Open Access

Microarray analysis of differentially expressed genes in L929 mouse fibroblast cells exposed to leptin and hypoxia

  • Authors:
    • Ping Ouyang
    • Sen Wang
    • He Zhang
    • Zhigang Huang
    • Pei Wei
    • Ye Zhang
    • Zhuguo Wu
    • Tao Li
  • View Affiliations

  • Published online on: May 17, 2017     https://doi.org/10.3892/mmr.2017.6596
  • Pages: 181-191
  • Copyright: © Ouyang et al. This is an open access article distributed under the terms of Creative Commons Attribution License.

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Abstract

Leptin and hypoxia are pro-fibrotic factors involved in fibrogenesis, however, the gene expression profiles remain to be fully elucidated. The aim of the present study was to investigate the regulatory roles of leptin and hypoxia on the L929 mouse fibroblast cell line. The cells were assigned to a normoxia, normoxia with leptin, hypoxia, and hypoxia with leptin group. The cDNA expression was detected using an Agilent mRNA array platform. The differentially expressed genes (DEGs) in response to leptin and hypoxia were identified using reverse transcription‑quantitative polymerase chain reaction analysis, followed by clustering analysis, Gene Ontology analysis and pathway analysis. As a result, 54, 1,507 and 1,502 DEGs were found in response to leptin, hypoxia and the two combined, respectively, among which 52 (96.30%), 467 (30.99%) and 495 (32.96%) of the DEGs were downregulated. The most significant functional terms in response to leptin were meiosis I for biological process (P=0.0041) and synaptonemal complex for cell component (P=0.0013). Only one significant pathway responded to leptin, which was axon guidance (P=0.029). Flow cytometry confirmed that leptin promoted L929 cell proliferation. The most significant functional terms in response to hypoxia were ion binding for molecular function (P=7.8621E‑05), glucose metabolic process for biological process (P=0.0008) and cell projection part for cell component (P=0.003). There were 12 pathways, which significantly responded to hypoxia (P<0.05) and the pathway with the highest significance was the chemokine signaling pathway (P=0.0001), which comprised 28 genes, including C‑C motif ligand (CCL)1, C‑X‑C motif ligand (CXCL)9, CXCL10, son of sevenless homolog 1, AKT serine/threonine kinase 2, Rho‑associated protein kinase 1, vav guanine nucleotide exchange factor 1, CCL17, arrestin β1 and C‑C motif chemokine receptor 2. In conclusion, the present study showed that leptin and hypoxia altered the profiles of gene expression in L929 cells. These findings not only extend the cell spectrum of leptin on cell proliferation, but also improve current understanding of hypoxia in fibroblast cells.

Introduction

Tissue fibrosis alters the tissue architecture and leads to organ dysfunction, which is major contributor to morbidity and mortality rates worldwide (1). The progression of fibrosis is similar in different organs, which is characterized by the activation and abnormal proliferation of fibroblasts/myofibroblasts and extracellular matrix remodeling (2). However, the mechanism underlying fibrogenesis is complex. Infection with pathogenic organisms, epigenetic alterations, B cells, transforming growth factor (TGF)-β signaling and TGFβ/small mothers against decapentaplegic (SMAD) 33-independent mechanisms have been reported to be involved in the activation of myofibroblasts (37). Several exogenous factors are also involved in fibrogenesis, including leptin and hypoxia (810). Previous studies have shown that leptin stimulates the production of tissue inhibitor of metalloproteinase 1 via the Janus kinase (JAK)/signal transducer and activator of transcription (STAT) pathway to directly promote fibrogenesis in hepatic stellate cells (11). Liver fibrosis is decreased in leptin- or leptin receptor-deficient mice (12). The in vitro administration of leptin to primary cardiofibroblasts has been found to result in the significant stimulation of pro-collagen Iα and also leads to a decrease in the gene expression of pro-matrix metalloproteinase-8, -9 and -13 at 24 h, which results in heart fibrosis (13). In addition, leptin is involved in renal fibrosis (14). Hypoxia is also an established profibrotic factor (9,15,16). In hepatic fibrosis, hypoxia acts as a major inducer of angiogenesis together with inflammation, and hepatic angiogenesis and fibrosis have been found to be closely associated in clinical and experimental conditions (8). Hypoxia was found to induce cardiac fibrosis by upregulating focal adhesion kinase in cardiac fibroblasts or in a mouse model of post-myocardial infarction (17). Hypoxia-induced deoxycytidine kinase contributes to epithelial proliferation in pulmonary fibrosis (18). Hypoxia is also involved in hepatic fibrosis through potentiating the activity of hypoxia inducible factor-1α, either directly or through the epidermal growth factor (EGF)/mitogen-activated protein kinase (MAPK) and vascular endothelial growth factor (VEGF)/AKT pathway (8). However, the effects of leptin and hypoxia on fibrosis remain to be fully elucidated. The aim of the present study was to investigate the gene expression profiles of leptin and hypoxia in mouse fibroblast cell line L929 and analyze their possible biological functions in fibrosis processes. The present study showed that leptin and hypoxia altered the profiles of gene expression in L929 cells. The pro-fibrotic roles of leptin may be through promoting L929 cell proliferation; whereas hypoxia affected L929 cell function primarily through the chemokine signaling pathway.

