KIF11 Functions as an Oncogene and Is Associated with Poor Outcomes from Breast Cancer

Kinesin 26B modulates M2 polarization of macrophage by activating cancer-associated fibroblasts to aggravate gastric cancer occurrence and metastasis

BACKGROUND

The regulatory effects of KIF26B on gastric cancer (GC) have been confirmed, but the specific mechanism still needs further exploration. Pan-cancer analysis shows that the KIF26B expression is highly related to immune infiltration of cancer-associated fibroblasts (CAFs), and CAFs promote macrophage M2 polarization and affect cancers' progression.

AIM

To investigate the regulatory functions of KIF26B on immune and metastasis of GC.

METHODS

We analyzed genes' mRNA levels by quantitative real-time polymerase chain reaction. Expression levels of target proteins were detected by immunohistochemistry, ELISA, and Western blotting. We injected AGS cells into nude mice for the establishment of a xenograft tumor model and observed the occurrence and metastasis of GC. The degree of inflammatory infiltration in pulmonary nodes was observed through hematoxylin-eosin staining. Transwell and wound healing assays were performed for the evaluation of cell invasion and migration ability. Tube formation assay was used for detecting angiogenesis. M2-polarized macrophages were estimated by immunofluorescence and flow cytometry.

RESULTS

KIF26B was significantly overexpressed in cells and tissues of GC, and the higher expression of KIF26B was related to GC metastasis and prognosis. According to in vivo experiments, KIF26B promoted tumor formation and metastasis of GC. KIF26B expression was positively associated with CAFs' degree of infiltration. Moreover, CAFs could regulate M2-type polarization of macrophages, affecting GC cells' migration, angiogenesis, invasion, and epithelial-mesenchymal transition process.

CONCLUSION

KIF26B regulated M2 polarization of macrophage through activating CAFs, regulating the occurrence and metastasis of GC.

Mitotic Functions and Characters of KIF11 in Cancers

Mitosis mediates the accurate separation of daughter cells, and abnormalities are closely related to cancer progression. KIF11, a member of the kinesin family, plays a vital role in the formation and maintenance of the mitotic spindle. Recently, an increasing quantity of data have demonstrated the upregulated expression of KIF11 in various cancers, promoting the emergence and progression of cancers. This suggests the great potential of KIF11 as a prognostic biomarker and therapeutic target. However, the molecular mechanisms of KIF11 in cancers have not been systematically summarized. Therefore, we first discuss the functions of the protein encoded by KIF11 during mitosis and connect the abnormal expression of KIF11 with its clinical significance. Then, we elucidate the mechanism of KIF11 to promote various hallmarks of cancers. Finally, we provide an overview of KIF11 inhibitors and outline areas for future work.

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).

Protooncogenic Role of ARHGAP11A and ARHGAP11B in Invasive Ductal Carcinoma: Two Promising Breast Cancer Biomarkers

Invasive duct carcinoma (IDC) is one of the most common types of breast cancer (BC) in women worldwide, with a high risk of malignancy, metastasis, recurrence, and death. So far, molecular patterns among IDC cases have not been fully defined. However, extensive evidence has shown that dysregulated Rho family small GTPases (Rho GTPases) including Rho GTPase activating proteins (RhoGAPs) have important roles in the invasive features of IDCs. In the current study, we analyzed the expression levels of two RhoGAP genes, ARHGAP11A and ARHGAP11B, in The Cancer Genome Atlas (TCGA) breast cancer (BRCA) and also our 51 IDC tumors compared to their matched normal tissues using quantitative polymerase chain reaction (qPCR). Our TCGA data analysis revealed higher expression of ARHGAP11A and ARHGAP11B in various cancers comprising BCs. Also, we found correlations between these genes and other genes in TCGA-BRCA. Moreover, our methylation analysis showed that their promotor methylation had a negative correlation with their overexpression. QPCR revealed their significant upregulation in our tumor samples. Furthermore, we found that the expression level of ARHGAP11A was considerably lower in women who were breastfeeding. Moreover, it had overexpression in cases who had regular menstrual cycles and early age (younger than 14) at menarche. However, ARHGAP11B had a higher expression in HER2-positive tumors versus HER2-positive and ER-positive tumors. Our study found possible protooncogenic roles for these genes and their involvement in IDC pathogenesis and malignancy. Therefore, they can be considered novel prognostic and diagnostic biomarkers for IDC.

KIF11 serves as a cell cycle mediator in childhood acute lymphoblastic leukemia

OBJECTIVE

To identify key gene in childhood acute lymphoblastic leukemia (ALL) through weighted gene co-expression network analysis (WGCNA), and their enriched biological functions and signaling pathways.

METHODS

Array data of the GSE73578 dataset, involving 46 childhood ALL samples, were acquired from the Gene Expression Omnibus (GEO) database. Hub modules associated with childhood ALL were screened out by WGCNA. Enriched biological functions and signaling pathways were then identified by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG). Hub genes were selected by overlapping those between down-regulated genes in GSE73578, GSE4698 and the hub module. Guilt by association (GBA) was adopted to verify the function of the identified KIF11 gene and to predict its target genes. Regulatory effects of KIF11 on the proliferation and cell cycle progression of ALL in vitro were determined by cytological experiments.

RESULTS

WGCNA showed that the yellow module was the most relevant to childhood ALL treatment, containing 698 genes that were enriched in cell division, mitotic nuclear division, DNA replication and DNA repair, cell cycle, DNA replication and the P53 signaling pathway. The KIF11 gene was screened out and predicted as a cell cycle mediator in childhood ALL. Knockdown of KIF11 in ALL cells inhibited cell proliferation and arrested cell cycle progression in G2/M phase.

CONCLUSIONS

The KIF11 gene is critical in the treatment process of childhood ALL, which is a promising therapeutic target for childhood ALL.

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

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

Transcriptomic profiles-based approach to decode the role of miR-122 in triple negative breast cancer

miR-122 has been considered both as tumor suppressor miRNA and oncomiR in breast tumor phenotypes. However, the role of miR-122 in triple-negative breast cancer (TNBC) is still unknown. In this study, the clinical value of miR-122 was used to describe the transcriptomic landscape of TNBC tumors obtained from The Cancer Genome Atlas database. Low expression levels of miR-122 were associated with poor overall survival (OS) of TNBC patients than those with higher expression levels of miR-122. We identified gene expression profiles in TNBC tumors expressed lower or higher miR-122. Gene coexpression networks analysis revealed gene modules and hub genes specific to TNBC tumors with low or high miR-122 levels. Gene ontology and KEGG pathways analysis revealed that gene modules in TNBC with gain of miR-122 were related to cell cycle and DNA repair, while in TNBC with loss of miR-122 were enriched in cell cycle, proliferation, apoptosis and activation of cell migration and invasion. The expression of hub genes distinguished TNBC tumors with gain or loss of miR-122 from normal breast tissues. Furthermore, high levels of hub genes were associated with better OS in TNBC patients. Interestingly, the gene coexpression network related to loss of miR-122 were enriched with target genes of miR-122, but this did not observed in those with gain of miR-122. Target genes of miR-122 are oncogenes mainly associated with cell differentiation-related processes. Finally, 75 genes were identified exclusively associated to loss of miR-122, which are also implicated in cell differentiation. In conclusion, miR-122 could act as tumor suppressor by controlling oncogenes in TNBC.

