standR: spatial transcriptomic analysis for GeoMx DSP data.

To gain a better understanding of the complexity of gene expression in normal and diseased tissues it is important to account for the spatial context and identity of cells in situ. State-of-the-art spatial profiling technologies, such as the Nanostring GeoMx Digital Spatial Profiler (DSP), now allow quantitative spatially resolved measurement of the transcriptome in tissues. However, the bioinformatics pipelines currently used to analyse GeoMx data often fail to successfully account for the technical variability within the data and the complexity of experimental designs, thus limiting the accuracy and reliability of the subsequent analysis. Carefully designed quality control workflows, that include in-depth experiment-specific investigations into technical variation and appropriate adjustment for such variation can address this issue. Here, we present standR, an R/Bioconductor package that enables an end-to-end analysis of GeoMx DSP data. With four case studies from previously published experiments, we demonstrate how the standR workflow can enhance the statistical power of GeoMx DSP data analysis and how the application of standR enables scientists to develop in-depth insights into the biology of interest.

Metabolomics at the tumor microenvironment interface: Decoding cellular conversations.

Cancer heterogeneity remains a significant challenge for effective cancer treatments. Altered energetics is one of the hallmarks of cancer and influences tumor growth and drug resistance. Studies have shown that heterogeneity exists within the metabolic profile of tumors, and personalized-combination therapy with relevant metabolic interventions could improve patient response. Metabolomic studies are identifying novel biomarkers and therapeutic targets that have improved treatment response. The spatial location of elements in the tumor microenvironment are becoming increasingly important for understanding disease progression. The evolution of spatial metabolomics analysis now allows scientists to deeply understand how metabolite distribution contributes to cancer biology. Recently, these techniques have spatially resolved metabolite distribution to a subcellular level. It has been proposed that metabolite mapping could improve patient outcomes by improving precision medicine, enabling earlier diagnosis and intraoperatively identifying tumor margins. This review will discuss how altered metabolic pathways contribute to cancer progression and drug resistance and will explore the current capabilities of spatial metabolomics technologies and how these could be integrated into clinical practice to improve patient outcomes.

Inhibition of Aurora B kinase (AURKB) enhances the effectiveness of 5-fluorouracil chemotherapy against colorectal cancer cells.

BACKGROUND: 5-Fluorouracil (5-FU) remains a core component of systemic therapy for colorectal cancer (CRC). However, response rates remain low, and development of therapy resistance is a primary issue. Combinatorial strategies employing a second agent to augment the therapeutic effect of chemotherapy is predicted to reduce the incidence of treatment resistance and increase the durability of response to therapy. METHODS: Here, we employed quantitative proteomics approaches to identify novel druggable proteins and molecular pathways that are deregulated in response to 5-FU, which might serve as targets to improve sensitivity to chemotherapy. Drug combinations were evaluated using 2D and 3D CRC cell line models and an ex vivo culture model of a patient-derived tumour. RESULTS: Quantitative proteomics identified upregulation of the mitosis-associated protein Aurora B (AURKB), within a network of upregulated proteins, in response to a 24 h 5-FU treatment. In CRC cell lines, AURKB inhibition with the dihydrogen phosphate prodrug AZD1152, markedly improved the potency of 5-FU in 2D and 3D in vitro CRC models. Sequential treatment with 5-FU then AZD1152 also enhanced the response of a patient-derived CRC cells to 5-FU in ex vivo cultures. CONCLUSIONS: AURKB inhibition may be a rational approach to augment the effectiveness of 5-FU chemotherapy in CRC.

Tissue biomarkers of immune checkpoint inhibitor therapy.

Cancer immunotherapy has been rejuvenated by the growing understanding of the immune system's role in tumor activity over the past two decades. During cancer initiation and progression, tumor cells employ various mechanisms that resemble peripheral immune tolerance to evade the antitumor responses of the immune system. Immune checkpoint molecules are the major mechanism of immune resistance that are exploited by tumor cells to inhibit T-cell activation and suppress immune responses. The targeting of immune checkpoint pathways has led to substantial improvements in survival rates in a number of solid cancers. However, a lack of understanding of the heterogeneity of the tumor microenvironment (TME) has resulted in inefficient therapy responses. A greater understanding of the TME is needed to identify patients likely to respond, and those that will have resistance to immune checkpoint inhibitors (ICIs). Advancement in spatial single-cell technologies has allowed deeper insight into the phenotypic and functional diversities of cells in the TME. In this review, we provide an overview of ICI biomarkers and highlight how high-dimensional spatially resolved, single-cell approaches provide deep molecular insights into the TME and allow for the discovery of biomarkers of clinical benefit.

