51
|
Xue M, Dong L, Zhang H, Li Y, Qiu K, Zhao Z, Gao M, Han L, Chan AKN, Li W, Leung K, Wang K, Pokharel SP, Qing Y, Liu W, Wang X, Ren L, Bi H, Yang L, Shen C, Chen Z, Melstrom L, Li H, Timchenko N, Deng X, Huang W, Rosen ST, Tian J, Xu L, Diao J, Chen CW, Chen J, Shen B, Chen H, Su R. METTL16 promotes liver cancer stem cell self-renewal via controlling ribosome biogenesis and mRNA translation. J Hematol Oncol 2024; 17:7. [PMID: 38302992 PMCID: PMC10835888 DOI: 10.1186/s13045-024-01526-9] [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: 04/19/2023] [Accepted: 01/20/2024] [Indexed: 02/03/2024] Open
Abstract
BACKGROUND While liver cancer stem cells (CSCs) play a crucial role in hepatocellular carcinoma (HCC) initiation, progression, recurrence, and treatment resistance, the mechanism underlying liver CSC self-renewal remains elusive. We aim to characterize the role of Methyltransferase 16 (METTL16), a recently identified RNA N6-methyladenosine (m6A) methyltransferase, in HCC development/maintenance, CSC stemness, as well as normal hepatogenesis. METHODS Liver-specific Mettl16 conditional KO (cKO) mice were generated to assess its role in HCC pathogenesis and normal hepatogenesis. Hydrodynamic tail-vein injection (HDTVi)-induced de novo hepatocarcinogenesis and xenograft models were utilized to determine the role of METTL16 in HCC initiation and progression. A limiting dilution assay was utilized to evaluate CSC frequency. Functionally essential targets were revealed via integrative analysis of multi-omics data, including RNA-seq, RNA immunoprecipitation (RIP)-seq, and ribosome profiling. RESULTS METTL16 is highly expressed in liver CSCs and its depletion dramatically decreased CSC frequency in vitro and in vivo. Mettl16 KO significantly attenuated HCC initiation and progression, yet only slightly influenced normal hepatogenesis. Mechanistic studies, including high-throughput sequencing, unveiled METTL16 as a key regulator of ribosomal RNA (rRNA) maturation and mRNA translation and identified eukaryotic translation initiation factor 3 subunit a (eIF3a) transcript as a bona-fide target of METTL16 in HCC. In addition, the functionally essential regions of METTL16 were revealed by CRISPR gene tiling scan, which will pave the way for the development of potential inhibitor(s). CONCLUSIONS Our findings highlight the crucial oncogenic role of METTL16 in promoting HCC pathogenesis and enhancing liver CSC self-renewal through augmenting mRNA translation efficiency.
Collapse
Affiliation(s)
- Meilin Xue
- Department of Systems Biology, Beckman Research Institute of City of Hope, Monrovia, CA, 91016, USA
- Department of General Surgery, Pancreatic Disease Center, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China
| | - Lei Dong
- Department of Systems Biology, Beckman Research Institute of City of Hope, Monrovia, CA, 91016, USA
- Quantitative Biomedical Research Center, Peter O'Donnell Jr. School of Public Health, UT Southwestern Medical Center, Dallas, TX, 7539, USA
| | - Honghai Zhang
- Department of Systems Biology, Beckman Research Institute of City of Hope, Monrovia, CA, 91016, USA
| | - Yangchan Li
- Department of Systems Biology, Beckman Research Institute of City of Hope, Monrovia, CA, 91016, USA
- Department of Radiation Oncology, The First Affiliated Hospital of Sun Yat-Sen University, Guangzhou, 510080, Guangdong, China
| | - Kangqiang Qiu
- Department of Cancer Biology, University of Cincinnati College of Medicine, Cincinnati, OH, 45267, USA
| | - Zhicong Zhao
- Department of Systems Biology, Beckman Research Institute of City of Hope, Monrovia, CA, 91016, USA
- Department of Liver Surgery, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, 200127, China
| | - Min Gao
- Department of Systems Biology, Beckman Research Institute of City of Hope, Monrovia, CA, 91016, USA
| | - Li Han
- Department of Systems Biology, Beckman Research Institute of City of Hope, Monrovia, CA, 91016, USA
- School of Pharmacy, China Medical University, Shenyang, 110001, Liaoning, China
| | - Anthony K N Chan
- Department of Systems Biology, Beckman Research Institute of City of Hope, Monrovia, CA, 91016, USA
| | - Wei Li
- Department of Systems Biology, Beckman Research Institute of City of Hope, Monrovia, CA, 91016, USA
| | - Keith Leung
- Department of Systems Biology, Beckman Research Institute of City of Hope, Monrovia, CA, 91016, USA
| | - Kitty Wang
- Department of Systems Biology, Beckman Research Institute of City of Hope, Monrovia, CA, 91016, USA
| | - Sheela Pangeni Pokharel
- Department of Systems Biology, Beckman Research Institute of City of Hope, Monrovia, CA, 91016, USA
| | - Ying Qing
- Department of Systems Biology, Beckman Research Institute of City of Hope, Monrovia, CA, 91016, USA
| | - Wei Liu
- Department of Systems Biology, Beckman Research Institute of City of Hope, Monrovia, CA, 91016, USA
| | - Xueer Wang
- Department of Systems Biology, Beckman Research Institute of City of Hope, Monrovia, CA, 91016, USA
| | - Lili Ren
- Department of Systems Biology, Beckman Research Institute of City of Hope, Monrovia, CA, 91016, USA
| | - Hongjie Bi
- Department of Systems Biology, Beckman Research Institute of City of Hope, Monrovia, CA, 91016, USA
| | - Lu Yang
- Department of Systems Biology, Beckman Research Institute of City of Hope, Monrovia, CA, 91016, USA
| | - Chao Shen
- Department of Systems Biology, Beckman Research Institute of City of Hope, Monrovia, CA, 91016, USA
| | - Zhenhua Chen
- Department of Systems Biology, Beckman Research Institute of City of Hope, Monrovia, CA, 91016, USA
| | - Laleh Melstrom
- Division of Surgical Oncology, Department of Surgery, Beckman Research Institute of City of Hope Comprehensive Cancer Center, Duarte, CA, 91010, USA
| | - Hongzhi Li
- Department of Molecular Medicine, City of Hope National Medical Center, Duarte, CA, 91016, USA
| | - Nikolai Timchenko
- Division of General and Thoracic Surgery, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, 45229, USA
| | - Xiaolan Deng
- Department of Systems Biology, Beckman Research Institute of City of Hope, Monrovia, CA, 91016, USA
| | - Wendong Huang
- Department of Diabetes Complications and Metabolism, Diabetes and Metabolism Research Institute, Beckman Research Institute of City of Hope, Duarte, CA, 91010, USA
- Graduate School of Biological Science, City of Hope, Duarte, CA, 91010, USA
| | - Steven T Rosen
- City of Hope Comprehensive Cancer Center, City of Hope, Duarte, CA, 91010, USA
| | - Jingyan Tian
- State Key Laboratory of Medical Genomics, Clinical Trial Center, Shanghai Institute of Endocrine and Metabolic Diseases, Department of Endocrinology and Metabolism, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China
| | - Lin Xu
- Quantitative Biomedical Research Center, Peter O'Donnell Jr. School of Public Health, UT Southwestern Medical Center, Dallas, TX, 7539, USA
| | - Jiajie Diao
- Department of Cancer Biology, University of Cincinnati College of Medicine, Cincinnati, OH, 45267, USA
| | - Chun-Wei Chen
- Department of Systems Biology, Beckman Research Institute of City of Hope, Monrovia, CA, 91016, USA
- City of Hope Comprehensive Cancer Center, City of Hope, Duarte, CA, 91010, USA
| | - Jianjun Chen
- Department of Systems Biology, Beckman Research Institute of City of Hope, Monrovia, CA, 91016, USA
- City of Hope Comprehensive Cancer Center, City of Hope, Duarte, CA, 91010, USA
- Gehr Family Center for Leukemia Research, City of Hope, Duarte, CA, 91010, USA
| | - Baiyong Shen
- Department of General Surgery, Pancreatic Disease Center, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China.
| | - Hao Chen
- Department of General Surgery, Pancreatic Disease Center, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China.
| | - Rui Su
- Department of Systems Biology, Beckman Research Institute of City of Hope, Monrovia, CA, 91016, USA.
- City of Hope Comprehensive Cancer Center, City of Hope, Duarte, CA, 91010, USA.
| |
Collapse
|
52
|
Chen G, Xu W, Long Z, Chong Y, Lin B, Jie Y. Single-cell Technologies Provide Novel Insights into Liver Physiology and Pathology. J Clin Transl Hepatol 2024; 12:79-90. [PMID: 38250462 PMCID: PMC10794276 DOI: 10.14218/jcth.2023.00224] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/12/2023] [Revised: 06/25/2023] [Accepted: 07/12/2023] [Indexed: 01/23/2024] Open
Abstract
The liver is the largest glandular organ in the body and has a unique distribution of cells and biomolecules. However, the treatment outcome of end-stage liver disease is extremely poor. Single-cell sequencing is a new advanced and powerful technique for identifying rare cell populations and biomolecules by analyzing the characteristics of gene expression between individual cells. These cells and biomolecules might be used as potential targets for immunotherapy of liver diseases and contribute to the development of precise individualized treatment. Compared to whole-tissue RNA sequencing, single-cell RNA sequencing (scRNA-seq) or other single-cell histological techniques have solved the problem of cell population heterogeneity and characterize molecular changes associated with liver diseases with higher accuracy and resolution. In this review, we comprehensively summarized single-cell approaches including transcriptomic, spatial transcriptomic, immunomic, proteomic, epigenomic, and multiomic technologies, and described their application in liver physiology and pathology. We also discussed advanced techniques and recent studies in the field of single-cell; our review might provide new insights into the pathophysiological mechanisms of the liver to achieve precise and individualized treatment of liver diseases.
Collapse
Affiliation(s)
| | | | - Zhicong Long
- Department of Infectious Diseases, The Third Affiliated Hospital of Sun Yat-sen University, Guangzhou, Guangdong, China
| | - Yutian Chong
- Department of Infectious Diseases, The Third Affiliated Hospital of Sun Yat-sen University, Guangzhou, Guangdong, China
| | - Bingliang Lin
- Department of Infectious Diseases, The Third Affiliated Hospital of Sun Yat-sen University, Guangzhou, Guangdong, China
| | - Yusheng Jie
- Department of Infectious Diseases, The Third Affiliated Hospital of Sun Yat-sen University, Guangzhou, Guangdong, China
| |
Collapse
|
53
|
Liu G, Hu Q, Peng S, Ning H, Mai J, Chen X, Tao M, Liu Q, Huang H, Jiang Y, Ding Y, Zhang X, Gu J, Xie Z. The spatial and single-cell analysis reveals remodeled immune microenvironment induced by synthetic oncolytic adenovirus treatment. Cancer Lett 2024; 581:216485. [PMID: 38008394 DOI: 10.1016/j.canlet.2023.216485] [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: 08/01/2023] [Revised: 10/16/2023] [Accepted: 11/04/2023] [Indexed: 11/28/2023]
Abstract
Oncolytic viruses are multifaceted tumor killers, which can function as tumor vaccines to boost systemic antitumor immunity. In previous study, we rationally designed a synthetic oncolytic adenovirus (SynOV) harboring a synthetic gene circuit, which can kill tumors in mouse hepatocellular carcinoma (HCC) models. In this study, we demonstrated that SynOV could sense the tumor biomarkers to lyse tumors in a dosage-dependent manner, and killed PD-L1 antibody resistant tumor cells in mouse model. Meanwhile, we observed SynOV could cure liver cancer and partially alleviate the liver cancer with distant metastasis by activating systemic antitumor immunity. To understand its high efficacy, it is essential to explore the cellular and molecular features of the remodeled tumor microenvironment (TME). By combining spatial transcriptome sequencing and single-cell RNA sequencing, we successfully depicted the remodeled TME at single cell resolution. The state transition of immune cells and stromal cells towards an antitumor and normalized status exemplified the overall cancer-suppressive TME after SynOV treatment. Specifically, SynOV treatment increased the proportion of CD8+ T cells, enhanced the cell-cell communication of Cxcl9-Cxcr3, and normalized the Kupffer cells and macrophages in the TME. Furthermore, we observed that SynOV could induce distant responses to reduce tumor burden in metastatic HCC patient in the Phase I clinical trial. In summary, our results suggest that SynOV can trigger systemic antitumor immunity to induce CD8+ T cells and normalize the abundance of immune cells to remodel the TME, which promises a powerful option to treat HCC in the future.
Collapse
Affiliation(s)
- Gan Liu
- MOE Key Laboratory of Bioinformatics and Bioinformatics Division, Center for Synthetic and Systems Biology, Department of Automation, Beijing National Research Center for Information Science and Technology, Tsinghua University, Beijing, 100084, China; Beijing SyngenTech Co., LTD, Zhongguancun Life Science Park, Changping District, Beijing, 102206, China.
| | - Qifan Hu
- MOE Key Laboratory of Bioinformatics and Bioinformatics Division, Center for Synthetic and Systems Biology, Department of Automation, Beijing National Research Center for Information Science and Technology, Tsinghua University, Beijing, 100084, China
| | - Shuguang Peng
- MOE Key Laboratory of Bioinformatics and Bioinformatics Division, Center for Synthetic and Systems Biology, Department of Automation, Beijing National Research Center for Information Science and Technology, Tsinghua University, Beijing, 100084, China
| | - Hui Ning
- MOE Key Laboratory of Bioinformatics and Bioinformatics Division, Center for Synthetic and Systems Biology, Department of Automation, Beijing National Research Center for Information Science and Technology, Tsinghua University, Beijing, 100084, China
| | - Jiajia Mai
- Phase I Clinical Research Center, The First Hospital of Jilin University, Jilin, China
| | - Xi Chen
- MOE Key Laboratory of Bioinformatics and Bioinformatics Division, Center for Synthetic and Systems Biology, Department of Automation, Beijing National Research Center for Information Science and Technology, Tsinghua University, Beijing, 100084, China
| | - Minzhen Tao
- MOE Key Laboratory of Bioinformatics and Bioinformatics Division, Center for Synthetic and Systems Biology, Department of Automation, Beijing National Research Center for Information Science and Technology, Tsinghua University, Beijing, 100084, China
| | - Qiang Liu
- Beijing SyngenTech Co., LTD, Zhongguancun Life Science Park, Changping District, Beijing, 102206, China
| | - Huiya Huang
- Beijing SyngenTech Co., LTD, Zhongguancun Life Science Park, Changping District, Beijing, 102206, China
| | - Yun Jiang
- Beijing SyngenTech Co., LTD, Zhongguancun Life Science Park, Changping District, Beijing, 102206, China
| | - Yanhua Ding
- Phase I Clinical Research Center, The First Hospital of Jilin University, Jilin, China.
| | - Xuegong Zhang
- MOE Key Laboratory of Bioinformatics and Bioinformatics Division, Center for Synthetic and Systems Biology, Department of Automation, Beijing National Research Center for Information Science and Technology, Tsinghua University, Beijing, 100084, China; School of Life Sciences and School of Medicine, Tsinghua University, Beijing, 100084, China.
| | - Jin Gu
- MOE Key Laboratory of Bioinformatics and Bioinformatics Division, Center for Synthetic and Systems Biology, Department of Automation, Beijing National Research Center for Information Science and Technology, Tsinghua University, Beijing, 100084, China.
| | - Zhen Xie
- MOE Key Laboratory of Bioinformatics and Bioinformatics Division, Center for Synthetic and Systems Biology, Department of Automation, Beijing National Research Center for Information Science and Technology, Tsinghua University, Beijing, 100084, China.
| |
Collapse
|
54
|
Gan X, Dong W, You W, Ding D, Yang Y, Sun D, Li W, Ding W, Liang Y, Yang F, Zhou W, Dong H, Yuan S. Spatial multimodal analysis revealed tertiary lymphoid structures as a risk stratification indicator in combined hepatocellular-cholangiocarcinoma. Cancer Lett 2024; 581:216513. [PMID: 38036041 DOI: 10.1016/j.canlet.2023.216513] [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: 08/09/2023] [Revised: 11/04/2023] [Accepted: 11/21/2023] [Indexed: 12/02/2023]
Abstract
The microenvironment created by tertiary lymphoid structures (TLSs) can support and regulate immune responses, affecting the prognosis and immune treatment of patients. Nevertheless, the actual importance of TLSs for predicting the prognosis of combined hepatocellular-cholangiocarcinoma (cHCC-CCA) patients remains unclear. Herein, using spatial transcriptomic analysis, we revealed that a gene signature of TLSs specific to cHCC-CCA was associated with high-intensity immune infiltration. Then, a novel scoring system was developed to evaluate the distribution and frequency of TLSs in intra-tumoral and extra-tumoral regions (iTLS and eTLS scores) in 146 cHCC-CCA patients. iTLS score was positively associated with promising prognosis, likely due to the decreased frequency of suppressive immune cell like Tregs, and the ratio of CD163+ macrophages to macrophages in intra-tumoral TLSs via imaging mass cytometry, while improved prognosis is not necessarily indicated by a higher eTLS score. Overall, this study highlights the potential of TLSs as a prognostic factor and an indicator of immune therapy in cHCC-CCA.
Collapse
Affiliation(s)
- Xiaojie Gan
- The Third Department of Hepatic Surgery, Eastern Hepatobiliary Surgery Hospital, Naval Medical University, 225 Changhai Road, Shanghai, 200438, China; Department of General Surgery, The First Affiliated Hospital of Soochow University, Suzhou, 215006, China
| | - Wei Dong
- The Department of Pathology, Eastern Hepatobilliary Surgery Hospital, Naval Medical University, 225 Changhai Road, Shanghai, 200438, China
| | - Wenhua You
- School of Chemistry and Chemical Engineering, Southeast University, Nanjing, 211189, China
| | - Dongyang Ding
- The Third Department of Hepatic Surgery, Eastern Hepatobiliary Surgery Hospital, Naval Medical University, 225 Changhai Road, Shanghai, 200438, China
| | - Yuan Yang
- The Third Department of Hepatic Surgery, Eastern Hepatobiliary Surgery Hospital, Naval Medical University, 225 Changhai Road, Shanghai, 200438, China
| | - Dapeng Sun
- The Third Department of Hepatic Surgery, Eastern Hepatobiliary Surgery Hospital, Naval Medical University, 225 Changhai Road, Shanghai, 200438, China
| | - Wen Li
- The Third Department of Hepatic Surgery, Eastern Hepatobiliary Surgery Hospital, Naval Medical University, 225 Changhai Road, Shanghai, 200438, China
| | - Wenbin Ding
- The Third Department of Hepatic Surgery, Eastern Hepatobiliary Surgery Hospital, Naval Medical University, 225 Changhai Road, Shanghai, 200438, China
| | - Yuan Liang
- School of Biological Science & Medical Engineering, Southeast University, Nanjing, 211189, China
| | - Fu Yang
- The Department of Medical Genetics, Naval Medical University, Shanghai, 200438, China; Shanghai Key Laboratory of Medical Bioprotection, Shanghai, 200433, China; Key Laboratory of Biological Defense, Ministry of Education, Shanghai, 200433, China.
| | - Weiping Zhou
- The Third Department of Hepatic Surgery, Eastern Hepatobiliary Surgery Hospital, Naval Medical University, 225 Changhai Road, Shanghai, 200438, China.
| | - Hui Dong
- The Department of Pathology, Eastern Hepatobilliary Surgery Hospital, Naval Medical University, 225 Changhai Road, Shanghai, 200438, China.
| | - Shengxian Yuan
- The Third Department of Hepatic Surgery, Eastern Hepatobiliary Surgery Hospital, Naval Medical University, 225 Changhai Road, Shanghai, 200438, China.
| |
Collapse
|
55
|
Du Y, Shi J, Wang J, Xun Z, Yu Z, Sun H, Bao R, Zheng J, Li Z, Ye Y. Integration of Pan-Cancer Single-Cell and Spatial Transcriptomics Reveals Stromal Cell Features and Therapeutic Targets in Tumor Microenvironment. Cancer Res 2024; 84:192-210. [PMID: 38225927 DOI: 10.1158/0008-5472.can-23-1418] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/12/2023] [Revised: 09/14/2023] [Accepted: 11/01/2023] [Indexed: 01/17/2024]
Abstract
Stromal cells are physiologically essential components of the tumor microenvironment (TME) that mediates tumor development and therapeutic resistance. Development of a logical and unified system for stromal cell type identification and characterization of corresponding functional properties could help design antitumor strategies that target stromal cells. Here, we performed a pan-cancer analysis of 214,972 nonimmune stromal cells using single-cell RNA sequencing from 258 patients across 16 cancer types and analyzed spatial transcriptomics from 16 patients across seven cancer types, including six patients receiving anti-PD-1 treatment. This analysis uncovered distinct features of 39 stromal subsets across cancer types, including various functional modules, spatial locations, and clinical and therapeutic relevance. Tumor-associated PGF+ endothelial tip cells with elevated epithelial-mesenchymal transition features were enriched in immune-depleted TME and associated with poor prognosis. Fibrogenic and vascular pericytes (PC) derived from FABP4+ progenitors were two distinct tumor-associated PC subpopulations that strongly interacted with PGF+ tips, resulting in excess extracellular matrix (ECM) abundance and dysfunctional vasculature. Importantly, ECM-related cancer-associated fibroblasts enriched at the tumor boundary acted as a barrier to exclude immune cells, interacted with malignant cells to promote tumor progression, and regulated exhausted CD8+ T cells via immune checkpoint ligand-receptors (e.g., LGALS9/TIM-3) to promote immune escape. In addition, an interactive web-based tool (http://www.scpanstroma.yelab.site/) was developed for accessing, visualizing, and analyzing stromal data. Taken together, this study provides a systematic view of the highly heterogeneous stromal populations across cancer types and suggests future avenues for designing therapies to overcome the tumor-promoting functions of stromal cells. SIGNIFICANCE Comprehensive characterization of tumor-associated nonimmune stromal cells provides a robust resource for dissecting tumor microenvironment complexity and guiding stroma-targeted therapy development across multiple human cancer types.
