Charles M. Roth
· Professor, Department ChairVerifiedRutgers University · Cellular, Molecular and Biomedical Sciences
Active 1928–2026
About
Charles M. Roth is a Professor and Department Chair in the Department of Biomedical Engineering at Rutgers University. He holds a Ph.D. in Chemical Engineering from the University of Delaware and completed postdoctoral training in Bioengineering at Harvard Medical School. His research involves the application of molecular and nanobioengineering approaches to biomedical problems such as cancer and infection. His work centers on developing technology for the efficient delivery of oligonucleotides for gene silencing and antimicrobial drugs for infection control. Current projects include aerosolized nanomedicine for lung infections, nanomaterials for antimicrobial drug delivery to wounds, and physiologically based pharmacokinetic modeling of nanomedicines. Dr. Roth has received numerous honors, including the 2015 Outstanding Engineering Faculty Award at Rutgers, fellowship in the American Institute of Medical and Biological Engineering, and several awards for teaching and research excellence. He is actively involved in various research programs and has contributed significantly to the field of biomedical engineering through his innovative research and leadership.
Research topics
- Cancer research
- Genetics
- Medicine
- Biology
- Computational biology
- Biophysics
- Materials science
- Nanotechnology
- Biomedical engineering
- Optics
- Ecology
- Chemistry
Selected publications
Aerosol Delivery of Polyelectrolyte Surfactant—Antimicrobial Nanoparticles to the Lungs
Pharmaceutical Research · 2026-01-09
articleOpen accessSenior authorBACKGROUND: Lung infections affect over 80% of adults with cystic fibrosis, with Pseudomonas aeruginosa being a leading pathogen. Although antibiotics are frequently nebulized as standard treatments, the physicochemical environment of the diseased lung often limits their diffusion and overall effectiveness. Our previous studies showed polyelectrolyte surfactants (PS) to be a promising delivery system for cationic antimicrobials in vitro. This study seeks to expand that knowledge by evaluating their potential for nebulized delivery. METHODS: To achieve this, we evaluated their size and antimicrobial activity following nebulization; in vitro toxicity against epithelial cells and erythrocytes; and biodistribution and expression of inflammation markers following administration to healthy mice. RESULTS: The nanoparticle formulation exhibited a mucolytic effect on an artificial mucus model of cystic fibrosis mucus. Following nebulization, nanoparticles retained both their size and biological activity. Additionally, they displayed no observable toxicity in vitro against either human lung epithelial cells or erythrocytes; instead, epithelial cells treated with PS-based nanoparticles showed increased cell viability. Following administration of these formulations to mice via inhalation, over 70% of the recovered nanoparticles were retained in the lungs 24 h after treatment, with a small fraction being uniformly distributed to other tissues. A screen of key inflammatory cytokines revealed that inhalation treatment led to a slight increase of IL-6 in the liver and IL-18 in the spleen. These increases seem to be consistent with a minor inflammatory response. CONCLUSION: Overall, the results suggest that PS are a promising nanotechnology for the pulmonary delivery of cationic drugs.
bioRxiv (Cold Spring Harbor Laboratory) · 2025-07-04 · 1 citations
preprintOpen accessSenior authorCorrespondingABSTRACT Nearly 80% of cystic fibrosis patients are affected by persistent lung infections, with Pseudomonas aeruginosa being one of the major culprits. Treatment of P. aeruginosa is further complicated by its ability to form biofilms. Anionic compounds within the biofilm and thick cystic fibrosis mucus interact with cationic antimicrobials, hindering treatment efficacy. In this study, we investigated the treatment of lung infections by delivering antimicrobials via polyelectrolyte surfactants that are composed of an anionic poly(alkylacrylic acid) backbone with grafted polyetheramine pendent chains. When combined with cationic antimicrobials, they self-assemble into nanoparticles via electrostatic interactions. We assessed the role of backbone chemistry and graft density on nanoparticle physical properties and evaluated the antimicrobial activity of these formulations against planktonic and biofilm cultures of P. aeruginosa strains derived from clinical isolates. All synthesized polyelectrolyte surfactants demonstrated high levels of antimicrobial encapsulation, with the extent of drug bound corresponding to the calculated hydrophilic-lipophilic balance values. We observed significantly increased antimicrobial activity against planktonic cultures using nanoformulations containing one of the polyelectrolyte surfactants, PMAA-g-10%J. In contrast, all tested nanoformulations retained, but did not increase, activity against biofilms. By monitoring membrane potentials and nanoparticle uptake, it was found that the nanoparticles directly associate with the bacterial cell membranes, which may enhance drug delivery and underlie the improved activity against the planktonic bacteria. In conclusion, we provide a proof of concept for the design of polyelectrolyte surfactants for the nanoencapsulation and delivery of cationic drug cargoes against P. aeruginosa infections.
