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APPENDIX A & B

Use of “Omic” Technology to Inform the Risk Assessment

Support Document for Case Study: Propiconazole
Page 2 of 78

Table of Contents

APPENDIX – A MODE OF ACTION (MOA) ANALYSIS/PROPOSED MOA.......................................................... 5

I. INTRODUCTION ....................................................................................................................................................5

II. TOXICOLOGICAL FINDINGS FOR PROPICONAZOLE .........................................................................................................5

A. Classical toxicology studies.........................................................................................................................5

B. Mechanistic studies....................................................................................................................................5

C. Mechanistic studies conducted by NEEHRL: classical toxicological endpoints (apical endpoints)............6

D. Mechanistic studies conducted by NEEHRL: genomic, proteomic and metabolomic endpoints...............6

III. MODE OF ACTION (MOA) FOR MOUSE LIVER TUMORS ................................................................................................7

IV. APPLICATION OF THE CANCER GUIDELINES MOA FRAMEWORK ......................................................................................7

V. POSTULATED MOA AND EVIDENCE TO SUPPORT THE KEY EVENTS...................................................................................8

A. Description of the Postulated MOA for Propiconazole ...............................................................................8

B. Key Events...................................................................................................................................................8

1. Identification of Key Events.................................................................................................................................... 8

2. Data supporting the key events.............................................................................................................................. 9

3 Causal relationships between key events and the tumor response ..................................................................... 18

4 Strength, consistency, and specificity of association of tumor response with key events.................................. 21

5 Biological plausibility and coherence ................................................................................................................... 23

6 Alternative modes of action ................................................................................................................................. 23

7 Human relevance following the IPCS framework ................................................................................................. 25

8. Uncertainties and limitations in the database...................................................................................................... 28

VI. REFERENCES ......................................................................................................................................................29

APPENDIX - B TABLES AND FIGURES...............................................................................................................34

TABLES................................................................................................................................................................35

FIGURES..............................................................................................................................................................60
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LIST OF TABLES

TABLE 1. HEPATOCELLULAR TUMORS IN MALE MICE RECEIVING DIETARY LEVELS (PPM) OFPROPICONAZOLE FOR 2

YEARS A...............................................................................................................................................................35

TABLE 2. SUMMARIZED KEY EVENTS ASSOCIATED WITH TUMOR INDUCTION IN MALE MICE FED DIETS CONTAINING PROPICONAZOLE

(SUBMITTED STUDIES)

A B 36

TABLE 3. SUMMARIZED KEY EVENTS ASSOCIATED WITH TUMOR INDUCTION IN MALE MICE FED DIETS CONTAINING PROPICONAZOLE 

(SUBMITTED MECHANISTIC STUDIES)

A B

.......................................................................................................................38

TABLE 4. SUMMARIZED KEY EVENTS ASSOCIATED WITH TUMOR INDUCTION IN MALE MICE FED DIETS CONTAINING PROPICONAZOLE

(SUBMITTED MECHANISTIC STUDIES FROM THE OPEN LITERATURE)

A,B

39

TABLE 5. TEMPORAL ASSOCIATION- TOXICOLOGY, GENOMIC AND PROTEOMIC STUDIES WITH TUMORIGENESIS....................................41

TABLE 6. CYTOTOXICITY OF PROPICONAZOLE AND FIVE OF ITS METABOLITES IN LIVER CELLS AT THE HIGHEST CONCENTRATION EVALUATED 

(400 ΜM) A (CHEN ET AL., 2008).............................................................................................................................43

TABLE 7. ACTIVATION OF NUCLEAR RECEPTORS BY PROPICONAZOLE FEED TREATMENT (2500 PPM) FOR 4 DAYS (NESNOW ET AL., 2009)

...........................................................................................................................................................................43

TABLE 8. SIGNIFICANT INGENUITY PATHWAY ANALYSIS TOX LISTS AND CANONICAL PATHWAYS FROM DEGS OBTAINED AFTER 30D OF 

TREATMENT WITH PHENOBARBITAL (PB) (850 PPM) OR PROPICONAZOLE (PRO) (2500 PPM).A (NESNOW ET AL. 2009)............44

TABLE 9 EFFECTS ON HEPATIC MICROSOMAL AND CYTOSOLIC PROTEIN AND ENZYME ACTIVITIES IN MALE MICE FED DIETS CONTAINING

PROPICONAZOLE OR PHENOBARBITAL 14 DAYS ..............................................................................................................46

TABLE 10 INCIDENCE OF LIVER HYPERTROPHY IN MICE FED PROPICONAZOLE IN THE DIET.

A

†............................................................47

TABLE 11. EXPRESSION OF CHOLESTEROL BIOSYNTHETIC GENES AFTER TREATMENT WITH THE HIGH DOSE (2500 PPM) PROPICONAZOLE: 4

DAYS OF TREATMENT A..............................................................................................................................................47

TABLE 12. SIGNIFICANT EXPRESSION OF CHOLESTEROL BIOSYNTHETIC GENES AFTER CONAZOLE TREATMENT OF 2500 PPM PROPICONAZOLE 

TREATMENT (FROM WARD ET AL (2006) AND NESNOW ET AL 2009) ...............................................................................48

TABLE 13. DIFFERENTIALLY EXPRESSED SOLUBLE PROTEINS FROM LIVERS OF MICE TREATED FOR 4 DAYS WITH PROPICONAZOLE. PROTEINS 

WERE QUANTIFIED BY 2D-DIGE AND IDENTIFIED BY MS/MS MASS SPECTROMETRY AND PROTEIN DATABASE MATCHING. (ORTIZ ET 

AL., 2010) ............................................................................................................................................................49

TABLE 14. MOUSE LIVER CELL PROLIFERATION DATA IN MALE MICE FED PROPICONAZOLE IN THE DIET; PROLIFERATING CELL NUCLEAR 

ANTIGEN (PCNA) INDICES ........................................................................................................................................53

TABLE 15. SUMMARIZED RESULTS OF FIFRA GUIDELINE MUTAGENICITY STUDIES ON PROPICONAZOLE............................................54

TABLE 16. STRUCTURE-ACTIVITY RELATIONSHIP OF RELATED TRIAZOLE COMPOUNDS A,B................................................................55

TABLE 17. INCIDENCE AND SEVERITY OF HEPATOXIC EFFECTS OF 4, 8, AND 13 WEEKS DIETARY ADMINISTRATION OF CGA-64250 IN CD-1

MALE MICE1)..........................................................................................................................................................58

TABLE 18. KEY EVENTS HUMAN RELEVANCY: COMPARISON OF KEY EVENTS IN RODENTS AND HUMANS FOR PROPICONAZOLE.............59
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LIST OF FIGURES

FIGURE 1. PROPOSED MODE OF ACTION OF PROPICONAZOLE FOR MOUSE LIVER TUMORS USING TOXICOGENOMIC DATA........................60

FIGURE 2. PROPICONAZOLE METABOLITES; METABOLITE IDENTIFIED AS U2 IN MRID 00164795 = CGA 91305.DATA EXTRACTED FROM 

CHEN ET AL., 2009. ................................................................................................................................................61

FIGURE 3. LIVER MICROSOMAL ALKOXYRESORUFIN DEALKYLASE (AROD) ACTIVITIES IN LIVERS FROM CD-1 MICE FED DIETS OF 

PROPICONAZOLE. DATA EXTRACTED FROM ALLEN ET AL., 2006........................................................................................62

FIGURE 4. EFFECTS OF PROPICONAZOLE ON MOUSE LIVER TO BODY WEIGHT MEASUREMENTS. DATA EXTRACTED FROM ALLEN ET AL.,

2006; DOYLE AND RINDE, 1992; MRID 00129570. ..................................................................................................63

FIGURE 5. RETINOIC ACID BIOSYNTHESIS AND METABOLISM PATHWAY: GENE EXPRESSION LEVELS ALTERED BY PROPICONAZOLE 4, 30 AND 

90 DAYS OF TREATMENT. DATA EXTRACTED FROM NESNOW ET AL., 2009. ........................................................................64

FIGURE 6. EFFECT OF PROPICONAZOLE ON HEPATIC MICROSOMAL ATRA METABOLISM AFTER 4 DAYS OF TREATMENT. DATA EXTRACTED 

FROM CHEN ET AL., 2009.........................................................................................................................................65

FIGURE 7. EFFECTS OF PROPICONAZOLE ON CELL PROLIFERATION. DATA EXTRACTED FROM ALLEN ET AL., 2006; DEWHURST AND 

DELLARCO, 2003; MRID 45215802. .......................................................................................................................66

FIGURE 8. EFFECTS OF PROPICONAZOLE ON CELL CYCLE GENES OVER TIME. DATA EXTRACTED FROM NESNOW ET AL., 2009..................67

FIGURE 9. EFFECTS OF PROPICONAZOLE ON APOPTOTIC GENES. DATA EXTRACTED FROM NESNOW ET AL., 2009. ...............................68

FIGURE 10. INDUCTION OF MOUSE LIVER TUMORS BY PROPICONAZOLE DATA FROM MALE MOUSE STUDY, HEPATOCELLULAR TUMOR

INCIDENCE. DATA EXTRACTED FROM MRID 00129570.................................................................................................69

FIGURE 11. CONCORDANCE OF CAR TARGET EXPRESSION WITH LIVER: BODY-WEIGHT. DATA EXTRACTED FROM ALLEN ET AL., 2006;

WARD ET AL., 2006................................................................................................................................................70

FIGURE 12. CONCORDANCE OF PROD ACTIVITY WITH CYP2B10 GENE EXPRESSION. DATA EXTRACTED FROM ALLEN ET AL., 2006;

NESNOW ET AL., 2009. ...........................................................................................................................................71

FIGURE 13. SOME GENES ASSOCIATED WITH PXR ACTIVATION AT 4 DAYS OF PROPICONAZOLE TREATMENT. DATA EXTRACTED FROM 

NESNOW ET AL., 2009. ...........................................................................................................................................72

FIGURE 14. GENES ASSOCIATED WITH RETINOIC ACID METABOLISM. DATA EXTRACTED FROM NESNOW ET AL., 2009..........................73

FIGURE 15. GENES ASSOCIATED WITH OXIDATIVE STRESS. DATA EXTRACTED FROM NESNOW ET AL., 2009........................................74

FIGURE 16. GENES ASSOCIATED WITH DNA DAMAGE. DATA EXTRACTED FROM NESNOW ET AL., 2009............................................75

FIGURE 17. CONCORDANCE OF CELL CYCLE GENE EXPRESSION WITH LIVER CELL PROLIFERATION AFTER 4 DAYS OF PROPICONAZOLE 

TREATMENT. DATA EXTRACTED FROM NESNOW ET AL., 2009. ........................................................................................76

FIGURE 18. GENES ASSOCIATED WITH APOPTOSIS. DATA EXTRACTED FROM NESNOW ET AL., 2009. ...............................................77

FIGURE 19. ALTERATIONS OF CELL CYCLE GENES WITHIN THE PHASES OF THE CELL CYCLE BY PHENOBARBITAL (PB) AND PROPICONAZOLE 

(PRO). DATA EXTRACTED FROM NESNOW ET AL., 2009..................................................................................................78
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APPENDIX – A MODE OF ACTION (MOA) ANALYSIS/PROPOSED MOA

I. Introduction

This document (Appendix A) contains classical toxicology and toxicogenomic data that support the mode 

of action (MOA) analysis, which was developed for the propiconazole Case Study. It is accompanied by 

an appendix of associated Tables and Figures (Appendix B). The Office of Pesticide Programs (OPP) in 

collaboration with the Office of Research and Development (ORD) has shaped an approach to 

incorporate mechanistic data into the cancer risk assessment through linkage of toxicogenomic data to 

key events in carcinogenesis. The use of toxicogenomic data to conduct a mode of action (MOA) 

framework analysis is presented in this document on the hepatotumorigen, propiconazole. 

Propiconazole was selected for this effort based on discussions between OPP and the National Health 

and Environmental Effects Research Laboratory (NHEERL) of ORD and on the wealth of available 

information on this conazole. Compounds in this class are antifungal pesticides commonly used in the 

protection of fruit, vegetable and cereal crops. In addition to the wide spread agricultural use, many 

conazoles are also used as pharmaceuticals for treatment of local and systemic fungal infections in 

humans. Antifungal activity is exerted through inhibition of a specific cytochrome, P450, CYP51, a critical 

step in the biosynthesis of ergosterol, a steroid required for formation of the fungal cell wall. In 

mammals, many of these conazoles induce a wide range of toxicities that include induction or inhibition 

of hepatic CYP isoforms, oxidative stress, dyregulation of cholesterol biosynthesis and metabolism, 

hepatotoxiciy, and liver tumors. The present effort concentrates on propiconazole, which induces both 

liver adenomas and carcinomas in mice. It should be noted that the regulatory status of propiconazole 

is not the focus of this undertaking; propiconazole was selected as a model compound to test and 

illustrate an approach to incorporate toxicogenomic data into the risk assessment process.

II. Toxicological findings for propiconazole

A. Classical toxicology studies

Carcinogenicity studies show that propiconazole is carcinogenic to male mice based on the significant 

increase in the incidence of hepatocellular adenomas and adenomas/carcinomas combined at 2500 ppm 

(Table 1, See Appendix B). Also observed consistently throughout the toxicology database was evidence 

of increased liver weights, hypertrophy, and decreased cholesterol levels (Table 2, See Appendix B).

B. Mechanistic studies

Results from two mechanistic studies show that cytochrome P450 was significantly increased, 7-

ethoxyresorufin-O-dealkylase (EROD) was increased but only slightly, and 7-pentoxyresorufin-Odealkylase (PROD) was increased 30-55-fold at 850 and 2500 ppm, respectively (Table 3, See Appendix 

B). These findings are indicative of CYP2B induction. In the second study, hepatocellular proliferation 

was examined in male mice receiving dietary levels of 0, 850 and 2500 ppm. It was found that within 2 

days of treatment, propiconazole induced dose-related increases in liver weights. Hepatocellular 

hypertrophy was dose- and time-related, commencing at 24 hours and persisting until study termination 

(60 days). Similarly, cell proliferation, indicated by increased BrdU-staining in hepatocytes was markedly 

increased at 24 hours, peaked at 48 hours and returned to normal levels at 7 days.
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C. Mechanistic studies conducted by NEEHRL: classical 

toxicological endpoints (apical endpoints)

Five mechanistic studies of classical toxicological endpoints (apical endpoints) as well as toxicogenomic 

responses were also conducted and published by scientist at NHEERL. The study of Allen et al. (2006), 

describes analyses of mice administered 100, 500 and 2500 ppm of propiconazole in feed over 4, 30 and 

90 days. Two reports (Sun et al., 2005; Goetz et al., 2006) describe separate analyses from a common 

experiment in which animals were administered 10, 75 or 100 mg/kg-bw/day of propiconazole by 

gavage for 14 days. Two reports, Chen et al (2009), and Bruno et al. (2009), detail separate analyses of 

mice administered propiconazole by daily intraperitoneal (ip) injections of 210 mg/kg-bw/day, or 

continuously in feed (2500 ppm), over 4 consecutive days. Methodologies and endpoints measured in 

these studies included: histopathologic analysis (liver hypertrophy); AROD assays (liver enzyme 

activities); qRT-PCR (liver metabolic gene mRNA levels); proliferating cell nuclear antigen (PCNA)-

labeling (liver cell proliferation); clinical chemistry (serum cholesterol/triglycerides/HDL levels); all transretinoic acid (atRA) metabolism and atRA hepatic levels (HPLC/ LC/MS) ; Western immunoblotting; twodimensional gel electrophoresis; and mass spectrometry (liver protein carbonylation and related 

indicators of oxidative damage). 

As shown in (Table 4, See Appendix B). The results from these studies using different doses, routes, and 

durations of exposure are in good agreement and show that propiconazole increases liver weights and 

histopathological effects (e.g., hypertrophy), and induces specific enzymes functioning in xenobiotic 

metabolism (e.g., CYP2B, CYP3A). Propiconazole effects on body weights were assessed in all of the 

studies; however, only Allen et al. (2006) reported a significant reduction in body weight gain compared 

with controls. This study also demonstrates increased liver cell proliferation and reduced serum 

cholesterol and high-density lipoproteins (HDL), sometimes with a concomitant increase in triglycerides. 

Chen et al. (2009) reported that propiconazole increased hepatic microsomal retinoic acid metabolism 

and decreased retinoic acid levels. Increases in liver protein carbonylation and other measures of 

oxidative damage to cellular proteins were shown by Bruno et al. (2009). The overall results from these 

studies confirm the earlier data from the classic toxicology assays indicating that propiconazole induces 

histological changes in the liver. They also suggest that propiconazole induces mouse liver tumors 

through an MOA that is associated with, induction of liver enzyme activity, oxidative damage, altered 

cholesterol biosynthesis/metabolism, reduced RA levels, and perturbed regulation of cell growth.

D. Mechanistic studies conducted by NEEHRL: genomic, proteomic 

and metabolomic endpoints 

Three genomic studies, one proteomic study and one metabolomic study have been published by EPA 

scientists that investigated the effects of conazoles on mouse liver: Ward et al. 2006; Nesnow et al. 

2009; Goetz et al. 2006; Ortiz et al., 2010, Nesnow et al., 2011. Each provides a different view of the 

transcriptional/ proteomic/metabolomic responses to conazoles. Each study has strengths and 

weaknesses due to the design differences. Both Ward et al. (2006) and Nesnow et al. (2009) studies 

used the same propiconazole data from Affymetrix Genechips (25-mer gene probes) that came from 

liver tissues obtained from male CD-1 mice fed 3 doses (tumorigenic and non-tumorigenic) of 

propiconazole after 4, 30, or 90 days of treatment as reported in Allen et al., 2006, however they used 

different statistical and bioinformatic approaches and comparisons. In addition, Ward et al (2006) 
Page 7 of 78

examined the transcriptional effects of two additional conazoles, myclobutanil and triadimefon which 

were also part of the Allen et al. (2006) study, while Nesnow et al. (2009) compared propiconazole to 

triadimefon and phenobarbital (PB). In contrast to Ward et al. (2006) and Nesnow et al. (2009) feeding 

studies, Goetz et al. (2006) examined four triazole fungicides for their hepatotoxic effects in mouse liver 

at three dose levels using oral gavage as a route of exposure. Complimentary to the three genomics 

studies is the report on global proteomic responses to propiconazole treatment provided by Ortiz et al. 

(2010). This was a comprehensive study profiling changes in protein expression of soluble proteins in 

livers from mice treated with the mouse liver tumoriogen, propiconazole, to uncover the pathways and 

networks altered by this fungicide. Nesnow et al., 2011 is a dose response metabolomic study of liver 

homogenates from mice fed propiconazole at 0, 500, 1250, and 2500 ppm for 4 days. Results from 

these studies were in good agreement with the classical toxicological approach and identified additional 

activities (Table 5, See Appendix B), which enhanced the toxicological assessment and set the stage for a 

comprehensive analysis of the MOA for the mouse liver tumors. 

