Gene expression profiles predict the possible regulatory role of OPN-mediated signaling pathways in rat liver regeneration

Gene 576 (2016) 782–790

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Research paper

Gene expression profiles predict the possible regulatory role of OPN-mediated signaling pathways in rat liver regeneration Gaiping Wang a,b, Shasha Chen a,b, Congcong Zhao a,b, Xiaofang Li a,b, Ling Zhang c, Weiming Zhao a,b, Cuifang Chang b, Cunshuan Xu b,⁎ a b c

College of Life Science, Henan Normal University, Xinxiang 453007, Henan, China Key Laboratory for Cell Differentiation Regulation, Henan Normal University, Xinxiang 453007, Henan, China Henan Academy of Fishery Science, Zhengzhou 450044, Henan, China

a r t i c l e

i n f o

Article history: Received 10 August 2015 Received in revised form 3 November 2015 Accepted 8 November 2015 Available online 12 November 2015 Keywords: Rat liver regeneration Osteopontin Signaling pathway Gene expression profiles Rat Genome 230 2.0

a b s t r a c t Osteopontin (OPN; gene Spp1), as a pro-inflammatory cytokine, has a range of activities relevant to the occurrence and progression of hepatitis, liver fibrosis or liver tumors. However, little is known about the role of OPN in liver regeneration (LR). To reveal the expression profiles of OPN and its receptors and the possible regulatory role of OPN in rat LR, Rat Genome 230 2.0 was used to detect expression profiles of OPN-mediated signaling pathway-associated genes after partial hepatectomy (PH), and the results showed that 81 genes were significantly changed at mRNA level, and among which, 65 genes were up-regulated. Then, k-means clustering was employed to classify above 81 genes into 5 clusters based on gene expression similarity, and EASE analysis further indicated that the above genes were mainly associated with stress response, inflammatory response, cell activation, proliferation, adhesion and migration. Thereafter, IPA software and Western blot were used to analyze potential effects of every branch of OPN signaling pathways during LR, and the results suggested that the genes expression changes of OPN signaling pathways may account for enhanced cell proliferation, survival, adhesion and migration, augmented inflammation response and attenuated apoptosis during LR. © 2015 Elsevier B.V. All rights reserved.

1. Introduction Osteopontin (OPN), also named as secreted phosphoprotein 1 (SPP1), is a member of Th1 cytokines. In obesity-induced hepatic steatosis, it could activate natural killer T (NKT) cells and neutrophils by interacting with its receptors, and trigger the recruitment and infiltration of neutrophils, and then aggravate liver damage (Kiefer et al., 2011). OPN is likely to promote hepatic fibrosis through affecting the activation of hepatic stellate cells (HSC) and boosting the expression of collagen, matrix metalloproteinase (MMP) and cytokines (Sabo-Attwood et al., 2011; Urtasun et al., 2012). Moreover, overexpression of OPN is closely related to metastasis and prognosis of hepatocellular carcinoma (HCC), and OPN depletion by siRNA could reduce formed colony numbers in HCC cell lines (Lin et al., 2011). Together, OPN has been shown to enhance inflammation response and promote cell activation, proliferation and Abbreviations: AKT, v-akt murine thymoma viral oncogene homolog 1; Bcl2, B-cell CLL/lymphoma 2; ERK, extracellular regulated protein kinases; Fos, FBJ osteosarcoma oncogene; IKBKB, inhibitor of κB kinase β; JAK, Janus kinase; JNK, c-Jun NH2-terminal kinase; Jun, jun protooncogene; LR, liver regeneration; MAPK, mitogen-activated protein kinase; Myc, myelocytomatosis oncogene; NF-κB, nuclear factor NF-κ-B p105 subunit; OPN, osteopontin; PH, partial hepatectomy; PI3K, phosphoinositide 3-kinase; RhoA, ras homolog family member A; STAT, signal transducer and activator of transcription. ⁎ Corresponding author at: College of Life Science, Henan Normal University, No. 46, Construction East Road, Xinxiang 453007, Henan, China. E-mail address: [email protected] (C. Xu).

http://dx.doi.org/10.1016/j.gene.2015.11.008 0378-1119/© 2015 Elsevier B.V. All rights reserved.

