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Identification of the interaction network of hub genes for melanoma treated with vemurafenib based on microarray data

Abstract

Aims and background

The objective of this study was to identify possible biomarkers and to explore the mechanisms of suppression of vemurafenib on melanoma progression.

Methods

GSE42872 affymetrix microarray data were downloaded from the Gene Expression Omnibus database for further analysis. Differentially expressed genes (DEGs) between vehicle-treated samples and vemurafenib-treated samples were identified. Gene ontology and pathway enrichment analysis of DEGs were performed, followed by protein-protein interaction (PPI) network construction. Furthermore, the functional modules of the PPI network were screened using BioNet analysis tool. Finally, Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis was performed for DEGs in the module.

Results

In total, 794 upregulated transcripts corresponding to 214 genes and 977 downregulated transcripts corresponding to 325 genes were screened. The downregulated DEGs were significantly enriched in pathways such as cell cycle, DNA replication, and p53 signaling pathway. Upregulated DEGs were significantly enriched in phosphatidylinositol signaling system and inositol phosphate metabolism. Significantly enriched functions of downregulated DEGs were mitotic cell cycle, nuclear division, DNA metabolic process, cell cycle, and mitosis. Upregulated DEGs were mainly enriched in single multicellular organism process and multicellular organismal process. Moreover, cell division cycle 6, checkpoint kinase 1 (CHEK1), E2F transcription factor 1 (E2F1), epidermal growth factor receptor (EGFR), and phosphoinositide-3-kinase, regulatory subunit 1-α (PIK3R1) of the module were remarkably enriched in pathways such as cell cycle, apoptosis, focal adhesion, and DNA replication.

Conclusions

Cell division cycle 6, CHEK1, E2F1, EGFR, and PIK3R1 of the module and their relative pathways, cell cycle, and focal adhesion might play important roles of suppression of vemurafenib on melanoma progression.

Tumori 2015; 101(4): 368 - 374

Article Type: ORIGINAL RESEARCH ARTICLE

DOI:10.5301/tj.5000316

Authors

Liangliang Quan, Yang Wang, Jiulong Liang, Jie Shi, Yu Zhang, Kai Tao

Article History

Disclosures

Financial support: None.
Conflict of interest: None.

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Introduction

Melanoma is a deadly skin cancer, which results from the malignant transformation of melanocytes and is characterized by rapid development, high metastasis ability, and limited efficiency of therapeutics (1, 2). The incidence of death from melanoma has increased by 7% from 1990 to 2006 (3). The prognosis is discouraging for patients with metastatic melanoma. About 50% of patients develop metastasis within an average of 36 months, frequently to the liver, and a median survival of only 6 months after metastasis has been reported (4). Additionally, melanoma is resistant to chemotherapy (5). Hence, the need for new and improved therapies is urgent.

Currently, therapeutic drugs targeting for oncogenes and signaling pathways are identified for the treatment of advanced melanoma. Oncogene BRAF (v-raf murine sarcoma viral oncogene homolog B1 gene) mutations were reported as a common event in about 60% of melanoma patients (6, 7). Vemurafenib, called PLX4032, is a serine threonine kinase inhibitor specially targeting mutated BRAF and has been approved for treating melanomas induced by BRAFV600E mutation by the US Food and Drug Administration (8). Moreover, vemurafenib enhanced overall survival relative to traditional chemotherapeutic agents (9) and improved median progression-free survival as compared with dacarbazine (10). Vemurafenib opens a new avenue for researchers and brings new promise for personalized medicine to melanoma patients (10). A former study showed that BRAF inhibition potently suppressed cell death and cell cycle progression through ­inhibition of GLUT1/3 and hexokinase II expression in melanoma cells as well as clinical BRAFV600 melanoma biopsies (6). BRAFV600E inhibition induces apoptosis and blocks cell proliferation in melanoma in vitro and blocks xenograft growth in vivo (11). Several researchers have also demonstrated that vemurafenib and other inhibitors of RAF kinases can enhance the activity of the MAPK pathway in wild-type BRAF cells, which might explain the beneficial therapeutic effect of vemurafenib in patients with BRAFV600E mutation melanoma (12, 13). Despite the therapy effects of vemurafenib, patients develop resistance to vemurafenib. Studies from other groups have shown that the MAPK pathway is also reactivated in resistant tumors (14). Thus it is urgent to explore the molecular mechanism of inhibition of vemurafenib on the progression of melanoma.

