A population-based comparison of European and North American sinonasal cancer survival

International Consensus Statement on Allergy and Rhinology: Sinonasal Tumors

BACKGROUND

Sinonasal neoplasms, whether benign and malignant, pose a significant challenge to clinicians and represent a model area for multidisciplinary collaboration in order to optimize patient care. The International Consensus Statement on Allergy and Rhinology: Sinonasal Tumors (ICSNT) aims to summarize the best available evidence and presents 48 thematic and histopathology-based topics spanning the field.

METHODS

In accordance with prior International Consensus Statement on Allergy and Rhinology documents, ICSNT assigned each topic as an Evidence-Based Review with Recommendations, Evidence-Based Review, and Literature Review based on the level of evidence. An international group of multidisciplinary author teams were assembled for the topic reviews using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses format, and completed sections underwent a thorough and iterative consensus-building process. The final document underwent rigorous synthesis and review prior to publication.

RESULTS

The ICSNT document consists of four major sections: general principles, benign neoplasms and lesions, malignant neoplasms, and quality of life and surveillance. It covers 48 conceptual and/or histopathology-based topics relevant to sinonasal neoplasms and masses. Topics with a high level of evidence provided specific recommendations, while other areas summarized the current state of evidence. A final section highlights research opportunities and future directions, contributing to advancing knowledge and community intervention.

CONCLUSION

As an embodiment of the multidisciplinary and collaborative model of care in sinonasal neoplasms and masses, ICSNT was designed as a comprehensive, international, and multidisciplinary collaborative endeavor. Its primary objective is to summarize the existing evidence in the field of sinonasal neoplasms and masses.

A Combined Model Integrating Radiomics and Deep Learning Based on Contrast-Enhanced CT for Preoperative Staging of Laryngeal Carcinoma

RATIONALE AND OBJECTIVES

Accurate staging of laryngeal carcinoma can inform appropriate treatment decision-making. We developed a radiomics model, a deep learning (DL) model, and a combined model (incorporating radiomics features and DL features) based on the venous-phase CT images and explored the performance of these models in stratifying patients with laryngeal carcinoma into stage I-II and stage III-IV, and also compared these models with radiologists.

MATERIALS AND METHODS

Three hundreds and nineteen patients with pathologically confirmed laryngeal carcinoma were randomly divided into a training set (n = 223) and a test set (n = 96). In the training set, the radiomics features with inter- and intraclass correlation coefficients (ICCs)> 0.75 were screened by Spearman correlation analysis and recursive feature elimination (RFE); then support vector machine (SVM) classifier was applied to develop the radiomics model. The DL model was built using ResNet 18 by the cropped 2D regions of interest (ROIs) in the maximum tumor ROI slices and the last fully connected layer of this network served as the DL feature extractor. Finally, a combined model was developed by pooling the radiomics features and extracted DL features to predict the staging.

RESULTS

The area under the curves (AUCs) for radiomics model, DL model, and combined model in the test set were 0.704 (95% confidence interval [CI]: 0.588-0.820), 0.724 (95% CI: 0.613-0.835), and 0.849 (95% CI: 0.755-0.943), respectively. The combined model outperformed the radiomics model and the DL model in discriminating stage I-II from stage III-IV (p = 0.031 and p = 0.020, respectively). Only the combined model performed significantly better than radiologists (p < 0.050 for both).

CONCLUSION

The combined model can help tailor the therapeutic strategy for laryngeal carcinoma patients by enabling more accurate preoperative staging.

p16 Overexpression in Sinonasal Squamous Cell Carcinoma: Association with Human Papillomavirus and Prediction of Survival Outcomes

p16 overexpression is often used as a surrogate marker for human papillomavirus (HPV) infection in oropharyngeal squamous cell carcinoma but remains an uncertain diagnostic tool for HPV-related sinonasal squamous cell carcinoma (SNSCC). Our study involved 79 consecutive SNSCC patients who were treated at a tertiary referral university hospital during 2006-2021. We retrospectively examined their clinical characteristics and conducted p16 immunohistochemistry and HPV detection. We found that 12.7% of the patients exhibited p16 overexpression, which was significantly more common in the nasal cavity and increased from 2015 onward. The HPV was a high-risk type and viral loads ranged from 4.2 to 1.6 × 106 copies/ng DNA with genome integration. Five-year overall survival (OS) and five-year relapse-free survival (RFS) rates were 74.6% and 69.9%, respectively. Our multivariate analysis showed that T category (T1-4a) and hemoglobin levels (≥13.7) were significant favorable prognostic factors for OS, while T category, performance status, and p16 overexpression were significantly associated with RFS. In patients with p16 overexpression, OS was 100% and RFS was 90%. Our findings suggest that p16 overexpression is a reliable surrogate marker for transcriptionally active HPV infection and predicts a favorable prognosis.

