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Fattahi MR, Dehghani M, Paknahad S, Rahiminia S, Zareie D, Hoseini B, Oroomi TR, Motedayyen H, Arefnezhad R. Clinical insights into nanomedicine and biosafety: advanced therapeutic approaches for common urological cancers. Front Oncol 2024; 14:1438297. [PMID: 39193389 PMCID: PMC11347329 DOI: 10.3389/fonc.2024.1438297] [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: 05/25/2024] [Accepted: 07/29/2024] [Indexed: 08/29/2024] Open
Abstract
Urological cancers including those of the prostate, bladder, and kidney, are prevalent and often lethal malignancies besides other less common ones like testicular and penile cancers. Current treatments have major limitations like side effects, recurrence, resistance, high costs, and poor quality of life. Nanotechnology offers promising solutions through enhanced diagnostic accuracy, targeted drug delivery, controlled release, and multimodal imaging. This review reflects clinical challenges and nanomedical advances across major urological cancers. In prostate cancer, nanoparticles improve delineation and radiosensitization in radiation therapy, enable fluorescent guidance in surgery, and enhance chemotherapy penetration in metastatic disease. Nanoparticles also overcome bladder permeability barriers to increase the residence time of intravesical therapy and chemotherapy agents. In renal cancer, nanocarriers potentiate tyrosine kinase inhibitors and immunotherapy while gene vectors and zinc oxide nanoparticles demonstrate antiproliferative effects. Across modalities, urological applications of nanomedicine include polymeric, liposomal, and metal nanoparticles for targeted therapy, prodrug delivery, photodynamic therapy, and thermal ablation. Biosafety assessments reveal favorable profiles but clinical translation remains limited, necessitating further trials. In conclusion, nanotechnology holds significant potential for earlier detection, precise intervention, and tailored treatment of urological malignancies, warranting expanded research to transform patient outcomes.
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Affiliation(s)
- Mohammad Reza Fattahi
- School of Advanced Technologies in Medicine, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | | | | | - Shafa Rahiminia
- School of Medicine, Guilan University of Medical Sciences, Rasht, Iran
| | - Deniz Zareie
- School of Medicine, Shahroud University of Medical Sciences, Shahroud, Iran
| | - Behzad Hoseini
- School of Medicine, Mazandaran University of Medical Sciences, Sari, Iran
| | | | - Hossein Motedayyen
- Autoimmune Diseases Research Center, Kashan University of Medical Sciences, Kashan, Iran
| | - Reza Arefnezhad
- Coenzyme R Research Institute, Tehran, Iran
- Shiraz University of Medical Sciences, Shiraz, Iran
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Danckaert W, Spaas M, Sundahl N, De Bruycker A, Fonteyne V, De Paepe E, De Wagter C, Vanhaecke L, Ost P. Microbiome and metabolome dynamics during radiotherapy for prostate cancer. Radiother Oncol 2023; 189:109950. [PMID: 37827280 DOI: 10.1016/j.radonc.2023.109950] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/20/2023] [Revised: 10/02/2023] [Accepted: 10/07/2023] [Indexed: 10/14/2023]
Abstract
BACKGROUND Prostate cancer patients treated with radiotherapy are susceptible to acute gastrointestinal (GI) toxicity due to substantial overlap of the intestines with the radiation volume. Due to their intimate relationship with GI toxicity, faecal microbiome and metabolome dynamics during radiotherapy were investigated. MATERIAL & METHODS This prospective study included 50 prostate cancer patients treated with prostate (bed) only radiotherapy (PBRT) (n = 28) or whole pelvis radiotherapy (WPRT) (n = 22) (NCT04638049). Longitudinal sampling was performed prior to radiotherapy, after 10 fractions, near the end of radiotherapy and at follow-up. Patient symptoms were dichotomized into a single toxicity score. Microbiome and metabolome fingerprints were analyzed by 16S rRNA gene sequencing and ultra-high-performance liquid chromatography hybrid high-resolution mass spectrometry, respectively. RESULTS The individual α-diversity did not significantly change over time. Microbiota composition (β-diversity) changed significantly over treatment (PERMANOVA p-value = 0.03), but there was no significant difference in stability when comparing PBRT versus WPRT. Levels of various metabolites were significantly altered during radiotherapy. Baseline α-diversity was not associated with any toxicity outcome. Based on the metabolic fingerprint, no natural clustering according to toxicity profile could be achieved. CONCLUSIONS Radiation dose and treatment volume demonstrated limited effects on microbiome and metabolome fingerprints. In addition, no distinctive signature for toxicity status could be established. There is an ongoing need for toxicity risk stratification tools for diagnostic and therapeutic purposes, but the current evidence implies that the translation of metabolic and microbial biomarkers into routine clinical practice remains challenging.
