ArticleFrontiers in genetics2022
Deciphering the expression patterns of homologous recombination-related lncRNAs identifies new molecular subtypes and emerging therapeutic opportunities in epithelial ovarian cancer.
Article in Frontiers in genetics, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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2 citing papers in PubMed, 5 citations in OpenAlex.
- Senescence-Related LncRNAs: Pioneering Indicators for Ovarian Cancer Outcomes.Phenomics (Cham, Switzerland) · 2024Review
- Identification of a DNA damage repair-related LncRNA signature for predicting the prognosis and immunotherapy response of hepatocellular carcinoma.BMC genomics · 2024Article
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5 authors at 3 institutions in 1 country.
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Abstract
Epithelial ovarian cancer (EOC) is the leading killer among women with gynecologic malignancies. Homologous recombination deficiency (HRD) has attracted increasing attention due to its significant implication in the prediction of prognosis and response to treatments. In addition to the germline and somatic mutations of homologous recombination (HR) repair genes, to widely and deeply understand the molecular characteristics of HRD, we sought to screen the long non-coding RNAs (lncRNAs) with regard to HR repair genes and to establish a prognostic risk model for EOC. Herein, we retrieved the transcriptome data from the Genotype-Tissue Expression Project (GTEx) and The Cancer Genome Atlas (TCGA) databases. HR-related lncRNAs (HRRlncRNAs) associated with prognosis were identified by co-expression and univariate Cox regression analyses. The least absolute shrinkage and selection operator (LASSO) and multivariate stepwise Cox regression were performed to construct an HRRlncRNA risk model containing AC138904.1, AP001001.1, AL603832.1, AC138932.1, and AC040169.1. Next, Kaplan-Meier analysis, time-dependent receiver operating characteristics (ROC), nomogram, calibration, and DCA curves were made to verify and evaluate the model. Gene set enrichment analysis (GSEA), immune analysis, and prediction of the half-maximal inhibitory concentration (IC
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