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Keywords:

  • bioinformatics analysis;
  • cervical cancer;
  • epidermal growth factor;
  • small molecule;
  • sub-pathway

Abstract

  1. Top of page
  2. Abstract
  3. Introduction
  4. Methods
  5. Results
  6. Discussion
  7. Disclosure
  8. References
  9. Supporting Information

Aim

We sought to explore the mechanisms of cervical carcinoma response to epidermal growth factor (EGF), and then identify biologically active small molecules capable of targeting the sub-pathways that were dysregulated in cervical cancer cells in the response to EGF.

Material and Methods

Differentially expressed genes and pathways were analyzed based on the transcription profile of GSE6783, and then the differentially expressed molecules were further analyzed by several bioinformatics methods.

Results

Our results suggested that EGF could promote cervical cancer cell proliferation through triggering the dysregulation of certain sub-pathways in the mitogen-activated protein kinase signaling pathway, p53 signaling pathway and pathways in cancer. Furthermore, our bioinformatics analysis revealed a total of 49 small molecules which may play a role in perturbing the response to EGF of cervical cancer cells.

Conclusions

Candidate drugs identified by our approach may provide the groundwork for a combination therapy approach for cervical cancer; however, further studies are still needed to make sure that the use of parthenolide or other anti-cancer agents is effective without inhibiting important host defense mechanisms in cervical cancer.


Introduction

  1. Top of page
  2. Abstract
  3. Introduction
  4. Methods
  5. Results
  6. Discussion
  7. Disclosure
  8. References
  9. Supporting Information

Cervical cancer is the second most prevalent and the fifth most deadly malignancy seen in women worldwide.[1] It accounts for about 500 000 new cases and over 270 000 deaths estimated every year.[2, 3] The treatment of cervical cancer varies worldwide, largely due to large variances in disease burden in developed and developing nations, access to surgeons skilled in radical pelvic surgery, and the emergence of ‘fertility-sparing therapy’ in developed nations. Current approaches for treating cervical cancer have limited success, with an estimated 5-year survival rate of 60% for women with cervical cancer.[4]

Because cervical cancers are radiosensitive, radiation may be used in all stages where surgical options do not exist. Chemotherapy and radiotherapy could have a synergistic effect.5 Cisplatin is believed to augment the effects of radiation by inhibiting the repair of radiation-induced sublethal damage and by sensitizing hypoxic cells to radiation.6 The use of a combination of two chemotherapy drugs of topotecan and cisplatin are recommended for women with late-stage cervical cancer by the US Food and Drug Administration; however, combination treatment has significant risk of neutropenia, anemia, and thrombocytopenia side-effects. There is an urgent need to develop new therapies for cervical cancer because of their poor prognosis.

Epidermal growth factor (EGF) is a growth factor that stimulates cell growth, proliferation, and differentiation by binding to its receptor EGFR.[7] When EGF and its relatives bind the erythroblastic leukemia viral oncogene homolog (ErbB) family of receptors, they trigger a rich network of signaling pathways, culminating in responses ranging from cell division to death, motility to adhesion.[8] Dysregulated activation of this network has been implicated in diverse types of human cancer,[9] including cervical cancer.

In the present study, we sought to explore the mechanisms of cervical carcinoma response to EGF, and then identify biologically active small molecules capable of targeting the sub-pathways, which were dysregulated in cervical cancer cells in the response to EGF. Candidate agents identified by our approach may provide the groundwork for a combination therapy approach for cervical cancer; however, further evaluation for their potential use in the treatment of cervical cancer is still needed.

Methods

  1. Top of page
  2. Abstract
  3. Introduction
  4. Methods
  5. Results
  6. Discussion
  7. Disclosure
  8. References
  9. Supporting Information

Affymetrix microarray data

The transcription profile of GSE6783 was obtained from National Center for Biotechnology Information Gene Expression Omnibus (GEO) database (http://www.ncbi.nlm.nih.gov/geo/), which is based on the Affymetrix Human Genome U133 Array. A total of seven chips, purchased from Weizmann Institute of Science (Israel), were used for analysis. HELA cells were subjected to EGF stimulation for different time courses. HELA cells derived from human cervical tumor were grown in Dulbecco modified Eagle medium (DMEM) supplemented with 10% fetal calf serum (FCS) and antibiotics, following stimulation with 10 ng/mL EGF for 0, 20, 40, 60, 120, 240 and 480 min. Unstimulated HELA were used as controls.

