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Xiong C, Schindler S, Luo J, Morris J, Bateman R, Holtzman D, Cruchaga C, Babulal G, Henson R, Benzinger T, Bui Q, Agboola F, Grant E, Emily G, Moulder K, Geldmacher D, Clay O, Roberson E, Murchison C, Wolk D, Shaw L. Baseline levels and longitudinal rates of change in plasma Aβ42/40 among self-identified Black/African American and White individuals. Res Sq 2024:rs.3.rs-3783571. [PMID: 38260384 PMCID: PMC10802715 DOI: 10.21203/rs.3.rs-3783571/v1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/24/2024]
Abstract
Objective The use of blood-based biomarkers of Alzheimer disease (AD) may facilitate access to biomarker testing of groups that have been historically under-represented in research. We evaluated whether plasma Aβ42/40 has similar or different baseline levels and longitudinal rates of change in participants racialized as Black or White. Methods The Study of Race to Understand Alzheimer Biomarkers (SORTOUT-AB) is a multi-center longitudinal study to evaluate for potential differences in AD biomarkers between individuals racialized as Black or White. Plasma samples collected at three AD Research Centers (Washington University, University of Pennsylvania, and University of Alabama-Birmingham) underwent analysis with C2N Diagnostics' PrecivityAD™ blood test for Aβ42 and Aβ40. General linear mixed effects models were used to estimate the baseline levels and rates of longitudinal change for plasma Aβ measures in both racial groups. Analyses also examined whether dementia status, age, sex, education, APOE ε4 carrier status, medical comorbidities, or fasting status modified potential racial differences. Results Of the 324 Black and 1,547 White participants, there were 158 Black and 759 White participants with plasma Aβ measures from at least two longitudinal samples over a mean interval of 6.62 years. At baseline, the group of Black participants had lower levels of plasma Aβ40 but similar levels of plasma Aβ42 as compared to the group of White participants. As a result, baseline plasma Aβ42/40 levels were higher in the Black group than the White group, consistent with the Black group having lower levels of amyloid pathology. Racial differences in plasma Aβ42/40 were not modified by age, sex, education, APOE ε4 carrier status, medical conditions (hypertension and diabetes), or fasting status. Despite differences in baseline levels, the Black and White groups had a similar longitudinal rate of change in plasma Aβ42/40. Interpretation Black individuals participating in AD research studies had a higher mean level of plasma Aβ42/40, consistent with a lower level of amyloid pathology, which, if confirmed, may imply a lower proportion of Black individuals being eligible for AD clinical trials in which the presence of amyloid is a prerequisite. However, there was no significant racial difference in the rate of change in plasma Aβ42/40, suggesting that amyloid pathology accumulates similarly across racialized groups.
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Affiliation(s)
| | | | | | | | | | | | | | | | | | | | - Quoc Bui
- Washington University School of Medicine
| | | | | | | | | | | | | | | | | | - David Wolk
- Department of Neurology, University of Pennsylvania
| | - Leslie Shaw
- Perelman School of Medicine, University of Pennsylvania
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Stevens S, Jang JK, Kershaw K, Viramontes J, Dar TB, Nguyen AT, Henson R, Guarnerio J, Underhill D, Shiao SL. Fungal Depletion Bolsters Anti-Tumor Immune Response Elicited by Anti-PD1 Alone and in Combination with Radiation Therapy. Int J Radiat Oncol Biol Phys 2023; 117:S166. [PMID: 37784414 DOI: 10.1016/j.ijrobp.2023.06.265] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/04/2023]
Abstract
PURPOSE/OBJECTIVE(S) Pembrolizumab in combination with chemotherapy has become the standard of care treatment for both metastatic and early-stage triple negative breast cancer (TNBC). Clinical trials are currently underway investigating the use of pembrolizumab with radiation in the neoadjuvant setting in early TNBC. Several groups have described a link between the microbiome and the efficacy of chemotherapy and anti-PD1 immune checkpoint inhibitors (ICIs) in preclinical models. Recent work from our lab has shown that targeting commensal fungi in the microbiome enhances the radiation induced antitumor immune response. Therefore, we hypothesized that fungal depletion might positively impact anti-PD1 therapy and combination treatment with anti-PD1 and radiation therapy (RT). MATERIALS/METHODS This study utilized an orthotopic syngeneic breast tumor model in which the syngeneic cell line E0771 was injected into the mammary fat pad of female C57BL/6 mice. Tumor-bearing mice were then treated with and without the antifungal fluconazole, anti-PD1, and radiation (16 Gy single fraction) using the X-RAD SmART platform with CT guidance. Tumor volumes were compared using 2-way ANOVA and survival curves analyzed using log rank. In a separate set of experiments, tumor-infiltrating immune cells were isolated and analyzed by high-dimensional multiplex flow cytometry. RESULTS We found that fungal depletion with fluconazole prior to treatment with anti-PD1 reduced the tumor volume and significantly improved survival in comparison to those treated with anti-PD1 alone (P = 0.0016). To identify what changes in the tumor immune microenvironment is driving this increased anti-tumor response, we performed flow cytometry on immune cells isolated from the tumors. We found that the use of fluconazole prior to anti-PD1 treatment reduced the proportion of CD11b+F4/80+ tumor-associated macrophages (TAMs) (P = 0.01) and increased tumor infiltrating cytotoxic T cell population (P = 0.04) when compared with the use of anti-PD1 alone. We also evaluated the effect of fungal depletion on combination therapy with RT and anti-PD1. Strikingly, we found that mice depleted of fungi with fluconazole prior to radiation and anti-PD1 therapy, have decreased tumor burden and significantly increased survival when compared to their fungally-intact counterparts (P = 0.043). CONCLUSION Our data indicates that the depletion of the gut fungal populations induces an increased antitumor response following anti-PD1 alone and in combination with radiation. This increased antitumor immune response is associated with an increase in the cytotoxic CD8+ T cell compartment with concomitant decrease in immunosuppressive tumor associated macrophages.
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Affiliation(s)
- S Stevens
- Department of Radiation Oncology, Cedars-Sinai Medical Center, Los Angeles, CA
| | - J K Jang
- Department of Radiation Oncology, Cedars-Sinai Medical Center, Los Angeles, CA
| | - K Kershaw
- Cedars-Sinai Medical Center, Los Angeles, CA
| | - J Viramontes
- Department of Radiation Oncology, Cedars-Sinai Medical Center, Los Angeles, CA
| | - T B Dar
- Cedars-Sinai Medical Center, Los Angeles, CA
| | - A T Nguyen
- Department of Radiation Oncology, Cedars-Sinai Medical Center, Los Angeles, CA
| | - R Henson
- Department of Radiation Oncology, Cedars-Sinai Medical Center, Los Angeles, CA
| | - J Guarnerio
- Department of Radiation Oncology, Cedars-Sinai Medical Center, Los Angeles, CA
| | - D Underhill
- Department of Biomedical Sciences, Cedars-Sinai Medical Center, Los Angeles, CA
| | - S L Shiao
- Department of Radiation Oncology, Cedars-Sinai Medical Center, Los Angeles, CA
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Dar TB, Nguyen AT, Stevens S, Viramontes J, Henson R, Jang JK, Guarnerio J, Underhill D, Shiao SL. Reshaping Macrophage Polarization Potential Enhances Antitumor Immune Response to Radiation Therapy. Int J Radiat Oncol Biol Phys 2023; 117:e225-e226. [PMID: 37784913 DOI: 10.1016/j.ijrobp.2023.06.1133] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/04/2023]
Abstract
PURPOSE/OBJECTIVE(S) Although radiation therapy (RT) remains a cornerstone in the treatment of breast cancer, many trials combining RT with immune checkpoint blockade (ICB) have failed to demonstrate benefit in solid tumors including breast cancer. Maximal efficacy of RT relies on the generation of antitumor immunity following treatment which largely consists of cytotoxic T cells and macrophages. Broad depletion of macrophages modestly enhances tumor responses to RT suggesting that they can shape RT-induced antitumor immunity. Although IL4 signaling through GATA-3 is known to polarize T cells into the protumor Th2 phenotype, such central drivers of macrophage polarization are not well established. Given that macrophages abundantly express IL4 receptor, we hypothesized that GATA-3 may direct the transition of macrophages to M2/alternative phase and that genetic ablation of GATA-3 in macrophages can enhance antitumor immunity by arresting macrophage transition to an M2-like pro-tumor state. MATERIALS/METHODS We generated a macrophage specific GATA-3 KO mouse model (mG3KO) driven by the LysM-Cre promoter. Using a syngeneic orthotopic murine model of breast cancer (EO771), we evaluated the differential effect of RT (16Gy x 1) in WT and mG3KO mice. Multiparametric flow cytometry was performed to investigate the immune changes within the tumor microenvironment on day 3, day 5 and day 10 after RT. T cell depletion was performed using antibodies to CD4 and CD8 by intraperitoneal injections to understand the role of adaptive immunity in the response to RT in WT and mG3KO mice. RESULTS We found that mG3KO mice bearing advanced EO771 tumors demonstrated significantly improved tumor regression compared to WT mice (p<0.001), which translated to increased overall survival. In vitro characterization of bone-marrow derived macrophages from mG3KO and WT mice suggest that macrophages with ablated GATA-3 expressed increased levels of iNOS and decreased levels of Arginase (Arg-1), consistent with an M1-like phenotype. Immune profiling of the tumors also revealed that mGATA-3 KO animals have significant enrichment of CD8+ T cells in the tumor milieu post RT and these CD8+ T cells express higher amounts of interferon gamma (p<0.001) and Granzyme B (p<0.0015) than their WT counterparts. Using neutralizing antibodies to deplete CD8+ T cells, we show that anti-tumor effects in the mG3KO mice were abolished, suggesting that mG3KO macrophages impact survival, at least, in part by enhancing cytotoxic CD8+T cells. Studies are currently ongoing to reveal the detailed mechanism of GATA-3 ablation in improving the efficacy of RT. CONCLUSION Our data indicates that GATA-3 is a central regulator of macrophage polarization in response to RT. Further, directed ablation of GATA-3 appears to drive macrophages towards an M1-like phenotype, which enhances T cell recruitment to irradiated tumors. These data suggest that the antitumor efficacy of RT can be prolonged by targeting GATA-3-dependent signaling within myeloid cells.
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Affiliation(s)
- T B Dar
- Department of Radiation Oncology, Cedars-Sinai Medical Center, Los Angeles, CA
| | - A T Nguyen
- Department of Radiation Oncology, Cedars-Sinai Medical Center, Los Angeles, CA
| | - S Stevens
- Department of Radiation Oncology, Cedars-Sinai Medical Center, Los Angeles, CA
| | - J Viramontes
- Department of Radiation Oncology, Cedars-Sinai Medical Center, Los Angeles, CA
| | - R Henson
- Department of Radiation Oncology, Cedars-Sinai Medical Center, Los Angeles, CA
| | - J K Jang
- Department of Radiation Oncology, Cedars-Sinai Medical Center, Los Angeles, CA
| | - J Guarnerio
- Department of Radiation Oncology, Cedars-Sinai Medical Center, Los Angeles, CA
| | - D Underhill
- Department of Biomedical Sciences, Cedars-Sinai Medical Center, Los Angeles, CA
| | - S L Shiao
- Department of Radiation Oncology, Cedars-Sinai Medical Center, Los Angeles, CA
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4
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Bottomly D, Long N, Schultz AR, Kurtz SE, Tognon CE, Johnson K, Abel M, Agarwal A, Avaylon S, Benton E, Blucher A, Borate U, Braun TP, Brown J, Bryant J, Burke R, Carlos A, Chang BH, Cho HJ, Christy S, Coblentz C, Cohen AM, d'Almeida A, Cook R, Danilov A, Dao KHT, Degnin M, Dibb J, Eide CA, English I, Hagler S, Harrelson H, Henson R, Ho H, Joshi SK, Junio B, Kaempf A, Kosaka Y, Laderas T, Lawhead M, Lee H, Leonard JT, Lin C, Lind EF, Liu SQ, Lo P, Loriaux MM, Luty S, Maxson JE, Macey T, Martinez J, Minnier J, Monteblanco A, Mori M, Morrow Q, Nelson D, Ramsdill J, Rofelty A, Rogers A, Romine KA, Ryabinin P, Saultz JN, Sampson DA, Savage SL, Schuff R, Searles R, Smith RL, Spurgeon SE, Sweeney T, Swords RT, Thapa A, Thiel-Klare K, Traer E, Wagner J, Wilmot B, Wolf J, Wu G, Yates A, Zhang H, Cogle CR, Collins RH, Deininger MW, Hourigan CS, Jordan CT, Lin TL, Martinez ME, Pallapati RR, Pollyea DA, Pomicter AD, Watts JM, Weir SJ, Druker BJ, McWeeney SK, Tyner JW. Integrative analysis of drug response and clinical outcome in acute myeloid leukemia. Cancer Cell 2022; 40:850-864.e9. [PMID: 35868306 PMCID: PMC9378589 DOI: 10.1016/j.ccell.2022.07.002] [Citation(s) in RCA: 68] [Impact Index Per Article: 34.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/01/2022] [Revised: 05/30/2022] [Accepted: 06/30/2022] [Indexed: 12/17/2022]
Abstract
Acute myeloid leukemia (AML) is a cancer of myeloid-lineage cells with limited therapeutic options. We previously combined ex vivo drug sensitivity with genomic, transcriptomic, and clinical annotations for a large cohort of AML patients, which facilitated discovery of functional genomic correlates. Here, we present a dataset that has been harmonized with our initial report to yield a cumulative cohort of 805 patients (942 specimens). We show strong cross-cohort concordance and identify features of drug response. Further, deconvoluting transcriptomic data shows that drug sensitivity is governed broadly by AML cell differentiation state, sometimes conditionally affecting other correlates of response. Finally, modeling of clinical outcome reveals a single gene, PEAR1, to be among the strongest predictors of patient survival, especially for young patients. Collectively, this report expands a large functional genomic resource, offers avenues for mechanistic exploration and drug development, and reveals tools for predicting outcome in AML.