Materials and methods

Cell culture and treatment

The L929 mouse fibroblast cells, purchased from the Kunming Cell Bank (Kunming, China) were cultured in Dulbecco's modified Eagle's medium with 5% fetal bovine serum (Gibco; Thermo Fisher Scientific, Inc., Waltham, MA, USA) in a humidified 5% CO2 incubator at 37°C. The L929 cells were used for all the following experiments. For leptin treatment, mouse recombinant leptin (200 ng/ml; Sigma-Aldrich; Merck Millipore, Darmstadt, Germany) was added to the cells. For hypoxic treatment, the L929 cells were transferred to a hypoxia chamber (MIC101; Billups-Rothenberg, Inc., Del Mar, CA, USA) where the total oxygen concentration was reduced to <1%.

cDNA expression array

The cells were cultured in 10 cm plates with 2.5×106 cells and divided into the following four groups: Group I, cells cultured in normoxia; Group II, cells treated with leptin in normoxia; Group III, cells cultured in hypoxia; Groups IV, cells treated with leptin in hypoxia. Every group included three parallel samples and the treatment temperature was 37°C. After 24 h, the cells were collected and placed in TRIzol reagent (Invitrogen; Thermo Fisher Scientific, Inc.), respectively.

Total RNA was extracted using TRIzol reagent according to the manufacturer's protocol. The RNA was purified using the mirVana miRNA isolation kit (Ambion; Thermo Fisher Scientific, Inc.). The RNA quality from each sample was assessed by visualization of the 28S/18S ribosomal RNA ratio using 1% formaldehyde denaturing gel electrophoresis. The Agilent mouse mRNA array was designed with eight identical arrays per slide (8×60K format), with each array containing probes interrogating ~39,430 Entrez Gene RNAs. The array also contained 1,280 Agilent control probes. The arrays were hybridized in an Agilent hybridization oven overnight at a rotation speed of 40 g at 42°C and washed with two consecutive solutions (0.2% SDS, 2X SSC at 42°C for 5 min and 0.2X SSC for 5 min at room temperature).

The array data were analyzed for data summarization, normalization and quality control using GeneSpring software V12 (Agilent; Thermo Fisher Scientific, Inc.) (19). To select the differentially expressed genes (DEGs), threshold values of ≥2 and ≤-2-fold change (FC) and a P-value of 0.05 were used. The data was Log2-transformed and median centered by genes using the Adjust Data function of Cluster 3.0 software (www.falw.vu/~huik/cluster.htm), and then further analyzed by hierarchical clustering with average linkage (20). Finally, tree visualization was performed using Treeview (Stanford University School of Medicine, Stanford, CA, USA) (21).

