Christos Patriotis

Ovarian Cancer Biomarker Performance in Prostate, Lung, Colorectal, and Ovarian Cancer Screening Trial Specimens

Establishing a cancer screening biomarkers intended performance requires “phase III” specimens obtained in asymptomatic individuals before clinical diagnosis rather than “phase II” specimens obtained from symptomatic individuals at diagnosis. We used specimens from the Prostate, Lung, Colorectal, and Ovarian (PLCO) Cancer Screening Trial to evaluate ovarian cancer biomarkers previously assessed in phase II sets. Phase II specimens from 180 ovarian cancer cases and 660 benign disease or general population controls were assembled from four Early Detection Research Network or Ovarian Cancer Specialized Program of Research Excellence sites and used to rank 49 biomarkers. Thirty-five markers, including 6 additional markers from a fifth site, were then evaluated in PLCO proximate specimens from 118 women with ovarian cancer and 474 matched controls. Top markers in phase II specimens included CA125, HE4, transthyretin, CA15.3, and CA72.4 with sensitivity at 95% specificity ranging from 0.73 to 0.40. Except for transthyretin, these markers had similar or better sensitivity when moving to phase III specimens that had been drawn within 6 months of the clinical diagnosis. Performance of all markers declined in phase III specimens more remote than 6 months from diagnosis. Despite many promising new markers for ovarian cancer, CA125 remains the single-best biomarker in the phase II and phase III specimens tested in this study. Cancer Prev Res; 4(3); 365–74. ©2011 AACR.

A Framework for Evaluating Biomarkers for Early Detection: Validation of Biomarker Panels for Ovarian Cancer

A panel of biomarkers may improve predictive performance over individual markers. Although many biomarker panels have been described for ovarian cancer, few studies used prediagnostic samples to assess the potential of the panels for early detection. We conducted a multisite systematic evaluation of biomarker panels using prediagnostic serum samples from the Prostate, Lung, Colorectal, and Ovarian Cancer (PLCO) screening trial. Using a nested case–control design, levels of 28 biomarkers were measured laboratory-blinded in 118 serum samples obtained before cancer diagnosis and 951 serum samples from matched controls. Five predictive models, each containing 6 to 8 biomarkers, were evaluated according to a predetermined analysis plan. Three sequential analyses were conducted: blinded validation of previously established models (step 1); simultaneous split-sample discovery and validation of models (step 2); and exploratory discovery of new models (step 3). Sensitivity, specificity, sensitivity at 98% specificity, and AUC were computed for the models and CA125 alone among 67 cases diagnosed within one year of blood draw and 476 matched controls. In step 1, one model showed comparable performance to CA125, with sensitivity, specificity, and AUC at 69.2%, 96.6%, and 0.892, respectively. Remaining models had poorer performance than CA125 alone. In step 2, we observed a similar pattern. In step 3, a model derived from all 28 markers failed to show improvement over CA125. Thus, biomarker panels discovered in diagnostic samples may not validate in prediagnostic samples; utilizing prediagnostic samples for discovery may be helpful in developing validated early detection panels. Cancer Prev Res; 4(3); 375–83. ©2011 AACR.

Construction and Analysis of the NCI-EDRN Breast Cancer Reference Set for Circulating Markers of Disease

Background: Many circulating biomarkers have been reported for the diagnosis of breast cancer, but few, if any, have undergone rigorous credentialing using prospective cohorts and blinded evaluation. Methods: The NCI Early Detection Research Network (EDRN) has created a prospective, multicenter collection of plasma and serum samples from 832 subjects designed to evaluate circulating biomarkers for the detection and diagnosis of breast cancer. These samples are available to investigators who wish to evaluate their biomarkers using a set of blinded samples. The breast cancer reference set is composed of blood samples collected using a standard operating procedure at four U.S. medical centers from 2008 to 2010 from women undergoing either tissue diagnosis for breast cancer or routine screening mammography. The reference set contains samples from women with incident invasive cancer (n = 190), carcinoma in situ (n = 55), benign pathology with atypia (n = 63), benign disease with no atypia (n = 231), and women with no evidence of breast disease by screening mammography (BI-RADS 1 or 2, n = 276). Using a subset of plasma samples (n = 505) from the reference set, we analyzed 90 proteins by multiplexed immunoassays for their potential utility as diagnostic markers. Results: We found that none of these markers is useful for distinguishing cancer from benign controls. However, elevated CA-125 does appear to be a candidate marker for estrogen receptor–negative cancers. Conclusions: Markers that can distinguish benign breast conditions from invasive cancer have not yet been found. Impact: Availability of prospectively collected samples should improve future validation efforts. Cancer Epidemiol Biomarkers Prev; 24(2); 435–41. ©2014 AACR.

