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Li W, Dong Y, Liu W, Tang Z, Sun C, Lowe S, Chen S, Bentley R, Zhou Q, Xu C, Li W, Wang B, Wang H, Dong S, Hu Z, Liu Q, Cai X, Feng X, Zhao W, Yin C. A deep belief network-based clinical decision system for patients with osteosarcoma. Front Immunol 2022; 13:1003347. [PMID: 36466868 PMCID: PMC9716099 DOI: 10.3389/fimmu.2022.1003347] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/26/2022] [Accepted: 10/19/2022] [Indexed: 09/16/2023] Open
Abstract
Osteosarcoma was the most frequent type of malignant primary bone tumor with a poor survival rate mainly occurring in children and adolescents. For precision treatment, an accurate individualized prognosis for Osteosarcoma patients is highly desired. In recent years, many machine learning-based approaches have been used to predict distant metastasis and overall survival based on available individual information. In this study, we compared the performance of the deep belief networks (DBN) algorithm with six other machine learning algorithms, including Random Forest, XGBoost, Decision Tree, Gradient Boosting Machine, Logistic Regression, and Naive Bayes Classifier, to predict lung metastasis for Osteosarcoma patients. Therefore the DBN-based lung metastasis prediction model was integrated as a parameter into the Cox proportional hazards model to predict the overall survival of Osteosarcoma patients. The accuracy, precision, recall, and F1 score of the DBN algorithm were 0.917/0.888, 0.896/0.643, 0.956/0.900, and 0.925/0.750 in the training/validation sets, respectively, which were better than the other six machine-learning algorithms. For the performance of the DBN survival Cox model, the areas under the curve (AUCs) for the 1-, 3- and 5-year survival in the training set were 0.851, 0.806 and 0.793, respectively, indicating good discrimination, and the calibration curves showed good agreement between the prediction and actual observations. The DBN survival Cox model also demonstrated promising performance in the validation set. In addition, a nomogram integrating the DBN output was designed as a tool to aid clinical decision-making.
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Affiliation(s)
- Wenle Li
- Department of Orthopaedic Surgery, People’s Hospital of Xinjiang Uygur Autonomous Region, Urumqi, Xinjiang, China
- Center for Molecular Imaging and Translational Medicine, Xiamen University, Xiamen, China
| | - Youzheng Dong
- Key Laboratory of Molecular Medicine, The Second Affiliated Hospital of Nanchang University, Nanchang, China
| | - Wencai Liu
- Department of Orthopaedic Surgery, the First Affiliated Hospital of Nanchang University, Nanchang, China
| | - Zhiri Tang
- School of Physics and Technology, Wuhan University, Wuhan, China
| | - Chenyu Sun
- AMITA Health Saint Joseph Hospital Chicago, Chicago, IL, United States
| | - Scott Lowe
- College of Osteopathic Medicine, Kansas City University, Kansas, MO, United States
| | - Shuya Chen
- Foundation Program, Newham University Hospital, London, United Kingdom
| | - Rachel Bentley
- College of Osteopathic Medicine, Kansas City University, Kansas, MO, United States
| | - Qin Zhou
- Radiation Oncology, Mayo Clinic, Rochester, MN, United States
| | - Chan Xu
- Clinical Medical Research Center, Xianyang Central Hospital, Xianyang, China
| | - Wanying Li
- Clinical Medical Research Center, Xianyang Central Hospital, Xianyang, China
| | - Bing Wang
- Clinical Medical Research Center, Xianyang Central Hospital, Xianyang, China
| | - Haosheng Wang
- Department of Orthopaedics, The Second Hospital of Jilin University, Changchun, China
| | - Shengtao Dong
- Department of Spine Surgery, Second Affiliated Hospital of Dalian Medical University, Dalian, China
| | - Zhaohui Hu
- Department of Spine Surgery, Liuzhou People’s Hospital, Liuzhou, China
| | - Qiang Liu
- Clinical Medical Research Center, Xianyang Central Hospital, Xianyang, China
| | - Xintian Cai
- Graduate School, Xinjiang Medical University, Urumqi, Xinjiang, China
| | - Xiaowei Feng
- Department of Neuro Rehabilitation, Shaanxi Provincial Rehabilitation Hospital, Xi 'an, China
| | - Wei Zhao
- Department of Orthopaedic Surgery, People’s Hospital of Xinjiang Uygur Autonomous Region, Urumqi, Xinjiang, China
| | - Chengliang Yin
- Faculty of Medicine, Macau University of Science and Technology, Macau, Macau SAR, China
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Liu X, Du S, Wang S, Ye K. Ferroptosis in osteosarcoma: A promising future. Front Oncol 2022; 12:1031779. [PMID: 36457488 PMCID: PMC9705963 DOI: 10.3389/fonc.2022.1031779] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/30/2022] [Accepted: 11/01/2022] [Indexed: 10/25/2023] Open
Abstract
The incidence of osteosarcoma (OS) is increasing year by year, and the prognosis of patients with advanced OS is extremely poor due to the tendency of recurrence and chemotherapy resistance after surgery. Ferroptosis is a novel form of programmed cell death (PCD) that kills cells through iron-dependent lipid peroxidation. Current studies have shown that ferroptosis is closely related to OS and could reduce chemotherapy resistance to a certain extent, which has great therapeutic potential. In this paper, we review the regulatory mechanism of ferroptosis and its research progress in OS, hoping to provide new help for the clinical treatment of OS.