Comprehensive analysis of prognostic value, relationship to cell cycle, immune infiltration and m6A modification of ZSCAN20 in hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is a common tumor across the globe with a high mortality rate. ZSCAN20 is a ZNF transcription factor, a key determinant of gene expression. Nonetheless, the mechanism of ZSCAN20 as a potential clinical biomarker and therapeutic target for HCC is not understood. Here, TIMER, TCGA, ICGC databases and immunohistochemical (IHC) and Western Blot found ZSCAN20 mRNA and protein levels were upregulated. Additionally, Kaplan-Meier Plotter, GEPIA and TCGA databases showed high ZSCAN20 expression was related to the short survival time of HCC patients. Multivariate Cox analysis exposed that ZSCAN20 can act as an independent prognostic factor. We observed methylation level of ZSCAN20 was associated with the clinicopathological characteristics and prognosis of HCC patients through UALCAN. Furthermore, enrichment examination exposed functional association between ZSCAN20 and cell cycle, immune infiltration. Functional experiments showed that interference with ZSCAN20 significantly reduced the invasion, migration and proliferation abilities of HCC cells. An immune infiltration analysis showed that ZSCAN20 was associated with immune cells, particularly T cells. The expression of ZSCAN20 was correlated with poor prognosis in the Regulatory T-cell. And Real-Time RT-PCR analysis found interference with ZSCAN20 significantly reduced the expression of some chemokines. Finally, the TCGA and ICGC data analysis suggested that the ZSCAN20 expression was greatly related to m6A modifier related genes. In conclusion, ZSCAN20 can serve as a prognostic biomarker for HCC and provide clues about cell cycle, immune infiltration, and m6A modification.

Kinesin Eg5 Selective Inhibition by Newly Synthesized Molecules as an Alternative Approach to Counteract Breast Cancer Progression: An In Vitro Study

Breast cancer (BC) is one of the most diagnosed cancers in women. Recently, a promising target for BC treatment was found in kinesin Eg5, a mitotic motor protein that allows bipolar spindle formation and cell replication. Thus, the aim of this work was to evaluate the effects of novel thiadiazoline-based Eg5 inhibitors, analogs of K858, in an in vitro model of BC (MCF7 cell line). Compounds 2 and 41 were selected for their better profile as they reduce MCF7 viability at lower concentrations and with minimal effect on non-tumoral cells with respect to K858. Compounds 2 and 41 counteract MCF7 migration by negatively modulating the NF-kB/MMP-9 pathway. The expression of HIF-1α and VEGF appeared also reduced by 2 and 41 administration, thus preventing the recruitment of the molecular cascade involved in angiogenesis promotion. In addition, 2 provokes an increased caspase-3 activation thus triggering the MCF7 apoptotic event, while 41 and K858 seem to induce the necrosis axis, as disclosed by the increased expression of PARP. These results allow us to argue that 2 and 41 are able to simultaneously intervene on pivotal molecular signaling involved in breast cancer progression, leading to the assumption that Eg5 inhibition can represent a valid approach to counteract BC progression.

KIF11 manipulates SREBP2-dependent mevalonate cross talk to promote tumor progression in pancreatic ductal adenocarcinoma

Cholesterol metabolism is highly correlated with risks of pancreatic ductal adenocarcinoma (PDAC). Nevertheless, the underlying mechanisms of activation of cholesterol biogenesis remain inconclusive. KIF11 is a key component of the bipolar spindle and expresses highly in various malignancies. However, its functional role in PDAC tumorigenesis is still unclear. This study aims to elucidate the oncogenic functions of KIF11 in stimulating cholesterol metabolism, thereby driving PDAC progression. We utilized bioinformatics analysis to identify that KIF11 expressed highly in tumor samples versus paired normal tissues and high KIF11 correlated with high clinical stages of patients. Patients with high KIF11 had worse survival outcomes relative to those with low KIF11. Gene set enrichment analysis (GSEA) revealed that KIF11 correlated intensively with the mevalonate (MVA) metabolic pathway. Positive associations were observed between KIF11 and MVA-signature (HMGCR, FDFT1, SQLE, and MSMO1). KIF11 could elevate the free cholesterol content of PDAC cells and targeting MVA inhibited the in vitro growth of KIF11-overexpressing cells. Mechanistically, we found KIF11 could interact with SREBP2, the master regulator of MVA. High KIF11 could increase SREBP2 proteins, but not alter their mRNA levels. KIF11 could attenuate the ubiquitination-mediated degradation of SREBP2, thereby enhancing its stability and accumulation. Accordingly, KIF11 stimulated the expressions of MVA-signature and free cholesterol contents depending on SREBP2. In addition, KIF11 depended on SREBP2 to promote cell growth, migration, stemness, and colony formation abilities. The subcutaneous xenograft models indicated that targeting MVA biogenesis (atorvastatin) is effective to restrict the in vivo growth of KIF11high PDAC. Taken together, our study identified that KIF11 could activate the MVA cross talk to drive PDAC progression and inhibiting the KIF11/MVA axis provided a therapeutic vulnerability in the treatment of PDAC.

KIF11 Is a Promising Therapeutic Target for Thyroid Cancer Treatment

Objective. To assess KIF11 expression in human thyroid tumor tissues and further evaluate its involvement in thyroid cancer. Methods. The expression of KIF11 in 71 cases of thyroid carcinoma as well as corresponding tissues was detected by the immunohistochemical (IHC) method. Patients were divided into the high KIF11 expression as well as low expression groups based on the staining levels. In addition, to study the relationship between the expression of KIF11 as well as clinicopathological features, the effects of KIF11 were detected on the proliferation, apoptosis, and cell cycle of two types of thyroid cancer cells, TPC-1 and KTC-1, through colony formation assays, MTT assays, and FCM assays, respectively. We further assessed the potential effects of KIF11 on tumor growth using an animal model. Results. The significantly high expression of KIF11 in thyroid tumor tissues was revealed, and the correlations between KIF11 expression levels as well as clinical pathological features (T stage and intraglandular dissemination) of patients were revealed. We further noticed that KIF11 knockdown remarkably suppressed thyroid cancer cell proliferation as well as induced cell apoptosis of thyroid cancer cells. Additionally, KIF11 contributed to tumor growth of thyroid cancer cells in mice. Conclusions. We noticed the involvement of KIF11 in the progression of thyroid cancer.

