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High-quality RNA is crucial in clinical diagnostics and precision medicine. Formalin-fixed and paraffin-embedded (FFPE) tissues pose a challenge due to nucleic acid fragmentation and crosslinking. In this pilot study, various commercially available techniques for extracting RNA from small FFPE samples were compared. We evaluated the KingFisher Duo automated system or the manual MagMAX FFPE DNA/RNA Ultra Kit as an RNA extraction method combined with either a xylene, d-limonene, or AutoLys M tubes deparaffinization method. Additionally, the automated Maxwell RSC RNA FFPE kit and the High Pure FFPET RNA Isolation Kit were examined using FFPE samples from inflammatory bowel disease (IBD) patients, as well as samples from ovarian, kidney, and breast cancer and the skin. The KingFisher Duo system gave a higher yield and more consistent RNA quantities, especially from small volumes of IBD samples, compared to manual extraction. The deparaffinization method also impacted results, with AutoLys M tubes proving effective in combination with the KingFisher Duo system. Conversely, the High Pure kit exhibited higher yields for larger FFPE samples. While RNA integrity is a critical factor, particularly for messenger RNA (mRNA) expression studies, its role is less prominent in microRNA (miRNA) analyses. Recognizing this, our study focused on RNA yield and purity (A260/A230) to evaluate RNA extraction methods for various sample types. These findings emphasize the importance of selecting appropriate RNA extraction methods based on sample characteristics and research goals, highlighting the performance of automated methods and the impact of deparaffinization choices. The findings contribute to refining RNA extraction for molecular biology analyses, suggesting avenues for further exploration, including cost-effectiveness under specific experimental conditions.

Background: In the FIGO 2018 classification, women with cervical cancer and a depth of invasion ≤ 5 mm and a horizontal spread of > 7 mm in excisional biopsy with tumour-free margins, are now classified as stage IA instead of IB. This stage shift may reduce the likelihood of surgical lymph node staging. It is therefore crucial to estimate the risk and risk factors of lymph node metastasis (pN+) in this group., Methods: Women diagnosed with cervical cancer between 2005 and 2022 were identified from nationwide population-based registries from the Netherlands, Denmark, and Sweden. Inclusion criteria were squamous cell carcinoma or adenocarcinoma, FIGO 2009 stage IB1, a depth of invasion ≤ 5 mm and horizontal spread of > 7-≤ 40 mm. All cases underwent radical hysterectomy or radical trachelectomy, and surgical lymph node staging. Logistic regression was used to identify risk factors of pN+., Results: We included 992 women (pN+ 4.1 %; n = 41). Lymphovascular space invasion (LVSI) was a significant risk factor of pN+ (odds ratio 4.26, 95 % confidence interval 2.24-8.32). Accordingly, the risk of pN+ was ≥ 7.3 % in LVSI-positive tumours. The risk was lowest in LVSI-negative tumours with a size of > 7-≤ 20 mm (2.2 %), although this varied by depth of invasion and histological subtype (pN+ range 0.6-5.1 %)., Conclusion: Women with LVSI-positive FIGO 2018 IA cervical cancer and a horizontal spread > 7 mm, should undergo surgical lymph node staging. In LVSI-negative tumours, lymph node staging should not be routinely performed; tumour size, depth of invasion and histology should be considered., Competing Interests: Declaration of Competing Interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: HF: Board Member Surgical Science, PJ: MSD Advisory Board for cervical cancer, All other authors declare that they have no competing interests., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

