To the extent possible under law, AOP-Wiki has waived all copyright and related or neighboring rights to KER:351

Relationship: 351


The title of the KER should clearly define the two KEs being considered and the sequential relationship between them (i.e., which is upstream and which is downstream). Consequently all KER titles take the form “upstream KE leads to downstream KE”.  More help

Increased, Induced Mutations in Critical Genes leads to Increased, Clonal Expansion / Cell Proliferatin to form Pre-Neoplastic Altered Hepatic Foci

Upstream event
Upstream event in the Key Event Relationship. On the KER page, clicking on the Event name under Upstream Relationship will bring the user to that individual KE page. More help
Downstream event
Downstream event in the Key Event Relationship. On the KER page, clicking on the Event name under Upstream Relationship will bring the user to that individual KE page. More help

Key Event Relationship Overview

The utility of AOPs for regulatory application is defined, to a large extent, by the confidence and precision with which they facilitate extrapolation of data measured at low levels of biological organisation to predicted outcomes at higher levels of organisation and the extent to which they can link biological effect measurements to their specific causes. Within the AOP framework, the predictive relationships that facilitate extrapolation are represented by the KERs. Consequently, the overall WoE for an AOP is a reflection in part, of the level of confidence in the underlying series of KERs it encompasses. Therefore, describing the KERs in an AOP involves assembling and organising the types of information and evidence that defines the scientific basis for inferring the probable change in, or state of, a downstream KE from the known or measured state of an upstream KE. More help

AOPs Referencing Relationship

This table is automatically generated upon addition of a KER to an AOP. All of the AOPs that are linked to this KER will automatically be listed in this subsection. Clicking on the name of the AOP in the table will bring you to the individual page for that AOP. More help

Taxonomic Applicability

Select one or more structured terms that help to define the biological applicability domain of the KER. In general, this will be dictated by the more restrictive of the two KEs being linked together by the KER. Authors can indicate the relevant taxa for this KER in this subsection. The process is similar to what is described for KEs (see pages 30-31 and 37-38 of User Handbook) More help

Sex Applicability

Authors can indicate the relevant sex for this KER in this subsection. The process is similar to what is described for KEs (see pages 31-32 of the User Handbook). More help

Life Stage Applicability

Authors can indicate the relevant life stage for this KER in this subsection. The process is similar to what is described for KEs (see pages 31-32 of User Handbook). More help

Key Event Relationship Description

Provide a brief, descriptive summation of the KER. While the title itself is fairly descriptive, this section can provide details that aren’t inherent in the description of the KEs themselves (see page 39 of the User Handbook). This description section can be viewed as providing the increased specificity in the nature of upstream perturbation (KEupstream) that leads to a particular downstream perturbation (KEdownstream), while allowing the KE descriptions to remain generalised so they can be linked to different AOPs. The description is also intended to provide a concise overview for readers who may want a brief summation, without needing to read through the detailed support for the relationship (covered below). Careful attention should be taken to avoid reference to other KEs that are not part of this KER, other KERs or other AOPs. This will ensure that the KER is modular and can be used by other AOPs. More help

There is no direct evidence addressing AFB1 induced critical gene mutations and the subsequent induction of AHF. However, in general the progression from chemical exposure to pre-neoplastic lesions appears to include six general mechanisms: 1) decrease in the activity of the Keap1/Nrf2/ARE pathway; 2) decrease in p53 function leading to increased survival in the presence of genomic instability; 3) changes in the tumor microenvironment within cells; 4) alterations in apoptosis; 5) changes in Wnt/b-catenin signaling, and 6) gene expression changes that may be related to cancer promotion/progression. In addition to these six possible mechanisms, epigenetic changes in DNA methylation may occur and may be related to the progression of cancer.

