Molecular scores to predict ovarian cancer outcomes: a worthy goal, but not ready for prime time

Noncanonical NF-κB factor p100/p52 regulates homologous recombination and modulates sensitivity to DNA-damaging therapy

Homologous recombination (HR) serves multiple roles in DNA repair that are essential for maintaining genomic stability, including double-strand DNA break (DSB) repair. The central HR protein, RAD51, is frequently overexpressed in human malignancies, thereby elevating HR proficiency and promoting resistance to DNA-damaging therapies. Here, we find that the non-canonical NF-κB factors p100/52, but not RelB, control the expression of RAD51 in various human cancer subtypes. While p100/p52 depletion inhibits HR function in human tumor cells, it does not significantly influence the proficiency of non-homologous end joining, the other key mechanism of DSB repair. Clonogenic survival assays were performed using a pair DLD-1 cell lines that differ only in their expression of the key HR protein BRCA2. Targeted silencing of p100/p52 sensitizes the HR-competent cells to camptothecin, while sensitization is absent in HR-deficient control cells. These results suggest that p100/p52-dependent signaling specifically controls HR activity in cancer cells. Since non-canonical NF-κB signaling is known to be activated after various forms of genomic crisis, compensatory HR upregulation may represent a natural consequence of DNA damage. We propose that p100/p52-dependent signaling represents a promising oncologic target in combination with DNA-damaging treatments.

Modeling Between-Study Heterogeneity for Improved Replicability in Gene Signature Selection and Clinical Prediction

In the genomic era, the identification of gene signatures associated with disease is of significant interest. Such signatures are often used to predict clinical outcomes in new patients and aid clinical decision-making. However, recent studies have shown that gene signatures are often not replicable. This occurrence has practical implications regarding the generalizability and clinical applicability of such signatures. To improve replicability, we introduce a novel approach to select gene signatures from multiple datasets whose effects are consistently non-zero and account for between-study heterogeneity. We build our model upon some rank-based quantities, facilitating integration over different genomic datasets. A high dimensional penalized Generalized Linear Mixed Model (pGLMM) is used to select gene signatures and address data heterogeneity. We compare our method to some commonly used strategies that select gene signatures ignoring between-study heterogeneity. We provide asymptotic results justifying the performance of our method and demonstrate its advantage in the presence of heterogeneity through thorough simulation studies. Lastly, we motivate our method through a case study subtyping pancreatic cancer patients from four gene expression studies.

Double-negative feedback interaction between DNA methyltransferase 3A and microRNA-145 in the Warburg effect of ovarian cancer cells

Ovarian cancer is the most lethal gynecological malignancy because of its poor prognosis. The Warburg effect is one of the key mechanisms mediating cancer progression. Molecules targeting the Warburg effect are therefore of significant therapeutic value for the treatment of cancers. Many microRNAs (miR) are dysregulated in cancers, and aberrant miR expression patterns have been suggested to correlate with the Warburg effect in cancer cells. In our study, we found that miR-145 negatively correlated with DNA methyltransferase (DNMT)3A expression at cellular/histological levels. miR-145 inhibited the Warburg effect by targeting HK2. Luciferase reporter assays confirmed that miR-145-mediated downregulation of DNMT3A occurred through direct targeting of its mRNA 3'-UTRs, whereas methylation-specific PCR (MSP) assays found that knockdown of DNMT3A increased mRNA level of miR-145 and decreased methylation levels of promoter regions in the miR-145 precursor gene, thus suggesting a crucial crosstalk between miR-145 and DNMT3A by a double-negative feedback loop. DNMT3A promoted the Warburg effect through miR-145. Coimmunoprecipitation assays confirmed no direct binding between DNMT3A and HK2. In conclusion, a feedback loop between miR-145 and DNMT3A is a potent signature for the Warburg effect in ovarian cancer, promising a potential target for improved anticancer treatment.