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Affiliation(s)
- Willeke Danckaert
- Department of Human Structure and Repair, Faculty of Medicine and Health Sciences, Ghent University, Ghent, Belgium; Department of Radiation Oncology, Ghent University Hospital, Ghent, Belgium; Cancer Research Institute Ghent (CRIG), Ghent, Belgium.
| | - Mathieu Spaas
- Department of Human Structure and Repair, Faculty of Medicine and Health Sciences, Ghent University, Ghent, Belgium; Department of Radiation Oncology, Ghent University Hospital, Ghent, Belgium; Cancer Research Institute Ghent (CRIG), Ghent, Belgium
| | - Nora Sundahl
- Department of Radiation Oncology, AZ Groeninge Kortrijk, Kortrijk, Belgium
| | - Aurélie De Bruycker
- Department of Human Structure and Repair, Faculty of Medicine and Health Sciences, Ghent University, Ghent, Belgium; Department of Radiation Oncology, Ghent University Hospital, Ghent, Belgium; Department of Radiation Oncology, AZ Groeninge Kortrijk, Kortrijk, Belgium
| | - Valérie Fonteyne
- Department of Human Structure and Repair, Faculty of Medicine and Health Sciences, Ghent University, Ghent, Belgium; Department of Radiation Oncology, Ghent University Hospital, Ghent, Belgium; Cancer Research Institute Ghent (CRIG), Ghent, Belgium
| | - Ellen De Paepe
- Laboratory of Integrative Metabolomics (LIMET), Department of Translational Physiology, Infectiology and Public Health, Faculty of Veterinary Medicine, Ghent University, Ghent, Belgium
| | - Carlos De Wagter
- Department of Human Structure and Repair, Faculty of Medicine and Health Sciences, Ghent University, Ghent, Belgium; Department of Radiation Oncology, Ghent University Hospital, Ghent, Belgium
| | - Lynn Vanhaecke
- Cancer Research Institute Ghent (CRIG), Ghent, Belgium; Laboratory of Integrative Metabolomics (LIMET), Department of Translational Physiology, Infectiology and Public Health, Faculty of Veterinary Medicine, Ghent University, Ghent, Belgium; Institute for Global Food Security, School of Biological Sciences, Queen's University, BT7 1NN Belfast, United Kingdom
| | - Piet Ost
- Department of Human Structure and Repair, Faculty of Medicine and Health Sciences, Ghent University, Ghent, Belgium; Cancer Research Institute Ghent (CRIG), Ghent, Belgium; Department of Radiation Oncology, Iridium Netwerk, Wilrijk, Belgium
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Benešová I, Křížová Ľ, Kverka M. Microbiota as the unifying factor behind the hallmarks of cancer. J Cancer Res Clin Oncol 2023; 149:14429-14450. [PMID: 37555952 PMCID: PMC10590318 DOI: 10.1007/s00432-023-05244-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/05/2023] [Accepted: 08/01/2023] [Indexed: 08/10/2023]
Abstract
The human microbiota is a complex ecosystem that colonizes body surfaces and interacts with host organ systems, especially the immune system. Since the composition of this ecosystem depends on a variety of internal and external factors, each individual harbors a unique set of microbes. These differences in microbiota composition make individuals either more or less susceptible to various diseases, including cancer. Specific microbes are associated with cancer etiology and pathogenesis and several mechanisms of how they drive the typical hallmarks of cancer were recently identified. Although most microbes reside in the distal gut, they can influence cancer initiation and progression in distant tissues, as well as modulate the outcomes of established cancer therapies. Here, we describe the mechanisms by which microbes influence carcinogenesis and discuss their current and potential future applications in cancer diagnostics and management.
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Affiliation(s)
- Iva Benešová
- Laboratory of Cellular and Molecular Immunology, Institute of Microbiology v.v.i., Czech Academy of Sciences, Vídeňská 1083, 142 00, Prague 4-Krč, Czech Republic
| | - Ľudmila Křížová
- Department of Oncology, First Faculty of Medicine, Charles University in Prague and General University Hospital in Prague, Prague, Czech Republic
| | - Miloslav Kverka
- Laboratory of Cellular and Molecular Immunology, Institute of Microbiology v.v.i., Czech Academy of Sciences, Vídeňská 1083, 142 00, Prague 4-Krč, Czech Republic.