Collapse
Affiliation(s)
- Yanhua Du
- Department of Thoracic Surgery, Shanghai Chest Hospital, Shanghai Institute of Immunology, Shanghai Jiao Tong University School of Medicine, Shanghai, People's Republic of China
- State Key Laboratory of Systems Medicine for Cancer, Renji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, People's Republic of China
| | - Jintong Shi
- Department of Thoracic Surgery, Shanghai Chest Hospital, Shanghai Institute of Immunology, Shanghai Jiao Tong University School of Medicine, Shanghai, People's Republic of China
- State Key Laboratory of Systems Medicine for Cancer, Renji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, People's Republic of China
| | - Jiaxin Wang
- Center for Immune-Related Diseases at Shanghai Institute of Immunology, State Key Laboratory of Medical Genomics, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, People's Republic of China
| | - Zhenzhen Xun
- Department of Thoracic Surgery, Shanghai Chest Hospital, Shanghai Institute of Immunology, Shanghai Jiao Tong University School of Medicine, Shanghai, People's Republic of China
- State Key Laboratory of Systems Medicine for Cancer, Renji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, People's Republic of China
| | - Zhuo Yu
- Hongqiao International Institute of Medicine, Shanghai Tongren Hospital, Key Laboratory of Cell Differentiation and Apoptosis of Chinese Ministry of Education, Faculty of Basic Medicine, Shanghai Jiao Tong University School of Medicine, Shanghai, People's Republic of China
| | - Hongxiang Sun
- Department of Thoracic Surgery, Shanghai Chest Hospital, Shanghai Institute of Immunology, Shanghai Jiao Tong University School of Medicine, Shanghai, People's Republic of China
| | - Rujuan Bao
- Department of Thoracic Surgery, Shanghai Chest Hospital, Shanghai Institute of Immunology, Shanghai Jiao Tong University School of Medicine, Shanghai, People's Republic of China
- State Key Laboratory of Systems Medicine for Cancer, Renji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, People's Republic of China
| | - Junke Zheng
- Hongqiao International Institute of Medicine, Shanghai Tongren Hospital, Key Laboratory of Cell Differentiation and Apoptosis of Chinese Ministry of Education, Faculty of Basic Medicine, Shanghai Jiao Tong University School of Medicine, Shanghai, People's Republic of China
| | - Zhigang Li
- Department of Thoracic Surgery, Shanghai Chest Hospital, Shanghai Institute of Immunology, Shanghai Jiao Tong University School of Medicine, Shanghai, People's Republic of China
| | - Youqiong Ye
- Department of Thoracic Surgery, Shanghai Chest Hospital, Shanghai Institute of Immunology, Shanghai Jiao Tong University School of Medicine, Shanghai, People's Republic of China
- State Key Laboratory of Systems Medicine for Cancer, Renji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, People's Republic of China
- Center for Immune-Related Diseases at Shanghai Institute of Immunology, State Key Laboratory of Medical Genomics, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, People's Republic of China
| |
Collapse
|
56
|
Cao J, Zheng Z, Sun D, Chen X, Cheng R, Lv T, An Y, Zheng J, Song J, Wu L, Yang C. Decoder-seq enhances mRNA capture efficiency in spatial RNA sequencing. Nat Biotechnol 2024:10.1038/s41587-023-02086-y. [PMID: 38228777 DOI: 10.1038/s41587-023-02086-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2023] [Accepted: 12/04/2023] [Indexed: 01/18/2024]
Abstract
Spatial transcriptomics technologies with high resolution often lack high sensitivity in mRNA detection. Here we report a dendrimeric DNA coordinate barcoding design for spatial RNA sequencing (Decoder-seq), which offers both high sensitivity and high resolution. Decoder-seq combines dendrimeric nanosubstrates with microfluidic coordinate barcoding to generate spatial arrays with a DNA density approximately ten times higher than previously reported methods while maintaining flexibility in resolution. We show that the high RNA capture efficiency of Decoder-seq improved the detection of lowly expressed olfactory receptor (Olfr) genes in mouse olfactory bulbs and contributed to the discovery of a unique layer enrichment pattern for two Olfr genes. The near-cellular resolution provided by Decoder-seq has enabled the construction of a spatial single-cell atlas of the mouse hippocampus, revealing dendrite-enriched mRNAs in neurons. When applying Decoder-seq to human renal cell carcinomas, we dissected the heterogeneous tumor microenvironment across different cancer subtypes and identified spatial gradient-expressed genes related to epithelial-mesenchymal transition with the potential to predict tumor prognosis and progression.
Collapse
Affiliation(s)
- Jiao Cao
- Institute of Molecular Medicine, Shanghai Key Laboratory for Nucleic Acid Chemistry and Nanomedicine, Department of Urology, Renji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Zhong Zheng
- Institute of Molecular Medicine, Shanghai Key Laboratory for Nucleic Acid Chemistry and Nanomedicine, Department of Urology, Renji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Di Sun
- Institute of Molecular Medicine, Shanghai Key Laboratory for Nucleic Acid Chemistry and Nanomedicine, Department of Urology, Renji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Xin Chen
- Institute of Molecular Medicine, Shanghai Key Laboratory for Nucleic Acid Chemistry and Nanomedicine, Department of Urology, Renji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Rui Cheng
- Institute of Molecular Medicine, Shanghai Key Laboratory for Nucleic Acid Chemistry and Nanomedicine, Department of Urology, Renji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Tianpeng Lv
- Institute of Molecular Medicine, Shanghai Key Laboratory for Nucleic Acid Chemistry and Nanomedicine, Department of Urology, Renji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Yu An
- Institute of Molecular Medicine, Shanghai Key Laboratory for Nucleic Acid Chemistry and Nanomedicine, Department of Urology, Renji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Junhua Zheng
- Institute of Molecular Medicine, Shanghai Key Laboratory for Nucleic Acid Chemistry and Nanomedicine, Department of Urology, Renji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
| | - Jia Song
- Institute of Molecular Medicine, Shanghai Key Laboratory for Nucleic Acid Chemistry and Nanomedicine, Department of Urology, Renji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
| | - Lingling Wu
- Institute of Molecular Medicine, Shanghai Key Laboratory for Nucleic Acid Chemistry and Nanomedicine, Department of Urology, Renji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
| | - Chaoyong Yang
- Institute of Molecular Medicine, Shanghai Key Laboratory for Nucleic Acid Chemistry and Nanomedicine, Department of Urology, Renji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
- The MOE Key Laboratory of Spectrochemical Analysis & Instrumentation, State Key Laboratory of Physical Chemical of Solid Surfaces, Department of Chemical Biology, College of Chemistry and Chemical Engineering, Xiamen University, Xiamen, China.
| |
Collapse
|
57
|
Hao M, Luo E, Chen Y, Wu Y, Li C, Chen S, Gao H, Bian H, Gu J, Wei L, Zhang X. STEM enables mapping of single-cell and spatial transcriptomics data with transfer learning. Commun Biol 2024; 7:56. [PMID: 38184694 PMCID: PMC10771471 DOI: 10.1038/s42003-023-05640-1] [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] [Accepted: 11/27/2023] [Indexed: 01/08/2024] Open
Abstract
Profiling spatial variations of cellular composition and transcriptomic characteristics is important for understanding the physiology and pathology of tissues. Spatial transcriptomics (ST) data depict spatial gene expression but the currently dominating high-throughput technology is yet not at single-cell resolution. Single-cell RNA-sequencing (SC) data provide high-throughput transcriptomic information at the single-cell level but lack spatial information. Integrating these two types of data would be ideal for revealing transcriptomic landscapes at single-cell resolution. We develop the method STEM (SpaTially aware EMbedding) for this purpose. It uses deep transfer learning to encode both ST and SC data into a unified spatially aware embedding space, and then uses the embeddings to infer SC-ST mapping and predict pseudo-spatial adjacency between cells in SC data. Semi-simulation and real data experiments verify that the embeddings preserved spatial information and eliminated technical biases between SC and ST data. We apply STEM to human squamous cell carcinoma and hepatic lobule datasets to uncover the localization of rare cell types and reveal cell-type-specific gene expression variation along a spatial axis. STEM is powerful for mapping SC and ST data to build single-cell level spatial transcriptomic landscapes, and can provide mechanistic insights into the spatial heterogeneity and microenvironments of tissues.
Collapse
Affiliation(s)
- Minsheng Hao
- MOE Key Laboratory of Bioinformatics and Bioinformatics Division, BNRIST, Department of Automation, Tsinghua University, Beijing, 100084, China
| | - Erpai Luo
- MOE Key Laboratory of Bioinformatics and Bioinformatics Division, BNRIST, Department of Automation, Tsinghua University, Beijing, 100084, China
| | - Yixin Chen
- MOE Key Laboratory of Bioinformatics and Bioinformatics Division, BNRIST, Department of Automation, Tsinghua University, Beijing, 100084, China
| | - Yanhong Wu
- MOE Key Laboratory of Bioinformatics and Bioinformatics Division, BNRIST, Department of Automation, Tsinghua University, Beijing, 100084, China
| | - Chen Li
- MOE Key Laboratory of Bioinformatics and Bioinformatics Division, BNRIST, Department of Automation, Tsinghua University, Beijing, 100084, China
| | - Sijie Chen
- MOE Key Laboratory of Bioinformatics and Bioinformatics Division, BNRIST, Department of Automation, Tsinghua University, Beijing, 100084, China
| | - Haoxiang Gao
- MOE Key Laboratory of Bioinformatics and Bioinformatics Division, BNRIST, Department of Automation, Tsinghua University, Beijing, 100084, China
| | - Haiyang Bian
- MOE Key Laboratory of Bioinformatics and Bioinformatics Division, BNRIST, Department of Automation, Tsinghua University, Beijing, 100084, China
| | - Jin Gu
- MOE Key Laboratory of Bioinformatics and Bioinformatics Division, BNRIST, Department of Automation, Tsinghua University, Beijing, 100084, China
| | - Lei Wei
- MOE Key Laboratory of Bioinformatics and Bioinformatics Division, BNRIST, Department of Automation, Tsinghua University, Beijing, 100084, China.
| | - Xuegong Zhang
- MOE Key Laboratory of Bioinformatics and Bioinformatics Division, BNRIST, Department of Automation, Tsinghua University, Beijing, 100084, China.
- School of Life Sciences and School of Medicine, Center for Synthetic and Systems Biology, Tsinghua University, Beijing, 100084, China.
| |
Collapse
|
58
|
Li Z, Pai R, Gupta S, Currenti J, Guo W, Di Bartolomeo A, Feng H, Zhang Z, Li Z, Liu L, Singh A, Bai Y, Yang B, Mishra A, Yang K, Qiao L, Wallace M, Yin Y, Xia Q, Chan JKY, George J, Chow PKH, Ginhoux F, Sharma A. Presence of onco-fetal neighborhoods in hepatocellular carcinoma is associated with relapse and response to immunotherapy. NATURE CANCER 2024; 5:167-186. [PMID: 38168935 DOI: 10.1038/s43018-023-00672-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/17/2023] [Accepted: 10/16/2023] [Indexed: 01/05/2024]
Abstract
Onco-fetal reprogramming of the tumor ecosystem induces fetal developmental signatures in the tumor microenvironment, leading to immunosuppressive features. Here, we employed single-cell RNA sequencing, spatial transcriptomics and bulk RNA sequencing to delineate specific cell subsets involved in hepatocellular carcinoma (HCC) relapse and response to immunotherapy. We identified POSTN+ extracellular matrix cancer-associated fibroblasts (EM CAFs) as a prominent onco-fetal interacting hub, promoting tumor progression. Cell-cell communication and spatial transcriptomics analysis revealed crosstalk and co-localization of onco-fetal cells, including POSTN+ CAFs, FOLR2+ macrophages and PLVAP+ endothelial cells. Further analyses suggest an association between onco-fetal reprogramming and epithelial-mesenchymal transition (EMT), tumor cell proliferation and recruitment of Treg cells, ultimately influencing early relapse and response to immunotherapy. In summary, our study identifies POSTN+ CAFs as part of the HCC onco-fetal niche and highlights its potential influence in EMT, relapse and immunotherapy response, paving the way for the use of onco-fetal signatures for therapeutic stratification.
Collapse
Affiliation(s)
- Ziyi Li
- Shanghai Institute of Immunology, Department of Immunology and Microbiology, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Rhea Pai
- Harry Perkins Institute of Medical Research, QEII Medical Centre and Centre for Medical Research, Perth, Western Australia, Australia
- Curtin Medical School, Curtin University, Perth, Western Australia, Australia
| | - Saurabh Gupta
- Harry Perkins Institute of Medical Research, QEII Medical Centre and Centre for Medical Research, Perth, Western Australia, Australia
- Curtin Medical School, Curtin University, Perth, Western Australia, Australia
| | - Jennifer Currenti
- Harry Perkins Institute of Medical Research, QEII Medical Centre and Centre for Medical Research, Perth, Western Australia, Australia
- Curtin Medical School, Curtin University, Perth, Western Australia, Australia
| | - Wei Guo
- Shanghai Institute of Immunology, Department of Immunology and Microbiology, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Anna Di Bartolomeo
- Storr Liver Centre, The Westmead Institute for Medical Research and Westmead Hospital, University of Sydney, Sydney, New South Wales, Australia
| | - Hao Feng
- Department of Liver Surgery, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China
- Shanghai Institute of Transplantation, Shanghai, China
| | - Zijie Zhang
- Department of Liver Surgery, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China
| | - Zhizhen Li
- Department of Biliary Tract Surgery I, Eastern Hepatobiliary Surgery Hospital, Shanghai, China
| | - Longqi Liu
- BGI-Shenzhen, Beishan Industrial Zone, Shenzhen, P. R. China
| | - Abhishek Singh
- Harry Perkins Institute of Medical Research, QEII Medical Centre and Centre for Medical Research, Perth, Western Australia, Australia
| | - Yinqi Bai
- BGI-Shenzhen, Beishan Industrial Zone, Shenzhen, P. R. China
| | | | - Archita Mishra
- Singapore Immunology Network (SIgN), Agency for Science, Technology and Research (A∗STAR), Singapore, Singapore
- Telethon Kids Institute, University of Western Australia, Perth Children's Hospital, Nedlands, Western Australia, Australia
| | - Katharine Yang
- Singapore Immunology Network (SIgN), Agency for Science, Technology and Research (A∗STAR), Singapore, Singapore
| | - Liang Qiao
- Storr Liver Centre, The Westmead Institute for Medical Research and Westmead Hospital, University of Sydney, Sydney, New South Wales, Australia
| | - Michael Wallace
- Department of Hepatology and Western Australian Liver Transplant Service, Sir Charles Gairdner Hospital, Nedlands, Western Australia, Australia
- Medical School, University of Western Australia, Nedlands, Western Australia, Australia
| | - Yujia Yin
- Department of Obstetrics and Gynecology, Xinhua Hospital Affiliated to Shanghai Jiaotong University Medicine School, Shanghai, China
| | - Qiang Xia
- Department of Liver Surgery, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China
- Shanghai Institute of Transplantation, Shanghai, China
| | - Jerry Kok Yen Chan
- Department of Reproductive Medicine, KK Women's and Children's Hospital, Singapore, Singapore
- Academic Clinical Program in Obstetrics and Gynaecology, Duke-NUS Medical School, Singapore, Singapore
- Department of Obstetrics and Gynaecology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
| | - Jacob George
- Storr Liver Centre, The Westmead Institute for Medical Research and Westmead Hospital, University of Sydney, Sydney, New South Wales, Australia
| | - Pierce Kah-Hoe Chow
- Department of Hepatopancreatobiliary and Transplant Surgery, Singapore General Hospital and National Cancer Centre Singapore, Singapore, Singapore.
- Surgery Academic Clinical Programme, Duke-NUS Medical School, Singapore, Singapore.
| | - Florent Ginhoux
- Shanghai Institute of Immunology, Department of Immunology and Microbiology, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
- Singapore Immunology Network (SIgN), Agency for Science, Technology and Research (A∗STAR), Singapore, Singapore.
- Translational Immunology Institute, SingHealth Duke-NUS Academic Medical Centre, Singapore, Singapore.
- Gustave Roussy Cancer Campus, Villejuif, France.
| | - Ankur Sharma
- Harry Perkins Institute of Medical Research, QEII Medical Centre and Centre for Medical Research, Perth, Western Australia, Australia.
- Curtin Medical School, Curtin University, Perth, Western Australia, Australia.
- Institute of Molecular and Cell Biology, A∗STAR, Singapore, Singapore.
- KK Research Centre, KK Women's and Children's Hospital, Singapore, Singapore.
| |
Collapse
|
59
|
Kumar G, Pandurengan RK, Parra ER, Kannan K, Haymaker C. Spatial modelling of the tumor microenvironment from multiplex immunofluorescence images: methods and applications. Front Immunol 2023; 14:1288802. [PMID: 38179056 PMCID: PMC10765501 DOI: 10.3389/fimmu.2023.1288802] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/04/2023] [Accepted: 12/07/2023] [Indexed: 01/06/2024] Open
Abstract
Spatial modelling methods have gained prominence with developments in high throughput imaging platforms. Multiplex immunofluorescence (mIF) provides the scope to examine interactions between tumor and immune compartment at single cell resolution using a panel of antibodies that can be chosen based on the cancer type or the clinical interest of the study. The markers can be used to identify the phenotypes and to examine cellular interactions at global and local scales. Several translational studies rely on key understanding of the tumor microenvironment (TME) to identify drivers of immune response in immunotherapy based clinical trials. To improve the success of ongoing trials, a number of retrospective approaches can be adopted to understand differences in response, recurrence and progression by examining the patient's TME from tissue samples obtained at baseline and at various time points along the treatment. The multiplex immunofluorescence (mIF) technique provides insight on patient specific cell populations and their relative spatial distribution as qualitative measures of a favorable treatment outcome. Spatial analysis of these images provides an understanding of the intratumoral heterogeneity and clustering among cell populations in the TME. A number of mathematical models, which establish clustering as a measure of deviation from complete spatial randomness, can be applied to the mIF images represented as spatial point patterns. These mathematical models, developed for landscape ecology and geographic information studies, can be applied to the TME after careful consideration of the tumor type (cold vs. hot) and the tumor immune landscape. The spatial modelling of mIF images can show observable engagement of T cells expressing immune checkpoint molecules and this can then be correlated with single-cell RNA sequencing data.
Collapse
Affiliation(s)
| | | | | | - Kasthuri Kannan
- Department of Translational Molecular Pathology, MD Anderson Cancer Center, Houston, TX, United States
| | - Cara Haymaker
- Department of Translational Molecular Pathology, MD Anderson Cancer Center, Houston, TX, United States
| |
Collapse
|
60
|
Xu H, Wang S, Fang M, Luo S, Chen C, Wan S, Wang R, Tang M, Xue T, Li B, Lin J, Qu K. SPACEL: deep learning-based characterization of spatial transcriptome architectures. Nat Commun 2023; 14:7603. [PMID: 37990022 PMCID: PMC10663563 DOI: 10.1038/s41467-023-43220-3] [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: 12/24/2022] [Accepted: 11/03/2023] [Indexed: 11/23/2023] Open
Abstract
Spatial transcriptomics (ST) technologies detect mRNA expression in single cells/spots while preserving their two-dimensional (2D) spatial coordinates, allowing researchers to study the spatial distribution of the transcriptome in tissues; however, joint analysis of multiple ST slices and aligning them to construct a three-dimensional (3D) stack of the tissue still remain a challenge. Here, we introduce spatial architecture characterization by deep learning (SPACEL) for ST data analysis. SPACEL comprises three modules: Spoint embeds a multiple-layer perceptron with a probabilistic model to deconvolute cell type composition for each spot in a single ST slice; Splane employs a graph convolutional network approach and an adversarial learning algorithm to identify spatial domains that are transcriptomically and spatially coherent across multiple ST slices; and Scube automatically transforms the spatial coordinate systems of consecutive slices and stacks them together to construct a 3D architecture of the tissue. Comparisons against 19 state-of-the-art methods using both simulated and real ST datasets from various tissues and ST technologies demonstrate that SPACEL outperforms the others for cell type deconvolution, for spatial domain identification, and for 3D alignment, thus showcasing SPACEL as a valuable integrated toolkit for ST data processing and analysis.
Collapse
Affiliation(s)
- Hao Xu
- Department of Oncology, The First Affiliated Hospital of USTC, School of Basic Medical Sciences, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, 230027, China
| | - Shuyan Wang
- Institute of Artificial Intelligence, Hefei Comprehensive National Science Center, Hefei, 230088, China
- School of Data Science, University of Science and Technology of China, Hefei, 230027, China
| | - Minghao Fang
- Institute of Artificial Intelligence, Hefei Comprehensive National Science Center, Hefei, 230088, China
| | - Songwen Luo
- Department of Oncology, The First Affiliated Hospital of USTC, School of Basic Medical Sciences, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, 230027, China
| | - Chunpeng Chen
- Department of Oncology, The First Affiliated Hospital of USTC, School of Basic Medical Sciences, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, 230027, China
| | - Siyuan Wan
- Institute of Artificial Intelligence, Hefei Comprehensive National Science Center, Hefei, 230088, China
- School of Data Science, University of Science and Technology of China, Hefei, 230027, China
| | - Rirui Wang
- Department of Oncology, The First Affiliated Hospital of USTC, School of Basic Medical Sciences, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, 230027, China
| | - Meifang Tang
- Department of Oncology, The First Affiliated Hospital of USTC, School of Basic Medical Sciences, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, 230027, China
| | - Tian Xue
- Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, 230027, China
| | - Bin Li
- National Institute of Biological Sciences, Beijing, 102206, China.
| | - Jun Lin
- Department of Oncology, The First Affiliated Hospital of USTC, School of Basic Medical Sciences, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, 230027, China.
- Institute of Artificial Intelligence, Hefei Comprehensive National Science Center, Hefei, 230088, China.
| | - Kun Qu
- Department of Oncology, The First Affiliated Hospital of USTC, School of Basic Medical Sciences, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, 230027, China.
- Institute of Artificial Intelligence, Hefei Comprehensive National Science Center, Hefei, 230088, China.
- School of Data Science, University of Science and Technology of China, Hefei, 230027, China.
| |
Collapse
|
61
|
Xiao X, Juan C, Drennon T, Uytingco CR, Vishlaghi N, Sokolowskei D, Xu L, Levi B, Sammarco MC, Tower RJ. Spatial transcriptomic interrogation of the murine bone marrow signaling landscape. Bone Res 2023; 11:59. [PMID: 37926705 PMCID: PMC10625929 DOI: 10.1038/s41413-023-00298-1] [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: 05/22/2023] [Revised: 09/19/2023] [Accepted: 09/28/2023] [Indexed: 11/07/2023] Open
Abstract
Self-renewal and differentiation of skeletal stem and progenitor cells (SSPCs) are tightly regulated processes, with SSPC dysregulation leading to progressive bone disease. While the application of single-cell RNA sequencing (scRNAseq) to the bone field has led to major advancements in our understanding of SSPC heterogeneity, stem cells are tightly regulated by their neighboring cells which comprise the bone marrow niche. However, unbiased interrogation of these cells at the transcriptional level within their native niche environment has been challenging. Here, we combined spatial transcriptomics and scRNAseq using a predictive modeling pipeline derived from multiple deconvolution packages in adult mouse femurs to provide an endogenous, in vivo context of SSPCs within the niche. This combined approach localized SSPC subtypes to specific regions of the bone and identified cellular components and signaling networks utilized within the niche. Furthermore, the use of spatial transcriptomics allowed us to identify spatially restricted activation of metabolic and major morphogenetic signaling gradients derived from the vasculature and bone surfaces that establish microdomains within the marrow cavity. Overall, we demonstrate, for the first time, the feasibility of applying spatial transcriptomics to fully mineralized tissue and present a combined spatial and single-cell transcriptomic approach to define the cellular components of the stem cell niche, identify cell‒cell communication, and ultimately gain a comprehensive understanding of local and global SSPC regulatory networks within calcified tissue.
