Improving Specificity for Ovarian Cancer Screening Using a Novel Extracellular Vesicle-Based Blood Test: Performance in a Training and Verification Cohort.

The low incidence of ovarian cancer (OC) dictates that any screening strategy needs to be both highly sensitive and highly specific. This study explored the utility of detecting multiple colocalized proteins or glycosylation epitopes on single tumor-associated extracellular vesicles from blood. The novel Mercy Halo Ovarian Cancer Test (OC Test) uses immunoaffinity capture of tumor-associated extracellular vesicles, followed by proximity-ligation real-time quantitative PCR to detect combinations of up to three biomarkers to maximize specificity and measures multiple combinations to maximize sensitivity. A high-grade serous carcinoma (HGSC) case-control training set of EDTA plasma samples from 397 women was used to lock down the test design, the data interpretation algorithm, and the cutoff between cancer and noncancer. Performance was verified and compared with cancer antigen 125 in an independent blinded case-control set of serum samples from 390 women (132 controls, 66 HGSC, 83 non-HGSC OC, and 109 benign). In the verification study, the OC Test showed a specificity of 97.0% (128/132; 95% CI, 92.4%-99.6%), a HGSC sensitivity of 97.0% (64/66; 95% CI, 87.8%-99.2%), and an area under the curve of 0.97 (95% CI, 0.93-0.99) and detected 73.5% (61/83; 95% CI, 62.7%-82.6%) of the non-HGSC OC cases. This test exhibited fewer false positives in subjects with benign ovarian tumors, nonovarian cancers, and inflammatory conditions when compared with cancer antigen 125. The combined sensitivity and specificity of this new test suggests it may have potential in OC screening.

Getting our ducks in a row: The need for data utility comparisons of healthcare systems data for clinical trials.

BACKGROUND: Better use of healthcare systems data, collected as part of interactions between patients and the healthcare system, could transform planning and conduct of randomised controlled trials. Multiple challenges to widespread use include whether healthcare systems data captures sufficiently well the data traditionally captured on case report forms. "Data Utility Comparison Studies" (DUCkS) assess the utility of healthcare systems data for RCTs by comparison to data collected by the trial. Despite their importance, there are few published UK examples of DUCkS. METHODS-AND-RESULTS: Building from ongoing and selected recent examples of UK-led DUCkS in the literature, we set out experience-based considerations for the conduct of future DUCkS. Developed through informal iterative discussions in many forums, considerations are offered for planning, protocol development, data, analysis and reporting, with comparisons at "patient-level" or "trial-level", depending on the item of interest and trial status. DISCUSSION: DUCkS could be a valuable tool in assessing where healthcare systems data can be used for trials and in which trial teams can play a leading role. There is a pressing need for trials to be more efficient in their delivery and research waste must be reduced. Trials have been making inconsistent use of healthcare systems data, not least because of an absence of evidence of utility. DUCkS can also help to identify challenges in using healthcare systems data, such as linkage (access and timing) and data quality. We encourage trial teams to incorporate and report DUCkS in trials and funders and data providers to support them.

Plasma cell-free DNA methylation analysis for ovarian cancer detection: Analysis of samples from a case-control study and an ovarian cancer screening trial.

Analysis of cell-free DNA methylation (cfDNAme), alone or combined with CA125, could help to detect ovarian cancers earlier and may reduce mortality. We assessed cfDNAme in regions of ZNF154, C2CD4D and WNT6 via targeted bisulfite sequencing in diagnostic and early detection (preceding diagnosis) settings. Diagnostic samples were obtained via prospective blood collection in cell-free DNA tubes in a convenience series of patients with a pelvic mass. Early detection samples were matched case-control samples derived from the UK Familial Ovarian Cancer Screening Study (UKFOCSS). In the diagnostic set (ncases = 27, ncontrols = 41), the specificity of cfDNAme was 97.6% (95% CI: 87.1%-99.9%). High-risk cancers were detected with a sensitivity of 80% (56.3%-94.3%). Combination of cfDNAme and CA125 resulted in a sensitivity of 94.4% (72.7%-99.9%) for high-risk cancers. Despite technical issues in the early detection set (ncases = 29, ncontrols = 29), the specificity of cfDNAme was 100% (88.1%-100.0%). We detected 27.3% (6.0%-61.0%) of high-risk cases with relatively lower genomic DNA (gDNA) contamination. The sensitivity rose to 33.3% (7.5%-70.1%) in samples taken <1 year before diagnosis. We detected ovarian cancer in several patients up to 1 year before diagnosis despite technical limitations associated with archival samples (UKFOCSS). Combined cfDNAme and CA125 assessment may improve ovarian cancer screening in high-risk populations, but future large-scale prospective studies will be required to validate current findings.

Insights from UKCTOCS for design, conduct and analyses of large randomised controlled trials.

