Mining of Self-Organizing Map Gene-Expression Portraits Reveals Prognostic Stratification of HPV-Positive Head and Neck Squamous Cell Carcinoma

Tumor Subtype Classification Tool for HPV-associated Head and Neck Cancers

Importance

Molecular subtypes of HPV-associated Head and Neck Squamous Cell Carcinoma (HNSCC), named IMU (immune strong) and KRT (highly keratinized), are well-recognized and have been shown to have distinct mechanisms of carcinogenesis, clinical outcomes, and potentially differing optimal treatment strategies. Currently, no standardized method exists to subtype a new HPV+ HNSCC tumor. Our paper introduces a machine learning-based classifier and webtool to reliably subtype HPV+ HNSCC tumors using the IMU/KRT paradigm and highlights the importance of subtype in HPV+ HNSCC.

Objective

To develop a robust, accurate machine learning-based classification tool that standardizes the process of subtyping HPV+ HNSCC, and to investigate the clinical, demographic, and molecular features associated with subtype in a meta-analysis of four patient cohorts.

Data Sources

We conducted RNA-seq on 67 HNSCC FFPE blocks from University of Michigan hospital. Combining this with three publicly available datasets, we utilized a total of 229 HPV+ HNSCC RNA-seq samples. All participants were HPV+ according to RNA expression. An ensemble machine learning approach with five algorithms and three different input training gene sets were developed, with final subtype determined by majority vote. Several additional steps were taken to ensure rigor and reproducibility throughout.

Study Selection

The classifier was trained and tested using 84 subtype-labeled HPV+ RNA-seq samples from two cohorts: University of Michigan (UM; n=18) and TCGA-HNC (n=66). The classifier robustness was validated with two independent cohorts: 83 samples from the HPV Virome Consortium and 62 additional samples from UM. We revealed 24 of 39 tested clinicodemographic and molecular variables significantly associated with subtype.

Results

The classifier achieved 100% accuracy in the test set. Validation on two additional cohorts demonstrated successful separation by known features of the subtypes. Investigating the relationship between subtype and 39 molecular and clinicodemographic variables revealed IMU is associated with epithelial-mesenchymal transition (p=2.25×10-4), various immune cell types, and lower radiation resistance (p=0.0050), while KRT is more highly keratinized (p=2.53×10-8), and more likely female than IMU (p=0.0082).

Conclusions and Relevance

This study provides a reliable classifier for subtyping HPV+ HNSCC tumors as either IMU or KRT based on bulk RNA-seq data, and additionally, improves our understanding of the HPV+ HNSCC subtypes.

Tumor molecular landscape of Epstein-Barr virus (EBV) related nasopharyngeal carcinoma in EBV-endemic and non-endemic areas: Implications for improving treatment modalities

Epstein-Barr virus (EBV) related- nasopharyngeal carcinoma (NPC) is a squamous carcinoma of the nasopharyngeal mucosal lining. Endemic areas (EA) are east and Southeast Asia, were NPC was recorded with higher incidence and longer estimated survival than in non-endemic area (NEA) such as Europe, We analyzed the gene expression and microenvironment properties of NPC in both areas to identify molecular subtypes and assess biological and clinical correlates that might explain the differences in incidence and outcome between EA- and NEA-NPCs. Six EA-NPC transcriptomic datasets, including tumor and normal samples, were integrated in a meta-analysis to identify molecular subtypes using a ConsensusClusterPlus bioinformatic approach. Based on the biological/functional characterization of four identified clusters were identified: Cl1, Immune-active; Cl2, defense-response; Cl3, proliferation; Cl4, perineural-interaction/EBV-exhaustion. Kaplan-Meier survival analysis, applied to the single dataset with available disease-free survival indicated Cl3 as the cluster with the worst prognosis (P = 0.0476), confirmed when applying four previously published prognostic signatures. A Cl3 classifier signature was generated and its prognostic performance was confirmed (P = 0.0368) on a validation dataset. Prediction of treatment response suggested better responses to: radiotherapy and immune checkpoint inhibitors immune-active and defense-response clusters; chemotherapy proliferation cluster; cisplatin perineural-interaction/EBV-exhaustion cluster. RNA sequencing for gene expression profiling was performed on 50 NEA-NPC Italian samples. In the NEA cohort, Cl1, Cl2 and Cl3 were represented, while perineural-interaction/EBV-exhaustion was almost absent. The immune/biological characterization and treatment-response prediction analyses of NEA-NPC partially replicated the EA-NPC results. Well characterized EA- and NEA-NPC retrospective and prospective cohorts are needed to validate the obtained results and can help designing future clinical studies.

