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Lu W, Wang Q, Liu L, Luo W. Exploring the mystery of colon cancer from the perspective of molecular subtypes and treatment. Sci Rep 2024; 14:10883. [PMID: 38740818 DOI: 10.1038/s41598-024-60495-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2023] [Accepted: 04/23/2024] [Indexed: 05/16/2024] Open
Abstract
The molecular categorization of colon cancer patients remains elusive. Gene set enrichment analysis (GSEA), which investigates the dysregulated genes among tumor and normal samples, has revealed the pivotal role of epithelial-to-mesenchymal transition (EMT) in colon cancer pathogenesis. In this study, we employed multi-clustering method for grouping data, resulting in the identification of two clusters characterized by varying prognostic outcomes. These two subgroups not only displayed disparities in overall survival (OS) but also manifested variations in clinical variables, genetic mutation, and gene expression profiles. Using the nearest template prediction (NTP) method, we were able to replicate the molecular classification effectively within the original dataset and validated it across multiple independent datasets, underscoring its robust repeatability. Furthermore, we constructed two prognostic signatures tailored to each of these subgroups. Our molecular classification, centered on EMT, hold promise in offering fresh insights into the therapy strategies and prognosis assessment for colon cancer.
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Affiliation(s)
- Wenhong Lu
- The Second Affiliated Hospital of Hunan University of Chinese Medicine, Changsha, 410005, Hunan, People's Republic of China
| | - Qiwei Wang
- Hunan Provincial Rehabilitation Hospital, Changsha, 410007, Hunan, People's Republic of China
| | - Lifang Liu
- The First Affiliated Hospital of Hunan University of Chinese Medicine, Changsha, 410007, Hunan, People's Republic of China
| | - Wenpeng Luo
- The Second Affiliated Hospital of Hunan University of Chinese Medicine, Changsha, 410005, Hunan, People's Republic of China.
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Karimi B, Mokhtari K, Rozbahani H, Peymani M, Nabavi N, Entezari M, Rashidi M, Taheriazam A, Ghaedi K, Hashemi M. Pathological roles of miRNAs and pseudogene-derived lncRNAs in human cancers, and their comparison as prognosis/diagnosis biomarkers. Pathol Res Pract 2024; 253:155014. [PMID: 38128189 DOI: 10.1016/j.prp.2023.155014] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/23/2023] [Revised: 12/02/2023] [Accepted: 12/02/2023] [Indexed: 12/23/2023]
Abstract
This review examines and compares the diagnostic and prognostic capabilities of miRNAs and lncRNAs derived from pseudogenes in cancer patients. Additionally, it delves into their roles in cancer pathogenesis. Both miRNAs and pseudogene-derived lncRNAs have undergone thorough investigation as remarkably sensitive and specific cancer biomarkers, offering significant potential for cancer detection and monitoring. . Extensive research is essential to gain a complete understanding of the precise roles these non-coding RNAs play in cancer, allowing the development of novel targeted therapies and biomarkers for improved cancer detection and treatment approaches.
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Affiliation(s)
- Bahareh Karimi
- Department of Cellular and Molecular Biology and Microbiology, Faculty of Biological Science and Technology, University of Isfahan, Isfahan, Iran
| | - Khatere Mokhtari
- Department of Animal Biotechnology, Cell Science Research Center, Royan Institute for Biotechnology, ACECR, Isfahan, Iran
| | - Hossein Rozbahani
- Department of Psychology, North Tehran Branch, Islamic Azad University, Tehran, Iran; Department of Psychology, West Tehran Branch, Islamic Azad University, Tehran, Iran
| | - Maryam Peymani
- Department of Biology, Faculty of Basic Sciences, Shahrekord Branch, Islamic Azad University, Shahrekord, Iran
| | - Noushin Nabavi
- Department of Urologic Sciences and Vancouver Prostate Centre, University of British Columbia, Vancouver, BC V6H3Z6, Canada
| | - Maliheh Entezari
- Farhikhtegan Medical Convergence Sciences Research Center, Farhikhtegan Hospital Tehran Medical Sciences, Islamic Azad University, Tehran, Iran; Department of Genetics, Faculty of Advanced Science and Technology, Tehran Medical Sciences, Islamic Azad University, Tehran, Iran
| | - Mohsen Rashidi
- Department Pharmacology, Faculty of Medicine, Mazandaran University of Medical Sciences, Sari, Iran; The Health of Plant and Livestock Products Research Center, Mazandaran University of Medical Sciences, Sari, Iran.