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Affiliation(s)
- Daniel Bottomly
- Division of Bioinformatics and Computational Biology, Department of Medical Informatics and Clinical Epidemiology, Oregon Health & Science University, Portland, OR 97239, USA; Knight Cancer Institute, Oregon Health & Science University, Portland, OR 97239, USA
| | - Nicola Long
- Knight Cancer Institute, Oregon Health & Science University, Portland, OR 97239, USA; Division of Hematology & Medical Oncology, Department of Medicine, Oregon Health & Science University, Portland, OR 97239, USA
| | - Anna Reister Schultz
- Knight Cancer Institute, Oregon Health & Science University, Portland, OR 97239, USA; Department of Cell, Developmental & Cancer Biology, Oregon Health & Science University, Portland, OR 97239, USA
| | - Stephen E Kurtz
- Knight Cancer Institute, Oregon Health & Science University, Portland, OR 97239, USA; Division of Hematology & Medical Oncology, Department of Medicine, Oregon Health & Science University, Portland, OR 97239, USA
| | - Cristina E Tognon
- Knight Cancer Institute, Oregon Health & Science University, Portland, OR 97239, USA; Division of Hematology & Medical Oncology, Department of Medicine, Oregon Health & Science University, Portland, OR 97239, USA
| | - Kara Johnson
- Knight Cancer Institute, Oregon Health & Science University, Portland, OR 97239, USA; Division of Hematology & Medical Oncology, Department of Medicine, Oregon Health & Science University, Portland, OR 97239, USA
| | - Melissa Abel
- Knight Cancer Institute, Oregon Health & Science University, Portland, OR 97239, USA; Department of Cell, Developmental & Cancer Biology, Oregon Health & Science University, Portland, OR 97239, USA
| | - Anupriya Agarwal
- Knight Cancer Institute, Oregon Health & Science University, Portland, OR 97239, USA; Department of Cell, Developmental & Cancer Biology, Oregon Health & Science University, Portland, OR 97239, USA; Department of Molecular & Medical Genetics, Oregon Health & Science University, Portland, OR 97239, USA; Division of Oncologic Sciences, Department of Medicine, Oregon Health & Science University, Portland, OR 97239, USA
| | - Sammantha Avaylon
- Knight Cancer Institute, Oregon Health & Science University, Portland, OR 97239, USA; Division of Hematology & Medical Oncology, Department of Medicine, Oregon Health & Science University, Portland, OR 97239, USA
| | - Erik Benton
- Division of Bioinformatics and Computational Biology, Department of Medical Informatics and Clinical Epidemiology, Oregon Health & Science University, Portland, OR 97239, USA; Oregon Clinical and Translational Research Institute, Oregon Health & Science University, Portland, OR 97239, USA
| | - Aurora Blucher
- Division of Bioinformatics and Computational Biology, Department of Medical Informatics and Clinical Epidemiology, Oregon Health & Science University, Portland, OR 97239, USA; Knight Cancer Institute, Oregon Health & Science University, Portland, OR 97239, USA
| | - Uma Borate
- Division of Hematology, Department of Internal Medicine, James Cancer Center, Ohio State University, Columbus, OH 43210, USA
| | - Theodore P Braun
- Knight Cancer Institute, Oregon Health & Science University, Portland, OR 97239, USA; Division of Hematology & Medical Oncology, Department of Medicine, Oregon Health & Science University, Portland, OR 97239, USA
| | - Jordana Brown
- Knight Cancer Institute, Oregon Health & Science University, Portland, OR 97239, USA; Department of Cell, Developmental & Cancer Biology, Oregon Health & Science University, Portland, OR 97239, USA
| | - Jade Bryant
- Knight Cancer Institute, Oregon Health & Science University, Portland, OR 97239, USA; Department of Cell, Developmental & Cancer Biology, Oregon Health & Science University, Portland, OR 97239, USA
| | - Russell Burke
- Knight Cancer Institute, Oregon Health & Science University, Portland, OR 97239, USA; Division of Hematology & Medical Oncology, Department of Medicine, Oregon Health & Science University, Portland, OR 97239, USA
| | - Amy Carlos
- Knight Cancer Institute, Oregon Health & Science University, Portland, OR 97239, USA; Integrated Genomics Laboratory, Oregon Health & Science University, Portland, OR 97239, USA
| | - Bill H Chang
- Knight Cancer Institute, Oregon Health & Science University, Portland, OR 97239, USA; Division of Hematology and Oncology, Department of Pediatrics, Oregon Health & Science University, Portland, OR 97239, USA
| | - Hyun Jun Cho
- Knight Cancer Institute, Oregon Health & Science University, Portland, OR 97239, USA; Department of Molecular Microbiology and Immunology, Oregon Health & Science University, Portland, OR 97239, USA
| | - Stephen Christy
- Knight Cancer Institute, Oregon Health & Science University, Portland, OR 97239, USA; Division of Hematology & Medical Oncology, Department of Medicine, Oregon Health & Science University, Portland, OR 97239, USA
| | - Cody Coblentz
- Knight Cancer Institute, Oregon Health & Science University, Portland, OR 97239, USA; Division of Hematology & Medical Oncology, Department of Medicine, Oregon Health & Science University, Portland, OR 97239, USA
| | - Aaron M Cohen
- Division of Bioinformatics and Computational Biology, Department of Medical Informatics and Clinical Epidemiology, Oregon Health & Science University, Portland, OR 97239, USA; Knight Cancer Institute, Oregon Health & Science University, Portland, OR 97239, USA; Oregon Clinical and Translational Research Institute, Oregon Health & Science University, Portland, OR 97239, USA
| | - Amanda d'Almeida
- Knight Cancer Institute, Oregon Health & Science University, Portland, OR 97239, USA; Department of Cell, Developmental & Cancer Biology, Oregon Health & Science University, Portland, OR 97239, USA
| | - Rachel Cook
- Knight Cancer Institute, Oregon Health & Science University, Portland, OR 97239, USA; Division of Hematology & Medical Oncology, Department of Medicine, Oregon Health & Science University, Portland, OR 97239, USA
| | - Alexey Danilov
- Department of Hematology and Hematopoietic Stem Cell Transplant, City of Hope National Medical Center, Duarte, CA 91010, USA
| | | | - Michie Degnin
- Knight Cancer Institute, Oregon Health & Science University, Portland, OR 97239, USA; Division of Hematology & Medical Oncology, Department of Medicine, Oregon Health & Science University, Portland, OR 97239, USA
| | - James Dibb
- Knight Cancer Institute, Oregon Health & Science University, Portland, OR 97239, USA; Division of Hematology & Medical Oncology, Department of Medicine, Oregon Health & Science University, Portland, OR 97239, USA
| | - Christopher A Eide
- Knight Cancer Institute, Oregon Health & Science University, Portland, OR 97239, USA; Division of Hematology & Medical Oncology, Department of Medicine, Oregon Health & Science University, Portland, OR 97239, USA
| | - Isabel English
- Knight Cancer Institute, Oregon Health & Science University, Portland, OR 97239, USA; Division of Hematology & Medical Oncology, Department of Medicine, Oregon Health & Science University, Portland, OR 97239, USA
| | - Stuart Hagler
- Division of Bioinformatics and Computational Biology, Department of Medical Informatics and Clinical Epidemiology, Oregon Health & Science University, Portland, OR 97239, USA; Oregon Clinical and Translational Research Institute, Oregon Health & Science University, Portland, OR 97239, USA
| | - Heath Harrelson
- Division of Bioinformatics and Computational Biology, Department of Medical Informatics and Clinical Epidemiology, Oregon Health & Science University, Portland, OR 97239, USA; Oregon Clinical and Translational Research Institute, Oregon Health & Science University, Portland, OR 97239, USA
| | - Rachel Henson
- Knight Cancer Institute, Oregon Health & Science University, Portland, OR 97239, USA; Integrated Genomics Laboratory, Oregon Health & Science University, Portland, OR 97239, USA
| | - Hibery Ho
- Knight Cancer Institute, Oregon Health & Science University, Portland, OR 97239, USA; Division of Hematology & Medical Oncology, Department of Medicine, Oregon Health & Science University, Portland, OR 97239, USA
| | - Sunil K Joshi
- Knight Cancer Institute, Oregon Health & Science University, Portland, OR 97239, USA; Division of Hematology & Medical Oncology, Department of Medicine, Oregon Health & Science University, Portland, OR 97239, USA
| | - Brian Junio
- Knight Cancer Institute, Oregon Health & Science University, Portland, OR 97239, USA; Division of Hematology & Medical Oncology, Department of Medicine, Oregon Health & Science University, Portland, OR 97239, USA
| | - Andy Kaempf
- Knight Cancer Institute, Oregon Health & Science University, Portland, OR 97239, USA; Biostatistics Shared Resource, Oregon Health & Science University, Portland, OR 97239, USA
| | - Yoko Kosaka
- Knight Cancer Institute, Oregon Health & Science University, Portland, OR 97239, USA; Department of Molecular Microbiology and Immunology, Oregon Health & Science University, Portland, OR 97239, USA
| | | | - Matt Lawhead
- Division of Bioinformatics and Computational Biology, Department of Medical Informatics and Clinical Epidemiology, Oregon Health & Science University, Portland, OR 97239, USA; Oregon Clinical and Translational Research Institute, Oregon Health & Science University, Portland, OR 97239, USA
| | - Hyunjung Lee
- Knight Cancer Institute, Oregon Health & Science University, Portland, OR 97239, USA; Department of Cell, Developmental & Cancer Biology, Oregon Health & Science University, Portland, OR 97239, USA
| | - Jessica T Leonard
- Knight Cancer Institute, Oregon Health & Science University, Portland, OR 97239, USA; Division of Hematology & Medical Oncology, Department of Medicine, Oregon Health & Science University, Portland, OR 97239, USA
| | - Chenwei Lin
- Knight Cancer Institute, Oregon Health & Science University, Portland, OR 97239, USA; Integrated Genomics Laboratory, Oregon Health & Science University, Portland, OR 97239, USA
| | - Evan F Lind
- Knight Cancer Institute, Oregon Health & Science University, Portland, OR 97239, USA; Department of Molecular Microbiology and Immunology, Oregon Health & Science University, Portland, OR 97239, USA
| | - Selina Qiuying Liu
- Knight Cancer Institute, Oregon Health & Science University, Portland, OR 97239, USA; Division of Hematology & Medical Oncology, Department of Medicine, Oregon Health & Science University, Portland, OR 97239, USA
| | - Pierrette Lo
- Knight Cancer Institute, Oregon Health & Science University, Portland, OR 97239, USA; Division of Hematology & Medical Oncology, Department of Medicine, Oregon Health & Science University, Portland, OR 97239, USA
| | - Marc M Loriaux
- Knight Cancer Institute, Oregon Health & Science University, Portland, OR 97239, USA; Department of Pathology, Oregon Health & Science University, Portland, OR 97239, USA
| | - Samuel Luty
- Knight Cancer Institute, Oregon Health & Science University, Portland, OR 97239, USA; Division of Hematology & Medical Oncology, Department of Medicine, Oregon Health & Science University, Portland, OR 97239, USA
| | - Julia E Maxson
- Knight Cancer Institute, Oregon Health & Science University, Portland, OR 97239, USA; Division of Oncologic Sciences, Department of Medicine, Oregon Health & Science University, Portland, OR 97239, USA
| | - Tara Macey
- Knight Cancer Institute, Oregon Health & Science University, Portland, OR 97239, USA; Division of Hematology & Medical Oncology, Department of Medicine, Oregon Health & Science University, Portland, OR 97239, USA
| | - Jacqueline Martinez
- Knight Cancer Institute, Oregon Health & Science University, Portland, OR 97239, USA; Division of Hematology & Medical Oncology, Department of Medicine, Oregon Health & Science University, Portland, OR 97239, USA
| | - Jessica Minnier
- Knight Cancer Institute, Oregon Health & Science University, Portland, OR 97239, USA; Biostatistics Shared Resource, Oregon Health & Science University, Portland, OR 97239, USA; OHSU-PSU School of Public Health, VA Portland Health Care System, Oregon Health & Science University, Portland, OR 97239, USA
| | - Andrea Monteblanco