migration, and ultimately plays a vital role in the occurrence and progression of liver diseases. Liver is unique in its ability to regenerate rapidly, even in adulthood. After injured or partial hepatectomy (PH), about 95% of quiescent hepatocytes re-enter synchronously into cell cycle to replenish the missing liver tissues, which is called liver regeneration (LR). OPN, besides closely related to the occurrence of liver disease, probably could promote hepatic self-repair and then protect liver during LR. Arai and his colleagues found that OPN protein was expressed in regenerating hepatocytes and bile ductular structures in the livers of fulminant hepatic failure patients, and surmised that OPN may play an important role in LR due to activation of hepatic stem cells (Arai et al., 2004; Arai et al., 2006). Moreover, several studies have confirmed that OPN could perform its functions through phosphoinositide 3-kinase/v-akt murine thymoma viral oncogene homolog 1 (PI3K/AKT), mitogen-activated protein kinase (MAPK) and nuclear factor NF-κ-B (NF-κB) signaling pathways upon binding to a number of integrins receptors (Sodek et al., 2000; Denhardt et al., 2001; Chakraborty et al., 2006; Urtasun, et al., 2012), or through PI3K/AKT (Chakraborty, et al., 2006; Wang and Denhardt, 2008) and Janus kinase/signal transducer and activator of transcription (JAK/STAT) (Behera et al., 2010) signaling pathways when interacting with CD44. However, little is known about the expression profiles of OPN and its receptors during LR, and the possible modulatory effects of OPN on LR.

G. Wang et al. / Gene 576 (2016) 782–790

Therefore, in this study, the network of OPN-mediated signaling pathways was comprehensively built, and expression changes of genes related to OPN-mediated signaling pathways at the transcriptional level were detected by Rat Genome 230 2.0, and the possible roles of OPN signaling during LR were predicted by systems biology and IPA software, which will be helpful to reveal the relationships between the expression changes of OPN signaling pathway-related genes and several biological processes during LR. 2. Materials and methods 2.1. Rat regenerating livers preparation Healthy male Sprague–Dawley (SD) rats (200 ± 10 g), supplied by the Experimental Animal Center of Henan Normal University, were housed in a controlled temperature room (22 ± 1 °C) with a 12:12 h light–dark cycle. A total of 76 male rats were picked up and randomly divided into 19 groups with 4 rats in each: 9 PH groups, 9 shamoperated (SO) groups and one normal control (NC) group. PH groups were subjected to 2/3 PH, as described by Higgins and Anderson (1931). SO group received the same procedure as for the PH group, without liver removal. Four rats were anesthetized and sacrificed at 0, 2, 6, 12, 24, 30, 36, 72, 120 and 168 h after PH, respectively, and their liver tissues from the middle part of the right lobe were instantly removed and stored at −80 °C for use. All operations and handling procedures were carried out in accordance with the current Animal Protection Law of China.

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Chakraborty et al., 2006; Urtasun, et al., 2012), or through PI3K/ AKT (Chakraborty, et al., 2006; Wang and Denhardt, 2008) and JAK/ STAT (Behera et al., 2010) signaling pathways when interacting with CD44. Therefore, “integrin signaling pathway,” “PI3K/AKT signaling pathway” and “JAK/STAT signaling pathway” were respectively entered into the “Pathway and function” module of Ingenuity Pathway Analysis (IPA) software to obtain the interaction network of proteins in every corresponding signaling pathway, and the above results were filtered and integrated by researching signaling pathway maps at the databases including GenMAPP (Gan et al., 2015), KEGG, BIOCARTA, QIAGEN and Biocompare, and then the signaling stream and members in the interaction network of OPN-mediated signaling pathways were reconfirmed through retrieving several pertinent articles. 2.5. Quantitative RT-PCR To verify the chip data, six target genes involved in OPN-mediated signaling pathways including Spp1, Ikbkb (inhibitor of κB kinase β), Jun (jun protooncogene), Myc (myelocytomatosis oncogene), Fos (FBJ osteosarcoma oncogene), and Bcl2 (B-cell CLL/lymphoma 2) were selected for quantitative reverse transcription PCR (qRT-PCR) analysis. The primers were designed with Primer Express 2.0 software according to mRNA sequences of the above six genes and internal control β-actin, and synthesized by Shanghai Generay Biotech Co., Ltd. (Table 1). qRT-PCR was carried out as described previously (Zhang et al., 2014) using above-mentioned specific primers. Every sample was analyzed in triplicate, and no template control (NTC) with water instead of the template was included in each run.

