Publications by authors named "Daniel I S Rosenbloom"

23 Publications

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Allogeneic bone marrow transplantation with post-transplant cyclophosphamide for patients with HIV and haematological malignancies: a feasibility study.

Authors:
Christine M Durand Adam A Capoferri Andrew D Redd Marianna Zahurak Daniel I S Rosenbloom Ayla Cash Robin K Avery Javier Bolaños-Meade Catherine M Bollard C Korin Bullen Charles Flexner Ephraim J Fuchs Joel Gallant Doug E Gladstone Christopher D Gocke Richard J Jones Yvette L Kasamon Jun Lai Mark Levis Leo Luznik Kieren A Marr Holly L McHugh Seema Mehta Steinke Paul Pham Christopher Pohlmeyer Keith Pratz Shmuel Shoham Nina Wagner-Johnston Daniel Xu Janet D Siliciano Thomas C Quinn Robert F Siliciano Richard F Ambinder

Lancet HIV 2020 09 7;7(9):e602-e610. Epub 2020 Jul 7.

Sidney Kimmel Cancer Center, Baltimore, MD, USA.

Background: Allogeneic blood or marrow transplantation (alloBMT) is a potentially life-saving treatment for individuals with HIV and haematological malignancies; challenges include identifying donors and maintaining antiretroviral therapy (ART). The objectives of our study were to investigate interventions to expand donor options and to prevent ART interruptions for patients with HIV in need of alloBMT.

Methods: This single-arm, interventional trial took place at the Johns Hopkins Sidney Kimmel Comprehensive Cancer Center (Baltimore, MD, USA). Individuals with HIV who were at least 18 years of age and referred for alloBMT for a standard clinical indication were eligible. The only exclusion criterion was a history of documented resistance to enfuvirtide. We used post-transplant cyclophosphamide as graft-versus-host disease (GVHD) prophylaxis to expand donor options and an optimised ART strategy of avoiding pharmacoenhancers and adding subcutaneous enfuvirtide during post-transplant cyclophosphamide and during oral medication intolerance. Our primary outcome was the proportion of participants who maintained ART through day 60 after alloBMT. We measured the HIV latent reservoir using a quantitative viral outgrowth assay. This study is registered on ClinicalTrials.gov, NCT01836068.

Findings: Between June 1, 2013, and August 27, 2015, nine patients who were referred for transplant provided consent. Two patients had relapsed malignancy before donor searches were initiated. Seven patients had suitable donors identified (two matched sibling, two matched unrelated, two haploidentical, and one single-antigen mismatched unrelated) and proceeded to alloBMT. All patients maintained ART through day 60 and required ART changes (median 1, range 1-3) in the first 90 days. One patient stopped ART and developed HIV rebound with grade 4 meningoencephalitis at day 146. Among six patients who underwent alloBMT and had longitudinal measurements available, the HIV latent reservoir was not detected post-alloBMT in four patients with more than 95% donor chimerism, consistent with a 2·06-2·54 log reduction in the HIV latent reservoir. In the two patients with less than 95% donor chimerism, the HIV latent reservoir remained stable.

Interpretation: By using post-transplant cyclophosphamide as GVHD prophylaxis, we successfully expanded alloBMT donor options for patients with HIV. Continuing ART with a regimen that includes enfuvirtide post-alloBMT was safe, but life-threatening viral rebound can occur with ART interruption.

Funding: amfAR (the Foundation for AIDS Research), Johns Hopkins University Center for AIDS Research, and National Cancer Institute.
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http://dx.doi.org/10.1016/S2352-3018(20)30073-4DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7484204PMC
September 2020

Assessing intra-lab precision and inter-lab repeatability of outgrowth assays of HIV-1 latent reservoir size.

Authors:
Daniel I S Rosenbloom Peter Bacchetti Mars Stone Xutao Deng Ronald J Bosch Douglas D Richman Janet D Siliciano John W Mellors Steven G Deeks Roger G Ptak Rebecca Hoh Sheila M Keating Melanie Dimapasoc Marta Massanella Jun Lai Michele D Sobolewski Deanna A Kulpa Michael P Busch

PLoS Comput Biol 2019 04 12;15(4):e1006849. Epub 2019 Apr 12.