Background: Next-generation sequencing (NGS) has been implemented in clinical oncology as a personalized medicine tool to identify targetable genetic alterations and to guide treatment decisions. However, the optimal NGS test strategy and target genes for clinical use are still being discussed. The aim was to compare the performance of the Oncomine™ Comprehensive Assay v3 (OCAv3) (targeted gene panel) and whole-exome sequencing (WES) to investigate somatic single and multiple nucleotide variants and small indels in ovarian cancer patients., Methods and Results: Genomic DNA was isolated from fresh frozen samples of five high-grade serous (HGSC) and three clear cell ovarian (oCCC) cancer patients. Exome sequencing libraries were prepared by using the Ion AmpliSeq Exome RDY kit, whereas libraries for OCAv3 were prepared using by Ion AmpliSeq™ Library Kit Plus. Sequencing was performed using the Ion S5XL System (Thermo Fisher Scientific). When including only variants classified as pathogenic, likely pathogenic or unknown significance based on ClinVar database verdicts and comparing overlapping regions covered both by the OCAv3 assay and WES, 23 variants were detected by both assays. However, OCAv3 detected additionally two variants: ARID1A: p.Gln563Ter and TP53: p.Ser261ValfsTer84 that have not passed WES filtering criteria due to low coverage., Conclusions: With the present treatment possibilities, OCAv3 panel testing provided higher diagnostic yield due to better coverage. Our study emphasizes that WES, although offering the potential to identify novel findings in genes not covered by OCAv3, might overlook variants in genes relevant for OC., (© 2024. The Author(s).)

To identify credible causal risk variants (CCVs) associated with different histotypes of epithelial ovarian cancer (EOC), we performed genome-wide association analysis for 470,825 genotyped and 10,163,797 imputed SNPs in 25,981 EOC cases and 105,724 controls of European origin. We identified five histotype-specific EOC risk regions (p value <5 × 10 -8 ) and confirmed previously reported associations for 27 risk regions. Conditional analyses identified an additional 11 signals independent of the primary signal at six risk regions (p value <10 -5 ). Fine mapping identified 4,008 CCVs in these regions, of which 1,452 CCVs were located in ovarian cancer-related chromatin marks with significant enrichment in active enhancers, active promoters, and active regions for CCVs from each EOC histotype. Transcriptome-wide association and colocalization analyses across histotypes using tissue-specific and cross-tissue datasets identified 86 candidate susceptibility genes in known EOC risk regions and 32 genes in 23 additional genomic regions that may represent novel EOC risk loci (false discovery rate <0.05). Finally, by integrating genome-wide HiChIP interactome analysis with transcriptome-wide association study (TWAS), variant effect predictor, transcription factor ChIP-seq, and motifbreakR data, we identified candidate gene-CCV interactions at each locus. This included risk loci where TWAS identified one or more candidate susceptibility genes (e.g., HOXD-AS2, HOXD8, and HOXD3 at 2q31) and other loci where no candidate gene was identified (e.g., MYC and PVT1 at 8q24) by TWAS. In summary, this study describes a functional framework and provides a greater understanding of the biological significance of risk alleles and candidate gene targets at EOC susceptibility loci identified by a genome-wide association study., Competing Interests: Declaration of interests The authors declare no competing interests., (Copyright © 2024 American Society of Human Genetics. Published by Elsevier Inc. All rights reserved.)

Survival from ovarian cancer depends on the resection status after primary surgery. We performed genome-wide association analyses for resection status of 7705 ovarian cancer patients, including 4954 with high-grade serous carcinoma (HGSOC), to identify variants associated with residual disease. The most significant association with resection status was observed for rs72845444, upstream of MGMT, in HGSOC (p = 3.9 × 10 -8 ). In gene-based analyses, PPP2R5C was the most strongly associated gene in HGSOC after stage adjustment. In an independent set of 378 ovarian tumours from the AGO-OVAR 11 study, variants near MGMT and PPP2R5C correlated with methylation and transcript levels, and PPP2R5C mRNA levels predicted progression-free survival in patients with residual disease. MGMT encodes a DNA repair enzyme, and PPP2R5C encodes the B56γ subunit of the PP2A tumour suppressor. Our results link heritable variation at these two loci with resection status in HGSOC., (© 2024. The Author(s).)

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., (© 2023. The Author(s).)

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., Competing Interests: Competing interestsThe authors declare no competing interests., (©Copyright : © 2023 The Authors; This is an open access article under the CC BY-NC license.)

