CDC20, a potential cancer therapeutic target, is negatively regulated by p53

CDC20 and CCNB1 Overexpression as Prognostic Markers in Bladder Cancer

Background: Bladder cancer (BC) is one of the ten most common cancers worldwide, with a high recurrence rate and significant variation in clinical outcomes based on tumor grade and stage. This study aimed to investigate the gene expression profiles at different cancer stages to assess their potential prognostic value. Methods: RNA was extracted from paraffin-embedded BC tissues and the gene expression levels of CDC20 and CCNB1 were analyzed using qRT-PCR. A total of 54 BC patient samples were included in the analysis and categorized into low-grade (LG) (n = 23) and high-grade (HG) (n = 31) tumors, as well as stages pTa, pT1, and pT2. Results: CDC20 gene expression was significantly higher in the HG group (mean fold-change: 16.1) compared to the LG group (mean fold-change: 10.54), indicating a significant association with tumor grade (p = 0.039). However, no significant differences were observed in CDC20 expression across the cancer stages. For CCNB1, while gene expression was significantly elevated in higher-stage tumors (pT2 vs. pTa; p = 0.038), no significant association was found between CCNB1 expression and tumor grade. Survival analysis revealed that increased CCNB1 expression and advanced cancer stage were associated with poorer overall survival, whereas no significant impact of CDC20 expression or tumor grade on survival was observed. Correlation analysis indicated a positive relationship between CDC20 expression and tumor grade (r = 0.284, p = 0.038) and between CCNB1 expression and tumor stage (r = 0.301, p = 0.027). Conclusions: Our findings suggest that CDC20 overexpression is linked to higher tumor grades, while CCNB1 overexpression is associated with more advanced cancer stages in BC. These results underscore the potential utility of CDC20 and CCNB1 as biomarkers for tumor prognosis and as therapeutic targets. Further studies with larger cohorts are needed to validate these findings and better understand the molecular mechanisms driving BC progression.

The oncogenic role of EIF4A3/CDC20 axis in the endometrial cancer

Eukaryotic initiation factor 4A-3 (EIF4A3) is a key component of the exon junction complex (EJC) and is extensively involved in RNA splicing, inducing mRNA decay, and regulating the cell cycle and apoptosis. However, the potential role of EIF4A3 in EC has not been comprehensively investigated and remains unknown. Here, we report that the expression level of EIF4A3 is dramatically elevated in endometrial cancer (EC) samples compared with normal EC samples via bioinformatics analysis and immunohistochemistry analysis, and that high expression of EIF4A3 promotes the proliferation, migration, and invasion of EC cells. Mechanistically, we found that high EIF4A3 expression stabilized cell division cyclin 20 (CDC20) mRNA, and high EIF4A3 expression induced pro-carcinogenic effects in EC cells that were efficiently antagonized upon knockdown of CDC20, as well as Apcin, an inhibitor of CDC20. These findings reveal a novel mechanism by which high expression of EIF4A3 induces CDC20 upregulation, thus leading to EC tumorigenesis and metastasis, indicating a potential treatment strategy for EC patients with high EIF4A3 expression using Apcin. KEY MESSAGES: The expression level of EIF4A3 was dramatically elevated in endometrial cancer (EC) samples compared with normal endometrial cancer samples. High EIF4A3 expression stabilized CDC20 mRNA, and high EIF4A3 expression induced pro-carcinogenic effect in EC cells which was efficiently antagonized upon knockdown of CDC20. Apcin, an inhibitor of CDC20, could effectively counteract high expression of EIF4A3 inducing EC tumourigenesis and metastasis, indicating the potential treatment strategy for EC patients with EIF4A3 high expression by using Apcin.

Prognostic and Therapeutic Implications of Cell Division Cycle 20 Homolog in Breast Cancer

Cell division cycle 20 homolog (CDC20) is a well-known regulator of cell cycle progression. Abnormal expression of CDC20 leads to mitotic defects, which play a significant role in cancer development. In breast cancer (BC), CDC20 has been identified as a biomarker that has been linked to poor patient outcomes. In this study, we investigated the association of CDC20 with BC prognosis and immune cell infiltration by using multiple online databases, including UALCAN, KM plotter, TIMER2.0, HPA, TNM-plot, bc-GenExMiner, LinkedOmics, STRING, and GEPIA. The results demonstrate that BC patients have an elevated CDC20 expression in tumor tissues compared with the adjacent normal tissue. In addition, BC patients with overexpressed CDC20 had a median survival of 63.6 months compared to 169.2 months in patients with low CDC20 expression. Prognostic analysis of the examined data indicated that elevated expression of CDC20 was associated with poor prognosis and a reduction of overall survival in BC patients. These findings were even more prevalent in chemoresistance triple-negative breast cancer (TNBC) patients. Furthermore, the Gene Set Enrichment Analysis tool indicated that CDC20 regulates BC cells' cell cycle and apoptosis. CDC20 also significantly correlates with increased infiltrating B cells, CD4+ T cells, neutrophils, and dendritic cells in BC. In conclusion, the findings of this study suggest that CDC20 may be involved in immunomodulating the tumor microenvironment and provide evidence that CDC20 inhibition may serve as a potential therapeutic approach for the treatment of BC patients. In addition, the data indicates that CDC20 can be a reliable prognostic biomarker for BC.

Evaluating Ovarian Cancer Chemotherapy Response Using Gene Expression Data and Machine Learning

Background

Ovarian cancer (OC) is the most lethal gynecological cancer in the United States. Among the different types of OC, serous ovarian cancer (SOC) stands out as the most prevalent. Transcriptomics techniques generate extensive gene expression data, yet only a few of these genes are relevant to clinical diagnosis.

Methods

Methods for feature selection (FS) address the challenges of high dimensionality in extensive datasets. This study proposes a computational framework that applies FS techniques to identify genes highly associated with platinum-based chemotherapy response on SOC patients. Using SOC datasets from the Gene Expression Omnibus (GEO) database, LASSO and varSelRF FS methods were employed. Machine learning classification algorithms such as random forest (RF) and support vector machine (SVM) were also used to evaluate the performance of the models.

Results

The proposed framework has identified biomarkers panels with 9 and 10 genes that are highly correlated with platinum-paclitaxel and platinum-only response in SOC patients, respectively. The predictive models have been trained using the identified gene signatures and accuracy of above 90% was achieved.

Conclusions

In this study, we propose that applying multiple feature selection methods not only effectively reduces the number of identified biomarkers, enhancing their biological relevance, but also corroborates the efficacy of drug response prediction models in cancer treatment.

Activation of the Anaphase Promoting Complex Restores Impaired Mitotic Progression and Chemosensitivity in Multiple Drug-Resistant Human Breast Cancer

The development of multiple-drug-resistant (MDR) cancer all too often signals the need for toxic alternative therapy or palliative care. Our recent in vivo and in vitro studies using canine MDR lymphoma cancer cells demonstrate that the Anaphase Promoting Complex (APC) is impaired in MDR cells compared to normal canine control and drug-sensitive cancer cells. Here, we sought to establish whether this phenomena is a generalizable mechanism independent of species, malignancy type, or chemotherapy regime. To test the association of blunted APC activity with MDR cancer behavior, we used matched parental and MDR MCF7 human breast cancer cells, and a patient-derived xenograft (PDX) model of human triple-negative breast cancer. We show that APC activating mechanisms, such as APC subunit 1 (APC1) phosphorylation and CDC27/CDC20 protein associations, are reduced in MCF7 MDR cells when compared to chemo-sensitive matched cell lines. Consistent with impaired APC function in MDR cells, APC substrate proteins failed to be effectively degraded. Similar to our previous observations in canine MDR lymphoma cells, chemical activation of the APC using Mad2 Inhibitor-1 (M2I-1) in MCF7 MDR cells enhanced APC substrate degradation and resensitized MDR cells in vitro to the cytotoxic effects of the alkylating chemotherapeutic agent, doxorubicin (DOX). Using cell cycle arrest/release experiments, we show that mitosis is delayed in MDR cells with elevated substrate levels. When pretreated with M2I-1, MDR cells progress through mitosis at a faster rate that coincides with reduced levels of APC substrates. In our PDX model, mice growing a clinically MDR human triple-negative breast cancer tumor show significantly reduced tumor growth when treated with M2I-1, with evidence of increased DNA damage and apoptosis. Thus, our results strongly support the hypothesis that APC impairment is a driver of aggressive tumor development and that targeting the APC for activation has the potential for meaningful clinical benefits in treating recurrent cases of MDR malignancy.

Bioinformatics analysis and experimental validation reveal that CDC20 overexpression promotes bladder cancer progression and potential underlying mechanisms

BACKGROUND

Bladder cancer is a prevalent malignancy. CDC20, a pivotal cell cycle regulator gene, plays a significant role in tumour cell proliferation, but its role in bladder cancer remains unclear.

OBJECTIVE

This study aimed to analyse CDC20 expression in bladder cancer and explore its roles in tumour progression, treatment response, patient prognosis, and cellular proliferation mechanisms.

METHODS

We systematically analysed CDC20 expression in bladder cancer using bioinformatics. Our study investigated the impact of CDC20 on chemotherapy and radiotherapy sensitivity, patient prognosis, and changes in CDC20 methylation levels. We also explored the role and potential underlying mechanisms of CDC20 in bladder cancer cell growth. We used lentiviral transfection to downregulate CDC20 expression in 5637 and T24 cells, followed by CCK-8, colony formation, scratch, invasion, apoptosis, and cell cycle analyses.

