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Bozgeyik E, Elek A, Gocer Z, Bozgeyik I. The fate and function of non-coding RNAs during necroptosis. Epigenomics 2024:1-15. [PMID: 38884366 DOI: 10.1080/17501911.2024.2354653] [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: 09/14/2023] [Accepted: 05/07/2024] [Indexed: 06/18/2024] Open
Abstract
Necroptosis is a novel form of cell death which is activated when apoptotic cell death signals are disrupted. Accumulating body of observations suggests that noncoding RNAs, which are the lately discovered mystery of the human genome, are significantly associated with necroptotic signaling circuitry. The fate and function of miRNAs have been well documented in human disease, especially cancer. Recently, lncRNAs have gained much attention due to their diverse regulatory functions. Although available studies are currently based on bioinformatic analysis, predicted interactions desires further attention, as these hold significant promise and should not be overlooked. In the light of these, here we comprehensively review and discuss noncoding RNA molecules that play significant roles during execution of necroptotic cell death.
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Affiliation(s)
- Esra Bozgeyik
- Department of Medical Services & Techniques, Vocational School of Health Services, Adiyaman University, Adiyaman, Turkey
| | - Alperen Elek
- Faculty of Medicine, Ege University, Izmir, Turkey
| | - Zekihan Gocer
- Faculty of Medicine, Gaziantep University, Gaziantep, Turkey
| | - Ibrahim Bozgeyik
- Department of Medical Biology, Faculty of Medicine, Adiyaman University, Adiyaman, Turkey
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2
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Qin Y, Sheng Y, Ren M, Hou Z, Xiao L, Chen R. Identification of necroptosis-related gene signatures for predicting the prognosis of ovarian cancer. Sci Rep 2024; 14:11133. [PMID: 38750159 PMCID: PMC11096311 DOI: 10.1038/s41598-024-61849-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/10/2024] [Accepted: 05/10/2024] [Indexed: 05/18/2024] Open
Abstract
Ovarian cancer (OC) is one of the most prevalent and fatal malignant tumors of the female reproductive system. Our research aimed to develop a prognostic model to assist inclinical treatment decision-making.Utilizing data from The Cancer Genome Atlas (TCGA) and copy number variation (CNV) data from the University of California Santa Cruz (UCSC) database, we conducted analyses of differentially expressed genes (DEGs), gene function, and tumor microenvironment (TME) scores in various clusters of OC samples.Next, we classified participants into low-risk and high-risk groups based on the median risk score, thereby dividing both the training group and the entire group accordingly. Overall survival (OS) was significantly reduced in the high-risk group, and two independent prognostic factors were identified: age and risk score. Additionally, three genes-C-X-C Motif Chemokine Ligand 10 (CXCL10), RELB, and Caspase-3 (CASP3)-emerged as potential candidates for an independent prognostic signature with acceptable prognostic value. In Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses, pathways related to immune responses and inflammatory cell chemotaxis were identified. Cellular experiments further validated the reliability and precision of our findings. In conclusion, necroptosis-related genes play critical roles in tumor immunity, and our model introduces a novel strategy for predicting the prognosis of OC patients.
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Affiliation(s)
- Yuling Qin
- Guang'anmen Hospital, China Academy of Chinese Medical Sciences, No. 5, Beixiange Road, Xicheng District, Beijing, 100053, China
| | - Yawen Sheng
- Shandong University of Traditional Chinese Medicine, Jinan, 250014, Shandong, China
| | - Mengxue Ren
- Guang'anmen Hospital, China Academy of Chinese Medical Sciences, No. 5, Beixiange Road, Xicheng District, Beijing, 100053, China
| | - Zitong Hou
- Guang'anmen Hospital, China Academy of Chinese Medical Sciences, No. 5, Beixiange Road, Xicheng District, Beijing, 100053, China
| | - Lu Xiao
- Guang'anmen Hospital, China Academy of Chinese Medical Sciences, No. 5, Beixiange Road, Xicheng District, Beijing, 100053, China
| | - Ruixue Chen
- Guang'anmen Hospital, China Academy of Chinese Medical Sciences, No. 5, Beixiange Road, Xicheng District, Beijing, 100053, China.
