Identification of stably expressed microRNAs in plasma from high-grade serous ovarian carcinoma and benign tumor patients.

BACKGROUND: Ovarian cancer is a lethal gynecological cancer and no reliable minimally invasive early diagnosis tools exist. High grade serous ovarian carcinoma (HGSOC) is often diagnosed at advanced stages, resulting in poorer outcome than those diagnosed in early stage. Circulating microRNAs have been investigated for their biomarker potential. However, due to lack of standardization methods for microRNA detection, there is no consensus, which microRNAs should be used as stable endogenous controls. We aimed to identify microRNAs that are stably expressed in plasma of HGSOC and benign ovarian tumor patients. METHODS AND RESULTS: We isolated RNA from plasma samples of 60 HGSOC and 48 benign patients. RT-qPCR was accomplished with a custom panel covering 40 microRNAs and 8 controls. Stability analysis was performed using five algorithms: Normfinder, geNorm, Delta-Ct, BestKeeper and RefFinder using an R-package; RefSeeker developed by our study group [1]. Among 41 analyzed RNAs, 13 were present in all samples and eligible for stability analysis. Differences between stability rankings were observed across algorithms. In HGSOC samples, hsa-miR-126-3p and hsa-miR-23a-3p were identified as the two most stable miRNAs. In benign samples, hsa-miR-191-5p and hsa-miR-27a-3p were most stable. In the combined HGSOC and benign group, hsa-miR-23a-3p and hsa-miR-27a-3p were identified by both the RefFinder and Normfinder analysis as the most stable miRNAs. CONCLUSIONS: Consensus regarding normalization approaches in microRNA studies is needed. The choice of endogenous microRNAs used for normalization depends on the histological content of the cohort. Furthermore, normalization also depends on the algorithms used for stability analysis.

The influence of insulin-related genetic variants on fetal growth, fetal blood flow, and placental weight in a prospective pregnancy cohort.

The fetal insulin hypothesis proposes that low birthweight and type 2 diabetes (T2D) in adulthood may be two phenotypes of the same genotype. In this study we aimed to explore this theory further by testing the effects of GWAS-identified genetic variants related to insulin release and sensitivity on fetal growth and blood flow from week 20 of gestation to birth and on placental weight at birth. We calculated genetic risk scores (GRS) of first phase insulin release (FPIR), fasting insulin (FI), combined insulin resistance and dyslipidaemia (IR + DLD) and insulin sensitivity (IS) in a study population of 665 genotyped newborns. Two-dimensional ultrasound measurements with estimation of fetal weight and blood flow were carried out at week 20, 25, and 32 of gestation in all 665 pregnancies. Birthweight and placental weight were registered at birth. Associations between the GRSs and fetal growth, blood flow and placental weight were investigated using linear mixed models. The FPIR GRS was directly associated with fetal growth from week 20 to birth, and both the FI GRS, IR + DLD GRS, and IS GRS were associated with placental weight at birth. Our findings indicate that insulin-related genetic variants might primarily affect fetal growth via the placenta.

Are we ready for translational research based on material and data from the Danish CancerBiobank and can we gain new knowledge from biobank registration?

Bio-and GenomeBank, Denmark (RBGB) is a nationwide infra-structure. Danish CancerBiobank (DCB) is a biobank in RBGB. The aim is to describe the degree of biological material collected and stored in DCB for patients diagnosed with primary ovarian cancer registered in The Danish Gynecologic Cancer Database (DGCD). Furthermore, to investigate the concordance between predicted organ of disease registered in RBGB at time of sampling (presumed diagnosis) with final diagnosis for patient. Data extraction from DGCD and DCB. Biological materials are present for 1.347 (62%) of 2.172 patients with primary ovarian cancer (OC). The median age of OC patients were 68 years (range: 18-90 years). Median age of patients with biological material in DCB was 67 years and for patients without biological material in DCB 69 years (p ≤ 0.0001). The histological subtypes for the 1347 OC patients with biological material were 911 (68%) serous adenocarcinoma, 97 (7%) endometrioid adenocarcinoma, 80 (6%) mucinous adenocarcinoma, 58 (4%) clear cell carcinoma, and for 201 (15%) no information were registered. For 327 patients (24%), the presumed diagnosis was hematological with a final diagnosis of OC. Using clinical data and biological material including pre-analytical data regarding the biological material the possibility for translational research is optimal. Furthermore, information registered through daily working procedures may propose the need for additional biomarkers to aid clinicians to stratify patients to treatment in correct fast-track packages.

