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Xue P, Zheng J, Li R, Yan L, Wang Z, Jia Q, Zhang L, Li X. High Expression of KIFC1 in Glioma Correlates with Poor Prognosis. J Korean Neurosurg Soc 2024; 67:364-375. [PMID: 38720546 PMCID: PMC11079566 DOI: 10.3340/jkns.2023.0155] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/20/2023] [Revised: 09/06/2023] [Accepted: 10/19/2023] [Indexed: 05/12/2024] Open
Abstract
OBJECTIVE Kinesin family member C1 (KIFC1), a non-essential kinesin-like motor protein, has been found to serve a crucial role in supernumerary centrosome clustering and the progression of several human cancer types. However, the role of KIFC1 in glioma has been rarely reported. Thus, the present study aimed to investigate the role of KIFC1 in glioma progression. METHODS Online bioinformatics analysis was performed to determine the association between KIFC1 expression and clinical outcomes in glioma. Immunohistochemical staining was conducted to analyze the expression levels of KIFC1 in glioma and normal brain tissues. Furthermore, KIFC1 expression was knocked in the glioma cell lines, U251 and U87MG, and the functional roles of KIFC1 in cell proliferation, invasion and migration were analyzed using cell multiplication, wound healing and Transwell invasion assays, respectively. The autophagic flux and expression levels matrix metalloproteinase-2 (MMP2) were also determined using imaging flow cytometry, western blotting and a gelation zymography assay. RESULTS The results revealed that KIFC1 expression levels were significantly upregulated in glioma tissues compared with normal brain tissues, and the expression levels were positively associated with tumor grade. Patients with glioma with low KIFC1 expression levels had a more favorable prognosis compared with patients with high KIFC1 expression levels. In vitro, KIFC1 knockdown not only inhibited the proliferation, migration and invasion of glioma cells, but also increased the autophagic flux and downregulated the expression levels of MMP2. CONCLUSION Upregulation of KIFC1 expression may promote glioma progression and KIFC1 may serve as a potential prognostic biomarker and possible therapeutic target for glioma.
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Affiliation(s)
- Pengfei Xue
- Department of Neurosurgery, Liaocheng People's Hospital, Liaocheng, China
| | - Juan Zheng
- Joint Laboratory for Translational Medicine Research, Liaocheng People's Hospital, Liaocheng, China
| | - Rongrong Li
- Joint Laboratory for Translational Medicine Research, Liaocheng People's Hospital, Liaocheng, China
| | - Lili Yan
- Joint Laboratory for Translational Medicine Research, Liaocheng People's Hospital, Liaocheng, China
| | - Zhaohao Wang
- Department of Neurosurgery, Yantaishan Hospital Affiliated to Binzhou Medical University, Yantai, China
| | - Qingbin Jia
- Department of Neurosurgery, Liaocheng People's Hospital, Liaocheng, China
| | - Lianqun Zhang
- Department of Neurosurgery, Liaocheng People's Hospital, Liaocheng, China
| | - Xin Li
- Department of Neurosurgery, Liaocheng People's Hospital, Liaocheng, China
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Özbek M, Toy HI, Oktay Y, Karakülah G, Suner A, Pavlopoulou A. An in silico approach to the identification of diagnostic and prognostic markers in low-grade gliomas. PeerJ 2023; 11:e15096. [PMID: 36945359 PMCID: PMC10024901 DOI: 10.7717/peerj.15096] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/04/2022] [Accepted: 02/28/2023] [Indexed: 03/18/2023] Open
Abstract
Low-grade gliomas (LGG) are central nervous system Grade I tumors, and as they progress they are becoming one of the deadliest brain tumors. There is still great need for timely and accurate diagnosis and prognosis of LGG. Herein, we aimed to identify diagnostic and prognostic biomarkers associated with LGG, by employing diverse computational approaches. For this purpose, differential gene expression analysis on high-throughput transcriptomics data of LGG versus corresponding healthy brain tissue, derived from TCGA and GTEx, respectively, was performed. Weighted gene co-expression network analysis of the detected differentially expressed genes was carried out in order to identify modules of co-expressed genes significantly correlated with LGG clinical traits. The genes comprising these modules were further used to construct gene co-expression and protein-protein interaction networks. Based on the network analyses, we derived a consensus of eighteen hub genes, namely, CD74, CD86, CDC25A, CYBB, HLA-DMA, ITGB2, KIF11, KIFC1, LAPTM5, LMNB1, MKI67, NCKAP1L, NUSAP1, SLC7A7, TBXAS1, TOP2A, TYROBP, and WDFY4. All detected hub genes were up-regulated in LGG, and were also associated with unfavorable prognosis in LGG patients. The findings of this study could be applicable in the clinical setting for diagnosing and monitoring LGG.
