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McDowell JA, Kosmacek EA, Baine MJ, Adebisi O, Zheng C, Bierman MM, Myers MS, Chatterjee A, Liermann-Wooldrik KT, Lim A, Dickinson KA, Oberley-Deegan RE. Exogenous APN protects normal tissues from radiation-induced oxidative damage and fibrosis in mice and prostate cancer patients with higher levels of APN have less radiation-induced toxicities. Redox Biol 2024; 73:103219. [PMID: 38851001 PMCID: PMC11201354 DOI: 10.1016/j.redox.2024.103219] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/07/2024] [Revised: 05/26/2024] [Accepted: 05/28/2024] [Indexed: 06/10/2024] Open
Abstract
Radiation causes damage to normal tissues that leads to increased oxidative stress, inflammation, and fibrosis, highlighting the need for the selective radioprotection of healthy tissues without hindering radiotherapy effectiveness in cancer. This study shows that adiponectin, an adipokine secreted by adipocytes, protects normal tissues from radiation damage invitro and invivo. Specifically, adiponectin (APN) reduces chronic oxidative stress and fibrosis in irradiated mice. Importantly, APN also conferred no protection from radiation to prostate cancer cells. Adipose tissue is the primary source of circulating endogenous adiponectin. However, this study shows that adipose tissue is sensitive to radiation exposure exhibiting morphological changes and persistent oxidative damage. In addition, radiation results in a significant and chronic reduction in blood APN levels from adipose tissue in mice and human prostate cancer patients exposed to pelvic irradiation. APN levels negatively correlated with bowel toxicity and overall toxicities associated with radiotherapy in prostate cancer patients. Thus, protecting, or modulating APN signaling may improve outcomes for prostate cancer patients undergoing radiotherapy.
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Affiliation(s)
- Joshua A McDowell
- Department of Biochemistry and Molecular Biology, University of Nebraska Medical Center, Omaha, NE, 68198, USA
| | - Elizabeth A Kosmacek
- Department of Biochemistry and Molecular Biology, University of Nebraska Medical Center, Omaha, NE, 68198, USA
| | - Michael J Baine
- Department of Radiation Oncology, University of Nebraska Medical Center, Omaha, NE, 68198, USA
| | - Oluwaseun Adebisi
- Department of Biochemistry and Molecular Biology, University of Nebraska Medical Center, Omaha, NE, 68198, USA
| | - Cheng Zheng
- Department of Biostatistics, University of Nebraska Medical Center, Omaha, NE, 68198, USA
| | - Madison M Bierman
- Department of Biochemistry and Molecular Biology, University of Nebraska Medical Center, Omaha, NE, 68198, USA
| | - Molly S Myers
- Department of Biochemistry and Molecular Biology, University of Nebraska Medical Center, Omaha, NE, 68198, USA
| | - Arpita Chatterjee
- Department of Biochemistry and Molecular Biology, University of Nebraska Medical Center, Omaha, NE, 68198, USA
| | - Kia T Liermann-Wooldrik
- Department of Biochemistry and Molecular Biology, University of Nebraska Medical Center, Omaha, NE, 68198, USA
| | - Andrew Lim
- College of Nursing, University of Nebraska Medical Center, Omaha, NE, 68198, USA
| | - Kristin A Dickinson
- College of Nursing, University of Nebraska Medical Center, Omaha, NE, 68198, USA
| | - Rebecca E Oberley-Deegan
- Department of Biochemistry and Molecular Biology, University of Nebraska Medical Center, Omaha, NE, 68198, USA.