Collapse
Affiliation(s)
- Xue Xiao
- Quantitative Biomedical Research Center, Peter O'Donnell Jr. School of Public Health, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - Conan Juan
- Department of Surgery, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - Tingsheng Drennon
- Department of Cell Biology & Applications, 10x Genomics, Pleasanton, CA, USA
| | - Cedric R Uytingco
- Department of Cell Biology & Applications, 10x Genomics, Pleasanton, CA, USA
| | - Neda Vishlaghi
- Department of Surgery, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - Dimitri Sokolowskei
- Department of Surgery, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - Lin Xu
- Quantitative Biomedical Research Center, Peter O'Donnell Jr. School of Public Health, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - Benjamin Levi
- Department of Surgery, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - Mimi C Sammarco
- Department of Surgery, Tulane School of Medicine, New Orleans, LA, USA
| | - Robert J Tower
- Department of Surgery, University of Texas Southwestern Medical Center, Dallas, TX, USA.
| |
Collapse
|
62
|
Xie Z, Huang J, Li Y, Zhu Q, Huang X, Chen J, Wei C, Luo S, Yang S, Gao J. Single-cell RNA sequencing revealed potential targets for immunotherapy studies in hepatocellular carcinoma. Sci Rep 2023; 13:18799. [PMID: 37914817 PMCID: PMC10620237 DOI: 10.1038/s41598-023-46132-w] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/28/2023] [Accepted: 10/27/2023] [Indexed: 11/03/2023] Open
Abstract
Hepatocellular carcinoma (HCC) is a solid tumor prone to chemotherapy resistance, and combined immunotherapy is expected to bring a breakthrough in HCC treatment. However, the tumor and tumor microenvironment (TME) of HCC is highly complex and heterogeneous, and there are still many unknowns regarding tumor cell stemness and metabolic reprogramming in HCC. In this study, we combined single-cell RNA sequencing data from 27 HCC tumor tissues and 4 adjacent non-tumor tissues, and bulk RNA sequencing data from 374 of the Cancer Genome Atlas (TCGA)-liver hepatocellular carcinoma (LIHC) samples to construct a global single-cell landscape atlas of HCC. We analyzed the enrichment of signaling pathways of different cells in HCC, and identified the developmental trajectories of cell subpopulations in the TME using pseudotime analysis. Subsequently, we performed transcription factors regulating different subpopulations and gene regulatory network analysis, respectively. In addition, we estimated the stemness index of tumor cells and analyzed the intercellular communication between tumors and key TME cell clusters. We identified novel HCC cell clusters that specifically express HP (HCC_HP), which may lead to higher tumor differentiation and tumor heterogeneity. In addition, we found that the HP gene expression-positive neutrophil cluster (Neu_AIF1) had extensive and strong intercellular communication with HCC cells, tumor endothelial cells (TEC) and cancer-associated fibroblasts (CAF), suggesting that clearance of this new cluster may inhibit HCC progression. Furthermore, ErbB signaling pathway and GnRH signaling pathway were found to be upregulated in almost all HCC tumor-associated stromal cells and immune cells, except NKT cells. Moreover, the high intercellular communication between HCC and HSPA1-positive TME cells suggests that the immune microenvironment may be reprogrammed. In summary, our present study depicted the single-cell landscape heterogeneity of human HCC, identified new cell clusters in tumor cells and neutrophils with potential implications for immunotherapy research, discovered complex intercellular communication between tumor cells and TME cells.
Collapse
Affiliation(s)
- Zhouhua Xie
- Laboratory of Infectious Disease, HIV/AIDS Clinical Treatment Center of Guangxi (Nanning) and The Fourth People's Hospital of Nanning, Nanning, 530023, Guangxi Zhuang Autonomous Region, China
- Department of Tuberculosis, HIV/AIDS Clinical Treatment Center of Guangxi (Nanning) and The Fourth People's Hospital of Nanning, Nanning, 530023, China
| | - Jinping Huang
- Laboratory of Infectious Disease, HIV/AIDS Clinical Treatment Center of Guangxi (Nanning) and The Fourth People's Hospital of Nanning, Nanning, 530023, Guangxi Zhuang Autonomous Region, China
- Department of Infectious Diseases, HIV/AIDS Clinical Treatment Center of Guangxi (Nanning) and The Fourth People's Hospital of Nanning, Nanning, 530023, China
| | - Yanjun Li
- Laboratory of Infectious Disease, HIV/AIDS Clinical Treatment Center of Guangxi (Nanning) and The Fourth People's Hospital of Nanning, Nanning, 530023, Guangxi Zhuang Autonomous Region, China
- Department of Infectious Diseases, HIV/AIDS Clinical Treatment Center of Guangxi (Nanning) and The Fourth People's Hospital of Nanning, Nanning, 530023, China
| | - Qingdong Zhu
- Department of Tuberculosis, HIV/AIDS Clinical Treatment Center of Guangxi (Nanning) and The Fourth People's Hospital of Nanning, Nanning, 530023, China
| | - Xianzhen Huang
- Department of Tuberculosis, HIV/AIDS Clinical Treatment Center of Guangxi (Nanning) and The Fourth People's Hospital of Nanning, Nanning, 530023, China
| | - Jieling Chen
- Laboratory of Infectious Disease, HIV/AIDS Clinical Treatment Center of Guangxi (Nanning) and The Fourth People's Hospital of Nanning, Nanning, 530023, Guangxi Zhuang Autonomous Region, China
| | - Cailing Wei
- Laboratory of Infectious Disease, HIV/AIDS Clinical Treatment Center of Guangxi (Nanning) and The Fourth People's Hospital of Nanning, Nanning, 530023, Guangxi Zhuang Autonomous Region, China
| | - Shunda Luo
- Department of Clinical Laboratory, HIV/AIDS Clinical Treatment Center of Guangxi (Nanning) and The Fourth People's Hospital of Nanning, Nanning, 530023, China
| | - Shixiong Yang
- Laboratory of Infectious Disease, HIV/AIDS Clinical Treatment Center of Guangxi (Nanning) and The Fourth People's Hospital of Nanning, Nanning, 530023, Guangxi Zhuang Autonomous Region, China.
- Administrative Office, HIV/AIDS Clinical Treatment Center of Guangxi (Nanning) and The Fourth People's Hospital of Nanning, Nanning, 530023, China.
| | - Jiamin Gao
- Laboratory of Infectious Disease, HIV/AIDS Clinical Treatment Center of Guangxi (Nanning) and The Fourth People's Hospital of Nanning, Nanning, 530023, Guangxi Zhuang Autonomous Region, China.
- Department of Infectious Diseases, HIV/AIDS Clinical Treatment Center of Guangxi (Nanning) and The Fourth People's Hospital of Nanning, Nanning, 530023, China.
| |
Collapse
|
63
|
Ma C, Yang C, Peng A, Sun T, Ji X, Mi J, Wei L, Shen S, Feng Q. Pan-cancer spatially resolved single-cell analysis reveals the crosstalk between cancer-associated fibroblasts and tumor microenvironment. Mol Cancer 2023; 22:170. [PMID: 37833788 PMCID: PMC10571470 DOI: 10.1186/s12943-023-01876-x] [Citation(s) in RCA: 15] [Impact Index Per Article: 15.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/11/2023] [Accepted: 10/02/2023] [Indexed: 10/15/2023] Open
Abstract
Cancer-associated fibroblasts (CAFs) are a heterogeneous cell population that plays a crucial role in remodeling the tumor microenvironment (TME). Here, through the integrated analysis of spatial and single-cell transcriptomics data across six common cancer types, we identified four distinct functional subgroups of CAFs and described their spatial distribution characteristics. Additionally, the analysis of single-cell RNA sequencing (scRNA-seq) data from three additional common cancer types and two newly generated scRNA-seq datasets of rare cancer types, namely epithelial-myoepithelial carcinoma (EMC) and mucoepidermoid carcinoma (MEC), expanded our understanding of CAF heterogeneity. Cell-cell interaction analysis conducted within the spatial context highlighted the pivotal roles of matrix CAFs (mCAFs) in tumor angiogenesis and inflammatory CAFs (iCAFs) in shaping the immunosuppressive microenvironment. In patients with breast cancer (BRCA) undergoing anti-PD-1 immunotherapy, iCAFs demonstrated heightened capacity in facilitating cancer cell proliferation, promoting epithelial-mesenchymal transition (EMT), and contributing to the establishment of an immunosuppressive microenvironment. Furthermore, a scoring system based on iCAFs showed a significant correlation with immune therapy response in melanoma patients. Lastly, we provided a web interface ( https://chenxisd.shinyapps.io/pancaf/ ) for the research community to investigate CAFs in the context of pan-cancer.
Collapse
Affiliation(s)
- Chenxi Ma
- Department of Human Microbiome and Periodontology and Implantology and Orthodontics, School and Hospital of Stomatology, Cheeloo College of Medicine, Shandong University and Shandong Key Laboratory of Oral Tissue Regeneration and Shandong Engineering Laboratory for Dental Materials and Oral Tissue Regeneration and Shandong Provincial Clinical Research Center for Oral Diseases, Jinan, 250012, China
| | - Chengzhe Yang
- Department of Oral and Maxillofacial Surgery, Qilu Hospital of Shandong University, Jinan, Shandong, China
- Institute of Stomatology, Shandong University, Jinan, Shandong, China
| | - Ai Peng
- Department of Human Microbiome and Periodontology and Implantology and Orthodontics, School and Hospital of Stomatology, Cheeloo College of Medicine, Shandong University and Shandong Key Laboratory of Oral Tissue Regeneration and Shandong Engineering Laboratory for Dental Materials and Oral Tissue Regeneration and Shandong Provincial Clinical Research Center for Oral Diseases, Jinan, 250012, China
| | - Tianyong Sun
- Department of Human Microbiome and Periodontology and Implantology and Orthodontics, School and Hospital of Stomatology, Cheeloo College of Medicine, Shandong University and Shandong Key Laboratory of Oral Tissue Regeneration and Shandong Engineering Laboratory for Dental Materials and Oral Tissue Regeneration and Shandong Provincial Clinical Research Center for Oral Diseases, Jinan, 250012, China
| | - Xiaoli Ji
- Department of Stomatology, Central Hospital Affiliated to Shandong First Medical University, No.105 Jiefang Road, Jinan, Shandong, China
| | - Jun Mi
- Department of Human Microbiome and Periodontology and Implantology and Orthodontics, School and Hospital of Stomatology, Cheeloo College of Medicine, Shandong University and Shandong Key Laboratory of Oral Tissue Regeneration and Shandong Engineering Laboratory for Dental Materials and Oral Tissue Regeneration and Shandong Provincial Clinical Research Center for Oral Diseases, Jinan, 250012, China
| | - Li Wei
- Department of Human Microbiome and Periodontology and Implantology and Orthodontics, School and Hospital of Stomatology, Cheeloo College of Medicine, Shandong University and Shandong Key Laboratory of Oral Tissue Regeneration and Shandong Engineering Laboratory for Dental Materials and Oral Tissue Regeneration and Shandong Provincial Clinical Research Center for Oral Diseases, Jinan, 250012, China
| | - Song Shen
- Department of Human Microbiome and Periodontology and Implantology and Orthodontics, School and Hospital of Stomatology, Cheeloo College of Medicine, Shandong University and Shandong Key Laboratory of Oral Tissue Regeneration and Shandong Engineering Laboratory for Dental Materials and Oral Tissue Regeneration and Shandong Provincial Clinical Research Center for Oral Diseases, Jinan, 250012, China
| | - Qiang Feng
- Department of Human Microbiome and Periodontology and Implantology and Orthodontics, School and Hospital of Stomatology, Cheeloo College of Medicine, Shandong University and Shandong Key Laboratory of Oral Tissue Regeneration and Shandong Engineering Laboratory for Dental Materials and Oral Tissue Regeneration and Shandong Provincial Clinical Research Center for Oral Diseases, Jinan, 250012, China.
- State Key Laboratory of Microbial Technology, Shandong University, Qingdao, 266237, China.
| |
Collapse
|
64
|
Yuan Z, Yao J. Harnessing computational spatial omics to explore the spatial biology intricacies. Semin Cancer Biol 2023; 95:25-41. [PMID: 37400044 DOI: 10.1016/j.semcancer.2023.06.006] [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: 12/02/2022] [Revised: 05/09/2023] [Accepted: 06/19/2023] [Indexed: 07/05/2023]
Abstract
Spatially resolved transcriptomics (SRT) has unlocked new dimensions in our understanding of intricate tissue architectures. However, this rapidly expanding field produces a wealth of diverse and voluminous data, necessitating the evolution of sophisticated computational strategies to unravel inherent patterns. Two distinct methodologies, gene spatial pattern recognition (GSPR) and tissue spatial pattern recognition (TSPR), have emerged as vital tools in this process. GSPR methodologies are designed to identify and classify genes exhibiting noteworthy spatial patterns, while TSPR strategies aim to understand intercellular interactions and recognize tissue domains with molecular and spatial coherence. In this review, we provide a comprehensive exploration of SRT, highlighting crucial data modalities and resources that are instrumental for the development of methods and biological insights. We address the complexities and challenges posed by the use of heterogeneous data in developing GSPR and TSPR methodologies and propose an optimal workflow for both. We delve into the latest advancements in GSPR and TSPR, examining their interrelationships. Lastly, we peer into the future, envisaging the potential directions and perspectives in this dynamic field.
Collapse
Affiliation(s)
- Zhiyuan Yuan
- Center for Medical Research and Innovation, Shanghai Pudong Hospital, Fudan University Pudong Medical Center, Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China.
| | | |
Collapse
|
65
|
Wang Q, Zhi Y, Zi M, Mo Y, Wang Y, Liao Q, Zhang S, Gong Z, Wang F, Zeng Z, Guo C, Xiong W. Spatially Resolved Transcriptomics Technology Facilitates Cancer Research. ADVANCED SCIENCE (WEINHEIM, BADEN-WURTTEMBERG, GERMANY) 2023; 10:e2302558. [PMID: 37632718 PMCID: PMC10602551 DOI: 10.1002/advs.202302558] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/21/2023] [Revised: 07/16/2023] [Indexed: 08/28/2023]
Abstract
Single cell RNA sequencing (scRNA-seq) provides a great convenience for studying tumor occurrence and development for its ability to study gene expression at the individual cell level. However, patient-derived tumor tissues are composed of multiple types of cells including tumor cells and adjacent non-malignant cells such as stromal cells and immune cells. The spatial locations of various cells in situ tissues plays a pivotal role in the occurrence and development of tumors, which cannot be elucidated by scRNA-seq alone. Spatially resolved transcriptomics (SRT) technology emerges timely to explore the unrecognized relationship between the spatial background of a particular cell and its functions, and is increasingly used in cancer research. This review provides a systematic overview of the SRT technologies that are developed, in particular the more widely used cutting-edge SRT technologies based on next-generation sequencing (NGS). In addition, the main achievements by SRT technologies in precisely unveiling the underappreciated spatial locations on gene expression and cell function with unprecedented high-resolution in cancer research are emphasized, with the aim of developing more effective clinical therapeutics oriented to a deeper understanding of the interaction between tumor cells and surrounding non-malignant cells.
Collapse
Affiliation(s)
- Qian Wang
- NHC Key Laboratory of Carcinogenesis and Hunan Key Laboratory of Cancer MetabolismHunan Cancer Hospital and the Affiliated Cancer Hospital of Xiangya School of MedicineCentral South UniversityChangshaHunan410008P. R. China
- Key Laboratory of Carcinogenesis and Cancer Invasion of the Chinese Ministry of EducationCancer Research InstituteCentral South UniversityChangshaHunan410008P. R. China
| | - Yuan Zhi
- Department of Oral and Maxillofacial SurgeryThe Second Xiangya Hospital of Central South UniversityChangshaHunan410012P. R. China
| | - Moxin Zi
- Department of Oral and Maxillofacial SurgeryThe Second Xiangya Hospital of Central South UniversityChangshaHunan410012P. R. China
| | - Yongzhen Mo
- Key Laboratory of Carcinogenesis and Cancer Invasion of the Chinese Ministry of EducationCancer Research InstituteCentral South UniversityChangshaHunan410008P. R. China
- Department of Otolaryngology Head and Neck SurgeryXiangya HospitalCentral South UniversityChangshaHunan410008P. R. China
| | - Yumin Wang
- Department of Otolaryngology Head and Neck SurgeryXiangya HospitalCentral South UniversityChangshaHunan410008P. R. China
| | - Qianjin Liao
- NHC Key Laboratory of Carcinogenesis and Hunan Key Laboratory of Cancer MetabolismHunan Cancer Hospital and the Affiliated Cancer Hospital of Xiangya School of MedicineCentral South UniversityChangshaHunan410008P. R. China
| | - Shanshan Zhang
- Department of Otolaryngology Head and Neck SurgeryXiangya HospitalCentral South UniversityChangshaHunan410008P. R. China
| | - Zhaojian Gong
- Department of Oral and Maxillofacial SurgeryThe Second Xiangya Hospital of Central South UniversityChangshaHunan410012P. R. China
| | - Fuyan Wang
- Key Laboratory of Carcinogenesis and Cancer Invasion of the Chinese Ministry of EducationCancer Research InstituteCentral South UniversityChangshaHunan410008P. R. China
| | - Zhaoyang Zeng
- NHC Key Laboratory of Carcinogenesis and Hunan Key Laboratory of Cancer MetabolismHunan Cancer Hospital and the Affiliated Cancer Hospital of Xiangya School of MedicineCentral South UniversityChangshaHunan410008P. R. China
- Key Laboratory of Carcinogenesis and Cancer Invasion of the Chinese Ministry of EducationCancer Research InstituteCentral South UniversityChangshaHunan410008P. R. China
| | - Can Guo
- NHC Key Laboratory of Carcinogenesis and Hunan Key Laboratory of Cancer MetabolismHunan Cancer Hospital and the Affiliated Cancer Hospital of Xiangya School of MedicineCentral South UniversityChangshaHunan410008P. R. China
- Key Laboratory of Carcinogenesis and Cancer Invasion of the Chinese Ministry of EducationCancer Research InstituteCentral South UniversityChangshaHunan410008P. R. China
| | - Wei Xiong
- NHC Key Laboratory of Carcinogenesis and Hunan Key Laboratory of Cancer MetabolismHunan Cancer Hospital and the Affiliated Cancer Hospital of Xiangya School of MedicineCentral South UniversityChangshaHunan410008P. R. China
- Key Laboratory of Carcinogenesis and Cancer Invasion of the Chinese Ministry of EducationCancer Research InstituteCentral South UniversityChangshaHunan410008P. R. China
| |
Collapse
|
66
|
Chen Y, Yang C, Sheng L, Jiang H, Song B. The Era of Immunotherapy in Hepatocellular Carcinoma: The New Mission and Challenges of Magnetic Resonance Imaging. Cancers (Basel) 2023; 15:4677. [PMID: 37835371 PMCID: PMC10572030 DOI: 10.3390/cancers15194677] [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: 08/05/2023] [Revised: 09/11/2023] [Accepted: 09/13/2023] [Indexed: 10/15/2023] Open
Abstract
In recent years, significant advancements in immunotherapy for hepatocellular carcinoma (HCC) have shown the potential to further improve the prognosis of patients with advanced HCC. However, in clinical practice, there is still a lack of effective biomarkers for identifying the patient who would benefit from immunotherapy and predicting the tumor response to immunotherapy. The immune microenvironment of HCC plays a crucial role in tumor development and drug responses. However, due to the complexity of immune microenvironment, currently, no single pathological or molecular biomarker can effectively predict tumor responses to immunotherapy. Magnetic resonance imaging (MRI) images provide rich biological information; existing studies suggest the feasibility of using MRI to assess the immune microenvironment of HCC and predict tumor responses to immunotherapy. Nevertheless, there are limitations, such as the suboptimal performance of conventional MRI sequences, incomplete feature extraction in previous deep learning methods, and limited interpretability. Further study needs to combine qualitative features, quantitative parameters, multi-omics characteristics related to the HCC immune microenvironment, and various deep learning techniques in multi-center research cohorts. Subsequently, efforts should also be undertaken to construct and validate a visual predictive tool of tumor response, and assess its predictive value for patient survival benefits. Additionally, future research endeavors must aim to provide an accurate, efficient, non-invasive, and highly interpretable method for predicting the effectiveness of immune therapy.
Collapse
Affiliation(s)
- Yidi Chen
- Department of Radiology, West China Hospital, Sichuan University, Chengdu 610064, China; (Y.C.); (C.Y.); (L.S.)
| | - Chongtu Yang
- Department of Radiology, West China Hospital, Sichuan University, Chengdu 610064, China; (Y.C.); (C.Y.); (L.S.)
| | - Liuji Sheng
- Department of Radiology, West China Hospital, Sichuan University, Chengdu 610064, China; (Y.C.); (C.Y.); (L.S.)
| | - Hanyu Jiang
- Department of Radiology, West China Hospital, Sichuan University, Chengdu 610064, China; (Y.C.); (C.Y.); (L.S.)
| | - Bin Song
- Department of Radiology, West China Hospital, Sichuan University, Chengdu 610064, China; (Y.C.); (C.Y.); (L.S.)
- Department of Radiology, Sanya People’s Hospital, Sanya 572000, China
| |
Collapse
|
67
|
Li H, Ma T, Hao M, Guo W, Gu J, Zhang X, Wei L. Decoding functional cell-cell communication events by multi-view graph learning on spatial transcriptomics. Brief Bioinform 2023; 24:bbad359. [PMID: 37824741 DOI: 10.1093/bib/bbad359] [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: 07/12/2023] [Revised: 08/25/2023] [Accepted: 09/18/2023] [Indexed: 10/14/2023] Open
Abstract
Cell-cell communication events (CEs) are mediated by multiple ligand-receptor (LR) pairs. Usually only a particular subset of CEs directly works for a specific downstream response in a particular microenvironment. We name them as functional communication events (FCEs) of the target responses. Decoding FCE-target gene relations is: important for understanding the mechanisms of many biological processes, but has been intractable due to the mixing of multiple factors and the lack of direct observations. We developed a method HoloNet for decoding FCEs using spatial transcriptomic data by integrating LR pairs, cell-type spatial distribution and downstream gene expression into a deep learning model. We modeled CEs as a multi-view network, developed an attention-based graph learning method to train the model for generating target gene expression with the CE networks, and decoded the FCEs for specific downstream genes by interpreting trained models. We applied HoloNet on three Visium datasets of breast cancer and liver cancer. The results detangled the multiple factors of FCEs by revealing how LR signals and cell types affect specific biological processes, and specified FCE-induced effects in each single cell. We conducted simulation experiments and showed that HoloNet is more reliable on LR prioritization in comparison with existing methods. HoloNet is a powerful tool to illustrate cell-cell communication landscapes and reveal vital FCEs that shape cellular phenotypes. HoloNet is available as a Python package at https://github.com/lhc17/HoloNet.