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Yi Y, Lu W, Shen L, Wu Y, Zhang Z. The gut microbiota as a booster for radiotherapy: novel insights into radio-protection and radiation injury. Exp Hematol Oncol 2023; 12:48. [PMID: 37218007 DOI: 10.1186/s40164-023-00410-5] [Citation(s) in RCA: 10] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/07/2023] [Accepted: 05/04/2023] [Indexed: 05/24/2023] Open
Abstract
Approximately 60-80% of cancer patients treated with abdominopelvic radiotherapy suffer post-radiotherapy toxicities including radiation enteropathy and myelosuppression. Effective preventive and therapeutic strategies are lacking for such radiation injury. The gut microbiota holds high investigational value for deepening our understanding of the pathogenesis of radiation injury, especially radiation enteropathy which resembles inflammatory bowel disease pathophysiology and for facilitating personalized medicine by providing safer therapies tailored for cancer patients. Preclinical and clinical data consistently support that gut microbiota components including lactate-producers, SCFA-producers, indole compound-producers and Akkermansia impose intestinal and hematopoietic radio-protection. These features serve as potential predictive biomarkers for radiation injury, together with the microbial diversity which robustly predicts milder post-radiotherapy toxicities in multiple types of cancer. The accordingly developed manipulation strategies including selective microbiota transplantation, probiotics, purified functional metabolites and ligands to microbe-host interactive pathways are promising radio-protectors and radio-mitigators that merit extensive validation in clinical trials. With massive mechanistic investigations and pilot clinical trials reinforcing its translational value the gut microbiota may boost the prediction, prevention and mitigation of radiation injury. In this review, we summarize the state-of-the-art landmark researches related with radio-protection to provide illuminating insights for oncologists, gastroenterologists and laboratory scientists interested in this overlooked complexed disorder.
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Affiliation(s)
- Yuxi Yi
- Department of Radiation Oncology, Fudan University Shanghai Cancer Center, Shanghai, China
- Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China
- Shanghai Clinical Research Center for Radiation Oncology, Shanghai, China
- Shanghai Key Laboratory of Radiation Oncology, Shanghai, China
| | - Weiqing Lu
- Department of Radiation Oncology, Fudan University Shanghai Cancer Center, Shanghai, China
- Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China
- Shanghai Clinical Research Center for Radiation Oncology, Shanghai, China
- Shanghai Key Laboratory of Radiation Oncology, Shanghai, China
| | - Lijun Shen
- Department of Radiation Oncology, Fudan University Shanghai Cancer Center, Shanghai, China.
- Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China.
- Shanghai Clinical Research Center for Radiation Oncology, Shanghai, China.
- Shanghai Key Laboratory of Radiation Oncology, Shanghai, China.
| | - Yang Wu
- Key Laboratory of Medical Molecular Virology (MOE/NHC/CAMS), Shanghai Frontiers Science Center of Pathogenic Microorganisms and Infection, School of Basic Medical Sciences, Shanghai Medical College, Fudan University, Shanghai, China.
| | - Zhen Zhang
- Department of Radiation Oncology, Fudan University Shanghai Cancer Center, Shanghai, China.
- Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China.
- Shanghai Clinical Research Center for Radiation Oncology, Shanghai, China.
- Shanghai Key Laboratory of Radiation Oncology, Shanghai, China.
