Download Use of High-Throughput DNA Microarrays to Identify

Clinical Chemistry 49:1
23–31 (2003)
Review
Use of High-Throughput DNA Microarrays to
Identify Biomarkers for Bladder Cancer
Marta Sánchez-Carbayo
Bladder Cancer: Pathologic and Clinical Features
Background: Numerous markers have been described
to correlate to some extent with tumor stage and prognosis of patients with bladder cancer. The power of
many of these biomarkers in detecting superficial disease or predicting the clinical outcome of individual
tumors is limited, and alternative markers are still in
demand. High-throughput microarrays represent novel
means for cancer research and tumor marker discovery.
Approach: The aim of this report was to discuss the
application of DNA technologies to provide novel biomarkers for bladder cancer.
Content: Specific bladder tumor subtypes have distinct
gene expression profiles. The use of high-throughput
DNA microarrays allows identification of the most
prevalent and relevant alterations within bladder tumors. Clusters of differentially expressed genes will
become biomarkers to discriminate subgroups of patients with different histopathology or clinical outcome.
Additionally, the identified individual molecular targets might be further validated and developed into
novel serum or urinary biomarkers for the diagnosis
and/or as prognostic factors to be applied in clinical
practice. The diagnosis and prognosis of bladder cancer
would be enhanced by the use of such markers, and the
marker itself may constitute a therapeutic target when
studied in appropriate patients and control groups.
Summary: Expression profiling with high-throughput
DNA microarrays has the potential of providing critical
clues for the management of bladder cancer patients. As
the quality, standardization, and ease of use of the
technology increase and the costs decrease, DNA microarrays will move from being a technology restricted
to research to clinical laboratories in the near future.
Bladder cancer is the sixth most common malignancies in
developed countries, where most bladder tumors are
transitional cell carcinomas (TCCs)1 (1 ). In contrast, squamous cell carcinoma of the bladder is the predominant
presentation in Middle Eastern countries (2 ). Approximately 75% of uroepithelial TCCs are superficial (TIS, Ta,
and T1), 20% are muscle infiltrating (T2–T4), and 5% are
metastatic at the time of diagnosis (1 ). Most superficial
cases are treated conservatively by transurethral removal
of the tumor, followed by adjuvant intravesical therapy,
but without removal of the bladder. Muscle-infiltrating
tumors are generally treated by cystectomy plus systemic
adjuvant chemotherapy or radiotherapy. Bladder cancers
follow widely varying clinical courses. Of the superficial
tumors, ⬃20% are cured by surgical removal of the
presenting lesion (5 years with no evidence of disease),
50 –70% recur one or more times, but do not progress into
invasive disease, and 10 –30% progress to invasive and
potentially lethal disease (3 ). In contrast, ⬃50% of patients
with muscle-infiltrating tumors harbor or will develop
metastatic disease. Although recent advances in systemic
chemotherapy have improved the prognosis for patients
with metastatic disease, the vast majority ultimately die
from their disease. Thus, it is important to identify patients whose tumors are likely to recur or progress so that
they can be treated more aggressively.
The chances of superficial tumor progression are augmented with increased pathologic stage and grade, tumor
size, presence of concomitant carcinoma in situ, and
multicentricity (2, 3 ). The power of these histopathologic
variables in defining the clinical subtypes of bladder
cancer and predicting the clinical outcome of individual
patients has certain limitations. Many groups of investigators have examined additional molecular characteristics
of bladder cancer that may be of predictive value.
Bladder tumors, including some superficial lesions,
© 2003 American Association for Clinical Chemistry
Division of Molecular Pathology, Memorial Sloan-Kettering Cancer Center, 1275 York Ave., New York, NY 10021. Fax 212-794-3186; e-mail
[email protected].
Received April 9, 2002; accepted October 1, 2002.
1
Nonstandard abbreviations: TCC, transitional cell carcinoma; P5C, pyrroline 5-carboxylate; SNP, single-nucleotide polymorphism; and EST, expressed sequence tag.
23
24
Sánchez-Carbayo: DNA Microarrays for Biomarkers of Bladder Cancer
carry a substantial number of genetic alterations at the
time of diagnosis (4 ). A large body of work has suggested
that superficial papillary tumors (pTa) differ from flat
carcinoma in situ lesions (TIS) and muscle-invasive tumors in their molecular pathogenesis and pathways of
progression (1– 8 ). The number of genetic alterations is
substantially higher in the invasive lesions, but there also
appears to be a difference in the specific alterations
present. On the basis of data from several groups, it
appears that at least two major molecular pathways of
bladder tumor development and evolution can be followed (Fig. 1). Briefly, the first pathway, represented by
papillary superficial tumors, is associated with chromosome 9 losses, including inactivation of CDKN-2 (p16) on
9p and still unknown genes associated with telomeric 9q
loci (5 ). The second pathway includes inactivation of p53
on chromosome 17 (17p11.3) and Rb on 13q14, ascribed to
flat carcinoma in situ and pT1 tumors (6, 7 ). Phenotypic
features associated with biological tumor aggressiveness
include cell cycle and apoptosis regulators studied by
appropriate sensitive molecular techniques. Numerous
markers have been identified that correlate to some extent
with tumor stage and prognosis. However, the power of
many of these markers in predicting the clinical outcome
of individual tumors is limited, and alternative markers
are still needed for detection of the disease and for
predictive purposes.
