Authors: Gillian O’Hurley, Evelina Sjostedt, Arman Rahman, Bo Lia,

Caroline Kampf, Fredrik Ponten, William M. Gallagher,

Cecilia Lindskog

Online: Free online access

Issue: Mol Oncol. 2014 Jun;8(4):783-98. 

PMID: 24725481

The use of immunohistochemistry (IHC) in clinical cohorts is of paramount importance in

determining the utility of a biomarker in clinical practice. A major bottleneck in translating

a biomarker from bench-to-bedside is the lack of well characterized, specific antibodies

suitable for IHC. Despite the widespread use of IHC as a biomarker validation tool, no universally

accepted standardization guidelines have been developed to determine the applicability

of particular antibodies for IHC prior to its use. In this review, we discuss the

technical challenges faced by the use of immunohistochemical biomarkers and rigorously

explore classical and emerging antibody validation technologies. Based on our review of

these technologies, we provide strict criteria for the pragmatic validation of antibodies

for use in immunohistochemical assays.

for visualization of specific antigens in tissues or cells

based on antibody-antigen recognition, using brightfield or

fluorescent microscopy. The history of IHC goes back to the

early 1940s, when Coons and colleagues detected antigens in

frozen tissue sections by developing an immunofluorescence

technique (Coons et al., 1941). Introduction of a method based

on peroxidase-labelled antibodies opened the door to development

of more advanced approaches (Mason et al., 1969;

Nakane, 1968), enabling IHC to be used on routinely processed

tissue sections, such as formalin-fixed paraffin-embedded

(FFPE) tissues. However, it took until the early 1990s for the

method to become generally accepted in diagnostic pathology

(Leong, 1992; Taylor, 1994).

IHC is today a widely used method that can be rapidly performed

in most laboratories. The procedure is short, simple

and cost-effective. Indeed, IHC has emerged as an important

tool to detect cellular markers defining specific phenotypes

relative to disease status and biology. Moreover, IHC is utilized

for basic and clinical research, from small projects to highthroughput

strategies, to evaluate potential biomarkers in

clinical patient cohorts. However, the lack of standardized

guidelines for determining the specificity and functionality

of antibodies renders the translation of promising biomarkers

to the clinic difficult. Herein, we discuss the various limitations

and technical challenges that need to be addressed

when using IHC for biomarker development and clinical

validation.

A biomarker is defined as a molecule that is objectively

measured and evaluated as an indicator of normal biological

process, pathogenic process, or pharmacological responses to

therapeutic intervention (Biomarkers-Definitions-Working-

Group, 2001). Although great efforts have been made in the

last decade to discover novel cancer biomarkers for use in

clinical practice, a striking number of these efforts fail to

make it into the clinic (Fuzery et al., 2013). One of the causes

of this failure of translation could be the limited knowledge

that scientists working in biomarker discovery have in

analytical, diagnostic and regulatory requirements for clinical

assays (Fuzery et al., 2013). Over the last few decades a

number of key FDA approved cancer biomarkers have been

introduced into the clinic for differential diagnosis of specific

tumours, leading to improvement of cancer detection and

staging, identification of tumour subclasses, prediction of outcome after treatment, and selection of patients for different treatment options. However, of these approved biomarkers,

only five are individual IHC-based biomarkers

(Fuzery et al., 2013) (Table 1). The earliest FDA approved biomarkers

for IHC application were assays to detect the estrogen

receptor (ER), progesterone receptor (PR) and HER-2/neu

(c-erbB-2). The presence of these biomarkers in breast cancer

tissue serves as a diagnostic, prognostic and predictive

method to assist pathologists in identifying breast cancer

subtypes and determine whether patients are suitable candidates

to receive certain targeted therapies such as Tamoxifen

(ER positive patients) or Trastuzumab (Her-2 positive patients).

The IHC biomarker c-kit (CD117), which is used in

the clinic to detect gastrointestinal stromal tumours (GISTs)

(Debiec-Rychter et al., 2004), and p63, which is used to detect

the presence of basal cells indicative of normal prostate

glands (Shah et al., 2002; Weinstein et al., 2002), are the latest

FDA approved single marker IHC-based assays which were

approved almost a decade ago in 2004 and 2005, respectively.

Since then no other individual biomarker developed for

detection in an IHC assay has been FDA approved. However,

despite lack of FDA approval, there are many IHC markers utilized

in some clinics to assist pathologists in diagnosis and

decision making. Such examples include the use of E-Cadherin

and/or p120 staining to assist diagnosis of invasive

lobular breast carcinoma (Rakha et al., 2010), various antibody

panels for diagnosis and sub-classification of malignant

lymphomas, as well as the use of the proliferating nuclear

marker, Ki67.

An ideal biomarker demonstrating clinical sensitivity and

specificity of 100% is almost never achieved in practice due

the fact that increasing one of the parameters is only

achieved at the expense of the other. As a result, panel

biomarker assays are becoming more relevant. Two emerging

IHC panel-based assays are Mammostrat by Clarient InsightDx and IHC4 by Genoptix Medical Laboratory. Mammostrat is an IHC-based panel assay that can estimate risk

of recurrence in hormone receptor-positive, early stage

breast cancer patients which is independent of proliferation

and grade. This assay quantifies p53, HTF9C, CEACAM5,

NDRG1 and SLC7A5 by a defined mathematical algorithm

resulting in a risk index (Bartlett et al., 2012, 2010). Similarly,

IHC4 is another emerging assay which estimates recurrence

risk for early stage breast cancer patients by quantifying

IHC measurement of ER, PR, HER2 and Ki-67 using Aqua

technology (Cuzick et al., 2011).

