Recent developments in application of single-cell RNA sequencing in the tumour immune microenvironment and cancer therapy

Pei-Heng Li; Xiang-Yu Kong; Ya-Zhou He; Yi Liu; Xi Peng; Zhi-Hui Li; Heng Xu; Han Luo; Jihwan Park

doi:10.1186/s40779-022-00414-y

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Recent developments in application of single-cell RNA sequencing in the tumour immune microenvironment and cancer therapy

REVIEW | Updated：2023-07-21

- Recent developments in application of single-cell RNA sequencing in the tumour immune microenvironment and cancer therapy
- Recent developments in application of single-cell RNA sequencing in the tumour immune microenvironment and cancer therapy
- MMR 2023年10卷第3期页码：383-402
- Affiliations：
  
  1.Department of Thyroid and Parathyroid Surgery, Laboratory of Thyroid and Parathyroid Disease, Frontiers Science Centre for Disease-Related Molecular Network, Department of General Surgery, West China Hospital, Sichuan University, Chengdu 610044, China
  2.Department of Oncology, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu 610044, China
  3.Department of Rheumatology and Immunology, Rare Diseases Centre, West China Hospital, Sichuan University, Chengdu 610044, China
  4.College of Computer Science, Sichuan University, Chengdu 610065, China
  5.State Key Laboratory of Biotherapy and Cancer Centre, West China Hospital, Sichuan University and Collaborative Innovation Centre, Chengdu 610044, China
  6.School of Life Sciences, Gwangju Institute of Science and Technology (GIST), Gwangju 61005, Republic of Korea
- Author bio：
  
  * luohan-hx@scu.edu.cn;
  jihwan.park@gist.ac.kr
- Funds：
  
  the National Key Research Development Program of China(2021YFA1301203);the National Natural Science Foundation of China(82103031;82103918;81973408);the Clinical Research Incubation Project, West China Hospital, Sichuan University(22HXFH019);the China Postdoctoral Science Foundation(2019 M653416);the International Cooperation Project of Chengdu Municipal Science and Technology Bureau(2020-GH02-00017-HZ);the "1.3.5 Project for Disciplines of Excellence, West China Hospital, Sichuan University"(ZYJC18035;ZYJC18025;ZYYC20003;ZYJC18003);the GIST Research Institute (GRI) IIBR grants funded by the GIST;the National Research Foundation of Korea funded by the Korean government (MSIP)(2019R1C1C1005403;2019R1A4A1028802;2021M3H9A2097520);the Post-Doctor Research Project, West China Hospital, Sichuan University(2021HXBH054)
- DOI：10.1186/s40779-022-00414-y
  中图分类号：
- 纸质出版：2023-06
- Accepted：
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Recent developments in application of single-cell RNA sequencing in the tumour immune microenvironment and cancer therapy[J]. MMR, 2023,10(3):383-402.

Cite this article as: Li PH, Kong XY, He YZ, Liu Y, Peng X, Li ZH, et al. Recent developments in application of single-cell RNA sequencing in the tumour immune microenvironment and cancer therapy. Mil Med Res. 2022;9(1):52.
Recent developments in application of single-cell RNA sequencing in the tumour immune microenvironment and cancer therapy[J]. MMR, 2023,10(3):383-402. DOI： 10.1186/s40779-022-00414-y.

Cite this article as: Li PH, Kong XY, He YZ, Liu Y, Peng X, Li ZH, et al. Recent developments in application of single-cell RNA sequencing in the tumour immune microenvironment and cancer therapy. Mil Med Res. 2022;9(1):52. DOI： 10.1186/s40779-022-00414-y.

摘要

Abstract

The advent of single-cell RNA sequencing (scRNA-seq) has provided insight into the tumour immune microenvironment (TIME). This review focuses on the application of scRNA-seq in investigation of the TIME. Over time

scRNA-seq methods have evolved

and components of the TIME have been deciphered with high resolution. In this review

we first introduced the principle of scRNA-seq and compared different sequencing approaches. Novel cell types in the TIME

a continuous transitional state

and mutual intercommunication among TIME components present potential targets for prognosis prediction and treatment in cancer. Thus

we concluded novel cell clusters of cancer-associated fibroblasts (CAFs)

T cells

tumour-associated macrophages (TAMs) and dendritic cells (DCs) discovered after the application of scRNA-seq in TIME. We also proposed the development of TAMs and exhausted T cells

as well as the possible targets to interrupt the process. In addition

the therapeutic interventions based on cellular interactions in TIME were also summarized. For decades

quantification of the TIME components has been adopted in clinical practice to predict patient survival and response to therapy and is expected to play an important role in the precise treatment of cancer. Summarizing the current findings

we believe that advances in technology and wide application of single-cell analysis can lead to the discovery of novel perspectives on cancer therapy

which can subsequently be implemented in the clinic. Finally

we propose some future directions in the field of TIME studies that can be aided by scRNA-seq technology.

关键词

Keywords

references

Vitale I , Shema E , Loi S , Galluzzi L . Intratumoral heterogeneity in cancer progression and response to immunotherapy . Nat Med . 2021 ; 27 ( 2 ): 212 - 24 .

Parker JS , Mullins M , Cheang MC , Leung S , Voduc D , Vickery T , et al . Supervised risk predictor of breast cancer based on intrinsic subtypes . J Clin Oncol . 2009 ; 27 ( 8 ): 1160 - 7 .

Robertson AG , Kim J , Al-Ahmadie H , Bellmunt J , Guo G , Cherniack AD , et al . Comprehensive molecular characterization of muscle-invasive bladder cancer . Cell . 2017 ; 171 ( 3 ): 540 - 56 .

Choi W , Porten S , Kim S , Willis D , Plimack ER , Hoffman-Censits J , et al . Identification of distinct basal and luminal subtypes of muscle-invasive bladder cancer with different sensitivities to frontline chemotherapy . Cancer Cell . 2014 ; 25 ( 2 ): 152 - 65 .

Choi W , Ochoa A , McConkey DJ , Aine M , Hoglund M , Kim WY , et al . Genetic alterations in the molecular subtypes of bladder cancer: illustration in the cancer genome atlas dataset . Eur Urol . 2017 ; 72 ( 3 ): 354 - 65 .

