Many solid malignant tumors arise on a background of inflamed and/or fibrotic tissues, features that are found in more than 80% hepatocellular carcinomas (HCC). Activated hepatic stellate cells (HSC) play a critical role in fibrogenesis associated with HCC onset and progression, yet their functional impact on hepatocyte fate remains largely unexplored. Here, we used a coculture model to investigate the cross-talk between hepatocytes (human hepatoma cells) and activated human HSCs. Unsupervised genome-wide expression profiling showed that hepatocyte–HSC cross-talk is bidirectional and results in the deregulation of functionally relevant gene networks. Notably, coculturing increased the expression of proinflammatory cytokines and modified the phenotype of hepatocytes toward motile cells. Hepatocyte–HSC cross-talk also generated a permissive proangiogenic microenvironment, particularly by inducing VEGFA and matrix metalloproteinase (MMP)9 expression in HSCs. An integrative genomic analysis revealed that the expression of genes associated with hepatocyte–HSC cross-talk correlated with HCC progression in mice and was predictive of a poor prognosis and metastasis propensity in human HCCs. Interestingly, the effects of cross-talk on migration and angiogenesis were reversed by the histone deacetylase inhibitor trichostatin A. Our findings, therefore, indicate that the cross-talk between hepatoma cells and activated HSCs is an important feature of HCC progression, which may be targeted by epigenetic modulation. Cancer Res; 72(10); 2533–42. ©2012 AACR.
Extensive evidence from genetics, genomics, and cell biology showed that cancer onset and progression is not only determined by tumor cells but also influenced by the microenvironment (1–3). Microenvironment is a complex system, which largely consists of extracellular matrix (ECM) proteins and proteoglycans, soluble factors, and small signaling molecules such as cytokines and chemokines, along with a variety of cell types such as fibroblasts, immune cells, and endothelial cells. Under normal conditions, the microenvironment constitutes an important modulator of epithelium cell fate and a barrier to cell transformation (4). Dynamic communications between the epithelium and the microenvironment notably modulate cell growth, apoptosis, and maintain epithelial cell polarity and differentiation (4). In cancer, the microenvironment, which is also referred to as stroma, experiences drastic changes including the recruitment and the activation of stromal cells and the remodeling of ECM. Importantly, coevolution of tumor cells with their microenvironment during tumorigenesis suggests that tumor–stroma cross-talk may likely influence the phenotype of tumor cells and may provide a selective pressure for tumor initiation, progression, and metastasis (1, 5, 6).
Hepatocellular carcinoma (HCC) is the most common primary tumor of the liver. The incidence of HCC is increasing in many countries and its prognosis is typically poor. Thus, with 550,000 cases newly diagnosed and 600,000 deaths annually, HCC ranks among the deadliest forms of human malignancies worldwide (7). The remodeling of liver microenvironment is a hallmark of HCC pathogenesis (8). Indeed, more than 80% HCCs develop in the setting of chronic hepatitis, fibrosis, and cirrhosis, conditions in which inflammation and ECM deposition profoundly alter the hepatic microenvironment (9). However, the functional impact of the disrupted microenvironment on hepatocyte biology remains poorly understood (10). Over the last decade, high-throughput genomic studies provided important insights to classify HCCs at a molecular level and to identify deregulated gene networks and signaling pathways (11). However, most of gene expression signatures in HCCs have been derived from whole-tumor tissues consisting of both the cancer epithelial cells and their surrounding microenvironment, a strategy which rendered elusive to evaluate the specific contribution of each compartment.
Activation of hepatic stellate cells (HSC) is a key feature of liver fibrosis and cirrhosis (12). Following liver injury, quiescent HSCs become activated and convert into highly proliferative myofibroblast-like cells, which express inflammatory and fibrogenic mediators responsible for ECM accumulation within the microenvironment (12, 13). Therefore, the present study was specifically designed to address the functional impact and the clinical relevance of the cross-talk between tumor hepatocytes and activated HSCs. By using a coculture model system, genome-wide expression profiling, and functional assays, we showed that the cross-talk between hepatocytes and activated HSCs (i) is bidirectional, (ii) induces an alteration of hepatocyte phenotype toward migration, (iii) generates a permissive proinflammatory and proangiogenic microenvironment, (iv) is predictive of a poor prognosis in human HCC, and (v) could be targeted by epigenetic modulation.
