Background
In the United States, ovarian cancer represents 3% of all the new cancer cases in women, but accounts for 5% of all the cancer deaths [
1]. This discrepancy is due, in part, to the common resistance of ovarian cancer to current chemotherapy regimens. The vast majority of ovarian cancer patients with advanced disease are treated with surgery followed by adjuvant chemotherapy consisting of a platinum agent (typically carboplatin) in combination with a taxane (paclitaxel). Unfortunately, while most patients initially respond to this combination chemotherapy, a majority of the patients (up to 75%) will eventually relapse within 18 months, many with drug resistant disease [
2]. The optimal management of patients with recurrent tumors is unclear, especially for drug resistant disease (by definition, a recurrence that has occurred within 6 months of initial treatment), and various studies have suggested different second line chemotherapy approaches, all with limited success [
3]. Ultimately, the frequent development of drug resistance and the lack of alternatives for the treatment of drug resistant disease are responsible for a 5-year survival of approximately 30% in ovarian cancer patients with advanced disease. Indeed, 90% of the deaths from ovarian cancer can be attributed to drug resistance [
4].
Studies have shown that ovarian cancer resistance is multifactorial and may involve increased drug inactivation/efflux, increased DNA repair, alterations in cell cycle control, and changes in apoptotic threshold. For example, the copper transporter CTR1 has been shown to mediate cisplatin uptake and cells with decreased CTR1 exhibit increased resistance to cisplatin [
5,
6]. Another pathway, the PTEN-PI3K-AKT axis, has been suggested to play an important role in the development of drug resistance in several malignancies [
7], including ovarian cancer [
8‐
10]. Overall, these studies indicate that a better understanding of the mechanisms of drug action and drug resistance may ultimately lead to new approaches for circumventing resistance and improve patient survival. However, in spite of recent advances, the exact pathways important for the development of drug resistance in ovarian cancer remain unclear. A better understanding of the molecular mechanisms leading to drug resistance may provide new opportunities for the development of strategies for reversing or circumventing drug resistance [
4,
11].
In this manuscript, we generate novel drug resistant ovarian cancer cell lines independently selected for resistance to cisplatin, doxorubicin or paclitaxel, and we use gene expression profiling to identify genes and pathways that may be important to the development of drug resistance in ovarian cancer.
Discussion
Drug resistance remains a major obstacle in cancer therapy and significant efforts have been directed at understanding the mechanisms leading to the development of resistance. Gene expression profiling has played a key role in providing us with important clues regarding genes and pathways that may be affected in drug resistance. Overall, the picture that has emerged is that the drug resistance is a multifactorial process involving mechanisms that are both drug- and tissue-dependent. To address these issues in ovarian cancer, we have generated cell lines that are individually resistant to cisplatin, paclitaxel, or doxorubicin. The combination of a platinum compound (cisplatin) and paclitaxel represent the standard initial chemotherapy for ovarian cancer, while doxorubicin has shown some promise in the treatment of recurrent drug-resistant disease [
16]. Various studies have investigated drug resistance, but few have compared the drug resistance mechanisms associated with the development of resistance to different drugs.
We found that the gene expression changes associated with the development of drug resistance was dependent on the drug used (Figure
1B), but the individual lines generated from a given drug were extremely similar to each other. This suggests that while cell lines adopted different mechanisms to develop resistance to different drugs, a given drug and conditions seem to favor similar pathways. Interestingly, the patterns of expression associated with cisplatin and doxorubicin resistance were more similar to each other than they were to cell lines developed through paclitaxel exposure (Figure
2A). This is further supported by the observation that the number of differentially expressed genes shared by cisplatin and doxorubicin (149) was greater than the number of genes shared by cisplatin and paclitaxel (115) or paclitaxel and doxorubicin (97) (Figure
1C). Doxorubicin and paclitaxel resistance can both arise through a multi-drug resistance (MDR)-type mechanism, which generally results from overexpression of ATP Binding cassette (ABC) transporters [
17], while cisplatin resistance is not believe to have a significant MDR component. On the other hand, cisplatin and doxorubicin are both DNA-damaging agents (albeit acting through different mechanisms), while paclitaxel is a microtubule stabilizing agent. Our data suggest that the overall changes in gene expression tend to reflect the drug target rather than an association with the MDR phenotype.
Overall, relatively few genes were simultaneously altered in the 3 drug resistance phenotypes studied: only 18 genes were elevated and 44 genes decreased. Many of these genes were validated and shown to be differentially expressed at the protein level (Figure
3C). Pathway enrichment analysis of these genes revealed that the most significantly enriched pathway was "fatty acid metabolism and oxidation" (4 genes were part of this pathway). Certain genes consistently downregulated in all the drug resistant lines were particularly interesting. In particular,
MSMB was found highly downregulated in drug resistant cells at both the mRNA and the protein levels (Figure
3B,C). Interestingly,
MSMB has been found decreased in prostate cancer and has been suggested to function through its ability to regulate apoptosis [
18]. With this function in mind, it is intriguing that we identified
MSMB as one of the most downregulated genes following the development of drug resistance for all three drugs. These findings suggest that
MSMB or derivatives may be useful in sensitizing ovarian cancer cells to chemotherapy. In particular, a small peptide derived from the
MSMB protein has been shown to exhibit anti-tumor properties [
19] and has been suggested as a potential therapeutic agent in prostate cancer [
20]. It will be interesting to determine whether this peptide may be useful in reversing drug resistance in ovarian cancer and we are currently investigating this enticing possibility.
