Integrated single-cell and bulk gene expression and ATAC-seq reveals heterogeneity and early changes in pathways associated with resistance to cetuximab in HNSCC-sensitive cell lines

Development of a novel prognostic signature derived from super-enhancer-associated gene by machine learning in head and neck squamous cell carcinoma

Dysregulated super-enhancer (SE) results in aberrant transcription that drives cancer initiation and progression. SEs have been demonstrated as novel promising diagnostic/prognostic biomarkers and therapeutic targets across multiple human cancers. Here, we sought to develop a novel prognostic signature derived from SE-associated genes for head and neck squamous cell carcinoma (HNSCC). SE was identified from H3K27ac ChIP-seq datasets in HNSCC cell lines by ROSE algorithm and SE-associated genes were further mapped and functionally annotated. A total number of 133 SE-associated genes with mRNA upregulation and prognostic significance was screened via differentially-expressed genes (DEGs) and Cox regression analyses. These candidates were subjected for prognostic model constructions by machine learning approaches using three independent HNSCC cohorts (TCGA-HNSC dataset as training cohort, GSE41613 and GSE42743 as validation cohorts). Among dozens of prognostic models, the random survival forest algorithm (RSF) stood out with the best performance as evidenced by the highest average concordance index (C-index). A prognostic nomogram integrating this SE-associated gene signature (SEAGS) plus tumor size demonstrated satisfactory predictive power and excellent calibration and discrimination. Moreover, WNT7A from SEARG was validated as a putative oncogene with transcriptional activation by SE to promote malignant phenotypes. Pharmacological disruption of SE functions by BRD4 or EP300 inhibitor significantly impaired tumor growth and diminished WNT7A expression in a HNSCC patient-derived xenograft model. Taken together, our results establish a novel, robust SE-derived prognostic model for HNSCC and suggest the translational potentials of SEs as promising therapeutic targets for HNSCC.

Exploiting new strategies in combating head and neck carcinoma: A comprehensive review on phytochemical approaches passing through PI3K/Akt/mTOR signaling pathway

Recently, malignant neoplasms have growingly caused human morbidity and mortality. Head and neck cancer (HNC) constitutes a substantial group of malignancies occurring in various anatomical regions of the head and neck, including lips, mouth, throat, larynx, nose, sinuses, oropharynx, hypopharynx, nasopharynx, and salivary glands. The present study addresses the phosphoinositide 3-kinase (PI3K)/protein kinase B (Akt)/mammalian target of rapamycin (mTOR) pathway as a possible therapeutic target in cancer therapy. Finding new multitargeting agents capable of modulating PI3K/Akt/mTOR and cross-linked mediators could be viewed as an effective strategy in combating HNC. Recent studies have introduced phytochemicals as multitargeting agents and rich sources for finding and developing new therapeutic agents. Phytochemicals have exhibited immense anticancer effects, including targeting different stages of HNC through the modulation of several signaling pathways. Moreover, phenolic/polyphenolic compounds, alkaloids, terpenes/terpenoids, and other secondary metabolites have demonstrated promising anticancer activities because of their diverse pharmacological and biological properties like antiproliferative, antineoplastic, antioxidant, and anti-inflammatory activities. The current review is mainly focused on new therapeutic strategies for HNC passing through the PI3K/Akt/mTOR pathway as new strategies in combating HNC.

Nuclear miR-451a activates KDM7A and leads to cetuximab resistance in head and neck squamous cell carcinoma

Cetuximab resistance has been a major challenge for head and neck squamous cell carcinoma (HNSCC) patients receiving targeted therapy. However, the mechanism that causes cetuximab resistance, especially microRNA (miRNA) regulation, remains unclear. Growing evidence suggests that miRNAs may act as "nuclear activating miRNAs" for targeting promoter regions or enhancers related to target genes. This study elucidates a novel mechanism underlying cetuximab resistance in HNSCC involving the nuclear activation of KDM7A transcription via miR-451a. Herein, small RNA sequencing, quantitative real-time polymerase chain reaction (qRT‒PCR) and fluorescence in situ hybridization (FISH) results provided compelling evidence of miR-451a nuclear enrichment in response to cetuximab treatment. Chromatin isolation via RNA purification, microarray analysis, and bioinformatic analysis revealed that miR-451a interacts with an enhancer region in KDM7A, activating its expression and further facilitating cetuximab resistance. It has also been demonstrated that the activation of KDM7A by nuclear miR-451a is induced by cetuximab treatment and is AGO2 dependent. Logistic regression analyses of 87 HNSCC samples indicated the significance of miR-451a and KDM7A in the development of cetuximab resistance. These discoveries support the potential of miR-451a and KDM7A as valuable biomarkers for cetuximab resistance and emphasize the function of nuclear-activating miRNAs.

Cetuximab chemotherapy resistance: Insight into the homeostatic evolution of head and neck cancer (Review)

The complex evolution of genetic alterations in cancer that occurs in vivo is a selective process involving numerous factors and mechanisms. Chemotherapeutic agents that prevent the growth and spread of cancer cells induce selective pressure, leading to rapid artificial selection of resistant subclones. This rapid evolution is possible because antineoplastic drugs promote alterations in tumor‑cell metabolism, thus creating a bottleneck event. The few resistant cells that survive in this new environment obtain differential reproductive success that enables them to pass down the newly selected resistant gene pool. The present review aims to summarize key findings of tumor evolution, epithelial‑mesenchymal transition and resistance to cetuximab therapy in head and neck squamous cell carcinoma.