III. Mode of action (MOA) for mouse liver tumors

Chemically induced liver carcinogenesis is a multistage process. One stage involves alterations to DNA 

leading to a mutagenic event (initiation). The DNA alteration may be a result of the direct interaction of 

the chemical (or its metabolically-activated reactive form) with DNA or by an indirect pathway such as 

chemical induction of reactive oxygen species, which can modify DNA, or by intercalation of the 

chemical with DNA. A second stage involves increased cell proliferation (promotion) that increases 

clonal expansion, and inhibits apoptosis of initiated cells. The third stage is progression, which can 

involve karyotypic instability, activation of protooncogenes and loss of functional tumor suppressor 

genes (Pitot et al., 1996; Klaunig and Kamendulis, 2004). There are a myriad of altered cellular events 

and/or pathways within each stage that can contribute to the mode of action of a chemical. These 

altered events and/or pathways can be a result of the plieotropic effects of the chemical such as altering 

intermediary metabolism, inducing oxidative stress, activation of key nuclear receptors and alterations 

in cell signaling pathways to name some examples. 

Conazoles are azole-containing chemicals designed to inhibit fungal Cyp51. In mammalian systems, they 

demonstrate effects on many hepatocellular functions, pathways and biological intermediates. The 

proposed MOA for propiconazole encompasses a group of key events that incorporate a number of 

propiconazole altered hepatic functions and, in total, explain the carcinogenic effects of this fungicide. 

IV. Application of the cancer guidelines MOA framework

The revised U.S EPA Guidelines for Carcinogen Risk Assessment describe a framework that can be used 

to determine whether a postulated MOA is operative (USEPA, 2005). Steps in the Cancer Guidelines 

framework include: an outline of the sequence of events leading to cancer, identification of the key 

events and determination of whether there is a causal relationship between events and cancer (e.g., 

dose-response relationship and temporal associations). Additionally, the plausibility of the hypothesis 

and the examination of other potential MOAs are explored. Finally, the relevance to humans is 

assessed.
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V. Postulated MOA and evidence to support the key events

A. Description of the Postulated MOA for Propiconazole

Based on currently available information, it is postulated that propiconazole induces tumors in the 

mouse liver following dietary exposure through a proposed series of key events. Many of these key 

events can be separated into actions related either to Cyp induction or Cyp inhibition. Cyp induction 

includes the key events: activation of CAR and PXR, increased expression of Cyp2b and Cyp3a proteins, 

increased hepatic hypertrophy, induction of oxidative stress, increased mutations, and decreased 

hepatic levels of all trans retinoic acid (atRA). Cyp inhibition includes the key events: dysregulation of 

cholesterol biosynthesis and metabolism through inhibition of Cyp51 and increased levels of mevalonic 

acid. Suppression of apoptosis and the preceeding key events lead to increased cell proliferation and 

tumor formation.

B. Key Events

1. Identification of Key Events.

The key events proposed to result in a carcinogenic effect of propiconazole are illustrated in Figure 1

(See Appendix B). ). The key events are grouped as described above and differentiated by color (Blue =

Enzyme induction; Green = Enzyme inhibition; and Orange = Increased cell proliferation, suppression 

of apoptosis, and tumor formation). Each key event is enclosed in a box. Those key events that are 

supported with sufficient data are in boxes with solid lines. Solid lines connecting the key events are 

supported by sufficient data. It should be noted that the key events detected by the genomic analysis 

were identified at the first sampling time of 4 days. It is reasonable to assume that several were 

perturbed earlier. Therefore, the exact sequence of events is not known at this time. The ordering of 

events, shown below, represents a credible arrangement to facilitate the discussion. The key events 

leading to liver tumors include:

a) Activation of CAR and PXR nuclear receptors 

(Causal)1 (Molecular Initiating Event)2

b) Increased Cyp2b and Cyp3a mRNA levels, protein levels 

and increased Cyp metabolic activities (Causal) 

c) Increased hepatic hypertrophy (Associated)3

 

1

Causal is defined as an obligatory event that is required for the process to continue to tumor development.

2 Molecular initiating event is the initial point of chemical-biological intersection within the organism. Additional 

key events further along the pathway that lead to, and are experimentally or toxicologically associated with the 

adverse outcome are referred to as “key events”. 

3

Associative is defined, as an event that contributes to the key event but of itself is not required for the process to 

move forward. 
Page 9 of 78

d) Increased atRA metabolism/decreased hepatic 

retinoic acid levels (Causal)

e) Oxidative stress (Causal)

f) Induction of vivo mutation (Causal)

g) Dysregulation of cholesterol biosynthesis/metabolism 

through inhibition of Cyp51 (Causal)

h) Increase in hepatic mevalonic acid levels (Causal)

i) Increased cell proliferation (Causal)

j) Suppression of apoptosis (Causal)

k) Tumor induction

2. Data supporting the key events 

a) Metabolism is not required for toxicological activity

The metabolism of orally administered [14C]-phenyl propiconazole was studied in mice. In male mice, 

60% of the radioactivity in 0-24 hour urine was represented by one metabolite, the glucuronic acid 

conjugate of 1-(2,4-dichlorophenyl)-2-(1 H-1, 2,4-triazol-1-yl) ethanol (Figure 2, see Appendix B). This 

demonstrates that the major metabolic pathway in mice involves dioxolane ring cleavage (INCHEM, 

1987; MRID 00164795). Propiconazole was cytotoxic while its metabolites were not cytotoxic to primary 

mouse hepatocytes including the major mouse metabolite, CGA 91305 (Table 6, see Appendix B) (Chen

et al., 2008). Several propiconazole metabolites were cytotoxic to human (HepG2) and mouse hepatic 

tumor (Hepa1c1c7) cells; however, their responses were less than the parent molecule, propiconazole 

(Chen et al., 2008). Since most metabolically activated forms of chemicals are generally more cytotoxic 

than their parent molecules, it was concluded that metabolism of propiconazole is not a key event in its 

tumorigenic MOA. 

b) Activation of CAR and PXR nuclear receptors (Causal)

Dietary treatment with 2500 ppm propiconazole increased liver to body weight measures over a 90-day 

period (Allen et al., 2006; Nesnow et al., 2009). Propiconazole treatment for 4 days activated a series of 

nuclear receptors including CAR, PXR, LXR, PPARα and TR by transcriptomic pathway analyses (Table 7, 

see Appendix B). CAR activation was inferred from the AROD data of the 14-day mechanistic study 

submitted by the sponsor (Table 3) and from the mechanistic studies in the open literature (Table 4). 

At 30 days of treatment, CAR/RXR4activation, PXR/RXR activation, PPARα/RXRα activation, TR/RXR 

 

4 CAR/RXR: Constitutive androstane receptor/retinoid X receptor, also known as a nuclear receptor subfamily, 

functions as a sensor of xenobiotic substances and in response upregulates the expression of target genes (e.g., 

Cyp2b10) to produce the gene product (e.g., Cyp2b), which is responsible for the metabolism of harmful substances. 

Activation of CAR is a necessary step in the hepatocarcinogenic MOA for certain chemicals. 
Page 10 of 78

activation, and FXR/RXR activation were also identified (Table 8, see Appendix B). At 90 days of 

treatment, CAR/RXR activation, PXR/RXR activation, PPARα/RXRα activation, TR/RXR activation, 

VDR/RXR activation, and FXR/RXR activation were identified. The genomic analysis, performed in this 

study identified CAR/RXR activation and PXR/RXR activation as IPA Canonical pathways and or IPA Tox 

Lists and the activation of these nuclear receptors are considered to be key events in the mode of action 

for propiconazole-induced hepatic tumorigenesis. At 4 days, some of the significantly expressed genes in 

these two pathways were for CAR/RXR: Aldh1a1, aldehyde dehydrogenase family 1, subfamily A1 (1.3-

fold), Ald1a7, aldehyde dehydrogenase family 1, subfamily A7 (2-fold), Alas1, aminolevulinic acid 

synthase 1 (17.6-fold), Cyp2b10, cytochrome P450, family 2, subfamily B, polypeptide 10 (45.6-fold), and 

Gstm1, glutathione S-transferase, mu1 (1.43-fold). These genes are the same as those associated with 

CAR activation using wild type and CAR knock-out mice (Maglich et al., 2002). Several of the key 

significantly expressed genes detected in the PXR/RXR pathway were: Gstm1, (1.43-fold), Cyp2c65 (41.5-

fold), Aldh1a1 (1.3-fold), Abcc3, ATP-binding cassette, sub-family C (1.7-fold) and Papps2 (3'-

phosphoadenosine 5'-phosphosulfate synthase 2 (1.6-fold). Several specific genes and proteins from the

CAR/RXR and PXR/RXR activation pathways were studied further. Q-RT-PCR analysis of mRNA from livers 

from mice treated with propiconazole demonstrated increases in Cyp2b10 (29.8-fold), Cyp3a11 (6.6-

fold), and Cyp3a13 (2.4-fold), genes (Sun et al., 2005; Goetz et al., 2006; Chen et al., 2009) at 4 days of 

treatment. 

Protein levels of many of these genes have been examined by proteomics analyses and Western blot 

analyses (Bruno et al., 2009; Chen et al., 2009; Ortiz et al., 2010). Increased protein levels of the 

following enzymes were observed: Aldh1a1, Aldh1a7, Gsta3, Gstm1, Gstm2, Gstm3, Gstt, Cyp2b10, and 

Cyp3a which confirmed the genomic results (Chen et al., 2009; Ortiz et al, 2010). Pentoxyresorufin Odealkylase activities (PROD, a measure of Cyp2b protein enzymatic activities) were significantly 

increased by propiconazole after 4, 30, and 90 days of treatment (Allen et al., 2006). Transcriptomic 

analyses of liver mRNA from mice fed diets of 2500 ppm propiconazole for 30 and 90 days had CAR/RXR 

and PXR/RXR significantly altered Tox Lists or Canonical pathways (Nesnow et al., 2009). As indicated by 

the sustained hypertrophy, genomic pathways profiles and high PROD levels over time, the activation of 

CAR/RXR and PXR/RXR is demonstrable up to 90 days and based on increased hypertrophy probably 

continues up to 119 days, the last time point reported in a series of studies (see Hypertrophy below).

Propiconazole activates hPXR from published reporter assays (Sueyoshi et al., 1999).

Car knock-out mice were found to be refractory to the tumor promoting effects of phenobarbital 

suggesting that Car is required for phenobarbital to promote mouse dimethylnitrosamine initiated cells 

into tumors (Yamamoto et al., 2004). At present there are no available chronic studies of propiconazole 

in Car or Pxr knockout mice.

c) Increased Cyp2b and Cyp3a mRNA levels, protein levels 

and increased P450 metabolic activities (Causal)

Q-RT-PCR analysis of mRNA from the livers of mice treated with propiconazole under different 

treatment conditions had increased expression of Cyp2b10, Cyp3a11, and Cyp3a13 genes. Male CD-1 

mice treated with propiconazole by gavage (150 mg/kg/d for 14 days) had a 2.39-fold increased 

expression of Cyp2b10 and 5.19-fold increase of Cyp3a11 (Sun et al., 2005; Table 4). Male CD-1 mice 

injected daily for 4 days with propiconazole (210 mg/kg/d) had a 29.8-fold increase in Cyp2b10, a 6.55-

fold increase in Cyp3a11, and a 2.43-fold increase in Cyp3a13 gene expression (Chen et al., 2009).

Genomic analysis identified CAR/RXR activation and PXR/RXR activation as IPA Canonical pathways and 
Page 11 of 78

or Tox Lists after 4, 30 and 90 days of treatment suggesting that these genes were over-expressed at all 

time points (Nesnow et al., 2009). Western blot analyses were performed on microsomes obtained from 

male CD-1 mice injected daily for 4 days with propiconazole (210 mg/kg/d). The results demonstrated 

increased expression of Cyp2b and Cyp3a proteins in the treated mice while these proteins were not 

detected in the control mice (Chen et al., 2009). 

Cytochrome P450 enzymatic activity was determined using alkoxyresorufin assays. PROD activity is 

strongly associated with Cyp2b activity (Burke et al., 1994; Sun et al., 2005), while benzyloxy Odealkyase (BROD) activity is associated with many Cyps including Cyp2b, Cyp2c and Cyp3a (Burke et al., 

1994; Yang et al., 1994). Liver microsomes from propiconazole treated male CD-1 mice (150, 75 or 10 

mg/kg/d for 14 days by gavage) had a dose-response in PROD and BROD activities. At the highest dose 

(150 mg/kg/d), PROD activities were increased 5.1-fold and BROD activities 3.9-fold compared to the 

respective controls (Sun et al., 2005; Goetz et al., 2006). PROD activities were determined in male CD-1 

mouse liver microsomes from mice fed dietary levels of propiconazole (2500, 500, 100 ppm) in a time 

course and dose response study (Figure 3, see Appendix B). Propiconazole induced PROD activities in a 

dose response manner at each time point and increased over time from 13.3-fold at 4 days to 37.5-fold 

at 30 days which were maintained up to 90 days (Allen et al., 2006). PROD activity in male CD-1 mice, 

fed diets containing 850 ppm or 2500 ppm propiconazole for 14 days, was increased 30 or 55X , 

respectively, over control (Table 3). The effects of propiconazole on testosterone 16β-hydroxylation, a 

measure of Cyp3a protein enzymatic activity (Bornheim and Correia, 1990) was determined. In male CD1 mice fed a diet of 2500 ppm propiconazole and 850 ppm propiconazole for 14 days, testosterone 16βhydroxylation was induced 52.4- and 36.6-fold, respectively (MRID 45215803). In the same study 

coumarin-7-hydroxylase activity, a measure of Cyp2a5 protein activity (Kimonen et al., 1995) was 

determined. Propiconazole (2500 ppm and 850 ppm) induced coumarin-7-hydroxylase 23.8- and 5.3-fold 

respectively(MRID 45215803; Table 9). UDP-glucoronosyltransferase, cytosolic glutathione transferase 

and epoxide hydrolase activities were also induced by propiconazole at both the 850 ppm and 2500 ppm 

feed levels. Genomic analyses of hepatic tissues from mice fed 2500 ppm propiconazole indicated 

increased expression of mRNA from: Gsta3, Gstm1, Gstm2, Gstm3, Gstt3, Ugt1a9, Ugt2b34, Ugt2b35 (4 

days); Cyp2a5, Gsta3, Gstm1, Gstm2, Gstm3, Gstt3, Ugt1a6a, Ugt1a9, Ugt2b34, Ugt2b35 (30 days);

Cyp2a5, Gsta2, Gsta4, Gstm1, Gstm2, Gstm3, Gstm3, Gstm4, Gstm5, Gstt3,Ugt1a6a ,Ugt1a9, Ugt2b1, 

Ugt2b34, Ugt2b35 (90 days) (Nesnow et al., 2009).

d) Increased hepatic hypertrophy (Associated)

Apical evidence of hypertrophy in the mouse liver was apparent in virtually every toxicology study 

submitted by the registrant, commencing on day 1 (Table 3) and persisting through 2 years (Table 9). 

Similar evidence of hypertrophy was observed in the mechanistic studies from the open literature

(Table 4). Transcriptomic analysis of liver mRNA from male CD-1 mice after dietary treatment of 2500 

ppm for 4 and 30 days revealed a series of IPA Hepatic Tox Functions (disease states) associated with the 

treatment: cholestatis, steatosis, and hyperplasia/hyperproliferation (Nesnow et al., 2009). Hepatic 

hypertrophy was determined by histologic measures in 2 studies. Hepatic hypertrophy has been 

generally associated with increases in the smooth endoplasmic reticulum and increases in drug 

metabolism enzymes such as cytochrome P450s. After 4, 30 and 90 days of treatment with 

propiconazole hepatic hypertrophy was induced in all male CD-1 mice examined at all time points at 

2500 ppm. At lower doses and all time points, 500 and 100 ppm, hepatic hypertrophy was observed 

(Table 10, see Appensix B) (Allen et al., 2006). In a second study, male CD-1 mice treated with 

propiconazole for 17 wk had evidence of hepatic hypertrophy in all mice treated with 2500 and 1450 
Page 12 of 78

ppm. Seventy percent of male mice treated with 850 ppm propiconazole also had hepatic hypertrophy( 

MRID 42050501, Table 2). An indirect measure of hepatic hypertrophy is the percentage of liver to body 

weight. Propiconazole treatment with 2500 ppm increased liver to body weight ratios from the first 

observation at 4 day up to, and including, the completion of the study at 2 years (Figure 4, see Appendix 

B). Male CD-1 mice treated with 2500 ppm propiconazole had increased liver to body weight ratios after 

4, 30 and 90 days of treatment, while 500 and 100 ppm exposures produced no significant effects (Allen

et al., 2006). Male CD-1 mice fed a diet of 2500 ppm propiconazole (207.9 mg/kg/d average daily 

consumed dose) and 850 ppm propiconazole (158.5 mg kg/d average daily consumed dose) for 14 days 

had a 12.2% and 8.0% liver to body weight ratio, respectively( MRID 45215803; Table 3). Male CD-1 

mice treated with propiconazole for 13 wk had significant increases in liver to body weight ratios after 

500, 850, 1450, and 2500 ppm propiconazole( MRID 42050502; Table 2). 

e) Increased atRA metabolism/decreased hepatic retinoic 

acid levels (Causal)

Transcriptomic studies of mRNA from livers of male CD-1 mice treated with 2500 ppm propiconazole in 

the diet found alterations in the retinol metabolism pathway, both at 4 and 30 days of treatment 

(Nesnow et al., 2009). Analysis of the pathway indicated that a group of Cyps associated with the 

metabolism of atRA to 4-hydroxy-atRA were significantly up-regulated (Cyp26a1, Cyp2b10 (human 

ortholog, CYP2B6), Cyp2c55 (human ortholog, CYP2C18), and Cyp2c65 (human ortholog, CYP2C8) 

(Figure 5, see Appendix B). This was evaluated in vitro with an atRA metabolism assay using liver 

microsomes from propiconazole-treated mice. Propiconazole treatment of mice for 4 days significantly 

increased the metabolism of atRA to 4-hydroxy-atRA and 4-oxo-atRA compared to those from control 

mice (Figure 6, see Appendix B). In addition to Cyp26a1 and Cyp2b10, other Cyps were found to 

catalyze the metabolism of atRA, Cyp3a11 and Cyp3a13 (Chen et al., 2009). The effects of propiconazole 

treatment on mouse hepatic atRA levels were examined. Propiconazole treatment by dietary 

administration (2500 ppm) or by ip injection (210 mg/kg-bw) for 4 days significantly reduced hepatic 

tissue atRA levels 45-50% (Table 4) (Chen et al., 2009). Hepatic atRA levels in mice have been shown to 

be modulated by chemical treatment. TCDD treatment of male C57BL/6 mice increased hepatic atRA 

levels. This increase was ascribed to an increase in retinal oxidase, a key enzyme in the atRA biosynthetic 

pathway (Yang et al., 2005). The effects of pretreatment of mice with phenobarbital or 3-

methylcholanthrene on the levels of orally administered atRA have been reported (Kalin et al., 1984). 

Male BDF1 mice pretreated with phenobarbital and then orally treated with atRA, exhibited a 54% 

reduction in hepatic atRA levels while similar studies with 3-methylcholanthrene showed no effects on 

atRA levels. These results were interpreted in terms of phenobarbital induction of specific atRA 

metabolic enzymes. 

