Biomarkers In Serous Ovarian Cancer Research Articles

Discovery and ranking of the most robust prognostic biomarkers in serous ovarian cancer

Progress in ovarian cancer treatment lags behind other tumor types. With diagnosis usually at an advanced stage, there is a high demand for reliable prognostic biomarkers capable of the selection of effective chemo- and targeted therapies. Our goal was to establish a large-scale transcriptomic database and use it to uncover and rank survival-associated genes. Ovarian cancer cohorts with transcriptome-level gene expression data and clinical follow-up were identified from public repositories. All samples were normalized and entered into an integrated database. Cox univariate survival analysis was performed for all genes and was followed by multivariate analysis for selected genes involving clinical and pathological variables. False discovery rate was computed for multiple hypothesis testing and a 1% cutoff was used to determine statistical significance. The complete integrated database comprises 1816 samples from 17 datasets. Altogether, 2468 genes were correlated to progression-free survival (PFS), and 704 genes were correlated with overall survival (OS). The most significant genes were WBP1L, ASAP3, CNNM2, and NCAPH2 for progression-free survival and CSE1L, NUAK1, ALPK2, and SHKBP1 for overall survival. Genes significant for PFS were also preferentially significant for predicting OS as well. All data including HR and p values as well as the used cutoff values for all genes for both PFS and OS are provided to enable the ranking of future biomarker candidates across all genes. Our results help to prioritize genes and to neglect those which are most likely to fail in studies aiming to establish new clinically useful biomarkers and therapeutic targets in serous ovarian cancer.

Identification of an Individualized Prognostic Biomarker for Serous Ovarian Cancer: A Qualitative Model.

Serous ovarian cancer is the most common type of ovarian epithelial cancer and usually has a poor prognosis. The objective of this study was to construct an individualized prognostic model for predicting overall survival in serous ovarian cancer. Based on the relative expression orderings (Ea > Eb/Ea ≤ Eb) of gene pairs closely associated with serous ovarian prognosis, we tried constructing a potential individualized qualitative biomarker by the greedy algorithm and evaluated the performance in independent validation datasets. We constructed a prognostic biomarker consisting of 20 gene pairs (SOV-P20). The overall survival between high- and low-risk groups stratified by SOV-P20 was statistically significantly different in the training and independent validation datasets from other platforms (p < 0.05, Wilcoxon test). The average area under the curve (AUC) values of the training and three validation datasets were 0.756, 0.590, 0.630, and 0.680, respectively. The distribution of most immune cells between high- and low-risk groups was quite different (p < 0.001, Wilcoxon test). The low-risk patients tended to show significantly better tumor response to chemotherapy than the high-risk patients (p < 0.05, Fisher's exact test). SOV-P20 achieved the highest mean index of concordance (C-index) (0.624) compared with the other seven existing prognostic signatures (ranging from 0.511 to 0.619). SOV-P20 is a promising prognostic biomarker for serous ovarian cancer, which will be applicable for clinical predictive risk assessment.

BDP1 as a biomarker in serous ovarian cancer.

TFIIIB, an RNA polymerase III specific transcription factor has been found to be deregulated in human cancers with much of the research focused on the TBP, BRF1, and BRF2 subunits. To date, the TFIIIB specific subunit BDP1 has not been investigated in ovarian cancer but has previously been shown to be deregulated in neuroblastoma, breast cancer, and Non-Hodgkins lymphoma. Using in silico analysis of clinically derived platforms, we report a decreased BDP1 expression as a result of deletion in serous ovarian cancer and a correlation with higher and advanced ovarian stages. Further analysis in the context of TP53 mutations, a major contributor to ovarian tumorigenesis, suggests that high BDP1 expression is unfavorable for overall survival and high BDP1 expression occurs in stages 2, 3 and 4 serous ovarian cancer. Additionally, high BDP1 expression is disadvantageous and unfavorable for progression-free survival. Lastly, BDP1 expression significantly decreased in patients treated with first-line chemotherapy, platin and taxane, at twelve-month relapse-free survival. Taken together with a ROC analysis, the data suggest BDP1 could be of clinical relevance as a predictive biomarker in serous ovarian cancer. Lastly, this study further demonstrates that both the over- and under expression of BDP1 warrants further investigation and suggests BDP1 may exhibit dual function in the context of tumorigenesis.

Expression and Clinical Significance of Microtubule-Actin Cross-Linking Factor 1 in Serous Ovarian Cancer.

Ovarian Cancer (OC) remains the first leading cause of gynecologic malignancy. The survival rate from Serous Ovarian Cancer (SOC) is very low, and the present prognostic predictors of SOC are not very sensitive or specific. The present study aimed to investigate Microtubule-Actin Cross-Linking Factor 1 (MACF1) expression in SOC tissues (including paraffin-embedded and fresh tissues) and to assess its expression and significant value in patients with SOC. A total of 18 fresh SOC tissues and their paired paratumor tissues were performed with reverse-transcription quantitative PCR analysis to detect MACF1 mRNA expression. Moreover, 175 paraffin-embedded SOC tissues and 41 paratumor tissues were assessed for MACF1 expression using immunohistochemistry. The mRNA and protein expression of MACF1, both were higher in cancer tissues than that in paratumor tissues, and the high expression of MACF1 was associated with shorter Recurrence Free Survival (RFS) and Overall Survival (OS) in patients with SOC. Furthermore, multivariate regression analysis showed that high MACF1 expression was an independent poor survival predictor of patients with SOC. MACF1 is upregulated in SOC, and it may be used as a useful prognostic biomarker in SOC.