Abstract: Randomised controlled trials are challenging to deliver. There is a constant need to review and refine recruitment and implementation strategies if they are to be completed on time and within budget. We present the strategies adopted in the United Kingdom Collaborative Trial of Ovarian Cancer Screening, one of the largest individually randomised controlled trials in the world. The trial recruited over 202,000 women (2001-5) and delivered over 670,000 annual screens (2001-11) and over 3 million women-years of follow-up (2001-20). Key to the successful completion were the involvement of senior investigators in the day-to-day running of the trial, proactive trial management and willingness to innovate and use technology. Our underlying ethos was that trial participants should always be at the centre of all our processes. We ensured that they were able to contact either the site or the coordinating centre teams for clarifications about their results, for follow-up and for rescheduling of appointments. To facilitate this, we shared personal identifiers (with consent) with both teams and had dedicated reception staff at both site and coordinating centre. Key aspects were a comprehensive online trial management system which included an electronic data capture system (resulting in an almost paperless trial), biobanking, monitoring and project management modules. The automation of algorithms (to ascertain eligibility and classify results and ensuing actions) and processes (scheduling of appointments, printing of letters, etc.) ensured the protocol was closely followed and timelines were met. Significant engagement with participants ensured retention and low rates of complaints. Our solutions to the design, conduct and analyses issues we faced are highly relevant, given the renewed focus on trials for early detection of cancer. Future work: There is a pressing need to increase the evidence base to support decision making about all aspects of trial methodology. Trial registration: ISRCTN-22488978; ClinicalTrials.gov-NCT00058032. Funding: This article presents independent research funded by the National Institute for Health and Care Research (NIHR) Health Technology Assessment programme as award number 16/46/01. The long-term follow-up UKCTOCS (2015 20) was supported by National Institute for Health and Care Research (NIHR HTA grant 16/46/01), Cancer Research UK, and The Eve Appeal. UKCTOCS (2001-14) was funded by the MRC (G9901012 and G0801228), Cancer Research UK (C1479/A2884), and the UK Department of Health, with additional support from The Eve Appeal. Researchers at UCL were supported by the NIHR UCL Hospitals Biomedical Research Centre and by the MRC Clinical Trials Unit at UCL core funding (MC_UU_00004/09, MC_UU_00004/08, MC_UU_00004/07). The views expressed are those of the authors and not necessarily those of the NHS, the NIHR, or the UK Department of Health and Social Care.

Randomised controlled trials help us decide whether new health-care approaches are better than those in current use. To successfully complete these on time and within budget, there is a constant need to review and revise the procedures used for delivering various aspects such as invitation, enrolment, follow-up of participants, delivery of the new test, data collection, and analysis. We report on the processes used in the United Kingdom Collaborative Trial of Ovarian Cancer Screening, one of the largest such trials. The United Kingdom Collaborative Trial of Ovarian Cancer Screening enrolled over 202,000 women (2001­5), delivered over 670,000 yearly screens (2001­11) and followed all participants until 2020. Key to our successful completion were the involvement of senior investigators in day-to-day running of the trial, a pre-emptive approach to issues, a willingness to innovate, and the use of technology. Our underlying ethos was that trial participants should always be at the centre of all our processes. We ensured that they were able to always contact either their local or the central team for clarifications and rescheduling of appointments. To facilitate this, we shared participant contact details (with consent) with both teams. We built a comprehensive electronic system to manage all aspects of the trial. This included online forms that the teams completed in real time (resulting in an almost paperless trial) and systems to check and manage trial processes and track blood samples. We automated key steps such as checking whether participants were eligible, assigning correct action based on results of screening tests, scheduling appointments and printing letters. As a result, all participants were treated as set out in the trial plan. Our engagement with participants ensured that they continued participating and we had a low rate of complaints. We faced issues with regard to our initial trial design and the way we planned to analyse the data. We feel that our solutions are highly relevant, especially as there is a renewed focus on trials for early detection of cancer.

Tumour stage, treatment, and survival of women with high-grade serous tubo-ovarian cancer in UKCTOCS: an exploratory analysis of a randomised controlled trial.

