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      Combined circulating tumor DNA and protein biomarker-based liquid biopsy for the earlier detection of pancreatic cancers

      research-article

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      Proceedings of the National Academy of Sciences of the United States of America

      National Academy of Sciences

      early cancer detection, liquid biopsy, circulating tumor DNA, protein biomarkers, pancreatic cancer

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          Significance

          Few patients with pancreatic cancer survive longer than 5 y, in part because most patients are identified only after their disease has progressed to an advanced stage. In this study, we show how combining mutations in circulating tumor DNA (ctDNA) with protein markers can result in a screening test with improved sensitivity while retaining specificity. The combination of the ctDNA and protein markers was superior to any single marker. Moreover, the combination detected nearly two-thirds of pancreatic cancers that had no evidence of distant metastasis at the time of surgical resection. The strategy may represent an approach to detect cancers of many types at an earlier stage.

          Abstract

          The earlier diagnosis of cancer is one of the keys to reducing cancer deaths in the future. Here we describe our efforts to develop a noninvasive blood test for the detection of pancreatic ductal adenocarcinoma. We combined blood tests for KRAS gene mutations with carefully thresholded protein biomarkers to determine whether the combination of these markers was superior to any single marker. The cohort tested included 221 patients with resectable pancreatic ductal adenocarcinomas and 182 control patients without known cancer. KRAS mutations were detected in the plasma of 66 patients (30%), and every mutation found in the plasma was identical to that subsequently found in the patient’s primary tumor (100% concordance). The use of KRAS in conjunction with four thresholded protein biomarkers increased the sensitivity to 64%. Only one of the 182 plasma samples from the control cohort was positive for any of the DNA or protein biomarkers (99.5% specificity). This combinatorial approach may prove useful for the earlier detection of many cancer types.

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          Most cited references25

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          Detection and quantification of rare mutations with massively parallel sequencing.

          The identification of mutations that are present in a small fraction of DNA templates is essential for progress in several areas of biomedical research. Although massively parallel sequencing instruments are in principle well suited to this task, the error rates in such instruments are generally too high to allow confident identification of rare variants. We here describe an approach that can substantially increase the sensitivity of massively parallel sequencing instruments for this purpose. The keys to this approach, called the Safe-Sequencing System ("Safe-SeqS"), are (i) assignment of a unique identifier (UID) to each template molecule, (ii) amplification of each uniquely tagged template molecule to create UID families, and (iii) redundant sequencing of the amplification products. PCR fragments with the same UID are considered mutant ("supermutants") only if ≥95% of them contain the identical mutation. We illustrate the utility of this approach for determining the fidelity of a polymerase, the accuracy of oligonucleotides synthesized in vitro, and the prevalence of mutations in the nuclear and mitochondrial genomes of normal cells.
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            Blood-based analyses of cancer: circulating tumor cells and circulating tumor DNA.

            The ability to study nonhematologic cancers through noninvasive sampling of blood is one of the most exciting and rapidly advancing fields in cancer diagnostics. This has been driven both by major technologic advances, including the isolation of intact cancer cells and the analysis of cancer cell-derived DNA from blood samples, and by the increasing application of molecularly driven therapeutics, which rely on such accurate and timely measurements of critical biomarkers. Moreover, the dramatic efficacy of these potent cancer therapies drives the selection for additional genetic changes as tumors acquire drug resistance, necessitating repeated sampling of cancer cells to adjust therapy in response to tumor evolution. Together, these advanced noninvasive diagnostic capabilities and their applications in guiding precision cancer therapies are poised to change the ways in which we select and monitor cancer treatments. Recent advances in technologies to analyze circulating tumor cells and circulating tumor DNA are setting the stage for real-time, noninvasive monitoring of cancer and providing novel insights into cancer evolution, invasion, and metastasis. ©2014 American Association for Cancer Research.
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              Evolutionary dynamics of cancer in response to targeted combination therapy

              In solid tumors, targeted treatments can lead to dramatic regressions, but responses are often short-lived because resistant cancer cells arise. The major strategy proposed for overcoming resistance is combination therapy. We present a mathematical model describing the evolutionary dynamics of lesions in response to treatment. We first studied 20 melanoma patients receiving vemurafenib. We then applied our model to an independent set of pancreatic, colorectal, and melanoma cancer patients with metastatic disease. We find that dual therapy results in long-term disease control for most patients, if there are no single mutations that cause cross-resistance to both drugs; in patients with large disease burden, triple therapy is needed. We also find that simultaneous therapy with two drugs is much more effective than sequential therapy. Our results provide realistic expectations for the efficacy of new drug combinations and inform the design of trials for new cancer therapeutics. DOI: http://dx.doi.org/10.7554/eLife.00747.001
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                Author and article information

