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High CENPM Mrna Expression and Its Prognostic Signifcance in Hepatocellular Carcinoma: a Study Based on Data Mining Zeng‑Hong Wu and Dong‑Liang Yang*

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High CENPM Mrna Expression and Its Prognostic Signifcance in Hepatocellular Carcinoma: a Study Based on Data Mining Zeng‑Hong Wu and Dong‑Liang Yang* Wu and Yang Cancer Cell Int (2020) 20:406 https://doi.org/10.1186/s12935-020-01499-y Cancer Cell International PRIMARY RESEARCH Open Access High CENPM mRNA expression and its prognostic signifcance in hepatocellular carcinoma: a study based on data mining Zeng‑hong Wu and Dong‑liang Yang* Abstract Background: Hepatocellular carcinoma (HCC) is a high mortality disease, the ffth most general cancer worldwide, and the second leading to cancer‑related deaths, with more than 500,000 new patients diagnosed each year. First, the high expression of centromere M (CENPM) in mammary gland tissue of b‑catenin transformed mice was identifed. Materials and methods: In our study, we evaluated the expression of CENPM in hepatocellular carcinoma based on data obtained from an online database. Multivariate analysis showed that the expression of CENPM and M classifca‑ tion was an independent prognostic factor for patients with hepatocellular carcinoma. Results: Survival analysis showed that patients with high CENPM had a worse prognosis than patients with low CENPM (P < 0.01). A multivariate Cox regression hazard model showed that B cells, CD8 T cells, macrophages, and dendritic cells infltrated by immune cells were statistically signifcant in liver cancer (P <+ 0.05). Using the network, the 50 most frequently changed neighbor genes of CENPM were shown, and the most common change was RAD21 (18.3%). Conclusion: Our study found that the expression of CENPM was signifcantly increased in patients with hepatocellu‑ lar carcinoma, and it was related to a variety of clinical characteristics, its correlation with the level of immune infltra‑ tion and poor prognosis, so CENPM can be used as a useful prognosis for patients’ markers and HCC. Keywords: Hepatocellular carcinoma, Centromere protein M, Data mining, Prognosis Background is only 34 to 50% [4]. Despite the rapid development of Hepatocellular carcinoma (HCC), a high mortality dis- advanced medical technology, there are still no useful ease which is the ffth most general cancer in the world curable strategies for HCC patients [5]. Byeno et al. [6] and the second most common lead to cancer-related reported that based on long-term survival data, serum deaths, with over 500,000 new patients diagnosed each OPN and DKK1 levels in patients with liver cancer can year [1, 2]. Viral hepatitis and nonalcoholic steato- be deemed as novel biomarkers that show prognostic hepatitis are the most common causes of cirrhosis and useful for liver cancer. Other serum markers, such as approximately 80% of cases develop to HCC [3]. Due to alpha-fetoprotein (AFP) and alkaline phosphatase (ALP the recurrence of HCC the prognosis of HCC remains or AKP), are proverbially used in clinical, but they lack discouraging and the 5-year overall survival rate which sufcient sensitivity and specifcity [7]. Terefore, fnd- ing useful biomarkers is indispensable for diagnosis and treatment for HCC patients. *Correspondence: [email protected] Post-transcriptional modifcations are essential for Department of Infectious Diseases, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430022, tumorigenesis and development. Centromere protein China M (CENPM; otherwise called PANE1, CENP-M and © The Author(s) 2020. This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creat iveco mmons .org/licen ses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creat iveco mmons .org/publi cdoma in/ zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data. Wu and Yang Cancer Cell Int (2020) 20:406 Page 2 of 10 C22orf18), which encodes a kinetic protein, binds to tumor types. Te abundance of immune infltrates spindle microtubules to regulate chromosomal separa- (CD8+ T cells, B cells, CD4+ T cells, macrophages, neu- tion during cell division [8]. Expression of the PANE1 trophils, and dendritic cells) was evaluated by our statis- gene was found preferentially in immune cells involv- tical methods and has been estimated using pathology ing tumor tissues and tumor derived cell lines and leu- Methods evaluated it. Te network also enables users kemias and lymphomas [9]. Brickner et al. [10] found to explore the clinical relevance of one or more tumor highly expressed in B lineage chronic lymphocytic leu- immune subpopulations and has the fexibility to correct kemia (B-CLL) cells and resting CD19 (+) B cells, may multiple covariates in a multivariate Cox proportional be a potential therapeutic target for B-CLL. Bierie et