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KSHV co-infection down-regulates HPV16 E6 and E7 from cervical cancer cells

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Oncotarget. 2017; 8:35792-35803. https://doi.org/10.18632/oncotarget.16207

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Lu Dai, Yueyu Cao, Wei Jiang, Jovanny Zabaleta, Zhongmin Liu, Jing Qiao and Zhiqiang Qin _

Abstract

Lu Dai1,2,4, Yueyu Cao2, Wei Jiang3, Jovanny Zabaleta5, Zhongmin Liu2, Jing Qiao1, Zhiqiang Qin1,2,4

1Department of Pediatrics, East Hospital, Tongji University School of Medicine, Shanghai 200120, China

2Research Center for Translational Medicine and Key Laboratory of Arrhythmias, East Hospital, Tongji University School of Medicine, Shanghai 200120, China

3Department of Microbiology and Immunology, Division of Infectious Diseases, Department of Medicine, Medical University of South Carolina, Charleston, SC 29425, USA

4Departments of Genetics Louisiana State University Health Sciences Center, Louisiana Cancer Research Center, New Orleans, LA 70112, USA

5Pediatrics, Louisiana State University Health Sciences Center, Louisiana Cancer Research Center, New Orleans, LA 70112, USA

Correspondence to:

Jing Qiao, email: qiaoj123@hotmail.com

Zhiqiang Qin, email: zqin@lsuhsc.edu

Keywords: HPV, KSHV, E6, E7, microRNA

Received: February 14, 2017     Accepted: March 07, 2017     Published: March 15, 2017

ABSTRACT

High-risk human papillomavirus (HPV) infection is the etiological agent of some malignancies such as cervical, oral and oropharyngeal cancers. Kaposi sarcoma-associated herpesvirus (KSHV) represents a principal causative agent of several human cancers arising in those immunocompromised patients. Interestingly, KSHV DNA has been detected in the oral cavity and the female genital tract, although its detection rate in cervical samples is very low and few reports are about KSHV/HPV co-infection. Therefore, it remains unclear about the role of KSHV co-infection in the development of HPV-related neoplasias. In the current study, we report that HPV16-integrated cervical cancer cell-line SiHa is susceptible to KSHV latent infection and replication. We also have found that KSHV infection or viral latent proteins are capable of reducing HPV16 E6/E7 expression through the manipulation of cellular microRNA function. Array analysis indicates that KSHV infection induces some inflammatory cytokines/chemokines production as well as up-regulates a series of interferon-induced genes expression, which may facilitate host immune defense system attacking these co-infected cells and clearance of viruses. Together, our data have provided possible explanations for very low detection rate of KSHV shedding as well as of KSHV/HPV co-infection in cervical samples and/or cervical cancer cells.


KSHV co-infection down-regulates HPV16 E6 and E7 from cervical cancer cells | Dai | Oncotarget

INTRODUCTION

Cervical cancer represents one of the most common malignancies in females worldwide. The pathogenesis of cervical cancer occurs following persistent infection with high-risk human papillomavirus (HPV) such as subtype 16 and 18 [1]. High-risk HPV-encoded E6 and E7 proteins are major viral oncoproteins which are closely associated with human cervical carcinogenesis [2]. E6 and E7 can bind to the p53 and retinoblastoma (Rb) family proteins, respectively, resulting in the regulation of cell cycle and final transformation [3]. In addition, high-risk HPV infection is also prevalent in oral cavity and related to oral and oropharyngeal cancer development [46].

