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(searched for: doi:10.4103/jcrt.jcrt_491_17)
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Xuewei Zhang, Mingming Dong, Guoxing Zheng, Jinhao Zhu, Bang An, Zibin Zhou, Yonghao Bi, Meng Sun, Chuzhao Zhang, Junfeng Lian, et al.
Published: 20 January 2023
Abstract:
Background The up-regulation of KIF3A possibly predicts the dismal prognostic outcome of hepatocellular carcinoma (HCC). The present work is focused on investigating KIF3A’s function in the growth and migration of HCC cells. Methods KIF3A expression and its role in predicting HCC prognosis were assessed using the TCGA and Genotype-Tissue Expression (GTEx) databases. KIF3A detection conditions in HCC patients were studied using an immunohistochemical panel. siKIF3A was created and then transfected into HepG2 HCC cells. Cell proliferation was examined with the use of the EDU and CCK8. Using the scratch wound healing assays, cell migration was assessed. RT-PCR and Western-blot (WB) assays were adopted for evaluating the expression of genes and proteins. Results KIF3A expression increased in HCC tissues as compared to matched non-carcinoma samples, and it was tightly associated with poor survival and risk factors (Ps < 0.05). KIF3A knockdown hindered the proliferation and migration of HCC cells (Ps < 0.05). KIF3A silencing reduced RelA (NF-κBp65) expression, thus, affecting the activity of HCC cells (Ps < 0.05). Conclusion In this study, the oncogene of hepatocellular carcinoma is KIF3A. Silencing KIF3A inhibited HCC cell growth and migration by suppressing the NF-κB signal pathway. KIF3A was identified as a potential new anti-HCC therapeutic target.
Jun Zhang, Lanfen An, Rong Zhao, Rui Shi, Xing Zhou, Sitian Wei, Qi Zhang, Tangansu Zhang, Dilu Feng, Zhicheng Yu, et al.
Published: 5 December 2022
Molecular Carcinogenesis; https://doi.org/10.1002/mc.23487

, Duanyang Zhai, Mengmeng Zhang, Runyi Ye, Xiaying Kuang, Nan Shao, Jiong Bi,
Published: 1 November 2022
Journal: Cancer Letters
Cancer Letters, Volume 548; https://doi.org/10.1016/j.canlet.2022.215904

World Journal of Gastrointestinal Oncology, Volume 14, pp 1239-1251; https://doi.org/10.4251/wjgo.v14.i7.1239

Abstract:
Esophageal squamous cell carcinoma (ESCC) is one of the most common malignancies. A total of 45 kinesin superfamily proteins (KIFs) have been identified in humans, among which several family members have demonstrated varied functions in tumor pathobiology via different mechanisms, including regulation of cell cycle progression and metastasis. KIFC3 has microtubule motor activity and is involved in cancer cell invasion and migration, as well as survival. However, the role of KIFC3 in ESCC is still unknown. To evaluate the role of KIFC3 in ESCC and the underlying mechanisms. Expression of KIFC3 was evaluated in ESCC tissues and adjacent normal eso phageal tissues. The prognostic value of KIFC3 was analyzed using Kaplan–Meier Plotter. Colony formation, EdU assays, cell cycle analysis, Transwell assay, immunofluorescence, and western blotting were performed in ESCC cell lines after transfection with pLVX-Puro-KIFC3-shRNA- and pLVX-Puro-KIFC3-expressing lentiviruses. A xenograft tumor model in nude mice was used to evaluate the role of KIFC3 in tumorigenesis. Inhibitor of β-catenin, XAV-939, was used to clarify the mechanism of KIFC3 in ESCC. To analyze the differences between groups, t test and nonparametric tests were used. P < 0.05 was consi dered statistically significant. Immunohistochemical staining indicated that KIFC3 was upregulated in ESCC tissues compared with adjacent normal tissues. Kaplan–Meier Plotter revealed that overexpressed KIFC3 was associated with poor prognosis in ESCC patients. Colony formation and EdU assay showed that KIFC3 overexpression promoted cell proliferation, while KIFC3 knockdown inhibited cell proliferation in ESCC cell lines. In addition, cell cycle analysis showed that KIFC3 overexpression promoted cell cycle progression. KIFC3 knockdown suppressed ESCC tumorigenesis in vivo. Transwell assay and western blotting revealed that KIFC3 overexpression promoted cell migration and invasion, as well as epithelial–mesenchymal transition (EMT), while KIFC3 knockdown showed the opposite results. Mechanistically, KIFC3 overexpression promoted β-catenin signaling in KYSE450 cells; however, the role of KIFC3 was abolished by XAV-939, the inhibitor of β-catenin signaling. KIFC3 was overexpressed in ESCC and was associated with poor prognosis. Furthermore, KIFC3 promoted proliferation, migration and invasion of ESCC via β-catenin signaling and EMT.
Huiling Liao, Lan Zhang, Shimin Lu, Wei Li,
Published: 22 June 2022
Frontiers in Genetics, Volume 13; https://doi.org/10.3389/fgene.2022.848926

Abstract:
Background: KIFC3, belongs to kinesin superfamily proteins (KIFs), is well known for its role in intracellular cargo movement. KIFC3 has been identified as a docetaxel resistance gene in breast cancer cells, however, the role of KIFC3 and its potential mechanism in colorectal cancer (CRC) remains elusive.Objectives: We aims to investigate the effects of KIFC3 in proliferation, migration, and invasion in CRC as well as the potential mechanism inside.Methods: We investigated the expression of KIFC3 in the Oncomine, Gene Expression Profiling Interactive Analysis databases. The KIFC3 protein expression and mRNA level in CRC cells were evaluated by western blot and qRT-PCR. Cell proliferation ability was detected by CCK-8, EdU, colony formation assay and xenograft tumor in nude mice. Flow cytometry was used to detect the cell cycle. The effect of KIFC3 on the epithelial-to-mesenchymal transition (EMT) was investigated by transwell and wound healing assay. The association of KIFC3 with EMT and PI3K/AKT/mTOR signaling pathway were measured by western blot and immunofluorescence staining.Results: The expression of KIFC3 was higher in CRC tissues than normal colorectal tissue, and was negatively correlated with the overall survival of patients with CRC. KIFC3 silencing inhibited the proliferation, migration and invasion of CRC cells. Meanwhile, it could decrease the number of cells in S phase. KIFC3 silencing inhibited the expression of proliferating cell nuclear antigen, Cyclin A2, Cyclin E1, and CDK2 and increased the expression of p21 and p53. KIFC3 overexpression promoted the G1/S phase transition. KIFC3 silencing inhibited the EMT process, which decreased the level of N-cadherin, Vimentin, SNAIL 1, TWIST, MMP-2, MMP-9 and increased E-cadherin, while KIFC3 overexpression show the opposite results. Furthermore, the knockdown of KIFC3 suppressed the EMT process by modulating the PI3K/AKT/mTOR signaling pathway. KIFC3 silencing decreased the expression of phosphorylated PI3K, AKT, mTOR, but total PI3K, AKT, mTOR have no change. Inversely, the upregulation of KIFC3 increased the expression of phosphorylated PI3K, AKT and mTOR, total PI3K, AKT, mTOR have no change. In a xenograft mouse model, the depletion of KIFC3 suppressed tumor growth. the increased expression levels of KIFC3 could enhance the proliferation, migration and invasion of CRC cells, and enhance the EMT process through the PI3K/AKT/mTOR pathway.Conclusion: Our study substantiates that KIFC3 can participate in the regulation of CRC progression by which regulates EMT via the PI3K/AKT/mTOR axis.
Lei-Bo Wang, Xue-Bin Zhang, Jun Liu, Qing-Jun Liu
Published: 8 April 2022
Frontiers in Genetics, Volume 13; https://doi.org/10.3389/fgene.2022.858882

Abstract:
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.
Jinglin Mi, Shanshan Ma, Wei Chen, Min Kang, Meng Xu, Chang Liu, Bo Li, Fang Wu, Fengju Liu, Yong Zhang, et al.
Published: 11 March 2022
Frontiers in Oncology, Volume 12; https://doi.org/10.3389/fonc.2022.772816

