A 6-Antibody Panel for the Classification of Lung Adenocarcinoma Versus Squamous Cell Carcinoma

Abstract

Non-small cell lung cancer can be classified into several histologic subtypes, most commonly lung adenocarcinoma (LADC) or squamous cell carcinoma (SqCC). With the introduction of targeted therapies that can result in dramatically different outcomes based on subtype, the importance of accurate classification has been amplified. Six antibodies (Napsin A, Desmoglein 3, TTF-1, CK5, p63, and tripartite motif-containing 29) were selected for evaluation on cases of LADC of lung SqCC. Guided by the sensitivities and specificities determined for individual antibodies, a protocol was developed using a sequential series of 2-antibody cocktails that resulted in the classification of 93% of cases with 100% specificity. Importantly, the initial step in this method, a napsin A+Desmoglein 3 antibody cocktail classified >85% of cases, resulting in <15% of cases requiring further evaluation beyond a single test. Two new antibodies specifically developed and optimized for the diagnosis of LADC and lung SqCC, a rabbit polyclonal Napsin A and a mouse monoclonal Desmoglein 3 [BC11], were the key elements of the antibody panel. Most importantly, the described protocol uses routine interpretation methods and an uncomplicated algorithm for classification. Given the increased difficulty of diagnosing poorly differentiated tumors, the ability of this 6-antibody panel to classify 96% and 87% of moderately and poorly differentiated cases, respectively, is of particular value, especially when limited tissue for molecular testing is an issue.

Full text

A 6-Antibody Panel for the Classification of Lung
Adenocarcinoma Versus Squamous Cell Carcinoma
David Tacha, PhD,* Charie Yu, MD,* Ryan Bremer, PhD,* Weiman Qi, PhD,*
and Thomas Haas, DO
w
Abstract: Non-small cell lung cancer can be classified into sev-
eral histologic subtypes, most commonly lung adenocarcinoma
(LADC) or squamous cell carcinoma (SqCC). With the in-
troduction of targeted therapies that can result in dramatically
different outcomes based on subtype, the importance of accurate
classification has been amplified. Six antibodies (Napsin A,
Desmoglein 3, TTF-1, CK5, p63, and tripartite motif-containing
29) were selected for evaluation on cases of LADC of lung
SqCC. Guided by the sensitivities and specificities determined
for individual antibodies, a protocol was developed using a se-
quential series of 2-antibody cocktails that resulted in the clas-
sification of 93% of cases with 100% specificity. Importantly,
the initial step in this method, a napsin A+Desmoglein 3 anti-
body cocktail classified >85% of cases, resulting in <15% of
cases requiring further evaluation beyond a single test. Two new
antibodies specifically developed and optimized for the diag-
nosis of LADC and lung SqCC, a rabbit polyclonal Napsin A
and a mouse monoclonal Desmoglein 3 [BC11], were the key
elements of the antibody panel. Most importantly, the described
protocol uses routine interpretation methods and an un-
complicated algorithm for classification. Given the increased
difficulty of diagnosing poorly differentiated tumors, the ability
of this 6-antibody panel to classify 96% and 87% of moderately
and poorly differentiated cases, respectively, is of particular
value, especially when limited tissue for molecular testing is
an issue.
Key Words: lung adenocarcinoma, lung squamous cell carcino-
ma, Napsin A, Desmoglein 3, TRIM29
(Appl Immunohistochem Mol Morphol 2012;20:201–207)
Lung cancer is the leading cause of cancer deaths among
both men and women. More people die of lung cancer
than of colon, breast, and prostate cancers combined.
1
Non-small cell lung carcinoma (NSCLC) comprises ap-
proximately 80% of lung cancers and can be classified
into several histologic types, most commonly adeno-
carcinoma or squamous cell carcinoma (SqCC). Classi-
fication of lung carcinomas into histologic types is
typically carried out by morphologic examination using
hematoxylin and eosin or immunohistochemistry, and in
some cases, mucin stains.