Nowadays, gene expression microarray has been widely applied in studying the development and progression of tumors to advance techniques and lower expenses. In the present work, we made use of bioinformatics approaches to analyze the information obtained from GSE42872 in order to investigate the melanoma-related genes and to explore the mechanism of suppression of vemurafenib on melanoma progression. Gene ontology (GO) functions and pathways were identified. Candidate genes and pathways identified by our approach might provide the groundwork for a therapy for melanoma. However, further evaluations of their potential use in the treatment of melanoma are needed.

Methods and materials

Analysis of Affymetrix microarray data

The gene expression profile of GSE42872 (6) was downloaded from the National Center of Biotechnology Information Gene Expression Omnibus (http://www.ncbi.nlm.nih.gov/geo/), which was on the basis of GPL6244 platform of Affymetrix Human Gene 1.0 ST Array. Samples were obtained from Peter MacCallum Cancer Centre, East Melbourne, Australia. In this study, there were 6 expression samples data, including 3 from BRAFV600E A375 melanoma cells treated with vehicle (0.1% DMSO) (GSM1052615, GSM1052616, GSM1052617) as control group and 3 from BRAFV600E A375 melanoma cells treated with vemurafenib (GSM1052618, GSM1052619, GSM1052620) as treated group. Raw data and the probe annotation files were downloaded for further analysis.

Data preprocessing and identification of differentially expressed genes

The Affy package (15) from Bioconductor and Affy probe annotation files offered by Brain Array Lab were applied to preprocess the gene expression profile data of GSE42872. Data in CEL format were converted into expression measures, followed by background correction. Subsequently, quartile data normalization was performed using the robust multiarray average algorithm (16). Then, probe was summarized. Eventually, gene expression matrix was obtained.

The classical t test was applied in our analysis to identify differentially expressed genes (DEGs) between vehicle-treated samples and vemurafenib-treated samples. The Benjamini & Hochberg method (17) was used to adjust the raw p value into the false discovery rate (FDR). False discovery rate <0.01 and |log FC| ≥2 were regarded as the cutoff criterion for DEGs.

Gene ontology enrichment analysis

Based on Gene Ontology Database (http://www.geneontology.org/), the functions of DEGs between vehicle-treated samples and vemurafenib-treated samples were analyzed via GO, which is a commonly used approach for functional enrichment studies of large-scale genes (18). A p value less than 0.01 was selected as the threshold.

Pathway enrichment analysis

Kyoto Encyclopedia of Genes and Genomes (KEGG) is a bioinformatics database including biochemistry pathways (19). Database for Annotation, Visualization and Integrated Discovery (DAVID) provides analytic tools for extracting biological meaning from a large list of genes (20). The DAVID was used for KEGG pathway enrichment analysis of upregulated and downregulated DEGs, respectively. All pathways were analyzed for significant differences. A p value less than 0.01 was chosen as the cutoff value.

Gene functional annotation

Based on transcription factor (TF) data, we screened and annotated DEGs to determine whether these DEGs had transcriptional regulatory functions. Additionally, tumor suppressor (TS) genes database (21) combined with tumor-associated genes (TAG) database (22) were used to further extract all the known oncogenes and TF genes.

