Dataset Information

HPV Status as Prognostic Biomarker in Head and Neck Cancer-Which Method Fits the Best for Outcome Prediction?

ABSTRACT: The incidence of human papillomavirus (HPV)-related head and neck cancer (HNSCC) is rising globally, presenting challenges for optimized clinical management. To date, it remains unclear which biomarker best reflects HPV-driven carcinogenesis, a process that is associated with better therapeutic response and outcome compared to tobacco/alcohol-induced cancers. Six potential HPV surrogate biomarkers were analyzed using FFPE tissue samples from 153 HNSCC patients (n = 78 oropharyngeal cancer (OPSCC), n = 35 laryngeal cancer, n = 23 hypopharyngeal cancer, n = 17 oral cavity cancer): p16, CyclinD1, pRb, dual immunohistochemical staining of p16 and Ki67, HPV-DNA-PCR, and HPV-DNA-in situ hybridization (ISH). Biomarkers were analyzed for correlation with one another, tumor subsite, and patient survival. P16-IHC alone showed the best performance for discriminating between good (high expression) vs poor outcome (low expression; p = 0.0030) in OPSCC patients. Additionally, HPV-DNA-ISH (p = 0.0039), HPV-DNA-PCR (p = 0.0113), and p16-Ki67 dual stain (p = 0.0047) were significantly associated with prognosis in uni- and multivariable analysis for oropharyngeal cancer. In the non-OPSCC group, however, none of the aforementioned surrogate markers was prognostic. Taken together, P16-IHC as a single biomarker displays the best diagnostic accuracy for prognosis stratification in OPSCC patients with a direct detection of HPV-DNA by PCR or ISH as well as p16-Ki67 dual stain as potential alternatives.

SUBMITTER: Kuhn JP

PROVIDER: S-EPMC8469433 | biostudies-literature | 2021 Sep

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

HPV Status as Prognostic Biomarker in Head and Neck Cancer-Which Method Fits the Best for Outcome Prediction?

Kühn Jan Philipp JP Schmid Wendelin W Körner Sandrina S Bochen Florian F Wemmert Silke S Rimbach Hugo H Smola Sigrun S Radosa Julia Caroline JC Wagner Mathias M Morris Luc G T LGT Bozzato Victoria V Bozzato Alessandro A Schick Bernhard B Linxweiler Maximilian M

Cancers 20210921 18

The incidence of human papillomavirus (HPV)-related head and neck cancer (HNSCC) is rising globally, presenting challenges for optimized clinical management. To date, it remains unclear which biomarker best reflects HPV-driven carcinogenesis, a process that is associated with better therapeutic response and outcome compared to tobacco/alcohol-induced cancers. Six potential HPV surrogate biomarkers were analyzed using FFPE tissue samples from 153 HNSCC patients (<i>n</i> = 78 oropharyngeal cancer ...[more]

PMID: 34572957

Similar Datasets

Project description:BackgroundHead and Neck Cancer (HNC) is a major cause of cancer morbidity and mortality in the United States, but the burden is not evenly distributed. Rural and racial disparities are obvious across the HNC continuum. Most HNC disparities research have emphasized individual factors perpetuating rural and racial disparities, ignoring the role of community-level factors.MethodsWe analyzed data from the Surveillance Epidemiology and End Results (SEER) program's "Specialized HNC-Human Papillomavirus (HPV) Census-Tract SES" datafile (2010-2016). In addition to cancer patient characteristics, this data includes a socioeconomic status (SES) quintile based on the patient's census-tract. Our outcome variables included whether the HNC patient 1) was diagnosed at a distant stage, 2) received initial treatment two or more months after diagnosis, 3) received radiation therapy, 4) survived two years after diagnosis. We tested for differences across SES quintiles, in the full sample and then within rural/racial categories. We then tested for differences between each rural/racial category conditional on SES quintile.ResultsFor both HPV(-) and HPV + HNCs, patients in higher SES census-tracts have 8-10% lower rates of distant stage diagnoses and delayed treatment initiation, and 12.0-14.5% higher survival rates than patients in lower SES census-tracts. Radiation treatment only varied across SES quintiles in HPV + HNC patients. We find little evidence of rural-urban differences within each socioeconomic quintile. However, within lower SES quintiles, we found significant racial disparities in delayed detection and treatment. These differences were largest in the lowest SES quintile, as non-Hispanic Black patients reported 10-11% higher rates of delayed detection and treatment initiation than non-Hispanic White patients.ConclusionsOur research illustrates the value and constraints in leveraging community-level factors in health disparities research that can ultimately assist in designing effective policies that address and achieve rural and racial cancer equity.

Project description:Squamous cell carcinoma of the head and neck (SCCHN) is a commonly detected cancer worldwide. Human papillomavirus (HPV) is emerging as an important risk factor affecting SCCHN prognosis. Therefore, identification of HPV status is essential for effective therapies in SCCHN. The aim of this study was to investigate the prognostic value of HPV-associated RNA biomarkers for SCCHN. The clinical data, survival data, and RNA-seq data of SCCHN were downloaded from The Cancer Genome Atlas database. Before the differential expression analysis, the heterogeneity between the 2 groups (HPV+ vs HPV-) of samples was analyzed using principal component analysis. The differentially expressed genes (DEGs) between HPV+ and HPV- SCCHN samples were analyzed using the R edgeR package. The Gene Ontology functional annotations, including biological process, molecular function and cellular component (CC), and Kyoto Encyclopedia of Genes And Genomes pathways enriched by the DEGs were analyzed using DAVID. The obtained matrix was analyzed by weighed gene coexpression network analysis. A total of 350 significant DEGs were identified through differential analysis, and these DEGs were significantly enriched in functions associated with keratinization, and the pathway of neuroactive ligand-receptor interaction. Moreover, 72 hub genes were identified through weighed gene coexpression network analysis. After the hub genes and DEGs were combined, we obtained 422 union genes, including 65 survival-associated genes. After regression analysis, a HPV-related prognostic model was established, which consisted of 8 genes, including Clorf105, CGA, CHRNA2, CRIP3, CTAG2, ENPP6, NEFH, and RNF212. The obtained regression model could be expressed by an equation as follows: risk score = 0.065 × Clorf105 + 0.012 × CGA + 0.01 × CHRNA2 + 0.047 × CRIP3 + 0.043 × CTAG2-0.034 × ENPP6 - 0.003 × NEFH - 0.068 × RNF212. CGA interacted with 3 drugs, and CHRNA2 interacted with 11 drugs. We have identified an 8 HPV-RNA signature associated with the prognosis of SCCHN patients. Such prognostic model might serve as possible candidate biomarker and therapeutic target for SCCHN.

Dataset Information

HPV Status as Prognostic Biomarker in Head and Neck Cancer-Which Method Fits the Best for Outcome Prediction?

Publications

HPV Status as Prognostic Biomarker in Head and Neck Cancer-Which Method Fits the Best for Outcome Prediction?

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets