Open access peer-reviewed chapter
Abstract
New ways of looking at tumor genetics and dynamics have been developed: the Liquid Biopsy (LB), which has been incorporated into clinical practice as a noninvasive analysis of circulating material derived from tumors, which represents an innovative tool in precision oncology and overcomes the current limitations associated with tissue biopsies. An LB is a new tool of great value, constituting a diagnostic, prognostic, and predictive marker. The elements that makeup LB are circulating tumor cells (CTCs) and circulating tumor nucleic acids (ctNA: DNA or RNA) in free cells or contained in exosomes, microvesicles, and platelets. The ctDNA and CTCs are the only one’s components with a clinical application approved by the US Food and Drug Administration (FDA).
Keywords
- cancer
- NGS
- blood sample
- ctDNA
- CTC
1. Introduction
Precision medicine is an innovative approach to disease prevention and treatment that considers differences in people’s genes, injuries, environments, and lifestyles to target the right therapies to the right patients at the right time. In oncology, precision medicine uses genetic and molecular information to develop more specific and optimized drugs or treatments, with the aim that the therapy is the most appropriate to treat an individual, with greater effectiveness and a decrease in side effects. Therapeutic advances in genomic-guided precision oncology rely on prospective molecular identification of oncogenic alterations and resistance mechanisms to guide precise treatments. Many new therapeutic agents require the presence of biomarkers to direct their mechanism of action, and the tumor tissue is the reference sample [1].
In cancer patients, biopsies have been used to diagnose the disease for 1000 years through the histological definition of the disease and the tumor’s genetic profile [2]. However, its obtaining presents certain limitations, including the discomfort suffered by the patient when taking the sample, the inherent clinic of his disease, possible surgical complications, and economic considerations. Also, some tumors are inaccessible due to their anatomical location, as in the case of the lung, so obtaining a representative and sufficient sample to perform an adequate molecular study can be complex. If the sample is inadequate, re-biopsy should be considered, with the consequent risk to the patient, who should undergo an invasive procedure again. In addition, this leads to a delay in the result, which can be crucial to establishing the most appropriate treatment for the patient’s situation [2].
Unfortunately, it has been shown that a portion taken from different parts of a primary tumor and its metastases showed extensive inter-tumor and intra-tumor evolution. Tumors present enormous heterogeneity, as Gerlinger et al. found in their study, so that each area of the tumor has its genetic characteristics, which may result in the sample analyzed not being representative of all tumor cells, producing discordant results between samples from the same patient [3]. This tumor heterogeneity highlights the difficulty of dictating a therapeutic course of action based on a single biopsy, as it is likely to underestimate its complexity [4, 5]. Also, tumors are not static, and their molecular characteristics can change with the development of the disease. Selecting resistant subclones due to targeted drugs may intervene in the appearance of new genetic alterations, which produce molecular differences between the primary tumor and its metastases [3].
This tumor heterogeneity demonstrates the difficulty of selecting a therapy based on a single biopsy, as it is likely to underestimate the genomic complexity of the tumor (Figure 1).
Figure 1.
Tumor heterogeneity in patients with metastases implies that the analysis of several tissue biopsies needs to be addressed for complete genotyping. Unlike liquid biopsy, a single sample allows the study of the drainage material of all tumors simultaneously, either primary or metastasis. This analysis can be performed on ctDNA/cfDNA from plasma or circulating tumor cells from anticoagulated whole blood (“created with
Considering these limitations in individual biopsies, new ways of looking at tumor genetics and dynamics have been developed: the Liquid Biopsy, which has been incorporated into clinical practice as a noninvasive analysis of circulating material derived from tumors, which represents an innovative tool in precision oncology and overcomes the current limitations associated with tissue biopsies [6]. Liquid Biopsy is a new tool of great value, constituting a diagnostic, prognostic, and predictive marker. It allows diagnosing the disease by detecting genetic material or cells from the tumor in the blood, checking if a person is cured (if there is no presence of genetic material or tumor cells in the blood) or if, on the contrary, he suffers from a minimal residual disease, evaluating the effect of the treatment by measuring in real time the fluctuations of genetic material from the tumor and detect possible genetic alterations that indicate resistance to the drugs used. All this with a blood draw [5, 7].
The elements that makeup BL are circulating tumor cells (CTCs) and circulating tumor nucleic acids (ctNA: DNA or RNA) in free cells or contained in exosomes, microvesicles, and platelets (Figure 2). The ctDNA and CTCs are the only one’s components with a clinical application approved by the US Food and Drug Administration (FDA) [8].
Figure 2.
Liquid biopsy may be taken, for example, after the patient’s diagnosis, from a venipuncture, and after sample processing, allowing the analysis of their analytes with different technical approaches. In the same way, this type of sample can be studied during follow-up, especially in case of resistance to the treatment (“created with
2. Cell-free DNA
DNA was discovered in 1869 by a Swiss physician, Friedrich Miescher, who obtained the first crude purification of “nuclein” due to its occurrence in the cells’ nuclei, and the double helix structure of DNA was discovered in 1953 [9, 10].
Although it is believed that free circulating nucleic acids are a recent finding, as early as 1948, before determining the structure of DNA, Mandel et al. found nucleic acids in the blood of healthy individuals, unknowingly that it would be the first step toward “liquid biopsy” [11].
The cfDNA is usually a double-stranded DNA whose length ranges between 100 and 300 base pairs. On many occasions, the length of cfDNA corresponds to the characteristic pattern of the process of apoptosis of multiples of 180 base pairs. There are at least two potential, but not mutually exclusive, mechanisms by which DNA can enter the bloodstream. These mechanisms can be classified into passive and active mechanisms [12]:
The passive mechanism, the primary cause of the presence of cfDNA in the blood, is due to release when normal cell damage occurs during the process of apoptosis or in situations of necrosis, where cells release nuclear DNA and mitochondrial DNA into circulation during cell destruction.
The active release of DNA has been identified in studies with cultured cell lines of different origins, raising the hypothesis of the spontaneous release of DNA fragments into circulation.
Multiple theories have been formulated to explain why cancer cells actively release DNA into circulation, including the possibility that cancer cells release oncogenic DNA to affect the transformation of susceptible cells at distant sites and thus generate invasion in other organs [13].
