Aberrant KIF20A Expression Is Associated with Adverse Clinical Outcome and Promotes Tumor Progression in Prostate Cancer

The role of kinesin family members in hepatobiliary carcinomas: from bench to bedside

As a major component of the digestive system malignancies, tumors originating from the hepatic and biliary ducts seriously endanger public health. The kinesins (KIFs) are molecular motors that enable the microtubule-dependent intracellular trafficking necessary for mitosis and meiosis. Normally, the stability of KIFs is essential to maintain cell proliferation and genetic homeostasis. However, aberrant KIFs activity may destroy this dynamic stability, leading to uncontrolled cell division and tumor initiation. In this work, we have made an integral summarization of the specific roles of KIFs in hepatocellular and biliary duct carcinogenesis, referring to aberrant signal transduction and the potential for prognostic evaluation. Additionally, current clinical applications of KIFs-targeted inhibitors have also been discussed, including their efficacy advantages, relationship with drug sensitivity or resistance, the feasibility of combination chemotherapy or other targeted agents, as well as the corresponding clinical trials. In conclusion, the abnormally activated KIFs participate in the regulation of tumor progression via a diverse range of mechanisms and are closely associated with tumor prognosis. Meanwhile, KIFs-aimed inhibitors also carry out a promising tumor-targeted therapeutic strategy that deserves to be further investigated in hepatobiliary carcinoma (HBC).

Comprehensive analysis of co-expressed genes with TDP-43: prognostic and therapeutic potential in lung adenocarcinoma

BACKGROUND

Transactivating DNA-binding protein 43 (TDP-43) is intimately associated with tumorigenesis and progression by regulating mRNA splicing, transport, stability, and non-coding RNA molecules. The exact role of TDP-43 in lung adenocarcinoma (LUAD) has not yet been fully elucidated, despite extensive research on its function in various cancer types. An imperative aspect of comprehending the underlying biological characteristics associated with TDP-43 involves investigating the genes that are co-expressed with this protein. This study assesses the prognostic significance of these co-expressed genes in LUAD and subsequently explores potential therapeutic strategies based on these findings.

METHODS

Transcriptomic and clinical data pertaining to LUAD were retrieved from open-access databases to establish an association between mRNA expression profiles and the presence of TDP-43. A risk-prognosis model was developed to compare patient survival rates across various groups, and its accuracy was also assessed. Additionally, differences in tumor stemness, mutational profiles, tumor microenvironment (TME) characteristics, immune checkpoints, and immune cell infiltration were analyzed in the different groups. Moreover, the study entailed predicting the potential response to immunotherapy as well as the sensitivity to commonly employed chemotherapeutic agents and targeted drugs for each distinct group.

RESULTS

The TDP-43 Co-expressed Gene Risk Score (TCGRS) model was constructed utilizing four genes: Kinesin Family Member 20A (KIF20A), WD Repeat Domain 4 (WDR4), Proline Rich 11 (PRR11), and Glia Maturation Factor Gamma (GMFG). The value of this model in predicting LUAD patient survival is effectively illustrated by both the Kaplan-Meier (K-M) survival curve and the area under the receiver operating characteristic curve (AUC-ROC). The Gene Set Enrichment Analysis (GSEA) revealed that the high TCGRS group was primarily enriched in biological pathways and functions linked to DNA replication and cell cycle; the low TCGRS group showed primary enrichment in immune-related pathways and functions. The high and low TCGRS groups showed differences in tumor stemness, mutational burden, TME, immune infiltration level, and immune checkpoints. The predictions analysis of immunotherapy indicates that the Tumor Immune Dysfunction and Exclusion (TIDE) score (p < 0.001) and non-response rate (74% vs. 51%, p < 0.001) in the high TCGRS group are higher than those in the low TCGRS group. The Immune Phenotype Score (IPS) in the high TCGRS group is lower than in the low TCGRS group (p < 0.001). The drug sensitivity analysis revealed that the half-maximal inhibitory concentration (IC50) values for cisplatin, docetaxel, doxorubicin, etoposide, gemcitabine, paclitaxel, vincristine, erlotinib, and gefitinib (all p < 0.01) in the high TCGRS group are lower than those in the low TCGRS group.

CONCLUSIONS

The TCGRS derived from the model exhibits a reliable biomarker for evaluating both prognosis and treatment effectiveness among patients with LUAD. This study is anticipated to offer valuable insights into developing effective treatment strategies for this patient population. It is believed that this study is anticipated to contribute significantly to clinical diagnostics, the development of therapeutic drugs, and the enhancement of patient care.

