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Discover Oncology
Review
Circulating tumor cells clusters andtheir role inBreast cancer
metastasis; areview ofliterature
ZeinabS.Sayed1· MohamedG.Khattap2· MostafaA.Madkour4· NohaS.Yasen3· HananA.Elbary1·
ReemA.Elsayed1· DaliaA.Abdelkawy1· Al‑HassanSolimanWadan5· IslamOmar6· MohamedH.Nafady7,8
Received: 18 November 2023 / Accepted: 21 March 2024
© The Author(s) 2024 OPEN
Abstract
Breast cancer is a signicant and deadly threat to women globally. Moreover, Breast cancer metastasis is a complicated
process involving multiple biological stages, which is considered a substantial cause of death, where cancer cells spread
from the original tumor to other organs in the body—representing the primary mortality factor. Circulating tumor cells
(CTCs) are cancer cells detached from the primary or metastatic tumor and enter the bloodstream, allowing them to
establish new metastatic sites. CTCs can travel alone or in groups called CTC clusters. Studies have shown that CTC clusters
have more potential for metastasis and a poorer prognosis than individual CTCs in breast cancer patients. However, our
understanding of CTC clusters’ formation, structure, function, and detection is still limited. This review summarizes the
current knowledge of CTC clusters’ biological properties, isolation, and prognostic signicance in breast cancer. It also
highlights the challenges and future directions for research and clinical application of CTC clusters.
Keywords Breast cancer· Metastasis· Circulating tumor cells· CTC clusters· CTC detection· CTC biology· CTC
prognosis
1 Introduction
Breast cancer (BC) has been identied as one of the most widespread cancers among women worldwide [1–5]. BC can be
classied into two primary categories: carcinomas and sarcomas [5]. Carcinomas originate from the epithelial component
of the breast and contain terminal ducts and cells that line the lobules. At the same time, sarcomas are another group
of breast cancers that arise from the breast’s stromal components and consist of myobroblasts and blood vessel cells
[5, 6]. Some factors aid the development of BC, such as age, hormone status, genetic predisposition, and family history
[7]. BC has some stages to develop [8]. In Stage 0, no signicant change occurs; in Stage I, the tumor mass is considered
* Mohamed H. Nafady, Mohamed.nafady@must.edu.eg; Zeinab S. Sayed, zeinabshaban438@gmail.com; Mohamed G. Khattap,
mohamed.Ghareb@gu.edu.eg; Mostafa A. Madkour, mustafa140500@fmed.bu.edu.eg; Noha S. Yasen, nohayasen1724@gmail.com; Hanan
A. Elbary, hananabdelbary9@gmail.com; Reem A. Elsayed, ralaa2133@gmail.com; Dalia A. Abdelkawy, daliaadelaliabdelkawy@gmail.com;
Al‑Hassan Soliman Wadan, Amohamed6521@su.edu.eg; Islam Omar, islamomar662@gmail.com | 1Faculty ofApplied Medical Science,
Misr University forScience andTechnology, 26Th of July Corridor, 6Th of October, GizaGovernoratePostalCode:77, Egypt. 2Technology
ofRadiology andMedical Imaging Program, Faculty ofApplied Health Sciences Technology, Galala University, Suez435611,
Egypt. 3Radiology andImaging Technology Department, Faculty ofApplied Health Science Technology, Delta University forScience
andTechnology, Gamasa,AlMansurah, Egypt. 4Faculty ofMedicine, Benha University, Qalyubiyya, Egypt. 5Faculty ofDentistry, Sinai
University, Arish, NorthSinai, Egypt. 6Faculty ofPharmacy, South Valley University, Qena, Egypt. 7Radiation Sciences Department, Medical
Research Institute, Alexandria University, Alexandria, Egypt. 8 Faculty ofApplied Health Science Technology, Misr University forScience
andTechnology, 6thofoctober, Egypt.
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minor and has no spread outside the breast. In stage II, the tumor is usually less than 2cm in diameter, and it may exist
in axillary lymph nodes; in stage III, the size of the tumor varies, meaning it can be any size, and at this stage, inamma‑
tion and change in skin color of the breast may occur due to the spread of the tumor to the chest wall. Stage IV is the
most severe, as cancer metastasizes to distant areas like the lungs, bones, or brain, marking the start of metastatic breast
cancer (MBC) as it invades far‑reaching organs [8, 9] (Fig.1).
BC metastasis is a complicated process involving multiple biological stages [10]. Initially, BC cells begin to separate
from the extracellular matrix (ECM) [8]. They then start to invade and migrate locally [11]. Subsequently, a metastatic
cascade is triggered when cancer cells separate from adjacent cells and the basement membrane [8, 12]. Cells that can
invade the surrounding tissue employ proteolytic enzymes to degrade the ECM and facilitate invasion [13]. Cancer cells
then attach to the endothelial wall and enter the circulation through lymph or blood vessels, eventually reaching other
organs [8]. When some cancer cells break away from the original tumor or metastatic tumor, circulating tumor cells (CTCs)
are formed from these separated cancer cells [14–16]. These cells can travel through the bloodstream, developing new
metastases in other body parts [17]. CTCs were rst discovered by an Australian physician, Thomas Ashworth, in 1869 [18].
Over the years, more has been learned about these rare cells in small numbers in the blood (a few per 10ml) [19]. CTCs
can circulate either as single cells or in clusters [20]. Those circulating in clusters appear to have developed mechanisms
to survive the harsh bloodstream conditions [20–22]. Several studies have explored the composition of CTC clusters,
revealing that they consist of two types of cells: tumor cells (homotypic) and non‑tumor cells (heterotypic), such as mes‑
enchymal cells, epithelial cells, pericytes, immune cells, platelets, and cancer‑associated broblasts. These non‑tumor
components are critical in enhancing the clusters’ survival rate and metastatic advantages [20, 23–32]. Isolating CTCs is
relatively straightforward, as it can be done through a blood draw, making it more accessible than other methods like
biopsy and imaging [33].
Furthermore, several respected studies have established a correlation between the formation of CTC clusters and a
poorer prognosis and lower patient survival rates [20, 21, 34–38]. Therefore, focusing on various aspects of CTCs, including
understanding their biology, function, and detection and isolation methods, would be a valuable pursuit to gain deeper
insights into BC and its metastasis. In this narrative review, we demonstrate the association between BC metastasis’s
potential incidence and the formation of CTC Clusters. We begin by oering insights into the biology, functionality, and
mechanisms of CTC Clusters. This leads to exploring the potential utility of CTC clusters as predictive tools for monitor‑
ing therapeutic responses and forecasting patient prognoses in BC. Additionally, we provide general information about
BC and its stages.
1.1 Biology ofCTC clusters
CTC clusters are tumor cells that move together in a cancer patient’s bloodstream and have strong cell–cell contacts [39,
40]. Pathologist Rudolf Virchow rst postulated CTC clusters in 1858, suggesting that the arrest of tumor microemboli in
the vasculature could be the cause of metastasis [41, 42]. In 1954, Watanabe demonstrated the role of CTC clusters in the
progression of tumor metastases by injecting bronchogenic carcinoma cells into the jugular veins of mice. He found that
CTCs developed metastases in clusters rather than as individual cells [43]. One of the most essential questions about CTC
Fig. 1 Stages of breast cancer. Stage (0) There is no spread to other breast tissues. Stage (I) cancer size in breast tissue is less than 2cm.
Stage (II) cancer size in breast tissue is 2–5cm. Stage (III) tumor is more than 5 cm, and the cancer has spread to auxiliary lymph nodes.
Stage (IV) Cancer has spread beyond the breast to distant organs. Preferential metastasis to the brain, lungs, liver, and bones
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clusters is their origin. There are two main hypotheses; the rst is that CTC clusters shed directly from the primary tumor
(Self‑seed), and the second is that they can be formed when a single CTC in the circulation aggregates together [23,
44] (Fig.2). Cheung etal. tested the last hypothesis by engrafting equal mixtures of tandem dimer TD‑Tomato and cyan
blue uorescent protein (CFP)‑expressing breast tumor cells in the same mammary fat pad [45]. The frequent polyclonal
metastatic seedling discovered by the authors was likely caused by oligoclonal CTC clusters [46]. Additionally, they found
no evidence of bicolored metastasis in the lungs following intravenous injection of a single uorescent cell or grafting
uorescent tumor cells into a mouse’s distinct mammary fat pad [46]. It should be mentioned that primary and meta‑
static tumors can both emit CTC clusters, which can serve as local or distant "self‑seeding" sources for malignancies [47].
