modulation of gene expression and cell cycle signaling...

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Modulation of Gene Expression and Cell Cycle Signaling

Pathways by the EGFR Inhibitor Gefitinib (Iressa) in Rat

Urinary Bladder Cancer

Yan Lu1, 2, Pengyuan Liu1, 2, Francoise Van den Bergh5, Victoria Zellmer5, Michael

James5,Weidong Wen1, Clinton J. Grubbs3, Ronald A. Lubet4, and Ming You1, 5, 6

1Department of Surgery and The Alvin J Siteman Cancer Center, Washington University School

of Medicine, Saint Louis, MO 63110, USA

2Department of Physiology and the Cancer Center, Medical College of Wisconsin, Milwaukee,

WI 53226, USA

3Department of Surgery, University of Alabama at Birmingham, Birmingham, AL, USA

4Division of Cancer Prevention, National Cancer Institute, Executive Plaza North, Suite 2110,

6130 Executive Boulevard, Bethesda, MD 20852, USA

5Department of Pharmacology and Toxicology and the Cancer Center, Medical College of

Wisconsin, Milwaukee, WI 53226, USA

Running title: Effects of Iressa on rat urinary bladder cancers

Key words: Bladder cancer, gene expression, Iressa, cell cycle, rat

6 Corresponding author:

Ming You

Department of Pharmacology and Toxicology and the Cancer Center

Medical College of Wisconsin

Milwaukee, WI 53226, USA.

Tel: 414-955-2565; Fax: 414-955-6058

E-mail: [email protected]

Cancer Research. on June 28, 2019. © 2011 American Association forcancerpreventionresearch.aacrjournals.org Downloaded from

Author manuscripts have been peer reviewed and accepted for publication but have not yet been edited. Author Manuscript Published OnlineFirst on October 7, 2011; DOI: 10.1158/1940-6207.CAPR-10-0363

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Abstract

The EGFR inhibitor Iressa has demonstrated strong preventive efficacy in the N-butyl-N-

(4-hydroxybutyl)-nitrosamine (OH-BBN) model of bladder cancer in the rat. To explore its

antitumor mechanism, we implemented a systems biology approach to characterize gene

expression and signaling pathways in rat urinary bladder cancers treated with Iressa. Eleven

bladder tumors from control rats, seven tumors from rats treated with Iressa and seven normal

bladder epithelia were profiled using Affymetrix Rat Exon 1.0 ST Arrays. We identified 713

down-regulated and 641 up-regulated genes in comparing bladder tumors vs. normal bladder

epithelia. In addition, 178 genes were down-regulated and 96 genes were up-regulated when

comparing control tumors vs. Iressa-treated tumors. Two coexpression modules that were

significantly correlated with tumor status and treatment status were identified (r = 0.70, P = 2.80

× 10-15 (bladder tumor vs. normal bladder epithelium) and r = 0.63, P = 2.00 × 10-42 (Iressa-

treated tumor vs. control tumor), respectively). Both tumor module and treatment module were

enriched for genes involved in cell cycle processes. Twenty-four and twenty-one highly

connected hub genes likely to be key drivers in cell cycle were identified in the tumor module

and treatment module, respectively. Analysis of microRNA genes on the array chips

demonstrated that tumor module and treatment module were significantly associated with

expression levels of let-7c (r = 0.54, P = 3.70 × 10-8 and r = 0.73, P = 1.50 × 10-65 respectively).

These results suggest that let-7c down-regulation and its regulated cell cycle pathway may play

an integral role in governing bladder tumor suppression or collaborative oncogenesis and that

Iressa exhibits its preventive efficacy on bladder tumorigenesis by up-regulating let-7 and

inhibiting the cell cycle. Cell culture study confirmed that the increased expression of Let-7c

decreases Iressa-treated bladder tumor cell growth. The identified hub genes may also serve as




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pharmacodynamic or efficacy biomarkers in clinical trials of chemoprevention in human bladder

cancer.




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Introduction

Bladder cancer is one of the most common cancers in the United States and occues

predominantly in men. In 2010, there will be an estimated 70,530 new cases of bladder cancer,

with 52,760 cases in males (1). It is also the most expensive form of cancer to treat.

Approximately 15% of bladder tumors become invasive tumors after infiltration through the

basement membrane. Patients with muscle invasive disease are at high risk for recurrence,

progression, and metastasis.

Treatment of mice or rats with N-butyl-N-(4-hydroxybutyl)-nitrosamine (OH-BBN)

results in transitional and squamous cell urinary bladder cancers that bear significant

histopathological similarities to human bladder cancer and tends to be muscle invasive (2-4).