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Lazebnik T, Bunimovich-Mendrazitsky S. Predicting lung cancer's metastats' locations using bioclinical model. Front Med (Lausanne) 2024; 11:1388702. [PMID: 38846148 PMCID: PMC11153684 DOI: 10.3389/fmed.2024.1388702] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/20/2024] [Accepted: 05/13/2024] [Indexed: 06/09/2024] Open
Abstract
Background Lung cancer is a global leading cause of cancer-related deaths, and metastasis profoundly influences treatment outcomes. The limitations of conventional imaging in detecting small metastases highlight the crucial need for advanced diagnostic approaches. Methods This study developed a bioclinical model using three-dimensional CT scans to predict the spatial spread of lung cancer metastasis. Utilizing a three-layer biological model, we identified regions with a high probability of metastasis colonization and validated the model on real-world data from 10 patients. Findings The validated bioclinical model demonstrated a promising 74% accuracy in predicting metastasis locations, showcasing the potential of integrating biophysical and machine learning models. These findings underscore the significance of a more comprehensive approach to lung cancer diagnosis and treatment. Interpretation This study's integration of biophysical and machine learning models contributes to advancing lung cancer diagnosis and treatment, providing nuanced insights for informed decision-making.
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Affiliation(s)
- Teddy Lazebnik
- Department of Cancer Biology, Cancer Institute, University College London, London, United Kingdom
- Department of Mathematics, Ariel University, Ariel, Israel
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Nakano H, Shiinoki T, Tanabe S, Utsunomiya S, Takizawa T, Kaidu M, Nishio T, Ishikawa H. Mathematical model combined with microdosimetric kinetic model for tumor volume calculation in stereotactic body radiation therapy. Sci Rep 2023; 13:10981. [PMID: 37414844 PMCID: PMC10326039 DOI: 10.1038/s41598-023-38232-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/13/2023] [Accepted: 07/05/2023] [Indexed: 07/08/2023] Open
Abstract
We proposed a new mathematical model that combines an ordinary differential equation (ODE) and microdosimetric kinetic model (MKM) to predict the tumor-cell lethal effect of Stereotactic body radiation therapy (SBRT) applied to non-small cell lung cancer (NSCLC). The tumor growth volume was calculated by the ODE in the multi-component mathematical model (MCM) for the cell lines NSCLC A549 and NCI-H460 (H460). The prescription doses 48 Gy/4 fr and 54 Gy/3 fr were used in the SBRT, and the effect of the SBRT on tumor cells was evaluated by the MKM. We also evaluated the effects of (1) linear quadratic model (LQM) and the MKM, (2) varying the ratio of active and quiescent tumors for the total tumor volume, and (3) the length of the dose-delivery time per fractionated dose (tinter) on the initial tumor volume. We used the ratio of the tumor volume at 1 day after the end of irradiation to the tumor volume before irradiation to define the radiation effectiveness value (REV). The combination of MKM and MCM significantly reduced REV at 48 Gy/4 fr compared to the combination of LQM and MCM. The ratio of active tumors and the prolonging of tinter affected the decrease in the REV for A549 and H460 cells. We evaluated the tumor volume considering a large fractionated dose and the dose-delivery time by combining the MKM with a mathematical model of tumor growth using an ODE in lung SBRT for NSCLC A549 and H460 cells.
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Affiliation(s)
- Hisashi Nakano
- Department of Radiation Oncology, Niigata University Medical and Dental Hospital, 1-757 Asahimachi-dori, Chuo-ku, Niigata-shi, Niigata, Japan.
- Department of Medical Physics and Engineering, Osaka University Graduate School of Medicine, 1-7 Yamadaoka, Suita-shi, Osaka, Japan.
