单细胞测序技术在乳腺癌研究中的应用进展

刘强; 方仪; 王靖

doi:10.19401/j.cnki.1007-3639.2022.07.007

您当前的位置：

首页 >

文章列表页 >

单细胞测序技术在乳腺癌研究中的应用进展

综述 | 更新时间：2025-12-31

- 单细胞测序技术在乳腺癌研究中的应用进展
- Application progress of single-cell sequencing technology in breast cancer research
- 中国癌症杂志 2022年32卷第7期页码：635-642
- 作者机构：
  
  国家癌症中心,国家肿瘤临床医学研究中心,中国医学科学院北京协和医学院肿瘤医院乳腺外科,北京 100021
- 作者简介：
  
  [ "刘强（ORCID: 0000-0003-4690-8447）,博士在读,E-mail: liuqaing@email.ncu.edu.cn。" ]
  王靖（ORCID: 0000-0002-3224-3993）,博士,主任医师、教授,E-mail: wangjing@cicams.ac.cn。
- 基金信息：
  
  国家自然科学基金(81872160)
- DOI：10.19401/j.cnki.1007-3639.2022.07.007
  中图分类号： R737.9
- 收稿：2021-12-01，
  
  纸质出版：2022-07-30
- 稿件说明：
移动端阅览
刘强, 方仪, 王靖. 单细胞测序技术在乳腺癌研究中的应用进展[J]. 中国癌症杂志, 2022,32(7):635-642.

Qiang LIU, Yi FANG, Jing WANG. Application progress of single-cell sequencing technology in breast cancer research[J]. China Oncology, 2022, 32(7): 635-642.
刘强, 方仪, 王靖. 单细胞测序技术在乳腺癌研究中的应用进展[J]. 中国癌症杂志, 2022,32(7):635-642. DOI： 10.19401/j.cnki.1007-3639.2022.07.007.

Qiang LIU, Yi FANG, Jing WANG. Application progress of single-cell sequencing technology in breast cancer research[J]. China Oncology, 2022, 32(7): 635-642. DOI： 10.19401/j.cnki.1007-3639.2022.07.007.

摘要

乳腺癌是全球女性发病率最高的恶性肿瘤

也是女性癌症相关致死的主要原因之一。乳腺癌是一种高度异质性的疾病

肿瘤间异质性和肿瘤内异质性使得精准分型治疗工作进展缓慢。传统高通量测序技术在乳腺癌研究中的应用已为揭示乳腺癌的发生、发展、驱动基因、精确分型、诊断及治疗方面提供了重要参考

但仍有局限性

无法揭示肿瘤内异质性。近年来兴起的单细胞测序技术在灵敏度、准确度和效率方面都得到了极大的提高

研究人员可以分析复杂混合细胞中的单个细胞的分子生物学信息

该技术在研究肿瘤异质性方面展现出极大的优越性。近年来

单细胞测序技术在乳腺癌研究中的应用已有多项重要研究成果发表

包括从单细胞层面解析乳腺癌转录组图谱、探索乳腺癌微环境异质性、探索乳腺癌耐药发生机制、探索乳腺癌克隆异质性及克隆演化研究

以及综合挖掘单细胞公共数据资源揭示乳腺癌异质性。本文对近年来单细胞测序技术在乳腺癌中的应用相关前沿重要研究进行综述并深入思考

旨在为乳腺癌研究者应用单细胞测序技术提供参考

促进单细胞测序技术在乳腺癌研究中的广泛应用。

Abstract

Breast cancer is a malignant tumor with the highest incidence in women in the world

and it represents the leading cause of cancer-related deaths in women. Breast cancer is a highly heterogeneous disease

including the heterogeneity between tumors and even within the tumor microenvironment

making precise classification and treatment of the disease difficult. The application of traditional high-throughput sequencing technology in breast cancer research has provided an important reference for revealing the occurrence and development of breast cancer

