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Dive into the research topics where Daniel I. S. Rosenbloom is active.

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Featured researches published by Daniel I. S. Rosenbloom.


Cell | 2013

Replication-Competent Noninduced Proviruses in the Latent Reservoir Increase Barrier to HIV-1 Cure

Ya Chi Ho; Liang Shan; Nina N. Hosmane; Jeffrey Wang; Sarah B. Laskey; Daniel I. S. Rosenbloom; Jun Lai; Joel N. Blankson; Janet D. Siliciano; Robert F. Siliciano

Antiretroviral therapy fails to cure HIV-1 infection because latent proviruses persist in resting CD4(+) T cells. T cell activation reverses latency, but <1% of proviruses are induced to release infectious virus after maximum in vitro activation. The noninduced proviruses are generally considered defective but have not been characterized. Analysis of 213 noninduced proviral clones from treated patients showed 88.3% with identifiable defects but 11.7% with intact genomes and normal long terminal repeat (LTR) function. Using direct sequencing and genome synthesis, we reconstructed full-length intact noninduced proviral clones and demonstrated growth kinetics comparable to reconstructed induced proviruses from the same patients. Noninduced proviruses have unmethylated promoters and are integrated into active transcription units. Thus, it cannot be excluded that they may become activated in vivo. The identification of replication-competent noninduced proviruses indicates that the size of the latent reservoir-and, hence, the barrier to cure-may be up to 60-fold greater than previously estimated.


Nature | 2014

Rapid seeding of the viral reservoir prior to SIV viraemia in rhesus monkeys

James B. Whitney; Alison L. Hill; Srisowmya Sanisetty; Pablo Penaloza-MacMaster; Jinyan Liu; Mayuri Shetty; Lily Parenteau; Crystal Cabral; Jennifer Shields; Stephen Blackmore; Jeffrey Y. Smith; Amanda L. Brinkman; Lauren Peter; Sheeba Mathew; Kaitlin M. Smith; Erica N. Borducchi; Daniel I. S. Rosenbloom; Mark G. Lewis; Jillian Hattersley; Bei Li; Joseph Hesselgesser; Romas Geleziunas; Merlin L. Robb; Jerome H. Kim; Nelson L. Michael; Dan H. Barouch

The viral reservoir represents a critical challenge for human immunodeficiency virus type 1 (HIV-1) eradication strategies. However, it remains unclear when and where the viral reservoir is seeded during acute infection and the extent to which it is susceptible to early antiretroviral therapy (ART). Here we show that the viral reservoir is seeded rapidly after mucosal simian immunodeficiency virus (SIV) infection of rhesus monkeys and before systemic viraemia. We initiated suppressive ART in groups of monkeys on days 3, 7, 10 and 14 after intrarectal SIVMAC251 infection. Treatment with ART on day 3 blocked the emergence of viral RNA and proviral DNA in peripheral blood and also substantially reduced levels of proviral DNA in lymph nodes and gastrointestinal mucosa as compared with treatment at later time points. In addition, treatment on day 3 abrogated the induction of SIV-specific humoral and cellular immune responses. Nevertheless, after discontinuation of ART following 24 weeks of fully suppressive therapy, virus rebounded in all animals, although the monkeys that were treated on day 3 exhibited a delayed viral rebound as compared with those treated on days 7, 10 and 14. The time to viral rebound correlated with total viraemia during acute infection and with proviral DNA at the time of ART discontinuation. These data demonstrate that the viral reservoir is seeded rapidly after intrarectal SIV infection of rhesus monkeys, during the ‘eclipse’ phase, and before detectable viraemia. This strikingly early seeding of the refractory viral reservoir raises important new challenges for HIV-1 eradication strategies.


Journal of Clinical Investigation | 2015

Ex vivo analysis identifies effective HIV-1 latency–reversing drug combinations

Gregory M. Laird; C. Korin Bullen; Daniel I. S. Rosenbloom; Alyssa R. Martin; Alison L. Hill; Christine M. Durand; Janet D. Siliciano; Robert F. Siliciano

Reversal of HIV-1 latency by small molecules is a potential cure strategy. This approach will likely require effective drug combinations to achieve high levels of latency reversal. Using resting CD4+ T cells (rCD4s) from infected individuals, we developed an experimental and theoretical framework to identify effective latency-reversing agent (LRA) combinations. Utilizing ex vivo assays for intracellular HIV-1 mRNA and virion production, we compared 2-drug combinations of leading candidate LRAs and identified multiple combinations that effectively reverse latency. We showed that protein kinase C agonists in combination with bromodomain inhibitor JQ1 or histone deacetylase inhibitors robustly induce HIV-1 transcription and virus production when directly compared with maximum reactivation by T cell activation. Using the Bliss independence model to quantitate combined drug effects, we demonstrated that these combinations synergize to induce HIV-1 transcription. This robust latency reversal occurred without release of proinflammatory cytokines by rCD4s. To extend the clinical utility of our findings, we applied a mathematical model that estimates in vivo changes in plasma HIV-1 RNA from ex vivo measurements of virus production. Our study reconciles diverse findings from previous studies, establishes a quantitative experimental approach to evaluate combinatorial LRA efficacy, and presents a model to predict in vivo responses to LRAs.