MLH1 Is a Prognostic Biomarker for Serous Ovarian Cancer Treated With Platinum- and Taxane-based Chemotherapy.

The potential of the DNA mismatch repair (MMR) system as a prognostic predictor has been evaluated in several cancer types. However, associations between MMR and the prognostic factors of ovarian cancer are poorly understood. MLH1 expression was evaluated by immunohistochemistry in patients with advanced serous ovarian cancer treated with platinum- and taxane-based chemotherapy. Associations between MLH1 expression and clinicopathological factors as well as claudin-4 expression were examined. Low MLH1 expression was significantly associated with increased progression-free and overall survival, and a normalisation of CA125 levels after chemotherapy. Additionally, low claudin-4 expression was more frequently found among the group with low MLH1 expression. Low MLH1 expression was associated with improved prognosis and is a possible predictor of the chemosensitivity of ovarian cancer. Claudin-4 might be involved in the molecular mechanisms underlying how MLH1 influences survival and chemosensitivity in patients with ovarian cancer.

Expression of potential biomarkers associated with homologous recombination repair in patients with ovarian or triple-negative breast cancer.

Poly(ADP)-ribose polymerase (PARP) inhibitors such as olaparib can induce cell death in cancer cells with homologous recombination (HR) DNA repair deficiencies, such as BRCA1/2 mutations. To identify prognostic biomarkers of long-term outcomes in cancer patients. Immunohistochemistry was used to analyse expression of key HR pathway proteins (ATM, ATR, BRCA1, MDC1, MRE11) and PARP-1 in 100 serous ovarian cancer (SOC) and 100 triple-negative breast cancer (TNBC) tumour samples from Japanese patients. RECIST assessment was used. Patient demographic data and BRCA1/2 mutation status were unavailable. Most proteins listed previously were detected in > 80% of tissue samples, with BRCA1 expression detected in 60-65%. A potential link between BRCA1 expression and overall survival (M stage adjusted) in SOC patients was observed, but was not statistically significant after multiple testing adjustment. Correlations between other biomarker expression and survival were not observed. In TNBC patients, MDC1 staining was associated with progressive disease, but this was not statistically significant; the analysis did not identify significant correlations between biomarker expression and disease control. Limited event numbers prevented assessment of the prognostic value of BRCA1 in TNBC. BRCA1 expression may be a candidate for a prognostic biomarker in SOC. Further studies are warranted.

Mitochondrial estrogen receptor β2 drives antiapoptotic pathways in advanced serous ovarian cancer.

We previously showed an unfavorable prognostic role of the cytoplasmic estrogen receptor β2 (cERβ2) in serous ovarian cancer. Here we aimed to investigate molecular determinants in cell survival function of cERβ2 in this malignant disease. We used immunohistochemistry to evaluate differences in apoptosis (quantified by the expression of cleaved caspase-3) and cell proliferation (quantified by the expression of Ki-67) in 56 advanced serous ovarian cancer cases, stratified according to the absence or presence of estrogen receptor β2 (ERβ2) protein in the cytoplasmic compartment (31 cERβ2- and 25 cERβ2+ cases, respectively). Thereafter, by immunofluorescence, we visualized the subcellular distribution of ERβ2, and by the proximity ligation assays, we characterized in situ its ability to interact with other proteins specifically involved in the apoptosis cascade. Finally, we assessed cytochrome c expression by immunohistochemistry. We demonstrated that, although not affecting tumor proliferation, cytoplasmic ERβ2 expression was indeed associated to a lower apoptotic rate in ovarian cancer cases. Then, we proved that cERβ2 is targeted to mitochondria where it interacts as a binding partner with BAD (B-cell lymphoma [Bcl] 2-associated death promoter). This interaction, precluding the Bcl-xL (B-cell lymphoma extra large)/BAD heterodimer formation, inhibited Bax (Bcl-2-like protein 4) oligomerization, the release of cytochrome c, and ultimately apoptosis. In conclusion, we provide in vivo mechanistic evidence for an antiapoptotic function of mitochondrial ERβ2, a finding supporting the value of its cytoplasmic expression as an unfavorable prognostic biomarker for serous ovarian cancer.

