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Jia F, Liu L, Weng Q, Zhang H, Zhao X. Glycolysis-Metabolism-Related Prognostic Signature for Ewing Sarcoma Patients. Mol Biotechnol 2023:10.1007/s12033-023-00899-5. [PMID: 37775679 DOI: 10.1007/s12033-023-00899-5] [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: 07/07/2023] [Accepted: 09/11/2023] [Indexed: 10/01/2023]
Abstract
Ewing sarcoma (EwS) is a malignant sarcoma which occurs in bone and soft tissues commonly happening in children with poor survival rates. Changes in cell metabolism, such as glycolysis, may provide the environment for the transformation and progression of tumors. We aimed to build a model to predict prognosis of EwS patients based on glycolysis and metabolism genes. Candidate genes were obtained by differential gene expression analysis based on GSE17679, GSE17674 and ICGC datasets. We performed GO and KEGG pathway enrichment analysis on candidate genes. Univariate Cox and LASSO Cox regression analyses were conducted to construct a model to calculate the Risk Score. GSEA was done between high-risk and low-risk groups. CIBERSORT was applied to analyze the immune landscape. We got 295 candidate glycolysis-metabolism-related genes which were enriched in 620 GO terms and 18 KEGG pathways. 12 Genes were selected by univariate Cox model and 5 of them were determined by LASSO Cox regression analysis to be used in the construction of the Risk Score model. The Risk Score could be considered as an independent prognosis factor. The immune landscape and immune checkpoints' expression significantly differed between high- and low-risk groups. Our research constructed a new glycolysis-metabolism-related genes (FABP5, EMILIN1, GLCE, PHF11 and PALM3) based prognostic signature for EwS patients and assisted in gaining insight into prognosis to improve therapies further.
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Affiliation(s)
- Fusen Jia
- Department of Hand & Foot Surgery, Zibo Central Hospital, Zhangdian District, Zibo, 255036, Shandong, People's Republic of China
| | - Lei Liu
- Orthopedic Surgery 2nd, Qilu Hospital Huantai Branch, Huantai County, Zibo, 256400, Shandong, People's Republic of China
| | - Qi Weng
- Department of Psychology, Zibo Maternal and Child Health Hospital, Zhangdian District, Zibo, 255022, Shandong, People's Republic of China
| | - Haiyang Zhang
- Department of Hand & Foot Surgery, Zibo Central Hospital, Zhangdian District, Zibo, 255036, Shandong, People's Republic of China
| | - Xuesheng Zhao
- Orthopedic Surgery 2nd, The Fifth People's Hospital of Jinan, No. 24297 Jingshi Road, Huaiyin District, Jinan, 250000, Shandong, People's Republic of China.
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Wang Y, Jiang R, Wang T, Wu Z, Gong H, Cai X, Liu J, Yang X, Wei H, Jiao J, Jia Q, Yang C, Zhao C, Xiao J. Identification of ARAP3 as a regulator of tumor progression, macrophage infiltration and osteoclast differentiation in a tumor microenvironment-related prognostic model of Ewing sarcoma. Am J Cancer Res 2023; 13:3721-3740. [PMID: 37693165 PMCID: PMC10492096] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/19/2022] [Accepted: 06/11/2023] [Indexed: 09/12/2023] Open
Abstract
Understanding the specificity and complexity of the tumor microenvironment (TME) of Ewing sarcoma (ES) is essential for identifying the immune characteristics of ES, improving the prediction of immunotherapeutic response, and facilitating therapeutic target discovery. In this study, we not only evaluated the gene sets associated with TME in ES using ESTIMATE and WGCNA algorithms based on the transcriptome data of ES, but also constructed a prognostic model (ES Score) using univariate Cox regression and Lasso regression and assessed its predictive ability on immune cell infiltration. Subsequently, we identified ARAP3 as a key gene affecting the TME of ES. In addition, bioinformatic analyses and in vitro experiments proved that the high expression of ARAP3 regulated ES cell proliferation, migration, as well as apoptosis via the p53 signaling pathway and affected macrophage infiltration and osteoclast differentiation through regulating IL1B and IL11 secretion of tumor cells.