2–5
However, an accurate clas-
sification can be difficult with poorly differentiated lung
carcinoma. Diagnosis can be further complicated by the
use of core needle biopsies, which provide limited
amounts of tissue for both immunohistochemistry and
molecular testing, and may include crush artifacts. Many
lung tumors are unresectable at diagnosis, thus requiring
accurate chemotherapy and/or targeted radioteherapy.
Although the majority of lung cancers (particularly
grades I and II) can be diagnosed with only hematoxylin
and eosin staining, diagnostic parameters have changed
and a more detailed approach to diagnosis has emerged.
Furthermore, the availability of targeted therapies has
created a need for accurate subtyping of NSCLC. The
current Food and Drug Administration-approved stand-
ard of treatment for NSCLC is carboplastin/taxol/avas-
tin; however, patients with lung SqCC should not receive
avastin due to a 30% mortality rate by fatal pulmonary
hemorrhage.
5–7
Historically, the antibodies TTF-1 and
p63 have often been used to differentiate primary adeno-
carcinoma from SqCC of the lung.
8–13
Recently, a panel
of TTF-1, p63, Napsin A, and CK5/6 was used to classify
77% of poorly differentiated cases of NSCLC; however,
23% of the cases remained unclassified.
2
Similarly, a 5-
antibody panel that included CK5/6, tripartite motif-
containing 29 (TRIM29), LAT-1, CEACAM5, and
MUC1 used a weighted mathematical formula to classify
85% of lung adenocarcinoma (LADC) cases and 88% of
lung SqCC cases, respectively, while leaving 12.8% of the
cases unclassified.
5
Two new antibodies, TRIM29 and
Desmoglein 3 (DSG3), have also emerged as potential
markers for SqCC lung cancer; however, only limited
studies of these antibodies have been reported.
5,14,15
With
the more stringent requirements for histologic classi-
fication of lung cancers, the need for a panel of antibodies
that easily and definitively differentiates LADC from
lung SqCC is of utmost importance.
In a pilot study, 15 antibodies were evaluated for
their sensitivity and specificity for LADC and lung SqCC,
Received for publication September 6, 2011; accepted October 17, 2011.
From the *Biocare Medical, Concord, CA; and wMercy Health System,
Janesville, WI.
D. Tacha, C. Yu, R. Bremer and W. Qi are employees of Biocare
Medical. T. Haas is a consultant to Biocare Medical.
Reprints: David Tacha, PhD, Biocare Medical, 4040 Pike Lane, Con-
cord, CA 94520 (e-mail: dtacha@biocare.net).
Supplemental Digital Content is available for this article. Direct URL
citations appear in the printed text and are provided in the HTML
and PDF versions of this article on the journal’s Website, www.
appliedimmunohist.com.
Copyright r2011 by Lippincott Williams & Wilkins
RESEARCH ARTICLE
Appl Immunohistochem Mol Morphol Volume 20, Number 3, May 2012 www.appliedimmunohist.com |201

using an immunohistochemical (IHC) method (Supple-
mentary Table 1; Supplemental Digital Content-1 http://
links.lww.com/AIMM/A17).
16
As part of this study, a
Napsin A rabbit polyclonal antibody and DSG3 [clone
BC11] mouse monoclonal antibody were generated and
optimized with special emphasis for their utility for lung
cancer diagnosis. On the basis of sensitivity and specificity
determined in the pilot study, 6 antibodies (TTF-1,
Napsin A, p63, TRIM29, DSG3, and CK5) were selected
for further evaluation on 210 various lung cancer cases.
17
Lung cancer classification was divided by phenotype
(adenocarcinoma vs. SqCC), and in each group that had
previously been diagnosed as well, moderately, or poorly
differentiated grades I, II, and III were assigned, res-
pectively. Analysis of the staining percentages for each
antibody facilitated the development of an algorithm that
can be used to classify >93% of cases as LADC
or SqCC.
