Quantification of putative ovarian cancer serum protein biomarkers using a multiplexed targeted mass spectrometry assay.

BACKGROUND: Ovarian cancer is the most lethal gynecologic malignancy in women, and high-grade serous ovarian cancer (HGSOC) is the most common subtype. Currently, no clinical test has been approved by the FDA to screen the general population for ovarian cancer. This underscores the critical need for the development of a robust methodology combined with novel technology to detect diagnostic biomarkers for HGSOC in the sera of women. Targeted mass spectrometry (MS) can be used to identify and quantify specific peptides/proteins in complex biological samples with high accuracy, sensitivity, and reproducibility. In this study, we sought to develop and conduct analytical validation of a multiplexed Tier 2 targeted MS parallel reaction monitoring (PRM) assay for the relative quantification of 23 putative ovarian cancer protein biomarkers in sera. METHODS: To develop a PRM method for our target peptides in sera, we followed nationally recognized consensus guidelines for validating fit-for-purpose Tier 2 targeted MS assays. The endogenous target peptide concentrations were calculated using the calibration curves in serum for each target peptide. Receiver operating characteristic (ROC) curves were analyzed to evaluate the diagnostic performance of the biomarker candidates. RESULTS: We describe an effort to develop and analytically validate a multiplexed Tier 2 targeted PRM MS assay to quantify candidate ovarian cancer protein biomarkers in sera. Among the 64 peptides corresponding to 23 proteins in our PRM assay, 24 peptides corresponding to 16 proteins passed the assay validation acceptability criteria. A total of 6 of these peptides from insulin-like growth factor-binding protein 2 (IBP2), sex hormone-binding globulin (SHBG), and TIMP metalloproteinase inhibitor 1 (TIMP1) were quantified in sera from a cohort of 69 patients with early-stage HGSOC, late-stage HGSOC, benign ovarian conditions, and healthy (non-cancer) controls. Confirming the results from previously published studies using orthogonal analytical approaches, IBP2 was identified as a diagnostic biomarker candidate based on its significantly increased abundance in the late-stage HGSOC patient sera compared to the healthy controls and patients with benign ovarian conditions. CONCLUSIONS: A multiplexed targeted PRM MS assay was applied to detect candidate diagnostic biomarkers in HGSOC sera. To evaluate the clinical utility of the IBP2 PRM assay for HGSOC detection, further studies need to be performed using a larger patient cohort.

Development of a Multiprotein Classifier for the Detection of Early Stage Ovarian Cancer.

BACKGROUND: Individual serum biomarkers are neither adequately sensitive nor specific for use in screening the general population for ovarian cancer. The purpose of this study was to develop a multiprotein classifier to detect the early stages of ovarian cancer, when it is most treatable. METHODS: The Olink Proseek Multiplex Oncology II panel was used to simultaneously quantify the expression levels of 92 cancer-related proteins in sera. RESULTS: In the discovery phase, we generated a multiprotein classifier that included CA125, HE4, ITGAV, and SEZ6L, based on an analysis of sera from 116 women with early stage ovarian cancer and 336 age-matched healthy women. CA125 alone achieved a sensitivity of 87.9% at a specificity of 95%, while the multiprotein classifier resulted in an increased sensitivity of 91.4%, while holding the specificity fixed at 95%. The performance of the multiprotein classifier was validated in a second cohort comprised of 192 women with early stage ovarian cancer and 467 age-matched healthy women. The sensitivity at 95% specificity increased from 74.5% (CA125 alone) to 79.2% with the multiprotein classifier. In addition, the multiprotein classifier had a sensitivity of 95.1% at 98% specificity for late stage ovarian cancer samples and correctly classified 80.5% of the benign samples using the 98% specificity cutpoint. CONCLUSIONS: The inclusion of the proteins HE4, ITGAV, and SEZ6L improved the sensitivity and specificity of CA125 alone for the detection of early stages of ovarian cancer in serum samples. Furthermore, we identified several proteins that may be novel biomarkers of early stage ovarian cancer.

Evaluation of the potential of Pap test fluid and cervical swabs to serve as clinical diagnostic biospecimens for the detection of ovarian cancer by mass spectrometry-based proteomics.

