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BACKGROUND: Somatic pathogenic variants (PVs) in homologous recombination DNA repair (HR)-related genes found in high-grade serous ovarian carcinomas (HGSC) are not well-characterised in older patients (≥70 years). This may reflect low testing rates in older patients. METHODS: Data from 1210 HGSC patients in AACR Project GENIE and 324 patients in an independent dataset INOVATe were analysed. Cases where somatic variants could be distinguished from germline variants were included, and analysis was restricted to those with a somatic TP53 variant, to ensure cases were HGSC. RESULTS: Of 1210 patients in GENIE, 27% (n = 325) were aged ≥70 years at testing. Patients with somatic-only PVs in BRCA2 were older compared with BRCA1 (median 71 vs 60 years, p = 0.002). Median age for 21 patients with somatic-only PVs in 11 other HR-related genes ranged from 40 to 67 years. In older patients, 7% (n = 22) had somatic BRCA1/2 PVs, and 1% (n = 2) had PVs other HR-related genes; this rate was not significantly different to younger patients (<70 years), 7% (n = 62) BRCA1/2 and 2% (n = 19) other HR-related genes (p = 0.36). The overall frequency of somatic BRCA1/2 PVs was similar in INOVATe (n = 25; 7.7%) and somatic-only BRCA2 PVs were again found in older patients compared with BRCA1 (median age: at testing, 70 vs 63 years; at diagnosis, 68 vs 60 years). CONCLUSIONS: The overall frequency of somatic-only PVs in HR-related genes was similar in older and younger patients with HGSC, highlighting the importance of somatic testing irrespective of age. Limiting somatic testing by age may exclude patients who could benefit from maintenance poly(ADP-ribose) polymerase (PARP) inhibitors.

Engineering single base edits using CRISPR technology including specific deaminases and single-guide RNA (sgRNA) is a rapidly evolving field. Different types of base edits can be constructed, with cytidine base editors (CBEs) facilitating transition of C-to-T variants, adenine base editors (ABEs) enabling transition of A-to-G variants, C-to-G transversion base editors (CGBEs) and recently adenine transversion editors (AYBE) that create A-to-C and A-to-T variants. The base-editing machine learning algorithm BE-Hive predicts which sgRNA and base editor combinations have the strongest likelihood of achieving desired base edits. We have used BE-Hive and TP53 mutation data from The Cancer Genome Atlas (TCGA) ovarian cancer cohort to predict which mutations can be engineered, or reverted to wild-type (WT) sequence, using CBEs, ABEs or CGBEs. We have developed and automated a ranking system to assist in selecting optimally designed sgRNA that considers the presence of a suitable protospacer adjacent motif (PAM), the frequency of predicted bystander edits, editing efficiency and target base change. We have generated single constructs containing ABE or CBE editing machinery, an sgRNA cloning backbone and an enhanced green fluorescent protein tag (EGFP), removing the need for co-transfection of multiple plasmids. We have tested our ranking system and new plasmid constructs to engineer the p53 mutants Y220C, R282W and R248Q into WT p53 cells and shown that these mutants cannot activate four p53 target genes, mimicking the behaviour of endogenous p53 mutations. This field will continue to rapidly progress, requiring new strategies such as we propose to ensure desired base-editing outcomes.

Computational models are becoming an increasingly valuable tool in biomedical research. Their accuracy and effectiveness, however, rely on the identification of suitable parameters and on appropriate validation of the in-silico framework. Both these steps are highly dependent on the experimental model used as a reference to acquire the data. Selecting the most appropriate experimental framework thus becomes key, together with the analysis of the effect of combining results from different experimental models, a common practice often necessary due to limited data availability. In this work, the same in-silico model of ovarian cancer cell growth and metastasis, was calibrated with datasets acquired from traditional 2D monolayers, 3D cell culture models or a combination of the two. The comparison between the parameters sets obtained in the different conditions, together with the corresponding simulated behaviours, is presented. It provides a framework for the study of the effect of the different experimental models on the development of computational systems. This work also provides a set of general guidelines for the comparative testing and selection of experimental models and protocols to be used for parameter optimization in computational models.

