Cellular Barcoding Identifies Clonal Substitution as a Hallmark of Local Recurrence in a Surgical Model of Head and Neck Squamous Cell Carcinoma

Clonal tracking in cancer and metastasis

The eradication of many cancers has proven challenging due to the presence of functionally and genetically heterogeneous clones maintained by rare cancer stem cells (CSCs), which contribute to disease progression, treatment refractoriness, and late relapse. The characterization of functional CSC activity has necessitated the development of modern clonal tracking strategies. This review describes viral-based and CRISPR-Cas9-based cellular barcoding, lineage tracing, and imaging-based approaches. DNA-based cellular barcoding technology is emerging as a powerful and robust strategy that has been widely applied to in vitro and in vivo model systems, including patient-derived xenograft models. This review also highlights the potential of these methods for use in the clinical and drug discovery contexts and discusses the important insights gained from such approaches.

Best Practices in Designing, Sequencing, and Identifying Random DNA Barcodes

Random DNA barcodes are a versatile tool for tracking cell lineages, with applications ranging from development to cancer to evolution. Here, we review and critically evaluate barcode designs as well as methods of barcode sequencing and initial processing of barcode data. We first demonstrate how various barcode design decisions affect data quality and propose a new design that balances all considerations that we are currently aware of. We then discuss various options for the preparation of barcode sequencing libraries, including inline indices and Unique Molecular Identifiers (UMIs). Finally, we test the performance of several established and new bioinformatic pipelines for the extraction of barcodes from raw sequencing reads and for error correction. We find that both alignment and regular expression-based approaches work well for barcode extraction, and that error-correction pipelines designed specifically for barcode data are superior to generic ones. Overall, this review will help researchers to approach their barcoding experiments in a deliberate and systematic way.

Clonal selection parallels between normal and cancer tissues

Clonal selection and drift drive both normal tissue and cancer development. However, the biological mechanisms and environmental conditions underpinning these processes remain to be elucidated. Clonal selection models are centered in Darwinian evolutionary theory, where some clones with the fittest features are selected and populate the tissue or tumor. We suggest that different subclasses of stem cells, each of which is responsible for a distinct feature of the selection process, share common features between normal and cancer conditions. While active stem cells populate the tissue, dormant cells account for tissue replenishment/regeneration in both normal and cancerous tissues. We also discuss potential mechanisms that drive clonal drift, their interactions with clonal selection, and their similarities during normal and cancer tissue development.

Tissue factor-induced fibrinogenesis mediates cancer cell clustering and multiclonal peritoneal metastasis

Peritoneal metastasis is one of the most frequent causes of death in several types of advanced cancers; however, the underlying molecular mechanisms remain largely unknown. In this study, we exploited multicolor fluorescent lineage tracking to investigate the clonality of peritoneal metastasis in mouse xenograft models. When peritoneal metastasis was induced by intraperitoneal or orthotopic injection of multicolored cancer cells, each peritoneally metastasized tumor displayed multicolor fluorescence regardless of metastasis sites, indicating that it consists of multiclonal cancer cell populations. Multicolored cancer cell clusters form within the peritoneal cavity and collectively attach to the peritoneum. In vitro, peritoneal lavage fluid or cleared ascitic fluid derived from cancer patients induces cancer cell clustering, which is inhibited by anticoagulants. Cancer cell clusters formed in vitro and in vivo are associated with fibrin formation. Furthermore, tissue factor knockout in cancer cells abrogates cell clustering, peritoneal attachment, and peritoneal metastasis. Thus, we propose that cancer cells activate the coagulation cascade via tissue factor to form fibrin-mediated cell clusters and promote peritoneal attachment; these factors lead to the development of multiclonal peritoneal metastasis and may be therapeutic targets.

The continuing evolution of barcode applications: Functional toxicology to cell lineage

DNA barcoding is a method to identify biological entities, including individual cells, tissues, organs, or species, by unique DNA sequences. With the advent of next generation sequencing (NGS), there has been an exponential increase in data acquisition pertaining to medical diagnosis, genetics, toxicology, ecology, cancer, and developmental biology. While barcoding first gained wide access in identifying species, signature tagged mutagenesis has been useful in elucidating gene function, particularly in microbes. With the advent of CRISPR/CAS9, methodology to profile eukaryotic genes has made a broad impact in toxicology and cancer biology. Designed homing guide RNAs (hgRNAs) that self-target DNA sequences facilitate cell lineage barcoding by introducing stochastic mutations within cell identifiers. While each of these applications has their limitations, the potential of sequence barcoding has yet to be realized. This review will focus on signature-tagged mutagenesis and briefly discuss the history of barcoding, experimental problems, novel detection methods, and future directions.

