1
|
Jiang Y, Gao S, Sun H, Wu X, Gu J, Wu H, Liao Y, Ben-Ami R, Miao C, Shen R, Liu J, Chen W. Targeting NEDD8 suppresses surgical stress-facilitated metastasis of colon cancer via restraining regulatory T cells. Cell Death Dis 2024; 15:8. [PMID: 38177106 PMCID: PMC10767093 DOI: 10.1038/s41419-023-06396-6] [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: 07/20/2023] [Revised: 12/10/2023] [Accepted: 12/15/2023] [Indexed: 01/06/2024]
Abstract
Regulatory T cells (Tregs) are a key determinant for the immunosuppressive and premetastatic niche for cancer progression after surgery resection. However, the precise mechanisms regulating Tregs function during surgical stress-facilitated cancer metastasis remain unknown. This study aims to unravel the mechanisms and explore potential strategies for preventing surgical stress-induced metastasis by targeting NEDD8. Using a surgical stress mouse model, we found that surgical stress results in the increased expression of NEDD8 in Tregs. NEDD8 depletion abrogates postoperative lung metastasis of colon cancer cells by inhibiting Treg immunosuppression and thereby partially recovering CD8+T cell and NK cell-mediated anti-tumor immunity. Furthermore, Treg mitophagy and mitochondrial respiration exacerbated in surgically stressed mice were attenuated by NEDD8 depletion. Our observations suggest that cancer progression may result from surgery-induced enhancement of NEDD8 expression and the subsequent immunosuppressive function of Tregs. More importantly, depleting or inhibiting NEDD8 can be an efficient strategy to reduce cancer metastasis after surgery resection by regulating the function of Tregs.
Collapse
Affiliation(s)
- Yi Jiang
- Department of Anesthesiology, Zhongshan Hospital, Fudan University, Shanghai, 200032, China
- Shanghai Key laboratory of Perioperative Stress and Protection, Shanghai, 200032, China
| | - Shenjia Gao
- Department of Anesthesiology, Zhongshan Hospital, Fudan University, Shanghai, 200032, China
- Shanghai Key laboratory of Perioperative Stress and Protection, Shanghai, 200032, China
| | - Hao Sun
- Department of Anesthesiology, Zhongshan Hospital, Fudan University, Shanghai, 200032, China
- Shanghai Key laboratory of Perioperative Stress and Protection, Shanghai, 200032, China
| | - Xinyi Wu
- Department of Anesthesiology, Zhongshan Hospital, Fudan University, Shanghai, 200032, China
- Shanghai Key laboratory of Perioperative Stress and Protection, Shanghai, 200032, China
| | - Jiahui Gu
- Department of Anesthesiology, Zhongshan Hospital, Fudan University, Shanghai, 200032, China
- Shanghai Key laboratory of Perioperative Stress and Protection, Shanghai, 200032, China
| | - Han Wu
- Department of Anesthesiology, Zhongshan Hospital, Fudan University, Shanghai, 200032, China
- Shanghai Key laboratory of Perioperative Stress and Protection, Shanghai, 200032, China
| | - Yun Liao
- School of Basic Medical Science, Shanghai Medical College of Fudan University, Shanghai, 200032, China
| | - Ronen Ben-Ami
- Infectious Diseases Unit, Tel Aviv Sourasky Medical Center, Faculty of Medicine, Tel Aviv University, Tel Aviv, 6997801, Israel
| | - Changhong Miao
- Department of Anesthesiology, Zhongshan Hospital, Fudan University, Shanghai, 200032, China
- Shanghai Key laboratory of Perioperative Stress and Protection, Shanghai, 200032, China
| | - Rong Shen
- Department of Pathology, Nanfang Hospital, Southern Medical University, Guangzhou, 510515, Guangdong, China.
| | - Jinlong Liu
- Institute of Translational Medicine, Shanghai University, Shanghai, 200444, China.
| | - Wankun Chen
- Department of Anesthesiology, Zhongshan Hospital, Fudan University, Shanghai, 200032, China.
- Shanghai Key laboratory of Perioperative Stress and Protection, Shanghai, 200032, China.
- Department of Anesthesiology, Shanghai Geriatric Medical Center, Shanghai, 201104, China.
- Department of Anesthesiology, QingPu Branch of Zhongshan Hospital, Fudan University, Shanghai, 201799, China.
| |
Collapse
|
2
|
Sun J, Chen F, Wu G. Role of NF-κB pathway in kidney renal clear cell carcinoma and its potential therapeutic implications. Aging (Albany NY) 2023; 15:11313-11330. [PMID: 37847185 PMCID: PMC10637793 DOI: 10.18632/aging.205129] [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: 07/14/2023] [Accepted: 10/02/2023] [Indexed: 10/18/2023]
Abstract
Kidney renal clear cell carcinoma (KIRC), a common malignant tumor of the urinary system, is the most aggressive renal tumor subtype. Since the discovery of nuclear factor kappa B (NF-κB) in 1986, many studies have demonstrated abnormal NF-κB signaling is associated with the development of various cancers, including kidney renal clear cell carcinoma. In this study, the relationship between NF-κB and kidney renal clear cell carcinoma was confirmed using bioinformatics analysis. First, we explored the differential expression of copy number variation (CNV), single nucleotide variant (SNV), and messenger RNA (mRNA) in NF-κB-related genes in different types of cancer, as well as the impact on cancer prognosis and sensitivity to common chemotherapy drugs. Then, we divided the mRNA expression levels of NF-κB-related genes in KIRC patients into three groups through GSVA cluster analysis and explored the correlation between the NF-κB pathway and clinical data of KIRC patients, classical cancer-related genes, common anticancer drug responsiveness, and immune cell infiltration. Finally, 11 tumor-related genes were screened using least absolute shrinkage and selection operator (LASSO) regression to construct a prognostic model. In addition, we used the UALCAN and HPA databases to verify the protein levels of three key NF-κB-related genes (CHUK, IKGGB, and IKBKG) in KIRC. In conclusion, our study established a prognostic survival model based on NF-κB-related genes, which can be used to predict the prognosis of patients with KIRC.
Collapse
Affiliation(s)
- Jiaao Sun
- Department of Urology, The First Affiliated Hospital of Dalian Medical University, Dalian 116011, China
| | - Feng Chen
- Department of Urology, The First Affiliated Hospital of Dalian Medical University, Dalian 116011, China
| | - Guangzhen Wu
- Department of Urology, The First Affiliated Hospital of Dalian Medical University, Dalian 116011, China
| |
Collapse
|