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Affiliation(s)
- Yao Wang
- Spine Tumor Center, Department of Orthopedic Oncology, Changzheng Hospital, Naval Medical University Shanghai, China
| | - Runyi Jiang
- Spine Tumor Center, Department of Orthopedic Oncology, Changzheng Hospital, Naval Medical University Shanghai, China
| | - Ting Wang
- Spine Tumor Center, Department of Orthopedic Oncology, Changzheng Hospital, Naval Medical University Shanghai, China
| | - Zhipeng Wu
- Spine Tumor Center, Department of Orthopedic Oncology, Changzheng Hospital, Naval Medical University Shanghai, China
| | - Haiyi Gong
- Spine Tumor Center, Department of Orthopedic Oncology, Changzheng Hospital, Naval Medical University Shanghai, China
| | - Xiaopan Cai
- Spine Tumor Center, Department of Orthopedic Oncology, Changzheng Hospital, Naval Medical University Shanghai, China
| | - Jialiang Liu
- Spine Tumor Center, Department of Orthopedic Oncology, Changzheng Hospital, Naval Medical University Shanghai, China
| | - Xinghai Yang
- Spine Tumor Center, Department of Orthopedic Oncology, Changzheng Hospital, Naval Medical University Shanghai, China
| | - Haifeng Wei
- Spine Tumor Center, Department of Orthopedic Oncology, Changzheng Hospital, Naval Medical University Shanghai, China
| | - Jian Jiao
- Spine Tumor Center, Department of Orthopedic Oncology, Changzheng Hospital, Naval Medical University Shanghai, China
| | - Qi Jia
- Spine Tumor Center, Department of Orthopedic Oncology, Changzheng Hospital, Naval Medical University Shanghai, China
| | - Cheng Yang
- Spine Tumor Center, Department of Orthopedic Oncology, Changzheng Hospital, Naval Medical University Shanghai, China
| | - Chenglong Zhao
- Spine Tumor Center, Department of Orthopedic Oncology, Changzheng Hospital, Naval Medical University Shanghai, China
| | - Jianru Xiao
- Spine Tumor Center, Department of Orthopedic Oncology, Changzheng Hospital, Naval Medical University Shanghai, China
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Du Q, Zhou R, Wang H, Li Q, Yan Q, Dang W, Guo J. A metabolism-related gene signature for predicting the prognosis in thyroid carcinoma. Front Genet 2023; 13:972950. [PMID: 36685893 PMCID: PMC9846547 DOI: 10.3389/fgene.2022.972950] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/19/2022] [Accepted: 11/23/2022] [Indexed: 01/06/2023] Open
Abstract
Metabolic reprogramming is one of the cancer hallmarks, important for the survival of malignant cells. We investigated the prognostic value of genes associated with metabolism in thyroid carcinoma (THCA). A prognostic risk model of metabolism-related genes (MRGs) was built and tested based on datasets in The Cancer Genome Atlas (TCGA), with univariate Cox regression analysis, LASSO, and multivariate Cox regression analysis. We used Kaplan-Meier (KM) curves, time-dependent receiver operating characteristic curves (ROC), a nomogram, concordance index (C-index) and restricted mean survival (RMS) to assess the performance of the risk model, indicating the splendid predictive performance. We established a three-gene risk model related to metabolism, consisting of PAPSS2, ITPKA, and CYP1A1. The correlation analysis in patients with different risk statuses involved immune infiltration, mutation and therapeutic reaction. We also performed pan-cancer analyses of model genes to predict the mutational value in various cancers. Our metabolism-related risk model had a powerful predictive capability in the prognosis of THCA. This research will provide the fundamental data for further development of prognostic markers and individualized therapy in THCA.
