Human papillomavirus deregulates the response of a cellular network comprising of chemotactic and proinflammatory genes.
ABSTRACT Despite the presence of intracellular pathogen recognition receptors that allow infected cells to attract the immune system, undifferentiated keratinocytes (KCs) are the main targets for latent infection with high-risk human papilloma viruses (hrHPVs). HPV infections are transient but on average last for more than one year suggesting that HPV has developed means to evade host immunity. To understand how HPV persists, we studied the innate immune response of undifferentiated human KCs harboring episomal copies of HPV16 and 18 by genome-wide expression profiling. Our data showed that the expression of the different virus-sensing receptors was not affected by the presence of HPV. Poly(I:C) stimulation of the viral RNA receptors TLR3, PKR, MDA5 and RIG-I, the latter of which indirectly senses viral DNA through non-self RNA polymerase III transcripts, showed dampening in downstream signalling of these receptors by HPVs. Many of the genes downregulated in HPV-positive KCs involved components of the antigen presenting pathway, the inflammasome, the production of antivirals, pro-inflammatory and chemotactic cytokines, and components downstream of activated pathogen receptors. Notably, gene and/or protein interaction analysis revealed the downregulation of a network of genes that was strongly interconnected by IL-1β, a crucial cytokine to activate adaptive immunity. In summary, our comprehensive expression profiling approach revealed that HPV16 and 18 coordinate a broad deregulation of the keratinocyte's inflammatory response, and contributes to the understanding of virus persistence.
[show abstract] [hide abstract]
ABSTRACT: Estimates of the worldwide incidence and mortality from 27 cancers in 2008 have been prepared for 182 countries as part of the GLOBOCAN series published by the International Agency for Research on Cancer. In this article, we present the results for 20 world regions, summarizing the global patterns for the eight most common cancers. Overall, an estimated 12.7 million new cancer cases and 7.6 million cancer deaths occur in 2008, with 56% of new cancer cases and 63% of the cancer deaths occurring in the less developed regions of the world. The most commonly diagnosed cancers worldwide are lung (1.61 million, 12.7% of the total), breast (1.38 million, 10.9%) and colorectal cancers (1.23 million, 9.7%). The most common causes of cancer death are lung cancer (1.38 million, 18.2% of the total), stomach cancer (738,000 deaths, 9.7%) and liver cancer (696,000 deaths, 9.2%). Cancer is neither rare anywhere in the world, nor mainly confined to high-resource countries. Striking differences in the patterns of cancer from region to region are observed.International Journal of Cancer 12/2010; 127(12):2893-917. · 5.44 Impact Factor
[show abstract] [hide abstract]
ABSTRACT: Approximately 35 years ago a role of human papillomaviruses (HPV) in cervical cancer has been postulated. Today it is well established that this very heterogeneous virus family harbours important human carcinogens, causing not only the vast majority of cervical, but also a substantial proportion of other anogenital and head and neck cancers. In addition, specific types have been linked to certain cutaneous cancers. In females, HPV infections on a global scale account for more than 50% of infection-linked cancers, in males for barely 5%. Vaccines against the high risk HPV types 16 and 18 represent the first preventive vaccines directly developed to protect against a major human cancer (cervical carcinoma). This review will cover some of the historical aspects of papillomavirus research; it tries briefly to analyze the present state of linking HPV to human cancers and will discuss some emerging developments.Virology 02/2009; 384(2):260-5. · 3.35 Impact Factor
Article: Prevalence of human papillomavirus in cervical cancer: a worldwide perspective. International biological study on cervical cancer (IBSCC) Study Group.[show abstract] [hide abstract]
ABSTRACT: Epidemiologic studies have shown that the association of genital human papillomavirus (HPV) with cervical cancer is strong, independent of other risk factors, and consistent in several countries. There are more than 20 different cancer-associated HPV types, but little is known about their geographic variation. Our aim was to determine whether the association between HPV infection and cervical cancer is consistent worldwide and to investigate geographic variation in the distribution of HPV types. More than 1000 specimens from sequential patients with invasive cervical cancer were collected and stored frozen at 32 hospitals in 22 countries. Slides from all patients were submitted for central histologic review to confirm the diagnosis and to assess histologic characteristics. We used polymerase chain reaction-based assays capable of detecting more than 25 different HPV types. A generalized linear Poisson model was fitted to the data on viral type and geographic region to assess geographic heterogeneity. HPV DNA was detected in 93% of the tumors, with no significant variation in HPV positivity among countries. HPV 16 was present in 50% of the specimens, HPV 18 in 14%, HPV 45 in 8%, and HPV 31 in 5%. HPV 16 was the predominant type in all countries except Indonesia, where HPV 18 was more common. There was significant geographic variation in the prevalence of some less common virus types. A clustering of HPV 45 was apparent in western Africa, while HPV 39 and HPV 59 were almost entirely confined to Central and South America. In squamous cell tumors, HPV 16 predominated (51% of such specimens), but HPV 18 predominated in adenocarcinomas (56% of such tumors) and adenosquamous tumors (39% of such tumors). Our results confirm the role of genital HPVs, which are transmitted sexually, as the central etiologic factor in cervical cancer worldwide. They also suggest that most genital HPVs are associated with cancer, at least occasionally. The demonstration that more than 20 different genital HPV types are associated with cervical cancer has important implications for cervical cancer-prevention strategies that include the development of vaccines targeted to genital HPVs.JNCI Journal of the National Cancer Institute 07/1995; 87(11):796-802. · 13.76 Impact Factor
Human Papillomavirus Deregulates the Response of a
Cellular Network Comprising of Chemotactic and
Rezaul Karim1,2,3, Craig Meyers4, Claude Backendorf5, Kristina Ludigs2¤a, Rienk Offringa2¤b, Gert-Jan B.
van Ommen1, Cornelis J. M. Melief2, Sjoerd H. van der Burg3, Judith M. Boer1,6*
1Center for Human and Clinical Genetics, Leiden University Medical Center, Leiden, The Netherlands, 2Department of Immunohematology and Blood Transfusion, Leiden
University Medical Center, Leiden, The Netherlands, 3Department of Clinical Oncology, Leiden University Medical Center, Leiden, The Netherlands, 4Department of
Microbiology and Immunology, The Pennsylvania State University College of Medicine, Hershey, Pennsylvania, United States of America, 5Laboratory of Molecular
Genetics, Leiden Institute of Chemistry, Gorlaeus Laboratories, Leiden University, Leiden, The Netherlands, 6Netherlands Bioinformatics Centre, Nijmegen, The
Despite the presence of intracellular pathogen recognition receptors that allow infected cells to attract the immune system,
undifferentiated keratinocytes (KCs) are the main targets for latent infection with high-risk human papilloma viruses
(hrHPVs). HPV infections are transient but on average last for more than one year suggesting that HPV has developed means
to evade host immunity. To understand how HPV persists, we studied the innate immune response of undifferentiated
human KCs harboring episomal copies of HPV16 and 18 by genome-wide expression profiling. Our data showed that the
expression of the different virus-sensing receptors was not affected by the presence of HPV. Poly(I:C) stimulation of the viral
RNA receptors TLR3, PKR, MDA5 and RIG-I, the latter of which indirectly senses viral DNA through non-self RNA polymerase III
transcripts, showed dampening in downstream signalling of these receptors by HPVs. Many of the genes downregulated in
HPV-positive KCs involved components of the antigen presenting pathway, the inflammasome, the production of antivirals,
pro-inflammatory and chemotactic cytokines, and components downstream of activated pathogen receptors. Notably, gene
and/or protein interaction analysis revealed the downregulation of a network of genes that was strongly interconnected by
IL-1b, a crucial cytokine to activate adaptive immunity. In summary, our comprehensive expression profiling approach
revealed that HPV16 and 18 coordinate a broad deregulation of the keratinocyte’s inflammatory response, and contributes
to the understanding of virus persistence.
