Skip to main content

The double agents in liquid biopsy: promoter and informant biomarkers of early metastases in breast cancer

Abstract

Breast cancer continues to be a major global problem with significant mortality associated with advanced stage and metastases at clinical presentation. However, several findings suggest that metastasis is indeed an early occurrence. The standard diagnostic techniques such as invasive core needle biopsy, serological protein marker assays, and non-invasive radiological imaging do not provide information about the presence and molecular profile of small fractions of early metastatic tumor cells which are prematurely dispersed in the circulatory system. These circulating tumor cells (CTCs) diverge from the primary tumors as clusters with a defined secretome comprised of circulating cell-free nucleic acids and small microRNAs (miRNAs). These circulatory biomarkers provide a blueprint of the mutational profile of the tumor burden and tumor associated alterations in the molecular signaling pathways involved in oncogenesis. Amidst the multitude of circulatory biomarkers, miRNAs serve as relatively stable and precise biomarkers in the blood for the early detection of CTCs, and promote step-wise disease progression by executing paracrine signaling that transforms the microenvironment to guide the metastatic CTCs to anchor at a conducive new organ. Random sampling of easily accessible patient blood or its serum/plasma derivatives and other bodily fluids collectively known as liquid biopsy (LB), forms an efficient alternative to tissue biopsies. In this review, we discuss in detail the divergence of early metastases as CTCs and the involvement of miRNAs as detectable blood-based diagnostic biomarkers that warrant a timely screening of cancer, serial monitoring of therapeutic response, and the dynamic molecular adaptations induced by miRNAs on CTCs in guiding primary and second-line systemic therapy.

Key points

  • ❖ Tumor cells escape into the circulation at an early stage of transformation.

  • ❖ Metastatic tumor cells may be single cells or a polyclonal cluster of leader cells that differ in mutations and gene expressions from the primary tumors.

  • ❖ The secreted cell-free nucleic acids, small microRNAs, circulating tumor cells and proteins act as early diagnostic biomarkers of breast tumor.

  • ❖ CTCs, CTC-specific microRNAs and circulatory miRs are collectively predictive of an early metastatic spread with prospective implications as therapeutic tools for targeting metastatic cells.

Introduction

Cancer is the leading cause of death worldwide, with the incidence of female breast cancers (BCs) now surpassing lung cancer, with an estimated 2.3 million new cancer incidences and 685,000 deaths worldwide in 2020 [1]. Though this era is marked by advancements in precision diagnostics aiding an early detection of primary tumors (PTs), evidences of the presence of the undetectable systemic micrometastases that diversify even before surgical resection and later revert to recurrence, remains a persistent challenge [2]. Despite implementing best therapeutic strategies, nearly 20–30% of patients report clinical presentations of distant metastases arising from a single metastatic lesion which are capable of involving multiple organs [3, 4]. Early detection of metastatic breast cancer (MBC) entails screening for an upsurge in the levels of circulating protein tumor markers, carcinoembryonic antigen (CEA), cancer antigen (CA)-15–3, and CA-125 in liaison with simultaneous whole-body imaging [3]. The baseline expression value for these serum biomarkers varies across patients and the positive expression of few of these markers under the influence of anti-hypertensive medications and in inflammatory diseases affecting the liver, kidneys, and other organs have the capacity to impede theutility of these biomarkers in predicting MBC accurately [3]. Alternatively, the metastatic potential of node-positive and node-negative breast tumors is evaluated based on the protein levels of serine protease urokinase plasminogen activator (uPA) and the plasminogen activator inhibitor type-1 (PAI-1) in fresh or frozen tumor tissue of size not less than 0.125 cm3 which is impractical in unresected tumors of early breast cancer (EBC) [5, 6]. This underscores the need for a highly sensitive, non-invasive, and specific biomarker from an easily accessible source such as blood for the timely detection of metastatic spread and inception of therapy against the early metastatic clusters as well.

Tumor cells detach from the primary tumor bed and migrate to the circulatory system as singular units or clusters termed as circulating tumor cells (CTCs) [7]. These CTCs represent a minor fraction of early metastatic cells or a predominant set of late stage metastatic tumor cells that are latent with the potential of implantation at distinct organs even at an earlier time point of the disease [7, 8]. The concept of CTCs in blood was first described by Thomas Ashworth in 1896 [9] and nearly a century later Dr. Bernie Fisher (1965) proposed “the systemic or Fisher hypothesis of breast cancer” stating that “breast cancer is a systemic disease with malignant cells likely to be disseminated throughout the body before diagnosis” [10,11,12]. The current trend of cancer research addresses the “hypothesis of oligometastases” proposed by Hellman and Weichselbaum (1995) which state that “a limited number of metastases may represent a clinically significant disease state in which the full metastatic potential is not reached” [13]. The emerging molecular biology techniques have enabled the detection of oligometastatic CTCs in peripheral blood alongside the cellular by-products such as cell-free circulating nucleic acids (cfcNAs) - (ctDNA and ctRNA - miRNAs, microvesicles, exosomes) and circulating proteins collectively deemed as the “liquid biopsy” (LB) [7, 8, 14]. CTCs and the biomarkers involved have implications in detection of cancer, prediction and monitoring of therapeutic responses and stratification of patients to guide therapeutic cancer management [7, 8, 14,15,16,17,18,19,20].

Highly proliferative and aggressive breast tumor subtypes typically possess regions of enhanced apoptosis or necrosis subsequent to nutrient depletion, growth inhibition, and hypoxic conditions prevalent within the tissue core, which in turn releases nucleic acids (ctDNA and ctRNA) into the local tissues and circulation [17]. Despite these ctDNAs retaining their intrinsic mutation profile and the tumor-specific genetic and epigenetic aberrations of the breast tumor subtype, they may misleadingly represent the genomic status of dead cells and not that of the surviving fraction of highly metastatic tumor cells [18]. The diminishing concentrations of these components in bodily fluids is a major limitation to translational research efforts evaluating these biomarkers, which is technically challenging to overcome.

In the past two decades, there has been an increase in the research interest surrounding short (25 nucleotide (nt) long), single-stranded noncoding RNAs known as mi(cro)RNAs as abundantly expressed regulators of the transcription of protein coding genes [21]. MiRNAs are relatively stable and evade the enzymatic cleavage activity of the RNases which are abundant in the blood [22, 23]. The functional roles of miRNAs are versatile with a binary role in the maintenance of normal epithelial homeostasis as well as in the process of driving the oncogenic transformation. Moreover, they act as promising biomarkers which are highly informative in differentiating between normal and tumor subtypes, while remaining more stable than messenger RNA (mRNA) and ctDNA [24]. MiRNAs have great potential in the early diagnosis of multiple cancers, in accurate classification of poorly differentiated tumors, detection of tumor metastases, recurrence, prognosis and biological heterogeneity [24,25,26,27,28,29,30,31,32,33,34]. Interestingly, the secretion of miRNAs into the interstitial fluid (IF) and the tumor microenvironment (TME), also favours its utility as a blood-based biomarker for the early detection of metastatic cells [34, 35].

The objective of the current review is to address the molecular mechanisms that trigger an early undetected metastatic event and the genomic variations between early and late stage metastatic tumor cells. Secondly, we provide an updated view on the survival mechanisms adapted by these CTCs in circulation. Third, we elaborate on the additional biomarker components in blood that are disease-specific and explain how circulating and CTC-specific miRNAs may be considered as a sensitive and superior minimally-invasive liquid biopsy biomarker for accurate diagnosis of early metastatic CTCs. Following this we summarize on miRNA mediated targeted therapies against breast cancer metastases and the prognostic implications, the limitations encountered and conclude by suggesting promising future directions.

The nuances of early metastases in breast cancer

The notion that fully transformed late disseminating tumor cells (DTCs) alone are able to initiate metastases is dismissed by studies that state even early transformed breast cancer cells (EBCs) with the crucial genetic and epigenetic mutations that reverse cell dormancy, are also capable of progressing to metastases [36, 37]. These EBCs need not originate from large tumors and may undergo metastases 5–7 years prior to the diagnosis of PTs [38]. The phenomenon of asymptomatic, clinically undetected minimal residual disease (MRD) or dormant DTCs attribute its origin to an early migration of small clusters (CTCs) from the original cancer or emerge as recurrence following an extended period of latency [39]. Though renamed for practical purpose, another variant to CTCs (also known as disseminated tumor cells (DTCs)) serve as reservoirs of small, dormant seeds that are capable of re-entering the vasculature and set-off a cycle of secondary spread throughout the body [40, 41].

Emigration of PT cells at an earlystage require disruption of the underlying basement membrane which is a major detectable sign of invasion [38]. Electron microscopic imaging reveals that few of the hyperplastic tumor cells of atypical ductal hyperplasia (ADH) lesions are capable of breaching the basement membrane by inducing localized secretion of proteolytic enzymes which is activated as a part of the gene regulatory program driven by the transcription factor Twist [38]. Of note, not all patients with detectable CTCs/DTCs in circulation develop metastases; previous studies have observed that CTCs/DTCs may remain in a state of dormancy without any clinical evidence of recurrence for up to 10–22 years until unknown mechanisms trigger the transition to overt metastases [42, 43]. The research community is still oblivious of the molecular mechanisms governing the dormancy of DTCs, the re-awakening cycles of MBCs and the identity of CTC subsets that are the true malignant seeds that can spread the disease.

Genomic variations between EBCs and metastatic clones

Meta-analysis of multiple tumors reveal that gene expression signatures of metastases differs considerably from their PTs and a uniform expression pattern is displayed by metastatic cells homing at the same secondary organ [34]. The location of secondary seeding plays a significant role in framing the genomic landscape and the malignant phenotype of metastatic cancer cells as the intrinsic molecular signature continue to evolve throughout its life history [34]. Almost 57% of cytokeratin-positive (CK+) single DTCs from the bone marrow of M0-stage breast cancer patients displayed significantly fewer and randomly generated chromosomal aberrations than PTs or cells from M1-stage patients that harboured different chromosomal imbalances typical of late metastatic cells [43]. Accrual of approximately 15,600 mutations in 65% of tumor cells have led to the emergence of dominant metastatic clones from the EBC primary tumor clones, imparting an unlimited proliferation potential and the ability to form metastatic tumor mass at distinct sites [7, 44]. Chromosomal imbalances are associated with hyper-proliferation in morphologically defined EBC lesions and occurs more frequently during the transition from ADH to carcinoma in situ (CIS), than in invasive cancers [45,46,47]. Furthermore, gene expression profiles of early primary breast cancers have differed from brain metastases (BM) with significant downregulation of immune-related gene signatures [48]. A parallel study affirmed that breast CTCs associated with BM also share the copy number alterations (CNA) of PTs, suggesting that BM competent cells have undergone clonal selection [49]. The overall indication is that CTCs from advanced stage breast cancers resemble the mutational profile of PTs more than the CTCs released at an early stage of breast cancer.