Protein-protein interaction network construction and modules mining

As proteins seldom perform their functions alone, it is important to comprehend the interaction of these proteins by studying larger functional groups of proteins (23). The Search Tool for the Retrieval of Interacting Genes (STRING) database (24) provides both experimental and predicted interaction information. We used the STRING database to annotate functional interactions between DEGs and other genes. Based on this information, a protein-protein interaction (PPI) network was visualized by Cytoscape (25). Node degree ≥20 was selected as the threshold.

The edges and nodes of the PPI network were so complicated that further analysis was needed to expose the enriched functional modules of the PPI network using BioNet analysis tool (26). False discovery rate <0.00005 was regarded as the cutoff criterion. Subsequently, we performed KEGG pathway enrichment analysis of genes in the module.

Results

Identification of DEGs

According to the research criterion FDR <0.01 and |log FC| ≥2, a total of 1771 transcripts were screened, including 794 upregulated transcripts corresponding to 214 genes and 977 downregulated transcripts corresponding to 325 genes. The ratio of the number of upregulated to downregulated genes was 1:1.52 (Tab. I).

The results of the differentially expressed genes in vemurafenib-treated samples

Transcript counts Gene counts
Downregulated 977 325
Upregulated 794 214
Total 1771 539

Gene ontology functional enrichment analysis

We used the DAVID to identify GO-enriched functions for significant DEGs. Downregulated DEGs from BRAFV600E A375 melanoma cells treated with vemurafenib were significantly enriched in mitotic cell cycle (p<1.11E-16), nuclear division (p<1.11E-16), DNA metabolic process (p<1.11E-16), cell cycle (p<1.11E-16), and mitosis (p<1.11E-16). These functions were associated with cell cycle regulation (Tab. II). Upregulated DEGs mainly participated in single multicellular ­organism process (p = 1.92E-05) and multicellular organismal process (p = 2.76E-05).

Top 5 Gene Ontology categories of the differentially expressed genes from BRAFV600E A375 melanoma cells treated with vemurafenib

Gene ontology ID Term Gene counts p Value
Gene counts refer to the number of differentially expressed genes enriched in the gene ontology function.
Downregulated genes GO:0000278 Mitotic cell cycle 82 <1.11E-16
GO:0000280 Nuclear division 44 <1.11E-16
GO:0006259 DNA metabolic process 72 <1.11E-16
GO:0007049 Cell cycle 107 <1.11E-16
GO:0007067 Mitosis 44 <1.11E-16
Upregulated genes GO:0044707 Single multicellular organism process 93 1.92E-05
GO:0032501 Multicellular organismal process 95 2.76E-05
GO:0055021 Regulation of cardiac muscle tissue growth 5 3.17E-05
GO:0023052 Signaling 82 3.90E-05
GO:0044700 Single organism signaling 82 3.90E-05

Analysis of KEGG pathway

The DAVID was used to determine the profound KEGG pathways to obtain further insights into the function of DEGs. The pathways of the upregulated and downregulated genes were obtained with p value less than 0.01 (Tab. III). On the basis of the results, the downregulated DEGs were significantly enriched in pathways such as cell cycle (p = 3.14E-11), DNA replication (p = 6.05E-06), p53 signaling pathway (p = 0.000410847), base excision repair (p = 0.000474269), mismatch repair (p = 0.001055235), and ribosomebiogenesis in eukaryote (p = 0.005422121).

The KEGG pathway of the differentially expressed genes from BRAFV600E A375 melanoma cells treated with ­vemurafenib

KEGG pathway Gene counts p Value
KEGG = Kyoto Encyclopedia of Genes and Genomes.
Gene counts refer to the number of differentially expressed genes enriched in the KEGG pathway.
Downregulated genes Cell cycle 18 3.14E-11
DNA replication 7 6.05E-06
P53 signaling pathway 7 0.000410847
Base excision repair 5 0.000474269
Mismatch repair 4 0.001055235
Upregulated genes Ribosome biogenesis in eukaryotes 6 0.005422121
Phosphatidylinositol signaling system 5 0.001975
Inositol phosphate metabolism 4 0.004102
Phosphatidylinositol signaling system 5 0.001975

The upregulated DEGs were significantly enriched in phosphatidylinositol signaling system (p = 0.001975), inositol phosphate metabolism (p = 0.004102), and phosphatidylinositol signaling system (p = 0.001975).