Blood Systems Research Institute, San Francisco, California, United States of America.

Quantitative viral outgrowth assays (QVOA) use limiting dilutions of CD4+ T cells to measure the size of the latent HIV-1 reservoir, a major obstacle to curing HIV-1. Efforts to reduce the reservoir require assays that can reliably quantify its size in blood and tissues. Although QVOA is regarded as a "gold standard" for reservoir measurement, little is known about its accuracy and precision or about how cell storage conditions or laboratory-specific practices affect results. Owing to this lack of knowledge, confidence intervals around reservoir size estimates-as well as judgments of the ability of therapeutic interventions to alter the size of the replication-competent but transcriptionally inactive latent reservoir-rely on theoretical statistical assumptions about dilution assays. To address this gap, we have carried out a Bayesian statistical analysis of QVOA reliability on 75 split samples of peripheral blood mononuclear cells (PBMC) from 5 antiretroviral therapy (ART)-suppressed participants, measured using four different QVOAs at separate labs, estimating assay precision and the effect of frozen cell storage on estimated reservoir size. We found that typical assay results are expected to differ from the true value by a factor of 1.6 to 1.9 up or down. Systematic assay differences comprised a 24-fold range between the assays with highest and lowest scales, likely reflecting differences in viral outgrowth readout and input cell stimulation protocols. We also found that controlled-rate freezing and storage of samples did not cause substantial differences in QVOA compared to use of fresh cells (95% probability of < 2-fold change), supporting continued use of frozen storage to allow transport and batched analysis of samples. Finally, we simulated an early-phase clinical trial to demonstrate that batched analysis of pre- and post-therapy samples may increase power to detect a three-fold reservoir reduction by 15 to 24 percentage points.
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http://dx.doi.org/10.1371/journal.pcbi.1006849DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6481870PMC
April 2019

Pharmacogenomic landscape of patient-derived tumor cells informs precision oncology therapy.

Authors:
Jin-Ku Lee Zhaoqi Liu Jason K Sa Sang Shin Jiguang Wang Mykola Bordyuh Hee Jin Cho Oliver Elliott Timothy Chu Seung Won Choi Daniel I S Rosenbloom In-Hee Lee Yong Jae Shin Hyun Ju Kang Donggeon Kim Sun Young Kim Moon-Hee Sim Jusun Kim Taehyang Lee Yun Jee Seo Hyemi Shin Mijeong Lee Sung Heon Kim Yong-Jun Kwon Jeong-Woo Oh Minsuk Song Misuk Kim Doo-Sik Kong Jung Won Choi Ho Jun Seol Jung-Il Lee Seung Tae Kim Joon Oh Park Kyoung-Mee Kim Sang-Yong Song Jeong-Won Lee Hee-Cheol Kim Jeong Eon Lee Min Gew Choi Sung Wook Seo Young Mog Shim Jae Ill Zo Byong Chang Jeong Yeup Yoon Gyu Ha Ryu Nayoung K D Kim Joon Seol Bae Woong-Yang Park Jeongwu Lee Roel G W Verhaak Antonio Iavarone Jeeyun Lee Raul Rabadan Do-Hyun Nam

Nat Genet 2018 10 27;50(10):1399-1411. Epub 2018 Sep 27.

Institute for Refractory Cancer Research, Samsung Medical Center, Seoul, Republic of Korea.

Outcomes of anticancer therapy vary dramatically among patients due to diverse genetic and molecular backgrounds, highlighting extensive intertumoral heterogeneity. The fundamental tenet of precision oncology defines molecular characterization of tumors to guide optimal patient-tailored therapy. Towards this goal, we have established a compilation of pharmacological landscapes of 462 patient-derived tumor cells (PDCs) across 14 cancer types, together with genomic and transcriptomic profiling in 385 of these tumors. Compared with the traditional long-term cultured cancer cell line models, PDCs recapitulate the molecular properties and biology of the diseases more precisely. Here, we provide insights into dynamic pharmacogenomic associations, including molecular determinants that elicit therapeutic resistance to EGFR inhibitors, and the potential repurposing of ibrutinib (currently used in hematological malignancies) for EGFR-specific therapy in gliomas. Lastly, we present a potential implementation of PDC-derived drug sensitivities for the prediction of clinical response to targeted therapeutics using retrospective clinical studies.
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http://dx.doi.org/10.1038/s41588-018-0209-6DOI Listing
October 2018

Insight into treatment of HIV infection from viral dynamics models.