BACKGROUND: In UKCTOCS, there was a decrease in the diagnosis of advanced stage tubo-ovarian cancer but no reduction in deaths in the multimodal screening group compared with the no screening group. Therefore, we did exploratory analyses of patients with high-grade serous ovarian cancer to understand the reason for the discrepancy. METHODS: UKCTOCS was a 13-centre randomised controlled trial of screening postmenopausal women from the general population, aged 50-74 years, with intact ovaries. The trial management system randomly allocated (2:1:1) eligible participants (recruited from April 17, 2001, to Sept 29, 2005) in blocks of 32 using computer generated random numbers to no screening or annual screening (multimodal screening or ultrasound screening) until Dec 31, 2011. Follow-up was through national registries until June 30, 2020. An outcome review committee, masked to randomisation group, adjudicated on ovarian cancer diagnosis, histotype, stage, and cause of death. In this study, analyses were intention-to-screen comparisons of women with high-grade serous cancer at censorship (Dec 31, 2014) in multimodal screening versus no screening, using descriptive statistics for stage and treatment endpoints, and the Versatile test for survival from randomisation. This trial is registered with the ISRCTN Registry, 22488978, and ClinicalTrials.gov, NCT00058032. FINDINGS: 202 562 eligible women were recruited (50 625 multimodal screening; 50 623 ultrasound screening; 101 314 no screening). 259 (0·5%) of 50 625 participants in the multimodal screening group and 520 (0·5%) of 101 314 in the no screening group were diagnosed with high-grade serous cancer. In the multimodal screening group compared with the no screening group, fewer were diagnosed with advanced stage disease (195 [75%] of 259 vs 446 [86%] of 520; p=0·0003), more had primary surgery (158 [61%] vs 219 [42%]; p<0·0001), more had zero residual disease following debulking surgery (119 [46%] vs 157 [30%]; p<0·0001), and more received treatment including both surgery and chemotherapy (192 [74%] vs 331 [64%]; p=0·0032). There was no difference in the first-line combination chemotherapy rate (142 [55%] vs 293 [56%]; p=0·69). Median follow-up from randomisation of 779 women with high-grade serous cancer in the multimodal and no screening groups was 9·51 years (IQR 6·04-13·00). At censorship (June 30, 2020), survival from randomisation was longer in women with high-grade serous cancer in the multimodal screening group than in the no screening group with absolute difference in survival of 6·9% (95% CI 0·4-13·0; p=0·042) at 18 years (21% [95% CI 15·6-26·2] vs 14% [95% CI 10·5-17·4]). INTERPRETATION: To our knowledge, this is the first evidence that screening can detect high-grade serous cancer earlier and lead to improved short-term treatment outcomes compared with no screening. The potential survival benefit for women with high-grade serous cancer was small, most likely due to only modest gains in early detection and treatment improvement, and tumour biology. The cumulative results of the trial suggest that surrogate endpoints for disease-specific mortality should not currently be used in screening trials for ovarian cancer. FUNDING: National Institute for Health Research, Medical Research Council, Cancer Research UK, The Eve Appeal.

Discovery and validation of serum glycoprotein biomarkers for high grade serous ovarian cancer.

PURPOSE: This study aimed to identify serum glycoprotein biomarkers for early detection of high-grade serous ovarian cancer (HGSOC), the most common and aggressive histotype of ovarian cancer. EXPERIMENTAL DESIGN: The glycoproteomics pipeline lectin magnetic bead array (LeMBA)-mass spectrometry (MS) was used in age-matched case-control serum samples. Clinical samples collected at diagnosis were divided into discovery (n = 30) and validation (n = 98) sets. We also analysed a set of preclinical sera (n = 30) collected prior to HGSOC diagnosis in the UK Collaborative Trial of Ovarian Cancer Screening. RESULTS: A 7-lectin LeMBA-MS/MS discovery screen shortlisted 59 candidate proteins and three lectins. Validation analysis using 3-lectin LeMBA-multiple reaction monitoring (MRM) confirmed elevated A1AT, AACT, CO9, HPT and ITIH3 and reduced A2MG, ALS, IBP3 and PON1 glycoforms in HGSOC. The best performing multimarker signature had 87.7% area under the receiver operating curve, 90.7% specificity and 70.4% sensitivity for distinguishing HGSOC from benign and healthy groups. In the preclinical set, CO9, ITIH3 and A2MG glycoforms were altered in samples collected 11.1 ± 5.1 months prior to HGSOC diagnosis, suggesting potential for early detection. CONCLUSIONS AND CLINICAL RELEVANCE: Our findings provide evidence of candidate early HGSOC serum glycoprotein biomarkers, laying the foundation for further study in larger cohorts.

Serum biomarker-based early detection of pancreatic ductal adenocarcinomas with ensemble learning.

BACKGROUND: Earlier detection of pancreatic ductal adenocarcinoma (PDAC) is key to improving patient outcomes, as it is mostly detected at advanced stages which are associated with poor survival. Developing non-invasive blood tests for early detection would be an important breakthrough. METHODS: The primary objective of the work presented here is to use a dataset that is prospectively collected, to quantify a set of cancer-associated proteins and construct multi-marker models with the capacity to predict PDAC years before diagnosis. The data used is part of a nested case-control study within the UK Collaborative Trial of Ovarian Cancer Screening and is comprised of 218 samples, collected from a total of 143 post-menopausal women who were diagnosed with pancreatic cancer within 70 months after sample collection, and 249 matched non-cancer controls. We develop a stacked ensemble modelling technique to achieve robustness in predictions and, therefore, improve performance in newly collected datasets. RESULTS: Here we show that with ensemble learning we can predict PDAC status with an AUC of 0.91 (95% CI 0.75-1.0), sensitivity of 92% (95% CI 0.54-1.0) at 90% specificity, up to 1 year prior to diagnosis, and at an AUC of 0.85 (95% CI 0.74-0.93) up to 2 years prior to diagnosis (sensitivity of 61%, 95% CI 0.17-0.83, at 90% specificity). CONCLUSIONS: The ensemble modelling strategy explored here outperforms considerably biomarker combinations cited in the literature. Further developments in the selection of classifiers balancing performance and heterogeneity should further enhance the predictive capacity of the method.