Ginsenoside 20(S)-Rg3 reduces KIF20A expression and promotes CDC25A proteasomal degradation in epithelial ovarian cancer

Background

Ginsenoside 20(S)-Rg3 shows promising tumor-suppressive effects in ovarian cancer via inhibiting NF-κB signaling. This study aimed to explore the downstream tumor suppressive mechanisms of ginsenoside Rg3 via this signaling pathway.

Materials and methods

A systematical screening was applied to examine the expression profile of 41 kinesin family member genes in ovarian cancer. The regulatory effect of ginsenoside Rg3 on KIF20A expression was studied. In addition, we explored interacting proteins of KIF20A and their molecular regulations in ovarian cancer. RNA-seq data from The Cancer Genome Atlas (TCGA) was used for bioinformatic analysis. Epithelial ovarian cancer cell lines SKOV3 and A2780 were used as in vitro and in vivo cell models. Commercial human ovarian cancer tissue arrays were used for immunohistochemistry staining.

Results

KIF20A is a biomarker of poor prognosis among the kinesin genes. It promotes ovarian cancer cell growth in vitro and in vivo. Ginsenoside Rg3 can suppress the transcription of KIF20A. GST pull-down and co-immunoprecipitation (IP) assays confirmed that KIF20A physically interacts with BTRC (β-TrCP1), a substrate recognition subunit for SCFβ-TrCP E3 ubiquitin ligase. In vitro ubiquitination and cycloheximide (CHX) chase assays showed that via interacting with BTRC, KIF20A reduces BTRC-mediated CDC25A poly-ubiquitination and enhances its stability. Ginsenoside Rg3 treatment partly abrogates KIF20A overexpression-induced CDC25A upregulation.

Conclusion

This study revealed a novel anti-tumor mechanism of ginsenoside Rg3. It can inhibit KIF20A transcription and promote CDC25A proteasomal degradation in epithelial ovarian cancer.

Circ_0084188 Regulates the progression of colorectal cancer through the miR-769-5p/KIF20A axis

BACKGROUND

Colorectal cancer (CRC) is one of the major gastrointestinal malignancies threatening human health. More and more studies indicate that circular RNAs (circRNAs) are important regulatory factors of CRC, but the mechanism is still indistinct.

METHODS

Quantitative real-time polymerase chain reaction (qRT-PCR) and Western blot were used to detect the expression of circ_0084188, microRNA-769-5p (miR-769-5p), and kinesin family member 20A (KIF20A) in CRC tissues. Kaplan-Meier curve was used to analyze the relationship between circ_0084188 expression and the survival rate of CRC patients. Cell proliferation, viability, apoptosis, migration, and invasion were analyzed by 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT), 5-ethynyl-2'-deoxyuridine (EdU), flow cytometry, wound-healing, and transwell assays, respectively. The relationship between miR-769-5p and circ_0084188 or KIF20A was detected by a dual-luciferase reporter and RNA pull-down. The effect of circ_0084188 on tumor growth was verified by xenograft studies in vivo.

RESULTS

Circ_0084188 and KIF20A were upregulated and miR-769-5p was downregulated in CRC. Circ_0084188 knockdown repressed the proliferation, migration, and invasion of CRC cells, as well as enhanced apoptosis in vitro. Mechanistically, circ_0084188 targeted miR-769-5p, and the reduction of miR-769-5p reversed the effects of circ_0084188 knockdown on cell functional behaviors. KLF20A was a direct miR-769-5p target, and circ_0084188 acted as a sponge for miR-769-5p to regulate the KIF20A level. Moreover, miR-769-5p regulated the functional behaviors of CRC cells by targeting KIF20A. In addition, circ_0084188 knockdown confined the growth of xenograft tumors in vivo.

CONCLUSION

Circ_0084188 upregulated the expression of KIF20A to promote the tumorigenesis of CRC through miR-769-5p, providing a new therapeutic target for CRC.

