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

Blood Plasma Small Non-Coding RNAs as Diagnostic Molecules for the Progesterone-Receptor-Negative Phenotype of Serous Ovarian Tumors

The expression level of the progesterone receptor (PGR) plays a crucial role in determining the biological characteristics of serous ovarian carcinoma. Low PGR expression is associated with chemoresistance and a poorer outcome. In this study, our objective was to explore the relationship between tumor progesterone receptor levels and RNA profiles (miRNAs, piwiRNAs, and mRNAs) to understand their biological characteristics and behavior. To achieve this, we employed next-generation sequencing of small non-coding RNAs, quantitative RT-PCR, and immunohistochemistry to analyze both FFPE and frozen tumor samples, as well as blood plasma from patients with benign cystadenoma (BSC), serous borderline tumor (SBT), low-grade serous ovarian carcinoma (LGSOC), and high-grade serous ovarian carcinoma (HGSOC). Our findings revealed significant upregulation of MMP7 and MUC16, along with downregulation of PGR, in LGSOC and HGSOC compared to BSC. We observed significant correlations of PGR expression levels in tumor tissue with the contents of miR-199a-5p, miR-214-3p, miR-424-3p, miR-424-5p, and miR-125b-5p, which potentially target MUC16, MMP7, and MMP9, as well as with the tissue content of miR-16-5p, miR-17-5p, miR-20a-5p, and miR-93-5p, which are associated with the epithelial-mesenchymal transition (EMT) of cells. The levels of EMT-associated miRNAs were significantly correlated with the content of hsa_piR_022437, hsa_piR_009295, hsa_piR_020813, hsa_piR_004307, and hsa_piR_019914 in tumor tissues. We developed two optimal logistic regression models using the quantitation of hsa_piR_020813, miR-16-5p, and hsa_piR_022437 or hsa_piR_004307, hsa_piR_019914, and miR-93-5p in the tumor tissue, which exhibited a significant ability to diagnose the PGR-negative tumor phenotype with 93% sensitivity. Of particular interest, the blood plasma levels of miR-16-5p and hsa_piR_022437 could be used to diagnose the PGR-negative tumor phenotype with 86% sensitivity even before surgery and chemotherapy. This knowledge can help in choosing the most effective treatment strategy for this aggressive type of ovarian cancer, such as neoadjuvant chemotherapy followed by cytoreduction in combination with hyperthermic intraperitoneal chemotherapy and targeted therapy, thus enhancing the treatment's effectiveness and the patient's longevity.

Common Genetic Aberrations Associated with Metabolic Interferences in Human Type-2 Diabetes and Acute Myeloid Leukemia: A Bioinformatics Approach

Type-2 diabetes mellitus (T2D) is a chronic metabolic disorder, associated with an increased risk of developing solid tumors and hematological malignancies, including acute myeloid leukemia (AML). However, the genetic background underlying this predisposition remains elusive. We herein aimed at the exploration of the genetic variants, related transcriptomic changes and disturbances in metabolic pathways shared by T2D and AML, utilizing bioinformatics tools and repositories, as well as publicly available clinical datasets. Our approach revealed that rs11709077 and rs1801282, on PPARG, rs11108094 on USP44, rs6685701 on RPS6KA1 and rs7929543 on AC118942.1 comprise common SNPs susceptible to the two diseases and, together with 64 other co-inherited proxy SNPs, may affect the expression patterns of metabolic genes, such as USP44, METAP2, PPARG, TIMP4 and RPS6KA1, in adipose tissue, skeletal muscle, liver, pancreas and whole blood. Most importantly, a set of 86 AML/T2D common susceptibility genes was found to be significantly associated with metabolic cellular processes, including purine, pyrimidine, and choline metabolism, as well as insulin, AMPK, mTOR and PI₃K signaling. Moreover, it was revealed that the whole blood of AML patients exhibits deregulated expression of certain T2D-related genes. Our findings support the existence of common metabolic perturbations in AML and T2D that may account for the increased risk for AML in T2D patients. Future studies may focus on the elucidation of these pathogenetic mechanisms in AML/T2D patients, as well as on the assessment of certain susceptibility variants and genes as potential biomarkers for AML development in the setting of T2D. Detection of shared therapeutic molecular targets may enforce the need for repurposing metabolic drugs in the therapeutic management of AML.

Hormone therapy for ovarian cancer: Emphasis on mechanisms and applications (Review)

Ovarian cancer (OC) remains the leading cause of mortality due to gynecological malignancies. Epidemiological studies have demonstrated that steroid hormones released from the hypothalamic-pituitary-ovarian axis can play a role in stimulating or inhibiting OC progression, with gonadotropins, estrogens and androgens promoting OC progression, while gonadotropin-releasing hormone (GnRH) and progesterone may be protective factors in OC. Experimental studies have indicated that hormone receptors are expressed in OC cells and mediate the growth stimulatory or growth inhibitory effects of hormones on these cells. Hormone therapy agents have been evaluated in a number of clinical trials. The majority of these trials were conducted in patients with relapsed or refractory OC with average efficacy and limited side-effects. A better understanding of the mechanisms through which hormones affect cell growth may improve the efficacy of hormone therapy. In the present review article, the role of hormones (GnRH, gonadotropins, androgens, estrogens and progestins) and their receptors in OC tumorigenesis, and hormonal therapy in OC treatment is discussed and summarized.

Survival analysis across the entire transcriptome identifies biomarkers with the highest prognostic power in breast cancer

Introduction

Extensive research is directed to uncover new biomarkers capable to stratify breast cancer patients into clinically relevant cohorts. However, the overall performance ranking of such marker candidates compared to other genes is virtually absent. Here, we present the ranking of all survival related genes in chemotherapy treated basal and estrogen positive/HER2 negative breast cancer.

Methods

We searched the GEO repository to uncover transcriptomic datasets with available follow-up and clinical data. After quality control and normalization, samples entered an integrated database. Molecular subtypes were designated using gene expression data. Relapse-free survival analysis was performed using Cox proportional hazards regression. False discovery rate was computed to combat multiple hypothesis testing. Kaplan-Meier plots were drawn to visualize the best performing genes.

Results

The entire database includes 7,830 unique samples from 55 independent datasets. Of those with available relapse-free survival time, 3,382 samples were estrogen receptor-positive and 696 were basal. In chemotherapy treated ER positive/ERBB2 negative patients the significant prognostic biomarker genes achieved hazard rates between 1.76 and 3.33 with a p value below 5.8E−04. The significant prognostic genes in adjuvant chemotherapy treated basal breast cancer samples reached hazard rates between 1.88 and 3.61 with a p value below 7.2E−04. Our integrated platform was extended enabling the validation of future biomarker candidates.

