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Chapter 5 Cancer Genomics Tissue Microarrays in Studying Gynecological Cancers Cécile Le Page 1 Anne-Marie Mes-Masson 1,2 Anthony M. Magliocco 3 1 Centre hospitalier de l’Universite´ de Montre´al, Institut du Cancer de Montre´al, Montreal, QC, Canada 2 Universite´ de Montre´al, Department of Medicine, Montreal, QC, Canada 3 H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL, USA Contents Introduction 66 Materials and Tissues 67 Instruments 67 Tissues 68 Ethics and Regulatory Issues 69 Design of Microarrays 69 Methods and Construction 70 Selection of Tissues and Cores 70 Cutting Slides 71 Antigen Retrieval 71 Staining 71 65 Cancer Genomics. DOI: http://dx.doi.org/10.1016/B978-0-12-396967-5.00005-0 © 2014 Elsevier Inc. All rights reserved.

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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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