Urinary Tumor Biomarkers in Bladder Cancer
The diagnosis of bladder cancer is basically based on the
combined information provided by urinary cytology and
cystoscopy. Unfortunately, cystoscopy does not provide
100% sensitivity for the diagnosis of bladder cancer, and it
is an invasive, uncomfortable diagnostic method for many
patients (2, 3 ). Urinary cytology as the standard noninvasive method also has sensitivity limitations, extreme dependence on sample quality, and high interobserver variability (2, 3, 8 ). Thus, alternative noninvasive objective
methods have been developed for the diagnosis and
monitoring of the disease. Urinary tumor markers represent an option of interest for the early detection and
surveillance of the disease because of sample accessibility
and the direct contact of urine with the tumor. Many
urinary tumor markers have been evaluated in the last
Fig. 1. Overview of genetic alterations of the two major progression pathways described for bladder cancer.
25
Clinical Chemistry 49, No. 1, 2003
few years (9 –24 ); Table 1 summarizes some of the characteristics of these markers. The sensitivity overall and by
stage and grade is better for most available markers
compared with cytology, although they are less specific in
high-grade tumors (23 ). Overall, urinary tumor markers
could potentially replace urinary cytology in clinical daily
practice (9 –23 ). However, their overall sensitivity has not
been demonstrated to be sufficient to replace cystoscopy
as the gold standard. Most of the studies reported to date
are descriptive evaluations of the sensitivity and specificity of these markers at the time where diagnosis is
established, whereas the utility of urinary markers in
monitoring of the disease has been less frequently reported (22 ). Multicenter studies are necessary to reach a
consensus in the optimization of sample acquisition and
preanalytical issues critical for reliable laboratory results,
which markers are the best option for every clinical need,
and when and how they should be determined (23, 24 ). It
is our hope that the increase in bladder cancer detected in
superficial preinvasive stages is attributable not only to
simplified procedures, such as the use of flexible cystoscopy in combination with urinary cytology, but also to the
introduction of noninvasive urinary tumor markers in the
clinical setting. The use of exclusion criteria can improve
the specificity of urinary tumor markers at first diagnosis
and in the surveillance of bladder cancer patients (9 –24 ).
However, the lack of specificity of urinary tumor markers
in certain circumstances is leading investigators to search
for novel biomarkers that may display higher specificity.
Candidate biomarkers include other cytokeratins (25 );
other nuclear matrix proteins, such as BLCA4 (26 ); other
molecules, such as survivin (27 ), cyclooxygenase-2 (28 ),
and Mcm5 (29 ); or the use of highly sensitive and specific
techniques such as microsatellite analysis (17 ) or dual
parametric flow cytometry (30 ). One potential approach
involves molecular profiling of bladder tumors by highthroughput technologies (31 ). Developments in areas of
research such as gene expression microarrays or proteom-
ics represent novel means for cancer screening and potential urinary tumor marker discovery.
Potential Role of High-Throughput DNA Microarrays in
Identifying Biomarkers in Cancer
Understanding the biology underlying tumorigenesis and
tumor progression of bladder cancer is essential for improving the capacity to diagnose and treat the disease.
Unraveling the biological complexity underlying these
processes is expected to provide novel tools of predictive
nature and to enable identification of therapeutic targets
by selecting those molecular targets significantly differentially expressed in bladder tumors. The further characterization of regulatory mechanisms and pathways controlling cellular homeostasis that are altered in bladder
tumors will be achieved, at least in part, by global
analyses of gene expression. Until recently, the ability to
identify and analyze gene expression patterns has been
technically limited to relatively few genes per study. This
limitation is being overcome by the development of
several methods that allow more comprehensive analysis
of these patterns. Some of the most powerful methods
include differential display (32 ), serial analysis of gene
expression (SAGE) (33 ), protein composition-based approaches such as protein microarrays (34 ), and combined
two-dimensional gel electrophoresis followed by mass
spectrometric analysis (35 ).
Concurrent with the development of these methods
has been the tremendous increase in the DNA sequence
information available through genome sequencing efforts
(36, 37 ). This expansion of gene and genome information
has served as the basis for development of DNA microarrays, one of the most powerful new methodologies available to provide both static and dynamic views of gene
expression patterns in cells and tissues (38 ).
The utility of DNA in microarray format arises from
the ability of single-stranded nucleic acids to hybridize
with high specificity to a second strand containing the
Table 1. Main characteristics of several of the most extensively studied urinary tumor markers.
Marker
Antigen type
Sensitivity,a %
Specificity,a %
Method
NMP22b
BTA STATb
BTA TRAKb
FDPb
Telomerase
Hyaluronic acid/hyaluronidase
Immunocyt
Quanticyt
UBC
CYFRA 21-1
BLCA4
Solublec
Soluble
Soluble
Soluble
Cellular
Soluble
Cellularc
Cellularc
Soluble
Soluble
Soluble
47–87
57–82
55–80
41–93
53–91
82–92
86–95
45–59
59–79
74–99
85–96
58–91
61–82
38–98
77–94
46–99
83–96
79–90
70–93
84–96
57–78
85–100
EIAd
Antigen-antibody colorimetric
EIA
Antigen-antibody colorimetric
PCR
EIA
IFI; cytology
Morphometry
EIA
ECLIA
EIA
a
Sensitivity and specificity are taken from Lotan and Roehrborn (23 ).
Food and Drug Administration approved.
c
Preservative necessary.
d
EIA, enzyme immunoanalysis; IFI, immunofluorescence immunoassay; ECLIA, electrochemiluminescence assay.
b
Manufacturer
Matritech
Bard Diagnostics
Bard Diagnostics
Intracel Corp.