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Affiliation(s)
- Xiang Liu
- Department of Orthopedics, Second Hospital of Lanzhou University, Lanzhou, China
- Key Laboratory of Bone and Joint Diseases of Gansu Province, Second Hospital of Lanzhou University, Lanzhou, China
| | - Shaowen Du
- Department of Orthopedics, Second Hospital of Lanzhou University, Lanzhou, China
- Key Laboratory of Bone and Joint Diseases of Gansu Province, Second Hospital of Lanzhou University, Lanzhou, China
| | - Shengdong Wang
- Department of Orthopedics, Second Hospital of Lanzhou University, Lanzhou, China
- Key Laboratory of Bone and Joint Diseases of Gansu Province, Second Hospital of Lanzhou University, Lanzhou, China
| | - Kaishan Ye
- Department of Orthopedics, Second Hospital of Lanzhou University, Lanzhou, China
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Wang X, Xia G, Xiao S, Wu S, Zhang L, Huang J, Zhang W, Cao X. A ferroptosis-related gene signature associated with immune landscape and therapeutic response in osteosarcoma. Front Oncol 2022; 12:1024915. [PMID: 36439512 PMCID: PMC9691858 DOI: 10.3389/fonc.2022.1024915] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/22/2022] [Accepted: 10/19/2022] [Indexed: 09/22/2023] Open
Abstract
BACKGROUND The role of ferroptosis in tumor progression and immune microenvironment is extensively investigated. However, the potential value of ferroptosis regulators in predicting prognosis and therapeutic strategies for osteosarcoma (OS) patients remains to be elucidated. METHODS Here, we extracted transcriptomic and survival data from Therapeutically Applicable Research to Generate Effective Treatments (TARGET) and Gene Expression Omnibus (GEO) to investigate the expression and prognostic value of ferroptosis regulators in OS patients. After comprehensive analyses, including Gene set variation analysis (GSVA), single-sample gene-set enrichment analysis (ssGSEA), Estimated Stromal and Immune cells in Malignant Tumor tissues using Expression (ESTIMATE), single-cell RNA sequencing, and biological experiments, our constructed 8-ferroptosis-regulators prognostic signature effectively predicted the immune landscape, prognosis, and chemoradiotherapy strategies for OS patients. RESULTS We constructed an 8-ferroptosis-regulators signature that could predict the survival outcome of OS. The signature algorithm scored samples, and high-scoring patients were more prone to worse prognoses. The tumor immune landscape suggested the positive relevance between risk score and immunosuppression. Interfering HILPDA and MUC1 expression would inhibit tumor cell proliferation and migration, and MUC1 might improve the ferroptosis resistance of OS cells. Moreover, we predicted chemoradiotherapy strategies of cancer patients following ferroptosis-risk-score groups. CONCLUSION Dysregulated ferroptosis gene expression can affect OS progression by affecting the tumor immune landscape and ferroptosis resistance. Our risk model can predict OS survival outcomes, and we propose that HILPDA and MUC1 are potential targets for cancer therapy.
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Affiliation(s)
- Xinxing Wang
- Department of Orthopaedics, The Third Xiangya Hospital, Central South University, Changsha, China
| | - Guang Xia
- Department of Orthopaedics, The Third Xiangya Hospital, Central South University, Changsha, China
| | - Shilang Xiao
- Department of Gastroenterology, The Third Xiangya Hospital, Central South University, Changsha, China
| | - Song Wu
- Department of Orthopaedics, The Third Xiangya Hospital, Central South University, Changsha, China
| | - Lina Zhang
- Department of Orthopaedics, The Third Xiangya Hospital, Central South University, Changsha, China
| | - Junjie Huang
- Department of Orthopaedics, The Third Xiangya Hospital, Central South University, Changsha, China
| | - Wenxiu Zhang
- Department of Orthopaedics, The Third Xiangya Hospital, Central South University, Changsha, China
| | - Xu Cao
- Department of Orthopaedics, The Third Xiangya Hospital, Central South University, Changsha, China
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Identification and Development of an Age-Related Classification and Signature to Predict Prognosis and Immune Landscape in Osteosarcoma. JOURNAL OF ONCOLOGY 2022; 2022:5040458. [PMID: 36276293 PMCID: PMC9581613 DOI: 10.1155/2022/5040458] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/11/2022] [Accepted: 09/17/2022] [Indexed: 11/17/2022]
Abstract
Background. In childhood and adolescence, the prevailing bone tumor is osteosarcoma associated with frequent recurrence and lung metastasis. This research focused on predicting the survival and immune landscape of osteosarcoma by developing a prognostic signature and establishing aging-related genes (ARGs) subtypes. Methods. The training group comprised of the transcriptomic and associated clinical data of 84 patients with osteosarcoma accessed at the TARGET database and the validation group consisted of 53 patients from GSE21257. The aging-related subtypes were identified using unsupervised consensus clustering analysis. The ARG signature was developed utilizing multivariate Cox analysis and LASSO regression. The prognostic value was assessed using the univariate and multivariate Cox analyses, Kaplan-Meier plotter, time-dependent ROC curve, and nomogram. The functional enrichment analyses were performed by GSEA, GO, and KEGG analysis, while the ssGSEA, ESTIMATE, and CIBERSORT analyses were conducted to reveal the immune landscape in osteosarcoma. Results. The two clusters of osteosarcoma patients formed based on 543 ARGs, depicted a considerable difference in the tumor microenvironment, and the overall survival and immune cell infiltration rate varied as well. Among these, the selected 23 ARGs were utilized for the construction of an efficient predictive prognostic signature for the overall survival prediction. The testing in the validation group of osteosarcoma patients confirmed the status of the high-risk score as an independent indicator for poor prognosis, which was already identified as such using the univariate and multivariate Cox analyses. Furthermore, the ARG signature could distinguish different immune-related functions, infiltration status of immune cells, and tumor microenvironment, as well as predict the immunotherapy response of osteosarcoma patients. Conclusion. The aging-related subtypes were identified and a prognostic signature was developed in this research, which determined different prognoses and allowed for treatment of osteosarcoma patients to be tailored. Additionally, the immunotherapeutic response of individuals with osteosarcoma could also be predicted by the ARG signature.
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Identification of ATG7 as a Regulator of Proferroptosis and Oxidative Stress in Osteosarcoma. OXIDATIVE MEDICINE AND CELLULAR LONGEVITY 2022; 2022:8441676. [PMID: 36254233 PMCID: PMC9569205 DOI: 10.1155/2022/8441676] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/04/2022] [Revised: 09/08/2022] [Accepted: 09/13/2022] [Indexed: 11/17/2022]
Abstract
Background Ferroptosis has gained significant attention from oncologists as a vital outcome of oxidative stress. The aim of this study was to develop a prognostic signature that was based on the ferroptosis-related genes (FRGs) for osteosarcoma patients and explore their specific role in osteosarcoma. Methods The training cohort dataset was extracted from the Therapeutically Applicable Research to Generate Effective Treatments (TARGET) database. Different techniques like the univariate Cox regression, least absolute shrinkage and selection operator (LASSO) regression, multivariate Cox regression analyses, and the Kaplan-Meier (KM) survival analyses were utilized to develop a prognostic signature. Then, the intrinsic relationship between the developed gene signature and the infiltration levels of the immune cells was further investigated. An external validation dataset from the Gene Expression Omnibus (GEO) database was employed to assess the predictive ability of the developed gene signature. Subsequently, the specific function of potential FRG in affecting the oxidative stress reaction and ferroptosis of osteosarcoma cells was identified. Results A prognostic signature based on 5 FRGs (CBS, MUC1, ATG7, SOCS1, and PEBP1) was developed, and the patients were classified into the low- and high-risk groups (categories). High-risk patients displayed poor overall survival outcomes. The risk level was seen to be an independent risk factor for determining the prognosis of osteosarcoma patients (p < 0.001, hazard ratio: 7.457, 95% CI: 3.302-16.837). Additionally, the risk level was associated with immune function, which might affect the survival status of osteosarcoma patients. Moreover, the findings of the study indicated that the expression of ATG7 was related to the regulation of oxidative stress in osteosarcoma. Silencing the ATG7 gene promoted the proliferation and migration in osteosarcoma cells, suppressing the oxidative stress and ferroptosis process. Conclusions A novel FRG signature was developed in this study to predict the prognosis of osteosarcoma patients. The results indicated that ATG7 might regulate the process of oxidative stress and ferroptosis in osteosarcoma cells and could be used as a potential target to develop therapeutic strategies for treating osteosarcoma.
