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Review

Circulating Cells with Macrophage-like Characteristics in Cancer: The Importance of Circulating Neoplastic-Immune Hybrid Cells in Cancer

by
Thomas L. Sutton
1,
Ranish K. Patel
1,
Ashley N. Anderson
2,
Stephen G. Bowden
3,
Riley Whalen
2,
Nicole R. Giske
2 and
Melissa H. Wong
2,4,*
1
Department of Surgery, Oregon Health & Science University, Portland, OR 97239, USA
2
Department of Cell, Developmental and Cancer Biology, Oregon Health & Science University, Portland, OR 97201, USA
3
Department of Neurological Surgery, Oregon Health & Science University, Portland, OR 97239, USA
4
Knight Cancer Institute, Oregon Health & Science University, Portland, OR 97201, USA
*
Author to whom correspondence should be addressed.
Cancers 2022, 14(16), 3871; https://doi.org/10.3390/cancers14163871
Submission received: 21 July 2022 / Revised: 8 August 2022 / Accepted: 9 August 2022 / Published: 11 August 2022
(This article belongs to the Collection Malignant and Non-malignant Atypical Circulating Cell in Cancer: Their Heterogeneity and Plasticity)
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Abstract

:

Simple Summary

In cancer, disseminated neoplastic cells circulating in blood are a source of tumor DNA, RNA, and protein, which can be harnessed to diagnose, monitor, and better understand the biology of the tumor from which they are derived. Historically, circulating tumor cells (CTCs) have dominated this field of study. While CTCs are shed directly into circulation from a primary tumor, they remain relatively rare, particularly in early stages of disease, and thus are difficult to utilize as a reliable cancer biomarker. Neoplastic-immune hybrid cells represent a novel subpopulation of circulating cells that are more reliably attainable as compared to their CTC counterparts. Here, we review two recently identified circulating cell populations in cancer—cancer-associated macrophage-like cells and circulating hybrid cells—and discuss the future impact for the exciting area of disseminated hybrid cells.

Abstract

Cancer remains a significant cause of mortality in developed countries, due in part to difficulties in early detection, understanding disease biology, and assessing treatment response. If effectively harnessed, circulating biomarkers promise to fulfill these needs through non-invasive “liquid” biopsy. While tumors disseminate genetic material and cellular debris into circulation, identifying clinically relevant information from these analytes has proven difficult. In contrast, cell-based circulating biomarkers have multiple advantages, including a source for tumor DNA and protein, and as a cellular reflection of the evolving tumor. While circulating tumor cells (CTCs) have dominated the circulating cell biomarker field, their clinical utility beyond that of prognostication has remained elusive, due to their rarity. Recently, two novel populations of circulating tumor-immune hybrid cells in cancer have been characterized: cancer-associated macrophage-like cells (CAMLs) and circulating hybrid cells (CHCs). CAMLs are macrophage-like cells containing phagocytosed tumor material, while CHCs can result from cell fusion between cancer and immune cells and play a role in the metastatic cascade. Both are detected in higher numbers than CTCs in peripheral blood and demonstrate utility in prognostication and assessing treatment response. Additionally, both cell populations are heterogeneous in their genetic, transcriptomic, and proteomic signatures, and thus have the potential to inform on heterogeneity within tumors. Herein, we review the advances in this exciting field.

1. Cancer Biomarkers: In Search of the Holy Grail

Cancer is the most common cause of death and is responsible for ~10 million deaths annually, worldwide [1]. Each disease site or histologic variant brings unique challenges in diagnosis, prognostication, and treatment. Current modalities to track cancer evolution or response to therapy include procedure-based, imaging-based, and biopsy-based technologies. Procedure-based biomarkers, such as screening colonoscopy for colon cancer or endoscopy for esophageal cancer, are effective in cancer detection but are resource-intensive, require specialized staff and equipment, and are not widely accessible [2,3,4]. Imaging-based biomarkers, such as computed tomography (CT), magnetic resonance imaging (MRI), ultrasonography, and positron emission tomography (PET) are non-invasive, repeatable tools that can be readily employed for the screening, surveillance, and assessment of therapeutic response. However, the performance of imaging devices considerably varies and protocols are not standardized [5]. Furthermore, imaging is dependent on the expertise of the interpreting radiologist: secondary interpretation of imaging-based biomarkers by sub-specialized diagnostic radiologists has been shown to uncover management-changing discrepancies in 18.6% of cases [6]. Additionally, many imaging modalities are expensive and not widely accessible in resource poor environments, thus limiting their utility as a universal approach to guiding clinical cancer care [7]. Tissue biopsy is currently the gold standard biomarker for diagnosing and evaluating tumor genetic, proteomic, or transcriptomic data; however, it is invasive, painful, carries potential adverse side effects, and is subject to false-negatives from sampling or pathologic interpretation [8]. Thus, the development of biomarkers of evolving tumors that can overcome these barriers represents a critical need in the monitoring and management of cancer [9].
The ideal biomarker is easily acquirable, non-invasive, operator-independent, and broadly relevant across a variety of diseases and treatment stages. For these reasons, peripheral blood is an optimal source for cancer biomarkers, including proteins [such as carcinoembryonic antigen (CEA) and cancer antigen 19-9 (CA 19-9)], exosomes, and cell-free tumor DNA (cfDNA)—all which derive from cancer cells [10,11,12,13,14,15,16]—as well as intact disseminated tumor-associated cell populations [17,18,19,20,21,22,23,24,25,26,27,28,29]. The requisite tumor origin of cell-derived components indicates that a cell-based assay provides the greatest diversity of information reflecting the evolving tumor biology, including genomic, proteomic, transcriptomic, and epigenetic profiles. Circulating tumor cells (CTCs) were discovered and first reported in 1869, and their study has dominated the field of circulating cells in cancer [30]. However, the limitation of CTCs as a clinically useful biomarker are increasingly apparent, highlighting the need for a focus on other tumor-derived circulating cell populations. Herein, we review atypical and newly defined circulating tumor-derived cell populations in cancer, focusing on circulating macrophage-like cells (CAMLs) [31], and circulating hybrid cells (CHCs) [29], which demonstrate exciting potential for their use to provide insights into tumor progression, tumor heterogeneity, and treatment response.

2. Circulating Tumor Cells

CTCs were first identified in the 19th century and are still considered the quintessential circulating neoplastic cell population in cancer [30]. While an in-depth review of CTCs in cancer is outside the scope of this review, we provide a brief overview of their advantages and disadvantages, which provides useful context when discussing other cell types. Conventionally-defined CTCs are defined by their expression of tumor-specific proteins (e.g., cytokeratin (CK) or epithelial cellular adhesion molecule (EpCAM) in epithelial malignancies), and the absence of the pan-leukocyte marker, CD45 [32,33]. CTC levels correlate with poor prognoses across a wide variety of disease sites, including colorectal cancer (CRC), pancreatic ductal adenocarcinoma (PDAC), breast cancer, and prostate cancer [17,18,19,20,21,22,23,24,25,26,27,28]. With regard to prostate cancer, CTC levels outperform the prostate-specific antigen as an early marker of response to chemotherapy [34]. Unfortunately, CTCs are rare in circulation, particularly in the early stages of many cancers. This is highlighted by the fact that a threshold of ≥5 CTCs per mL of blood (containing 5 − 10 × 106 nucleated cells per mL) correlates with high disease burden when used for prognostication [17,18,19,20,21,22,23,24,25,26,27,28]. As such, detection platforms for studies exploring CTCs as a clinical biomarker must utilize complex techniques to enrich for CTCs in patient blood by utilizing combinations of density, charge, size, and surface marker expression [35,36,37,38,39,40,41,42,43,44,45,46,47,48].
In spite of these limitations, CTCs are the only circulating cell population derived from cancer with commercially available assays approved for clinical use (e.g., CellSearch®) [49]. However, it should be noted that while CellSearch® does have FDA approval to inform prognosis in metastatic CRC, breast, and prostate cancer patients, the platform’s reliance on epithelial markers and exclusion of cells with immune antigen expression fail to capture important subpopulations with prognostic value [50,51,52,53,54]. Additionally, it is important to recognize that utility in prognostication does not necessarily equate to demonstrable benefits in care or clinician decision-making. To this end, CTC assays have been investigated as an early measure of chemotherapy response, with trial protocols triggering a change in the chemotherapy regimen if CTC levels do not drop following the initiation of 1st-line therapy. Unfortunately, none of the three trials that explored CTC correlates—the SWOG S0500 trial, CirCe01 trial, and the STIC CTC trial—demonstrated CTC-guided chemotherapy to be superior to chemotherapy guided by the judgement of a clinician informed by imaging surveillance during treatment [55,56,57]. Despite these limitations, studies have turned to combining CTCs with other circulating biomarkers such as CA19-9 [50,58], or by expanding protein marker phenotypic profiling, including the expression of cyclooxygenase-2 (COX2), leucine rich repeat containing G-protein coupled receptor 5 (LGR5), or caudal-type homeobox 2 (CDX2); in CTCs in CRC [59,60,61]; or mesenchymal markers, Vimentin, or Twist in PDAC [51,53,62,63]. To date, however, no assay utilizing a combinatorial approach, or protein marker expansion profiling has been found suitable for clinical use. Further, use of the CellSearch® platform beyond prognostication is considered off-label.
While CTCs are the best-studied circulating cell in cancer with hundreds of publications over several decades, limitations undoubtedly exist: (1) their rarity across disease stages inhibits their use in early detection and as a reliable “liquid tumor biopsy” for genetic, transcriptomic, or proteomic analyses on a commercial scale; (2) their hypothesized role in cancer metastasis remains unproven; (3) to date, multiple prospective studies have failed to show CTC enumeration improves clinical decision-making to affect outcomes. Due to these limitations, there is clearly space to consider alternative circulating tumor-derived cell populations in cancer as potential biomarkers of disease burden and state. Given that CTCs are defined by their lack of immune expression (i.e., CD45-negativity), we focus on the spectrum of tumor–immune cell interactions, and how these interactions can give rise to novel circulating tumor-derived cell populations with full or partial immune identity.

