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Chapter 5
Cancer GenomicsTissue Microarrays in StudyingGynecological Cancers
Cécile Le Page1
Anne-Marie Mes-Masson1,2
Anthony M. Magliocco3
1Centre hospitalier de l’Universite de Montreal, Institut du Cancer de
Montreal, Montreal, QC, Canada
2Universite de Montreal, Department of Medicine, Montreal, QC,
Canada
3H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL, USA
ContentsIntroduction 66Materials and Tissues 67
Instruments 67Tissues 68Ethics and Regulatory Issues 69Design of Microarrays 69
Methods and Construction 70Selection of Tissues and Cores 70Cutting Slides 71Antigen Retrieval 71Staining 71
65Cancer Genomics. DOI: http://dx.doi.org/10.1016/B978-0-12-396967-5.00005-0
© 2014 Elsevier Inc. All rights reserved.
In Situ Hybridization and Fluorescence In SituHybridization (ISH and FISH) 72
Quality Control and Analysis 72Slide Conservation and Storage 72Staining and Antibody Quality 72Scoring and Analysis 73
Conclusion 74Glossary 74Abbreviations 74References 75
Key Concepts
� TMAs are cost- and time-effective means of validating
cancer biological markers identified by genomic
approaches� TMAs allow the analysis of hundreds of samples
simultaneously and enable the conservation of priceless
tissue� TMAs allow the validation and analysis of several
known and putative markers simultaneously and enable
more reliable correlative analysis between markers� The TMA has a large number of applications in cancer
and pathology research providing a more
comprehensible assessment of the tumor biology� Good quality standards are required for the optimal
utilization and analysis of TMAs
INTRODUCTION
Tumorigenesis is caused by the accumulation of
genetic and epigenetic changes that give rise to differ-
ent molecular abnormalities in numerous genes and
proteins in cancer cells. Genetic changes can be single
mutations, chromosome rearrangements or amplifica-
tion resulting in aberrant protein expression. Some of
these protein or gene modifications are silent in the
sense that they have no impact on cell functions that
contribute to tumorigenesis, while other so-called
driver events may induce specific functional alterations
that contribute to the pathogenesis of cancer cells. The
identification of such molecular changes often occurs
in cell lines or a small number of tissues and, subse-
quently, necessitates the analysis of a large number of
patient samples to determine their relative abundance
in a particular tumor type.
The investigation of pathogenesis has been revolu-
tionized by the introduction of high-throughput tech-
nologies, such as DNA and tissue microarrays
(TMAs). The TMA technology allows the transposition
of punches of tissues from donor to a recipient block,
resulting in a recipient block which can contain several
hundreds of small tissue cores from many donor speci-
mens. Hence, this method allows a rapid and simulta-
neous investigation of one or a few molecular markers
in hundreds of tumor samples by means of in situ
molecular assays such as immunohistochemistry (IHC)
and fluorescence in situ hybridization (FISH). In addi-
tion, advanced computer image analysis methods, such
as fractal dimension calculations, can also be applied
[1]. As the recipient block can be sectioned multiple
times, this allows a parallel molecular profiling of spe-
cimens for multiple in situ marker types (DNA, RNA
or protein) on multiple sections of the same array.
This technology therefore allows a more efficient and
comprehensive assessment of tumor biology, and
enables the identification of tumor makers more
rapidly and at a lower cost compared to traditional
“single tissue block” methods.
Another useful application of TMAs is for compara-
tive studies to evaluate and qualify tissue specimens [2],
to perform antibody screening or diminish the intra- and
interlaboratory variability in staining methods and results
[3]. Even if tissue immunostaining on whole tissue sec-
tion is a common laboratory practice, it still entails high
slide-to-slide and batch variability effects, which are
mitigated in TMAs. TMAs can also pool samples from
different sources to diminish variables caused by inter-
laboratory variables related to such variables as antigen
retrieval, staining time, antibody source, antibody concen-
tration and in the interpretation of staining results.
Therefore, TMAs offer a useful method to control the
quality and uniformity of results.
The technique was first described in 1986 by Battifora
who reported a multitumor tissue block method in which
1-mm-thick cylindrical cores of different tissues were
embedded in one paraffin block and from which numer-
ous sections were cut and individually stained by immu-
nohistochemistry [4]. Shortly after, the array format was
described by Wan et al. in 1987 [5]. However, it took
10 years to develop a device that allows the technique to
perform accurate arrays and be easily and reproducibly
usable in research and pathology laboratories [6]. Since
then a dramatic increase in the popularity and utility of
the technique has been observed, which is reflected by
the number of publications per year in which TMAs are
used (Figure 5.1).
In its most common form, a tissue microarray is built
from several cylindrical cores of tissues, withdrawn from
either a formalin-fixed, paraffin-embedded (FFPE) block
or from fixed or frozen tissues. Cores are vertically
placed into an empty grid identified recipient paraffin
block. The constructed recipient block can be horizontally
sectioned in 3�5 µm sections allowing the production of
numerous replicated slices. The thin layers of tissues are
66 PART | 2 Genomics Technologies, Concepts and Resources
then placed individually on a microscopic glass slide for
subsequent analysis (Figure 5.2).