Conclusions

A reference ranking for all genes in two chemotherapy treated breast cancer cohorts is presented. The results help to neglect those with unlikely clinical significance and to focus future research on the most promising candidates.

The Utility of Resolving Asthma Molecular Signatures Using Tissue-Specific Transcriptome Data

An integrative analysis focused on multi-tissue transcriptomics has not been done for asthma. Tissue-specific DEGs remain undetected in many multi-tissue analyses, which influences identification of disease-relevant pathways and potential drug candidates. Transcriptome data from 609 cases and 196 controls, generated using airway epithelium, bronchial, nasal, airway macrophages, distal lung fibroblasts, proximal lung fibroblasts, CD4+ lymphocytes, CD8+ lymphocytes from whole blood and induced sputum samples, were retrieved from Gene Expression Omnibus (GEO). Differentially regulated asthma-relevant genes identified from each sample type were used to identify (a) tissue-specific and tissue-shared asthma pathways, (b) their connection to GWAS-identified disease genes to identify candidate tissue for functional studies, (c) to select surrogate sample for invasive tissues, and finally (d) to identify potential drug candidates via connectivity map analysis. We found that inter-tissue similarity in gene expression was more pronounced at pathway/functional level than at gene level with highest similarity between bronchial epithelial cells and lung fibroblasts, and lowest between airway epithelium and whole blood samples. Although public-domain gene expression data are limited by inadequately annotated per-sample demographic and clinical information which limited the analysis, our tissue-resolved analysis clearly demonstrated relative importance of unique and shared asthma pathways, At the pathway level, IL-1b signaling and ERK signaling were significant in many tissue types, while Insulin-like growth factor and TGF-beta signaling were relevant in only airway epithelial tissue. IL-12 (in macrophages) and Immunoglobulin signaling (in lymphocytes) and chemokines (in nasal epithelium) were the highest expressed pathways. Overall, the IL-1 signaling genes (inflammatory) were relevant in the airway compartment, while pro-Th2 genes including IL-13 and STAT6 were more relevant in fibroblasts, lymphocytes, macrophages and bronchial biopsies. These genes were also associated with asthma in the GWAS catalog. Support Vector Machine showed that DEGs based on macrophages and epithelial cells have the highest and lowest discriminatory accuracy, respectively. Drug (entinostat, BMS-345541) and genetic perturbagens (KLF6, BCL10, INFB1 and BAMBI) negatively connected to disease at multi-tissue level could potentially repurposed for treating asthma. Collectively, our study indicates that the DEGs, perturbagens and disease are connected differentially depending on tissue/cell types. While most of the existing literature describes asthma transcriptome data from individual sample types, the present work demonstrates the utility of multi-tissue transcriptome data. Future studies should focus on collecting transcriptomic data from multiple tissues, age and race groups, genetic background, disease subtypes and on the availability of better-annotated data in the public domain.

Indole Derivative Interacts with Estrogen Receptor Beta and Inhibits Human Ovarian Cancer Cell Growth

Ovarian cancer remains the leading cause of mortality among gynecological tumors. Estrogen receptor beta (ERβ) expression has been suggested to act as a tumor suppressor in epithelial ovarian cancer by reducing both tumor growth and metastasis. ERβ expression abnormalities represent a critical step in the development and progression of ovarian cancer: for these reasons, its re-expression by genetic engineering, as well as the use of targeted ERβ therapies, still constitute an important therapeutic approach. 3-{[2-chloro-1-(4-chlorobenzyl)-5-methoxy-6-methyl-1H-indol-3-yl]methylene}-5-hydroxy-6-methyl-1,3-dihydro-2H-indol-2-one, referred to here as compound 3, has been shown to have cytostatic as well cytotoxic effects on various hormone-dependent cancer cell lines. However, the mechanism of its anti-carcinogenic activity is not well understood. Here, we offer a possible explanation of such an effect in the human ovarian cancer cell line IGROV1. Chromatin binding protein assay and liquid chromatography mass spectrometry were exploited to localize and quantify compound 3 in cells. Molecular docking was used to prove compound 3 binding to ERβ. Mass spectrometry-based approaches were used to analyze histone post-translational modifications. Finally, gene expression analyses revealed a set of genes regulated by the ERβ/3 complex, namely CCND1, MYC, CDKN2A, and ESR2, providing possible molecular mechanisms that underline the observed antiproliferative effects.

Synedrella nodiflora (Linn.) Gaertn. inhibits inflammatory responses through the regulation of Syk in RAW 264.7 macrophages

Synedrella nodiflora (Linn.) Gaertn. (S. nodiflora) has long been used for the treatment of inflammatory diseases, including liver disease, asthma, rheumatism and earache, in tropical countries throughout America, Asia and Africa. However, the biological effects of S. nodiflora have not been extensively studied at the molecular level. Notably, it remains unclear how S. nodiflora exerts anti-inflammatory activity. In the present study, the anti-inflammatory mechanism of a methanol extract of S. nodiflora (MSN) in RAW 264.7 macrophages activated by lipopolysaccharide (LPS) was investigated. Non-cytotoxic concentrations of MSN (≤400 µg/ml) decreased the expression of inducible nitric oxide synthase (iNOS) and cyclooxygenase-2 (COX-2), which resulted in a decrease in nitric oxide and prostaglandin E₂ (PGE₂) production. The mRNA expression of pro-inflammatory cytokines such as interleukin (IL)-6, IL-1β, and tumor necrosis factor (TNF)-α was reduced upon MSN treatment. In addition, the activation of spleen tyrosine kinase (Syk) and Akt was suppressed by MSN. Taken together, these findings recommend the traditional medicinal application of S. nodiflora in the treatment of several inflammation-associated diseases and indicate the possibility of MSN as a novel therapeutic reagent of inflammation-related diseases.

SNCG promotes the progression and metastasis of high-grade serous ovarian cancer via targeting the PI3K/AKT signaling pathway

Background

The poor prognosis of patients with ovarian cancer is mainly due to cancer progression. γ-Synuclein (SNCG) has reported as a critical player in cancer metastasis. However, its biological roles and mechanism are yet incompletely understood in ovarian cancer, especially in high-grade serous ovarian cancer (HGSOC).

Methods

This is a retrospective study of 312 patients with ovarian cancer at a single center between 2006 and 2016. Ovarian cancer tissues were stained by immunohistochemistry to analyze the relationship between SNCG expression and clinicopathologic factors. The clinical outcomes versus SNCG expression level were evaluated by Kaplan–Meier method and multiple Cox regression analysis. Next, systematical functional experiments were given to examine the proliferation and metastatic abilities of SNCG both in vitro and in vivo using loss- and gain- of function approaches. Furthermore, the mechanisms of SNCG overexpression were examined by human phospho-kinase array kit and western blot analysis.