Another oncogenic virus, Kaposi sarcoma-associated herpesvirus (KSHV) represents a principal causative agent of several human cancers arising in those immunocompromised patients, including Kaposi’s Sarcoma (KS), Primary effusion lymphoma (PEL) and Multicentric Castleman’s disease (MCD) [79]. Published literatures have reported that KSHV DNA sequences can be detected in the prostate [10], semen [11], oral cavity [12] and the female genital tract [13, 14]. Moreover, person-to-person transmission of KSHV is thought to occur primarily through exchange of oropharyngeal secretions [15]. In contrast to the high prevalence of KSHV shedding in oral cavity, the detection rate of KSHV DNA or virus infection in cervical samples are relatively low (< 2%), even in those high-risk population such as sex workers and HIV+ persons [14, 16]. Furthermore, currently there are few studies reporting the co-infection of KSHV and HPV in cervical samples and/or cervical cancer cells. Therefore, it remains unclear about the role of KSHV co-infection in the development of HPV-related neoplasias. In the current study, we tested the susceptibility of HPV16-integrated cervical cancer cell-line SiHa to KSHV infection, replication and their impacts on HPV-encoded oncoproteins expression. Interestingly, we found that KSHV de novo infection or viral latent proteins significantly reduced HPV16 E6/E7 expression through the manipulation of cellular microRNA function. We also found that KSHV infection induced some inflammatory cytokines/chemokines production as well as up-regulated a series of interferon-induced genes expression, which may facilitate host immune defense system attacking these co-infected cells and clearance of viruses.

RESULTS

KSHV can establish latent infection within SiHa cells and possess replicative potential

Latent KSHV infection is dependent upon intranuclear expression of KSHV-encoded latency associated nuclear antigen (LANA), which tethers viral episome to host cell chromatin [17]. To first determine whether SiHa cells are susceptible to KSHV infection, we incubated them with purified KSHV virions and used immunofluorescence (IFA) to quantify LANA expression within individual cells. The confocal microscopy images revealed LANA expression within > 95% of SiHa cell nuclear following 72 h post infection (p.i.) with an MOI ~10, while no LANA dots observed in the control mock cells (Figure 1). To further validate replicative potential of these viruses in latently infected SiHa cells, we treated infected cells with valproic acid (VA) for 5 days, a common chemical inducing viral lytic reactivation [18]. Then we used qRT-PCR to quantify the transcripts of representative viral latent and lytic genes. Our results indicated VA treatment greatly induced different viral lytic genes expression (RTA, vGPCR, K8.1 and ORF57), while dramatically reducing latent gene LANA expression from infected SiHa cells (Figure 2A). Immunoblots analysis confirmed the elevated expression of K8.1, one of lytic proteins by VA (Figure 2B). Furthermore, we found that VA induced infected SiHa cells release of infectious KSHV particles in culture supernatants, as demonstrated by increased LANA expression within fresh KSHV-naïve cells following their exposure to VA-treated SiHa supernatants (Figure 2C). Together, our data demonstrate that SiHa are susceptible to KSHV latent infection and these viruses are capable of self-replication once stimulated to lytic reactivation.

Establishment of latent KSHV infection within SiHa cells.

Figure 1: Establishment of latent KSHV infection within SiHa cells. SiHa were incubated with purified KSHV (MOI~10), or medium control (mock) for 2 h. After cells were incubated for an additional 72 h in fresh media, immunofluorescence was performed to quantify expression of KSHV-encoded LANA as indicated by the typical intranuclear, punctate staining pattern (red dots). Nuclei were identified using DAPI (blue). Bars, 20 μm.

Induction of lytic reactivation and virus production from KSHV latently infected SiHa cells.

Figure 2: Induction of lytic reactivation and virus production from KSHV latently infected SiHa cells. (AB) KSHV latently infected SiHa cells were incubated with 0.6 mM valproic acid (VA) or vehicle for 5 days, then qRT-PCR and immunoblots were performed as described in the Methods. (C) The virion production was collected as described in the Methods, followed by infection of fresh SiHa cells. Lana transcripts were quantified by using qRT-PCR. Error bars represent the S.D. for 3 independent experiments, **= p < 0.01.

Global signature of cellular cytokine/chemokine altered within KSHV-infected SiHa cells

By using a cytokine/chemokine array, we identified a global signature altered within KSHV-infected SiHa when compared to the control mock cells. We found that KSHV infection increased several inflammatory factors production from SiHa cells, including Chemokine (C-X-C motif) ligand 1 (CXCL1), Interleukin 6 (IL-6), Plasminogen activator inhibitor-1 (PAI-1), Chemokine (C-C motif) ligand 5 (CCL5), Interleukin 8 (IL-8) and Macrophage migration inhibitory factor (MIF) (Figure 3). Our additional data have demonstrated KSHV infection does not affect SiHa cell growth and viability (Supplementary Figure 1), therefore which is not responsible for the increased cytokines/chemokines production we have observed.