Spatial resolution of the head and neck cancer tumor microenvironment to identify tumor and stromal features associated with therapy response.

Head and neck cancer (HNC) is the seventh most common cancer globally, resulting in 440 000 deaths per year. While there have been advancements in chemoradiotherapy and surgery, relapse occurs in more than half of HNCs, and these patients have a median survival of 10 months and a 2-year survival of < 20%. Only a subset of patients displays durable benefits from immunotherapies in metastatic and recurrent HNC, making it critical to understand the tumor microenvironment (TME) underpinning therapy responses in HNC. To recognize biological differences within the TME that may be predictive of immunotherapy response, we applied cutting-edge geospatial whole-transcriptome profiling (NanoString GeoMx Digital Spatial Profiler) and spatial proteomics profiling (Akoya PhenoCycler-Fusion) on a tumor microarray consisting of 25 cores from 12 patients that included 4 immunotherapy-unresponsive (8 cores) and 2 immunotherapy-responsive patients (5 cores), as well as 6 immunotherapy naïve patients (12 cores). Through high-plex, regional-based transcriptomic mapping of the tumor and TME, pathways involved with the complement system and hypoxia were identified to be differentially expressed in patients who went on to experience a poor immunotherapy response. Single-cell, targeted proteomic analysis found that immune cell infiltration of the cancer cell mass and interactions of CD8 T cells with tumor and other immune cells were associated with positive immunotherapy response. The relative abundance of specific tumor phenotypes and their interactions with various immune cells was identified to be different between response groups. This study demonstrates how spatial transcriptomics and proteomics can resolve novel alterations in the TME of HNC that may contribute to therapy sensitivity and resistance.

Mapping the Spatial Dynamics of the CD4+ T Cell Spectrum in Classical Hodgkin Lymphoma.

As around 25% to 30% of classical Hodgkin lymphoma (cHL) patients with advanced stages do not respond to standard therapies, the tumor microenvironment of cHL is one avenue that may be explored with the aim of improving risk stratification. CD4+ T cells are thought to be one of the main cell types in the tumor microenvironment. However, few immune signatures have been studied, and many of these lack related spatial data. Thus, our aim is to spatially resolve the CD4+ T cell subtypes that influence cHL outcome, depicting new immune signatures or transcriptional patterns that are in crosstalk with the tumor cells. This study was conducted using the NanoString GeoMx digital spatial profiling technology, based on the selection of distinct functional areas of patients' tissues followed by gene-expression profiling. The goals were to assess the differences in CD4+ T cell populations between tumor-rich and immune-predominant areas defined by different CD30 and PD-L1 expression levels and seek correlations with clinical metadata. Our results depict a complex map of CD4+ T cells with different functions and differentiation states that are enriched at distinct locations, the flux of cytokines and chemokines that could be related to these, and the specific relationships with the clinical outcome.

Spatial insights into immunotherapy response in non-small cell lung cancer (NSCLC) by multiplexed tissue imaging.

The spatial localisation of immune cells within tumours are key to understand the intercellular communications that can dictate clinical outcomes. Here, we demonstrate an analysis pipeline for highly multiplexed CODEX data to phenotype and profile spatial features and interactions in NSCLC patients that subsequently received PD1 axis immunotherapy. We found that regulatory T cells (Tregs) are enriched in non-responding patients and this was consistent with their localization within stromal and peripheral tumour-margins. Proximity-based interactions between Tregs and both monocytes (p = 0.009) and CD8+ T cells (p = 0.009) were more frequently found in non-responding patients, while macrophages were more frequently located in proximity to HLADR+ tumour cells (p = 0.01) within responding patients. Cellular neighbourhoods analysis indicated that both macrophages (p = 0.003) and effector CD4+ T cells (p = 0.01) in mixed tumour neighbourhoods, as well as CD8+ T cells (p = 0.03) in HLADR+ tumour neighbourhoods were associated with favorable clinical response. Evaluation of the inferred regulatory functions between immune cells relative to the tumour suggested that macrophages exhibit an immunosuppressive phenotype against both CD4+ and CD8+ T cells, and that this association scores more highly in ICI refractory patients. These spatial patterns are associated with overall survival in addition to ICI response and may thus indicate features for the functional understanding of the tumour microenvironment.

