Exploring the relationship between the inhibition of gap junctional intercellular communication and other biological phenomena

H.S. Rosenkranz1, N. Pollack and A.R. Cunningham

Department of Environmental and Occupational Health, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, PA 15261, USA


    Abstract
 Top
 Abstract
 Introduction
 Materials and methods
 Results and discussion
 References
 
The mechanistic relationship of the inhibition of gap junctional intercellular communication (GJIC) to other toxicological phenomena was explored using a recently developed method that models the properties of a large population of molecules chosen to represent the `universe of chemicals'. The analyses indicate that inhibition of GJIC is strongly linked to the carcinogenic process in rodents, to cellular but not systemic toxicity, to biological phenomena that may involve inflammatory processes and to development effects. The inhibition of GJIC appears not to be associated with genotoxic mechanisms. With respect to cancer causation, integration of the analyses suggests that inhibition of GJIC is involved in non-genotoxic cancer induction or in the non-genotoxic phases of the carcinogenic process (such as inflammation, cell toxicity, cell proliferation, inhibition of cell differentiation and apoptosis).

Abbreviations: GJIC, gap junctional intercellular communication; SAR, structure–activity relationship.


    Introduction
 Top
 Abstract
 Introduction
 Materials and methods
 Results and discussion
 References
 
As a result of the perseverance of Trosko and associates (13), of Yamasaki et al. (4) and of Klaunig and Ruch (5), the role of inhibition of gap junctional intercellular communication (GJIC) in toxicological phenomena has gained acceptance. The more recent findings of the molecular targets of inhibition of GJIC, i.e. the connexins, have led to the recognition of the mechanism of this inhibition (615). Thus, studies with humans as well as connexin knockout mice have shown that a deficiency or a mutation in specific connexin genes results in developmental effects (1620). Independently, structure–activity relationship (SAR) studies in our laboratory (21) have shown that, based upon structural criteria, there were significant mechanistic similarities between inhibition of GJIC and some toxicological phenomena. However, while the results of comparisons among SAR models, i.e. structural overlaps, as carried out by us (21) are useful in hypothesis generation, by definition the chemicals used in deriving SAR models are rarely unbiased representatives of the `universe of chemicals'. This is due to the fact that toxicological data upon which a specific SAR model may be based are usually not derived from a coherent toxicological testing scheme. Rather, such models are based upon the data available in the peer reviewed literature. Usually, the data are limited to the results of about 300 chemicals (22). Accordingly, it may be difficult to extrapolate and to generalize based solely on comparisons of SAR models which are based on restricted samplings of chemical classes. In order to overcome this potential shortcoming, we have developed an approach that does not reflect the restricted bias of the chemicals that make up the database from which the SAR model is derived, but allows extrapolation to the `universe of chemicals' (23). Essentially, rather than looking for structural overlaps among SAR models, we chose 10 000 chemical representatives of the `universe of chemicals' (24). The various biological/toxicological properties of these chemicals are predicted using validated SAR models. The prevalence of chemicals predicted to possess two toxicological properties simultaneously is then determined and compared with that expected. The rationale of the approach as well as the interpretation of the results are described below.

We applied this approach to the phenomenon of inhibition of GJIC to determine whether it demonstrated the expected interactions and/or whether in addition it generated new testable mechanistic hypotheses.


    Materials and methods
 Top
 Abstract
 Introduction
 Materials and methods
 Results and discussion
 References
 
SAR methodology
For these studies we used the CASE/MULTICASE SAR expert systems described previously (25,26). Application of this methodology results in the development of four submodels, each of which are derived from different algorithms and useful for investigating different aspects of the biological phenomena under consideration. The projections of the four individual submodels were integrated into a single prediction based upon Bayes' theorem (27,28). In each instance the cut-offs used to predict the activity of the 10 000 chemicals (24) were set to ensure that the positive (or negative) predictive power of the test was optimal.

Each of the SAR models used herein had been characterized (22) with respect to its ability to predict the activity of chemicals external to the model (see Table IGo).


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Table I. Performance characteristics of SAR models
 
SAR models
The validated SAR models used for these studies have been described previously: inhibition of GJIC (21), binding to the Ah receptor (30), mutagenicity in Salmonella (31,32), SOS DNA repair, i.e. the Chromotest (33,34), carcinogenicity in rodents [a combination of results of bioassays conducted by the US National Toxicology Program (35) and of those analyzed by Gold and associates (3640) in the Carcinogenic Potency Data Base (28,29)], developmental toxicity in hamsters (41) and in humans (42), allergic contact dermatitis (43), ocular irritation (44), sensory irritation (45), respiratory hypersensitivity (46) and cellular toxicity (cultured BALB/c-3T3 cells) (47). The SAR model of {alpha}2µ-globulin-associated nephropathy was based upon data kindly supplied by Dr L.D.Lehman-McKeenan (Procter and Gamble), while the model for inhibition of human cytochrome P4502D6 was based upon data supplied by Dr G.Ströbl (GSF Institut für Toxikologie, Neuherberg, Germany). The SAR model for toxicity to cultured HeLa cells and for skin permeability were based upon published measurements (48,49). Systemic toxicity in rats was defined as an LD50 <=7.3 mmol/kg (this cut-off value was chosen arbitrarily as it allowed separation of the chemicals into two groups of equal size). The SAR model was derived from data provided by the US Food and Drug Agency.