| | - Afshin Taheriazam
- Department of Genetics, Faculty of Advanced Science and Technology, Tehran Medical Sciences, Islamic Azad University, Tehran, Iran; Department of Orthopedics, Faculty of medicine, Tehran Medical Sciences, Islamic Azad University, Tehran, Iran.
| | - Kamran Ghaedi
- Department of Cell and Molecular Biology and Microbiology, Faculty of Biological Science and Technology, University of Isfahan, Isfahan, Iran.
| | - Mehrdad Hashemi
- Farhikhtegan Medical Convergence Sciences Research Center, Farhikhtegan Hospital Tehran Medical Sciences, Islamic Azad University, Tehran, Iran; Department of Genetics, Faculty of Advanced Science and Technology, Tehran Medical Sciences, Islamic Azad University, Tehran, Iran.
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Wen H, Feng H, Ma Q, Liang C. LncRNA PCGEM1 induces proliferation and migration in non-small cell lung cancer cells through modulating the miR-590-3p/SOX11 axis. BMC Pulm Med 2021; 21:234. [PMID: 34261474 PMCID: PMC8278585 DOI: 10.1186/s12890-021-01600-9] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/08/2020] [Accepted: 05/24/2021] [Indexed: 01/23/2023] Open
Abstract
Background Non-small cell lung cancer (NSCLC) is one of the most prevalent cancers. As reported, long non-coding RNAs (lncRNAs) induce various biological behaviors in cancers. LncRNA PCGEM1 prostate-specific transcript (PCGEM1) is reported to exert carcinogenic effect on certain cancers. Our research aimed to explore the role of PCGEM1 in NSCLC. Methods We enrolled forty NSCLC patients to explore PCGEM1 expression in clinical NSCLC tissues. Colony formation assay, CCK-8, Transwell assay were conducted to reveal cell proliferation, viability, migration and invasion. Luciferase reporter assay, RNA pull down, and RIP assay were performed to investigate the downstream axis of PCGEM1. Results PCGEM1 was significantly upregulated in NSCLC cells and tissues. Subsequently, in vitro loss-of-function experiments illustrated the carcinogenic role of PCGEM1 in NSCLC through promoting viability, proliferation, migration, and invasion. MiR-590-3p was confirmed to be a downstream gene of PCGEM1. Furthermore, SRY-box transcription factor 11 (SOX11) was verified to be a target of miR-590-3p. Additionally, rescue experiments indicated that miR-590-3p inhibitor or pcDNA3.1/SOX11 rescued the impacts of downregulated PCGEM1 on NSCLC cell proliferation, viability, migration and invasion. Conclusions LncRNA PCGEM1 aggravated proliferative and migrative abilities in NSCLC via the miR-590-3p/SOX11 axis. Supplementary Information The online version contains supplementary material available at 10.1186/s12890-021-01600-9.
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Affiliation(s)
- Huanshun Wen
- Department of Thoracic Surgery, China-Japan Friendship Hospital, No. 2 Yinghua East Street, Chaoyang District, Beijing, 100029, China
| | - Hongxiang Feng
- Department of Thoracic Surgery, China-Japan Friendship Hospital, No. 2 Yinghua East Street, Chaoyang District, Beijing, 100029, China
| | - Qianli Ma
- Department of Thoracic Surgery, China-Japan Friendship Hospital, No. 2 Yinghua East Street, Chaoyang District, Beijing, 100029, China
| | - Chaoyang Liang
- Department of Thoracic Surgery, China-Japan Friendship Hospital, No. 2 Yinghua East Street, Chaoyang District, Beijing, 100029, China.