Spatial dynamics of tertiary lymphoid aggregates in head and neck cancer: insights into immunotherapy response.

BACKGROUND: Recurrent/metastatic head and neck squamous cell carcinoma (R/M HNSCC) generally has a poor prognosis for patients with limited treatment options. While incorporating immune checkpoint inhibitors (ICIs) has now become the standard of care, the efficacy is variable, with only a subset of patients responding. The complexity of the tumor microenvironment (TME) and the role of tertiary lymphoid structures (TLS) have emerged as critical determinants for immunotherapeutic response. METHODS: In this study, we analyzed two independently collected R/M HNSCC patient tissue cohorts to better understand the role of TLS in response to ICIs. Utilizing a multi-omics approach, we first performed targeted proteomic profiling using the Nanostring GeoMx Digital Spatial Profiler to quantify immune-related protein expression with spatial resolution. This was further characterized by spatially resolved whole transcriptome profiling of TLSs and germinal centers (GCs). Deeper single-cell resolved proteomic profiling of the TLSs was performed using the Akoya Biosciences Phenocycler Fusion platform. RESULTS: Our proteomic analysis revealed the presence of T lymphocyte markers, including CD3, CD45, and CD8, expressing cells and upregulation of immune checkpoint marker PD-L1 within tumor compartments of patients responsive to ICIs, indicative of 'hot tumor' phenotypes. We also observed the presence of antigen-presenting cells marked by expression of CD40, CD68, CD11c, and CD163 with upregulation of antigen-presentation marker HLA-DR, in patients responding to ICIs. Transcriptome analysis of TLS and GCs uncovered a marked elevation in the expression of genes related to immune modulation, diverse immune cell recruitment, and a potent interferon response within the TLS structure. Notably, the distribution of TLS-tumor distance was found to be significantly different across response groups (H = 9.28, p = 0.026). The proximity of TLSs to tumor cells was found to be a critical indicator of ICI response, implying that patients with TLSs located further from tumor cells have worse outcomes. CONCLUSION: The study underscores the multifaceted role of TLSs in modulating the immunogenic landscape of the TME in R/M HNSCC, likely influencing the efficacy of ICIs. Spatially resolved multi-omics approaches offer valuable insights into potential biomarkers for ICI response and highlight the importance of profiling the TME complexity when developing therapeutic strategies and patient stratification.

Immunotherapeutic targets in non-small cell lung cancer.

Non-small cell lung cancer (NSCLC) is one of the most common types of cancer in the world and has a 5-year survival rate of ~20%. Immunotherapies have shown promising results leading to durable responses, however, they are only effective for a subset of patients. To determine the best therapeutic approach, a thorough and in-depth profiling of the tumour microenvironment (TME) is required. The TME is a complex network of cell types that form an interconnected network, promoting tumour cell initiation, growth and dissemination. The stroma, immune cells and endothelial cells that comprise the TME generate a plethora of cytotoxic or cytoprotective signalling pathways. In this review, we discuss immunotherapeutic targets in NSCLC tumours and how the TME may influence patients' response to immunotherapy.

Multi-omic and spatial dissection of immunotherapy response groups in non-small cell lung cancer.

The composition and activation status of the cellular milieu contained within the tumour microenvironment (TME) is becoming increasingly recognized as a driving factor for immunotherapy response. Here, we employed multiplex immunohistochemistry (mIHC), and digital spatial profiling (DSP) to capture the targeted immune proteome and transcriptome of tumour and TME compartments from an immune checkpoint inhibitor (ICI)-treated (n = 41) non-small cell lung cancer (NSCLC) patient cohort. We demonstrate by mIHC that the interaction of CD68+ macrophages with PD1+ , FoxP3+ cells is enriched in ICI refractory tumours (p = 0.012). Patients responsive to ICI therapy expressed higher levels of IL2 receptor alpha (CD25, p = 0.028) within their tumour compartments, which corresponded with increased IL2 mRNA (p = 0.001) within their stroma. In addition, stromal IL2 mRNA levels positively correlated with the expression of pro-apoptotic markers cleaved caspase 9 (p = 2e-5 ) and BAD (p = 5.5e-4 ) and negatively with levels of memory marker, CD45RO (p = 7e-4 ). Immuno-inhibitory markers CTLA-4 (p = 0.021) and IDO-1 (p = 0.023) were suppressed in ICI-responsive patients. Tumour expression of CD44 was depleted in the responsive patients (p = 0.02), while higher stromal expression of one of its ligands, SPP1 (p = 0.008), was observed. Cox survival analysis also indicated tumour CD44 expression was associated with poorer prognosis (hazard ratio [HR] = 1.61, p = 0.01), consistent with its depletion in ICI-responsive patients. Through multi-modal approaches, we have dissected the characteristics of NSCLC immunotherapy treatment groups and provide evidence for the role of several markers including IL2, CD25, CD44 and SPP1 in the efficacy of current generations of ICI therapy.

