2
|
Terekhanova NV, Karpova A, Liang WW, Strzalkowski A, Chen S, Li Y, Southard-Smith AN, Iglesia MD, Wendl MC, Jayasinghe RG, Liu J, Song Y, Cao S, Houston A, Liu X, Wyczalkowski MA, Lu RJH, Caravan W, Shinkle A, Naser Al Deen N, Herndon JM, Mudd J, Ma C, Sarkar H, Sato K, Ibrahim OM, Mo CK, Chasnoff SE, Porta-Pardo E, Held JM, Pachynski R, Schwarz JK, Gillanders WE, Kim AH, Vij R, DiPersio JF, Puram SV, Chheda MG, Fuh KC, DeNardo DG, Fields RC, Chen F, Raphael BJ, Ding L. Epigenetic regulation during cancer transitions across 11 tumour types. Nature 2023; 623:432-441. [PMID: 37914932 PMCID: PMC10632147 DOI: 10.1038/s41586-023-06682-5] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/15/2022] [Accepted: 09/27/2023] [Indexed: 11/03/2023]
Abstract
Chromatin accessibility is essential in regulating gene expression and cellular identity, and alterations in accessibility have been implicated in driving cancer initiation, progression and metastasis1-4. Although the genetic contributions to oncogenic transitions have been investigated, epigenetic drivers remain less understood. Here we constructed a pan-cancer epigenetic and transcriptomic atlas using single-nucleus chromatin accessibility data (using single-nucleus assay for transposase-accessible chromatin) from 225 samples and matched single-cell or single-nucleus RNA-sequencing expression data from 206 samples. With over 1 million cells from each platform analysed through the enrichment of accessible chromatin regions, transcription factor motifs and regulons, we identified epigenetic drivers associated with cancer transitions. Some epigenetic drivers appeared in multiple cancers (for example, regulatory regions of ABCC1 and VEGFA; GATA6 and FOX-family motifs), whereas others were cancer specific (for example, regulatory regions of FGF19, ASAP2 and EN1, and the PBX3 motif). Among epigenetically altered pathways, TP53, hypoxia and TNF signalling were linked to cancer initiation, whereas oestrogen response, epithelial-mesenchymal transition and apical junction were tied to metastatic transition. Furthermore, we revealed a marked correlation between enhancer accessibility and gene expression and uncovered cooperation between epigenetic and genetic drivers. This atlas provides a foundation for further investigation of epigenetic dynamics in cancer transitions.
Collapse
Affiliation(s)
- Nadezhda V Terekhanova
- Department of Medicine, Washington University in St Louis, St Louis, MO, USA
- McDonnell Genome Institute, Washington University in St Louis, St Louis, MO, USA
| | - Alla Karpova
- Department of Medicine, Washington University in St Louis, St Louis, MO, USA
- McDonnell Genome Institute, Washington University in St Louis, St Louis, MO, USA
| | - Wen-Wei Liang
- Department of Medicine, Washington University in St Louis, St Louis, MO, USA
- McDonnell Genome Institute, Washington University in St Louis, St Louis, MO, USA
| | | | - Siqi Chen
- Department of Medicine, Washington University in St Louis, St Louis, MO, USA
- McDonnell Genome Institute, Washington University in St Louis, St Louis, MO, USA
| | - Yize Li
- Department of Medicine, Washington University in St Louis, St Louis, MO, USA
- McDonnell Genome Institute, Washington University in St Louis, St Louis, MO, USA
| | - Austin N Southard-Smith
- Department of Medicine, Washington University in St Louis, St Louis, MO, USA
- McDonnell Genome Institute, Washington University in St Louis, St Louis, MO, USA
| | - Michael D Iglesia
- Department of Medicine, Washington University in St Louis, St Louis, MO, USA
- McDonnell Genome Institute, Washington University in St Louis, St Louis, MO, USA
| | - Michael C Wendl
- Department of Medicine, Washington University in St Louis, St Louis, MO, USA
- McDonnell Genome Institute, Washington University in St Louis, St Louis, MO, USA
| | - Reyka G Jayasinghe
- Department of Medicine, Washington University in St Louis, St Louis, MO, USA
- McDonnell Genome Institute, Washington University in St Louis, St Louis, MO, USA
| | - Jingxian Liu
- Department of Medicine, Washington University in St Louis, St Louis, MO, USA
- McDonnell Genome Institute, Washington University in St Louis, St Louis, MO, USA
| | - Yizhe Song
- Department of Medicine, Washington University in St Louis, St Louis, MO, USA
- McDonnell Genome Institute, Washington University in St Louis, St Louis, MO, USA
| | - Song Cao
- Department of Medicine, Washington University in St Louis, St Louis, MO, USA
- McDonnell Genome Institute, Washington University in St Louis, St Louis, MO, USA
| | - Andrew Houston
- Department of Medicine, Washington University in St Louis, St Louis, MO, USA
- McDonnell Genome Institute, Washington University in St Louis, St Louis, MO, USA
| | - Xiuting Liu
- Department of Medicine, Washington University in St Louis, St Louis, MO, USA
