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Teixeira AF, Wang Y, Iaria J, Ten Dijke P, Zhu HJ. Simultaneously targeting extracellular vesicle trafficking and TGF-β receptor kinase activity blocks signaling hyperactivation and metastasis. Signal Transduct Target Ther 2023; 8:456. [PMID: 38105247 PMCID: PMC10725874 DOI: 10.1038/s41392-023-01711-1] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/29/2023] [Revised: 10/30/2023] [Accepted: 11/15/2023] [Indexed: 12/19/2023] Open
Abstract
Metastasis is the leading cause of cancer-related deaths. Transforming growth factor beta (TGF-β) signaling drives metastasis and is strongly enhanced during cancer progression. Yet, the use of on-target TGF-β signaling inhibitors in the treatment of cancer patients remains unsuccessful, highlighting a gap in the understanding of TGF-β biology that limits the establishment of efficient anti-metastatic therapies. Here, we show that TGF-β signaling hyperactivation in breast cancer cells is required for metastasis and relies on increased small extracellular vesicle (sEV) secretion. Demonstrating sEV's unique role, TGF-β signaling levels induced by sEVs exceed the activity of matching concentrations of soluble ligand TGF-β. Further, genetic disruption of sEV secretion in highly-metastatic breast cancer cells impairs cancer cell aggressiveness by reducing TGF-β signaling to nearly-normal levels. Otherwise, TGF-β signaling activity in non-invasive breast cancer cells is inherently low, but can be amplified by sEVs, enabling invasion and metastasis of poorly-metastatic breast cancer cells. Underscoring the translational potential of inhibiting sEV trafficking in advanced breast cancers, treatment with dimethyl amiloride (DMA) decreases sEV secretion, TGF-β signaling activity, and breast cancer progression in vivo. Targeting both the sEV trafficking and TGF-β signaling by combining DMA and SB431542 at suboptimal doses potentiated this effect, normalizing the TGF-β signaling in primary tumors to potently reduce circulating tumor cells, metastasis, and tumor self-seeding. Collectively, this study establishes sEVs as critical elements in TGF-β biology, demonstrating the feasibility of inhibiting sEV trafficking as a new therapeutic approach to impair metastasis by normalizing TGF-β signaling levels in breast cancer cells.
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Affiliation(s)
- Adilson Fonseca Teixeira
- Department of Surgery (The Royal Melbourne Hospital), The University of Melbourne, Parkville, VIC, Australia
- Huagene Institute, Kecheng Science and Technology Park, Pukou District, Nanjing, Jiangsu, China
| | - Yanhong Wang
- Department of Surgery (The Royal Melbourne Hospital), The University of Melbourne, Parkville, VIC, Australia
| | - Josephine Iaria
- Department of Surgery (The Royal Melbourne Hospital), The University of Melbourne, Parkville, VIC, Australia
- Huagene Institute, Kecheng Science and Technology Park, Pukou District, Nanjing, Jiangsu, China
| | - Peter Ten Dijke
- Department of Cell and Chemical Biology, Oncode Institute, Leiden University Medical Center, Leiden, The Netherlands
| | - Hong-Jian Zhu
- Department of Surgery (The Royal Melbourne Hospital), The University of Melbourne, Parkville, VIC, Australia.
- Huagene Institute, Kecheng Science and Technology Park, Pukou District, Nanjing, Jiangsu, China.