BACKGROUND: The purpose of this study was to determine whether the residual fixative from a liquid-based Pap test or a swab of the cervix contained proteins that were also found in the primary tumor of a woman with high grade serous ovarian cancer. This study is the first step in determining the feasibility of using the liquid-based Pap test or a cervical swab for the detection of ovarian cancer protein biomarkers. METHODS: Proteins were concentrated by acetone precipitation from the cell-free supernatant of the liquid-based Pap test fixative or eluted from the cervical swab. Protein was also extracted from the patient's tumor tissue. The protein samples were digested into peptides with trypsin, then the peptides were run on 2D-liquid chromatography mass spectrometry (2D-LCMS). The data was searched against a human protein database for the identification of peptides and proteins in each biospecimen. The proteins that were identified were classified for cellular localization and molecular function by bioinformatics integration. RESULTS: We identified almost 5000 proteins total in the three matched biospecimens. More than 2000 proteins were expressed in each of the three biospecimens, including several known ovarian cancer biomarkers such as CA125, HE4, and mesothelin. By Scaffold analysis of the protein Gene Ontology categories and functional analysis using PANTHER, the proteins were classified by cellular localization and molecular function, demonstrating that the Pap test fluid and cervical swab proteins are similar to each other, and also to the tumor extract. CONCLUSIONS: Our results suggest that Pap test fixatives and cervical swabs are a rich source of tumor-specific biomarkers for ovarian cancer, which could be developed as a test for ovarian cancer detection.

Cytomegalovirus and systemic inflammation at time of surgery is associated with worse outcomes in serous ovarian cancer.

OBJECTIVES: Cytomegalovirus (CMV) is a common infection that establishes latency in healthy people. CMV has been associated with alterations of the immune compartment leading to improved responses, while inflammation has been shown to adversely impact outcomes. We investigated whether CMV serostatus predicts outcomes in ovarian cancer in the presence or absence of inflammation. METHODS: A total of 106 patients with serous ovarian cancer from 2006 to 2009 were analyzed. CMV and systemic inflammation was measured using CMV immunoglobulin G (IgG) and C-reactive protein (CRP), respectively, in serum collected prior to cytoreduction. Patients were stratified by CMV IgG (non-reactive, reactive/borderline) and CRP (≤10, >10 mg/L) status. Overall survival (OS) and recurrence-free survival (RFS) were compared by group using log-rank tests and Cox proportional hazards regression models adjusting for age at surgery. RESULTS: Of 106 eligible patients, 40 (37.7%) were CMV+/CRP+, 24 (22.6%) CMV+/CRP-, 19 (17.9%) CMV-/CRP+, and 23 (21.7%) CMV-/CRP-. CRP+ had higher CA-125 levels (P = 0.05) and higher rates of suboptimal debulking (P = 0.03). There were no other significant differences in demographic, surgical, or pathologic factors between groups. CMV+/CRP+ patients median RFS and OS were 16.9 months (95% CI: 9.0-21.1) and 31.7 months (95% CI: 25.0-48.7), respectively, with a significantly worse RFS (aHR: 1.85, 95% CI: 1.05-3.24, P = 0.03) and OS (aHR: 2.12, 95% CI: 1.17-3.82, P = 0.01) compared to CMV-/CRP- (RFS = 31.2 months (95% CI: 16.0-56.4) and OS = 63.8 months (95% CI: 50.7-87.0)). CMV+/CRP- group displayed the longest OS (89.3 months). CONCLUSIONS: Previous exposure to CMV and high CRP at surgery portended worse RFS and OS compared to women who tested negative. The CMV+/CRP- group had the longest OS, indicating that CMV status alone, in the absence of inflammation, may be protective.

Inhibition of Ovarian Cancer Cell Spheroid Formation by Synthetic Peptides Derived from Nectin-4.