Ovarian cancer has the highest mortality of all of the gynecological malignancies. There are several distinct histotypes of this malignancy characterized by specific molecular events and clinical behavior. These histotypes have differing responses to platinum-based drugs that have been the mainstay of therapy for ovarian cancer for decades. For histotypes that initially respond to a chemotherapeutic regime of carboplatin and paclitaxel such as high-grade serous ovarian cancer, the development of chemoresistance is common and underpins incurable disease. Recent discoveries have led to the clinical use of PARP (poly ADP ribose polymerase) inhibitors for ovarian cancers defective in homologous recombination repair, as well as the anti-angiogenic bevacizumab. While predictive molecular testing involving identification of a genomic scar and/or the presence of germline or somatic BRCA1 or BRCA2 mutation are in clinical use to inform the likely success of a PARP inhibitor, no similar tests are available to identify women likely to respond to bevacizumab. Functional tests to predict patient response to any drug are, in fact, essentially absent from clinical care. New drugs are needed to treat ovarian cancer. In this review, we discuss applications to address the currently unmet need of developing physiologically relevant in vitro and ex vivo models of ovarian cancer for fundamental discovery science, and personalized medicine approaches. Traditional two-dimensional (2D) in vitro cell culture of ovarian cancer lacks critical cell-to-cell interactions afforded by culture in three-dimensions. Additionally, modelling interactions with the tumor microenvironment, including the surface of organs in the peritoneal cavity that support metastatic growth of ovarian cancer, will improve the power of these models. Being able to reliably grow pri

The non-canonical Wnt signalling receptor ROR1 is aberrantly expressed in numerous cancers, including ovarian and endometrial cancer. We previously reported that silencing ROR1 could inhibit the proliferation and metastatic potential of ovarian and endometrial cancer cells in vitro. Zilovertamab is an ROR1-targeting humanised monoclonal antibody, with demonstrated safety and efficacy in clinical trials of several ROR1-related malignancies. The aim of this study was to investigate the potential of zilovertamab alone, or in combination with commonly utilised gynaecological cancer therapies (cisplatin, paclitaxel and the PARP inhibitor—Olaparib) on high-grade serous ovarian cancer (HGSOC), including models of platinum resistance and homologous recombination deficiency (CaOV3, CaOV3CisR, PEO1 and PEO4) and endometrial cancer (EC) cell lines (Ishikawa and KLE). The effect of zilovertamab (at 25 µg/mL or 50 µg/mL) +/− agents was investigated using the IncuCyte S3 Live Cell imaging system. Zilovertamab alone inhibited the proliferation of HGSOC and EC cells in vitro, including in models of platinum resistance and homologous recombination deficiency. In general, the addition of commonly used chemotherapies to a fixed dose of zilovertamab did not enhance the observed anti-proliferative activity. This study supports the potential of zilovertamab, or other ROR1-targeting therapies, for treating women with HGSOC and EC.

The advent of molecular targeted therapies has made a significant impact on survival of women with ovarian cancer who have defects in homologous recombination repair (HRR). High-grade serous ovarian cancer (HGSOC) is the most common histological subtype of ovarian cancer, with over 50% displaying defective HRR. Poly ADP ribose polymerases (PARPs) are a family of enzymes that catalyse the transfer of ADP-ribose to target proteins, functioning in fundamental cellular processes including transcription, chromatin remodelling and DNA repair. In cells with deficient HRR, PARP inhibitors (PARPis) cause synthetic lethality leading to cell death. Despite the major advances that PARPis have heralded for women with ovarian cancer, questions and challenges remain, including: can the benefits of PARPis be brought to a wider range of women with ovarian cancer; can other drugs in clinical use function in a similar way or with greater efficacy than currently clinically approved PARPis; what can we learn from long-term responders to PARPis; can PARPis sensitise ovarian cancer cells to immunotherapy; and can synthetic lethal strategies be employed more broadly to develop new therapies for women with ovarian cancer. We examine these, and other, questions with focus on improving outcomes for women with ovarian cancer.