The Norwegian Women and Cancer (NOWAC) Post-Genome Cohort study compared the blood gene expression profile of healthy controls for up to 8 years before being diagnosed with early stage breast cancer and ascertained the supportive link between pathways regulating the immune system and metastatic spread [50]. The blood-borne CTCs of metastatic patients differed in expression of 55 mRNAs and 9 miRNAs from the CTCs of PTs and blood samples which is indicative of a molecular selection pressure exerted by minimally expressed miRNAs that are responsible for the emergence of receptor negative metastatic tumor cell fractions from estrogen receptor positive (ER+) PT cohort [51]. Nearly 80% of metastases from early-stage, low-density lesions are derived from early DTCs with the characteristic features of low proliferation, enhanced stemness, and a higher rate of migration supported by epithelial mesenchymal transition (EMT) [52], in comparison to advanced late-stage tumors that are more dense with proliferative cells and lower migratory potentials [53]. This shift from migration to proliferation is synchronised by a miRNA-mediated reversible downregulated expression of hormone receptors (HR) [53].

Genetic variations, mainly single nucleotide polymorphisms (SNPs), have been identified in miRNA and in the miRNA binding sites on target genes that may alter an individual’s susceptibility to breast cancer [54]. A SNP in the miRNA binding site is predicted to abolish miRNA–mediated silencing of the target mRNA leading to an upregulated translation of the corresponding encoded protein [54]. Amongst the five significant targets affected by the miRNA-associated SNPs, the master regulator of miRNA biogenesis DROSHA is the core nuclease that processes primary (pri-miRNAs) to precursor (pre-miRNAs) in the nucleus and a failure in suppressing Drosha leashes a massive synthesis of mature miRNAs that dynamically deregulate the normal tumor suppressor gene (tsg) signaling pathways and thereby increase the risk of breast cancer [54, 55]. Though the survival mechanisms adapted by tumor cells requires an intrinsic communication with the tumor microenvironment, miRNAs are crucial regulatory molecules with wide control over multiple genes and eventually proteins thus ensuring the existence of tumor cells in a dynamic host environment.

Adaptations of circulating tumor cell clusters (CTCs) in blood

A metastatic tumor is a clonal representation of the PT if seeded by a single cancer cell and results in polyclonal metastases if seeded by a cluster of CTCs [56]. The conventional model of metastasis proposed that each metastasis is from a single tumor cell. However, salient discovery annulled the notion and showed that metastasis develops from a collection of multiple genetically distinct clones or polyclones [57]. The biological phenomena that triggered the discrete shedding of CTCs as single cells or as clusters from a primary cancerous lesion merely depends on the hypoxic status of tumor cells [58]. CTC clusters are highly enriched for tumor cells undergoing hypoxia, whereas single CTCs are largely normoxic and this intra-tumor hypoxia heightened the rate of CTC cluster shedding and formation of metastases [58]. CTC clusters also develop from oligoclonal tumor cell groupings by excessive production of cell junction component plakoglobin, which is known to arbitrate intercellular adhesion and increase the metastatic potential of tumor cells up to 50-fold [59]. Plakoglobin (or γ-catenin) interacts with several intracellular molecules including signaling proteins and transcription factors, which accounts for its involvement in cellular and oncological signaling [60]. A comparative gene expression analysis of CTCs, lung metastases and localized DTCs revealed that plakoglobin unified the cytokeratin 14 expressing (CK14+) oligoclonal CTC clusters, thereby imparting a low immunogenic profile that contributes to a successful dissemination [59]. In addition, the CK14+ tumor cells are found to be enriched in desmosome and hemidesmosome adhesion complex genes, co-expressed effector molecules of metastasis such as Epiregulin (Ereg), Tenascin C (Tnc), Jagged1 (Jag1) that are collectively involved in niche modelling and are deficient in major histocompatibility (MHC) class II genes, indicating a low immunogenic profile [57]. These CTCs also represent the aggressive CK14+ basal stem cell phenotype capable of colonizing distant organs efficiently [57]. CTC clusters are also found to be enriched in Ki67-positive proliferative cells that are epigenetically modified with activation of the stemness- and proliferation-related transcription factors Oct4, Sox2, Nanog and Sin3a, which also highlights the metastasis-seeding capabilities of CTC clusters than matched single CTCs [61]. Thus, CTC clusters are likely to be causative agents in inducing metastatic seeding of malignancies of the breast.

The onset of distant metastases originates with the translocation of CTCs into the blood or lymphatic system. This may occur through a passive mode with intermittent entry of cells into leaky blood vessels or by an active mode that strictly follows the central dogma of malignant transformation, starting with EMT, intravasation into adjacent blood vessels, migration through tissue layers or circulation, embolization, survival, extravasation and eventual re-seeding at a new site [57, 62]. Upon entering the circulation, the cluster signaling mechanism that drives the establishment of tumor outgrowth occurs through secretion of the growth factor “epigen”, which becomes concentrated in the ‘nanolumina’ intercellular compartments. An interruption in the production of epigen aborts the CTC cluster proliferation and promotes the transition of clusters to a state of collective migration [63]. Blood platelets also surround and cloak the CTCs forming a “microemboli” and in the process it imparts some protection against shear stress in the circulation [64]. This cloaking mechanism in turn serves to protect the CTCs from recognition and attack of immune cells in circulation, adding to the immune evasion hallmark of tumor cells in establishing a new niche (Fig. 1).

Fig. 1
figure 1

Emergence of Circulating Tumor Cells in Early Stage Breast Cancer. Tumor cells enter the blood stream as single CTC or cluster of CTCs endowed with attributes of immune evasion, stemness and proliferation potentials. These cells also secrete cell-free nucleic acids that may be utilized as blood-based biomarkers for detecting the presence of breast cancer

Studying CTC-clusters rather than individual CTCs is seemingly more informative in providing additional prognostic value with progression-free survival (PFS), especially in advanced-stage patients with inflammatory breast cancer (IBC), one among the most aggressive subtype of breast cancer which is associated with poor survival and outcomes [65]. Interestingly, there is a surge in the frequency of CTC-clusters during the course of neo-adjuvant chemotherapy (NAC), which profoundly declines post-surgery [66]. Despite surgical intervention, there remains a higher proportion of clusters in patients who have non-responding or resistant disease [66]. Longitudinal evaluation of changes in the cell count of single CTCs and CTC-clusters in patients with MBC tend to improve the prognostic value over time and indicate a successful monitoring during the first-line of systemic therapy [65, 67]. The incorporation of CTC-specific miRNA profiling as a combined prediction model also amplifies the prognostic accuracy of MBC patients and have utility in predicting pathological complete response (pCR) and in detecting responders to NAC in clinical practice.

The limiting factor in accurate detection of CTCs from whole blood is the inability of epithelial marker-dependent cell isolation methods to recognize transformed cells expressing mesenchymal markers. The remedy is to focus on cell morphology and utilize an epithelial marker-independent, unbiased enrichment or filtration technique that improves detection of CTCs and several such tests prove that CTC-clusters are more frequent in EBC than in MBC reinforcing the concept that metastasis is definitely an early event in breast tumor progression [67, 68]. The best alternative would be to resort to blood-based biomarkers that can specifically detect the presence of rare quantities of CTCs, CTC clusters and DTCs in any homeostatic conditions and at any time point of sampling.

Multiple biomarker components of liquid biopsy in breast cancer

For decades, translational and clinical research efforts have been focused on the identification of molecular biomarkers capable of specifically distinguishing cancerous conditions from the healthy counterparts. Though tumor tissue biopsies provide a single preview of inherent tumor heterogeneity, it still falls short in accurate prediction of response to treatment. Liquid biopsies comprising of whole blood and other alternative body fluids such as urine, saliva, nipple aspirate fluid (NAF) and pleural effusions have previously overcome the limitations of painful invasive tissue resections [69]. Moreover, these offer a multi-modal reflection of the levels of tumor spread in the body, the associated cellular mutations, prediction of the emergence of drug resistance and an overall prognosis [69]. The predominant components of liquid biopsy are the factors released into blood stream by tumors such as CTCs, ctDNA, cfc-RNA (miRNAs and mRNAs), tumor-educated platelets (TEPs) and exosomes which show significant promise in pan-cancer diagnostics and in early-stage cancer detection [7, 8, 14, 70, 71] (Fig. 2).

Fig. 2
figure 2

Components of Blood Biopsy for the Early Detection of Breast Cancer. Molecular components of liquid biopsy with immense implications in precision medicine

CTCs and ctDNA in breast cancer

Detecting the presence of CTCs and ctDNA have become the standard therapy monitoring tools favouring sequential prognostic evaluation. Also the CTCs in blood delineate the temporal heterogeneity marked by gain or loss of HR expression which arises during the progression of localized tumors to metastases [72]. The presence of 1–10 CTCs per 7.5 ml of a blood sample is associated with decreased disease free survival (DFS), overall survival (OS) and in post chemotherapy patients, it is prognostic for poor relapse free survival (RFS) [73,74,75,76]. The maximum observed count of circulating cancer cells (CCC) per patient blood sample range from 2 for stage 1, 37 for stage 2, 19 for stage 3, and 1283 for stage 4 breast cancer patients clearly indicating that patients are more likely to have a metastatic disease if tested positive for CCC anytime during the sampling period [74].

HR status, tumor grade and the treatment modalities administered have previously illustrated no correlation to the presence of CTCs in stage 4 MBC patients [74]. Nearly 5% of HR–positive BC patients with a positive CTC assay displayed a 13-fold higher risk of late clinical recurrence (range: 0.1–2.8 years) when compared to negative CTC results. Despite similar CTC positivity, only 1 of 193 HR–negative patients (0.5%) displayed a late clinical recurrence at the time of the analysis [75]. CTCs and ctDNA are validated as independent markers of prognoses in MBC patients [76]. The question regarding how informative the presence of CTCs is remains since the spread of tumor cells is a phenomena known to be highly prevalent in advanced stages of the disease? Circulating cell-free DNA (ccfDNA) refers to any free DNA circulating in the bloodstream, regardless of origin and is higher in breast cancer patients compared to healthy subjects [77]. The short fragments (< 166 bp) of ccfDNA represent the tumor-originated DNA (ctDNA) [78] and the sequencing of ctDNA provide an updated mutational profile of the PTs, thereby enhancing individualized treatment options and longitudinal screening that aid in the decision-making to initiate adjuvant therapy to prevent recurrence [74].

A comparative screening of BC alterations in genomic DNA of tumor tissues and circulating free total nucleic acids (cfTNAs) from the plasma LB samples validated against the DNA from peripheral blood mononuclear cells (PBMCs), identified 7 disease-specific mutational variants in addition to HER2 amplification in tissues and plasma [79]. Post treatment with targeted therapy using Trastuzumab Emtansine (T-DM1), most HER2+ clones (with HER2 amplifications and PIK3CA mutations) disappeared allowing new passenger mutations (actionable ESR1/PIK3CA mutations and MYC/FGFR1 amplifications) to appear in blood (during sequential LB) suggesting a systematic, molecular subtype switch to a new resistant (HER2-) clonal variant [79]. Moreover, there remains a significant risk of disease recurrence associated with the detection of CTCs in circulation, particularly in the setting of phospho-inositide3-kinase (PIK3CA)-positive disease [80,81,82]. Bulk sequencing and array of tissue-only analysis would miss this extensive remodelling at the molecular level that affects the dynamic oncogenic dependencies, but is now traceable through liquid biopsy. Thus, LB enables accurate identification of patients that respond to T-DM1 within weeks of therapy and potentially select patients who could be advised to resort to innovative pulse dosing/de-escalation schedules, with minimal treatment-associated toxicity [79].