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5
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Sun Y, Zhang X, Jin C, Yue K, Sheng D, Zhang T, Dou X, Liu J, Jing H, Zhang L, Yue J. Prospective, longitudinal analysis of the gut microbiome in patients with locally advanced rectal cancer predicts response to neoadjuvant concurrent chemoradiotherapy. J Transl Med 2023; 21:221. [PMID: 36967379 PMCID: PMC10041716 DOI: 10.1186/s12967-023-04054-1] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/04/2022] [Accepted: 03/10/2023] [Indexed: 03/28/2023] Open
Abstract
BACKGROUND Neoadjuvant concurrent chemoradiotherapy (nCCRT) is a standard treatment for locally advanced rectal cancer (LARC). The gut microbiome may be reshaped by radiotherapy through its effects on microbial composition, mucosal immunity, and the systemic immune system. We sought to clarify dynamic, longitudinal changes in the gut microbiome and blood immunomodulators throughout nCCRT and to explore the relationship of such changes with outcomes after nCCRT. METHODS A total of 39 patients with LARC were recruited for this study. Fecal samples and peripheral blood samples were collected from all 39 patients before nCCRT, during nCCRT (at week 3), and after nCCRT (at week 5). The gut microbiota and the microbial community structure were analyzed by 16S rRNA sequencing of the V3-V4 region. Levels of blood immunomodulatory proteins were measured with a Millipore HCKPMAG-11 K kit and Luminex 200 platform (Luminex, USA). RESULTS Cross-sectional and longitudinal analyses revealed that the gut microbiome profile and enterotype exhibited characteristic variations that could distinguish patients with good response (AJCC TRG classification 0-1) vs poor response (TRG 2-3) to nCCRT. Sparse partial least squares regression and canonical correspondence analyses showed multivariate associations between specific microbial taxa, host immunomodulatory proteins, immune cells, and outcomes after nCCRT. An integrated model consisting of baseline Clostridium sensu stricto 1 levels, fold changes in Intestinimonas, blood levels of the herpesvirus entry mediator (HVEM/CD270), and lymphocyte counts could predict good vs poor outcome after nCCRT [area under the receiver-operating characteristics curve (AUC)= 0.821; area under the precision-recall curve [AUPR] = 0.911]. CONCLUSIONS Our results showed that longitudinal variations in specific gut taxa, associated host immune cells, and immunomodulatory proteins before and during nCCRT could be useful for early predictions of the efficacy of nCCRT, which could guide the choice of individualized treatment for patients with LARC.
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Affiliation(s)
- Yi Sun
- Department of Radiation Oncology, Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, China
- The Comprehensive Cancer Centre of Nanjing Drum Tower Hospital, The Affiliated Hospital of Nanjing University Medical School, Nanjing, China
| | - Xiang Zhang
- Department of Radiation Oncology, Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, China
| | - Chuandi Jin
- Department of Biostatistics, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, China
- Microbiome-X, National Institute of Health Data Science of China & Institute for Medical Dataology, Cheeloo College of Medicine, Shandong University, Jinan, China
| | - Kaile Yue
- Department of Biostatistics, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, China
- Microbiome-X, National Institute of Health Data Science of China & Institute for Medical Dataology, Cheeloo College of Medicine, Shandong University, Jinan, China
| | - Dashuang Sheng
- Department of Biostatistics, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, China
- Microbiome-X, National Institute of Health Data Science of China & Institute for Medical Dataology, Cheeloo College of Medicine, Shandong University, Jinan, China
| | - Tao Zhang
- Department of Biostatistics, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, China
| | - Xue Dou
- Department of Radiation Oncology, Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, China
| | - Jing Liu
- Department of Radiation Oncology, Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, China
| | - Hongbiao Jing
- Department of Pathology, Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, China
| | - Lei Zhang
- Department of Biostatistics, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, China.
- Microbiome-X, National Institute of Health Data Science of China & Institute for Medical Dataology, Cheeloo College of Medicine, Shandong University, Jinan, China.
- State Key Laboratory of Microbial Technology, Shandong University, Qingdao, China.
| | - Jinbo Yue
- Department of Radiation Oncology, Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, China.
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Ferreira MR, Andreyev JN, Wedlake L, Dearnaley DP. Comment on "Exploiting dietary fibre and the gut microbiota in pelvic radiotherapy patients". Br J Cancer 2023; 128:711-712. [PMID: 36717675 PMCID: PMC9977733 DOI: 10.1038/s41416-023-02163-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/22/2022] [Revised: 12/05/2022] [Accepted: 01/13/2023] [Indexed: 01/31/2023] Open
Affiliation(s)
- Miguel R Ferreira
- Guys and St Thomas NHS Foundation Trust, London, UK.
- King's College London, London, UK.