Pathway data

Kyoto Encyclopedia of Genes and Genomes (KEGG) is a collection of online databases dealing with genomes, enzymatic pathways, and biological chemicals.[10] The PATHWAY database records networks of molecular interactions in the cells, and variants of them specific to particular organisms (http://www.genome.jp/kegg/). A total of 130 pathways, involving 2287 genes, were collected from KEGG.

Small molecules data

The connectivity map (CMap) can be used to find connections among small molecules sharing a mechanism of action, chemicals and physiological processes, and diseases and drugs.[11] It is the first installment of a reference collection of gene-expression profiles from cultured human cells treated with bioactive small molecules, together with pattern-matching software to mine these data. The CMap dataset comprises genomic profiling data from 6100 treatment-control pairs (instances) involving 1309 bioactive molecules (perturbagens). The output consisted of a group of chemical perturbagens with a connectivity score ranging from +1 and −1. The score represented the correlation between the query signature profile and the gene profile of a treatment-control pair (instance). A high positive connectivity score indicated that the corresponding perturbagen induced the expression of the query signature, whereas a high negative connectivity score indicated reversal of expression of the query signature by the perturbagen. A zero or ‘null’ connectivity score indicated that no effect upon expression of the query signature was recorded. We downloaded all the profile data for further analysis.

Differentially expressed genes analysis

We used the Affy package in R to preprocess the data of profile GSE6783. The raw expression datasets from all conditions were scaled using the RMA method12 with the default setting implemented in Bioconductor, and then we constructed the linear model. For each sample, the expression values of all probes for a given gene were reduced to a single value by taking the average expression value. The fold change values larger than 1.5 were chosen as the cut-off criterion for differentially expressed genes (DEG).

Obtainment of sub-pathways by parsing the KEGG pathway

SubpathwayMiner is an R-based software package which facilitates sub-pathway identification of metabolic pathways by using pathway structure information. The sub-pathway is defined by an individual path from a start-point to an end-point in a pathway map. For a given KEGG pathway, the sub-pathways were obtained by searching all possible paths between start-points (membrane receptors or their ligands) and end-points (transcriptional factors or their immediate targets) in the adjacency matrix generated by node relations.[13]

The metabolic pathways downloaded from KEGG were converted to an undirected graph with enzymes as nodes. Two nodes in an undirected graph are connected by an edge if there is a common compound in the enzymes' corresponding reactions. To find the sub-pathways in which all enzymes have highly similar functions, we adopted the k-clique concept in social network analysis to define sub-pathways based on distance similarity among enzymes.[14] In social network analysis, a k-clique in a graph is considered as a sub-graph where the distance between any two nodes is no greater than a parameter, k. The distance among all enzymes in mined sub-pathways decreases as the value of the parameter k reduces. Here, we set k = 3.

Results

  1. Top of page
  2. Abstract
  3. Introduction
  4. Methods
  5. Results
  6. Discussion
  7. Disclosure
  8. References
  9. Supporting Information

Differentially expressed genes selection between EGF stimulated and unstimulated samples

To get differentially expressed genes between EGF stimulated and unstimulated samples, we obtained publicly available microarray data sets GSE6783 from GEO. A total of 617 genes with a fold change value larger than 1.5 were identified as DEG (Supplemental Table S1).

Sub-pathway mining in the response to EGF

We used SubpathwayMiner to annotate these differentially expressed genes to entire pathways and sub-pathways (k = 3) of metabolic pathways. With the strict cut-off of P-values less than 0.05, our system identified 13 enriched sub-pathways corresponding to three entire pathways of metabolic pathways (Table 1). The three entire pathways were respectively path: 04010 (mitogen-activated protein kinase [MAPK] signaling pathway), path: 04115 (p53 signaling pathway) and path: 05200 (pathways in cancer). These 13 sub-pathways performed close interaction in their corresponding entire pathways and were significantly dysregulated when treated with EGF in cervical cancer cells.