Enabling effective curation of cancer biomarker research data

The dramatic increase in data in the area of cancer research has elevated the importance of effectively managing the quality and consistency of research results from multiple providers. The U.S. National Cancer Institutes Early Detection Research Network (EDRN) is a prime example of a virtual organization, sponsoring distributed, collaborative work at dozens of institutions around the country. As part of a comprehensive informatics infrastructure, The NASA Jet Propulsion Laboratory, in collaboration with Dartmouth Medical School, has developed a web application for the curation of cancer biomarker research results. In this paper, we describe and evaluate the application in the context of the EDRN content management process, and detail our experience using the tool in an operational environment to capture and annotate biomarker research data generated by the EDRN.

Association Between Benign Breast Disease in African American and White American Women and Subsequent Triple-Negative Breast Cancer

Importance Compared with white American (WA) women, African American (AA) women have a 2-fold higher incidence of breast cancers that are negative for estrogen receptor, progesterone receptor, and ERBB2 (triple-negative breast cancer [TNBC]). Triple-negative breast cancer, compared with non-TNBC, likely arises from different pathogenetic pathways, and benign breast disease (BBD) predicts future non-TNBC. Objective To determine whether AA identity remains associated with TNBC for women with a prior diagnosis of BBD. Design, Setting, and Participants This study is a retrospective analysis of data of a cohort of 2588 AA and 3566 WA women aged between 40 and 70 years with a biopsy-proven BBD diagnosis. The data—obtained from the Pathology Information System of Henry Ford Health System (HFHS), an integrated multihospital and multispecialty health care system headquartered in Detroit, Michigan—include specimens of biopsies performed between January 1, 1994, and December 31, 2005. Data analysis was performed from November 1, 2015, to June 15, 2016. Main Outcomes and Measures Subsequent breast cancer was stratified on the basis of combinations of hormone receptor and ERBB2 expression. Results Case management, follow-up, and outcomes received or obtained by our cohort of 2588 AA and 3566 WA patients were similar, demonstrating that HFHS delivered care equitably. Subsequent breast cancers developed in 103 (4.1%) of AA patients (mean follow-up interval of 6.8 years) and 143 (4.0%) of WA patients (mean follow-up interval of 6.1 years). More than three-quarters of subsequent breast cancers in each subset were ductal carcinoma in situ or stage I. The 10-year probability estimate for developing TNBC was 0.56% (95% CI, 0.32%-1.0%) for AA patients and 0.25% (95% CI, 0.12%-0.53%) for WA patients. Among the 66 AA patients who developed subsequent invasive breast cancer, 16 (24.2%) developed TNBC compared with 7 (7.4%) of the 94 WA patients who developed subsequent invasive breast cancers and had complete biomarker data (P = .01). Conclusions and Relevance This study is the largest analysis to date of TNBC in the context of racial/ethnic identity and BBD as risk factors. The study found that AA identity persisted as a significant risk factor for TNBC. This finding suggests that AA identity is associated with inherent susceptibility for TNBC pathogenetic pathways.

Developing an open source, reusable platform for distributed collaborative information management in the Early Detection Research Network

For the past decade, the NASA Jet Propulsion Laboratory, in collaboration with Dartmouth University has served as the center for informatics for the Early Detection Research Network (EDRN). The EDRN is a multi-institution research effort funded by the U.S. National Cancer Institute (NCI) and tasked with identifying and validating biomarkers for the early detection of cancer. As the distributed network has grown, increasingly formal processes have been developed for the acquisition, curation, storage, and dissemination of heterogeneous research information assets, and an informatics infrastructure has emerged. In this paper we discuss the evolution of EDRN informatics, its success as a mechanism for distributed information integration, and the potential sustainability and reuse benefits of emerging efforts to make the platform components themselves open source. We describe our experience transitioning a large closed-source software system to a community-driven, open source project at the Apache Software Foundation, and point to lessons learned that will guide our present efforts to promote the reuse of the EDRN informatics infrastructure by a broader community.