Materials and Methods
Cell lines and coculture experiments
HepaRG and HuGB cell lines were established in our laboratory and maintained as previously described (14, 15). HepaRG cells were grown in William's E medium supplemented with 10% FBS, 100 U/mL penicillin, 100 μg/mL streptomycin, 5 μg/mL insulin, and 50 μmol/L hydrocortisone hemisuccinate. Differentiation of HepaRG from progenitors to mature well-differentiated hepatocytes was achieved in 4 weeks by culturing the cells in the supplemented medium in presence of 2% dimethyl sulfoxide (DMSO) for the last 2 weeks as previously described (ref. 16; Supplementary Fig. S1A). All experiments hereinafter referred to as HepaRG were carried out using mature hepatocytes selectively isolated by mild trypsinization from DMSO-treated cultures. LX2 cells (Supplementary Fig. S1B) were provided by S.L. Friedman (Mount Sinai School of Medicine, New York, NY) and were maintained in supplemented Dulbecco's Modified Eagles' Media (DMEM) as described (17). HepaRG–LX2 cocultures were conducted in serum- and DMSO-free William's E medium using 6-well plates and 1-μm pore size Transwell inserts, which allow diffusion of media components but prevent cell migration (BD Biosciences; Supplementary Fig. S1C). Huh7 and HepG2 cell lines were obtained from the European Collection of Cell Cultures, which conducted cell lines authentication by DNA barcoding. Primary human umbilical vein endothelial cells (HUVEC) were purchased from Invitrogen and were maintained in 200PRF medium supplemented with a low-serum growth supplement (LSGS). All cell cultures were conducted at 37°C in a 5% CO2 atmosphere. Trichostatin A (TSA) was purchased from Sigma-Aldrich. Independent culture experiments were carried out at least in triplicate.
Total RNA was purified from cells at 80% confluence with an RNeasy kit (Qiagen). Genome-wide expression profiling was conducted using the low-input Quick Amp Labeling Kit and human SurePrint G3 8 × 60K pangenomic microarrays (Agilent Technologies) as previously described (18). Starting from 150 ng total RNA, amplification yield was 9.7 ± 0.6 μg cRNA and specific activity was 20.3 ± 1.3 pmol Cy3 per μg cRNA. Gene expression data were processed using Feature Extraction and GeneSpring softwares (Agilent Technologies) and further analyzed using R-based BRB-ArrayTools. Briefly, differentially expressed genes were identified by a 2-sample univariate t test and a random variance model (P < 0.01; false discovery rate < 1%) as described (19). Permutation P values for significant genes were computed on the basis of 10,000 random permutations. Class prediction was conducted using 7 algorithms and misclassification rate was computed using a leave-one-out cross-validation method (20). Clustering analysis was done using Cluster 3.0 and TreeView 1.6 using uncentered correlation and average linkage options. MIAME compliant microarray data have been deposited into Gene Expression Omnibus (GEO) database (GSE32565).
Data mining and integrative genomics
Gene annotation was based on Gene Ontology and enrichment for specific biologic functions or canonical pathways was evaluated using FuncAssociate 2.0 program (21). Ingenuity Pathway Analysis (IPA) was used to examine the functional association between differentially expressed genes and to generate the highest significant gene networks (Ingenuity). Relevant networks were identified using the scoring system provided by IPA. Gene set enrichment analysis (GSEA) was conducted by using the Java tool developed at the Broad Institute (Cambridge, MA) as previously described (22). Unsupervised GSEA was done with the whole C2 collection of curated gene sets from the molecular signatures database (MSigDB). Enrichment score was determined after 1,000 permutations. Connectivity map algorithm was used to link gene expression signatures with putative therapeutic molecules (23). Integration of genomic data was conducted as previously described (20) using publicly available gene expression data sets downloaded from GEO.
Real-time reverse transcriptase PCR
Expression of relevant genes was measured by quantitative real-time PCR as previously described (22). Quantitative analysis of PCR data was conducted with the 2−ΔΔCt method using glyceraldehyde-3-phosphate dehydrogenase (GAPDH) Ct values for normalization. Melting analysis was conducted to validate the specificity of PCR products. PCR and microarray analysis were conducted using RNA extracted from independent culture experiments (n = 3).
HepaRG (10,000 cells per well) were seeded onto 96-well plates. Following 4-hour incubation at 37°C, the medium was replaced by serum-free medium supplemented with 50% (v/v) conditioned medium derived from culture and coculture of HepaRG and LX2. Proliferation was evaluated after 24, 48, and 72 hours using a CyQuant Cell Proliferation Assay Kit (Invitrogen). Experiments were carried out in triplicate.