To introduce the readers to the essential basis and
challenges of tissue microarray, this chapter provides a
short overview of this increasingly popular technology for
validating cancer biomarkers derived from genomics stud-
ies by focusing on several technical aspects of tissue
microarray construction and analysis.
MATERIALS AND TISSUES
Instruments
It is important to know that the construction of tissue
microarrays requires a substantial financial investment in
equipment as well as in human resources, as experienced
technicians or histotechnologists are required to prepare
and section the TMAs properly.
Arrayers
The main device, the microarrayer, is a high-precision
punching instrument (see Figure 5.2). Several suppliers
now offer microarrayers with prices ranging from $10 000
to more than $100 000. The microarrayer can be manual
or automated. One of the earliest instruments was supplied
by Beecher Instruments Inc., although several different
manufacturers now offer a variety of manual, semi-
automated and automated versions (see for example http://
www.pathologydevices.com/TMArrayer.htm). Differences
between the manual and automated arrayers include fea-
tures related to the positioning of the punches, software
(none typically associated with the manual version), and
speed and ease of replicate block production. However, an
important advantage of the manual arrayer is the ability to
control visually the depth of tissue punches, which is a sig-
nificant advantage when working with tissues of different
thicknesses.
Microscope
Another costly instrument required is a high-resolution
microscope for selection of tissue areas, histological vali-
dation of the TMA and downstream analyses. Because
the analysis of individual cores is a time-consuming step,
several software packages have been developed which
greatly facilitate high-throughput analyses. However,
automated analysis involves additional cost and training,
including the purchase of a slide scanner able to digitize
slides at a very high resolution [7].
Microtome
Once a TMA is constructed, it is sectioned in thin paraf-
fin layers (3� 6 µm), each of which contains the arrayed
tissues cores, then layers are mounted on microscope
glass slides. Cutting the TMA block is a delicate and
important step. The number of sections cut from a TMA
will impact the number of studies that can be done.
While, ideally, one wants to maximize the number of
slides produced from a given TMA, in order to maximize
the use of tissue, caution is required as thinner tissue
layers are more difficult to manipulate and thus easily
wasted. Considerable skill is required for reliable
1997
0
100Num
ber
of r
efer
ence
s/ye
ar
200
300
400
500
600
700
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
2011
FIGURE 5.1 Frequency of tissue microarray studies reported in
Pubmed*. The Pubmed database was used to search for the keywords
“tissue” and “microarray” and “immunohistochemistry” or “fluores-
cence”. References including gene microarray studies without tissue
microarray were manually excluded. * http://www.ncbi.nlm.nih.gov/
pubmed.
1 2
4 5
6 7
3
FIGURE 5.2 Construction of a tissue microarray. (1) The donor block
is aligned with the corresponding H&E slide to select an area of interest.
(2) An empty recipient paraffin block is positioned on the arrayer prior
to receiving cores from donor blocks. (3) A cylindrical core is punched
from the FFPE donor block. (4) The tumor core is vertically transferred
to the new recipient block. (5) Image of a new TMA block after comple-
tion. (6) Horizontal sectioning of the new TMA with a microtome.
(7) Image of a TMA slide after H&E staining.
67Chapter | 5 Tissue Microarrays in Studying Gynecological Cancers
sectioning of TMA blocks, also timing should be consid-
ered to remove the possibility of wasting material due to
“block facing” and “antigen decay” on unstained slides.
As TMA blocks become older there is “core fall out” as
individual cores become exhausted. Poorly cut or incom-
plete TMA sections can still be used as controls or as
experimental sections for working up novel assays.
Immunostaining Facilities or anImmunostainer
The quality of an assay is highly dependent on providing
stringent quality control over all steps of the staining
protocol. Automated staining robots have removed
human variation from staining by automating reagent
dispensing and, in some cases, the antigen retrieval pro-
cess. However, these devices cannot overcome any defi-
ciencies in specimen preparation prior to staining or
problems with the primary reagents, such as antibody
quality and activity. Automated immunohistochemical
stainers are available from several suppliers (Leica
Microsystem Covertiles, Ventana’s Benchmark and
Discovery, DAKO Autostainer Link, Biogenex Optimax,
and others).
Image Analysis Devices and Software
With the increased usage of TMAs, numerous commercial
sources of digital image acquisition and software have
become available to enable computer-assisted analysis of
target expression. These include Aperio, Caliper,
HistoRx, Definiens, Ventana, Visiomorph and others.
