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Identity matters: cancer stem cells and tumour plasticity in head and neck squamous cell carcinoma

Published online by Cambridge University Press:  06 February 2023

Abdelhakim Salem*
Affiliation:
Department of Oral and Maxillofacial Diseases, Clinicum, University of Helsinki, Helsinki, Finland Translational Immunology Research Program (TRIMM), Research Program Unit, University of Helsinki, Helsinki, Finland
Tuula Salo
Affiliation:
Department of Oral and Maxillofacial Diseases, Clinicum, University of Helsinki, Helsinki, Finland Translational Immunology Research Program (TRIMM), Research Program Unit, University of Helsinki, Helsinki, Finland Cancer and Translational Medicine Research Unit, University of Oulu, Oulu, Finland HUS, Helsinki University Hospital, Helsinki, Finland
*
Author for correspondence: Abdelhakim Salem, E-mail: abdelhakim.salem@helsinki.fi
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Abstract

Head and neck squamous cell carcinoma (HNSCC) represents frequent yet aggressive tumours that encompass complex ecosystems of stromal and neoplastic components including a dynamic population of cancer stem cells (CSCs). Recently, research in the field of CSCs has gained increased momentum owing in part to their role in tumourigenicity, metastasis, therapy resistance and relapse. We provide herein a comprehensive assessment of the latest progress in comprehending CSC plasticity, including newly discovered influencing factors and their possible application in HNSCC. We further discuss the dynamic interplay of CSCs within tumour microenvironment considering our evolving appreciation of the contribution of oral microbiota and the pressing need for relevant models depicting their features. In sum, CSCs and tumour plasticity represent an exciting and expanding battleground with great implications for cancer therapy that are only beginning to be appreciated in head and neck oncology.

Type
Review
Copyright
Copyright © The Author(s), 2023. Published by Cambridge University Press

Introduction

Cellular plasticity describes the ability of certain cells to adopt different phenotypes and functions, which is a characteristic feature of embryonic stem cells. However, such trait has also been observed in adult differentiated cells when challenged by chronic physiological or pathological conditions such as wound repair and tumourigenesis (Ref. Reference Yuan, Norgard and Stanger1). In cancer, cell plasticity endows tumours with enhanced self-renewal and pro-invasiveness capacities. Further, by attaining different phenotypes, tumour cells can bypass cell cycle arrest and apoptosis and circumvent therapeutic insults (Ref. Reference Boumahdi and de Sauvage2). Indeed, tumour microenvironment (TME) plays a crucial role in fuelling tumour plasticity by exposing tumour cells to a wide variety of stimuli from a heterogeneous niche, thereby imposing a significant obstacle in cancer management (Refs Reference Yuan, Norgard and Stanger1Reference da Silva-Diz3).

Head and neck squamous cell carcinoma (HNSCC) represents a group of common and aggressive epithelial tumours that arise in the oral cavity (oral SCC; OSCC), oropharynx and larynx. These tumours have strong associations with smokeless and smoking tobacco products, betel chewing, alcohol dependence and infection with human papillomavirus (HPV) types 16 and 18 (Ref. Reference Johnson4). Recently, a shift in the composition and relative abundance of oral microbiota (i.e. oral dysbiosis) has also been linked to HNSCC and certain lesions associated with an increased risk of OSCC known as potentially malignant disorders (Ref. Reference Metsäniitty5). Owing to their invasiveness and high metastatic potential, HNSCC accounted for 878 348 new cases and 444 347 new deaths in 2020 alone (Ref. Reference Sung6). Currently, treatment options include surgery, chemo-radiation, targeted therapy, immunotherapy or a combination of these modalities. Despite marked improvement in cancer management, metastasis and drug resistance remain the main causes of deaths in these patients. Although survival can be prolonged with a multimodal approach, this may, however, induce drug toxicity and deteriorate the patients' quality of life. Thus, the 5-year survival rate remains stagnant at approximately 50% (Refs Reference Johnson4, Reference Xing7, Reference Muzaffar8).

Recent technical advances in single-cell genomics, such as single-cell RNA sequencing (scRNA-seq), have revealed the complexity and heterogeneity of HNSCC, which influence both tumour plasticity and clinical response. Within such a diverse ecosystem, tumour cells exhibit variable expression of signatures related to cell cycle, stress, epithelial-to-mesenchymal transition (EMT), hypoxia and epithelial differentiation (Ref. Reference Puram9). Importantly, a distinct subpopulation of cancer stem (or stem-like) cells (CSCs) exists with enhanced self-renewal and protumourigenic properties in multiple cancers, including HNSCC (Fig. 1) (Refs Reference Prince10Reference Biddle12). It is thus critical to understand the behaviour of these dynamic cells to develop more effective anticancer therapies. Herein, we appraise the current knowledge of CSCs in HNSCC, highlighting some recently identified mechanisms that mediate their phenotypic plasticity and immune evasion. We also discuss critical factors governing their interplay within TME, including our evolving appreciation of the contribution of oral microbiota.

Fig. 1. Cancer stem cells (CSCs) in head and neck squamous cell carcinoma. CSCs represent a small subpopulation of tumour cells with the following main features: (a) self-renewal, (b) transdifferentiation and phenotypic switching, (c) tumour initiation (tumourigenesis) when transplanted into an animal host, (d) high invasive and metastatic potential, and (e) ability to develop anti-tumour drug resistance.

Intratumoural heterogeneity in HNSCC

Given the limited success of traditional therapies, attention has also been focused on identifying the genotype variations between cancer patients to predict their response to targeted drugs. However, TME harbours, within the same patient, subpopulations of tumour cells with different phenotypes and mutations, referred to as intratumoural heterogeneity (Ref. Reference Bedard13). Intratumoural heterogeneity drives clinical resistance and poses a major challenge for designing effective therapies in HNSCC (Refs Reference Bedard13, Reference Canning14). Initially, two models were proposed to explain intratumoural heterogeneity. On the one hand, the stochastic model of clonal evolution postulates that every tumour cell with an appropriate set of somatic mutations can initiate and sustain a ‘metastable’ tumour growth. However, this model conceives tumours as a homogeneous mass, hence falling short of explaining the variations in tumourigenic potential and multidrug resistance. On the other hand, according to the hierarchical cell model, cancer initiation and progression are driven mainly by a subpopulation of dynamic cells – CSCs – that are intrinsically different from the majority of more differentiated tumour cells (Refs Reference Shackleton15, Reference Fanelli, Naccarato and Scatena16).

In essence, CSCs were termed as such to highlight their stem cell-like properties, including their self-renewal, transdifferentiation and migration abilities. In this regard, there has been overwhelming evidence supporting this ‘stemness’ model. CSCs were first characterised as a minority of CD34+ve/CD38−ve cells in acute myeloid leukaemia (Ref. Reference Lapidot17). Thereafter, CSCs with other surface markers have been identified in different cancers. For instance, CD44+ve and CD133+ve CSCs sustained the capacity to initiate new tumours in non-obese diabetic/severe combined immunodeficient (NOD/SCID) mouse models of breast and colorectal cancers, respectively (Refs Reference Al-Hajj18, Reference O'Brien19). The first identification of CSCs in HNSCC was reported by Prince et al., who showed that only CD44+ve cancer cells – comprising <10% of the tumours – initiated new malignant growths in NOD/SCID mice (Ref. Reference Prince10). Interestingly, as few as 5 × 103 cells of early-passaged CD44+ve CSCs were able to produce new tumours in vivo, whereas CD44−ve cells failed to give rise to tumour events at a 100-fold higher density. Of note, CD44+ve cell-derived tumours comprised phenotypically diverse cells of both CD44+ve/CD44−ve clones, suggesting that CSCs may also drive intratumoural heterogeneity in HNSCC patients. These findings signify the role of CD44 in identifying CSCs in other tumours of epithelial origin (Ref. Reference Prince10). Several cell surface receptors and intracellular proteins have since been reported as applicable CSC markers in HNSCC, as summarised in Table 1.

Table 1. Common markers of cancer stem cells in head and neck cancers

3D, three-dimensional; ALDH, aldehyde dehydrogenase; Bmi-1, B-cell-specific Moloney murine leukaemia virus insertion site 1; CD, cluster of differentiation; c-Met, c-mesenchymal–epithelial transition factor; CSC, cancer stem cell; EMT, epithelial–mesenchymal transition; GPR49, G-protein coupled receptor 49; HCAM, homing cell adhesion molecule; HGFR, hepatocyte growth factor receptor; HNSCC, head and neck squamous cell carcinoma; Lgr5, leucine-rich repeat-containing G-protein coupled receptor 5; LSCC, laryngeal squamous cell carcinoma; NGFR, nerve growth factor receptor; NOD/SCID, non-obese diabetic/severe combined immunodeficient; Oct4, octamer-binding transcription factor 4; OSCC, oral squamous cell carcinoma; OTSCC, oral tongue squamous cell carcinoma; PCGF4, polycomb group RING finger protein 4; POU5F1, Pic-1, Oct1,2, Unc-86 transcription factor 1; PROM1, prominin-1; VM, vascular mimicry.

CSC markers in head and neck cancers

Fluorescence-activated cell sorting and magnetic bead sorting remain the most common methods to detect and isolate CSCs, wherein various cell markers were utilised, either individually or in combination. Besides their importance in understanding the complex behaviour of CSCs, these markers have emerged as valuable biomarkers and therapeutic targets in cancer. Here, we briefly outline recent findings of selected molecules that are more frequently applied as CSC markers in HNSCC.