MATERIALS AND METHODS
Formalin-fixed, paraffin-embedded tissue micro-
arrays (TMAs) of various lung cancer cases were proc-
essed in the usual manner for IHC analysis. TMA core
tissues (US Biomax) were randomly selected from pre-
viously diagnosed material and patient data included age
sex, tumor grade, and staging. The cases evaluated in-
cluded 156 men with an average age of 60 years and 54
women with an average age of 58 years. All tissue sections
were retrieved in a modified citrate buffer (DIVA, Biocare
Medical) in a pressure cooker (Decloaking Chamber,
Biocare Medical) at 1251C. Staining of TTF-1 [8G7G3/1],
Napsin A (P), p63 [4A4], TRIM29 (P), DSG3 [BC11], and
CK5 [EP1601Y] (Biocare Medical) was optimized with
custom diluents, based on sensitivity and specificity
(Supplementary Table 2; Supplemental Digital Content-2
http://links.lww.com/AIMM/A18). Antibodies and/or
antibody cocktails were evaluated on 95 cases of lung
SqCC and 115 cases of LADC. Detection was achieved
using a micropolymer detection system conjugated to
horseradish peroxidase or alkaline phosphatase (MACH
2, Biocare Medical) and visualized with DAB and/or Fast
Red, respectively.
Scoring Method for Interpretation
Scoring and interpretation methods were developed
based on those previously reported by Mukhopadhyay and
Katzenstein
2,5
and Ring et al.
5
For each antibody, cases
were considered positive if 10% or more tumor cells were
stained. Cases with <10% staining and no focal areas of
positive staining were scored as negative. Cases that were
mostly negative, but contained small areas of tumor cells in
which almost all tumor cells were positive were classified as
focally positive. If cases were stained with either TTF-1,
p63, or TRIM29 and all other antibodies in the 6-antibody
panel were negative, > 50% or strong diffuse staining was
required for classification. Two investigators independently
graded 33 cases of LADC and 42 cases of lung SqCC
according to these criteria. There was a 100% concordance
in their interpretations, thus indicating the reproducibility
of the scoring method.
Preparation of Mouse Monoclonal Antibody to
DSG3 [BC11]
DSG3 mouse monoclonal antibody was raised against
a recombinant protein expressed in Escherichia coli. Sple-
nocytes from BALB/c mice immunized with recombinant
DSG3 were fused with P3x/63Ag8.653 myeloma cells to
produce hybridomas. Tissue culture supernatant was
screened for anti- DSG3 activity by enzyme-linked im-
munosorbent assay, using recombinant DSG3 as antigen.
Hybridomas-producing high-affinity antibodies were subcl-
oned by limiting dilution. An IgG1 clone, designated as
BC11, was selected and further characterized by im-
munohistochemistry.
Preparation of Rabbit Polyclonal Antibody to
Napsin A
Peptides corresponding to the N-terminus of Nap-
sin A were synthesized and conjugated to keyhole limpet
haemocyanin (CalBiochem, La Jolla, CA). New Zealand
white rabbits were immunized subcutaneously with
0.2-mg immunoconjugates in PBS. After the initial im-
munization, animals were boosted 5 more times every 21
days in the same manner. The titers of the sera were
evaluated by enzyme-linked immunosorbent assay on
Napsin A peptide-coated plates. When the titer reached
1:10,000, the sera were purified by affinity column against
immunized peptides, conjugated with goat IgG. The
purified antibody was evaluated further by immuno-
histochemistry.
RESULTS
Napsin A, a novel aspartic proteinase, is a marker
that has been frequently described in the literature over
the last 10 years, but only recently has it come into its
own as an important marker in the clinical setting.
Studies have shown that Napsin A is a very specific
marker for LADC and is superior to TTF-1 and the
surfactant apoprotein
18–20
With the intent of developing a
rabbit Napsin A polyclonal antibody optimized for lung
cancer diagnosis, a rabbit polyclonal antibody was gen-
erated inhouse based on positive staining for LADCs and
negative staining for lung SqCC. A side-by-side compar-
ison of the inhouse rabbit Napsin A polyclonal antibody
with a mouse Napsin A monoclonal antibody [TMU-Ad
02], and with a commercially available rabbit Napsin A
polyclonal antibody was done on various lung cancers
and normal and neoplastic tissues (data not shown). The
inhouse rabbit Napsin A polyclonal antibody and the
mouse Napsin A mouse monoclonal antibody were 88%
sensitive and 100% specific and 84% sensitive and 100%
specific for LADC, respectively (data not shown). When
compared with the commercially available rabbit Napsin
A polyclonal antibody, the inhouse rabbit Napsin A
polyclonal antibody provided equal sensitivity, sharper
staining, and was more specific in that it was negative for
colon cancers (data not shown). Most importantly, the
Tacha et al Appl Immunohistochem Mol Morphol Volume 20, Number 3, May 2012
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inhouse rabbit Napsin A polyclonal antibody facilitates
its combination with mouse DSG3 in an antibody cock-
tail for multiplex staining.