An interesting finding is that the inception of spontaneous variations in specific cancer-associated genomic regions (CAGRs) are shown to harbour more than half of the reported human miRNAs [23, 83]. Genomic data analysis also proves that an amplification of DNA copy number aligns with an overexpression of miRNAs and genomic deletions correspond to the downregulation of miRNAs respectively [84]. This gives credit to the presence of an early set of secreted miRNAs as LB biomarkers as a sequel to gene mutations.

Circulating RNAs, exosomal RNAs and miRNAs in breast cancer

The PT cells and CTCs secrete cf-RNA/or ctRNA which includes mRNA and miRNAs that are encapsulated in exosomes which transform the tumor stroma and regulate multiple genes, thus facilitating the establishment of metastases [31]. Analysis of cf-mRNA in early-stage cancer patients provide valuable information regarding somatic mutations at the DNA level, gene expression profile of the tumor and also the epigenetic changes and other alterations in cellular pathways [73, 85]. MiRNAs are protected from ubiquitous ribonuclease (RNase) enzyme-mediated degradation by embedding in exosomes that are small membrane-bound extracellular vesicles (EVs) (30–200 nm), or in larger microvesicles (MVs) (250–400 nm) shed from the plasma membrane and also co-exist as free-form ctRNAs associated with a ribonucleoprotein complex or an argonaute-2 protein [22, 86,87,88,89]. Breast tumor secretory cells release microRNAs in microvesicles to regulate the gene expression of multiple neighbouring cells whereas miRNAs released by other cell types are as non-exosomal free oligonucleotides [90].

Although other non-coding RNAs (such as long-non-coding RNAs (lncRNAs)) act in unison with miRNAs as co-regulators of multiple protein-coding genes, lncRNAs mainly function as the molecular sponges of miRNAs by regulating the miRNA:target mRNA axis [91, 92]. Long non-coding RNA LINC00511 and onco-miR-301a-3p are found to be significantly overexpressed in early stage BC patients’ liquid biopsy samples and in patients with larger tumors (> 2 cm) as compared to later stages [92]. LINC00511 is also directly correlated with aggressiveness marked by Lymph node metastasis (LNM) and advanced tumor grade, whereas its downstream miRNA, miR-185-3p displayed a fourfold downregulated expression highlighting an independent mechanism of action suggesting that lncRNAs:miRNAs may also be utilized as tumor biomarkers in blood [93].

Extracellular RNAs (exRNAs) in circulation that are encapsulated within vesicles (EV’s) share the dimensions and density with the lipid components in circulation [86] which obscures the accurate identification and necessitates ultracentrifugation and chromatography techniques for purification of disease-specific EVs [94]. Combination of circulating EVs and CTCs are predictive of OS in MBC and other solid tumors [95]. The most important observation is that minute transitions in gene expression is reflected instantly at the transcriptional level. This wealth of information packaged into these exosomes maybe functional in eliciting a phenotypic response in recipient cells as in miRNAs and mRNAs [96]. Interestingly, miRNAs are found to be the most abundant exosomal RNA species, with nearly 593 detectable miRNAs that may have an important role in regulating biological functions, such as RNA splicing, protein phosphorylation, and angiogenesis [97]. Only a few highly abundant subset of cellular miRNAs are retained within the cell or are selectively released into the circulation and can be traced to the cell of origin [98]. These selectively released miRNAs (for example, miR-451 in breast cancer) are also found to be enriched in mammary fluids, blood and milk indicating that they are ideal diagnostic biomarkers for breast cancer and yet should be studied independent of the abundant cellular miRNAs [98]. A panel of circulating miRNAs (miR-141, miR-200a, miR-200b, miR-200c, miR-203, miR-210, miR-375, and miR-801) also predicted the CTC status of patients with MBC and previously differentiated the MBC cases from healthy controls [99]. Circulating miR-200b was identified as the best marker in distinguishing CTC-positive from CTC-negative patients [99]. The functional attributes of these selectively released miRs mediate the paracrine signaling between the tumor and stroma in promoting field cancerization [100].

MicroRNAs as diagnostic and prognostic biomarkers in liquid biopsy

Secreted miRNAs in body fluids such as serum, plasma, and whole blood are promising candidates to function as cancer biomarkers for BC screening [101, 102]. Normal and tumor cells often contain intracellular pri-miRNAs that are more than 1000 nt in length, cleaved to pre-miRNA which is transported to the cytoplasm and pre-processed to functional (22 nt long) mature miRNAs [21, 96]. Only a few mature miRs have shown promise as biomarkers for the detection of malignancy in the plasma of BC patients and a recent study strongly highlighted the presence of plasma pri-miR526b and pri-miR655 as biomarkers distinguishing the plasma of stage I from benign conditions [102, 103]. Interestingly, molecular changes such as maturation and subsequent differentiation of PBMCs transpire even from the early-stages of neoplastic lesion formation, indicating that the miRNA repertoire in circulation modifies the TME thus favouring an early onset of metastasis [103,104,105]. A four miRNA signature panel (miR-145, miR-139-5p, miR-130a, and miR-425-5p) previously displayed the highest diagnostic accuracy for detecting early-stage BC patients [106]. Also the involvement of miRs in directing the progression of CTCs through every stage of metastatic events opens up new possibilities for tracking the malignant transformation at an earlier stage based on the expression of metastases promoting pre-miRs [31].

MiRNAs as prognostic biomarkers in post-operative BC patients

MiRNAs are currently established as minimally invasive whole blood diagnostic tools for early stage detection of PTs and metastases with immense practicality even in post-operative BC patients [107]. Analysis of gene copy number aberrations (CNAs) in a single circulating tumor microemboli (CTMs) and the relative PT tissue sample in early-stage breast cancer patients have supported the notion that CTMs are disseminated from genetically diverse and advanced regions of PTs [107]. Moreover, this suggests these cells are primed in advance with genes responsible for metastatic development [107]. A five-miRNA signature (miR-149, miR-10a, miR-20b, miR-30a-3p and miR-342-5p), previously used to substratify breast cancer patients who succumbed to early recurrence into a ‘high-risk’ group (with shorter RFS) and the subsequent miRNA-mRNA target prediction revealed an overall upregulation of proliferation and angiogenesis related gene expression [108]. Similarly, comparative screening of the expression profiles of miR-19a, miR-21, miR-22 and miR-127 performed across post-operative, non-metastatic EBC patients and healthy donors reflected the significant diagnostic values of these miRNAs in identification of EBC prior to or after treatment with adjuvant chemotherapy and at 2 years of follow up [101]. Although miR-21 is a well-described oncogenic miRNA found highly expressed in the circulation of breast cancer patients, it has been reported to be significantly downregulated in T0 patient blood samples, suggestive of an early deregulation of inflammatory and immune processes [101, 109]. Similar inferences have been reported regarding the circulation of miR-331 and miR-195 whose expression in plasma effectively differentiated the localized Luminal A tumor from metastases [110].

MiRNAs as mediators of molecular subtype transitions

Even clusters of miRNAs coded by the same chromosome (Ch19 miRs) (− miR-520 g, −520f, −520c, −520d, etc.) have been reported to be differentially expressed in breast tumor cells, serving as molecular classifiers of tumor tissue that is independently validated by artificial intelligence (AI) based network modelling and experimental research [27, 111, 112]. An overexpression of miR-520c and miR-373 appear to target the metastasis-related CD44 gene, thus augmenting the invasion and metastasis of breast tumor cells [113]. The C19-miRs are also identified to target REST, CEBPB and TFF3 genes which tend to increase the expression of a basal epithelial stem cell marker CK14, which is also a marker of polyclonal CTC clusters [59]. The expression of CK14 in tandem with the transient loss of ERBB2 gene expression directs the molecular subtype switch of basal-HER2+ to the highly aggressive triple negative molecular subtype [114]. Notably, distinct yet interconverting phenotypes concur within CTCs in the same tumor subtype offering acquired drug resistance and evolution of MBCs [115]. CTCs in advanced ER+/HER2- primary tumors reflect a dynamic transition between HER2+ and HER2− subpopulations wherein HER2+ CTCs display a higher proliferation potential and HER2- CTCs exhibit a higher resistance to chemotherapy predicting that the TME (oxidative stress and cytotoxic chemo) define this spontaneous transition [115, 116].

Cell-free miRNAs and the targeted signaling pathways

A comparative study conducting miRNA profiling of liquid biopsies in healthy age-matched individuals previously revealed the differential role of cell-free miRNAs as well as the unique miRNAs packaged into exosomes targeting the neural and axonal development, TGF-beta signalling, and pathways in cancer [104]. Moreover, the intracellular miRNAs isolated from blood cells (RBCs, WBCs, platelets) are known to be profoundly enriched in miRNAs targeting self-renewal, focal adhesion, glioma, phosphatidylinositol and melanogenesis signalling pathways [104]. Plasma miR-1246 was the first microRNA isolated from EVs to be used to aid BC diagnosis [117]. Likewise, a three miRNA expression panel (miR-142-5p, miR-320a and miR-4433b-5p) measured in serum also accurately detected BC molecular subtypes [118], while another set of 4 differentially expressed ct-miRNAs in plasma (miR-20b-5p, miR-92a-2-5p, miR-106a-3p and miR-106a-5p) and in serum (miR-19b-3p, miR-20b-5p, miR-92a-3p and miR-106a-5p) successfully discriminated BC patients from control [119, 120]. Another study on LB reported an upregulated expression of miR-99a, miR-130a, miR-484 and miR-1260a in the plasma of BC patients and target predictions identified these miRNAs to be involved in regulating the Hippo and Transforming Growth Factor-beta (TGF-beta) signaling pathways [121]. A combination of only three miRNAs (miR-148b, miR-409-3p and miR-801) are found to be significantly upregulated in the plasma of BC patients, differentiating between BC cases and healthy controls [122].

Extracellular miRNAs should be considered as independent diagnostic markers of disease in comparison to cellular miRNAs as observed in the selective release of miR-1246 and miR-451 by BC cells and the concentration of these in body fluids during the transition from normal to abnormal cells [98]. The higher expression of hsa-miR-652-5p in pre-treatment plasma of BC patients also outlines it as a possible blood-based biomarker for early detection of breast cancer [123]. Another prominent systemic biomarker to discriminate EBC cases from controls is miR-195 [124]. A second study reported a downregulated expression of miR-195 in serum of early-stage BC patients with a much higher sensitivity of detection than conventional tumor markers CA153 and CEA [125]. Inconsistencies in expression levels, elusive targets and the mode of action are some of the hurdles associated with several of these systemic biomarkers.