Tissues
Even if tissue microarrays are most commonly con-
structed from FFPE blocks, TMAs can also be con-
structed from FFPE biopsies, FFPE cell pellets or from
OCT frozen tissues [8�10]. The quality of proteins and
nucleic acids in stored tissues is dependent on several fac-
tors that influence the quality and efficiency of subse-
quent experimentation. These factors can include time to
tissue processing (warm and cold ischemia), fixation con-
ditions, storage duration, and storage conditions. It has
often been reported that tissue processing within 30 min-
utes is preferred for most applications to avoid loss of
antigenicity and alteration of nucleic acids in the tissue
[11]. Loss of antigenicity can also be observed in tissues
stored for a long period, especially in non-optimal light
and temperature conditions, and this can contribute to an
important bias in the data obtained [12�15]. Within a
given cohort, it is essential to verify through statistical
analysis that the age of tissues and staining intensity are
not correlated.
Tissue fixation is an important factor that can affect
results generated from TMAs. The most common fixative
for histologic tissues is an aqueous aldehyde-based solu-
tion, either fomaldehyde (4%) or glutaraldehyde (2�3%),
which creates covalent bounds between macromolecules
to maintain the tissue architecture and integrity of cellular
components [16]. However, tissue fixation may also
affect antigenicity and cause damage to nucleic acids.
The chemical fixative can modify aldehyde groups of pro-
teins but also surrounding soluble proteins in the tissue
can be cross-linked to the cellular proteins and lead to an
allosteric modification of epitopes. The advantage of
formaldehyde over glutaraldehyde fixation is the revers-
ibility of cross-linkages by heating. Another important
advantage of the formaldehyde fixative is that membrane
proteins are not destroyed during the process of fixation
[17]. However, glutaraldehyde allows better morphologi-
cal preservation. The process of fixation and antigen
masking with aldehyde-based fixative is progressive.
With increased fixation time there is a proportional
decrease of immunoreactivity due to increased antigen
masking. However, an overly short fixation time can lead
to incomplete fixation particularly in the central portion
of the tissue and thereby subsequently creates a heteroge-
neous immunoreactivity. Furthermore, exposure to alco-
hol during the processing steps leads to protein
denaturation if formalin fixation is incomplete. Therefore,
more moderate fixation conditions are recommended in
order to maximize the use of the TMA. Clinically, it has
been recommended to use a minimum of 6�8 hours of
fixation to obtain a reliable estrogen receptor (ER) stain-
ing in breast cancer tissues and a maximum of 48�72
hours [18]. Several buffered formalin preparations are
used in histology, but neutral buffered formalin (NBF) is
the most common since it yields relatively good nucleic
acids quality compared to other buffers. However, it has
been reported that other fixatives may be more advanta-
geous for the detection of certain specific antigens [19].
Perhaps disturbingly, the cellular localization of different
stains has been shown to vary using different fixatives,
implying that artifacts have been introduced during tissue
processing [19]. Alternative fixatives are mostly alcohol
or zinc based. More recently, attention has focused on a
new generation of molecular fixatives that improve the
quality of embedded nucleic acids such as RNAlater
(however, protein antigenicity may be sacrificed). It is
therefore recommended to consider carefully the appro-
priate fixative for all proteins of interest and/or test
immunogenicity of the proteins in different fixatives
before preparing the tissues to be used in TMAs.
Pragmatically, however, many TMAs are constructed for
pathology-based archival tissues where the best practice
is at least to document the method of fixation used in the
clinical setting. An issue sometimes arises in TMA
68 PART | 2 Genomics Technologies, Concepts and Resources
construction due to variation in embedding paraffin hard-
ness making construction and cutting of a TMA difficult.
If this situation arises, we suggest re-embedding the donor
blocks with fresh paraffin of the same formulation used
for the host block. An additional problem arises in large
studies that include specimens from multiple institutions
spanning many years. We have observed significant dif-
ferences in antigenicity associated with institution of
specimen origin, and age of specimen. These changes are
probably attributable to pre-analytical handling conditions
(such as time to fixation and formulation of fixation) and
changes in laboratory tissue handling procedures over
time. Consequently, it is important to record these vari-
ables and possibly adjust for them during data analysis.
Ethics and Regulatory Issues
As many TMAs are produced from human tissues, it is
essential prior to construction to have obtained the appro-
priate approval from the designated research ethics board.
Several laws and guidelines need to be considered when
dealing with human tissues, and international standards
include such references as the Helsinki declaration (www.
wma.net) and the UNESCO policy (www.unesco.org). In
Canada, the Tri-Council Policy Statement: Ethical
Conduct for Research Involving Humans (TCPS) is the
joint research ethics policy statement of the federal
research agencies that fund health research. This policy
has recently been updated (www.pre.ethics.gc.ca/eng/
policy-politique/initiatives/tcps2-eptc2/Default/). Whether
participants providing tissues need to be prospectively
consented, can be retrospectively consented, or whether
anonymized tissues without consent can be used is deter-
mined largely by jurisdictional conventions. Consent
should always be obtained using qualified personnel, and
all laboratory members who use human biological speci-
mens should be adequately trained, including around
issues related to patient privacy and confidentiality. In the
USA, the Belmont report led to the Federal Policy for the
Protection of Human Subjects, informally known as the
“Common Rule”. The Office for Human Research
Protections (OHRP) was also established within HHS.