Evidence Supporting this KER

Assembly and description of the scientific evidence supporting KERs in an AOP is an important step in the AOP development process that sets the stage for overall assessment of the AOP (see pages 49-56 of the User Handbook). To do this, biological plausibility, empirical support, and the current quantitative understanding of the KER are evaluated with regard to the predictive relationships/associations between defined pairs of KEs as a basis for considering WoE (page 55 of User Handbook). In addition, uncertainties and inconsistencies are considered. More help
Biological Plausibility
Define, in free text, the biological rationale for a connection between KEupstream and KEdownstream. What are the structural or functional relationships between the KEs? For example, there is a functional relationship between an enzyme’s activity and the product of a reaction it catalyses. Supporting references should be included. However, it is recognised that there may be cases where the biological relationship between two KEs is very well established, to the extent that it is widely accepted and consistently supported by so much literature that it is unnecessary and impractical to cite the relevant primary literature. Citation of review articles or other secondary sources, like text books, may be reasonable in such cases. The primary intent is to provide scientifically credible support for the structural and/or functional relationship between the pair of KEs if one is known. The description of biological plausibility can also incorporate additional mechanistic details that help inform the relationship between KEs, this is useful when it is not practical/pragmatic to represent these details as separate KEs due to the difficulty or relative infrequency with which it is likely to be measured (see page 40 of the User Handbook for further information).   More help

AFB1 induces G:C to T:A transversions. The third nucleotide in codon 249 of the p53 gene is a guanine and is a preferred binding target for AFB1 metabolites. In humans, some evidence exists that this codon is a mutational hot spot in liver cancers in people exposed to AFB1. (Puisieux et al., 1991). Although there is a large literature describing mutations in this location in humans and the corresponding p53 codon 247 in rodents, whether these mutations by themselves actually lead to tumors is unknown. (Lee et al., 1998) In vitro data collected from two human cell lines suggest that doses of AFB1 sufficient to induce DNA damage also induce an incomplete cell cycle checkpoint response, likely involving p53; this suggests a potential mechanism that might ultimately lead to tumor formation in vivo.(Gursoy-Yuzugullu et al., 2011). In rats, Ki-ras codon 12 mutations observed after AFB1 dosing may also be associated with hyperplastic foci to a greater extent than in hepatocellular carcinomas (HCCs), suggesting some change in the mutational spectrum during tumor development. (Tokusashi et al., 1994)

In general, the exact origin of cells that form altered hepatic foci (AHF) is not known with certainty. (Sell, 1993, 2002; Sell and Leffert, 2008). Four types of cells in the liver are thought to be capable of becoming tumor cells: 1) mature hepatocytes, 2) bile duct progenitor cells, 3) ductular bipolar progenitor cells, and 4) periductular stem cells. Pre-neoplastic foci and HCCs likely form from the last two cell types. [6] In rats, pre-neoplastic foci expressing the placental form of GST appear to be descended from hepatocytes. (Bralet et al., 2002; Avril et al., 2004; Gournay et al., 2002).

However, Sell (2008) has criticized the hypothesis the HCC arise by de-differentiation of hepatocytes and suggested the cellular origin of HCC may be liver stem cells undergoing an arrest of maturation. Trosko (2014) has considered de-differentiation in light of one of the emerging “Hallmarks of Cancer”—alterations of cellular metabolism—and argues that the likelihood of cancer arising through de-differentiation is vanishingly small. (Hanahan and Weinberg, 2011; Trosko and Kang, 2012; Trosko, 2013, 2014). The questions of the origin of the progenitor cells that replace hepatocytes after liver injury and the origin of liver cancer stem cells are the subjects of intense research. (Gong et al., 2013; Jia et al., 2013; Miyajima et al., 2014; Rehman et al., 2014; Shin and Kaestner, 2014; Tanimizu and Mitaka, 2014). The cyotokine IL-6 may be involved in the transformation of hepatic progenitor cells into cancer stem cells. (Dang et al., 2014; He et al., 2013). In addition, Dragan et al. (1994) observed that the increase in BrdU labeling, indicating cell proliferation, occurred to a greater extent in altered hepatic foci (AHF).

