AI Article Synopsis
- The study aimed to identify autophagy-related biomarkers that can be used for prognosis, diagnosis, and treatment in cervical cancer.
- Utilizing RNA sequencing and clinical data from large databases, Cox regression analysis was applied to find significant survival signatures.
- The research identified several specific biomarkers associated with overall survival and recurrence-free survival, suggesting they could assist in personalizing treatment for cervical cancer patients.
Article Abstract
Background: To rummage autophagy-related prognostic, diagnostic, and therapeutic biomarkers in cervical cancer (CC).
Methods: The RNA-sequence and clinical information were from the TCGA and GTEx databases. We operated Cox regression to determine signatures related to overall survival (OS) and recurrence-free survival (RFS) respectively. The diagnostic and therapeutic effectiveness of prognostic biomarkers were further explored.
Results: We identified nine (VAMP7, MTMR14, ATG4D, KLHL24, TP73, NAMPT, CD46, HGS, ATG4C) and three risk signatures (SERPINA1, HSPB8, SUPT20H) with prognostic values for OS and RFS respectively. Six risk signatures (ATG4C, ATG4D, CD46, TP73, SERPINA1, HSPB8) were selected for qPCR. We screened five prognostic signatures(ATG4C, CD46, HSPB8, MTMR14, NAMPT) with diagnostic function through the GEO database. Correlation between our models and treatment targets certificated the prognostic score provided a reference for precision medicine.
Conclusions: We constructed OS and RFS prognostic models in CC. Autophagy-related risk signatures might serve as diagnostic and therapeutic biomarkers.
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|---|---|
| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8268251 | PMC |
| http://dx.doi.org/10.1186/s12935-021-02073-w | DOI Listing |
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