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Updated: Feb 3, 2026

Microarray-based Identification of Individual HERV Loci Expression: Application to Biomarker Discovery in Prostate Cancer
Published on: November 2, 2013
Microarray-based identification of genes associated with prognosis and drug resistance in ovarian cancer
Fuqiang Yin1,2, Shang Yi3, Luwei Wei4
1Life Sciences Institute, Guangxi Medical University, Nanning, Guangxi, China.
Abstract:
The outcome for patients with ovarian cancer (OC) is poor because of drug resistance. Therefore, identification of factors that affect drug resistance and prognosis in OC is needed. In the present study, we identified 131 genes significantly dysregulated in 90 platinum-resistant OC tissues compared with 197 sensitive tissues, of which 30 were significantly associated with disease-free survival (DFS; n = 16), overall survival (OS; n = 6), or both (n = 8) in 489 OC patients of the The Cancer Genome Atlas cohort. Of these 30 genes, 17 were significantly upregulated and 13 were downregulated in the 90 resistant tissues, and with one exception, all of the up-/downregulated genes in resistant tissues were predictors of shorter DFS or/and OS. LAX1, MECOM, and PDIA4 were independent risk factors for DFS, and KLF1, SLC7A11, and PDIA4 for OS; combining these genes provided more accurate predictions for DFS and OS than any of the genes used individually. We further verified downregulation of PDIA4 protein in 51 specimens of patients with OC (24 drug resistant's and 27 sensitive's), which confirmed that downregulated PDIA4 predicted DFS and OS. PDIA4 also consistently predicted OS in a larger sample of 1656 patients with OC. These 30 genes, particularly the PDIA4, could be therapeutic targets or biomarkers for managing OC.
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