paywalled: Meta-analysis of gene expression profiles associated with histological classification and survival in 829 ovarian cancer samples - International Journal of Cancer

Meta-analysis of gene expression profiles associated with histological classification and survival in 829 ovarian cancer samples - Fekete - 2011 - International Journal of Cancer

Abstract

Transcriptomic analysis of global gene expression in ovarian carcinoma can identify dysregulated genes capable to serve as molecular markers for histology subtypes and survival. The aim of our study was to validate previous candidate signatures in an independent setting and to identify single genes capable to serve as biomarkers for ovarian cancer progression. As several datasets are available in the GEO today, we were able to perform a true meta-analysis. First, 829 samples (11 datasets) were downloaded, and the predictive power of 16 previously published gene sets was assessed. Of these, eight were capable to discriminate histology subtypes, and none was capable to predict survival. To overcome the differences in previous studies, we used the 829 samples to identify new predictors. Then, we collected 64 ovarian cancer samples (median relapse-free survival 24.5 months) and performed TaqMan Real Time Polimerase Chain Reaction (RT-PCR) analysis for the best 40 genes associated with histology subtypes and survival. Over 90% of subtype-associated genes were confirmed. Overall survival was effectively predicted by hormone receptors (PGR and ESR2) and by TSPAN8. Relapse-free survival was predicted by MAPT and SNCG. In summary, we successfully validated several gene sets in a meta-analysis in large datasets of ovarian samples. Additionally, several individual genes identified were validated in a clinical cohort.

A snapshot of microarray-generated gene expression signatures associated with ovarian carcinoma

A snapshot of microarray-generated gene expression signatures associated with ovarian carcinoma:

Abstract

It was hypothesized that analysis of global gene expression in ovarian carcinoma can identify dysregulated genes that can serve as molecular markers and provide further insight into carcinogenesis and provide the basis for development of new diagnostic tools as well as new targeted therapy protocols................From these genes, merely three were identified in at least two different studies. This snapshot of available gene expression data not only provides independently described potential diagnostic and therapeutic targets for ovarian carcinoma but also emphasizes the drawbacks of the current state of global gene expression analyses in ovarian cancer.

open access: PLoS ONE: March 29th Integrated Analyses of microRNAs Demonstrate Their Widespread Influence on Gene Expression in High-Grade Serous Ovarian Carcinoma

PLoS ONE: Integrated Analyses of microRNAs Demonstrate Their Widespread Influence on Gene Expression in High-Grade Serous Ovarian Carcinoma

Background

The Cancer Genome Atlas (TCGA) Network recently comprehensively catalogued the molecular aberrations in 487 high-grade serous ovarian cancers, with much remaining to be elucidated regarding the microRNAs (miRNAs). Here, using TCGA ovarian data, we surveyed the miRNAs, in the context of their predicted gene targets.

Conclusions

This study establishes miRNAs as having a widespread impact on gene expression programs in ovarian cancer, further strengthening our understanding of miRNA biology as it applies to human cancer. As with gene transcripts, miRNAs exhibit high diversity reflecting the genomic heterogeneity within a clinically homogeneous disease population. Putative miRNA:mRNA interactions, as identified using integrative analysis, can be validated. TCGA data are a valuable resource for the identification of novel tumor suppressive miRNAs in ovarian as well as other cancers.

open access - PLoS ONE: Identification of a Potential Ovarian Cancer Stem Cell Gene Expression Profile from Advanced Stage Papillary Serous Ovarian Cancer

"...We propose the side population of ascites from women with high-grade advanced stage papillary serous ovarian adenocarcinoma would be enriched for cancer stem-like cells, and would express a gene signature trend for “stemness” in ovarian cancer stem-like cells...."

"Ethics Statement
Fresh ascites was obtained from 10 women with high-grade advanced stage ovarian adenocarcinoma at the time of primary cytoreductive surgery at Brigham and Women's Hospital, Boston, MA......

".....In summary, an expression profile for SP enriched for cancer stem-like cells from ascites of ovarian cancer patients is reported. The nature of the “stemness” of the SP gene signature was demonstrated by the identification of several stem cell-related genes including an activated Notch signaling pathway. The results were biologically validated using identified SP population from human ovarian cancer cell lines. The SP gene list generated from ovarian cancer patients was also found to be enriched in recurrent tumors from ovarian cancer patients. These results have important implications concerning the tumor recurrence and potential therapeutic approach. The SP cells showed a dose dependent sensitivity towards Notch pathway inhibitor, suggests the Notch signaling pathway may be an important therapeutic target in ovarian cancer."

Prognostic significance of L1CAM in (serous) ovarian cancer and its role in constitutive NF-κB activation

Conclusions:
L1CAM expression contributes to the invasive and metastatic phenotype of serous ovarian carcinoma. L1CAM expression and shedding in the tumor microenvironment could contribute to enhanced invasion and tumor progression through increased IL-1β production and NF-κB activation.