IHC-based biomarker assays represent an attractive

approach for biomarker detection in the clinic as the IHC technique

is routinely carried out in clinical laboratories, there is a

fast turn-around time from assay to results and it is costeffective.

However, the paucity of FDA-approved biomarkers

for IHC-based assays emphasizes the importance and urgent

requirement of standardized guidelines and workflows for

IHC assay development which should be implemented at an

early stage of biomarker discovery. This will ensure robust

analytical and clinical performance and ultimately lead to a

better chance of an IHC-based biomarker assay achieving

FDA approval.

The standard brightfield IHC technique is comprised of three

components; slide preparation, IHC procedure and interpretation.

Antibodies used in the clinic have undergone thorough

testing and every step of the protocol has been well established,

including both positive and negative controls. Factors

which may affect the outcome of IHC include tissue handling,

epitope retrieval, storage and handling of tissue sections,

choice of antibody, detection method and interpretation procedure.

To yield the expected staining pattern when establishing

a new antibody, all factors which may influence the

standardization and reproducibility of the process need to be

carefully considered. These factors are summarized in

Figure 1 and will be described more in detail below.

‘Ischemia time’ refers to the time from when a tissue or organ

is cut off from O2 supply through removal of a specimen from

the body in surgery, to fixation of the specimen. Ischemia

results in degradation of protein, RNA and DNA, as well as

activation of tissue enzymes and autolysis (Kumar et al.,

2005) and can therefore be a major factor influencing IHC results.

Recently, Pekmezci et al. demonstrated that longer

cold ischemia time affects the detection of ER and PR by IHC

in breast cancer (Pekmezci et al., 2012). Although the American

Society of Clinical Oncology and College of American Pathologists

(ASCO/CAP) has developed guidelines for handling

of tissues for ER, PR and HER-2 detection in breast cancer patients,

such guidelines are not available for other surgical

specimens (Comanescu et al., 2012; Hammond et al., 2010).

Fixation is another critical step in the IHC process to preserve

tissue morphology and retain antigenicity of the target molecules.

Two types of fixatives are commonly used in histopathology;

(1) non-coagulating fixatives (formaldehyde,

glutaraldehyde, osmium teroxide, potassium dichromate

and acetic acid) and (2) coagulating fixatives (alcohol, zinc

salts, mercuric chloride, chromium trioxide and picric acid).

The most common fixative used in histopathology is 10%

neutral-buffered formalin. This is composed of 4% paraformaldehyde

solution which is buffered to a neutral pH.

Formalin cross-links peptides by formation of hydroxymethyl

groups on reactive amino acid side chains, providing excellent

preservation of tissue architecture; however, formalin fixation

can mask epitopes and result in decreased antigenicity.

Several factors influence the formalin fixation method, such

as temperature, time, penetration rate, specimen dimension,

volume ratio, pH of the buffer and osmolality, but unfortunately,

there is a lack of available guidelines to establish a

standard practise across pathology laboratories.

3.2. Appropriate storage and handling of tissue sections

Another factor that may influence the IHC outcome is storage

of prepared tissue sections (Wester et al., 2000; Williams

et al., 1997). It has been suggested that storing tissue sections

longer than two months leads to loss of p53 antigen reactivity

(Prioleau and Schnitt, 1995). The mechanisms underlying the

loss of antigenicity in FFPE tissue is unclear. It has been

hypothesised that oxidation may be the key contributor of

antigenicity loss (Blind et al., 2008; Sauter and Mirlacher,

2002). Due to this and the fact that degradation of protein is

temperature dependent, a large variety of storage conditions

for cut sections have been advocated such as cold storage, paraffin coating or vacuum sealed desiccators. However, recently it has been suggested by Xie et al. (2011) that the

presence of water both endogenously and exogenously plays

a central role in loss of antigenicity. Therefore, slide storage

conditions that are protected from oxidization by vacuum

storage or paraffin coating are not completely protecting

slides from loss of antigenicity if residual water from inadequate

tissue processing is present on the tissue (Xie et al.,

2011). Thus, the optimal storage of unstained sections is yet

to be defined, making freshly cut sections or sections stored

for less than two months most ideal. For long-term storage,

vacuum containers or storage in colder conditions (þ4/18)

is often recommended.

Another major step that should be considered carefully when

performing IHC is antigen retrieval (AR). The two methods of

antigen retrieval are (1) heat-induced epitope retrieval (HIER)

(e.g. citrate pH 6.0, TriseEDTA pH 9.0 and EDTA pH 8.0) and

(2) proteolytic enzyme-induced epitope retrieval (PIER) (e.g. proteinase

K, trypsin, pepsin, pronase). Of the two methods, HIER

is most commonly used. The technique was first described by

Shi and colleagues (Shi et al., 1991) and has been improved by

a number of investigators (Cattoretti et al., 1993; Greenwell

et al., 1991, 1993) for its routine use in laboratories throughout

theworld. However, the mechanisms of AR are not fully understood.

