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29 results on '"Nizzero, Sara"'

1. Education and Outreach in Physical Sciences in Oncology

Author

Walker, Sierra A., Pham, Anthony, Nizzero, Sara, Kim, Mingee, Riter, Bob, Bletz, Julie, Judge, Sheila, Phillips, Benette, Noble, Dorottya, Murray, Diana, Wetzel, Erin, Samson, Susan, McMahon, Mariah, Flink, Carl, Couch, Jennifer, Tomlin, Claire, Swanson, Kristin, Anderson, Alexander R.A., Odde, David, Shen, Haifa, Hughes, Shannon, Zahir, Nastaran, Enderling, Heiko, and Wolfram, Joy

Published
2021
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2. Enhanced tumor control and survival in preclinical models with adoptive cell therapy preceded by low-dose radiotherapy.

Author

Puebla-Osorio, Nahum, Fowlkes, Natalie Wall, Barsoumian, Hampartsoum B., Xega, Kristina, Srivastava, Gitika, Kettlun-Leyton, Claudia, Nizzero, Sara, Voss, Tiffany, Riad, Thomas S., Wong, Christina, Huang, Ailing, Yun Hu, Mitchell, Joylise, Mingee Kim, Rafiq, Zahid, Kewen He, Sezen, Duygu, Hsu, Ethan, Masrorpour, Fatemeh, and Maleki, Aurian

Subjects
CHIMERIC antigen receptors, ATOMIC force microscopy, TREATMENT effectiveness, TUMOR growth, SURVIVAL rate
Abstract

Introduction: Effective infiltration of chimeric antigen receptor T (CAR-T) cells into solid tumors is critical for achieving a robust antitumor response and improving therapeutic outcomes. While CAR-T cell therapies have succeeded in hematologic malignancies, their efficacy in solid tumors remains limited due to poor tumor penetration and an immunosuppressive tumor microenvironment. This study aimed to evaluate the potential of low-dose radiotherapy (LDRT) administered before T-cell therapy to enhance the antitumor effect by promoting CAR-T cell infiltration. We hypothesized that combining LDRT with T-cell therapy would improve tumor control and survival compared to either treatment alone. Methods: We investigated this hypothesis using two NSG mouse models bearing GSU or CAPAN-2 solid tumors. The mice were treated with engineered CAR-T cells targeting guanyl cyclase-C (GCC) or mesothelin as monotherapy or in combination with LDRT. Additionally, we extended this approach to a C57BL/6 mouse model implanted with MC38-gp100+ cells, followed by adoptive transfer of pmel+ T cells before and after LDRT. Tumor growth and survival outcomes were monitored in all models. Furthermore, we employed atomic force microscopy (AFM) in a small cohort to assess the effects of radiotherapy on tumor stiffness and plasticity, exploring the role of tumor nanomechanics as a potential biomarker for treatment efficacy. Results: Our results demonstrated enhanced tumor control and prolonged survival in mice treated with LDRT followed by T-cell therapy across all models. The combination of LDRT with CAR-T or pmel+ T-cell therapy led to superior tumor suppression and survival compared to monotherapy, highlighting the synergistic impact of the combined approach. Additionally, AFM analysis revealed significant changes in tumor stiffness and plasticity in response to LDRT, suggesting that the nanomechanical properties of the tumor may be predictive of therapeutic response. Discussion: The findings of this study highlight the transformative potential of incorporating LDRT as a precursor to adoptive T-cell therapy in solid tumors. By promoting CAR-T and pmel+ T-cell infiltration into the tumor microenvironment, LDRT enhanced tumor control and improved survival outcomes, offering a promising strategy to overcome the challenges associated with CAR-T therapy in solid tumors. Additionally, the changes in tumor nanomechanics observed through AFM suggest that tumor stiffness and plasticity could be biomarkers for predicting treatment outcomes. These results support further investigation into the clinical application of this combined approach to improve the efficacy of cellbased therapies in patients with solid tumors. [ABSTRACT FROM AUTHOR]

Published
2024
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8. 216 Tissue nanomechanical signature as a novel, clinically translatable predictor of response to immunotherapy combined with low-dose radiation

