Cécile Le Page

Tissue array analysis of expression microarray candidates identifies markers associated with tumor grade and outcome in serous epithelial ovarian cancer

Molecular profiling is a powerful approach to identify potential clinical markers for diagnosis and prognosis as well as providing a better understanding of the biology of epithelial ovarian cancer. On the basis of the analysis of HuFL expression data, we have previously identified genes that distinguish low malignant potential and invasive serous epithelial ovarian tumors. In this study, we used immunohistochemistry to monitor a subset of differently expressed candidates (Ahr, Paep, Madh3, Ran, Met, Mek1, Ccne1, Ccd20, Cks1 and Cas). A tissue array composed of 244 serous tumors of different grades (0–3) and stages (I–IV) was used in this analysis. All markers assayed presented differential protein expression between serous tumors of low and high grade. Significant differences in Ccne1 and Ran expression were observed in a comparison of low malignant potential and grade 1 tumor samples (p < 0.01). In addition, irrespective of the grade, Ccne1, Ran, Cdc20 and Cks1 showed significant differences of expression in association with the clinical stage of disease. While high level of Ccne1 have previously been associated with poor outcomes, here we found that high level of either Ran or Cdc20 appear to be more tightly associated with a poor prognosis (p < 0.001, 0.03, respectively). The application of these biomarkers in both the initial diagnosis and prognostic attributes of patients with epithelial ovarian tumors should prove to be useful in patient management.

Expression and Nuclear Localization of ErbB3 in Prostate Cancer

Purpose: The ErbB1 and ErbB2 receptors have been implicated in prostate cancer progression, but less is known about the role and biology of other ErbB receptor family members in prostate cancer. The aim of this study was to analyze the expression and localization of ErbB3 in prostate tissues and prostate cancer cell lines. Experimental Design: Immunohistochemistry of ErbB3 was done on prostate cancer tissue sections from 143 patients and on a tissue microarray containing 390 cores of radical prostatectomy-derived specimens representing normal, prostatic intraepithelial neoplasia, and malignant tissues from 81 patients. ErbB3 subcellular localization was studied by Western blot analysis in LNCaP, 22Rv1, PC-3, and DU145 prostate cancer cell lines. Results: Immunohistochemistry analysis of prostate cancer tissues revealed that >90% of prostate cancer tissues displayed cytoplasmic ErbB3 staining. Minimal ErbB3 nuclear staining was observed in normal prostate tissues and benign prostatic hyperplasia tissues; in contrast, ErbB3 was frequently localized in the nucleus of cancerous tissues. This nuclear localization was more frequent (P < 0.001) in hormone-refractory tissues (17 of 17, 100%) compared with hormone-sensitive samples (37 of 92, 40.2%). Additionally, in the tissue microarray, increased nuclear ErbB3 was associated with increasing Gleason grade. Interestingly, Western blot analysis of cytoplasmic and nuclear subcellular fractions showed that ErbB3 nuclear localization was more prevalent in hormone-sensitive prostate cancer cell lines (LNCaP and 22Rv1) compared with hormone-insensitive cell lines (PC-3 and DU145). Conclusions: ErbB3 nuclear localization discriminates normal from malignant prostate tissues and between tumors from hormone-sensitive versus hormone-refractory prostate cancer. ErbB3 nuclear staining seems to be associated with risk of disease progression. The high frequency of ErbB3 nuclear localization in hormone-refractory tissues indicates that ErbB3 warrants further study to understand its association with prostate cancer disease progression.