The inhouse generated monoclonal antibody DSG3
[BC11] was evaluated on TMAs of LADC and lung
SqCC. A high percentage of lung SqCC were positive and
all LADC s were negative (data not shown).
Subsequent to the pilot study of 15 antibodies pre-
viously reported to have utility in lung cancer classi-
fication, 6 antibodies were selected for further evaluation
based on their sensitivities and specificities and their po-
tential for definitive classification of the greatest number
of LADC and lung SqCC cases, when used in combina-
tion: Napsin A, DSG3, TTF-1, CK5, p63, and TRIM29.
The 6-antibody panel was evaluated for sensitivity
and specificity on 95 cases of SqCC and 115 cases of
LADC. The results for each individual antibody are
summarized in Table 1. However, the greatest utility of
this antibody panel is observed when combinations of
antibodies are used. For example, Napsin A provided
87% sensitivity and 100% specificity for LADC, whereas
TTF-1 provided 69% sensitivity and 94.7% specificity for
LADC. Together, these 2 antibodies (positive staining
with Napsin A and/or TTF-1) provided increased sensi-
tivity for LADC (91.3%) and 100% specificity, when
both Napsin A and TTF-1 were positive, or either were
positive and 2 or more squamous cell markers were neg-
ative (Table 2).
Similarly, the combination of DSG3 and CK5 is
particularly valuable for the identification of lung SqCC.
Although DSG3 and CK5 are both 100% specific for
SqCC, they have sensitivities of 85.3% and 86.4%, re-
spectively, when used individually. When evaluated in
combination (positive staining for either antibody), sen-
sitivity for lung SqCC is increased to 92.6% and 100%
specificity is maintained (Table 2). Finally, when used
together, p63 and TRIM29 provided 94.7% sensitivity
and 89.5% specificity for SqCC, which increased to 100%
specificity in cases in which both TTF-1 and Napsin A
were negative (Table 2).
The above-described combinations of antibodies
specific for either LADC or lung SqCC clearly offer en-
hanced sensitivity and specificity over using the antibodies
individually. A potentially more valuable application of
the 6-antibody panel was identified using pairs of anti-
bodies, wherein one of the antibodies is specific for
LADC and the other for lung SqCC. Using this ap-
proach, an algorithm was developed based on the suc-
cessive evaluation of antibody pairs that ultimately led to
the classification of >93% of cases, with 100% specificity
(Fig. 1).
An initial application of a Napsin A+DSG3 anti-
body cocktail allowed the classification of > 85% of
cases, with 100% specificity (Figs. 2, 3). Less than 15% of
cases required further evaluation. A subsequent applica-
tion of a CK5+TTF-1 antibody cocktail increased the
number of cases classified to 92%, while maintaining
strong specificity (Figs. 4, 5). Finally, a few additional
cases of lung SqCC can be classified by a p63+TRIM29
antibody cocktail (Fig. 6), raising the total number of
cases classified by the 6-antibody panel to > 93%.
In all cases of NSCLCs, 14 of 210 (6.7%) remained
unclassified by the 6-antibody panel (Table 4). Specifi-
cally, nine of 115 (7.8%) LADC and 5 of 95 (5.3%) SqCC
cases were unclassified. Of note, 100% (29 of 29) of grade
I cases and 96% (133 of 138) of grade II cases were able to
be classified using this method. Although slightly lower,
87% (60 of 69) of grade III tumors were also successfully
classified using the 6-antibody panel (Table 3).
DISCUSSION
In selecting antibodies from the pilot study for a
detailed evaluation, particular attention was paid to
identifying those with the greatest specificity. Of partic-
ular note in the initial screening, HMW cytokeratin
[34betaE12] and CK7 both stained a high percentage of
lung SqCC and LADCs, respectively; however, both
provided poor specificity. MUC1 and CEACAM5 offered
various sensitivities for both LADC and lung SqCC.