Author

Nizzero, Sara, primary, Srivastava, Gitika, additional, Puebla-Osorio, Nahum, additional, Wasley, Mark, additional, Mitchell, Joylise, additional, Huang, Ailing, additional, Riad, Thomas, additional, Ndiaye, Papa Diogop, additional, Gachechiladze, Mariam, additional, Oertle, Philipp, additional, Appenzeller, Tobias, additional, Cristini, Vittorio, additional, Loparic, Marko, additional, Plodinec, Marija, additional, and Welsh, James, additional

Published
2023
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11. Abstract PD4-04: PD4-04 A quantitative spatial analysis of microenvironmental biomarkers for breast cancer outcome

Author

Nizzero, Sara, primary, Soni, Maria Pelaez, additional, Xu, Yitian, additional, Zhang, Licheng, additional, Zheng, Junjun, additional, Menegaz, Brian A., additional, Jordan, Lee B, additional, Purdie, Colin A, additional, Quinlan, Philip R, additional, Nagi, Chandandeep, additional, Sepulveda, Karla A, additional, Oertle, Philipp, additional, Appenzeller, Tobias A, additional, Loparic, Marko, additional, Wang, Zhihui, additional, Chen, Shu-Hsia, additional, Cristini, Vittorio, additional, Plodinec, Marija, additional, and Thompson, Alastair M., additional

Published
2023
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12. Mass Transport Model of Radiation Response: Calibration and Application to Chemoradiation for Pancreatic Cancer

Author

Wang, Charles X., primary, Elganainy, Dalia, additional, Zaid, Mohamed M., additional, Butner, Joseph D., additional, Agrawal, Anshuman, additional, Nizzero, Sara, additional, Minsky, Bruce D., additional, Holliday, Emma B., additional, Taniguchi, Cullen M., additional, Smith, Grace L., additional, Koong, Albert C., additional, Herman, Joseph M., additional, Das, Prajnan, additional, Maitra, Anirban, additional, Wang, Huamin, additional, Wolff, Robert A., additional, Katz, Matthew H.G., additional, Crane, Christopher H., additional, Cristini, Vittorio, additional, and Koay, Eugene J., additional

Published
2022
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13. Abstract 1963: Spatial patterns of microenvironmental biomarkers drive long-term breast cancer outcome

Author

Nizzero, Sara, primary, Zhang, Licheng, additional, Xu, Yitian, additional, Pelaez-Soni, Maria J., additional, Dogra, Prashant, additional, Menegaz, Brian A., additional, Jordan, Lee B., additional, Purdie, Colin A., additional, Quinlan, Philip R., additional, Nagi, Chandandeep, additional, Sepulveda, Karla A., additional, Oertle, Philipp, additional, Appenzeller, Tobias A., additional, Chen, Shu-Hsia, additional, Loparic, Marko, additional, Wang, Zhihui, additional, Cristini, Vittorio, additional, Plodinec, Marija, additional, and Thompson, Alastair M., additional

Published
2022
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14. A Mathematical Model to Estimate Chemotherapy Concentration at the Tumor-Site and Predict Therapy Response in Colorectal Cancer Patients with Liver Metastases

Author

Anaya, Daniel A., primary, Dogra, Prashant, additional, Wang, Zhihui, additional, Haider, Mintallah, additional, Ehab, Jasmina, additional, Jeong, Daniel K., additional, Ghayouri, Masoumeh, additional, Lauwers, Gregory Y., additional, Thomas, Kerry, additional, Kim, Richard, additional, Butner, Joseph D., additional, Nizzero, Sara, additional, Ramírez, Javier Ruiz, additional, Plodinec, Marija, additional, Sidman, Richard L., additional, Cavenee, Webster K., additional, Pasqualini, Renata, additional, Arap, Wadih, additional, Fleming, Jason B., additional, and Cristini, Vittorio, additional

Published
2021
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17. Image‐guided mathematical modeling for pharmacological evaluation of nanomaterials and monoclonal antibodies

Author

Dogra, Prashant, primary, Butner, Joseph D., additional, Nizzero, Sara, additional, Ruiz Ramírez, Javier, additional, Noureddine, Achraf, additional, Peláez, María J., additional, Elganainy, Dalia, additional, Yang, Zhen, additional, Le, Anh‐Dung, additional, Goel, Shreya, additional, Leong, Hon S., additional, Koay, Eugene J., additional, Brinker, C. Jeffrey, additional, Cristini, Vittorio, additional, and Wang, Zhihui, additional