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Affiliation(s)
- Melih Özbek
- Izmir Biomedicine and Genome Center, Izmir, Turkey
- Izmir International Biomedicine and Genome Institute, Dokuz Eylül University, Izmir, Turkey
| | - Halil Ibrahim Toy
- Department of Epidemiology and Cancer Control, St. Jude Children’s Research Hospital, Memphis, Tennessee, United States
| | - Yavuz Oktay
- Izmir Biomedicine and Genome Center, Izmir, Turkey
- Faculty of Medicine, Department of Medical Biology, Dokuz Eylül University, Izmir, Turkey
| | - Gökhan Karakülah
- Izmir Biomedicine and Genome Center, Izmir, Turkey
- Izmir International Biomedicine and Genome Institute, Dokuz Eylül University, Izmir, Turkey
| | - Aslı Suner
- Faculty of Medicine, Department of Biostatistics and Medical Informatics, Izmir, Turkey
| | - Athanasia Pavlopoulou
- Izmir Biomedicine and Genome Center, Izmir, Turkey
- Izmir International Biomedicine and Genome Institute, Dokuz Eylül University, Izmir, Turkey
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An integrated multi-omics analysis of topoisomerase family in pan-cancer: Friend or foe? PLoS One 2022; 17:e0274546. [PMID: 36288358 PMCID: PMC9604985 DOI: 10.1371/journal.pone.0274546] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/17/2022] [Accepted: 08/29/2022] [Indexed: 11/05/2022] Open
Abstract
BACKGROUND Topoisomerases are nuclear enzymes that get to the bottom of topological troubles related with DNA all through a range of genetic procedures. More and more studies have shown that topoisomerase-mediated DNA cleavage plays crucial roles in tumor cell death and carcinogenesis. There is however still a lack of comprehensive multi-omics studies related to topoisomerase family genes from a pan-cancer perspective. METHODS In this study, a multiomics pan-cancer analysis of topoisomerase family genes was conducted by integrating over 10,000 multi-dimensional cancer genomic data across 33 cancer types from The Cancer Genome Atlas (TCGA), 481 small molecule drug response data from cancer therapeutics response portal (CTRP) as well as normal tissue data from Genotype-Tissue Expression (GTEx). Finally, overall activity-level analyses of topoisomerase in pan-cancers were performed by gene set variation analysis (GSVA), together with differential expression, clinical relevancy, immune cell infiltration and regulation of cancer-related pathways. RESULTS Dysregulated gene expression of topoisomerase family were related to genomic changes and abnormal epigenetic modifications. The expression levels of topoisomerase family genes could significantly impact cancer progression, intratumoral heterogeneity, alterations in the immunological condition and regulation of the cancer marker-related pathways, which in turn caused the differences in potential drugs sensitivity and the distinct prognosis of patients. CONCLUSION It was anticipated that topoisomerase family genes would become novel prognostic biomarkers for cancer patients and provide new insights for the diagnosis and treatment of tumors.
