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Clinical Cancer Research Vol. 7, 620-633, March 2001
© 2001 American Association for Cancer Research

Experimental Therapeutics, Preclinical Pharmacology

Screening for and Identification of Novel Agents Directed at Renal Cell Carcinoma1

Susan D. Mertins2, Timothy G. Myers, Melinda Hollingshead, Donald Dykes, Esther Bodde, Pauline Tsai, Christine A. Jefferis, Ruchi Gupta, W. Marston Linehan, Michael Alley and Susan E. Bates

Molecular Therapeutics Section, Medicine Branch [S. D. M., E. B., P. T., C. A. J., R. G., S. E. B.], Developmental Therapeutics Program [T. G. M., M. H., M. A.], and Urologic Oncology Branch [W. M. L.], National Cancer Institute, Bethesda, Maryland 20892, and Southern Research Institute, Birmingham, Alabama 35255 [D. D.]


   ABSTRACT
Top
 ABSTRACT
INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 REFERENCES
 
We were interested in identifying novel agents for renal cell carcinoma (RCC) by screening for activities that model renal tumor biology. Searching for relative renal cell sensitivity and leukemia insensitivity among cytotoxicity profiles in the NCI Drug Screen database, we identified 16 potential agents with renal selectivity. We evaluated the agents in 10 RCC cell lines (of primary and metastatic origin) isolated from 5 patients. The 50% inhibitory concentrations (IC50) in these cell lines ranged from 0.019 ± 0.013 to 11.4 ± 0.55 µM and were comparable with values obtained with renal cell lines in the NCI Drug Screen panel. Because RCC are slowly growing tumors, we evaluated the compounds on rapidly (27% S phase) or slowly (6% S phase) growing cells. In contrast to doxorubicin, where cytotoxicity was restricted to rapidly proliferating cells, three compounds (NSC 280074, 281613, and 281817) were more cytotoxic in slowly proliferating cells. NSC 72151 and 268965 were equitoxic for both populations. NSC 94889, 638850, and 630938 were more cytotoxic in rapidly growing cells. In in vitro time exposure studies, four compounds, NSC 268965, 280074, 281613, and 281817, were maximally cytotoxic with as little as 3 h exposure time. From an analysis comparing the p53 genotype of the 60 cell lines of the National Cancer Institute (NCI) Drug Screen with the cytotoxicity profiles for the 16 putative renal compounds, 13 compounds were classified as likely to be indifferent to p53 status. We also developed a panel specificity detection method for the NCI Drug Screen database to evaluate the prevalence of renal sensitive compounds. Of the 16 studied compounds, 14 were among those identified as renal sensitive by the statistical analysis. Lastly, we found reduced tumor growth in mice with established renal human tumor xenografts after treatment with two of the renal active compounds. These studies describe compounds with potential renal activity that are candidates for preclinical development for renal cell carcinoma.


   INTRODUCTION
Top
 ABSTRACT
 INTRODUCTION
MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 REFERENCES
 
RCC3 in humans is one of the most difficult malignancies to treat (1) . Few effective therapies have been found; presently, only biological therapy offers some minimal benefit for patients with this disease. The mechanism of the extensive drug resistance observed in RCC has not been elucidated, although expression of membrane transporters and metabolism have been suggested (2) . Few antineoplastic compounds have been developed in a specific search for agents active in this disease. One potential strategy is to identify compounds active in the 7 RCC cell lines in the 60 cell line panel of the NCI Drug Screen. Similarly, it was shown that ellipticines target neurological tumors but have little activity against other tumor types (3) . Such a search strategy can be distinguished from most drug development efforts today, which focus on reaching a particular molecular target, such as p53, EGFr, or Rb (4, 5, 6) . Although both the phenotypic screen (activity in renal cancer cell lines) and the focused screen (activity in specific target assays) have advantages, the phenotypic screen can better approximate some in vivo aspects of tumor biology. To this end, we screened for activity of potential new anticancer agents for RCC in a functional manner using principles established in a recent report (7) .

RCC exhibit distinct characteristics which may make phenotypic studies potentially valuable in the search for new cytotoxic agents. First, RCC are more slowly growing than hematological neoplasms. This suggests the need to identify compounds that act on cells with this slower proliferation rate. Previous work has shown that it is possible to evaluate the action of such compounds on a colon cancer line that proliferates slowly when seeded at high density (8) . Secondly, RCC are among the most intrinsically resistant tumors and are reported to express, except for adrenocortical cancer, the highest levels of P-glycoprotein (Pgp) among tumors (9) . Thus, it would be useful to identify compounds not susceptible to Pgp-mediated resistance. Previous work has shown that if levels of MDR-1 mRNA and IC50 values are positively correlated, potential Pgp substrates could be identified (10 , 11) . Furthermore, a compound that exerts its cytotoxic action rapidly, before intrinsic resistance mechanisms activate, may also be useful.

In the studies reported here, we selected 16 compounds from the NCI Drug Screen using a visual inspection method of the cytotoxicity profiles that demonstrated greater activity in RCC lines and less in the leukemia cell lines. We then confirmed the renal activity in a panel of primary and metastatic cell lines derived from patient tumors. The compounds were evaluated in both rapidly and slowly proliferating RCC, and an in vitro time course of cytotoxicity was determined. Using the molecular target data available in the NCI database and comparing the genotype of the renal cancer cell lines with cytotoxicity profiles, we correlated MDR-1 mRNA levels, p53 status, and the presence of ras mutation with IC50 values for the compounds of interest. We also developed a panel selectivity detection method that can identify compounds with an organ-specific profile. And lastly, we found that two of three tested renal active compounds are effective in human renal xenograft models without lethality. These studies indicate that compounds with particular activity in RCC can be identified for clinical development.