Table 1. Enriched entire pathways and sub-pathways (k = 3) of metabolic pathways
Entire pathway IDEntire pathway nameSub-pathway IDP-valuesFDR
  1. MAPK, mitogen-activated protein kinase; FDR, false discovery rate.

path:04010MAPK signaling pathwaypath:04010_167.36E-060.00255
path:04010_171.36E-050.007878
path:04010_225.92E-060.00255
path:04010_313.93E-060.00255
path:04010_323.22E-060.00255
path:04010_341.17E-070.00255
path:04010_358.23E-060.003916
path:04115p53 signaling pathwaypath:04115_12.76E-087.64E-05
path:04115_29.78E-060.007878
path:04115_35.74E-060.00255
path:04115_45.74E-060.00255
path:04115_76.89E-060.00255
path:05200Pathways in cancerpath:05200_295.79E-080.000149

Identification of candidate small molecules

According to the gene-expression profiles data from 6100 treatment-control pairs (instances) involving 1309 bioactive small molecules in the Connectivity Map, we performed differentially expressed genes analysis for the 1309 small molecules. A total of 1221 out of 1309 small molecules have DEG.

For the 1221 small molecules, we then used SubpathwayMiner to annotate these differentially expressed genes to entire pathways and sub-pathways of metabolic pathways. With the strict cut-off of false discovery rate (FDR) less than 0.001, our system identified 353 enriched sub-pathways of metabolic pathways.

By integrating the previous 13 sub-pathways and these 353 pathways, we can select the significant overlapping sub-pathways, that is, these sub-pathways are related to EGF response and small molecules. Then, we can hypothesize that these small molecules may play a role in perturbing the response to EGF of cervical cancer cells. A total of 49 small molecules were identified (Table 2, unabridged results are provided in Supplementary Table S2). We performed text-mining of the 49 small molecules in the PubMed database and found three of the 49 small molecules were suggested to have anti-cancer effect in cervical cancer in the published reports (Table 3).

Table 2. Top 10 significant overlapping small molecules
Small moleculeP-valueOverlap number
Parthenolide09
Pyrvinium08
Ciclopirox1.78E-156
Bepridil6.49E-135
Metyrapone6.49E-135
Trifluridine6.49E-135
Etoposide3.89E-125
Deferoxamine3.61E-115
Etacrynic acid3.61E-115
Ag-0286712.12E-104
Table 3. Text-mining showed that three small molecules have an anti-cancer effect in cervical cancer small molecules
Molecule nameKeywordsKey countPubMed ID
CiclopiroxAnti-cancer and cervical1pmid21366640
EtoposideAnti-cancer and cervical4pmid18665234|pmid10450922|pmid7778422|pmid3794454|
ThioridazineAnti-cancer and cervical1pmid22460505

By integrating the relationships above, a network was built between the small molecules and sub-pathways which were perturbed by the small molecules (Fig. 1). In this network, some small molecules can perturb one or several sub-pathways by themselves, while some small molecules perturb sub-pathways by cooperating with other small molecules.

figure

Figure 1. Small molecules perturb the sub-pathways in the response to epidermal growth factor (EGF) in cervical cancer cells. The triangular nodes are small molecules and the circular nodes are sub-pathways. The sub-pathways in the same color are included in the same entire pathways.

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Discussion

  1. Top of page
  2. Abstract
  3. Introduction
  4. Methods
  5. Results
  6. Discussion
  7. Disclosure
  8. References
  9. Supporting Information

In this study, we used the gene expression profile downloaded from GEO to explore the mechanisms of cervical cancer cells' response to EGF. Furthermore, we showed the utility of using bioinformatics analysis for the identification of new therapeutics for cervical cancer. A total of 617 genes were identified differentially expressed after treatment with EGF in cervical cancer cells. Sub-pathway mining results showed that three entire pathways, MAPK signaling pathway, p53 signaling pathway and pathways in cancer, were dysregulated after treatment with EGF. A total of 49 small molecules were identified which may play a role in perturbing the response to EGF of cervical cancer cells.

Current approaches typically study entire pathways, whether by singular enrichment analysis or by gene set enrichment analysis;[15] however, sub-pathways analysis may be more suitable than entire pathways for identification of drug response.[13] We identified that a total of 13 sub-pathways were dysregulated in the response to EGF, including seven sub-pathways in MAPK signaling pathway, five sub-pathways in p53 signaling pathway and one sub-pathway in pathways in cancer. Our results suggest that EGF could promote cervical cancer cell proliferation through triggering the dysregulation of certain sub-pathways in MAPK signaling pathway, p53 signaling pathway and pathways in cancer. Our results are consistent with a previous study that determined that a number of MAPK phosphatases undergo transcriptional induction after growth factor activation.[16]

The MAPK pathways transduce a large variety of external signals, leading to a wide range of cellular responses, including cell proliferation, differentiation, inflammation and apoptosis.17 The dysregulation of the MAPK signaling pathway has been implicated in a large variety of pathological conditions, including cancer, ischemic heart disease and inflammatory disorders,[18] and has therefore been appreciated as an attractive candidate for drug development. Moreover, MAPK inhibitors have been used in combination with other immunosuppressive drugs, including biological therapy.[18]

