The role of kinesin KIF18A in the invasion and metastasis of hepatocellular carcinoma

Next-Generation Metabolic Glycosylation Reporters Enable Detection of Protein O-GlcNAcylation in Living Cells without S-Glyco Modification

Protein O-GlcNAcylation is a ubiquitous posttranslational modification of cytosolic and nuclear proteins involved in numerous fundamental regulation processes. Investigation of O-GlcNAcylation by metabolic glycoengineering (MGE) has been carried out for two decades with peracetylated N-acetylglucosamine (GlcNAc) and N-acetylgalactosamine derivatives modified with varying reporter groups. Recently, it has been shown that these derivatives can result in non-specific protein labeling termed S-glyco modification. Here, we report norbornene-modified GlcNAc derivatives with a protected phosphate at the anomeric position and their application in MGE. These derivatives overcome two limitations of previously used O-GlcNAc reporters. They do not lead to detectable S-glyco modification, and they efficiently react in the inverse-electron-demand Diels-Alder (IEDDA) reaction, which can be carried out even within living cells. Using a derivative with an S-acetyl-2-thioethyl-protected phosphate, we demonstrate the protein-specific detection of O-GlcNAcylation of several proteins and the protein-specific imaging of O-GlcNAcylation inside living cells by Förster resonance energy transfer (FRET) visualized by confocal fluorescence lifetime imaging microscopy (FLIM).

Motor proteins, spermatogenesis and testis function

The role of motor proteins in supporting intracellular transports of vesicles and organelles in mammalian cells has been known for decades. On the other hand, the function of motor proteins that support spermatogenesis is also well established since the deletion of motor protein genes leads to subfertility and/or infertility. Furthermore, mutations and genetic variations of motor protein genes affect fertility in men, but also a wide range of developmental defects in humans including multiple organs besides the testis. In this review, we seek to provide a summary of microtubule and actin-dependent motor proteins based on earlier and recent findings in the field. Since these two cytoskeletons are polarized structures, different motor proteins are being used to transport cargoes to different ends of these cytoskeletons. However, their involvement in germ cell transport across the blood-testis barrier (BTB) and the epithelium of the seminiferous tubules remains relatively unknown. It is based on recent findings in the field, we have provided a hypothetical model by which motor proteins are being used to support germ cell transport across the BTB and the seminiferous epithelium during the epithelial cycle of spermatogenesis. In our discussion, we have highlighted the areas of research that deserve attention to bridge the gap of research in relating the function of motor proteins to spermatogenesis.

Kinesin Family Member-18A (KIF18A) Promotes Cell Proliferation and Metastasis in Hepatocellular Carcinoma

BACKGROUND & AIMS

Kinesin family member 18A (KIF18A) is notable for its aberrant expression across various cancer types and its pivotal role is driving cancer progression. In this study, we aim to investigate the intricate molecular mechanisms underlying the impact of KIF18A on the progression of HCC.

METHODS

Western blotting assays, a quantitative real-time PCR and immunohistochemical analyses were performed to quantitatively assess KIF18A expression in HCC tissues. We then performed genetic manipulations within HCC cells by silencing endogenous KIF18A using short hairpin RNA (shRNA) and introducing exogenous plasmids to overexpress KIF18A. We monitored cell progression, analyzed cell cycle and cell apoptosis and assessed cell migration and invasion both in vitro and in vivo. Moreover, we conducted RNA-sequencing to explore KIF18A-related signaling pathways utilizing Reactome and KEGG enrichment methods and validated these critical mediators in these pathways.

RESULTS

Analysis of the TCGA-LIHC database revealed pronounced overexpression of KIF18A in HCC tissues, the finding was subsequently confirmed through the analysis of clinical samples obtained from HCC patients. Notably, silencing KIF18A in cells led to an obvious inhibition of cell proliferation, migration and invasion in vitro. Furthermore, in subcutaneous and orthotopic xenograft models, suppression of KIF18A sgnificantly redudce tumor weight and the number of lung metastatic nodules. Mechanistically, KIF18A appears to facilitate cell proliferation by upregulating MAD2 and CDK1/CyclinB1 expression levels, with the activation of SMAD2/3 signaling contributing to KIF18A-driven metastasis.

CONCLUSION

Our study elucidates the molecular mechanism by which KIF18A mediates proliferation and metastasis in HCC cells, offering new insights into potential therapeutic targets.

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).

Development and Validation of the novel Cuproptosis- and Immune-related Signature for Predicting Prognosis in Hepatocellular Carcinoma

Background: Hepatocellular carcinoma often results in late-stage diagnosis, leading to decreased treatment success. To improve prognosis, this study integrates cuproptosis with immune risk scoring models for HCC patients. Method: We identified differentially expressed genes connected to cuproptosis and immune responses using Pearson correlation. A risk signature was then constructed via LASSO regression, and its robustness was validated in the International Cancer Genome Consortium dataset. Additionally, qPCR confirmed findings in tumor and normal tissues. Results: Eight genes emerged as key prognostic markers from the 110 differentially expressed genes linked to cuproptosis and immunity. A risk-scoring model was developed using gene expression, effectively categorizing patients into low- or high-risk groups. Validated in the ICGC dataset, high-risk patients had significantly reduced survival times. Multivariate Cox regression affirmed the risk signature's independent predictive capability. A clinical nomogram based on the risk signature was generated. Notably, low-risk patients might benefit more from immune checkpoint inhibitors. qPCR and western blotting results substantiated our bioinformatics findings. Conclusions: The genetic risk signature linked to cuproptosis and immunity holds potential as a vital prognostic biomarker for Hepatocellular carcinoma, providing avenues for tailored therapeutic strategies.

Whole-exome sequencing reveals the metastatic potential of hepatocellular carcinoma from the perspective of tumor and circulating tumor DNA

BACKGROUND

Relapse of hepatocellular carcinoma (HCC) due to vascular invasion is common, but the genomic mechanisms remain unclear, and molecular determinants of high-risk relapse cases are lacking. We aimed to reveal the evolutionary trajectory of microvascular invasion (MVI) and develop a predictive signature for relapse in HCC.

METHODS

Whole-exome sequencing was performed on tumor and peritumor tissues, portal vein tumor thrombus (PVTT), and circulating tumor DNA (ctDNA) to compare the genomic profiles between 5 HCC patients with MVI and 5 patients without MVI. We conducted an integrated analysis of exome and transcriptome to develop and validate a prognostic signature in two public cohorts and one cohort from Zhongshan Hospital, Fudan University.

