SMARCB1-Retained and SMARCB1-Deficient SNUC are Genetically Distinct: A Pilot Study Using RNA Sequencing

Author:

Chitguppi Chandala1,Rosen Marc1,Nyquist Gurston1,Toskala Elina1,Evans James2,Gargano Stacey3,Tuluc Madalina3,Ertel Adam4,Dsouza Glen1,Addya Sankar4,Johnson Jennifer5,Bar-Ad Voichita6,Rabinowitz Mindy1

Affiliation:

1. Department of Otolaryngology and Head and Neck Surgery, Thomas Jefferson University Hospitals, Philadelphia, Pennsylvania, United States

2. Department of Neurological Surgery, Thomas Jefferson University Hospitals, Philadelphia, Pennsylvania, United States

3. Department of Pathology, Anatomy, and Cell Biology, Thomas Jefferson University Hospitals, Philadelphia, Pennsylvania, United States

4. Department of Cancer Biology, Thomas Jefferson University and Sidney Kimmel Cancer Center, Philadelphia, Pennsylvania, United States

5. Department of Hematology and Medical Oncology, Thomas Jefferson University Hospitals, Philadelphia, Pennsylvania, United States

6. Department of Radiation Oncology-Head and Neck Cancer, Thomas Jefferson University Hospitals, Philadelphia, Pennsylvania, United States

Abstract

Abstract Background Understanding the genetic basis for the molecular classification of sinonasal undifferentiated carcinoma (SNUC) based on SMARCB1 may improve our understating regarding the nature of the disease. The objective of the study was to compare the genetic profile of SMARCB1-retained (SR-SNUC) and SMARCB1-deficient SNUC (SD-SNUC). Methods Formalin-fixed, paraffin-embedded tissue from treatment-naive patients with SNUC were selected. Three cases of SR-SNUC, four cases of SD-SNUC, and four samples of nontumor tissue (control samples) were selected. Ribonucleic acid (RNA) sequencing was performed. Results SR-SNUC had a higher number of variants (1 variant for every 15,000 bases) compared with SD-SNUC (1 variant every 29,000 bases). The ratio of missense to silent mutation ratio was higher for SR-SNUC (0.8) as compared with SD-SNUC (0.7). Approximately 1,500 genes were differentially expressed between SR-SNUC and SD-SNUC. The genes that had a higher expression in SR-SNUC included TPD52L1, B3GNT3, GFY, TJP3, ELL3, CYP4F3, ALDH3B2, CKMT1B, VIPR1, SLC7A5, PPP2R2C, UPK3B, MUC1, ELF5, STY7, and H2AC14. The gene that had a higher expression in SD-SNUC was ZFHX4. Most of these genes were related to either protein translation or immune regulation. The most common (n = 3, 75%) mechanisms of loss of SMARCB1 gene in SD-SNUC was loss of heterozygosity. Conclusion RNA sequencing is a viable and informative approach for genomic profiling of archival SNUC samples. Both SR-SNUC and SD-SNUC were noted to have distinct genetic profiles underlying the molecular classification of these diseases.

Funder

NIH/NCI

Publisher

Georg Thieme Verlag KG

Subject

Neurology (clinical)

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