Nucleotide-free structures of KIF20A illuminate atypical mechanochemistry in this kinesin-6

KIF20A is a critical kinesin for cell division and a promising anti-cancer drug target. The mechanisms underlying its cellular roles remain elusive. Interestingly, unusual coupling between the nucleotide- and microtubule-binding sites of this kinesin-6 has been reported, but little is known about how its divergent sequence leads to atypical motility properties. We present here the first high-resolution structure of its motor domain that delineates the highly unusual structural features of this motor, including a long L6 insertion that integrates into the core of the motor domain and that drastically affects allostery and ATPase activity. Together with the high-resolution cryo-electron microscopy microtubule-bound KIF20A structure that reveals the microtubule-binding interface, we dissect the peculiarities of the KIF20A sequence that influence its mechanochemistry, leading to low motility compared to other kinesins. Structural and functional insights from the KIF20A pre-power stroke conformation highlight the role of extended insertions in shaping the motor's mechanochemical cycle. Essential for force production and processivity is the length of the neck linker in kinesins. We highlight here the role of the sequence preceding the neck linker in controlling its backward docking and show that a neck linker four times longer than that in kinesin-1 is required for the activity of this motor.

KIF20A as a potential biomarker of renal and bladder cancers based on bioinformatics and experimental verification

BACKGROUND

Bladder cancer (BC) is a malignant tumor that occurs in the bladder wall and often appears in elderly individuals. Renal cancer (RC) arises from the renal tubular epithelium, but its molecular mechanism remains unclear.

METHODS

We downloaded RC datasets (GSE14762 and GSE53757) and a BC dataset (GSE121711) to screen differentially expressed genes (DEGs). We also performed weighted gene coexpression network analysis (WGCNA). We created a protein-protein interaction (PPI) network and performed functional enrichment analysis, such as gene set enrichment analysis (GSEA). Heatmaps were made for gene expression. Survival analysis and immunoinfiltration analysis were performed. Comparative toxicogenomics database (CTD) analysis was performed to find the relationship between disease and hub genes. Western blotting was performed to verify the role of KIF20A in apoptosis.

RESULTS

A total of 764 DEGs were identified. The GSEA showed that the DEGs were mainly enriched in organic acid metabolism, drug metabolism, mitochondria, and metabolism of cysteine and methionine. The PPI network in GSE121711 showed that KIF20A was a hub gene of renal clear cell carcinoma. Where the expression level of KIF20A was higher, the prognosis of patients was worse. CTD analysis showed that KIF20A was associated with inflammation, proliferation, and apoptosis. KIF20A expression in the RC group was upregulated, as shown by western blotting. The core proteins (including pRB Ser 780, CyclinA, E2F1, CCNE1, and CCNE2) in the pRB Ser 780/CyclinA signaling pathway were also upregulated in the RC group.

CONCLUSIONS

KIF20A might be a novel biomarker for researching renal and bladder cancers.

Expression, regulating mechanism and therapeutic target of KIF20A in multiple cancer

Kinesin family member 20A (KIF20A) is a member of the kinesin family. It transports chromosomes during mitosis, plays a key role in cell division. Recently, studies proved that KIF20A was highly expressed in cancer. High expression of KIF20A was correlated with poor overall survival (OS). In this review, we summarized all the cancer that highly expressed KIF20A, described the role of KIF20A in cancer. We also organized phase I and phase II clinical trials of KIF20A peptides vaccine. All results indicated that KIF20A was a promising therapeutic target for multiple cancer.

High expression of KIF20A in bladder cancer as a potential prognostic target for poor survival of renal cell carcinoma

Urinary system tumors are malignant tumors, including renal cancer and bladder cancer. however, molecular target of them remains unclear. GSE14762 and GSE53757 were downloaded from GEO database to screen differentially expressed genes (DEGs). Weighted gene co-expression network analysis was performed. Gene Ontology (GO) and Kyoto encyclopedia of genes and genomes were used for enrichment analysis. Gene ontology and Kyoto encyclopedia of genes and genomes analyses were performed on whole genome, as formulated by gene set enrichment analysis. Survival analysis was also performed. Comparative toxicogenomics database was used to identify diseases most associated with hub genes. A total of 1517 DEGs were identified. DEGs were mainly enriched in cancer pathway, HIF-1 signaling pathway, organic acid metabolism, glyoxylate and dicarboxylate metabolism, and protein homodimerization activity. Ten hub genes (TPX2, ASPM, NUSAP1, RAD51AP1, CCNA2, TTK, PBK, MELK, DTL, kinesin family member 20A [KIF20A]) were obtained, which were up-regulated in tumor tissue. The expression of KIF20A was related with the overall survival of renal and bladder cancer. KIF20A was up-regulated in the tumor tissue, and might worsen the overall survival of bladder and kidney cancer. KIF20A could be a novel biomarker of bladder and kidney cancer.