Collapse
Affiliation(s)
- Haochen Li
- School of Medicine, Tsinghua University, Beijing 100084, China
| | - Tianxing Ma
- MOE Key Lab of Bioinformatics, Bioinformatics Division of BNRIST and Department of Automation, Tsinghua University, Beijing 100084, China
| | - Minsheng Hao
- MOE Key Lab of Bioinformatics, Bioinformatics Division of BNRIST and Department of Automation, Tsinghua University, Beijing 100084, China
| | - Wenbo Guo
- MOE Key Lab of Bioinformatics, Bioinformatics Division of BNRIST and Department of Automation, Tsinghua University, Beijing 100084, China
| | - Jin Gu
- MOE Key Lab of Bioinformatics, Bioinformatics Division of BNRIST and Department of Automation, Tsinghua University, Beijing 100084, China
| | - Xuegong Zhang
- School of Medicine, Tsinghua University, Beijing 100084, China
- MOE Key Lab of Bioinformatics, Bioinformatics Division of BNRIST and Department of Automation, Tsinghua University, Beijing 100084, China
| | - Lei Wei
- MOE Key Lab of Bioinformatics, Bioinformatics Division of BNRIST and Department of Automation, Tsinghua University, Beijing 100084, China
| |
Collapse
|
68
|
Du J, An ZJ, Huang ZF, Yang YC, Zhang MH, Fu XH, Shi WY, Hou J. Novel insights from spatial transcriptome analysis in solid tumors. Int J Biol Sci 2023; 19:4778-4792. [PMID: 37781515 PMCID: PMC10539699 DOI: 10.7150/ijbs.83098] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2023] [Accepted: 08/03/2023] [Indexed: 10/03/2023] Open
Abstract
Since its first application in 2016, spatial transcriptomics has become a rapidly evolving technology in recent years. Spatial transcriptomics enables transcriptomic data to be acquired from intact tissue sections and provides spatial distribution information and remedies the disadvantage of single-cell RNA sequencing (scRNA-seq), whose data lack spatially resolved information. Presently, spatial transcriptomics has been widely applied to various tissue types, especially for the study of tumor heterogeneity. In this review, we provide a summary of the research progress in utilizing spatial transcriptomics to investigate tumor heterogeneity and the microenvironment with a focus on solid tumors. We summarize the research breakthroughs in various fields and perspectives due to the application of spatial transcriptomics, including cell clustering and interaction, cellular metabolism, gene expression, immune cell programs and combination with other techniques. As a combination of multiple transcriptomics, single-cell multiomics shows its superiority and validity in single-cell analysis. We also discuss the application prospect of single-cell multiomics, and we believe that with the progress of data integration from various transcriptomics, a multilayered subcellular landscape will be revealed.
Collapse
Affiliation(s)
- Jun Du
- Department of Hematology, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, 160 Pujiang Road, Shanghai, 200127, China
| | - Zhi-Jie An
- School of Medicine, Shanghai Jiao Tong University, Shanghai, 200025, China
| | - Zou-Fang Huang
- Ganzhou Key Laboratory of Hematology, Department of Hematology, The First Affiliated Hospital of Gannan Medical University, Ganzhou, Jiangxi, 341000, China
| | - Yu-Chen Yang
- School of Medicine, Shanghai Jiao Tong University, Shanghai, 200025, China
| | - Ming-Hui Zhang
- School of Medicine, Shanghai Jiao Tong University, Shanghai, 200025, China
| | - Xue-Hang Fu
- Department of Hematology, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, 160 Pujiang Road, Shanghai, 200127, China
| | - Wei-Yang Shi
- Ministry of Education Key Laboratory of Marine Genetics and Breeding, College of Marine Life Sciences, Ocean University of China, Qingdao 266003, China
| | - Jian Hou
- Department of Hematology, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, 160 Pujiang Road, Shanghai, 200127, China
| |
Collapse
|
69
|
Wang Y, Wang P, Zhang Z, Zhou J, Fan J, Sun Y. Dissecting the tumor ecosystem of liver cancers in the single-cell era. Hepatol Commun 2023; 7:e0248. [PMID: 37639704 PMCID: PMC10461950 DOI: 10.1097/hc9.0000000000000248] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/08/2023] [Accepted: 06/24/2023] [Indexed: 08/31/2023] Open
Abstract
Primary liver cancers (PLCs) are a broad class of malignancies that include HCC, intrahepatic cholangiocarcinoma, and combined hepatocellular and intrahepatic cholangiocarcinoma. PLCs are often associated with a poor prognosis due to their high relapse and low therapeutic response rates. Importantly, PLCs exist within a dynamic and complex tumor ecosystem, which includes malignant, immune, and stromal cells. It is critical to dissect the PLC tumor ecosystem to uncover the underlying mechanisms associated with tumorigenesis, relapse, and treatment resistance to facilitate the discovery of novel therapeutic targets. Single-cell and spatial multi-omics sequencing techniques offer an unprecedented opportunity to elucidate spatiotemporal interactions among heterogeneous cell types within the complex tumor ecosystem. In this review, we describe the latest advances in single-cell and spatial technologies and review their applications with respect to dissecting liver cancer tumor ecosystems.
Collapse
|
70
|
You M, Gao Y, Fu J, Xie R, Zhu Z, Hong Z, Meng L, Du S, Liu J, Wang FS, Yang P, Chen L. Epigenetic regulation of HBV-specific tumor-infiltrating T cells in HBV-related HCC. Hepatology 2023; 78:943-958. [PMID: 36999652 PMCID: PMC10442105 DOI: 10.1097/hep.0000000000000369] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/12/2022] [Revised: 02/07/2023] [Accepted: 02/08/2023] [Indexed: 04/01/2023]
Abstract
BACKGROUND AND AIMS HBV shapes the T-cell immune responses in HBV-related HCC. T cells can be recruited to the nidus, but limited T cells participate specifically in response to the HBV-related tumor microenvironment and HBV antigens. How epigenomic programs regulate T-cell compartments in virus-specific immune processes is unclear. APPROACH AND RESULTS We developed Ti-ATAC-seq. 2 to map the T-cell receptor repertoire, epigenomic, and transcriptomic landscape of αβ T cells at both the bulk-cell and single-cell levels in 54 patients with HCC. We deeply investigated HBV-specific T cells and HBV-related T-cell subsets that specifically responded to HBV antigens and the HBV + tumor microenvironment, respectively, characterizing their T-cell receptor clonality and specificity and performing epigenomic profiling. A shared program comprising NFKB1/2-, Proto-Oncogene, NF-KB Sub unit, NFATC2-, and NR4A1-associated unique T-cell receptor-downstream core epigenomic and transcriptomic regulome commonly regulated the differentiation of HBV-specific regulatory T-cell (Treg) cells and CD8 + exhausted T cells; this program was also selectively enriched in the HBV-related Treg-CTLA4 and CD8-exhausted T cell-thymocyte selection associated high mobility subsets and drove greater clonal expansion in HBV-related Treg-CTLA4 subset. Overall, 54% of the effector and memory HBV-specific T cells are governed by transcription factor motifs of activator protein 1, NFE2, and BACH1/2, which have been reported to be associated with prolonged patient relapse-free survival. Moreover, HBV-related tumor-infiltrating Tregs correlated with both increased viral titer and poor prognosis in patients. CONCLUSIONS This study provides insight into the cellular and molecular basis of the epigenomic programs that regulate the differentiation and generation of HBV-related T cells from viral infection and HBV + HCC unique immune exhaustion.
Collapse
Affiliation(s)
- Maojun You
- Chongqing International Institute for Immunology, Chongqing, China
- Key Laboratory of Infection and Immunity of CAS, CAS Center for Excellence in Biomacromolecules, Institute of Biophysics, Chinese Academy of Sciences, University of Chinese Academy of Sciences, Beijing, China
| | - Yanan Gao
- Chongqing International Institute for Immunology, Chongqing, China
- Key Laboratory of Infection and Immunity of CAS, CAS Center for Excellence in Biomacromolecules, Institute of Biophysics, Chinese Academy of Sciences, University of Chinese Academy of Sciences, Beijing, China
| | - Junliang Fu
- Senior Department of Infectious Diseases, The Fifth Medical Center of Chinese PLA General Hospital, National Clinical Research Center for Infectious Diseases, Beijing, China
| | - Runze Xie
- Chongqing International Institute for Immunology, Chongqing, China
- Key Laboratory of Infection and Immunity of CAS, CAS Center for Excellence in Biomacromolecules, Institute of Biophysics, Chinese Academy of Sciences, University of Chinese Academy of Sciences, Beijing, China
| | - Zhenyu Zhu
- Senior Department of Hepatobiliary Surgery, The Fifth Medical Center of Chinese PLA Centeral Hospital, Beijing, China
| | - Zhixian Hong
- Senior Department of Hepatobiliary Surgery, The Fifth Medical Center of Chinese PLA Centeral Hospital, Beijing, China
| | - Lingzhan Meng
- Senior Department of Hepatobiliary Surgery, The Fifth Medical Center of Chinese PLA Centeral Hospital, Beijing, China
| | - Shunda Du
- Department of Liver Surgery, Peking Union Medical College (PUMC) Hospital, Chinese Academy of Medical Science and PUMC, Beijing, China
| | - Junliang Liu
- Chongqing International Institute for Immunology, Chongqing, China
- Key Laboratory of Infection and Immunity of CAS, CAS Center for Excellence in Biomacromolecules, Institute of Biophysics, Chinese Academy of Sciences, University of Chinese Academy of Sciences, Beijing, China
| | - Fu-Sheng Wang
- Senior Department of Infectious Diseases, The Fifth Medical Center of Chinese PLA General Hospital, National Clinical Research Center for Infectious Diseases, Beijing, China
| | - Pengyuan Yang
- Chongqing International Institute for Immunology, Chongqing, China
- Key Laboratory of Infection and Immunity of CAS, CAS Center for Excellence in Biomacromolecules, Institute of Biophysics, Chinese Academy of Sciences, University of Chinese Academy of Sciences, Beijing, China
| | - Liang Chen
- School of Medicine, Shanghai University, Shanghai, China
| |
Collapse
|
71
|
Zhong X, Lv M, Ma M, Huang Q, Hu R, Li J, Yi J, Sun J, Zhou X. State of CD8 + T cells in progression from nonalcoholic steatohepatitis to hepatocellular carcinoma: From pathogenesis to immunotherapy. Biomed Pharmacother 2023; 165:115131. [PMID: 37429231 DOI: 10.1016/j.biopha.2023.115131] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/21/2023] [Revised: 06/26/2023] [Accepted: 07/02/2023] [Indexed: 07/12/2023] Open
Abstract
With the obesity epidemic, nonalcoholic steatohepatitis (NASH) is emerging as the fastest growing potential cause of hepatocellular carcinoma (HCC). NASH has been demonstrated to establish a tumor-prone liver microenvironment where both innate and adaptive immune systems are involved. As the most typical anti-tumor effector, the cell function of CD8+ T cells is remodeled by chronic inflammation, metabolic alteration, lipid toxicity and oxidative stress in the liver microenvironment along the NASH to HCC transition. Unexpectedly, NASH may blunt the effect of immune checkpoint inhibitor therapy against HCC due to the dysregulated CD8+ T cells. Growing evidence has supported that NASH is likely to facilitate the state transition of CD8+ T cells with changes in cell motility, effector function, metabolic reprogramming and gene transcription according to single-cell sequencing. However, the mechanistic insight of CD8+ T cell states in the NASH-driven HCC is not comprehensive. Herein, we focus on the characterization of state phenotypes of CD8+ T cells with both functional and metabolic signatures in NASH-driven fibrosis and HCC. The NASH-specific CD8+ T cells are speculated to mainly have a dualist effect, where its aberrant activated phenotype sustains chronic inflammation in NASH but subsequently triggers its exhaustion in HCC. As the exploration of CD8+ T cells on the distribution and phenotypic shifts will provide a new direction for the intervention strategies against HCC, we also discuss the implications for targeting different phenotypes of CD8+ T cells, shedding light on the personalized immunotherapy for NASH-driven HCC.
Collapse
Affiliation(s)
- Xin Zhong
- Department of Liver Disease, Shenzhen Traditional Chinese Medicine Hospital, Shenzhen, Guangdong, China; Department of Liver Disease, the fourth Clinical Medical College of Guangzhou University of Chinese Medicine, Shenzhen, Guangdong, China
| | - Minling Lv
- Department of Liver Disease, Shenzhen Traditional Chinese Medicine Hospital, Shenzhen, Guangdong, China; Department of Liver Disease, the fourth Clinical Medical College of Guangzhou University of Chinese Medicine, Shenzhen, Guangdong, China
| | - MengQing Ma
- Department of Liver Disease, Shenzhen Traditional Chinese Medicine Hospital, Shenzhen, Guangdong, China; Department of Liver Disease, the fourth Clinical Medical College of Guangzhou University of Chinese Medicine, Shenzhen, Guangdong, China
| | - Qi Huang
- Department of Liver Disease, Shenzhen Traditional Chinese Medicine Hospital, Shenzhen, Guangdong, China; Department of Liver Disease, the fourth Clinical Medical College of Guangzhou University of Chinese Medicine, Shenzhen, Guangdong, China
| | - Rui Hu
- Department of Liver Disease, Shenzhen Traditional Chinese Medicine Hospital, Shenzhen, Guangdong, China; Department of Liver Disease, the fourth Clinical Medical College of Guangzhou University of Chinese Medicine, Shenzhen, Guangdong, China
| | - Jing Li
- Department of Liver Disease, Shenzhen Traditional Chinese Medicine Hospital, Shenzhen, Guangdong, China; Department of Liver Disease, the fourth Clinical Medical College of Guangzhou University of Chinese Medicine, Shenzhen, Guangdong, China
| | - Jinyu Yi
- Department of Liver Disease, Shenzhen Traditional Chinese Medicine Hospital, Shenzhen, Guangdong, China; Department of Liver Disease, the fourth Clinical Medical College of Guangzhou University of Chinese Medicine, Shenzhen, Guangdong, China
| | - Jialing Sun
- Department of Liver Disease, Shenzhen Traditional Chinese Medicine Hospital, Shenzhen, Guangdong, China; Department of Liver Disease, the fourth Clinical Medical College of Guangzhou University of Chinese Medicine, Shenzhen, Guangdong, China
| | - Xiaozhou Zhou
- Department of Liver Disease, Shenzhen Traditional Chinese Medicine Hospital, Shenzhen, Guangdong, China; Department of Liver Disease, the fourth Clinical Medical College of Guangzhou University of Chinese Medicine, Shenzhen, Guangdong, China.
| |
Collapse
|
72
|
Adlat S, Vázquez Salgado AM, Lee M, Yin D, Wangensteen KJ. Emerging and potential use of CRISPR in human liver disease. Hepatology 2023:01515467-990000000-00538. [PMID: 37607734 PMCID: PMC10881897 DOI: 10.1097/hep.0000000000000578] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/17/2023] [Accepted: 08/13/2023] [Indexed: 08/24/2023]
Abstract
CRISPR is a gene editing tool adapted from naturally occurring defense systems from bacteria. It is a technology that is revolutionizing the interrogation of gene functions in driving liver disease, especially through genetic screens and by facilitating animal knockout and knockin models. It is being used in models of liver disease to identify which genes are critical for liver pathology, especially in genetic liver disease, hepatitis, and in cancer initiation and progression. It holds tremendous promise in treating human diseases directly by editing DNA. It could disable gene function in the case of expression of a maladaptive protein, such as blocking transthyretin as a therapy for amyloidosis, or to correct gene defects, such as restoring the normal functions of liver enzymes fumarylacetoacetate hydrolase or alpha-1 antitrypsin. It is also being studied for treatment of hepatitis B infection. CRISPR is an exciting, evolving technology that is facilitating gene characterization and discovery in liver disease and holds the potential to treat liver diseases safely and permanently.
Collapse
Affiliation(s)
- Salah Adlat
- Division of Gastroenterology and Hepatology, Department of Medicine, Mayo Clinic, Rochester, Minnesota, USA
| | | | | | | | | |
Collapse
|
73
|
Arora R, Cao C, Kumar M, Sinha S, Chanda A, McNeil R, Samuel D, Arora RK, Matthews TW, Chandarana S, Hart R, Dort JC, Biernaskie J, Neri P, Hyrcza MD, Bose P. Spatial transcriptomics reveals distinct and conserved tumor core and edge architectures that predict survival and targeted therapy response. Nat Commun 2023; 14:5029. [PMID: 37596273 PMCID: PMC10439131 DOI: 10.1038/s41467-023-40271-4] [Citation(s) in RCA: 11] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2022] [Accepted: 07/19/2023] [Indexed: 08/20/2023] Open
Abstract
The spatial organization of the tumor microenvironment has a profound impact on biology and therapy response. Here, we perform an integrative single-cell and spatial transcriptomic analysis on HPV-negative oral squamous cell carcinoma (OSCC) to comprehensively characterize malignant cells in tumor core (TC) and leading edge (LE) transcriptional architectures. We show that the TC and LE are characterized by unique transcriptional profiles, neighboring cellular compositions, and ligand-receptor interactions. We demonstrate that the gene expression profile associated with the LE is conserved across different cancers while the TC is tissue specific, highlighting common mechanisms underlying tumor progression and invasion. Additionally, we find our LE gene signature is associated with worse clinical outcomes while TC gene signature is associated with improved prognosis across multiple cancer types. Finally, using an in silico modeling approach, we describe spatially-regulated patterns of cell development in OSCC that are predictably associated with drug response. Our work provides pan-cancer insights into TC and LE biology and interactive spatial atlases ( http://www.pboselab.ca/spatial_OSCC/ ; http://www.pboselab.ca/dynamo_OSCC/ ) that can be foundational for developing novel targeted therapies.
Collapse
Affiliation(s)
- Rohit Arora
- Department of Biochemistry & Molecular Biology, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada
| | - Christian Cao
- Department of Biochemistry & Molecular Biology, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada
- Temerty Faculty of Medicine, University of Toronto, Toronto, ON, Canada
| | - Mehul Kumar
- Department of Biochemistry & Molecular Biology, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada
- Arnie Charbonneau Cancer Institute, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada
| | - Sarthak Sinha
- Department of Comparative Biology and Experimental Medicine, Faculty of Veterinary Medicine, University of Calgary, Calgary, AB, Canada
| | - Ayan Chanda
- Department of Biochemistry & Molecular Biology, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada
- Arnie Charbonneau Cancer Institute, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada
| | - Reid McNeil
- Department of Biochemistry & Molecular Biology, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada
- Arnie Charbonneau Cancer Institute, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada
| | - Divya Samuel
- Department of Biochemistry & Molecular Biology, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada
- Arnie Charbonneau Cancer Institute, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada
| | - Rahul K Arora
- Center for Health Informatics, University of Calgary, Calgary, AB, Canada
- Institute of Biomedical Engineering, University of Oxford, Oxford, United Kingdom
| | - T Wayne Matthews
- Ohlson Research Initiative, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada
- Section of Otolaryngology Head & Neck Surgery, Department of Surgery, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada
| | - Shamir Chandarana
- Ohlson Research Initiative, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada
- Section of Otolaryngology Head & Neck Surgery, Department of Surgery, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada
| | - Robert Hart
- Ohlson Research Initiative, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada
- Section of Otolaryngology Head & Neck Surgery, Department of Surgery, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada
| | - Joseph C Dort
- Arnie Charbonneau Cancer Institute, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada
- Ohlson Research Initiative, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada
- Section of Otolaryngology Head & Neck Surgery, Department of Surgery, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada
- Department of Community Health Sciences, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada
| | - Jeff Biernaskie
- Department of Comparative Biology and Experimental Medicine, Faculty of Veterinary Medicine, University of Calgary, Calgary, AB, Canada
- Alberta Children's Hospital Research Institute, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada
- Hotchkiss Brain Institute, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada
- Department of Surgery, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada
| | - Paola Neri
- Arnie Charbonneau Cancer Institute, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada
- Division of Hematology, Department of Oncology, University of Calgary, Calgary, AB, Canada
| | - Martin D Hyrcza
- Arnie Charbonneau Cancer Institute, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada
- Department of Pathology and Laboratory Medicine, University of Calgary, Calgary, AB, Canada
| | - Pinaki Bose
- Department of Biochemistry & Molecular Biology, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada.
- Arnie Charbonneau Cancer Institute, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada.
- Institute of Biomedical Engineering, University of Oxford, Oxford, United Kingdom.
- Department of Oncology, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada.
| |
Collapse
|
74
|
Liu Z, Wu D, Zhai W, Ma L. SONAR enables cell type deconvolution with spatially weighted Poisson-Gamma model for spatial transcriptomics. Nat Commun 2023; 14:4727. [PMID: 37550279 PMCID: PMC10406862 DOI: 10.1038/s41467-023-40458-9] [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: 01/10/2023] [Accepted: 07/25/2023] [Indexed: 08/09/2023] Open
Abstract
Recent advancements in spatial transcriptomic technologies have enabled the measurement of whole transcriptome profiles with preserved spatial context. However, limited by spatial resolution, the measured expressions at each spot are often from a mixture of multiple cells. Computational deconvolution methods designed for spatial transcriptomic data rarely make use of the valuable spatial information as well as the neighboring similarity information. Here, we propose SONAR, a Spatially weighted pOissoN-gAmma Regression model for cell-type deconvolution with spatial transcriptomic data. SONAR directly models the raw counts of spatial transcriptomic data and applies a geographically weighted regression framework that incorporates neighboring information to enhance local estimation of regional cell type composition. In addition, SONAR applies an additional elastic weighting step to adaptively filter dissimilar neighbors, which effectively prevents the introduction of local estimation bias in transition regions with sharp boundaries. We demonstrate the performance of SONAR over other state-of-the-art methods on synthetic data with various spatial patterns. We find that SONAR can accurately map region-specific cell types in real spatial transcriptomic data including mouse brain, human heart and human pancreatic ductal adenocarcinoma. We further show that SONAR can reveal the detailed distributions and fine-grained co-localization of immune cells within the microenvironment at the tumor-normal tissue margin in human liver cancer.
Collapse
Affiliation(s)
- Zhiyuan Liu
- Key Laboratory of Zoological Systematics and Evolution, Institute of Zoology, Chinese Academy of Sciences, 100101, Beijing, China
- University of the Chinese Academy of Sciences, 100049, Beijing, China
| | - Dafei Wu
- Key Laboratory of Zoological Systematics and Evolution, Institute of Zoology, Chinese Academy of Sciences, 100101, Beijing, China
| | - Weiwei Zhai
- Key Laboratory of Zoological Systematics and Evolution, Institute of Zoology, Chinese Academy of Sciences, 100101, Beijing, China.
- University of the Chinese Academy of Sciences, 100049, Beijing, China.
- Center for Excellence in Animal Evolution and Genetics, Chinese Academy of Sciences, 650223, Kunming, China.
| | - Liang Ma
- Key Laboratory of Zoological Systematics and Evolution, Institute of Zoology, Chinese Academy of Sciences, 100101, Beijing, China.
| |
Collapse
|
75
|
Zheng J, Wu H, Wang X, Zhang G, Lu J, Xu W, Xu S, Fang Y, Zhang A, Shao A, Chen S, Zhao Z, Zhang J, Yu J. Temporal dynamics of microglia-astrocyte interaction in neuroprotective glial scar formation after intracerebral hemorrhage. J Pharm Anal 2023; 13:862-879. [PMID: 37719195 PMCID: PMC10499589 DOI: 10.1016/j.jpha.2023.02.007] [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: 10/08/2022] [Revised: 02/02/2023] [Accepted: 02/16/2023] [Indexed: 02/25/2023] Open
Abstract
The role of glial scar after intracerebral hemorrhage (ICH) remains unclear. This study aimed to investigate whether microglia-astrocyte interaction affects glial scar formation and explore the specific function of glial scar. We used a pharmacologic approach to induce microglial depletion during different ICH stages and examine how ablating microglia affects astrocytic scar formation. Spatial transcriptomics (ST) analysis was performed to explore the potential ligand-receptor pair in the modulation of microglia-astrocyte interaction and to verify the functional changes of astrocytic scars at different periods. During the early stage, sustained microglial depletion induced disorganized astrocytic scar, enhanced neutrophil infiltration, and impaired tissue repair. ST analysis indicated that microglia-derived insulin like growth factor 1 (IGF1) modulated astrocytic scar formation via mechanistic target of rapamycin (mTOR) signaling activation. Moreover, repopulating microglia (RM) more strongly activated mTOR signaling, facilitating a more protective scar formation. The combination of IGF1 and osteopontin (OPN) was necessary and sufficient for RM function, rather than IGF1 or OPN alone. At the chronic stage of ICH, the overall net effect of astrocytic scar changed from protective to destructive and delayed microglial depletion could partly reverse this. The vital insight gleaned from our data is that sustained microglial depletion may not be a reasonable treatment strategy for early-stage ICH. Inversely, early-stage IGF1/OPN treatment combined with late-stage PLX3397 treatment is a promising therapeutic strategy. This prompts us to consider the complex temporal dynamics and overall net effect of microglia and astrocytes, and develop elaborate treatment strategies at precise time points after ICH.