Mastering the use of cellular barcoding to explore cancer heterogeneity

Tumours are often composed of a multitude of malignant clones that are genomically unique, and only a few of them may have the ability to escape cancer therapy and grow as symptomatic lesions. As a result, tumours with a large degree of genomic diversity have a higher chance of leading to patient death. However, clonal fate can be driven by non-genomic features. In this context, new technologies are emerging not only to track the spatiotemporal fate of individual cells and their progeny but also to study their molecular features using various omics analysis. In particular, the recent development of cellular barcoding facilitates the labelling of tens to millions of cancer clones and enables the identification of the complex mechanisms associated with clonal fate in different microenvironments and in response to therapy. In this Review, we highlight the recent discoveries made using lentiviral-based cellular barcoding techniques, namely genetic and optical barcoding. We also emphasize the strengths and limitations of each of these technologies and discuss some of the key concepts that must be taken into consideration when one is designing barcoding experiments. Finally, we suggest new directions to further improve the use of these technologies in cancer research.

Multi-omics analysis: Paving the path toward achieving precision medicine in cancer treatment and immuno-oncology

The acceleration of large-scale sequencing and the progress in high-throughput computational analyses, defined as omics, was a hallmark for the comprehension of the biological processes in human health and diseases. In cancerology, the omics approach, initiated by genomics and transcriptomics studies, has revealed an incredible complexity with unsuspected molecular diversity within a same tumor type as well as spatial and temporal heterogeneity of tumors. The integration of multiple biological layers of omics studies brought oncology to a new paradigm, from tumor site classification to pan-cancer molecular classification, offering new therapeutic opportunities for precision medicine. In this review, we will provide a comprehensive overview of the latest innovations for multi-omics integration in oncology and summarize the largest multi-omics dataset available for adult and pediatric cancers. We will present multi-omics techniques for characterizing cancer biology and show how multi-omics data can be combined with clinical data for the identification of prognostic and treatment-specific biomarkers, opening the way to personalized therapy. To conclude, we will detail the newest strategies for dissecting the tumor immune environment and host–tumor interaction. We will explore the advances in immunomics and microbiomics for biomarker identification to guide therapeutic decision in immuno-oncology.

DNA barcoded competitive clone-initiating cell analysis reveals novel features of metastatic growth in a cancer xenograft model

A problematic feature of many human cancers is a lack of understanding of mechanisms controlling organ-specific patterns of metastasis, despite recent progress in identifying many mutations and transcriptional programs shown to confer this potential. To address this gap, we developed a methodology that enables different aspects of the metastatic process to be comprehensively characterized at a clonal resolution. Our approach exploits the application of a computational pipeline to analyze and visualize clonal data obtained from transplant experiments in which a cellular DNA barcoding strategy is used to distinguish the separate clonal contributions of two or more competing cell populations. To illustrate the power of this methodology, we demonstrate its ability to discriminate the metastatic behavior in immunodeficient mice of a well-established human metastatic cancer cell line and its co-transplanted LRRC15 knockdown derivative. We also show how the use of machine learning to quantify clone-initiating cell (CIC) numbers and their subsequent metastatic progeny generated in different sites can reveal previously unknown relationships between different cellular genotypes and their initial sites of implantation with their subsequent respective dissemination patterns. These findings underscore the potential of such combined genomic and computational methodologies to identify new clonally-relevant drivers of site-specific patterns of metastasis.

Therapy-related transcriptional subtypes in matched primary and recurrent head and neck cancer

PURPOSE

The genetic relatedness between primary and recurrent head and neck squamous cell carcinomas (HNSCC) reflects the extent of heterogeneity and therapy-driven selection of tumor subpopulations. Yet, current treatment of recurrent HNSCC ignores the molecular characteristics of therapy-resistant tumor populations.

