FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W3001195005> ?p ?o ?g. }

• W3001195005 endingPage "337" @default.
• W3001195005 startingPage "319" @default.
• W3001195005 abstract "Liquid biopsy allows assessment of multiple analytes, providing temporal information with potential for improving understanding of cancer evolution and clinical management of patients. Although liquid biopsies are intensely investigated for prediction and response monitoring, preanalytic variables are of primary concern for clinical implementation, including categories of collection method and sample storage. Herein, an integrated high-density single-cell assay workflow for morphometric and genomic analysis of the liquid biopsy is used to characterize the effects of preanalytical variation and reproducibility of data from a breast cancer cohort. Following prior work quantifying performance of commonly used blood collection tubes, this study completes the analysis of four time points to assay (24, 48, 72, and 96 hours), demonstrating precision up to 48 hours after collection for assay sensitivity, highly reproducible rare cell enumeration, morphometric characterization, and high efficiency and capacity for single-cell genomic analysis. For the cell-free analysis, both freezing and use of fresh plasma produced similar quality and quantity of cell-free DNA for sequencing. The genomic analysis (copy number variation and single-nucleotide variation) described herein is broadly applicable to liquid biopsy platforms capable of isolating cell-free and cell-based DNA. Morphometric parameters and genomic signatures of individual circulating tumor cells were evaluated in relation to patient clinical response, providing preliminary evidence of clinical validity as a potential biomarker aiding clinical diagnostics or monitoring progression. Liquid biopsy allows assessment of multiple analytes, providing temporal information with potential for improving understanding of cancer evolution and clinical management of patients. Although liquid biopsies are intensely investigated for prediction and response monitoring, preanalytic variables are of primary concern for clinical implementation, including categories of collection method and sample storage. Herein, an integrated high-density single-cell assay workflow for morphometric and genomic analysis of the liquid biopsy is used to characterize the effects of preanalytical variation and reproducibility of data from a breast cancer cohort. Following prior work quantifying performance of commonly used blood collection tubes, this study completes the analysis of four time points to assay (24, 48, 72, and 96 hours), demonstrating precision up to 48 hours after collection for assay sensitivity, highly reproducible rare cell enumeration, morphometric characterization, and high efficiency and capacity for single-cell genomic analysis. For the cell-free analysis, both freezing and use of fresh plasma produced similar quality and quantity of cell-free DNA for sequencing. The genomic analysis (copy number variation and single-nucleotide variation) described herein is broadly applicable to liquid biopsy platforms capable of isolating cell-free and cell-based DNA. Morphometric parameters and genomic signatures of individual circulating tumor cells were evaluated in relation to patient clinical response, providing preliminary evidence of clinical validity as a potential biomarker aiding clinical diagnostics or monitoring progression. Cancer evolves from the point of initiation to lethal metastatic disease through the course of natural disease progression and in response to treatment pressures. To achieve distant metastasis, cancer cells must travel through the bloodstream to distant sites and adapt to growth in a foreign environment, ultimately proliferating to the point of disrupting the health of the patient. Diagnostic evaluation of this process, which often takes years, is thus a problem of both time and space. In such a complex pathology, the liquid biopsy, based on a simple blood draw, affords a minimally invasive route to assess molecular biomarkers in solid tumor cancers at multiple time points over a course of treatment, allowing for a greater understanding of the time-related changes of cancer progression and treatment response. The high-density single-cell assay (HD-SCA) employed in this study is an integrated workflow that detects circulating tumor cells (CTCs) and combines molecular