The chemical diversity approach: rationale
The procedure is based upon the premise that the mechanistic relationship between biological phenomena can be derived from knowledge of the prevalence of chemicals which give identical responses in assays designed to probe that relationship. Thus, at the time the electrophilic theory of cancer causation was recognized (50) and the dogma that `carcinogens are mutagens' (51) led to the development of surrogate tests for putative carcinogens, we discovered significant experimental overlaps using rodent carcinogens and genotoxicants. However, further studies clearly found that a significant number of non-mutagens also induced cancers in rodents. The basis of `non-genotoxic' carcinogenesis is still under active investigation but clearly it derives from a number of different mechanisms. Still, based upon the above premise, we should be able to gain a mechanistic insight into this phenomenon by evaluating the concordance, or lack thereof, between non-genotoxicants that induce cancers in rodents and agents that cause non-genotoxic phenomena (e.g. peroxisome proliferation, mitogenesis and binding to the estrogen receptor). Thus, an evaluation of the toxicological profiles of a population of chemicals might reveal significant associations between `non-genotoxic' inducers of cancers and inducers of another toxicological phenomenon. The observed prevalence of chemicals that induce both phenomena could then be compared with the prevalence expected, if it is assumed that the two phenomena are unrelated (i.e. the null hypothesis). If the observed prevalence is significantly greater than the expected one, then it can be concluded that the two phenomena are related to one another mechanistically. (Similarly, if the observed prevalence is significantly lower than the expected one, it suggests that the two phenomena are antagonistic with one another, e.g. they could compete for an active site.)

In implementing such an approach, it quickly became obvious that there is a scarcity of experimental data on the same chemicals across a variety of end-points. Hence, the significance of the observed joint prevalences cannot be ascertained. The current approach was devised to overcome this shortcoming. It is based upon the availability of characterized and validated models describing structure–activity relationships. Moreover, while reliable databases of toxicological models, when available, are usually limited to 200–300 chemicals, the approach used herein predicts the toxicological profiles of 10 000 chemicals representative of the `universe of chemicals' (23). While no SAR model is perfectly predictive when applied to a population of 10 000 chemicals, provided the sensitivity and specificity are approximately equal we can expect that the overall prevalence will reflect the true distribution. This in turn will allow a determination of the significance of the observed joint prevalences.

The approach can be used to confirm specific hypotheses (e.g. the electrophilic theory of cancer causation) as well as to generate new (knowledge-based) hypotheses driven solely by the data and the availability of appropriate SAR models.


    Results and discussion
 Top
 Abstract
 Introduction
 Materials and methods
 Results and discussion
 References
 
The impetus for the development of assays for inhibition of GJIC was based upon the insight of Trosko et al. (3) that this phenomenon could be a measure of tumor promotion as well as of the abolition of contact inhibition among adjacent cells, a phenomenon that is associated with cancer promotion and progression. Indeed, our earlier studies of structural overlaps between SAR models of carcinogenicity and inhibition of GJIC (21) showed a significant commonality between these phenomena. In the present study, the chemicals that were predicted to be rodent carcinogens as well as inhibitors of GJIC showed the greatest deviation (n = 239) from independence (see Table IIGo), clearly indicating that the two phenomena are related. On the other hand, the ability to inhibit GJIC appeared unrelated mechanistically to the induction of {alpha}2µ-globulin-mediated nephropathy or to the ability to inhibit human cytochrome P4502D6, two phenomena which our earlier structural overlap study had also identified as unrelated to inhibition of GJIC. Our earlier studies had also indicated that there was no structural overlap between inhibition of GJIC and ability to bind to the Ah receptor (21). In the present study, it is actually shown that the two phenomena are antagonistic to one another, i.e. the deviation from the expected value is a negative one. Molecules that bind to the Ah receptor are typically lipophilic. Chemicals which cause inhibition of GJIC are also, to a large extent, characterized by being lipophilic (21). Conceivably, these lipophilic inhibitors of GJIC could distort the Ah receptor, thus not allowing the normal ligand to bind. In that connection, it is interesting to note that inhibitors of GJIC are related to agents that are skin permeable (Table IIGo). The latter phenomenon has also been shown to be associated with lipophilicity (52,53).