Abstract:
Background: KIF15 plays a vital role in many biological processes and has been reported to influence the occurrence and development of certain human cancers. However, there are few systematic evaluations on the role of KIF15 in human cancers, and the role of KIF15 in the diagnosis and prognosis of nasopharyngeal carcinoma (NPC) also remains unexplored. Therefore, this study aimed to conduct a pan-cancer analysis of KIF15 and evaluate its diagnostic and prognostic potential in NPC.Methods: The expression pattern, prognostic value, molecular function, tumor mutation burden, microsatellite instability, and immune cell infiltration of KIF15 were examined based on public databases. Next, the diagnostic value of KIF15 in NPC was analyzed using the Gene Expression Omnibus (GEO) database and immunohistochemistry (IHC). Kaplan–Meier curves, Cox regression analyses, and nomograms were used to evaluate the effects of KIF15 expression on NPC prognosis. Finally, the effect of KIF15 on NPC was explored by in vitro experiments.Results: The expression of KIF15 was significantly upregulated in 20 out of 33 cancer types compared to adjacent normal tissue. Kyoto Encyclopedia of Genes and Genomes enrichment (KEGG) analysis showed that KIF15 could participate in several cancer-related pathways. The increased expression level of KIF15 was correlated with worse clinical outcomes in many types of human cancers. Additionally, KIF15 expression was related to cancer infiltration of immune cells, tumor mutation burden, and microsatellite instability. In the analysis of NPC, KIF15 was significantly upregulated based on the GEO database and immunohistochemistry. A high expression of KIF15 was negatively associated with the prognosis of patients with NPC. A nomogram model integrating clinical characteristics and KIF15 expression was established, and it showed good predictive ability with an area under the curve value of 0.73. KIF15 knockdown significantly inhibited NPC cell proliferation and migration.Conclusions: Our findings revealed the important and functional role of KIF15 as an oncogene in pan-cancer. Moreover, high expression of KIF15 was found in NPC tissues, and was correlated with poor prognosis in NPC. KIF15 may serve as a potential therapeutic target in NPC treatment.
Hong‐Cheng Lv, Yan‐Yan Lv, Gang Wang, Xie‐Hua Zhang, Sheng‐Nan Li, Xiao‐Fen Yue,
Published: 20 January 2022
The Kaohsiung Journal of Medical Sciences; https://doi.org/10.1002/kjm2.12499

The publisher has not yet granted permission to display this abstract.
Dan Li, Tao Yu, Jingjing Han, Xu Xu, Jie Wu, Wei Song, Gang Liu, Hua Zhu,
Published: 17 January 2022
Frontiers in Molecular Biosciences, Volume 8; https://doi.org/10.3389/fmolb.2021.799651

Abstract:
As one of the members of the kinesin family, the role and potential mechanism of kinesin family member C1 (KIFC1) in the development of liver hepatocellular carcinoma (LIHC), especially in the immune infiltration, have not been fully elucidated. In this study, multiple databases and immunohistochemistry were employed to analyze the role and molecular mechanism including the immune infiltration of KIFC1 in LIHC. Generally, KIFC1 mRNA expression was overexpressed in LIHC tissues than normal tissues, and its protein was also highly expressed in the LIHC. KIFC1 mRNA expression was correlated with tumor grade and TNM staging, which was negatively correlated with overall survival and disease-free survival. Moreover, univariable and multivariate Cox analysis revealed that upregulated KIFC1 mRNA is an independent prognostic factor for LIHC. The KIFC1 promoter methylation level was negatively associated with KIFC1 mRNA expression and advanced stages and grade in LIHC. The different methylation sites of KIFC1 had a different effect on the prognosis of LIHC. Specifically, the KIFC1 mRNA expression level showed intense correlation with tumor immunity, such as tumor-infiltrating immune cells and immune scores as well as multiple immune-related genes. Moreover, KIFC1 co-expressed with some immune checkpoints and related to the responses to immune checkpoint blockade (ICB) and chemotherapies. Significant GO analysis showed that genes correlated with KIFC1 served as catalytic activity, acting on DNA, tubulin binding, histone binding, ATPase activity, and protein serine/threonine kinase activity. KEGG pathway analysis showed that these genes related to KIFC1 are mainly enriched in signal pathways such as cell cycle, spliceosome, pyrimidine metabolism, and RNA transport. Conclusively, KIFC1 was upregulated and displayed a prognostic value in LIHC. Moreover, KIFC1 may be involved in the LIHC progression partially through immune evasion and serve as a predictor of ICB therapies and chemotherapies.
Lingwei Wang, Gang Liu, Enkhbat Bolor-Erdene, Qinchuan Li, Yunqing Mei, Lei Zhou
Published: 14 November 2021
Journal: Aging
Aging, Volume 13, pp 24050-24070; https://doi.org/10.18632/aging.203585

Jing Chen, Cui-Cui Zhao, Fei-Ran Chen, Guo-Wei Feng, Fei Luo,
Published: 11 November 2021
Biomed Research International, Volume 2021, pp 1-12; https://doi.org/10.1155/2021/8249293

Abstract:
Background. Pancreatic cancer is a malignant tumor of the digestive tract, which is difficult to diagnose and treat due to bad early diagnosis. We aimed to explore the role of kinesin superfamily 4A (KIF4A) in pancreatic ductal adenocarcinoma (PDAC). Methods. We first used the bioinformatic website to screen the data of pancreatic cancer in TCGA, and KIF4A protein was detected among the 86 specimens of patients in our hospital combined with clinic-pathological characteristics and survival analysis. KIF4A loss-expression cell lines were established by RNA interference (RNAi). In addition, we performed in vitro cell assays to detect the changes in cell proliferation, migration, and invasion. The proteins involved in the proliferation and metastasis of cancer cells were also detected by western blot. The above results could be proved in vivo. Further, the correlation between KIF4A and CDC5L was analyzed by TCGA and IHC data. Results. We first found a high expression of KIF4A in pancreatic cancer, suggesting a role of KIF4A in the development of pancreatic cancer. KIF4A was found to be differentially expressed ( P<0.05 ) among the 86 specimens of patients in our hospital and was significantly associated with PDAC TNM stages and tumor size. High KIF4A expression also significantly worsened overall survival (OS) and disease-free survival rate (DFS) ( P<0.05 , respectively). In addition, cell proliferation, migration, and invasion were inhibited by the KIF4A-shRNA group compared with the control ( P<0.05 , respectively). In the end, knockdown of KIF4A could inhibit tumor development and metastasis in vivo. Further, the positive correlation between KIF4A and CDC5L existed, and KIF4A might promote pancreatic cancer proliferation by affecting CDC5L expression. Conclusion. In conclusion, the high expression level of KIF4A in PDAC was closely related to poor clinical and pathological status, lymphatic metastasis, and vascular invasion. KIF4A might be involved in promoting the development of PDAC in vitro and in vivo, which might be a new therapeutic target of PDAC.
Qiuyu Lin, Qianle Qi, Sen Hou, Zhen Chen, Nan Jiang, Laney Zhang,
Published: 25 September 2021
Journal: Tissue and Cell
Tissue and Cell, Volume 73; https://doi.org/10.1016/j.tice.2021.101655

The publisher has not yet granted permission to display this abstract.
Qian Ding, Caihua Jiang, Yajing Zhou, Jianping Duan, Jianming Lai, Min Jiang, Dongdong Lin
Published: 7 September 2021
Bioscience, Biotechnology, and Biochemistry, Volume 85, pp 2241-2249; https://doi.org/10.1093/bbb/zbab154

Abstract:
The current work was intended to explore the function and mechanism of Kinesin family member 2C (KIF2C) in hepatocellular carcinoma (HCC). In this study, KIF2C expression was at a high level in HCC and indicated poor prognosis. Silencing KIF2C significantly suppressed the proliferation, migration, and invasion in HCC cells. Furthermore, silencing KIF2C markedly decreased the expression of Snail, Vimentin, p-MEK, and p-ERK, but increased E-cadherin expression in HCC cells. Moreover, we also found that MEK/ERK inhibitor U0126 could enhance the impact on cell proliferation, migration, and invasion induced by silencing KIF2C in HCC. On the contrary, MEK/ERK activator PAF could weaken the impact induced by silencing KIF2C in HCC. Thus, our findings indicate that KIF2C can promote the proliferation, migration, and invasion by activating MEK/ERK pathway in HCC.
Zhiqin Chen, Haifei Song, Xiaochen Zeng, , Yong Gao
Published: 20 August 2021
G3 Genes|genomes|genetics, Volume 11; https://doi.org/10.1093/g3journal/jkab296

Abstract:
The prognosis of pancreatic cancer is poor because patients are usually asymptomatic in the early stage and the early diagnostic rate is low. Therefore, in the present study, we aimed to identify potential prognosis-related genes in pancreatic cancer to improve diagnosis and the outcome of patients. The mRNA expression profile data from The Cancer Genome Atlas database and GSE79668, GSE62452, and GSE28735 datasets from Gene Expression Omnibus were downloaded. The prognosis-relevant genes and clinical factors were analyzed using Cox regression analysis and the optimal gene sets were screened using the Cox proportional model. Next, the Kaplan-Meier survival analysis was used to evaluate the relationship between risk grouping and patient prognosis. Finally, an optimal gene-based prognosis prediction model was constructed and validated using a test dataset to discriminate the model accuracy and reliability. The results showed that 325 expression variable genes were identified, and 48 prognosis-relevant genes and three clinical factors, including lymph node stage (pathologic N), new tumor, and targeted molecular therapy were preliminary obtained. In addition, a gene set containing 16 optimal genes was identified, and included FABP6, MAL, KIF19, and REG4, which were significantly associated with the prognosis of pancreatic cancer. Moreover, a prognosis prediction model was constructed and validated to be relatively accurate and reliable. In conclusion, a gene set consisting of 16 prognosis-related genes was identified and a prognosis prediction model was constructed, which is expected to be applicable in the clinical diagnosis and treatment guidance of pancreatic cancer in the future.
Ting Gui, Chenhe Yao, Binghan Jia, Keng Shen
Published: 18 June 2021
Journal: PLOS ONE
Abstract:
Background: Though considerable efforts have been made to improve the treatment of epithelial ovarian cancer (EOC), the prognosis of patients has remained poor. Identifying differentially expressed genes (DEGs) involved in EOC progression and exploiting them as novel biomarkers or therapeutic targets is of great value. Methods: Overlapping DEGs were screened out from three independent gene expression omnibus (GEO) datasets and were subjected to Gene ontology (GO) and Kyoto encyclopedia of genes and genomes (KEGG) pathway enrichment analyses. The protein-protein interactions (PPI) network of DEGs was constructed based on the STRING database. The expression of hub genes was validated in GEPIA and GEO. The relationship of hub genes expression with tumor stage and overall survival and progression-free survival of EOC patients was investigated using the cancer genome atlas data. Results: A total of 306 DEGs were identified, including 265 up-regulated and 41 down-regulated. Through PPI network analysis, the top 20 genes were screened out, among which 4 hub genes, which were not researched in depth so far, were selected after literature retrieval, including CDC45, CDCA5, KIF4A, ESPL1. The four genes were up-regulated in EOC tissues compared with normal tissues, but their expression decreased gradually with the continuous progression of EOC. Survival curves illustrated that patients with a lower level of CDCA5 and ESPL1 had better overall survival and progression-free survival statistically. Conclusion: Two hub genes, CDCA5 and ESPL1, identified as probably playing tumor-promotive roles, have great potential to be utilized as novel therapeutic targets for EOC treatment.
Peng Zhang, Jing Feng, Xue Wu, Weike Chu, Yilian Zhang, Ping Li
Published: 26 March 2021
Pathology and Oncology Research, Volume 27; https://doi.org/10.3389/pore.2021.588532