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Mousavi SR, Khosravian F, Hemmat N, Feizbakhshan S, Salmanizadeh S, Foroutan FS, Ghaedi K, Salehi M. A glance at glioblastoma molecular culprits through in-silico analysis. GENE REPORTS 2021. [DOI: 10.1016/j.genrep.2021.101048] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/24/2022]
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5
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Liu D, Zhang P, Zhao J, Yang L, Wang W. Identification of Molecular Characteristics and New Prognostic Targets for Thymoma by Multiomics Analysis. BIOMED RESEARCH INTERNATIONAL 2021; 2021:5587441. [PMID: 34104648 PMCID: PMC8159640 DOI: 10.1155/2021/5587441] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 01/16/2021] [Revised: 03/16/2021] [Accepted: 04/01/2021] [Indexed: 11/17/2022]
Abstract
BACKGROUND Thymoma is a heterogeneous tumor originated from thymic epithelial cells. The molecular mechanism of thymoma remains unclear. METHODS The expression profile, methylation, and mutation data of thymoma were obtained from TCGA database. The coexpression network was constructed using the variance of gene expression through WGCNA. Enrichment analysis using clusterProfiler R package and overall survival (OS) analysis by Kaplan-Meier method were carried out for the intersection of differential expression genes (DEGs) screened by limma R package and important module genes. PPI network was constructed based on STRING database for genes with significant impact on survival. The impact of key genes on the prognosis of thymoma was evaluated by ROC curve and Cox regression model. Finally, the immune cell infiltration, methylation modification, and gene mutation were calculated. RESULTS We obtained eleven coexpression modules, and three of them were higher positively correlated with thymoma. DEGs in these three modules mainly involved in MAPK cascade and PPAR pathway. LIPE, MYH6, ACTG2, KLF4, SULT4A1, and TF were identified as key genes through the PPI network. AUC values of LIPE were the highest. Cox regression analysis showed that low expression of LIPE was a prognostic risk factor for thymoma. In addition, there was a high correlation between LIPE and T cells. Importantly, the expression of LIPE was modified by methylation. Among all the mutated genes, GTF2I had the highest mutation frequency. CONCLUSION These results suggested that the molecular mechanism of thymoma may be related to immune inflammation. LIPE may be the key genes affecting prognosis of thymoma. Our findings will help to elucidate the pathogenesis and therapeutic targets of thymoma.
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Affiliation(s)
- Dazhong Liu
- Department of Thoracic Surgery, Second Affiliated Hospital of Harbin Medical University, Harbin 150086, China
| | - Pengfei Zhang
- Department of Thoracic Surgery, Second Affiliated Hospital of Harbin Medical University, Harbin 150086, China
| | - Jiaying Zhao
- Department of Thoracic Surgery, Second Affiliated Hospital of Harbin Medical University, Harbin 150086, China
| | - Lei Yang
- Department of Thoracic Surgery, Second Affiliated Hospital of Harbin Medical University, Harbin 150086, China
| | - Wei Wang
- Department of Thoracic Surgery, Second Affiliated Hospital of Harbin Medical University, Harbin 150086, China
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Liu J, Zhang H, Zhang J, Bing Z, Wang Y, Li Q, Yang K. Identification of robust diagnostic and prognostic gene signatures in different grades of gliomas: a retrospective study. PeerJ 2021; 9:e11350. [PMID: 34026352 PMCID: PMC8121073 DOI: 10.7717/peerj.11350] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/20/2020] [Accepted: 04/05/2021] [Indexed: 12/23/2022] Open
Abstract
Background Gliomas are the most common primary tumors of the central nervous system. The complexity and heterogeneity of the tumor makes it difficult to obtain good biomarkers for drug development. In this study, through The Cancer Genome Atlas (TCGA) and Chinese Glioma Genome Atlas (CGGA), we analyze the common diagnostic and prognostic moleculer markers in Caucasian and Asian populations, which can be used as drug targets in the future. Methods The RNA-seq data from Genotype-Tissue Expression (GTEx) and The Cancer Genome Atlas (TCGA) were analyzed to identify signatures. Based on the signatures, the prognosis index (PI) of every patient was constructed to predict the prognostic risk. Also, gene ontology (GO) functional enrichment analysis and KEGG analysis were conducted to investigate the biological functions of these mRNAs. Glioma patients’ data in the CGGA database were introduced to validate the effectiveness of the signatures among Chinese populations. Excluding the previously reported prognostic markers of gliomas from this study, the expression of HSPA5 and MTPN were examined by qRT-PCR and immunohistochemical assay. Results In total, 20 mRNAs were finally selected to build PI for patients from TCGA, including 16 high-risk genes and four low-risk genes. For Chinese patients, the log-rank test p values of PI were both less than 0.0001 in two independent datasets. And the AUCs were 0.831 and 0.907 for 3 years of two datasets, respectively. Moreover, among these 20 mRNAs, 10 and 15 mRNAs also had a significant predictive effect via univariate COX analysis in CGGA_693 and CGGA_325, respectively. qRT-PCR and Immunohistochemistry assay indicated that HSPA5 and MTPN over-expressed in Glioma samples compared to normal samples. Conclusion The 20-gene signature can forecast the risk of Glioma in TCGA effectively, moreover it can also predict the risks of Chinese patients through validation in the CGGA database. HSPA5 and MTPN are possible biomarkers of gliomas suitable for all populations to improve the prognosis of these patients.