Results

Clinically, the expression of SNCG was significantly upregulated in ovarian cancer compared with the borderline and benign tumor, normal ovary, and fallopian tube. Notably, the high level of SNCG correlated with high-risk clinicopathologic features and showed poor survival for patients with HGSOC, indicating an independent prognostic factor for these patients. Functionally, we observed that overexpression of SNCG promoted cell proliferation, tumor formation, migration, and invasion both in vitro and in vivo. Mechanistically, we identified that SNCG promoted cancer cell metastasis through activating the PI3K/AKT signaling pathway.

Conclusions

Our results reveal SNCG up-regulation contributes to the poor clinical outcome of patients with HGSOC and highlight the metastasis-promoting function of SNCG via activating the PI3K/Akt signaling pathway in HGSOC.

FOXM1 functions collaboratively with PLAU to promote gastric cancer progression

Background: Gastric cancer (GC) is one of the main mortality cause worldwide. Previously, we found Forkhead box protein (FOXM1) or Urokinase-type plasminogen activator (PLAU) are independent prognostic markers of GC. This study aims to explore the combining prognostic efficacy and the potential insights underlying additive effect of FOXM1 to PLAU in GC progression through in-silico analyses. Method: The expression of FOXM1 and PLAU were profiled in 33 cancer types using public data. A merged GC expression dataset containing 598 samples was used for evaluating prognostic significance of FOXM1/PLAU. Gene Set Enrichment Analysis (GSEA) was performed to elucidate the mechanisms underlying FOXM1/PLAU promoted GC progression. The Cancer Genome Atlas (TCGA) was used for analyzing the association between FOXM1/PLAU and tumor immune infiltration. Genomic and proteomic differences between FOXM1+PLAU+ and FOXM1-PLAU- groups were also computed using TCGA GC data. Drugs targeting FOXM1/PLAU associated gene expression pattern was analyzed using LINCs database. Results: FOXM1 and PLAU are overexpressed in 17/33 cancer types including GC. Kaplan-Meier analyses indicate that the FOXM1+PLAU+ subgroup have the worst prognosis, while FOXM1-PLAU- subgroup have the best survival. Bioinformatics analysis indicated that FOXM1+PLAU+ associated genes are enriched in TGF-beta, DNA repair and drug resistance signaling pathways; FOXM1 and PLAU expression are negatively correlated with tumor immune infiltration. Genomic and proteomic differences between FOXM1+PLAU+ and FOXM1-PLAU- groups were presented. Data mining from LINCs suggested several chemicals or drugs that could target the gene expression pattern of FOXM1+PLAU+ patients. Conclusion: FOXM1+PLAU+ can serve as effective prognostic biomarkers and potential therapeutic targets for GC. Due to the additive effect of these two genes, screening for drugs or chemicals that targeting the expression patterns PLAU+FOXM1+ subgroup may exert important clinical impact on GC management.

Evaluation of the epidemiological and prognosis significance of ESR2 rs3020450 polymorphism in ovarian cancer

AIM

To investigate the correlation between the polymorphism of estrogen receptor β gene (ESR2) rs3020450 and cancer susceptibility, and explore the epidemiological significance and the effect of ESR2 expression levels on the prognosis of ovarian cancer.

METHODS

Based on meta-analysis the association between ESR2 rs3020450 polymorphism and cancer susceptibility was estimated and a case-control design was used to verify this result in ovarian cancer. The epidemiological effect of ESR2 rs3020450 polymorphism was assessed by attributable risk percentage (ARP) and population attributable risk percentage (PARP). Kaplan Meier plotters were used to evaluate overall survival (OS) and progression-free survival (PFS) in ovarian cancer patients and GEPIA for the differential expression of ESR2 levels in ovarian cancer and adjacent normal tissues.

RESULTS

The pooled analysis indicated no significant correlation between the ESR2 rs3020450 polymorphism and the cancer susceptibility. In the stratified analysis by cancer types, significantly decreased risk was found in ovarian cancer (AG vs GG: OR = 0.73, 95%CI: 0.53-0.97, P = 0.03). Unconditional logistic regression results of case-control study in ovarian cancer observed significant differences in all comparisons (AG vs GG: OR = 0.81, 95%CI: 0.62-0.98, P = 0.04; AA vs GG: OR = 0.63, 95%CI: 0.42-0.92, P = 0.01 and AG + AA vs GG: OR = 0.73, 95%CI: 0.53-0.96, P < 0.001). Based on meta-analysis and case-control pooled results, ARP and PARP were evaluated respectively in allele (21.95% and7.97%), heterozygote (36.99% and 12.11%) and dominant model (36.84% and 12.97%) of rs3020450 polymorphism in ovarian cancer. The expression levels of ESR2 in normal tissues was significantly higher than that in cancer tissues (OV, Median, 4.7:0.21), and significant correlations were observed between high ESR2 expression levels and long OS (HR = 0.80, 95%CI: 0.70-0.92, P = 0.002) and PFS (HR = 0.767, 95%Cl: 0.67-0.88, P < 0.001).

CONCLUSION

Our results indicated that ESR2 rs3020450 polymorphism was associated with ovarian cancer risk from epidemiological perspective, and high ESR2 expression levels was associated with long survival in patients with ovarian cancer.

Blood-based analysis of type-2 diabetes mellitus susceptibility genes identifies specific transcript variants with deregulated expression and association with disease risk

Despite significant progress by genome-wide association studies, the ability of genetic variants to conduce to the prediction or prognosis of type-2 diabetes (T2D) is weak. Expression analysis of the corresponding genes may suggest possible links between single-nucleotide polymorphisms and T2D phenotype and/or risk. Herein, we investigated the expression patterns of 24 T2D-susceptibility genes, and their individual transcript variants (tv), in peripheral blood of T2D patients and controls (CTs), applying RNA-seq and real-time qPCR methodologies, and explore possible associations with disease features. Our data revealed the deregulation of certain transcripts in T2D patients. Among them, the down-regulation of CAPN10 tv3 was confirmed as an independent predictor for T2D. In patients, increased expression of CDK5 tv2, CDKN2A tv3 or THADA tv5 correlated positively with serum insulin levels, of CDK5 tv1 positively with % HbA1c levels, while in controls, elevated levels of TSPAN8 were associated positively with the presence of T2D family history. Herein, a T2D-specific expression profile of specific transcripts of disease-susceptibility genes is for the first time described in human peripheral blood. Large-scale studies are needed to evaluate the potential of these molecules to serve as disease biomarkers.

