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ORIGINAL ARTICLE
Nodal metastasis and survival in oral cancer: Association with protein expression
of SLPI, not with LCN2, TACSTD2, or THBS2
Rob Noorlag, MD,1 * Petra van der Groep, PhD,2,3 Frank K. J. Leusink, MD,1 Sander R. van Hooff, MSc,4 Micha€el H. Frank, DDS, MD,1
Stefan M. Willems, MD, PhD,2 Robert J. J. van Es, DDS, MD, PhD1
1
Department of Oral and Maxillofacial Surgery, University Medical Center Utrecht, Utrecht, The Netherlands, 2Department of Internal Medicine and Dermatology, University Medical
Center Utrecht, Utrecht, The Netherlands, 3Department of Pathology, University Medical Center Utrecht, Utrecht, The Netherlands, 4Department of Molecular Cancer Research,
University Medical Center Utrecht, Utrecht, The Netherlands.
Accepted 21 April 2014
Published online 19 July 2014 in Wiley Online Library (wileyonlinelibrary.com). DOI 10.1002/hed.23716
ABSTRACT: Background. Gene expression profiling revealed a strong
signature predicting lymph node metastases in oral squamous cell carcinoma (OSCC). Four of the most predictive genes are secretory leukocyte
protease inhibitor (SLPI), lipocalin-2 (LCN2), thrombospondin-2 (THBS2),
and tumor-associated calcium signal transducer 2 (TACSTD2). This
study correlates their protein expression with lymph node metastases,
overall survival (OS), and disease-specific survival (DSS).
Methods. Two hundred twelve patients with OSCC were included for protein expression analysis by immunohistochemistry.
Results. SLPI expression correlates with lymph node metastases in the
whole cohort, not in a subgroup of cT1 to 2N0. SLPI expression corre-
INTRODUCTION
Head and neck cancer is the sixth most common malignancy
worldwide, of which one-third consists of oral squamous cell
carcinoma (OSCC). Its incidence in The Netherlands, being
6.2 per 100 000 in 2010, is rising annually. Despite improvements in therapy, the 5-year survival rate has not changed
over the past decades and remains approximately 50%.1–3
The prognosis depends on numerous clinical and pathological
factors, of which cervical lymph node metastases is a major
determinant.4 To perform appropriate treatment, it is therefore pivotal to determine the nodal status of the neck. However, in 30% to 40% of the patients, even optimal imaging
is unable to detect nodal disease.5
To improve the negative predictive value for metastasis
detection in OSCC, new diagnostic tools, such as molecular
diagnosis and tumor profiling, have been developed.5 Roepman et al6 showed that microarray gene expression profiling
could be used to predict lymph node metastases for OSCC.
*Corresponding author: R. Noorlag, Department of Oral and Maxillofacial Surgery, University Medical Center Utrecht, G05.222, Heidelberglaan 100, 3584
CX Utrecht, The Netherlands. E-mail: [email protected]
Contract grant sponsor: Stefan M. Willems was funded by the Dutch Cancer
Society (clinical fellowship: 2011-4964).
Additional Supporting Information may be found in the online version of this
article.
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lates with OS (hazard ratio [HR] 5 0.61) and DSS (HR 5 0.47) in multivariate analysis. LCN2, THBS2, and TACSTD2 show no correlation with
lymph node metastases, OS, or DSS.
Conclusion. Although SLPI expression correlates with lymph node metastases, it has no additional value in determining lymph node metastases
in early oral cancer. However, it is an independent predictor for both OS
C 2014
and DSS and therefore a relevant prognostic biomarker in OSCC. V
Wiley Periodicals, Inc. Head Neck 37: 1130–1136, 2015
KEY WORDS: oral cancer, secretory leukocyte protease inhibitor
(SLPI), immunohistochemistry, lymph node metastases, survival
Recently, this gene expression signature has been validated
in a multicenter study and focused on the prediction of
lymph node metastases in early oral cancer.7 Four of the
strongest predictive genes in this signature encode for the
proteins lipocalin-2 (LCN2), thrombospondin-2 (THBS2),
tumor-associated calcium signal transducer 2 (TACSTD2),
and secretory leukocyte protease inhibitor (SLPI).