A robust platform for integrative spatial multi-omics analysis to map immune responses to SARS-CoV-2 infection in lung tissues.

The SARS-CoV-2 (COVID-19) virus has caused a devastating global pandemic of respiratory illness. To understand viral pathogenesis, methods are available for studying dissociated cells in blood, nasal samples, bronchoalveolar lavage fluid and similar, but a robust platform for deep tissue characterization of molecular and cellular responses to virus infection in the lungs is still lacking. We developed an innovative spatial multi-omics platform to investigate COVID-19-infected lung tissues. Five tissue-profiling technologies were combined by a novel computational mapping methodology to comprehensively characterize and compare the transcriptome and targeted proteome of virus infected and uninfected tissues. By integrating spatial transcriptomics data (Visium, GeoMx and RNAScope) and proteomics data (CODEX and PhenoImager HT) at different cellular resolutions across lung tissues, we found strong evidence for macrophage infiltration and defined the broader microenvironment surrounding these cells. By comparing infected and uninfected samples, we found an increase in cytokine signalling and interferon responses at different sites in the lung and showed spatial heterogeneity in the expression level of these pathways. These data demonstrate that integrative spatial multi-omics platforms can be broadly applied to gain a deeper understanding of viral effects on cellular environments at the site of infection and to increase our understanding of the impact of SARS-CoV-2 on the lungs.

Transcriptomic profiling of cardiac tissues from SARS-CoV-2 patients identifies DNA damage.

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is known to present with pulmonary and extra-pulmonary organ complications. In comparison with the 2009 pandemic (pH1N1), SARS-CoV-2 infection is likely to lead to more severe disease, with multi-organ effects, including cardiovascular disease. SARS-CoV-2 has been associated with acute and long-term cardiovascular disease, but the molecular changes that govern this remain unknown. In this study, we investigated the host transcriptome landscape of cardiac tissues collected at rapid autopsy from seven SARS-CoV-2, two pH1N1, and six control patients using targeted spatial transcriptomics approaches. Although SARS-CoV-2 was not detected in cardiac tissue, host transcriptomics showed upregulation of genes associated with DNA damage and repair, heat shock, and M1-like macrophage infiltration in the cardiac tissues of COVID-19 patients. The DNA damage present in the SARS-CoV-2 patient samples, were further confirmed by γ-H2Ax immunohistochemistry. In comparison, pH1N1 showed upregulation of interferon-stimulated genes, in particular interferon and complement pathways, when compared with COVID-19 patients. These data demonstrate the emergence of distinct transcriptomic profiles in cardiac tissues of SARS-CoV-2 and pH1N1 influenza infection supporting the need for a greater understanding of the effects on extra-pulmonary organs, including the cardiovascular system of COVID-19 patients, to delineate the immunopathobiology of SARS-CoV-2 infection, and long term impact on health.

Liquid Biopsy Snapshots of Key Phosphoproteomic Pathways in Lung Cancer Patients for Diagnosis and Therapy Monitoring.

Phosphorylation is a post-translational modification in proteins that changes protein conformation and activity for regulating signal transduction pathways. This mechanism is frequently impaired in lung cancer, resulting in permanently active constitutive phosphorylation to initiate tumor growth and/or reactivate pathways in response to therapy. We developed a multiplexed phosphoprotein analyzer chip (MPAC) that enables rapid (detection time: 5 min) and sensitive (LOD: 2 pg/µL) detection of protein phosphorylation and presents phosphoproteomic profiling of major phosphorylation pathways in lung cancer. We monitored phosphorylated receptors and downstream proteins involved in mitogen-activated protein kinase (MAPK) and PI3K/AKT/mTOR pathways in lung cancer cell line models and patient-derived extracellular vesicles (EV). Using kinase inhibitor drugs in cell line models, we found that the drug can inhibit the phosphorylation and/or activation of the kinase pathway. We then generated a phosphorylation heatmap by EV phosphoproteomic profiling of plasma samples isolated from 36 lung cancer patients and 8 noncancer individuals. The heatmap showed a clear difference between the noncancer and cancer samples and identify the specific proteins that are activated in the cancer samples. Our data also showed that MPAC could monitor immunotherapy responses by assessment of the phosphorylation states of the proteins, particularly for PD-L1. Finally, with a longitudinal study, we found that the phosphorylation levels of the proteins were indicative of a positive response to therapy. We believe that this study will lead to personalized treatment by providing a better understanding of the active and resistant pathways and will provide a tool for selecting combined and targeted therapies for precision medicine.

