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Table 1 Bioinformatics-based data mining method for the identification of potential ovarian cancer biomarkers

From: Kallikrein family proteases KLK6 and KLK7 are potential early detection and diagnostic biomarkers for serous and papillary serous ovarian cancer subtypes

Potential biomarkers for ovarian cancer
ATP7B CA125 CLEC3B KLK6 TOP2A ARID4B CEA ID2 IGFBP2 INHA
PDGFA HE4 DUSP1 BSG CLDN3 REEP5 MIF IGF2BP1 LGALS3BP CDC25C
BRCA2 CA72-4 IL13RA2 STAT3 CLDN4 CCT3 AFP IQGAP1 MSLN NME1
DNAJC15 BARD 1 PLK1 RAET1E COPS5 CD47 Prolactin RHOC ST14 AKT2
KLK14 BCL2 VIL2 TITF1 CSF1 ETV4 MUC 1 RNASE2 AMH ANGPT2
KLK9 IGFII APOD TFF1 EFNB1 MAGEA4 AMH SYCP1 CDC25A XIST
WFDC2 BAG1 CD247 SPINK1 KLK11 SCGB2A1 WT 1 TRIM25 CSF1R KLK10
ERCC1 BAG3 CDC25B PRSS8 KLK13 SIX5 OGP P11 GADD45A KLK15
KLK8 BAG 4 DAB2 CCNE1 MVP ZNF217 CDX2 CYP2A HLA-G KLK5
RBL2 Osteopontn HMGA1 CEACAM6 PARP1 EYA2 SMRP PTK2 JUP KLK7
SKP2 Maspin HOXB7 ETS1 VEGFC ELF1 Bcl-XL TACC3 MLANA SOD2
IGFBP5 MSN BCHE EPHA2 ASNS MUC5AC TNFRSF1B    
  1. BioXM software was used to mine the Cancer Gene Index (CGI) to identify genes that are differentially regulated in OVC. This bioinformatics-guided approach identified 117 genes that are supported by experimental evidence in the published literature. Genes are categorized based on signaling pathways and 12 genes showing robust differential expression in the majority of the 21 OVC cell lines versus normal ovarian cell lines (all with p <0.05) are highlighted in bold text.