ArticleJournal of ovarian research2021
Construction autophagy-related prognostic risk signature to facilitate survival prediction, individual treatment and biomarker excavation of epithelial ovarian cancer patients.
Article in Journal of ovarian research, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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Who cites it
10 citing papers in PubMed, 24 citations in OpenAlex.
- Novel protein-based prognostic signature linked to immunotherapeutic efficiency in ovarian cancer.Journal of ovarian research · 2024Article
- Novel immune-related gene signature for risk stratification and prognosis prediction in ovarian cancer.Journal of ovarian research · 2023Article
- Role of autophagy and its regulation by noncoding RNAs in ovarian cancer.Experimental biology and medicine (Maywood, N.J.) · 2023Review
- A novel autophagy-related gene signature associated with prognosis and immune microenvironment in ovarian cancer.Journal of ovarian research · 2023Article
- A novel defined risk signature of endoplasmic reticulum stress-related genes for predicting the prognosis and immune infiltration status of ovarian cancer.Journal of Zhejiang University. Science. B · 2023Article
- Maggot Extract Inhibits Cell Migration and Tumor Growth by Targeting HSP90AB1 in Ovarian Cancer.Journal of clinical medicine · 2022Article
- Protein expression profiling identifies a prognostic model for ovarian cancer.BMC women's health · 2022Article
- Long non-coding RNA HOXA11-AS knockout inhibits proliferation and overcomes drug resistance in ovarian cancer.Bioengineered · 2022Article
- Integrated clinical characteristics and omics analysis identifies a ferroptosis and iron-metabolism-related lncRNA signature for predicting prognosis and therapeutic responses in ovarian cancer.Journal of ovarian research · 2022Article
- A Novel Autophagy-Related Prognostic Risk Model and a Nomogram for Survival Prediction of Oral Cancer Patients.BioMed research international · 2022Article
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Authors and funding
3 authors at 3 institutions in 1 country.
Funding
Abstract
backgroundExisting clinical methods for prognosis evaluating for Epithelial Ovarian Cancer (EOC) patients had defects of invasive, unsystematic and subjective and little data are available for individualizing treatment, therefore, to identify potential prognostic markers and new therapeutic targets for EOC is urgently required.
resultsExpression of 232 autophagy-related genes (ARGs) in 354 EOC and 56 human ovarian surface epithelial specimens from 7 independent laboratories were analyzed, 31 mRNAs were identified as DEARGs. We did functional and pathway enrichment analysis and constructed protein-protein interaction network for all DEARGs. To screen out candidate DEARGs related to EOC patients' survival and construct an autophagy-related prognostic risk signature, univariate and multivariate Cox proportional hazards models were established separately. Finally, 5 optimal independent prognostic DEARGs (PEX3, DNAJB9, RB1, HSP90AB1 and CXCR4) were confirmed and the autophagy-related risk model was established by the 5 prognostic DEARGs. The accuracy and robustness of the prognostic risk model for survival prediction were evaluated and verified by analyzing the correlation between EOC patients' survival status, clinicopathological features and risk scores.
conclusionsThe autophagy-related prognostic risk model can be independently used to predict overall survival in EOC patients, it can also potentially assist in individualizing treatment and biomarker development.
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