Cytokine/chemokine profile altered within KSHV latently infected SiHa cells.

Figure 3: Cytokine/chemokine profile altered within KSHV latently infected SiHa cells. (A) SiHa were incubated with purified KSHV (MOI ~ 10), or medium control (mock) as describe above, then the supernatants were collected and the concentrations of different cytokines/chemokines were measured as described in the Methods. (B) The density of dot-blot was scanned and quantified by using the ImageJ software. Ref: reference positive control wells; Neg: negative control wells.

The down-regulation of HPV16 E6 and E7 by KSHV and/or viral latent proteins

SiHa cells contain an integrated HPV16 genome, and E6/E7 represent major HPV-encoded oncogenic proteins [1, 2]. Interestingly, our data indicated that KSHV infection significantly reduced both E6 and E7 expression from SiHa cells (Figure 4A). In contrast to this, VA treatment abolished this reduction, implying the important role of KSHV-encoded latent proteins in this regulation (Figure 4B). To prove that, we ectopically expressed LANA and vFLIP (viral FLICE inhibitory protein), two major KSHV-encoded latent proteins in SiHa cells using the recombinant constructs, respectively. We found that ectopic expression of either LANA or vFLIP effectively down-regulated E6 and E7 expression in a dose-dependent manner (Figure 4C4D).

The down-regulation of HPV16 E6 and E7 by KSHV and/or viral latent proteins.

Figure 4: The down-regulation of HPV16 E6 and E7 by KSHV and/or viral latent proteins. (AB) SiHa cells were infected by KSHV or induced lytic reactivation as described above, then gene transcripts were quantified by using qRT-PCR. (CD) SiHa were transfected with control vector pcDNA3.1 (pc), pcDNA3.1-LANA (pcLANA) or pcDNA3.1-vFLIP (pcvFLIP) as described in the Methods, then gene transcripts were quantified by using qRT-PCR. The Error bars represent the S.D. for 3 independent experiments, **= p < 0.01.

The up-regulation of miR129-5p is required for KSHV/viral proteins reducing E6 and E7 expression

We subsequently sought to determine how KSHV infection and/or viral latent proteins reducing E6 and E7 expression. One of potential mechanisms is through cellular microRNAs such as miRNA129-5p and miRNA331-3p [19, 20]. Zhang et al. have reported that interferon-β treatment can induce miRNA129-5p, while its levels gradually decrease with the development of cervical intraepithelial lesions and correlate with E6 and E7 expression [19]. Another group has found that miRNA331-3p can suppress cervical cancer cell proliferation and E6/E7 expression by targeting Neuropilin 2 (NRP2) [20]. So we tested these 2 cellular microRNAs expression in SiHa cells. We found that either KSHV infection or ectopic expression of LANA or vFLIP significantly increased miRNA129-5p but not miRNA331-3p from SiHa cells (Figure 5A5B). We next used specific miRNA129-5p inhibitor to block its activities (Supplementary Figure 2), which effectively restored E6/E7 expression from KSHV-infected or LANA-/vFLIP-transfected SiHa cells (Figure 5C5E). These data demonstrate that miRNA129-5p but not miRNA331-3p is required for KSHV and/or viral latent proteins reducing E6/E7 expression from SiHa cells.

The up-regulation of miR129-5p is required for KSHV/viral latent proteins reducing HPV16 E6 and E7 expression.

Figure 5: The up-regulation of miR129-5p is required for KSHV/viral latent proteins reducing HPV16 E6 and E7 expression. (AB) SiHa cells were infected by KSHV or transfected using LANA or vFLIP recombinant constructs as described above, then miRNAs transcripts were quantified by using qRT-PCR. (CE) SiHa cells were transfected with control or miR129-5p inhibitor prior to KSHV infection or ectopic expression of LANA or vFLIP, then gene transcripts were quantified by using qRT-PCR. The Error bars represent the S.D. for 3 independent experiments, *= p < 0.05, **= p < 0.01.