driving genes

precise classification

diagnosis and treatment. However

the limitation of traditional high-throughput sequencing technology is its inability to explore heterogeneity within the tumor microenvironment. The single-cell sequencing technology emerged in recent years has been greatly improved in terms of sensitivity

accuracy and efficiency

enabling us to analyze single-cell genome information in complex mixed cells

which has shown great performance in studying tumor heterogeneity. In recent years

there are a number of important research results obtained by harnessing single-cell sequencing technology in breast cancer research

including analyzing breast cancer transcriptome at the single-cell level

exploring the heterogeneity of breast cancer microenvironment

breast cancer drug resistance mechanisms

the clonal heterogeneity and clonal evolution of breast cancer

and comprehensively mining single-cell public data resources to reveal the heterogeneity of breast cancer. This article reviewed important research in recent years regarding the application of single-cell sequencing technology in breast cancer era. We aimed to provide references for breast cancer researchers to manipulate the single-cell sequencing technology and promote the in-depth use of single-cell sequencing technology in breast cancer research.

关键词

Keywords

references

SUNG H , FERLAY J , SIEGEL R L , et al . Global cancer statistics 2020: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries [J ] . CA Cancer J Clin , 2021 , 71 ( 3 ): 209 - 249 . DOI: 10.3322/caac.21660 http://doi.org/10.3322/caac.21660 https://onlinelibrary.wiley.com/doi/10.3322/caac.21660 https://onlinelibrary.wiley.com/doi/10.3322/caac.21660

WANG Y , MASHOCK M , TONG Z , et al . Changing technologies of RNA sequencing and their applications in clinical oncology [J ] . Front Oncol , 2020 , 10 : 447 . DOI: 10.3389/fonc.2020.00447 http://doi.org/10.3389/fonc.2020.00447 https://www.frontiersin.org/article/10.3389/fonc.2020.00447/full https://www.frontiersin.org/article/10.3389/fonc.2020.00447/full

TANG F C , BARBACIORU C , WANG Y Z , et al . mRNA-Seq whole-transcriptome analysis of a single cell [J ] . Nat Methods , 2009 , 6 ( 5 ): 377 - 382 .

KARAAYVAZ M , CRISTEA S , GILLESPIE S M , et al . Unravelling subclonal heterogeneity and aggressive disease states in TNBC through single-cell RNA-seq [J ] . Nat Commun , 2018 , 9 ( 1 ): 3588 . DOI: 10.1038/s41467-018-06052-0 http://doi.org/10.1038/s41467-018-06052-0 https://doi.org/10.1038/s41467-018-06052-0 https://doi.org/10.1038/s41467-018-06052-0

KIM C , GAO R L , SEI E , et al . Chemoresistance evolution in triple-negative breast cancer delineated by single-cell sequencing [J ] . Cell , 2018 , 173 ( 4 ): 879 - 893 .e13. DOI: 10.1016/j.cell.2018.03.041 http://doi.org/10.1016/j.cell.2018.03.041 https://linkinghub.elsevier.com/retrieve/pii/S0092867418303659 https://linkinghub.elsevier.com/retrieve/pii/S0092867418303659

WU S Z , RODEN D L , WANG C F , et al . Stromal cell diversity associated with immune evasion in human triple-negative breast cancer [J ] . EMBO J , 2020 , 39 ( 19 ): e104063.

CHUNG W , EUM H H , LEE H O , et al . Single-cell RNA-seq enables comprehensive tumour and immune cell profiling in primary breast cancer [J ] . Nat Commun , 2017 , 8 : 15081 . DOI: 10.1038/ncomms15081 http://doi.org/10.1038/ncomms15081 http://www.nature.com/articles/ncomms15081 http://www.nature.com/articles/ncomms15081

NGUYEN Q H , PERVOLARAKIS N , BLAKE K , et al . Profiling human breast epithelial cells using single cell RNA sequencing identifies cell diversity [J ] . Nat Commun , 2018 , 9 ( 1 ): 2028 . DOI: 10.1038/s41467-018-04334-1 http://doi.org/10.1038/s41467-018-04334-1 https://doi.org/10.1038/s41467-018-04334-1 https://doi.org/10.1038/s41467-018-04334-1