Independent validation of induced overexpression efficiency across 242 experiments shows a success rate of 39

Although numerous studies containing induced gene expression have already been published, independent authentication of their results has not yet been performed. Here, we utilized available transcriptomic data to validate the achieved efficiency in overexpression studies. Microarray data of experiments containing cell lines with induced overexpression in one or more genes were analyzed. All together 342 studies were processed, these include 242 different genes overexpressed in 184 cell lines. The final database includes 4,755 treatment-control sample pairs. Successful gene induction (fold change induction over 1.44) was validated in 39.3% of all genes at p < 0.05. Number of repetitions within a study (p < 0.0001) and type of used vector (p = 0.023) had significant impact on successful overexpression efficacy. In summary, over 60% of studies failed to deliver a reproducible overexpression. To achieve higher efficiency, robust and strict study design with multi-level quality control will be necessary.

Cross-validation of survival associated biomarkers in gastric cancer using transcriptomic data of 1,065 patients

Introduction

Multiple gene expression based prognostic biomarkers have been repeatedly identified in gastric carcinoma. However, without confirmation in an independent validation study, their clinical utility is limited. Our goal was to establish a robust database enabling the swift validation of previous and future gastric cancer survival biomarker candidates.

Results

The entire database incorporates 1,065 gastric carcinoma samples, gene expression data. Out of 29 established markers, higher expression of BECN1 (HR = 0.68, p = 1.5E-05), CASP3 (HR = 0.5, p = 6E-14), COX2 (HR = 0.72, p = 0.0013), CTGF (HR = 0.72, p = 0.00051), CTNNB1 (HR = 0.47, p = 4.3E-15), MET (HR = 0.63, p = 1.3E-05), and SIRT1 (HR = 0.64, p = 2.2E-07) correlated to longer OS. Higher expression of BIRC5 (HR = 1.45, p = 1E-04), CNTN1 (HR = 1.44, p = 3.5E- 05), EGFR (HR = 1.86, p = 8.5E-11), ERCC1 (HR = 1.36, p = 0.0012), HER2 (HR = 1.41, p = 0.00011), MMP2 (HR = 1.78, p = 2.6E-09), PFKB4 (HR = 1.56, p = 3.2E-07), SPHK1 (HR = 1.61, p = 3.1E-06), SP1 (HR = 1.45, p = 1.6E-05), TIMP1 (HR = 1.92, p = 2.2E- 10) and VEGF (HR = 1.53, p = 5.7E-06) were predictive for poor OS.

MATERIALS AND METHODS

We integrated samples of three major cancer research centers (Berlin, Bethesda and Melbourne datasets) and publicly available datasets with available follow-up data to form a single integrated database. Subsequently, we performed a literature search for prognostic markers in gastric carcinomas (PubMed, 2012–2015) and re-validated their findings predicting first progression (FP) and overall survival (OS) using uni- and multivariate Cox proportional hazards regression analysis.

Conclusions

The major advantage of our analysis is that we evaluated all genes in the same set of patients thereby making direct comparison of the markers feasible. The best performing genes include BIRC5, CASP3, CTNNB1, TIMP-1, MMP-2, SIRT, and VEGF.

Gene Expression Profiling Reveals Novel Candidate Markers of Ovarian Carcinoma Intraperitoneal Metastasis

Epithelial ovarian cancer (EOC) has the highest mortality among gynecological carcinomas. The lack of specific markers for prognostic determination of EOC progression hinders the search for novel effective therapies.

The aim of the present study was (i) to explore differences in expressions of ATP-binding cassette (ABC) and solute carrier (SLC) transporter genes, genes associated with drug metabolism and cell cycle regulation between control ovarian tissues (n = 14), primary EOCs (n = 44) and intraperitoneal metastases (n = 29); (ii) to investigate associations of gene expression levels with prognosis of patients with intraperitoneal metastases.

In all tissue samples, transcript levels of the above target genes were assessed using quantitative real-time PCR. Gene expression levels were compared between particular tissue types and evaluated with regard to progression-free survival (PFS) and drug-resistance status of patients with metastases.

Gene expression of ABCA7 significantly increased and that of ESR2 decreased in the order control ovarian tissues - primary EOCs - metastases. High expressions of ABCA2/8/9/10, ABCB1, ABCC9, ABCG2, ATP7A, SLC16A14, and SOD3 genes were significantly associated with longer progression-free survival of patients. In intraperitoneal metastases, expression of all of these genes highly correlated and indicated prognostic profile. Transporters from the ABCA family, ABCG2, and ESR2 are involved mainly in lipid metabolism, membrane transport, and cell proliferation. These processes are thus probably the most important for EOC progression.

Based on these results, we have proposed novel markers of ovarian carcinoma progression and metastatic spread which might be potentially useful as therapeutic targets. Their significance should be further explored on a larger independent set of patients.

Overexpression of HS6ST2 is associated with poor prognosis in patients with gastric cancer

The purpose of the present study was to investigate the clinical significance of the expression of heparan sulfate 6-O-sulfotransferase 2 (HS6ST2) in gastric cancer (GC). The Affymetrix GeneChip^® Human Genome U133 Plus 2.0 Array (Affymetrix; Thermo Fisher Scientific, Inc., Waltham, MA, USA) was used to identify differentially expressed genes in GC tissues vs. adjacent non-tumor gastric tissues. Candidate genes were further verified by reverse transcription quantitative polymerase chain reaction (RT-qPCR) and immunohistochemistry (IHC). In addition, an independent dataset was obtained from the Gene Expression Omnibus, and a survival analysis was performed. Microarray analysis demonstrated that HS6ST2 was upregulated (>12-fold) in GC tissues compared with that in adjacent non-tumor tissues. RT-qPCR and IHC analysis of HS6ST2 in GC tissues and adjacent non-tumor tissues confirmed the microarray data. Furthermore, a positive association was demonstrated between HS6ST2 overexpression with the depth of tumor invasion, distant metastasis, and tumor-node metastasis stage. Survival analysis revealed an association between patients with increased expression of HS6ST2 and a poor prognosis of gastric cancer. Cox regression analysis indicated that the expression of HS6ST2 was an independent negative prognostic factor for GC. The expression of HS6ST2 in GC was significantly associated with specific clinicopathological parameters and prognosis of disease, thus we propose that HS6ST2 may represent a novel biomarker for GC.