EXPERIMENTAL DESIGN

From 150 tumors, 74 primary HNSCCs were RNA-sequenced and 38 matched primary/recurrent tumor pairs were both, whole-exome and RNA-sequenced. Transcriptome analysis determined the predominant classical (CL), basal (BA) and inflamed-mesenchymal (IMS) transcriptional subtypes according to an established classification. Genomic alterations and clonal compositions of tumors were evaluated from whole-exome data.

RESULTS

While CL and IMS subtypes were more common in primary HNSCC with low recurrence rates, the BA subtype was more prevalent and stable in recurrent tumors. The BA subtype was associated with a transcriptional signature of partial epithelial-to-mesenchymal transition (p-emt) and early recurrence. In 44% of matched cases, the dominant subtype changed from primary to recurrent tumors, preferably from IMS to BA or CL. Gene set enrichment analysis identified upregulation of Hypoxia, p-emt and radiation resistance signatures and downregulation of tumor inflammation in recurrences compared to index tumors. A relevant subset of primary/recurrent tumor pairs presented no evidence for a common clonal origin.

CONCLUSIONS

Our study showed a high degree of genetic and transcriptional heterogeneity between primary/recurrent tumors, suggesting therapy-related selection of a transcriptional subtype with characteristics unfavorable for therapy. We conclude that therapy decisions should be based on genetic and transcriptional characteristics of recurrences rather than primary tumors to enable optimally tailored treatment strategies.

CRISPR-to-Kill (C2K)-Employing the Bacterial Immune System to Kill Cancer Cells

Simple Summary

Reasoning that multiple DNA breaks will trigger programmed cell death, we generated lentiviral CRISPR-to-kill (C2K) vectors targeting highly repetitive SINE sequences for cancer gene therapy. In proof-of-concept experiments, C2K-Alu-vectors selectively killed human, but not murine cell lines, and efficiently inhibited the growth of patient-derived glioblastoma cell lines resistant to high-dose irradiation. In combination with tumor-targeting approaches, the C2K system might represent a promising tool for cancer gene therapy.

Abstract

CRISPR/Cas9 was described as a bacterial immune system that uses targeted introduction of DNA double-strand breaks (DSBs) to destroy invaders. We hypothesized that we can analogously employ CRISPR/Cas9 nucleases to kill cancer cells by inducing maximal numbers of DSBs in their genome and thus triggering programmed cell death. To do so, we generated CRISPR-to-kill (C2K) lentiviral particles targeting highly repetitive Short Interspersed Nuclear Element-Alu sequences. Our Alu-specific sgRNA has more than 15,000 perfectly matched target sites within the human genome. C2K-Alu-vectors selectively killed human, but not murine cell lines. More importantly, they efficiently inhibited the growth of cancer cells including patient-derived glioblastoma cell lines resistant to high-dose irradiation. Our data provide proof-of-concept for the potential of C2K as a novel treatment strategy overcoming common resistance mechanisms. In combination with tumor-targeting approaches, the C2K system might therefore represent a promising tool for cancer gene therapy.

High-Complexity cellular barcoding and clonal tracing reveals stochastic and deterministic parameters of radiation resistance

It is elusive whether clonal selection of tumor cells in response to ionizing radiation (IR) is a deterministic or stochastic process. With high resolution clonal barcoding and tracking of over 400 000 HNSCC patient-derived tumor cells the clonal dynamics of tumor cells in response to IR was analyzed. Fractionated IR induced a strong selective pressure for clonal reduction which significantly exceeded uniform clonal survival probabilities indicative for a strong clone-to-clone difference within tumor cell lines. IR induced clonal reduction affected the majority of tumor cells ranging between 96% and 75% and correlated to the degree of radiation sensitivity. Survival to IR is driven by a deterministic clonal selection of a smaller population which commonly survives radiation, while increased clonogenic capacity is a result of clonal competition of cells which have been selected stochastically. A 2-fold increase in radiation resistance results in a 4-fold (P < .05) higher deterministic clonal selection showing that the ratio of these parameters is amenable to radiation sensitivity which correlates to prognostic biomarkers of HNSCC. Evidence for the existence of a rare subpopulation with an intrinsically radiation resistant phenotype commonly surviving IR was found at a frequency of 0.6% to 3.3% (P < .001, FDR 3%). With cellular barcoding we introduce a novel functional heterogeneity associated qualitative readout for tracking dynamics of clonogenic survival in response to radiation. This enables the quantification of intrinsically radiation resistant tumor cells from patient samples and reveals the contribution of stochastic and deterministic clonal selection processes in response to IR.

