Establishment of a Machine Learning Model for the Risk Assessment of Perineural Invasion in Head and Neck Squamous Cell Carcinoma.

Perineural invasion is a prevalent pathological finding in head and neck squamous cell carcinoma and a risk factor for unfavorable survival. An adequate diagnosis of perineural invasion by pathologic examination is limited due to the availability of tumor samples from surgical resection, which can arise in cases of definitive nonsurgical treatment. To address this medical need, we established a random forest prediction model for the risk assessment of perineural invasion, including occult perineural invasion, and characterized distinct cellular and molecular features based on our new and extended classification. RNA sequencing data of head and neck squamous cell carcinoma from The Cancer Genome Atlas were used as a training cohort to identify differentially expressed genes that are associated with perineural invasion. A random forest classification model was established based on these differentially expressed genes and was validated by inspection of H&E-stained whole image slides. Differences in epigenetic regulation and the mutational landscape were detected by an integrative analysis of multiomics data and single-cell RNA-sequencing data were analyzed. We identified a 44-gene expression signature related to perineural invasion and enriched for genes mainly expressed in cancer cells according to single-cell RNA-sequencing data. A machine learning model was trained based on the expression pattern of the 44-gene set with the unique feature to predict occult perineural invasion. This extended classification model enabled a more accurate analysis of alterations in the mutational landscape and epigenetic regulation by DNA methylation as well as quantitative and qualitative differences in the cellular composition in the tumor microenvironment between head and neck squamous cell carcinoma with or without perineural invasion. In conclusion, the newly established model could not only complement histopathologic examination as an additional diagnostic tool but also guide the identification of new drug targets for therapeutic intervention in future clinical trials with head and neck squamous cell carcinoma patients at a higher risk for treatment failure due to perineural invasion.

Mitochondrial RNA modifications shape metabolic plasticity in metastasis.

Aggressive and metastatic cancers show enhanced metabolic plasticity1, but the precise underlying mechanisms of this remain unclear. Here we show how two NOP2/Sun RNA methyltransferase 3 (NSUN3)-dependent RNA modifications-5-methylcytosine (m5C) and its derivative 5-formylcytosine (f5C) (refs.2-4)-drive the translation of mitochondrial mRNA to power metastasis. Translation of mitochondrially encoded subunits of the oxidative phosphorylation complex depends on the formation of m5C at position 34 in mitochondrial tRNAMet. m5C-deficient human oral cancer cells exhibit increased levels of glycolysis and changes in their mitochondrial function that do not affect cell viability or primary tumour growth in vivo; however, metabolic plasticity is severely impaired as mitochondrial m5C-deficient tumours do not metastasize efficiently. We discovered that CD36-dependent non-dividing, metastasis-initiating tumour cells require mitochondrial m5C to activate invasion and dissemination. Moreover, a mitochondria-driven gene signature in patients with head and neck cancer is predictive for metastasis and disease progression. Finally, we confirm that this metabolic switch that allows the metastasis of tumour cells can be pharmacologically targeted through the inhibition of mitochondrial mRNA translation in vivo. Together, our results reveal that site-specific mitochondrial RNA modifications could be therapeutic targets to combat metastasis.

Prognostic Gene Signature for Squamous Cell Carcinoma with a Higher Risk for Treatment Failure and Accelerated MEK-ERK Pathway Activity.

Squamous cell carcinoma (SCC) is the most prevalent histological type of human cancer, including head and neck squamous cell carcinoma (HNSCC). However, reliable prognostic gene signatures for SCC and underlying genetic and/or epigenetic principles are still unclear. We identified 37 prognostic candidate genes by best cutoff computation based on survival in a pan-SCC cohort (n = 1334) of The Cancer Genome Atlas (TCGA), whose expression stratified not only the pan-SCC cohort but also independent HNSCC validation cohorts into three distinct prognostic subgroups. The most relevant prognostic genes were prioritized by a Least Absolute Shrinkage and Selection Operator Cox regression model and were used to identify subgroups with high or low risks for unfavorable survival. An integrative analysis of multi-omics data identified FN1, SEMA3A, CDH2, FBN1, COL5A1, and ADAM12 as key nodes in a regulatory network related to the prognostic phenotype. An in-silico drug screen predicted two MEK inhibitors (Trametinib and Selumetinib) as effective compounds for high-risk SCC based on the Cancer Cell Line Encyclopedia, which is supported by a higher p-MEK1/2 immunohistochemical staining of high-risk HNSCC. In conclusion, our data identified a molecular classifier for high-risk HNSCC as well as other SCC patients, who might benefit from treatment with MEK inhibitors.

Immune-Related Mutational Landscape and Gene Signatures: Prognostic Value and Therapeutic Impact for Head and Neck Cancer.

