Purpose The genetic differences between Human papilloma Virus (HPV)-positive and negative head and neck squamous cell carcinomas (HNSCC) remain largely unknown. In order to identify differential biology and novel therapeutic targets for both entities we determined mutations and copy number aberrations in a large cohort of locoregionally-advanced HNSCC. Experimental Design We performed massively parallel sequencing of 617 cancer-associated genes in 120 matched tumor/normal samples (42.5% HPV-positive). Mutations and copy number aberrations were determined and results validated with a secondary method. Results The overall mutational burden in HPV-negative and HPV-positive HNSCC was similar with an average of 15.2 versus 14.4 somatic exonic mutations in the targeted cancer-associated genes. HPV-negative tumors showed a mutational spectrum concordant with published lung squamous cell carcinoma analyses with enrichment for mutations in TP53, CDKN2A, MLL2, CUL3, NSD1, PIK3CA and NOTCH genes. HPV-positive tumors showed unique mutations in DDX3X, FGFR2/3 and aberrations in PIK3CA, KRAS, MLL2/3 and NOTCH1 were enriched in HPV-positive tumors. Currently targetable genomic alterations were identified in FGFR1, DDR2, EGFR, FGFR2/3, EPHA2 and PIK3CA. EGFR, CCND1, and FGFR1 amplifications occurred in HPV-negative tumors, while 17.6% of HPV-positive tumors harbored mutations in Fibroblast Growth Factor Receptor genes (FGFR2/3) including six recurrent FGFR3 S249C mutations. HPV-positive tumors showed a 5.8% incidence of KRAS mutations, and DNA repair gene aberrations including 7.8% BRCA1/2 mutations were identified. Conclusions The mutational makeup of HPV-positive and HPV-negative HNSCC differs significantly, including targetable genes. HNSCC harbors multiple therapeutically important genetic aberrations, including frequent aberrations in the FGFR and PI3K pathway genes.

Purpose: Current classification of head and neck squamous cell carcinomas (HNSCC) based on anatomic site and stage fails to capture biologic heterogeneity or adequately inform treatment.Experimental

The Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) virus is continuously evolving, and this poses a major threat to antibody therapies and currently authorized Coronavirus Disease 2019 (COVID-19) vaccines. It is therefore of utmost importance to investigate and predict the putative mutations on the spike protein that confer immune evasion. Antibodies are key components of the human immune system’s response to SARS-CoV-2, and the spike protein is a prime target of neutralizing antibodies (nAbs) as it plays critical roles in host cell recognition, fusion, and virus entry. The potency of therapeutic antibodies and vaccines partly depends on how readily the virus can escape neutralization. Recent structural and functional studies have mapped the epitope landscape of nAbs on the spike protein, which illustrates the footprints of several nAbs and the site of escape mutations. In this review, we discuss (1) the emerging SARS-CoV-2 variants; (2) the structural basis for antibody-mediated neutralization of SARS-CoV-2 and nAb classification; and (3) identification of the RBD escape mutations for several antibodies that resist antibody binding and neutralization. These escape maps are a valuable tool to predict SARS-CoV-2 fitness, and in conjunction with the structures of the spike-nAb complex, they can be utilized to facilitate the rational design of escape-resistant antibody therapeutics and vaccines.

Purpose: Intratumoral hypoxia and immunity have been correlated with patient outcome in various tumor settings. However, these factors are not currently considered for treatment selection in head and neck cancer (HNC) due to lack of validated biomarkers. Here we sought to develop a hypoxiaimmune classifier with potential application in patient prognostication and prediction of response to targeted therapy.Experimental Design: A 54-gene hypoxia-immune signature was constructed on the basis of literature review. Gene expression was analyzed in silico using the The Cancer Genome Atlas (TCGA) HNC dataset (n ¼ 275) and validated using two independent cohorts (n ¼ 130 and 123). IHC was used to investigate the utility of a simplified protein signature. The spatial distribution of hypoxia and immune markers was examined using multiplex immunofluorescence staining.Results: Unsupervised hierarchical clustering of TCGA dataset (development cohort) identified three patient subgroups with distinct hypoxia-immune phenotypes and sur-vival profiles: hypoxia low /immune high , hypoxia high /immune low , and mixed, with 5-year overall survival (OS) rates of 71%, 51%, and 49%, respectively (P ¼ 0.0015). The prognostic relevance of the hypoxia-immune gene signature was replicated in two independent validation cohorts. Only PD-L1 and intratumoral CD3 protein expression were associated with improved OS on multivariate analysis. Hypoxia low / immune high and hypoxia high /immune low tumors were overrepresented in "inflamed" and "immune-desert" microenvironmental profiles, respectively. Multiplex staining demonstrated an inverse correlation between CA-IX expression and prevalence of intratumoral CD3 þ T cells (r ¼ À0.5464; P ¼ 0.0377), further corroborating the transcription-based classification.Conclusions: We developed and validated a hypoxiaimmune prognostic transcriptional classifier, which may have clinical application to guide the use of hypoxia modification and targeted immunotherapies for the treatment of HNC.

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