Hieu Nguyen

All Publications

• Ultrasensitive and multiplexed tracking of single cells using whole-body PET/CT. Science advances Nguyen, H. T., Das, N., Ricks, M., Zhong, X., Takematsu, E., Wang, Y., Ruvalcaba, C., Mehadji, B., Roncali, E., Chan, C. K., Pratx, G. 2024; 10 (24): eadk5747

  Abstract

  In vivo molecular imaging tools are crucially important for elucidating how cells move through complex biological systems; however, achieving single-cell sensitivity over the entire body remains challenging. Here, we report a highly sensitive and multiplexed approach for tracking upward of 20 single cells simultaneously in the same subject using positron emission tomography (PET). The method relies on a statistical tracking algorithm (PEPT-EM) to achieve a sensitivity of 4 becquerel per cell and a streamlined workflow to reliably label single cells with over 50 becquerel per cell of 18F-fluorodeoxyglucose (FDG). To demonstrate the potential of the method, we tracked the fate of more than 70 melanoma cells after intracardiac injection and found they primarily arrested in the small capillaries of the pulmonary, musculoskeletal, and digestive organ systems. This study bolsters the evolving potential of PET in offering unmatched insights into the earliest phases of cell trafficking in physiological and pathological processes and in cell-based therapies.

  View details for DOI 10.1126/sciadv.adk5747

  View details for PubMedID 38875333

  View details for PubMedCentralID PMC11177933

• Increased [18F]FDG uptake of radiation-induced giant cells: a single-cell study in lung cancer models. Npj imaging Das, N., Nguyen, H. T., Lu, W. J., Natarajan, A., Khan, S., Pratx, G. 2024; 2 (1): 14

  Abstract

  Positron emission tomography (PET), a cornerstone in cancer diagnosis and treatment monitoring, relies on the enhanced uptake of fluorodeoxyglucose ([18F]FDG) by cancer cells to highlight tumors and other malignancies. While instrumental in the clinical setting, the accuracy of [18F]FDG-PET is susceptible to metabolic changes introduced by radiation therapy. Specifically, radiation induces the formation of giant cells, whose metabolic characteristics and [18F]FDG uptake patterns are not fully understood. Through a novel single-cell gamma counting methodology, we characterized the [18F]FDG uptake of giant A549 and H1299 lung cancer cells that were induced by radiation, and found it to be considerably higher than that of their non-giant counterparts. This observation was further validated in tumor-bearing mice, which similarly demonstrated increased [18F]FDG uptake in radiation-induced giant cells. These findings underscore the metabolic implications of radiation-induced giant cells, as their enhanced [18F]FDG uptake could potentially obfuscate the interpretation of [18F]FDG-PET scans in patients who have recently undergone radiation therapy.

  View details for DOI 10.1038/s44303-024-00017-3

  View details for PubMedID 38912527

  View details for PubMedCentralID PMC11186760

• Radioluminescence from polymer dots based on thermally activated delayed fluorescence NANOSCALE ADVANCES Asanuma, D., Nguyen, H., Liu, Z., Tojo, S., Shigemitsu, H., Yamaji, M., Kawai, K., Mori, T., Kida, T., Pratx, G., Fujitsuka, M., Osakada, Y. 2023

  View details for DOI 10.1039/d3na00308f

  View details for Web of Science ID 000998986500001

• Red, green, and blue radio-luminescent polymer dots doped with heteroleptic tris-cyclometalated iridium complexes. RSC advances Liu, Z., Nguyen, H. T., Asanuma, D., Tojo, S., Yamaji, M., Kawai, K., Pratx, G., Fujitsuka, M., Osakada, Y. 2023; 13 (22): 15126-15131

  Abstract

  In this study, we synthesized radioexcitable luminescent polymer dots (P-dots) doped with heteroleptic tris-cyclometalated iridium complexes that emit red, green, and blue light. We investigated the luminescence properties of these P-dots under X-ray and electron beam irradiation, revealing their potential as new organic scintillators.

  View details for DOI 10.1039/d3ra01216f

  View details for PubMedID 37207100

  View details for PubMedCentralID PMC10190261

• Preclinical evaluation of 89Zr-Panitumumab for biology-guided radiotherapy. International journal of radiation oncology, biology, physics Natarajan, A., Khan, S., Liang, X., Nguyen, H., Das, N., Anders, D., Malik, N., Oderinde, O. M., Chin, F., Rosenthal, E., Pratx, G. 2023