2.2. Rat Genome 230 2.0 microarray detection and data analysis

2.6. Bioinformatics analysis

Microarray detection and further data analysis were both performed according to the methods previously described (Xu et al., 2012; Li et al., 2014). Briefly, total RNA was extracted from 0.5 g liver tissue according to the manual of TRIzol reagent (Invitrogen, Carlsbad, CA). The cDNA first chain was synthesized using the SuperScript II RT reverse transcription system (Invitrogen, Carlsbad, CA), and the second chain was synthesized according to the guidelines for the Affymetrix cDNA kit. Biotinlabeled cRNA was prepared using GeneChip IVT kit according to the manufacturer's instructions. cRNA fragments of 35–200 bp were prepared by fragmentation reagent treatment for 35 min at 94 °C. The Rat Genome 230 2.0 Microarray was hybridized with the cRNA fragments, which had been pretreated. They were then stained, washed automatically using a GeneChip Fluidics Station 450 and scanned and imaged with a GeneChip Scanner 3000. The signal values were normalized by using Affymetrix GCOS 2.0. The data of each array were initially normalized by scaling all signals to a target intensity of 200. To minimize the experimental operation and microarray test differences, each sample was repeated three times, and the average value was used for statistical analysis.

In order to comprehensively characterize the expression patterns of OPN signaling pathway-related genes during LR, we employed k-means clustering to classify the significantly changed genes in OPN signaling pathways according to gene expression similarity. Then the genes in every cluster were uploaded onto Expressing Analysis Systematic Explorer (EASE) to determine whether some Gene Ontology (GO) categories are over-represented or not. EASE analyses were conducted to identify over-represented GO categories according to EASE score, with Bonferroni multiple testing correction (Hosack et al., 2003). The GO categories with EASE scores of b 0.05 and b 0.01 are considered to be significantly and highly significantly over-represented, respectively. Generally, liver regeneration is divided into three stages, including the initiation stage (2–6 h after PH), progression stage (12–72 h after PH) and termination stage (120–168 h after PH) (Wang and Xu, 2011). To further predict how OPN signaling pathways modulates physiological processes at different phases of LR, genes associated with each branch of OPN signaling pathways were put together. Then, Ingenuity Pathway Analysis (IPA) version 9.0 (Redwood City, CA, http://www.ingenuity.com) software was

2.3. Identification of liver regeneration-related genes The normalized signal values in PH group to that in control were used to calculate the relative value, that is, ratio value of gene expression abundance. In this study, when ratio value is ≥ 2, it means that gene expression was significantly up-regulated, when ≤0.5, significantly down-regulated, and when 0.5–2, biologically non-significant. In addition, only the genes which significantly changed at least at one time point during LR with 0.01 ≤ P b 0.05 or P ≤ 0.01 between PH and SO, were referred to as associated with LR. 2.4. Confirmation of OPN-mediated signaling pathways and their related genes Previous studies have reported that OPN could deliver signal to cells through PI3K/AKT, MAPK and NF-κB signaling pathways upon binding to integrins (Sodek et al., 2000; Denhardt et al., 2001;

Table 1 Primer sequences used in qRT-PCR. Genes

Accession numbers

Spp1

NM_012881##

Ikbkb

NM_053355

Jun

NM_021835

Myc

NM_012603

Fos

NM_022197

Bcl2

NM_016993

Primer sequences FP: 5′-TGATGACGACGACGATGACGATGG-3′ RP: 5′-ACGCTGGGCAACTGGGATGACCTT-3′ FP: 5′-GCACCTTGGATGACCTAGAGG-3′ RP: 5′-CTGAGAGTAAATCACCCGCACT-3′ FP: 5′-TGCAAAGATGGAAACGACCTT-3′ RP: 5′-CCGTAGGCGCCACTCT-3′ FP: 5′-GAGGAGAAACGAGCTGAAGCG-3′ RP: 5′-TGAACGGACAGGATGTAGGC-3′ FP: 5′-CGGGTTTCAACGCCGACTA-3′ RP: 5′-TTGGCACTAGAGACGGACAGA-3′ FP: 5′-GACGCGAAGTGCTATTGGTA-3′ RP: 5′-TCAGGCTGGAAGGAGAAGAT-3′

Abbreviations: FP, forward primer; RP, reverse primer.