Collapse
Affiliation(s)
- Jingwei Zheng
- Department of Neurosurgery, Second Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, 310000, China
- Stroke Research Center for Diagnostic and Therapeutic Technologies of Zhejiang Province, Hangzhou, 310000, China
| | - Haijian Wu
- Department of Neurosurgery, Second Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, 310000, China
- Stroke Research Center for Diagnostic and Therapeutic Technologies of Zhejiang Province, Hangzhou, 310000, China
| | - Xiaoyu Wang
- Department of Neurosurgery, Second Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, 310000, China
| | - Guoqiang Zhang
- Department of Neurosurgery, Second Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, 310000, China
| | - Jia'nan Lu
- Department of Neurosurgery, Second Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, 310000, China
| | - Weilin Xu
- Department of Neurosurgery, Second Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, 310000, China
- Stroke Research Center for Diagnostic and Therapeutic Technologies of Zhejiang Province, Hangzhou, 310000, China
| | - Shenbin Xu
- Department of Neurosurgery, Second Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, 310000, China
- Stroke Research Center for Diagnostic and Therapeutic Technologies of Zhejiang Province, Hangzhou, 310000, China
| | - Yuanjian Fang
- Department of Neurosurgery, Second Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, 310000, China
- Stroke Research Center for Diagnostic and Therapeutic Technologies of Zhejiang Province, Hangzhou, 310000, China
| | - Anke Zhang
- Department of Neurosurgery, Second Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, 310000, China
| | - Anwen Shao
- Department of Neurosurgery, Second Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, 310000, China
- Stroke Research Center for Diagnostic and Therapeutic Technologies of Zhejiang Province, Hangzhou, 310000, China
| | - Sheng Chen
- Department of Neurosurgery, Second Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, 310000, China
- Stroke Research Center for Diagnostic and Therapeutic Technologies of Zhejiang Province, Hangzhou, 310000, China
| | - Zhen Zhao
- Center for Neurodegeneration and Regeneration, Zilkha Neurogenetic Institute and Department of Physiology and Biophysics, Keck School of Medicine, University of Southern California, Los Angeles, CA, 90089, USA
| | - Jianmin Zhang
- Department of Neurosurgery, Second Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, 310000, China
- Key Laboratory of Precise Treatment and Clinical Translational Research of Neurological Diseases, Hangzhou, 310000, China
- Stroke Research Center for Diagnostic and Therapeutic Technologies of Zhejiang Province, Hangzhou, 310000, China
| | - Jun Yu
- Department of Neurosurgery, Second Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, 310000, China
- Stroke Research Center for Diagnostic and Therapeutic Technologies of Zhejiang Province, Hangzhou, 310000, China
| |
Collapse
|
76
|
Wu L, Yan J, Bai Y, Chen F, Zou X, Xu J, Huang A, Hou L, Zhong Y, Jing Z, Yu Q, Zhou X, Jiang Z, Wang C, Cheng M, Ji Y, Hou Y, Luo R, Li Q, Wu L, Cheng J, Wang P, Guo D, Huang W, Lei J, Liu S, Yan Y, Chen Y, Liao S, Li Y, Sun H, Yao N, Zhang X, Zhang S, Chen X, Yu Y, Li Y, Liu F, Wang Z, Zhou S, Yang H, Yang S, Xu X, Liu L, Gao Q, Tang Z, Wang X, Wang J, Fan J, Liu S, Yang X, Chen A, Zhou J. An invasive zone in human liver cancer identified by Stereo-seq promotes hepatocyte-tumor cell crosstalk, local immunosuppression and tumor progression. Cell Res 2023; 33:585-603. [PMID: 37337030 PMCID: PMC10397313 DOI: 10.1038/s41422-023-00831-1] [Citation(s) in RCA: 24] [Impact Index Per Article: 24.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/18/2023] [Accepted: 05/22/2023] [Indexed: 06/21/2023] Open
Abstract
Dissecting and understanding the cancer ecosystem, especially that around the tumor margins, which have strong implications for tumor cell infiltration and invasion, are essential for exploring the mechanisms of tumor metastasis and developing effective new treatments. Using a novel tumor border scanning and digitization model enabled by nanoscale resolution-SpaTial Enhanced REsolution Omics-sequencing (Stereo-seq), we identified a 500 µm-wide zone centered around the tumor border in patients with liver cancer, referred to as "the invasive zone". We detected strong immunosuppression, metabolic reprogramming, and severely damaged hepatocytes in this zone. We also identified a subpopulation of damaged hepatocytes with increased expression of serum amyloid A1 and A2 (referred to collectively as SAAs) located close to the border on the paratumor side. Overexpression of CXCL6 in adjacent malignant cells could induce activation of the JAK-STAT3 pathway in nearby hepatocytes, which subsequently caused SAAs' overexpression in these hepatocytes. Furthermore, overexpression and secretion of SAAs by hepatocytes in the invasive zone could lead to the recruitment of macrophages and M2 polarization, further promoting local immunosuppression, potentially resulting in tumor progression. Clinical association analysis in additional five independent cohorts of patients with primary and secondary liver cancer (n = 423) showed that patients with overexpression of SAAs in the invasive zone had a worse prognosis. Further in vivo experiments using mouse liver tumor models in situ confirmed that the knockdown of genes encoding SAAs in hepatocytes decreased macrophage accumulation around the tumor border and delayed tumor growth. The identification and characterization of a novel invasive zone in human cancer patients not only add an important layer of understanding regarding the mechanisms of tumor invasion and metastasis, but may also pave the way for developing novel therapeutic strategies for advanced liver cancer and other solid tumors.
Collapse
Affiliation(s)
- Liang Wu
- Zhongshan-BGI Precision Medical Center, Zhongshan Hospital, Fudan University, Shanghai, China
- BGI-Southwest, BGI-Shenzhen, Chongqing, China
- BGI-Shenzhen, Beishan Industrial Zone, Shenzhen, Guangdong, China
| | - Jiayan Yan
- Zhongshan-BGI Precision Medical Center, Zhongshan Hospital, Fudan University, Shanghai, China
- Department of Liver Surgery & Transplantation, Liver Cancer Institute, Zhongshan Hospital, Fudan University; Key Laboratory of Carcinogenesis and Cancer Invasion, Ministry of Education, Shanghai, China
| | - Yinqi Bai
- Zhongshan-BGI Precision Medical Center, Zhongshan Hospital, Fudan University, Shanghai, China
- BGI-Shenzhen, Beishan Industrial Zone, Shenzhen, Guangdong, China
- BGI-Hangzhou, Hangzhou, Zhejiang, China
| | - Feiyu Chen
- Zhongshan-BGI Precision Medical Center, Zhongshan Hospital, Fudan University, Shanghai, China
- Department of Liver Surgery & Transplantation, Liver Cancer Institute, Zhongshan Hospital, Fudan University; Key Laboratory of Carcinogenesis and Cancer Invasion, Ministry of Education, Shanghai, China
| | - Xuanxuan Zou
- BGI-Southwest, BGI-Shenzhen, Chongqing, China
- BGI-Shenzhen, Beishan Industrial Zone, Shenzhen, Guangdong, China
- College of Life Sciences, University of Chinese Academy of Sciences, Beijing, China
| | - Jiangshan Xu
- BGI-Shenzhen, Beishan Industrial Zone, Shenzhen, Guangdong, China
- College of Life Sciences, University of Chinese Academy of Sciences, Beijing, China
| | - Ao Huang
- Zhongshan-BGI Precision Medical Center, Zhongshan Hospital, Fudan University, Shanghai, China
- Department of Liver Surgery & Transplantation, Liver Cancer Institute, Zhongshan Hospital, Fudan University; Key Laboratory of Carcinogenesis and Cancer Invasion, Ministry of Education, Shanghai, China
| | - Liangzhen Hou
- BGI-Shenzhen, Beishan Industrial Zone, Shenzhen, Guangdong, China
- College of Life Sciences, University of Chinese Academy of Sciences, Beijing, China
| | - Yu Zhong
- BGI-Shenzhen, Beishan Industrial Zone, Shenzhen, Guangdong, China
| | - Zehua Jing
- BGI-Shenzhen, Beishan Industrial Zone, Shenzhen, Guangdong, China
- College of Life Sciences, University of Chinese Academy of Sciences, Beijing, China
| | - Qichao Yu
- BGI-Shenzhen, Beishan Industrial Zone, Shenzhen, Guangdong, China
- College of Life Sciences, University of Chinese Academy of Sciences, Beijing, China
| | - Xiaorui Zhou
- BGI-Shenzhen, Beishan Industrial Zone, Shenzhen, Guangdong, China
- College of Life Sciences, University of Chinese Academy of Sciences, Beijing, China
| | - Zhifeng Jiang
- Department of Liver Surgery & Transplantation, Liver Cancer Institute, Zhongshan Hospital, Fudan University; Key Laboratory of Carcinogenesis and Cancer Invasion, Ministry of Education, Shanghai, China
| | - Chunqing Wang
- BGI-Shenzhen, Beishan Industrial Zone, Shenzhen, Guangdong, China
- College of Life Sciences, University of Chinese Academy of Sciences, Beijing, China
| | - Mengnan Cheng
- BGI-Shenzhen, Beishan Industrial Zone, Shenzhen, Guangdong, China
- College of Life Sciences, University of Chinese Academy of Sciences, Beijing, China
| | - Yuan Ji
- Zhongshan-BGI Precision Medical Center, Zhongshan Hospital, Fudan University, Shanghai, China
- Department of Pathology, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Yingyong Hou
- Department of Pathology, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Rongkui Luo
- Department of Pathology, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Qinqin Li
- Department of Pathology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Liang Wu
- BGI-Shenzhen, Beishan Industrial Zone, Shenzhen, Guangdong, China
- College of Life Sciences, University of Chinese Academy of Sciences, Beijing, China
| | - Jianwen Cheng
- Department of Liver Surgery & Transplantation, Liver Cancer Institute, Zhongshan Hospital, Fudan University; Key Laboratory of Carcinogenesis and Cancer Invasion, Ministry of Education, Shanghai, China
| | - Pengxiang Wang
- Department of Liver Surgery & Transplantation, Liver Cancer Institute, Zhongshan Hospital, Fudan University; Key Laboratory of Carcinogenesis and Cancer Invasion, Ministry of Education, Shanghai, China
| | - Dezhen Guo
- Department of Liver Surgery & Transplantation, Liver Cancer Institute, Zhongshan Hospital, Fudan University; Key Laboratory of Carcinogenesis and Cancer Invasion, Ministry of Education, Shanghai, China
| | - Waidong Huang
- BGI-Shenzhen, Beishan Industrial Zone, Shenzhen, Guangdong, China
- College of Life Sciences, University of Chinese Academy of Sciences, Beijing, China
| | - Junjie Lei
- BGI-Shenzhen, Beishan Industrial Zone, Shenzhen, Guangdong, China
- College of Life Sciences, University of Chinese Academy of Sciences, Beijing, China
| | - Shang Liu
- BGI-Shenzhen, Beishan Industrial Zone, Shenzhen, Guangdong, China
| | - Yizhen Yan
- BGI-Shenzhen, Beishan Industrial Zone, Shenzhen, Guangdong, China
| | - Yiling Chen
- BGI-Shenzhen, Beishan Industrial Zone, Shenzhen, Guangdong, China
| | - Sha Liao
- BGI-Southwest, BGI-Shenzhen, Chongqing, China
- BGI-Shenzhen, Beishan Industrial Zone, Shenzhen, Guangdong, China
| | - Yuxiang Li
- BGI-Shenzhen, Beishan Industrial Zone, Shenzhen, Guangdong, China
| | - Haixiang Sun
- Department of Liver Surgery & Transplantation, Liver Cancer Institute, Zhongshan Hospital, Fudan University; Key Laboratory of Carcinogenesis and Cancer Invasion, Ministry of Education, Shanghai, China
| | - Na Yao
- Department of Liver Surgery & Transplantation, Liver Cancer Institute, Zhongshan Hospital, Fudan University; Key Laboratory of Carcinogenesis and Cancer Invasion, Ministry of Education, Shanghai, China
| | - Xiangyu Zhang
- Department of Liver Surgery & Transplantation, Liver Cancer Institute, Zhongshan Hospital, Fudan University; Key Laboratory of Carcinogenesis and Cancer Invasion, Ministry of Education, Shanghai, China
| | - Shiyu Zhang
- Department of Liver Surgery & Transplantation, Liver Cancer Institute, Zhongshan Hospital, Fudan University; Key Laboratory of Carcinogenesis and Cancer Invasion, Ministry of Education, Shanghai, China
| | - Xi Chen
- BGI-Shenzhen, Beishan Industrial Zone, Shenzhen, Guangdong, China
| | - Yang Yu
- National Facility for Protein Science in Shanghai, Zhangjiang Lab, Shanghai Advanced Research Institute, Chinese Academy of Sciences, Shanghai, China
| | - Yao Li
- National Facility for Protein Science in Shanghai, Zhangjiang Lab, Shanghai Advanced Research Institute, Chinese Academy of Sciences, Shanghai, China
| | - Fengming Liu
- National Facility for Protein Science in Shanghai, Zhangjiang Lab, Shanghai Advanced Research Institute, Chinese Academy of Sciences, Shanghai, China
| | - Zheng Wang
- Department of Liver Surgery & Transplantation, Liver Cancer Institute, Zhongshan Hospital, Fudan University; Key Laboratory of Carcinogenesis and Cancer Invasion, Ministry of Education, Shanghai, China
| | - Shaolai Zhou
- Department of Liver Surgery & Transplantation, Liver Cancer Institute, Zhongshan Hospital, Fudan University; Key Laboratory of Carcinogenesis and Cancer Invasion, Ministry of Education, Shanghai, China
| | - Huanming Yang
- BGI-Shenzhen, Beishan Industrial Zone, Shenzhen, Guangdong, China
| | - Shuang Yang
- Zhongshan-BGI Precision Medical Center, Zhongshan Hospital, Fudan University, Shanghai, China
- BGI-Shenzhen, Beishan Industrial Zone, Shenzhen, Guangdong, China
- College of Life Sciences, University of Chinese Academy of Sciences, Beijing, China
| | - Xun Xu
- Zhongshan-BGI Precision Medical Center, Zhongshan Hospital, Fudan University, Shanghai, China
- BGI-Shenzhen, Beishan Industrial Zone, Shenzhen, Guangdong, China
- Guangdong Provincial Key Laboratory of Genome Read and Write, Shenzhen, Guangdong, China
| | - Longqi Liu
- Zhongshan-BGI Precision Medical Center, Zhongshan Hospital, Fudan University, Shanghai, China
- BGI-Hangzhou, Hangzhou, Zhejiang, China
| | - Qiang Gao
- Zhongshan-BGI Precision Medical Center, Zhongshan Hospital, Fudan University, Shanghai, China
- Department of Liver Surgery & Transplantation, Liver Cancer Institute, Zhongshan Hospital, Fudan University; Key Laboratory of Carcinogenesis and Cancer Invasion, Ministry of Education, Shanghai, China
| | - Zhaoyou Tang
- Zhongshan-BGI Precision Medical Center, Zhongshan Hospital, Fudan University, Shanghai, China
- Department of Liver Surgery & Transplantation, Liver Cancer Institute, Zhongshan Hospital, Fudan University; Key Laboratory of Carcinogenesis and Cancer Invasion, Ministry of Education, Shanghai, China
| | - Xiangdong Wang
- Zhongshan-BGI Precision Medical Center, Zhongshan Hospital, Fudan University, Shanghai, China
- Department of Pulmonary and Critical Care Medicine, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Jian Wang
- Zhongshan-BGI Precision Medical Center, Zhongshan Hospital, Fudan University, Shanghai, China
- BGI-Shenzhen, Beishan Industrial Zone, Shenzhen, Guangdong, China
- James D. Watson Institute of Genome Science, Hangzhou, Zhejiang, China
| | - Jia Fan
- Zhongshan-BGI Precision Medical Center, Zhongshan Hospital, Fudan University, Shanghai, China
- Department of Liver Surgery & Transplantation, Liver Cancer Institute, Zhongshan Hospital, Fudan University; Key Laboratory of Carcinogenesis and Cancer Invasion, Ministry of Education, Shanghai, China
| | - Shiping Liu
- Zhongshan-BGI Precision Medical Center, Zhongshan Hospital, Fudan University, Shanghai, China.
- BGI-Shenzhen, Beishan Industrial Zone, Shenzhen, Guangdong, China.
- Shenzhen Key Laboratory of Single-Cell Omics, BGI-Shenzhen, Shenzhen, Guangdong, China.
| | - Xinrong Yang
- Zhongshan-BGI Precision Medical Center, Zhongshan Hospital, Fudan University, Shanghai, China.
- Department of Liver Surgery & Transplantation, Liver Cancer Institute, Zhongshan Hospital, Fudan University; Key Laboratory of Carcinogenesis and Cancer Invasion, Ministry of Education, Shanghai, China.
| | - Ao Chen
- Zhongshan-BGI Precision Medical Center, Zhongshan Hospital, Fudan University, Shanghai, China.
- BGI-Southwest, BGI-Shenzhen, Chongqing, China.
- BGI-Shenzhen, Beishan Industrial Zone, Shenzhen, Guangdong, China.
- JFL-BGI STOmics Center, Jinfeng Laboratory, Chongqing, China.
| | - Jian Zhou
- Zhongshan-BGI Precision Medical Center, Zhongshan Hospital, Fudan University, Shanghai, China.
- Department of Liver Surgery & Transplantation, Liver Cancer Institute, Zhongshan Hospital, Fudan University; Key Laboratory of Carcinogenesis and Cancer Invasion, Ministry of Education, Shanghai, China.
- State Key Laboratory of Genetic Engineering, Fudan University, Shanghai, China.
| |
Collapse
|
77
|
Shi J, Pan Y, Liu X, Cao W, Mu Y, Zhu Q. Spatial Omics Sequencing Based on Microfluidic Array Chips. BIOSENSORS 2023; 13:712. [PMID: 37504111 PMCID: PMC10377411 DOI: 10.3390/bios13070712] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/18/2023] [Revised: 07/03/2023] [Accepted: 07/04/2023] [Indexed: 07/29/2023]
Abstract
Spatial profiling technologies fill the gap left by the loss of spatial information in traditional single-cell sequencing, showing great application prospects. After just a few years of quick development, spatial profiling technologies have made great progress in resolution and simplicity. This review introduces the development of spatial omics sequencing based on microfluidic array chips and describes barcoding strategies using various microfluidic designs with simplicity and efficiency. At the same time, the pros and cons of each strategy are compared. Moreover, commercialized solutions for spatial profiling are also introduced. In the end, the future perspective of spatial omics sequencing and research directions are discussed.
Collapse
Affiliation(s)
- Jianyu Shi
- State Key Laboratory of Industrial Control Technology, Research Center for Analytical Instrumentation, Institute of Cyber-Systems and Control, College of Control Science and Engineering, Zhejiang University, Hangzhou 310000, China
| | - Yating Pan
- State Key Laboratory of Industrial Control Technology, Research Center for Analytical Instrumentation, Institute of Cyber-Systems and Control, College of Control Science and Engineering, Zhejiang University, Hangzhou 310000, China
| | - Xudong Liu
- State Key Laboratory of Industrial Control Technology, Research Center for Analytical Instrumentation, Institute of Cyber-Systems and Control, College of Control Science and Engineering, Zhejiang University, Hangzhou 310000, China
| | - Wenjian Cao
- State Key Laboratory of Industrial Control Technology, Research Center for Analytical Instrumentation, Institute of Cyber-Systems and Control, College of Control Science and Engineering, Zhejiang University, Hangzhou 310000, China
| | - Ying Mu
- State Key Laboratory of Industrial Control Technology, Research Center for Analytical Instrumentation, Institute of Cyber-Systems and Control, College of Control Science and Engineering, Zhejiang University, Hangzhou 310000, China
| | - Qiangyuan Zhu
- State Key Laboratory of Industrial Control Technology, Research Center for Analytical Instrumentation, Institute of Cyber-Systems and Control, College of Control Science and Engineering, Zhejiang University, Hangzhou 310000, China
| |
Collapse
|
78
|
Zhao HC, Chen CZ, Tian YZ, Song HQ, Wang XX, Li YJ, He JF, Zhao HL. CD168+ macrophages promote hepatocellular carcinoma tumor stemness and progression through TOP2A/β-catenin/ YAP1 axis. iScience 2023; 26:106862. [PMID: 37275516 PMCID: PMC10238939 DOI: 10.1016/j.isci.2023.106862] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/10/2022] [Revised: 03/20/2023] [Accepted: 05/08/2023] [Indexed: 06/07/2023] Open
Abstract
Liver cancer stem-like cells (LCSCs) are the main cause of heterogeneity and poor prognosis in hepatocellular carcinoma (HCC). In this study, we aimed to explore the origin of LCSCs and the role of the TOP2A/β-catenin/YAP1 axis in tumor stemness and progression. Using single-cell RNA-seq analysis, we identified TOP2A+CENPF+ LCSCs, which were mainly regulated by CD168+ M2-like macrophages. Furthermore, spatial location analysis and fluorescent staining confirmed that LCSCs were enriched at tumor margins, constituting the spatial heterogeneity of HCC. Mechanistically, TOP2A competitively binds to β-catenin, leading to disassociation of β-catenin from YAP1, promoting HCC stemness and overgrowth. Our study provides valuable insights into the spatial transcriptome heterogeneity of the HCC microenvironment and the critical role of TOP2A/β-catenin/YAP1 axis in HCC stemness and progression.
