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Li B, Li X, Ma M, Wang Q, Shi J, Wu C. Analysis of long non-coding RNAs associated with disulfidptosis for prognostic signature and immunotherapy response in uterine corpus endometrial carcinoma. Sci Rep 2023; 13:22220. [PMID: 38097686 PMCID: PMC10721879 DOI: 10.1038/s41598-023-49750-6] [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: 09/13/2023] [Accepted: 12/12/2023] [Indexed: 12/17/2023] Open
Abstract
Disulfidptosis, the demise of cells caused by the abnormal breakdown of disulfide bonds and actin in the cytoprotein backbone, has attracted attention in studies concerning disulfide-related cell death and its potential implications in cancer treatment. This study utilized bioinformatics to detect disulfidptosis associated lncRNA prognostic markers (DALPMs) with Uterine Corpus Endometrial Carcinoma (UCEC)-related to investigate the correlation between these indicators and the tumor immune microenvironment. The RNA sequencing data and somatic mutation information of patients with UCEC were obtained from the Cancer Genome Atlas (TCGA) database. Patients were randomly divided into Train and Test groups. The findings revealed a potential prognostic model comprising 14 DALPMs. Both univariate and multivariate Cox analyses demonstrated that the model-derived risk score functioned as a standalone prognostic indicator for patients. Significant disparities in survival outcomes were observed between the high- and low-risk groups as defined by the model. Differences in tumor mutational burden (TMB), tumor immune dysfunction and exclusion (TIDE), and tumor microenvironment (TME) stromal cells between patients of the high- and low-risk groups were also observed. The forecast model comprising long non-coding RNAs (lncRNAs) associated with disulfidptosis can effectively anticipate patients' prognoses.
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Affiliation(s)
- Bohan Li
- Department of Gynecology and Oncology, Inner Mongolia Medical University, Affiliated Cancer Hospital, 42 Zhaowuda Road, Saihan District, Hohhot, 010000, Inner Mongolia, China
| | - Xiaoling Li
- Department of General Surgery, Inner Mongolia Medical University, Affiliated Cancer Hospital, 42 Zhaowuda Road, Saihan District, Hohhot, 010000, Inner Mongolia, China
| | - Mudan Ma
- Department of Gynecology and Oncology, Inner Mongolia Medical University, Affiliated Cancer Hospital, 42 Zhaowuda Road, Saihan District, Hohhot, 010000, Inner Mongolia, China
| | - Qing Wang
- Department of Gynaecology and Obstetrics, Xi'an No. 3 Hospital, The Affiliated Hospital of Northwest University, No. 10, East Section of Fengcheng Third Road, Weiyang District, Xi'an, 710018, Shaanxi, China
| | - Jie Shi
- Department of Gynecology and Oncology, Inner Mongolia Medical University, Affiliated Cancer Hospital, 42 Zhaowuda Road, Saihan District, Hohhot, 010000, Inner Mongolia, China.
| | - Chao Wu
- Department of Pancreatic Cancer, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin's Clinical Research Center for Cancer, Huanhu West Road, Hexi District, Tianjin, 300060, China.
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Chen Y, Tang J, Chen L, Chen J. Novel cuproptosis-related lncRNAs can predict the prognosis of patients with multiple myeloma. Transl Cancer Res 2023; 12:3074-3087. [PMID: 38130312 PMCID: PMC10731335 DOI: 10.21037/tcr-23-960] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/03/2023] [Accepted: 09/28/2023] [Indexed: 12/23/2023]
Abstract
Background Cuproptosis-related long-stranded non-coding RNAs (lncRNAs) have several implications for the prognosis of multiple myeloma (MM). This research aimed to construct a prognostic risk model for MM patients and explore the potential signaling pathways in the risk group. Methods Cuproptosis-related lncRNAs were obtained from the co-expression analysis of cuproptosis-related genes and lncRNAs. Subsequently, twelve cuproptosis-related lncRNAs were selected to construct a prognostic risk model of MM patients by the least absolute shrinkage and selection operator (LASSO) regression. Then, the clinical data of these patients were randomly divided into the training group and the testing group. Next, patients were divided into the low- and high-risk groups according to the median risk score. The Kaplan-Meier survival analysis was performed to clarify the prognostic differences between risk subtypes. Besides, the Cox analysis was conducted to identify whether the risk score can be used as an independent prognostic factor. In addition, the receiver operating characteristic (ROC) curve analysis and the concordance index (C-index) curve analysis were performed to elucidate the value of risk score as a prognostic indicator. Finally, the differential risk analysis and functional enrichment analysis were carried out to identify the potential signaling pathways in the low- and high-risk groups. Results The results demonstrated that the overall survival (OS) of patients in the high-risk group was shorter than that in the low-risk group. There were significant differences in the expression of genes in MM patients between the high- and low-risk groups. The Gene Ontology (GO) analysis results showed that the differentially expressed risk-related genes (DERGs) were mainly concentrated on the collagen-containing extracellular matrix. According to the Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis results, the DERGs may be related to the neuroactive ligand-receptor interaction and mitogen-activated protein kinase (MAPK) signaling pathway, indicating that they may be involved in the progression of tumors. Conclusions The findings of this study suggest that cuproptosis-related lncRNAs may be effective biomarkers for predicting the prognosis of MM patients, which is anticipated to contribute to the improvement of clinical outcomes.