Euxanthone inhibits glycolysis and triggers mitochondria-mediated apoptosis by targeting hexokinase 2 in epithelial ovarian cancer

Epithelial ovarian cancer (EOC) is one of the most prevalent gynaecological cancers. Euxanthone, an active ingredient of the medicinal plant Polygala caudata, exhibits a selective cytotoxic effect in tumour cells. The present study was aimed to determine whether euxanthone could suppress ovarian tumour growth, and to study the relevant mechanism. Two EOC cell lines, SKOV3 and A2780, were used as the in vitro model and treated with euxanthone. Cell viability and apoptosis were assayed using Cell Counting Kit-8 (CCK-8) and Annexin-V FITC/PI staining, respectively. Commercially available kits were used to measure the glucose consumption, lactate production, and intracellular ATP levels. Western blots assay was conducted to examine the level of apoptotic markers. To examine the roles of HK2 and STAT3 in the anti-tumour effect of euxanthone, cells were transfected with vectors overexpressing HK2 or STAT3, and assayed as above. Finally, SKOV3 cells were injected to mice models to appreciate the anti-neoplastic effect of euxanthone in vivo. We found that euxanthone impaired the cell viability and induced apoptosis via the intrinsic pathway in a concentration-dependent fashion in both SKOV3 and A2780 cells. Euxanthone also caused inhibition of glycolysis. Apoptosis and glycolysis inhibition was mediated by the downregulation of HK2, which in turn was a result of STAT3 inactivation. In vivo experiments also supported that euxanthone could exert anti-cancer activities without general toxicity. In conclusion, euxanthone triggered mitochondrial apoptosis and inhibited glycolysis in EOC cells.

SIGNIFICANCE OF THE STUDY

Euxanthone triggered mitochondrial apoptosis and inhibited glycolysis in EOC cells. Our findings provide preliminary experimental data that support further studies on the potential therapeutic role of euxanthone in ovarian cancer.

Effect of Ginsenoside Rh-2 via Activation of Caspase-3 and Bcl-2-Insensitive Pathway in Ovarian Cancer Cells

Ginsenoside has been reported to have therapeutic effects for some types of cancer, but its effect on ovarian cancer cells has not been evaluated. In this study, we monitored the effects of ginsenoside-Rh2 (Rh2) on the inhibition of cell proliferation and the apoptotic process in the ovarian cancer cell line SKOV3 using an MTT assay and TUNEL assay. We found that Rh2 inhibited cell proliferation and significantly induced apoptosis. We confirmed the apoptotic effects of Rh2 using western blot analysis of apoptosis-related proteins. Specifically, the levels of cleaved poly ADP ribose polymerase (PARP) and cleaved caspase-3 significantly increased in SKOV3 cells treated with Rh2. Therefore, Rh2 clearly suppressed the growth of SKOV3 cells in vitro, which was associated with induction of the apoptosis pathway. Moreover, the migration assay showed that Rh2 inhibited the invasive ability of SKOV3 cells. Taken together, our results suggest that Rh2 has anticancer effects in SKOV3 cells through inhibition of cell proliferation and induction of apoptosis. Considering the therapeutic potential of Rh2, more studies should be carried out to facilitate the future application of this natural product as a potential anti-cancer agent.

Single-sample expression-based chemo-sensitivity score improves survival associations independently from genomic mutations for ovarian cancer Patients

Platinum-based chemotherapies are first-line treatments for ovarian cancer (OC) patients. Although chemotherapy has a high initial response rate, some patients exhibit inherent chemo-resistance. With advancements of molecular and genomic profiling, it is of high interest to identify molecular and genomic signatures predictive of chemo- sensitivity priori to treatment initiation in order to better personalize care decisions. Previous efforts have made use of mRNA expression levels of selected genes responsible for repairing DNA damage, under the hypothesis that chemo efficacy is associated with their proficiency. However, the resulting scores have been difficult to interpret. In this study, we designed a single-sample based approach known as eCARD to investigate chemo-sensitivity in ovarian cancer patients from The Cancer Genome Atlas. We demonstrated that the proposed single-sample based approach can lead to a molecular-based chemo-sensitivity score predictive of prognosis, which validates in 5 independent cohorts, and associates with increasing mutation burden and likelihood of BRCA1/2 mutation.

Treatment monitoring of patients with epithelial ovarian cancer using invasive circulating tumor cells (iCTCs)

GOALS

Contemporary management of epithelial ovarian cancer (EOC) uses biomarkers to monitor response to therapy. This study evaluates the role of invasive circulating tumor cells (iCTCs) in monitoring EOC treatment in comparison with serum cancer antigen 125 (CA125).

METHODS

Molecular and microscopic analyses were used to identify seprase and CD44 as tumor progenitor (TP) markers. The iCTC flow cytometry assay was optimized using blood donated by 64 healthy donors, 49 patients with benign abdominal diseases and 123 EOC patients. Serial changes in iCTCs and CA125 were measured in 129 blood and 169 serum samples, respectively, from 31 EOC patients to assess their concordance during therapy and their relationship with risk of progressive disease (PD).