Identification of TTC21A as a Potential Prognostic Marker in Head and Neck Squamous Cell Carcinoma: In Silico Analysis

BACKGROUND/AIM

Tetratricopeptide repeat domain 21A (TTC21A) plays a crucial role in ciliary function and has been associated with various pathogenic processes, including carcinogenesis. However, its role in head and neck squamous cell carcinoma (HNSCC) has not been elucidated.

MATERIALS AND METHODS

Based on the sequencing and microarray data of HNSCC from publicly available databases, the expression of TTC21A was compared between different subgroups based on clinical and molecular parameters. The survival analysis and regression analysis were conducted using the Kaplan-Meier method and the Cox method, respectively. Functional analysis was performed by the Kyoto Encyclopedia of Genes and Genomes (KEGG), Gene Ontology (GO), and gene set enrichment analysis (GSEA) tools. Immune infiltration analysis was performed based on the expression of TTC21A.

RESULTS

TTC21A decreased in tumor tissues and was associated with N stage, histologic grade, HPV infection, and TP53 mutation in HNSCC. TTC21A was an independent indicator of overall survival for patients with HNSCC. A high level of TTC21A expression indicated a favorable prognosis. The TTC21A expression level was involved with immune-related signaling regulation, immune-related gene expression, and immune cell infiltration. TTC21A expression was potent in predicting immunotherapeutic benefits.

CONCLUSION

TTC21A, as a potential predictor of favorable outcomes and immunotherapy response for HNSCC, is related to immune-related signaling regulation, immune-related gene expression, and immune cell infiltration.

Bioinformatics analysis of immune characteristics in tumors with alternative carcinogenesis pathways induced by human papillomaviruses

BACKGROUND

Human papillomaviruses (HPVs) induce a subset of head and neck squamous cell carcinomas (HNSCC) and anogenital cancers, particularly cervical cancer (CC). The major viral proteins that contribute to tumorigenesis are the E6 and E7 oncoproteins, whose expression is usually enhanced after the integration of viral DNA into the host genome. Recently, an alternative tumorigenesis pathway has been suggested in approximately half of HNSCC and CC cases associated with HPV infection. This pathway is characterized by extrachromosomal HPV persistence and increased expression of the viral E2, E4, and E5 genes. The E6, E7, E5, and E2 proteins have been shown to modify the expression of numerous cellular immune-related genes. The antitumor immune response is a critical factor in the prognosis of HPV-driven cancers, and its characterization may contribute to the prediction and personalization of the increasingly used cancer immunotherapy.

METHODS

We analyzed the immune characteristics of HPV-dependent tumors and their association with carcinogenesis types. Transcriptomic HNSCC and CC datasets from The Cancer Genome Atlas were used for this analysis.

RESULTS

Clustering with immune-related genes resulted in two clusters of HPV16-positive squamous cell carcinomas in both tumor types: cluster 1 had higher activation of immune responses, including stimulation of the antigen processing and presentation pathway, which was associated with higher immune cell infiltration and better overall survival, and cluster 2 was characterized by keratinization. In CC, the distribution of tumor samples into clusters 1 and 2 did not depend on the level of E2/E5 expression, but in HNSCC, most E2/E5-high tumors were localized in cluster 1 and E2/E5-low tumors in cluster 2. Further analysis did not reveal any association between the E2/E5 levels and the expression of immune-related genes.

CONCLUSIONS

Our results suggest that while the detection of immune responses associated with preserved expression of genes encoding components of antigen processing and presentation machinery in HPV-driven tumors may be markers of better prognosis and an important factor in therapy selection, the type of carcinogenesis does not seem to play a decisive role in the induction of antitumor immunity.