Oncor
Diagnocure
Gentian Scientific Software
IDL
Roche Diagnostics
Eichrom Technologies
26
Sánchez-Carbayo: DNA Microarrays for Biomarkers of Bladder Cancer
complementary sequence, thus forming double-stranded
nucleic acid molecules. The main advantage of DNA
arrays is that they allow the study of multiple transcriptional events in a single experiment (38 ). Hybridizationbased assays and the microarray format provide an extremely versatile technology. There is an increasingly broad
range of applications to which microarrays have been applied, including genotyping of polymorphisms and mutations (39 ), determining the binding sites of DNA-binding
proteins (40 ), and identifying structural alterations by use of
arrayed comparative genome hybridization approaches
(41 ). The most widespread use of this technology to date has
been the analysis of gene expression.
Because genetic alterations and the resulting changes
in gene expression are primary determinants controlling
neoplastic transformation and progression, it is not surprising that expression profiling by use of high-throughput DNA microarrays has found wide application in
cancer research and has the potential of providing critical
clues for the management of bladder cancer patients. It is
expected that specific tumor subtypes will have distinct
gene expression profiles (31, 38 ). The use of highthroughput DNA microarrays will allow identification of
the most prevalent and relevant alterations within bladder tumors. Clusters of differentially expressed genes will
become biomarkers themselves to discriminate subgroups
of patients with different histopathologies or clinical
outcomes. Additionally, the identified individual molecular targets might be further validated and developed
into novel biomarkers for use in diagnosis and/or prognosis in clinical practice in the near future. The diagnosis
and prognosis of bladder cancer would be enhanced by
the use of such markers, and any marker may itself
constitute a therapeutic target when studied in appropriate patients and control groups.
Expression profiling by use of DNA microarrays can
render a variety of clusters or molecular targets depending on the experimental designs taken. For example, comparison of the expression profiles of bladder tumors vs
respective healthy urothelium can provide information on
the molecular events that take place during transformation.
These type of studies may make it possible to assign potential functional roles to novel genes in both the signaling
pathways controlling bladder cancer development and the
phenotypic changes associated with that development. Additionally, elucidation of the molecular events involved in
bladder tumorigenesis and tumor progression can lead to
the discovery and application of novel biological markers.
The output of high-throughput microarrays can be clusters
of genes that define patients more likely to display superficial or invasive disease, to develop node or distant metastasis, or to display a shorter disease-free or survival time. Each
of these clusters of genes can be considered a marker itself,
and these expression patterns will represent the novel biomarkers of the disease, a concept that will have to be
validated with comprehensive multicenter studies. Additionally, once an individual molecular target gene is found
differentially expressed in bladder cancer, its potential role
as a tumor marker can be studied at the RNA level by use of
high-throughput tissue microarrays incorporating in situ
hybridization or at the protein level by arrays incorporating
immunohistochemistry (Fig. 2). This represents a highthroughput strategy to evaluate the potential clinical utility
of novel biomarkers using clinically well-annotated tumors
at the microanatomic level (42, 43 ), which will be illustrated
below with an example applied to bladder cancer.
An early detection research network has been established by the National Cancer Institute to coordinate
research among biomarker development and validation
laboratories, clinical repositories, and population-screening programs. Five consecutive phases have been proposed to guide the process of biomarker development.
The first, preclinical exploratory phase identifies promising uses for the target. During the second, validation
phase, the clinical assay is evaluated for detection of an
established disease. Phase 3 includes retrospective longitudinal studies to define whether the biomarker can
detect disease before it becomes clinical and to define
criteria for a positive screen. Prospective screening is
performed during phase 4, in which the ability of a test to
detect the extent and characteristics of disease is evaluated and the false-positive rate for the test is determined.
Cancer control is the fifth phase, in which the impact of
screening on reducing the burden of disease on the
population is quantified (44 ).
DNA Microarray Studies in Bladder Cancer to Date
Expression profiling studies using in vitro cultured cell
lines as well as fresh or frozen clinical material have been
used to gain insight into the molecular events associated
with the disease. Below is a summary of these studies.
studies using cultured cells
This technology can be applied to gene function and
pathway discovery using in vitro models. The tumor
growth inhibition produced by genistein in TCCSUP, a
susceptible bladder cancer cell line, was studied using
DNA microarrays (45 ). Expression profiles were then
analyzed at various time points, using cDNA chips containing 884 sequence-verified known human genes. The
study reported many groups of genes with distinct expression profiles, most of them encoding for proteins that
regulate cell growth or cell cycle. Interestingly, transient
induction of epidermal growth factor receptor-1 was
identified, and this molecular target was related to its
proliferation and differentiation effects (45 ).
An example of the functional classification of genes by
use of cultured cells with different phenotypes is the
study relating the expression patterns of p53-mediated
apoptosis in resistant bladder cancer cell lines vs sensitive
cells (46 ). The ECV-304 bladder carcinoma cell line was
selected for resistance to p53 by repeated infections with
a p53 recombinant adenovirus, Ad5CMV-p53 (46 ). Its
expression pattern in cDNA arrays containing 5730 genes
Clinical Chemistry 49, No. 1, 2003
27
Fig. 2. The general procedure of an expression profiling experiment.
The procedure includes RNA isolation from tumor biopsy and control samples, preparation of the hybridization probe using an oligonucleotide or cDNA platform,
hybridization to the DNA microarray, data acquisition and analysis, and verification of the results by use of, for example, tissue microarrays. Tissue arrays represent
a high-throughput methodology to validate the clinical utility of markers identified in molecular profiling studies using DNA microarrays. They can be used for
immunohistochemistry at the protein level, in situ hybridization at the RNA level, or fluorescence in situ hybridization at the DNA level.
was compared that of with p53-sensitive ECV-304 cells.