CD44

The cluster differentiation CD44 is the key stem cell marker in solid tumours and the first used to study HNSCC-derived CSCs. CD44 is a multistructural and multifunctional transmembrane adhesion receptor that binds to several extracellular matrix (ECM) ligands, particularly to hyaluronic acid (HA; aka hyaluronan) – a glycosaminoglycan involved in pivotal tumourigenic events. CD44 has mediated cancer cell proliferation, migration, angiogenesis and stemness properties, ultimately leading to tumour progression and metastasis (Refs Reference Ludwig20Reference Wang and Bourguignon23). Recently, Ludwig et al. (Ref. Reference Ludwig20) analysed the association of CD44 with the pro-angiogenic genotype in HNSCC using the Cancer Genome Atlas. Interestingly, they found that HNSCC has the second highest CD44 expression among all cancer types included in the Pan-Cancer Atlas. Moreover, using an orthotopic carcinogen-induced mouse model, CD44+ve expression was consistently upregulated at different stages of oral carcinogenesis, from dysplastic lesions to advanced carcinomas (Ref. Reference Ludwig20). The immunogenicity of CSCs was examined using primary human HNSCC samples and patient-derived xenografts. Surprisingly, CD44+ve CSCs in HNSCC revealed EMT features and were less immunogenic than other CD44−ve tumour cells when cultured with autologous CD8+ve tumour-infiltrating lymphocytes (TILs). Further, programmed death-ligand 1 (PD-L1) was selectively expressed on CD44+ve CSCs compared with CD44−ve cells (Ref. Reference Lee24). In addition, HNSCC-derived spheroids exhibited increased expression of CD44, whereas the levels of other putative CSC markers, such as CD24 and CD133, were not notably increased (Ref. Reference Byun25).

Human CD44 is encoded by the highly conserved CD44 gene on chromosome 11. Following extensive alternative splicing, it generates multiple variant isoforms, including the standard (CD44s) and variant (CD44v) forms, the latter representing a promising prognostic and therapeutic target in different cancers (Ref. Reference Wang26). In this regard, Wang et al. (Ref. Reference Wang26) showed that HNSCC cells (HSC-3) expressed at least four CD44 isoforms (v3, v6, v10) and CD44s. Of note, these CD44 isoforms mediated cancer cell migration, proliferation and cisplatin sensitivity. Importantly, tumours expressing the variant isoforms (v3, v6, v10) alone or in combination showed a greater proportion of metastatic lymph nodes and tumour progression than the standard form (Ref. Reference Wang26). A meta-analysis revealed a significant association between CD44 and worsening T stage, N status, higher tumour grades and 5-year overall survival (OS) rates in patients with HNSCC (Ref. Reference Chen27). However, despite its wide use in CSC studies, the increased levels of CD44+ve cells in some cohorts suggest that such population may not represent a ‘pure’ mass of CSCs. Thus, combining multiple surface markers, such as CD44 and aldehyde dehydrogenase (ALDH) has been increasingly used in HNSCC (Ref. Reference Kamarajan28).

ALDH

This family comprises a group of intracellular detoxifying enzymes that oxidise exogenous and endogenous aldehydes, hence mediating drug resistance in cancer patients (Ref. Reference Januchowski, Wojtowicz and Zabel29). ALDH has been considered a functional marker of HNSCC-derived CSCs (Refs Reference Clay11, Reference Kamarajan28, Reference Chen30). Among the first reports on this molecule in HNSCC, Chen et al. (Ref. Reference Chen30) showed that ALDH1+ve tumour cells displayed EMT features and radioresistance and represented a reservoir for tumour initiation. Unlike the copious expression of CD44, most HNSCC cells had low ALDH activity; nevertheless, ALDHhigh cells (1.0–7.8%) clearly co-expressed CD44 and sustained high tumourigenic potential in NOD/SCID mice (Ref. Reference Clay11). In agreement with these studies, HNSCC-derived ALDH1+ve CSCs had higher stemness traits, including sphere-forming capacity than ALDH1−ve cells (Ref. Reference Yu31).

These findings support the role of ALDH as a selective marker for HNSCC CSCs and hold promising therapeutic and prognostic utilities. In this regard, targeting ALDH with Aldi-6 (ALDH3A1 inhibitor) sensitised HNSCC cells to cisplatin and reduced tumour growth burden in vivo (Ref. Reference Kim32). Prince et al. (Ref. Reference Prince33) presented a feasible approach to prepare ALDHhigh CSC-based vaccines to induce anti-HNSCC immunity, implying a clinical utility to treat cancer patients. Recently, a multifactorial analysis revealed that HNSCC patients with negative immunoexpression of ALDH1A1 had 5.25 times higher OS than the ALDH1A1+ve group (P = 0.01). Furthermore, using univariate and multivariate analysis, only ALDH1A1 staining positivity showed a significant effect on OS in HNSCC patients compared with other CSC markers such as CD44 (Ref. Reference Szafarowski34). Of interest, HNSCC-ALDH1+ve CSCs were found to possess high levels of the transcriptional repressor Bmi-1, another putative marker of CSCs, regulating their stemness and drug resistance (Ref. Reference Chen30).

Bmi-1

The B-cell-specific Moloney murine leukaemia virus insertion site 1 (Bmi-1) is a key factor responsible for self-renewal and enrichment of stem cells. In their seminal work on characterizing CSCs in HNSCC, Prince et al. (Ref. Reference Prince10) reported a differential expression of Bmi-1 in the tumourigenic CD44+ve population, indicating a potential role for this molecule in tumour plasticity. Interestingly, Bmi-1 levels were abnormally upregulated in HNSCC patients, which correlated positively with chemo- and radioresistance (Ref. Reference Vormittag35). Thus, these findings have made it an attractive target for CSC examination in HNSCC studies. A recent comparative study found that Bmi-1 and BCL11B effectively discriminated between healthy and cancerous tissues in HNSCC patients, whereas ALDH1A1 and CD44 were both expressed to a comparable extent in these tissues (Ref. Reference Sharaf36). Interestingly, Bmi-1+ve cells were convincingly shown to be slow-cycled tumour-initiating CSCs that did not only initiated the tumour but also mediated cervical lymph node metastasis in a mouse model of chemically induced HNSCC (4-nitroquinoline-1-oxide: 4-NQO). Congruous with CSC features, Bmi-1+ve tumour cells were highly tumourigenic and chemo-resistant, whereas a combination of Bmi-1 inhibitor and cisplatin treatment effectively inhibited HNSCC (Ref. Reference Chen37).

Using a multicolour lineage tracing method in a 4-NQO-induced mouse model of OSCC, Tanaka et al. (Ref. Reference Tanaka38) reported that Bmi-1+ve cells could serve as oral CSCs. They showed that Bmi-1+ve cells were scattered in the developing tumours, which then proliferated to produce new patches – fuelling tumour growth and maintenance. However, some Bmi-1+ve cells remained single and gradually disappeared from the malignant tissue, implying that Bmi-1 was also expressed by differentiated cells, which have limited capacity to self-renew and maintain tumourigenesis (Ref. Reference Tanaka38). This finding also signifies the importance of employing multiple markers to better characterise CSCs. Of note, a recent study showed that Bmi-1 inhibition not only helped to abolish CSCs but also augmented PD1 blockade by activating tumour cell-intrinsic immunity, which hindered metastasis and prevented relapse in HNSCC (Ref. Reference Jia, Zhang and Wang39).

Other less frequently studied CSC markers are summarised in Table 1.

CSC plasticity: a partial phenotypic transition?

In addition to the aforementioned intratumoural heterogeneity patterns, a newer more nuanced model was recently proposed as ‘CSC plasticity’, whereby cells reversibly switch between stemness and differentiated states. Such transition is mediated by genetic and epigenetic alterations as well as by cues from key processes, particularly EMT and mesenchymal-to-epithelial transition (MET) (Refs Reference Fanelli, Naccarato and Scatena16, Reference Ghuwalewala40, Reference La Fleur, Johansson and Roberg41).

During embryogenesis, cells undergo highly dynamic and reversible shifts between epithelial and mesenchymal states. When the shift is towards the mesenchymal phenotype, cells undergo EMT and obtain potent migratory and invasive characteristics. EMT transcription factors include three main families: Snail, Twist and ZEB (Ref. Reference Yeung and Yang42). In contrast to EMT, cells may start losing these migratory features and shift towards an epithelial state by acquiring junctional attachments and apico-basal polarisation – a process referred to as MET (Ref. Reference Thiery43). Although the role of MET/EMT in cancer plasticity is still under investigation, it is nevertheless widely accepted that much of the intratumoural heterogeneity, invasion, metastasis and drug resistance are driven by these processes. CSCs can employ EMT to dissociate from the primary tumours, intravasate into the circulation and initiate new locoregional/distant colonies. Upon reaching a preferable metastatic niche, cells revert to an epithelial state (MET) to terminate migration, promote proliferation and seed new heterogeneous tumour colonies (Ref. Reference Nieto44).