Expression Stability Analysis of Candidate References for Normalization of RT-qPCR Data Using RefSeeker R package.

When performing expression analysis either for coding RNA (e.g., mRNA) or non-coding RNA (e.g., miRNA), reverse transcription quantitative real-time polymerase chain reaction (RT-qPCR) is a widely used method. To normalize these data, one or more stable endogenous references must be identified. RefFinder is an online web-based tool using four almost universally used algorithms for assessing candidate endogenous references-delta-Ct, BestKeeper, geNorm, and Normfinder. However, the online interface is presently cumbersome and time consuming. We developed an R package, RefSeeker, which performs easy and straightforward RefFinder analysis by enabling raw data import and calculation of stability from each of the algorithms and provides data output tools to create graphs and tables. This protocol uses RefSeeker R package for fast and simple RefFinder stability analysis. Key features Perform stability analysis using five algorithms: Normfinder, geNorm, delta-Ct, BestKeeper, and RefFinder. Identification of endogenous references for normalization of RT-qPCR data. Create publication-ready graphs and tables output. Step-by-step guide dialog window for novice R users.

Strategies for data normalization and missing data imputation and consequences for potential diagnostic microRNA biomarkers in epithelial ovarian cancer.

MicroRNAs (miRNAs) are small non-coding RNA molecules regulating gene expression with diagnostic potential in different diseases, including epithelial ovarian carcinomas (EOC). As only a few studies have been published on the identification of stable endogenous miRNA in EOC, there is no consensus which miRNAs should be used aiming standardization. Currently, U6-snRNA is widely adopted as a normalization control in RT-qPCR when investigating miRNAs in EOC; despite its variable expression across cancers being reported. Therefore, our goal was to compare different missing data and normalization approaches to investigate their impact on the choice of stable endogenous controls and subsequent survival analysis while performing expression analysis of miRNAs by RT-qPCR in most frequent subtype of EOC: high-grade serous carcinoma (HGSC). 40 miRNAs were included based on their potential as stable endogenous controls or as biomarkers in EOC. Following RNA extraction from formalin-fixed paraffin embedded tissues from 63 HGSC patients, RT-qPCR was performed with a custom panel covering 40 target miRNAs and 8 controls. The raw data was analyzed by applying various strategies regarding choosing stable endogenous controls (geNorm, BestKeeper, NormFinder, the comparative ΔCt method and RefFinder), missing data (single/multiple imputation), and normalization (endogenous miRNA controls, U6-snRNA or global mean). Based on our study, we propose hsa-miR-23a-3p and hsa-miR-193a-5p, but not U6-snRNA as endogenous controls in HGSC patients. Our findings are validated in two external cohorts retrieved from the NCBI Gene Expression Omnibus database. We present that the outcome of stability analysis depends on the histological composition of the cohort, and it might suggest unique pattern of miRNA stability profiles for each subtype of EOC. Moreover, our data demonstrates the challenge of miRNA data analysis by presenting various outcomes from normalization and missing data imputation strategies on survival analysis.

Randomised phase II trial of stereotactic body radiotherapy in combination with checkpoint inhibitors in metastatic castration-resistant prostate cancer (CheckPRO): a study protocol.

INTRODUCTION: Immunotherapy with checkpoint inhibitors (CPIs) has revolutionised cancer treatment but has no convincing effect in metastatic castration-resistant prostate cancer (mCRPC). It has been suggested that a combination of CPI and hypofractionated stereotactic body radiotherapy (SBRT) may work synergistically, and recent trials have supported this. We hypothesise that adding SBRT to CPI treatment can improve response rates in patients with mCRPC. METHODS AND ANALYSIS: The CheckPRO trial is an open-label, randomised, two-stage, phase II trial. We aim to enrol and randomise 80 evaluable patients with mCRPC who progressed following ≥2 lines of treatment. Enrolment started in November 2019 with 38 months expected enrolment period. The participants receive treatment for 52 weeks including four cycles of ipilimumab and nivolumab with or without concomitant SBRT (24 Gray in three fractions) to a single soft tissue or bone metastasis, followed by 10 cycles of nivolumab. Participants are followed until progression, death, or for 12 months after the end of treatment.Co-primary endpoints are the objective response rate and prostate-specific antigen (PSA) response rate. Secondary endpoints include safety, radiographic progression-free survival, clinical benefit rate, duration of response, PSA-progression-free survival beyond 12 weeks, quality of life and overall survival. Exploratory endpoints include translational analyses of tumour biopsies and consecutive blood samples. Biopsies from metastatic sites are collected at baseline, before the third treatment and at the end of treatment. Blood sampling for immune monitoring and circulating tumour DNA is performed consecutively at baseline and every radiographic assessment. ETHICS AND DISSEMINATION: This study follows the Helsinki Declaration and is approved by the Danish Ethics Committee System (journal no. H-19016100). All participants must receive written and oral information and provide a signed informed consent document prior to inclusion. The study results will be published in an international peer-review journal. TRIAL REGISTRATION NUMBER: EudraCT number: 2018-003461-34. CLINICALTRIALS: gov ID NCT05655715.