There is no direct evidence addressing AFB1 induced critical gene mutations and the subsequent induction of AHF. However, in general the progression from chemical exposure to pre-neoplastic lesions appears to include six general mechanisms: 1) decrease in the activity of the Keap1/Nrf2/ARE pathway; 2) decrease in p53 function leading to increased survival in the presence of genomic instability; 3) changes in the tumor microenvironment within cells; 4) alterations in apoptosis; 5) changes in Wnt/β-catenin signaling, and 6) gene expression changes that may be related to cancer promotion/progression (Miyajima et al., 2014; Gong et al., 2013; Jia et al., 2013; Dang et al., 2014; He et al., 2013; Caballero et al., 2004; Ma and He, 2012; Gross-Steinmeyer and Eaton, 2012; Liby et al., 2008; Yates et al., 2007; Liby and Sporn, 2012; Ikeda et al., 2004; Haridas et al., 2004). In addition to these six possible mechanisms, epigenetic changes in DNA methylation may occur and may be related to the progression of cancer (Kwak et al., 2001; Honda et al., 2011; Shelton and Jaiswal, 2013; Fabregat, 2009; Zhang et al., 2003).

The following is an overview of these 6 general biological processes that appear to be involved in the progression of mutant cells (whether occurring as the result of direct chemical induction or increased due other events such as cell proliferation and clonal expansion of spontaneously occurring mutant cells) to AHF and pre-neoplastic lesions.

Decrease in p53 function

A defective p53 gene may contribute to telomere dysfunction. Continuous hepatocyte renewal may be associated with telomere shortening and chromosomal instability [42-44]. In transgenic mice, telomere dysfunction enhanced tumor initiation but interfered with tumor progression/promotion. However, p53 mutation leading to inactivation of the gene, in combination with telomere dysfunction and increased hepatocyte turnover, may increase the risk of HCC (Zhang et al., 2006, 2012; Wu et al., 2013; Pogribny et al., 2011; Farazi et al., 2003).

The Tumor Microenvironment

Intracellular signaling mechanisms are involved in the creation of tumor microenvironment. (Hanahan and Weinberg, 2011). These include alterations in cellular circuits governing proliferation, differentiation, motility, and viability. The x gene is one of the four genes in the Hepatitis B Virus (HBV) genome that is capable of trans-activating cellular genes to contribute to the development of a tumor microenvironment (Brechot et al., 2000, 2010). The x gene can be expressed through stable transfection into LE/6 cells, a cell line derived from hepatic oval cells harvested from rats fed a choline-deficient diet. When LE/6 cells that were transfected with HBx and injected into nude mice administered a single dose of 240 μg/kg AFB1 by IP injection, or in the drinking water continuously for 16 weeks, the mice developed HCC from these rat liver stem cells, indicative of the stem cell-origin of HCC and suggesting that HBV and x expression may foster a tumor microenvironment.

TGF-β has a dual effect on hepatocytes—inhibiting proliferation and inducing apoptosis. Experiments using TGF-β null mutant mice show that this signal is required for normal development and appears to be involved in destruction of damaged cells in the liver. TGF-β 1 also mediates interferon-induced apoptosis in AHF in rats. In rats, AFB1 altered biological processes in hepatic stem-like cells related to cell motion, cell adhesion, immune response, and signal transduction (Yang et al., 2014). Reduced levels of TGF-β produce an increase in E-cadherin and reduce cellular motility, one of the intracellular networks associated with the cancer hallmark of invasion and metastasis (Fransvea et al., 2008).

Effects on Apoptotic Signaling

TGF-β normally inhibits growth and proliferation and induces apoptosis of damaged cells. In primary rat hepatocytes and a cell line (NRML) derived from these primary rat cells, TGF-β inhibited cell proliferation measured by DNA synthesis and the ability to form colonies. In vitro treatment of NRML cells with AFB1 blocked the TGF-β-mediated inhibition of cell growth and proliferation (McMahon et al., 1986). AFB1 transformed cells were also resistant to the growth-inhibiting effects of tumor necrosis factor-alpha (TNF-α) (Chapekar et al., 1989). However, BL9 cells, derived from rat hepatocytes transformed with reactive metabolites if activated AFB1, retained the sensitivity to the inhibitory effects of TGF-β on cell growth.