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Jiang M, Jike Y, Gan F, Li J, Hu Y, Xie M, Liu K, Qin W, Bo Z. Verification of Ferroptosis Subcluster-Associated Genes Related to Osteosarcoma and Exploration of Immune Targeted Therapy. OXIDATIVE MEDICINE AND CELLULAR LONGEVITY 2022; 2022:9942014. [PMID: 36211822 PMCID: PMC9534693 DOI: 10.1155/2022/9942014] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/30/2022] [Revised: 08/04/2022] [Accepted: 08/12/2022] [Indexed: 11/17/2022]
Abstract
Background Despite tremendous advances in treating osteosarcoma (OS), the survival rates of patients have failed to improve dramatically over the past decades. Ferroptosis, a newly discovered iron-dependent type of regulated cell death, is implicated in tumors, and its features in OS remain unascertained. We designed to determine the involvement of ferroptosis subcluster-related modular genes in OS progression and prognosis. Methods The OS-related datasets retrieved from GEO and TARGET database were clustered for identifying molecular subclusters with different ferroptosis-related genes (FRGs) expression patterns. Weighted gene coexpression network analysis (WGCNA) was applied to identify modular genes from FRG subclusters. The least absolute shrinkage and selection operator (LASSO) algorithm and multivariable Cox regression analysis were adopted to develop the prognostic model. Potential mechanisms of development and prognosis in OS were explored by gene ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and gene set enrichment analysis (GSEA). Then, a comprehensive analysis was conducted for immune checkpoint markers and assessment of predictive power to drug response. The protein expression levels of the three ferroptosis subcluster-related modular genes were verified by immunohistochemistry. Results Two independent subclusters presenting diverse expression profiles of FRGs were obtained, with significantly different survival states. Ferroptosis subcluster-related modular genes were screened with WGCNA, and the GESA results showed that ferroptosis subcluster-related modular genes could affect the cellular energy metabolism, thus influencing the development and prognosis of osteosarcoma. A prognostic model was established by incorporating three ferroptosis subcluster-related modular genes (LRRC1, ACO2, and CTNNBIP1) and a nomogram by integrating clinical features, and they were evaluated for the predictive power on OS prognosis. The 20 immune checkpoint-related genes confirmed the insensitivity to tumor immunotherapy in high-risk patients. IC50s of Axitinib and Cytarabine suggested a higher sensitivity to the targeted drug. Finally, the quantitative reverse transcription-polymerase chain reaction (qRT-PCR) and immunohistochemistry were consistent with bioinformatics analysis. Conclusion Ferroptosis are closely associated with the OS prognosis. The risk-scoring model incorporating three ferroptosis subcluster-related modular genes has shown outstanding advantages in predicting patient prognosis.
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Affiliation(s)
- Mingyang Jiang
- Department of Bone and Joint Surgery, The First Affiliated Hospital of Guangxi Medical University, Nanning, China
| | - Yiji Jike
- Department of Bone and Joint Surgery, The First Affiliated Hospital of Guangxi Medical University, Nanning, China
| | - Fu Gan
- Department of Urology Surgery, The Affiliated Hospital of Youjiang Medical University for Nationalities, Baise, China
| | - Jia Li
- Department of Pathology, The First Affiliated Hospital of Guangxi Medical University, Nanning, China
| | - Yang Hu
- Department of Bone and Joint Surgery, The First Affiliated Hospital of Guangxi Medical University, Nanning, China
| | - Mingjing Xie
- Department of Bone and Joint Surgery, The First Affiliated Hospital of Guangxi Medical University, Nanning, China
| | - Kaicheng Liu
- Department of Bone and Joint Surgery, The First Affiliated Hospital of Guangxi Medical University, Nanning, China
| | - Wentao Qin
- Department of Bone and Joint Surgery, The First Affiliated Hospital of Guangxi Medical University, Nanning, China
| | - Zhandong Bo
- Department of Bone and Joint Surgery, The First Affiliated Hospital of Guangxi Medical University, Nanning, China
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Yang J, Zhang J, Na S, Wang Z, Li H, Su Y, Ji L, Tang X, Yang J, Xu L. Integration of single-cell RNA sequencing and bulk RNA sequencing to reveal an immunogenic cell death-related 5-gene panel as a prognostic model for osteosarcoma. Front Immunol 2022; 13:994034. [PMID: 36225939 PMCID: PMC9549151 DOI: 10.3389/fimmu.2022.994034] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/14/2022] [Accepted: 09/05/2022] [Indexed: 11/13/2022] Open
Abstract
BackgroundDespite the comparatively low prevalence of osteosarcoma (OS) compared to other cancer types, metastatic OS has a poor overall survival rate of fewer than 30%. Accumulating data has shown the crucial functions of immunogenic cell death (ICD) in various cancers; nevertheless, the relationship between ICD and OS was not previously well understood. This research aims to determine the function of ICD in OS and construct an ICD-based prognostic panel.MethodsSingle cell RNA sequencing data from GSE162454 dataset distinguished malignant cells from normal cells in OS. The discrepancy in ICD scores and corresponding gene expression was intensively explored between malignant cells and normal cells. Using the RNA sequencing data of the TARGET-OS, GSE16091, GSE21257, and GSE39058 datasets, the molecular subtype of OS was determined by clustering seventeen ICD-related genes obtained from the literature. Differentially expressed genes (DEGs) between different molecular subtypes were identified to develop a novel ICD-associated prognostic panel.ResultsThe malignant cells had a remarkable decrease in the ICD scores and corresponding gene expression compared with normal cells. A total of 212 OS patients were successfully stratified into two subtypes: C1 and C2. C1-like OS patients were characterized by better prognostic outcomes, overexpression of ICD genes, activation of the ICD pathway, high inflitration abundance of immunocytes, and low expression levels of immune checkpoint genes (ICGs); however, the reverse is true in C2-like OS patients. Utilizing the limma programme in R, the DEGs between two subtypes were determined, and a 5-gene risk panel consisting of BAMBI, TMCC2, NOX4, DKK1, and CBS was developed through LASSO-Cox regression analysis. The internal- and external-verification cohorts were employed to verify the efficacy and precision of the risk panel. The AUC values of ROC curves indicated excellent prognostic prediction values of our risk panel.ConclusionsOverall, ICD represented a protective factor against OS, and our 5-gene risk panel serving as a biomarker could effectively evaluate the prognostic risk in patients with OS.