LCN2 participates in carcinogenesis by favoring iron
uptake from the extracellular space within the tumor cell,
a fundamental process for maintaining neoplastic cell
multiplication. Although increased LCN2 plasma levels in
patients with OSCC were found, no correlation was established with regional or distant metastases.8
THBS2 suppresses angiogenesis by inhibiting endothelial cell migration, inducing endothelial cell apoptosis and
preventing the interaction of growth factors with the cell
surface receptors of the endothelial cell.9 In supraglottic
cancer, THBS2 gene expression seems inversely correlated with nodal metastases.10
TACSDT2, also known as TROP-2, belongs to a unique
family of transmembrane glycoproteins that has a regulatory role in cell-cell adhesion and has a key controlling
role in human cancer growth. Tumor development is
quantitatively driven by TACSTD2 expression levels in
many tumors.11 Fong et al12 correlated increased
TACSTD2 expression in OSCC with decreased overall
survival (OS), but found no correlation with nodal
metastases.
SLPI
TABLE 1. Baseline characteristics.
Variables
Sex
Female
Male
Age at diagnosis, y
Median (range)
Smoking
Never
Ceased >1 y
Active smoker or ceased <1 y
Missing
Alcohol
Never
Occasionally
1–4 drinks/d
5 drinks/d
Missing
Clinical N classification
cN0
cN1–3
Clinical T classification
cT1
cT2
cT3
cT4
Pathological N classification
pN0
pN1–3
Pathological T classification
pT1
pT2
pT3
pT4
Infiltration depth
<4.0 mm
4.0 mm
Differentiation grade
Good/moderate
Poor/undifferentiated
Vasoinvasion
No
Yes
Missing
Bone invasion
No
Yes
Perineural growth
No
Yes
Missing
Invasive pattern
Cohesive
Noncohesive
Missing
Extracapsular spread
No
Yes
No nodal metastasis
High risk HPV status
Negative
Positive
Abbreviation: HPV, human papillomavirus
No. of patients (%)
84 (40)
128 (60)
61 (26–87)
43 (20)
34 (16)
133 (63)
2 (1)
46 (22)
49 (23)
71 (33)
44 (21)
2 (1)
146 (69)
66 (31)
44 (21)
79 (37)
19 (9)
70 (33)
97 (46)
115 (54)
44 (21)
73 (34)
22 (10)
73 (34)
19 (9)
193 (91)
173 (82)
39 (18)
39 (18)
169 (80)
4 (2)
152 (72)
60 (28)
122 (57)
80 (38)
10 (5)
44 (21)
167 (79)
1 (<1)
59 (28)
56 (26)
97 (46)
210 (99)
2 (1)
EXPRESSION, NODAL METASTASIS, AND SURVIVAL IN ORAL CANCER
SLPI, also known as antileukoproteinase, is a protease
inhibitor of neutrophil elastase, cathepsin G, chymotrypsin, and trypsin,13,14 enzymes with extracellular matrix
degradative properties, and associated with cancer development, invasiveness, and progression.15,16 SLPI expression has recently been associated with carcinogenesis and
metastasis in various types of cancer, although its role
remains controversial. In gastric and prostate cancer,
increased SLPI expression is associated with invasiveness,
metastases, and a worse survival.17–19 This is in contrast
with the reports of SLPI expression in ovarian cancer, in
which SLPI expression is associated with decreased tumor
growth and fewer nodal metastases.20 In head and neck
cancer, SLPI mRNA and protein levels seem to be
increased compared to normal tissue.21 Reports correlating SLPI expression with lymph node metastases are
contradicting.22,23
The purpose of this study was to present the correlation
of the aforementioned protein expressions with lymph
node metastases, OS, and disease specific survival (DSS),
and evaluate their potential role as biomarkers for treatment decision and predictors of survival in OSCC.