CD73 Is Associated with Poor Prognosis in High-Grade Serous Ovarian Cancer

The cell surface nucleotidase CD73 is an immunosuppressive enzyme involved in tumor progression and metastasis. Although preclinical studies suggest that CD73 can be targeted for cancer treatment, the clinical impact of CD73 in ovarian cancer remains unclear. In this study, we investigated the prognostic value of CD73 in high-grade serous (HGS) ovarian cancer using gene and protein expression analyses. Our results demonstrate that high levels of CD73 are significantly associated with shorter disease-free survival and overall survival in patients with HGS ovarian cancer. Furthermore, high levels of CD73 expression in ovarian tumor cells abolished the good prognosis associated with intraepithelial CD8(+) cells. Notably, CD73 gene expression was highest in the C1/stromal molecular subtype of HGS ovarian cancer and positively correlated with an epithelial-to-mesenchymal transition gene signature. Moreover, in vitro studies revealed that CD73 and extracellular adenosine enhance ovarian tumor cell growth as well as expression of antiapoptotic BCL-2 family members. Finally, in vivo coinjection of ID8 mouse ovarian tumor cells with mouse embryonic fibroblasts showed that CD73 expression in fibroblasts promotes tumor immune escape and thereby tumor growth. In conclusion, our study highlights a role for CD73 as a prognostic marker of patient survival and also as a candidate therapeutic target in HGS ovarian cancers.

Discrimination between serous low malignant potential and invasive epithelial ovarian tumors using molecular profiling

Tumors of low malignant potential (LMP) represent 20% of epithelial ovarian cancers (EOCs) and are associated with a better prognosis than the invasive tumors (TOV). Defining the relationship between LMPs and TOVs remains an important goal towards understanding the molecular pathways that contribute to prognosis, as well as providing molecular markers, for these EOCs. To this end, DNA microarray analyses were performed either in a primary culture or a tumor tissue model system and selected candidate genes showing a distinctive expression profile between LMPs and TOVs were identified using a class prediction approach based on three statistical methods of analysis. Both model systems appear relevant as candidate genes identified by either model allowed the proper reclassification of samples as either LMPs or TOVs. Selected candidate genes (CAS, CCNE1, LGALS8, ITGβ3, ATP1B1, FLIP, KRT7 and KRT19) were validated by real-time quantitative PCR analysis and show differential expression between LMPs and TOVs. Immunohistochemistry analyses showed that the two tumor classes were distinguishable by their expression of CAS, TNFR1A, FLIP, CKS1 and CCNE1. These results define signature patterns for gene expression of LMPs and TOVs and identify gene candidates that warrant further study to deepen our understanding of the biology of EOC.

BMP-2 signaling in ovarian cancer and its association with poor prognosis

BackgroundWe previously observed the over-expression of BMP-2 in primary cultures of epithelial ovarian cancer (EOC) cells as compared to normal epithelial cells based on Affymetrix microarray profiling [1]. Here we investigate the effect of BMP-2 on several parameters of ovarian cancer tumorigenesis using the TOV-2223, TOV-1946 and TOV-112D EOC cell lines.MethodsWe treated each EOC cell line with recombinant BMP-2 and assayed various parameters associated with tumorigenesis. More specifically, cell signaling events induced by BMP-2 treatment were investigated by western-blot using anti-phosphospecific antibodies. Induction of Id1, Snail and Smad6 mRNA expression was investigated by real time RT-PCR. The ability of cells to migrate was tested using the scratch assay. Cell-cell adhesion was analyzed by the ability of cells to form spheroids. We also investigated BMP-2 expression in tissue samples from a series of EOC patients.ResultsTreatment of these cell lines with recombinant BMP-2 induced a rapid phosphorylation of Smad1/5/8 and Erk MAPKs. Increased expression of Id1, Smad6 and Snail mRNAs was also observed. Only in the TOV-2223 cell line were these signaling events accompanied by an alteration in cell proliferation. We also observed that BMP-2 efficiently increased the motility of all three cell lines. In contrast, BMP-2 treatment decreased the ability of TOV-1946 and TOV-112D cell lines to form spheroids indicating an inhibition of cell-cell adhesion. The expression of BMP-2 in tumor tissues from patients was inversely correlated with survival.ConclusionThese results suggest that EOC cell secretion of BMP-2 in the tumor environment contributes to a modification of tumor cell behavior through a change in motility and adherence. We also show that BMP-2 expression in tumor tissues is associated with a poorer prognosis for ovarian cancer patients.