RESULTS

The assay had 97% specificity and 83% sensitivity for detecting iCTCs in blood of EOC patients. iCTCs were detected in each monitoring patient (31/31, 100%) and in 110 of the 129 blood samples (85.3%). The concordance between changes in iCTCs/CA125 levels and changes in the intervals associated with no evidence of disease (NED) were markedly stronger (specificity: CA125 93.8%; iCTCs 90.6%), whereas increases in iCTCs (79.5%) were more sensitive than increases in CA125 (67.6%) to predict PD or relapse. Among the six patients who had greater than 6 measurements, iCTCs but not CA125 antedated changes in clinical status from PD to NED during and after chemotherapy and predated relapse.

CONCLUSION

Serial measurements of iCTCs could predict therapeutic responsiveness in 31 EOC patients who underwent standard taxol/carboplatin therapy.

DNA repair pathway gene expression score correlates with repair proficiency and tumor sensitivity to chemotherapy

Mutagenesis is a hallmark of malignancy, and many oncologic treatments function by generating additional DNA damage. Therefore, DNA damage repair is centrally important in both carcinogenesis and cancer treatment. Homologous recombination (HR) and nonhomologous end joining are alternative pathways of double-strand DNA break repair. We developed a method to quantify the efficiency of DNA repair pathways in the context of cancer therapy. The recombination proficiency score (RPS) is based on the expression levels for four genes involved in DNA repair pathway preference (Rif1, PARI, RAD51, and Ku80), such that high expression of these genes yields a low RPS. Carcinoma cells with low RPS exhibit HR suppression and frequent DNA copy number alterations, which are characteristic of error-prone repair processes that arise in HR-deficient backgrounds. The RPS system was clinically validated in patients with breast or non-small cell lung carcinomas (NSCLCs). Tumors with low RPS were associated with greater mutagenesis, adverse clinical features, and inferior patient survival rates, suggesting that HR suppression contributes to the genomic instability that fuels malignant progression. This adverse prognosis associated with low RPS was diminished if NSCLC patients received adjuvant chemotherapy, suggesting that HR suppression and associated sensitivity to platinum-based drugs counteract the adverse prognosis associated with low RPS. Therefore, RPS may help oncologists select which therapies will be effective for individual patients, thereby enabling more personalized care.

Ginsenoside 20(S)‑Rg3 inhibits the Warburg effect through STAT3 pathways in ovarian cancer cells

Cancer cells prefer to metabolize glucose through aerobic glycolysis, known as the Warburg effect. It plays a crucial role in proliferation and progression of cancer cells. However, the complete mechanism remains elusive. In recent studies, the signal transducer and activator of transcription 3 (STAT3) signaling has been discovered to have roles in cancer‑associated changes in metabolism. In this study, we find that the ginsenoside 20(S)‑Rg3, a pharmacologically active component of the traditional Chinese herb Panax ginseng, inhibits glycolysis in ovarian cancer cells by regulating hexokinase 2 (HK2) and pyruvate kinase M2 (PKM2). We also show that 20(S)‑Rg3 regulates HK2 through downregulation of p‑STAT3 (Tyr705). Furthermore, overexpression of STAT3 in ovarian cancer cells weakened the suppression of Warburg effect induced by 20(S)‑Rg3. Importantly, 20(S)‑Rg3 treatment represses HK2 expression in nude mouse xenograft models of ovarian cancer. Taken together, our results show that 20(S)‑Rg3 inhibits the Warburg effect by targeting STAT3/HK2 pathway in ovarian cancer cells, highlighting the potentiality of 20(S)‑Rg3 to be used as a therapeutic agent for ovarian cancer.