The formation of 3D multicellular spheroids in the ascites fluid of ovarian cancer patients is an understudied component of the disease progression. Spheroids are less sensitive to chemotherapy, in part due to the protection afforded by their structure, but also due to their slower proliferation rate. Previous studies suggest that the cell adhesion molecule Nectin-4 plays a key role in the formation of ovarian cancer spheroids. In this study, we further examined the role of Nectin-4 at early time points in spheroid formation using real-time digital photography. Human NIH:OVCAR5 ovarian cancer cells formed aggregates within 8 h, which further contracted into compact spheroids over 24 h. In contrast, Nectin-4 knockdown cells did not form tightly compacted spheroids. Synthetic peptides derived from Nectin-4 were tested for their ability to alter spheroid formation in two ovarian cancer cell lines. Nectin-4 peptide 10 (N4-P10) had an immediate effect on disrupting ovarian cancer spheroid formation, which continued for over 24 h, while a scrambled version of the peptide had no effect. N4-P10 inhibited spheroid formation in a concentration-dependent manner and was not cytotoxic; suggesting that N4-P10 treatment could maintain the cancer cells as single cells which may be more sensitive to chemotherapy.

Effect of chemotherapy on cancer stem cells and tumor-associated macrophages in a prospective study of preoperative chemotherapy in soft tissue sarcoma.

BACKGROUND: Cancer stem cells (CSC) may respond to chemotherapy differently from other tumor cells. METHODS: This study examined the expression of the putative cancer stem cell markers ALDH1, CD44, and CD133; the angiogenesis marker CD31; and the macrophage marker CD68 in soft tissue sarcomas (STS) before and after 4 cycles of chemotherapy with doxorubicin and ifosfamide in 31 patients with high-grade soft tissue sarcoma in a prospective clinical trial. RESULTS: None of the markers clearly identified CSCs in STS samples. Macrophages represented a prominent component in viable tumor areas in pre-treatment STS biopsies, ranging from < 5 to > 50%. Furthermore, macrophages expressed CD44 and ALDH1. Macrophage density correlated with baseline maximum standardized uptake value (SUVmax) on fluoro-deoxyglucose positron emission tomography (PET) imaging. Pre-chemotherapy CD68 staining correlated positively with the baseline SUVmax, and negatively with the percent of viable tumor cells in post-chemotherapy resection samples. In particular, cases with more CD68-positive cells at biopsy had fewer viable tumor cells at resection, suggesting a better response to chemotherapy. CONCLUSIONS: In conclusion, ALDH1, CD44, and CD133 are not likely to be useful markers of CSCs in STS. However, our observation of infiltrating macrophages in STS specimens indicates that these immune cells may contribute significantly to STS biology and response to chemotherapy, and could provide a potential target of therapy. Future studies should investigate macrophage contribution to STS pathophysiology by cytokine signaling.

Simultaneous Measurement of 92 Serum Protein Biomarkers for the Development of a Multiprotein Classifier for Ovarian Cancer Detection.

The best known ovarian cancer biomarker, CA125, is neither adequately sensitive nor specific for screening the general population. By using a combination of proteins for screening, it may be possible to increase the sensitivity and specificity over CA125 alone. In this study, we used Proseek Multiplex Oncology II plates to simultaneously measure the expression of 92 cancer-related proteins in serum using proximity extension assays. This technology combines the sensitivity of the PCR with the specificity of antibody-based detection methods, allowing multiplex biomarker detection and high-throughput quantification. We analyzed 1 µL of sera from each of 61 women with ovarian cancer and compared the values obtained with those from 88 age-matched healthy women. Principle component analysis and unsupervised hierarchical clustering separated the ovarian cancer patients from the healthy, with minimal misclassification. Data from the Proseek plates for CA125 levels exhibited a strong correlation with clinical values for CA125. We identified 52 proteins that differed significantly (P < 0.006) between ovarian cancer and healthy samples, several of which are novel serum biomarkers for ovarian cancer. In total, 40 proteins had an estimated area under the ROC curve of 0.70 or greater, suggesting their potential to serve as biomarkers for ovarian cancer. CA125 alone achieved a sensitivity of 93.4% at a specificity of 98%. By adding the Oncology II values for five proteins to CA125 in a multiprotein classifier, we increased the assay sensitivity to 98.4% at a specificity of 98%, thereby improving the sensitivity and specificity of CA125 alone.

