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Singh P, Solanki R, Tasneem A, Suri S, Kaur H, Shah SR, Dohare R. Screening of miRNAs as prognostic biomarkers and their associated hub targets across Hepatocellular carcinoma using survival-based bioinformatics approach. J Genet Eng Biotechnol 2024; 22:100337. [PMID: 38494261 DOI: 10.1016/j.jgeb.2023.100337] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/19/2024]
Abstract
BACKGROUND The hepatocellular carcinoma (HCC) incident rate is gradually increasing yearly despite all the research and efforts taken by scientific communities and governing bodies. Approximately 90% of all liver cancer cases belong to HCC. Usually, HCC patients approach the treatment in the late stages of this malignancy which becomes the primary cause of high mortality rate. The knowledge about molecular pathogenesis of HCC is limited and needs more attention from researchers to identify the driver genes and miRNAs, which causes to translate this information into clinical practice. Therefore, the key regulators identification of miRNA-mRNA regulatory network is essential to identify HCC-associated genes. METHODOLOGY We extracted microRNA (miRNA) and messenger RNA (mRNA) expression datasets of normal and tumor HCC patient samples from UCSC Xena followed by identifying differentially expressed genes (DEGs) and differentially expressed miRNAs (DEMs). Univariate and multivariate cox-proportional hazard models were utilized to identify DEMs having significant association with overall survival (OS). Kaplan-Meier (KM) plotter was used to validate the presence of prognostic DEMs. A risk-score model was used to evaluate the effectiveness of KM-plotter validated DEMs combination on risk of samples. Target DEGs of prognostic miRNAs were identified via sources such as miRTargetLink and miRWalk followed by their validation in an external microarray cohort and enrichment analysis. RESULTS 562 DEGs and 388 DEMs were identified followed by seven prognostic miRNAs (i.e., miR-19a, miR-19b, miR-30d-5p, miR-424-5p, miR-3677-5p, miR-3913-5p, miR-7705) post univariate, multivariate, risk-score model evaluation and KM-plotter analyses. ANLN, MRO, CPEB3 were their targets and were also validated in GSE84005 dataset. CONCLUSIONS The findings of this study decipher that most significant miRNAs and their identified target genes have association with apoptosis, inflammation, cell cycle regulation and cancer-related pathways, which appear to contribute to HCC pathogenesis and therefore, the discovery of new targets.
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Affiliation(s)
- Prithvi Singh
- Centre for Interdisciplinary Research in Basic Sciences, Jamia Millia Islamia, New Delhi 110025, India
| | - Rubi Solanki
- School of Interdisciplinary Sciences and Technology, Jamia Hamdard, New Delhi 110062, India
| | - Alvea Tasneem
- Centre for Interdisciplinary Research in Basic Sciences, Jamia Millia Islamia, New Delhi 110025, India
| | - Simran Suri
- Centre for Interdisciplinary Research in Basic Sciences, Jamia Millia Islamia, New Delhi 110025, India
| | - Harleen Kaur
- Department of Computer Science and Engineering, School of Engineering Sciences and Technology, Jamia Hamdard, New Delhi 110062, India
| | - Sapna Ratan Shah
- School of Computational and Integrative Sciences, Jawaharlal Nehru University, New Delhi 110067, India
| | - Ravins Dohare
- Centre for Interdisciplinary Research in Basic Sciences, Jamia Millia Islamia, New Delhi 110025, India.
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Ruan Y, Li Z, Xie Y, Sun W, Guo J. Detecting plasma hsa_circ_0061276 in patients with gastric cancer by reverse transcription-digital polymerase chain reaction. Front Oncol 2022; 12:1042248. [PMID: 36620570 PMCID: PMC9816570 DOI: 10.3389/fonc.2022.1042248] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/12/2022] [Accepted: 12/12/2022] [Indexed: 12/24/2022] Open
Abstract
Background The role of circular RNAs (circRNAs) in the occurrence of gastric cancer is still unclear. Therefore, the diagnostic value and mechanisms underlying hsa_circ_0061276 in the occurrence of gastric cancer were explored. Methods Reverse transcription-droplet digital polymerase chain reaction was used to detect the copy number of hsa_circ_0061276 in plasma from healthy individuals, as well as from patients with gastric precancerous lesions or early-stage or advanced gastric cancer. Plasmids overexpressing or knocking down hsa_circ_0061276 expression were transfected into gastric cancer cells. The effects on the growth, migration, and cell cycle distribution of gastric cancer cells were then analyzed. Finally, miRanda and RNAhybrid were used to explore the binding sites between hsa_circ_0061276 and microRNAs (miRNAs). A double luciferase reporter gene assay was used to confirm the miRNA sponge effect. Results The results show that plasma hsa_circ_0061276 copy number showed a trend of a gradual decrease when comparing healthy controls to the early cancer group and advanced gastric cancer group. Overexpression of hsa_circ_0061276 inhibited the growth and migration of gastric cancer cells. Through bioinformatic analyses combined with cellular experiments, it was found that hsa_circ_0061276 inhibited the growth of gastric cancer by binding to hsa-miR-7705. Conclusion Hsa_circ_0061276 may be a new biomarker for gastric cancer. The tumor suppressor role of hsa_circ_0061276 on gastric cancer likely occurs through a sponge effect on miRNAs such as hsa-miR-7705.