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utilized to analyze the heatmap of biofunctions based on the expression changes of each branch-related genes. Briefly, the differentially expressed genes in each branch and their corresponding extremum of expression values at three stages of LR were uploaded to the “Dataset Files” of IPA. Then core analysis and comparison analyses among three stages of LR proceeded successively. Next, heatmaps of biofunctions were obtained in the model of “Diseases and Functions,” and every heat map square can be clicked to display the network and the possible crucial genes in the network. In addition, to further predict the more predominant pathway in OPN-mediated five branches, the differentially expressed genes involved in OPN signaling pathways were analyzed by IPA for canonical pathways. Similarly, a dataset containing these genes and respective extremum of expression values was uploaded into “Dataset Files” of the IPA. Then IPA core analysis was performed, and the canonical pathways obtained in this study were identified from the IPA library based on Fisher's exact test.

3. Results 3.1. Validation of chip results by qRT-PCR To confirm the results of the microarray analysis, real-time qRT-PCR assays were used to detect the expression changes of six genes in regenerating livers at 0, 2, 6, 12, 24, 30, 36, 72, 120 and 168 h after PH. The genes surveyed were composed of Spp1, the corresponding gene for OPN protein, and Ikbkb, a gene involved in signaling transduction and Jun, Myc, Fos and Bcl2 four downstream target genes for OPN-mediated signaling pathways. The results showed that, although there were somewhat differences between the relative degrees of up-regulation measured by qRT-PCR and microarray, expression trends of the genes detected by the above two methods were generally consistent, suggesting that the array results were reliable (Fig. 1). 3.2. Global expression profiles of OPN signaling pathway-related genes

2.7. Western blot analysis The expressions of OPN and several key proteins in OPN-mediated signaling pathways were measured by Western blot (WB) analysis according to Towbin's method (Towbin et al., 1979). Briefly, 50 μg proteins from regenerating livers at every time point were separated by SDS–PAGE and then transferred to a PVDF membrane (GE Healthcare). After transferred, blocked with 5% nonfat-milk, the membranes were subsequently incubated overnight at 4 °C with primary antibodies, including rabbit anti-OPN (Santa Cruz, 1:500), −JAK3 (Bioss, 1:1000), − ERK1/2 (Cell Signaling, 1:2000), − JNK3 (Cell Signaling, 1:1500), −AKT3 (Bioss, 1:1000), −MYC (Cell Signaling, 1:2000). Then the membrane was further incubated with horseradish peroxidase-conjugated secondary antibodies goat anti-rabbit IgG (Cell signaling, 1:2000) for 2 h. Finally, protein bands were visualized with the enhanced chemiluminescence substrate (Western Lightning® Plus-ECL), and the relative abundance of target proteins was measured by using ImageQuant TL software. β-actin (Cell signaling, 1:2000) was served as an internal reference in this study.

In this study, IPA software and several database including GenMAPP, KEGG, BIOCARTA, QIAGEN and Biocompare were relied mainly on to construct the interaction network of OPN signaling pathways. The results showed that 5 branches and total of 151 genes were involved in OPNmediated signaling pathways. Branch 1 JAK/STAT signaling pathway: OPN/CD44 → JAK → STAT; Branch 2 extracellular regulated protein kinases (ERK)1/2 signaling pathway: OPN/CAV1 → FYN → SOS → RAS → RAF, OPN/ITG → FAK → SRC → SOS/C3G → RAS/RAP1 → RAF; Branch 3 c-Jun NH2-terminal kinase (JNK) signaling pathway: OPN/ ITG → FAK/SRC → PI3K → RAC → PAK/MAP3K → MEK4/7 → JNK; Branch 4 NF-κB signaling pathway: OPN → RTK → PI3K → Akt → NF-κB, OPN → CD44 → PKC → IKK → NF-κB. In branch 5, cytoskeletonassociated signaling pathway based on ras homolog family member A (RhoA) branch was included. Then Rat Genome 230 2.0 was used to detect expression profiles of OPN signaling pathway-associated genes at 2, 6, 12, 24, 30, 36, 72, 120 and 168 h after PH, and the results showed 81 genes were significantly changed at mRNA level, and among which, 65 genes were up-regulated, 12 genes down-regulated, 4 genes up/ down-regulated (Supplementary Table 1 and Fig. 2).