miRNA Expression in Ovarian Cancer in Fresh Frozen, Formalin-fixed Paraffin-embedded and Plasma Samples.

BACKGROUND/AIM: MicroRNAs (miRNAs) are small noncoding RNAs involved in gene expression regulation and have been investigated as potential biomarkers for various diseases, including ovarian cancer (OC). However, lack of standardized protocols regarding e.g., RNA isolation, cDNA synthesis, spike-in controls for experimental steps, and data normalization, impacts cross validation of results across research groups and hinders implementation of miRNAs as clinical biomarkers. MATERIALS AND METHODS: RNA was isolated from matching fresh-frozen tissue (FF), formalin-fixed paraffin embedded (FFPE) tissue, and plasma samples from twenty women diagnosed with OC using three commercial kits: miRNeasy Tissue/Cells, miRNeasy FFPE, and miRNeasy Serum/Plasma (Qiagen, Copenhagen, Denmark). RNA isolation, cDNA synthesis, and PCR performance were tested using miRCURY LNA miRNA Quality Control PCR (QC) Panels (Qiagen). Finally, miRNA stability was assessed using five algorithms: BestKeeper, Normfinder, GeNorm, comparative delta-Ct and comprehensive ranking provided by a web-based RefFinder tool. RESULTS: RNA from FF, FFPE and plasma was extracted using commercially available kits and the differences in yield and purity were examined. We developed a simple method for identifying and potentially excluding samples based on their crossing point values from RT-qPCR data, which could improve existing manufacture guidelines. Moreover, we discussed how assessment of miRNA stability differs between algorithms, possibly leading to inconsistent results. CONCLUSION: We present guidelines for RNA isolation, cDNA synthesis, and data normalization for successful miRNA expression profiling using RT-qPCR in corresponding biological OC specimens. We recommend QC panels in combination with spike-in controls and interplate controls to monitor process efficiencies.

Oncomine™ Comprehensive Assay v3 vs. Oncomine™ Comprehensive Assay Plus.

The usage of next generation sequencing in combination with targeted gene panels has enforced a better understanding of tumor compositions. The identification of key genomic biomarkers underlying a disease are crucial for diagnosis, prognosis, treatment and therapeutic responses. The Oncomine™ Comprehensive Assay v3 (OCAv3) covers 161 cancer-associated genes and is routinely employed to support clinical decision making for a therapeutic course. An improved version, Oncomine™ Comprehensive Assay Plus (OCA-Plus), has been recently developed, covering 501 genes (144 overlapping with OCAv3) in addition to microsatellite instability (MSI) and tumor mutational burden (TMB) assays in one workflow. The validation of MSI and TMB was not addressed in the present study. However, the implementation of new assays must be validated and confirmed across multiple samples before it can be introduced into a clinical setting. Here, we report the comparison of DNA sequencing results from 50 ovarian cancer formalin-fixed, paraffin-embedded samples subjected to OCAv3 and OCA-Plus. A validation assessment of gene mutations identified using OCA-Plus was performed on the 144 overlapping genes and 313,769 intersecting nucleotide positions of the OCAv3 and the OCA-Plus. Our results showed a 91% concordance within variants classified as likely-pathogenic or pathogenic. Moreover, results showed that a region of PTEN is poorly covered by the OCA-Plus assay, hence, we implemented rescue filters for those variants. In conclusion, the OCA-Plus can reflect the mutational profile of genomic variants compared with OCAv3 of 144 overlapping genes, without compromising performance.