Single-cell RNA sequencing and bioinformatics as tools to decipher cancer heterogenicity and mechanisms of drug resistance

It is well known that cancer is an aggressive disease, often associated with relapse, in many cases due to drug resistance. Cancer stem cell and clonal evolution are frequently causes of innate or acquired drug resistance. Current RNA sequencing technologies do not distinguish gene expression of different cell lineages because they are based on bulk cell studies. Single-cell RNA sequencing technologies and related bioinformatics clustering and differential expression analysis represent a turning point in cancer research. They are emerging as essential tools for dissecting tumors at single-cell resolution and represent novel tools to understand carcinogenesis and drug response. In this review, we will outline the role of these new technologies in addressing cancer heterogeneity and cell lineage-dependent drug resistance.

Radioresistance and Transcriptional Reprograming of Invasive Glioblastoma Cells

PURPOSE

Infiltrative growth pattern is a hallmark of glioblastoma (GBM). Radiation therapy aims to eradicate microscopic residual GBM cells after surgical removal of the visible tumor bulk. However, in-field recurrences remain the major pattern of therapy failure. We hypothesized that the radiosensitivity of peripheral invasive tumor cells (peri) may differ from the predominantly investigated tumor bulk.

METHODS AND MATERIALS

Invasive GBM populations were generated via debulking of the visible tumor core and serial orthotopic transplantation of peri cells, and sustained proinvasive phenotype of peri cells was confirmed in vitro by scratch assay and time lapse imaging. In parallel, invasive GBM cells were selected by transwell assay and from peri cells of patient-derived 3-dimensional spheroid cultures. Transcriptome analysis deciphered a GBM invasion-associated gene signature, and functional involvement of key pathways was validated by pharmacologic inhibition.

RESULTS

Compared with the bulk cells, invasive GBM populations acquired a radioresistant phenotype characterized by increased cell survival, reduced cell apoptosis, and enhanced DNA double-strand break repair proficiency. Transcriptome analysis revealed a reprograming of invasive cells toward augmented activation of epidermal growth factor receptor- and nuclear factor-κB-related pathways, whereas metabolic processes were downregulated. An invasive GBM score derived from this transcriptional fingerprint correlated well with patient outcome. Inhibition of epidermal growth factor receptor and nuclear factor-κB signaling resensitized invasive cells to irradiation. Invasive cells were eradicated with similar efficacy by particle therapy with carbon ions.

CONCLUSIONS

Our data indicate that invasive tumor cells constitute a phenotypically distinct and highly radioresistant GBM subpopulation with prognostic impact that may be vulnerable to targeted therapy and carbon ions.

Unraveling Tumor Heterogeneity by Using DNA Barcoding Technologies to Develop Personalized Treatment Strategies in Advanced-Stage PDAC

Tumor heterogeneity is a hallmark of many solid tumors, including pancreatic ductal adenocarcinoma (PDAC), and an inherent consequence of the clonal evolution of cancers. As such, it is considered the underlying concept of many characteristics of the disease, including the ability to metastasize, adapt to different microenvironments, and to develop therapy resistance. Undoubtedly, the high mortality of PDAC can be attributed to a high extent to these properties. Despite its apparent importance, studying tumor heterogeneity has been a challenging task, mainly due to its complexity and lack of appropriate methods. However, in recent years molecular DNA barcoding has emerged as a sophisticated tool that allows mapping of individual cells or subpopulations in a cell pool to study heterogeneity and thus devise new personalized treatment strategies. In this review, we provide an overview of genetic and non-genetic inter- and intra-tumor heterogeneity and its impact on (personalized) treatment strategies in PDAC and address how DNA barcoding technologies work and can be applied to study this clinically highly relevant question.