assays of DNA extracted from CTCs (single-cell DNA) and cell-free DNA (cfDNA) from a single blood collection tube. The HD-SCA is the only workflow that integrates the analysis of circulating cells and cfDNA, thus providing multiplexed molecular analysis of biomarkers with the increased potential for guiding treatment and improving clinical management of the disease. To employ CTCs as a biomarker of disease and show clinical utility as a diagnostic, prognostic, or predictive tool in the clinic, a detection platform must be both precise and accurate. The features of cellular and acellular components are likely to differ among cancer types and will certainly vary over the evolution of disease, which has to be recognized as a potential challenge in the development and deployment of a detection system. Most likely specific analytes, such as CTCs and cfDNA, will require separate validation for clinical utility in different disease settings. Recently, a joint review from the American Society of Clinical Oncology and the College of American Pathologists summarized the current information about clinical cfDNA assays to initiate a framework to guide future research.1Merker J.D. Oxnard G.R. Compton C. Diehn M. Hurley P. Lazar A.J. Lindeman N. Lockwood C.M. Rai A.J. Schilsky R.L. Tsimberidou A.M. Vasalos P. Billman B.L. Oliver T.K. Bruinooge S.S. Hayes D.F. Turner N.C. Circulating tumor DNA analysis in patients with cancer: American Society of Clinical Oncology and College of American Pathologists Joint Review.J Clin Oncol. 2018; 36: 1631-1641Crossref PubMed Scopus (527) Google Scholar Although general exploration is necessary for biological discovery, in clinical medicine, a procedure must have demonstrated reproducibility with characterization of known deviations or fluctuations. Robust liquid biopsy detection technology must be capable of detecting extremely rare analytes, such as circulating tumor DNA and CTCs, in a background of billions of normal blood cells and plasma. Development of a rare cell detection assay for a specific context of use requires full analytical validation that the assay is fit for the purpose indicated.2Pantel K. Hille C. Scher H.I. Circulating tumor cells in prostate cancer: from discovery to clinical utility.Clin Chem. 2019; 65: 87-99Crossref PubMed Scopus (90) Google Scholar, 3Parkinson D.R. McCormack R.T. Keating S.M. Gutman S.I. Hamilton S.R. Mansfield E.A. Piper M.A. Deverka P. Frueh F.W. Jessup J.M. McShane L.M. Tunis S.R. Sigman C.C. Kelloff G.J. Evidence of clinical utility: an unmet need in molecular diagnostics for patients with cancer.Clin Cancer Res. 2014; 20: 1428-1444Crossref PubMed Scopus (66) Google Scholar, 4Scher H.I. Graf R.P. Schreiber N.A. Jayaram A. Winquist E. McLaughlin B. Lu D. Fleisher M. Orr S. Lowes L. Anderson A. Wang Y. Dittamore R. Allan A.L. Attard G. Heller G. Assessment of the validity of nuclear-localized androgen receptor splice variant 7 in circulating tumor cells as a predictive biomarker for castration-resistant prostate cancer.JAMA Oncol. 2018; 4: 1179-1186Crossref PubMed Scopus (158) Google Scholar Clinical validation can then be done to generate the evidence that associates the assay output with clinical outcomes.5Perez-Gracia J.L. Sanmamed M.F. Bosch A. Patino-Garcia A. Schalper K.A. Segura V. Bellmunt J. Tabernero J. Sweeney C.J. Choueiri T.K. Martin M. Fusco J.P. Rodriguez-Ruiz M.E. Calvo A. Prior C. Paz-Ares L. Pio R. Gonzalez-Billalabeitia E. Gonzalez Hernandez A. Paez D. Piulats J.M. Gurpide A. Andueza M. de Velasco G. Pazo R. Grande E. Nicolas P. Abad-Santos F. Garcia-Donas J. Castellano D. Pajares M.J. Suarez C. Colomer R. Montuenga L.M. Melero I. Strategies to design clinical studies to identify predictive biomarkers in cancer research.Cancer Treat Rev. 2017; 53: 79-97Abstract Full Text Full Text PDF PubMed Scopus (65) Google Scholar This is followed by clinical utility, which clearly demonstrates that the use of the assay output in clinical management improves patient outcomes relative to nonuse.2Pantel K. Hille C. Scher H.I. Circulating tumor cells in prostate cancer: from discovery to clinical utility.Clin Chem. 2019; 65: 87-99Crossref PubMed Scopus (90) Google Scholar, 3Parkinson D.R. McCormack R.T. Keating S.M. Gutman S.I. Hamilton S.R. Mansfield E.A. Piper M.A. Deverka P. Frueh F.W. Jessup J.M. McShane L.M. Tunis S.R. Sigman C.C. Kelloff G.J. Evidence of clinical utility: an unmet need in molecular diagnostics for patients with cancer.Clin Cancer Res. 2014; 20: 1428-1444Crossref PubMed Scopus (66) Google Scholar, 4Scher H.I. Graf R.P. Schreiber N.A. Jayaram A. Winquist E. McLaughlin B. Lu D. Fleisher M. Orr S. Lowes L. Anderson A. Wang Y. Dittamore R. Allan A.L. Attard G. Heller G. Assessment of the validity of nuclear-localized androgen receptor splice variant 7 in circulating tumor cells as a predictive biomarker for castration-resistant prostate cancer.JAMA Oncol. 