RESULTS

CDC20 is highly expressed in bladder cancer and is significantly correlated with poor prognosis. Moreover, CDC20 demonstrated high diagnostic potential for bladder cancer (AUC > 0.9). The tumour methylation levels of CDC20 in tumour tissues markedly decreased compared with those in normal tissues, and lower methylation levels were associated with a worse prognosis. Elevated CDC20 expression is linked to increased mutation burden. Our findings suggested a potential association between high CDC20 expression and resistance to chemotherapy and radiotherapy, as CDC20 expression may impact immune cell infiltration levels. Mechanistic analysis revealed the influence of CDC20 on bladder cancer cell proliferation through cell cycle-related pathways. According to the cell experiments, CDC20 downregulation significantly impedes bladder cancer cell proliferation and invasion, leading to G1 phase arrest.

CONCLUSION

Aberrantly high CDC20 expression promotes tumour progression in bladder cancer, resulting in a poor prognosis, and may also constitute a promising therapeutic target.

Design, synthesis and biological evaluation of CDC20 inhibitors for treatment of triple-negative breast cancer

The involvement of CDC20 in promoting tumor growth in different types of human cancers and it disturbs the process of cell division and impedes tumor proliferation. In this work, a novel of Apcin derivatives targeting CDC20 were designed and synthesized to evaluate for their biological activities. The inhibitory effect on the proliferation of four human tumor cell lines (MCF-7, MDA-MB-231, MDA-MB-468 and A549) was observed. Among them, compound E1 exhibited the strongest inhibitory effect on the proliferation of MDA-MB-231 cells with an IC50 value of 1.43 μM, which was significantly superior to that of Apcin. Further biological studies demonstrated that compound E1 inhibited cancer cell migration and colony formation. Furthermore, compound E1 specifically targeted CDC20 and exhibited a higher binding affinity to CDC20 compared to that of Apcin, thereby inducing cell cycle arrest in the G2/M phase of cancer cells. Moreover, it has been observed that compound E1 induces autophagy in cancer cells. In 4T1 Xenograft Models compound E1 exhibited the potential antitumor activity without obvious toxicity. These findings suggest that E1 could be regarded as a CDC20 inhibitor deserved further investigation.

Non-canonical function of histone methyltransferase G9a in the translational regulation of chronic inflammation

We report a novel translation-regulatory function of G9a, a histone methyltransferase and well-understood transcriptional repressor, in promoting hyperinflammation and lymphopenia; two hallmarks of endotoxin tolerance (ET)-associated chronic inflammatory complications. Using multiple approaches, we demonstrate that G9a interacts with multiple translation regulators during ET, particularly the N6-methyladenosine (m6A) RNA methyltransferase METTL3, to co-upregulate expression of certain m6A-modified mRNAs that encode immune-checkpoint and anti-inflammatory proteins. Mechanistically, G9a promotes m6A methyltransferase activity of METTL3 at translational/post-translational level by regulating its expression, its methylation, and its cytosolic localization during ET. Additionally, from a broader view extended from the G9a-METTL3-m6A translation regulatory axis, our translatome proteomics approach identified numerous "G9a-translated" proteins that unite the networks associated with inflammation dysregulation, T cell dysfunction, and systemic cytokine response. In sum, we identified a previously unrecognized function of G9a in protein-specific translation that can be leveraged to treat ET-related chronic inflammatory diseases.

The potential role of CDC20 in tumorigenesis, cancer progression and therapy: A narrative review

The cell division cycle 20 homologue (CDC20) is known to regulate the cell cycle. Many studies have suggested that dysregulation of CDC20 is associated with various pathological processes in malignant solid tumors, including tumorigenesis, progression, chemoradiotherapy resistance, and poor prognosis, providing a biomarker for cancer diagnosis and prognosis. Some researchers have demonstrated that CDC20 also regulates apoptosis, immune microenvironment, and tumor angiogenesis. In this review, we have systematically summarized the biological functions of CDC20 in solid cancers. Furthermore, we briefly synthesized multiple medicines that inhibited CDC20. We anticipate that CDC20 will be a promising and effective biomarker and therapeutic target for the treatment of human cancer.

CDC20 Is Regulated by the Histone Methyltransferase, KMT5A, in Castration-Resistant Prostate Cancer

The methyltransferase KMT5A has been proposed as an oncogene in prostate cancer and therefore represents a putative therapeutic target. To confirm this hypothesis, we have performed a microarray study on a prostate cancer cell line model of androgen independence following KMT5A knockdown in the presence of the transcriptionally active androgen receptor (AR) to understand which genes and cellular processes are regulated by KMT5A in the presence of an active AR. We observed that 301 genes were down-regulated whilst 408 were up-regulated when KMT5A expression was reduced. KEGG pathway and gene ontology analysis revealed that apoptosis and DNA damage signalling were up-regulated in response to KMT5A knockdown whilst protein folding and RNA splicing were down-regulated. Under these conditions, the top non-AR regulated gene was found to be CDC20, a key regulator of the spindle assembly checkpoint with an oncogenic role in several cancer types. Further investigation revealed that KMT5A regulates CDC20 in a methyltransferase-dependent manner to modulate histone H4K20 methylation within its promoter region and indirectly via the p53 signalling pathway. A positive correlation between KMT5A and CDC20 expression was also observed in clinical prostate cancer samples, further supporting this association. Therefore, we conclude that KMT5A is a valid therapeutic target for the treatment of prostate cancer and CDC20 could potentially be utilised as a biomarker for effective therapeutic targeting.

Epigenetic reprogramming of cell cycle genes by ACK1 promotes breast cancer resistance to CDK4/6 inhibitor

Hormone receptor-positive, HER2-negative advanced breast cancers exhibit high sensitivity to CDK4/6 inhibitors such as palbociclib. However, most patients inevitably develop resistance, thus identification of new actionable therapeutic targets to overcome the recurrent disease is an urgent need. Immunohistochemical studies of tissue microarray revealed increased activation of non-receptor tyrosine kinase, ACK1 (also known as TNK2) in most of the breast cancer subtypes, independent of their hormone receptor status. Chromatin immunoprecipitation studies demonstrated that the nuclear target of activated ACK1, pY88-H4 epigenetic marks, were deposited at cell cycle genes, CCNB1, CCNB2 and CDC20, which in turn initiated their efficient transcription. Pharmacological inhibition of ACK1 using its inhibitor, (R)-9b dampened CCNB1, CCNB2 and CDC20 expression, caused G2/M arrest, culminating in regression of palbociclib-resistant breast tumor growth. Further, (R)-9b suppressed expression of CXCR4 receptor, which resulted in significant impairment of metastasis of breast cancer cells to lung. Overall, our pre-clinical data identifies activated ACK1 as an oncogene that epigenetically controls the cell cycle genes governing the G2/M transition in breast cancer cells. ACK1 inhibitor, (R)-9b could be a novel therapeutic option for the breast cancer patients that have developed resistance to CDK4/6 inhibitors.

Genetic deviation associated with photodynamic therapy in HeLa cell

Photodynamic therapy (PDT) is a method that is used in cancer treatment. The main therapeutic effect is the production of singlet oxygen (1O2). Phthalocyanines for PDT produce high singlet oxygen with absorbers of about 600-700 nm.

AIM

It is aimed to analyze cancer cell pathways by flow cytometry analysis and cancer-related genes with q-PCR device by applying phthalocyanine L1ZnPC, which we use as photosensitizer in photodynamic therapy, in HELA cell line. In this study, we investigate the molecular basis of L1ZnPC's anti-cancer activity.

MATERIAL METHOD

The cytotoxic effects of L1ZnPC, a phthalocyanine obtained from our previous study, in HELA cells were evaluated and it was determined that it led to a high rate of death as a result. The result of photodynamic therapy was analyzed using q-PCR. From the data received at the conclusion of this investigation, gene expression values were calculated, and expression levels were assessed using the 2-∆∆Ct method to examine the relative changes in these values. Cell death pathways were interpreted with the FLOW cytometer device. One-Way Analysis of Variance (ANOVA) and the Tukey-Kramer Multiple Comparison Test with Post-hoc Test were used for the statistical analysis.

CONCLUSION

In our study, it was observed that HELA cancer cells underwent apoptosis at a rate of 80% with drug application plus photodynamic therapy by flow cytometry method. According to q-PCR results, CT values ​​of eight out of eighty-four genes were found to be significant and their association with cancer was evaluated. L1ZnPC is a new phthalocyanine used in this study and our findings should be supported by further studies. For this reason, different analyses are needed to be performed with this drug in different cancer cell lines. In conclusion, according to our results, this drug looks promising but still needs to be analyzed through new studies. It is necessary to examine in detail which signaling pathways they use and their mechanism of action. For this, additional experiments are required.

Network and functional analyses of differentially expressed genes in gastric cancer provide new biomarkers associated with disease pathogenesis

BACKGROUND

Gastric cancer is a dominant source of cancer-related death around the globe and a serious threat to human health. However, there are very few practical diagnostic approaches and biomarkers for the treatment of this complex disease.

METHODS

This study aimed to evaluate the association between differentially expressed genes (DEGs), which may function as potential biomarkers, and the diagnosis and treatment of gastric cancer (GC). We constructed a protein-protein interaction network from DEGs followed by network clustering. Members of the two most extensive modules went under the enrichment analysis. We introduced a number of hub genes and gene families playing essential roles in oncogenic pathways and the pathogenesis of gastric cancer. Enriched terms for Biological Process were obtained from the "GO" repository.

RESULTS

A total of 307 DEGs were identified between GC and their corresponding normal adjacent tissue samples in GSE63089 datasets, including 261 upregulated and 261 downregulated genes. The top five hub genes in the PPI network were CDK1, CCNB1, CCNA2, CDC20, and PBK. They are involved in focal adhesion formation, extracellular matrix remodeling, cell migration, survival signals, and cell proliferation. No significant survival result was found for these hub genes.