Influence of conditioned medium on HepaRG migration was determined using a 2-dimensional gap closure radius 96-well migration assay, according to manufacturer's instructions (Cell Biolabs). Cell migration was independently evaluated from scratch-wounded confluent monolayers of HepaRG incubated in presence of serum-free medium supplemented with 50% conditioned medium as above. Migration was evaluated up to 72 hours in triplicate.
In vitro angiogenesis
HUVECs (30,000 cells per well) were seeded onto 48-well plates previously coated with Geltrex-reduced growth factor basement membrane matrix (100 μL/cm2) using nonsupplemented 200PRF medium (Invitrogen). Endothelial tube formation was monitored after 6 hours in the presence of 50% (v/v) serum-free conditioned medium from culture/coculture of LX2 and HepaRG. LSGS-supplemented HepaRG medium (2% FBS; 3 ng/mL basic fibroblast growth factor) was used as a positive inducer control and nonsupplemented HepaRG medium was used as a negative control. Triplicate experiments were carried out.
Matrix metalloproteinase (MMP) activity in conditioned medium was evaluated in triplicate by gelatine zymography as described (8). Recombinant human MMP2 and MMP9 were used as positive controls. After scanning, images were analyzed by densitometry using ImageJ (NIH, Bethesda, MD).
Quantitative results were expressed as mean and SD and the significance was evaluated by Student t test.
Coculturing hepatocytes with activated HSCs results in a bidirectional cross-talk
HepaRG and LX2 cells were used as a paradigm to model the cross-talk between transformed but differentiated human hepatocytes and activated HSCs in the context of liver cancer (Supplementary Fig. S1). HepaRG cell line was established in our laboratory from a well-differentiated Edmondson grade I HCC and was shown to possess the unique property to spontaneously differentiate into functional mature hepatocytes and biliary cells (14, 16). LX2 cells were reported to greatly recapitulate the in vivo phenotype of primary human activated HSC (17). However, as gene expression profiles during HSC activation may differ in culture and in vivo (24), we first conducted a gene expression profiling to validate the molecular phenotype of LX2 cells in our culture conditions. IPA showed that highly expressed genes in LX2 (top 1%, 163 genes) were significantly linked to hepatic fibrosis and HSC activation (Supplementary Fig. S2A). As expected, these genes included major regulators of ECM synthesis and degradation (e.g., COL1A1 and MMP2), markers of HSC activation (e.g., ACTG2 and VIM), as well as proinflammatory cytokines (e.g., IL1B). Further validating the choice of this cell line, GSEA showed that highly expressed genes in LX2 were significantly enriched in a rat model of hepatic fibrosis and were characteristic of the transformation of quiescent HSCs into myofibroblasts (Supplementary Fig. S2B).
Hepatocyte–HSC cross-talk was next addressed by analyzing cocultures of HepaRG and LX2 separated by a Transwell insert (Supplementary Fig. S1C). Microarray experiments were carried out after 48 hours, when cells reached 80% confluency. In HepaRG, the analysis of gene expression profiles by means of class comparison and class prediction algorithms identified 212 genes whose expression was significantly modulated (P < 0.01; 1.5 fold change) by the presence of LX2 (Fig. 1A and Supplementary Table S1). More than 83% genes were upregulated suggesting that coculture with LX2 induced a global shift toward transcriptional activation in HepaRG (Fig. 1A). In LX2, the expression of 123 genes was significantly altered by the coculture condition (Fig. 1B and Supplementary Table S2), including the upregulation of master genes involved in ECM remodeling and angiogenesis (e.g., MMP9 and VEGFA). Importantly, the unsupervised analysis of genes differentially expressed in coculture versus culture condition revealed a bidirectional cross-talk between HepaRG and LX2.