2018; 4: 1179-1186Crossref PubMed Scopus (158) Google Scholar Quality laboratory practices are important to the health and welfare of the population. Laboratory-developed tests are not subject to US Food and Drug Administration regulation, but certification under Clinical Laboratory Improvement Amendments/College of American Pathologists is required to ensure quality and validity for the purpose of diagnosis, prevention, treatment of disease, or assessment of health (Clinical Laboratory Improvement Amendments, https://www.cdc.gov/clia/law-regulations.html). By characterizing and quantifying all aspects of laboratory testing, including preanalytics, significant improvement can be made in the quality, accuracy, and relevance of laboratory practices (US Food and Drug Administration, https://www.accessdata.fda.gov/scripts/cdrh/cfdocs/cfcfr/cfrsearch.cfm). Preanalytical variation in the detection of CTCs includes such categories as collection method, shipping conditions, and sample storage. For moderate- to high-risk laboratory-developed tests, the US Food and Drug Administration's proposed regulation requires US Food and Drug Administration authorization before marketing in the United States through either the premarket approval or 510(k) premarket notification pathways (US Food and Drug Administration, https://www.fda.gov/media/89841/download). The 510(k) is a premarket submission that demonstrates the laboratory-developed test to be marketed (generally class II; moderate risk) is at least as safe and effective as a legally marketed device that is not subject to premarket approval. The enumeration of CTCs of epithelial origin in patients with metastatic breast, colon, or prostate cancer using CellSearch (Menarini Silicon Biosystems, Huntington Valley, PA) currently has US Food and Drug Administration 510(k) approval, and general guidelines include the CellSave Preservative blood collection tube (BCT; Menarini Silicon Biosystems) with ambient temperature storage and a time to assay (TTA) of <96 hours. The HD-SCA workflow offers significant promise in the multianalyte analysis of the liquid biopsy, while gaining biological insights relevant to disease progression. Using an analogous method, Epic Sciences (San Diego, CA) recently released a predictive and prognostic CTC test for metastatic castration-resistant prostate cancer certified under US Clinical Laboratory Improvement Amendments and accredited by the College of American Pathologists.6Scher H.I. Graf R.P. Schreiber N.A. McLaughlin B. Lu D. Louw J. Danila D.C. Dugan L. Johnson A. Heller G. Fleisher M. Dittamore R. Nuclear-specific AR-V7 protein localization is necessary to guide treatment selection in metastatic castration-resistant prostate cancer.Eur Urol. 2017; 71: 874-882Abstract Full Text Full Text PDF PubMed Scopus (128) Google Scholar, 7Scher H.I. Graf R.P. Schreiber N.A. Winquist E. McLaughlin B. Lu D. Orr S. Fleisher M. Lowes L. Anderson A.K.L. Wang Y. Dittamore R.V. Allan A.L. Attard G. Heller G. Validation of nuclear-localized AR-V7 on circulating tumor cells (CTC) as a treatment-selection biomarker for managing metastatic castration-resistant prostate cancer (mCRPC).J Clin Oncol. 2018; 36: 273Crossref Google Scholar, 8Scher H.I. Lu D. Schreiber N.A. Louw J. Graf R.P. Vargas H.A. Johnson A. Jendrisak A. Bambury R. Danila D. McLaughlin B. Wahl J. Greene S.B. Heller G. Marrinucci D. Fleisher M. Dittamore R. Association of AR-V7 on circulating tumor cells as a treatment-specific biomarker with outcomes and survival in castration-resistant prostate cancer.JAMA Oncol. 