Transcriptomic analysis of the gene profile altered in KSHV-infected SiHa cells

We used the HumanHT-12 v4 Expression BeadChip (Illumina), which contains more than 47,000 probes derived from the NCBI RefSeq Release 38 and other sources, to study the gene profile altered within KSHV-infected SiHa cells. We found that 71 genes were significantly up-regulated and 27 were down-regulated (≥ 2 fold and p < 0.05) within KSHV-infected SiHa cells when compared to the control mock cells (Tables 1 and 2). For validation of microarray analysis, we next selected 5 candidate genes from Tables 1 and 2, respectively, to perform qRT-PCR analysis. Our results indicated that all of the 10 selected genes were significantly altered in a manner comparable to those found in the microarray data, demonstrating the credibility of our results. Specifically, IFI27, KRT34, IL6, CEMIP and MX1 were significantly up-regulated, while AKR1C3, SEMA3C, ATOH8, ALDH3A1 and CRIP2 were significantly down-regulated within KSHV-infected SiHa cells (Supplementary Figure 3). We also performed enrichment analysis of these significantly altered candidates by using the Pathway Maps, Gene Ontology (GO) Processes and Process Networks modules from Metacore Software (Thompson Reuters). Our analysis showed that these significantly altered candidates belong to several major functional categories, including cellular response to type I interferon (IFN), defense response to virus infection/replication, cellular response to stress and inflammation (Figure 6). In addition, the top 2 scored pathway maps and protein networks were also listed in Supplementary Figures 4 and 5, respectively. Notably, we found that KSHV infection induced strong cellular response to type I IFN, especially those IFN-induced genes expression. Our qRT-PCR data confirmed that a series of 10 IFN-induced genes were significantly up-regulated from KSHV-infected SiHa cells when compared to the control mock cells (Figure 7).

