Table 1 Molecular characterization of circulating tumor cells

Genome

FISH

• CNA

• Reduced experimental time

• Reduced cost

• Allows spatial information

• Limited number of genes

Leversha et al. [27]; Onozato et al. [28]

Targeted DNA sequencing

• Point mutations from a small to a moderate set of genes

• High sensitivity

• Reduced cost

• Limited number of genes

De Luca et al. [29]

Single-cell exome sequencing

• CNA

• Point mutations from exome regions

• Comprehensive profiling in exon regions

• WGA required

• High dropout levels

Lohr et al. [12]; Ni et al. [30]

Single-cell whole-genome sequencing

• CNA

• DNA rearrangements

• Point mutations

• Comprehensive profiling of the genome

• WGA required

• False-positive errors introduced during WGA

• High allele dropout levels

• Non-uniform coverage

• Allelic imbalance introduced during WGA

Carter et al. [31]; Heitzer et al. [32]

Transcriptome

qRT-PCR

• Expression level of a moderate set of genes

• High sensitivity for genes expressed at low levels

• Reduced experimental time

• Reduced cost

• Limited number of transcripts

• Requires pre-amplification of targeted cDNA

Gorges et al. [33]

RNA in situ hybridization

• Expression level of a set of genes

• High sensitivity for genes expressed at low levels

• Allows targeted or comprehensive profiling

• Reduced experimental time

• Allows spatial information

• Reduced cost

• Limited to transcripts that are included in the probe design

Gasch et al. [34]; Yu et al. [35]; Ortega et al. [36]

Single-cell RNA sequencing

• Whole-transcriptome expression

• CNA

• Point mutations from cDNA regions

• Comprehensive profiling

• Allows alternative splicing analysis

• Allows discovery of new annotated transcripts

• Low success rate of WTA

• Amplification bias introduced during WTA

• Low sensitivity for transcripts with low abundance

Aceto et al. [21]; Ting et al. [37]; Miyamoto et al. [38]

Epigenome

Targeted

• Epigenetic marks

• High sensitivity

• Reduced cost

• Reduced experimental time

• Limited number of genes

Pixberg et al. [39]

Whole-genome bisulfite sequencing

• Epigenetic marks from the whole genome

• Comprehensive profiling

• WGA required

• High dropout levels

Gkountela et al. [40]

ATAC-seq

• Chromatin accessibility

• Comprehensive profiling

• Low coverage data

• High dropout levels

Klotz et al. [41]

Proteome

Immunostaining

• Protein levels of a small set of targets

• Reduced cost

• Reduced experimental time

• Limited number of proteins

• Relies on antibody specificity and proper controls

Paoletti et al. [42]

Single-cell western blot

• Up to eight different targets

• High specificity

• Reduced cost

• Reduced experimental time

• Limited number of proteins

Sinkala et al. [43]

Single-cell mass cytometry

• Up to 40 different targets

• Reduced cost

• Reduced experimental time

• Limited number of proteins

Gerdtsson et al. [44]

Bulk mass spectroscopy

• Whole proteome levels

• Comprehensive profiling

• Limited number of proteins

• Low sensitivity for features with low abundance

Jordan et al. [45]

Single-cell mass spectroscopy

• Whole proteome levels

• Comprehensive profiling

• Not well established yet

Abouleila et al. [19]

Single-cell multi-omics

Genome and transcriptome

• CNA

• DNA rearrangements

• Point mutations from the whole genome or exome regions

• Whole-transcriptome expression

• Allows quantitative trait loci analysis

• Yields lower quality data compared to individual protocols

Szczerba et al. [46]