Many molecules that help in tumor cell aggregation in BC form CTC clusters. It has been found that keratin 14 and
plakoglobin, both linked to desmosomes and hemidesmosomes, are essential for CTC clusters formation [23]. Distal
metastases and CTC clusters formation decreased by inhibiting these proteins [20, 45]. Also, BC cell aggregation is
inuenced by interactions between galectin‑3 and Thomsen‑Friedenreich glycoantigen [48]. Furthermore, several pro‑
inammatory cytokines, like interleukin‑6 and tumor necrosis factor‑α, may enhance the clustering of tumor cells [49].
1.2 CTC clusters categories
CTC clusters can be divided into two categories: homotypic and heterotypic CTC clusters. Tumor cells are the only com‑
ponent of homotypic clusters. s Heterotypic clusters are composed of an aggregation of cancer cells and non‑cancerous
cells like blood cells, endothelial cells, platelets, and broblasts [20, 21, 50, 51]. Homotypic CTC clusters represent a small
percentage (1–30%) of all CTC events when detected in the peripheral circulation of patients or mice models, and their
presence is dependent on the tumor size, disease stage, and molecular features [20, 51–53]. In BC, homotypic clustering
of CTCs can be regulated by CD44 homophilic interactions, which activate various signaling pathways such as OCT4,
EGFR, and the p21‑activated kinase 2 /focal adhesion kinase (FAK) [22, 54]. Intercellular Adhesion Molecule 1 (ICAM1), a
recently discovered stemness‑promoting adhesion molecule, is also involved [54]. Other studies have proved that intra‑
tumor hypoxia can cause cluster development [55]. OCT4, SOX2, and NANOG are essential stemness genes enhanced by
CTC homotypic clustering, encouraging stemness and clustered cell proliferation [56]. The development of CTC clusters
may be enhanced by the cooperation of several adhesion and junction proteins [21].
It has been found that heterotypic CTC clusters are vital in seeding tumor clusters and maintaining resistance against
host immune responses through their non‑cancerous cells [57–60]. CTC‑neutrophil clusters appear signicant in the
metastatic process; IL‑1 b and IL6 are involved in a cytokine‑receptor interaction that mediates this [60]. The intercellular
Fig. 2 Caption CTC clusters metastasis. Circulating tumor cell (CTC) clusters are a group of tumor cells that move together in a cancer
patient’s bloodstream and have strong cell–cell contacts. These cells shed directly from the primary tumor "self‑seeding" (1), or they can be
formed when single CTCs in the circulation aggregate together and form clusters of tumor cells in other tissues (2)
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connections that hold CTC‑neutrophil clusters together depend on VCAM‑1 [60]. In BC animal models, a decrease in neu‑
trophils has been associated with a delay in releasing CTCs and CTC‑neutrophil clusters from the primary tumor site. This
reduction has also been linked to a delay in the development of metastases and a shorter overall survival rate in mice [44].
One intriguing observation is that the rst contact between CTCs and neutrophils seems to occur at the primary tumor
site, not in the bloodstream. Tumor‑inltrating neutrophils leave the primary cancer site and cancer cells and enter the
bloodstream as CTC‑neutrophils clusters [60]. Another type of heterotypic CTC cluster that has been found to promote
the metastatic ability of CTC clusters is the CTC‑platelets cluster. CTC clusters in the circulation are physically shielded by
platelets from shear forces and immune responses [61, 62]. In many studies, the relationship between CTCs and platelets
has also been established in patient samples by identifying the expression of platelet markers (such as SELP, ITGA2B,
SPARC, and ITGB3) from total RNA extracts of CTCs (both single and clustered) [20, 60, 63]. Additionally, heterotypic CTC
clusters in migration or circulation show the presence of cancer‑associated broblasts, previously known to promote
cancer invasion and spread from the primary tumor [64]. This was demonstrated in a mice experiment where the ability
of the mice to develop lung metastases was decreased by removing broblasts from the clusters [24].
1.3 Relationship betweenCTCs andmicroorganisms
Transitioning from the cellular dynamics of CTC clusters, we explore the pivotal role of microorganisms in inuenc‑
ing breast cancer metastasis. Microbial interactions with CTCs present a complex layer of regulation, impacting tumor
progression and metastatic potential. This relationship underscores the e microbiome’s inuence on cancer pathways,
including the critical process of epithelial‑mesenchymal transition (EMT), which facilitates CTC migration and survival. By
understanding these microbial interactions, we gain insights into novel therapeutic avenues targeting the microbiome
to mitigate metastasis.
A growing eld of research examines the nature of the microbiome in metastatic disease. The human commensal
microbiota comprises every type of microbe that lives in the human body, including viruses, bacteria, protozoa, and fungi
[65]. The growth of the immune system and the host’s defense against several diseases, including cancer, are inuenced
by gut microbes [66]. Interaction between the immune system and the microbiota of tumor cells may boost the chance of
cell survival and stimulate tumor cell migration [67]. The microbiota inuences the EMT, a critical stage for CTC migration
and survival. Toxins produced by bacteria cause EMT [68]. Certain microorganisms, such as Fusobacterium nucleatum,
E. faecalis, and Bacteroides fragilis, can remove the transmembrane adhesion protein E‑cadherin from epithelial cells,
which promotes the growth of colonic epithelial cells [69]. It’s currently unclear how certain microbiota compositions,
the inammatory response, and treatment resistance connected to EMT are related [70]. Changes in the gut microbiota
could boost EMT via the WNT, TGFβ, and Notch signaling pathways and SNAIL, Slug, ZEB1, Twist, and ZEB2 transcription
factors, resulting in invasive and metastatic cancer processes [71–73].
The generation of inammatory cytokines and macrophage activation were facilitated by antibiotic‑induced gut
dysbiosis, which in turn promoted EMTin colorectal cancer [74]. Bacteria recognized to be implicated in the advance‑
ment of colorectal cancer include Salmonella enterica, Bacteroides fragilis, Fusobacterium nucleatum, and Enterococcus
faecalis. These bacteria produce virulence factors that aid in the growth of cancer and EMT[75]. In the case of BC, the
well‑known role that estrogens play in the development of hormone‑dependent BC is impacted by the gut microbiota’s
inuence on estrogen metabolism [76]. Bacteria in the phylum Proteobacteria, including Escherichia and Shigella, express
b‑glucuronidase enzymes that facilitate sexual hormone reabsorption through the enterohepatic pathway. This process
raises circulating estrogen levels, aecting BC growth [77, 78]. A study of fecal samples revealed that the gut microbiome
of BC patients with bone metastases had a higher level of Acinetobacter, Bacilli, Collinsella, Epsilonproteobacteria, Campy‑
lobacter, Lactobacillales, Streptococcus, Veillonella, Pseudomonadales, and Moraxellaceae than control samples. On the
other hand, the fecal sample analysis from individuals with metastatic disease revealed much‑reduced concentrations
of Paraprevotella, Clostridia, Megamonas, Akkermansia, and Gemmiger. As a result, researchers hypothesized that a cor‑
relation between the occurrence of bone metastases and reduced levels of Megamonas and Akkermansia may exist [79].
