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. Author manuscript; available in PMC: 2017 May 1.
Published in final edited form as: Gynecol Oncol. 2016 Mar 11;141(2):348–356. doi: 10.1016/j.ygyno.2016.02.030

Table 1. Dominant and dormant driver NR genes from TCGA dataset.

Gene expression of those NRs included in the TCGA analysis on high-grade serous ovarian cancers was analyzed using a “tight clustering” algorithm (see methods section) and identified five patient clusters based on differential gene expression. Driver genes of each cluster were investigated with the gene-dominant and gene-dormant index method (21). This method extends the signal to noise ratio to identify features as either dominant or dormant in a specific cluster compared to the other clusters. The associated table identifies those genes included in the analysis and whether the gene of interest is considered dominant or dormant for each of the 5 clusters. Statistically significant drivers are highlighted.

Nuclear Receptor Cluster (Dominant) p-value Cluster (Dormant) p-value
AR 5 0.1917 1 0.1431
ESR1 4 0.1938 1 0.7332
ESRRA 3 0.5610 2 0.0001
HNF4A 3 <0.0001 5 0.1358
NR1D2 5 <0.0001 3 0.0119
NR1H2 3 0.0220 1 0.1246
NR1H3 4 0.0488 2 0.7286
NR2C1 2 0.0004 3 0.0766
NR2C2 4 0.0801 1 0.5953
NR2E3 3 0.0189 5 0.0006
NR2F1 2 0.2902 4 0.0338
NR2F2 2 0.0021 4 0.4752
NR2F6 2 0.3093 4 0.6245
NR3C1 4 0.1591 2 <0.0001
NR3C2 4 <0.0001 2 0.0002
NR4A1 1 <0.0001 4 0.1686
NR4A2 1 <0.0001 2 0.2969
NR4A3 1 <0.0001 5 0.5827
NR5A1 3 0.0077 5 0.0416
NR6A1 3 0.0128 1 0.1253
PGR 2 <0.0001 5 0.0495
PPARA 4 0.0071 2 0.0003
PPARD 3 0.0011 5 0.1183
RARA 3 <0.0001 4 0.2198
RARB 1 <0.0001 2 0.7096
RARG 5 0.0002 2 0.0292
RORA 1 0.8749 5 0.1937
RORC 4 0.3249 1 0.2564
RXRA 3 0.1722 2 0.0316
RXRB 2 0.5655 1 <0.0001
THRA 2 0.7246 4 0.8499
THRB 4 0.0181 2 0.0245
VDR 1 0.0619 2 0.0076
GPER 3 0.0012 1 0.8310
PGRMC1 2 0.0027 4 0.0119
PGRMC2 4 0.8194 3 0.0078