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Objectives Alcohol consumption is closely associated with prognosis for laryngeal squamous cell carcinoma (LSCC) patients. As key enzymes in ethanol metabolism, proteins in the alcohol dehydrogenase (ADH) family make for valuable targets to establish a novel predictive nomogram model. This study attempts to do so by focusing on the single nucleotide polymorphisms (SNPs) of ADH1B and ADH1C in LSCC. Methods Sixty eight LSCC patients that were followed up for more than 10 years were retrospectively analyzed. Endpoints of the current study included disease‐free survival and overall survival. Survival analyses were performed using the Kaplan–Meier method and evaluated by log‐rank test. The prognostic value of eight ADH1B SNPs and three ADH1C SNPs were evaluated using univariate and multivariate Cox regression analyses. A nomogram model for disease‐free survival was established and evaluated using the receiver operating characteristic curve, the C‐index, and a calibration plot. Results Significant association was exhibited between rs17033 (p < 0.001) and rs1229984 (p = 0.002) with an increase in LSCC recurrence rate on Kaplan–Meier curves. Multivariate logistic regression analysis revealed that the rs17033 polymorphism of ADH1B was independently associated with an increased risk of LSCC recurrence (HR = 3.325, 95% CI = 1.684–6.566, p = 0.001). Based on these findings, a prognostic nomogram of LSCC patients involving ADH1B rs17033 was constructed. Conclusion This study has demonstrated an independent association between ADH1B gene variants and the recurrence of LSCC. A nomogram model based on rs17033 of ADH1B, age, T, and N stages were successfully developed for the first time to predict the probability of recurrence in LSCC patients. Level of Evidence 3 Retrospective cohort study Laryngoscope, 132:2169–2176, 2022

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Background As a human tumor disease, head and neck squamous cell carcinoma (HNSCC) is associated with a high mortality rate worldwide. Nicotinic acetylcholine receptors (nAChRs) are transmembrane receptor proteins and exert their biological effects following activation by nicotine. We aimed to construct a prognostic signature based on the expression of nAChRs among smokers with HNSCC. Methods The transcriptome profile of nAChRs was obtained from The Cancer Genome Atlas (TCGA). Following the integration of survival information, univariate Cox regression and least absolute shrinkage and selection operator (LASSO) analyses were performed to screen the prognosis-related nAChRs and construct a prognostic signature. Kaplan–Meier (KM), receiver operating characteristic (ROC), principal component analysis (PCA), and independent prognostic analysis were utilized to verify the predictive power of the nAChR-associated prognostic signature. The expression of α5 nAChR in clinical samples was verified by quantitative reverse transcriptase PCR. Results Subunits α2, α5, α9, and β4 were related to the prognosis. The prognostic signature comprised the expression of subunits α5, α9, and β4. The nAChR-associated signature showed high sensitivity and specificity for prognostic prediction and was an independent factor for overall survival. Based on the clinical variables and expression of nAChRs, a nomogram was constructed for predicting the outcomes of HNSCC patients who were smokers in the clinical settings. In clinical specimens, α5 nAChR showed high expression in HNSCC tissues, especially among smokers. Conclusions The nAChR-associated signature constructed in this study may provide a better system for the classification of HNSCC patients and facilitate personalized treatment according to their smoking habits.