Histopathology and molecular biology of ovarian epithelial tumors

Characterization of ovarian cancer cells and tissues by Fourier transform infrared spectroscopy

Background

Ovarian cancer is the most lethal of gynecological malignancies. Fourier Transform Infrared (FTIR) spectroscopy has gradually developed as a convenient, inexpensive and non-destructive technique for the study of many diseases. In this study, FTIR spectra of normal and several heterogeneous ovarian cancer cell lines as well as ovarian cancer tissue samples were compared in the spectral region of 4000 cm^− 1 - 600 cm^− 1.

Methods

Cell samples were collected from human ovarian surface epithelial cell line (HOSEpiC) and five ovarian cancer cell lines (ES2, A2780, OVCAR3, SKOV3 and IGROV1). Validation spectra were performed on normal and cancerous tissue samples from 12 ovarian cancer patients. FTIR spectra were collected from a NICOLET iN10 MX spectrometer and the spectral data were analyzed by OMNIC 8.0 software.

Results

Spectral features discriminating malignant tissues from normal tissues were integrated by cell line data and tissue data. In particular changes in cancerous tissues, the decrease in the amount of lipids and nucleic acids were observed. Protein conformation and composition were also altered in some cancer cells. The band intensity ratio of 1454/1400 was higher in normal cells/tissues and lower in cancer cells/tissues.

Conclusion

The spectral features revealed the important molecular characteristics about ovarian cancer cells/tissues. These findings demonstrate the possible diagnostic use of FTIR spectroscopy, providing the research model and evidences, and supporting the future study on more tissue samples to establish a data bank of spectra features for the possible discrimination of ovarian cancers.

Histotype-specific copy-number alterations in ovarian cancer

Background

Epithelial ovarian cancer is characterized by multiple genomic alterations; most are passenger alterations which do not confer tumor growth. Like many cancers, it is a heterogeneous disease and can be broadly categorized into 4 main histotypes of clear cell, endometrioid, mucinous, and serous. To date, histotype-specific copy number alterations have been difficult to elucidate. The difficulty lies in having sufficient sample size in each histotype for statistical analyses.

Methods

To dissect the heterogeneity of ovarian cancer and identify histotype-specific alterations, we used an in silico hypothesis-driven approach on multiple datasets of epithelial ovarian cancer.

Results

In concordance with previous studies on global copy number alterations landscape, the study showed similar alterations. However, when the landscape was de-convoluted into histotypes, distinct alterations were observed. We report here significant histotype-specific copy number alterations in ovarian cancer and showed that there is genomic diversity amongst the histotypes. 76 cancer genes were found to be significantly altered with several as potential copy number drivers, including ERBB2 in mucinous, and TPM3 in endometrioid histotypes. ERBB2 was found to have preferential alterations, where it was amplified in mucinous (28.6%) but deleted in serous tumors (15.1%). Validation of ERBB2 expression showed significant correlation with microarray data (p=0.007). There also appeared to be reciprocal relationship between KRAS mutation and copy number alterations. In mucinous tumors where KRAS mutation is common, the gene was not significantly altered. However, KRAS was significantly amplified in serous tumors where mutations are rare in high grade tumors.

Conclusions

The study demonstrates that the copy number landscape is specific to the histotypes and identification of these alterations can pave the way for targeted drug therapy specific to the histotypes.

Identification of novel epithelial ovarian cancer biomarkers by cross-laboratory microarray analysis

The purpose of this study was to pool information in epithelial ovarian cancer by combining studies using Affymetrix expression microarray datasets made at different laboratories to identify novel biomarkers. Epithelial microarray expression information across laboratories was screened and combined after preprocessing raw microarray data, then ANOVA and unpaired T test statistical analysis was performed for identifying differentially expressed genes (DEGs), followed by clustering and pathway analysis for these DEGs. In this work, we performed a combination analysis on microarrays from three different laboratories using gene expression data on ovarian cancer and obtained a list of differential expression profiles identified as potential candidate in aggressiveness of ovarian cancer. The clustering and pathway analysis explored the different molecular basis of different ovarian cancer stages and potential important regulatory pathways in ovarian cancer development. Our results showed that combination of microarray data from different laboratories in the same platforms may overcome biases derived from probe design and technical features, thereby accelerating the identification of trustworthy DEGs, and demonstrating the advantage of integrative analysis in gene expression studies on epithelial ovarian cancer research.