Bioinformatics in Early Cancer Detection

Bioinformatics is a pretty recent branch of biology that encompasses the use of algebraic, analytic, and computing approaches to the processing and interpretation of biological information. A wide term, "bioinformatics" refers to the use of digital technology to study biological processes using high-dimensional data collected from many resources. The design and testing of the software tools required to evaluate the information are the core of bioinformatics research, which is conducted in great portions in silico and typically involves the synthesis of new learning from available data. Early diagnosis of cancer results in improved prognosis, but at the same time, it is difficult to conform to diagnosis at a very early stage. The use of DNA microarrays and proteomics studies for large-scale gene expression research has advanced technology, thus elevating the significance of bioinformatics tools. In today's research, wet experimentation and the application of bioinformatics analytics go side by side. Molecular profiling of tumor biopsies is becoming more and more crucial to both cancer research and the treatment of cancer.

Clinical, morphologic and molecular heterogeneity of HPV-associated oropharyngeal cancer

The incidence of human papillomavirus-positive (HPV+) oropharyngeal squamous cell carcinoma (OPSCC) is rising rapidly and has exceeded cervical cancer to become the most common HPV-induced cancer in developed countries. Since patients with HPV + OPSCC respond very favorably to standard aggressive treatment, the emphasis has changed to reducing treatment intensity. However, recent multi-center clinical trials failed to show non-inferiority of de-escalation strategies on a population basis, highlighting the need to select low-risk patients likely to respond to de-intensified treatments. In contrast, there is a substantial proportion of patients who develop recurrent disease despite aggressive therapy. This supports that HPV + OPSCC is not a homogeneous disease, but comprises distinct subtypes with clinical and biological variations. The overall goal for this review is to identify biomarkers for HPV + OPSCC that may be relevant for patient stratification for personalized treatment. We discuss HPV + OPSCC as a heterogeneous disease from multifaceted perspectives including clinical behavior, tumor morphology, and molecular phenotype. Molecular profiling from bulk tumors as well as single-cell sequencing data are discussed as potential driving factors of heterogeneity between tumor subgroups. Finally, we evaluate key challenges that may impede in-depth investigations of HPV + OPSCC heterogeneity and outline potential future directions, including a section on racial and ethnic differences.

Whole-genome CpG-resolution DNA Methylation Profiling of HNSCC Reveals Distinct Mechanisms of Carcinogenesis for Fine-scale HPV+ Cancer Subtypes

DNA methylation is a vital early step in carcinogenesis. Most findings of aberrant DNA methylation in head and neck squamous cell carcinomas (HNSCC) are array based with limited coverage and resolution, and mainly explored by human papillomavirus (HPV) status, ignoring the high heterogeneity of this disease. In this study, we performed whole-genome bisulfite sequencing on a well-studied HNSCC cohort (n = 36) and investigated the methylation changes between fine-scaled HNSCC subtypes in relation to genomic instability, repetitive elements, gene expression, and key carcinogenic pathways. The previously observed hypermethylation phenotype in HPV-positive (HPV+) tumors compared with HPV-negative tumors was robustly present in the immune-strong (IMU) HPV+ subtype but absent in the highly keratinized (KRT) HPV+ subtype. Methylation levels of IMU tumors were significantly higher in repetitive elements, and methylation showed a significant correlation with genomic stability, consistent with the IMU subtype having more genomic stability and better prognosis. Expression quantitative trait methylation (cis-eQTM) analysis revealed extensive functionally-relevant differences, and differential methylation pathway analysis recapitulated gene expression pathway differences between subtypes. Consistent with their characteristics, KRT and HPV-negative tumors had high regulatory potential for multiple regulators of keratinocyte differentiation, which positively correlated with an expression-based keratinization score. Together, our findings revealed distinct mechanisms of carcinogenesis between subtypes in HPV+ HNSCC and uncovered previously ignored epigenomic differences and clinical implications, illustrating the importance of fine-scale subtype analysis in cancer.

Significance

This study revealed that the previously observed hypermethylation of HPV(+) HNSCC is due solely to the IMU subtype, illustrating the importance of fine-scale subtype analysis in such a heterogeneous disease. Particularly, IMU has significantly higher methylation of transposable elements, which can be tested as a prognosis biomarker in future translational studies.