Several potential p53 transcription or related targets were
identified as playing roles in cell cycle regulation, DNA
repair, redox control, cell adhesion, apoptosis, and differentiation. Proline oxidase, a mitochondrial enzyme involved in the proline/pyrroline 5-carboxylate (P5C) redox
cycle, was up-regulated in sensitive but not in resistant
cells. Additional experiments with P5C, a proline-derived
metabolite generated by proline oxidase, inhibited the
proliferation and survival of resistant and sensitive cells,
inducing apoptosis in both cell lines. These results suggested the involvement of proline oxidase and the proline/P5C pathway in p53-induced growth suppression
and apoptosis, molecular events that had not been identified in p53 resistance in bladder cancer (46 ).
The expression profiles of nine bladder cancer cell
lines, including T24, J82, 5637, HT-1376, RT4, SCaBER,
TCCSUP, UMUC-3, and HT1197, have been compared
against a pool containing equal amounts of RNA from
each of these cell lines by use of cDNA arrays containing
8976 genes (47 ). Hierarchical clustering classified these
tumor cells according to the histopathologic characteristics of the tumors from which they were derived. The
squamous carcinoma cell line SCaBER was distinguished
from the other cell lines obtained from transitional carcinomas. Moreover, cell lines from invasive lesions clustered together and were segregated from cell lines obtained from a metastatic and a papillary superficial tumor.
Additional analyses were directed to identifying potential targets that differentiated squamous features
within bladder cancer based on the genes that were
differentially expressed in SCaBER (47 ). Caveolin-1 and
keratin 10 were differentially expressed in SCaBER and
certain invasive tumor cell lines compared with RT4 cells,
which are derived from a papillary superficial bladder
tumor. The patterns of expression of keratin 10 and
caveolin-1 were characterized in primary bladder tumors
spotted on tissue microarrays and were shown to be
significantly associated with the presence of squamous
differentiation. Moreover, when a bootstrapping resampling technique was applied, the cells clustered based on
their p53, Rb, and INK4A status. E-Cadherin, zyxin, and
moesin were identified as genes differentially expressed
in these clusters. Interestingly, the expression of these five
genes was significantly associated with histopathologic
stage and tumor grade in bladder tumors contained in
28
Sánchez-Carbayo: DNA Microarrays for Biomarkers of Bladder Cancer
tissue microarrays. Moreover, moesin provided prognostic information regarding overall survival. These results
revealed that molecular profiling clustered bladder cancer
not only on the basis of histopathogenesis but also on
biological criteria. Additionally, novel molecular targets
identified were associated with histopathologic criteria
and might become biomarkers of clinical utility in the
management of patients with bladder cancer (47 ). This
study represents an example of the strategy, outlined in
Fig. 2, for use of DNA microarrays as a high-throughput
approach to identify novel targets of clinical utility in the
management of bladder cancer. In addition, these molecules may be validated by use of high-throughput microarrays containing well-annotated tumor samples
(42, 43 ). Translation of individual patterns of gene expression obtained for in vitro-cultured cells to in vivo situations should be performed carefully because differences
in gene expression using RT-PCR have been reported
between cultured cancer cells and the tumors they were
originated from (48 ). However, this study revealed that
expression profiling of cultured cancer cells might reflect
the biology underlying human tumor development.
studies using clinical material
To date, there have been few expression analysis reports
using DNA microarrays on clinical material. The following studies show how oligonucleotides or cDNA microarrays can identify and correlate changes in the expression
of specific genes and groups of genes with cancer and
cancer-related phenotypes (31 ). The use of mutation or
single-nucleotide polymorphism (SNP) chips will also be
commented on.
The most extensive study dealing with molecular classification of bladder tumors published to date used oligonucleotide arrays carrying probes for 6500 genes to explore the expression patterns of superficial and invasive
tumor cell suspensions (49 ). Using a sample size containing 36 normal urothelium biopsies and 29 bladder tumor
biopsies, the authors prepared pools of cells made from
normal urothelium and tumors of different stage– grade
combinations, such as from pTa grade I and II and pT2
grade III and IV bladder tumors. Single-cell suspensions
were prepared from cooled biopsies immediately after
surgery, according to a procedure used previously for the
preparation of bladder tumors cells for flow cytometry.
These cell suspensions were inspected under the microscope to ensure the presence of enriched urothelial cells
and similar numbers of tumor cells from each specimen
(49 ). This pool approach may smooth individual differences, but it can dilute strong expression of relevant genes
that may differentiate specific groups with different prognoses regarding recurrence, progression, or overall survival. Hierarchical clustering of gene expression not only
correlated with the stage and/or grade of the samples
studied but also identified several stage-characteristic and
functionally related clusters concerned with cell proliferation, oncogenes and growth factors, cell adhesion, im-
munology, transcription, proteinases, and ribosomes (49 ).
By organizing genes with similar expression patterns into
clusters, the authors identified several functionally related
genes that could be developed as tumor biomarkers for
bladder cancer alone or in combination. Superficial papillary tumors showed increased amounts of transcription
factor and ribosomal genes, as well as proteinases encoding genes up-regulation. In the invasive tumors, increased
amounts of cell-cycle related transcripts were observed,
which might reflect the increased concentrations of
growth factor and oncogene transcripts found. A loss of
cellular adhesion proteins was found in invasive tumors
and may be related to tissue invasion and metastasis. In
this study, the invading tumor cells seemed to challenge
to the immune system, as reflected by an increase in
immunology-related proteins (49 ).