Clinical and genomic characterization of chemoradiation-resistant HPV-positive oropharyngeal squamous cell carcinoma

Introduction

Most patients with HPV-positive oropharyngeal squamous cell carcinoma (OPSCC) have an excellent response to chemoradiation, and trials are now investigating de-escalated treatment. However, up to 25% of patients with HPV-positive OPSCC will experience recurrence, and up to 5% will even progress through primary treatment. Currently, there are no molecular markers to identify patients with poor prognosis who would be harmed by de-escalation. Herein we report the clinical and genomic characteristics of persistent HPV-positive OPSCC after definitive platinum-based chemoradiation therapy.

Methods

Patients with HPV-positive OPSCC treated with curative intent platinum-based chemoradiation between 2007 and 2017 at two institutions and with a persistent locoregional disease were included. We evaluated clinical characteristics, including smoking status, age, stage, treatment, and overall survival. A subset of five patients had tissue available for targeted exome DNA sequencing and RNA sequencing. Genomic analysis was compared to a previously published cohort of 47 treatment-responsive HPV+ OPSCC tumors after batch correction. Mutational landscape, pathway activation, and OncoGPS tumor states were employed to characterize these tumors.

Results

Ten patients met the inclusion criteria. The tumor and nodal stages ranged from T1 to T4 and N1 to N2 by AJCC 8th edition staging. All patients were p16-positive by immunohistochemistry, and eight with available in situ hybridization were confirmed to be HPV-positive. The 1-year overall survival from the time of diagnosis was 57%, and the 2-year overall survival was 17%. TP53 mutations were present in three of five (60%) persistent tumors compared to 2% (one of 47) of treatment-responsive HPV-positive tumors (p = 0.008). Other genes with recurrent mutations in persistent HPV-positive OPSCC tumors were NF1, KMT2D, PIK3C2B, and TFGBR2. Compared to treatment-responsive HPV-positive tumors, persistent tumors demonstrated activation of DNA Repair and p53, EMT, MYC, SRC, and TGF-beta signaling pathways, with post-treatment samples demonstrating significant activation of the PI3K-EMT-Stem pathways compared to pretreatment samples.

Conclusion

Chemoradiation-resistant HPV-positive OPSCC occurs infrequently but portends a poor prognosis. These tumors demonstrate higher rates of p53 mutation and activation of MYC, SRC, and TGF-beta pathways. A comparison of tumors before and after treatment demonstrates PI3K-EMT-Stem pathways post-treatment in HPV-positive tumors with persistent disease after platinum-based chemoradiation.

DELFOS-drug efficacy leveraging forked and specialized networks-benchmarking scRNA-seq data in multi-omics-based prediction of cancer sensitivity

MOTIVATION

Cancer is currently one of the most notorious diseases, with over 1 million deaths in the European Union alone in 2022. As each tumor can be composed of diverse cell types with distinct genotypes, cancer cells can acquire resistance to different compounds. Moreover, anticancer drugs can display severe side effects, compromising patient well-being. Therefore, novel strategies for identifying the optimal set of compounds to treat each tumor have become an important research topic in recent decades.

RESULTS

To address this challenge, we developed a novel drug response prediction algorithm called Drug Efficacy Leveraging Forked and Specialized networks (DELFOS). Our model learns from multi-omics data from over 65 cancer cell lines, as well as structural data from over 200 compounds, for the prediction of drug sensitivity. We also evaluated the benefits of incorporating single-cell expression data to predict drug response. DELFOS was validated using datasets with unseen cell lines or drugs and compared with other state-of-the-art algorithms, achieving a high prediction performance on several correlation and error metrics. Overall, DELFOS can effectively leverage multi-omics data for the prediction of drug responses in thousands of drug-cell line pairs.

AVAILABILITY AND IMPLEMENTATION

The DELFOS pipeline and associated data are available at github.com/MoreiraLAB/delfos.

Application of single-cell RNA sequencing in head and neck squamous cell carcinoma

Single-cell RNA sequencing has been broadly applied to head and neck squamous cell carcinoma (HNSCC) for characterizing the heterogeneity and genomic mutations of HNSCC benefiting from the advantage of single-cell resolution. We summarized most of the current studies and aimed to explore their research methods and ideas, as well as how to transform them into clinical applications. Through single-cell RNA sequencing, we found the differences in tumor cells' expression programs and differentiation tracks. The studies of immune microenvironment allowed us to distinguish immune cell subpopulations, the extensive expression of immune checkpoints, and the complex crosstalk network between immune cells and non-immune cells. For cancer-associated fibroblasts (CAFs), single-cell RNA sequencing had made an irreplaceable contribution to the exploration of their differentiation status, specific CAFs markers, and the interaction with tumor cells and immune cells. In addition, we demonstrated in detail how single-cell RNA sequencing explored the HNSCC epithelial-to-mesenchymal transition (EMT) model and the mechanism of drug resistance, as well as its clinical value.