An evaluation of KIF20A as a prognostic factor and therapeutic target for lung adenocarcinoma using integrated bioinformatics analysis

The identification of prognostic and therapeutic biomarkers is essential to reduce morbidity and mortality from lung adenocarcinoma (LUAD). This study aimed to identify a reliable prognostic and therapeutic biomarker for LUAD using integrated bioinformatics. Based on the cancer genome atlas (TCGA) and genome-tissue expression (GTEx) analyses, KIF20A has been identified as the hub gene. Following validation using a series of cohorts, survival analysis, meta-analysis, and univariate Cox analysis was conducted. ESTIMATE and CIBERSORT algorithms were then used to study the association of KIF20A with the tumor microenvironment (TME) and the percentage of tumor-infiltrating immune cells (TICs). In vitro experiments were conducted to determine the function of KIF20A. Finally, there was a negative association between the expression of the KIF20A and overall survival, progression-free survival, and disease-free survival, which was confirmed by meta-analysis and COX analysis. Furthermore, KIF20A also had a potential role of altering the TME and TICs proportions in LUAD. Validations in vitro were performed on A549 and PC-9 cell lines, and we found that the knockdown of KIF20A exhibited inhibitory effects on cell proliferation, resulted in cell cycle arrest during the G2/M phase, and induced cellular apoptosis. Our study demonstrated that KIF20A could be utilized as a reliable prognostic marker and treatment target for LUAD. However, further studies are required to validate these findings.

Integrated Analysis of Transcriptome Data Revealed AURKA and KIF20A as Critical Genes in Medulloblastoma Progression

Medulloblastoma is the neuroepithelial tumor with the highest degree of malignancy in the central nervous system, accounting for about 8% to 10% of children’s brain tumors. It has a high degree of malignancy and is easily transmitted through cerebrospinal fluid, with a relatively poor prognosis. Although medulloblastoma has been widely studied and treated, its molecular mechanism remains unclear. To determine which gene plays a crucial role in medulloblastoma development and progression, we analyzed three microarray datasets from Gene Expression Omnibus. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes were used to detect and evaluate differentially expressed genes. Protein interaction network was established, and the hub genes were determined in cytoHubba through various assessment methods, while the target genes were screened out using survival analysis. Ultimately, human medulloblastoma samples were utilized to confirm target gene expression. In conclusion, This study found that aurora kinase A (AURKA) and kinesin family member 20A (KIF20A) may be involved in the initiation and development of medulloblastoma, have a close association with prognosis, and may become a potential therapeutic target and prognostic marker of MED.

LncRNA ARAP1-AS1 Promotes Bladder Cancer Development by Regulating the miR-3918/KIF20A Axis

This study is to clarify the effect of the long non-coding RNA ArfGAP with RhoGAP domain, ankyrin repeat and PH domain 1-antisense RNA 1 (ARAP1-AS1)/microRNA (miR)-3918/kinesin family member 20A (KIF20A) on bladder cancer cell function. ARAP1-AS1, miR-3918, and KIF20A expression levels in bladder cancer cells were determined using quantitative reverse transcription-polymerase chain reaction. The effects of ARAP1-AS1, miR-3918, and KIF20A on bladder cell activity, proliferation, apoptosis, and in vivo growth were examined using the cell counting kit-8, colony formation, caspase-3 activity, and xenograft tumor growth assays, respectively, in nude mice. The binding relationships among ARAP1-AS1, miR-3918, and KIF20A were analyzed using luciferase and RNA immunoprecipitation assays. ARAP1-AS1 and KIF20A were overexpressed in bladder cancer, while miR-3918 was underexpressed. The downregulation of ARAP1-AS1 or KIF20A expression significantly inhibited the viability and proliferation of cancer cells and promoted apoptosis, whereas low expression of miR-3918 or high expression of ARAP1-AS1/KIF20A showed the opposite effect. miR-3918 was sponged by ARAP1-AS1, and targeted KIF20A. In addition, miR-3918 expression was inversely correlated with ARAP1-AS1 and KIF20a expression levels in bladder cancer tissues. In addition, the rescue experiment showed that interference with miR-3918 could reverse the effect of low ARAP1-AS1 or KIF20A expression on bladder cancer cell malignancy. ARAP1-AS1 facilitates the malignant behavior of bladder cancer cells via the regulation of KIF20A expression by sponging miR-3918.

