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Multimodal Dimension Reduction and Subtype Classification of Head and Neck Squamous Cell Tumors

ABSTRACT: Traditional analysis of genomic data from bulk sequencing experiments seek to group and compare sample cohorts into biologically meaningful groups. To accomplish this task, large scale databases of patient-derived samples, like that of TCGA, have been established, giving the ability to interrogate multiple data modalities per tumor. We have developed a computational strategy employing multimodal integration paired with spectral clustering and modern dimension reduction techniques such as PHATE to provide a more robust method for cancer sub-type classification. Using this integrated approach, we have examined 514 Head and Neck Squamous Carcinoma (HNSC) tumor samples from TCGA across gene-expression, DNA-methylation, and microbiome data modalities. We show that these approaches, primarily developed for single-cell sequencing can be efficiently applied to bulk tumor sequencing data. Our multimodal analysis captures the dynamic heterogeneity, identifies new and refines subtypes of HNSC, and orders tumor samples along well-defined cellular trajectories. Collectively, these results showcase the inherent molecular complexity of tumors and offer insights into carcinogenesis and importance of targeted therapy. Computational techniques as highlighted in our study provide an organic and powerful approach to identify granular patterns in large and noisy datasets that may otherwise be overlooked.

SUBMITTER: Bard J

PROVIDER: S-EPMC9326399 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:BackgroundLong noncoding RNAs (lncRNAs) play a critical role in innate and adaptive immune responses. Thus, we aimed to identify ideal subtypes for head and neck squamous cell carcinoma (HNSCC) based on immune-related lncRNAs.MethodsTCGA HNSCC cohort was divided into two datasets (training and validation dataset), and 960 previously characterized immune-related lncRNAs were extracted for non-negative matrix factorization analysis. We characterized our HNSCC subtypes based on biological behaviors, immune landscape and response to immunotherapy in both training and validation cohort. A lncRNA-signature was generated to predict our HNSCC subtypes, and essential lncRNAs involved in tumor microenvironment (TME) were identified.ResultsWe developed and validated two HNSCC subtypes (C1 and C2) based on the 70 lncRNAs in the training and validation cohort. C2 subtype displayed good prognosis, high immune cell infiltration, immune-related genes expression and sensitivity to PD-1 blockade. C1 subtype was associated with high activity of mTORC1 signaling and glycolysis as well as high fraction of inactive immune cells. Finally, we generated a 31-lncRNA signature that could predict our above subtypes with high accurate. Additionally, TRG-AS1 was identified as the essential lncRNA involving TME formation. Knockdown of TRG-AS1 inhibited the expression of HLA-A, HLA-B, HLA-C, CXCL9, CXCL10 and CXCL11. High expression of TRG-AS1 indicated a favorable prognosis in HNSCC and anti-PD-L1 cohort (IMvigor210).ConclusionsOur study establishes a novel HNSCC classification on the basis of 31-lncRNA, helping to identify beneficiaries for anti-PD-1 treatment. In addition, a critical lncRNA TRG-AS1 is identified as a new potential prognosis biomarker as well as therapeutic target.

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p63 Directs Subtype-Specific Gene Expression in HPV+ Head and Neck Squamous Cell Carcinoma.

Project description:The complex heterogeneity of head and neck squamous cell carcinoma (HNSCC) reflects a diverse underlying etiology. This heterogeneity is also apparent within Human Papillomavirus-positive (HPV+) HNSCC subtypes, which have distinct gene expression profiles and patient outcomes. One aggressive HPV+ HNSCC subtype is characterized by elevated expression of genes involved in keratinization, a process regulated by the oncogenic transcription factor ΔNp63. Furthermore, the human TP63 gene locus is a frequent HPV integration site and HPV oncoproteins drive ΔNp63 expression, suggesting an unexplored functional link between ΔNp63 and HPV+ HNSCC. Here we show that HPV+ HNSCCs can be molecularly stratified according to ΔNp63 expression levels and derive a ΔNp63-associated gene signature profile for such tumors. We leveraged RNA-seq data from p63 knockdown cells and ChIP-seq data for p63 and histone marks from two ΔNp63high HPV+ HNSCC cell lines to identify an epigenetically refined ΔNp63 cistrome. Our integrated analyses reveal crucial ΔNp63-bound super-enhancers likely to mediate HPV+ HNSCC subtype-specific gene expression that is anchored, in part, by the PI3K-mTOR pathway. These findings implicate ΔNp63 as a key regulator of essential oncogenic pathways in a subtype of HPV+ HNSCC that can be exploited as a biomarker for patient stratification and treatment choices.

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Head and neck squamous cell carcinoma

Project description:Quantitative (iTRAQ 4-plex) proteomic analysis of progressive head and neck cancers

2022-03-01 | PXD001438 | Pride

Metabolism-associated molecular classification and prognosis signature of head and neck squamous cell carcinoma.

