Serous Ovarian Cancer Samples Research Articles

Identification of tumor suppressors and oncogenes from genomic and epigenetic features in ovarian cancer.

The identification of genetic and epigenetic alterations from primary tumor cells has become a common method to identify genes critical to the development and progression of cancer. We seek to identify those genetic and epigenetic aberrations that have the most impact on gene function within the tumor. First, we perform a bioinformatic analysis of copy number variation (CNV) and DNA methylation covering the genetic landscape of ovarian cancer tumor cells. We separately examined CNV and DNA methylation for 42 primary serous ovarian cancer samples using MOMA-ROMA assays and 379 tumor samples analyzed by The Cancer Genome Atlas. We have identified 346 genes with significant deletions or amplifications among the tumor samples. Utilizing associated gene expression data we predict 156 genes with altered copy number and correlated changes in expression. Among these genes CCNE1, POP4, UQCRB, PHF20L1 and C19orf2 were identified within both data sets. We were specifically interested in copy number variation as our base genomic property in the prediction of tumor suppressors and oncogenes in the altered ovarian tumor. We therefore identify changes in DNA methylation and expression for all amplified and deleted genes. We statistically define tumor suppressor and oncogenic features for these modalities and perform a correlation analysis with expression. We predicted 611 potential oncogenes and tumor suppressors candidates by integrating these data types. Genes with a strong correlation for methylation dependent expression changes exhibited at varying copy number aberrations include CDCA8, ATAD2, CDKN2A, RAB25, AURKA, BOP1 and EIF2C3. We provide copy number variation and DNA methylation analysis for over 11,500 individual genes covering the genetic landscape of ovarian cancer tumors. We show the extent of genomic and epigenetic alterations for known tumor suppressors and oncogenes and also use these defined features to identify potential ovarian cancer gene candidates.

Wnt and Hedgehog Gene Pathway Expression in Serous Ovarian Cancer

Ovarian cancer has very heterogeneous histological classification, and response to therapy of the same grade and type varies. We studied genes in the Wnt and hedgehog (Hh) pathways, which are essential for embryonic development and which play critical roles in proliferation in a variety of human cancers. Variations in these pathway genes causing proliferation could play a role in the variation in tumor progression and response to therapy. Using real-time polymerase chain reaction, we studied 16 primary grade 3 International Federation of Gynecology and Obstetrics stage III serous ovarian cancer samples for expression of the Wnt pathway gene AXIN2, fibroblast growth factor 9, and Hh pathway gene expressions of glioma-associated oncogene 1, glioma-associated oncogene 2, patched homolog 1, patched homolog 2, Indian Hedgehog (HH), sonic HH, and Smoothened, a G protein-coupled receptor protein. Normal ovary epithelial cell line was used as control. We found wide variation of up-regulation of pathway component and target genes in the primary tumor samples and apparent cross talk between the pathways. AXIN2, a Wnt target gene, showed increased expression in all serous ovarian cancer samples. Fibroblast growth factor 9 was also overexpressed in all tumors with greater than 1000-fold increase in gene expression in 4 tumors. Expression of Hh pathway genes varied greatly. More than half of the tumor samples showed involvement of Hh signaling or pathway activation either by expression of transcription factors and Hh ligands or by overexpression of Indian HH/sonic HH and the receptor-encoding patched homolog 1/patched homolog 2. We found a wide variation in fold expression of genes involved in the Wnt and Hh pathway between patient samples.

Circulating biomarker tissue kallikrein-related peptidase KLK5 impacts ovarian cancer patients’ survival

BackgroundEffective cancer biomarkers for early detection, prognosis, or therapy response prediction are urgently needed in ovarian cancer. Kallikrein-related peptidases, including KLK5, have been reported to play an important role in the course of the disease. Patients and methodsKLK5 antigen content was determined by enzyme-linked immunosorbent assay in ovarian cancer patients’ [FIGO (International Federation of Gynecology and Obstetrics) stages I–IV, n = 52] serum as well as ascitic fluid and compared with KLK5 content in serum of patients with benign ovarian tumors (n = 45). ResultsKLK5 antigen content was significantly elevated in the serum of ovarian cancer patients compared with the serum of patients with benign ovarian tumors. Forty-two of 52 ovarian cancer serum samples, 42 of 43 benign ovarian tumor serum samples, and all 41 ascitic fluid samples were KLK5 positive. Elevated KLK5 antigen in serum and ascitic fluid of ovarian cancer patients was a prognostic factor for progression-free survival. ConclusionsOur data support the finding that ovarian cancer patients release significant amounts of KLK5 into serum and ascitic fluid but KLK5 antigen is low in serum of patients with benign ovarian tumors. Increased serum and ascitic fluid KLK5 levels are associated with poor patient outcome, thus underlining the importance of KLK5 as a biomarker for early detection as well as for disease management in ovarian cancer.

