Gene Expression Changes Induced by PPAR Gamma Agonists in Animal and Human Liver

Table 2

Modulation of gene expression in human liver cell models after treatment with PPAR𝛾 agonists.

	Ref.	[34]	[35]	[65]	Rogue et al. unpublished															[74]	[75]	[76]	[77]	[78]	[79]	[80]	[81]
	model	PHH			PHH DONOR 1		PHH DONOR 2		PHH DONOR 3		PHH DONOR 4			PHH DONOR 5			HepaRG cells			HepaRG cells	Hep3b Huh7	Huh7	Hepg2			HLF	HLF, HAK, HuH-7
	treatment	TRO 24 h 5,50,100; 𝜇M-	TRO 24 h 25 𝜇M-	TRO 24 h 10 𝜇M-	TRO 24 h 5 𝜇M-	TRO 24 h 20 𝜇M-	TRO 24 h 5 𝜇M-	TRO 24 h 20 𝜇M-	TRO 24 h 5 𝜇M-	TRO 24 h 20 𝜇M-	TRO 24 h 5 𝜇M-	TRO 24 h 20 𝜇M-	TRO 24 h 40 𝜇M-	TRO 24 h 5 𝜇M-	TRO 24 h 20 𝜇M-	TRO 24 h 40 𝜇M-	TRO 24 h 5 𝜇M-	TRO 24 h 20 𝜇M-	TRO 24 h 40 𝜇M-	TRO 24 h 0,024 𝜇M–25 𝜇M	TRO04; 8 h -; 50 𝜇M-	TRO-ROSI 1–8–; 24 h 50 𝜇M-	TRO 6 h 30 𝜇M-	TRO-4 h 10–30 𝜇 M	TRO-ROSI 48 h 25–100 𝜇M-	TRO for up 48  h 50 𝜇M	TRO 24 h 50 𝜇M
	method	q-PCR		Amer-sham	Agilent												Agilent			q-PCR		Super Array Bioscience qPCR	q-PCR/ northern blotting	q-PCR
	ABCB1	+			0	+	0	0	+	+	0	0	+	+	+	+	0	0	0
Transporters	ABCC2	+			0	0	0	0	0	0	0	0	0	0	0	+	0	0	0
	ABCC3	+			+	0	0	0	0	0	0	0	0	0	0	0	0	0	0
	SLC10A1	−			0	0	0	0	0	0	0	0	0	0	0	−	−	−	−
	ABCB4	+			0	0	0	0	+	+	0	+	+	+	+	+	0	0	0
	SLCO1B1	0			0	0	0	0	0	0	0	0	0	0	0	0	0	0	−
	SLCO1B3	−			−	−	−	−	−	−	0	−	−	0	−	−	0	0	0
	CCND1	+			0	+	+	+	0	+	0	0	0	0	0	0	0	0	0
Cell cycle, proliferation, death and differentiation	CDKN1A	0			0	0	+	+	+	+	0	0	0	0	0	0	0	0	0							+	+
	GADD45G	+			0	+	0	0	0	+	0	0	0	+	+	+	0	0	0
	AFP	−			0	−	0	−	0	0	0	−	−	0	0	0	0	0	0
	TGFA	+			0	0	0	−	−	−	0	0	0	0	0	0	0	0	0
	CCNE1				0	0	0	0	0	0	0	0	0	0	0	0	0	0	+							0	0
	ALB	0			0	0	0	0	0	0	0	0	0	0	0	0	0	0	−
	CDKN1B				0	0	0	0	0	0	0	0	0	0	0	0	0	0	0							0	0
	JUND	0			0	0	0	0	0	0	0	0	0	0	0	0	0	0	0
	CCNG1	0			0	0	−	−	0	−	0	0	0	0	0	0	0	0	0
	MYC	0			0	0	0	0	0	0	0	0	0	0	0	0	0	0	0
	TGFB1	0			0	0	+	+	0	+	0	0	0	0	0	0	0	0	0
	ALPL	0			0	0	0	0	0	0	0	0	+	0	0	0	0	0	−
	GADD45A	+			0	0	0	0	0	0	0	0	0	0	0	0	0	0	0
	IGFBP1				0	0	0	−	−	−	0	0	0	0	+	0	0	0	+						+
	SKP2				0	0	0	0	0	0	0	0	0	0	0	0	0	0	+							−
	FABP1	+			+	+	+	+	+	+	0	+	+	+	+	+	+	0	−
Lipid metabolism	FASN	+			0	0	0	0	0	0	0	0	0	+	+	0	0	0	0
	CPT1A	+			0	+	+	+	0	0	0	+	+	+	+	+	0	0	0
	SREBF2				+	0	0	+	0	0	0	0	0	0	0	0	0	0	0					−
	HMGCR				0	0	0	0	0	0	0	0	0	0	0	0	0	0	−					−
	INSIG1				0	0	0	0	0	0	0	0	0	+	+	+	0	0	0					nd
	LDLR				0	0	0	0	0	0	0	0	0	0	0	0	0	0	0					−