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Affiliation(s)
- Yao Ruan
- Department of Gastrointestinal Surgery, The Affiliated People’s Hospital of Ningbo University, Ningbo, China,Department of Biochemistry and Molecular Biology, and Zhejiang Key Laboratory of Pathophysiology, School of Basic Medical Sciences, School of Medicine, Ningbo University, Ningbo, China
| | - Zhe Li
- Department of Biochemistry and Molecular Biology, and Zhejiang Key Laboratory of Pathophysiology, School of Basic Medical Sciences, School of Medicine, Ningbo University, Ningbo, China
| | - Yaoyao Xie
- Department of Biochemistry and Molecular Biology, and Zhejiang Key Laboratory of Pathophysiology, School of Basic Medical Sciences, School of Medicine, Ningbo University, Ningbo, China
| | - Weiliang Sun
- Department of Gastrointestinal Surgery, The Affiliated People’s Hospital of Ningbo University, Ningbo, China,Institute of Gastrointestinal Tumor of Ningbo University, Ningbo, China
| | - Junming Guo
- Department of Gastrointestinal Surgery, The Affiliated People’s Hospital of Ningbo University, Ningbo, China,Department of Biochemistry and Molecular Biology, and Zhejiang Key Laboratory of Pathophysiology, School of Basic Medical Sciences, School of Medicine, Ningbo University, Ningbo, China,Institute of Gastrointestinal Tumor of Ningbo University, Ningbo, China,*Correspondence: Junming Guo,
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Song Y, Du Y, Qin C, Liang H, Yang W, Lin J, Ding M, Han J, Xu T. Gemcitabine-Resistant Biomarkers in Bladder Cancer are Associated with Tumor-Immune Microenvironment. Front Cell Dev Biol 2022; 9:809620. [PMID: 35127724 PMCID: PMC8814447 DOI: 10.3389/fcell.2021.809620] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/05/2021] [Accepted: 12/13/2021] [Indexed: 12/24/2022] Open
Abstract
To identify key biomarkers in gemcitabine (GEM)-resistant bladder cancer (BCa) and investigate their associations with tumor-infiltrating immune cells in a tumor immune microenvironment, we performed the present study on the basis of large-scale sequencing data. Expression profiles from the Gene Expression Omnibus GSE77883 dataset and The Cancer Genome Atlas BLCA dataset were analyzed. Both BCa development and GEM-resistance were identified to be immune-related through evaluating tumor-infiltrating immune cells. Eighty-two DEGs were obtained to be related to GEM-resistance. Functional enrichment analysis demonstrated they were related to regulation of immune cells proliferation. Protein-protein interaction network selected six key genes (CAV1, COL6A2, FABP4, FBLN1, PCOLCE, and CSPG4). Immunohistochemistry confirmed the down-regulation of the six key genes in BCa. Survival analyses revealed the six key genes were significantly associated with BCa overall survival. Correlation analyses revealed the six key genes had high infiltration of most immune cells. Gene set enrichment analysis further detected the key genes might regulate GEM-resistance through immune response and drug metabolism of cytochrome P450. Next, microRNA-gene regulatory network identified three key microRNAs (hsa-miR-124-3p, hsa-miR-26b-5p, and hsa-miR-192-5p) involved in GEM-resistant BCa. Connectivity Map analysis identified histone deacetylase inhibitors might circumvent GEM-resistance. In conclusion, CAV1, COL6A2, FABP4, FBLN1, PCOLCE, and CSPG4 were identified to be critical biomarkers through regulating the immune cell infiltration in an immune microenvironment of GEM-resistance and could act as promising treatment targets for GEM-resistant muscle-invasive BCa.