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Affiliation(s)
- Yuying Chen
- Department of Hematology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China
| | - Jialin Tang
- Department of Hematology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China
| | - Lin Chen
- Department of Hematology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China
| | - Jianbin Chen
- Department of Hematology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China
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Ding W, Zhang M, Zhang P, Zhang X, Sun J, Lin B. Identification of anoikis-related subtypes and immune landscape in kidney renal clear cell carcinoma. Sci Rep 2023; 13:18069. [PMID: 37872217 PMCID: PMC10593771 DOI: 10.1038/s41598-023-45069-4] [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: 06/20/2023] [Accepted: 10/15/2023] [Indexed: 10/25/2023] Open
Abstract
Anoikis is a specific form of programmed cell death induced by the loss of cell contact with the extracellular matrix and other cells, and plays an important role in organism development, tissue homeostasis, disease development and tumor metastasis. We comprehensively investigated the expression patterns of anoikis-related genes (ARGs) in kidney renal clear cell carcinoma (KIRC) from public databases. Anoikis-related prognostic signatures were established based on four ARGs expression, in which KIRC patients were assigned different risk scores and divided into two different risk groups. In addition, four ARGs expression was validated by qRT-PCR. A better prognosis was observed in the low-risk group, but with lower immune activity (including immune cells and immune-related functions) in the tumor microenvironment. Combined with the relevant clinical characteristics, a nomogram for clinical application was established. Receiver operating characteristics (ROC) and calibration curves were constructed to demonstrate the predictive power of this risk signature. In addition, higher risk scores were significantly and positively correlated with higher gene expression of tumor mutation load (TMB), immune checkpoints (ICPs) and mismatch repair (MMR)-related proteins in general. The results also suggested that the high-risk group was more sensitive to immunotherapy and certain chemotherapeutic agents. Anoikis-related prognostic signatures may provide a better understanding of the roles of ARGs and offer new perspectives for clinical prognosis and individualized treatment.
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Affiliation(s)
- Wencong Ding
- The Department of Nephrology and Hemopurification Center, Affiliated Guangdong Hospital of Integrated Traditional Chinese and Western Medicine of Guangzhou University of Chinese Medicine, Foshan, 528000, Guangdong, China
| | - Min Zhang
- The Department of Nephrology and Hemopurification Center, Affiliated Guangdong Hospital of Integrated Traditional Chinese and Western Medicine of Guangzhou University of Chinese Medicine, Foshan, 528000, Guangdong, China
| | - Ping Zhang
- The Department of Nephrology and Hemopurification Center, Affiliated Guangdong Hospital of Integrated Traditional Chinese and Western Medicine of Guangzhou University of Chinese Medicine, Foshan, 528000, Guangdong, China
| | - Xianghong Zhang
- The Department of Nephrology and Hemopurification Center, Affiliated Guangdong Hospital of Integrated Traditional Chinese and Western Medicine of Guangzhou University of Chinese Medicine, Foshan, 528000, Guangdong, China
| | - Junwei Sun
- The Department of Nephrology and Hemopurification Center, Affiliated Guangdong Hospital of Integrated Traditional Chinese and Western Medicine of Guangzhou University of Chinese Medicine, Foshan, 528000, Guangdong, China
| | - Biying Lin
- The Department of Nephrology and Hemopurification Center, Affiliated Guangdong Hospital of Integrated Traditional Chinese and Western Medicine of Guangzhou University of Chinese Medicine, Foshan, 528000, Guangdong, China.
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Ghafouri-Fard S, Askari A, Behzad Moghadam K, Hussen BM, Taheri M, Samadian M. A review on the role of ZEB1-AS1 in human disorders. Pathol Res Pract 2023; 245:154486. [PMID: 37120907 DOI: 10.1016/j.prp.2023.154486] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/13/2023] [Revised: 04/19/2023] [Accepted: 04/24/2023] [Indexed: 05/02/2023]
Abstract
ZEB1 Antisense RNA 1 (ZEB1-AS1) is a type of RNA characterized as long non-coding RNA (lncRNA). This lncRNA has important regulatory roles on its related gene, Zinc Finger E-Box Binding Homeobox 1 (ZEB1). In addition, role of ZEB1-AS1 has been approved in diverse malignancies such as colorectal cancer, breast cancer, glioma, hepatocellular carcinoma and gastric cancer. ZEB1-AS1 serves as a sponge for a number of microRNAs, namely miR-577, miR-335-5p, miR-101, miR-505-3p, miR-455-3p, miR-205, miR-23a, miR-365a-3p, miR-302b, miR-299-3p, miR-133a-3p, miR-200a, miR-200c, miR-342-3p, miR-214, miR-149-3p and miR-1224-5p. In addition to malignant conditions, ZEB1-AS1 has functional role in non-malignant conditions like diabetic nephropathy, diabetic lung, arthrosclerosis, Chlamydia trachomatis infection, pulmonary fibrosis and ischemic stroke. This review outlines different molecular mechanisms of ZEB1-AS1 in a variety of disorders and highlights its importance in their pathogenesis.