Dec 2011: Journal of Ovarian Research Gene Expression and Pathway Analysis of Ovarian Cancer Cells Selected for Resistance to Cisplatin, Paclitaxel, or Doxorubicin

Background

Resistance to current chemotherapeutic agents is a major cause of therapy failure in ovarian cancer patients, but the exact mechanisms leading to the development of drug resistance remain unclear. 

Results

A total of 845 genes (p<0.01) were found altered in at least one drug resistance phenotype when compared to the parental, drug sensitive cell line.......

Conclusions

Ovarian cancer cells develop drug resistance through different pathways depending on the drug used in the generation of chemoresistance. A better understanding of these mechanisms may lead to the development of novel strategies to circumvent the problem of drug resistance.

The complete article is available as a provisional PDF. The fully formatted PDF and HTML versions are in production.

abstract: Meta-analysis of gene expression profiles associated with histological classification and survival in 829 ovarian cancer samples

abstract: Mutation and Loss of Expression of ARID1A in Uterine Low-grade Endometrioid Carcinoma

Abstract:

ARID1A is a recently identified tumor suppressor gene that is mutated in approximately 50% of ovarian clear cell and 30% of ovarian endometrioid carcinomas. The mutation is associated with loss of protein expression as assessed by immunohistochemistry.

In this study, we evaluated ARID1A immunoreactivity in a wide variety of carcinomas to determine the prevalence of ARID1A inactivation in carcinomas. Mutational analysis of ARID1A was carried out in selected cases. Immunoreactivity was not detected (corresponding to inactivation or mutation of ARID1A) in 36 (3.6%) of 995 tumors.

Uterine low-grade endometrioid carcinomas showed a relatively high-frequency loss of ARID1A expression, as 15 (26%) of 58 cases were negative. The other tumor that had a relatively high-frequency loss of ARID1A expression was gastric carcinoma (11%). Mutational analysis showed 10 (40%) of 25 uterine endometrioid carcinomas; none of 12 uterine serous carcinomas and none of 56 ovarian serous and mucinous carcinomas harbored somatic ARID1A mutations. All mutations in endometrioid carcinomas were nonsense or insertion/deletion mutations, and tumors with ARID1A mutations showed complete loss or clonal loss of ARID1A expression.

In conclusion, this study is the first large-scale analysis of a wide variety of carcinomas showing that uterine low-grade endometrioid carcinoma is the predominant tumor type harboring ARID1A mutations and frequent loss of ARID1A expression. These findings suggest that the molecular pathogenesis of low-grade uterine endometrioid carcinoma is similar to that of ovarian low-grade endometrioid and clear cell carcinoma, tumors that have previously been shown to have a high-frequency loss of expression and mutation of ARID1A.

full free access: PLoS ONE: Comparison of Expression Profiles in Ovarian Epithelium In Vivo and Ovarian Cancer Identifies Novel Candidate Genes Involved in Disease Pathogenesis (Mar 15/2011)

Note: research/technical/primary focus on serous cell type

Breast cancer classification algorithm to identify 20 gene signature developed using Microsoft Excel

"....The 10 most highly ranked genes predictive of poor prognosis and those 10 genes most highly predictive of good prognosis established a 20-gene expression based predictor, which was found to perform as well as two other models in the validation group. According to Hassell, "Our algorithm produces prediction models with comparable accuracy to other feature selection techniques while having generally better accessibility and useability for biological research scientists. We've begun using our algorithm to generate gene expression based prediction models of breast cancer cell sensitivity to commonly used anti-cancer therapies"....cont'd

Gene Expression Profile of BRCAness That Correlates With Responsiveness to Chemotherapy and With Outcome in Patients With Epithelial Ovarian Cancer -- Konstantinopoulos et al., 10.1200/JCO.2009.27.5719 -- Journal of Clinical Oncology

In Research: Gene Expression Profile for Predicting Survival in Advanced-Stage Serous Ovarian Cancer Across Two Independent Datasets (Japan)

In Research: 

Introduction:
Patients with advanced-stage ovarian cancer generally undergo primary debulking surgery followed by platinum/taxane-based chemotherapy. Although postoperative introduction of taxane drug has improved the 5-year survival rate for advanced-stage ovarian cancer..... Clinicopathological characteristics, such as debulking status after primary surgery, are clinically considered important indicators of prognosis. However, recurrence after optimal debulking surgery occurs in some patients, while disease-free status after incomplete surgery is maintained in others......Therefore, these clinicopathological factors alone are insufficient for predicting prognosis and elucidating the pathological mechanisms of disease progression or recurrence. Molecular biology approaches can be used to identify new prognosis-related profiles leading to elucidation of pathological issues of advanced-stage serous ovarian cancer.

Meanwhile, there are no microarray kits for clinical diagnosis and management in patients with ovarian cancer yet."