Reverse transcription-quantitative polymerase chain reaction (RT-qPCR) analysis

The DEGs regulated by leptin and hypoxia identified by the microarray, were verified using RT-qPCR analysis. In total, five genes [Arrestin β1 (Arrb1), C-C motif ligand (Ccl)1, G protein-coupled receptor kinase 4 (Grk)4, Ccl17 and C-C motif chemokine receptor 2 (Ccr2)] were selected. Total RNA was extracted and the quality was assessed, as described above. The first-strand cDNA was synthesized using 500 ng total RNA in a 20.0 µl final volume by reverse transcription utilizing PrimeScript™ RT Master mix (Perfect Real Time; Takara Bio, Inc., Otsu, Japan). Subsequently, the cDNA was diluted in five volumes sterile water. The qPCR was performed in a volume of 20.0 µl using 2.0 µl cDNA, 0.8 µl specific forward primer, 0.8 µl specific reverse primer, 10.0 µl SYBR® Select Master mix (Thermo Fisher Scientific, USA) and 6.4 µl deionized water. The amplification was performed using a Roche LightCycler® detection system (Roche Diagnostics, Indianapolis, IN, USA). The primers (Sangon Biotech Co, Ltd., Shanghai, China) were as follows: Arrb1, forward 5′-AGGCATCACTGGATAAGGAG-3′ and reverse 5′-GTCTTGTTGGTGTTGTTGGTG-3′; Ccl1, forward 5′-TTCCCCTGAAGTTTATCCAG-3′ and reverse 5′-GATTTTGAACCCACGTTTTG-3′; Grk4, forward 5′-ATGGAGGGGATTTGAAGTAC-3′ and reverse 5′-CTGGCTTTAGGTCTCTGTAT-3′; Ccl17, forward 5′-GCTGCCTGGATTACTTCAAAG-3′ and reverse 5′-TTTGTCTTTGGGGTCTGCAC-3′; Ccr2, forward 5′-TGTAGTCACTTGGGTGGTGG-3′ and reverse 5′-TAAGGGCCACAGGTGTAATG-3′. For all RT-qPCR experiments, negative controls comprised a non-reverse transcription reaction and a non-sample reaction (data not shown). Actin was amplified as an internal standard. The 2−∆∆Cq method was applied for data analysis (22).

Functional enrichment analysis

The Database for Annotation, Visualization, and Integrated Discovery (DAVID) is widely used in functional enrichment analysis of DEGs (23). In the present study, DAVID (david.abcc.ncifcrf.gov) was used to perform functional enrichment analysis for the DEGs regulated by leptin, hypoxia and the two combined, respectively. The genes were mapped to Gene Ontology (GO) terms for this purpose. The GO annotation (www.geneontology.org) provides a descriptive framework and functional annotation of DEGs, and is comprised of biological processes, cellular components and molecular functions. In addition, Kyoto Encyclopedia of Genes and Genomes (KEGG; http://www.genome.jp/kegg/) pathway enrichment analysis was performed to map the potential pathways of the DEGs (24). The P-value cut-off associated with this analysis was set at P<0.05 in order to identify significantly enriched functional terms and pathways.

Cell cycle analysis using flow cytometry (FCM)

The cells were seeded at a density of 10×104 per well in six-well plates in triplicate and allowed to adhere for 24 h. Following starvation, the cells were treated with or without leptin (200 ng/ml) in normoxic conditions at 37°C. Following culture for 24 h, the cells were harvested and fixed in 70% cold ethanol at −20°C overnight. The cells were stained with propidium iodide (Sigma-Aldrich; Merck Millipore) at 50 µg/ml with 20 µg/ml RNase A at room temperature in the dark for 1 h prior to analysis. The cell population fraction in each phase of the cell cycle was determined as a function of the DNA content using FCM (FACSCalibur; BD Biosciences, Franklin Lakes, NJ, USA). Data analysis was performed using FlowJo v10 software (Tree Star, Inc., Ashland, OR, USA) (25). This experiment was repeated three times.

Statistical analysis

Values are presented as the mean ± standard deviation unless otherwise indicated using SPSS version 13.0 (SPSS, Inc., Chicago, IL, USA). Statistical analysis was performed using Student's t-test. P<0.05 was considered to indicate a statistically significant difference.

Results

Microarray analysis and hierarchical clustering

The genes induced in the cultured L929 cells by leptin, hypoxia and the two combined were analyzed using a cDNA array. The array included four groups containing 12 samples. The cluster results of the four sets of microarray data are shown in Fig. 1. The two primary gene clusters were identified visually based on the heat map signal intensity in groups I and II, vs. groups III and IV. The expression of genes in cluster 1 were higher in groups I and II, compared with that in groups III and IV, suggesting that those genes may be suppressed by hypoxia. By contrast, cluster 2 consisted of genes activated by hypoxia. It appeared that leptin was a weak factor affecting gene profiling in normoxia and hypoxia.