RESULTS

Shared genomic landscapes and identical clonal origins among tumor, PVTT, and ctDNA were observed in MVI ( +) HCC, suggesting that genomic changes favoring metastasis occur at the primary tumor stage and are inherited in metastatic lesions and ctDNA. There was no clonal relatedness between the primary tumor and ctDNA in MVI ( - ) HCC. HCC had dynamic mutation alterations during MVI and exhibited genetic heterogeneity between primary and metastatic tumors, which can be comprehensively reflected by ctDNA. A relapse-related gene signature named RGSHCC was developed based on the significantly mutated genes associated with MVI and shown to be a robust classifier of HCC relapse.

CONCLUSIONS

We characterized the genomic alterations during HCC vascular invasion and revealed a previously undescribed evolution pattern of ctDNA in HCC. A novel multiomics-based signature was developed to identify high-risk relapse populations.

Development and validation of a novel anoikis-related gene signature in clear cell renal cell carcinoma

Background

Despite numerous treatments available, clear cell renal cell carcinoma (ccRCC) remains a deadly and invasive cancer. Anoikis-related genes (ARGs) are essential regulators of tumor metastasis and development. However, the potential roles of ARGs in ccRCC remain unclear.

Methods

Based on the TCGA-KIRC cohort and GeneCards database, we identified differentially expressed ARGs in ccRCC. Then a 4 ARGs risk model was created by Cox regression and LASSO. The Kaplan-Meier and receiver operating characteristic (ROC) curves were utilized to verify the predictive efficacy of the prognostic signature. Subsequently, the possible molecular mechanism of ARGs was investigated by functional enrichment analysis. To assess the immune infiltration, immune checkpoint genes, and immune function in various risk groups, single sample gene set enrichment (ssGSEA) algorithm was employed. Furthermore, the low-risk and high-risk groups were compared in terms of tumor mutation burden (TMB). Ultimately, we analyzed the protein expression of these four ARGs utilizing the western blot test.

Results

Four genes were utilized to create a risk signature that may predict prognosis, enabling the classification of KIRC patients into groups with low or high risk. The reliability of the signature was examined utilizing survival analysis and ROC analysis. According to the multivariate Cox regression result, the risk score was a reliable independent prognostic predictor for KIRC patients. The novel risk model could differentiate between KIRC patients with various clinical outcomes and represent KIRC's specific immune status. An analysis of the correlation of TMB and risk score indicated a positive correlation between them, with high TMB being potentially linked to worse outcomes.

Conclusion

Based on our findings, the prognostic signature of ARGs may be employed as an independent prognostic factor for ccRCC patients. It may introduce alternative perspectives on prognosis evaluation and serve as a prominent reference for personalized and precise therapy in KIRC.

KIF18A improves migration and invasion of colorectal cancer (CRC) cells through inhibiting PTEN signaling

BACKGROUND

Kinesin family member 18A (KIF18A) is involved in the development of a variety of human malignancies. However, we have never known the influences of KIF18A on colorectal cancer (CRC). The study is designed to investigate the effect and molecular mechanism of KIF18A on the progression of colorectal cancer.

METHODS

We have not only analyzed the database using GEO, but have examined the effect of KIF18A on the development of CRC by subcutaneous tumorigenesis in nude mice. HE staining was used to observe tumor size. Besides, we make use of Western blotting to monitor the expression of related proteins. In addition, the scratch wound assay and Transwell assay were conducted to detect the effect of KIF18A on the migration and invasion of CRC cells.

RESULTS

The results of GEO database analysis suggested that KIF18A had a positive correlation with the growth of CRC. The results of subcutaneous tumorigenesis and HE staining in nude mice explained that KIF18A promoted the progression of CRC. Both scratch wound assay and Transwell indicated that the migration and invasion of CRC could be promoted by KIF18A. The results of Western blot illustrated that KIF18A could forward the migration and invasion of CRC cells, and inhibit PTEN, which promoted the activation of PI3K/Akt signaling pathway, thus bringing about the expression of MMP2 and MMP9.

CONCLUSION

In conclusion, KIF18A can further the activation of PI3K/Akt signaling pathway by means of inhibiting PTEN transcription. Therefore, it is inferred that that KIF18A is a therapeutic target for CRC.

KIF18A interacts with PPP1CA to promote the malignant development of glioblastoma

Glioblastoma (GBM), which has poor prognosis and low 5-year survival rate, is the most common primary central nervous system malignant tumour in adults. Kinesin family member 18A (KIF18A) plays an important role in multiple tumours and is potential therapeutic target for GBM. Therefore, the present study investigated the role of KIF18A in GBM. The expression level and survival prognosis of KIF18A and protein phosphatase 1 catalytic subunit α (PPP1CA) in GBM patients were analysed using the Chinese Glioma Genome Atlas (CGGA) database. Reverse transcription-quantitative PCR and western blot analysis were applied to measure the expression of KIF18A and PPP1CA in normal and GBM cell lines. KIF18A expression was inhibited through cell transfection with a KIF18A-targeting short hairpin RNA. Cell proliferation was detected with the Cell Counting Kit-8 assay. Flow cytometry was used to detect cell cycle changes. Transwell and wound healing assays were used to measure cell invasion and migration. Western blotting was utilized for the detection of invasion- and migration-related proteins MMP9 and MMP2. Biological General Repository for Interaction Datasets and GeneMANIA databases were used to analyse the interaction between KIF18A and PPP1CA. The correlation between PPP1CA and KIF18A was examined using data from the CGGA database. Immunoprecipitation was used to demonstrate the binding relationship between KIF18A and PPP1CA. PPP1CA was overexpressed using cell transfection technology and its mechanism was further examined. The results demonstrated that KIF18A was upregulated in GBM cells compared with normal microglia HMC3. Compared with that in sh-NC group, silencing of KIF18A reduced cell proliferation, induced G₂/M cycle arrest and inhibited the migration and the invasion of A172 GBM cells by interacting with PPP1CA. In conclusion, KIF18A interacted with PPP1CA to promote the proliferation, cycle arrest, migration and invasion of GBM cells.

Dynamic Regulation Genes at Microtubule Plus Ends: A Novel Class of Glioma Biomarkers

Simple Summary

Microtubule plus-end-related genes (MPERGs) encode a group of proteins that specifically aggregate at the microtubule plus ends to play critical biological roles in the cell cycle, cell movement, ciliogenesis, and neuronal development by coordinating microtubule assembly and dynamics; however, the MPERG correlations and their clinical significance in glioma are not fully understood. This study is the first to systematically analyze and define a seven-gene signature (CTTNBP2, KIF18A, NAV1, SLAIN2, SRCIN1, TRIO, and TTBK2) and nomogram model closely associated with clinical factors and the tumor microenvironment as a reliable and independent prognostic biomarker to guide personalized choices of immunotherapy and chemotherapy for glioma patients.

