Identification of Immune-Related Prognostic Biomarkers Associated with HPV-Positive Head and Neck Squamous Cell Carcinoma

Prognostic value of dysadherin in cancer: A systematic review and meta-analysis

Cancer is a leading cause of death worldwide and novel prognostic factors are reported with increasing numbers. Systematic reviews and meta-analyses on cumulative research data are crucial in estimating the true prognostic value of proposed factors. Dysadherin (FXYD Domain Containing Ion Transport Regulator 5; FXYD5) is a cell membrane glycoprotein that modulates Na+, K+-ATPase activity and cell-cell adhesion. It is abundantly expressed in a variety of cancer cells, but only in a limited number of normal cells and its levels are increased in many different tumor types. The expression or level of dysadherin has been suggested as an independent predictor for metastasis and poor prognosis by number of studies, yet we lack a definitive answer. In this study, we systematically evaluated the prognostic value of dysadherin in cancer and summarized the current knowledge on the subject. PubMed, Scopus, Web of Science and relevant clinical trial and preprint databases were searched for relevant publications and PRISMA and REMARK guidelines were applied in the process. After a careful review, a total of 23 original research articles were included. In each study, dysadherin was pointed as a marker for poor prognosis. Meta-analyses revealed 3- and 1.5-fold increases in the risk of death (fixed effects HR 3.08, 95% CI 1.88-5.06, RR 1.47, 95% CI 1.06-2.05 on overall survival, respectively) for patients with high (>50%) tumoral FXYD5 level. In many studies, a connection between dysadherin expression or level and metastatic behavior of the cancer as well as inverse correlation with E-cadherin level were reported. Thus, we conclude that dysadherin might be a useful prognostic biomarker in the assessment of disease survival of patients with solid tumors.

Tumor Cell Extrinsic Synaptogyrin 3 Expression as a Diagnostic and Prognostic Biomarker in Head and Neck Cancer

Over 70% of oropharyngeal head and neck squamous cell carcinoma (HNSC) cases in the United States are positive for human papillomavirus (HPV) yet biomarkers for stratifying oropharyngeal head and neck squamous cell carcinoma (HNSC) patient risk are limited. We used immunogenomics to identify differentially expressed genes in immune cells of HPV(+) and HPV(-) squamous carcinomas. Candidate genes were tested in clinical specimens using both quantitative RT-PCR and IHC and validated by IHC using the Carolina Head and Neck Cancer Study (CHANCE) tissue microarray of HNSC cases. We performed multiplex immunofluorescent staining to confirm expression within the immune cells of HPV(+) tumors, receiver operating characteristic (ROC) curve analyses, and assessed survival outcomes. The neuronal gene Synaptogyrin-3 (SYNGR3) is robustly expressed in immune cells of HPV(+) squamous cancers. Multiplex immunostaining and single cell RNA-seq analyses confirmed SYNGR3 expression in T cells, but also unexpectedly in B cells of HPV(+) tumors. ROC curve analyses revealed that combining SYNGR3 and p16 provides more sensitivity and specificity for HPV detection compared to p16 IHC alone. SYNGR3-high HNSC patients have significantly better prognosis with five-year OS and DSS rates of 60% and 71%, respectively. Moreover, combining p16 localization and SYNGR3 expression can further risk stratify HPV(+) patients such that high cytoplasmic, low nuclear p16 do significantly worse (Hazard Ratio, 8.6; P = 0.032) compared to patients with high cytoplasmic, high nuclear p16. SYNGR3 expression in T and B cells is associated with HPV status and enhanced survival outcomes of HNSC patients.

A Glycosyltransferase-Related Signature for Predicting Overall Survival in Head and Neck Squamous Cell Carcinoma

Background: Here, we establish a prognostic signature based on glycosyltransferase-related genes (GTRGs) for head and neck squamous cell carcinoma (HNSCC) patients.