3. Tumor-Associated Macrophages, Phagocytosis, and Cancer-Associated Macrophage-Like Cells (CAMLs)

3.1. Tumor-Associated Macrophages

Macrophages are a multifaceted CD45-expressing immune cell population with known diverse roles in cancer biology [64,65,66,67]. Under homeostatic conditions, macrophages serve key roles in maintaining tissue protection through pro-inflammatory signaling and direct function including the phagocytosis of dead or dying cells [68]. In cancer, tissue-resident macrophages migrate toward hypoxic and necrotic tumor areas. Additionally, specific chemotactic factors released by neoplastic cells recruit peripheral monocytes (precursors of differentiated macrophages) to repopulate and augment the pool of tissue-resident macrophages [64,65,69]. Once recruited to the tumor microenvironment (TME), local cues shape the different functional and phenotypic populations [70]. The net effect of these processes is significant, resulting in tumor-associated macrophages (TAMs) composing up to 50% of total tumor mass in some cases [66,67].
Curiously, TAMs display oppositional functional phenotypes that depend on metabolite-linked crosstalk in the surrounding TME [71]. Classically activated M1 macrophages mediate several anti-tumor functions by forming reactive oxygen and nitrogen species, secreting pro-inflammatory cytokines [tissue necrosis factor-alpha, (TNF-α) interleukin-6 (IL-6), interferon-gamma (INF-γ)] to recruit tumor-killing leukocytes, or directly phagocytosing tumor cells [72]. In contrast, alternatively activated M2 macrophages are described as tumor-promoting, breaking down the basement membrane to facilitate tumor invasion, promoting angiogenesis, and protecting against T-cell mediated anti-tumor immune responses. TAMs are now known to not belong to just two populations, but rather exist on a dynamic spectrum; however, there may still be two predominant net functions (tumor-killing and promoting) [73,74,75,76,77]. TAM populations confer prognostic significance accordingly: an increase in M1-like TAMs is a relatively favorable prognostic factor, while M2-like TAM elevation is a biomarker of poor outcomes [78]. The spectrum of states that TAMs adopt—tumor-interfacing macrophages with both tumor-suppressing and tumor-promoting roles—coupled with their antigen presenting capabilities have generated great interest in circulating cells that express immune markers as a liquid biopsy for cancer [79,80].

3.2. Cancer-Associated Macrophage-Like Cells

Differentiated macrophages are rarely observed in peripheral blood; however, circulating macrophage-like cells that contain vesicles harboring tumor material were identified in patients with breast, pancreatic, and prostate cancer in 2014 by Adams et al. [31]. These cells were called cancer-associated macrophage-like cells (CAMLs) based on their cell surface expression of the macrophage protein CD14. CAMLs are a morphologically heterogeneous population, generally larger than CTCs, ranging from 25 to 300 µm in size. They have atypical or multiple nuclei, and they contain phagocytosed tumor protein epitopes in the cytoplasmic vesicles. Additionally, these cells may undergo homotypic fusion with other macrophages to result in their large size and frequent multinucleated phenotype: a well-described process for macrophages in chronic inflammatory diseases [81]. Notably, these cells are immune cells and cannot re-capitulate tumorigenesis like CTCs or CHCs.
CAMLs are found in esophageal, lung, liver, pancreatic, colorectal, breast, and prostate cancer [31,82,83,84,85,86,87]. Like CTCs, CAMLs are detectable in patients with advanced cancers, but have low sensitivity for detecting disease in early stages [82,84]. Similarly, epitope-detection in monocyte (EDIM) technologies measure circulating CD14+/CD16+ activated monocytes/macrophages with internalized tumor-derived proteins such as Apo10 and transketolase-like protein 1 (TKTL1) [88,89]. Such circulating cells are highly prevalent in oral cancer, PDAC, CRC, and cholangiocarcinoma, and reflect Apo10 and TKTL1 expression in primary tumors [88,89]. Due to definitional and measurement differences, it is difficult to assess whether cells detected by EDIM platforms are CAMLs, as phagocytosis is just one method by which circulating cells in cancer can reflect tumor characteristics, such as cell death associated with treatment response.
Published data indicate that while having higher levels of CAMLs pre-treatment is correlated with shorter overall and progression free survival [82,85], CAML enumeration tends to track with treatment response, where CAML numbers transiently increase in response to chemotherapy [31]. Notably, numbers of CAMLs change in an inverse relationship to CTCs (or CHCs), which decrease with therapy response, highlighting the functional nature of disseminated macrophage-like cells. Presumably these cells survey and engulf dying cancer cells, and thus increase in numbers when treatment is effective. Interestingly, CAML size differs in relation to treatment status; higher pre- and post-treatment CAML sizes in esophageal cancer and non-small cell lung carcinoma (NSCLC) have been correlated to worsened overall survival, possibly related to more aggressive disease subtypes [86,87].

4. Tumor Cell Fusion, Tumor-Immune Hybrids, and Circulating Hybrid Cells

4.1. Intratumoral Tumor–Immune Hybrids

The theory that fusion between immune cells and cancer plays a functional role in tumor progression and metastasis was first introduced by the German pathologist, Otto Aichel in 1911 [90]. This concept was predicated upon the notion that macrophage/leukocyte phenotypes expressed in neoplastic cells could be associated with functions known to drive cancer metastasis (i.e., migration, extravasation, immune evasion) [90]. While cell fusion occurs in both homeostatic and noncancerous inflammatory states [91,92,93], it has recently been described in malignancy [94,95,96,97,98,99,100,101,102]. Heterotypic cell fusion hybrids are generated in cell co-culture [29], in vitro murine models of injury-regeneration [94,96], in tumorigenesis [29,103], and in human cancer patients [29,33,104,105,106,107,108,109,110,111]. Much like the sampling of a tumor’s genome and proteome by CAMLs, tumor-immune hybrid cells harbor immune and neoplastic cell attributes, and thus provide important information with regard to tumor state and the tumor microenvironment. Given that neoplastic-immune hybrid cells harbor functional attributes of both parental cells of origin, these hybrids are implicated in influencing tumor progression and the metastatic spread of disease (Figure 1).
Spontaneous cell fusion is observed in real time by in vitro live-imaging of co-culturing murine MC-38 CRC cells expressing red fluorescent protein (RFP) and green fluorescent protein (GFP) expressing macrophages. Hybrid cells harboring cytoplasmic GFP and intact nuclear RFP are characteristic. GFP+/RFP+ hybrid cells are mitotically active, with sustained co-expression of fluorescent markers in daughter cells across multiple generations [29]. Other groups similarly characterized fusion hybrids in murine breast cancer and glioblastoma models and with in vitro human breast cancer cell lines [33,112,113,114,115]. These findings delineate cellular fusion from other immune cell functions and phenomena such as phagocytosis and trogocytosis [116].
Findings from in vitro studies suggest that cell fusion hybrids may participate in the metastatic cascade. MC38-derived hybrids display enhanced migratory and invasive properties relative to unfused MC38 cells as measured using a Boyden chamber assay [29]. In addition to the acquisition of macrophage migratory and invasive behaviors, in vitro-derived melanoma-macrophage hybrid cells initiated tumorigenesis when orthotopically injected into recipient mice. In this setting, unfused tumor cells required an order of magnitude higher numbers of cells to support tumor growth [29,33]. Similar findings have also been shown in human and murine models of ovarian, breast, and gastric carcinoma, with evidence suggesting that fusion promotes the epithelial-to-mesenchymal transition (EMT) and activates Wnt/β-catenin signaling pathways [103,117,118]. Notably, growth at the primary site of tumor–immune hybrid injection has not been shown in all studies [119]. Finally, in vitro-derived MC38 hybrid cells generated pulmonary metastases with higher numbers and growth than unfused MC38 cells using an experimental model of metastasis [29].
A number of groups have demonstrated the spontaneous generation of cell fusion hybrids using in vivo models. Inflammation and epithelial proliferation are key mediators within the TME required to facilitate cellular fusion, and these conditions can be recreated in murine models by utilizing γ-irradiation and bone marrow derived cell (BMDC) transplantation [94,96]. Using this model system, several BMDC populations displayed the ability to fuse with host intestinal epithelia, including common myeloid and lymphoid progenitors, mature B/T cells, and macrophages. However, macrophages displayed the most robust cell fusion capacity, at a proportion significantly higher than other BMDC lineages [95]. This suggests that the macrophage is one principal fusogenic leukocyte. Further, given the importance of the monocyte/macrophage lineage within the TME, this indicates that circulating tumor-immune cells could provide information on the evolving immune landscape within the tumor.
Hybrid cells generated in bone marrow transplanted mice with intestinal tumors harbored transcriptomic signatures of both macrophage and epithelial cells, while simultaneously displaying a unique transcriptomic signature [95]. Several genes associated with metastatic spread were upregulated in hybrid cells relative to unfused tumor cells, including activated leukocyte cell adhesion molecule (ALCAM), runt-related transcription factor 1 (RUNX1), and fms-related tyrosine kinase 4 (FLT4) [95,120,121,122]. Similar findings were identified within in vitro models of spontaneous fusion hybrid formation in sarcoma [123]. The theme of cellular reprogramming following fusion has been recapitulated across numerous studies in cancer and other physiologic states, including injury-regeneration in multiple organ sites [92,94,96,115,124,125,126,127,128,129,130,131,132,133].
Tumor–immune hybrids in circulation harbor features of solid malignancies. The strongest in vivo evidence comes from female recipients of sex-mismatched bone marrow transplants who subsequently developed solid organ malignancies. In these patients who developed PDAC, tumor specimens harbored cells positive for Y chromosomes and tumor markers, such as CK, indicating cellular fusion between male donor leukocytes and recipient tissue intratumorally [29]. The list of malignancies in which tumor–immune hybrids have been identified continues to expand, now including PDAC, renal cell carcinoma, head and neck squamous cell carcinoma (HNSCC), lung adenocarcinoma, NSCLC, melanoma, prostate adenocarcinoma, and ovarian adenocarcinoma [29,103,109,110,115,134,135,136,137].
Together, the available evidence on macrophage–tumor cell fusion hybrids suggests that fusion imparts a highly proliferative, migratory, and tumorigenic phenotype relative to unfused cancer cells, one that is the result of genetic and phenotypic reprogramming and provides a basic mechanism for tumor–immune cell fusions to participate in cancer progression and metastasis, with a corresponding potential utility as a biomarker.