Targeting kinesin family member 21B by miR-132-3p represses cell proliferation, migration and invasion in gastric cancer

Recently, kinesin family member 21B (KIF21B) has been reported to be an oncogene in non-small cell lung cancer and hepatocellular carcinoma. However, the functional role of KIF21B and related molecular mechanisms in gastric cancer (GC) remain largely uncovered. In this study, online bioinformatics analysis showed that KIF21B was overexpression in GC and predicted poor prognosis. Consistently, we found that the protein expression of KIF21B was upregulated in GC tissues compared with adjacent tissues by immunohistochemistry. Knockdown of KIF21B significantly suppressed cell proliferation, migration and invasion in GC cell lines (AGS and SNU-5) using Cell counting kit‑8 (CCK-8) assay, colony formation and transwell assay. KIF21B was confirmed as the target of miR-132-3p in GC cells by luciferase reporter assay. Moreover, miR-132-3p was down-regulated and KIF21B expression was upregulated in GC tissues. Overexpression of KIF21B reversed the miR-132-3p-mediated suppressive effects on GC cell proliferation, migration and invasion. Furthermore, miR-132-3p overexpression downregulated the protein levels of Wnt1, c-Myc, β-catenin, proliferating cell nuclear antigen (PCNA) and N-cadherin, and upregulated E-cadherin expression in GC cells, which were all alleviated after KIF21B overexpression. In conclusion, our findings indicate that down-regulation of KIF21B by miR-132-3p suppresses cellular functions in GC, which might be linked to reduced Wnt/β-catenin signaling.

Oncological drug discovery: AI meets structure-based computational research

The integration of machine learning and structure-based methods has proven valuable in the past as a way to prioritize targets and compounds in early drug discovery. In oncological research, these methods can be highly beneficial in addressing the diversity of neoplastic diseases portrayed by the different hallmarks of cancer. Here, we review six use case scenarios for integrated computational methods, namely driver prediction, computational mutagenesis, (off)-target prediction, binding site prediction, virtual screening, and allosteric modulation analysis. We address the heterogeneity of integration approaches and individual methods, while acknowledging their current limitations and highlighting their potential to bring drugs for personalized oncological therapies to the market faster.

Negative Modulation of the Angiogenic Cascade Induced by Allosteric Kinesin Eg5 Inhibitors in a Gastric Adenocarcinoma In Vitro Model

Eg5 is a kinesin essential in bipolar spindle formation, overexpressed in tumours, thus representing a new target in cancer therapy. We aimed at evaluating the anti-cancer activity of Eg5 thiadiazoline inhibitors 2 and 41 on gastric adenocarcinoma cells (AGS), focusing on the modulation of angiogenic signalling. Docking studies confirmed a similar interaction with Eg5 to that of the parent compound K858. Thiadiazolines were also tested in combination with Hesperidin (HSD). Cell cycle analysis reveals a reduction of G1 and S phase percentages when 41 is administered as well as HSD in combination with K858. Western blot reveals Eg5 inhibitors capability to reduce PI3K, p-AKT/Akt and p-Erk/Erk expressions; p-Akt/Akt ratio is even more decreased in HSD+2 sample than the p-Erk/Erk ratio in HSD+41 or K858. VEGF expression is reduced when HSD+2 and HSD+41 are administered with respect to compounds alone, after 72 h. ANGPT2 gene expression increases in cells treated with 41 and HSD+2 compared to K858. The wound-healing assay highlights a reduction in the cut in HSD+2 sample compared to 2 and HSD. Thus, Eg5 inhibitors appear to modulate angiogenic signalling by controlling VEGF activity even better if combined with HSD. Overall, Eg5 inhibitors can represent a promising starting point to develop innovative anti-cancer strategies.

Screening and predicted value of potential biomarkers for breast cancer using bioinformatics analysis

Breast cancer is the most common cancer and the leading cause of cancer-related deaths in women. Increasing molecular targets have been discovered for breast cancer prognosis and therapy. However, there is still an urgent need to identify new biomarkers. Therefore, we evaluated biomarkers that may aid the diagnosis and treatment of breast cancer. We searched three mRNA microarray datasets (GSE134359, GSE31448 and GSE42568) and identified differentially expressed genes (DEGs) by comparing tumor and non-tumor tissues using GEO2R. Functional and pathway enrichment analyses of the DEGs were performed using the DAVID database. The protein-protein interaction (PPI) network was plotted with STRING and visualized using Cytoscape. Module analysis of the PPI network was done using MCODE. The associations between the identified genes and overall survival (OS) were analyzed using an online Kaplan-Meier tool. The redundancy analysis was conducted by DepMap. Finally, we verified the screened HUB gene at the protein level. A total of 268 DEGs were identified, which were mostly enriched in cell division, cell proliferation, and signal transduction. The PPI network comprised 236 nodes and 2132 edges. Two significant modules were identified in the PPI network. Elevated expression of the genes Discs large-associated protein 5 (DLGAP5), aurora kinase A (AURKA), ubiquitin-conjugating enzyme E2 C (UBE2C), ribonucleotide reductase regulatory subunit M2(RRM2), kinesin family member 23(KIF23), kinesin family member 11(KIF11), non-structural maintenance of chromosome condensin 1 complex subunit G (NCAPG), ZW10 interactor (ZWINT), and denticleless E3 ubiquitin protein ligase homolog(DTL) are associated with poor OS of breast cancer patients. The enriched functions and pathways included cell cycle, oocyte meiosis and the p53 signaling pathway. The DEGs in breast cancer have the potential to become useful targets for the diagnosis and treatment of breast cancer.

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

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

Dauricine inhibits human pancreatic carcinoma cell proliferation through regulating miRNAs

Pancreatic cancer is one of the most malignant digestive tract tumors with the worst prognosis. Dauricine (Dau) can inhibit the proliferation of the pancreatic cancer cell line, and has the potential to be used as an adjuvant drug against pancreatic cancer; however, the working mechanism of Dau has not been elucidated. To unravel the effects and mechanisms of Dau on proteins and metabolic pathways, we evaluated the mRNA and microRNA expression in BxPC3 cells treated with Dau. The differences in the gene expression were compared using principal component analysis using mRNA and miRNA data to detect and analyze the sample discrimination. 187 miRNA and 907 mRNA that were significantly differentially expressed were identified using Python programming. On comparing genes and miRNAs in the DISEASES database, 79 known miRNA and 47 mRNA were found to be affected by Dau. The up-regulated and down-regulated genes were annotated with GO biological processes to determine the functional effect. Interactions between mRNA and mRNA were analyzed using the STRING database and the miRBase database was queried to obtain experimentally verified interactions between miRNA and mRNA as edges of miRNA and mRNA in the network. Finally, 413 sites and 2125 sides of the network were obtained, including 1 up-regulated and 18 down-regulated miRNAs. The expression of 19 miRNAs was identified by qPCR. The analysis of the protein-protein interaction network, using the Molecular Complex Detection (MCODE) plug-in of cytoscape, helped in identifying 12 important sub-networks. Most subnets are indirectly or directly related to specific miRNAs. This study provides evidence for the anticancer effect of Dau as a potential anticancer compound.