Abstract

Glioma is the most prevalent and aggressive primary nervous system tumor with an unfavorable prognosis. Microtubule plus-end-related genes (MPERGs) play critical biological roles in the cell cycle, cell movement, ciliogenesis, and neuronal development by coordinating microtubule assembly and dynamics. This research seeks to systematically explore the oncological characteristics of these genes in microtubule-enriched glioma, focusing on developing a novel MPERG-based prognostic signature to improve the prognosis and provide more treatment options for glioma patients. First, we thoroughly analyzed and identified 45 differentially expressed MPERGs in glioma. Based on these genes, glioma patients were well distinguished into two subgroups with survival and tumor microenvironment infiltration differences. Next, we further screened the independent prognostic genes (CTTNBP2, KIF18A, NAV1, SLAIN2, SRCIN1, TRIO, and TTBK2) using 36 prognostic-related differentially expressed MPERGs to construct a signature with risk stratification and prognostic prediction ability. An increased risk score was related to the malignant progression of glioma. Therefore, we also designed a nomogram model containing clinical factors to facilitate the clinical use of the risk signature. The prediction accuracy of the signature and nomogram model was verified using The Cancer Genome Atlas and Chinese Glioma Genome Atlas datasets. Finally, we examined the connection between the signature and tumor microenvironment. The signature positively correlated with tumor microenvironment infiltration, especially immunoinhibitors and the tumor mutation load, and negatively correlated with microsatellite instability and cancer stemness. More importantly, immune checkpoint blockade treatment and drug sensitivity analyses confirmed that this prognostic signature was helpful in anticipating the effect of immunotherapy and chemotherapy. In conclusion, this research is the first study to define and validate an MPERG-based signature closely associated with the tumor microenvironment as a reliable and independent prognostic biomarker to guide personalized choices of immunotherapy and chemotherapy for glioma patients.

Comprehensive Pan-Cancer Analysis of KIF18A as a Marker for Prognosis and Immunity

KIF18A belongs to the Kinesin family, which participates in the occurrence and progression of tumors. However, few pan-cancer analyses have been performed on KIF18A to date. We used multiple public databases such as TIMER, The Cancer Genome Atlas (TCGA), Genotype-Tissue Expression (GTEx), and Human Protein Atlas (HPA) to explore KIF18A mRNA expression in 33 tumors. We performed immunohistochemistry on liver cancer and pancreatic cancer tissues and corresponding normal tissues to examine the expression of KIF18A protein. Univariate Cox regression and Kaplan-Meier survival analysis were applied to detect the effect of KIF18A on overall survival (OS), disease-specific survival (DSS), and progression-free interval (PFI) of patients with these tumors. Subsequently, we explored KIF18A gene alterations in different tumor tissues using cBioPortal. The relationship between KIF18A and clinical characteristics, tumor microenvironment (TME), immune regulatory genes, immune checkpoints, tumor mutational burden (TMB), microsatellite instability (MSI), mismatch repairs (MMRs), DNA methylation, RNA methylation, and drug sensitivity was applied for further study using the R language. Gene Set Enrichment Analysis (GSEA) was utilized to explore the molecular mechanism of KIF18A. Bioinformatic analysis and immunohistochemical experiments confirmed that KIF18A was up-regulated in 27 tumors and was correlated with the T stage, N stage, pathological stage, histological grade, and Ki-67 index in many cancers. The overexpression of KIF18A had poor OS, DSS, and PFI in adrenocortical carcinoma (ACC), kidney renal clear cell carcinoma (KIRC), kidney renal papillary cell carcinoma (KIRP), brain lower-grade glioma (LGG), liver cancer (LIHC), lung adenocarcinoma (LUAD), and pancreatic cancer (PAAD). Univariate and multivariate regression analysis confirmed KIF18A as an independent prognostic factor for LIHC and PAAD. The mutation frequency of KIF18A is the highest in endometrial cancer. KIF18A expression levels were positively associated with immunocyte infiltration, immune regulatory genes, immune checkpoints, TMB, MSI, MMRs, DNA methylation, RNA methylation, and drug sensitivity in certain cancers. In addition, we discovered that KIF18A participated in the cell cycle at the single-cell level and GSEA analysis for most cancers. These findings suggested that KIF18A could be regarded as a latent prognostic marker and a new target for cancer immunological therapy.

An anoikis-related gene signature predicts prognosis and reveals immune infiltration in hepatocellular carcinoma

Background

Hepatocellular carcinoma (HCC) is a global health burden with poor prognosis. Anoikis, a novel programmed cell death, has a close interaction with metastasis and progression of cancer. In this study, we aimed to construct a novel bioinformatics model for evaluating the prognosis of HCC based on anoikis-related gene signatures as well as exploring the potential mechanisms.

Materials and methods

We downloaded the RNA expression profiles and clinical data of liver hepatocellular carcinoma from TCGA database, ICGC database and GEO database. DEG analysis was performed using TCGA and verified in the GEO database. The anoikis-related risk score was developed via univariate Cox regression, LASSO Cox regression and multivariate Cox regression, which was then used to categorize patients into high- and low-risk groups. Then GO and KEGG enrichment analyses were performed to investigate the function between the two groups. CIBERSORT was used for determining the fractions of 22 immune cell types, while the ssGSEA analyses was used to estimate the differential immune cell infiltrations and related pathways. The "pRRophetic" R package was applied to predict the sensitivity of administering chemotherapeutic and targeted drugs.

Results

A total of 49 anoikis-related DEGs in HCC were detected and 3 genes (EZH2, KIF18A and NQO1) were selected out to build a prognostic model. Furthermore, GO and KEGG functional enrichment analyses indicated that the difference in overall survival between risk groups was closely related to cell cycle pathway. Notably, further analyses found the frequency of tumor mutations, immune infiltration level and expression of immune checkpoints were significantly different between the two risk groups, and the results of the immunotherapy cohort showed that patients in the high-risk group have a better immune response. Additionally, the high-risk group was found to have higher sensitivity to 5-fluorouracil, doxorubicin and gemcitabine.

Conclusion

The novel signature of 3 anoikis-related genes (EZH2, KIF18A and NQO1) can predict the prognosis of patients with HCC, and provide a revealing insight into personalized treatments in HCC.

ZNF320 is a hypomethylated prognostic biomarker involved in immune infiltration of hepatocellular carcinoma and associated with cell cycle

Hepatocellular carcinoma (HCC) is one of the most deadly and common malignant cancers around the world, and the prognosis of HCC patients is not optimistic. ZNF320 belongs to Krüppel like zinc finger gene family. However, no studies have focused on the influence of ZNF320 in HCC. We first analyzed ZNF320 expression in HCC by using data from TCGA and ICGC, then conducted a joint analysis with TIMER and UALCAN, and validated by immunohistochemistry in clinical HCC samples. Then we applied UALCAN to explore the correlation between ZNF320 expression and clinicopathological characteristics. Consequently, using Kaplan-Meier Plotter analysis and the Cox regression, we can predict the prognostic value of ZNF320 for HCC patients. Next, the analysis by GO, KEGG, and GSEA revealed that ZNF320 was significantly correlated to cell cycle and immunity. Finally, TIMER and GEPIA analysis verified that ZNF320 expression is closely related to tumor infiltrating immune cells (TIIC), including B cells, CD8+ T cells, CD4+ T cells, macrophages, neutrophils, and dendritic cells. The analysis of the TCGA and ICGC data sets revealed that ZNF320 expression was significantly correlated with m6A related genes (RBMX, YTHDF1, and METTL3). In conclusion, ZNF320 may be a prognostic biomarker related to immunity as a candidate for liver cancer.