Collapse
Affiliation(s)
- Hai-Chao Zhao
- Third Hospital of Shanxi Medical University, Shanxi Academy of Medical Sciences, Taiyuan 030032, China
- Department of Liver Surgery and Transplantation, Liver Cancer Institute, Zhongshan Hospital, Fudan University, Shanghai 200032, China
| | - Chang-Zhou Chen
- Department of Liver Surgery and Transplantation, Liver Cancer Institute, Zhongshan Hospital, Fudan University, Shanghai 200032, China
| | - Yan-Zhang Tian
- Shanxi Bethune Hospital, Shanxi Academy of Medical Sciences, Taiyuan 030032, China
| | - Huang-Qin Song
- Third Hospital of Shanxi Medical University, Shanxi Academy of Medical Sciences, Taiyuan 030032, China
| | - Xiao-Xiao Wang
- Third Hospital of Shanxi Medical University, Shanxi Academy of Medical Sciences, Taiyuan 030032, China
| | - Yan-Jun Li
- Shanxi Bethune Hospital, Shanxi Academy of Medical Sciences, Taiyuan 030032, China
| | - Jie-Feng He
- Third Hospital of Shanxi Medical University, Shanxi Academy of Medical Sciences, Taiyuan 030032, China
- Shanxi Bethune Hospital, Shanxi Academy of Medical Sciences, Taiyuan 030032, China
| | - Hao-Liang Zhao
- Third Hospital of Shanxi Medical University, Shanxi Academy of Medical Sciences, Taiyuan 030032, China
- Shanxi Bethune Hospital, Shanxi Academy of Medical Sciences, Taiyuan 030032, China
| |
Collapse
|
79
|
Fu W, Yang R, Li J. Single-cell and spatial transcriptomics reveal changes in cell heterogeneity during progression of human tendinopathy. BMC Biol 2023; 21:132. [PMID: 37280595 DOI: 10.1186/s12915-023-01613-2] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/22/2022] [Accepted: 05/03/2023] [Indexed: 06/08/2023] Open
Abstract
BACKGROUND Musculoskeletal tissue degeneration impairs the life quality and motor function of many people, especially seniors and athletes. Tendinopathy is one of the most common diseases associated with musculoskeletal tissue degeneration, representing a major global healthcare burden that affects both athletes and the general population, with the clinical presentation of long-term recurring chronic pain and decreased tolerance to activity. The cellular and molecular mechanisms at the basis of the disease process remain elusive. Here, we use a single-cell and spatial RNA sequencing approach to provide a further understanding of cellular heterogeneity and molecular mechanisms underlying tendinopathy progression. RESULTS To explore the changes in tendon homeostasis during the tendinopathy process, we built a cell atlas of healthy and diseased human tendons using single-cell RNA sequencing of approximately 35,000 cells and explored the variations of cell subtypes' spatial distributions using spatial RNA sequencing. We identified and localized different tenocyte subpopulations in normal and lesioned tendons, found different differentiation trajectories of tendon stem/progenitor cells in normal/diseased tendons, and revealed the spatial location relationship between stromal cells and diseased tenocytes. We deciphered the progression of tendinopathy at a single-cell level, which is characterized by inflammatory infiltration, followed by chondrogenesis and finally endochondral ossification. We found diseased tissue-specific endothelial cell subsets and macrophages as potential therapeutic targets. CONCLUSIONS This cell atlas provides the molecular foundation for investigating how tendon cell identities, biochemical functions, and interactions contributed to the tendinopathy process. The discoveries revealed the pathogenesis of tendinopathy at single-cell and spatial levels, which is characterized by inflammatory infiltration, followed by chondrogenesis, and finally endochondral ossification. Our results provide new insights into the control of tendinopathy and potential clues to developing novel diagnostic and therapeutic strategies.
Collapse
Affiliation(s)
- Weili Fu
- Department of Orthopedics, Orthopedic Research Institute, West China Hospital, Sichuan University, Chengdu, 610041, China.
| | - Runze Yang
- Department of Orthopedics, Orthopedic Research Institute, West China Hospital, Sichuan University, Chengdu, 610041, China
| | - Jian Li
- Department of Orthopedics, Orthopedic Research Institute, West China Hospital, Sichuan University, Chengdu, 610041, China
| |
Collapse
|
80
|
Ryaboshapkina M, Azzu V. Sample size calculation for a NanoString GeoMx spatial transcriptomics experiment to study predictors of fibrosis progression in non-alcoholic fatty liver disease. Sci Rep 2023; 13:8943. [PMID: 37268815 DOI: 10.1038/s41598-023-36187-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/17/2023] [Accepted: 05/29/2023] [Indexed: 06/04/2023] Open
Abstract
Sample size calculation for spatial transcriptomics is a novel and understudied research topic. Prior publications focused on powering spatial transcriptomics studies to detect specific cell populations or spatially variable expression patterns on tissue slides. However, power calculations for translational or clinical studies often relate to the difference between patient groups, and this is poorly described in the literature. Here, we present a stepwise process for sample size calculation to identify predictors of fibrosis progression in non-alcoholic fatty liver disease as a case study. We illustrate how to infer study hypothesis from prior bulk RNA-sequencing data, gather input requirements and perform a simulation study to estimate required sample size to evaluate gene expression differences between patients with stable fibrosis and fibrosis progressors with NanoString GeoMx Whole Transcriptome Atlas assay.
Collapse
Affiliation(s)
- Maria Ryaboshapkina
- Translational Science and Experimental Medicine, Research and Early Development, Cardiovascular, Renal and Metabolism (CVRM), BioPharmaceuticals R&D, AstraZeneca, Gothenburg, Sweden.
| | - Vian Azzu
- Translational Science and Experimental Medicine, Research and Early Development, Cardiovascular, Renal and Metabolism (CVRM), BioPharmaceuticals R&D, AstraZeneca, Cambridge, UK
| |
Collapse
|
81
|
Park H, Jo SH, Lee RH, Macks CP, Ku T, Park J, Lee CW, Hur JK, Sohn CH. Spatial Transcriptomics: Technical Aspects of Recent Developments and Their Applications in Neuroscience and Cancer Research. ADVANCED SCIENCE (WEINHEIM, BADEN-WURTTEMBERG, GERMANY) 2023; 10:e2206939. [PMID: 37026425 PMCID: PMC10238226 DOI: 10.1002/advs.202206939] [Citation(s) in RCA: 13] [Impact Index Per Article: 13.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/25/2022] [Revised: 03/10/2023] [Indexed: 06/04/2023]
Abstract
Spatial transcriptomics is a newly emerging field that enables high-throughput investigation of the spatial localization of transcripts and related analyses in various applications for biological systems. By transitioning from conventional biological studies to "in situ" biology, spatial transcriptomics can provide transcriptome-scale spatial information. Currently, the ability to simultaneously characterize gene expression profiles of cells and relevant cellular environment is a paradigm shift for biological studies. In this review, recent progress in spatial transcriptomics and its applications in neuroscience and cancer studies are highlighted. Technical aspects of existing technologies and future directions of new developments (as of March 2023), computational analysis of spatial transcriptome data, application notes in neuroscience and cancer studies, and discussions regarding future directions of spatial multi-omics and their expanding roles in biomedical applications are emphasized.
Collapse
Affiliation(s)
- Han‐Eol Park
- Center for NanomedicineInstitute for Basic ScienceYonsei UniversitySeoul03722Republic of Korea
- Graduate Program in Nanobiomedical EngineeringAdvanced Science InstituteYonsei UniversitySeoul03722Republic of Korea
- School of Biological SciencesSeoul National UniversitySeoul08826Republic of Korea
| | - Song Hyun Jo
- Graduate School of Medical Science and EngineeringKorea Advanced Institute of Science and Technology (KAIST)Daejeon34141Republic of Korea
| | - Rosalind H. Lee
- School of Life SciencesGwangju Institute of Science and Technology (GIST)Gwangju61005Republic of Korea
| | - Christian P. Macks
- Center for NanomedicineInstitute for Basic ScienceYonsei UniversitySeoul03722Republic of Korea
- Graduate Program in Nanobiomedical EngineeringAdvanced Science InstituteYonsei UniversitySeoul03722Republic of Korea
| | - Taeyun Ku
- Graduate School of Medical Science and EngineeringKorea Advanced Institute of Science and Technology (KAIST)Daejeon34141Republic of Korea
| | - Jihwan Park
- School of Life SciencesGwangju Institute of Science and Technology (GIST)Gwangju61005Republic of Korea
| | - Chung Whan Lee
- Department of ChemistryGachon UniversitySeongnamGyeonggi‐do13120Republic of Korea
| | - Junho K. Hur
- Department of GeneticsCollege of MedicineHanyang UniversitySeoul04763Republic of Korea
| | - Chang Ho Sohn
- Center for NanomedicineInstitute for Basic ScienceYonsei UniversitySeoul03722Republic of Korea
- Graduate Program in Nanobiomedical EngineeringAdvanced Science InstituteYonsei UniversitySeoul03722Republic of Korea
| |
Collapse
|
82
|
Chen M, Jiang J, Hou J. Single-cell technologies in multiple myeloma: new insights into disease pathogenesis and translational implications. Biomark Res 2023; 11:55. [PMID: 37259170 DOI: 10.1186/s40364-023-00502-8] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/19/2023] [Accepted: 05/12/2023] [Indexed: 06/02/2023] Open
Abstract
Multiple myeloma (MM) is a hematological malignancy characterized by clonal proliferation of plasma cells. Although therapeutic advances have been made to improve clinical outcomes and to prolong patients' survival in the past two decades, MM remains largely incurable. Single-cell sequencing (SCS) is a powerful method to dissect the cellular and molecular landscape at single-cell resolution, instead of providing averaged results. The application of single-cell technologies promises to address outstanding questions in myeloma biology and has revolutionized our understanding of the inter- and intra-tumor heterogeneity, tumor microenvironment, and mechanisms of therapeutic resistance in MM. In this review, we summarize the recently developed SCS methodologies and latest MM research progress achieved by single-cell profiling, including information regarding the cancer and immune cell landscapes, tumor heterogeneities, underlying mechanisms and biomarkers associated with therapeutic response and resistance. We also discuss future directions of applying transformative SCS approaches with contribution to clinical translation.
Collapse
Affiliation(s)
- Mengping Chen
- Department of Hematology, Ren Ji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200127, China
| | - Jinxing Jiang
- Department of Hematology, Ren Ji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200127, China
| | - Jian Hou
- Department of Hematology, Ren Ji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200127, China.
| |
Collapse
|
83
|
He JZ, Chen Y, Zeng FM, Huang QF, Zhang HF, Wang SH, Yu SX, Pang XX, Liu Y, Xu XE, Wu JY, Shen WJ, Li ZY, Li EM, Xu LY. Spatial analysis of stromal signatures identifies invasive front carcinoma-associated fibroblasts as suppressors of anti-tumor immune response in esophageal cancer. J Exp Clin Cancer Res 2023; 42:136. [PMID: 37254126 DOI: 10.1186/s13046-023-02697-y] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/12/2023] [Accepted: 05/03/2023] [Indexed: 06/01/2023] Open
Abstract
BACKGROUND Increasing evidence indicates that the tumor microenvironment (TME) is a crucial determinant of cancer progression. However, the clinical and pathobiological significance of stromal signatures in the TME, as a complex dynamic entity, is still unclear in esophageal squamous cell carcinoma (ESCC). METHODS Herein, we used single-cell transcriptome sequencing data, imaging mass cytometry (IMC) and multiplex immunofluorescence staining to characterize the stromal signatures in ESCC and evaluate their prognostic values in this aggressive disease. An automated quantitative pathology imaging system determined the locations of the lamina propria, stroma, and invasive front. Subsequently, IMC spatial analyses further uncovered spatial interaction and distribution. Additionally, bioinformatics analysis was performed to explore the TME remodeling mechanism in ESCC. To define a new molecular prognostic model, we calculated the risk score of each patient based on their TME signatures and pTNM stages. RESULTS We demonstrate that the presence of fibroblasts at the tumor invasive front was associated with the invasive depth and poor prognosis. Furthermore, the amount of α-smooth muscle actin (α-SMA)+ fibroblasts at the tumor invasive front positively correlated with the number of macrophages (MØs), but negatively correlated with that of tumor-infiltrating granzyme B+ immune cells, and CD4+ and CD8+ T cells. Spatial analyses uncovered a significant spatial interaction between α-SMA+ fibroblasts and CD163+ MØs in the TME, which resulted in spatially exclusive interactions to anti-tumor immune cells. We further validated the laminin and collagen signaling network contributions to TME remodeling. Moreover, compared with pTNM staging, a molecular prognostic model, based on expression of α-SMA+ fibroblasts at the invasive front, and CD163+ MØs, showed higher accuracy in predicting survival or recurrence in ESCC patients. Regression analysis confirmed this model is an independent predictor for survival, which also identifies a high-risk group of ESCC patients that can benefit from adjuvant therapy. CONCLUSIONS Our newly defined biomarker signature may serve as a complement for current clinical risk stratification approaches and provide potential therapeutic targets for reversing the fibroblast-mediated immunosuppressive microenvironment.
Collapse
Affiliation(s)
- Jian-Zhong He
- Guangdong Provincial Key Laboratory of Infectious Diseases and Molecular Immunopathology, Institute of Oncologic Pathology, Shantou University Medical College, Shantou, 515041, Guangdong, People's Republic of China
- Department of Pathology, The Fifth Affiliated Hospital, Sun Yat-Sen University, Zhuhai, 519000, Guangdong Province, People's Republic of China
| | - Yang Chen
- Guangdong Provincial Key Laboratory of Infectious Diseases and Molecular Immunopathology, Institute of Oncologic Pathology, Shantou University Medical College, Shantou, 515041, Guangdong, People's Republic of China
- Department of Pathology, First People's Hospital of Yunnan Province, Kunming, 650032, Yunnan Province, China
| | - Fa-Min Zeng
- Department of Pathology, The Fifth Affiliated Hospital, Sun Yat-Sen University, Zhuhai, 519000, Guangdong Province, People's Republic of China
| | - Qing-Feng Huang
- Guangdong Provincial Key Laboratory of Infectious Diseases and Molecular Immunopathology, Institute of Oncologic Pathology, Shantou University Medical College, Shantou, 515041, Guangdong, People's Republic of China
- Cancer Research Center, Shantou University Medical College, Shantou, 515041, Guangdong, People's Republic of China
| | - Hai-Feng Zhang
- Department of Pathology and Laboratory Medicine, University of British Columbia, Vancouver, British Columbia, V5Z 1L3, Canada
| | - Shao-Hong Wang
- Departments of Pathology, Shantou Central Hospital, Shantou, 515041, Guangdong, People's Republic of China
| | - Shuai-Xia Yu
- Guangdong Provincial Key Laboratory of Infectious Diseases and Molecular Immunopathology, Institute of Oncologic Pathology, Shantou University Medical College, Shantou, 515041, Guangdong, People's Republic of China
- Department of Pathology, Sichuan Academy of Medical Sciences and Sichuan Provincial People's Hospital, Chinese Academy of Sciences Sichuan Translational Medicine Research Hospital, Chengdu, 610072, China
| | - Xiao-Xiao Pang
- Guangdong Provincial Key Laboratory of Infectious Diseases and Molecular Immunopathology, Institute of Oncologic Pathology, Shantou University Medical College, Shantou, 515041, Guangdong, People's Republic of China
- Cancer Research Center, Shantou University Medical College, Shantou, 515041, Guangdong, People's Republic of China
| | - Ye Liu
- Department of Pathology, The Fifth Affiliated Hospital, Sun Yat-Sen University, Zhuhai, 519000, Guangdong Province, People's Republic of China
| | - Xiu-E Xu
- Guangdong Provincial Key Laboratory of Infectious Diseases and Molecular Immunopathology, Institute of Oncologic Pathology, Shantou University Medical College, Shantou, 515041, Guangdong, People's Republic of China
- Cancer Research Center, Shantou University Medical College, Shantou, 515041, Guangdong, People's Republic of China
| | - Jian-Yi Wu
- Guangdong Provincial Key Laboratory of Infectious Diseases and Molecular Immunopathology, Institute of Oncologic Pathology, Shantou University Medical College, Shantou, 515041, Guangdong, People's Republic of China
- Key Laboratory of Molecular Biology for High Cancer Incidence Coastal Chaoshan Area, Department of Biochemistry and Molecular Biology, Shantou University Medical College, Shantou, 515041, Guangdong, People's Republic of China
| | - Wen-Jun Shen
- Guangdong Provincial Key Laboratory of Infectious Diseases and Molecular Immunopathology, Institute of Oncologic Pathology, Shantou University Medical College, Shantou, 515041, Guangdong, People's Republic of China.
- Department of Bioinformatics, Shantou University Medical College, Shantou, 515041, Guangdong, People's Republic of China.
| | - Zhan-Yu Li
- Department of Pathology, The Fifth Affiliated Hospital, Sun Yat-Sen University, Zhuhai, 519000, Guangdong Province, People's Republic of China.
| | - En-Min Li
- Guangdong Provincial Key Laboratory of Infectious Diseases and Molecular Immunopathology, Institute of Oncologic Pathology, Shantou University Medical College, Shantou, 515041, Guangdong, People's Republic of China.
- Key Laboratory of Molecular Biology for High Cancer Incidence Coastal Chaoshan Area, Department of Biochemistry and Molecular Biology, Shantou University Medical College, Shantou, 515041, Guangdong, People's Republic of China.
| | - Li-Yan Xu
- Guangdong Provincial Key Laboratory of Infectious Diseases and Molecular Immunopathology, Institute of Oncologic Pathology, Shantou University Medical College, Shantou, 515041, Guangdong, People's Republic of China.
- Cancer Research Center, Shantou University Medical College, Shantou, 515041, Guangdong, People's Republic of China.
| |
Collapse
|
84
|
Xie S, Yan R, Zheng A, Shi M, Tang L, Li X, Liu J, Gan Y, Wang Y, Jiang D, Liu L, Wu H, Wang Z. T cell receptor and B cell receptor exhibit unique signatures in tumor and adjacent non-tumor tissues of hepatocellular carcinoma. Front Immunol 2023; 14:1161417. [PMID: 37313417 PMCID: PMC10258310 DOI: 10.3389/fimmu.2023.1161417] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/08/2023] [Accepted: 05/16/2023] [Indexed: 06/15/2023] Open
Abstract
Background The tumor microenvironment in hepatocellular carcinoma (HCC) is complicated. Tumor-infiltrating T and B cells play a pivotal role in anti-tumor immunity. T cell receptor (TCR) and B cell receptor (BCR) features may reflect the disease-associated antigen response. Methods By combining bulk TCR/BCR-sequencing, RNA-sequencing, whole exome-sequencing, and human leukocyte antigen-sequencing, we examined the immune repertoire (IR) features of tumor and adjacent non-tumor tissues obtained from 64 HCC patients. Results High IR heterogeneity with weak similarity was discovered between tumor and non-tumor tissues. Higher BCR diversity, richness, and somatic hypermutation (SHM) were found in non-tumor tissues, while TCRα and TCRβ diversity and richness were comparable or higher in tumor. Additionally, lower immune infiltration was found in tumor than non-tumor tissues; the microenvironment in tumor appeared to keep stably inhibited and changed slightly with tumor progression. Moreover, BCR SHM was stronger, whereas TCR/BCR diversity declined with HCC progression. Importantly, we found that higher IR evenness in tumor and lower TCR richness in non-tumor tissues indicated better survival in HCC patients. Collectively, the results revealed that TCR and BCR exhibited distinct features in tumor and non-tumor tissues. Conclusions We demonstrated that IR features vary between different tissues of HCC. IR features may represent a biomarker for the diagnosis and treatment of HCC patients, providing references for subsequent immunotherapy research and strategy selection.
Collapse
Affiliation(s)
- Shi Xie
- Guangdong Provincial Key Laboratory of Viral Hepatitis Research, Department of Infectious Diseases and Hepatology Unit, Nanfang Hospital, Southern Medical University, Guangzhou, China
| | - Rong Yan
- Guangdong Provincial Key Laboratory of Viral Hepatitis Research, Department of Infectious Diseases and Hepatology Unit, Nanfang Hospital, Southern Medical University, Guangzhou, China
| | - Anqi Zheng
- Guangdong Provincial Key Laboratory of Viral Hepatitis Research, Department of Infectious Diseases and Hepatology Unit, Nanfang Hospital, Southern Medical University, Guangzhou, China
| | - Mengfen Shi
- Guangdong Provincial Key Laboratory of Viral Hepatitis Research, Department of Infectious Diseases and Hepatology Unit, Nanfang Hospital, Southern Medical University, Guangzhou, China
| | | | - Xueying Li
- Guangdong Provincial Key Laboratory of Viral Hepatitis Research, Department of Infectious Diseases and Hepatology Unit, Nanfang Hospital, Southern Medical University, Guangzhou, China
| | - Jiabang Liu
- Guangdong Provincial Key Laboratory of Viral Hepatitis Research, Department of Infectious Diseases and Hepatology Unit, Nanfang Hospital, Southern Medical University, Guangzhou, China
| | - Yifan Gan
- Guangdong Provincial Key Laboratory of Viral Hepatitis Research, Department of Infectious Diseases and Hepatology Unit, Nanfang Hospital, Southern Medical University, Guangzhou, China
| | - Yu Wang
- Department of Hepatobiliary Surgery, Nanfang Hospital, Southern Medical University, Guangzhou, China
| | - Deke Jiang
- Guangdong Provincial Key Laboratory of Viral Hepatitis Research, Department of Infectious Diseases and Hepatology Unit, Nanfang Hospital, Southern Medical University, Guangzhou, China
| | - Li Liu
- Guangdong Provincial Key Laboratory of Viral Hepatitis Research, Department of Infectious Diseases and Hepatology Unit, Nanfang Hospital, Southern Medical University, Guangzhou, China
| | - Hongkai Wu
- State Key Laboratory of Respiratory Disease, National Clinical Research Center for Respiratory Disease, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou Medical University, Guangzhou, China
| | - Zhanhui Wang
- Guangdong Provincial Key Laboratory of Viral Hepatitis Research, Department of Infectious Diseases and Hepatology Unit, Nanfang Hospital, Southern Medical University, Guangzhou, China
| |
Collapse
|
85
|
Yan C, Huang H, Zheng Z, Ma X, Zhao G, Zhang T, Chen X, Cao F, Wei H, Dong J, Tang P, Jiang H, Wang M, Wang P, Pang Q, Zhang W. Spatial distribution of tumor-infiltrating T cells indicated immune response status under chemoradiotherapy plus PD-1 blockade in esophageal cancer. Front Immunol 2023; 14:1138054. [PMID: 37275884 PMCID: PMC10235618 DOI: 10.3389/fimmu.2023.1138054] [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: 01/05/2023] [Accepted: 05/04/2023] [Indexed: 06/07/2023] Open
Abstract
Background The spatial distribution of tumor-infiltrating T cells and its dynamics during chemoradiotherapy combined with PD-1 blockade is little known in esophageal squamous cell carcinoma (ESCC). Methods We applied the multiplex immunofluorescence method to identify T cells (CD4+, CD8+ T cells, and their PD-1- or PD-1+ subsets) and myeloid-derived cells (CD11c+ dendritic cells, CD68+ macrophages, and their PD-L1+ subpopulations) in paired tumor biopsies (n = 36) collected at baseline and during combination (40 Gy of radiation) from a phase Ib trial (NCT03671265) of ESCC patients treated with first-line chemoradiotherapy plus anti-PD-1 antibody camrelizumab. We used the FoundationOne CDx assay to evaluate tumor mutational burden (TMB) in baseline tumor biopsies (n = 14). We dynamically assessed the nearest distance and proximity of T-cell subsets to tumor cells under combination and estimated the association between T-cell spatial distribution and combination outcome, myeloid-derived subsets, TMB, and patient baseline characteristics. Findings We found that the tumor compartment had lower T-cell subsets than the stromal compartment but maintained a comparable level under combination. Both before and under combination, PD-1- T cells were located closer than PD-1+ T cells to tumor cells; T cells, dendritic cells, and macrophages showed the highest accumulation in the 5-10-μm distance. Higher CD4+ T cells in the tumor compartment and a shorter nearest distance of T-cell subsets at baseline predicted poor OS. Higher baseline CD4+ T cells, dendritic cells, and macrophages were associated with worse OS in less than 10-μm distance to tumor cells, but related with better OS in the farther distance. Higher on-treatment PD-1-positive-expressed CD4+ and CD8+ T cells within the 100-μm distance to tumor cells predicted longer OS. T cells, dendritic cells, and macrophages showed a positive spatial correlation. Both high TMB and smoking history were associated with a closer location of T cells to tumor cells at baseline. Conclusions We firstly illustrated the T-cell spatial distribution in ESCC. Combining chemoradiotherapy with PD-1 blockade could improve the antitumor immune microenvironment, which benefits the treatment outcome. Further understanding the precision spatiality of tumor-infiltrating T cells would provide new evidence for the tumor immune microenvironment and for the combination treatment with immunotherapy.