Towards Data Driven RT Prescription: Integrating Genomics into RT Clinical Practice

The genomic era has significantly changed the practice of clinical oncology. The use of genomic-based molecular diagnostics including prognostic genomic signatures and new-generation sequencing has become routine for clinical decisions regarding cytotoxic chemotherapy, targeted agents and immunotherapy. In contrast, clinical decisions regarding radiation therapy (RT) remain uninformed about the genomic heterogeneity of tumors. In this review, we discuss the clinical opportunity to utilize genomics to optimize RT dose. Although from the technical perspective, RT has been moving towards a data-driven approach, RT prescription dose is still based on a one-size-fits all approach, with most RT dose based on cancer diagnosis and stage. This approach is in direct conflict with the realization that tumors are biologically heterogeneous, and that cancer is not a single disease. Here, we discuss how genomics can be integrated into RT prescription dose, the clinical potential for this approach and how genomic-optimization of RT dose could lead to new understanding of the clinical benefit of RT.

Consensus clustering methodology to improve molecular stratification of non-small cell lung cancer

Recent advances in machine learning research, combined with the reduced sequencing costs enabled by modern next-generation sequencing, paved the way to the implementation of precision medicine through routine multi-omics molecular profiling of tumours. Thus, there is an emerging need of reliable models exploiting such data to retrieve clinically useful information. Here, we introduce an original consensus clustering approach, overcoming the intrinsic instability of common clustering methods based on molecular data. This approach is applied to the case of non-small cell lung cancer (NSCLC), integrating data of an ongoing clinical study (PROMOLE) with those made available by The Cancer Genome Atlas, to define a molecular-based stratification of the patients beyond, but still preserving, histological subtyping. The resulting subgroups are biologically characterized by well-defined mutational and gene-expression profiles and are significantly related to disease-free survival (DFS). Interestingly, it was observed that (1) cluster B, characterized by a short DFS, is enriched in KEAP1 and SKP2 mutations, that makes it an ideal candidate for further studies with inhibitors, and (2) over- and under-representation of inflammation and immune systems pathways in squamous-cell carcinomas subgroups could be potentially exploited to stratify patients treated with immunotherapy.

Evolution-Informed Strategies for Combating Drug Resistance in Cancer

The ever-changing nature of cancer poses the most difficult challenge oncologists face today. Cancer's remarkable adaptability has inspired many to work toward understanding the evolutionary dynamics that underlie this disease in hopes of learning new ways to fight it. Eco-evolutionary dynamics of a tumor are not accounted for in most standard treatment regimens, but exploiting them would help us combat treatment-resistant effectively. Here, we outline several notable efforts to exploit these dynamics and circumvent drug resistance in cancer.

Visualization and Semantic Labeling of Mood States Based on Time-Series Features of Eye Gaze and Facial Expressions by Unsupervised Learning

This study is intended to develop a stress measurement and visualization system for stress management in terms of simplicity and reliability. We present a classification and visualization method of mood states based on unsupervised machine learning (ML) algorithms. Our proposed method attempts to examine the relation between mood states and extracted categories in human communication from facial expressions, gaze distribution area and density, and rapid eye movements, defined as saccades. Using a psychological check sheet and a communication video with an interlocutor, an original benchmark dataset was obtained from 20 subjects (10 male, 10 female) in their 20s for four or eight weeks at weekly intervals. We used a Profile of Mood States Second edition (POMS2) psychological check sheet to extract total mood disturbance (TMD) and friendliness (F). These two indicators were classified into five categories using self-organizing maps (SOM) and U-Matrix. The relation between gaze and facial expressions was analyzed from the extracted five categories. Data from subjects in the positive categories were found to have a positive correlation with the concentrated distributions of gaze and saccades. Regarding facial expressions, the subjects showed a constant expression time of intentional smiles. By contrast, subjects in negative categories experienced a time difference in intentional smiles. Moreover, three comparative experiment results demonstrated that the feature addition of gaze and facial expressions to TMD and F clarified category boundaries obtained from U-Matrix. We verify that the use of SOM and its two variants is the best combination for the visualization of mood states.