CONCLUSIONS

Using comprehensive analysis and bioinformatics methods, important key pathways and pivotal genes related to GC progression were identified, potentially informing further studies and new therapeutic targets for GC treatment.

p53 directly downregulates the expression of CDC20 to exert anti-tumor activity in mantle cell lymphoma

BACKGROUND

Cell cycle dysregulation characterized by cyclin D1 overexpression is common in mantle cell lymphoma (MCL), while mitotic disorder was less studied. Cell division cycle 20 homologue (CDC20), an essential mitotic regulator, was highly expressed in various tumors. Another common abnormality in MCL is p53 inactivation. Little was known about the role of CDC20 in MCL tumorigenesis and the regulatory relationship between p53 and CDC20 in MCL.

METHODS

CDC20 expression was detected in MCL patients and MCL cell lines harboring mutant p53 (Jeko and Mino cells) and wild-type p53 (Z138 and JVM2 cells). Z138 and JVM2 cells were treated with CDC20 inhibitor apcin, p53 agonist nutlin-3a, or in combination, and then cell proliferation, cell apoptosis, cell cycle, cell migration and invasion were determined by CCK-8, flow cytometry and Transwell assays. The regulatory mechanism between p53 and CDC20 was revealed by dual-luciferase reporter gene assay and CUT&Tag technology. The anti-tumor effect, safety and tolerability of nutlin-3a and apcin were investigated in vivo in the Z138-driven xenograft tumor model.

RESULTS

CDC20 was overexpressed in MCL patients and cell lines compared with their respective controls. The typical immunohistochemical marker of MCL patients, cyclin D1, was positively correlated with CDC20 expression. CDC20 high expression indicated unfavorable clinicopathological features and poor prognosis in MCL patients. In Z138 and JVM2 cells, either apcin or nutlin-3a treatment could inhibit cell proliferation, migration and invasion, and induce cell apoptosis and cell cycle arrest. GEO analysis, RT-qPCR and WB results showed that p53 expression was negatively correlated with CDC20 expression in MCL patients, Z138 and JVM2 cells, while this relationship was not observed in p53-mutant cells. Dual-luciferase reporter gene assay and CUT&Tag assay revealed mechanistically that CDC20 was transcriptionally repressed by p53 through directly binding p53 to CDC20 promoter from - 492 to + 101 bp. Moreover, combined treatment of nutlin-3a and apcin showed better anti-tumor effect than single treatment in Z138 and JVM2 cells. Administration of nutlin-3a/apcin alone or in combination confirmed their efficacy and safety in tumor-bearing mice.

CONCLUSIONS

Our study validates the essential role of p53 and CDC20 in MCL tumorigenesis, and provides a new insight for MCL therapeutics through dual-targeting p53 and CDC20.

Current Progress and Perspectives of CDC20 in Female Reproductive Cancers

The cancers of the cervix, endometrium, ovary, and breast are great threats to women's health. Cancer is characterized by the uncontrolled proliferation of cells and deregulated cell cycle progression is one of the main causes of malignancy. Agents targeting cell cycle regulators may have potential anti-tumor effects. CDC20 (cell division cycle 20 homologue) is a co-activator of the anaphase-promoting complex/cyclosome (APC/C) and thus acts as a mitotic regulator. In addition, CDC20 serves as a subunit of the mitotic checkpoint complex (MCC) whose function is to inhibit APC/C. Recently, higher expression of CDC20 has been reported in these cancers and was closely associated with their clinicopathological parameters, indicating CDC20 a potential target for cancer treatment that is worth further study. In the present review, we summarized current progress and put forward perspectives of CDC20 in female reproductive cancers.

Prognostic significance of CDC20 expression in malignancy patients: A meta-analysis

BACKGROUND

Cell Division Cycle Protein 20(CDC20) is reported to promote cancer initiation, progression and drug resistance in many preclinical models and is demonstrated in human cancer tissues. However, the correlation between CDC20 and cancer patients' prognosis has not yet been systematically evaluated. Therefore, this present meta-analysis was performed to determine the prognostic value of CDC20 expression in various malignancy tumors.

METHODS

A thorough database search was performed in EMBASE, PubMed, Cochrane Library and Web of Science from inception to May 2022. Stata14.0 Software was used for the statistical analysis. The pooled hazard ratios(HRs) and their 95% confidence intervals (95% CIs) were used to analysis of overall survival (OS), recurrence-free survival (RFS), distant-metastasis free survival (DMFS). Qualities of the included literature were assessed by JBI Critical appraisal checklist. Egger's test was used to assess publication bias in the included studies.

RESULTS

Ten articles were selected, and 2342 cancer patients were enrolled. The cancer types include breast, colorectal, lung, gastric, oral, prostate, urothelial bladder cancer, and hepatocellular carcinoma. The result showed strong significant associations between high expression of CDC20 and endpoints: OS (HR 2.52, 95%CI 2.13-2.99; HR 2.05, 95% CI 1.50-2.82, respectively) in the multivariate analysis and in the univariate analysis. Also, high expression of CDC20 was significantly connected with poor RFS (HR 2.08, 95%CI 1.46-2.98) and poor DMFS (HR 4.49, 95%CI 1.57-12.85). The subgroup analysis was also performed, which revealed that CDC20 upregulated expression was related to poor OS in non-small cell lung cancer (HR 2.40, 95% CI 1.91-3.02).

CONCLUSIONS

This meta-analysis demonstrated that highly expressing CDC20 was associated with poor survival in human malignancy tumors. CDC20 may be a valuable prognostic predictive biomarker and a potential therapeutic target in various cancer parents.

The targets of aspirin in bladder cancer: bioinformatics analysis

Background

The anti-carcinogenic properties of aspirin have been observed in some solid tumors. However, the molecular mechanism of therapeutic effects of aspirin on bladder cancer is still indistinct. We introduced a bioinformatics analysis approach, to explore the targets of aspirin in bladder cancer (BC).

Methods

To find out the potential targets of aspirin in BC, we analyzed direct protein targets (DPTs) of aspirin in Drug Bank 5.0. The protein-protein interaction (PPI) network and signaling pathway of aspirin DPTs were then analyzed subsequently. A detailed analysis of the KEGG (Kyoto Encyclopedia of Genes and Genomes) pathway has shown that aspirin is linked to BC. We identified overexpressed genes in BC comparing with normal samples by Oncomine and genes that interlinked with aspirin target genes in BC by STRING.

Results

Firstly, we explored 16 direct protein targets (DPT) of aspirin. We analyzed the protein-protein interaction (PPI) network and signaling pathways of aspirin DPT. We found that aspirin is closely associated with a variety of cancers, including BC. Then, we classified mutations in 3 aspirin DPTs (CCND1, MYC and TP53) in BC using the cBio Portal database. In addition, we extracted the top 50 overexpressed genes in bladder cancer by Oncomine and predicted the genes associated with the 3 aspirin DPTs (CCND1, MYC and TP53) in BC by STRING. Finally, 5 exact genes were identified as potential therapeutic targets of aspirin in bladder cancer.

Conclusion

The analysis of relevant databases will improve our mechanistic understanding of the role of aspirin in bladder cancer. This will guide the direction of our next drug-disease interaction studies.

Germline Missense Variants in CDC20 Result in Aberrant Mitotic Progression and Familial Cancer

CDC20 is a coactivator of the anaphase promoting complex/cyclosome (APC/C) and is essential for mitotic progression. APC/CCDC20 is inhibited by the spindle assembly checkpoint (SAC), which prevents premature separation of sister chromatids and aneuploidy in daughter cells. Although overexpression of CDC20 is common in many cancers, oncogenic mutations have never been identified in humans. Using whole-exome sequencing, we identified heterozygous missense CDC20 variants (L151R and N331K) that segregate with ovarian germ cell tumors in two families. Functional characterization showed these mutants retain APC/C activation activity but have impaired binding to BUBR1, a component of the SAC. Expression of L151R and N331K variants promoted mitotic slippage in HeLa cells and primary skin fibroblasts derived from carriers. Generation of mice carrying the N331K variant using CRISPR-Cas9 showed that, although homozygous N331K mice were nonviable, heterozygotes displayed accelerated oncogenicity of Myc-driven cancers. These findings highlight an unappreciated role for CDC20 variants as tumor-promoting genes.

SIGNIFICANCE

Two germline CDC20 missense variants that segregate with cancer in two families compromise the spindle assembly checkpoint and lead to aberrant mitotic progression, which could predispose cells to transformation. See related commentary by Villarroya-Beltri and Malumbres, p. 3432.

Impaired Cdc20 signaling promotes senescence in normal cells and apoptosis in non-small cell lung cancer cells

Cellular senescence is a form of irreversible growth arrest that cancer cells evade. The cell division cycle protein 20 homolog (Cdc20) is a positive regulator of cell division, but how its dysregulation may relate to senescence is unclear. Here, we find that Cdc20 mRNA and protein expression are downregulated in stress-induced premature senescent lung fibroblasts in a p53-dependent manner. Either Cdc20 downregulation or inhibition of anaphase-promoting complex/cyclosome (APC/C) is sufficient to induce premature senescence in lung fibroblasts, while APC/C activation inhibits stress-induced premature senescence. Mechanistically, we show both Cdc20 downregulation and APC/C inhibition induce premature senescence through glycogen synthase kinase (GSK)-3β-mediated phosphorylation and downregulation of securin expression. Interestingly, we determined Cdc20 expression is upregulated in human lung adenocarcinoma. We find that downregulation of Cdc20 in non-small cell lung cancer (NSCLC) cells is sufficient to inhibit cell proliferation and growth in soft agar and to promote apoptosis, but not senescence, in a manner dependent on downregulation of securin following GSK-3β-mediated securin phosphorylation. Similarly, we demonstrate securin expression is downregulated and cell viability is inhibited in NSCLC cells following inhibition of APC/C. Furthermore, we show chemotherapeutic drugs downregulate both Cdc20 and securin protein expression in NSCLC cells. Either Cdc20 downregulation by siRNA or APC/C inhibition sensitize, while securin overexpression inhibits, chemotherapeutic drug-induced NSCLC cell death. Together, our findings provide evidence that Cdc20/APC/C/securin-dependent signaling is a key regulator of cell survival, and its disruption promotes premature senescence in normal lung cells and induces apoptosis in lung cancer cells that have bypassed the senescence barrier.