The product of the p53 gene mutated at codon 249 may itself impair the apoptotic process. In Hep3B human hepatoma cells, transfection with mutant p53 (p53mt249) increased transcription of insulin-like growth factor II (IGF-II). Wild-type p53 inhibited binding of the TATA-box binding protein (TBP) and the Sp1 transcription factors to the IGF-II promoter, possibly by binding to this promoter. However, p53mt249 increased the formation of transcription complexes, possibly due to lack of binding to the promoter. Chang liver cells show characteristics of hepatocytes; transfection with p53mt249 or addition of IGF-II blocked apoptosis mediated by TNF-α or the HBV x gene (Lee et al., 2000).

Adult tree shrews were administered AFB1 at 150 μg/kg/d five times weekly for 105 weeks. Interim sacrifices were performed every 30 weeks to observe liver histopathology, specifically immunohistochemical staining for p53, bcl-2, and bax, proteins in the p53 pathway that leads to apoptosis (Duan et al., 2005). Immunohistochemistry was also conducted to visualize survivin, a protein that acts directly on caspases to inhibit the activity of caspase-3 and caspase-7 to block the terminal pathway of apoptosis (Cheung et al., 2013). Terminal deoxynucleotidyl transferase dUTP nick end labeling (TUNEL) staining was used to detect apoptotic cells.

Bcl-2 and bax were observed in the livers of less than 10% of treated animals at 30 weeks. This result seems somewhat paradoxical because these proteins are intermediates in the p53 apoptotic pathway; however, the determinant of apoptotic progression may be the bcl-2 / bax ratio (Korsmeyer et al., 1993). The actions of survivin occur much later in the apoptotic pathway and this protein was detected in 40% of livers. Also, the apoptotic index measured by TUNEL was increased significantly at 30 weeks (Duan et al., 2005).

Wnt/β-catenin Signaling

Wnt/β-catenin signaling is a key determinant of liver cell proliferation and eventual differentiation to mature hepatocytes or cholangiocytes. This signaling cascade is generally inactive in healthy adult liver save for a small periportal region of a hepatic lobule. Hepatocytes in this region have constitutively active β-catenin that in turn regulates expression of genes associated with ammonia and xenobiotic metabolism (Monga, 2014). An increase in Wnt/β-catenin signaling appears to play a role in the development of hepatocellular cancers, and mutations in the β-catenin gene have been observed in HCCs from humans (Laurent-Puig and Zucman-Rossi, 2006; Devereux et al., 2001). In areas of high AFB1 exposure in China, β-catenin was overexpressed in a higher proportion of liver samples from HCC patients than in Malaysia where AFB1 exposure is lower (Chen Ban et al., 2004).

Paradoxically, AFB1 appears to increase microRNA-33a, which in turn down-regulates β-catenin (Fang et al., 2013). However, this study was conducted in human cancer cell lines and the signaling pathways in such cells may be considerably different than they are in vivo.

Genomic Changes in Response to AFB1

Administration of AFB1 to rat hepatic stem-like WB-F344 cells derived from oval cells produced changes in pathways related to TGF-β signaling, Wnt signaling, MAPK signaling, regulation of the cytoskeleton, cell adhesion, changes in energy metabolism, and ECM-receptor interaction (Yang et al., 2014). A number of these can be conceptually linked to the hallmarks of cancer (Hanahan and Weinberg, 2011). In another study, the AFB1-induced transcriptome, measured by RNA-Seq with increased resolution and sensitivity was compared to microarrays for pathways with differentially expressed genes, such as glutathione metabolism, cell cycle dysregulation, cancer pathways, Nrf2-mediated oxidative stress, and ten various intermediary and amino acid metabolism pathways (Merrick et al., 2013).

