Literature DB >> 31347734

Integrative prognostic subtype discovery in high-grade serous ovarian cancer.

Hongyu Xie1, Huan Xu1, Yan Hou1, Yuqing Cai1, Zhiwei Rong1, Wei Song1, Wenjie Wang1, Kang Li1.   

Abstract

OBJECTIVE: We sought to identify novel molecular subtypes of high-grade serous ovarian cancer (HGSC) by the integration of gene expression and proteomics data and to find the underlying biological characteristics of ovarian cancer to improve the clinical outcome.
METHODS: The iCluster method was utilized to analysis 131 common HGSC samples between TCGA and Clinical Proteomic Tumor Analysis Consortium databases. Kaplan-Meier survival curves were used to estimate the overall survival of patients, and the differences in survival curves were assessed using the log-rank test.
RESULTS: Two novel ovarian cancer subtypes with different overall survival (P = .00114) and different platinum status (P = .0061) were identified. Eighteen messenger RNAs and 38 proteins were selected as differential molecules between subtypes. Pathway analysis demonstrated arrhythmogenic right ventricular cardiomyopathy pathway played a critical role in the discrimination of these two subtypes and desmosomal cadherin DSG2, DSP, JUP, and PKP2 in this pathway were overexpression in subtype I compared with subtype II.
CONCLUSION: Our study extended the underlying prognosis-related biological characteristics of high-grade serous ovarian cancer. Enrichment of desmosomal cadherin increased the risk for HGSC prognosis among platinum-sensitive patients, the results guided the revision of the treatment options for platinum-sensitive ovarian cancer patients to improve outcomes.
© 2019 Wiley Periodicals, Inc.

Entities:  

Keywords:  high-grade serous ovarian cancer; integration; platinum sensitive; prognosis; subtypes

Year:  2019        PMID: 31347734     DOI: 10.1002/jcb.29049

Source DB:  PubMed          Journal:  J Cell Biochem        ISSN: 0730-2312            Impact factor:   4.429


  6 in total

1.  Deep learning-based ovarian cancer subtypes identification using multi-omics data.

Authors:  Long-Yi Guo; Ai-Hua Wu; Yong-Xia Wang; Li-Ping Zhang; Hua Chai; Xue-Fang Liang
Journal:  BioData Min       Date:  2020-08-24       Impact factor: 2.522

2.  Combined PD-1/PD-L1 and tumor-infiltrating immune cells redefined a unique molecular subtype of high-grade serous ovarian carcinoma.

Authors:  Ping Liu; Ruoxu Chen; Xudong Zhang; Ruiting Fu; Lin Tao; Wei Jia
Journal:  BMC Genomics       Date:  2022-01-13       Impact factor: 3.969

3.  Nonnegative matrix factorization-based bioinformatics analysis reveals that TPX2 and SELENBP1 are two predictors of the inner sub-consensuses of lung adenocarcinoma.

Authors:  Haiwei Wang; Xinrui Wang; Liangpu Xu; Hua Cao; Ji Zhang
Journal:  Cancer Med       Date:  2021-11-03       Impact factor: 4.452

4.  KAZN as a diagnostic marker in ovarian cancer: a comprehensive analysis based on microarray, mRNA-sequencing, and methylation data.

Authors:  Songling Zhu; Hongxia Bao; Meng-Chun Zhang; Huidi Liu; Yao Wang; Caiji Lin; Xingjuan Zhao; Shu-Lin Liu
Journal:  BMC Cancer       Date:  2022-06-16       Impact factor: 4.638

5.  Machine learning analysis of TCGA cancer data.

Authors:  Jose Liñares-Blanco; Alejandro Pazos; Carlos Fernandez-Lozano
Journal:  PeerJ Comput Sci       Date:  2021-07-12

6.  Desmoglein-2 as a prognostic and biomarker in ovarian cancer.

Authors:  Jiho Kim; Peter Beidler; Hongjie Wang; Chang Li; Abdullah Quassab; Cari Coles; Charles Drescher; Darrick Carter; André Lieber
Journal:  Cancer Biol Ther       Date:  2020-11-20       Impact factor: 4.742

  6 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.