Polygenic risk modeling of tumor stage and survival in bladder cancer

Introduction

Bladder cancer assessment with non-invasive gene expression signatures facilitates the detection of patients at risk and surveillance of their status, bypassing the discomforts given by cystoscopy. To achieve accurate cancer estimation, analysis pipelines for gene expression data (GED) may integrate a sequence of several machine learning and bio-statistical techniques to model complex characteristics of pathological patterns.

Methods

Numerical experiments tested the combination of GED preprocessing by discretization with tree ensemble embeddings and nonlinear dimensionality reductions to categorize oncological patients comprehensively. Modeling aimed to identify tumor stage and distinguish survival outcomes in two situations: complete and partial data embedding. This latter experimental condition simulates the addition of new patients to an existing model for rapid monitoring of disease progression. Machine learning procedures were employed to identify the most relevant genes involved in patient prognosis and test the performance of preprocessed GED compared to untransformed data in predicting patient conditions.

Results

Data embedding paired with dimensionality reduction produced prognostic maps with well-defined clusters of patients, suitable for medical decision support. A second experiment simulated the addition of new patients to an existing model (partial data embedding): Uniform Manifold Approximation and Projection (UMAP) methodology with uniform data discretization led to better outcomes than other analyzed pipelines. Further exploration of parameter space for UMAP and t-distributed stochastic neighbor embedding (t-SNE) underlined the importance of tuning a higher number of parameters for UMAP rather than t-SNE. Moreover, two different machine learning experiments identified a group of genes valuable for partitioning patients (gene relevance analysis) and showed the higher precision obtained by preprocessed data in predicting tumor outcomes for cancer stage and survival rate (six classes prediction).

Conclusions

The present investigation proposed new analysis pipelines for disease outcome modeling from bladder cancer-related biomarkers. Complete and partial data embedding experiments suggested that pipelines employing UMAP had a more accurate predictive ability, supporting the recent literature trends on this methodology. However, it was also found that several UMAP parameters influence experimental results, therefore deriving a recommendation for researchers to pay attention to this aspect of the UMAP technique. Machine learning procedures further demonstrated the effectiveness of the proposed preprocessing in predicting patients’ conditions and determined a sub-group of biomarkers significant for forecasting bladder cancer prognosis.

Large-scale prediction of key dynamic interacting proteins in multiple cancers

Tracking cancer dynamic protein-protein interactions (PPIs) and deciphering their pathogenesis remain a challenge. We presented a dynamic PPIs' hypothesis: permanent and transient interactions might achieve dynamic switchings from normal cells to malignancy, which could cause maintenance functions to be interrupted and transient functions to be sustained. Based on the hypothesis, we first predicted >1400 key cancer genes (KCG) by applying PPI-express we proposed to 18 cancer gene expression datasets. We then further screened out key dynamic interactions (KDI) of cancer based on KCG and transient and permanent interactions under both conditions. Two prominent functional characteristics, "Cell cycle-related" and "Immune-related", were presented for KCG, suggesting that these might be their general characteristics. We found that, compared to permanent to transient KDI pairs (P2T) in the network, transient to permanent (T2P) have significantly higher edge betweenness (EB), and P2T pairs tending to locate intra-functional modules may play roles in maintaining normal biological functions, while T2P KDI pairs tending to locate inter-modules may play roles in biological signal transduction. It was consistent with our hypothesis. Also, we analyzed network characteristics of KDI pairs and their functions. Our findings of KDI may serve to understand and explain a few hallmarks of cancer.

Identifying General Tumor and Specific Lung Cancer Biomarkers by Transcriptomic Analysis

The bioinformatic pipeline previously developed in our research laboratory is used to identify potential general and specific deregulated tumor genes and transcription factors related to the establishment and progression of tumoral diseases, now comparing lung cancer with other two types of cancer. Twenty microarray datasets were selected and analyzed separately to identify hub differentiated expressed genes and compared to identify all the deregulated genes and transcription factors in common between the three types of cancer and those unique to lung cancer. The winning DEGs analysis allowed to identify an important number of TFs deregulated in the majority of microarray datasets, which can become key biomarkers of general tumors and specific to lung cancer. A coexpression network was constructed for every dataset with all deregulated genes associated with lung cancer, according to DAVID’s tool enrichment analysis, and transcription factors capable of regulating them, according to oPOSSUM´s tool. Several genes and transcription factors are coexpressed in the networks, suggesting that they could be related to the establishment or progression of the tumoral pathology in any tissue and specifically in the lung. The comparison of the coexpression networks of lung cancer and other types of cancer allowed the identification of common connectivity patterns with deregulated genes and transcription factors correlated to important tumoral processes and signaling pathways that have not been studied yet to experimentally validate their role in lung cancer. The Kaplan–Meier estimator determined the association of thirteen deregulated top winning transcription factors with the survival of lung cancer patients. The coregulatory analysis identified two top winning transcription factors networks related to the regulatory control of gene expression in lung and breast cancer. Our transcriptomic analysis suggests that cancer has an important coregulatory network of transcription factors related to the acquisition of the hallmarks of cancer. Moreover, lung cancer has a group of genes and transcription factors unique to pulmonary tissue that are coexpressed during tumorigenesis and must be studied experimentally to fully understand their role in the pathogenesis within its very complex transcriptomic scenario. Therefore, the downstream bioinformatic analysis developed was able to identify a coregulatory metafirm of cancer in general and specific to lung cancer taking into account the great heterogeneity of the tumoral process at cellular and population levels.

CDC20 in and out of mitosis: a prognostic factor and therapeutic target in hematological malignancies

Cell division cycle 20 homologue (CDC20) is a well-known regulator of cell cycle, as it controls the correct segregation of chromosomes during mitosis. Many studies have focused on the biological role of CDC20 in cancer development, as alterations of its functionality have been linked to genomic instability and evidence demonstrated that high CDC20 expression levels are associated with poor overall survival in solid cancers. More recently, novel CDC20 functions have been demonstrated or suggested, including the regulation of apoptosis and stemness properties and a correlation with immune cell infiltration. Here, we here summarize and discuss the role of CDC20 inside and outside mitosis, starting from its network of interacting proteins. In the last years, CDC20 has also attracted more interest in the blood cancer field, being overexpressed and showing an association with prognosis both in myeloid and lymphoid malignancies. Preclinical findings showed that selective CDC20 and APC/CCDC20/APC/CCDH1 inhibitors, namely Apcin and proTAME, are effective against lymphoma and multiple myeloma cells, resulting in mitotic arrest and apoptosis and synergizing with clinically-relevant drugs. The evidence and hypothesis presented in this review provide the input for further biological and chemical studies aiming to dissect novel potential CDC20 roles and targeting strategies in hematological malignancies.

Integrative Analysis for Identification of Therapeutic Targets and Prognostic Signatures in Non-Small Cell Lung Cancer

Differential expressions of certain genes during tumorigenesis may serve to identify novel manageable targets in the clinic. In this work with an integrated bioinformatics approach, we analyzed public microarray datasets from Gene Expression Omnibus (GEO) to explore the key differentially expressed genes (DEGs) in non-small cell lung cancer (NSCLC). We identified a total of 984 common DEGs in 252 healthy and 254 NSCLC gene expression samples. The top 10 DEGs as a result of pathway enrichment and protein–protein interaction analysis were further investigated for their prognostic performances. Among these, we identified high expressions of CDC20, AURKA, CDK1, EZH2, and CDKN2A genes that were associated with significantly poorer overall survival in NSCLC patients. On the contrary, high mRNA expressions of CBL, FYN, LRKK2, and SOCS2 were associated with a significantly better prognosis. Furthermore, our drug target analysis for these hub genes suggests a potential use of Trichostatin A, Pracinostat, TGX-221, PHA-793887, AG-879, and IMD0354 antineoplastic agents to reverse the expression of these DEGs in NSCLC patients.

TORC1 inactivation promotes APC/C-dependent mitotic slippage in yeast and human cells

Unsatisfied kinetochore-microtubule attachment activates the spindle assembly checkpoint to inhibit the metaphase-anaphase transition. However, some cells eventually override mitotic arrest by mitotic slippage. Here, we show that inactivation of TORC1 kinase elicits mitotic slippage in budding yeast and human cells. Yeast mitotic slippage was accompanied with aberrant aspects, such as degradation of the nucleolar protein Net1, release of phosphatase Cdc14, and anaphase-promoting complex/cyclosome (APC/C)-Cdh1-dependent degradation of securin and cyclin B in metaphase. This mitotic slippage caused chromosome instability. In human cells, mammalian TORC1 (mTORC1) inactivation also invoked mitotic slippage, indicating that TORC1 inactivation-induced mitotic slippage is conserved from yeast to mammalian cells. However, the invoked mitotic slippage in human cells was not dependent on APC/C-Cdh1. This study revealed an unexpected involvement of TORC1 in mitosis and provides information on undesirable side effects of the use of TORC1 inhibitors as immunosuppressants and anti-tumor drugs.