The epidermal growth factor receptor (EGFR) is overexpressed in many types of cancer, including epithelial ovarian cancer (EOC), and its expression has been found to correlate with advanced stage and poor prognosis. The EGFR ligand amphiregulin (AREG) has been investigated as a target for human cancer therapy and is known to have an autocrine role in many cancers. A cytokine array identified AREG as one of several cytokines upregulated by EGF in a phosphatidylinositol 3-kinase (PI3-K) dependent manner in EOC cells. To investigate the functional role of AREG in EOC, its effect on cellular migration and proliferation was assessed in two EOC cells lines, OV167 and SKOV3. AREG increased both migration and proliferation of EOC cell line models through activation of PI3-K signaling, but independent of mitogen activated protein kinase (MAPK) signaling. Through an AREG autocrine loop mediated via PI3-K, upregulation of AREG led to increased levels of both AREG transcript and secreted AREG, while downregulation of endogenous AREG decreased the ability of exogenous AREG to induce cell migration and proliferation. Further, inhibition of endogenous AREG activity or metalloproteinase activity decreased EGF-induced EOC migration and proliferation, indicating a role for soluble endogenous AREG in mediating the functional effects of EGFR in inducing migration and proliferation in EOC.

© 2018 The Author(s). Published by Wolters Kluwer Health, Inc. The gene CDC73 (previously known as HRPT2) encodes the protein parafibromin. Biallelic mutation of CDC73 is strongly associated with malignancy in parathyroid tumors. Heterozygous germline mutations cause hyperparathyroidism jaw tumor syndrome,which is associated with a high life-time risk of parathyroid carcinoma. Therefore loss of parafibromin expression by immunohistochemistry may triage genetic testing for hyperparathyroidism jaw tumor syndrome and be associated with malignant behavior in atypical parathyroid tumors. We share our experience that parafibromin-negative parathyroid tumors show distinctive morphology. We searched our institutional database for parathyroid tumors demonstrating complete loss of nuclear expression of parafibromin with internal positive controls. Forty-three parafibromin-negative tumors from 40 (5.1%) of 789 patients undergoing immunohistochemistry were identified. Thirty-three (77%) were external consultation cases; the estimated incidence in unselected tumors was 0.19%. Sixteen (37.2%) fulfilled World Health Organization 2017 criteria for parathyroid carcinoma and 63% had serum calcium greater than 3mmol/L. One of 27 (3.7%) noninvasive but parafibromin-negative tumors subsequently metastasized. Parafibromin-negative patients were younger (mean, 36 vs. 63 y; P<0.001) and had larger tumors (mean, 3.04 vs. 0.62 g; P<0.001). Not all patients had full testing, but 26 patients had pathogenic CDC73 mutation/deletions confirmed in tumor (n=23) and/or germline (n=16). Parafibromin-negative tumors demonstrated distinctive morphology including extensive sheet-like rather than acinar growth, eosinophilic cytoplasm, nuclear enlargement with distinctive coarse chromatin, perinuclear cytoplasmic clearing, a prominent arborizing vasculature, and, frequently, a thick capsule. Microcystic change was found in 21 (48.8%). In conclusion, there are previously unrecognized morphologic clues to p

Germline alterations of the tumor suppressor PTEN have been extensively characterized in patients with PTEN hamartoma tumor syndromes, encompassing subsets of Cowden syndrome, Bannayan-Riley-Ruvalcaba syndrome, Proteus and Proteus-like syndromes, as well as autism spectrum disorder. Studies have shown an increase in the risk of developing specific cancer types in the presence of a germline PTEN mutation. Furthermore, outside of the familial setting, somatic variants of PTEN occur in numerous malignancies. Here we introduce and discuss the prospect of moving toward a systems pathology approach for PTEN diagnostics, incorporating clinical and molecular pathology data with the goal of improving the clinical management of patients with a PTEN mutation. Detection of a germline PTEN mutation can inform cancer surveillance and in the case of somatic mutation, have value in predicting disease course. Given that PTEN functions in the PI3K/AKT/mTOR pathway, identification of a PTEN mutation may highlight new therapeutic opportunities and/or inform therapeutic choices.

