Evidence map›Paper›PMID 35136353›Full record

ArticleInternational journal of general medicine2022

A Novel Glutamine Metabolism-Related Gene Signature in Prognostic Prediction of Osteosarcoma.

Lu Wan, Wenchao Zhang, Zhongyue Liu, Zhimin Yang, Chao Tu, Zhihong Li

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Article in International journal of general medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

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5citing papers in PubMed
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5 citing papers in PubMed.

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5 · Who and what money

Authors and funding

6 authors.

Lu WanKey Laboratory of Tumor Models and Individualized Medicine, The Second Xiangya Hospital of Central South University, Changsha, Hunan, People's Republic of China.
Wenchao ZhangKey Laboratory of Tumor Models and Individualized Medicine, The Second Xiangya Hospital of Central South University, Changsha, Hunan, People's Republic of China.
Zhongyue LiuKey Laboratory of Tumor Models and Individualized Medicine, The Second Xiangya Hospital of Central South University, Changsha, Hunan, People's Republic of China.
Zhimin YangKey Laboratory of Tumor Models and Individualized Medicine, The Second Xiangya Hospital of Central South University, Changsha, Hunan, People's Republic of China.
Chao TuKey Laboratory of Tumor Models and Individualized Medicine, The Second Xiangya Hospital of Central South University, Changsha, Hunan, People's Republic of China.
Zhihong LiKey Laboratory of Tumor Models and Individualized Medicine, The Second Xiangya Hospital of Central South University, Changsha, Hunan, People's Republic of China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeMetabolic reprogramming, as one of the hallmarks of cancer, shows promising translational potential for cancer diagnosis, treatment and prognostic prediction. This study aims to construct and validate a prognostic prediction model for osteosarcoma based on glutamine metabolism-related genes. MATERIALS AND

methodsA group of glutamine metabolism-related genes was identified from a public database and intersected with a list of osteosarcoma survival-related genes, and a risk score model based on sixteen glutamine metabolism-related genes was developed by using LASSO penalized Cox regression analysis.

resultsThe prognosis of patients in the high-risk group was significantly worse than that of patients in the low-risk group in the training dataset (high- vs low-risk, 5-year overall survival: 11% vs 88%, p < 0.0001) and in two other external validation cohorts (high- vs low-risk, 5-year overall survival: 39% vs 81%, p = 0.015; 50% vs 94%, p = 0.011).In addition, a novel nomogram was constructed by integrating the risk score and clinical characteristics, including age, sex, metastasis status and chemotherapy response. This nomogram had superior predictive power compared with a nomogram composed of only conventional factors. Gene set enrichment analysis indicated that several well-known malignancy-associated gene sets, including MYC targets V1, DNA repair, and unfolded protein response, were enriched in the high-risk subgroup.

conclusionA novel glutamine metabolism-related prognostic prediction model and nomogram for osteosarcoma was developed and validated in the present study, which could predict the survival of patients with osteosarcoma and may facilitate individualized clinical decision-making for patients.

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amino acid metabolismbone tumornomogramsurvivorship

Identifiers

PMID35136353
PMCPMC8817953

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