Authors:
Alison L Hill Daniel I S Rosenbloom Martin A Nowak Robert F Siliciano

Immunol Rev 2018 09;285(1):9-25

Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland.

The odds of living a long and healthy life with HIV infection have dramatically improved with the advent of combination antiretroviral therapy. Along with the early development and clinical trials of these drugs, and new field of research emerged called viral dynamics, which uses mathematical models to interpret and predict the time-course of viral levels during infection and how they are altered by treatment. In this review, we summarize the contributions that virus dynamics models have made to understanding the pathophysiology of infection and to designing effective therapies. This includes studies of the multiphasic decay of viral load when antiretroviral therapy is given, the evolution of drug resistance, the long-term persistence latently infected cells, and the rebound of viremia when drugs are stopped. We additionally discuss new work applying viral dynamics models to new classes of investigational treatment for HIV, including latency-reversing agents and immunotherapy.
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http://dx.doi.org/10.1111/imr.12698DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6155466PMC
September 2018

Life cycle synchronization is a viral drug resistance mechanism.

Authors:
Iulia A Neagu Jason Olejarz Mark Freeman Daniel I S Rosenbloom Martin A Nowak Alison L Hill

PLoS Comput Biol 2018 02 15;14(2):e1005947. Epub 2018 Feb 15.

Program for Evolutionary Dynamics, Department of Mathematics and Department of Organismic & Evolutionary Biology, Harvard University, Cambridge, Massachusetts, United States of America.

Viral infections are one of the major causes of death worldwide, with HIV infection alone resulting in over 1.2 million casualties per year. Antiviral drugs are now being administered for a variety of viral infections, including HIV, hepatitis B and C, and influenza. These therapies target a specific phase of the virus's life cycle, yet their ultimate success depends on a variety of factors, such as adherence to a prescribed regimen and the emergence of viral drug resistance. The epidemiology and evolution of drug resistance have been extensively characterized, and it is generally assumed that drug resistance arises from mutations that alter the virus's susceptibility to the direct action of the drug. In this paper, we consider the possibility that a virus population can evolve towards synchronizing its life cycle with the pattern of drug therapy. The periodicity of the drug treatment could then allow for a virus strain whose life cycle length is a multiple of the dosing interval to replicate only when the concentration of the drug is lowest. This process, referred to as "drug tolerance by synchronization", could allow the virus population to maximize its overall fitness without having to alter drug binding or complete its life cycle in the drug's presence. We use mathematical models and stochastic simulations to show that life cycle synchronization can indeed be a mechanism of viral drug tolerance. We show that this effect is more likely to occur when the variability in both viral life cycle and drug dose timing are low. More generally, we find that in the presence of periodic drug levels, time-averaged calculations of viral fitness do not accurately predict drug levels needed to eradicate infection, even if there is no synchronization. We derive an analytical expression for viral fitness that is sufficient to explain the drug-pattern-dependent survival of strains with any life cycle length. We discuss the implications of these findings for clinically relevant antiviral strategies.
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http://dx.doi.org/10.1371/journal.pcbi.1005947DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5813899PMC
February 2018

Re-evaluating evolution in the HIV reservoir.

Authors:
Daniel I S Rosenbloom Alison L Hill Sarah B Laskey Robert F Siliciano

Nature 2017 11;551(7681):E6-E9

Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA.

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http://dx.doi.org/10.1038/nature24634DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6103791PMC
November 2017

Correction: Real-Time Predictions of Reservoir Size and Rebound Time during Antiretroviral Therapy Interruption Trials for HIV.

Authors:
Alison L Hill Daniel I S Rosenbloom Edward Goldstein Emily Hanhauser Daniel R Kuritzkes Robert F Siliciano Timothy J Henrich

PLoS Pathog 2017 Jul 6;13(7):e1006488. Epub 2017 Jul 6.