This rodent model has been used extensively to characterize the tumorigenic process and to

assess the efficacy of potential chemopreventive agents to inhibit the development of carcinogen-

induced bladder cancers (4-8). OH-BBN-induced bladder tumors have increased production of

survivin and GST-Pi, and decreased production of FHIT due to promoter methylation by

immunohistochemistry analysis (9, 10). Similar molecular changes are observed in human

bladder tumors (11). Microarray analysis of OH-BBN-induced bladder tumors revealed a wide

variety of induced genes, including cyclin D1, PCNA, COX-2, the calcium binding proteins

S100A4, S100A8, S100A10, and Annexin1 (12). Tumors which form in the rat bladder tumor

model are similar at the level of gene expression to muscle invasive bladder tumors found in

humans (13).

Recently, we examined the preventive effects of the EGFR inhibitor Iressa on the

induction of bladder tumors by OH-BBN (14). Treatment with Iressa (10 mg/kg body




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weight/day), beginning either two weeks or 12 weeks after the last dose of OH-BBN (when

microinvasive carcinomas exist), decreased the incidence of large palpable bladder cancer

by >90% at 6 months after the last dose of OH-BBN. To explore the mechanism of the antitumor

action of Iressa in the treatment of bladder tumors, we implemented a systems biology approach

to characterize gene expression and pathway modulation in rat bladder tumors treated with Iressa.

Materials and Methods

Rat bladder tumors

Female Fischer-344 rats were obtained from Harlan Sprague-Dawley, Inc. (Indianapolis,

IN; virus-free colony 202) at 28 days of age and were housed in polycarbonate cages (five per

cage). The animals were kept in a lighted room 12 hours each day and maintained at 22 ± 0.5°C.

Teklad 4% mash diet (Harlan Teklad, Madison, WI) and tap water were provided ad libitum. The

carcinogen, N-butyl-N-(4-hydroxybutyl)-nitrosamine (OH-BBN, TCI America, Portland, OR)

(150 mg/gavage, 2x/week) was started when the rats were 49 days of age and continued for 8

weeks. The carcinogen vehicle was ethanol: water (20:80) in 0.5 ml. All animals (unless

sacrificed early because of palpable tumor burden greater than 2 cm, weight loss greater than

20% of initial body weight or because animals became moribund), were sacrificed 8 months

following the initial OH-BBN treatment. Starting six months after the initial dose of OH-BBN,

animals were palpated twice per week for the development of lesions. when an animal had

developed a small palpable tumor (150-300 mg), rats were treated daily with Iressa at a dose

level of 10 mg/ kg body weight, and sacrificed five days later. At the time of sacrifice, the

urinary bladder from each rat was tied off, and samples of control bladder tumors, normal

bladder epithelia, and bladder tumors from rats treated with Iressa were excised, snap-frozen in




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liquid nitrogen, and stored at -80ºC for subsequent RNA isolation and protein extraction.

Additional bladder tissue from the same rat was fixed with 10% neutral formalin. After fixation,

the bladders were examined under a high-intensity light dissecting microscope for lesions. Each

lesion was separately embedded in a paraffin block, and random transverse sections (5 µm) from

two different levels were cut and stained with hematoxylin and eosin (H&E) for histopathology.

All bladder tumors used in this study were diagnosed as bladder cancers with a mixed histology

showing elements of both transitional and squamous cells. Normal bladder epithelia came from

age-matched controls. To isolate bladder epithelia, we separated epithelial cells from the stroma

and muscle tissues by cutting the bladder into halves and scraping off the epithelium using a

surgical blade and forceps.

RNA isolation and amplification

Total RNA from normal bladder epithelia, bladder tumors, and bladder tumors treated

with Iressa were isolated by Trizol (Invitrogen, Carlsbad, CA) and purified using the RNeasy

Mini Kit and RNase-free DNase Set (QIAGEN, Valencia, CA) according to the manufacturer’s

protocols. In vitro transcription-based RNA amplification was performed on each sample. cDNA

for each sample was synthesized using a Superscript cDNA Synthesis Kit (Invitrogen) and a T7-

(dT)24 primer: 5’-GGCCAGTGAATTGTAATACGACT-CACTATAGGGAGGCGG-(dT)24-3’.

The cDNA was purified using phase-lock gel (Fisher Cat ID E0032005101) phenol/chloroform

extraction, and then the biotin-labeled cRNA was transcribed in vitro from cDNA using a

BioArray High Yield RNA Transcript Labeling Kit (ENZO Biochem, New York, NY) and

further purified using the RNeasy Mini Kit.




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Affymetrix rat exon arrays

The labeled cRNA was applied to the Affymetrix Rat Exon 1.0 ST Array (Affymetrix,

Santa Clara, CA) according to the manufacturer’s recommendations at Vanderbilt Gene

Microarray Core. Routine quality assessment was performed on each exon array. The study used

10 arrays from bladder tumors, 7 arrays from normal bladder epithelia and 7 arrays from Iressa-

treated bladder tumors that had passed quality control criterion as recommended by the

manufactures. Gene-level and individual exon signal estimates for the CEL files from the

platform Rat Exon 1.0 ST Array were derived by the Robust Multi-array Average (RMA)

algorithm, as implemented with Expression Console v1.1.1

(Http://www.affymetrix.com/products_services/software/specific/expression_console_software.a

ffx).