Zhang L , Ren Z , Su Z , Liu Y , Yang T , Cao M , et al . Novel recurrent altered genes in Chinese patients with anaplastic thyroid cancer . J Clin Endocrinol Metab . 2021 ; 106 ( 4 ): 988 - 98 .

Qian J , Olbrecht S , Boeckx B , Vos H , Laoui D , Etlioglu E , et al . A pancancer blueprint of the heterogeneous tumor microenvironment revealed by single-cell profiling . Cell Res . 2020 ; 30 ( 9 ): 745 - 62 .

Boussiotis VA . Molecular and biochemical aspects of the PD-1 checkpoint pathway . N Engl J Med . 2016 ; 375 ( 18 ): 1767 - 78 .

Topalian SL , Hodi FS , Brahmer JR , Gettinger SN , Smith DC , McDermott DF , et al . Safety, activity, and immune correlates of anti-PD-1 antibody in cancer . N Engl J Med . 2012 ; 366 ( 26 ): 2443 - 54 .

Kechagia JZ , Ivaska J , Roca-Cusachs P . Integrins as biomechanical sensors of the microenvironment . Nat Rev Mol Cell Biol . 2019 ; 20 ( 8 ): 457 - 73 .

Bolouri H . Network dynamics in the tumor microenvironment . Semin Cancer Biol . 2015 ; 30 : 52 - 9 .

Shi Y , Du L , Lin L , Wang Y . Tumour-associated mesenchymal stem/ stromal cells: emerging therapeutic targets . Nat Rev Drug Discov . 2017 ; 16 ( 1 ): 35 - 52 .

Newman AM , Steen CB , Liu CL , Gentles AJ , Chaudhuri AA , Scherer F , et al . Determining cell type abundance and expression from bulk tissues with digital cytometry . Nat Biotechnol . 2019 ; 37 ( 7 ): 773 - 82 .

Tsoucas D , Dong R , Chen H , Zhu Q , Guo G , Yuan GC . Accurate estimation of cell-type composition from gene expression data . Nat Commun . 2019 ; 10 ( 1 ): 2975 .

Chrzanowska NM , Kowalewski J , Lewandowska MA . Use of fluorescence in situ hybridization (FISH) in diagnosis and tailored therapies in solid tumors . Molecules . 2020 ; 25 ( 8 ): 1864 .

Lin X , Wang F , Chen J , Liu J , Lin YB , Li L , et al . N(6)-methyladenosine modification of CENPK mRNA by ZC3H13 promotes cervical cancer stemness and chemoresistance . Mil Med Res . 2022 ; 9 ( 1 ): 19 .

Finotello F , Rieder D , Hackl H , Trajanoski Z . Next-generation computational tools for interrogating cancer immunity . Nat Rev Genet . 2019 ; 20 ( 12 ): 724 - 46 .

Levitin HM , Yuan J , Sims PA . Single-cell transcriptomic analysis of tumor heterogeneity . Trends Cancer . 2018 ; 4 ( 4 ): 264 - 8 .

González-Silva L , Quevedo L , Varela I . Tumor functional heterogeneity unraveled by scRNA-seq technologies . Trends Cancer . 2020 ; 6 ( 1 ): 13 - 9 .

Ji JJ , Fan J . Discovering myeloid cell heterogeneity in the lung by means of next generation sequencing . Mil Med Res . 2019 ; 6 ( 1 ): 33 .

Wang Y , Wang JY , Schnieke A , Fischer K . Advances in single-cell sequencing: insights from organ transplantation . Mil Med Res . 2021 ; 8 ( 1 ): 45 .

Greten FR , Grivennikov SI . Inflammation and cancer: triggers, mechanisms, and consequences . Immunity . 2019 ; 51 ( 1 ): 27 - 41 .

Binnewies M , Roberts EW , Kersten K , Chan V , Fearon DF , Merad M , et al . Understanding the tumor immune microenvironment (TIME) for effective therapy . Nat Med . 2018 ; 24 ( 5 ): 541 - 50 .

Lim B , Lin Y , Navin N . Advancing cancer research and medicine with single-cell genomics . Cancer Cell . 2020 ; 37 ( 4 ): 456 - 70 .

Gawad C , Koh W , Quake SR . Single-cell genome sequencing: current state of the science . Nat Rev Genet . 2016 ; 17 ( 3 ): 175 - 88 .

Picelli S . Single-cell RNA-sequencing: the future of genome biology is now . RNA Biol . 2017 ; 14 ( 5 ): 637 - 50 .

Potter SS . Single-cell RNA sequencing for the study of development, physiology and disease . Nat Rev Nephrol . 2018 ; 14 ( 8 ): 479 - 92 .

Zhang X , Marjani SL , Hu Z , Weissman SM , Pan X , Wu S . Single-cell sequencing for precise cancer research: progress and prospects . Cancer Res . 2016 ; 76 ( 6 ): 1305 - 12 .

Xin Y , Kim J , Ni M , Wei Y , Okamoto H , Lee J , et al . Use of the Fluidigm C1 platform for RNA sequencing of single mouse pancreatic islet cells . Proc Natl Acad Sci USA . 2016 ; 113 ( 12 ): 3293 - 8 .

See P , Lum J , Chen J , Ginhoux F . A single-cell sequencing guide for immunologists . Front Immunol . 2018 ; 9 : 2425 .

DeLaughter DM . The use of the Fluidigm C1 for RNA expression analyses of single cells . Curr Protoc Mol Biol . 2018 ; 122 ( 1 ): e55 .

Klein AM , Mazutis L , Akartuna I , Tallapragada N , Veres A , Li V , et al . Droplet barcoding for single-cell transcriptomics applied to embryonic stem cells . Cell . 2015 ; 161 ( 5 ): 1187 - 201 .

Macosko EZ , Basu A , Satija R , Nemesh J , Shekhar K , Goldman M , et al . Highly parallel genome-wide expression profiling of individual cells using nanoliter droplets . Cell . 2015 ; 161 ( 5 ): 1202 - 14 .