Since advancements in genome sequencing in recent years, researchers have shown that microbiomes, sometimes
known as tumor microbiomes, are present in solid human tumors [80–82]. Compared to other body regions, the bac‑
terial pattern seen in normal BC is distinct and includes Actinobacteria, Firmicutes, Proteobacteria, and Bacteroidetes
[83–85]. BC formation and progression are probably inuenced by the dierent microbiota found in breast tumors
compared to normal counterparts [76]. According to Fu, Aikun, etal., the intracellular microbiota present in tumors plays
a role in the reorganization of the actin cytoskeleton of tumor cells, which increases the cells’ resistance to uid shear
stress upon entry into the systemic circulation. This ultimately leads to an increased risk of metastatic colonization and
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cancer aggressiveness [86]. The intratumoral microbiome can potentially contribute to BC recurrence and metastasis
by promoting tumor stem cell activity, transforming epithelial cells into mesenchymal cells, and facilitating cell migra‑
tion [87]. According to research by Parhi and colleagues, Fusobacterium nucleatum colonizes BC through Gal‑GalNAc,
which is present in large amounts in tumor cells. It then encourages the growth and spread of BC by preventing T‑cell
aggregation in the tumor’s surrounding tissue. [88]. In the murine spontaneous breast tumor model, the decrease of the
tumor microbiome brought on by antibiotic therapy prevented the formation of lung metastases. It was shown that the
intratumoral delivery of certain bacteria, including Ligilactobacillus animalis, Spilopsyllus cuniculi, and Staphylococcus
xylosus, raised the number of lung metastases in mice without changing the main tumors [86].
1.4 CTC clusters andmetastasis
Even though metastasis is the primary cause of mortality among BC patients, research is still ongoing to understand the
mechanisms that promote the spread of tumor cells and the formation of metastases. However, this may be assisted by
studying the mechanism of action of CTCs, the progenitors of metastatic spread. As known, more than 90 percent of
malignant cells shed into blood circulation have a low probability of surviving; only a tiny fraction of individual CTC or
clusters can survive [44]. A study by Liu etal. has demonstrated that CTC clusters are more potent in facilitating metas‑
tasis formation than single CTCs, particularly in triple‑negative patient‑derived BC models (PDXs) [33]. Strong cell–cell
connections enable these tricky cells to disseminate in clusters, avoid anoikis, a form of apoptosis, and supply survival
factors that encourage their metastatic potential [39, 57]. In BC, the proteins circulating galectin‑3 and CD44‑mediated
signaling pathways, as well as cancer‑associated mucin1 (MUC1), interact altogether, inhibiting anoikis of clusters in
the circulation, promoting their aggregation and enhancing their seeding to distant organs [22, 89]. CTCs initiate their
extravasation process by slowing down within tiny capillaries, clinging to the endothelial lining of vascular structures,
and traversing the endothelium [90]. Two primary mechanisms have been proposed to explain the extravasation of cir‑
culating tumor cells CTCs. The rst mechanism is a physical blockage of the CTCs in smaller diameter capillaries due to
of the expression of ligands and receptors on endothelial cells and CTCs. The second mechanism involves cell adhesion
to the endothelium in veins larger in diameter [91].
In addition, tumor cells can create a "premetastatic niche" [92] via which systemic signals (cytokines, exosomes, and
extracellular matrix remodeling enzymes) are released from the primary tumor, providing a more hospitable microen‑
vironment for CTCs [93]. Consequently, this mechanism is considered necessary for their work, improving their adapt‑
ability to various microenvironments and helping CTC clusters metastasize easily. Therefore, it has been proved that the
poor prognosis and the increasing metastatic phenotype observed in BC patients are linked to the epigenetic signature
identied in clusters of CTCs; these clusters are characterized by hypomethylated regions that are abundant in binding
sites for embryonic stem cell transcription factors [56].
1.5 CTC clusters immunology
Immunologically, CTC clusters possess the unique ability to aggregate with dierent immune cells (heterotypic clus‑
ters), which act as a physical shield, providing a protective barrier against immunological surveillance. Interestingly, it
has been discovered that neutrophils, a subtype of white blood cell, directly interact with breast CTCs, inuencing the
transcriptional prole of tumor cells, promoting the progression of the cell cycle in the blood, and hastening the seed‑
ing of metastases. Studies have indicated that individuals diagnosed with BC who presented with a minimum of one
CTC cluster containing neutrophils had a signicantly poorer prognosis than those with less than ve CTCs in a volume
of 7.5 ml of peripheral blood [60]. Indeed, heterotypic clusters in BC can metastasize quickly due to the presence of
stroma‑derived cells and platelets [94]; the latter coats clusters as a physical shield to protect them from shear forces in
the circulation, collisions with other blood cells, and immunological reactions mediated by cytotoxic natural killer (NK)
and T cells [61]. Additionally, this aggregation can facilitate CTC migration through the endothelial barrier by improving
their adherence to the vasculature [95].
Moreover, platelets can maintain the integrity of CTC clusters using paracrine secretion of substances such as trans‑
forming growth factor (TGF), a well‑established inducer of theEMT process. This process is fundamental to developing
intrinsic heterogeneity in CTCs [96]. Predominantly, Cancer cells initially colonize through a reversible process known as
a mesenchymal‑to‑epithelial transition (MET), which facilitates their colonization in metastatic foci [97]. The CTC cluster
exhibits both epithelial and mesenchymal characteristics simultaneously in MBC patients [98, 99]; the hybrid epithelial‑
mesenchymal phenotype that is observed endows these aggregates with a considerable degree of plasticity, thereby
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conferring a trait of advantageous survival, as has been proposed in the literature [100]. The underlying mechanism
appears to be the combination of mesenchymal traits that favor a migratory phenotype and the maintenance of cell–cell
junctions in epithelial cells [94].
1.6 Comparison betweensingle CTCs andCTC clusters inBC metastasis
A collection of cancerous cells, consisting of more than two or three (Even up to a hundred, which exhibit signicant
cell–cell interactions), have been identied as a CTC cluster inside a cancer patient’s bloodstream. Although extremely
metastatic, it seems to be exceedingly uncommon; in a mouse model, clusters were demonstrated to make up around
50% of BC metastases despite making up just 2–5% of total CTCs. Moreover, the metastatic potential of these clusters
has been estimated to be between 23 and 50 times more than that of single CTCs [44]. Additionally, unlike single CTCs
in many cancer classications, the occurrence of CTC clusters and the size of their clusters are linked to worse clinical
outcomes [20, 36, 37, 101]. It was also proposed that maintaining robust cell–cell adhesions might shield cell clusters
from anoikis (apoptotic cell death), brought on by a relative lack of adherence [102]. Therefore, CTC clusters could have
benets in terms of survival both during circulation and during dispersion. Studies have demonstrated that CTC clusters
have less apoptosis, increased survival, and colony‑forming capability [20, 45]. Conversely, because of their interception
via small vessels, the duration of CTC clusters in circulation is incredibly brief (much briefer than individual CTCs, which
may persist in circulation for only a few hours [103]. Invivo, ow cytometry determined the clearance rate of the tagged
clusters and individual CTCs from the blood [20].
Further research shows that CTC clusters dier from single CTCs in gene prole expression and dispersion methods.
Cell–cell junctions may be crucial in constructing and preserving CTC clusters in the circulatory system, according to
transcriptome investigations, which have revealed that these structures retain epithelial characteristics. Plakoglobin and
keratin 14 (K14), two proteins participating at desmosome and hemidesmosome junctions, have shown higher expres‑
sion in clusters than in single cells [20, 45]. While single‑cell whole‑genome bisulte sequencing (sc‑WGBS) investiga‑
tion of DNA methylation patterns across both individual and clustered CTCs has demonstrated that clustering causes
hypomethylation of Linking locations associated with stemness as well as prevalence regulatory, which include SOX2,
SIN3A, OCT4, and NANOG. Moreover, hypermethylation of Polycomb target genes is also shown to increase stemness
and proliferation concurrently [56]. The CTC cluster’s impact on MBC survivability has also been noticed by Jansson etal.
[36], who demonstrated that follow‑up samples of patients having CTCs and CTC clusters following systemic irradiation
had the worst prognosis in terms of progression‑free survival (PFS) and overall survival (OS) compared to those without
such cells. In the Mu etal. study [104], patients with BC phases III and IV had a lower PFS when their baseline numbers of
both single CTCs and CTC clusters (classied as C2 CTCs) were high. According to Paoletti etal.’s research, CTC clusters
are signicant in metastatic triple‑negative BC (TNBC) and apoptosis [105] Table1.
2 Methods forCTC cluster detection andisolation
A single CTC is uncommon in peripheral blood, and CTC clusters—about 3% of all CTCs are much less common [108].