  Abstract

  Biology-guided radiotherapy (BgRT) uses real-time line-of-response data from on-board PET detectors to guide beamlet delivery during therapeutic radiation. The current workflow requires 18F-fluorodeoxyglucose (FDG) administration daily prior to each treatment fraction. However, there are advantages to reducing the number of tracer injections by using a PET tracer with a longer decay time. In this context, we investigated 89Zr-Panitumumab (89Zr-Pan), an antibody PET tracer with a half-life of 78 hours that can be imaged for up to 9 days using PET.The BgRT workflow was evaluated pre-clinically in mouse colorectal cancer xenografts (HCT116) using small-animal PET/CT for imaging, and image-guided kilovoltage conformal irradiation for therapy. Mice (n=5 per group) received 7 MBq of 89Zr-Pan as a single dose 2 weeks after tumor induction, with or without fractionated radiation therapy (RT; 6×6.6 Gy) to the tumor region. The mice were imaged longitudinally to assess the kinetics of the tracer over 9 days. PET images were then analyzed to determine the stability of the PET signal in irradiated tumors over time.Mice in the treatment group experienced complete tumor regression, whereas those in the control group were sacrificed due to tumor burden. PET imaging of 89Zr-Pan showed well-delineated tumors with minimal background in both groups. On day 9 post-injection, tumor uptake of 89Zr-Pan was 7.2 ± 1.7 in the control group vs 5.2 ± 0.5 in the treatment group (mean %ID/g ± SD; P = 0.07), both significantly higher than FDG uptake (1.1 ± 0.5 %ID/g) 1 hour post injection. To assess BgRT feasibility, the clinical eligibility criteria was computed using human-equivalent uptake values that were extrapolated from preclinical PET data. Based on this semiquantitative analysis, BgRT may be feasible for 5 consecutive days following a single 740 MBq injection of 89Zr-Pan.This study indicates the potential of long-lived antibody-based PET tracers for guiding clinical BgRT.

  View details for DOI 10.1016/j.ijrobp.2023.01.007

  View details for PubMedID 36669541

• Characterization of Ex Vivo Nonmelanoma Skin Tissue Using Raman Spectroscopy PHOTONICS Nguyen, H. M., Zhang, Y., Moy, A. J., Feng, X., Sebastian, K. R., Reichenberg, J. S., Fox, M. C., Markey, M. K., Tunnell, J. W. 2021; 8 (7)

  View details for DOI 10.3390/photonics8070282

  View details for Web of Science ID 000676683600001

• Laser nanobubbles induce immunogenic cell death in breast cancer. Nanoscale Nguyen, H. T., Katta, N., Widman, J. A., Takematsu, E., Feng, X., Torres-Hurtado, S. A., Betancourt, T., Baker, A. B., Suggs, L. J., Milner, T. E., Tunnell, J. W. 2021; 13 (6): 3644-3653

  Abstract

  Recent advances in immunotherapy have highlighted a need for therapeutics that initiate immunogenic cell death in tumors to stimulate the body's immune response to cancer. This study examines whether laser-generated bubbles surrounding nanoparticles ("nanobubbles") induce an immunogenic response for cancer treatment. A single nanosecond laser pulse at 1064 nm generates micron-sized bubbles surrounding gold nanorods in the cytoplasm of breast cancer cells. Cell death occurred in cells treated with nanorods and irradiated, but not in cells with irradiation treatment alone. Cells treated with nanorods and irradiation had increased damage-associated molecular patterns (DAMPs), including increased expression of chaperone proteins human high mobility group box 1 (HMGB1), adenosine triphosphate (ATP), and heat shock protein 70 (HSP70). This enhanced expression of DAMPs led to the activation of dendritic cells. Overall, this treatment approach is a rapid and highly specific method to eradicate tumor cells with simultaneous immunogenic cell death signaling, showing potential as a combination strategy for immunotherapy.

  View details for DOI 10.1039/d0nr06587k

  View details for PubMedID 33538275

  View details for PubMedCentralID PMC8710258

• Assessment of Raman Spectroscopy for Reducing Unnecessary Biopsies for Melanoma Screening. Molecules (Basel, Switzerland) Zhang, Y., Moy, A. J., Feng, X., Nguyen, H. T., Sebastian, K. R., Reichenberg, J. S., Wilke, C. O., Markey, M. K., Tunnell, J. W. 2020; 25 (12)

  Abstract

  A key challenge in melanoma diagnosis is the large number of unnecessary biopsies on benign nevi, which requires significant amounts of time and money. To reduce unnecessary biopsies while still accurately detecting melanoma lesions, we propose using Raman spectroscopy as a non-invasive, fast, and inexpensive method for generating a "second opinion" for lesions being considered for biopsy. We collected in vivo Raman spectral data in the clinical skin screening setting from 52 patients, including 53 pigmented lesions and 7 melanomas. All lesions underwent biopsies based on clinical evaluation. Principal component analysis and logistic regression models with leave one lesion out cross validation were applied to classify melanoma and pigmented lesions for biopsy recommendations. Our model achieved an area under the receiver operating characteristic (ROC) curve (AUROC) of 0.903 and a specificity of 58.5% at perfect sensitivity. The number needed to treat for melanoma could have been decreased from 8.6 (60/7) to 4.1 (29/7). This study in a clinical skin screening setting shows the potential of Raman spectroscopy for reducing unnecessary skin biopsies with in vivo Raman data and is a significant step toward the application of Raman spectroscopy for melanoma screening in the clinic.

