Introduction
Single-cell sequencing technologies
Isolation of single cells
Whole-genome amplification
Method | Enzyme used | Application | Genome coverage | SNV detection | CNV detection | Amplification bias |
---|---|---|---|---|---|---|
DOP-PCR |
Taq DNA polymerase | Single nucleus sequencing | Low (~10%) | High false negative and false positive rates | Useful | High (102–106 fold) |
MDA | φ29 DNA polymerase; Bst DNA polymerase | Single nucleus exome sequencing | Moderate (>70%) | Useful but has a high false negative rate due to amplification bias | Not accurate | Moderate (3- to 4-fold) |
MALBAC |
Bst DNA polymerase | Single-cell genome/exome sequencing | High (>90%) | High false positive rate due to low fidelity | Accurate | Low |
Whole-transcriptome amplification
Method | Reverse-transcription enzyme used | WTA method | Reverse-transcript size | Position bias |
---|---|---|---|---|
Tang’s method | Reverse transcriptase | Poly-A tailing | 0.5–3.0 kb | 3′-end |
Smart-seq/Smart-seq2 | M-MLV RT | Template-switching; locked nucleic acid in Smart-seq2 | Full-length | Low 3′-end |
Quartz-seq | Reverse transcriptase | Poly-A tailing; suppression PCR | 0.4–4.0 kb | 3′-end |
CEL-seq/CEL-seq2 | In vitro transcription | Poly-A tailing; barcoding | 3′-end only | High 3′-end |
STRT | Reverse transcriptase | Template-switching; barcoding | Full-length, only detect 5′-end | 5′-end |
Sequencing considerations
Data analysis
Single-cell sequencing of tumor cells
Cancer stem cells
Primary tumors
Breast cancer
Tumor | Tissue source (number of cells, patients/cell lines) | Data type | Results | Reference |
---|---|---|---|---|
Breast
| ||||
TNBC (200, 2) | CNV | TNBC displays punctuated clonal evolution where CNVs are shared across single cells | [6] | |
TNBC (66, 1), ER + HER2- (113, 1) | CNV and SNV | TNBC has a higher mutation rate than ER + HER2- tumors or normal cells; CNVs are an early event in tumorigenesis | [39] | |
TNBC (1000, 12) | CNV | Supports theory of punctuated clonal evolution | [40] | |
ER + (332, 2) | CNV | Supports theory of punctuated clonal evolution | [41] | |
MDA-MB-231 and CN34 cell lines (44, 2) | RNA-seq | Rare cell populations with highly variable gene expression differences have increased metastatic capacity and ability to survive treatment | [42] | |
MDA-MB-231 cell line (15, 1) | RNA-seq | Development of drug-resistance to paclitaxel is associated with unique mutations; gene expression changes not detectable in bulk tumors | [43] | |
HER2 + (8, 2)a
| RNA-seq | 404 genes differentially expressed in breast cancer stem cells, including CA12 which may be prognostic | [37] | |
Lung
| ||||
Lung adenocarcinoma PDX (34, 1) | RNA-seq | Gene expression profiling identifies a subpopulation of PDX cells with poor prognosis | [44] | |
Lung adenocarcinoma PDX (34, 1) | RNA-seq and WES | Identification of a subpopulation of KRAS+/low risk cells that were drug resistant | [45] | |
LC2/ad and LC2/ad-R lung cancer cell lines (336, 7) | RNA-seq | Increased plasticity in gene expression among cells is associated with vandetanib resistance | [46] | |
Brain
| ||||
EGFR amplified glioblastomas (50-60, 2) | CNV | Patterns of EGFR mutations differ among cells; heterogeneity may contribute to therapy resistance | [48] | |
Glioblastomas (430, 5)a
| RNA-seq | Variable EGFR CNVs and cells reflecting different subtypes are present in primary glioblastomas | [38] | |
Colon
| ||||
Colon tumor and normal adjacent cells (63, 1) | SNV | Different mutational profiles found in two sub-clonal populations of cells may suggest bi-clonal origins | [49] | |
HCT116 cell line (96, 1) | RNA-seq | SCS reveals cryptic mutations not detected in bulk tumor | [50] | |
Bladder
| ||||
