Predicting therapy response by analysis of metastasis founder cells: emerging perspectives for personalized tumor therapy

Figures & data

Table 1. Overview of studies reporting established CTC-derived preclinical models from advanced patients

Type of cancer	Type of culture	Enrichment method	Expansion Technology	Number of permanent CTC models	Success rate (models per cases)	Reference
Breast cancer	in vivo	RosetteSep/flow cytometry sorted	Transplantation in femoral medullar cavity	N/A	3/110 (3%)	Baccelli et al., 2013 [54]
Breast cancer	in vitro	Flow cytometry sorted	2D cell culture	3	3/8 (37.5%)	Zhang et al., 2013 [61]
SCLC	in vivo	RosetteSep	s.c. injection with matrigel	4	4/6 (67%)	Hodgkinson et al., 2014 [57]
Prostate cancer	in vitro	RosetteSep	Organoid culture	1	1/17 (6%)	Gao et al., 2014 [56]
Breast cancer	in vitro	iChip	Sphere culture	6	6/36 (17%)	Yu et al., 2014 [58]
Colon cancer	in vitro	RosetteSep	Sphere culture	1	1/71 (1%)	Cayrefourcq et al., 2015 [55]
Melanoma	in vivo	RosetteSep	s.c. injection with matrigel	6	6/47 (13%)	Girotti et al., 2016 [60]
NSCLC	in vivo	RosetteSep	s.c. injection with matrigel	1	1/1 (100%)	Morrow et al., 2016 [62]
Colon cancer	in vitro	RosetteSep	3D sphere culture	2	3/16 (19%)	Grillet et al., 2017 [63]
SCLC	in vivo	CTC-iChip RosetteSep/Ficoll	s.c. injection with matrigel	16 1	16/42 (35%) 1/4 (25%)	Drapkin et al., 2018 [65]
Breast cancer	in vivo	Gradient centrifugation	s.c. injection with matrigel	1	1/32 (3%)	Pereira-Veiga et al., 2019 [64]
Breast cancer	in vivo	Flow cytometry sorted	Intracardiac injection	1	1/3 (33%)	Vishnoi et al., 2019 [66]
Prostate cancer	in vivo	RosetteSep	Intercapsular fat pad with matrigel	1	1/22 (5%)	Faugeroux et al., 2020 [67]
Breast cancer	in vitro	RosetteSep	2D cell culture	1	1/50 (2%)	Koch et al., 2020 [68]
Gastroesophageal cancer	in vitro	RosetteSep	2D and 3D sphere culture	2	2/23 (9%)	Brungs et al., 2020 [59]
Pancreatic cancer	in vitro	Labyrinth microfluidic device	2D cell culture	3	3/10 (30%)	Rivera-Baez et al., 2020 [69]

Figure 1. Perspective for implementation of CTCs and DCCs in adjuvant precision medicine. Routine sampling of BM and LN should be performed and technologies for identification and isolation of CTCs/DCCs should be improved. Existing multi-omics technologies including genome, DNA methylome, transcriptome, small RNAs, and proteome data as well as corresponding bioinformatics analysis tools addressing single metastasis founder cells will support the discovery of improved biomarkers. In parallel, first preclinical CTC/DCC models should become available for discovery of novel adjuvant therapies and/or repurposing of approved and investigational drugs in the context of adjuvant treatment. Molecular and functional data should be linked to clinical information to develop and initiate innovative clinical trials

Abbreviations: PT: primary tumor, BM: bone marrow, LN: lymph node, CTC: circulating tumor cell, DCC: disseminated cancer cell

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