Background: Women with low-grade ovarian serous carcinoma (LGSC) benefit from surgical treatment; however, the role of chemotherapy is controversial. We examined an international database through the Ovarian Cancer Association Consortium to identify factors that affect survival in LGSC., Methods: We performed a retrospective cohort analysis of patients with LGSC who had had primary surgery and had overall survival data available. We performed univariate and multivariate analyses of progression-free survival and overall survival, and generated Kaplan-Meier survival curves., Results: Of the 707 patients with LGSC, 680 (96.2%) had available overall survival data. The patients' median age overall was 54 years. Of the 659 patients with International Federation of Obstetrics and Gynecology stage data, 156 (23.7%) had stage I disease, 64 (9.7%) had stage II, 395 (59.9%) had stage III, and 44 (6.7%) had stage IV. Of the 377 patients with surgical data, 200 (53.0%) had no visible residual disease. Of the 361 patients with chemotherapy data, 330 (91.4%) received first-line platinum-based chemotherapy. The median follow-up duration was 5.0 years. The median progression-free survival and overall survival were 43.2 months and 110.4 months, respectively. Multivariate analysis indicated a statistically significant impact of stage and residual disease on progression-free survival and overall survival. Platinum-based chemotherapy was not associated with a survival advantage., Conclusion: This multicentre analysis indicates that complete surgical cytoreduction to no visible residual disease has the most impact on improved survival in LGSC. This finding could immediately inform and change practice., Competing Interests: Competing interests: Stephanie Lheureux reports study grants from AstraZeneca, GSK and Roche, consulting fees from AstraZeneca, GSK, Roche, Novartis, Merck, Eisai Co. and Shattuck Labs, and speaker’s honororia from AstraZeneca, GSK, Eisai Co. and Merck. Line Bjørge is president of the Nordic Society of Gynaecological Oncology executive board. Anna deFazio sits on the Australia New Zealand Gynaecological Oncology Group (ANZGOG) Research Advisory Committee, the Clinical and Scientific Expert Advisory Panel of Ovarian Cancer Australia and the Scientific Advisory Committee of the Australian Gynaecological Cancer Foundation. She is chair of the Translational ANZGOG (TRANZGOG) Steering Committee, chair of the International Consortium for Low-Grade Serous Ovarian Cancer Steering Committee and chair of the ANZGOG Translational subcommittee. Michael Friedlander reports consulting fees from AstraZeneca, GSK, MSD, Eli Lilly and Company, Takeda and Novartis; payment or honoraria for lectures, presentations, speakers bureaus, manuscript writing or educational events from Astra-Zeneca, GSK and ACT Genomics; and support for attending meetings and/or travel from AstraZeneca. He sits on the Australasian Gastrointestinal Trial Group independent data monitoring committee and is a Steering Committee member for Abbvie’s VELIA trial. Catherine Kennedy is a member of the International Society for Biological and Environmental Repositories Science Policy Committee and of the Australasian Biospecimen Network (ABNA) Management Committee. She is past president and treasurer of ABNA. Liv Cecilie Vestrheim Thomsen reports grants from AstraZeneca, and payment or honoraria for lectures, presentations, speakers bureaus, manuscript writing or educational events from Bayer and AstraZeneca. She sits on an advisory board for Eisai Co. Ignace Vergote reports consulting fees from Deciphera Pharmaceuticals, Jazz Pharmaceuticals and Oncoinvent AS, and payment or honoraria for lectures, presentations, speakers bureaus, manuscript writing or educational events from Agenus, AkseBio, AstraZeneca, Bristol Myers Squibb, Deciphera Pharmaceuticals, Eisai Co., F. Hoffmann-La Roche, Genmab, GSK, ImmunoGen, Jazz Pharmaceuticals, Karyopharm Therapeutics, MSD, Novocure, Novartis, Oncoinvent AS, Seagen and Sotio Biotech. He sits on a data safety monitoring board or advisory board for Agenus, AstraZeneca, Bristol Myers Squibb, Deciphera Pharmaceuticals, Eisai Co., F. Hoffmann-La Roche, Genmab, GSK, ImmunoGen, MSD, Novocure, Novartis, Seagen and Sotio Biotech. Penelope Webb reports a speaker’s honorarium from AstraZeneca. No other competing interests were declared., (© 2023 CMA Impact Inc. or its licensors.)