The genes with FC values >2.0 and P<0.05 were considered to be a DEG. In the present study, 54 DEGs were found in the leptin-treated group, of which 52 (96.30%) were downregulated. A total of 1,507 DEGs were found under hypoxia treatment, of which 467 (30.99%) were downregulated. In the group treated with leptin and hypoxia, 1,502 DEGs were found, among which 495 (32.96%) were downregulated. However, compared with the hypoxia group, there were only 11 genes altered in the leptin and hypoxia treatment group, comprising three (27.27%) downregulated and eight (72.73%) upregulated genes.

Verification of array data using RT-qPCR analysis

To assess the reliability of the array data, five genes (Arrb1, Ccl1, Grk4, Ccl17 and Ccr2) were selected for amplification, with normoxia and hypoxia samples as a template, using RT-qPCR analysis. The 2-∆∆Cq method was used for the determination of target mRNA following normalizing of target mRNA Cq values with those for actin (ΔCq). In the array data, two genes (Arrb1 and Ccl1) were upregulated in the hypoxia samples by 3.51- and 6.78-fold, respectively. In the RT-qPCR experiments, the upregulated FC values were 2.78- and 5.44-fold, respectively (Fig. 2). The other three genes (Grk4, Ccl17 and Ccr2) were downregulated in the hypoxia samples, by 2.11-, 2.11- and 2.15-fold, respectively, and the FC values in the RT-qPCR experiments were 1.92-, 3.19- and 2.87-fold, respectively (Fig. 2). These results suggested that the array data was in correspondence with the RT-qPCR experiments.

Functional enrichment analysis

To investigate the biological roles of the DEGs regulated by leptin, hypoxia and the two combined in L929 cells, a categorized GO enrichment analysis was performed, comprising 54, 1,507 and 1,502 genes, respectively (Tables IIII). For the DEGs response to leptin, meiosis I (P=0.004) and synaptonemal complex (P=0.001) were the most significantly enriched functional terms for biological processes and cellular components, respectively. For the DEGs response to hypoxia, glucose metabolic process (P=0.0008), cell projection part (P=0.003) and ion binding (P=7.8621E-05) were the most significantly enriched functional terms for biological processes, cellular components and molecular functions, respectively. For the DEGs regulated by leptin and hypoxia combined, phosphate metabolic process (P=0.0007) and extracellular region (P=0.0022) were the most significantly enriched functional terms for biological processes and cellular components, respectively.

Table I.

GO analysis for the differentially expressed genes regulated by leptin.

Table I.

GO analysis for the differentially expressed genes regulated by leptin.

TermGenes (n)P-value
Molecular function
Biological process
  GO:0007127 meiosis I30.004056677
  GO:0022402 cell cycle process50.021448529
  GO:0051327 M phase of meiotic cell cycle30.023847468
  GO:0007126 meiosis30.023847468
  GO:0007049 cell cycle60.023981901
  GO:0051321 meiotic cell cycle30.024865727
  GO:0007129 synapsis20.045322159
  GO:0070192 chromosome organization involved in meiosis20.045322159
Cell component
  GO:0000795 synaptonemal complex30.001322361
  GO:0044454 nuclear chromosome part40.002698438
  GO:0000793 condensed chromosome40.003006214
  GO:0000228 nuclear chromosome40.004250276
  GO:0000794 condensed nuclear chromosome30.005772372
  GO:0044427 chromosomal part50.010435104
  GO:0005694 chromosome50.018637296
  GO:0000800 lateral element20.018883838

[i] GO, Gene Ontology.

Table III.

GO analysis for the differentially expressed genes regulated by leptin and hypoxia.

Table III.

GO analysis for the differentially expressed genes regulated by leptin and hypoxia.