However, both lack specificity for lung carcinomas, as
they have been found to also stain a high percentage of
nonpulmonary tissues.
21,22
Of the antibodies selected for a detailed evaluation,
TTF-1, Napsin A, and p63, or combinations thereof, have
been well described in the literature and are in routine use
by many histopathology laboratories.
2,3,6,16,17
CK5 was
selected for the panel over CK5/6 based on its superior
specificity. Two new antibodies with relatively limited
reports in the literature, DSG3 and TRIM29, were also
included in the 6-antibody panel.
To date, 3 desmoglein subfamily members have
been identified and all are members of the cadherin cell
adhesion molecule superfamily.
14
DSG3 is a calcium-
binding transmembrane glycoprotein component of des-
mosomes in vertebrate epithelial cells. Microarray data
have shown that DSG3 had a sensitivity and specificity of
88% and 98%, respectively, in detecting SqCC versus
adenocarcinoma.
15
However, only grades I to II lung
cancers were evaluated in this study. Positive IHC stain-
ing with DSG3 has also been associated with longer
survival for all lung cancer patients regardless of their
TABLE 1. Six-Antibody Panel
Antibodies TTF-1 Napsin A p63 TRIM 29 DSG-3 CK5
Lung ADC 80/115 (70.0%) 99/115 (86.0%) 13/115 (11.3%) 8/115 (7.0%) 0/115 (0%) 0/115 (0%)
Lung SqCC 5/95 (5.3%) 0/95 (0%) 84/95 (88.4%) 89/95 (93.7%) 82/95 (85.3%) 83/95 (87.4%)
ADC indicates adenocarcinoma; SqCC, squamous cell carcinoma.
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histologic subtypes (5-year survival of 49.5% vs.
20.9%).
16
Therefore, the expression of DSG3 is not only a
specific marker for lung SqCC, but has potential
prognostic value.
TRIM29, a member of the TRIM protein family, is
a putative transcriptional regulatory factor involved in
carcinogenesis and/or differentiation.
5
High expression of
TRIM29 has been reported in gastric cancer and pan-
creatic cancer, correlating with enhanced tumor growth
and lymph node metastasis.
23,24
TRIM29 was previously
used in a panel with four other antibodies for the classi-
fication of LADC versus lung SqCC; however, no data
were provided for the sensitivity or specificity of the in-
dividual antibodies in the study.
5
A rabbit monoclonal CK5 antibody was selected for
the antibody panel over the mouse monoclonal CK5/6
antibody, based on the greater specificity of CK5 for lung
SqCC. CK5 and CK5/6 showed 79% and 100% and 75%
and 100% sensitivity and specificity, respectively.
6,14
In
this study, the rabbit monoclonal CK5 achieved 87.4%
sensitivity and 100% specificity for lung SqCC. Other
studies have shown that CK5/6 lacked absolute specificity
TABLE 2. Antibody Combinations Specific for Lung Adenocarcinoma or Squamous Cell Carcinoma
Napsin A+TTF-1 (LADC) DSG3+CK5 (SqCC) TRIM29+p63 (SqCC)
Expression of either or both antigens 105/115 88/95 90/95
Coexpression of both antigens 80/115 (73%) 80/95 (84.3%) 84/95 (88.4%)
Sensitivity 91.3% 92.6% 94.7%
Specificity 94.7%* 100% 88.7%w
Unclassified 8.7% 7.4% 5.3%
*100% specific when Napsin A and TTF-1 are both positive or DSG3 and CK5 are negative.
w100% specific when Napsin A and TTF-1 are both negative.
LADC indicates lung adenocarcinoma; SqCC, squamous cell carcinoma.
