Construction and validation of a prognostic model for gastrointestinal stromal tumors based on copy number alterations and clinicopathological characteristics

Autor: Heng Zhao, Nuohan Song, Hao Feng, Qiang Lei, Yingying Zheng, Jing Liu, Chunyan Liu, Zhengbin Chai
Jazyk: angličtina
Rok vydání: 2022
Předmět:
Zdroj: Frontiers in Oncology, Vol 12 (2022)
Druh dokumentu: article
ISSN: 2234-943X
DOI: 10.3389/fonc.2022.1055174
Popis: BackgroundThe increasing incidence of gastrointestinal stromal tumors (GISTs) has led to the discovery of more novel prognostic markers. We aim to establish an unsupervised prognostic model for the early prediction of the prognosis of future patients with GISTs and to guide clinical treatment.MethodsWe downloaded the GISTs dataset through the cBioPortal website. We extracted clinical information and pathological information, including the microsatellite instability (MSI) score, fraction genome altered (FGA) score, tumor mutational burden (TMB), and copy number alteration burden (CNAB), of patients with GISTs. For survival analysis, we used univariate Cox regression to analyze the contribution of each factor to prognosis and calculated a hazard ratio (HR) and 95% confidence interval (95% CI). For clustering groupings, we used the t-distributed stochastic neighbor embedding (t-SNE) method for data dimensionality reduction. Subsequently, the k-means method was used for clustering analysis.ResultsA total of 395 individuals were included in the study. After dimensionality reduction with t-SNE, all patients were divided into two subgroups. Cluster 1 had worse OS than cluster 2 (HR=3.45, 95% CI, 2.22-5.56, P
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