Single-cell transcriptional profiling reveals the heterogeneity in embryonal rhabdomyosarcoma

被引:3
|
作者
Hong, Bo [1 ,2 ]
Xia, Tian [2 ,3 ]
Ye, Chun-Jing [1 ,2 ]
Zhan, Yong [1 ,2 ]
Yang, Ran [1 ,2 ]
Liu, Jia [1 ,2 ]
Li, Yi [1 ,2 ]
Chen, Zhi-Xue [1 ,2 ]
Yao, Wei [1 ,2 ]
Li, Kai [1 ,2 ]
Wang, Jia [4 ]
Dong, Kui-Ran [1 ,2 ]
Dong, Rui [1 ,2 ]
机构
[1] Fudan Univ, Childrens Hosp, Dept Pediat Surg, Shanghai, Peoples R China
[2] Shanghai Key Lab Birth Defect, Shanghai, Peoples R China
[3] Fudan Univ, Childrens Hosp, Dept Orthopaed, Shanghai, Peoples R China
[4] Shanghai Jiao Tong Univ, State Key Lab Oncogenes & Related Genes, Renji Med Clin Stem Cell Res Ctr 10, Ren Ji Hosp,Sch Med, Shanghai, Peoples R China
关键词
embryonal rhabdomyosarcoma; evolutionary history; GO; KEGG analysis; pseudo-time analysis; single-cell RNA sequencing; TUMOR-GROWTH; STEM; FIBROBLASTS; EXPRESSION; MARKER; MUSCLE;
D O I
10.1097/MD.0000000000026775
中图分类号
R5 [内科学];
学科分类号
1002 ; 100201 ;
摘要
Rhabdomyosarcoma is the most common soft tissue sarcoma in children, and embryonal rhabdomyosarcoma is the most typical type of rhabdomyosarcoma. The heterogeneity, etiology, and origin of embryonal rhabdomyosarcoma remain unknown. After obtaining the gene expression data of every cell in the tumor tissue by single-cell RNA sequencing, we used the Seurat package in R studio for quality control, analysis, and exploration of the data. All cells are divided into tumor cells and non-tumor cells, and we chose tumor cells by marker genes. Then, we repeated the process to cluster the tumor cells and divided the subgroups by their differentially expressed genes and gene ontology/Kyoto Encyclopedia of Genes and Genomes analysis. Additionally, Monocle 2 was used for pseudo-time analysis to obtain the evolution trajectory of cells in tumor tissues. Tumor cells were divided into 5 subgroups according to their functions, which were characterized by high proliferation, sensing and adaptation to oxygen availability, enhanced epigenetic modification, enhanced nucleoside phosphonic acid metabolism, and ossification. Evolution trajectory of cells in tumor tissues is obtained. We used pseudo-time analysis to distinguish between mesenchymal stem cells and fibroblasts, proved that embryonal rhabdomyosarcoma in the pelvic originated from skeletal muscle progenitor cells, showed the evolutionary trajectory of embryonal rhabdomyosarcoma, and improved the method of evaluating the degree of malignancy of embryonal rhabdomyosarcoma.
引用
收藏
页数:9
相关论文
共 50 条
  • [41] Comprehensive single-cell transcriptome analysis reveals heterogeneity in endometrioid adenocarcinoma tissues
    Hashimoto, Shinichi
    Tabuchi, Yuta
    Yurino, Hideaki
    Hirohashi, Yoshihiko
    Deshimaru, Shungo
    Asano, Takuya
    Mariya, Tasuku
    Oshima, Kenshiro
    Takamura, Yuzuru
    Ukita, Yoshiaki
    Ametani, Akio
    Kondo, Naoto
    Monma, Norikazu
    Takeda, Tadayuki
    Misu, Sadahiko
    Okayama, Toshitugu
    Ikeo, Kazuho
    Saito, Tsuyoshi
    Kaneko, Shuich
    Suzuki, Yutaka
    Hattori, Masahira
    Matsushima, Kouji
    Torigoe, Toshihiko
    SCIENTIFIC REPORTS, 2017, 7
  • [42] Dissecting human trophoblast cell transcriptional heterogeneity in preeclampsia using single-cell RNA sequencing
    Zhang, Tao
    Bian, Qianqian
    Chen, Yanchun
    Wang, Xiaolin
    Yu, Shaowei
    Liu, Shunhua
    Ji, Ping
    Li, Ling
    Shrestha, Mandakini
    Dong, Shujun
    Guo, Rong
    Zhang, Hong
    MOLECULAR GENETICS & GENOMIC MEDICINE, 2021, 9 (08):
  • [43] Single-cell RNA Sequencing Reveals Heterogeneity of Cultured Bovine Satellite Cells
    Lyu, Pengcheng
    Qi, Yumin
    Tu, Zhijian J.