The kinesin KIF20A promotes progression to castration-resistant prostate cancer through autocrine activation of the androgen receptor

Prostate cancer that recurs following androgen-deprivation therapy is termed castration-resistant, which is incurable and is marked by reactivation of androgen receptor (AR) signaling. KIF20A, a kinesin with unique structural features, is overexpressed in human castration-resistant prostate cancer (CRPC) compared to androgen-dependent PC and benign tissue. KIF20A has well-described roles in mitotic processes, but it has a less characterized function in vesicle fission and trafficking within Golgi-driven secretory pathways. Stable expression of KIF20A in androgen-dependent PC cells promoted progression to CRPC through the activation of AR signaling in vitro and in vivo. KIF20A expression resulted in the secretion of autocrine factors in the conditioned media that activated AR and caused castration-resistant proliferation of naïve androgen-dependent cells. Pharmacologic disruption of vesicle biogenesis blocked KIF20A-driven castration-resistant proliferation of androgen-dependent PC. KIF20A depletion or treatment with the KIF20A-specific inhibitor, paprotrain, reduced CRPC. These data are the first to establish KIF20A as a driver of CRPC progression through AR activation and as a promising therapeutic target against CRPC.

Identifying Mitotic Kinesins as Potential Prognostic Biomarkers in Ovarian Cancer Using Bioinformatic Analyses

Ovarian cancer (OC) is characterized by late-stage presentation, chemoresistance, and poor survival. Evaluating the prognosis of OC patients via effective biomarkers is essential to manage OC progression and to improve survival; however, it has been barely established. Here, we intend to identify differentially expressed genes (DEGs) as potential prognostic biomarkers of OC via bioinformatic analyses. Initially, a total of thirteen DEGs were extracted from different public databases as candidates. The expression of KIF20A, one of the DEGs, was correlated with a worse outcome of OC patients. The functional correlation of the DEGs with mitosis and the prognostic value of KIF20A imply a high correlation between mitotic kinesins (KIFs) and OC development. Finally, we found that KIF20A, together with the other nine mitotic KIFs (4A, 11, 14, 15, 18A, 18B, 23, C1, and2C) were upregulated and activated in OC tissues. Among the ten, seven overexpressed mitotic KIFs (11, 14, 18B, 20A, 23, and C1) were correlated with unfavorable clinical prognosis. Moreover, KIF20A and KIF23 overexpression was associated with worse prognosis in OC patients treated with platinum/taxol chemotherapy, while OCs overexpressing mitotic KIFs (11, 15, 18B, and C1) were resistant to MAPK pathway inhibitors. In conclusion, worse outcomes of OC patients were correlated with overexpression of several mitotic KIFs, which may serve both as prognostic biomarkers and therapeutic targets for OC.

Identification of Prognostic Signature and Gliclazide as Candidate Drugs in Lung Adenocarcinoma

Background

Lung adenocarcinoma (LUAD) is the most common pathological type of lung cancer, with high incidence and mortality. To improve the curative effect and prolong the survival of patients, it is necessary to find new biomarkers to accurately predict the prognosis of patients and explore new strategy to treat high-risk LUAD.

Methods

A comprehensive genome-wide profiling analysis was conducted using a retrospective pool of LUAD patient data from the previous datasets of Gene Expression Omnibus (GEO) including GSE18842, GSE19188, GSE40791 and GSE50081 and The Cancer Genome Atlas (TCGA). Differential gene analysis and Cox proportional hazard model were used to identify differentially expressed genes with survival significance as candidate prognostic genes. The Kaplan–Meier with log-rank test was used to assess survival difference. A risk score model was developed and validated using TCGA-LUAD and GSE50081. Additionally, The Connectivity Map (CMAP) was used to predict drugs for the treatment of LUAD. The anti-cancer effect and mechanism of its candidate drugs were studied in LUAD cell lines.

Results

We identified a 5-gene signature (KIF20A, KLF4, KRT6A, LIFR and RGS13). Risk Score (RS) based on 5-gene signature was significantly associated with overall survival (OS). Nomogram combining RS with clinical pathology parameters could potently predict the prognosis of patients with LUAD. Moreover, gliclazide was identified as a candidate drug for the treatment of high-RS LUAD. Finally, gliclazide was shown to induce cell cycle arrest and apoptosis in LUAD cells possibly by targeting CCNB1, CCNB2, CDK1 and AURKA.