Predictive and prognostic protein biomarkers in epithelial ovarian cancer: recommendation for future studies

Epithelial ovarian cancer is the most lethal gynecological malignancy. Due to its lack of symptoms, this disease is diagnosed at an advanced stage when the cancer has already spread to secondary sites. While initial rates of response to first treatment is >80%, the overall survival rate of patients is extremely low, mainly due to development of drug resistance. To date, there are no reliable clinical factors that can properly stratify patients for suitable chemotherapy strategies. Clinical parameters such as disease stage, tumor grade and residual disease, although helpful in the management of patients after their initial surgery to establish the first line of treatment, are not efficient enough. Accordingly, reliable markers that are independent and complementary to clinical parameters are needed for a better management of these patients. For several years, efforts to identify prognostic factors have focused on molecular markers, with a large number having been investigated. This review aims to present a summary of the recent advances in the identification of molecular biomarkers in ovarian cancer patient tissues, as well as an overview of the need and importance of molecular markers for personalized medicine in ovarian cancer.

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.

Serous and mucinous borderline (low malignant potential) tumors of the ovary

The prognosis for stage I serous borderline ovarian tumors (SBOTs) is thought to be excellent, despite rare, late recurrences. The behavior of advanced-stage SBOTs primarily depends on the invasiveness vs noninvasiveness of associated extraovarian implants. Pelvic and abdominal lymph node involvement and foci of microinvasion do not seem to adversely affect prognosis. Serous tumors with a micropapillary and/or cribriform growth pattern seem to be more frequently bilateral and exophytic and manifest at an advanced stage with a higher incidence of invasive implants than typical SBOTs. Molecular data suggest that such tumors may represent an intermediate stage in the typical SBOT-invasive low-grade serous carcinoma progression. Limited experience with endocervical (müllerian)-type mucinous borderline tumors shows a possible relation to SBOTs in clinicopathologic features and biologic behavior Intestinal-type mucinous borderline ovarian tumors (I-MBOTs) and well-differentiated mucinous carcinomas manifest at stage I in most cases; the prognosis is excellent. Mucinous tumors associated with pseudomyxoma peritonei are almost always secondary to similar tumors of the appendix or other gastrointestinal sites and should not be diagnosed as high-stage I-MBOTs. Rare primary ovarian mucinous tumors associated with pseudomyxoma peritonei are those arising in mature cystic teratomas. Advanced-stage ovarian mucinous carcinomas typically show frank, infiltrative-type invasion; the prognosis is poor.

Overexpression of cyclin D1 and c-Myc gene products in human primary epithelial ovarian cancer

Cyclin D1 and c-Myc are key participants in the cell-cycle pathway, in which aberrancies have been associated with malignant transformation. To date, data on the relationship of expression of these proteins and histologic subtype of epithelial ovarian cancer are still scarce and discordant. Immunohistochemical analysis was performed on 12 normal ovaries and 47 cases of serous, mucinous, endometrioid, and clear cell ovarian carcinomas. No abnormal expression of cyclin D1 or c-Myc was demonstrated in any of the 12 normal ovarian specimens. However, compared to normal ovarian tissues, overexpression of cyclin D1 and c-Myc was observed in 42.6% (20/47) and 65.9% (31/47) of tumors examined, respectively. There was no significant difference of overexpression of cyclin D1 or c-Myc gene products between these four histologic subtypes of ovarian adenocarcinomas. This study shows that cyclin D1 and c-Myc are frequently overexpressed in epithelial ovarian carcinomas, but they are not correlated with a particular histologic subtype. Although our preliminary results need to be validated in a larger number of tumors, the abnormal expression of cyclin D1 and c-Myc in epithelial ovarian cancer reaffirms the notion that they are crucial components in the pathway of tumorigenesis and deserve further study.

The role of CD24 in various human epithelial neoplasias

CD24 is a small, heavily glycosylated glycosylphosphatidylinositol-linked cell surface protein, which is expressed in hematologic malignancies and in a large variety of solid tumors. It appears to function as a ligand of P-selectin, an adhesion molecule present in activated platelets and endothelial cells. The authors aimed at evaluating CD24 protein expression in adenoma and adenocarcinoma of the stomach, colon, gallbladder, ovary, and breast to establish a correlation with clinicopathologic data. Staining was evaluated using four degrees of positivity (negative, weakly, moderately, strongly positive), and the staining patterns (membranous vs. intracytoplasmic) were analyzed for statistical analysis. The present study clearly demonstrates that CD24 is abundantly expressed in adenocarcinoma compared to adenoma of the colon and breast. Moreover, the positivity degree of CD24 expression increases with positive nodal status in advanced gastric carcinoma. Intracytoplasmic CD24 expression was found to be highly associated with adenocarcinoma of the colon, gallbladder, and ovary compared to the adenoma group of those organs, and with the positive nodal status compared to the negative nodal status of the colonic adenocarcinoma. We conclude that the degree of positivity and the staining pattern of CD24 constitute an important molecular marker for various epithelial neoplasms, which could help to define malignant transformation and to predict lymph node metastasis.

cDNA microarray analysis of vestibular schwannomas

BACKGROUND

Vestibular schwannomas are known to harbor mutations in the neurofibromatosis type 2 tumor suppressor gene, but the mechanism of the neurofibromatosis type 2 tumor suppressor gene action is not well understood. Identification of genes differentially expressed in normal and diseased tissues through the use of a large-scale, cDNA microarray approach may lead to increased understanding of pathways that lead to tumor formation.

