| Autor: |
Ruud H. Brakenhoff, C. René Leemans, Tito Poli, Elena Thai, Elisabeth Bloemena, Mark A. van de Wiel, Arjen Brink, Jos B. Poell, Steven W. Mes, Reinout H. de Roest |
| Rok vydání: |
2023 |
| DOI: |
10.1158/1078-0432.c.6527912 |
| Popis: |
Purpose:To investigate the pathobiological origin of local relapse after chemoradiotherapy, we studied genetic relationships of primary tumors (PT) and local relapses (LR) of patients treated with chemoradiotherapy.Experimental Design:First, low-coverage whole genome sequencing was performed on DNA from 44 biopsies of resected head and neck squamous cell carcinoma (HNSCC) specimens (median 3 biopsies/tumor) to assess suitability of copy number alterations (CNAs) as biomarker for genetic relationships. CNAs were compared within and between tumors and an algorithm was developed to assess genetic relationships with consideration of intratumor heterogeneity. Next, this CNA-based algorithm was combined with target enrichment sequencing of genes frequently mutated in HNSCC to assess the genetic relationships of paired tumors and LRs of patients treated with chemoradiotherapy.Results:Genetic relationship analysis using CNAs could accurately (96%) predict tumor biopsy pairs as patient-matched or independent. However, subsequent CNA analysis of PTs and LRs after chemoradiotherapy suggested genetic relationships in only 20% of cases, and absence in 80%. Target enrichment sequencing for mutations confirmed absence of any genetic relationship in half of the paired PTs and LRs.Conclusions:There are minor variations in CNA profiles within different areas of HNSCC tumors and many between independent tumors, suggesting that CNA profiles could be exploited as a marker of genetic relationship. Using CNA profiling and mutational analysis of cancer driver genes, relapses after chemoradiotherapy appear to be partially genetically related to the corresponding PTs, but seem often genetically unrelated. This remarkable observation warrants further studies and will impact therapeutic innovations and prognostic modeling when using index tumor characteristics. |
| Databáze: |
OpenAIRE |
| Externí odkaz: |
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