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Yeast TORC1 inhibition promotes Net1 degradation and Cdc14 release

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Yeast TORC1 inhibition invokes mitotic slippage in an APC/C-Cdh1-dependent manner

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Human mTORC1 inhibition also elicits mitotic slippage

Crosstalk between Plk1, p53, cell cycle, and G2/M DNA damage checkpoint regulation in cancer: computational modeling and analysis

Different cancer cell lines can have varying responses to the same perturbations or stressful conditions. Cancer cells that have DNA damage checkpoint-related mutations are often more sensitive to gene perturbations including altered Plk1 and p53 activities than cancer cells without these mutations. The perturbations often induce a cell cycle arrest in the former cancer, whereas they only delay the cell cycle progression in the latter cancer. To study crosstalk between Plk1, p53, and G2/M DNA damage checkpoint leading to differential cell cycle regulations, we developed a computational model by extending our recently developed model of mitotic cell cycle and including these key interactions. We have used the model to analyze the cancer cell cycle progression under various gene perturbations including Plk1-depletion conditions. We also analyzed mutations and perturbations in approximately 1800 different cell lines available in the Cancer Dependency Map and grouped lines by genes that are represented in our model. Our model successfully explained phenotypes of various cancer cell lines under different gene perturbations. Several sensitivity analysis approaches were used to identify the range of key parameter values that lead to the cell cycle arrest in cancer cells. Our resulting model can be used to predict the effect of potential treatments targeting key mitotic and DNA damage checkpoint regulators on cell cycle progression of different types of cancer cells.

Identification of Key Genes Associated with Progression and Prognosis of Bladder Cancer through Integrated Bioinformatics Analysis

Simple Summary

Bladder cancer is a heterogeneous disease with high recurrence rates. The current prognostication depends on tumor stage and grade and there is a need for predictive biomarkers that can distinguish between progressive versus non-progressive disease. We have identified a 3-gene signature panel having prognostic value in bladder cancer, which could aid in clinical decision making.

Abstract

Bladder cancer prognosis remains dismal due to lack of appropriate biomarkers that can predict its progression. The study aims to identify novel prognostic biomarkers associated with the progression of bladder cancer by utilizing three Gene Expression Omnibus (GEO) datasets to screen differentially expressed genes (DEGs). A total of 1516 DEGs were identified between non-muscle invasive and muscle invasive bladder cancer specimens. To identify genes of prognostic value, we performed gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis. A total of seven genes, including CDKN2A, CDC20, CTSV, FOXM1, MAGEA6, KRT23, and S100A9 were confirmed with strong prognostic values in bladder cancer and validated by qRT-PCR conducted in various human bladder cancer cells representing stage-specific disease progression. ULCAN, human protein atlas and The Cancer Genome Atlas datasets were used to confirm the predictive value of these genes in bladder cancer progression. Moreover, Kaplan–Meier analysis and Cox hazard ratio analysis were performed to determine the prognostic role of these genes. Univariate analysis performed on a validation set identified a 3-panel gene set viz. CDKN2A, CTSV and FOXM1 with 95.5% sensitivity and 100% specificity in predicting bladder cancer progression. In summary, our study screened and confirmed a 3-panel biomarker that could accurately predict the progression and prognosis of bladder cancer.

Identification of Key Biomarkers and Pathways in Small-Cell Lung Cancer Using Biological Analysis

Background

Small-cell lung cancer (SCLC) is a major cause of carcinoma-related deaths worldwide. The aim of this study was to identify the key biomarkers and pathways in SCLC using biological analysis.

Methods

Key genes involved in the development of SCLC were identified by downloading three datasets from the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) were screened using the GEO2R online analyzer; for the functional annotation and pathway enrichment analysis of genes, Funrich software was used. Construction of protein-to-protein interaction (PPI) networks was accomplished using the Search Tool for the Retrieval of Interacting Genes (STRING), and network visualization and module identification were performed using Cytoscape.

Results

A total of 268 DEGs were ultimately obtained. The enriched functions and pathways of the upregulated DEGs included cell cycle, mitotic, and DNA replication, and the downregulated DEGs were enriched in epithelial-to-mesenchymal transition, serotonin degradation, and noradrenaline. Analysis of significant modules demonstrated that the upregulated genes are primarily concentrated in functions related to cell cycle and DNA replication. Kaplan-Meier analysis of hub genes revealed that they may promote the carcinogenesis and progression of SCLC. The result of ONCOMINE demonstrated that these 10 hub genes were significantly overexpressed in SCLC compared with normal samples.

Conclusion

Identification of the molecular functions and signaling pathways of participating DEGs can deepen the current understanding of the molecular mechanisms of SCLC. The knowledge gained from this work may contribute to the development of treatment options and improve the prognosis of SCLC in the future.

NF2 Gene Participates in Regulation of the Cell Cycle of Meningiomas by Restoring Spindle Assembly Checkpoint Function and Inhibiting the Binding of Cdc20 Protein to Anaphase Promoting Complex/Cyclosome

BACKGROUND

The neurofibromatosis type 2 (NF2) gene mutation is the leading genetic event in meningiomas, usually accompanied by malignant features. Dysfunction of the spindle assembly checkpoint (SAC) induces tumorigenesis. However, the crosstalk between NF2 and SAC in meningiomas remains unclear.

METHODS

Cell proliferation, invasion, apoptosis, and cell cycle of meningiomas were determined by cell counting kit-8 assay, transwell assay, and flow cytometry, respectively. The expression of SAC in meningioma cells was detected by quantitative real-time polymerase chain reaction and Western blot. The interaction between anaphase promoting complex/cyclosome (APC/C) and cell division cycle 20 (Cdc20) protein in meningioma cells was further explored by co-immunoprecipitation.

RESULTS

We found that the expression of NF2/merlin was low or absent in malignant meningiomas. Overexpression of NF2 suppressed the proliferation and invasion of meningioma cells, prolonged the G₂/M phase, and elevated the expression of SAC proteins at posttranscription. Furthermore, the interaction between APC/C and Cdc20 was inhibited by NF2.

CONCLUSIONS

Our findings suggested that NF2 might restore SAC function by impairing the binding of APC/C and Cdc20, thereby limiting the mitotic rate and inhibiting proliferation of meningiomas.

Application of comprehensive bioinformatics approaches to reconnoiter crucial genes and pathways underpinning hepatocellular carcinoma: a drug repurposing endeavor

Hepatocellular carcinoma (HCC) is the fifth most common neoplasm in the world. Chronic inflammation of liver and associated wound healing processes collectively contribute to the development of cirrhosis which further progresses to dysplastic nodule and then to HCC. Etiological mediators and ongoing manipulations at cellular level in HCC are well established; however, key protein interactions and genetic alterations involved in stepwise hepatocarcinogenic pathways are seldom explored. This study aims to unravel novel targets of HCC and repurpose the FDA-approved drugs against the same. Genetic data pertinent to different stages of HCC were retrieved from GSE6764 dataset and analyzed via GEO2R. Subsequently, protein-protein interaction network analysis of differentially expressed genes was performed to identify the hub genes with significant interaction. Hub genes displaying higher interactions were considered as potential HCC targets and were validated thorough UALCAN and GEPIA databases. These targets were screened against FDA-approved drugs through molecular docking and dynamics simulation studies to capture the drugs with potential activity against HCC. Finally, cytotoxicity of the shortlisted drug was confirmed in vitro by MTT assay. CDC20 was identified as potential druggable target. Docking, binding energy calculations, and dynamic studies revealed significant interaction exhibited by Labetalol with CDC20. Further, in MTT assay, Labetalol demonstrated an IC₅₀ of 200.29 µg/ml in inhibiting the cell growth of HepG2 cell line. In conclusion, this study discloses a series of key genetic underpinnings of HCC and recommends the pertinence of labetalol as a potential repurposable drug against HCC.

PIGN spatiotemporally regulates the spindle assembly checkpoint proteins in leukemia transformation and progression

Phosphatidylinositol glycan anchor biosynthesis class N (PIGN) has been linked to the suppression of chromosomal instability. The spindle assembly checkpoint complex is responsible for proper chromosome segregation during mitosis to prevent chromosomal instability. In this study, the novel role of PIGN as a regulator of the spindle assembly checkpoint was unveiled in leukemic patient cells and cell lines. Transient downregulation or ablation of PIGN resulted in impaired mitotic checkpoint activation due to the dysregulated expression of spindle assembly checkpoint-related proteins including MAD1, MAD2, BUBR1, and MPS1. Moreover, ectopic overexpression of PIGN restored the expression of MAD2. PIGN regulated the spindle assembly checkpoint by forming a complex with the spindle assembly checkpoint proteins MAD1, MAD2, and the mitotic kinase MPS1. Thus, PIGN could play a vital role in the spindle assembly checkpoint to suppress chromosomal instability associated with leukemic transformation and progression.