- Knight Cancer Institute, Oregon Health & Science University, Portland, OR 97239, USA; Division of Hematology & Medical Oncology, Department of Medicine, Oregon Health & Science University, Portland, OR 97239, USA
| | - Motomi Mori
- Department of Biostatistics, St. Jude Children's Research Hospital, Memphis, TN 38105, USA
| | - Quinlan Morrow
- Knight Cancer Institute, Oregon Health & Science University, Portland, OR 97239, USA; Department of Cell, Developmental & Cancer Biology, Oregon Health & Science University, Portland, OR 97239, USA
| | - Dylan Nelson
- High-Throughput Screening Services Laboratory, Oregon State University, Corvallis, OR 97331, USA
| | - Justin Ramsdill
- Division of Bioinformatics and Computational Biology, Department of Medical Informatics and Clinical Epidemiology, Oregon Health & Science University, Portland, OR 97239, USA; Oregon Clinical and Translational Research Institute, Oregon Health & Science University, Portland, OR 97239, USA
| | - Angela Rofelty
- Knight Cancer Institute, Oregon Health & Science University, Portland, OR 97239, USA; Department of Cell, Developmental & Cancer Biology, Oregon Health & Science University, Portland, OR 97239, USA
| | - Alexandra Rogers
- Knight Cancer Institute, Oregon Health & Science University, Portland, OR 97239, USA; Division of Hematology & Medical Oncology, Department of Medicine, Oregon Health & Science University, Portland, OR 97239, USA
| | - Kyle A Romine
- Knight Cancer Institute, Oregon Health & Science University, Portland, OR 97239, USA; Department of Cell, Developmental & Cancer Biology, Oregon Health & Science University, Portland, OR 97239, USA
| | - Peter Ryabinin
- Division of Bioinformatics and Computational Biology, Department of Medical Informatics and Clinical Epidemiology, Oregon Health & Science University, Portland, OR 97239, USA; Knight Cancer Institute, Oregon Health & Science University, Portland, OR 97239, USA
| | - Jennifer N Saultz
- Knight Cancer Institute, Oregon Health & Science University, Portland, OR 97239, USA; Division of Hematology & Medical Oncology, Department of Medicine, Oregon Health & Science University, Portland, OR 97239, USA
| | - David A Sampson
- Knight Cancer Institute, Oregon Health & Science University, Portland, OR 97239, USA; Division of Hematology & Medical Oncology, Department of Medicine, Oregon Health & Science University, Portland, OR 97239, USA
| | - Samantha L Savage
- Knight Cancer Institute, Oregon Health & Science University, Portland, OR 97239, USA; Division of Hematology & Medical Oncology, Department of Medicine, Oregon Health & Science University, Portland, OR 97239, USA
| | | | - Robert Searles
- Knight Cancer Institute, Oregon Health & Science University, Portland, OR 97239, USA; Integrated Genomics Laboratory, Oregon Health & Science University, Portland, OR 97239, USA
| | - Rebecca L Smith
- Knight Cancer Institute, Oregon Health & Science University, Portland, OR 97239, USA; Division of Hematology & Medical Oncology, Department of Medicine, Oregon Health & Science University, Portland, OR 97239, USA
| | - Stephen E Spurgeon
- Knight Cancer Institute, Oregon Health & Science University, Portland, OR 97239, USA; Division of Hematology & Medical Oncology, Department of Medicine, Oregon Health & Science University, Portland, OR 97239, USA
| | - Tyler Sweeney
- Knight Cancer Institute, Oregon Health & Science University, Portland, OR 97239, USA; Division of Hematology & Medical Oncology, Department of Medicine, Oregon Health & Science University, Portland, OR 97239, USA
| | - Ronan T Swords
- Knight Cancer Institute, Oregon Health & Science University, Portland, OR 97239, USA; Division of Hematology & Medical Oncology, Department of Medicine, Oregon Health & Science University, Portland, OR 97239, USA
| | - Aashis Thapa
- Knight Cancer Institute, Oregon Health & Science University, Portland, OR 97239, USA; Division of Hematology & Medical Oncology, Department of Medicine, Oregon Health & Science University, Portland, OR 97239, USA
| | - Karina Thiel-Klare
- Knight Cancer Institute, Oregon Health & Science University, Portland, OR 97239, USA; Division of Hematology & Medical Oncology, Department of Medicine, Oregon Health & Science University, Portland, OR 97239, USA
| | - Elie Traer
- Knight Cancer Institute, Oregon Health & Science University, Portland, OR 97239, USA; Division of Hematology & Medical Oncology, Department of Medicine, Oregon Health & Science University, Portland, OR 97239, USA
| | - Jake Wagner
- Knight Cancer Institute, Oregon Health & Science University, Portland, OR 97239, USA; Division of Hematology & Medical Oncology, Department of Medicine, Oregon Health & Science University, Portland, OR 97239, USA
| | - Beth Wilmot
- Division of Bioinformatics and Computational Biology, Department of Medical Informatics and Clinical Epidemiology, Oregon Health & Science University, Portland, OR 97239, USA; Oregon Clinical and Translational Research Institute, Oregon Health & Science University, Portland, OR 97239, USA
| | - Joelle Wolf
- Knight Cancer Institute, Oregon Health & Science University, Portland, OR 97239, USA; Division of Hematology & Medical Oncology, Department of Medicine, Oregon Health & Science University, Portland, OR 97239, USA
| | - Guanming Wu
- Division of Bioinformatics and Computational Biology, Department of Medical Informatics and Clinical Epidemiology, Oregon Health & Science University, Portland, OR 97239, USA; Knight Cancer Institute, Oregon Health & Science University, Portland, OR 97239, USA; Oregon Clinical and Translational Research Institute, Oregon Health & Science University, Portland, OR 97239, USA
| | - Amy Yates
- Division of Bioinformatics and Computational Biology, Department of Medical Informatics and Clinical Epidemiology, Oregon Health & Science University, Portland, OR 97239, USA; Oregon Clinical and Translational Research Institute, Oregon Health & Science University, Portland, OR 97239, USA
| | - Haijiao Zhang
- Knight Cancer Institute, Oregon Health & Science University, Portland, OR 97239, USA; Division of Oncologic Sciences, Department of Medicine, Oregon Health & Science University, Portland, OR 97239, USA
| | - Christopher R Cogle
- Department of Medicine, Division of Hematology and Oncology, University of Florida, Gainesville, FL 32610, USA
| | - Robert H Collins
- Department of Internal Medicine/ Hematology Oncology, University of Texas Southwestern Medical Center, Dallas, TX 75390-8565, USA
| | - Michael W Deininger
- Division of Hematology & Hematologic Malignancies, Department of Internal Medicine, University of Utah, Salt Lake City, UT 84112, USA; Huntsman Cancer Institute, University of Utah, Salt Lake City, UT 84112, USA
| | - Christopher S Hourigan
- National Heart, Lung and Blood Institute, National Institutes of Health, Bethesda, MD 20814-1476, USA
| | - Craig T Jordan
- Division of Hematology, University of Colorado, Denver, CO 80045, USA
| | - Tara L Lin
- Division of Hematologic Malignancies & Cellular Therapeutics, University of Kansas, Kansas City, KS 66205, USA
| | - Micaela E Martinez
- Clinical Research Services, University of Miami Sylvester Comprehensive Cancer Center, Miami, FL 33136, USA
| | - Rachel R Pallapati
- Clinical Research Services, University of Miami Sylvester Comprehensive Cancer Center, Miami, FL 33136, USA
| | - Daniel A Pollyea
- Division of Hematology, University of Colorado, Denver, CO 80045, USA
| | - Anthony D Pomicter
- Huntsman Cancer Institute, University of Utah, Salt Lake City, UT 84112, USA
| | - Justin M Watts
- Division of Hematology, Department of Medicine, University of Miami Sylvester Comprehensive Cancer Center, Miami, FL 33136, USA
| | - Scott J Weir
- Department of Cancer Biology, Division of Medical Oncology, Department of Medicine, University of Kansas Medical Center, Kansas City, KS 66160, USA
| | - Brian J Druker
- Knight Cancer Institute, Oregon Health & Science University, Portland, OR 97239, USA; Division of Hematology & Medical Oncology, Department of Medicine, Oregon Health & Science University, Portland, OR 97239, USA.
| | - Shannon K McWeeney
- Division of Bioinformatics and Computational Biology, Department of Medical Informatics and Clinical Epidemiology, Oregon Health & Science University, Portland, OR 97239, USA; Knight Cancer Institute, Oregon Health & Science University, Portland, OR 97239, USA; Oregon Clinical and Translational Research Institute, Oregon Health & Science University, Portland, OR 97239, USA.
| | - Jeffrey W Tyner
- Knight Cancer Institute, Oregon Health & Science University, Portland, OR 97239, USA; Department of Cell, Developmental & Cancer Biology, Oregon Health & Science University, Portland, OR 97239, USA.
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5
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Queder N, Phelan MJ, Taylor L, Tustison N, Doran E, Hom C, Nguyen D, Lai F, Pulsifer M, Price J, Kreisl WC, Rosas HD, Krinsky‐McHale S, Brickman AM, Yassa MA, Schupf N, Silverman W, Lott IT, Head E, Mapstone M, Keator DB, Ances BM, Andrews HF, Bell K, Birn RM, Brickman AM, Bulova P, Cheema A, Chen K, Christian BT, Clare I, Clark L, Cohen AD, Constantino JN, Doran EW, Fagan A, Feingold E, Foroud TM, Handen BL, Hartley SL, Head E, Henson R, Hom C, Honig L, Ikonomovic MD, Johnson SC, Jordan C, Kamboh MI, Keator D, Klunk WE, Kofler JK, Kreisl WC, Krinsky‐McHale SJ, Lai F, Lao P, Laymon C, Lee JH, Lott IT, Lupson V, Mapstone M, Mathis CA, Minhas DS, Nadkarni N, O'Bryant S, Pang D, Petersen M, Price JC, Pulsifer M, Reiman E, Rizvi B, Rosas HD, Schupf N, Silverman WP, Tudorascu DL, Tumuluru R, Tycko B, Varadarajan B, White DA, Yassa MA, Zaman S, Zhang F. Joint-label fusion brain atlases for dementia research in Down syndrome. Alzheimers Dement (Amst) 2022; 14:e12324. [PMID: 35634535 PMCID: PMC9131930 DOI: 10.1002/dad2.12324] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 01/11/2022] [Revised: 03/28/2022] [Accepted: 04/25/2022] [Indexed: 01/07/2023]
Abstract
Research suggests a link between Alzheimer's Disease in Down Syndrome (DS) and the overproduction of amyloid plaques. Using Positron Emission Tomography (PET) we can assess the in-vivo regional amyloid load using several available ligands. To measure amyloid distributions in specific brain regions, a brain atlas is used. A popular method of creating a brain atlas is to segment a participant's structural Magnetic Resonance Imaging (MRI) scan. Acquiring an MRI is often challenging in intellectually-imparied populations because of contraindications or data exclusion due to significant motion artifacts or incomplete sequences related to general discomfort. When an MRI cannot be acquired, it is typically replaced with a standardized brain atlas derived from neurotypical populations (i.e. healthy individuals without DS) which may be inappropriate for use in DS. In this project, we create a series of disease and diagnosis-specific (cognitively stable (CS-DS), mild cognitive impairment (MCI-DS), and dementia (DEM-DS)) probabilistic group atlases of participants with DS and evaluate their accuracy of quantifying regional amyloid load compared to the individually-based MRI segmentations. Further, we compare the diagnostic-specific atlases with a probabilistic atlas constructed from similar-aged cognitively-stable neurotypical participants. We hypothesized that regional PET signals will best match the individually-based MRI segmentations by using DS group atlases that aligns with a participant's disorder and disease status (e.g. DS and MCI-DS). Our results vary by brain region but generally show that using a disorder-specific atlas in DS better matches the individually-based MRI segmentations than using an atlas constructed from cognitively-stable neurotypical participants. We found no additional benefit of using diagnose-specific atlases matching disease status. All atlases are made publicly available for the research community. Highlight Down syndrome (DS) joint-label-fusion atlases provide accurate positron emission tomography (PET) amyloid measurements.A disorder-specific DS atlas is better than a neurotypical atlas for PET quantification.It is not necessary to use a disease-state-specific atlas for quantification in aged DS.Dorsal striatum results vary, possibly due to this region and dementia progression.