Citation: Karim R, Meyers C, Backendorf C, Ludigs K, Offringa R, et al. (2011) Human Papillomavirus Deregulates the Response of a Cellular Network Comprising of
Chemotactic and Proinflammatory Genes. PLoS ONE 6(3): e17848. doi:10.1371/journal.pone.0017848
Editor: Dong-Yan Jin, University of Hong Kong, Hong Kong
Received December 6, 2010; Accepted February 10, 2011; Published March 14, 2011
Copyright: ? 2011 Karim et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits
unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Funding: This work was supported by the Centre for Medical Systems Biology, a Centre of Excellence supported by the Netherlands Genomics Initiative. CJMM
was supported by Public Health Service Grant AI057988. SHvdB and JMB were supported by the Netherlands Organization for Health Research (NWO/ZonMw)
TOP grant 91209012. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Competing Interests: The authors have declared that no competing interests exist.
* E-mail: firstname.lastname@example.org
¤a Current address: Department of Biochemistry, Universite ´ de Lausanne, Lausanne, Switzerland
¤b Current address: Genentech Inc., South San Francisco, California, United States of America
Cervical cancer is the second most common cancer in women
worldwide. More than 520,000 women are diagnosed with
invasive cervical cancer each year . Cervical and other
anogenital carcinomas arise as result of an uncontrolled persistent
infection with a high-risk type human papillomavirus (HPV), in
particular types HPV16 and HPV18 [2,3]. A detectable
cervicovaginal HPV infection in young women is close to 1–2
years  before it is cleared, suggesting that HPV can evade host
immunity. Indeed, the infection cycle of HPV is one in which viral
replication and release is not associated with overt inflammation
[5,6] and HPV-specific adaptive immune responses are often weak
or lacking in patients with progressive HPV infections [7–10].
Stratified squamous epithelia consist of undifferentiated (basal
layer) and increasingly differentiated KCs. The basal KCs are the
primary target of HPV infection . In these cells, innate
immunity acts as the first line of defense against invading viruses.
KCs express pathogen recognition receptors (PRRs) including
TLR9, which responds to viral DNA , as well as TLR3,
protein kinase R (EIF2AK2), and the RNA helicases RIG-I
(DDX58) and MDA5 (IFIH1), which recognize single-stranded
and double-stranded RNA (dsRNA) . Ligand binding to these
PRRs leads to direct NF-kappa-B activation resulting in the
upregulation of pro-inflammatory cytokines, and/or activation of
type I interferon (IFN) response genes including transcription
factors IRF3 and IRF7 regulating the production of antiviral
Expression of specific viral oncoproteins, E6 and E7, is required
for maintaining the malignant growth of cervical cancer cells .
To understand how HPV infection may alter KCs and evade PRR
activation, direct protein interactions including the binding of the
HPV E6 oncoprotein to IRF3 have been studied [24,25]. An
OncoChip expression study showed that retrovirally expressed E6
PLoS ONE | www.plosone.org1March 2011 | Volume 6 | Issue 3 | e17848
and E7 efficiently downregulated type I IFN responses in
keratinocytes, but surprisingly also upregulated the expression of
pro-inflammatory cytokines . Another early microarray study
described downregulation of interferon-inducible genes in KCs
containing episomal HPV type 31 . These studies indicated
that HPV-derived proteins could meddle with host immunity but
the full spectrum of interference is within the limitations of these
studies not visible.
We aimed at understanding the effects of high-risk HPVs on the
immune response in KCs. First, we confirmed expression of the
viral RNA receptors in undifferentiated and differentiated cells,
while DNA sensor TLR9 was restricted to differentiated cells, and
showed that HPV does not interfere with expression levels of the
PRRs. Next, we focused our studies on undifferentiated KCs, since
these are the target cells for latent infection with HPV. We
generated expression profiles of several different control KCs and
KCs harboring episomal copies of entire HPV16 or 18 genomes
[28,29] on microarrays representing 24,500 well-annotated
transcripts to study differences in the baseline gene expression
by the presence of HPV. In addition, we studied differences in
response to triggering the viral RNA PRRs with the synthetic
dsRNA poly(I:C). Although HPV is a DNA virus, non-self dsDNA
can serve as template for transcription into dsRNA by polymerase
III and induce type I interferon and NF-Kappa-B through the
RIG-I pathway [30–32]. Here, we show that HPVs were able to
dampen a network of genes associated with activation of the
adaptive immune response encoding antimicrobial molecules,
chemotactic and pro-inflammatory cytokines, and proteins that
are involved in antigen presentation, and that most of them are
interconnected via IL1B.
Materials and Methods
The use of discarded human foreskin, cervical and vaginal
keratinocyte tissues to develop cell lines for these studies was
approved by the Institutional Review Board at the Pennsylvania
State University College of Medicine and by the Institutional
Review Board at Pinnacle Health Hospitals. The Medical Ethical
Committee of the Leiden University Medical Center approved the
human tissue sections (healthy foreskin, healthy cervix, HPV16- or
18-positive cervical neoplasias) used for staining. All sections and
cell lines were derived from discarded tissues and de-identified,
therefore no informed consent was necessary.
Human epidermal KCs were isolated from foreskin, vagina, or
cervix of unrelated donors  and established on a layer of
primary KCs - devoid of contaminating cells - were grown in
serum-free medium (Defined KSFM, Invitrogen, Breda, The
Netherlands). Partial differentiation was induced by 1.8 mM Ca2+
for 24 hrs, terminal differentiation by placing KCs in single-cell
suspension into serum-free medium containing 1.75% methylcel-
lulose and 1.8 mM Ca2+ for 24 hrs . KC cell lines
maintaining episomal copies of HPV16 and HPV18 were created
via an electroporation technique described previously [28,29] but
without antibiotic selection. The cell lines were 100% HPV-
positive. Southern analyses confirmed the recircularization and
subsequent maintenance of episomal viral genomes at approxi-
mately 50–100 copies per cell (data not shown). The HPV-positive
lines growed at similar rates with population doubling times of ,2
days) and, when placed in raft culture, all underwent the late stages
of the virus life cycle, such as genome amplification, late gene
137Cs-irradiated mouse 3T3 fibroblasts. Passage 4–5 of
expression, and virus production (data not shown). HPV-positive
cells were grown in monolayer culture using E medium in the
presence of mitomycin C-treated 3T3 fibroblasts [28,29] for
passage 6–7, and adapted to serum-free medium for one passage
before experimentation. All cells used were tested and found free
of mycoplasm. Where indicated, cells were stimulated with
poly(I:C) (25 mg/ml, InvivoGen, San Diego, USA). CCL5 and
IL-1B concentrations in supernatants were determined using the
Quantikine ELISA kits (R&D Systems, Minneapolis, USA).
Standard immunohistochemical staining was performed using
antibodies against human RNASE7 (Sigma-Aldrich, Zwijndrecht,
Netherlands, dilution 1:1600) and TLR9 (clone 26C593.2,
Imgenex, San Diego, USA, 1:800). Four-mm sections of forma-
lin-fixed, paraffin-embedded tissues were deparaffinized, endoge-
nous peroxidase was quenched with 0.3% H2O2 in methanol for
20 minutes, and antigen retrieval was performed by boiling the
sections for 10 minutes in Tris-EDTA buffer (pH 9.0). For TLR9
antibody stainings, antigen retrieval was performed by boiling the
sections for 10 minutes in citrate buffer (pH 6.0). Isotype control
antibody against mouse IgG1 (1:1000 dilution, code X0931,
DAKO, Glostrup, Denmark) was used. Primary antibodies were
incubated overnight at room temperature. The Powervision
detection system was applied (DAKO, Heverlee, Belgium).
Mayer’s haematoxylin was used for counterstaining of the slides.