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Affiliation(s)
- Jiaqi Yang
- Department of Dermatology, Second Affiliated Hospital of Dalian Medical University, Dalian, China
- Department of Orthopedics, First Affiliated Hospital of Dalian Medical University, Dalian, China
| | - Jian Zhang
- Department of Orthopedics, First Affiliated Hospital of Dalian Medical University, Dalian, China
| | - Song Na
- Emergency Intensive Care Unit, Affiliated Zhongshan Hospital of Dalian University, Dalian, China
| | - Zhizhou Wang
- Department of General Surgery, First Affiliated Hospital of Dalian Medical University, Dalian, China
| | - Hanshuo Li
- Department of General Surgery, First Affiliated Hospital of Dalian Medical University, Dalian, China
| | - Yuxin Su
- Cardiovascular Research Institute of Northern Theater Command General Hospital, Shenyang, China
| | - Li Ji
- Department of Gastroenterology, DongZhiMen Hospital, Beijing University of Chinese Medicine, Beijing, China
| | - Xin Tang
- Department of Orthopedics, First Affiliated Hospital of Dalian Medical University, Dalian, China
- *Correspondence: Lu Xu, ; Xin Tang, ; Jun Yang,
| | - Jun Yang
- Department of Orthopedics, First Affiliated Hospital of Dalian Medical University, Dalian, China
- *Correspondence: Lu Xu, ; Xin Tang, ; Jun Yang,
| | - Lu Xu
- Department of Dermatology, Second Affiliated Hospital of Dalian Medical University, Dalian, China
- Institute of Cancer Stem Cell, Dalian Medical University, Dalian, China
- *Correspondence: Lu Xu, ; Xin Tang, ; Jun Yang,
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Liu B, Feng C, Liu Z, Tu C, Li Z. A novel necroptosis-related lncRNAs signature effectively predicts the prognosis for osteosarcoma and is associated with immunity. Front Pharmacol 2022; 13:944158. [PMID: 36105232 PMCID: PMC9465333 DOI: 10.3389/fphar.2022.944158] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/14/2022] [Accepted: 07/29/2022] [Indexed: 12/24/2022] Open
Abstract
Background: Necroptosis is closely related to tumorigenesis and development. Accumulating evidence has revealed that long non-coding RNAs (lncRNAs) are also central players in osteosarcoma (OS). However, the role of necroptosis-related lncRNAs in OS remains unclear. In the present study, we aim to craft a prognostic signature based on necroptosis-related lncRNAs to improve the OS prognosis prediction. Methods: The signature based on necroptosis-related lncRNAs was discovered using univariate Cox, least absolute shrinkage and selection operator (LASSO), and multivariate Cox regression analysis. The prognosis efficiency of the signature was then estimated by employing various bioinformatics methods. Subsequently, immunological analysis and Gene Set Enrichment Analysis (GSEA) were used to explore the association between necroptosis-related lncRNAs with clinical outcomes and immune status. More importantly, several necroptosis-related lncRNAs were validated with RT-qPCR. Results: Consequently, a novel prognosis signature was successfully constructed based on eight necroptosis-related lncRNAs. Meanwhile, the novel necroptosis-related lncRNAs model could distribute OS patients into two risk groups with a stable and accurate predictive ability. Additionally, the GSEA and immune analysis revealed that the necroptosis-related lncRNAs signature affects the development and prognosis of OS by regulating the immune status. The necroptosis-related lncRNA signature was closely correlated with multiple anticancer agent susceptibility. Moreover, the RT-qPCR results indicated several necroptosis-related lncRNAs were significantly differently expressed in osteosarcoma and osteoblast cell lines. Conclusion: In this summary, a novel prognostic signature integrating necroptosis-related lncRNAs was firstly constructed and could accurately predict the prognosis of OS. This study may increase the predicted value and guide the personalized chemotherapy treatment for OS.