Identifying differentially expressed genes

Two-sample student t test was used to identify differentially expressed genes (DEGs)

between two groups. To adjust for multiple testing in the study of high-dimensional microarray

data, the local false discovery rate (LFDR) was estimated (15), which was implemented in the R

package fdrtool (http://www.r-project.org/). The DEGs were defined as genes with LFDR < 0.05

and fold change > 1.5 between two groups.

Gene set enrichment analysis

Gene set enrichment analysis (GSEA) was performed to analyze the pattern of

differential gene expression. GSEA is a computational method that determines whether a set of

genes shows statistically significant differences in expression between two biological states, and

has proved successful in discovering molecular pathways involved in human diseases




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(http://www.broad.mit.edu/gsea). Using the Kolmogorov-Smirnov statistic, GSEA assesses the

degree of “enrichment” of a set of genes (e.g. a pathway) in the entire range of the strength of

associations with the phenotype of interest. GSEA was used to identify a priori defined sets of

genes that were differentially expressed (16, 17). We used curated gene sets (c2) which contain

genes in certain molecular pathways, and gene ontology (GO) gene sets (c5) which consist of

genes annotated by the same GO terms in the Molecular Signature Database (MSigDB,

http://www.broad.mit.edu/gsea/msigdb/msigdb_index.html). Due to a small sample size, the

GSEA with the gene set permutation option was performed. Selected gene sets identified from

GSEA were then visualized with MetaCore™ software (http://www.genego.com/).

Hierarchical clustering analysis

Hierarchical clustering was performed as follows. For the selected genes, expression

indexes were transformed across samples to an N (0,1) distribution using a standard statistical Z-

transform. These values were input to the GeneCluster program of Eisen et al. (18) and genes

were clustered using average linkage and correlation dissimilarity.

Coexpression network analysis

To characterize gene expression and pathways in rat bladder tumors treated with Iressa,

we applied a systems biology approach using a weighted gene coexpression network analysis

(WGCNA) (19). The WGCNA converts gene coexpression measures into connection weights as

topology overlap measure (TOM). We chose expression profiles of 4500 genes in the

coexpression network analysis. These genes were either significantly differentially expressed

between tumors with and without Iressa treatment (LFDR < 0.05 and fold change > 1.5 between

two groups) or showed a large variability in expression. In weighted gene coexpression networks,




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modules correspond to clusters of highly correlated genes. We defined modules using a static

method by hierarchically clustering the genes using 1-TOM as the distance measure with a

height cutoff of 0.95 and a minimum size (gene number) cutoff of 40 for the resulting

dendrogram.

To identify which module is correlated with treatment, we first calculated the module

eigengene (i.e., first principal component of the expression values across subjects) using all

genes in each module. We then correlated the module eigengenes to treatment using the

Spearman Correlation. We determined intramodular connectivity for each gene by summing the

connectivity of that gene with every other gene in that module. All network analyses were

implemented in the statistical package WGCNA in R environment (20). The VisANT program

was used to construct gene-gene interaction (connections) networks (21). Genes within modules

were analyzed for GO term enrichment by the program DAVID (22).

Exon splicing analysis

A number of splicing-related mutations have been reported to be associated with

malignancies, and some of these are within splice sites or splicing enhancers/silencers of cancer-

related genes (23-25). To identify exon splicing, we first calculated the splicing index for each

exon. The splicing index gives a measure of the difference in expression level for each probeset

in a gene between two sets of arrays, relative to the gene-level average in each set. This is

calculated only for those probesets that are defined as exon targeting and non-multitargeted.

Then, MIDAS (Microarray Detection of Alternative Splicing) algorithm was used for the

detection of alternative splicing events. MIDAS p-value was calculated by the "splanova"

function. For genes containing at least one significant exon targeting probeset, we also calculated

the maximum splicing index and retrieved the average fold change for each gene. The average




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fold changes were used to partition the dataset into (on average) up and down- regulated genes.

All exon splicing analyses were implemented in the statistical package exonmap

(http://bioinformatics.picr.man.ac.uk).

Cell culture and treatment

The iressa sensitive UMUC-5 cell line (human squamous cell carcinoma of the bladder;

Sigma, St. Louis, MO) were cultured in EMEM (EBSS) supplemented with 2mM Glutamine, 1%

Non Essential Amino Acids (NEAA), 1% penicillin/streptomycin, and 10% Foetal Bovine

Serum (FBS) (Invitrogen, Carlsbad, CA). The iressa (Santa Cruz Biotechnology, Santa Cruz, CA)

was reconstituted in DMSO at a stock concentration of 70 mmol/L, and stored at -80°C. This

stock was diluted in medium just before use so that the concentration of DMSO never exceeded

0.1%. For qPCR, the cells were grown in 10cm dishes and allowed to reach 50-70% confluency;

at that point the cells were treated with the indicated concentration of iressa for 24 hours.