In HNSCC, CSCs are often localised to the tumour invasive front, wherein both EMT and metastasis are executed, contrary to the upper layers of the tumour bulk, which remain largely epithelial (Ref. Reference Sterz45). Consistent with this, Chowdhury et al. (Ref. Reference Chowdhury46) showed that the tumour leading edges in a subset of OSCC were enriched by CD44high/ALDHhigh CSCs, which demonstrated greater proliferative and invasive activities. Notably, CD44high CSCs from HNSCC tumours revealed clear EMT features such as migration and invasion. Further, CD44high cells formed bilateral lung metastases in NOD-SCID mice, in contrast to CD44low, which failed to generate similar metastatic growths (Ref. Reference Davis47). When analysing EMT genes in 25 HNSCC cell lines, Johansson et al. (Ref. Reference La Fleur, Johansson and Roberg41) found that EMT-expressing cells were mainly CD44high with an enhanced motility. Of interest, these cells had low levels of epidermal growth factor receptor – a pattern associated with stemness (Refs Reference La Fleur, Johansson and Roberg41, Reference Johansson48). Moreover, the expression of Twist1, a key inducer of EMT, was correlated with radioresistance in HNSCC (Ref. Reference Johansson48). In support of these reports, Twist1 directly regulated the expression of the putative CSC marker Bmi-1. Furthermore, Twist1 and Bmi-1 were mutually essential to promote EMT and tumour-initiating capability and associated with unfavourable clinical outcomes in HNSCC (Ref. Reference Yang49). In OSCC, EMT characteristics such as ZEB1 overexpression and loss of E-cadherin were markedly higher in CD44high/CD24low CSCs, indicating that tumour cell stemness co-occurs with and is probably promoted by EMT (Ref. Reference Ghuwalewala40). Recently, 16 canonical EMT markers were surveyed in a pan-cancer cohort collected from various tumours, confirming the presence of EMT features in HNSCC patients (Ref. Reference Gibbons and Creighton50).

Recent evidence has shown that tumour cells do not necessarily undergo a complete phenotypic transition; rather, cells tend to execute partial (pEMT) or hybrid EMT by concurrently revealing epithelial and mesenchymal phenotypes (Ref. Reference Bakir51). Supporting the ‘CSC plasticity’ model, transcriptional profiles of ~6000 single cells from HNSCC patients showed that pEMT-expressing cancer cells were localised to the leading edge of primary tumours. These cells were in proximity to cancer-associated fibroblasts and their pEMT programme was deemed to be an independent predictor of nodal metastasis, tumour grade and adverse pathologic features (Ref. Reference Puram9). In this regard, it is logical to assume that CSCs utilise their mesenchymal gene repertoire at the tumoural front to invade and disseminate, while maintaining their epithelial characteristics to reseed and establish new metastatic growths. Such plasticity is influenced by many TME-related factors such as hypoxia (Ref. Reference Mimeault and Batra52).

Role of hypoxic microenvironment

Hypoxia, either persistent or temporary, is a feature of most solid tumours. Accumulating experimental data suggest hypoxia as a crucial inducer of EMT and CSC plasticity, wherein hypoxia-inducible factors (HIFs) are associated with tumour cell stemness, metastasis, angiogenesis and drug resistance (Refs Reference Mimeault and Batra52, Reference Lee and Simon53). Like other solid tumours, hypoxia ensues in HNSCC when the blood supply becomes insufficient due to tumour growth, vascular disturbances or metabolic stress. Besides its pro-stemness effect, hypoxia was shown to promote anti-apoptotic pathways and tumour aggressiveness, predict poor therapeutic response and induce the formation of functional invadopodia in HNSCC cells (Refs Reference Sasabe54Reference Wiechec58). A recent study found that hypoxia-related genes were enriched in CD44+ve CSCs from patients with HNSCC. Interestingly, functional assays indicated that HIF-1α promoted stemness, drug resistance and EMT in these CD44+ve CSCs. It is noteworthy that inhibition of HIF1α-driven pathways reversed the CD44-mediated chemoresistance in vivo, implying new therapeutic opportunities in HNSCC (Ref. Reference Byun25). Although reports assessing the direct influence of hypoxia on CSCs in HNSCC are limited, hypoxia may mediate its pro-stemness effects through EMT. In this regard, hypoxia induced the expression of key EMT transcriptional factors and promoted pulmonary metastasis in OSCC (Refs Reference Wiechec58, Reference Huang59). Further, co-expression of hypoxia and EMT markers (Twist 2/Snip1 and HIF-1α, respectively) served as an independent prognosticator for both OS and disease-free survival in patients with tongue SCC (TSCC) (Ref. Reference Liang60). These reports suggest that hypoxia is not only a promoter of tumour stemness and EMT but can also regulate therapeutic response to anticancer agents. Additional evidence of the impact of hypoxia on cancer stemness can be found in reviews (Refs Reference Mimeault and Batra52, Reference Lee and Simon53, Reference Yeo61). One important aspect of hypoxia-induced stemness is the induction of an intriguing pattern of tumour vasculature, termed vascular mimicry (VM), which will be discussed in the next section.

Plasticity underlies tumour cell mimicry

Emerging evidence reveals that certain tumour cells can acquire intrinsic differentiation programmes of distinct cell types, including vascular, neuron and immune cell mimicry to survive harsh TME and facilitate tumour progression and clinical resistance.

Endothelial cell mimicry

Angiogenesis is a hallmark of cancer. However, the limited success of antiangiogenic strategies remains a daunting challenge in treating many solid tumours including HNSCC (Ref. Reference Ribatti62). In fact, despite the growing number of clinical trials, targeting the classical angiogenic pathways (e.g. vascular endothelial growth factor, VEGF) showed only a modest improvement in the OS of cancer patients. Unexpectedly, inhibiting the VEGF pathway has been associated with persistent tumour invasiveness, increased distant metastasis and worsening treatment outcome (Refs Reference Ebos63, Reference Pàez-Ribes64). Questions have therefore emerged regarding how tumour cells can survive such harsh hypoxic conditions and also how they can become more ‘metastable’ and resistant following treatment with angiogenic inhibitors.

Tumour vasculature has long been assumed to arise from pre-existing endothelial cells (ECs). However, a significant number of studies suggest that CSCs utilise their phenotypic plasticity to acquire differentiation programmes of distinct cell types, such as EC-like phenotype (Ref. Reference Seftor65). Indeed, the CSC marker CD44 has been implicated in promoting several tumour proangiogenic events (Ref. Reference Wang and Bourguignon23). In this regard, VM represents an alternative pattern of tumour microcirculation in which aggressive tumour cells mimic ECs by initiating perfusable networks of vessel-like structures in vitro (Refs Reference Salem and Salo66, Reference Hujanen67). Notably, tumour cells capable of VM share considerable molecular similarity with that of CSCs (Refs Reference Seftor65, Reference Salem and Salo66, Reference Fan68). For instance, up to 90% of CSCs were able to transdifferentiate into functional ECs in glioblastoma, the most common and aggressive brain tumour, implying that a significant portion of tumour vasculature has a neoplastic origin (Ref. Reference Ricci-Vitiani69). Recently, we showed that metastatic OSCC cells co-express the endothelial marker CD31 in vitro. Furthermore, tissue samples from OSCC patients revealed distinct CD31+ve mosaic VM lumens that also contained red blood cells (Refs Reference Hujanen21, Reference Almahmoudi70). Interestingly, and unlike VM-free regions, such VM-competent cells display CD44high/E-cadherinlow phenotype, denoting a common stemness-related state (Ref. Reference Hujanen21).

Apart from frank angiogenesis, tumour lymphatics play a pivotal role in cancer progression. In a recent study on basal-like breast cancer, CSCs were capable of undergoing lymphatic cell differentiation via the activation of the VEGF-C pathway by which lymphatic vessel-like channels were initiated. Further in vivo and in vitro experiments revealed that lymphangiogenic mimicry (LM) served as a conduit for CSCs to lymphatic vessels and accelerated lymphatic metastases (Ref. Reference Wang71). Our group has recently demonstrated that the lymphatic vessel endothelial hyaluronan receptor 1 (LYVE-1), a homologue of CSC marker CD44, is expressed by OSCC cells and promotes their dissemination and vessel-like formation (Ref. Reference Karinen72). Notably, patients with tumours expressing high levels of LYVE-1 tend to suffer more lymph node metastasis and have worse survival (Refs Reference Karinen72, Reference Karinen73). Of interest, LYVE-1 is a receptor for HA – a key component of ECM that influences, directly and indirectly, the self-renewal and maintenance of CSCs (Ref. Reference Chanmee74). Thus, targeting the LYVE-1 or VEGF-C pathway (or both) may represent a novel therapeutic approach to conquer CSC-driven lymphatic metastasis in HNSCC. Nevertheless, the potential clinical applications of LM remain unclear, warranting further in-depth investigations.

Immune and neuronal cell mimicry

In addition to the vascular cell phenotype, recent studies uncovered more intriguing differentiation programmes of CSCs, including the acquisition of immune and neuronal cell states to facilitate tumour progression (Refs Reference Gangoso75Reference Zeng77). However, conventional bulk transcriptomic profiling can be ineffective in distinguishing such tumour-intrinsic programmes from other TME-infiltrating cells.

