Nomogram of uveal melanoma as prediction model of metastasis risk.
Nomogram
Uveal melanoma
Journal
Heliyon
ISSN: 2405-8440
Titre abrégé: Heliyon
Pays: England
ID NLM: 101672560
Informations de publication
Date de publication:
Aug 2023
Aug 2023
Historique:
received:
21
01
2023
revised:
01
08
2023
accepted:
03
08
2023
medline:
23
8
2023
pubmed:
23
8
2023
entrez:
23
8
2023
Statut:
epublish
Résumé
Since the poor prognosis of uveal melanoma with distant metastasis, we intended to screen out possible biomarkers for uveal melanoma metastasis risk and establish a nomogram model for predicting the risk of uveal melanoma (UVM) metastasis. Two datasets of UVM (GSE84976, GSE22138) were selected. Data was analyzed by R language, CTD database and GEPIA. The co-upregulated genes of two datasets, HTR2B, CHAC1, AHNAK2, and PTP4A3 were identified using a Venn diagram. These biomarkers are combined with clinical characteristics, and Lasso regression was conducted to filter the metastasis-related biomarkers. HTR2B, CHAC1, AHNAK2, PTP4A3, tumor thickness, and retinal detachment (RD) were selected to establish the nomogram. Our study provides a comprehensive predictive model and personalized risk estimation tool for assessment of 3-year metastasis risk of UVM with a better accuracy.
Sections du résumé
Background
UNASSIGNED
Since the poor prognosis of uveal melanoma with distant metastasis, we intended to screen out possible biomarkers for uveal melanoma metastasis risk and establish a nomogram model for predicting the risk of uveal melanoma (UVM) metastasis.
Methods
UNASSIGNED
Two datasets of UVM (GSE84976, GSE22138) were selected. Data was analyzed by R language, CTD database and GEPIA.
Results
UNASSIGNED
The co-upregulated genes of two datasets, HTR2B, CHAC1, AHNAK2, and PTP4A3 were identified using a Venn diagram. These biomarkers are combined with clinical characteristics, and Lasso regression was conducted to filter the metastasis-related biomarkers. HTR2B, CHAC1, AHNAK2, PTP4A3, tumor thickness, and retinal detachment (RD) were selected to establish the nomogram.
Conclusion
UNASSIGNED
Our study provides a comprehensive predictive model and personalized risk estimation tool for assessment of 3-year metastasis risk of UVM with a better accuracy.
Identifiants
pubmed: 37609406
doi: 10.1016/j.heliyon.2023.e18956
pii: S2405-8440(23)06164-9
pmc: PMC10440531
doi:
Types de publication
Journal Article
Langues
eng
Pagination
e18956Informations de copyright
© 2023 Published by Elsevier Ltd.
Déclaration de conflit d'intérêts
The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
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