The expression profiles of 15 bladder tumors have been
analyzed against a pool of bladder cancer cell lines by use
of cDNA microarrays containing 17 842 known genes and
expressed sequence tags (ESTs) (50 ). The application of
bootstraps and multidimensional scaling methods to the
hierarchical clustering allowed classification of superficial
bladder tumors vs lesions that invaded the muscular layer
(Fig. 3). Critical known targets involved in bladder cancer
progression, such as cytokeratin 20 (25 ), p21 (51 ), and
cyclin E (52 ), as well as novel molecular targets such as
neuropilin-2 (53 ) were identified as differentially expressed
between superficial tumors and tumors invading the muscular layer. These molecular targets were shown to be
significantly associated with stage and grade. The application of tissue microarrays represents a high-throughput
approach for validation of novel potential markers for bladder cancer by immunohistochemistry or fluorescence in situ
hybridization in paraffin blocks [Refs. (43, 44, 52, 54, 55 ); Fig.
2]. Focus has intensified within this field to construct optimal
frozen tissue microarrays that would enable further characterization of novel genes by in situ hybridization of ESTs and
known genes for which specific antibodies are not available
to study the potential clinical relevance of gene targets not
previously evaluated.
Testing for mutations of the TP53 gene in bladder tumors
is a valuable predictor for disease outcome. Today, TP53
mutations can by analyzed by use of commercial variant
oligonucleotide chips in which the 1464 gene chip positions
correspond to the p53 gene sequence. When this microarray
was compared with the traditional manual dideoxy sequencing for sequencing of DNA extracted from 140 human
bladder tumors, the concordance rate was 92% (56 ). Microarray-based sequencing is a novel option to assess TP53
mutations and represents a rapid, inexpensive method compared with conventional sequencing, with the additional
advantage that the system is almost free from interference by
mixtures of templates from nonpathologic and pathologic
tissue. A target concentration as low as 1% in the diseased
tissue can be detected in the presence of 99% wild-type
sequences. The improved sensitivity reflects the fact that
with the microchip sequencing technology, each spot (or
29
Clinical Chemistry 49, No. 1, 2003
Fig. 3. Molecular profiling using cDNA microarrays.
Microarrays containing ⬎17 842 known genes and ESTs
segregated superficial tumors from invasive tumors and
bladder tumors developing metastases. Sup, superficial;
Inv, invasive; Met, metastatic.
position) coated with a specific oligonucleotide tests for a
unique sequence (56 ).
Recently, genome-wide screening using SNP arrays
has been applied to DNA isolated from microdissected
superficially invasive T1 and muscle-invasive T2– 4 bladder tumors (57 ). These commercial oligonucleotide microarrays contain 1494 biallelic polymorphic sequences
and can detect the loss or gain of at least one allele. The
authors reported that of a genotype of 1204 loci, 343 were
heterozygous in the bladder tumors under study. Allelic
imbalance was detected in known areas of imbalance on
chromosomes 6, 8, 9, 11, and 17, and a new area of
imbalance was detected on the p arm of chromosome 6.
Microsatellite analysis of T2– 4 tumors and Ta tumors
showed that allelic imbalance was more frequent in T2– 4
tumors than in Ta or T1 tumors. However, when pairs of
T1 and T2– 4 tumors were analyzed from eight patients,
68% of imbalances detected in T1 tumors (146 imbalances)
occurred in the subsequent T2– 4 tumors (99 imbalances).
Homozygous TP53 mutations were more often associated
with high allelic imbalance than with low allelic imbalance. In this study, SNP arrays were shown to be feasible
for high-throughput, genome-wide scanning for allelic
imbalances in bladder cancer that was faster than comparable microsatellite-based analyses. Not only did the
arrays confirm known areas of chromosomal losses, they
may have identified areas with common allelic imbalances that could harbor potential tumor suppressors in
bladder cancer (7 ). Although these chips are restricted to
the polymorphic areas contained in the arrays, in the
future, it should be possible to fabricate high-density SNP
microarrays for other predefined chromosomal locations,
which could make noninformative areas informative. In
addition, high-throughput comparative genome hybridization arrays may be of interest to confirm alterations
found at the genomic level (41 ).
Critical Issues to Be Considered for DNA Microarrays
Several issues need to be considered when interpreting
the results of expression profiling using DNA microarrays
in bladder cancer; the importance of these issues depends
heavily on the questions the investigator wishes to address and the resources available. These include the type
of DNA microarray used; sample preparation, including
specimen types, sample availability, and tissue heterogeneity; and the critical area of data analysis.
Issues of cost, set-up time, available personnel, flexibility, and product range will influence the decision of
manufacturers or buyers of any of the commercially
available oligonucleotide, glass, or nylon cDNA microarrays (58, 59 ). For experimental design and results interpretation, it is critical to keep in mind that in oligonucleotide chips and nylon macro and radioactive microarrays,
the sample under study is directly hybridized to the chip
(58 ). In cDNA glass microarrays, the sample tested is
hybridized simultaneously with a reference sample labeled with a different fluorochrome (59 ).
Critical issues include the control of quantity and
quality of the RNA from which the hybridization sample
is prepared, especially when the RNA is isolated from
clinical specimens. Potential solutions to the quantitative
limitations include probe labeling protocols that increase
sensitivity through label signal amplification using dendrimers (60 ), probe amplification protocols that reduce
the amount of RNA required through the use of highly
efficient phage RNA polymerases or PCR amplification
(61, 62 ), and posthybridization amplification methods in
which the target-probe duplexes are detected enzymatically (62 ). Problems of RNA quality usually are severe
when working with blood, urine, or archived samples
because many fixing and embedding protocols may damage RNA integrity (63 ). Nonetheless, the issue of RNA
30
Sánchez-Carbayo: DNA Microarrays for Biomarkers of Bladder Cancer
quality is controversial, at least for certain tumors, when
standard fixation protocols are used.