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Affiliation(s)
- Jieting Liu
- The First Clinical Medical College, Lanzhou University, Lanzhou, China.,Department of Anesthesiology, Lanzhou University Second Hospital, Lanzhou, China.,Evidence-based Medicine Center, Lanzhou University, Lanzhou, China
| | - Hongrui Zhang
- College of Pharmacy, Lanzhou University, Lanzhou, China
| | - Jingyun Zhang
- School of Public Health and the Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Zhitong Bing
- Department of Computational Physics, Institute of Modern Physics, Chinese Academy of Sciences, Lanzhou, China.,School of Nuclear Science and Technology, University of Chinese Academy of Sciences, Lanzhou, China
| | - Yingbin Wang
- Department of Anesthesiology, Lanzhou University Second Hospital, Lanzhou, China
| | - Qiao Li
- Department of Neurosurgery, Lanzhou University Second Hospital, Lanzhou, China
| | - Kehu Yang
- The First Clinical Medical College, Lanzhou University, Lanzhou, China.,Evidence-based Medicine Center, Lanzhou University, Lanzhou, China
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Liu F, Dong H, Mei Z, Huang T. Investigation of miRNA and mRNA Co-expression Network in Ependymoma. Front Bioeng Biotechnol 2020; 8:177. [PMID: 32266223 PMCID: PMC7096354 DOI: 10.3389/fbioe.2020.00177] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/02/2020] [Accepted: 02/20/2020] [Indexed: 12/18/2022] Open
Abstract
Ependymoma (EPN) is a rare primary tumor of the central nervous system (CNS) that affects both children and adults. Despite the definition and classification of distinct molecular subgroups, there remains a group of EPNs with a balanced genome, which makes it difficult to predict a prognosis of patients with EPN. The role of miRNA-mRNA network on EPN is still poorly understood. We assessed the involvement of miRNA-mRNA pairs in EPN by applying a weighted co-expression network analysis (WGCNA) approach. Using whole genome expression profile analysis followed by functional enrichment, we detected hub genes involved in active proliferation and DNA replication of nerve cells. Key genes including CYP11B1, KRT33B, RUNX1T1, SIK1, MAP3K4, MLANA, and SFRP5 identified in co-expression networks were regulated by miR-15a and miR-24-1. These seven miRNA-mRNA pairs were considered to influence not only pathways in cancer and tumor suppression process, but also MAPK, NF-kappaB, and WNT signaling pathways which were associated with tumorigenesis and development. This study provides a novel insight into potential diagnostic biomarkers of EPN and may have value in choosing therapeutic targets with clinical utility.