2016; 2: 1441-1449Crossref PubMed Scopus (474) Google Scholar This exemplifies the potential for clinical utility of the HD-SCA workflow for the identification of a biomarker in breast cancer patients. The HD-SCA workflow is inherently a nonenrichment high-content direct imaging method capable of providing visualization of both typical and atypical tumor-related cells in circulation and molecular parameters at both the single-cell level and cfDNA level. This allows for both the identification of genetic mutations important for targeted therapies and for a greater understanding of the genomic drift in the tumor cell population, which may lead to treatment resistance. The value of single-cell genomic analysis conducted on this platform has been previously reported, showing compatibility with clinical practice.9Dago A.E. Stepansky A. Carlsson A. Luttgen M. Kendall J. Baslan T. Kolatkar A. Wigler M. Bethel K. Gross M.E. Hicks J. Kuhn P. Rapid phenotypic and genomic change in response to therapeutic pressure in prostate cancer inferred by high content analysis of single circulating tumor cells.PLoS One. 2014; 9: e101777Crossref PubMed Scopus (115) Google Scholar,10Ruiz C. Li J. Luttgen M.S. Kolatkar A. Kendall J.T. Flores E. Topp Z. Samlowski W.E. McClay E. Bethel K. Ferrone S. Hicks J. Kuhn P. Limited genomic heterogeneity of circulating melanoma cells in advanced stage patients.Phys Biol. 2015; 12: 016008Crossref PubMed Scopus (35) Google Scholar The HD-SCA workflow has the potential to transform cancer research and clinical practice by applying a genomic approach to specific cell populations that have only been initially characterized by cytomorphology in the liquid biopsy. In addition, genomic analysis of the circulating cfDNA from plasma isolated from these cancer patients may be measured and evaluated with the same principles, providing complementary genomic information. Single-cell and next-generation sequencing (NGS) technologies are rapidly evolving, making it imperative to control for technical and biological variations, ensuring reproducible and accurate findings. Sequencing analysis is affected by preanalytical variables that may introduce errors at each step, affecting the quality of the data for analysis and their interpretation. Quality controls for each step in the HD-SCA workflow have been developed and established to detect, prevent, and mitigate errors, while accounting for technical variation and analysis biases of overall CTC enumeration or CTC subclasses, which may be relevant to guide specific clinical decisions. Few studies have rigorously examined the technical reproducibility of single-cell sequencing after CTC enumeration and isolation. Most methods have shown similar overall performances and sensitivity, but they often lack important necessary evidence of assay performance, including accuracy and specificity. This presents a serious barrier to the ultimate goal of identifying signatures that are clinically meaningful. This study systematically analyzed the influence of preanalytical variables in the context of blood biospecimen collection, handling, and processing, with respect to the analysis of the complete liquid biopsy for scalable clinical utility in routinely obtained peripheral blood samples from breast cancer patients. The variables under investigation were TTA (time from blood draw to cryostorage) for CTC evaluation and fresh versus frozen (FVF) plasma preparations for cfDNA isolation for the application of single-cell and cfDNA genomic analysis. This study completes a set of four TTAs (24, 48, 72, and 96 hours) in the assessment of CTC detection for optimization of the HD-SCA workflow. The results recommend using the Streck cell-free DNA BCT (Streck, La Vista, NE) up to a 48-hour TTA, which ensures cellular retention and the highest efficacy of rare cell identification by the HD-SCA workflow, while providing high-quality single-cell genomic sequencing data. In addition, the quality of isolated cfDNA and resulting sequencing data was independent of freezing. This study does the following: i) validates the potential of the HD-SCA workflow for CTC discovery, ii) demonstrates the feasibility of single-cell and cfDNA copy number variation (CNV) and single-nucleotide variation (SNV) profiling, and iii) outlines the preanalytical variables integral for the scalability and reproducibility of a complete analysis of the liquid biopsy. The main goals of this study were to complete a comprehensive analysis of the preanalytical variables for five BCTs, four TTAs, and FVF for the genomic assessment of the cellular and acellular fractions of the liquid biopsy in a large cohort of primary breast cancer patients. To determine the blood collection, handling, and processing variations across a wide range of disease states to represent the clinical scenario, the patient cohort consisted of