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Curated Papers > Recent high-impact research on "single-cell sequencing" (IF≥30, last 5 years)

Applications of single-cell sequencing in cancer research: progress and perspectives. ​

Literature Information ​

DOI10.1186/s13045-021-01105-2
PMID34108022
JournalJournal of hematology & oncology
Impact Factor40.4
JCR QuartileQ1
Publication Year2021
Times Cited303
KeywordsCirculating tumor cells, Heterogeneity, Microenvironment, Single-cell sequencing
Literature TypeJournal Article, Research Support, Non-U.S. Gov't, Review
ISSN1756-8722
Pages91
Issue14(1)
AuthorsYalan Lei, Rong Tang, Jin Xu, Wei Wang, Bo Zhang, Jiang Liu, Xianjun Yu, Si Shi

TL;DR ​

This review discusses the transformative impact of single-cell sequencing technologies on cancer research, highlighting their ability to provide detailed insights into tumor heterogeneity, malignant and immune cell landscapes, and the mechanisms driving tumor behavior. The findings suggest that these advancements will enhance diagnostic capabilities, inform targeted therapies, and improve prognostic predictions, ultimately leading to more precise treatment options for cancer patients.

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Circulating tumor cells · Heterogeneity · Microenvironment · Single-cell sequencing

Abstract ​

Single-cell sequencing, including genomics, transcriptomics, epigenomics, proteomics and metabolomics sequencing, is a powerful tool to decipher the cellular and molecular landscape at a single-cell resolution, unlike bulk sequencing, which provides averaged data. The use of single-cell sequencing in cancer research has revolutionized our understanding of the biological characteristics and dynamics within cancer lesions. In this review, we summarize emerging single-cell sequencing technologies and recent cancer research progress obtained by single-cell sequencing, including information related to the landscapes of malignant cells and immune cells, tumor heterogeneity, circulating tumor cells and the underlying mechanisms of tumor biological behaviors. Overall, the prospects of single-cell sequencing in facilitating diagnosis, targeted therapy and prognostic prediction among a spectrum of tumors are bright. In the near future, advances in single-cell sequencing will undoubtedly improve our understanding of the biological characteristics of tumors and highlight potential precise therapeutic targets for patients.

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Primary Questions Addressed ​

  1. How can single-cell sequencing improve our understanding of tumor microenvironments in different cancer types?
  2. What are the challenges and limitations associated with the implementation of single-cell sequencing in clinical settings for cancer diagnosis?
  3. In what ways does single-cell sequencing contribute to the identification of novel therapeutic targets in oncology?
  4. How does single-cell sequencing help in understanding the role of immune cells in the tumor heterogeneity observed in various cancers?
  5. What future advancements in single-cell sequencing technologies could further enhance cancer research and treatment strategies?

Key Findings ​

Research Background and Purpose ​

Single-cell sequencing (SCS) has emerged as a transformative technology in cancer research, enabling the detailed exploration of cellular and molecular heterogeneity at unprecedented resolution. Traditional bulk sequencing methods provide averaged data from heterogeneous cell populations, which can obscure critical insights into tumor biology. This review summarizes recent advancements in single-cell sequencing technologies and their applications in understanding cancer biology, including tumor heterogeneity, immune microenvironments, and the identification of potential therapeutic targets.

Main Methods/Materials/Experimental Design ​

The review details several key single-cell sequencing technologies, including:

  1. Single-Cell RNA Sequencing (scRNA-seq): Allows for the profiling of transcriptomes from individual cells.
  2. Single-Cell DNA Sequencing: Used for analyzing genetic variations at the single-cell level.
  3. Single-Cell Epigenomics: Techniques like ATAC-seq and ChIP-seq provide insights into chromatin accessibility and histone modifications.
  4. Proteomics: Techniques such as mass cytometry enable the analysis of protein expression in single cells.
  5. Multiomics: Integration of various omics data (genomics, transcriptomics, proteomics) for a comprehensive understanding of cellular states.

The sequencing process typically involves:

  • Isolation of single cells
  • RNA extraction and reverse transcription
  • Preamplification and sequencing
  • Data analysis using advanced bioinformatics tools
Mermaid diagram

Key Results and Findings ​

  • Tumor Heterogeneity: SCS has revealed significant intra-tumoral heterogeneity, allowing the identification of distinct subpopulations of cancer cells and their dynamic behaviors during tumor progression.
  • Immune Microenvironment: The technology has provided insights into the immune landscape of tumors, including the characterization of tumor-infiltrating lymphocytes (TILs) and their interactions with cancer cells.
  • Circulating Tumor Cells (CTCs): SCS has improved the understanding of CTCs, their role in metastasis, and their potential as biomarkers for cancer progression and treatment response.
  • Therapeutic Targets: Novel therapeutic targets have been identified through the analysis of single-cell transcriptomic and genomic data, facilitating the development of personalized cancer therapies.