Proceedings of the National Academy of Sciences of the United States of America | 2014

Predicting the outcomes of treatment to eradicate the latent reservoir for HIV-1

Alison L. Hill; Daniel I. S. Rosenbloom; Feng Fu; Martin A. Nowak; Robert F. Siliciano

Significance HIV infection cannot be cured by current antiretroviral drugs, due to the presence of long-lived latently infected cells. New antilatency drugs are being tested in clinical trials, but major unknowns remain. It is unclear how much latent virus must be eliminated for a cure, which remains difficult to answer empirically due to few case studies and limited sensitivity of viral reservoir assays. In this paper, we introduce a mathematical model of HIV dynamics to calculate the likelihood and timing of viral rebound following antilatency treatment. We derive predictions for the required efficacy of antilatency drugs, and demonstrate that rebound times may be highly variable and occur after years of remission. These results will aid in designing and interpreting HIV cure studies. Massive research efforts are now underway to develop a cure for HIV infection, allowing patients to discontinue lifelong combination antiretroviral therapy (ART). New latency-reversing agents (LRAs) may be able to purge the persistent reservoir of latent virus in resting memory CD4+ T cells, but the degree of reservoir reduction needed for cure remains unknown. Here we use a stochastic model of infection dynamics to estimate the efficacy of LRA needed to prevent viral rebound after ART interruption. We incorporate clinical data to estimate population-level parameter distributions and outcomes. Our findings suggest that ∼2,000-fold reductions are required to permit a majority of patients to interrupt ART for 1 y without rebound and that rebound may occur suddenly after multiple years. Greater than 10,000-fold reductions may be required to prevent rebound altogether. Our results predict large variation in rebound times following LRA therapy, which will complicate clinical management. This model provides benchmarks for moving LRAs from the laboratory to the clinic and can aid in the design and interpretation of clinical trials. These results also apply to other interventions to reduce the latent reservoir and can explain the observed return of viremia after months of apparent cure in recent bone marrow transplant recipients and an immediately-treated neonate.


Nature Medicine | 2012

Antiretroviral dynamics determines HIV evolution and predicts therapy outcome

Daniel I. S. Rosenbloom; Alison L. Hill; S. Alireza Rabi; Robert F. Siliciano; Martin A. Nowak

Despite the high inhibition of viral replication achieved by current anti-HIV drugs, many patients fail treatment, often with emergence of drug-resistant virus. Clinical observations show that the relationship between adherence and likelihood of resistance differs dramatically among drug classes. We developed a mathematical model that explains these observations and predicts treatment outcomes. Our model incorporates drug properties, fitness differences between susceptible and resistant strains, mutations and adherence. We show that antiviral activity falls quickly for drugs with sharp dose-response curves and short half-lives, such as boosted protease inhibitors, limiting the time during which resistance can be selected for. We find that poor adherence to such drugs causes treatment failure via growth of susceptible virus, explaining puzzling clinical observations. Furthermore, our model predicts that certain single-pill combination therapies can prevent resistance regardless of patient adherence. Our approach represents a first step for simulating clinical trials of untested anti-HIV regimens and may help in the selection of new drug regimens for investigation.


Nature Genetics | 2016

Clonal evolution of glioblastoma under therapy

Jiguang Wang; Emanuela Cazzato; Erik Ladewig; Veronique Frattini; Daniel I. S. Rosenbloom; Sakellarios Zairis; Francesco Abate; Zhaoqi Liu; Oliver Elliott; Yong Jae Shin; Jin Ku Lee; In Hee Lee; Woong-Yang Park; Marica Eoli; Andrew J. Blumberg; Anna Lasorella; Do Hyun Nam; Gaetano Finocchiaro; Antonio Iavarone; Raul Rabadan

Glioblastoma (GBM) is the most common and aggressive primary brain tumor. To better understand how GBM evolves, we analyzed longitudinal genomic and transcriptomic data from 114 patients. The analysis shows a highly branched evolutionary pattern in which 63% of patients experience expression-based subtype changes. The branching pattern, together with estimates of evolutionary rate, suggests that relapse-associated clones typically existed years before diagnosis. Fifteen percent of tumors present hypermutation at relapse in highly expressed genes, with a clear mutational signature. We find that 11% of recurrence tumors harbor mutations in LTBP4, which encodes a protein binding to TGF-β. Silencing LTBP4 in GBM cells leads to suppression of TGF-β activity and decreased cell proliferation. In recurrent GBM with wild-type IDH1, high LTBP4 expression is associated with worse prognosis, highlighting the TGF-β pathway as a potential therapeutic target in GBM.