Total RNA isolation and quantitative RT-PCR
Total RNA was isolated using TRIzol (Invitrogen, Breda, The
Netherlands) followed by the RNeasy Mini Protocol (Qiagen,
Venlo, The Netherlands). Total RNA (0.2 mg) was reverse
transcribed using SuperScript III (Invitrogen) and oligo dT
primers (Promega, Madison, USA). Triplicate PCR reactions
were performed with 20 pmol of gene-specific primers and Taq
DNA polymerase (Promega) using PCR conditions and primers as
described previously for TLRs  and SPRR2A . Pre-
designed primers and probe mixes for TLR3, CCL5, IL1B,
RNASE7, NLRP2, and GAPDH were from Applied Biosystems
(Foster City, USA). Threshold cycle numbers (Ct) were deter-
mined with 7900HT Fast Real-Time PCR System (Applied
Biosystems) and the relative quantities of mRNA per sample were
calculated using the DDCt method with GAPDH as the calibrator
gene. The relative levels of mRNA were determined by setting the
mRNA expression level of the lowest expressing control KCs to 1,
unless otherwise indicated.
cRNA synthesis and microarray hybridization
We used four primary KC cultures, HVKp1 and HVKp2 (both
vaginal), HFKc1 and ESG2 (both foreskin), as well as four KC cell
lines stably maintaining episomal HPV16 or 18, HVK16 (vaginal),
HVK18 (vaginal), HCK18 (cervical), and HPV16 (foreskin). Cells
were harvested at three conditions: unstimulated, 4 hrs and 24 hrs
of 25 mg/ml poly(I:C). Total RNA for these 24 samples was
isolated as stated above, and analyzed on an RNA 6000 Nano
Lab-on-a-Chip in the 2100 Bioanalyzer (Agilent Technologies,
Waldbronn, Germany), showing RIN scores above 9.6. Total
RNA (50–100 ng) was reverse-transcribed, amplified and biotin-
labeled using the Ambion Illumina TotalPrep RNA Amplification
kit (Applied Biosystems, Streetsville, ON, Canada). Concentration
measurements were done using the NanoDrop ND-3300 (Isogen
Life Science, De Meern, The Netherlands), 750 ng of labeled
cRNA was hybridized to Sentrix HumanRef-8 V2 BeadChips
(22K, Illumina, San Diego CA, USA), and scanned with
BeadArrayer 500GX (Illumina). The samples were randomized
hrHPVs Suppress Immune Response in Keratinocytes
PLoS ONE | www.plosone.org2March 2011 | Volume 6 | Issue 3 | e17848
for two cRNA synthesis batches and (sub)array location. Raw
probe level intensity values were summarized and exported with
Illumina probe annotations using Illumina BeadStudio v3.2 (Gene
Expression Module BSGX Version 3.2.7). Non-background
corrected data were variance stabilizing transformed followed by
robust spline normalization  using the lumi v1.6.2 [36,37] and
lumiHumanAll.db v1.2.0  BioConductor v2.2 packages in R
v2.7.1 (R Development Core Team, www.R-project.org). All
microarray data is MIAME compliant and the raw data has been
deposited in the MIAME compliant database Gene Expression
Omnibus with accession number GSE21260, as detailed on the
MGED Society website http://www.mged.org/Workgroups/
Analysis of differential gene expression
We fitted a linear model in limma v2.14.7  with ‘virus’
(HPV-positive) and ‘stimulation’ (4 and 24 hrs) effects. We used a
nested variable within ‘virus’ for the individual cell lines, where
HVKp1 and HVK16 were the reference cells for the HPV-
negative and HPV-positive groups, respectively. Multiple-testing
corrected p-values  and log2 fold changes were extracted for
different contrasts. For Table S1, the 4 and 24 hrs timepoints were
combined into one F-test in limma. One-dimensional hierarchical
clustering of log2 fold changes derived from limma was done in
Spotfire DecisionSite 9.1 v19.1.977 using correlation as similarity
measure and complete linkage.
Functional genomics analyses
Functional annotation of the groups of co-regulated genes
identified by hierarchical clustering was performed using Anni 2.0
. We used GenMAPP v2.1  to overlay expression on the
TLR signaling pathway, which was based on automatic extraction
from KEGG  hsa04620 (7/17/09) with improved layout using
PathVisio v1.0 beta software . The edited pathway is available
from GenMAPP and WikiPathways .
We used CORE_TF (www.lgtc.nl/CORE_TF) based on Trans-
Fac 11.2 and Ensembl 49  to identify over-represented
transcription factor binding sites in promoters compared to a
random set of 2966 promoters (1000 bp upstream+exon 1).
Microarray probe EntrezGene IDs were converted to Ensembl
Gene IDs using IDconverter , entries resulting in multiple or
missing Ensembl Gene IDs wereremoved. The match cutoffwasset
to minimize the sum of false positives and false negatives; position
weight matrices with a p-value for over-representation #0.01 and a
frequency below 50% in the random set were selected.
The network was constructed using Ingenuity Pathways
Analysis (IPA 7.6; IngenuityH Systems, Inc., www.ingenuity.
com). The 663 HPV signature genes were filtered for the more
extreme log fold changes to obtain a gene signature strongly
affected by HPVs, and to get the number of genes below 500,
which is the maximum limit of IPA for making a network. Genes
not connected were deleted, the remaining HPV signature genes
that were initially excluded as stated above were included to
generate the final network consisting of 212 connected genes. All
edges are supported by at least one reference from the literature,
from a textbook, or from canonical information stored in the
Ingenuity Pathways Knowledge Base.
Expression of viral pathogen recognition receptors in KCs
We determined the mRNA expression of Toll-like receptors and
retinoic acid-inducible gene I (RIG-I)-like receptors in undiffer-
entiated, partially and fully differentiated KCs. Expression of the
small proline-rich protein 2A (SPRR2A) was used as a molecular
marker of KC differentiation (Fig. S1A). Undifferentiated KCs
were found to express TLR1, TLR2, TLR3, TLR5, TLR6, TLR10,
RIG-I and MDA5 (Fig. 1A, 1B). Among the viral PRRs, TLR7,
TLR8 and TLR9 were not detectable while TLR3, RIG-I and
MDA5 were expressed. In parallel experiments, transcripts of
TLR4 and TLR7-9 were readily detected in mRNA samples from
Ramos B-cells and monocytes (Fig. S1B). The expression in KCs is
largely in line with previous reports by others . HPV-positive
KCs showed essentially the same pattern of PRR expression
(Fig. 1A, 1B). Additionally, real-time RT-PCR showed similar
levels of TLR3 in HPV-negative and HPV-positive KCs (Fig. 1C).
Upon differentiation KCs also expressed the DNA sensor TLR9,
which was confirmed by immunohistochemistry in human foreskin
and cervical epithelia (Fig. S2). TLR9 was also expressed in the
differentiated layers of HPV-positive cervical epithelial neoplasias
(Fig. S3). The absence of TLR4 expression in differentiated KCs,
which was confirmed by expression microarray (see below), is
consistent with work by others showing that TLR4 was only found
in HaCat cells, but not in primary human KCs [16,48]. The
pattern of TLR expression in differentiated HPV-positive KCs was
similar to that in HPV-negative cells. Thus, HPVs did not affect
mRNA expression of the tested PRRs.
Figure 1. KCs express pathogen recognition receptors. Total RNA of indicated KCs was subjected to RT-PCR (35 cycles) with specific primers
for human TLR1-10, GAPDH (indicated by a G) (A), RIG-I or MDA5 (B). Control KC correspond to HFK2. Size markers (1 kb plus DNA Ladder, Invitrogen)
from high to low: 1000, 850, 650, 500, 400, 300, 200, 100 bp; 1.8% agarose gel. (C), TaqMan RT-PCR results showing TLR3 mRNA expression in HPV-
negative (HFK2 and HVK2) and HPV-positive (HPV16 and HVK18) KCs. Fold-changes are relative to HFK2. Data are mean 6 SD, n=3.
hrHPVs Suppress Immune Response in Keratinocytes
PLoS ONE | www.plosone.org3March 2011 | Volume 6 | Issue 3 | e17848
HPV signature genes
We subsequently studied whether HPVs affected the signalling
of PRRs using genome-wide expression profiling. Control KCs
(n=4) and KCs with episomal HPV16 or HPV18 genomes (n=4)
of foreskin, vaginal or cervical origin from eight different
individuals were used to include biological variation. Since HPVs
infect basal KCs, we focused on the viral PRRs expressed in
undifferentiated cells, including TLR3, RIG-I and MDA5, which
respond to the synthetic dsRNA poly(I:C) . In agreement with
the RT-PCR data, the presence of HPV did not change the
expression of these PRRs (Table S1).