4.2. Tumor–Immune Hybrids in Circulation

Tumor–immune hybrids disseminate from the primary tumor into peripheral blood where they are termed circulating hybrid cells (CHCs). These cells were first identified in a murine model of tumorigenesis, leveraging the co-expression of tumor and macrophage proteins [29]. RFP-labeled B16F10 melanoma cells, subdermally injected in Actin-GFP mice, facilitated the detection of RFP+GFP+ CHCs in peripheral blood using flow cytometry and confirmed by FACS-sorting and downstream analyses [29]. Notably, CHCs comprised 90% of the disseminated tumor cells detected in peripheral blood. Unfused tumor cells (RFP+GFP), analogous to CTCs, made up the remaining minor population of circulating tumor-derived cells [29,33,104]. Importantly, CHCs are heterogeneous with respect to their immune and tumor antigens [29,33]. However, the vast majority of murine RFP+GFP+ CHCs expressed the pan-leukocyte antigen CD45; thus, CD45-expression can be used as a marker for hybrid cell identity in human cancer patients to detect CHCs [29]. Given their abundance and phenotypic similarities with invasive and migratory intratumoral fusion hybrids, CHCs have been implicated in the metastatic cascade, but may also serve an important function as a plentiful source of tumor-derived cells for analysis.
Detection of CHCs using CD45 or other immune marker expressions has been reported in a wide array of disease sites, including PDAC; HNSCC; uveal melanoma; gastric, breast, colon, rectal, lung, gastrointestinal stromal tumors; and glioblastoma [29,33,50,106,107,111,138,139,140,141,142,143,144]. The earliest report of human CHCs was in breast cancer patients in 2014, where CK+/CD45+circulating cells were associated with poor survival [139]. Subsequently, Toyoshima et al. compared the tumor initiation capacity of isolated EpCAM+/CD45+ and EpCAM+/CD45− circulating cells from patients with gastric cancer. The injection of these fractions into immunodeficient mice revealed the enhanced tumorigenicity of the CD45+ population compared to the CD45− population: greater numbers of mice injected with EpCAM+/CD45+ cells developed tumors [138]. Similarly, from melanoma patients, Clawson et al. successfully cultured peripheral blood cells that co-expressed epithelial (CK, EpCAM), melanocyte (Melan-A, ALCAM), and macrophage (CD204, CD206, CD163) proteins, and demonstrated their downstream tumorigenic capacity when injected into immunodeficient mice [106]. Critically, these cells were identified in the primary tumors of melanoma patients, to support the primary tumor origin of CHCs.
The link between tumor and circulating hybrids is perhaps best demonstrated by the identification of the Y chromosome in CHCs (CK+/CD45+ and tumor-specific MUC4) in female recipients of sex-mismatched BMT who subsequently developed cancers [29]. Dietz et al. further demonstrated primary tumor and CHC relationships, as evidenced by the identification of Kirsten rat sarcoma virus (KRAS) mutation in a subset of CHCs isolated from the blood of a patient with PDAC [33]. They went on to present conserved protein expression patterns between tumor biopsy and disseminated CHCs from breast cancer patients undergoing therapy [33]. Importantly, CHCs have also been shown to harbor tumor copy number alterations [145]. Together, these data highlight CHC detectability, specificity to the tumor of origin, and conserved ubiquity across myriad cancer types, indicating their considerable potential as a circulating tumor-derived biomarker with the potential to non-invasively inform tumor biology.

4.3. CHCs as a Biomarker in Human Malignancy

Tumor heterogeneity evolves with time and in response to therapeutic treatment; thus, the extent to which phenotypic heterogeneity of CHCs reflect the evolving tumor biology is of great interest. Recently, Dietz and colleagues profiled this heterogeneity within tissue biopsies using cyclic immunofluorescence (cyCIF) via antibodies specific to stromal, immune, epithelial, and vascular compartments of the tumor [33]. In two patients with breast cancer, phenotypic changes within neoplastic cells that occurred during systemic treatment were characterized relative to a pre-treatment biopsy. The post-therapy biopsy demonstrated changes in proliferative, epithelial, hormonal, and stem marker-expressing cells in response to treatment. Leveraging cyCIF technology, they demonstrated that phenotypes observed in the primary tumor were reflected in the disseminated CHCs, indicating that tumor hybrids and CHCs share heterogeneous phenotypes [33]. Given the alignment of protein expression in CHCs with the primary tumor, utilizing CHCs to characterize the disease phenotype and surveil disease progression during treatment may be on the horizon. Serial blood draws may reveal phenotypic changes in CHCs, such as the maintenance of stem features that relate to the evolving tumor environment [33]. Further, this liquid biopsy approach could identify treatment-resistant populations within the tumor allowing for better directed, cell-specific treatment. Along with the single-cell analyses of CHCs isolated from tumors, the heterogeneity of CHCs isolated from peripheral blood may suggest the clinical relevance of targetable antigens and warrants further investigation.
While the term CHC is novel, atypical circulating cells with macrophage/monocyte-like characteristics in patients with cancer have been widely reported, supporting the potential use of this population as a biomarker [50,138,139,140,141,142,146,147,148,149,150]. Indeed, initial investigations of CHCs highlight potential through their correlation with disease stage, survival, and response to treatment. CHC numbers in untreated patients with PDAC correlate with disease stage and survival, and with metastasis in lung cancer [29,111,151]. Manjunath et al. corroborated these findings in NSCLC patients, finding that the co-positive “tumor-macrophage fusion cell” population correlated with the tumor stage. Further, they demonstrated that the number of larger, so-called “giant” CHCs independently predicted survival [111]. Additionally, CHC enumeration showed promise in the pre-operative setting for oral cavity HNSCC by predicting the presence of both clinically overt and occult nodal metastases [105]. Strikingly, CHC levels following neoadjuvant therapy for either rectal or esophageal adenocarcinoma adequately discriminated a pathologic complete response from an incomplete response and were associated with the recurrence risk in esophageal adenocarcinoma [104]. Two of these patients with rectal cancer were serially monitored during neoadjuvant therapy, with the CHC number decreasing in response to therapy and increasing before the clinical evidence of disease progression. Collectively, these studies show considerable promise for CHCs as a biomarker of disease status, treatment response, and prognosis.

5. Discussion

A cellular-level analysis provides genomic, epigenetic, and transcriptomic data of the tumor’s biology and the extent of heterogeneity therein. This information is critical to the diagnosis, treatment, and management of cancer patients. While procurement of the tumor tissue through invasive biopsy or surgery is currently the gold standard, non-invasive approaches such as monitoring atypical circulating tumor-associated cells provide an exciting area of ongoing research and possibilities to guide decision-making. Circulating cells in cancer can be leveraged in a multitude of ways, as they can yield DNA, RNA, protein, and vesicles for use in clinical assays, including those of cell-free DNA (cfDNA) if intentionally lysed [152]. Unlike cfDNA, however, monitoring intact circulating cells has the potential advantage of monitoring tumor heterogeneity and its evolution in real time, through an analysis of phenotypic subpopulations of disseminated cells. While a recent longitudinal study of circulating tumor DNA (ctDNA) in patients with liver-metastatic CRC demonstrated that changes in levels during systemic therapy were highly prognostic, by itself this provides little actionable information as to the underlying resistant disease mechanisms [153]. In contrast, monitoring the evolution of circulating cellular subpopulations may provide a readout of response/resistance to treatment, such as the proportion of circulating cancer-derived cells in breast cancer that express or contain the estrogen receptor (ER) or overexpress human epidermal growth factor-receptor 2 (HER2) in breast cancer, both of which are therapeutic targets. Similarly, monitoring the population of triple negative circulating cells in a patient with ER+ or HER2+ breast cancer in targeted therapy may allow early identification of the emerging resistant disease. Additionally, for CHCs it is yet to be determined whether they are direct effectors of metastatic risk; however, longitudinal monitoring of CHCs or other circulating effector cell populations may have clinical utility in predicting the metastatic risk at diagnosis and after curative-intent procedures or therapeutics [104,105].
Disseminated neoplastic cells in peripheral blood have complementary attributes that can inform on tumor biology. While CTCs are the most thoroughly studied circulating cells in cancer, it is acknowledged that their use is limited by their exceedingly low numbers. This has hampered their robust characterization, as well as the gap between their identities for clinical use versus their evolving phenotypes in research. Further prospective studies to date have not shown their utility in guiding treatment decision-making. In contrast, circulating cell populations expressing immune proteins such as CHCs and CAMLs are detected in higher numbers [29,33,104], and demonstrate exciting promise for early detection, diagnosis, and surveillance of a wide range of cancers. One limitation is that these entities have not yet been studied prospectively. CAMLs are a direct result of anti-tumor immune activity within the tumor, and they may be best suited to measuring cancer cells that are responding to treatment; however, no evidence exists demonstrating that CAMLs can identify treatment-resistant populations. Indeed, one would expect treatment-resistant disease to undergo phagocytosis less frequently than treatment-sensitive disease, and CAMLs are unlikely to proportionally reflect the heterogeneity of the tumor. In contrast, cell fusion results in heterogeneous cell fusion hybrid progeny, even from monoclonal parental populations. This may allow the monitoring of tumor–immune hybrids and CHCs to detect sufficient phenotypic variability that aligns with primary or metastatic tumor heterogeneity. CHCs appear to adopt a range of tumor phenotypes, are not dependent on tumor cell death for their formation, and may more proportionally reflect tumor heterogeneity: all distinguishing features from CAMLs. To date, however, there have been few publications investigating both of these populations compared to the immense volume of CTC-centric research spanning the last several decades, with even fewer publications evaluating their biology.
A mechanistic and prospective study of these intriguing, newly described cell populations is required to determine how they may be harnessed as clinically useful biomarkers. Not only are CHCs and CAMLs generally more plentiful than CTCs [29,33,104], allowing higher signal-to-noise ratios when comparing diseased versus healthy states, but they also contain relevant tumor proteomic, transcriptomic, and genomic data. Additionally, combining an analysis of multiple circulating cellular biomarkers may have benefits compared to using single analytes for analyses. For example, a ratio of CAMLs to CHC/CTCs or their clinically-relevant subpopulations may reflect how successful the immune system is at controlling the tumor, with higher ratios favoring a tumor-killing state. Interventions to enhance immune surveillance or promote tumor cell death may influence such a ratio through reducing the number of disseminated tumor cells.

6. Conclusions

Circulating neoplastic-immune hybrid cells represent a novel subpopulation of circulating neoplastic cells derived from the primary tumors of cancer patients. Unlike CTCs, both CAMLs and CHCs are readily attainable across different disease types and stages, and thus are better suited to be utilized as cancer biomarkers. To date, both CAML and CHC levels have been demonstrated to correlate with survival and treatment outcomes, and treatment-related protein expression pattern changes in primary tumors have been shown to reflect in their CHC counterparts. Many questions exist in this exciting field as neoplastic-immune hybrid cells have extraordinary potential to transform the care and management of disease in cancer patients.

Author Contributions

Conceptualization, T.L.S. and M.H.W.; writing—original draft preparation, T.L.S., R.K.P., A.N.A., S.G.B., R.W. and N.R.G.; writing—review and editing, T.L.S., R.K.P. and M.H.W.; visualization, A.N.A.; supervision, M.H.W.; funding acquisition, M.H.W. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by the National Institutes of Health, National Cancer Institute, CA069533, CA118235, CA172334; the National Institutes of Health, National Center for Advancing Translational Science, TL1TR002371.