Uncertainties and Inconsistencies
In addition to outlining the evidence supporting a particular linkage, it is also important to identify inconsistencies or uncertainties in the relationship. Additionally, while there are expected patterns of concordance that support a causal linkage between the KEs in the pair, it is also helpful to identify experimental details that may explain apparent deviations from the expected patterns of concordance. Identification of uncertainties and inconsistencies contribute to evaluation of the overall WoE supporting the AOPs that contain a given KER and to the identification of research gaps that warrant investigation (seep pages 41-42 of the User Handbook).Given that AOPs are intended to support regulatory applications, AOP developers should focus on those inconsistencies or gaps that would have a direct bearing or impact on the confidence in the KER and its use as a basis for inference or extrapolation in a regulatory setting. Uncertainties that may be of academic interest but would have little impact on regulatory application don’t need to be described. In general, this section details evidence that may raise questions regarding the overall validity and predictive utility of the KER (including consideration of both biological plausibility and empirical support). It also contributes along with several other elements to the overall evaluation of the WoE for the KER (see Section 4 of the User Handbook).  More help

There is no direct information as to whether AFB1 induced mutations in critical genes leads to cellular proliferation and clonal expansion of mutant cells. It is known, however that the Hepatitis B virus plays a large role in the development of HCC in many endemic AFB1 regions, and viral infection is thought to interact with AFB1 exposure increasing the possibility that individual cells progress down the pathway to tumor formation. It seems reasonable that this infection may contribute to increased cell proliferation which could contribute to more clonal expansion (and, therefore, an increase in tumor formation) of AFB1-induced critical cancer gene mutant cells. It might also contribute to inflammation and increased cell proliferation which could result in an increased number of spontaneously mutant cells containing mutants in cancer critical genes (such as p53) thus also resulting in HCC (via a non-mutagenic MOA). This interaction between AFB1 and viral infection has motivated much research (Chittmittrapap et al., 2013; Farazi et al., 2006; Gouas et al., 2010; Kew 2003).

Response-response Relationship
This subsection should be used to define sources of data that define the response-response relationships between the KEs. In particular, information regarding the general form of the relationship (e.g., linear, exponential, sigmoidal, threshold, etc.) should be captured if possible. If there are specific mathematical functions or computational models relevant to the KER in question that have been defined, those should also be cited and/or described where possible, along with information concerning the approximate range of certainty with which the state of the KEdownstream can be predicted based on the measured state of the KEupstream (i.e., can it be predicted within a factor of two, or within three orders of magnitude?). For example, a regression equation may reasonably describe the response-response relationship between the two KERs, but that relationship may have only been validated/tested in a single species under steady state exposure conditions. Those types of details would be useful to capture.  More help
This sub-section should be used to provide information regarding the approximate time-scale of the changes in KEdownstream relative to changes in KEupstream (i.e., do effects on KEdownstream lag those on KEupstream by seconds, minutes, hours, or days?). This can be useful information both in terms of modelling the KER, as well as for analyzing the critical or dominant paths through an AOP network (e.g., identification of an AO that could kill an organism in a matter of hours will generally be of higher priority than other potential AOs that take weeks or months to develop). Identification of time-scale can also aid the assessment of temporal concordance. For example, for a KER that operates on a time-scale of days, measurement of both KEs after just hours of exposure in a short-term experiment could lead to incorrect conclusions regarding dose-response or temporal concordance if the time-scale of the upstream to downstream transition was not considered. More help
Known modulating factors
This sub-section presents information regarding modulating factors/variables known to alter the shape of the response-response function that describes the quantitative relationship between the two KEs (for example, an iodine deficient diet causes a significant increase in the slope of the relationship; a particular genotype doubles the sensitivity of KEdownstream to changes in KEupstream). Information on these known modulating factors should be listed in this subsection, along with relevant information regarding the manner in which the modulating factor can be expected to alter the relationship (if known). Note, this section should focus on those modulating factors for which solid evidence supported by relevant data and literature is available. It should NOT list all possible/plausible modulating factors. In this regard, it is useful to bear in mind that many risk assessments conducted through conventional apical guideline testing-based approaches generally consider few if any modulating factors. More help
Known Feedforward/Feedback loops influencing this KER
This subsection should define whether there are known positive or negative feedback mechanisms involved and what is understood about their time-course and homeostatic limits? In some cases where feedback processes are measurable and causally linked to the outcome, they should be represented as KEs. However, in most cases these features are expected to predominantly influence the shape of the response-response, time-course, behaviours between selected KEs. For example, if a feedback loop acts as compensatory mechanism that aims to restore homeostasis following initial perturbation of a KE, the feedback loop will directly shape the response-response relationship between the KERs. Given interest in formally identifying these positive or negative feedback, it is recommended that a graphical annotation (page 44) indicating a positive or negative feedback loop is involved in a particular upstream to downstream KE transition (KER) be added to the graphical representation, and that details be provided in this subsection of the KER description (see pages 44-45 of the User Handbook).  More help