Gene functional annotation

We mainly observed the expression of TFs and TAGs from A375 melanoma cells treated with vemurafenib. The expression levels of 25 TFs were significantly downregulated in the vemurafenib-treated group. By contrast, only 9 TF levels were upregulated after vemurafenib treatment (Tab. IV).

Analysis of transcriptional regulation functions of the differentially expressed genes from BRAFV600E A375 melanoma cells treated with vemurafenib

TF counts TF genes
TF = transcription factor.
Down 25 BRCA2, CDK2, E2F7, ELK3, ETV4, ETV5, HHEX, HIVEP3, HMGA2, LEF1, MYBBP1A, MYBL1, MYBL2, NFATC2, NFIB, NPAS2, POU2F1, PPARG, RBL1, SOX11, TEAD4, TFAP2C, TP73, VDR, WT1
Up 9 ATF3, FOXP2, ID3, MAF, MEF2C, PBX1, PITX2, TCF4, ZNF83

Moreover, 35 downregulated DEGs were identified to be closely related to the occurrence and development of tumors based on the results of TAG genes, including 10 known oncogenes and 20 known TSs (Tab. V). In the upregulated DEGs, 23 TAG genes were screened, containing 4 oncogenes and 16 known TSs (Tab. V). Interestingly, epidermal growth factor receptor (EGFR), E2F transcription factor 1 (E2F1), and phosphoinositide-3-kinase, regulatory subunit 1-α (PIK3R1) were found to be closely related to the formation of melanoma.

Analysis of tumor-associated gene functions of the differentially expressed genes from BRAFV600E A375 melanoma cells treated with vemurafenib

TAG counts Oncogene Tumor suppressor Other
TAG = tumor-associated gene.
Down 35 AURKA, CCNA2, EGFR, ETV1, FOSL1, HMGA2, MYB, MYBL1, MYBL2, NET1 ADAMTS9, BRCA2, BUB1B, CHEK1, DUSP6, E2F1, ERRFI1, GPRC5A, IGFBP3, MFSD2A, MYBBP1A, RBL1, RBM14, SFRP1, SOX11, SPRY2, TIMP3, TNFRSF10A, TP73, WT1 CDK2, EVI2B, MSH6, TFAP2C, ZFP36L2
Up 23 FGFR2, MRAS, PBX1, ROS1 CCNDBP1, EGLN3, HBP1, HPGD, KLK6, MTUS1, NDRG2, PARK2, PCDH10, PLCD1, PLCE1, PPAP2A, RARB, TCF4, TP53INP1, TSC22D1 DDR1, LRRC17, MAF

Protein-protein interaction network construction and analysis of KEGG pathway enrichment of the module genes

The STRING tool was used to obtain the PPI relationships of the DEGs. Node degree ≥20 was selected as the threshold. In Figure 1, several PPI nodes had higher degrees, as follows: cyclin-dependent kinase 1 (CDK1) (degree = 43), cyclin A2 (CCNA2) (degree = 39), cell division cycle associated 8 (CDCA8) (degree = 35), kinesin family member 11 (KIF11) (degree = 26), BUB1 mitotic checkpoint serine/threonine kinase B (BUB1B) (degree = 24), cell division cycle 6 (CDC6) (degree = 24), NUF2, NDC80 kinetochore complex component (NUF2) (degree = 24), centromere protein A (CENPA) (degree = 24), proliferating cell nuclear antigen (PCNA) (degree = 23), TTK protein kinase (TTK) (degree = 20), and kinesin family member 23 (KIF23) (degree = 20).