Fig. 1. Verification of gene expression in regenerating livers after partial hepatectomy by qRT-PCR. The results of qRT-PCR and Rat Genome 230 2.0 array are presented as a real line and a dotted line, respectively. X-axis represents relative mRNA abundance of gene. The densitometric values represent the mean values of triplicate determinations, and the error bar represents the inter-variability.

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Fig. 2. The network of five branches of OPN-mediated signaling pathway and their relationships were shown. The ordinal numbers in circle represent JAK/STAT, ERK1/2, JNK, NF-κB, and RhoA signaling pathway, respectively.

Subsequently, the above-mentioned 81 genes were categorized into 5 clusters by k-means according to gene expression similarity (Fig. 3A): Cluster 1 (C1) contained 31 genes which displayed two expression peaks at 6–12 h and 72 h after PH. Cluster 2 (C2) included 6 genes which were significantly down-regulated in LR. Twenty-six genes were embodied in cluster 3 (C3), and majority of them were strengthened in expression at 72 h, while others at 2 h. Cluster 4 (C4) involved 9 genes which were strikingly up-regulated with peaking at 6–30 h and 72 h after PH. There were 9 genes classified into cluster 5 (C5), and all of them exhibited significant expression at least one time point during LR, but the variations for them were relatively small (Fig. 3B).

3.3. Functional enrichment analysis of OPN signaling pathway-related genes After expression patterns of OPN signaling pathway-related genes during rat LR were characterized, EASE analysis was carried out for the gene sets of C1-5 in Fig. 3 to determine whether some GO categories are over-represented or not, and the over-represented GO categories with EASE scores (P values) of b0.05 were selected out. Obviously, C1 was enriched with categories of cell activation and proliferation, etc. Regeneration inhibition and cell differentiation-related genes were mainly observed in C3. Stress response and inflammation response-related genes were predominant in C4, while a majority of stress responserelated genes in C1 and C3. Phosphorylation-associated genes involved in intracellular signal transduction were enriched in C1, C2 and C3, while genes related to cytoskeletal reorganization, cell adhesion and migration were scattered in C1, C3 and C5 (Table 2).

3.4. Predicted regulatory effects of branches of OPN signaling pathway on LR For every branch of OPN signaling pathway, function enrichment heatmaps at three stages of LR were obtained through the function modules of “Core analysis” and “Comparison analysis” in IPA software (Fig. 4). The results showed that JAK/STAT signaling pathway may participate in the proliferation of immune cell, but not relevant to inflammation response. In whole process of LR (mainly at the initiation and progression phases), ERK1/2, JNK, NF-κB and RhoA signaling pathways, especially ERK1/2, may be involved in the proliferation of various cell types. The physiological processes modulated by NF-κB and JNK signaling pathway were similar, but NF-κB signaling pathway may have stronger effect on inhibition of apoptosis and promotion of cell survival than the latter. As expected, cytoskeleton associated signaling pathways based on RhoA may promote cytoskeleton reorganization, and then facilitate cell movement during the whole LR. To further clarify which branch may play more important roles during LR, pathway analysis was performed to connect the differentially expressed genes with canonical biological pathways by IPA software. A Benjamini–Hochberg corrected Fischer's exact test was utilized to calculate the p-values associated with a canonical pathway. Additionally, a ratio was used to determine the number of focus molecules to overall molecules in each canonical pathway. Therefore, we analyzed 81 genes that were differentially expressed during rat LR using IPA, and the significantly enriched five branches were sequenced in Fig 5. Obviously, five branches including JAK/STAT, ERK, JNK, NF-κB and RhoA signaling pathways were all activated during LR. However, ERK signaling had the smallest p-value and may play more vital roles in LR, which

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Fig. 3. Global expression profiles of OPN-mediated signaling pathway-related genes during rat liver regeneration. A. K-means clustering of total of 81 genes. Red and green colors denote the expression level higher and lower than the control, respectively. B. Differences in clusters (C) 1–5.