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Zhou P, Lu Y, Zhang Y, Wang L. Construction of an Immune-Related Six-lncRNA Signature to Predict the Outcomes, Immune Cell Infiltration, and Immunotherapy Response in Patients With Hepatocellular Carcinoma. Front Oncol 2021; 11:661758. [PMID: 34277410 PMCID: PMC8283691 DOI: 10.3389/fonc.2021.661758] [Citation(s) in RCA: 38] [Impact Index Per Article: 12.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2021] [Accepted: 06/08/2021] [Indexed: 12/15/2022] Open
Abstract
BACKGROUND Hepatocellular carcinoma (HCC) is one of the world's most lethal malignant tumors with a poor prognosis. Growing evidence has been demonstrating that immune-related long non-coding RNAs (lncRNAs) are relevant to the tumor microenvironment (TME) and can help assess the effects of immunotherapy and evaluate one's prognosis. This study aims to identify an immune-related lncRNA signature for the prospective assessment of the immunotherapy and prognosis in HCC. METHOD We downloaded HCC RNA-seq data and clinical information from The Cancer Genome Atlas (TCGA) project database. We first used ESTIMATE to evaluate the TME. Then, we conducted a cox regression analysis to construct a prognostic signature and the riskScore. We then applied the univariate Cox regression, multivariate Cox regression, principal components analysis (PCA), receiver operating characteristic (ROC) curve, and stratification analyses to confirm our previous assessments. Afterward, we employed a gene set enrichment analysis (GSEA) to explore the biological processes and pathways. Besides, we used CIBERSORT to estimate the abundance of tumor-infiltrating immune cells (TIICs). Furthermore, we investigated the relationship between the immune-related lncRNA signature and immune checkpoint genes. Finally, we used the quantitative real-time polymerase chain reaction (qRT-PCR) assays to demonstrate the expression of the six lncRNAs. RESULTS We identified six immune-related lncRNAs - MSC-AS1, AC145207.5, SNHG3, AL365203.2, AL031985.3, NRAV - which show the ability to stratify patients into high-risk and low-risk groups with significantly different survival rates. The univariate Cox regression, multivariate Cox regression, ROC, and stratification analyses confirmed that the immune-related six-lncRNA signature was a novel independent prognostic factor in HCC patients. The high-risk group and low-risk group illustrated contrasting distributions in PCA. The GSEA suggested that the immune-related six-lncRNA signature was involved in the immune-related biological processes and pathways. Besides, the immune-related six-lncRNA signature was associated with the infiltration of immune cells. Furthermore, it was linked with the expression of critical immune genes and could predict immunotherapy's clinical response. Finally, the qRT-PCR demonstrated that the six lncRNAs were significantly differentially expressed in HCC cell lines and normal hepatic cell lines. CONCLUSION In summary, we identified an immune-related six-lncRNA signature that can predict the outcomes, immune cell infiltration, and immunotherapy response in patients with hepatocellular carcinoma.
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Affiliation(s)
| | - Yuhua Lu
- Department of Hepatobiliary and Pancreatic Surgery, Affiliated Hospital of Nantong University, Nantong, China
| | - Yewei Zhang
- Department of Hepatobiliary and Pancreatic Surgery, Southeast University Zhongda Hospital, Nanjing, China
- Department of Hepatobiliary and Pancreatic Surgery, The Second Affiliated Hospital of Nanjing Medical University, Nanjing, China
| | - Lei Wang
- Department of Hepatobiliary and Pancreatic Surgery, Affiliated Hospital of Nantong University, Nantong, China
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Zhang F, Yu X, Lin Z, Wang X, Gao T, Teng D, Teng W. Using Tumor-Infiltrating Immune Cells and a ceRNA Network Model to Construct a Prognostic Analysis Model of Thyroid Carcinoma. Front Oncol 2021; 11:658165. [PMID: 34141614 PMCID: PMC8204697 DOI: 10.3389/fonc.2021.658165] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/25/2021] [Accepted: 04/13/2021] [Indexed: 12/24/2022] Open
Abstract
Thyroid carcinoma is a solid malignant tumor that has had a fast-growing incidence in recent years. Our research used thyroid carcinoma gene expression profiling from TCGA (The Cancer Genome Atlas) database to identify differentially expressed ceRNAs. Using the gene expression profiling from 502 carcinoma thyroid tissues and 58 normal thyroid tissues from the TCGA database, we established the thyroid carcinoma-specific competitive endogenous RNA (ceRNA) network and found nine overall survival (OS)-associated genes (PRDM1, TGFBR3, E2F1, FGF1, ADAM12, ALPL, RET, AL928654.2, AC128688.2). We quantified the proportions of immune cells using the algorithm “CIBERSORT”, found three OS-associated immune cells (memory B cells, M0 macrophages, and activated dendritic cells), and established a thyroid carcinoma-specific immune cell network based on that. The good reliabilities AUC (area under the curve) of 10-year survival (0.955, 0.944, respectively) were accessed from the nomograms of genes and immune cells. Subsequently, by conducting co-expression analyses, we found a potential regulation network among ceRNAs and immune cells. Besides, we found that ALPL (alkaline phosphatase) and hsa-miR-204-5p were significantly correlated and that ALPL was related to activated dendritic cells. We took advantage of multi-dimensional databases to verify our discovery. Besides, immunohistochemistry (IHC) assays were conducted to detect the expression of a dendritic cell marker (CD11c) and ALPL in thyroid carcinoma (TC) and paracancerous tissues. In summary, our study found a potential mechanism in which hsa-miR-204-5p regulated ALPL in activated dendritic cells, which may allow them to play a critical role in thyroid carcinoma. These findings provide potential prognostic biomarkers and therapeutic targets for thyroid carcinoma.
