Single-Cell Transcriptomics for Unlocking Personalized Cancer Immunotherapy: Toward Targeting the Origin of Tumor Development Immunogenicity
Abstract
:Simple Summary
Abstract
1. Introduction
2. Current Status of Cancer Immunotherapy and Cancer Personalized Immunotherapy
3. Individual Origin of Tumor Development: Concepts and Facts
4. Single-Cell Transcriptomics for Detecting and Targeting the Immunogenicity of OTD
5. Future Steps
6. Conclusions
Author Contributions
Funding
Conflicts of Interest
References
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Method | Technology Name | Minimum Cells | Developer Company | Advantages | Disadvantages | Cost | Library Preparation Time | Sequencing Depth | Applications | Platforms for Analysis |
---|---|---|---|---|---|---|---|---|---|---|
Droplet-based | Drop-seq | 1000 | Macosko Lab | High throughput, low cost per cell, UMI-based quantification | Low coverage, limited information on isoforms, SNPs and VDJ rearrangements, cell doublets may occur | USD 0.06–0.2 per cell | 1–2 days | 0.1–0.5 million reads per cell | Cell type identification, gene expression profiling, trajectory inference | Seurat, Monocle, Scanpy |
inDrop | 1000 | Klein Lab and Shalek Lab | High throughput, low cost per cell, UMI-based quantification, flexible barcode design | Low coverage, limited information on isoforms, SNPs and VDJ rearrangements, cell doublets may occur | USD 0.06–0.2 per cell | 1–2 days | 0.1–0.5 million reads per cell | Cell type identification, gene expression profiling, trajectory inference | Seurat, Monocle, Scanpy | |
Chromium 10× | 500–10,000 | 10× Genomics | High throughput, low cost per cell, UMI-based quantification, multiple applications (e.g., immune profiling, spatial transcriptomics) | Low coverage, limited information on isoforms, SNPs and VDJ rearrangements, cell doublets may occur | USD 0.55–1.1 per cell | 1–2 days | 0.5–2 million reads per cell | Cell type identification, gene expression profiling, trajectory inference, immune repertoire analysis, spatial transcriptomics | Cell Ranger, Seurat, Monocle, Scanpy | |
Full-length | Smart-seq2 (SS2) | 1–96 | Picelli Lab and Sandberg Lab | High coverage, detection of isoforms, SNPs and VDJ rearrangements, low technical noise | Low throughput, high cost per cell, no UMI-based quantification | USD 35–70 per cell | 2–3 days | 5–20 million reads per cell | Isoform detection and quantification, SNP calling and phasing, VDJ rearrangement analysis | Cufflinks, DESeq2, edgeR |
Smart-seq3 (SS3) | 1–96 | Sandberg Lab and Linnarsson Lab | High coverage, detection of isoforms, SNPs and VDJ rearrangements, low technical noise, UMI-based quantification | Low throughput, high cost per cell, requires fine-tuning to balance internal and UMI-containing reads | USD 35–70 per cell (estimated) | 2–3 days | 5–20 million reads per cell | Isoform detection and quantification, SNP calling and phasing, VDJ rearrangement analysis | Cufflinks, DESeq2, edgeR | |
FLASH-seq (FS) | 1–96 | Picelli Lab | High coverage, detection of isoforms, SNPs and VDJ rearrangements, low technical noise, UMI-based quantification with reduced strand-invasion artifacts, fast and simple protocol | Low throughput, high cost per cell | USD 35–70 per cell (estimated) | <4.5 h | 5–20 million reads per cell | Isoform detection and quantification, SNP calling and phasing, VDJ rearrangement analysis | Cufflinks, DESeq2, edgeR |
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Khodayari, S.; Khodayari, H.; Saeedi, E.; Mahmoodzadeh, H.; Sadrkhah, A.; Nayernia, K. Single-Cell Transcriptomics for Unlocking Personalized Cancer Immunotherapy: Toward Targeting the Origin of Tumor Development Immunogenicity. Cancers 2023, 15, 3615. https://doi.org/10.3390/cancers15143615
Khodayari S, Khodayari H, Saeedi E, Mahmoodzadeh H, Sadrkhah A, Nayernia K. Single-Cell Transcriptomics for Unlocking Personalized Cancer Immunotherapy: Toward Targeting the Origin of Tumor Development Immunogenicity. Cancers. 2023; 15(14):3615. https://doi.org/10.3390/cancers15143615
Chicago/Turabian StyleKhodayari, Saeed, Hamid Khodayari, Elnaz Saeedi, Habibollah Mahmoodzadeh, Alireza Sadrkhah, and Karim Nayernia. 2023. "Single-Cell Transcriptomics for Unlocking Personalized Cancer Immunotherapy: Toward Targeting the Origin of Tumor Development Immunogenicity" Cancers 15, no. 14: 3615. https://doi.org/10.3390/cancers15143615