[This corrects the article DOI: 10.1371/journal.ppat.1005535.].
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http://dx.doi.org/10.1371/journal.ppat.1006488DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5500350PMC
July 2017

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

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

J Exp Med 2017 04 24;214(4):959-972. Epub 2017 Mar 24.

Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD 21205

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 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.
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http://dx.doi.org/10.1084/jem.20170193DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5379987PMC
April 2017

Evolutionary scalpels for dissecting tumor ecosystems.

Authors:
Daniel I S Rosenbloom Pablo G Camara Tim Chu Raul Rabadan

Biochim Biophys Acta Rev Cancer 2017 Apr 5;1867(2):69-83. Epub 2016 Dec 5.

Department of Systems Biology, Columbia University College of Physicians and Surgeons, 1130 St. Nicholas Avenue, New York, NY 10032, USA; Department of Biomedical Informatics, Columbia University College of Physicians and Surgeons, 1130 St. Nicholas Avenue, New York, NY 10032, USA. Electronic address:

Amidst the growing literature on cancer genomics and intratumor heterogeneity, essential principles in evolutionary biology recur time and time again. Here we use these principles to guide the reader through major advances in cancer research, highlighting issues of "hit hard, hit early" treatment strategies, drug resistance, and metastasis. We distinguish between two frameworks for understanding heterogeneous tumors, both of which can inform treatment strategies: (1) The tumor as diverse ecosystem, a Darwinian population of sometimes-competing, sometimes-cooperating cells; (2) The tumor as tightly integrated, self-regulating organ, which may hijack developmental signals to restore functional heterogeneity after treatment. While the first framework dominates literature on cancer evolution, the second framework enjoys support as well. Throughout this review, we illustrate how mathematical models inform understanding of tumor progression and treatment outcomes. Connecting models to genomic data faces computational and technical hurdles, but high-throughput single-cell technologies show promise to clear these hurdles. This article is part of a Special Issue entitled: Evolutionary principles - heterogeneity in cancer?, edited by Dr. Robert A. Gatenby.
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http://dx.doi.org/10.1016/j.bbcan.2016.11.005DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5704952PMC
April 2017

Insufficient Evidence for Rare Activation of Latent HIV in the Absence of Reservoir-Reducing Interventions.

Authors:
Alison L Hill Daniel I S Rosenbloom Janet D Siliciano Robert F Siliciano

PLoS Pathog 2016 08 25;12(8):e1005679. Epub 2016 Aug 25.

Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland, United States of America.

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http://dx.doi.org/10.1371/journal.ppat.1005679DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4999146PMC
August 2016

Topological Data Analysis Generates High-Resolution, Genome-wide Maps of Human Recombination.

Authors:
Pablo G Camara Daniel I S Rosenbloom Kevin J Emmett Arnold J Levine Raul Rabadan

Cell Syst 2016 07 23;3(1):83-94. Epub 2016 Jun 23.

Department of Systems Biology, Columbia University College of Physicians and Surgeons, 1130 St. Nicholas Avenue, New York, NY 10032, USA; Department of Biomedical Informatics, Columbia University College of Physicians and Surgeons, 1130 St. Nicholas Avenue, New York, NY 10032, USA. Electronic address:

Meiotic recombination is a fundamental evolutionary process driving diversity in eukaryotes. In mammals, recombination is known to occur preferentially at specific genomic regions. Using topological data analysis (TDA), a branch of applied topology that extracts global features from large data sets, we developed an efficient method for mapping recombination at fine scales. When compared to standard linkage-based methods, TDA can deal with a larger number of SNPs and genomes without incurring prohibitive computational costs. We applied TDA to 1,000 Genomes Project data and constructed high-resolution whole-genome recombination maps of seven human populations. Our analysis shows that recombination is generally under-represented within transcription start sites. However, the binding sites of specific transcription factors are enriched for sites of recombination. These include transcription factors that regulate the expression of meiosis- and gametogenesis-specific genes, cell cycle progression, and differentiation blockage. Additionally, our analysis identifies an enrichment for sites of recombination at repeat-derived loci matched by piwi-interacting RNAs.
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http://dx.doi.org/10.1016/j.cels.2016.05.008DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4965322PMC
July 2016

Clonal evolution of glioblastoma under therapy.