  View details for DOI 10.3390/molecules25122852

  View details for PubMedID 32575717

  View details for PubMedCentralID PMC7355922

• Diffuse reflectance spectroscopy as a potential method for nonmelanoma skin cancer margin assessment Translational Biophotonics Zhang, Y., Moy, A. J., Nguyen, H. T., Sebastian, K. R., Reichenberg, J. S., Markey, M. K., Tunnell, J. W. 2020; 2

  View details for DOI 10.1002/tbio.202000001

• Physiological model using diffuse reflectance spectroscopy for nonmelanoma skin cancer diagnosis. Journal of biophotonics Zhang, Y., Moy, A. J., Feng, X., Nguyen, H. T., Reichenberg, J. S., Markey, M. K., Tunnell, J. W. 2019; 12 (12): e201900154

  Abstract

  Diffuse reflectance spectroscopy (DRS) is a noninvasive, fast, and low-cost technology with potential to assist cancer diagnosis. The goal of this study was to test the capability of our physiological model, a computational Monte Carlo lookup table inverse model, for nonmelanoma skin cancer diagnosis. We applied this model on a clinical DRS dataset to extract scattering parameters, blood volume fraction, oxygen saturation and vessel radius. We found that the model was able to capture physiological information relevant to skin cancer. We used the extracted parameters to classify (basal cell carcinoma [BCC], squamous cell carcinoma [SCC]) vs actinic keratosis (AK) and (BCC, SCC, AK) vs normal. The area under the receiver operating characteristic curve achieved by the classifiers trained on the parameters extracted using the physiological model is comparable to that of classifiers trained on features extracted via Principal Component Analysis. Our findings suggest that DRS can reveal physiologic characteristics of skin and this physiologic model offers greater flexibility for diagnosing skin cancer than a pure statistical analysis. Physiological parameters extracted from diffuse reflectance spectra data for nonmelanoma skin cancer diagnosis.

  View details for DOI 10.1002/jbio.201900154

  View details for PubMedID 31325232

• Raman biophysical markers in skin cancer diagnosis. Journal of biomedical optics Feng, X., Moy, A. J., Nguyen, H. T., Zhang, Y., Zhang, J., Fox, M. C., Sebastian, K. R., Reichenberg, J. S., Markey, M. K., Tunnell, J. W. 2018; 23 (5): 1-10

  Abstract

  Raman spectroscopy (RS) has demonstrated great potential for in vivo cancer screening; however, the biophysical changes that occur for specific diagnoses remain unclear. We recently developed an inverse biophysical skin cancer model to address this issue. Here, we presented the first demonstration of in vivo melanoma and nonmelanoma skin cancer (NMSC) detection based on this model. We fit the model to our previous clinical dataset and extracted the concentration of eight Raman active components in 100 lesions in 65 patients diagnosed with malignant melanoma (MM), dysplastic nevi (DN), basal cell carcinoma, squamous cell carcinoma, and actinic keratosis. We then used logistic regression and leave-one-lesion-out cross validation to determine the diagnostically relevant model components. Our results showed that the biophysical model captures the diagnostic power of the previously used statistical classification model while also providing the skin's biophysical composition. In addition, collagen and triolein were the most relevant biomarkers to represent the spectral variances between MM and DN, and between NMSC and normal tissue. Our work demonstrates the ability of RS to reveal the biophysical basis for accurate diagnosis of different skin cancers, which may eventually lead to a reduction in the number of unnecessary excisional skin biopsies performed.

  View details for DOI 10.1117/1.JBO.23.5.057002

  View details for PubMedID 29752800

• Raman active components of skin cancer. Biomedical optics express Feng, X., Moy, A. J., Nguyen, H. T., Zhang, J., Fox, M. C., Sebastian, K. R., Reichenberg, J. S., Markey, M. K., Tunnell, J. W. 2017; 8 (6): 2835-2850

  Abstract

  Raman spectroscopy (RS) has shown great potential in noninvasive cancer screening. Statistically based algorithms, such as principal component analysis, are commonly employed to provide tissue classification; however, they are difficult to relate to the chemical and morphological basis of the spectroscopic features and underlying disease. As a result, we propose the first Raman biophysical model applied to in vivo skin cancer screening data. We expand upon previous models by utilizing in situ skin constituents as the building blocks, and validate the model using previous clinical screening data collected from a Raman optical fiber probe. We built an 830nm confocal Raman microscope integrated with a confocal laser-scanning microscope. Raman imaging was performed on skin sections spanning various disease states, and multivariate curve resolution (MCR) analysis was used to resolve the Raman spectra of individual in situ skin constituents. The basis spectra of the most relevant skin constituents were combined linearly to fit in vivo human skin spectra. Our results suggest collagen, elastin, keratin, cell nucleus, triolein, ceramide, melanin and water are the most important model components. We make available for download (see supplemental information) a database of Raman spectra for these eight components for others to use as a reference. Our model reveals the biochemical and structural makeup of normal, nonmelanoma and melanoma skin cancers, and precancers and paves the way for future development of this approach to noninvasive skin cancer diagnosis.

  View details for DOI 10.1364/BOE.8.002835

  View details for PubMedID 28663910

  View details for PubMedCentralID PMC5480433