It is speculated that both HIER and PIER serve to break

the methylene bridges created during fixation, exposing the

antigenic sites in order to allow the antibodies to bind

(D’Amico et al., 2009; Fowler et al., 2011; Kakimoto et al., 2008;

Leong and Leong, 2007; Suurmeijer and Boon, 1993).

There are several different AR variables that can affect IHC

staining results such as heating, the choice of AR solution, its

pH and molarity, and the effect of metal ions (D’Amico et al.,

2009; Emoto et al., 2005). An appropriately controlled AR

method can restore antigenicity in formalin fixed paraffin

embedded (FFPE) tissue to resemble the antigenicity of frozen

tissue. Moreover, it can facilitate IHC standardization, despite

variations in tissue fixation and subsequent handling (von

Boguslawsky, 1994) (Shi et al., 2007; Taylor, 2006). However,

the appropriate AR protocol is dependent on both the antibody

and the target protein, and needs to be optimized for every antibody.

The three cardinal points that must be considered when

buying commercial primary antibodies for IHC are as follows:

(1) use reliable, recommended companies, (2) obtain complete

information about the antibody to ensure it is applicable or

recommended for IHC and, (3) characterize the specificity of

the antibody. A significant number of commercial antibodies

are not thoroughly analysed for off-target binding, e.g. using

protein arrays (Chang, 1983; Nilsson et al., 2005). In addition,

several companies do not provide the sequence of the antigen

the antibody was raised against (Saper, 2009) and, therefore,

antibody validation is a mandatory step before proceeding

with IHC.

The choice of using either monoclonal or polyclonal primary

antibodies for IHC further complicates the issue of

epitope specificity and determining which antibody would

be more suitable for IHC (Bordeaux et al., 2003). Polyclonal

antibodies are a collection of antibodies targeted against

multiple epitopes of a particular antigen. Generally, when

an animal is injected with a specific antigen, the immune

system elicits a primary immune response by producing

multiple B cell clones against the antigen. After subsequent

immunization with the same antigen, these B cells differentiate

into plasma cells producing and secreting antibodies

found in the serum. The serum containing polyclonal antibodies

can be affinity purified using the antigen as a ligand,

which eliminates 99% of antibodies recognizing other targets

than the antigen. This procedure results in antibodies

with higher specificity than conventional polyclonal antibodies,

still retaining the ability to recognize different epitopes

on the same antigen (Lindskog et al., 2005). A

monoclonal antibody is generated by selection of one single

B cell from spleen or bone marrow of the immunized animal

and fusing this cell with immortal myeloma cells to

produce hybridoma cells (Kohler and Milstein, 1975). As

such, the culture supernatant contains only one type of

antibody specific for a single epitope of the immunizing

peptide. The advantages and disadvantages of using polyclonal

and monoclonal antibodies for IHC are summarized

in Table 2.

A useful tool to search for appropriate antibodies suitable

for IHC is the portal, Antibodypedia (http://www.antibodypedia.

com). Here, antibodies are listed with reference to antibody

companies and associated validation data (Bjorling and

Uhlen, 2008).

The outcome of an IHC assay depends on the use of sensitive

protein detection system in order to visualize the antigeneantibody

reaction. The most popular methods of detection

are enzyme and fluorophore-mediated detection

systems. With chromogenic substrates, an enzyme label is

reacted with the substrate to yield a strong colour product

visualized by brightfield imaging. Alkaline phosphatase (AP)

and horseradish peroxidase (HRP) are the two most extensively

used enzymes, both with available chromogenic, fluorogenic

and chemiluminescent substrates.

Detection systems in IHC can be divided into two broad categories,

namely direct or indirect. In the direct detection

method, the primary antibody is labelled with enzymes or

fluorochromes, enabling direct detection of the antigen on

the tissue section without the requirement of a secondary

antibody. This method of detection is simpler and less time

consuming; however, it has the disadvantage of lower sensitivity

compared with indirect methods. The indirect detection

method involves the use of unlabelled primary antibodies and

labelled secondary/tertiary antibodies, which are specific for

the bound primary antibody. Although this method is time

consuming and complicated by multiple steps, indirect detection

method is more sensitive in detecting tissue antigens.

Some commonly used indirect detections mechanisms are

as follows; the avidin-biotin complex (ABC) method, the

labelled streptavidin biotin (LSAB) method, the phosphataseanti-

phosphatase (PAP) and the polymer-based detection

system. There are several other immunohistochemical detection

methods such as tyramide amplification, cycled tyramide

amplification, fluorescyl-tyramide amplification and rolling

circle amplification, but these are not heavily used to date in

routine IHC.

Post-translational modifications are important biological

events that control the behaviour of a protein. Phosphorylation

is a post-translational process regulating protein activity

by the addition and removal of a phosphate group.

Tissue phosphoproteomic studies show promise for the

discovery of key phosphorylated proteins and signalling

pathways in many diseases (Bodo and Hsi, 2011). The

detection and quantification of phosphorylation has been

well established using techniques such as Western blotting

on cell lysates but it represents a new era in diagnostic pathology.