Conclusion

This study identified a 5-gene signature that can predict the prognosis of patients with LUAD, and Gliclazide as a potential therapeutic drug for LUAD. It provides a new direction for the prognosis and treatment of patients with LUAD.

A novel 10 glycolysis-related genes signature could predict overall survival for clear cell renal cell carcinoma

Background

The role of glycolysis in tumorigenesis has received increasing attention and multiple glycolysis-related genes (GRGs) have been proven to be associated with tumor metastasis. Hence, we aimed to construct a prognostic signature based on GRGs for clear cell renal cell carcinoma (ccRCC) and to explore its relationships with immune infiltration.

Methods

Clinical information and RNA-sequencing data of ccRCC were obtained from The Cancer Genome Atlas (TCGA) and ArrayExpress datasets. Key GRGs were finally selected through univariate COX, LASSO and multivariate COX regression analyses. External and internal verifications were further carried out to verify our established signature.

Results

Finally, 10 GRGs including ANKZF1, CD44, CHST6, HS6ST2, IDUA, KIF20A, NDST3, PLOD2, VCAN, FBP1 were selected out and utilized to establish a novel signature. Compared with the low-risk group, ccRCC patients in high-risk groups showed a lower overall survival (OS) rate (P = 5.548Ee-13) and its AUCs based on our established signature were all above 0.70. Univariate/multivariate Cox regression analyses further proved that this signature could serve as an independent prognostic factor (all P < 0.05). Moreover, prognostic nomograms were also created to find out the associations between the established signature, clinical factors and OS for ccRCC in both the TCGA and ArrayExpress cohorts. All results remained consistent after external and internal verification. Besides, nine out of 21 tumor-infiltrating immune cells (TIICs) were highly related to high- and low- risk ccRCC patients stratified by our established signature.

Conclusions

A novel signature based on 10 prognostic GRGs was successfully established and verified externally and internally for predicting OS of ccRCC, helping clinicians better and more intuitively predict patients’ survival.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12885-021-08111-0.

Bioinformatics analysis identified hub genes in prostate cancer tumorigenesis and metastasis

OBJECTIVE

Prostate cancer (PCa) is the most frequent cancer found in males worldwide, and its mortality rate is increasing every year. To discover key molecular changes in PCa development and metastasis, we analyzed microarray data of localized PCa, metastatic PCa and normal prostate tissue samples from clinical specimens.

METHODS

Gene expression profiling datasets of PCa were analyzed online. The DAVID was used to perform GO functional and KEGG pathway enrichment analyses. CytoHubba in Cytoscape software was applied to identify hub genes. Survival data were downloaded from GEPIA. Gene expression data were obtained from ONCOMINE and UALCAN.

RESULTS

We obtained 4 sets of differentially expressed genes (DEGs), DEGs 1: a comparison of the gene expression between 4 normal prostate and 5 localized PCa samples in GSE27616; DEGs 2: a comparison of the gene expression between 6 normal prostate and 7 localized PCa samples in GSE3325; DEGs 3: a comparison of the gene expression between 5 localized PCa and 4 metastatic PCa samples in GSE27616; DEGs 4: a comparison of the gene expression between 7 localized PCa and 6 metastatic PCa samples in GSE3325. A comparison of these 4 sets of genes revealed 51 overlapped genes. GO function analysis revealed enrichment of the 51 DEGs in functions related to the proteinaceous extracellular matrix and centrosome, protein homodimerization activity and chromatin binding were the main functions of these genes, which participated in regulating cell division, mitotic nuclear division, proteinaceous extracellular matrix, cell adhesion and apoptotic process. KEGG pathway analysis indicated that these identified DEGs were mainly enriched in progesterone-mediated oocyte maturation, oocyte meiosis and cell cycle. We defined the 16 genes with the highest degree of connectivity as the hub genes in the 51 overlapped DEGs. Cox regression revealed TOP2A, CCNB2, BUB1, CDK1 and EZH2 were related to Disease-free survival (DFS). The expression levels of the 5 genes were 2.232-, 1.786-, 2.303-, 1.699-, and 1.986-fold higher in PCa than the levels in normal tissues, respectively (P < 0.05). We obtained 20 hub genes from DEGs by the comparison of normal prostate tissue vs. localized cancer tissue. Among them, KIF20A, CDKN3, PBK and CDCA2, were expressed higher in PCa than in normal tissues, and were associated with the DFS of PCa patients. Meanwhile, we obtained 20 hub genes from DEGs by the comparison of localized cancer tissue vs. metastatic cancer tissue. Cox regression revealed PLK1, CCNA2 and CDC20, were associated with both the DFS and overall survival of PCa patients.