Authors:
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

Nat Genet 2016 07 6;48(7):768-76. Epub 2016 Jun 6.

Department of Systems Biology, Columbia University, New York, New York, USA.

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.
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http://dx.doi.org/10.1038/ng.3590DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5627776PMC
July 2016

Real-Time Predictions of Reservoir Size and Rebound Time during Antiretroviral Therapy Interruption Trials for HIV.

Authors:
Alison L Hill Daniel I S Rosenbloom Edward Goldstein Emily Hanhauser Daniel R Kuritzkes Robert F Siliciano Timothy J Henrich

PLoS Pathog 2016 04 27;12(4):e1005535. Epub 2016 Apr 27.

Division of Experimental Medicine, Department of Medicine, University of California, San Francisco, California, United States of America.

Monitoring the efficacy of novel reservoir-reducing treatments for HIV is challenging. The limited ability to sample and quantify latent infection means that supervised antiretroviral therapy (ART) interruption studies are generally required. Here we introduce a set of mathematical and statistical modeling tools to aid in the design and interpretation of ART-interruption trials. We show how the likely size of the remaining reservoir can be updated in real-time as patients continue off treatment, by combining the output of laboratory assays with insights from models of reservoir dynamics and rebound. We design an optimal schedule for viral load sampling during interruption, whereby the frequency of follow-up can be decreased as patients continue off ART without rebound. While this scheme can minimize costs when the chance of rebound between visits is low, we find that the reservoir will be almost completely reseeded before rebound is detected unless sampling occurs at least every two weeks and the most sensitive viral load assays are used. We use simulated data to predict the clinical trial size needed to estimate treatment effects in the face of highly variable patient outcomes and imperfect reservoir assays. Our findings suggest that large numbers of patients-between 40 and 150-will be necessary to reliably estimate the reservoir-reducing potential of a new therapy and to compare this across interventions. As an example, we apply these methods to the two "Boston patients", recipients of allogeneic hematopoietic stem cell transplants who experienced large reductions in latent infection and underwent ART-interruption. We argue that the timing of viral rebound was not particularly surprising given the information available before treatment cessation. Additionally, we show how other clinical data can be used to estimate the relative contribution that remaining HIV+ cells in the recipient versus newly infected cells from the donor made to the residual reservoir that eventually caused rebound. Together, these tools will aid HIV researchers in the evaluating new potentially-curative strategies that target the latent reservoir.
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http://dx.doi.org/10.1371/journal.ppat.1005535DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4847932PMC
April 2016

Measuring the Frequency of Latent HIV-1 in Resting CD4⁺ T Cells Using a Limiting Dilution Coculture Assay.

Authors:
Gregory M Laird Daniel I S Rosenbloom Jun Lai Robert F Siliciano Janet D Siliciano

Methods Mol Biol 2016 ;1354:239-53

Department of Medicine, Johns Hopkins University School of Medicine, 733 N. Broadway, Baltimore, MD, 21205, USA.

Combination antiretroviral therapy (cART) can reduce HIV-1 viremia to clinically undetectable levels. However, replication competent virus persists in a long-lived latent reservoir in resting, memory CD4(+) T cells. The latent reservoir in resting CD4(+) T cells is the major barrier to curing HIV-1 infection. The recent case of the Berlin patient has suggested that it may be possible to cure HIV-1 infection in certain situations. As efforts to cure HIV-1 infection progress, it will become critical to measure the latent reservoir in patients participating in clinical trials of eradication strategies. Our laboratory has developed a limiting dilution virus outgrowth assay that can be used to demonstrate the presence and persistence of latent HIV-1 in patients. Here we describe both the original and a simplified version of the quantitative virus outgrowth assay (QVOA) to measure the frequency of latently infected resting CD4(+) T cells with replication competent provirus in patients on suppressive cART.
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http://dx.doi.org/10.1007/978-1-4939-3046-3_16DOI Listing
October 2016

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

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

Open Forum Infect Dis 2015 Dec 26;2(4):ofv123. Epub 2015 Aug 26.