Multiomics Empowers Predictive Pancreatic Cancer Immunotherapy

Advances in cancer immunotherapy, particularly immune checkpoint inhibitors, have dramatically improved the prognosis for patients with metastatic melanoma and other previously incurable cancers. However, patients with pancreatic ductal adenocarcinoma (PDAC) generally do not respond to these therapies. PDAC is exceptionally difficult to treat because of its often late stage at diagnosis, modest mutation burden, and notoriously complex and immunosuppressive tumor microenvironment. Simultaneously interrogating features of cancer, immune, and other cellular components of the PDAC tumor microenvironment is therefore crucial for identifying biomarkers of immunotherapeutic resistance and response. Notably, single-cell and multiomics technologies, along with the analytical tools for interpreting corresponding data, are facilitating discoveries of the systems-level cellular and molecular interactions contributing to the overall resistance of PDAC to immunotherapy. Thus, in this review, we will explore how multiomics and single-cell analyses provide the unprecedented opportunity to identify biomarkers of resistance and response to successfully sensitize PDAC to immunotherapy.

Direct tool for quantitative analysis of cell/object dynamic behavior - metastasis and far beyond

INTRODUCTION

The dynamics and depth of invasion as well as the ability of cancer cells to penetrate the walls of  lymphatic or blood vessels represent critical survival-influencing factors in cancer patients. Depending on the cell type and tissue environment, cancer cell invasion differ in terms of motility mechanism and migration modes. Thus, there is the need of effective models allowing not only for single cell invasion potential assessment but also for collective migration and expansive growth evaluation in 3D microenvironment e.g. basement membranes. To meet this task, the specimens should be compared and analyzed in terms of the dynamics of movement and the evolution of the shape.

OBJECTIVES

Our main objective was development of the mathematical method that enables fast and credible calculation of parameters of shape and position, namely standard deviations (σ_X, σ_Y), centroid position (μ_X, μ_Y) and correlation coefficient ρ, based only on the contour of the aggregate.

METHODS

In order to accomplish this goal we measured geometrical properties of aggregates of RGM1 cells seeded in 3D Geltrex basement membrane. Referential microscopic images were taken 24 and 48 h after seeding and cell group dynamics was registered over 8 h periods using time lapse microscopy.

RESULTS

Based on gathered data, we managed to develop and fully test universal numerical tool allowing for estimation of statistical parameters of cell groups and aggregates which then allows for the precise evaluation of their behavior within microenvironment with time.

CONCLUSION

We conclude, that our tool is suitable for any research on the metastatic potential and motility of cancer cells in a given microenvironment, regardless of the migration mechanism, which together with the advanced analysis like cell single-cell transcriptomic, proteomic, and chromatin accessibility data may allow to identify precise targets for anti-cancer therapies, to predict the degree of malignancy of neoplastic lesions as well as it can be useful during architecting therapeutic strategies. Moreover, the developed tool seems to be broadly applicable for assessment of behavioural dynamics of any population.

A transcriptomic map of EGFR-induced epithelial-to-mesenchymal transition identifies prognostic and therapeutic targets for head and neck cancer

Background

Epidermal growth factor receptor (EGFR) is both a driver oncogene and a therapeutic target in advanced head and neck squamous cell carcinoma (HNSCC). However, response to EGFR treatment is inconsistent and lacks markers for treatment prediction. This study investigated EGFR-induced epithelial-to-mesenchymal transition (EMT) as a central parameter in tumor progression and identified novel prognostic and therapeutic targets, and a candidate predictive marker for EGFR therapy response.

Methods

Transcriptomic profiles were analyzed by RNA sequencing (RNA-seq) following EGFR-mediated EMT in responsive human HNSCC cell lines. Exclusive genes were extracted via differentially expressed genes (DEGs) and a risk score was determined through forward feature selection and Cox regression models in HNSCC cohorts. Functional characterization of selected prognostic genes was conducted in 2D and 3D cellular models, and findings were validated by immunohistochemistry in primary HNSCC.

Results

An EGFR-mediated EMT gene signature composed of n = 171 genes was identified in responsive cell lines and transferred to the TCGA-HNSCC cohort. A 5-gene risk score comprising DDIT4, FADD, ITGB4, NCEH1, and TIMP1 prognosticated overall survival (OS) in TCGA and was confirmed in independent HNSCC cohorts. The EGFR-mediated EMT signature was distinct from EMT hallmark and partial EMT (pEMT) meta-programs with a differing enrichment pattern in single malignant cells. Molecular characterization showed that ITGB4 was upregulated in primary tumors and metastases compared to normal mucosa and correlated with EGFR/MAPK activity in tumor bulk and single malignant cells. Preferential localization of ITGB4 together with its ligand laminin 5 at tumor-stroma interfaces correlated with increased tumor budding in primary HNSCC tissue sections. In vitro, ITGB4 knock-down reduced EGFR-mediated migration and invasion and ITGB4-antagonizing antibody ASC8 impaired 2D and 3D invasion. Furthermore, a logistic regression model defined ITGB4 as a predictive marker of progression-free survival in response to Cetuximab in recurrent metastatic HNSCC patients.

Conclusions

EGFR-mediated EMT conveyed through MAPK activation contributes to HNSCC progression upon induction of migration and invasion. A 5-gene risk score based on a novel EGFR-mediated EMT signature prognosticated survival of HNSCC patients and determined ITGB4 as potential therapeutic and predictive target in patients with strong EGFR-mediated EMT.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12943-022-01646-1.