CONCLUSIONS

The results suggested that the functions of KIF20A, CDKN3, PBK and CDCA2 may contribute to PCa development and the functions of PLK1, CCNA2 and CDC20 may contribute to PCa metastasis. Meanwhile, the functions of TOP2A, CCNB2, BUB1, CDK1 and EZH2 may contribute to both PCa development and metastasis.

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.

Molecular MR Imaging of Prostate Cancer

This review summarizes recent developments regarding molecular imaging markers for magnetic resonance imaging (MRI) of prostate cancer (PCa). Currently, the clinical standard includes MR imaging using unspecific gadolinium-based contrast agents. Specific molecular probes for the diagnosis of PCa could improve the molecular characterization of the tumor in a non-invasive examination. Furthermore, molecular probes could enable targeted therapies to suppress tumor growth or reduce the tumor size.

Analysis of Hub Genes Involved in Distinction Between Aged and Fetal Bone Marrow Mesenchymal Stem Cells by Robust Rank Aggregation and Multiple Functional Annotation Methods

Stem cells from fetal tissue protect against aging and possess greater proliferative capacity than their adult counterparts. These cells can more readily expand in vitro and senesce later in culture. However, the underlying molecular mechanisms for these differences are still not fully understood. In this study, we used a robust rank aggregation (RRA) method to discover robust differentially expressed genes (DEGs) between fetal bone marrow mesenchymal stem cells (fMSCs) and aged adult bone marrow mesenchymal stem cells (aMSCs). Multiple methods, including gene set enrichment analysis (GSEA), Gene Ontology (GO) analysis, and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis were performed for functional annotation of the robust DEGs, and the results were visualized using the R software. The hub genes and other genes with which they interacted directly were detected by protein–protein interaction (PPI) network analysis. Correlation of gene expression was measured by Pearson correlation coefficient. A total of 388 up-regulated and 289 down-regulated DEGs were identified between aMSCs and fMSCs. We found that the down-regulated genes were mainly involved in the cell cycle, telomerase activity, and stem cell proliferation. The up-regulated DEGs were associated with cell adhesion molecules, extracellular matrix (ECM)–receptor interactions, and the immune response. We screened out four hub genes, MYC, KIF20A, HLA-DRA, and HLA-DPA1, through PPI-network analysis. The MYC gene was negatively correlated with TXNIP, an age-related gene, and KIF20A was extensively involved in the cell cycle. The results suggested that MSCs derived from the bone marrow of an elderly donor present a pro-inflammatory phenotype compared with that of fMSCs, and the HLA-DRA and HLA-DPA1 genes are related to the immune response. These findings provide new insights into the differences between aMSCs and fMSCs and may suggest novel strategies for ex vivo expansion and application of adult MSCs.

Upregulation of KIF20A promotes tumor proliferation and invasion in renal clear cell carcinoma and is associated with adverse clinical outcome

Extensive research has revealed the pivotal role of kinesin family member 20A (KIF20A) in cancer. However, its latent involvement in renal clear cell carcinoma (ccRCC) still remains unclear. Thus, here we explored the role of KIF20A in ccRCC. For this, a series of software including R (v. 3.6.1), SPSS (v. 23), ImageJ and FlowJo were used for the analyses. Open-access data were obtained from The Cancer Genome Atlas (TCGA), International Cancer Genome Consortium (ICGC) and Gene Expression Omnibus (GEO) databases. Weighted Gene Co-expression Network Analysis (WGCNA) was used for module gene identification. In vitro results indicated that KIF20A expression is up-regulated in ccRCC tissue. KIF20A knockdown was able to inhibite cell proliferation and invasion of kidney A498 and Caki-1 cells. Meanwhile, KIF20A showed a strong association with immune infiltration. Particularly, KIF20A had a strong positive correlation with Th2 cells, Treg cells and Macrophages, but a negative correlation with Th17 cells, Mast cells and NK cells. These correlations may suggest the use of KIF20A as an underlying immunotherapy target in ccRCC. Our data indicated that KIF20A may promote cell invasion and proliferation in ccRCC, thus serving as an independent tumor marker and a putative therapeutic target.