Undetected metastases to secondary organs is a major cause for mortality and unfortunately 30–55% of those diagnosed with triple negative breast cancer (TNBC) and HER2+ breast carcinoma succumb to brain metastases (BM) [31]. Survival in such instances is dismal (median survival: 4–14 months) [31, 126, 127]. Disseminated tumor cells from PTs alone are not capable of executing this multi-step process of BM, particularly due to the presence of the blood–brain barrier (BBB). In circulation, the CTCs secrete miRNAs via exosomes which suppresses the immune system, transform the brain stroma, and breach the BBB for BM [31]. BM prone BC cells release EVs carrying miRNA-181c that targets the actin dynamics and eventually lead to the destruction of the intact BBB [128]. A proportion of BC patients may develop distant metastases to bone leading to formation of osteolytic lesions [129]. The bone-tropic ER+ breast cancer cells tend to secrete exosomal miR-19a and Integrin-Binding Sialoprotein (IBSP), thus enhancing the expression levels of these markers in circulation of ER+ BC patients [130]. IBSP attracts osteoclast cells to the bone and exosomal miR-19a induce osteoclastogenesis by remodelling the TME in a paracrine manner favouring BC cell colonization in the bone without directly affecting the cancer cells [130]. All these findings suggest that CTCs alone are incapable of establishing metastases to different sites, but require the assistance of circulating miRNAs to regulate the multiple cellular and molecular events promoting the advancement of BC.

MiRNAs as predictors of therapeutic resistance

In the translational research arm of the prospective, multicentre neoadjuvant NeoALTTO trial, increased expression of plasma ct-miR-148a-3p, ct-miR-374a-5p and ct-miR-140-5p correlated with a 54% increase in pCR in patients being treated with neoadjuvant trastuzumab-based therapy for HER2+ disease within two weeks of initial treatment [131]. Non-responders to NAC in TNBC are identified through varying expression levels of blood-derived exosomal miRNA biomarkers, marked by a reduced expression of miR-185, miR-4283, miR-5008, and miR-3613, as well as upregulated levels of miR-1302, miR-4715 and miR-3144 [132]. The target genes of these miRNAs belong to pathways typically related to immune response activation and suppression, highlighting a defective immune system may be responsible for resistance to NAC in TNBC patients [132]. Interestingly, the measurement of a five miRNA expression panel (miR-1246, miR-1307-3p, miR-4634, miR-6861-5p and miR-6875-5p) in serum, accurately detected EBC with 97% sensitivity from the non-BC patients [133]. The SUCCESS clinical trial previously investigated the presence of plasma miRNAs in BC patients pre- and post-chemotherapy against healthy controls [134]. This trial observed significantly increased plasma levels of miR-16, miR-27a and miR-132 in BC patients prior to chemotherapy versus controls, while levels of these biomarkers later reduced to match the levels observed in healthy women post chemotherapy [134]. Therefore, it is reasonable to suggest that these miRNAs have oncogenic properties and may be useful in gauging treatment response to NAC. Additionally, expression levels of miR-16, miR-107, miR-130a and miR-146a have been previously reported to substratify patients with lymph node positive and lymph node negative disease [134]. The levels of miR-130a and miR-146a also differed – based on HER2 status suggesting a potential role of these miRNAs in the HER2 signaling pathway in these biologically distinct cancers [134].

Analysing the plasma levels of miR-923 and CA-15-3 protein in combination with routine clinicopathological data has clearly predicted disease recurrence and prognosis in preoperative patients, irrespective of the treatment regimen [135]. Screening for an upregulated expression level of serum exosomal miRNAs (miRNA-21, miRNA-222 and miRNA-155) identified patients who failed to respond to NAC and subsequently developed distant disease [136]. These studies also emphasize the collective use of exosomal miRNAs, cell-free proteins, and CTCs as both diagnostic, prognostic, and predictive biomarkers in BC (Table 1). The technical obstacles associated with the comprehensive tracking of relatively minor changes in expression levels of molecular biomarkers that originate with the release of a single or multiple CTCs and monoclonal or polyclonal CTC clusters in the blood stream remains to be determined.

Table 1 Cumulative list of circulating biomarkers in liquid biopsies of early and metastatic stage breast cancer patients

MiRNA mediated targeted therapy against CTCs

Over the years, the enumeration of CTCs-miRNAs seems promising with an emerging trend of multiple clinical studies reporting miRNAs secreted by CTCs in liquid biopsies. The challenge is that the therapeutic value depends on the utilization of BC-specific miRNAs for accurate prediction and functional reversal of the breast cancer proliferation and metastases [137]. In a previous analysis where post-screening of 436 breast tumor tissue miRNAs was performed, miR-183 was the sole “CTC-specific” miRNA with high expression levels in patient blood samples having CTCs ≥5 /7.5 mL [51, 112]. CTCs display heterogeneous expression profiles of miR-10b, which is a regulator of viability in MBCs with effect in inducing miRNA-mediated targeted elimination of metastatic tumor cells [138, 139]. MiRNAs are crucial not only for the detection of CTC clusters, but are also key in efficiently targeting CTCs. Despite EMT being known as a pre-requisite for migration and metastases, evidence illustrates that BC metastases to lungs is more commonly enriched with non-EMT CTCs which successfully retain the typical epithelial morphology [140]. The formation of recurrent lung metastasis post-chemotherapy is mainly attributed to an acquired resistance and lower rate of proliferation in EMT cells to survive cyclophosphamide treatment. An overexpression of miR-200 abolished this chemoresistance in EMT prone cells indicating the potential utility of anti-miRNA therapy in combination with conventional chemotherapy regimen for treating aggressive BCs [140].

The presence of the primary unprocessed miRNA transcript pri-miR526b and pri-miR655 in the plasma of cancer patients effectively distinguished ER+ and HER2-fractions from ER- and HER2+ respectively, making them useful as adjuncts to current conventional endocrine therapy [101]. In TNBC and HER2+ disease, metastases to the brain is the most common early onset scenario. The advantages of focusing on secretory miRNAs is that the variations in expression levels is in accordance with BM progression, thus enabling sequential monitoring of the disease burden, response to therapy, and for accurate differentiation of brain lesions (BL) and metastatic deposits [31]. Mir-10, miR-21, miR-223, miR-711, miR-125, and miR-935 signatures in the cerebro-spinal fluid (CSF) have clearly discriminated the malignancies of central nervous system (CNS) from the metastatic deposits originating from breast and lung carcinoma [31, 141]. A miRNA cluster family (miR-93/20b/106a/106b) formed the core of the regulatory network that co-ordinated the suppression of multiple lncRNAs (MESTIT1, LOC100128164, and DNMBP-AS1) which are significantly associated with poor overall survival in breast cancer patients [142]. Combinatorial targeting of these key non-coding RNAs may provide new therapeutic strategies to prevent the progression of BC from an early-stage to advanced stage disease.

Limitations and future implications

Metastasis is a rate–limiting progressive process with miRNAs acting as upstream master regulators of oncogenes and tumor suppressor genes. Despite the vast knowledge on the mutational profile of breast tumors and the subsequent events of invasion and metastases, there remains a paucity of data linking genetic mutations and miRNA expression profiles in primary and metastatic tumor cells. Yet to be addressed are scientific questions: (i) Does any of the major driver mutations occur in the genomic regions coding for miRNAs that are crucial in regulating metastases? (ii) How changes in miRNA expression levels impact the phenotype and cell fate of CTCs originating from EBCs and advanced BCs? (iii) Are systemically expressed miRNAs quantifiable representatives of tumor or are they host-related factors?

The lack of consensus between the different ct-miRNA signatures experimentally validated by various groups from the plasma samples of BC patients at various stages of the disease also raises concerns: (i) Why are there no uniform miRNA expression signatures reported in BC? (ii) Are the research findings reproducible across BC patients in different regions and among differing ethnic communities? (iii) Are there other external factors such as diet, immunological, and stress-related phenomena that tend to overpower the disease-specificity of these biomarkers in circulation? and finally, (iv) Do we need to follow a standard experimental protocol for retrieving a universally acceptable miRNA signature? Progress in screening techniques that warrants specificity and consistency is mandatory for the identification of novel cell-free miRs in circulation that is disease specific, reflects the tissue-of-origin and is measureable at significant levels in any sampling conditions.

Despite the secretion of miRNAs from a number of sources including PTs, MBCs, or CTCs in circulation, the expression levels might be reduced by a plethora of host and environmental factors. Thus the detection of miRNA signatures from within the CTCs warrant accuracy in enumeration and quantification of CTCs. A novel technology SILVER-seq (Small Input Liquid Volume Extracellular RNA Sequencing) can efficiently sequence both cell-specific and circulating fragmented exRNAs from a small volume (5 μL to 7 μL) of input serum liquid biopsy sample and even quantify donor-to-donor variations [143]. This offers the advantages of higher sensitivity, a less biased view of the small RNA transcriptome, as well as an increase in the number of putative miRNAs with prospective implications in clinical management of breast cancer. Designing novel techniques to enhance the accuracy in detection of even nano-levels of miRNAs is highly recommended.

Availability of data and materials

Not applicable.

Abbreviations

LB:

Liquid biopsy

EBC:

Early breast cancer

MBC:

Metastatic breast cancer

RNA:

Ribonucleic acid

miR:

MicroRNA

mRNA:

Messenger RNA

DNA:

Deoxy-ribonucleic acid

CTC:

Circulating tumor cell

cfcNA:

Cell-free circulating nucleic acid

DFS:

Disease free survival

CEA:

Carcinoembryonic antigen

CA:

Cancer antigen

ELISA:

Enzyme-linked Immunosorbent Assay

uPA:

Urokinase plasminogen activator

PAI-1:

Plasminogen activator inhibitor type-1

IF:

Interstitial fluid

TME:

Tumor microenvironment

MRD:

Minimal residual disease

DTCs:

Disseminated tumor cells

NOWAC:

The Norwegian Women and Cancer (NOWAC) Post-Genome study

SNPs:

Single nucleotide polymorphisms

EMT:

Epithelial mesenchymal transition

PIPs:

Progesterone-induced paracrine signals

CK14:

Cytoskeletal keratin 14

EL:

Early lesion

Ereg:

Epiregulin

Tnc:

Tenascin C

Jag1:

Jagged1

MHC:

Major histocompatibility

PFS:

Progression-free survival

IBC:

Inflammatory breast cancer

NAC:

Neo-adjuvant chemotherapy

pCR:

Pathological complete response

pri-miRNA:

Primary microRNA

pre-miRNA:

Precursor miRNA

t-RNA:

Transfer RNA

rRNA:

Ribosomal RNA

PBMC:

Peripheral blood mononucleated cell

NKcells:

Natural killer cells

CNA:

Copy number aberrations

CTM:

Circulating tumor emboli

AI:

Artificial intelligence

BL:

Brain lesions

BM:

Brain metastases

CSF:

Cerebro-spinal fluid

CNS:

Central nervous system

NGS:

Next-generation sequencing

References

  1. Sung H, Ferlay J, Siegel RL, Laversanne M, Soerjomataram I, Jemal A, et al. Global cancer statistics 2020: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA Cancer J Clin. 2021;71:209–49. https://doi.org/10.3322/caac.21660.

