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Published on: February 8, 2018
Pan-Cancer Analyses Refine the Single-Cell Portrait of Tumor-Infiltrating Dendritic Cells
Tianyi Ma1,2,3, Xiaojing Chu1,4, Jinyu Wang1
1Changping Laboratory, Beijing, China.
Abstract:
Dendritic cells (DC) are pivotal orchestrators of antitumor immunity. DC-based antitumor treatments are being actively developed, but effective clinical responses have not yet been achieved. Further exploration of DC heterogeneity in the tumor microenvironment and across cancer types could provide insights for developing DC-based immunotherapies. In this study, we integrated single-cell RNA sequencing data of DCs from more than 2,500 samples across 33 cancer types and established a comprehensive blueprint of human DCs. Several rare subsets of DCs infiltrated the tumors, including AXL+SIGLEC6+ DCs and Langerhans cell-like DCs, and displayed functional potentials marked with distinct transcriptomic characteristics. Computational analyses demonstrated that the Langerhans cell-like subset could be an additional cellular origin of tumor-enriched LAMP3+ DCs and that distinct cellular origins are associated with the pleiotropic functional potentials of LAMP3+ DCs. Furthermore, this DC atlas enabled the development of a machine learning model to guide DC annotation for subsequent single-cell analysis and prioritization of a valuable target for enhancing antitumor DC vaccination. This integrative resource provides a panoramic view to unravel the complexity of tumor-infiltrating DCs and offers valuable insights for developing therapies targeting DCs.
Significance:
The comprehensive dissection of tumor-infiltrating dendritic cells redefined cell subsets with different regulations, tissue preferences, and functional potentials and provided an atlas as a rich resource with promising applications. This article is part of a special series: Driving Cancer Discoveries with Computational Research, Data Science, and Machine Learning/AI.
Insights
This study maps human dendritic cells (DCs) in tumors, revealing rare subsets like Langerhans cell-like DCs. This DC atlas aids in developing targeted immunotherapies for better anti-tumor responses.
Area of Science:
- Immunology
- Cancer Biology
- Single-cell Genomics
Background:
- Dendritic cells (DCs) are crucial for anti-tumor immunity, but current DC-based therapies have limited clinical success.
- Understanding DC heterogeneity within the tumor microenvironment (TME) is key to improving immunotherapies.
Purpose of the Study:
- To create a comprehensive human DC atlas by integrating single-cell RNA sequencing data from diverse cancer types.
- To identify and characterize rare DC subsets within tumors and explore their functional significance.
- To develop computational tools for DC analysis and identify targets for enhanced DC vaccination.
Main Methods:
- Integrated single-cell RNA sequencing data from over 2,500 tumor samples across 33 cancer types.
- Performed computational analyses to identify DC subsets, their origins, and transcriptomic characteristics.
- Developed a machine learning model for DC annotation and target identification.
Main Results:
- Established a comprehensive blueprint of human tumor-infiltrating dendritic cells.
- Identified rare DC subsets, including AXL+SIGLEC6+ (AS) DCs and Langerhans cell (LC)-like DCs, with distinct transcriptomic profiles.
- Demonstrated that LC-like DCs can be a cellular origin for LAMP3+ DCs, linking cellular origin to functional potential.
Conclusions:
- The DC atlas provides a detailed view of tumor-infiltrating DC complexity.
- Insights into DC heterogeneity and origins can guide the development of novel DC-based anti-tumor immunotherapies.
- The developed machine learning model and identified targets offer potential for enhancing anti-tumor DC vaccination strategies.