Systematic, evidence-based discovery of biomarkers at the National Cancer Institute.

T he discovery of cancer biomarkers has been plagued by several sample-related issues, in particular, study designs and validation processes leading to unsatisfactory progress in the translation of biomarkers to clinical use. Most often, laboratory discoveries are made using convenience samples and without due consideration of intended clinical use. A recent clinical trial conducted by Early Detection Research Network (EDRN) investigators in collaboration with Specialized Program for Research Excellence and prostate, lung, colorectal and ovarian cancer investigators failed to identify any biomarkers from among more than 70 candidates tested that can detect ovarian cancer reliably more than 6 months before the manifestation of any clinical symptoms of the disease. The single best biomarker still remains to be CA-125, which has poor diagnostic performance for premalignant or early-stage disease. Furthermore, its increased levels are found in approximately 3% of postmenopausal women, resulting in a significant number of false positives for this biomarker. The study confirmed that although the HE4 biomarker performs almost as well as CA125, it does not add value to it. This outcome emphasizes the importance of using appropriate specimens for biomarker research, from early discovery stages to clinical validation. Bias introduced by systematic differences in the case and control specimens during biomarker discovery, which can significantly inflate the performance of biomarkers, must be maximally avoided by adapting the principles of Prospectivespecimen collection, Retrospective Blinded Evaluation (PRoBE) study design. Another factor for failure is the poor understanding of the natural history of the disease and the discovery of biomarkers in advanced cancer lesions, which may not be present in the preneoplastic and early neoplastic lesions that are the precursors of aggressively growing disease. In 2000, the National Cancer Institute established a network of investigators comprising basic scientists, epidemiologists, physicians, and bioinformaticians to address some of the biomarkers developmental issues. The network (EDRN; www.cancer.gov/edrn) has emerged as the leading platform supported by the National Cancer institute to systematically discover, develop, and validate biomarkers for assessing cancer risk, early cancer detection, and diagnosis and prognosis of cancer. The EDRN has developed a 5-phase schema and go/ no-go criteria for selecting biomarkers that are useful. In the 5-phase schema, phase 1 includes the exploratory discovery stage to identify potentially useful biomarkers. In phase 2, biomarkers are studied to determine their capacity for distinguishing between cases with cancer and those without. Phase 2 is called the validation phase. Repositories of longitudinally collected preclinical specimens from research cohorts are used in phase 3 to determine the capacity of a biomarker to detect preclinical disease. Phase 4 consists of the use of prospective screening studies. Finally, large-scale population studies that evaluate not just the role of the biomarker for the detection of cancer but the overall impact of screening on the population comprise phase 5. The criteria have been further expanded, especially for phases 2 and 3, which include the following (1) prospective collection of samples from the target population, (2) retrospective random sampling of cases and controls after the outcome status is ascertained. Specimens assayed for biomarkers are blinded to the case-control status. This design is also known as the PRoBE study design. The PRoBE design has been the basis of EDRN’s efforts to collect reference samples for quickly and cheaply evaluating biomarkers. The speaker will describe how EDRN is addressing some challenges associated with the discovery, development, and validation of biomarkers and will propose an international alliance of cohort consortia, which are engaged in screendetected and clinically detected ovarian and other cancers. It is hoped that one such collaboration will help us measure the extent of and potential ways to address overdiagnosis and to develop biomarkers of progression. SUPPLEMENT ARTICLE

Molecular Detection and Diagnosis of Cancer

The incidence of cancer is increasing worldwide, owing to the trends toward increased lifespan and adaptation to western lifestyle. Although progress has been made in therapeutic and diagnostic strategies contributing to a slight reduction in mortality, cancer still remains a serious health condition and is often fatal. Many cancer deaths occur because the disease is usually diagnosed at advanced stages and has spread to distant organs with lymph node involvement, where most of the treatment options fail. It has been well demonstrated that if the disease is detected earlier the chances of 5-year cancer-free survival and reduction in mortality are better. For example, colon cancer survival rates for localized disease are 82–93 %, compared with only 5–8 % for cases with distant disease. Similarly, significant mortality reduction in cervical cancer cases is mainly due to the availability of effective screening strategies. Some cancers such as ovarian, pancreatic, and lung remain asymptomatic and are diagnosed at advanced stages with poor survival.