Decoding mechanism of action and sensitivity to drug candidates from integrated transcriptome and chromatin state

Omics-based technologies are driving major advances in precision medicine, but efforts are still required to consolidate their use in drug discovery. In this work, we exemplify the use of multi-omics to support the development of 3-chloropiperidines, a new class of candidate anticancer agents. Combined analyses of transcriptome and chromatin accessibility elucidated the mechanisms underlying sensitivity to test agents. Furthermore, we implemented a new versatile strategy for the integration of RNA- and ATAC-seq (Assay for Transposase-Accessible Chromatin) data, able to accelerate and extend the standalone analyses of distinct omic layers. This platform guided the construction of a perturbation-informed basal signature predicting cancer cell lines' sensitivity and to further direct compound development against specific tumor types. Overall, this approach offers a scalable pipeline to support the early phases of drug discovery, understanding of mechanisms, and potentially inform the positioning of therapeutics in the clinic.

Epigenomic interplay in tumor heterogeneity: Potential of epidrugs as adjunct therapy

"Heterogeneity" in tumor mass has immense importance in cancer progression and therapy. The impact of tumor heterogeneity is an emerging field and not yet fully explored. Tumor heterogeneity is mainly considered as intra-tumor heterogeneity and inter-tumor heterogeneity based on their origin. Intra-tumor heterogeneity refers to the discrepancy within the same cancer mass while inter-tumor heterogeneity refers to the discrepancy between different patients having the same tumor type. Both of these heterogeneity types lead to variation in the histopathological as well as clinical properties of the cancer mass which drives disease resistance towards therapeutic approaches. Cancer stem cells (CSCs) act as pinnacle progenitors for heterogeneity development along with various other genetic and epigenetic parameters that are regulating this process. In recent times epigenetic factors are one of the most studied parameters that drive oxidative stress pathways essential during cancer progression. These epigenetic changes are modulated by various epidrugs and have an impact on tumor heterogeneity. The present review summarizes various aspects of epigenetic regulation in the tumor microenvironment, oxidative stress, and progression towards tumor heterogeneity that creates complications during cancer treatment. This review also explores the possible role of epidrugs in regulating tumor heterogeneity and personalized therapy against drug resistance.

From single-omics to interactomics: How can ligand-induced perturbations modulate single-cell phenotypes?

Cells suffer from perturbations by different stimuli, which, consequently, rise to individual alterations in their profile and function that may end up affecting the tissue as a whole. This is no different if we consider the effect of a therapeutic agent on a biological system. As cells are exposed to external ligands their profile can change at different single-omics levels. Detecting how these changes take place through different sequencing technologies is key to a better understanding of the effects of therapeutic agents. Single-cell RNA-sequencing stands out as one of the most common approaches for cell profiling and perturbation analysis. As a result, single-cell transcriptomics data can be integrated with other omics data sources, such as proteomics and epigenomics data, to clarify the perturbation effects and mechanism at the cell level. Appropriate computational tools are key to process and integrate the available information. This chapter focuses on the recent advances on ligand-induced perturbation and single-cell omics computational tools and algorithms, their current limitations, and how the deluge of data can be used to improve the current process of drug research and development.

Harnessing changes in open chromatin determined by ATAC-seq to generate insulin-responsive reporter constructs

BACKGROUND

Gene regulation is critical for proper cellular function. Next-generation sequencing technology has revealed the presence of regulatory networks that regulate gene expression and essential cellular functions. Studies investigating the epigenome have begun to uncover the complex mechanisms regulating transcription. Assay for transposase-accessible chromatin by sequencing (ATAC-seq) is quickly becoming the assay of choice for many epigenomic investigations. However, whether intervention-mediated changes in accessible chromatin determined by ATAC-seq can be harnessed to generate intervention-inducible reporter constructs has not been systematically assayed.

RESULTS

We used the insulin signaling pathway as a model to investigate chromatin regions and gene expression changes using ATAC- and RNA-seq in insulin-treated Drosophila S2 cells. We found correlations between ATAC- and RNA-seq data, especially when stratifying differentially-accessible chromatin regions by annotated feature type. In particular, our data demonstrated a weak but significant correlation between chromatin regions annotated to enhancers (1-2 kb from the transcription start site) and downstream gene expression. We cloned candidate enhancer regions upstream of luciferase and demonstrate insulin-inducibility of several of these reporters.

CONCLUSIONS

Insulin-induced chromatin accessibility determined by ATAC-seq reveals enhancer regions that drive insulin-inducible reporter gene expression.

OBIF: an omics-based interaction framework to reveal molecular drivers of synergy

Bioactive molecule library screening may empirically identify effective combination therapies, but molecular mechanisms underlying favorable drug–drug interactions often remain unclear, precluding further rational design. In the absence of an accepted systems theory to interrogate synergistic responses, we introduce Omics-Based Interaction Framework (OBIF) to reveal molecular drivers of synergy through integration of statistical and biological interactions in synergistic biological responses. OBIF performs full factorial analysis of feature expression data from single versus dual exposures to identify molecular clusters that reveal synergy-mediating pathways, functions and regulators. As a practical demonstration, OBIF analyzed transcriptomic and proteomic data of a dyad of immunostimulatory molecules that induces synergistic protection against influenza A and revealed unanticipated NF-κB/AP-1 cooperation that is required for antiviral protection. To demonstrate generalizability, OBIF analyzed data from a diverse array of Omics platforms and experimental conditions, successfully identifying the molecular clusters driving their synergistic responses. Hence, unlike existing synergy quantification and prediction methods, OBIF is a phenotype-driven systems model that supports multiplatform interrogation of synergy mechanisms.