Project description:Although the fundamental processes and chemical changes in metabolic programs have been elucidated in many cancers, the expression patterns of metabolism-related genes in head and neck squamous cell carcinoma (HNSCC) remain unclear. The mRNA expression profiles from the Cancer Genome Atlas included 502 tumour and 44 normal samples were extracted. We explored the biological functions and prognosis roles of metabolism-associated genes in patients with HNSCC. The results indicated that patients with HNSCC could be divided into three molecular subtypes (C1, C2 and C3) based on 249 metabolism-related genes. There were markedly different clinical characteristics, prognosis outcomes, and biological functions among the three subtypes. Different molecular subtypes also have different tumour microenvironments and immune infiltration levels. The established prognosis model with 17 signature genes could predict the prognosis of patients with HNSCC and was validated using an independent cohort dataset. An individual risk scoring tool was developed using the risk score and clinical parameters; the risk score was an independent prognostic factor for patients with HNSCC. Different risk stratifications have different clinical characteristics, biological features, tumour microenvironments and immune infiltration levels. Our study could be used for clinical risk management and to help conduct precision medicine for patients with HNSCC.

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Head and neck squamous cell carcinoma.

Project description:Most head and neck cancers are derived from the mucosal epithelium in the oral cavity, pharynx and larynx and are known collectively as head and neck squamous cell carcinoma (HNSCC). Oral cavity and larynx cancers are generally associated with tobacco consumption, alcohol abuse or both, whereas pharynx cancers are increasingly attributed to infection with human papillomavirus (HPV), primarily HPV-16. Thus, HNSCC can be separated into HPV-negative and HPV-positive HNSCC. Despite evidence of histological progression from cellular atypia through various degrees of dysplasia, ultimately leading to invasive HNSCC, most patients are diagnosed with late-stage HNSCC without a clinically evident antecedent pre-malignant lesion. Traditional staging of HNSCC using the tumour-node-metastasis system has been supplemented by the 2017 AJCC/UICC staging system, which incorporates additional information relevant to HPV-positive disease. Treatment is generally multimodal, consisting of surgery followed by chemoradiotherapy (CRT) for oral cavity cancers and primary CRT for pharynx and larynx cancers. The EGFR monoclonal antibody cetuximab is generally used in combination with radiation in HPV-negative HNSCC where comorbidities prevent the use of cytotoxic chemotherapy. The FDA approved the immune checkpoint inhibitors pembrolizumab and nivolumab for treatment of recurrent or metastatic HNSCC and pembrolizumab as primary treatment for unresectable disease. Elucidation of the molecular genetic landscape of HNSCC over the past decade has revealed new opportunities for therapeutic intervention. Ongoing efforts aim to integrate our understanding of HNSCC biology and immunobiology to identify predictive biomarkers that will enable delivery of the most effective, least-toxic therapies.

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Predictive models for stage and risk classification in head and neck squamous cell carcinoma (HNSCC).

Project description:Machine learning techniques are increasingly used in the analysis of high throughput genome sequencing data to better understand the disease process and design of therapeutic modalities. In the current study, we have applied state of the art machine learning (ML) algorithms (Random Forest (RF), Support Vector Machine Radial Kernel (svmR), Adaptive Boost (AdaBoost), averaged Neural Network (avNNet), and Gradient Boosting Machine (GBM)) to stratify the HNSCC patients in early and late clinical stages (TNM) and to predict the risk using miRNAs expression profiles. A six miRNA signature was identified that can stratify patients in the early and late stages. The mean accuracy, sensitivity, specificity, and area under the curve (AUC) was found to be 0.84, 0.87, 0.78, and 0.82, respectively indicating the robust performance of the generated model. The prognostic signature of eight miRNAs was identified using LASSO (least absolute shrinkage and selection operator) penalized regression. These miRNAs were found to be significantly associated with overall survival of the patients. The pathway and functional enrichment analysis of the identified biomarkers revealed their involvement in important cancer pathways such as GP6 signalling, Wnt signalling, p53 signalling, granulocyte adhesion, and dipedesis. To the best of our knowledge, this is the first such study and we hope that these signature miRNAs will be useful for the risk stratification of patients and the design of therapeutic modalities.

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Project description:Prognosis in relapsed metastatic head and neck squamous cell cancer (RM-HNSCC) is dismal. Platinum based chemotherapy in combination with Cetuximab is used in first-line setting, while no further validated options are available at progression. Immunotherapy has produced durable clinical benefit in some patients with RM-HNSCC although the premises are several patients are nonresponders. Studies are ongoing to determine predictive factors and the ideal setting/combination of novel immunotherapies. In this paper, we discuss the past and present of immunotherapy in head and neck cancer and provide an up-to-date information regarding the potential ways to improve immunotherapy outcomes in HNSCC.

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Exosomes in Head and Neck Squamous Cell Carcinoma.

Project description:Exosomes are small membranous vesicles that contain proteins, lipids, genetic material, and metabolites with abundant information from parental cells. Exosomes carry and deliver bioactive contents that can reprogram the functions of recipient cells and modulate the tumor microenvironment to induce pathological events through cell-to-cell communication and signal transduction. Tumor-derived exosomes (TDEs) in head and neck squamous cell carcinoma (HNSCC) are involved in most aspects of cancer initiation, invasion, progression, immunoregulation, therapeutic applications, and treatment resistance. In addition, HNSCC-derived exosomes can be used to obtain information on diagnostic and therapeutic biomarkers in circulating blood and saliva. Currently, the biology, mechanisms, and applications of TDEs in HNSCC are still unclear, and further research is required. In this review, we discuss various aspects of exosome biology, including exosomal components, exosomal biomarkers, and molecular mechanisms involved in immunoregulation, cancer metastasis, and therapy resistance. We also describe recent applications to update our understanding of exosomes in HNSCC.

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