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Recently, Schlafen family member 11 (SLFN11) has been reported to increase the sensitivity of cancer cells to DNA-damaging agents, including platinum derivatives; thus, SLFN11 may be a predictive biomarker for platinum-based chemoradiotherapy (CRT). In this study, we examined whether SLFN11 expression was associated with the therapeutic outcome of platinum-based CRT in head and neck squamous cell carcinoma (HNSCC). We performed immunohistochemical analyses for SLFN11 expression in 161 HNSCC tissues from patients who had been administered cisplatin-based CRT and examined the correlation between SLFN11 expression and progression-free survival (PFS). Additionally, SLFN11 expression was examined in 10 paired samples obtained before and after CRT in patients with local failure. Furthermore, in vitro experiments were performed using several HNSCC cell lines and isogenic SLFN11-knockout cells to assess the association between SLFN11 expression and drug sensitivity. PFS was found to be significantly better in the SLFN11-positive group than in the SLFN11-negative group among the 161 patients (5-year PFS: 78.8% vs. 52.8%, respectively, p < 0.001). Similar results were observed for the PFS at each primary site. The percentage of SLFN11 positivity was lower in tumor samples from patients with local failure after CRT than that in the corresponding primary tumors before CRT in 8 of 10 cases. Results of the in vitro assay demonstrated that SLFN11-knockout cells exhibited reduced sensitivity to DNA-damaging agents but not to the non-DNA-damaging agent docetaxel. Our findings suggest that SLFN11 may serve as a potential biomarker for predicting the response of HNSCC patients to platinum-based CRT.

Pharyngeal cancer patients treated with intensity-modulated proton therapy (IMPT) using a model-based approach were retrospectively reviewed, and acute toxicities were analyzed. From June 2016 to March 2019, 15 pharyngeal (7 naso-, 5 oro- and 3 hypo-pharyngeal) cancer patients received IMPT with robust optimization. Simulation plans for IMPT and intensity-modulated X-ray therapy (IMXT) were generated before treatment. We also reviewed 127 pharyngeal cancer patients with IMXT in the same treatment period. In the simulation planning comparison, all of the normal-tissue complication probability values for dysphagia, dysgeusia, tube-feeding dependence and xerostomia were lower for IMPT than for IMXT in the 15 patients. After completing IMPT, 13 patients completed the evaluation, and 12 of thesepatientshad a complete response. The proportions of patients who experienced grade 2 or worse acute toxicities in the IMPT and IMXT cohorts were 21.4 and 56.5% for dysphagia (P < 0.05), 46.7 and 76.3% for dysgeusia (P < 0.05), 73.3 and 62.8% for xerostomia (P = 0.43), 73.3 and 90.6% formucositis (P = 0.08) and 66.7 and 76.4% for dermatitis (P = 0.42), respectively. Multivariate analysis revealed that IMPT was independently associated with a lower rate of grade 2 or worse dysphagia and dysgeusia. After propensity score matching, 12 pairs of IMPT and IMXT patients were selected. Dysphagia was also statistically lower in IMPT than in IMXT (P < 0.05). IMPT using a model-based approach may have clinical benefits for acute dysphagia.

Pharyngeal cancer patients treated with intensity-modulated proton therapy (IMPT) using a model-based approach were retrospectively reviewed, and acute toxicities were analyzed. From June 2016 to March 2019, 15 pharyngeal (7 naso-, 5 oro- and 3 hypo-pharyngeal) cancer patients received IMPT with robust optimization. Simulation plans for IMPT and intensity-modulated X-ray therapy (IMXT) were generated before treatment. We also reviewed 127 pharyngeal cancer patients with IMXT in the same treatment period. In the simulation planning comparison, all of the normal-tissue complication probability values for dysphagia, dysgeusia, tube-feeding dependence and xerostomia were lower for IMPT than for IMXT in the 15 patients. After completing IMPT, 13 patients completed the evaluation, and 12 of thesepatientshad a complete response. The proportions of patients who experienced grade 2 or worse acute toxicities in the IMPT and IMXT cohorts were 21.4 and 56.5% for dysphagia (P < 0.05), 46.7 and 76.3% for dysgeusia (P < 0.05), 73.3 and 62.8% for xerostomia (P = 0.43), 73.3 and 90.6% formucositis (P = 0.08) and 66.7 and 76.4% for dermatitis (P = 0.42), respectively. Multivariate analysis revealed that IMPT was independently associated with a lower rate of grade 2 or worse dysphagia and dysgeusia. After propensity score matching, 12 pairs of IMPT and IMXT patients were selected. Dysphagia was also statistically lower in IMPT than in IMXT (P < 0.05). IMPT using a model-based approach may have clinical benefits for acute dysphagia.

Purpose : To predict local control / failure by a multiparametric approach using magnetic resonance (MR)-derived tumor morphological and functional parameters in pharynx squamous cell carcinoma (SCC) patients. Materials and Methods : Twenty-eight patients with oropharyngeal and hypopharyngeal SCCs were included in this study. Quantitative morphological parameters and intratumoral characteristics on T2-weighted images, tumor blood flow from pseudo-continuous arterial spin labeling, and tumor diffusion parameters of three diffusion models from multi-b-value diffusion-weighted imaging as well as patients’ characteristics were analyzed. The patients were divided into local control / failure groups. Univariate and multiparametric analysis were performed for the patient group division. Results : The value of morphological parameter of ‘sphericity’ and intratumoral characteristic of ‘homogeneity’ was revealed respectively significant for the prediction of the local control status in univariate analysis. Higher diagnostic performance was obtained with the sensitivity of 0.8, specificity of 0.75, positive predictive value of 0.89, negative predictive value of 0.6 and accuracy of 0.79 by multiparametric diagnostic model compared to results in the univariate analysis. Conclusion : A multiparametric analysis with MR-derived quantitative parameters may be useful to predict local control in pharynx SCC patients.

