ArticleOncology letters2020
Chemoresistance-associated alternative splicing signatures in serous ovarian cancer.
Article in Oncology letters, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers, 1 of them a synthesis that pooled it.
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Who cites it
8 citing papers in PubMed, 1 synthesis or guideline pooled it, 13 citations in OpenAlex.
- Predictive Value of Machine Learning for Platinum Chemotherapy Responses in Ovarian Cancer: Systematic Review and Meta-Analysis.Journal of medical Internet research · 2024Pooled it
- Alternative splicing in ovarian cancer.Cell communication and signaling : CCS · 2024Review
- Cisplatin-induced PANDAR-Chemo-EVs contribute to a more aggressive and chemoresistant ovarian cancer phenotype through the SRSF9-SIRT4/SIRT6 axis.Journal of gynecologic oncology · 2024Article
- Multi-omics analysis of the Indian ovarian cancer cohort revealed histotype-specific mutation and gene expression patterns.Frontiers in genetics · 2023Article
- Comprehensive characterization of the alternative splicing landscape in ovarian cancer reveals novel events associated with tumor-immune microenvironment.Bioscience reports · 2022Article
- Clinical significance of metabolism-related genes and FAK activity in ovarian high-grade serous carcinoma.BMC cancer · 2022Article
- Identification of Phospho-Tyrosine Targets as a Strategy for the Treatment of Esophageal Adenocarcinoma Cells.OncoTargets and therapy · 2021Article
- Prognostic Signatures of Alternative Splicing Events in Esophageal Carcinoma Based on TCGA Splice-Seq Data.Frontiers in oncology · 2021Article
Corrections and comments
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Authors and funding
2 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Primary platinum-based chemoresistance occurs in ~30% of patients with serous ovarian cancer. Chemoresistance is the main cause of disease recurrence, and accurate predictors to identify these patients with chemoresistance are required. Alternative splicing (AS) is a post-transcriptional modification process that is altered in cancer. A possible association between AS and chemoresistance is unclear and needs to be studied comprehensively in ovarian cancer. In the present study, RNA-sequencing data and clinical information for 320 patients with ovarian serous cystadenocarcinoma (OV) were downloaded from The Cancer Genome Atlas (TCGA) database. Splicing events were determined using the TCGA SpliceSeq tool. Seven types of AS events were identified. Univariate and multivariate logistic analyses were performed, and predictive models for OV chemoresistance were established, as well as a splicing network. A total of 22,036 AS events were identified in 7,404 genes, with 915 AS events detected in 677 genes that were significantly associated with chemoresistance in patients with OV. A receiver operating characteristic (ROC) curve was constructed for resistance predictive models composed of the most significant AS events. The area under the ROC curve was 0.931, indicating strong and efficient prediction of chemoresistance. Additionally, the high-risk score was associated with shorter overall survival. The splicing correlation network suggested a potential role of splicing factors in chemoresistance. In summary, the present study created a powerful predictor for primary platinum-based chemoresistance in patients with OV, identified splicing networks that could be involved in potential mechanisms of chemoresistance and provided potential targets to overcome chemoresistance.
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