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Shao J, Zhang Y, Chang Z, Du S, Li W, Bai Y, Lu C, Xu T. A novel ferroptosis-related microRNA signature with prognostic value in osteosarcoma. Acta Biochim Biophys Sin (Shanghai) 2023; 55:1758-1769. [PMID: 37814812 PMCID: PMC11000229 DOI: 10.3724/abbs.2023236] [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: 02/20/2023] [Accepted: 05/06/2023] [Indexed: 10/11/2023] Open
Abstract
The induction of ferroptosis is suggested to be a potential therapeutic strategy for cancers. MicroRNAs (miRNAs) are reported to play an important role in cell death processes. This study aims to construct and validate a risk model based on ferroptosis-related miRNAs (FR_miRNAs) to predict prognosis and identify novel therapeutic targets for osteosarcoma. Data from the Therapeutically Applicable Research to Generate Effective Treatments database are used as the training cohort. A prognostic signature based on two FR_miRNAs (miR-635 and miR-593) is developed using univariate Cox regression, least absolute shrinkage and selection operator regression, and multivariate Cox regression analyses. The area under the curve values of the prognostic signature to predict the 1-year, 2-year, 3-year, and 5-year overall survival rates in patients with osteosarcoma are 0.782, 0.781, 0.722, and 0.777, respectively, indicating a good predictive ability. Based on the risk score, patients are divided into low-risk and high-risk groups. Patients with high-risk scores are associated with poor survival. The risk level is determined to be an independent prognostic factor. A nomogram is established for predicting prognosis. The expression levels of PRNP (miR-635-related ferroptosis-related gene (FRG); P=0.024) and HILPDA (miR-593-related FRG; P=0.025) are significantly different between the low-risk and high-risk groups. All results are validated in an external cohort (GSE39040). The results of the functional assay reveal that miR-635 mimics inhibit osteosarcoma (OS) cell proliferation and migration, whereas miR-593 overexpression exerts the opposite effect. In conclusion, miR-635 and miR-593 exert contrasting regulatory effects on OS cell proliferation and migration.
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Affiliation(s)
- Jie Shao
- Department of Spine SurgeryChanghai HospitalNaval Medical University (Second Military Medical
University)Shanghai200043China
| | - Yi Zhang
- Department of Spine SurgeryChanghai HospitalNaval Medical University (Second Military Medical
University)Shanghai200043China
| | - Zhu Chang
- Department of Orthopaedic SurgeryNaval Medical University (Second Military Medical
University)Shanghai200052China
| | - Shiyao Du
- Department of Orthopaedic SurgeryNaval Medical University (Second Military Medical
University)Shanghai200052China
| | - Wei Li
- Department of Spine SurgeryChanghai HospitalNaval Medical University (Second Military Medical
University)Shanghai200043China
| | - Yushu Bai
- Department of Spine SurgeryChanghai HospitalNaval Medical University (Second Military Medical
University)Shanghai200043China
| | - Chunwen Lu
- Department of Orthopaedic SurgeryNaval Medical University (Second Military Medical
University)Shanghai200052China
| | - Tianming Xu
- Department of Orthopaedic SurgeryNaval Medical University (Second Military Medical
University)Shanghai200052China
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Wang G, Liu X, Liu H, Zhang X, Shao Y, Jia X. A novel necroptosis related gene signature and regulatory network for overall survival prediction in lung adenocarcinoma. Sci Rep 2023; 13:15345. [PMID: 37714937 PMCID: PMC10504370 DOI: 10.1038/s41598-023-41998-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/20/2022] [Accepted: 09/04/2023] [Indexed: 09/17/2023] Open
Abstract
We downloaded the mRNA expression profiles of patients with LUAD and corresponding clinical data from The Cancer Genome Atlas (TCGA) database and used the Least Absolute Shrinkage and Selection Operator Cox regression model to construct a multigene signature in the TCGA cohort, which was validated with patient data from the GEO cohort. Results showed differences in the expression levels of 120 necroptosis-related genes between normal and tumor tissues. An eight-gene signature (CYLD, FADD, H2AX, RBCK1, PPIA, PPID, VDAC1, and VDAC2) was constructed through univariate Cox regression, and patients were divided into two risk groups. The overall survival of patients in the high-risk group was significantly lower than of the patients in the low-risk group in the TCGA and GEO cohorts, indicating that the signature has a good predictive effect. The time-ROC curves revealed that the signature had a reliable predictive role in both the TCGA and GEO cohorts. Enrichment analysis showed that differential genes in the risk subgroups were associated with tumor immunity and antitumor drug sensitivity. We then constructed an mRNA-miRNA-lncRNA regulatory network, which identified lncRNA AL590666. 2/let-7c-5p/PPIA as a regulatory axis for LUAD. Real-time quantitative PCR (RT-qPCR) was used to validate the expression of the 8-gene signature. In conclusion, necroptosis-related genes are important factors for predicting the prognosis of LUAD and potential therapeutic targets.
