Abstract：
The newly emerging sinonasal carcinomas have demonstrated diverse morphologies and specific molecular rearrangements along with deviant clinical behavior from conventional counterparts. We aim to propose a diagnostic algorithm that is based on molecular findings of each sinonasal cancer and is considering the new entities has been called upon. Such a diagnostic algorithm should help diagnostic pathologists establish a diagnosis of a challenging sinonasal blue cell carcinomas and researchers performing retrospective analysis of archival cases. Along with consulting our archival cases, literature mining was conducted to retrieve the immunohistochemical and molecular findings regarding the newly emerging entities. Our proposed algorithm distinguishes poorly differentiated (non) keratinizing SNSCC, from anaplastic myoepithelial carcinoma, NUT midline carcinoma, SMARCB1/SMARCA4-deficient teratocarcinosarcoma, SMARCB1/SMARCA4-deficient carcinosarcoma, olfactory neuroblastoma, sinonasal undifferentiated carcinoma, HPV-related multiphenotypic sinonasal carcinoma and other adenocarcinomas. By incorporating morphologic features, immunohistochemical markers, and molecular investigations, the algorithm enhances the accuracy of diagnosis, particularly in cases where comprehensive molecular testing is not readily available. This algorithm serves as a valuable resource for pathologists, facilitating the proper diagnosis of sinonasal malignancies and guiding appropriate patient management.
摘要：
新出现的鼻窦癌表现出多种形态和特定的分子重排，以及与常规对应物不同的临床行为。我们的目标是提出一种诊断算法，该算法基于每种鼻窦癌的分子发现，并考虑了新的实体。这种诊断算法应有助于诊断病理学家建立具有挑战性的鼻窦蓝细胞癌的诊断，并帮助研究人员对档案病例进行回顾性分析。除了咨询我们的档案案例，进行文献挖掘以检索有关新出现的实体的免疫组织化学和分子发现。我们提出的算法区分了低分化(非)角化SNSCC，间变性肌上皮癌，NUT中线癌，SMARCB1/SMARCA4缺陷型畸胎癌肉瘤，SMARCB1/SMARCA4缺陷性癌肉瘤，嗅觉神经母细胞瘤,鼻窦未分化癌,HPV相关的多表型鼻腔鼻窦癌和其他腺癌。通过结合形态学特征，免疫组织化学标记，和分子研究，该算法提高了诊断的准确性，特别是在全面的分子检测不容易获得的情况下。该算法是病理学家的宝贵资源，促进鼻窦恶性肿瘤的正确诊断并指导适当的患者管理。