Translation of Precision Medicine Research Into Biomarker-Informed Care in Radiation Oncology

The reach of personalized medicine in radiation oncology has expanded greatly over the past few decades as technical precision has improved the delivery of radiation to each patient's unique anatomy. Yet, the consideration of biological heterogeneity between patients has largely not been translated to clinical care. There are innumerable promising advancements in the discovery and validation of biomarkers, which could be used to alter radiation therapy directly or indirectly. Directly, biomarker-informed care may alter treatment dose or identify patients who would benefit most from radiation therapy and who could safely avoid more aggressive care. Indirectly, a variety of biomarkers could assist with choosing the best radiosensitizing chemotherapies. The translation of these advancements into clinical practice will bring radiation oncology even further into the era of precision medicine, treating patients according to their unique anatomical and biological differences.

Clinical Validity of a Prognostic Gene Expression Cluster-Based Model in Human Papillomavirus-Positive Oropharyngeal Carcinoma

Under common therapeutic regimens, the prognosis of human papillomavirus (HPV)–positive squamous oropharyngeal carcinomas (OPCs) is more favorable than HPV-negative OPCs. However, the prognosis of some tumors is dismal, and validated prognostic factors are missing in clinical practice. The present work aimed to validate the prognostic significance of our published three-cluster model and to compare its prognostic value with those of the 8^th edition of the tumor-node-metastasis staging system (TNM8) and published signatures and clustering models.

Pembrolizumab in the first-line treatment of advanced head and neck cancer

INTRODUCTION

Recurrent or metastatic (R/M) head and neck squamous cell carcinoma (HNSCC) is associated with dismal prognosis and has limited therapeutic options. PD-1/PD-L1 axis blockade was initially shown to improve outcomes in platinum-refractory HNSCC. More recently, pembrolizumab monotherapy or pembrolizumab combined with chemotherapy resulted in better overall survival than platinum, 5-fluorouracil, and cetuximab (EXTREME regimen) as first-line therapy for R/M HNSCC, establishing a new standard-of-care therapy for this disease.

AREAS COVERED

We review pembrolizumab in the first-line treatment of R/M HNSCC and summarize the impact of PD-L1 expression, tumor and symptom burden, and patient's performance status on treatment decisions. Future perspectives are summarized.

EXPERT OPINION

The standard-of-care first-line therapy for R/M HNSCC is pembrolizumab monotherapy for patients with a PD-L1 combined positive score (CPS)≥1 or pembrolizumab combined with platinum and 5-fluorouracil for patients with any PD-L1 status. Addition of chemotherapy to pembrolizumab increases the response rate but also toxicity and is preferred for patients with good performance status and significant tumor and symptom burden. For patients with a PD-L1 CPS <1, the EXTREME regimen should be considered. New strategies combining pembrolizumab with targeted therapies and immune checkpoints inhibitors are being explored to synergize or overcome resistance to anti-PD-1.

Causes and Consequences of HPV Integration in Head and Neck Squamous Cell Carcinomas: State of the Art

A constantly increasing incidence in high-risk Human Papillomaviruses (HPV)s driven head and neck squamous cell carcinomas (HNSCC)s, especially of oropharyngeal origin, is being observed. During persistent infections, viral DNA integration into the host genome may occur. Studies are examining if the physical status of the virus (episomal vs. integration) affects carcinogenesis and eventually has further-reaching consequences on disease progression and outcome. Here, we review the literature of the most recent five years focusing on the impact of HPV integration in HNSCCs, covering aspects of detection techniques used (from PCR up to NGS approaches), integration loci identified, and associations with genomic and clinical data. The consequences of HPV integration in the human genome, including the methylation status and deregulation of genes involved in cell signaling pathways, immune evasion, and response to therapy, are also summarized.

Pan-cancer prediction of radiotherapy benefit using genomic-adjusted radiation dose (GARD): a cohort-based pooled analysis

BACKGROUND

Despite advances in cancer genomics, radiotherapy is still prescribed on the basis of an empirical one-size-fits-all paradigm. Previously, we proposed a novel algorithm using the genomic-adjusted radiation dose (GARD) model to personalise prescription of radiation dose on the basis of the biological effect of a given physical dose of radiation, calculated using individual tumour genomics. We hypothesise that GARD will reveal interpatient heterogeneity associated with opportunities to improve outcomes compared with physical dose of radiotherapy alone. We aimed to test this hypothesis and investigate the GARD-based radiotherapy dosing paradigm.