KIF11 Serves as an Independent Prognostic Factor and Therapeutic Target for Patients With Lung Adenocarcinoma

Background

Lung adenocarcinoma (LUAD) is challenging in clinical practice due to the poor understanding of molecular mechanisms and limited therapeutic targets. Herein, the work aimed to use bioinformatics to identify a promising molecular target for LUAD therapy.

Methods

Differentially expressed genes (DEGs) from the Cancer Genome Atlas (TCGA) dataset were used for a weighted gene co-expression network analysis (WGCNA) to screen the hub gene. After a prognostic estimation with meta-analysis and COX regression analysis, we performed a function analysis on the corresponding gene. The ESTIMATE and CIBERSORT methods were adopted to analyze the association of the hub gene with the tumor microenvironment (TME). A cohort of functional assays was conducted to establish the functional roles of the hub gene in A549 and PC-9 cells.

Results

Our screen identified KIF11 as a prognostic factor, which indicated the poor overall survival and the worse progression-free survival in LUAD patients. Additionally, KIF11 was primarily involved in cell cycle, TME alteration and tumor-infiltrating immune cells proportions. KIF11 knockdown exerted inhibitory effects on cell proliferation, migration, and invasion. Results of the flow cytometry analysis revealed that KIF11 knockdown induced a G2/M phase arrest and improved apoptosis in LUAD cells.

Conclusions

KIF11 is essential for LUAD cell proliferation and metastasis, and it may serve as an independent prognostic factor as well as a promising therapeutic target for LUAD patients.

Exploration and validation of a novel prognostic signature based on comprehensive bioinformatics analysis in hepatocellular carcinoma

The present study aimed to construct a novel signature for indicating the prognostic outcomes of hepatocellular carcinoma (HCC). Gene expression profiles were downloaded from Gene Expression Omnibus (GEO), The Cancer Genome Atlas (TCGA) and the International Cancer Genome Consortium (ICGC) databases. The prognosis-related genes with differential expression were identified with weighted gene co-expression network analysis (WGCNA), univariate analysis, the least absolute shrinkage and selection operator (LASSO). With the stepwise regression analysis, a risk score was constructed based on the expression levels of five genes: Risk score = (−0.7736* CCNB2) + (1.0083* DYNC1LI1) + (−0.6755* KIF11) + (0.9588* SPC25) + (1.5237* KIF18A), which can be applied as a signature for predicting the prognosis of HCC patients. The prediction capacity of the risk score for overall survival was validated with both TCGA and ICGC cohorts. The 1-, 3- and 5-year ROC curves were plotted, in which the AUC was 0.842, 0.726 and 0.699 in TCGA cohort and 0.734, 0.691 and 0.700 in ICGC cohort, respectively. Moreover, the expression levels of the five genes were determined in clinical tumor and normal specimens with immunohistochemistry. The novel signature has exhibited good prediction efficacy for the overall survival of HCC patients.

Integrative analysis of transcriptional profile reveals LINC00052 as a suppressor of breast cancer cell migration

BACKGROUND

Long-non-coding RNAs, a class of transcripts with lengths > 200 nt, play key roles in tumour progression. Previous reports revealed that LINC00052 (long intergenic non-coding RNA 00052) was strongly downregulated during breast cancer multicellular spheroids formation and suggested a role in cell migration and oxidative metabolism.

OBJECTIVE

To examine the function of LINC00052 in MCF-7 breast cancer cells.

METHODS

Loss-of-function studies were performed to evaluate LINC00052 role on MCF-7 breast cancer cells. Microarray expression assays were performed to determine genes and cellular functions modified after LINC00052 knockdown. Next, the impact of LINC00052 depletion on MCF-7 cell respiration and migration was evaluated.

RESULTS

1,081 genes were differentially expressed upon LINC00052 inhibition. Gene set enrichment analysis, Gene Ontology and Key Pathway Advisor analysis showed that signalling networks related to cell migration and oxidative phosphorylation were enriched. However, whereas LINC00052 knockdown in MCF-7 cells revealed marginal difference in oxygen consumption rates when compared with control cells, LINC00052 inhibition enhanced cell migration in vitro and in vivo, as observed using a Zebrafish embryo xenotransplant model.

CONCLUSION

Our data show that LINC00052 modulates MCF-7 cell migration. Genome-wide microarray experiments suggest that cancer cell migration is affected by LINC00052 through cytoskeleton modulation and Notch/β-catenin/NF-κB signalling pathways.

KIF11 inhibitors filanesib and ispinesib inhibit meningioma growth in vitro and in vivo

Treatment of aggressive meningiomas remains challenging due to a high rate of recurrence in higher-grade meningiomas, frequent subtotal resections, and the lack of effective systemic treatments. Substantial overexpression associated with a poor prognosis has been demonstrated for kinesin family member 11 (KIF11) in high-grade meningiomas. Due to anti-tumor activity for KIF11 inhibitors (KIF11i) filanesib and ispinesib in other cancer types, we sought to investigate their mode of action and efficacy for the treatment of aggressive meningiomas. Dose curve analysis of both KIF11i revealed IC50 values of less than 1 nM in anaplastic and benign meningioma cell lines. Both compounds induced G2/M arrest and subsequent subG1 increase in all cell lines. Profound induction of apoptosis was detected in the anaplastic cell lines determined by annexin V staining. KIF11i significantly inhibited meningioma growth in xenotransplanted mice by up to 83%. Furthermore, both drugs induced minor hematological side effects, which were less pronounced for filanesib. We identified substantial in vitro and in vivo anti-tumor effects of the KIF11 inhibitors filanesib and ispinesib, with filanesib demonstrating better tolerability, suggesting future use of filanesib for the treatment of aggressive meningioma.