Single-Cell Profiling Reveals Heterogeneity of Primary and Lymph Node Metastatic Tumors and Immune Cell Populations and Discovers Important Prognostic Significance of CCDC43 in Oral Squamous Cell Carcinoma

Although substantial progress has been made in biological research and clinical treatment in recent years, the clinical prognosis of oral squamous cell carcinoma (OSCC) is still not satisfactory. Tumor immune microenvironment (TIME) is a potential target, which plays an essential role in the response of anti-tumor immunity and immunotherapy. In this study, we used scRNA-seq data, revealing the heterogeneity of TIME between metastatic and primary site. We found that in the metastatic site, the content of cytotoxic T cells and classical activated macrophages (M1 macrophages) increases significantly, while alternately activated macrophages (M2 macrophages) and inflammatory cancer-associated fibroblasts (iCAFs) decrease, which may be due to the increased immunogenicity of OSCC cells in the metastatic site and the changes in some signal pathways. We also found that iCAFs may recruit alternately activated macrophages (M2 macrophages) by secreting CXCL12. Then, we described a regulatory network for communication between various TIME cells centered on OSCC cells, which can help to clarify the possible mechanism of lymph node metastasis in OSCC cells. By performing pseudotime trajectory analysis, we found that the expression CCDC43 is upregulated in more advanced OSCC cells and is an independent prognostic factor for poor living conditions. Other than this, the high expression of CCDC43 may impair the antitumor immunity of the human body and promote the metastasis of OSCC cells. Our research provides a profound insight into the immunological study of OSCC and an essential resource for future drug discovery.

Assay for transposase-accessible chromatin with high-throughput sequencing reveals radioresistance-related genes in oral squamous cell carcinoma cells

Radiotherapy is commonly used to treat oral squamous cell carcinoma (OSCC), and radioresistance is a critical factor resulting in poor outcomes. Several genes have been reported to be therapeutic targets for radioresistance; however, the involvement of chromatin accessibility in radioresistance has not been clarified in OSCC cells. Accordingly, in this study, we evaluated chromatin accessibility in radioresistant (HSC-3) and radiosensitive (KOSC-2) cells, identified from nine OSCC cell lines using clonogenic survival assays after irradiation. Chromatin accessibility in radioresistant OSCC cells was assessed using assay for transposase-accessible chromatin with high-throughput sequencing (ATAC-seq). Gene expression was evaluated by quantitative reverse transcriptase-polymerase chain reaction (RT-qPCR) and immunoblot analysis. Viability was assessed by MTS assay. We found 1273 peaks (open chromatin regions by ATAC-seq) related to 8 Gy irradiation in HSC-3 but not KOSC-2 cells, among which 235 genes located around the chromatin open peaks were identified by ChIPpeakAnno analysis. Subsequently, 12 genes were selected as signal transduction-related genes by Gene Ontology analysis, and gene expression was confirmed by RT-qPCR. Among these genes, adenylate cyclase 2 (ADCY2) was significantly upregulated after treatment with irradiation in HSC-3 but not KOSC-2 cells. To further evaluate ADCY2 function in radioresistant cells, we performed ADCY2 knockdown by transfection of HSC-3 cells with small interfering RNA (siADCY2). Cell viability after irradiation was significantly decreased in siADCY2-transfected cells compared with that in control cells. These results suggested that ADCY2 expression was related to the open chromatin region in radioresistant OSCC cells and that ADCY2 may have therapeutic efficacy when used in combination with radiotherapy in patients with OSCC.

scInTime: A Computational Method Leveraging Single-Cell Trajectory and Gene Regulatory Networks to Identify Master Regulators of Cellular Differentiation

Trajectory inference (TI) or pseudotime analysis has dramatically extended the analytical framework of single-cell RNA-seq data, allowing regulatory genes contributing to cell differentiation and those involved in various dynamic cellular processes to be identified. However, most TI analysis procedures deal with individual genes independently while overlooking the regulatory relations between genes. Integrating information from gene regulatory networks (GRNs) at different pseudotime points may lead to more interpretable TI results. To this end, we introduce scInTime-an unsupervised machine learning framework coupling inferred trajectory with single-cell GRNs (scGRNs) to identify master regulatory genes. We validated the performance of our method by analyzing multiple scRNA-seq data sets. In each of the cases, top-ranking genes predicted by scInTime supported their functional relevance with corresponding signaling pathways, in line with the results of available functional studies. Overall results demonstrated that scInTime is a powerful tool to exploit pseudotime-series scGRNs, allowing for a clear interpretation of TI results toward more significant biological insights.

The Epithelial-Mesenchymal Transition Influences the Resistance of Oral Squamous Cell Carcinoma to Monoclonal Antibodies via Its Effect on Energy Homeostasis and the Tumor Microenvironment

Oral squamous cell carcinoma (OSCC) is a major type of cancer that accounts for over 90% of all oral cancer cases. Recently developed evidence-based therapeutic regimens for OSCC based on monoclonal antibodies (mAbs), such as cetuximab, pembrolizumab, and nivolumab, have attracted considerable attention worldwide due to their high specificity, low toxicity, and low rates of intolerance. However, the efficacy of those three mAbs remains poor because of the low rate of responders and acquired resistance within a short period of time. The epithelial-mesenchymal transition (EMT) process is fundamental for OSCC growth and metastasis and is also responsible for the poor response to mAbs. During EMT, cancer cells consume abundant energy substrates and create an immunosuppressive tumor microenvironment to support their growth and evade T cells. In this review, we provide an overview of the complex roles of major substrates and signaling pathways involved in the development of therapeutic resistance in OSCC. In addition, we summarize potential therapeutic strategies that may help overcome this resistance. This review aims to help oral oncologists and researchers aiming to manage OSCC and establish new treatment modalities.