OBJECTIVE

The objectives of this study were to evaluate the gene expression profiles in vestibular schwannomas in comparison with normal vestibular nerve tissues and to identify pathways that may be altered in schwannomas.

METHODS

Total RNA was extracted from one normal vestibular nerve and seven vestibular schwannomas. The normal vestibular nerve was from one of the seven patients with small vestibular schwannomas. Radiolabeled cDNA was synthesized and hybridized to cDNA microarray filters that contained 25,920 known genes or expressed sequence tags. Expression profiles were imaged and analyzed. Selected genes that showed three-fold or greater difference in the intensity between the normal nerve and the schwannomas were further examined by real-time polymerase chain reaction and by immunohistochemical staining.

RESULTS

Forty-two genes (0.2%) were upregulated 3-fold or more in at least 5 of the 7 tumors when the filter images were compared with a normal adjacent vestibular nerve. Among them, osteonectin, an angiogenesis mediator, and RhoB GTPase, which is important in cell signaling, were significantly upregulated in 5 of 7 tumors. Among genes that were downregulated, an apoptosis-related LUCA-15 gene was highly underexpressed in 6 of 7 schwannomas when compared with the normal nerve. Also, ezrin, a relative of the NF2 protein, was significantly downregulated in 5 of 7 tumors. Real-time PCR and immunohistochemistry data support the cDNA microarray findings.

CONCLUSION

Our cDNA microarray analysis of schwannomas suggested several interesting and potentially important tumorigenesis pathways associated with vestibular schwannoma formation. Further in vivo study is necessary to define the roles of these identified genes and their potential relationships with the neurofibromatosis type 2 tumor suppressor gene.

Monitoring gene expression profile changes in bladder transitional cell carcinoma using cDNA microarray

PURPOSE

Differential gene expression profiles between normal bladder mucosas and bladder transitional cell carcinomas TCC were detected.

MATERIALS AND METHODS

cDNA microarrays were prepared by spotting PCR products of 12,800 human genes onto specially treated glass slides. The cDNA probes were prepared by labeling normal bladder mucosa mRNA and TCC tissue mRNA with Cy3-dUTP and Cy5-dUTP respectively through reverse transcription. The arrays were then hybridized against the cDNA probe mixture and the fluorescent signals were scanned. The ratios of Cy5/Cy3 were computed. Northern analysis was used to confirm the results of microarray hybridization.

RESULTS

Eighty-three genes (0.65%), whose ratios of Cy5/Cy3 were greater than 4.0 or less than 0.25, were screened out after 10 groups of hybridization. In the cancerous tissues 28 of them showed higher expression and 55 lower. Twenty-three genes are unregistered in GenBank. These differentially expressed genes are always involved in the physiological processes such as signal transduction, apoptosis and cell cycle, etc.

CONCLUSIONS

This technique provides a powerful method for quantitative analysis of the expression levels of thousands of genes in parallel, and is used to identify genes involved in TCC carcinogenesis. The data obtained by this means are comparable to those obtained by other methods. Using cDNA microarrays to define alterations in gene expression associated with a specific cancer may be an efficient way to uncover the clues to specific molecular derangements that account for its pathogenesis and thus identify potential targets for therapeutic intervention.

Analysis of gene expression profiles in normal and neoplastic ovarian tissue samples identifies candidate molecular markers of epithelial ovarian cancer

Epithelial ovarian cancer is the leading cause of death from gynecologic cancer, in part because of the lack of effective early detection methods. Although alterations of several genes, such as c-erb-B2, c-myc, and p53, have been identified in a significant fraction of ovarian cancers, none of these mutations are diagnostic of malignancy or predictive of tumor behavior over time. Here, we used oligonucleotide microarrays with probe sets complementary to >6,000 human genes to identify genes whose expression correlated with epithelial ovarian cancer. We extended current microarray technology by simultaneously hybridizing ovarian RNA samples in a highly parallel manner to a single glass wafer containing 49 individual oligonucleotide arrays separated by gaskets within a custom-built chamber (termed "array-of-arrays"). Hierarchical clustering of the expression data revealed distinct groups of samples. Normal tissues were readily distinguished from tumor tissues, and tumors could be further subdivided into major groupings that correlated both to histological and clinical observations, as well as cell type-specific gene expression. A metric was devised to identify genes whose expression could be considered ideal for molecular determination of epithelial ovarian malignancies. The list of genes generated by this method was highly enriched for known markers of several epithelial malignancies, including ovarian cancer. This study demonstrates the rapidity with which large amounts of expression data can be generated. The results highlight important molecular features of human ovarian cancer and identify new genes as candidate molecular markers.