From gene profiling to diagnostic markers: IL-18 and FGF-2 complement CA125 as serum-based markers in epithelial ovarian cancer.

We used an oligonucleotide‐based DNA microarray to identify potential markers in 39 primary cultures of ovarian cancer specimens compared with 11 primary cultures of normal ovarian epithelia. Differential gene expression of IL‐18 and FGF‐2 was validated on a subset of samples by quantitative PCR and by IHC, using an independent tissue array of 90 cores of 20 normal ovarian surface epithelia and 70 EOCs representing different grades and pathologies of ovarian disease. We further compared, by ELISA, these two markers with CA125 in sera from 25 cancer‐free and 47 ovarian cancer patients. IL‐18 and FGF‐2 proteins were significantly elevated in tumor tissues (p<0.04) and sera (p<0.05) from patients with ovarian cancer. In combination, the three markers (IL‐18, FGF‐2, and CA125) showed similar sensitivity in scoring for ovarian cancer (35/45 patients) compared to that of CA125 alone (37/45) and significantly improved the specificity of detection (20/25 patients) compared to each marker individually (15/25 for CA125; 18/25 FGF‐2; 16/25 for IL‐18). In conclusion we show that a combination of the three serum markers (IL‐18, FGF‐2 and CA125) is associated with EOC, with higher specificity than CA125 alone. Prospective studies with a large cohort of susceptible ovarian cancer patients will be required to expand these findings.

SET complex in serous epithelial ovarian cancer

With low cure rates but increasing diverse treatment options that provide variable remission times, ovarian cancer is increasingly being recognized as a chronic disease. This reality indicates the need for a better understanding of factors influencing disease progression. In a previous global analysis of gene expression, we identified genes differentially expressed when comparing serous epithelial ovarian tumors of low and high malignant potential (grade 0 vs grade 3). In this analysis, 4 out of 5 members of the SET complex, SET, APE1, NM23 and HMGB2, were highly expressed in invasive grade 3 tumors. To further investigate the expression of these genes and the fifth member of the SET complex (pp32), we performed immunohistochemistry, on a tissue array composed of 235 serous tumors of different grades and disease stages. A significant correlation between expression of all SET complex proteins and the tumor differentiation was observed (p < 0.05). When combining all tumors, overexpression of Nm23 (p = 0.04), Set (p = 0.004) and Ape1 (p = 0.004) was associated with the clinical stage of the disease. No marker by itself was associated with prognosis. The combination of a high level of Nm23 in the context of a low level of Set compared to all other combinations of these markers did confer a better prognosis (p = 0.03). When combined, high expression of Hmgb2 and low expression of Ape1 was also associated with patient prognosis (p = 0.05). These findings suggest that a strategy that sums the activities of different partners within a pathway may be more appropriate in designing nomograms for patient stratification.

Proteome profiling of human epithelial ovarian cancer cell line TOV-112D

A proteome profiling of the epithelial ovarian cancer cell line TOV-112D was initiated as a protein expression reference in the study of ovarian cancer. Two complementary proteomic approaches were used in order to maximise protein identification: two-dimensional gel electrophoresis (2DE) protein separation coupled to matrix assisted laser desorption/ionisation time-of-flight mass spectrometry (MALDI-TOF MS) and one-dimensional gel electrophoresis (1DE) coupled to liquid-chromatography tandem mass spectrometry (LC MS/MS). One hundred and seventy-two proteins have been identified among 288 spots selected on two-dimensional gels and a total of 579 proteins were identified with the 1DE LC MS/MS approach. This proteome profiling covers a wide range of protein expression and identifies several proteins known for their oncogenic properties. Bioinformatics tools were used to mine databases in order to determine whether the identified proteins have previously been implicated in pathways associated with carcinogenesis or cell proliferation. Indeed, several of the proteins have been reported to be specific ovarian cancer markers while others are common to many tumorigenic tissues or proliferating cells. The diversity of proteins found and their association with known oncogenic pathways validate this proteomic approach. The proteome 2D map of the TOV-112D cell line will provide a valuable resource in studies on differential protein expression of human ovarian carcinomas while the 1DE LC MS/MS approach gives a picture of the actual protein profile of the TOV-112D cell line. This work represents one of the most complete ovarian protein expression analysis reports to date and the first comparative study of gene expression profiling and proteomic patterns in ovarian cancer.