was consistent with the result in Fig. 4. Furthermore, NF-κB signaling ranked before JNK signaling, suggesting NF-κB signaling may have more effects than the latter on LR. Surprisingly, JAK/STAT signaling stayed before RhoA signaling, which was contrary to the result displayed in Fig. 4. According to the microarray results, besides remarkable upregulation of Spp1 at 2–30 h, 72 h and 168 h, Jak3 in JAK/STAT signaling was slightly up-regulated at 6 h, Mapk3 in ERK1/2 signaling at 2 h and 30–168 h, Mapk10 in JNK signaling pathway at 2–36 h and 120 h, and Akt3 in NF-κB signaling and one key downstream gene Myc were both notably up-regulated at the initiation phase of LR. To further confirm the microarray results, the expressions of OPN, JAK3, ERK1/ 2, JNK3, AKT3 and MYC, which are corresponding proteins encoded by the above-mentioned 6 genes, were detected by WB. The results in Fig. 6A showed that ERK1/2 protein was up-regulated at 2–6 h and 24–120 h after PH, JNK3 at 2–36 h and 120–168 h, AKT3 at 6– 12 h and MYC at 2–6 h, 24–36 h and 120–168 h, but the expression abundance of target proteins detected by WB was overall lower than that of genes by microarray analysis (Fig. 6B). Therefore the expression trends of ERK1/2, JNK3, AKT3 and MYC at protein level were not quite similar to those at mRNA level. In addition, JAK3 protein was not significantly affected at protein level, which was in agreement with the slightly up-regulation of Jak3. Notably, OPN showed smaller changes in protein expression, which looks different from the striking changes in mRNA. However, the relative abundance values obtained by ImageQuant TL software showed that the expression of OPN exceeded control levels by more than 1.5-fold at 2–12 h and 36–168 h.

4. Discussion OPN, besides closely related to the occurrence of liver disease, probably could promote hepatic self-repair and then protect liver during LR. This study was designed to uncover the expression profiles of OPN and its receptors, and then the possible regulatory role of OPN during LR. The microarray detection results showed that 81 genes involved in OPN-mediated signaling pathways were significantly changed at mRNA level. Subsequently, qRT-PCR analysis revealed that Spp1 was upregulated at 6–12 h and 72 h, and Myc was up-regulated at 2–6 h and 168 h. Thus it was confusing that Myc, acting as downstream to Spp1, presented earlier up-regulation than Spp1. Such phenomenon could be partially explained by the following WB detection results which indicate that the above two proteins of OPN and MYC were both up-regulated from 2 h with peaking at 6 h. In addition, the expression of JAK3 protein detected by WB analysis was different from that of its corresponding gene, which was the unique significantly-changed gene in JAK/STAT signaling pathway. JAK3 protein did not exhibit significant change and thus JAK/STAT signaling may not be affected during rat LR. Furthermore, WB analysis results showed that the expression trends of OPN, ERK1/2, JNK3 and AKT3 were up-regulated, demonstrating that PH indeed promoted the expressions of OPN and some key regulators in OPN signaling pathways, and these regulators may play a role during rat LR. The studies from Wu et al. (2014) and Liu et al. (2014) reported that OPN could promote the growth and proliferation of gastric cancer cells and colorectal cancer cells. In this study, several cell proliferationrelated genes including Jun, Fos and Myc were up-regulated during LR,

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Table 2 Overrepresented functional categories in five clusters of OPN-mediated signaling pathway-related genes during rat liver regeneration. P-value represents EASE score (a modified Fisher's exact test). Enriched biological processes Cluster 1 Response to organic substance Response to drug Response to abiotic stimulus Cellular response to stress Response to mechanical stimulus Response to inorganic substance Response to bacterium Positive regulation of immune system process Cell activation Lymphocyte activation Leukocyte activation T cell activation Positive regulation of cell activation Cell proliferation T cell proliferation Mononuclear cell proliferation Lymphocyte proliferation Leukocyte proliferation Regulation of cell proliferation Positive regulation of cell proliferation Small GTPase mediated signal transduction Intracellular signaling cascade Protein kinase cascade Phosphorylation Protein amino acid phosphorylation Phosphorus metabolic process Phosphate metabolic process Regulation of cellular protein metabolic process Cytoskeleton organization Actin cytoskeleton organization Cell motion Cell motility Cell migration Cell adhesion Muscle tissue development Muscle organ development Cardiac muscle tissue morphogenesis