METHODS

We did a pooled, pan-cancer analysis of 11 previously published clinical cohorts of unique patients with seven different types of cancer, which are all available cohorts with the data required to calculate GARD, together with clinical outcome. The included cancers were breast cancer, head and neck cancer, non-small-cell lung cancer, pancreatic cancer, endometrial cancer, melanoma, and glioma. Our dataset comprised 1615 unique patients, of whom 1298 (982 with radiotherapy, 316 without radiotherapy) were assessed for time to first recurrence and 677 patients (424 with radiotherapy and 253 without radiotherapy) were assessed for overall survival. We analysed two clinical outcomes of interest: time to first recurrence and overall survival. We used Cox regression, stratified by cohort, to test the association between GARD and outcome with separate models using dose of radiation and sham-GARD (ie, patients treated without radiotherapy, but modelled as having a standard-of-care dose of radiotherapy) for comparison. We did interaction tests between GARD and treatment (with or without radiotherapy) using the Wald statistic.

FINDINGS

Pooled analysis of all available data showed that GARD as a continuous variable is associated with time to first recurrence (hazard ratio [HR] 0·98 [95% CI 0·97-0·99]; p=0·0017) and overall survival (0·97 [0·95-0·99]; p=0·0007). The interaction test showed the effect of GARD on overall survival depends on whether or not that patient received radiotherapy (Wald statistic p=0·011). The interaction test for GARD and radiotherapy was not significant for time to first recurrence (Wald statistic p=0·22). The HR for physical dose of radiation was 0·99 (95% CI 0·97-1·01; p=0·53) for time to first recurrence and 1·00 (0·96-1·04; p=0·95) for overall survival. The HR for sham-GARD was 1·00 (0·97-1·03; p=1·00) for time to first recurrence and 1·00 (0·98-1·02; p=0·87) for overall survival.

INTERPRETATION

The biological effect of radiotherapy, as quantified by GARD, is significantly associated with time to first recurrence and overall survival for patients with cancer treated with radiation. It is predictive of radiotherapy benefit, and physical dose of radiation is not. We propose integration of genomics into radiation dosing decisions, using a GARD-based framework, as the new paradigm for personalising radiotherapy prescription dose.

FUNDING

None. VIDEO ABSTRACT.

Molecular Tumor Subtypes of HPV-Positive Head and Neck Cancers: Biological Characteristics and Implications for Clinical Outcomes

Until recently, research on the molecular signatures of Human papillomavirus (HPV)-associated head and neck cancers mainly focused on their differences with respect to HPV-negative head and neck squamous cell carcinomas (HNSCCs). However, given the continuing high incidence level of HPV-related HNSCC, the time is ripe to characterize the heterogeneity that exists within these cancers. Here, we review research thus far on HPV-positive HNSCC molecular subtypes, and their relationship with clinical characteristics and HPV integration into the host genome. Different omics data including host transcriptomics and epigenomics, as well as HPV characteristics, can provide complementary viewpoints. Keratinization, mesenchymal differentiation, immune signatures, stromal cells and oxidoreductive processes all play important roles.

Gene Expression and Resistance to Glucocorticoid-Induced Apoptosis in Acute Lymphoblastic Leukemia: A Brief Review and Update

BACKGROUND

Resistance to glucocorticoid (GC)-induced apoptosis in Acute Lymphoblastic Leukemia (ALL), is considered one of the major prognostic factors for the disease. Prednisolone is a corticosteroid and one of the most important agents in the treatment of acute lymphoblastic leukemia. The mechanics of GC resistance are largely unknown and intense ongoing research focuses on this topic.

AIM

The aim of the present study is to review some aspects of GC resistance in ALL, and in particular of Prednisolone, with emphasis on previous and present knowledge on gene expression and signaling pathways playing a role in the phenomenon.

METHODS

An electronic literature search was conducted by the authors from 1994 to June 2019. Original articles and systematic reviews selected, and the titles and abstracts of papers screened to determine whether they met the eligibility criteria, and full texts of the selected articles were retrieved.