Evaluation of EVI1 and EVI1s (Δ324) as potential therapeutic targets in ovarian cancer

Purpose The MDS1 and EVI1 complex locus (MECOM) at 3q26 gives rise to several alternatively spliced transcripts implicated in leukemic oncogenesis. Overexpression of EVI1 in ovarian cancer has led to a proposed oncogenic role. Our objective was to evaluate the therapeutic potential of EVI1 and EVI1s (also known as Δ324) in ovarian cancer. Methods Expression of EVI1 mRNA and protein isoforms was evaluated in ovarian cancers, normal ovaries, benign ovarian neoplasms, and fallopian tube fimbria. Effects of EVI1 isoform overexpression and knockdown on proliferation, cisplatin-induced apoptosis, and double stranded DNA breaks were investigated. Results EVI1 and EVI1s mRNAs were ubiquitously expressed in ovarian cancers and benign gynecologic tissues examined, with highest expression of both isoforms noted in the cancer samples. The EVI1s to total EVI1 mRNA ratio was uniform among the examined tissues. In contrast, EVI1 protein isoform levels were undetectable in normal ovarian tissues, and highest in serous ovarian cancers. EVI1 protein expression patterns were similar between serous ovarian cancer samples, fallopian tube fimbria, and benign neoplasms. Expression of EVI1 or EVI1s did not increase proliferation in EVI1-null OVCAR8 cells. Total and isoform selective knockdown of EVI1 isoforms in EVI1 expressing ovarian cancer cells had no effect on proliferation, cisplatin-induced apoptosis, or γ-H2AX levels in ovarian cancer cells. Conclusion Our data do not support a role for EVI1 or EVI1s in ovarian cancer cell proliferation or response to DNA damage. Further research is required before EVI1 can be considered an oncogene or a therapeutic target in ovarian cancer.

Abstract 5480: Expression and function of EVI1 and EVI1s (Δ324) ovarian cancer

Abstract Objective: The MDS1 and EVI1 complex locus (MECOM) located at the 3q26 locus is amplified in many cancers and gives rise to a number of alternatively spliced transcripts and proteins including EVI1 and MDS1-EVI1 (ME). EVI1 functions as an oncogene in human and murine myeloproliferative disorders and myelogenous leukemias. Amplification and over expression of EVI1 and ME have been demonstrated in ovarian cancers, and these proteins have been proposed as potential therapeutic targets that may also play a role in chemoresistance. Our objective was to evaluate the expression and biological function of EVI1 and one of its splice isoform known as EVI1s or Δ324 in ovarian cancer. Methods: Expression of EVI1 isoforms was evaluated in serous ovarian cancer samples, normal ovaries, benign ovarian neoplasms, and fallopian tube fimbria (emerging as the likely site of origin of many serous ovarian cancers) using realtime RT-PCR, and immunoblotting. Alterations in EVI1 and EVI1s expression were induced by retroviral transduction and isoform selective siRNA. Proliferation was measured using MTT and BrdU assays. Dose response to paclitaxel and cisplatin was measured following isoform selective knockdown of EVI1 and EVI1s using a histone release apoptosis ELISA. Results: EVI1 and EVI1s transcripts were present in normal ovaries, fimbria, benign ovarian neoplasms, and papillary serous ovarian cancers, with highest expression of both isoforms noted in the ovarian cancer samples. There was no change in relative expression of EVI1s among the different tissue types examined. In contrast, EVI1 protein isoforms were essentially undetectable in normal ovarian tissues. While highest average expression of ME, EVI1, and EVI1s protein isoforms was observed in serous ovarian cancer samples, considerable variability was noted between different serous ovarian cancer samples. In addition, variable expression of the same EVI1 protein isoforms was also observed in normal fallopian tube fimbria and several benign ovarian neoplasms. Forced expression of EVI1 and EVI1s did not result in any increased proliferation in OVCAR8 ovarian cancers (that lack endogenous EVI1 expression) nor in HEK293T cells. Furthermore, no effects on proliferation were observed following knockdown of EVI1, EVI1s, or all EVI1 transcripts. In dose response assays there was no significant effect on cisplatin and paclitaxel induced apoptosis following EVI1 knockdown. Daunorubicin induced DNA damage as determined by phospho-H2AX expression was also unaltered following isoform selective EVI1 siRNA. Conclusion: There is a lack of correlation between EVI1 transcript and protein isoforms in gynecologic tissues. Our results suggest that EVI1 protein expression in some serous ovarian cancers may be related to their derivation from fallopian tube origin, and that alteration of EVI1 and EVI1s protein levels doesn't influence ovarian cancer cell growth, apoptosis, or response to chemotherapy. Note: This abstract was not presented at the AACR 101st Annual Meeting 2010 because the presenter was unable to attend. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 101st Annual Meeting of the American Association for Cancer Research; 2010 Apr 17-21; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2010;70(8 Suppl):Abstract nr 5480.