Abstract P4-02-05: A blinded multicenter phase II study of a panel of plasma biomarkers for the detection of triple negative breast cancer

Background : Triple negative breast cancers (TNBC) comprise 15-20% of all breast cancers and frequently present as interval cancers with high proliferative rates and increased risk of mortality. There is a clinical need for biomarkers for the early detection of TNBC to complement radiologic imaging. No plasma biomarkers for TNBC currently exist. The purpose of this study is to evaluate a panel of novel plasma biomarkers for TNBC for the discrimination of TNBC and benign breast disease as a crucial step in identifying a panel of plasma biomarkers for early detection. Methods : In a multicenter collaboration between the NCI EDRN and the CPTAC consortium, we conducted a prospective blinded phase II biomarker study that evaluated 76 candidate TNBC plasma biomarkers. Plasma samples collected at the time of diagnosis from 65 TNBC cases and 195 matched controls with benign breast disease without atypia were identified from multiple clinical sites. The samples were distributed as blinded aliquots to the biomarker laboratories for protein and autoantibody detection. Candidate protein (n=54) and autoantibody (n=22) biomarkers were selected and ranked prior to evaluation. All results were centrally analyzed. The sensitivity at 95% specificity was calculated for each biomarker. Effects of age, race, and specimen source on biomarkers were evaluated. Logistic regression was used to assess complementarity of biomarkers. The top three biomarkers underwent verification with an independent set of 60 TNBC cases and 180 matched controls from women undergoing mammography. Results : Statistically significant differences in case versus control signals were observed for 3 biomarkers with sensitivities of 17-23% at 95% specificity (p Conclusion : We have developed a pipeline strategy for the validation of plasma biomarkers for detection of breast cancer. At least three biomarkers for TNBC were confirmed in this study. Further evaluation of these biomarkers for early detection is ongoing. Citation Format: Karen S Anderson, Margaret Pepe, Jeffrey Marks, Paul Engstrom, Christos Patriotis, Richard Zangar, Steven Skates, Paul Lampe, Joshua LaBaer, Christopher I Li. A blinded multicenter phase II study of a panel of plasma biomarkers for the detection of triple negative breast cancer [abstract]. In: Proceedings of the Thirty-Seventh Annual CTRC-AACR San Antonio Breast Cancer Symposium: 2014 Dec 9-13; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2015;75(9 Suppl):Abstract nr P4-02-05.

A Laboratory-Targeted, Data Management and Processing System for the Early Detection Research Network

The National Institutes of Health (NIH), National Cancer Institutes Early Detection Research Network (EDRN) is a cross-institutional collaborative initiative seeking to accelerate the clinical application of cancer biomarker research. Over the past decade, it has been our role, as EDRNs Informatics Center (IC), to develop a comprehensive information services infrastructure as well as a set of software tools and services to support this overall initiative. We have recently developed a novel application called the Laboratory Catalog and Archive Service (LabCAS) whose focus is to extend EDRN IC data management and processing capabilities to EDRN laboratories. By leveraging the same technologies used to manage and process NASA Earth and Planetary data sets, we offer EDRN researchers an effective way of managing their laboratory data. More specifically, LabCAS enables EDRN researchers to reliably archive their experimental data, to optionally share these data in a controlled manner with other researchers, and to gain insight into these data through highly configurable data analysis pipelines tailored to the broad range of biomarker related experiments. This particular collaboration leverages expertise from NASAs Jet Propulsion Laboratory, Vanderbilt University Medical Center, and Dartmouth Medical School, as well as builds upon existing cross-governmental collaboration between NASA and the NIH.