Based on scRNA-seq datasets and experimental models, an elevated immune-like transcriptional programme was recently seen in cells of multiple cancer types, which was progressively acquired during the course of malignant transformation. Specifically, an enrichment of B cell, T cell and myeloid cell signatures was revealed in tumour cells from lung, breast, kidney and pancreatic cancers. The score was, however, lower in tumour cells than in immune cells, implying a partial acquisition of this immune mimicry during progression from normalcy to neoplasm (Ref. Reference Gao76). Of note, such mimetic profile might adversely influence the prognostic value of immune cell signatures in cancer studies. Hence, through the exclusion of tumour cell-related immune genes, a new optimised immune response signature was proposed, which offered more reliable prognostic estimates (Ref. Reference Gao76). These findings are consistent with a recent work showing a striking gain in immune evasion capabilities of CSCs following the acquisition of a transcriptional module that hampered the immune response in glioblastoma multiforme (Ref. Reference Gangoso75). In primary HNSCC, Lee et al. (Ref. Reference Lee24) provided a mechanism by which long-lived CD44+ve CSCs can selectively evade host immune responses. Interestingly, CD44+ve cells expressed higher levels of PD-L1, which was associated with constitutive phosphorylation of signal transducer and activator of transcription 3 (STAT3) and decreased immunogenicity. Importantly, PD-1/PD-L1 blockade partially reversed the weakened immunogenicity and activated the TILs response against CD44+ve CSCs (Ref. Reference Lee24). Indeed, these data highlight the complex genetic and phenotypic changes of CSCs and their infinite ability to hijack the immune response and remodel TME. Although this is still a new area of research, it is paramount to investigate whether the immune mimicry is implicated in HNSCC, wherein mechanisms underpinning its immunosuppressive TME remain an enigma.

To survive and initiate metastatic colonisation in the brain, tumour cells must render their new neural niche to an amenable microenvironment. In this context, Neman et al. (Ref. Reference Neman78) showed that HER2+ve, breast-to-brain metastatic (BBM) CSCs can attain neuronal phenotype by expressing and metabolizing gamma-aminobutyric acid (GABA) – the chief inhibitory neurotransmitter in mammalian brains. GABA was utilised by tumour cells to promote their proliferation and GABAergic neuronal properties. Further, BBM cells expressed Reelin, a critical neuronal glycoprotein for brain development, which was directly associated with HER2 (Ref. Reference Neman78). Supporting these observations, a recent preprint (not peer-reviewed) study showed that small-cell lung cancer (SCLC) cells undergo neuronal mimicry – a transition towards neuronal phenotype during tumour progression and metastasis. More importantly, this neuronal mimicry was critical for establishing SCLC growth in the brain, whereby tumour cells secrete neuronal pro-survival factors (e.g. Reelin) to recruit astrocytes and promote brain metastases (Ref. Reference Fangfei79). In essence, although brain metastasis in HNSCC is a rare event, comprising <1% of all cases (Ref. Reference Barrett80), these reports further assert the concept of CSCs and stress the need for more studies in this exciting area with much more to reveal.

Oral microbiota and CSCs: emerging evidence

Recently, the ‘polymorphic microbiome’ has been proposed as a new hallmark of cancer (Ref. Reference Hanahan81). Dysbiosis of the commensal microbiota can contribute, both positively and negatively, to the initiation and progression of HNSCC and, through immunomodulation, to anticancer drug response (Ref. Reference Metsäniitty5). Recent research has advanced our understanding of the interactions between microbiota and tumour cells, and there is a growing appreciation of the potential of microbiota to transform treatment strategies for cancer patients. This review briefly outlines a few examples of microbiota commonly implicated in HNSCC, to then focus on their possible role in tumour plasticity.

Oral cavity hosts diverse microbial communities inhabiting different sites such as teeth, saliva, tongue and other mucosal surfaces. Using germ-free animal models, particular microorganisms, chiefly but not exclusively bacteria, were shown to impact key features associated with tumour cell stemness such as EMT, proliferation, migration and invasion. Among these, two prominent oral bacteria, Porphyromonas gingivalis (P. gingivalis) and Fusobacterium nucleatum (F. nucleatum), influenced oral carcinogenesis and tumour progression. For example, infection with P. gingivalis, a major anaerobic Gram-negative periodontopathogen, induced EMT-driven morphological changes in OSCC cells and augmented their migratory and invasive capacities. Importantly, P. gingivalis-infected tumour cells exhibited evident plasticity features, including the upregulation of CSC markers (CD44 and CD133) and chemotherapeutic resistance (Ref. Reference Ha82). Using a murine model of periodontitis-associated oral TSCC, infection with both P. gingivalis and F. nucleatum markedly enhanced the tumour size and invasiveness. Furthermore, administration of these periodontopathogens significantly induced the activation of STAT3 – an important regulator of CSCs in HNSCC (Ref. Reference Binder Gallimidi83). Exposure to lipopolysaccharides from P. gingivalis, F. nucleatum or Escherichia coli resulted in a strong upregulation of certain EMT transcripts (vimentin, Snail, Twist) in OSCC cells. On the other hand, the epithelial adhesion molecule E-cadherin was downregulated, implying shifting towards a mesenchymal state. Notably, these infected tumour cells showed morphological changes resembling those of fibroblasts, while unstimulated cells maintained a classical epithelial cobble-stone morphology (Ref. Reference Abdulkareem84).

Epstein–Barr virus (EBV) is a human herpesvirus associated with several malignancies such as nasopharyngeal carcinoma (NPC). Lun et al. (Ref. Reference Lun85) found that CSC markers (CD44 and SOX2) were overexpressed in a minor population of EBV+ve NPC cells, which were resistant to chemotherapy and showed high spheroid formation efficiency. Consistent with CSC properties, the authors revealed that the sorted CD44+ve cells generated a heterogeneous population of both CD44+ve and CD44−ve cells (Ref. Reference Lun85). The exact mechanisms by which EBV and other pathogenic microbiota induce tumour cell stemness are still being elucidated. For instance, the latent membrane protein 1 (LMP1) constitutes a key oncoprotein of EBV. Interestingly, Kondo et al. (Ref. Reference Kondo86) revealed that EBV induces the development of CD44high/CD24low phenotype of CSCs and cancer progenitor cells in NPC via LMP1. Moreover, LMP1 induction in nasopharyngeal epithelial cells resulted in high tumourigenicity, rapid proliferation and enhanced self-renewal abilities. Morphologically, LMP1-expressing cells changed into fibroblast-like, spindle-shaped cells (Ref. Reference Kondo86).

HPV-induced oropharyngeal HNSCC is one of the most rapidly increasing cancers in high-income countries, also affecting younger individuals (Ref. Reference Lechner87). Despite the evident prognostic value of HPV status in HNSCC patients, its influence on CSCs and cell stemness remains poorly understood and sometimes conflicting. For instance, HPV status was shown to not correlate with the proportion of ALDHhigh CSCs in HNSCC (Ref. Reference Tang88). By contrast, another study showed that HPV16+ve HNSCC had a 62.5-fold greater intrinsic CSC pool than HPV−ve cells (Ref. Reference Zhang89). Further, transfecting tumour cells with HPV16 genome enhanced CSC features including ALDH activity, tumour growth, migration/invasion and self-renewal capacity (Ref. Reference Lee90). However, it is perhaps difficult to explain how HPV+ve tumours – characterised by substantially better prognosis – harbour higher CSCs, which render the tumours more aggressive and drug-resistant. Nevertheless, recent studies have suggested that HPV could impact the CSC population in HNSCC after initiating the therapeutic regimen. In this sense, Reid et al. (Ref. Reference Reid91) demonstrated that HPV−ve tumours had significant elevations in CD44+ve/ALDH+veCSCs following irradiation, with greater escalation than HPV+ve cell lines.

Collectively, although these illustrative examples are rather limited and comprise small sample sizes, they encourage further research to uncover the relationship between oral microbiota and CSCs and how it might influence carcinogenesis in head and neck tissues.

A need for new models?

The characteristics of CSCs are traditionally assessed in vitro using numerous three-dimensional (3D) techniques (comprehensively reviewed in references Reference Reid91, Reference Langhans92). Among these, the sphere (or spheroid-like) formation assay is commonly used to assess the ability of CSCs to grow in extremely low attachment/serum conditions and form tumourspheres. These tumourspheres are also termed ‘orospheres’ when formed by HNSCC CSCs, indicating their origin from the oral cavity and head and neck tumours (Ref. Reference Krishnamurthy and Nör94). Typically, tumourspheres are generated using scaffold-free (e.g. hanging drop cultures and low adhesion plates) and scaffold-based models (Fig. 2a and b). The latter scaffold-based 3D cultures provide more physiologically relevant conditions, particularly when incorporating biologically derived hydrogels such as collagen, fibrin or Matrigel. These matrices facilitate cell-to-cell and cell-to-ECM interactions, thereby allowing more reliable assessment of CSC tumourigenicity, stemness and drug response, including possible chemo-/radioresistance. In particular, Matrigel, a matrix extracted from Engelbreth–Holm–Swarm (EHS) mouse sarcoma tissue, has been broadly used to assess CSC features due to its high content of ECM proteins, growth factors and proteoglycans (Refs Reference Langhans92Reference Aramini95). However, animal-derived matrices, such as Matrigel, have several limitations, making them suboptimal for human CSC research, including non-human origin, inter-batch variations and presence of several undefined factors (Ref. Reference Pamarthy and Sabaawy96). Therefore, the safety and efficacy of 85% of the drugs identified in such models are not translated to early clinical trials (Ref. Reference Ledford97).