Pancreatic cancers are most frequently detected at an advanced stage. This limits treatment options and contributes to the dismal survival rates currently recorded. The development of new tests that could improve detection of early-stage disease is fundamental to improve outcomes. Here, we use advanced data analysis techniques to devise an early detection test for pancreatic cancer. We use data on markers in the blood from people enrolled on a screening trial. Our test correctly identifies as positive for pancreatic cancer 91% of the time up to 1 year prior to diagnosis, and 78% of the time up to 2 years prior to diagnosis. These results surpass previously reported tests and should encourage further evaluation of the test in different populations, to see whether it should be adopted in the clinic.

Performance Characteristics of the Ultrasound Strategy during Incidence Screening in the UK Collaborative Trial of Ovarian Cancer Screening (UKCTOCS).

Randomised controlled trials of ovarian cancer (OC) screening have not yet demonstrated an impact on disease mortality. Meanwhile, the screening data from clinical trials represents a rich resource to understand the performance of modalities used. We report here on incidence screening in the ultrasound arm of UKCTOCS. 44,799 of the 50,639 women who were randomised to annual screening with transvaginal ultrasound attended annual incidence screening between 28 April 2002 and 31 December 2011. Transvaginal ultrasound was used both as the first and the second line test. Participants were followed up through electronic health record linkage and postal questionnaires. Out of 280,534 annual incidence screens, 960 women underwent screen-positive surgery. 113 had ovarian/tubal cancer (80 invasive epithelial). Of the screen-detected invasive epithelial cancers, 37.5% (95% CI: 26.9-49.0) were Stage I/II. An additional 52 (50 invasive epithelial) were diagnosed within one year of their last screen. Of the 50 interval epithelial cancers, 6.0% (95% CI: 1.3-16.5) were Stage I/II. For detection of all ovarian/tubal cancers diagnosed within one year of screen, the sensitivity, specificity, and positive predictive values were 68.5% (95% CI: 60.8-75.5), 99.7% (95% CI: 99.7-99.7), and 11.8% (95% CI: 9.8-14) respectively. When the analysis was restricted to invasive epithelial cancers, sensitivity, specificity and positive predictive values were 61.5% (95% CI: 52.6-69.9); 99.7% (95% CI: 99.7-99.7) and 8.3% (95% CI: 6.7-10.3), with 12 surgeries per screen positive. The low sensitivity coupled with the advanced stage of interval cancers suggests that ultrasound scanning as the first line test might not be suitable for population screening for ovarian cancer. Trial registration: ISRCTN22488978. Registered on 6 April 2000.

UKCTOCS update: applying insights of delayed effects in cancer screening trials to the long-term follow-up mortality analysis.

BACKGROUND: During trials that span decades, new evidence including progress in statistical methodology, may require revision of original assumptions. An example is the continued use of a constant-effect approach to analyse the mortality reduction which is often delayed in cancer-screening trials. The latter led us to re-examine our approach for the upcoming primary mortality analysis (2020) of long-term follow-up of the United Kingdom Collaborative Trial of Ovarian Cancer Screening (LTFU UKCTOCS), having initially (2014) used the proportional hazards (PH) Cox model. METHODS: We wrote to 12 experts in statistics/epidemiology/screening trials, setting out current evidence, the importance of pre-specification, our previous mortality analysis (2014) and three possible choices for the follow-up analysis (2020) of the mortality outcome: (A) all data (2001-2020) using the Cox model (2014), (B) new data (2015-2020) only and (C) all data (2001-2020) using a test that allows for delayed effects. RESULTS: Of 11 respondents, eight supported changing the 2014 approach to allow for a potential delayed effect (option C), suggesting various tests while three favoured retaining the Cox model (option A). Consequently, we opted for the Versatile test introduced in 2016 which maintains good power for early, constant or delayed effects. We retained the Royston-Parmar model to estimate absolute differences in disease-specific mortality at 5, 10, 15 and 18 years. CONCLUSIONS: The decision to alter the follow-up analysis for the primary outcome on the basis of new evidence and using new statistical methodology for long-term follow-up is novel and has implications beyond UKCTOCS. There is an urgent need for consensus building on how best to design, test, estimate and report mortality outcomes from long-term randomised cancer screening trials. TRIAL REGISTRATION: ISRCTN22488978 . Registered on 6 April 2000.