RNA-based ovarian cancer research from 'a gene to systems biomedicine' perspective

Ovarian cancer remains the leading cause of death from a gynecologic malignancy, and treatment of this disease is harder than any other type of female reproductive cancer. Improvements in the diagnosis and development of novel and effective treatment strategies for complex pathophysiologies, such as ovarian cancer, require a better understanding of disease emergence and mechanisms of progression through systems medicine approaches. RNA-level analyses generate new information that can help in understanding the mechanisms behind disease pathogenesis, to identify new biomarkers and therapeutic targets and in new drug discovery. Whole RNA sequencing and coding and non-coding RNA expression array datasets have shed light on the mechanisms underlying disease progression and have identified mRNAs, miRNAs, and lncRNAs involved in ovarian cancer progression. In addition, the results from these analyses indicate that various signalling pathways and biological processes are associated with ovarian cancer. Here, we present a comprehensive literature review on RNA-based ovarian cancer research and highlight the benefits of integrative approaches within the systems biomedicine concept for future ovarian cancer research. We invite the ovarian cancer and systems biomedicine research fields to join forces to achieve the interdisciplinary caliber and rigor required to find real-life solutions to common, devastating, and complex diseases such as ovarian cancer.

ABBREVIATIONS

CAF: cancer-associated fibroblasts; COG: Cluster of Orthologous Groups; DEA: disease enrichment analysis; EOC: epithelial ovarian carcinoma; ESCC: oesophageal squamous cell carcinoma; GSI: gamma secretase inhibitor; GO: Gene Ontology; GSEA: gene set enrichment analyzes; HAS: Hungarian Academy of Sciences; lncRNAs: long non-coding RNAs; MAPK/ERK: mitogen-activated protein kinase/extracellular signal-regulated kinases; NGS: next-generation sequencing; ncRNAs: non-coding RNAs; OvC: ovarian cancer; PI3K/Akt/mTOR: phosphatidylinositol-3-kinase/protein kinase B/mammalian target of rapamycin; RT-PCR: real-time polymerase chain reaction; SNP: single nucleotide polymorphism; TF: transcription factor; TGF-β: transforming growth factor-β.

Effect of estrogen receptor β agonists on proliferation and gene expression of ovarian cancer cells

Background

Estrogen receptor (ER) β has been suggested to affect ovarian carcinogenesis. We examined the effects of four ERβ agonists on proliferation and gene expression of two ovarian cancer cell lines.

Methods

OVCAR-3 and OAW-42 ovarian cancer cells were treated with the ERβ agonists ERB-041, WAY200070, Liquiritigenin and 3β-Adiol and cell growth was measured by means of the Cell Titer Blue Assay (Promega). ERβ expression was knocked down by transfection with specific siRNA. Additionally, transcriptome analyses were performed by means of Affymetrix GeneChip arrays. To confirm the results of DNA microarray analysis, Western blot experiments were performed.

Results

All ERβ agonists tested significantly decreased proliferation of OVCAR-3 and OAW-42 cells at a concentration of 10 nM. Maximum antiproliferative effects were induced by flavonoid Liquiritigenin, which inhibited growth of OVCAR-3 cells by 31.2% after 5 days of treatment, and ERB-041 suppressing proliferation of the same cell line by 29.1%. In OAW-42 cells, maximum effects were observed after treatment with the ERβ agonist WAY200070, inhibiting cell growth by 26.8%, whereas ERB-041 decreased proliferation by 24.4%. In turn, knockdown of ERβ with specific siRNA increased cell growth of OAW-42 cells about 1.9-fold. Transcriptome analyses revealed a set of genes regulated by ERβ agonists including ND6, LCN1 and PTCH2, providing possible molecular mechanisms underlying the observed antiproliferative effects.

Conclusion

In conclusion, the observed growth-inhibitory effects of all ERβ agonists on ovarian cancer cell lines in vitro encourage further studies to test their possible use in the clinical setting.

Joint features and complementarities of Tspan8 and CD151 revealed in knockdown and knockout models

Tetraspanins are highly conserved 4-transmembrane proteins which form molecular clusters with a large variety of transmembrane and cytosolic proteins. By these associations tetraspanins are engaged in a multitude of biological processes. Furthermore, tetraspanin complexes are located in specialized microdomains, called tetraspanin-enriched microdomains (TEMs). TEMs provide a signaling platform and are poised for invagination and vesicle formation. These vesicles can be released as exosomes (Exo) and are important in cell contact-independent intercellular communication. Here, we summarize emphasizing knockdown and knockout models' pathophysiological joint and selective activities of CD151 and Tspan8, and discuss the TEM-related engagement of CD151 and Tspan8 in Exo activities.

Synuclein-γ (SNCG) expression in ovarian cancer is associated with high-risk clinicopathologic disease

Background

Synuclein gamma (SNCG) expression is associated with advanced disease and chemoresistance in multiple solid tumors. Our goal was to determine if SNCG protein expression in ovarian cancer was correlated with clinicopathologic variables and patient outcomes.

Methods

Tissue microarrays from primary tumors of 357 ovarian, fallopian tube, and primary peritoneal cancer patients, who underwent primary surgery at Roswell Park Cancer Institute between 1995 and 2007, were immunohistochemically stained for SNCG. A pathologist blinded to patient data scored tumors as positive if ≥10 % of the sample stained for SNCG. Medical records were reviewed for clinicopathologic and demographic variables. Between the positive and negative groups, Wilcoxon rank-sum test was used to compare the median ages and Fisher’s exact test was used to compare groups in categorical variables. Cox proportional hazard models examined associations between SNCG and overall and progression-free survival.

Results

The median follow-up was 36 months, median overall survival was 39 months, and median progression-free survival was 18 months. SNCG presence was associated with clinical variables of serous histology, grade 3 disease, suboptimal debulking, ascites at surgery, FIGO stage III-IV cancer, or initial CA-125 level >485. There was no significant difference in overall survival (HR 1.06 95 % CI 0.81–1.39 P 0.69) or progression-free survival (HR 1.16 95 % CI 0.89–1.50 P 0.28) for patients with or without SNCG expression.

Conclusions

SNCG expression in ovarian cancer is frequent in patients with high-risk features, but it does not correlate with chemotherapy response, overall survival, or progression-free survival.

Electronic supplementary material

The online version of this article (doi:10.1186/s13048-016-0281-4) contains supplementary material, which is available to authorized users.

Downregulation of ALDOB is associated with poor prognosis of patients with gastric cancer

Objectives

To examine the expression of ALDOB in gastric cancer (GC) tissue and to reveal its potential clinicopathological and prognostic significance.

Materials and methods

We screened for genes that were differentially expressed between GC and nontumor tissues using a microarray, specifically the Affymetrix U133 Plus 2.0 Array platform. We then verified the transcriptional and translational levels of ALDOB by performing quantitative real-time polymerase chain reaction (qRT-PCR) and immunohistochemistry (IHC). In addition, a merged data set based on the Gene Expression Omnibus was generated and a survival analysis performed.