| | | | | | - David P Dearnaley
- The Royal Marsden NHS Foundation Trust, London, UK
- The Institute of Cancer Research, London, UK
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7
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Pei Y, Ning R, Hu W, Li P, Zhang Z, Deng Y, Hong Z, Sun Y, Guo X, Zhang Q. Carbon Ion Radiotherapy Induce Metabolic Inhibition After Functional Imaging-Guided Simultaneous Integrated Boost for Prostate Cancer. Front Oncol 2022; 12:845583. [PMID: 35936669 PMCID: PMC9354483 DOI: 10.3389/fonc.2022.845583] [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: 12/30/2021] [Accepted: 06/13/2022] [Indexed: 11/13/2022] Open
Abstract
PurposeAs local recurrence remains a challenge and the advantages of the simultaneous integrated boost (SIB) technique have been validated in photon radiotherapy, we applied the SIB technique to CIRT. The aim was to investigate the metabolomic changes of the CIRT with concurrent androgen deprivation therapy (ADT) in localized prostate cancer (PCa) and the unique metabolic effect of the SIB technique.Material and MethodsThis study enrolled 24 pathologically confirmed PCa patients. All patients went through CIRT with concurrent ADT. The gross target volume (GTV) boost was defined as positive lesions on both 68Ga-PSMA PET/CT and mpMRI images. Urine samples collected before and after CIRT were analyzed by the Q-TOF UPLC-MS/MS system. R platform and MetDNA were used for peak detection and identification. Statistical analysis and metabolic pathway analysis were performed on Metaboanalyst.ResultsThe metabolite profiles were significantly altered after CIRT. The most significantly altered metabolic pathway is PSMA participated alanine, aspartate and glutamate metabolism. Metabolites in this pathway showed a trend to be better suppressed in the SIB group. A total of 11 identified metabolites were significantly discriminative between two groups and all of them were better down-regulated in the SIB group. Meanwhile, among these metabolites, three metabolites in DNA damage and repair related purine metabolism were down-regulated to a greater extent in the SIB group.ConclusionMetabolic dysfunction was one of the typical characteristics of PCa. CIRT with ADT showed a powerful inhibition of PCa metabolism, especially in PSMA participated metabolic pathway. The SIB CIRT showed even better performance on down-regulation of most metabolism than uniform-dose-distribution CIRT. Meanwhile, the SIB CIRT also showed its unique superiority to inhibit purine metabolism. PSMA PET/CT guided SIB CIRT showed its potentials to further benefit PCa patients.
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Affiliation(s)
- Yulei Pei
- Department of Radiation Oncology, Shanghai Proton and Heavy Ion Center, Fudan University Cancer Hospital, Shanghai, China
- Shanghai Key Laboratory of Radiation Oncology (20dz2261000), Shanghai, China
- Shanghai Engineering Research Center of Proton and Heavy lon Radiation Therapy, Shanghai, China
| | - Renli Ning
- Shanghai Key Laboratory of Radiation Oncology (20dz2261000), Shanghai, China
- Shanghai Engineering Research Center of Proton and Heavy lon Radiation Therapy, Shanghai, China
- Department of Research and Development, Shanghai Proton and Heavy Ion Center, Fudan University Cancer Hospital, Shanghai, China
| | - Wei Hu
- Department of Radiation Oncology, Shanghai Proton and Heavy Ion Center, Fudan University Cancer Hospital, Shanghai, China
- Shanghai Key Laboratory of Radiation Oncology (20dz2261000), Shanghai, China
- Shanghai Engineering Research Center of Proton and Heavy lon Radiation Therapy, Shanghai, China
| | - Ping Li
- Shanghai Key Laboratory of Radiation Oncology (20dz2261000), Shanghai, China
- Shanghai Engineering Research Center of Proton and Heavy lon Radiation Therapy, Shanghai, China
- Department of Radiation Oncology, Shanghai Proton and Heavy Ion Center, Shanghai, China
| | - Zhenshan Zhang
- Department of Radiation Oncology, Shanghai Proton and Heavy Ion Center, Fudan University Cancer Hospital, Shanghai, China
- Shanghai Key Laboratory of Radiation Oncology (20dz2261000), Shanghai, China
- Shanghai Engineering Research Center of Proton and Heavy lon Radiation Therapy, Shanghai, China
| | - Yong Deng
- Shanghai Key Laboratory of Radiation Oncology (20dz2261000), Shanghai, China
- Shanghai Engineering Research Center of Proton and Heavy lon Radiation Therapy, Shanghai, China
- Department of Research and Development, Shanghai Proton and Heavy Ion Center, Shanghai, China
| | - Zhengshan Hong
- Shanghai Key Laboratory of Radiation Oncology (20dz2261000), Shanghai, China