Prognostic Biomarker KIF18A and Its Correlations With Immune Infiltrates and Mitosis in Glioma

Background: Glioma is globally recognised as one of the most frequently occurring primary malignant brain tumours, making the identification of glioma biomarkers critically significant. The protein KIF18A (Kinesin Family Member 18A) is a member of the kinesin superfamily of microtubule-associated molecular motors and has been shown to participate in cell cycle and mitotic metaphase and anaphase. This is the first investigation into the expression of KIF18A and its prognostic value, potential biological functions, and effects on the immune system and mitosis in glioma patients. Methods: Gene expression and clinicopathological analysis, enrichment analysis, and immune infiltration analysis were based on data obtained from The Cancer Genome Atlas (TCGA), with additional bioinformatics analyses performed. Statistical analysis was conducted in R software. Clinical samples were used to evaluate the expression of KIF18A via immunohistochemical staining. In addition, the expression level of KIF18A was validated on U87 cell line. Results: Our results highlighted that KIF18A plays a key role as an independent prognostic factor in patients with glioma. KIF18A was highly expressed in glioma tissues, and KIF18A expression was associated with age, World Health Organization grade, isocitrate dehydrogenase (IDH) status, 1p/19q codeletion, primary therapy outcome, and overall survival (OS). Enrichment analysis revealed that KIF18A is closely correlated with the cell cycle and mitosis. Single sample gene set enrichment analysis (ssGSEA) analysis revealed that KIF18A expression was related to the immune microenvironment. The increased expression of KIF18A in glioma was verified in clinical samples and U87 cell line. Conclusion: The identification of KIF18A as a new biomarker for glioma could help elucidate how changes in the glioma cell and immune microenvironment promote glioma malignancy. With further analysis, KIF18A may serve as an independent prognostic indicator for human glioma.

The Proliferation of Glioblastoma Is Contributed to Kinesin Family Member 18A and Medical Data Analysis of GBM

Background: Glioblastoma (GBM) is widely known as a classical kind of malignant tumor originating in the brain with high morbidity and mortality. Targeted therapy has shown great promise in treating glioblastoma, but more promising targets, including effective therapeutic targets, remain to be identified. 18A (KIF18A) is a microtubule-based motor protein that is dysregulated and involved in the progression of multiple human cancers. However, the possible effects of KIF18A on GBM progression are still unclear.

Methods: We performed DEG analysis, medical data analysis, and network analysis to identify critical genes affecting glioma progression. We also performed immunohistochemical analysis of the KIF18A levels in 94 patients with glioblastoma and the associated surrounding tissues. Patients were divided into two groups according to the high and low expression. Using a clinical analysis, we showed the potential associations between KIF18A expression and clinical characteristics of 94 GBM patients. We then investigated the effects of KIF18A on GBM cell proliferation by colony establishment, MTT, and immune blogging. The possible effect of KIF18A on GBM tumor growth was determined in mice.

Results: We identified KIF18A as a potential gene affecting GBM progression. We further demonstrated that GBM tissues expressed KIF18A much higher, and its presentation was associated with recurrence in glioblastoma patients. We believe KIF18A promotes GBM cell proliferation.

Conclusion: We demonstrated that KIF18A could be a promising target in treating GBM.

KIF2C: a novel link between Wnt/β-catenin and mTORC1 signaling in the pathogenesis of hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is the most common primary liver malignancy and is the fourth-leading cause of cancer-related deaths worldwide. HCC is refractory to many standard cancer treatments and the prognosis is often poor, highlighting a pressing need to identify biomarkers of aggressiveness and potential targets for future treatments. Kinesin family member 2C (KIF2C) is reported to be highly expressed in several human tumors. Nevertheless, the molecular mechanisms underlying the role of KIF2C in tumor development and progression have not been investigated. In this study, we found that KIF2C expression was significantly upregulated in HCC, and that KIF2C up-regulation was associated with a poor prognosis. Utilizing both gain and loss of function assays, we showed that KIF2C promoted HCC cell proliferation, migration, invasion, and metastasis both in vitro and in vivo. Mechanistically, we identified TBC1D7 as a binding partner of KIF2C, and this interaction disrupts the formation of the TSC complex, resulting in the enhancement of mammalian target of rapamycin complex1 (mTORC1) signal transduction. Additionally, we found that KIF2C is a direct target of the Wnt/β-catenin pathway, and acts as a key factor in mediating the crosstalk between Wnt/β-catenin and mTORC1 signaling. Thus, the results of our study establish a link between Wnt/β-catenin and mTORC1 signaling, which highlights the potential of KIF2C as a therapeutic target for the treatment of HCC.

DUSP12 regulates the tumorigenesis and prognosis of hepatocellular carcinoma

Background

Dual specificity protein phosphatase (DUSP)12 is an atypical member of the protein tyrosine phosphatase family, which are overexpressed in multiple types of malignant tumors. This protein family protect cells from apoptosis and promotes the proliferation and motility of cells. However, the pathological role of DUSP12 in hepatocellular carcinoma (HCC) is incompletely understood.

Methods

We analyzed mRNA expression of DUSP12 between HCC and normal liver tissues using multiple online databases, and explored the status of DUSP12 mutants using the cBioPortal database. The correlation between DUSP12 expression and tumor-infiltrating immune cells was demonstrated using the Tumor Immune Estimation Resource database and the Tumor and Immune System Interaction Database. Loss of function assay was utilized to evaluate the role of DUSP12 in HCC progression.

Results

DUSP12 had higher expression along with mRNA amplification in HCC tissues compared with those in normal liver tissues, which suggested that higher DUSP12 expression predicted shorter overall survival. Analyses of functional enrichment of differentially expressed genes suggested that DUSP12 regulated HCC tumorigenesis, and that knockdown of DUSP12 expression by short hairpin (sh)RNA decreased the proliferation and migration of HCC cells. Besides, DUSP12 expression was positively associated with the infiltration of cluster of differentiation (CD)4+ T cells (especially CD4+ regulatory T cells), macrophages, neutrophils and dendritic cells. DUSP12 expression was positively associated with immune-checkpoint moieties, and was downregulated in a C3 immune-subgroup of HCC (which had the longest survival).

