Literature DB >> 33952718

Identification of a novel glycolysis-related gene signature for predicting the prognosis of osteosarcoma patients.

Mengkai Yang1, Xiaojun Ma1, Zhuoying Wang1, Tao Zhang1, Yingqi Hua1, Zhengdong Cai1.   

Abstract

Glycolysis ensures energy supply to cancer cells, thereby facilitating tumor progression. Here, we identified glycolysis-related genes that could predict the prognosis of patients with osteosarcoma. We examined 198 glycolysis-related genes that showed differential expression in metastatic and non-metastatic osteosarcoma samples in the TARGET database, and identified three genes (P4HA1, ABCB6, and STC2) for the establishment of a risk signature. Based on the signature, patients in the high-risk group had poor outcomes. An independent Gene Expression Omnibus database GSE21257 was selected as the validation cohort. Receiver operating characteristic curve analysis was performed and the accuracy of predicting the 1- and 3-year survival rates was shown by the areas under the curve. The results were 0.884 and 0.790 in the TARGET database, and 0.740 and 0.759 in the GSE21257, respectively. Furthermore, we applied ESTIMATE algorithm and performed single sample gene set enrichment analysis to compare tumor immunity between high- and low-risk groups. We found that the low-risk group had higher immune scores and immune infiltration levels than the high-risk group. Finally, we chose P4HA1 as a representative gene to verify the function of risk genes in vitro and in vivo and found that P4HA1 could promote the metastasis of osteosarcoma cells. Our study established a novel glycolysis-related risk signature that could predict the prognosis of patients with osteosarcoma.

Entities:  

Keywords:  P4HA1; glycolysis; metastasis; osteosarcoma; prognosis

Year:  2021        PMID: 33952718     DOI: 10.18632/aging.202958

Source DB:  PubMed          Journal:  Aging (Albany NY)        ISSN: 1945-4589            Impact factor:   5.682


  6 in total

1.  Global Characterization of Metabolic Genes Regulating Survival and Immune Infiltration in Osteosarcoma.

Authors:  Zhongpei Zhu; Min Zhang; Weidong Wang; Peng Zhang; Yuqiang Wang; Limin Wang
Journal:  Front Genet       Date:  2022-01-13       Impact factor: 4.599

2.  Identification of a seven-gene prognostic signature using the gene expression profile of osteosarcoma.

Authors:  Zhe Liu; Yun Zhong; Senling Meng; Qinyuan Liao; Weicai Chen
Journal:  Ann Transl Med       Date:  2022-01

Review 3.  Stanniocalcin 2 (STC2): a universal tumour biomarker and a potential therapeutical target.

Authors:  Shuo Qie; Nianli Sang
Journal:  J Exp Clin Cancer Res       Date:  2022-05-02

Review 4.  A Pan-Cancer Analysis Reveals the Prognostic and Immunotherapeutic Value of Stanniocalcin-2 (STC2).

Authors:  Zhong-Hui Jiang; Xianfeng Shen; Yanhong Wei; Yongji Chen; Hongbo Chai; Lingyun Xia; Weidong Leng
Journal:  Front Genet       Date:  2022-07-22       Impact factor: 4.772

5.  Development and validation of apoptosis-related signature and molecular subtype to improve prognosis prediction in osteosarcoma patients.

Authors:  Jinjiong Hong; Qun Li; Xiaofeng Wang; Jie Li; Wenquan Ding; Haoliang Hu; Lingfeng He
Journal:  J Clin Lab Anal       Date:  2022-05-16       Impact factor: 3.124

Review 6.  Metastatic Progression of Osteosarcomas: A Review of Current Knowledge of Environmental versus Oncogenic Drivers.

Authors:  Guillaume Anthony Odri; Joëlle Tchicaya-Bouanga; Diane Ji Yun Yoon; Dominique Modrowski
Journal:  Cancers (Basel)       Date:  2022-01-12       Impact factor: 6.639

  6 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.