AZIZI E , CARR A J , PLITAS G , et al . Single-cell map of diverse immune phenotypes in the breast tumor microenvironment [J ] . Cell , 2018 , 174 ( 5 ): 1293 - 1308 .e36. DOI: 10.1016/j.cell.2018.05.060 http://doi.org/10.1016/j.cell.2018.05.060 https://linkinghub.elsevier.com/retrieve/pii/S0092867418307232 https://linkinghub.elsevier.com/retrieve/pii/S0092867418307232

BARTOSCHEK M , OSKOLKOV N , BOCCI M , et al . Spatially and functionally distinct subclasses of breast cancer-associated fibroblasts revealed by single cell RNA sequencing [J ] . Nat Commun , 2018 , 9 ( 1 ): 5150 . DOI: 10.1038/s41467-018-07582-3 http://doi.org/10.1038/s41467-018-07582-3 https://doi.org/10.1038/s41467-018-07582-3 https://doi.org/10.1038/s41467-018-07582-3

SEBASTIAN A , HUM N R , MARTIN K A , et al . Single-cell transcriptomic analysis of tumor-derived fibroblasts and normal tissue-resident fibroblasts reveals fibroblast heterogeneity in breast cancer [J ] . Cancers , 2020 , 12 ( 5 ): 1307 . DOI: 10.3390/cancers12051307 http://doi.org/10.3390/cancers12051307 https://www.mdpi.com/2072-6694/12/5/1307 https://www.mdpi.com/2072-6694/12/5/1307

SAVAS P , VIRASSAMY B , YE C Z , et al . Single-cell profiling of breast cancer T cells reveals a tissue-resident memory subset associated with improved prognosis [J ] . Nat Med , 2018 , 24 ( 7 ): 986 - 993 . DOI: 10.1038/s41591-018-0078-7 http://doi.org/10.1038/s41591-018-0078-7 https://doi.org/10.1038/s41591-018-0078-7 https://doi.org/10.1038/s41591-018-0078-7

HOLLERN D P , XU N , THENNAVAN A , et al . B cells and T follicular helper cells mediate response to checkpoint inhibitors in high mutation burden mouse models of breast cancer [J ] . Cell , 2019 , 179 ( 5 ): 1191 - 1206 .e21. DOI: 10.1016/j.cell.2019.10.028 http://doi.org/10.1016/j.cell.2019.10.028 https://linkinghub.elsevier.com/retrieve/pii/S009286741931178X https://linkinghub.elsevier.com/retrieve/pii/S009286741931178X

KUMAR M P , DU J Y , LAGOUDAS G , et al . Analysis of single-cell RNA-seq identifies cell-cell communication associated with tumor characteristics [J ] . Cell Rep , 2018 , 25 ( 6 ): 1458 - 1468 .e4. DOI: 10.1016/j.celrep.2018.10.047 http://doi.org/10.1016/j.celrep.2018.10.047 https://linkinghub.elsevier.com/retrieve/pii/S221112471831636X https://linkinghub.elsevier.com/retrieve/pii/S221112471831636X

HONG S P , CHAN T E , LOMBARDO Y , et al . Single-cell transcriptomics reveals multi-step adaptations to endocrine therapy [J ] . Nat Commun , 2019 , 10 ( 1 ): 3840 . DOI: 10.1038/s41467-019-11721-9 http://doi.org/10.1038/s41467-019-11721-9 https://doi.org/10.1038/s41467-019-11721-9 https://doi.org/10.1038/s41467-019-11721-9

DENG J H , THENNAVAN A , SHAH S , et al . Serial single-cell profiling analysis of metastatic TNBC during Nab-paclitaxel and pembrolizumab treatment [J ] . Breast Cancer Res Treat , 2021 , 185 ( 1 ): 85 - 94 . DOI: 10.1007/s10549-020-05936-4 http://doi.org/10.1007/s10549-020-05936-4 https://doi.org/10.1007/s10549-020-05936-4 https://doi.org/10.1007/s10549-020-05936-4