The Oncogenic Role of APC/C Activator Protein Cdc20 by an Integrated Pan-Cancer Analysis in Human Tumors

The landscape of CDC20 gene expression and its biological impacts across different types of cancers remains largely unknown. Here, a pan-cancer analysis was performed to analyze the role of Cdc20 in various human cancers. Our results indicated that the expression levels of the CDC20 gene were significantly elevated in bladder cancer, breast cancer, colon cancer, rectum cancer, stomach cancer, esophageal cancer, head and neck cancer, kidney cancer, liver cancer, lung cancer, prostate cancer, pancreatic cancer, and uterine cancer. In addition, the expression of CDC20 was significantly and positively correlated with the increase of clinical stages in multiple cancer types, including breast cancer, kidney cancer, and lung cancer, et al. Among 33 cancer subtypes in the TCGA dataset, the high expression of CDC20 was correlated with poor prognosis in 10 cancer types. Furthermore, the abundance of phosphorylated Cdc20 in the primary tumor was elevated and correlated with increased tumor grade. Next, we sought to elucidate the oncogenic role by analyzing its association with immune infiltration. For most cancer types, the CDC20 expression was positively correlated with the infiltration of cancer-associated fibroblasts and myeloid-derived suppressor cells. To further understand its functional activity, we explored the classic Cdc20 downstream substrates, which were found to be mutually exclusive with the expression of Cdc20. Moreover, the pan-cancer analysis of the molecular function of Cdc20 indicated that BUB1, CCNA2, CCNB1, CDK1, MAD2L1, and PLK1 might play a critical role in interaction with Cdc20. The abundance of Cdc20 was further validated at transcriptional and translational levels with a publicly available dataset and clinical tumor tissues. The knockdown of Cdc20 dramatically inhibited tumor growth both in vivo and in vitro. Therefore, our studies delineated the oncogenic role of CDC20 and its prognostic significance at the pan-cancer level and proved its functional activity in Cdc20 high expression cancer types. Our studies will merits further molecular assays to understand the potential role of Cdc20 in tumorigenesis and provide the rationale for developing novel therapeutic strategies.

Identification of CDC20 as a Novel Biomarker in Diagnosis and Treatment of Wilms Tumor

Objective: Wilms tumor (WT) is a common malignant solid tumor in children. Many tumor biomarkers have been reported; however, there are poorly targetable molecular mechanisms which have been defined in WT. This study aimed to identify the oncogene in WT and explore the potential mechanisms. Methods: Differentially expressed genes (DEGs) in three independent RNA-seq datasets were downloaded from The Cancer Genome Atlas data portal and the Gene Expression Omnibus database (GSE66405 and GSE73209). The common DEGs were then subjected to Gene Ontology enrichment analysis, protein-protein interaction (PPI) network analysis, and gene set enrichment analysis. The protein expression levels of the hub gene were analyzed by immunohistochemical analysis and Western blotting in a 60 WT sample. The univariate Kaplan-Meier analysis for overall survival was performed, and the log-rank test was utilized. A small interfering RNA targeting cell division cycle 20 (CDC20) was transfected into G401 and SK-NEP-1 cell lines. The Cell Counting Kit-8 assay and wound healing assay were used to observe the changes in cell proliferation and migration after transfection. Flow cytometry was used to detect the effect on the cell cycle. Western blot was conducted to study the changes of related functional proteins. Results: We commonly identified 44 upregulation and 272 downregulation differentially expressed genes in three independent RNA-seq datasets. Gene and pathway enrichment analyses of the regulatory networks involving hub genes suggested that cell cycle changes are crucial in WT. The top 15 highly connected genes were found by PPI network analysis. Furthermore, we demonstrated that one candidate biomarker, CDC20, for the diagnosis of WT was detected, and its high expression predicted poor prognosis of WT patients. Moreover, the area under the curve value obtained by receiver operating characteristic curve analysis from paired WT samples was 0.9181. Finally, we found that the suppression of CDC20 inhibited proliferation and migration and resulted in G2/M phase arrest in WT cells. The mechanism may be involved in increasing the protein level of securin, cyclin B1, and cyclin A Conclusion: Our results suggest that CDC20 could serve as a candidate diagnostic and prognostic biomarker for WT, and suppression of CDC20 may be a potential approach for the prevention and treatment of WT.

CDC20 regulates the cell proliferation and radiosensitivity of P53 mutant HCC cells through the Bcl-2/Bax pathway

Purpose: The incidence of hepatocellular carcinoma (HCC) is extremely high, and China accounts for approximately 50% of global liver cancer cases. Previous studies reported that CDC20 is involved in the occurrence and progression of a variety of malignant tumors. So, whether CDC20 will affect the development of HCC, we have conducted in-depth research on this. Methods: We selected Hep3B and HepG2 for cell culture, and performed siRNA transfection, lentiviral infection, western blot, MTS determination, cell cycle determination, apoptosis test, immunodeficiency test, clone survival test and subcutaneous parthenogenesis in nude mice. Results: Knockdown of CDC20 greatly enhanced the radiation efficacy on the growth retardation in HepG2, and protein level of CDC20 was decreased for the activation of P53 by radiation. Downregulation of CDC20 combined with radiation can inhibit proliferation, aggravate DNA damage, increase G2/M arrest, and promote apoptosis of HCC cells to a greater extent, and the relative survival fraction of HCC cells was gradually reduced with radiation dose increased in P53 mutated Hep3B cells. After knocking down CDC20 in HCC, Bcl-2 was down-regulated and Bax expression increased. Down-regulation of CDC20 can inhibit further invasion by promoting the radiosensitivity of HCC. Conclusion: In this study, we found that that CDC20 was highly expressed in HCC and participated in radio resistance of HCC cells with P53 mutation Bcl-2/Bax via signaling pathway. This study is the first to present evidence that CDC20 may play a role in improving the efficacy of radiotherapy in HCC.

Activation of the aryl hydrocarbon receptor by 3-methylcholanthrene, but not by indirubin, suppresses mammosphere formation via downregulation of CDC20 expression in breast cancer cells

The aryl hydrocarbon receptor (AhR) is a ligand-activated transcription factor that regulates various toxicological and biological functions. We reported previously that 3-methylcholanthrene (3MC), an exogenous AhR agonist, inhibited tumorsphere (mammosphere) formation from breast cancer cell lines, while the endogenous AhR agonist, indirubin, very weakly inhibited this process. However, the difference in inhibition mechanism of mammosphere formation by 3MC or indirubin is still unknown. In this study, we established AhR-re-expressing (KOTR-AhR) cells from AhR knockout MCF-7 cells using the tetracycline (Tet)-inducible gene expression systems. To identify any difference in inhibition of mammosphere formation by 3MC or indirubin, RNA-sequencing (RNA-seq) experiments were performed using KOTR-AhR cells. RNA-seq experiments revealed that cell division cycle 20 (CDC20), which regulates the cell cycle and mitosis, was decreased by 3MC, but not by indirubin, in the presence of AhR expression. Furthermore, the mRNA and protein levels of CDC20 were decreased by 3MC in MCF-7 cells via the AhR. In addition, mammosphere formation was suppressed by small interfering RNA-mediated CDC20 knockdown compared to the negative control in MCF-7 cells. These results suggest that AhR activation by 3MC suppresses mammosphere formation via downregulation of CDC20 expression in breast cancer cells. This study provides useful information for the development of AhR-targeted anti-cancer drugs.

Application of Molecular Nanoprobes in the Analysis of Differentially Expressed Genes and Prognostic Models of Primary Hepatocellular Carcinoma

Analyzing hub genes related to tumorigenesis based on biological big data has recently become a hotspot in biomedicine. Nanoprobes, nanobodies and theranostic molecules targeting hub genes delivered by nanocarriers have been widely applied in tumor theranostics. Hepatocellular carcinoma (HCC) is one of the most common cancers, with a poor prognosis and high mortality. Identifying hub genes according to the gene expression levels and constructing prognostic signatures related to the onset and outcome of HCC will be of great significance. In this study, the expression profiles of HCC and normal tissue were obtained from the GEO database and analyzed by GEO₂R to identify DEGs. GO terms and KEGG pathways were enriched in DAVID software. The STRING database was consulted to find protein-protein interactions between proteins encoded by the DEGs, which were visualized by Cytoscape. Then, overall survival associated with the hub genes was calculated by the Kaplan-Meier plotter online tool, and verification of the results was carried out on TCGA samples and their corresponding clinical information. A total of 603 DEGs were obtained, of which 479 were upregulated and 124 were downregulated. PPI networks including 603 DEGs and 18 clusters were constructed, of which 7 clusters with MCODE score ≥3 and nodes ≥5 were selected. The 5 genes with the highest degrees of connectivity were identified as hub genes, and a prognostic model was constructed. The expression and prognostic potential of this model was validated on TCGA clinical data. In conclusion, a five-gene signature (TOP2A, PCNA, AURKA, CDC20, CCNB2) overexpressed inHCC was identified, and a prognostic model was constructed. This gene signature may act as a prognostic model for HCC and provide potential targets of nanotechnology.

Machine learning and network-based models to identify genetic risk factors to the progression and survival of colorectal cancer

Colorectal cancer (CRC) is one of the most common and lethal malignant lesions. Determining how the identified risk factors drive the formation and development of CRC could be an essential means for effective therapeutic development. Aiming this, we investigated how the altered gene expression resulting from exposure to putative CRC risk factors contribute to prognostic biomarker identification. Differentially expressed genes (DEGs) were first identified for CRC and other eight risk factors. Gene set enrichment analysis (GSEA) through the molecular pathway and gene ontology (GO), as well as protein-protein interaction (PPI) network, were then conducted to predict the functions of these DEGs. Our identified genes were explored through the dbGaP and OMIM databases to compare with the already identified and known prognostic CRC biomarkers. The survival time of CRC patients was also examined using a Cox Proportional Hazard regression-based prognostic model by integrating transcriptome data from The Cancer Genome Atlas (TCGA). In this study, PPI analysis identified 4 sub-networks and 8 hub genes that may be potential therapeutic targets, including CXCL8, ICAM1, SOD2, CXCL2, CCL20, OIP5, BUB1, ASPM and IL1RN. We also identified seven signature genes (PRR5.ARHGAP8, CA7, NEDD4L, GFR2, ARHGAP8, SMTN, OIP5) in independent analysis and among which PRR5. ARHGAP8 was found in both multivariate analyses and in analyses that combined gene expression and clinical information. This approach provides both mechanistic information and, when combined with predictive clinical information, good evidence that the identified genes are significant biomarkers of processes involved in CRC progression and survival.