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Affiliation(s)
- Binfeng Liu
- Department of Orthopaedics, The Second Xiangya Hospital, Central South University, Changsha, Hunan, China
- Hunan Key Laboratory of Tumor Models and Individualized Medicine, The Second Xiangya Hospital of Central South University, Changsha, Hunan, China
| | - Chengyao Feng
- Department of Orthopaedics, The Second Xiangya Hospital, Central South University, Changsha, Hunan, China
- Hunan Key Laboratory of Tumor Models and Individualized Medicine, The Second Xiangya Hospital of Central South University, Changsha, Hunan, China
| | - Zhongyue Liu
- Department of Orthopaedics, The Second Xiangya Hospital, Central South University, Changsha, Hunan, China
- Hunan Key Laboratory of Tumor Models and Individualized Medicine, The Second Xiangya Hospital of Central South University, Changsha, Hunan, China
| | - Chao Tu
- Department of Orthopaedics, The Second Xiangya Hospital, Central South University, Changsha, Hunan, China
- Hunan Key Laboratory of Tumor Models and Individualized Medicine, The Second Xiangya Hospital of Central South University, Changsha, Hunan, China
- *Correspondence: Chao Tu, , Zhihong Li,
| | - Zhihong Li
- Department of Orthopaedics, The Second Xiangya Hospital, Central South University, Changsha, Hunan, China
- Hunan Key Laboratory of Tumor Models and Individualized Medicine, The Second Xiangya Hospital of Central South University, Changsha, Hunan, China
- *Correspondence: Chao Tu, , Zhihong Li,
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Wei N, Chao-yang G, Wen-ming Z, Ze-yuan L, Yong-qiang S, Shun-bai Z, Kai Z, Yan-chao M, Hai-hong Z. A ubiquitin-related gene signature for predicting prognosis and constructing molecular subtypes in osteosarcoma. Front Pharmacol 2022; 13:904448. [PMID: 36060009 PMCID: PMC9428517 DOI: 10.3389/fphar.2022.904448] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/25/2022] [Accepted: 07/19/2022] [Indexed: 11/13/2022] Open
Abstract
Background: Ubiquitination is medicated by three classes of enzymes and has been proven to involve in multiple cancer biological processes. Moreover, dysregulation of ubiquitination has received a growing body of attention in osteosarcoma (OS) tumorigenesis and treatment. Therefore, our study aimed to identify a ubiquitin-related gene signature for predicting prognosis and immune landscape and constructing OS molecular subtypes. Methods: Therapeutically Applicable Research to Generate Effective Treatments (TARGET) was regarded as the training set through univariate Cox regression, Lasso Cox regression, and multivariate Cox regression. The GSE21257 and GSE39055 served as the validation set to verify the predictive value of the signature. CIBERSORT was performed to show immune infiltration and the immune microenvironment. The NMF algorithm was used to construct OS molecular subtypes. Results: In this study, we developed a ubiquitin-related gene signature including seven genes (UBE2L3, CORO6, DCAF8, DNAI1, FBXL5, UHRF2, and WDR53), and the gene signature had a good performance in predicting prognosis for OS patients (AUC values at 1/3/5 years were 0.957, 0.890, and 0.919). Multivariate Cox regression indicated that the risk score model and prognosis stage were also independent prognostic prediction factors. Moreover, analyses of immune cells and immune-related functions showed a significant difference in different risk score groups and the three clusters. The drug sensitivity suggested that IC50 of proteasome inhibitor (MG-132) showed a notable significance between the risk score groups (p < 0.05). Through the NMF algorithm, we obtained the three clusters, and cluster 3 showed better survival outcomes. The expression of ubiquitin-related genes (CORO6, UBE2L3, FBXL5, DNAI1, and DCAF8) showed an obvious significance in normal and osteosarcoma tissues. Conclusion: We developed a novel ubiquitin-related gene signature which showed better predictive prognostic ability for OS and provided additional information on chemotherapy and immunotherapy. The OS molecular subtypes would also give a useful guide for individualized therapy.
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Affiliation(s)
- Nan Wei
- Orthopaedics Key Laboratory of Gansu Province, Lanzhou, China
- Lanzhou University Second Hospital, Lanzhou, China
| | - Gong Chao-yang
- Orthopaedics Key Laboratory of Gansu Province, Lanzhou, China
- Lanzhou University Second Hospital, Lanzhou, China
| | - Zhou Wen-ming
- Orthopaedics Key Laboratory of Gansu Province, Lanzhou, China
- Lanzhou University Second Hospital, Lanzhou, China
| | - Lei Ze-yuan
- Orthopaedics Key Laboratory of Gansu Province, Lanzhou, China
- Lanzhou University Second Hospital, Lanzhou, China
| | - Shi Yong-qiang
- Orthopaedics Key Laboratory of Gansu Province, Lanzhou, China
- Lanzhou University Second Hospital, Lanzhou, China
| | - Zhang Shun-bai
- Orthopaedics Key Laboratory of Gansu Province, Lanzhou, China
- Lanzhou University Second Hospital, Lanzhou, China
| | - Zhang Kai
- Orthopaedics Key Laboratory of Gansu Province, Lanzhou, China
- Lanzhou University Second Hospital, Lanzhou, China
| | - Ma Yan-chao
- Orthopaedics Key Laboratory of Gansu Province, Lanzhou, China
- Lanzhou University Second Hospital, Lanzhou, China
- *Correspondence: Ma Yan-chao, ; Zhang Hai-hong,
| | - Zhang Hai-hong
- Orthopaedics Key Laboratory of Gansu Province, Lanzhou, China
- Lanzhou University Second Hospital, Lanzhou, China
- *Correspondence: Ma Yan-chao, ; Zhang Hai-hong,
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The Regulatory Role of Ferroptosis in Bone Homeostasis. Stem Cells Int 2022; 2022:3568597. [PMID: 35873534 PMCID: PMC9300333 DOI: 10.1155/2022/3568597] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/30/2022] [Accepted: 06/27/2022] [Indexed: 12/16/2022] Open
Abstract
Ferroptosis is an iron-dependent form of programmed cell death and an important type of biological catabolism. Through the action of divalent iron or ester oxygenase, ferroptosis can induce lipid peroxidation and cell death, regulating a variety of physiological processes. The role of ferroptosis in the modulation of bone homeostasis is a significant topic of interest. Herein, we review and discuss recent studies exploring the mechanisms and functions of ferroptosis in different bone-related cells, including mesenchymal stem cells, osteoblasts, osteoclasts, and osteocytes. The association between ferroptosis and disorders of bone homeostasis is also explored in this review. Overall, we aim to provide a detailed overview of ferroptosis, summarizing recent understanding on its role in regulation of bone physiology and bone disease pathogenesis.
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Peng X, Xu Z, Guo Y, Zhu Y. Necroptosis-Related Genes Associated With Immune Activity and Prognosis of Colorectal Cancer. Front Genet 2022; 13:909245. [PMID: 35783272 PMCID: PMC9243386 DOI: 10.3389/fgene.2022.909245] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2022] [Accepted: 05/10/2022] [Indexed: 12/24/2022] Open
Abstract
This study aims at screening out the key necroptosis-related genes in colorectal cancer and elucidating the role of necroptosis-related genes in the immune activity and prognosis of colorectal cancer (CRC). The CRC patients’ data were downloaded from The Cancer Genome Atlas (TCGA). The non-negative matrix factorization method was applied to identify new molecular subgroups. Survival analysis and single sample Gene Set Enrichment Analysis were performed to determinate the differences in the overall survival time and immune status of the subgroups. Prognostic model was constructed on the basis of univariate Cox regression and LASSO analysis. Functional analyses were used to explore the potential mechanisms. Based on prognostic related necroptosis genes, we identify two molecular subgroups with significantly different survival. The better prognosis was associated with more active immune infiltration and upregulated expression of immune checkpoints. We screened nine necroptosis related genes as key prognostic genes and established a risk model, which showed a good potential for survival prediction in colorectal cancer. Nomogram assessment showed that the model had high reliability for predicting the prognosis of colorectal cancer patients. The high-risk and low-risk group also has different sensitivity to immunotherapy and commonly used drugs for colorectal cancer. Overall, necroptosis related genes were involved in the immune microenvironment of colorectal cancer patient, could be utilized to predict the prognosis of colorectal cancer and develop more individualized treatment.