| | - Matthew A Wyczalkowski
- Department of Medicine, Washington University in St Louis, St Louis, MO, USA
- McDonnell Genome Institute, Washington University in St Louis, St Louis, MO, USA
| | - Rita Jui-Hsien Lu
- Department of Medicine, Washington University in St Louis, St Louis, MO, USA
- McDonnell Genome Institute, Washington University in St Louis, St Louis, MO, USA
| | - Wagma Caravan
- Department of Medicine, Washington University in St Louis, St Louis, MO, USA
- McDonnell Genome Institute, Washington University in St Louis, St Louis, MO, USA
| | - Andrew Shinkle
- Department of Medicine, Washington University in St Louis, St Louis, MO, USA
| | - Nataly Naser Al Deen
- Department of Medicine, Washington University in St Louis, St Louis, MO, USA
- McDonnell Genome Institute, Washington University in St Louis, St Louis, MO, USA
| | - John M Herndon
- Department of Surgery, Washington University in St Louis, St Louis, MO, USA
- Siteman Cancer Center, Washington University in St Louis, St Louis, MO, USA
| | - Jacqueline Mudd
- Department of Surgery, Washington University in St Louis, St Louis, MO, USA
| | - Cong Ma
- Department of Computer Science, Princeton University, Princeton, NJ, USA
| | - Hirak Sarkar
- Department of Computer Science, Princeton University, Princeton, NJ, USA
| | - Kazuhito Sato
- Department of Medicine, Washington University in St Louis, St Louis, MO, USA
- McDonnell Genome Institute, Washington University in St Louis, St Louis, MO, USA
| | - Omar M Ibrahim
- Department of Medicine, Washington University in St Louis, St Louis, MO, USA
- McDonnell Genome Institute, Washington University in St Louis, St Louis, MO, USA
| | - Chia-Kuei Mo
- Department of Medicine, Washington University in St Louis, St Louis, MO, USA
- McDonnell Genome Institute, Washington University in St Louis, St Louis, MO, USA
| | - Sara E Chasnoff
- Department of Surgery, Washington University in St Louis, St Louis, MO, USA
- Siteman Cancer Center, Washington University in St Louis, St Louis, MO, USA
| | - Eduard Porta-Pardo
- Josep Carreras Leukaemia Research Institute, Barcelona, Spain
- Barcelona Supercomputing Center, Barcelona, Spain
| | - Jason M Held
- Department of Medicine, Washington University in St Louis, St Louis, MO, USA
- Siteman Cancer Center, Washington University in St Louis, St Louis, MO, USA
| | - Russell Pachynski
- Department of Medicine, Washington University in St Louis, St Louis, MO, USA
- Siteman Cancer Center, Washington University in St Louis, St Louis, MO, USA
| | - Julie K Schwarz
- Department of Radiation Oncology, Washington University in St Louis, St Louis, MO, USA
| | - William E Gillanders
- Department of Surgery, Washington University in St Louis, St Louis, MO, USA
- Siteman Cancer Center, Washington University in St Louis, St Louis, MO, USA
| | - Albert H Kim
- Siteman Cancer Center, Washington University in St Louis, St Louis, MO, USA
- Department of Neurological Surgery, Washington University in St Louis, St Louis, MO, USA
| | - Ravi Vij
- Department of Medicine, Washington University in St Louis, St Louis, MO, USA
- Siteman Cancer Center, Washington University in St Louis, St Louis, MO, USA
| | - John F DiPersio
- Department of Medicine, Washington University in St Louis, St Louis, MO, USA
- Siteman Cancer Center, Washington University in St Louis, St Louis, MO, USA
| | - Sidharth V Puram
- Department of Otolaryngology-Head & Neck Surgery, Washington University in St Louis, St Louis, MO, USA
| | - Milan G Chheda
- Department of Medicine, Washington University in St Louis, St Louis, MO, USA
- Siteman Cancer Center, Washington University in St Louis, St Louis, MO, USA
| | - Katherine C Fuh
- Department of Obstetrics and Gynecology, University of California, San Francisco, San Francisco, CA, USA
- Department of Obstetrics and Gynecology, Washington University in St Louis, St Louis, MO, USA
| | - David G DeNardo
- Department of Medicine, Washington University in St Louis, St Louis, MO, USA
- Siteman Cancer Center, Washington University in St Louis, St Louis, MO, USA
| | - Ryan C Fields
- Department of Surgery, Washington University in St Louis, St Louis, MO, USA.
- Siteman Cancer Center, Washington University in St Louis, St Louis, MO, USA.
| | - Feng Chen
- Department of Medicine, Washington University in St Louis, St Louis, MO, USA.
- Siteman Cancer Center, Washington University in St Louis, St Louis, MO, USA.
| | - Benjamin J Raphael
- Department of Computer Science, Princeton University, Princeton, NJ, USA.
| | - Li Ding
- Department of Medicine, Washington University in St Louis, St Louis, MO, USA.
- McDonnell Genome Institute, Washington University in St Louis, St Louis, MO, USA.
- Siteman Cancer Center, Washington University in St Louis, St Louis, MO, USA.
