L. DeEtte Walker

Gene expression profiling supports the hypothesis that human ovarian surface epithelia are multipotent and capable of serving as ovarian cancer initiating cells

BackgroundAccumulating evidence suggests that somatic stem cells undergo mutagenic transformation into cancer initiating cells. The serous subtype of ovarian adenocarcinoma in humans has been hypothesized to arise from at least two possible classes of progenitor cells: the ovarian surface epithelia (OSE) and/or an as yet undefined class of progenitor cells residing in the distal end of the fallopian tube.MethodsComparative gene expression profiling analyses were carried out on OSE removed from the surface of normal human ovaries and ovarian cancer epithelial cells (CEPI) isolated by laser capture micro-dissection (LCM) from human serous papillary ovarian adenocarcinomas. The results of the gene expression analyses were randomly confirmed in paraffin embedded tissues from ovarian adenocarcinoma of serous subtype and non-neoplastic ovarian tissues using immunohistochemistry. Differentially expressed genes were analyzed using gene ontology, molecular pathway, and gene set enrichment analysis algorithms.ResultsConsistent with multipotent capacity, genes in pathways previously associated with adult stem cell maintenance are highly expressed in ovarian surface epithelia and are not expressed or expressed at very low levels in serous ovarian adenocarcinoma. Among the over 2000 genes that are significantly differentially expressed, a number of pathways and novel pathway interactions are identified that may contribute to ovarian adenocarcinoma development.ConclusionsOur results are consistent with the hypothesis that human ovarian surface epithelia are multipotent and capable of serving as the origin of ovarian adenocarcinoma. While our findings do not rule out the possibility that ovarian cancers may also arise from other sources, they are inconsistent with claims that ovarian surface epithelia cannot serve as the origin of ovarian cancer initiating cells.

Molecular profiling supports the role of epithelial-to-mesenchymal transition (EMT) in ovarian cancer metastasis

BackgroundWhile metastasis ranks among the most lethal of all cancer-associated processes, on the molecular level, it remains one of the least well understood. One model that has gained credibility in recent years is that metastasizing cells at least partially recapitulate the developmental process of epithelial-to-mesenchymal transition (EMT) in their transit from primary to metastatic sites. While experimentally supported by cell culture and animal model studies, the lack of unambiguous confirmatory evidence in cancer patients has led to persistent challenges to the model’s relevance in humans.MethodsGene expression profiling (Affymetrix, U133) was carried out on 14 matched sets of primary (ovary) and metastatic (omentum) ovarian cancer (serous adenocarcinoma) patient samples. Hierarchical clustering and functional pathway algorithms were used in the data analysis.ResultsWhile histological examination reveled no morphological distinction between the matched sets of primary and metastatic samples, gene expression profiling clearly distinguished two classes of metastatic samples. One class displayed expression patterns statistically indistinguishable from primary samples isolated from the same patients while a second class displayed expression patterns significantly different from primary samples. Further analyses focusing on genes previously associated with EMT clearly distinguished the primary from metastatic samples in all but one patient.ConclusionOur results are consistent with a role of EMT in most if not all ovarian cancer metastases and demonstrate that identical morphologies between primary and metastatic cancer samples is insufficient evidence to negate a role of EMT in the metastatic process.

Evidence for the complexity of microRNA-mediated regulation in ovarian cancer: a systems approach.

MicroRNAs (miRNAs) are short (∼22 nucleotides) regulatory RNAs that can modulate gene expression and are aberrantly expressed in many diseases including cancer. Previous studies have shown that miRNAs inhibit the translation and facilitate the degradation of their targeted messenger RNAs (mRNAs) making them attractive candidates for use in cancer therapy. However, the potential clinical utility of miRNAs in cancer therapy rests heavily upon our ability to understand and accurately predict the consequences of fluctuations in levels of miRNAs within the context of complex tumor cells. To evaluate the predictive power of current models, levels of miRNAs and their targeted mRNAs were measured in laser captured micro-dissected (LCM) ovarian cancer epithelial cells (CEPI) and compared with levels present in ovarian surface epithelial cells (OSE). We found that the predicted inverse correlation between changes in levels of miRNAs and levels of their mRNA targets held for only ∼11% of predicted target mRNAs. We demonstrate that this low inverse correlation between changes in levels of miRNAs and their target mRNAs in vivo is not merely an artifact of inaccurate miRNA target predictions but the likely consequence of indirect cellular processes that modulate the regulatory effects of miRNAs in vivo. Our findings underscore the complexities of miRNA-mediated regulation in vivo and the necessity of understanding the basis of these complexities in cancer cells before the therapeutic potential of miRNAs can be fully realized.