TermGenes (n)P-value
Molecular function
Biological process
  GO:0006796 phosphate metabolic process870.00069201
  GO:0006793 phosphorus metabolic process870.00069201
  GO:0016265 death570.000914867
  GO:0006468 protein amino acid phosphorylation670.001122958
  GO:0017157 regulation of exocytosis90.001368273
  GO:0008219 cell death550.001517519
  GO:0055114 oxidation reduction680.002418208
  GO:0012501 programmed cell death510.002614104
  GO:0044271 nitrogen compound biosynthetic process350.004597316
  GO:0006915 apoptosis490.004983028
  GO:0016310 phosphorylation700.005034959
  GO:0003016 respiratory system process40.005961782
  GO:0009743 response to carbohydrate stimulus70.008246776
  GO:0006006 glucose metabolic process190.009614291
  GO:0051241 negative regulation of multicellular organismal process150.010348645
  GO:0007601 visual perception150.011259001
  GO:0032940 secretion by cell230.011798862
  GO:0050953 sensory perception of light stimulus150.012230633
  GO:0046903 secretion260.013035463
  GO:0001666 response to hypoxia110.013616099
  GO:0070482 response to oxygen levels110.015106629
  GO:0009746 response to hexose stimulus60.016635896
  GO:0001974 blood vessel remodeling60.016635896
  GO:0009749 response to glucose stimulus60.016635896
  GO:0034284 response to monosaccharide stimulus60.016635896
  GO:0006730 one-carbon metabolic process160.01753354
  GO:0009719 response to endogenous stimulus220.019740633
  GO:0048608 reproductive structure development170.020659779
  GO:0048545 response to steroid hormone stimulus100.023972008
  GO:0003013 circulatory system process150.024166653
  GO:0008015 blood circulation150.024166653
  GO:0001775 cell activation270.025299039
  GO:0007242 intracellular signaling cascade810.02535934
  GO:0006865 amino acid transport110.026707116
  GO:0006681 galactosylceramide metabolic process30.027127455
  GO:0019374 galactolipid metabolic process30.027127455
  GO:0005996 monosaccharide metabolic process220.028503233
  GO:0019318 hexose metabolic process200.029456322
  GO:0006470 protein amino acid dephosphorylation150.029624933
  GO:0045944 positive regulation of transcription from RNA polymerase II promoter360.030944318
  GO:0006778 porphyrin metabolic process60.032936937
  GO:0033013 tetrapyrrole metabolic process60.032936937
  GO:0003006 reproductive developmental process280.033137813
  GO:0003001 generation of a signal involved in cell-cell signaling120.033562678
  GO:0009967 positive regulation of signal transduction200.034460687
  GO:0046324 regulation of glucose import50.040773001
  GO:0006357 regulation of transcription from RNA polymerase II promoter560.041404785
  GO:0045893 positive regulation of transcription, DNA-dependent400.041795439
  GO:0006979 response to oxidative stress120.041889132
  GO:0051254 positive regulation of RNA metabolic process400.045730238
  GO:0009220 pyrimidine ribonucleotide biosynthetic process40.047696549
  GO:0009218 pyrimidine ribonucleotide metabolic process40.047696549
  GO:0010827 regulation of glucose transport50.048213767
  GO:0042398 cellular amino acid derivative biosynthetic process80.049928789
Cell component
  GO:0005576 extracellular region1450.002250808
  GO:0044463 cell projection part230.003001467
  GO:0005777 peroxisome160.00482117
  GO:0042579 microbody160.00482117
  GO:0042995 cell projection550.011330557
  GO:0045121 membrane raft130.013007776
  GO:0031225 anchored to membrane240.015194373
  GO:0005886 plasma membrane2270.016114278
  GO:0008021 synaptic vesicle110.017112432
  GO:0044456 synapse part240.019656437
  GO:0033267 axon part60.025413
  GO:0044421 extracellular region part680.028509841
  GO:0019898 extrinsic to membrane440.035509102
  GO:0005730 nucleolus310.035643165
  GO:0043232 intracellular non-membrane-bounded organelle1520.036036538
  GO:0043228 non-membrane-bounded organelle1520.036036538

[i] GO, Gene Ontology.

Pathway enrichment analysis

KEGG pathway enrichment analysis was performed to assess the biological roles of the DEGs (Table IV). Axon guidance was the only significant pathway in response to leptin (P=0.0294). There were 12 significant pathways in response to hypoxia, among which the chemokine signaling pathway (P=0.00014) was the most significant, which suggested inflammatory factors were crucial in the response to hypoxia in L929 cells. For the combined treatment group, nine pathways were significant, of which eight were identical to the responses to hypoxia: Nitrogen metabolism, focal adhesion, chemokine signaling pathway, arginine and proline metabolism, starch and sucrose metabolism, pyruvate metabolism, VEGF signaling pathway and MAPK signaling pathway.