Ginsenoside 20(S)-Rg3 targets HIF-1α to block hypoxia-induced epithelial-mesenchymal transition in ovarian cancer cells

The prognosis of patients with ovarian cancer has remained poor mainly because of aggressive cancer progression. Since epithelial-mesenchymal transition (EMT) is an important mechanism mediating invasion and metastasis of cancer cells, targeting the EMT process with more efficacious and less toxic compounds to inhibit metastasis is of great therapeutic value for the treatment of ovarian cancer. We have found for the first time that the ginsenoside 20(S)-Rg3, a pharmacologically active component of the traditional Chinese herb Panax ginseng, potently blocks hypoxia-induced EMT of ovarian cancer cells in vitro and in vivo. Mechanistic studies confirm the mode of action of 20(S)-Rg3, which reduces the expression of hypoxia-inducible factor 1α (HIF-1α) by activating the ubiquitin-proteasome pathway to promote HIF-1α degradation. A decrease in HIF-1α in turn leads to up-regulation, via transcriptional suppression of Snail, of the epithelial cell-specific marker E-cadherin and down-regulation of the mesenchymal cell-specific marker vimentin under hypoxic conditions. Importantly, 20(S)-Rg3 effectively inhibits EMT in nude mouse xenograft models of ovarian cancer, promising a novel therapeutic agent for anticancer therapy.

PALB2: the hub of a network of tumor suppressors involved in DNA damage responses

PALB2 was first identified as a partner of BRCA2 that mediates its recruitment to sites of DNA damage. PALB2 was subsequently found as a tumor suppressor gene. Inherited heterozygosity for this gene is associated with an increased risk of cancer of the breast and other sites. Additionally, biallelic mutation of PALB2 is linked to Fanconi anemia, which also has an increased risk of developing malignant disease. Recent work has identified numerous interactions of PALB2, suggesting that it functions in a network of proteins encoded by tumor suppressors. Notably, many of these tumor suppressors are related to the cellular response to DNA damage. The recruitment of PALB2 to DNA double-strand breaks at the head of this network is via a ubiquitin-dependent signaling pathway that involves the RAP80, Abraxas and BRCA1 tumor suppressors. Next, PALB2 interacts with BRCA2, which is a tumor suppressor, and with the RAD51 recombinase. These interactions promote DNA repair by homologous recombination (HR). More recently, PALB2 has been found to bind the RAD51 paralog, RAD51C, as well as the translesion polymerase pol η, both of which are tumor suppressors with functions in HR. Further, an interaction with MRG15, which is related to chromatin regulation, may facilitate DNA repair in damaged chromatin. Finally, PALB2 interacts with KEAP1, a regulator of the response to oxidative stress. The PALB2 network appears to mediate the maintenance of genome stability, may explain the association of many of the corresponding genes with similar spectra of tumors, and could present novel therapeutic opportunities.

Risk prediction for late-stage ovarian cancer by meta-analysis of 1525 patient samples

BACKGROUND

Ovarian cancer causes more than 15000 deaths per year in the United States. The survival of patients is quite heterogeneous, and accurate prognostic tools would help with the clinical management of these patients.

METHODS

We developed and validated two gene expression signatures, the first for predicting survival in advanced-stage, serous ovarian cancer and the second for predicting debulking status. We integrated 13 publicly available datasets totaling 1525 subjects. We trained prediction models using a meta-analysis variation on the compound covariable method, tested models by a "leave-one-dataset-out" procedure, and validated models in additional independent datasets. Selected genes from the debulking signature were validated by immunohistochemistry and quantitative reverse-transcription polymerase chain reaction (qRT-PCR) in two further independent cohorts of 179 and 78 patients, respectively. All statistical tests were two-sided.

RESULTS

The survival signature stratified patients into high- and low-risk groups (hazard ratio = 2.19; 95% confidence interval [CI] = 1.84 to 2.61) statistically significantly better than the TCGA signature (P = .04). POSTN, CXCL14, FAP, NUAK1, PTCH1, and TGFBR2 were validated by qRT-PCR (P < .05) and POSTN, CXCL14, and phosphorylated Smad2/3 were validated by immunohistochemistry (P < .001) as independent predictors of debulking status. The sum of immunohistochemistry intensities for these three proteins provided a tool that classified 92.8% of samples correctly in high- and low-risk groups for suboptimal debulking (area under the curve = 0.89; 95% CI = 0.84 to 0.93).

CONCLUSIONS

Our survival signature provides the most accurate and validated prognostic model for early- and advanced-stage high-grade, serous ovarian cancer. The debulking signature accurately predicts the outcome of cytoreductive surgery, potentially allowing for stratification of patients for primary vs secondary cytoreduction.

Comparative meta-analysis of prognostic gene signatures for late-stage ovarian cancer

BACKGROUND

Ovarian cancer is the fifth most common cause of cancer deaths in women in the United States. Numerous gene signatures of patient prognosis have been proposed, but diverse data and methods make these difficult to compare or use in a clinically meaningful way. We sought to identify successful published prognostic gene signatures through systematic validation using public data.