BTN3A2 Expression in Epithelial Ovarian Cancer Is Associated with Higher Tumor Infiltrating T Cells and a Better Prognosis

BTN3A2/BT3.2 butyrophilin mRNA expression by tumoral cells was previously identified as a prognostic factor in a small cohort of high grade serous epithelial ovarian cancer (HG-EOC). Here, we evaluated the prognostic value of BT3.2 at the protein level in specimen from 199 HG-EOC patients. As the only known role of butyrophilin proteins is in immune regulation, we evaluated the association between BT3.2 expression and intratumoral infiltration of immune cells by immunohistochemistry with specific antibodies against BT3.2, CD3, CD4, CD8, CD20, CD68 and CD206. Epithelial BT3.2 expression was significantly associated with longer overall survival and lower risk of disease progression (HR = 0.651, p = 0.006 and HR = 0.642, p = 0.002, respectively) and significantly associated with a higher density of infiltrating T cells, particularly CD4+ cells (0.272, p<0.001). We also observed a strong association between the relative density of CD206+ cells, as evaluated by the ratio of intratumoral CD206+/CD68+ expression, and risk of disease progression (HR = 1.355 p = 0.044, respectively). In conclusion, BT3.2 protein is a potential prognostic biomarker for the identification of HG-EOC patients with better outcome. In contrast, high CD206+/CD68+ expression is associated with high risk of disease progression. While the role of BT3.2 is still unknown, our result suggest that BT3.2 expression by epithelial cells may modulates the intratumoral infiltration of immune cells.

An Immunohistochemical Algorithm for Ovarian Carcinoma Typing.

There are 5 major histotypes of ovarian carcinomas. Diagnostic typing criteria have evolved over time, and past cohorts may be misclassified by current standards. Our objective was to reclassify the recently assembled Canadian Ovarian Experimental Unified Resource and the Alberta Ovarian Tumor Type cohorts using immunohistochemical (IHC) biomarkers and to develop an IHC algorithm for ovarian carcinoma histotyping. A total of 1626 ovarian carcinoma samples from the Canadian Ovarian Experimental Unified Resource and the Alberta Ovarian Tumor Type were subjected to a reclassification by comparing the original with the predicted histotype. Histotype prediction was derived from a nominal logistic regression modeling using a previously reclassified cohort (N=784) with the binary input of 8 IHC markers. Cases with discordant original or predicted histotypes were subjected to arbitration. After reclassification, 1762 cases from all cohorts were subjected to prediction models (&khgr;2 Automatic Interaction Detection, recursive partitioning, and nominal logistic regression) with a variable IHC marker input. The histologic type was confirmed in 1521/1626 (93.5%) cases of the Canadian Ovarian Experimental Unified Resource and the Alberta Ovarian Tumor Type cohorts. The highest misclassification occurred in the endometrioid type, where most of the changes involved reclassification from endometrioid to high-grade serous carcinoma, which was additionally supported by mutational data and outcome. Using the reclassified histotype as the endpoint, a 4-marker prediction model correctly classified 88%, a 6-marker 91%, and an 8-marker 93% of the 1762 cases. This study provides statistically validated, inexpensive IHC algorithms, which have versatile applications in research, clinical practice, and clinical trials.