Retinoids are well-known anticancer agents as they signal differentiation and growth suppressive signals 

in normal, premalignant, and malignant cells (Freemantle et al., 2003). One of the major roles of 

retinoids is to control cell proliferation in epithelial cells. The growth of MCF-7 breast cancer cells was 

inhibited by atRA (Teixeira and Pratt, 1997). This was associated with inhibition and accumulation of 

cells in G1 phase of the cell cycle due to the inhibition of cdk2 mRNA and protein production and by a 

decrease in CDK2 activity. Retinoblastoma protein phosphorylation was also partially reduced and the 

level of retinoblastoma protein was decreased (Teixeira and Pratt, 1997). Conversely, alcohol-induced 

liver cancer in rats was associated with increased Cyp2e1 induction, increased cell proliferation and 

decreased retinoic acid levels (Liu et al., 2002; Wang, 2003). The cell proliferation responses were 

reversed with dietary atRA supplementation (Chung et al., 2002). These data suggest that the decrease 
Page 13 of 78

in atRA levels would provide a tumor promoting environment (Wang, 2003). The results on the effects of

propiconazole on cell proliferation are in general agreement with the effects of propiconazole on the 

depression of hepatic atRA levels in mice as propiconazole treatment at 4 days was found to both 

depress the hepatic levels of atRA (Chen et al., 2009), and to statistically increase hepatic labeling 

indices (Allen et al., 2006). 

f) Oxidative stress (Causal) 

It has been reported that several Cyps: Cyp1a1, Cyp1a2, Cyp2b1, Cyp3a, and Cyp2e1 are susceptible to 

uncoupling of their catalytic cycle generating reactive oxygen species (ROS) and oxidative stress. Aroclorinduced rat liver microsomes (known to contain Cyp1a1 and Cyp1a2 produce ROS in the presence of 

NADPH and 3, 3’, 4, 4’-tetrachlorobiphenyl. Recombinant human CYP1A1 and CYP1A2 microsomes in the 

presence of NADPH also produced ROS (Schlezinger et al., 1999). Overexpression of CYP2E1 has been 

linked to ROS production, lipid peroxidation and oxidative stress (Caro and Cederbaum, 2004). Purified 

Cyp2b1 proteins in a reconstituted system produced lipid peroxidation and hydrogen peroxide and 

superoxide radical in the presence of NADPH (Ekstrom and Ingelman-Sundberg, 1986). This was 

confirmed in vivo in mice and rats as phenobarbital treatment increased F(2)-isoprostane levels 

(products of free radical peroxidation of arachidonate) in livers and urine (Dostalek et al., 2007; Dostalek

et al., 2008). Rats treated with dexamethasone responded with 50-fold increases in hepatic CYP3A 

proteins and when these rats were pulsed with salicylic acid, 17.2-fold increases in plasma 2,3-

dihydroxysalicylic acid (a measure of ROS formation) were detected (Strolin-Benedetti et al., 1999). 

Transcriptomic analysis of liver mRNA from CD-1 mice fed 2500 ppm propiconazole for 4, 30 and 90 days 

revealed canonical pathways associated with oxidative stress and NRf2 mediated oxidative stress 

(Nesnow et al., 2009). PROD activities were determined in male CD-1 mouse liver microsomes from mice 

fed dietary levels of propiconazole (2500, 500, 100 ppm) over a 90 day period and were highly increased 

over controls supporting the extended oxidative stress responses observed by transcriptomic analyses 

(Allen et al., 2006). Testosterone β-hydroxylation (a measure of Cyp3a) was also increased by 

propiconazole (MRID 45215803).

Propiconazole treatment of male CD-1 mice increased several direct measures of oxidative stress in the 

liver, protein carbonylation was increased 13-fold, and the GSH/GSSG ratio was decreased ~2-fold 

(Bruno et al., 2009). A number of specific proteins were identified as being carbonylated (oxidized) and 

these proteins have been associated with glycolysis, ATP production, and cellular antioxidant defense 

and detoxification. Network analysis of these carbonylated proteins indicated several central hub 

proteins, hepatocyte necrosis factor 4A (HNF4A) a transcription factor, and FOS that with JUN forms the 

transcription factor complex, AP-1, known to be activated by oxidative stress (Klaunig and Kamendulis, 

2004; Bruno et al., 2009). As shown above propiconazole treatment over-expressed Cyp2b10 and 

Cyp3a11 mRNA, is a strong inducer of Cyp2b and Cyp3a protein and Cyp2b10 and Cyp3a associated 

enzymatic activities, suggesting that part of the oxidative stress outcomes induced by propiconazole are 

a result of Cyp2b and Cyp3a induction and uncoupling of the mixed-function oxidase catalytic cycle. 

Antioxidant responses to propiconazole-induced oxidative stress include overexpression of the 

glutathione S-transferase genes: Gsta3, Gstm isoforms 1,2,3 and Gstt, which was confirmed by 

proteomics, western and enzymatic activity measurents where GST activities were increased 1.9-fold 

(Ward et al, 2006, Nesnow et al 2009, Bruno et al., 2009, Ortiz et al., 2010).

Another source of oxidative stress is mitochondrial oxidative stress. Mitochondria are the primary 

source of cellular oxidants due to leakage of electrons to oxygen. Xenobiotics that block electron 
Page 14 of 78

transport can increase the reduction level of carriers located upstream of the inhibition site (Turrens, 

2003). Conazoles (ketoconazole, miconazole and fluconazole) have been found to inhibit various 

enzymes in the respiratory cycle (Rodriguez and Acosta, 1996). Ketoconazole was the most potent and 

was found to inhibit several components of Complex 1 of the respiratory chain (Rodriguez and Acosta, 

1996). Ketoconazole has also been shown to increase ROS production in rats as measured by increases 

in hepatic malondialdehyde formation and reduced GSH content (Amin and Hamza, 2005). 

Mitochondrial function has been studied in primary mouse hepatocytes and mouse and human 

hepatoma cell lines (Hepa1c1c7, HepG2) treated with propiconazole (Chen et al., 2008). Propiconazole 

treatment reduced the mitochondrial reduction of 3-(4,5-dimethythiazol-2yl)-2,5-diphenyl tetrazolium 

bromide (MTT) indicating mitochondrial damage, consistent with oxidative stress. Based on these data, 

it is proposed that the oxidative stress induced by propiconazole is due to a combination of Cyp 

uncoupling and mitochondrial oxidative stress.

The role of oxidative stress in cancer has been reviewed (Klaunig and Kamendulis, 2004). Oxidative 

stress can lead to DNA damage via direct interactions of ROS with nucleic acid bases (e.g. 8-oxodeoxyguanosine) or indirectly through lipid peroxidation products binding to DNA [e.g. M1dG (a 

malondialdehyde deoxyguanosine adduct)]. Oxidative stress can also induce mitogenesis and cell 

proliferation, modulate apoptosis, activate kinases (e.g. protein kinase C), and generally alter gene 

expression. Several transcription factors are activated by oxidative stress, including AP-1 and NFkappaB. 

These factors are involved in both cell proliferation and apoptosis (Klaunig and Kamendulis, 2004). 

g) Induction of in vivo mutation (Causal)

Mice carrying a lac I transgene (Big Blue Mouse®) in each of their tissues were subjected to dietary 

propiconazole treatment at 2500 ppm. Mutational analysis of the transgene recovered from the livers 

demonstrated clear evidence for a 1.97-fold increase in mutant frequency over control mice (Ross et al., 

2009). Moreover, the mutational analyses indicated that the mutation spectra induced by 

propiconazole was different than the mutation spectra in the control mice. Further analyses of the 

propiconazole induced mutants revealed that the CpG dinucleotides had the highest relative 

mutabilities and these results are consistent with the hypothesis that propiconazole-induced mutations 

do not represent clonal expansion of background mutations and support the hypothesis that they arise 

from the accumulation of reactive electrophilic metabolic intermediates within the liver in vivo (Ross 

and Leavitt, 2010). It has been shown that the lacI transgene in Big Blue mice have high levels of 

methylated CpG dinucleotides (You et al., 1998) and that methylated CpG dinucleotides are associated 

with attack by electrophilic species (Monroe et al., 2001). The CpG mutations suggest probable sites for 

DNA modifications on guanine and/or cytosine. Another conazole, penconazole, was found to form 

unidentified DNA adducts in exponentially growing cultures of the yeast, Metschnikowia pulcherrima but 

no adducts were formed when added to the cultures during other growth phases (Jawich et al., 2006). 

DNA modifications that might explain the mutational spectra could be related to the oxidative stress 

induced by propiconazole resulting in DNA oxidation via reactive oxygen species (ROS). These could be 

adducts from lipid peroxidation (e.g. malondialdehyde, 9-noneneal), oxidized bases (e.g. 8-oxodeoxyguanosine, 5-hydroxymethylcytosine) or a small endogenous electrophile. These hypotheses are 

currently being tested. DNA adduct profiles of endogenous adducts in the livers of Big Blue transgenic 

mice induced by propiconazole treatment have been found to be related to its in vivo mutagenic and 

tumorigenic activities (Nelson et al., 2011).
Page 15 of 78

Transcriptomic analyses identified a number of over-expressed genes associated with DNA repair in 

male CD-1 mice fed diets of 2500 ppm propiconazole for 4 days. Apex1 (DNA-(apurinic or apyrimidinic 

site) lyase) was up-regulated 1.5-fold. Apex1, which modulates a number of genes (e.g. TP53, AP-1), is 

regulated by ROS, and is an endonuclease that is involved in the repair of apurinic/apyrimidinic (AP) 

sites. H2afx (H2A histone family, member, X) was up-regulated 2.3-fold and plays a central role in 

transcription regulation, DNA repair, DNA replication and chromosomal stability. Gadd45b was upregulated 22.4-fold and is involved in the control of cell cycle, DNA repair and apoptosis (Thyss et al., 

2005). Transcriptomic analysis of livers from mice fed 2500 ppm propiconazole for 30 and 90 days 

exhibited evidence of a number of up-regulated genes associated with DNA repair (Nesnow et al., 2009). 

At 30 days of treatment Parp2, (poly (ADP-ribose) polymerase family, member 2) was up-regulated 5.7-

fold. Parp2 is involved in the base excision repair pathway, by catalyzing the poly(ADP-ribosyl)ation of a 

limited number of acceptor proteins involved in chromatin architecture. Atr (ataxia telangiectasia and 

Rad3 related) was upregulated 2.6-fold. Atr is a serine/threonine-specific protein kinase that is involved 

in sensing DNA damage and activating the DNA damaged checkpoints, leading to cell cycle arrest (Sancar

et al., 2004). At 90 days of treatment, Atr was up-regulated 4.5-fold. 

h) Dysregulation of cholesterol biosynthesis and 

metabolism through inhibition of Cyp51 (Causal) 

Transcriptomic studies of mRNA from livers of male CD-1 mice treated with propiconazole in the diet 

found a series of genes in the cholesterol biosynthesis pathway that had increased expression (Ward et 

al., 2006). Conazoles were specifically developed to inhibit Cyp51 (lanosterol α-demethylase), a key step 

in the ergosterol and cholesterol biosynthesis pathway (Vanden Bossche et al., 1989; Zarn et al., 2003). 

Propiconazole treatment at 2500 ppm resulted in a persistent decrease in serum cholesterol over a 17 

week period based on three separate studies in different strains and sexes of mice: 4 days (29%) (Allen

et al., 2006), 28 days (64%) (MRID; 42050502), 30 days (24%) (Allen et al., 2006), 56 days (50%); 91 days 

(41%), and 119 days (44-45%)(MRIDs 42050401; 42050501; 42050502; also see Tables Table 2- Table 

4).

Microarray analyses of the mRNA from the livers of mice treated with a number of conazoles indicated 

that the genes involved in the biosynthesis of cholesterol were consistently up-regulated but to differing 

extents, presumably through a negative feedback compensatory mechanism to produce more 

cholesterol. Mice treated with propiconazole (2500 ppm) for 4 days over expressed squalene epoxidase 

(Sqle, 2.6-fold), lanosterol α-demethylase (Cyp51, 1.7-fold) and sterol-C4-methyl oxidase (Sc4mol, 1.6-

fold), 7-dehydrocholesterol reductase (Dhcr7, 1.5-fold).(Table 11, see Appendix B). Cholesterol is 

further metabolized to hydroxylated cholesterols and further converted into bile acids. Metabolomic 

analyses revealed that both 7α-hydroxycholesterol and 7β-hydroxycholesterol levels were increased 2.8-

fold and 1.8-fold, respectively. 7β-hydroxycholesterol is formed from 7α-hydroxycholesterol through 7-

ketocholesterol. 7α-Hydroxycholesterol is further metabolized to a series of bile acids including 

chenodeoxycholate and taurochenodeoxycholate. Taurochenodeoxycholate levels showed a strong dose 

response with propiconazole treatment with a maximum fold increase of 4.8. Chenodeoxycholate levels 

were increased 1.9-fold. Taurocholate levels were not altered and cholate levels were decreased -2.6-

fold (Nesnow et al, 2011). Several genes in these pathways were also upregulated at 4 days of 

treatment: Cyp7a (cholesterol 7α-hydroxylase) 1.8-fold, aldo-keto reductase family 1, member D1 

(Akr1d1, 2.1-fold), and aldehyde dehydrogenase family 1, subfamily A7 (Aldh1a7, 1.8-fold) (Ward et al., 

2006, Nesnow et al., 2009). From proteomic analyses of livers of propiconazole treated mice for 4 days, 

aldo-keto reductase family 1, member D1 (Akr1d1) was increased 1.7-fold and aldehyde dehydrogenase 
Page 16 of 78

family 1, subfamily A1 (Aldh1a1) increased 1.3-fold confirming the transcriptomic results (Ortiz et al., 

2010) These data suggest that propiconazole increased the flux in cholesterol biosynthesis. 

Propiconazole treatment (2500 ppm) induced a non-significant decrease in serum cholesterol levels in 

mice treated for 4 days and statistically significant (55%) decreases after 30 and 90 d (Allen et al., 2006; 

Table 4). There are several explanations for these observations, a general decrease in hepatic 

cholesterol levels reflected in the serum or an inhibition of cholesterol transport. Acyl-coenzyme A 

(CoA): cholesterol acyltransferases (ACATs) are membrane-bound proteins that utilize long-chain fatty 

acyl-CoA and cholesterol as substrates to form cholesteryl esters. ACATs play important roles in cellular 

cholesterol homeostasis in various tissues (Chang et al., 2009). The inhibition of ACAT activity has been 

associated with decreased plasma cholesterol levels (Leon et al., 2005). Transcriptomic data from the 

livers of mice treated with propiconazole indicated significant decreases (-1.7 to -1.9-fold) in Acat1

levels over a 90 day period (Nesnow et al., 2009) suggesting a continued suppression in cholesteryl ester 

formation and transport of cholesterol out of the hepatocyte (Table 12, see Appendix B). It is noted that 

while Ortiz et al, (2010) showed no changes in the expression of Acat2 at 4 days, ACAT2 protein levels 

were up-regulated by 4 days (Ortiz et al., 2010 (Table 13, see Appendix B). 

i) Increase in hepatic mevalonic acid levels (Causal)

Transcriptomic data at 4 day of treatment revealed significant increases in a series of genes within the 

cholesterol biosynthesis and metabolism pathways suggesting a dysregulation of cholesterol 

biosynthesis and metabolism. This creates a situation where the flux of cholesterol biosynthesis is 

increased (Table 12). Cholesterol biosynthesis essentially begins with the action of HMG-CoA reductase 

on 3-hydroxy-3-methylglutaryl-CoA (HMG-CoA) to form mevalonic acid. Mevalonate production is a step 

in the cholesterol biosynthetic pathway, which leads to the formation of isopentenyl pyrophosphate, 

farnesyl pyrophosphate and lanosterol. Farnesylation of ras protein by farnesyl pyrophosphate is a 

posttranslational modification that allows attachment of ras to the plasma membrane. Eventually this 

triggers the ras/MAPK signaling pathway that drives malignant transformation through mutant ras GTP 

complexes (End, 1999). Ras regulates cyclin D1 expression and affects the G1 to S transition and the 

progression of cells through the G1 checkpoint into S phase leading to proliferation. Inhibition of 

mevalonate synthesis would block this process since it has been shown that inhibition of mevalonate 

would prevents farnesylation of p21ras proteins and arrest cell growth of CHO cells (Goldstein and 

Brown, 1990). It is; therefore, hypothesized that cholesterol reduction induces a negative feedback loop 

increasing hepatic mevalonic acid levels that can result in increased cell proliferation. This hypothesis 

has been tested and verified using immortalized mouse hepatocytes (Murphy et al., 2001). As further 

shown in Table 12, the increases in the expression of cholesterol biosynthesis and metabolism genes is 

reduced at 30 days and 90 days of treatment where almost all of the genes are down-regulated.

j) Increased cell proliferation (Causal)

Transcriptomic studies of livers from male CD-1 mice treated with 2500 ppm propiconazole in the diet 

for 4 and 30 days identified a family of genes with altered expression that are associated with different 

phases of the cell cycle. The majority of these genes with altered expression were up-regulated at both 4 

and 30 days (Figure 7, see Appendix B). These patterns of changes seen at 4 days were consistent with 

apical measurements (see below) (Nesnow et al., 2009). Pathway analysis of the same samples indicated 

a series of altered cell cycle related pathways 4 days: Cell cycle: G1/S checkpoint; Cell cycle: G2M 

checkpoint; and Role of APC in cell cycle regulation; 30 days Cell cycle: G2M checkpoint; Influence of Ras 

and Rho on G1 to S transition; Role 14-3-3 proteins in cell cycle regulation (Ward et al., 2006). The 
Page 17 of 78

genomic analysis of Ward et al. (2006) further indicated that propiconazole significantly altered the Wnt 

signaling pathway, which is well known for its role in embryogenesis and cancer, across all time points. 

The cadherin-catenin complexes, which are constituents of the adherens junctions, are important in 

mediating Wnt signaling, and increased β-catenin protein is a common marker for Wnt signaling in 

multiple cancers including liver cancer. After 30 days, propiconazole also altered the 

IGF/PI3K/AKT/PTEN/AKT/PTEN/mTOR pathways, which are critical mediators of oncogenic signaling

Apical data for cell proliferation from the mechanistic studies submitted by the registrant or from the 

open literature appear in Table 3 and Table 4. As shown, increases in cell proliferation commenced on 

day 1 of treatment with 850 or 2500 ppm, peaked on day 2 (49- and 37-fold increase at 850 and 2500 

ppm, respectively), declined on day 3 (19- and 6-fold increase at 850 and 2500 ppm, respectively), and 

returned to baseline on day 14 for both doses. Cell proliferation measurements, using a PCNA antibody 

to identify proliferating cells, were performed on liver tissues taken from male CD-1 mice treated with 

propiconazole in the feed at 0, 100, 500, and 2500 ppm for 4, 30 or 90 days. Mice treated for 4 days 

with 2500 ppm exhibited a significant increase (9-fold) in PCNA stained nuclei (Table 4); mice treated 

for 4 days at 500 ppm, 30 days at 2500 ppm had slight but not significant increases and data for longer 

time periods showed no increase in cell proliferation (Table 14, see Appendix B). The time course of 

these data is consistent with results of Allen et al. (2006) (Figure 7). While the labeling indices for 

propiconazole (by PCNA staining) were not significantly increased compared to control at 30 or 90 days 

(Table 14), changes in cell cycle genes were evident (Figure 8, see Appendix B). These results suggest 

that hepatocytes in these treated mice might be proliferating at low rates that are undetectable by 

PCNA or Ki-67 immunohisto-chemistry assays using labeling indices (Nesnow et al., 2009). 

k) Suppression of apoptosis (Causal)

Apoptosis was not measured in the “classical toxicology” protocols. However, a series of apoptosisrelated genes with altered expression levels were detected by microarray analyses of livers from mice 

fed dietary propiconazole (2500 ppm) for 4, 30 and 90 days ( Ward et al., 2006). All of the following antiapoptotic genes, Gadd45b, Ikbkb, Ikbke, Ikbkg, Hsp70 and Hsp90 (Li et al., 2000; Pandey et al., 2000), 

and Tmbim4, were up-regulated. The pro-apoptotic genes: c-jun, Fas, and TNFsf19 were upregulated at 

4, 30 and 90 days except for c-jun at 30 day, Fas at 4 days and TNFsf19 at 30 days and 90 days which 

were down-regulated. TNF receptor, Fas and c-jun are early steps in the apoptosis pathway, and the upregulation of anti-apoptotic genes in later steps (e.g. Gadd45b, Hsp 70 and Hsp90), will counter the 

actions of these pro-apoptotic genes. These data strongly indicated that at all three timepoints; 

propiconazole suppresses apoptosis in mouse livers. Gadd45b has been reported to mediate the NF-kB 

suppression of JNK-induced apoptosis (Papa et al., 2007). The extremely high levels of induction of 

Gadd45b mRNA at each time point indicated the extremely high levels of protection against apoptosis in 

the livers of propiconazole-treated mice. 