   MATERIALS AND METHODS
Top
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
RESULTS
 DISCUSSION
 REFERENCES
 
Cell Lines.
Five pairs of primary and metastatic renal cell lines derived from tumor biopsies were used in these studies (109, 109LN; 121, 121LN; 124, 124LN; 154, 154LN; 161, 161LN) (12, 13, 14, 15) . The metastatic cell lines were derived from lymph node metastases. The renal cell lines A498 and CAKI-1 were obtained from the NCI Drug Screen and used to confirm in vitro cytotoxicity. For Pgp reversal studies, both the SW620 colon cell line and its multidrug-resistant subline SW620 AD300 (16) and four of the renal lines listed above were used (109, 109LN, 121, 121LN). The cell lines were maintained in Iscove’s minimal essential medium (renal lines) or RPMI (colon lines) supplemented with 10% (v/v) FCS, 20 mM glutamine, and 1000 units/ml penicillin and 1000 units/ml streptomycin (Biofluids and Life Technologies, Inc., Gaithersburg, MD).

Cytotoxic Agents.
All compounds were solubilized in DMSO (Sigma, St. Louis, MO) and stored at -20°C. Chemical structures for 11 of 16 compounds are depicted in Fig. 1Citation . Doxorubicin hydrochloride (Pharmacia, Inc., Kalamazoo, MI), cisplatin (Sigma), BCNU (Sigma), and paclitaxel (Bristol Myers Squibb, Princeton, NJ) were used as positive controls.



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  		Fig. 1. Structures of 11 renal selective compounds studied.

 
Cytotoxicity Assays.
Primary and metastatic RCC lines, A498, and CAKI-1 were seeded into 96-well plates at a concentration of 2 x 103 cells/well 1 day before drug addition. Each test compound concentration was evaluated in quadruplicate. In brief, cells were incubated for 96 h with drug, fixed with 10% (w/v) trichloroacetic acid, and then stained with SRB as previously described (17) . SRB was solubilized with 10 mM unbuffered Tris. The A564 was measured using a Bio-Rad microplate spectrophotometer. For experiments evaluating the effect of PSC 833, a Pgp modulator, 1 µg/ml (final concentration) was used. No measurable cytotoxicity occurred at this concentration.

Percent growth inhibition was calculated using the formula: . For each drug, the results were graphed using a semilog plot, and the IC50 was extrapolated.

We also adapted a previously described method of Drewinko et al. (8) . Aliquots of 2–4 x 106 cells (high density) and 3–5 x 105 cells (low density) of the 121 RCC cell line were seeded into 100 x 20-mm Petri dishes (Falcon, Franklin Lakes, NJ) containing 10 ml of complete medium and maintained in a humidified 5% CO2 incubator at 37°C without refeeding. After 72 h, compound was added directly into the plated cells. After 1 h of incubation at 37°C, the cells were trypsinized, washed, counted, and replated at different densities (1000, 2000, and 5000 cells/well). Doxorubicin was used as a routine positive control for differential activity on proliferating cells. The cells were then harvested on days 2, 3 and 4. The cells were stained with SRB using the previously described assay.

In separate in vitro time course cytotoxicity experiments, the renal active compounds were exposed to RCC line A498 (5000 cells/well) for various times and concentration ranges and then harvested using the SRB method described above.

Measurement of BrdUrd Uptake.
Cells were plated at high (2–4 x 106 cells/plate) and low density (3–5 x 105 cells/plate) cultured for 3 days before analysis of cell cycle compartments (18) . BrdUrd (Sigma) was added directly to the culture medium (10 µM) and incubated for 30 min at 37°C. The cells were then trypsinized and washed (1% (w/v) BSA (ICN Biomedicals, Inc., Aurora, OH) in PBS (PBS without magnesium and calcium; Biofluids, Rockville, MD). The cells were fixed in cold 70% (v/v) ethanol while vortexing. To denature the DNA, 2 N HCl with 0.5% Triton X-100 (v/v) (Sigma) was added to the cells while vortexing. This suspension was incubated for 30 min at room temperature and then washed. To neutralize the acid, the cells were resuspended in 0.1 M sodium tetraborate (pH 8.5; Fisher Scientific, Fair Lawn, NJ). The cells were washed, resuspended in 0.5% (v/v) Tween 20 (Sigma, St. Louis, MO) and 1.0% (w/v) BSA in PBS, and then counted. To measure the incorporated BrdUrd, 1 x 106 cells were incubated with antiBrdUrd FITC (Becton Dickinson, San Jose, CA) for 30 min at room temperature. After washing, the cells were resuspended in 5 µg/ml propidium iodide (Sigma). For the bivariate measurement of fluorescent anti-BrdUrd and the total DNA content, a FACS flow cytometer equipped with an argon laser (488 nm) was used.