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Affiliation(s)
- Xinyi Peng
- The First Clinical College of Zhejiang Chinese Medical University, Hangzhou, China
- Zhejiang Provincial Hospital of Traditional Chinese Medicine, Hangzhou, China
| | - Zhili Xu
- The First Clinical College of Zhejiang Chinese Medical University, Hangzhou, China
- Zhejiang Provincial Hospital of Traditional Chinese Medicine, Hangzhou, China
| | - Yong Guo
- The First Clinical College of Zhejiang Chinese Medical University, Hangzhou, China
- Zhejiang Provincial Hospital of Traditional Chinese Medicine, Hangzhou, China
- *Correspondence: Yong Guo, ; Ying Zhu,
| | - Ying Zhu
- The First Clinical College of Zhejiang Chinese Medical University, Hangzhou, China
- Zhejiang Provincial Hospital of Traditional Chinese Medicine, Hangzhou, China
- *Correspondence: Yong Guo, ; Ying Zhu,
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Hong J, Li Q, Wang X, Li J, Ding W, Hu H, He L. Development and validation of apoptosis-related signature and molecular subtype to improve prognosis prediction in osteosarcoma patients. J Clin Lab Anal 2022; 36:e24501. [PMID: 35576501 PMCID: PMC9280000 DOI: 10.1002/jcla.24501] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/06/2022] [Revised: 05/05/2022] [Accepted: 05/06/2022] [Indexed: 11/12/2022] Open
Abstract
BACKGROUND Previous evidence has shown that apoptosis performs integral functions in the tumorigenesis and development of various tumors. Therefore, this study aimed to establish a molecular subtype and prognostic signature based on apoptosis-related genes (ARGs) to understand the molecular mechanisms and predict prognosis in patients with osteosarcoma. METHODS The GEO and TARGET databases were utilized to obtain the expression levels of ARGs and clinical information of osteosarcoma patients. Consensus clustering analysis was used to explore the different molecular subtypes based on ARGs. GO, KEGG, GSEA, ESTIMATE, and ssGSEA analyses were performed to examine the differences in biological functions and immune characteristics between the distinct molecular subtypes. Then, we constructed an ARG signature by LASSO analysis. The prognostic significance of the ARG signature in osteosarcoma was determined by Kaplan-Meier plotter, Cox regression, and nomogram analyses. RESULTS Two apoptosis-related subtypes were identified. Cluster 1 had a better prognosis, higher immunogenicity, and immune cell infiltration, as well as a better response to immunotherapy than Cluster 2. We discovered that patients in the high-risk cohort had a lower survival rate than those in the low-risk cohort according to the ARG signature. Furthermore, Cox regression analysis confirmed that a high risk score independently acted as an unfavorable prognostic marker. Additionally, the nomogram combining risk scores with clinical characteristics can improve prediction efficiency. CONCLUSION We demonstrated that patients suffering from osteosarcoma may be classified into two apoptosis-related subtypes. Moreover, we developed an ARG prognostic signature to predict the prognosis status of osteosarcoma patients.
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Affiliation(s)
- Jinjiong Hong
- Department of Hand Surgery, Department of Plastic Reconstructive Surgery, Ningbo No. 6 Hospital, Ningbo, China
| | - Qun Li
- Department of Otorhinolaryngology Head and Neck Surgery, Ningbo Medical Center Lihuili Hospital, Ningbo, China
| | - Xiaofeng Wang
- Department of Hand Surgery, Department of Plastic Reconstructive Surgery, Ningbo No. 6 Hospital, Ningbo, China
| | - Jie Li
- Department of Orthopedics, Ningbo Medical Center Lihuili Hospital, Ningbo, China
| | - Wenquan Ding
- Department of Hand Surgery, Department of Plastic Reconstructive Surgery, Ningbo No. 6 Hospital, Ningbo, China
| | - Haoliang Hu
- Department of Hand Surgery, Department of Plastic Reconstructive Surgery, Ningbo No. 6 Hospital, Ningbo, China
| | - Lingfeng He
- Department of Hand Surgery, Department of Plastic Reconstructive Surgery, Ningbo No. 6 Hospital, Ningbo, China
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Chen S, Zeng J, Huang L, Peng Y, Yan Z, Zhang A, Zhao X, Li J, Zhou Z, Wang S, Jing S, Hu M, Li Y, Wang D, Wang W, Yu H, Miao J, Li J, Deng Y, Li Y, Liu T, Xu D. RNA adenosine modifications related to prognosis and immune infiltration in osteosarcoma. J Transl Med 2022; 20:228. [PMID: 35568866 PMCID: PMC9107650 DOI: 10.1186/s12967-022-03415-6] [Citation(s) in RCA: 19] [Impact Index Per Article: 9.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/03/2022] [Accepted: 04/27/2022] [Indexed: 11/14/2022] Open
Abstract
Background RNA adenosine modifications, which are primarily mediated by “writer” enzymes (RMWs), play a key role in epigenetic regulation in various biological processes, including tumorigenesis. However, the expression and prognostic role of these genes in osteosarcoma (OS) remain unclear. Methods Univariate and multivariate Cox analyses were used to construct the RMW signature for OS using Target datasets. RMW expression in OS tissue was detected by qPCR analysis. Xcell and GSVA were used to determine the relationship between RMWs and immune infiltration. The DGIdb and CMap databases were used for drug prediction. In vivo and in vitro experiments showed that strophanthidin elicited antitumor activity against OS. Results A 3-RMW (CSTF2, ADAR and WTAP) prognostic signature in OS was constructed using the Target dataset and verified using GEO datasets and 63 independent OS tissues via qPCR analysis. High-risk OS patients had poor overall survival, and the prognostic signature was an independent prognostic factor for OS. Functional studies showed that tumour-, metabolism-, cell cycle- and immune-related pathways were related to high risk. Next, we found that RMW-derived high-risk patients exhibited increased infiltration of M2 macrophages and cDCs. Furthermore, we predicted the potential drugs for OS using the DGIdb and CMap databases. In vivo and in vitro experiments showed that strophanthidin elicited antitumor activity against OS by repressing cell growth and inducing cell cycle arrest at the G1 phase. Conclusion The 3-RWM-based prognostic signature established in this study is a novel gene signature associated with immune infiltration, and strophanthidin was identified as a candidate therapy for OS by repressing OS cell growth and the cell cycle. Supplementary Information The online version contains supplementary material available at 10.1186/s12967-022-03415-6.