RESULTS

Identification of gene targets responsible for glucocorticoid resistance may allow discovery of drugs, which in combination with glucocorticoids may increase the effectiveness of anti-leukemia therapies. The inherent plasticity of clinically evolving cancer justifies approaches to characterize and prevent undesirable activation of early oncogenic pathways.

CONCLUSION

Study of the pattern of intracellular signal pathway activation by anticancer drugs can lead to development of efficient treatment strategies by reducing detrimental secondary effects.

AKR1C3 is a biomarker and druggable target for oropharyngeal tumors

PURPOSE

Oropharynx squamous cell carcinoma (OPSCC) is a subtype of head and neck squamous cell carcinoma (HNSCC) arising from the base of the tongue, lingual tonsils, tonsils, oropharynx or pharynx. The majority of HPV-positive OPSCCs has a good prognosis, but a fraction of them has a poor prognosis, similar to HPV-negative OPSCCs. An in-depth understanding of the molecular mechanisms underlying OPSCC is mandatory for the identification of novel prognostic biomarkers and/or novel therapeutic targets.

METHODS

14 HPV-positive and 15 HPV-negative OPSCCs with 5-year follow-up information were subjected to gene expression profiling and, subsequently, compared to three extensive published OPSCC cohorts to define robust biomarkers for HPV-negative lesions. Validation of Aldo-keto-reductases 1C3 (AKR1C3) by qRT-PCR was carried out on an independent cohort (n = 111) of OPSCC cases. In addition, OPSCC cell lines Fadu and Cal-27 were treated with Cisplatin and/or specific AKR1C3 inhibitors to assess their (combined) therapeutic effects.

RESULTS

Gene set enrichment analysis (GSEA) on the four datasets revealed that the genes down-regulated in HPV-negative samples were mainly involved in immune system, whereas those up-regulated mainly in glutathione derivative biosynthetic and xenobiotic metabolic processes. A panel of 30 robust HPV-associated transcripts was identified, with AKR1C3 as top-overexpressed transcript in HPV-negative samples. AKR1C3 expression in 111 independent OPSCC cases positively correlated with a worse survival, both in the entire cohort and in HPV-positive samples. Pretreatment with a selective AKR1C3 inhibitor potentiated the effect of Cisplatin in OPSCC cells exhibiting higher basal AKR1C3 expression levels.

CONCLUSIONS

We identified AKR1C3 as a potential prognostic biomarker in OPSCC and as a potential drug target whose inhibition can potentiate the effect of Cisplatin.

5-Hydroxymethylation highlights the heterogeneity in keratinization and cell junctions in head and neck cancers

BACKGROUND

Head and neck squamous cell carcinoma (HNSCC) is the sixth most prevalent cancer worldwide, with human papillomavirus (HPV)-related HNSCC rising to concerning levels. Extensive clinical, genetic and epigenetic differences exist between HPV-associated HNSCC and HPV-negative HNSCC, which is often linked to tobacco use. However, 5-hydroxymethylation (5hmC), an oxidative derivative of DNA methylation and its heterogeneity among HNSCC subtypes, has not been studied.

RESULTS

We characterized genome-wide 5hmC profiles in HNSCC by HPV status and subtype in 18 HPV(+) and 18 HPV(-) well-characterized tumors. Results showed significant genome-wide hyper-5hmC in HPV(-) tumors, with both promoter and enhancer 5hmC able to distinguish meaningful tumor subgroups. We identified specific genes whose differential expression by HPV status is driven by differential hydroxymethylation. CDKN2A (p16), used as a key biomarker for HPV status, exhibited the most extensive hyper-5hmC in HPV(+) tumors, while HPV(-) tumors showed hyper-5hmC in CDH13, TIMP2, MMP2 and other cancer-related genes. Among the previously reported two HPV(+) subtypes, IMU (stronger immune response) and KRT (more keratinization), the IMU subtype revealed hyper-5hmC and up-regulation of genes in cell migration, and hypo-5hmC with down-regulation in keratinization and cell junctions. We experimentally validated our key prediction of higher secreted and intracellular protein levels of the invasion gene MMP2 in HPV(-) oral cavity cell lines.