Following the incubation, the cells were collected by trypsinization, washed in cold PBS,

counted, and frozen as cell pellets. For MTS assay (CellTiter 96® AQueous One Solution Cell

Proliferation Assay, Promega, Madison, WI), 10,000 cells per well were plated in 24 well-plates.

24 hours later, the medium was changed and the indicated amount of iressa was added. The MTS

assay was performed following manufacturer protocol on that day (as day 0) and the following

days.

miRNA qPCR

The protocol for miRNA isolation using the miRNeasy Mini kit (Qiagen, Valencia, CA)

was followed, including following Appendix A which deals specifically with the preparation of a

miRNA-enriched fraction using the Qiagen RNeasy MinElute Cleanup Kit. The protocol for RT2




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miRNA first strand kit was followed to obtain the cDNA template for the qPCR reaction. The

SsoFast Evagreen supermix (Biorad, Hercules, CA) protocol was followed for the qPCR

reactions – performed in triplicate, a no-DNA reaction and a primer set corresponding to a

house-keeping miRNA was included. The cycling program included a melt curve. The primer

sets for let-7c (MPH0003A-200) and RNU6-2 (MPH01653A-200) were purchased from Qiagen

(Valencia, CA).

Results

Differentially expressed bladder cancer genes altered with Iressa treatment

We observed 713 down-regulated and 641 up-regulated genes in OH-BBN-induced rat

bladder tumors (LFDR < 0.05 and fold change > 1.5 between two groups). Down-regulated

genes in bladder tumors are enriched in several metabolic processes such as lipid metabolic

processes and cellular ketone metabolic processes (Figure 1a and Table S1) and up-regulated

genes are enriched in cell proliferation and migration processes (Figure 1b and Table S2).

Similarly, we compared gene expression in control bladder tumors and Iressa-treated tumors

identified 178 up-regulated genes and 96 down-regulated genes in Iressa treated versus control

tumors. Most of the Iressa up-regulated genes are involved in metabolic processes (Figure 1c and

Table S3). The three most significant GO terms found in the down-regulated genes after Iressa

treatment were: cell cycle phase, cell cycle processes, and M phase (Figure 1d and Table S3).

Differentially expressed genes (DEGs) were input into hierarchical clustering analysis of all the

samples. Three distinct groups were identified in complete concordance with the sample status as

normal bladder epithelia, bladder tumor, and bladder tumor treated with Iressa (Figure 2a),

implying that these DEGs capture biological differences of the three tissue groups. Additionally,




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Iressa-treated tumors clustered more closely to normal bladder epithelia than bladder tumors

without Iressa treatment. Thus, short term Iressa treatment reversed many of the gene changes

associated with bladder neoplastic transformation and progression such as Mki67, Bub1, Cdc20,

TOP2A and etc. This is further supported by hierarchical clustering of cell cycle-related DEGs

which revealed that Iressa-treated tumors were more similar to normal bladder epithelium, than

control tumors (Figure 2b).

Gene coexpression networks and biological pathways

Sets of genes with expression levels that are highly correlated may share common

biological process and regulatory mechanisms. To examine this possibility we analyzed global

expression profiles and their interactions in the study samples. To accomplish this, we

constructed weighted gene coexpression networks based on pairwise Pearson correlations

between the expression profiles. As indicated previously, the identified DEGs captured

biological significance of the three tissue groups and thus were used to construct the network.

The analysis included an additional 2,872 genes with greatest variability which determined by

their coefficient of variance from 13,855 remaining genes. We performed coexpression network

analyses in datasets of control tumors vs. normal bladder epithelia, and control bladder tumors vs.

bladder tumors treated with Iressa, separately.

The WGCNA analysis identified a number of modules with highly coexpressed genes in

both datasets (Figure 3). These modules are significantly enriched for biologically important

processes that are relevant to cancer, including those for the cell cycle, immune response,

lymphocyte and T cell activation, response to DNA damage, and RNA binding and processing.

We then examined if individual expression profiles within each of the identified modules are

associated with clinically-related traits by estimating the module eigengene. In the datasets of




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control tumors vs. normal samples, we found significant correlation of tissue status (i.e., cancer

vs. normal) with the salmon-colored module (r = 0.70, P = 2.80 × 10-15) (Figure 4a).

Interestingly, the salmon-colored module also showed a significant correlation with expression

levels of let-7c which is a microRNA gene (r = 0.54, P = 3.70 × 10-8) (Figure 4b). In the dataset

of control bladder tumors vs. bladder tumors treated with Iressa samples, we found that the

green-colored module is associated with both tumor treatment status (i.e., tumors with Iressa

treatment vs. tumors without Iressa treatment) (r = 0.63, P = 2.00 × 10-42) (Figure 4c) and let-7c

expression (r = 0.73, P = 1.50 × 10-65) (Figure 4d). Both the salmon- and green-colored modules

are significantly enriched for cell cycle processes (P = 5.97 × 10-9 and P = 1.90 × 10-16,

respectively).