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Affiliation(s)
- Soudeh Ghafouri-Fard
- Department of Medical Genetics, School of Medicine, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | - Arian Askari
- Phytochemistry Research Center, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | | | - Bashdar Mahmud Hussen
- Department of Pharmacognosy, College of Pharmacy, Hawler Medical University, Erbil, Iraq
| | - Mohammad Taheri
- Institue of Human Genetics, Jena University Hospital, Jena, Germany; Urology and Nephrology Research Center, Shahid Beheshti University of Medical Sciences, Tehran, Iran.
| | - Mohammad Samadian
- Skull Base Research Center, Loghman Hakim Hospital, Shahid Beheshti University of Medical Sciences, Tehran, Iran.
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Ding W, Li B, Zhang Y, He L, Su J. A neutrophil extracellular traps-associated lncRNA signature predicts the clinical outcomes in patients with lung adenocarcinoma. Front Genet 2022; 13:1047231. [PMID: 36419832 PMCID: PMC9676361 DOI: 10.3389/fgene.2022.1047231] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/17/2022] [Accepted: 10/25/2022] [Indexed: 10/24/2023] Open
Abstract
Backgrounds: Neutrophil extracellular traps (NETs) play an important role in the occurrence, metastasis, and immune escape of cancers. We aim to investigate Long non-coding RNAs (lncRNAs) that are correlated to NETs to find some potentially useful biomarkers for lung adenocarcinoma (LUAD), and to explore their correlations with immunotherapy and chemotherapy, as well as the tumor microenvironment. Methods: Based on the The Cancer Genome Atlas (TCGA) database, we identified the prognosis-related lncRNAs which are associated with NETs using cox regression. The patients were then separated into two clusters based on the expression of NETs-associated lncRNAs to perform tumor microenvironment analysis and immune-checkpoint analysis. Least absolute shrinkage and selection operator (LASSO) regression was then performed to establish a prognostic signature. Furthermore, nomogram analysis, tumor mutation burden analysis, immune infiltration analysis, as well as drug sensitivity analysis were performed to test the signature. Results: Using univariate cox regression, we found 10 NETs-associated lncRNAs that are associated with the outcomes of LUAD patients. Also, further analysis which separated the patients into 2 clusters showed that the 10 lncRNAs had significant correlations with the tumor microenvironment. Using LASSO regression, we finally constructed a signature to predict the outcomes of the patients based on 4 NETs-associated lncRNAs. The 4 NETs-associated lncRNAs were namely SIRLNT, AL365181.3, FAM83A-AS1, and AJ003147.2. Using Kaplan-Meier (K-M) analysis, we found that the risk model was strongly associated with the survival outcomes of the patients both in the training group and in the validation group 1 and 2 (p < 0.001, p = 0.026, and p < 0.01). Using receiver operating characteristic (ROC) curve, we tested the sensitivity combined with the specificity of the model and found that the risk model had a satisfactory level of 1-year, 3-year, and 5-year concordance index (C-index) (C = 0.661 in the training group, C = 0.679 in validation group 1, C = 0.692 in validation group 2). We also explored the immune microenvironment and immune checkpoint correlation of the risk model and found some significant results. Conclusion: We constructed a NETs-associated lncRNA signature to predict the outcome of patients with LUAD, which is associated with immunephenoscores and immune checkpoint-gene expression.
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Affiliation(s)
- Wencong Ding
- Department of Rheumatology, Affiliated Guangdong Hospital of Integrated Traditional Chinese and Western Medicine of Guangzhou University of Chinese Medicine, Foshan, Guangdong, China
| | - Biyi Li
- Department of Emergency Foshan Hospital of Traditional Chinese Medicine, Foshan, Guangdong, China
| | - Yuan Zhang
- Department of Emergency, Affiliated Guangdong Hospital of Integrated Traditional Chinese and Western Medicine of Guangzhou University of Chinese Medicine, Foshan, Guangdong, China
| | - Liu He
- Guangdong Hospital of Traditional Chinese Medicine, Guangzhou, Guangdong, China
| | - Junwei Su
- Department of Emergency, Affiliated Guangdong Hospital of Integrated Traditional Chinese and Western Medicine of Guangzhou University of Chinese Medicine, Foshan, Guangdong, China
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