nonmetastatic, treatment-naive patients and metastatic patients. Patients with breast cancer participated in the ongoing prospective Physical Sciences in Oncology study (PSOC-0068) entitled OPTImization of blood COLLection (Figure 1). A total of 163 patients were enrolled between April 2013 and January 17, 2017, at multiple clinical sites in the United States [namely, Billings Clinic (Billings, MT), Duke University (Durham, NC), City of Hope Comprehensive Cancer Center (Duarte, CA), MD Anderson Cancer Center (Houston, TX), University of Southern California Norris Comprehensive Cancer Center (Los Angeles, CA), University of Southern California Norris Oncology/Hematology (Newport Beach, CA), and Los Angeles County and University of Southern California Medical Center (Los Angeles, CA)]. Patient recruitment took place according to an institutional review board–approved protocol. Recruitment and study schedules were established and unified across clinical sites for patients with nonmetastatic, treatment-naïve disease and metastatic disease.11Rodríguez-Lee M. Kolatkar A. McCormick M. Dago A.D. Kendall J. Carlsson N.A. Bethel K. Greenspan E.J. Hwang S.E. Waitman K.R. Nieva J.J. Hicks J. Kuhn P. Effect of blood collection tube type and time to processing on the enumeration and high-content characterization of circulating tumor cells using the high-definition single cell assay.Arch Pathol Lab Med. 2018; 142: 198-207Crossref PubMed Scopus (28) Google Scholar Nonmetastatic, treatment-naïve patients had two study-related blood draws: before any initial treatment and 3 to 8 weeks after surgical resection of the primary lesion with or without adjuvant drug treatment as primary therapy. Patients with metastatic disease were eligible for participation at the start of a new line of therapy, either as a first line of therapy or after experiencing progression while on therapy for treatment of metastatic disease. These patients had a potential for up to 14 study-related blood draws at intervals of 8 to 12 weeks, coordinated with routine clinic visits. This collection scheme was designed with a primary goal of screening and reproducible identification of circulating rare cells, and only as a secondary goal for clinical correlations. An institutional review board at each site approved all procedures, and all study participants provided written informed consent. To complete the prior analysis of the most commonly used BCTs (cfDNA, EDTA, acid-citrate-dextrose, and heparin), the CellSave Preservative BCT (catalog number 7900005; Veridex LLC, Raritan, NJ) was employed to evaluate any differences in rare cell detection compared with the previously superior cfDNA Streck BCT (catalog number 218962; Streck Laboratories, Omaha, NE) in peripheral blood samples collected from breast cancer patients.11Rodríguez-Lee M. Kolatkar A. McCormick M. Dago A.D. Kendall J. Carlsson N.A. Bethel K. Greenspan E.J. Hwang S.E. Waitman K.R. Nieva J.J. Hicks J. Kuhn P. Effect of blood collection tube type and time to processing on the enumeration and high-content characterization of circulating tumor cells using the high-definition single cell assay.Arch Pathol Lab Med. 2018; 142: 198-207Crossref PubMed Scopus (28) Google Scholar A total of 23 patients provided 33 pairs of BCTs with 8 mL of blood collected in each and processed at 24 hours for rare cell detection with the goal of determining the optimal BCT for the HD-SCA workflow. For complete analysis of up to 96 hours TTA, study participants underwent phlebotomy of up to 40 mL of blood into a predetermined set of BCTs. Tube brand and lot number were tracked between clinical sites and throughout the study. A total of four Streck BCTs with 8 mL of blood were collected at each draw: 24, 48, 72, and 96 hours TTA. The acceptable period defining each TTA was ±8 hours; therefore, 24-hour TTA samples were processed 16 to 32 hours after sample collection. Plasma from each patient draw collected in the Streck BCT and processed at 24-hour TTA was divided into two equal aliquots to generate fresh and frozen plasma preparations. This study tested components potentially leading to large degrees of preanalytic variability, made constant several others by strict prescription of methods, and tracked many additional variables that may add variability to the final results, but may not necessarily be controllable. The formally tested variables were TTA for rare cell detection and FVF plasma samples for cfDNA genomic