Single-cell transcriptomic analysis of HPV-related multiphenotypic sinonasal carcinoma uncovers MYB-HPV association
Ontology highlight
ABSTRACT:
ORGANISM(S): Homo sapiens
PROVIDER: GSE293187 | GEO | 2025/10/22
REPOSITORIES: GEO
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Project description:The incidence of HPV-related oropharyngeal squamous cell carcinoma (OPSCC) has increased in recent years. RNAseq was performed for systems-based analysis of cellular pathways involved in HPV+ve OPSCCs.
2025-01-10 | GSE193388 | GEO
Project description:Oropharyngeal squamous cell carcinoma (OPSCC), a distinct head and neck cancer subtype that develops in the oropharynx, is well known to be categorized into human papillomavirus induced (HPV+) and non-HPV induced (HPV-). While HPV+ OPSCC is reported to be clinically advantageous compared to HPV- OPSCC, the heterogeneous responses in HPV+ OPSCC during immunotherapy treatment have not been well characterized at the molecular level. In this study, we assess both tumor and immune cells of the OPSCC tumor microenvironment (TME) via single-cell RNA sequencing (scRNA-seq) and single-cell TCR sequencing (scTCR-seq). By dissecting the transcriptome of OPSCC tumor cells, we find that cancer cell transcriptional diversity may be a strong factor in negating HPV associated clinical benefits. By assessing immune cells, we observed molecular antiviral and anti-tumor characteristics of T cells that is associated with HPV infection, and key cell-cell interaction differences among resident memory T cells (Trm), follicular helper T cells, and B cells. Importantly, we identify a novel molecular state within the HPV+ OPSCC that is distinguished by the expression KLRB1 (CD161) in the Trm that inhibits anti-tumor activity, which may further explain the heterogeneous clinical benefits of HPV+OPSCC. Association of KLRB1 expression of Trm and immunotherapy outcome was confirmed via immunofluorescence analysis, suggesting CD161 as a novel therapeutic target to improve cancer treatment of HPV+ OPSCC.
2024-06-01 | GSE226620 | GEO
Project description:The diagnosis of sinonasal tumors is challenging due to a heterogeneous spectrum of various differential diagnoses as well as poorly defined, disputed entities such as sinonasal undifferentiated carcinomas (SNUCs). In this study, we apply machine learning algorithm based on DNA methylation patterns to classify sinonasal tumors with clinical-grade reliability. We further show that sinonasal tumors with SNUC morphology are not as undifferentiated as their current terminology suggests but rather reassigned to four distinct molecular classes defined by epigenetic, mutational and proteomic profiles. This includes two classes with neuroendocrine differentiation, characterized by IDH2 or SMARCA4/ARID1A mutations with an overall favorable clinical course, whereas tumors that are driven by SMARCB1-deficiency and tumors that represent previously misclassified adenoid cystic carcinomas are highly aggressive. Our findings have the potential to dramatically improve the diagnostic classification of sinonasal tumors and will fundamentally change the current perception of SNUCs.
2022-09-25 | GSE196227 | GEO
Project description:DNA methylation analysis in oropharyngeal squamous carcinoma (OPSCC) samples and oropharyngeal non-cancerous mucosa samples. Infinium HumanMethylation450 BeadChip was used to obtain DNA methylation profiles across 485,577 CpG sites. Total samples included 89 OPSCC samples and 5 non-cancerous mucosa samples.
2020-01-20 | GSE124464 | GEO
Project description:DNA methylation analysis in oropharyngeal squamous carcinoma (OPSCC) samples and oropharyngeal non-cancerous mucosa samples. Infinium MethylationEPIC BeadChip Kit was used to obtain DNA methylation profiles across more than 850,000 CpG sites. Total samples included 89 OPSCC samples and 5 non-cancerous mucosa samples.
2020-01-20 | GSE124632 | GEO
Project description:The histopathological diagnosis of sinonasal tumors is challenging as it encompasses a heterogeneous spectrum of various differential diagnoses as well as poorly defined, disputed entities such as sinonasal undifferentiated carcinomas (SNUCs). In this study, we show that a machine learning algorithm based on DNA methylation is able to classify sinonasal tumors with clinical-grade reliability. We further show that tumors with SNUC morphology are not as undifferentiated as their current terminology suggests, but can be assigned to four molecular classes defined by distinct epigenic, mutational and proteomic profiles. This includes two classes with neuroendocrine differentiation, characterized by IDH2 or SWI/SNF chromatin remodeling complex mutations and overall favorable clinical course, highly aggressive tumors that are driven by SMARCB1-deficiency and tumors that represent previously misclassified adenoid-cystic carcinomas. Our findings have the potential to dramatically improve the diagnostic of challenging sinonasal tumors and could fundamentally change the current perception of SNUCs.
