Identification of a novel nine-SnoRNA signature with potential prognostic and therapeutic value in ovarian cancer.

ABSTRACT:

Background

Increasing evidence has been confirmed that small nucleolar RNAs (SnoRNAs) play critical roles in tumorigenesis and exhibit prognostic value in clinical practice. However, there is short of systematic research on SnoRNAs in ovarian cancer (OV).

Material/methods

379 OV patients with RNA-Seq and clinical parameters from TCGA database and 5 paired clinical OV tissues were embedded in our study. Cox regression analysis was used to identify prognostic SnoRNAs and construct prediction model. SNORic database was adopted to examine the copy number variation of SnoRNAs. ROC curves and KM plot curves were applied to validate the prognostic model. Besides, the model was validated in 5 paired clinical tissues by real-time PCR, H&E staining and immunohistochemistry.

Results

SUBMITTER: Zhu W 

PROVIDER: S-EPMC9119353 | biostudies-literature | 2022 May

REPOSITORIES: biostudies-literature