Abstract:
Background and Objective: Hepatocellular carcinoma (HCC) is a highly aggressive malignant tumor of the digestive system worldwide. Chronic hepatitis B virus (HBV) infection and aflatoxin exposure are predominant causes of HCC in China, whereas hepatitis C virus (HCV) infection and alcohol intake are likely the main risk factors in other countries. It is an unmet need to recognize the underlying molecular mechanisms of HCC in China.Methods: In this study, microarray datasets (GSE84005, GSE84402, GSE101685, and GSE115018) derived from Gene Expression Omnibus (GEO) database were analyzed to obtain the common differentially expressed genes (DEGs) by R software. Moreover, the gene ontology (GO) functional annotation and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis were performed by using Database for Annotation, Visualization and Integrated Discovery (DAVID). Furthermore, the protein-protein interaction (PPI) network was constructed, and hub genes were identified by the Search Tool for the Retrieval of Interacting Genes (STRING) and Cytoscape, respectively. The hub genes were verified using Gene Expression Profiling Interactive Analysis (GEPIA), UALCAN, and Kaplan-Meier Plotter online databases were performed on the TCGA HCC dataset. Moreover, the Human Protein Atlas (HPA) database was used to verify candidate genes’ protein expression levels.Results: A total of 293 common DEGs were screened, including 103 up-regulated genes and 190 down-regulated genes. Moreover, GO analysis implied that common DEGs were mainly involved in the oxidation-reduction process, cytosol, and protein binding. KEGG pathway enrichment analysis presented that common DEGs were mainly enriched in metabolic pathways, complement and coagulation cascades, cell cycle, p53 signaling pathway, and tryptophan metabolism. In the PPI network, three subnetworks with high scores were detected using the Molecular Complex Detection (MCODE) plugin. The top 10 hub genes identified were CDK1, CCNB1, AURKA, CCNA2, KIF11, BUB1B, TOP2A, TPX2, HMMR and CDC45. The other public databases confirmed that high expression of the aforementioned genes related to poor overall survival among patients with HCC.Conclusion: This study primarily identified candidate genes and pathways involved in the underlying mechanisms of Chinese HCC, which is supposed to provide new targets for the diagnosis and treatment of HCC in China.
Weihua Zhu, Lixin Ru,
Published: 12 March 2021
Frontiers in Oncology, Volume 11; https://doi.org/10.3389/fonc.2021.626654

Abstract:
Purpose Hepatocellular carcinoma (HCC) is a common solid-tumor malignancy with high heterogeneity, and accurate prognostic prediction in HCC remains difficult. This analysis was performed to find a novel prognostic multigene signature. Methods The TCGA-LIHC dataset was analyzed for differentially coexpressed genes through weighted gene coexpression network analysis (WGCNA) and differential gene expression analysis. A protein-protein interaction (PPI) network and univariate Cox regression analysis of overall survival (OS) were utilized to identify their prognostic value. Next, we used least absolute shrinkage and selection operator (LASSO) Cox regression to establish a prognostic module. Subsequently, the ICGC-LIRI-JP dataset was applied for further validation. Based on this module, HCC cases were stratified into high-risk and low-risk groups, and differentially expressed genes (DEGs) were identified. Functional enrichment analyses of these DEGs were conducted. Finally, single-sample gene set enrichment analysis (ssGSEA) was performed to explore the correlation between the prognostic signature and immune status. Results A total of 393 differentially coexpressed genes were obtained. Forty differentially coexpressed hub genes were identified using the CytoHubba plugin, and 38 of them were closely correlated with OS. Afterward, we established the four-gene prognostic signature with an acceptable accuracy (area under the curve [AUC] of 1-year survival: 0.739). The ICGC-LIRI-JP dataset also supported the acceptable accuracy (AUC of 1-year survival:0.752). Compared with low-risk cohort, HCC cases in the high-risk cohort had shorter OS, higher tumor grades, and higher T stages. The risk scores of this signature still act as independent predictors of OS (P<0.001). Functional enrichment analyses suggest that it was mainly organelle fission and nuclear division that were enriched. Finally, ssGSEA revealed that this signature is strongly associated with the immune status of HCC patients. Conclusions The proposed prognostic signature of four differentially coexpressed hub genes has satisfactory prognostic ability, providing important insight into the prediction of HCC prognosis.
Yuqin Tang, Yongqiang Zhang,
Published: 8 December 2020
Biomed Research International, Volume 2020, pp 1-19; https://doi.org/10.1155/2020/4251761

Abstract:
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.
Ding Cui, Yang Liu, Junyan Ma, Kaiqing Lin, Kaihong Xu,
Published: 7 December 2020
Journal: Peerj
Abstract:
The purpose of this study was to integrate the existing expression profile data on endometriosis (EM)-related tissues in order to identify the differentially expressed genes. In this study, three series of raw expression data were downloaded from GEO database. Differentially expressed genes (DEGs) in three tissue types were screened. GO, KEGG pathway enrichment analysis, core differential genes (CDGs) protein–protein interaction (PPI) network and weighted gene co-expression network analysis (WGCNA) were performed, finally, the dysregulation of Hippo pathway in ectopic endometrium (EC) was detected by Western blotting. A total of 1,811 DEGs between eutopic (EU) and normal endometrium (NE), 5,947 DEGs between EC and EU, and 3,192 DEGs between EC and NE datasets were identified. After screening, 394 CDGs were obtained, and 5 hub genes identified in the PPI network. CDGs enrichment and WGCNA network analysis revealed cell proliferation, differentiation, migration and other biological processes, Hippo and Wnt signaling pathways, and a variety of tumor-related pathways. Western blotting results showed that YAP/TAZ was upregulated, and MOB1, pMOB1, SAV1, LATS1 and LATS2 were downregulated in EC. Moreover, CDGs, especially the hub genes, are potential biomarkers and therapeutic targets. Finally, the Hippo pathway might play a key role in the development of endometriosis.
Xiaofei Wang, Jie Qiao,
Published: 13 November 2020
Bioscience Reports, Volume 40; https://doi.org/10.1042/bsr20203263

Abstract:
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.
Zhe-Xiang Wang, Shao-Chun Ren, Zi-Song Chang,
Published: 3 November 2020
Biomed Research International, Volume 2020, pp 1-9; https://doi.org/10.1155/2020/7102757

Abstract:
Background. Osteosarcoma is known as a type of common human bone malignancy, and more therapeutic targets are still required to combat this disease. In recent years, the involvement of KIF2A in cancer progression has been widely revealed; however, its potential effect on osteosarcoma development remains unknown. This study is to assess the KIF2A expression levels in human osteosarcoma tissues and explore its potential role in osteosarcoma development. Methods. Immunohistochemical (IHC) assays were conducted to evaluate the expression levels of KIF2A in a total of 74 samples of osteosarcoma tissues and adjacent nontumor tissues. According to the staining intensity in tumor tissues, patients were divided into highly expressed and low expression KIF2A groups. The possible links between the KIF2A expression and the clinical pathological features were explored and analyzed, and the effects of KIF2A on osteosarcoma cell proliferation, migration, and invasion were detected through colony formation assay, MTT assay, wound closure assay, and transwell assay, respectively. The effects of KIF2A on tumor growth and metastasis were detected by the use of animal models. Results. KIF2A was highly expressed in human osteosarcoma tissues. Meanwhile, KIF2A was obviously correlated to the tumor size ( P = 0.001 ∗ ) and clinical stage ( P = 0.014 ∗ ) of osteosarcoma patients. Our results also revealed that the ablation of KIF2A dramatically blocked the proliferation, migration, and invasion capacity of osteosarcoma cells in vitro and blocked tumor growth and metastasis in mice. Conclusions. We investigated the involvement of KIF2A in the development and metastasis of osteosarcoma and therefore thought KIF2A as a promising therapeutic target for osteosarcoma treatment.
Lisa M. Pinatti Bs, Hana N. Sinha, Collin V. Brummel Ba, Christine M. Goudsmit Bs, Timothy J. Geddes Bs, , Jan A. Akervall Md, , Heather M. Walline,
Published: 19 October 2020
Journal: Head & Neck
Head & Neck, Volume 43, pp 544-557; https://doi.org/10.1002/hed.26501