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Affiliation(s)
- Guoyu Wang
- Department of Traditional Chinese Medicine, Beijing Shijitan Hospital, Capital Medical University, Beijing, China
| | - Xue Liu
- Department of Respiration, The Affiliated Hospital of Shandong University of Traditional Chinese Medicine, Jinan, China
| | - Huaman Liu
- Department of General Medicine, The Affiliated Hospital of Shandong University of Traditional Chinese Medicine, Jinan, China
| | - Xinyue Zhang
- First Clinical Medical College, Shandong University of Traditional Chinese Medicine, Jinan, China
| | - Yumeng Shao
- College of Traditional Chinese Medicine, Shandong University of Traditional Chinese Medicine, Jinan, China
| | - Xinhua Jia
- Department of Respiration, The Affiliated Hospital of Shandong University of Traditional Chinese Medicine, Jinan, China.
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Yu Z, Lu C, Lu B, Gao H, Liang R, Xiang W. A novel prognostic signature for clear cell renal cell carcinoma constructed using necroptosis-related miRNAs. BMC Genomics 2023; 24:162. [PMID: 36991314 DOI: 10.1186/s12864-023-09258-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/25/2022] [Accepted: 03/20/2023] [Indexed: 03/30/2023] Open
Abstract
Abstract
Background
This work aims to analyze the relationship between necroptosis-related microRNAs (miRNAs) and the prognosis of clear cell renal cell carcinoma (ccRCC).
Methods
The miRNAs expression profiles of ccRCC and normal renal tissues from The Cancer Genome Atlas (TCGA) database were used to construct a matrix of the 13 necroptosis-related miRNAs. Cox regression analysis was used to construct a signature to predict the overall survival of ccRCC patients. The genes targeted by the necroptosis-related miRNAs in the prognostic signature were predicted using miRNA databases. Gene Ontology (Go) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were used to investigate the genes targeted by the necroptosis-related miRNAs. The expression levels of selected miRNAs in 15 paired samples (of ccRCC tissues and adjacent normal renal tissues) were investigated using reverse transcriptase quantitative polymerase chain reaction (RT-qPCR).
Results
Six necroptosis-related miRNAs were found to differentially expressed between ccRCC and normal renal tissues. A prognostic signature consisting of miR-223-3p, miR-200a-5p, and miR-500a-3p was constructed using Cox regression analysis and risk scores were calculated. Multivariate Cox regression analysis showed that the hazard ratio was 2.0315 (1.2627–3.2685, P = 0.0035), indicating that the risk score of the signature was an independent risk factor. The receiver operating characteristic (ROC) curve showed that the signature has a favorable predictive capacity and the Kaplan-Meier survival analysis indicated that ccRCC patients with higher risk scores had worse prognoses (P < 0.001). The results of the RT-qPCR verified that all three miRNAs used in the signature were differentially expressed between ccRCC and normal tissues (P < 0.05).
Conclusion
The three necroptosis-related-miRNAs used in this study could be a valuable signature for the prognosis of ccRCC patients. Necroptosis-related miRNAs should be further explored as prognostic indicators for ccRCC.
