Nomogram of uveal melanoma as prediction model of metastasis risk

BACKGROUND: 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: Two datasets of UVM (GSE84976, GSE22138...

Descripción completa

Detalles Bibliográficos
Autores principales: Wang, Yimin, Xie, Minyue, Lin, Feng, Sheng, Xiaonan, Zhao, Xiaohuan, Zhu, Xinyue, Wang, Yuwei, Lu, Bing, Chen, Jieqiong, Zhang, Ting, Wan, Xiaoling, Liu, Wenjia, Sun, Xiaodong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10440531/
https://www.ncbi.nlm.nih.gov/pubmed/37609406
http://dx.doi.org/10.1016/j.heliyon.2023.e18956
_version_ 1785093175482777600
author Wang, Yimin
Xie, Minyue
Lin, Feng
Sheng, Xiaonan
Zhao, Xiaohuan
Zhu, Xinyue
Wang, Yuwei
Lu, Bing
Chen, Jieqiong
Zhang, Ting
Wan, Xiaoling
Liu, Wenjia
Sun, Xiaodong
author_facet Wang, Yimin
Xie, Minyue
Lin, Feng
Sheng, Xiaonan
Zhao, Xiaohuan
Zhu, Xinyue
Wang, Yuwei
Lu, Bing
Chen, Jieqiong
Zhang, Ting
Wan, Xiaoling
Liu, Wenjia
Sun, Xiaodong
author_sort Wang, Yimin
collection PubMed
description BACKGROUND: 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: Two datasets of UVM (GSE84976, GSE22138) were selected. Data was analyzed by R language, CTD database and GEPIA. RESULTS: 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: 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.
format Online
Article
Text
id pubmed-10440531
institution National Center for Biotechnology Information
language English
publishDate 2023
publisher Elsevier
record_format MEDLINE/PubMed
spelling pubmed-104405312023-08-22 Nomogram of uveal melanoma as prediction model of metastasis risk Wang, Yimin Xie, Minyue Lin, Feng Sheng, Xiaonan Zhao, Xiaohuan Zhu, Xinyue Wang, Yuwei Lu, Bing Chen, Jieqiong Zhang, Ting Wan, Xiaoling Liu, Wenjia Sun, Xiaodong Heliyon Research Article BACKGROUND: 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: Two datasets of UVM (GSE84976, GSE22138) were selected. Data was analyzed by R language, CTD database and GEPIA. RESULTS: 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: 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. Elsevier 2023-08-06 /pmc/articles/PMC10440531/ /pubmed/37609406 http://dx.doi.org/10.1016/j.heliyon.2023.e18956 Text en © 2023 Published by Elsevier Ltd. https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
spellingShingle Research Article
Wang, Yimin
Xie, Minyue
Lin, Feng
Sheng, Xiaonan
Zhao, Xiaohuan
Zhu, Xinyue
Wang, Yuwei
Lu, Bing
Chen, Jieqiong
Zhang, Ting
Wan, Xiaoling
Liu, Wenjia
Sun, Xiaodong
Nomogram of uveal melanoma as prediction model of metastasis risk
title Nomogram of uveal melanoma as prediction model of metastasis risk
title_full Nomogram of uveal melanoma as prediction model of metastasis risk
title_fullStr Nomogram of uveal melanoma as prediction model of metastasis risk
title_full_unstemmed Nomogram of uveal melanoma as prediction model of metastasis risk
title_short Nomogram of uveal melanoma as prediction model of metastasis risk
title_sort nomogram of uveal melanoma as prediction model of metastasis risk
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10440531/
https://www.ncbi.nlm.nih.gov/pubmed/37609406
http://dx.doi.org/10.1016/j.heliyon.2023.e18956
work_keys_str_mv AT wangyimin nomogramofuvealmelanomaaspredictionmodelofmetastasisrisk
AT xieminyue nomogramofuvealmelanomaaspredictionmodelofmetastasisrisk
AT linfeng nomogramofuvealmelanomaaspredictionmodelofmetastasisrisk
AT shengxiaonan nomogramofuvealmelanomaaspredictionmodelofmetastasisrisk
AT zhaoxiaohuan nomogramofuvealmelanomaaspredictionmodelofmetastasisrisk
AT zhuxinyue nomogramofuvealmelanomaaspredictionmodelofmetastasisrisk
AT wangyuwei nomogramofuvealmelanomaaspredictionmodelofmetastasisrisk
AT lubing nomogramofuvealmelanomaaspredictionmodelofmetastasisrisk
AT chenjieqiong nomogramofuvealmelanomaaspredictionmodelofmetastasisrisk
AT zhangting nomogramofuvealmelanomaaspredictionmodelofmetastasisrisk
AT wanxiaoling nomogramofuvealmelanomaaspredictionmodelofmetastasisrisk
AT liuwenjia nomogramofuvealmelanomaaspredictionmodelofmetastasisrisk
AT sunxiaodong nomogramofuvealmelanomaaspredictionmodelofmetastasisrisk