[Radiotherapy of rare head and neck tumors]

Management of head and neck tumors is complex because of multiple anatomical locations and histologies possibilities. Rare tumors must be managed in a specialized center and be registered in the French network of expertise on ENT Cancers (Refcor). Despite heterogeneous levels of evidence, radiotherapy plays an essential role in their treatment. Radiation therapy is generally indicated in the adjuvant setting, or in case of non-operability. Dose and target volumes depend on histology, location and extensions of the tumor, and the quality of the excision if applicable. We present here a review of the literature and available guidelines for the management by radiotherapy of rare upper aerodigestive tract tumors.

Sinonasal adenocarcinomas: Retrospective analysis from an oncology center

INTRODUCTION AND OBJECTIVES

Sinonasal adenocarcinomas are rare and heterogeneous tumors and for this reason remain understudied. Our purpose is to analyze clinical presentation, outcomes and factors affecting survival of patients with sinonasal adenocarcinomas, treated at our institution.

MATERIAL AND METHODS

Retrospective review of clinical records of patients with sinonasal adenocarcinoma, treated at a tertiary oncology institution (January 2010 to December 2019).

RESULTS

Sixty patients diagnosed with adenocarcinoma were included, with male preponderance (54.90%) and a mean age of 57.5±14.9 years. Adenocarcinoma was the most frequent type of sinonasal cancer, contrary to previous reports from our institution. In most patients, it was detected at an advanced disease stage, significantly decreasing their survival rate when compared to patients diagnosed at initial stages (p<0.029). Intestinal type adenocarcinoma was established in 47 patients, the most frequent being the colonic subtype (24%). Tumors with good/moderate histologic differentiation presented a survival advantage over those that were poorly differentiated (p=0.043). The most common treatment modality was surgery followed by radiotherapy. Endoscopic resection was performed in 53% of the patients and an external approach was used in 40% of the patients. Estimated overall survival rates at 3 and 5-years were 64% and 53%, respectively, and cancer specific survival 72% and 65%, for the same period. Recurrence rate was 32% and occurred mainly locally. Disease Free Survival rate was 71% at 3 years and 65% at 5 years.

CONCLUSIONS

Despite being the most common sinonasal malignancy in our sample, in contrast to other series, sinonasal adenocarcinomas are still rare tumors with a substantial local failure rate of around 30%. Advanced stage at diagnosis and histologic differentiation grade negatively affected prognosis of these tumors.

The MUSES∗: a prognostic study on 1360 patients with sinonasal cancer undergoing endoscopic surgery-based treatment: ∗MUlti-institutional collaborative Study on Endoscopically treated Sinonasal cancers

BACKGROUND

Over the last 2 decades, transnasal endoscopic surgery (TES) has become the most frequently employed surgical technique to treat sinonasal malignancies. The rarity and heterogeneity of sinonasal cancers have hampered large non-population-based analyses.

METHODOLOGY

All patients receiving TES-including treatment between 1995 and 2021 in 5 referral hospitals were included. A prognostic study was performed, and multivariable models were transformed into nomograms. Training and validation sets were based on results from 3 European and 2 non-European centres, respectively.

RESULTS

The training and validation set included 940 and 420 patients, respectively. The mean age at surgery, primary-versus-recurrent presentation, histology distribution, type of surgery, T category and type of adjuvant treatment were differently distributed in the training and validation set. In the training set, 5-year overall survival and recurrence-free survival with a 95%-confidence interval were 72.7% (69.5-76.0%) and 66.4% (63.1-69.8%), respectively, significantly varying with histology. At multivariable analyses, age, gender, previous treatment, the extent of resection on the cranial, lateral and posterolateral axes, grade/subtype, T category, nodal status, margin status and adjuvant treatment were all associated with different prognostic outcomes, displaying a heterogeneous significance and effect size according to histology. The internal and external validation of nomograms was satisfactory (optimism-corrected C-index >0.7 and cumulative area under curve >0.7) for all histologies but mucosal melanoma.

CONCLUSIONS

Outcomes of TES-based treatment of sinonasal cancers vary substantially with histology. This large, non-population-based study provides benchmark data on the prognosis of sinonasal cancers that are deemed suitable for treatment including TES.