Fig. 2. Examples of models used to assess the features of cancer stem cells (CSCs). Ex vivo models are broadly categorised as follows: (a) scaffold-free cultures, such as hanging drops, low-attachment plates and suspension cultures, to assess the formation of tumourspheres, and (b) scaffold-based models, including the use of biological hydrogels such as Matrigel and Myogel, for three-dimensional assays. (c) In vivo models are mainly used to assess the capacity of CSC-like cells to initiate and sustain new growths (and hence, they are also termed tumour-initiating/propagating cells). The most commonly used models include non-obese diabetic/severe combined immunodeficient (NOD/SCID) and NOD/SCID IL2Rγ null mice. (d) Humanised animal models (e.g. XactMice and GSS zebrafish) represent promising potential platforms to assess the human CSC hypothesis in a more relevant niche encompassing human hematopoietic stem and progenitor cells (HSPCs), which are able to recreate the original tumour microenvironment observed clinically. HSPCs are expanded ex vivo and injected into the NOD/SCID gamma mice. (e) In addition, zebrafish larvae may represent an attractive and cost-effective model in CSC research, particularly for assessing tumour progression and drug resistance.

To provide a reliable alternative to animal-derived matrices, our group developed ‘Myogel’, a matrix isolated from human uterus leiomyoma that provides a physiologically relevant 3D milieu for ex vivo cancer modelling. Although its proteome is substantially different from murine EHS-derived matrices, Myogel comprises key ECM proteins such as laminin, collagen (types IV, XII and XIV), tenascin-C, heparan sulphate proteoglycans, nidogen and EGF (Ref. Reference Salo98). A balanced physiological pH environment is important for the regulation and maintenance of stem cell activities including proliferation, viability and differentiation (Ref. Reference Teo, Mantalaris and Lim99). In this context, Myogel pH is neutral and more stable during cell culture than that of Matrigel, hence providing a good control of CSC experiments. Importantly, key CSC-related properties were more efficiently represented in Myogel, including tumour cell migration, invasion and response to targeted anti-HNSCC therapy (Refs Reference Salo98, Reference Naakka100, Reference Tuomainen101). Furthermore, primary HNSCC cell lines showed a greater tendency to form VM in Myogel, whereas human ECs formed consistent and dense tubes throughout the matrix, suggesting that ECM is an important modulator of the tumour cell-derived tubulogenesis (Ref. Reference Hujanen21). Thus, when selecting a 3D scaffold for CSC studies, it is important to consider matrices that sustain stemness traits and closely recapitulate the structural and molecular features of human TME.

Tumour-initiating/propagating capacity is considered to be the gold standard for identifying CSCs. Currently, most in vivo studies of CSCs rely upon tumour engraftment into severely immunocompromised mouse models – typically NOD/SCID and NOD/SCID IL2Rγ null mice (Fig. 2c). These mice are B cell- and T cell-deficient models and exhibit defective activity of dendritic cells, macrophages and natural killer cells, thus enhancing the chances of successful xenotransplantation (Ref. Reference Skidan and Steiniger102). While they led to most seminal findings on CSCs, these models do not reliably represent the native tumour stroma, including the dearth of cytokines regulating CSC activities. Thus, for more rigorous assessment of the human CSC hypothesis, tumour cells need to be transferred into mice installed with all the requisite human supporting cells (Ref. Reference Kelly103). To overcome such constraints, Morton et al. (Ref. Reference Morton104) developed a humanised xenochimeric mouse model of HNSCC (XactMice) comprising human hematopoietic stem and progenitor cells (HSPCs) able to recreate the original TME observed clinically. Following the harvesting of HSPCs from either donated cord blood or adult peripheral blood, cells were expanded ex vivo and injected into sub-lethally irradiated NOD/SCID gamma mice to generate XactMice, wherein HNSCC cells were later engrafted (Fig. 2d). Interestingly, XactMice tumours showed epithelial, stromal and immune gene signature that aligns more closely to the original TME observed clinically – an effect partly mediated by HSPC-/tumour cell-driven cytokines (Ref. Reference Morton104). Additionally, the same group developed a dual infusion protocol of HSPCs and mesenchymal stem cells, resulting in higher degrees of ‘humanisation’ of the HNSCC mouse model. This includes incremental human bone marrow engraftment, excessive increase in human immune cells and intratumoural homing with better lineage reconstitution. This optimised model more closely resembles that of the originating patient's tumour, suggesting an enhanced capability to accurately recapitulate a human TME (Ref. Reference Morton105).

Another platform that could be useful for CSC research is Zebrafish – a model that has been increasingly used in anticancer screening. Recently, our group utilised zebrafish larvae as a xenograft model of human OSCC to evaluate tumour cell metastasis, VM formation and personalised drug response (Fig. 2e) (Refs Reference Hujanen21, Reference Karinen72, Reference Wahab106, Reference Al-Samadi107). Indeed, zebrafish has several advantages over murine models with regard to its efficiency, feasibility and cost- and labour-effectiveness. Further, zebrafish larvae are optically transparent, making them an excellent candidate for live imaging, which can be particularly advantageous in CSC research (Refs Reference Hujanen21, Reference Karinen72). However, similar to mice, the zebrafish model is devoid of critical cytokines, chemokines and other TME factors released in human patients. To alleviate this limitation, Rajan et al. (Ref. Reference Rajan108) pioneered the first humanised triple GSS (GM-CSF, SCF, SDF1α) transgenic zebrafish that express multiple human hematopoietic-specific cytokines. By transplanting primary HSPCs and leukaemia cells, they showed that their model exhibits hematopoietic niche homing that more precisely represents the behaviour of human leukaemia. Further, this humanised model promoted survival, self-renewal and multi-lineage differentiation of HSPCs (Ref. Reference Rajan108). Although this platform, to our knowledge, has not yet been harnessed to study head and neck tumourigenesis and CSCs, the findings pave the way for a new modelling paradigm in humanised animal-based research.

Taken together, developing physiologically relevant ex vivo and in vivo models that faithfully recapitulate CSCs' niche and enable their characterisation and therapeutic targeting will facilitate the translation of basic discoveries to clinical practice in a timely manner. Such approaches are paramount for the development of novel drugs that can selectively target and destroy CSCs.

Conclusions, knowledge gaps and future perspectives

HNSCC encompass highly heterogeneous tumours, wherein CSCs seem to play multifaceted roles with regard to tumour progression, metastasis, clinical resistance and possible relapse. Although the CSC model has generated considerable controversy, recent technological advances, such as scRNA-seq, have led to unprecedented understanding of CSCs and their intricate interplay with other TME factors. However, much work remains to be done before this understanding can be translated into successful anticancer therapies, with the prognosis for HNSCC patients generally remaining dismal. To this end, several areas need to be elucidated, including, among others, pathways involved in CSC signalling, considering in particular oral microbiota, the molecular underpinning of CSC-driven drug resistance and immune cell mimicry. Another challenge is to develop more relevant models for CSC research. Despite the tremendous progress made with humanised animal platforms, they remain relatively immature with several shortcomings. For instance, besides cost and labour intensiveness, development of xenogeneic graft-versus-host disease (GVHD) is a major obstacle in such models. GVHD not only affects the number of viable experimental animals but also complicates data interpretation by overlaying a second set of diseases (Ref. Reference Greenblatt109). Nevertheless, these emerging alternative systems, including humanised zebrafish, remain a promising approach with a high potential for improvement to better identify CSCs and to catalogue the diverse cellular activities in HNSCC.

Lastly, but importantly, there is a pressing need to identify specific (i.e. exclusive) markers for CSCs in HNSCC. To our knowledge, there are no available universal markers that can label CSCs alone to date. On the contrary, several current markers are also expressed by other cell types, such as normal stem cells. In particular, the recognition of pEMT paradigm has made it more technically challenging to trace CSCs with such dynamic ‘identity-switching’ capacity. Thus, combining different putative labels of CSCs is recommended. Importantly, novel therapies need to be carefully designed to exclusively target this subpopulation of tumour cells without abrogating tissue stem cells or disrupting vital functions (Refs Reference Prince33, Reference Skidan and Steiniger102). In the therapeutic sense, anti-cancer vaccines targeting CSCs through dendritic cells and other immune cell types have shown promising results in HNSCC and could be further elaborated in the future (Ref. Reference Prince33). In conclusion, tumour cell plasticity and CSCs represent an exciting and expanding battleground in cancer research, with great implications for cancer therapy that are only beginning to be appreciated in head and neck oncology.

Acknowledgements

The authors gratefully acknowledge the funders of this study: The Jane and Aatos Erkko Foundation, the Finnish Dental Association (Apollonia) and the Cancer Society of Finland. Figures were created with BioRender.com.

Author contributions

A. S. researched data and wrote the article. T. S. reviewed the manuscript before submission.

Conflict of interest

None.