- Shanghai Engineering Research Center of Proton and Heavy lon Radiation Therapy, Shanghai, China
- Department of Radiation Oncology, Shanghai Proton and Heavy Ion Center, Shanghai, China
| | - Yun Sun
- Shanghai Key Laboratory of Radiation Oncology (20dz2261000), Shanghai, China
- Shanghai Engineering Research Center of Proton and Heavy lon Radiation Therapy, Shanghai, China
- Department of Research and Development, Shanghai Proton and Heavy Ion Center, Fudan University Cancer Hospital, Shanghai, China
- *Correspondence: Qing Zhang, ; Xiaomao Guo, ; Yun Sun,
| | - Xiaomao Guo
- Shanghai Key Laboratory of Radiation Oncology (20dz2261000), Shanghai, China
- Shanghai Engineering Research Center of Proton and Heavy lon Radiation Therapy, Shanghai, China
- Department of Research and Development, Shanghai Proton and Heavy Ion Center, Fudan University Cancer Hospital, Shanghai, China
- *Correspondence: Qing Zhang, ; Xiaomao Guo, ; Yun Sun,
| | - Qing Zhang
- Department of Radiation Oncology, Shanghai Proton and Heavy Ion Center, Fudan University Cancer Hospital, Shanghai, China
- Shanghai Key Laboratory of Radiation Oncology (20dz2261000), Shanghai, China
- Shanghai Engineering Research Center of Proton and Heavy lon Radiation Therapy, Shanghai, China
- *Correspondence: Qing Zhang, ; Xiaomao Guo, ; Yun Sun,
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8
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Pannkuk EL, Laiakis EC, Garty G, Bansal S, Ponnaiya B, Wu X, Ghandhi SA, Amundson SA, Brenner DJ, Fornace AJ. Biofluid Metabolomics and Lipidomics of Mice Exposed to External Very High-Dose Rate Radiation. Metabolites 2022; 12:520. [PMID: 35736453 PMCID: PMC9228171 DOI: 10.3390/metabo12060520] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/09/2022] [Revised: 05/26/2022] [Accepted: 05/30/2022] [Indexed: 02/01/2023] Open
Abstract
High-throughput biodosimetry methods to determine exposure to ionizing radiation (IR) that can also be easily scaled to multiple testing sites in emergency situations are needed in the event of malicious attacks or nuclear accidents that may involve a substantial number of civilians. In the event of an improvised nuclear device (IND), a complex IR exposure will have a very high-dose rate (VHDR) component from an initial blast. We have previously addressed low-dose rate (LDR, ≤1 Gy/day) exposures from internal emitters on biofluid small molecule signatures, but further research on the VHDR component of the initial blast is required. Here, we exposed 8- to 10-week-old male C57BL/6 mice to an acute dose of 3 Gy using a reference dose rate of 0.7 Gy/min or a VHDR of 7 Gy/s, collected urine and serum at 1 and 7 d, then compared the metabolite signatures using either untargeted (urine) or targeted (serum) approaches with liquid chromatography mass spectrometry platforms. A Random Forest classification approach showed strikingly similar changes in urinary signatures at 1 d post-irradiation with VHDR samples grouping closer to control samples at 7 d. Identical metabolite panels (carnitine, trigonelline, xanthurenic acid, N6,N6,N6-trimethyllysine, spermine, and hexosamine-valine-isoleucine-OH) could differentiate IR exposed individuals with high sensitivity and specificity (area under the receiver operating characteristic (AUROC) curves 0.89-1.00) irrespective of dose rate at both days. For serum, the top 25 significant lipids affected by IR exposure showed slightly higher perturbations at 0.7 Gy/min vs. 7 Gy/s; however, identical panels showed excellent sensitivity and specificity at 1 d (three hexosylceramides (16:0), (18:0), (24:0), sphingomyelin [26:1], lysophosphatidylethanolamine [22:1]). Mice could not be differentiated from control samples at 7 d for a 3 Gy exposure based on serum lipid signatures. As with LDR exposures, we found that identical biofluid small molecule signatures can identify IR exposed individuals irrespective of dose rate, which shows promise for more universal applications of metabolomics for biodosimetry.
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Affiliation(s)
- Evan L. Pannkuk
- Department of Oncology, Lombardi Comprehensive Cancer Center, Georgetown University Medical Center, Washington, DC 20057, USA; (E.C.L.); (S.B.); (A.J.F.J.)
- Department of Biochemistry and Molecular & Cellular Biology, Georgetown University Medical Center, Washington, DC 20057, USA
- Center for Metabolomic Studies, Georgetown University, Washington, DC 20057, USA
| | - Evagelia C. Laiakis
- Department of Oncology, Lombardi Comprehensive Cancer Center, Georgetown University Medical Center, Washington, DC 20057, USA; (E.C.L.); (S.B.); (A.J.F.J.)