Simulating Interclonal Interactions in Diffuse Large B-Cell Lymphoma
Bioengineering · 2023-11-27 · 3 citations
articleOpen accessDiffuse large B-cell lymphoma (DLBCL) is one of the most common types of cancers, accounting for 37% of B-cell tumor cases globally. DLBCL is known to be a heterogeneous disease, resulting in variable clinical presentations and the development of drug resistance. One underexplored aspect of drug resistance is the evolving dynamics between parental and drug-resistant clones within the same microenvironment. In this work, the effects of interclonal interactions between two cell populations-one sensitive to treatment and the other resistant to treatment-on tumor growth behaviors were explored through a mathematical model. In vitro cultures of mixed DLBCL populations demonstrated cooperative interactions and revealed the need for modifying the model to account for complex interactions. Multiple best-fit models derived from in vitro data indicated a difference in steady-state behaviors based on therapy administrations in simulations. The model and methods may serve as a tool for understanding the behaviors of heterogeneous tumors and identifying the optimal therapeutic regimen to eliminate cancer cell populations using computer-guided simulations.
Simulating Interclonal Interactions in Diffuse Large B-Cell Lymphoma
bioRxiv (Cold Spring Harbor Laboratory) · 2023-09-29
preprintOpen accessAbstract Diffuse large B-cell lymphoma (DLBCL) is one of the most common types of cancers, accounting for 37% of B-cell tumors globally. DLBCL is known to be a heterogeneous disease, resulting in variable clinical presentations and the development of drug resistance. One underexplored aspect of drug resistance is the evolving dynamics between parental and drug-resistant clones with the same microenvironment. In this work, the effects of interclonal interactions between two cell populations - one sensitive to treatment and another resistant to treatment - on tumor growth behaviors were explored through a mathematical model. In vitro cultures of mixed DLBCL populations demonstrated cooperative interactions and revealed the need for modifying the model to account for complex interactions. Multiple best-fit models derived from in vitro data indicated a difference in steady-state behaviors based on therapy administrations in simulations. The model and methods may serve as a tool in understanding the behaviors of heterogeneous tumors and in identifying the optimal therapeutic regimen to eliminate cancer cell populations using computer-guided simulations. Importance The cellular makeup of tumors can play a vital role in its growth and cancer development. In this work, two different types of cell populations of diffuse large B-cell lymphoma (DLBCL) were studied together to understand how they interact with each other in cultures. In mixed cultures, both types of cells cooperated with each other and increased their growth in complex manners. A mathematical model was created to simulate the growth behavior of mixed cultures. The model can potentially be used to predict future cell behavior and help in identifying more effective therapy regimens to maximize tumor cell reduction.
Biomedicines · 2023-08-21 · 2 citations
articleOpen accessSenior authorCorrespondingAccurate pharmacokinetic–pharmacodynamic (PK-PD) models of biofilm treatment could be used to guide formulation and administration strategies to better control bacterial lung infections. To this end, we developed a detailed pharmacodynamic model of P. aeruginosa treatment with the front-line antibiotics, tobramycin and colistin, and validated it on a detailed dataset of killing dynamics. A compartmental model structure was developed in which the key features are the diffusion of the drug through a boundary layer to the bacteria, concentration-dependent interactions with bacteria, and the passage of the bacteria through successive transit states before death. The number of transit states employed was greater for tobramycin, which is a ribosomal inhibitor, than for colistin, which disrupts bacterial membranes. For both drugs, the experimentally observed delay in the killing of bacteria following drug exposure was consistent with the sum of the diffusion time and the time for passage through the transit states. For each drug, the PD model with a single set of parameters described data across a ten-fold range of concentrations and for both continuous and transient exposure protocols, as well as for combined drug treatments. The ability to predict drug response over a range of administration protocols allows this PD model to be integrated with PK descriptions to describe in vivo antibiotic response dynamics and to predict drug delivery strategies for the improved control of bacterial lung infections.