Conclusion

These data suggest that DUSP12 may have a critical role in the tumorigenesis, infiltration of immune cells, and prognosis of HCC.

N6-methyladenosine (m6A) RNA methylation regulator SNRPC is a prognostic biomarker and is correlated with immunotherapy in hepatocellular carcinoma

Background

Hepatocellular carcinoma (HCC) is one of the most common malignancies in the world, and due to its complex pathogenic factors, its prognosis is poor. N6-methyladenosine (m⁶A) RNA methylation plays an important role in the tumorigenesis, progression, and prognosis of many tumors. The m⁶A RNA methylation regulator small nuclear ribonucleoprotein polypeptide C (SNRPC), which encodes one of the specific protein components of the U1 small nuclear ribonucleoprotein (snRNP) particle, has been proven to be related to the prognosis of patients with HCC. However, the effect of SNRPC on the tumor microenvironment and immunotherapy in HCC remains unclear.

Case presentation

The HCC RNA-seq profiles in The Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium (ICGC) databases, including 421 LIHC and 440 LIRI-JP samples, respectively, were used in this study. Both the expression of SNRPC in HCC was upregulated in the TCGA and ICGC databases compared to normal tissues. Next, the expression of SNRPC was validated as a risk factor for prognosis by Kaplan-Meier analysis and employed to establish a nomogram with T pathologic stage. By gene set variation (GSVA) analysis and gene set enrichment (GSEA) analysis, we found that SNRPC was mainly related to protein metabolism and the immune process. Furthermore, the estimation of stromal and immune cells in malignant tumor tissues using expression (ESTIMATE), microenvironment cell population counter (MCP-counter), and single sample GSEA (ssGSEA) algorithms revealed that the high-SNRPC group had a lower stromal score, lower abundance of endothelial cells and fibroblasts, and lower immune infiltration. Ultimately, a tumor immune dysfunction and exclusion (TIDE) analysis revealed that patients in the low-SNRPC group may be more sensitive to immune checkpoint inhibitor therapy.

Conclusion

SNRPC could serve as a promising prognostic and immunotherapeutic marker in HCC and might contribute to new directions and strategies for HCC treatment.

KIF18A knockdown reduces proliferation, migration, invasion and enhances radiosensitivity of esophageal cancer

Kinesin family member 18A (KIF18A) is significantly overexpressed and is related to the poor prognosis of human cancers. However, the function of KIF18A in esophageal cancer (EC) is still unclear. Human EC cell lines were used in this study. KIF18A expression in human tissues was assessed using Gene Expression Profiling Interactive Analysis 2.0 (GEPIA2). The expressions of KIF18A or IGF2BP3 in EC cells were detected using qRT-PCR or WB. Cells were transfected using si-KIF18A, si-IGF2BP3, and plasmid IGF2BP3. The abilities of proliferation, migration, and invasion were detected by EdU, wound-healing, and transwell assay. The interaction between KIF18A and IGF2BP3 was predicted by starBase v3.0 and studied by RIP and RNA stability assay. Colony formation assay was used to reflect the changes of radiosensitivity in EC cells. KIF18A was upregulated in EC, and KIF18A knockdown inhibited EC cell proliferation, migration, invasion, and radioresistance. The prediction in starBase and RIP assay results showed that KIF18A mRNA could bind to IGF2BP3 protein in EC cells. RNA stability assay was performed to confirm that IGF2BP3 affects mRNA stability of KIF18A. Further studies also showed that IGF2BP3 could positively regulate KIF18A on proliferation, migration, invasion, and radioresistance. Our findings first revealed an oncogenic effect of KIF18A in human EC progression. KIF18A expression was associated with radioresistance of EC cells. The binding relationship between KIF18A and IGF2BP3 might influence the mRNA stability of KIF18A in EC cell lines.

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.

Development and Clinical Validation of a Seven-Gene Prognostic Signature Based on Multiple Machine Learning Algorithms in Kidney Cancer

About a third of patients with kidney cancer experience recurrence or cancer-related progression. Clinically, kidney cancer prognoses may be quite different, even in patients with kidney cancer at the same clinical stage. Therefore, there is an urgent need to screen for kidney cancer prognosis biomarkers. Differentially expressed genes (DEGs) were identified using kidney cancer RNA sequencing data from the Gene Expression Omnibus (GEO) database. Biomarkers were screened using random forest (RF) and support vector machine (SVM) models, and a multigene signature was constructed using the least absolute shrinkage and selection operator (LASSO) regression analysis. Univariate and multivariate Cox regression analyses were performed to explore the relationships between clinical features and prognosis. Finally, the reliability and clinical applicability of the model were validated, and relationships with biological pathways were identified. Western blots were also performed to evaluate gene expression. A total of 50 DEGs were obtained by intersecting the RF and SVM models. A seven-gene signature (RNASET2, EZH2, FXYD5, KIF18A, NAT8, CDCA7, and WNT7B) was constructed by LASSO regression. Univariate and multivariate Cox regression analyses showed that the seven-gene signature was an independent prognostic factor for kidney cancer. Finally, a predictive nomogram was established in The Cancer Genome Atlas (TCGA) cohort and validated internally. In tumor tissue, RNASET2 and FXYD5 were highly expressed and NAT8 was lowly expressed at the protein and transcription levels. This model could complement the clinicopathological characteristics of kidney cancer and promote the personalized management of patients with kidney cancer.

Network-based survival analysis to discover target genes for developing cancer immunotherapies and predicting patient survival

Recently, cancer immunotherapies have been life-savers, however, only a fraction of treated patients have durable responses. Consequently, statistical methods that enable the discovery of target genes for developing new treatments and predicting patient survival are of importance. This paper introduced a network-based survival analysis method and applied it to identify candidate genes as possible targets for developing new treatments. RNA-seq data from a mouse study was used to select differentially expressed genes, which were then translated to those in humans. We constructed a gene network and identified gene clusters using a training set of 310 human gliomas. Then we conducted gene set enrichment analysis to select the gene clusters with significant biological function. A penalized Cox model was built to identify a small set of candidate genes to predict survival. An independent set of 690 human glioma samples was used to evaluate predictive accuracy of the survival model. The areas under time-dependent ROC curves in both the training and validation sets are more than 90%, indicating strong association between selected genes and patient survival. Consequently, potential biomedical interventions targeting these genes might be able to alter their expressions and prolong patient survival.