MATERIALS AND METHODS
Patient selection
Patients with histologically confirmed OSCC, whose
primary treatment was by surgery between 1996 and 2005
in our institute were included in this study. Patients who
had had a synchronous primary tumor or a previous
malignancy in the head and neck region were excluded.
Two hundred twelve patients were selected on the
availability of both representative formaldehyde-fixed,
paraffin-embedded tissue blocks and frozen tissue samples
of the primary tumor.
A dedicated head and neck pathologist examined all
hematoxylin-eosin stained slides with special attention to
the following pathological characteristics: type of tumor,
differentiation grade, infiltration depth, invasive pattern,
perineural growth, vasoinvasive growth, extracapsular
spread, and bone invasion.
A tissue microarray was made of the paraffinembedded tissue. For each tumor block, 3 central tissue
cylinders and 3 tissue cylinders at the tumor front with a
diameter of 0.6 mm were punched out, avoiding areas of
necrosis, and arrayed in a recipient paraffin block. Normal epithelium from the floor of the mouth, gingiva, and
tonsil was incorporated in each block to ensure similarity
of staining between the different blocks, as described
earlier.24
From each patient, clinical characteristics, clinical
TNM classification (based on palpation, ultrasoundguided fine-needle aspiration, MRI or CT, and classified
in a multidisciplinary panel), pathological TNM classification, and cause of death were retrieved from the medical records, as listed in Table 1.
Gene expression
For a subgroup of 83 tumors, normalized gene expression data were available from an earlier study for which
methods has been described in detail earlier.7 In short,
frozen tumor samples were sectioned, aliquoted in Trizol
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(Life Technologies, Frederick, MD), and sent to Agendia
Laboratories (Amsterdam, The Netherlands) for expression profile analysis. Tumor areas with a percentage of at
least 50% were assessed on hematoxylin-eosin stained
sections and taken in parallel; RNA was isolation and
amplification. Tumor sample RNA was labeled as Cy3,
and reference RNA was labeled Cy5. As a reference, the
Universal Human Reference RNA (Agilent Technologies,
Santa Clara, CA) was used. Samples were hybridized on
full-genome Agilent arrays. Raw fluorescence intensities
were quantified using Agilent Feature Extraction software
and imported into R/Bioconductor (http://www.bioconductor.org/) for normalization (loess normalization using the
LIMMA package) and additional analysis.
Human papillomavirus type 16 analysis
Human papillomavirus type 16 (HPV-16) active tumors
were determined by p16 immunohistochemistry (IHC) followed by GP 51/61 polymerase chain reaction in positive p16 staining, a reliable algorithm for detection of
HPV-16 in paraffin-embedded head and neck cancer
specimens, as described by Smeets et al.25
Immunohistochemistry
IHC was performed on 4-mm thick paraffin sections.
The tissue sections were deparaffinized with xylene and
rehydrated. Endogenous peroxidase activity was blocked
for 15 minutes in a 0.3% hydrogen peroxide phosphatecitrate buffer. Then, tissue sections were washed in water
and subsequently subjected to antigen retrieval by boiling
the slides in ethylenediaminetetraacetic acid buffer, pH
9.0 (SLPI) or citrate buffer, and pH 6.0 (TACSTD2,
LCN2, and THBS2) for 20 minutes. Sections were cooled
down within the buffers for 30 minutes. After washing
with phosphate-buffered saline (PBS) for 5 minutes, tissue
slides were incubated with the primary antibody SLPI
(clone 31; HyCult biotechnology, Uden, The Netherlands;
dilution 1:50), primary antibody TACSTD2 (AF650,
R&D Systems, Oxon, England; dilution 1:50), primary
antibody LCN2 (MAB1757; R&D Systems, Oxon, England; dilution 1:50), or primary antibody THBS2 (sc12313, Santa Cruz Biotechnology, Santa Cruz, CA; dilution 1:50) for 60 minutes. After washing with PBS (3
times), incubation with poly-HRP Goat anti-Mouse/Rabbit/Rat (Brightvision, Immunologic, Duiven, The Netherlands; ready to use) for 30 minutes was followed by
washing with PBS (3 times). Slides were then developed
with diaminobenzidine for 10 minutes, counterstained
with hematoxylin, followed by dehydration, and mounted.