Department of Medicine , Johns Hopkins University School of Medicine ; Howard Hughes Medical Institute , Baltimore, Maryland.

Limiting dilution assays are widely used in infectious disease research. These assays are crucial for current human immunodeficiency virus (HIV)-1 cure research in particular. In this study, we offer new tools to help investigators design and analyze dilution assays based on their specific research needs. Limiting dilution assays are commonly used to measure the extent of infection, and in the context of HIV they represent an essential tool for studying latency and potential curative strategies. Yet standard assay designs may not discern whether an intervention reduces an already miniscule latent infection. This review addresses challenges arising in this setting and in the general use of dilution assays. We illustrate the major statistical method for estimating frequency of infectious units from assay results, and we offer an online tool for computing this estimate. We recommend a procedure for customizing assay design to achieve desired sensitivity and precision goals, subject to experimental constraints. We consider experiments in which no viral outgrowth is observed and explain how using alternatives to viral outgrowth may make measurement of HIV latency more efficient. Finally, we discuss how biological complications, such as probabilistic growth of small infections, alter interpretations of experimental results.
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http://dx.doi.org/10.1093/ofid/ofv123DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4602119PMC
December 2015

Imperfect drug penetration leads to spatial monotherapy and rapid evolution of multidrug resistance.

Authors:
Stefany Moreno-Gamez Alison L Hill Daniel I S Rosenbloom Dmitri A Petrov Martin A Nowak Pleuni S Pennings

Proc Natl Acad Sci U S A 2015 Jun 18;112(22):E2874-83. Epub 2015 May 18.

Department of Biology, Stanford University, Stanford, CA 94305; Department of Biology, San Francisco State University, San Francisco, CA 94132; and Department of Organismic and Evolutionary Biology, Harvard University, Cambridge, MA 02138

Infections with rapidly evolving pathogens are often treated using combinations of drugs with different mechanisms of action. One of the major goal of combination therapy is to reduce the risk of drug resistance emerging during a patient's treatment. Although this strategy generally has significant benefits over monotherapy, it may also select for multidrug-resistant strains, particularly during long-term treatment for chronic infections. Infections with these strains present an important clinical and public health problem. Complicating this issue, for many antimicrobial treatment regimes, individual drugs have imperfect penetration throughout the body, so there may be regions where only one drug reaches an effective concentration. Here we propose that mismatched drug coverage can greatly speed up the evolution of multidrug resistance by allowing mutations to accumulate in a stepwise fashion. We develop a mathematical model of within-host pathogen evolution under spatially heterogeneous drug coverage and demonstrate that even very small single-drug compartments lead to dramatically higher resistance risk. We find that it is often better to use drug combinations with matched penetration profiles, although there may be a trade-off between preventing eventual treatment failure due to resistance in this way and temporarily reducing pathogen levels systemically. Our results show that drugs with the most extensive distribution are likely to be the most vulnerable to resistance. We conclude that optimal combination treatments should be designed to prevent this spatial effective monotherapy. These results are widely applicable to diverse microbial infections including viruses, bacteria, and parasites.
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http://dx.doi.org/10.1073/pnas.1424184112DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4460514PMC
June 2015

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

Authors:
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

J Clin Invest 2015 May 30;125(5):1901-12. Epub 2015 Mar 30.

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.
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http://dx.doi.org/10.1172/JCI80142DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4463209PMC
May 2015

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

Authors:
Alison L Hill Daniel I S Rosenbloom Feng Fu Martin A Nowak Robert F Siliciano

Proc Natl Acad Sci U S A 2014 Sep 5;111(37):13475-80. Epub 2014 Aug 5.

Department of Medicine and Howard Hughes Medical Institute, The Johns Hopkins University School of Medicine, Baltimore, MD 21205.

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.
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http://dx.doi.org/10.1073/pnas.1406663111DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4169952PMC
September 2014

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

Authors:
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 E Peter Sheeba I 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

Nature 2014 Aug 20;512(7512):74-7. Epub 2014 Jul 20.

1] Center for Virology and Vaccine Research, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, Massachusetts 02215, USA [2] Ragon Institute of MGH, MIT and Harvard, Cambridge, Massachusetts 02139, USA.