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Affiliation(s)
- Fan Zhang
- Department of Endocrinology and Metabolism, Institute of Endocrinology, National Health Commission Key Laboratory of Diagnosis and Treatment of Thyroid Diseases, The First Hospital of China Medical University, Shenyang, China
| | - Xiaohui Yu
- Department of Endocrinology and Metabolism, Institute of Endocrinology, National Health Commission Key Laboratory of Diagnosis and Treatment of Thyroid Diseases, The First Hospital of China Medical University, Shenyang, China
| | - Zheyu Lin
- Department of Endocrinology and Metabolism, Institute of Endocrinology, National Health Commission Key Laboratory of Diagnosis and Treatment of Thyroid Diseases, The First Hospital of China Medical University, Shenyang, China
| | - Xichang Wang
- Department of Endocrinology and Metabolism, Institute of Endocrinology, National Health Commission Key Laboratory of Diagnosis and Treatment of Thyroid Diseases, The First Hospital of China Medical University, Shenyang, China
| | - Tiantian Gao
- Department of Endocrinology and Metabolism, Institute of Endocrinology, National Health Commission Key Laboratory of Diagnosis and Treatment of Thyroid Diseases, The First Hospital of China Medical University, Shenyang, China
| | - Di Teng
- Department of Endocrinology and Metabolism, Institute of Endocrinology, National Health Commission Key Laboratory of Diagnosis and Treatment of Thyroid Diseases, The First Hospital of China Medical University, Shenyang, China
| | - Weiping Teng
- Department of Endocrinology and Metabolism, Institute of Endocrinology, National Health Commission Key Laboratory of Diagnosis and Treatment of Thyroid Diseases, The First Hospital of China Medical University, Shenyang, China
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Duan W, Wang K, Duan Y, Chen X, Chu X, Hu P, Xiong B. Combined Analysis of RNA Sequence and Microarray Data Reveals a Competing Endogenous RNA Network as Novel Prognostic Markers in Malignant Pleural Mesothelioma. Front Oncol 2021; 11:615234. [PMID: 33968720 PMCID: PMC8104912 DOI: 10.3389/fonc.2021.615234] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/08/2020] [Accepted: 02/15/2021] [Indexed: 12/13/2022] Open
Abstract
Malignant pleural mesothelioma (MPM) is a highly aggressive cancer with short survival time. Unbalanced competing endogenous RNAs (ceRNAs) have been shown to participate in the tumor pathogenesis and served as biomarkers for the clinical prognosis. However, the comprehensive analyses of the ceRNA network in the prognosis of MPM are still rarely reported. In this study, we obtained the transcriptome data of the MPM and the normal samples from TCGA, EGA, and GEO databases and identified the differentially expressed (DE) mRNAs, lncRNAs, and miRNAs. The functions of the prognostic genes and the overlapped DEmRNAs were further annotated by the multiple enrichment analyses. Then, the targeting relationships among lncRNA–miRNA and miRNA–mRNA were predicted and calculated, and a prognostic ceRNA regulatory network was established. We included the prognostic 73 mRNAs and 13 miRNAs and 26 lncRNAs into the ceRNA network. Moreover, 33 mRNAs, three miRNAs, and seven lncRNAs were finally associated with prognosis, and a model including seven mRNAs, two lincRNAs, and some clinical factors was finally established and validated by two independent cohorts, where CDK6 and SGMS1-AS1 were significant to be independent prognostic factors. In addition, the identified co-expressed modules associated with the prognosis were overrepresented in the ceRNA network. Multiple enrichment analyses showed the important roles of the extracellular matrix components and cell division dysfunction in the invasion of MPM potentially. In summary, the prognostic ceRNA network of MPM was established and analyzed for the first time and these findings shed light on the function of ceRNAs and revealed the potential prognostic and therapeutic biomarkers of MPM.