Most CTC enrichment methods use specic markers to distinguish CTCs from leukocytes. The most prevalent epithelial
cell markers are cytokeratins (CKs) and EpCAM (epithelial adhesion molecule) [109]. A hybrid epithelial‑mesenchymal
feature can be seen in CTC clusters, so using strategies based on epithelial markers is not helpful to CTC clusters [109].
nity‑based and label‑free approaches are to isolate CTCs and CTC clusters [110]. Anity‑based techniques for captur‑
ing CTC clusters employ cell surface markers and antigen–antibody [109]. The most frequently used biological approach
for isolating CTCs or reducing leukocytes involves using antigen‑specic antibodies attached to paramagnetic particles,
selectively concentrating the target cells [109].
In contrast, label‑free methods exploit the size dierences between blood cells and CTC clusters [110]. Physical meth‑
ods, as label‑free methods, primarily use size, density, and electrical charge dierences to distinguish CTCs from nor‑
mal cells. Both approaches have benets and drawbacks. For example, anity‑based methods can capture physically
heterogeneous populations of CTCs due to their high purity. In contrast, label‑free methods can capture biologically
heterogeneous populations of CTCs due to their high throughput [110].
Generally, the advantages of the label‑free method as the ISET: (i) It doesn’t require antibody binding to maintain the
CTC clusters’ native state; (ii) it allows direct ltration of peripheral blood without preprocessing; (iii) It is capable of pre‑
serving CTC cluster integrity; (iv) It is less expensive than Anity‑based methods [23] f. The limitations of anity‑based
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Table 1 Studies comparing the biological and pathological characteristics of CTCs and CTC clusters
Study Tumor type Metastatic potential CTCs and CTC Cluster detection
method Study main ndings Reference
Cheung etal. (2016) Breast cancer mouse model The exvivo colony formation
increased by > 15‑fold, and invivo
metastasis development increased
by > 100‑fold when tumor cells
were aggregated into clusters
Multicolor lineage tracing In a mouse model, multicolored
tumor cell clusters were observed
across all main phases of metasta‑
sis, including collective invasion,
local dissemination, intravascular
emboli, circulating tumor cell
clusters, and micrometastases
[45]
Donato etal. (2020) Breast cancer mouse model The average number of cells in
hypoxic CTC clusters was larger
than that of normoxic CTC clus‑
ters, with 5.3 cells per hypoxic CTC
cluster and 2.82 cells per normoxic
CTC cluster
Live imaging of HIF1a reporter In a mouse model, Most CTC clus‑
ters are hypoxic; conversely, most
single CTCs are normoxic
[55]
Szczerba etal. (2019) Patients with breast cancer and
mouse models Among breast CTCs, CTC‑neutrophil
clusters are the most eective
subpopulation for metastasis
formation, and a patient’s blood‑
stream containing these cells is
linked to a poor prognosis
Parsortix microuidic device ‑ In breast cancer patients, those
with 7.5 ml of peripheral blood
containing at least one CTC‑neu‑
trophil cluster had a substantially
worse progression‑free survival
than those with ve or more CTCs
in 7.5 ml of peripheral blood
‑ Research revealed that mice
administered CTCs from CTC–
neutrophil clusters experienced a
signicantly lower survival period
and overt metastasis than those
injected with CTCs alone
[60]
Aceto etal. (2014) Breast cancer mouse model CTC clusters have been estimated to
be between 23 and 50 times more
than that of single CTCs
Herringbone HB CTC‑Chip In a mouse model, clusters were
demonstrated to make up around
50% of breast cancer metastases
despite making up just 2–5% of
total CTCs. Still, CTC clusters have
been estimated to be between
23 and 50 times more than that
of single CTCs and contribute to
approximately half of all meta‑
static lesions in orthotopic breast
cancer models
[20]
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Table 1 (continued)
Study Tumor type Metastatic potential CTCs and CTC Cluster detection
method Study main ndings Reference
Duda etal. (2010) Mouse lung cancer cell line The presence of broblasts in
clusters makes cancer cells more
viable in the bloodstream and at
the secondary location
Whole‑mount uorescence micros‑
copy Using diphtheria toxin treatment 24
h after cell infusion to eliminate
carcinoma‑associated broblasts
(CAFs), the number of metastases
assessed two weeks after infusion
did not change signicantly. These
ndings demonstrate the ability
of tumor‑associated broblasts
to stimulate lung metastasis. This
advancement cannot occur when
the CAFs are not directly associ‑
ated with the cancer cells within
the metastatic foci
[24]
Liu etal. (2019) Patients with breast cancer and
mouse models CTC clusters are more potent in
facilitating metastasis formation
than single CTCs, particularly in
triple‑negative patient‑derived BC
models (PDXs)
Cell search and uorescence micros‑
copy ‑CTC clusters are more potent in
facilitating metastasis formation
than single CTCs, particularly in
triple‑negative patient‑derived BC
models (PDXs)
‑The breast cancer stem cell marker
CD44 was highly expressed
by aggregating tumor cells,
encouraging carcinogenesis and
polyclonal metastases
‑ The interactions mediate tumour
cluster aggregation between
CD44 homophiles and, subse‑
quently, CD44–PAK2. That will
encourage the creation of new
targeted techniques to prevent
polyclonal metastasis and result in
novel biomarker applications that
predict prognosis
[22]
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Table 1 (continued)
Study Tumor type Metastatic potential CTCs and CTC Cluster detection
method Study main ndings Reference
Murlidhar etal. (2017) Patients with surgically resectable
(clinical stage I‑III) lung cancer The cells within CTC clusters can
avoid cell death, given their prog‑
nostic relevance and capacity for
metastasis. CTC clusters have been
demonstrated to be linked to a
poor prognosis
Microuidic device In early‑stage lung cancer, (CTCs)
can help predict an early relapse
and assist in the early diagnosis
of metastases. A notably greater
quantity of CTCs in the (PV) blood
has been discovered thanin the
Preoperative (Pe) blood. Gene
ontology analysis enriched cell
migration and immune‑related
pathways in CTC clusters, indicat‑
ing a possible survival benet of
the clusters while in circulation
[106]
Gkountela etal. (2019) BC patients and mouse models CTCs’ ability to shape clusters has
been connected to expanded
metastatic potential
Whole‑genome bisulte sequenc‑
ing (sc‑WGBS) investigation Demonstrated that clustering
causes hypomethylation of
Linking locations associated
with stemness and prevalence
regulatory, including SOX2, SIN3A,
OCT4, and NANOG. Moreover,
hypermethylation of Polycomb
target genes is also shown to
increase stemness and prolifera‑
tion concurrently
[56]
Paoletti etal. (2015) Metastatic triple‑negative breast
cancer (TNBC) Metastatic CellSearch® In correlational studies, CTC clusters
are signicant in metastatic triple‑
negative breast cancer (TNBC) and
apoptosis
[107]
Mu etal. (2015) Metastatic Breast cancer (Stage
III‑IV) Metastatic CellSearch® Patients with breast cancer phases
III and IV had a lower PFS when
their baseline numbers of both
single CTCs and CTC clusters (clas‑
sied as C2 CTCs) were high
[35]
Jansson etal. (2016) Metastatic Breast cancer (Stage
III‑IV) Metastatic CellSearch® In an observational study, follow‑up
(FU) samples of patients having
CTCs and CTC clusters following
systemic irradiation had the worst
prognosis in terms of PFS and OS
compared to those without such
cells
[36]
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methods are thatcapture requires optimal velocity and shear conditions forantibody–antigen binding [111, 112]. A very
high shear may disrupt any bonds if formed, while a very low shear is conducive to non‑specic cell binding and the
limited expression of target antigens [23] (Fig.3).
2.1 Label‑free methods
The ISET (Isolation by Size of Epithelial Tumor Cells), a label‑free‑method, is a widely used physical technique that captures
most epithelial cells (20–30µm) while allowing smaller leukocytes to pass through pores of a specic size and shape.