Overexpression of EZH2/NSD2 Histone Methyltransferase Axis Predicts Poor Prognosis and Accelerates Tumor Progression in Triple-Negative Breast Cancer

Two histone methyltransferases, enhancer of zeste homolog 2 (EZH2) and nuclear SET domain-containing 2 (NSD2), are aberrantly expressed in several types of human cancers. However, the regulatory relationship between EZH2 and NSD2 and their prognostic values in breast cancer (BC) have not been fully elucidated. In this study, we demonstrated that EZH2 and NSD2 were overexpressed in BC compared with benign lesions and normal tissues using tissue microarray, immunohistochemistry, and bioinformatic databases. Both EZH2 and NSD2 expression were associated with pathological grade of tumor and lymph node metastasis. A comprehensive survival analysis using Kaplan-Meier Plotter database indicated that EZH2 expression was negatively correlated with relapse-free survival (RFS), overall survival (OS), distant metastasis-free survival (DMFS), and postprogression survival (PPS) in 3951 BC patients, and NSD2 expression was negatively correlated with RFS and DMFS. Notably, EZH2 and NSD2 expression were coordinately higher in triple-negative breast cancer (TNBC) than that in other subtypes. Stable knockdown of EZH2 using lentiviral shRNA vector significantly reduced the proliferation, migration and invasion abilities of TNBC cell line MDA-MB-231 and MDA-MB-468, and downregulated NSD2 expression as well as the levels of H3K27me3 and H3K36me2, two histone methylation markers catalyzed by EZH2 and NSD2, respectively. By contrast, overexpression of EZH2 using adenovirus vector displayed an inverse phenotype. Furthermore, knockdown of NSD2 in EZH2-overexpressing cells could dramatically attenuate EZH2-mediated oncogenic effects. Bioinformatic analysis further revealed the function and pathway enrichments of co-expressed genes and interactive genes of EZH2/NSD2 axis, suggesting that EZH2/NSD2 axis was associated with cell division, mitotic nuclear division and transition of mitotic cell cycle in TNBC. Taken together, EZH2/NSD2 axis may act as a predictive marker for poor prognosis and accelerate the progression of TNBC.

High KIF11 expression is associated with poor outcome of NSCLC

PURPOSE

To clarify the correlation between KIF11 (kinesin family member 11) and clinicopathologic characteristics of non-small cell lung cancer (NSCLC) and identify the prognostic value of KIF11 in patients with NSCLC.

METHODS

For investigating the expression of KIF11 in NSCLC, two tissue microarrays (TMAs: one contained 60 paired NSCLC tissues and paratumor tissues, the other contained 140 NSCLC tissues and 10 normal lung tissues) were constructed, stained, and scored. The Cancer Genome Atlas (TCGA) datasets were used to explore the differential expression level of KIF11 between NSCLC and paratumor. Kaplan-Meier survival curves were plotted and multivariate analysis were carried out.

RESULTS

The staining of KIF11 mainly distributed throughout the cytoplasm of tumor cells. Its expression was higher in NSCLC than paratumor cells, and similar results were obtained from TCGA datasets. We found that high expression of KIF11 had a significant correlation with lymph node metastases (p = 0.024) and pathologic stage (p = 0.018); that significant difference was not found in any other clinicopathologic characteristic. As univariate and multivariate analysis showed, KIF11 expression was significantly correlated with overall survival time of NSCLC (p = 0.002, p = 0.025, respectively). High KIF11 expression was found to significantly associate with overall survival of stage II-III (p = 0.001) and lung adenocarcinoma (p = 0.036).

CONCLUSION

High KIF11 expression predicts poor outcome in NSCLC. KIF11 is expected to be a viable prognostic biomarker for NSCLC.

Identification of the Hub Genes Associated with the Prognosis of Ovarian Cancer Patients via Integrated Bioinformatics Analysis and Experimental Validation

Background

This study aimed to identify the hub genes associated with prognosis of patients with ovarian cancer by using integrated bioinformatics analysis and experimental validation.

Methods

Four microarray datasets (GSE12470, GSE14407, GSE18521 and GSE46169) were analyzed by the GEO2R tool to screen common differentially expressed genes (DEGs). Gene Ontology, the Kyoto Encyclopedia of Genes and Genomes, the (KEGG) pathway and Reactome pathway enrichment analysis, protein–protein interaction (PPI) construction, and the identification of hub genes were performed. Furthermore, we performed the survival and expression analysis of the hub genes. In vitro functional assays were performed to assess the effects of hub genes on ovarian cancer cell proliferation, caspase-3/7 activity and invasion.

Results

A total of 89 common DEGs were identified among these four datasets. The KEGG and Reactome pathway results showed that the DEGs were mainly associated with cell cycle, mitotic and p53 signaling pathway. A total of 20 hub genes were identified from the PPI network by using sub-module analysis. The survival analysis revealed that high expression of six hub genes (AURKA, BUB1B, CENPF, KIF11, KIF23 and TOP2A) were significantly correlated with shorter overall survival and progression-free survival of patients with ovarian cancer. Furthermore, the expression of the six hub genes were validated by the GEPIA database and Human Protein Atlas, and functional studies revealed that knockdown of KIF11 and KIF23 suppressed the SKOV3 cell proliferation, increased caspase-3/7 activity and attenuated invasive potentials of SKOV3 cells. In addition, knockdown of KIF11 and KIF23 up-regulated E-cadherin mRNA expression but down-regulated N-cadherin and vimentin mRNA expression in SKOV3 cells.

Conclusion

Our results showed that six hub genes were up-regulated in ovarian cancer tissues and may predict poor prognosis of patients with ovarian cancer. KIF11 and KIF23 may play oncogenic roles in ovarian cancer cell progression via promoting ovarian cancer cell proliferation and invasion.

Upregulation of KIF11 in TP53 Mutant Glioma Promotes Tumor Stemness and Drug Resistance

Glioma is the most common type of primary brain malignancy with high morbidity and mortality, but little is known about its pathological mechanisms. Kinesin family member 11 (KIF11) is a key driver of malignancy in glioblastoma, a grade IV glioma, but its involvement in glioma chemoresistance remains to be determined. We accessed the TCGA open datasets, collected glioma tumor tissue samples, and analyzed the expression of KIF11 in glioma patients. Meanwhile, the correlation between KIF11 and survival outcomes was determined by the Kaplan-Meier analysis. The role of KIF11 in glioma tumor cell function was assessed in an in vitro knockdown and overexpressing system. Here, we found that KIF11 was upregulated in glioma tumors and negatively correlated with overall survival outcomes via analyzing the open datasets. KIF11 was negatively correlated with TP53 expression. Furthermore, KIF11 promoted the stemness in glioma cells, accompanied by increased cell proliferation and chemoresistance. Mechanistically, we found that KIF11 promoted cell cycle progression via upregulating cyclin expression.