Objective: Despite of rapid advances in endoscopic surgery, the gold standard for sinonasal squamous cell carcinoma (SNSCC) surgery has remained the open approach with en-block resection due to the aggressive nature of SNSCC, including frequent recurrence and high mortality rate. For that reason, few studies have focused on SNSCC treated by endoscopic surgery alone. The objective of this study was to evaluate the usefulness of endoscopic surgery for patients with SNSCC. Methods: A retrospective analysis was performed for 15 consecutive SNSCC patients who underwent endoscopic surgery without an open approach. We carefully selected patients whose tumor attachment sites could be fully visualized and completely resected through an endonasal approach. Results: Of the fifteen patients, 4 patients (27%) were diagnosed with T1, 7 (47%) with T2, 4 (27%) with T3, and no patients with T4a or T4b disease. Four of the 15 (27%) patients showed positive surgical margins. The 5-yr overall survival, disease-specific survival, and local control rate was 72.4%, 79.6%, and 92.9%, respectively. The 5-yr disease-specific survival for T1, T2, and T3 disease was 100% and 75% and 75%, respectively. Patients with negative surgical margins had a better disease-specific survival rate than did those with positive surgical margins (p = 0.0253). Conclusion: Endoscopic surgery for patients with SNSCC appears to afford an effective method in selected cases. The achievement of negative surgical margins with a good view of the tumor attachment site was considered to be critical to the management of SNSCC. (c) 2020 Oto-Rhino-Laryngological Society of Japan Inc. Published by Elsevier B.V. All rights reserved.

Objective: Despite of rapid advances in endoscopic surgery, the gold standard for sinonasal squamous cell carcinoma (SNSCC) surgery has remained the open approach with en-block resection due to the aggressive nature of SNSCC, including frequent recurrence and high mortality rate. For that reason, few studies have focused on SNSCC treated by endoscopic surgery alone. The objective of this study was to evaluate the usefulness of endoscopic surgery for patients with SNSCC. Methods: A retrospective analysis was performed for 15 consecutive SNSCC patients who underwent endoscopic surgery without an open approach. We carefully selected patients whose tumor attachment sites could be fully visualized and completely resected through an endonasal approach. Results: Of the fifteen patients, 4 patients (27%) were diagnosed with T1, 7 (47%) with T2, 4 (27%) with T3, and no patients with T4a or T4b disease. Four of the 15 (27%) patients showed positive surgical margins. The 5-yr overall survival, disease-specific survival, and local control rate was 72.4%, 79.6%, and 92.9%, respectively. The 5-yr disease-specific survival for T1, T2, and T3 disease was 100% and 75% and 75%, respectively. Patients with negative surgical margins had a better disease-specific survival rate than did those with positive surgical margins (p = 0.0253). Conclusion: Endoscopic surgery for patients with SNSCC appears to afford an effective method in selected cases. The achievement of negative surgical margins with a good view of the tumor attachment site was considered to be critical to the management of SNSCC. (c) 2020 Oto-Rhino-Laryngological Society of Japan Inc. Published by Elsevier B.V. All rights reserved.

The purpose of this study was to determine the predictive power for treatment outcome of a machine-learning algorithm combining magnetic resonance imaging (MRI)-derived data in patients with sinonasal squamous cell carcinomas (SCCs). Thirty-six primary lesions in 36 patients were evaluated. Quantitative morphological parameters and intratumoral characteristics from T2-weighted images, tumor perfusion parameters from arterial spin labeling (ASL) and tumor diffusion parameters of five diffusion models from multi-b-value diffusion-weighted imaging (DWI) were obtained. Machine learning by a non-linear support vector machine (SVM) was used to construct the best diagnostic algorithm for the prediction of local control and failure. The diagnostic accuracy was evaluated using a 9-fold cross-validation scheme, dividing patients into training and validation sets. Classification criteria for the division of local control and failure in nine training sets could be constructed with a mean sensitivity of 0.98, specificity of 0.91, positive predictive value (PPV) of 0.94, negative predictive value (NPV) of 0.97, and accuracy of 0.96. The nine validation data sets showed a mean sensitivity of 1.0, specificity of 0.82, PPV of 0.86, NPV of 1.0, and accuracy of 0.92. In conclusion, a machine-learning algorithm using various MR imaging-derived data can be helpful for the prediction of treatment outcomes in patients with sinonasal SCCs.

The purpose of this study was to determine the predictive power for treatment outcome of a machine-learning algorithm combining magnetic resonance imaging (MRI)-derived data in patients with sinonasal squamous cell carcinomas (SCCs). Thirty-six primary lesions in 36 patients were evaluated. Quantitative morphological parameters and intratumoral characteristics from T2-weighted images, tumor perfusion parameters from arterial spin labeling (ASL) and tumor diffusion parameters of five diffusion models from multi-b-value diffusion-weighted imaging (DWI) were obtained. Machine learning by a non-linear support vector machine (SVM) was used to construct the best diagnostic algorithm for the prediction of local control and failure. The diagnostic accuracy was evaluated using a 9-fold cross-validation scheme, dividing patients into training and validation sets. Classification criteria for the division of local control and failure in nine training sets could be constructed with a mean sensitivity of 0.98, specificity of 0.91, positive predictive value (PPV) of 0.94, negative predictive value (NPV) of 0.97, and accuracy of 0.96. The nine validation data sets showed a mean sensitivity of 1.0, specificity of 0.82, PPV of 0.86, NPV of 1.0, and accuracy of 0.92. In conclusion, a machine-learning algorithm using various MR imaging-derived data can be helpful for the prediction of treatment outcomes in patients with sinonasal SCCs.