It has been observed that in cancer patients, cfDNA levels are much higher than those in healthy individuals because as the tumor increases in size, it induces both adjacent healthy cells and tumor cells to be apoptotic and necrotic processes. Considering this event, cfDNA belonging to tumor cells called circulating tumor DNA (ctDNA) can also be found in the blood. The amount of cfDNA that comes from tumor cells (ctDNA) depends on the characteristics of each tumor such as its size, the stage in which it is or its ability to invade the vascular endothelium [14].
Blood ctDNA analysis offers a novel clinical application to detect tumor-specific genetic aberrations in patients. This approach has a more excellent dynamic range than cfDNA, is more specific, and has many potential clinical applications. However, it is also technically more challenging due to high levels of cfDNA originating from the initial nontumor tissue. High analytical sensitivity and specialized equipment for ctDNA detection are required because the quantity and quality of tumor-derived DNA can vary dramatically. Techniques allow reliable monitoring of tumor-associated genetic aberrations, including somatic mutations, loss of heterozygosity, and chromosomal aberrations in the blood at frequencies as low as 0.01% [15].
In addition, ctDNA can also be detected in biological fluids other than blood, such as urine, cerebrospinal fluid, or pleural fluid, which further increases its diagnostic possibilities [16].
2.1 Cell-free DNA analysis
The success of Liquid Biopsy analysis is strictly related to the preanalytical steps, including blood, sampling, storage, and processing. Delays between plasma extraction and isolation may increase background levels due to DNA derived from the lysis of peripheral blood cells. The primary source of cfDNA is plasma that is isolated in peripheral blood. Plasma is preferred to serum because normal DNA can be released during coagulation, resulting in a more significant dilution of ctDNA. EDTA tubes or tubes containing formaldehyde-free preservative reagents should be used to prevent clotting and DNAase activity for blood collection. When EDTA-containing tubes are used to collect blood, plasma separation should be performed within 4 hours of removal to prevent lysis of leukocytes [16, 17].
The ctDNA generally represents between 0.01 and 10% of cfDNA, so its detection requires high analytical capacity and sensitivity [16]. In this context, next-generation sequencing (NGS) allows cancer diagnosis and improves the prognosis and the monitoring of the efficacy of therapies. Several different NGS platforms use different sequencing technologies, but all these platforms sequence millions of small DNA fragments in parallel. Bioinformatics analyses aim to piece together these fragments by mapping the individual reads to the human reference genome (pipelines). Each of the three billion bases in the human genome is sequenced several times to provide accurate data and insight into unexpected DNA variation. NGS can sequence whole genomes or specific genomic areas of interest, including all 22,000 coding genes, whole-genome sequencing (WGS), and whole-exome sequencing (WES), which is a genomic technique for sequencing all of the protein-coding regions of genes in a genome, known as the exome; or small numbers of individual genes (NGS panels) [18].
Figure 3 shows the mathematical relationship between the kb covered by the sequencing and the depth of readings obtained, which is inversely proportional. In a ctDNA, as input is scarce, panels of a few genes up to approximately 300 genes are the most used technique, with a desired depth of more than 1000X. Although WGS has been used with ctDNA, the depth used is 0.1 x (Tumor Fraction).
Figure 3.
Next-generation sequence approaches according to the properties of each method (“created with
Emphasis will be placed in Liquid Biopsy on the following:
Tumor Mutation Burden (TMB) is the number of mutations per megabase of DNA (Mut/Mb). It indirectly measures the neoantigens needed to boost the immune response. This measure correlates with response to immunotherapy [19].
Tumor Burden (ctDNA/cfDNA ratio) is the quantity of ctDNA related to the total amount of cfDNA and has been suggested as a tool for prognostication and follow-up in patients. The ctDNA generally represents between 0.01 and 10% of cfDNA, so its detection requires high analytical capacity and sensitivity. However, the prognostic value of ctDNA and its relation to tumor burden has yet to be substantiated [20].
Fragmentomic is the pattern in length of cfDNA originating in different types of cells. Neoplasms result in altered fragmentomic profiles of cfDNA that could help identify tumors in early stages since they vary according to the stage, localization, and tissue origin [21].
Methylomic is the study of the addition of a methyl group (-CH3) to a cytokine base (C) of DNA located before, continuously, to a guanine (G). It is the principal epigenetic mechanism and can cause alterations in transcription without the need for an alteration in the DNA sequence. It plays a critical regulatory role in the onset and progression of cancer. Methylation signatures are encoded in cfDNA, and this information is helpful for diagnosis but can also be harnessed to identify the location of tumors, especially those of unknown primary [22].
Tumor Fraction (TFx) is an estimate using computational tools of the fraction of tumors in cell-free DNA from ultra-low-pass whole-genome sequencing (ULP-WGS, 0.1x coverage). Different algorithms exist for calculating TFx from cfDNA data, such as ichorCNA and ACE. TFx could correlate with clinical features associated with overall survival, and decreased TFx could be a promising biomarker for initial therapeutic response. Quantification of transcription factors (TF) in ctDNA has the potential to serve as a pragmatic, tumor-independent prognostic tool [23].
Clonal Hematopoiesis of Indeterminate Potential (CHIP) is defined as the age-related accumulation of somatic mutations in hematopoietic stem cells, which leads to clonal expansion of mutations in blood cells and is a primary source of false-positive results from ctDNA analysis [24].
MicroSatellite Instability (MSI) is genetic hypermutability resulting from impaired DNA mismatch repair (MMR). This measure correlates with response to immunotherapy [25].
Research on cfDNA has recently increased thanks to new digital genomic technologies that allow us to find rare variants of different mutations in DNA, such as digital PCR (dPCR), BEAMing (beads, emulsion, amplification, and magnetics), and polymerization activated by pyrophosphorolysis [18].
In all cases, Liquid Biopsy allows the study of druggable tumor markers, the follow-up of the patient throughout the treatment, and the detection of resistance to it. With a single sample and over time using only a blood sample, it is possible to detect and identify in real-time the tumor analytes drained into the bloodstream that characterizes the tumor and its metastases with high sensitivity and specificity (Figure 4).
Figure 4.