Detection of MicroRNA as Novel Biomarkers of Epithelial Ovarian Cancer From the Serum of Ovarian Cancer Patient

MicroRNA (miRNA) is an abundant class of small noncoding RNAs that act as gene regulators. Recent studies have suggested that miRNA deregulation is associated with the initiation and progression of human cancer. However, information about cancer-related miRNA is mostly limited to tissue miRNA. The aim of this study was to find specific profiles of serum-derived miRNAs of ovarian cancer based on a comparative study using a miRNA microarray of serum, tissue, and ascites. From 2 ovarian cancer patients and a healthy control, total RNA was isolated from their serum, tissue, and ascites, respectively, and analyzed by a microarray. Under the comparative study of each miRNA microarray, we sorted out several miRNAs showing a consistent regulation tendency throughout all 3 specimens and the greatest range of alteration in serum as potential biomarkers. The availability of biomarkers was confirmed by qRT-PCR of 18 patients and 12 controls. Out of 2222 kinds of total miRNAs that were identified in the microarray analysis, 95 miRNAs were down-regulated and 88 miRNAs were up-regulated, in the serum, tissue, and ascites of cancer patients. Among the miRNAs that showed a consistent regulation tendency through all specimens and showed more than a 2-fold difference in serum, 5 miRNAs (miR-132, miR-26a, let-7b, miR-145, and miR-143) were determined as the 5 most markedly down-regulated miRNAs in the serum from ovarian cancer patients with respect to those of controls. Four miRNAs (miR-132, miR-26a, let-7b, and miR-145) out of 5 selected miRNAs were significantly underexpressed in the serum of ovarian cancer patients in qRT-PCR. Serum miR-132, miR-26a, let-7b, and miR-145 could be considered as potential candidates as novel biomarkers in serous ovarian cancer. Also, serum miRNAs is a promising and useful tool for discriminating between controls and patients with serous ovarian cancer.

Identification of Receptor Tyrosine Kinase, Discoidin Domain Receptor 1 (DDR1), as a Potential Biomarker for Serous Ovarian Cancer

Ovarian cancer, one of the most common gynecological malignancies, has an aggressive phenotype. It is necessary to develop novel and more effective treatment strategies against advanced disease. Protein tyrosine kinases (PTKs) play an important role in the signal transduction pathways involved in tumorigenesis, and represent potential targets for anticancer therapies. In this study, we performed cDNA subtraction following polymerase chain reaction (PCR) using degenerate oligonucleotide primers to identify specifically overexpressed PTKs in ovarian cancer. Three PTKs, janus kinase 1, insulin-like growth factor 1 receptor, and discoidin domain receptor 1 (DDR1), were identified and only DDR1 was overexpressed in all ovarian cancer tissues examined for the validation by quantitative real-time PCR. The DDR1 protein was expressed in 63% (42/67) of serous ovarian cancer tissue, whereas it was undetectable in normal ovarian surface epithelium. DDR1 was expressed significantly more frequently in high-grade (79%) and advanced stage (77%) tumors compared to low-grade (50%) and early stage (43%) tumors. The expression of the DDR1 protein significantly correlated with poor disease-free survival. Although its functional role and clinical utility remain to be examined in future studies, our results suggest that the expression of DDR1 may serve as both a potential biomarker and a molecular target for advanced ovarian cancer.

P53 Autoantibodies as Potential Detection and Prognostic Biomarkers in Serous Ovarian Cancer

p53 Autoantibodies as Potential Detection and Prognostic Biomarkers in Serous Ovarian Cancer

P53 Autoantibodies as Potential Detection and Prognostic Biomarkers in Serous Ovarian Cancer

This study examined the value of serum p53 autoantibodies (p53-AAb) as detection and prognostic biomarkers in ovarian cancer. p53-AAb were detected by ELISA in sera obtained preoperatively from women undergoing surgery for a pelvic mass. This group included women subsequently diagnosed with invasive serous ovarian cancer (n = 60), nonserous ovarian cancers (n = 30), and women with benign disease (n = 30). Age-matched controls were selected from the general population (n = 120). Receiver operating characteristic curves were constructed to compare the values of p53-AAb, CA 125, and HE4 as a screening biomarker. Kaplan-Meier curves and Cox proportional hazards modeling were used to assess its prognostic value on survival. p53-AAb were detected in 25 of 60 (41.7%) of serous cases, 4 of 30 (13.3%) nonserous cases, 3 of 30 (10%) benign disease cases, and 10 of 120 (8.3%) controls (combined P = 0.0002). p53-AAb did not significantly improve the detection of cases [area under the curve (AUC), 0.69] or the discrimination of benign versus malignant disease (AUC, 0.64) compared with CA 125 (AUC, 0.99) or HE4 (AUC, 0.98). In multivariate analysis among cases, p53-AAb correlated only with a family history of breast cancer (P = 0.01). Detectable p53 antibodies in pretreatment sera were correlated with improved overall survival (P = 0.04; hazard ratio, 0.57; 95% confidence interval, 0.33-0.97) in serous ovarian cancer. Antibodies to p53 are detected in the sera of 42% of patients with advanced serous ovarian cancer. Although their utility as a preoperative diagnostic biomarker, beyond CA 125 and HE4, is limited, p53-AAb are prognostic for improved overall survival.