Post-Surgery Subcutaneous Seeding of Laryngeal Squamous Cell Carcinoma: A Rare Case

Laryngeal squamous cell carcinoma (LSCC) is the most common malignant head and neck cancer, with a 40% recurrence rate in the first 3 years after radical treatment. Recurrence of LSCC mostly comprises lymphogenous metastasis, hematogenic metastasis, and locoregional recurrence, while LSCC seeding is rarest: there are only 4 cases reported in PubMed, and none of them is one of subcutaneous seeding. We report a case with post-surgery subcutaneous seeding of LSCC. The final biopsy demonstrated that the subcutaneous seeding of the LSCC was 2 cm away from the primary lesion, with no recurrent foci observed in the larynx and tracheostoma and little relation to the primary lesion. Thus, we drew the conclusion that LSCC surgeries should stick to the principle of the non-tumor technique to prevent subcutaneous seeding.

Development and Validation of Epigenetic Signature Predict Survival for Patients with Laryngeal Squamous Cell Carcinoma

Establishing epigenetic signature to improve the accuracy of survival prediction and optimize therapeutic strategies for laryngeal squamous cell carcinoma (LSCC) by a genome-wide integrated analysis of methylation and the transcriptome. LSCC DNA methylation datasets and RNA sequencing datasets were acquired from the Cancer Genome Atlas (TCGA). MethylMix was applied to detect DNA methylation-driven genes (MDGs), which developed an epigenetic signature. The predictive accuracy and clinical value of the epigenetic signature were evaluated by receiver operating characteristic and decision curve analysis, and compared with tumor-node-metastasis (TNM) stage system. In addition, prognostic value of the epigenetic signature was validated by external Gene Expression Omnibus (GEO) database. According to five MDGs of epigenetic signature, the candidate small molecules for LSCC were screen out by the CMap database. A total of 88 DNA MDGs were identified, five of which (MAGEB2, SUSD1, ZNF382, ZNF418, and ZNF732) were chosen to construct an epigenetic signature. The epigenetic signature can effectively divide patients into high-risk and low-risk group, with the area under curve (AUC) of 0.8 (5-year overall survival [OS]) and AUC of 0.745 (3-year OS). Stratification analysis affirmed that the epigenetic signature was still a significant statistical prognostic model in subsets of patients with different clinical variables. Multivariate Cox regression analysis indicated that the efficacy of epigenetic signature appears independent of other clinicopathological characteristics. In terms of predictive capacity and clinical usefulness, the epigenetic signature was superior to traditional TNM stage. In addition, the epigenetic signature was confirmed in external LSCC cohorts from GEO. Finally, CMap matched the 10 most significant small molecules as promising therapeutic drugs to reverse the LSCC gene expression. An epigenetic signature, with five DNA MDGs, was identified and validated in LSCC patients by integrating multidimensional genomic data, which may offer novel research directions and prospects for individualized treatment of patients with LSCC.

Identification and validation of methylation-driven genes prognostic signature for recurrence of laryngeal squamous cell carcinoma by integrated bioinformatics analysis

Background

Recurrence remains a major obstacle to long-term survival of laryngeal squamous cell carcinoma (LSCC). We conducted a genome-wide integrated analysis of methylation and the transcriptome to establish methylation-driven genes prognostic signature (MDGPS) to precisely predict recurrence probability and optimize therapeutic strategies for LSCC.

Methods

LSCC DNA methylation datasets and RNA sequencing (RNA-seq) dataset were acquired from the Cancer Genome Atlas (TCGA). MethylMix was applied to detect DNA methylation-driven genes (MDGs). By univariate and multivariate Cox regression analyses, five genes of DNA MDGs was developed a recurrence-free survival (RFS)-related MDGPS. The predictive accuracy and clinical value of the MDGPS were evaluated by receiver operating characteristic (ROC) and decision curve analysis (DCA), and compared with TNM stage system. Additionally, prognostic value of MDGPS was validated by external Gene Expression Omnibus (GEO) database. According to 5 MDGs, the candidate small molecules for LSCC were screen out by the CMap database. To strengthen the bioinformatics analysis results, 30 pairs of clinical samples were evaluated by digoxigenin-labeled chromogenic in situ hybridization (CISH).

Results

A total of 88 DNA MDGs were identified, and five RFS-related MDGs (LINC01354, CCDC8, PHYHD1, MAGEB2 and ZNF732) were chosen to construct a MDGPS. The MDGPS can effectively divide patients into high-risk and low-risk group, with the area under curve (AUC) of 0.738 (5-year RFS) and AUC of 0.74 (3-year RFS). Stratification analysis affirmed that the MDGPS was still a significant statistical prognostic model in subsets of patients with different clinical variables. Multivariate Cox regression analysis indicated the efficacy of MDGPS appears independent of other clinicopathological characteristics. In terms of predictive capacity and clinical usefulness, the MDGPS was superior to traditional TNM stage. Additionally, the MDGPS was confirmed in external LSCC cohorts from GEO. CMap matched the 9 most significant small molecules as promising therapeutic drugs to reverse the LSCC gene expression. Finally, CISH analysis in 30 LSCC tissues and paired adjacent normal tissues revealed that MAGEB2 has significantly higher expression of LSCC compared to adjacent non-neoplastic tissues; LINC01354, CCDC8, PHYHD1, and ZNF732 have significantly lower expression of LSCC compared to adjacent non-neoplastic tissues, which were in line with bioinformatics analysis results.