Many phospho-specific antibodies have been

generated for immunohistochemical application; however,

the detection step remains challenging due to the labile

nature of phosphorylated proteins, reflecting dynamic processes.

In addition, tissues become oxygen deficient

shortly after being isolated from the blood supply and subsequently

undergo rapid protein dephosphorylation (Blow,

2007). Therefore, if the tissues are not fixed within 60 min

post-surgical removal from the living body, the majority of

phospho-epitopes are lost (Baker et al., 2005; Jones et al.,

2008). Due to this, most phosphorylation studies have not

been reproduced. Other variations between studies leading

to these discrepant results can include sample procurement,

processing, scoring/quantification and subjectively

selected cut-offs (Bodo and Hsi, 2011). Therefore, rigorous

standardization of laboratory procedures for tissue preservation

and for the overall IHC technique as well as quantification

is required for success in quantifying

phosphorylation by IHC in tissue. Post-translational modifications

such as phosphorylation can also be studied with

proximity ligation assay (PLA), described in Section 4.3.

However, many of the same issues discussed here will

also apply to PLA.

A major milestone in the standardization, reliability and

reproducibility of IHC is the invention of automated IHC platforms.

Many critical steps in the manual IHC method are

operator-dependent and essential to the quality of the final

IHC result and its reproducibility (Shi and Taylor, 2011). These

include the critical antigen retrieval step, reagent preparation,

application of reagents, appropriate washing steps and multiple

incubation times. The use of automated IHC not only allows

for larger volumes of slides to be stained

simultaneously under standardized conditions, but also provides

assistance to operators through additional processing

monitoring errors such as alarms for inappropriate temperatures,

insufficient volumes of reagent, expired reagents and

even the selection of an incorrect reagent via the use of barcode

scanning (Fetsch and Abati, 1999; Moreau et al., 1998;

Prichard et al., 2011).

Many automated IHC machines, particularly those used in

a clinical setting, are what is termed as “closed systems”

which means the instrument is closed to introducing variations.

Although this is an important advantage for standardization

of IHC staining, it can be a drawback for research as the

flexibility of choosing reagents, retrieval methods and introduction

of subtle variation to the technique is lost. This has

led to the development of “open” automated systems, offering

similar flexibility as manual staining (Prichard et al., 2011).

However, as HIER is not performed on an “open” platform,

some of the same limitations of manual IHC discussed previously

apply to this type of automated IHC. Clearly, there are

advantages and disadvantages to the manual staining method

and the “open” and “closed” automated systems so the choice

of method should be influenced by the laboratory’s purpose

(Prichard et al., 2011). However, for large-scale IHC efforts

where planning and standardized IHC protocols are necessary

(Uhlen et al., 2005; Warford et al., 2004) it can be anticipated

that automated IHC may lead to reduction in error rate as

each step of the staining procedure is recorded (Howat et al.,

2014). Together with tissue microarray (TMA) technology

(Battifora, 1986; Kononen et al., 1998), where a large number

of tissues from different organs or individuals are assembled

on a single slide, high-throughput IHC minimizes reproducibility

issues.

Manual assessment of IHC staining remains the traditional

method for most diagnostic and predictive decisions in pathology.

However, manual interpretation of IHC data can be

time intensive, laborious and an inherently subjective and

semi-quantitative process (Fiore et al., 2012). Observer variability

can exist in three forms; intra-observer variability,

inter-observer variability and inter-laboratory variability

(Conway et al., 2008). The latter is usually attributed to issues

regarding tissue fixation and processing, antibodies used and

detection systems. Intra-observer variability, referring to the

lack of consistent assessment by the observer, occurs less

frequently than inter-observer variability due to the fact that

pathologists adhere to their own internal standards (Kay

et al., 1994). Inter-observer variability is the greatest problem

associated with human-based assessment of IHC staining,

influenced by factors such as misplaced orientation on a

TMA slide, eye fatigue, complexity of data management

following differential categorical scoring, quality of microscope,

illumination of microscope and individual human

vision limitations (Conway et al., 2008).

Utilizing image analysis systems on virtual microscopy

slides or whole slide images has been proposed as solving

the problem of standardized quantification of IHC data, due

to its capability of producing continuous datasets eliminating

categorical and biased assessment. High-throughput image

analysis methods can also reduce workloads and outperform

human manual scoring in terms of reproducibility and precision,

as they are not affected by fatigue or subjectivity. Enormous

advances in image analysis systems on tissue sections

have been achieved over the years (Taylor and Levenson,

2006). However, despite these advances, image analysis is

far from ready to replace the expert pathologist, as it is still

very much a semi-automated approach as most algorithms

require specific input and training by a pathologist in order

to produce accurate output. In addition, image analysis approaches

are highly influenced by a number of factors that

can affect the quality of their performance. For example, the

quality of sections/TMAs hugely affects the resulting data obtained

from image analysis. This is due to the inability of most

of the current automated image analysis systems to identify

irregularities on a section that the human eye can ignore,

such as artefacts, edge effect staining, folding of tissue and

thickness of tissue section, which may produce a false score.

Moreover, image analysis often fails to distinguish tumour

from benign tissue. Nevertheless, it is widely accepted that

the continuous development of computer-aided image analysis

technologies will lead to quantitative systems that will

compliment and support the pathologist/human expert to

produce a less subjective and accurate IHC assessment.