- Department of Biochemistry and Molecular & Cellular Biology, Georgetown University Medical Center, Washington, DC 20057, USA
- Center for Metabolomic Studies, Georgetown University, Washington, DC 20057, USA
| | - Guy Garty
- Radiological Research Accelerator Facility, Columbia University, Irvington, NY 10032, USA;
- Center for Radiological Research, Columbia University Irving Medical Center, New York, NY 10032, USA; (B.P.); (X.W.); (S.A.G.); (S.A.A.); (D.J.B.)
| | - Shivani Bansal
- Department of Oncology, Lombardi Comprehensive Cancer Center, Georgetown University Medical Center, Washington, DC 20057, USA; (E.C.L.); (S.B.); (A.J.F.J.)
| | - Brian Ponnaiya
- Center for Radiological Research, Columbia University Irving Medical Center, New York, NY 10032, USA; (B.P.); (X.W.); (S.A.G.); (S.A.A.); (D.J.B.)
| | - Xuefeng Wu
- Center for Radiological Research, Columbia University Irving Medical Center, New York, NY 10032, USA; (B.P.); (X.W.); (S.A.G.); (S.A.A.); (D.J.B.)
| | - Shanaz A. Ghandhi
- Center for Radiological Research, Columbia University Irving Medical Center, New York, NY 10032, USA; (B.P.); (X.W.); (S.A.G.); (S.A.A.); (D.J.B.)
| | - Sally A. Amundson
- Center for Radiological Research, Columbia University Irving Medical Center, New York, NY 10032, USA; (B.P.); (X.W.); (S.A.G.); (S.A.A.); (D.J.B.)
| | - David J. Brenner
- Center for Radiological Research, Columbia University Irving Medical Center, New York, NY 10032, USA; (B.P.); (X.W.); (S.A.G.); (S.A.A.); (D.J.B.)
| | - Albert J. Fornace
- Department of Oncology, Lombardi Comprehensive Cancer Center, Georgetown University Medical Center, Washington, DC 20057, USA; (E.C.L.); (S.B.); (A.J.F.J.)
- Department of Biochemistry and Molecular & Cellular Biology, Georgetown University Medical Center, Washington, DC 20057, USA
- Center for Metabolomic Studies, Georgetown University, Washington, DC 20057, USA
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9
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Read GH, Bailleul J, Vlashi E, Kesarwala AH. Metabolic response to radiation therapy in cancer. Mol Carcinog 2022; 61:200-224. [PMID: 34961986 PMCID: PMC10187995 DOI: 10.1002/mc.23379] [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: 08/11/2021] [Revised: 12/01/2021] [Accepted: 12/01/2021] [Indexed: 11/11/2022]
Abstract
Tumor metabolism has emerged as a hallmark of cancer and is involved in carcinogenesis and tumor growth. Reprogramming of tumor metabolism is necessary for cancer cells to sustain high proliferation rates and enhanced demands for nutrients. Recent studies suggest that metabolic plasticity in cancer cells can decrease the efficacy of anticancer therapies by enhancing antioxidant defenses and DNA repair mechanisms. Studying radiation-induced metabolic changes will lead to a better understanding of radiation response mechanisms as well as the identification of new therapeutic targets, but there are few robust studies characterizing the metabolic changes induced by radiation therapy in cancer. In this review, we will highlight studies that provide information on the metabolic changes induced by radiation and oxidative stress in cancer cells and the associated underlying mechanisms.