The publisher has not yet granted permission to display this abstract.
Wei-Tian Liang, Xiao-Fang Liu, Hai-Bo Huang, Zi-Ming Gao,
World Journal of Gastrointestinal Oncology, Volume 12, pp 1104-1118; https://doi.org/10.4251/wjgo.v12.i10.1104

Abstract:
Kinesin super family 23 (KIF23) is a member of the KIF family, and it plays an important role in mitosis and cytokinesis. Loss of expression can cause mitotic arrest. The Oncomine database is one of the largest oncogene chip databases in the world, and is an integrated data mining platform for cancer gene information. By querying the database, differences in expression between tumor tissue and normal tissue can be determined. To study the expression and prognostic significance of KIF23 in gastric cancer (GC). We used immunohistochemistry to compare the expression of KIF23 in GC and normal gastric tissues. We mined the data on the expression and prognosis of KIF23 in GC using Oncomine and Kaplan–Meier plotter database. Compared with normal gastric tissues, KIF23 expression was increased in GC tissues, and correlated with T, N, and tumor–node–metastasis stages. Survival analysis showed that patients with high expression of KIF23 had a poor overall survival. There were five studies in the Oncomine database in which expression of KIF23 was significantly higher in GC tissues than in normal gastric tissues (P< 0.05). Kaplan–Meier plotter database analysis showed that recurrence-free survival, overall survival, distant metastasis free survival, and post progression survival of patients with high expression of KIF23 were lower than those of patients with low expression. Further stratified analysis found that prognostic survival indicators worsened in patients with T2 and T3 poorly differentiated adenocarcinoma with high expression of KIF23. KIF23 is highly expressed in GC and is associated with a poor prognosis of patients. It may be of great significance in the diagnosis, treatment, and prognostic evaluation of GC.
Wensi Liu, Zhaojin Yu, Haichao Tang, Xiangyi Wang, Bing Zhang, Jianhang Zhao, Xinli Liu, Jingdong Zhang,
Published: 8 October 2020
Journal: Ebiomedicine
Abstract:
Background Sarcomas are rare heterogeneous tumours, derived from primitive mesenchymal stem cells, with more than 100 distinct subtypes. Radioresistance remains a major clinical challenge for sarcomas, demanding urgent for effective biomarkers of radiosensitivity. Methods The radiosensitive gene Kinesin family member 18B (KIF18B) was mined through bioinformatics with integrating of 15 Gene Expression Omnibus (GEO) datasets and The Cancer Genome Atlas (TCGA) database. We used radiotherapy-sh-KIF18B combination to observe the anti-tumour effect in sarcoma cells and subcutaneous or orthotopic xenograft models. The KIF18B-sensitive drug T0901317 (T09) was further mined to act as radiosensitizer using the Genomics of Drug Sensitivity in Cancer (GDSC) database. Findings KIF18B mRNA was significantly up-regulated in most of the subtypes of bone and soft tissue sarcoma. Multivariate Cox regression analysis showed that KIF18B high expression was an independent risk factor for prognosis in sarcoma patients with radiotherapy. Silencing KIF18B or using T09 significantly improved the radiosensitivity of sarcoma cells, delayed tumour growth in subcutaneous and orthotopic xenograft model, and elongated mice survival time. Furthermore, we predicted that T09 might bind to the structural region of KIF18B to exert radiosensitization. Interpretation These results indicated that sarcomas with low expression of KIF18B may benefit from radiotherapy. Moreover, the radiosensitivity of sarcomas with overexpressed KIF18B could be effectively improved by silencing KIF18B or using T09, which may provide promising strategies for radiotherapy treatment of sarcoma. Fundings A full list of funding can be found in the Funding Sources section.
Xian-Chang Zeng, Lu Zhang, Wen-Jun Liao, Lu Ao, Ze-Man Lin, Wen Kang, Wan-Nan Chen,
Published: 30 September 2020
Frontiers in Genetics, Volume 11; https://doi.org/10.3389/fgene.2020.555537

Abstract:
Hepatocellular carcinoma (HCC) is one of the most lethal cancers globally. Hepatitis B virus (HBV) infection might cause chronic hepatitis and cirrhosis, leading to HCC. To screen prognostic genes and therapeutic targets for HCC by bioinformatics analysis and determine the mechanisms underlying HBV-related HCC, three high-throughput RNA-seq based raw datasets, namely GSE25599, GSE77509, and GSE94660, were obtained from the Gene Expression Omnibus database, and one RNA-seq raw dataset was acquired from The Cancer Genome Atlas (TCGA). Overall, 103 genes were up-regulated and 127 were down-regulated. A protein–protein interaction (PPI) network was established using Cytoscape software, and 12 pivotal genes were selected as hub genes. The 230 differentially expressed genes and 12 hub genes were subjected to functional and pathway enrichment analyses, and the results suggested that cell cycle, nuclear division, mitotic nuclear division, oocyte meiosis, retinol metabolism, and p53 signaling-related pathways play important roles in HBV-related HCC progression. Further, among the 12 hub genes, kinesin family member 11 (KIF11), TPX2 microtubule nucleation factor (TPX2), kinesin family member 20A (KIF20A), and cyclin B2 (CCNB2) were identified as independent prognostic genes by survival analysis and univariate and multivariate Cox regression analysis. These four genes showed higher expression levels in HCC than in normal tissue samples, as identified upon analyses with Oncomine. In addition, in comparison with normal tissues, the expression levels of KIF11, TPX2, KIF20A, and CCNB2 were higher in HBV-related HCC than in HCV-related HCC tissues. In conclusion, our results suggest that KIF11, TPX2, KIF20A, and CCNB2 might be involved in the carcinogenesis and development of HBV-related HCC. They can thus be used as independent prognostic genes and novel biomarkers for the diagnosis of HBV-related HCC and development of pertinent therapeutic strategies.
Zhonglin Cai,
Published: 1 September 2020
Oncotargets and Therapy, pp 9573-9586; https://doi.org/10.2147/ott.s268859

Abstract:
Abstract: Bladder cancer (BC) is the most common urinary system malignancy and is a serious threat to human health. Circular RNAs (circRNAs) are members of a newly defined class of noncoding RNAs (ncRNAs) that can regulate gene expression at the transcriptional or posttranscriptional level. Studies have shown that circRNAs are related to the clinicopathological characteristics, prognosis, and chemosensitivity of BC, and basic research has further confirmed that changes in the expression of circRNAs in BC are closely related to various tumor biological functions. CircRNAs promote tumor development by interacting with miRNAs to regulate transcription factors and both classical and nonclassical tumor signaling pathways. The nonclassical signaling pathways are related to cell cycle progression, epithelial–mesenchymal transition (EMT), extracellular matrix maintenance, and tumor stem cell maintenance. In this article, the relationships between circRNAs and the clinical characteristics of BC are reviewed, and the molecular mechanisms by which circRNAs promote tumor development are explored.
Ran Li, Liyan Shui, ,
Published: 13 August 2020
Frontiers in Genetics, Volume 11; https://doi.org/10.3389/fgene.2020.00906

Abstract:
Hepatocellular carcinoma (HCC) is one of the most prevalent life-threatening human cancers and the leading cause of cancer-related mortality, with increased global incidence within the last decade. Identification of effective diagnostic and prognostic biomarkers would enable reliable risk stratification and efficient screening of high-risk patients, thereby facilitating clinical decision-making. Herein, we performed a comprehensive, robust DNA methylation analysis based on genome-wide DNA methylation profiling. We constructed a diagnostic signature with five DNA methylation markers, which precisely distinguished HCC patients from normal controls. Cox regression and LASSO analysis were applied to construct a prognostic signature with four DNA methylation markers. A one-to-one correlation analysis was carried out between genes of the whole genome and our prognostic signature. Exploration of the biological function and the role of the underlying significantly correlated genes was conducted. A mixed dataset of 463 HCC patients and 253 normal controls, derived from six independent datasets, was used to valid the diagnostic signature. Results showed a specificity of 96.84% and sensitivity of 96.77%. Class scores for the diagnostic signature were significantly different between normal controls, individuals with liver diseases, and HCC patients. The present signature has the potential to serve as a biomarker to monitor health in normal controls. Additionally, HCC patients were successfully separated into low-risk and high-risk groups by the prognostic signature, with a better prognosis for patients in the low-risk group. Kaplan-Meier and ROC analysis confirmed that the prognostic signature performed well. We found eight of the top ten genes to positively correlate with risk scores of the prognostic signature, and to be involved in cell cycle regulation. This eight-gene panel also served as a prognostic signature. The robust evidence presented in this study therefore demonstrates the effectiveness of the prognostic signature. In summary, we constructed diagnostic and prognostic signatures, which have potential for use in diagnosis, surveillance, and prognostic prediction for HCC patients. Eight genes that were significantly and positively correlated with the prognostic signature were strongly associated with cell cycle processes. Therefore, the prognostic signature can be used as a guide by which to measure responsiveness to cell-cycle-targeting agents.
Published: 28 July 2020
International Journal of Genomics, Volume 2020, pp 1-18; https://doi.org/10.1155/2020/2061024