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Shiau JP, Chuang YT, Yen CY, Chang FR, Yang KH, Hou MF, Tang JY, Chang HW. Modulation of AKT Pathway-Targeting miRNAs for Cancer Cell Treatment with Natural Products. Int J Mol Sci 2023; 24:ijms24043688. [PMID: 36835100 PMCID: PMC9961959 DOI: 10.3390/ijms24043688] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/21/2022] [Revised: 02/06/2023] [Accepted: 02/10/2023] [Indexed: 02/16/2023] Open
Abstract
Many miRNAs are known to target the AKT serine-threonine kinase (AKT) pathway, which is critical for the regulation of several cell functions in cancer cell development. Many natural products exhibiting anticancer effects have been reported, but their connections to the AKT pathway (AKT and its effectors) and miRNAs have rarely been investigated. This review aimed to demarcate the relationship between miRNAs and the AKT pathway during the regulation of cancer cell functions by natural products. Identifying the connections between miRNAs and the AKT pathway and between miRNAs and natural products made it possible to establish an miRNA/AKT/natural product axis to facilitate a better understanding of their anticancer mechanisms. Moreover, the miRNA database (miRDB) was used to retrieve more AKT pathway-related target candidates for miRNAs. By evaluating the reported facts, the cell functions of these database-generated candidates were connected to natural products. Therefore, this review provides a comprehensive overview of the natural product/miRNA/AKT pathway in the modulation of cancer cell development.
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Affiliation(s)
- Jun-Ping Shiau
- Division of Breast Oncology and Surgery, Department of Surgery, Kaohsiung Medical University Hospital, Kaohsiung Medical University, Kaohsiung 80708, Taiwan
| | - Ya-Ting Chuang
- Graduate Institute of Medicine, College of Medicine, Kaohsiung Medical University, Kaohsiung 80708, Taiwan
| | - Ching-Yu Yen
- School of Dentistry, Taipei Medical University, Taipei 11031, Taiwan
- Department of Oral and Maxillofacial Surgery, Chi-Mei Medical Center, Tainan 71004, Taiwan
| | - Fang-Rong Chang
- Graduate Institute of Natural Products, Kaohsiung Medical University, Kaohsiung 80708, Taiwan
| | - Kun-Han Yang
- Graduate Institute of Natural Products, Kaohsiung Medical University, Kaohsiung 80708, Taiwan
| | - Ming-Feng Hou
- Division of Breast Oncology and Surgery, Department of Surgery, Kaohsiung Medical University Hospital, Kaohsiung Medical University, Kaohsiung 80708, Taiwan
- Department of Biomedical Science and Environmental Biology, College of Life Science, Kaohsiung Medical University, Kaohsiung 80708, Taiwan
| | - Jen-Yang Tang
- School of Post-Baccalaureate Medicine, Kaohsiung Medical University, Kaohsiung 80708, Taiwan
- Department of Radiation Oncology, Kaohsiung Medical University Hospital, Kaohsiung Medical University, Kaohsiung 80708, Taiwan
- Correspondence: (J.-Y.T.); (H.-W.C.); Tel.: +88-67-3121101 (ext. 8105) (J.-Y.T.); +88-67-3121101 (ext. 2691) (H.-W.C.)
| | - Hsueh-Wei Chang
- Graduate Institute of Medicine, College of Medicine, Kaohsiung Medical University, Kaohsiung 80708, Taiwan
- Department of Biomedical Science and Environmental Biology, College of Life Science, Kaohsiung Medical University, Kaohsiung 80708, Taiwan
- Institute of Medical Science and Technology, National Sun Yat-sen University, Kaohsiung 80424, Taiwan
- Center for Cancer Research, Kaohsiung Medical University, Kaohsiung 80708, Taiwan
- Correspondence: (J.-Y.T.); (H.-W.C.); Tel.: +88-67-3121101 (ext. 8105) (J.-Y.T.); +88-67-3121101 (ext. 2691) (H.-W.C.)