© 2017 Elsevier Inc. Objectives The most widely used approach for the clinical management of women with high-grade serous ovarian cancer (HGSOC) is surgery, followed by platinum and taxane based chemotherapy. The degree of macroscopic disease remaining at the conclusion of surgery is a key prognostic factor determining progression free and overall survival. We sought to develop a non-invasive test to assist surgeons to determine the likelihood of achieving complete surgical resection. This knowledge could be used to plan surgical approaches for optimal clinical management. Methods We profiled 170 serum microRNAs (miRNAs) using the Serum/Plasma Focus miRNA PCR panel containing locked nucleic acid (LNA) primers (Exiqon) in women with HGSOC (N = 56) and age-matched healthy volunteers (N = 30). Additionally, we measured serum CA-125 levels in the same samples. The HGSOC cohort was further classified based on the degree of macroscopic disease at the conclusion of surgery. Stepwise logistic regression was used to identify predictive markers. Results We identified a combination of miR-375 and CA-125 as the strongest discriminator of healthy versus HGSOC serum, with an area under the curve (AUC) of 0.956. The inclusion of miR-210 increased the AUC to 0.984; however, miR-210 was affected by hemolysis. The combination of miR-34a-5p and CA-125 was the strongest predictor of completeness of surgical resection with an AUC of 0.818. Conclusion A molecular test incorporating circulating miRNA to predict completeness of surgical resection for women with HGSOC has the potential to contribute to planning for optimal patient management, ultimately improving patient outcome.

© The Author(s) 2017. Somatic mutation of the tumor suppressor gene TP53 is reported in at least 50% of human malignancies. Most high-grade serous ovarian cancers (HGSC) have a mutant TP53 allele. Accurate detection of these mutants in heterogeneous tumor tissue is paramount as therapies emerge to target mutant p53. We used a Fluidigm Access Array™ System with Massively Parallel Sequencing (MPS) to analyze DNA extracted from 76 serous ovarian tumors. This dataset has been made available to researchers through the European Genome-phenome Archive (EGA; EGAS00001002200). Herein, we present analyses of this dataset using HaplotypeCaller and MuTect2 through the Broad Institute's Genome Analysis Toolkit (GATK). We anticipate that this TP53 mutation dataset will be useful to researchers developing and testing new software to accurately determine high and low frequency variant alleles in heterogeneous aneuploid tumor tissue. Furthermore, the analysis pipeline we present provides a valuable framework for determining somatic variants more broadly in tumor tissue.

The tumour suppressor p53 is mutated in cancer, including over 96% of high-grade serous ovarian cancer (HGSOC). Mutations cause loss of wild-type p53 function due to either gain of abnormal function of mutant p53 (mutp53), or absent to low mutp53. Massively parallel sequencing (MPS) enables increased accuracy of detection of somatic variants in heterogeneous tumours. We used MPS and immunohistochemistry (IHC) to characterise HGSOCs for TP53 mutation and p53 expression. TP53 mutation was identified in 94% (68/72) of HGSOCs, 62% of which were missense. Missense mutations demonstrated high p53 by IHC, as did 35% (9/26) of non-missense mutations. Low p53 was seen by IHC in 62% of HGSOC associated with non-missense mutations. Most wild-type TP53 tumours (75%, 6/8) displayed intermediate p53 levels. The overall sensitivity of detecting a TP53 mutation based on classification as 'Low', 'Intermediate' or 'High' for p53 IHC was 99%, with a specificity of 75%. We suggest p53 IHC can be used as a surrogate marker of TP53 mutation in HGSOC; however, this will result in misclassification of a proportion of TP53 wild-type and mutant tumours. Therapeutic targeting of mutp53 will require knowledge of both TP53 mutations and mutp53 expression.

© 2016 Shah 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. microRNAs have emerged as powerful regulators of many biological processes, and their expression in many cancer tissues has been shown to correlate with clinical parameters such as cancer type and prognosis. Present in a variety of biological fluids, microRNAs have been described as a 'gold mine' of potential noninvasive biomarkers. Release of microRNA content of blood cells upon hemolysis dramatically alters the microRNA profile in blood, potentially affecting levels of a significant number of proposed biomarker microRNAs and, consequently, accuracy of serum or plasma-based tests. Several methods to detect low levels of hemolysis have been proposed; however, a direct comparison assessing their sensitivities is currently lacking. In this study, we evaluated the sensitivities of four methods to detect hemolysis in serum (listed in the order of sensitivity): measurement of hemoglobin using a Coulter1AcT diff™Analyzer, visual inspection, the absorbance of hemoglobin measured by spectrophotometry at 414 nm and the ratio of red blood cell-enriched miR- 451a to the reference microRNA miR-23a-3p. The miR ratio detected hemolysis down to approximately 0.001%, whereas the Coulter1AcT diff™Analyzer was unable to detect hemolysis lower than 1%. The spectrophotometric method could detect down to 0.004% hemolysis, and correlated with the miR ratio. Analysis of hemolysis in a cohort of 86 serum samples from cancer patients and healthy controls showed that 31 of 86 (36%) were predicted by the miR ratio to be hemolyzed, whereas only 8 of these samples (9%) showed visible pink discoloration. Using receiver operator characteristic (ROC) analyses, we identified absorbance cutoffs of 0.072 and 0.3 that could identify samples with low an