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Affiliation(s)
- Shijie Chen
- Department of Spine Surgery, The Third Xiangya Hospital of Central South University, 138 Tongzipo Rd, Changsha, 410013, Hunan, China.,Shanghai Key Laboratory of Regulatory Biology, Institute of Biomedical Sciences and School of Life Sciences, East China Normal University, 500 Dongchuan Rd, Shanghai, 200241, China
| | - Jin Zeng
- Department of Spine Surgery, The Third Xiangya Hospital of Central South University, 138 Tongzipo Rd, Changsha, 410013, Hunan, China
| | - Liping Huang
- Department of Spine Surgery, The Third Xiangya Hospital of Central South University, 138 Tongzipo Rd, Changsha, 410013, Hunan, China
| | - Yi Peng
- Department of Spine Surgery, The Third Xiangya Hospital of Central South University, 138 Tongzipo Rd, Changsha, 410013, Hunan, China
| | - Zuyun Yan
- Department of Spine Surgery, The Third Xiangya Hospital of Central South University, 138 Tongzipo Rd, Changsha, 410013, Hunan, China
| | - Aiqian Zhang
- Department of Obstetrics and Gynecology, The Third Xiangya Hospital of Central South University, 138, Tongzipo Road, Changsha, 410013, China
| | - Xingping Zhao
- Department of Obstetrics and Gynecology, The Third Xiangya Hospital of Central South University, 138, Tongzipo Road, Changsha, 410013, China
| | - Jun Li
- Department of Orthopedics, The Second Affiliated Hospital of Anhui Medical University, 678 Furong Rd, Hefei, 230601, Anhui, China
| | - Ziting Zhou
- The Third Xiangya Hospital of Central South University, 138 Tongzipo Rd, Changsha, 410013, Hunan, China
| | - Sidan Wang
- The Third Xiangya Hospital of Central South University, 138 Tongzipo Rd, Changsha, 410013, Hunan, China
| | - Shengyu Jing
- The Third Xiangya Hospital of Central South University, 138 Tongzipo Rd, Changsha, 410013, Hunan, China
| | - Minghua Hu
- Department of Anatomy, Histology, and Embryology, Changsha Medical University, 1501 Leifeng Avenue, Changsha, 410219, Hunan, China
| | - Yuezhan Li
- Department of Spine Surgery, The Third Xiangya Hospital of Central South University, 138 Tongzipo Rd, Changsha, 410013, Hunan, China
| | - Dong Wang
- Department of Spine Surgery, The Third Xiangya Hospital of Central South University, 138 Tongzipo Rd, Changsha, 410013, Hunan, China
| | - Weiguo Wang
- Department of Spine Surgery, The Third Xiangya Hospital of Central South University, 138 Tongzipo Rd, Changsha, 410013, Hunan, China
| | - Haiyang Yu
- School of Basic Medical Science, Central South University, 172 Tongzipo Rd, Changsha, 410013, Hunan, China
| | - Jinglei Miao
- Department of Spine Surgery, The Third Xiangya Hospital of Central South University, 138 Tongzipo Rd, Changsha, 410013, Hunan, China
| | - Jinsong Li
- Department of Spine Surgery, The Third Xiangya Hospital of Central South University, 138 Tongzipo Rd, Changsha, 410013, Hunan, China
| | - Youwen Deng
- Department of Spine Surgery, The Third Xiangya Hospital of Central South University, 138 Tongzipo Rd, Changsha, 410013, Hunan, China
| | - Yusheng Li
- Department of Orthopeadics, Xiangya Hospital, Central South University, 87 Xiangya Rd, Changsha, 410008, Hunan, China.
| | - Tang Liu
- Department of Orthopaedics, The Second Xiangya Hospital of Central South University, 139 Renmin Middle Rd, Changsha, 410011, Hunan, China.
| | - Dabao Xu
- Department of Obstetrics and Gynecology, The Third Xiangya Hospital of Central South University, 138, Tongzipo Road, Changsha, 410013, China.
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A Risk-Scoring Model Based on Evaluation of Ferroptosis-Related Genes in Osteosarcoma. JOURNAL OF ONCOLOGY 2022; 2022:4221756. [PMID: 35386212 PMCID: PMC8979715 DOI: 10.1155/2022/4221756] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 01/21/2022] [Revised: 03/02/2022] [Accepted: 03/03/2022] [Indexed: 12/15/2022]
Abstract
Background Osteosarcoma (OS) is a bone malignancy frequently seen in pediatrics and has high mortality and incidence. Ferroptosis is an important cell death process in regulating the apoptosis and invasion of tumor cells, so constructing the risk-scoring model based on OS ferroptosis-related genes (FRGs) will benefit the evaluation of both treatment and prognosis. Methods The OS dataset was screened from the Therapeutically Applicable Research to Generate Effective Treatments (TARGET) database, and OS-related FRGs were found through the Ferroptosis Database (FerrDb) using a multivariate Cox regression model, followed by the generation of the risk scores and a risk-scoring prediction model. Further systematical exploration for immune cell infiltration and assessing the prediction of response to targeted drugs was conducted. Results Based on OS-related FRGs, a risk-scoring model of FRGs in OS was constructed. The six FRGs played a role in the carbon metabolism, glutathione metabolism, and pentose phosphate pathways. Results from targeted drug sensitivity analyses were concordant to pathway analyses. The response to targeted drugs statistically differed between the two groups with different risks, and the high-risk group presented a high sensitivity to targeted drugs. Conclusions We identified a 6-ferroptosis-gene-based prognostic signature in OS and created and verified a risk-scoring model to predict the prognosis of OS at 1, 3, and 5 years for OS patients independently.