Omics and Computational Modeling Approaches for the Effective Treatment of Drug-Resistant Cancer Cells

Chemotherapy is a mainstream cancer treatment, but has a constant challenge of drug resistance, which consequently leads to poor prognosis in cancer treatment. For better understanding and effective treatment of drug-resistant cancer cells, omics approaches have been widely conducted in various forms. A notable use of omics data beyond routine data mining is to use them for computational modeling that allows generating useful predictions, such as drug responses and prognostic biomarkers. In particular, an increasing volume of omics data has facilitated the development of machine learning models. In this mini review, we highlight recent studies on the use of multi-omics data for studying drug-resistant cancer cells. We put a particular focus on studies that use computational models to characterize drug-resistant cancer cells, and to predict biomarkers and/or drug responses. Computational models covered in this mini review include network-based models, machine learning models and genome-scale metabolic models. We also provide perspectives on future research opportunities for combating drug-resistant cancer cells.

Possible Immunotherapeutic Strategies Based on Carcinogen-Dependent Subgroup Classification for Oral Cancer

The oral cavity serves as an open local organ of the human body, exposed to multiple external factors from the outside environment. Coincidentally, initiation and development of oral cancer are attributed to many external factors, such as smoking and drinking, to a great extent. This phenomenon was partly explained by the genetic abnormalities traditionally induced by carcinogens. However, more and more attention has been attracted to the influence of carcinogens on the local immune status. On the other hand, immune heterogeneity of cancer patients is a huge obstacle for enhancing the clinical efficacy of tumor immunotherapy. Thus, in this review, we try to summarize the current opinions about variant genetic changes and multiple immune alterations induced by different oral cancer carcinogens and discuss the prospects of targeted immunotherapeutic strategies based on specific immune abnormalities caused by different carcinogens, as a predictive way to improve clinical outcomes of immunotherapy-treated oral cancer patients.

Current Insights and Advancements in Head and Neck Cancer: Emerging Biomarkers and Therapeutics with Cues from Single Cell and 3D Model Omics Profiling

Head and neck cancer (HNC) is among the ten leading malignancies worldwide, with India solely contributing one-third of global oral cancer cases. The current focus of all cutting-edge strategies against this global malignancy are directed towards the heterogeneous tumor microenvironment that obstructs most treatment blueprints. Subsequent to the portrayal of established information, the review details the application of single cell technology, organoids and spheroid technology in relevance to head and neck cancer and the tumor microenvironment acknowledging the resistance pattern of the heterogeneous cell population in HNC. Bioinformatic tools are used for study of differentially expressed genes and further omics data analysis. However, these tools have several challenges and limitations when analyzing single-cell gene expression data that are discussed briefly. The review further examines the omics of HNC, through comprehensive analyses of genomics, transcriptomics, proteomics, metabolomics, and epigenomics profiles. Patterns of alterations vary between patients, thus heterogeneity and molecular alterations between patients have driven the clinical significance of molecular targeted therapies. The analyses of potential molecular targets in HNC are discussed with connotation to the alteration of key pathways in HNC followed by a comprehensive study of protein kinases as novel drug targets including its ATPase and additional binding pockets, non-catalytic domains and single residues. We herein review, the therapeutic agents targeting the potential biomarkers in light of new molecular targeted therapies. In the final analysis, this review suggests that the development of improved target-specific personalized therapies can combat HNC's global plight.

PD-L1 is upregulated via BRD2 in head and neck squamous cell carcinoma models of acquired cetuximab resistance

BACKGROUND

Tumor models resistant to EGFR tyrosine kinase inhibitors or cisplatin express higher levels of the immune checkpoint molecule PD-L1. We sought to determine whether PD-L1 expression is elevated in head and neck squamous cell carcinoma (HNSCC) models of acquired cetuximab resistance and whether the expression is regulated by bromodomain and extraterminal domain (BET) proteins.

METHODS

Expression of PD-L1 was assessed in HNSCC cell line models of acquired cetuximab resistance. Proteolysis targeting chimera (PROTAC)- and RNAi-mediated targeting were used to assess the role of BET proteins.

RESULTS

Cetuximab-resistant HNSCC cells expressed elevated PD-L1 compared to cetuximab-sensitive controls. Treatment with the BET inhibitor JQ1, the BET PROTAC MZ1, or RNAi-mediated knockdown of BRD2 decreased PD-L1 expression. Knockdown of BRD2 also reduced the elevated levels of PD-L1 seen in a model of acquired cisplatin resistance.

CONCLUSIONS

PD-L1 is significantly elevated in HNSCC models of acquired cetuximab and cisplatin resistance where BRD2 is the primary regulator.

HDAC Inhibitors: Dissecting Mechanisms of Action to Counter Tumor Heterogeneity

Intra-tumoral heterogeneity presents a major obstacle to cancer therapeutics, including conventional chemotherapy, immunotherapy, and targeted therapies. Stochastic events such as mutations, chromosomal aberrations, and epigenetic dysregulation, as well as micro-environmental selection pressures related to nutrient and oxygen availability, immune infiltration, and immunoediting processes can drive immense phenotypic variability in tumor cells. Here, we discuss how histone deacetylase inhibitors, a prominent class of epigenetic drugs, can be leveraged to counter tumor heterogeneity. We examine their effects on cellular processes that contribute to heterogeneity and provide insights on their mechanisms of action that could assist in the development of future therapeutic approaches.