Collapse
Affiliation(s)
- Cihui Yan
- Department of Immunology, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Key Laboratory of Cancer Immunology and Biotherapy, Tianjin’s Clinical Research Center for Cancer, Tianjin, China
| | - Hui Huang
- Department of Radiation Oncology, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin’s Clinical Research Center for Cancer, Tianjin, China
| | - Zhunhao Zheng
- Department of Radiation Oncology, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin’s Clinical Research Center for Cancer, Tianjin, China
| | - Xiaoxue Ma
- Department of Radiation Oncology, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin’s Clinical Research Center for Cancer, Tianjin, China
| | - Gang Zhao
- Department of Pathology, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin’s Clinical Research Center for Cancer, Tianjin, China
| | - Tian Zhang
- Department of Radiation Oncology, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin’s Clinical Research Center for Cancer, Tianjin, China
| | - Xi Chen
- Department of Radiation Oncology, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin’s Clinical Research Center for Cancer, Tianjin, China
| | - Fuliang Cao
- Department of Endoscopy Diagnosis and Therapy, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin’s Clinical Research Center for Cancer, Tianjin, China
| | - Hui Wei
- Department of Radiation Oncology, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin’s Clinical Research Center for Cancer, Tianjin, China
| | - Jie Dong
- Department of Nutrition Therapy, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin’s Clinical Research Center for Cancer, Tianjin, China
| | - Peng Tang
- Department of Esophageal Cancer, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin’s Clinical Research Center for Cancer, Tianjin, China
| | - Hongjing Jiang
- Department of Esophageal Cancer, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin’s Clinical Research Center for Cancer, Tianjin, China
| | - Meng Wang
- Department of Lung Cancer, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin’s Clinical Research Center for Cancer, Tianjin, China
| | - Ping Wang
- Department of Radiation Oncology, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin’s Clinical Research Center for Cancer, Tianjin, China
| | - Qingsong Pang
- Department of Radiation Oncology, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin’s Clinical Research Center for Cancer, Tianjin, China
| | - Wencheng Zhang
- Department of Radiation Oncology, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin’s Clinical Research Center for Cancer, Tianjin, China
| |
Collapse
|
86
|
Peng W, Bai S, Zheng M, Chen W, Li Y, Yang Y, Zhao Y, Xiong S, Wang R, Cheng B. An exosome-related lncRNA signature correlates with prognosis, immune microenvironment, and therapeutic responses in hepatocellular carcinoma. Transl Oncol 2023; 31:101651. [PMID: 36933293 PMCID: PMC10031146 DOI: 10.1016/j.tranon.2023.101651] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/24/2022] [Revised: 01/04/2023] [Accepted: 03/05/2023] [Indexed: 03/18/2023] Open
Abstract
BACKGROUND Exosomes act as essential modulators of cancer development and progression in hepatocellular carcinoma. However, little is known about the potential prognostic value and underlying molecular features of exosome-related long non-coding RNAs. METHODS Genes associated with exosome biogenesis, exosome secretion, and exosome biomarkers were collected. Exosome-related lncRNA modules were identified using PCA and WGCNA analysis. A prognostic model based on data from the TCGA, GEO, NODE, and ArrayExpress was developed and validated. A comprehensive analysis of the genomic landscape, functional annotation, immune profile, and therapeutic responses underlying the prognostic signature was performed on multi-omics data, and bioinformatics methods were also applied to predict potential drugs for patients with high risk scores. qRT-PCR was used to validate the differentially expressed lncRNAs in normal and cancer cell lines. RESULTS Twenty-six hub lncRNAs were identified as highly correlated with exosomes and overall survival and were used for prognosis modeling. Three cohorts consistently showed higher scores in the high-risk group, with an AUC greater than 0.7 over time. These higher scores implied poorer overall survival, higher genomic instability, higher tumor purity, higher tumor stemness, pro-tumor pathway activation, lower anti-tumor immune cell and tertiary lymphoid structure infiltration, and poor responses to immune checkpoint blockade therapy and transarterial chemoembolization therapy. CONCLUSION Through developing an exosome-related lncRNA predictor for HCC patients, we revealed the clinical relevance of exosome-related lncRNAs and their potential as prognostic biomarkers and therapeutic response predictors.
Collapse
Affiliation(s)
- Wang Peng
- Department of Gastroenterology and Hepatology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China
| | - Shuya Bai
- Department of Gastroenterology and Hepatology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China
| | - Mengli Zheng
- Department of Gastroenterology and Hepatology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China
| | - Wei Chen
- Department of Gastroenterology and Hepatology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China
| | - Yanlin Li
- Department of Gastroenterology and Hepatology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China
| | - Yilei Yang
- Department of Gastroenterology and Hepatology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China
| | - Yuchong Zhao
- Department of Gastroenterology and Hepatology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China
| | - Si Xiong
- Department of Gastroenterology and Hepatology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China
| | - Ronghua Wang
- Department of Surgery, University of Pittsburgh School of Medicine, Pittsburgh, PA 15213, USA
| | - Bin Cheng
- Department of Gastroenterology and Hepatology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China.
| |
Collapse
|
87
|
Liang J, Zhang W, Yang J, Wu M, Dai Q, Yin H, Xiao Y, Kong L. Deep learning supported discovery of biomarkers for clinical prognosis of liver cancer. NAT MACH INTELL 2023. [DOI: 10.1038/s42256-023-00635-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/05/2023]
|
88
|
Liu Y, Xun Z, Ma K, Liang S, Li X, Zhou S, Sun L, Liu Y, Du Y, Guo X, Cui T, Zhou H, Wang J, Yin D, Song R, Zhang S, Cai W, Meng F, Guo H, Zhang B, Yang D, Bao R, Hu Q, Wang J, Ye Y, Liu L. Identification of a tumour immune barrier in the HCC microenvironment that determines the efficacy of immunotherapy. J Hepatol 2023; 78:770-782. [PMID: 36708811 DOI: 10.1016/j.jhep.2023.01.011] [Citation(s) in RCA: 125] [Impact Index Per Article: 125.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/22/2022] [Revised: 12/09/2022] [Accepted: 01/16/2023] [Indexed: 01/28/2023]
Abstract
BACKGROUND & AIMS The tumour microenvironment (TME) is a crucial mediator of cancer progression and therapeutic outcome. The TME subtype correlates with patient response to immunotherapy in multiple cancers. Most previous studies have focused on the role of different cellular components in the TME associated with immunotherapy efficacy. However, the specific structure of the TME and its role in immunotherapy efficacy remain largely unknown. METHODS We combined spatial transcriptomics with single-cell RNA-sequencing and multiplexed immunofluorescence to identify the specific spatial structures in the TME that determine the efficacy of immunotherapy in patients with hepatocellular carcinoma (HCC) receiving anti-PD-1 treatment. RESULTS We identified a tumour immune barrier (TIB) structure, a spatial niche composed of SPP1+ macrophages and cancer-associated fibroblasts (CAFs) located near the tumour boundary, which is associated with the efficacy of immune checkpoint blockade. Furthermore, we dissected ligand‒receptor networks among malignant cells, SPP1+ macrophages, and CAFs; that is, the hypoxic microenvironment promotes SPP1 expression, and SPP1+ macrophages interact with CAFs to stimulate extracellular matrix remodelling and promote TIB structure formation, thereby limiting immune infiltration in the tumour core. Preclinically, the blockade of SPP1 or macrophage-specific deletion of Spp1 in mice led to enhanced efficacy of anti-PD-1 treatment in mouse liver cancer, accompanied by reduced CAF infiltration and increased cytotoxic T-cell infiltration. CONCLUSIONS We identified that the TIB structure formed by the interaction of SPP1+ macrophages and CAFs is related to immunotherapy efficacy. Therefore, disruption of the TIB structure by blocking SPP1 may be considered a relevant therapeutic approach to enhance the therapeutic effect of immune checkpoint blockade in HCC. IMPACT AND IMPLICATIONS Only a limited number of patients with hepatocellular carcinoma (HCC) benefit from tumour immunotherapy, which significantly hinders its application. Herein, we used multiomics to identify the spatial structure of the tumour immune barrier (TIB), which is formed by the interaction of SPP1+ macrophages and cancer-associated fibroblasts in the HCC microenvironment. This structure constrains immunotherapy efficacy by limiting immune cell infiltration into malignant regions. Preclinically, we revealed that blocking SPP1 or macrophage-specific deletion of Spp1 in mice could destroy the TIB structure and sensitize HCC cells to immunotherapy. These results provide the first key steps towards finding more effective therapies for HCC and have implications for physicians, scientists, and drug developers in the field of HCC.
Collapse
Affiliation(s)
- Yao Liu
- Department of Hepatobiliary Surgery, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Anhui Province Key Laboratory of Hepatopancreatobiliary Surgery, Anhui Provincial Clinical Research Center for Hepatobiliary Diseases, Hefei 230001, China
| | - Zhenzhen Xun
- Shanghai Institute of Immunology, State Key Laboratory of Oncogenes and Related Genes, Department of Immunology and Microbiology, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China
| | - Kun Ma
- Department of Hepatobiliary Surgery, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Anhui Province Key Laboratory of Hepatopancreatobiliary Surgery, Anhui Provincial Clinical Research Center for Hepatobiliary Diseases, Hefei 230001, China
| | - Shuhang Liang
- Department of Gastrointestinal Surgery, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Anhui Province Key Laboratory of Hepatopancreatobiliary Surgery, Hefei 230001, China
| | - Xianying Li
- Department of Hepatobiliary Surgery, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Anhui Province Key Laboratory of Hepatopancreatobiliary Surgery, Anhui Provincial Clinical Research Center for Hepatobiliary Diseases, Hefei 230001, China
| | - Shuo Zhou
- Department of Hepatobiliary Surgery, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Anhui Province Key Laboratory of Hepatopancreatobiliary Surgery, Anhui Provincial Clinical Research Center for Hepatobiliary Diseases, Hefei 230001, China
| | - Linmao Sun
- Department of Hepatobiliary Surgery, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Anhui Province Key Laboratory of Hepatopancreatobiliary Surgery, Anhui Provincial Clinical Research Center for Hepatobiliary Diseases, Hefei 230001, China
| | - Yufeng Liu
- Department of Hepatobiliary Surgery, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Anhui Province Key Laboratory of Hepatopancreatobiliary Surgery, Anhui Provincial Clinical Research Center for Hepatobiliary Diseases, Hefei 230001, China
| | - Yanhua Du
- Shanghai Institute of Immunology, State Key Laboratory of Oncogenes and Related Genes, Department of Immunology and Microbiology, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China
| | - Xinyu Guo
- Department of Hepatobiliary Surgery, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Anhui Province Key Laboratory of Hepatopancreatobiliary Surgery, Anhui Provincial Clinical Research Center for Hepatobiliary Diseases, Hefei 230001, China
| | - Tianming Cui
- Department of Hepatobiliary Surgery, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Anhui Province Key Laboratory of Hepatopancreatobiliary Surgery, Anhui Provincial Clinical Research Center for Hepatobiliary Diseases, Hefei 230001, China
| | - Huanran Zhou
- Department of Endocrinology, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei 230001, China
| | - Jizhou Wang
- Department of Hepatobiliary Surgery, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Anhui Province Key Laboratory of Hepatopancreatobiliary Surgery, Anhui Provincial Clinical Research Center for Hepatobiliary Diseases, Hefei 230001, China
| | - Dalong Yin
- Department of Hepatobiliary Surgery, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Anhui Province Key Laboratory of Hepatopancreatobiliary Surgery, Anhui Provincial Clinical Research Center for Hepatobiliary Diseases, Hefei 230001, China
| | - Ruipeng Song
- Department of Hepatobiliary Surgery, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Anhui Province Key Laboratory of Hepatopancreatobiliary Surgery, Anhui Provincial Clinical Research Center for Hepatobiliary Diseases, Hefei 230001, China
| | - Shugeng Zhang
- Department of Hepatobiliary Surgery, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Anhui Province Key Laboratory of Hepatopancreatobiliary Surgery, Anhui Provincial Clinical Research Center for Hepatobiliary Diseases, Hefei 230001, China
| | - Wei Cai
- Department of Hepatobiliary Surgery, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Anhui Province Key Laboratory of Hepatopancreatobiliary Surgery, Anhui Provincial Clinical Research Center for Hepatobiliary Diseases, Hefei 230001, China
| | - Fanzheng Meng
- Department of Hepatobiliary Surgery, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Anhui Province Key Laboratory of Hepatopancreatobiliary Surgery, Anhui Provincial Clinical Research Center for Hepatobiliary Diseases, Hefei 230001, China
| | - Hongrui Guo
- Department of Hepatobiliary Surgery, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Anhui Province Key Laboratory of Hepatopancreatobiliary Surgery, Anhui Provincial Clinical Research Center for Hepatobiliary Diseases, Hefei 230001, China
| | - Bo Zhang
- Department of Gastrointestinal Surgery, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Anhui Province Key Laboratory of Hepatopancreatobiliary Surgery, Hefei 230001, China
| | - Di Yang
- Shanghai Institute of Immunology, State Key Laboratory of Oncogenes and Related Genes, Department of Immunology and Microbiology, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China
| | - Rujuan Bao
- Shanghai Institute of Immunology, State Key Laboratory of Oncogenes and Related Genes, Department of Immunology and Microbiology, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China
| | - Qingsong Hu
- Department of Hepatobiliary Surgery, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Anhui Province Key Laboratory of Hepatopancreatobiliary Surgery, Anhui Provincial Clinical Research Center for Hepatobiliary Diseases, Hefei 230001, China.
| | - Jiabei Wang
- Department of Hepatobiliary Surgery, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Anhui Province Key Laboratory of Hepatopancreatobiliary Surgery, Anhui Provincial Clinical Research Center for Hepatobiliary Diseases, Hefei 230001, China.
| | - Youqiong Ye
- Shanghai Institute of Immunology, State Key Laboratory of Oncogenes and Related Genes, Department of Immunology and Microbiology, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China.
| | - Lianxin Liu
- Department of Hepatobiliary Surgery, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Anhui Province Key Laboratory of Hepatopancreatobiliary Surgery, Anhui Provincial Clinical Research Center for Hepatobiliary Diseases, Hefei 230001, China.
| |
Collapse
|
89
|
Zhou H, Tan L, Liu B, Guan XY. Cancer stem cells: Recent insights and therapies. Biochem Pharmacol 2023; 209:115441. [PMID: 36720355 DOI: 10.1016/j.bcp.2023.115441] [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: 10/30/2022] [Revised: 12/20/2022] [Accepted: 01/25/2023] [Indexed: 01/31/2023]
Abstract
Tumors are intricate ecosystems containing malignant components that generate adaptive and evolutionarily driven abnormal tissues. Through self-renewal and differentiation, cancers are reconstructed by a dynamic subset of stem-like cells that enforce tumor heterogeneity and remodel the tumor microenvironment (TME). Through recent technology advances, we are now better equipped to investigate the fundamental role of cancer stem cells (CSCs) in cancer biology. In this review, we discuss the latest insights into characteristics, markers and mechanism of CSCs and describe the crosstalk between CSCs and other cells in TME. Additionally, we explore the performance of single-cell sequencing and spatial transcriptome analysis in CSCs studies and summarize the therapeutic strategies to eliminate CSCs, which could broaden the understanding of CSCs and exploit for therapeutic benefit.
Collapse
Affiliation(s)
- Hongyu Zhou
- Department of Clinical Oncology, The University of Hong Kong, Hong Kong, China
| | - Licheng Tan
- Department of Clinical Oncology, The University of Hong Kong, Hong Kong, China
| | - Beilei Liu
- Department of Clinical Oncology, The University of Hong Kong, Hong Kong, China; Department of Clinical Oncology, The University of Hong Kong-Shenzhen Hospital, Shenzhen, Guangdong, China.
| | - Xin-Yuan Guan
- Department of Clinical Oncology, The University of Hong Kong, Hong Kong, China; Department of Clinical Oncology, The University of Hong Kong-Shenzhen Hospital, Shenzhen, Guangdong, China; State Key Laboratory for Liver Research, The University of Hong Kong, Hong Kong, China; MOE Key Laboratory of Tumor Molecular Biology, Jinan University, Guangzhou, Guangdong, China; Advanced Nuclear Energy and Nuclear Technology Research Center, Advanced Energy Science and Technology Guangdong Laboratory, Huizhou, Guangdong, China.
| |
Collapse
|
90
|
Akce M, El-Rayes BF, Wajapeyee N. Combinatorial targeting of immune checkpoints and epigenetic regulators for hepatocellular carcinoma therapy. Oncogene 2023; 42:1051-1057. [PMID: 36854723 DOI: 10.1038/s41388-023-02646-1] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/16/2023] [Revised: 02/16/2023] [Accepted: 02/21/2023] [Indexed: 03/02/2023]
Abstract
Hepatocellular carcinoma (HCC) is the second leading cause of cancer-related mortality worldwide. The five-year survival rate of patients with unresectable HCC is about 12%. The liver tumor microenvironment (TME) is immune tolerant and heavily infiltrated with immunosuppressive cells. Immune checkpoint inhibitors (ICIs), in some cases, can reverse tumor cell immune evasion and enhance antitumor immunity. Rapidly evolving ICIs have expanded systemic treatment options in advanced HCC; however, single-agent ICIs achieve a limited 15-20% objective response rate in advanced HCC. Therefore, other combinatorial approaches that amplify the efficacy of ICIs or suppress other tumor-promoting pathways may enhance clinical outcomes. Epigenetic alterations (e.g., changes in chromatin states and non-genetic DNA modifications) have been shown to drive HCC tumor growth and progression as well as their response to ICIs. Recent studies have combined ICIs and epigenetic inhibitors in preclinical and clinical settings to contain several cancers, including HCC. In this review, we outline current ICI treatments for HCC, the mechanism behind their successes and failures, and how ICIs can be combined with distinct epigenetic inhibitors to increase the durability of ICIs and potentially treat "immune-cold" HCC.
Collapse
Affiliation(s)
- Mehmet Akce
- Division of Hematology and Oncology, Department of Medicine, O'Neal Comprehensive Cancer Center of University of Alabama at Birmingham, Heersink School of Medicine, Birmingham, AL, 35233, USA.
| | - Bassel F El-Rayes
- Division of Hematology and Oncology, Department of Medicine, O'Neal Comprehensive Cancer Center of University of Alabama at Birmingham, Heersink School of Medicine, Birmingham, AL, 35233, USA
| | - Narendra Wajapeyee
- Department of Biochemistry and Molecular Genetics, O'Neal Comprehensive Cancer Center of University of Alabama at Birmingham, Heersink School of Medicine, Birmingham, AL, 35233, USA.
| |
Collapse
|
91
|
Fang Y, Peng Z, Wang Y, Yuan X, Gao K, Fan R, Liu R, Liu Y, Zhang H, Xie Z, Jiang W. Improvements and challenges of tissue preparation for spatial transcriptome analysis of skull base tumors. Heliyon 2023; 9:e14133. [PMID: 36938455 PMCID: PMC10018477 DOI: 10.1016/j.heliyon.2023.e14133] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/13/2022] [Revised: 02/21/2023] [Accepted: 02/22/2023] [Indexed: 03/09/2023] Open
Abstract
Background Spatial transcriptome (ST) provides molecular profiles of tumor cells at the spatial level, which brings new progress to the research of tumors and the tumor microenvironment. This study summarizes the experiences and lessons learned in the spatial section preparation of two different pathological types of nose and skull base tumors at our institution, with the aim of offering guidelines to researchers to avoid wasting precious samples and provide a basis for the application of ST in clinical practice. Methods Frozen tissue blocks from patients with squamous cell carcinoma and adenocarcinoma of the nose and skull base diagnosed at our institution were prepared. The effects of different procedures and pathological tissue types on slide quality were explored and evaluated using RNA integrity number (RIN) and HE scores as criteria. The effects of different RIN values on ST sequencing data were explored. Results A total of 43 samples were obtained from 26 patients, including 22 with squamous carcinomas and 21 with adenocarcinomas. Thirteen samples with satisfactory RNA quality control and good histological morphology were sequenced for ST. Sample isolation time <15 min and abandonment of snap-frozen isopentane significantly improved RNA quality (p = 0.004, p < 0.0001) and histomorphological integrity (p = 0.02, p = 0.02). Selection of a suitable tissue RNA extraction kit was critical for RNA quality (p < 0.0001). No difference between 6 ≤ RIN <7 and RIN >7 in ST sequencing results was found, indicating that RIN ≥6 can be used as a criterion for qualified RNA quality control. Therefore, fresh tissues washed as soon as possible with cold PBS and then dried using OCT for snap freezing are currently the best method for preparing spatial sections of nose and skull base tumor tissues of different pathological types. Conclusion This study is the first to investigate the feasibility of applying ST to different pathological types of nose and skull base tumors and to demonstrate the widespread application of ST in tumors. Rational optimization of spatial slide preparation procedures and exploration of individualized pre-sequencing protocols are used as the first stage to ensure the quality of spatial sequencing and lay the foundation for subsequent spatial analysis.