Domain of Applicability

As for the KEs, there is also a free-text section of the KER description that the developer can use to explain his/her rationale for the structured terms selected with regard to taxonomic, life stage, or sex applicability, or provide a more generalizable or nuanced description of the applicability domain than may be feasible using standardized terms. More help

In mammals, the identification of AHF as a pre-neoplastic lesion has been recognized for many years as part of the general etiology of HCC (Beer and Pitot, 1987; Dragan et al., 1995; Goldsworthy et al., 1986; Pitot et al., 1990; Sargent et al., 1989). In rats, the presence of AHF with altered growth characteristics has been observed in a number of studies (Bannasch et al., 1985; Fischer, 1986; Fischer et al., 1987; Gil et al., 1988; Godlewski et al., 1985; Manson et al., 1984; Newberne, 1976; Nishizumi et al., 1977; Roebuck et al., 1991; Youngman and Campbell, 1992). The mechanisms involved in the formation of AHF appear to be generalizable across animals and likely apply to fish and birds as well as mammals.


List of the literature that was cited for this KER description using the appropriate format. Ideally, the list of references should conform, to the extent possible, with the OECD Style Guide (OECD, 2015). More help

Avril A., Pichard V., Bralet M.P., Ferry N. 2004. Mature hepatocytes are the source of small hepatocyte-like progenitor cells in the retrorsine model of liver injury.. J Hepatol. 41(5), 737-43.

Bannasch P., Benner U., Enzmann H., Hacker H.J.1985. Tigroid cell foci and neoplastic nodules in the liver of rats treated with a single dose of aflatoxin B1.. Carcinogenesis. 6(11), 1641-8

Beer D.G., Pitot H.C.1987. Biological markers characterizing the development of preneoplastic and neoplastic lesions in rodent liver.. Arch Toxicol Suppl. 1068-8

Bralet M.P., Pichard V., Ferry N.2002. Demonstration of direct lineage between hepatocytes and hepatocellular carcinoma in diethylnitrosamine-treated rats.. Hepatology. 36(3), 623-30

Bréchot C., Gozuacik D., Murakami Y., Paterlini-Bréchot P.2000. Molecular bases for the development of hepatitis B virus (HBV)-related hepatocellular carcinoma (HCC).. Semin Cancer Biol. 10(3), 211-31 http://10.1006/scbi.2000.032

Brechot C., Kremsdorf D., Soussan P., Pineau P., Dejean A., Paterlini-Brechot P., Tiollais P.2010. Hepatitis B virus (HBV)-related hepatocellular carcinoma (HCC): molecular mechanisms and novel paradigms.. Pathol Biol (Paris). 58(4), 278-87 http://10.1016/j.patbio.2010.05.00

Caballero F, Meiss R, Gimenez A, Batlle A, and Vazquez E. Immunohistochemical analysis of heme oxygenase-1 in preneoplastic and neoplastic lesions during chemical hepatocarcinogenesis. Int J Exp Pathol. 2004, Oct;85(4):213-22.