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Affiliation(s)
- Qiujing Du
- Department of General Medicine, Third Hospital of Shanxi Medical University, Shanxi Bethune Hospital, Shanxi Academy of Medical Sciences, Tongji Shanxi Hospital, Taiyuan, China
| | - Ruhao Zhou
- Department of Orthopedics, Shanxi Key Laboratory of Bone and Soft Tissue Injury Repair, Second Clinical Medical College, Shanxi Medical University, Taiyuan, China
| | - Heng Wang
- Department of Vascular Surgery, Second Clinical Medical College, Shanxi Medical University, Taiyuan, China
| | - Qian Li
- Basic Medical College, Shanxi Medical University, Jinzhong, China
| | - Qi Yan
- Department of Endocrinology, Second Clinical Medical College, Shanxi Medical University, Taiyuan, China
| | - Wenjiao Dang
- Department of General Medicine, Third Hospital of Shanxi Medical University, Shanxi Bethune Hospital, Shanxi Academy of Medical Sciences, Tongji Shanxi Hospital, Taiyuan, China
| | - Jianjin Guo
- Department of General Medicine, Third Hospital of Shanxi Medical University, Shanxi Bethune Hospital, Shanxi Academy of Medical Sciences, Tongji Shanxi Hospital, Taiyuan, China,*Correspondence: Jianjin Guo,
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Zhang J, Ma C, Qin H, Wang Z, Zhu C, Liu X, Hao X, Liu J, Li L, Cai Z. Construction and validation of a metabolic-related genes prognostic model for oral squamous cell carcinoma based on bioinformatics. BMC Med Genomics 2022; 15:269. [PMID: 36566175 PMCID: PMC9789624 DOI: 10.1186/s12920-022-01417-3] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/12/2022] [Accepted: 12/13/2022] [Indexed: 12/25/2022] Open
Abstract
BACKGROUND Oral squamous cell carcinoma (OSCC) accounts for a frequently-occurring head and neck cancer, which is characterized by high rates of morbidity and mortality. Metabolism-related genes (MRGs) show close association with OSCC development, metastasis and progression, so we constructed an MRGs-based OSCC prognosis model for evaluating OSCC prognostic outcome. METHODS This work obtained gene expression profile as well as the relevant clinical information from the The Cancer Genome Atlas (TCGA) database, determined the MRGs related to OSCC by difference analysis, screened the prognosis-related MRGs by performing univariate Cox analysis, and used such identified MRGs for constructing the OSCC prognosis prediction model through Lasso-Cox regression. Besides, we validated the model with the GSE41613 dataset based on Gene Expression Omnibus (GEO) database. RESULTS The present work screened 317 differentially expressed MRGs from the database, identified 12 OSCC prognostic MRGs through univariate Cox regression, and then established a clinical prognostic model composed of 11 MRGs by Lasso-Cox analysis. Based on the optimal risk score threshold, cases were classified as low- or high-risk group. As suggested by Kaplan-Meier (KM) analysis, survival rate was obviously different between the two groups in the TCGA training set (P < 0.001). According to subsequent univariate and multivariate Cox regression, risk score served as the factor to predict prognosis relative to additional clinical features (P < 0.001). Besides, area under ROC curve (AUC) values for patient survival at 1, 3 and 5 years were determined as 0.63, 0.70, and 0.76, separately, indicating that the prognostic model has good predictive accuracy. Then, we validated this clinical prognostic model using GSE41613. To enhance our model prediction accuracy, age, gender, risk score together with TNM stage were incorporated in a nomogram. As indicated by results of ROC curve and calibration curve analyses, the as-constructed nomogram had enhanced prediction accuracy compared with clinicopathological features alone, besides, combining clinicopathological characteristics with risk score contributed to predicting patient prognosis and guiding clinical decision-making. CONCLUSION In this study, 11 MRGs prognostic models based on TCGA database showed superior predictive performance and had a certain clinical application prospect in guiding individualized.