Epithelial ovarian cancer has the highest mortality of the gynecological malignancies. High grade serous epithelial ovarian cancer (SEOC) is the most common subtype, with the majority of women presenting with advanced disease where 5-year survival is around 25%. Platinum-based chemotherapy in combination with paclitaxel remains the most effective treatment despite platinum therapies being introduced almost 40 years ago. Advances in molecular medicine are underpinning new strategies for the treatment of cancer. Major advances have been made by international initiatives to sequence cancer genomes. For SEOC, with the exception of TP53 that is mutated in virtually 100% of these tumors, there is no other gene mutated at high frequency. There is extensive copy number variation, as well as changes in methylation patterns that will influence gene expression. To date, the role of histones and their post-translational modifications in ovarian cancer is a relatively understudied field. Post-translational histone modifications play major roles in gene expression as they direct the configuration of chromatin and so access by transcription factors. Histone modifications include methylation, acetylation, and monoubiquitination, with involvement of enzymes including histone methyltransferases, histone acetyltransferases/deacetylases, and ubiquitin ligases/deubiquitinases, respectively. Complexes such as the Polycomb repressive complex also play roles in the control of histone modifications and more recently roles for long non-coding RNA and microRNAs are emerging. Epigenomic-based therapies targeting histone modifications are being developed and offer new approaches for the treatment of ovarian cancer. Here, we discuss histone modifications and their aberrant regulation in malignancy and specifically in ovarian cancer. We review current and upcoming histone-based therapies that have the potential to inform and improve treatment strategies for women with ovarian cancer.

Introduction: Serum profiling using proteomic techniques has great potential to detect biomarkers that might improve diagnosis and predict outcome for breast cancer patients (BC). This study used surface-enhanced laser desorption/ionization time-of-flight (SELDI-TOF) mass spectrometry (MS) to identify differentially expressed proteins in sera from BC and healthy volunteers (HV), with the goal of developing a new prognostic biomarker panel.Methods: Training set serum samples from 99 BC and 51 HV subjects were applied to four adsorptive chip surfaces (anion-exchange, cation-exchange, hydrophobic, and metal affinity) and analyzed by time-of-flight MS. For validation, 100 independent BC serum samples and 70 HV samples were analyzed similarly. Cluster analysis of protein spectra was performed to identify protein patterns related to BC and HV groups. Univariate and multivariate statistical analyses were used to develop a protein panel to distinguish breast cancer sera from healthy sera, and its prognostic potential was evaluated.Results: From 51 protein peaks that were significantly up- or downregulated in BC patients by univariate analysis, binary logistic regression yielded five protein peaks that together classified BC and HV with a receiver operating characteristic (ROC) area-under-the-curve value of 0.961. Validation on an independent patient cohort confirmed the five-protein parameter (ROC value 0.939). The five-protein parameter showed positive association with large tumor size (P = 0.018) and lymph node involvement (P = 0.016). By matrix-assisted laser desorption/ionization time-of-flight (MALDI-TOF) MS, immunoprecipitation and western blotting the proteins were identified as a fragment of apolipoprotein H (ApoH), ApoCI, complement C3a, transthyretin, and ApoAI. Kaplan-Meier analysis on 181 subjects after median follow-up of >5 years demonstrated that the panel significantly predicted disease-free survival (P = 0.005), its efficacy apparently greater in women with