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In silico analysis revealed the potential circRNA-miRNA-mRNA regulative network of non-small cell lung cancer (NSCLC). Comput Biol Med 2023; 152:106315. [PMID: 36495751 DOI: 10.1016/j.compbiomed.2022.106315] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/03/2022] [Revised: 10/31/2022] [Accepted: 11/13/2022] [Indexed: 11/19/2022]
Abstract
BACKGROUND The primary source of death in the world is non-small cell lung cancer (NSCLC). However, NSCLCs pathophysiology is still not completely understood. The current work sought to study the differential expression of mRNAs involved in NSCLC and their interactions with miRNAs and circRNAs. METHODS We utilized three microarray datasets (GSE21933, GSE27262, and GSE33532) from the GEO NCBI database to identify the differentially expressed genes (DEGs) in NSCLC. We employed DAVID Functional annotation tool to investigate the underlying GO biological process, molecular functions, and KEGG pathways involved in NSCLC. We performed the Protein-protein interaction (PPI) network, MCODE, and CytoHubba analysis from Cytoscape software to identify the significant DEGs in NSCLC. We utilized miRnet to anticipate and build interaction between miRNAs and mRNAs in NSCLC and ENCORI to predict the miRNA-circRNA relationships and build the ceRNA regulatory network. Finally, we executed the gene expression and Kaplan-Meier survival analysis to validate the significant DEGs in the ceRNA network utilizing TCGA NSCLC and GEPIA data. RESULTS We revealed a total of 156 overlapped DEGs (47 upregulated and 109 downregulated genes) in NSCLC. The PPI network, MCODE, and CytoHubba analysis revealed 12 hub genes (cdkn3, rrm2, ccnb1, aurka, nuf2, tyms, kif11, hmmr, ccnb2, nek2, anln, and birc5) that are associated with NSCLC. We identified that these 12 genes encode 12 mRNAs that are strongly linked with 8 miRNAs, and further, we revealed that 1 circRNA was associated with this 5 miRNA. We constructed the ceRNAs network that contained 1circRNA-5miRNAs-7mRNAs. The expression of these seven significant genes in LUAD & LUSC (NSCLC) was considerably higher in the TCGA database than in normal tissues. Kaplan-Meier survival plot reveals that increased expression of these hub genes was related to a poor survival rate in LUAD. CONCLUSION Overall, we developed a circRNA-miRNA-mRNA regulation network to study the probable mechanism of NSCLC.
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Hua L, Lei P, Hu Y. Construction and validation model of necroptosis-related gene signature associates with immunity for osteosarcoma patients. Sci Rep 2022; 12:15893. [PMID: 36151259 PMCID: PMC9508147 DOI: 10.1038/s41598-022-20217-4] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/27/2022] [Accepted: 09/09/2022] [Indexed: 11/24/2022] Open
Abstract
Osteosarcoma is the most common malignant tumor in children and adolescents and its diagnosis and treatment still need to be improved. Necroptosis has been associated with many malignancies, but its significance in diagnosing and treating osteosarcoma remains unclear. The objective is to establish a predictive model of necroptosis-related genes (NRGs) in osteosarcoma for evaluating the tumor microenvironment and new targets for immunotherapy. In this study, we download the osteosarcoma data from the TARGET and GEO websites and the average muscle tissue data from GTEx. NRGs were screened by Cox regression analysis. We constructed a prediction model through nonnegative matrix factorization (NMF) clustering and the least absolute shrinkage and selection operator (LASSO) algorithm and verified it with a validation cohort. Kaplan–Meier survival time, ROC curve, tumor invasion microenvironment and CIBERSORT were assessed. In addition, we establish nomograms for clinical indicators and verify them by calibration evaluation. The underlying mechanism was explored through the functional enrichment analysis. Eight NRGs were screened for predictive model modeling. NRGs prediction model through NMF clustering and LASSO algorithm was established. The survival, ROC and tumor microenvironment scores showed significant statistical differences among subgroups (P < 0.05). The validation model further verifies it. By nomogram and calibration, we found that metastasis and risk score were independent risk factors for the poor prognosis of osteosarcoma. GO and KEGG analyses demonstrate that the genes of osteosarcoma cluster in inflammatory, apoptotic and necroptosis signaling pathways. The significant role of the correlation between necroptosis and immunity in promoting osteosarcoma may provide a novel insight into detecting molecular mechanisms and targeted therapy.
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Affiliation(s)
- Long Hua
- Department of Orthopedics, Xiangya Hospital Central South University, Changsha, Hunan, People's Republic of China.,Department of Orthopedics, The First Affiliated Hospital, Medical College of Zhejiang University, Hangzhou, People's Republic of China.,Department of Orthopedics, The Sixth Affiliated Hospital, Xinjiang Medical University, Ürümqi, People's Republic of China
| | - Pengfei Lei
- Department of Orthopedics, Xiangya Hospital Central South University, Changsha, Hunan, People's Republic of China. .,Department of Orthopedics, The First Affiliated Hospital, Medical College of Zhejiang University, Hangzhou, People's Republic of China.
| | - Yihe Hu
- Department of Orthopedics, Xiangya Hospital Central South University, Changsha, Hunan, People's Republic of China. .,Department of Orthopedics, The First Affiliated Hospital, Medical College of Zhejiang University, Hangzhou, People's Republic of China.
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