Results

The microarray analysis revealed that ALDOB was downregulated (more than sevenfold) in GC compared with nontumor tissue. Both qRT-PCR and IHC validated the decrease of ALDOB in GC tissue. Moreover, we found that the expression of ALDOB was significantly related to tumor-invasion depth, lymph-node metastasis, distant metastasis, and TNM stage. The survival analysis, based on the IHC and merged data set, indicated that the overall survival was better in patients with high ALDOB expression. The Cox regression analysis showed that ALDOB expression was an independent prognostic factor for GC.

Conclusion

The expression of ALDOB in GC tissue was significantly related to the clinicopathological features and prognosis of the disease, thus suggesting that ALDOB could act as a novel molecular marker for GC.

Identification of Cathepsin K in the Peritoneal Metastasis of Ovarian Carcinoma Using In-silico, Gene Expression Analysis

Ovarian carcinomas (OC) are often found in the advanced stage with wide peritoneal dissemination. Differentially-expressed genes (DEGs) between primary ovarian carcinoma (POC) and peritoneal metastatic ovarian carcinomas (PMOC) may have diagnostic and therapeutic values. In this study, we identified 246 DEGs by in-silico analysis using microarrays for 153 POCs and 57 PMOCs. Pathway analysis shows that many of these genes are associated with lipid metabolism. Microfluidic, card-based, quantitative PCR validated 19 DEGs in PMOCs versus POCs (p<0.05). Immunohistochemistry confirmed overexpression of MMP13, CTSK, FGF1 and GREM1 in PMOCs (p<0.05). ELISA detection indicated that serum CTSK levels were significantly increased in OCs versus controls (p<0.001). CTSK levels discriminated between OCs and healthy controls (ROC 0.739; range 0.685-0.793). Combining CA125 and HE4 with CTSK levels produced an improved specificity in the predictive of OCs (sensitivity 88.3%, specificity 92.0%, Youden's index 80.3%). Our study suggests that CTSK levels may be helpful in the diagnosis of primary, ovarian carcinoma.

Regulation of human MAPT gene expression

The number of known pathologies involving deregulated Tau expression/metabolism is increasing. Indeed, in addition to tauopathies, which comprise approximately 30 diseases characterized by neuronal aggregation of hyperphosphorylated Tau in brain neurons, this protein has also been associated with various other pathologies such as cancer, inclusion body myositis, and microdeletion/microduplication syndromes, suggesting its possible function in peripheral tissues. In addition to Tau aggregation, Tau deregulation can occur at the expression and/or splicing levels, as has been clearly demonstrated in some of these pathologies. Here, we aim to review current knowledge regarding the regulation of human MAPT gene expression at the DNA and RNA levels to provide a better understanding of its possible deregulation. Several aspects, including repeated motifs, CpG island/methylation, and haplotypes at the DNA level, as well as the key regions involved in mRNA expression and stability and the splicing patterns of different mRNA isoforms at the RNA level, will be discussed.

Relationship between differentially expressed mRNA and mRNA-protein correlations in a xenograft model system

Differential mRNA expression studies implicitly assume that changes in mRNA expression have biological meaning, most likely mediated by corresponding changes in protein levels. Yet studies into mRNA-protein correspondence have shown notoriously poor correlation between mRNA and protein expression levels, creating concern for inferences from only mRNA expression data. However, none of these studies have examined in particular differentially expressed mRNA. Here, we examined this question in an ovarian cancer xenograft model. We measured protein and mRNA expression for twenty-nine genes in four drug-treatment conditions and in untreated controls. We identified mRNAs differentially expressed between drug-treated xenografts and controls, then analysed mRNA-protein expression correlation across a five-point time-course within each of the four experimental conditions. We evaluated correlations between mRNAs and their protein products for mRNAs differentially expressed within an experimental condition compared to those that are not. We found that differentially expressed mRNAs correlate significantly better with their protein product than non-differentially expressed mRNAs. This result increases confidence for the use of differential mRNA expression for biological discovery in this system, as well as providing optimism for the usefulness of inferences from mRNA expression in general.

CIAPIN1 and ABCA13 are markers of poor survival in metastatic ovarian serous carcinoma

Background

The objective of this study was to investigate the expression and clinical role of 14 genes previously shown to be associated with chemotherapy response and/or progression-free survival in a smaller series of ovarian serous carcinoma effusions.

Methods

Advanced-stage serous ovarian carcinoma effusions (n = 150) were analyzed for mRNA expression of AKR1C1, ABCA4, ABCA13, ABCB10, BIRC6, CASP9, CIAPIN1, FAS, MGMT, MUTYH, POLH, SRC, TBRKB and XPA using quantitative real-time PCR. mRNA expression was studied for association with clinicopathologic parameters, including chemotherapy response and survival.

Results

ABCA4 mRNA expression was significantly related to better (complete) chemotherapy response at diagnosis in the entire cohort (p = 0.018), whereas higher POLH mRNA levels were significantly related to better chemoresponse at diagnosis in analysis to 58 patients with pre-chemotherapy effusions treated with standard chemotherapy (carboplatin + paclitaxel; p = 0.023). In univariate survival analysis for patients with pre-chemotherapy effusions (n = 77), CIAPIN1 mRNA expression was significantly related to shorter overall (p = 0.007) and progression-free (p = 0.038) survival, whereas ABCA13 mRNA expression was significantly related to shorter OS (p = 0.024). Higher CIAPIN1 mRNA expression was an independent marker of poor overall survival in Cox multivariate analysis (p = 0.044).

Conclusions

Our data identify ABCA4 and POLH as markers of better chemotherapy response in metastatic serous carcinoma. CIAPIN1 and ABCA13 may be novel markers of poor outcome in pre-chemotherapy serous carcinoma effusions.

MEK1 is associated with carboplatin resistance and is a prognostic biomarker in epithelial ovarian cancer

BACKGROUND

Primary systemic treatment for ovarian cancer is surgery, followed by platinum based chemotherapy. Platinum resistant cancers progress/recur in approximately 25% of cases within six months. We aimed to identify clinically useful biomarkers of platinum resistance.

METHODS

A database of ovarian cancer transcriptomic datasets including treatment and response information was set up by mining the GEO and TCGA repositories. Receiver operator characteristics (ROC) analysis was performed in R for each gene and these were then ranked using their achieved area under the curve (AUC) values. The most significant candidates were selected and in vitro functionally evaluated in four epithelial ovarian cancer cell lines (SKOV-3-, CAOV-3, ES-2 and OVCAR-3), using gene silencing combined with drug treatment in viability and apoptosis assays. We collected 94 tumor samples and the strongest candidate was validated by IHC and qRT-PCR in these.