Zhang X , Li T , Liu F , Chen Y , Yao J , Li Z , et al . Comparative analysis of droplet-based ultra-high-throughput single-cell RNA-seq systems . Mol Cell . 2019 ; 73 ( 1 ): 130 - 42 .

Zheng GX , Terry JM , Belgrader P , Ryvkin P , Bent ZW , Wilson R , et al . Massively parallel digital transcriptional profiling of single cells . Nat Commun . 2017 ; 8 : 14049 .

Papalexi E , Satija R . Single-cell RNA sequencing to explore immune cell heterogeneity . Nat Rev Immunol . 2018 ; 18 ( 1 ): 35 - 45 .

Picelli S , Björklund ÅK , Faridani OR , Sagasser S , Winberg G , Sandberg R . Smart-seq2 for sensitive full-length transcriptome profiling in single cells . Nat Methods . 2013 ; 10 ( 11 ): 1096 - 8 .

Hashimshony T , Wagner F , Sher N , Yanai I . CEL-Seq: single-cell RNASeq by multiplexed linear amplification . Cell Rep . 2012 ; 2 ( 3 ): 666 - 73 .

Jaitin DA , Kenigsberg E , Keren-Shaul H , Elefant N , Paul F , Zaretsky I , et al . Massively parallel single-cell RNA-seq for marker-free decomposition of tissues into cell types . Science . 2014 ; 343 ( 6172 ): 776 - 9 .

Islam S , Zeisel A , Joost S , La Manno G , Zajac P , Kasper M , et al . Quantitative single-cell RNA-seq with unique molecular identifiers . Nat Methods . 2014 ; 11 ( 2 ): 163 - 6 .

Hochgerner H , Lönnerberg P , Hodge R , Mikes J , Heskol A , Hubschle H , et al . STRT-seq-2i: dual-index 5' single cell and nucleus RNA-seq on an addressable microwell array . Sci Rep . 2017 ; 7 ( 1 ): 16327 .

Fan HC , Fu GK , Fodor SP . Expression profiling. Combinatorial labeling of single cells for gene expression cytometry . Science . 2015 ; 347 ( 6222 ): 1258367 .

Shum EY , Walczak EM , Chang C , Fan HC . Quantitation of mRNA transcripts and proteins using the BD Rhapsody™ single-cell analysis system . Adv Exp Med Biol . 2019 ; 1129 : 63 - 79 .

Rosenberg AB , Roco CM , Muscat RA , Kuchina A , Sample P , Yao Z , et al . Single-cell profiling of the developing mouse brain and spinal cord with split-pool barcoding . Science . 2018 ; 360 ( 6385 ): 176 - 82 .

Fan J , Lee HO , Lee S , Ryu DE , Lee S , Xue C , et al . Linking transcriptional and genetic tumor heterogeneity through allele analysis of single-cell RNA-seq data . Genome Res . 2018 ; 28 ( 8 ): 1217 - 27 .

Laks E , McPherson A , Zahn H , Lai D , Steif A , Brimhall J , et al . Clonal decomposition and DNA replication states defined by scaled single-cell genome sequencing . Cell . 2019 ; 179 ( 5 ): 1207-21.e22 .

Liu L , Chen D , Wang J , Chen J . Advances of single-cell protein analysis . Cells . 2020 ; 9 ( 5 ): 1271 .

Shema E , Bernstein BE , Buenrostro JD . Single-cell and single-molecule epigenomics to uncover genome regulation at unprecedented resolution . Nat Genet . 2019 ; 51 ( 1 ): 19 - 25 .

Andrews TS , Kiselev VY , McCarthy D , Hemberg M . Tutorial: guidelines for the computational analysis of single-cell RNA sequencing data . Nat Protoc . 2021 ; 16 ( 1 ): 1 - 9 .

Korsunsky I , Millard N , Fan J , Slowikowski K , Zhang F , Wei K , et al . Fast, sensitive and accurate integration of single-cell data with Harmony . Nat Methods . 2019 ; 16 ( 12 ): 1289 - 96 .

Haghverdi L , Lun ATL , Morgan MD , Marioni JC . Batch effects in single-cell RNA-sequencing data are corrected by matching mutual nearest neighbors . Nat Biotechnol . 2018 ; 36 ( 5 ): 421 - 7 .

Hie B , Bryson B , Berger B . Efficient integration of heterogeneous single-cell transcriptomes using Scanorama . Nat Biotechnol . 2019 ; 37 ( 6 ): 685 - 91 .

Tran HTN , Ang KS , Chevrier M , Zhang X , Lee NYS , Goh M , et al . A benchmark of batch-effect correction methods for single-cell RNA sequencing data . Genome Biol . 2020 ; 21 ( 1 ): 12 .

Ringnér M . What is principal component analysis? Nat Biotechnol . 2008 ; 26 ( 3 ): 303 - 4 .

Lin X , Boutros PC . Optimization and expansion of non-negative matrix factorization . BMC Bioinform . 2020 ; 21 ( 1 ): 7 .

Eraslan G , Avsec Ž , Gagneur J , Theis FJ . Deep learning: new computational modelling techniques for genomics . Nat Rev Genet . 2019 ; 20 ( 7 ): 389 - 403 .

Koch FC , Sutton GJ , Voineagu I , Vafaee F . Supervised application of internal validation measures to benchmark dimensionality reduction methods in scRNA-seq data . Brief Bioinform . 2021 ; 22 ( 6 ): bbab304 .

Wu Y , Zhang K . Tools for the analysis of high-dimensional single-cell RNA sequencing data . Nat Rev Nephrol . 2020 ; 16 ( 7 ): 408 - 21 .

Jiang R , Sun T , Song D , Li JJ . Statistics or biology: the zero-inflation controversy about scRNA-seq data . Genome Biol . 2022 ; 23 ( 1 ): 31 .

van Dijk D , Sharma R , Nainys J , Yim K , Kathail P , Carr AJ , et al . Recovering gene interactions from single-cell data using data diffusion . Cell . 2018 ; 174 ( 3 ): 716-29.e27 .