Main Conclusions/Significance/Innovation ​

The advancements in single-cell sequencing technologies represent a significant leap forward in cancer research, offering unprecedented insights into tumor biology. These technologies enhance our understanding of tumor heterogeneity, the immune response, and the mechanisms of drug resistance. The integration of multiomic data holds the potential to revolutionize cancer diagnosis, treatment, and prognosis, paving the way for more precise and effective therapeutic strategies.

Research Limitations and Future Directions ​

Despite its transformative potential, single-cell sequencing faces several limitations:

  • Technical Challenges: Issues such as low sensitivity for rare transcripts and batch effects can complicate data interpretation.
  • Cost and Accessibility: High costs associated with sequencing and data analysis limit widespread application in clinical settings.
  • Data Complexity: The integration of multiomic data requires sophisticated computational methods to unravel complex biological interactions.

Future research should focus on improving the accuracy and sensitivity of sequencing technologies, reducing costs, and developing robust computational frameworks for data analysis. Enhanced understanding of tumor biology through single-cell sequencing can lead to innovative strategies for cancer treatment and management.

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Literatures Citing This Work ​

  1. Analyzing Modern Biomolecules: The Revolution of Nucleic-Acid Sequencing - Review. - Gabriel Dorado;Sergio Gálvez;Teresa E Rosales;Víctor F Vásquez;Pilar Hernández - Biomolecules (2021)
  2. Trends in the Research Into Immune Checkpoint Blockade by Anti-PD1/PDL1 Antibodies in Cancer Immunotherapy: A Bibliometric Study. - Yiting Sun;Liqing Jiang;Ti Wen;Xiaoyu Guo;Xinye Shao;Hui Qu;Xi Chen;Yujia Song;Fang Wang;Xiujuan Qu;Zhi Li - Frontiers in pharmacology (2021)
  3. High-Throughput Strategies for the Discovery of Anticancer Drugs by Targeting Transcriptional Reprogramming. - Lijun Huang;Xiaohong Yi;Xiankuo Yu;Yumei Wang;Chen Zhang;Lixia Qin;Dale Guo;Shiyi Zhou;Guanbin Zhang;Yun Deng;Xilinqiqige Bao;Dong Wang - Frontiers in oncology (2021)
  4. Application of Single-Cell Multi-Omics in Dissecting Cancer Cell Plasticity and Tumor Heterogeneity. - Deshen Pan;Deshui Jia - Frontiers in molecular biosciences (2021)
  5. Tumor Heterogeneity and Consequences for Bladder Cancer Treatment. - Etienne Lavallee;John P Sfakianos;David J Mulholland - Cancers (2021)
  6. Single-Cell Sequencing: Biological Insight and Potential Clinical Implications in Pediatric Leukemia. - Donát Alpár;Bálint Egyed;Csaba Bödör;Gábor T Kovács - Cancers (2021)
  7. Evolution and Targeting of Myeloid Suppressor Cells in Cancer: A Translational Perspective. - Augusto Bleve;Francesca Maria Consonni;Chiara Porta;Valentina Garlatti;Antonio Sica - Cancers (2022)
  8. Integration of liquid biopsy and pharmacogenomics for precision therapy of EGFR mutant and resistant lung cancers. - Jill Kolesar;Spencer Peh;Levin Thomas;Gayathri Baburaj;Nayonika Mukherjee;Raveena Kantamneni;Shirley Lewis;Ananth Pai;Karthik S Udupa;Naveena Kumar An;Vivek M Rangnekar;Mahadev Rao - Molecular cancer (2022)
  9. Single-cell and spatially resolved analysis uncovers cell heterogeneity of breast cancer. - Si-Qing Liu;Zhi-Jie Gao;Juan Wu;Hong-Mei Zheng;Bei Li;Si Sun;Xiang-Yu Meng;Qi Wu - Journal of hematology & oncology (2022)
  10. Distinct outcomes, ABL1 mutation profile, and transcriptome features between p190 and p210 transcripts in adult Philadelphia-positive acute lymphoblastic leukemia in the TKI era. - Ting Shi;Mixue Xie;Li Chen;Wei Yuan;Yungui Wang;Xin Huang;Wanzhuo Xie;Haitao Meng;Yinjun Lou;Wenjuan Yu;Hongyan Tong;Xiujin Ye;Jinyan Huang;Jie Jin;Honghu Zhu - Experimental hematology & oncology (2022)

... (293 more literatures)

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