Motor Proteins and Spermatogenesis

Unlike the intermediate filament- and septin-based cytoskeletons which are apolar structures, the microtubule (MT) and actin cytoskeletons are polarized structures in mammalian cells and tissues including the testis, most notable in Sertoli cells. In the testis, these cytoskeletons that stretch across the epithelium of seminiferous tubules and lay perpendicular to the basement membrane of tunica propria serve as tracks for corresponding motor proteins to support cellular cargo transport. These cargoes include residual bodies, phagosomes, endocytic vesicles and most notably developing spermatocytes and haploid spermatids which lack the ultrastructures of motile cells (e.g., lamellipodia, filopodia). As such, these developing germ cells require the corresponding motor proteins to facilitate their transport across the seminiferous epithelium during the epithelial cycle of spermatogenesis. Due to the polarized natures of these cytoskeletons with distinctive plus (+) and minus (-) end, directional cargo transport can take place based on the use of corresponding actin- or MT-based motor proteins. These include the MT-based minus (-) end directed motor proteins: dyneins, and the plus (+) end directed motor proteins: kinesins, as well as the actin-based motor proteins: myosins, many of which are plus (+) end directed but a few are also minus (-) end directed motor proteins. Recent studies have shown that these motor proteins are essential to support spermatogenesis. In this review, we briefly summarize and evaluate these recent findings so that this information will serve as a helpful guide for future studies and for planning functional experiments to better understand their role mechanistically in supporting spermatogenesis.

Knockdown of Circ_CCNB2 Sensitizes Prostate Cancer to Radiation Through Repressing Autophagy by the miR-30b-5p/KIF18A Axis

Background: Circular RNAs (circRNAs) have recently emerged as crucial regulatory molecules in prostate cancer (PCa), but few researches focus on the effects of circRNAs on PCa radiosensitivity. The issue will be addressed in this study using circRNA Cyclin B2 (circ_CCNB2) as an object. Materials and Methods: All RNA and protein levels were severally examined using quantitative real-time polymerase chain reaction and Western blot. Colony formation assay and flow cytometry were implemented for detecting cell colony capacity and apoptotic cells, respectively. Cellular migration and invasion abilities were evaluated by transwell assay. The combination between potential target molecules was analyzed by dual-luciferase reporter and RNA immunoprecipitation (RIP) assays. The effect of circ_CCNB2 on PCa radiosensitivity in vivo was explored using xenograft models in mice. Results: Circ_CCNB2 was upregulated in irradiation-resistant PCa tissues and cells. Circ_CCNB2 knockdown had promoted effect on the radiosensitivity of irradiation-resistant PCa cells by inhibiting autophagy. Besides, circ_CCNB2 could directly sponge miR-30b-5p, and the promotion of circ_CCNB2 knockdown on PCa radiosensitivity was achieved by elevating miR-30b-5p. MiR-30b-5p enhanced the radiosensitivity of irradiation-resistant PCa cells through repressing the expression of its target kinesin family member 18A (KIF18A). Furthermore, circ_CCNB2 regulated the KIF18A level through targeting miR-30b-5p. Circ_CCNB2 downregulation facilitated PCa radiosensitivity in vivo through inhibiting autophagy by miR-30b-5p/KIF18A. Conclusions: In this study, knockdown of circ_CCNB2 was shown to promote PCa radiosensitivity through autophagy repression by miR-30b-5p/KIF18A axis, developing a molecular resistance mechanism of PCa radiotherapy and a feasible strategy to increase radiosensitivity.

Bioinformatics analysis of the genes involved in the extension of prostate cancer to adjacent lymph nodes by supervised and unsupervised machine learning methods: The role of SPAG1 and PLEKHF2

The present study aimed to identify the genes associated with the involvement of adjunct lymph nodes of patients with prostate cancer (PCa) and to provide valuable information for the identification of potential diagnostic biomarkers and pathological genes in PCa metastasis. The most important candidate genes were identified through several machine learning approaches including K-means clustering, neural network, Naïve Bayesian classifications and PCA with or without downsampling. In total, 21 genes associated with lymph nodes involvement were identified. Among them, nine genes have been identified in metastatic prostate cancer, six have been found in the other metastatic cancers and four in other local cancers. The amplification of the candidate genes was evaluated in the other PCa datasets. Besides, we identified a validated set of genes involved in the PCa metastasis. The amplification of SPAG1 and PLEKHF2 genes were associated with decreased survival in patients with PCa.

Kinesin KIF18A is a novel PUM-regulated target promoting mitotic progression and survival of a human male germ cell line

Regulation of proliferation, apoptosis and cell cycle is crucial for the physiology of germ cells. Their malfunction contributes to infertility and germ cell tumours. The kinesin KIF18A is an important regulator of those processes in animal germ cells. Post-transcriptional regulation of KIF18A has not been extensively explored. Owing to the presence of PUM-binding elements (PBEs), KIF18A mRNA is a potential target of PUM proteins, where PUM refers to Pumilio proteins, RNA-binding proteins that act in post-transcriptional gene regulation. We conducted RNA co-immunoprecipitation combined with RT-qPCR, as well as luciferase reporter assays, by applying an appropriate luciferase construct encoding wild-type KIF18A 3'-UTR, upon PUM overexpression or knockdown in TCam-2 cells, representing human male germ cells. We found that KIF18A is repressed by PUM1 and PUM2. To study how this regulation influences KIF18A function, an MTS proliferation assay, and apoptosis and cell cycle analysis using flow cytometry, was performed upon KIF18A mRNA siRNA knockdown. KIF18A significantly influences proliferation, apoptosis and the cell cycle, with its effects being opposite to PUM effects. Repression by PUM proteins might represent one of mechanisms influencing KIF18A level in controlling proliferation, cell cycle and apoptosis in TCam-2 cells.

Selective and ATP-competitive kinesin KIF18A inhibitor suppresses the replication of influenza A virus

The influenza virus is one of the major public health threats. However, the development of efficient vaccines and therapeutic drugs to combat this virus is greatly limited by its frequent genetic mutations. Because of this, targeting the host factors required for influenza virus replication may be a more effective strategy for inhibiting a broader spectrum of variants. Here, we demonstrated that inhibition of a motor protein kinesin family member 18A (KIF18A) suppresses the replication of the influenza A virus (IAV). The expression of KIF18A in host cells was increased following IAV infection. Intriguingly, treatment with the selective and ATP‐competitive mitotic kinesin KIF18A inhibitor BTB‐1 substantially decreased the expression of viral RNAs and proteins, and the production of infectious viral particles, while overexpression of KIF18A enhanced the replication of IAV. Importantly, BTB‐1 treatment attenuated the activation of AKT, p38 MAPK, SAPK and Ran‐binding protein 3 (RanBP3), which led to the prevention of the nuclear export of viral ribonucleoprotein complexes. Notably, administration of BTB‐1 greatly improved the viability of IAV‐infected mice. Collectively, our results unveiled a beneficial role of KIF18A in IAV replication, and thus, KIF18A could be a potential therapeutic target for the control of IAV infection.

Kinesin Family Member 18A (KIF18A) Contributes to the Proliferation, Migration, and Invasion of Lung Adenocarcinoma Cells In Vitro and In Vivo

Objective

To determine the expression levels of KIF18A in lung adenocarcinoma and its relationship with the clinicopathologic features of patients undergoing radical colectomy and explore the potential role in the progression of lung adenocarcinoma.