Lin P , Troup M , Ho JW . CIDR: Ultrafast and accurate clustering through imputation for single-cell RNA-seq data . Genome Biol . 2017 ; 18 ( 1 ): 59 .

Li WV , Li JJ . An accurate and robust imputation method scImpute for single-cell RNA-seq data . Nat Commun . 2018 ; 9 ( 1 ): 997 .

St Paul M , Ohashi PS . The roles of CD8 + T cell subsets in antitumor immunity . Trends Cell Biol . 2020 ; 30 ( 9 ): 695 - 704 .

Moeller M , Kershaw MH , Cameron R , Westwood JA , Trapani JA , Smyth MJ , et al . Sustained antigen-specific antitumor recall response mediated by gene-modified CD4 + T helper-1 and CD8 + T cells . Cancer Res . 2007 ; 67 ( 23 ): 11428 - 37 .

Yamanaka K , Clark R , Dowgiert R , Hurwitz D , Shibata M , Rich BE , et al . Expression of interleukin-18 and caspase-1 in cutaneous T-cell lymphoma . Clin Cancer Res . 2006 ; 12 ( 2 ): 376 - 82 .

Lv L , Pan K , Li XD , She KL , Zhao JJ , Wang W , et al . The accumulation and prognosis value of tumor infiltrating IL-17 producing cells in esophageal squamous cell carcinoma . PLoS ONE . 2011 ; 6 ( 3 ): e18219 .

Lai C , August S , Behar R , Polak M , Ardern-Jones M , Theaker J , et al . Characteristics of immunosuppressive regulatory T cells in cutaneous squamous cell carcinomas and role in metastasis . Lancet . 2015 ; 385 ( Suppl 1 ): S59 .

Liénart S , Merceron R , Vanderaa C , Lambert F , Colau D , Stockis J , et al . Structural basis of latent TGF-β1 presentation and activation by GARP on human regulatory T cells . Science . 2018 ; 362 ( 6417 ): 952 - 6 .

Vivier E , Ugolini S , Blaise D , Chabannon C , Brossay L . Targeting natural killer cells and natural killer T cells in cancer . Nat Rev Immunol . 2012 ; 12 ( 4 ): 239 - 52 .

Liu X , Li L , Si F , Huang L , Zhao Y , Zhang C , et al . NK and NKT cells have distinct properties and functions in cancer . Oncogene . 2021 ; 40 ( 27 ): 4521 - 37 .

Munir MT , Kay MK , Kang MH , Rahman MM , Al-Harrasi A , Choudhury M , et al . Tumor-associated macrophages as multifaceted regulators of breast tumor growth . Int J Mol Sci . 2021 ; 22 ( 12 ): 6526 .

Gabrilovich DI , Ostrand-Rosenberg S , Bronte V . Coordinated regulation of myeloid cells by tumours . Nat Rev Immunol . 2012 ; 12 ( 4 ): 253 - 68 .

Fricke I , Gabrilovich DI . Dendritic cells and tumor microenvironment: a dangerous liaison . Immunol Invest . 2006 ; 35 ( 3–4 ): 459 - 83 .

Audsley KM , McDonnell AM , Waithman J . Cross-presenting XCR1 + dendritic cells as targets for cancer immunotherapy . Cells . 2020 ; 9 ( 3 ): 565 .

Chen X , Song E . Turning foes to friends: targeting cancer-associated fibroblasts . Nat Rev Drug Discov . 2019 ; 18 ( 2 ): 99 - 115 .

Bu L , Baba H , Yoshida N , Miyake K , Yasuda T , Uchihara T , et al . Biological heterogeneity and versatility of cancer-associated fibroblasts in the tumor microenvironment . Oncogene . 2019 ; 38 ( 25 ): 4887 - 901 .

Li X , Bu W , Meng L , Liu X , Wang S , Jiang L , et al . CXCL12/CXCR4 pathway orchestrates CSC-like properties by CAF recruited tumor associated macrophage in OSCC . Exp Cell Res . 2019 ; 378 ( 2 ): 131 - 8 .

Hutton C , Heider F , Blanco-Gomez A , Banyard A , Kononov A , Zhang X , et al . Single-cell analysis defines a pancreatic fibroblast lineage that supports anti-tumor immunity . Cancer Cell . 2021 ; 39 ( 9 ): 1227-44.e20 .

Shen P , Fillatreau S . Antibody-independent functions of B cells: a focus on cytokines . Nat Rev Immunol . 2015 ; 15 ( 7 ): 441 - 51 .

Shah S , Divekar AA , Hilchey SP , Cho HM , Newman CL , Shin SU , et al . Increased rejection of primary tumors in mice lacking B cells: inhibition of anti-tumor CTL and TH1 cytokine responses by B cells . Int J Cancer . 2005 ; 117 ( 4 ): 574 - 86 .

Schioppa T , Moore R , Thompson RG , Rosser EC , Kulbe H , Nedospasov S , et al . B regulatory cells and the tumor-promoting actions of TNF-α during squamous carcinogenesis . Proc Natl Acad Sci USA . 2011 ; 108 ( 26 ): 10662 - 7 .

Olkhanud PB , Damdinsuren B , Bodogai M , Gress RE , Sen R , Wejksza K , et al . Tumor-evoked regulatory B cells promote breast cancer metastasis by converting resting CD4 + T cells to T-regulatory cells . Cancer Res . 2011 ; 71 ( 10 ): 3505 - 15 .

Petitprez F , de Reyniès A , Keung EZ , Chen TW , Sun CM , Calderaro J , et al . B cells are associated with survival and immunotherapy response in sarcoma . Nature . 2020 ; 577 ( 7791 ): 556 - 60 .

Cabrita R , Lauss M , Sanna A , Donia M , Skaarup Larsen M , Mitra S , et al . Tertiary lymphoid structures improve immunotherapy and survival in melanoma . Nature . 2020 ; 577 ( 7791 ): 561 - 5 .

Wang B , Zhu J , Pierson E , Ramazzotti D , Batzoglou S . Visualization and analysis of single-cell RNA-seq data by kernel-based similarity learning . Nat Methods . 2017 ; 14 ( 4 ): 414 - 6 .