Feasibility of Detecting Prostate Cancer by Ultraperformance Liquid Chromatography–Mass Spectrometry Serum Metabolomics

Prostate cancer (PCa) is the second leading cause of cancer-related mortality in men. The prevalent diagnosis method is based on the serum prostate-specific antigen (PSA) screening test, which suffers from low specificity, overdiagnosis, and overtreatment. In this work, untargeted metabolomic profiling of age-matched serum samples from prostate cancer patients and healthy individuals was performed using ultraperformance liquid chromatography coupled to high-resolution tandem mass spectrometry (UPLC-MS/MS) and machine learning methods. A metabolite-based in vitro diagnostic multivariate index assay (IVDMIA) was developed to predict the presence of PCa in serum samples with high classification sensitivity, specificity, and accuracy. A panel of 40 metabolic spectral features was found to be differential with 92.1% sensitivity, 94.3% specificity, and 93.0% accuracy. The performance of the IVDMIA was higher than the prevalent PSA test. Within the discriminant panel, 31 metabolites were identified by MS and MS/MS, with 10 further confirmed chromatographically by standards. Numerous discriminant metabolites were mapped in the steroid hormone biosynthesis pathway. The identification of fatty acids, amino acids, lysophospholipids, and bile acids provided further insights into the metabolic alterations associated with the disease. With additional work, the results presented here show great potential toward implementation in clinical settings.

Epigenetic changes within the promoter region of the HLA-G gene in ovarian tumors

BackgroundPrevious findings have suggested that epigenetic-mediated HLA-G expression in tumor cells may be associated with resistance to host immunosurveillance. To explore the potential role of DNA methylation on HLA-G expression in ovarian cancer, we correlated differences in HLA-G expression with methylation changes within the HLA-G regulatory region in an ovarian cancer cell line treated with 5-aza-deoxycytidine (5-aza-dC) and in malignant and benign ovarian tumor samples and ovarian surface epithelial cells (OSE) isolated from patients with normal ovaries.ResultsA region containing an intact hypoxia response element (HRE) remained completely methylated in the cell line after treatment with 5-aza-dC and was completely methylated in all of the ovarian tumor (malignant and benign) samples examined, but only variably methylated in normal OSE samples. HLA-G expression was significantly increased in the 5-aza-dC treated cell line but no significant difference was detected between the tumor and OSE samples examined.ConclusionSince HRE is the binding site of a known repressor of HLA-G expression (HIF-1), we hypothesize that methylation of the region surrounding the HRE may help maintain the potential for expression of HLA-G in ovarian tumors. The fact that no correlation exists between methylation and HLA-G gene expression between ovarian tumor samples and OSE, suggests that changes in methylation may be necessary but not sufficient for HLA-G expression in ovarian cancer.

The effects of MicroRNA transfections on global patterns of gene expression in ovarian cancer cells are functionally coordinated

BackgroundMicroRNAs (miRNAs) are a class of small RNAs that have been linked to a number of diseases including cancer. The potential application of miRNAs in the diagnostics and therapeutics of ovarian and other cancers is an area of intense interest. A current challenge is the inability to accurately predict the functional consequences of exogenous modulations in the levels of potentially therapeutic miRNAs.MethodsIn an initial effort to systematically address this issue, we conducted miRNA transfection experiments using two miRNAs (miR-7, miR-128). We monitored the consequent changes in global patterns of gene expression by microarray and quantitative (real-time) polymerase chain reaction. Network analysis of the expression data was used to predict the consequence of each transfection on cellular function and these predictions were experimentally tested.ResultsWhile ~20% of the changes in expression patterns of hundreds to thousands of genes could be attributed to direct miRNA-mRNA interactions, the majority of the changes are indirect, involving the downstream consequences of miRNA-mediated changes in regulatory gene expression. The changes in gene expression induced by individual miRNAs are functionally coordinated but distinct between the two miRNAs. MiR-7 transfection into ovarian cancer cells induces changes in cell adhesion and other developmental networks previously associated with epithelial-mesenchymal transitions (EMT) and other processes linked with metastasis. In contrast, miR-128 transfection induces changes in cell cycle control and other processes commonly linked with cellular replication.ConclusionsThe functionally coordinated patterns of gene expression displayed by different families of miRNAs have the potential to provide clinicians with a strategy to treat cancers from a systems rather than a single gene perspective.

Evidence for the importance of personalized molecular profiling in pancreatic cancer.

Objectives There is a growing body of evidence that targeted gene therapy holds great promise for the future treatment of cancer. A crucial step in this therapy is the accurate identification of appropriate candidate genes/pathways for targeted treatment. One approach is to identify variant genes/pathways that are significantly enriched in groups of afflicted individuals relative to control subjects. However, if there are multiple molecular pathways to the same cancer, the molecular determinants of the disease may be heterogeneous among individuals and possibly go undetected by group analyses. Methods In an effort to explore this question in pancreatic cancer, we compared the most significantly differentially expressed genes/pathways between cancer and control patient samples as determined by group versus personalized analyses. Results We found little to no overlap between genes/pathways identified by gene expression profiling using group analyses relative to those identified by personalized analyses. Conclusions Our results indicate that personalized and not group molecular profiling is the most appropriate approach for the identification of putative candidates for targeted gene therapy of pancreatic and perhaps other cancers with heterogeneous molecular etiology.