    Article  PubMed  Google Scholar 

  2. Redig AJ, McAllister SS. Breast cancer as a systemic disease: a view of metastasis. J Intern Med. 2013;274(2):113–26. https://doi.org/10.1111/joim.12084.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  3. Di Gioia D, Stieber P, Schmidt GP, Nagel D, Heinemann V, Baur-Melnyk A. Early detection of metastatic disease in asymptomatic breast cancer patients with whole-body imaging and defined tumour marker increase. Br J Cancer. 2015;112(5):809–18. https://doi.org/10.1038/bjc.2015.8.

    Article  PubMed  PubMed Central  Google Scholar 

  4. Kennecke H, Yerushalmi R, Woods R, Cheang MC, Voduc D, et al. Metastatic behavior of breast cancer subtypes. J Clin Oncol. 2010;28(20):3271–7. https://doi.org/10.1200/JCO.2009.25.9820.

    Article  PubMed  Google Scholar 

  5. Cardoso F, Kyriakides S, Ohno S, Penault-Llorca F, Poortmans P, et al. Early breast cancer: ESMO clinical practice guidelines for diagnosis, treatment and follow-up. Ann Oncol. 2019;30:1194–220. https://doi.org/10.1093/annonc/mdz173.

    Article  CAS  PubMed  Google Scholar 

  6. Look MP, van Putten WL, Duffy MJ, Harbeck N, Christensen IJ, et al. Pooled analysis of prognostic impact of urokinase-type plasminogen activator and its inhibitor PAI-1 in 8377 breast cancer patients. J Natl Cancer Inst. 2002;94(2):116–28. https://doi.org/10.1093/jnci/94.2.116.

    Article  CAS  PubMed  Google Scholar 

  7. Baccelli I, Schneeweiss A, Riethdorf S, Stenzinger A, Schillert A, et al. Identification of a population of blood circulating tumor cells from breast cancer patients that initiates metastasis in a xenograft assay. Nat Biotechnol. 2013;31:539–44. https://doi.org/10.1038/nbt.2576.

    Article  CAS  PubMed  Google Scholar 

  8. Zhang H, Lin X, Huang Y, Wang M, Cen C, et al. Detection methods and clinical applications of circulating tumor cells in breast cancer. Front Oncol. 2021;11:1816. https://doi.org/10.3389/fonc.2021.652253.

    Article  CAS  Google Scholar 

  9. Ashworth TR. A case of cancer in which cells similar to those in the tumours were seen in the blood after death. Aust Med J. 1869;14:146.

    Google Scholar 

  10. Fisher B. Biological research in the evolution of cancer surgery: a personal perspective. Cancer Res. 2008;68(24):10007. https://doi.org/10.1158/0008-5472.

    Article  PubMed  Google Scholar 

  11. Fisher B, Ravdin RG, Ausman RK, Slack NH, Moore GE, Noer RJ. Surgical adjuvant chemotherapy in cancer of the breast: results of a decade of cooperative investigation. Ann Surg. 1968;168(3):337–56. https://doi.org/10.1097/00000658-196809000-00004.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  12. Rabinovitch R, Kavanagh B. Double Helix of breast cancer therapy: intertwining the Halsted and Fisher hypotheses. J Clin Oncol. 2009;27(15):2422–3. https://doi.org/10.1200/JCO.2009.21.8453.

    Article  PubMed  Google Scholar 

  13. Hellman S, Weichselbaum RR. Oligometastases. J Clin Oncol. 1995;13(1):8–10. https://doi.org/10.1200/JCO.1995.13.1.8.

    Article  CAS  PubMed  Google Scholar 

  14. Domínguez-Vigil IG, Moreno-Martínez AK, Wang JY, Roehrl MHA, Barrera-Saldaña HA. The dawn of the liquid biopsy in the fight against cancer. Oncotarget. 2017;9(2):2912–22.

    Article  PubMed  PubMed Central  Google Scholar 

  15. Alix-Panabières C, Pantel K. Clinical applications of circulating tumor cells and circulating tumor DNA as liquid biopsy. Cancer Discov. 2016;6(5):479–91. https://doi.org/10.1158/2159-8290.Cd-15-1483.

    Article  PubMed  Google Scholar 

  16. Yang C, Xia B-R, Jin W-L, Lou G: Circulating tumor cells in precision oncology: clinical applications in liquid biopsy and 3D organoid model. Cancer Cell Int 2019, 19(1):341. doi: https://doi.org/10.1186/s12935-019-1067-8.

  17. Yang M, Forbes ME, Bitting RL, O'Neill SS, Chou PC, Topaloglu U, et al. Incorporating blood-based liquid biopsy information into cancer staging: time for a TNMB system? Ann Oncol. 2018;29(2):311–23.

    Article  CAS  PubMed  Google Scholar 

  18. Siravegna G, Bardelli A. Genotyping cell-free tumor DNA in the blood to detect residual disease and drug resistance. Genome Biol. 2014;15(8):449.

    Article  PubMed  PubMed Central  Google Scholar 

  19. Davey MG, Davies M, Lowery AJ, Miller N, Kerin MJ. The role of MicroRNA as clinical biomarkers for breast cancer surgery and treatment. Int J Mol Sci. 2021;22(15):8290.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  20. Davey MG, Lowery AJ, Miller N, Kerin MJ. MicroRNA expression profiles and breast cancer chemotherapy. Int J Mol Sci. 2021;22(19):10812.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  21. Lewis BP, Burge CB, Bartel DP. Conserved seed pairing, often flanked by adenosines, indicates that thousands of human genes are microRNA targets. Cell. 2005;120(1):15–20. https://doi.org/10.1016/j.cell.2004.12.035.

    Article  CAS  PubMed  Google Scholar 

  22. Huan J, Hornick NI, Shurtleff MJ, Skinner AM, Goloviznina NA, Roberts CT Jr, et al. RNA trafficking by acute myelogenous leukemia exosomes. Cancer Res. 2013;73(2):918–29.

    Article  CAS  PubMed  Google Scholar 

  23. Calin GA, Croce CM. MicroRNA signatures in human cancers. Nat Rev Cancer. 2006;6(11):857–66.

    Article  CAS  PubMed  Google Scholar 

  24. Richard V, Davey MG, Annuk H, Miller N, Dwyer RM, Lowery A, et al. MicroRNAs in molecular classification and pathogenesis of breast tumors. Cancers (Basel). 2021;13(21):5332. https://doi.org/10.3390/cancers13215332.

    Article  CAS  PubMed Central  Google Scholar 

  25. Bartels CL, Tsongalis GJ. MicroRNAs: novel biomarkers for human cancer. Clin Chem. 2009;55:623. https://doi.org/10.1373/clinchem.2008.112805.

    Article  CAS  PubMed  Google Scholar 

  26. Blenkiron C, Goldstein LD, Thorne NP, Spiteri I, Chin SF, et al. MicroRNA expression profiling of human breast cancer identifies new markers of tumor subtype. Genome Biol. 2007;8(10):R214. https://doi.org/10.1186/gb-2007-8-10-r214.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  27. Lowery AJ, Miller N, Devaney A, McNeill RE, Davoren PA, et al. MicroRNA signatures predict oestrogen receptor, progesterone receptor and HER2/neu receptor status in breast cancer. Breast Cancer Res. 2009;11(3):R27. https://doi.org/10.1186/bcr2257.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  28. McGuire A, Brown JA, Kerin MJ. Metastatic breast cancer: the potential of miRNA for diagnosis and treatment monitoring. Cancer Metastasis Rev. 2015;34(1):145–55. https://doi.org/10.1007/s10555-015-9551-7.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  29. Lu J, Getz G, Miska EA, et al. MicroRNA expression profiles classify human cancers. Nature. 2005;435(7043):834–8. https://doi.org/10.1038/nature03702.

    Article  CAS  PubMed  Google Scholar 

  30. Sathipati SY, Ho S-Y. Identifying a miRNA signature for predicting the stage of breast cancer. Sci Rep. 2018;8(1):16138. https://doi.org/10.1038/s41598-018-34604-3.

    Article  CAS  Google Scholar 

  31. Kanchan RK, Siddiqui JA, Mahapatra S, et al. MicroRNAs orchestrate pathophysiology of breast cancer brain metastasis: advances in therapy. Mol Cancer. 2020;19:29. https://doi.org/10.1186/s12943-020-1140-x.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  32. Michael IP, Saghafinia S, Hanahan D. A set of microRNAs coordinately controls tumorigenesis, invasion, and metastasis. PNAS. 2019;116(48):24184–95. https://doi.org/10.1073/pnas.1913307116.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  33. Hamam R, Hamam D, Alsaleh KA, et al. Circulating microRNAs in breast cancer: novel diagnostic and prognostic biomarkers. Cell Death Dis. 2017;8(9):e3045. https://doi.org/10.1038/cddis.2017.440.

    Article  PubMed  PubMed Central  Google Scholar 

  34. Nik-Zainal S, Alexandrov LB, Wedge DC, et al. Mutational processes molding the genomes of 21 breast cancers. Cell. 2012;149(5):979–93. https://doi.org/10.1016/j.cell.2012.04.024.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  35. Bertucci F, Ng CKY, Patsouris A, Droin N, Piscuoglio S, et al. Genomic characterization of metastatic breast cancers. Nature. 2019;569:560–4. https://doi.org/10.1038/s41586-019-1056-z.

    Article  CAS  PubMed  Google Scholar 

  36. Hüsemann Y, Geigl JB, Schubert F, Musiani P, Meyer M, et al. Systemic spread is an early step in breast cancer. Cancer Cell. 2008;13(1):58–68. https://doi.org/10.1016/j.ccr.2007.12.003.

    Article  CAS  PubMed  Google Scholar 

  37. Krol I, Schwab FD, Carbone R, Ritter M, Picocci S, et al. Detection of clustered circulating tumour cells in early breast cancer. Br J Cancer. 2021;125(1):23–7. https://doi.org/10.1038/s41416-021-01327-8.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  38. Engel J, Eckel R, Kerr J, Schmidt M, Fürstenberger G, et al. The process of metastasisation for breast cancer. Eur J Cancer. 2003;39(12):1794–806. https://doi.org/10.1016/S0959-8049(03)00422-2.

    Article  CAS  PubMed  Google Scholar 

  39. Dasgupta A, Lim AR, Ghajar CM. Circulating and disseminated tumor cells: harbingers or initiators of metastasis? Mol Oncol. 2017;11(1):40–61. https://doi.org/10.1002/1878-0261.12022.

    Article  PubMed  PubMed Central  Google Scholar 

  40. Steeg P. Tumor metastasis: mechanistic insights and clinical challenges. Nat Med. 2006;12:895–904. https://doi.org/10.1038/nm1469.