Kiselev VY , Kirschner K , Schaub MT , Andrews T , Yiu A , Chandra T , et al . SC3: consensus clustering of single-cell RNA-seq data . Nat Methods . 2017 ; 14 ( 5 ): 483 - 6 .

Zhu L , Lei J , Klei L , Devlin B , Roeder K . Semisoft clustering of single-cell data . Proc Natl Acad Sci USA . 2019 ; 116 ( 2 ): 466 - 71 .

Nadif M , Role F . Unsupervised and self-supervised deep learning approaches for biomedical text mining . Brief Bioinform . 2021 ; 22 ( 2 ): 1592 - 603 .

Zeisel A , Muñoz-Manchado AB , Codeluppi S , Lönnerberg P , La Manno G , Juréus A , et al . Brain structure. Cell types in the mouse cortex and hippocampus revealed by single-cell RNA-seq . Science . 2015 ; 347 ( 6226 ): 1138 - 42 .

Kiselev VY , Andrews TS , Hemberg M . Challenges in unsupervised clustering of single-cell RNA-seq data . Nat Rev Genet . 2019 ; 20 ( 5 ): 273 - 82 .

Shao X , Liao J , Lu X , Xue R , Ai N , Fan X . scCATCH: automatic annotation on cell types of clusters from single-cell RNA sequencing data . iScience . 2020 ; 23 ( 3 ): 100882 .

Zhang AW , O'Flanagan C , Chavez EA , Lim JLP , Ceglia N , McPherson A , et al . Probabilistic cell-type assignment of single-cell RNA-seq for tumor microenvironment profiling . Nat Methods . 2019 ; 16 ( 10 ): 1007 - 15 .

Ekiz HA , Conley CJ , Stephens WZ , O'Connell RM . CIPR: a web-based R/shiny app and R package to annotate cell clusters in single cell RNA sequencing experiments . BMC Bioinform . 2020 ; 21 ( 1 ): 191 .

Shao L , Zhu F , Li X . Transfer learning for visual categorization: a survey . IEEE Trans Neural Netw Learn Syst . 2015 ; 26 ( 5 ): 1019 - 34 .

Cahan P , Li H , Morris SA , da Rocha EL , Daley GQ , Collins JJ . Cell Net: network biology applied to stem cell engineering . Cell . 2014 ; 158 ( 4 ): 903 - 15 .

Pliner HA , Shendure J , Trapnell C . Supervised classification enables rapid annotation of cell atlases . Nat Methods . 2019 ; 16 ( 10 ): 983 - 6 .

Kiselev VY , Yiu A , Hemberg M . Scmap: projection of single-cell RNA-seq data across data sets . Nat Methods . 2018 ; 15 ( 5 ): 359 - 62 .

Hu J , Li X , Hu G , Lyu Y , Susztak K , Li M . Iterative transfer learning with neural network for clustering and cell type classification in single-cell RNA-seq analysis . Nat Mach Intell . 2020 ; 2 ( 10 ): 607 - 18 .

Elyada E , Bolisetty M , Laise P , Flynn WF , Courtois ET , Burkhart RA , et al . Cross-species single-cell analysis of pancreatic ductal adenocarcinoma reveals antigen-presenting cancer-associated fibroblasts . Cancer Discov . 2019 ; 9 ( 8 ): 1102 - 23 .

Mei Y , Xiao W , Hu H , Lu G , Chen L , Sun Z , et al . Single-cell analyses reveal suppressive tumor microenvironment of human colorectal cancer . Clin Transl Med . 2021 ; 11 ( 6 ): e422 .

Sebastian A , Hum NR , Martin KA , Gilmore SF , Peran I , Byers SW , et al . Single-cell transcriptomic analysis of tumor-derived fibroblasts and normal tissue-resident fibroblasts reveals fibroblast heterogeneity in breast cancer . Cancers . 2020 ; 12 ( 5 ): 1307 .

Li H , Courtois ET , Sengupta D , Tan Y , Chen KH , Goh JJL , et al . Reference component analysis of single-cell transcriptomes elucidates cellular heterogeneity in human colorectal tumors . Nat Genet . 2017 ; 49 ( 5 ): 708 - 18 .

Bartoschek M , Oskolkov N , Bocci M , Lövrot J , Larsson C , Sommarin M , et al . Spatially and functionally distinct subclasses of breast cancer-associated fibroblasts revealed by single cell RNA sequencing . Nat Commun . 2018 ; 9 ( 1 ): 5150 .

Azizi E , Carr AJ , Plitas G , Cornish AE , Konopacki C , Prabhakaran S , et al . Single-cell map of diverse immune phenotypes in the breast tumor microenvironment . Cell . 2018 ; 174 ( 5 ): 1293-308.e36 .

Cheng S , Li Z , Gao R , Xing B , Gao Y , Yang Y , et al . A pan-cancer single-cell transcriptional atlas of tumor infiltrating myeloid cells . Cell . 2021 ; 184 ( 3 ): 792 - 809 .

Zheng L , Qin S , Si W , Wang A , Xing B , Gao R , et al . Pan-cancer single-cell landscape of tumor-infiltrating T cells . Science . 2021 ; 374 ( 6574 ): abe6474 .

Durante MA , Rodriguez DA , Kurtenbach S , Kuznetsov JN , Sanchez MI , Decatur CL , et al . Single-cell analysis reveals new evolutionary complexity in uveal melanoma . Nat Commun . 2020 ; 11 ( 1 ): 496 .

Zheng C , Zheng L , Yoo JK , Guo H , Zhang Y , Guo X , et al . Landscape of infiltrating T cells in liver cancer revealed by single-cell sequencing . Cell . 2017 ; 169 ( 7 ): 1342-56.e16 .

Zhang L , Yu X , Zheng L , Zhang Y , Li Y , Fang Q , et al . Lineage tracking reveals dynamic relationships of T cells in colorectal cancer . Nature . 2018 ; 564 ( 7735 ): 268 - 72 .

Sathe A , Grimes SM , Lau BT , Chen J , Suarez C , Huang RJ , et al . Single-cell genomic characterization reveals the cellular reprogramming of the gastric tumor microenvironment . Clin Cancer Res . 2020 ; 26 ( 11 ): 2640 - 53 .