References

Yuan, S, Norgard, RJ and Stanger, BZ (2019) Cellular plasticity in cancer. Cancer Discovery 9, 837851.CrossRefGoogle ScholarPubMed
Boumahdi, S and de Sauvage, FJ (2020) The great escape: tumour cell plasticity in resistance to targeted therapy. Nature Reviews Drug Discovery 19, 3956.CrossRefGoogle ScholarPubMed
da Silva-Diz, V et al. (2018) Cancer cell plasticity: impact on tumor progression and therapy response. Seminars in Cancer Biology 53, 4858.CrossRefGoogle ScholarPubMed
Johnson, DE et al. (2020) Head and neck squamous cell carcinoma. Nature Reviews Disease Primers 6, 92.CrossRefGoogle ScholarPubMed
Metsäniitty, M et al. (2021) Oral microbiota – a new frontier in the pathogenesis and management of head and neck cancers. Cancers 14, 46.CrossRefGoogle ScholarPubMed
Sung, H et al. (2021) Global cancer statistics 2020: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA: A Cancer Journal for Clinicians 71, 209249.Google ScholarPubMed
Xing, DT et al. (2021) Recent research on combination of radiotherapy with targeted therapy or immunotherapy in head and neck squamous cell carcinoma: a review for radiation oncologists. Cancers 13, 5716.CrossRefGoogle ScholarPubMed
Muzaffar, J et al. (2021) Recent advances and future directions in clinical management of head and neck squamous cell carcinoma. Cancers 13, 338.CrossRefGoogle ScholarPubMed
Puram, SV et al. (2017) Single-cell transcriptomic analysis of primary and metastatic tumor ecosystems in head and neck cancer. Cell 171, 16111624.CrossRefGoogle ScholarPubMed
Prince, ME et al. (2007) Identification of a subpopulation of cells with cancer stem cell properties in head and neck squamous cell carcinoma. Proceedings of the National Academy of Sciences of the USA 104, 973978.CrossRefGoogle ScholarPubMed
Clay, MR et al. (2010) Single-marker identification of head and neck squamous cell carcinoma cancer stem cells with aldehyde dehydrogenase. Head & Neck 32, 11951201.CrossRefGoogle ScholarPubMed
Biddle, A et al. (2016) Phenotypic plasticity determines cancer stem cell therapeutic resistance in oral squamous cell carcinoma. EBioMedicine 4, 138145.CrossRefGoogle ScholarPubMed
Bedard, PL et al. (2013) Tumour heterogeneity in the clinic. Nature 501, 355364.CrossRefGoogle ScholarPubMed
Canning, M et al. (2019) Heterogeneity of the head and neck squamous cell carcinoma immune landscape and its impact on immunotherapy. Frontiers in Cell and Developmental Biology 7, 52.CrossRefGoogle ScholarPubMed
Shackleton, M et al. (2009) Heterogeneity in cancer: cancer stem cells versus clonal evolution. Cell 138, 822829.CrossRefGoogle ScholarPubMed
Fanelli, GN, Naccarato, AG and Scatena, C (2020) Recent advances in cancer plasticity: cellular mechanisms, surveillance strategies, and therapeutic optimization. Frontiers in Oncology 10, 569.CrossRefGoogle ScholarPubMed
Lapidot, T et al. (1994) A cell initiating human acute myeloid leukaemia after transplantation into SCID mice. Nature 367, 645648.CrossRefGoogle ScholarPubMed
Al-Hajj, M et al. (2003) Prospective identification of tumorigenic breast cancer cells. Proceedings of the National Academy of Sciences of the USA 100, 39833988.CrossRefGoogle ScholarPubMed
O'Brien, CA et al. (2007) A human colon cancer cell capable of initiating tumour growth in immunodeficient mice. Nature 445, 106110.CrossRefGoogle ScholarPubMed
Ludwig, N et al. (2019) CD44(+) tumor cells promote early angiogenesis in head and neck squamous cell carcinoma. Cancer Letters 467, 8595.CrossRefGoogle ScholarPubMed
Hujanen, R et al. (2021) Comparative analysis of vascular mimicry in head and neck squamous cell carcinoma: in vitro and in vivo approaches. Cancers 13, 4747.CrossRefGoogle ScholarPubMed
Boxberg, M et al. (2018) Immunohistochemical expression of CD44 in oral squamous cell carcinoma in relation to histomorphological parameters and clinicopathological factors. Histopathology 73, 559572.CrossRefGoogle ScholarPubMed
Wang, SJ and Bourguignon, LY (2011) Role of hyaluronan-mediated CD44 signaling in head and neck squamous cell carcinoma progression and chemoresistance. The American Journal of Pathology 178, 956963.CrossRefGoogle ScholarPubMed
Lee, Y et al. (2016) CD44+ cells in head and neck squamous cell carcinoma suppress T-cell-mediated immunity by selective constitutive and inducible expression of PD-L1. Clinical Cancer Research 22, 357135781.CrossRefGoogle ScholarPubMed
Byun, JY et al. (2022) Targeting HIF-1α/NOTCH1 pathway eliminates CD44+ cancer stem-like cell phenotypes, malignancy, and resistance to therapy in head and neck squamous cell carcinoma. Oncogene 41, 13521363.CrossRefGoogle ScholarPubMed
Wang, SJ et al. (2009) CD44 variant isoforms in head and neck squamous cell carcinoma progression. The Laryngoscope 119, 15181530.CrossRefGoogle ScholarPubMed
Chen, J et al. (2014) Significance of CD44 expression in head and neck cancer: a systemic review and meta-analysis. BMC Cancer 14, 15.CrossRefGoogle ScholarPubMed
Kamarajan, P et al. (2017) Head and neck squamous cell carcinoma metabolism draws on glutaminolysis, and stemness is specifically regulated by glutaminolysis via aldehyde dehydrogenase. Journal of Proteome Research 16, 13151326.CrossRefGoogle ScholarPubMed
Januchowski, R, Wojtowicz, K and Zabel, M (2013) The role of aldehyde dehydrogenase (ALDH) in cancer drug resistance. Biomedicine & Pharmacotherapy 67, 669680.CrossRefGoogle ScholarPubMed
Chen, YC et al. (2009) Aldehyde dehydrogenase 1 is a putative marker for cancer stem cells in head and neck squamous cancer. Biochemical and Biophysical Research Communications 385, 307313.CrossRefGoogle ScholarPubMed
Yu, CC et al. (2011) Bmi-1 regulates snail expression and promotes metastasis ability in head and neck squamous cancer-derived ALDH1 positive cells. Journal of Oncology 2011, 609259.CrossRefGoogle ScholarPubMed
Kim, J et al. (2017) Targeting aldehyde dehydrogenase activity in head and neck squamous cell carcinoma with a novel small molecule inhibitor. Oncotarget 8, 5234552356.CrossRefGoogle ScholarPubMed
Prince, MEP et al. (2016) Evaluation of the immunogenicity of ALDH(high) human head and neck squamous cell carcinoma cancer stem cells in vitro. Oral Oncology 59, 3042.CrossRefGoogle ScholarPubMed
Szafarowski, T et al. (2020) Assessment of cancer stem cell marker expression in primary head and neck squamous cell carcinoma shows prognostic value for aldehyde dehydrogenase (ALDH1A1). European Journal of Pharmacology 867, 172837.CrossRefGoogle ScholarPubMed
Vormittag, L et al. (2009) Co-expression of Bmi-1 and podoplanin predicts overall survival in patients with squamous cell carcinoma of the head and neck treated with radio(chemo)therapy. International Journal of Radiation Oncology, Biology, Physics 73, 913918.CrossRefGoogle ScholarPubMed
Sharaf, K et al. (2021) Discrimination of cancer stem cell markers ALDH1A1, BCL11B, BMI-1, and CD44 in different tissues of HNSCC patients. Current Oncology 28, 27632774.CrossRefGoogle ScholarPubMed
Chen, D et al. (2017) Targeting BMI1 + cancer stem cells overcomes chemoresistance and inhibits metastases in squamous cell carcinoma. Cell Stem Cell 20, 621634.CrossRefGoogle ScholarPubMed
Tanaka, T et al. (2016) Bmi1-positive cells in the lingual epithelium could serve as cancer stem cells in tongue cancer. Scientific Reports 6, 39386.CrossRefGoogle ScholarPubMed
Jia, L, Zhang, W and Wang, CY (2020) BMI1 inhibition eliminates residual cancer stem cells after PD1 blockade and activates antitumor immunity to prevent metastasis and relapse. Cell Stem Cell 27, 238253.CrossRefGoogle ScholarPubMed
Ghuwalewala, S et al. (2016) CD44(high)CD24(low) molecular signature determines the cancer stem cell and EMT phenotype in oral squamous cell carcinoma. Stem Cell Research 16, 405417.CrossRefGoogle ScholarPubMed
La Fleur, L, Johansson, AC and Roberg, K (2012) A CD44high/EGFRlow subpopulation within head and neck cancer cell lines shows an epithelial-mesenchymal transition phenotype and resistance to treatment. PLoS ONE 7, e44071.CrossRefGoogle ScholarPubMed
Yeung, KT and Yang, J (2017) Epithelial-mesenchymal transition in tumor metastasis. Molecular Oncology 11, 2839.CrossRefGoogle ScholarPubMed
Thiery, JP et al. (2009) Epithelial-mesenchymal transitions in development and disease. Cell 139, 871890.CrossRefGoogle ScholarPubMed
Nieto, MA et al. (2016) EMT: 2016. Cell 166, 2145.CrossRefGoogle ScholarPubMed
Sterz, CM et al. (2010) A basal-cell-like compartment in head and neck squamous cell carcinomas represents the invasive front of the tumor and is expressing MMP-9. Oral Oncology 46, 116122.CrossRefGoogle ScholarPubMed
Chowdhury, FN et al. (2019) Leading edge or tumor core: intratumor cancer stem cell niches in oral cavity squamous cell carcinoma and their association with stem cell function. Oral Oncology 98, 118124.CrossRefGoogle ScholarPubMed
Davis, SJ et al. (2010) Metastatic potential of cancer stem cells in head and neck squamous cell carcinoma. Archives of Otolaryngology – Head & Neck Surgery 136, 12601266.CrossRefGoogle ScholarPubMed
Johansson, AC et al. (2016) The relationship between EMT, CD44high/EGFRlow phenotype, and treatment response in head and neck cancer cell lines. Journal of Oral Pathology and Medicine 45, 640646.CrossRefGoogle Scholar
Yang, MH et al. (2010) Bmi1 is essential in Twist1-induced epithelial-mesenchymal transition. Nature Cell Biology 12, 982992.CrossRefGoogle ScholarPubMed
Gibbons, DL and Creighton, CJ (2018) Pan-cancer survey of epithelial-mesenchymal transition markers across the Cancer Genome Atlas. Developmental Dynamics 247, 555564.CrossRefGoogle ScholarPubMed
Bakir, B et al. (2020) EMT, MET, plasticity, and tumor metastasis. Trends in Cell Biology 30, 764776.CrossRefGoogle ScholarPubMed
Mimeault, M and Batra, SK (2013) Hypoxia-inducing factors as master regulators of stemness properties and altered metabolism of cancer- and metastasis-initiating cells. Journal of Cellular and Molecular Medicine 17, 3054.CrossRefGoogle ScholarPubMed
Lee, KE and Simon, MC (2012) From stem cells to cancer stem cells: HIF takes the stage. Current Opinion in Cell Biology 24, 232235.CrossRefGoogle ScholarPubMed
Sasabe, E et al. (2005) Mechanism of HIF-1alpha-dependent suppression of hypoxia-induced apoptosis in squamous cell carcinoma cells. Cancer Science 96, 394402.CrossRefGoogle ScholarPubMed
Moreno Roig, E et al. (2018) Prognostic role of hypoxia-inducible factor-2α tumor cell expression in cancer patients: a meta-analysis. Frontiers in Oncology 8, 224.CrossRefGoogle ScholarPubMed
Beasley, NJ et al. (2002) Hypoxia-inducible factors HIF-1alpha and HIF-2alpha in head and neck cancer: relationship to tumor biology and treatment outcome in surgically resected patients. Cancer Research 62, 24932497.Google ScholarPubMed
Díaz, B et al. (2013) Notch increases the shedding of HB-EGF by ADAM12 to potentiate invadopodia formation in hypoxia. The Journal of Cell Biology 201, 279292.CrossRefGoogle ScholarPubMed
Wiechec, E et al. (2022) Hypoxia induces radioresistance, epithelial-mesenchymal transition, cancer stem cell-like phenotype and changes in genes possessing multiple biological functions in head and neck squamous cell carcinoma. Oncology Reports 47, 58.CrossRefGoogle ScholarPubMed
Huang, CH et al. (2009) Regulation of membrane-type 4 matrix metalloproteinase by SLUG contributes to hypoxia-mediated metastasis. Neoplasia 11, 13711382.CrossRefGoogle ScholarPubMed
Liang, X et al. (2011) Hypoxia-inducible factor-1 alpha, in association with TWIST2 and SNIP1, is a critical prognostic factor in patients with tongue squamous cell carcinoma. Oral Oncology 47, 9297.CrossRefGoogle ScholarPubMed
Yeo, CD et al. (2017) The role of hypoxia on the acquisition of epithelial-mesenchymal transition and cancer stemness: a possible link to epigenetic regulation. The Korean Journal of Internal Medicine 32, 589599.CrossRefGoogle ScholarPubMed
Ribatti, D et al. (2019) Limitations of anti-angiogenic treatment of tumors. Translational Oncology 12, 981986.CrossRefGoogle ScholarPubMed
Ebos, JM et al. (2009) Accelerated metastasis after short-term treatment with a potent inhibitor of tumor angiogenesis. Cancer Cell 15, 232239.CrossRefGoogle ScholarPubMed
Pàez-Ribes, M et al. (2009) Antiangiogenic therapy elicits malignant progression of tumors to increased local invasion and distant metastasis. Cancer Cell 15, 220231.CrossRefGoogle ScholarPubMed