Screening and identification of hub genes in bladder cancer by bioinformatics analysis and KIF11 is a potential prognostic biomarker

Bladder cancer (BC) is the ninth most common lethal malignancy worldwide. Great efforts have been devoted to clarify the pathogenesis of BC, but the underlying molecular mechanisms remain unclear. To screen for the genes associated with the progression and carcinogenesis of BC, three datasets were obtained from the Gene Expression Omnibus. A total of 37 tumor and 16 non-cancerous samples were analyzed to identify differentially expressed genes (DEGs). Subsequently, 141 genes were identified, including 55 upregulated and 86 downregulated genes. The protein-protein interaction network was established using the Search Tool for Retrieval of Interacting Genes database. Hub gene identification and module analysis were performed using Cytoscape software. Hierarchical clustering of hub genes was conducted using the University of California, Santa Cruz Cancer Genomics Browser. Among the hub genes, kinesin family member 11 (KIF11) was identified as one of the most significant prognostic biomarkers among all the candidates. The Kaplan Meier Plotter database was used for survival analysis of KIF11. The expression profile of KIF11 was analyzed using the ONCOMINE database. The expression levels of KIF11 in BC samples and bladder cells were measured using reverse transcription-quantitative pCR, immunohistochemistry and western blotting. In summary, KIF11 was significantly upregulated in BC and might act as a potential prognostic biomarker. The present identification of DEGs and hub genes in BC may provide novel insight for investigating the molecular mechanisms of BC.

KIF14 and KIF23 Promote Cell Proliferation and Chemoresistance in HCC Cells, and Predict Worse Prognosis of Patients with HCC

Background

Hepatocellular carcinoma (HCC) is one of the most common human malignant tumors. The prognosis of HCC patients is still unsatisfying. In this study, we performed the integrated bioinformatics analysis to identify potential biomarkers and biological pathways in HCC.

Methods

Gene expression profiles were obtained from the Gene Expression Omnibus database (GSE55048, GSE55758, and GSE56545) for the screening of the common differentially expressed genes (DEGs) between HCC tissues and matched non-tumor tissues. DEGs were subjected to Gene Ontology, KEGG pathway, and Reactome pathway analysis. The hub genes were identified by using protein–protein interaction (PPI) network analysis. The hub genes in HCC were further subjected to overall survival analysis of HCC patients. The hub genes were further validated by in vitro functional assays.

Results

A total of 544 common differentially expressed genes were screened from three datasets. Gene Ontology, KEGG and Reactome analysis results showed that DEGs are significantly associated with the biological process of cell cycle, cell division, and DNA replication. PPI network analysis identified 20 hub genes from the DEGs. These hub genes except CENPE were all significantly up-regulated in the HCC tissues when compared to non-tumor tissues. The Kaplan–Meier survival analysis results showed that the high expression of the 20 hub genes was associated with shorter survival of the HCC patients. Further validation studies showed that knockdown of KIF14 and KIF23 both suppressed the proliferative potential, increased the caspase-3/-7 activity, up-regulated Bax expression, and promoted the invasive and migratory abilities in the HCC cells. In addition, knockdown of KIF14 and KIF23 enhanced chemosensitivity to cisplatin and sorafenib in the HCC cells. Finally, the high expression of KIF14 and KIF23 was associated with shorter progression-free survival, recurrence-free survival, and disease-specific survival of patients with HCC.

Conclusion

In conclusion, the present study performed the integrated bioinformatics analysis and showed that KIF14 and KIF23 silence attenuated cell proliferation, invasion, and migration, and promoted chemosensitivity of HCC cells. KIF14 and KIF23 may serve as potential biomarkers for predicting the worse prognosis of patients with HCC.

Identification of Potential Hub Genes Related to Diagnosis and Prognosis of Hepatitis B Virus-Related Hepatocellular Carcinoma via Integrated Bioinformatics Analysis

Hepatocellular carcinoma (HCC) is a common malignant cancer with poor survival outcomes, and hepatitis B virus (HBV) infection is most likely to contribute to HCC. But the molecular mechanism remains obscure. Our study intended to identify the candidate potential hub genes associated with the carcinogenesis of HBV-related HCC (HBV-HCC), which may be helpful in developing novel tumor biomarkers for potential targeted therapies. Four transcriptome datasets (GSE84402, GSE25097, GSE94660, and GSE121248) were used to screen the 309 overlapping differentially expressed genes (DEGs), including 100 upregulated genes and 209 downregulated genes. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment were used to explore the biological function of DEGs. A PPI network based on the STRING database was constructed and visualized by the Cytoscape software, consisting of 209 nodes and 1676 edges. Then, we recognized 17 hub genes by CytoHubba plugin, which were further validated on additional three datasets (GSE14520, TCGA-LIHC, and ICGC-LIRI-JP). The diagnostic effectiveness of hub genes was assessed with receiver operating characteristic (ROC) analysis, and all hub genes displayed good performance in discriminating TNM stage I patient samples and normal tissue ones. For prognostic analysis, two prognostic key genes (TOP2A and KIF11) out of the 17 hub genes were screened and used to develop a prognostic signature, which showed good potential for overall survival (OS) stratification of HBV-HCC patients. Gene Set Enrichment Analysis (GSEA) was performed in order to better understand the function of this prognostic gene signature. Finally, the miRNA-mRNA regulatory relationships of all hub genes in human liver were predicted using miRNet. In conclusion, the current study gives further insight on the pathogenesis and carcinogenesis of HBV-HCC, and the identified DEGs provide a promising direction for improving the diagnostic, prognostic, and therapeutic outcomes of HBV-HCC.

Identification of candidate biomarkers correlated with the pathogenesis and prognosis of breast cancer via integrated bioinformatics analysis

BACKGROUND

This study was carried out to identify potential key genes associated with the pathogenesis and prognosis of breast cancer (BC).

METHODS

Seven GEO datasets (GSE24124, GSE32641, GSE36295, GSE42568, GSE53752, GSE70947, GSE109169) were downloaded from the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) between BC and normal breast tissue samples were screened by an integrated analysis of multiple gene expression profile datasets. Hub genes related to the pathogenesis and prognosis of BC were verified by employing protein-protein interaction (PPI) network.

RESULTS

Ten hub genes with high degree were identified, including CDK1, CDC20, CCNA2, CCNB1, CCNB2, BUB1, BUB1B, CDCA8, KIF11, and TOP2A. Lastly, the Kaplan-Meier plotter (KM plotter) online database demonstrated that higher expression levels of these genes were related to lower overall survival. Experimental validation showed that all 10 hub genes had the same expression trend as predicted.

CONCLUSION

The findings of this research would provide some directive significance for further investigating the diagnostic and prognostic biomarkers to facilitate the molecular targeting therapy of BC, which could be used as a new biomarker for diagnosis and to guide the combination medicine of BC.