Highly connected “hub” genes are hypothesized to play an important role in organizing

the behavior of biological modules (26). To identify hub genes in the salmon- and green-colored

modules, we estimated intramodular connectivity for each gene based on its Pearson correlation

with all of the other genes in the modules. The genes with high intramodular connectivity tended

to have stronger correlation with clinically-related traits (Figure 4). We set the weighted cutoff

value of 0.40 to identify hub genes with the strongest connections to other genes. As a result, we

identified 24 hub genes with at least 40 connections in the datasets of control tumors vs. normal

samples, including Cdca2, Lmnb1, Sgol2, Tpx2, Anln, Nuf2, Kif4, Ect2, Bub1, Prc1, Kif20a, Cit,

Uhrf1, Depdc1, Racgap1, RGD1310335, Casc5, Dtl, Ccna2, Bub1b, Tacc3, Iqgap3, Fancd2 and

Cenpf; while 20 genes were identified in the dataset of control bladder tumors vs. bladder tumors

treated with Iressa samples (Fancd2, Cep55, LOC683179, Kif2c, Ttk, Cenpf, Bub1, Ect2, Kif20a,

Nuf2, Tpx2, Cdca2, Ccnb1, Depdc1, Ncapd2, Melk, RGD1562646, Mastl, Ccna2, and Sgol2).




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To illustrate their relationship, these genes are visualized in Figure 5, suggesting a complex

regulatory gene network with varying topology.

To explore the effects of let-7c expression on Iressa-treated bladder tumor growth, we

checked the expression of let-7c in an iressa sensitive human squamous cell carcinoma of the

bladder cell line UMUC-5 in the presence of increasing amount of iressa. We first confirmed that

the UMUC-5 cell line was iressa sensitive following their growth curve in 0.1μM, 0.2μM, and

0.5μM iressa compared to no iressa added. As previously described (27) and as seen in Figure 6a,

iressa affected the growth of UMUC-5 at concentration higher than 0.1μM. This experiment was

done in triplicate and was performed twice with similar results. We then collected the miRNA

from UMUC-5 exposed for 24 hours to 0.2μM, and 0.5μM of iressa in parallel with a no

treatment condition. These three samples of miRNA were used in qPCR reactions using either

let-7c or RNU6-2 primer set. The results from the RNU6-2 reactions were used to normalize let-

7c expression. As observed in Figure 6b, iressa induced 3 and 8 fold up-regulation of let-7c

when added at 0.2μM and 0.5μM, respectively. This qPCR was performed twice with similar

results. These results confirmed the association of let-7c expression with iressa treatment

observed in our microarray analysis of rat model,

Exon splicing

Alternative processing of pre-mRNA transcripts is a major source of protein diversity in

eukaryotes and has been implicated in several disease processes including cancer (28). To

identify alternative splicing variants, we calculated the splicing index (SI) for each exon; a

measure of how much exon specific expression, with gene induction factored out, differs

between two types of tissues (e.g., bladder tumors vs. normal bladder epithelia, or bladder

tumors with treatment vs. without Iressa treatment). Using the cutoff of maximum SI > 1 and P <




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1.0 × 10-4, we identified 194 and 272 genes that have alternative splicing that are down and up-

regulated in bladder tumors vs. normal epithelia, respectively. Figure S1 listed the top genes

alternatively spliced between normal bladder epithelia and bladder tumors.. These alternatively

spliced genes are enriched in organ morphogenesis, regulation of cell proliferation, cell

migration, and immune system processes. Using the same criteria, we also identified 57 genes

that have alternative splicing that are differentially expressed in control tumors and Iressa-treated

tumors (Table S4). Interestingly, 24 of the 57 genes overlapped with the list of genes that have

alternative splicing in bladder tumors vs. normal bladder epithelia, suggesting that Iressa

treatment blocks aberrant splicing in these 24 genes in bladder tumors. For example, we

identified exon splicing in Prkn2 when comparing exon-specific expression between bladder

tumors and normal bladder tissues (Figure S2). The same exon splicing was observed between

control tumors and treated tumors. The rationale behind these two observations is that Iressa

treatment blocks aberrant splicing and thus treated tumors have similar splicing status to normal

samples.

Discussion

We have recently shown that EGFR inhibitors were highly effective in preventing

OHBBN-induced rat bladder cancer (14). Efficacy was observed either when Iressa treatment

was initiated early in tumor progression (early hyperplasia) or when invasive microcarcinomas

already existed (14). This indicates that Iressa is effective during the later stages of tumor

progression. The traditional concept of prevention would test the agents before cancer

development. In our study the animals in the Iressa treatment group were given Iressa after they

developed a small palpable tumor (150-300 mg). The reasons of such design are as follows: A)




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Human Phase III clinical trials in prevention are relatively late. The prime example of a

“prevention trial” in bladder is to inhibit the recurrence of bladder cancer by the cancer

chemopreventive retinoid N-(4 hydroxyphenyl)retinamide (4HPR) within a period of 18 months.