Time of DNA synthesis (Ts) and potential doubling time (Tpot) were calculated based on previous methodology that directly measures the time required for BrdUrd-labeled cells to traverse S phase (19) . Ts was used to calculate potential doubling time (which assumes that all cells in a given population will divide and considers the fraction of cells not labeled with BrdUrd). The formula used was Tpot = ln 2 (Ts)/{nu}, where {nu} = ln [1 + fraction of undivided cells/(1 - fraction of divided cells/2]. This multiparametric approach provided a quantitative analysis of the cell cycle compartments rather than a limited evaluation of cell growth.

Statistical Analysis.
The Student t test (two tailed) was used to evaluate any statistical significance between the mean IC50s in Fig. 3Citation .



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  		Fig. 3. Comparison of renal selective compound IC50 values of leukemia and renal lines of the 60 cell lines of the National Cancer Institute Drug Screen. Mean ± SD were calculated from reported IC50s (http://www.dtp.nci.nih.gov) (A). In general, the leukemia cell lines were more resistant than the renal cell lines. B, renal lines of the 60 cell lines of the National Cancer Institute Drug Screen and 10 renal lines previously isolated from 5 patients with primary and metastatic tumors. Mean ± SD were calculated from reported IC50s and results from standard cytotoxicity assays. In general, the IC50 values were not different in the two subsets of renal cell lines.

 
Spearman rank correlation coefficients were determined using ranked data analyzed by the Minitab Statistical software package (State College, PA). In particular, IC50 values of the renal active compounds tested in the 10 RCC cell lines and levels of mRNA expression or protein of targets of interest including measurements of MDR-1, MRP (multidrug resistance related protein), cytokeratin 8 (CK8), EGFr [described in a previous report (15) ] were ranked and then correlated. For these comparisons, correlation coefficients >0.60 were considered statistically significant at P < 0.05. In studies where the IC50s for the renal active compounds tested in the 60 cell lines of the NCI Drug Screen were used, correlation coefficients >0.40 were considered statistically significant at P < 0.05. Similar Spearman rank correlation coefficients were calculated between the Ts and the Tpot and the IC50s of the renal active compounds tested on the10 RCC cell lines. Doubling times for the 60 cell lines are publicly available (http://dtp.nci.nih.gov) and were correlated with the IC50 values for the renal active compounds tested in the same cell lines.

The Wilcoxon rank signed test was used for analysis of genotype preferences for the IC50s of the renal active agents and p53 and ras mutational status (4 , 5) .

Panel Specificity Detection Method.
We were interested in systematically surveying the NCI Drug Screen Database for examples in which the sensitive lines were all in the renal panel. We first identified compounds within the 70,000- compound database with activity patterns that had variance >0.15 (n = 45776). To perform a one tailed analysis, the patterns were divided into sensitive and resistant categories by calculating the difference between the renal mean IC50 and the nonrenal mean IC50. Because, in large databases, there will be cases in which those relatively sensitive lines will be clustered into the same histological panel due to chance, we simulated a random activity pattern data set by taking the actual data set and reassigning the cell line labels at random. This randomized data set was analyzed in parallel with the actual data set, and the results were compared.

Whether an activity pattern suggested panel sensitivity was evaluated using the ANOVA procedure in SAS software (SAS Institute, Cary, NC) on ranked data to compute an F statistic and a probability level for the difference between the sensitivity of the renal cell lines and that of the rest of the 60 cell lines in the screen. By calculating what was effectively a Student t test on the rank data, our results approximated those of a formal Wilcoxon rank sum test of sensitivity difference between the two groups of cell lines (renal and nonrenal). We used the panel sensitivity test results from the simulation set to indicate how many activity patterns we should expect to appear significant solely due to chance. We determined the value of the F statistic that would define the most significant 5% of the randomized activity patterns. This F cutoff value, used on the results for the actual data set, defined the compounds showing significant panel specificity at {alpha} = 0.05. An identical analysis was performed on the patterns showing resistance in the renal cancer cell lines.

In Vivo Testing of Selected Dimethane Sulfonates against Human Tumor Xenografts.
A series of assays were conducted to evaluate the potential of the dimethane sulfonates, to impact tumor growth in vivo. For these studies, human tumor xenografts were generated by injection of 1 x 107 tumor cells s.c. into athymic nude mice. These cells were derived from established tumors maintained by serial passage in mice for a maximum of 10 passages (20) . Initial doubling times for these renal tumor xenografts (derived from A498, Caki-1, and RXF 393) were ~3.5 days and had a log linear growth rate throughout the observation period. Male mice were used in all experiments except when NSC 280074 and NSC 281817 were tested against A498. All animals were provided by NCI contractors at the NCI-Frederick production facility or Taconic Laboratories (Germantown, NY).

Intraperitoneal drug treatment schedules were established from the tumor doubling times because pharmacological data were not available. The dose levels were determined by establishing a single injection maximum tolerated dose (MTD) from which the experimental doses were calculated as: dose (mg/kg) = [(1.5 x MTD)/no. of doses to be given]. Each experiment consisted of 20 control mice (based on statistical need) that received dosing vehicle (saline + 0.05% Tween 80) on the same schedule as used for the test articles. Each treated group contained six mice with three dose levels tested for each of the two compounds. Tumor volumes were measured two to three times weekly and the tumor weights were calculated using the formula for a prolate ellipsoid: (21) . The control tumors reached 500 mm3 in 27 days for A498, 24 days for Caki-1, and 12 days for RXF 393.