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. Sung, H.; Ferlay, J.; Siegel, R.L.; Laversanne, M.; Soerjomataram, I.; Jemal, A.; Bray, F. Global Cancer Statistics 2020: GLOBOCAN Estimates of Incidence and Mortality Worldwide for 36 Cancers in 185 Countries. CA Cancer J. Clin. 2021, 71, 209–249. [Google Scholar] [CrossRef] [PubMed]
  2. Lieberman, D.A.; Weiss, D.G.; Bond, J.H.; Ahnen, D.J.; Garewal, H.; Chejfec, G. Use of colonoscopy to screen asymptomatic adults for colorectal cancer. Veterans Affairs Cooperative Study Group 380. N. Engl. J. Med. 2000, 343, 162–168. [Google Scholar] [CrossRef] [PubMed]
  3. Qumseya, B.; Sultan, S.; Bain, P.; Jamil, L.; Jacobson, B.; Anandasabapathy, S.; Agrawal, D.; Buxbaum, J.L.; Fishman, D.S.; Gurudu, S.R.; et al. ASGE guideline on screening and surveillance of Barrett’s esophagus. Gastrointest. Endosc. 2019, 90, 335–359. [Google Scholar] [CrossRef] [Green Version]
  4. Zhang, M.; Qin, X.; Xu, W.; Wang, Y.; Song, Y.; Garg, S.; Luan, Y. Engineering of a dual-modal phototherapeutic nanoplatform for single NIR laser-triggered tumor therapy. J. Colloid Interface Sci. 2021, 594, 493–501. [Google Scholar] [CrossRef] [PubMed]
  5. O’Connor, J.P.; Aboagye, E.O.; Adams, J.E.; Aerts, H.J.; Barrington, S.F.; Beer, A.J.; Boellaard, R.; Bohndiek, S.E.; Brady, M.; Brown, G.; et al. Imaging biomarker roadmap for cancer studies. Nat. Rev. Clin. Oncol. 2017, 14, 169–186. [Google Scholar] [CrossRef] [PubMed]
  6. Rosenkrantz, A.B.; Duszak, R., Jr.; Babb, J.S.; Glover, M.; Kang, S.K. Discrepancy Rates and Clinical Impact of Imaging Secondary Interpretations: A Systematic Review and Meta-Analysis. J. Am. Coll. Radiol. 2018, 15, 1222–1231. [Google Scholar] [CrossRef]
  7. Schlemmer, H.P.; Bittencourt, L.K.; D’Anastasi, M.; Domingues, R.; Khong, P.L.; Lockhat, Z.; Muellner, A.; Reiser, M.F.; Schilsky, R.L.; Hricak, H. Global Challenges for Cancer Imaging. J. Glob. Oncol. 2018, 4, 1–10. [Google Scholar] [CrossRef] [Green Version]
  8. Ariga, R.; Bloom, K.; Reddy, V.B.; Kluskens, L.; Francescatti, D.; Dowlat, K.; Siziopikou, P.; Gattuso, P. Fine-needle aspiration of clinically suspicious palpable breast masses with histopathologic correlation. Am. J. Surg. 2002, 184, 410–413. [Google Scholar] [CrossRef]
  9. Strimbu, K.; Tavel, J.A. What are biomarkers? Curr. Opin. HIV AIDS 2010, 5, 463–466. [Google Scholar] [CrossRef]
  10. Cooperman, A.M.; Iskandar, M.E.; Wayne, M.G.; Steele, J.G. Prevention and Early Detection of Pancreatic Cancer. Surg. Clin. N. Am. 2018, 98, 1–12. [Google Scholar] [CrossRef]
  11. Locker, G.Y.; Hamilton, S.; Harris, J.; Jessup, J.M.; Kemeny, N.; Macdonald, J.S.; Somerfield, M.R.; Hayes, D.F.; Bast, R.C., Jr. ASCO 2006 update of recommendations for the use of tumor markers in gastrointestinal cancer. J. Clin. Oncol. Off. J. Am. Soc. Clin. Oncol. 2006, 24, 5313–5327. [Google Scholar] [CrossRef] [PubMed]
  12. Brabletz, T. EMT and MET in metastasis: Where are the cancer stem cells? Cancer Cell 2012, 22, 699–701. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  13. Dalerba, P.; Cho, R.W.; Clarke, M.F. Cancer stem cells: Models and concepts. Annu. Rev. Med. 2007, 58, 267–284. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  14. Leon, S.A.; Shapiro, B.; Sklaroff, D.M.; Yaros, M.J. Free DNA in the serum of cancer patients and the effect of therapy. Cancer Res. 1977, 37, 646–650. [Google Scholar]
  15. Stroun, M.; Anker, P.; Maurice, P.; Lyautey, J.; Lederrey, C.; Beljanski, M. Neoplastic characteristics of the DNA found in the plasma of cancer patients. Oncology 1989, 46, 318–322. [Google Scholar] [CrossRef]
  16. de Kok, J.B.; van Solinge, W.W.; Ruers, T.J.; Roelofs, R.W.; van Muijen, G.N.; Willems, J.L.; Swinkels, D.W. Detection of tumour DNA in serum of colorectal cancer patients. Scand. J. Clin. Lab. Investig. 1997, 57, 601–604. [Google Scholar] [CrossRef]
  17. Cohen, S.J.; Punt, C.J.; Iannotti, N.; Saidman, B.H.; Sabbath, K.D.; Gabrail, N.Y.; Picus, J.; Morse, M.; Mitchell, E.; Miller, M.C.; et al. Relationship of circulating tumor cells to tumor response, progression-free survival, and overall survival in patients with metastatic colorectal cancer. J. Clin. Oncol. Off. J. Am. Soc. Clin. Oncol. 2008, 26, 3213–3221. [Google Scholar] [CrossRef]
  18. Cristofanilli, M.; Budd, G.T.; Ellis, M.J.; Stopeck, A.; Matera, J.; Miller, M.C.; Reuben, J.M.; Doyle, G.V.; Allard, W.J.; Terstappen, L.W.; et al. Circulating tumor cells, disease progression, and survival in metastatic breast cancer. N. Engl. J. Med. 2004, 351, 781–791. [Google Scholar] [CrossRef] [Green Version]
  19. Krebs, M.G.; Sloane, R.; Priest, L.; Lancashire, L.; Hou, J.M.; Greystoke, A.; Ward, T.H.; Ferraldeschi, R.; Hughes, A.; Clack, G.; et al. Evaluation and prognostic significance of circulating tumor cells in patients with non-small-cell lung cancer. J. Clin. Oncol. Off. J. Am. Soc. Clin. Oncol. 2011, 29, 1556–1563. [Google Scholar] [CrossRef]
  20. Torphy, R.J.; Tignanelli, C.J.; Kamande, J.W.; Moffitt, R.A.; Herrera Loeza, S.G.; Soper, S.A.; Yeh, J.J. Circulating tumor cells as a biomarker of response to treatment in patient-derived xenograft mouse models of pancreatic adenocarcinoma. PLoS ONE 2014, 9, e89474. [Google Scholar] [CrossRef]
  21. Court, C.M.; Ankeny, J.S.; Sho, S.; Winograd, P.; Hou, S.; Song, M.; Wainberg, Z.A.; Girgis, M.D.; Graeber, T.G.; Agopian, V.G.; et al. Circulating Tumor Cells Predict Occult Metastatic Disease and Prognosis in Pancreatic Cancer. Ann. Surg. Oncol. 2018, 25, 1000–1008. [Google Scholar] [CrossRef] [PubMed]
  22. Miller, M.C.; Doyle, G.V.; Terstappen, L.W. Significance of Circulating Tumor Cells Detected by the CellSearch System in Patients with Metastatic Breast Colorectal and Prostate Cancer. J. Oncol. 2010, 2010, 617421. [Google Scholar] [CrossRef] [PubMed]
  23. van Dalum, G.; Stam, G.J.; Scholten, L.F.; Mastboom, W.J.; Vermes, I.; Tibbe, A.G.; De Groot, M.R.; Terstappen, L.W. Importance of circulating tumor cells in newly diagnosed colorectal cancer. Int. J. Oncol. 2015, 46, 1361–1368. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  24. van Dalum, G.; van der Stam, G.J.; Tibbe, A.G.; Franken, B.; Mastboom, W.J.; Vermes, I.; de Groot, M.R.; Terstappen, L.W. Circulating tumor cells before and during follow-up after breast cancer surgery. Int. J. Oncol. 2015, 46, 407–413. [Google Scholar] [CrossRef] [Green Version]
  25. Boral, D.; Vishnoi, M.; Liu, H.N.; Yin, W.; Sprouse, M.L.; Scamardo, A.; Hong, D.S.; Tan, T.Z.; Thiery, J.P.; Chang, J.C.; et al. Molecular characterization of breast cancer CTCs associated with brain metastasis. Nat. Commun. 2017, 8, 196. [Google Scholar] [CrossRef] [Green Version]
  26. Giuliano, M.; Giordano, A.; Jackson, S.; De Giorgi, U.; Mego, M.; Cohen, E.N.; Gao, H.; Anfossi, S.; Handy, B.C.; Ueno, N.T.; et al. Circulating tumor cells as early predictors of metastatic spread in breast cancer patients with limited metastatic dissemination. Breast Cancer Res. BCR 2014, 16, 440. [Google Scholar] [CrossRef] [Green Version]
  27. Lucci, A.; Hall, C.S.; Lodhi, A.K.; Bhattacharyya, A.; Anderson, A.E.; Xiao, L.; Bedrosian, I.; Kuerer, H.M.; Krishnamurthy, S. Circulating tumour cells in non-metastatic breast cancer: A prospective study. Lancet Oncol. 2012, 13, 688–695. [Google Scholar] [CrossRef]
  28. Bidard, F.C.; Michiels, S.; Riethdorf, S.; Mueller, V.; Esserman, L.J.; Lucci, A.; Naume, B.; Horiguchi, J.; Gisbert-Criado, R.; Sleijfer, S.; et al. Circulating Tumor Cells in Breast Cancer Patients Treated by Neoadjuvant Chemotherapy: A Meta-analysis. J. Natl. Cancer Inst. 2018, 110, 560–567. [Google Scholar] [CrossRef]
  29. Gast, C.E.; Silk, A.D.; Zarour, L.; Riegler, L.; Burkhart, J.G.; Gustafson, K.T.; Parappilly, M.S.; Roh-Johnson, M.; Goodman, J.R.; Olson, B.; et al. Cell fusion potentiates tumor heterogeneity and reveals circulating hybrid cells that correlate with stage and survival. Sci. Adv. 2018, 4, eaat7828. [Google Scholar] [CrossRef] [Green Version]
  30. Ashworth, T. A case of cancer in which cells similar to those in the tumors were seen in the blood after death. Austrailian Med. J. 1869, 1869, 146–147. [Google Scholar]
  31. Adams, D.L.; Martin, S.S.; Alpaugh, R.K.; Charpentier, M.; Tsai, S.; Bergan, R.C.; Ogden, I.M.; Catalona, W.; Chumsri, S.; Tang, C.M.; et al. Circulating giant macrophages as a potential biomarker of solid tumors. Proc. Natl. Acad. Sci. USA 2014, 111, 3514–3519. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  32. Sutton, T.L.; Walker, B.S.; Wong, M.H. Circulating Hybrid Cells Join the Fray of Circulating Cellular Biomarkers. Cell Mol. Gastroenterol. Hepatol. 2019, 8, 595–607. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  33. Dietz, M.S.; Sutton, T.L.; Walker, B.S.; Gast, C.E.; Zarour, L.; Sengupta, S.K.; Swain, J.R.; Eng, J.; Parappilly, M.; Limbach, K.; et al. Relevance of circulating hybrid cells as a non-invasive biomarker for myriad solid tumors. Sci. Rep. 2021, 11, 13630. [Google Scholar] [CrossRef]