Completeness and accuracy of national cancer and death registration for outcome ascertainment in trials-an ovarian cancer exemplar.

BACKGROUND: There is a trend to increasing use of routinely collected health data to ascertain outcome measures in trials. We report on the completeness and accuracy of national ovarian cancer and death registration in the United Kingdom Collaborative Trial of Ovarian Cancer Screening (UKCTOCS). METHODS: Of the 202,638 participants, 202,632 were successfully linked and followed through national cancer and death registries of Northern Ireland, Wales and England. Women with registrations of any of 19 pre-defined ICD-10 codes suggestive of tubo-ovarian cancer or notification of ovarian/tubal/peritoneal cancer from hospital episode statistics or trial sites were identified. Copies of hospital and primary care notes were retrieved and reviewed by an independent outcomes review committee. National registration of site and cause of death as ovarian/tubal/peritoneal cancer (C56/C57/C48) obtained up to 3 months after trial censorship was compared to that assigned by outcomes review (reference standard). RESULTS: Outcome review was undertaken in 3110 women on whom notification was received between 2001 and 2014. Ovarian cancer was confirmed in 1324 of whom 1125 had a relevant cancer registration. Sensitivity and specificity of ovarian/tubal/peritoneal cancer registration were 85.0% (1125/1324; 95% CI 83.7-86.2%) and 94.0% (1679/1786; 95% CI 93.2-94.8%), respectively. Of 2041 death registrations reviewed, 681 were confirmed to have a tubo-ovarian cancer of whom 605 had relevant death registration. Sensitivity and specificity were 88.8% (605/681; 95% CI 86.4-91.2%) and 96.7% (1482/1533, 95% CI 95.8-97.6%), respectively. When multiple electronic health record sources were considered, sensitivity for cancer site increased to 91.1% (1206/1324, 95% CI 89.4-92.5%) and for cause of death 94.0% (640/681, 95% CI 91.9-95.5%). Of 1232 with cancer registration, 8.7% (107/1232) were wrongly designated as ovarian/tubal/peritoneal cancers by the registry and 4.0% (47/1172) of confirmed tubo-ovarian cancers were mis-registered. In 656 with death registrations, 7.8% (51/656) were wrongly assigned as due to ovarian/tubal/peritoneal cancers while 6.2% (40/645) of confirmed tubo-ovarian cancer deaths were mis-registered. CONCLUSION: Follow-up of trial participants for tubo-ovarian cancer using national registry data will result in incomplete ascertainment, particularly of the site due in part to the latency of registration. This can be reduced by using other routinely collected data such as hospital episode statistics. Central adjudication by experts though resource intensive adds value by improving the accuracy of diagnoses. TRIAL REGISTRATION: ISRCTN: ISRCTN22488978 . Registered on 6 April 2000.

Ovarian cancer symptoms, routes to diagnosis and survival - Population cohort study in the 'no screen' arm of the UK Collaborative Trial of Ovarian Cancer Screening (UKCTOCS).

OBJECTIVE: There are widespread efforts to increase symptom awareness of 'pelvic/abdominal pain, increased abdominal size/bloating, difficulty eating/feeling full and urinary frequency/urgency' in an attempt to diagnose ovarian cancer earlier. Long-term survival of women with these symptoms adjusted for known prognostic factors is yet to be determined. This study explored the association of symptoms, routes and interval to diagnosis and long-term survival in a population-based cohort of postmenopausal women diagnosed with invasive epithelial tubo-ovarian cancer (iEOC) in the 'no screen' (control) UKCTOCS arm. METHODS: Of 101,299 women in the control arm, 574 were confirmed on outcome review to have iEOC between randomisation (2001-2005) and 31 December 2014. Data was extracted from medical notes and electronic records. A multivariable model was fitted for individual symptoms, time interval from symptom onset to diagnosis, route to diagnosis, speciality, morphological Type, age at diagnosis, year of diagnosis (period effect), stage, primary treatment, and residual disease. RESULTS: Women presenting with symptoms listed in the NICE guidelines (HR1.48, 95%CI1.16-1.89, p = 0.001) or the modified Goff Index (HR1·68, 95%CI1·32-2.13, p < 0.0001) had significantly worse survival than those who did not. Each additional presenting symptom decreased survival (HR1·20, 95%CI1·12-1·28, p < 0.0001). In multivariable analysis, in addition to advanced stage, increasing residual disease and inadequate primary treatment, abdominal pain and loss of appetite/feeling full were significantly associated with increased mortality. CONCLUSIONS: The ovarian cancer symptom indices identify postmenopausal women with a poorer prognosis. This study however cannot exclude the possibility of better outcomes in those who are aware and act on their symptoms.

The Enhanced Liver Fibrosis test is associated with liver-related outcomes in postmenopausal women with risk factors for liver disease.