Epithelial-Mesenchymal Transition Associated with Head and Neck Squamous Cell Carcinomas: A Review

Head and neck squamous cell carcinomas (HNSCCs) are aggressive, recurrent, and metastatic neoplasms with a high occurrence around the world and can lead to death when not treated appropriately. Several molecules and signaling pathways are involved in the malignant conversion process. Epithelial-mesenchymal transition (EMT) has been described in HNSCCs, a major type of aggressive carcinoma. EMT describes the development of epithelial cells into mesenchymal cells, which depends on several molecular interactions and signaling pathways that facilitate mesenchymal conversion. This is related to interactions with the microenvironment of the tumor, hypoxia, growth factors, matrix metalloproteinases, and the presence of viral infections. In this review, we focus on the main molecules related to EMT, their interactions with the tumor microenvironment, plasticity phenomena, epigenetic regulation, hypoxia, inflammation, their relationship with immune cells, and the inhibition of EMT in the context of HNSCCs.

Linc00467 promotes invasion and inhibits apoptosis of head and neck squamous cell carcinoma by regulating miR-1285-3p/TFAP2A

OBJECTIVE

To explore the invasion and apoptosis of head and neck squamous cell carcinoma (HNSCC) regulated by Linc00467 through the miR-1285-3p/TFAP2A axis.

METHODS

qRT-PCR was used to detect the expressions of Linc00467, miR-1285-3p, and TFAP2A in tissues and cells of HNSCC patients. The targeting relationships between Linc00467 and miR-1285-3p, miR-1285-3p, and TFAP2A were verified by dual-luciferase reporter assay. Transfection and grouping were carried out, after HNSCC cell lines were screened. Transwell assay and flow cytometry were used to test cell invasion and apoptosis, respectively.

RESULTS

Compared with normal tissues adjacent to the tumor, the expressions of Linc00467 and TFAP2A increased significantly in cancer tissues, while the expression of miR-1285-3p decreased (all P<0.05). Compared with the si-NC group, the invasion of the si-Linc00467 group decreased and the apoptosis rate increased (both P<0.05). In HNSCC cells, over-expression of Linc00467 promoted increased cell invasion and decreased apoptosis rate, which could be partially rescued by over-expression of miR-1285-3p (all P<0.05). Over-expression of miR-1285-3p caused decreased cell invasion and increased apoptosis rate, which was partially reversed by over-expression of TFAP2A (all P<0.05).

CONCLUSION

Linc00467 can be used as ceRNA to adsorb miR-1285-3p to regulate the expression of TFAP2A, promote invasion and inhibit apoptosis of HNSCC cells. Linc00467 inhibitors may become one of the targeted therapeutic drugs for HNSCC.

Oct4 confers stemness and radioresistance to head and neck squamous cell carcinoma by regulating the homologous recombination factors PSMC3IP and RAD54L

Head and neck squamous cell carcinoma (HNSCC) is often being diagnosed at an advanced stage, conferring a poor prognosis. The probability of local tumor control after radiotherapy depends on the eradication of cancer stem cells (CSCs) with activated DNA repair. This study provides evidence that the CSC-related transcription factor Oct4 contributes to HNSCC radioresistance by regulating DNA damage response and the CSC phenotype. Knockdown of Oct4 A isoform reduced self-renewal capacity in HNSCC and led to partial tumor cell radiosensitization caused by transcriptional downregulation of the cell cycle checkpoint kinases CHK1 and WEE1 and homologous recombination (HR) repair genes PSMC3IP and RAD54L. Besides, PARP inhibition with Olaparib selectively radiosensitized Oct4 A knockout, but not wild-type HNSCC cells. This finding links Oct4 A to the HR-mediated DNA repair mechanisms. In turn, knockdown of PSMC3IP and RAD54L reduced the HNSCC self-renewal capacity and clonogenic cell survival after irradiation, suggesting the interplay between DNA repair and the CSC phenotype. Similar to the effect of Oct4 knockdown, overexpression of Oct4 also resulted in significant HNSCC radiosensitization and increased DNA damage, suggesting that Oct4-dependent regulation of DNA repair depends on its fine-tuned expression. In line with this observation, HNSCC patients with high and low nuclear Oct4 expression at the invasive tumor front exhibited better loco-regional tumor control after postoperative radio(chemo)therapy compared to the intermediate expression subgroup. Thus, we found that the Oct4-driven transcriptional program plays a critical role in regulating HNSCC radioresistance, and a combination of radiotherapy with PARP inhibitors may induce synthetic lethality in Oct4-deregulated tumors.