Although this method is appropriate for detecting CTC clusters, which vary in size, it also retains larger leukocytes, reduc‑
ing its specicity [109]. CTC clusters and CTCs are more prominent than leukocytes in the blood. Thus, their isolation by
size is an easy process [113, 114]. This technique seemed not specic for isolating CTC clusters and stems from the lter’s
ability to retain larger leukocytes [109]. Generally, ISET technology can isolate CTCs from all types of cancers as whole
cells without needing prior selection based on the immune system [115]. ISET is considered a more precise technique
than other invitro methods. In a study, 43% of patients with non‑small cell lung cancer (NSCLC) were found to have CTC
clusters through the use of ISET. However, the detection of CTCs was not fully achieved by Cell Search. Another study that
utilized a similar ISET platform isolated CTC clusters from all lung cancer patients [116]. One study found that the ISET
platform could detect clusters of CTCs in 2 out of 23 individuals with primary liver cancer [117]. Via utilizing ScreenCell®
(ScreenCell, Sarcelles, France), an easy, non‑invasive technology, to separate CTCs and CTC clusters by size on a micropo‑
rous membrane lter, allowing for later characterization and sorting. The ScreenCell’s ltration membrane devices can
enable nucleated cells to pass while holding up CTCs and preserving the CTCs’ morphology and structures [115].
The ScreenCell® device’s circular lter is polycarbonate and has a smooth, at, and hydrophilic surface. They sought to
alter the pores’ size, bringing it up to 15m, to make it possible to lter huge CTC clusters selectively [118]. These devices
are intended to isolate (a) xed cells for cytological studies (ScreenCell® Cyto), (b) live cells for culture (ScreenCell® CC),
and (c) molecular biology (ScreenCell® MB) [119]. Using a blood‑ltration technique, we identied CTC clusters in 6 6 EBC
Fig. 3 Basic techniques used for CTCs and CTC cluster detection
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patient samples and determined if DNA aberrations were present in 96% of the 48 examined clusters [120]. A unique
exible microspring array (FMSA) technology was recently developed to enrich viable CTCs according to their size, inde‑
pendent of antigen expression [121]. In colon, lung, and BC, FMSA detected CTC clusters of 2–20 tumor cells [121]. (Fig.4).
2.2 Affinity‑based methods
The fundamental idea of technologies like CellSearch [122] involves the anity between an antigen and an antibody.
Antigens present on the membrane of CTC clusters are targeted by specic antibodies that can be immobilized onto
a solid surface [123]. The optimal conditions for anity‑binding allow the antigens to attach themselves to the target
antibodies. Then, depending on how they were captured, the bound cells can be separated for additional testing [124].
The identication of CTCs and CTC clusters is achieved through immunomagnetic techniques, wherein CTCs are
marked with antigen‑specic antibodies conjugated to magnetic beads [125–128]. CTCs are captured using antibodies
that target specic markers on epithelial cells, such as CKs, EpCAM‑specic antigens, tumor antigens, carcinoembryonic
antigen (CEA), and human epidermal growth factor HER2 [109]. Cells bound by antibodies attached to magnetic beads
can be separated from leukocytes using a magnetic eld. These isolated CTCs can then undergo further analysis. Some
systems used for this technology include EasySep from Stem Cell Technologies in Canada, Dynal Magnetic Beads from
Invitrogen in the USA, and MACS (Magnetic Activated Cell Sorting) from Miltenyi Biotec GmbH in Germany [129–131].
The CellSearch System, authorized by the US Food and Drug Administration (FDA), is the only test available for clinically
detecting CTCs. The AdnaTest, developed by AdnaGen AG in Germany, is used to isolate CTCs using a magnet and then
lyse them to measure the expression of markers for MUC1, HER2, and GA73.3 surface glycoprotein‑2, allowing for the
identication of CTCs [132]. According to a research study, the use of CK and prostate‑specic antigens as combined
biomarkers for prostate cancer showed that the occurrence of CTC clusters was up to 80% [126]. Another study on
colorectal cancer found that using immunomagnetic labeled CK antibodies, CTC clusters could be isolated from the
peripheral blood of 68.8% of patients [127]. The antibody‑based techniques are ineective for CTC clusters because they
have lower surface‑area‑to‑volume ratios and the restricted expression of target antigens, decreasing antibody capture
eectiveness [112].
In immunology, there are two types of selection: positive and negative. Positive selection involves using specic mark‑
ers found on the surface of epithelial cancer cells. These markers are targeted by antibodies to identify CTCs in samples.
Fig. 4 Caption Features of Homotypic Circulating Tumor Cell (CTC) Clusters. Once CTCs assemble into clusters, they establish favorable con‑
ditions for their survival through various mechanisms. Cancer cells preserve crucial intercellular junction molecules, including CD44, ICAM1,
and plakoglobin, among others, to resist anoikis. The amalgamation of cancer cells induces hypomethylation in transcription factor binding
sites associated with stem cells and proliferation, such as OCT4, SOX2, NANOG, and SIN3A. CTC clusters maintain a hypoxic environment,
and there is a notable increase in the expression of PD–L1. Through these means, they successfully evade immune surveillance and lead to
immune escape. Additionally, CTC clusters exhibit a mixed epithelial/mesenchymal phenotype, and when encountering small‑diameter ves‑
sels, they organize into chains. Collectively, these characteristics contribute to the heightened metastatic capabilities of CTC clusters
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Systems such as CellSearch® and Adnatest® use this approach to detect CTCs in breast carcinoma patients and monitor
their response to chemotherapy or surgery [115]. At the same time, negative selection is a process that can be used to
remove white blood cells and other types of blood cells. In the context of CTC enrichment, negative selection involves
depleting white blood cells using antibodies that target specic biomarkers, such as CD66b or CD45 [115]. (Fig.5.)
2.3 Predictive value ofCTC cluster counts inmonitoring therapy response
2.3.1 CTC clusters inprimary BC
CTCs,specically CTC clusters, are considered potential metastatic seeds. The molecular characteristics of these cells,
their persistence in circulation throughout therapy, and other prognostically signicant information may be revealed
by a greater understanding of these cells. While CTC clusters have been extensively studied in MBC patients [36–38,
133, 134], their properties in individuals with earlier stages of the disease remain less understood. Identifying early BC
patients with CTC clusters may allow us to identify high‑risk individuals who develop metastasis and expose them to
cluster‑targeting agents [135].
Krol etal. [136] have recently validated the existence of CTC clusters in the peripheral circulation of early BC patients
who have not yet metastasized, and they are over three times more prevalent than in MBC patients [137, 138]. This inves‑
tigation employed non‑disruptive CTC visualization technology, identifying clusters in various subtypes: luminal‑A‑like,
luminal‑B‑like, and HER2‑positive, but not in triple‑negative cases. The size of the detected CTC clusters varied, ranging
from pairs to aggregates exceeding 50 cells. This nding emphasizes the early involvement of CTC clusters in BC and
highlights the need for further research, particularly in developing early‑stage, cluster‑specic therapies. According to
[139], marker‑independent ltration technologies have revealed that 70% of early BC cases display CTC clusters, com‑
pared to just 20% of MBC patients. This suggests a higher incidence of CTC clusters in the early stages of BC compared
to MBC, challenging the prevailing view that CTC clusters are mainly characteristic of advanced stages of the disease.
Additionally, CTC clusters were shown to be substantially more common in women with HER2‑negative tumors [137,
139]. A related study involving six early‑stage BC patients supports the ndings of Krol etal. and Reduzzi etal. on the early
appearance of CTC clusters in BC [120]. This research focuses on CTC clusters in early‑stage patients, revealing notable
tumor fractions and genomic dierences compared to primary tumors. It emphasizes the signicance of CTC clusters in
Fig. 5 Caption Heterotypic Circulating Tumor Cell (CTC) Clusters. Formation of circulating tumor cell (CTC) clusters with diverse cell types.
Heterotypic interactions occur between CTCs and white blood cells, such as neutrophils (A), platelets (B), and myeloid‑derived suppressor
cells (MDSCs) (C). These interactions play a role in facilitating immune evasion and promoting proliferation. Abbreviations: CSF1, colony‑
stimulating factor 1; CSF3, colony‑stimulating factor 3; Il, interleukin; ROS, reactive oxygen species; TGF‑β3, transforming growth factor‑β3;
VCAM‑1, vascular cell adhesion molecule 1
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early‑stage BC, suggesting they may arise from varied tumor regions or micrometastases, and highlights the necessity
for more concentrated research on cluster‑specic therapies in the early stages of the disease.