Seftor, RE et al. (2012) Tumor cell vasculogenic mimicry: from controversy to therapeutic promise. The American Journal of Pathology 181, 11151125.CrossRefGoogle ScholarPubMed
Salem, A and Salo, T (2021) Vasculogenic mimicry in head and neck squamous cell carcinoma-time to take notice. Frontiers in Oral Health 2, 666895.CrossRefGoogle ScholarPubMed
Hujanen, R et al. (2020) Vasculogenic mimicry: a promising prognosticator in head and neck squamous cell carcinoma and esophageal cancer? A systematic review and meta-analysis. Cells 9, 507. http://dx.doi.org/10.3390/cells9020507.CrossRefGoogle ScholarPubMed
Fan, YL et al. (2013) A new perspective of vasculogenic mimicry: EMT and cancer stem cells (Review). Oncology Letters 6, 11741180.CrossRefGoogle Scholar
Ricci-Vitiani, L et al. (2010) Tumour vascularization via endothelial differentiation of glioblastoma stem-like cells. Nature 468, 824828.CrossRefGoogle ScholarPubMed
Almahmoudi, R et al. (2021) The effect of interleukin-17F on vasculogenic mimicry in oral tongue squamous cell carcinoma. Cancer Science 112, 22232232.CrossRefGoogle ScholarPubMed
Wang, QS et al. (2018) FOXF2 deficiency permits basal-like breast cancer cells to form lymphangiogenic mimicry by enhancing the response of VEGF-C/VEGFR3 signaling pathway. Cancer Letters 420, 116126.CrossRefGoogle ScholarPubMed
Karinen, S et al. (2021) Tumour cells express functional lymphatic endothelium-specific hyaluronan receptor in vitro and in vivo: lymphatic mimicry promotes oral oncogenesis? Oncogenesis 10, 23.CrossRefGoogle ScholarPubMed
Karinen, S et al. (2022) The prognostic influence of lymphatic endothelium-specific hyaluronan receptor 1 in cancer: a systematic review. Cancer Science 113, 1727.CrossRefGoogle ScholarPubMed
Chanmee, T et al. (2015) Key roles of hyaluronan and its CD44 receptor in the stemness and survival of cancer stem cells. Frontiers in Oncology 5, 180.CrossRefGoogle ScholarPubMed
Gangoso, E et al. (2021) Glioblastomas acquire myeloid-affiliated transcriptional programs via epigenetic immunoediting to elicit immune evasion. Cell 184, 24542470.CrossRefGoogle ScholarPubMed
Gao, R et al. (2021) Cancer cell immune mimicry delineates onco-immunologic modulation. iScience 24, 103133.CrossRefGoogle ScholarPubMed
Zeng, Q et al. (2019) Synaptic proximity enables NMDAR signalling to promote brain metastasis. Nature 573, 526531.CrossRefGoogle ScholarPubMed
Neman, J et al. (2014) Human breast cancer metastases to the brain display GABAergic properties in the neural niche. Proceedings of the National Academy of Sciences of the USA 111, 984989.CrossRefGoogle Scholar
Fangfei, Qu et al. (2021) Neuronal mimicry generates an ecosystem critical for brain metastatic growth of SCLC. Preprint at bioRxiv.Google Scholar
Barrett, TF et al. (2018) Brain metastasis from squamous cell carcinoma of the head and neck: a review of the literature in the genomic era. Neurosurgical Focus 44, E11.CrossRefGoogle ScholarPubMed
Hanahan, D (2022) Hallmarks of cancer: new dimensions. Cancer Discovery 12, 3146.CrossRefGoogle ScholarPubMed
Ha, NH et al. (2015) Prolonged and repetitive exposure to Porphyromonas gingivalis increases aggressiveness of oral cancer cells by promoting acquisition of cancer stem cell properties. Tumour Biology 36, 99479960.CrossRefGoogle ScholarPubMed
Binder Gallimidi, A et al. (2015) Periodontal pathogens Porphyromonas gingivalis and Fusobacterium nucleatum promote tumor progression in an oral-specific chemical carcinogenesis model. Oncotarget 6, 2261322623.CrossRefGoogle Scholar
Abdulkareem, AA et al. (2018) Periodontal pathogens promote epithelial-mesenchymal transition in oral squamous carcinoma cells in vitro. Cell Adhesion & Migration 12, 127137.Google ScholarPubMed
Lun, SW et al. (2012) CD44+ cancer stem-like cells in EBV-associated nasopharyngeal carcinoma. PLoS ONE 7, e52426.CrossRefGoogle ScholarPubMed
Kondo, S et al. (2011) Epstein-Barr virus latent membrane protein 1 induces cancer stem/progenitor-like cells in nasopharyngeal epithelial cell lines. Journal of Virology 85, 1125511264.CrossRefGoogle ScholarPubMed
Lechner, M et al. (2022) HPV-associated oropharyngeal cancer: epidemiology, molecular biology and clinical management. Nature Reviews. Clinical Oncology 19, 306327.CrossRefGoogle ScholarPubMed
Tang, AL et al. (2013) Head and neck cancer stem cells: the effect of HPV – an in vitro and mouse study. Otolaryngology – Head and Neck Surgery 149, 252260.CrossRefGoogle Scholar
Zhang, M et al. (2014) Elevated intrinsic cancer stem cell population in human papillomavirus-associated head and neck squamous cell carcinoma. Cancer 120, 9921001.CrossRefGoogle ScholarPubMed
Lee, SH et al. (2015) Human papillomavirus 16 (HPV16) enhances tumor growth and cancer stemness of HPV-negative oral/oropharyngeal squamous cell carcinoma cells via miR-181 regulation. Papillomavirus Research 1, 116125.CrossRefGoogle ScholarPubMed
Reid, P et al. (2020) Influence of the human papillomavirus on the radio-responsiveness of cancer stem cells in head and neck cancers. Scientific Reports 10, 2716.CrossRefGoogle ScholarPubMed
Langhans, SA (2018) Three-dimensional in vitro cell culture models in drug discovery and drug repositioning. Frontiers in Pharmacology 9, 6.CrossRefGoogle ScholarPubMed
Zhang, C et al. (2020) 3D culture technologies of cancer stem cells: promising ex vivo tumor models. Journal of Tissue Engineering 11, 2041731420933407.CrossRefGoogle ScholarPubMed
Krishnamurthy, S and Nör, JE (2013) Orosphere assay: a method for propagation of head and neck cancer stem cells. Head & Neck 35, 10151021.CrossRefGoogle ScholarPubMed
Aramini, B et al. (2022) Dissecting tumor growth: the role of cancer stem cells in drug resistance and recurrence. Cancers 14, 976.CrossRefGoogle ScholarPubMed
Pamarthy, S and Sabaawy, HE (2021) Patient derived organoids in prostate cancer: improving therapeutic efficacy in precision medicine. Molecular Cancer 20, 125.CrossRefGoogle ScholarPubMed
Ledford, H (2011) Translational research: 4 ways to fix the clinical trial. Nature 477, 526528.CrossRefGoogle ScholarPubMed
Salo, T et al. (2015) A novel human leiomyoma tissue derived matrix for cell culture studies. BMC Cancer 15, 981.CrossRefGoogle ScholarPubMed
Teo, AL, Mantalaris, A and Lim, M (2014) Influence of culture pH on proliferation and cardiac differentiation of murine embryonic stem cells. Biochemical Engineering Journal 90, 815.CrossRefGoogle Scholar
Naakka, E et al. (2019) Fully human tumor-based matrix in three-dimensional spheroid invasion assay. Journal of Visualized Experiments 7, 147.Google Scholar
Tuomainen, K et al. (2019) Human tumor-derived matrix improves the predictability of head and neck cancer drug testing. Cancers 12, 92.CrossRefGoogle ScholarPubMed
Skidan, I and Steiniger, SC (2014) In vivo models for cancer stem cell research: a practical guide for frequently used animal models and available biomarkers. Journal of Physiology and Pharmacology 65, 157169.Google ScholarPubMed
Kelly, PN et al. (2007) Tumor growth need not be driven by rare cancer stem cells. Science 317, 337.CrossRefGoogle Scholar
Morton, JJ et al. (2016) XactMice: humanizing mouse bone marrow enables microenvironment reconstitution in a patient-derived xenograft model of head and neck cancer. Oncogene 35, 290300.CrossRefGoogle Scholar
Morton, JJ et al. (2018) Dual use of hematopoietic and mesenchymal stem cells enhances engraftment and immune cell trafficking in an allogeneic humanized mouse model of head and neck cancer. Molecular Carcinogenesis 57, 16511663.CrossRefGoogle Scholar
Wahab, A et al. (2021) The effect of fascin 1 inhibition on head and neck squamous cell carcinoma cells. European Journal of Oral Sciences 129, e12819.CrossRefGoogle ScholarPubMed
Al-Samadi, A et al. (2019) PCR-based zebrafish model for personalised medicine in head and neck cancer. Journal of Translational Medicine 17, 235.CrossRefGoogle ScholarPubMed
Rajan, V et al. (2020) Humanized zebrafish enhance human hematopoietic stem cell survival and promote acute myeloid leukemia clonal diversity. Haematologica 105, 23912399.CrossRefGoogle ScholarPubMed
Greenblatt, MB et al. (2012) Graft versus host disease in the bone marrow, liver and thymus humanized mouse model. PLoS ONE 7, e44664.CrossRefGoogle ScholarPubMed
Yu, CC et al. (2016) Targeting CD133 in the enhancement of chemosensitivity in oral squamous cell carcinoma-derived side population cancer stem cells. Head & Neck 38(suppl. 1), E231E238.CrossRefGoogle ScholarPubMed
Oliveira, LR et al. (2014) CD44+/CD133+ immunophenotype and matrix metalloproteinase-9: influence on prognosis in early-stage oral squamous cell carcinoma. Head & Neck 36, 17181726.CrossRefGoogle ScholarPubMed
Zhang, Q et al. (2010) A subpopulation of CD133(+) cancer stem-like cells characterized in human oral squamous cell carcinoma confer resistance to chemotherapy. Cancer Letters 289, 151160.CrossRefGoogle ScholarPubMed
Modur, V et al. (2016) CD24 expression may play a role as a predictive indicator and a modulator of cisplatin treatment response in head and neck squamous cellular carcinoma. PLoS ONE 11, e0156651.CrossRefGoogle Scholar
Zimmerer, RM et al. (2017) CD24+ tumor-initiating cells from oral squamous cell carcinoma induce initial angiogenesis in vivo. Microvascular Research 112, 101108.CrossRefGoogle ScholarPubMed
Han, J et al. (2014) Identification and characterization of cancer stem cells in human head and neck squamous cell carcinoma. BMC Cancer 14, 173.CrossRefGoogle ScholarPubMed
Murillo-Sauca, O et al. (2014) CD271 is a functional and targetable marker of tumor-initiating cells in head and neck squamous cell carcinoma. Oncotarget 5, 68546866.CrossRefGoogle ScholarPubMed
Elkashty, OA et al. (2020) Cancer stem cells enrichment with surface markers CD271 and CD44 in human head and neck squamous cell carcinomas. Carcinogenesis 41, 458466.CrossRefGoogle ScholarPubMed
Chung, MK et al. (2018) CD271 confers an invasive and metastatic phenotype of head and neck squamous cell carcinoma through the upregulation of slug. Clinical Cancer Research 24, 674683.CrossRefGoogle ScholarPubMed
Joshua, B et al. (2012) Frequency of cells expressing CD44, a head and neck cancer stem cell marker: correlation with tumor aggressiveness. Head & Neck 34, 4249.CrossRefGoogle ScholarPubMed
Irani, S and Dehghan, A (2018) The expression and functional significance of vascular endothelial-cadherin, CD44, and vimentin in oral squamous cell carcinoma. Journal of International Society of Preventive & Community Dentistry 8, 110117.CrossRefGoogle ScholarPubMed
Sun, S and Wang, Z (2011) Head neck squamous cell carcinoma c-Met⁺ cells display cancer stem cell properties and are responsible for cisplatin-resistance and metastasis. International Journal of Cancer 129, 23372348.CrossRefGoogle ScholarPubMed
Lim, YC et al. (2012) Overexpression of c-Met promotes invasion and metastasis of small oral tongue carcinoma. Oral Oncology 48, 11141119.CrossRefGoogle ScholarPubMed
Zhao, D et al. (2011) Intratumoral c-Met expression is associated with vascular endothelial growth factor C expression, lymphangiogenesis, and lymph node metastasis in oral squamous cell carcinoma: implications for use as a prognostic marker. Human Pathology 42, 15141523.CrossRefGoogle ScholarPubMed
Lüttich, L et al. (2021) Tyrosine kinase c-MET as therapeutic target for radiosensitization of head and neck squamous cell carcinomas. Cancers 13, 1865.CrossRefGoogle ScholarPubMed
Vsiansky, V et al. (2018) Prognostic role of c-Met in head and neck squamous cell cancer tissues: a meta-analysis. Scientific Reports 8, 10370.CrossRefGoogle ScholarPubMed
Koo, BS et al. (2015) Oct4 is a critical regulator of stemness in head and neck squamous carcinoma cells. Oncogene 34, 23172324.CrossRefGoogle ScholarPubMed
Routila, J et al. (2022) Cisplatin overcomes radiotherapy resistance in OCT4-expressing head and neck squamous cell carcinoma. Oral Oncology 127, 105772.CrossRefGoogle ScholarPubMed
Nathansen, J et al. (2021) Oct4 confers stemness and radioresistance to head and neck squamous cell carcinoma by regulating the homologous recombination factors PSMC3IP and RAD54L. Oncogene 40, 42144228.CrossRefGoogle ScholarPubMed
Figure 0