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Affiliation(s)
- Nazek Queder
- Department of Psychiatry and Human BehaviorUniversity of California IrvineIrvineCaliforniaUSA,Department of Neurobiology and Behavior and Center for the Neurobiology of Learning and MemoryUniversity of California IrvineIrvineCaliforniaUSA
| | - Michael J. Phelan
- Institute for Memory Impairments and Neurological DisordersUniversity of California IrvineIrvineCaliforniaUSA
| | - Lisa Taylor
- Department of Psychiatry and Human BehaviorUniversity of California IrvineIrvineCaliforniaUSA
| | - Nicholas Tustison
- Department of RadiologyUniversity of VirginiaCharlottesvilleVirginiaUSA
| | - Eric Doran
- Department of PediatricsUniversity of CaliforniaIrvine Medical CenterOrangeCaliforniaUSA
| | - Christy Hom
- Department of Psychiatry and Human BehaviorUniversity of California IrvineIrvineCaliforniaUSA
| | - Dana Nguyen
- Department of Psychiatry and Human BehaviorUniversity of California IrvineIrvineCaliforniaUSA
| | - Florence Lai
- Massachusetts General HospitalHarvard UniversityBostonMassachusettsUSA
| | - Margaret Pulsifer
- Massachusetts General HospitalHarvard UniversityBostonMassachusettsUSA
| | - Julie Price
- Massachusetts General HospitalHarvard UniversityBostonMassachusettsUSA
| | | | - Herminia D. Rosas
- Massachusetts General HospitalHarvard UniversityBostonMassachusettsUSA
| | - Sharon Krinsky‐McHale
- New York State Institute for Basic Research in Developmental DisabilitiesNew YorkNew YorkUSA
| | - Adam M. Brickman
- Department of NeurologyColumbia UniversityNew YorkNew YorkUSA,Taub Institute for Research on Alzheimer's Disease and the Aging BrainDepartment of NeurologyVagelos College of Physicians and SurgeonsColumbia UniversityNew YorkNew YorkUSA
| | - Michael A. Yassa
- Department of Psychiatry and Human BehaviorUniversity of California IrvineIrvineCaliforniaUSA,Department of Neurobiology and Behavior and Center for the Neurobiology of Learning and MemoryUniversity of California IrvineIrvineCaliforniaUSA,Department of NeurologyUniversity of California IrvineIrvineCaliforniaUSA
| | - Nicole Schupf
- Department of NeurologyColumbia UniversityNew YorkNew YorkUSA,Taub Institute for Research on Alzheimer's Disease and the Aging BrainDepartment of NeurologyVagelos College of Physicians and SurgeonsColumbia UniversityNew YorkNew YorkUSA
| | - Wayne Silverman
- Department of PediatricsUniversity of CaliforniaIrvine Medical CenterOrangeCaliforniaUSA
| | - Ira T. Lott
- Department of PediatricsUniversity of CaliforniaIrvine Medical CenterOrangeCaliforniaUSA
| | - Elizabeth Head
- Department of Pathology & Laboratory MedicineUniversity of California IrvineIrvineCaliforniaUSA
| | - Mark Mapstone
- Department of NeurologyUniversity of California IrvineIrvineCaliforniaUSA
| | - David B. Keator
- Department of Psychiatry and Human BehaviorUniversity of California IrvineIrvineCaliforniaUSA
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6
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Zhang H, Wilmot B, Bottomly D, Dao KHT, Stevens E, Eide CA, Khanna V, Rofelty A, Savage S, Reister Schultz A, Long N, White L, Carlos A, Henson R, Lin C, Searles R, Collins RH, DeAngelo DJ, Deininger MW, Dunn T, Hein T, Luskin MR, Medeiros BC, Oh ST, Pollyea DA, Steensma DP, Stone RM, Druker BJ, McWeeney SK, Maxson JE, Gotlib JR, Tyner JW. Genomic landscape of neutrophilic leukemias of ambiguous diagnosis. Blood 2019; 134:867-879. [PMID: 31366621 PMCID: PMC6742922 DOI: 10.1182/blood.2019000611] [Citation(s) in RCA: 51] [Impact Index Per Article: 10.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/14/2019] [Accepted: 06/27/2019] [Indexed: 12/12/2022] Open
Abstract
Chronic neutrophilic leukemia (CNL), atypical chronic myeloid leukemia (aCML), and myelodysplastic/myeloproliferative neoplasms, unclassifiable (MDS/MPN-U) are a group of rare and heterogeneous myeloid disorders. There is strong morphologic resemblance among these distinct diagnostic entities as well as a lack of specific molecular markers and limited understanding of disease pathogenesis, which has made diagnosis challenging in certain cases. The treatment has remained empirical, resulting in dismal outcomes. We, therefore, performed whole-exome and RNA sequencing of these rare hematologic malignancies and present the most complete survey of the genomic landscape of these diseases to date. We observed a diversity of combinatorial mutational patterns that generally do not cluster within any one diagnosis. Gene expression analysis reveals enrichment, but not cosegregation, of clinical and genetic disease features with transcriptional clusters. In conclusion, these groups of diseases represent a continuum of related diseases rather than discrete diagnostic entities.
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Affiliation(s)
- Haijiao Zhang
- Department of Cell, Developmental and Cancer Biology
- Division of Hematology and Medical Oncology, and
| | - Beth Wilmot
- Division of Bioinformatics and Computational Biology, Department of Medical Informatics and Clinical Epidemiology, Knight Cancer Institute, Oregon Health & Science University, Portland, OR
| | - Daniel Bottomly
- Division of Bioinformatics and Computational Biology, Department of Medical Informatics and Clinical Epidemiology, Knight Cancer Institute, Oregon Health & Science University, Portland, OR
| | | | - Emily Stevens
- Fred Hutchinson Cancer Research Institute, Washington University School of Medicine, Seattle, WA
| | - Christopher A Eide
- Division of Hematology and Medical Oncology, and
- Howard Hughes Medical Institute, Chevy Chase, MD
| | - Vishesh Khanna
- Division of Hematology and Medical Oncology, and
- Howard Hughes Medical Institute, Chevy Chase, MD
| | - Angela Rofelty
- Department of Cell, Developmental and Cancer Biology
- Division of Hematology and Medical Oncology, and
| | - Samantha Savage
- Department of Cell, Developmental and Cancer Biology
- Division of Hematology and Medical Oncology, and
| | - Anna Reister Schultz
- Department of Cell, Developmental and Cancer Biology
- Division of Hematology and Medical Oncology, and
| | - Nicola Long
- Department of Cell, Developmental and Cancer Biology
- Division of Hematology and Medical Oncology, and
| | - Libbey White
- Division of Bioinformatics and Computational Biology, Department of Medical Informatics and Clinical Epidemiology, Knight Cancer Institute, Oregon Health & Science University, Portland, OR
| | - Amy Carlos
- Integrated Genomics Laboratories, Oregon Health & Science University, Portland, OR
| | - Rachel Henson
- Integrated Genomics Laboratories, Oregon Health & Science University, Portland, OR
| | - Chenwei Lin
- Integrated Genomics Laboratories, Oregon Health & Science University, Portland, OR
| | - Robert Searles
- Integrated Genomics Laboratories, Oregon Health & Science University, Portland, OR
| | - Robert H Collins
- Hematology/Oncology, Department of Internal Medicine, University of Texas Southwestern Medical Center, Dallas, TX
| | - Daniel J DeAngelo
- Department of Medical Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA
| | | | - Tamara Dunn
- Stanford Cancer Institute, Stanford University School of Medicine, Stanford, CA
| | - Than Hein
- Huntsman Cancer Institute, University of Utah, Salt Lake City, UT
| | - Marlise R Luskin
- Department of Medical Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA
| | - Bruno C Medeiros
- Stanford Cancer Institute, Stanford University School of Medicine, Stanford, CA
| | - Stephen T Oh
- Hematology Division, Department of Medicine, Washington University School of Medicine, Washington University in St. Louis, St. Louis, MO; and
| | - Daniel A Pollyea
- Division of Hematology, Oncology, and Bone Marrow Transplantation, University of Colorado School of Medicine, Aurora, CO
| | - David P Steensma
- Department of Medical Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA
| | - Richard M Stone
- Department of Medical Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA
| | - Brian J Druker
- Division of Hematology and Medical Oncology, and
- Howard Hughes Medical Institute, Chevy Chase, MD
| | - Shannon K McWeeney
- Division of Bioinformatics and Computational Biology, Department of Medical Informatics and Clinical Epidemiology, Knight Cancer Institute, Oregon Health & Science University, Portland, OR
| | | | - Jason R Gotlib
- Stanford Cancer Institute, Stanford University School of Medicine, Stanford, CA
| | - Jeffrey W Tyner
- Department of Cell, Developmental and Cancer Biology
- Division of Hematology and Medical Oncology, and
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7
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Zhang H, Savage S, Schultz AR, Bottomly D, White L, Segerdell E, Wilmot B, McWeeney SK, Eide CA, Nechiporuk T, Carlos A, Henson R, Lin C, Searles R, Ho H, Lam YL, Sweat R, Follit C, Jain V, Lind E, Borthakur G, Garcia-Manero G, Ravandi F, Kantarjian HM, Cortes J, Collins R, Buelow DR, Baker SD, Druker BJ, Tyner JW. Clinical resistance to crenolanib in acute myeloid leukemia due to diverse molecular mechanisms. Nat Commun 2019; 10:244. [PMID: 30651561 PMCID: PMC6335421 DOI: 10.1038/s41467-018-08263-x] [Citation(s) in RCA: 95] [Impact Index Per Article: 19.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/01/2018] [Accepted: 12/21/2018] [Indexed: 12/19/2022] Open
Abstract
FLT3 mutations are prevalent in AML patients and confer poor prognosis. Crenolanib, a potent type I pan-FLT3 inhibitor, is effective against both internal tandem duplications and resistance-conferring tyrosine kinase domain mutations. While crenolanib monotherapy has demonstrated clinical benefit in heavily pretreated relapsed/refractory AML patients, responses are transient and relapse eventually occurs. Here, to investigate the mechanisms of crenolanib resistance, we perform whole exome sequencing of AML patient samples before and after crenolanib treatment. Unlike other FLT3 inhibitors, crenolanib does not induce FLT3 secondary mutations, and mutations of the FLT3 gatekeeper residue are infrequent. Instead, mutations of NRAS and IDH2 arise, mostly as FLT3-independent subclones, while TET2 and IDH1 predominantly co-occur with FLT3-mutant clones and are enriched in crenolanib poor-responders. The remaining patients exhibit post-crenolanib expansion of mutations associated with epigenetic regulators, transcription factors, and cohesion factors, suggesting diverse genetic/epigenetic mechanisms of crenolanib resistance. Drug combinations in experimental models restore crenolanib sensitivity. FLT3 is commonly mutated in acute myeloid leukaemia and treatment with FLT3 inhibitors often ends with relapse. Here, the authors perform exome sequencing of samples from patients treated with the FLT3 inhibitor, crenolanib, to show that resistance occurs due to diverse molecular mechanisms, not primarily due to secondary FLT3 mutations.
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Affiliation(s)
- Haijiao Zhang
- Department of Cell, Developmental & Cancer Biology, Oregon Health & Science University Knight Cancer Institute, Portland, 97239, OR, USA.,Division of Hematology and Medical Oncology, Oregon Health & Science University Knight Cancer Institute, Portland, 97239, OR, USA
| | - Samantha Savage
- Department of Cell, Developmental & Cancer Biology, Oregon Health & Science University Knight Cancer Institute, Portland, 97239, OR, USA.,Division of Hematology and Medical Oncology, Oregon Health & Science University Knight Cancer Institute, Portland, 97239, OR, USA
| | - Anna Reister Schultz
- Department of Cell, Developmental & Cancer Biology, Oregon Health & Science University Knight Cancer Institute, Portland, 97239, OR, USA.,Division of Hematology and Medical Oncology, Oregon Health & Science University Knight Cancer Institute, Portland, 97239, OR, USA
| | - Daniel Bottomly
- Division of Bioinformatics and Computational Biology, Department of Medical Informatics and Clinical Epidemiology, Oregon Health & Science University Knight Cancer Institute, Portland, 97239, OR, USA
| | - Libbey White
- Division of Bioinformatics and Computational Biology, Department of Medical Informatics and Clinical Epidemiology, Oregon Health & Science University Knight Cancer Institute, Portland, 97239, OR, USA
| | - Erik Segerdell
- Division of Bioinformatics and Computational Biology, Department of Medical Informatics and Clinical Epidemiology, Oregon Health & Science University Knight Cancer Institute, Portland, 97239, OR, USA
| | - Beth Wilmot
- Division of Bioinformatics and Computational Biology, Department of Medical Informatics and Clinical Epidemiology, Oregon Health & Science University Knight Cancer Institute, Portland, 97239, OR, USA
| | - Shannon K McWeeney
- Division of Bioinformatics and Computational Biology, Department of Medical Informatics and Clinical Epidemiology, Oregon Health & Science University Knight Cancer Institute, Portland, 97239, OR, USA
| | - Christopher A Eide
- Division of Hematology and Medical Oncology, Oregon Health & Science University Knight Cancer Institute, Portland, 97239, OR, USA.,Howard Hughes Medical Institute, Portland, 97239, OR, USA
| | - Tamilla Nechiporuk
- Department of Cell, Developmental & Cancer Biology, Oregon Health & Science University Knight Cancer Institute, Portland, 97239, OR, USA.,Division of Hematology and Medical Oncology, Oregon Health & Science University Knight Cancer Institute, Portland, 97239, OR, USA
| | - Amy Carlos
- Integrated Genomics, Knight Cancer Institute, Oregon Health & Science University Knight Cancer Institute, Portland, 97239, OR, USA
| | - Rachel Henson
- Integrated Genomics, Knight Cancer Institute, Oregon Health & Science University Knight Cancer Institute, Portland, 97239, OR, USA
| | - Chenwei Lin
- Integrated Genomics, Knight Cancer Institute, Oregon Health & Science University Knight Cancer Institute, Portland, 97239, OR, USA
| | - Robert Searles
- Integrated Genomics, Knight Cancer Institute, Oregon Health & Science University Knight Cancer Institute, Portland, 97239, OR, USA
| | - Hoang Ho
- AROG Pharmaceuticals, Dallas, 75240, TX, USA
| | | | | | | | - Vinay Jain
- AROG Pharmaceuticals, Dallas, 75240, TX, USA
| | - Evan Lind
- Molecular Microbiology & Immunology, Oregon Health & Science University Knight Cancer Institute, Portland, 97239, OR, USA
| | - Gautam Borthakur
- The University of Texas MD Anderson Cancer Center, Houston, 77030, TX, USA
| | | | - Farhad Ravandi
- The University of Texas MD Anderson Cancer Center, Houston, 77030, TX, USA
| | - Hagop M Kantarjian
- The University of Texas MD Anderson Cancer Center, Houston, 77030, TX, USA
| | - Jorge Cortes
- The University of Texas MD Anderson Cancer Center, Houston, 77030, TX, USA
| | - Robert Collins
- University of Texas Southwestern Medical Center, Dallas, 75390, TX, USA
| | - Daelynn R Buelow
- The Ohio State University College of Pharmacy and Comprehensive Cancer Center, Columbus, 43210, OH, USA
| | - Sharyn D Baker
- The Ohio State University College of Pharmacy and Comprehensive Cancer Center, Columbus, 43210, OH, USA
| | - Brian J Druker
- Division of Hematology and Medical Oncology, Oregon Health & Science University Knight Cancer Institute, Portland, 97239, OR, USA.,Howard Hughes Medical Institute, Portland, 97239, OR, USA
| | - Jeffrey W Tyner
- Department of Cell, Developmental & Cancer Biology, Oregon Health & Science University Knight Cancer Institute, Portland, 97239, OR, USA. .,Division of Hematology and Medical Oncology, Oregon Health & Science University Knight Cancer Institute, Portland, 97239, OR, USA.