Identification of Hub Genes in Anaplastic Thyroid Carcinoma: Evidence From Bioinformatics Analysis

Anaplastic thyroid carcinoma (ATC) is a rare type of thyroid cancer that results in fatal clinical outcomes; the pathogenesis of this life-threatening disease has yet to be fully elucidated. This study aims to identify the hub genes of ATC that may play key roles in ATC development and could serve as prognostic biomarkers or therapeutic targets. Two microarray datasets (GSE33630 and GSE53072) were obtained from the Gene Expression Omnibus database; these sets included 16 ATC and 49 normal thyroid samples. Differential expression analyses were performed for each dataset, and 420 genes were screened as common differentially expressed genes using the robust rank aggregation method. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analyses were conducted to explore the potential bio-functions of these differentially expressed genes (DEGs). The terms and enriched pathways were primarily associated with cell cycle, cell adhesion, and cancer-related signaling pathways. Furthermore, a protein-protein interaction network of DEG expression products was constructed using Cytoscape. Based on the whole network, we identified 7 hub genes that included CDK1, TOP2A, CDC20, KIF11, CCNA2, NUSAP1, and KIF2C. The expression levels of these hub genes were validated using quantitative polymerase chain reaction analyses of clinical specimens. In conclusion, the present study identified several key genes that are involved in ATC development and provides novel insights into the understanding of the molecular mechanisms of ATC development.

Identification of Metastasis-Associated Biomarkers in Synovial Sarcoma Using Bioinformatics Analysis

Synovial sarcoma (SS) is a highly aggressive soft tissue tumor with high risk of local recurrence and metastasis. However, the mechanisms underlying SS metastasis are still largely unclear. The purpose of this study is to screen metastasis-associated biomarkers in SS by integrated bioinformatics analysis. Two mRNA datasets (GSE40018 and GSE40021) were selected to analyze the differentially expressed genes (DEGs). Using the Database for Annotation, Visualization and Integrated Discovery (DAVID) and gene set enrichment analysis (GSEA), functional and pathway enrichment analyses were performed for DEGs. Then, the protein-protein interaction (PPI) network was constructed via the Search Tool for the Retrieval of Interacting Genes (STRING) database. The module analysis of the PPI network and hub genes validation were performed using Cytoscape software. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis of the hub genes were performed using WEB-based GEne SeT AnaLysis Toolkit (WebGestalt). The expression levels and survival analysis of hub genes were further assessed through Gene Expression Profiling Interactive Analysis (GEPIA) and the Kaplan-Meier plotter database. In total, 213 overlapping DEGs were identified, of which 109 were upregulated and 104 were downregulated. GO analysis revealed that the DEGs were predominantly involved in mitosis and cell division. KEGG pathways analysis demonstrated that most DEGs were significantly enriched in cell cycle pathway. GSEA revealed that the DEGs were mainly enriched in oocyte meiosis, cell cycle and DNA replication pathways. A key module was identified and 10 hub genes (CENPF, KIF11, KIF23, TTK, MKI67, TOP2A, CDC45, MELK, AURKB, and BUB1) were screened out. The expression and survival analysis disclosed that the 10 hub genes were upregulated in SS patients and could result in significantly reduced survival. Our study identified a series of metastasis-associated biomarkers involved in the progression of SS, and may provide novel therapeutic targets for SS metastasis.

Knockdown of Kinase Family 15 Inhibits Cancer Cell Proliferation In vitro and its Clinical Relevance in Triple-Negative Breast Cancer

PURPOSE

Breast cancer is the most prevalent malignancy and the leading cause of death among women. Triple-negative breast cancer (TNBC) is a subtype of breast cancer and shows a distinctly aggressive nature with higher rates of relapse and shorter overall survival in the metastatic setting compared to other subtypes of breast cancer. This study aimed to assess the effect of KIF15 on various clinicopathological characteristics, survival analysis, and cell proliferation in triple-negative breast cancer, which has not been reported to our knowledge.

METHODS

A total of 165 patients with triple-negative breast cancer were enrolled and clinical data were obtained, Mann-Whitney U analysis was performed to assess the correlation between the expression of KIF15 and clinical pathological characteristics of TNBC patients. Survival analysis was performed by Kaplan-Meier analysis and Log-rank test. The expression levels of KIF15 in cancer tissues and adjacent tissues were evaluated via Sign test. Lentivirus was used to down-regulate the expression of KIF15 in TNBC cells. The cell proliferation, colony formation capacity and apoptosis were examined by MTT, Giemsa staining and flow cytometry assay, respectively.

RESULTS

Our results showed that, among the 165 TNBC patients, the expression of KIF15 was positive correlation with clinicopathological features of TNBC. In addition, KIF15 low-expression group showed higher disease-free survival than KIF15 highexpression group and univariate analysis showed that KIF15 high-expression group appeared higher mortality than KIF low-expression group (P ≤ 0.05). Meanwhile, the expression levels of KIF15 in cancer tissue notably up-regulated in comparison with adjacent tissue. In vitro, knockdown of KIF15 significantly promoted cell apoptosis and suppressed cell proliferation and colony formation of TNBC cells.

CONCLUSION

By utilizing survival analysis, we found that high-expression of KIF15 in the TNBC samples were associated with poorer overall survival, while the anti-tumor effect of KIF15 knockdown was also confirmed at the cellular level in vitro. Taken together, KIF15 can be applied as a potential diagnostic and therapeutic target in TNBC.

GSG2 (Haspin) promotes development and progression of bladder cancer through targeting KIF15 (Kinase-12)

Bladder cancer is the most commonly diagnosed malignant tumor in urological system worldwide. The relationship between GSG2 and bladder cancer has not been demonstrated and remains unclear. In this study, it was demonstrated that GSG2 was up-regulated in bladder cancer tissues compared with the normal tissues and its high expression was correlated with more advanced malignant grade and lower survival rate. Further investigations indicated that the overexpression/knockdown of GSG2 could promote/inhibit proliferation, colony formation and migration of bladder cancer cells, while inhibiting/promoting cell apoptosis. Moreover, knockdown of GSG2 could also suppress tumorigenicity of bladder cancer cells in vivo. RNA-sequencing followed by Ingenuity pathway analysis (IPA) was performed for exploring downstream of GSG2 and identified KIF15 as the potential target. Furthermore, our study revealed that knockdown of KIF15 could inhibit development of bladder cancer in vitro, and alleviate the GSG2 overexpression induced promotion of bladder cancer. In conclusion, our study showed, as the first time, GSG2 as a prognostic indicator and tumor promotor for bladder cancer, whose function was carried out probably through the regulation of KIF15.