When measuring protein expression levels in tissue, a decision

must be made as to whether assessment should be performed

by IHC using brightfield imaging or

immunofluorescence (IF) using fluorescent imaging, where

both techniques offer advantages over the other. Brightfield

imaging utilizes visible white light to illuminate the tissue,

and protein expression is classically observed and graded

based on the intensity of 3,30-diaminobenzidine (DAB), generating

a brown staining (Gustashaw et al., 2010). Counterstaining

with haematoxylin keeps morphological detail of the

surrounding tissue intact and allows visualisation and analysis

of localized protein. The IF technique visualizes protein

expression in tissue against a dark background, using an antibody

with a chemically attached fluorochrome, such as fluorescein

isothiocyanate (FITC) or tetramethyl rhodamine

isothiocyanate (TRITC) (Jordan et al., 2002). The antigeneantibody

complex can be visualized using a fluorescent imaging

instrument such as a microscope or scanner.

IHC using brightfield imaging is one of the pillars of modern

pathology and a fundamental research tool in both

pathology and translational research (Robertson and Savage,

2008), due to the many advantages associated with the technique.

It can be performed routinely on FFPE tissue, which

permits a pathologist or researcher to work with a familiar,

conventional microscope (Jordan et al., 2002). In addition, it

can detect antigens expressed at relatively low levels due to

chromogenic enhancement steps, the equipment cost is low,

and only minimal laboratory space is required. Most importantly

in a clinical setting, the chromogens are very stable

and long-term slide storage is possible for many years. However,

as a research tool, there are some major limitations associated

with the technique. Firstly, the resolution of antigen

localization is limited due to the chromogenic substrate precipitate,

as well as the thickness of the sections imaged in

the light microscope. Secondly, saturation of chromogenic

systems occurs easily, which restricts quantitative analyses

(Robertson and Savage, 2008). Above all, IHC using brightfield

microscopy has a narrow dynamic range limiting its capability

of multiplexing, and as cross reactivity is common, three antibodies/

chromogens at a time is a maximum. Therefore,

sequential or multi-step staining is crucial to ensure

cross reactivity does not occur with enzymes used or with

primary/secondary antibodies raised in the same species.

In addition, choosing colour combinations that are

distinguishable by eye from each other and from the counterstain

can be challenging, particularly when looking at colocalized

proteins. The concentration of precipitate may also

inhibit further reaction, making it difficult to visualize rare

targets and highly abundant targets on the same slide

(Christensen and Winthers, 2009). Moreover, quantitation of

multi-staining using brightfield microscopy is even more

limited, as most brightfield image analysis tools are primarily

designed to quantify single chromogens. However, the use of

spectral imaging technologies allows unmixing of stains and

individual quantification of each chromogen.

In contrast to brightfield IHC, IF has a better capability of

multiple labelling, as IF is of higher resolution due to the fluorophores

being directly conjugated to the antibody (Robertson

and Savage, 2008). Although choosing dyes with distinguishable

spectral properties is still an issue, fluorescent imaging

has a much broader dynamic range compared with brightfield

imaging (Christensen and Winthers, 2009). On the other hand,

IF-based detection presents certain difficulties in respect to

interpretation of tissue morphology, as well as the cost of reagents

and equipment. Moreover, a fluorescent signal can be

quenched when the fluorophores are in close proximity, and

as fluorophores are not as stable as chromogens, photobleaching

of stored slides is an issue. The most restraining aspect of IF is inherent autofluorescence of FFPE material, making high quality immunofluorescence imaging capricious (Robertson

and Savage, 2008) and limiting the use of clinical material. Examples

of consecutive sections stained with both brightfield

and darkfield are displayed in Figure 2, illustrating some of

the advantages and disadvantages with both methods.

The use of multispectral imaging has overcome many of

the issues regarding autofluorescence on FFPE tissue

(Mansfield et al., 2005; Robertson and Savage, 2008). However,

many reports using IF labelling of FFPE sections (Bataille et al.,

2006; Bossard et al., 2006; Ferri et al., 1997; Hoover et al., 1998;

Mason et al., 2000; Niki et al., 2004; Nurnberger et al., 2006;

Papaxoinis et al., 2007; Scott et al., 2004; Suetterlin et al.,

2004) have not been widely acknowledged by the scientific

community (Robertson and Savage, 2008) rendering IHC by

brightfield microscopy a more accepted assay for clinical use

in quantifying protein expression. However, continuous

research and development of new methods in the area of IF

and image analysis, such as the new technique MxIF (Gerdes

et al., 2013), will bridge the gap between classical IHC of FFPE

material and the acceptance of IF analysis of human FFPE

tissues.

One potentially might also consider application of both

brightfield and fluorescent imaging, e.g. use of H&E staining/

brightfield imaging for localisation of tumour regions and

use of fluorescence-based imaging for quantitation of consecutive

tissue sections.

Commercial production of antibodies is well established;

however, there are no universally accepted guidelines or standardized

methods for determining the validity of these reagents

(Bordeaux et al., 2003). The production and validation

of specific antibodies is a challenging, costly and time

consuming process. Perhaps as a result, the quality control

by the antibody vendors is not always what it should be

(Couchman, 2009). Moreover, the information supplied in academic

publications where the antibodies are used is often

insufficient. Therefore, it is imperative that investigators

take requisite steps to assure themselves that the specificity

of each antibody is as advertised. Here we explore both classical

and emerging technologies for antibody validation.