  34. Scher, H.I.; Jia, X.; de Bono, J.S.; Fleisher, M.; Pienta, K.J.; Raghavan, D.; Heller, G. Circulating tumour cells as prognostic markers in progressive, castration-resistant prostate cancer: A reanalysis of IMMC38 trial data. Lancet Oncol. 2009, 10, 233–239. [Google Scholar] [CrossRef] [Green Version]
  35. Rosenberg, R.; Gertler, R.; Friederichs, J.; Fuehrer, K.; Dahm, M.; Phelps, R.; Thorban, S.; Nekarda, H.; Siewert, J.R. Comparison of two density gradient centrifugation systems for the enrichment of disseminated tumor cells in blood. Cytometry 2002, 49, 150–158. [Google Scholar] [CrossRef] [PubMed]
  36. Campton, D.E.; Ramirez, A.B.; Nordberg, J.J.; Drovetto, N.; Clein, A.C.; Varshavskaya, P.; Friemel, B.H.; Quarre, S.; Breman, A.; Dorschner, M.; et al. High-recovery visual identification and single-cell retrieval of circulating tumor cells for genomic analysis using a dual-technology platform integrated with automated immunofluorescence staining. BMC Cancer 2015, 15, 360. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  37. Elvington, E.S.; Salmanzadeh, A.; Stremler, M.A.; Davalos, R.V. Label-free isolation and enrichment of cells through contactless dielectrophoresis. J. Vis. Exp. JoVE 2013, 79, e50634. [Google Scholar] [CrossRef] [Green Version]
  38. Fernandez, S.V.; Bingham, C.; Fittipaldi, P.; Austin, L.; Palazzo, J.; Palmer, G.; Alpaugh, K.; Cristofanilli, M. TP53 mutations detected in circulating tumor cells present in the blood of metastatic triple negative breast cancer patients. Breast Cancer Res. BCR 2014, 16, 445. [Google Scholar] [CrossRef] [Green Version]
  39. Gupta, V.; Jafferji, I.; Garza, M.; Melnikova, V.O.; Hasegawa, D.K.; Pethig, R.; Davis, D.W. ApoStream(), a new dielectrophoretic device for antibody independent isolation and recovery of viable cancer cells from blood. Biomicrofluidics 2012, 6, 24133. [Google Scholar] [CrossRef] [Green Version]
  40. Freidin, M.B.; Tay, A.; Freydina, D.V.; Chudasama, D.; Nicholson, A.G.; Rice, A.; Anikin, V.; Lim, E. An assessment of diagnostic performance of a filter-based antibody-independent peripheral blood circulating tumour cell capture paired with cytomorphologic criteria for the diagnosis of cancer. Lung Cancer 2014, 85, 182–185. [Google Scholar] [CrossRef]
  41. Farace, F.; Massard, C.; Vimond, N.; Drusch, F.; Jacques, N.; Billiot, F.; Laplanche, A.; Chauchereau, A.; Lacroix, L.; Planchard, D.; et al. A direct comparison of CellSearch and ISET for circulating tumour-cell detection in patients with metastatic carcinomas. Br. J. Cancer 2011, 105, 847–853. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  42. Adams, D.L.; Stefansson, S.; Haudenschild, C.; Martin, S.S.; Charpentier, M.; Chumsri, S.; Cristofanilli, M.; Tang, C.M.; Alpaugh, R.K. Cytometric characterization of circulating tumor cells captured by microfiltration and their correlation to the CellSearch((R)) CTC test. Cytom. Part A J. Int. Soc. Anal. Cytol. 2015, 87, 137–144. [Google Scholar] [CrossRef] [Green Version]
  43. Raimondi, C.; Nicolazzo, C.; Gradilone, A.; Giannini, G.; De Falco, E.; Chimenti, I.; Varriale, E.; Hauch, S.; Plappert, L.; Cortesi, E.; et al. Circulating tumor cells: Exploring intratumor heterogeneity of colorectal cancer. Cancer Biol. Ther. 2014, 15, 496–503. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  44. Talasaz, A.H.; Powell, A.A.; Huber, D.E.; Berbee, J.G.; Roh, K.H.; Yu, W.; Xiao, W.; Davis, M.M.; Pease, R.F.; Mindrinos, M.N.; et al. Isolating highly enriched populations of circulating epithelial cells and other rare cells from blood using a magnetic sweeper device. Proc. Natl. Acad. Sci. USA 2009, 106, 3970–3975. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  45. Winer-Jones, J.P.; Vahidi, B.; Arquilevich, N.; Fang, C.; Ferguson, S.; Harkins, D.; Hill, C.; Klem, E.; Pagano, P.C.; Peasley, C.; et al. Circulating tumor cells: Clinically relevant molecular access based on a novel CTC flow cell. PLoS ONE 2014, 9, e86717. [Google Scholar] [CrossRef]
  46. Nagrath, S.; Sequist, L.V.; Maheswaran, S.; Bell, D.W.; Irimia, D.; Ulkus, L.; Smith, M.R.; Kwak, E.L.; Digumarthy, S.; Muzikansky, A.; et al. Isolation of rare circulating tumour cells in cancer patients by microchip technology. Nature 2007, 450, 1235–1239. [Google Scholar] [CrossRef] [Green Version]
  47. Brychta, N.; Drosch, M.; Driemel, C.; Fischer, J.C.; Neves, R.P.; Esposito, I.; Knoefel, W.; Mohlendick, B.; Hille, C.; Stresemann, A.; et al. Isolation of circulating tumor cells from pancreatic cancer by automated filtration. Oncotarget 2017, 8, 86143–86156. [Google Scholar] [CrossRef] [Green Version]
  48. Chen, F.; Wang, S.; Fang, Y.; Zheng, L.; Zhi, X.; Cheng, B.; Chen, Y.; Zhang, C.; Shi, D.; Song, H.; et al. Feasibility of a novel one-stop ISET device to capture CTCs and its clinical application. Oncotarget 2017, 8, 3029–3041. [Google Scholar] [CrossRef] [Green Version]
  49. Millner, L.M.; Linder, M.W.; Valdes, R., Jr. Circulating tumor cells: A review of present methods and the need to identify heterogeneous phenotypes. Ann. Clin. Lab. Sci. 2013, 43, 295–304. [Google Scholar]
  50. Zhang, Y.; Wang, F.; Ning, N.; Chen, Q.; Yang, Z.; Guo, Y.; Xu, D.; Zhang, D.; Zhan, T.; Cui, W. Patterns of circulating tumor cells identified by CEP8, CK and CD45 in pancreatic cancer. Int. J. Cancer 2015, 136, 1228–1233. [Google Scholar] [CrossRef]
  51. Poruk, K.E.; Valero, V.; Saunders, T.; Blackford, A.L.; Griffin, J.F.; Poling, J.; Hruban, R.H.; Anders, R.A.; Herman, J.; Zheng, L.; et al. Circulating Tumor Cell Phenotype Predicts Recurrence and Survival in Pancreatic Adenocarcinoma. Ann. Surg. 2016, 264, 1073–1081. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  52. Poruk, K.E.; Blackford, A.L.; Weiss, M.J.; Cameron, J.L.; He, J.; Goggins, M.; Rasheed, Z.A.; Wolfgang, C.L.; Wood, L.D. Circulating Tumor Cells Expressing Markers of Tumor-Initiating Cells Predict Poor Survival and Cancer Recurrence in Patients with Pancreatic Ductal Adenocarcinoma. Clin. Cancer Res. An. Off. J. Am. Assoc. Cancer Res. 2017, 23, 2681–2690. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  53. Gemenetzis, G.; Groot, V.P.; Yu, J.; Ding, D.; Teinor, J.A.; Javed, A.A.; Wood, L.D.; Burkhart, R.A.; Cameron, J.L.; Makary, M.A.; et al. Circulating Tumor Cells Dynamics in Pancreatic Adenocarcinoma Correlate with Disease Status: Results of the Prospective CLUSTER Study. Ann. Surg. 2018, 268, 408–420. [Google Scholar] [CrossRef] [PubMed]
  54. Andree, K.C.; van Dalum, G.; Terstappen, L.W. Challenges in circulating tumor cell detection by the CellSearch system. Mol. Oncol. 2016, 10, 395–407. [Google Scholar] [CrossRef] [Green Version]
  55. Smerage, J.B.; Barlow, W.E.; Hortobagyi, G.N.; Winer, E.P.; Leyland-Jones, B.; Srkalovic, G.; Tejwani, S.; Schott, A.F.; O’Rourke, M.A.; Lew, D.L.; et al. Circulating tumor cells and response to chemotherapy in metastatic breast cancer: SWOG S0500. J. Clin. Oncol. Off. J. Am. Soc. Clin. Oncol. 2014, 32, 3483–3489. [Google Scholar] [CrossRef]
  56. Cabel, L.; Berger, F.; Cottu, P.; Loirat, D.; Rampanou, A.; Brain, E.; Cyrille, S.; Bourgeois, H.; Kiavue, N.; Deluche, E.; et al. Clinical utility of circulating tumour cell-based monitoring of late-line chemotherapy for metastatic breast cancer: The randomised CirCe01 trial. Br. J. Cancer 2021, 124, 1207–1213. [Google Scholar] [CrossRef]
  57. Bidard, F.C.; Jacot, W.; Kiavue, N.; Dureau, S.; Kadi, A.; Brain, E.; Bachelot, T.; Bourgeois, H.; Gonçalves, A.; Ladoire, S.; et al. Efficacy of Circulating Tumor Cell Count-Driven vs. Clinician-Driven First-line Therapy Choice in Hormone Receptor-Positive, ERBB2-Negative Metastatic Breast Cancer: The STIC CTC Randomized Clinical Trial. JAMA Oncol. 2021, 7, 34–41. [Google Scholar] [CrossRef]
  58. Xu, Y.; Qin, T.; Li, J.; Wang, X.; Gao, C.; Xu, C.; Hao, J.; Liu, J.; Gao, S.; Ren, H. Detection of Circulating Tumor Cells Using Negative Enrichment Immunofluorescence and an In Situ Hybridization System in Pancreatic Cancer. Int. J. Mol. Sci. 2017, 18, 622. [Google Scholar] [CrossRef] [Green Version]
  59. Cai, J.; Huang, L.; Huang, J.; Kang, L.; Lin, H.; Huang, P.; Zhu, P.; Wang, J.; Dong, J.; Wang, L.; et al. Associations between the cyclooxygenase-2 expression in circulating tumor cells and the clinicopathological features of patients with colorectal cancer. J. Cell. Biochem. 2019, 120, 4935–4941. [Google Scholar] [CrossRef]