Evaluation of immunohistochemical staining
A core was considered inadequate/lost when the core
contained <5% tumor tissue or when >95% of the core
contained no tissue. Patients were only included in the
study when one or more tumor cores were available.
When two or more cores were available from one patient,
the mean (SLPI, THBS2, or LCN2) or maximum
(TACSTD2) score was calculated for that patient.
The expression of SLPI and THBS2 in the primary
tumor was evaluated by scoring the percentage of cytoplasm staining. The percentage of cytoplasm stained was
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classified as 0 (<5%), 1 (5% to 30%), 2 (31% to 75%),
or 3 (>75%), see Figure 1.22,26 Expression of TACSTD2
was evaluated by scoring the staining intensity of the cell
membrane as 0 5 no, 1 5 weak, 2 5 moderate, or
3 5 strong staining. For LCN2 expression, both the intensity (0 5 no, 1 5 weak, 2 5 moderate, or 3 5 strong) and
percentage of cytoplasm staining was scored, multiplying
the intensity score with the percentage of staining classified as 1 (25%), 2 (26% to 50%), 3 (51% to 75%), or 4
(>75%) was used as a final score for LCN2 expression.
Scores 3 were interpreted as negative, and scores >3 as
positive.27 A dedicated head and neck pathologist (S.W.)
and a researcher (R.N.), both blinded to the clinical characteristics of the patients, evaluated the protein expressions independently. Consensus was reached regarding
discordant findings.
Statistical analysis
An interrater reliability analysis using the Spearman
(for continuous data) and Kappa (for categorical data) statistic was performed to determine consistency of IHC
scoring among raters. The Mann–Whitney test was used
to determine differences in gene expression between
lymph node-positive and lymph node-negative tumors.
Receiver operating characteristic (ROC) curve analysis
was used to determine cutoff points for the correlation of
gene and protein expression and nodal metastases. Correlations between gene expression or protein expression and
lymph node metastases were assessed by the chi-square
test.
OS was defined as the length of the time interval from
surgery to death from any cause. DSS was defined as the
time interval from surgery to either death because of or
as a recurrence of the disease. ROC curve analysis was
used to determine cutoff points for protein expression and
survival. The OS and the DSS curves were constructed
using the Kaplan–Meier method and the log-rank test was
used to test for significance. Prognostic value was examined by univariate and multivariate analyses using the
Cox proportional hazards regression model. Characteristics with a p < .10 in univariate analysis and potential
confounders were included, and the model was created
with backward logistic regression. All p values were
based on 2-tailed statistical analysis and p < .05 was considered statistically significant. Statistical analysis was
performed using the SPSS 20.0 statistical package (SPSS,
Chicago, IL).
RESULTS
Human papillomavirus type 16 analysis
Of our 212 tumor samples, 36 showed p16 overexpression on IHC. Of this group, only 2 samples (0.9%) proved
to be true HPV-16 positive with polymerase chain reaction, see Table 1.
Immunohistochemistry: descriptive analysis
A total of 1080 cores (85%) stained with SLPI antibody, 1119 cores (88%) stained with THBS2 antibody,
1077 cores (85%) stained with LCN2 antibody, and 1077
cores (84%) stained with TACSTD2 antibody were available for analysis. There was at least 1 core of each tumor
SLPI
EXPRESSION, NODAL METASTASIS, AND SURVIVAL IN ORAL CANCER
FIGURE 1. Scoring system for secretory leukocyte protease inhibitor (SLPI), lipocalin-2 (LCN2), tumor-associated calcium signal transducer 2
(TACSTD2), and thrombospondin-2 (THBS2).
suitable for each staining so no tumors were excluded
from analysis. The level of interrater concordance was
high, with a Spearman’s rank correlation of 0.975
(p < .001) for continuous data and a Kappa of 0.874
(95% confidence interval, 0.806–0.942; p < .001) for categorical data, scatter plot in Supplemenary Figure 1, online
only. The IHC results are given in Table 2.