The signal intensity is generally related to the antibody concentration

(Dabbs, 2006). In order to get an optimal dilution

of an antibody, rendering the greatest contrast between

desired (specific) positivity and unwanted (non-specific) background,

it is necessary to know which staining pattern to

expect. Hence, the first crucial step in antibody validation is

to understand the nature of the target protein. For wellknown

or partly characterized proteins, information

regarding the expected staining pattern can be obtained

from available databases such as Uniprot (www.uniprot.org),

the Human Protein Atlas (www.proteinatlas.org), or by

searches in published literature. Bioinformatic prediction

algorithms for expected subcellular localisation, including

presence of signal peptides or transmembrane regions, is

gathered in online sources such as MDM (Fagerberg et al.,

2010), SPOCTOPUS (Viklund et al., 2008) and Phobius (Kall

et al., 2004). Furthermore, information on post-translational

modifications or splice variants is important in order to

predict detection of multiple bands in Western blotting.

Such information can be retrieved from e.g. OMIM

(www.ncbi.nlm.nih.gov/omim) or Genecards (www.genecards.

org). A large fraction of the human proteins are essentially

uncharacterized and experimental data is needed for validation

of the generated staining pattern in IHC.

The standard antibody validation method is Western blotting,

whereby antibody specificity is confirmed by the presence of a

single band corresponding to the predicted molecular weight

of the target protein. However, as many proteins have a

similar molecular weight, a band of the correct size is not

full evidence for targeting the intended protein. Moreover,

the kinetics of antibody-antigen binding is context dependent

and validation needs to be performed in an applicationspecific

manner. Therefore, even if an antibody yields a

band of correct predicted size in Western blotting, it does

not necessarily imply that the antibody is functional in IHC assays

on FFPE tissue. This is mainly due to the fact that immunogenic

epitopes are exposed differently in SDS-PAGE

compared to formalin fixation. Proteins are denatured during

the Western blotting process so post-translational modifications

on the native protein may not be represented, while

epitope masking (Hawkes et al., 1982) can occur with formalin

fixation. Furthermore, as Western blot is dependent on the

relative concentration of both the target and other proteins

in the sample, even antibodies validated as highly specific

may generate cross-reactivity to off-target proteins in the

sample. This may be overcome by using cell lysates overexpressing

the full-length target protein, as the probability of

correct protein detection is higher when a protein is present

at sufficiently high level (Algenas et al., 2014).

Paired antibodies are defined as antibodies raised against

different, non-overlapping epitopes on the same target protein.

A similar IHC staining pattern yielded by two separate

antibodies towards the same target protein on consecutive

sections suggests a higher level of reliability, especially of

importance for proteins lacking previous characterization

(Uhlen et al., 2010). A dissimilar staining pattern does not

however necessarily imply that both antibodies are unspecific,

as one of them still could show the correct pattern. In

addition, dissimilar antibodies could potentially mean that

the antibodies are directed towards different isoforms of the

same target protein, and other methods are necessary to

decide if the antibody is specific. Even a similar staining patterns

obtained by a set of paired antibodies can be difficult

to interpret, and do not conclude if the two antibodies display

the same unspecific background. The latter can be further

elucidated using in situ proximity ligation assay (PLA).

The PLA technique is highly sensitive method determining

protein interactions and analysing post-translational modifications

(Blokzijl et al., 2010; Lizardi et al., 1998; Soderberg

et al., 2006). It is based on the principle that two or more

oligonucleotide-conjugated antibodies need to bind in close

proximity in order to detect a signal, and can be utilized

directly in frozen or FFPE tissue sections (Soderberg et al.,

2008; Zieba et al., 2010). The binding is visualized by labelling

the oligonucleotides with fluorophores or HRP. As two separate

binding events are required to produce a signal, PLA

also serves as a useful and reliable tool for antibody validation,

using antibodies directed towards different epitopes on the

same target protein. The signal generated by PLA can be quantified,

and as each event produces a single “dot”, the outcome

can be measured more easily compared to IHC staining intensity,

facilitating automated image analysis.

The central dogma suggests a direct relationship between

mRNA expression and protein levels in a population of cells

at steady state. Lately, development of RNA sequencing

(RNA-Seq) has provided sensitive and reproducible expression

analyses which can be easily applied for large scale exploration

(Brawand et al., 2011; Wang et al., 2009). Comparison

with transcription data may be a valuable antibody validation

tool, whereby the quantitative measurement of the transcript

abundance can be used to support the validation of protein

expression. Several comprehensive RNA expression datasets

are available online, e.g. at the Human Protein Atlas

(www.proteinatlas.org) (Fagerberg et al., 2013), the RNA-Seq

atlas (www.medicalgenomics.org) (Krupp et al., 2012) and

the BioGPS portal (www.biogps.org) (Wuet al., 2009). However,

expression and abundance data is more noisy and complex

than the underlying genomic sequence information, and protein

levels are influenced by translational and posttranslational

mechanisms. Some proteins are secreted or

transported to other sites, and may not be observed in the organ

where mRNA is expressed. This is the case for e.g. liver,

where a large set of genes displaying high liver-specific

mRNA expression are negative for the corresponding proteins

in liver, while positive in plasma (Kampf et al., 2014). Hence,

some proteins may be present at levels not readily predicted

by mRNA levels (Ghaemmaghami et al., 2003;

Schwanhausser et al., 2011). On the contrary, a high correlation

between mRNA and protein levels has still been shown

in a number of studies (Greenbaum et al., 2002; Lu et al.,

2007). The molecular pathways determining the expression

patterns need to be further elucidated, in order to answer

the fundamental question to what extent mRNA and protein

expression correlate.