  60. Messaritakis, I.; Sfakianaki, M.; Papadaki, C.; Koulouridi, A.; Vardakis, N.; Koinis, F.; Hatzidaki, D.; Georgoulia, N.; Kladi, A.; Kotsakis, A.; et al. Prognostic significance of CEACAM5mRNA-positive circulating tumor cells in patients with metastatic colorectal cancer. Cancer Chemother. Pharmacol. 2018, 82, 767–775. [Google Scholar] [CrossRef]
  61. Wang, W.; Wan, L.; Wu, S.; Yang, J.; Zhou, Y.; Liu, F.; Wu, Z.; Cheng, Y. Mesenchymal marker and LGR5 expression levels in circulating tumor cells correlate with colorectal cancer prognosis. Cell. Oncol. 2018, 41, 495–504. [Google Scholar] [CrossRef] [PubMed]
  62. Zhao, X.H.; Wang, Z.R.; Chen, C.L.; Di, L.; Bi, Z.F.; Li, Z.H.; Liu, Y.M. Molecular detection of epithelial-mesenchymal transition markers in circulating tumor cells from pancreatic cancer patients: Potential role in clinical practice. World J. Gastroenterol. 2019, 25, 138–150. [Google Scholar] [CrossRef] [PubMed]
  63. Zhao, R.; Cai, Z.; Li, S.; Cheng, Y.; Gao, H.; Liu, F.; Wu, S.; Liu, S.; Dong, Y.; Zheng, L.; et al. Expression and clinical relevance of epithelial and mesenchymal markers in circulating tumor cells from colorectal cancer. Oncotarget 2017, 8, 9293–9302. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  64. Franklin, R.A.; Liao, W.; Sarkar, A.; Kim, M.V.; Bivona, M.R.; Liu, K.; Pamer, E.G.; Li, M.O. The cellular and molecular origin of tumor-associated macrophages. Science 2014, 344, 921–925. [Google Scholar] [CrossRef] [Green Version]
  65. Henze, A.T.; Mazzone, M. The impact of hypoxia on tumor-associated macrophages. J. Clin. Investig. 2016, 126, 3672–3679. [Google Scholar] [CrossRef]
  66. Morita, Y.; Zhang, R.; Leslie, M.; Adhikari, S.; Hasan, N.; Chervoneva, I.; Rui, H.; Tanaka, T. Pathologic evaluation of tumor-associated macrophage density and vessel inflammation in invasive breast carcinomas. Oncol. Lett. 2017, 14, 2111–2118. [Google Scholar] [CrossRef] [Green Version]
  67. Kim, J.; Bae, J.S. Tumor-Associated Macrophages and Neutrophils in Tumor Microenvironment. Mediat. Inflamm. 2016, 2016, 6058147. [Google Scholar] [CrossRef] [Green Version]
  68. Malyshev, I.; Malyshev, Y. Current Concept and Update of the Macrophage Plasticity Concept: Intracellular Mechanisms of Reprogramming and M3 Macrophage “Switch” Phenotype. BioMed Res. Int. 2015, 2015, 341308. [Google Scholar] [CrossRef] [Green Version]
  69. Hirayama, D.; Iida, T.; Nakase, H. The Phagocytic Function of Macrophage-Enforcing Innate Immunity and Tissue Homeostasis. Int. J. Mol. Sci. 2017, 19, 92. [Google Scholar] [CrossRef] [Green Version]
  70. Coussens, L.M.; Werb, Z. Inflammation and cancer. Nature 2002, 420, 860–867. [Google Scholar] [CrossRef]
  71. Chen, D.; Zhang, X.; Li, Z.; Zhu, B. Metabolic regulatory crosstalk between tumor microenvironment and tumor-associated macrophages. Theranostics 2021, 11, 1016–1030. [Google Scholar] [CrossRef] [PubMed]
  72. Cheng, N.; Bai, X.; Shu, Y.; Ahmad, O.; Shen, P. Targeting tumor-associated macrophages as an antitumor strategy. Biochem. Pharm. 2021, 183, 114354. [Google Scholar] [CrossRef] [PubMed]
  73. Mosser, D.M.; Edwards, J.P. Exploring the full spectrum of macrophage activation. Nat. Rev. Immunol. 2008, 8, 958–969. [Google Scholar] [CrossRef]
  74. Chanmee, T.; Ontong, P.; Konno, K.; Itano, N. Tumor-associated macrophages as major players in the tumor microenvironment. Cancers 2014, 6, 1670–1690. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  75. Lavin, Y.; Mortha, A.; Rahman, A.; Merad, M. Regulation of macrophage development and function in peripheral tissues. Nat. Rev. Immunol. 2015, 15, 731–744. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  76. Martinez, F.O.; Gordon, S. The M1 and M2 paradigm of macrophage activation: Time for reassessment. F1000Prime Rep. 2014, 6, 13. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  77. Murray, P.J.; Allen, J.E.; Biswas, S.K.; Fisher, E.A.; Gilroy, D.W.; Goerdt, S.; Gordon, S.; Hamilton, J.A.; Ivashkiv, L.B.; Lawrence, T.; et al. Macrophage activation and polarization: Nomenclature and experimental guidelines. Immunity 2014, 41, 14–20. [Google Scholar] [CrossRef] [Green Version]
  78. Zhou, J.; Tang, Z.; Gao, S.; Li, C.; Feng, Y.; Zhou, X. Tumor-Associated Macrophages: Recent Insights and Therapies. Front. Oncol. 2020, 10, 188. [Google Scholar] [CrossRef]
  79. Italiani, P.; Boraschi, D. From Monocytes to M1/M2 Macrophages: Phenotypical vs. Functional Differentiation. Front. Immunol. 2014, 5, 514. [Google Scholar] [CrossRef] [Green Version]
  80. Unanue, E.R. Antigen-presenting function of the macrophage. Annu. Rev. Immunol. 1984, 2, 395–428. [Google Scholar] [CrossRef]
  81. Vignery, A. Osteoclasts and giant cells: Macrophage-macrophage fusion mechanism. Int. J. Exp. Pathol. 2000, 81, 291–304. [Google Scholar] [CrossRef] [PubMed]
  82. Tang, C.M.; Zhu, P.; Li, S.; Makarova, O.V.; Amstutz, P.T.; Adams, D.L. Blood-based biopsies-clinical utility beyond circulating tumor cells. Cytom. Part A J. Int. Soc. Anal. Cytol. 2018, 93, 1246–1250. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  83. Mu, Z.; Benali-Furet, N.; Uzan, G.; Znaty, A.; Ye, Z.; Paolillo, C.; Wang, C.; Austin, L.; Rossi, G.; Fortina, P.; et al. Detection and Characterization of Circulating Tumor Associated Cells in Metastatic Breast Cancer. Int. J. Mol. Sci. 2016, 17, 1665. [Google Scholar] [CrossRef] [PubMed]
  84. Adams, D.L.; Adams, D.K.; Alpaugh, R.K.; Cristofanilli, M.; Martin, S.S.; Chumsri, S.; Tang, C.M.; Marks, J.R. Circulating Cancer-Associated Macrophage-Like Cells Differentiate Malignant Breast Cancer and Benign Breast Conditions. Cancer Epidemiol. Biomark. Prev. 2016, 25, 1037–1042. [Google Scholar] [CrossRef] [Green Version]
  85. Mu, Z.; Wang, C.; Ye, Z.; Rossi, G.; Sun, C.; Li, L.; Zhu, Z.; Yang, H.; Cristofanilli, M. Prognostic values of cancer associated macrophage-like cells (CAML) enumeration in metastatic breast cancer. Breast Cancer Res. Treat. 2017, 165, 733–741. [Google Scholar] [CrossRef] [PubMed]
  86. Gironda, D.J.; Adams, D.L.; He, J.; Xu, T.; Gao, H.; Qiao, Y.; Komaki, R.; Reuben, J.M.; Liao, Z.; Blum-Murphy, M.; et al. Cancer associated macrophage-like cells and prognosis of esophageal cancer after chemoradiation therapy. J. Transl. Med. 2020, 18, 413. [Google Scholar] [CrossRef]
  87. Augustyn, A.; Adams, D.L.; He, J.; Qiao, Y.; Verma, V.; Liao, Z.; Tang, C.M.; Heymach, J.V.; Tsao, A.S.; Lin, S.H. Giant Circulating Cancer-Associated Macrophage-Like Cells Are Associated With Disease Recurrence and Survival in Non-Small-Cell Lung Cancer Treated With Chemoradiation and Atezolizumab. Clin. Lung Cancer 2021, 22, e451–e465. [Google Scholar] [CrossRef]
  88. Saman, S.; Stagno, M.J.; Warmann, S.W.; Malek, N.P.; Plentz, R.R.; Schmid, E. Biomarkers Apo10 and TKTL1: Epitope-detection in monocytes (EDIM) as a new diagnostic approach for cholangiocellular, pancreatic and colorectal carcinoma. Cancer Biomark. 2020, 27, 129–137. [Google Scholar] [CrossRef] [Green Version]
  89. Grimm, M.; Kraut, W.; Hoefert, S.; Krimmel, M.; Biegner, T.; Teriete, P.; Cetindis, M.; Polligkeit, J.; Kluba, S.; Munz, A.; et al. Evaluation of a biomarker based blood test for monitoring surgical resection of oral squamous cell carcinomas. Clin. Oral. Investig. 2016, 20, 329–338. [Google Scholar] [CrossRef]
  90. Aichel, O. Über Zellverschmelzung mit Qualitativ Abnormer Chromosomenverteilung als Ursache der Geschwulstbildung [About Cell Fusion with Qualitatively Abnormal Chromosome Distribution as Cause for Tumor Formation]; Wilhelm Engelmann: Leipzig, Germany, 1911. [Google Scholar]
  91. Singec, I.; Snyder, E.Y. Inflammation as a matchmaker: Revisiting cell fusion. Nat. Cell Biol. 2008, 10, 503–505. [Google Scholar] [CrossRef]
  92. Johansson, C.B.; Youssef, S.; Koleckar, K.; Holbrook, C.; Doyonnas, R.; Corbel, S.Y.; Steinman, L.; Rossi, F.M.; Blau, H.M. Extensive fusion of haematopoietic cells with Purkinje neurons in response to chronic inflammation. Nat. Cell Biol. 2008, 10, 575–583. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  93. Nygren, J.M.; Liuba, K.; Breitbach, M.; Stott, S.; Thoren, L.; Roell, W.; Geisen, C.; Sasse, P.; Kirik, D.; Bjorklund, A.; et al. Myeloid and lymphoid contribution to non-haematopoietic lineages through irradiation-induced heterotypic cell fusion. Nat. Cell Biol. 2008, 10, 584–592. [Google Scholar] [CrossRef] [PubMed]