- Department of Genetics, Washington University in St Louis, St Louis, MO, USA.
| |
Collapse
|
3
|
Li J, Wang S, Chi X, He Q, Tao C, Ding Y, Wang J, Zhao J, Wang W. Identification of heterogeneous subtypes and a prognostic model for gliomas based on mitochondrial dysfunction and oxidative stress-related genes. Front Immunol 2023; 14:1183475. [PMID: 37334354 PMCID: PMC10272431 DOI: 10.3389/fimmu.2023.1183475] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/10/2023] [Accepted: 05/22/2023] [Indexed: 06/20/2023] Open
Abstract
Objective Mitochondrial dysfunction and oxidative stress are known to involved in tumor occurrence and progression. This study aimed to explore the molecular subtypes of lower-grade gliomas (LGGs) based on oxidative stress-related and mitochondrial-related genes (OMRGs) and construct a prognostic model for predicting prognosis and therapeutic response in LGG patients. Methods A total of 223 OMRGs were identified by the overlap of oxidative stress-related genes (ORGs) and mitochondrial-related genes (MRGs). Using consensus clustering analysis, we identified molecular subtypes of LGG samples from TCGA database and confirmed the differentially expressed genes (DEGs) between clusters. We constructed a risk score model using LASSO regression and analyzed the immune-related profiles and drug sensitivity of different risk groups. The prognostic role of the risk score was confirmed using Cox regression and Kaplan-Meier curves, and a nomogram model was constructed to predict OS rates. We validated the prognostic role of OMRG-related risk score in three external datasets. Quantitative real-time PCR (qRT-PCR) and immunohistochemistry (IHC) staining confirmed the expression of selected genes. Furthermore, wound healing and transwell assays were performed to confirm the gene function in glioma. Results We identified two OMRG-related clusters and cluster 1 was significantly associated with poor outcomes (P<0.001). The mutant frequencies of IDH were significantly lower in cluster 1 (P<0.05). We found that the OMRG-related risk scores were significantly correlated to the levels of immune infiltration and immune checkpoint expression. High-risk samples were more sensitive to most chemotherapeutic agents. We identified the prognostic role of OMRG-related risk score in LGG patients (HR=2.665, 95%CI=1.626-4.369, P<0.001) and observed that patients with high-risk scores were significantly associated with poor prognosis (P<0.001). We validated our findings in three external datasets. The results of qRT-PCR and IHC staining verified the expression levels of the selected genes. The functional experiments showed a significant decrease in the migration of glioma after knockdown of SCNN1B. Conclusion We identified two molecular subtypes and constructed a prognostic model, which provided a novel insight into the potential biological function and prognostic significance of mitochondrial dysfunction and oxidative stress in LGG. Our study might help in the development of more precise treatments for gliomas.
Collapse
Affiliation(s)
- Junsheng Li
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
- China National Clinical Research Center for Neurological Diseases, Beijing, China
- Center of Stroke, Beijing Institute for Brain Disorders, Beijing, China
- Beijing Key Laboratory of Translational Medicine for Cerebrovascular Disease, Beijing, China
- Beijing Translational Engineering Center for 3D Printer in Clinical Neuroscience, Beijing, China
| | - Siyu Wang
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Xiaojing Chi
- NHC Key Laboratory of Systems Biology of Pathogens, Institute of Pathogen Biology, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China
| | - Qiheng He
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
- China National Clinical Research Center for Neurological Diseases, Beijing, China
- Center of Stroke, Beijing Institute for Brain Disorders, Beijing, China
- Beijing Key Laboratory of Translational Medicine for Cerebrovascular Disease, Beijing, China
- Beijing Translational Engineering Center for 3D Printer in Clinical Neuroscience, Beijing, China
| | - Chuming Tao
- Department of Neurosurgery, Second Affiliated Hospital of Soochow University, Suzhou, China
| | - Yaowei Ding
- Department of Clinical Diagnosis, Laboratory of Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Jia Wang
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
- China National Clinical Research Center for Neurological Diseases, Beijing, China
- Center of Stroke, Beijing Institute for Brain Disorders, Beijing, China
- Beijing Key Laboratory of Translational Medicine for Cerebrovascular Disease, Beijing, China
- Beijing Translational Engineering Center for 3D Printer in Clinical Neuroscience, Beijing, China
| | - Jizong Zhao
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
- China National Clinical Research Center for Neurological Diseases, Beijing, China
- Center of Stroke, Beijing Institute for Brain Disorders, Beijing, China
- Beijing Key Laboratory of Translational Medicine for Cerebrovascular Disease, Beijing, China
- Beijing Translational Engineering Center for 3D Printer in Clinical Neuroscience, Beijing, China
- Savaid Medical School, University of the Chinese Academy of Sciences, Beijing, China
| | - Wen Wang
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
- China National Clinical Research Center for Neurological Diseases, Beijing, China
- Center of Stroke, Beijing Institute for Brain Disorders, Beijing, China
- Beijing Key Laboratory of Translational Medicine for Cerebrovascular Disease, Beijing, China
- Beijing Translational Engineering Center for 3D Printer in Clinical Neuroscience, Beijing, China
| |
Collapse
|