Genomic Sub-Classification of Ovarian Clear Cell Carcinoma Revealed by Distinct Mutational Signatures.

Ovarian clear cell carcinoma (OCCC) is characterized by dismal prognosis, partially due to its low sensitivity to standard chemotherapy regimen. It is also well-known for presenting unique molecular features in comparison to other epithelial ovarian cancer subtypes. Here, we aim to identify potential subgroups of patients in order to (1) determine their molecular features and (2) characterize their mutational signature. Furthermore, we sought to perform the investigation based on a potentially clinically relevant setting. To that end, we assessed the mutational profile and genomic instability of 55 patients extracted from the Gynecologic Cancer Database (DGCD) by using a panel comprised of 409 cancer-associated genes and a microsatellite assay, respectively; both are currently used in our routine environment. In accordance with previous findings, ARID1A and PIK3CA were the most prevalent mutations, present in 49.1% and 41.8%, respectively. From those, the co-occurrence of ARID1A and PIK3CA mutations was observed in 36.1% of subjects, indicating that this association might be a common feature of OCCC. The microsatellite instability frequency was low across samples. An unbiased assessment of signatures identified the presence of three subgroups, where "PIK3CA" and "Double hit" (with ARID1A and PIK3CA double mutation) subgroups exhibited unique signatures, whilst "ARID1A" and "Undetermined" (no mutations on ARID1A nor PIK3CA) subgroups showed similar profiles. Those differences were further indicated by COSMIC signatures. Taken together, the current findings suggest that OCCC presents distinct mutational landscapes within its group, which may indicate different therapeutic approaches according to its subgroup. Although encouraging, it is noteworthy that the current results are limited by sample size, and further investigation on a larger group would be crucial to better elucidate them.

Integrated microRNA and mRNA signatures associated with overall survival in epithelial ovarian cancer.

Ovarian cancer (OC), the eighth-leading cause of cancer-related death among females worldwide, is mainly represented by epithelial OC (EOC) that can be further subdivided into four subtypes: serous (75%), endometrioid (10%), clear cell (10%), and mucinous (3%). Major reasons for high mortality are the poor biological understanding of the OC mechanisms and a lack of reliable markers defining each EOC subtype. MicroRNAs (miRNAs) are small non-coding RNA molecules that regulate gene expression primarily by targeting messenger RNA (mRNA) transcripts. Their aberrant expression patterns have been associated with cancer development, including OC. However, the role of miRNAs in tumorigenesis is still to be determined, mainly due to the lack of consensus regarding optimal methodologies for identification and validation of miRNAs and their targets. Several tools for computational target prediction exist, but false interpretations remain a problem. The experimental validation of every potential miRNA-mRNA pair is not feasible, as it is laborious and expensive. In this study, we analyzed the correlation between global miRNA and mRNA expression patterns derived from microarray profiling of 197 EOC patients to identify the signatures of miRNA-mRNA interactions associated with overall survival (OS). The aim was to investigate whether these miRNA-mRNA signatures might have a prognostic value for OS in different subtypes of EOC. The content of our cohort (162 serous carcinomas, 15 endometrioid carcinomas, 11 mucinous carcinomas, and 9 clear cell carcinomas) reflects a real-world scenario of EOC. Several interaction pairs between 6 miRNAs (hsa-miR-126-3p, hsa-miR-223-3p, hsa-miR-23a-5p, hsa-miR-27a-5p, hsa-miR-486-5p, and hsa-miR-506-3p) and 8 mRNAs (ATF3, CH25H, EMP1, HBB, HBEGF, NAMPT, POSTN, and PROCR) were identified and the findings appear to be well supported by the literature. This indicates that our study has a potential to reveal miRNA-mRNA signatures relevant for EOC. Thus, the evaluation on independent cohorts will further evaluate the performance of such findings.

Next Generation Sequencing Technology in the Clinic and Its Challenges.

Data analysis has become a crucial aspect in clinical oncology to interpret output from next-generation sequencing-based testing. NGS being able to resolve billions of sequencing reactions in a few days has consequently increased the demand for tools to handle and analyze such large data sets. Many tools have been developed since the advent of NGS, featuring their own peculiarities. Increased awareness when interpreting alterations in the genome is therefore of utmost importance, as the same data using different tools can provide diverse outcomes. Hence, it is crucial to evaluate and validate bioinformatic pipelines in clinical settings. Moreover, personalized medicine implies treatment targeting efficacy of biological drugs for specific genomic alterations. Here, we focused on different sequencing technologies, features underlying the genome complexity, and bioinformatic tools that can impact the final annotation. Additionally, we discuss the clinical demand and design for implementing NGS.