Table IV.

Pathway analysis of the differentially expressed genes regulated by leptin, hypoxia and the two in combination.

Table IV.

Pathway analysis of the differentially expressed genes regulated by leptin, hypoxia and the two in combination.

KEGG IDTermnP-value
Leptin-treated
  mmu04360Axon guidance  30.029392665
Hypoxia-treated
  mmu04062Chemokine signaling pathway280.00014053
  mmu00500Starch and sucrose metabolism100.000638251
  mmu00910Nitrogen metabolism  70.004127542
  mmu00052Galactose metabolism  70.009539235
  mmu04510Focal adhesion240.010772098
  mmu00380Tryptophan metabolism  80.019533919
  mmu04360Axon guidance170.020000767
  mmu00620Pyruvate metabolism  80.022185656
  mmu00330Arginine and proline metabolism  90.0297123
  mmu04010MAPK signaling pathway280.029963278
  mmu04370VEGF signaling pathway110.03808443
  mmu00010 Glycolysis/gluconeogenesis100.046234215
Leptin and hypoxia-treated
  mmu00910Nitrogen metabolism  70.004076684
  mmu04510Focal adhesion250.005345589
  mmu04062Chemokine signaling pathway230.007744979
  mmu00330Arginine and proline metabolism100.010268331
  mmu00500Starch and sucrose metabolism  80.010980612
  mmu00620Pyruvate metabolism  80.021915205
  mmu04630JAK-STAT signaling pathway180.035405855
  mmu04370VEGF signaling pathway110.037534097
  mmu04010MAPK signaling pathway270.047450835

[i] KEGG, Kyoto Encyclopedia of Genes and Genomes; MAPK, mitogen-activated protein kinase; VEGF, vascular endothelial growth factor; JAK, Janus kinase; STAT, signal transducer and activator of transcription.

Leptin promotes the proliferation of L929 cells

The results of the functional enrichment analysis suggested that leptin affected the cell cycle progression of L929 cells under hypoxia. To confirm this, the numbers of cells in different cell cycle phases were detected using FCM. Exposing the L929 cells to leptin resulted in a high percentage of cells in the S+G2/M phases, which indicated that leptin promoted L929 cell proliferation (Fig. 3A and B).

Discussion

Investigations have increasingly focused on the pro-fibrotic microenvironment of organs. Leptin and hypoxia are pro-fibrotic factors, which are involved in fibrogenesis. In the present study, a high-throughput microarray method was applied to detect the expression profile response to leptin, hypoxia and the two combined in L929 cells. It was found that leptin promoted mouse fibroblast cell proliferation, whereas hypoxia affected L929 cell function, primarily through the chemokine signaling pathway.

The present study identified 54 leptin-responsive genes, 52 of which were downregulated >2-fold. Among these, nephronophthisis 3, also known as pcy, showed a marked reduction by 3.3-fold. It has been reported that pcy mice undergoing cystogenesis present with progressive increasingly severe renal fibrosis (26). Another gene, E2f transcription factor 4 (E2f4), showed a marked reduction by 3.0-fold. E2f4 is important in the suppression of proliferation-associated genes and is involved in the G1/S phase of the mitotic cell cycle (2730). This may account for the percentage of cells in the G1/S phase being decreased and that in the S+G2/M being increased in response to leptin. Leptin-stimulated cell proliferation had been reported previously, including in vascular smooth muscle cell proliferation (31), hepatic stellate cells (32) and cancer cells (33).

Pathway analysis revealed the significant pathway regulated by leptin was axon guidance, of which three genes, Eph receptor A5, Rho-associated coiled-coil containing protein kinase 1 (Rock1) and semaphoring 6D, were significantly affected. These results were concordant with previous studies. A study by Simerly (34) found that leptin may direct the development of hypothalamic pathways by promoting axonal projections. A study by Harrold (35) indicated novel regulatory roles for leptin in synaptic plasticity and axon guidance.