Cytokine-induced memory-like natural killer cells have enhanced function, proliferation, and in vivo expansion against ovarian cancer cells.

OBJECTIVE: Natural killer (NK) cells are lymphocytes well suited for adoptive immunotherapy. Attempts with adoptive NK cell immunotherapy against ovarian cancer have proven unsuccessful, with the main limitations including failure to expand and diminished effector function. We investigated if incubation of NK cells with interleukin (IL)-12, IL-15, and IL-18 for 16h could produce cytokine-induced memory-like (CIML) NK cells capable of enhanced function against ovarian cancer. METHODS: NK cells were preactivated briefly with IL-12, IL-15, and IL-18, rested, then placed against ovarian cancer targets to assess phenotype and function via flow cytometry. Real-time NK-cell-mediated tumor-killing was evaluated. Using ascites cells and cell-free ascites fluid, NK cell proliferation and function within the immunosuppressive microenvironment was evaluated in vitro. Finally, CIML NK cells were injected intraperitoneal (IP) into an in vivo xenogeneic mouse model of ovarian cancer. RESULTS: CIML NK cells demonstrate enhanced cytokine (IFN-γ) production and NK-cell-mediated killing of ovarian cancer. NK cells treated overnight with cytokines led to robust activation characterized by temporal shedding of CD16, induction of CD25, and enhanced proliferation. CIML NK cells proliferate more with enhanced effector function compared to controls in an immunosuppressive microenvironment. Finally, human CIML NK cells exhibited potent antitumor effects within a xenogeneic mouse model of ovarian cancer. CONCLUSIONS: CIML NK cells have enhanced functionality and persistence against ovarian cancer in vitro and in vivo, even when exposed to ascites fluid. These findings provide a strategy for NK cell-based immunotherapy to circumvent the immunosuppressive nature of ovarian cancer.

Development of a multiplexed giant magnetoresistive biosensor array prototype to quantify ovarian cancer biomarkers.

In this work, we developed benchtop and handheld Giant Magnetoresistive (GMR) biosensing systems that serve as platforms for detecting a wide variety of protein biomarkers for human diseases. System development included spintronic and nanomagnetic materials, biomolecular chemistry, electronic circuitry, analog and digital signal processing, firmware programming, user interface programming on both PC and Android smartphone, communications over both USB and Bluetooth, and mechanical integration. In this work, we demonstrated the benchtop GMR biosensing system in the context of ovarian cancer assay development. The prototype system delivered the required performance in terms of high-sensitivity multiplex assays in a portable format with enough flexibility to serve as a platform for ovarian cancer and many other diseases. We achieved multiplex detection of cancer antigen 125 (CA125 II), human epididymis protein 4 (HE4), and interleukin 6 (IL6), with limits of detection (LOD) as low as 3.7 U/mL, 7.4 pg/mL, and 7.4 pg/mL, respectively.

Evaluating the potential of residual Pap test fluid as a resource for the metaproteomic analysis of the cervical-vaginal microbiome.

The human cervical-vaginal area contains proteins derived from microorganisms that may prevent or predispose women to gynecological conditions. The liquid Pap test fixative is an unexplored resource for analysis of microbial communities and the microbe-host interaction. Previously, we showed that the residual cell-free fixative from discarded Pap tests of healthy women could be used for mass spectrometry (MS) based proteomic identification of cervical-vaginal proteins. In this study, we reprocessed these MS raw data files for metaproteomic analysis to characterize the microbial community composition and function of microbial proteins in the cervical-vaginal region. This was accomplished by developing a customized protein sequence database encompassing microbes likely present in the vagina. High-mass accuracy data were searched against the protein FASTA database using a two-step search method within the Galaxy for proteomics platform. Data was analyzed by MEGAN6 (MetaGenomeAnalyzer) for phylogenetic and functional characterization. We identified over 300 unique peptides from a variety of bacterial phyla and Candida. Peptides corresponding to proteins involved in carbohydrate metabolism, oxidation-reduction, and transport were identified. By identifying microbial peptides in Pap test supernatants it may be possible to acquire a functional signature of these microbes, as well as detect specific proteins associated with cervical health and disease.

