Diagnostic algorithm for challenging blue cell sinonasal carcinoma

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.