   RESULTS
Top
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
DISCUSSION
 REFERENCES
 
Selection and Cytotoxicity of Compounds with Renal Activity.
From the NCI Drug Screen Database of 70,000 compounds, ~200 were identified that were active in the renal cell lines and less so in the remaining cell lines (K. Paull, Developmental Therapeutics Program, NCI). We studied 16, based on the relative renal sensitivity and leukemic insensitivity and compound availability. This selection was based on visual inspection of cytotoxicity profiles, examining the fingerprints for the IC50, the TGI, and the LC50 (22) . Representative TGI fingerprints for one selected compound and that of doxorubicin are shown in Fig. 2Citation . The structures of 11 of the 16 selected compounds are shown in Fig. 1Citation . The fingerprints plot the mean concentration for TGI in the 60 cell lines. For each cell line, the mean is plotted on the graph. By convention, bars to the left indicate resistance, and bars to the right indicate sensitivity. To verify this selection process, the mean IC50 ± SD of each compound was calculated for the renal and leukemia cell line panels. In 15 of 16 cases, the IC50 was lower in the renal cell lines than was the IC50 for the leukemic lines (Fig. 3A)Citation and ranged from 1.3-fold (NSC 281613) to 16.7-fold (NSC 94889). Statistically significant differences between the mean IC50s were found for compounds NSC 94889, 638850, 684459, 684480, and 684481 (P < 0.05).



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  		Fig. 2. Mean graphs of a representative renal active compound and doxorubicin. The average TGI was calculated for the 60 cell lines of the National Cancer Institute Drug Screen and used as a comparison for all other lines. The selective renal activity of NSC 281817 was of interest. The mean graph for doxorubicin is presented as a comparison.

 
To confirm the activity of the compounds in cell lines different from those of the NCI Drug Screen, we evaluated the cytotoxicity of the 16 compounds of interest in 10 renal cell lines isolated from primary and metastatic tumors from 5 patients. The IC50s in these cell lines ranged from 0.019 ± 0.013 to 11.4 ± 0.55 µM and were comparable with the NCI Drug Screen values (Fig. 3B)Citation . In 15 of 16 cases, the IC50s differed by <1 log. In only one case, NSC 281817, was a large difference noted, where the NCI Drug Screen renal lines were more sensitive.

Renal Active Compounds Act on Slowly and Rapidly Proliferating RCC.
To screen for compounds with activity on cell populations with different growth rates, we first determined the growth rate of RCC line 121 at different plating densities using incorporation of BrdUrd as a sensitive assay for DNA synthesis. Cells were seeded at high and low density, cultured for 3 days and then labeled with BrdUrd for 30 min. The results of a representative experiment shown in Fig. 4Citation indicate that a greater proportion of cells incorporated BrdUrd in low density plated (25.9%) compared with high density plated (1.9%) cells, indicating that cells plated at the lower density could serve as an assay for rapidly proliferating cells and that cells plated at high density could serve as an assay for slowly proliferating cells.



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  		Fig. 4. Effect of low and high density plating on RCC line 121 as measured by antiBrdUrd labeling. RCC line 121 was plated at high and low density 2 days before a 30-min treatment with BrdUrd. Measurement of uptake and DNA content was completed on fixed cells and then analyzed by FACS. Approximately 20% of the cells grown at low density were synthesizing DNA, whereas cells growing at high density cells were not.

 
Using this model system, we evaluated the cytotoxic effect of three concentrations of three standard agents at the two plating densities during a 1-h exposure (Fig. 5)Citation . The concentrations required ranged from 5- to 450-fold greater than the 2-day IC50. As previously shown, in slowly proliferating cells, doxorubicin had little or no cytotoxic effect; whereas in rapidly proliferating cells, cytotoxicity was measured in a concentration-dependent manner (Fig. 5A)Citation (8) . For cisplatin and BCNU, cytotoxicity was evident in both populations of cells although there was greater cytotoxic effect in the rapidly proliferating cells in a concentration dependent fashion (Fig. 5, B and C)Citation . Cytotoxicity for both cycling and noncycling populations has been reported for these two compounds (8 , 23 , 24) .



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  		Fig. 5. Effect of standard anticancer agents on rapidly and slowly growing renal cells. High and low density cells were exposed to a range of concentrations (5, 50, and 450 times the IC50 values obtained at 2 days) for 1 h, washed, and replated. Cell growth was evaluated by methods detailed in the text on days 2–4. •, {blacktriangleup}, {blacksquare}, high density cells; {circ}, {triangleup}, {square}, low density cells. As expected, only rapidly growing cells were affected by doxorubicin. In contrast, cisplatin and BCNU were equitoxic to both populations.

 
To determine whether the renal active compounds were active in slowly proliferating and/or rapidly proliferating cells, RCC line 121 was plated at high and low density and then treated for one h with renal active compound at concentrations 50 fold higher than the IC50. 9-fold higher and lower concentrations were also tested. The results indicated that three compounds (NSC 280074, 281613, and 281817) were more cytotoxic in slowly growing cells compared with rapidly growing cells (Fig. 6, A–C)Citation . Two compounds (NSC 72151 and 268965) were equitoxic to both populations (Table 1)Citation . For three compounds (NSC 94889, 638850, and 630938), there was greater cytotoxicity in rapidly proliferating cells at the two highest concentrations tested (Table 1)Citation .