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8
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Tyner JW, Tognon CE, Bottomly D, Wilmot B, Kurtz SE, Savage SL, Long N, Schultz AR, Traer E, Abel M, Agarwal A, Blucher A, Borate U, Bryant J, Burke R, Carlos A, Carpenter R, Carroll J, Chang BH, Coblentz C, d'Almeida A, Cook R, Danilov A, Dao KHT, Degnin M, Devine D, Dibb J, Edwards DK, Eide CA, English I, Glover J, Henson R, Ho H, Jemal A, Johnson K, Johnson R, Junio B, Kaempf A, Leonard J, Lin C, Liu SQ, Lo P, Loriaux MM, Luty S, Macey T, MacManiman J, Martinez J, Mori M, Nelson D, Nichols C, Peters J, Ramsdill J, Rofelty A, Schuff R, Searles R, Segerdell E, Smith RL, Spurgeon SE, Sweeney T, Thapa A, Visser C, Wagner J, Watanabe-Smith K, Werth K, Wolf J, White L, Yates A, Zhang H, Cogle CR, Collins RH, Connolly DC, Deininger MW, Drusbosky L, Hourigan CS, Jordan CT, Kropf P, Lin TL, Martinez ME, Medeiros BC, Pallapati RR, Pollyea DA, Swords RT, Watts JM, Weir SJ, Wiest DL, Winters RM, McWeeney SK, Druker BJ. Functional genomic landscape of acute myeloid leukaemia. Nature 2018; 562:526-531. [PMID: 30333627 PMCID: PMC6280667 DOI: 10.1038/s41586-018-0623-z] [Citation(s) in RCA: 731] [Impact Index Per Article: 121.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/04/2018] [Accepted: 08/14/2018] [Indexed: 01/08/2023]
Abstract
The implementation of targeted therapies for acute myeloid leukaemia (AML) has been challenging because of the complex mutational patterns within and across patients as well as a dearth of pharmacologic agents for most mutational events. Here we report initial findings from the Beat AML programme on a cohort of 672 tumour specimens collected from 562 patients. We assessed these specimens using whole-exome sequencing, RNA sequencing and analyses of ex vivo drug sensitivity. Our data reveal mutational events that have not previously been detected in AML. We show that the response to drugs is associated with mutational status, including instances of drug sensitivity that are specific to combinatorial mutational events. Integration with RNA sequencing also revealed gene expression signatures, which predict a role for specific gene networks in the drug response. Collectively, we have generated a dataset-accessible through the Beat AML data viewer (Vizome)-that can be leveraged to address clinical, genomic, transcriptomic and functional analyses of the biology of AML.
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Affiliation(s)
- Jeffrey W Tyner
- Department of Cell, Developmental & Cancer Biology, Oregon Health & Science University, Portland, OR, USA
- Knight Cancer Institute, Oregon Health & Science University, Portland, OR, USA
| | - Cristina E Tognon
- Knight Cancer Institute, Oregon Health & Science University, Portland, OR, USA
- Division of Hematology & Medical Oncology, Department of Medicine, Oregon Health & Science University, Portland, OR, USA
- Howard Hughes Medical Institute, Portland, OR, USA
| | - Daniel Bottomly
- Knight Cancer Institute, Oregon Health & Science University, Portland, OR, USA
- Division of Bioinformatics and Computational Biology, Department of Medical Informatics and Clinical Epidemiology, Oregon Health & Science University, Portland, OR, USA
| | - Beth Wilmot
- Knight Cancer Institute, Oregon Health & Science University, Portland, OR, USA
- Division of Bioinformatics and Computational Biology, Department of Medical Informatics and Clinical Epidemiology, Oregon Health & Science University, Portland, OR, USA
- Oregon Clinical & Translational Research Institute, Oregon Health & Science University, Portland, OR, USA
| | - Stephen E Kurtz
- Knight Cancer Institute, Oregon Health & Science University, Portland, OR, USA
- Division of Hematology & Medical Oncology, Department of Medicine, Oregon Health & Science University, Portland, OR, USA
| | - Samantha L Savage
- Department of Cell, Developmental & Cancer Biology, Oregon Health & Science University, Portland, OR, USA
- Knight Cancer Institute, Oregon Health & Science University, Portland, OR, USA
| | - Nicola Long
- Knight Cancer Institute, Oregon Health & Science University, Portland, OR, USA
- Division of Hematology & Medical Oncology, Department of Medicine, Oregon Health & Science University, Portland, OR, USA
| | - Anna Reister Schultz
- Department of Cell, Developmental & Cancer Biology, Oregon Health & Science University, Portland, OR, USA
- Knight Cancer Institute, Oregon Health & Science University, Portland, OR, USA
| | - Elie Traer
- Knight Cancer Institute, Oregon Health & Science University, Portland, OR, USA
- Division of Hematology & Medical Oncology, Department of Medicine, Oregon Health & Science University, Portland, OR, USA
| | - Melissa Abel
- Department of Cell, Developmental & Cancer Biology, Oregon Health & Science University, Portland, OR, USA
- Knight Cancer Institute, Oregon Health & Science University, Portland, OR, USA
| | - Anupriya Agarwal
- Knight Cancer Institute, Oregon Health & Science University, Portland, OR, USA
- Department of Molecular & Medical Genetics, Oregon Health & Science University, Portland, OR, USA
| | - Aurora Blucher
- Knight Cancer Institute, Oregon Health & Science University, Portland, OR, USA
- Division of Bioinformatics and Computational Biology, Department of Medical Informatics and Clinical Epidemiology, Oregon Health & Science University, Portland, OR, USA
| | - Uma Borate
- Knight Cancer Institute, Oregon Health & Science University, Portland, OR, USA
- Division of Hematology & Medical Oncology, Department of Medicine, Oregon Health & Science University, Portland, OR, USA
| | - Jade Bryant
- Department of Cell, Developmental & Cancer Biology, Oregon Health & Science University, Portland, OR, USA
- Knight Cancer Institute, Oregon Health & Science University, Portland, OR, USA
| | - Russell Burke
- Knight Cancer Institute, Oregon Health & Science University, Portland, OR, USA
- Division of Hematology & Medical Oncology, Department of Medicine, Oregon Health & Science University, Portland, OR, USA
| | - Amy Carlos
- Knight Cancer Institute, Oregon Health & Science University, Portland, OR, USA
- Integrated Genomics Laboratories, Oregon Health & Science University, Portland, OR, USA
| | - Richie Carpenter
- Knight Cancer Institute, Oregon Health & Science University, Portland, OR, USA
- Division of Hematology & Medical Oncology, Department of Medicine, Oregon Health & Science University, Portland, OR, USA
| | - Joseph Carroll
- Knight Cancer Institute, Oregon Health & Science University, Portland, OR, USA
- Technology Transfer & Business Development, Oregon Health & Science University, Portland, OR, USA
| | - Bill H Chang
- Knight Cancer Institute, Oregon Health & Science University, Portland, OR, USA
- Division of Hematology and Oncology, Department of Pediatrics, Oregon Health & Science University, Portland, OR, USA
| | - Cody Coblentz
- Knight Cancer Institute, Oregon Health & Science University, Portland, OR, USA
- Division of Hematology & Medical Oncology, Department of Medicine, Oregon Health & Science University, Portland, OR, USA
| | - Amanda d'Almeida
- Department of Cell, Developmental & Cancer Biology, Oregon Health & Science University, Portland, OR, USA
- Knight Cancer Institute, Oregon Health & Science University, Portland, OR, USA
| | - Rachel Cook
- Knight Cancer Institute, Oregon Health & Science University, Portland, OR, USA
- Division of Hematology & Medical Oncology, Department of Medicine, Oregon Health & Science University, Portland, OR, USA
| | - Alexey Danilov
- Knight Cancer Institute, Oregon Health & Science University, Portland, OR, USA
- Division of Hematology & Medical Oncology, Department of Medicine, Oregon Health & Science University, Portland, OR, USA
| | - Kim-Hien T Dao
- Knight Cancer Institute, Oregon Health & Science University, Portland, OR, USA
- Division of Hematology & Medical Oncology, Department of Medicine, Oregon Health & Science University, Portland, OR, USA
| | - Michie Degnin
- Knight Cancer Institute, Oregon Health & Science University, Portland, OR, USA
- Division of Hematology & Medical Oncology, Department of Medicine, Oregon Health & Science University, Portland, OR, USA
| | - Deirdre Devine
- Knight Cancer Institute, Oregon Health & Science University, Portland, OR, USA
- Division of Hematology & Medical Oncology, Department of Medicine, Oregon Health & Science University, Portland, OR, USA
| | - James Dibb
- Knight Cancer Institute, Oregon Health & Science University, Portland, OR, USA
- Division of Hematology & Medical Oncology, Department of Medicine, Oregon Health & Science University, Portland, OR, USA
| | - David K Edwards
- Department of Cell, Developmental & Cancer Biology, Oregon Health & Science University, Portland, OR, USA
- Knight Cancer Institute, Oregon Health & Science University, Portland, OR, USA
| | - Christopher A Eide
- Knight Cancer Institute, Oregon Health & Science University, Portland, OR, USA
- Division of Hematology & Medical Oncology, Department of Medicine, Oregon Health & Science University, Portland, OR, USA
- Howard Hughes Medical Institute, Portland, OR, USA
| | - Isabel English
- Knight Cancer Institute, Oregon Health & Science University, Portland, OR, USA
- Division of Hematology & Medical Oncology, Department of Medicine, Oregon Health & Science University, Portland, OR, USA
| | - Jason Glover
- Knight Cancer Institute, Oregon Health & Science University, Portland, OR, USA
- Division of Hematology and Oncology, Department of Pediatrics, Oregon Health & Science University, Portland, OR, USA
| | - Rachel Henson
- Knight Cancer Institute, Oregon Health & Science University, Portland, OR, USA
- Integrated Genomics Laboratories, Oregon Health & Science University, Portland, OR, USA
| | - Hibery Ho
- Knight Cancer Institute, Oregon Health & Science University, Portland, OR, USA
- Division of Hematology & Medical Oncology, Department of Medicine, Oregon Health & Science University, Portland, OR, USA
| | - Abdusebur Jemal
- Knight Cancer Institute, Oregon Health & Science University, Portland, OR, USA
- Division of Hematology and Oncology, Department of Pediatrics, Oregon Health & Science University, Portland, OR, USA
| | - Kara Johnson
- Knight Cancer Institute, Oregon Health & Science University, Portland, OR, USA
- Division of Hematology & Medical Oncology, Department of Medicine, Oregon Health & Science University, Portland, OR, USA
| | - Ryan Johnson
- Knight Cancer Institute, Oregon Health & Science University, Portland, OR, USA
- Division of Hematology & Medical Oncology, Department of Medicine, Oregon Health & Science University, Portland, OR, USA
| | - Brian Junio
- Knight Cancer Institute, Oregon Health & Science University, Portland, OR, USA
- Division of Hematology & Medical Oncology, Department of Medicine, Oregon Health & Science University, Portland, OR, USA
| | - Andy Kaempf
- Knight Cancer Institute, Oregon Health & Science University, Portland, OR, USA
- Biostatistics Shared Resource, Oregon Health & Science University, Portland, OR, USA
| | - Jessica Leonard
- Knight Cancer Institute, Oregon Health & Science University, Portland, OR, USA
- Division of Hematology & Medical Oncology, Department of Medicine, Oregon Health & Science University, Portland, OR, USA
| | - Chenwei Lin
- Knight Cancer Institute, Oregon Health & Science University, Portland, OR, USA
- Integrated Genomics Laboratories, Oregon Health & Science University, Portland, OR, USA
| | - Selina Qiuying Liu
- Knight Cancer Institute, Oregon Health & Science University, Portland, OR, USA
- Division of Hematology & Medical Oncology, Department of Medicine, Oregon Health & Science University, Portland, OR, USA
| | - Pierrette Lo
- Knight Cancer Institute, Oregon Health & Science University, Portland, OR, USA
- Division of Hematology & Medical Oncology, Department of Medicine, Oregon Health & Science University, Portland, OR, USA
| | - Marc M Loriaux
- Knight Cancer Institute, Oregon Health & Science University, Portland, OR, USA
- Dapartment of Pathology, Oregon Health & Science University, Portland, OR, USA
| | - Samuel Luty
- Knight Cancer Institute, Oregon Health & Science University, Portland, OR, USA
- Division of Hematology & Medical Oncology, Department of Medicine, Oregon Health & Science University, Portland, OR, USA
| | - Tara Macey
- Knight Cancer Institute, Oregon Health & Science University, Portland, OR, USA
- Division of Hematology & Medical Oncology, Department of Medicine, Oregon Health & Science University, Portland, OR, USA
| | - Jason MacManiman
- Department of Cell, Developmental & Cancer Biology, Oregon Health & Science University, Portland, OR, USA
- Knight Cancer Institute, Oregon Health & Science University, Portland, OR, USA
| | - Jacqueline Martinez
- Department of Cell, Developmental & Cancer Biology, Oregon Health & Science University, Portland, OR, USA
- Knight Cancer Institute, Oregon Health & Science University, Portland, OR, USA
| | - Motomi Mori
