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Shi Z, Hu C, Zheng X, Sun C, Li Q. Feedback loop between hypoxia and energy metabolic reprogramming aggravates the radioresistance of cancer cells. Exp Hematol Oncol 2024; 13:55. [PMID: 38778409 PMCID: PMC11110349 DOI: 10.1186/s40164-024-00519-1] [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: 02/20/2024] [Accepted: 05/07/2024] [Indexed: 05/25/2024] Open
Abstract
Radiotherapy is one of the mainstream approaches for cancer treatment, although the clinical outcomes are limited due to the radioresistance of tumor cells. Hypoxia and metabolic reprogramming are the hallmarks of tumor initiation and progression and are closely linked to radioresistance. Inside a tumor, the rate of angiogenesis lags behind cell proliferation, and the underdevelopment and abnormal functions of blood vessels in some loci result in oxygen deficiency in cancer cells, i.e., hypoxia. This prevents radiation from effectively eliminating the hypoxic cancer cells. Cancer cells switch to glycolysis as the main source of energy, a phenomenon known as the Warburg effect, to sustain their rapid proliferation rates. Therefore, pathways involved in metabolic reprogramming and hypoxia-induced radioresistance are promising intervention targets for cancer treatment. In this review, we discussed the mechanisms and pathways underlying radioresistance due to hypoxia and metabolic reprogramming in detail, including DNA repair, role of cancer stem cells, oxidative stress relief, autophagy regulation, angiogenesis and immune escape. In addition, we proposed the existence of a feedback loop between energy metabolic reprogramming and hypoxia, which is associated with the development and exacerbation of radioresistance in tumors. Simultaneous blockade of this feedback loop and other tumor-specific targets can be an effective approach to overcome radioresistance of cancer cells. This comprehensive overview provides new insights into the mechanisms underlying tumor radiosensitivity and progression.
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Affiliation(s)
- Zheng Shi
- Institute of Modern Physics, Chinese Academy of Sciences, Lanzhou, China
- Key Laboratory of Heavy Ion Radiation Biology and Medicine of Chinese Academy of Sciences, Lanzhou, China
- Key Laboratory of Basic Research on Heavy Ion Radiation Application in Medicine, Lanzhou, China
- University of Chinese Academy of Sciences, Beijing, China
| | - Cuilan Hu
- Institute of Modern Physics, Chinese Academy of Sciences, Lanzhou, China
- Key Laboratory of Heavy Ion Radiation Biology and Medicine of Chinese Academy of Sciences, Lanzhou, China
- Key Laboratory of Basic Research on Heavy Ion Radiation Application in Medicine, Lanzhou, China
- University of Chinese Academy of Sciences, Beijing, China
| | - Xiaogang Zheng
- Institute of Modern Physics, Chinese Academy of Sciences, Lanzhou, China
- Key Laboratory of Heavy Ion Radiation Biology and Medicine of Chinese Academy of Sciences, Lanzhou, China
- Key Laboratory of Basic Research on Heavy Ion Radiation Application in Medicine, Lanzhou, China
- University of Chinese Academy of Sciences, Beijing, China
| | - Chao Sun
- Institute of Modern Physics, Chinese Academy of Sciences, Lanzhou, China.
- Key Laboratory of Heavy Ion Radiation Biology and Medicine of Chinese Academy of Sciences, Lanzhou, China.
- Key Laboratory of Basic Research on Heavy Ion Radiation Application in Medicine, Lanzhou, China.
- University of Chinese Academy of Sciences, Beijing, China.
| | - Qiang Li
- Institute of Modern Physics, Chinese Academy of Sciences, Lanzhou, China.
- Key Laboratory of Heavy Ion Radiation Biology and Medicine of Chinese Academy of Sciences, Lanzhou, China.
- Key Laboratory of Basic Research on Heavy Ion Radiation Application in Medicine, Lanzhou, China.
- University of Chinese Academy of Sciences, Beijing, China.