Tissues removed for diagnostic purposes are an excel-
lent source of material for research study and TMA con-
struction. However, these materials are governed by
regulations, laws and policies overseeing diagnostic clini-
cal laboratories. In the USA, these include rules devel-
oped by CLIA (Clinical Laboratory Improvement
Amendments) and certification bodies such as the College
of American Pathologists. Some of these regulations
restrict use of diagnostic tissue for research purposes up
to 2 years and require clinical laboratories to maintain
specimens for at least 10 years. Specimens may also be
subject to local state and provincial laws. There is a lack
of clarity regarding “ownership” of tissues but, in general,
diagnostic tissues are assumed to be under the custodian-
ship of the medical director of the diagnostic laboratory
processing the specimen. Diagnostic material has special
status as it may be needed for medico-legal reasons, or
for additional testing (for example to assess a new inte-
gral marker necessary for enrollment into a clinical trial).
Design of Microarrays
The optimal design should take into consideration the
study goal and the end user. If the array is visually
scored, placing the cores in asymmetrical sub-arrays will
considerably ease the interpretation of the staining analy-
sis by orienting the user when viewing cores under the
microscope (Figure 5.3). In addition, even if a large num-
ber of tissue cores may render the tissue array more effi-
cient, too many cores can introduce staining variations,
particularly on the edges of the array. For this reason, we
do not generally recommend the construction of very
large TMA with more than 500 cores but rather divide
cases into sub-arrays in separate TMA blocks. If the
cohort under study has to be divided over several TMAs,
it is best to stain all slides at one time in order to
A.
B.
C.
FIGURE 5.3 (A) Example of an ovarian cancer TMA stained with
anti-E-cadherin antibody. Left image represents 13 magnification.
Middle image represents a 203 magnification of cytoplasmic and mem-
brane of E-cadherin. Right image represents a 2003 magnification used
for scoring analysis. (B) Representative images of immunofluorescence
on ovarian cancer tissue. Blue DAPI signal in nuclei. Image 203 . Left
image: Macrophage CD681 staining (red). Middle image: CD2061
staining (green). Right image: Merge staining showing the co-
localization of CD68 and CD206 markers (orange). Here CD206 expres-
sion is almost exclusively co-localized with CD68 staining. (C) Example
of SISH staining. Low (left) and high (right) magnification.
69Chapter | 5 Tissue Microarrays in Studying Gynecological Cancers
minimize experimental variability. The introduction of
positive and negative staining controls should be included
whenever possible and may include different tissue types
or cell lines with known profiles for the marker of inter-
est. In addition, genetically modified cell lines that either
under- or overexpress a marker of interest can be incorpo-
rated into the TMA. However, cell lines tend to stain dif-
ferently from fixed tissue so, in the case of tumor cell
lines, xenograft grown in immunocompromised animals
can serve as excellent controls. Including the same con-
trols on TMAs for a given cohort provides an additional
means of ensuring that staining across different slides
remains comparable. It is advantageous to include identi-
cal specimens across multiple TMAs to facilitate interpre-
tation and enable normalization of data. It is also helpful
to include additional controls of different organ tissue
(such as normal liver) to help orient arrays. Orientation
becomes progressively problematic as arrays are used and
cores “drop out”. Some investigators have noted that
staining may have spatial variation across the array
(stronger at top or sides) due to some manual methods of
applying staining reagents. Consequently, balanced ran-
dom construction designs are recommended to mitigate
these effects.
A map should be designed to record the position of
each tissue core within the TMA and scoring should be
tied to this map. The scoring can then be linked to the
clinical parameters of interest for subsequent analysis.
Microsoft’s Excel program is a simple way to store the
map design, scoring results and clinical data. However,
this platform may not be suitable for large TMAs with
extended and complex associated data. We recommend
cautious use of Excel as it is easy to corrupt data through
accidental “sorting” of columns in data sheets. Some
groups have designed publicly available software to facil-
itate the merger of TMA data and clinicopathological
parameters [20,21] (http://genome-www.stanford.edu/
TMA/combiner). Most recent automated scanners are sup-
plied with software that automatically collects tissue
images and links them to comprehensive database files
that are easily linked to image analysis software.
METHODS AND CONSTRUCTION
Selection of Tissues and Cores
Most of the work involved in the construction of a
TMA is spent during the process of tissue selection.
Not only does it requires a large amount of time,
depending on the size of the TMA, but also it is a cru-
cial step involving technical and ethical issues. The
data obtained from the analysis of a TMA are highly
dependent on the quality of the TMA, including tissue
quality, quality of core selection and design of the
TMA. The selection of tissues is defined by the pur-
pose of the study and should be able to answer the
study question(s) with statistical robustness. For this
purpose, the analytical variables should be carefully
considered. Since human tissues are precious material,
such selection will limit the number of cases in the
TMA without decreasing the statistical robustness of
the study. This includes parameters such as number of
cases to be selected with specific clinical variables
[22]. This is particularly important for outcome-based
or progression-based disease TMA. For example, in the
analysis of a potential prognosis marker, the TMA
should include enough cases with good and worse prog-
nosis, but each group of patients should have similar
clinical characteristics, such as same range of grade,
stages and age.