Coculture with LX2 induces an inflammatory response and a motile phenotype in HepaRG
Gene Ontology and ingenuity analysis showed that the genes related to cell chemotaxis, motility, and inflammation were significantly enriched in the HepaRG–LX2 signature (Supplementary Table S3). Notably, several important proinflammatory and profibrogenic cytokines [e.g., interleukin (IL)-1B, IL-6, and IL-8], acute-phase proteins (e.g., CP and SAA1), and growth factors (e.g., AREG and EREG) were upregulated in HepaRG when the 2 cell types were cultured together (Fig. 1A and Supplementary Table S1). Accordingly, a well-organized gene network linked to IL-1B, IL-6, IL-8, and CCL2, which is also known as the monocyte chemoattractant protein 1 (MCP1) was identified by IPA (Fig. 2A and Supplementary Fig. S3). The expression of IL-6, IL-8, and CCL2 was further evaluated by quantitative reverse transcriptase PCR (Q-RT-PCR) using RNA extracted from independent cell culture experiments. As shown in Fig. 2B, all genes were significantly upregulated in HepaRG after 48-hour coculture with LX2. Together, these data suggested that the cross-talk between HepaRG and LX2 resulted in the establishment of a proinflammatory microenvironment. To validate this observation, we conducted a GSEA using an independent gene set that covered the whole response of Hep3B hepatocytes to proinflammatory cytokines (25). This approach unambiguously showed that coculture with LX2 induced a prominent inflammatory response in HepaRG (Fig. 2C). Inflammation is thought to play a key role in cancer initiation and progression by fostering multiple hallmarks of cancer including tumor cell proliferation and motility (1). To evaluate whether the coculture condition had any impact on the phenotype of HepaRG, mature hepatocytes were isolated from new HepaRG cultures and were exposed to conditioned media derived from the initial cultures and cocultures of HepaRG and LX2. Gap closure assay showed that exposing fresh HepaRG hepatocytes to conditioned medium derived from HepaRG–LX2 coculture significantly induced cell migration (Fig. 3). Of note, cell proliferation remained unaffected by conditioned medium treatment, suggesting that gap closure was not secondary to enhanced cell proliferation (data not shown). Collectively, these data indicated that coculturing hepatocytes with activated HSCs resulted in the production of soluble factors, including proinflammatory signals, which were able to modify the phenotype of hepatocytes toward migration.
HepaRG–LX2 cross-talk generates a permissive proangiogenic microenvironment by modulating MMP9 and VEGFA in LX2 cells
Data mining of 112 genes differentially expressed when LX2 were cocultured with HepaRG (LX2–HepaRG signature; Fig. 1B) identified a gene network linked to VEGFA and MMP9 (Fig. 4A). Upregulation of VEGFA and MMP9 genes was validated by Q-RT-PCR using RNA derived from independent experiments (Fig. 4B). Together with Gene Ontology and ingenuity analysis (Supplementary Table S3), these results suggested that HepaRG–LX2 cross-talk may have profound impact on angiogenesis and ECM remodeling. This hypothesis was first tested by exposing HUVECs to conditioned medium derived from the culture or the coculture of LX2 and HepaRG. As shown in Fig. 4C, conditioned medium (CM) issued from coculture experiments (LX2–HepaRG-CM) induced the formation of tubule complexes by HUVECs. In contrast, conditioned medium issued from LX2 cultured alone (LX2-CM) failed to induce in vitro angiogenesis (Fig. 4C). Absence of tube formation was also noticed when HUVECs were exposed to conditioned medium derived from HepaRG cultured alone (data not shown). Next, MMP activity in conditioned medium was evaluated by gelatin zymography. In agreement with the increased expression of MMP9 (Fig. 4B), we showed that MMP9 activity was significantly higher (P < 0.01) in LX2–HepaRG-CM than in LX2-CM (Fig. 4D). Similar observation was made for MMP2. These data suggested that hepatocyte–HSC cross-talk resulted in the establishment of a permissive proangiogenic microenvironment that may facilitate the migration of tumor cells.