al. hazard model. Meanwhile, we contrast the diferen- [9] also demonstrated that human CENPM transcript tial level of CENPM between tumors and normal on all cRNA was detected only in vivo or in vitro in activated TCGA tumors. B cells and T cells. Tese studies suggested CENPM may play critical role in tumor immune response and may be UALCAN and c‑BioPortal analysis deemed to therapeutic target for immunotherapy. How- UALCAN [13] is a user-friendly intelligent network asset ever, the role of CENPM in HCC prognostic remains for analyzing, discovering cancer data and in-depth anal- unclear. In our study, we evaluated the expression of ysis of TCGA gene expression information. One of the CENPM in HCC based on data from an online database highlights of the portal is that it allows users to found to further understand the biological pathway of CENPM between biomarkers or computer approval of potential related to the pathogenesis of HCC. In addition, we genes of interest, and to evaluate genes in diferent clini- also analyzed the connection between CENPM expres- cal subgroups (such as gender, age, race, tumor grade, sion and clinical features as well as the correlation of its etc.) expression. cBioPortal [14] is an online free asset expression with immune infltration level in HCC comes that can visualize, analyze, and download large-scale an online tumor infltrating immune cells analysis tool. cancer transcription datasets. Te portal included 245 cancer studies. Te tab biological interaction network of Materials and methods CENPM and its co-expressed genes was got, and neigh- Data collection boring genes with altered frequencies were contained. Information on RNA-sequencing data (424 tissues, workfow type: HTSeqCounts) and comparative clinical TargetScan analysis data (377 patients, data format: BCR XML) were identi- TargetScan [15] is a web for predicting potential biologi- fed and got from the level 3 (standardized FPKM) of the cal targets of miRNAs. TargetScanHuman deems that TCGA-HCC cohort. Use boxplots to imagine expression the match to human 3′UTR and its orthologs is estimate diferences for discrete variables [11]. Te clinical factors by a UCSC genome-wide adjustment. As an alternative, included gender, stage, age, grade, T-phase, M-phase, they are ranked according to their predicted conservative N-phase, survival status and number of days of survival. positioning possibilities. FunRich [16] is a tool designed Data analysis were checked by R (version 3.5.3) and R to process varieties of gene/protein datasets, in spite of Bioconductor software packages. the organism, and used for functional enrichment analy- sis. We used Funrich tools for miRNA enrichment analy- GSEA enrichment sis, including analysis of biological pathways, biological Gene Set Enrichment Analysis (GSEA) created a list of processes (BP), cellular components (CC) and molecular all gene permutations related to CENPM expression. Te functions (MF). samples were then divided into a high CENPM group and a low CENPM group as training sets to distinguish Statistical analysis potential functions and use GSEA to clarify signifcant Scatter plots and paired plots visualize the diferences survival diferences. Genome replacement is performed between normal and tumor samples. Use delete ways to multiple times with each exam. Te degree of expression handle disappeared data, and if any individual value is of CENPM was used as a phenotypic marker. Normal- disappeared, the data will exclude the full sample. Te ized enrichment scores (NES) and nominal P-values have relationship between clinical factors and CENPM was been used to classify the pathways of enrichment in each used by logistic regression, Wilcoxon rank sum test, and phenotype. Kruskal test. Multivariate Cox analysis was used to assess the efect of CENPM expression on survival and other Immune infltrates analysis clinical factors (such as age, gender, stage, distant metas- TIMER [12] is a comprehensive database for the system- tasis). Benjamini–Hochberg’s means of converting P val- atic study of immune infltration in various malignant ues to FDR. Wu and Yang Cancer Cell Int (2020) 20:406 Page 3 of 10 Results (67.6%) male patients. Stage I was located in 175 patients Patients’ characteristics (46.4%), stage II in 87 (23.1%), stage III in 86 (22.8%) Te TCGA database contains 377 patients. Te clini- and stage IV in 5 (1.3%). Tumor stage was found T1 in cal and pathological properties of these samples are 185 patients (49.1%), T2 in 95 (25.2%), T3 in 81 (21.5%) shown in Table 1. Te middle age at diagnosis in TCGA and T4 in 13 (3.4%). Node stage contained N0 in 257 was 53 years old (range 16–90 years) and median (68.2%) and N1 in 4 (1.1%), 4 of 377 (1.1%) cases had fnally contact for subjects was 28.0 months (range distant metastases.
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