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  		Fig. 6. Effect of renal active compounds on rapidly and slowly growing renal cells. High and low density cells were exposed to a range of concentrations (5, 50, and 450 times the IC50 values obtained at 2 days) for 1 h, washed, and replated. Cell growth was evaluated by methods detailed in the text on days 2–4. •, {blacktriangleup}, {blacksquare}, high density cells; {circ}, {triangleup}, {square}, low density cells. For these three compounds, greater cytotoxicity was observed in the slowly growing cells.

 

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  		Table 1 Cytotoxicity of compounds in rapidly and slowly proliferating cells

 
Correlations between Potential Doubling Time and IC50 Values May Identify Compounds Active in Slowly Growing Cells.
As a second strategy to evaluate the efficacy of the compounds against cells with a low growth rate, we correlated IC50s for the compounds in the 10 cell lines with the potential doubling time of each of the 10 cell lines. Using the BrdUrd labeling methodology, we calculated the potential doubling time in the 10 RCC cell lines as previously described (19) . The results showed that the potential doubling times ranged from 15.9 to 35.7 h (Table 2)Citation .


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  		Table 2 Calculated cell cycle parameters in RCC linesa

 
As a preliminary test of this hypothesis, a correlation was determined for the potential doubling times in the 10 cell lines and the IC50 values for doxorubicin previously reported (15) . Consistent with the results of the cell density experiments, there was a significant positive correlation for doxorubicin (r = 0.60; P < 0.05), indicating that the sensitivity to doxorubicin is dependent on the potential doubling time, with resistance occurring in cells with longer doubling times. When similar correlations were determined for the potential doubling times in the 10 renal cell lines with the IC50s of the 16 renal active compounds, a significant positive correlation was found only for NSC 684480 (Table 3Citation , r = 0.79; P < 0.05). No significant negative correlations were found, and the remaining compounds had correlations near zero. This suggested that, except for NSC 684480, the compounds were equitoxic in cells of varying doubling time. Similar results were found when the correlations were performed between the doubling time measured in growth assays in the 60-cell line Drug Screen panel, with only NSC 684481 having a positive correlation suggestive of resistance in more slowly growing cells (Table 3)Citation .


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  		Table 3 Correlation coefficients for renal active compounds and doubling timea

 
Short Exposures to Renal Active Compounds Lead to Cytotoxic Activity.
Within the set of 16 selected compounds were a family of four dimethane sulfonates (NSC 268965, 280074, 281613, and 281817) with a component resembling the known alkylating agent, busulfan. In vitro time course assays were performed on these dimethane sulfonates. Profiles of activity in the A498 renal cell carcinoma line demonstrate that all agents confer near maximum activity with brief drug exposures (<=3 h) to similar drug concentrations (with the possible exception of NSC 281613 which appears to require somewhat higher molar drug concentrations). These drug sensitivity profiles differ from most chemotherapeutic agents which often require long exposures (>=24 h) to achieve maximum or near-maximum activity. As shown in Fig. 7Citation , concentrations of 0.05–0.78 µM generally produce 50% net growth inhibition (IC50), concentrations of 0.76–3.5 µM produce TGI, and concentrations of 1.2–12.2 µM produce LC50.



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  		Fig. 7. In vitro time course assays for four renal selective compounds. Renal line A498 was exposed to a wide range of concentrations for various times. Profiles of activity demonstrate that all agents confer near maximum activity with brief drug exposures (<=3 h) to similar drug concentrations (with the possible exception of NSC 281613, which appears to require somewhat higher molar drug concentrations at the shorter intervals).

 
Renal Active Compounds as MDR-1 Substrates.
Because RCC exhibits one of the highest levels of Pgp expression in cancer, we asked whether any of the 16 compounds were substrates for Pgp-mediated resistance. It has been shown, in the 60-cell line panel, that MDR-1 mRNA expression can be effectively correlated with IC50s (10) . A significant positive correlation between the MDR-1 expression pattern and the cytotoxicity profile of a compound demarcates that compound as a Pgp substrate. No positive correlations were found by COMPARE analysis between the IC50s for the putative renal active agents and the MDR-1 mRNA levels in the 60 cell lines. Only a negative correlation for NSC 106399 was statistically significant using the 60-cell line panel IC50 values (data not shown), suggesting that this compound might be more active in MDR-1 expressing cells.

To confirm that the compounds were not Pgp substrates, cytotoxicity assays were also performed to evaluate (a) the relative resistance in a Pgp-expressing cell line and (b) sensitization by the Pgp antagonist PSC 833. For the former question, the compounds were tested in a parental colon carcinoma cell line, SW620, and its multidrug-resistant derivative, SW620 Ad300. As shown in Table 4Citation , there was no evidence of resistance to these compounds in the SW620 Ad300 cells, in contrast to the resistance observed for a known Pgp substrate, paclitaxel. Studies evaluating the effect of PSC 833 in RCC lines 109, 109LN, 121, and 121LN gave consistent results, showing no evidence of sensitization when added to the renal active compounds. Taken together, these studies confirm that the six tested compounds are not substrates for Pgp-mediated resistance.