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., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2023 Lopacinska-Jørgensen et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Objective: Lymph node metastases (pN+) in presumed early-stage cervical cancer negatively impact prognosis. Using federated learning, we aimed to develop a tool to identify a group of women at low risk of pN+, to guide the shared decision-making process concerning the extent of lymph node dissection., Methods: Women with cervical cancer between 2005 and 2020 were identified retrospectively from population-based registries: the Danish Gynaecological Cancer Database, Swedish Quality Registry for Gynaecologic Cancer and Netherlands Cancer Registry. Inclusion criteria were: squamous cell carcinoma, adenocarcinoma or adenosquamous carcinoma; The International Federation of Gynecology and Obstetrics 2009 IA2, IB1 and IIA1; treatment with radical hysterectomy and pelvic lymph node assessment. We applied privacy-preserving federated logistic regression to identify risk factors of pN+. Significant factors were used to stratify the risk of pN+., Results: We included 3606 women (pN+ 11%). The most important risk factors of pN+ were lymphovascular space invasion (LVSI) (odds ratio [OR] 5.16, 95% confidence interval [CI], 4.59-5.79), tumour size 21-40 mm (OR 2.14, 95% CI, 1.89-2.43) and depth of invasion>10 mm (OR 1.81, 95% CI, 1.59-2.08). A group of 1469 women (41%)-with tumours without LVSI, tumour size ≤20 mm, and depth of invasion ≤10 mm-had a very low risk of pN+ (2.4%, 95% CI, 1.7-3.3%)., Conclusion: Early-stage cervical cancer without LVSI, a tumour size ≤20 mm and depth of invasion ≤10 mm, confers a low risk of pN+. Based on an international privacy-preserving analysis, we developed a useful tool to guide the shared decision-making process regarding lymph node dissection., (Copyright © 2023 Elsevier Ltd. All rights reserved.)

Objectives: The Ovarian Cancer Comorbidity Index (OCCI) is an age-specific index developed and previously found to be more predictive of overall and cancer-specific survival than the Charlson Comorbidity Index (CCI). The objective was to perform secondary validation of the OCCI in a US population., Methods: A cohort of ovarian cancer patients undergoing primary or interval cytoreductive surgery from January 2005 to January 2012 was identified in SEER-Medicare. OCCI scores were calculated with the regression coefficients determined from the original developmental cohort for five comorbidities. Cox regression analyses were used to calculate associations between the OCCI risk groups and 5-year overall survival and 5-year cancer-specific survival in comparison to the CCI., Results: A total of 5052 patients were included. Median age was 74 (range 66-82) years. 47% (n=2375) had stage III and 24% (n=1197) had stage IV disease at diagnosis. 67% had a serous histology subtype (n=3403). All patients were categorized as moderate (48.4%) or high risk (51.6%). The prevalence of the five predictive comorbidities were: coronary artery disease 3.7%, hypertension 67.5%, chronic obstructive pulmonary disease 16.7%, diabetes 21.8%, and dementia 1.2%. Controlling for histology, grade, and age-stratification, worse overall survival was associated with both a higher OCCI (hazard ratio (HR) 1.57; 95% confidence interval (CI) 1.46 to 1.69) and CCI (HR 1.96; 95% CI 1.66 to 2.32). Cancer-specific survival was associated with the OCCI (HR 1.33; 95% CI 1.22 to 1.44) but was not associated with the CCI (HR 1.15; 95% CI 0.93 to 1.43)., Conclusions: This internationally developed comorbidity score for ovarian cancer patients is predictive for both overall and cancer-specific survival in a US population. CCI was not predictive for cancer-specific survival. This score may have research applications when utilizing large administrative datasets., Competing Interests: Competing interests: There are no relevant conflicts. However, LAM reports research funding from AstraZeneca, consulting for Glaxo-Smith-Kline, and stocks in Crispr, Invitae, Denali, and Bristol-Myers Squibb. CCS also reports funding from AstraZeneca. The remaining authors report no conflicts of interest., (© IGCS and ESGO 2023. No commercial re-use. See rights and permissions. Published by BMJ.)