These results suggest a mechanism for reduced apoptosis in propiconazole treated mouse liver which 

focuses on Gadd45b as the key anti-apoptotic protein. After TNF receptor activation through the binding 

of TNF to the TNF receptor (TNFR), the TNF-TNFR complex mediates apoptosis through the formation of 

complex II (recruiting TRADD and FADD) that results in the cleavage of procaspases to caspases (Figure 

9, see Appendix B). The TNF-TNFR complex can also mediate anti-apoptosis through the formation of 

complex I (recruiting TRADD, TRAFs and RIP), which will activate IKK (inhibitor of nuclear factor (NF) B 

(I B) kinase complex) and free NF- B for entry into nuclei, causing rapid transcription of anti-apoptotic 

genes (Papa et al., 2004b; Meier and Vousden, 2007). It has been reported that CAR activation by 
Page 18 of 78

TCPOBOP or phenobarbital, also induces Gadd45b expression through TNF-independent pathway in 

murine liver (Columbano et al., 2005). There is also evidence that Gadd45b mediates the NF-kB 

suppression of JNK induced apoptosis by targeting the MKK7/JNKK2 (Papa et al., 2004a; Papa et al., 

2004b; Papa et al., 2007; Tornatore et al., 2008), and Gadd45b inactivates MKK7/JNKK2 by binding to it 

tightly (Papa et al., 2007). Gadd45b is induced not only by CAR but also by NF-kB (De Smaele et al., 2001; 

Jin et al., 2002). Propiconazole also induces Gadd45b over-expression, the expression of Gadd45b was 

up-regulated about 22-fold after 4 days of treatment, and the levels of induction increased as treatment 

continued. The fold induction reached 52-fold at the 90 day time point. It has been demonstrated that 

Gadd45b is responsible for repressing TNF- induced cell death in the livers of phenobarbital treated 

mice (Negishi 2008). 

Propiconazole treatment up-regulated TNFrsf19 at 30 and 90 days (Ward et al., 2006), and oxidative 

stress has also been reported (Bruno et al., 2009). Both of these effects are possible inducers of the JNK 

pathway, which also induces apoptosis. Although the mechanism of JNK induced apoptosis is not clear, 

there are two possible signaling pathways for JNK. One is through AP-1 (Czaja, 2003) and the other is 

through Bmf (Lei and Davis, 2003). AP-1 is a heterodimer of the Fos and Jun families, including c-Fos, 

FosB, c-Jun, JunB and JunD. The expression of c-Jun and Bmf is altered in the 90-day time point by 

propiconazole indicating a possible alteration in JNK activity. 

l) Tumor induction: 

Male mouse liver tumors were first recorded at the 1-year sacrifice interval and consisted of 11% 

adenomas and 33% carcinomas at 2500 ppm propiconazole versus 9% adenomas and 0% carcinomas in 

the negative control group (MRID 00129570). 

3 Causal relationships between key events and the tumor 

response

To be relevant, key events must be observed at dose(s) lower than or equal to the tumorigenic dose and 

occur at time intervals before tumors are noted. Accordingly, data from the apical and genomic 

endpoints (i.e., toxicogenomics) were combined in Table 5 to develop the causal relationships for the 

dose response and temporal associations of the key events. As shown in Figure 10 (see Appendix B), 

there was no increase in the tumor incidence compared to control at 500 ppm. However at the high 

dose of 2500 ppm, the tumor incidence was significant (p<0.001) increased and reached a combined 

rate of over 85% at study termination. 

Data for the key events are discussed below, compared to the appropriate toxicological and genomic 

profiles and shown in corresponding figures in Appendix B.

a) Dose response of toxicology and toxicogenomic 

responses

(1) CAR-dependent induction of Cyp2b protein and 

enzymatic activities

Cyp2b10 was among the most strongly and consistently responding transcripts to propiconazole 

treatment, measuring ~20- and 45-fold increases at 500 and 2500 ppm, respectively. These 
Page 19 of 78

transcriptional changes also correlated with the liver body weight measures and with Cyp2b10-related 

enzyme activity as measured as PROD at all sampling times (Figure 11, see Appendix B). Similarly, in 

the toxicity profile study of Allen et al. (2006), PROD fold changes (2X, 12X and 13X at 100, 500 and 2500 

ppm, respectively) were remarkably greater than any other measured AROD enzyme activities (Figure 

12, see Appendix B)

A number of genes are associated with PXR activation and Cyp3a is the most representative. Cyp 3a11 

were upregulated by propiconazole at 2500 ppm at 30 and 90 days but not detected at lower doses 

(Ward et al., 2006). Other genes include Cyp2c65 (human ortholog, CYP2C8) and the transporter Abcc. 

Of the group of genes associated with PXR activation, the dose responses for Cyp2c65 and Abcc3 are 

described in (Figure 13see Appendix B). Cyp2c65 were the most responsive transcripts (measuring an ~ 

40-fold increase) to propiconazole treatment. Both genes exhibited a dose response to treatment at 4 

days. Similarly, the significant 6-fold increase in expression of the Cyp2c65 gene, which was observed by 

Chen et al. (2009) using either quantitative real-time polymerase chain reaction (q-RTPCR), is consistent 

with the microarray findings.

(2) Hypertrophy

There is compelling evidence that hypertrophy occurs within 1 day of dosing and at levels below the 

tumorigenic dose (850 ppm, Table 3 and 500 ppm Table 2) in the studies submitted by the registrant. 

Allen et al. (2006) also recorded hypertrophy in 80% of the male mice receiving a dose as low as 100 

ppm within 4 days (Table 5). 

(3) RA metabolism 

Many of the cytochrome P450s (Cyp2b10, Cyp2c55, Cyp2c65, Cyp3a11, Cyp3a13, and Cyp26a1) genes 

that are associated with the metabolism of atRA were also altered over time after feeding diets 

containing propiconazole. The fold changes for five genes over a 90-day period are shown in Figure 14

(see Appendix B). Both Cyp2b10 and Cyp2c65 demonstrated strong up regulated dose responses to 

propiconazole treatment (≈20- to 50-fold), while Cyp3a13 showed modest increases (≤2-fold). Chen et 

al. (2009) also demonstrated a 45% reduction in atRA levels in mice when 2500 ppm was delivered in 

the diet. Thus, the data from these two approaches agree; it is, therefore, likely that the depletion in 

retinoic acid would potentially lead to cell proliferation. 

(4) Oxidative stress/DNA damage

Genes associated with oxidative stress (Gstm1, Gstm2, Gstm3 and Gstt3) were analyzed for their dose 

response to propiconazole treatment. Many of these genes exhibited a dose response over multiple 

days of treatment (Figure 15 see Appendix B). Oxidative stress measurements have also been 

determined at 2500 ppm of propiconazole (protein carbonyls, GSSG/GSH ratio, GST activity). At 4 days 

of treatment, a significant and ~2-fold increase in GST activity was reported by (Bruno et al., 2009). 

The expression levels of Gadd45b, which is associated with DNA damage, were present at 4, 30, and 90 

days of treatment and at all propiconazole doses. Gadd45b is a gene that signals DNA damage and also 

has anti-apoptotic functions. Atr (Ataxia telangiectasia and Rad3 related) kinases, which were slightly 

altered at 90 days, are activated by DNA damage. Atr complexes with other proteins to initiate the DNA 
Page 20 of 78

damage checkpoint by phosphorylating a number of key proteins. Once activated, the checkpoint leads 

to cell cycle arrest and either DNA repair or apoptosis. (Figure 16, see Appendix B). 

(5) Induction of in vivo mutations 

Propiconazole induced a 2-fold increase in the mutant frequency 4 days after exposure of lacI transgenic 

mice to the tumorigenic dose of 2500 ppm; no other dose was tested. The marked increase in overexpression of Gadd45b (Figure 16) at 4 days, which was just discussed, provides genomic support for 

the causal relationships of this event. However, all of the conventional genetic toxicology tests were 

negative. 

(6) Dysregulation of cholesterol biosynthesis and 

metabolism through inhibition of Cyp51

A number of cholesterol biosyntheses and metabolism genes were upregulated at the tumorigenic dose 

of propiconazole (Table 11). Another marker for this dysregulation are serum cholesterol levels, which 

were significantly lower than control at ≥850 ppm propiconazole and manifested as early as 4 weeks, 

have been shown to be dose dependent (Table 2). Expression of cholesterol biosynthesis genes at 500 

ppm at 4 days of propiconazole treatment showed no compound effect or in somes cases were 

suppressed. The levels of hydroxylated cholesterols (7α-hydroxycholesterol and 7β-hydroxycholesterol) 

and several bile acids were increased at 1250-2500 ppm propiconazole treatment at 4 days (Nesnow et 

al., 2011). 

(7) Cell proliferation

Two genes, Eif4e and Bag3 were selected, as representative of the cell proliferation regulatory family of 

genes, and was compared to the cell proliferation response reported by Allen et al. (2006) using PCNA 

immunohistochemistry. Eif4e is a crtical node in an RNA regulon that controls cell proliferation and is 

associated with cyclin B1, ornithine decarboxylase, Pim1, and c-Myc (Culjkovic et al., 2006). The most 

effective gene response, which was with the Bag3, was ~3.5- and 2.5- fold increased at 2500 and 500 

ppm, respectively (Nesnow et al., 2009; Figure 17, see Appendix B). By contrast, fold increases in the 

labeling index were increased within one day of treatment with 850 or 2500 ppm (19 and 10-fold, 

respectively) and 5X higher than control at 500 ppm after 4 consecutive days of feeding dietary levels of 

propiconazole (Table 3 and Table 4). 

(8) Apoptosis

Gadd45b and Ikbke have anti-apoptotic functions while Fas has pro-apoptotic activities. These data are 

presented in Figure 18 (see Appendix B) for all propiconazole doses tested at 4, 30, and 90 days of 

treatments. Up-regulation of Gadd45b occurred at all time points while the other two genes (Ikbke and 

Fas) had different effects at different times; these findings suggest an overall suppressioin of apoptosis. 

No apical data were available for this endpoint.

(9) Tumor induction

A significant (p<0.001), 86% increase in the combined incidence of hepatocellular tumors (adenomas 

and carcinomas) was reported in male mice receiving dietary preparations of 2500-ppm propiconazole 
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in the long-term feeding study (MRID No. 00129570; also see Table 1, Appendix B). The combined 

incidence at the low dose (500 ppm) was lower than the control value. 

b) Temporal association of toxicology and toxicogenomic 

responses

The temporal responses of the key events in relationship to tumor formation are also summarized in 

Table 5 (see Appendix B). All of the key events, whether apical or genomic, that lead to tumorigenesis, 

occurred early after treatment commenced (4 days). Although apical evidence of increased cell 

proliferation was apparent after 1- 4 days in the timeline, it is important to note that the earliest 

sampling time for the genomic data was 4 days. It is, therefore, conceivable that alterations in genes 

associated with cell proliferation would likely be expressed 1 day posttreatment. As further shown in 

Table 5, many of the key events continue to be present up to 90 or 119 days of treatment. Although the 

sequence of the key events is complex, what is, however, clear from the data is that propiconazole 

activates CAR and PXR nuclear receptors leading to hepatic hypertrophy, increased Cyp2b and Cyp3a 

levels and enzymatic activities. Since many of the toxicogenomic and apical events were recorded at 4 

days and the exact time each took place within this narrow window is unknown, we envision that Cyp 

induction would then leads to increased oxidative stress, which in turn can causes DNA damage and 

induction of gene mutations. Cyp induction would also cause an increase in the metabolism of atRA, 

which would be followed by a reduction in hepatic atRA levels. Based on published information the 

reduction in retinoic acid levels can lead to an increase in cell proliferation. While not directly 

measured, propiconazole treatment is proposed to suppress apoptosis based on genomic data. Finally, 

propiconazole reduces serum cholesterol levels at 30 and 90 days and at 4 days there is a concomitant 

increase in the expression of genes involved in cholesterol biosynthesis and metabolism. Each of these 

events has been directly or indirectly linked to the tumorigenesis process, and occurred long before 

tumors are detected at either the tumorigenic or lower doses. 

4 Strength, consistency, and specificity of association of tumor 

response with key events 

Several lines of evidence suggest that many of the key events in propiconazole that induced mouse liver 

carcinogenesis are consistent with tumor development. The logic supporting this conclusion is 

presented below: 

a) CAR-dependent induction of Cyp2b protein and 

enzymatic activities

Knock-out CAR mice do not develop liver tumors after a dimethylnitrosamine initiation-phenobarbital 

promotion regimen indicating that CAR is necessary for mouse liver tumor promotion (Yamamoto et al., 

2004). Furthermore, activation of the nuclear receptors CAR and PXR has been shown to lead to the 

over expression of Cyp2b and Cyp3a mRNA, proteins and enzymatic activity and associated oxidative 

stress with a strong indication of the involvement of Cyp2b subfamily enzymes (Dostalek et al., 2007). 

b) Retinoic Acid Metabolism

atRA has been shown to inhibit the morphological transformation of cells in vitro (Lotan, 1996) and the 

proliferation of hepatocellular carcinoma cells in culture (Alisi et al., 2003). atRA treatment was found to 
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inhibit liver tumorigenesis in rats initiated with N-nitrosomorpholine and retinoids reduced spontaneous 

liver carcinogenesis in several mouse strains (Lotan, 1996). All of these effects have been ascribed to 

atRA’s effects on cell proliferation, apoptosis, and it its ability to induce differentiation. It is reasonable 

to assume that cell proliferation would increase in cells and tissues where retinoic acid levels are 

decreased. 

c) Oxidative Stress

Propiconazole induces oxidative stress in hepatic tissues as evidenced by increased gene expression of 

anti-oxidant genes, depletion of antioxidants, and increases in protein oxidation. Oxidative stress has 

been linked to cancer induction through alterations in DNA, signaling pathways, intercellular 

communication, protein kinase activity, membrane structure and function, and gene expression 

associated with cell proliferation (Klaunig et al., 1995; Klaunig et al., 1998). Propiconazole treatment of 

mice induces hepatic ROS formation and oxidized proteins. ROS formation has been associated with lipid 

peroxidation and the formation of lipid peroxidation products (Marnett, 2002). Malondialdehyde, a lipid 

peroxidation byproduct, is mutagenic in human cells (Niedernhofer et al., 2003). Patients with cancer 

prone liver disease excrete high levels of lipid peroxidation-derived DNA adducts including 

malondialdehyde-DNA adducts (Nair et al., 2009).

d) DNA Damage/ Induction of In Vivo Gene Mutations 

Mutational events are a hallmark of cancer and are caused by DNA damage. Mutations in critical tumor 

oncogenes or tumor suppressor genes have been linked with cancer in experimental animals and in 

humans (Ross and Nesnow, 1999; Pfeifer and Besaratinia, 2009). Mutations in the TP53 gene in liver 

have been associated with hepatocellular carcinoma in humans (Hussain et al., 2007). Although 

propiconazole is not directly genotoxic, it is mutagenic suggesting DNA damage by an indirect process 

leading to mutation.

e) Dysregulation of cholesterol biosynthesis and 

metabolism through inhibition of Cyp 51/ Increased 

mevalonic acid levels

Conazoles inhibit Cyp51 by preventing the demethylation of lanosterol and ultimately dsyregulate 

cholesterol biosynthesis and metabolism as evidenced by reduced serum cholesterol levels. There is 

genomic evidence for a compensatory feedback mechanism to biosynthesize more cholesterol. One of 

these lanosterol precursors is mevalonic acid. Mevalonic acid has been shown to promote the growth of 

human tumors in nude mice and human cancer cells in culture (Duncan, 2004). Blocking 3-hydroxy-3-

methylglutaryl-CoA reductase and mevalonate production suppresses DNA synthesis specifically during 

the S phase of the cell cycle in synchronized BHK cells (Quesney-Huneeus et al., 1979). Other studies 

have shown that there is a critical time period, several hours before S phase, when PDGF-stimulated 

human fibroblast cells require mevalonate in order for DNA synthesis to proceed (Fairbanks et al., 1984). 

Further studies have shown that growth regulating ras p21 proteins are farnesylated and inhibition of 

mevalonate synthesis prevents farnesylation and blocks cell growth (End, 1999). These findings are 

consistent with a role for mevalonic acid in cell proliferation. From the genomic data, it is proposed; 

therefore, that hepatic mevalonic acid and downstream lanosterol precursors are over-produced and 

this would exert a pro-growth effect in hepatic tissues from propiconazole treated mice.
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f) Cell proliferation

Propiconazole increases cell proliferation and suppresses apoptosis in mouse liver. Self-sufficiency in 

growth signals, insensitivity to anti-growth signals, and evasion of apoptosis have been described as 

hallmarks of cancer. These are characteristics of many types of tumor cells and are a result of the 

multistep cancer process in which cells evolve from normalcy to malignancy (Hanahan and Weinberg, 

2000). The combined effects of ROS induction, apoptosis inhibition and enhanced cell proliferation, 

would, therefore, increase the probability of initiated cells not being repaired or removed.

Based on these considerations, we conclude that there is strong and consistent evidence that the key 

events outlined for propiconazole are linked to the liver tumor development in mice. 

5 Biological plausibility and coherence

Activation of the nuclear receptors CAR and PXR have been shown to lead to the over expression of 

Cyp2b and Cyp3a mRNA, proteins and enzymatic activity. The increased activities of Cyp2b, Cyp3a as 

well as other CYPs (e.g., Cyp2c55, Cyp2c65) have been shown to induce oxidative stress (Bruno et al., 

2009) and increase the metabolism of atRA (Chen et al., 2009). This increase in enzymatic activities of 

these Cyps has been linked to a decrease in hepatic atRA levels in propiconazole-treated mice and an 

increase in oxidative stress through ROS production as measured by increased protein oxidation, 

decreased hepatic GSH/GSSG ratio and increased expression of GST proteins and GST enzymatic activity 

(Bruno et al., 2009). ROS could damage DNA directly or through the adduction of lipid peroxidation 

products (Marnett, 2002; Niedernhofer et al., 2003). Similarly, apoptosis was decreased based on 

analyses of the gene expression studies. This provides defective cells with a decided advantage to confer 

their damaged DNA to daughter cells. The data suggest that this is the case since decreased apoptosis is 

known to be highly associated with the carcinogenesis process (Hanahan and Weinberg, 2000).