To obtain a robust signature of genes affected by HPVs, we
selected differentially expressed genes between HPV-positive and -
negative KCs at 0, 4 or 24 hrs of poly(I:C) stimulation with a false
discovery rate (FDR) of 0.05 (1529 probes). Furthermore, we
applied an absolute log2-fold change filter $1 to select genes that
were at least two-fold up- or downregulated (663 probes
representing 634 unique genes), designated ‘‘HPV signature
genes’’ (union of genes in Venn diagram Fig. 2A, Table S2).
The majority of HPV-specific differentially expressed genes were
shared between all three (213) or two (150) conditions, with most
overlap between 0 and 4 hrs. Notably, 219 genes were changed in
the virus-positive group only after 24 hrs of poly(I:C) stimulation,
showing that the effect of HPVs was more pronounced after
Poly(I:C) response in control KCs
We first focused on the effect of poly(I:C) stimulation in control
KCs. While after 4 hrs (Fig. 2B left) we found 123 differentially
expressed probes that were mainly upregulated, the response was
more balanced and involved over 700 genes after 24 hrs of
stimulation (Fig. 2B right). Many genes were upregulated,
including pathogen-sensing receptors (RIG-I, MDA5, PKR),
adaptor molecules (MYD88, TICAM1/TRIF, TICAM2/TRAM),
and interferon regulatory factors (IRF1, IRF6, IRF7), see Table S1.
These results are similar to a previous report showing that
poly(I:C) stimulation induces antiviral and inflammatory responses
in KCs . Overlay of differential expression after 24 hrs of
poly(I:C) stimulation on the TLR signaling pathway (KEGG
hsa04620) showed upregulation of the Jak-STAT signaling
pathway, triggered by temporary upregulation of IFNB1 after
4 hrs poly(I:C) through the TRAF3/TBK1 signal transduction
route, resulting in upregulation of STAT1 and chemotactic
cytokines CXCL10 and CXCL11. In addition, via TRAF6 the NF-
kappa-B signaling pathway was triggered, activating cytokines/
chemokines TNF, IL1B, IL6, IL8, CCL3, CCL4, and CCL5 (Fig.
S4). The cytoplasmic RNA sensing receptors MDA5 and RIG-I,
which are not shown in the TLR signaling pathway, initiate
signaling pathways that differ in their initial steps from TLR3
signaling, but converge in the activation of TBK1 and NFKB
Deregulation of poly(I:C) response in HPV-positive KCs
The differentially expressed genes in the HPV-positive cells
upon poly(I:C) stimulation largely overlapped with those in control
KCs (Fig. 2B). Next, we studied the effect of the virus in the
context of the TLR signaling pathway. Activation of the TLR
signaling pathway in HPV-positive KCs upon 24 hrs of poly(I:C)
stimulation was largely similar to the response in control cells (Fig.
S5). However, when directly comparing HPV-positive and –
negative cells after 24 hrs of stimulation, relative downregulation
of the adaptor TICAM1 and several cytokines (IL1B, IL6, CCL5/
RANTES) was evident. These results suggest that the dsRNA PRR
signaling pathway is less activated in HPV-positive cells (Fig. S6).
Co-regulated genes downregulated by HPVs
We extended our analyses to the full set of HPV signature genes,
and identified genes with similar expression patterns over the sample
groups by unsupervised clustering (Fig. 2C, Table S2). The gene
dendrogram was cut at six clusters to generate profiles of co-regulated
in the coordinated expression changes, we analyzed the promoter
sequences of the genes in each of these clusters for enrichment of
predicted transcription factor binding sites .
The first three clusters contained genes that were downregulat-
ed in HPV-positive compared to HPV-negative cells. Binding sites
for early growth response (EGR) family transcription factors,
involved in differentiation and mitogenesis, were significantly
enriched in these clusters (Table S3). Cluster 1 genes (164 probes),
including inflammasome components (NLRP2, PYCARD), were
downregulated in HPV-positive KCs irrespective of poly(I:C)
stimulation. Many of these downregulated genes, including several
others in expression clusters 2 and 3, are involved in epidermis
development and KC differentiation, fitting with the biological
effect of HPV in delaying differentiation . Cluster 2 genes (194
probes), including antimicrobials (DEFB103B, LOC728454, AQP9,
RNASE7, SRGN), antigen presenting molecules (HLA-A, -B, -C, -G,
HCP5), pro-inflammatory cytokines and chemokines (CCL5/
RANTES, CSF2/GM-CSF, TGF-alpha, IL23A), interferon-inducible
genes (IFI27, IFITM1), and TICAM1 showed lower expression in
the group of unstimulated HPV-positive cells. Moreover, the
upregulation of these genes at 24 hrs of poly(I:C) stimulation as
found in control KCs was suppressed in HPV-positive cells. Plots
with microarray log2 intensities for four probes, CCL5/RANTES,
IL1B (cluster 3, see below), TICAM1 and RNASE7 show the HPV
effect as well as the biological variation inherent to using KCs
derived from different individuals and different tissues, combined
with two different HPV types (Fig. 3A). Downregulation of CCL5
and TICAM1 was confirmed by qRT-PCR (Fig. 3B and 3D), and
ELISA showed lower CCL5 secretion in HPV-positive KCs upon
poly(I:C) stimulation (Fig. 3C). For the small number of cluster 3
genes (15 probes), including pro-inflammatory cytokines (IL1B,
IL1A, IL6), baseline expression (most likely activated by serum
components) and upregulation at 4 and 24 hrs of poly(I:C)-
stimulation were suppressed in HPV-positive cells. These genes
were already upregulated after 4 hrs of stimulation, and showed
promoter enrichment of binding sites for Rel/NFKB family
members and STAT5 (Table S3).
Interestingly, the majority of expression cluster 2 and 3 genes
followeda similarpattern of suppressed poly(I:C)response,suggesting
that many of these genes are downstream targets of PRR signaling.
We focused on the antimicrobial molecule RNASE7, a member of
the RNase A superfamily with broad-spectrum antimicrobial activity
by viral infection. qRT-PCR confirmed RNASE7 upregulation upon
poly(I:C) stimulation in control KCs, and suppression of poly(I:C)-
mediated upregulation in the presence of HPVs (Fig. 4A). Normal
cervical epithelial cells expressed RNASE7 throughout the epithelia,
and high expression was observed in the basal layer, the in vivo
equivalent to undifferentiated KCs (Fig. 4B). In contrast, RNASE7
protein was not expressed in any of the layers of undifferentiated cells
within a representative HPV-induced CIN3 lesion. These data
suggest that by suppressing the gene activation of antimicrobial
molecules such as RNASE7, HPVs evaded the innate antiviral
responses of the host.