DNA Methylation in Ovarian Tumors-a Comparison Between Fresh Tissue and FFPE Samples.

Among women, ovarian cancer (OC) is one of the most severe forms of malignancy, accounting for a low 5-year survival rate, of approximately 52%. Early symptoms are unspecific and hence hard to detect. The origin of OC and its subtypes are still unclear, underlying the need for efficient diagnostic biomarkers. In that regard, epigenetics studies are emerging in cancer diagnostics, with encouraging outcomes. Among them, DNA methylation profiling has shown that the origins of the cancer epigenome are associated with molecular factors that are crucial to carcinogenesis, such as regulation of oncogenes and tumor suppressors. Furthermore, those events have been detected in abnormal cell morphology before neoplastic formation, indicating its potential crucial use in the OC diagnostics in the future. Nonetheless, studies are limited, and whether methylation analysis can be performed optimally in formalin-fixed paraffin-embedded (FFPE) preparations of OC cases is still elusive. In the present report, we investigated the performance of DNA methylation analysis in FFPE samples, compared to their matched fresh frozen tissue in a small cohort of OC samples. We found that the overall DNA methylation profile in FFPE tissue showed high concordance to that found in fresh frozen tissue, and accounting for the small cohort size, the differentially methylated sites found primarily in frozen tissue, compared to benign samples, were also reproducible in FFPE. Overall, by using samples from our current clinical setting of tissue preservation, these preliminary observations might provide insights into the clinical use of FFPE tissues in methylation studies without critically compromising the outcome.

Gene expression profile association with poor prognosis in epithelial ovarian cancer patients.

Ovarian cancer (OC) is the eighth most common type of cancer for women worldwide. The current diagnostic and prognostic routine available for OC management either lack specificity or are very costly. Gene expression profiling has shown to be a very effective tool in exploring new molecular markers for patients with OC, although association of such markers with patient survival and clinical outcome is still elusive. Here, we performed gene expression profiling of different subtypes of OC to evaluate its association with patient overall survival (OS) and aggressive forms of the disease. By global mRNA microarray profiling in a total of 196 epithelial OC patients (161 serous, 15 endometrioid, 11 mucinous, and 9 clear cell carcinomas), we found four candidates-HSPA1A, CD99, RAB3A and POM121L9P, which associated with OS and poor clinicopathological features. The overexpression of all combined was correlated with shorter OS and progression-free survival (PFS). Furthermore, the combination of at least two markers were further associated with advanced grade, chemotherapy resistance, and progressive disease. These results indicate that a panel comprised of a few predictors that associates with a more aggressive form of OC may be clinically relevant, presenting a better performance than one marker alone.

Cetuximab plus irinotecan administered biweekly with reduced infusion time to heavily pretreated patients with metastatic colorectal cancer and related RAS and BRAF mutation status.

Metastatic colorectal cancer (mCRC) is treated with cetuximab 250 mg/m2 administered weekly over 1 hour or biweekly (q2w) over 3.5 hours when combined with irinotecan. This prospective study investigated cetuximab 500 mg/m2 plus irinotecan 180 mg/m2 administered q2w over 1.5 hours independent of RAS or BRAF mutation status in mCRC patients in a third-line setting. The intention-to-treat population included 181 patients. No patients had complete response, 18% had partial responses (PR) and 48% stable disease (SD). For cetuximab, a relative dose intensity of ≥90% was reached in 78% and for irinotecan in 67% of the patients. Grade 3 to 4 toxicities were pain (17%), fatigue (9%), neutropenia (8%), diarrhea (8%), rash (8%), infection (7%) and hypersensitivity (3%). No deaths occurred. Next-generation sequencing in 96.7% of the patients revealed that 50.3% had RAS and BRAFV600E wild type (WT), with a mutation type (MT) in 45.1% of the RAS and 4.4% of the BRAFV600E genes. In patients with RAS-WT and RAS-MT tumors, a PR was obtained in 32% and 4% (P = .000003) and an SD in 43% and 53%, respectively, with a superior PFS (6.2 vs 3.7 months; hazard ratio [HR] 2.12, P = .00001) and OS (12.9 vs 8.8 months; HR 1.71, P = .0008). Treatment efficacy was poor in 7.4% of patients with an RAS mutation outside KRAS exon 2 and in 38% of patients with KRAS exon 2 mutations. Administration of cetuximab and irinotecan q2w, shortening treatment time from 3.5 to 1.5 hours, is recommended as standard therapy.