Before the physical construction of a TMA, a list of
the selected tissues is generated. Then, all tissue blocks of
the appropriate specimens are collected from the archive
and reviewed by a pathologist in order to select the opti-
mal donor blocks and appropriate punching areas.
Depending on the endpoint of the study or the marker of
interest, different tissue areas can be selected. When
selecting the punching area, it would also be pertinent to
record the tumor location of the punches in the tissue, i.e.
center of the tumor, peripheral edge of the tumor, near a
necrotic or inflammatory area, etc. This will help to deter-
mine if the staining of interest is dependent on the tumor
heterogeneity or tumor location. It should also be consid-
ered that antigen preservation is often better near the edge
of the specimen due to more rapid exposure to fixative.
In general, a marker of true clinical value should display
a uniform staining in the tumor and this could be assessed
by the use of TMA with different tissue areas from
several specimens.
The main critique of TMA in comparison of whole tis-
sue slides is the small amount of tissue to be analyzed,
which may not be representative of the whole tissue. Core
size and number will depend on the tissue type and
marker. Few studies have demonstrated a good concor-
dance between results obtained with only one or two
cores of 0.6 mm and whole tissue slides from ovarian or
breast tissues [23�26]. However, for some markers, such
as Ki-67, exhibiting strong tissue heterogeneity, addi-
tional cores should be included. Heterogeneous markers
may be prone to false negative results on TMA analysis.
In addition, a technical problem associated with TMA
analysis is the tissue lost or folding during the sectioning
or the staining. For ovarian or breast cancer TMA, we
recommend that at least two cores per tissue should be
considered, particularly if the cohort under study is small
and each individual in the cohort is necessary to maintain
a statistical robustness. Additional cores also enable an
assessment of tumor heterogeneity and perhaps a more
70 PART | 2 Genomics Technologies, Concepts and Resources
accurate estimate of antigen expression than single cores
lending statistical approaches such as calculating mean
expression. Core sizes usually range from 0.6 mm to
2 mm, with 0.6 mm being the “gold standard” for breast
and ovarian cancer tissues. The main advantage of a
smaller core is obviously a smaller depletion of the origi-
nal tissue specimens and the possibility of building TMA
slides with a greater number of cases per TMA slide. In
addition, larger cores make the sections more difficult to
manipulate and, especially in the case of breast tissue that
may have a high fat content, cores are easily lost during
processing when larger than 0.6 mm. Several websites
describe the production of TMAs, and a visual construc-
tion of TMA with a manual arrayer can be viewed at:
www.jove.com/video/3620/production-tissue-microarrays-
immunohistochemistry-staining.
Cutting Slides
Once the TMA is constructed, the new paraffin block
containing tissue cores can be cut into thin paraffin layers
and transferred onto microscope glass slides. This step is
technically delicate and, when poorly executed, can result
in tissue loss, folding of thin sections and even shift cores
from their initial location on the paraffin block. Sections
are traditionally cut with a microtome and transferred to a
water bath to collect TMA sections on the microscope
slide. An alternative technique commonly used to
decrease the frequency of tissue loss during sectioning is
the tape transfer method which consists of using an adhe-
sive tape placed over the face of the paraffin block prior
to sectioning to stabilize the section during cutting and
subsequent transfer to a microscope glass slide [27].
However increased non-specific staining of specific mar-
kers has been associated with this technique [28].
A single TMA block can potentially create 200 sec-
tions. However, since all donor tissue specimens are not
of the same depth, the first and last sections are usually
not appropriate for staining. In practice, 50 to 150 work-
ing sections are generated from one TMA block with
90% of cores in good condition.
An additional issue is antigen stability. It is recom-
mended that immunohistochemical stains be performed
on as freshly cut tissue sections as possible because anti-
gens can decay due to oxidation. It is possible to reduce
the extent of oxidation using techniques such as storing
slides in nitrogen gas, dipping them in paraffin, or wrap-
ping and freezing them. It is unfortunate that each time
an array is sectioned there is a potential for tissue loss
due to “trimming”, consequently, it is advisable to batch
stain a series of sections from a TMA to ensure maxi-
mum usage of tissue. We also recommend saving poorly
cut or incomplete sections for use as pilot testing or
controls.
Antigen Retrieval
Antigen masking that occurs during tissue fixation needs
to be retrieved to recover the tissue antigenicity. Several
methods have been implemented over the years and their
performance is variable and dependent on the applications
[29]. In particular, the antigen retrieval method is antigen/
antibody dependent. The most common methods, which
work for the majority of proteins, are 10 mM citrate
buffer (pH 6) and EDTA or EGTA (pH 9) buffer with
incubations between 80 and 100�C. Although several fac-
tors affect the efficiency of antigen retrieval, such as type
of buffer, pH, time, the most important factor is heat,
which induces hydrolytic breaks of intra- and intermolec-
ular cross-links [30]. More recently, Namimatsu et al.
have reported that a 0.05% citraconic anhydride solution
at neutral pH may work as an efficient method for anti-
gens difficult to stain such as CD4, cyclin D1 on breast
cancer tissues [31,32]. Several suppliers offer pre-made
retrieval solutions (Dako, Vector Labs, R&D Systems and
Novocastra to mention only some). In addition, clinical
manufacturers have developed robotic machinery to stan-
dardize the retrieval process (e.g. PT link from DAKO
and Ventana Benchmark which has built-in retrieval
protocols).