An increase in mutation frequency in livers of mice treated with propiconazole is suggested to be key 

event in propiconazole induced carcinogenicity (Ross et al., 2009). While the type of DNA damage 

leading to this mutation is not presently known, the concomitant induction of oxidative stress by 

propiconazole in the livers of mice suggests an action associated with the oxidation of DNA or lipid 

peroxidation leading to DNA damage. 

Hepatic cell proliferation was increased by propiconazole (Allen et al., 2006) and this could be associated 

with decreased hepatic atRA levels (Alisi et al., 2003). Serum cholesterol levels were decreased by 

propiconazole and gene expression analysis indicated the over expression of several enzymes involved 

in the biosynthesis of cholesterol (Allen et al., 2006; Ward et al., 2006). Mevalonic acid, a cholesterol 

biosynthetic intermediate, is known to increase the growth of tumor cells (Duncan et al., 2004). It is 

possible, therefore, that there is an increased flux in cholesterol biosynthesis and metabolism producing 

more mevalonic acid and downstream metabolites (e.g. farnesyl diphosphate), which increase 

farnesylation of oncogenic ras proteins. This scenario can lead to increased cell replication in the livers 

of propiconazole treated mice. 

6 Alternative modes of action

Because propiconazole has a toxicology profile of liver tumors in male mice, several known modes of 

action associated with mouse liver tumors were considered as possible alternatives to the MOA 
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proposed for propiconazole. These include: direct mutagenesis, PPARα induction, hormone disruption, 

phenobarbital-like response and cytotoxicity and regenerative cell proliferation.

a) Direct mutagenesis 

One of the proposed key events in the mode of action of propiconazole is the induction of mutations in 

the liver. Propiconazole is predominantly negative in a wide range of standard tests for genotoxicity and 

is not severely cytotoxic (Table 15, see Appendix B). Based on these results it is concluded that 

propiconazole (or its metabolites) do not directly interact or bind to DNA. However, propiconazole 

increases the mutation frequency in the livers of transgenic mice fed tumorigenic levels of 

propiconazole. These mutations are more likely a result of propiconazole affecting a downstream 

process such as inducing reactive oxygen species (ROS), which can damage DNA. 

Propiconazole is predominantly negative for direct mutagenesis in conventional in vitro and in vivo 

genetic toxicology assays. Similarly, conazoles in general are not considered to pose a mutagenic concern 

(Table 16, see Appendix B). Based on these results it is concluded that propiconazole (or its 

metabolites) do not directly interact or bind to DNA. However, propiconazole increases the mutation 

frequency in the livers of transgenic mice fed tumorigenic levels of propiconazole. These mutations are 

more likely a result of propiconazole affecting a downstream process such as inducing reactive oxygen 

species (ROS), which can damage DNA. Since oxidation of DNA appears to occur after CAR activation, it 

is not likely that these are the key events that initiate the tumorigenic process. Additionally, mutagenic 

liver carcinogens are expected to elicit a tumorigenic response in multiple organs and species and in 

both sexes. This is inconsistent with the tumor profile for propiconazole.

b) PPARα induction 

The hallmarks of PPARα induction are: hepatomegaly as measured by increased liver weights and 

increases numbers of peroxisomes; increased levels of enzymes involved in peroxisiomal fatty acid 

metabolism and cell proliferation. Propiconazole did induce liver hypertrophy; however, the genomic 

analysis clearly shows that levels of Pparα were under expressed by propiconazole 11.3-fold. Moreover, 

increased peroxisomal activity was not indicated as there was decreased expression of a gene producing 

the microsomal fatty acid-oxidizing enzymes which belong to the CYP4A subfamily of cytochrome P450: 

Cyp4a10 was under expressed 4.7-fold. Finally lauric acid hydroxylation, specifically a result of 

peroxisome proliferation, was not induced by propiconazole. Hence, these data are inconsistent with 

the toxicogenomic profile of propiconazole.

c) Hormone disruption 

No data suggesting that hormone disruption was a possible mode of action for the propiconazoleinduced liver tumors were found.

d) Phenobarbital-like response 

The genomic data of Nesnow et al. (2009), comparing the transcriptional responses of mouse livers to 

treatment with the tumorigenic doses of propiconazole and phenobarbital, are presented in Section E 2. 

These findings show evidence that mice treated with propiconazole have a substantially different 

pattern of gene expression than mice treated with phenobarbital. For example, phenobarbital produced 
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1814 differentially expressed genes (DEG) as opposed to propiconazole, which produced 1021. 

Differences also exist between both pathways and networks for these two agents. Many phenobarbital 

altered pathways, particularly growth signaling pathways were not altered by propiconazole. 

Correspondingly, many growth signaling pathways altered by propiconazole were not altered by 

phenobarbital. Marked differences in cell cycle gene alterations are also apparent (Figure 19, see 

Appendix B). Examples include: the overexpression of Chaf1b, Gadd45a, Srd5a1 and Wisp1 and the 

under-expression of Sdc1 and Tsn by phenobarbital but not by propiconazole at 4 and 30 days. This is 

further contrasted by the alteration of Kpnb1, Stat5b, and Tmpo by propiconazole at 4 or 30 days but 

not by phenobarbital. Similarly, the analysis of concordance of specific genes identified in the human 

hepatocellular carcinoma (HHC) compilation and those found in the livers from propiconazole treatment 

but not from phenobarbital treatment revealed concordance for Ass1, C9, Cxcl12, Pgd, Fat10, and Fst. 

The authors consider the overexpression of Fat10, and Fst in both the HCC compilation and the mouse 

livers treated with propiconazole as potential biomarkers for the human relevance evaluation. Overall, 

these data do not support the phenobarbital-like response as a credible alternative MOA.

e) Cytotoxicity and regenerative cell proliferation

Histological analyses of the livers from mice after 4, 8, and 13 wks of treatment with propiconazole 

(2500 ppm) revealed evidence for monocellular necrosis and necrosis which was classified as mild to 

moderate (Table 17, see Appendix B) suggesting that this MOA was not operative. 

Based on these considerations, direct mutagenesis, PPARα induction, hormone disruption, the 

phenobarbital-like response, and cytotoxicity and regenerative proliferation, are not consistent with the 

data and, therefore, ruled out as possible MOAs for the mouse liver tumor induced propiconazole.

7 Human relevance following the IPCS framework

The IPCS framework for analyzing the relevance of a cancer mode of action for humans established an 

approach that enables the evaluation of the relevant general scientific information along with chemical 

specific data to determine if a series of biological events that are associated are causally linked to a 

tumorigenic response in an animal model could plausibly occur in an appropriately exposed human. 

This framework requires the answer to a series of questions. The first two are qualitative and set the 

stage for a quantitative evaluation of the data for human health risk (Boobis et al., 2006). 

The first question is “Is the weight of evidence sufficient to establish a mode of action (MOA) in 

animals?” This question was addressed in the previous sections and it is the opinion of the current 

authors of this document that there is indeed sufficient information for the establishment of the 

proposed mode of action in the mouse liver after chronic exposure to propiconazole. 

The second question is “Can human relevance of the MOA reasonably be excluded on the basis of 

fundamental, qualitative differences in key events between experimental animals and humans?” The 

present section makes the case that the key events proposed for the animal mode of action cannot be 

excluded in humans; data supporting this position are presented in Table 18(see Appendix B).
Page 26 of 78

a) Activation of nuclear receptors/Increased Cyp2b and 

Cyp3a

The nuclear receptors in mice, mCAR and mPXR, have human counterparts, hCAR and hPXR. Although 

there are differences in the mouse and human gene sequences (Krasowski et al., 2005), both human and 

mouse genes are similarly activated by a number of the same ligands and induce the 2B and 3A families 

of CYPs in hepatocytes (Maglich et al., 2002; Kharasch et al., 2004; Grimm et al., 2006; Plant, 2007 

Biochim Biophys Acta 1770:478-88). For example the CYP3A family of metabolizing enzymes are 

similarly present is several tissues such as the liver and intestine in humans and laboratory animals 

including the mouse. The CYP3A family is one of the most abundant in human liver and is involved in 

the metabolism of many drugs (Lewis et al., 1998; Wang et al., 2008). In fact, CYP3A represents up to 

30-60% of the total P450 in human liver (Shimada, 1994). There is incidental evidence that PXR ligands 

induce CYP3A4 in humans and contribute to lower ATRA levels (De Botton et al 1998). While the 

magnitude of metabolic capability may be different across species, qualitatively the spectrum of 

substrates and active metabolism is similar (Komura and Iwaki, 2008). 

b) Increased hepatic hypertrophy

As shown in virtually every “classical” toxicology study sponsored by the registrant (Table 3 and Table 

2) plus the open literature studies (Table 4), hypertrophy in the mouse liver is apparent. Similarly, liver 

hypertrophy in humans has been shown to accompany activation of nuclear receptors activation 

(Holsapple et al., 2005). 

c) Increased atRA metabolism/decreased hepatic RA levels

Retinoids have been shown to inhibit cell proliferation in a variety of human cells in culture including 

hepatocellular carcinoma cells (Klaassen et al., 2001; Alisi et al., 2003; Tatebe et al., 2008). Retinoic acid 

inhibits squamous metaplasia and is used as a chempreventive agent for epithelial carcinogenesis 

(Hansen et al., 2000). Retinoids have also been used as chemotherapeutic agents for epithelial cancers 

such as ovarian and mammary in humans (Zhang et al., 2000; Yang et al., 2002). These data suggest that 

decreased availability of retinoids would be pro-proliferative in the affected tissues.

d) Oxidative stress

Oxidative stress and the production of ROS have been associated as factors in human liver diseases and 

cancer (Tien Kuo and Savaraj, 2006; Lu and Cederbaum, 2008). Increased ROS levels were found in liver 

biopsies of patients with chronic hepatitis and at different stages of malignancy. Reduced expression 

levels of superoxide dismutase showed strong correlations with the progression of hepatocellular 

carcinoma. ROS-induced DNA damage, as measured by the formation of 8-oxo-dG in adjacent liver 

lesions, was found in 23 patients (Tien Kuo and Savaraj, 2006) and patients with cancer-prone liver 

diseases had high levels of lipid peroxidation-derived DNA damage in their urine (Nair et al., 2009). 

e) DNA damage/Induction of in vivo mutations

As mentioned above, ROS induces DNA damage and DNA damage can lead to mutations in animals and 

humans. DNA damage is the primary tenant of cancer being a disease of gene mutations. Therefore, this 

event is highly plausible in humans.
Page 27 of 78

f) Dysregulation of cholesterol biosynthesis/metabolism 

through inhibition of Cyp 51

Lanosterol-14 α-demethylase (CYP51) is required for sterol biosynthesis and is the most widely 

distributed P450 found in all biological kingdoms with its function being evolutionarily conserved 

(Lepesheva et al., 2003; Lepesheva and Waterman, 2004). Hence, the likelihood of dysregulation of 

cholesterol biosynthesis and metabolism leading to a decrease in serum cholesterol in humans is highly 

plausible.

g) Cell proliferation

Compelling data have been presented from the mouse mechanistic studies and from the genomic 

analysis of increased cell proliferation occurring early (within 1 day), peaking early (by day 2) and 

returning to baseline within 1 to 2 weeks. This is the expected response for a liver mitogen in all 

mammals. Thus, the plausibility of this event occurring in the human is very strong. 

h) Suppression of apoptosis 

Although apoptosis was not measured in any of the classical toxicology studies, there are adequate 

microarray data pointing to a series of apoptosis-related genes with altered gene expression in the livers 

of mice treated with propiconazole (Ward et al., 2006). In the same way, the inability to remove cells 

with severe DNA damage in human tissues is an accepted step in the process of tumor formation. 

Consequently, it is plausible that this event will also take place in humans exposed to propiconazole. 

From these data on human cell systems and tissues and the similarities across species for the major 

molecular pathways perturbed in the early phases in this MOA, it would seem logical that qualitatively 

the animal mode of action for mouse liver tumors is biologically plausible in human tissues. 

The third and critical question in the IPCS Human Relevance Framework is “Can human relevance of 

the MOA be reasonably excluded on the basis of quantitative differences in either kinetic or dynamic 

factors between experimental animals and humans?” This is a much more difficult question and 

requires a more substantial data set. In the case of toxicokinetics, the data are not available to compare 

human tissue levels with the rodent models. However, the rodent and in vitro data suggest that it is the 

tissue concentration of the parent propiconazole and not a metabolite that initiates the cascade of 

events leading to mouse liver tumors. Therefore, it would be plausible to suggest that if sufficient 

propiconazole were present in the liver, in the hepatocytes, then the cascade of events could be 

initiated in humans. The specific concentration needed to initiate that process is not known. The data 

to suggest an answer to the second part of the question about toxicodynamic differences suggests that 

humans may be less, or at worst, no more sensitive than the mouse because the potency is far less for 

establishing an inhibitory concentration for human CYP51 than fungal CYP51. Recombinant human 

CYP51 enzyme did show inhibition with a battery of conazole fungal agents used for agricultural and 

pharmaceutical purposes leading to altered human steroid biosynthesis (Trösken et al., 2006). These 

data suggest that the dose needed to inhibit CYP51 in the target species, fungi, is far less than what is 

needed to inhibit the same enzyme in human cells. One human study found that low doses of 

fluconazole did not affect serum cholesterol levels (Devenport et al., 1989), however, there is little 

available human data on the effects of conazoles at higher doses. Nevertheless, the analysis comparing 

transcriptomic profiles of propiconazole and phenobarbital at tumorigenic doses strongly points to the 

conclusion that this mouse hepatotumorigenic agent exerts its tumorigenic activity through a different 
Page 28 of 78

MOA (Nesnow et al., 2009). The implications of these findings are that while there is epidemiological 

evidence that phenobarbital does not induce human liver neoplasia; propiconazole’s potential effects in 

humans have yet to be ascertained. 

8. Uncertainties and limitations in the database

While the database on propiconazole is rich and provides more than adequate support for the 

hypothesized MOA, one major uncertainty has been uncovered. The consistent lack of genotoxic effects 

of propiconazole using standard gene-tox test results compared to the positive in vivo transgenic mouse 

mutation assay is a source of uncertainty regarding a potential mutagenic MOA. It is assumed that the 

lack of genotoxic activity of propiconazole in standard test battery is due to its inability to adduct 

directly with DNA and induce DNA damage and mutations. However, the data do show that 

propiconazole induces significant oxidative stress that can lead to DNA modifications, DNA damage and 

mutations. Over-expression of DNA damage response genes has been detected in the microarray 

analysis. Similarly, Nelson et al. (2012) measured the spectra of endogenous DNA adducts in the livers 

of mice treated with propiconazole in the mouse transgenic assay (TGA) and found the same 13 adducts 

in the treated compared the control liver samples. While these adducts were the same qualitatively, 

they differed quantitatively, with higher levels associated with the livers from propiconazole dosed 

mice. The mutations that occurred in the in vivo transgenic mouse assay are likely a result of 

propiconazole affecting a downstream process such as inducing reactive oxygen species (ROS), which 

can damage DNA, and produce DNA adducts. 

Using the weight-of-the-evidence and sound scientific judgment, however, it is concluded that the 

overall quality and quantity of the studies in the database is high and that there are no weaknesses in 

the database that would limit the MOA analysis. Therefore, it is concluded that propiconazole acts 

through a series of mitogenic and other events that lead to hepatocarcinogenicity in the mouse. The 

molecular initiating event is CAR/PXR nuclear receptor activation followed by the key events of: Cyp 

induction, effects on retinoic acid and mevalonic acid levels, oxidative stress, in vivo mutagenicity, cell 

proliferation, suppression of apoptosis and tumor induction. 

The overall study also showed that “omics” data were instrumental in expanding the apical endpoint 

analysis, identifying key events that were missed in the apical endpoint analysis, and eliminated an 

alternative MOA that may have had implications for human relevance determination.
Page 29 of 78

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Page 34 of 78

APPENDIX - B Tables and Figures

Use of “Omic” Technology to Inform the Risk Assessment

Support Document for Case Study: Propiconazole
Page 35 of 78

TABLES

Table 1. Hepatocellular Tumors in Male Mice Receiving Dietary Levels (ppm) 

ofPropiconazole for 2 years a

0 500 2500

Adenomas

(%)

P value

13/64

(20)

0.00*

12/62

(19)

0.514

28/56 

(50)

0.000**

Carcinomas

(%)

P value

14/60

(20)

0.028*

11/58

(19)

0.801

20/54

(37)

0.05

Combined 

Adenomas/Carcinomas (%)

P value

27/63

(43)

0.000**

23/62

(37)

0.718

48/56

(86)

0.000**

 a Data were derived from Long Term Feeding Study in Mice (2 years) (MRID 00129570)

 Significance of trend denoted at Control.