    Article  CAS  PubMed  Google Scholar 

  41. Meng S, Tripathy D, Frenkel EP, Shete S, Naftalis EZ, et al. Circulating tumor cells in patients with breast cancer dormancy. Clin Cancer Res. 2004;10(24):8152. https://doi.org/10.1158/1078-0432.CCR-04-1110.

    Article  PubMed  Google Scholar 

  42. Braun S, Vogl FD, Naume B, Janni W, Osborne MP, et al. A pooled analysis of bone marrow micrometastasis in breast cancer. N Engl J Med. 2005;353(8):793–802.

    Article  CAS  PubMed  Google Scholar 

  43. Hartung F, Wang Y, Aronow B, Weber GF. A core program of gene expression characterizes cancer metastases. Oncotarget. 2017;8(60):102161–75. https://doi.org/10.18632/oncotarget.22240.

    Article  PubMed  PubMed Central  Google Scholar 

  44. Schmidt-Kittler O, Ragg T, Daskalakis A, Granzow M, Ahr A, et al. From latent disseminated cells to overt metastasis: genetic analysis of systemic breast cancer progression. Proc Nat Acad Sci. 2003;100(13):7737. https://doi.org/10.1073/pnas.1331931100.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  45. Schardt JA, Meyer M, Hartmann CH, Schubert F, Schmidt-Kittler O, et al. Genomic analysis of single cytokeratin-positive cells from bone marrow reveals early mutational events in breast cancer. Cancer Cell. 2005;8(3):227–39. https://doi.org/10.1016/j.ccr.2005.08.003.

    Article  CAS  PubMed  Google Scholar 

  46. Waldman FM, DeVries S, Chew KL, Moore DH II, Kerlikowske K, Ljung B-M. Chromosomal alterations in ductal carcinomas in situ and their in situ recurrences. J Natl Cancer Inst. 2000;92(4):313–20. https://doi.org/10.1093/jnci/92.4.313.

    Article  CAS  PubMed  Google Scholar 

  47. Chin K, de Solorzano CO, Knowles D, Jones A, Chou W, et al. In situ analyses of genome instability in breast cancer. Nat Genet. 2004;36(9):984–8. https://doi.org/10.1038/ng1409.

    Article  CAS  PubMed  Google Scholar 

  48. Iwamoto T, Niikura N, Ogiya R, et al. Distinct gene expression profiles between primary breast cancers and brain metastases from pair-matched samples. Sci Rep. 2019;9(1):13343. https://doi.org/10.1038/s41598-019-50099-y.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  49. Riebensahm C, Joosse SA, Mohme M, Hanssen A, Matschke J, et al. Clonality of circulating tumor cells in breast cancer brain metastasis patients. Breast Cancer Res. 2019;21(1):101. https://doi.org/10.1186/s13058-019-1184-2.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  50. Holsbø E, Olsen KS. Metastatic breast cancer and pre-diagnostic blood gene expression profiles—the Norwegian Women and Cancer (NOWAC) post-genome cohort. Front Oncol. 2020;10(2277). https://doi.org/10.3389/fonc.2020.575461.

  51. Sieuwerts AM, Mostert B, Bolt-de Vries J, Peeters D, de Jongh FE, et al. mRNA and microRNA expression profiles in circulating tumor cells and primary tumors of metastatic breast cancer patients. Clin Cancer Res. 2011;17(11):3600. https://doi.org/10.1158/1078-0432.CCR-11-0255.

    Article  CAS  PubMed  Google Scholar 

  52. Yu M, Bardia A, Wittner BS, et al. Circulating breast tumor cells exhibit dynamic changes in epithelial and mesenchymal composition. Science. 2013;339(6119):580–4. https://doi.org/10.1126/science.1228522.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  53. Hosseini H, Obradović MMS, Hoffmann M, et al. Early dissemination seeds metastasis in breast cancer. Nature. 2016;540(7634):552–8. https://doi.org/10.1038/nature20785.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  54. Khan S, Greco D, Michailidou K, Milne RL, Muranen TA, et al. MicroRNA related polymorphisms and breast cancer risk. PLoS One. 2014;9(11):e109973. https://doi.org/10.1371/journal.pone.0109973.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  55. Lee Y, Ahn C, Han J, et al. The nuclear RNase III Drosha initiates microRNA processing. Nature. 2003;425(6956):415–9. https://doi.org/10.1038/nature01957.

    Article  CAS  PubMed  Google Scholar 

  56. Cheung KJ, Ewald AJ. A collective route to metastasis: seeding by tumor cell clusters. Science. 2016;352(6282):167–9. https://doi.org/10.1126/science.aaf6546.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  57. Cheung KJ, Padmanaban V, Silvestri V, Schipper K, Cohen JD, et al. Polyclonal breast cancer metastases arise from collective dissemination of keratin 14-expressing tumor cell clusters. PNAS. 2016;113(7):E854. https://doi.org/10.1073/pnas.1508541113.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  58. Donato C, Kunz L, Castro-Giner F, et al. Hypoxia triggers the intravasation of clustered circulating tumor cells. Cell Rep. 2020;32(10):108105. https://doi.org/10.1016/j.celrep.2020.108105.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  59. Aceto N, Bardia A, Miyamoto DT, et al. Circulating tumor cell clusters are oligoclonal precursors of breast cancer metastasis. Cell. 2014;158(5):1110–22. https://doi.org/10.1016/j.cell.2014.07.013.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  60. Aktary Z, Pasdar M. Plakoglobin: role in tumorigenesis and metastasis. Int J Cell Biol. 2012;2012:189521. https://doi.org/10.1155/2012/189521.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  61. Gkountela S, Castro-Giner F, Szczerba BM, Vetter M, Landin J, et al. Circulating tumor cell clustering shapes DNA methylation to enable metastasis seeding. Cell. 2019;176(1–2):98–112.e114. https://doi.org/10.1016/j.cell.2018.11.046.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  62. Smietanka U, Szostakowska-Rodzos M, Tabor S, Fabisiewicz A, Grzybowska EA. Clusters, assemblies and aggregates of tumor cells in the blood of breast cancer patients; composition, mode of action, detection and impact on metastasis and survival. Int J Transl Med. 2021;1(1):55–68. https://doi.org/10.3390/ijtm1010005.

    Article  Google Scholar 

  63. Wrenn ED, Yamamoto A, Moore BM, Huang Y, McBirney M, et al. Regulation of collective metastasis by nanolumenal signaling. Cell. 2020;183(2):395–410.e19. https://doi.org/10.1016/j.cell.2020.08.045.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  64. Ward MP, Kane LE, Norris LA, et al. Platelets, immune cells and the coagulation cascade; friend or foe of the circulating tumour cell? Mol Cancer. 2021;20(1):59. https://doi.org/10.1186/s12943-021-01347-1.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  65. Tan W, Liang G, Xie X, et al. Incorporating microRNA into molecular phenotypes of circulating tumor cells enhances the prognostic accuracy for patients with metastatic breast cancer. Oncologist. 2019;24(11):e1044–54. https://doi.org/10.1634/theoncologist.2018-0697.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  66. Reduzzi C, Di Cosimo S, Gerratana L, et al. Circulating tumor cell clusters are frequently detected in women with early-stage breast cancer. Cancers (Basel). 2021;13(10):2356. https://doi.org/10.3390/cancers13102356.

    Article  CAS  Google Scholar 

  67. Larsson AM, Jansson S, Bendahl PO, et al. Longitudinal enumeration and cluster evaluation of circulating tumor cells improve prognostication for patients with newly diagnosed metastatic breast cancer in a prospective observational trial. Breast Cancer Res. 2018;20(1):48. https://doi.org/10.1186/s13058-018-0976-0.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  68. Wang C, Mu Z, Chervoneva I, et al. Longitudinally collected CTCs and CTC-clusters and clinical outcomes of metastatic breast cancer. Breast Cancer Res Treat. 2017;161(1):83–94. https://doi.org/10.1007/s10549-016-4026-2.

    Article  PubMed  Google Scholar 

  69. Mohanty A, Mohanty SK, Rout S, Pani C. Liquid biopsy, the hype vs. hope in molecular and clinical oncology. Semin Oncol. 2021;48(3):259–67. https://doi.org/10.1053/j.seminoncol.2021.06.002.

    Article  PubMed  Google Scholar 

  70. Alimirzaie S, Bagherzadeh M, Akbari MR. Liquid biopsy in breast cancer: a comprehensive review. Clin Genet. 2019;95(6):643–60. https://doi.org/10.1111/cge.13514.

    Article  CAS  PubMed  Google Scholar 

  71. Qi F, Gao F, Cai Y, Han X, Qi Y, et al. Complex age- and cancer-related changes in human blood transcriptome-implications for pan-cancer diagnostics. Front Genet. 2021;12:746879. https://doi.org/10.3389/fgene.2021.746879.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  72. Keller L, Pantel K. Unravelling tumour heterogeneity by single-cell profiling of circulating tumour cells. Nat Rev Cancer. 2019;19(10):553–67. https://doi.org/10.1038/s41568-019-0180-2.

    Article  CAS  PubMed  Google Scholar 

  73. Seale KN, Tkaczuk KHR. Circulating biomarkers in breast cancer. Clin Breast Cancer. 2021. https://doi.org/10.1016/j.clbc.2021.09.006.

  74. Tkaczuk KHR, Goloubeva O, Tait NS, Feldman F, Tan M, et al. The significance of circulating epithelial cells in breast cancer patients by a novel negative selection method. Breast Cancer Res Treat. 2008;111(2):355–64. https://doi.org/10.1007/s10549-007-9771-9.

    Article  PubMed  Google Scholar 

  75. Sparano J, O’Neill A, Alpaugh K, Wolff AC, Northfelt DW, Dang CT, et al. Association of circulating tumor cells with late recurrence of estrogen receptor–positive breast cancer: a secondary analysis of a randomized clinical trial. JAMA Oncol. 2018;4(12):1700–6. https://doi.org/10.1001/jamaoncol.2018.2574.

    Article  PubMed  PubMed Central  Google Scholar 

  76. Bortolini Silveira A, Bidard FC, Tanguy ML, Girard E, Trédan O, et al. Multimodal liquid biopsy for early monitoring and outcome prediction of chemotherapy in metastatic breast cancer. NPJ Breast Cancer. 2021;7(1):115. https://doi.org/10.1038/s41523-021-00319-4.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  77. Panagopoulou M, Karaglani M, Balgkouranidou I, Biziota E, Koukaki T, et al. Circulating cell-free DNA in breast cancer: size profiling, levels, and methylation patterns lead to prognostic and predictive classifiers. Oncogene. 2019;38(18):3387–401. https://doi.org/10.1038/s41388-018-0660-y.