RESULTS

All together 1,452 eligible patients were identified. Based on the ROC analysis the eight most significant genes were JRK, CNOT8, RTF1, CCT3, NFAT2CIP, MEK1, FUBP1 and CSDE1. Silencing of MEK1, CSDE1, CNOT8 and RTF1, and pharmacological inhibition of MEK1 caused significant sensitization in the cell lines. Of the eight genes, JRK (p = 3.2E-05), MEK1 (p = 0.0078), FUBP1 (p = 0.014) and CNOT8 (p = 0.00022) also correlated to progression free survival. The correlation between the best biomarker candidate MEK1 and survival was validated in two independent cohorts by qRT-PCR (n = 34, HR = 5.8, p = 0.003) and IHC (n = 59, HR = 4.3, p = 0.033).

CONCLUSION

We identified MEK1 as a promising prognostic biomarker candidate correlated to response to platinum based chemotherapy in ovarian cancer.

An on-chip Cell-SELEX process for automatic selection of high-affinity aptamers specific to different histologically classified ovarian cancer cells

Ovarian cancer (OvCa) is the second most common type of gynecological cancer. More seriously, the prognosis for survival is relatively poor if an early OvCa diagnosis is not achieved. However, it is extremely challenging to diagnose very early stage OvCa, when treatments are the most effective, because of the lack of specific and sensitive biomarkers. Therefore, in order to achieve early detection of OvCa, screening and identifying biomarkers with high specificity and affinity are greatly needed. In this study, an integrated microfluidic system capable of performing cell-based systematic evolution of ligands by an exponential enrichment (Cell-SELEX) process was developed for automatic, high-throughput screening of multiple cell lines to competitively select aptamer-based biomarkers for OvCa. This on-chip Cell-SELEX process only required five rounds of aptamer selection, which is much faster than using a conventional SELEX process (22 rounds). Using this on-chip process, 13 aptamers specific to OvCa cells were successfully screened and three of them showed high affinity towards target cells with dissociation constants of 1.8 nM, 8.3 nM, and 1.3 nM. Analysis of stained fluorescence images and competitive testing against multiple cancer cell lines (cervical cancer, breast cancer, lung cancer, and liver cancer) were performed to verify the specificity of these selected aptamers. The results demonstrated that this developed system could perform the on-chip Cell-SELEX selection successfully and could be applied for personalized aptamer screening or targeted therapy monitoring in the near future.

Prediagnostic transcriptomic markers of Chronic lymphocytic leukemia reveal perturbations 10 years before diagnosis

BACKGROUND

B-cell lymphomas are a diverse group of hematological neoplasms with differential etiology and clinical trajectories. Increased insights in the etiology and the discovery of prediagnostic markers have the potential to improve the clinical course of these neoplasms.

METHODS

We investigated in a prospective study global gene expression in peripheral blood mononuclear cells of 263 incident B-cell lymphoma cases, diagnosed between 1 and 17 years after blood sample collection, and 439 controls, nested within two European cohorts.

RESULTS

Our analyses identified only transcriptomic markers for specific lymphoma subtypes; few markers of multiple myeloma (N = 3), and 745 differentially expressed genes in relation to future risk of chronic lymphocytic leukemia (CLL). The strongest of these associations were consistently found in both cohorts and were related to (B-) cell signaling networks and immune system regulation pathways. CLL markers exhibited very high predictive abilities of disease onset even in cases diagnosed more than 10 years after blood collection.

CONCLUSIONS

This is the first investigation on blood cell global gene expression and future risk of B-cell lymphomas. We mainly identified genes in relation to future risk of CLL that are involved in biological pathways, which appear to be mechanistically involved in CLL pathogenesis. Many but not all of the top hits we identified have been reported previously in studies based on tumor tissues, therefore suggesting that a mixture of preclinical and early disease markers can be detected several years before CLL clinical diagnosis.

Identification of the IGF1/PI3K/NF κB/ERK gene signalling networks associated with chemotherapy resistance and treatment response in high-grade serous epithelial ovarian cancer

BACKGROUND

Resistance to platinum-based chemotherapy remains a major impediment in the treatment of serous epithelial ovarian cancer. The objective of this study was to use gene expression profiling to delineate major deregulated pathways and biomarkers associated with the development of intrinsic chemotherapy resistance upon exposure to standard first-line therapy for ovarian cancer.

METHODS

The study cohort comprised 28 patients divided into two groups based on their varying sensitivity to first-line chemotherapy using progression free survival (PFS) as a surrogate of response. All 28 patients had advanced stage, high-grade serous ovarian cancer, and were treated with standard platinum-based chemotherapy. Twelve patient tumours demonstrating relative resistance to platinum chemotherapy corresponding to shorter PFS (< eight months) were compared to sixteen tumours from platinum-sensitive patients (PFS > eighteen months). Whole transcriptome profiling was performed using an Affymetrix high-resolution microarray platform to permit global comparisons of gene expression profiles between tumours from the resistant group and the sensitive group.

RESULTS

Microarray data analysis revealed a set of 204 discriminating genes possessing expression levels which could influence differential chemotherapy response between the two groups. Robust statistical testing was then performed which eliminated a dependence on the normalization algorithm employed, producing a restricted list of differentially regulated genes, and which found IGF1 to be the most strongly differentially expressed gene. Pathway analysis, based on the list of 204 genes, revealed enrichment in genes primarily involved in the IGF1/PI3K/NF κB/ERK gene signalling networks.

CONCLUSIONS

This study has identified pathway specific prognostic biomarkers possibly underlying a differential chemotherapy response in patients undergoing standard platinum-based treatment of serous epithelial ovarian cancer. In addition, our results provide a pathway context for further experimental validations, and the findings are a significant step towards future therapeutic interventions.

Tau protein as a potential predictive marker in epithelial ovarian cancer patients treated with paclitaxel/platinum first-line chemotherapy

Background

The aim of the study was to evaluate predictive and prognostic significance of microtubule-associated protein Tau in epithelial ovarian cancer (EOC) patients treated with paclitaxel and platinum-based chemotherapy.

Methods

74 patients with EOC (stage I-IV) who underwent cytoreductive surgery followed by standard paclitaxel/platinum chemotherapy were included in the retrospective analysis. Their formalin-fixed, paraffin-embedded tissue specimens were immunohistochemically stained for Tau protein, using semi-quantitative DAKO test. Tau expression was acknowledged as negative (0 and 1+) or positive (2+ and 3+). The correlation between Tau expression, progression free survival (PFS) and overall survival (OS) was evaluated. Statistical analysis included Kaplan-Meyer estimator, long rank test, Mann Whitney test and Cox proportional hazards model.