The seductive allure of spatial biology: accelerating new discoveries in the life sciences.

Spatial biology is a rapidly developing field which enables the visualization of protein and transcriptomic data while preserving tissue context and architecture. Initially used in discovery, there is growing promise for translational and diagnostic assay developments. Immediate applications are in precision medicine, such as being able to match patients to optimal therapies through better understanding the tumor microenvironment. However, it also has ramifications for many other disciplines (e.g. immunology, cancer, infectious disease and digital pathology). With increasingly massive data sets being generated, data storage, curation, analysis and sharing require more computational approaches and artificial intelligence-powered tools to fully utilize spatial tools. Here, we discuss spatial biology as an important convergent science approach to tackling complex global challenges in areas such as health.

Genomic communication via circulating extracellular vesicles and long-term health consequences of COVID-19.

COVID-19 continues to affect an unprecedented number of people with the emergence of new variants posing a serious challenge to global health. There is an expansion of knowledge in understanding the pathogenesis of Coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), and the impact of the acute disease on multiple organs. In addition, growing evidence reports that the impact of COVID-19 on different organs persists long after the recovery phase of the disease, leading to long-term consequences of COVID-19. These long-term consequences involve pulmonary as well as extra-pulmonary sequelae of the disease. Noteably, recent research has shown a potential association between COVID-19 and change in the molecular cargo of extracellular vesicles (EVs). EVs are vesicles released by cells and play an important role in cell communication by transfer of bioactive molecules between cells. Emerging evidence shows a strong link between EVs and their molecular cargo, and regulation of metabolism in health and disease. This review focuses on current knowledge about EVs and their potential role in COVID-19 pathogenesis, their current and future implications as tools for biomarker and therapeutic development and their possible effects on long-term impact of COVID-19.

Profiling of lung SARS-CoV-2 and influenza virus infection dissects virus-specific host responses and gene signatures.

BACKGROUND: The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) which emerged in late 2019 has spread globally, causing a pandemic of respiratory illness designated coronavirus disease 2019 (COVID-19). A better definition of the pulmonary host response to SARS-CoV-2 infection is required to understand viral pathogenesis and to validate putative COVID-19 biomarkers that have been proposed in clinical studies. METHODS: Here, we use targeted transcriptomics of formalin-fixed paraffin-embedded tissue using the NanoString GeoMX platform to generate an in-depth picture of the pulmonary transcriptional landscape of COVID-19, pandemic H1N1 influenza and uninfected control patients. RESULTS: Host transcriptomics showed a significant upregulation of genes associated with inflammation, type I interferon production, coagulation and angiogenesis in the lungs of COVID-19 patients compared to non-infected controls. SARS-CoV-2 was non-uniformly distributed in lungs (emphasising the advantages of spatial transcriptomics) with the areas of high viral load associated with an increased type I interferon response. Once the dominant cell type present in the sample, within patient correlations and patient-patient variation, had been controlled for, only a very limited number of genes were differentially expressed between the lungs of fatal influenza and COVID-19 patients. Strikingly, the interferon-associated gene IFI27, previously identified as a useful blood biomarker to differentiate bacterial and viral lung infections, was significantly upregulated in the lungs of COVID-19 patients compared to patients with influenza. CONCLUSION: Collectively, these data demonstrate that spatial transcriptomics is a powerful tool to identify novel gene signatures within tissues, offering new insights into the pathogenesis of SARS-COV-2 to aid in patient triage and treatment.

Understanding the tumor microenvironment for effective immunotherapy.

Advances in immunotherapy have led to durable and long-term benefits in a subset of patients across a number of solid tumor types. Understanding of the subsets of patients that respond to immune checkpoint inhibitors at the cellular level, and in the context of their tumor microenvironment (TME) is becoming increasingly important. The TME is composed of a heterogeneous milieu of tumor and immune cells. The immune landscape of the TME can inhibit or promote tumor initiation and progression; thus, a deeper understanding of tumor immunity is necessary to develop immunotherapeutic strategies. Recent developments have focused on characterizing the TME immune contexture (type, density, and function) to discover mechanisms and biomarkers that may predict treatment outcomes. This has, in part, been powered by advancements in spatial characterization technologies. In this review article, we address the role of specific immune cells within the TME at various stages of tumor progression and how the immune contexture determinants affecting tumor growth are used therapeutically.