Spatial omics and multiplexed imaging to explore cancer biology

Understanding intratumoral heterogeneity-the molecular variation among cells within a tumor-promises to address outstanding questions in cancer biology and improve the diagnosis and treatment of specific cancer subtypes. Single-cell analyses, especially RNA sequencing and other genomics modalities, have been transformative in revealing novel biomarkers and molecular regulators associated with tumor growth, metastasis and drug resistance. However, these approaches fail to provide a complete picture of tumor biology, as information on cellular location within the tumor microenvironment is lost. New technologies leveraging multiplexed fluorescence, DNA, RNA and isotope labeling enable the detection of tens to thousands of cancer subclones or molecular biomarkers within their native spatial context. The expeditious growth in these techniques, along with methods for multiomics data integration, promises to yield a more comprehensive understanding of cell-to-cell variation within and between individual tumors. Here we provide the current state and future perspectives on the spatial technologies expected to drive the next generation of research and diagnostic and therapeutic strategies for cancer.

The site of breast cancer metastases dictates their clonal composition and reversible transcriptomic profile

Intratumoral heterogeneity is a driver of breast cancer progression, but the nature of the clonal interactive network involved in this process remains unclear. Here, we optimized the use of optical barcoding to visualize and characterize 31 cancer subclones in vivo. By mapping the clonal composition of thousands of metastases in two clinically relevant sites, the lungs and liver, we found that metastases were highly polyclonal in lungs but not in the liver. Furthermore, the transcriptome of the subclones varied according to their metastatic niche. We also identified a reversible niche-driven signature that was conserved in lung and liver metastases collected during patient autopsies. Among this signature, we found that the tumor necrosis factor-α pathway was up-regulated in lung compared to liver metastases, and inhibition of this pathway affected metastasis diversity. These results highlight that the cellular and molecular heterogeneity observed in metastases is largely dictated by the tumor microenvironment.

RGB-Marking to Identify Patterns of Selection and Neutral Evolution in Human Osteosarcoma Models

Osteosarcoma (OS) is a highly aggressive tumor characterized by malignant cells producing pathologic bone; the disease presents a natural tendency to metastasize. Genetic studies indicate that the OS genome is extremely complex, presenting signs of macro-evolution, and linear and branched patterns of clonal development. However, those studies were based on the phylogenetic reconstruction of next-generation sequencing (NGS) data, which present important limitations. Thus, testing clonal evolution in experimental models could be useful for validating this hypothesis. In the present study, lentiviral LeGO-vectors were employed to generate colorimetric red, green, blue (RGB)-marking in murine, canine, and human OS. With this strategy, we studied tumor heterogeneity and the clonal dynamics occurring in vivo in immunodeficient NOD.Cg-Prkdcscid-Il2rgtm1Wjl/SzJ (NSG) mice. Based on colorimetric label, tumor clonal composition was analyzed by confocal microscopy, flow cytometry, and different types of supervised and unsupervised clonal analyses. With this approach, we observed a consistent reduction in the clonal composition of RGB-marked tumors and identified evident clonal selection at the first passage in immunodeficient mice. Furthermore, we also demonstrated that OS could follow a neutral model of growth, where the disease is defined by the coexistence of different tumor sub-clones. Our study demonstrates the importance of rigorous testing of the selective forces in commonly used experimental models.

New Insights into Therapy-Induced Progression of Cancer

The malignant tumor is a complex heterogeneous set of cells functioning in a no less heterogeneous microenvironment. Like any dynamic system, cancerous tumors evolve and undergo changes in response to external influences, including therapy. Initially, most tumors are susceptible to treatment. However, remaining cancer cells may rapidly reestablish the tumor after a temporary remission. These new populations of malignant cells usually have increased resistance not only to the first-line agent, but also to the second- and third-line drugs, leading to a significant decrease in patient survival. Multiple studies describe the mechanism of acquired therapy resistance. In past decades, it became clear that, in addition to the simple selection of pre-existing resistant clones, therapy induces a highly complicated and tightly regulated molecular response that allows tumors to adapt to current and even subsequent therapeutic interventions. This review summarizes mechanisms of acquired resistance, such as secondary genetic alterations, impaired function of drug transporters, and autophagy. Moreover, we describe less obvious molecular aspects of therapy resistance in cancers, including epithelial-to-mesenchymal transition, cell cycle alterations, and the role of intercellular communication. Understanding these molecular mechanisms will be beneficial in finding novel therapeutic approaches for cancer therapy.