Background: Cyclin E1 (CCNE1) is a potential predictive marker and therapeutic target in tubo-ovarian high-grade serous carcinoma (HGSC). Smaller studies have revealed unfavorable associations for CCNE1 amplification and CCNE1 overexpression with survival, but to date no large-scale, histotype-specific validation has been performed. The hypothesis was that high-level amplification of CCNE1 and CCNE1 overexpression, as well as a combination of the two, are linked to shorter overall survival in HGSC., Methods: Within the Ovarian Tumor Tissue Analysis consortium, amplification status and protein level in 3029 HGSC cases and mRNA expression in 2419 samples were investigated., Results: High-level amplification (>8 copies by chromogenic in situ hybridization) was found in 8.6% of HGSC and overexpression (>60% with at least 5% demonstrating strong intensity by immunohistochemistry) was found in 22.4%. CCNE1 high-level amplification and overexpression both were linked to shorter overall survival in multivariate survival analysis adjusted for age and stage, with hazard stratification by study (hazard ratio [HR], 1.26; 95% CI, 1.08-1.47, p = .034, and HR, 1.18; 95% CI, 1.05-1.32, p = .015, respectively). This was also true for cases with combined high-level amplification/overexpression (HR, 1.26; 95% CI, 1.09-1.47, p = .033). CCNE1 mRNA expression was not associated with overall survival (HR, 1.00 per 1-SD increase; 95% CI, 0.94-1.06; p = .58). CCNE1 high-level amplification is mutually exclusive with the presence of germline BRCA1/2 pathogenic variants and shows an inverse association to RB1 loss., Conclusion: This study provides large-scale validation that CCNE1 high-level amplification is associated with shorter survival, supporting its utility as a prognostic biomarker in HGSC., (© 2022 The Authors. Cancer published by Wiley Periodicals LLC on behalf of American Cancer Society.)

Purpose: Advanced-stage mucinous ovarian carcinoma (MOC) has poor chemotherapy response and prognosis and lacks biomarkers to aid stage I adjuvant treatment. Differentiating primary MOC from gastrointestinal (GI) metastases to the ovary is also challenging due to phenotypic similarities. Clinicopathologic and gene-expression data were analyzed to identify prognostic and diagnostic features., Experimental Design: Discovery analyses selected 19 genes with prognostic/diagnostic potential. Validation was performed through the Ovarian Tumor Tissue Analysis consortium and GI cancer biobanks comprising 604 patients with MOC (n = 333), mucinous borderline ovarian tumors (MBOT, n = 151), and upper GI (n = 65) and lower GI tumors (n = 55)., Results: Infiltrative pattern of invasion was associated with decreased overall survival (OS) within 2 years from diagnosis, compared with expansile pattern in stage I MOC [hazard ratio (HR), 2.77; 95% confidence interval (CI), 1.04-7.41, P = 0.042]. Increased expression of THBS2 and TAGLN was associated with shorter OS in MOC patients (HR, 1.25; 95% CI, 1.04-1.51, P = 0.016) and (HR, 1.21; 95% CI, 1.01-1.45, P = 0.043), respectively. ERBB2 (HER2) amplification or high mRNA expression was evident in 64 of 243 (26%) of MOCs, but only 8 of 243 (3%) were also infiltrative (4/39, 10%) or stage III/IV (4/31, 13%)., Conclusions: An infiltrative growth pattern infers poor prognosis within 2 years from diagnosis and may help select stage I patients for adjuvant therapy. High expression of THBS2 and TAGLN in MOC confers an adverse prognosis and is upregulated in the infiltrative subtype, which warrants further investigation. Anti-HER2 therapy should be investigated in a subset of patients. MOC samples clustered with upper GI, yet markers to differentiate these entities remain elusive, suggesting similar underlying biology and shared treatment strategies., (©2022 The Authors; Published by the American Association for Cancer Research.)

Introduction: Clinical Quality Registries (CQRs) were initiated in order to compare clinical outcomes between hospitals or regions within a country. To get an overview of these CQRs worldwide the aim of this study was to identify these CQRs for gynecological oncology and to summarize their characteristics, processes and QI's and to establish whether it is feasible to make an international comparison in the future., Methods: To identify CQRs in gynecological oncology a literature search in Pubmed was performed. All papers describing the use of a CQR were included. Administrative, epidemiological and cancer registries were excluded as these registries do not primarily serve to measure quality of care through QI's. The taskforce or contact person of the included CQR were asked to participate and share information on registered items, processes and indicators., Results: Five nations agreed to collaborate: Australia, Denmark, Italy, the Netherlands and Sweden. Denmark, Netherlands and Sweden established a nationwide registry, collecting data on multiple tumor types, and various QI's. Australia and Italy included patients with ovarian cancer only. All nations had a different process to report feedback results to participating hospitals., Conclusion: CQRs serve the same purpose to improve quality of care but vary on different aspects. Although similarities are observed in the topics measured by the QI's, an international comparison was not feasible as numerators or denominators differ between registries. In order to compare on an international level it would be useful to harmonize these registries and to set an international standard to measure the quality of care with similar indicators., Competing Interests: Declaration of competing interest There was no conflict of interest., (Copyright © 2022 The Authors. Published by Elsevier Ltd.. All rights reserved.)