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.
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http://dx.doi.org/10.1038/nature13594DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4126858PMC
August 2014

Frequency-dependent selection can lead to evolution of high mutation rates.

Authors:
Daniel I S Rosenbloom Benjamin Allen

Am Nat 2014 May 7;183(5):E131-53. Epub 2014 Apr 7.

Program for Evolutionary Dynamics, Harvard University, Cambridge, Massachusetts 02138.

Theoretical and experimental studies have shown that high mutation rates can be advantageous, especially in novel or fluctuating environments. Here we examine how frequency-dependent competition may lead to fluctuations in trait frequencies that exert upward selective pressure on mutation rates. We use a mathematical model to show that cyclical trait dynamics generated by "rock-paper-scissors" competition can cause the mutation rate in a population to converge to a high evolutionarily stable mutation rate, reflecting a trade-off between generating novelty and reproducing past success. Introducing recombination lowers the evolutionarily stable mutation rate but allows stable coexistence between mutation rates above and below the evolutionarily stable rate. Even considering strong mutational load and ignoring the costs of faithful replication, evolution favors positive mutation rates if the selective advantage of prevailing in competition exceeds the ratio of recombining to nonrecombining offspring. We discuss a number of genomic mechanisms that may meet our theoretical requirements for the adaptive evolution of mutation. Overall, our results suggest that local mutation rates may be higher on genes influencing cyclical competition and that global mutation rates in asexual species may be higher in populations subject to strong cyclical competition.
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http://dx.doi.org/10.1086/675505DOI Listing
May 2014

Replication-competent noninduced proviruses in the latent reservoir increase barrier to HIV-1 cure.

Authors:
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

Cell 2013 Oct 24;155(3):540-51. Epub 2013 Oct 24.

Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA.

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.
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http://dx.doi.org/10.1016/j.cell.2013.09.020DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3896327PMC
October 2013

Antiretroviral dynamics determines HIV evolution and predicts therapy outcome.

Authors:
Daniel I S Rosenbloom Alison L Hill S Alireza Rabi Robert F Siliciano Martin A Nowak

Nat Med 2012 Sep;18(9):1378-85

Department of Mathematics, Harvard University, Cambridge, Massachusetts, USA.

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.
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http://dx.doi.org/10.1038/nm.2892DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3490032PMC
September 2012

Evolutionary dynamics of HIV at multiple spatial and temporal scales.

Authors:
Alison L Hill Daniel I S Rosenbloom Martin A Nowak

J Mol Med (Berl) 2012 May 3;90(5):543-61. Epub 2012 May 3.

Program for Evolutionary Dynamics, Department of Mathematics, Harvard University, Cambridge, MA 02138, USA.

Infectious diseases remain a formidable challenge to human health, and understanding pathogen evolution is crucial to designing effective therapeutics and control strategies. Here, we review important evolutionary aspects of HIV infection, highlighting the concept of selection at multiple spatial and temporal scales. At the smallest scale, a single cell may be infected by multiple virions competing for intracellular resources. Recombination and phenotypic mixing introduce novel evolutionary dynamics. As the virus spreads between cells in an infected individual, it continually evolves to circumvent the immune system. We discuss evolutionary mechanisms of HIV pathogenesis and progression to AIDS. Viral spread throughout the human population can lead to changes in virulence and the transmission of immune-evading variation. HIV emerged as a human pathogen due to selection occurring between different species, adapting from related viruses of primates. HIV also evolves resistance to antiretroviral drugs within a single infected host, and we explore the possibility for the spread of these strains between hosts, leading to a drug-resistant epidemic. We investigate the role of latency, drug-protected compartments, and direct cell-to-cell transmission on viral evolution. The introduction of an HIV vaccine may select for viral variants that escape vaccine control, both within an individual and throughout the population. Due to the strong selective pressure exerted by HIV-induced morbidity and mortality in many parts of the world, the human population itself may be co-evolving in response to the HIV pandemic. Throughout the paper, we focus on trade-offs between costs and benefits that constrain viral evolution and accentuate how selection pressures differ at different levels of selection.
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http://dx.doi.org/10.1007/s00109-012-0892-1DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7080006PMC
May 2012