 Significance of pair-wise comparison denoted at dose

If * then p<0.05 and if ** then p<0.001 by Peto’s Prevalence Test.
Page 36 of 78

Table 2. Summarized Key Events Associated with Tumor Induction in Male Mice Fed Diets Containing Propiconazole

(Submitted Studies) a b

Key Event Dose 

(ppm) Weeks

4 8 9 13 14 17 52-53 78 100

MRID -502a-502a-401a-502a-501a-401a-501a-401 a570a-401a-570a

↑Liver/Body 

Weight 500 b

- - 10% 18% - - - 13% 12% 10% 6%

850 - - 33% 34% - - - 29% - 20% -

1450 - - - 56% - - - - - - -

2500 - - - 94% - - - - 41% - 50%

↑Hypertrophy 

500 b100% 80% c60% c80% - - 20% 60% 18% d56% 33% d

850 90% 100% 100% 100% - - 70% 80% - 58%

1450 100% 100% - 100% - - 100% - - -

2500 90% 100% - 100% - - 100% - 78% d- 86% d

↓Serum 

Cholesterol 500 b NC NC -11% NC NC -14% -12% -15% -15% -24% -6%

850 -29% -9% -25%- -30% -10% -24% -24% -34% - -29% -

1450 -37% -49% - -39% -42% - -45% - - - -

2500 -64% -50% - -45% -41% - -44% - -28%- - +44%

Single cell 

necrosis 500 b

40% 80% 10% 25% - - 0 0 0 0 0

850 70% 40% 30% 65% - - 0 0 0

1450 90% 90% - 90% - - 10%

2500 90% 90% - 100% - - 60% 0 0

Necrosis

500 b10% 10% 30% 25% - - 10% 0 0 0 0

850 30% 0 -50% 15% - - 20% 0 0

1450 30% 50% - 30% - - 40%
Page 37 of 78

Key Event Dose 

(ppm) Weeks

4 8 9 13 14 17 52-53 78 100

MRID -502a-502a-401a-502a-501a-401a-501a-401 a570a-401a-570a

2500 70% 60% - 30% - - 60% 0 0

Tumorsf 

500 b10% 37%

850 24%

1450

2500 86%

a Data were derived from MRID Nos. 42050502, 42050401, 42050501, 45215801, and 000129570.

b Results for lower doses (≤ 100 ppm) were generally comparable to the vehicle control group. /10 = number of animals

c MRID 45215801: reread of histological slides from MRID 42050502 (8-week) and 44381401 (9-week)

d Listed as “hepatocyte enlargement, presumed to be hepatocyte hypertrophy.

f Combined adenomas and carcinomas
Page 38 of 78

Table 3. Summarized Key Events Associated with Tumor Induction in Male Mice Fed Diets Containing Propiconazole (Submitted 

Mechanistic Studies) a b

Key Event Dose 

(ppm) Days

Reference

1 2 3 4 7 14 28 60

CARc Activation

Total P450 850 3X d 45215803

2500 3.9X

EROD 850 2.2X

2500 3.9X

PROD 850 30X

2500 55X

Coumarin 7-

hydroxylase

850 5X

2500 24X

UDPGT 850 1.6X

2500 1.4X

Cytosolic GST 850 1.6X

2500 1.8X

Liver/Body 

Weight

850 1.3X

2500 2X

850 1.1X 1.3X 1.3X 1.3X 1.3X 1.3X 1.4X 1.3X 45215802

2500 1.2X 1.4X 1.5X 1.7X 1.9X 2.1X 2.3X 2X

Hypertrophy 850 Mi Mi Mi Mi Mi Mi Mo-Ma Mo-Ma

2500 Mi Mi Mi Mi Mi Mi Mo-Ma Mo-Ma

Cell Proliferation 850 19X 37X 6X 5X <1X <1X <1X <1X

2500 11X 50X 19X 10X 8X 1X 2X 1X

a Data were derived from MRID Nos. 45215802 and 45215803.

b n generally = 5 mice/group.

c Abbreviations:

CAR = Constitutive androsane receptor UDPGT = Uridine diphosphate glucuronosyl-transferase EROD = Ethoxyresorufin O-dealkylase

GT = Glutathione S-transferase PROD = Pentoxyresorufin O-dealkylase Mi = Minimal Mo-Ma = Moderate-Marked

d Fold increase
Page 39 of 78

Table 4. Summarized Key Events Associated with Tumor Induction in Male Mice Fed Diets Containing Propiconazole

(Submitted Mechanistic Studies From the Open Literature) a,b

Key Event Dose 

(ppm))

Dose

(mg/kg/da)

Days Reference

4 14-15 30 90

Activation of Nuclear Receptor: CAR/PXRd 

EROD 500 50 1.7Xc1.8X Allen et al., 2006

75 1.2X Sun et al., 2005

150 1.3X Sun et al., 2005

2500 350 2.1X 3.1X 4X Allen et al., 2006

PROD 500 50 11.6X 14.0X 10.9X Allen et al., 2006

75 3.5X Sun et al., 2005

150 5.4X Sun et al., 2005

2500 350 13.3X 37.5X 35.9X Allen et al., 2006

Cyp2b10 500 50

75

150 2.4X

2.6X

Sun et al., 2005; 

Goetz et al., 2006

2500 350 -- -- -- --

Cyp2c55 150 27.6X Goetz et al., 2006

2500 350 -- -- -- --

4 14-15 30 90

150 5.2X Sun et al., 2005

Cyp3a11 2500 350 -- -- -- --

↑ Liver Weight

500 50

75

150 1.5X

1.4X

Sun et al., 2005 

Goetz et al., 2006

2500 350 1.4X 1.9X 1.95X Allen et al., 2006 

Bruno et al., 
Page 40 of 78

Key Event Dose 

(ppm))

Dose

(mg/kg/da)

Days Reference

1.3X

2009

Liver Hypertrophy

100 10 80% 60% 60% Allen et al., 2006

500 50 60% 80% 100% Allen et al., 2006

75

150

2500 350 100% 100% 100% Allen et al., 2006

↑atRA/↓Hepatic Retinoic Acid Levels

2500 350 55%↓

Chen et al., 2009

↑Cell Proliferation

500 50

2500 350 9X 6X 1.8X Allen et al., 2006

a Data were derived from Allen et al. (2006); Sun et al. (2005); Goetz et al.(2006); Chen et al. (2009) and Bruno et al. (2009),

b N = 4-12 mice’group (Allen et al., 2006); 4 mice/group (Sun et al., 2005) 6 mice/group (Goetz et al., 2006); 3 mice/group (Chen et al., 2009); and

5-12 mice/group (Bruno et al., 2009).

c Values expressed as X= fold increase over control: values expressed as % = % of control.

d Abbreviations:

CAR = Constitutive androsane receptor

RXR = Retinoid X receptor

PXR = Pregnane X receptor

EROD = Ethoxyresorufin O-dealkylase

PROD = Pentoxyresorufin O-dealkylase
Page 41 of 78

Table 5. Temporal association- toxicology, genomic and proteomic studies with tumorigenesis

Time, d (feed levels)

Key event 1 2 3 4 7 14 28/30 56 90 119 2yr

CAR/PXR Activation G, IA (2500 

ppm)

G/IA 

(2500 

ppm)

G/IA 

(2500 

ppm)

IA

Increased Cyp2b Cyp3a A, G 500, 

2500 ppm)

A A, G (500, 

2500 

ppm)

A, G 

(500, 

2500 

ppm)

Increased hypertrophy A (2500 

ppm)

A A (2500 

ppm)

IA 

(2500 

ppm)

A A

Increased atRA 

metabolism-decreased 

hepatic atRA levels

A, G (2500 

ppm)

IG (2500 

ppm)

IG 

(2500 

ppm)

IA

Increased oxidative stress A, G, P (2500 

ppm)

IA, IG 

(2500 

ppm)

IA, IG 

(2500 

ppm)

In vivo mutation A, G (2500 

ppm)

IG 

Inhibition of CYP51-

dysregulation of 

cholesterol biosynthesis 

/metabolism and 

reduction in serum 

cholesterol levels

Increased 

hydroxylated 

cholesterols 

and bile 

acids. M 

(1250-2500) 

Decreased 

serum 

cholesterol 

A (2500 

ppm)

A A 

(2500 

ppm)

A
Page 42 of 78

levels A 

(2500)

Increase hepatic 

mevalonic acid levels 

IG (2500 

ppm)

Increased cell 

proliferation

A A A A (2500 

ppm)

IG IG

Suppression of apoptosis IG (2500 

ppm)

IG IG

Tumors A 

(2500 

ppm)

Bold = causal key event; not bold = associative key event 

A= apical endpoint measured

G= genomic endpoint measured

P= proteomic endpoint measured

M= metabolomic endpoint

IA= inferred from apical endpoint

IG= inferred from genomic endpoint
Page 43 of 78

Table 6. Cytotoxicity of propiconazole and five of its metabolites in liver cells at the highest 

concentration evaluated (400 μM) a (Chen et al., 2008)

Hepa1c1c7 cells

Primary mouse 

hepatocytes

HepG2 cells 

Chemical % Viability, mean ± S.D.

Propiconazole 1.65 ± 1.51 b,c 0 b10.6 ± 9.1 b,c

CGA 136735 24.2 ± 6.7 b,d 110.9 ± 24.8 61.8 ± 9.1 b,d

CGA 118245 51.1 ± 5.1 b102.7 ± 20 48.9 ± 7.5 b

CGA 118244 64.3 ± 16.4 b112.2 ± 20.1 55.9 ± 5.7 b

CGA 91304 76.1 ± 6.3 72.1 ± 12.1 75.5 ± 14.9

CGA 91305 86.1 ± 26.2 86.4 ± 20.6 82.2 ± 16.8

a

The chemical treatment exposure time was 24 h for Hepa1c1c7 (mouse hepatoma cells) and 

HepG2 (human hepatoma cells) cell lines and 48 h for primary mouse hepatocytes. Data are 

represented as the mean + S.D. (n = 6 for each concentration in HepG2 and Hepa1c1c7 cells (; n 

= 3 mice for each concentration in primary mouse hepatocytes).

b

Significantly different from the control by Dunnett's multiple comparison test (p < 0.05).

c

Significantly different from each other by Student’s t-test (p < 0.05).

d

Significantly different from each other by Student’s t-test (p < 0.05).

Table 7. Activation of nuclear receptors by propiconazole feed treatment (2500 ppm) for 4 

days (Nesnow et al., 2009) 

Nuclear receptor activation P-value

CAR/RXR Activation 0.0000

PPARα/RXRα Activation 0.0010

PXR/RXR Activation 0.0000

RAR Activation 0.0324

LXR/RXR Activation 0.0339

TR/RXR Activation 0.0158
Page 44 of 78

Table 8. Significant Ingenuity Pathway Analysis Tox Lists and Canonical Pathways from DEGs 

obtained after 30d of treatment with Phenobarbital (PB) (850 ppm) or Propiconazole (Pro) 

(2500 ppm).a (Nesnow et al. 2009).

Tox List and/or Canonical Pathway SourcebTreatment that altered list 

or pathway 

Acute Phase Response Signaling Can PB Pro

β-Alanine Metabolism Can PB Pro

Apoptosis Signaling Can PB Pro

Arachidonic Acid Metabolism Can PB Pro

Aryl Hydrocarbon Receptor Signaling Can, Tox PB Pro

Ascorbate and Aldarate Metabolism Can PB Pro

Bile Acid Biosynthesis Can PB Pro

Butanoate Metabolism Can PB Pro

CAR/RXR Activation Tox PB Pro

Coagulation System Can PB Pro

Cysteine Metabolism Can PB Pro

Cytochrome P450 Panel - Substrate is a Xenobiotic 

(Mouse)

Tox PB Pro

Endoplasmic Reticulum Stress Pathway Can PB Pro

Estrogen Receptor Signaling Can PB Pro

Fatty Acid Elongation in Mitochondria Can PB Pro

Fatty Acid Metabolism Can, Tox PB Pro

FXR/RXR Activation Can, Tox PB Pro

Glutathione Metabolism Can PB Pro

Hepatic Cholestasis Can, Tox PB Pro

Hepatic Fibrosis / Hepatic Stellate Cell Activation Can PB Pro

Keratan Sulfate Biosynthesis Can PB Pro

Linoleic Acid Metabolism Can PB Pro

LPS/IL-1 Mediated Inhibition of RXR Function Can, Tox PB Pro

Lysine Degradation Can PB Pro

Mechanism of Gene Regulation by Peroxisome 

Proliferators via PPARα

Tox PB Pro

Metabolism of Xenobiotics by Cytochrome P450 Can PB Pro

Negative Acute Phase Response Proteins Tox PB Pro

Nicotinate and Nicotinamide Metabolism Can PB Pro

NRF2-mediated Oxidative Stress Response Can/Tox PB Pro

Oxidative Stress Tox PB Pro

p38 MAPK Signaling Can PB Pro

Positive Acute Phase Response Proteins Tox PB Pro

PPARα/RXR Activation Tox PB Pro

PPARα/RXRα Activation Can PB Pro

Propanoate Metabolism Can PB Pro

Protein Ubiquitination Pathway Can PB Pro

PXR/RXR Activation Can, Tox PB Pro

Pyruvate Metabolism Can PB Pro
Page 45 of 78

Tox List and/or Canonical Pathway SourcebTreatment that altered list 

or pathway 

RAR Activation Can PB Pro

Retinol Metabolism Can PB Pro

Selenoamino Acid Metabolism Can PB Pro

Sphingolipid Metabolism Can PB Pro

Synthesis and Degradation of Ketone Bodies Can PB Pro

Toll-like Receptor Signaling Can PB Pro

Tryptophan Metabolism Can PB Pro

Valine, Leucine and Isoleucine Degradation Can PB Pro

Xenobiotic Metabolism Tox PB Pro

Xenobiotic Metabolism Signaling Can PB Pro

IGF-1 Signaling Can PB Pro

Insulin Receptor Signaling Can PB Pro

PI3K/AKT Signaling Can PB

Actin Cytoskeleton Signaling Can PB

Antigen Presentation Pathway Can PB

BMP signaling pathway Can PB

Chemokine Signaling Can PB

Dopamine Receptor Signaling Can PB

ERK/MAPK Signaling Can PB

Glycerophospholipid Metabolism Can PB

Integrin Signaling Can PB

Neuregulin Signaling Can PB

Synaptic Long Term Potentiation Can PB

Androgen and Estrogen Metabolism Can Pro

C21-Steroid Hormone Metabolism Can Pro

Complement System Can Pro

Cytochrome P450 Panel - Substrate is a Sterol 

(Mouse)

Tox Pro

Glucocorticoid Receptor Signaling Can Pro

D-glutamine and D-glutamate Metabolism Can Pro

Glutamate Metabolism Can Pro

GM-CSF Signaling Can Pro

LXR/RXR Activation Can, Tox Pro

Mitochondrial Dysfunction Can, Tox Pro

One Carbon Pool by Folate Can Pro

Oxidative Phosphorylation Can Pro

TR/RXR Activation Can, Tox Pro

14-3-3-mediated Signaling Can Pro

Alanine and Aspartate Metabolism Can Pro

Ceramide Signaling Can Pro

Citrate Cycle Can Pro

EGF Signaling Can Pro

Hypoxia Signaling in the Cardiovascular System Can Pro

Hypoxia-Inducible Factor Signaling Tox Pro
Page 46 of 78

Tox List and/or Canonical Pathway SourcebTreatment that altered list 

or pathway 

IL-2 Signaling Can Pro

JAK/Stat Signaling Can Pro

PDGF Signaling Can Pro

SAPK/JNK Signaling Can Pro

TGF-β Signaling Can, Tox Pro

Urea Cycle and Metabolism of Amino Groups Can Pro

a

Each list or pathway was statistically significant, p < 0.05.

b

Source is Tox List (Tox) or Canonical Pathway (Can).

Table 9

Effects on hepatic microsomal and cytosolic

protein and enzyme activities in male mice fed diets containing

propiconazole or phenobarbital 14 days a

Parameter Control

Propiconazole PB 

850 ppm 850 ppm 2500 ppm

Microsomal Protein (mg/g) 21.57 23.41 24.48 21.02

Cytosolic Protein (mg/g) 109.9 106.8 102.9 101.3*

Cytochrome P450 (nmol/g) 18.46 55.46*** (300) b71.90*** (389) 44.21*** (239)

EROD (nmol/min/g) 1.771 3.885*** (219) 6.871*** (388) 4.111*** (232)

PROD (nmol/min/g) 0.328 9.92*** (3024) 18.13*** (5524) 11.59*** (3534)

Coumarin 7-hydroxylase (nmol/min/g) 0.594 3.17*** (534) 14.16*** (2384) 2.850*** (480)

Lauric Acid 11-hydroxylase (nmol/min/g) 13.57 36.25*** (267) 41.10*** (305) 36.81*** (271)

Lauric Acid 12-hydroxylase (nmol/min/g) 11.72 17.88** (153) 18.82** (161) 19.06** (163)

Microsomal UDPGT (nmol/min/g) 1241 1935*** (156) 1720*** (139) 1942*** (156)

Cytosolic GST (nmol/min/g) 553.0 875*** (158) 1019*** (184) 1036*** (187)

Epoxide Hydrolase (nmol/min/g) 84.6 148.8*** (172) 278.0*** (321) 154.9*** (179)

a Data from MRID 45215803

b Results in parentheses are % of control when statistically significant

n = 6 mice/group

**p 0.01, ***p 0.001

EROD = Ethoxyresorufin O-dealkylase

PROD = Pentoxyresorufin O-dealkylase

UDPGT = Uridine diphosphate glucuronosyl-transferase

GST = Glutathione S-transferase
Page 47 of 78

Table 10

 Incidence of liver hypertrophy in mice fed propiconazole in the diet.a†

Treatment 4 Days of Treatment 30 Days of Treatment 90 Days of Treatment

Control 0/5 0 1/5 0.2 ± 0.5 (1.0) 1/5 0.2 ± 0.5 (1.0)

100 ppm 4/5 1.2 ± 0.8* (1.5 ± 0.6) 3/5 1.0 ± 1.0 (1.7 ± 0.6) 3/5 1.0 ± 1.0 (1.7 ± 0.6)

500 ppm 3/5 1.0 ± 0.5 (1.7 ± 0.6) 4/5 1.4 ± 0.9* (1.0 ± 0.5) 5/5 1.4 ± 0.6**

2500 ppm 5/5 2.0 ± 0** 5/5 3.2 ± 0.8** 5/5 3.0 ± 0.7**

a

Data were extracted from Allen et al. (2006).

† Incidence, mean lesion score for group ± S.D. (mean lesion score for affected animals when fewer than entire 

group ± SD). N= 5 

* Different from concurrent control by Student’s T-test (p<0.05). 

** Different from concurrent control by Student’s T-test and Dunnett’s multiple comparison test (p<0.05). 

Table 11. Expression of cholesterol biosynthetic genes after treatment with the high dose 

(2500 ppm) propiconazole: 4 days of treatment a.