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  		Table 4 Effect of PSC 833 on IC50 of renal selective compoundsa

 
Correlations with Genotypic and Phenotypic Markers.
Because these studies suggested that the putative renal compounds were active in slowly proliferating cells, and were not Pgp substrates, we sought to identify interactions with other characterized molecular targets. Among the previously characterized targets in the NCI Drug Screen (http://www.dtp.nci.nih.gov), there were no statistically significant correlations found. Median IC50 values for each compound in the 60 cell lines of the NCI Drug Screen were grouped depending on p53 genotype (Fig. 8)Citation or ras genotype (data not shown; wild type or mutant). Differences between the two groups were evaluated by a one sided Wilcoxon signed rank test as previously published (4 , 5) . Higher Ps may indicate that for cell lines with wild-type p53 or ras, the compound is more active; smaller Ps may indicate that for cell lines with mutant p53 or ras, the compound is less active. The results suggested that 13 compounds were likely to be indifferent to p53 status and that only 3 compounds were likely to be more active in p53 wild-type cell lines (NSC 281613, 281817, and 638850). It is likely that all compounds are indifferent to the ras genotype (data not shown). Fig. 8Citation shows the scatterplot of IC50 values distributed according to the p53 status for two of the compounds and bleomycin, showing more activity in p53 wild-type cells.



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  		Fig. 8. Distribution of IC50s for renal active compounds in wild-type and mutant p53 cell lines of the National Cancer Institute Drug Screen. Bleomycin was used because it is a representative standard agent that is dependent on p53 status (4) . Mean ± SD were calculated and evaluated for any statistical differences among the two populations. Three [NSC 281817, NSC 281613, and NSC 638850 (data not shown)] of 16 renal selective compounds were expected to be more active in wild-type p53 cell lines (P < 0.05).

 
Several parameters potentially relevant to intrinsic drug resistance were measured in the 10-cell line panel in a previous study (15) . We asked whether these parameters, CK8, EGFr, and MRP, might be relevant to sensitivity or resistance to these compounds, correlating the IC50s with the measured target values in the 10-cell line panel (Table 5)Citation . For CK8, a differentiation marker, two statistically significant correlations were found: a positive one for NSC 72151 (r = 0.69, P < 0.05); and a negative one for NSC 630938 (r = -0.80, P < 0.05). For MRP, a non-Pgp multidrug transporter, the correlation between MRP mRNA expression levels and the IC50s of the renal active compounds found one significant positive result, NSC 684459 (Table 5Citation ; r = 0.60; P < 0.05). For EGFr, a mitogenic or survival growth factor receptor of potential importance in renal cell cancer because of the very high levels of expression (25) , correlation between mRNA expression levels and the IC50s of the renal active compounds revealed three significant results: NSC 107658 (r = 0.70; P < 0.05); NSC 661153 (r = 0.61; P < 0.05); and NSC 684480 [r = 0.60; P < 0.05 (Table 5)Citation ]. These correlations could identify compounds with activity in cells expressing particular levels of the target and may direct attention to a mechanism of action or of resistance. However, the number of cell lines involved in the correlation is small, and the results require validation.


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  		Table 5 Significant Spearman correlations for 10 RCC line parameters and IC50sa

 
Detection of Panel Specificity.
Because the set of 16 compounds and the original list of 200 came from a file of compounds identified by visual inspection as having particular renal activity, we asked whether a statistically derived methodology could be developed to identify lead compounds, rather than the visual inspection method used. Cell line designations were reassigned randomly to generate new compound activity patterns. The 5% most mock-renal sensitive patterns in the randomized set were used to generate a cutoff. This cutoff, applied to the actual data set, identified a set of compounds that appeared to have patterns at least as renal selective as the top 5% in the randomized database. A false positive rate could be predicted based on the ratio of compounds above the cutoff in the random data set compared with the actual data set (Table 6)Citation . Thus, the number of compounds with renal selective activity patterns identified by chance alone can be considered to be 1023 based on the IC50 patterns and 576 based on the TGI patterns. In the actual data set, 1220 and 1523 compounds were identified as more sensitive at the IC50 and the TGI, respectively, with associated false positive rates of 84 and 38%. Among the 1220 identified by the IC50 panel specificity detection method were 13 of the16 compounds we studied, and among the 365 identified by the TGI panel sensitivity method were 9 of the 16 compounds. This method with the LC50 data generated 1180 compounds with a 21% predicted false positive rate and found 8 of the 16 compounds chosen by visual inspection. Taken together, 14 of the 16 compounds were identified by the panel specificity detection method.


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  		Table 6 Renal subpanel specific toxicity detection

 
Evaluation of Selected Compounds in an in Vivo Human Xenograft Model.
Xenograft studies were performed to determine whether three of the renal active compounds had any in vivo antitumor activity. This work was conducted by the Developmental Therapeutics Program in the NCI. For these studies, human tumor xenografts (renal cell lines A498, RXF 393, and CaKi-1) were generated following previously established protocols (20) . In each experiment, control mice received the vehicle alone on the same schedule as used for the test articles. Tumor volumes were measured 2–3 times weekly, and the tumor weights were calculated. A treated versus control value of 40% or less is considered indicative of activity. Because these values are medians, no statistical significance is inferred (Table 7)Citation . Also, a net log kill of 0.5 or greater is considered promising for future development by the Developmental Therapeutics Program. One compound (NSC 281817) markedly reduced tumor growth against all three renal tumor xenografts. NSC 268965 and 280074 had activity against RXF 393 at the highest doses, modest activity against CaKi-1 xenografts and no activity against A498 xenografts. Although there was marked body weight loss compared with controls for the A498 and RXF-393 studies (data not shown), there were no deaths at any of the doses evaluated. Thus, at least one of the renal selective compounds that are cytotoxic in vitro can alter tumor growth in vivo.


