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Biostatistics Mining Associated Method Identifies AKR1B10

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Biostatistics Mining Associated Method Identifies AKR1B10 www.nature.com/scientificreports OPEN Biostatistics mining associated method identifes AKR1B10 enhancing hepatocellular Received: 26 February 2018 Accepted: 25 June 2018 carcinoma cell growth and Published: xx xx xxxx degenerated by miR-383-5p Junqing Wang 1,2,3, Yunyun Zhou4, Xiaochun Fei5, Xuehua Chen2,3 & Yongjun Chen1 Previous studies have reported that the aberrantly expressed AKR1B10 is associated with many cancer development, however the functional roles of AKR1B10 and its regulatory mechanisms in hepatocellular carcinoma (HCC) have been limited studied. In this project, we identifed AKR1B10 functional as an oncogene in HCC through tumor/normal human tissue comparison from both GEO microarray and TCGA RNAseq dataset. Further experimental validations from three HCC cell lines (SMMC-7721, HePG2 and HeP3B) also suggested the ontogenetic functions of AKR1B10 in HCC tumor growth. By knocking down AKR1B10 through shRNA in HCC HeP3B cells, we showed it signifcantly induced cell cycle arrest and inhibited cell growth. Interestingly, integrative analysis of TCGA RNAseq data and miRNA-seq data predicted that miR-383-5p, a novel post-transcriptional tumor suppressor, is negatively associated with AKR1B10 expression. To further investigate the role of miR-383-5p in regulating AKR1B10 in HCC, we performed Dual-luciferase reporter assay experiments. Results showed that miR-383-5p is an upstream modulator targeting AKR1B10 in the post-transcriptional stage. Thus, we report AKR1B10 modulated regulated by miR-383-5p, promotes HCC tumor progress, and could be potentially a therapeutic target for precision medicine in HCC. World widely, hepatocellular carcinoma (HCC) presents a high incidence rate among human malignancies, rank- ing a ffh of morbidity and second of malignancy-related mortality1,2. Biomarkers aberrantly expressed in HCC at either mRNA or protein stages have been gradually illustrated for HCC tumorigenesis. However, comprehensive and integrative analysis for identifying new therapeutic targets and understanding their functional roles in tumor progression are critically important in the development of novel HCC cancer therapies for precision medicine. Data mining the public database from Gene Expression Omnibus (GEO) database and the Cancer Genome Altas (TCGA) database provides opportunities for detecting characteristic gene expressions in certain malig- nancies. In this study, we screened diferentially expressed genes (DEGs) by tumor/normal comparison for GEO datasets and explored the signifcantly enriched Gene Ontology and KEGG pathway in HCC. Ten we focused on 3 up-regulated and 11 down-regulated DEGs all shared among in both GEO microarray and TCGA RNAseq data for down streaming analysis. Te Search Tool for the Retrieval of Interacting Genes (STRING) database was applied to construct the protein-protein interaction (PPI) network for the shared DEGs and their interacted genes. Among our shared DEGs, Aldo-Keto Reductase Family 1 Member B10 (AKR1B10) was observed as an 1Department of Surgery, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, 197, Rui Jin Er Road, Shanghai, 20025, People’s Republic of China. 2Shanghai Institute of Digestive Surgery, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, 197, Rui Jin Er Road, Shanghai, 20025, People’s Republic of China. 3Shanghai Key Laboratory of Gastric Neoplasms, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, 197, Rui Jin Er Road, Shanghai, 20025, People’s Republic of China. 4Department of Data Science, University of Mississippi Medical Center, Jackson, MS, 39216, USA. 5Department of Pathology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, 197, Rui Jin Er Road, Shanghai, 20025, People’s Republic of China. Junqing Wang and Yunyun Zhou contributed equally to this work. Correspondence and requests for materials should be addressed to J.W. (email: [email protected]) or Y.C. (email: [email protected]) SCIENTIFIC REPORTS | (2018) 8:11094 | DOI:10.1038/s41598-018-29271-3 1 www.nature.com/scientificreports/ Figure 1. DEGs identifed from NCBI GEO datasets (A) Venn chart of the over-expressing genes in GSE14520, GSE14323 and GSE6764 liver cancer datasets, which overlapped according to the analysis of FunRich sofware. Four DEGs extremely over-expressed in the three datasets were selected, including AKR1B10, GABBR1, COL15A1, AKR1B100. (B) Venn chart of the decreasing genes in three live cancer datasets. Eleven DEGs extremely decreased were selected, including FCN3, FCN2, MT1M, ADRA1A, HAMP, LPA, IL1RAP, APOF, YP2C19, KCNN2 and SLCO1B3. (C) Te identifed overlapped 15 DEGs from microarray were further tested in TCGA mRNA expression from RNAseq data by Welch’s t-test with P < 0.05 as the cutof for tumor and normal samples comparison. (D) Heatmap generated through TCGA database exploration and data mining. Expressions of the 15 DEGs above were presented by hot spots with gradient from red as high expression to blue as low expression. oncogene participating in the progress