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Affiliation(s)
- Jingfei Zhang
- grid.440653.00000 0000 9588 091XDepartment of Stomatology, Binzhou Medical University, Yantai, 264000 Shandong China
| | - Chenxi Ma
- grid.27255.370000 0004 1761 1174Department of Human Microbiome, School and Hospital of Stomatology, Shandong Provincial Key Laboratory of Oral Tissue Regeneration, Shandong Engineering Laboratory for Dental Materials and Oral Tissue Regeneration, Shandong University, Jinan, 250000 Shandong China
| | - Han Qin
- grid.440653.00000 0000 9588 091XDepartment of Stomatology, Binzhou Medical University, Yantai, 264000 Shandong China
| | - Zhi Wang
- grid.415946.b0000 0004 7434 8069Department of Stomatology, Linyi People’s Hospital, Linyi, 276000 Shandong China
| | - Chao Zhu
- grid.415946.b0000 0004 7434 8069Department of Stomatology, Linyi People’s Hospital, Linyi, 276000 Shandong China
| | - Xiujuan Liu
- grid.415946.b0000 0004 7434 8069Department of Stomatology, Linyi People’s Hospital, Linyi, 276000 Shandong China
| | - Xiuyan Hao
- grid.415946.b0000 0004 7434 8069Department of Stomatology, Linyi People’s Hospital, Linyi, 276000 Shandong China
| | - Jinghua Liu
- grid.415946.b0000 0004 7434 8069Department of Hepatobiliary Surgery and Minimally Invasive Institute of Digestive Surgery and Prof. Cai’s Laboratory, Linyi People’s Hospital, Shandong University, Linyi, 264000 Shandong China
| | - Ling Li
- grid.415946.b0000 0004 7434 8069Department of Stomatology, Linyi People’s Hospital, Linyi, 276000 Shandong China
| | - Zhen Cai
- grid.415946.b0000 0004 7434 8069Department of Stomatology, Linyi People’s Hospital, Linyi, 276000 Shandong China
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Wen J, Wan L, Dong X. The prognostic value of autophagy related genes with potential protective function in Ewing sarcoma. BMC Bioinformatics 2022; 23:306. [PMID: 35902797 PMCID: PMC9335970 DOI: 10.1186/s12859-022-04849-x] [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: 04/24/2022] [Accepted: 07/19/2022] [Indexed: 11/19/2022] Open
Abstract
Background Ewing sarcoma (ES) is the second most common primary malignant bone tumor mainly occurring in children, adolescents and young adults with high metastasis and mortality. Autophagy has been reported to be involved in the survival of ES, but the role remains unclear. Therefore, it’s necessary to investigate the prognostic value of autophagy related genes using bioinformatics methods. Results ATG2B, ATG10 and DAPK1 were final screened genes for a prognostic model. KM and risk score plots showed patients in high score group had better prognoses both in training and validation sets. C-indexes of the model for training and validation sets were 0.68 and 0.71, respectively. Calibration analyses indicated the model had high prediction accuracy in training and validation sets. The AUC values of ROC for 1-, 3-, 5-year prediction were 0.65, 0.73 and 0.84 in training set, 0.88, 0.73 and 0.79 in validation set, which suggested high prediction accuracy of the model. Decision curve analyses showed that patients could benefit much from the model. Differential and functional analyses suggested that autophagy and apoptosis were upregulated in high risk score group. Conclusions ATG2B, ATG10 and DAPK1 were autophagy related genes with potential protective function in ES. The prognostic model established by them exhibited excellent prediction accuracy and discriminatory capacities. They might be used as potential prognostic biomarkers and therapeutic targets in ES. Supplementary Information The online version contains supplementary material available at 10.1186/s12859-022-04849-x.
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Affiliation(s)
- Jian Wen
- Medical College of Nanchang University, Nanchang, 330006, Jiangxi, China.,Department of Orthopedics, Jiangxi Provincial People's Hospital, 152 Aiguo Road, Nanchang, 330006, Jiangxi, China.,JXHC Key Laboratory of Digital Orthopedics (Jiangxi Provincial People's Hospital), 152 Aiguo Road, Nanchang, 330006, Jiangxi, China
| | - Lijia Wan
- Department of Pediatrics, The Second Xiangya Hospital, Central South University, Changsha, 410011, Hunan, China
| | - Xieping Dong
- Medical College of Nanchang University, Nanchang, 330006, Jiangxi, China. .,Department of Orthopedics, Jiangxi Provincial People's Hospital, 152 Aiguo Road, Nanchang, 330006, Jiangxi, China. .,JXHC Key Laboratory of Digital Orthopedics (Jiangxi Provincial People's Hospital), 152 Aiguo Road, Nanchang, 330006, Jiangxi, China.
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