Research over the past 3 decades has identified that p53 is a transcription factor that controls a major pathway protecting cells from malignant transformation.[19, 20] This anti-cancer activity profile, together with genomic and mutational analyses documenting inactivation of p53 in more than 50% of human cancers, motivated anti-cancer drug development efforts to (re-)activate p53 in established tumors.[21]

EGF is part of a complex network of growth factors and receptors that together help to modulate the growth of cells.22 As such, targeting the EGF receptors, or the cellular signaling pathways activated by EGF, is a rational approach to identifying new therapeutic targets. Early in the 1980s, Sato et al. hypothesized that a monoclonal antibody that binds to EGF receptors and that can block the binding of EGF might prevent cell proliferation by inhibiting the signal transduction pathways that depend on activation of the EGF receptor.[23-25]

There are several important implications of this work. The identification of a group of small molecules with potential therapeutic efficacy for cervical cancer is an important observation. A total of 49 molecules were identified as having common sub-pathways with EGF response of cervical cancer cells. Text-mining results showed that ciclopirox, etoposide and thioridazine were suggested to have anti-cancer effect in cervical cancer.[26-31] These small molecules should be evaluated further with a high level of concern. Besides, some small molecules were suggested to have an anti-cancer effect in other cancer lines, such as parthenolide, pyrvinium and ciclopirox.

Parthenolide, one of the major sesquiterpene lactones found in the medicinal plant, feverfew (Tanacetum parthenium), is utilized primarily for prevention and/or relief of migraine as well as for anti-inflammatory effects in arthritis.[32, 33] More recently, parthenolide has been found to have several other properties, including antitumor activity, inhibition of DNA synthesis, and inhibition of cell proliferation in different cancer cell lines, such as colorectal cancer, hepatoma, cholangiocarcinoma, and pancreatic cancer.[34-39] In addition, parthenolide sensitizes cancer cells to other antitumor agents.[40-42]

Furthermore, pyrvinium has also been reported to display anticancer activity. Pyrvinium was an old anthelminthic medicine. Esumi et al. recently reported that it was preferentially toxic to glucose-starved cancer cells and had anti-cancer activity in a hypovascular Panc-1 pancreatic cancer model, known to be resistant to hypoglycemia.[43] Ciclopirox is a synthetic antifungal agent that has clinically been used to treat mycoses of the skin and nails for 20 years.[44-46] Most recent studies have revealed that ciclopirox displays preclinical anticancer activity against breast tumors and may be a potential antitumor agent.[47]

The most significant small molecules of our result have been reported to display anticancer activity. Thus, our results are credible. The further study of the rest of the 49 small molecules will provide the groundwork for developing new therapies for treatment of cervical cancer.

In conclusion, our study showed that EGF could promote cervical cancer cell proliferation through triggering the dysregulation of certain sub-pathways in the MAPK signaling pathway, the p53 signaling pathway and pathways in cancer. Furthermore, our bioinformatics analysis revealed a total of 49 small molecules which may play a role in perturbing the response to EGF of cervical cancer cells. Of these, ciclopirox, etoposide and thioridazine were suggested to have anti-cancer effects in cervical cancer in the published reports. Also, some small molecules were suggested to have an anti-cancer effect in other cancer lines, such as parthenolide and pyrvinium. Further studies are needed to make sure that the use of parthenolide or other anti-cancer agents is effective without inhibiting important host defense mechanisms in cervical cancer.

References

  1. Top of page
  2. Abstract
  3. Introduction
  4. Methods
  5. Results
  6. Discussion
  7. Disclosure
  8. References
  9. Supporting Information

Supporting Information

  1. Top of page
  2. Abstract
  3. Introduction
  4. Methods
  5. Results
  6. Discussion
  7. Disclosure
  8. References
  9. Supporting Information
FilenameFormatSizeDescription
jog12022-sup-0001-si.xlsx33K

Table S1 The differentially expressed genes between EGF stimulated and unstimulated samples.

jog12022-sup-0002-si.xls25K

Table S2 The 49 candidate small molecules.

jog12022-sup-0003-si.pdf1547K

Supporting Information

Please note: Wiley Blackwell is not responsible for the content or functionality of any supporting information supplied by the authors. Any queries (other than missing content) should be directed to the corresponding author for the article.