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., (Copyright © 2022, International Institute of Anticancer Research (Dr. George J. Delinasios), All rights reserved.)

Objective: Studies on low-grade serous ovarian cancer (LGSC) are limited by a low number of cases. The aim of this study was to define the prognostic significance of age, stage, and CA-125 levels on survival in a multi-institutional cohort of women with pathologically confirmed LGSC., Methods: Women with LGSC were identified from the collaborative Ovarian Cancer Association Consortium (OCAC). Cases of newly diagnosed primary LGSC were included if peri-operative CA-125 levels were available. Age at diagnosis, FIGO stage, pre- and post-treatment CA-125 levels, residual disease, adjuvant chemotherapy, disease recurrence, and vital status were collected by the participating institutions. Progression-free (PFS) and overall survival (OS) were calculated. Multivariable (MVA) Cox proportional hazard models were used and hazard ratios (HR) calculated., Results: A total of 176 women with LGSC were included in this study; 82% had stage III/IV disease. The median PFS was 2.3 years and the median OS was 6.4 years. Age at diagnosis was not significantly associated with worse PFS ( p = 0.23) or OS ( p = 0.3) (HR per year: 0.99; 95%CI, 0.96-1.01 and 0.98; 95%CI 0.95-1.01). FIGO stage III/IV was independently associated with PFS (HR 4.26, 95%CI 1.43-12.73) and OS (HR 1.69, 95%CI 0.56-5.05). Elevated CA-125 (≥35 U/mL) at diagnosis was not significantly associated with worse PFS ( p = 0.87) or OS ( p = 0.78) in MVA. Elevated CA-125 (≥35 U/mL) after completion of primary treatment was independently associated with worse PFS (HR 2.81, 95%CI 1.36-5.81) and OS (HR 6.62, 95%CI 2.45-17.92). In the MVA, residual disease was independently associated with PFS (0.022), but not OS (0.85)., Conclusion: Advanced LGSC was associated with poor long-term prognosis. FIGO stage and abnormal post-treatment CA-125 level are key prognostic factors inversely associated with PFS and OS., Highlights: 1. Through a multi-center collaborative effort, data from 176 women with low-grade serous ovarian cancer were analyzed. 2. Although low-grade serous ovarian cancer is often considered indolent, the progression-free and overall survival are poor. 3. Elevated post-treatment CA-125 levels are independently associated with poor survival.

