Identification of autophagy-related risk signatures for the prognosis, diagnosis, and targeted therapy in cervical cancer.
Cancer Cell Int 2021;
21:362. [PMID:
34238288 PMCID:
PMC8268251 DOI:
10.1186/s12935-021-02073-w]
[Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/22/2021] [Accepted: 07/02/2021] [Indexed: 12/24/2022] Open
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.
Supplementary Information
The online version contains supplementary material available at 10.1186/s12935-021-02073-w.
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