Table 1: The genes up-regulated within KSHV-infected SiHa cells

Gene Symbol

Description

Ratio

IFI27

Interferon alpha-inducible protein 27, mitochondrial

13.24683

KRT34

Keratin, type I cuticular Ha4

10.96868

IL6

Interleukin-6

6.189084

CEMIP

Cell migration-inducing and hyaluronan-binding protein

4.637684

MX2

Interferon-induced GTP-binding protein Mx2

4.297035

EPSTI1

Epithelial-stromal interaction protein 1

3.975506

RSAD2

Radical S-adenosyl methionine domain-containing protein 2

3.695813

MX1

Interferon-induced GTP-binding protein Mx1

3.616665

DHRS2

Dehydrogenase/reductase SDR family member 2, mitochondrial

3.584949

CXCL8

Interleukin-8

3.533108

HIST1H4H

Histone H4

3.443781

NT5E

5′-nucleotidase

3.408309

ISG15

Ubiquitin-like protein ISG15

3.371505

IGF2BP2

Insulin-like growth factor 2 mRNA-binding protein 2

3.326956

NKD2

Protein naked cuticle homolog 2

3.230526

GADD45A

Growth arrest and DNA damage-inducible protein GADD45 alpha

3.21191

OASL

2′-5′-oligoadenylate synthase-like protein

3.158974

USP18

Ubl carboxyl-terminal hydrolase 18

3.0996

STC2

Stanniocalcin-2

2.99668

RASD1

Dexamethasone-induced Ras-related protein 1

2.964571

LINC00161

long intergenic non-protein coding RNA 161 transcript

2.940959

IFIT1

Interferon-induced protein with tetratricopeptide repeats 1

2.915374

PPP1R15A

Protein phosphatase 1 regulatory subunit 15A

2.883852

IFIT2

Interferon-induced protein with tetratricopeptide repeats 2

2.849808

IFI44

Interferon-induced protein 44

2.807813

RELB

Transcription factor RelB

2.803865

AP-1

Transcription factor AP-1

2.746863

PLD6

Mitochondrial cardiolipin hydrolase

2.714222

SNHG15

small nucleolar RNA host gene 15 transcript

2.642434

PHLDA1

Pleckstrin homology-like domain family A member 1

2.604317

IFIT3

Interferon-induced protein with tetratricopeptide repeats 3

2.598199

RIMKLB

Beta-citrylglutamate synthase B

2.581286

OAS1

2′-5′-oligoadenylate synthetase 1

2.571998

LRP5L

Low-density lipoprotein receptor-related protein 5-like protein

2.488861

CCND1

G1/S-specific cyclin-D1

2.451345

DUSP5

Dual specificity protein phosphatase 5

2.441991

OLR1

Oxidized low-density lipoprotein receptor 1

2.431704

LOC285074

Anaphase promoting complex subunit 1 pseudogene

2.369141

CCL5

C-C motif chemokine 5

2.359643

IFI6

Interferon alpha-inducible protein 6

2.327306

CTGF

Connective tissue growth factor

2.324625

SLCO2A1

Solute carrier organic anion transporter family member 2A1

2.321616

DDIT3

DNA damage-inducible transcript 3 protein

2.312649

MAFF

Transcription factor MafF

2.29661

OTUD1

OTU domain-containing protein 1

2.268293

SNHG12

Putative uncharacterized protein SNHG12

2.267007

TUBB2B

Tubulin beta-2B chain

2.262177

ETV5

ETS translocation variant 5

2.257368

PMAIP1

Phorbol-12-myristate-13-acetate-induced protein 1

2.244876

HIST1H4D

Histone H4

2.243342

WARS

Tryptophan--tRNA ligase, cytoplasmic

2.23195

PDP1

[Pyruvate dehydrogenase [acetyl-transferring]]-phosphatase 1, mitochondrial

2.217114

OAS2

2′-5′-oligoadenylate synthetase 2

2.199281

ASNS

Asparagine synthetase [glutamine-hydrolyzing]