Circulating biomarkers in patients with glioblastoma.

Gliomas are the most common tumours of the central nervous system and the most aggressive form is glioblastoma (GBM). Despite advances in treatment, patient survival remains low. GBM diagnosis typically relies on imaging techniques and postoperative pathological diagnosis; however, both procedures have their inherent limitations. Imaging modalities cannot differentiate tumour progression from treatment-related changes that mimic progression, known as pseudoprogression, which might lead to misinterpretation of therapy response and delay clinical interventions. In addition to imaging limitations, tissue biopsies are invasive and most of the time cannot be performed over the course of treatment to evaluate 'real-time' tumour dynamics. In an attempt to address these limitations, liquid biopsies have been proposed in the field. Blood sampling is a minimally invasive procedure for a patient to endure and could provide tumoural information to guide therapy. Tumours shed tumoural content, such as circulating tumour cells, cell-free nucleic acids, proteins and extracellular vesicles, into the circulation, and these biomarkers are reported to cross the blood-brain barrier. The use of liquid biopsies is emerging in the field of GBM. In this review, we aim to summarise the current literature on circulating biomarkers, namely circulating tumour cells, circulating tumour DNA and extracellular vesicles as potential non-invasively sampled biomarkers to manage the treatment of patients with GBM.

PD-L1 expressing circulating tumour cells in head and neck cancers.

BACKGROUND: Blockade of the PD-1/PD-L1 immune checkpoint pathway is emerging as a promising immunotherapeutic approach for the management and treatment of head and neck cancer patients who do not respond to 1st/2nd line therapy. However, as checkpoint inhibitors are cost intensive, identifying patients who would most likely benefit from anti PD-L1 therapy is required. Developing a non-invasive technique would be of major benefit to the patient and to the health care system. CASE PRESENTATION: We report the case of a 56 year old man affected by a supraglottic squamous cell carcinoma (SCC). A CT scan showed a 20 mm right jugulodigastric node and suspicious lung lesions. The lung lesion was biopsied and confirmed to be consistent with SCC. The patient was offered palliative chemotherapy. At the time of presentation, a blood sample was taken for circulating tumour cell (CTC) analysis. The dissemination of cancer was confirmed by the detection of CTCs in the peripheral blood of the patient, measured by the CellSearch System (Janssen Diagnostics). Using marker-independent, low-shear spiral microfluidic technology combined with immunocytochemistry, CTC clusters were found in this patient at the same time point, expressing PD-L1. CONCLUSION: This report highlights the potential use of CTCs to identify patients which might respond to anti PD-L1 therapy.

Circulating tumour cells in metastatic head and neck cancers.

Head and neck squamous cell carcinoma (HNSCC) is the sixth most common cancer with 650,000 new cases p/a worldwide. HNSCC causes high morbidity with a 5-year survival rate of less than 60%, which has not improved due to the lack of early detection (Bozec et al. Eur Arch Otorhinolaryngol. 2013;270: 2745-9). Metastatic disease remains one of the leading causes of death in HNSCC patients. This review article provides a comprehensive overview of literature over the past 5 years on the detection of circulating tumour cells (CTCs) in HNSCC; CTC biology and future perspectives. CTCs are a hallmark of invasive cancer cells and key to metastasis. CTCs can be used as surrogate markers of overall survival and progression-free survival. CTCs are currently used as prognostic factors for breast, prostate and colorectal cancers using the CellSearch® system. CTCs have been detected in HNSCC, however, these numbers depend on the technique applied, time of blood collection and the clinical stage of the patient. The impact of CTCs in HNSCC is not well understood, and thus, not in routine clinical practice. Validated detection technologies that are able to capture CTCs undergoing epithelial-mesenchymal transition are needed. This will aid in the capture of heterogeneous CTCs, which can be compiled as new targets for the current food and drug administration-cleared CellSearch® system. Recent studies on CTCs in HNSCC with the CellSearch® have shown variable data. Therefore, there is an immediate need for large clinical trials encompassing a suite of biomarkers capturing CTCs in HNSCC, before CTCs can be used as prognostic markers in HNSCC patient management.