2022-09-25 | GSE189778 | GEO
Project description:Tobacco use is an independent adverse prognostic feature in human papillomavirus (HPV)-associated oropharyngeal squamous cell carcinoma (OPSCC). Despite this, the biologic features associated with tobacco use have not been systematically investigated in this population. We sought to characterize the genomic and immunologic features of HPV(+) OPSCC associated with tobacco use and adverse oncologic outcomes. Whole exome sequencing of 47 primary HPV(+) OPSCC tumors was performed to investigate mutational differences associated with tobacco exposure. To characterize the tumor immune microenvironment (TIME), targeted mRNA hybridization was performed. Low expression of transcripts in a T cell-inflamed gene expression profile (TGEP) was associated with tobacco use at the time of diagnosis and lower overall and disease-free survival. Tobacco use was associated with an increased proportion of T>C substitutions and a lower proportion of mutational signatures typically observed in HPV(+) OPSCC tumors, but was not associated with increases in mutational burden or the rate of recurrent oncogenic mutations. Our work suggests that rather than increased mutational burden, tobacco’s primary and clinically relevant association in HPV(+) OPSCC is immunosuppression of the tumor immune microenvironment.
2022-04-02 | GSE199029 | GEO
Project description:The incidence of HPV-related oropharyngeal squamous cell carcinoma (OPSCC) has increased more than 200% in the past 20 years. Recent genetic sequencing efforts have elucidated relevant genes in head and neck cancer, but HPV-related tumors have consistently shown few DNA mutations. In this study, we sought to analyze alternative splicing events (ASE) that could alter gene function independent of mutations. To identify ASE unique to HPV-related tumors, RNA sequencing was performed on 46 HPV-positive OPSCC and 25 normal tissue samples. A novel algorithm using outlier statistics on RNA-sequencing junction expression identified 109 splicing events, which were confirmed in a validation set from The Cancer Genome Atlas.
2018-03-20 | GSE112026 | GEO
Project description:The incidence of HPV-related oropharyngeal squamous cell carcinoma (OPSCC) has increased more than 200% in the past 20 years. Recent genetic sequencing efforts have elucidated relevant genes in head and neck cancer, but HPV-related tumors have consistently shown few DNA mutations. In this study, we sought to analyze alternative splicing events (ASE) that could alter gene function independent of mutations. To identify ASE unique to HPV-related tumors, RNA sequencing was performed on 46 HPV-positive OPSCC and 25 normal tissue samples. A novel algorithm using outlier statistics on RNA-sequencing junction expression identified 109 splicing events, which were confirmed in a validation set from The Cancer Genome Atlas.
2018-03-20 | GSE112023 | GEO
Project description:The global rise of HPV(+) oropharyngeal squamous cell carcinoma (OPSCC) has generated considerable interest underlying its etiology and management. Despite an overall decline in head and neck malignancies, the incidence in OPSCC has by contrast sharply risen, with HPV(+) subtypes now comprising 80% of all OPSCC.1,2 Relative to HPV(-) OPSCC, HPV(+) patients are more responsive to chemoradiation and harbor a 52% risk-of-death reduction.3 Despite this distinct outcome, treatment regimens remain the same for all OPSCC subtypes (smoking-driven and virus-driven), rather than an adaptive approach to what most consider distinct diseases. The short-term effects (e.g., mucositis, odynophagia) and long-term toxicities (e.g., xerostomia, dysphagia, ototoxicity) from treatment substantially affect quality of life, and rival the impact of the cancer itself. Recently published as well as ongoing trials are actively examining deintensification approaches2,4-9, with the goal of diminishing treatment sequelae for HPV(+) subtypes. While deintensification may decrease chemoradiation-related toxicities, it nonetheless may also undertreat a meaningful percentage of HPV(+) patients who may then recur. In examining national trials, 19% of HPV(+) patients had disease progression after therapy, with a two-year survival rate of 60%.10 Current methods to ascertain HPV status involve p16 staining. However, on comparison with gold standard E6/E7 expression by qPCR, p16 harbored a 15% false positivity rate11, suggesting limited utility as a sole biomarker for deintensification. Improved molecular stratification would greatly enhance the clinician’s ability to precisely tailor treatment while minimizing the risk of jeopardizing outcomes. One approach encompasses in-depth proteomic profiling of HPV(+) OPSCC to reveal distinct protein expression profiles and delineate clinically relevant upstream pathways. In turn, these proteomic differences may distinguish higher-risk disease (cases predisposed to recurrence that may benefit from treatment intensification) from lower-risk phenotypes (cases whose treatment response is sufficiently robust to warrant deintensification). Here, two HPV(+) OPSCC cohorts stratified by treatment response are compared via a hybrid data dependent acquisition/data independent acquisition (DDA/DIA) approach via mass spectrometry. We focused on detection of low-abundance proteins to highlight proteomic signatures that can be potentially exploited for treatment stratification.
2022-05-05 | PXD028618 | Pride