Co-regulated genes upregulated by HPVs
Clusters 4–6 contained genes that were specifically upregulated
in the HPV-positive compared to HPV-negative cells. Cluster 4
hrHPVs Suppress Immune Response in Keratinocytes
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genes (167 probes) included heat-shock response genes, cell cycle
regulators and genes involved in replication initiation, transcrip-
tion and splicing. These HPV-activated genes were downregulated
upon poly(I:C) stimulation, but not to the same level as in control
KCs. Binding sites for MEF2A, involved in the activation of stress-
induced genes, and E2F, a family of transcription factors with a
crucial role in the control of cell cycle that is indirectly activated by
HPV E7, were enriched (Table S3). Cluster 5 (112 probes)
contained cancer-related genes including tumor-promoting cyto-
kines/chemokines and their receptors, e.g. CXCR7, of which the
expression was higher in HPV-positive KCs irrespective of
poly(I:C) stimulation. Many transcription factor binding sites were
enriched, including motifs binding the oncoprotein MYC (Table
S3). Finally, the smallest cluster 6 (11 probes) included several
antiviral response genes (TRIM5, ZC3HAV1, IFIT2, RARRES3,
CXCL16) that were stronger upregulated in HPV-positive than in
Figure 2. HPVs affect gene expression of KCs both at baseline and upon PRR stimulation. (A), Venn diagram depicting the overlap
between 663 HPV signature genes with adjusted p-value#0.05 and absolute log2-fold change$1 altered by HPVs at baseline (unstimulated) and 4
and 24 hrs of poly(I:C) stimulation. Numbers in red represent upregulated genes while green indicates downregulated genes. (B), Venn diagrams
showing the overlapping genes between control and HPV-positive KCs in their response to poly(I:C) stimulation for 4 hrs (left panel) and 24 hrs (right
panel). Significance thresholds and colors as in (A). (C), One-dimensional hierarchical clustering of 663 HPV signature genes based on Pearson
correlation using a complete linkage algorithm. Rows represent genes, columns represent ordered experimental groups each including four
independent biological replicates. Limma log2-fold changes of the indicated conditions compared to the HPV-negative, unstimulated group are
shown in the heatmap using red and green for up- and down-regulation, respectively. Black indicates no change. Six clusters based on cutting the
gene dendrogram (red dashed vertical line) are indicated with color bars to the right. (D), Profile plots of co-regulated genes grouped according to
the six expression clusters. Colors of the gene profiles match the bars to the right of the heatmap in (C). The y-axis shows the log2-fold change
compared to HPV-negative, unstimulated KCs, the x-axis shows the ordered sample groups.
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control KCs. Enriched binding sites included IFN-stimulated
response element (ISRE), bound by transcription factor ISGF-3,
and binding sites bound by interferon-response factors (IRFs).
In summary, the presence of episomal HPVs caused downreg-
ulation of genes involved in innate and adaptive immune responses
as well as KC differentiation, while upregulated genes were
involved in cell cycle, RNA and DNA metabolism. Overall, these
data showed that HPVs induced coordinated changes in KC gene
expression, detectable in unstimulated ‘baseline’ cells (mainly
expression clusters 1, 5, majority of cluster 4) or after poly(I:C)
stimulation (mainly expression clusters 2, 3, 6).
HPVs deregulate cellular networks
Understanding the network topology of gene and/or protein
interactions may identify highly interconnected gene ‘‘hubs’’
targeted by HPVs. Therefore, we explored connections among
the HPV signature genes based on literature and high-throughput
database information collected in Ingenuity Pathways Analysis
. On the resulting network of 212 genes, we overlaid the
expression log2-fold changes of HPV-positive versus control KCs
after 24 hrs of poly(I:C) stimulation (Fig. 5). The center of the
network was formed by the most interconnected gene IL1B,
necessary for activation of the adaptive immune response ,
and IL6. IL1B and IL6 were downregulated, and connected to
genes encoding cytokines and antigen presentation molecules that
were also lower expressed in HPV-positive cells. We studied IL1B
in more detail, since it represented a central target for HPV-
mediated suppression of both the innate and adaptive immune
responses of KCs. RT-PCR data validated the microarray data
showing that both the baseline and PRR-stimulated levels of IL1B
were downregulated in HPV-positive KCs compared to control
cells (Fig. 6A). Also, both the baseline and PRR-stimulated IL-1b
secretion was lower in HPV-positive KCs (Fig. 6B). Secretion of
IL-1b requires activity of both the TLR/NF-kappa-B and the
inflammasome pathways . The TLR/NF-kappa-B pathway
activates pro-IL-1b expression, which is cleaved to active IL-1b by
the inflammasome. In addition to the downregulation of pro-IL-
1b, HPVs specifically downregulated the genes encoding inflam-
masome components NLRP2 in three of the four HPV-positive
lines (Fig. 6C) and PYCARD/ASC, but not NALP3, possibly
contributing to the observed lower level of IL-1b. The most
interconnected upregulated gene of the network was CDKN2A,
involved in cell cycle progression. Thus, by targeting highly
interconnected genes, HPVs reprogrammed the gene network of
KCs in favor of immune escape and cell proliferation of HPV-
We studied systematic differences in genome-wide expression
profiles of control and HPV-positive undifferentiated (basal) KCs
focusing on immune-related effects. The parallel analysis of several
control and HPV16- and 18-positive KCs from several genital
tissues ensured that the results can be generalized. The HPV-
positive KCs expressed the full array of HPV genes and mimic
latent HPV infection in vivo, which is also reflected by the fact that
these cells display the entire differentiation-dependent HPV life
cycle upon culture in organotypic raft cultures [28,29]. Our studies
revealed that while KCs are well equipped to respond to viral
pathogens, latent infection with HPV results in suppression
downstream of the PRRs as reflected by lower expression levels
of effector molecules involved in innate and adaptive immune
No difference was observed in expression levels of viral RNA
PRRs TLR3, TLR9, RIG-I, MDA5 and PKR between control and
HPV-positive KCs. We found that viral DNA PRR TLR9 was
lacking in the basal layers in stratified squamous epithelia, but
expressed in the suprabasal layers of the non-neoplastic epitheli-
um. Previous studies suggested that E6/E7 expression affected
Figure 3. HPVs cause expression changes in immune-related genes. (A), Microarray log2 intensities (y-axis) for the expression levels of four
example genes in HPV-negative and HPV-positive KCs, unstimulated or stimulated with poly(I:C) for 4 or 24 hrs. The eight individual KC cultures are
color-coded. A star indicates a significant difference between HPV-positive and control KCs (see Materials and Methods for details). TaqMan RT-PCR
showing CCL5 (RANTES) (B) and TICAM1 (C) mRNA expression in control (HVKp1 and HVKp2) and HPV-positive (HVK16 and HVK18) KCs at baseline and
after poly(I:C) for 24 hrs. Data are mean 6 SD, n=3. (D), CCL5 secretion of control (HFK1 and HFK2) and HPV-positive (HPV16, HCK18, and HVK16) KCs
measured by ELISA. Data are mean 6 SD over three replicate samples.
Figure 4. HPV inhibits RNASE7 expression in stimulated KCs and cervical neoplasia. (A), TaqMan RT-PCR showing RNASE7 mRNA
expression in control (HVKp1 and HVKp2) and HPV-positive (HVK16 and HVK18) KCs. Data are mean 6 SD, n=3. (B), RNASE7 protein is downregulated
in cervical intraepithelial neoplasia 3 (CIN3). Immunohistochemical staining of paraffin-embedded sections showing RNASE7 protein expression in
normal healthy ectocervical epithelium (left) and CIN3 (right). Original magnification 1256. Stainings shown are representative of at least three
samples of different individuals.
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neither the expression nor the function of TLR9 , whereas
others reported that E6/E7 expression resulted in loss of TLR9
expression . Our data showed that forced differentiation of
HPV-positive KCs resulted in the expression of TLR9, however,
as HPVs inhibits differentiation this may appear as TLR9 loss
similar to what was seen previously . Thus, TLR9 is absent in
the cells targeted by HPV, but other viral PRRs are expressed,
including RIG-I that has been shown to indirectly function as a
PRR for DNA viruses [30–32], suggesting that in essence
undifferentiated KCs can sense HPV infection.
As there were no overt differences in the expression levels of
PRRs, we focused on the interference of HPVs with the
downstream pathogen-sensing machinery. First, our data showed
that HPVs downregulated genes that have a direct antimicrobial
function. Moreover, the presence of HPVs was associated with the
downregulation of an array of pro-inflammatory and chemotactic
cytokines, and antigen-processing and presenting molecules, and
IL-1b and IL6 were the hubs in the center of this HPV signature
gene network. Notably, the expression level of most of these genes
was already lower at baseline. Poly(I:C), which triggers viral PRRs
including TLR3 and importantly also RIG-I, increased their
expression level in HPV-positive KCs albeit not to the same level
as in control KCs. Previously it was shown that HPV31-positive
KCs responded less well to interferon stimulation  and this fits
with our own data showing that interferon-inducible genes (cluster
2) are downregulated. Apparently, this is not the only immune
signaling pathway that is downregulated by HPV as our data
reveal that also the TLR and the RIG-I-like receptor signaling
pathways are suppressed in HPV-positive KCs. Notably, the
failure of HPV31-positive KCs to respond to interferon was
associated with downregulation of STAT1 (25). Specific down-
regulation of STAT1 was found only in our HPV16-positive KCs
Figure 6. HPVs downregulate IL1B and inflammasome components. (A), TaqMan RT-PCR showing pro-IL1B mRNA expression in control
(HVKp1 and HVKp2) and HPV-positive (HVK16 and HVK18) KCs. (B), IL-1b protein secretion of control (HFK1 and HFK2) and HPV-positive (HPV16,
HCK18 and HVK16) KCs as measured by ELISA. (C), TaqMan RT-PCR showing NLRP2 mRNA expression in HPV-negative (HFK1, HVK1, HVK2, HFK2) and
HPV-positive (HPV16, HCK18, HVK16 and HVK18) KCs. In all three panels, data are mean 6 SD, n=3.