Desmoglein 3 + Napsin A
Add CK5 + TTF-1
Add p63 + TRIM29
DSG-3 +Napsin A -
85.3% sensitive
100% specific
CK5 +TTF-1 -
DSG-3 -Napsin A -
SqCC
92.6% sensitive
100% specific
p63 or TRIM29 +
CK5 -TTF-1 -
DSG-3 -Napsin A -
SqCC
94.7% sensitive
100% specific
CK5 -TTF-1 +
DSG-3 -Napsin A -
LADC
91.3% sensitive
100% specific
p63 -TRIM29 -
CK5 -TTF-1 -
DSG-3 -Napsin A -
195/210 (92.9%) classified
18/210 (7.1%) unclassified
DSG-3 -Napsin A +
86.0% sensitive
100% specific
DSG-3 -Napsin A -
DSG-3 -Napsin A -
CK5 -TTF-1 -
SqCC
SqCC
LADC
LADC
182/210 (87%) classified
28/210 (13%) unclassified
193/210 (92%) classified
17/210 (8%) unclassified
FIGURE 1. An algorithm for the classification of lung adenocarcinoma and lung squamous cell carcinoma using sequential
application of 3-antibody cocktails (DSG3+Napsin A, CK5+TTF-1, p63+TRIM29).
Tacha et al Appl Immunohistochem Mol Morphol Volume 20, Number 3, May 2012
204 |www.appliedimmunohist.com r2011 Lippincott Williams & Wilkins

for SqCC and stained LADCs.
3,6,25,26
Furthermore, ex-
amination of mRNA expression of CK5, CK6, p63, and
DSG3 in adenocarcinoma and SqCC of the lung found
that CK5 and CK6 produced the highest sensitivity for
SqCC, but also detected a moderate to high expression of
an isoform of CK6 (CK6B) in 16 of 57 adenocarcinomas
(28%), showing that CK5 expression is more specific for
SqCC.
14
In this same study, the expression of p63 was
high in most SqCC cases, but p63 was also identified in 10
of 57 (18%) adenocarcinomas. In contrast, DSG3 was
found to be more specific, with high expression in 88% of
SqCC cases, compared with only on1 in 57 (<2%) of
adenocarcinomas with detectable levels of DSG3.
The most valuable application of the 6-antibody
panel is clearly the successive application of antibody
cocktails in a stepwise manner for the classification of
FIGURE 2. Lung adenocarcinoma stained with DSG3
(DAB)+Napsin A (Fast Red).
FIGURE 3. Lung squamous cell carcinoma stained with DSG3
(DAB)+Napsin A (Fast Red).
FIGURE 4. Lung adenocarcinoma stained with CK5 (Fast
Red)+TTF-1 (DAB).
FIGURE 5. Lung squamous cell carcinoma stained with CK5
(Fast Red)+TTF-1 (DAB).
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LADC or lung SqCC (Fig. 1). The proposed algorithm
offers a simple and straightforward method for inter-
pretation at each step. In developing such an algorithm,
specificity is preferred over sensitivity in the first step, so
as to ensure an unambiguous classification and avoid the
need for further testing, even at the expense of leaving
some cases initially unclassified. For this reason, the use
of Napsin A and DSG3 as the first antibody pair is a key
feature of the algorithm. The 100% specificities of these
two antibodies allow for definitive classification of
>85% of cases with this single antibody cocktail. Pro-
ceeding through the subsequent steps of the algorithm,
antibodies of greater sensitivity are used, so as to increase
the number of cases classified. CK5 and TTF-1 were se-
lected for the second antibody cocktail due to the in-
creased sensitivity of both. Using CK5+TTF-1 increased
the number of SqCC and LADC cases classified by 7%
and 5%, respectively. Thus, with just 2 antibody cock-
tails, 92% of cases were classified. Most importantly,
although as each successive tier adds diagnostic infor-
mation to that already determined, 100% specificity can
be maintained. For example, although TTF-1 is 94.7%
specific alone (Table 1), it is 100% specific when DSG3
and CK5 are both negative (Table 2), precisely the sce-
nario that would occur when applying the antibody
cocktails in the sequence described here. Finally, the most
sensitive antibody in the panel, TRIM29 (94.7%), com-
bined with p63, was found to identify additional cases of
SqCC (1%) not previously marked with DSG3 or CK5,
supporting their inclusion as a final antibody cocktail to
maximize the potential for classification. Again, due to
the fact that TRIM29+p63 is 100% specific when Napsin
A and TTF-1 are both negative (Table 2), 100% specif-
icity can be maintained, as a Napsin A negative/TTF-1
negative scenario is implied anytime one arrives at the
TRIM29+p63 cocktail in the algorithm.