Conclusion

A MDGPS, with five DNA MDGs, was identified and validated in LSCC patients by combining transcriptome and methylation datasets analysis. Compared TNM stage alone, it generates more accurate estimations of the recurrence prediction and maybe offer novel research directions and prospects for individualized treatment of patients with LSCC.

Development and validation of nomograms to accurately predict risk of recurrence for patients with laryngeal squamous cell carcinoma: Cohort study

BACKGROUND

Recurrence is still major obstacle to long-term survival in laryngeal squamous cell carcinoma (LSCC). We aimed to establish and validate a nomogram to precisely predict recurrence probability in patients with LSCC.

METHODS

A total of 283 consecutive patients with LSCC received curative-intend surgery between 2011 and 2014 at were enrolled in this study. Subsequently, 283 LSCC patients were randomly assigned to a training cohort (N = 171) and a validation cohort (N = 112) in a 3:2 ratio. According to the results of multivariable Cox regression analysis in the training cohort, we developed a nomogram. The predictive accuracy and discriminative ability of the nomogram were evaluated by calibration curve and concordance index (C-index), and compared with TNM stage system by C-index, receiver operating characteristic (ROC) analysis. Decision curve analysis (DCA) was performed to estimate clinical value of our nomogram.

RESULTS

Six independent factors rooted in multivariable analysis of the training cohort to predict recurrence were age, tumor site, smoking, alcohol, N stage and hemoglobin, which were all integrated into the nomogram. The calibration curve for the probability of recurrence presented that the nomogram-based predictions were in good correspondence with actual observations. The C-index of the nomogram was 0.81 (0.75-0.88), and the area under curve (AUC) of nomogram in predicting recurrence free survival (RFS) was 0.894, which were significantly better than traditional TNM stage. Decision curve analysis further affirmed that our nomogram had a larger net benefit than TNM stage. The results were confirmed in the validation cohort.

CONCLUSION

A risk prediction nomogram for patients with LSCC, incorporating readily assessable clinicopathologic variables, generates more accurate estimations of the recurrence probability when compared TNM stage alone, but still needs additional data before being used in clinical implications.

A Genomic-Clinicopathologic Nomogram Predicts Survival for Patients with Laryngeal Squamous Cell Carcinoma

Background

Long noncoding RNAs (lncRNAs), which have little or no ability to encode proteins, have attracted special attention due to their potential role in cancer disease. We aimed to establish a lncRNA signature and a nomogram incorporating the genomic and clinicopathologic factors to improve the accuracy of survival prediction for laryngeal squamous cell carcinoma (LSCC).

Methods

A LSCC RNA-sequencing (RNA-seq) dataset and the matched clinicopathologic information were downloaded from The Cancer Genome Atlas (TCGA). Using univariable Cox regression and least absolute shrinkage and selection operator (LASSO) analysis, we developed a thirteen-lncRNA signature related to prognosis. On the basis of multivariable Cox regression analysis results, a nomogram integrating the genomic and clinicopathologic predictors was built. The predictive accuracy and discriminative ability of the inclusive nomogram were confirmed by calibration curve and a concordance index (C-index), and compared with the TNM staging system by C-index and receiver operating characteristic (ROC) analysis. Decision curve analysis (DCA) was conducted to evaluate the clinical value of our nomogram.

Results

Thirteen overall survival- (OS-) related lncRNAs were identified, and the signature consisting of the selected thirteen lncRNAs could effectively divide patients into high-risk and low-risk subgroups, with area under curves (AUC) of 0.89 (3-year OS) and 0.885 (5-year OS). Independent factors derived from multivariable analysis to predict survival were margin status, tumor status, and lncRNA signature, which were all assembled into the nomogram. The calibration curve for the survival probability showed that the predictions based on the nomogram coincided well with actual observations. The C-index of the nomogram was 0.82 (0.77-0.87), and the area under curve (AUC) of the nomogram in predicting overall survival (OS) was 0.938, both of which were significantly higher than the traditional TNM stage. Decision curve analysis further demonstrated that our nomogram had larger net benefit than TNM stage.

Conclusion

An inclusive nomogram for patients with LSCC, comprising genomic and clinicopathologic variables, generates more accurate estimations of the survival probability when compared with TNM stage alone, but more data are needed before the nomogram is used in clinical practice.