Several genes varied in response to hypoxia. The most significant pathway response to hypoxia was the chemokine signaling pathway, and the expression of 28 genes (Ccl1, adenylate cyclase 4, protein kinase C, G protein subunit α1, Cxcl9, G protein subunit γ (Gng)13, Cxcl10, dedicator of cytokinesis 2, son of sevenless homolog 1, Gng2, phosphoinositide-3-kinase regulatory subunit 3, phospholipase Cβ2, SHC adaptor protein 2, AKT serine/threonine kinase 2, Gng7, mitogen-activated protein kinase kinase 1, Rock1, vav guanine nucleotide exchange factor 1, Ccl17, engulfment and cell motility 1, Arrb1, glycogen synthase kinase 3β, Ccr2, G protein subunit β5, RAP1A, member of RAS oncogene family, Grk4, Jak3 and Crk) were altered in this pathway. Among these, Ccr2 and CC chemokine ligand 2 (Ccl2) receptor were previously reported to be altered in oxygen shortage (36). In addition, Cxcl9, Cxcl10 and Ccl17 have been reported to be involved in the pathogenesis of lung fibrosis (37). This result further suggested that inflammation was important in L929 function, particularly in pathological states. Therefore, it was hypothesized that the hypoxic microenvironment facilitates L929 cell proliferation through the chemokine signaling pathway, and the uncontrolled inflammation further promotes fibrosis. Further understanding of the mechanisms involved in chemokine-mediated cell proliferation may lead to improved therapeutic strategies in fibrosis.

Several other pathways were involved in the response to hypoxia, including starch and sucrose metabolism, nitrogen metabolism and galactose metabolism. These pathways associated to metabolism were in accordance with expectations, as cell adaptation to low oxygen concentrations involves repression of mitochondrial respiration and induction of glycolysis to sustain cell function in hypoxic conditions (38). Axon guidance was also a significant pathway response to hypoxia and to leptin, which was coincident with a previous study (39). Therefore, under hypoxia, several pathways may function in concert to restore oxygen supply to cells and modulate cell function to adapt the hypoxic conditions.

In conclusion, the present study showed that leptin and hypoxia altered gene expression profiles in L929 cells. The results suggested that the pro-fibrotic effects of leptin may be through promoting mouse fibroblast cell proliferation; whereas hypoxia affected mouse fibroblast cell function predominantly through the chemokine signaling pathway. These findings improve understanding of leptin and hypoxia in fibroblast cells. Axon guidance and the chemokine signaling pathway may represent novel therapeutic targets for leptin and hypoxia injury in fibrogenesis, and require further investigation.

Acknowledgements

This study was supported by grants from the National Natural Science Foundation of China (grant nos. 81200082, 81302244 and 81502899), the Medical Science and Technology Research Fund of Guangdong province (grant no. B2012272) and the PhD Start-up Fund of Guangdong Medical College (grant no. B2011019).

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July-2017
Volume 16 Issue 1

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Spandidos Publications style
Ouyang P, Wang S, Zhang H, Huang Z, Wei P, Zhang Y, Wu Z and Li T: Microarray analysis of differentially expressed genes in L929 mouse fibroblast cells exposed to leptin and hypoxia. Mol Med Rep 16: 181-191, 2017
APA
Ouyang, P., Wang, S., Zhang, H., Huang, Z., Wei, P., Zhang, Y. ... Li, T. (2017). Microarray analysis of differentially expressed genes in L929 mouse fibroblast cells exposed to leptin and hypoxia. Molecular Medicine Reports, 16, 181-191. https://doi.org/10.3892/mmr.2017.6596
MLA
Ouyang, P., Wang, S., Zhang, H., Huang, Z., Wei, P., Zhang, Y., Wu, Z., Li, T."Microarray analysis of differentially expressed genes in L929 mouse fibroblast cells exposed to leptin and hypoxia". Molecular Medicine Reports 16.1 (2017): 181-191.
Chicago
Ouyang, P., Wang, S., Zhang, H., Huang, Z., Wei, P., Zhang, Y., Wu, Z., Li, T."Microarray analysis of differentially expressed genes in L929 mouse fibroblast cells exposed to leptin and hypoxia". Molecular Medicine Reports 16, no. 1 (2017): 181-191. https://doi.org/10.3892/mmr.2017.6596