LCN2 (p < .001), TACSTD2 (p 5 .002), and THBS2
(p 5 .001), see Figure 2. Optimal cutoff points determined
with ROC curve analysis (Supplemenary Figure 2 and
Supplementary Table 1, online only) revealed that gene
expression is a significant predictor of lymph node metastasis for all 4 genes. SLPI, LCN2, and TACSTD2 mRNA
are downregulated and THBS2 mRNA is upregulated in
lymph node-positive patients, see Table 3.
Gene expression and lymph node metastases
Analysis of 83 OSCCs show a statistically significant
differential gene expression between lymph node-positive
and lymph node-negative patients for SLPI (p 5 .001),
Immunohistochemistry and lymph node metastases
In the whole cohort, SLPI expression is significantly
correlated with lymph node metastases (p 5 .010), using
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TABLE 2. Immunohistochemical descriptive results.
Variables
SLPI
THBS2
TABLE 3. Gene expressions correlated with lymph node metastases.
LCN2
TACSTD2
No. of cores (%)
Tumor
1080 1119
1077
(85)
(88)
(85)
No tumor
50 (4) 86 (7)
68 (5)
No core
142 67 (5)
127 (10)
(11)
No. of cores per tumor (212 tumors)
6
110
107
109
5
50
60
53
4
26
20
23
3
16
18
16
2
8
6
7
1
2
1
4
Score per tumor (212 tumors)
Score
5%
103
24
3
126
6% to 30%
90
100 >3
86
31% to 75%
19
87
>75%
0
1
Lymph node
metastases
1074 (84)
Gene expression
73 (6)
125 (10)
SLPI
M 0.130
M >0.130
LCN2
M -0.360
M >-0.360
TACSTD2
M 0.027
109
51
24
16
9
3
Score
0
11
21
31
22
63
73
54
No. of
patients
No (%)
57
26
18 (32)
19 (73)
39 (68)
7 (27)
<.001
43
40
11 (26)
26 (65)
32 (74)
14 (35)
<.001
47
14 (30)
33 (70)
36
23 (64)
13 (36)
34
49
7 (79)
30 (61)
27 (21)
19 (39)
Yes (%)
p value
.002
M >0.027
THBS2
M >0.100
M 0.100
<.001
Abbreviations: SLPI, secretory leukocyte protease inhibitor; THBS2, thrombospondin-2; LCN2,
lipocalin-2; TACSTD2, tumor-associated calcium signal transducer 2; M, log2 (sample/reference pool).
Abbreviations: SLPI, secretory leukocyte protease inhibitor; THBS2, thrombospondin-2; LCN2,
lipocalin-2; TACSTD2, tumor-associated calcium signal transducer 2.
30% as the cutoff point, with a negative predictive value
of 74%. However, in a subgroup of early cancers, which
were clinically lymph node-negative (cT1–T2N0), significance disappeared. Analysis of protein expression of
LCN2, TACSTD2, and THBS2 revealed no significant
correlation with lymph node metastases in the whole
cohort or in a subgroup of cT1-T2N0 tumors (Table 4).
For ROC curves, see the Supplementary Figure 3 and
Supplementary Table 2, online only.
Immunohistochemistry and survival
Kaplan–Meier curves show a significant difference
between SLPI expression for both OS and DSS. The 5year OS and DSS of patients with 5% or more staining is,
respectively, 62% and 76%, in contrast with the patients
with <5% staining with a 5-year OS and DSS of, respec-
tively, 41% and 53%, see Figure 3. For ROC curves, see
Supplementary Figure 4 and Supplementary Table 3,
online only. LCN2, TACSTD2, and THBS2 expression
showed no correlation with OS or DSS (data not shown).