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Affiliation(s)
- Graham H. Read
- Department of Radiation Oncology, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, California
| | - Justine Bailleul
- Department of Radiation Oncology, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, California
| | - Erina Vlashi
- Department of Radiation Oncology, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, California
- Jonsson Comprehensive Cancer Center, University of California, Los Angeles, Los Angeles, California
| | - Aparna H. Kesarwala
- Department of Radiation Oncology, Winship Cancer Institute, Emory University School of Medicine, Atlanta, Georgia
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Ning R, Pei Y, Li P, Hu W, Deng Y, Hong Z, Sun Y, Zhang Q, Guo X. Carbon Ion Radiotherapy Evokes a Metabolic Reprogramming and Individualized Response in Prostate Cancer. Front Public Health 2021; 9:777160. [PMID: 34950631 PMCID: PMC8688694 DOI: 10.3389/fpubh.2021.777160] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2021] [Accepted: 11/03/2021] [Indexed: 11/29/2022] Open
Abstract
Introduction: Carbon ion radiotherapy (CIRT) is a novel treatment for prostate cancer (PCa). However, the underlying mechanism for the individualized response to CIRT is still not clear. Metabolic reprogramming is essential for tumor growth and proliferation. Although changes in metabolite profiles have been detected in patients with cancer treated with photon radiotherapy, there is limited data regarding CIRT-induced metabolic changes in PCa. Therefore, the study aimed to investigate the impact of metabolic reprogramming on individualized response to CIRT in patients with PCa. Materials and Methods: Urine samples were collected from pathologically confirmed patients with PCa before and after CIRT. A UPLC-MS/MS system was used for metabolite detection. XCMS online, MetDNA, and MS-DIAL were used for peak detection and identification of metabolites. Statistical analysis and metabolic pathway analysis were performed on MetaboAnalyst. Results: A total of 1,701 metabolites were monitored in this research. Principal component analysis (PCA) revealed a change in the patient's urine metabolite profiles following CIRT. Thirty-five metabolites were significantly altered, with the majority of them being amino acids. The arginine biosynthesis and histidine metabolism pathways were the most significantly altered pathways. Hierarchical cluster analysis (HCA) showed that after CIRT, the patients could be clustered into two groups according to their metabolite profiles. The arginine biosynthesis and phenylalanine, tyrosine, and tryptophan biosynthesis pathways are the most significantly discriminated pathways. Conclusion: Our preliminary findings indicate that metabolic reprogramming and inhibition are important mechanisms involved in response to CIRT in patients with PCa. Therefore, changes in urine metabolites could be used to timely assess the individualized response to CIRT.
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Affiliation(s)
- Renli Ning
- Department of Research and Development, Shanghai Proton and Heavy Ion Center, Fudan University Cancer Hospital, Shanghai, China.,Shanghai Key Laboratory of Radiation Oncology (20dz2261000), Shanghai, China.,Shanghai Engineering Research Center of Proton and Heavy lon Radiation Therapy, Shanghai, China
| | - Yulei Pei
- Shanghai Key Laboratory of Radiation Oncology (20dz2261000), Shanghai, China.,Shanghai Engineering Research Center of Proton and Heavy lon Radiation Therapy, Shanghai, China.,Department of Radiation Oncology, Shanghai Proton and Heavy Ion Center, Fudan University Cancer Hospital, Shanghai, China
| | - Ping Li
- Shanghai Key Laboratory of Radiation Oncology (20dz2261000), Shanghai, China.,Shanghai Engineering Research Center of Proton and Heavy lon Radiation Therapy, Shanghai, China.,Department of Radiation Oncology, Shanghai Proton and Heavy Ion Center, Shanghai, China
| | - Wei Hu
- Shanghai Key Laboratory of Radiation Oncology (20dz2261000), Shanghai, China.,Shanghai Engineering Research Center of Proton and Heavy lon Radiation Therapy, Shanghai, China.,Department of Radiation Oncology, Shanghai Proton and Heavy Ion Center, Fudan University Cancer Hospital, Shanghai, China
| | - Yong Deng
- Shanghai Key Laboratory of Radiation Oncology (20dz2261000), Shanghai, China.,Shanghai Engineering Research Center of Proton and Heavy lon Radiation Therapy, Shanghai, China.,Department of Research and Development, Shanghai Proton and Heavy Ion Center, Shanghai, China
| | - Zhengshan Hong
- Shanghai Key Laboratory of Radiation Oncology (20dz2261000), Shanghai, China.,Shanghai Engineering Research Center of Proton and Heavy lon Radiation Therapy, Shanghai, China.,Department of Radiation Oncology, Shanghai Proton and Heavy Ion Center, Shanghai, China
| | - Yun Sun
- Department of Research and Development, Shanghai Proton and Heavy Ion Center, Fudan University Cancer Hospital, Shanghai, China.,Shanghai Key Laboratory of Radiation Oncology (20dz2261000), Shanghai, China.,Shanghai Engineering Research Center of Proton and Heavy lon Radiation Therapy, Shanghai, China
| | - Qing Zhang
- Shanghai Key Laboratory of Radiation Oncology (20dz2261000), Shanghai, China.,Shanghai Engineering Research Center of Proton and Heavy lon Radiation Therapy, Shanghai, China.,Department of Radiation Oncology, Shanghai Proton and Heavy Ion Center, Fudan University Cancer Hospital, Shanghai, China
| | - Xiaomao Guo
- Department of Research and Development, Shanghai Proton and Heavy Ion Center, Fudan University Cancer Hospital, Shanghai, China.,Shanghai Key Laboratory of Radiation Oncology (20dz2261000), Shanghai, China.,Shanghai Engineering Research Center of Proton and Heavy lon Radiation Therapy, Shanghai, China
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