HepaRG–LX2 cross-talk signals a poor prognosis in human HCCs and correlates with tumor progression
Integrative genomics was next used to evaluate the clinical relevance of the cross-talk between cultured hepatocytes and activated HSCs. The HepaRG–LX2 signature (i.e., 212 genes differentially expressed in HepaRG by the coculture condition; Fig. 1A) was first integrated with the gene expression profiles of 139 cases of human HCCs, which were extensively characterized (20, 26–28). Hierarchical clustering analysis of the integrated data set identified 2 robust clusters whose organization was driven by the culture condition of HepaRG: cluster 1, HepaRG–LX2 coculture; cluster 2, HepaRG culture (Fig. 5A). Interestingly, we observed that clinical and biologic parameters of HCCs were not randomly distributed between the clusters 1 and 2. Strikingly, cluster 1 included significantly more tumors, which were previously assigned to a poor prognosis group, than cluster 2 (Fig. 5A). As shown in Fig. 5B, cluster 1 HCCs were previously defined by a bad survival (27), hepatoblast traits (28), along with the activation of oncogenic MET/hepatocyte growth factor (HGF; ref. 26) and TGFβ pathways (20). In addition, they exhibited a poorly differentiated phenotype (Edmondson grade >III), signs of vascular invasion, and were significantly bigger in size (Fig. 5B). More importantly, the survival of patients included in cluster 1 was significantly reduced (P < 0.01). Interestingly, if these observations showed that the HepaRG–LX2 cross-talk signature is predictive of a poor prognosis when evaluated as a unique gene set, we also reported that 85% of genes included in the signature and expressed in primary HCCs were clinically relevant when analyzed individually (Supplementary Table S4). Unsupervised GSEA further supported the relevance of HepaRG–LX2 signature in predicting a poor prognosis phenotype not only in HCCs but also in other cancers. In the context of HCCs, we found that specific signatures for recurrence (29), c-Myc/TGFα aggressive mouse model of HCC (30) or TGFβ (20) were significantly enriched in the HepaRG–LX2 gene profiles (Supplementary Table S5). This approach also showed that gene signatures associated with a bad prognosis in cancers other than HCCs (e.g., invasive breast cancer, advanced gastric cancer, metastatic stromal cells, and highly metastatic pancreatic cancer cells) were significantly (P < 0.01) enriched both in HepaRG and LX2 under coculture conditions (Supplementary Fig. S4). To further investigate the relevance of the HepaRG–LX2 cross-talk signature in HCC progression, we conducted a cross-species integrative genomic approach as described previously (20). First, we integrated the HepaRG–LX2 signature with the gene expression profiles of 80 cases of HCCs derived from 4 transgenic mouse models of HCC (c-Myc, E2f1, c-Myc/E2f1, and c-Myc/TGFα; refs. 19, 30). Consistent with the unsupervised GSEA, the analysis of the integrated data sets showed that the HepaRG–LX2 signature clustered specifically with HCCs derived from c-Myc/TGFα (Supplementary Fig. S5A). This observation pointed out c-Myc/TGFα transgenic mice as the best in vivo model for evaluating the HepaRG–LX2 signature in HCC onset and progression. This was investigated by using the gene expression profiles characteristic of c-Myc/TGFα–induced hepatocarcinogenesis. These profiles were established previously using liver samples collected at various time points of tumor onset and progression in transgenic mice, ranging from 3 weeks (moderate dysplasia), 3 months (severe dysplasia), and 9 months (HCCs; ref. 30). By using a multidimensional scaling approach, we showed that the HepaRG–LX2 signature effectively discriminated the mouse samples on the basis of HCC progression (Supplementary Fig. S5B).
Because HSC activation is an early event in the pathogenesis of HCCs, we asked whether the HepaRG–LX2 signature within cirrhosis tissues from patients with HCCs could predict any specific clinical outcome. To test this hypothesis, we used a publicly available gene expression data set established from the noncancerous hepatic tissue of patients with primary HCCs (GSE5093 in GEO database). In this cohort, patients were divided in 2 groups on the basis of the presence or absence of venous metastasis (31). Accordingly, cirrhosis tissues isolated from patients with or without metastasis were, respectively, termed metastasis-inclined microenvironment (MIM) and metastasis-averse microenvironment (MAM; ref. 31). On the basis of the HepaRG–LX2 signature, we showed that MIM and MAM samples coclustered with HepaRG–LX2 and HepaRG samples, respectively (Fig. 5C). GSEA confirmed that the genes that signed the cross-talk between HepaRG and LX2 were significantly enriched in the expression profiles of cirrhosis tissue from patients with metastasis (Fig. 5C). Altogether, these results showed that the expression of genes embedded in the HepaRG–LX2 signature, either in cirrhosis or in HCCs, was predictive of a poor prognosis and was associated with metastasis propensity.