  94. Rizvi, A.Z.; Swain, J.R.; Davies, P.S.; Bailey, A.S.; Decker, A.D.; Willenbring, H.; Grompe, M.; Fleming, W.H.; Wong, M.H. Bone marrow-derived cells fuse with normal and transformed intestinal stem cells. Proc. Natl. Acad. Sci. USA 2006, 103, 6321–6325. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  95. Powell, A.E.; Anderson, E.C.; Davies, P.S.; Silk, A.D.; Pelz, C.; Impey, S.; Wong, M.H. Fusion between Intestinal epithelial cells and macrophages in a cancer context results in nuclear reprogramming. Cancer Res. 2011, 71, 1497–1505. [Google Scholar] [CrossRef] [Green Version]
  96. Davies, P.S.; Powell, A.E.; Swain, J.R.; Wong, M.H. Inflammation and proliferation act together to mediate intestinal cell fusion. PLoS ONE 2009, 4, e6530. [Google Scholar] [CrossRef]
  97. Silk, A.D.; Gast, C.E.; Davies, P.S.; Fakhari, F.D.; Vanderbeek, G.E.; Mori, M.; Wong, M.H. Fusion between hematopoietic and epithelial cells in adult human intestine. PLoS ONE 2013, 8, e55572. [Google Scholar] [CrossRef] [Green Version]
  98. Duelli, D.; Lazebnik, Y. Cell fusion: A hidden enemy? Cancer Cell 2003, 3, 445–448. [Google Scholar] [CrossRef] [Green Version]
  99. Pawelek, J.M. Tumour-cell fusion as a source of myeloid traits in cancer. Lancet Oncol. 2005, 6, 988–993. [Google Scholar] [CrossRef]
  100. Pawelek, J.M. Tumour cell hybridization and metastasis revisited. Melanoma Res. 2000, 10, 507–514. [Google Scholar] [CrossRef]
  101. Pawelek, J.M.; Chakraborty, A.K. Fusion of tumour cells with bone marrow-derived cells: A unifying explanation for metastasis. Nat. Rev. Cancer 2008, 8, 377–386. [Google Scholar] [CrossRef]
  102. Pawelek, J.M.; Chakraborty, A.K. The cancer cell–Leukocyte fusion theory of metastasis. Adv. Cancer Res. 2008, 101, 397–444. [Google Scholar] [CrossRef] [PubMed]
  103. Ramakrishnan, M.; Mathur, S.R.; Mukhopadhyay, A. Fusion-derived epithelial cancer cells express hematopoietic markers and contribute to stem cell and migratory phenotype in ovarian carcinoma. Cancer Res. 2013, 73, 5360–5370. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  104. Walker, B.S.; Sutton, T.L.; Zarour, L.; Hunter, J.G.; Wood, S.G.; Tsikitis, V.L.; Herzig, D.O.; Lopez, C.D.; Chen, E.Y.; Mayo, S.C.; et al. Circulating Hybrid Cells: A Novel Liquid Biomarker of Treatment Response in Gastrointestinal Cancers. Ann. Surg. Oncol. 2021, 28, 8567–8578. [Google Scholar] [CrossRef] [PubMed]
  105. Henn, T.E.; Anderson, A.N.; Hollett, Y.R.; Sutton, T.L.; Walker, B.S.; Swain, J.R.; Sauer, D.A.; Clayburgh, D.R.; Wong, M.H. Circulating hybrid cells predict presence of occult nodal metastases in oral cavity carcinoma. Head Neck 2021, 43, 2193–2201. [Google Scholar] [CrossRef] [PubMed]
  106. Clawson, G.A.; Matters, G.L.; Xin, P.; Imamura-Kawasawa, Y.; Du, Z.; Thiboutot, D.M.; Helm, K.F.; Neves, R.I.; Abraham, T. Macrophage-tumor cell fusions from peripheral blood of melanoma patients. PLoS ONE 2015, 10, e0134320. [Google Scholar] [CrossRef] [Green Version]
  107. Clawson, G.A.; Matters, G.L.; Xin, P.; McGovern, C.; Wafula, E.; dePamphilis, C.; Meckley, M.; Wong, J.; Stewart, L.; D’Jamoos, C.; et al. “Stealth dissemination” of macrophage-tumor cell fusions cultured from blood of patients with pancreatic ductal adenocarcinoma. PLoS ONE 2017, 12, e0184451. [Google Scholar] [CrossRef] [Green Version]
  108. Cheng, K.S.; Pan, R.; Pan, H.; Li, B.; Meena, S.S.; Xing, H.; Ng, Y.J.; Qin, K.; Liao, X.; Kosgei, B.K.; et al. ALICE: A hybrid AI paradigm with enhanced connectivity and cybersecurity for a serendipitous encounter with circulating hybrid cells. Theranostics 2020, 10, 11026–11048. [Google Scholar] [CrossRef]
  109. Lazova, R.; Laberge, G.S.; Duvall, E.; Spoelstra, N.; Klump, V.; Sznol, M.; Cooper, D.; Spritz, R.A.; Chang, J.T.; Pawelek, J.M. A Melanoma Brain Metastasis with a Donor-Patient Hybrid Genome following Bone Marrow Transplantation: First Evidence for Fusion in Human Cancer. PLoS ONE 2013, 8, e66731. [Google Scholar] [CrossRef]
  110. LaBerge, G.S.; Duvall, E.; Grasmick, Z.; Haedicke, K.; Pawelek, J. A Melanoma Lymph Node Metastasis with a Donor-Patient Hybrid Genome following Bone Marrow Transplantation: A Second Case of Leucocyte-Tumor Cell Hybridization in Cancer Metastasis. PLoS ONE 2017, 12, e0168581. [Google Scholar] [CrossRef]
  111. Manjunath, Y.; Mitchem, J.B.; Suvilesh, K.N.; Avella, D.M.; Kimchi, E.T.; Staveley-O’Carroll, K.F.; Deroche, C.B.; Pantel, K.; Li, G.; Kaifi, J.T. Circulating Giant Tumor-Macrophage Fusion Cells Are Independent Prognosticators in Patients With NSCLC. J. Thorac. Oncol. 2020, 15, 1460–1471. [Google Scholar] [CrossRef]
  112. Lizier, M.; Anselmo, A.; Mantero, S.; Ficara, F.; Paulis, M.; Vezzoni, P.; Lucchini, F.; Pacchiana, G. Fusion between cancer cells and macrophages occurs in a murine model of spontaneous neu+ breast cancer without increasing its metastatic potential. Oncotarget 2016, 7, 60793–60806. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  113. Rappa, G.; Mercapide, J.; Lorico, A. Spontaneous formation of tumorigenic hybrids between breast cancer and multipotent stromal cells is a source of tumor heterogeneity. Am. J. Pathol. 2012, 180, 2504–2515. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  114. Ding, J.; Jin, W.; Chen, C.; Shao, Z.; Wu, J. Tumor associated macrophage× cancer cell hybrids may acquire cancer stem cell properties in breast cancer. PLoS ONE 2012, 7, e41942. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  115. Cao, M.F.; Chen, L.; Dang, W.Q.; Zhang, X.C.; Zhang, X.; Shi, Y.; Yao, X.H.; Li, Q.; Zhu, J.; Lin, Y.; et al. Hybrids by tumor-associated macrophages × glioblastoma cells entail nuclear reprogramming and glioblastoma invasion. Cancer Lett. 2019, 442, 445–452. [Google Scholar] [CrossRef]
  116. Joly, E.; Hudrisier, D. What is trogocytosis and what is its purpose? Nat. Immunol. 2003, 4, 815. [Google Scholar] [CrossRef]
  117. Xue, J.; Zhu, Y.; Sun, Z.; Ji, R.; Zhang, X.; Xu, W.; Yuan, X.; Zhang, B.; Yan, Y.; Yin, L.; et al. Tumorigenic hybrids between mesenchymal stem cells and gastric cancer cells enhanced cancer proliferation, migration and stemness. BMC Cancer 2015, 15, 793. [Google Scholar] [CrossRef] [Green Version]
  118. Zhang, L.N.; Huang, Y.H.; Zhao, L. Fusion of macrophages promotes breast cancer cell proliferation, migration and invasion through activating epithelial-mesenchymal transition and Wnt/β-catenin signaling pathway. Arch. Biochem. Biophys. 2019, 676, 108137. [Google Scholar] [CrossRef]
  119. Fan, H.; Lu, S. Fusion of human bone hemopoietic stem cell with esophageal carcinoma cells didn’t generate esophageal cancer stem cell. Neoplasma 2014, 61, 540–545. [Google Scholar] [CrossRef]
  120. Weichert, W.; Knösel, T.; Bellach, J.; Dietel, M.; Kristiansen, G. ALCAM/CD166 is overexpressed in colorectal carcinoma and correlates with shortened patient survival. J. Clin. Pathol. 2004, 57, 1160–1164. [Google Scholar] [CrossRef]
  121. Jayasinghe, C.; Simiantonaki, N.; Michel-Schmidt, R.; Kirkpatrick, C.J. Endothelial VEGFR-3 expression in colorectal carcinomas is associated with hematogenous metastasis. Oncol. Rep. 2009, 22, 1093–1100. [Google Scholar] [CrossRef] [Green Version]
  122. Planagumà, J.; Díaz-Fuertes, M.; Gil-Moreno, A.; Abal, M.; Monge, M.; García, A.; Baró, T.; Thomson, T.M.; Xercavins, J.; Alameda, F.; et al. A differential gene expression profile reveals overexpression of RUNX1/AML1 in invasive endometrioid carcinoma. Cancer Res. 2004, 64, 8846–8853. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  123. Lartigue, L.; Merle, C.; Lagarde, P.; Delespaul, L.; Lesluyes, T.; Le Guellec, S.; Pérot, G.; Leroy, L.; Coindre, J.M.; Chibon, F. Genome remodeling upon mesenchymal tumor cell fusion contributes to tumor progression and metastatic spread. Oncogene 2020, 39, 4198–4211. [Google Scholar] [CrossRef]
  124. Ogle, B.M.; Cascalho, M.; Platt, J.L. Biological implications of cell fusion. Nat. Rev. Mol. Cell Biol. 2005, 6, 567–575. [Google Scholar] [CrossRef]
  125. Yamanaka, S.; Blau, H.M. Nuclear reprogramming to a pluripotent state by three approaches. Nature 2010, 465, 704–712. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  126. Cowan, C.A.; Atienza, J.; Melton, D.A.; Eggan, K. Nuclear reprogramming of somatic cells after fusion with human embryonic stem cells. Science 2005, 309, 1369–1373. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  127. Blau, H.M.; Blakely, B.T. Plasticity of cell fate: Insights from heterokaryons. Semin. Cell Dev. Biol. 1999, 10, 267–272. [Google Scholar] [CrossRef]
  128. Blau, H.M.; Chiu, C.P.; Webster, C. Cytoplasmic activation of human nuclear genes in stable heterocaryons. Cell 1983, 32, 1171–1180. [Google Scholar] [CrossRef]
  129. Pomerantz, J.; Blau, H.M. Nuclear reprogramming: A key to stem cell function in regenerative medicine. Nat. Cell Biol. 2004, 6, 810–816. [Google Scholar] [CrossRef]