Abstract:
Chronic infection with hepatitis B virus (HBV) has long been recognized as a dominant hazard factor for hepatocellular carcinoma (HCC) and accounts for at least half of HCC instances globally. However, the underlying molecular mechanism of HBV-linked HCC has not been completely elucidated. Here, three microarray datasets, totally containing 170 tumoral samples and 181 adjacent normal tissues from the liver of patients suffering from HBV-related HCC assembled from the Gene Expression Omnibus (GEO) database, were subjected to integrated analysis of differentially expressed genes (DEGs). Subsequently, the analysis of function and pathway enrichment as well as the protein-protein interaction network (PPI) was performed. The ten hub genes screened out from the PPI network were further subjected to expression profile and survival analysis. Overall, 329 DEGs (67 upregulated and 262 downregulated) were identified. Ten DEGs with the highest degree of connectivity included cyclin-dependent kinase 1 (CDK1), cyclin B1 (CCNB1), cyclin B2 (CCNB2), PDZ-binding kinase (PBK), abnormal spindle microtubule assembly (ASPM), nuclear division cycle 80 (NDC80), aurora kinase A (AURKA), targeting protein for xenopus kinesin-like protein 2 (TPX2), kinesin family member 2C (KIF2C), and centromere protein F (CENPF). Kaplan-Meier analysis unveiled that overexpression levels of KIF2C and TPX2 were relevant to both the poor overall survival and relapse-free survival. In summary, the hub genes validated in the present study may provide promising targets for the diagnosis, prognosis, and therapy of HBV-associated HCC. Additionally, our work uncovers various crucial biological components (e.g., extracellular exosome) and signaling pathways that participate in the progression of HCC induced by HBV, serving comprehensive knowledge of the mechanisms regarding HBV-related HCC.
Jianxiong Tang, Jianxiao Zou, Xiaoran Zhang, Mei Fan, Qi Tian, Shuyao Fu, Shihong Gao,
Published: 15 May 2020
Journal: BMC Genomics
BMC Genomics, Volume 21, pp 1-15; https://doi.org/10.1186/s12864-020-6768-9

Abstract:
Background: The computational prediction of methylation levels at single CpG resolution is promising to explore the methylation levels of CpGs uncovered by existing array techniques, especially for the 450 K beadchip array data with huge reserves. General prediction models concentrate on improving the overall prediction accuracy for the bulk of CpG loci while neglecting whether each locus is precisely predicted. This leads to the limited application of the prediction results, especially when performing downstream analysis with high precision requirements. Results: Here we reported PretiMeth, a method for constructing precise prediction models for each single CpG locus. PretiMeth used a logistic regression algorithm to build a prediction model for each interested locus. Only one DNA methylation feature that shared the most similar methylation pattern with the CpG locus to be predicted was applied in the model. We found that PretiMeth outperformed other algorithms in the prediction accuracy, and kept robust across platforms and cell types. Furthermore, PretiMeth was applied to The Cancer Genome Atlas data (TCGA), the intensive analysis based on precise prediction results showed that several CpG loci and genes (differentially methylated between the tumor and normal samples) were worthy for further biological validation. Conclusion: The precise prediction of single CpG locus is important for both methylation array data expansion and downstream analysis of prediction results. PretiMeth achieved precise modeling for each CpG locus by using only one significant feature, which also suggested that our precise prediction models could be probably used for reference in the probe set design when the DNA methylation beadchip update. PretiMeth is provided as an open source tool via https://github.com/JxTang-bioinformatics/PretiMeth.
Yixin Sun,
Genetic Testing and Molecular Biomarkers, Volume 24, pp 296-308; https://doi.org/10.1089/gtmb.2019.0242

Abstract:
Background: Hepatocellular carcinoma (HCC) is one of the leading causes of cancer-related deaths worldwide. Patients suffering from HCC are usually diagnosed during an advanced stage, which limits the effectiveness of treatment. This phenomenon has led to an urgent need to discover promising HCC diagnostic biomarkers and to identify novel targets for HCC treatment. Materials and Methods: In this study, the gene expression profiles of the GSE45436 participants were downloaded from the Gene Expression Omnibus database. The HCC differentially expressed genes (HCC_DEGs) were identified through a comparison with healthy controls. The Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analyses were performed by DAVID, a free website used for annotating genes. Next, we used STRING, an online website, to identify likely protein–protein interactions among the DEGs. Cytoscape software was utilized to construct a protein–protein interaction network. MCODE, a plug-in of the Cytoscape software, was used for a module analysis. Finally, we used the Gene Expression Profiling Interactive Analysis website to determine the module genes' effects on overall survival. Results: A total of 313 genes were identified as differentially expressed, which comprised 118 upregulated genes and 195 downregulated genes. We used these data to identify 67 module genes. These were further verified using The Cancer Genome Atlas database resulting in 57 that remained statistically significant. Foremost, we identified one significant gene, DEP domain-containing protein 1B (DEPDC1B), which should be investigated for its usefulness as a new biomarker for diagnoses and prognoses. Conclusion: To our knowledge, DEPDC1B has not previously been reported as being associated with HCC. These results suggest that in silico methods, such as those employed, can provide valuable and even unique candidate biomarkers for further evaluation.
Dengchuan Wang, Jun Liu, Shengshuo Liu,
Published: 24 April 2020
Frontiers in Genetics, Volume 11; https://doi.org/10.3389/fgene.2020.00342

Abstract:
The dreadful prognosis of hepatocellular carcinoma (HCC) is primarily due to the low early diagnosis rate, rapid progression, and high recurrence rate. Valuable prognostic biomarkers are urgently needed for HCC. In this study, microarray data were downloaded from GSE14520, GSE22058, International Cancer Genome Consortium (ICGC), and The Cancer Genome Atlas (TCGA). Differentially expressed genes (DEGs) were identified among GSE14520, GSE22058, and ICGC databases. Weighted gene co-expression network analysis (WGCNA) was used to establish gene co-expression modules of DEGs, and genes of key modules were examined to identify hub genes using univariate Cox regression in the ICGC cohort. Expression levels and time-dependent receiver operating characteristic (ROC) and area under the curve (AUC) were determined to estimate the prognostic competence of the hub genes. These hub genes were also validated in the Gene Expression Profiling Interactive Analysis (GEPIA) and TCGA databases. TIMER algorithm and GSCALite database were applied to analyze the association of the hub genes with immunocytotic infiltration and their pathway enrichment. Altogether, 276 DEGs were identified and WGCNA described a unique and significantly DEGs-associated co-expression module containing 148 genes, with 10 hub genes selected by univariate Cox regression in the ICGC cohort (BIRC5, FOXM1, CENPA, KIF4A, DTYMK, PRC1, IGF2BP3, KIF2C, TRIP13, and TPX2). Most of the genes were validated in the GEPIA databases, except IGF2BP3. The results of multivariate Cox regression analysis indicated that the abovementioned hub genes are all independent predictors of HCC. The 10 genes were also confirmed to be associated with immune cell infiltration using the TIMER algorithm. Moreover, four-gene signature was developed, including BIRC5, CENPA, FOXM1, DTYMK. These hub genes and the model demonstrated a strong prognostic capability and are likely to be a therapeutic target for HCC. Moreover, the association of these genes with immune cell infiltration improves our understanding of the occurrence and development of HCC.
Lixian Ding, Bin Li, Xiaotong Yu, Zhongsheng Li, Xinglong Li, Shuwei Dang, Qiang Lv, Jiufeng Wei, Haixia Sun, Hongsheng Chen, et al.
Published: 15 April 2020
Cancer Cell International, Volume 20, pp 1-14; https://doi.org/10.1186/s12935-020-01199-7

Abstract:
Background Kinesin superfamily proteins (KIFs) can transport membranous organelles and protein complexes in an ATP-dependent manner. Kinesin family member 15 (KIF15) is overexpressed in various cancers. However, the function of KIF15 in gastric cancer (GC) is still unclear. Methods GC patients’ data from The Cancer Genome Atlas (TCGA) were analyzed by bioinformatics methods. The expression of KIF15 was examined in GC and paracarcinoma tissues from 41 patients to verify the analysis results. The relationship between KIF15 expression and clinical characteristics were also observed by bioinformatics methods. Kaplan–Meier survival analysis of 122 GC patients in our hospital was performed to explore the relationship between KIF15 expression levels and GC patients’ prognosis. KIF15 was downregulated in GC cell lines AGS and SGC-7901 by transfecting a lentivirus-mediated shRNA plasmid targeting KIF15. In vitro, GC cell proliferation and apoptosis were detected by MTT assay, colony formation assay, and Annexin V-APC staining. In vivo, xenograft experiments were used to verify the in vitro results. Furthermore, Human Apoptosis Antibody Array kit was used to screen possible targets of KIF15 in GC cell lines. Results The bioinformatics results showed that KIF15 expression levels were higher in GC tissues than in normal tissues. IHC showed same results. High expression of KIF15 was statistical correlated with high age and early histologic stage. Kaplan–Meier curves indicated that high KIF15 expression predict poor prognosis in patients with GC. MTT assay and colony formation assay showed that KIF15 promote GC cell proliferation. Annexin V-APC staining found that KIF15 can inhibit GC cell apoptosis. Xenograft experiments reveal that downregulating KIF15 can inhibit GC tumor growth and promote GC apoptosis. Through detection of 43 anti-apoptotic proteins by the Human Apoptosis Antibody Array kit, it was confirmed that knocking down KIF15 can reduce seven anti-apoptotic proteins expression. Conclusions Taken together, our study revealed a critical role for KIF15 to inhibit GC cell apoptosis and promote GC cell proliferation. KIF15 may decrease anti-apoptotic proteins expression by regulating apoptosis pathways. High expression of KIF15 predicts a poor prognosis in patients with GC. KIF15 might be a novel prognostic biomarker and a therapeutic target for GC.
Xiaoting Wang, Shouzi Hu, Wenbin Ji, Yan Tang,
Published: 13 April 2020
Journal of International Medical Research, Volume 48; https://doi.org/10.1177/0300060520912139