Construction of protein-protein interaction network of differentially expressed genes associated with melanoma. Red nodes represent significant upregulated genes and green nodes represent significant downregulated genes.

We then screened the module of the PPI network using BioNet analysis tool (Fig. 2). In our study, 35 nodes were involved in this module and 5 hub genes with the higher degrees, including CDCA8 (degree = 11), CENPA (degree = 7), CDC6 (degree = 7), checkpoint kinase 1 (CHEK1) (degree = 6), and aurora kinase A (AURKA) (degree = 6).

Protein-protein interaction module of differentially expressed genes (DEGs) related to melanoma. The degrees of color depth of nodes are associated with fold change value of DEGs. Red nodes represent upregulated genes; green nodes represent downregulated genes; white nodes stand for normal genes. Square nodes indicate lower importance of genes in the module; circular nodes indicate significant importance of genes in the module.

We also performed KEGG pathway enrichment analysis of genes in the module. The results are shown in Table VI. Cell division cycle associated 8, CENPA, CDC6, CHEK1, and AURKA were enriched in pathways such as cell cycle, apoptosis, focal adhesion, and DNA replication. Notably, EGFR, E2F1, and PIK3R1 were involved in the module, and there was an indirect interaction with CDC6 and AURKA.

The KEGG pathway of the differentially expressed genes in the module

KEGG pathway Gene counts p Value Genes
KEGG = Kyoto Encyclopedia of Genes and Genomes.
Gene counts refer to the number of differentially expressed genes in the module enriched in the KEGG pathway.
Cell cycle 7 2.59E-08 BUB1B, CDC6, CHEK1, ORC1, MCM3, E2F1, MCM5
Apoptosis 3 0.001840211 BCL2, PIK3R1, NFKBIA
Focal adhesion 4 0.002195198 BCL2, EGFR, ITGB5, PIK3R1
DNA replication 2 0.004694167 MCM3, MCM5

Discussion

Melanoma is a deadly skin cancer and its occurrence and mortality have been rising worldwide for the last 30 years (27). In the current study, we investigated gene expression profile GSE42872 and explored the underlying molecular mechanisms of melanoma treated with vemurafenib using bioinformatics methods. A total of 1771 transcripts were screened, including 794 upregulated transcripts corresponding to 214 genes and 977 downregulated transcripts corresponding to 325 genes. Additionally, the expression levels of 25 TFs were significantly downregulated and only 9 TF levels were upregulated after vemurafenib treatment. Moreover, CDC6, CHEK1, E2F1, EGFR, and PIK3R1 of the module were remarkably enriched in pathways such as cell cycle, apoptosis, focal adhesion, and DNA replication.

Cancer is characterized by uncontrolled cell proliferation resulting from dysregulation of the cell cycle (28). In the present work, our results argued for an important role of cell cycle out of control in the pathogenesis of malignant melanoma, and several candidate genes were identified to be downregulated after vemurafenib treatment, such as CDC6, E2F1, and CHEK1. CDC6 is an essential regulator of DNA replication in eukaryotic cells (29). Additionally, CDC6 is an oncogene and abnormal expression of CDC6 can cause DNA damage and genetic instability (30). A previous study has demonstrated that depletion of CDC6 through microinjection of anti-CDC6 antibody inhibits initiation of DNA replication in a human tumor cell line (31). However, overexpression of CDC6 gene and its relevant proteins were exhibited in an independent melanoma tumor (7). E2F transcription factor 1 is a member of the E2F family. Free E2Fs can activate the transcription of target gene (CDC6), promoting S-phase and cell cycle progression (32). Our results were consistent with previous studies. In the present study, there was interaction relationship between E2F1 and CDC6, and E2F1 was downregulated after treatment of vemurafenib. Hence, as demonstrated here, the inhibition of vemurafenib on melanoma development via downregulating E2F1 and CDC6 highlights the potential use of vemurafenib in controlling cell cycle progression in melanoma.