Methods: The prognostic signature of GTRGs was constructed via univariate and multivariate Cox analyses after obtaining the expression patterns of GTRGs from the TCGA. A nomogram based on the signature and clinical parameters was established to predict the survival of each HNSCC patient. Potential mechanisms were explored through gene set enrichment analysis (GSEA) and immune cell infiltration, immune checkpoints, immunotherapy, and tumor mutational burden (TMB) analyses. The expression differences and prognostic efficacy of the signature were verified through the gene expression omnibus (GEO) and several online databases.

Results: The prognostic signature was constructed based on five glycosyltransferases (PYGL, ALG3, EXT2, FUT2, and KDELC1) and validated in the GSE65858 dataset. The pathways enriched in the high- and low-risk groups were significantly different. The high-risk group had higher tumor purity; lower infiltration of immune cells, such as CD8⁺ T cells and Tregs; higher cancer-associated fibroblast (CAF) infiltration; lower immune function; and lower checkpoint expression. The signature can also be applied to distinguish whether patients benefit from immunotherapy. In addition, the high-risk group had a higher TMB and more gene mutations, including those in TP53, CSMD1, CDKN2A, and MUC17.

Conclusion: We propose a prognostic signature based on glycosyltransferases for HNSCC patients that may provide potential targets and biomarkers for the precise treatment of HNSCC.

Clinical Validity of a Prognostic Gene Expression Cluster-Based Model in Human Papillomavirus-Positive Oropharyngeal Carcinoma

Under common therapeutic regimens, the prognosis of human papillomavirus (HPV)–positive squamous oropharyngeal carcinomas (OPCs) is more favorable than HPV-negative OPCs. However, the prognosis of some tumors is dismal, and validated prognostic factors are missing in clinical practice. The present work aimed to validate the prognostic significance of our published three-cluster model and to compare its prognostic value with those of the 8^th edition of the tumor-node-metastasis staging system (TNM8) and published signatures and clustering models.

Anti-PD-1 and Anti-PD-L1 in Head and Neck Cancer: A Network Meta-Analysis

Objective

The monoclonal antibodies anti-programmed death protein-1 (anti-PD-1) nivolumab and pembrolizumab are the first immune checkpoint inhibitors (ICIs) approved for treatment of recurrent/metastatic head and neck carcinoma R/M HNSCC in first line and in platinum refractory disease. This network meta-analysis aims to investigate the efficacy of anti-PD-1- vs anti-PD-L1-based therapy in R/M HNSCC cancer patients through a systematic review of the literature to provide support for evidence-based treatment decisions. In particular, the effectiveness of ICIs for R/M HNSCC is analyzed according to the different mechanisms of action of the check-points inhibitory drugs in different subgroups of patients.

Methods

We did a systematic literature review and network meta-analysis (NMA) of randomized controlled trials (RCTs) in PubMed, ClinicalTrials.gov, Embase, Medline, the Cochrane Central Register of Controlled Trials, Web of Science. Our search identified a total of five randomized controlled trials: Keynote 040, Keynote 048, Eagle, Condor, Checkmate 141. These trials included 3001 patients. Treatment was sub-categorized into PD-L1-based, PD-1-based, and standard chemotherapy. Treatments were indirectly compared with anti-PD-L1-based therapy.

Results

The network meta-analysis demonstrated no significant differences in OS between different subgroups except for the metastatic patients in which anti-PD-1-based therapy was associated with significantly less risk of death. Furthermore, anti-PD-1-based therapy appeared to be effective in smoker patients and in human papilloma-negative (HPV) patients. Conversely, anti-PD-L1-based therapy seems to be better efficient in female patients, in locally recurrent setting and in HPV positive patients.

Conclusion

This is the first NMA study that aimed to indirectly compare anti-PD-1- and anti-PD-L1-based therapy in HNSCC patients. The results of our NMA could help define a profile of patient responder or resistant to specific classes of immune drugs and can be used to guide/design future studies in the novel scenario of precision immune-oncology.