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Affiliation(s)
- Weicheng Duan
- Department of Forensic Medicine, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Kang Wang
- Department of Forensic Medicine, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Yijie Duan
- Department of Forensic Medicine, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Xiuyi Chen
- Key Laboratory of Environment and Health (HUST), Ministry of Education, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Xufeng Chu
- Department of Forensic Medicine, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Ping Hu
- Key Laboratory of Environment and Health (HUST), Ministry of Education, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Bo Xiong
- Department of Forensic Medicine, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
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Zhang Z, Ji M, Li J, Wu Q, Huang Y, He G, Xu J. Molecular Classification Based on Prognostic and Cell Cycle-Associated Genes in Patients With Colon Cancer. Front Oncol 2021; 11:636591. [PMID: 33898311 PMCID: PMC8059408 DOI: 10.3389/fonc.2021.636591] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2020] [Accepted: 02/11/2021] [Indexed: 01/27/2023] Open
Abstract
The molecular classification of patients with colon cancer is inconclusive. The gene set enrichment analysis (GSEA) of dysregulated genes among normal and tumor tissues indicated that the cell cycle played a crucial role in colon cancer. We performed univariate Cox regression analysis to find out the prognostic-related genes, and these genes were then intersected with cell cycle-associated genes and were further recognized as prognostic and cell cycle-associated genes. Unsupervised non-negative matrix factorization (NMF) clustering was performed based on cell cycle-associated genes. Two subgroups were identified with different overall survival, clinical features, cell cycle enrichment profile, and mutation profile. Through nearest template prediction (NTP), the molecular classification could be effectively repeated in the original data set and validated in several independent data sets indicating that the classification is highly repeatable. Furthermore, we constructed two prognostic signatures in two subgroups, respectively. Our molecular classification based on cell cycle may provide novel insight into the treatment and the prognosis of colon cancer.
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Affiliation(s)
- Zhiyuan Zhang
- Department of General Surgery, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Meiling Ji
- Department of General Surgery, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Jie Li
- Department of General Surgery, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
| | - Qi Wu
- Department of General Surgery, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Yuanjian Huang
- Department of General Surgery, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
| | - Guodong He
- Department of General Surgery, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Jianmin Xu
- Department of General Surgery, Zhongshan Hospital, Fudan University, Shanghai, China
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Zhang J, Lou W. A Key mRNA-miRNA-lncRNA Competing Endogenous RNA Triple Sub-network Linked to Diagnosis and Prognosis of Hepatocellular Carcinoma. Front Oncol 2020; 10:340. [PMID: 32257949 PMCID: PMC7092636 DOI: 10.3389/fonc.2020.00340] [Citation(s) in RCA: 38] [Impact Index Per Article: 9.5] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/19/2019] [Accepted: 02/26/2020] [Indexed: 01/27/2023] Open
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.
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Affiliation(s)
- Junjie Zhang
- Department of Hepatobiliary Surgery, The First People's Hospital of Fuyang Hangzhou, Hangzhou, China
| | - Weiyang Lou
- Department of Breast Surgery, The First Affiliated Hospital of Zhejiang University, College of Medicine, Zhejiang University, Hangzhou, China
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Zhao H, Zhang S, Shao S, Fang H. Identification of a Prognostic 3-Gene Risk Prediction Model for Thyroid Cancer. Front Endocrinol (Lausanne) 2020; 11:510. [PMID: 32849296 PMCID: PMC7423967 DOI: 10.3389/fendo.2020.00510] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/18/2019] [Accepted: 06/25/2020] [Indexed: 12/13/2022] Open
Abstract
Objective: We aimed to screen the genes associated with thyroid cancer (THCA) prognosis, and construct a poly-gene risk prediction model for prognosis prediction and improvement. Methods: The HTSeq-Counts data of THCA were accessed from TCGA database, including 505 cancer samples and 57 normal tissue samples. "edgeR" package was utilized to perform differential analysis, and weighted gene co-expression network analysis (WGCNA) was applied to screen the differential co-expression genes associated with THCA tissue types. Univariant Cox regression analysis was further used for the selection of survival-related genes. Then, LASSO regression model was constructed to analyze the genes, and an optimal prognostic model was developed as well as evaluated by Kaplan-Meier and ROC curves. Results: Three thousand two hundred seven differentially expressed genes (DEGs) were obtained by differential analysis and 23 co-expression genes (|COR| > 0.5, P < 0.05) were gained after WGCNA analysis. In addition, eight genes significantly related to THCA survival were screened by univariant Cox regression analysis, and an optimal prognostic 3-gene risk prediction model was constructed after genes were analyzed by the LASSO regression model. Based on this model, patients were grouped into the high-risk group and low-risk group. Kaplan-Meier curve showed that patients in the low-risk group had much better survival than those in the high-risk group. Moreover, great accuracy of the 3-gene model was revealed by ROC curve and the remarkable correlation between the model and patients' prognosis was verified using the multivariant Cox regression analysis. Conclusion: The prognostic 3-gene model composed by GHR, GPR125, and ATP2C2 three genes can be used as an independent prognostic factor and has better prediction for the survival of THCA patients.
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