P-Value

Enriched biological processes

2.1E − 06 6.9E − 04 1.7E − 03 2.5E − 03 2.4E − 05 2.8E − 03 1.2E − 03 1.4E − 04 1.7E − 04 3.1E − 05 9.5E − 05 1.0E − 04 1.8E − 03 2.2E − 03 3.9E − 05 2.3E − 06 2.1E − 06 2.3E − 06 7.0E − 05 1.7E − 05 1.5E − 03 6.8E − 04 2.7E − 03 7.7E − 04 3.2E − 04 2.1E − 03 2.1E − 03 2.6E − 04 5.9E − 05 3.7E − 05 2.0E − 03 6.9E − 04 2.4E − 04 3.2E − 03 2.3E − 04 5.0E − 04 1.5E − 03

Cluster 2 Phosphate metabolic process Phosphorus metabolic process Protein amino acid phosphorylation Cluster 3 Response to organic substance Response to growth hormone stimulus Response to inorganic substance Intracellular signaling cascade Integrin-mediated signaling pathway Growth hormone receptor signaling pathway Cell adhesion Cell migration Cell morphogenesis Cell motility Cell motion Cell projection organization Cell-matrix adhesion Cell-substrate adhesion Regulation of cell adhesion Actin cytoskeleton organization Actin filament-based process Negative regulation of cell differentiation Negative regulation of myeloid cell differentiation Regeneration Cellular component morphogenesis Cluster 4 Response to steroid hormone stimulus Response to extracellular stimulus Response to organic substance Response to wounding Response to vitamin Response to hormone stimulus Response to endogenous stimulus Response to nutrient Inflammatory response Cluster 5 Regulation of actin cytoskeleton Focal adhesion

and hepatic cell proliferation and activation-related genes were found to be predominant in C1 with two peaks at 6–12 h and 72 h, respectively. Cell proliferation activity predicted by IPA was stronger in initiation phase than that in progression phase, which was not consistent well with the conclusion that cell proliferation during LR mainly occurred at 24–72 h (Khan and Mudan, 2007). Furthermore, several ERK1/2 signaling pathway-related genes including Rras2, Rapgef1, Crkl and Mapk3 were enhanced in mRNA expression and also enriched in C1, and it was more clear that ERK1/2 signaling pathway was mainly involved in promoting DNA synthesis, S phase, mitosis and cell cycle progression (Fig. 4), suggesting that ERK1/2 signaling pathway may play an important role in promoting hepatic cells proliferation, which is similar to the report by Li et al. (2011). Overwhelming evidence has shown that OPN could inhibit the apoptosis of NKT cells, neutrophils, macrophages and hepatoma cells (Kiefer et al., 2010; Wu et al., 2012). Functional enrichment heatmap generated from IPA indicated that apoptosis and cell death were both significantly decreased in the progression phase, which was in agreement with the enhanced activity of cell proliferation at this stage of LR (Khan and Mudan, 2007). Zhao et al. (2008) have reported that OPN siRNA led to down-regulation of integrin genes and Bcl-2/Bcl-x, and promoted apoptosis mediated by mitochondria in HCC cell line. Similarly, this study found that the mRNA level of OPN was strikingly increased at 2–30, 72 and 168 h after PH, Bcl-2 at 6 and 72–168 h, and several integrin genes were up-regulated (Supplementary Table 1), demonstrating that OPN may exert anti-apoptosis effect on LR. In addition, OPN is profibrogenic by promoting HSC activation in vitro and in vivo (Leung et al., 2013). Over-expression of OPN could enhance viability in cultured