Background:Tissue protein expression profiling has the potential to detect new biomarkers to improve breast cancer (BC) diagnosis, staging, and prognostication. This study aimed to identify tissue proteins that differentiate breast cancer tissue from healthy breast tissue using protein chip mass spectrometry and to examine associations with conventional pathological features.Methods:To develop a training model, 82 BC and 82 adjacent unaffected tissue (AT) samples were analysed on cation-exchange protein chips by time-of-flight mass spectrometry. For validation, 89 independent BC and AT sample pairs were analysed.Results:From the protein peaks that were differentially expressed between BC and AT by univariate analysis, binary logistic regression yielded two peaks that together classified BC and AT with a ROC area under the curve of 0.92. Two proteins, ubiquitin and S100P (in a novel truncated form), were identified by liquid chromatography/tandem mass spectrometry and validated by immunoblotting and reactive-surface protein chip immunocapture. The combined marker panel was positively associated with high histologic grade, larger tumour size, lymphovascular invasion, ER and PR positivity, and HER2 overexpression, suggesting that it may be associated with a HER2-enriched molecular subtype of breast cancer.Conclusion:This independently validated protein panel may be valuable in the classification and prognostication of breast cancer patients. © 2013 Cancer Research UK. All rights reserved.

Stone, M. H., O’Bryant, H. S., Hornsby, G., Cunanan, A., Mizuguchi, S., Suarez, D. G., South, M., Marsh, D., Haff, G. G., Ramsey, M. W., Beckham, G. K., Santana, H. A. P., Wagle, J. P., Stone, M. E., & Pierce, K. C. (2019). Using the isometric midthigh pull in the monitoring of weightlifters: 25+ years of experience. Professional Strength and Conditioning, 54, 19-26. https://www.uksca.org.uk/uksca-iq-article/screening/1890/using-the-isometric-midthigh-pull-in-the-monitoring-of-weightlifters-25-years-of-experience

Several poly (adenosine diphosphate-ribose) polymerase (PARP) inhibitors are now in clinical use for tumours with defects in BReast CAncer genes BRCA1 or BRCA2 that result in deficient homologous recombination repair (HRR). Use of olaparib, niraparib or rucaparib for the treatment of high-grade serous ovarian cancer, including in the maintenance setting, has extended both progression free and overall survival for women with this malignancy. While different PARP inhibitors (PARPis) are mechanistically similar, differences are apparent in their chemical structures, toxicity profiles, PARP trapping abilities and polypharmacological landscapes. We have treated ovarian cancer cell line models of known BRCA status, including the paired cell lines PEO1 and PEO4, and UWB1.289 and UWB1.289+BRCA1, with five PARPis (olaparib, niraparib, rucaparib, talazoparib and veliparib) and observed differences between PARPis in both cell viability and cell survival. A cell line model of acquired resistance to veliparib showed increased resistance to the other four PARPis tested, suggesting that acquired resistance to one PARPi may not be able to be rescued by another. Lastly, as a proof of principle, HRR proficient ovarian cancer cells were sensitised to PARPis by depletion of BRCA1. In the future, guidelines will need to emerge to assist clinicians in matching specific PARPis to specific patients and tumours.

Several poly (adenosine diphosphate-ribose) polymerase (PARP) inhibitors are now in clinical use for tumours with defects in BReast CAncer genes BRCA1 or BRCA2 that result in deficient homologous recombination repair (HRR). Use of olaparib, niraparib or rucaparib for the treatment of high-grade serous ovarian cancer, including in the maintenance setting, has extended both progression free and overall survival for women with this malignancy. While different PARP inhibitors (PARPis) are mechanistically similar, differences are apparent in their chemical structures, toxicity profiles, PARP trapping abilities and polypharmacological landscapes. We have treated ovarian cancer cell line models of known BRCA status, including the paired cell lines PEO1 and PEO4, and UWB1.289 and UWB1.289+BRCA1, with five PARPis (olaparib, niraparib, rucaparib, talazoparib and veliparib) and observed differences between PARPis in both cell viability and cell survival. A cell line model of acquired resistance to veliparib showed increased resistance to the other four PARPis tested, suggesting that acquired resistance to one PARPi may not be able to be rescued by another. Lastly, as a proof of principle, HRR proficient ovarian cancer cells were sensitised to PARPis by depletion of BRCA1. In the future, guidelines will need to emerge to assist clinicians in matching specific PARPis to specific patients and tumours.