  130. Itokowa, T.; Zhu, M.L.; Troiano, N.; Bian, J.; Kawano, T.; Insogna, K. Osteoclasts lacking Rac2 have defective chemotaxis and resorptive activity. Calcif. Tissue Int. 2011, 88, 75–86. [Google Scholar] [CrossRef] [Green Version]
  131. Islam, M.Q.; Meirelles Lda, S.; Nardi, N.B.; Magnusson, P.; Islam, K. Polyethylene glycol-mediated fusion between primary mouse mesenchymal stem cells and mouse fibroblasts generates hybrid cells with increased proliferation and altered differentiation. Stem Cells Dev. 2006, 15, 905–919. [Google Scholar] [CrossRef]
  132. Goldenberg, D.M.; Zagzag, D.; Heselmeyer-Haddad, K.M.; Berroa Garcia, L.Y.; Ried, T.; Loo, M.; Chang, C.H.; Gold, D.V. Horizontal transmission and retention of malignancy, as well as functional human genes, after spontaneous fusion of human glioblastoma and hamster host cells in vivo. Int. J. Cancer 2012, 131, 49–58. [Google Scholar] [CrossRef] [PubMed]
  133. Goldenberg, D.M.; Gold, D.V.; Loo, M.; Liu, D.; Chang, C.H.; Jaffe, E.S. Horizontal transmission of malignancy: In-vivo fusion of human lymphomas with hamster stroma produces tumors retaining human genes and lymphoid pathology. PLoS ONE 2013, 8, e55324. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  134. Yilmaz, Y.; Lazova, R.; Qumsiyeh, M.; Cooper, D.; Pawelek, J. Donor Y chromosome in renal carcinoma cells of a female BMT recipient: Visualization of putative BMT-tumor hybrids by FISH. Bone Marrow Transplant. 2005, 35, 1021–1024. [Google Scholar] [CrossRef] [Green Version]
  135. Xu, M.H.; Gao, X.; Luo, D.; Zhou, X.D.; Xiong, W.; Liu, G.X. EMT and acquisition of stem cell-like properties are involved in spontaneous formation of tumorigenic hybrids between lung cancer and bone marrow-derived mesenchymal stem cells. PLoS ONE 2014, 9, e87893. [Google Scholar] [CrossRef] [PubMed]
  136. Luo, F.; Liu, T.; Wang, J.; Li, J.; Ma, P.; Ding, H.; Feng, G.; Lin, D.; Xu, Y.; Yang, K. Bone marrow mesenchymal stem cells participate in prostate carcinogenesis and promote growth of prostate cancer by cell fusion in vivo. Oncotarget 2016, 7, 30924–30934. [Google Scholar] [CrossRef] [Green Version]
  137. Laberge, G.S.; Duvall, E.; Haedicke, K.; Pawelek, J. Leukocyte(-)Cancer Cell Fusion-Genesis of a Deadly Journey. Cells 2019, 8, 170. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  138. Toyoshima, K.; Hayashi, A.; Kashiwagi, M.; Hayashi, N.; Iwatsuki, M.; Ishimoto, T.; Baba, Y.; Baba, H.; Ohta, Y. Analysis of circulating tumor cells derived from advanced gastric cancer. Int. J. Cancer 2015, 137, 991–998. [Google Scholar] [CrossRef] [PubMed]
  139. Lustberg, M.B.; Balasubramanian, P.; Miller, B.; Garcia-Villa, A.; Deighan, C.; Wu, Y.; Carothers, S.; Berger, M.; Ramaswamy, B.; Macrae, E.R.; et al. Heterogeneous atypical cell populations are present in blood of metastatic breast cancer patients. Breast Cancer Res. BCR 2014, 16, R23. [Google Scholar] [CrossRef] [Green Version]
  140. de Wit, S.; Zeune, L.L.; Hiltermann, T.J.N.; Groen, H.J.M.; Dalum, G.V.; Terstappen, L. Classification of Cells in CTC-Enriched Samples by Advanced Image Analysis. Cancers 2018, 10, 377. [Google Scholar] [CrossRef] [Green Version]
  141. Nel, I.; Jehn, U.; Gauler, T.; Hoffmann, A.C. Individual profiling of circulating tumor cell composition in patients with non-small cell lung cancer receiving platinum based treatment. Transl. Lung Cancer Res. 2014, 3, 100–106. [Google Scholar] [CrossRef]
  142. Allan, A.L.; Vantyghem, S.A.; Tuck, A.B.; Chambers, A.F.; Chin-Yee, I.H.; Keeney, M. Detection and quantification of circulating tumor cells in mouse models of human breast cancer using immunomagnetic enrichment and multiparameter flow cytometry. Cytom. Part A J. Int. Soc. Anal. Cytol. 2005, 65, 4–14. [Google Scholar] [CrossRef] [PubMed]
  143. Liu, Q.; Liao, Q.; Zhao, Y. Myeloid-derived suppressor cells (MDSC) facilitate distant metastasis of malignancies by shielding circulating tumor cells (CTC) from immune surveillance. Med. Hypotheses 2016, 87, 34–39. [Google Scholar] [CrossRef] [PubMed]
  144. Li, H.; Meng, Q.H.; Noh, H.; Somaiah, N.; Torres, K.E.; Xia, X.; Batth, I.S.; Joseph, C.P.; Liu, M.; Wang, R.; et al. Cell-surface vimentin-positive macrophage-like circulating tumor cells as a novel biomarker of metastatic gastrointestinal stromal tumors. Oncoimmunology 2018, 7, e1420450. [Google Scholar] [CrossRef]
  145. Reduzzi, C.; Vismara, M.; Gerratana, L.; Silvestri, M.; De Braud, F.; Raspagliesi, F.; Verzoni, E.; Di Cosimo, S.; Locati, L.D.; Cristofanilli, M.; et al. The curious phenomenon of dual-positive circulating cells: Longtime overlooked tumor cells. Semin. Cancer Biol. 2020, 60, 344–350. [Google Scholar] [CrossRef]
  146. Sajay, B.N.; Chang, C.P.; Ahmad, H.; Khuntontong, P.; Wong, C.C.; Wang, Z.; Puiu, P.D.; Soo, R.; Rahman, A.R. Microfluidic platform for negative enrichment of circulating tumor cells. Biomed. Microdevices 2014, 16, 537–548. [Google Scholar] [CrossRef] [PubMed]
  147. Lustberg, M.; Jatana, K.R.; Zborowski, M.; Chalmers, J.J. Emerging technologies for CTC detection based on depletion of normal cells. Minimal Residual Dis. Circ. Tumor Cells Breast Cancer 2012, 195, 97–110. [Google Scholar] [CrossRef] [Green Version]
  148. Takao, M.; Takeda, K. Enumeration, characterization, and collection of intact circulating tumor cells by cross contamination-free flow cytometry. Cytom. Part A J. Int. Soc. Anal. Cytol. 2011, 79, 107–117. [Google Scholar] [CrossRef]
  149. Stott, S.L.; Hsu, C.H.; Tsukrov, D.I.; Yu, M.; Miyamoto, D.T.; Waltman, B.A.; Rothenberg, S.M.; Shah, A.M.; Smas, M.E.; Korir, G.K.; et al. Isolation of circulating tumor cells using a microvortex-generating herringbone-chip. Proc. Natl. Acad. Sci. USA 2010, 107, 18392–18397. [Google Scholar] [CrossRef] [Green Version]
  150. Riethdorf, S.; Fritsche, H.; Muller, V.; Rau, T.; Schindlbeck, C.; Rack, B.; Janni, W.; Coith, C.; Beck, K.; Janicke, F.; et al. Detection of circulating tumor cells in peripheral blood of patients with metastatic breast cancer: A validation study of the CellSearch system. Clin. Cancer Res. An. Off. J. Am. Assoc. Cancer Res. 2007, 13, 920–928. [Google Scholar] [CrossRef] [Green Version]
  151. Aguirre, L.A.; Montalbán-Hernández, K.; Avendaño-Ortiz, J.; Marín, E.; Lozano, R.; Toledano, V.; Sánchez-Maroto, L.; Terrón, V.; Valentín, J.; Pulido, E.; et al. Tumor stem cells fuse with monocytes to form highly invasive tumor-hybrid cells. Oncoimmunology 2020, 9, 1773204. [Google Scholar] [CrossRef]
  152. Yan, Y.Y.; Guo, Q.R.; Wang, F.H.; Adhikari, R.; Zhu, Z.Y.; Zhang, H.Y.; Zhou, W.M.; Yu, H.; Li, J.Q.; Zhang, J.Y. Cell-Free DNA: Hope and Potential Application in Cancer. Front. Cell Dev. Biol. 2021, 9, 639233. [Google Scholar] [CrossRef] [PubMed]
  153. Tie, J.; Wang, Y.; Cohen, J.; Li, L.; Hong, W.; Christie, M.; Wong, H.L.; Kosmider, S.; Wong, R.; Thomson, B.; et al. Circulating tumor DNA dynamics and recurrence risk in patients undergoing curative intent resection of colorectal cancer liver metastases: A prospective cohort study. PLoS Med. 2021, 18, e1003620. [Google Scholar] [CrossRef] [PubMed]
Cancers 14 03871 g001 550
Figure 1. Circulating hybrid cells. CAMLs (immune cells), CTCs, and CHCs (neoplastic cells) are disseminated into peripheral blood from the tumor. Monitoring their presence in blood provides different information into the tumor evolution or response to therapy.
Figure 1. Circulating hybrid cells. CAMLs (immune cells), CTCs, and CHCs (neoplastic cells) are disseminated into peripheral blood from the tumor. Monitoring their presence in blood provides different information into the tumor evolution or response to therapy.
Cancers 14 03871 g001
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Sutton, T.L.; Patel, R.K.; Anderson, A.N.; Bowden, S.G.; Whalen, R.; Giske, N.R.; Wong, M.H. Circulating Cells with Macrophage-like Characteristics in Cancer: The Importance of Circulating Neoplastic-Immune Hybrid Cells in Cancer. Cancers 2022, 14, 3871. https://doi.org/10.3390/cancers14163871

AMA Style

Sutton TL, Patel RK, Anderson AN, Bowden SG, Whalen R, Giske NR, Wong MH. Circulating Cells with Macrophage-like Characteristics in Cancer: The Importance of Circulating Neoplastic-Immune Hybrid Cells in Cancer. Cancers. 2022; 14(16):3871. https://doi.org/10.3390/cancers14163871

Chicago/Turabian Style

Sutton, Thomas L., Ranish K. Patel, Ashley N. Anderson, Stephen G. Bowden, Riley Whalen, Nicole R. Giske, and Melissa H. Wong. 2022. "Circulating Cells with Macrophage-like Characteristics in Cancer: The Importance of Circulating Neoplastic-Immune Hybrid Cells in Cancer" Cancers 14, no. 16: 3871. https://doi.org/10.3390/cancers14163871

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