In a meta‑analysis involving 6825 BC patients from 49 studies, CTCs have been shown to have predictive power in meta‑
static patients and individuals with early‑stage malignancies [140]. The data demonstrated that early‑stage patients with
CTCs face a higher risk of recurrence, as indicated by the pooled Hazard Ratio and a 95% condence interval. Moreover,
CTCs consistently serve as a reliable prognostic marker throughout treatment, unaected by systemic therapy. According
to Mu etal. [35], CTC clusters may have more predictive value (PFS) than CTC enumeration alone at baseline in patients
with stages III and IV BC. Interestingly, it has been found that plakoglobin expression (a protein that constitutes both
adherents’ junctions and desmosomes) was higher in CTC clusters than in single CTCs and that its expression in primary
tumors was associated with a signicant reduction in distant metastasis‑free survival (DMFS) [20]. In a similar study on
121 early‑stage BC patients, plakoglobin expression in primary tumors has been identied as a signicant prognostic
indicator for distant metastasis in BC contexts,[141]. The ndings from this study suggest that individuals exhibiting
elevated levels of plakoglobin expression were associated with markedly poorer DMFS and exhibited a considerable
increase in E‑cadherin expression, a recognized marker of EMT [141]. These observations imply that plakoglobin not
only correlates with the aggressiveness of breast cancer but also may be a more eective prognostic factor for predict‑
ing distant metastasis, highlighting its importance in evaluating patient outcomes. In light of the ndings, exploring
CTC clusters in primary BC highlights their potential as early indicators of metastasis risk, underscoring the necessity for
further research. Such research should focus on elucidating the precise role of these clusters in the early stages of the
disease and exploring their prognostic signicance across dierent BC subtypes. This endeavor is crucial for identifying
individuals at a higher risk of progression and integrating targeted therapeutic strategies.
2.3.2 CTC clusters inMBC
Typically, treatment progress for primary or metastatic tumors is made based on histology biopsy, which has several
drawbacks, such as limited access to intratumoral heterogeneity, making it an impractical method for long‑term disease
surveillance. On the other hand, liquid biopsy is less invasive, simple to do, and doesn’t require highly skilled medical
workers. It can also be repeated frequently with minimum side eects [142]. Detecting CTC clusters in peripheral blood
vessels in patients with MBC is a potential biomarker that strengthens the predictive value of counting single CTCs and
evaluating treatment ecacy [133, 142]. About 3.4 percent of all CTCs are clustered, and 35 and 50 percent of patients
with MBC have clusters. Also, clusters have a shorter half‑life in the bloodstream (6–10 min compared to 25–30 min for
single CTC) [143, 144].
Numerous studies have shown that CTC clusters have a greater potential for metastatic spread than single CTCs.
Still, the degree of this disparity varies from 20 up to more than 100 times, and in mouse models, it was responsible for
50–97% of metastatic tumors [21, 145]. The capability of clusters to extravasate and survive in adverse environments, as
well as their structural deformability, vascular shunts that allow them to circulate, their hybrid epithelial‑mesenchymal
phenotype, their stem cell characteristics, and the concentration on genes associated with replication and growth, and
their improved cellular viability, all contribute to the explanation of the clusters’ metastatic potential. The dimensions
and density of groups in the blood aect all of those factors [22, 133]. Due to that, the detection of CTC clusters has
been related to poor prognosis in MBC patients [37, 142]. Multiple studies showed that enumeration of CTC clusters
has independent prognostic signicance and increases predictive value to enumeration of CTC alone at baseline and
follow‑up [38, 133]. Table2 compares the results of ve studies that investigated the connection between CTC clusters
and the prognosis of MBC patients. The presented Table2 provides evidence that majority of investigations indicate a
connection between the existence of CTC clusters and unfavorable results, including decreased PFS and OS, as well as an
elevated hazard of disease progression and mortality. Moreover, mentioned studies in Table2 reveals that CTC clusters
exhibit a greater prevalence in specic BC subtypes, such as HER2‑positive and triple‑negative, and that the quantity
and dimensions of these clusters may impact patient survival.
Jansson etal. [36] looked at whether diagnostic information will be obtained from CTC clusters and apoptotic CTC
in MBC together with CTC enumeration in all BC subtypes. According to time‑dependent landmark analysis, patients
who presented an increasing fraction of CTC clusters per CTC number in follow‑up samples had a substantially worse
prognosis. They concluded that independent of other predictive markers such as CTC numbers and BC subtype, Greater
mortality was linked to the presence of apoptotic CTCs and CTC clusters at any given time. The study limitation was the
small number of patients that hindered the statistical power and under presentation of HER2‑positive and triple‑negative
subgroups despite being diagnosed more frequently with CTC clusters at baseline.
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Table 2 Five Studies showed that CTC‑cluster enumeration has independent prognostic signicance and adds predictive value
Study Name Study TYPE Number of patients Treatment GROUPS Primary endpoint
results Breast cancer sub‑
type CTC cluster detection
method Statistical signicance
of results
Jansson etal. [36] A prospective
observational study
(cohort study)
Fifty‑two patients
newly diagnosed
with a rst meta‑
static incident were
scheduled to begin
rst‑line therapy
in the metastatic
context
They did not have
dierent treatment
groups but followed
the patients who
received rst‑line
therapy in the
metastatic context
according to their
BC subtype (hor‑
mone receptor‑pos‑
itive, HER2‑positive,
or triple‑negative)
The CTC clus‑
ters detected
in the blood at
1–3months and
6months were
linked to a shorter
PFS. At 1–3months,
CTC clusters were
also linked to
shorter OS. Still, at
6months, OS could
not be assessed
because every
patient in the group
that had clusters
died before patients
in the group with‑
out clusters
They followed the
patients accord‑
ing to their BC
subtype (hormone
receptor‑positive,
HER2‑positive, or
triple‑negative).
They found that
CTC clusters were
less commonly
detected at base‑
line and between
1 and 3months in
patients with hor‑
mone receptor‑pos‑
itive tumors than
in HER2‑positive
and triple‑negative
BC patients. Still,
at 6months, there
was no signicant
variance
Used CellSearch
analysis to detect
apoptotic CTC, CTC
clusters, and WBC‑
CTCs. They dened
CTC clusters as two
or more CTCs close
to each other within
the same image
eld
The CTC clusters in
the blood at 1–3
and 6months were
linked to shorter PFS.
At 1–3months, CTC
clusters were also
related to shorter OS.
Patients with clusters
had a greater risk of
cancer progression
and mortality com‑
pared to those who
had no CTC clusters
at any stage during
the trial duration
Wang etal. [37] Cohort study Before beginning a
new therapy, there
were one hundred
twenty‑eight
female patients
with metastatic BC
They did not have
dierent treatment
groups but followed
the research types
and received various
therapies according
to their physician’s
discretion
Baseline CTC clusters
signicantly corre‑
lated with reduced
PFS outcome. Addi‑
tionally, the longitu‑
dinal analysis found
that CTC clusters
had more predic‑
tive value than
CTC enumeration
alone. Also, changes
in both CTCs and
CTC clusters from
baseline to the rst
follow‑up predicted
patient survival
NA Used the CellSearch
System to detect
CTCs and CTC clus‑
ters. They dened
CTC clusters as two
or more CTCs close
to each other within
the same image
eld
Baseline CTC clusters
signicantly cor‑
related with reduced
PFS outcome. CTC
clusters had more
excellent predic‑
tive value than
CTC enumeration
alone. Changes in
both CTCs and CTC
clusters signicantly
predicted patient
survival. CTC cluster
size signicantly cor‑
related with patient
outcomes [115]
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Table 2 (continued)
Study Name Study TYPE Number of patients Treatment GROUPS Primary endpoint
results Breast cancer sub‑
type CTC cluster detection
method Statistical signicance
of results
Larsson etal. [38] A prospective
observational study
(cohort study)
One hundred fty‑
six patients with
recently diagnosed
metastatic BC
They did not have
dierent treatment
groups but followed
the patients who
received systemic
therapy according
to their physician’s
discretion
Patients with CTC
clusters at baseline
had poorer OS
and PFS rates than
those without CTC
clusters. The hazard
ratio of both PFS
and OS increased
with the presence of
CTC clusters during
systemic therapy
NA Used CellSearch tech‑
nology to identify
CTCs and CTC clus‑
ters. They dened
CTC clusters as two
or more CTCs close
to each other within
the same image
eld
The patients with CTC
clusters at base‑
line had worse OS
and PFS. PFS and
OS hazard ratios
increased when CTC
clusters were present
during therapy.