CONCLUSION

Our results implicate 5hmC in driving differences in keratinization, cell junctions and other cancer-related processes among tumor subtypes. We conclude that 5hmC levels are critical for defining tumor characteristics and potentially used to define clinically meaningful cancer patient subgroups.

Development of a multiomics database for personalized prognostic forecasting in head and neck cancer: The Big Data to Decide EU Project

Background

Despite advances in treatments, 30% to 50% of stage III‐IV head and neck squamous cell carcinoma (HNSCC) patients relapse within 2 years after treatment. The Big Data to Decide (BD2Decide) project aimed to build a database for prognostic prediction modeling.

Methods

Stage III‐IV HNSCC patients with locoregionally advanced HNSCC treated with curative intent (1537) were included. Whole transcriptomics and radiomics analyses were performed using pretreatment tumor samples and computed tomography/magnetic resonance imaging scans, respectively.

Results

The entire cohort was composed of 71% male (1097)and 29% female (440): oral cavity (429, 28%), oropharynx (624, 41%), larynx (314, 20%), and hypopharynx (170, 11%); median follow‐up 50.5 months. Transcriptomics and imaging data were available for 1284 (83%) and 1239 (80%) cases, respectively; 1047 (68%) patients shared both.

Conclusions

This annotated database represents the HNSCC largest available repository and will enable to develop/validate a decision support system integrating multiscale data to explore through classical and machine learning models their prognostic role.

Transcriptomics and Epigenomics in head and neck cancer: available repositories and molecular signatures

For many years, head and neck squamous cell carcinoma (HNSCC) has been considered as a single entity. However, in the last decades HNSCC complexity and heterogeneity have been recognized. In parallel, high-throughput omics techniques had allowed picturing a larger spectrum of the behavior and characteristics of molecules in cancer and a large set of omics web-based tools and informative repository databases have been developed. The objective of the present review is to provide an overview on biological, prognostic and predictive molecular signatures in HNSCC. To contextualize the selected data, our literature survey includes a short summary of the main characteristics of omics data repositories and web-tools for data analyses. The timeframe of our analysis was fixed, encompassing papers published between January 2015 and January 2019. From more than 1000 papers evaluated, 61 omics studies were selected: 33 investigating mRNA signatures, 11 and 13 related to miRNA and other non-coding-RNA signatures and 4 analyzing DNA methylation signatures. More than half of identified signatures (36) had a prognostic value but only in 10 studies selection of a specific anatomical sub-site (8 oral cavity, 1 oropharynx and 1 both oral cavity and oropharynx) was performed. Noteworthy, although the sample size included in many studies was limited, about one-half of the retrieved studies reported an external validation on independent dataset(s), strengthening the relevance of the obtained data. Finally, we highlighted the development and exploitation of three gene-expression signatures, whose clinical impact on prognosis/prediction of treatment response could be high. Based on this overview on omics-related literature in HNSCC, we identified some limits and strengths. The major limits are represented by the low number of signatures associated to DNA methylation and to non-coding RNA (miRNA, lncRNA and piRNAs) and the availability of a single dataset with multiple omics on more than 500 HNSCC (i.e. TCGA). The major strengths rely on the integration of multiple datasets through meta-analysis approaches and on the growing integration among omics data obtained on the same cohort of patients. Moreover, new approaches based on artificial intelligence and informatic analyses are expected to be available in the next future.

PYHIN Proteins and HPV: Role in the Pathogenesis of Head and Neck Squamous Cell Carcinoma

In the last decades, the human papillomavirus (HPV) emerged as an etiological cause of head and neck squamous cell carcinoma (HNSCC), especially in the oropharynx. The role of two intracellular DNA sensors, which belong to the PYHIN family (interferon-inducible protein 16 (IFI16) and absent in melanoma 2 protein (AIM2)), has been analyzed in relation to HPV infection and head and neck carcinogenesis. In particular, IFI16 and AIM2 expression depends on HPV infection in HNSCC. They represent viral restriction factors and are key components of the intrinsic immunity activated against different viruses, including HPV. This review analyzed and summarized the recent findings about the role of PYHIN proteins in HPV⁺ and HPV⁻ HNSCC.