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Table II. Comparisons between observed and expected joint overlaps for 10 000 chemicals
 
In our previous study (21), inhibition of GJIC was shown to display a mechanistic similarity to mutagenicity, albeit the effect was significantly less than the commonality between inhibition of GJIC and carcinogenicity. We attributed the relationship between mutagenicity and inhibition of GJIC not to a common causality, but rather to the fact that the two phenomena may both involve a nucleophilic target, albeit they are different, i.e. attack on DNA in the case of the former and on connexin in the latter. In the present study, using a more sensitive procedure, we find that there is only a slight deviation from the expected prevalence (Table IIGo) and it does not reach statistical significance. This finding was confirmed by examining the overlap between inhibition of GJIC and induction of SOS DNA repair (the Chromotest), which, like mutagenicity, is a consequence of an electrophilic attack on DNA. That overlap also did not reach statistical significance (Table IIGo). These findings suggest that the approach used herein may provide further discrimination between association and causality with respect to the mechanism of toxicological activity.

Inhibition of GJIC overlaps with human and hamster developmental toxicity. This may well reflect the observation that alterations in the function and/or presence of connexins, i.e. the target of inhibition of GJIC, results in developmental effects (1620). Moreover, it is noteworthy that the extent of overlap between inhibition of GJIC is significantly lower for human than it is for hamster developmental toxicants (P > 0.0001). This possibly reflects the fact that the extensive prescreening that precedes the introduction into human usage of new products (54) may include toxicological tests that eliminate from consideration a number of classes of inhibitors of GJIC and therefore of putative human developmental toxicants. Obviously, this is not the situation with respect to chemicals tested in hamsters (41), wherein no such prescreen was imposed. In fact, a rodent developmental toxicity screen may have been used to eliminate some of the agents that otherwise would have proven detrimental to humans and hence the mechanisms represented among the human developmental toxicants are more limited (54).

There was a significantly higher than expected prevalence of a number of acute toxicological effects such as allergic contact dermatitis, ocular irritation, sensory irritation and respiratory hypersensitivity associated with inhibition of GJIC (Table IIGo). This was unexpected, as each of these are thought to occur by different mechanisms, although a possibly unifying symptomatic effect could result from the induction of inflammatory mediators, such as cytokines (55). It was also surprising that irrespective of inhibition of GJIC, the observed prevalence of molecules that have potential for jointly inducing allergic contact dermatitis, ocular irritation, sensory irritation and respiratory hypersensitivity is much greater than expected (2008 versus 554, P < 0.00001), again suggesting a commonality between the phenomena. Such molecules also have a much greater than expected prevalence (647 versus 151, P < 0.00001) of being putative inhibitors of GJIC. These findings suggest a commonality in mechanisms that is worthy of further study. These observations are given some credence by the fact that a subclass of inhibitors of GJIC, i.e. the tumor promoters, are reported to be irritants as well as inflammatory agents (5659) and by the finding that inhibition of GJIC may be mediated by an arachidonic acid-sensitive mechanism (60).

With respect to systemic toxicity, it is noteworthy that inhibition of GJIC is not associated with even moderately toxic substances, i.e. agents with LD50 values below 7.3 mmol/kg. This is consistent with the spectrum of toxicological effects associated with inhibition of GJIC, e.g. carcinogenicity and developmental and inflammatory effects. Expression of each of these requires survival of the test object. On the other hand, at the cellular level, inhibitors of GJIC are significantly related to toxicity to both cultured HeLa and BALB/c-3T3 cells. This may be related to the observation that many inhibitors of GJIC are lipophilic (21), which is a recognized mechanism of toxicity. Moreover, cell toxicity has been investigated as a mechanistic basis for epigenetic carcinogenesis (3). Other studies have suggested that cellular toxicity and the resulting mitogenesis and cell proliferation may provide an alternative mechanism of cancer causation (6164). The possibility that inhibitors of GJIC possess inherent cytotoxic potential would provide an additional link between this phenomenon and carcinogenesis.

The present study, using refined methodologies, independently extends an earlier approach based upon overlaps among SAR models (21) to assess mechanistic similarities among toxicological phenomena. With respect to the phenomenon of inhibition of GJIC, the results reported herein provide independent confirmation that inhibition of GJIC is related to carcinogenesis as well as to induction of developmental effects. A number of observations appear novel and deserve further investigation: (i) a putative relationship between inhibition of GJIC and inflammatory processes; (ii) a possible direct involvement of inhibition of GJIC in certain aspects of cellular toxicity that may result in mitogenesis and subsequent cancer induction by a non-genotoxic mechanism. The present findings offer persuasive evidence that inhibition of GJIC is not the result of a genotoxic event.


    Acknowledgments
 
The SAR method used herein (CASE/MULTICASE) was made available free of charge by MULTICASE Inc. (Beachwood, OH). That company was founded and is partly owned by Case Western Reserve University, Gilles Klopman and Herbert S.Rosenkranz. The support of the Vira Heinz Endowment and the US Army Medical Research and Materiel Command Breast Cancer Research Project is gratefully acknowledged.


    Notes
 
1 To whom correspondence should be addressed. Email: rsnkranz{at}pitt.edu Back


    References
 Top
 Abstract
 Introduction
 Materials and methods
 Results and discussion
 References
 

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Received July 1, 1999; revised November 19, 1999; accepted December 28, 1999.