Allometric-like scaling of AAV gene therapy for systemic protein delivery
Molecular Therapy — Methods & Clinical Development · 2022 · 19 citations
- Computational biology
- Medicine
- Biology
kinetic secretion data laying groundwork for future customization and model-informed dose justification for AAV candidates.
bioRxiv (Cold Spring Harbor Laboratory) · 2022-07-31
preprintOpen accessSenior authorCorrespondingAbstract Chronic infection by gram-negative bacteria such as Pseudomonas aeruginosa is a leading cause of morbidity and mortality in cystic fibrosis patients in whom overabundant mucus and the formation of bacterial biofilms pose barriers to drug delivery and effectiveness. Accurate pharmacokinetic-pharmacodynamic (PK-PD) models of biofilm treatment could be used to guide formulation and administration strategies to better control bacterial lung infections. To this end, we have developed a detailed pharmacodynamic model of P. aeruginosa treatment with the front-line antibiotics, tobramycin and colistin, and validated it on a detailed dataset of killing dynamics. A compartmental model structure was developed in which the key features are diffusion of drug through a boundary layer to the bacteria, concentration dependent interactions with bacteria, and passage of the bacteria through successive transit states before death. The number of transit states employed was greater for tobramycin, which is a ribosomal inhibitor, than for colistin, which disrupts bacterial membranes. For both drugs, the experimentally observed delay in killing of bacteria following drug exposure was replicated and was consistent with the diffusion time, though for tobramycin, there was an additional delay reflected in the model by passage through the transit states. For each drug, the PD model with a single set of parameters described data across a ten-fold range of concentrations and for both continuous and transient exposure protocols. Furthermore, the parameters fit for each drug individually were used to model the response of biofilms to combined treatment with tobramycin and colistin. The ability to predict drug response over a range of administration protocols allows this PD model to be integrated with PK descriptions to describe in vivo antibiotic response dynamics and to predict drug delivery strategies for improved control of bacterial lung infections. Author Summary Biofilms are self-assembling bacterial communities that adhere to a surface and encase themselves in a protective coating. Biofilm infections are notoriously difficult to treat with conventional antibiotic administrations. To understand better the dynamics of bacterial biofilm killing in response to antibiotic treatment, we developed a mathematical model that integrates several features: drug diffusion through a boundary layer that includes the biofilm casing, concentration dependent cell damage, and passage of the cell through damaged states to eventual death. We validated the model by comparison with an extensive published dataset of biofilm response to treatment with the antibiotics, tobramycin and colistin. The model fits to these datasets were able to capture the observed trends for several antibiotic administration protocols, with model parameters reflecting the differences in mechanism of action between the two drugs. This validated model can be integrated with pharmacokinetic descriptions of drug distribution in the body over time to predict dosing and administration protocols for preclinical and clinical studies.