METHODS

A systematic review identified 14 prognostic models for late-stage ovarian cancer. For each, we evaluated its 1) reimplementation as described by the original study, 2) performance for prognosis of overall survival in independent data, and 3) performance compared with random gene signatures. We compared and ranked models by validation in 10 published datasets comprising 1251 primarily high-grade, late-stage serous ovarian cancer patients. All tests of statistical significance were two-sided.

RESULTS

Twelve published models had 95% confidence intervals of the C-index that did not include the null value of 0.5; eight outperformed 97.5% of signatures including the same number of randomly selected genes and trained on the same data. The four top-ranked models achieved overall validation C-indices of 0.56 to 0.60 and shared anticorrelation with expression of immune response pathways. Most models demonstrated lower accuracy in new datasets than in validation sets presented in their publication.

CONCLUSIONS

This analysis provides definitive support for a handful of prognostic models but also confirms that these require improvement to be of clinical value. This work addresses outstanding controversies in the ovarian cancer literature and provides a reproducible framework for meta-analytic evaluation of gene signatures.

Comparative meta-analysis of prognostic gene signatures for late-stage ovarian cancer

BACKGROUND

Ovarian cancer is the fifth most common cause of cancer deaths in women in the United States. Numerous gene signatures of patient prognosis have been proposed, but diverse data and methods make these difficult to compare or use in a clinically meaningful way. We sought to identify successful published prognostic gene signatures through systematic validation using public data.

METHODS

A systematic review identified 14 prognostic models for late-stage ovarian cancer. For each, we evaluated its 1) reimplementation as described by the original study, 2) performance for prognosis of overall survival in independent data, and 3) performance compared with random gene signatures. We compared and ranked models by validation in 10 published datasets comprising 1251 primarily high-grade, late-stage serous ovarian cancer patients. All tests of statistical significance were two-sided.

RESULTS

Twelve published models had 95% confidence intervals of the C-index that did not include the null value of 0.5; eight outperformed 97.5% of signatures including the same number of randomly selected genes and trained on the same data. The four top-ranked models achieved overall validation C-indices of 0.56 to 0.60 and shared anticorrelation with expression of immune response pathways. Most models demonstrated lower accuracy in new datasets than in validation sets presented in their publication.

CONCLUSIONS

This analysis provides definitive support for a handful of prognostic models but also confirms that these require improvement to be of clinical value. This work addresses outstanding controversies in the ovarian cancer literature and provides a reproducible framework for meta-analytic evaluation of gene signatures.

Risk prediction for late-stage ovarian cancer by meta-analysis of 1525 patient samples

BACKGROUND

Ovarian cancer causes more than 15000 deaths per year in the United States. The survival of patients is quite heterogeneous, and accurate prognostic tools would help with the clinical management of these patients.

METHODS

We developed and validated two gene expression signatures, the first for predicting survival in advanced-stage, serous ovarian cancer and the second for predicting debulking status. We integrated 13 publicly available datasets totaling 1525 subjects. We trained prediction models using a meta-analysis variation on the compound covariable method, tested models by a "leave-one-dataset-out" procedure, and validated models in additional independent datasets. Selected genes from the debulking signature were validated by immunohistochemistry and quantitative reverse-transcription polymerase chain reaction (qRT-PCR) in two further independent cohorts of 179 and 78 patients, respectively. All statistical tests were two-sided.

RESULTS

The survival signature stratified patients into high- and low-risk groups (hazard ratio = 2.19; 95% confidence interval [CI] = 1.84 to 2.61) statistically significantly better than the TCGA signature (P = .04). POSTN, CXCL14, FAP, NUAK1, PTCH1, and TGFBR2 were validated by qRT-PCR (P < .05) and POSTN, CXCL14, and phosphorylated Smad2/3 were validated by immunohistochemistry (P < .001) as independent predictors of debulking status. The sum of immunohistochemistry intensities for these three proteins provided a tool that classified 92.8% of samples correctly in high- and low-risk groups for suboptimal debulking (area under the curve = 0.89; 95% CI = 0.84 to 0.93).

CONCLUSIONS

Our survival signature provides the most accurate and validated prognostic model for early- and advanced-stage high-grade, serous ovarian cancer. The debulking signature accurately predicts the outcome of cytoreductive surgery, potentially allowing for stratification of patients for primary vs secondary cytoreduction.