Tubo-ovarian high-grade serous carcinomas (HGSC) are highly proliferative neoplasms that generally respond well to platinum/taxane chemotherapy. We recently identified minichromosome maintenance complex component 3 (MCM3), which is involved in the initiation of DNA replication and proliferation, as a favorable prognostic marker in HGSC. Our objective was to further validate whether MCM3 mRNA expression and possibly MCM3 protein levels are associated with survival in patients with HGSC. MCM3 mRNA expression was measured using NanoString expression profiling on formalin-fixed and paraffin-embedded tissue (N = 2355 HGSC) and MCM3 protein expression was assessed by immunohistochemistry (N = 522 HGSC) and compared with Ki-67. Kaplan-Meier curves and the Cox proportional hazards model were used to estimate associations with survival. Among chemotherapy-naïve HGSC, higher MCM3 mRNA expression (one standard deviation increase in the score) was associated with longer overall survival (HR = 0.87, 95% CI 0.81-0.92, p < 0.0001, N = 1840) in multivariable analysis. MCM3 mRNA expression was highest in the HGSC C5.PRO molecular subtype, although no interaction was observed between MCM3, survival and molecular subtypes. MCM3 and Ki-67 protein levels were significantly lower after exposure to neoadjuvant chemotherapy compared to chemotherapy-naïve tumors: 37.0% versus 46.4% and 22.9% versus 34.2%, respectively. Among chemotherapy-naïve HGSC, high MCM3 protein levels were also associated with significantly longer disease-specific survival (HR = 0.52, 95% CI 0.36-0.74, p = 0.0003, N = 392) compared to cases with low MCM3 protein levels in multivariable analysis. MCM3 immunohistochemistry is a promising surrogate marker of proliferation in HGSC., (© 2021. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Polygenic risk scores (PRS) for epithelial ovarian cancer (EOC) have the potential to improve risk stratification. Joint estimation of Single Nucleotide Polymorphism (SNP) effects in models could improve predictive performance over standard approaches of PRS construction. Here, we implemented computationally efficient, penalized, logistic regression models (lasso, elastic net, stepwise) to individual level genotype data and a Bayesian framework with continuous shrinkage, "select and shrink for summary statistics" (S4), to summary level data for epithelial non-mucinous ovarian cancer risk prediction. We developed the models in a dataset consisting of 23,564 non-mucinous EOC cases and 40,138 controls participating in the Ovarian Cancer Association Consortium (OCAC) and validated the best models in three populations of different ancestries: prospective data from 198,101 women of European ancestries; 7,669 women of East Asian ancestries; 1,072 women of African ancestries, and in 18,915 BRCA1 and 12,337 BRCA2 pathogenic variant carriers of European ancestries. In the external validation data, the model with the strongest association for non-mucinous EOC risk derived from the OCAC model development data was the S4 model (27,240 SNPs) with odds ratios (OR) of 1.38 (95% CI: 1.28-1.48, AUC: 0.588) per unit standard deviation, in women of European ancestries; 1.14 (95% CI: 1.08-1.19, AUC: 0.538) in women of East Asian ancestries; 1.38 (95% CI: 1.21-1.58, AUC: 0.593) in women of African ancestries; hazard ratios of 1.36 (95% CI: 1.29-1.43, AUC: 0.592) in BRCA1 pathogenic variant carriers and 1.49 (95% CI: 1.35-1.64, AUC: 0.624) in BRCA2 pathogenic variant carriers. Incorporation of the S4 PRS in risk prediction models for ovarian cancer may have clinical utility in ovarian cancer prevention programs., (© 2021. The Author(s).)

Objective: To examine clinical trends in Denmark for younger and older epithelial ovarian cancer (EOC) patients, focusing on incidence, treatment, and survival changes., Methods: We included a nationwide cohort diagnosed with EOC from 2005 to 2018. We described age-standardized incidence, surgical patterns, residual disease trends, and cancer-specific survival stratified by age (<70 and ≥ 70 years), stage, and period (2005-09, 2010-13, 2014-18)., Results: We included 7522 patients. The incidence decreased from 16.3 (2005) to 11.4 (2018) per 100,000 woman-years, driven by the younger cohort. While the proportion of patients with stage IIIC-IV disease undergoing primary debulking surgery (PDS) decreased, the proportion of patients having interval debulking surgery (IDS) and no debulking surgery increased significantly. In 2014-18, 36% and 24% had PDS for younger and older patients, respectively, compared to 72% and 62% in 2005-09. In both age cohorts, the proportion of patients debulked to no residual disease increased significantly among patients with stage IIIC-IV and in the total cohort. Two-year cancer-specific survival increased from 75% (2005-09) to 84% (2014-18) for younger patients and from 53% to 66% for older patients. After adjusting for potential confounders, age ≥ 70 was associated with a 1.4-fold increased risk of cancer-specific death (95% confidence interval: 1.2,1.5)., Conclusions: The proportion of patients with advanced EOC not undergoing PDS or IDS increased significantly. During the same period, patients debulked to no residual disease, and cancer-specific survival increased. However, a survival gap in favor of the younger patients remains after adjusting for potential confounders., Competing Interests: Declaration of Competing Interest The authors report no conflicts of interest., (Copyright © 2021 The Authors. Published by Elsevier Inc. All rights reserved.)

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.

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.

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., Competing Interests: The authors have declared that no competing interests exist.