Tumor heterogeneity is a critical issue in tumor expression profiling in general and particularly in the case of
bladder cancer. Tumor cells are surrounded by healthy
connective tissue and inflammatory infiltrates. In addition to
manual microdissection of tissue sections from embedded
frozen tumor blocks, laser capture microdissection appears
to be a method capable of isolating relatively pure cancer
cells populations from clinical specimens (64 ). However, the
extent to which the laser beam affects the quality of the RNA
obtained is still controversial. Flow cytometric sorting is also
possible, using bladder washes or disaggregated tissue
preparations as described previously (49 ).
Expression profiling experiments produce huge data
sets. The outcome of these studies is extremely dependent
on the algorithms applied in the analysis. Various mathematical, statistical, and bioinformatic tools have been
developed to cluster genes by integrating them with
biological pathways or to perform class predictions that
identify expression patterns that correlate with phenotypic characteristics, such as tumor type. An international
effort is underway to develop guidelines and a consensus
on data handling and annotation (MIAME standards),
which may facilitate access to the raw data from published microarray experiments in a uniform format.
7.
8.
9.
10.
11.
12.
13.
14.
15.
Final Comments
The aim of this report was to discuss how DNA technologies might provide novel biomarkers for bladder cancer.
In the near future, expression profiles or gene clusters may
themselves become biomarkers of clinical utility in the
management of patients with bladder cancer. Additionally,
individual identified molecular targets might be clinically
validated and developed into new serum or urinary tumor
markers. Because the quality, standardization, and ease of
use of the technology are increasing and the costs are
decreasing, DNA microarrays may move from being a
technology restricted to research or a few well-funded
laboratories to clinical laboratories.
16.
17.
18.
19.
References
1. Landis SH, Murray T, Bolden S, Wingo PA. Cancer statistics, 1999.
CA Cancer J Clin 1999;49:8 –31.
2. Reuter VE, Melamed MR. The lower urinary tract. In: Sternberg SS,
ed. Diagnostic surgical pathology. New York: Raven Press, 1989:
1355–92.
3. de Vere White RW, Stapp E. Predicting prognosis in patients with
superficial bladder tumors. Oncology 1998;12:1717–23.
4. Neiman PE, Hartwell LH. Malignant instability. Workshop on
Genetic Instability and its Role in Carcinogenesis sponsored by
the Programs in Molecular Medicine of the Fred Hutchinson
Cancer Research Center and the University of Washington, Seattle, WA, U S A, January 11–12, 1991. New Biol 1991;3:347–51.
5. Balazs M, Carroll P, Kerschmann R, Sauter G, Waldman FM. Frequent
homozygous deletion of cyclin-dependent kinase inhibitor 2 (MTS1,
p16) in superficial bladder cancer detected by fluorescence in situ
hybridization. Genes Chromosomes Cancer 1997;19:84–9.
6. Cote RJ, Dunn MD, Chatterjee SJ, Stein JP, Shi SR, Tran QC, et al.
20.
21.
22.
23.
Elevated and absent pRb expression is associated with bladder
cancer progression and has cooperative effects with p53. Cancer
Res 1998;58:1090 – 4.
Knowles MA. What we could do now: molecular pathology of
bladder cancer. Mol Pathol 2001;54:215–21.
Wiener HG, Vooijs GP, van’t Hof-Grootenboer B. Accuracy of
urinary cytology in the diagnosis of primary and recurrent bladder
cancer. Acta Cytol 1993;37:163–9.
Thomas L, Leyh H, Marberger M, Bombardieri E, Bassi P, Pagano
F, et al. Multicenter trial of the quantitative BTA TRAK assay in the
detection of bladder cancer. Clin Chem 1999;45:472–7.
Schmetter BS, Habicht KK, Lamm DL, Morales A, Bander NH,
Grossman HB, et al. A multicenter trial evaluation of the fibrin/
fibrinogen degradation products marcador for detection and monitoring of bladder cancer. J Urol 1997;158:801–5.
Soloway MS, Briggman V, Carpinito GA, Chodak GW, Church PA, et
al. Use of a new tumor marker, urinary NMP22, in the detection of
occult or rapidly recurring transitional cell carcinoma of the urinary
tract following surgical treatment. J Urol 1996;156:363–7.
Mian C, Pycha A, Wiener H, Haitel A, Lodde M, Marberger M.
Immunocyt: a new tool for detecting transitional cell cancer of the
urinary tract. J Urol 1999;161:1486 –9.
Dalbagni G, Han W, Zhang ZF, Cordon-Cardo C, Saigo P, Fair WR,
et al. Evaluation of the telomeric repeat amplification protocol
(TRAP) assay for telomerase as a diagnostic modality in recurrent
bladder cancer. Clin Cancer Res 1997;3:1593– 8.
Pham HT, Block NL, Lokeshwar VB. Tumor-derived hyaluronidase:
a diagnostic urine marker for high-grade bladder cancer. Cancer
Res 1997;57:778 – 83.
van der Poel HG, Witjes JA, van Stratum P, Boon ME, Debruyne
FM, Schalken JA. Quanticyt: karyometric analysis of bladder
washing for patients with superficial bladder cancer. Urology
1996;48:357– 64.