Ovarian cancer: targeting the untargetable

The premise that all tumors are targetable has been met with some controversy in the approach to epithelial ovarian cancer (EOC). Genomic analysis shows that these tumors (specifically, high-grade serous carcinomas) are genomically unstable and lack actionable driver mutations, much like HER2 in breast and gastric cancers. In this paper, Michael Birrer, MD, PhD, Massachusetts General Hospital, argues that the interpretation of genomic data in ovarian cancer requires a more thoughtful approach that necessitates a closer inspection of the data beyond the mere presence or absence of mutations. We must look at the extensive genomic alterations in DNA and, to understand more about the role of those genes affected by these changes, look beyond the tumor to the role of the stroma. As such, Dr. Birrer is arguing for the importance of translational research. This will be the key to precision medicine in ovarian cancer, as we approach drug discovery and improvements in treatment. Dr. Birrer is a world-renowned scientist who has devoted his career to the study of gynecologic cancers. He has published over 200 papers and written over 27 book chapters and reviews, served on numerous leadership positions in gynecologic oncology (including as co-chair of the National Cancer Institute's Gynecologic Cancer Steering Committee), and remains a clinician-scientist with an active lab and an active clinic. His career trajectory has shown me it is possible to be engaged as a researcher and a clinician and the work he has done has already impacted the care of patients with ovarian cancer. Don S. Dizon, MD, ASCO Educational Book Editor.

Clinical value of protein expression of kallikrein-related peptidase 7 (KLK7) in ovarian cancer

Expression of the kallikrein-related peptidase 7 (KLK7) is dysregulated in ovarian cancer. We assessed KLK7 expression by ELISA and quantitative immunohistochemistry and analyzed its association with clinicopathological parameters and patients’ outcome. KLK7 antigen concentrations were determined in tumor tissue extracts of 98 ovarian cancer patients by ELISA. For analysis of KLK7 immunoexpression in ovarian cancer tissue microarrays, a manual quantitative scoring system as well as a software tool for quantitative high-throughput automated image analysis was used. In immunohistochemical analyses, expression levels of KLK7 were not associated with patients’ outcome. However, in multivariate analyses, KLK7 antigen levels in tumor tissue extracts were significantly associated with both overall and progression-free survival: ovarian cancer patients with high KLK7 levels had a significantly, 2-fold lower risk of death [hazard ratio (HR)=0.51, 95% confidence interval (CI)=0.29–0.90, p=0.019] or relapse [HR=0.47, 95% CI=0.25–0.91, p=0.024), as compared with patients who displayed low KLK7 levels. Our results indicate that – in contrast to earlier findings – high KLK7 antigen levels in tumor tissue extracts may be associated with a better prognosis of ovarian cancer patients.

Nibrin is a marker of clinical outcome in patients with advanced serous ovarian cancer treated in the phase III OVA-301 trial

OBJECTIVE

This study investigated the relationship between 13 proteins involved in DNA damage and the outcomes of patients with recurrent ovarian cancer (ROC).

PATIENTS AND METHODS

Immunohistochemistry staining was performed in 114 diagnostic samples from patients with serous ROC who participated in the OVA-301 study, which compared pegylated liposomal doxorubicin (PLD) with a combination of trabectedin plus PLD. Percentage of positive cells for every marker was calculated and correlated with overall response rate (ORR), progression-free survival (PFS) and overall survival (OS).

RESULTS

A statistically significant correlation between high levels of nibrin and lower ORR (P=0.03), shorter PFS (P=0.007) and shorter OS (P=0.01) was observed. After stratification, in patients with platinum-sensitive disease treated with the combination of trabectedin plus PLD, high levels of nibrin correlated with lower ORR (P=0.01) and shorter PFS (P=0.02). A better clinical outcome (ORR, PFS and OS) was also associated to low levels of CHK2 in trabectedin plus PLD treated patients. No correlations were found in PLD-treated patients. According to the results of a multivariate analysis, there was a statistically significant correlation between high nibrin (P=0.001) and low BRCA2 levels (P=0.03) and a worse PFS, and between high nibrin levels and a worse OS (P=0.006).

CONCLUSION

Our results indicate that high nibrin expression seems to be associated with a worse clinical outcome in serous ROC, particularly in patients treated with the combination trabectedin plus PLD. Prospective studies to determine clinical usefulness of nibrin as a possible biomarker in other series of patients with ROC are warranted.