Chapekar M.S., Huggett A.C., Thorgeirsson S.S.1989. Growth modulatory effects of a liver-derived growth inhibitor, transforming growth factor beta 1, and recombinant tumor necrosis factor alpha, in normal and neoplastic cells.. Exp Cell Res. 185(1), 247-57

Chen Ban K., Singh H., Krishnan R., Fong Seow H.2004. Comparison of the expression of beta-catenin in hepatocellular carcinoma in areas with high and low levels of exposure to aflatoxin B1.. J Surg Oncol. 86(3), 157-63 http://10.1002/jso.2005

Cheung C.H., Huang C.C., Tsai F.Y., Lee J.Y., Cheng S.M., Chang Y.C., Huang Y.C., Chen S.H., Chang J.Y.2013. Survivin - biology and potential as a therapeutic target in oncology.. Onco Targets Ther. 61453-62 http://10.2147/OTT.S3337

Chittmittrapap S., Chieochansin T., Chaiteerakij R., Treeprasertsuk S., Klaikaew N., Tangkijvanich P., Komolmit P., Poovorawan Y.2013. Prevalence of aflatoxin induced p53 mutation at codon 249 (R249s) in hepatocellular carcinoma patients with and without hepatitis B surface antigen (HBsAg).. Asian Pac J Cancer Prev. 14(12), 7675-9

Dang HT, Budhu A, and Wang XW. The origin of cancer stem cells. J Hepatol. 2014, Jun;60(6):1304-5.

Devereux T.R., Stern M.C., Flake G.P., Yu M.C., Zhang Z.Q., London S.J., Taylor J.A.2001. CTNNB1 mutations and beta-catenin protein accumulation in human hepatocellular carcinomas associated with high exposure to aflatoxin B1.. Mol Carcinog. 31(2), 68-7

Dragan Y.P., Hully J., Crow R., Mass M., Pitot H.C.1994. Incorporation of bromodeoxyuridine in glutathione S-transferase-positive hepatocytes during rat multistage hepatocarcinogenesis.. Carcinogenesis. 15(9), 1939-47

Dragan Y., Teeguarden J., Campbell H., Hsia S., Pitot H.1995. The quantitation of altered hepatic foci during multistage hepatocarcinogenesis in the rat: transforming growth factor alpha expression as a marker for the stage of progression.. Cancer Lett. 93(1), 73-83 http://10.1016/0304-3835(95)03789-

Duan X.X., Ou J.S., Li Y., Su J.J., Ou C., Yang C., Yue H.F., Ban K.C.2005. Dynamic expression of apoptosis-related genes during development of laboratory hepatocellular carcinoma and its relation to apoptosis.. World J Gastroenterol. 11(30), 4740-4

Fabregat I. Dysregulation of apoptosis in hepatocellular carcinoma cells. World J Gastroenterol. 2009, Feb 2;15(5):513-20.

Fang Y., Feng Y., Wu T., Srinivas S., Yang W., Fan J., Yang C., Wang S.2013. Aflatoxin B1 negatively regulates Wnt/β-catenin signaling pathway through activating miR-33a.. PLoS One. 8(8), e73004 http://10.1371/journal.pone.007300

Farazi P.A., Glickman J., Jiang S., Yu A., Rudolph K.L., DePinho R.A.2003. Differential impact of telomere dysfunction on initiation and progression of hepatocellular carcinoma.. Cancer Res. 63(16), 5021-7

Farazi P.A., Glickman J., Horner J., Depinho R.A.2006. Cooperative interactions of p53 mutation, telomere dysfunction, and chronic liver damage in hepatocellular carcinoma progression.. Cancer Res. 66(9), 4766-73 http://10.1158/0008-5472.CAN-05-460

Fischer G.1986. Increased UDP-glucuronyltransferase and gamma-glutamyltranspeptidase in enzyme-altered rat liver lesions produced by low doses of aflatoxin B1.. Virchows Arch B Cell Pathol Incl Mol Pathol. 51(5), 443-60

Fischer G., Domingo M., Lodder D., Katz N., Reinacher M., Eigenbrodt E.1987. Immunohistochemical demonstration of decreased L-pyruvate kinase in enzyme altered rat liver lesions produced by different carcinogens.. Virchows Arch B Cell Pathol Incl Mol Pathol. 53(6), 359-6

Fransvea E., Angelotti U., Antonaci S., Giannelli G.2008. Blocking transforming growth factor-beta up-regulates E-cadherin and reduces migration and invasion of hepatocellular carcinoma cells.. Hepatology. 47(5), 1557-66 http://10.1002/hep.2220