Figure 5. HPVs deregulate a gene network in KCs. A network was constructed of 212 connected HPV signature genes using interaction data
curated from literature and high-throughput screens in Ingenuity Pathways Analysis. (A), Overlay with gene expression changes of 24 hrs of poly(I:C)-
stimulated HPV-positive KCs versus 24 hrs of poly(I:C)-stimulated HPV-negative KCs. (B), Zoom-in to central region of the network highlighting highly
interconnected genes. Molecules are represented as nodes, and the biological relationship between two nodes is represented as an edge (line).
Green, downregulated genes; red, upregulated genes; gray, not differentially expressed at the 24-hrs comparison; solid line, direct interaction; dashed
line, indirect interaction.
hrHPVs Suppress Immune Response in Keratinocytes
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(data not shown) suggesting that there may be a number of type-
specific interactions with the host’s immune system. Together
these data suggest that HPVs dampen but do not block PRR
signaling, and imply that the attraction of innate immune cells to
the site of HPV infection, the subsequent initiation of adaptive
immunity as well as the recognition of HPV-infected KCs is
slowed down but not prevented. This clearly corresponds with the
fact that it may take months or even a year to control HPV
infections , and the increase in HPV-infected subjects capable
of mounting an HPV-specific immune response in time .
Furthermore, it fits with the detection of HPV-specific memory
responses after infection [9,57,58].
In particular, we found that HPVs downregulated toll-like
receptor adaptor molecule 1 (TICAM1), a critical molecule in the
TLR3 pathway that mediates NF-kappa-B and interferon-
regulatory factor (IRF) activation via downstream molecules
TRAF3, TRAF6 and RIP1 . Notably, the other poly(I:C)
recognizing PRRs also malfunction in HPV-positive KCs
suggesting that HPVs affect the TBK1 and NF-kappa-B signaling
pathways downstream of the PRRs and implying that downreg-
ulation of TICAM1 is just part of the immune evasion strategy of
HPVs. This is also illustrated by our finding that HPVs
downregulated inflammasome components – needed to convert
pro-IL-1b to the active form of IL-1b  - contributing to the
lower secretion of IL-1b by HPV-positive cells. Of all candidate
downstream targets IRF1 , IRF3 , the coactivator CPB
, the IkB kinase complex , and the interferon-stimulated
gene factor 3 (ISGF3) transcription complex  have been
named as targets for either E6 and E7 proteins of HPV responsible
for downregulating NF-kappa-B and TBK1 signaling. Others,
however, have shown that E6 – instead of downregulating - may
promote NF-kappa-B signaling [26,64]. Importantly, all of these
studies relied on the overexpression of either one or both
oncoproteins, which is more relevant for our understanding of
HPV-transformed cells. The strength of our study lies in the use of
KCs with episomal expression of the full array of HPV genes
reflecting latent infection [28,29]. It would be of great importance
to perform a genome-wide study of HPV-positive KCs during
differentiation and interaction with (innate) immune cells thereby
closely mimicking the situation in situ, but such an experiment
would be technically challenging.
Non-cleared infection with high-risk HPVs leads to cervical and
other anogenital carcinomas in which the virus genome integrates
in the host genome [2,3]. The replication cycle of the virus is
tightly coupled to the differentiation of basal KCs to stratified
squamous epithelia and it is well known that HPVs inhibit KC
differentiation . In our expression data, this was reflected by
concerted upregulation of cell cycle regulators and DNA/RNA
synthesis, and downregulation of epidermis development and KC
differentiation genes. CDKN2A, a critical cell cycle regulator
upregulated by HPVs, was identified as one of the highly-
connected hub genes in the network of HPV signature genes.
Similar results were described by Nees et al. using a cDNA
We have shown that HPV16 and 18 dampen a cellular
immune-related network in HPV-positive KCs, and affect a much
broader spectrum of PRR responses than the previously described
IRF route. Our study provides a framework for future exploration
into the molecular mechanisms involved in HPV-downregulated
immunity. The biological variation in gene expression between
different donors might reflect genomic variation that could play a
role the balance between clearance and persistence of HPV.
Additionally, it would be of interest to study if other viruses
capable of causing persistent infection or low-risk HPVs that cause
benign genital warts use similar mechanisms to escape host’s
ation and PRR expression. (A), Reverse transcription PCR
detection of the small proline-rich protein 2A (SPRR2A), a
molecular marker of KC differentiation after 20, 25 and 30 PCR
cycles in undifferentiated (1), partially differentiated (2) and fully
differentiated (3) normal foreskin keratinocytes. SPRR2A expres-
sion was absent from undifferentiated KCs, low in Ca2+-treated
KCs and high in KCs cultured in suspension with Ca2+ and
methylcellulose, confirming that the KCs consisted of undifferen-
tiated (basal) cells and differentiated in vitro. (B), Reverse
transcription PCR detection of TLRs 1–10 and GAPDH (‘‘G’’)
in mRNA samples from Ramos B-cells and monocytes.
Positive controls for keratinocyte differenti-
progressively increases with KC differentiation stage. (A), Total
RNA of the indicated cells was subjected to RT-PCR (35 cycles)
with specific primers human TLR1–10 or GAPDH as indicated by
a ‘‘G’’. (B), TaqMan real-time PCR was performed for TLR9 on
total RNA samples from indicated cell types. TLR9 expression was
normalized against GAPDH mRNA levels. Data represent an
average of three independent experiments. (C), Immunohisto-
chemical staining of paraffin-embedded healthy foreskin sections
and (D) sections of healthy ectocervical epithelium with human
TLR9-specific monoclonal antibody (left panels) or isotype control
antibody (right panels) in combination with peroxidase-conjugated
secondary antibody. Cell nuclei were counterstained with
haematoxylin. Original magnification 1256. Stainings shown are
representative of at least three samples of different origin.
TLR9 expression in stratified squamous epithelia
positive cervical epithelial neoplasia. Immunohistochemical staining
with TLR9-specific or isotype control antibody of paraffin-embedded
sections of normal and dysplastic genital epithelia. Staining was
performed as described in the legend to Figure S2. Original
magnification 1256. Sections of the following epithelial samples are
shown: A) normal cervical epithelium, B) CIN1, C) CIN2.
TLR9 is expressed in differentiated cell layers of HPV-
pathway (KEGG hsa4620) overlaid with differentially expressed
genes between 24 hrs poly(I:C) stimulated and unstimulated
uninfected keratinocyte cultures. Differentially expressed genes
(FDR#0.05) were colored bright red (log2 fold change$1) or dim
red (log2 fold change between 0 and 1) for upregulation upon
poly(I:C) stimulation, or bright green (log2 fold change#21) or dim
green (log2 fold change between 0 and 21) for downregulation.
Grey boxes represent genes not fulfilling the above criteria, while
white boxes are genes not represented by probes on the array.
TLR signalling in KCs. Toll-like receptor signalling
signalling pathway (KEGG hsa4620) overlaid with differentially
expressed genes between 24 hrs poly(I:C) stimulated and un-
stimulated HPV-infected keratinocyte cultures. For explanation of
colors, see Figure S4.