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  		Table 7 Antitumor activity of dimethane sulfonates in xenograft-bearing mice

 

   DISCUSSION
Top
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
REFERENCES
 
Because RCC is one of the most refractory of human cancers, we sought an agent active in the disease. We identified 16 compounds from the NCI Drug Screen Database of >70,000 compounds that may have particular activity in renal cancer cell lines. The cytotoxicity and IC50s were confirmed in five paired RCC lines isolated from primary and metastatic tumors. We further evaluated the cytotoxic effect of these renal active compounds on slowly and rapidly growing cells. Differential growth rates were confirmed using a BrdUrd uptake sensitive assay for the identification of synthesizing cells. Three compounds were more active, and two were equitoxic in slowly proliferating cells compared with rapidly proliferating ones. These observations were supported by correlations between the measured doubling time of the RCC lines and the IC50s, which found that the compounds were indifferent to growth rate. Four compounds were found to require only a 3-h exposure for maximum cytotoxicity in an in vitro time course assay. In genotypic screens, the IC50 values were correlated to MDR-1 mRNA expression as a means to identify potential Pgp substrates. None of the compounds was predicted to be Pgp substrates by COMPARE analysis with the 60-cell line panel. This was confirmed by Pgp reversal studies in renal cell lines and in a multidrug-resistant colon cancer cell line. Other genotypic correlations identified individual compounds as having significant correlations with p53 status, CK8, MRP, and EGFr expression. We also developed a panel specificity detection method that objectively identifies cytotoxicity patterns unique to a particular organ. Finally, we tested two compounds in three human renal tumor xenograft models and found antitumor activity.

An original goal of the NCI Drug Screen was to discover compounds that are targeted to specific tumor types (26) . The IC50 profiles of the 60 cell lines allowed us to identify compounds that were most sensitive for renal cell lines and somewhat resistant in the other cell lines representing the different tumor types. Our findings are similar to previous studies that identified ellipticinium salts as selectively active in the central nervous system tumor subpanel with a 10– to 100-fold increase in sensitivity compared with the rest of the panel (3) . Subsequent studies have not clarified the mechanisms of selectivity in the central nervous system lines for ellipticinium salts although membrane potential was identified as a potential explanation (27 , 28) . The range of sensitivity for the renal lines relative to the remaining panel was 10- (NSC 106399) to 1000-fold (NSC 634355). It is possible that the sensitivity suggests subversion of the intrinsic resistance mechanisms of RCC.

Alkylating agents such as BCNU and mitomycin C act on both noncycling and cycling cells (8 , 23 , 24) . The renal active compounds that we identified as at least equitoxic (NSC 72151 and 268965) and, in some cases, with enhanced toxicity in noncycling cells (NSC 280074, 281613, 281817), had cytotoxicity fingerprints similar to alkylating agents by COMPARE analysis in the 60-cell line panel (data not shown). Furthermore, these compounds are related dimethane sulfonates, a structure related to that of busulfan, and would be expected to possess alkylating activity. Such an activity in noncycling cells may be useful for therapeutic application in renal carcinomas because of the relative slower growth fraction compared to hematologic malignancies. The results suggest that confluent dependent resistance may not be a significant impediment to the success of this family of compounds (NSC 280074, 281613, 281817) (29) .

The usefulness of the phenotypic screen in cycling and noncycling cells awaits results from xenograft and toxicity studies in mice. Our preliminary findings, reported here, support the presence of antitumor activity in vivo. At least one of the dimethane sulfonates evaluated in these studies has significant antitumor activity against human renal carcinoma xenografts. Although other antitumor agents, e.g., L-phenylalanine mustard, have shown some effect against human renal tumor xenografts, they have not performed well in the clinical setting. The broad spectrum of renal tumor xenografts sensitive to the dimethane sulfonates is encouraging and supports the need for further studies to define the utility of these agents in human renal carcinoma.

We evaluated an in vitro time course using the renal carcinoma cell line A498 as a phenotypic screen. Rapid uptake and cytotoxic action of an anticancer agent by the renal tumor is a property that would be beneficial to success of a new anticancer agent. Four compounds reach a maximal cytotoxic response after a 3-h exposure. These findings suggest either that the intrinsic transport mechanisms do not hinder the cytotoxic response or that the compound is rapidly sequestered by binding to its target(s) before significant efflux can occur. Moreover, these findings parallel the results from the density experiments. The same group of compounds was active in both assay systems.