Epigenetic modulation of HepaRG–LX2 cross-talk by TSA
The clinical relevance of HepaRG–LX2 signature in predicting a poor prognosis in human HCCs suggested that molecules targeting hepatocyte–HSC cross-talk may represent a promising therapeutic strategy. In this context, connectivity map was used to identify molecules that could reverse the global gene expression profile induced by LX2 on HepaRG. Interestingly, the top 10 ranked molecules identified by this approach included 3 inhibitors of histone deacetylases, vorinostat, TSA, and valproic acid (Supplementary Table S6). TSA was chosen for further experiments on the basis of the higher number of hits obtained with a connectivity map (n = 182 hits, Fig. 6A) and the results of the unsupervised GSEA, which showed that genes silenced by TSA in pancreatic cancer were significantly (P < 0.01) enriched in the gene profiles of both HepaRG and LX2 under coculture conditions (Supplementary Fig. S4). To test whether TSA could modulate the HepaRG–LX2 cross-talk, we produced conditioned medium from culture and coculture of HepaRG and LX2 cells exposed to 500 nmol/L TSA or DMSO control. As shown in Fig. 6B, the migration of freshly isolated HepaRG hepatocytes in response to HepaRG–LX2-CM was completely abrogated in presence of TSA. We further showed in HepaRG that LX2 induced upregulation of amphiregulin and epiregulin, 2 genes that have been linked to invasion and metastasis and that were abolished by TSA (Supplementary Fig. S6A). Our data also suggested that TSA was able to inhibit coculture-induced angiogenesis as evidenced by the absence of tube formation by endothelial cells and the reduced VEGFA expression by LX2 cells under coculture condition (Supplementary Fig. S6B).
The tumor microenvironment contributes in the acquisition of multiple hallmarks of cancer (1). However, the underlying molecular mechanisms involved in the interactions between the tumor cells and the microenvironment remain poorly understood. We investigated the molecular mechanisms involved in the cross-talk between tumor cells and their microenvironment in liver cancer, by analyzing cocultures of hepatoma cells and activated HSCs. We propose a model in which this cross-talk is bidirectional and leads to a permissive microenvironment through ECM remodeling and angiogenesis, along with the alteration of hepatocyte phenotype toward motile cells (Fig. 7). Thus, the data suggest that the dynamic interactions between hepatocytes and activated HSCs through soluble mediators play an important role in the progression of HCCs. Supporting this hypothesis, we further established by integrative genomics that hepatocyte–HSC cross-talk in vitro is clinically relevant and is associated with a poor prognosis in human HCCs. More investigations will be needed to fully establish the contribution of each specific genes and/or pathways in HepaRG–LX2 cross-talk. Interestingly, analyzing the cross-talk between LX2 and other hepatoma cells, namely, Huh7 and HepG2, showed that the regulation of some important factors, such as IL-8, was conserved (Supplementary Fig. S7). More broadly, the results also suggested that the cross-talk with LX2 may depend on the differentiation status of the cells. Indeed, HepaRG cell line was established from an Edmonson grade I, well-differentiated HCCs, and showed a unique property to differentiate into mature hepatocytes. Taking this feature into account was particularly relevant given that several studies reported an accumulation of activated HSCs in dysplastic nodules at early stages of HCC development.
Unsupervised analysis of genes deregulated in HepaRG in response to the coculture with LX2 highlighted proinflammatory cytokines (e.g., IL-1B and IL-6) and chemokines (e.g., IL-8, and CCL2) as key orchestrators of the cross-talk between hepatocytes and activated HSCs, consistent with previous observations (32, 33). Inflammatory cells and mediators are frequent in the local environment of tumors and several lines of evidences suggested that inflammation contributes to the acquisition of core hallmark capabilities in cancer (1). Notably, epidemiologic studies suggested that inflammatory diseases predispose individuals to cancer (34). Thus, an increase expression of IL-6 was reported in the serum of most patients with cancer. In HCCs, IL-6 expression was found to correlate with a rapid progression from hepatitis to HCCs (35), and an activation of IL-6 pathway was reported in HCCs with a poor prognosis (36). The invasive capacity of malignant cells has been shown to be increased in presence of IL-1B and IL-6 (34). Recently, somatic alterations of gp130 and STAT3, which are required for IL-6 signaling, have been reported in inflammatory hepatocellular adenomas (37, 38).
Previous studies by Omenetti and colleagues described a similar bidirectional cross-talk between HSCs and cholangiocytes and provided evidence supporting the importance of the Hedgehog signaling (39). This pathway has been shown also to promote the viability of HSCs (40). In the HepaRG–LX2 coculture model, no significant difference was observed in the expression of Hedgehog ligands (e.g., SHH), receptors (e.g., PTCH1), inducible transcription factors (e.g., GLI2) or inhibitors (e.g., HHIP; Supplementary Fig. S8), suggesting that the Hedgehog is not the prominent signaling pathway involved in the cross-talk between mature hepatocytes and activated HSCs. Given the fundamental role of this pathway in the cross-talk between immature liver epithelial cells and HSCs (39), it is plausible that Hedgehog signaling may play a role in the fate of progenitor HepaRG cells.