2.19681

LINC01554

Putative uncharacterized protein encoded by LINC01554

2.158002

NR2C1

Nuclear receptor subfamily 2 group C member 1

2.154326

KRT16

Keratin, type I cytoskeletal 16

2.144548

EPB41L4A-AS1

EPB41L4A antisense RNA 1 transcript

2.143205

GADD45B

Growth arrest and DNA damage-inducible protein GADD45 beta

2.142809

HIST1H2BC

Histone H2B type 1-C/E/F/G/I

2.140187

SLC15A3

Solute carrier family 15 member 3

2.117546

ERRFI1

ERBB receptor feedback inhibitor 1

2.112755

HIST1H4E

Histone H4

2.108247

TAF1D

TATA box-binding protein-associated factor RNA polymerase I subunit D

2.108209

IFITM1

Interferon-induced transmembrane protein 1

2.096043

SNAPC4

snRNA-activating protein complex subunit 4

2.059977

ARNT2

Aryl hydrocarbon receptor nuclear translocator 2

2.028269

SNHG1

small nucleolar RNA host gene 1 transcript

2.01646

RHOB

Rho-related GTP-binding protein RhoB

2.015713

HELZ2

Helicase with zinc finger domain 2

2.015691

NFIL3

Nuclear factor interleukin-3-regulated protein

2.014101

Table 2: The genes down-regulated within KSHV-infected SiHa cells

Gene Symbol

Description

Ratio

AKR1C3

Aldo-keto reductase family 1 member C3

0.273224

KRT19

Keratin, type I cytoskeletal 19

0.297783

SBSPON

Somatomedin-B and thrombospondin type-1 domain-containing protein

0.339295

SEMA3C

Semaphorin-3C

0.350578

ATOH8

Protein atonal homolog 8

0.370948

SPTSSA

Serine palmitoyltransferase small subunit A

0.376402

SYNC

Syncoilin

0.379147

ALDH3A1

Aldehyde dehydrogenase, dimeric NADP-preferring

0.383731

COBLL1

Cordon-bleu protein-like 1

0.399284

DDIT4L

DNA damage-inducible transcript 4-like protein

0.40746

MPZL2

Myelin protein zero-like protein 2

0.408897

ADIRF

Adipogenesis regulatory factor

0.416268

CRIP2

Cysteine-rich protein 2

0.417072

ARL6IP5

PRA1 family protein 3

0.420077

ALPP

Alkaline phosphatase, placental type

0.423014

HEATR5A

HEAT repeat-containing protein 5A

0.427246

QPCT

Glutaminyl-peptide cyclotransferase

0.427804

CLIC3

Chloride intracellular channel protein 3

0.431867

GLS

Glutaminase kidney isoform, mitochondrial

0.445419

TNS3

Tensin-3

0.458781

RHOBTB3

Rho-related BTB domain-containing protein 3

0.463897

IDH1

Isocitrate dehydrogenase [NADP] cytoplasmic

0.469876

C14orf132

Uncharacterized protein C14orf132

0.476645

TIMP3

Metalloproteinase inhibitor 3

0.478399

CD14

Monocyte differentiation antigen CD14

0.488419

CXXC5

CXXC-type zinc finger protein 5

0.491275

SUMF1

Sulfatase-modifying factor 1

0.492325

The enrichment analysis of gene profile alterations in KSHV-infected SiHa cells.

Figure 6: The enrichment analysis of gene profile alterations in KSHV-infected SiHa cells. (AC) The enrichment analysis of gene profile significantly altered (up/down ≥ 2 fold and p < 0.05) in KSHV-infected SiHa cells was performed using the Metacore Software (Thompson Reuters) Modules: Pathway Maps (A), Gene Ontology Processes (B), and Process Networks (C).

The up-regulation of interferon-induced genes from KSHV-infected SiHa cells.

Figure 7: The up-regulation of interferon-induced genes from KSHV-infected SiHa cells. SiHa cells were infected by KSHV as described above, then gene transcripts were quantified by using qRT-PCR. The Error bars represent the S.D. for 3 independent experiments, *= p < 0.05, **= p < 0.01.

DISCUSSION

To our knowledge, this is the first study reporting KSHV infection and/or viral latent proteins can down-regulate HPV16 E6 and E7 expression from cervical cancer cells. We also have found the underlying mechanism is through the down-regulation of at least one cellular microRNA, miRNA129-5p, although some other mechanisms are possibly involved as well. Interestingly, the down-regulation of E6 and E7 expression usually causes the suppression of cervical cancer cell proliferation and the promotion of cancer cell apoptosis [1922]. However, we do not observe that KSHV infection can affect SiHa cell proliferation or viability, implying that some KSHV-related factors (viral or host) may compensate the effects of down-regulation of HPV16 E6 and E7 on cancer cell growth. Instead, we have found that KSHV infection greatly reduced SiHa cell invasiveness when compared to the control mock cells (data not shown). It remains unclear whether this down-regulation of E6 and E7 by KSHV is cell-line or HPV subtype specific, although we have reported that KSHV can establish latent infection within HPV18-integrated HeLa cells as well [23]. So we will test the susceptibility of other HPV+ cervical cancer cell-lines to KSHV infection, replication and their impacts on HPV-encoded oncoproteins such as E6 and E7.

One remaining question is the mechanisms through which miRNA129-5p inhibiting E6 and E7 expression. Zhang et al. have reported that the transcription factor SP1 is a direct downstream target of miR-129-5p in Hela cells, and SP1 expression is down-regulated significantly by over-expressed miR-129-5p [19]. Interestingly, the upstream regulatory regions of HPV-18 genes contain the SP1 binding site, which have been shown to determine E6 and E7 expression [24, 25]. So future work will try to determine whether the similar mechanisms are present in SiHa cells, or whether E6 and E7 are direct targets by miR-129-5p. Another interesting question is how KSHV infection can manipulate miR-129-5p expression in SiHa cells. In fact, KSHV infection or viral proteins have been found to regulate a variety of cellular microRNAs expression [26]. For instance, Tsai and colleagues have reported that KSHV-encoded K15 protein, minor form named as K15M, can induce cell migration and invasion through the up-regulation of cellular miR-21 and miR-31 via its conserved Src-Homology 2 (SH2)-binding motif [27]. KHSV infection and ectopic expression of vFLIP can suppress the expression of one chemokine receptor, CXCR4, through the up-regulation of cellular miR-146a expression, a miRNA that is known to bind to the 3’UTR of CXCR4 mRNA [28].