The RNA-Seq technique may provide quantitative measurements

of transcript levels; however, the comparison to IHC

data is quite crude. The sequence mRNA pool from a tissue

sample reflects all the different cell types present in the sample,

and the RNA-Seq lacks the precise localization and high

cellular resolution provided by IHC. For morphological

information on spatial distribution, in situ hybridization (ISH)

uses RNA probes labelled with e.g. biotin that can be visualized

in FFPE tissues (Carson et al., 2002; Gall and Pardue,

1969; Jin and Lloyd, 1997). One example of a large-scale initiative

using ISH spatial data is the Allen Brain Atlas (Lein et al.,

2007), extensively used in the field of neuroscience. ISH renders

a staining that can be compared with that of IHC and

may thus serve as an antibody validation technique, e.g. identifying

false positive results (Kiflemariam et al., 2012). However,

as for several other methods, blocking of endogenous

peroxidase and biotin could be a limiting factor (Qian and

Lloyd, 2003), and in addition, ISH lacks the sensitivity to distinguish

between sequences of high homology.

Mass spectrometry provides the standard for detecting and

quantifying a targeted set of proteins in a sample. The

method uses the principle of ionizing peptides derived by

proteolysis, and measuring the signal intensity of fragment

ions over time, which indicates the abundance of the peptide

in the sample (Anderson and Hunter, 2006; Towbin et al.,

1979). As mass spectrometry yields a quantitative measurement

of the target protein, it may be an important complement

in validating the expression pattern rendered by an

antibody, i.e. in analysing unexpected bands yielded by Western

blotting. However, mass spectrometry lacks the spatial

resolution that can be provided by IHC, and has sensitivity

problems. It has been shown that the signal response of

different peptides from the same protein can vary as much

as 100-fold in intensity (Picotti et al., 2007). Mass spectrometry

also has a bias towards highly expressed proteins, as a

low detection limit results in a reduced signal-to-noise-ratio

(Hack, 2004; Lange et al., 2008).

Another approach to ensure antibody specificity is to perform

IHC on positive and negative FFPE control cell lines known to

express or not express the target protein, and to perform

Western blotting on their subsequent lysates. This is also a

useful tool to ensure your antibody is applicable to use on

FFPE material prior to its use on valuable FFPE tissue. However,

cell lines in which targets have appropriate levels of

expression or lack of expression can be limited. In these instances,

alternative approaches of cell manipulation can be

performed to create positive and negative control cells. Overexpression

models can be created and used as positive controls

by introducing viral constructs that contain the gene/

protein of interest into a cell line via lentiviral or retroviral

transduction or plasmid-based transfection (Seth, 2005). Similarly,

negative control cell lines can be derived by RNA interference

(RNAi), whereby expression of a target gene can be

knocked down with high specificity (Rao et al., 2009). Alternatively,

the use of the recently developed approach of clustered

regularly interspaced short palindromic repeats (CRISPR) (Cho

and Kim, 2013; Mali et al., 2013) could be used to generate a

negative control. Unlike RNAi knockdown where transfection

efficiency rarely reaches 100%, the CRISPR approach allows for complete knockdown which is ideal for insurance of antibody specificity. In addition, the use of tissue where a knockout of

the gene has been engineered can be used to argue specificity

of the primary antibody. It must also be noted that there is an

increasing provision of commercial recombinant cell lines on

the market with either ectopic overexpression of specific proteins

(e.g. from Origene Technologies Inc.) or knockouts in cell

lines (e.g. Horizon Discovery Ltd.).

Many other techniques available through antibody suppliers

can be carried out on tissue to test for antibody specificity.

Isotope controls can be used to control for cross-reactivity.

This method ensures that the staining observed is not a result

of immunoglobulins binding non-specifically to Fc receptors

present on the cell surface. However, the method does not

prove that the antibody is binding to the target antigen.

Synthetic peptides towards which the commercial antibodies

were generated can be used in competitive assays,

where antiserumis incubated with the synthetic peptide prior

to staining. If the staining component of the antiserum is

raised against that antigen, the antibodies should adsorb to

the peptide and little or no staining should be observed

(Saper, 2005). However, although this is an acceptable assay

for validation of polyclonal antibodies, the technique cannot

be used for monoclonal antibodies as they will always be

adsorbed by their antigen, even if they are staining something

entirely different in the tissue (Saper, 2005). Furthermore,

even as a polyclonal antibody validation tool, it does not rule

out that other tissue proteins cross-react with the synthetic

peptide.

There does not exist an unflawed antibody validation method

for IHC, and each method has its own advantages and disadvantages.