Staining
Several applications can be performed with a paraffin-
embedded TMA. The most common application is
immunohistochemistry (IHC) with one or two markers,
immunofluorescence with multiple markers or fluores-
cence in situ hybridization (FISH). IHC involves a pri-
mary and at least one secondary antibody and a
chromogenic substrate for detection. Several companies
now offer kits to ensure reliable and reproducible stain-
ing. The most common kits are manufactured by DAKO
Inc. While robust and reliable, this method cannot be
used for the detection of more than two markers in the
same tissue. Another major criticism of IHC is that analy-
sis is generally semi-quantitative at best.
An alternative approach to protein labeling by IHC is
immunofluorescence (IF) labeling with fluorophores. In
recent years, there has not been an increasing number of
reports describing the IF labeling of TMA sections com-
pared to IHC because this approach is technically and
financially challenging. A major technical challenge often
observed, but poorly described, is the autofluorescence of
cellular structures in FFPE tissues [33]. Several methodol-
ogies have been developed to deal with this problem [34].
Pretreatment of tissue slides with sodium borohydride
and glycine, and inclusion of normal goat and normal
donkey sera as a blocking step between antibodies, has
also been proposed [35]. The reagent performance to
71Chapter | 5 Tissue Microarrays in Studying Gynecological Cancers
mask autofluorescence depends on the fixative used and
tissue type under study. Sudan Black B 0.1% in 70% eth-
anol has been successfully used on ovarian cancer TMAs,
for example [36].
Another aspect to consider carefully is the choice of
fluorophore combination when two or more are used.
Several parameters should be considered and, ideally, the
spectra of fluorophores should be well separated. As the
level of protein expression affects the methodology, it is
recommended that least expressed proteins be analyzed
with the brightest fluorophores. Brightness index values
are not absolute and can vary depending on the antibody,
the antigen, the instrument, the staining protocol, the cell
type, and other factors. BioLegend offers a brightness
index guide to assist the choice (http://www.biolegend.
com/multicolor_staining#data). The combination of pri-
mary antibody and fluorophores can also lead to different
levels of background and even the sequence of hybridiza-
tion involving different fluorophores should also be tested
to reduce the autofluorescent background.
In addition to overcome technical challenges, quantita-
tive IF labeling and analysis of FFPE material, particu-
larly for TMA, needs an assisted fluorescence imaging
system. Scanned images can be processed and quantified
using sophisticated software, although defining para-
meters within these systems is not trivial. The major
advantage of IF labeling is obviously the quantitative
aspect of the technique and the possibility to perform
multicolor labeling, analyzing several molecular candi-
dates or identifying cellular subtypes on the same tissue
specimen. Using such techniques Mote et al. were able to
visualize the differential expression of progesterone
receptors A and B isoforms on endometrial tissues during
menstrual cycle [33]. Multiple antigen detection using IF
approaches not only addresses aspects of material deple-
tion but also allows concomitant and quantitative analysis
of several candidates within the same cells. A fluorescent
approach also provides the possibility of superior marker
subcellular localization based on the co-staining of pro-
teins of interest and a localization marker.
In Situ Hybridization and FluorescenceIn Situ Hybridization (ISH and FISH)
Tissue sections also lend themselves to in situ hybridiza-
tion approaches to visualize nucleic acid changes includ-
ing chromosomal structural changes such as gene
amplification, deletions, rearrangements and chromosome
changes such as polysomy [37]. Additional methods can
also visualize RNA. Further, pathogenic DNA or RNA
can also be targeted to visualize infectious agents such as
human papilloma virus (HPV) or Epstein-Barr virus
(EBV) [38]. In general, labeled DNA probes are
hybridized to tissue sections using appropriate tempera-
tures to denature and re-anneal target DNA or RNA.
After washing, the bound probes are visualized using anti-
bodies linked to enzymes causing signal development.
Signals may be fluorescent (FISH), chromogenic (CISH)
or precipitated silver (SISH) [39]. Some of the automated
staining devices (such as the Ventana Platforms, www.
ventana.com) are capable of performing the entire
deparaffinization, antigen retrieval and in situ hybridiza-
tion automatically. Multiple probes can be used simulta-
neously with FISH and CISH enabling translocations and
gene amplifications to be detected on a single slide.
When SISH is used, generally multiple slides are used to
calculate gene ratios to determine presence of amplifica-
tion, deletion and polysomy. FISH has the advantage of
multiplexing but the disadvantages of lack of signal sta-
bility and requirement of fluorescent microscopy. In addi-
tion, FISH is difficult to impossible to interpret manually
on standard TMAs if an automated imaging acquisition
device is not used. SISH and CISH have the advantage of
signal stability and ease of visibility using standard
bright-field microscopy, enabling manual observation and
interpretation.