CDC20 and PTTG1 are Important Biomarkers and Potential Therapeutic Targets for Metastatic Prostate Cancer

INTRODUCTION

Metastatic prostate cancer (mPCa) is responsible for most prostate cancer (PCa) deaths worldwide. The present study aims to explore the molecular differences between mPCa and PCa.

METHODS

The authors downloaded GSE6752, GSE6919, and GSE32269 from the Gene Expression Omnibus and employed integrated analysis to identify differentially expressed genes (DEGs) between mPCa and PCa. Functional and pathway-enrichment analyses were performed, and a protein-protein interaction (PPI) network and modules were constructed. Clinical mPCa specimens were collected to verify the results by performing RT-qPCR. The Cancer Genome Atlas database was used to conduct a survival analysis, and an immunohistochemical assay was performed. The invasion ability of PCa cells was verified by Transwell assay.

RESULTS

One-hundred six consistently DEGs were found in mPCa compared with PCa. DEGs significantly enriched the positive regulation of cell proliferation, cell division, and cell adhesion in small cell lung cancer and PCa. Cell division, nucleoplasm, and cell cycle were selected from the PPI network, and the top 10 hub genes were selected. CDC20 and PTTG1 with genetic alterations were significantly associated with poorer disease-free survival. Immunohistochemical assay results showed that the expression levels of CDC20 and PTTG1 in mPCa were higher than those in PCa. The results of the migration assay indicated that CDC20 and PTTG1 could enhance the migration ability of PCa cells.

CONCLUSION

The present study revealed that CDC20 and PTTG1 contribute more to migration, progression, and poorer prognoses in mPCa compared with PCa. CDC20 and PTTG1 could represent therapeutic targets in mPCa medical research and clinical studies.

Inhibition of Cdc20 suppresses the metastasis in triple negative breast cancer (TNBC)

BACKGROUND

Cdc20 is a crucial activator of the anaphase-promoting complex (APC/C) and is known to be essential in mitosis regulation. Abnormally high expression of Cdc20 has been reported in several malignancies. We aimed to study the Cdc20 expression in human breast cancer tissues, focusing specifically on Cdc20 in Triple-Negative Breast Cancer (TNBC).

METHODS

The expression of mitotic regulators mRNA in three TNBC cell lines or three other breast cancer cell lines was determined by the RNA-sequencing database. 14,713 human breast cancer patient samples included in Breast Cancer-GenExminer v4.5 were used to analyze whether cell division cycle 20 (Cdc20) expression was related to TNBC. To find whether Cdc20 expression impacted prognosis in TNBC, we used 2,249 TNBC patients database. The loss of Cdc20 by RNA interference (shRNA) and several mitotic inhibitors including Apcin, ZM447439, BI 2536, and VX-680 on the capacities of proliferation, migration, invasion were evaluated by colony-forming, wound-healing, transwell assay, and western blot, respectively.

RESULTS

We studied the mitosis-related genes and proteins that are closely related to TNBC through the National Center for Biotechnology Information (NCBI) database. We found that Cdc20, one of the central mitotic regulators, is significantly upregulated in human TNBC, and its expression level is positively correlated with metastasis-free and relapse-free patient survival. We also found Cdc20 is highly conserved in TNBC in comparison to other breast cancer subtype cell lines. Cdc20 deficiency results in a decrease in cell growth and migration in four TNBC cell lines. Also, several mitotic inhibitors, such as Apcin, VX-680, ZM447439, and BI 2536, blocked cancer cell growth and invasion.

CONCLUSIONS

These results suggest an essential role of Cdc20 in tumor formation and metastasis of TNBC, which might be a potential target therapy for TNBC treatment.

Bioinformatics analysis identified CDC20 as a potential drug target for cholangiocarcinoma

BACKGROUND

Cholangiocarcinoma (CCA) is a malignancy that originates from bile duct cells. The incidence and mortality of CCA are very high especially in Southeast Asian countries. Moreover, most CCA patients have a very poor outcome. Presently, there are still no effective treatment regimens for CCA. The resistance to several standard chemotherapy drugs occurs frequently; thus, searching for a novel effective treatment for CCA is urgently needed.

METHODS

In this study, comprehensive bioinformatics analyses for identification of novel target genes for CCA therapy based on three microarray gene expression profiles (GSE26566, GSE32225 and GSE76297) from the Gene Expression Omnibus (GEO) database were performed. Based on differentially expressed genes (DEGs), gene ontology and pathway enrichment analyses were performed. Protein-protein interactions (PPI) and hub gene identifications were analyzed using STRING and Cytoscape software. Then, the expression of candidate genes from bioinformatics analysis was measured in CCA cell lines using real time PCR. Finally, the anti-tumor activity of specific inhibitor against candidate genes were investigated in CCA cell lines cultured under 2-dimensional and 3-dimensional cell culture models.

RESULTS

The three microarray datasets exhibited an intersection consisting of 226 DEGs (124 up-regulated and 102 down-regulated genes) in CCA. DEGs were significantly enriched in cell cycle, hemostasis and metabolism pathways according to Reactome pathway analysis. In addition, 20 potential hub genes in CCA were identified using the protein-protein interaction (PPI) network and sub-PPI network analysis. Subsequently, CDC20 was identified as a potential novel targeted drug for CCA based on a drug prioritizing program. In addition, the anti-tumor activity of a potential CDC20 inhibitor, namely dinaciclib, was investigated in CCA cell lines. Dinaciclib demonstrated huge anti-tumor activity better than gemcitabine, the standard chemotherapeutic drug for CCA.

CONCLUSION

Using integrated bioinformatics analysis, CDC20 was identified as a novel candidate therapeutic target for CCA.

Integrated Protein-Protein Interaction and Weighted Gene Co-expression Network Analysis Uncover Three Key Genes in Hepatoblastoma

Hepatoblastoma (HB) is the most common liver tumor in the pediatric population, with typically poor outcomes for advanced-stage or chemotherapy-refractory HB patients. The objective of this study was to identify genes involved in HB pathogenesis via microarray analysis and subsequent experimental validation. We identified 856 differentially expressed genes (DEGs) between HB and normal liver tissue based on two publicly available microarray datasets (GSE131329 and GSE75271) after data merging and batch effect correction. Protein–protein interaction (PPI) analysis and weighted gene co-expression network analysis (WGCNA) were conducted to explore HB-related critical modules and hub genes. Subsequently, Gene Ontology (GO) analysis was used to reveal critical biological functions in the initiation and progression of HB. Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis showed that genes involved in cell cycle phase transition and the PI3K/AKT signaling were associated with HB. The intersection of hub genes identified by both PPI and WGCNA analyses revealed five potential candidate genes. Based on receiver operating characteristic (ROC) curve analysis and reports in the literature, we selected CCNA2, CDK1, and CDC20 as key genes of interest to validate experimentally. CCNA2, CDK1, or CDC20 small interfering RNA (siRNA) knockdown inhibited aggressive biological properties of both HepG2 and HuH-6 cell lines in vitro. In conclusion, we identified CCNA2, CDK1, and CDC20 as new potential therapeutic biomarkers for HB, providing novel insights into important and viable targets in future HB treatment.

Identification of the hub gene BUB1B in hepatocellular carcinoma via bioinformatic analysis and in vitro experiments

Background

Hepatocellular carcinoma (HCC) is one of the most commonly diagnosed cancers and the fourth leading cause of cancer-related deaths in the world. Although the treatment of HCC has made great progress in recent years, the therapeutic effects on HCC are still unsatisfactory due to difficulty in early diagnosis, chemoresistance and high recurrence rate post-surgery.

Methods

In this study, we identified differentially expressed genes (DEGs) based on four Gene Expression Omnibus (GEO) datasets (GSE45267, GSE98383, GSE101685 and GSE112790) between HCC and normal hepatic tissues. A protein–protein interaction (PPI) network was established to identify the central nodes associated with HCC. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis of the central nodes were conducted to find the hub genes. The expression levels of the hub genes were validated based on the ONCOMINE and Gene Expression Profiling Interactive Analysis (GEPIA) databases. Additionally, the genetic alterations of the hub genes were evaluated by cBioPortal. The role of the hub genes on the overall survival (OS) and relapse survival (RFS) of HCC patients was evaluated by Kaplan-Meier plotter. At last, the mechanistic role of the hub genes was illustrated by in vitro experiments.

Results

We found the following seven hub genes: BUB1B, CCNB1, CCNB2, CDC20, CDK1, MAD2L1 and RRM2 using integrated bioinformatics analysis. All of the hub genes were significantly upregulated in HCC tissues. And the seven hub genes were associated with the OS and RFS of HCC patients. Finally, in vitro experiments indicated that BUB1B played roles in HCC cell proliferation, migration, invasion, apoptosis and cell cycle by partially affecting mitochondrial functions.

Conclusions

In summary, we identified seven hub genes that were associated with the expression and prognosis of HCC. The mechanistic oncogenic role of BUB1B in HCC was first illustrated. BUB1B might play an important role in HCC and could be potential therapeutic targets for HCC.