A multiplex platform for the identification of ovarian cancer biomarkers.

BACKGROUND: Currently, there are no FDA approved screening tools for detecting early stage ovarian cancer in the general population. Development of a biomarker-based assay for early detection would significantly improve the survival of ovarian cancer patients. METHODS: We used a multiplex approach to identify protein biomarkers for detecting early stage ovarian cancer. This new technology (Proseek® Multiplex Oncology Plates) can simultaneously measure the expression of 92 proteins in serum based on a proximity extension assay. We analyzed serum samples from 81 women representing healthy, benign pathology, early, and advanced stage serous ovarian cancer patients. RESULTS: Principle component analysis and unsupervised hierarchical clustering separated patients into cancer versus non-cancer subgroups. Data from the Proseek® plate for CA125 levels exhibited a strong correlation with current clinical assays for CA125 (correlation coefficient of 0.89, 95% CI 0.83, 0.93). CA125 and HE4 were present at very low levels in healthy controls and benign cases, while higher levels were found in early stage cases, with highest levels found in the advanced stage cases. Overall, significant trends were observed for 38 of the 92 proteins (p < 0.001), many of which are novel candidate serum biomarkers for ovarian cancer. The area under the ROC curve (AUC) for CA125 was 0.98 and the AUC for HE4 was 0.85 when comparing early stage ovarian cancer versus healthy controls. In total, 23 proteins had an estimated AUC of 0.7 or greater. Using a naïve Bayes classifier that combined 12 proteins, we improved the sensitivity corresponding to 95% specificity from 93 to 95% when compared to CA125 alone. Although small, a 2% increase would have a significant effect on the number of women correctly identified when screening a large population. CONCLUSIONS: These data demonstrate that the Proseek® technology can replicate the results established by conventional clinical assays for known biomarkers, identify new candidate biomarkers, and improve the sensitivity and specificity of CA125 alone. Additional studies using a larger cohort of patients will allow for validation of these biomarkers and lead to the development of a screening tool for detecting early stage ovarian cancer in the general population.

Ectodomain shedding of the cell adhesion molecule Nectin-4 in ovarian cancer is mediated by ADAM10 and ADAM17.

We previously showed that the cell adhesion molecule Nectin-4 is overexpressed in ovarian cancer tumors, and its cleaved extracellular domain can be detected in the serum of ovarian cancer patients. The ADAM (adisintegrin and metalloproteinase) proteases are involved in ectodomain cleavage of transmembrane proteins, and ADAM17 is known to cleave Nectin-4 in breast cancer. However, the mechanism of Nectin-4 cleavage in ovarian cancer has not yet been determined. Analysis of ovarian cancer gene microarray data showed that higher expression of Nectin-4, ADAM10, and ADAM17 is associated with significantly decreased progression-free survival. We quantified Nectin-4 shedding from the surface of ovarian cancer cells after stimulation with lysophosphatidic acid. We report that ADAM17 and ADAM10 cleave Nectin-4 and release soluble Nectin-4 (sN4). Small molecule inhibitors and siRNA knockdown of both ADAM proteases confirmed these results. In matched samples from 11 high-grade serous ovarian cancer patients, we detected 2-20-fold more sN4 in ascites fluid than serum. Co-incubation of ovarian cancer cells with ascites fluid significantly increased sN4 shedding, which could be blocked using a dual inhibitor of ADAM10 and ADAM17. Furthermore, we detected RNA for Nectin-4, ADAM10, and ADAM17 in primary ovarian carcinoma tumors, secondary omental metastases, and ascites cells isolated from serous ovarian cancer patients. In a signaling pathway screen, lysophosphatidic acid increased phosphorylation of AKT, EGF receptor, ERK1/2, JNK1/2/3, and c-Jun. Understanding the function of Nectin-4 shedding in ovarian cancer progression is critical to facilitate its development as both a serum biomarker and a therapeutic target for ovarian cancer.

The expression of Nectin-4 on the surface of ovarian cancer cells alters their ability to adhere, migrate, aggregate, and proliferate.