Zhang Q , He Y , Luo N , Patel SJ , Han Y , Gao R , et al . Landscape and fynamics of single immune cells in hepatocellular carcinoma . Cell . 2019 ; 179 ( 4 ): 829-45.e20 .

Lavin Y , Kobayashi S , Leader A , Amir ED , Elefant N , Bigenwald C , et al . Innate immune landscape in early lung adenocarcinoma by paired single-cell analyses . Cell . 2017 ; 169 ( 4 ): 750-65.e17 .

Chung W , Eum HH , Lee HO , Lee KM , Lee HB , Kim KT , et al . Single-cell RNA-seq enables comprehensive tumour and immune cell profiling in primary breast cancer . Nat Commun . 2017 ; 8 : 15081 .

Cao J , Spielmann M , Qiu X , Huang X , Ibrahim DM , Hill AJ , et al . The single-cell transcriptional landscape of mammalian organogenesis . Nature . 2019 ; 566 ( 7745 ): 496 - 502 .

Wei J , Zhou T , Zhang X , Tian T . DTFLOW: inference and visualization of single-cell pseudotime trajectory using diffusion propagation . Genom Proteom Bioinform . 2021 ; 19 : 306 - 18 .

Haghverdi L , Büttner M , Wolf FA , Buettner F , Theis FJ . Diffusion pseudotime robustly reconstructs lineage branching . Nat Methods . 2016 ; 13 ( 10 ): 845 - 8 .

Cannoodt R , Saelens W , Sichien D , Tavernier S , Janssens S , Guilliams M , et al . SCORPIUS improves trajectory inference and identifies novel modules in dendritic cell development . 2016 . https://doi.org/10.1101/079509 https://doi.org/10.1101/079509 .

Ji Z , Ji H . TSCAN: pseudo-time reconstruction and evaluation in singlecell RNA-seq analysis . Nucleic Acids Res . 2016 ; 44 ( 13 ): e117 .

Chen J , Rénia L , Ginhoux F . Constructing cell lineages from single-cell transcriptomes . Mol Aspects Med . 2018 ; 59 : 95 - 113 .

Lambrechts D , Wauters E , Boeckx B , Aibar S , Nittner D , Burton O , et al . Phenotype molding of stromal cells in the lung tumor microenvironment . Nat Med . 2018 ; 24 ( 8 ): 1277 - 89 .

Tirosh I , Izar B , Prakadan SM , Wadsworth MH 2nd , Treacy D , Trombetta JJ , et al . Dissecting the multicellular ecosystem of metastatic melanoma by single-cell RNA-seq . Science . 2016 ; 352 ( 6282 ): 189 - 96 .

van der Leun AM , Thommen DS , Schumacher TN . CD8 + T cell states in human cancer: insights from single-cell analysis . Nat Rev Cancer . 2020 ; 20 ( 4 ): 218 - 32 .

Guo X , Zhang Y , Zheng L , Zheng C , Song J , Zhang Q , et al . Global characterization of T cells in non-small-cell lung cancer by single-cell sequencing . Nat Med . 2018 ; 24 ( 7 ): 978 - 85 .

Kim N , Kim HK , Lee K , Hong Y , Cho JH , Choi JW , et al . Single-cell RNA sequencing demonstrates the molecular and cellular reprogramming of metastatic lung adenocarcinoma . Nat Commun . 2020 ; 11 ( 1 ): 2285 .

Luo H , Xia X , Kim GD , Liu Y , Xue Z , Zhang L , et al . Characterizing dedifferentiation of thyroid cancer by integrated analysis . Sci Adv . 2021 ; 7 ( 31 ): eabf3657 .

Finlay DB , Duffull SB , Glass M . 100 years of modelling ligand-receptor binding and response: a focus on GPCRs . Br J Pharmacol . 2020 ; 177 ( 7 ): 1472 - 84 .

Wang Y , Wang R , Zhang S , Song S , Wang L . iTALK: an R package to characterize and illustrate intercellular communication . 2019 . https://doi.org/10.1101/507871 https://doi.org/10.1101/507871 .

Cillo AR , Kürten CHL , Tabib T , Qi Z , Onkar S , Wang T , et al . Immune landscape of viral- and carcinogen-driven head and neck cancer . Immunity . 2020 ; 52 ( 1 ): 183-99.e9 .

Efremova M , Vento-Tormo M , Teichmann SA , Vento-Tormo R . Cell PhoneDB: inferring cell-cell communication from combined expression of multi-subunit ligand-receptor complexes . Nat Protoc . 2020 ; 15 ( 4 ): 1484 - 506 .

Browaeys R , Saelens W , Saeys Y . NicheNet: modeling intercellular communication by linking ligands to target genes . Nat Methods . 2020 ; 17 ( 2 ): 159 - 62 .

Ma F , Zhang S , Song L , Wang B , Wei L , Zhang F . Applications and analytical tools of cell communication based on ligand-receptor interactions at single cell level . Cell Biosci . 2021 ; 11 ( 1 ): 121 .

Shao X , Lu X , Liao J , Chen H , Fan X . New avenues for systematically inferring cell-cell communication: through single-cell transcriptomics data . Protein Cell . 2020 ; 11 ( 12 ): 866 - 80 .

Galon J , Bruni D . Tumor immunology and tumor evolution: intertwined histories . Immunity . 2020 ; 52 ( 1 ): 55 - 81 .

Nickerson NK , Mill CP , Wu HJ , Riese DJ 2nd , Foley J . Autocrine-derived epidermal growth factor receptor ligands contribute to recruitment of tumor-associated macrophage and growth of basal breast cancer cells in vivo . Oncol Res . 2013 ; 20 ( 7 ): 303 - 17 .

Zhao X , Li H , Lyu S , Zhai J , Ji Z , Zhang Z , et al . Single-cell transcriptomics reveals heterogeneous progression and EGFR activation in pancreatic adenosquamous carcinoma . Int J Biol Sci . 2021 ; 17 ( 10 ): 2590 - 605 .