Fig. 1. Cancer stem cells (CSCs) in head and neck squamous cell carcinoma. CSCs represent a small subpopulation of tumour cells with the following main features: (a) self-renewal, (b) transdifferentiation and phenotypic switching, (c) tumour initiation (tumourigenesis) when transplanted into an animal host, (d) high invasive and metastatic potential, and (e) ability to develop anti-tumour drug resistance.

Figure 1

Table 1. Common markers of cancer stem cells in head and neck cancers

Figure 2

Fig. 2. Examples of models used to assess the features of cancer stem cells (CSCs). Ex vivo models are broadly categorised as follows: (a) scaffold-free cultures, such as hanging drops, low-attachment plates and suspension cultures, to assess the formation of tumourspheres, and (b) scaffold-based models, including the use of biological hydrogels such as Matrigel and Myogel, for three-dimensional assays. (c) In vivo models are mainly used to assess the capacity of CSC-like cells to initiate and sustain new growths (and hence, they are also termed tumour-initiating/propagating cells). The most commonly used models include non-obese diabetic/severe combined immunodeficient (NOD/SCID) and NOD/SCID IL2Rγnull mice. (d) Humanised animal models (e.g. XactMice and GSS zebrafish) represent promising potential platforms to assess the human CSC hypothesis in a more relevant niche encompassing human hematopoietic stem and progenitor cells (HSPCs), which are able to recreate the original tumour microenvironment observed clinically. HSPCs are expanded ex vivo and injected into the NOD/SCID gamma mice. (e) In addition, zebrafish larvae may represent an attractive and cost-effective model in CSC research, particularly for assessing tumour progression and drug resistance.