Moreover, mortality
was 11 times higher
in patients with high
CTC counts (CTCs
5) and CTC clusters
compared to indi‑
viduals without these
characteristics
Costa etal. [133] Cohort study Fifty‑four female
metastatic BC
patients
They did not have
dierent treatment
groups but followed
the patients who
received various
therapies according
to their physician’s
discretion and
their BC subtype
(HR + HER2‑,
HR + HER2 + , HR‑
HER2 + , or triple‑
negative)
At baseline, the CTC
cluster showed
a higher risk of
disease progression
and death. The PFS,
OS, and survival
time were also
shorter. Further‑
more, it was discov‑
ered that patients
with a CTC cluster
of four or more
cells had a higher
likelihood of disease
progression than
those with a CTC
cluster of 2–3 cells
(which, compared
to patients without
a CTC cluster, had a
greater risk of dis‑
ease progression)
They followed the
patients according
to their BC subtype
(HR + HER2‑,
HR + HER2 + , HR‑
HER2 + , or triple‑
negative). They
found that patients
with the HR + HER2
subtype were more
frequently found to
have CTC clusters
Used the CellSearch
System to isolate
and count CTCs and
CTC clusters. They
dened CTC clusters
as two or more CTCs
close to each other
within the same
image eld
At baseline, the CTC‑
cluster had a higher
chance of disease
progression and
death, along with
shorter PFS, OS, and
survival time. Patients
with a 4 + cell CTC‑
cluster had a greater
probability of disease
progression. The
continuous existence
of CTC clusters in the
circulatory blood was
related to shorter OS
and a greater mortal‑
ity risk
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Table 2 (continued)
Study Name Study TYPE Number of patients Treatment GROUPS Primary endpoint
results Breast cancer sub‑
type CTC cluster detection
method Statistical signicance
of results
Paoletti etal. [134] prospectively
designed retrospec‑
tive translational
medicine study
They include 595
female patients
with established
BC and signs of
metastatic cancer
on clinical and/or
radiographic assess‑
ments
They had two treat‑
ment groups:
one that received
eribulin mesylate
(a chemotherapy
drug) and one that
received capecit‑
abine (another
chemotherapy
drug)
They found that
patients with dou‑
blets and clusters
had statistically
lower OS at baseline
and the First Follow‑
up than those
with couples only,
clusters only, or no
doublets or clusters.
Also, CTC clusters
were associated
with a poorer prog‑
nosis, regardless of
their detection time
NA Used the CellSearch
system to count the
CTCs, classifying
them as clusters
when there are
three or more and
as doublets when
there are two. They
used the "revised"
CellSearch CTC enu‑
meration algorithm,
which counts the
number of CTCs in
a couple or cluster
and each CTC to
determine the total
CTC enumeration
Paoletti etal. found
that patients with
doublets and clusters
had lower OS at
baseline and the
rst follow‑up. CTC
clusters were linked
to a worse prognosis,
whether discovered
at baseline or the rst
follow‑up
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Wang etal. [37] The size of CTC‑clusters and patient outcomes were found to be correlated in a time‑dependent analy‑
sis usinglongitudinal CTC and CTC cluster records, in particular OS, and a higher risk of disease progression in relation to
the size of the CTC cluster. This phenomenon was not observable in the PFS analysis but was present in OS analysis. They
claimed that larger CTC clusters produced more metastatic foci. This result disproves the traditional consensus that the
extremely tiny capillaries that separate the CTC clusters from the circulation are too thinto pass through, demonstrating
that they can pass through capillaries by unfolding into single‑cell chains [146]. The study limitations were (1) patient
enrollment and treatment were not homogeneous because the clinical trial was not prospectively designed clinical trial.
(2) Findings must be conrmed in larger, independent populations due to the small patient sample size and short follow‑
up. (3) Despite the lack of a standard for these tests, They proved that repeated CTC and CTC cluster measurements were
stronger than single ‑point enumerations in predicting patient prognosis. Also, comprehensive assessments are required
to determine how eectively these metrics work clinically.
Larsson etal. [40] identied CTCs and CTC clusters at baseline, 1, 3, and 6months after starting systemic therapy.
Patients with MBC who underwent a 6‑month longitudinal analysis of dynamic changes of CTC and CTC cluster had better
prognostication and therapy monitoring. They reported that CTC clusters detected patients with poorer outcomes and
were independently and signicantly predictive at all times. This study’s positive advantage is the prospective design of
a 6‑month assessment for CTC clusters and serial CTC in women with recently diagnosed MBC and sampling before the
initiation of rst‑line systemic treatment and systematic assessment at scheduled periods. The study limitation was the
extended period of inclusion due to restrictive inclusion criteria, which contained exclusively recently diagnosed MBC
patients prior to initiating rst‑line therapy, and the performance status score for the Eastern Cooperative Oncology
Group ranges from zero to two.
Costa etal. [133] while at baseline, the existence of CTC cluster presented prognostic signicance at follow‑up, it didn’t
due to few patients from whom samples were obtained for follow‑up (38 out of the 54 patients only 18.4% of them had
CTC clusters) and the short time of some patients’ follow‑up. CTC cluster changes from baseline to follow‑up could not
forecast patient survival or progression. Their ndings indicate that in patients with fewer than 20 CTCs, the existence of
CTC clusters added prognostic information independent of CTC count. In contrast, in patients with more than 20 CTCs,
CTC clusters had no predictive value. However, they suggested that a larger cohort study would be required to dress
this issuedress this issue adequately.
Paoletti etal. [134] found that dierent disease locations and BC subtypes did not signicantly dier in the frequency
of CTC doublets and clusters. They concluded that neither clusters nor doublets signicantly impact the course of rst‑line
chemotherapy for patients with MBC and that the number of CTC present probably caused the poor correlation between
clusters and OS. They must note that they used the "revised" CellSearch CTC enumeration algorithm. The number of CTCs
in a doublet or cluster, as well as each individual CTC, were counted to determine the total CTC enumeration, so a patient
who initially had only 1–4 CTCs (below the cuto for positivity) might have more CTCs in the revised algorithm than clas‑
sic algorithm also the power of their analysis is also limited by the size of the subgroup. They recommended that further
predictive data for patients with MBC could be obtained through longitudinal evaluation of CTC doublets and clusters.
According to Jansson etal. [36] analysis of the prognostic importance of the existence of WBC‑CTCs, at baseline or
1–3months, patients with WBC‑CTCs present did not signicantly outlive patients without WBC‑CTCs. In contrast, at
6months, patients with WBC‑CTCs had worse OS and PFS. According to Costa etal. [133], both at baseline and follow‑up,
WBC‑CTCs were linked to a greater CTC count (more than 5 CTCs/7.5mL); however, clustered WBC‑CTC was unable to
predict patient outcomes; this may be because of their small patient population and brief follow‑up period. Also, it was
noted that CD44 + CTC clusters were linked to a worse OS than CD44‑CTC clusters [22, 143]. Additionally, Jansson etal.
[36] discovered that the existence of apoptotic CTCs at 1–3 and 6months following the start of treatment was linked
to higher mortality regardless of other prognostic markers, including CTC counts and BC subtype. Paoletti etal. [107]
showed no evidence of a predictive role for apoptotic CTCs either at baseline or in follow‑up samples.