MUCIÑO-OLMOS E A , VÁZQUEZ-JIMÉNEZ A , AVILA-PONCE DE LEÓN U , et al . Unveiling functional heterogeneity in breast cancer multicellular tumor spheroids through single-cell RNA-seq [J ] . Sci Rep , 2020 , 10 ( 1 ): 12728 . DOI: 10.1038/s41598-020-69026-7 http://doi.org/10.1038/s41598-020-69026-7 https://doi.org/10.1038/s41598-020-69026-7 https://doi.org/10.1038/s41598-020-69026-7

GAO R L , KIM C , SEI E , et al . Nanogrid single-nucleus RNA sequencing reveals phenotypic diversity in breast cancer [J ] . Nat Commun , 2017 , 8 ( 1 ): 228 . DOI: 10.1038/s41467-017-00244-w http://doi.org/10.1038/s41467-017-00244-w http://www.nature.com/articles/s41467-017-00244-w http://www.nature.com/articles/s41467-017-00244-w

POWELL A A , TALASAZ A H , ZHANG H Y , et al . Single cell profiling of circulating tumor cells: transcriptional heterogeneity and diversity from breast cancer cell lines [J ] . PLoS One , 2012 , 7 ( 5 ): e33788.

CHEN Y C , SAHOO S , BRIEN R , et al . Single-cell RNA-sequencing of migratory breast cancer cells: discovering genes associated with cancer metastasis [J ] . Analyst , 2019 , 144 ( 24 ): 7296 - 7309 . DOI: 10.1039/C9AN01358J http://doi.org/10.1039/C9AN01358J http://xlink.rsc.org/?DOI=C9AN01358J http://xlink.rsc.org/?DOI=C9AN01358J

ACETO N , BARDIA A , MIYAMOTO D T , et al . Circulating tumor cell clusters are oligoclonal precursors of breast cancer metastasis [J ] . Cell , 2014 , 158 ( 5 ): 1110 - 1122 . DOI: 10.1016/j.cell.2014.07.013 http://doi.org/10.1016/j.cell.2014.07.013 https://linkinghub.elsevier.com/retrieve/pii/S0092867414009271 https://linkinghub.elsevier.com/retrieve/pii/S0092867414009271

WANG Y , WATERS J , LEUNG M L , et al . Clonal evolution in breast cancer revealed by single nucleus genome sequencing [J ] . Nature , 2014 , 512 ( 7513 ): 155 - 160 . DOI: 10.1038/nature13600 http://doi.org/10.1038/nature13600 https://doi.org/10.1038/nature13600 https://doi.org/10.1038/nature13600

EIREW P , STEIF A , KHATTRA J , et al . Dynamics of genomic clones in breast cancer patient xenografts at single-cell resolution [J ] . Nature , 2015 , 518 ( 7539 ): 422 - 426 . DOI: 10.1038/nature13952 http://doi.org/10.1038/nature13952 https://doi.org/10.1038/nature13952 https://doi.org/10.1038/nature13952

DEMEULEMEESTER J , KUMAR P , MØLLER E K , et al . Tracing the origin of disseminated tumor cells in breast cancer using single-cell sequencing [J ] . Genome Biol , 2016 , 17 ( 1 ): 250 . DOI: 10.1186/s13059-016-1109-7 http://doi.org/10.1186/s13059-016-1109-7 http://genomebiology.biomedcentral.com/articles/10.1186/s13059-016-1109-7 http://genomebiology.biomedcentral.com/articles/10.1186/s13059-016-1109-7

LAWSON D A , BHAKTA N R , KESSENBROCK K , et al . Single-cell analysis reveals a stem-cell program in human metastatic breast cancer cells [J ] . Nature , 2015 , 526 ( 7571 ): 131 - 135 . DOI: 10.1038/nature15260 http://doi.org/10.1038/nature15260 https://doi.org/10.1038/nature15260 https://doi.org/10.1038/nature15260