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Affiliation(s)
- Feili Liu
- Department of Neurosurgery, Huashan Hospital, Fudan University, Shanghai, China
| | - Hang Dong
- Shanghai Institute of Nutrition and Health, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai, China
| | - Zi Mei
- Shanghai Institute of Nutrition and Health, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai, China
| | - Tao Huang
- Shanghai Institute of Nutrition and Health, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai, China
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Yang Y, Liu X, Cheng L, Li L, Wei Z, Wang Z, Han G, Wan X, Wang Z, Zhang J, Chen C. Tumor Suppressor microRNA-138 Suppresses Low-Grade Glioma Development and Metastasis via Regulating IGF2BP2. Onco Targets Ther 2020; 13:2247-2260. [PMID: 32214825 PMCID: PMC7082711 DOI: 10.2147/ott.s232795] [Citation(s) in RCA: 21] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/28/2019] [Accepted: 02/25/2020] [Indexed: 12/25/2022] Open
Abstract
Background Low-grade gliomas (LGG), approximately constitute one-third of all types of gliomas, are prone to relapse and metastasis. MicroRNA-138 (miR-138) is reported to be dysregulated in diverse human tumors and mainly function as a tumor suppressor. In this study, we analyzed the expression profile and function of miR-138 in LGG. Methods Quantitative PCR (qPCR) and public database bioinformatics analysis were performed to determine the miR-138 levels in LGG. MiR-138 overexpression in LGG cells was achieved by miR-138 mimics transfection. Cell proliferation was assessed by CCK8, EdU and colony formation assays. Cell invasion and migration were analyzed by transwell and wound-healing assays. Xenograft model was employed to study the role of miR-138 in LGG growth in vivo. The target of miR-138 was validated by multiple methods, such as luciferase reporter assay, RT-qPCR and Western blot. Bioinformatics analysis was conducted to explore the molecular mechanisms by which miR-138 contributed to LGG progression. Results miR-138 was significantly downregulated in LGG tumor tissues and low expression of miR-138 was significantly associated with poor prognosis as well as relapse and metastasis in LGG patients. Functional analysis indicated that ectopic miR-138 expression suppressed LGG cell growth and invasive phenotype in vitro, and inhibited tumor development in vivo. Moreover, miR-138 directly targeted and repressed insulin-like growth factor 2 mRNA binding protein 2 (IGF2BP2) by targeting the 3ʹ-UTR of IGF2BP2, inhibiting epithelial to mesenchymal transition (EMT) to attenuate LGG aggressiveness. In addition, we found that elevated IGF2BP2 expression correlates with poor survival of LGG patients. Conclusion miR-138 may function as a tumor inhibitor by directly inhibiting IGF2BP2 and suppressing EMT in the progression of LGG.
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Affiliation(s)
- Yang Yang
- Henan Key Laboratory for Medical Imaging of Neurological Diseases, People's Hospital of Zhengzhou University, Zhengzhou 450003, People's Republic of China.,Department of Neurosurgery, Zhumadian Central Hospital, Zhumadian 463000, People's Republic of China
| | - Xinyu Liu
- School of Intelligent Manufacturing, The Huanghuai University, Zhumadian 463000, People's Republic of China
| | - Lulu Cheng
- Department of Neurosurgery, Zhumadian Central Hospital, Zhumadian 463000, People's Republic of China
| | - Li Li
- Department of Neurosurgery, Zhumadian Central Hospital, Zhumadian 463000, People's Republic of China
| | - Zhenyu Wei
- Department of Neurosurgery, Second Affiliated Hospital of Xinxiang Medical College, Xinxiang 453000, People's Republic of China
| | - Zong Wang
- Department of Neurosurgery, Zhumadian Central Hospital, Zhumadian 463000, People's Republic of China
| | - Gang Han
- Department of Neurosurgery, Zhumadian Central Hospital, Zhumadian 463000, People's Republic of China
| | - Xuefeng Wan
- Department of Neurosurgery, Zhumadian Central Hospital, Zhumadian 463000, People's Republic of China
| | - Zaizhong Wang
- Department of Neurosurgery, Zhumadian Central Hospital, Zhumadian 463000, People's Republic of China
| | - Jianhua Zhang
- Medical Engineering Technology and Data Mining Institute of Zhengzhou University, Zhengzhou 450000, People's Republic of China
| | - Chuanliang Chen
- Henan Key Laboratory for Medical Imaging of Neurological Diseases, People's Hospital of Zhengzhou University, Zhengzhou 450003, People's Republic of China
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