This is not an early intervention similar to the study with OHBBN proposed. Recently we have

argued strongly that a later intervention in animal models appears more relevant to apparent

Phase III clinical trials particularly given that the animal models are typically not as genetically

as advanced as human cancers (29). We showed that Iressa is highly effective in this model when

administered at the time that microcarcinomas already exist implying that most of the effects of

the agent are in the latter stages of progression (14). B) Examining for biomarkers in palpable

lesions. The argument for examining for biomarkers in early stage palpable lesions comes from

the results observed in breast cancer. Results in humans have shown clearly that the two known

positive “preventive” agents SERMs examined in large prevention trials and Aromatase

Inhibitors in prevention trials but clear data from inhibition of tumors of the contralateral breast

in an adjuvant setting yield major changes in biomarkers in a presurgical setting with early stage

cancer (30). We have used such an approach to examine a wide variety of effective and

ineffective agents in a breast cancer model and found a close correlation between alterations of

biomarkers in this presurgical setting and efficacy in long term prevention studies particularly

when initiated further along in tumor progression (31). This is not an argument that there are

agents which might be effective early in the process of tumor progression but are ineffective at

later times will not give a strong signal in this later intervention. C) Practical questions. For

many of the earlier stages of tumor progression one either gets limited numbers of lesions or the

lesions are fairly small and can only be identified when tissue is fixed. These practical problems

virtually preclude the overall screening by arrays or proteomics of changes in earlier lesions.




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The objective of part of this study is to define potential biomarkers which we might examine in

earlier lesions either by IHC or RT-PCR. It is not a therapeutic study per se but rather a search

for potentially useful pharmacodynamic and perhaps efficacy biomarkers.

The efficacy of Iressa agrees with findings that genes and proteins associated with the

EGFR pathway are over expressed in bladder tumors as compared to normal bladder epithelia in

both rodent model and humans (12, 32 ). Initial studies showed great promise for the use of

EGFR inhibitors in the setting of advanced bladder cancer in humans (33, 34). As expected,

Iressa treatment strikingly decreased levels of phosphorylated EGFR, AKT and ERK (Data not

shown.). The present study examined the effects of Iressa on gene expression in lesions with two

objectives: to (1) identify processes and pathways involved in the mechanism of Iressa efficacy;

and (2) identify biomarkers which might be useful in clinical trials with this class of antitumor

agents.

Studies suggest that highly centralized ‘hub’ genes in the network architecture are more

likely to be key drivers for cellular function (35). Characterization of these hub genes may help

to give novel insight into bladder tumorigenesis and to develop additional novel drug targets for

bladder cancer. Many of the hub genes we identified in the tumor and treatment modules are cell

cycle regulators such as Bub1, Casc5, Ccna2, Cenpf and so on. Bub1, which was identified as a

highly connected gene in both modules, encodes a kinase involved in spindle checkpoint

function. This kinase functions in part by phosphorylating a member of the mitotic checkpoint

complex and activating the spindle checkpoint. P53 physically interacts with Bub1 at

kinetochores in response to mitotic spindle damage, suggesting a direct role for hBub1 in the

suppression of p53 mediated cell death (36). Altered expression of Bub1 is associated with

therapy failure and death in patients with multiple types of cancer (37). Casc5, identified as




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another hub gene in both modules, is required for chromosome alignment and the mitotic

checkpoint through direct interaction with Bub1 and BubR1 (38). Ccna2 binds and activates

CDC2 or CDK2 kinases, and thus promotes both cell cycle G1/S and G2/M transitions (39, 40).

Cdca2 is a cell cycle regulator and selectively recruits PP1γ onto mitotic chromatin at anaphase

and into the subsequent interphase. Depletion of Cdca2 by RNAi knockdown leads to large-scale

cell death by apoptosis, primarily in interphase; as did overexpression of this dominant-negative

mutant (41). Cenpf is another cell cycle regulator. Farnesylation of Cenpf is required for G2/M

progression and degradation after mitosis (42).

Several unique hub genes were identified in the module associated with efficacy of Iressa

treatment, including Ccnb1, Cep55, Kif2c, LOC683179, Mastl, Melk, Ncapd2, and

RGD1562646. Cep55 encodes a centrosomal associated protein involved in centrosome

duplication, cell cycle progression, and in the regulation of cytokinesis (43). Kif2c encodes a

kinesin-like protein which has a role in bipolar spindle assembly (44). Melk is a potential

regulator of G2/M progression and may antagonize the CDC25B phosphatase (45). Ncapd2 is an

essential component of the human condensin complex required for mitotic chromosome

condensation (46). These hub genes might be useful biomarkers in clinical trials with this class

of agents.