RFTN1 is another gene consistently downregulated in all three drug resistance phenotype and it encodes a lipid raft protein.
RFTN1 is located on chromosome 3p24, a region shown to be frequently deleted in ovarian cancer, including in OV90 cells [
21]. This gene has also been shown to be mutated in some ovarian tumors [
22], suggesting that it may represent a genuine tumor suppressor gene in this disease. Our results suggest that it may also be involved in drug resistance.
Multiple mechanisms can mediate the development of drug resistance and include 1) changes in the regulation or repair of the primary target of the drug (DNA, microtubule, etc), 2) drug retention (increased influx or decreased uptake), 3) increased drug inactivation or sequestration, 4) signaling pathways that affect survival. For cisplatin, copper transporter CTR1 has been shown to play a crucial role in cisplatin uptake and knockout of the CTR1 alleles can lead to resistance to cisplatin toxicity [
5]. On the other hand, paclitaxel and doxorubicin are known substrates for the ATP-dependent efflux pump P-glycoprotein (MDR transporter system,
ABCB1) and up-regulation of MDR1 has been associated with clinical drug resistance in multiple systems [
23]. While we failed to observe changes in the expression of
CTR1 in cisplatin (or other) resistant lines, we did identify MDR1 (
ABCB1) as one of our most up-regulated genes in all the resistant phenotypes, including cisplatin resistant cells. Genes of the
GAGE and
MAGEA family have also been found elevated in drug resistance. In particular,
MAGEA3,
6,11,12 as well as
GAGE2,4,5,6 and
7 were found elevated in ovarian cancer cells resistant to paclitaxel and doxorubicin [
24]. In this study, we also find
GAGE5,6,7 and
XAGE1 to be consistently elevated in the various drug resistant lines, although the levels varied according to the resistance phenotype.
While drug resistance development clearly involves changes in a large number of genes and pathways, we wondered whether pathway analysis may help us identify "dominant" pathways for each drug resistance phenotype. Using pathway analysis, we were indeed able to identify several dominant pathways altered in the different drug resistant cells (Table
2 and Figure
4). Different pathway databases identified different pathways, likely because of variations in annotation and curation, but comparison of the results from different databases allowed us to find pathways that were consistently identified (Figure
4). In cisplatin-derived resistance, we frequently found changes in ECM pathways altered. ECM-Integrin interactions have previously been shown to control cell survival [
25] and ECM has been implicated in ovarian cancer drug resistance [
26] as well as lung cancer drug resistance [
27]. The development of doxorubicin resistance exhibited strong changes in pathways associated with proteasome degradation, This is particularly interesting considering that bortezomib, a proteasome inhibitor, has been found effective in combination therapy with doxorubicin in several studies [
28,
29]. Because of the specific proteasome genes found altered, as well as the presence of cell cycle genes differentially expressed (such as CDK7), it is likely that the proteasome pathway changes affect the cell cycle. It has been shown that doxorubicin can affect G2/M transition and cyclin B1 activity [
30], and changes in the cell cycle may therefore influence the response to doxorubicin through changes in apoptosis sensitivity [
31]. Paclitaxel resistance was associated with changes in pathways important for mRNA and protein synthesis, oxidative stress and glycolysis. The exact mechanisms by which these pathways can affect the resistance to paclitaxel remain under investigation, but changes in apoptosis sensitivity is a certain possibility since general mRNA degradation and oxidative stress have been implicated in apoptosis [
32,
33].
In conclusion, we have generated drug resistant ovarian cancer cell lines through exposure to three different chemotherapeutic drugs and identified gene expression patterns altered during the development of chemoresistance. Among the genes that are consistently elevated we identify previously known genes such as
ABCB1 and genes of the
MAGEA family. Among the genes downregulated, we find genes such as
MSMB and
PRSS family members that are implicated for the first time in drug resistance. Overall, we find that different drug resistance phenotypes have different expression patterns and we identify many novel genes that may be important in the development of cisplatin, doxorubicin and paclitaxel resistance. Pathway analysis suggests enticing new mechanisms for the development of resistance to cisplatin, doxorubicin, and paclitaxel in ovarian cancer and we find that each resistance phenotype is associated with specific pathway alterations (Figure
5). Whether the identified pathways are causally related to drug resistance remains to be determined and it will be important to follow up these findings with mechanistic studies to better understand the roles of the genes and pathways we have identified.
Competing interests
The authors declare that they have no competing interests.
Authors' contributions
CASB generated some of the drug resistant lines, performed the survival experiments on the ovarian cancer cell lines, and helped in drafting the manuscript. KGB participated in the microarray experiments design and analysis. WHW performed the microarray experiments. YZ analyzed the microarray data. PJM conceived the study, oversaw the experiments, analyzed the data, and drafted the manuscript. All the authors in this manuscript have read and approved the final version.