    Article  CAS  PubMed  Google Scholar 

  78. Mouliere F, Rosenfeld N. Circulating tumor-derived DNA is shorter than somatic DNA in plasma. Proc Natl Acad Sci. 2015;112(11):3178. https://doi.org/10.1073/pnas.1501321112.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  79. Allegretti M, Fabi A, Giordani E, Ercolani C, Romania P, et al. Liquid biopsy identifies actionable dynamic predictors of resistance to Trastuzumab Emtansine (T-DM1) in advanced HER2-positive breast cancer. Mol Cancer. 2021;20(1):151. https://doi.org/10.1186/s12943-021-01438-z.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  80. Russo A, Incorvaia L, Del Re M, Malapelle U, Capoluongo E, et al. The molecular profiling of solid tumors by liquid biopsy: a position paper of the AIOM-SIAPEC-IAP-SIBioC-SIC-SIF Italian Scientific Societies. ESMO Open. 2021;6(3):100164. https://doi.org/10.1016/j.esmoop.2021.100164.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  81. André F, Ciruelos EM, Juric D, Loibl S, Campone M, et al. Alpelisib plus fulvestrant for PIK3CA-mutated, hormone receptor-positive, human epidermal growth factor receptor-2-negative advanced breast cancer: final overall survival results from SOLAR-1. Ann Oncol. 2021;32(2):208–17. https://doi.org/10.1016/j.annonc.2020.11.011.

    Article  CAS  PubMed  Google Scholar 

  82. O’Leary B, Hrebien S, Morden JP, Beaney M, Fribbens C, Huang X, et al. Early circulating tumor DNA dynamics and clonal selection with palbociclib and fulvestrant for breast cancer. Nat Commun. 2018;9(1):896. https://doi.org/10.1038/s41467-018-03215-x.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  83. Calin GA, Sevignani C, Dumitru CD, Hyslop T, Noch E, et al. Human microRNA genes are frequently located at fragile sites and genomic regions involved in cancers. Proc Natl Acad Sci U S A. 2004;101(9):2999–3004.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  84. Iorio MV, Ferracin M, Liu C-G, Veronese A, Spizzo R, et al. MicroRNA gene expression deregulation in human breast cancer. 2005;65(16):7065–70. https://doi.org/10.1158/0008-5472.CAN-05-1783.

  85. Gold B, Cankovic M, Furtado LV, Meier F, Gocke CD. Do circulating tumor cells, exosomes, and circulating tumor nucleic acids have clinical utility? A report of the association for molecular pathology. J Mol Diagn. 2015;17(3):209–24. https://doi.org/10.1016/j.jmoldx.2015.02.001.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  86. Doyle LM, Wang MZ. Overview of extracellular vesicles, their origin, composition, purpose, and methods for exosome isolation and analysis. Cells. 2019;8(7):727. https://doi.org/10.3390/cells8070727.

    Article  CAS  PubMed Central  Google Scholar 

  87. Izzotti A, Carozzo S, Pulliero A, Zhabayeva D, Ravetti JL, Bersimbaev R. Extracellular MicroRNA in liquid biopsy: applicability in cancer diagnosis and prevention. Am J Cancer Res. 2016;6(7):1461–93.

    CAS  PubMed  PubMed Central  Google Scholar 

  88. Schrauder MG, Strick R, Schulz-Wendtland R, Strissel PL, Kahmann L, et al. Circulating micro-RNAs as potential blood-based markers for early stage breast cancer detection. PLoS One. 2012;7(1):e29770. https://doi.org/10.1371/journal.pone.0029770.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  89. Arroyo JD, Chevillet JR, Kroh EM, Ruf IK, Pritchard CC, et al. Argonaute2 complexes carry a population of circulating microRNAs independent of vesicles in human plasma. Proc Natl Acad Sci U S A. 2011;108(12):5003–8. https://doi.org/10.1073/pnas.1019055108.

    Article  PubMed  PubMed Central  Google Scholar 

  90. Valadi H, Ekström K, Bossios A, Sjöstrand M, Lee JJ, Lötvall JO. Exosome-mediated transfer of mRNAs and microRNAs is a novel mechanism of genetic exchange between cells. Nat Cell Biol. 2007;9(6):654–9. https://doi.org/10.1038/ncb1596.

    Article  CAS  PubMed  Google Scholar 

  91. Mercer TR, Dinger ME, Mattick JS. Long non-coding RNAs: insights into functions. Nat Rev Genet. 2009;10(3):155–9. https://doi.org/10.1038/nrg2521.

    Article  CAS  PubMed  Google Scholar 

  92. López-Urrutia E, Bustamante Montes LP, Ladrón de Guevara Cervantes D, Pérez-Plasencia C, Campos-Parra AD. Crosstalk between long non-coding rnas, micro-RNAs and mRNAs: Deciphering molecular mechanisms of master regulators in cancer. Front Oncol. 2019;9:669. https://doi.org/10.3389/fonc.2019.00669.

    Article  PubMed  PubMed Central  Google Scholar 

  93. Mahmoud MM, Sanad EF, Elshimy RAA, Hamdy NM. Competitive endogenous role of the LINC00511/miR-185-3p axis and miR-301a-3p from liquid biopsy as molecular markers for breast cancer diagnosis. Front Oncol. 2021;11:749753. https://doi.org/10.3389/fonc.2021.749753.

    Article  PubMed  PubMed Central  Google Scholar 

  94. Théry C, Witwer KW, Aikawa E, Alcaraz MJ, Anderson JD, et al. Minimal information for studies of extracellular vesicles 2018 (MISEV2018): a position statement of the International Society for Extracellular Vesicles and update of the MISEV2014 guidelines. J Extracell Vesicles. 2018;7(1):1535750. https://doi.org/10.1080/20013078.2018.1535750.

    Article  PubMed  PubMed Central  Google Scholar 

  95. Nanou A, Miller MC, Zeune LL, de Wit S, Punt CJ, et al. Tumour-derived extracellular vesicles in blood of metastatic cancer patients associate with overall survival. Br J Cancer. 2020;122(6):801–11. https://doi.org/10.1038/s41416-019-0726-9.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  96. O’Brien K, Breyne K, Ughetto S, Laurent LC, Breakefield XO. RNA delivery by extracellular vesicles in mammalian cells and its applications. Nat Rev Mol Cell Biol. 2020;21(10):585–606. https://doi.org/10.1038/s41580-020-0251-y.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  97. Huang X, Yuan T, Tschannen M, Sun Z, Jacob H, et al. Characterization of human plasma-derived exosomal RNAs by deep sequencing. BMC Genomics. 2013;14(1):319. https://doi.org/10.1186/1471-2164-14-319.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  98. Pigati L, Yaddanapudi SCS, Iyengar R, Kim D-J, Hearn SA, et al. Selective release of microRNA species from normal and malignant mammary epithelial cells. PLoS One. 2010;5(10):e13515. https://doi.org/10.1371/journal.pone.0013515.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  99. Madhavan D, Zucknick M, Wallwiener M, Cuk K, Modugno C, et al. Circulating miRNAs as surrogate markers for circulating tumor cells and prognostic markers in metastatic breast cancer. Clin Cancer Res. 2012;18(21):5972. https://doi.org/10.1158/1078-0432.CCR-12-1407.

    Article  CAS  PubMed  Google Scholar 

  100. Heaphy CM, Griffith JK, Bisoffi M. Mammary field cancerization: molecular evidence and clinical importance. Breast Cancer Res Treat. 2009;118(2):229–39. https://doi.org/10.1007/s10549-009-0504-0.

    Article  PubMed  Google Scholar 

  101. Alunni-Fabbroni M, Majunke L, Trapp EK, et al. Whole blood microRNAs as potential biomarkers in post-operative early breast cancer patients. BMC Cancer. 2018;18:141. https://doi.org/10.1186/s12885-018-4020-7.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  102. Majumder M, Ugwuagbo KC, Maiti S, Lala PK, Brackstone M. Pri-miR526b and Pri-miR655 are potential blood biomarkers for breast cancer. Cancers. 2021;13(15):3838. https://doi.org/10.3390/cancers13153838.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  103. Shin B, Feser R, Nault B, Hunter S, Maiti S, Ugwuagbo KC, et al. MiR526b and miR655 induce oxidative stress in breast cancer. Int J Mol Sci. 2019;20(16):4039. https://doi.org/10.3390/ijms20164039.

    Article  CAS  PubMed Central  Google Scholar 

  104. Cheng L, Sharples RA, Scicluna BJ, Hill AF. Exosomes provide a protective and enriched source of miRNA for biomarker profiling compared to intracellular and cell-free blood. J Extracell Vesicles. 2014;3. https://doi.org/10.3402/jev.v3403.23743.

  105. Hunter S, Nault B, Ugwuagbo KC, Maiti S, Majumder M. Mir526b and Mir655 promote tumour associated angiogenesis and lymphangiogenesis in breast cancer. Cancers. 2019;11(7):938. https://doi.org/10.3390/cancers11070938.

    Article  CAS  PubMed Central  Google Scholar 

  106. Itani MM, Nassar FJ, Tfayli AH, Talhouk RS, Chamandi GK, et al. A signature of four circulating microRNAs as potential biomarkers for diagnosing early-stage breast cancer. Int J Mol Sci. 2021;22(11):6121.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  107. Silvestri M, Reduzzi C, Feliciello G, et al. Detection of genomically aberrant cells within circulating tumor microemboli (CTMs) isolated from early-stage breast cancer patients. Cancers (Basel). 2021;13(6):1409. https://doi.org/10.3390/cancers13061409.

    Article  CAS  Google Scholar 

  108. Pérez-Rivas LG, Jerez JM, Carmona R, de Luque V, Vicioso L, et al. A microRNA signature associated with early recurrence in breast cancer. PLoS One. 2014;9(3):e91884. https://doi.org/10.1371/journal.pone.0091884.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  109. Yan LX, Huang XF, Shao Q, et al. MicroRNA miR-21 overexpression in human breast cancer is associated with advanced clinical stage, lymph node metastasis and patient poor prognosis. RNA. 2008;14(11):2348–60. https://doi.org/10.1261/rna.1034808.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  110. McAnena P, Tanriverdi K, Curran C, et al. Circulating microRNAs miR-331 and miR-195 differentiate local luminal a from metastatic breast cancer. BMC Cancer. 2019;19(1):436. https://doi.org/10.1186/s12885-019-5636-y.

    Article  PubMed  PubMed Central  Google Scholar 

  111. Søkilde R, Persson H, Ehinger A, et al. Refinement of breast cancer molecular classification by miRNA expression profiles. BMC Genomics. 2019;20(1):503. https://doi.org/10.1186/s12864-019-5887-7.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  112. Lowery AJ, Miller N, Dwyer RM, Kerin MJ. Dysregulated miR-183 inhibits migration in breast cancer cells. BMC Cancer. 2010;10:502. https://doi.org/10.1186/1471-2407-10-502.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  113. Huang Q, Gumireddy K, Schrier M, et al. The microRNAs miR-373 and miR-520c promote tumour invasion and metastasis. Nat Cell Biol. 2008;10(2):202–10. https://doi.org/10.1038/ncb1681.