Hara T , Chanoch-Myers R , Mathewson ND , Myskiw C , Atta L , Bussema L , et al . Interactions between cancer cells and immune cells drive transitions to mesenchymal-like states in glioblastoma . Cancer Cell . 2021 ; 39 ( 6 ): 779-92.e11 .

Steele NG , Carpenter ES , Kemp SB , Sirihorachai V , The S , Delrosario L , et al . Multimodal mapping of the tumor and peripheral blood immune landscape in human pancreatic cancer . Nat Cancer . 2020 ; 1 ( 11 ): 1097 - 112 .

Jin S , Li R , Chen MY , Yu C , Tang LQ , Liu YM , et al . Single-cell transcriptomic analysis defines the interplay between tumor cells, viral infection, and the microenvironment in nasopharyngeal carcinoma . Cell Res . 2020 ; 30 ( 11 ): 950 - 65 .

Li X , Sun Z , Peng G , Xiao Y , Guo J , Wu B , et al . Single-cell RNA sequencing reveals a pro-invasive cancer-associated fibroblast subgroup associated with poor clinical outcomes in patients with gastric cancer . Theranostics . 2022 ; 12 ( 2 ): 620 - 38 .

Chen YP , Yin JH , Li WF , Li HJ , Chen DP , Zhang CJ , et al . Single-cell transcriptomics reveals regulators underlying immune cell diversity and immune subtypes associated with prognosis in nasopharyngeal carcinoma . Cell Res . 2020 ; 30 ( 11 ): 1024 - 42 .

Böttcher JP , Bonavita E , Chakravarty P , Blees H , Cabeza-Cabrerizo M , Sammicheli S , et al . NK cells stimulate recruitment of cDC1 into the tumor microenvironment promoting cancer immune control . Cell . 2018 ; 172 ( 5 ): 1022-37.e14 .

Ren X , Zhong G , Zhang Q , Zhang L , Sun Y , Zhang Z . Reconstruction of cell spatial organization from single-cell RNA sequencing data based on ligand-receptor mediated self-assembly . Cell Res . 2020 ; 30 ( 9 ): 763 - 78 .

Giladi A , Cohen M , Medaglia C , Baran Y , Li B , Zada M , et al . Dissecting cellular crosstalk by sequencing physically interacting cells . Nat Biotechnol . 2020 ; 38 ( 5 ): 629 - 37 .

Rao A , Barkley D , Franca GS , Yanai I . Exploring tissue architecture using spatial transcriptomics . Nature . 2021 ; 596 ( 7871 ): 211 - 20 .

Saviano A , Henderson NC , Baumert TF . Single-cell genomics and spatial transcriptomics: discovery of novel cell states and cellular interactions in liver physiology and disease biology . J Hepatol . 2020 ; 73 ( 5 ): 1219 - 30 .

Longo SK , Guo MG , Ji AL , Khavari PA . Integrating single-cell and spatial transcriptomics to elucidate intercellular tissue dynamics . Nat Rev Genet . 2021 ; 22 ( 10 ): 627 - 44 .

Stickels RR , Murray E , Kumar P , Li J , Marshall JL , di Bella DJ , et al . Highly sensitive spatial transcriptomics at near-cellular resolution with SlideseqV2 . Nat Biotechnol . 2021 ; 39 ( 3 ): 313 - 9 .

Cho CS , Xi J , Si Y , Park SR , Hsu JE , Kim M , et al . Microscopic examination of spatial transcriptome using Seq-Scope . Cell . 2021 ; 184 ( 13 ): 3559-72.e22 .

Vistain LF , Tay S . Single-cell proteomics . Trends Biochem Sci . 2021 ; 46 ( 8 ): 661 - 72 .

Nam AS , Chaligne R , Landau DA . Integrating genetic and nongenetic determinants of cancer evolution by single-cell multi-omics . Nat Rev Genet . 2021 ; 22 ( 1 ): 3 - 18 .

Galon J , Mlecnik B , Bindea G , Angell HK , Berger A , Lagorce C , et al . Towards the introduction of the “Immunoscore” in the classification of malignant tumours . J Pathol . 2014 ; 232 ( 2 ): 199 - 209 .

Jiang Y , Zhang Q , Hu Y , Li T , Yu J , Zhao L , et al . ImmunoScore signature: a prognostic and predictive tool in gastric cancer . Ann Surg . 2018 ; 267 ( 3 ): 504 - 13 .

Sun Y , Wu L , Zhong Y , Zhou K , Hou Y , Wang Z , et al . Single-cell landscape of the ecosystem in early-relapse hepatocellular carcinoma . Cell . 2021 ; 184 ( 2 ): 404 - 21 .

Zhao QY , Liu LP , Lu L , Gui R , Luo YW . A novel intercellular communication-associated gene signature for prognostic prediction and clinical value in patients with lung adenocarcinoma . Front Genet . 2021 ; 12 : 702424 .

Jiang YQ , Wang ZX , Zhong M , Shen LJ , Han X , Zou X , et al . Investigating mechanisms of response or resistance to immune checkpoint inhibitors by analyzing cell-cell communications in tumors before and after programmed cell death-1 (PD-1) targeted therapy: an integrative analysis using single-cell RNA and bulk-RNA sequencing data . Oncoimmunology . 2021 ; 10 ( 1 ): 1908010 .

Lee HW , Chung W , Lee HO , Jeong DE , Jo A , Lim JE , et al . Single-cell RNA sequencing reveals the tumor microenvironment and facilitates strategic choices to circumvent treatment failure in a chemorefractory bladder cancer patient . Genome Med . 2020 ; 12 ( 1 ): 47 .

Loeuillard E , Yang J , Buckarma E , Wang J , Liu Y , Conboy C , et al . Targeting tumor-associated macrophages and granulocytic myeloidderived suppressor cells augments PD-1 blockade in cholangiocarcinoma . J Clin Invest . 2020 ; 130 ( 10 ): 5380 - 96 .

Deng W , Ma Y , Su Z , Liu Y , Liang P , Huang C , et al . Single-cell RNAsequencing analyses identify heterogeneity of CD8 + T cell subpopulations and novel therapy targets in melanoma . Mol Ther Oncolytics . 2021 ; 20 : 105 - 18 .