The cell adhesion molecule Nectin-4 is overexpressed in epithelial cancers, including ovarian cancer. The objective of this study was to determine the biological significance of Nectin-4 in the adhesion, aggregation, migration, and proliferation of ovarian cancer cells. Nectin-4 and its binding partner Nectin-1 were detected in patients' primary tumors, omental metastases, and ascites cells. The human cell lines NIH:OVCAR5 and CAOV3 were genetically modified to alter Nectin-4 expression. Cells that overexpressed Nectin-4 adhered to Nectin-1 in a concentration and time-dependent manner, and adhesion was inhibited by antibodies to Nectin-4 and Nectin-1, as well as synthetic Nectin peptides. In functional assays, CAOV3 cells with Nectin-4 knock-down were unable to form spheroids and migrated more slowly than CAOV3 parental cells expressing Nectin-4. NIH:OVCAR5 parental cells proliferated more rapidly, migrated faster, and formed larger spheroids than either the Nectin-4 knock-down or over-expressing cells. Parental cell lines expressed higher levels of epithelial markers and lower levels of mesenchymal markers compared to Nectin-4 knock-down cells, suggesting a role for Nectin-4 in epithelial-mesenchymal transition. Our results demonstrate that Nectin-4 promotes cell-cell adhesion, migration, and proliferation. Understanding the biology of Nectin-4 in ovarian cancer progression is critical to facilitate its development as a novel therapeutic target.

Gene expression identifies heterogeneity of metastatic behavior among gastrointestinal stromal tumors.

BACKGROUND: Adjuvant imatinib is useful in patients with gastrointestinal stromal tumors (GIST) at high risk of recurrence. At present, the risk of recurrence is determined based on tumor size, mitotic rate, tumor site, and tumor rupture. Previous studies using various biochemical pathways identified gene expression patterns that distinguish two subsets of aggressive fibromatosis (AF), serous ovarian carcinoma (OVCA), and clear cell renal cell carcinoma (RCC). These gene sets separated soft tissue sarcomas into two groups with different probabilities of developing metastatic disease. The present study used these gene sets to identify GIST subgroups with different probabilities of developing metastatic disease. METHODS: We utilized these three gene sets, hierarchical clustering, and Kaplan-Meier analysis, to examine 60 primary resected GIST samples using Agilent chip expression profiling. RESULTS: Hierarchical clustering using both the combined and individual AF-, OVCA-, and RCC- gene sets identified differences in probabilities of developing metastatic disease between the clusters defined by the first branch point of the clustering dendrograms (p = 0.029 for the combined gene set, p = 0.003 for the AF-gene set, p < 0.001 for the OVCA-gene set, and p = 0.003 for the RCC-gene set). CONCLUSIONS: Hierarchical clustering using these gene sets identified at least two subsets of GIST with distinct clinical behavior and risk of metastatic disease. The use of gene expression analysis along with other known prognostic factors may better predict the long-term outcome following surgery, and thus restrict the use of adjuvant therapy to high-risk GIST, and reduce heterogeneity among groups in clinical trials of new drugs.

Gene expression identifies heterogeneity of metastatic behavior among high-grade non-translocation associated soft tissue sarcomas.

BACKGROUND: The biologic heterogeneity of soft tissue sarcomas (STS), even within histological subtypes, complicates treatment. In earlier studies, gene expression patterns that distinguish two subsets of clear cell renal carcinoma (RCC), serous ovarian carcinoma (OVCA), and aggressive fibromatosis (AF) were used to separate 73 STS into two or four groups with different probabilities of developing metastatic disease (PrMet). This study was designed to confirm our earlier observations in a larger independent data set. METHODS: We utilized these gene sets, hierarchical clustering (HC), and Kaplan-Meier analysis, to examine 309 STS, using Affymetrix chip expression profiling. RESULTS: HC using the combined AF-, RCC-, and OVCA-gene sets identified subsets of the STS samples. Analysis revealed differences in PrMet between the clusters defined by the first branch point of the clustering dendrogram (p = 0.048), and also among the four different clusters defined by the second branch points (p < 0.0001). Analysis also revealed differences in PrMet between the leiomyosarcomas (LMS), dedifferentiated liposarcomas (LipoD), and undifferentiated pleomorphic sarcomas (UPS) (p = 0.0004). HC of both the LipoD and UPS sample sets divided the samples into two groups with different PrMet (p = 0.0128, and 0.0002, respectively). HC of the UPS samples also showed four groups with different PrMet (p = 0.0007). HC found no subgroups of the LMS samples. CONCLUSIONS: These data confirm our earlier studies, and suggest that this approach may allow the identification of more than two subsets of STS, each with distinct clinical behavior, and may be useful to stratify STS in clinical trials and in patient management.

