

In this study, our data revealed the crucial TIICs and potential immune‐related biomarkers for pRCC and provided compelling insights into the pathogenesis and potential therapeutic targets for pRCC.

METTL3-mediated m6A methylation of ASPM drives hepatocellular carcinoma cells growth and metastasis

Background

Abnormal spindle‐like microcephaly (ASPM) has been proved to participate in tumor progression. However, the underlying mechanism of ASPM in liver hepatocellular carcinoma (LIHC) remains elusive.

Methods

The mRNA and protein expression were determined using Western blot and qRT‐PCR, and the capacities of cells proliferation, migration, and invasion were evaluated by CCK‐8, colony formation, wound healing, and transwell. MeRIP was performed to validate the interaction between ASPM and methyltransferase‐like 3 (METTL3).

Results

Herein, we found that ASPM was significantly upregulated in LIHC, and the high expression of ASPM was associated with poor LIHC prognosis. Furthermore, ASPM knockdown could suppress LIHC cells proliferation, migration, and invasion, while ASPM overexpression exerted reverse effect. Mechanistically, we revealed that the N6‐methyladenosine (m6A) modification of ASPM mRNA mediated by METTL3 promoted its expression in LIHC. More importantly, silencing METTL3 suppressed LIHC cells proliferation, migration, and invasion, which could be retained by ASPM overexpression.

Conclusion

Collectively, our findings suggested that METTL3/ASPM axis could serve as a novel promising therapeutic candidate for LIHC.

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.

Identifying and Validating Potential Biomarkers of Early Stage Lung Adenocarcinoma Diagnosis and Prognosis

Background

Lung adenocarcinoma (LUAD) is the most common pathological type of lung cancer. At present, most patients with LUAD are diagnosed at an advanced stage, and the prognosis of advanced LUAD is poor. Hence, we aimed to identify novel biomarkers for the diagnosis and treatment of early stage LUAD and to explore their predictive value.

Methods

The microarray datasets GSE63459, GSE27262, and GSE33532 were searched, and the differentially expressed genes (DEGs) were obtained using GEO2R. The DEGs were subjected to gene ontology (GO) and pathway enrichment analyses using METASCAPE. A protein–protein interaction (PPI) network was plotted with STRING and visualized by Cytoscape. Module analysis of the PPI network was performed using MCODE. Overall survival (OS) analysis and analysis of the mRNA expression levels of genes identified by MCODE were performed with UALCAN. Western blot analysis of hub genes in LUAD patients, MTS assays, and clonogenic assays were performed to test the effects of the hub genes on cell proliferation in vitro.

Results

A total of 341 DEGs were obtained, which were mainly enriched in terms related to blood vessel development, growth factor binding, and extracellular matrix organization. A PPI network consisting of 300 nodes and 1140 edges was constructed, and a significant module including 15 genes was identified. Elevated expression of ASPM, CCNB2, CDCA5, PRC1, KIAA0101, and UBE2T was associated with poor OS in LUAD patients. In the protein level, the hub gene was overexpressed in LUAD patients. In vitro experiments showed that knockdown of the hub genes in the LUAD cell lines could promote cell proliferation.

Conclusions

DEGs are potential biomarkers for early stage lung adenocarcinoma and could have utility for the diagnosis and predicting treatment efficacy.

Use of four genes in exosomes as biomarkers for the identification of lung adenocarcinoma and lung squamous cell carcinoma

The determination of biomarkers in the blood specific for lung adenocarcinoma (LUAD) and lung squamous cell carcinoma (LUSC) is crucial for the selection of effective treatment strategies and the prediction of prognosis. The purpose of the present study was to analyze the differentially expressed genes (DEGs) in LUSC and LUAD from The Cancer Genome Atlas (TCGA) database. In order to identify the potential biomarkers for non-small cell lung cancer (NSCLC) for clinical diagnosis, bioinformatics was used to analyze the DEGs of two subtypes of NSCLC, LUAD and LUSC. Exosomes were isolated from the serum of patients with LUAD or LUSC and identified using transmission electron microscopy, nanoparticle tracking analysis and western blot analysis. A total of four differential exosomal mRNAs were selected for validation with serum samples from 70 patients with NSCLC via reverse transcription-quantitative polymerase chain reaction. Receiver operating characteristic curves were established to evaluate the clinical diagnostic value of four DEGs for patients with LUAD and LUSC. The analysis based on TCGA data revealed the DEGs in LUSC and LUAD: A total of 1,619 genes were differentially expressed in patients with LUSC and LUAD. DEGs analyzed by Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analyses revealed that inflammation-related signaling pathways, such as complement pathways, and multiple autoimmune diseases, such as systemic lupus erythematosus and asthma were mainly enriched in LUAD. The cell cycle, Hippo signaling pathway, Rap1 signaling pathway and Wnt signaling pathway were the main signaling pathways enriched in LUSC. The combination of tumor protein P63 (TP63), keratin 5 (KRT5), CEA cell adhesion molecule 6 (CEACAM6) and surfactant protein B (SFTPB) improved the specificity and sensitivity in the diagnosis of different lung cancer subtypes. Exosomal TP63, KRT5, CEACAM6 and SFTPB mRNAs can thus be used as biomarkers to differentiate between LUSC and LUAD, and may provide a novel strategy for their differential diagnosis and treatment.

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.

Identification of potential markers for differentiating epithelial ovarian cancer from ovarian low malignant potential tumors through integrated bioinformatics analysis

Background

Epithelial ovarian cancer (EOC), as a lethal malignancy in women, is often diagnosed as advanced stages. In contrast, intermediating between benign and malignant tumors, ovarian low malignant potential (LMP) tumors show a good prognosis. However, the differential diagnosis of the two diseases is not ideal, resulting in delays or unnecessary therapies. Therefore, unveiling the molecular differences between LMP and EOC may contribute to differential diagnosis and novel therapeutic and preventive policies development for EOC.

Methods

In this study, three microarray data (GSE9899, GSE57477 and GSE27651) were used to explore the differentially expressed genes (DEGs) between LMP and EOC samples. Then, 5 genes were screened by protein–protein interaction (PPI) network, receiver operating characteristic (ROC), survival and Pearson correlation analysis. Meanwhile, chemical-core gene network construction was performed to identify the potential drugs or risk factors for EOC based on 5 core genes. Finally, we also identified the potential function of the 5 genes for EOC through pathway analysis.

Results

Two hundred thirty-four DEGs were successfully screened, including 81 up-regulated genes and 153 down-regulated genes. Then, 5 core genes (CCNB1, KIF20A, ASPM, AURKA, and KIF23) were identified through PPI network analysis, ROC analysis, survival and Pearson correlation analysis, which show better diagnostic efficiency and higher prognostic value for EOC. Furthermore, NetworkAnalyst was used to identify top 15 chemicals that link with the 5 core genes. Among them, 11 chemicals were potential drugs and 4 chemicals were risk factors for EOC. Finally, we found that all 5 core genes mainly regulate EOC development via the cell cycle pathway by the bioinformatic analysis.

Conclusion

Based on an integrated bioinformatic analysis, we identified potential biomarkers, risk factors and drugs for EOC, which may help to provide new ideas for EOC diagnosis, condition appraisal, prevention and treatment in future.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13048-021-00794-0.