BACKGROUND: Chronic liver disease (CLD) is usually asymptomatic but earlier detection is critical to permit life-saving interventions for those at risk due to high alcohol consumption and increased body mass index (BMI). The aim of this study was to estimate the association between the Enhanced Liver Fibrosis (ELF) test and liver-related events (LRE) and its performance in predicting LRE in postmenopausal women with risk factors in a nested case-control study within the United Kingdom Trial of Ovarian Cancer Screening (UKCTOCS). METHODS: In a cohort of 95,126 we performed a case-control study measuring ELF in blinded samples from 173 participants with self-reported high alcohol use and / or BMI ≥25 kg/m2 comprising all 58 cases who developed LRE and 115 controls matched for age, alcohol and BMI who did not develop LRE during median follow-up of 8.5 years. RESULTS: Using Cox regression at an ELF threshold of 10.51 hazard ratios (HR) for LRE were 4.88 (95% confidence interval (CI) 2.37-10.03) (unadjusted model) and 4.62 (95% CI 2.12-10.08) (adjusted for deprivation and self-reported hypertension, heart disease, hypercholesterolaemia and diabetes). At a threshold of 9.8 HR for LRE were 2.21 (95% CI 1.22-3.97) (unadjusted model) and 2.18 (95% CI 1.19-4.01) (adjusted). ELF was evaluated as a time dependent variable by generating time-dependent Cox models; HRs at an ELF threshold of 10.51 were 1.94 (95% CI 1.10-3.39) (unadjusted) and 2.05 (95% CI 1.16-3.64) (adjusted) and at a threshold of 9.8 HRs were 1.85 (95% CI 1.09-3.15) (unadjusted) and 1.80 (95% CI 1.04-3.13) (adjusted). Area under the receiver operating characteristic curve for recruitment ELF predicting LRE was 0.58 (95% CI 0.49-0.68), and for second subsequent ELF 0.61 (95% CI 0.52-0.71). CONCLUSION: This study demonstrates the association between ELF and CLD in postmenopausal women with risk factors for liver disease, creating the opportunity to intervene to reduce liver-related mortality and morbidity. Although larger studies are required, these results demonstrate the potential of ELF as a prognostic tool in health checks in primary care. TRIAL REGISTRATION: This study is nested in UKCTOCS. UKCTOCS is registered as an International Standard Randomised Controlled Trial, number ISRCTN22488978. Registered 06/04/2000.

The 14q32 maternally imprinted locus is a major source of longitudinally stable circulating microRNAs as measured by small RNA sequencing.

Understanding the normal temporal variation of serum molecules is a critical factor for identifying useful candidate biomarkers for the diagnosis and prognosis of chronic disease. Using small RNA sequencing in a longitudinal study of 66 women with no history of cancer, we determined the distribution and dynamics (via intraclass correlation coefficients, ICCs) of the miRNA profile over 3 time points sampled across 2-5 years in the course of the screening trial, UKCTOCS. We were able to define a subset of longitudinally stable miRNAs (ICC >0.75) that were individually discriminating of women who had no cancer over the study period. These miRNAs were dominated by those originating from the C14MC cluster that is subject to maternal imprinting. This assessment was not significantly affected by common confounders such as age, BMI or time to centrifugation nor alternative methods to data normalisation. Our analysis provides important benchmark data supporting the development of miRNA biomarkers for the impact of life-course exposure as well as diagnosis and prognostication of chronic disease.

Identification of a Biomarker Panel for Early Detection of Lung Cancer Patients.

Lung cancer is the most common cause of cancer-related mortality worldwide, characterized by late clinical presentation (49-53% of patients are diagnosed at stage IV) and consequently poor outcomes. One challenge in identifying biomarkers of early disease is the collection of samples from patients prior to symptomatic presentation. We used blood collected during surgical resection of lung tumors in an iTRAQ isobaric tagging experiment to identify proteins effluxing from tumors into pulmonary veins. Forty proteins were identified as having an increased abundance in the vein draining from the tumor compared to "healthy" pulmonary veins. These protein markers were then assessed in a second cohort that utilized the mass spectrometry (MS) technique: Sequential window acquisition of all theoretical fragment ion spectra (SWATH) MS. SWATH-MS was used to measure proteins in serum samples taken from 25 patients <50 months prior to and at lung cancer diagnosis and 25 matched controls. The SWATH-MS analysis alone produced an 11 protein marker panel. A machine learning classification model was generated that could discriminate patient samples from patients within 12 months of lung cancer diagnosis and control samples. The model was evaluated as having a mean AUC of 0.89, with an accuracy of 0.89. This panel was combined with the SWATH-MS data from one of the markers from the first cohort to create a 12 protein panel. The proteome signature developed for lung cancer risk can now be developed on further cohorts.