Identifying of biomarkers associated with gastric cancer based on 11 topological analysis methods of CytoHubba

Gastric cancer (GC) is one of the most common types of malignancy. Its potential molecular mechanism has not been clarified. In this study, we aimed to explore potential biomarkers and prognosis-related hub genes associated with GC. The gene chip dataset GSE79973 was downloaded from the GEO datasets and limma package was used to identify the differentially expressed genes (DEGs). A total of 1269 up-regulated and 330 down-regulated genes were identified. The protein-protein interactions (PPI) network of DEGs was constructed by STRING V11 database, and 11 hub genes were selected through intersection of 11 topological analysis methods of CytoHubba in Cytoscape plug-in. All the 11 selected hub genes were found in the module with the highest score from PPI network of all DEGs by the molecular complex detection (MCODE) clustering algorithm. In order to explore the role of the 11 hub genes, we performed GO function and KEGG pathway analysis for them and found that the genes were enriched in a variety of functions and pathways among which cellular senescence, cell cycle, viral carcinogenesis and p53 signaling pathway were the most associated with GC. Kaplan-Meier analysis revealed that 10 out of the 11 hub genes were related to the overall survival of GC patients. Further, seven of the 11 selected hub genes were verified significantly correlated with GC by uni- or multivariable Cox model and LASSO regression analysis including C3, CDK1, FN1, CCNB1, CDC20, BUB1B and MAD2L1. C3, CDK1, FN1, CCNB1, CDC20, BUB1B and MAD2L1 may serve as potential prognostic biomarkers and therapeutic targets for GC.

Identification of Seven Cell Cycle-Related Genes with Unfavorable Prognosis and Construction of their TF-miRNA-mRNA regulatory network in Breast Cancer

Breast cancer (BC), with complex tumorigenesis and progression, remains the most common malignancy in women. We aimed to explore some novel and significant genes with unfavorable prognoses and potential pathways involved in BC initiation and progression via bioinformatics methods. BC tissue-specific microarray datasets of GSE42568, GSE45827 and GSE54002, which included a total of 651 BC tissues and 44 normal breast tissues, were obtained from the Gene Expression Omnibus (GEO) database, and 124 differentially expressed genes (DEGs) were identified between BC tissues and normal breast tissues via R software and an online Venn diagram tool. Database for Annotation, Visualization and Integration Discovery (DAVID) software showed that 65 upregulated DEGs were mainly enriched in the regulation of the cell cycle, and Search Tool for the Retrieval of Interacting Genes (STRING) software identified the 39 closest associated upregulated DEGs in protein-protein interactions (PPIs), which validated the high expression of genes in BC tissues by the Gene Expression Profiling Interactive Analysis (GEPIA) tool. In addition, 36 out of 39 BC patients showed significantly worse outcomes by Kaplan-Meier plotter (KM plotter), and an additional Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis revealed that seven genes (cyclin E2 (CCNE2), cyclin B1 (CCNB1), cyclin B2 (CCNB2), mitotic checkpoint serine/threonine kinase B (BUB1B), dual-specificity protein kinase (TTK), cell division cycle 20 (CDC20), and pituitary tumor transforming gene 1 (PTTG1)) were markedly enriched in the cell cycle pathway. Analysis of the clinicopathological characteristics of hub genes revealed that seven cell cycle-related genes (CCRGs) were significantly highly expressed in four BC subtypes (luminal A, luminal B, HER2-positive and triple-negative (TNBC)), and except for the CCNE2 gene, high expression levels were significantly associated with tumor pathological grade and stage and metastatic events of BC. Furthermore, genetic mutation analysis indicated that genetic alterations of CCRGs could also significantly affect BC patients' prognosis. A quantitative real-time polymerase chain reaction (qRT-PCR) assay found that the seven CCRGs were significantly differentially expressed in BC cell lines. Integration of published multilevel expression data and a bioinformatics computational approach were used to predict and construct a regulation mechanism: a transcription factor (TF)-microRNA (miRNA)-messenger RNA (mRNA) regulation network. The present work is the first to construct a regulatory network of TF-miRNA-mRNA in BC for CCRGs and provides new insights into the molecular mechanism of BC.

Identification of CDK1 as a candidate marker in cutaneous squamous cell carcinoma by integrated bioinformatics analysis

BACKGROUND

Cutaneous squamous cell carcinoma (cSCC) is a relatively common cancer that accounts for nearly 50% of non-melanoma skin cancer cases. However, the genotypes that are linked with poor prognosis and/or high relapse rates and pathogenic mechanisms of cSCC are not fully understood. To address these points, three gene expression datasets were analyzed to identify candidate biomarker genes in cSCC.

METHODS

The GSE117247, GSE32979, and GSE98767 datasets comprising a total of 32 cSCC samples and 31 normal skin tissue samples were obtained from the National Center for Biotechnology Information Gene Expression Omnibus database. Differentially expressed genes (DEGs) were identified and underwent pathway enrichment analyses with the Gene Ontology and Kyoto Encyclopedia of Genes and Genomes (KEGG). A putative DEG protein-protein interaction (PPI) network was also established that included hub genes. The expression of CDK1, MAD2L1, BUB1 ans CDC20 were examined in the study.

RESULTS

A total of 335 genes were identified, encompassing 219 found to be upregulated and 116 genes that were downregulated in cSCC, compared to normal tissue. Enriched functions of these DEGs were associated with Ephrin receptor signaling and cell division; cytosol, membrane, and extracellular exosomes; ATP-, poly(A) RNA-, and identical protein binding. We also established a PPI network comprising 332 nodes and identified KIF2C, CDC42, AURKA, MAD2L1, MYC, CDK1, FEN1, H2AFZ, BUB1, BUB1B, CKS2, CDC20, CCT2, ACTR2, ACTB, MAPK14, and HDAC1 as candidate hub genes. The expression of CDK1 are significantly higher in the cSCC tissues than that in normal skin.

CONCLUSIONS

The DEGs identified in this study are potential therapeutic targets and biomarkers for cSCC. CDK1 is a gene closely related to the occurrence and development of cSCC, which may play an important role. Bioinformatics analysis shows that it is involved in the important pathway of the pathogenesis of cSCC, and may be recognized and applied as a new biomarker in the future diagnosis and treatment of cSCC.

Novel gene-specific translation mechanism of dysregulated, chronic inflammation reveals promising, multifaceted COVID-19 therapeutics

Hyperinflammation and lymphopenia provoked by SARS-CoV-2-activated macrophages contribute to the high mortality of Coronavirus Disease 2019 (COVID-19) patients. Thus, defining host pathways aberrantly activated in patient macrophages is critical for developing effective therapeutics. We discovered that G9a, a histone methyltransferase that is overexpressed in COVID-19 patients with high viral load, activates translation of specific genes that induce hyperinflammation and impairment of T cell function or lymphopenia. This noncanonical, pro-translation activity of G9a contrasts with its canonical epigenetic function. In endotoxin-tolerant (ET) macrophages that mimic conditions which render patients with pre-existing chronic inflammatory diseases vulnerable to severe symptoms, our chemoproteomic approach with a biotinylated inhibitor of G9a identified multiple G9a-associated translation regulatory pathways that were upregulated by SARS-CoV-2 infection. Further, quantitative translatome analysis of ET macrophages treated progressively with the G9a inhibitor profiled G9a-translated proteins that unite the networks associated with viral replication and the SARS-CoV-2-induced host response in severe patients. Accordingly, inhibition of G9a-associated pathways produced multifaceted, systematic effects, namely, restoration of T cell function, mitigation of hyperinflammation, and suppression of viral replication. Importantly, as a host-directed mechanism, this G9a-targeted, combined therapeutics is refractory to emerging antiviral-resistant mutants of SARS-CoV-2, or any virus, that hijacks host responses.

Identification of potential target genes and crucial pathways in small cell lung cancer based on bioinformatic strategy and human samples

Small cell lung cancer (SCLC) is a carcinoma of the lungs with strong invasion, poor prognosis and resistant to multiple chemotherapeutic drugs. It has posed severe challenges for the effective treatment of lung cancer. Therefore, searching for genes related to the development and prognosis of SCLC and uncovering their underlying molecular mechanisms are urgent problems to be resolved. This study is aimed at exploring the potential pathogenic and prognostic crucial genes and key pathways of SCLC via bioinformatic analysis of public datasets. Firstly, 117 SCLC samples and 51 normal lung samples were collected and analyzed from three gene expression datasets. Then, 102 up-regulated and 106 down-regulated differentially expressed genes (DEGs) were observed. And then, functional annotation and pathway enrichment analyzes of DEGs was performed utilizing the FunRich. The protein-protein interaction (PPI) network of the DEGs was constructed through the STRING website, visualized by Cytoscape. Finally, the expression levels of eight hub genes were confirmed in Oncomine database and human samples from SCLC patients. It showed that CDC20, BUB1, TOP2A, RRM2, CCNA2, UBE2C, MAD2L1, and BUB1B were upregulated in SCLC tissues compared to paired adjacent non-cancerous tissues. These suggested that eight hub genes might be viewed as new biomarkers for prognosis of SCLC or to guide individualized medication for the therapy of SCLC.

Ubiquitin-proteasome system (UPS) as a target for anticancer treatment

The ubiquitin-proteasome system (UPS) plays an important role in the cellular processes for protein quality control and homeostasis. Dysregulation of the UPS has been implicated in numerous diseases, including cancer. Indeed, components of UPS are frequently mutated or abnormally expressed in various cancers. Since Bortezomib, a proteasome inhibitor, received FDA approval for the treatment of multiple myeloma and mantle cell lymphoma, increasing numbers of researchers have been seeking drugs targeting the UPS as a cancer therapeutic strategy. Here, we introduce the essential component of UPS, including ubiquitinating enzymes, deubiquitinating enzymes and 26S proteasome, and we summarize their targets and mechanisms that are crucial for tumorigenesis. In addition, we briefly discuss some UPS inhibitors, which are currently in clinical trials as cancer therapeutics.