High Throughput Transcriptome Data Analysis and Computational Verification Reveal Immunotherapy Biomarkers of Compound Kushen Injection for Treating Triple-Negative Breast Cancer

doi:10.3389/fonc.2021.747300

	High Throughput Transcriptome Data Analysis and Computational Verification Reveal Immunotherapy Biomarkers of Compound Kushen Injection for Treating Triple-Negative Breast Cancer
	Liu, Xinkui 1; Wu, Yang 2; Zhang, Yingying 3; Bu, Dechao 4; Wu, Chao 1; Lu, Shan 1; Huang, Zhihong 1; Song, Yurong 1; Zhao, Yi 2,5; Guo, Fengying 6; Ye, Peizhi 7; Fu, Changgeng 8; Shen, Liangliang 1; Zhang, Jingyuan 1; Wang, Haojia 1; Duan, Xianchun 9; Wu, Jiarui 1
	2021-09-17
发表期刊	FRONTIERS IN ONCOLOGY
ISSN	2234-943X
卷号	11 页码:23
摘要	Background Although notable therapeutic and prognostic benefits of compound kushen injection (CKI) have been found when it was used alone or in combination with chemotherapy or radiotherapy for triple-negative breast cancer (TNBC) treatment, the effects of CKI on TNBC microenvironment remain largely unclear. This study aims to construct and validate a predictive immunotherapy signature of CKI on TNBC. Methods The UPLC-Q-TOF-MS technology was firstly used to investigate major constituents of CKI. RNA sequencing data of CKI-perturbed TNBC cells were analyzed to detect differential expression genes (DEGs), and the GSVA algorithm was applied to explore significantly changed pathways regulated by CKI. Additionally, the ssGSEA algorithm was used to quantify immune cell abundance in TNBC patients, and these patients were classified into distinct immune infiltration subgroups by unsupervised clustering. Then, prognosis-related genes were screened from DEGs among these subgroups and were further overlapped with the DEGs regulated by CKI. Finally, a predictive immunotherapy signature of CKI on TNBC was constructed based on the LASSO regression algorithm to predict mortality risks of TNBC patients, and the signature was also validated in another TNBC cohort. Results Twenty-three chemical components in CKI were identified by UPLC-Q-TOF-MS analysis. A total of 3692 DEGs were detected in CKI-treated versus control groups, and CKI significantly activated biological processes associated with activation of T, natural killer and natural killer T cells. Three immune cell infiltration subgroups with 1593 DEGs were identified in TNBC patients. Then, two genes that can be down-regulated by CKI with hazard ratio (HR) > 1 and 26 genes that can be up-regulated by CKI with HR < 1 were selected as key immune- and prognosis-related genes regulated by CKI. Lastly, a five-gene prognostic signature comprising two risky genes (MARVELD2 and DYNC2I2) that can be down-regulated by CKI and three protective genes (RASSF2, FERMT3 and RASSF5) that can be up-regulated by CKI was developed, and it showed a good performance in both training and test sets. Conclusions This study proposes a predictive immunotherapy signature of CKI on TNBC, which would provide more evidence for survival prediction and treatment guidance in TNBC as well as a paradigm for exploring immunotherapy biomarkers in compound medicines.
关键词	compound kushen injection triple-negative breast cancer RNA sequencing tumor microenvironment prognostic signature
DOI	10.3389/fonc.2021.747300
收录类别	SCI
语种	英语
资助项目	National Natural Science Foundation of China[82074284]
WOS研究方向	Oncology
WOS类目	Oncology
WOS记录号	WOS:000717283900001
出版者	FRONTIERS MEDIA SA
引用统计	被引频次：4[WOS] [WOS记录] [WOS相关记录]
文献类型	期刊论文
条目标识符	http://119.78.100.204/handle/2XEOYT63/17888
专题	中国科学院计算技术研究所期刊论文_英文
通讯作者	Duan, Xianchun; Wu, Jiarui
作者单位	1.Beijing Univ Chinese Med, Sch Chinese Pharm, Beijing, Peoples R China 2.Chinese Acad Sci, Adv Comp Res Ctr, Inst Comp Technol, Key Lab Intelligent Informat Proc, Beijing, Peoples R China 3.Peoples Liberat Army PLA Rocket Force Characteris, New Era Stroke Care & Res Inst, Dept Vasc Neurosurg, Beijing, Peoples R China 4.Chinese Acad Sci, Pervas Comp Res Ctr, Inst Comp Technol, Beijing, Peoples R China 5.Beijing Univ Chinese Med, Sch Tradit Chinese Med, Beijing, Peoples R China 6.Beijing Univ Chinese Med, Sch Management, Beijing, Peoples R China 7.Chinese Acad Med Sci & Peking Union Med Coll, Natl Canc Ctr, Natl Clin Res Ctr Canc, Canc Hosp, Beijing, Peoples R China 8.China Acad Chinese Med Sci, Xiyuan Hosp, Beijing, Peoples R China 9.Anhui Univ Tradit Chinese Med, Dept Pharm, Affiliated Hosp 1, Hefei, Peoples R China
推荐引用方式 GB/T 7714	Liu, Xinkui,Wu, Yang,Zhang, Yingying,et al. High Throughput Transcriptome Data Analysis and Computational Verification Reveal Immunotherapy Biomarkers of Compound Kushen Injection for Treating Triple-Negative Breast Cancer[J]. FRONTIERS IN ONCOLOGY,2021,11:23.
APA	Liu, Xinkui.,Wu, Yang.,Zhang, Yingying.,Bu, Dechao.,Wu, Chao.,...&Wu, Jiarui.(2021).High Throughput Transcriptome Data Analysis and Computational Verification Reveal Immunotherapy Biomarkers of Compound Kushen Injection for Treating Triple-Negative Breast Cancer.FRONTIERS IN ONCOLOGY,11,23.
MLA	Liu, Xinkui,et al."High Throughput Transcriptome Data Analysis and Computational Verification Reveal Immunotherapy Biomarkers of Compound Kushen Injection for Treating Triple-Negative Breast Cancer".FRONTIERS IN ONCOLOGY 11(2021):23.