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Feng H, Wang L, Liu J, Wang S. The bioinformatic approach identifies PARM1 as a new potential prognostic factor in osteosarcoma. Front Oncol 2022; 12:1059547. [PMID: 36950314 PMCID: PMC10025378 DOI: 10.3389/fonc.2022.1059547] [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: 10/01/2022] [Accepted: 12/23/2022] [Indexed: 03/08/2023] Open
Abstract
Objective To explore the key factors affecting the prognosis of osteosarcoma patients. Methods Based on the GEO dataset and differential expression analysis of normal and osteosarcoma tissues, the gene modules related to the prognosis of osteosarcoma patients were screened by WGCNA, and intersecting genes were taken with differential genes, and the risk prognosis model of osteosarcoma patients was constructed by LASSO regression analysis of intersecting genes, and the prognosis-related factors of osteosarcoma patients were obtained by survival analysis, followed by target for validation, and finally, the expression of prognostic factors and their effects on osteosarcoma cell migration were verified by cellular assays and lentiviral transfection experiments. Results The prognosis-related gene module of osteosarcoma patients were intersected with differential genes to obtain a total of 9 common genes. PARM1 was found to be a prognostic factor in osteosarcoma patients by LASSO regression analysis, followed by cellular assays to verify that PARM1 was lowly expressed in osteosarcoma cells and that overexpression of PARM1 in osteosarcoma cells inhibited cell migration. Pan-cancer analysis showed that PARM1 was lowly expressed in most cancers and that low expression of PARM1 predicted poor prognosis for patients. Conclusion The data from this study suggest that PARM1 is closely associated with the prognosis of osteosarcoma patients, and PARM1 may serve as a novel potential prognostic target for osteosarcoma, providing a heartfelt direction for the prevention and treatment of osteosarcoma.
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Affiliation(s)
- Haijun Feng
- Department of Orthopedics, Second Hospital of Lanzhou University, Lanzhou, Gansu, China
| | - Liping Wang
- Department of Orthopedics, Second Hospital of Lanzhou University, Lanzhou, Gansu, China
| | - Jie Liu
- Department of Neurosurgery, Liaocheng Second People’s Hospital, Liaocheng, Shandong, China
| | - Shengbao Wang
- Second Hospital of Lanzhou University, Lanzhou, Gansu, China
- *Correspondence: Shengbao Wang,
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Song P, Xie Z, Chen C, Chen L, Wang X, Wang F, Xie X, Hong X, Wang Y, Wu X. Identification of a novel iron zinc finger protein 36 (ZFP36) for predicting the overall survival of osteosarcoma based on the Gene Expression Omnibus (GEO) database. ANNALS OF TRANSLATIONAL MEDICINE 2021; 9:1552. [PMID: 34790758 PMCID: PMC8576698 DOI: 10.21037/atm-21-5086] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/17/2021] [Accepted: 10/22/2021] [Indexed: 12/04/2022]
Abstract
Background The purpose of this study is to explore the relationship between the ferroptosis-related gene zinc finger protein 36 (ZFP36) and the prognosis of osteosarcoma patients after surgery. Methods Differential expression genes (DEGs) between osteosarcoma and normal tissues were screened using osteosarcoma chip data in GEO database. Based on the median expression quantity, ferroptosis DEGs were divided into high and low expression groups. Combined with its corresponding clinical survival data, the survival analysis of ferroptosis DEGs was carried out using the Survival package, and ferroptosis-related genes related to prognosis were identified. Next, the clinical data of 60 osteosarcoma patients treated in Jiangyin Hospital Affiliated to Nanjing University of Chinese Medicine, Zhongda Hospital and Nanjing Drum Tower Hospital from January 2011 to January 2016 were retrospectively analyzed. Immunohistochemistry and reverse transcription quantitative polymerase chain reaction (qRT-PCR) were used to detect gene expression in osteosarcoma. The Kaplan-Meier method and log rank test were used for univariate survival analysis, the Cox regression method was used for multivariate analysis, and the nomogram was constructed for internal verification on this basis. Results Immunohistochemical and reverse transcription quantitative PCR results showed that the expression of ZFP36 was mainly higher in cancer-adjacent tissues than in tumor tissues. There were significant differences in age, tumor location, Enneking stage, and tumor specific growth factor (TSGF) between the high and low expression groups of ZFP36 (P<0.05). The final study included 60 patients, of whom 23 patients died (mortality rate: 38.33%), and 37 patients survived (survival rate: 61.67%), with a median progression-free survival (PFS) of 32.5 months and a median overall survival (OS) of 77 months. The Cox multivariate analysis showed that distant metastasis and ZFP36 were independent risk factors affecting tumor progression (P=0.021 and P=0.006, respectively). Elevated ZFP36 can significantly prolong the OS and PFS of osteosarcoma patients. In internal verification, the Concordance index (C-index) of the nomogram was 0.7211 [95% confidence interval (CI): 0.6308–0.8115], and the prediction model had certain accuracy. Conclusions Elevated ZFP36 can significantly prolong the OS and PFS in osteosarcoma patients. At the same time, ZFP36 could be used as a new predictive biomarker and novel therapeutic target for osteosarcoma patients.
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Affiliation(s)
- Peng Song
- Department of Spinal Surgery, Zhongda Hospital, School of Medicine, Southeast University, Nanjing, China
| | - Zhiyang Xie
- Department of Spinal Surgery, Zhongda Hospital, School of Medicine, Southeast University, Nanjing, China
| | - Changhong Chen
- Department of Orthopaedic Surgery, Jiangyin Hospital Affiliated to Nanjing University of Chinese Medicine, Wuxi, China
| | - Ling Chen
- Department of Pathology, Nanjing Drum Tower Hospital, Nanjing University Medical School, Nanjing, China
| | - Xiaohu Wang
- Department of Spinal Surgery, Zhongda Hospital, School of Medicine, Southeast University, Nanjing, China
| | - Feng Wang
- Department of Spinal Surgery, Zhongda Hospital, School of Medicine, Southeast University, Nanjing, China
| | - Xinhui Xie
- Department of Spinal Surgery, Zhongda Hospital, School of Medicine, Southeast University, Nanjing, China
| | - Xin Hong
- Department of Spinal Surgery, Zhongda Hospital, School of Medicine, Southeast University, Nanjing, China
| | - Yuntao Wang
- Department of Spinal Surgery, Zhongda Hospital, School of Medicine, Southeast University, Nanjing, China
| | - Xiaotao Wu
- Department of Spinal Surgery, Zhongda Hospital, School of Medicine, Southeast University, Nanjing, China
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