Gene Response, Treated/control

Propiconazole

Acetoacetyl-CoA synthetase (Aacs) 0.94

HMG-Coenzyme A synthase 1 (Hmgcs1) 1.1

HMG-Coenzyme A reductase (Hmgcr) 1.4

Mevalonate kinase (Mvk) 0.93

Mevalonate decarboxylase (Mvd) 0.91

IPP isomerase (Idi1) 1.3

Farnesyl phosphate transferase 1 (Fdft1) 0.97

Squalene epoxidase (Sqle) 2.6b

Lanosterol -demethylase (CYP51) 1.7b

7-Dehydrocholesterol reductase (Dhcr7) 1.5b

a Extracted from Ward et al. (2006).

b

Statistically significant compared to controls, p < 0.05.
Page 48 of 78

Table 12. Significant Expression of cholesterol biosynthetic genes after conazole treatment of 

2500 ppm propiconazole treatment (from Ward et al (2006) and Nesnow et al 2009)

4 days 30 days 90 days

Gene

Response, 

Treated/contro

l

Response 

Treated/control

Response 

Treated/control

Acetoacetyl-CoA synthetase (Aacs)

HMG-Coenzyme A synthase 1 (Hmgcs1)

HMG-Coenzyme A synthase 1 (Hmgcs2) -1.8 -1.5 -1.6

HMG-Coenzyme A reductase (Hmgcr)

Mevalonate kinase (Mvk) -1.4

Mevalonate decarboxylase (Mvd)

IPP isomerase (Idi1) -1.7

farnesyl phosphate transferase 1 (Fdft1)

squalene epoxidase (Sqle) 2.6 -1.4

lanosterol synthase (Lss)

lanosterol α-demethylase (CYP51) 1.7 -1.6

sterol-C4-methyl oxidase-like (Sc4mol) 1.6

7-dehydrocholesterol reductase (Dhcr7) 1.5

aldo-keto reductase (Akr1d1) 2.1a1.9

aldehyde dehydrogenase (Aldh1a7) 1.8 2.2 1.8

Cytochrome 7a1 (Cyp7a1) 1.8 -3.3

Acetyl-Coenzyme A acetyltransferase 1 

(Acat1) -1.9 -1.9 -1.7

All expression values are statistically significant compared to controls, p<0.05
Page 49 of 78

Table 13. Differentially expressed soluble proteins from livers of mice treated for 4 days with propiconazole. Proteins were 

quantified by 2D-DIGE and identified by MS/MS mass spectrometry and protein database matching. (Ortiz et al., 2010)

Gel spot number, protein name and abbreviation Function

Protein Quantitation Protein Identification

Fold 

change p-Value

Accession 

number

Sequence 

coverage 

(%)

MW 

(kDa)/PI

MatchedpeptidesProtein 

score

17, 4-hydroxyphenylpyruvic acid dioxygenase (HPD) Amino acid metabolism 1.32 7.20E-03 33859486 56 45/6.6 18 260

54, Aminoacylase 1 (ACY 1) Amino acid metabolism -1.31 4.20E-03 81880060 51 45.8/5.9 15 180

32, Lactate dehydrogenase A ((LDHA) Amino acid metabolism -1.35 3.00E-03 6754524 60 36.5/7.6 15 236

41, Carbamoyl phosphate synthetase 1 (CPS 1) Amino acid metabolism -1.46 5.90E-04 124248512 52 16.5/6.5 61 1030

46, Dimethylglycine dehydrogenase precursor (DMGDH) Amino acid metabolism -1.62 4.10E-04 21311901 53 97.2/7.8 30 360

43, Aminoadipate-semialdehyde synthase precursor (AASS) Amino acid metabolism -1.76 9.50E-03 31980703 25 102.9/6.4 18 230

52, Hypoxia upregulated 1 (Hyou 1) Anti-apoptosis -1.92 2.00E-03 157951706 26 111.1/4.9 19 200

58, Succinate coenzyme A ligase, ADP-forming beta subunit 

(SUCLA 2)

Carbohydrate 

metabolism -1.36 8.00E-03 46849708 39 50.1/6.6 15 252

30, Carbonic anhydrase 3 (CA 3)

Carbon dioxide 

metabolism -1.38 2.90E-03 31982861 37 29.3/7.0 8 90

56, Methionine adenosyltransferase 1 alpha (MAT1A) Cell growth -1.65 3.00E-04 19526790 44 43.5/5.4 12 140

48, Formiminotransferase cyclodeaminase (FTCD) Cytoskeletal -1.95 4.30E-04 18252784 16 58.9/5.7 8 90
Page 50 of 78

Gel spot number, protein name and abbreviation Function

Protein Quantitation Protein Identification

Fold 

change p-Value

Accession 

number

Sequence 

coverage 

(%)

MW 

(kDa)/PI

MatchedpeptidesProtein 

score

40, Vinculin (VCL) Cytoskeletal structure -1.22 7.70E-03 31543942 47 116.6/5.7 42 704

50, Glutamate dehydrogenase 1 ((GLUD 1) Detoxification -1.5 8.70E-03 6680027 53 61.3/7.9 25 476

53, Catechol-o-methyltransferase (CATECHOL) Detoxification -2.14 1.30E-03 161484634 55 29.5/5.5 10 152

49, Esterase 31 isoform 1 (CES3) Detoxification -3.37 2.30E-04 63578904 18 63.3/5.7 8 98

15, Fumarate hydratase 1 (FH 1) Energy metabolism 1.5 1.90E-03 33859554 23 54.3/9.4 8 108

31, Electron transferring flavoprotein, (ETFA) Energy metabolism -1.53 1.30E-04 13097375 61 35.0/8.5 17 212

13, UDP glucose pyrophosphorylase 2 ( UGP2) Glycogen biosynthesis 2.41 3.70E-07 21314832 52 56.9/7.4 22 334

42, Pyruvate carboxylase (PC)

gluconeogenesis and 

lipogenesis, -1.4 2.00E-03 6679237 49 12.9/6.3 43 610

61, Hydroxyacyl-Coenzyme A dehydrogenase (HADHB) Hydratase 1.37 2.20E-03 21704100 18.9 51.3/9.8 10 90

59, Hypothetical protein LOC70984 (C11ORF54) Hydrolase 3.56 4.20E-08 19526926 54 35.0/5.8 13 266

21, Acetyl coenzyme A, acetyltransferase 2 (ACAT 2) Lipid metabolism 2.11 6.10E-03 148747461 22 41.3/7.2 7 70

25, Proteasome subunit alpha type 7 (PSMA7) Proteasome 2.35 4.80E-07 7106389 53 27.8/8.7 11 184

3, Proteasome subunit alpha type 2 (PSMA2) Proteasome 1.8 2.20E-04 1709759 72 25.9/8.6 11 150

9, Proteasome 26s subunit non- ATPase subunit 11 (PSMD11) Proteasome 1.61 2.10E-03 134053905 63 47.4/6.1 24 320
Page 51 of 78

Gel spot number, protein name and abbreviation Function

Protein Quantitation Protein Identification

Fold 

change p-Value

Accession 

number

Sequence 

coverage 

(%)

MW 

(kDa)/PI

MatchedpeptidesProtein 

score

8, Proteasome 26s subunit ATPase 2 (PSMC 2) Proteasome 1.51 6.40E-04 33859604 38 52.8/5.9 16 210

22, Proteasome 26s ATPase subunit 6 (PSMC6) Proteasome 1.48 1.70E-03 34783985 53 43.3/7.3 15 224

28, Proteasome 26s, subunit 13 (PSMD 13) Proteasome 1.44 8.50E-03 6755210 49 42.8/5.4 17 238

7, A chain A, vcp P97 Proteasome 1.42 3.10E-03 34809664 63 89.2/5 42 762

10, Leucyl aminopeptidase (lap3) Proteasome 1.3 7.50E-03 71059803 38 56.1/7.6 16 298

37, UV excision repair protein RAD 23 homolog B (RAD23B) Proteasome -1.48 6.90E-03 1709986 30 43.5/4.6 11 120

62, Alpha-2-macroglobulin 35 kDa subunit (PZP) Protease inhibitor 1.34 3.10E-03 134035924 54 28.2/7.1 13 130

35, Regucalcin (RGN) Protein binding -1.49 4.70E-03 6677739 66 33.4/5.0 14 236

45, Transferrin (TF) Protein binding -1.83 6.10E-03 20330802 51 76.7/6.8 33 492

44, Albumin (ALB) Protein binding -1.62 1.60E-03 163310765 32 68.6/5.7 17 236

38, BIP-immunoglobulin heavy chain binding protein (HPA5) -also 

known as HSP70-5 Protein binding -1.85 5.90E-04 2598562 49 72.4/4.9 29 370

14, Chaperonin subunit 4 delta (CCT4) Protein folding 1.74 8.90E-03 6753322 54 58/8.0 21 276

39, Tumor rejecting antigen gp96 Protein folding -2.13 1.40E-03 6755863 23 92.4/4.6 14 148

11, Aldehyde dehydrogenase family 1, subfamily A1 (ALDH1A1) Redox 2.21 8.80E-04 85861182 55 54.4/7.7 26 458

19, Carbonyl reductase 1 (CR 1) Redox 2.14 4.50E-04 113680352 61 30.6/8.4 6 246

18, Aldo-keto reductase family 1 member D1 (AKR1D1) Redox 1.7 1.50E-04 21703734 51 37.3/6.5 15 202

4, NADPH dehdyrogenase quinone 2 (NQO2) Redox 1.23 1.20E-03 9937970 46 26.2/6.6 8 100

12, Aldehyde dehydrogenase family 8, member A1 (ALDH8A1) Redox 1.22 7.00E-03 30520135 56 53.6/7.4 21 318

1, Peroxiredoxin 1 (PRDX1) Redox 1.2 4.20E-03 6754976 52 22.2/8.2 10 158

16, Cysteine conjugate beta lyase 1 (CCBL1) Redox 1.2 2.60E-03 31982063 29 47.5/6.5 10 164
Page 52 of 78

Gel spot number, protein name and abbreviation Function

Protein Quantitation Protein Identification

Fold 

change p-Value

Accession 

number

Sequence 

coverage 

(%)

MW 

(kDa)/PI

MatchedpeptidesProtein 

score

34, 3-hydroxyanthranilate 3,4-dioxygenase (HAAO) Redox -1.53 2.00E-04 17921976 71 32.8/6.1 15 230

57, Aldehyde dehydrogenase 2 (ALDH2) Redox -1.69 6.40E-03 6753036 37 56.5/7.5 14 160

36, Protein disulfide isomerase precursor (PDI) Redox -1.78 2.80E-03 129729 53 57.1/4.6 24 310

60, Thioredoxin domain containing protein 4 precursor (TXNDC4) Redox -1.98 1.10E-04 19072792 18 46.8/5.0 6 50

20, Aldolase 2 beta isoform (ALDOB) Signal transduction 1.54 6.80E-04 21450291 34 39.5/8.2 12 160

55, TNF receptor-associated protein 1 (TRAP1) Signal transduction -1.43 1.10E-03 13385998 43 80.2/6.2 23 302

47, Phospholipase C alpha (PLCα) Signal transduction -2.01 7.00E-06 200397 38 56.6/5.9 18 230

23, Glutathione S-Transferase mu 3 (GSTM3) Transferase 5.46 3.80E-07 33468899 57 25.7/7.8 6 358

27, Glutathione S-Transferase theta 3 (GSTT3) Transferase 4.47 4.00E-08 21536248 45 27.4/7.6 10 120

24, Glutathione S-Transferase mu 2 (GSTM2) Transferase 3.64 2.60E-04 6680121 72 25.9/7.2 18 422

29, Glutathione S-Transferase mu 1 (GSTM1) Transferase 3.11 1.20E-06 6754084 51 25.9/8.1 10 408

26, Glutathione S-Transferase alpha 3 (GSTA3) Transferase 3.06 2.20E-04 31981724 69 25.3/9.1 12 340

6, Tyrosine ester sulfotransferase (SULTD1) Transferase 2.57 9.60E-08 4096440 50 36.7/5.9 13 228

2, Glutathione S-Transferasetheta 1 (GSTT1) Transferase 1.73 1.00E-03 2495109 35 27.4/6.9 9 120

5, Indolethylamine N-methyltransferase (INMT) Transferase 1.64 2.40E-04 6678281 46 29.4/6.0 11 190

51, 3-hydroxy-3-methylglutaryl coenzyme A synthase 2 (HMGCS2) Transferase -1.5 2.20E-04 31560689 20 56.8/8.4 8 168

33, Sulfotransferase like protein 1 (SULT1D1) Transferase -1.99 2.40E-03 28202011 60 33.3/6.6 15 208
Page 53 of 78

Table 14. Mouse liver cell proliferation data in male mice fed propiconazole in the diet; 

proliferating cell nuclear antigen (PCNA) indices

Treatment 4 Days of Treatment 30 Days of Treatment 90 Days of Treatment

Control 0.490 ± 0.39 0.076 ± 0.12 0.210 ± 0.27

100 ppm 0.155 ± 0.30 0.230 ± 0.30 0.094 ± 0.11

500 ppm 2.720 ± 3.60 0.272 ± 0.34 0.167 ± 0.10

2500 ppm 4.380 ± 4.42 b, c 0.458 ± 0.26 0.381 ± 0.22

a

Data were extracted from Allen et al. (2006).

† Mean labeling index of group ± SD. N=5 mice/group 

b

Significantly different from concurrent control by Student’s T-test, p<0.05. 

c Significantly different compared to concurrent control by Dunnett’s multiple comparison test, p<0.05.
Page 54 of 78

Table 15. Summarized Results of FIFRA Guideline Mutagenicity Studies on Propiconazole

GL # MRID Study Type Results and Classification

84-2

870-5100

00058601 Bacterial reverse mutation

25-2025 μg/plate

Sept. 17, 1979

Negative in Salmonella strains with or without S-9 

activation. Unacceptable: test material purity not 

specified, not tested up to cytotoxic dose.

84-2

870-5575

00133343 Mitotic gene conversion assay 

(Saccharomyces cerevisiae), 

technical, # Op. 103119; 

purity 90.7%

August 19, 1982

No increase in revertants (did not induce mutation) or 

convertants (mitotic gene conversion) tested at 10, 30, 90 

or 270 μg/ml with or without activation. Concentrations of 

30μg/ml had inhibitory effect on yeast cell growth. 

Acceptable/guideline

84-2

870-5385

00058603 In vivo micronucleus test 

(bone marrow chromosomal 

aberration) - Chinese 

hamsters; Tech. # INA 35/1 

P1, purity 90.0%; 0, 251, 502 

or 1004 mg/kg

Negative for induction of micronuclei in bone marrow cells 

at all levels tested.

Acceptable/guideline

84-2

5450

00058602 Dominant lethal assay in mice: 

165 or 495 mg/kg single dose 

oral gavage, Tech. # INA 35/1 

P1, purity 90.0%;

October 31, 1979

No evidence of dominant lethal effects was observed in the 

progeny of male mice treated with propiconazole.

Acceptable/guideline

84-2

870-5550

00133347 Unscheduled DNA synthesis in 

human fibroblasts, Tech. # Op. 

103119, Purity 90.7%

August 12, 1982

Negative for inducing Unscheduled DNA Synthesis at 

concentrations up to and including 9.32 μg/ml. Highest 

dose tested to allow at least 25% cell viability

Acceptable/guideline

84-2

870-5550

00133348 Unscheduled DNA synthesis in 

primary rat hepatocytes, 

technical,# Op. 103119; purity 

90.7%;

August 12, 1982

Negative for inducing Unscheduled DNA Synthesis at 

concentrations up to and including 83.5 μg/ml. Highest 

dose tested to allow at least 25% cell viability

Acceptable/guideline

84-2

870-5300

00133349 In vitro cell transformation 

assay (BALB/3T3), technical,# 

Op. 103119; purity 90.7%; 

1.16-18.5 μg/ml

August 10, 1982

Negative: did not cause a measurable increase in 

transformation of BALB/T3 cells. Highest dose produced 

25% reduction in colony forming ability.

Acceptable/guideline
Page 55 of 78

Table 16. Structure-Activity Relationship of Related Triazole Compounds a,b

Compound Structure Carcinogenic Effect Carcinogen

Class/Mutagen

Triadimefon 

(Bayleton)

PC 109901

Tx.# 862AA

NMRI Mouse Only hepatocellular 

adenoma, at 1800 in (22%) F (18%) 

M <0.05 for trend and pairwise 

comparisons. Historical control 

incidence: 18.4% M and 2.0% F.

Wistar Rat Dose related trend in 

thyroid F-cell adenomas in M & F 

combined adenomas/carcinomas 

with cystic hyperplasia in & ; 

Pair wise comparisons not 

significant.

C NO Q 1*

Negative for 

mutagenicity but 

positive in the 

Big BlueTM lacI

transgenic mice 

assay (see Ross 

et al., 2009)

Triadimenol (Baytan)

PC 127201

Tx.# 074A

F1-W74 Mouse, 2000 ppm: 

Hepatocellular adenomas and 

hyperplastic nodules (p<0.01) in F. 

No increase in M. Adrenal 

adenomas noted in LDT and HDT 

but within historical control range. 

No elevation in carcinomas. 

Rat, 125-2000 ppm, increases in 

thyroid adenomas.

Weak C SAP

Negative for 

mutagenicity 

Baycor

PC 112403

Tx.# 087AA

Mouse: up to 500 ppm: (-) 

Rat: up to 500 ppm : (-)

Negative for 

mutagenicity

Uniconazole

PC 128976

Tx.# 207H

Crl:CD-1(ICR)BR Mouse Increased 

incidence of hepatocellular 

adenomas and carcinomas in 

males only at HDT .

Crl:CD-1(ICR)SD Rat No increase in 

neoplastic findings

C NO Q 1*

Negative for 

mutagenicity: 

Ames/E. coli; 

mouse bone 

marrow 

micronucleus 

assay BUT 

Positive Chinese 

hamster ovary 

(CHO) 

chromosome 
Page 56 of 78

Compound Structure Carcinogenic Effect Carcinogen

Class/Mutagen

aberration+ S9. 

Rodent dominant 

lethal assay 

recommended 

Hexaconazole

PC 128925

Tx. # 480G

CD-1/Alpk Mouse, 5, 40 & 200 

ppm. No oncogenic effect. Should 

be seen with caution because MTD 

was not reached. No oncogenic 

effect. 

ALpk:APfSD (Wistar derived) Rat, 

10, 100, 1000 ppm. There was a 

significant (p<0.01) dose-related 

trend and a significant pairwise 

comparison with controls at the 

HDT for benign Leydig cell tumors 

in the testes. The incidence at the 

HDT (16%) exceeded historical 

control values of up to 6.0%

C with Q 1*

Mutagenicity 

Negative:

Ames, 

chromosome 

aberrations in 

human lymphocytes; 1° rat 

hepatocytes unscheduled DNA 

synthesis (UDS) 

& mouse bone 

marrow 

micronucleus 

assays

Cyproconazole

PC 128993

Tx. # 272E

CD-1 Mouse, 5,15, 100 & 200 ppm. 

Significant incidence of liver 

adenomas and carcinomas at the 

MDT and HDT in males and at the 

HDT in females.

B2

Negative for 

mutagenicity: 

Ames; CHO cells 

at HGPRT locus; 

CHO chromosome 

aberrations, 1° 

rat UDS & mouse 

bone marrow 

micronucleus 

assays 1° rat 

hepatocytes unscheduled DNA 

synthesis (UDS); 

cell transformation; mouse 

bone marrow 

micronucleus 

assays & rat 

dominant lethal 

assays but 

positive in vitro 

chromosome 
Page 57 of 78

Compound Structure Carcinogenic Effect Carcinogen

Class/Mutagen

aberration assay. 

No concern for 

mutagenicity

Tetraconazole

PC 120603

CD-1 Mouse, 10, 90, 800 & 1250 

ppm. Significant increasing trend in 

both sexes with differences in the 

pair-wise comparisons of the 1250-

ppm dose group with the controls 

for liver adenomas, carcinomas 

and combined 

adenomas/carcinomas , all at p < 

0.01. There were also significant 

differences in the pair-wise 

comparisons of the 800-ppm dose 

group with the controls for liver 

benign tumors and for benign 

and/or malignant tumors 

combined in both sexes, both at p 

< 0.01.

Likely

Mutagenicity 

Negative:

Ames; mouse 

lymphoma ; TK 

+/-;chromosome 

aberration assay 

(CHO cells); 

HeLa cell UDS & 

mouse bone 

marrow 

Micro-nucleus

assays

Metconazole

PC 125619

CD-1 Mouse: 30, 300 & 1000 ppm. 

Male mice had significant 

increasing trends, and significant 

differences in the pair-wise 

comparison of the 1000 ppm dose 

group with the controls, for liver 

adenomas and adenomas and/or 

carcinomas combined, all at p < 

0.01. Female mice had significant 

increasing trends, and significant 

differences in the pair-wise 

comparison of the 1000 ppm dose 

group with the controls, for liver 

adenomas, carcinomas and 

adenomas and/or carcinomas 

combined, all at p < 0.01

Not likely 

Negative for 

mutagenicity: 

Ames; mouse 

lymphoma TK +/-

; Mouse bone 

marrow 

micronucleus; in 

vivo rat hepatocyte UDS assays 

but positive CHO 

chromosome 

aberration assay. 

Not considered a 

mutagenic 

concern

a Taken from Cancer Assessment Document: Evaluation of the Carcinogenic Potential of Epoxiconazole. HED 

Document Nos. 014451 & TXR No. 0054211.

b Abbreviations: : Female; : Male; HDT: Highest dose tested; LDT: Lowest dose tested; SAP: Scientific Advisory 

Panel
Page 58 of 78

Table 17. Incidence and severity of hepatoxic effects of 4, 8, and 13 weeks dietary administration of CGA-64250 

in CD-1 male mice1)

Dose 

PPM

Hepatocellular. 