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Ning C, Cai P, Liu X, Li G, Bao P, Yan L, Ning M, Tang K, Luo Y, Guo H, Wang Y, Wang Z, Chen L, Lu ZJ, Yin J. A comprehensive evaluation of full-spectrum cell-free RNAs highlights cell-free RNA fragments for early-stage hepatocellular carcinoma detection. EBioMedicine 2023; 93:104645. [PMID: 37315449 PMCID: PMC10363443 DOI: 10.1016/j.ebiom.2023.104645] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/13/2023] [Revised: 05/20/2023] [Accepted: 05/22/2023] [Indexed: 06/16/2023] Open
Abstract
BACKGROUND Various studies have reported cell-free RNAs (cfRNAs) as noninvasive biomarkers for detecting hepatocellular carcinoma (HCC). However, they have not been independently validated, and some results are contradictory. We provided a comprehensive evaluation of various types of cfRNA biomarkers and a full mining of the biomarker potential of new features of cfRNA. METHODS We first systematically reviewed reported cfRNA biomarkers and calculated dysregulated post-transcriptional events and cfRNA fragments. In 3 independent multicentre cohorts, we further selected 6 cfRNAs using RT-qPCR, built a panel called HCCMDP with AFP using machine learning, and internally and externally validated HCCMDP's performance. FINDINGS We identified 23 cfRNA biomarker candidates from a systematic review and analysis of 5 cfRNA-seq datasets. Notably, we defined the cfRNA domain to describe cfRNA fragments systematically. In the verification cohort (n = 183), cfRNA fragments were more likely to be verified, while circRNA and chimeric RNA candidates were neither abundant nor stable as qPCR-based biomarkers. In the algorithm development cohort (n = 287), we build and test the panel HCCMDP with 6 cfRNA markers and AFP. In the independent validation cohort (n = 171), HCCMDP can distinguish HCC patients from control groups (all: AUC = 0.925; CHB: AUC = 0.909; LC: AUC = 0.916), and performs well in distinguishing early-stage HCC patients (all: AUC = 0.936; CHB: AUC = 0.917; LC: AUC = 0.928). INTERPRETATION This study comprehensively evaluated full-spectrum cfRNA biomarker types for HCC detection, highlighted the cfRNA fragment as a promising biomarker type in HCC detection, and provided a panel HCCMDP. FUNDING National Natural Science Foundation of China, and The National Key Basic Research Program (973 program).
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Affiliation(s)
- Chun Ning
- Chinese Academy of Medical Sciences & Peking Union Medical College, No. 9 Dongdansantiao, Beijing, 100730, China; MOE Key Laboratory of Bioinformatics, Centre for Synthetic and Systems Biology, School of Life Sciences, Tsinghua University, Beijing, 100084, China
| | - Peng Cai
- Department of Epidemiology, Naval Medical University, Key Laboratory of Biosafety Defense, Ministry of Education, Shanghai, 200433, China
| | - Xiaofan Liu
- MOE Key Laboratory of Bioinformatics, Centre for Synthetic and Systems Biology, School of Life Sciences, Tsinghua University, Beijing, 100084, China
| | - Guangtao Li
- Department of Hepatobiliary Cancer, Liver Cancer Research Centre, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Centre for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin's Clinical Research Centre for Cancer, Tianjin, 300060, China
| | - Pengfei Bao
- MOE Key Laboratory of Bioinformatics, Centre for Synthetic and Systems Biology, School of Life Sciences, Tsinghua University, Beijing, 100084, China
| | - Lu Yan
- MOE Key Laboratory of Bioinformatics, Centre for Synthetic and Systems Biology, School of Life Sciences, Tsinghua University, Beijing, 100084, China
| | - Meng Ning
- Tianjin Third Central Hospital, 83 Jintang Road, Hedong District, Tianjin, 300170, China
| | - Kaichen Tang
- Chinese Academy of Medical Sciences & Peking Union Medical College, No. 9 Dongdansantiao, Beijing, 100730, China; MOE Key Laboratory of Bioinformatics, Centre for Synthetic and Systems Biology, School of Life Sciences, Tsinghua University, Beijing, 100084, China
| | - Yi Luo
- Department of Hepatobiliary Cancer, Liver Cancer Research Centre, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Centre for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin's Clinical Research Centre for Cancer, Tianjin, 300060, China
| | - Hua Guo
- Department of Hepatobiliary Cancer, Liver Cancer Research Centre, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Centre for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin's Clinical Research Centre for Cancer, Tianjin, 300060, China
| | - Yunjiu Wang
- Department of Clinical Laboratory, Shuguang Hospital Affiliated to Shanghai University of Traditional Chinese Medicine, Shanghai, 200433, China
| | - Zhuoran Wang
- Department of Surgery, Eastern Hepatobiliary Surgery Hospital, Navy Medical University, Shanghai, 200433, China
| | - Lu Chen
- Department of Hepatobiliary Cancer, Liver Cancer Research Centre, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Centre for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin's Clinical Research Centre for Cancer, Tianjin, 300060, China.
| | - Zhi John Lu
- MOE Key Laboratory of Bioinformatics, Centre for Synthetic and Systems Biology, School of Life Sciences, Tsinghua University, Beijing, 100084, China.
| | - Jianhua Yin
- Department of Epidemiology, Naval Medical University, Key Laboratory of Biosafety Defense, Ministry of Education, Shanghai, 200433, China.
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