Gil R., Callaghan R., Boix J., Pellin A., Llombart-Bosch A.1988. Morphometric and cytophotometric nuclear analysis of altered hepatocyte foci induced by N-nitrosomorpholine (NNM) and aflatoxin B1 (AFB1) in liver of Wistar rats.. Virchows Arch B Cell Pathol Incl Mol Pathol. 54(6), 341-9

Godlewski C.E., Boyd J.N., Sherman W.K., Anderson J.L., Stoewsand G.S.1985. Hepatic glutathione S-transferase activity and aflatoxin B1-induced enzyme altered foci in rats fed fractions of brussels sprouts.. Cancer Lett. 28(2), 151-7

Goldsworthy T.L., Hanigan M.H., Pitot H.C.1986. Models of hepatocarcinogenesis in the rat--contrasts and comparisons.. Crit Rev Toxicol. 17(1), 61-89 http://10.3109/1040844860903707

Gong P, Wang Y, Zhang J, and Wang Z. Differential hepatic stem cell proliferation and differentiation after partial hepatectomy in rats. Mol Med Rep. 2013, Oct;8(4):1005-10.

Gouas D.A., Shi H., Hautefeuille A.H., Ortiz-Cuaran S.L., Legros P.C., Szymanska K.J., Galy O., Egevad L.A., Abedi-Ardekani B., Wiman K.G., Hantz O., Caron de Fromentel C., Chemin I.A., Hainaut P.L.2010. Effects of the TP53 p.R249S mutant on proliferation and clonogenic properties in human hepatocellular carcinoma cell lines: interaction with hepatitis B virus X protein.. Carcinogenesis. 31(8), 1475-82 http://10.1093/carcin/bgq118

Gournay J., Auvigne I., Pichard V., Ligeza C., Bralet M.P., Ferry N.2002. In vivo cell lineage analysis during chemical hepatocarcinogenesis in rats using retroviral-mediated gene transfer: evidence for dedifferentiation of mature hepatocytes.. Lab Invest. 82(6), 781-8

Gross-Steinmeyer K, and Eaton DL. Dietary modulation of the biotransformation and genotoxicity of aflatoxin B(1). Toxicology. 2012, Sep 9;299(2-3):69-79.

Gursoy-Yuzugullu O., Yuzugullu H., Yilmaz M., Ozturk M.2011. Aflatoxin genotoxicity is associated with a defective DNA damage response bypassing p53 activation.. Liver Int. 31(4), 561-71.

Hanahan D., Weinberg R.A.2011. Hallmarks of cancer: the next generation.. Cell. 144(5), 646-74 http://10.1016/j.cell.2011.02.013

Haridas V, Hanausek M, Nishimura G, Soehnge H, Gaikwad A, Narog M, et al. Triterpenoid electrophiles (avicins) activate the innate stress response by redox regulation of a gene battery. J Clin Invest. 2004, Jan;113(1):65-73.

He G, Dhar D, Nakagawa H, Font-Burgada J, Ogata H, Jiang Y, et al. Identification of liver cancer progenitors whose malignant progression depends on autocrine IL-6 signaling. Cell. 2013, Oct 10;155(2):384-96.

Honda T, Yoshizawa H, Sundararajan C, David E, Lajoie MJ, Favaloro FG, et al. Tricyclic compounds containing nonenolizable cyano enones. A novel class of highly potent anti-inflammatory and cytoprotective agents. J Med Chem. 2011, Mar 3;54(6):1762-78.

Ikeda H, Nishi S, and Sakai M. Transcription factor Nrf2/MafK regulates rat placental glutathione S-transferase gene during hepatocarcinogenesis. Biochem J. 2004, Jun 6;380(Pt 2):515-21

Jia S-Q, Ren J-J, Dong P-D, and Meng X-K. Probing the hepatic progenitor cell in human hepatocellular carcinoma. Gastroenterol Res Pract. 2013;2013145253.

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