Throughout the patient’s follow-up, serial liquid biopsies can be taken to be evaluated, and therapeutic decisions can be made based on their results (“created with
3. Circulating tumor cell (CTC)
Circulating Tumor Cells (CTCs) are, by definition, epithelial cells, which means they present an epithelial phenotype characterized by the expression of markers such as E-cadherin, Cytokeratins family (CKs), Epithelial splicing regulator1 (ESPR1), Zonula occludens (ZO), and Epithelial cellular adhesion molecule (EpCAM). These epithelial markers are crucial for maintaining the architectural integrity of cells [26, 27, 28].
E-cadherin, in particular, plays a significant role in supporting epithelial tissue architecture and is a critical component of adherens junctions [29]. The downregulation of E-cadherin during tumoral processes is associated with increased dissemination ability of tumor cells (TCs) and the progression of Epithelial-Mesenchymal Transition (EMT) [30].
CKs are intermediate filaments forming a complex network extending from the nucleus’s surface to the periphery of epithelial cells [31]. They are essential cytoskeleton components and include a large protein family with up to 20 types found in various epithelial tissues. Among the principal CKs are CK7, CK8, CK18, and CK19. Like E-cadherin, CKs’ expression is associated with the disease’s evolution and dissemination ability.
ESPR1 is a protein that exhibits high expression associated with the epithelial phenotype under pathophysiological conditions like cancer. It specifically regulates the expression of FGFR2-IIIb, an epithelial cell-specific isoform of FGFR2. Its downregulation is linked to the EMT process [32].
ZO refers to cytological structures in epithelium and endothelium cells, creating an impenetrable barrier preventing the free flow of substances between cells. These structures consist of a protein network that approximates the lipid membranes of adjacent cells, including Claudins and Ocludins. The downregulation of these proteins is involved in the initial steps of the EMT process [33].
EpCAM is a cell surface glycoprotein highly expressed in epithelial cancer cells, mediating cell-cell adhesion in epithelia [34, 35]. The expression of this protein depends on the stage of EMT. CTCs face various pressures as they circulate through the bloodstream and encounter different microenvironments in the body [36]. Blood flow shear stress affects the physical properties of CTCs, potentially altering their shape, size, and adhesion properties. Additionally, they navigate through narrow capillaries and small vessels, which may influence their ability to establish secondary tumors in distant organs.
Furthermore, CTCs encounter immune system pressure since the immune system recognizes them as foreign entities [37]. Like natural killer (NK) cells and cytotoxic T cells, immune cells exert pressure on CTCs to eliminate them from circulation. CTCs may evade immune surveillance by downregulating surface antigens and immune checkpoint proteins [38]. Upon reaching distant organs, CTCs encounter unique microenvironments with varying nutrient availability, oxygen levels, and interactions with the extracellular matrix. Adapting to these microenvironments is essential for CTC survival and metastatic formation.
CTCs acquire new biological features in response to these pressures, leading to morphological heterogeneity. This heterogeneity is associated with EMT, where CTCs can exhibit different cellular characteristics, such as retaining an epithelial phenotype resembling the original tumor cells, showing a more mesenchymal phenotype, or even displaying hybrid phenotypes with both epithelial and mesenchymal markers [39, 40].
EMT is a complex biological process through which epithelial cells undergo molecular changes resulting in acquiring mesenchymal characteristics and losing the epithelial phenotype. EMT involves a loss of cell-cell adhesion, cytoskeleton rearrangement, and gene expression changes. N-cadherin and other factors play a significant role in promoting the mesenchymal characteristics of transitioning cells [41, 42]. While EMT is necessary for CTC survival, its persistence may inhibit tumor cell proliferation. The process is reversible, and it is thought that CTCs may acquire an epithelial phenotype after undergoing EMT. However, the reversion may not be complete, leading to differences between tumor cells from the primary tumor and those found in metastases [43].
3.1 Molecular dynamics of CTCs induced by interaction with the microenvironment
The phenotypic and morphological heterogeneity is a result of genetic and epigenetic changes. As a critical survival mechanism for these CTCs, the EMT process activation involves the regulation of different gene pathways, biochemical pathways, and metabolic reprogramming [39].
The regulation and activation of EMT are complex processes involving numerous gene pathways. The activation of N-cadherin, a canonical gene in this process, is governed by p120 catenin, which localizes N-cadherin at cholesterol-rich microdomains [44]. When N-cadherin’s extracellular domains initially bind, it triggers the activation of Rac, a member of the Rho GTPase family. This activation promotes localized actin filament assembly and the formation of membrane protrusions at cell-cell contact points [45]. Subsequently, RhoA, another member of the Rho GTPase family, becomes activated, displacing Rac’s function. RhoA facilitates the maturation of N-cadherin-based cell-cell junctions by causing β-catenin to be sequestered into the cadherin intracellular domain [46]. β-catenin plays a crucial role by linking to α-catenin, which accumulates at newly formed cell-cell junctions and suppresses actin branching.