Abstract:
To identify genes associated with the clinicopathological features of colorectal cancer (CRC). Gene expression profiles were downloaded and preprocessed by GEOquery and affy R packages, respectively. The limma package was applied to identify the differentially expressed genes (DEGs) in CRC. Gene Ontology and Kyoto Gene and Genome Encyclopedia (KEGG) pathway enrichment analyses for the DEGs were carried out using the clusterProfiler package. Protein–protein interaction (PPI) and weighted gene co-expression (WGC) networks were constructed using the STRING database and WGCNA package, respectively. A total of 523 DEGs (283 downregulated and 240 upregulated genes) in CRC tissues were identified. These DEGs were mainly enriched in 111 biological processes, 16 cellular components and 40 molecular functions, such as proteinaceous extracellular matrix, extracellular structure organization and chemokine-mediated signalling pathway. PPI and WGC networks showed that four upregulated genes (KIF2C, CDC45, CEP55 and DTL) were key genes. Subgroup analysis based on individual cancer stages and histological subtypes indicated that the expression of these key genes was upregulated in CRC stages I–IV, adenocarcinoma and mucinous adenocarcinoma. The study provides new insights into understanding the pathogenesis of CRC. These identified genes may act as potential targets for CRC diagnosis and treatment.
Mike Wagenbach, , Yulia Ovechkina, Sarah Domnitz, Linda Wordeman
Molecular Biology of the Cell, Volume 31, pp 580-588; https://doi.org/10.1091/mbc.e19-09-0503

Abstract:
MCAK/Kif2C is a microtubule-depolymerizing kinesin. Its activity can be rapidly quantified in fluorescently labeled cells using Cell Profiler. This method was used to interrogate MCAK/Kif2C missense mutations catalogued in the cBioPortal database. A majority of the mutations tested are deleterious and likely to increase karyotype evolution in cancer.
Junjie Zhang, Weiyang Lou
Published: 17 March 2020
Frontiers in Oncology, Volume 10; https://doi.org/10.3389/fonc.2020.00340

Abstract:
Growing evidence has illustrated critical roles of competing endogenous RNA (ceRNA) regulatory network in human cancers including hepatocellular carcinoma. In this study, we aimed to find promising diagnostic and prognostic biomarkers for patients with hepatocellular carcinoma. Three novel unfavorable prognosis-associated genes (CELSR3, GPSM2, and CHEK1) was first identified. We also demonstrated that these genes were significantly upregulated in hepatocellular carcinoma cell lines and tissues. Next, 154 potential miRNAs of CELSR3, GPSM2, and CHEK1 were predicted. CHEK1-hsa-mir-195-5p/hsa-mir-497-5p and GPSM2-hsa-mir-122-5p axes were defined as two key pathways in carcinogenesis of hepatocellular carcinoma by combination of in silico analysis and experimental validation. Subsequently, lncRNAs binding to hsa-mir-195-5p, hsa-mir-497-5p, and hsa-mir-122-5p were predicted via starBase and miRNet databases. After performing expression analysis and survival analysis for these predicted lncRNAs, we showed that nine lncRNAs (SNHG1, SNHG12, LINC00511, HCG18, FGD5-AS1, CERS6-AS1, NUTM2A-AS1, SNHG16, and ASB16-AS1) were markedly increased in hepatocellular carcinoma and their upregulation indicated poor prognosis. Moreover, a similar mRNA-miRNA-lncRNA analysis for six “known” genes (CLEC3B, DNASE1L3, PTTG1, KIF2C, XPO5, and UBE2S) was performed. Subsequently, a comprehensive mRNA-miRNA-lncRNA triple ceRNA network linked to prognosis of patients with hepatocellular carcinoma was established. Moreover, all RNAs in this network exhibited significantly diagnostic values for patients with hepatocellular carcinoma. In summary, the current study constructed a mRNA-miRNA-lncRNA ceRNA network associated with diagnosis and prognosis of hepatocellular carcinoma.
Guo‐Pei Zhang, Shun‐Li Shen, Yang Yu, Xiao Yue, Wen‐Jie Hu, Shao‐Qiang Li
Published: 14 February 2020
Journal of Cellular Biochemistry, Volume 121, pp 4419-4430; https://doi.org/10.1002/jcb.29665

Abstract:
Kinesin family member 2C (KIF2C), a substantial mitotic regulator, has been verified to exert a malignant function in several cancers. However, its function in hepatocellular carcinoma (HCC) remains unclear. In this study, the expression profile of KIF2C in HCC was characterized through the dataset from the TCGA and clinical tissue microarrays containing 220 pairs of resected HCC tissues and adjacent nontumor tissues in our hospital. The results indicated that KIF2C was substantially higher expression in tumor tissues than adjacent nontumor tissues. High expression of KIF2C significantly correlated with large tumor (>5.0 cm) (P = .001) and implied a dismal postoperative overall survival (OS) (hazard ratio [HR] = 1.729; P = .002) in our cohort of patients. Gain and loss of function assays displayed that KIF2C promoted HCC cell proliferation, accelerated cell cycle progression, and impeded apoptosis. By bioinformatic tools and mechanistic investigation, we found that KIF2C interacted with various cell‐cycle‐related proteins and was significantly involved in growth‐promoting pathways. KIF2C upregulated PCNA and CDC20 expression. Subsequently, we investigated the regulation of KIF2C by competing endogenous RNA and elucidated that has‐miR‐6715a‐3p was directly bond to the 3′‐untranslated region of KIF2C through dual luciferase assays, thereby inhibiting KIF2C expression. Furthermore, the long noncoding RNA GS1‐358P8.4 was found to be a candidate of KIF2C for has‐miR‐6715a‐3p binding. HCC patients with high lncRNA‐GS1‐358P8.4 expression had shorter OS and relapse‐free survival compared to those with low expression, which was accordance with the KIF2C. Taken together, KIC2C aggravated HCC progression, it could serve as a prognostic indicator and confer a novel target for clinical treatment.
Huijuan Zeng, , Duanyang Zhai, Jiong Bi, Xiaying Kuang, Sihong Lu, Zhen Shan, Ying Lin
International Journal of Biological Sciences, Volume 16, pp 2084-2093; https://doi.org/10.7150/ijbs.44204

Abstract:
Breast cancer (BC) is one of the most common female cancers, and its incidence has been increasing in recent years. Although treatments are continuously improving, the prognosis of patients in the advanced stage is still unsatisfactory. Thus, an in-depth understanding of its molecular mechanisms is necessary for curing breast cancer. KIF15 is a tetrameric spindle motor which can regulate mitosis in cellular process and exert the crucial functions in several cancers. The purpose of our research was to investigate the functions of KIF15 in breast cancer. We tested the expression of KIF15 in breast cancer tissues and the survival rate of breast cancer patients with high or low level of KIF15 through TCGA data. What's more, western blot and immunohistochemistry assay were utilized to evaluate the protein level and mRNA level of KIF15 in breast cancer tissues. Then CCK-8, wound healing, transwell and flow cytometry experiments were adopted separately to test cell viability, migration, invasion and cell cycle distribution. We discovered that KIF15 was highly expressed in breast cancer tissues and high level KIF15 was associated with a low survival rate of breast cancer patients. Moreover, silence of KIF15 suppressed cell viability, migration, invasion and cell cycle distribution. Following, we discovered that ZNF367 was the upstream transcription factor of KIF15. In addition, silenced ZNF367 could also repress the growth of breast cancer cells. And rescue experiments indicated that overexpressed KIF15 could counteract the inhibition effect of silencing ZNF367 on the progression of breast cancer. Importantly, we discovered that KIF15 and ZNF367 were associated with the regulation of cell cycle. In short, ZNF367-activated KIF15 accelerated the progression of breast cancer by regulating cell cycle progress.
Qingchun Zhou, Juan Yu, QingYou Zheng, Tao Wu, Ziliang Ji,
Published: 27 November 2019
Journal: Febs Open Bio
Febs Open Bio, Volume 11, pp 1487-1496; https://doi.org/10.1002/2211-5463.12768