    Article  CAS  PubMed  Google Scholar 

  114. Jinesh GG, Flores ER, Brohl AS. Chromosome 19 miRNA cluster and CEBPB expression specifically mark and potentially drive triple negative breast cancers. PLoS One. 2018;13(10):e0206008. https://doi.org/10.1371/journal.pone.0206008.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  115. Jordan N, Bardia A, Wittner B, et al. HER2 expression identifies dynamic functional states within circulating breast cancer cells. Nature. 2016;537:102–6. https://doi.org/10.1038/nature19328.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  116. Yu T, Wang C, Xie M, Zhu C, Shu Y, Tang J, et al. Heterogeneity of CTC contributes to the organotropism of breast cancer. Biomed Pharmacother. 2021;137:111314. https://doi.org/10.1016/j.biopha.2021.111314.

    Article  CAS  PubMed  Google Scholar 

  117. Hannafon BN, Trigoso YD, Calloway CL, Zhao YD, Lum DH, et al. Plasma exosome microRNAs are indicative of breast cancer. Breast Cancer Res. 2016;18(1):90.

    Article  PubMed  PubMed Central  Google Scholar 

  118. Ozawa PMM, Vieira E, Lemos DS, Souza ILM, Zanata SM, et al. Identification of miRNAs enriched in extracellular vesicles derived from serum samples of breast cancer patients. Biomolecules. 2020;10(1). https://doi.org/10.3390/biom10010150.

  119. Li M, Zhou Y, Xia T, Zhou X, Huang Z, et al. Circulating microRNAs from the miR-106a–363 cluster on chromosome X as novel diagnostic biomarkers for breast cancer. Breast Cancer Res Treat. 2018;170(2):257–70. https://doi.org/10.1007/s10549-018-4757-3.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  120. Ozawa PMM, Jucoski TS, Vieira E, Carvalho TM, Malheiros D. Ribeiro EMdSF: liquid biopsy for breast cancer using extracellular vesicles and cell-free microRNAs as biomarkers. Transl Res. 2020;223:40–60. https://doi.org/10.1016/j.trsl.2020.04.002.

    Article  CAS  PubMed  Google Scholar 

  121. Holubekova V, Kolkova Z, Grendar M, Brany D, Dvorska D, et al. Pathway analysis of selected circulating miRNAs in plasma of breast cancer patients: a preliminary study. Int J Mol Sci. 2020;21(19). https://doi.org/10.3390/ijms21197288.

  122. Cuk K, Zucknick M, Heil J, Madhavan D, Schott S, et al. Circulating microRNAs in plasma as early detection markers for breast cancer. Int J Cancer. 2013;132(7):1602–12. https://doi.org/10.1002/ijc.27799.

    Article  CAS  PubMed  Google Scholar 

  123. Lagendijk M, Sadaatmand S, Koppert LB, Tilanus-Linthorst MMA, de Weerd V, et al. MicroRNA expression in pre-treatment plasma of patients with benign breast diseases and breast cancer. Oncotarget. 2018;9(36):24335–46. https://doi.org/10.18632/oncotarget.25262.

    Article  PubMed  PubMed Central  Google Scholar 

  124. Heneghan HM, Miller N, Kelly R, Newell J, Kerin MJ. Systemic miRNA-195 differentiates breast cancer from other malignancies and is a potential biomarker for detecting noninvasive and early stage disease. Oncologist. 2010;15(7):673–82. https://doi.org/10.1634/theoncologist.2010-0103.

    Article  PubMed  PubMed Central  Google Scholar 

  125. Zhao F-l, Dou Y-c, Wang X-f, Han D-c, Lv Z-g, Ge S-l, et al. Serum microRNA-195 is down-regulated in breast cancer: a potential marker for the diagnosis of breast cancer. Mol Biol Rep. 2014;41(9):5913–22. https://doi.org/10.1007/s11033-014-3466-1.

    Article  CAS  PubMed  Google Scholar 

  126. Witzel I, Oliveira-Ferrer L, Pantel K, Müller V, Wikman H. Breast cancer brain metastases: biology and new clinical perspectives. Breast Cancer Res. 2016;18(1):8. https://doi.org/10.1186/s13058-015-0665-1.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  127. Jin J, Gao Y, Zhang J, Wang L, Wang B, Cao J, et al. Incidence, pattern and prognosis of brain metastases in patients with metastatic triple negative breast cancer. BMC Cancer. 2018;18(1):446. https://doi.org/10.1186/s12885-018-4371-0.

    Article  PubMed  PubMed Central  Google Scholar 

  128. Tominaga N, Kosaka N, Ono M, Katsuda T, Yoshioka Y, et al. Brain metastatic cancer cells release microRNA-181c-containing extracellular vesicles capable of destructing blood–brain barrier. Nat Commun. 2015;6(1):6716. https://doi.org/10.1038/ncomms7716.

    Article  CAS  PubMed  Google Scholar 

  129. Kang Y, Siegel PM, Shu W, Drobnjak M, Kakonen SM, et al. A multigenic program mediating breast cancer metastasis to bone. Cancer Cell. 2003;3(6):537–49. https://doi.org/10.1016/S1535-6108(03)00132-6.

    Article  CAS  PubMed  Google Scholar 

  130. Wu K, Feng J, Lyu F, Xing F, Sharma S, et al. Exosomal miR-19a and IBSP cooperate to induce osteolytic bone metastasis of estrogen receptor-positive breast cancer. Nat Commun. 2021;12(1):5196. https://doi.org/10.1038/s41467-021-25473-y.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  131. Di Cosimo S, Appierto V, Pizzamiglio S, Silvestri M, Baselga J, et al. Early modulation of circulating microRNAs levels in HER2-positive breast cancer patients treated with trastuzumab-based neoadjuvant therapy. Int J Mol Sci. 2020;21(4):1386.

    Article  CAS  PubMed Central  Google Scholar 

  132. Salvador-Coloma C, Santaballa A, Sanmartín E, Calvo D, García A, et al. Immunosuppressive profiles in liquid biopsy at diagnosis predict response to neoadjuvant chemotherapy in triple-negative breast cancer. Eur J Cancer (Oxford, England: 1990). 2020;139:119–34. https://doi.org/10.1016/j.ejca.2020.08.020.

    Article  CAS  Google Scholar 

  133. Shimomura A, Shiino S, Kawauchi J, Takizawa S, Sakamoto H, et al. Novel combination of serum microRNA for detecting breast cancer in the early stage. Cancer Sci. 2016;107(3):326–34. https://doi.org/10.1111/cas.12880.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  134. Stückrath I, Rack B, Janni W, Jäger B, Pantel K, Schwarzenbach H. Aberrant plasma levels of circulating miR-16, miR-107, miR-130a and miR-146a are associated with lymph node metastasis and receptor status of breast cancer patients. Oncotarget. 2015;6(15):13387–401. https://doi.org/10.18632/oncotarget.3874.

    Article  PubMed  PubMed Central  Google Scholar 

  135. Lasham A, Fitzgerald SJ, Knowlton N, Robb T, Tsai P, et al. A predictor of early disease recurrence in patients with breast cancer using a cell-free RNA and protein liquid biopsy. Clin Breast Cancer. 2020;20(2):108–16. https://doi.org/10.1016/j.clbc.2019.07.003.

    Article  CAS  PubMed  Google Scholar 

  136. Rodríguez-Martínez A, de Miguel-Pérez D, Ortega FG, García-Puche JL, Robles-Fernández I, et al. Exosomal miRNA profile as complementary tool in the diagnostic and prediction of treatment response in localized breast cancer under neoadjuvant chemotherapy. Breast Cancer Res. 2019;21(1):21. https://doi.org/10.1186/s13058-019-1109-0.

    Article  PubMed  PubMed Central  Google Scholar 

  137. Riethdorf S. Detection of microRNAs in circulating tumor cells. Trans Can Res. 2017;7(2):S197–208. https://doi.org/10.21037/tcr.2017.10.24.

    Article  CAS  Google Scholar 

  138. Gasch C, Plummer PN, Jovanovic L, et al. Heterogeneity of miR-10b expression in circulating tumor cells. Sci Rep. 2015;5:15980. https://doi.org/10.1038/srep15980.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  139. Yoo B, Kavishwar A, Wang P, et al. Therapy targeted to the metastatic niche is effective in a model of stage IV breast cancer. Sci Rep. 2017;7:45060. https://doi.org/10.1038/srep45060.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  140. Fischer KR, Durrans A, Lee S, et al. Epithelial-to-mesenchymal transition is not required for lung metastasis but contributes to chemoresistance. Nature. 2015;527(7579):472–6. https://doi.org/10.1038/nature15748.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  141. Drusco A, Bottoni A, Laganà A, et al. A differentially expressed set of microRNAs in cerebro-spinal fluid (CSF) can diagnose CNS malignancies. Oncotarget. 2015;6(25):20829–39. https://doi.org/10.18632/oncotarget.4096.

    Article  PubMed  PubMed Central  Google Scholar 

  142. Gao S, Lu X, Ma J, Zhou Q, Tang R, Fu Z, et al. Comprehensive analysis of lncRNA and miRNA regulatory network reveals potential prognostic non-coding RNA involved in breast cancer progression. Front Genet. 2021;12:621809.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  143. Zhou Z, Wu Q, Yan Z, Zheng H, Chen CJ, et al. Extracellular RNA in a single droplet of human serum reflects physiologic and disease states. Proc Natl Acad Sci U S A. 2019;116(38):19200–8. https://doi.org/10.1073/pnas.1908252116.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

Download references

Acknowledgements

We wish to acknowledge Emer Hennessy for providing administrative support.

Funding

“This publication has emanated from research conducted with the financial support of Precision Oncology Ireland, a Consortium of 5 Irish Universities, 6 Irish Charities, and 7 Industry Partners, which is part-funded by the National Breast Cancer Research Institute [NBCRI] and Science Foundation Ireland [SFI] Strategic Partnership Programme, under Grant number [18/SPP/3522]. VR and MGD received postdoctoral and doctoral fellowship support from Precision Oncology Ireland (POI) and National Breast Cancer Research Institute (NBCRI) Ireland respectively.

Author information

Authors and Affiliations

Authors

Contributions

Literature review and manuscript preparation —V.R., M.G.D., H.A.; Diagram representations—V.R.; Conception of the work—V.R., M.J.K.; Acquisition of project funding and project supervision—M.J.K.; Critical revision of the article— N.M., M.J.K. MJK gave the final approval of the version to be published. The author(s) read and approved the final manuscript.

Corresponding authors

Correspondence to Vinitha Richard or Michael J. Kerin.

Ethics declarations

Ethics approval and consent to participate

Not applicable.

Consent for publication

Not applicable.

Competing interests

The authors declare no competing interests.

Additional information

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, 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 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://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Richard, V., Davey, M.G., Annuk, H. et al. The double agents in liquid biopsy: promoter and informant biomarkers of early metastases in breast cancer. Mol Cancer 21, 95 (2022). https://doi.org/10.1186/s12943-022-01506-y

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1186/s12943-022-01506-y

Keywords