Published
2020
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19. A Mathematical Model to Estimate Chemotherapy Concentration at the Tumor-Site and Predict Therapy Response in Colorectal Cancer Patients with Liver Metastases

Author

Anaya, Daniel A., primary, Dogra, Prashant, additional, Wang, Zhihui, additional, Haider, Mintallah, additional, Ehab, Jasmina, additional, Jeong, Daniel, additional, Ghayouri, Masoumeh, additional, Lauwers, Gregory Y., additional, Thomas, Kerry, additional, Kim, Richard, additional, Butner, Joseph D., additional, Nizzero, Sara, additional, Ramírez, Javier Ruiz, additional, Plodinec, Marija, additional, Sidman, Richard L., additional, Pasqualini, Renata, additional, Arap, Wadih, additional, Fleming, Jason B., additional, and Cristini, Vittorio, additional

Published
2020
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24. Abstract LB-019: Empowering preclinical studies: A systematic and quantitative analysis of biodistribution methods to facilitate clinical translation of new drugs

Author

Nizzero, Sara, primary, Li, Feng, additional, Venuta, Alessandro, additional, Zhang, Guodong, additional, Borsoi, Carlotta, additional, Wolfram, Joy, additional, Mai, Junhua, additional, Shen, Haifa, additional, Li, Zheng, additional, Blanco, Elvin, additional, and Ferrari, Mauro, additional

Published
2018
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26. Towards the Virtual Rheometer

Author

Economides, Athena, primary, Amoudruz, Lucas, additional, Litvinov, Sergey, additional, Alexeev, Dmitry, additional, Nizzero, Sara, additional, Hadjidoukas, Panagiotis E., additional, Rossinelli, Diego, additional, and Koumoutsakos, Petros, additional

Published
2017
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29. Image-guided mathematical modeling for pharmacological evaluation of nanomaterials and monoclonal antibodies.

Author

Dogra P, Butner JD, Nizzero S, Ruiz Ramírez J, Noureddine A, Peláez MJ, Elganainy D, Yang Z, Le AD, Goel S, Leong HS, Koay EJ, Brinker CJ, Cristini V, and Wang Z

Subjects
Animals, Cell Line, Tumor, Humans, Mice, Models, Theoretical, Neoplasms diagnostic imaging, Neoplasms drug therapy, Theranostic Nanomedicine, Xenograft Model Antitumor Assays, Antibodies, Monoclonal metabolism, Antibodies, Monoclonal pharmacokinetics, Antibodies, Monoclonal pharmacology, Antibodies, Monoclonal therapeutic use, Image Processing, Computer-Assisted, Nanostructures
Abstract

While plasma concentration kinetics has traditionally been the predictor of drug pharmacological effects, it can occasionally fail to represent kinetics at the site of action, particularly for solid tumors. This is especially true in the case of delivery of therapeutic macromolecules (drug-loaded nanomaterials or monoclonal antibodies), which can experience challenges to effective delivery due to particle size-dependent diffusion barriers at the target site. As a result, disparity between therapeutic plasma kinetics and kinetics at the site of action may exist, highlighting the importance of target site concentration kinetics in determining the pharmacodynamic effects of macromolecular therapeutic agents. Assessment of concentration kinetics at the target site has been facilitated by non-invasive in vivo imaging modalities. This allows for visualization and quantification of the whole-body disposition behavior of therapeutics that is essential for a comprehensive understanding of their pharmacokinetics and pharmacodynamics. Quantitative non-invasive imaging can also help guide the development and parameterization of mathematical models for descriptive and predictive purposes. Here, we present a review of the application of state-of-the-art imaging modalities for quantitative pharmacological evaluation of therapeutic nanoparticles and monoclonal antibodies, with a focus on their integration with mathematical models, and identify challenges and opportunities. This article is categorized under: Therapeutic Approaches and Drug Discovery > Nanomedicine for Oncologic Disease Diagnostic Tools > in vivo Nanodiagnostics and Imaging Nanotechnology Approaches to Biology > Nanoscale Systems in Biology., (© 2020 The Authors. WIREs Nanomedicine and Nanobiotechnology published by Wiley Periodicals, Inc.)

Published
2020
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