- Knight Cancer Institute, Oregon Health & Science University, Portland, OR, USA
- Biostatistics Shared Resource, Oregon Health & Science University, Portland, OR, USA
- Oregon Health & Science University-Portland State University School of Public Health, Portland, OR, USA
| | - Dylan Nelson
- High-Throughput Screening Services Laboratory, Oregon State University, Corvalis, OR, USA
| | - Ceilidh Nichols
- Knight Cancer Institute, Oregon Health & Science University, Portland, OR, USA
- Division of Hematology & Medical Oncology, Department of Medicine, Oregon Health & Science University, Portland, OR, USA
| | - Jill Peters
- Knight Cancer Institute, Oregon Health & Science University, Portland, OR, USA
- Division of Hematology & Medical Oncology, Department of Medicine, Oregon Health & Science University, Portland, OR, USA
| | - Justin Ramsdill
- Division of Bioinformatics and Computational Biology, Department of Medical Informatics and Clinical Epidemiology, Oregon Health & Science University, Portland, OR, USA
- Oregon Clinical & Translational Research Institute, Oregon Health & Science University, Portland, OR, USA
| | - Angela Rofelty
- Department of Cell, Developmental & Cancer Biology, Oregon Health & Science University, Portland, OR, USA
- Knight Cancer Institute, Oregon Health & Science University, Portland, OR, USA
| | - Robert Schuff
- Division of Bioinformatics and Computational Biology, Department of Medical Informatics and Clinical Epidemiology, Oregon Health & Science University, Portland, OR, USA
- Oregon Clinical & Translational Research Institute, Oregon Health & Science University, Portland, OR, USA
| | - Robert Searles
- Knight Cancer Institute, Oregon Health & Science University, Portland, OR, USA
- Integrated Genomics Laboratories, Oregon Health & Science University, Portland, OR, USA
| | - Erik Segerdell
- Knight Cancer Institute, Oregon Health & Science University, Portland, OR, USA
- Division of Bioinformatics and Computational Biology, Department of Medical Informatics and Clinical Epidemiology, Oregon Health & Science University, Portland, OR, USA
| | - Rebecca L Smith
- Knight Cancer Institute, Oregon Health & Science University, Portland, OR, USA
- Division of Hematology & Medical Oncology, Department of Medicine, Oregon Health & Science University, Portland, OR, USA
| | - Stephen E Spurgeon
- Knight Cancer Institute, Oregon Health & Science University, Portland, OR, USA
- Division of Hematology & Medical Oncology, Department of Medicine, Oregon Health & Science University, Portland, OR, USA
| | - Tyler Sweeney
- Knight Cancer Institute, Oregon Health & Science University, Portland, OR, USA
- Division of Hematology & Medical Oncology, Department of Medicine, Oregon Health & Science University, Portland, OR, USA
| | - Aashis Thapa
- Knight Cancer Institute, Oregon Health & Science University, Portland, OR, USA
- Division of Hematology & Medical Oncology, Department of Medicine, Oregon Health & Science University, Portland, OR, USA
| | - Corinne Visser
- Knight Cancer Institute, Oregon Health & Science University, Portland, OR, USA
- Division of Hematology & Medical Oncology, Department of Medicine, Oregon Health & Science University, Portland, OR, USA
| | - Jake Wagner
- Knight Cancer Institute, Oregon Health & Science University, Portland, OR, USA
- Division of Hematology & Medical Oncology, Department of Medicine, Oregon Health & Science University, Portland, OR, USA
| | - Kevin Watanabe-Smith
- Knight Cancer Institute, Oregon Health & Science University, Portland, OR, USA
- Division of Hematology & Medical Oncology, Department of Medicine, Oregon Health & Science University, Portland, OR, USA
| | - Kristen Werth
- Knight Cancer Institute, Oregon Health & Science University, Portland, OR, USA
- Division of Hematology & Medical Oncology, Department of Medicine, Oregon Health & Science University, Portland, OR, USA
| | - Joelle Wolf
- Knight Cancer Institute, Oregon Health & Science University, Portland, OR, USA
- Division of Hematology and Oncology, Department of Pediatrics, Oregon Health & Science University, Portland, OR, USA
| | - Libbey White
- Knight Cancer Institute, Oregon Health & Science University, Portland, OR, USA
- Division of Bioinformatics and Computational Biology, Department of Medical Informatics and Clinical Epidemiology, Oregon Health & Science University, Portland, OR, USA
| | - Amy Yates
- Division of Bioinformatics and Computational Biology, Department of Medical Informatics and Clinical Epidemiology, Oregon Health & Science University, Portland, OR, USA
- Oregon Clinical & Translational Research Institute, Oregon Health & Science University, Portland, OR, USA
| | - Haijiao Zhang
- Department of Cell, Developmental & Cancer Biology, Oregon Health & Science University, Portland, OR, USA
- Knight Cancer Institute, Oregon Health & Science University, Portland, OR, USA
| | - Christopher R Cogle
- Department of Medicine, Division of Hematology and Oncology, University of Florida, Gainesville, FL, USA
| | - Robert H Collins
- Department of Internal Medicine/Hematology Oncology, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - Denise C Connolly
- Molecular Therapeutics Program, Fox Chase Cancer Center, Philadelphia, PA, USA
- Fox Chase Cancer Center Biosample Repository Facility, Philadelphia, PA, USA
| | - Michael W Deininger
- Division of Hematology & Hematologic Malignancies, Department of Internal Medicine, University of Utah, Salt Lake City, UT, USA
| | - Leylah Drusbosky
- Department of Medicine, Division of Hematology and Oncology, University of Florida, Gainesville, FL, USA
| | - Christopher S Hourigan
- National Heart, Lung and Blood Institute, National Institutes of Health, Bethesda, MD, USA
| | - Craig T Jordan
- Division of Hematology, University of Colorado, Denver, CO, USA
| | - Patricia Kropf
- Bone Marrow Transplant Program, Fox Chase Cancer Center, Philadelphia, PA, USA
| | - Tara L Lin
- Division of Hematologic Malignancies & Cellular Therapeutics, University of Kansas, Kansas City, KS, USA
| | - Micaela E Martinez
- Clinical Research Services, University of Miami Sylvester Comprehensive Cancer Center, Miami, FL, USA
| | - Bruno C Medeiros
- Department of Medicine-Hematology, Stanford University, Stanford, CA, USA
| | - Rachel R Pallapati
- Clinical Research Services, University of Miami Sylvester Comprehensive Cancer Center, Miami, FL, USA
| | | | - Ronan T Swords
- Department of Hematology, University of Miami Sylvester Comprehensive Cancer Center, Miami, FL, USA
| | - Justin M Watts
- Department of Hematology, University of Miami Sylvester Comprehensive Cancer Center, Miami, FL, USA
| | - Scott J Weir
- Department of Toxicology, Pharmacology and Therapeutics, University of Kansas Medical Center, Kansas City, KS, USA
- Department of Medicine, Division of Medical Oncology, University of Kansas Medical Center, Kansas City, KS, USA
| | - David L Wiest
- Blood Cell Development and Function Program, Fox Chase Cancer Center, Philadelphia, PA, USA
| | - Ryan M Winters
- Fox Chase Cancer Center Biosample Repository Facility, Philadelphia, PA, USA
| | - Shannon K McWeeney
- Knight Cancer Institute, Oregon Health & Science University, Portland, OR, USA.
- Division of Bioinformatics and Computational Biology, Department of Medical Informatics and Clinical Epidemiology, Oregon Health & Science University, Portland, OR, USA.
- Oregon Clinical & Translational Research Institute, Oregon Health & Science University, Portland, OR, USA.
| | - Brian J Druker
- Knight Cancer Institute, Oregon Health & Science University, Portland, OR, USA.
- Division of Hematology & Medical Oncology, Department of Medicine, Oregon Health & Science University, Portland, OR, USA.
- Howard Hughes Medical Institute, Portland, OR, USA.
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9
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Walhovd KB, Fjell AM, Westerhausen R, Nyberg L, Ebmeier KP, Lindenberger U, Bartrés-Faz D, Baaré WFC, Siebner HR, Henson R, Drevon CA, Knudsen GP, Budin-Ljøsne I, Penninx BWJH, Ghisletta P, Rogeberg O, Tyler L, Bertram L. Healthy minds from 0-100 years: Optimising the use of European brain imaging cohorts ("Lifebrain"). Eur Psychiatry 2017; 47:76-87. [PMID: 29127911 DOI: 10.1016/j.eurpsy.2017.10.005] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/27/2017] [Revised: 10/04/2017] [Accepted: 10/05/2017] [Indexed: 11/17/2022] Open
Abstract
The main objective of "Lifebrain" is to identify the determinants of brain, cognitive and mental (BCM) health at different stages of life. By integrating, harmonising and enriching major European neuroimaging studies across the life span, we will merge fine-grained BCM health measures of more than 5,000 individuals. Longitudinal brain imaging, genetic and health data are available for a major part, as well as cognitive and mental health measures for the broader cohorts, exceeding 27,000 examinations in total. By linking these data to other databases and biobanks, including birth registries, national and regional archives, and by enriching them with a new online data collection and novel measures, we will address the risk factors and protective factors of BCM health. We will identify pathways through which risk and protective factors work and their moderators. Exploiting existing European infrastructures and initiatives, we hope to make major conceptual, methodological and analytical contributions towards large integrative cohorts and their efficient exploitation. We will thus provide novel information on BCM health maintenance, as well as the onset and course of BCM disorders. This will lay a foundation for earlier diagnosis of brain disorders, aberrant development and decline of BCM health, and translate into future preventive and therapeutic strategies. Aiming to improve clinical practice and public health we will work with stakeholders and health authorities, and thus provide the evidence base for prevention and intervention.
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Affiliation(s)
- K B Walhovd
- Department of Psychology, University of Oslo Centre for Lifespan Changes in Brain and Cognition (UiO), Harald Schelderups Hus, Forskningsveien 3A, N-0373 Oslo, Norway.
| | - A M Fjell
- Department of Psychology, University of Oslo Centre for Lifespan Changes in Brain and Cognition (UiO), Harald Schelderups Hus, Forskningsveien 3A, N-0373 Oslo, Norway
| | - R Westerhausen
- Department of Psychology, University of Oslo Centre for Lifespan Changes in Brain and Cognition (UiO), Harald Schelderups Hus, Forskningsveien 3A, N-0373 Oslo, Norway
| | - L Nyberg
- Centre for Functional Brain Imaging (Umeå), Umeå Universitet, SE-90187 Umeå, Sweden.
| | - K P Ebmeier
- Department of Psychiatry (UOXF), University of Oxford Wellcome Centre for Integrative Neuroimaging, Warneford Hospital, University of Oxford, OX37JX Oxford, UK.
| | - U Lindenberger
- Centre for Lifespan Psychology (MPIB), Max-Planck Institute for Human Development, Lentzeallee 94, D-14195 Berlin, Germany.
| | - D Bartrés-Faz
- Facultat de Medicina, Campus Clínic, C/. Casanova, University of Barcelona Brain Stimulation Lab (UB), 143, Ala Nord, 5a planta, S-08036 Barcelona, Spain.
| | - W F C Baaré
- Region Hovedstaden (RegionH), Danish Research Centre for Magnetic Resonance, Centre for Functional and Diagnostic Imaging and Research, Copenhagen University Hospital Hvidovre, Section 714, Kettegard Allé 30, DK-2650 Hvidovre, Denmark.
| | - H R Siebner
- Region Hovedstaden (RegionH), Danish Research Centre for Magnetic Resonance, Centre for Functional and Diagnostic Imaging and Research, Copenhagen University Hospital Hvidovre, Section 714, Kettegard Allé 30, DK-2650 Hvidovre, Denmark
| | - R Henson
- Medical Research Council Cognition and Brain Science Unit (MRC), University of Cambridge, 15, Chaucer Road, CB2 7EF Cambridge, UK.
| | - C A Drevon
- Vitas AS (Analytical Services), Gaustadalléen 21, N-0349 Oslo, Norway.
| | - G P Knudsen
- Norwegian Institute of Public Health Oslo (NIPH), PO Box 4404 Nydalen, N-0403 Oslo, Norway.
| | - I Budin-Ljøsne
- Norwegian Institute of Public Health Oslo (NIPH), PO Box 4404 Nydalen, N-0403 Oslo, Norway
| | - B W J H Penninx
- VU University Medical Centre (VUmc), PO Box 7057, NL-1007 Amsterdam, MB, USA.
| | - P Ghisletta
- Research Group: Methodology and Data Analysis, Faculty of Psychology and Educational Sciences, University of Geneva (UNIGE), Sandrine Amstutz, Uni Mail, 4(e) étage, boulevard du Pont-d'Arve 40, 1205 Geneva, Switzerland; Swiss Distance Learning University, Überlandstrasse 12, Postfach 689 CH-3900 Brig, Switzerland.
| | - O Rogeberg
- Ragnar Frisch Centre for Economic Research (Frisch), Gaustadalleen 21, N-0349 Oslo, Norway.
| | - L Tyler
- University of Cambridge Department of Psychology (UCAM), Downing Street, CB2 3EB Cambridge, UK.
| | - L Bertram
- University of Lübeck Interdisciplinary Platform for Genome Analytics (LIGA-UzL), University of Lübeck, Maria-Goeppert-Str. 1 (MFC1), 23562 D-Lübeck, Germany.