QUALITY CONTROL AND ANALYSIS
Slide Conservation and Storage
TMA blocks and sections are a non-sustainable resource
and thereby a very precious material. To save material
and avoid loss during the sectioning step, some laborato-
ries may decide to cut a large number of sections at once.
However, tissues deteriorate rapidly due to oxidation in
contact with air, which can affect antigenicity of some
proteins as reported with cytokeratins, PR and HER2 and
ER on breast cancer tissues [13,40�42]. To prevent tissue
oxidation, cut sections can be paraffin coated and stored
in a dessicator at 4�C until further use but, to ensure the
preservation of antigenicity [13], each antibody of interest
should be cross-verified on fresh and stored tissues.
Staining and Antibody Quality
An important consideration in IHC and IF assays is the
antibody quality and titer. The antibody staining should
be specific and reproducible (Table 5.1). Specificity
should be assessed, preferably by the same technique as
the one being used for the study, i.e. IHC or IF, with the
appropriate controls or blocking peptides. These can con-
sist of formalin-fixed paraffin-embedded cell line pellets
[9], cell line xenografts, or tissues with known expression
patterns. However, validation in IHC can be challenging
since appropriate negative and positive controls are not
always available. Concomitant validation of the antibody
72 PART | 2 Genomics Technologies, Concepts and Resources
specificity by western-blot analysis in well-characterized
cell lines is also encouraged. Unfortunately, in the past,
antibody validation has not consistently been considered
as a standard for publication which, in part, explains the
number of inconsistent reports in the literature related to
ovarian cancer IHC analysis [43]. For more details about
antibody validation methods see Bordeaux et al. [44].
Optimal results are obtained with an appropriate anti-
body concentration. Titration of the antibody determines
the lowest dilution that gives the strongest signal with the
lowest background. Although this is a general rule for sec-
ondary antibodies, it may not be directly applied to primary
antibodies. The titer of antibody may affect the endpoint
data, particularly when scoring is associated with clinical
parameters or patient outcomes. Low concentration of anti-
body will highlight differences in the range of high expres-
sion while high antibody concentration will discriminate
differences in the low range of expression. An interesting
example was provided by the study of McCabe et al. [45]
who showed that when high concentrations of HER2 and
p53 antibodies were used, the lowest staining of these pro-
teins was associated with poor survival. In contrast, when
low antibody concentrations were used a stronger staining
was associated with poor survival. This particular example
is striking and has also to do with the complexity of the
breast cancer disease which includes several subtypes with
different clinical outcomes.
In IF, where labeling combinations are used, each com-
bination of antibodies should be tested to ensure that there
is no cross-reactivity. When using mouse secondary fluores-
cence labeled antibodies, the Mouse-on-Mouse blocking
agent (Vector Labs) permits the consecutive use of several
mouse secondary antibodies without cross-reactivity.
Investigators should be aware that antibody performance
may vary dramatically from batch to batch and decay over
time. Consequently, it is advised that, for a TMA study, a
single lot of antibody should be used and staining per-
formed in a batch whenever possible.
Scoring and Analysis
The visual scoring of TMA can be very laborious. The
traditional visualization with a microscope may take up to
2 hours of analysis per 100 cores, depending on the stain-
ing complexity and marker location. In this regard, digital
imaging has tremendously facilitated this step.
There are two main methods for scoring � visual and
automated. For visual scoring, the simplest is the semi-
quantitative evaluation, usually by visual inspection of
the staining intensity, giving each core a global value
from 0 to 3. This type of scoring provides categorical
data relatively easy to analyze and compare to clinical
parameters. When staining is not homogeneous a percent-
age of stained tissue area can also be evaluated. A more
complex approach takes into account both staining inten-
sity and stained area, giving rise to a staining index called
the “Quick score” that provides continuous values for sta-
tistical analyses [46,47]. The choice of scoring method
will depend on the marker. For example, analyses of
ovarian cancer tissues using antibodies directed against
Ki67 or p53 are usually evaluated by the percentage of
positive nuclei [48], while WT1 is scored by intensity and
percentage of staining [49,50]. Because this type of analy-
sis is subjective and arbitrary, at least two independent
observers are necessary to reduce bias of personal inter-
pretation and inter-observer variability should be assessed
[51] by an intraclass correlation method. The Intraclass
Correlation Coefficient (ICC), Cohen’s kappa statistic,
the Fleiss kappa and the concordance correlation coeffi-
cient have been proposed as suitable measures of agree-
ment among non-exchangeable observers [52]. In
addition, to reach a good scoring consensus between
observers, classifier parameters should be well defined
between observers to maintain consistency in the scoring.