In the present study, we have found that KSHV de novo infection can induce some inflammatory cytokines/chemokines production from SiHa cells. Interestingly, one of these factors, CXCL1 (also named as growth regulated oncogene 1, GRO-1), its serum levels were significantly higher in patients with cervical squamous cell carcinoma (CSCC) when compared with patients with cervical intraepithelial neoplasia (CIN) and the healthy controls [29]. However, these up-regulated inflammatory cytokines/chemokines may promote the recruitment of immune cells such as neutrophils and macrophages, enhance local inflammatory response, and finally facilitate attacking infected cells and/or the clearance of viruses. Another interesting finding in our study is that KSHV infection up-regulates a series of IFN-induced genes expression from SiHa cells. We actually have observed similar responses within KSHV-infected human primary oral fibroblasts [30]. As we know, high-risk HPV infection down-regulates IFNα-inducible gene expression, for example, the HPV16 E6 and E7 oncoproteins interact directly with the components of the IFN signaling pathways [31]. Since IFN has been widely used in the treatment of CIN and cervical cancer, the down-regulation of E6 and E7 expression may be responsible for the positive clinical outcomes observed with IFN treatment [19]. Therefore, our data suppose that KSHV co-infection may arouse IFN signaling pathway activities to accelerate virus clearance by host immune system. Taken together, our data have provided possible explanations for very low detection rate of KSHV shedding as well as of KSHV/HPV co-infection in cervical samples and/or cervical cancer cells.

MATERIALS AND METHODS

Cell culture and KSHV purification/infection

Body cavity-based lymphoma cells (BCBL-1, KSHV+/EBVneg) were kindly provided by Dr. Dean Kedes (University of Virginia) and maintained in RPMI 1640 medium (Gibco) with supplements as described previously [32]. SiHa cells were purchased from ATCC and maintained in Eagle’s Minimum Essential Medium (ATCC) supplemented with 10% FBS. All cells were incubated at 37°C in 5% CO2. All experiments were carried out using cells harvested at low passages (< 20). To obtain KSHV for infection experiments, BCBL-1 cells were incubated with 0.6 mM valproic acid for 6 days, and purified virus was concentrated from culture supernatants and infectious titers were determined as described previously [33].

Human cytokine/chemokine array

The human cytokine/chemokine array was performed by using Proteome ProfilerTM Array (R&D Systems) which contains 36 different human cytokines according to the manufacturers’ instructions. The density of dot-blot was scanned and quantified by using the ImageJ software.

Microarray

Microarray analysis was performed and analyzed at the Stanley S. Scott Cancer Center’s Translational Genomics Core at LSUHSC. Total RNA was isolated using Qiagen RNeasy kit (Qiagen), and 500 ng of total RNA was used to synthesize dscDNA. Biotin-labeled RNA was generated using the TargetAmp-Nano Labeling Kit for Illumina Expression BeadChip (Epicentre), and hybridized to the HumanHT-12 v4 Expression BeadChip (Illumina) at 58°C for 16 h. The chip was washed, stained with streptavadin-Cy3, and scanned with the Illumina BeadStation 500 and BeadScan. Using the Illumina’s GenomeStudio software, we normalized the signals using the “cubic spline algorithm” that assumes that the distribution of transcript abundance is similar in all samples. The background signal was removed using the “detection p-value algorithm” to remove targets with signal intensities equal or lower than that of irrelevant probes (with no known targets in the human genome but thermodynamically similar to the relevant probes). The microarray experiments were performed twice for each group and the average values were used for analysis. The enrichment analysis were performed using the MetaCore Software (Thompson Reuters). The microarray original data have been submitted to Gene Expression Omnibus (GEO) database (Accession number: GSE90039).