Previous studies showed that several hub genes are associated with human bladder cancer.

For example, the expression levels of NUF2 were increased in the majority of small cell lung

cancer, cholangiocellular cancer, urinary bladder cancer and renal cell cancers (47). The

MPHOSPH1/PRC1 complex is likely to play a crucial role in bladder carcinogenesis and that

inhibition of the MPHOSPH1/PRC1 expression or their interaction should be novel therapeutic

targets for bladder cancers (48). KIF20A were up-regulated in bladder tumors in both humans




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and rodents (49). An immunohistochemistry-based UHRF1 detection in urine sediment or

surgical specimens can be a sensitive and cancer-specific diagnostic and/or prognosis method,

and may greatly improve the current diagnosis based on cytology (50). Immunocytochemical

staining analysis detected strong staining of endogenous DEPDC1 protein in the nucleus of

bladder cancer cells and DEPDC1 expression was hardly detectable in any of 24 normal human

tissues except the testis. Suppression of DEPDC1 expression with small-interfering RNA

significantly inhibited growth of bladder cancer cells. DEPDC1 might play an essential role in

the growth of bladder cancer cells, and would be a promising molecular-target for novel

therapeutic drugs or cancer peptide-vaccine to bladder cancers (51). RacGAP1 are expressed at

high levels in superficial bladder TCC patient samples (52).

We identified two modules that are significantly associated with either cancer status

(control cancer vs. normal bladder epithelium) or Iressa treatment status (Iressa-treated tumors vs.

control tumors). An increase in proliferation-related genes was observed in the cancer vs.

normal bladder epithelium, while a decrease in proliferation-related genes were observed in

Iressa-treated tumors vs. control tumors. Interestingly, these two modules also showed

significant association with let-7c expression. Let-7 is a microRNA and is a bona fide tumor

suppressor. Let-7 inhibits the expression of multiple oncogenes, including RAS, MYC and

HMGA2. Multiple important cell cycle control genes are repressed by let-7, including cyclin D1,

cyclin D3, cyclin A, CDK4 and CCNA2, CDC25A, CDK6, and CDK8 (53, 54). Decreased let-7

expression is linked to increased tumorigenesis and poor patient prognosis (55-58). This is in

agreement with our observation that a decrease in let-7c expression in tumors vs. normal bladder

epithelium and an increase in expression in Iressa-treated tumors vs. control tumors. Cell culture

study also confirmed that the increased expression of Let-7c decreases Iressa-treated bladder




20

tumor cell growth. By searching miRNA target database, we found two hub genes differentially

expressed with Iressa treatment, Uhrf1 and Tacc3, is target of Let-7c.

Transitional cell carcinoma (TCC) is by far the most common form of human bladder

cancer. It accounts for overall >90% of bladder cancer cases. 70% of TCC cases are

characterized as superficial, meaning that the cancer is confined to the lining of the patient's

bladder, and therefore unlikely to spread into neighboring tissue (i.e. metastasize). The remaining

30% of TCC cases are characterized as muscle invasive, meaning that they have invaded through

the lining into the muscular wall of the bladder, and therefore potentially into other nearby

organs. Squamous cell carcinoma accounts for around 8% of bladder cancer cases. These cancers

originate from the thin, flat cells that typically form as a result of bladder inflammation or

irritation that has taken place for many months or years. Nearly all squamous cell carcinomas are

invasive. The comparison of gene expression profile of advanced squamous and transitional cell

carcinoma of the bladder showed that out of the 516 genes which were differentially expressed ,

only 30 showed significant differences between TCC and SCC (59). Another study showed that

major histocompatibility complex class II, tumor necrosis factor, cytokines, and chemokines are

among the up-regulated genes in bladder SCC (60), which are similar to the findings of others

who found that the invading cells of the bladder TCC stimulate the immune system. However, a

group of immunology related genes were downregulated in SCC compared with normal

urothelium, including interferon, different immunoglobulins, human leukocyte antigens protein,

and interleukin-8, and interleukin-13. Cell adhesion molecules such as laminins, integrins, and 2

cadherins (E-cadherin and P-cadherin were down-regulated in both SCC bladder cancer and

invasive bladder TCC. These data indicated that the majority of gene expression profiles of

bladder TCC and SCC are similar. In experiments conducted using male and female Fischer 344




21

rats, intragastric administration of OH-BBN has been shown to induce transitional cell

carcinomas of the urinary bladder which were histologically similar to the human counterpart(4).

This should be a good animal model to find potential biomarkers of chemoprevention agents.