Gene silencing of HIF-2α disrupts glioblastoma stem cell phenotype
Cancer Drug Resistance · 2020 · 24 citations
Senior authorCorresponding- Biology
- Cancer research
- Genetics
AIM: Improved treatment strategies are desperately needed for eradicating cancer stem cells (CSCs), which drive malignancy and recurrence in glioblastoma multiforme. Hypoxic regions within the tumor microenvironment help maintain and promote the proliferation of CSCs. Here, we explored the effects of silencing hypoxia inducible factor-2α (HIF-2α) because of its specificity for CSCs within the hypoxic environment. METHODS: Cancer stem cell neurospheres were formed by enriching from both the glioblastoma cell line U87 and from brain tumor stem cells isolated directly from human brain tumors. Silencing of human HIF-2α was performed using both commercial and in-house transfection of a validated short interfering RNA, with all results compared to an established non-silencing control short interfering RNA. Silencing of HIF-2α was established by Western blotting, and phenotypic effects were assayed by cell migration assays, cell viability measurements, and immunofluorescence staining of differentiation markers. RESULTS: Transfection with either our previously reported pH-sensitive, cationic amphiphilic macromolecule-based delivery system or Lipofectamine was similarly effective in silencing HIF-2α. The chemotherapeutic resistance and neurosphere formation were reduced when HIF-2α was silenced. Migratory capacities in the presence of macrophage conditioned media were modulated. HIF-2α silencing was complementary to temozolomide treatment in producing phenotypic rather than cytotoxic effects. CONCLUSION: HIF-2α silencing under hypoxia inhibited CSC phenotypes while promoting differentiated cell phenotypes and is complementary to existing DNA alkylating treatments in inhibiting glioma CSC activity.
Shortwave infrared emitting multicolored nanoprobes for biomarker-specific cancer imaging in vivo
BMC Cancer · 2020 · 11 citations
- Materials science
- Cancer research
- Nanotechnology
BACKGROUND: The ability to detect tumor-specific biomarkers in real-time using optical imaging plays a critical role in preclinical studies aimed at evaluating drug safety and treatment response. In this study, we engineered an imaging platform capable of targeting different tumor biomarkers using a multi-colored library of nanoprobes. These probes contain rare-earth elements that emit light in the short-wave infrared (SWIR) wavelength region (900-1700 nm), which exhibits reduced absorption and scattering compared to visible and NIR, and are rendered biocompatible by encapsulation in human serum albumin. The spectrally distinct emissions of the holmium (Ho), erbium (Er), and thulium (Tm) cations that constitute the cores of these nanoprobes make them attractive candidates for optical molecular imaging of multiple disease biomarkers. METHODS: SWIR-emitting rare-earth-doped albumin nanocomposites (ReANCs) were synthesized using controlled coacervation, with visible light-emitting fluorophores additionally incorporated during the crosslinking phase for validation purposes. Specifically, HoANCs, ErANCs, and TmANCs were co-labeled with rhodamine-B, FITC, and Alexa Fluor 647 dyes respectively. These Rh-HoANCs, FITC-ErANCs, and 647-TmANCs were further conjugated with the targeting ligands daidzein, AMD3100, and folic acid respectively. Binding specificities of each nanoprobe to distinct cellular subsets were established by in vitro uptake studies. Quantitative whole-body SWIR imaging of subcutaneous tumor bearing mice was used to validate the in vivo targeting ability of these nanoprobes. RESULTS: Each of the three ligand-functionalized nanoprobes showed significantly higher uptake in the targeted cell line compared to untargeted probes. Increased accumulation of tumor-specific nanoprobes was also measured relative to untargeted probes in subcutaneous tumor models of breast (4175 and MCF-7) and ovarian cancer (SKOV3). Preferential accumulation of tumor-specific nanoprobes was also observed in tumors overexpressing targeted biomarkers in mice bearing molecularly-distinct bilateral subcutaneous tumors, as evidenced by significantly higher signal intensities on SWIR imaging. CONCLUSIONS: The results from this study show that tumors can be detected in vivo using a set of targeted multispectral SWIR-emitting nanoprobes. Significantly, these nanoprobes enabled imaging of biomarkers in mice bearing bilateral tumors with distinct molecular phenotypes. The findings from this study provide a foundation for optical molecular imaging of heterogeneous tumors and for studying the response of these complex lesions to targeted therapy.