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Seibert E, Zhu F, Kuhlmann MK, Henson R, Oribello AM, Girndt M, Kotanko P, Levin NW. Slope analysis of blood volume and calf bioimpedance monitoring in hemodialysis patients. Nephrol Dial Transplant 2012; 27:4430-6. [DOI: 10.1093/ndt/gfr734] [Citation(s) in RCA: 9] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
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11
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Ewbank M, Henson R, Rowe J, Calder A. Different neural mechanisms underlie repetition suppression to facial identity for same-size and different-size faces in the occipitotemporal lobe. J Vis 2011. [DOI: 10.1167/11.11.640] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/24/2022] Open
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12
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Salyakina D, Ma DQ, Jaworski JM, Konidari I, Whitehead PL, Henson R, Martinez D, Robinson JL, Sacharow S, Wright HH, Abramson RK, Gilbert JR, Cuccaro ML, Pericak-Vance MA. Variants in several genomic regions associated with asperger disorder. Autism Res 2010; 3:303-10. [PMID: 21182207 PMCID: PMC4435556 DOI: 10.1002/aur.158] [Citation(s) in RCA: 34] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/14/2023]
Abstract
Asperger disorder (ASP) is one of the autism spectrum disorders (ASD) and is differentiated from autism largely on the absence of clinically significant cognitive and language delays. Analysis of a homogenous subset of families with ASP may help to address the corresponding effect of genetic heterogeneity on identifying ASD genetic risk factors. To examine the hypothesis that common variation is important in ASD, we performed a genome-wide association study (GWAS) in 124 ASP families in a discovery data set and 110 ASP families in a validation data set. We prioritized the top 100 association results from both cohorts by employing a ranking strategy. Novel regions on 5q21.1 (P = 9.7 × 10(-7) ) and 15q22.1-q22.2 (P = 7.3 × 10(-6) ) were our most significant findings in the combined data set. Three chromosomal regions showing association, 3p14.2 (P = 3.6 × 10(-6) ), 3q25-26 (P = 6.0 × 10(-5) ) and 3p23 (P = 3.3 × 10(-4) ) overlapped linkage regions reported in Finnish ASP families, and eight association regions overlapped ASD linkage areas. Our findings suggest that ASP shares both ASD-related genetic risk factors, as well as has genetic risk factors unique to the ASP phenotype.
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Affiliation(s)
- D Salyakina
- John P Hussman Institute for Human Genomics, University of Miami Miller School of Medicine, Miami, Florida 33136, USA
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13
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Rossion B, Alonso-Prieto E, Caharel S, Henson R. S38-7 The neurophysiology of acquired prosopagnosia. Clin Neurophysiol 2010. [DOI: 10.1016/s1388-2457(10)60241-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/18/2022]
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14
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Flandin G, Henson R, Daunizeau J, Friston K, Mattout J. A Generic Framework for fMRI-constrained MEG Source Reconstruction. Neuroimage 2009. [DOI: 10.1016/s1053-8119(09)71789-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/20/2022] Open
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15
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Smith ML, Taylor J, Christensen S, Henson R. Reproducibility of MEG Evoked Fields within and across sessions during a lexical decision task. Neuroimage 2009. [DOI: 10.1016/s1053-8119(09)71398-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/20/2022] Open
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16
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Abstract
Interleukin-6 (IL-6) is overexpressed and contributes to tumor cell growth in cholangiocarcinoma. Enforced IL-6 production can alter the expression of specific microRNAs (miRNAs) involved in tumor growth, and moreover can modulate expression of methylation-dependent genes. Thus, we assessed the methylation-dependent regulation of miRNA expression in human malignant cholangiocytes stably transfected to overexpress IL-6. The expression of the methyltransferases DNA methyltransferase enzyme-1 and HASJ4442 was increased by IL-6 overexpression, but was decreased by the methylation inhibitor 5-aza-2'-deoxycytidine (5-aza-CdR). Expression profiling identified seven miRNAs that were significantly downregulated by IL-6 overexpression (<0.4-fold) and upregulated (>2-fold) by 5-aza-CdR. One of these, miR-370, is embedded in a CpG island. Although 5-aza-CdR increased miR-370 expression by 2.1-fold in malignant cells, the expression in nonmalignant cells was unchanged. The oncogene mitogen-activated protein kinase kinase kinase 8 (MAP3K8) was identified as a target of miR-370, and its expression was decreased by 5-aza-CdR in cholangiocarcinoma cells. Overexpression of IL-6 reduced miR-370 expression and reinstated MAP3K8 expression in vitro as well as in tumor cell xenografts in vivo. Thus, IL-6 may contribute to tumor growth by modulation of expression of selected miRNAs, such as miR-370. These studies define a mechanism by which inflammation-associated cytokines can epigenetically modulate gene expression and directly contribute to tumor biology.
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Affiliation(s)
- F Meng
- Department of Internal Medicine, Scott and White Clinic, Texas A&M University System Health Science Center College of Medicine, Temple, TX, USA
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17
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Abstract
In this note we describe a heuristic, starting with a dimensional analysis, which relates hemodynamic changes to the spectral profile of ongoing EEG activity. In brief, this analysis suggests that 'activation', as indexed by increases in hemodynamic signals, should be associated with a loss of power in lower EEG frequencies, relative to higher frequencies. The fact that activation is expressed in terms of frequency (i.e., per second) is consistent with a dimensional analysis in the sense that activations reflect the rate of energy dissipation (per second). In this heuristic, activation causes an acceleration of temporal dynamics leading to (i) increased energy dissipation; (ii) decreased effective membrane time constants; (iii) increased effective coupling among neuronal ensembles; and (iv) a shift in the EEG spectral profile to higher frequencies. These predictions are consistent with empirical observations of how changes in the EEG spectrum are expressed hemodynamically. Furthermore, the heuristic provides a simple measure of neuronal activation based on spectral analyses of EEG.
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Affiliation(s)
- J M Kilner
- The Wellcome Department of Imaging Neuroscience, Institute of Neurology, London, UK.
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19
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Lawson HW, Henson R, Bobo JK, Kaeser MK. Implementing recommendations for the early detection of breast and cervical cancer among low-income women. Oncology (Williston Park) 2000; 14:1528-30, 1638, 1641-2 passim. [PMID: 11125939] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 02/18/2023]
Affiliation(s)
- H W Lawson
- Division of Cancer Prevention and Control, National Center for Chronic Disease Prevention and Health Promotion, Atlanta, Georgia, USA
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20
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Lantz PM, Richardson LC, Sever LE, Macklem DJ, Hare ML, Orians CE, Henson R. Mass screening in low-income populations: the challenges of securing diagnostic and treatment services in a national cancer screening program. J Health Polit Policy Law 2000; 25:451-471. [PMID: 10946385 DOI: 10.1215/03616878-25-3-451] [Citation(s) in RCA: 17] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/23/2023]
Abstract
Funding for many mass screening programs for low-income and uninsured populations provides resources for screening tests, yet only rarely does it provide coverage for necessary follow-up diagnostic and treatment services. The National Breast and Cervical Cancer Early Detection Program (NBCCEDP), a federally funded initiative that provides cancer screening to low-income uninsured and underinsured women, covers some diagnostic follow-up tests and no treatment services. We conducted in-depth case studies of seven state programs participating in the NBCCEDP to investigate the strategies and approaches being used to secure diagnostic and treatment services. The results suggest that the program relies on a patchwork of resources--at state and local levels--to provide diagnostic and treatment services. This includes a number of components of local safety nets, all of which are unstable and have uncertain futures. Public health disease-screening initiatives need to reconsider the feasibility of continued reliance on case-by-case appeals to the local safety net for diagnostic follow-up and treatment services.
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21
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Lawson HW, Henson R, Bobo JK, Kaeser MK. Implementing recommendations for the early detection of breast and cervical cancer among low-income women. MMWR Recomm Rep 2000; 49:37-55. [PMID: 15580731] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/01/2023] Open
Abstract
SCOPE OF THE PROBLEM Among U.S. women, breast cancer is the most commonly diagnosed cancer and remains second only to lung cancer as a cause of cancer-related mortality. The American Cancer Society (ACS) estimates that 182,800 new cases of female breast cancer and 41,200 deaths from breast cancer will occur in 2000. Since the 1950s, the incidence of invasive cervical cancer and mortality from this disease have decreased substantially; much of the decline is attributed to widespread use of the Papanicolaou (Pap) test. ACS estimates that 12,800 new cases of invasive cervical cancer will be diagnosed, and 4,600 deaths from this disease will occur in the United States in 2000. ETIOLOGIC FACTORS The risk for breast cancer increases with advancing age; other risk factors include personal or family history of breast cancer, certain benign breast diseases, early age at menarche, late age at menopause, white race, nulliparity, and igher socioeconomic status. Risk factors for cervical cancer include certain human papilloma virus infections, early age at first intercourse, multiple male sex partners, a history of sexually transmitted diseases, and low socioeconomic status. Black, Hispanic, or American Indian racial/ethnic background is considered a risk factor because cervical cancer detection and death rates are higher among these women. RECOMMENDATIONS FOR PREVENTION Because studies of the etiology of breast cancer have failed to identify feasible primary prevention strategies suitable for use in the general population, reducing mortality from breast cancer through early detection has become a high priority. The potential for reducing death rates from breast cancer is contingent on increasing mammography screening rates and subsequently detecting the disease at an early stage--when more treatment options are available and survival rates are higher. Effective control of cervical cancer depends primarily on early detection of precancerous lesions through use of the Papanicolaou test, followed by timely evaluation and treatment. Thus, the intended outcome of cervical cancer screening differs from that of breast cancer screening. In 1991, the National Breast and Cervical Cancer Early Detection Program (NBCCEDP) was implemented to increase breast and cervical cancer screening among uninsured, low-income women. RESEARCH AGENDA To support recommended priority activities for NBCCEDP, CDC has developed a research agenda comprising six priorities. These six priorities are a) determining effective strategies to communicate changes in NBCCEDP policy to cancer screening providers and women enrolled in the program; b) identifying effective strategies to increase the proportion of enrolled women who complete routine breast and cervical cancer rescreening according to NBCCEDP policy; c) identifying effective strategies to increase NBCCEDP enrollment among eligible women who have never received breast or cervical cancerscreening; d) evaluating variations in clinical practice patterns among providers of NBCCEDP screening services; e) determining optimal models for providing case-management services to women in NBCCEDP who have an abnormal screening result, precancerous breast or cervical lesion, or a diagnosis of cancer; and f) conducting economic analyses to determine costs of providing screening services in NBCCEDP. CONCLUSION The NBCCEDP, through federal, state, territorial, and tribal governments, in collaboration with national and community-based organizations, has increased access to breast and cervical cancer screening among low-income and uninsured women. This initiative enabled the United States to make substantial progress toward achieving the Healthy People 2000 objectives for breast and cervical cancer control among racial/ethnic minorities and persons who are medically underserved. A continuing challenge for the future is to increase national commitment to providing screening services for all eligible uninsured women to ultimately reduce morbidity and mortality from breast and cervical cancer.