analysis. Those variables held constant by conformity to strict protocols, as well as those inherently less controllable parameters, were tracked, but not controlled for with a standardized questionnaire.11Rodríguez-Lee M. Kolatkar A. McCormick M. Dago A.D. Kendall J. Carlsson N.A. Bethel K. Greenspan E.J. Hwang S.E. Waitman K.R. Nieva J.J. Hicks J. Kuhn P. Effect of blood collection tube type and time to processing on the enumeration and high-content characterization of circulating tumor cells using the high-definition single cell assay.Arch Pathol Lab Med. 2018; 142: 198-207Crossref PubMed Scopus (28) Google Scholar Clinical variables, as available, were additionally recorded. Standard operating procedure for blood collection was provided to each clinical site, including descriptive details on collection into the five specialized and proprietary tube types, in no particular order, through no particular needle type, with room temperature storage. A questionnaire was developed to assess the preanalytic variables related to collection and handling of blood samples with the purpose of tracking what cannot be prescribed. Variables, such as type of draw, anatomic location, collection device, BCT order, and needle gauge, were tracked. The blood draw questionnaire data for each draw were collected from each clinical site. The blood collection questionnaire used in this study can be located at http://kuhn.usc.edu/OPTICOLL/HDSCA_Blood_Draw_Questionnaire.pdf (last accessed August 6, 2019). All BCTs were packaged and shipped to the processing laboratory using a validated temperature-stable shipper, International Organization for Standardization–certified GreenBox Thermal Management System (ThermoSafe Brands, Arlington Heights, IL) and Standard71 shippers (Paradigm Design Solutions, Los Angeles, CA). Shipping events were tracked and monitored throughout the study. Each shipper received from blood collection sites was visually inspected for container integrity on unpacking at the laboratory. When components showed damage, the dysfunctional parts were replaced, or the entire box was discarded. Temperature maintenance tests of 10% of the shippers were completed with the use of XpressPDF temperature labels (PakSense; Emerson Cargo Solutions, Boise, ID). A total set of 40 peripheral blood samples were collected from 25 patients with breast cancer in a multicenter study.11Rodríguez-Lee M. Kolatkar A. McCormick M. Dago A.D. Kendall J. Carlsson N.A. Bethel K. Greenspan E.J. Hwang S.E. Waitman K.R. Nieva J.J. Hicks J. Kuhn P. Effect of blood collection tube type and time to processing on the enumeration and high-content characterization of circulating tumor cells using the high-definition single cell assay.Arch Pathol Lab Med. 2018; 142: 198-207Crossref PubMed Scopus (28) Google Scholar All patients were diagnosed with organ-confined or metastatic breast cancer. For each patient, up to 10 mL of peripheral blood was collected into CellSave blood collection tubes (BCTs; Veridex LLC) for the CellSearch test and 7.5 mL of blood was collected in Cell-Free DNA BCTs (Streck) for the HD-SCA workflow. The first 2 mL of blood drawn was discarded to remove any potential contamination. Blood was drawn at various time points during treatment. This study was approved by the institutional review board at Billings Clinical Hospital and Duke University Comprehensive Cancer Center. Informed consent was obtained from all participating patients. CTC enumeration was conducted using the CellSearch system (Veridex LLC), according to the manufacturer's protocol by a third-party laboratory. Enumeration of HD-CTCs by HD-SCA was conducted as described below. All blood samples were processed as previously described.11Rodríguez-Lee M. Kolatkar A. McCormick M. Dago A.D. Kendall J. Carlsson N.A. Bethel K. Greenspan E.J. Hwang S.E. Waitman K.R. Nieva J.J. Hicks J. Kuhn P. Effect of blood collection tube type and time to processing on the enumeration and high-content characterization of circulating tumor cells using the high-definition single cell assay.Arch Pathol Lab Med. 2018; 142: 198-207Crossref PubMed Scopus (28) Google Scholar,12Marrinucci D. Bethel K. Kolatkar A. Luttgen M.S. Malchiodi M. Baehring F. Voigt K. Lazar D. Nieva J. Bazhenova L. Ko A.H. Korn W.M. Schram E. Coward M. Yang X. Metzner T. Lamy R. Honnatti M. Yoshioka C. Kunken J. Petrova Y. Sok D. Nelson D. Kuhn P. Fluid biopsy in patients with metastatic prostate, pancreatic and breast