TABLE 5.1 Summary Table of Problems and
Troubleshooting Encountered with TMA Staining and
Scoring
Problems Encountered
with TMA and IHC
Troubleshooting
Tumor heterogeneity Increase the number of cores pertissue
Loss of tissue cores Increase the number of cores pertissue
Artifactual staininglocalization
Fixation time
Type of fixative
Optimization of antibodyconcentration and incubation time
Time of specimen processing
Antigen retrieval Antigen retrieval buffer and pH
Non-specific staining Specificity of antibodies, introducepositive and negative control tissues
Optimization of antibodyconcentration and incubation time
Weak staining Optimization of antibodyconcentration and incubation time
Type of fixative
Age of tissue specimen
Time of specimen processing
Objective and tediousmanual scoring
Virtual microscopy
73Chapter | 5 Tissue Microarrays in Studying Gynecological Cancers
When there is discrepancy between observers scoring
should be reviewed. Another concern when evaluating
scoring is the interlaboratory variability [53]. There are
numerous studies with conflicting results as to the prog-
nostic value of individual biomarkers in the same malig-
nancy such as ovarian cancer [43]. To address this issue,
several groups have proposed standardized scoring meth-
ods for commonly used specific markers such as p53, ER
and PR in breast cancer tissues [54,55].
The automated method requires investment of capital
into digital microscopy including a scanning device and
image analysis software. There are now numerous com-
mercial systems available that are designed for the quanti-
fication of IHC or IF staining [7,56,57]. This approach
has the advantage of being more reproducible compared
to the manual scoring once algorithms are defined in the
software prior to analysis, more rapid and, importantly,
give rise to continuous data instead of categorical data.
Before initiating the study analysis, there are impor-
tant analytical parameters to verify. First, when several
cores from the same patient are incorporated in the TMA,
a core-to-core correlation test should be assessed to
ensure that the number of cores is representative of a
whole tissue section or that the tumor heterogeneity is
represented. Second, since the TMA is constructed from
archival tissue blocks, it is important to verify that the
antigenicity of the epitope of interest has not been lost
over time. A correlation test between age of tissue and
scoring should be performed to ensure there is no statisti-
cal bias associated with archival tissues.
Advanced digital acquisition techniques may allow
normalization of data prior to analysis. This could be
accomplished by taking ratios of signal in cancer cells to
internal controls such as stromal elements or adjacent
benign tissues, or adjusting the signals for variables such
as block age. It may also be advantageous to transform
the data prior to data analysis using log transformation, or
other methods that mitigate the effects of extreme data
outliers on the analysis.
To analyze scoring data and correlation with clinical
parameters, several statistical tests can be appropriate
depending on a number of factors such as distribution of
values, type of values (nominal, ordinal, categorical or con-
tinuous) [58]. A biostatistician can suggest the best test
and should be consulted for deeper analysis. To visualize
the survival distribution and the marker of interest, the
most common tests are Kaplan�Meier plots, logistic
regression or Cox regression analysis. In addition, it is also
important that data are reported in a comprehensive man-
ner to allow critical evaluation and comparison between
studies. To this purpose, the NCI-European Organization
for Research and Treatment of Cancer working group has
developed guidelines, called REMARK, for the reporting
of tumor marker studies [59]. There are also some
powerful data analysis tools such as X-Tile available from
the Rimm Laboratory that allow exploration of multiple
cut points in continuous data to define optimal expression
levels associated with key clinical endpoints. In general,
when novel cut points are identified using discovery meth-
ods, it is incumbent on the investigator to validate the
method on an alternate specimen collection TMA.
CONCLUSION
TMAs are a very effective approach for high-throughput
molecular analysis of pathological tissues supporting the
identification of new potential diagnostic and prognostic
markers in human cancers. TMAs are now widely used
for all types of tissue-based research, particularly in
oncology. They offer a range of applications in research
and quality assessment. TMAs have led to a significant
acceleration of basic research findings towards clinical
applications. Because TMAs have a limited representation
of tumor heterogeneity, biomarkers that score signifi-
cantly on this platform may represent the most robust of
indicators. However, TMAs remain a research tool and
should not be used as a diagnostic/prognostic tool at the
individual patient level, for which analysis of a greater
amount of tissue will ultimately be required. The migra-
tion of promising predictive marker assays from TMAs
into routine clinical use will require careful evaluation of
the staining characteristics of the selected marker in
whole tissue sections with development of precise quanti-
fication or analytical measurement approaches.
GLOSSARY
Fluorescence in situ hybridization (FISH) is a cytogenetic tech-
nique that is used to detect and localize DNA sequences on
chromosomes.
High-throughput screening Type of technique allowing a
researcher to conduct quickly millions of chemical, genetic or
pharmacological tests.
Immunohistochemistry (IHC) is a technique allowing the colori-
metric detection of antigens in cells or tissue sections with
antibodies.
Tissue microarray (TMA) is a technology allowing the transposi-
tion of punches of tissue cores from tissue donor blocks,
arranged in an array fashion.
ABBREVIATIONS
FISH Fluorescence in situ hybridization
FFPE Formalin-fixed, paraffin-embedded tissue
IHC Immunohistochemistry
OCT Optimum cutting temperature
TMA Tissue microarray
74 PART | 2 Genomics Technologies, Concepts and Resources
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