FOXM1 modulates docetaxel resistance in prostate cancer by regulating KIF20A

Background

Docetaxel resistance affects prognosis in advanced prostate cancer (PCa). The precise mechanisms remain unclear. Transcription factor Forkhead box M1 (FOXM1), which participates in cell proliferation and cell cycle progression, has been reported to affect the sensitivity of chemotherapy. This study explores the role of FOXM1 in PCa docetaxel resistance and its association with kinesin family member 20 A (KIF20A), which is known to promote therapeutic resistance in some cancers.

Methods

We monitored cell growth using MTT and colony formation assays, and cell apoptosis and cell cycle progression using flow cytometry. Wound-healing and transwell assays were used to detect cell invasion and migration. mRNA and protein expression were analyzed using quantitative reverse transcription polymerase chain reaction (qRT-PCR) and western blotting. We monitored FOXM1 binding to the KIF20A promoter using a ChIP assay. Tumorigenicity in nude mice was used to assess in vivo tumorigenicity.

Results

FOXM1 knockdown induced cell apoptosis and G2/M cell cycle arrest, suppressing cell migration and invasion in docetaxel-resistant PCa cell lines (DU145-DR and VCaP-DR). Exogenous FOXM1 overexpression was found in their parental cells. Specific FOXM1 inhibitor thiostrepton significantly weakened docetaxel resistance in vitro and in vivo. We also found that FOXM1 and KIF20A exhibited consistent and highly correlated overexpression in PCa cells and tissues. FOXM1 also regulated KIF20A expression at the transcriptional level by acting directly on a Forkhead response element (FHRE) in its promoter. KIF20A overexpression could partially reverse the effect on cell proliferation, cell cycle proteins (cyclinA2, cyclinD1 and cyclinE1) and apoptosis protein (bcl-2 and PARP) of FOXM1 depletion.

Conclusions

Our findings indicate that highly expressed FOXM1 may help promote docetaxel resistance by inducing KIF20A expression, providing insight into novel chemotherapeutic strategies for combatting PCa docetaxel resistance.

A novel DNA methylation 10-CpG prognostic signature of disease-free survival reveal that MYBL2 is associated with high risk in prostate cancer

BACKGROUND

Prostate cancer (PC) is the most common non-cutaneous malignancy among men in the western world. However, heterogeneity remains a pressing clinical problem.

RESEARCH DESIGN AND METHODS

The least absolute shrinkage and selection operator (LASSO) was used to screen the prognostic signature. Weighted correlation network analysis (WGCNA) was used to identify the target genes associated with high-risk characteristics. Gene set enrichment analysis was used to suggest the molecular mechanism of MYBL2 in PC. In addition, in vitro experiments were carried out to validate the role of MYBL2 in PC.

RESULTS

Ten DNA methylation sites were selected as the prognostic signature. A high expression of MYBL2 was associated with a poor prognosis in PC patients. The effect of MYBL2 in PC was related to KRAS, AKT, IL21, and ATM. MYBL2 facilitates the proliferation, migration, invasion, and metastasis of PC cells.

CONCLUSIONS

We developed a DNA methylation 10-CpG prognostic signature to predict the prognosis of PC patients. And the high expression of MYBL2 in PC may be related to poor prognosis.

Characterization of KIF20A as a prognostic biomarker and therapeutic target for different subtypes of breast cancer

The aim of the present study was to identify novel prognostic biomarkers and therapeutic targets for breast cancer; thus, genes that are frequently overexpressed in several types of breast cancer were screened. Kinesin family member 20A (KIF20A) was identified as a candidate molecule during this process. Immunohistochemical staining performed using tissue microarrays from 257 samples of different breast cancer subtypes revealed that KIF20A was expressed in 195 (75.9%) of these samples, whereas it was seldom expressed in normal breast tissue. KIF20A protein was expressed in all types of breast cancer observed. However, it was more frequently expressed in human epidermal growth factor receptor 2 (HER2)‑positive and triple‑negative breast cancer than in the luminal type. Moreover, KIF20A expression was significantly associated with the poor prognosis of patients with breast cancer. A multivariate analysis indicated that KIF20A expression was an independent prognostic factor for patients with breast cancer. The suppression of endogenous KIF20A expression using small interfering ribonucleic acids or via treatment with paprotrain, a selective inhibitor of KIF20A, significantly inhibited breast cancer cell growth through cell cycle arrest at the G2/M phase and subsequent mitotic cell death. These results suggest that KIF20A is a candidate prognostic biomarker and therapeutic target for different types of breast cancer.