TLR signalling in HPV-KCs. Toll-like receptor
hrHPVs Suppress Immune Response in Keratinocytes
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KCs. Toll-like receptor signalling pathway (KEGG hsa4620)
overlaid with differentially expressed genes between HPV-infected
and uninfected keratinocytes, both after 24 hrs poly(I:C) stimula-
tion. Differentially expressed genes (FDR#0.05) were colored
according to their log2 fold change (see legend Figure S4) for
upregulation (red) or downregulation (green) in HPV-positive cells.
Differential TLR signalling between HPV-KCs and
and signalling molecules in HPV-infected and uninfected kerati-
Differential expression of pattern recognition receptors
HPV signature genes.
HPV signature gene promoters.
Enrichment of transcription factor binding sites in
We thank Enno Dreef, Yavuz Ariyurek, and the Leiden Genome
Technology Center for excellent experimental assistance. We thank
Thomas Kelder and Martijn van Iersel for automatically extracted KEGG
pathways and GO terms and PathVisio beta software.
Conceived and designed the experiments: SHvdB CJMM G-JBvO RO RK
JMB. Performed the experiments: RK CM CB KL. Analyzed the data: RK
SHvdB JMB. Wrote the paper: RK SHvdB JMB. Critical revision of the
manuscript: RO CJMM GJBvO CM CB KL.
1. Ferlay J, Shin HR, Bray F, Forman D, Mathers C, et al. (2010) Estimates of
worldwide burden of cancer in 2008: GLOBOCAN 2008. Int J Cancer.
2. zur Hausen H (2009) Papillomaviruses in the causation of human cancers - a
brief historical account. Virology 384: 260–265.
3. Bosch FX, Manos MM, Munoz N, Sherman M, Jansen AM, et al. (1995)
Prevalence of human papillomavirus in cervical cancer: a worldwide perspective.
International biological study on cervical cancer (IBSCC) Study Group. J Natl
Cancer Inst 87: 796–802.
4. Richardson H, Kelsall G, Tellier P, Voyer H, Abrahamowicz M, et al. (2003)
The natural history of type-specific human papillomavirus infections in female
university students. Cancer Epidemiol Biomarkers Prev 12: 485–490.
5. Tindle RW (2002) Immune evasion in human papillomavirus-associated cervical
cancer. Nat Rev Cancer 2: 59–65.
6. Stanley M (2006) Immune responses to human papillomavirus. Vaccine 24
Suppl 1: S16–S22.
7. Woo YL, Sterling J, Damay I, Coleman N, Crawford R, et al. (2008)
Characterising the local immune responses in cervical intraepithelial neoplasia: a
cross-sectional and longitudinal analysis. BJOG 115: 1616–1621.
8. van Poelgeest MI, van Seters M, van Beurden M, Kwappenberg KM, Heijmans-
Antonissen C, et al. (2005) Detection of human papillomavirus (HPV) 16-specific
CD4+ T-cell immunity in patients with persistent HPV16-induced vulvar
intraepithelial neoplasia in relation to clinical impact of imiquimod treatment.
Clin Cancer Res 11: 5273–5280.
9. de Jong A, van Poelgeest MI, van der Hulst JM, Drijfhout JW, Fleuren GJ, et al.
(2004) Human papillomavirus type 16-positive cervical cancer is associated with
impaired CD4+ T-cell immunity against early antigens E2 and E6. Cancer Res
10. de Vos van Steenwijk P, Piersma SJ, Welters MJ, van der Hulst JM, Fleuren G,
et al. (2008) Surgery followed by persistence of high-grade squamous
intraepithelial lesions is associated with the induction of a dysfunctional
HPV16-specific T-cell response. Clin Cancer Res 14: 7188–7195.
11. Doorbar J (2006) Molecular biology of human papillomavirus infection and
cervical cancer. Clin Sci (Lond) 110: 525–541.
12. Hasan UA, Bates E, Takeshita F, Biliato A, Accardi R, et al. (2007) TLR9
expression and function is abolished by the cervical cancer-associated human
papillomavirus type 16. J Immunol 178: 3186–3197.
13. Kalali BN, Kollisch G, Mages J, Muller T, Bauer S, et al. (2008) Double-
stranded RNA induces an antiviral defense status in epidermal keratinocytes
through TLR3-, PKR-, and MDA5/RIG-I-mediated differential signaling.
J Immunol 181: 2694–2704.
14. Mempel M, Voelcker V, Kollisch G, Plank C, Rad R, et al. (2003) Toll-like
receptor expression in human keratinocytes: nuclear factor kappaB controlled
gene activation by Staphylococcus aureus is toll-like receptor 2 but not toll-like
receptor 4 or platelet activating factor receptor dependent. J Invest Dermatol
15. Lebre MC, van der Aar AM, van Baarsen L, van Capel TM, Schuitemaker JH,
et al. (2007) Human keratinocytes express functional Toll-like receptor 3, 4, 5,
and 9. J Invest Dermatol 127: 331–341.
16. Kollisch G, Kalali BN, Voelcker V, Wallich R, Behrendt H, et al. (2005) Various
members of the Toll-like receptor family contribute to the innate immune
response of human epidermal keratinocytes. Immunology 114: 531–541.
17. Andersen JM, Al-Khairy D, Ingalls RR (2006) Innate immunity at the mucosal
surface: role of toll-like receptor 3 and toll-like receptor 9 in cervical epithelial
cell responses to microbial pathogens. Biol Reprod 74: 824–831.
18. Hemmi H, Takeuchi O, Sato S, Yamamoto M, Kaisho T, et al. (2004) The roles
of two IkappaB kinase-related kinases in lipopolysaccharide and double stranded
RNA signaling and viral infection. J Exp Med 199: 1641–1650.
19. Lemaire PA, Lary J, Cole JL (2005) Mechanism of PKR activation: dimerization
and kinase activation in the absence of double-stranded RNA. J Mol Biol 345:
20. Pichlmair A, Schulz O, Tan CP, Naslund TI, Liljestrom P, et al. (2006) RIG-I-
mediated antiviral responses to single-stranded RNA bearing 59-phosphates.
Science 314: 997–1001.
21. Sankar S, Chan H, Romanow WJ, Li J, Bates RJ (2006) IKK-i signals through
IRF3 and NFkappaB to mediate the production of inflammatory cytokines. Cell
Signal 18: 982–993.
22. Yoneyama M, Kikuchi M, Matsumoto K, Imaizumi T, Miyagishi M, et al.
(2005) Shared and unique functions of the DExD/H-box helicases RIG-I,
MDA5, and LGP2 in antiviral innate immunity. J Immunol 175: 2851–2858.
23. zur Hausen H (2002) Papillomaviruses and cancer: from basic studies to clinical
application. Nat Rev Cancer 2: 342–350.
24. Park JS, Kim EJ, Kwon HJ, Hwang ES, Namkoong SE, et al. (2000) Inactivation
of interferon regulatory factor-1 tumor suppressor protein by HPV E7
oncoprotein. Implication for the E7-mediated immune evasion mechanism in
cervical carcinogenesis. J Biol Chem 275: 6764–6769.
25. Ronco LV, Karpova AY, Vidal M, Howley PM (1998) Human papillomavirus
16 E6 oncoprotein binds to interferon regulatory factor-3 and inhibits its
transcriptional activity. Genes Dev 12: 2061–2072.
26. Nees M, Geoghegan JM, Hyman T, Frank S, Miller L, et al. (2001)
Papillomavirus type 16 oncogenes downregulate expression of interferon-
responsive genes and upregulate proliferation-associated and NF-kappaB-
responsive genes in cervical keratinocytes. J Virol 75: 4283–4296.
27. Chang YE, Laimins LA (2000) Microarray analysis identifies interferon-
inducible genes and Stat-1 as major transcriptional targets of human
papillomavirus type 31. J Virol 74: 4174–4182.
28. McLaughlin-Drubin ME, Christensen ND, Meyers C (2004) Propagation,
infection, and neutralization of authentic HPV16 virus. Virology 322: 213–219.
29. Meyers C, Mayer TJ, Ozbun MA (1997) Synthesis of infectious human
papillomavirus type 18 in differentiating epithelium transfected with viral DNA.
J Virol 71: 7381–7386.
