[Identification of lncrnas associated with aniline toxicity in male bladder cancer and construction of tumor risk prediction models].
Zhonghua Nan Ke Xue
; 29(9): 790-798, 2023 Sep.
Article
em Zh
| MEDLINE
| ID: mdl-38639590
ABSTRACT
OBJECTIVE:
Aniline poisoning is considered to be an important factor mediating the development and progression of male bladder cancer,and long non-coding RNA(lncRNA)has also been shown to affect the prognosis of male bladder cancer.Therefore,this study intended to screen and identify lncrnas associated with highly sensitive aniline poisoning of male bladder cancer,and to construct a tumor risk prediction model accordingly.METHODS:
Gene expression and clinical data from 410 tissues were downloaded from the Cancer Genome Atlas(TCGA),and all samples were randomly divided into training and testing groups.Lncrnas associated with aniline poisoning were distinguished.We then performed univariate COX and multivariate COX regressions,in parallel with LASSO regression,to establish a lncRNA risk model associated with aniline poisoning.Kaplan-Meier curve,scatterplot,C-index,ROCcurve,nomogram,PCAanalysis,and univariate and multivariate Cox regression were used to test the accuracy of the risk model and predict patient survival.RESULTS:
Seven lncrnas associated with aniline poisoning(LINC01184, LINC00513,LINC02443,SMARCA5-AS1,BDNF-AS,SOD2-OT1,HYI-AS1)were screened and identified,and based on this,a risk prediction model with high sensitivity to the malignant progression of bladder cancer was constructed.It is also verified that the model can effectively predict the overall survival(OS)of the test group and the whole cohort at different stages.CONCLUSIONS:
We identified 7 lncrnas associated with aniline poisoning and established a novel risk model of lncrnas associated with aniline poisoning,which provides new insights for prognosis assessment and may guide the comprehensive treatment of male bladder cancer.Palavras-chave
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Base de dados:
MEDLINE
Assunto principal:
Neoplasias da Bexiga Urinária
/
RNA Longo não Codificante
Idioma:
Zh
Ano de publicação:
2023
Tipo de documento:
Article
País de afiliação:
China