of HCC. We explored and verifed the expression status of AKR1B10 in both HCC cell lines and tissue samples from our medical center. Knock-down of AKR1B10 in HCC HeP3B cells signifcantly induced cell cycle arrest and cell growth obstruction. AKR1B10 is a member of the Aldo/keto reductase super-family, which mainly reduce the aliphatic and aro- matic aldehydes efcifently3. Accumulating evidence reveals that AKR1B10 functions as a pivotal promotor of human cancers in multiple tissues and organs, including breast, lung, liver, endometrium and gastrointestinal mucosa3–6. However, AKR1B10 in HCC has been controversially discussed, and AKR1B10 was described as either a negative prognostic factor or an independent promoting factor of HCC7–10. To investigate the AKR1B10 functions, in our study, we performed integrative analysis for TCGA mRNA and miRNA data and built a difer- entially expressed miRNA-mRNA regulatory network in HCC. Results suggested AKR1B10 is interacted with microRNA-383-5p (miR-383-5p). According to further validation, AKR1B10 was proved to be directly degener- ated by miR-383-5p, a tumor suppressor gene in HCC. Herein, we suggest AKR1B10 as a biomarker promoting HCC targeted by miR-383-5p directly. Our fndings provide us potential therapeutic targets in metabolism dis- order related HCC treatment. Results Diferentially expressed mRNA associated with HCC and pathway analysis. Based on the crite- rion of log2FC ≥1.5 and P value < 1.0E-04 for selecting DEGs, 403 genes presented amplifcation in the HCC tissues compared to the non-cancerous samples. Moreover, other 639 genes decreased determined by the same criterion were set. We noticed signifcant enrichment of the processes closely related to cancer genesis and pro- gress. Results suggested the most signifcant pathway is the cellular aldehyde metabolic process (P-Value: 2.46e- 07) (Supp. Table 1). We further focused on 4 over-expressed genes (AKR1B10, GABBR1, COL15A1, ROBO10) out of 403 candidates (Fig. 1A), and 11 down-expressed genes (FCN3, FCN2, MT1M, ADRA1A, HAMP, LPA, IL1RAP, APOF, YP2C19, KCNN2, and SLCO1B3) shared among the three datasets (Fig. 1B). Te identifed over- lapped 15 DEGs from microarray were further tested in TCGA mRNA expression from RNAseq data by Welch’s t-test with P < 0.05 as the cutof for tumor and normal samples comparison. Only the P value of GABBR1 gene did not pass the signifcant cutof. Terefore we ignored this gene from further analysis (Fig. 1C). Te mRNA expression pattern of the 14 DEGs in tumor and normal liver tissues was demonstrated by heatmap in Fig. 1D, through TCGA database exploration of 369 liver hepatocellular carcinoma samples and 49 adjacent specimens. SCIENTIFIC REPORTS | (2018) 8:11094 | DOI:10.1038/s41598-018-29271-3 2 www.nature.com/scientificreports/ Figure 2. Protein-protein Interaction of the DEGs and selection of AKR1B10. (A) Online tool of STRING database analysis of the PPI network for the 11 DEGs decreased in liver cancer datasets. (B) Online tool of STRING database analysis of the PPI network for the 4 DEGs over-expressed in liver cancer datasets. (C) Amplifcation of the network for PPI associated with AKR1B10, which demonstrates a complex network between AKR1B10 and proteins critically functions in tumorigenesis and process. Protein-protein interaction network for the overlapped DEGs from STRING database, and Cytoscape sof- ware was shown in Fig. 2A,B. Te detailed statistic summaries for the interacted proteins of the DE mRNAs with the combined score cutof 0.4 predicted by STRING database was shown in Supp. Table 2. Interestingly, AKR1B10, a member of aldo/keto reductase super-family, has been reported as key molecular reducing aliphatic and aromatic aldehydes for cell metabolism11. Tis process is involved in physiological reactions such as the reduction of isoprenyl aldehydes, conversion of retinal to retinol, and bio-transformation of pro-carcinogens12. Te PPI network for AKR1B10 was shown in Fig. 2C. Gene expression pattern of AKR1B10 in the HCC tissues and cell lines. As Fig. 3A showed, the initial exploration of the three databases demonstrated that AKR1B10 presented a signifcantly higher level of expression in tumor tissues compared to the normal liver tissues (P = 3.50E-11 for GSE14323, P = 8.17E-7 for GSE14520 and P = 6.98E-9 for GSE6764). To validate the discoveries from the database mining, we explored the expression pattern of AKR1B10 by using IHC assay in our 53 paired HCC tumor and non-cancerous tissue samples. Te cases were evaluated according to the expression intensity of AKR1B10, and were separated into low and high AKR1B10 expression group. For the tumor samples, 69.81% (37/53) of the cases were observed highly expressed AKR1B10, and only a portion of 30.19% (16/53) cases presented low AKR1B10 expression. For the non-cancerous specimens paired, SCIENTIFIC REPORTS | (2018) 8:11094 | DOI:10.1038/s41598-018-29271-3 3 www.nature.com/scientificreports/ Figure 3. AKR1B10 expression profle in NCBI GEO datasets and HCC patients’ specimens (A) Comparison of AKR1B10 mRNA expression status respectively in GSE14520, GSE14323 and GSE6764 liver cancer datasets through t-test.
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