Cox proportional hazard regression model revealed
SLPI protein expression as an independent predictor for
both OS and DSS. Other independent predictors of OS
are age, clinical N classification, the pathological characteristics of vasoinvasion, noncohesive invasive pattern,
and bone invasion, see Table 5. For DSS, clinical N classification, and extracapsular spread are other independent
predictors, see Table 6.
DISCUSSION
Biomarkers with diagnostic and prognostic value for
determining lymph node metastases and predicting survival in OSCC are crucial for determining treatment
TABLE 4. Biomarkers correlated with lymph node metastases.
Whole cohort
(212 tumors)
Biomarker
expression
FIGURE 2. Gene expression and nodal status. Mann–Whitney test,
**p < .01, ***p < .001. SLPI, secretory leukocyte protease inhibitor; THBS2, thrombospondin-2; LCN2, lipocalin-2; TACSTD2,
tumor-associated calcium signal transducer 2; pN1, pathologic
lymph node positive; pN0, pathologic lymph node negative.
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SLPI
30%
> 30%
LCN2
Score 3
Score > 3
TACSTD2
0 to 11
21 to 31
THBS2
5%
> 5%
pN0 (%)
pN1
(%)
cT1–2N0
(101 tumors)
p
value pN0 (%) pN1 (%)
p
value
83 (43) 110 (57) .01 55 (63)
14 (74) 5 (26)
9 (69)
33 (37)
4 (31)
NS
51 (41) 75 (59)
46 (54) 40 (46)
NS
33 (60)
31 (67)
22 (40)
15 (33)
NS
35 (41) 50 (59)
62 (49) 65 (51)
NS
31 (65)
33 (62)
17 (35)
20 (38)
NS
13 (52) 12 (48)
84 (45) 103 (55)
NS
7 (78)
57 (62)
2 (22)
35 (38)
NS
Abbreviations: pN0, pathologic lymph node-negative; pN1, pathologic lymph node-positive;
SLPI, secretory leukocyte protease inhibitor; NS, not significant; THBS2, thrombospondin-2;
LCN2, lipocalin-2; TACSTD2, tumor-associated calcium signal transducer 2.
SLPI
EXPRESSION, NODAL METASTASIS, AND SURVIVAL IN ORAL CANCER
FIGURE 3. Secretory leukocyte
protease inhibitor (SLPI) expression and survival. Log-rank test,
overall survival (OS) p 5 .002,
disease-specific survival (DSS)
p < .001.
planning and possible targets for personalized treatment
in the future. Gene expression profiling revealed LCN2,
THBS2, TACSTD2, and SLPI as genes with a strong statistically significant differential gene expression between
pN1 and pN0 patients with early oral cancer.7 Although
the precise function of these genes is yet not fully understood, an explanation might be their joint role in matrix
remodeling.28
In our cohort of OSCC, LCN2, THBS2, and TACSTD2
showed no correlation with lymph node metastases or survival on protein expression level despite significant differences in staining between tumors on IHC. There are
several reasons for the poor correlations between mRNA
and protein expression levels. First, there is the undervalued role of complicated and varied posttranscriptional and
translational mechanisms, which are not yet sufficiently
defined. Second, proteins differ substantially in degradation and in vivo half-lives.29,30 Finally, both protein and
mRNA experiments contain a significant amount of errors
and noise that limits our ability to get a clear picture.30 A
combination of one or more of these factors may explain
these poor correlations, which is in line with several studies that report discrepancies between mRNA and protein
correlations with prognostically relevant outcomes.31–33
Therefore, mRNA levels cannot be used as surrogates for
corresponding protein levels without validation.
To our knowledge, this is the first study that shows the
correlation between SLPI expression by IHC and lymph
TABLE 5. Cox regression analysis of overall survival.
Variables
HR (95% CI)
p value
0.56 (0.39–0.81)
.002
0.61 (0.41–0.89)
1.04 (1.02–1.06)
3.81 (2.58–5.65)
1.59 (1.02–2.46)
2.69 (1.53–4.73)
1.75 (1.17–2.63)
.010
<.001
<.001
.040
.001
.007
node metastases, OS, and DSS in a large cohort of
patients with OSCC.