                Journal
                Proc Natl Acad Sci U S A
                Proc. Natl. Acad. Sci. U.S.A
                pnas
                pnas
                PNAS
                Proceedings of the National Academy of Sciences of the United States of America
                National Academy of Sciences
                0027-8424
                1091-6490
                19 September 2017
                5 September 2017
                : 114
                : 38
                : 10202-10207
                Affiliations
                [1] aThe Ludwig Center, The Johns Hopkins Medical Institutions , Baltimore, MD 21287;
                [2] bHoward Hughes Medical Institute, The Johns Hopkins Medical Institutions , Baltimore, MD 21287;
                [3] cSidney Kimmel Cancer Center at Johns Hopkins, The Johns Hopkins Medical Institutions , Baltimore, MD 21287;
                [4] dThe Sol Goldman Pancreatic Cancer Research Center, The Johns Hopkins Medical Institutions , Baltimore, MD 21287;
                [5] eDepartment of Biomedical Engineering, The Johns Hopkins University School of Medicine, Baltimore, MD 21205;
                [6] fDepartment of Surgery, The Johns Hopkins Medical Institutions , Baltimore, MD 21287;
                [7] gDivision of Systems Biology and Personalized Medicine, Walter and Eliza Hall Institute of Medical Research , Parkville, VIC 3021, Australia;
                [8] hFaculty of Medicine, Dentistry and Health Sciences, The University of Melbourne, Melbourne, VIC 3010, Australia;
                [9] iDepartment of Medical Oncology, Western Health, Melbourne, VIC 3021, Australia;
                [10] jDepartment of Surgery, Indiana University School of Medicine, Indianapolis, IN 46202;
                [11] kDepartment of Biochemistry and Molecular Biology, Indiana University School of Medicine, Indianapolis, IN 46202;
                [12] lDepartment of Surgery, Memorial Sloan-Kettering Cancer Center , New York, NY 10065;
                [13] mDepartment of Medicine, Memorial Sloan-Kettering Cancer Center, New York, NY 10065;
                [14] nDepartment of Medicine, University of Pittsburgh , Pittsburgh, PA 15260;
                [15] oDepartment of Pathology, University of Pittsburgh , Pittsburgh, PA 15260;
                [16] pDepartment of Epidemiology, Mayo Clinic , Rochester, MN 55902;
                [17] qDepartment of Pathology, Asan Medical Center, University of Ulsan College of Medicine , Seoul 05505, Korea;
                [18] rDepartment of Hepatobiliary and Pancreas Surgery, Asan Medical Center, University of Ulsan College of Medicine , Seoul 05505, Korea;
                [19] sDivision of Pancreatic Surgery, Department of Surgery, San Raffaele Scientific Institute Research Hospital , 20132 Milan, Italy;
                [20] tDepartment of Pathology, San Raffaele Scientific Institute Research Hospital , 20132 Milan, Italy;
                [21] uThe Sheikh Ahmed Center for Pancreatic Cancer Research, The University of Texas MD Anderson Cancer Center , Houston, TX 77030;
                [22] vDepartment of Biostatistics, The Johns Hopkins Bloomberg School of Public Health, Baltimore, MD 21205;
                [23] wDepartment of Medicine, The Johns Hopkins Medical Institutions , Baltimore, MD 21287;
                [24] xDepartment of Pathology, The Johns Hopkins Medical Institutions , Baltimore, MD 21287;
                [25] yDepartment of Epidemiology, The Johns Hopkins Bloomberg School of Public Health, Baltimore, MD 21205;
                [26] zDivision of Biostatistics and Bioinformatics, Department of Oncology, The Johns Hopkins Medical Institutions , Baltimore, MD 21287
                Author notes
                1To whom correspondence may be addressed. Email: bertvog@ 123456gmail.com or amlennon@ 123456jhmi.edu .

                Contributed by Bert Vogelstein, May 4, 2017 (sent for review April 4, 2017; reviewed by Daniel A. Haber and Lance Liotta)

                Author contributions: J.D.C., A.A.J., F.W., Y.W., N.P., K.W.K., B.V., and A.M.L. designed research; J.D.C., A.A.J., C. Thoburn, Y.W., L.L., J.P., L.D., J.S., N.S., M.P., N.P., K.W.K., B.V., and A.M.L. performed research; J.D.C., A.A.J., J.T., P.G., C.M.S., M.T.Y.-S., P.J.A., M.S., R.E.B., A.D.S., G.M.P., S.-M.H., S.C.K., M.F., C.D., M.J.W., N.A., J.H., M.A.M., A.M., S.M.H., M.D.M., Y.W., L.L., M.G.G., R.H.H., C.L.W., C. Tomasetti, N.P., K.W.K., B.V., and A.M.L. contributed new reagents/analytic tools; C. Tomasetti designed the algorithm for the sequencing data analysis; J.D.C., A.A.J., C. Thoburn, F.W., Y.W., L.L., A.P.K., C. Tomasetti, N.P., K.W.K., B.V., and A.M.L. analyzed data; and J.D.C., A.A.J., F.W., N.P., K.W.K., B.V., and A.M.L. wrote the paper.

                Reviewers: D.A.H., Massachusetts General Hospital; and L.L., George Mason University.

                Article
                PMC5617273 PMC5617273 5617273 201704961
                10.1073/pnas.1704961114
                5617273
                28874546
                912f5fa1-ecd7-47a4-aacf-1e9a2555e5b9
                Page count
                Pages: 6
                Funding
                Funded by: Lustgarten Foundation 100005979
                Award ID: N/A
                Funded by: Virginia and D.K. Ludwig Fund for Cancer Research (D.K. Ludwig Fund) 100006352
                Award ID: N/A
                Funded by: HHS | National Institutes of Health (NIH) 100000002
                Award ID: P50-CA62924
                Funded by: HHS | National Institutes of Health (NIH) 100000002
                Award ID: CA-06973
                Funded by: HHS | National Institutes of Health (NIH) 100000002
                Award ID: GM-07309
                Funded by: HHS | National Institutes of Health (NIH) 100000002
                Award ID: U01CA152753
                Funded by: HHS | National Institutes of Health (NIH) 100000002
                Award ID: P50-CA102701
                Categories
                Biological Sciences
                Medical Sciences

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