Furthermore, α-catenin anchors the N-cadherin-catenin complex to the actin cytoskeleton through actin-binding proteins like cortactin and α-actinin, thus promoting the maturation of cell-cell contacts [47]. Notably, the adhesive function of N-cadherin is regulated by posttranslational modifications of the N-cadherin-catenin complex. For instance, the stability of the N-cadherin-catenin complex heavily relies on the phosphorylation status of N-cadherin and the associated catenins, which are under the control of tyrosine kinases such as Fer and Src, as well as the tyrosine phosphatase PTP1B. These posttranslational modifications can influence the strength and dynamics of cell–cell adhesion mediated by N-cadherin, ultimately affecting various cellular processes, including EMT [48]. Therefore, the Upregulation of N-cadherin identifies an aggressive phenotype associated with an increased ability of CTCs to migrate [49]. CTCs can migrate as single cells or clusters, a “collective cell migration” [50, 51]. Collective cell migration facilitates the invasion of epithelial cells through the localized tumor-host microenvironment, thereby promoting metastasis [52]. Additionally, this process allows the maintenance of physical interconnectivity, collective cell polarity, and coordinated cytoskeletal activity and facilitates a more efficient directional migration in response to a chemotactic gradient than individual migrating cells. This is an interesting point since the ability of CTCs to survive is higher when they travel in clusters [53]. Circulating tumor cells (CTCs) and their clusters, known as circulating tumor microemboli (CTM), are related to tumor heterogeneity and clonal evolution [54]. These CTM exhibit distinct phenotypic and molecular characteristics compared to single CTCs and demonstrate higher metastatic potential and resistance to apoptosis compared to their single-cell counterparts [55]. The microemboli are composed of different cell types, including immune cells such as neutrophils or platelets [56]. CTM exhibits a different molecular profile compared to single cells. In this way, it has been demonstrated that CTM’s epigenetic profile differs from single CTCs. Similarly, single-cell RNA sequencing revealed very little difference in expression patterns among single CTCs and CTM [57]. Recent works have demonstrated that the association of tumor cells with immune cells, such as platelets, can modify the expression of pathway genes correlated with EMT and promote the expression of stemness [58, 59]. Platelets have also been shown to decrease NK cell antitumor activity through a TGF-β-mediated decrease in NKG2D [60]. An exciting aspect of these interactions with platelets is the exchange of biological information between CTCs and platelets through direct interaction, making this transference of biomolecules a bidirectional process [61]. The transfer of biomolecules from platelets to tumor cells involves an increase in proliferation pathways, inhibition of antiapoptotic pathways, and even modification of lipid composition of the nuclear and cell membranes. The main consequence of this exchange is the modification at functional, genetic, and phenotypic levels [59].
Regarding the interaction with other immune cells, neutrophils play a significant role [62]. Neutrophils promote cell cycle progression [63]. Like platelets, CTCs can interact indirectly by secreting soluble factors, and they can also directly interact with neutrophils through different receptors, including VCAM1, ICAM-1, and β1 integrin. Interestingly, there is a strong alliance between platelets, neutrophils, and CTCs, as releasing soluble mediators, such as CXCL5 or CXCL7, by activated platelets promotes the recruitment of neutrophils [64]. The interaction with neutrophils, thus, favors the formation and arrest of tumor cell/neutrophil complexes on the endothelium wall, which supports the survival of CTCs in the blood system [65].
All this evidence suggests that the association of CTCs with different nontumor cells, such as platelets or neutrophils, is an essential process in the dissemination, migration, and survival of CTCs. These interactions can induce the expression of transcription factors (TFs) that allow the activation of the EMT process [66]. It has been demonstrated that these interactions with different immune cells promote the activation of the TFs Twist1 and Snail, both of which are associated with the EMT process [67]. Twist1 is an essential helix–loop–helix transcription factor involved in embryogenesis and tumor development and progression through the activation of EMT [68]. This transcription factor negatively acts on the E-box of E-cadherin. Its role in metastasis and CTC diffusion implicates complex relationships with oncogenic and antioncogenic proteins.
Additionally, these interactions induce the activation of the AKT2 and PI3K pathways. AKT2 is a member of the protein kinase B (PKB) family, which are serine/threonine protein kinases [69, 70]. The oncogenic serine/threonine kinase AKT, a downstream effector of the phosphatidylinositol 3′ kinase (PI3K), has been described as a transcriptional repressor of the E-cadherin gene. Both elements are associated with EMT and are used to classify the presence of CTCs with EMT phenotype [71]. They are part of the PI3K/AKT/mTOR pathway, which plays a significant role in the motility of cancer cells. The AKT pathway is pivotal in EMT and has a nodal function for extracellular and intracellular signaling pathways. Furthermore, the regulation of AKT depends on the Upregulation of PI3K expression and the downregulation of the phosphatase PTEN expression.
The Phosphatase and Tensin Homolog (PTEN) gene is a critical tumor suppressor gene that significantly regulates cell growth, survival, and proliferation. It encodes a protein called PTEN, which functions primarily as a lipid phosphatase, modulating the levels of phosphatidylinositol (3,4,5)-trisphosphate (PIP3) within cells. Additionally, EMT can induce several receptors that mediate interactions between neutrophils and CTCs, or between CTCs and platelets/fibrin, including CD44, ICAM-1, αvβ3, and VCAM1 [72].
One of the significant consequences of EMT in CTCs is its impact on antiapoptotic pathways [73]. Epithelial cells usually have strong cell–cell adhesion, which provides a protective environment and promotes cell survival. However, CTCs lose these tight cell-cell adhesions during EMT, making them more vulnerable to apoptosis or programmed cell death. Nevertheless, acquiring mesenchymal characteristics during EMT helps CTCs escape apoptosis signals and gain a survival advantage. These interactions can promote, in the same way, the Upregulation of antiapoptotic proteins, such as Bcl-2 and Bcl-xL, which inhibit the intrinsic pathway of apoptosis [74]. These proteins prevent mitochondrial outer membrane permeabilization and the release of pro-apoptotic factors, thereby protecting CTCs from apoptosis. Additionally, EMT can also downregulate pro-apoptotic proteins, like Bax and Bak, which are involved in promoting apoptosis. The reduction of these proteins further contributes to the resistance of CTCs to apoptosis signals [75].
The survival and capacity of CTCs have also been correlated with the acquisition of characteristics of CSCs (Cancer Stem Cells) [76]. Different hypotheses have been proposed to understand the presence of a subpopulation of CTCs with stem cell properties. One of them is based on the fact that tumor somatic cells undergoing EMT migrate from the primary tumor into the blood. The second hypothesis suggests that fully differentiated cancer cells can acquire these stem cell properties due to the induction of EMT pathways [77, 78]. As mentioned in previous works, the interaction of CTCs (somatic cells) with platelets could induce the expression of genes associated with stem cell markers. Among these markers are REX1, OCT4, and NANOG. OCT4 and NANOG have been found to activate and regulate REX-1 (Zfp-42) cooperatively. REX-1 is a pluripotency marker usually found in undifferentiated embryonic stem cells [34]. OCT4, NANOG, SOX-2, and REX-1 are essential elements of self-regulation, and substantial evidence shows these transcription factors’ epigenetic role in regulating stem cells [79].