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Affiliation(s)
- Yuxuan Song
- Department of Urology, Peking University People’s Hospital, Beijing, China
- Biomedical Pioneering Innovation Center (BIOPIC), School of Life Sciences, Peking University, Beijing, China
| | - Yiqing Du
- Department of Urology, Peking University People’s Hospital, Beijing, China
| | - Caipeng Qin
- Department of Urology, Peking University People’s Hospital, Beijing, China
| | - Haohong Liang
- Biomedical Pioneering Innovation Center (BIOPIC), School of Life Sciences, Peking University, Beijing, China
| | - Wenbo Yang
- Department of Urology, Peking University People’s Hospital, Beijing, China
| | - Jiaxing Lin
- Department of Urology, Peking University People’s Hospital, Beijing, China
| | - Mengting Ding
- Department of Urology, Peking University People’s Hospital, Beijing, China
| | - Jingli Han
- Department of Urology, Peking University People’s Hospital, Beijing, China
| | - Tao Xu
- Department of Urology, Peking University People’s Hospital, Beijing, China
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Zhu R, Yang X, Guo W, Xu XJ, Zhu L. An eight-mRNA signature predicts the prognosis of patients with bladder urothelial carcinoma. PeerJ 2019; 7:e7836. [PMID: 31660264 PMCID: PMC6814068 DOI: 10.7717/peerj.7836] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/05/2019] [Accepted: 09/05/2019] [Indexed: 12/27/2022] Open
Abstract
Background Bladder cancer is one of the most common cancers, and its histopathological type is mainly bladder urothelial carcinoma, accounting for about 90%. The prognostic biomarkers of bladder cancer are classified into clinical features biomarkers and molecular biomarkers. Nevertheless, due to the existence of individual specificity, patients with similar pathological characteristics still have great differences in the risk of disease recurrence. Therefore, it is often inaccurate to predict the survival status of patients based on clinical characteristic biomarkers, and a prognostic molecular biomarker that can grade the risk of bladder cancer patients is needed. Methods A total of three bladder urothelial carcinoma datasets were used in this study from the Cancer Genome Atlas database and Gene Expression Omnibus database. In order to avoid overfitting, all samples were randomly divided into one training set and three validation sets, which were used to construct and test the prognostic biomarker model of bladder urothelial carcinoma. Univariate and multivariate Cox regression were used to screen candidate mRNAs and construct prognostic biomarkers model. Kaplan-Meier survival analysis and the receiver operating characteristic (ROC) curve were used to evaluate the predictive performance of the model. Results A prognostic biomarker model of bladder urothelial carcinoma combining with eight mRNA was constructed. Kaplan-Meier analyses indicated that a significant difference in the survival time of patients between the high-risk and the low-risk group. The area under the ROC curve were 0.632 (95% confidence interval (CI) [0.541-0.723]), 0.693 (95% CI [0.601-0.784]) and 0.686 (95% CI [0.540-0.831]) when the model was used to predict the patient's survival time in three validation datasets. The model showed high accuracy and applicability.
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Affiliation(s)
- Rui Zhu
- Department of Mathematics, Shanghai University, Shanghai, China.,School of Life Sciences, Shanghai University, Shanghai, China
| | - Xin Yang
- School of Life Sciences, Shanghai University, Shanghai, China
| | - Wenna Guo
- School of Life Sciences, Zhengzhou University, Zhengzhou, Henan, China
| | - Xin-Jian Xu
- Department of Mathematics, Shanghai University, Shanghai, China
| | - Liucun Zhu
- School of Life Sciences, Shanghai University, Shanghai, China
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Chen F, Zhou H, Wu C, Yan H. Identification of miRNA profiling in prediction of tumor recurrence and progress and bioinformatics analysis for patients with primary esophageal cancer: Study based on TCGA database. Pathol Res Pract 2018; 214:2081-2086. [PMID: 30477645 DOI: 10.1016/j.prp.2018.10.009] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/29/2018] [Revised: 09/13/2018] [Accepted: 10/17/2018] [Indexed: 02/07/2023]
Abstract
OBJECT This study focused on the identification of prognostic miRNAs for the prediction of tumor recurrence and progress in esophageal cancer. METHODS MiRNA profiling and clinical characteristics of esophageal cancer patients was downloaded from the TCGA database. Univariate analysis was performed to select potential prognostic miRNAs and covariates. LASSO based logistic regression was conducted to identify the prognostic miRNAs given covariates. Bioinformatics analysis including gene ontology, disease ontology and pathway enrichment analysis were performed. A nomogram was generated based on multivariate logistic regression to illustrate the association between the identified miRNAs and the risk of tumor recurrence and progress. RESULTS A total of 1881 miRNAs and 10 clinical characteristics were obtained from TCGA database. 18 miRNAs were finally identified in which 6 miRNAs were identified for the first time to be associated with the tumor recurrence and progress of esophageal cancer given covariates. Bioinformatics analysis suggested that the identified miRNAs were associated with the tumor recurrence and progress of esophageal cancer. The association between identified miRNAs and risk of tumor recurrence and progress were presented in a nomogram. CONCLUSION The 6 newly identified miRNAs may be potential biomarkers for the prediction of tumor recurrence and progress of esophageal cancer.