Expression of FAP, ADAM12, WISP1, and SOX11 is heterogeneous in aggressive fibromatosis and spatially relates to the histologic features of tumor activity.

Aggressive fibromatosis (AF) represents a group of tumors with a variable and unpredictable clinical course, characterized by a monoclonal proliferation of myofibroblastic cells. The optimal treatment for AF remains unclear. Identification and validation of genes whose expression patterns are associated with AF may elucidate biological mechanisms in AF, and aid treatment selection. This study was designed to examine the protein expression by immunohistochemistry (IHC) of four genes, ADAM12, FAP, SOX11, and WISP1, that were found in an earlier study to be uniquely overexpressed in AF compared with normal tissues. Digital image analysis was performed to evaluate inter- and intratumor heterogeneity, and correlate protein expression with histologic features, including a histopathologic assessment of tumor activity, defined by nuclear chromatin density ratio (CDR). AF tumors exhibited marked inter- and intratumor histologic heterogeneity. Pathologic assessment of tumor activity and digital assessment of average nuclear size and CDR were all significantly correlated. IHC revealed protein expression of all four genes. IHC staining for ADAM12, FAP, and WISP1 correlated with CDR and was higher, whereas SOX11 staining was lower in tumors with earlier recurrence following excision. All four proteins were expressed, and the regional variation in tumor activity within and among AF cases was demonstrated. A spatial correlation between protein expression and nuclear morphology was observed. IHC also correlated with the probability of recurrence following excision. These proteins may be involved in AF pathogenesis and the corresponding pathways could serve as potential targets of therapy.

Targeting CD133 in an in vivo ovarian cancer model reduces ovarian cancer progression.

OBJECTIVES: While most women with ovarian cancer will achieve complete remission after treatment, the majority will relapse within two years, highlighting the need for novel therapies. Cancer stem cells (CSC) have been identified in ovarian cancer and most other carcinomas as a small population of cells that can self-renew. CSC are more chemoresistant and radio-resistant than the bulk tumor cells; it is likely that CSC are responsible for relapse, the major problem in cancer treatment. CD133 has emerged as one of the most promising markers for CSC in ovarian cancer. The hypothesis driving this study is that despite their low numbers in ovarian cancer tumors, CSC can be eradicated using CD133 targeted therapy and tumor growth can be inhibited. METHODS: Ovarian cancer cell lines were evaluated using flow cytometry for expression of CD133. In vitro viability studies with an anti-CD133 targeted toxin were performed on one of the cell lines, NIH:OVCAR5. The drug was tested in vivo using a stably transfected luciferase-expressing NIH:OVCAR5 subline in nude mice, so that tumor growth could be monitored by digital imaging in real time. RESULTS: Ovarian cancer cell lines showed 5.6% to 16.0% CD133 expression. dCD133KDEL inhibited the in vitro growth of NIH:OVCAR5 cells. Despite low numbers of CD133-expressing cells in the tumor population, intraperitoneal drug therapy caused a selective decrease in tumor progression in intraperitoneal NIH:OVCAR5-luc tumors. CONCLUSIONS: Directly targeting CSC that are a major cause of drug resistant tumor relapse with an anti-CD133 targeted toxin shows promise for ovarian cancer therapy.

Establishment, characterization and downstream application of primary ovarian cancer cells derived from solid tumors.