Checkpoints are present in all stages of the cell cycle and are considered the gatekeepers in order to maintain the integrity of the genome (33, 34). Deregulation of cell cycle checkpoints seems to be a universal phenomenon in human cancers. CHEK1 was found to be a mediator of the checkpoints in G2/M as well as S phase in mammals (35, 36) and to respond to DNA damage by initiating cell cycle arrest. Moreover, CHEK1 was demonstrated to express highly in many types of tumors (37). It is known that the inhibition of CHEK1 enhances the cytotoxicity of DNA-damaging drugs via abrogating of the cell cycle checkpoint (38). Recent study has demonstrated that CHEK1 inhibitors can be used to increase the sensitivity of tumor cells to replication inhibitors in vitro and in vivo (39). In our study, CHEK1 was downregulated in melanoma after treatment of vemurafenib. Thus, we infer that the suppression of vemurafenib on melanoma progression may downregulate CHEK1 to further deprive the cancer cells of the defensive mechanism of circumventing cell cycle arrest.

Another major functional pathway, focal adhesion, was identified, involved in EGFR and PIK3R1 genes. Focal adhesion is an outstanding determinant in the process of initiation, progression, and metastasis of cancer (40). Focal adhesion kinase (FAK) is a major kinase that plays a key role in the regulation of migration and cell adhesion (41). Epidermal growth factor receptor is known to bind to FAK in mammals to promote cell migration (42) and to activate MAPK in Drosophila (43). Among the molecular targeted therapy of cancer, anti-EGFR therapeutic approaches are the most promising and the most advanced at the clinical level (44). Our results were in accordance with former studies. In the current study, EGFR was found to be closely related to the formation of melanoma based on the results of TAG genes and was downregulated in melanoma after treatment with vemurafenib. Additionally, a previous report has found that inhibition of RAF and EGFR in BRAF mutant colorectal cancers suppresses the MAPK signal pathway and significantly increases therapeutic efficacy in vitro (45). Therefore, we infer that inhibition of vemurafenib on melanoma progression might be attributed to the downregulation of EGFR through suppressing MAPK signal pathway, which further influences the changes in cellular adhesion and migration.

PIK3R1 encoded p85α, which was one submit of phosphatidylinositol 3-kinase (PI3K) (46). The PI3K pathway is important and known to participate in proliferation, invasion, and migration in cancers (47, 48). Moreover, excessive activation of PI3K is a hallmark of a range of tumors (49). Several studies have suggested that PIK3R1 appears to play a role as a TF gene (46, 50). A former study showed that underexpression of PIK3R1 is a prognostic marker in breast cancer (51). In the current study, PIK3R1 was upregulated in melanoma after vemurafenib treatment. Hence, we speculate that vemurafenib may upregulate PIK3R1 via suppressing the PI3K signal pathway to inhibit melanoma progression.

Although we obtained some significant genes and pathways in melanoma treated by vemurafenib, there are some limitations to our study. The study was carried out based on bioinformatics methods and the conclusions have not been proved by experiments. Additionally, the sample size in our study was limited. Hence, more work is warranted to further explore the molecular mechanisms of melanoma and to apply molecular genetic diagnosis to the clinic.

In conclusion, our study sheds new light on the mechanism of suppressing the progression of melanoma after vemurafenib treatment. Cell division cycle 6, CHEK1, E2F1, EGFR, and PIK3R1 of the module and their relative pathways, cell cycle, and focal adhesion might play important roles in vemurafenib inhibition on melanoma progression. Our research may provide a theory model in melanoma treated by vemurafenib. However, the results described should be verified in animal experiments.

Disclosures

Financial support: None.
Conflict of interest: None.
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Authors

Affiliations

  • Department of Plastic Surgery, General Hospital of Shenyang Military Area Command, PLA, Liaoning - China

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