cancers.Phys Biol. 2012; 9: 016003Crossref PubMed Scopus (224) Google Scholar Each sample was treated independently regardless of TTA. A maximum of 12 replicate slides for rare cell identification and characterization were prepared and stored at −80°C until further analysis. One test for detection of candidate cells consists of two slides. An immunofluorescence staining protocol based on the published HD-SCA workflow11Rodríguez-Lee M. Kolatkar A. McCormick M. Dago A.D. Kendall J. Carlsson N.A. Bethel K. Greenspan E.J. Hwang S.E. Waitman K.R. Nieva J.J. Hicks J. Kuhn P. Effect of blood collection tube type and time to processing on the enumeration and high-content characterization of circulating tumor cells using the high-definition single cell assay.Arch Pathol Lab Med. 2018; 142: 198-207Crossref PubMed Scopus (28) Google Scholar was used, which included an antibody cocktail of pan-cytokeratin (CK; catalog number C2562; Sigma-Aldrich, St. Louis, MO), anti-CK19 (catalog number M088801; Agilent Dako, Santa Clara, CA), anti-CD45 (catalog number MCA87A-647; Bio-Rad, Hercules, CA), anti–estrogen receptor (SP1; catalog number RM-9101-S; Thermo Fisher Scientific, Waltham, MA), and DAPI.11Rodríguez-Lee M. Kolatkar A. McCormick M. Dago A.D. Kendall J. Carlsson N.A. Bethel K. Greenspan E.J. Hwang S.E. Waitman K.R. Nieva J.J. Hicks J. Kuhn P. Effect of blood collection tube type and time to processing on the enumeration and high-content characterization of circulating tumor cells using the high-definition single cell assay.Arch Pathol Lab Med. 2018; 142: 198-207Crossref PubMed Scopus (28) Google Scholar Secondary antibodies were catalog number A-21127 and A-11034 from Life Technologies (Carlsbad, CA). The number of total retained cells was estimated using the count of the DAPI-stained nuclei. Cells that were CK+, CD45−, with intact nucleus, and generally larger and morphologically distinct from surrounding white blood cells (WBCs; HD-CTCs), as well as cells that only partially met these criteria (marginal CTC populations), were recorded.13Nieva J. Wendel M. Luttgen M.S. Marrinucci D. Bazhenova L. Kolatkar A. Santala R. Whittenberger B. Burke J. Torrey M. Bethel K. Kuhn P. High-definition imaging of circulating tumor cells and associated cellular events in non-small cell lung cancer patients: a longitudinal analysis.Phys Biol. 2012; 9: 016004Crossref PubMed Scopus (84) Google Scholar Marginal populations included the following: i) CTC small: CK+, CD45−, cells with intact nuclei that were the same size or smaller than neighboring WBCs; ii) CTC low CK: cells with CK levels lower than HD-CTCs or absent, CD45−, and large morphologically distinct nuclei; and iii) CTC cfDNA producing: CK+ CD45− cells with a DAPI pattern of nuclear condensation and fragmentation and plasma membrane blebs that are common features of apoptotic cells.14Tone S. Sugimoto K. Tanda K. Suda T. Uehira K. Kanouchi H. Samejima K. Minatogawa Y. Earnshaw W.C. Three distinct stages of apoptotic nuclear condensation revealed by time-lapse imaging, biochemical and electron microscopy analysis of cell-free apoptosis.Exp Cell Res. 2007; 313: 3635-3644Crossref PubMed Scopus (134) Google Scholar,15Wickman G. Julian L. Olson M.F. How apoptotic cells aid in the removal of their own cold dead bodies.Cell Death Differ" @default.
• W3001195005 created "2020-01-30" @default.
• W3001195005 creator A5000472988 @default.
• W3001195005 creator A5008106929 @default.
• W3001195005 creator A5015617292 @default.
• W3001195005 creator A5025053302 @default.
• W3001195005 creator A5035038616 @default.
• W3001195005 creator A5038921783 @default.
• W3001195005 creator A5039368375 @default.
• W3001195005 creator A5039465161 @default.
• W3001195005 creator A5040299950 @default.
• W3001195005 creator A5046869833 @default.
• W3001195005 creator A5053825989 @default.
• W3001195005 creator A5069092297 @default.
• W3001195005 creator A5069146532 @default.
• W3001195005 creator A5071469591 @default.
• W3001195005 creator A5073079380 @default.
• W3001195005 creator A5074650864 @default.
• W3001195005 creator A5077852290 @default.
• W3001195005 date "2020-03-01" @default.
• W3001195005 modified "2023-10-01" @default.
• W3001195005 title "Preanalytical Variables for the Genomic Assessment of the Cellular and Acellular Fractions of the Liquid Biopsy in a Cohort of Breast Cancer Patients" @default.
• W3001195005 cites W1948838904 @default.
• W3001195005 cites W1980565270 @default.