2.4 Prevention ofCTC cluster formation inBC patients
CTCs, are infrequent cellular entities within the blood’s periphery that can form clusters in BC patients [3]. These clusters
can lead to the spread of cancer and are, therefore, a target for prevention. A few research projects on mitigating metas‑
tasis. In an invivo study using the 4T1 mouse model of BC metastasis, they found that injecting clinical thrombolytic
agent urokinase‑type plasminogen activator into the host animals was an eective way to prevent CTC cluster assembly
and extend overall host survival by about 20% in comparison to control animals [147].
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Table 3 A therapeutic target to decrease breast cancer metastasis
Treatment Description Mechanism
ADGRG1 inhibitors [150] ADGRG1 is a protein that actively facilitates the process of tumorigen‑
esis, invasion/migration, and cell–cell adhesion in cells associated with
triple‑negative breast cancer
Inhibitors of ADGRG1 could prevent CTC cluster formation by blocking its
role in cell–cell adhesion
Estrogen receptor alpha (ER/ESR1)
inhibitors [151]Mutations in ER/ESR1 have been detected in 20–40% of metastatic
breast cancers resistant to endocrine therapy. These mutations are
linked to unfavorable outcomes
Inhibitors of ER/ESR1 could prevent CTC cluster formation by blocking its
role in metastasis
Chemotherapy drugs [152] Chemotherapy is the prevailing approach for managing systemic
therapy in triple‑negative breast cancer (TNBC) patients It can still eectively prevent CTC cluster formation by killing cancer cells
and preventing their spread
Customized drug screening [153] A culture assay of CTC derived from patients can be a valuable tool for
evaluating anticancer drugs to guide therapy for personalized treat‑
ment
This approach allows for evaluating drug response using patient‑derived
CTC cultures obtained from a liquid biopsy
VEGF inhibitors [55] The protein VEGF serves to activate the genesis of novel blood vessels The growth of new blood vessels that provide tumors with oxygen and
nutrients exists through inhibitors that target VEGF
Pro‑angiogenic treatment [55] The pro‑angiogenic treatment promotes the genesis of novel blood
vessels This treatment could improve blood ow to tumors, allowing for better
chemotherapy drugs and oxygen delivery
Epigen [154] Clusters promoted the expression of the low‑anity EGFR ligand epigen,
which promotes eective metastatic outgrowth and is exhibited in the
highest levels in metastatic tumors
The metastatic outgrowth was reduced by 94% upon Epigen knock‑
down. Additionally, there was a decrease in the size of lung metastases,
although the total number was not aected
Plakoglobin [155]Plakoglobin, a component of desmosomes and adherence junctions, was
overexpressed 219‑fold more in CTC clusters and was associated with
lower distant metastasis‑free survival (p = 0.008)
Eliminating intercellular contacts crucial for cluster formation was
achieved through Plakoglobin knockdown, and the count of tumor‑
derived CTC clusters decreased in experimental mouse tumors
Keratin‑14 [45] Desmosome and hemidesmosome adhesion complex genes, which
control cell–matrix adhesion, cell–cell adhesion, and immune evasion,
were abundant in keratin 14 cells
The mean number of metastases was seven times lower in keratin 14
knockdown tumors than in control tumors
ICAM‑1 [156] ICAM‑1 is a transmembrane glycoprotein crucial for melanoma cells’
adhesion to the endothelial monolayer [124]ICAM‑1 expression is increased with an increase in tumor cell adhesion.
Thus, treatment with specic anti‑ICAM‑1 antibodies decreases this
eect
Hemophilic CD44 [157] CD44, a multifaceted transmembrane glycoprotein, facilitates the
epithelial‑mesenchymal transition process [126]CD44‑positive cells exhibited a heightened propensity for tumor forma‑
tion in immunodecient mice relative to their CD44‑negative counter‑
parts
Na + /K + ATPase inhibitor [158, 159] Na + /K + ATPase exists on the cell membrane; its expression is highly
expressed in breast cancer cases Ouabain treatment inhibits the expression of Na + /K + ATPase in mice,
which inhibits distant tumor formation in multiple mouse metastasis
models
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Moreover, the clinical signicance of ICAM1 expression to patient outcomes was determined by analyzing two dis‑
tinct cohorts of BC patients. High levels of ICAM1 mRNA expression in breast tumors correlated with poorer distant
metastasis‑free survival. ICAM1 promotes metastasis by triggering cellular pathways associated with stemness and cell
cycle. Additionally, disrupting ICAM1 interactions signicantly hinders the formation of CTC clusters and tumor cell trans‑
endothelial migration. Therefore, ICAM1 presents a potential therapeutic target for initiating TNBC metastases [148].
To limit the quantity or size of CTC clusters, a variety of commonly used chemotherapeutic drugs target the cytoskel‑
eton microtubules and induce cell cycle arrest during mitosis. An invitro study investigated the impact of mitotic arrest
on the ability of BC cells to form clusters. It was discovered that the chemotherapy medicines vinorelbine and paclitaxel,
which target microtubules, impair the ability of MCF‑7 cancer cells to aggregate. They saw that MCF‑7 BC cells aggregated
poorly and formed loose clusters when experimentally synchronized and blocked in metaphase. Because microtubule‑
targeting anticancer medications prevent cancer cells from aggregating, they may lessen the chance that circulating
tumor cells would metastatically spread [149].
Here are some drugs for BC (Table3), including their mechanisms of action. These treatments include ADGRG1 inhibi‑
tors, estrogen receptor alpha inhibitors, chemotherapy drugs, customized drug screening, VEGF inhibitors, pro‑angi‑
ogenic treatment, and other medications for metastasis. Each therapy has a unique mechanism of action that could
prevent the formation of CTC clusters or improve the delivery of chemotherapy drugs and oxygen to tumors. Moreover,
the methods by which various treatments operate dier; they can block the function of specic proteins involved in
cell–cell adhesion or metastasis, eliminate cancer cells and halt their spread, improve blood ow to tumors, or obstruct
the development of new blood vessels that supply oxygen and nutrients to malignancies. These therapies aim to either
inhibit the formation of CTC clusters or enhance the delivery of chemotherapy drugs and oxygen to tumors. Further
research is essential to determine each patient’s most eective course of action.
3 Authors’ conclusion
CTC clusters, while rare, play a signicant role in the progression and spread of BC. These clusters’ unique biological
characteristics and molecular proles increase their survival, invasion, and stemness abilities. Various techniques based
on physical or immunological properties can be used to detect and isolate CTC clusters from the blood of BC patients.
CTC clusters have been linked to poorer clinical outcomes, such as reduced survival rates and an increased likelihood of
disease progression. As such, CTC clusters may be useful as biomarkers for monitoring treatment response, predicting
prognosis, and guiding personalized therapy. However, many challenges still need to be solved in CTC clusters’ study and
clinical application, including their low frequency, heterogeneity, dynamicity, and standardization. Further research is
required to better understand the origin, composition, mechanisms of action, and potential therapeutic targets of CTC
clusters in BC and to develop more sensitive and reliable methods for their detection and characterization.
Author contributions Study concept and design: Zeinab S. Sayed; Mohamed G. Khattap; Noha S. Yasen. Searching the literature: Hanan A.
Elbary; Reem A. Elsayed, Islam Omar, Mostafa A. Madkour; Dalia A. Abdelkawy. Data collection: Zeinab S. Sayed, Mostafa A. Madkour, Noha
S. Yasen; Reem A. Elsayed. Manuscript drafting: Mohamed G. Khattap; Hanan A. Elbary, Islam Omar, Dalia A. Abdelkawy; Al‑Hassan Soliman
Wadan. Manuscript revision: Al‑Hassan Soliman Wadan; Mohamed H. Nafady. Supervision: Mohamed H. Nafady.
Funding Open access funding provided by The Science, Technology & Innovation Funding Authority (STDF) in cooperation with The Egyptian
Knowledge Bank (EKB). The authors declare that no funds, grants, or other support were received during the preparation of this manuscript.
Data availability No data associated with the manuscript.
Declarations
Ethics approval and consent to participate Not applicable.
Competing interests The authors have no relevant nancial or non‑nancial interests to disclose.
Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adapta‑
tion, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source,
provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article
are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in
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the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will
need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http:// creat iveco mmons. org/ licen ses/ by/4. 0/.
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