	INSIG2				0	0	0	0	0	−	0	0	0	0	0	0	0	0	0					+
	CYP1A1		0		+	+	0	0	0	+	0	0	0	0	0	0	0	−	0	0
Xenobiotic metabolism	CYP1A2	+	0		0	0	−	0	0	0	0	0	+	0	0	+	0	0	0	0
	CYP2B6			+	+	+	0	0	+	+	0	+	+	0	0	+	0	0	0	+
	CYP2C9	+			0	0	0	0	0	0	0	0	+	+	+	+	+	0	0
	CYP2E1	+			0	0	−	−	−	−	0	0	0	0	0	0	0	0	−
	CYP3A4	+	+		0	0	0	0	+	+	0	+	+	+	+	+	+	+	+	+
	UGT1A10	+			0	0	0	0	0	0	0	0	0	0	0	0	0	0	0
	GSTP1	+			0	0	0	0	−	−	0	0	0	0	0	0	0	0	0
	GSTA1	0			0	0	0	0	0	0	0	0	0	0	0	0	0	0	−
	G6PC				0	0	0	0	−	−	0	0	0	0	0	0	0	−	−
Carbohydrate metabolism	PDK4				−	0	−	−	−	−	0	+	+	+	+	+	0	+	+
	PEPCK				0	0	0	0	−	−	0	0	0	0	0	+	+	+	+
	FBP1	0			0	0	0	0	0	0	0	0	0	0	0	0	0	0	−
	HMOX1	+			+	+	+	+	+	+	+	+	+	0	0	0	0	+	+
Oxidative stres	PTGS2				0	0	0	0	0	0	0	0	0	0	0	0	0	0	0		−		−
	HSPA1A	+			+	+	0	0	+	+	0	0	0	0	0	0	0	0	0
	TXN	+			0	0	0	0	0	0	0	0	0	0	0	0	0	0	0
	COX-2																				−
	CAT				−	0	0	−	−	0	0	0	0	0	0	0	0	0	0			+
	HNF4A	+			+	0	0	0	0	0	0	0	0	0	0	0	0	0	0
Transcription factors	PPARG				0	0	0	0	0	0	0	0	0	0	0	0	0	0	0		+			0
	CEBPA	0			0	+	+	+	+	+	0	0	0	0	0	0	0	0	0
	CEBPB	0			0	+	0	0	0	0	0	0	0	0	0	0	0	0	0
	NR1I2	0			0	0	0	0	0	0	0	0	0	0	0	0	0	0	0
	NR1I3	0			0	0	0	−	0	0	0	0	0	0	0	0	0	0	−
	GSN	0			0	0	0	0	0	0	0	0	0	0	0	0	0	0	0
Fbrosis/; senescence	TIMP1	0			0	0	0	0	0	0	0	0	0	0	0	0	0	0	0
	CDH1	+			+	+	0	0	0	0	0	0	0	0	0	−	0	0	0
	RGN	0			0	0	0	0	0	0	0	0	0	0	0	0	0	0	−
	PDIA4				0	0	−	−	0	0	0	0	0	0	0	0	0	0	0						+
Miscellaneous	ACTA1	0			+	0	+	+	0	0	0	0	0	0	0	−	0	0	0

+: up-regulated
−: down-regulated
0: not modulated
The case is empty when the gene has not been studied.
Differentiated HepaRG cells from three different passages and 2-day human hepatocyte cultures from 5 donors were treated for 24 h with different concentrations of TRO. 500 ng of RNA samples from control and treated cultures were separately reverse transcribed and amplified using Quick Amplification Labeling Kit (Agilent). Then they were hybridized using 4×44 K Agilent microarrays satisfying Minimum Information About a Microarray Experiment (MIAME) requirements as previously described [82]. Normalization algorithms and background subtractions were automatically applied to each array to reduce systematic errors and to adjust effects due to technological rather than biological variations using FE and Resolver softwares. The combination of technical and biological replicates uses the error-weighted log ratio average and an estimated error method of the Rosetta Resolver system.