HPV16 is sufficient to induce squamous cell carcinoma specifically in the tongue base in transgenic mice

Head and neck squamous cell carcinomas (HNSCCs) associated with human papillomavirus (HPV) occur specifically in the tonsils and the tongue base, but the reasons for this specificity remain unknown. We studied the distribution of oral and pharyngeal lesions in HPV16-transgenic mice where the expression of all the HPV16 early genes is targeted to keratinising squamous epithelia by the cytokeratin 14 (Krt14) gene promoter. At 30 weeks of age, 100% of mice developed low- and high-grade intraepithelial dysplasia at multiple sites. Twenty per cent of animals developed invasive cancers that remarkably were restricted to the tongue base, in association with the circumvallate papilla. The lesions maintained expression of CK14 (KRT14) and the HPV16 E6 and E7 oncogenes, and displayed deregulated cell proliferation and up-regulation of p16^INK4A . Malignant lesions were poorly differentiated and destroyed the tongue musculature. We hypothesised that the tongue base area might contain a transformation zone similar to those observed in the cervix and anus, explaining why HPV-positive cancers target that area specifically. Immunohistochemistry for two transformation zone markers, CK7 (KRT7) and p63 (TP63), revealed a squamocolumnar junction in the terminal duct of von Ebner's gland, composed of CK7⁺ luminal cells and p63⁺ basal cells. Dysplastic and invasive lesions retained diffuse p63 expression but only scattered positivity for CK7. Site-specific HPV-induced carcinogenesis in the tongue base may be explained by the presence of a transformation zone in the circumvallate papilla. This mouse model reproduces key morphological and molecular features of HPV-positive HNSCC, providing a unique in vivo tool for basic and translational research. © 2020 Pathological Society of Great Britain and Ireland. Published by John Wiley & Sons, Ltd.

Quantification of the dynamics of population heterogeneities in CHO cultures with stably integrated fluorescent markers

Cell population heterogeneities and their changes in mammalian cell culture processes are still not well characterized. In this study, the formation and dynamics of cell population heterogeneities were investigated with flow cytometry and stably integrated fluorescent markers based on the lentiviral gene ontology (LeGO) vector system. To achieve this, antibody-producing CHO cells were transduced with different LeGO vectors to stably express single or multiple fluorescent proteins. This enables the tracking of the transduced populations and is discussed in two case studies from the field of bioprocess engineering: In case study I, cells were co-transduced to express red, green, and blue fluorescent proteins and the development of sub-populations and expression heterogeneities were investigated in high passage cultivations (total 130 days). The formation of a fast-growing and more productive population was observed with a simultaneous increase in cell density and product titer. In case study II, different preculture growth phases and their influence on the population dynamics were investigated in mixed batch cultures with flow cytometry (offline and automated). Four cell line derivatives, each expressing a different fluorescent protein, were generated and cultivated for different time intervals, corresponding to different growth phases. Mixed cultures were inoculated from them, and changes in the composition of the cell populations were observed during the first 48 h of cultivation with reduced process productivity. In summary, we showed how the dynamics of population heterogeneities can be characterized. This represents a novel approach to investigate the dynamics of cell population heterogeneities under near-physiological conditions with changing productivity in mammalian cell culture processes.

Improved detection of differentially represented DNA barcodes for high-throughput clonal phenomics

Cellular DNA barcoding has become a popular approach to study heterogeneity of cell populations and to identify clones with differential response to cellular stimuli. However, there is a lack of reliable methods for statistical inference of differentially responding clones. Here, we used mixtures of DNA-barcoded cell pools to generate a realistic benchmark read count dataset for modelling a range of outcomes of clone-tracing experiments. By accounting for the statistical properties intrinsic to the DNA barcode read count data, we implemented an improved algorithm that results in a significantly lower false-positive rate, compared to current RNA-seq data analysis algorithms, especially when detecting differentially responding clones in experiments with strong selection pressure. Building on the reliable statistical methodology, we illustrate how multidimensional phenotypic profiling enables one to deconvolute phenotypically distinct clonal subpopulations within a cancer cell line. The mixture control dataset and our analysis results provide a foundation for benchmarking and improving algorithms for clone-tracing experiments.