Discrimination analysis of mass spectrometry proteomics for ovarian cancer detection1

A discrimination analysis has been explored for the probabilistic classification of healthy versus ovarian cancer serum samples using proteomics data from mass spectrometry (MS). The method employs data normalization, clustering, and a linear discriminant analysis on surface-enhanced laser desorption ionization (SELDI) time-of-flight MS data. The probabilistic classification method computes the optimal linear discriminant using the complex human blood serum SELDI spectra. Cross-validation and training/testing data-split experiments are conducted to verify the optimal discriminant and demonstrate the accuracy and robustness of the method. The cluster discrimination method achieves excellent performance. The sensitivity, specificity, and positive predictive values are above 97% on ovarian cancer. The protein fraction peaks, which significantly contribute to the classification, can be available from the analysis process. The discrimination analysis helps the molecular identities of differentially expressed proteins and peptides between the healthy and ovarian patients.

Gene expression patterns of chemoresistant and chemosensitive serous epithelial ovarian tumors with possible predictive value in response to initial chemotherapy

Chemotherapy (CT) resistance in ovarian cancer is broad and encompasses diverse, unrelated drugs, suggesting more than one mechanism of resistance. We aimed to analyze the gene expression patterns in primary serous epithelial ovarian cancer (EOC) samples displaying different responses to first-line CT in an attempt to identify specific molecular signatures associated with response to CT. Initially, the expression profiles of 15 chemoresistant serous EOC tumors [time to recurrence (TTR) </=6 months] and 10 chemosensitive serous EOC tumors (TTR > or =30 months) were independently analyzed which allowed the identification of specific sets of differentially expressed genes that might be functionally implicated in the evolution of the chemoresistant or the chemosensitive phenotype. Our data suggest that the intrinsic chemoresistance in serous EOC cells may be attributed to the combined action of different molecular mechanisms and factors linked with drug influx and efflux and cell proliferation, as possible implications of other molecular events including altered metabolism, apoptosis and inflammation cannot be excluded. Next, gene expression comparison using hierarchical clustering clearly distinguished chemosensitive and chemoresistant tumors from the 25 serous EOC samples (training set), and consecutive class prediction analysis was used to develop a 43-gene classifier that was further validated in an independent cohort of 15 serous EOC patients and 2 patients with other ovarian cancer histotypes (test set). The 43-gene predictor set properly classified serous EOC patients at high risk for early (< or =22 months) versus late (>22 months) relapse after initial CT. Thus, gene expression array technology can effectively classify serous EOC tumors according to CT response. The proposed 43-gene model needs further validation.

Identification of hemoglobin‐α and ‐β subunits as potential serum biomarkers for the diagnosis and prognosis of ovarian cancer

The development of new biomarkers for ovarian cancer is clearly necessary for the improved detection and monitoring of the disease. Surface enhanced laser desorption and ionization time-of-flight mass spectrometry (SELDI-TOF-MS) can be employed in the identification of differentially expressed proteins in cancer cells. The objective of this study was, then, to identify potential diagnostic serological biomarkers for ovarian cancer. We performed protein expression difference analyses of 45 serum samples using SELDI protein chip array. Forty-five sera obtained from ovarian cancer patients (n=35) and normal healthy females (n=10), were profiled on the surface of SELDI protein chip. The candidate biomarkers were purified by CM-Sepharose, and their N-terminal amino sequence was determined. The amounts of hemoglobin (Hb) in cancer patient's sera versus that of normal sera were measured by ELISA. Nine sera proteins that were found to be significantly differentially expressed (P<0.05) between the sera of ovarian cancer patients and that of normal healthy females were selected using the WCX2 array. The most distinctive polypeptide peaks detected in the ovarian cancer samples were at 15.1 and 15.8 kDa and these two peaks were identified as the hemoglobin-alpha (Hb-alpha) and -beta (Hb-beta) chain, respectively. ELISA indicated that the sensitivity for intact Hb level was 77% in sera obtained from ovarian cancer patients, as compared with normal healthy female sera. In conclusion, two ovarian cancer biomarker proteins were discovered and identified as Hb-alpha and Hb-beta. Hb levels were significantly different in ovarian cancer serum samples and those obtained from normal healthy females, as determined by ELISA. Additional studies are required to further validate Hb-alpha and Hb-beta biomarkers.