Collapse
Affiliation(s)
- Yan Fang
- Department of Otolaryngology Head and Neck Surgery, Xiangya Hospital, Central South University, Changsha, Hunan, 410008, China
- Otolaryngology Major Disease Research Key Laboratory of Hunan Province, Changsha, Hunan, 410008, China
- National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, Hunan, 410008, China
- Anatomy Laboratory of Division of Nose and Cranial Base, Clinical Anatomy Center of Xiangya Hospital, Central South University, Changsha, Hunan, 410008, China
| | - Zhouying Peng
- Department of Otolaryngology Head and Neck Surgery, Xiangya Hospital, Central South University, Changsha, Hunan, 410008, China
- Otolaryngology Major Disease Research Key Laboratory of Hunan Province, Changsha, Hunan, 410008, China
- National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, Hunan, 410008, China
- Anatomy Laboratory of Division of Nose and Cranial Base, Clinical Anatomy Center of Xiangya Hospital, Central South University, Changsha, Hunan, 410008, China
| | - Yumin Wang
- Department of Otolaryngology Head and Neck Surgery, Xiangya Hospital, Central South University, Changsha, Hunan, 410008, China
- Otolaryngology Major Disease Research Key Laboratory of Hunan Province, Changsha, Hunan, 410008, China
- National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, Hunan, 410008, China
- Anatomy Laboratory of Division of Nose and Cranial Base, Clinical Anatomy Center of Xiangya Hospital, Central South University, Changsha, Hunan, 410008, China
| | - Xiaotian Yuan
- Department of Otolaryngology Head and Neck Surgery, Xiangya Hospital, Central South University, Changsha, Hunan, 410008, China
- Otolaryngology Major Disease Research Key Laboratory of Hunan Province, Changsha, Hunan, 410008, China
- National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, Hunan, 410008, China
| | - Kelei Gao
- Department of Otolaryngology Head and Neck Surgery, Xiangya Hospital, Central South University, Changsha, Hunan, 410008, China
- Otolaryngology Major Disease Research Key Laboratory of Hunan Province, Changsha, Hunan, 410008, China
- Anatomy Laboratory of Division of Nose and Cranial Base, Clinical Anatomy Center of Xiangya Hospital, Central South University, Changsha, Hunan, 410008, China
| | - Ruohao Fan
- Department of Otolaryngology Head and Neck Surgery, Xiangya Hospital, Central South University, Changsha, Hunan, 410008, China
- Otolaryngology Major Disease Research Key Laboratory of Hunan Province, Changsha, Hunan, 410008, China
- National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, Hunan, 410008, China
- Anatomy Laboratory of Division of Nose and Cranial Base, Clinical Anatomy Center of Xiangya Hospital, Central South University, Changsha, Hunan, 410008, China
| | - Ruijie Liu
- National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, Hunan, 410008, China
- Department of Pathology, Xiangya Hospital, Central South University, Changsha, Hunan, 410008, China
| | - Yalan Liu
- Department of Otolaryngology Head and Neck Surgery, Xiangya Hospital, Central South University, Changsha, Hunan, 410008, China
- Otolaryngology Major Disease Research Key Laboratory of Hunan Province, Changsha, Hunan, 410008, China
- National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, Hunan, 410008, China
| | - Hua Zhang
- Department of Otolaryngology Head and Neck Surgery, Xiangya Hospital, Central South University, Changsha, Hunan, 410008, China
- Otolaryngology Major Disease Research Key Laboratory of Hunan Province, Changsha, Hunan, 410008, China
- National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, Hunan, 410008, China
- Anatomy Laboratory of Division of Nose and Cranial Base, Clinical Anatomy Center of Xiangya Hospital, Central South University, Changsha, Hunan, 410008, China
| | - Zhihai Xie
- Department of Otolaryngology Head and Neck Surgery, Xiangya Hospital, Central South University, Changsha, Hunan, 410008, China
- Otolaryngology Major Disease Research Key Laboratory of Hunan Province, Changsha, Hunan, 410008, China
- National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, Hunan, 410008, China
- Anatomy Laboratory of Division of Nose and Cranial Base, Clinical Anatomy Center of Xiangya Hospital, Central South University, Changsha, Hunan, 410008, China
| | - Weihong Jiang
- Department of Otolaryngology Head and Neck Surgery, Xiangya Hospital, Central South University, Changsha, Hunan, 410008, China
- Otolaryngology Major Disease Research Key Laboratory of Hunan Province, Changsha, Hunan, 410008, China
- National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, Hunan, 410008, China
- Anatomy Laboratory of Division of Nose and Cranial Base, Clinical Anatomy Center of Xiangya Hospital, Central South University, Changsha, Hunan, 410008, China
- Corresponding author. Department of Otolaryngology Head and Neck Surgery, Xiangya Hospital, Central South University, Changsha, Hunan, 410008, China.
| |
Collapse
|
92
|
Yuan Z, Pan W, Zhao X, Zhao F, Xu Z, Li X, Zhao Y, Zhang MQ, Yao J. SODB facilitates comprehensive exploration of spatial omics data. Nat Methods 2023; 20:387-399. [PMID: 36797409 DOI: 10.1038/s41592-023-01773-7] [Citation(s) in RCA: 20] [Impact Index Per Article: 20.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/10/2022] [Accepted: 01/06/2023] [Indexed: 02/18/2023]
Abstract
Spatial omics technologies generate wealthy but highly complex datasets. Here we present Spatial Omics DataBase (SODB), a web-based platform providing both rich data resources and a suite of interactive data analytical modules. SODB currently maintains >2,400 experiments from >25 spatial omics technologies, which are freely accessible as a unified data format compatible with various computational packages. SODB also provides multiple interactive data analytical modules, especially a unique module, Spatial Omics View (SOView). We conduct comprehensive statistical analyses and illustrate the utility of both basic and advanced analytical modules using multiple spatial omics datasets. We demonstrate SOView utility with brain spatial transcriptomics data and recover known anatomical structures. We further delineate functional tissue domains with associated marker genes that were obscured when analyzed using previous methods. We finally show how SODB may efficiently facilitate computational method development. The SODB website is https://gene.ai.tencent.com/SpatialOmics/ . The command-line package is available at https://pysodb.readthedocs.io/en/latest/ .
Collapse
Affiliation(s)
- Zhiyuan Yuan
- Institute of Science and Technology for Brain-Inspired Intelligence; MOE Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence; MOE Frontiers Center for Brain Science, Fudan University, Shanghai, China.
- Tencent AI Lab, Shenzhen, China.
| | - Wentao Pan
- Tencent AI Lab, Shenzhen, China
- Shenzhen International Graduate School, Tsinghua University, Shenzen, China
| | | | - Fangyuan Zhao
- Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China
- University of Chinese Academy of Sciences, Beijing, China
| | | | - Xiu Li
- Shenzhen International Graduate School, Tsinghua University, Shenzen, China
| | - Yi Zhao
- Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China
- University of Chinese Academy of Sciences, Beijing, China
| | - Michael Q Zhang
- Department of Biological Sciences, Center for Systems Biology, The University of Texas, Richardson, TX, USA.
| | | |
Collapse
|
93
|
Spatial transcriptomics reveals niche-specific enrichment and vulnerabilities of radial glial stem-like cells in malignant gliomas. Nat Commun 2023; 14:1028. [PMID: 36823172 PMCID: PMC9950149 DOI: 10.1038/s41467-023-36707-6] [Citation(s) in RCA: 34] [Impact Index Per Article: 34.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/18/2022] [Accepted: 02/14/2023] [Indexed: 02/25/2023] Open
Abstract
Diffuse midline glioma-H3K27M mutant (DMG) and glioblastoma (GBM) are the most lethal brain tumors that primarily occur in pediatric and adult patients, respectively. Both tumors exhibit significant heterogeneity, shaped by distinct genetic/epigenetic drivers, transcriptional programs including RNA splicing, and microenvironmental cues in glioma niches. However, the spatial organization of cellular states and niche-specific regulatory programs remain to be investigated. Here, we perform a spatial profiling of DMG and GBM combining short- and long-read spatial transcriptomics, and single-cell transcriptomic datasets. We identify clinically relevant transcriptional programs, RNA isoform diversity, and multi-cellular ecosystems across different glioma niches. We find that while the tumor core enriches for oligodendrocyte precursor-like cells, radial glial stem-like (RG-like) cells are enriched in the neuron-rich invasive niche in both DMG and GBM. Further, we identify niche-specific regulatory programs for RG-like cells, and functionally confirm that FAM20C mediates invasive growth of RG-like cells in a neuron-rich microenvironment in a human neural stem cell derived orthotopic DMG model. Together, our results provide a blueprint for understanding the spatial architecture and niche-specific vulnerabilities of DMG and GBM.
Collapse
|
94
|
Xun Z, Ding X, Zhang Y, Zhang B, Lai S, Zou D, Zheng J, Chen G, Su B, Han L, Ye Y. Reconstruction of the tumor spatial microenvironment along the malignant-boundary-nonmalignant axis. Nat Commun 2023; 14:933. [PMID: 36806082 PMCID: PMC9941488 DOI: 10.1038/s41467-023-36560-7] [Citation(s) in RCA: 18] [Impact Index Per Article: 18.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/16/2022] [Accepted: 02/06/2023] [Indexed: 02/22/2023] Open
Abstract
Although advances in spatial transcriptomics (ST) enlarge to unveil spatial landscape of tissues, it remains challenging to delineate pathology-relevant and cellular localizations, and interactions exclusive to a spatial niche (e.g., tumor boundary). Here, we develop Cottrazm, integrating ST with hematoxylin and eosin histological image, and single-cell transcriptomics to delineate the tumor boundary connecting malignant and non-malignant cell spots in tumor tissues, deconvolute cell-type composition at spatial location, and reconstruct cell type-specific gene expression profiles at sub-spot level. We validate the performance of Cottrazm along the malignant-boundary-nonmalignant spatial axis. We identify specific macrophage and fibroblast subtypes localized around tumor boundary that interacted with tumor cells to generate a structural boundary, which limits T cell infiltration and promotes immune exclusion in tumor microenvironment. In this work, Cottrazm provides an integrated tool framework to dissect the tumor spatial microenvironment and facilitates the discovery of functional biological insights, thereby identifying therapeutic targets in oncologic ST datasets.
Collapse
Affiliation(s)
- Zhenzhen Xun
- Center for Immune-Related Diseases at Shanghai Institute of Immunology, Department of Gastroenterology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- Shanghai Institute of Immunology, State Key Laboratory of Oncogenes and Related Genes, Department of Immunology and Microbiology, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China
| | - Xinyu Ding
- Center for Immune-Related Diseases at Shanghai Institute of Immunology, Department of Gastroenterology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- Shanghai Institute of Immunology, State Key Laboratory of Oncogenes and Related Genes, Department of Immunology and Microbiology, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China
| | - Yao Zhang
- Department of Gastroenterology, Ruijin Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China
| | - Benyan Zhang
- Department of Pathology, Ruijin Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China
| | - Shujing Lai
- Shanghai Institute of Immunology, State Key Laboratory of Oncogenes and Related Genes, Department of Immunology and Microbiology, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China
| | - Duowu Zou
- Department of Gastroenterology, Ruijin Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China
| | - Junke Zheng
- Hongqiao International Institute of Medicine, Shanghai Tongren Hospital, Key Laboratory of Cell Differentiation and Apoptosis of Chinese Ministry of Education, Faculty of Basic Medicine, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China
| | - Guoqiang Chen
- State Key Laboratory of Oncogenes and Related Genes, and Research Unit of Stress and Cancer, Chinese Academy of Medical Sciences, Shanghai Cancer Institute, Renji hospital, Shanghai Jiao Tong University School of Medicine (SJTU-SM), Shanghai, 200127, China
| | - Bing Su
- Center for Immune-Related Diseases at Shanghai Institute of Immunology, Department of Gastroenterology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- Shanghai Institute of Immunology, State Key Laboratory of Oncogenes and Related Genes, Department of Immunology and Microbiology, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China
| | - Leng Han
- Center for Epigenetics and Disease Prevention, Institute of Biosciences and Technology, Texas A&M University, Houston, TX, 77030, USA.
| | - Youqiong Ye
- Center for Immune-Related Diseases at Shanghai Institute of Immunology, Department of Gastroenterology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
- Shanghai Institute of Immunology, State Key Laboratory of Oncogenes and Related Genes, Department of Immunology and Microbiology, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China.
| |
Collapse
|
95
|
Lowe MM, Cohen JN, Moss MI, Clancy S, Adler J, Yates A, Naik HB, Pauli M, Taylor I, McKay A, Harris H, Kim E, Hansen SL, Rosenblum MD, Moreau JM. Tertiary Lymphoid Structures Sustain Cutaneous B cell Activity in Hidradenitis Suppurativa. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.02.14.528504. [PMID: 36824918 PMCID: PMC9949072 DOI: 10.1101/2023.02.14.528504] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/17/2023]
Abstract
Background Hidradenitis suppurativa (HS) skin lesions are highly inflammatory and characterized by a large immune infiltrate. While B cells and plasma cells comprise a major component of this immune milieu the biology and contribution of these cells in HS pathogenesis is unclear. Objective We aimed to investigate the dynamics and microenvironmental interactions of B cells within cutaneous HS lesions. Methods We combined histological analysis, single-cell RNA-sequencing (scRNAseq), and spatial transcriptomic profiling of HS lesions to define the tissue microenvironment relative to B cell activity within this disease. Results Our findings identify tertiary lymphoid structures (TLS) within HS lesions and describe organized interactions between T cells, B cells, antigen presenting cells and skin stroma. We find evidence that B cells within HS TLS actively undergo maturation, including participation in germinal center reactions and class switch recombination. Moreover, skin stroma and accumulating T cells are primed to support the formation of TLS and facilitate B cell recruitment during HS. Conclusion Our data definitively demonstrate the presence of TLS in lesional HS skin and point to ongoing cutaneous B cell maturation through class switch recombination and affinity maturation during disease progression in this inflamed non-lymphoid tissue.
Collapse
|
96
|
He J, Deng C, Krall L, Shan Z. ScRNA-seq and ST-seq in liver research. CELL REGENERATION (LONDON, ENGLAND) 2023; 12:11. [PMID: 36732412 PMCID: PMC9895469 DOI: 10.1186/s13619-022-00152-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 05/05/2022] [Accepted: 11/11/2022] [Indexed: 02/04/2023]
Abstract
Spatial transcriptomics, which combine gene expression data with spatial information, has quickly expanded in recent years. With application of this method in liver research, our knowledge about liver development, regeneration, and diseases have been greatly improved. While this field is moving forward, a variety of problems still need to be addressed, including sensitivity, limited capacity to obtain exact single-cell information, data processing methods, as well as others. Methods like single-cell RNA sequencing (scRNA-seq) are usually used together with spatial transcriptome sequencing (ST-seq) to clarify cell-specific gene expression. In this review, we explore how advances of scRNA-seq and ST-seq, especially ST-seq, will pave the way to new opportunities to investigate fundamental questions in liver research. Finally, we will discuss the strengths, limitations, and future perspectives of ST-seq in liver research.
Collapse
Affiliation(s)
- Jia He
- grid.440773.30000 0000 9342 2456State Key Laboratory of Conservation and Utilization of Bio-resources in Yunnan and Center for Life Sciences, School of Life Sciences, Yunnan University, Kunming, 650091 China
| | - Chengxiang Deng
- grid.440773.30000 0000 9342 2456State Key Laboratory of Conservation and Utilization of Bio-resources in Yunnan and Center for Life Sciences, School of Life Sciences, Yunnan University, Kunming, 650091 China
| | - Leonard Krall
- grid.440773.30000 0000 9342 2456State Key Laboratory of Conservation and Utilization of Bio-resources in Yunnan and Center for Life Sciences, School of Life Sciences, Yunnan University, Kunming, 650091 China
| | - Zhao Shan
- State Key Laboratory of Conservation and Utilization of Bio-resources in Yunnan and Center for Life Sciences, School of Life Sciences, Yunnan University, Kunming, 650091, China.
| |
Collapse
|
97
|
Suoangbaji T, Zhang VX, Ng IOL, Ho DWH. Single-Cell Analysis of Primary Liver Cancer in Mouse Models. Cells 2023; 12:cells12030477. [PMID: 36766817 PMCID: PMC9914042 DOI: 10.3390/cells12030477] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/05/2023] [Revised: 01/17/2023] [Accepted: 01/29/2023] [Indexed: 02/05/2023] Open
Abstract
Primary liver cancer (PLC), consisting mainly of hepatocellular carcinoma and intrahepatic cholangiocarcinoma, is one of the major causes of cancer-related mortality worldwide. The curative therapy for PLC is surgical resection and liver transplantation, but most PLCs are inoperable at diagnosis. Even after surgery, there is a high rate of tumor recurrence. There is an unmet clinical need to discover more effective treatment options for advanced PLCs. Pre-clinical mouse models in PLC research have played a critical role in identifying key oncogenic drivers and signaling pathways in hepatocarcinogenesis. Furthermore, recent advances in single-cell RNA sequencing (scRNA-seq) have provided an unprecedented degree of resolution in such characterization. In this review, we will summarize the recent studies that utilized pre-clinical mouse models with the combination of scRNA-seq to provide an understanding of different aspects of PLC. We will focus particularly on the potentially actionable targets regarding the cellular and molecular components. We anticipate that the findings in mouse models could complement those in patients. With more defined etiological background, mouse models may provide valuable insights.
Collapse
Affiliation(s)
| | | | - Irene Oi-Lin Ng
- Correspondence: (I.O.-L.N.); (D.W.-H.H.); Fax: +852-28872-5197 (I.O.-L.N.); +852-2819-5375 (D.W.-H.H.)
| | - Daniel Wai-Hung Ho
- Correspondence: (I.O.-L.N.); (D.W.-H.H.); Fax: +852-28872-5197 (I.O.-L.N.); +852-2819-5375 (D.W.-H.H.)
| |
Collapse
|
98
|
Liu HT, Chen SY, Peng LL, Zhong L, Zhou L, Liao SQ, Chen ZJ, Wang QL, He S, Zhou ZH. Spatially resolved transcriptomics revealed local invasion-related genes in colorectal cancer. Front Oncol 2023; 13:1089090. [PMID: 36816947 PMCID: PMC9928961 DOI: 10.3389/fonc.2023.1089090] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/23/2022] [Accepted: 01/16/2023] [Indexed: 02/04/2023] Open
Abstract
Objective Local invasion is the first step of metastasis, the main cause of colorectal cancer (CRC)-related death. Recent studies have revealed extensive intertumoral and intratumoral heterogeneity. Here, we focused on revealing local invasion-related genes in CRC. Methods We used spatial transcriptomic techniques to study the process of local invasion in four CRC tissues. First, we compared the pre-cancerous, cancer center, and invasive margin in one section (S115) and used pseudo-time analysis to reveal the differentiation trajectories from cancer center to invasive margin. Next, we performed immunohistochemical staining for RPL5, STC1, AKR1B1, CD47, and HLA-A on CRC samples. Moreover, we knocked down AKR1B1 in CRC cell lines and performed CCK-8, wound healing, and transwell assays to assess cell proliferation, migration, and invasion. Results We demonstrated that 13 genes were overexpressed in invasive clusters, among which the expression of CSTB and TM4SF1 was correlated with poor PFS in CRC patients. The ribosome pathway was increased, while the antigen processing and presentation pathway was decreased along CRC progression. RPL5 was upregulated, while HLA-A was downregulated along cancer invasion in CRC samples. Pseudo-time analysis revealed that STC1, AKR1B1, SIRPA, C4orf3, EDNRA, CES1, PRRX1, EMP1, PPIB, PLTP, SULF2, and EGFL6 were unpregulated along the trajectories. Immunohistochemic3al staining showed the expression of STC1, AKR1B1, and CD47 was increased along cancer invasion in CRC samples. Knockdown of AKR1B1 inhibited CRC cells' proliferation, migration, and invasion. Conclusions We revealed the spatial heterogeneity within CRC tissues and uncovered some novel genes that were associated with CRC invasion.
Collapse
Affiliation(s)
- Hong-Tao Liu
- Department of Gastroenterology, the Second Affiliated Hospital of Chongqing Medical University, Chongqing, China
| | - Si-Yuan Chen
- Department of Gastroenterology, the Second Affiliated Hospital of Chongqing Medical University, Chongqing, China,Centre for Lipid Research & Key Laboratory of Molecular Biology for Infectious Diseases (Ministry of Education), Institute for Viral Hepatitis, Department of Infectious Diseases, The Second Affiliated Hospital, Chongqing Medical University, Chongqing, China
| | - Ling-Long Peng
- Department of Gastrointestinal Surgery, the Second Affiliated Hospital of Chongqing Medical University, Chongqing, China
| | - Li Zhong
- Department of Gastroenterology, the Second Affiliated Hospital of Chongqing Medical University, Chongqing, China
| | - Li Zhou
- Department of Gastroenterology, the Second Affiliated Hospital of Chongqing Medical University, Chongqing, China
| | - Si-Qi Liao
- Department of Gastroenterology, the Second Affiliated Hospital of Chongqing Medical University, Chongqing, China
| | - Zhi-Ji Chen
- Department of Gastroenterology, the Second Affiliated Hospital of Chongqing Medical University, Chongqing, China
| | - Qing-Liang Wang
- Department of Pathology, the Second Affiliated Hospital of Chongqing Medical University, Chongqing, China
| | - Song He
- Department of Gastroenterology, the Second Affiliated Hospital of Chongqing Medical University, Chongqing, China,*Correspondence: Zhi-Hang Zhou, ; Song He,
| | - Zhi-Hang Zhou
- Department of Gastroenterology, the Second Affiliated Hospital of Chongqing Medical University, Chongqing, China,*Correspondence: Zhi-Hang Zhou, ; Song He,
| |
Collapse
|
99
|
Ospina O, Soupir A, Fridley BL. A Primer on Preprocessing, Visualization, Clustering, and Phenotyping of Barcode-Based Spatial Transcriptomics Data. Methods Mol Biol 2023; 2629:115-140. [PMID: 36929076 DOI: 10.1007/978-1-0716-2986-4_7] [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] [Indexed: 03/18/2023]
Abstract
Recent developments in spatially resolved transcriptomics (ST) have resulted in a large number of studies characterizing the architecture of tissues, the spatial distribution of cell types, and their interactions. Furthermore, ST promises to enable the discovery of more accurate drug targets while also providing a better understanding of the etiology and evolution of complex diseases. The analysis of ST brings similar challenges as seen in other gene expression assays such as scRNA-seq; however, there is the additional spatial information that warrants the development of suitable algorithms for the quality control, preprocessing, visualization, and other discovery-enabling approaches (e.g., clustering, cell phenotyping). In this chapter, we review some of the existing algorithms to perform these analytical tasks and highlight some of the unmet analytical challenges in the analysis of ST data. Given the diversity of available ST technologies, we focus this chapter on the analysis of barcode-based RNA quantitation techniques.
Collapse
Affiliation(s)
- Oscar Ospina
- Department of Biostatistics and Bioinformatics, Moffitt Cancer Center, Tampa, FL, USA
| | - Alex Soupir
- Department of Biostatistics and Bioinformatics, Moffitt Cancer Center, Tampa, FL, USA
| | - Brooke L Fridley
- Department of Biostatistics and Bioinformatics, H. Lee Moffitt Cancer Center & Research Institute, Tampa, FL, USA.
| |
Collapse
|
100
|
Duan H, Cheng T, Cheng H. Spatially resolved transcriptomics: advances and applications. BLOOD SCIENCE 2023; 5:1-14. [PMID: 36742187 PMCID: PMC9891446 DOI: 10.1097/bs9.0000000000000141] [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: 06/28/2022] [Accepted: 10/19/2022] [Indexed: 11/06/2022] Open
Abstract
Spatial transcriptomics, which is capable of both measuring all gene activity in a tissue sample and mapping where this activity occurs, is vastly improving our understanding of biological processes and disease. The field has expanded rapidly in recent years, and the development of several new technologies has resulted in spatially resolved transcriptomics (SRT) becoming highly multiplexed, high-resolution, and high-throughput. Here, we summarize and compare the major methods of SRT, including imaging-based methods, sequencing-based methods, and in situ sequencing methods. We also highlight some typical applications of SRT in neuroscience, cancer biology, developmental biology, and hematology. Finally, we discuss future possibilities for improving spatially resolved transcriptomic methods and the expected applications of such methods, especially in the adult bone marrow, anticipating that new developments will unlock the full potential of spatially resolved multi-omics in both biological research and the clinic.
Collapse
Affiliation(s)
- Honglin Duan
- State Key Laboratory of Experimental Hematology, Haihe Laboratory of Cell Ecosystem, National Clinical Research Center for Blood Diseases, Institute of Hematology and Blood Diseases Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Tianjin, China
| | - Tao Cheng
- State Key Laboratory of Experimental Hematology, Haihe Laboratory of Cell Ecosystem, National Clinical Research Center for Blood Diseases, Institute of Hematology and Blood Diseases Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Tianjin, China
- Center for Stem Cell Medicine, Chinese Academy of Medical Sciences, Tianjin, China
- Department of Stem Cell & Regenerative Medicine, Peking Union Medical College, Tianjin, China
| | - Hui Cheng
- State Key Laboratory of Experimental Hematology, Haihe Laboratory of Cell Ecosystem, National Clinical Research Center for Blood Diseases, Institute of Hematology and Blood Diseases Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Tianjin, China
- Center for Stem Cell Medicine, Chinese Academy of Medical Sciences, Tianjin, China
- Department of Stem Cell & Regenerative Medicine, Peking Union Medical College, Tianjin, China
| |
Collapse
|