Results

25.7% (19/74) and 74.3% (55/74) of the patients were classified as Tau-negative and Tau-positive, respectively. Median PFS was 28.7 months for Tau-negative group and 15.9 months for Tau-positive group (p = 0.0355). In the univariate analysis 3-year OS in Tau-negative and Tau-positive groups was 80.2% and 52.4%, respectively (p = 0.0198). Low expression of protein Tau was associated with better OS, whereas an advanced stage at diagnosis, suboptimal surgery, serous histological type and resistance to first line chemotherapy were each correlated with worse OS (p <0,05). In multivariate analysis only resistance to first line chemotherapy remained significant (HR 22.59; 95% CI, 8.71-58.55; p <0.0001).

Conclusions

Negative tau protein seems to be both good prognostic factor and a predictor of response to paclitaxel/platinum-based chemotherapy in EOC patients.

Ovarian cancer: in search of better marker systems based on DNA repair defects

Ovarian cancer is the fifth most common female cancer in the Western world, and the deadliest gynecological malignancy. The overall poor prognosis for ovarian cancer patients is a consequence of aggressive biological behavior and a lack of adequate diagnostic tools for early detection. In fact, approximately 70% of all patients with epithelial ovarian cancer are diagnosed at advanced tumor stages. These facts highlight a significant clinical need for reliable and accurate detection methods for ovarian cancer, especially for patients at high risk. Because CA125 has not achieved satisfactory sensitivity and specificity in detecting ovarian cancer, numerous efforts, including those based on single and combined molecule detection and “omics” approaches, have been made to identify new biomarkers. Intriguingly, more than 10% of all ovarian cancer cases are of familial origin. BRCA1 and BRCA2 germline mutations are the most common genetic defects underlying hereditary ovarian cancer, which is why ovarian cancer risk assessment in developed countries, aside from pedigree analysis, relies on genetic testing of BRCA1 and BRCA2. Because not only BRCA1 and BRCA2 but also other susceptibility genes are tightly linked with ovarian cancer-specific DNA repair defects, another possible approach for defining susceptibility might be patient cell-based functional testing, a concept for which support came from a recent case-control study. This principle would be applicable to risk assessment and the prediction of responsiveness to conventional regimens involving platinum-based drugs and targeted therapies involving poly (ADP-ribose) polymerase (PARP) inhibitors.

Ovarian cancer genome

Ovarian cancer (OC) is a relatively frequent malignant disease with a lifetime risk approaching to approximately 1 in 70. As many as 15-25 % OC arise due to known heterozygous germ-line mutations in DNA repair genes, such as BRCA1, BRCA2, RAD51C, NBN (NBS1), BRIP, and PALB2. Sporadic ovarian cancers often phenocopy the features of BRCA1-related hereditary disease (so-called BRCAness), i.e., show biallelic somatic inactivation of the BRCA1 gene. Tumor-specific BRCA1 deficiency renders selective sensitivity of transformed cells to platinating compounds and several other anticancer drugs, which explains high response rates of OC to systemic therapies. High-throughput molecular profiling of OC is instrumental for further progress in identification of novel OC diagnostic markers as well as for the development of new OC-specific treatments. However, interpretation of the huge bulk of incoming data may present a challenge. There is a critical need in the development of bioinformatic tools capable to integrate the multiplicity of available data sets into biologically and medically meaningful pieces of knowledge.

Analyzing illumina gene expression microarray data from different tissues: methodological aspects of data analysis in the metaxpress consortium

Microarray profiling of gene expression is widely applied in molecular biology and functional genomics. Experimental and technical variations make meta-analysis of different studies challenging. In a total of 3358 samples, all from German population-based cohorts, we investigated the effect of data preprocessing and the variability due to sample processing in whole blood cell and blood monocyte gene expression data, measured on the Illumina HumanHT-12 v3 BeadChip array.

Gene expression signal intensities were similar after applying the log₂ or the variance-stabilizing transformation. In all cohorts, the first principal component (PC) explained more than 95% of the total variation. Technical factors substantially influenced signal intensity values, especially the Illumina chip assignment (33–48% of the variance), the RNA amplification batch (12–24%), the RNA isolation batch (16%), and the sample storage time, in particular the time between blood donation and RNA isolation for the whole blood cell samples (2–3%), and the time between RNA isolation and amplification for the monocyte samples (2%). White blood cell composition parameters were the strongest biological factors influencing the expression signal intensities in the whole blood cell samples (3%), followed by sex (1–2%) in both sample types. Known single nucleotide polymorphisms (SNPs) were located in 38% of the analyzed probe sequences and 4% of them included common SNPs (minor allele frequency >5%). Out of the tested SNPs, 1.4% significantly modified the probe-specific expression signals (Bonferroni corrected p-value<0.05), but in almost half of these events the signal intensities were even increased despite the occurrence of the mismatch. Thus, the vast majority of SNPs within probes had no significant effect on hybridization efficiency.

In summary, adjustment for a few selected technical factors greatly improved reliability of gene expression analyses. Such adjustments are particularly required for meta-analyses.

Systematic analysis and validation of differential gene expression in ovarian serous adenocarcinomas and normal ovary

PURPOSE

Cancer of the ovary confers the worst prognosis among women with gynecological malignancies, primarily because most ovarian cancers are diagnosed at late stage. Hence, there is a substantial need to develop new diagnostic biomarkers to enable detection of ovarian cancer at earlier stages, which would confer better prognosis. In addition, the identification of druggable targets is of substantial interest to find new therapeutic strategies for ovarian cancer.

METHODS

The expression of 22,500 genes in a series of 67 serous papillary carcinomas was compared with 9 crudely enriched normal ovarian tissue samples by RNA hybridization on oligonucleotide microarrays. Multiple genes with near-uniformly expression were elevated in carcinomas of varying grade and malignant potential, including several previously described genes (e.g., MUC-1, CD9, CD24, claudin 3, and mesothelin). We performed immunohistochemical staining with antibodies against several of the proteins encoded by differentially expressed genes in an independent cohort of 71 cases of paraffin-embedded ovarian cancer samples.

RESULTS

We found striking differences in EpCAM (p < 0.005), CD9 (p < 0.001), MUC-1 (p < 0.001), and claudin 3 proteins (p < 0.001) but not for mesothelin (p > 0.05) using the Mann-Whitney U test.

CONCLUSIONS

Protein expression of a majority of the differentially expressed genes tested was found to be elevated in ovarian carcinomas and, as such, define potential new biomarkers or targets.