30. Pichlmair A, Schulz O, Tan CP, Naslund TI, Liljestrom P, et al. (2006) RIG-I-
mediated antiviral responses to single-stranded RNA bearing 59-phosphates.
Science 314: 997–1001.
31. Chiu YH, Macmillan JB, Chen ZJ (2009) RNA polymerase III detects cytosolic
DNA and induces type I interferons through the RIG-I pathway. Cell 138:
32. Ablasser A, Bauernfeind F, Hartmann G, Latz E, Fitzgerald KA, et al. (2009)
RIG-I-dependent sensing of poly(dA:dT) through the induction of an RNA
polymerase III-transcribed RNA intermediate. Nat Immunol 10: 1065–1072.
33. Fischer DF, Gibbs S, van De Putte P, Backendorf C (1996) Interdependent
transcription control elements regulate the expression of the SPRR2A gene
during keratinocyte terminal differentiation. Mol Cell Biol 16: 5365–5374.
34. Schaefer TM, Desouza K, Fahey JV, Beagley KW, Wira CR (2004) Toll-like
receptor (TLR) expression and TLR-mediated cytokine/chemokine production
by human uterine epithelial cells. Immunology 112: 428–436.
35. Cabral A, Voskamp P, Cleton-Jansen AM, South A, Nizetic D, et al. (2001)
Structural organization and regulation of the small proline-rich family of
cornified envelope precursors suggest a role in adaptive barrier function. J Biol
Chem 276: 19231–19237.
36. Lin SM, Du P, Huber W, Kibbe WA (2008) Model-based variance-stabilizing
transformation for Illumina microarray data. Nucleic Acids Res 36: e11.
37. Du P, Kibbe WA, Lin SM (2008) lumi: a pipeline for processing Illumina
microarray. Bioinformatics 24: 1547–1548.
38. Du P, Kibbe WA, Lin SM (2007) nuID: a universal naming scheme of
oligonucleotides for illumina, affymetrix, and other microarrays. Biol Direct 2: 16.
hrHPVs Suppress Immune Response in Keratinocytes
PLoS ONE | www.plosone.org 11 March 2011 | Volume 6 | Issue 3 | e17848
39. Smyth GK (2005) Limma: linear models for microarray data. In: Gentleman R,
Carey V, Dudoit S, Irizarry R, Huber W, eds. Bioinformatics and
Computational Biology Solutions using R and Bioconductor. New York:
Springer. pp 397–420.
40. Benjamini Y, Hochberg Y (1995) Controlling the False Discovery Rate - A
Practical and Powerful Approach to Multiple Testing. Journal of the Royal
Statistical Society Series B-Methodological 57: 289–300.
41. Jelier R, Schuemie MJ, Veldhoven A, Dorssers LC, Jenster G, et al. (2008) Anni
2.0: a multipurpose text-mining tool for the life sciences. Genome Biol 9: R96.
42. Salomonis N, Hanspers K, Zambon AC, Vranizan K, Lawlor SC, et al. (2007)
GenMAPP 2: new features and resources for pathway analysis. BMC
Bioinformatics 8: 217.
43. Kanehisa M, Goto S, Kawashima S, Okuno Y, Hattori M (2004) The KEGG
resource for deciphering the genome. Nucleic Acids Res 32: D277–D280.
44. van Iersel MP, Kelder T, Pico AR, Hanspers K, Coort S, et al. (2008) Presenting
and exploring biological pathways with PathVisio. BMC Bioinformatics 9: 399.
45. Pico AR, Kelder T, van Iersel MP, Hanspers K, Conklin BR, et al. (2008)
WikiPathways: pathway editing for the people. PLoS Biol 6: e184.
46. Hestand MS, van Galen M, Villerius MP, van Ommen GJ, den Dunnen JT,
et al. (2008) CORE_TF: a user-friendly interface to identify evolutionary
conserved transcription factor binding sites in sets of co-regulated genes. BMC
Bioinformatics 9: 495.
47. Alibes A, Yankilevich P, Canada A, az-Uriarte R (2007) IDconverter and
IDClight: conversion and annotation of gene and protein IDs. BMC
Bioinformatics 8: 9.
48. Pivarcsi A, Koreck A, Bodai L, Szell M, Szeg C, et al. (2004) Differentiation-
regulated expression of Toll-like receptors 2 and 4 in HaCaT keratinocytes.
Arch Dermatol Res 296: 120–124.
49. Kawai T, Takahashi K, Sato S, Coban C, Kumar H, et al. (2005) IPS-1, an
adaptor triggering RIG-I- and Mda5-mediated type I interferon induction. Nat
Immunol 6: 981–988.
50. Woodworth CD, Cheng S, Simpson S, Hamacher L, Chow LT, et al. (1992)
Recombinant retroviruses encoding human papillomavirus type 18 E6 and E7
genes stimulate proliferation and delay differentiation of human keratinocytes
early after infection. Oncogene 7: 619–626.
51. Harder J, Schroder JM (2002) RNase 7, a novel innate immune defense
antimicrobial protein of healthy human skin. J Biol Chem 277: 46779–46784.
52. Zhang J, Dyer KD, Rosenberg HF (2003) Human RNase 7: a new cationic
ribonuclease of the RNase A superfamily. Nucleic Acids Res 31: 602–607.
53. Calvano SE, Xiao W, Richards DR, Felciano RM, Baker HV, et al. (2005) A
network-based analysis of systemic inflammation in humans. Nature 437:
54. Ghiringhelli F, Apetoh L, Tesniere A, Aymeric L, Ma Y, et al. (2009) Activation
of the NLRP3 inflammasome in dendritic cells induces IL-1beta-dependent
adaptive immunity against tumors. Nat Med 15: 1170–1178.
55. Becker CE, O’Neill LA (2007) Inflammasomes in inflammatory disorders: the
role of TLRs and their interactions with NLRs. Semin Immunopathol 29:
56. Woo YL, van den Hende M, Sterling JC, Coleman N, Crawford RA, et al.
(2010) A prospective study on the natural course of low-grade squamous
intraepithelial lesions and the presence of HPV16 E2-, E6- and E7-specific T-cell
responses. Int J Cancer 126: 133–141.
57. Welters MJ, de Jong A, van den Eeden SJ, van der Hulst JM, Kwappenberg KM,
et al. (2003) Frequent display of human papillomavirus type 16 E6-specific
memory t-Helper cells in the healthy population as witness of previous viral
encounter. Cancer Res 63: 636–641.
58. de Jong A, van der Burg SH, Kwappenberg KM, van der Hulst JM,
Franken KL, et al. (2002) Frequent detection of human papillomavirus 16 E2-
specific T-helper immunity in healthy subjects. Cancer Res 62: 472–479.
59. O’Neill LA, Bowie AG (2007) The family of five: TIR-domain-containing
adaptors in Toll-like receptor signalling. Nat Rev Immunol 7: 353–364.
60. Petrilli V, Dostert C, Muruve DA, Tschopp J (2007) The inflammasome: a
danger sensing complex triggering innate immunity. Curr Opin Immunol 19:
61. Huang SM, McCance DJ (2002) Down regulation of the interleukin-8 promoter
by human papillomavirus type 16 E6 and E7 through effects on CREB binding
protein/p300 and P/CAF. J Virol 76: 8710–8721.
62. Spitkovsky D, Hehner SP, Hofmann TG, Moller A, Schmitz ML (2002) The
human papillomavirus oncoprotein E7 attenuates NF-kappa B activation by
targeting the Ikappa B kinase complex. J Biol Chem 277: 25576–25582.
63. Barnard P, McMillan NA (1999) The human papillomavirus E7 oncoprotein
abrogates signaling mediated by interferon-alpha. Virology 259: 305–313.
64. An J, Mo D, Liu H, Veena MS, Srivatsan ES, et al. (2008) Inactivation of the
CYLD deubiquitinase by HPV E6 mediates hypoxia-induced NF-kappaB
activation. Cancer Cell 14: 394–407.
hrHPVs Suppress Immune Response in Keratinocytes
PLoS ONE | www.plosone.org12 March 2011 | Volume 6 | Issue 3 | e17848