• W3001195005 cites W1985668297 @default.
• W3001195005 cites W1999095025 @default.
• W3001195005 cites W2001082792 @default.
• W3001195005 cites W2003069503 @default.
• W3001195005 cites W2025894409 @default.
• W3001195005 cites W2032518018 @default.
• W3001195005 cites W2045209734 @default.
• W3001195005 cites W2068674866 @default.
• W3001195005 cites W2074247829 @default.
• W3001195005 cites W2099607219 @default.
• W3001195005 cites W2104457974 @default.
• W3001195005 cites W2108596684 @default.
• W3001195005 cites W2126903025 @default.
• W3001195005 cites W2156858440 @default.
• W3001195005 cites W2167511369 @default.
• W3001195005 cites W2241632165 @default.
• W3001195005 cites W2279220517 @default.
• W3001195005 cites W2419065358 @default.
• W3001195005 cites W2419426348 @default.
• W3001195005 cites W2528992987 @default.
• W3001195005 cites W2564702165 @default.
• W3001195005 cites W2564717375 @default.
• W3001195005 cites W2586439328 @default.
• W3001195005 cites W2586986318 @default.
• W3001195005 cites W2770409203 @default.
• W3001195005 cites W2774591115 @default.
• W3001195005 cites W2775045801 @default.
• W3001195005 cites W2790122515 @default.
• W3001195005 cites W2793667186 @default.
• W3001195005 cites W2811305164 @default.
• W3001195005 cites W2907445134 @default.
• W3001195005 cites W2920863604 @default.
• W3001195005 cites W4237276785 @default.
• W3001195005 doi "https://doi.org/10.1016/j.jmoldx.2019.11.006" @default.
• W3001195005 hasPubMedCentralId "https://www.ncbi.nlm.nih.gov/pmc/articles/7103765" @default.
• W3001195005 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/31978562" @default.
• W3001195005 hasPublicationYear "2020" @default.
• W3001195005 type Work @default.
• W3001195005 sameAs 3001195005 @default.
• W3001195005 citedByCount "17" @default.
• W3001195005 countsByYear W30011950052019 @default.
• W3001195005 countsByYear W30011950052020 @default.
• W3001195005 countsByYear W30011950052021 @default.
• W3001195005 countsByYear W30011950052022 @default.
• W3001195005 countsByYear W30011950052023 @default.
• W3001195005 crossrefType "journal-article" @default.
• W3001195005 hasAuthorship W3001195005A5000472988 @default.
• W3001195005 hasAuthorship W3001195005A5008106929 @default.
• W3001195005 hasAuthorship W3001195005A5015617292 @default.
• W3001195005 hasAuthorship W3001195005A5025053302 @default.
• W3001195005 hasAuthorship W3001195005A5035038616 @default.
• W3001195005 hasAuthorship W3001195005A5038921783 @default.
• W3001195005 hasAuthorship W3001195005A5039368375 @default.
• W3001195005 hasAuthorship W3001195005A5039465161 @default.
• W3001195005 hasAuthorship W3001195005A5040299950 @default.
• W3001195005 hasAuthorship W3001195005A5046869833 @default.
• W3001195005 hasAuthorship W3001195005A5053825989 @default.
• W3001195005 hasAuthorship W3001195005A5069092297 @default.
• W3001195005 hasAuthorship W3001195005A5069146532 @default.
• W3001195005 hasAuthorship W3001195005A5071469591 @default.
• W3001195005 hasAuthorship W3001195005A5073079380 @default.
• W3001195005 hasAuthorship W3001195005A5074650864 @default.
• W3001195005 hasAuthorship W3001195005A5077852290 @default.
• W3001195005 hasBestOaLocation W30011950051 @default.
• W3001195005 hasConcept C121608353 @default.
• W3001195005 hasConcept C126322002 @default.
• W3001195005 hasConcept C142724271 @default.
• W3001195005 hasConcept C143998085 @default.
• W3001195005 hasConcept C2775934546 @default.
• W3001195005 hasConcept C2779529041 @default.
• W3001195005 hasConcept C530470458 @default.
• W3001195005 hasConcept C71924100 @default.
• W3001195005 hasConcept C72563966 @default.
• W3001195005 hasConceptScore W3001195005C121608353 @default.

• next