Kinesin family member 11 is a potential therapeutic target and is suppressed by microRNA-30a in breast cancer

Kinesin family member 11 (KIF11) is a plus end‐directed kinesin indispensable for the formation of the bipolar spindle in metaphase, where it objects to the action of minus end‐directed molecular motors. Here, we hypothesize that KIF11 might be a therapeutic target of breast cancer and regulated by miR‐30a. Cell Counting Kit 8 assays were used to investigate cell proliferation. Invasion assays were used to survey the motility of cells. Kaplan‐Meier and Cox proportional analyses were employed for this outcome study. The prognostic significance and performance of KIF11 were validated on 17 worldwide independent microarray datasets and two The Cancer Genome Atlas‐Breast Invasive Carcinoma sets. microRNA was predicted targeting KIF11 through sequence alignment in microRNA.org and confirmed by coexpression analysis in human breast cancer samples. Dual‐luciferase reporter assays were employed to validate the interaction between miR‐30a and KIF11 further. Higher KIF11 mRNA levels and lower miR‐30a were significantly associated with poor survival of breast cancer patients. Inhibition of KIF11 by small‐hairpin RNA significantly reduced the proliferation and invasion capabilities of the breast cancer cells. Meanwhile, downregulation of KIF11 could enhance the cytotoxicity of adriamycin in breast cancer cell lines MCF‐7 and MDA‐MB‐231. A population study also validated that chemotherapy and radiotherapy significantly improved survival in early‐stage breast cancer patients with low KIF11 expression levels. Further bioinformatics analysis demonstrated that miR‐30a could interact with KIF11 and validated by dual‐luciferase reporter assays. Therefore, KIF11 is a potential therapeutic target of breast cancer. miR‐30a could specifically interact with KIF11 and suppress its expression in breast cancer.

Development and validation of a five-gene model to predict postoperative brain metastasis in operable lung adenocarcinoma

One of the most common sites of extra-thoracic distant metastasis of nonsmall-cell lung cancer is the brain. Our study was performed to discover genes associated with postoperative brain metastasis in operable lung adenocarcinoma (LUAD). RNA seq was performed in specimens of primary LUAD from seven patients with brain metastases and 45 patients without recurrence. Immunohistochemical (IHC) assays of the differentially expressed genes were conducted in 272 surgical-resected LUAD specimens. LASSO Cox regression was used to filter genes related to brain metastasis and construct brain metastasis score (BMS). GSE31210 and GSE50081 were used as validation datasets of the model. Gene Set Enrichment Analysis was performed in patients stratified by risk of brain metastasis in the TCGA database. Through the initial screening, eight genes (CDK1, KPNA2, KIF11, ASPM, CEP55, HJURP, TYMS and TTK) were selected for IHC analyses. The BMS based on protein expression levels of five genes (TYMS, CDK1, HJURP, CEP55 and KIF11) was highly predictive of brain metastasis in our cohort (12-month AUC: 0.791, 36-month AUC: 0.766, 60-month AUC: 0.812). The validation of BMS on overall survival of GSE31210 and GSE50081 also showed excellent predictive value (GSE31210, 12-month AUC: 0.682, 36-month AUC: 0.713, 60-month AUC: 0.762; GSE50081, 12-month AUC: 0.706, 36-month AUC: 0.700, 60-month AUC: 0.724). Further analyses showed high BMS was associated with pathways of cell cycle and DNA repair. A five-gene predictive model exhibits potential clinical utility for the prediction of postoperative brain metastasis and the individual management of patients with LUAD after radical resection.

KIF11 and KIF15 mitotic kinesins are potential therapeutic vulnerabilities for malignant peripheral nerve sheath tumors

Background

Malignant peripheral nerve sheath tumor (MPNST) constitutes the leading cause of neurofibromatosis type 1–related mortality. MPNSTs contain highly rearranged hyperploid genomes and exhibit a high division rate and aggressiveness. We have studied in vitro whether the mitotic kinesins KIF11, KIF15, and KIF23 have a functional role in maintaining MPNST cell survival and can represent potential therapeutic vulnerabilities.

Methods

We studied the expression of kinesin mRNAs and proteins in tumors and cell lines and used several in vitro functional assays to analyze the impact of kinesin genetic suppression (KIF15, KIF23) and drug inhibition (KIF11) in MPNST cells. We also performed in vitro combined treatments targeting KIF11 together with other described MPNST targets.

Results

The studied kinesins were overexpressed in MPNST samples. KIF15 and KIF23 were required for the survival of MPNST cell lines, which were also more sensitive than benign control fibroblasts to the KIF11 inhibitors ispinesib and ARRY-520. Co-targeting KIF11 and BRD4 with ARRY-520 and JQ1 reduced MPNST cell viability, synergistically killing a much higher proportion of MPNST cells than control fibroblasts. In addition, genetic suppression of KIF15 conferred an increased sensitivity to KIF11 inhibitors alone or in combination with JQ1.

Conclusions

The mitotic spindle kinesins KIF11 and KIF15 and the cytokinetic kinesin KIF23 play a clear role in maintaining MPNST cell survival and may represent potential therapeutic vulnerabilities. Although further in vivo evidences are still mandatory, we propose a simultaneous suppression of KIF11, KIF15, and BRD4 as a potential therapy for MPNSTs.

Identification of KIF11 As a Novel Target in Meningioma

Kinesins play an important role in many physiological functions including intracellular vesicle transport and mitosis. The emerging role of kinesins in different cancers led us to investigate the expression and functional role of kinesins in meningioma. Therefore, we re-analyzed our previous microarray dataset of benign, atypical, and anaplastic meningiomas (n = 62) and got evidence for differential expression of five kinesins (KIFC1, KIF4A, KIF11, KIF14 and KIF20A). Further validation in an extended study sample (n = 208) revealed a significant upregulation of these genes in WHO°I to °III meningiomas (WHO°I n = 61, WHO°II n = 88, and WHO°III n = 59), which was most pronounced in clinically more aggressive tumors of the same WHO grade. Immunohistochemical staining confirmed a WHO grade-associated upregulated protein expression in meningioma tissues. Furthermore, high mRNA expression levels of KIFC1, KIF11, KIF14 and KIF20A were associated with shorter progression-free survival. On a functional level, knockdown of kinesins in Ben-Men-1 cells and in the newly established anaplastic meningioma cell line NCH93 resulted in a significantly inhibited tumor cell proliferation upon siRNA-mediated downregulation of KIF11 in both cell lines by up to 95% and 71%, respectively. Taken together, in this study we were able to identify the prognostic and functional role of several kinesin family members of which KIF11 exhibits the most promising properties as a novel prognostic marker and therapeutic target, which may offer new treatment options for aggressive meningiomas.