Mouse Tumor-Bearing Models as Preclinical Study Platforms for Oral Squamous Cell Carcinoma

Preclinical animal models of oral squamous cell carcinoma (OSCC) have been extensively studied in recent years. Investigating the pathogenesis and potential therapeutic strategies of OSCC is required to further progress in this field, and a suitable research animal model that reflects the intricacies of cancer biology is crucial. Of the animal models established for the study of cancers, mouse tumor-bearing models are among the most popular and widely deployed for their high fertility, low cost, and molecular and physiological similarity to humans, as well as the ease of rearing experimental mice. Currently, the different methods of establishing OSCC mouse models can be divided into three categories: chemical carcinogen-induced, transplanted and genetically engineered mouse models. Each of these methods has unique advantages and limitations, and the appropriate application of these techniques in OSCC research deserves our attention. Therefore, this review comprehensively investigates and summarizes the tumorigenesis mechanisms, characteristics, establishment methods, and current applications of OSCC mouse models in published papers. The objective of this review is to provide foundations and considerations for choosing suitable model establishment methods to study the relevant pathogenesis, early diagnosis, and clinical treatment of OSCC.

The transcription factor FOXM1 regulates the balance between proliferation and aberrant differentiation in head and neck squamous cell carcinoma

Sustained expression of FOXM1 is a hallmark of nearly all human cancers including squamous cell carcinomas of the head and neck (HNSCC). HNSCCs partially preserve the epithelial differentiation program, which recapitulates fetal and adult traits of the tissue of tumor origin but is deregulated by genetic alterations and tumor-supporting pathways. Using shRNA-mediated knockdown, we demonstrate a minimal impact of FOXM1 on proliferation and migration of HNSCC cell lines under standard cell culture conditions. However, FOXM1 knockdown in three-dimensional (3D) culture and xenograft tumor models resulted in reduced proliferation, decreased invasion, and a more differentiated-like phenotype, indicating a context-dependent modulation of FOXM1 activity in HNSCC cells. By ectopic overexpression of FOXM1 in HNSCC cell lines, we demonstrate a reduced expression of cutaneous-type keratin K1 and involucrin as a marker of squamous differentiation, supporting the role of FOXM1 in modulation of aberrant differentiation in HNSCC. Thus, our data provide a strong rationale for targeting FOXM1 in HNSCC. © 2019 Pathological Society of Great Britain and Ireland. Published by John Wiley & Sons, Ltd.

Proteomic Technology "Lens" for Epithelial-Mesenchymal Transition Process Identification in Oncology

The epithelial-mesenchymal transition (EMT) is a complex transformation process that induces local and distant progression of many malignant tumours. Due to its complex array of proteins that are dynamically over-/underexpressed during this process, proteomic technologies gained their place in the EMT research in the last years. Proteomics has identified new molecular pathways of this process and brought important insights to develop new therapy targets. Various proteomic tools and multiple combinations were developed in this area. Out of the proteomic technology armentarium, mass spectrometry and array technologies are the most used approaches. The main characteristics of the proteomic technology used in this domain are high throughput and detection of minute concentration in small samples. We present herein, using various proteomic technologies, the identification in cancer cell lines and in tumour tissue EMT-related proteins, proteins that are involved in the activation of different cellular pathways. Proteomics has brought besides standard EMT markers (e.g., cell-cell adhesion proteins and transcription factors) other future potential markers for improving diagnosis, monitoring evolution, and developing new therapy targets. Future will increase the proteomic role in clinical investigation and validation of EMT-related biomarkers.

Cancer Stem Cells in Head and Neck Squamous Cell Carcinoma: Identification, Characterization and Clinical Implications

Head and neck squamous cell carcinoma (HNSCC) is the sixth most commonly diagnosed cancer worldwide. Despite advances in the treatment management, locally advanced disease has a poor prognosis, with a 5-year survival rate of approximately 50%. The growth of HNSCC is maintained by a population of cancer stem cells (CSCs) which possess unlimited self-renewal potential and induce tumor regrowth if not completely eliminated by therapy. The population of CSCs is not only a promising target for tumor treatment, but also an important biomarker to identify the patients at risk for therapeutic failure and disease progression. This review aims to provide an overview of the recent pre-clinical and clinical studies on the biology and potential therapeutic implications of HNSCC stem cells.