4. Conclusions
Precision Medicine aims to eliminate the “one-size-fits-all” patient management model but needs tissue biopsies to identify druggable biomarkers. Nevertheless, tissues may be scarce or inaccessible for molecular studies. Liquid Biopsy is an effective alternative to select patients who may benefit from specific treatments, constituting a diagnostic, prognostic, and predictive tool. The Liquid Biopsy allows for diagnosing the disease by detecting ctDNA or CTCs in the blood, checking if a person has resolved their disease or if, on the contrary, they suffer from a minimal residual disease that can increase. Liquid Biopsy evaluates the result of the treatment by measuring in real time the fluctuations of the tumor analytes and detecting genetic alterations that determine resistance to the drugs used. The ctDNA and CTCs are the only components of Liquid Biopsy with a clinical application approved.
One of the main benefits of ctDNA is that it allows it to preserve the molecular characteristics of the tumor tissue from which it comes, including mutations, epigenetic changes, and copy number variations. This property makes the blood acquire a potential utility as a surrogate of the tumor, which can identify actionable or druggable alterations in circulating tumor-derived DNA.
CTCs’ morphological heterogeneity reflects the genetic and phenotypic diversity they acquire during EMT. This cellular plasticity allows CTCs to adapt to different microenvironments and survive, contributing to cancer metastasis. It is only possible to fully understand the biology of CTCs by analyzing their microenvironment. The ability of CTCs to survive, inhibit apoptosis pathways, and induce stemness could depend on direct and indirect interactions with other cell populations that coexist with them.
References
- 1.
Sholl LM, Aisner DL, Varella-Garcia M, Berry LD, Dias-Santagata D, Wistuba II, et al. Multi-institutional oncogenic driver mutation analysis in lung adenocarcinoma: The lung cancer mutation consortium experience. Journal of Thoracic Oncology. 2015; 10 :768-777. DOI: 10.1097/JTO.0000000000000516 - 2.
Crowley E, Di Nicolantonio F, Loupakis F, Bardelli A. Liquid biopsy: Monitoring cancer-genetics in the blood. Nature Reviews. Clinical Oncology. 2013; 10 :472-484. DOI: 10.1038/nrclinonc.2013.110 - 3.
Gerlinger M, Rowan AJ, Horswell S, Math M, Larkin J, Endesfelder D, Gronroos E, Martinez P, Matthews N, Stewart A, Tarpey P, Varela I, Phillimore B, Begum S, McDonald NQ , Butler A, Jones D, Raine K, Latimer C, Santos CR, Nohadani M, Eklund AC, Spencer-Dene B, Clark G, Pickering L, Stamp G, Gore M, Szallasi Z, Downward J, Futreal PA, Swanton Cet al. Intratumor heterogeneity and branched evolution revealed by multiregion sequencing. The New England Journal of Medicine 2012; 366 :883-892. DOI: 10.1056/NEJMoa1113205 - 4.
Bettegowda C, Sausen M, Leary RJ, Kinde I, Wang Y, Agrawal N, et al. Detection of circulating tumor DNA in early- and late-stage human malignancies. Science Translational Medicine. 2014; 6 :224ra24. DOI: 10.1126/scitranslmed.3007094 - 5.
Jamal-Hanjani M, Quezada SA, Larkin J, Swanton C. Translational implications of tumor heterogeneity. Clinical Cancer Research. 2015; 21 :1258-1266. DOI: 10.1158/1078-0432.CCR-14-1429 - 6.
Serrano MJ, Garrido-Navas MC, Diaz Mochon JJ, Cristofanilli M, Gil-Bazo I, Pauwels P, et al. International society of liquid biopsy. Precision prevention and cancer interception: The new challenges of liquid biopsy. Cancer Discovery. 2020; 10 :1635-1644. DOI: 10.1158/2159-8290.CD-20-0466 - 7.
Rolfo C, Mack PC, Scagliotti GV, Baas P, Barlesi F, Bivona TG, Herbst RS, Mok TS, Peled N, Pirker R, Raez LE, Reck M, Riess JW, Sequist LV, Shepherd FA, Sholl LM, Tan DSW, Wakelee HA, Wistuba II, Wynes MW, Carbone DP, Hirsch FR, Gandara DR. Liquid biopsy for advanced non-small cell lung cancer (NSCLC): A statement paper from the IASLC. Journal of Thoracic Oncology 2018;13:1248-1268. DOU: 10.1016/j.jtho.2018.05.030 - 8.
de Rubis G, Rajeev Krishnan S, Bebawy M. Liquid biopsies in cancer diagnosis, monitoring, and prognosis. Trends in Pharmacological Sciences. 2019; 40 :172-186. DOI: 10.1016/j.tips.2019.01.006 - 9.
Dahm R. Friedrich Miescher and the discovery of DNA. Developmental Biology. 2005; 278 :274-288. DOI: 10.1016/j.ydbio.2004.11.028 - 10.
Watson JD, Crick FH. Molecular structure of nucleic acids; a structure for deoxyribose nucleic acid. Nature. 1953; 171 (4356):737-738. DOI: 10.1038/171737a0 - 11.
Mandel P, Metais P. Les acides nucléiques du plasma sanguin chez l’homme [Nuclear Acids In Human Blood Plasma]. Comptes Rendus des Seances de la Societe de Biologie et de Ses Filiales. 1948; 142 :241-243 - 12.
Bohers E, Viailly PJ, Jardin F. cfDNA sequencing: Technological approaches and Bioinformatic issues. Pharmaceuticals (Basel). 2021; 14 :596. DOI: 10.3390/ph14060596 - 13.
Fares J, Fares MY, Khachfe HH, Salhab HA, Fares Y. Molecular principles of metastasis: A hallmark of cancer revisited. Signal Transduction and Targeted Therapy. 2020; 5 :28. DOI: 10.1038/s41392-020-0134-x - 14.
Volik S, Alcaide M, Morin RD, Collins C. Cell-free DNA (cfDNA): Clinical significance and utility in cancer shaped by emerging technologies. Molecular Cancer Research. 2016; 14 :898-908. DOI: 10.1158/1541-7786.MCR-16-0044 - 15.
Xia L, Li Z, Zhou B, Tian G, Zeng L, Dai H, et al. Statistical analysis of mutant allele frequency level of circulating cell-free DNA and blood cells in healthy individuals. Scientific Reports. 2017; 7 :7526. DOI: 10.1038/s41598-017-06106-1 - 16.