Mao X , Yang X , Chen X , Yu S , Yu S , Zhang B , et al . Single-cell transcriptome analysis revealed the heterogeneity and microenvironment of gastrointestinal stromal tumors . Cancer Sci . 2021 ; 112 ( 3 ): 1262 - 74 .

Obradovic A , Chowdhury N , Haake SM , Ager C , Wang V , Vlahos L , et al . Single-cell protein activity analysis identifies recurrence-associated renal tumor macrophages . Cell . 2021 ; 184 ( 11 ): 2988-3005.e16 .

Molgora M , Esaulova E , Vermi W , Hou J , Chen Y , Luo J , et al . TREM2 modulation remodels the tumor myeloid landscape enhancing anti-PD-1 immunotherapy . Cell . 2020 ; 182 ( 4 ): 886 - 900 .

Zhang M , Yang H , Wan L , Wang Z , Wang H , Ge C , et al . Single-cell transcriptomic architecture and intercellular crosstalk of human intrahepatic cholangiocarcinoma . J Hepatol . 2020 ; 73 ( 5 ): 1118 - 30 .

Ishizuka JJ , Manguso RT , Cheruiyot CK , Bi K , Panda A , Iracheta-Vellve A , et al . Loss of ADAR1 in tumours overcomes resistance to immune checkpoint blockade . Nature . 2019 ; 565 ( 7737 ): 43 - 8 .

Yamashita N , Long M , Fushimi A , Yamamoto M , Hata T , Hagiwara M , et al . MUC1-C integrates activation of the IFN-γ pathway with suppression of the tumor immune microenvironment in triple-negative breast cancer . J Immunother Cancer . 2021 ; 9 ( 1 ): e002115 .

Zhang H , He J , Dai Z , Wang Z , Liang X , He F , et al . PDIA5 is correlated with immune infiltration and predicts poor prognosis in gliomas . Front Immunol . 2021 ; 12 : 628966 .

Lu Y , Zhao Q , Liao JY , Song E , Xia Q , Pan J , et al . Complement signals determine opposite effects of B cells in chemotherapy-induced immunity . Cell . 2020 ; 180 ( 6 ): 1081-97.e24 .

Ni J , Wang X , Stojanovic A , Zhang Q , Wincher M , Bühler L , et al . Single-cell RNA sequencing of tumor-infiltrating NK cells reveals that inhibition of transcription factor HIF-1α unleashes NK cell activity . Immunity . 2020 ; 52 ( 6 ): 1075-87.e8 .

Wang Q , Guldner IH , Golomb SM , Sun L , Harris JA , Lu X , et al . Single-cell profiling guided combinatorial immunotherapy for fast-evolving CDK4/6 inhibitor-resistant HER2-positive breast cancer . Nat Commun . 2019 ; 10 ( 1 ): 3817 .

Lee JJ , Bernard V , Semaan A , Monberg ME , Huang J , Stephens BM , et al . Elucidation of tumor-stromal heterogeneity and the ligand-receptor interactome by single-cell transcriptomics in real-world pancreatic cancer biopsies . Clin Cancer Res . 2021 ; 27 ( 21 ): 5912 - 21 .

Sharma A , Seow JJW , Dutertre CA , Pai R , Bleriot C , Mishra A , et al . Onco-fetal reprogramming of endothelial cells drives immunosuppressive macrophages in hepatocellular carcinoma . Cell . 2020 ; 183 ( 2 ): 377 - 94 .

Nagaoka K , Shirai M , Taniguchi K , Hosoi A , Sun C , Kobayashi Y , et al . Deep immunophenotyping at the single-cell level identifies a combination of anti-IL-17 and checkpoint blockade as an effective treatment in a preclinical model of data-guided personalized immunotherapy . J Immunother Cancer . 2020 ; 8 ( 2 ): e001358 .

Aoki T , Chong LC , Takata K , Milne K , Marshall A , Chavez EA , et al . Single-cell profiling reveals the importance of CXCL13/CXCR5 axis biology in lymphocyte-rich classic Hodgkin lymphoma . Proc Natl Acad Sci U S A . 2021 ; 118 ( 41 ): e2105822118 .

Lähnemann D , Köster J , Szczurek E , McCarthy DJ , Hicks SC , Robinson MD , et al . Eleven grand challenges in single-cell data science . Genome Biol . 2020 ; 21 ( 1 ): 31 .

Camp JG , Platt R , Treutlein B . Mapping human cell phenotypes to genotypes with single-cell genomics . Science . 2019 ; 365 ( 6460 ): 1401 - 5 .

Kelsey G , Stegle O , Reik W . Single-cell epigenomics: recording the past and predicting the future . Science . 2017 ; 358 ( 6359 ): 69 - 75 .

Liao J , Lu X , Shao X , Zhu L , Fan X . Uncovering an organ's molecular architecture at single-cell resolution by spatially resolved transcriptomics . Trends Biotechnol . 2021 ; 39 ( 1 ): 43 - 58 .

Guillaumet-Adkins A , Rodríguez-Esteban G , Mereu E , Mendez-Lago M , Jaitin DA , Villanueva A , et al . Single-cell transcriptome conservation in cryopreserved cells and tissues . Genome Biol . 2017 ; 18 ( 1 ): 45 .

Martelotto LG , Baslan T , Kendall J , Geyer FC , Burke KA , Spraggon L , et al . Whole-genome single-cell copy number profiling from formalin-fixed paraffin-embedded samples . Nat Med . 2017 ; 23 ( 3 ): 376 - 85 .

Kim D , Kobayashi T , Voisin B , Jo JH , Sakamoto K , Jin SP , et al . Targeted therapy guided by single-cell transcriptomic analysis in drug-induced hypersensitivity syndrome: a case report . Nat Med . 2020 ; 26 ( 2 ): 236 - 43 .

Stewart CA , Gay CM , Xi Y , Sivajothi S , Sivakamasundari V , Fujimoto J , et al . Single-cell analyses reveal increased intratumoral heterogeneity after the onset of therapy resistance in small-cell lung cancer . Nat Cancer . 2020 ; 1 : 423 - 36 .

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