Consistent with previous observations using human or rat HSCs (32, 33), our results also show that hepatocyte–HSC cross-talk may greatly impact the local tumor microenvironment, particularly ECM turnover by MMPs and angiogenesis, 2 main mechanisms promoting tumor growth and metastasis. Previously, we have shown that hepatocyte–HSC interplays induce enhanced ECM remodeling though MMP2 activation (41). In the present study, in addition to the increased expression of VEGF and MMPs, we report that the enhanced expression of chemoattractant chemokines may also contribute to the establishment of a permissive microenvironment by recruiting other cell types than endothelial cells, notably immune cells. Particularly, we show that mRNA levels for IL-8, CCL2, CCL20, and CXCL2 genes were significantly induced in the coculture condition. These soluble mediators are potent chemoattractants for monocytes and lymphocytes. IL-8 is also a potent inducer of angiogenesis and metastasis. Interestingly, emerging evidences indicate that CCL2 may also modulate the T-helper (TH)1/TH2 immune responses. Indeed, CCL2 has been shown to induce the expression of IL-4, a potent TH2 cytokine, whereas decreasing the expression of IL-12, a major TH1 cytokine (42). Thus, the induction of CCL2, IL-6, and IL-8 suggests that the cross-talk between hepatocytes and HSCs may compromise a TH1 polarization and switch the expression of cytokines toward a TH2 profile. Differential expression of TH1 and TH2 cytokines has been reported in the microenvironment of various types of cancer in vivo. In breast cancer, analysis of gene expression profiles of tumor stroma identified a gene signature that predicted clinical outcome independently of existing standard clinical prognosis factors (43). Importantly, tumor stroma derived from patients with a poor outcome was characterized by an increased expression of genes linked to hypoxia and angiogenesis along with a decreased expression of genes characteristic of a TH1 response (43). Further supporting the hypothesis that a TH2 signature within tumor stroma was predictive of a poor prognosis, we show that the HepaRG–LX2 signature recapitulates the MIM group in HCCs, which was characterized by the presence of venous metastasis and reported to be significantly associated with an increase in TH2 cytokines and a decrease in TH1 cytokines (31).
Treatment of HCCs represents an important clinical challenge. Here, we provide evidences that targeting tumor–stroma cross-talk by epigenetic modulation may represent a promising therapeutic strategy (Fig. 7). Notably, TSA was able to inhibit the coculture-induced migration of HepaRG hepatocytes as well as angiogenesis and VEGFA expression in LX2. Interestingly, TSA has been also reported to abrogate TGFβ1-induced epithelial–mesenchymal transition (EMT) in hepatocytes and to reverse EMT-induced fibrosis by epigenetic modulation of type I collagen (44). Besides acting on hepatocytes, TSA could also mediate beneficial effects through HSCs. Indeed, TSA was shown to strongly suppress the proliferation of rat HSCs and to inhibit their conversion into myofibroblasts (45).
In conclusion, the study highlights the central role of the cross-talk between hepatocytes and their microenvironment in HCCs and suggests that targeting tumor-stroma cross-talk by epigenetic modulation may represent a promising therapeutic strategy.
Disclosure of Potential Conflicts of Interest
No potential conflicts of interests were disclosed.
This research was supported by INSERM, CNRS, University of Rennes 1, Institut National du Cancer Agence Nationale pour la Recherche and Association pour la Recherche sur le Cancer, France.
The costs of publication of this article were defrayed in part by the payment of page charges. This article must therefore be hereby marked advertisement in accordance with 18 U.S.C. Section 1734 solely to indicate this fact.
The authors thank Dr. S.L. Friedman, Mount Sinai School of Medicine, New York, NY, for his generous gift of LX2 cells, Dr. M. Ravache and K. Jarnouen, INSERM UMR991, for their help in cell migration assays and Q-RT-PCR, and the microarray core facility team from plateforme génomique santé, Biosit, Rennes.
Note: Supplementary data for this article are available at Cancer Research Online (http://cancerres.aacrjournals.org/).
- Received October 7, 2011.
- Revision received February 8, 2012.
- Accepted February 27, 2012.
- ©2012 American Association for Cancer Research.