Immunotherapy by immune checkpoint inhibition has become a main pillar in the armamentarium to treat head and neck cancer and is based on the premise that the host immune system can be reactivated to successfully eliminate cancer cells. However, the response rate remains low and only a small subset of head and neck cancer patients achieves a durable clinical benefit. The availability of multi-omics data and emerging computational technologies facilitate not only a deeper understanding of the cellular composition in the tumor immune microenvironment but also enables the study of molecular principles in the complex regulation of immune surveillance versus tolerance. These knowledges will pave the way to apply immunotherapy more precisely and effectively. This review aims to provide a holistic view on how the immune landscape dictates the tumor fate and vice versa, and how integrative analysis of multi-omics data contribute to our current knowledge on the accuracy of predictive biomarkers and on a broad range of factors influencing the response to immunotherapy in head and neck cancer.

Unraveling most abundant mutational signatures in head and neck cancer.

Genomic alterations are a driving force in the multistep process of head and neck cancer (HNC) and result from the interaction of exogenous environmental exposures and endogenous cellular processes. Each of these processes leaves a characteristic pattern of mutations on the tumor genome providing the unique opportunity to decipher specific signatures of mutational processes operative during HNC pathogenesis and to address their prognostic value. Computational analysis of whole exome sequencing data of the HIPO-HNC (Heidelberg Center for Personalized Oncology-head and neck cancer) (n = 83) and TCGA-HNSC (The Cancer Genome Atlas-Head and Neck Squamous Cell Carcinoma) (n = 506) cohorts revealed five common mutational signatures (Catalogue of Somatic Mutations in Cancer [COSMIC] Signatures 1, 2, 3, 13 and 16) and demonstrated their significant association with etiological risk factors (tobacco, alcohol and HPV16). Unsupervised hierarchical clustering identified four clusters (A, B, C1 and C2) of which Subcluster C2 was enriched for cases with a higher frequency of signature 16 mutations. Tumors of Subcluster C2 had significantly lower p16INK4A expression accompanied by homozygous CDKN2A deletion in almost one half of cases. Survival analysis revealed an unfavorable prognosis for patients with tumors characterized by a higher mutation burden attributed to signature 16 as well as cases in Subcluster C2. Finally, a LASSO-Cox regression model was applied to prioritize clinically relevant signatures and to establish a prognostic risk score for head and neck squamous cell carcinoma patients. In conclusion, our study provides a proof of concept that computational analysis of somatic mutational signatures is not only a powerful tool to decipher environmental and intrinsic processes in the pathogenesis of HNC, but could also pave the way to establish reliable prognostic patterns.

Integrative Analysis of Multi-omics Data Identified EGFR and PTGS2 as Key Nodes in a Gene Regulatory Network Related to Immune Phenotypes in Head and Neck Cancer.

PURPOSE: Malignant progression exhibits a tightly orchestrated balance between immune effector response and tolerance. However, underlying molecular principles that drive the establishment and maintenance of the tumor immune phenotype remain to be elucidated. EXPERIMENTAL DESIGN: We trained a novel molecular classifier based on immune cell subsets related to programmed death-ligand 1 (PD-L1) and interferon γ (IFNγ) expression, which revealed distinct subgroups with higher (cluster A) or lower (subcluster B3) cytotoxic immune phenotypes. Integrative analysis of multi-omics data was conducted to identify differences in genetic and epigenetic landscapes as well as their impact on differentially expressed genes (DEG) among immune phenotypes. A prognostic gene signature for immune checkpoint inhibition (ICI) was established by a least absolute shrinkage and selection operator (LASSO)-Cox regression model. RESULTS: Mutational landscape analyses unraveled a higher frequency of CASP8 somatic mutations in subcluster A1, while subcluster B3 exhibited a characteristic pattern of copy-number alterations affecting chemokine signaling and immune effector response. The integrative multi-omics approach identified EGFR and PTGS2 as key nodes in a gene regulatory network related to the immune phenotype, and several DEGs related to the immune phenotypes were affected by EGFR inhibition in tumor cell lines. Finally, we established a prognostic gene signature by a LASSO-Cox regression model based on DEGs between nonprogressive disease and progressive disease subgroups for ICI. CONCLUSIONS: Our data highlight a complex interplay between genetic and epigenetic events in the establishment of the tumor immune phenotype and provide compelling experimental evidence that a patient with squamous cell carcinoma of the head and neck at higher risk for ICI treatment failure might benefit from a combination with EGFR inhibition.

Association of pediatric allergic rhinitis with the ratings of attention-deficit/hyperactivity disorder.