The New England Journal of Medicine | 2015

Viremic relapse after HIV-1 remission in a perinatally infected child

Katherine Luzuriaga; Carrie Ziemniak; Keri B. Sanborn; Mohan Somasundaran; Kaitlin Rainwater-Lovett; John W. Mellors; Daniel I. S. Rosenbloom; Deborah Persaud

Recently the “Mississippi Child” was reported as having a prolonged clearance of HIV viremia after the initiation of antiretroviral therapy shortly after birth. Further follow-up of this case is now reported.


Journal of Experimental Medicine | 2017

Proliferation of latently infected CD4+ T cells carrying replication-competent HIV-1: Potential role in latent reservoir dynamics

Nina N. Hosmane; Kyungyoon J. Kwon; Katherine M. Bruner; Adam A. Capoferri; Subul A. Beg; Daniel I. S. Rosenbloom; Brandon F. Keele; Ya Chi Ho; Janet D. Siliciano; Robert F. Siliciano

A latent reservoir for HIV-1 in resting CD4+ T lymphocytes precludes cure. Mechanisms underlying reservoir stability are unclear. Recent studies suggest an unexpected degree of infected cell proliferation in vivo. T cell activation drives proliferation but also reverses latency, resulting in productive infection that generally leads to cell death. In this study, we show that latently infected cells can proliferate in response to mitogens without producing virus, generating progeny cells that can release infectious virus. Thus, assays relying on one round of activation underestimate reservoir size. Sequencing of independent clonal isolates of replication-competent virus revealed that 57% had env sequences identical to other isolates from the same patient. Identity was confirmed by full-genome sequencing and was not attributable to limited viral diversity. Phylogenetic and statistical analysis suggested that identical sequences arose from in vivo proliferation of infected cells, rather than infection of multiple cells by a dominant viral species. The possibility that much of the reservoir arises by cell proliferation presents challenges to cure.


Open Forum Infectious Diseases | 2015

Designing and Interpreting Limiting Dilution Assays: General Principles and Applications to the Latent Reservoir for Human Immunodeficiency Virus-1.

Daniel I. S. Rosenbloom; Oliver Elliott; Alison L. Hill; Timothy J. Henrich; Janet M. Siliciano; Robert F. Siliciano

Limiting dilution assays are widely used in infectious disease research. These assays are crucial for current HIV-1 cure research in particular. Here we offer new tools to help investigators design and analyze dilution assays based on their specific research needs.


Nature Genetics | 2017

Spatiotemporal Genomic Architecture Informs Precision Oncology in Glioblastoma

Jin-Ku Lee; Jiguang Wang; Jason K. Sa; Erik Ladewig; Hae-Ock Lee; In-Hee Lee; Hyun Ju Kang; Daniel I. S. Rosenbloom; Pablo G. Camara; Zhaoqi Liu; Patrick van Nieuwenhuizen; Sang Won Jung; Seung Won Choi; J. Kim; Andrew X. Chen; K.-W. Kim; Sang Shin; Yun Jee Seo; Jin-Mi Oh; Yong Jae Shin; Chul-Kee Park; Doo-Sik Kong; Ho Jun Seol; Andrew J. Blumberg; Jung-Il Lee; Antonio Iavarone; Woong-Yang Park; Raul Rabadan; Do-Hyun Nam

Precision medicine in cancer proposes that genomic characterization of tumors can inform personalized targeted therapies. However, this proposition is complicated by spatial and temporal heterogeneity. Here we study genomic and expression profiles across 127 multisector or longitudinal specimens from 52 individuals with glioblastoma (GBM). Using bulk and single-cell data, we find that samples from the same tumor mass share genomic and expression signatures, whereas geographically separated, multifocal tumors and/or long-term recurrent tumors are seeded from different clones. Chemical screening of patient-derived glioma cells (PDCs) shows that therapeutic response is associated with genetic similarity, and multifocal tumors that are enriched with PIK3CA mutations have a heterogeneous drug-response pattern. We show that targeting truncal events is more efficacious than targeting private events in reducing the tumor burden. In summary, this work demonstrates that evolutionary inference from integrated genomic analysis in multisector biopsies can inform targeted therapeutic interventions for patients with GBM.

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Robert F. Siliciano

Johns Hopkins University School of Medicine

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Janet D. Siliciano

Johns Hopkins University School of Medicine

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Jun Lai

Johns Hopkins University School of Medicine

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