Abstract:
Bladder cancer is one of the most common malignant tumors of the urinary system, with high morbidity and mortality. At present, the survival rates and prognosis of patients with bladder cancer are still relatively low, and thus there remains a need to improve prognosis by identifying novel targets. Kinesins (Kinesin super family proteins) are a series of microtubule‐based motor proteins which mediate various types of cellular processes. Kinesin family member 3A (KIF3A) is critical for cytoplasm separation in mitosis, and has been reported to be misexpressed in multiple types of cancers. However, its effects on the progression and development of bladder cancer remain unclear. Herein, we report that KIF3A is highly expressed in human bladder cancer. We identified a significant correlation between KIF3A and clinical features, including clinical stage (*p=0.047), pathologic tumor status (*p=0.045), lymph node status (*p=0.041), and metastasis (*p=0.035). KIF3A expression was also correlated with poor prognosis of patients with bladder cancer. Our results further indicated that KIF3A ablation resulted in cell cycle arrest and blocked the proliferation, migration and invasion of bladder cancer cells in vitro, and restrained tumor growth in mice in a microtubule‐dependent manner. In summary, our findings suggest that KIF3A is a potential therapeutic target for bladder cancer.
, Rao Du, Huan Gui, Mi Zhou, Wen Zhong, Chenmei Mao,
Published: 6 November 2019
Journal: Oncology Reports
Oncology Reports, Volume 43, pp 133-146; https://doi.org/10.3892/or.2019.7400

Abstract:
Hepatocellular carcinoma (HCC) is the fourth leading cause of cancer‑related deaths among cancer patients. Genes correlated with the progression and prognosis of HCC are critically needed to be identified. In the present study, 3 Gene Expression Omnibus (GEO) datasets (GSE46408, GSE65372 and GSE84402) were used to analyze the differentially expressed genes (DEGs) between HCC and non‑tumor liver tissues. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were conducted to clarify the functional roles of DEGs. A protein‑protein interaction network was established to screen the hub genes associated with HCC. The prognostic values of hub genes in HCC patients were analyzed using The Cancer Genome Atlas (TCGA) database. The expression levels of hub genes were validated based on ONCOMINE, TCGA and Human Protein Atlas (HPA) databases. Notably, 56 upregulated and 33 downregulated DEGs were markedly enriched under various GO terms and four KEGG terms. Among these DEGs, 10 hub genes with high connectivity degree were identified, including cyclin B1, cyclin A2, cyclin B2, condensin complex subunit 3, PDZ binding kinase, nucleolar and spindle‑associated protein 1, aurora kinase A, ZW10 interacting kinetochore protein, protein regulator of cytokinesis 1 and kinesin family member 4A. The upregulated expression levels of these hub genes in HCC tissues were further confirmed by ONCOMINE, TCGA, and HPA databases. Additionally, the increased mRNA expression of each hub gene was related to the unfavorable disease‑free survival and overall survival of HCC patients. The present study identified ten genes associated with HCC, which may help to provide candidate targets for the diagnosis and treatment of HCC.
Xing Li, Kunpeng Shu, Zhifeng Wang, Degang Ding
Published: 1 November 2019
Journal: Medicine
Abstract:
Background: The kinesin family (KIF) is reported to be aberrantly expressed and significantly correlated with survival outcomes in patients with various cancers. This meta-analysis was carried out to quantitatively evaluate the prognostic values of partial KIF members in cancer patients. Methods: Two well-known KIF members, KIF2A and KIF20A, were investigated to evaluate their potential values as novel prognostic biomarkers in human cancer. A comprehensive literature search was carried out of the PubMed, EMBASE, Cochrane Library, and Web of Science databases up to April 2019. Pooled hazard ratios (HRs) and odds ratios (ORs) with 95% confidence intervals (CIs) were calculated to assess the association of KIF2A and KIF20A expression with overall survival (OS) and clinicopathological parameters. Results: Twenty-five studies involving 7262 patients were finally incorporated, including nine about KIF2A and sixteen about KIF20A. Our results indicated that patients with high expression of KIF2 and KIF20A tended to have shorter OS than those with low expression (HR = 2.23, 95% CI = 1.87–2.65, P < .001; HR = 1.77, 95% CI = 1.57–1.99, P < .001, respectively). Moreover, high expression of these 2 KIF members was significantly associated with advanced clinical stage (OR = 1.98, 95% CI: 1.57–2.50, P < .001; OR = 2.63, 95% CI: 2.03–3.41, P < .001, respectively), positive lymph node metastasis (OR = 2.32, 95% CI: 1.65–3.27, P < .001; OR = 2.13, 95% CI: 1.59–2.83, P < .001, respectively), and distant metastasis (OR = 2.20, 95% CI: 1.21–3.99, P = .010; OR = 5.25, 95% CI: 2.82–9.77, P < .001, respectively); only high KIF20A expression was related to poor differentiation grade (OR = 1.82, 95% CI: 1.09–3.07, P = .023). Conclusions: High expression of KIF2 and KIF20A in human cancer was significantly correlated with worse prognosis and unfavorable clinicopathological features, suggesting that these 2 KIF members can be used as prognostic biomarkers for different types of tumors. PROSPERO REGISTRATION NUMBER: CRD42019134928.
Yuting Sun, Yi Zhang, Zhiquan Lang, Junfu Huang, Zhenhong Zou
Published: 1 October 2019
Journal: Medicine
Abstract:
Kinesin family member C1 (KIFC1), a C-type kinesin motor protein, plays important roles in centrosome assembly and intracellular transport. Numerous studies have focused on the prognostic value of KIFC1 in malignant tumors and the relationship between KIFC1 expression and clinicopathological traits of cancer patients, but the studies remain controversial. And no meta-analysis has yet shown the association between KIFC1 and various cancers. Systematic retrieval was carried out within several databases, including PubMed, Embase, Web of Science, Wanfang and China National Knowledge Infrastructure (CNKI). In addition, hazard ratios (HR) and relative risks (RR) with 95% confidence intervals (CIs) were calculated to examine the risk or hazard correlation by Stata SE15.1. Eleven studies with the overall 2424 participants were included in this research. High KIFC1 expression was remarkably correlated with worse OS (HR = 1.33, 95% CI = 1.07-1.60) and poorer relapse-free survival (HR = 2.28, 95% CI = 1.75-2.80). In subgroup analysis, high KIFC1 expression was a negative predictor for OS in patients with ovarian cancer (P < .001), breast cancer (P < .001), hepatocellular carcinoma (P < .001), and non-small cell lung cancer (P < .001), but not for esophageal squamous cell carcinoma (P = .246). Moreover, high levels of KIFC1 were related with positive lymph node metastasis (RR = 1.23, 95% CI = 1.01-1.50, P = .041) and advanced tumor node metastasis (TNM) stage (RR = 1.55, 95% CI = 1.27-1.89, P < .001). KIFC1 overexpression indicates poor prognosis and more serious clinicopathological characteristics in kinds of malignancies. Thus, we conclude that KIFC1 could be a target for clinical diagnosis and treatment of various cancers.
Shucai Xie, Xili Jiang, Jianquan Zhang, ShaoWei Xie, Yongyong Hua, Rui Wang,
Published: 30 July 2019
Journal: Peerj
Abstract:
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.
Qiuchan Zhang, Dongling Lu, Wenlin Liu, Shijie Ye, Huanping Guo, Tianyi Liao,
Published: 9 July 2019
Journal: Oncology Letters
Oncology Letters, Volume 18, pp 2718-2723; https://doi.org/10.3892/ol.2019.10597

Abstract:
Nasopharyngeal carcinoma (NPC) is a common tumor in south China. Kinesin family member 2A (KIF2A) belongs to the kinesin‑13 family and is associated with the growth and invasion of a number of different types of human cancer, including ovarian, breast and prostate cancer. The aim of the present study was to evaluate the expression of KIF2A in NPC and explore the relationship between KIF2A and the basic characteristics of 5‑8F cells. Immunohistochemistry was performed on tissues from 97 patients with NPC to assess KIF2A protein expression. KIF2A was knocked down by a specific short interfering (si)RNA in 5‑8F cell lines. Cell proliferation, apoptosis and cycle were analyzed by MTT assay and flow cytometry. The invasive ability and angiogenesis were evaluated by Matrigel assay and reverse transcription‑quantitative PCR. The level of KIF2A was associated with the growth and migration of primary tumor, nodal status and tumor stage. The viability of KIF2A‑knockdown cells was decreased compared with that of the control cells. The number of apoptotic cells, as well as the percentage of cells in the G0/G1 phase, was higher in the KIF2A siRNA group compared with the control group. The invasive and angiogenetic ability of 5‑8F cells in the KIF2A siRNA group was decreased compared with the control group. In conclusion, the expression of KIF2A correlated with the poor clinicopathological features in NPC. Therefore, KIF2A may serve an important role in the progression of NPC and proliferation of 5‑8F cells, which might present a potential therapeutic target for patients with NPC.
Zhiqiang Wu, Hao Zhang, Zhengwang Sun, Chunmeng Wang, Yong Chen, Peng Luo,
Published: 1 January 2019
Journal: Chemotherapy
Chemotherapy, Volume 64, pp 187-196; https://doi.org/10.1159/000505014