In summary, we identified two coexpression modules that are significantly correlated

with tumor status and Iressa treatment status. We further demonstrated that these two modules

are also significantly associated with expression levels of let-7c. Both tumor module and

treatment module are enriched for genes involved in cell cycle control. The tumor module and

treatment module contain 24 and 21 highly connected hub genes that are likely to be key drivers

of the cell cycle. These results suggest that let-7c and its regulated cell cycle pathway might play

a key role in governing bladder tumor suppression or collaborative oncogenesis and that Iressa

exhibits its preventive efficacy on bladder tumorigenesis by regulating let-7 and its cell cycle

control. Cell culture study confirmed that the increased expression of Let-7c decreases Iressa-

treated bladder tumor cell growth. The identified hub genes may also serve as pharmacodynamic

or efficacy biomarkers in clinical trials of bladder cancer chemoprevention. Characterization of

these hub genes may help to give novel insight into bladder tumorigenesis and develop novel

drug targets. Finally, we demonstrated that alternative exon usage correlates with bladder

tumorigenesis and could be inhibited by the chemopreventive agent Iressa. The short term Iressa

treatment may operate through blocking of such effects.

Acknowledgments

The funding for the studies was provided in part by NCI Contract Number HHSN-

261200433008C (N01-CN43308).

References




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26

Figure legend

Figure 1. Gene ontology (GO) of differentially expressed genes. (a) Genes down-regulated in

bladder tumors as compared with their normal bladder epithelia; (b) Genes up-regulated in

bladder tumors as compared with their normal bladder epithelia; (c) Genes down-regulated in

bladder tumors after Iressa treatment; and (d) Genes down-regulated in bladder tumors after

Iressa treatment. The top 10 GO terms are present in each category of differentially expressed

genes. Abscissa = Numbers of differentially expressed genes.

Figure 2. Gene expression patterns among the studied bladder samples. Hierarchical

clustering analysis was performed using (a) all of the differentially expressed genes and (b) cell

cycle-related differentially expressed genes.

Figure 3. Gene coexpression network analyses. Unsupervised hierarchical clustering was used

to detect modules of highly coexpressed genes in the two datasets: (a) control tumors vs. normal

epithelia, and (b) control tumors vs. Iressa-treated tumors. Each major branch in the figure

represents a color-coded module that contains a group of highly connected genes. The arrows in

(a) and (b) represent modules enriched for cell cycle process.

Figure 4. Associations of hub genes with clinical traits. Scatterplots were drawn for the scaled

intramodular connectivity K (x axis) against gene significance (y axis). Salmon module from the

datasets of control tumors vs. normal bladder epithelia samples and green module from the

datasets of control bladder tumors vs. bladder tumors treated with Iressa samples were analyzed.

Each point corresponds to a gene in the modules. The gene significance of the i-th gene was




27

defined as the absolute correlation between the i-th gene expression profile and the studied trait.

(a) Correlation of salmon module with cancer status (tumor or normal); (b) Correlation of

salmon module with let-7c expression ; (c) Correlation of green module with Iressa treatment

status (treated or not treated); and (d) Correlation of green module with let-7c expression .

Figure 5. Gene interactions within the two significant modules. (a) Salmon module from the

datasets of control tumors vs. normal bladder samples. Green module from the datasets of control

bladder tumors vs. bladder tumors treated with Iressa samples. Each node represents a gene and

red nodes are hub genes; bigger nodes indicate more connections.

Figure 6. The increased expression of Let-7c decreases Iressa-treated bladder tumor cell

growth. (a) MTT assay for the effect of increasing amount of Iressa on the growth of bladder

cancer cells UM-UC-5. (b) Quantitative real-time PCR to detect Let-7c expression in UM-UC-5

cells treated with different amount of Iressa.




28

Supplemental Figures

Figure S1 Top genes alternatively spliced between normal and tumor colored by fold

change. a) Top 30 genes with alternative splicing that are down-regulated in bladder tumors as

compared with normal bladder epithelia. b) Top 30 genes with alternative splicing that are up-

regulated in bladder tumors as compared with normal bladder epithelia. Each row corresponds to

a gene, each rectangle, an exon. Exons are arranged in position order. Exons targeted by multiple

probesets are drawn with these stacked horizontally within the exon. White rectangles

correspond to exons with missing data. Intense blue; up in tumor and intense red; up in normal.

Figure S2 Microarray expression data mapped to the gene structure for Prkn2. Six known

isoforms are represented in Ensembl. Expression data are mapped onto these isoforms and

colored according to fold change between normal bladder epithelia and bladder tumors (a) and

between Iressa-treated tumor and control tumors (b). The pattern of expression across the length

of the gene clearly corresponds to the known gene structure. Red lines plot for tumors and blue

lines plot for normal epithelia in (a) and Iressa-treated tumors in (b).




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Published OnlineFirst October 7, 2011.Cancer Prev Res Yan Lu, Pengyuan Liu, Weidong Wen, et al. Pathways in Iressa-treated Urinary Bladder Cancer in RatsModulation of Gene Expression and Cell Cycle Signaling

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