| | - Takehiro Shiinoki
- Department of Radiation Oncology, Yamaguchi University, Minamikogushi 1-1-1 Ube, Yamaguchi, Japan
| | - Satoshi Tanabe
- Department of Radiation Oncology, Niigata University Medical and Dental Hospital, 1-757 Asahimachi-dori, Chuo-ku, Niigata-shi, Niigata, Japan
| | - Satoru Utsunomiya
- Department of Radiological Technology, Niigata University Graduate School of Health Sciences, 2-746 Asahimachi-Dori, Chuo-ku, Niigata-shi, Niigata, Japan
| | - Takeshi Takizawa
- Department of Radiation Oncology, Niigata Neurosurgical Hospital, 3057 Yamada, Nishi-ku, Niigata-shi, Niigata, Japan
- Department of Radiology and Radiation Oncology, Niigata University Graduate School of Medical and Dental Sciences, 1-757 Asahimachi-dori, Chuo-ku, Niigata-shi, Niigata, Japan
| | - Motoki Kaidu
- Department of Radiology and Radiation Oncology, Niigata University Graduate School of Medical and Dental Sciences, 1-757 Asahimachi-dori, Chuo-ku, Niigata-shi, Niigata, Japan
| | - Teiji Nishio
- Department of Medical Physics and Engineering, Osaka University Graduate School of Medicine, 1-7 Yamadaoka, Suita-shi, Osaka, Japan
| | - Hiroyuki Ishikawa
- Department of Radiology and Radiation Oncology, Niigata University Graduate School of Medical and Dental Sciences, 1-757 Asahimachi-dori, Chuo-ku, Niigata-shi, Niigata, Japan
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Nakano H, Shiinoki T, Tanabe S, Nakano T, Takizawa T, Utsunomiya S, Sakai M, Tanabe S, Ohta A, Kaidu M, Nishio T, Ishikawa H. Multicomponent mathematical model for tumor volume calculation with setup error using single-isocenter stereotactic radiotherapy for multiple brain metastases. Phys Eng Sci Med 2023; 46:945-953. [PMID: 36940064 DOI: 10.1007/s13246-023-01241-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2022] [Accepted: 03/06/2023] [Indexed: 03/21/2023]
Abstract
We evaluated the tumor residual volumes considering six degrees-of-freedom (6DoF) patient setup errors in stereotactic radiotherapy (SRT) with multicomponent mathematical model using single-isocenter irradiation for brain metastases. Simulated spherical gross tumor volumes (GTVs) with 1.0 (GTV 1), 2.0 (GTV 2), and 3.0 (GTV 3)-cm diameters were used. The distance between the GTV center and isocenter (d) was set at 0-10 cm. The GTV was simultaneously translated within 0-1.0 mm (T) and rotated within 0°-1.0° (R) in the three axis directions using affine transformation. We optimized the tumor growth model parameters using measurements of non-small cell lung cancer cell lines' (A549 and NCI-H460) growth. We calculated the GTV residual volume at the irradiation's end using the physical dose to the GTV when the GTV size, d, and 6DoF setup error varied. The d-values that satisfy tolerance values (10%, 35%, and 50%) of the GTV residual volume rate based on the pre-irradiation GTV volume were determined. The larger the tolerance value set for both cell lines, the longer the distance to satisfy the tolerance value. In GTV residual volume evaluations based on the multicomponent mathematical model on SRT with single-isocenter irradiation, the smaller the GTV size and the larger the distance and 6DoF setup error, the shorter the distance that satisfies the tolerance value might need to be.
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Affiliation(s)
- Hisashi Nakano
- Department of Radiation Oncology, Niigata University Medical and Dental Hospital, 1-757 Asahimachi-Dori, Chuo-Ku, Niigata-Shi, Niigata, Japan. .,Department of Medical Physics and Engineering, Osaka University Graduate School of Medicine, 1-7 Yamadaoka, Suita-Shi, Osaka, Japan.