Ovarian cancer is the deadliest of the gynecological diseases and the fifth cause of cancer death among American women. This is mainly due to the lack of prognostic tools capable of detecting early stages of ovarian cancer and to the high rate of resistance to the current chemotherapeutic regimens. In this scenario the overall 5-year survival rate for ovarian cancer patients diagnosed at late stage is less than 25%. Abnormalities associated with the malignant phenotype and the mechanisms of tumor progression are not clearly understood. In vitro studies are necessary, yet have been hampered due to the limitations accompanied with the use of ovarian cancer cell lines and the heterogeneity of the ovarian cancer cell population derived from ascites fluids. In this study we present a simple, rapid and reproducible method for the isolation and characterization of ovarian cancer cells from solid tumor tissue and show that enzymatic digestion for 30 minutes with dispase II results in the most effective recovery of viable epithelial ovarian cancer (EOC) cells. The resulting cancer (EOC) cell preparations demonstrate a significant yield, high levels of viability and are fibroblast-free. They grow for up to six passages and retain the capacity of forming spheroids-like structures in agarose. In addition, they can be genetically manipulated and used for drug screening, thus rendering them highly suitable for downstream applications. Notably, isolation of ovarian cancer cells from solid specimens using this method has the advantage of allowing for isolation of cancer cells from early stages of ovarian cancer as well as obtaining cells from defined either primary and/or metastatic ovarian cancer sites. Thus, these cells are highly suitable for investigations aimed at understanding ovarian cancer.

Gene expression identifies heterogeneity of metastatic propensity in high-grade soft tissue sarcomas.

BACKGROUND: Metastatic propensity of soft tissue sarcoma (STS) is heterogeneous and may be determined by gene expression patterns that do not correlate well with morphology. The authors have reported gene expression patterns that distinguish 2 broad classes of clear cell renal carcinoma (ccRCC-gene set), and other patterns that can distinguish heterogeneity of serous ovarian carcinoma (OVCA-gene set) and aggressive fibromatosis (AF-gene set); however, clinical follow-up data were not available for these samples. METHODS: In the current study, gene expression patterns in 73 samples of high-grade STS were examined using spotted cDNA microarray slides that contained ∼16,000 unique UniGene clusters. Approximately 50% of the genes present in the ccRCC-, OVCA-, and AF-gene sets were also represented in the data from this chip set, and these were combined to form a composite gene set of 278 probes. RESULTS: Hierarchical clustering using this composite gene set suggested the existence of subsets of the STS samples. Analysis revealed differences in the time to development of metastatic disease between the clusters defined by the first branch point of the clustering dendrogram (P = .005), and also among the 4 different clusters defined by the second branch points (P = .001). CONCLUSIONS: This approach suggests the existence of >2 subsets of high-grade pleomorphic STS, each with distinct clinical behavior. A composite gene set such as that described here may be useful to stratify STS in clinical trials, and may be of practical utility in patient management.

Mathematical prognostic biomarker models for treatment response and survival in epithelial ovarian cancer.

Following initial standard chemotherapy (platinum/taxol), more than 75% of those patients with advanced stage epithelial ovarian cancer (EOC) experience a recurrence. There are currently no accurate prognostic tests that, at the time of the diagnosis/surgery, can identify those patients with advanced stage EOC who will respond to chemotherapy. Using a novel mathematical theory, we have developed three prognostic biomarker models (complex mathematical functions) that-based on a global gene expression analysis of tumor tissue collected during surgery and prior to the commencement of chemotherapy-can identify with a high accuracy those patients with advanced stage EOC who will respond to the standard chemotherapy [long-term survivors (>7 yrs)] and those who will not do so [short-term survivors (<3 yrs)]. Our three prognostic biomarker models were developed with 34 subjects and validated with 20 unknown (new and different) subjects. Both the overall biomarker model sensitivity and specificity ranged from 95.83% to 100.00%. The 12 most significant genes identified, which are also the input variables to the three mathematical functions, constitute three distinct gene networks with the following functions: 1) production of cytoskeletal components, 2) cell proliferation, and 3) cell energy production. The first gene network is directly associated with the mechanism of action of anti-tubulin chemotherapeutic agents, such as taxanes and epothilones. This could have a significant impact in the discovery of new, more effective pharmacological treatments that may significantly extend the survival of patients with advanced stage EOC.