Methods

Immunohistochemical assays were performed to explore the expression levels of KIF18A in 82 samples of lung adenocarcinoma and corresponding normal tissues. According to the levels of KIF18A expression in lung adenocarcinoma tissue samples, patients were classified into the KIF18A high expression group and low expression group. Clinical data related to the perioperative clinical features (age, gender, smoking, tumor size, differentiation, clinical stage, and lymph node metastasis), the potential correlation between KIF18A expression levels, and clinical features were analyzed, and the effects of KIF18A on lung adenocarcinoma cell proliferation, migration, and invasion were measured by colony formation assay, MTT assay, wound healing assay, and transwell assays. The possible effects of KIF18A on tumor growth and metastasis were measured in mice through tumor growth and tumor metastasis assays in vivo.

Results

KIF18A in lung adenocarcinoma tissues. Further, KIF18A was significantly associated to clinical characteristic features including the tumor size (P = 0.033) and clinical stage (P = 0.041) of patients with lung adenocarcinoma. Our data also investigated that KIF18A depletion dramatically impairs the proliferation, migration, and invasion capacity of lung adenocarcinoma cells in vitro and inhibits tumor growth and metastasis in mice.

Conclusions

Our study reveals the involvement of KIF18A in the progression and metastasis of lung adenocarcinoma and provides a novel therapeutic target for the treatment of lung adenocarcinoma.

KIF18A promotes head and neck squamous cell carcinoma invasion and migration via activation of Akt signaling pathway

BACKGROUND

KIF18A has been shown to participate in the development of various human malignancies. However, the role of KIF18A in head and neck squamous cell carcinoma (HNSCC) remains unknown. This study investigated the function of KIF18A in HNSCC as well as its possible mechanisms.

METHODS

In this study, we conducted in vitro experiments. First, we examined the effect of KIF18A on Tu686 and 6-10B cells via determining cell viability, colony formation ability and cell motility. And then, we examined that whether the carcinogenic effect of KIF18A is associated with Akt activation.

RESULTS

Our current study demonstrated that KIF18A expression was increased in HNSCC patients and its cell lines. Knockdown and overexpression of KIF18A in HNSCC cells indicated that KIF18A promoted cancer cell proliferation, invasion and migration. Moreover, these bioactivity changes in HNSCC cells were accompanied by enhanced Vimentin expression and suppressed E-cadherin expression induced by KIF18A. Further mechanistic analysis revealed that the carcinogenic effect of KIF18A is associated with Akt activation, and blocking the activity of Akt reversed the malignant progression caused by KIF18A overexpression in HNSCC cells.

CONCLUSIONS

Together, our study reveals that KIF18A accelerates the progression of HNSCC and that targeting KIF18A may be a potential therapeutic strategy for the HNSCC.

Expression of KIF18A Is Associated with Increased Tumor Stage and Cell Proliferation in Prostate Cancer

Background

The role of KIF18A in tumorigenesis and tumor development has been well studied in several cancers, but not in prostate cancer. In this study, we investigated the potential prognostic utility of KIF18A and its role in prostate cancer progression.

Material/Methods

We collected prostate cancer and paracancerous tissue samples from the same patient. Immunohistochemical staining was performed to investigate the KIF18A expression levels in the clinical sample. The Cancer Genome Atlas (TCGA) database was analyzed via a bioinformatics approach to gain insight into the relationship between KIF18A expression and prognosis. We examined the effect of KIF18A knockdown on PC-3 cell proliferation via colony formation and MTT assays. Flow cytometry was used to assess the effect of KIF18A knockdown on PC-3 cell apoptosis. Transwell invasion assay was performed to assess whether KIF18A affects the invasion ability of PC-3 cells.

Results

The KIF18A protein level was higher in PCa tissue than in paracancerous tissue. The In addition, upregulated KIF18A suggested a poor tumor stage and prognosis for prostate cancer patients. Our in vitro experiments demonstrated that KIF18A knockdown in PC-3 cells significantly inhibited proliferation and metastasis.

Conclusions

High KIF18A expression in prostate cancer patients predicts a poor prognosis. KIF18A knockdown inhibits prostate cell proliferation and metastasis. Therefore, this study confirms the usefulness of KIF18A as an oncological prognostic indicator and a potential therapeutic target for prostate cancer.

Identification of significant gene and pathways involved in HBV-related hepatocellular carcinoma by bioinformatics analysis

Background

Hepatocellular carcinoma (HCC) is a common malignant tumor affecting the digestive system and causes serious financial burden worldwide. Hepatitis B virus (HBV) is the main causative agent of HCC in China. The present study aimed to investigate the potential mechanisms underlying HBV-related HCC and to identify core biomarkers by integrated bioinformatics analyses.

Methods

In the present study, HBV-related HCC GSE19665, GSE55092, GSE94660 and GSE121248 expression profiles were downloaded from the Gene Expression Omnibus database. These databases contain data for 299 samples, including 145 HBV-related HCC tissues and 154 non-cancerous tissues (from patients with chronic hepatitis B). The differentially expressed genes (DEGs) from each dataset were integrated and analyzed using the RobustRankAggreg (RRA) method and R software, and the integrated DEGs were identified. Subsequently, the gene ontology (GO) functional annotation and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis were performed using the DAVID online tool, and the protein-protein interaction (PPI) network was constructed using STRING and visualized using Cytoscape software. Finally, hub genes were identified, and the cBioPortal online platform was used to analyze the association between the expression of hub genes and prognosis in HCC.

Results

First, 341 DEGs (117 upregulated and 224 downregulated) were identified from the four datasets. Next, GO analysis showed that the upregulated genes were mainly involved in cell cycle, mitotic spindle, and adenosine triphosphate binding. The majority of the downregulated genes were involved in oxidation reduction, extracellular region, and electron carrier activity. Signaling pathway analysis showed that the integrated DEGs shared common pathways in retinol metabolism, drug metabolism, tryptophan metabolism, caffeine metabolism, and metabolism of xenobiotics by cytochrome P450. The integrated DEG PPI network complex comprised 288 nodes, and two important modules with high degree were detected using the MCODE plug-in. The top ten hub genes identified from the PPI network were SHCBP1, FOXM1, KIF4A, ANLN, KIF15, KIF18A, FANCI, NEK2, ECT2, and RAD51AP1. Finally, survival analysis revealed that patients with HCC showing altered ANLN and KIF18A expression profiles showed worse disease-free survival. Nonetheless, patients with FOXM1, NEK2, RAD51AP1, ANLN, and KIF18A alterations showed worse overall survival.