Previous studies have indicated that it is possible to identify a mechanism of action, or a molecular target, based on correlating cytotoxicity profiles with measurements of biological characteristics, mRNA, or protein levels (10 , 11) . For example, Pgp substrates can be identified with correlation coefficients comparing the IC50 of a compound with MDR-1 mRNA expression levels for the 60 cell lines in the NCI Drug Screen panel. COMPARE analysis with the 60-cell line panel and the IC50 of the renal active compounds did not suggest a role for Pgp in mediating resistance to these compounds (data not shown). Genotypic correlations using the 60-cell line panel have also been successful for p53 and ras mutations (4 , 5) . We identified three compounds that may have preferential activity for p53 wild-type tumors, a reasonable attribute for a compound active in renal cancer because p53 mutations are infrequently found in tumor samples. The remaining compounds were indifferent to the p53 mutational status. These findings are consistent with our original selection criteria that emphasized renal activity. The p53 wild-type status may be relevant to the cytotoxic activity of these potential alkylating agents (NSC 281613 and 281817) if intact p53 effects a significant apoptotic response.

We also correlated the IC50s of the putative renal compounds with mRNA and protein levels of two potentially biologically relevant molecules in RCC. Using CK8 as a marker of differentiation, one compound (NSC 72151) was identified as potentially targeted to dedifferentiated cells whereas another (NSC 630938) may be more active in differentiated cells. Correlations were also evaluated for EGFr and the IC50s as a means to identify compounds that might be more sensitive to RCC. Three compounds were more resistant in cells expressing higher levels of EGFr mRNA. Each of these correlations was statistically significant using a Spearman rank test. However, the correlations were performed with data from only 10 cell lines, and independent models will need to be established to validate the findings.

The structures of some of the 16 renal active compounds may reveal possible mechanisms of action. For example, NSC 72151 is a coumarin derivative. Coumarins have anticoagulant and immune stimulatory properties that have been tested in patients with RCC (30 , 31) . NSC 72151, 268965, 280074, 281613, and 281817, as mentioned above, are dimethane sulfonates and are likely to be alkylating agents. NSC 94889 is a gardenin, a substituted flavone related to quercetin which has protein kinase C-modulating properties suggesting a role for differentiation (32) . In addition, gardenin D has also been shown to inhibit lipid peroxidation (33) . Two agents against cytoskeletal proteins, cucurbitacin E (NSC 106399) and cytochalasin (NSC 107658), appeared to have renal activity but are not likely candidates for preclinical studies because of apparent lethal toxicity in vivo (34, 35, 36) . NSC 281613 and 281817 are thiocarbanilamides linked to a dimethane sulfonate originally synthesized as antitubercular agents (37, 38, 39) . Interestingly, we independently selected NSC 638850, as possessing significant activity in the renal subpanel, especially when the 50% lethal concentration was compared between subpanels (40 , 41) . This compound, UCN-01, is currently in clinical trials as a protein kinase inhibitor. We also identified a group of compounds called thiophenes (NSC 629035) that have been noted previously to be selectively metabolized by some renal lines (42 , 43) . Thus, if structure reveals function, we have identified a diverse group of compounds that may act on many cellular targets in RCC.

Because in a large database patterns appearing to indicate disease specificity can be observed by chance alone, we developed a panel specificity detection method. First, a simulated data set consisting of randomized cytotoxicity patterns was evaluated. This allowed us to determine a false positive rate. A list of compounds could be generated that were more highly renal selective than a cutoff established by the simulated data set. Interestingly, 14 of the 16 compounds that we selected by visual inspection were included in those identified by the panel specificity detection method. These results suggest that this method can be used to generate a list of lead compounds with potential activity in a given tumor type.

In conclusion, we identified 16 agents with potential activity in RCC. Phenotypic and genotypic screens allowed us to further characterize these compounds to determine whether their activity profiles are consistent with our understanding of tumor biology in vivo. Antitumor activity in in vivo models provided supportive evidence for the utility of our screening process. Thus, compounds NSC 72151, 268965, 280074, 281613, and 281817 with potential alkylating activity have promise for new agents targeted to RCC.


   ACKNOWLEDGMENTS
 
We thank Drs. Robert J. Schultz, Ven Narayanan, and Ed Ketchledge, Development Therapeutics Program, National Cancer Institute, Bethesda, MD.

Permission to publish information relating to the following compounds is appreciated: NSC 630938, Dr. James B Pierce, CK Witco Corp., Middlebury, CT; NSC 634355, Drs. Stephen Miller and Stephanie French, Food and Drug Administration, Bethesda, MD.


   FOOTNOTES
 
The costs of publication of this article were defrayed in part by the payment of page charges. This article must therefore be hereby marked advertisement in accordance with 18 U.S.C. Section 1734 solely to indicate this fact.

1 Supported by National Cancer Institute Contract NO1-CM-47000. The animal studies reported herein were conducted at Southern Research Institute. Back

2 To whom requests for reprints should be addressed, at Molecular Therapeutics Section, Medicine Branch, National Cancer Institute, NIH, Building 10, Room 12N226, Bethesda, MD 20892. Phone: (301) 402-3524; Fax: (301) 402-0172; E-mail: smertins{at}box-s.nih.gov Back

3 The abbreviations used are: RCC, renal cell carcinoma; IC50, 50% inhibitory concentration; EGFr, epidermal growth factor receptor; Pgp, P-glycoprotein; SRB, sulforhodamine B; BrdUrd, bromodeoxyuridine; MRP, multidrug resistance related protein; CK8, cytokeratin 8; TGI, total growth inhibition; LC50, 50% lethal concentration; NCI, National Cancer Institute; BCNU, 1,3-bis(2-chloroethyl)-1-nitrosourea. Back

Received 2/28/00; revised 8/10/00; accepted 12/ 4/00.


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 DISCUSSION
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