Cancer Research · 2018-07-01
articleAbstract Breast cancer is made up of distinct heterogeneous subpopulations that influence treatment responses. Currently, molecular phenotyping of a tumor involves post-biopsy histology, which makes quantification and assessment of spatial heterogeneity difficult. While there has been moderate success in radiographic imaging of heterogeneity, by PET and MRI, there is an urgent need for non-invasive imaging modalities to quantitatively index tumor heterogeneity in real-time. Our study utilizes rare earth(Re) nanoprobes which absorb near infrared radiation (980nm) and emit in the short wave infrared (SWIR) region (1000- 3000nm), allowing for improved tissue penetration and detection depth. We designed Re nanoprobes encapsulated in albumin to form Rare-Earth Albumin NanoComposites (ReANCs), which can be administered in vivo to target and detect deep tissue microlesions (~18mm3) at a depth of ~1cm. Additionally, ReANCs have been shown to detect multi-organ micro-lesions early and have excellent safety and tolerability profile. Albumin encapsulation not only creates a biocompatible nanoparticle, but also allows for increased biodistribution, pharmacokinetics, and the possibility of functionalization. Most notably, the availability of different Re dopants, Erbium and Thulium, with distinct emission spectral bands allows for accurate indexing of cellular subsets. In this study, we first demonstrate the ability of multi-spectral, ReANCs to distinguish and map a heterogeneous tumor lesion. 3D spheroids made of varying ratios of prelabeled populations of MDA-MB-231 cells (erbium-doped) and HCC1954 (thulium doped) were engineered and imaged to obtain a training set for spatial mapping of the different cell populations. Ratiometric analysis of the spheroids was performed to develop an algorithm for indexing. Subsequently, cancer-targeted ReANCs were engineered and target validation was performed in a 3D spheroid model followed by spatial mapping of targeted populations leading to ratiometric indexing of the different populations. Briefly, erbium doped ReANCs (MDA-MB-231 cells) and thulium doped ReANCs (HCC1954 cells), were deployed to detect distinct subpopulations in a 3D heterogeneous spheroid model of Her2+/- breast cancer. Images were obtained using in vitro microscopy platforms, using 980 nm excitation sources. Separate band-pass filters isolated emissions from the distinct REANC dopants, allowing for quantification of each pre-labeled cell in the training set. This was followed by development of an algorithm to find the percentage of subsets with unknown proportions allowing indexing of unknown subsets in a single tumor spheroid. This novel in vivo imaging modality forms the early basis for real-time on molecular aspects of the tumor and real-time tumor response tracking. Citation Format: Harini Kantamneni, Michael Donzanti, Xinyu Zhao, Shuqing He, Mei Chee Tan, Mark Pierce, Charles M. Roth, Shridar Ganesan, Vidya Ganapathy, Prabhas V. Moghe. Spatial mapping and molecular phenotyping of heterogeneous breast cancer lesions with multi-spectral short wave infrared emitting rare-earth nanoprobes [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 4119.
Recent grants
NIH · $1.1M · 2008
NIH · $688k · 2012
NIH · $407k · 2015
CAREER: Molecular Systems Bioengineering
NSF · $424k · 2003–2009
RARE EARTH NANOPROBES FOR OPTICAL IMAGING AND DISEASE TRACKING
NIH · $4.3M · 2014–2025
Frequent coauthors
- 85 shared
Martin L. Yarmush
Shriners Hospitals for Children - Boston
- 40 shared
S. Patrick Walton
- 30 shared
Jeffrey R. Morgan
Providence College
- 21 shared
Joseph M. Le Doux
The Wallace H. Coulter Department of Biomedical Engineering
- 19 shared
Arul Jayaraman
Texas A&M University
- 19 shared
Prabhas V. Moghe
Rutgers, The State University of New Jersey
- 16 shared
Stelios T. Andreadis
Center for Excellence in Education
- 14 shared
Richard E. Riman
Education
- 1985
Ph.D., Biomedical Engineering
University of California, San Diego
- 1981
M.S., Biomedical Engineering
University of California, San Diego
- 1978
B.S., Electrical Engineering
University of California, San Diego
Awards & honors
- Outstanding Engineering Faculty Award, Rutgers University (2…
- Fellow, American Institute of Medical and Biological Enginee…
- Warren I. Susman Award for Excellence in Teaching (2008)
- Rutgers, FASIP Award for Teaching, Research and Service (200…
- NSF Faculty CAREER Award (2003)
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