Conclusions

The present study identified key genes and pathways involved in HBV-related HCC, which improved our understanding of the mechanisms underlying the development and recurrence of HCC and identified candidate targets for the diagnosis and treatment of HBV-related HCC.

Integrative analysis of KIF4A, 9, 18A, and 23 and their clinical significance in low-grade glioma and glioblastoma

To determine the prognostic significance of kinesin superfamily gene (KIF) expression in patients with brain cancer, including low-grade glioma (LGG) and glioblastoma (GBM), we comprehensively analyzed KIFs in 515 LGG and 595 GBM patients. Among KIFs, KIF4A, 9, 18A, and 23 showed significant clinical implications in both LGG and GBM. The mRNA and protein expression levels of KIF4A, 9, 18A, and 23 were significantly increased in LGG and GBM compared with those in the normal control groups. The mRNA expression levels of KIF4A, 9, 18A, and 23 in LGG were significantly increased in the high-histologic-grade group compared with those with a low histologic grade. Genomic analysis showed that the percent of mRNA upregulation of KIF4A, 9, 18A, and 23 was higher than that of other gene alterations, including gene amplification, deep deletion, and missense mutation. In addition, LGG patients with KIF4A, 18A, and 23 gene alterations were significantly associated with a poor prognosis. In survival analysis, the group with high expression of KIF4A, 9, 18A, and 23 mRNA was significantly associated with a poor prognosis in both LGG and GBM patients. Gene Set Enrichment Analysis (GSEA) revealed that high mRNA expression of KIF4A, 18A, and 23 in LGG and GBM patients showed significant positive correlations with the cell cycle, E2F targets, G₂M checkpoint, Myc target, and mitotic spindle. By contrast, high mRNA expression of KIF9 in both LGG and GBM patients was significantly negatively correlated with the cell cycle, G₂M checkpoint, and mitotic spindle pathway. However, it was significantly positively correlated with EMT and angiogenesis. This study has extended our knowledge of KIF4A, 9, 18A, and 23 in LGG and GBM and shed light on their clinical relevance, which should help to improve the treatment and prognosis of LGG and GBM.

Lactate Activates the E2F Pathway to Promote Cell Motility by Up-Regulating Microtubule Modulating Genes

Excess lactate production due to enhanced aerobic glycolysis is characteristic of malignant cancers, which is also intimately associated with poor cancer prognoses. Although tumor-associated lactate contributes to all major steps in carcinogenesis, its action mechanism remains obscure. To understand the molecular mechanism of the lactate-induced tumor metastatic process, we identified an array of lactate-responsive genes via transcriptome analysis of a metformin-induced hyper-glycolytic liver cancer model. Gene set enrichment analysis suggested E2F-RB pathway as the dominant regulator of the lactate-induced gene expression. We experimentally verified that lactate indeed activates E2F-mediated transcription by promoting E2F1 protein accumulation through a posttranscriptional mechanism. Literature-based analysis of target pathways potentially modulated by 136 top-ranked genes indicated that genes functioning in cell-cell or cell-matrix communications dominate the lactate-induced gene expression. Especially, those regulating microtubule functions, including a group of kinesin family members, were significantly up-regulated in lactate- and E2F1-dependent manners. Depletion of E2F1 or kinesins (KIF2C, KIF18B, KIF20A) led to deformation of microtubule structures, impairing cell motility as much as the deficit in lactate production. These results indicate that E2F pathway activation by tumor-associated lactate and subsequent transcriptional activation of microtubule functions play crucial roles in tumor metastasis, providing mechanistic clues to cell motility-directed anti-cancer strategies.

Emerging Insights into the Function of Kinesin-8 Proteins in Microtubule Length Regulation

Proper regulation of microtubules (MTs) is critical for the execution of diverse cellular processes, including mitotic spindle assembly and chromosome segregation. There are a multitude of cellular factors that regulate the dynamicity of MTs and play critical roles in mitosis. Members of the Kinesin-8 family of motor proteins act as MT-destabilizing factors to control MT length in a spatially and temporally regulated manner. In this review, we focus on recent advances in our understanding of the structure and function of the Kinesin-8 motor domain, and the emerging contributions of the C-terminal tail of Kinesin-8 proteins to regulate motor activity and localization.

Meiotic arrest and spindle defects are associated with altered KIF11 expression in porcine oocytes

Kinesin superfamily proteins (KIFs) act as molecular motors and are involved in material transport along microtubules to maintain normal cellular functions. KIF11 (also named kinesin-5, Eg5, and KSP) is a plus-end-directed homotetrameric kinesin that regulates spindle formation for actuate chromosomal separation during mitosis. However, the roles of KIF11 in meiosis are still unclear. In this study, we investigated the regulatory functions of KIF11 during porcine oocyte maturation. The results indicated that KIF11 was expressed in different stages during porcine oocyte meiosis. Inhibition of KIF11 activity led to the failure of the first polar body extrusion, and we found that cell cycle progression was disturbed, which was confirmed by the decreased Cdc2 expression. Furthermore, inhibition of KIF11 resulted in decreased tubulin acetylation and caused sequential disruption of the spindle assembly and chromosome alignment. We also found that in postovulatory aging porcine oocytes, the KIF11 expression was altered, indicating that KIF11 was involved with aging-induced spindle disorganization. In summary, our results showed that KIF11 regulated the cell cycle and tubulin acetylation related spindle formation in porcine oocyte meiosis. Environ. Mol. Mutagen. 59:805-812, 2018. © 2018 Wiley Periodicals, Inc.

Kif18a regulates Sirt2-mediated tubulin acetylation for spindle organization during mouse oocyte meiosis

Background

During oocyte meiosis, the cytoskeleton dynamics, especially spindle organization, are critical for chromosome congression and segregation. However, the roles of the kinesin superfamily in this process are still largely unknown.

Results

In the present study, Kif18a, a member of the kinesin-8 family, regulated spindle organization through its effects on tubulin acetylation in mouse oocyte meiosis. Our results showed that Kif18a is expressed and mainly localized in the spindle region. Knock down of Kif18a caused the failure of first polar body extrusion, dramatically affecting spindle organization and resulting in severe chromosome misalignment. Further analysis showed that the disruption of Kif18a caused an increase in acetylated tubulin level, which might be the reason for the spindle organization defects after Kif18a knock down in oocyte meiosis, and the decreased expression of deacetylase Sirt2 was found after Kif18a knock down. Moreover, microinjections of tubulin K40R mRNA, which could induce tubulin deacetylation, protected the oocytes from the effects of Kif18a downregulation, resulting in normal spindle morphology in Kif18a-knock down oocytes.

Conclusions

Taken together, our results showed that Kif18a affected Sirt2-mediated tubulin acetylation level for spindle organization during mouse oocyte meiosis. Our results not only revealed the critical effect of Kif18a on microtubule stability, but also extended our understanding of kinesin activity in meiosis.