Familial, sequencing, and genome-wide association studies (GWASs) and genetic correlation analyses have progressively unraveled the shared or pleiotropic germline genetics of breast and ovarian cancer. In this study, we aimed to leverage this shared germline genetics to improve the power of transcriptome-wide association studies (TWASs) to identify candidate breast cancer and ovarian cancer susceptibility genes. We built gene expression prediction models using the PrediXcan method in 681 breast and 295 ovarian tumors from The Cancer Genome Atlas and 211 breast and 99 ovarian normal tissue samples from the Genotype-Tissue Expression project and integrated these with GWAS meta-analysis data from the Breast Cancer Association Consortium (122,977 cases/105,974 controls) and the Ovarian Cancer Association Consortium (22,406 cases/40,941 controls). The integration was achieved through application of a pleiotropy-guided conditional/conjunction false discovery rate (FDR) approach in the setting of a TWASs. This identified 14 candidate breast cancer susceptibility genes spanning 11 genomic regions and 8 candidate ovarian cancer susceptibility genes spanning 5 genomic regions at conjunction FDR < 0.05 that were >1 Mb away from known breast and/or ovarian cancer susceptibility loci. We also identified 38 candidate breast cancer susceptibility genes and 17 candidate ovarian cancer susceptibility genes at conjunction FDR < 0.05 at known breast and/or ovarian susceptibility loci. The 22 genes identified by our cross-cancer analysis represent promising candidates that further elucidate the role of the transcriptome in mediating germline breast and ovarian cancer risk., Competing Interests: Declaration of interests The authors declare no competing interests.

The purpose of the current study was to clarify differences in microRNA expression according to clinicopathological characteristics, and to investigate if miRNA profiles could predict cytoreductive outcome in patients with FIGO stage IIIC and IV ovarian cancer. Patients enrolled in the Pelvic Mass study between 2004 and 2010, diagnosed and surgically treated for epithelial ovarian cancer, were used for investigation. MicroRNA was profiled from tumour tissue with global microRNA microarray analysis. Differences in miRNA expression profiles were analysed according to histologic subtype, FIGO stage, tumour grade, type I or II tumours and result of primary cytoreductive surgery. One microRNA, miR-130a, which was found to be associated with serous histology and advanced FIGO stage, was also validated using data from external cohorts. Another seven microRNAs (miR-34a, miR-455-3p, miR-595, miR-1301, miR-146-5p, 193a-5p, miR-939) were found to be significantly associated with the clinicopathological characteristics (p ≤ 0.001), in our data, but mere not similarly significant when tested against external cohorts. Further validation in comparable cohorts, with microRNA profiled using newest and similar methods are warranted., Competing Interests: The authors have declared that no competing interests exist.

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.

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.

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.

Background: Accumulating evidence suggests a relationship between endometrial cancer and ovarian cancer. Independent genome-wide association studies (GWAS) for endometrial cancer and ovarian cancer have identified 16 and 27 risk regions, respectively, four of which overlap between the two cancers. We aimed to identify joint endometrial and ovarian cancer risk loci by performing a meta-analysis of GWAS summary statistics from these two cancers., Methods: Using LDScore regression, we explored the genetic correlation between endometrial cancer and ovarian cancer. To identify loci associated with the risk of both cancers, we implemented a pipeline of statistical genetic analyses (i.e., inverse-variance meta-analysis, colocalization, and M-values) and performed analyses stratified by subtype. Candidate target genes were then prioritized using functional genomic data., Results: Genetic correlation analysis revealed significant genetic correlation between the two cancers ( r G = 0.43, P = 2.66 × 10 -5 ). We found seven loci associated with risk for both cancers ( P Bonferroni < 2.4 × 10 -9 ). In addition, four novel subgenome-wide regions at 7p22.2, 7q22.1, 9p12, and 11q13.3 were identified ( P < 5 × 10 -7 ). Promoter-associated HiChIP chromatin loops from immortalized endometrium and ovarian cell lines and expression quantitative trait loci data highlighted candidate target genes for further investigation., Conclusions: Using cross-cancer GWAS meta-analysis, we have identified several joint endometrial and ovarian cancer risk loci and candidate target genes for future functional analysis., Impact: Our research highlights the shared genetic relationship between endometrial cancer and ovarian cancer. Further studies in larger sample sets are required to confirm our findings., (©2020 American Association for Cancer Research.)