P-Value 3.1E − 03 3.1E − 03 2.4E − 02 1.4E − 04 2.1E − 04 1.3E − 03 1.4E − 04 5.7E − 05 8.8E − 05 1.3E − 04 8.5E − 05 3.0E − 04 2.5E − 04 7.6E − 04 4.0E − 04 1.8E − 04 3.0E − 04 5.9E − 05 2.5E − 04 3.0E − 04 3.3E − 05 8.5E − 04 1.2E − 03 4.8E − 04 7.1E − 04 7.9E − 04 1.9E − 03 2.1E − 03 2.3E − 03 3.6E − 03 5.0E − 03 7.6E − 03 8.4E − 03 4.1E − 07 2.0E − 05

liver progenitors (Coombes et al., 2014), and Arai et al. also conferred that OPN probably induce activation of oval cell in LR (Arai et al., 2004; Arai et al., 2006). This study consistently found that the activity trends of cell survival and viability negatively correlated with that of apoptosis. Further, the enhancement of cell survival and activation was more associated with ERK1/2 and NF-κB pathways (Fig. 4), suggesting that the above two pathways were likely to play key roles in cell survival and activation during LR. It is generally believed that cell adhesion and migration are closely related to angiogenesis, tumor infiltration and metastasis in liver cancer. Similarly, they were important for structure-function rebuilding in liver regeneration (Li et al., 2007). The expression level of OPN often correlated with invasive ability of HCC cell lines (Huang et al., 2010), illustrating that OPN was closely related to cell migration and invasion. Furthermore, Denhardt et al. (2001) had shown that OPN could activate RhoA-dependent gellsolin-associated PI3K via avb3 and enhanced cytoskeletal rearrangement, while Zou et al. (2013) reported that OPN might promote cytoskeletal rearrangement of mesenchymal stem cells via FAK and ERK signaling pathways. In this study, functional enrichment analysis by EASE showed that cytoskeletal rearrangement-, cell adhesion and migration-related genes were distributed in C1, C3 and C5 with some peaking at 2–12 h and 72 h, while some others were significantly changed at one time point in 2–12 h. More evidently, a number of genes including Acta1, Actb, Myh8, Myh9, Myh10, Myl3, and Myl7, which encoded cytoskeleton proteins ACTA, ACTB and MRLC, were upregulated, and our IPA analysis confirmed that RhoA signaling pathway contributed to cytoskeletal rearrangement and organization, cell spreading, migration and invasion during the whole LR. Furthermore, the

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Fig. 4. Biofunction heatmap analysis of OPN-mediated JAK/STAT, ERK1/2, JNK, NF-κB, and RhoA signaling pathway-related genes at three stages of liver regeneration by IPA software. The three columns from left to right in each pathway represent the initiation stage (I, 2–6 h), progression stage (P, 12–72 h) and termination stage (T, 120–168 h), respectively. The color of heat map square represents the activity of biofunctions. Red heat map square means activated biofunction, while blue heat map square means inhibited biofunction at certain stage of liver regeneration.

increased cell migration and invasion were also associated with ERK1/2, JNK, NF-κB signaling cascades and their related genes, which may coincide with the mechanisms of OPN promoting cell migration in several inflammatory diseases (Tuck et al., 2003; Zheng et al., 2009; Anwar et al., 2012). More innovatively, the activation of cell migration and invasion were found to be stronger in the progressing phase than that in the priming and terminal phases, indicating that it may be necessary for helping proliferated cells move to appropriate location in the progressing phase. Taken together, the expressions of OPN and its receptors genes were up-regulated, and the majority of genes related to OPN signaling pathways were found to be associated with LR induced by PH. Furthermore, the prediction analysis by EASE and IPA showed that cell proliferation,

survival, adhesion and migration, and inflammation response were facilitated, while apoptosis was inhibited. Our data also suggested the expression of OPN signaling pathway-related genes could account for the above changes in physiological processes. However, the conclusion is drawn mainly based on the microarray data and some protein data, and there is not direct cause–effect relationship between gene profiling and the conclusion. Therefore, in order to prove that these changes are truly dependent upon OPN, experiments of OPN overexpression or knockdown are needed to further analyze the regulatory effects of OPN signaling pathways on regenerating livers in future. In addition, we will consider RNA-Seq approach to profile transcriptional changes of OPN signaling pathways, so that more key regulators in OPN signaling pathways may be found to modulate liver regeneration.

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Fig. 5. OPN-mediated five canonical pathways were significantly enriched during rat liver regeneration by IPA analysis. Each histogram represents a particular pathway/branch. The size of the histogram is correlated with increasing overlap significance (Fisher's exact test p-value).

Fig. 6. Expression changes of OPN protein and several key regulators in OPN-mediated signaling pathways. A. The protein expression levels were detected by Western blot. β-actin was served as internal reference. B. The abundance values of above proteins were obtained by ImageQuant TL software.

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