Cell proliferation and apoptosis assays

Cell proliferation was measured by using the WST-1 assays (Roche) according to the manufacturers’ instructions. Flow cytometry was used for quantitative assessment of apoptosis using the FITC-Annexin V/propidium iodide (PI) Apoptosis Detection Kit I (BD Pharmingen).

Immunoblotting

Total cell lysates (20 μg) were resolved by 10% SDS–PAGE, transferred to nitrocellulose membranes, and immunoblotted with antibodies for K8.1 (ABI) and β-Actin (Sigma) for loading controls. Immunoreactive bands were identified using an enhanced chemiluminescence reaction (Perkin-Elmer), and visualized by autoradiography.

Immunofluorescence

Cells were incubated in 1:1 methanol-acetone at −20°C for fixation and permeabilization, then with a blocking reagent (10% normal goat serum, 3% bovine serum albumin, and 1% glycine) for an additional 30 minutes. Cells were then incubated for 1 h at 25°C with 1:1000 dilution of a rat anti-LANA monoclonal antibody (ABI) followed by 1:200 dilution of a goat anti-rat secondary antibody conjugated to Texas Red (Invitrogen). For identification of nuclei, cells were subsequently counterstained with 0.5 mg/mL 4′,6-diamidino-2-phenylindole (DAPI; Sigma) in 180 mM Tris-HCl (pH 7.5). Slides were washed once in 180 mM Tris-HCl for 15 min and prepared for visualization using a Leica TCPS SP5 AOBS confocal microscope.

Transfection assays

For plasmid transfection, SiHa were transfected with control vector pcDNA3.1, pcDNA3.1-LANA (pcLANA) or pcDNA3.1-vFLIP (pcvFLIP) [34, 35] in 12-well plates for 48 h using Lipofectamine 2000 (Invitrogen) according to the manufacturer’s instruction. Transfection efficiency was determined through co-transfection of a lacZ reporter construct and quantified as described previously [36].

qRT-PCR

Total RNA was isolated using the RNeasy Mini kit (QIAGEN), and cDNA was synthesized from equivalent total RNA using a SuperScript III First-Strand Synthesis SuperMix Kit (Invitrogen) according to the manufacturer’s instructions. Primers used for amplification of target genes are listed in Supplementary Table 1. Amplification was carried out using an iCycler IQ Real-Time PCR Detection System, and cycle threshold (Ct) values were tabulated in duplicate for each gene of interest in each experiment. “No template” (water) controls were used to ensure minimal background contamination. Using mean Ct values tabulated for each gene, and paired Ct values for β-actin as a loading control, fold changes for experimental groups relative to assigned controls were calculated using automated iQ5 2.0 software (Bio-rad). For amplification of human miRNAs, cDNA was synthesized using the Taqman miRNA RT kit (Applied Biosystems), and qPCR was performed using the Taqman MicroRNA Assays kit (Applied Biosystems) and a 7500 Real Time PCR System. Fold changes for microRNA were calculated using paired Ct values for RNU6B as recommended by the manufacturer (Applied Biosystems). The mirVana™ miRNA inhibitors for blocking miR129-5p or miR331-3p activities and the control were purchased from Invitrogen, and used according to the manufacturer’s instructions.

Statistical analysis

Significance for differences between experimental and control groups was determined using the two-tailed Student’s t-test (Excel 8.0), and p values < 0.05 or < 0.01 were considered significant or highly significant, respectively.

ACKNOWLEDGMENTS AND FUNDING

This work was supported by grants from a DOD Career Development Award (CA140437), the Leukemia Research Foundation, a Louisiana Clinical and Translational Science Center Pilot grant (U54GM104940 from NIH), NIH RO1s (AI091526 and AI128864) as well as awards from the National Natural Science Foundation of China (81472547, 81400164 and 81672924) and the Health Industry Project PW2013E-1 from Pudong Health Bureau of Shanghai, China. Funding sources had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

CONFLICTS OF INTEREST

All the authors declare no conflicts of interest.

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