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Guo N, Minas G, Synowsky SA, Dunne MR, Ahmed H, McShane R, Bhardwaj A, Donlon NE, Lorton C, O'Sullivan J, Reynolds JV, Caie PD, Shirran SL, Lynch AG, Stewart AJ, Arya S. Identification of plasma proteins associated with oesophageal cancer chemotherapeutic treatment outcomes using SWATH-MS. J Proteomics 2022; 266:104684. [PMID: 35842220 DOI: 10.1016/j.jprot.2022.104684] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/15/2022] [Revised: 07/01/2022] [Accepted: 07/08/2022] [Indexed: 10/17/2022]
Abstract
Oesophageal adenocarcinoma (OAC) is an aggressive cancer with a five-year survival of <15%. Current chemotherapeutic strategies only benefit a minority (20-30%) of patients and there are no methods available to differentiate between responders and non-responders. We performed quantitative proteomics using Sequential Window Acquisition of all THeoretical fragment-ion spectra-Mass Spectrometry (SWATH-MS) on albumin/IgG-depleted and non-depleted plasma samples from 23 patients with locally advanced OAC prior to treatment. Individuals were grouped based on tumour regression (TRG) score (TRG1/2/3 vs TRG4/5) after chemotherapy, and differentially abundant proteins were compared. Protein depletion of highly abundant proteins led to the identification of around twice as many proteins. SWATH-MS revealed significant quantitative differences in the abundance of several proteins between the two groups. These included complement c1q subunit proteins, C1QA, C1QB and C1QC, which were of higher abundance in the low TRG group. Of those that were found to be of higher abundance in the high TRG group, glutathione S-transferase pi (GSTP1) exhibited the lowest p-value and highest classification accuracy and Cohen's kappa value. Concentrations of these proteins were further examined using ELISA-based assays. This study provides quantitative information relating to differences in the plasma proteome that underpin response to chemotherapeutic treatment in oesophageal cancers. SIGNIFICANCE: Oesophageal cancers, including oesophageal adenocarcinoma (OAC) and oesophageal gastric junction cancer (OGJ), are one of the leading causes of cancer mortality worldwide. Curative therapy consists of surgery, either alone or in combination with adjuvant or neoadjuvant chemotherapy or radiation, or combination chemoradiotherapy regimens. There are currently no clinico-pathological means of predicting which patients will benefit from chemotherapeutic treatments. There is therefore an urgent need to improve oesophageal cancer disease management and treatment strategies. This work compared proteomic differences in OAC patients who responded well to chemotherapy as compared to those who did not, using quantitative proteomics prior to treatment commencement. SWATH-MS analysis of plasma (with and without albumin/IgG-depletion) from OAC patients prior to chemotherapy was performed. This approach was adopted to determine whether depletion offered a significant improvement in peptide coverage. Resultant datasets demonstrated that depletion increased peptide coverage significantly. Additionally, there was good quantitative agreement between commonly observed peptides. Data analysis was performed by adopting both univariate as well as multivariate analysis strategies. Differentially abundant proteins were identified between treatment response groups based on tumour regression grade. Such proteins included complement C1q sub-components and GSTP1. This study provides a platform for further work, utilising larger sample sets across different treatment regimens for oesophageal cancer, that will aid the development of 'treatment response prediction assays' for stratification of OAC patients prior to chemotherapy.
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Affiliation(s)
- Naici Guo
- School of Mathematics and Statistics, University of St Andrews, St Andrews KY16 9SS, United Kingdom
| | - Giorgos Minas
- School of Mathematics and Statistics, University of St Andrews, St Andrews KY16 9SS, United Kingdom
| | - Silvia A Synowsky
- Biomedical Sciences Research Complex, University of St Andrews, St Andrews KY16 9ST, United Kingdom
| | - Margaret R Dunne
- Department of Surgery, Trinity Translational Medicine Institute, Trinity College Dublin, St James's Hospital, Dublin D08 W9RT, Ireland; Trinity St James's Cancer Institute, St James's Hospital, Dublin D08 W9RT, Ireland; Department of Applied Science, Technological University Dublin, Tallaght, Dublin 24 D24 FKT9, Ireland
| | - Hasnain Ahmed
- Biomedical Sciences Research Complex, University of St Andrews, St Andrews KY16 9ST, United Kingdom; School of Medicine, University of St Andrews, St Andrews KY16 9TF, United Kingdom
| | - Rhiannon McShane
- Biomedical Sciences Research Complex, University of St Andrews, St Andrews KY16 9ST, United Kingdom; School of Medicine, University of St Andrews, St Andrews KY16 9TF, United Kingdom
| | - Anshul Bhardwaj
- Department of Surgery, Trinity Translational Medicine Institute, Trinity College Dublin, St James's Hospital, Dublin D08 W9RT, Ireland
| | - Noel E Donlon
- Department of Surgery, Trinity Translational Medicine Institute, Trinity College Dublin, St James's Hospital, Dublin D08 W9RT, Ireland; Trinity St James's Cancer Institute, St James's Hospital, Dublin D08 W9RT, Ireland
| | - Cliona Lorton
- Department of Surgery, Trinity Translational Medicine Institute, Trinity College Dublin, St James's Hospital, Dublin D08 W9RT, Ireland; Trinity St James's Cancer Institute, St James's Hospital, Dublin D08 W9RT, Ireland; Our Lady's Hospice & Care Services, Harold's Cross, Dublin 6w, Ireland
| | - Jacintha O'Sullivan
- Department of Surgery, Trinity Translational Medicine Institute, Trinity College Dublin, St James's Hospital, Dublin D08 W9RT, Ireland; Trinity St James's Cancer Institute, St James's Hospital, Dublin D08 W9RT, Ireland
| | - John V Reynolds
- Department of Surgery, Trinity Translational Medicine Institute, Trinity College Dublin, St James's Hospital, Dublin D08 W9RT, Ireland; Trinity St James's Cancer Institute, St James's Hospital, Dublin D08 W9RT, Ireland
| | - Peter D Caie
- School of Medicine, University of St Andrews, St Andrews KY16 9TF, United Kingdom
| | - Sally L Shirran
- Biomedical Sciences Research Complex, University of St Andrews, St Andrews KY16 9ST, United Kingdom
| | - Andy G Lynch
- School of Mathematics and Statistics, University of St Andrews, St Andrews KY16 9SS, United Kingdom; School of Medicine, University of St Andrews, St Andrews KY16 9TF, United Kingdom
| | - Alan J Stewart
- Biomedical Sciences Research Complex, University of St Andrews, St Andrews KY16 9ST, United Kingdom; School of Medicine, University of St Andrews, St Andrews KY16 9TF, United Kingdom.
| | - Swati Arya
- Biomedical Sciences Research Complex, University of St Andrews, St Andrews KY16 9ST, United Kingdom; School of Medicine, University of St Andrews, St Andrews KY16 9TF, United Kingdom.
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