Tumor microRNA expression patterns associated with resistance to platinum based chemotherapy and survival in ovarian cancer patients
Introduction
Epithelial ovarian cancer (EOC) is the fifth leading cause of cancer-related deaths in women in the United States and the leading cause of gynecologic cancer-related deaths [1]. Annually, there are more than 22,000 new cases of ovarian cancer in the United States and over 16,000 deaths. Despite efforts to develop an effective ovarian cancer screening method, most patients still present with advanced (stages III–IV) disease [2]. Survival of patients diagnosed with ovarian cancer is known to closely correlate with stage at diagnosis.
In the setting of primary advanced disease, the two most important prognostic factors for patients with advanced ovarian carcinoma are the amount of residual disease left after surgery and the response to platinum based chemotherapy [2], [3]. A complete clinical response can be achieved in approximately 80%–90% of patients with early-stage disease and in 50% of patients with advanced-stage disease. Despite achieving clinical remission after completion of initial treatment, most patients with advanced epithelial ovarian cancer will ultimately develop recurrent disease [4].
Patients who have a prolonged disease-free-interval after first line platinum based chemotherapy, can be re-treated with platinum and are more likely to respond well to second line therapy. This group of patients has an improved prognosis with a prolonged disease-free interval and longer overall survival. Patients who have progressive disease during platinum treatment or who suffer first recurrent disease within a short period of time are termed platinum-resistant. These patients are given alternative chemotherapy regimens which offer relatively small total response rates reaching 20–30% at most and usually have a poorer prognosis.
It is clinically important to identify biomarkers that may assist to detect and predict which patients with ovarian cancer will respond to platinum based chemotherapy and which patients will remain refractory to this standard treatment. Specific data may assist in tailoring treatment to each patient's specific clinical situation during the initial management of their disease and also offer the opportunity for better counseling regarding prognosis.
Comparison of the patterns of gene expressions in ovarian cancer and normal ovarian tissue using cDNA microarrays revealed several genes that are differentially expressed in ovarian cancer [5], [6], [7]. Others have identified patterns of gene expression that predict response to chemotherapeutic agents, and prognosis [8], [9], [10].
MicroRNAs (miRNAs), a group of 22-oligonucleotide RNA molecules are non-coding forms of RNAs involved in post-transcriptional gene regulation. As modulators of protein expression they may also operate as oncogenes and tumor suppressors [11]. These small RNAs act by binding to a complementary site in the 3′UTR of specific mRNA molecules, leading to either suppression of translation or cleavage of the mRNA. MiRNAs have been shown to be conserved through evolution, and are believed to represent 1–5% of the total genes in some species [12]. Studies have demonstrated an important role for miRNAs in various developmental, differentiation and maturation processes [13], [14], and more recently, miRNAs has been suggested to be involved in pathological conditions, amongst them, cancer [15], [16], [17], [18]. Understanding the regulatory role of miRNA may lead to better understanding of the molecular events involved in different biological processes, and can lead to the development of diagnostic tools and a novel class of drug targets for therapeutic interventions.
Using high-resolution array-based comparative genomic hybridization (CGH) researchers have demonstrated significant alterations in the copy number of genomic loci that contain miRNA genes in several cancers, including ovarian cancer [19].
In this study, we have assessed the expression pattern of miRNA in ovarian tumors. We determine that certain microRNA expression patterns predict outcome, response to chemotherapy and survival.
Section snippets
Patients and samples
Patients, who were surgically treated for ovarian cancer at the Rabin Medical Center between January, 2000 and December, 2004 were identified. All pathology slides were re-evaluated by an expert pathologist. Tumor histology was established and the diagnosis of EOC was confirmed. Only serous papillary and endometrioid histology were included in the study. Patients found to have a synchronous endometrial malignancy were excluded. For each patient, a formalin-fixed, paraffin-embedded (FFPE) tumor
Results
Fifty-seven patients were identified to fit study criteria. Nineteen patients had stage I disease at diagnosis, 38 patients stage III at diagnosis. Due to small numbers, stage II and stage IV patients were excluded from the study. Table 1 lists clinical parameters for the study cohort, divided into stage I patients, and stage III patients who were either platinum-resistant or platinum-sensitive (see Methods and below). One patient was censored after 161 days (due to death of other causes) and
Discussion
It is well known that stage at diagnosis is one of the most important prognostic factors in ovarian cancer. Only 25% of patients are diagnosed with stage I disease confined to the ovary but these patients have excellent survival, reaching 85% at 5 years [4]. Some investigators believe that stage I ovarian carcinoma is a completely separate disease from cases diagnosed with advanced disease [24], although this has not yet met with general acceptance. We have found that microRNA expression
Conflict of interest statement
Ram Eitan — no conflict of interest.
Michal Kushnir — full time employee of Rosetta genomics receiving salary and holding company equity.
Gila Lithwick-Yanai— full time employee of Rosetta genomics receiving salary and holding company equity.
Miriam Ben David— full time employee of Rosetta genomics receiving salary and holding company equity.
Moshe Hoshen— full time employee of Rosetta genomics receiving salary and holding company equity.
Marek Glezerman— no conflict of interest.
Moshe Hod — chairman
Acknowledgment
We thank Dr. Tamara Drozd from the Rabin Medical Center for her assistance.
References (32)
- et al.
Prediction of chemotherapeutic response in ovarian cancer with DNA microarray expression profiling
Cancer Genet. Cytogenet.
(2004) MicroRNAs: genomics, biogenesis, mechanism, and function
Cell
(2004)- et al.
Unique microRNA molecular profiles in lung cancer diagnosis and prognosis
Cancer Cell
(2006) - et al.
MicroRNA targeting specificity in mammals: determinants beyond seed pairing
Mol. Cell
(2007) - et al.
Early detection and treatment of ovarian cancer: shifting from early stage to minimal volume of disease based on a new model of carcinogenesis
Am. J. Obstet. Gynecol.
(2008) - et al.
Transcriptional activation of miR-34a contributes to p53-mediated apoptosis
Mol. Cell
(2007) - et al.
Role of microRNA miR-27a and miR-451 in the regulation of MDR1/P-glycoprotein expression in human cancer cells
Biochem. Pharmacol.
(2008) - et al.
Cancer statistics, 2007
C.A. Cancer J. Clin.
(2007) - et al.
Prognostic factors for stage III epithelial ovarian cancer: a Gynecologic Oncology Group Study
J Clin Oncol.
(2007) - et al.
Survival effect of maximal cytoreductive surgery for advanced ovarian carcinoma during the platinum era: a meta-analysis
J. Clin. Oncol.
(2002)
Epithelial ovarian cancer
Identification of differentially expressed genes in clinically distinct groups of serous ovarian carcinomas using cDNA microarray
Int. J. Mol. Med.
Characterization of differentially expressed genes in ovarian cancer by cDNA microarrays
Int. J. Gynecol. Cancer
Microarray analysis of differentially expressed genes associated with human ovarian cancer
Int. J. Oncol.
Analysis of gene expression profiles associated with cisplatin resistance in human ovarian cancer cell lines and tissues using cDNA microarray
Hum. Cell
Gene expression profiles with cDNA microarray reveal RhoGDI as a predictive marker for paclitaxel resistance in ovarian cancers
Oncol. Rep.
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RE, MK and GL-Y contributed equally to this work.