Noncoding RNA (ncRNA) Profile Association with Patient Outcome in Epithelial Ovarian Cancer Cases.

Ovarian cancer (OC) is the second most frequent type of gynecological cancers worldwide. In the past decades, the development of novel diagnostic and prognostic biomarkers available for OC has been limited, reflecting by the lack of specificity of such markers or very costly management. Microarray expression profiling has shown very effective results in exploring new molecular markers for patients with OC. Nonetheless, most screenings are focused on mutations or expression of molecules that are translated into proteins, corresponding to only 2% of the total human genome. In order to account for the vast majority of transcripts, in the present exploratory study, we assessed the expression levels of a comprehensive panel of noncoding RNA in different subtypes of OC. We further evaluated their association with patient overall survival (OS) and aggressive forms of the disease, such as tumor type, stage, and chemotherapy resistance. By microarray profiling in a total of 197 epithelial OC patients (162 serous carcinomas, 15 endometrioid carcinomas, 11 mucinous carcinomas, and 9 clear cell carcinomas), we found two candidates, SNORA68 and SNORD74, which associated with OS and poor clinicopathological features. The overexpression of those two targets combined was correlated with shorter OS and progression-free survival. That association was further observed to correlate with a more aggressive form of the disease. Overall, the results indicate that a panel comprised of SNORA68 and SNORD74 may be clinically relevant, where patients could be offered a more individualized, targeted follow-up, given its further validation on future prospective clinical studies.

Exome sequencing of 22 genes using tissue from patients with biliary tract cancer.

Biliary tract cancers (BTC) are a rare heterogeneous disease group with a dismal prognosis and limited treatment options. The mutational landscape consists of genetic aberrations both shared by and characteristic for anatomical location. Here, we present exome sequencing data on 22 genes from a phase 2 trial using a clinically validated panel used in patients with colorectal cancer. A total of 56 patients were included in a one-armed phase 2 trial investigating the treatment combination of capecitabine, gemcitabine, oxaliplatin, and cetuximab. Tissue DNA yield and quality allowed analysis of 30 patients on our panel including 22 genes. ARID1A (33%) and TP53 (33%) were found to be most frequently mutated followed by KRAS mutations found in 20% of the patients. Mutational aberrations in ARID1A were found more prevalent than expected, whereas TP53 and KRAS were in concordance with earlier reported data. Mutation in CTNNB1 was significantly associated with poor prognosis. Our panel is clinically validated and suitable for a high volume of samples to detect mutations in patients with BTC. However, it is reasonable to assume that the clinical utility could be optimized in this patient group by extending the panel to include BTC specific mutations with potential therapeutic consequences such as IDH1/2, FGFR fusions, ERBB3, and BRCA1/2.

Diagnostic plasma miRNA-profiles for ovarian cancer in patients with pelvic mass.

BACKGROUND: Ovarian cancer is the fifth most common cancer in women worldwide. Moreover, there are no reliable minimal invasive tests to secure the diagnosis of malignant pelvic masses. Cell-free, circulating microRNAs have the potential as diagnostic biomarkers in cancer. Here, we performed and validated a miRNA panel with the potential to distinguish OC from benign pelvic masses. METHODS: The profile of plasma microRNA was determined with a panel of 46 candidates in a discovery group and a validation group, each consisting of 190 pre-surgery plasma samples from age-matched patients with malignant (n = 95) and benign pelvic mass (n = 95), by real time RT-qPCR. RESULTS: Four up-regulated (miR-200c-3p, miR-221-3p, miR-21-5p, and miR-484) and two down-regulated (miR-195-5p and miR-451a) microRNAs were discovered. From those, miR-200c-3p and miR-221-3p were further confirmed in a validation cohort. A combination of these 2 microRNAs together with CA-125 yielded an overall diagnostic accuracy of AUC = 0.96. CONCLUSIONS: We showed consistent plasma microRNA profiles that provide independent diagnostic information of late stage OC.

Methylation and ovarian cancer: Can DNA methylation be of diagnostic use?

