Kerstin Zwirner1, Franz J Hilke2, German Demidov2, Jairo Socarras Fernandez3, Stephan Ossowski2,4, Cihan Gani5,6, Daniela Thorwarth3,6, Olaf Riess2,7, Daniel Zips5,6, Christopher Schroeder2, Stefan Welz5,6. 1. Department of Radiation Oncology, Medical Faculty and University Hospital, Eberhard Karls University, Hoppe-Seyler-Straße 3, 72076, Tübingen, Germany. Kerstin.Zwirner@med.uni-tuebingen.de. 2. Institute of Medical Genetics and Applied Genomics, Medical Faculty and University Hospital, Eberhard Karls University, Calwerstraße 7, 72076, Tübingen, Germany. 3. Section for Biomedical Physics, Department of Radiation Oncology, Medical Faculty and University Hospital, Eberhard Karls University, Hoppe-Seyler-Straße 3, 72076, Tübingen, Germany. 4. Centre for Genomic Regulation (CRG), The Barcelona Institute of Science and Technology, C/Dr. Aiguader 88, 08003, Barcelona, Spain. 5. Department of Radiation Oncology, Medical Faculty and University Hospital, Eberhard Karls University, Hoppe-Seyler-Straße 3, 72076, Tübingen, Germany. 6. German Cancer Research Center (DKFZ) partner site Tübingen, German Cancer Consortium (DKTK), Hoppe-Seyler-Straße 3, 72076, Tübingen, Germany. 7. NGS Competence Center Tübingen (NCCT), Eberhard Karls University, Calwerstraße 7, 72076, Tübingen, Germany.
Abstract
PURPOSE: Genetic tumour profiles and radiomic features can be used to complement clinical information in head and neck squamous cell carcinoma (HNSCC) patients. Radiogenomics imply the potential to investigate complementarity or interrelations of radiomic and genomic features, and prognostic factors might be determined. The aim of our study was to explore radiogenomics in HNSCC. METHODS: For 20 HNSCC patients treated with primary radiochemotherapy, next-generation sequencing (NGS) of tumour and corresponding normal tissue was performed. In total, 327 genes were investigated by panel sequencing. Radiomic features were extracted from computed tomography data. A hypothesis-driven approach was used for radiogenomic correlations of selected image-based heterogeneity features and well-known driver gene mutations in HNSCC. RESULTS: The most frequently mutated driver genes in our cohort were TP53 (involved in cell cycle control), FAT1 (Wnt signalling, cell-cell contacts, migration) and KMT2D (chromatin modification). Radiomic features of heterogeneity did not correlate significantly with somatic mutations in TP53 or KMT2D. However, somatic mutations in FAT1 and smaller primary tumour volumes were associated with reduced radiomic intra-tumour heterogeneity. CONCLUSION: The landscape of somatic variants in our cohort is well in line with previous reports. An association of somatic mutations in FAT1 with reduced radiomic tumour heterogeneity could potentially elucidate the previously described favourable outcomes of these patients. Larger studies are needed to validate this exploratory data in the future.
PURPOSE: Genetic tumour profiles and radiomic features can be used to complement clinical information in head and neck squamous cell carcinoma (HNSCC) patients. Radiogenomics imply the potential to investigate complementarity or interrelations of radiomic and genomic features, and prognostic factors might be determined. The aim of our study was to explore radiogenomics in HNSCC. METHODS: For 20 HNSCCpatients treated with primary radiochemotherapy, next-generation sequencing (NGS) of tumour and corresponding normal tissue was performed. In total, 327 genes were investigated by panel sequencing. Radiomic features were extracted from computed tomography data. A hypothesis-driven approach was used for radiogenomic correlations of selected image-based heterogeneity features and well-known driver gene mutations in HNSCC. RESULTS: The most frequently mutated driver genes in our cohort were TP53 (involved in cell cycle control), FAT1 (Wnt signalling, cell-cell contacts, migration) and KMT2D (chromatin modification). Radiomic features of heterogeneity did not correlate significantly with somatic mutations in TP53 or KMT2D. However, somatic mutations in FAT1 and smaller primary tumour volumes were associated with reduced radiomic intra-tumour heterogeneity. CONCLUSION: The landscape of somatic variants in our cohort is well in line with previous reports. An association of somatic mutations in FAT1 with reduced radiomic tumour heterogeneity could potentially elucidate the previously described favourable outcomes of these patients. Larger studies are needed to validate this exploratory data in the future.
Authors: Francesco Cianflone; Dejan Lazarevic; Anna Palmisano; Giuseppe Fallara; Alessandro Larcher; Massimo Freschi; Giacomo Dell'Antonio; Giulia Maria Scotti; Marco J Morelli; Anna Maria Ferrara; Francesco Trevisani; Alessandra Cinque; Antonio Esposito; Alberto Briganti; Carlo Tacchetti; Claudio Doglioni; Alessandro Del Maschio; Francesco de Cobelli; Roberto Bertini; Andrea Salonia; Francesco Montorsi; Giovanni Tonon; Umberto Capitanio Journal: Transl Androl Urol Date: 2022-02