Malapelle U, Pisapia P, Addeo A, Arrieta O, Bellosillo B, Cardona AF, et al. Liquid biopsy from research to clinical practice: Focus on non-small cell lung cancer. Expert Review of Molecular Diagnostics. 2021; 21 :1165-1178. DOI: 10.1080/14737159.2021.1985468 - 17.
Pisapia P, Luis Costa JL, Pepe F, Russo G, Gragnano G, Russo A, et al. Next generation sequencing for liquid biopsy-based testing in non-small cell lung cancer in 2021. Critical Reviews in Oncology/Hematology. 2021; 161 :103311. DOI: 10.1016/j.critrevonc.2021.103311 - 18.
Denninghoff VC. Molecular pathology in the new age of personalized medicine [internet]. In: Pathology - from Classics to Innovations. London, UK, London, UK: IntechOpen; 2021. DOI: 10.5772/intechopen.94927 - 19.
Lawlor RT, Mattiolo P, Mafficini A, Hong SM, Piredda ML, Taormina SV, et al. Tumor mutational burden as a potential biomarker for immunotherapy in pancreatic cancer: Systematic review and still-open questions. Cancers (Basel). 2021; 13 :3119. DOI: 10.3390/cancers13133119 - 20.
Arisi MF, Dotan E, Fernandez SV. Circulating tumor DNA in precision oncology and its applications in colorectal cancer. International Journal of Molecular Sciences. 2022; 23 :4441. DOI: 10.3390/ijms23084441 - 21.
Ding SC, Lo YMD. Cell-free DNA Fragmentomics in liquid biopsy. Diagnostics (Basel). 2022; 12 :978. DOI: 10.3390/diagnostics12040978 - 22.
Shimizu D, Taniue K, Matsui Y, Haeno H, Araki H, Miura F, et al. Pan-cancer methylome analysis for cancer diagnosis and classification of cancer cell of origin. Cancer Gene Therapy. 2022; 29 :428-436. DOI: 10.1038/s41417-021-00401-w - 23.
Husain H, Pavlick DC, Fendler BJ, Madison RW, Decker B, Gjoerup O, et al. Tukachinsky H tumor fraction correlates with detection of actionable variants across > 23,000 circulating tumor DNA samples. JCO Precision Oncology. 2022; 6 :e2200261. DOI: 10.1200/PO.22.00261 - 24.
Chan HT, Chin YM, Nakamura Y, Low SK. Clonal Hematopoiesis in liquid biopsy: From biological noise to valuable clinical implications. Cancers (Basel). 2020; 12 :2277. DOI: 10.3390/cancers12082277 - 25.
Tieng FYF, Abu N, Lee LH, Ab Mutalib NS. Microsatellite instability in colorectal cancer liquid biopsy-current updates on its potential in non-invasive detection, prognosis and as a predictive marker. Diagnostics (Basel). 2021; 11 :544. DOI: 10.3390/diagnostics11030544 - 26.
Mocellin S, Keilholz U, Rossi CR, Nitti D. Circulating tumor cells: The ‘leukemic phase’ of solid cancers. Trends in Molecular Medicine. 2006; 12 :130-139. DOI: 10.1016/j.molmed.2006.01.006 - 27.
Warzecha CC, Shen S, Xing Y, Carstens RP. The epithelial splicing factors ESRP1 and ESRP2 positively and negatively regulate diverse types of alternative splicing events. RNA Biology. 2009; 6 :546-562. DOI: 10.4161/rna.6.5.9606 - 28.
Lindley LE, Briegel KJ. Molecular characterization of TGFbeta-induced epithelial-mesenchymal transition in normal finite lifespan human mammary epithelial cells. Biochemical and Biophysical Research Communications. 2010; 399 :659-664. DOI: 10.1016/j.bbrc.2010.07.138 - 29.
Gall TM, Frampton AE. Gene of the month: E-cadherin (CDH1). Journal of Clinical Pathology. 2013; 66 :928-932. DOI: 10.1136/jclinpath-2013-201768 - 30.
Thiery JP, Sleeman JP. Complex networks orchestrate epithelial-mesenchymal transitions. Nature Reviews. Molecular Cell Biology. 2006; 7 :131-142. DOI: 10.1038/nrm1835 - 31.
Serrano MJ, Lorente JA, Delgado Rodríguez M, Fernández A, Fernández M, de la Torre C, et al. Circulating tumour cells in peripheral blood: Potential impact on breast cancer outcome. Clinical & Translational Oncology. 2011; 13 :204-208. DOI: 10.1007/s12094-011-0641-x - 32.
Warzecha CC, Jiang P, Amirikian K, Dittmar KA, Lu H, Shen S, et al. An ESRP-regulated splicing programme is abrogated during the epithelial-mesenchymal transition. The EMBO Journal. 2010; 29 :3286-3300. DOI: 10.1038/emboj.2010.195 - 33.
Umeda K, Matsui T, Nakayama M, Furuse K, Sasaki H, Furuse M, et al. Establishment and characterization of cultured epithelial cells lacking expression of ZO-1. The Journal of Biological Chemistry. 2004; 279 :44785-44794. DOI: 10.1074/jbc.M406563200 - 34.
Rao CG, Chianese D, Doyle GV, Miller MC, Russell T, Sanders RA Jr, et al. Expression of epithelial cell adhesion molecule in carcinoma cells present in blood and primary and metastatic tumors. International Journal of Oncology. 2005; 27 :49-57 - 35.
de Wit S, van Dalum G, Lenferink AT, Tibbe AG, Hiltermann TJ, Groen HJ, et al. The detection of EpCAM(+) and EpCAM(−) circulating tumor cells. Scientific Reports. 2015; 5 :12270. DOI: 10.1038/srep12270 - 36.
Heeke S, Mograbi B, Alix-Panabières C, Hofman P. Never travel alone: The crosstalk of circulating tumor cells and the blood microenvironment. Cell. 2019; 8 :714. DOI: 10.3390/cells8070714 - 37.