    Jiang, Honglin
    FRONTIERS IN GENETICS, 2021, 12
  • [44] Longitudinal single-cell profiling reveals molecular heterogeneity and tumor-immune evolution in refractory mantle cell lymphoma
    Zhang, Shaojun
    Jiang, Vivian Changying
    Han, Guangchun
    Hao, Dapeng
    Lian, Junwei
    Liu, Yang
    Zhang, Rongjia
    McIntosh, Joseph
    Wang, Ruiping
    Dang, Minghao
    Dai, Enyu
    Wang, Yuanxin
    Santos, David
    Badillo, Maria
    Leeming, Angela
    Chen, Zhihong
    Hartig, Kimberly
    Bigcal, John
    Zhou, Jia
    Kanagal-Shamanna, Rashmi
    Ok, Chi Young
    Lee, Hun
    Steiner, Raphael E.
    Zhang, Jianhua
    Song, Xingzhi
    Nair, Ranjit
    Ahmed, Sairah
    Rodriquez, Alma
    Thirumurthi, Selvi
    Jain, Preetesh
    Wagner-Bartak, Nicolaus
    Hill, Holly
    Nomie, Krystle
    Flowers, Christopher
    Futreal, Andrew
    Wang, Linghua
    Wang, Michael
    NATURE COMMUNICATIONS, 2021, 12 (01)
  • [45] Single-Cell Transcriptional Profiling Reveals Cell Type-Specific Sex-Dependent Molecular Patterns of Schizophrenia
    Zhou, Runguang
    Zhang, Tianli
    Sun, Baofa
    INTERNATIONAL JOURNAL OF MOLECULAR SCIENCES, 2025, 26 (05)
  • [46] Single-cell profiling reveals a potent role of quercetin in promoting hair regeneration
    Zhao, Qian
    Zheng, Yandong
    Zhao, Dongxin
    Zhao, Liyun
    Geng, Lingling
    Ma, Shuai
    Cai, Yusheng
    Liu, Chengyu
    Yan, Yupeng
    Belmonte, Juan Carlos Izpisua
    Wang, Si
    Zhang, Weiqi
    Liu, Guang-Hui
    Qu, Jing
    PROTEIN & CELL, 2023, 14 (06) : 398 - 415
  • [47] Single-Cell RNA Sequencing Reveals Transcriptional Signatures and Cell-Cell Communication in Diabetic Retinopathy
    Li, Muye
    Peng, Yueling
    Pang, Lin
    Wang, Lin
    Li, Junhong
    ENDOCRINE METABOLIC & IMMUNE DISORDERS-DRUG TARGETS, 2024, 24 (14) : 1651 - 1663
  • [48] Integrated single-cell transcriptome analysis reveals heterogeneity of esophageal squamous cell carcinoma microenvironment
    Dinh, Huy Q.
    Pan, Feng
    Wang, Geng
    Huang, Qing-Feng
    Olingy, Claire E.
    Wu, Zhi-Yong
    Wang, Shao-Hong
    Xu, Xin
    Xu, Xiu-E
    He, Jian-Zhong
    Yang, Qian
    Orsulic, Sandra
    Haro, Marcela
    Li, Li-Yan
    Huang, Guo-Wei
    Breunig, Joshua J.
    Koeffler, H. Phillip
    Hedrick, Catherine C.
    Xu, Li-Yan
    Lin, De-Chen
    Li, En-Min
    NATURE COMMUNICATIONS, 2021, 12 (01)
  • [49] Single-cell analyses of transcriptional heterogeneity in squamous cell carcinoma of urinary bladder
    Zhang, Xiaolong
    Zhang, Meng
    Hou, Yong
    Xu, Liqin
    Li, Weidong
    Zou, Zhihui
    Liu, Chunxiao
    Xu, Abai
    Wu, Song
    ONCOTARGET, 2016, 7 (40) : 66069 - 66076
  • [50] Single-cell transcriptional profiling of clear cell renal cell carcinoma reveals a tumor-associated endothelial tip cell phenotype
    Zvirblyte, Justina
    Nainys, Juozas
    Juzenas, Simonas
    Goda, Karolis
    Kubiliute, Raimonda
    Dasevicius, Darius
    Kincius, Marius
    Ulys, Albertas
    Jarmalaite, Sonata
    Mazutis, Linas
    COMMUNICATIONS BIOLOGY, 2024, 7 (01)