Modifying inter-cistronic sequence significantly enhances IRES dependent second gene expression in bicistronic vector: Construction of optimised cassette for gene therapy of familial hypercholesterolemia.

Internal ribosome entry site (IRES) sequences have become a valuable tool in the construction of gene transfer and therapeutic vectors for multi-cistronic gene expression from a single mRNA transcript. The optimal conditions for effective use of this sequence to construct a functional expression vector are not precisely defined but it is generally assumed that the internal ribosome entry site dependent expression of the second gene in such as cassette is less efficient than the cap-dependent expression of the first gene. Mainly tailoring inter-cistronic sequence significantly enhances IRES dependent second gene expression in bicistronic vector further in construction of optimised cassette for gene therapy of familial hypercholesterolemia. We tailored the size of the inter-cistronic spacer sequence at the 5' region of the internal ribosome entry site sequence using sequential deletions and demonstrated that the expression of the 3' gene can be significantly increased to similar levels as the cap-dependent expression of the 5' gene. Maximum expression efficiency of the downstream gene was obtained when the spacer is composed of 18-141 base pairs. In this case a single mRNA transcriptional unit containing both the first and the second Cistron was detected. Whilst constructs with spacer sequences of 216 bp or longer generate a single transcriptional unit containing only the first Cistron. This suggests that long spacers may affect transcription termination. When the spacer is 188 bp, both transcripts were produced simultaneously in most transfected cells, while a fraction of them expressed only the first but not the second gene. Expression analyses of vectors containing optimised cassettes clearly confirm that efficiency of gene transfer and biological activity of the expressed transgenic proteins in the transduced cells can be achieved. Furthermore, Computational analysis was carried out by molecular dynamics (MD) simulation to determine the most emerges as viable containing specific binding site and bridging of 5' and 3' ends involving direct RNA-RNA contacts and RNA-protein interactions. These results provide a mechanistic basis for translation stimulation and RNA resembling for the synergistic stimulation of cap-dependent translation.

Colorectal cancer ascertainment through cancer registries, hospital episode statistics, and self-reporting compared to confirmation by clinician: A cohort study nested within the UK Collaborative Trial of Ovarian Cancer Screening (UKCTOCS).

BACKGROUND: Electronic health records are frequently used for cancer epidemiology. We report on their quality for ascertaining colorectal cancer (CRC) in UK women. METHODS: Population-based, retrospective cohort study nested within the UK Collaborative Trial of Ovarian Cancer Screening (UKCTOCS). Postmenopausal women aged 50-74 who were diagnosed with CRC during 2001-11 following randomisation to the UKCTOCS were identified and their diagnosis confirmed with their treating clinician. The sensitivity and positive predictive value (PPV) of cancer and death registries, hospital episode statistics, and self-reporting were calculated by pairwise comparisons to the treating clinician's confirmation, while specificity and negative predictive value were estimated relative to expected cases. RESULTS: Notification of CRC events were received for 1,085 women as of 24 May 2011. Responses were received from 61% (660/1,085) of clinicians contacted. Nineteen women were excluded (18 no diagnosis date, one diagnosed after cut-off). Of the 641 eligible, 514 had CRC, 24 had a benign polyp, and 103 had neither diagnosis. The sensitivity of cancer registrations at one- and six-years post-diagnosis was 92 (95% CI 90-94) and 99% (97-100), respectively, with a PPV of 95% (95% CI 92/93-97). The sensitivity & PPV of cancer registrations (at one-year post-diagnosis) & hospital episode statistics combined were 98 (96-99) and 92% (89-94), respectively. CONCLUSIONS: Cancer and death registrations in the UK are a reliable resource for CRC ascertainment in women. Hospital episode statistics can supplement delays in cancer registration. Self-reporting seems less reliable.

Development and Validation of Apolipoprotein AI-Associated Lipoprotein Proteome Panel for the Prediction of Cholesterol Efflux Capacity and Coronary Artery Disease.

BACKGROUND: Cholesterol efflux capacity (CEC) is a measure of HDL function that, in cell-based studies, has demonstrated an inverse association with cardiovascular disease. The cell-based measure of CEC is complex and low-throughput. We hypothesized that assessment of the lipoprotein proteome would allow for precise, high-throughput CEC prediction. METHODS: After isolating lipoprotein particles from serum, we used LC-MS/MS to quantify 21 lipoprotein-associated proteins. A bioinformatic pipeline was used to identify proteins with univariate correlation to cell-based CEC measurements and generate a multivariate algorithm for CEC prediction (pCE). Using logistic regression, protein coefficients in the pCE model were reweighted to yield a new algorithm predicting coronary artery disease (pCAD). RESULTS: Discovery using targeted LC-MS/MS analysis of 105 training and test samples yielded a pCE model comprising 5 proteins (Spearman r = 0.86). Evaluation of pCE in a case-control study of 231 specimens from healthy individuals and patients with coronary artery disease revealed lower pCE in cases (P = 0.03). Derived within this same study, the pCAD model significantly improved classification (P < 0.0001). Following analytical validation of the multiplexed proteomic method, we conducted a case-control study of myocardial infarction in 137 postmenopausal women that confirmed significant separation of specimen cohorts in both the pCE (P = 0.015) and pCAD (P = 0.001) models. CONCLUSIONS: Development of a proteomic pCE provides a reproducible high-throughput alternative to traditional cell-based CEC assays. The pCAD model improves stratification of case and control cohorts and, with further studies to establish clinical validity, presents a new opportunity for the assessment of cardiovascular health.

