Golgi-apparatus genes related signature for predicting the progression-free interval of patients with papillary thyroid carcinoma.

ABSTRACT:

Background

We aimed to build a novel model with golgi apparatus related genes (GaGs) signature and relevant clinical parameters for predicting progression-free interval (PFI) after surgery for papillary thyroid carcinoma (PTC).

Methods

We performed a bioinformatic analysis of integrated PTC datasets with the GaGs to identify differentially expressed GaGs (DE-GaGs). Then we generated PFI-related DE-GaGs and established a novel GaGs based signature. After that, we validated the signature on multiple external datasets and PTC cell lines. Further, we conducted uni- and multivariate analyses to identify independent prognostic characters. Finally, we established a signature and clinical parameters-based nomogram for predicting the PFI of PTC.

Results

We identified 260 DE-Ga

SUBMITTER: Liu R 

PROVIDER: S-EPMC10041766 | biostudies-literature | 2023 Mar

REPOSITORIES: biostudies-literature