Literature DB >> 31646691

OSuvm: An interactive online consensus survival tool for uveal melanoma prognosis analysis.

Fengling Wang1, Qiang Wang1, Ning Li1, Linna Ge1, Mengsi Yang1, Yang An1, Guosen Zhang1, Huan Dong1, Shaoping Ji1, Wan Zhu2, Xiangqian Guo1.   

Abstract

Uveal melanoma (UM) is a rare, aggressive, but the most frequent primary intraocular malignancy in adults, and up to 50% of patients develop a tendency of liver metastases. Great efforts have been made to develop biomarkers that facilitate diagnosis, prediction of the risk, and response to treatment of UM. However, a biologically informative and highly accurate gold standard system for prognostic evaluation of UM remains to be established. To facilitate assessment of the prognosis of UM patients, we established a user-friendly Online consensus Survival tool for uveal melanoma, named OSuvm, by which users can easily estimate the prognostic values of genes of interest by the Kaplan-Meier survival plot with hazard ratio and log-rank test. OSuvm comprises four independent cohorts including 229 patients with both gene expression profiles and relevant clinical follow-up information, and it has shown great performance in evaluating the prognostic roles of previously reported biomarkers. Using OSuvm enables researchers and clinicians to rapidly and conveniently explore the prognostic value of genes of interest and develop new potential molecular biomarkers for UM. OSuvm can be accessed at http://bioinfo.henu.edu.cn/UVM/UVMList.jsp.
© 2019 Wiley Periodicals, Inc.

Entities:  

Keywords:  OSuvm; online survival tool; prognostic biomarker; uveal melanoma

Mesh:

Substances:

Year:  2019        PMID: 31646691     DOI: 10.1002/mc.23128

Source DB:  PubMed          Journal:  Mol Carcinog        ISSN: 0899-1987            Impact factor:   4.784


  8 in total

1.  OSluca: An Interactive Web Server to Evaluate Prognostic Biomarkers for Lung Cancer.

Authors:  Zhongyi Yan; Qiang Wang; Zhendong Lu; Xiaoxiao Sun; Pengfei Song; Yifang Dang; Longxiang Xie; Lu Zhang; Yongqiang Li; Wan Zhu; Tiantian Xie; Jing Ma; Yijie Zhang; Xiangqian Guo
Journal:  Front Genet       Date:  2020-05-26       Impact factor: 4.599

2.  Expression of tripartite motif-containing 44 and its prognostic and clinicopathological value in human malignancies:a meta-analysis.

Authors:  Guoliang Xiao; Qiuxi Yang; Ziwei Bao; Haixia Mao; Yi Zhang; Shibu Lin
Journal:  BMC Cancer       Date:  2020-06-05       Impact factor: 4.430

3.  Survival Genie, a web platform for survival analysis across pediatric and adult cancers.

Authors:  Bhakti Dwivedi; Hope Mumme; Sarthak Satpathy; Swati S Bhasin; Manoj Bhasin
Journal:  Sci Rep       Date:  2022-02-23       Impact factor: 4.379

4.  Proteomics analysis: inhibiting the expression of P62 protein by chloroquine combined with dacarbazine can reduce the malignant progression of uveal melanoma.

Authors:  Xifeng Fei; Xiangtong Xie; Ruwei Qin; Anqi Wang; Xuan Meng; Fei Sun; Yifan Zhao; Dongyi Jiang; Hanchun Chen; Qiang Huang; Xiaoyan Ji; Zhimin Wang
Journal:  BMC Cancer       Date:  2022-04-14       Impact factor: 4.430

5.  High APLN Expression Predicts Poor Prognosis for Glioma Patients.

Authors:  Shuangyu Lv; Yang An; Huan Dong; Longxiang Xie; Hong Zheng; Xiaoxia Cheng; Lei Zhang; Tieshan Teng; Qiang Wang; Zhongyi Yan; Xiangqian Guo
Journal:  Oxid Med Cell Longev       Date:  2022-09-22       Impact factor: 7.310

Review 6.  The Application of Deep Learning in Cancer Prognosis Prediction.

Authors:  Wan Zhu; Longxiang Xie; Jianye Han; Xiangqian Guo
Journal:  Cancers (Basel)       Date:  2020-03-05       Impact factor: 6.639

7.  OSskcm: an online survival analysis webserver for skin cutaneous melanoma based on 1085 transcriptomic profiles.

Authors:  Lu Zhang; Qiang Wang; Lijie Wang; Longxiang Xie; Yang An; Guosen Zhang; Wan Zhu; Yongqiang Li; Zhihui Liu; Xiaochen Zhang; Panpan Tang; Xiaozheng Huo; Xiangqian Guo
Journal:  Cancer Cell Int       Date:  2020-05-19       Impact factor: 5.722

8.  OSucs: An Online Prognostic Biomarker Analysis Tool for Uterine Carcinosarcoma.

Authors:  Yang An; Qiang Wang; Fengjie Sun; Guosen Zhang; Fengling Wang; Lu Zhang; Yanan Li; Weinan Ren; Wan Zhu; Yongqiang Li; Shaoping Ji; Xiangqian Guo
Journal:  Genes (Basel)       Date:  2020-09-03       Impact factor: 4.096

  8 in total

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