Risk of chronic liver disease in post-menopausal women due to body mass index, alcohol and their interaction: a prospective nested cohort study within the United Kingdom Collaborative Trial of Ovarian Cancer Screening (UKCTOCS).

BACKGROUND: We investigated the risk of chronic liver disease (CLD) due to alcohol consumption and body mass index (BMI) and the effects of their interaction in a prospective cohort study of women recruited to the UKCTOCS trial. METHODS: 95,126 post-menopausal women without documented CLD were stratified into 12 groups defined by combinations of BMI (normal, overweight, obese) and alcohol consumption (none, <1-15, 16-20 and ≥21 units/week), and followed for an average of 5.1 years. Hazard ratios (HR) were calculated for incident liver-related events (LRE). RESULTS: First LREs were reported in 325 (0.34%) participants. Compared to women with normal BMI, HR = 1.44 (95% CI; 1.10-1.87) in the overweight group and HR = 2.25 (95% CI; 1.70-2.97) in the obese group, adjusted for alcohol and potential confounders. Compared to those abstinent from alcohol, HR = 0.70 (95% CI; 0.55-0.88) for <1-15 units/week, 0.93 (95% CI; 0.50-1.73) for 16-20 units/week and 1.82 (95% CI; 0.97-3.39) for ≥21 units/week adjusted for BMI and potential confounders. Compared to women with normal BMI drinking no alcohol, HR for LRE in obese women consuming ≥21 units/week was 2.86 (95% CI; 0.67-12.42), 1.58 (95% CI; 0.96-2.61) for obese women drinking <1-15 units/week and 1.93 (95% CI; 0.66-5.62) in those with normal BMI consuming ≥21 units/week after adjustment for potential confounders. We found no significant interaction between BMI and alcohol. CONCLUSION: High BMI and alcohol consumption and abstinence are risk factors for CLD in post-menopausal women. However, BMI and alcohol do not demonstrate significant interaction in this group. TRIAL REGISTRATION: UKCTOCS is registered as an International Standard Randomised Controlled Trial, number ISRCTN22488978 . Registered 06/04/2000.

Decreased Serum Thrombospondin-1 Levels in Pancreatic Cancer Patients Up to 24 Months Prior to Clinical Diagnosis: Association with Diabetes Mellitus.

PURPOSE: Identification of serum biomarkers enabling earlier diagnosis of pancreatic ductal adenocarcinoma (PDAC) could improve outcome. Serum protein profiles in patients with preclinical disease and at diagnosis were investigated. EXPERIMENTAL DESIGN: Serum from cases up to 4 years prior to PDAC diagnosis and controls (UKCTOCS,n= 174) were studied, alongside samples from patients diagnosed with PDAC, chronic pancreatitis, benign biliary disease, type 2 diabetes mellitus, and healthy subjects (n= 298). Isobaric tags for relative and absolute quantification (iTRAQ) enabled comparisons of pooled serum from a test set (n= 150). Validation was undertaken using multiple reaction monitoring (MRM) and/or Western blotting in all 472 human samples and samples from a KPC mouse model. RESULTS: iTRAQ identified thrombospondin-1 (TSP-1) as reduced preclinically and in diagnosed samples. MRM confirmed significant reduction in levels of TSP-1 up to 24 months prior to diagnosis. A combination of TSP-1 and CA19-9 gave an AUC of 0.86, significantly outperforming both markers alone (0.69 and 0.77, respectively;P< 0.01). TSP-1 was also decreased in PDAC patients compared with healthy controls (P< 0.05) and patients with benign biliary obstruction (P< 0.01). Low levels of TSP-1 correlated with poorer survival, preclinically (P< 0.05) and at clinical diagnosis (P< 0.02). In PDAC patients, reduced TSP-1 levels were more frequently observed in those with confirmed diabetes mellitus (P< 0.01). Significantly lower levels were also observed in PDAC patients with diabetes compared with individuals with type 2 diabetes mellitus (P= 0.01). CONCLUSIONS: Circulating TSP-1 levels decrease up to 24 months prior to diagnosis of PDAC and significantly enhance the diagnostic performance of CA19-9. The influence of diabetes mellitus on biomarker behavior should be considered in future studies.