Hypertrophy 

Monocellular 

Necrosis 

Necrosis Fatty Change Lymphohistiocytic 

Infiltration

4 Week Sacrifice

0 0/10 5/10 (5,0,0)2) 1/10 (1,0,0) 0/10 6/10

20 1/10 (1, 0, 0) 1/10 (1, 0, 0) 0/10 0/10 3/10

500 10/10 (7, 3, 0) 4/10 (4, 0, 0) 1/10 (1, 0, 0) 0/10 3/10

850 9/10 (3,6,0) 7/10 (7,0, 0) 3/10 (1, 2, 0) 0/10 3/10

1450 10/10 (0, 2, 8) 9/10 (6, 3, 0) 3/10 (3, 0, 0) 2/10 (1, 1, 0) 1/10

2500 9/10 (0, 2, 7) 9/10 (0, 5, 4) 7/10 (3, 4, 0) 7/10 (3, 3, 1) 3/10

8 Week Sacrifice

0 0/10 6/10 (6, 0, 0) 0/10 0/10 3/10

20 0/10 4/10 (4, 0, 0) 0/10 0/10 4/10

500 8/10 (3, 4, 1) 8/10 (6, 2, 0) 1/10 (0, 1, 0) 1/10 (1,0, 0) 6/10

850 10/10 (0, 7, 3) 4/10 (3, 1, 0) 0/10 0/10 3/10

1450 10/10 (0, 5, 5) 9/10 (7, 2, 0) 5/10 (2, 2, 1) 4/10 (3, 1, 0) 1/10

2500 10/10 (0, 0, 10) 9/10 (4, 4, 1) 6/10 (4, 2, 0) 8/10 (4, 4, 0) 2/10

13 Week Sacrifice

0 0/20 9/20 (9, 0, 0) 0/20 0/20 12/20

20 1/20 (1, 0, 0) 6/20 (6, 0, 0) 0/20 1/20 (1, 0, 0) 9/20

500 8/20 (7, 1, 0) 5/20 (5, 0, 0) 1/20 (1,0 ,0) 1/20 (1, 0, 0) 7/20

850 20/20 (0, 19, 1) 13/20 (12, 1, 0) 3/20 (1, 2, 0) 3/20 (3, 0, 0) 10/20

1450 20/20 (0, 0, 20) 18/20 (12, 5, 1) 6/20 (4, 2, 0) 7/20 (4, 3, 0) 10/20

2500 20/20 (0, 0, 20) 20/20 (7, 10, 3) 6/20 (5, 1, 0) 16/20 (8, 7, 1) 8/20

1) Data reproduced from Tables 3, 4, 5 and 6 of Study Report MRID 45215801

2) Number of animals exhibiting the effect/total number of animals examined. Numbers in parenthesis are the 

number of animals with varying degree of hepatotoxiciy (mild, moderate, and severe). 
Page 59 of 78

Table 18. Key Events Human Relevancy: Comparison of Key Events in Rodents and Humans for 

Propiconazole

Key Events of Mode and Key Mechanistic 

Events

Rodent Human

Activation of nuclear receptors

(CAR and PXR)

Gene expression and 

the induction of 

downstream CYP 

proteins

Some pharmaceuticals

activate CAR and PXR

Increased Cyp2b and Cyp3a mRNA levels, 

protein levels and increased P450 metabolic 

activities

Gene expression and 

direct biochemical and 

molecular measures

Some pharmaceuticals 

induce CYP2B6 and CYP3A4

Increased hepatic hypertrophy Histology Has been shown to occur 

with nuclear receptor 

activators

Increased atRA metabolism/decreased 

hepatic retinoic acid levels

Gene expression and 

confirmation in vitro 

and in vivo

Plausible

Oxidative stress Gene expression and 

confirmatory 

biochemical measures

Plausible

Induction of in vivo mutations Direct measure in vivo 

and associated 

genomic data on the 

induction of DNA 

damage

Plausible

Inhibition of CYP51 and dysregulation of 

cholesterol biosynthesis and metabolism 

(decrease in serum cholesterol)

Propiconazole MOA, 

metabolomic analysis 

and direct serum 

measures

Propiconazole MOA and 

plausible

Increase in hepatic mevalonic acid levels Gene expression Plausible

Increased cell proliferation Direct measure Plausible

Suppression of apoptosis Gene expression Plausible

Liver tumors Diagnosed in chronic 

study

Plausible 
Page 60 of 78

FIGURES

Figure 1. Proposed mode of action of propiconazole for mouse liver tumors using 

toxicogenomic data. 

Key events enclosed in blue boxes are relate to CYP induction; key events enclosed in green 

boxes are related to enzyme inhibition; key events enclosed in orange boxes are result of 

previous key events or are the direct result of propiconazole treatment. 

Activate CAR, PXR 

Proposed MOA for Propiconazole

Induce high activities of 

Cyp2b, Cyp3a

Increase atRA 

metabolism/ 

decrease atRA 

levels

Increase cell 

proliferation/alter 

cell signaling 

Liver Tumors

Oxidative 

stress 

Dysregulate

cholesterol 

biosynthesis/

metabolism 

Mutation 

in vivo

Propiconazole parent

Hypertrophy

Decrease 

apoptosis

Increase 

mevalonic 

acid levels 
Page 61 of 78

Figure 2. Propiconazole metabolites; metabolite identified as U2 in MRID 00164795 = CGA 

91305. Data extracted from Chen et al., 2009.

Propiconazole metabolites

Cl Cl

O

O

H3C N N

N

Cl Cl

O

O

H3C N N

N

OH

Cl Cl

O

O

H3C N N

N

HO

Cl

Cl

O

N

N N

Cl

Cl

HO

N

N N

Cl Cl

O

O

N N

N

HO

Propiconazole

CGA 118245 CGA 118244 CGA 136735

CGA 91304 CGA 91305

Major mouse in vivo 

metabolite as 

glucuronide

Propiconazole metabolites

Cl Cl

O

O

H3C N N

N

Cl Cl

O

O

H3C N N

N

OH

Cl Cl

O

O

H3C N N

N

HO

Cl

Cl

O

N

N N

Cl

Cl

HO

N

N N

Cl Cl

O

O

N N

N

HO

Propiconazole

CGA 118245 CGA 118244 CGA 136735

CGA 91304 CGA 91305

Cl Cl

O

O

H3C N N

N

Cl Cl

O

O

H3C N N

N

OH

Cl Cl

O

O

H3C N N

N

HO

Cl

Cl

O

N

N N

Cl

Cl

HO

N

N N

Cl Cl

O

O

N N

N

HO

Propiconazole

CGA 118245 CGA 118244 CGA 136735

CGA 91304 CGA 91305

Major mouse in vivo 

metabolite as 

glucuronide
Page 62 of 78

Figure 3. Liver microsomal alkoxyresorufin dealkylase (AROD) activities in livers from CD-1 mice fed diets of propiconazole. Data 

extracted from Allen et al., 2006.
Page 63 of 78

Figure 4. Effects of propiconazole on mouse liver to body weight measurements. Data 

extracted from Allen et al., 2006; Doyle and Rinde, 1992; MRID 00129570.
Page 64 of 78

Figure 5. Retinoic acid biosynthesis and metabolism pathway: gene expression levels altered 

by propiconazole 4, 30 and 90 days of treatment. Data extracted from Nesnow et al., 2009.
Page 65 of 78

Figure 6. Effect of propiconazole on hepatic microsomal atRA metabolism after 4 days of 

treatment. Data extracted from Chen et al., 2009.

Control Propiconazole - NADPH

atRA metabolism, pmol/min/mg protein

0

50

100

150

200

250

300

4-hydroxy-atRA 

4-oxo-atRA 

Total metabolism 

*

*

*
Page 66 of 78

Figure 7. Effects of propiconazole on cell proliferation. Data extracted from Allen et al., 2006; 

Dewhurst and Dellarco, 2003; MRID 45215802.
Page 67 of 78

Figure 8. Effects of propiconazole on cell cycle genes over time. Data extracted from Nesnow 

et al., 2009
Page 68 of 78

Figure 9. Effects of propiconazole on apoptotic genes. Data extracted from Nesnow et al., 

2009.
Page 69 of 78

Figure 10. Induction of mouse liver tumors by propiconazole Data from male mouse study, 

hepatocellular tumor incidence. Data extracted from MRID 00129570.
Page 70 of 78

Figure 11. Concordance of CAR target expression with liver: body-weight. Data extracted 

from Allen et al., 2006; Ward et al., 2006.

Propiconazole Feed Level (ppm)

0 500 1000 1500 2000 2500 3000

Liver: Body Weight (%)

5.0

5.5

6.0

6.5

7.0

7.5

8.0

5 Gene Expression Fold Change

10

15

20

25

30

Liver: Body Weight (%)

Cyp2b10 Gene Expression

Alas1 Gene Expression

4 Day

Propiconazole Feed Level (ppm)

0 500 1000 1500 2000 2500 3000

Liver: Body Weight (%)

5.0

5.5

6.0

6.5

7.0

7.5

8.0

Gene Expression Fold Change

0

10

20

30

40

Liver: Body Weight (%)

Cyp2b10 Gene Expression

Alas1 Gene Expression

30 Day

Propiconazole Feed Level (ppm)

0 500 1000 1500 2000 2500 3000

Liver: Body Weight (%)

4

5

6

7

8

9

10

11

12

Gene Expression Fold Change

0

5

10

15

20

25

30

Liver: Body Weight (%)

Cyp2b10 Gene Expression

Alas1 Gene Expression

90 Day

Propiconazole Feed Level (ppm)

0 500 1000 1500 2000 2500 3000

Liver: Body Weight (%)

5.0

5.5

6.0

6.5

7.0

7.5

8.0

5 Gene Expression Fold Change

10

15

20

25

30

Liver: Body Weight (%)

Cyp2b10 Gene Expression

Alas1 Gene Expression

Propiconazole Feed Level (ppm)

0 500 1000 1500 2000 2500 3000

Liver: Body Weight (%)

5.0

5.5

6.0

6.5

7.0

7.5

8.0

Gene Expression Fold Change

0

10

20

30

40

Liver: Body Weight (%)

Cyp2b10 Gene Expression

Alas1 Gene Expression

Propiconazole Feed Level (ppm)

0 500 1000 1500 2000 2500 3000

Liver: Body Weight (%)

4

5

6

7

8

9

10

11

12

Gene Expression Fold Change

0

5

10

15

20

25

30

Liver: Body Weight (%)

Cyp2b10 Gene Expression

Alas1 Gene Expression
Page 71 of 78

Figure 12. Concordance of PROD Activity with Cyp2b10 gene expression. Data extracted from 

Allen et al., 2006; Nesnow et al., 2009. 

Propiconazole Feed Level (ppm)

0 500 1000 1500 2000 2500 3000

Enzyme Activity - Fold Induction

0

2

4

6

8

10

12

14

0 Gene Expression Fold Change

5

10

15

20

25

30

PROD

Cyp2b10

4 Day

Propiconazole Feed Level (ppm)

0 500 1000 1500 2000 2500 3000

Enzyme Activity - Fold Induction

0

5

10

15

20

25

30

35

40

Gene Expression Fold Change

0

10

20

30

40

PROD

Cyp2b10

30 Day

Propiconazole Feed Level (ppm)

0 500 1000 1500 2000 2500 3000

Enzyme Activity - Fold Induction

0

10

20

30

40

0 Gene Expression Fold Change

5

10

15

20

25

30

PROD

Cyp2b10

90 Day

Propiconazole Feed Level (ppm)

0 500 1000 1500 2000 2500 3000

Enzyme Activity - Fold Induction

0

2

4

6

8

10

12

14

0 Gene Expression Fold Change

5

10

15

20

25

30

PROD

Cyp2b10

Propiconazole Feed Level (ppm)

0 500 1000 1500 2000 2500 3000

Enzyme Activity - Fold Induction

0

5

10

15

20

25

30

35

40

Gene Expression Fold Change

0

10

20

30

40

PROD

Cyp2b10

Propiconazole Feed Level (ppm)

0 500 1000 1500 2000 2500 3000

Enzyme Activity - Fold Induction

0

10

20

30

40

0 Gene Expression Fold Change

5

10

15

20

25

30

PROD

Cyp2b10
Page 72 of 78

Figure 13. Some genes associated with PXR activation at 4 days of propiconazole treatment. 

Data extracted from Nesnow et al., 2009.
Page 73 of 78

Figure 14. Genes associated with retinoic acid metabolism. Data extracted from Nesnow et 

al., 2009.

4 Day

30 Day

90 Day

0 500 1000 1500 2000 2500 3000

Fold Change

0

1

2

3

4

5

6

Cyp26a1 Cyp3a11 Cyp3a13

0 500 1000 1500 2000 2500 3000

Fold Change

0.5

1.0

1.5

2.0

2.5

3.0

Cyp26a1 Cyp3a11 Cyp3a13

Propiconazole Feed Level (ppm)

0 500 1000 1500 2000 2500 3000

Fold Change

0.8

1.0

1.2

1.4

1.6

1.8 Cyp26a1 Cyp3a11 Cyp3a13

0 500 1000 1500 2000 2500 3000

Fold Change

0

10

20

30

40

50

Cyp2c55 Cyp2b10 Cyp2c65

0 500 1000 1500 2000 2500 3000

Fold Change

0

20

40

60

80

100

120

Cyp2c55 Cyp2b10 Cyp2c65

Propiconazole Feed Level (ppm)

0 500 1000 1500 2000 2500 3000

Fold Change

0

20

40

60

80

100

120

Cyp2c55 Cyp2b10 Cyp2c65

0 500 1000 1500 2000 2500 3000

Fold Change

0

1

2

3

4

5

6

Cyp26a1 Cyp3a11 Cyp3a13

0 500 1000 1500 2000 2500 3000

Fold Change

0.5

1.0

1.5

2.0

2.5

3.0

Cyp26a1 Cyp3a11 Cyp3a13

Propiconazole Feed Level (ppm)

0 500 1000 1500 2000 2500 3000

Fold Change

0.8

1.0

1.2

1.4

1.6

1.8 Cyp26a1 Cyp3a11 Cyp3a13

0 500 1000 1500 2000 2500 3000

Fold Change

0

1

2

3

4

5

6

Cyp26a1 Cyp3a11 Cyp3a13

0 500 1000 1500 2000 2500 3000

Fold Change

0.5

1.0

1.5

2.0

2.5

3.0

Cyp26a1 Cyp3a11 Cyp3a13

Propiconazole Feed Level (ppm)

0 500 1000 1500 2000 2500 3000

Fold Change

0.8

1.0

1.2

1.4

1.6

1.8 Cyp26a1 Cyp3a11 Cyp3a13

0 500 1000 1500 2000 2500 3000

Fold Change

0

10

20

30

40

50

Cyp2c55 Cyp2b10 Cyp2c65

0 500 1000 1500 2000 2500 3000

Fold Change

0

20

40

60

80

100

120

Cyp2c55 Cyp2b10 Cyp2c65

Propiconazole Feed Level (ppm)

0 500 1000 1500 2000 2500 3000

Fold Change

0

20

40

60

80

100

120

Cyp2c55 Cyp2b10 Cyp2c65
Page 74 of 78

Figure 15. Genes associated with oxidative stress. Data extracted from Nesnow et al., 2009. 

Propiconazole Feed Level (ppm)

0 500 1000 1500 2000 2500 3000

Fold Change

0

2

4

6

8

10

12

14

Gstm1

Gstm2

Gstm3

Gstm4

Gstt3

4 Day

Propiconazole Feed Level (ppm)

0 500 1000 1500 2000 2500 3000

Fold Change

0

2

4

6

8

Gstm1

Gstm2

Gstm3

Gstm4

Gstt3

30 Day

Propiconazole Feed Level (ppm)

0 500 1000 1500 2000 2500 3000

Fold Change

0

2

4

6

8

10

12

Gstm1

Gstm2

Gstm3

Gstm4

Gstt3

90 Day

Propiconazole Feed Level (ppm)

0 500 1000 1500 2000 2500 3000

Fold Change

0

2

4

6

8

10

12

14

Gstm1

Gstm2

Gstm3

Gstm4

Gstt3

Propiconazole Feed Level (ppm)

0 500 1000 1500 2000 2500 3000

Fold Change

0

2

4

6

8

Gstm1

Gstm2

Gstm3

Gstm4

Gstt3

Propiconazole Feed Level (ppm)

0 500 1000 1500 2000 2500 3000

Fold Change

0

2

4

6

8

10

12

Gstm1

Gstm2

Gstm3

Gstm4

Gstt3
Page 75 of 78

Figure 16. Genes associated with DNA damage. Data extracted from Nesnow et al., 2009.
Page 76 of 78

Figure 17. Concordance of cell cycle gene expression with liver cell proliferation after 4 days 

of propiconazole treatment. Data extracted from Nesnow et al., 2009.
Page 77 of 78

Figure 18. Genes associated with apoptosis. Data extracted from Nesnow et al., 2009.

Propiconazole Feed Level (ppm)

0 500 1000 1500 2000 2500 3000

Fold Change

0

2

4

6

8

10

12

14

16

18

20

22

24

26

28

30

Gadd45b (anti-apoptotic)

Ikbke (anti-apoptotic)

Fas (pro-apoptotic)

4 Day

Propiconazole Feed Level (ppm)

0 500 1000 1500 2000 2500 3000

Fold Change

0

5

10

15

20

25

30

35

40

45

50

55

Bmf (pro-apoptotic)

Gadd45b (anti-apoptotic)

Ikbke (anti-apoptotic)

Fas (pro-apoptotic)

30 Day

Propiconazole Feed Level (ppm)

0 500 1000 1500 2000 2500 3000

Fold Change

0

5

10

15

20

Bmf (pro-apoptotic)

Gadd45b (anti-apoptotic)

Ikbke (anti-apoptotic)

Fas (pro-apoptotic)

90 Day

Propiconazole Feed Level (ppm)

0 500 1000 1500 2000 2500 3000

Fold Change

0

2

4

6

8

10

12

14

16

18

20

22

24

26

28

30

Gadd45b (anti-apoptotic)

Ikbke (anti-apoptotic)

Fas (pro-apoptotic)

Propiconazole Feed Level (ppm)

0 500 1000 1500 2000 2500 3000

Fold Change

0

5

10

15

20

25

30

35

40

45

50

55

Bmf (pro-apoptotic)

Gadd45b (anti-apoptotic)

Ikbke (anti-apoptotic)

Fas (pro-apoptotic)

Propiconazole Feed Level (ppm)

0 500 1000 1500 2000 2500 3000

Fold Change

0

5

10

15

20

Bmf (pro-apoptotic)

Gadd45b (anti-apoptotic)

Ikbke (anti-apoptotic)

Fas (pro-apoptotic)
Page 78 of 78

Figure 19. Alterations of cell cycle genes within the phases of the cell cycle by 

Phenobarbital (PB) and Propiconazole (Pro). Data based DEGs from 4-days 

treatments. Genes in red are overexpressed, whereas genes in green are 

underexpressed. Data extracted from Nesnow et al., 2009.

Cell cycle