BRECHBUHL H M , VINOD-PAUL K , GILLEN A E , et al . Analysis of circulating breast cancer cell heterogeneity and interactions with peripheral blood mononuclear cells [J ] . Mol Carcinog , 2020 , 59 ( 10 ): 1129 - 1139 . DOI: 10.1002/mc.23242 http://doi.org/10.1002/mc.23242 https://onlinelibrary.wiley.com/doi/10.1002/mc.23242 https://onlinelibrary.wiley.com/doi/10.1002/mc.23242

DAVIS R T , BLAKE K , MA D , et al . Transcriptional diversity and bioenergetic shift in human breast cancer metastasis revealed by single-cell RNA sequencing [J ] . Nat Cell Biol , 2020 , 22 ( 3 ): 310 - 320 . DOI: 10.1038/s41556-020-0477-0 http://doi.org/10.1038/s41556-020-0477-0 https://doi.org/10.1038/s41556-020-0477-0 https://doi.org/10.1038/s41556-020-0477-0

BAO X W , SHI R , ZHAO T Y , et al . Integrated analysis of single-cell RNA-seq and bulk RNA-seq unravels tumour heterogeneity plus M2-like tumour-associated macrophage infiltration and aggressiveness in TNBC [J ] . Cancer Immunol Immunother , 2021 , 70 ( 1 ): 189 - 202 . DOI: 10.1007/s00262-020-02669-7 http://doi.org/10.1007/s00262-020-02669-7 https://doi.org/10.1007/s00262-020-02669-7 https://doi.org/10.1007/s00262-020-02669-7

BARRETT T , SUZEK T O , TROUP D B , et al . NCBI GEO: mining millions of expression profiles--database and tools [J ] . Nucleic Acids Res , 2005 , 33 (database issue): D562-D566.

GOLDMAN M , CRAFT B , ZHU J C , et al . Abstract 2584: the UCSC Xena system for cancer genomics data visualization and interpretation [J ] . Cancer Res , 2017 , 77 ( 13 supplement ): 2584.

PAPATHEODOROU I , MORENO P , MANNING J , et al . Expression Atlas update: from tissues to single cells [J ] . Nucleic Acids Res , 2020 , 48 ( D1 ): D77-D83.

REGEV A , TEICHMANN S A , LANDER E S , et al . The human cell atlas [J ] . Elife , 2017 , 6 : e27041.

FRANZÉN O , GAN L M , BJÖRKEGREN J L M . PanglaoDB: a web server for exploration of mouse and human single-cell RNA sequencing data [J ] . Database (Oxford) , 2019 , 2019 : baz046.

CAO Y , ZHU J J , JIA P L , et al . scRNASeqDB: a database for RNA-seq based gene expression profiles in human single cells [J ] . Genes (Basel) , 2017 , 8 ( 12 ): E368.

NGUYEN Q H , PERVOLARAKIS N , NEE K , et al . Experimental considerations for single-cell RNA sequencing approaches [J ] . Front Cell Dev Biol , 2018 , 6 : 108 . DOI: 10.3389/fcell.2018.00108 http://doi.org/10.3389/fcell.2018.00108 https://www.frontiersin.org/article/10.3389/fcell.2018.00108/full https://www.frontiersin.org/article/10.3389/fcell.2018.00108/full

浏览量

2005

下载量

CSCD

文章被引用时，请邮件提醒。

提交

工具集

关联资源

单细胞测序在口腔鳞状细胞癌研究中的价值

单细胞转录组测序及其在乳腺癌中的应用

基于EPR监测乳腺癌肿瘤微环境氧分压水平作为化疗敏感的指标研究

乳腺肿瘤微环境靶向治疗的研究进展

中国抗癌协会乳腺癌诊治指南与规范（2026年版）