Muscle-invasive bladder transitional-cell carcinoma (66, 1) | SNV | Cell-lineage-specific mutations may initiate carcinogenesis and drive cancer progression | [51] | |
Squamous cell carcinoma of the bladder (75, 1) | RNA-seq | Cell-to-cell heterogeneity in the expression of genes within cancer-related pathways may affect outcomes | [52] | |
Kidney
| ||||
Clear cell renal cell carcinoma (20, 1) | SNV | ccRCC more genetically complex than predicted based on whole-tumor sequencing | [53] | |
ccRCC primary carcinoma and paired metastasis propagated in PDX model (116, 1) | RNA-seq | Differential expression of targetable genes between cells supports multi-agent treatment strategy | [54] | |
Blood
| ||||
Secondary AML (36, 3) | SNV | SCS identifies genomic complexity not seen in whole-tumor analysis and resolves clonal relationships | [55] | |
Pediatric ALL (1479, 6) | SNV | CNVs precede somatic mutations; diversity of driver mutations affects clonal fitness | [56] | |
B-cell ALL (276, 3) | CNV | CNVs not detected in bulk tumors are observed in single cells; CNVs develop in response to environmental stressors | [57] | |
JAK2-negative myeloproliferative neoplasm (58, 1) | SNV | Lack of identifiable sub-clones suggests tumor is monoclonal, but large genetic distances exist between cells | [58] |
Adenocarcinoma of the lung
Glioblastoma
Colon cancer
Urinary system cancers
Hematopoietic tumors
Circulating and disseminated tumor cells
Cell type | Tumor type (number of cells, patients) | Data type | Results | Reference |
---|---|---|---|---|
CTCs
| ||||
Colorectal (37, 6) | Targeted sequencing | Most mutations in CTCs are present in sub-clonal populations of the primary tumor or metastases, but some mutations are exclusive to CTCs | [67] | |
Lung (68, 11) | WES/WGS | CNVs in CTCs are dissimilar between cancer subtypes; patterns of SNVs and INDELs in CTCs change during treatment, but CNVs remain constant | [68] | |
Prostate (99, 1) | WGS | SNVs and structural variations in CTCs are also present in primary tumors or metastases | [69] | |
Prostate (25, 2) | WES | The majority of mutations in CTCs are also present in the primary tumor and metastases | [70] | |
Breast (14, 4) | Targeted sequencing | High levels of heterogeneity in CTCs within and between patients as well as before and after treatment | [71] | |
Breast (115, 18) | Targeted sequencing | In some patients heterogeneity of PIK3CA mutations is observed among CTCs and between CTCs and the primary tumor | [72] | |
Breast (11, 2) | Targeted sequencing | Some CTCs carry the same TP53 mutation(s) as the primary carcinoma, other CTCs carry different mutations | [73] | |
Breast (185, 12) | Targeted sequencing | CTCs show genetic heterogeneity of PIK3CA mutations over time and discordance between DTCs and metastases | [74] | |
Breast (22, 2) | RNA-seq | HER2 + CTCs may arise in HER2- breast cancer patients and may contribute to progression and drug resistance | [75] | |
Prostate (77, 13) | RNA-seq | Heterogeneity in expression of androgen receptor mutations between CTCs within patients may influence treatment response | [77] | |
DTCs
| ||||
Breast (24, 1) | Targeted sequencing | DTCs show genetic discordance of PIK3CA mutations versus CTCs and metastases; mutations are stable during cell culture | [74] | |
Breast (2, 2) | WGS | In one patient, DTC was highly concordant with the non-complex primary tumor; DTC from complex primary tumor showed greater genetic divergence | [82] | |
Neuroblastoma (144, 10) | Targeted sequencing | Mutational status for the ALK gene is concordant between the primary tumor and DTCs for all patients | [84] | |
Breast (63, 6) | WGS | Some DTCs originate from clones in the primary carcinoma, other DTCs arise from LN metastases | [85] |