Ovarian cancer is a silent killer and, due to late diagnosis and frequent chemo resistance in patients, the primary cause of fatality amongst the various types of gynecological cancer. The discovery of a specific and sensitive biomarker for ovarian cancer could improve early diagnosis, thereby saving lives. Biomarkers could also improve treatment, by predicting which patients will benefit from specific treatment strategies. DNA methylation is an epigenetic mechanism, and 'methylation imbalance' is characteristic of cancer. Previous research suggests that changes in DNA methylation can be used diagnostically, and that they may predict resistance to treatment. This paper gives an up-to-date overview of research investigating the potential of DNA methylation-based markers for diagnostics, prognostics, screening and prediction of drug resistance for ovarian cancer patients. DNA methylation cancer-biomarkers may be useful for cancer treatment, particularly since they are chemically stable and since cancer-associated changes in methylation typically precedes tumor growth. DNA methylation markers could improve diagnosis and treatment and might even be used for screening in the future. Furthermore, DNA methylation biomarkers could facilitate the development of precision medicine. However, at this point no biomarkers for ovarian cancer have a sufficient combination of sensitivity and specificity in a clinical setting. A reason for this is that most studies have focused on a single or a few methylation sites. More large screenings and genome-wide studies must be performed to increase the chance of identifying a DNA methylation marker which can identify ovarian cancer.

Association of CD31 and p53 With Survival of Ovarian Cancer Patients.

BACKGROUND/AIM: New markers for ovarian cancer are needed. This study aimed to examine the expression of tumour cell p53 and endothelial cell CD31 proteins and correlate them to clinicopathological factors. PATIENTS AND METHODS: Expression of proteins was immunohistochemically assessed using tissue sections from 585-599 ovarian cancer patients from the Danish MALOVA study. RESULTS: High CD31 expression was found in poorly differentiated tumours (p=0.0006), and high p53 expression was found in poorly differentiated cancers (p<0.0001), high clinical stage (p<0.0001), non-radical surgery (p<0.0001) and high serum CA-125 values (p<0.0001). CD31 expression showed no prognostic survival value, but high hazard ratios were found for patients with high p53 expression (HR=2.313, p<0.0001). An interaction was found between p53 and stage of cancer, suggesting a prognostic impact of p53 in low-stage, but not in advanced-stage cancer. CONCLUSION: More than 5% of p53 tissue expression may predict shorter survival of ovarian cancer patients and may be useful for predicting the risk of disease progression in low-stage patients following primary surgery. CD31 has no strong prognostic value.

Identification of new biomarkers to promote personalised treatment of patients with inflammatory rheumatic disease: protocol for an open cohort study.

INTRODUCTION: The introduction of biological disease-modifying antirheumatic drugs (bDMARDs) has improved the treatment of inflammatory rheumatic diseases dramatically. However, bDMARD treatment failure occurs in 30%-40% of patients due to lack of effect or adverse events, and the tools to predict treatment outcomes in individual patients are currently limited. The objective of the present study is to identify diagnostic, prognostic and predictive biomarkers, which can be used to (1) diagnose inflammatory rheumatic diseases early in the disease course with high sensitivity and specificity, (2) improve prognostication or (3) predict and monitor treatment effectiveness and tolerability for the individual patient. METHODS AND ANALYSIS: The present study is an observational and translational open cohort study with prospective collection of clinical data and biological materials (primarily blood) in patients with inflammatory rheumatic diseases treated in routine care. Patients contribute with one cross-sectional blood sample and/or are enrolled for longitudinal follow-up on initiation of a new DMARD (blood sampling after 0, 3, 6, 12, 24, 36, 48, 60 months of treatment). Other biological materials will be collected when accessible and relevant. Demographics, disease characteristics, comorbidities and lifestyle factors are registered at inclusion; DMARD treatment and outcomes are collected repeatedly during follow-up. Currently (July 2017), >5000 samples from approximately 3000 patients have been collected. Data will be analysed using appropriate statistical analyses. ETHICS AND DISSEMINATION: The protocol is approved by the Danish Ethics Committee and the Danish Data Protection Agency. Participants give written and oral informed consent. Biomarkers will be evaluated and published according to the Reporting Recommendations for Tumour Marker (REMARK) prognostic studies, Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) and the Standards for Reporting of Diagnostic Accuracy (STARD) guidelines. Results will be published in peer-reviewed scientific journals and presented at international conferences. TRIAL REGISTRATION NUMBER: NCT03214263.