Sanchez-Carbayo M, Herrero E, Megias J, Mira A, Espasa A,
Chinchilla V, Soria F. Initial evaluation of the diagnostic performance of the new urinary bladder cancer antigen test as a tumor
marker for transitional cell carcinoma of the bladder. J Urol
1999;161:1110 –5.
Schneider A, Borgnat S, Lang H, Regine O, Lindner V, Kassem M,
et al. Evaluation of microsatellite analysis in urine sediment for
diagnosis of bladder cancer. Cancer Res 2000;60:4617–22.
Sanchez-Carbayo M, Espasa A, Chinchilla V, Herrero E, Megias J,
Mira A, et al. New electrochemiluminescent immunoassay for the
determination of CYFRA 21-1: analytical evaluation and clinical
diagnostic performance in urine samples of patients with bladder
cancer. Clin Chem 1999;45:1944 –53.
Konety BR, Nguyen TS, Dhir R, Day RS, Becich MJ, Stadler WM, et
al. Detection of bladder cancer using a novel nuclear matrix
protein, BLCA-4. Clin Cancer Res 2000;6:2618 –25.
Sanchez-Carbayo M, Urrutia M, Gonzalez de Buitrago JM, Navajo
JA. Evaluation of two new urinary tumor markers: bladder tumor
fibronectin and cytokeratin 18 for the diagnosis of bladder cancer.
Clin Cancer Res 2000;6:3585–94.
Bubendorf L, Grilli B, Sauter G, Mihatsch MJ, Gasser TC, et al.
Multiprobe FISH for enhanced detection of bladder cancer in
voided urine specimens and bladder washings. Am J Clin Pathol
2001;116:79 – 86.
Sanchez-Carbayo M, Urrutia M, Gonzalez de Buitrago JM, Navajo
JA. Utility of serial urinary tumor markers to individualize intervals
between cystoscopies in the monitoring of patients with bladder
carcinoma. Cancer 2001;92:2820 – 8.
Lotan Y, Roehrborn CG. Cost-effectiveness of a modified care
protocol substituting bladder tumor markers for cystoscopy for the
followup of patients with transitional cell carcinoma of the bladder: a decision analytical approach. J Urol 2002;167:75–9.
Clinical Chemistry 49, No. 1, 2003
24. Burchardt M, Burchardt T, Shabsigh A, De La Taille A, Benson MC,
Sawczuk I. Current concepts in biomarker technology for bladder
cancers. Clin Chem 2000;46:595– 605.
25. Buchumensky V, Klein A, Zemer R, Kessler OJ, Zimlichman S,
Nissenkorn I. Cytokeratin 20: a new marker for early detection of
bladder cell carcinoma? J Urol 1998;160:1971– 4.
26. Konety BR, Nguyen TS, Brenes G, Sholder A, Lewis N, Bastacky S,
et al. Clinical usefulness of the novel marker BLCA-4 for the
detection of bladder cancer. J Urol 2000;164:634 –9.
27. Smith SD, Wheeler MA, Plescia J, Colberg JW, Weiss RM, Altieri
DC. Urine detection of survivin and diagnosis of bladder cancer.
JAMA 2001;285:324 – 8.
28. Mohammed SI, Knapp DW, Bostwick DG, Foster RS, Khan KN,
Masferrer JL, et al. Expression of cyclooxygenase-2 (COX-2) in
human invasive transitional cell carcinoma (TCC) of the urinary
bladder. Cancer Res 1999;59:5647–50.
29. Stoeber K, Halsall I, Freeman A, Swinn R, Doble A, Morris L, et al.
Immunoassay for urothelial cancers that detects DNA replication
protein Mcm5 in urine. Lancet 1999;354:1524 –5.
30. Jankevicius F, Shibayama T, Decken K, Bojar H, Gerharz CD, Ebert T,
et al. Dual-parameter immunoflow cytometry in diagnosis and follow-up of patients with bladder cancer. Eur Urol 1998;34:492–9.
31. Liotta L, Petricoin E. Molecular profiling of human cancer [Review].
Nat Rev Genet 2000;1:48 –56.
32. Liang P, Pardee AB. Differential display of eukaryotic messenger
RNA by means of the polymerase chain reaction. Science 1992;
257:967–71.
33. Velculescu VE, Zhang L, Vogelstein B, Kinzler KW. Serial analysis
of gene expression. Science 1995;270:484 –7.
34. Haab BB, Dunham MJ, Brown PO. Protein microarrays for highly
parallel detection and quantitation of specific proteins and antibodies in complex solutions. Genome Biol 2001;2:1– 4.
35. Pandey A, Mann M. Proteomics to study genes and genomes.
Nature 2000;405:837– 46.
36. Lander ES, Linton LM, Birren B, Nusbaum C, Zody MC, Baldwin J,
et al. Initial sequencing and analysis of the human genome.
International Human Genome Sequencing Consortium. Nature
2001;409:860 –921.
37. Venter JC. Remarks at the Human Genome announcement. Funct
Integr Genomics 2000;1:154 –5.
38. Duggan DJ, Bittner M, Chen Y, Meltzer P, Trent JM. Expression
profiling using cDNA microarrays. Nat Genet 1999;21:10 – 4.
39. Hacia JG, Collins FS. Mutational analysis using oligonucleotide
microarrays. J Med Genet 1999;36:730 – 6.
40. Iyer VR, Horak CE, Scafe CS, Botstein D, Snyder M, Brown PO.
Genomic binding sites of the yeast cell-cycle transcription factors
SBF and MBF. Nature 2001;25;409:533– 8.