Garrido-Navas C, de Miguel-Perez D, Exposito-Hernandez J, Bayarri C, Amezcua V, Ortigosa A, et al. Cooperative and escaping mechanisms between circulating tumor cells and blood constituents. Cell. 2019; 8 :1382. DOI: 10.3390/cells8111382 - 38.
Liu X, Song J, Zhang H, Liu X, Zuo F, Zhao Y, et al. Immune checkpoint HLA-E:CD94-NKG2A mediates evasion of circulating tumor cells from NK cell surveillance. Cancer Cell. 2023; 41 :272-287.e9. DOI: 10.1016/j.ccell.2023.01.001 - 39.
Genna A, Vanwynsberghe AM, Villard AV, Pottier C, Ancel J, Polette M, et al. EMT-associated heterogeneity in circulating tumor cells: Sticky friends on the road to metastasis. Cancers (Basel). 2020; 12 :1632. DOI: 10.3390/cancers12061632 - 40.
Francart ME, Lambert J, Vanwynsberghe AM, Thompson EW, Bourcy M, Polette M, et al. Epithelial-mesenchymal plasticity and circulating tumor cells: Travel companions to metastases. Developmental Dynamics. 2018; 247 :432-450. DOI: 10.1002/dvdy.24506 - 41.
Bonnomet A, Brysse A, Tachsidis A, Waltham M, Thompson EW, Polette M, et al. Epithelial-to-mesenchymal transitions and circulating tumor cells. Journal of Mammary Gland Biology and Neoplasia. 2010; 15 :261-273. DOI: 10.1007/s10911-010-9174-0 - 42.
Jie XX, Zhang XY, Xu CJ. Epithelial-to-mesenchymal transition, circulating tumor cells and cancer metastasis: Mechanisms and clinical applications. Oncotarget. 2017; 8 :81558-81571. DOI: 10.18632/oncotarget.18277 - 43.
Jolly MK, Ware KE, Gilja S, Somarelli JA, Levine H. EMT and MET: Necessary or permissive for metastasis? Molecular Oncology. 2017; 11 :755-769. DOI: 10.1002/1878-0261.12083 - 44.
Taulet N, Comunale F, Favard C, Charrasse S, Bodin S, Gauthier-Rouviere C. N-cadherin/p120 catenin association at cell-cell contacts occurs in cholesterol-rich membrane domains and is required for RhoA activation and myogenesis. The Journal of Biological Chemistry. 2009; 284 :23137-23145. DOI: 10.1074/jbc.M109.017665 - 45.
Spiering D, Hodgson L. Dynamics of the rho-family small GTPases in actin regulation and motility. Cell Adhesion & Migration. 2011; 5 :170-180. DOI: 10.4161/cam.5.2.14403 - 46.
Huber AH, Weis WI. The structure of the β-catenin/E-cadherin complex and the molecular basis of diverse ligand recognition by β-catenin. Cell. 2001; 105 :391-402. DOI: 10.1016/s0092-8674(01)00330-0 - 47.
Desai R, Sarpal R, Ishiyama N, Pellikka M, Ikura M, Tepass U. Monomeric α-catenin links cadherin to the actin cytoskeleton. Nature Cell Biology. 2013; 15 :261-273. DOI: 10.1038/ncb2685 - 48.
Loh CY, Chai JY, Tang TF, Wong WF, Sethi G, Shanmugam MK, et al. The E-cadherin and N-cadherin switch in epithelial-to-mesenchymal transition: Signaling, therapeutic implications, and challenges. Cell. 2019; 8 :1118. DOI: 10.3390/cells8101118 - 49.
Mrozik KM, Blaschuk OW, Cheong CM, Zannettino ACW, Vandyke K. N-cadherin in cancer metastasis, its emerging role in haematological malignancies and potential as a therapeutic target in cancer. BMC Cancer. 2018; 18 :939. DOI: 10.1186/s12885-018-4845-0 - 50.
Friedl P, Gilmour D. Collective cell migration in morphogenesis, regeneration and cancer. Nature Reviews. Molecular Cell Biology. 2009; 10 :445-457. DOI: 10.1038/nrm2720 - 51.
Visal TH, den Hollander P, Cristofanilli M, Mani SA. Circulating tumour cells in the -omics era: How far are we from achieving the ‘singularity’? British Journal of Cancer. 2022; 127 :173-184. DOI: 10.1038/s41416-022-01768-9 - 52.
Wu S, Liu S, Liu Z, Huang J, Pu X, Li J, et al. Classification of circulating tumor cells by epithelial-mesenchymal transition markers. PLoS One. 2015; 10 :e0123976. DOI: 10.1371/journal.pone.0123976 - 53.
Perea Paizal J, Au SH, Bakal C. Squeezing through the microcirculation: Survival adaptations of circulating tumour cells to seed metastasis. British Journal of Cancer. 2021; 124 :58-65. DOI: 10.1038/s41416-020-01176-x - 54.
Zhang D, Zhao L, Zhou P, Ma H, Huang F, Jin M, et al. Circulating tumor microemboli (CTM) and vimentin+ circulating tumor cells (CTCs) detected by a size-based platform predict worse prognosis in advanced colorectal cancer patients during chemotherapy. Cancer Cell International. 2017; 17 :6. DOI: 10.1186/s12935-016-0373-7 - 55.
Menyailo ME, Tretyakova MS, Denisov EV. Heterogeneity of circulating tumor cells in breast cancer: Identifying metastatic seeds. International Journal of Molecular Sciences. 2020; 21 :1696. DOI: 10.3390/ijms21051696 - 56.
Kurma K, Alix-Panabières C. Mechanobiology and survival strategies of circulating tumor cells: A process towards the invasive and metastatic phenotype. Frontiers in Cell and Development Biology. 2023; 11 :1188499. DOI: 10.3389/fcell.2023.1188499 - 57.
Castro-Giner F, Aceto N. Tracking cancer progression: From circulating tumor cells to metastasis. Genome Medicine. 2020; 12 :31. DOI: 10.1186/s13073-020-00728-3 - 58.
Pereira-Veiga T, Schneegans S, Pantel K, Wikman H. Circulating tumor cell-blood cell crosstalk: Biology and clinical relevance. Cell Reports. 2022; 40 :111298. DOI: 10.1016/j.celrep.2022.111298 - 59.