As tumor grade increases, diagnosis may become
more difficult; in these cases, a more extensive panel, such
as that described in this study should be considered. The
6-antibody panel proved highly effective in classifying
grade I and II lung cancers (100% and 95.5% of cases
classified, respectively). Although grade III lung cancers
seem to be more difficult to classify, 85.7% were suc-
cessfully classified using this panel. When evaluating the
utility of an antibody panel for LADC versus SqCC
classification, the ability to classify less differentiated,
higher grade tumors is a critical feature.
In a study similar to that reported here, investigators
used a 5-antibody panel that included CK5/6, TRIM29,
LAT-1, CEACAM5, and MUC1 for the classification of
LADC and SqCC.
5
Using a weighted mathematical for-
mula based on scoring results, this panel of antibodies
achieved 85% and 88% classification for LADC and lung
SqCC, respectively, while leaving 12.8% of the total
number of cases unclassified (Table 4). In contrast, using a
routine interpretation familiar to all pathologists, the 6-
antibody panel reported here provided 91.3% and 94.7%
classification for LADC and lung SqCC, respectively, re-
sulting in fewer unclassified cases (7.1%).
The high percentage of classification achieved with
this 6-antibody panel compared with those previously
reported may be attributable to several major factors,
including the high specificity of DSG3 and sensitivity of
TRIM29; the development of a rabbit polyclonal Napsin
A specifically for lung diagnosis; and a highly sensitive
detection method that included the use of a pressure de-
vice and a modified citrate buffer formulation (DIVA).
Furthermore, the titer of each antibody was optimized in
custom diluents, thus providing increased specificity
(Supplementary Table 2). Careful selection of antibodies
with complementary sensitivities and specificities best
suited for definitive classification of the greatest number
of cases, in combination with retrieval and detection
protocols that optimize staining sensitivities, provides a
superior method for the classification of LADC and
lung SqCC.
The 6 antibodies selected from the pilot study based
on their sensitivities and specificities form a useful panel
for the classification of LADC and SqCC. Antibodies to
Napsin A and DSG3 specifically produced and optimized
for lung cancer diagnosis form the foundation of the
panel. Using the 6 antibodies in cocktails of 6 antibodies
(one specific for LADC and the other for lung SqCC) in a
straightforward algorithm based on routine interpretation
FIGURE 6. Lung squamous cell carcinoma stained with p63
(DAB)+TRIM29 (Fast Red).
TABLE 3. Tumor Grade Correlation
Grades No. Cases Percent Classified Percent Unclassified
I-III 210 (%) 195/210 (92.9%) 15/210 (7.1%)
I 29 (14%) 29/29 (100%) 0/29 (0%)
II 109 (52%) 104/110 (94.5%) 6/110 (5.5%)
III 69 (33%) 60/70 (85.7%) 10/70 (14.3%)
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provides a convenient method for definitive classification
of LADC and SqCC. Using antibody cocktails with the
proposed algorithm offers the additional advantage that
when challenged by limited tissues, a high majority of
lung cancer cases can be classified using only 1 or 2 slides.
To the best of our knowledge, this staining panel pro-
vided the highest sensitivity and specificity than that has
been previously reported.
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TABLE 4. Classification Using the 6-Antibody Panel Compared With the Antibody Panel of Reference
5
Percent Classified Percent Unclassified
Lung Carcinoma Six-Antibody Panel Reference 5 Six-Antibody Panel Reference 5
Adenocarcinoma 91.3% 85.4% 8.7% 14.6%
SqCC 94.7% 88.8% 5.3% 11.2%
Cases ± adenocarcinoma/SqCC 92.9% 87.2% 7.1% 12.8%
SqCC indicates squamous cell carcinoma.
Appl Immunohistochem Mol Morphol Volume 20, Number 3, May 2012 Lung Adenocarcinoma vs. Squamous Cell Carcinoma
r2011 Lippincott Williams & Wilkins www.appliedimmunohist.com |207