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Affiliation(s)
- H W Lawson
- Division of Cancer Prevention and Control, National Center for Chronic Disease Prevention and Health Promotion, USA
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22
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Abstract
Repetition priming has been characterized neurophysiologically as a decreased response following stimulus repetition. The present study used event-related functional magnetic resonance imaging to investigate whether this repetition-related response is sensitive to stimulus familiarity. A right fusiform region exhibited an attenuated response to the repetition of familiar stimuli, both faces and symbols, but exhibited an enhanced response to the repetition of unfamiliar stimuli. Moreover, both repetition effects were modulated by lag between successive presentations. Further experiments replicated the interactions between repetition, familiarity, and lag and demonstrated the persistence of these effects over multiple repetitions. Priming-related responses are therefore not unitary but depend on the presence or absence of preexisting stimulus representations.
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Affiliation(s)
- R Henson
- Wellcome Department of Cognitive Neurology, Institute of Neurology, Institute of Cognitive Neuroscience and Department of Psychology, University College London, London WC1E 6BT, UK.
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Henson R, Hadfield JM, Cooper S. Injury control strategies: extending the quality and quantity of data relating to road traffic accidents in children. J Accid Emerg Med 1999; 16:87-90. [PMID: 10191437 PMCID: PMC1343285 DOI: 10.1136/emj.16.2.87] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/04/2022]
Abstract
This review describes how an extended database of information can provide the opportunity to go beyond the traditionally distinct health, engineering, and education initiatives in order to identify the effectiveness of more overarching policies for injury control. Such information can be used to raise awareness and to encourage community participation in designing a road traffic accident prevention strategy.
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Affiliation(s)
- R Henson
- Telford Research Institute of Transport and Spatial Development, University of Salford
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Lawson HW, Lee NC, Thames SF, Henson R, Miller DS. Cervical cancer screening among low-income women: results of a national screening program, 1991-1995. Obstet Gynecol 1998; 92:745-52. [PMID: 9794662 DOI: 10.1016/s0029-7844(98)00257-9] [Citation(s) in RCA: 43] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/20/2022]
Abstract
OBJECTIVE To evaluate the results of cervical cytology screening in the National Breast and Cervical Cancer Early Detection Program and to compare the findings with results from other screening programs. METHODS We analyzed data on 312,858 women aged 18 years and older who received one or more Papanicolaou smears, and follow-up if indicated, from October 1991 through June 1995 at screening sites across the United States providing comprehensive National Breast and Cervical Cancer Early Detection Program services. RESULTS Of the women screened, more than half were 40 years or older; slightly less than half (44%) were of racial and ethnic minorities. During the first screening cycle, 3.8% of Papanicolaou tests were reported as abnormal (squamous intraepithelial lesion [SIL] or squamous cell cancer); proportions of abnormals decreased with increasing age. The age-adjusted rate of biopsy-confirmed cervical intraepithelial neoplasia (CIN) II or worse among women screened was 7.4 per 1000 Papanicolaou tests; rates of CIN were highest among young women, but cancer rates peaked among women in their 50s and 60s. The percentages of first screening cycle-Papanicolaou tests interpreted as high-grade SIL and squamous cell carcinoma associated with biopsy-confirmed CIN II or worse (the positive predictive value) were 56.0% for CIN II/III and 3.7% for invasive cancer. Of the 150 invasive cancers diagnosed, 54.0% were classified as local disease. CONCLUSION Observed results emphasize the duality of cervical neoplasia-CIN in younger women and invasive cancer in older women. This finding points to the importance of reaching both younger and older women for cervical cancer screening.
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Affiliation(s)
- H W Lawson
- Division of Cancer Prevention and Control, National Center for Chronic Disease Prevention and Health Promotion, Centers for Disease Control and Prevention, Atlanta, Georgia, USA.
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Abstract
Three experiments investigated the role of working memory in various aspects of thinking in chess. Experiment 1 examined the immediate memory for briefly presented chess positions from master games in players from a wide range of abilities, following the imposition of various secondary tasks designed to block separate components of working memory. Suppression of the articulatory loop (by preventing subvocal rehearsal) had no effect on measures of recall, whereas blocking the visuospatial sketchpad (by manipulation of a keypad) and blocking the central executive (by random letter generation) had equivalent disruptive effects, in comparison with a control condition. Experiment 2 investigated the effects of similar secondary tasks on the solution (i.e., move selection) of tactical chess positions, and a similar pattern was found, except that blocking the central executive was much more disruptive than in Experiment 1. Experiment 3 compared performance on two types of primary task, one concerned with solving chess positions as in Experiment 2, and the other a sentence-rearrangement task. The secondary tasks in each case were both designed to block the central executive, but one was verbal (vocal generation of random numbers), while the other was spatial in nature (random generation of keypresses). Performance of the spatial secondary task was affected to a greater extent by the chess primary task than by the verbal primary task, whereas there were no differential effects on these secondary tasks by the verbal primary task. In none of the three experiments were there any differential effects between weak and strong players. These results are interpreted in the context of the working-memory model and previous theories of the nature of cognition in chess.
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Abstract
Nurse executives are continually faced with issues related to nursing turnover and staff morale. This sample included 217 registered nurses working in a state health department where the turnover rate was 8%. In this study, the authors found that nurses with advanced educational preparation, higher-level positions, or both, demonstrated increased levels of morale. Conversely, nurses with increased years of service and nursing experience had lower morale levels. These findings could be useful in delineating situations to improve morale and lower turnover rates.
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Affiliation(s)
- M MacRobert
- Children's Hospital of Oklahoma, Oklahoma City
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Henson R. Computer databases built for HR. HRMAGAZINE 1991; 36:59, 61. [PMID: 10111081] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 04/12/2023]
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Speed JC, Culpepper V, Thompson DE, Henson R, Wint B, Bundy DA. A community-based study of gastrointestinal helminth and protozoan infection in Western Jamaica. W INDIAN MED J 1987; 36:73-9. [PMID: 3499709] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [MESH Headings] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/06/2023]
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Friedman IM, Litt IF, King DR, Henson R, Holtzman D, Halverson D, Kraemer HC. Compliance with anticonvulsant therapy by epileptic youth. Relationships to psychosocial aspects of adolescent development. J Adolesc Health Care 1986; 7:12-7. [PMID: 3943997 DOI: 10.1016/s0197-0070(86)80088-2] [Citation(s) in RCA: 40] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/08/2023]
Abstract
Independence in daily life, family harmony as perceived by youths and their parents, and self-esteem were investigated in relation to anticonvulsant medication compliance in 25 epileptics aged 9-17 years. Medication compliance was assessed by monthly home saliva sampling for phenobarbital concentrations. Psychosocial issues were assessed by standardized instruments. Each psychosocial issue was highly correlated with compliance. Partial correlation analysis reveals that these findings are not explained by the subject's demographic or clinical characteristics. Medication noncompliance appears to be associated with a restriction of independence in daily life, lack of harmony in family relations, and low self-esteem in teenage epileptics. Clinicians should observe for these conditions and initiate patient and family counseling in order to maximize medication compliance and seizure control.
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Oskinski B, Henson R. Health care blow-outs hit rubber city. Urban Health 1984; 13:30-1. [PMID: 10269277] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 02/12/2023]
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Abstract
A high pressure liquid chromatographic assay was developed for simultaneous measurement of the plasma levels of tolmesoxide and its principal metabolite, RX71112. The assay was used to study the disposition of intravenous and oral tolmesoxide in ten normotensive subjects. Two exponential terms were required to describe the disposition of the drug following intravenous administration, whilst a single exponential term sufficed to account for the decay in the plasma concentration after oral administration. The bioavailability of oral tolmesoxide from capsules averaged 84.5% and was independent of dose. The mean half-life after i.v. dosing was 2.6 h (+/- 0.3 SEM) compared to values of 1.9 h (+/- 0.1 SEM) and 2.7 h (+/- 0.5 SEM) following 200 and 400 mg oral doses respectively. In all subjects RX71112 appeared in plasma shortly after tolmesoxide following both routes of administration. The terminal half-life of the metabolite was significantly longer than tolmesoxide with a mean value of 4.9 h (+/- 0.9 SEM) following the 200 mg oral dose of tolmesoxide. The binding of tolmesoxide and RX71112 at therapeutic plasma concentration was 36.8% (+/- 0.5 SEM) and 58.5% (+/- 0.3 SEM) and this remained unchanged at higher concentrations.
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Blattner WA, Garber JE, Mann DL, McKeen EA, Henson R, McGuire DB, Fisher WB, Bauman AW, Goldin LR, Fraumeni JF. Waldenström's macroglobulinemia and autoimmune disease in a family. Ann Intern Med 1980; 93:830-2. [PMID: 6778280 DOI: 10.7326/0003-4819-93-6-830] [Citation(s) in RCA: 34] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/21/2023] Open
Abstract
We diagnosed Waldenström's macroglobulinemia in a father and three offspring. Clinical and subclinical autoimmune disorders occurred excessively in the family. The HLA haplotype A2, B8, DRw3 was detected in all patients with Waldenström's macroglobulinemia and all but one family member with autoimmune manifestations. A lod score [log odds] of 4.86 favors linkage to the HLA complex of a gene predisposing to lymphoproliferative and autoimmune disorders. Associated with this HLA haplotype were the B-cell alloantigens Ia-172 and 350, previously reported in patients with the lymphoma-prone sicca syndrome.
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Lloyd-Jones JG, Robinson P, Henson R, Biggs SR, Taylor T. Plasma concentration and disposition of buprenorphine after intravenous and intramuscular doses to baboons. Eur J Drug Metab Pharmacokinet 1980; 5:233-9. [PMID: 7250147 DOI: 10.1007/bf03189469] [Citation(s) in RCA: 16] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/24/2023]
Abstract
Buprenorphine is a newly-developed strong analgesic. A selected ion monitoring method has been developed to measure its plasma levels over the concentration range 20-3000ng ml-1. Six baboons each received intravenous and intramuscular doses of buprenorphine hydrochloride at a level of 5mg/kg in a cross-over study. The mean peak plasma concentrations (+/-standard deviation) were 2290 +/- 357ng ml-1 and 805 +/- 416ng ml-1 respectively and the corresponding times to the peak levels were 4.0 +/- 1.5 minutes and 30.3 +/- 24.6 minutes suggesting the rapid release of the drug from intramuscular sites. Comparison of areas under the plasma concentration versus time curves to 24 hours after dosing showed the mean bioavailability of buprenorphine from the intramuscular doses was 70% of that from the reference intravenous doses.
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Henson R, Lloyd-Jones JG, Nichols JD, Jordan BJ. Pharmacokinetics of fenclofenac following single and multiple doses. Eur J Drug Metab Pharmacokinet 1980; 5:217-23. [PMID: 7250145 DOI: 10.1007/bf03189467] [Citation(s) in RCA: 11] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/24/2023]
Abstract
The plasma concentration of the anti-inflammatory drug fenclofenac was investigated in volunteers following single oral doses of 200, 500 and 600 mg, as well as multiple doses of 600mg b.i.d. over five days, using gas chromatography with electron capture detection. The pharmacokinetic parameters derived were independent of dose, and the terminal half-life, t1/2, varied independently of dose between 20 and 38 hours (27.23 +/- 1.8 at 600mg). The apparent volume of distribution (Vd area) had similar values at doses of 200, 500 and 600mg of 15.2 +/- 2.6, 18.2 +/- 1.5 and 14.7 +/- 1.7 litres respectively. These small volumes of distribution indicate that fenclofenac distributes mainly into extracellular space. A mean peak plasma concentration of 63.5 +/- 4.6microgram/ml developed after 3 to4 hours following a single 600mg dose whilst a mean steady state plasma concentration (600mg b.i.d.) of 86.9 +/- 5.7 microgram/ml was achieved within four days, and this decayed with a mean terminal half-life of 25.9 +/- 4.2 hours.
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Barker R, Boden N, Cayley G, Charlton SC, Henson R, Holmes MC, Kelly ID, Knowles PF. Properties of cupric ions in benzylamine oxidase from pig plasma as studied by magnetic-resonance and kinetic methods. Biochem J 1979; 177:289-302. [PMID: 218560 PMCID: PMC1186368 DOI: 10.1042/bj1770289] [Citation(s) in RCA: 81] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
Benzylamine oxidase from pig plasma has been studied by a variety of chemical and physical techniques. 1. Analytical ultracentrifugation, gel electrophoresis and isoelectric-focusing studies suggest that the enzyme is composed of two subunits with closely similar primary structures. 2. E.s.r. and n.m.r. measurements show that the enzyme contains two well-separated (greater than 0.6 nm) Cu2+ ions at chemically distinct sites. Each Cu2+ ion is coordinated by two water molecules, one 'axial' and the other 'equatorial'. Both water molecules undergo fast exchange (10(5)--10(8) s-1) with solvent and are deprotonated in the pH range 8--9, but only the equatorial water molecule is displaced by the inhibitors N3- and CN-. 3. Kinetic and e.s.r. measurements show that azide and cyanide compete against O2 binding and also make the two Cu2+ sites identical. It is concluded that Cu2+ must participate in the re-oxidation of reduced enzyme by molecular O2.
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Brown FF, Campbell ID, Henson R, Hirst CW, Richards RE. A study of the interaction of manganese ions with ATP by 31P Fourier-transform nuclear-magnetic resonance. Eur J Biochem 1973; 38:54-8. [PMID: 4774125 DOI: 10.1111/j.1432-1033.1973.tb03032.x] [Citation(s) in RCA: 44] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [What about the content of this article? (0)] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/12/2023]
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