单细胞测序技术及其在乳腺癌研究中的应用

doi:10.16288/j.yczz.19-268

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Hereditas(Beijing) ›› 2020, Vol. 42 ›› Issue (3): 250-268.doi: 10.16288/j.yczz.19-268

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Single-cell sequencing and its application in breast cancer

Qiang Zhang, Mingliang Gu()

Joint Laboratory for Translational Medicine Research, Liaocheng City People's Hospital, Liaocheng 252000, China

Received:2019-10-25 Revised:2020-02-03 Online:2020-03-20 Published:2020-02-08
Contact: Gu Mingliang E-mail:minglianggu@hotmai.com
Supported by:
Supported by the National Key R&D Program of China No(2018YFA0109500);the Youth Fund of Natural Science Foundation of Shandong Province No(ZR2019QH009)

Abstract

Abstract:

Breast cancer originates from ducts and epithelial cells, and gradually develops from hyperplasia to atypical hyperplasia, in situ (adeno) carcinoma, to early and advanced invasive carcinoma. Traditional high-throughput sequencing mainly aims to identify candidate ‘driver genes’ attributable to development and progression of breast cancer, which has deficiencies in characterizing genomic structure alteration and subclone evolution, and thus ignores intratumoral, intertumoral or interpatient heterogeneity. The single-cell sequencing technology analyzes transcriptome (e.g., gene copy number and gene expression), explores cellular composition, differentiation and fate, fine-maps the tumor microenvironment, and provides supporting evidence for accurate stratification as well as personalized, precise therapy. At the same time, a complex relationship between breast cancer cells and T cells, macrophages and other immune cells can be revealed, thus facilitating discovery of new therapeutic targets and immune checkpoints. Here, we review state-of-the-art single-cell sequencing technologies and its application in breast cancer, in order to decipher multi-faceted alterations in the crosstalk/interactions between tumors and its microenvironments at the single-cell level, and provide a basis for better understanding of complicated pathogenesis and new avenues for immunotherapy.

Key words: single-cell sequencing, breast cancer, tumor microenvironment, immunotherapy

Qiang Zhang, Mingliang Gu. Single-cell sequencing and its application in breast cancer[J]. Hereditas(Beijing), 2020, 42(3): 250-268.

Figures/Tables 5

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样本来源	酶	时间(min)	温度(℃)	浓度	参考文献
肝脏	胶原蛋白酶IV	10	37	0.16 mg/mL	[17]
	胶原蛋白酶D	20	37	10 mg/mL	[18]
	链霉蛋白酶和胰蛋白酶	10	37	10 mg/mL,0.05%	[19]
肾脏	Liberase TL	15	37	2 mg/mL	[20]
脾脏	胶原蛋白酶D	45	37	2 mg/mL	[21]
胰腺	胶原蛋白酶P	30	37	8 mmol/L	[22]
	细胞消化液	8~10	37	1×	[23]
	胶原蛋白酶CLS IV	30	37	1 mg/mL	[24]
	胰蛋白酶	30	37	1×	[25]
肺	分散酶和弹性蛋白酶	45	37	0.33 U/mL 和3 U/mL	[26]
	分散酶和胶原蛋白酶	45	37	0.2% solution	[27]
	胰蛋白酶	15	37	0.125%	[28]
皮肤	胰蛋白酶	120	32	1×	[29]
皮肤	Liberase TL	15	37	2 mg/mL	[20]
视网膜	木瓜蛋白酶	45	37	4 U/mL	[30]
视网膜	细胞消化液	5	37	1×	[31]

方法	聚合酶	引物
LA-PR	Taq DNA聚合酶	随机引物
PEP-PCR	Taq DNA聚合酶	随机引物
DOP-PCR	Taq DNA聚合酶	简并寡核苷酸引物
MDA	φ29 DNA聚合酶	随机引物
MALBAC	Bst DNA聚合酶	随机引物和公共标记引物

方法	RNA捕获	cDNA覆盖	UMI
基于添加ployA尾巴
Tang2009	polyA	3′偏倚的全长	无
Quartz-seq	polyA	3′偏倚的全长	无
SUPeR-seq	polyA	全长	无
MATQ-seq	polyA	全长	有
基于5′模板置换机制
SMART-seq	polyA	3′偏倚的全长	无
SMART-seq2	polyA	全长	无
STRT-seq	polyA	5′标签	有
STRT-seq-2i	polyA	5′标签	有
SCRB-seq	polyA	3′标签	有
Drop-seq	polyA	3′标签	有
体外转录扩增(IVT)
CEL-seq	polyA	3′标签	无
CEL-seq2	polyA	3′标签	有
MARS-seq	polyA	3′标签	有
In Drops	polyA	3′标签	有

Single-cell sequencing and its application in breast cancer

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