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Affiliation(s)
- Fangyao Chen
- Department of Epidemiology and Health Statistics, School of Public Health, Xi'an Jiaotong University Health Science Center, 76 Yanta Xilu Road, Xi'an, Shaanxi, 710061, China
| | - Hui Zhou
- Department of Pharmacy, First Affiliated Hospital of Xi'an Jiaotong University, 277 Yanta Xilu Road, Xi'an, Shaanxi, 710061, China
| | - Chenqiuzi Wu
- First Affiliated Hospital of Xi'an Jiaotong University, 277 Yanta Xilu Road, Xi'an, Shaanxi, 710061, China
| | - Hong Yan
- Department of Epidemiology and Health Statistics, School of Public Health, Xi'an Jiaotong University Health Science Center, 76 Yanta Xilu Road, Xi'an, Shaanxi, 710061, China.
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Liu M, Chen Y, Huang B, Mao S, Cai K, Wang L, Yao X. Tumor-suppressing effects of microRNA-612 in bladder cancer cells by targeting malic enzyme 1 expression. Int J Oncol 2018; 52:1923-1933. [PMID: 29620192 PMCID: PMC5919718 DOI: 10.3892/ijo.2018.4342] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/10/2017] [Accepted: 03/28/2018] [Indexed: 12/21/2022] Open
Abstract
The present study investigated the possible tumor-suppressing function of microRNA (miR)-612 and the underlying molecular mechanism of its action in bladder cancer in vitro and in vivo. Reverse transcription-quantitative polymerase chain reaction (RT-qPCR) was carried out to quantify the expression levels of miR-612 in bladder cancer tissues and cell lines. The data demonstrated that the level of miR-612 expression was significantly reduced in bladder cancer tissues and cell lines, as compared with that in non-cancerous tissues and cells. Reduced miR-612 expression was associated with advanced tumor, lymph node and metastasis stages, and with distant metastasis of bladder cancer. A functional study revealed that transfection of cells with an miR-612 mimic suppressed bladder cancer cell growth, colony formation, migration, invasion and epithelial-mesenchymal transition. Bioinformatics analysis identified that miR-612 targeted the expression of malic enzyme 1 (ME1), and this was confirmed by western blot and luciferase reporter assay results. Furthermore, the ME1 expression levels were inversely associated with miR-612 expression in bladder cancer tissue specimens. In addition, knockdown of ME1 expression using ME1 siRNA mimicked the effect of ectopic miR-612 overexpression in bladder cancer cells in terms of tumor cell growth, migration and invasion. By contrast, ME1 overexpression weakened the inhibitory effect of the miR-612 mimic in bladder cancer cells. In conclusion, the present study demonstrated that miR-612 may function as a tumor suppressor in bladder cancer by targeting ME1 expression.
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Affiliation(s)
- Mengnan Liu
- Anhui Medical University, Hefei, Anhui 230601, P.R. China
| | - Yifan Chen
- Anhui Medical University, Hefei, Anhui 230601, P.R. China
| | - Bisheng Huang
- Anhui Medical University, Hefei, Anhui 230601, P.R. China
| | - Shiyu Mao
- Anhui Medical University, Hefei, Anhui 230601, P.R. China
| | - Keke Cai
- Anhui Medical University, Hefei, Anhui 230601, P.R. China
| | - Longsheng Wang
- Anhui Medical University, Hefei, Anhui 230601, P.R. China
| | - Xudong Yao
- Anhui Medical University, Hefei, Anhui 230601, P.R. China
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