Abstract:
Kinesin family (KIF) members have vital roles in mitosis, meiosis, and transport of macromolecules in eukaryotic cells. In this study, we aimed to investigate the role of KIF15 in osteosarcoma. Immunohistochemical staining was performed to determine expression levels of KIF15 in osteosarcoma tissues and adjacent normal tissues. Tissue microarray analysis showed a correlation between the expression of KIF15 and pathological features of patients. Subsequently, lentivirus was used to inhibit the expression of KIF15 in osteosarcoma cells. An MTT assay was performed to examine cell proliferation. Transwell and wound healing assays were used to estimate the invasion and migration of osteosarcoma cells, respectively. Flow cytometric analysis was employed to define the apoptosis of osteosarcoma cells. Our results showed that KIF15 expression was significantly upregulated in osteosarcoma tissues compared with adjacent normal tissues. The Mann-Whitney U test and Spearman correlation analysis showed that the expression levels of KIF15 in osteosarcoma tissues were positively correlated with tumor infiltrate, a pathological characteristic of patients. The expression of KIF15 was successfully suppressed by shKIF15, and the knockdown efficiency reached 80 and 69% in MNNG/HOS and U2OS cells, respectively. Subsequently, knockdown of KIF15 significantly inhibited the capacity of cell proliferation, colony formation, invasion, and migration, but enhanced G2 phase arrest and partially enhanced cell apoptosis. This study preliminarily showed KIF15 to be a critical regulatory molecule involved in osteosarcoma cell proliferation. Consequently, KIF15 can be a potential diagnostic and therapeutic target for osteosarcoma.
Guangwei Sun, Yalun Li, Yangjie Peng, Dapeng Lu, Fuqiang Zhang, Xueyang Cui, Qingyue Zhang,
Published: 21 August 2018
Journal of Cellular Physiology, Volume 234, pp 3829-3836; https://doi.org/10.1002/jcp.27154

Abstract:
Colorectal cancer (CRC) ranks as one of the most commonly diagnosed malignancies worldwide. Although mortality rates have been decreasing, the prognosis of CRC patients is still highly dependent on the individual. Therefore, identifying and understanding novel biomarkers for CRC prognosis remains crucial. The gene expression profiles of five‐gene expression omnibus (GEO) data sets of CRC were first downloaded. A total of 352 consistent differentially expressed genes (DEGs) were identified for CRC and paired with normal tissues. Functional analysis including gene ontology and Kyoto encyclopedia of genes and genomes pathway enrichment revealed that these DEGs were related to metabolic pathways, tight junctions, and the cell cycle. Ten hub DEGs were identified based on the search tool for the retrieval of interacting genes database and protein–protein interaction networks. By using univariate Cox proportional hazard regression analysis, we found 11 survival‐related genes among these DEGs. We finally established a five‐gene signature (kinesin family member 15, N‐acetyltransferase 2, glutathione peroxidase 3, secretogranin II, and chloride channel accessory 1) with prognostic value in CRC by step multivariate Cox regression analysis. Based on this risk scoring system, patients in the high‐risk group had significantly poorer survival results compared with those in the low‐risk group (log‐rank test, p < 0.0001). Finally, we validated our gene signature scoring system in two independent GEO cohorts (GSE17536 and GSE33113). We found all five of the signature genes to be DEGs in The Cancer Genome Atlas database. In conclusion, our findings suggest that our five DEG‐based signature can provide a novel biomarker with useful applications in CRC prognosis.
Li Sheng, Shuang-Li Hao, ,
Published: 3 August 2018
Journal: Gene
Gene, Volume 678, pp 90-99; https://doi.org/10.1016/j.gene.2018.08.005

Abstract:
Human KIF4 is a member of Kinesin-4 kinesin family. The highly conserved structure contains an N-terminal motor region, coiled-coil region and C-terminal loading region. KIF4 plays important roles in DNA repair and DNA replication, which maintains genetic stability. KIF4 is also essential for regulation of mitosis and meiosis. KIF4 cooperates with condensin I and TopoIIα to help with chromosomal condensation, and binds to a plethora of cell-cycle proteins to regulate spindle organization and cytokinesis. Additionally, KIF4 plays roles in germ plasm aggregation and radial order in germ cells. In neuronal cells, KIF4 promotes proper axon growth by transporting substrates P0 and L1 to their proper location. Interestingly, KIF4 is abnormally expressed in a variety of cancers, where KIF4 is often up-regulated but can also be down-regulated in some cancers. This suggests distinctive regulatory mechanisms for different cancers. Recent studies support important roles for KIF4 in cancers such as the promotion of drug resistance or inhibition of apoptosis. Previous studies showed that by inhibiting or enhancing the expression of KIF4, the proliferation of cancer cells can be significantly reduced. Therefore KIF4 has potential as a therapeutic target for cancer therapy. Moreover, the misregulation of KIF4 is related to viral infection and neural system diseases like Alzheimer. We believe better understanding of this protein will help us develop better therapies for the diseases mentioned above. Here, we summarize KIF4 functions in normal cells and in various cancers, and provide an overview on the association between KIF4 disorders and disease progression.
Baoqi Shi, Xuejun Zhang, Lumeng Chao, Yu Zheng, Yongsheng Tan, Liang Wang, Wei Zhang
Published: 26 June 2018
Journal: Febs Open Bio
Febs Open Bio, Volume 8, pp 1424-1436; https://doi.org/10.1002/2211-5463.12483

Abstract:
Human hepatocellular carcinoma (HCC) is a common aggressive cancer whose molecular mechanism remains elusive. We aimed to identify the key genes, microRNAs (miRNAs) and long non‐coding RNAs (lncRNAs) involved with HCC. We obtained mRNA, miRNA and lncRNA profiles for HCC from The Cancer Genome Atlas and then identified differentially expressed mRNAs (DEmRNAs), miRNAs (DEmiRNAs) and lncRNAs (DElncRNAs). We performed functional annotation of DEmRNAs and then constructed HCC‐specific DEmiRNA–DEmRNA, DEmiRNA–DElncRNA and DElncRNA–DEmiRNA–DEmRNA interaction networks. We searched for nearby target cis‐DEmRNAs of DElncRNAs and performed receiver operating characteristic and survival analyses. A total of 1239 DEmRNAs, 33 DEmiRNAs and 167 DElncRNAs in HCC were obtained. Retinol metabolism [false discovery rate (FDR) = 7.02 × 10−14] and metabolism of xenobiotics by cytochrome P450 (FDR = 7.30 × 10−11) were two significantly enriched pathways in HCC. We obtained 545 DEmiRNA–DEmRNA pairs that consisted of 258 DEmRNAs and 28 DEmiRNAs in HCC. mir‐424, miR‐93 and miR‐3607 are three hub DEmiRNAs of the HCC‐specific DEmiRNA–DEmRNA interaction network. HAND2‐AS1/ENSG00000232855–miR‐93–LRAT/RND3, ENSG00000232855–miR‐877–RCAN1 and ENSG00000232855–miR‐224–RND3 interactions were found in the HCC‐specific DElncRNA–DEmiRNA–DEmRNA interaction network. A total of three DElncRNA–nearby target DEmRNA pairs (HCG25–KIFC1, LOC105378687–CDC20 and LOC101927043–EPCAM) in HCC were obtained. Diagnostic and prognostic values of several selected DElncRNAs, DEmRNAs and DEmiRNAs for HCC were assessed. Our study identified several DEmRNAs, DEmiRNAs and DElncRNAs with great diagnostic or prognostic value for HCC, which may facilitate studies into the molecular mechanisms, and development of potential biomarkers and therapeutic target sites for HCC.
Veerabrahma Pratap Seshachalam, ,
Published: 19 April 2018
Journal of Gastroenterology and Hepatology, Volume 33, pp 2037-2047; https://doi.org/10.1111/jgh.14262

Abstract:
Background and Aim Hepatitis B virus, hepatitis C virus, alcoholic consumption and non‐alcoholic fatty liver are the major known risk factors for Hepatocellular carcinoma (HCC). There have been very few studies comparing the underlying biological mechanisms associated with the different etiologies of HCC. In this study, we hypothesized the existence of different regulatory networks associated with different liver disease etiologies involved in hepatocarcinogenesis. Methods Using upstream regulatory analysis tool in ingenuity pathway analysis software, URs were predicted using differential expressed genes for HCC to facilitate the interrogation of global gene regulation. Results Analysis of regulatory networks for HBV HCC revealed E2F1 as activated UR, regulating genes involved in cell cycle and DNA replication and HNF4A and HNF1A as inhibited UR. In HCV HCC, IFNG, involved in cellular movement and signaling was activated while IL1RN, MAPK1 involved in IL‐22 signaling and immune response was inhibited. In Alcoholic‐consumption HCC, ERBB2 involved in inflammatory response and cellular movement was activated, whereas HNF4A, NUPR1 were inhibited. For HCC derived from Non‐alcoholic fatty liver disease, miR‐1249‐5p was activated and NUPR1 involved in cell cycle and apoptosis was inhibited. The prognostic value of representative genes identified in the regulatory networks for HBV HCC can be further validated by an independent HBV HCC dataset established in our laboratory with survival data. Conclusions Our study identified functionally distinct candidate URs for HCC developed from different etiologic risk factors. Further functional validation studies of these regulatory networks could facilitate the management of HCC towards personalized medicine.
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