In this section, we describe and discuss two alternative

recommended work-flows to follow in order to ensure an

antibody is of highest quality prior to use in IHC. One is

intended for IHC in high-throughput strategies, such as the

Human Protein Atlas project (Figure 3), and one is suitable

for IHC in mainstream biomarker development applications,

particularly those intending clinical application (Figure 4).

Both approaches firstly involve the identification and selection

of an appropriate antibody, and searches of literature and

databases in order to fully understand the target protein and

identify positive and negative controls. In the case of well

characterized differentially expressed genes, IHC staining on

cell lines or tissues known to express or not express the target

protein is a relatively inexpensive, fast and an easily assessed

method. Ideally, the validation should be complemented by

Western blotting of the corresponding cell or tissue lysates.

Previous experiments suggest, however, that a large fraction

of all proteins are expressed in a house-keeping manner

(Fagerberg et al., 2013; Ponten et al., 2009). For such ubiquitously

expressed proteins, this validation strategy has

limitations as to lack of negative controls, as almost any antibody

could render a ubiquitous staining pattern in IHC

depending on the antibody concentration used. In addition,

many proteins are largely uncharacterized and a more thorough

investigation needs to be performed in order to ensure

the antibody binds to its intended target.

The recommended antibody validation techniques to

consider next largely rely on the cost and time that can be

spent for thorough validation, and the laboratory’s access to

tissues and certain equipment. Moreover, it needs to be taken

into consideration that the desired level of accuracy and specificity

versus sensitivity may differ depending on the aim of

the study. A biomarker intended to be used for labelling of

beta cells in pancreas may only require absent staining in

other cells of islet of Langerhans and abdominal organs adjacent

to pancreas, while unspecific antibody binding in other

tissues does not interfere with the result (Lindskog et al.,

2012). In contrast, a potential diagnostic marker with the

aim to accurately determine the origin of a metastasis tumour

needs a higher level of specificity, in order to set the correct

diagnosis (Gremel et al., 2014). The strategies also differ between

validation of antibodies in high-throughput projects

and antibodies intended to be used in biomarker assays.

One example of a high-throughput IHC initiative is the Human

Protein Atlas project, which systematically explores the

human proteome using in-house generated affinity purified

polyclonal antibodies on TMAs (Kampf et al., 2012; Uhlen

et al., 2005). The TMAs contain samples from 44 different

normal tissues, the 20 most common cancer types, 46 cell

lines and six samples of primary cells. The current publically

available version of the online atlas (www.proteinatlas.org)

covers 16,621 human genes, represented by data from 21,984

antibodies, and thus serves as a valuable resource in

biomarker discovery (Asplund and Edqvist, 2012; Ponten

et al., 2011). The Human Protein Atlas utilizes paired antibodies

and comparison with mRNA data, which in conjunction

with IHC staining on test TMAs and Western blotting

suggest a high level of antibody reliability. In challenging

cases where the obtained results are contradictive or indecisive,

thorough investigation with other methods such as

PLA, knockdown models, in situ hybridization or mass spectrometry

could add potential value in determining an antibody’s

specificity. A flow-chart recommended for such highthroughput

projects is displayed in Figure 3.

In oncology drug research and development, where researchers

seek to introduce drugs targeted to molecular pathways

and reduce development timelines, there is an

increasing demand for specific and sensitive cancer tissuebased

IHC biomarkers (Smith and Womack, 2014). The two

most critical elements of a successful IHC assay are reliable

antibodies and tissue sample integrity, and a failure to validate

these elements sufficiently will lead to conflicting, irreproducible

results (Smith and Womack, 2014). Therefore, we

propose a strict but appropriate IHC workflow that should be

adhered to for research and development of potential biomarkers

(Figure 4). In this workflow, inclusion of definite positive

and negative FFPE controls is imperative in every IHC run

where antibody specificity can be verified as well as controlling

for additional run variations. These controls may be in

the form of either cell or tissue controls. Moreover, the use

of automated systems is recommended to limit errors due to

technical and laboratory variability.

IHC is an invaluable validation tool in biomarker discovery.

However, considering the excessive number of existing

studies proposing novel IHC biomarkers, markers validated

in several clinical cohorts are extremely few, stressing the

need to raise quality standards for clinical biomarker studies.

Even if results can be reproduced, the transition towards a

routinely used marker is complex. For a new factor to become

of potential value in the clinic, it has to add an important value

compared with other already used factors. Moreover, it also

has to be taken into account in which patient material the factor

was analysed and if it fits with the population where it

potentially will be used. To be able to perform and reproduce

a multitude of studies for the same marker, a specific antibody

and standardized antibody validation workflow is crucial. We

agree with the proposal recently made by (Howat et al., 2014),

suggesting that the antibody conditions should be published

on an open access site following publication in order to keep

the knowledge already gained by research groups. This would

aid in protocol optimization, minimize waste of valuable patient

material and improve the quality of publications.

In this review, we described and discussed methods available

for the validation of antibodies prior to usage in IHC, as

well as numerous factors in the IHC procedure that can potentially

influence the end result. In addition, we provide strict

criteria that should be adhered for the pragmatic validation

of antibodies for use in both high-throughput, systematic investigations

and mainstream biomarker discovery-oriented

immunohistochemical assays.