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Kampan NC, Kartikasari AER, Deceneux C, Madondo MT, McNally OM, Flanagan KL, Aziz NA, Stephens AN, Reynolds J, Quinn MA, Plebanski M. Combining TNFR2-Expressing Tregs and IL-6 as Superior Diagnostic Biomarkers for High-Grade Serous Ovarian Cancer Masses. Cancers (Basel) 2023; 15:cancers15030667. [PMID: 36765633 PMCID: PMC9913655 DOI: 10.3390/cancers15030667] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/10/2022] [Revised: 01/14/2023] [Accepted: 01/19/2023] [Indexed: 01/24/2023] Open
Abstract
We hypothesised that the inclusion of immunosuppressive and inflammatory biomarkers in HGSOC patients would improve the sensitivity and specificity of the preoperative marker prediction of malignancy in patients with ovarian masses. We tested a panel of 29 soluble immune factors by multiplex bead immunoassay and 16 phenotypic T cell markers by flow cytometry in pre-treatment blood samples from 66 patients undergoing surgery for suspected ovarian cancer or ovarian cancer risk reduction. The potential diagnostic utility of all parameters was explored using Volcano plots, principal component analysis (PCA) and receiver operator characteristic (ROC) analysis. We also assessed the effect of culturing PBMCs from 20 healthy donors in the presence of malignant ascites fluid. The combination of TNFR2+ Tregs and IL-6 in the pre-treatment blood of patients with advanced HGSOC effectively discriminated patients with benign or malignant ovarian masses. In vitro culturing of the PBMCs of healthy donors in malignant ascites promoted an increase in TNFR2-expressing Tregs, which were decreased following blockade with IL-6 or STAT3 activity. Pre-treatment serum IL-6 and peripheral blood TNFR2+ Tregs may be potential clinical biomarkers that can discriminate patients with malignant compared to benign ovarian cancer masses, and the relationship between IL-6 and TNFR2+ Treg is likely to be mediated via the STAT3 signalling pathway.
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Affiliation(s)
- Nirmala Chandralega Kampan
- Department of Immunology & Pathology, Faculty of Medicine, Nursing and Health Sciences, Monash University, Level 6, The Alfred, Commercial Road, Melbourne, VIC 3181, Australia
- Oncology Unit, Royal Women’s Hospital, 20 Flemington Road, Parkville, VIC 3052, Australia
- Department of Obstetrics and Gynaecology, Faculty of Medicine, Universiti Kebangsaan Malaysia, Kuala Lumpur 56000, Malaysia
| | | | - Cyril Deceneux
- School of Health and Biomedical Sciences, RMIT University, Melbourne, VIC 3083, Australia
| | - Mutsa Tatenda Madondo
- Department of Immunology & Pathology, Faculty of Medicine, Nursing and Health Sciences, Monash University, Level 6, The Alfred, Commercial Road, Melbourne, VIC 3181, Australia
| | - Orla M. McNally
- Oncology Unit, Royal Women’s Hospital, 20 Flemington Road, Parkville, VIC 3052, Australia
- Department of Obstetrics and Gynaecology, Melbourne University, Parkville, VIC 3052, Australia
| | - Katie Louise Flanagan
- School of Health and Biomedical Sciences, RMIT University, Melbourne, VIC 3083, Australia
- Tasmanian Vaccine Trial Centre, Clifford Craig Foundation, Launceston General Hospital, Launceston, TAS 7250, Australia
- School of Health Sciences and School of Medicine, University of Tasmania, Hobart, TAS 7005, Australia
| | - Norhaslinda A. Aziz
- Department of Obstetrics and Gynaecology, Faculty of Medicine, Universiti Kebangsaan Malaysia, Kuala Lumpur 56000, Malaysia
| | - Andrew N. Stephens
- Centre for Cancer Research, Hudson Institute of Medical Research, Clayton, VIC 3168, Australia
- Department of Molecular and Translational Sciences, Monash University, Clayton, VIC 3800, Australia
- Epworth Research Institute, Epworth Healthcare, Richmond, VIC 3121, Australia
| | - John Reynolds
- Biostatistics Consulting Platform, Faculty of Medicine, Nursing and Health Sciences, Monash University, Level 6, The Alfred, Commercial Road, Melbourne, VIC 3181, Australia
| | - Michael A. Quinn
- Oncology Unit, Royal Women’s Hospital, 20 Flemington Road, Parkville, VIC 3052, Australia
| | - Magdalena Plebanski
- Department of Immunology & Pathology, Faculty of Medicine, Nursing and Health Sciences, Monash University, Level 6, The Alfred, Commercial Road, Melbourne, VIC 3181, Australia
- School of Health and Biomedical Sciences, RMIT University, Melbourne, VIC 3083, Australia
- Correspondence:
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Shared Genetic Regulatory Networks Contribute to Neuropathic and Inflammatory Pain: Multi-Omics Systems Analysis. Biomolecules 2022; 12:biom12101454. [PMID: 36291662 PMCID: PMC9599593 DOI: 10.3390/biom12101454] [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: 09/04/2022] [Revised: 09/27/2022] [Accepted: 10/07/2022] [Indexed: 11/17/2022] Open
Abstract
The mechanisms of chronic pain are complex, and genetic factors play an essential role in the development of chronic pain. Neuropathic pain (NP) and inflammatory pain (IP) are two primary components of chronic pain. Previous studies have uncovered some common biological processes in NP and IP. However, the shared genetic mechanisms remained poorly studied. We utilized multi-omics systematic analyses to investigate the shared genetic mechanisms of NP and IP. First, by integrating several genome-wide association studies (GWASs) with multi-omics data, we revealed the significant overlap of the gene co-expression modules in NP and IP. Further, we uncovered the shared biological pathways, including the previously reported mitochondrial electron transport and ATP metabolism, and stressed the role of genetic factors in chronic pain with neurodegenerative diseases. Second, we identified 24 conservative key drivers (KDs) contributing to NP and IP, containing two well-established pain genes, IL1B and OPRM1, and some novel potential pain genes, such as C5AR1 and SERPINE1. The subnetwork of those KDs highlighted the processes involving the immune system. Finally, gene expression analysis of the KDs in mouse models underlined two of the KDs, SLC6A15 and KCNQ5, with unidirectional regulatory functions in NP and IP. Our study provides strong evidence to support the current understanding of the shared genetic regulatory networks underlying NP and IP and potentially benefit the future common therapeutic avenues for chronic pain.
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