A novel strategy to identify candidate diagnostic and prognostic biomarkers for gastric cancer.

ABSTRACT:

Background

Gastric cancer (GC) is one of the most common cancer worldwide. It is essential to identify non-invasive diagnostic and prognostic biomarkers of GC. The aim of the present study was to screen candidate biomarkers associated with the pathogenesis and prognosis of GC by a novel strategy.

Methods

The expression level of gene higher in cancer than in adjacent non-cancer tissue was defined as "positive", and the top 5% genes with "positive rate" were filtered out as candidate diagnostic biomarkers in three Gene Expression Omnibus (GEO) datasets. Further, a prognostic risk model was constructed by multivariate Cox regression analysis in GEO dataset and validated in The Cancer Genome Atlas (TCGA). The expression level of candidate biomarkers was determined in serum and s

SUBMITTER: Liu L 

PROVIDER: S-EPMC8254335 | biostudies-literature | 2021 Jul

REPOSITORIES: biostudies-literature