Despite a significant correlation between SLPI protein
expression and lymph node metastases in the whole
cohort, SLPI expression has no additional diagnostic
value as a predictor for lymph node metastases in a subgroup of early cancers, which are clinically lymph nodenegative in this cohort of OSCC. Previous studies report
different results correlating SLPI expression with lymph
node metastases in head and neck squamous cell carcinoma. Westin et al23 found no significant correlation,
whereas Cordes et al22 found a strong correlation between
lower SLPI protein expression and an increased risk of
lymph node metastases (p < .001). However, there are
some drawbacks in comparing these studies. First, they
did not analyze whether SLPI had additional value as a
predictor for lymph node metastases. Second, most cancers in the Cordes study were located in the larynx, oropharynx, and hypopharynx (87.6%). This might explain
the difference with our findings in oral cancer, as also for
other genes, such as EGFR, pAkt, and PTEN, it is known
that its expressions vary between oral and oropharyngeal
carcinomas.34
Although Won et al34 suggested initially that the difference in HPV-related pathogenesis of the tumors could be
the reason for different protein expression in head and
neck subsites, a later study by Hoffmann et al35 identified
SLPI expression to be an HPV-independent predictor for
lymph node metastases in head and neck cancer. In addition, their cohort contained mainly laryngeal and oropharyngeal carcinomas. Another possibility for the
TABLE 6. Cox regression analysis of disease-specific survival.
SLPI expression
Multivariate model
SLPI expression
Age
cN classification
Vasoinvasion
Noncohesive invasive pattern
Bone invasion
Variables
Abbreviations: HR, hazard ratio; CI, confidence interval; SLPI, secretory leukocyte protease
inhibitor.
SLPI expression
Multivariate model
SLPI expression
cN classification
Extracapsular spread
HR (95% CI)
p value
0.43 (0.27–0.67)
<.001
0.47 (0.29–0.75)
2.14 (1.38–4.19)
1.93 (1.10–3.38)
.002
.002
.022
Abbreviations: HR, hazard ratio; CI, confidence interval; SLPI, secretory leukocyte protease
inhibitor.
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discrepancy could be the amount of tumors with moderate/strong immunoreactivity, which, in our cohort, was
9.0% compared to 31.4% in the Cordes cohort.22 As a
result, the group of tumors with moderate/strong immunoreactivity in our study could be too small to have additional value as a predictor for lymph node metastases.
We identified SLPI as an independent predictor for OS
and DSS in OSCC. Patients with low SLPI protein
expression had a worse OS and DSS compared with
patients with any SLPI expression, see Supplementary
Figures S3 and S4, online only. Earlier studies suggested
a role for SLPI expression as a prognostic biomarker in
head and neck cancer. Westin et al23 correlated stronger
SLPI expression with well-differentiated tumors in a
group of 26 head and neck cancers and suggested its use
as a prognostic tool, although they found no significant
relationship with lymph node metastases and did not correlate its expression with survival. Alkemade et al36 found
the same significant correlation between SLPI expression
and tumor differentiation in skin cancer. In addition, Wen
et al37 demonstrated inverse correlations of SLPI expression with multiple tumor invasion parameters, which suggests a protective role of SLPI against OSCC invasion.
They also suggested SLPI as a potential biomarker in
evaluating prognosis and treatment of the clinically lymph
node-negative neck, although they did not correlate SLPI
expression with lymph node metastases or survival.
In conclusion, this is, to our knowledge, the first study
that links SLPI expression with both lymph node metastases and survival in a large cohort of patients with OSCC.
Although SLPI expression is correlated with lymph node
metastases in the whole cohort, it has no additional value
in determining lymph node metastases in early cancers
that are clinically lymph node-negative. On the other
hand, SLPI seems to be an independent predictor for both
OS and DSS. Therefore, SLPI IHC might be relevant as a
prognostic biomarker for patients with OSCC. However,
its molecular role in progression and metastasis of different head and neck cancer subsites needs further
investigation.
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