Single-Cell Deconvolution of Head and Neck Squamous Cell Carcinoma

Complexities in cell-type composition have rightfully led to skepticism and caution in the interpretation of bulk transcriptomic analyses. Recent studies have shown that deconvolution algorithms can be utilized to computationally estimate cell-type proportions from the gene expression data of bulk blood samples, but their performance when applied to tumor tissues, including those from head and neck, remains poorly characterized. Here, we use single-cell data (~6000 single cells) collected from 21 head and neck squamous cell carcinoma (HNSCC) samples to generate cell-type-specific gene expression signatures. We leverage bulk RNA-seq data from >500 HNSCC samples profiled by The Cancer Genome Atlas (TCGA), and using single-cell data as a reference, apply two newly developed deconvolution algorithms (CIBERSORTx and MuSiC) to the bulk transcriptome data to quantitatively estimate cell-type proportions for each tumor in TCGA. We show that these two algorithms produce similar estimates of constituent/major cell-type proportions and that a high T-cell fraction correlates with improved survival. By further characterizing T-cell subpopulations, we identify that regulatory T-cells (Tregs) were the major contributor to this improved survival. Lastly, we assessed gene expression, specifically in the Treg population, and found that TNFRSF4 (Tumor Necrosis Factor Receptor Superfamily Member 4) was differentially expressed in the core Treg subpopulation. Moreover, higher TNFRSF4 expression was associated with greater survival, suggesting that TNFRSF4 could play a key role in mechanisms underlying the contribution of Treg in HNSCC outcomes.

Precision Medicine Approaches to Overcome Resistance to Therapy in Head and Neck Cancers

Head and neck squamous cell carcinoma (HNSCC) is the sixth most incident cancer worldwide. More than half of HNSCC patients experience locoregional or distant relapse to treatment despite aggressive multimodal therapeutic approaches that include surgical resection, radiation therapy, and adjuvant chemotherapy. Before the arrival of immunotherapy, systemic chemotherapy was previously employed as the standard first-line protocol with an association of cisplatin or carboplatin plus 5-fluorouracil plus cetuximab (anti-EFGR antibody). Unfortunately, acquisition of therapy resistance is common in patients with HNSCC and often results in local and distant failure. Despite our better understanding of HNSCC biology, no other molecular-targeted agent has been approved for HNSCC. In this review, we outline the mechanisms of resistance to the therapeutic strategies currently used in HNSCC, discuss combination treatment strategies to overcome them, and summarize the therapeutic regimens that are presently being evaluated in early- and late-phase clinical trials.

The Inhibition of CDK8/19 Mediator Kinases Prevents the Development of Resistance to EGFR-Targeting Drugs

Drug resistance is the main obstacle to achieving cures with both conventional and targeted anticancer drugs. The emergence of acquired drug resistance is initially mediated by non-genetic transcriptional changes, which occur at a much higher frequency than mutations and may involve population-scale transcriptomic adaptation. CDK8/19 kinases, through association with transcriptional Mediator complex, regulate transcriptional reprogramming by co-operating with different signal-responsive transcription factors. Here we tested if CDK8/19 inhibition could prevent adaptation to drugs acting on epidermal growth factor receptor (EGFR/ERBB1/HER1). The development of resistance was analyzed following long-term exposure of BT474 and SKBR3 breast cancer cells to EGFR-targeting small molecules (gefitinib, erlotinib) and of SW48 colon cancer cells to an anti-EGFR monoclonal antibody cetuximab. In all cases, treatment of small cell populations (~10⁵ cells) with a single dose of the drug initially led to growth inhibition that was followed by the resumption of proliferation and development of drug resistance in the adapted populations. However, this adaptation was always prevented by the addition of selective CDK8/19 inhibitors, even though such inhibitors alone had only moderate or no effect on cell growth. These results indicate that combining EGFR-targeting drugs with CDK8/19 inhibitors may delay or prevent the development of tumor resistance to therapy.

scTenifoldNet: A Machine Learning Workflow for Constructing and Comparing Transcriptome-wide Gene Regulatory Networks from Single-Cell Data

We present scTenifoldNet-a machine learning workflow built upon principal-component regression, low-rank tensor approximation, and manifold alignment-for constructing and comparing single-cell gene regulatory networks (scGRNs) using data from single-cell RNA sequencing. scTenifoldNet reveals regulatory changes in gene expression between samples by comparing the constructed scGRNs. With real data, scTenifoldNet identifies specific gene expression programs associated with different biological processes, providing critical insights into the underlying mechanism of regulatory networks governing cellular transcriptional activities.

Environmental Epigenetics of Diesel Particulate Matter Toxicogenomics

Autism spectrum disorder (ASD) is a neurodevelopmental disorder characterized by disruptions in social communication and behavioral flexibility. Both genetic and environmental factors contribute to ASD risk. Epidemiologic studies indicate that roadway vehicle exhaust and in utero exposure to diesel particulate matter (DPM) are associated with ASD. Using the Comparative Toxicogenomics Database (CTD), we identified genes connected to DPM exposure and ASD, extracted the known enhancers/promoters of the identified genes, and integrated this with Assay for Transposase Accessible Chromatin (ATAC-seq) data from DPM-exposed human neural progenitor cells. Enhancer/promoter elements with significantly different chromosome accessibility revealed enriched DNA sequence motifs with transcription factor binding sites for EGR1. Variant extraction for linkage disequilibrium blocks of these regions followed by analysis through Genome Wide Association Studies (GWAS) revealed multiple neurological trait associations including exploratory eye movement and brain volume measurement. This approach highlights the effects of pollution on the regulatory regions of genes implicated in ASD by genetic studies, indicating convergence of genetic and environmental factors on molecular networks that contribute to ASD. Integration of publicly available data from the CTD, cell culture exposure studies, and phenotypic genetics synergize extensive evidence of chemical exposures on gene regulation for altered brain development.