Molecular Profiling Predicts the Existence of Two Functionally Distinct Classes of Ovarian Cancer Stroma

Although stromal cell signaling has been shown to play a significant role in the progression of many cancers, relatively little is known about its importance in modulating ovarian cancer development. The purpose of this study was to investigate the process of stroma activation in human ovarian cancer by molecular analysis of matched sets of cancer and surrounding stroma tissues. RNA microarray profiling of 45 tissue samples was carried out using the Affymetrix (U133 Plus 2.0) gene expression platform. Laser capture microdissection (LCM) was employed to isolate cancer cells from the tumors of ovarian cancer patients (Cepi) and matched sets of surrounding cancer stroma (CS). For controls, ovarian surface epithelial cells (OSE) were isolated from the normal (noncancerous) ovaries and normal stroma (NS). Hierarchical clustering of the microarray data resulted in clear separations between the OSE, Cepi, NS, and CS samples. Expression patterns of genes encoding signaling molecules and compatible receptors in the CS and Cepi samples indicate the existence of two subgroups of cancer stroma (CS) with different propensities to support tumor growth. Our results indicate that functionally significant variability exists among ovarian cancer patients in the ability of the microenvironment to modulate cancer development.

Transcriptional override: a regulatory network model of indirect responses to modulations in microRNA expression

BackgroundDocumented changes in levels of microRNAs (miRNA) in a variety of diseases including cancer are leading to their development as early indicators of disease, and as a potential new class of therapeutic agents. A significant hurdle to the rational application of miRNAs as therapeutics is our current inability to reliably predict the range of molecular and cellular consequences of perturbations in the levels of specific miRNAs on targeted cells. While the direct gene (mRNA) targets of individual miRNAs can be computationally predicted with reasonable degrees of accuracy, reliable predictions of the indirect molecular effects of perturbations in miRNA levels remain a major challenge in molecular systems biology.ResultsChanges in gene (mRNA) and miRNA expression levels between normal precursor and ovarian cancer cells isolated from patient tissue samples were measured by microarray. Expression of 31 miRNAs was significantly elevated in the cancer samples. Consistent with previous reports, the expected decrease in expression of the mRNA targets of upregulated miRNAs was observed in only 20-30% of the cancer samples. We present and provide experimental support for a network model (The Transcriptional Override Model; TOM) to account for the unexpected regulatory consequences of modulations in the expression of miRNAs on expression levels of their target mRNAs in ovarian cancer.ConclusionsThe direct and indirect regulatory effects of changes in miRNA expression levels in vivo are interactive and complex but amenable to systems level modeling. Although TOM has been developed and validated within the context of ovarian cancer, it may be applicable in other biological contexts as well, including of potential future use in the rational design of miRNA-based strategies for the treatment of cancers and other diseases.

p66Shc longevity protein regulates the proliferation of human ovarian cancer cells

p66Shc functions as a longevity protein in murine and exhibits oxidase activity in regulating diverse biological activities. In this study, we investigated the role of p66Shc protein in regulating ovarian cancer (OCa) cell proliferation. Among three cell lines examined, the slowest growing OVCAR‐3 cells have the lowest level of p66Shc protein. Transient transfection with p66Shc cDNA expression vector in OVCAR‐3 cells increases cell proliferation. Conversely, knock‐down of p66Shc by shRNA in rapidly growing SKOV‐3 cells results in decreased cell growth. In estrogen (E2)‐treated CaOV‐3 cells, elevated p66Shc protein level correlates with ROS level, ErbB‐2 and ERK/MAPK activation, and cell proliferation. Further, the E2‐stimulated proliferation of CaOV‐3 cells was blocked by antioxidants and ErbB‐2 inhibitor. Additionally, in E2‐stimulated cells, the tartrate‐sensitive, but not the tartrate‐resistant, phosphatase activity decreases; concurrently, the tyrosine phosphorylation of ErbB‐2 increases. Conversely, inhibition of phosphatase activity by L(+)‐tartrate treatment increases p66Shc protein level, ErbB‐2 tyrosine phosphorylation, ERK/MAPK activation, and cell growth. Further, inhibition of the ERK/MAPK pathway by PD98059 blocks E2‐induced ERK/MAPK activation and cell proliferation in CaOV‐3 cells. Moreover, immunohistochemical analyses showed that the p66Shc protein level was significantly higher in cancerous cells than in noncancerous cells in archival OCa tissues (n = 76; P = 0.00037). These data collectively indicate that p66Shc protein plays a critical role in up‐regulating OCa progression.