Rodriguez-Martinez A, Simon-Saez I, Perales S, Garrido-Navas C, Russo A, de Miguel-Perez D, et al. Exchange of cellular components between platelets and tumor cells: Impact on tumor cells behavior. Theranostics. 2022; 12 :2150-2161. DOI: 10.7150/thno.64252 - 60.
Kopp HG, Placke T, Salih HR. Platelet-derived transforming growth factor-β Down-regulates NKG2D thereby inhibiting natural killer cell antitumor reactivity. Cancer Research. 2009; 69 :7775-7783. DOI: 10.1158/0008-5472.CAN-09-2123 - 61.
Labelle M, Begum S, Hynes RO. Direct signaling between platelets and cancer cells induces an epithelial-mesenchymal-like transition and promotes metastasis. Cancer Cell. 2011; 20 :576-590. DOI: 10.1016/j.ccr.2011.09.009 - 62.
Man Y, Minying Z, Rui N, Xiaohui Y, Shifeng T, Linlin F, et al. Roles of tumor-associated neutrophils in tumor metastasis and its clinical applications. Front Cell Developmental Biology. 2022; 10 :938289. DOI: 10.3389/fcell.2022.938289 - 63.
Leone K, Poggiana C, Zamarchi R. The interplay between circulating tumor cells and the immune system: From immune escape to cancer immunotherapy. Diagnostics (Basel). 2018; 8 :59. DOI: 10.3390/diagnostics8030059 - 64.
Braun A, Anders HJ, Gudermann T, Mammadova-Bach E. Platelet-cancer interplay: Molecular mechanisms and new therapeutic avenues. Frontiers in Oncology. 2021; 11 :665534. DOI: 10.3389/fonc.2021.665534 - 65.
Peralta M, Osmani N, Goetz JG. Circulating tumor cells: Towards mechanical phenotyping of metastasis. iScience. 2022; 25 :103969. DOI: 10.1016/j.isci.2022.103969 - 66.
Wang X, Zhao S, Wang Z, Gao T. Platelets involved tumor cell EMT during circulation: Communications and interventions. Cell Communication and Signaling: CCS. 2022; 20 :82. DOI: 10.1186/s12964-022-00887-3 - 67.
Pandolfi L, Bozzini S, Frangipane V, Percivalle E, De Luigi A, Violatto MB, et al. Neutrophil extracellular traps induce the epithelial-mesenchymal transition: Implications in post-COVID-19 fibrosis. Frontiers in Immunology. 2021; 12 :663303. DOI: 10.3389/fimmu.2021.663303 - 68.
Qin Q , Xu Y, He T, Qin C, Xu. Normal and disease-related biological functions of Twist1 and underlying molecular mechanisms. Journal of Cell Research. 2012; 22 :90-106. DOI: 10.1038/cr.2011.144 - 69.
Ward MP, E Kane L, A Norris L, Mohamed BM, Kelly T, Bates M, et al. Platelets, immune cells and the coagulation cascade; friend or foe of the circulating tumour cell? Molecular Cancer. 2021; 20 :59. DOI: 10.1186/s12943-021-01347-1 - 70.
Charles Jacob HK, Charles Richard JL, Signorelli R, Kashuv T, Lavania S, Vaish U, et al. Modulation of early neutrophil granulation: The circulating tumor cell-Extravesicular connection in pancreatic ductal adenocarcinoma. Cancers (Basel). 2021; 13 :2727. DOI: 10.3390/cancers13112727 - 71.
Smit DJ, Cayrefourcq L, Haider MT, Hinz N, Pantel K, Alix-Panabières C, et al. High sensitivity of circulating tumor cells derived from a colorectal cancer patient for dual inhibition with AKT and mTOR inhibitors. Cell. 2020; 9 :2129. DOI: 10.3390/cells9092129 - 72.
Ring A, Nguyen-Sträuli BD, Wicki A, Aceto N. Biology, vulnerabilities and clinical applications of circulating tumour cells. Nature Reviews. Cancer. 2023; 23 :95-111. DOI: 10.1038/s41568-022-00536-4 - 73.
Pang S, Xu S, Wang L, Wu H, Chu Y, Ma X, et al. Molecular profiles of single circulating tumor cells from early breast cancer patients with different lymph node statuses. Thorac Cancer. 2023; 14 :156-167. DOI: 10.1111/1759-7714.14728 - 74.
Kapoor I, Bodo J, Hill BT, Hsi ED, Almasan A. Targeting BCL-2 in B-cell malignancies and overcoming therapeutic resistance. Cell Death & Disease. 2020; 11 :941. DOI: 10.1038/s41419-020-03144-y - 75.
Carberry S, D'Orsi B, Monsefi N, Salvucci M, Bacon O, Fay J, et al. The BAX/BAK-like protein BOK is a prognostic marker in colorectal cancer. Cell Death & Disease. 2018; 9 :125. DOI: 10.1038/s41419-017-0140-2 - 76.
Aramini B, Masciale V, Arienti C, Dominici M, Stella F, Martinelli G, et al. Cancer stem cells (CSCs), circulating tumor cells (CTCs) and their interplay with cancer associated fibroblasts (CAFs): A New World of targets and treatments. Cancers (Basel). 2022; 14 :2408. DOI: 10.3390/cancers14102408 - 77.
Toloudi M, Apostolou P, Chatziioannou M, Papasotiriou I. Correlation between cancer stem cells and circulating tumor cells and their value. Case Reports in Oncology. 2011; 4 :44-54. DOI: 10.1159/000324403 - 78.
Laplane L. “the CSC Theory”. Cancer Stem Cells: Philosophy and Therapies. Cambridge, MA and London, England: Harvard University Press; 2016. pp. 27-44. DOI: 10.4159/9780674969582-004 - 79.
Shariati F, Favaedi R, Ramazanali F, Ghoraeian P, Afsharian P, Aflatoonian B, et al. Increased expression of stemness genes REX-1, OCT-4, NANOG, and SOX-2 in women with ovarian endometriosis versus normal endometrium: A case-control study. International Journal of Reproductive Biomedicine. 2019; 16 :ijrm.v16i12.3684. DOI: 10.18502/ijrm.v16i12.3684