41. Pinkel D, Segraves R, Sudar D, Clark S, Poole I, Kowbel D, et al.
High resolution analysis of DNA copy number variation using
comparative genomic hybridization to microarrays. Nat Genet
1998;20:207–11.
42. Hoos A, Urist MJ, Stojadinovic A, Mastorides S, Dudas ME, Leung
D, et al. Validation of tissue microarrays for immunohistochemical
profiling of cancer specimens using the example of human
fibroblastic tumors. Am J Pathol 2001;158:1245–51.
43. Rubin M, Zhou M, Dhanasekaran SM, Varambally S, Barrette TR,
Sanda MG, et al. ␣-Methylacyl coenzyme A racemase as a tissue
biomarker for prostate cancer. JAMA 2002;287:1662–70.
44. Pepe MS, Etzioni R, Feng Z, Potter JD, Thompson ML, Thornquist
M, et al. Phases of marker development for early detection of
cancer. J Natl Cancer Inst 2001;93:1054 – 61.
45. Chen CC, Shieh B, Jin YT, Liau YE, Huang CH, Liou JT, et al.
Microarray profiling of gene expression patterns in bladder tumor
cells treated with genistein. J Biomed Sci 2001;8:214 –22.
46. Maxwell SA, Davies GE. Differential gene expression in p53-
47.
48.
49.
50.
51.
52.
53.
54.
55.
56.
57.
58.
59.
60.
61.
62.
63.
64.
31
mediated apoptosis-resistant vs. apoptosis-sensitive tumor cell
lines. Proc Natl Acad Sci U S A 2000;97:13009 –14.
Sanchez-Carbayo M, Socci N, Charytonowicz E, Lu M, Prystosky M,
Childs G, et al. Molecular profiling of bladder cancer using cDNA
microarrays: defining histogenesis and biological phenotypes.
Cancer Res 2002;62:in press.
Dangles V, Lazar V, Validire P, Richon S, Wertheimer M, Laville V,
et al. Gene expression profiles of bladder cancers: evidence for a
striking effect of in vitro cell models on gene patterns. Br J Cancer
2002;86:1283–9.
Thykjaer T, Workman C, Kruhoffer M, Demtroder K, Wolf H,
Andersen LD, et al. Identification of gene expression patterns in
superficial and invasive human bladder cancer. Cancer Res
2001;61:2492–9.
Sanchez-Carbayo M, Belbin T, Socci N, Charytonowicz E, Harris T,
Prystowsky M, et al. Expression profiling of bladder tumors using
cDNA microarrays. Clin Chem 2002;48(Suppl 6):A26.
Lu M-L, Wikman F, Orntoft TF, Charytonowicz E, Rabbani F, Zhang
Z, et al. Impact of alterations affecting the p53 pathway in bladder
cancer on clinical outcome, assessed by conventional and arraybased methods. Clin Cancer Res 2002;8:171–9.
Richter J, Wagner U, Kononen J, Fijan A, Bruderer J, Schmid U, et
al. High-throughput tissue microarray analysis of cyclin E gene
amplification and overexpression in urinary bladder cancer. Am J
Pathol 2000;157:787–94.
Fakhari M, Pullirsch D, Abraham D, Paya K, Hofbauer R, Holzfeind
P, et al. Selective upregulation of vascular endothelial growth
factor receptors neuropilin-1 and -2 in human neuroblastoma.
Cancer 2002;94:258 – 63.
Nocito A, Bubendorf L, Maria Tinner E, Suess K, Wagner U, Forster
T, et al. Microarrays of bladder cancer tissue are highly representative of proliferation index and histological grade. J Pathol
2001;194:349 –57.
Kononen J, Bubendorf L, Kallioniemi A, Barlund M, Schraml P,
Leighton S, et al. Tissue microarrays for high-throughput molecular profiling of tumor specimens. Nat Med 1998;4:844 –7.
Wikman FP, Lu ML, Thykjaer T, Olesen SH, Andersen LD, CordonCardo C, et al. Evaluation of the performance of a p53 sequencing
microarray chip using 140 previously sequenced bladder tumor
samples. Clin Chem 2000;46:1555– 61.
Primdahl H, Wikman FP, von der Maase H, Zhou XG, Wolf H,
Orntoft TF. Allelic imbalances in human bladder cancer: genomewide detection with high-density single-nucleotide polymorphism
arrays. J Natl Cancer Inst 2002;94:216 –23.
Granjeaud S, Bertucci F, Jordan BR. Expression profiling: DNA
arrays in many guises. Bioessays 1999;21:781–90.
Cheung VG, Morley M, Aguilar F, Massimi A, Kucherlapati R,
Childs G. Making and reading microarrays. Nat Genet 1999;21:
15–9.
Stears RL, Getts RC, Gullans SR. A novel, sensitive detection
system for high-density microarrays using dendrimer technology.
Physiol Genomics 2000;3:93–9.
Wang E, Miller LD, Ohnmacht GA, Liu ET, Marincola FM. Highfidelity mRNA amplification for gene profiling. Nat Biotechnol
2000;18:457–9.
Eberwine J, Yeh H, Miyashiro K, Cao Y, Nair S, Finnell R, et al.
Analysis of gene expression in single live neurons. Proc Natl Acad
Sci U S A 1992;89:3010 – 4.
Klimecki WT, Futscher BW, Dalton WS. Effects of ethanol and
paraformaldehyde on RNA yield and quality. Biotechniques 1994;
16:1021–3.
Specht K, Richter T, Muller U, Walch A, Werner M, Hofler H.
Quantitative gene expression analysis in microdissected archival
formalin-fixed and paraffin-embedded tumor tissue. Am J Pathol
2001;158:419 –29.