BACKGROUND: Allergic rhinitis (AR) is currently the most prevalent allergic disease in children and adolescents. OBJECTIVE: Surveys conducted by population-based studies of East Asia revealed an increased prevalence of behavioral disorders in patients with AR. Thus, in this study, we explored the prevalence of attention-deficit/hyperactivity disorder (ADHD) in pediatric patients with AR. METHODS: A total of 333 children (6-12 years of age) with AR and a total of 322 age-matched controls were included in this study. An otorhinolaryngologist diagnosed all AR cases and evaluated the severity of the disease. Skin-prick test results for 18 major allergens, Paediatric Rhinoconjunctivitis Quality of Life Questionnaire (PRQLQ), Child Behavior Checklist (CBCL), and Swanson, Nolan, and Pelham version IV (SNAP-IV) scores were recorded. RESULTS: In total, 320 age-matched controls and 323 children with AR completed the study. With respect to the Total Nasal Symptom Score and the PRQLQ, the condition of the experimental group was more serious than that of the controls. The scores on the hyperactivity/impulsivity and inattention subscales, which evaluate ADHD symptoms, and those on the CBCL subscales were significantly higher in patients with AR than in the controls (all p values were <0.01). From the results of the Pearson correlation, we deduced that there were significant positive correlations between the AR-related data and each subscale of the CBCL and SNAP-IV in the AR group. Moreover, two basic characteristics (males and environmental exposure to tobacco smoke) present significant positive and age showed a significant negative correlations affect ADHD symptom in both the AR group and the control group. Also, in the "pure AR" group, hierarchical regression analyses were performed to determine the subtests of the PRQLQ, which are significant predictors of SNAP-IV and CBCL. CONCLUSIONS: Apart from AR per se, the possible comorbidities of impulsivity and inattention are important when managing children with AR. It is essential to evaluate the symptoms of ADHD in children and adolescents with AR.

Efficacy of Sublingual Immunotherapy for House Dust Mite-Induced Allergic Rhinitis: A Meta-Analysis of Randomized Controlled Trials.

PURPOSE: Allergic rhinitis (AR) has become a global issue for a large part of the general population. Sublingual immunotherapy (SLIT) has been used extensively to treat persistent allergic rhinitis (PAR). Although systematic reviews have confirmed the effectiveness of SLIT for the treatment of AR, a considerable number of studies using extracts of house dust mites (HDMs) for immunotherapy found no consensus on basic treatment parameters and questioned the efficacy of SLIT. METHODS: In this study, we evaluated SLIT for PAR by a meta-analysis of randomized controlled trials (RCTs). Medline, Embase, and Cochrane Library database searches were performed for RCTs on the treatment of PAR by SLIT that assessed clinical outcomes related to efficacy through May 2016. Descriptive and quantitative information was abstracted. An analysis was performed with standardized mean differences (SMDs) under a fixed or random effects model. Subgroup analyses were performed. Heterogeneity was assessed using the I² metric. RESULTS: In total, 25 studies were eligible for inclusion in the meta-analysis for symptom scores and 15 studies for medication scores. SLIT was significantly different from the controls for symptom scores (SMD=1.23; 95% confidence interval [CI]=1.74 to 0.73; P<0.001). For medication scores, significant differences for SLIT were also observed versus the controls (SMD=-1.39; 95% CI=-1.90 to -0.88; P<0.001). CONCLUSIONS: Our meta-analysis indicates that SLIT provided significant symptom relief and reduced the need for medications in PAR. In this study, significant evidence was obtained despite heterogeneity with regard to the use of mite extract. Specifically, the mite extract used was provided by the patients with PAR. Furthermore, to confirm both the objective outcomes and the effective doses of HDM allergen extracts, experimental data should be obtained from large high-quality population-based studies.

Efficacy and safety of sublingual immunotherapy for allergic rhinitis in pediatric patients: A meta-analysis of randomized controlled trials.

BACKGROUND: Allergic rhinitis (AR) has become a global health problem that constantly affects a large part of the general population, especially children. OBJECTIVE: Sublingual allergen immunotherapy (SLIT) has been used extensively for pediatric AR, although its efficacy and safety are often questioned. In this meta-analysis of randomized controlled trials (RCT), we evaluated the use of SLIT for pediatric AR. METHODS: A number of medical literature data bases were searched through January 2016 to identify RCTs that examined the use of SLIT for pediatric AR and that assessed clinical outcomes related to efficacy. Descriptive and quantitative information was abstracted. Standardized mean differences (SMD) were calculated by using fixed- and random-effects models. Subgroup analyses were performed. Heterogeneity was assessed by using the I2 metric. A network meta-analysis was used to estimate SMDs between two SLIT protocols for pediatric seasonal AR. All data were extracted from publications or received from the authors. RESULTS: Twenty-six studies were eligible for inclusion in the meta-analysis of rhinitis or rhinoconjunctivitis symptom scores, and 19 studies were eligible for the meta-analysis of medication scores. Descriptive and quantitative data were extracted. SLIT differed significantly from placebo in terms of symptom scores (SMD -0.55 [95% confidence interval {CI}, -0.86 to -0.25]; p = 0.0003, I2 = 90%) and medication scores (SMD -0.67 [95% CI, -0.96 to -0.38]; p < 0.00001, I2 = 83%). Oral pruritus was the adverse effect, which occurred most commonly in children who were receiving SLIT. Network meta-analysis revealed no significant difference between the pre-coseasonal and continuous SLIT protocols for seasonal AR in symptom scores (SMD -6.55 [95% CI, -25.38 to 12.29]; p = 0.496) and medication scores (SMD -8.83 [95% CI, -22.10 to 4.43]; p = 0.192). CONCLUSIONS: Our meta-analysis results indicated that SLIT provided significant symptom relief and reduced the need for medication in pediatric patients. Moreover, the safety of SLIT needs to be confirmed in RCTs with larger samples.