| | - Takehiro Shiinoki
- Department of Radiation Oncology, Yamaguchi University, Minamikogushi 1-1-1 Ube, Yamaguchi, Japan
| | - Satoshi Tanabe
- Department of Radiation Oncology, Niigata University Medical and Dental Hospital, 1-757 Asahimachi-Dori, Chuo-Ku, Niigata-Shi, Niigata, Japan
| | - Toshimichi Nakano
- Department of Radiology and Radiation Oncology, Niigata University Graduate School of Medical and Dental Sciences, 1-757 Asahimachi-Dori, Chuo-Ku, Niigata-Shi, Niigata, Japan
| | - Takeshi Takizawa
- Department of Radiology and Radiation Oncology, Niigata University Graduate School of Medical and Dental Sciences, 1-757 Asahimachi-Dori, Chuo-Ku, Niigata-Shi, Niigata, Japan.,Department of Radiation Oncology, Niigata Neurosurgical Hospital, 3057 Yamada, Nishi-Ku, Niigata-Shi, Niigata, Japan
| | - Satoru Utsunomiya
- Department of Radiological Technology, Niigata University Graduate School of Health Sciences, 2-746 Asahimachi-Dori, Chuo-Ku, Niigata-Shi, Niigata, Japan
| | - Madoka Sakai
- Department of Radiation Oncology, Niigata University Medical and Dental Hospital, 1-757 Asahimachi-Dori, Chuo-Ku, Niigata-Shi, Niigata, Japan
| | - Shunpei Tanabe
- Department of Radiation Oncology, Niigata University Medical and Dental Hospital, 1-757 Asahimachi-Dori, Chuo-Ku, Niigata-Shi, Niigata, Japan
| | - Atsushi Ohta
- Department of Radiation Oncology, Niigata University Medical and Dental Hospital, 1-757 Asahimachi-Dori, Chuo-Ku, Niigata-Shi, Niigata, Japan
| | - Motoki Kaidu
- Department of Radiology and Radiation Oncology, Niigata University Graduate School of Medical and Dental Sciences, 1-757 Asahimachi-Dori, Chuo-Ku, Niigata-Shi, Niigata, Japan
| | - Teiji Nishio
- Department of Medical Physics and Engineering, Osaka University Graduate School of Medicine, 1-7 Yamadaoka, Suita-Shi, Osaka, Japan
| | - Hiroyuki Ishikawa
- Department of Radiology and Radiation Oncology, Niigata University Graduate School of Medical and Dental Sciences, 1-757 Asahimachi-Dori, Chuo-Ku, Niigata-Shi, Niigata, Japan
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Chemoimmunotherapy Administration Protocol Design for the Treatment of Leukemia through Mathematical Modeling and In Silico Experimentation. Pharmaceutics 2022; 14:pharmaceutics14071396. [PMID: 35890295 PMCID: PMC9316854 DOI: 10.3390/pharmaceutics14071396] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/01/2022] [Revised: 06/25/2022] [Accepted: 06/27/2022] [Indexed: 02/04/2023] Open
Abstract
Cancer with all its more than 200 variants continues to be a major health problem around the world with nearly 10 million deaths recorded in 2020, and leukemia accounted for more than 300,000 cases according to the Global Cancer Observatory. Although new treatment strategies are currently being developed in several ongoing clinical trials, the high complexity of cancer evolution and its survival mechanisms remain as an open problem that needs to be addressed to further enhanced the application of therapies. In this work, we aim to explore cancer growth, particularly chronic lymphocytic leukemia, under the combined application of CAR-T cells and chlorambucil as a nonlinear dynamical system in the form of first-order Ordinary Differential Equations. Therefore, by means of nonlinear theories, sufficient conditions are established for the eradication of leukemia cells, as well as necessary conditions for the long-term persistence of both CAR-T and cancer cells. Persistence conditions are important in treatment protocol design as these provide a threshold below which the dose will not be enough to produce a cytotoxic effect in the tumour population. In silico experimentations allowed us to design therapy administration protocols to ensure the complete eradication of leukemia cells in the system under study when considering only the infusion of CAR-T cells and for the combined application of chemoimmunotherapy. All results are illustrated through numerical simulations. Further, equations to estimate cytotoxicity of chlorambucil and CAR-T cells to leukemia cancer cells were formulated and thoroughly discussed with a 95% confidence interval for the parameters involved in each formula.
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