Clinical utility of a custom next-generation sequencing panel in the diagnosis of needle biopsies from renal masses
| Autor: | Raju S.K. Chaganti, Rekha Soni, Sitharthan Kamalakaran, Venkata Thodima, Banumathy Gowrishankar, Jonathan A. Coleman, Massimiliano Spaliviero, Kelly Lynn Stratton, Manickam Janakiraman, Jane Houldsworth, Stephen B. Solomon, Jeremy C. Durack, Raghavendra Padmanabhan |
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| Rok vydání: | 2016 |
| Předmět: |
Cancer Research
Pathology medicine.medical_specialty medicine.diagnostic_test business.industry Library preparation Cancer Single-nucleotide polymorphism Computational biology medicine.disease DNA sequencing 03 medical and health sciences 0302 clinical medicine Oncology Targeted ngs 030220 oncology & carcinogenesis Biopsy medicine SNP business 030215 immunology |
| Zdroj: | Journal of Clinical Oncology. 34:528-528 |
| ISSN: | 1527-7755 0732-183X 2549-8568 |
| DOI: | 10.1200/jco.2016.34.2_suppl.528 |
| Popis: | 528 Background: Image-guided core-needle biopsies are increasingly being utilized to assist in the management of patients with renal masses, where only limited material is available for analysis. In this study, the performance of a custom next-generation sequencing (NGS) panel was evaluated for diagnostic and prognostic utility in this setting. Methods: DNA was available for NGS from 41 of 48 core-needle biopsies from renal masses previously submitted to array-CGH (aCGH) in this IRB-approved study. The targeted NGS panel comprised genes mutated in renal cancer, prognostic SNPs, and a 3Mbp SNP backbone. After library preparation from as little as 25ng DNA, sequencing was performed (MiSeq, Illumina), variants identified using CLCbio, and genomic gain/loss estimated by CNVKit (Talevich E, et al, manuscript in preparation). A classification algorithm based on 15 copy number alterations (CNAs) was applied to aCGH and NGS CNA profiles (PMID: 25498568). Histology of the biopsy or resected specimen (if available) served as the gold standard. Results: By histology, the 41 profiled biopsies comprised: 13 clear cell RCC (ccRCC), 9 papillary RCC (pRCC), 2 chromophobe RCC (chrRCC), 12 benign neoplasms, 2 unclassified, 2 high grade/poorly differentiated RCC, and 1 non-diagnostic. Among ccRCC, aCGH correctly subtyped 8/13. No CNAs were detected in the remaining 5, but for which NGS detected CNAs in 3/5 and TET2 mutations in 1. Mutations in PBRM1 and BAP1 with reported prognostic significance in ccRCC were found in 3 and 1 specimens respectively. Apart from 1 without any detectable mutations or CNAs, aCGH and NGS correctly subtyped 8/9 pRCCs based on CNAs. Also, activating MET mutations were seen in 2 pRCC specimens. aCGH and NGS accurately diagnosed the 2 chrRCC and detected pRCC-related CNAs in 2/13 benign neoplasms. In the two unclassified specimens, both methods identified ccRCC-related CNAs. Notably, NGS identified CNAs and mutations in the biopsy non-diagnostic by histology. Conclusions: Overall, targeted NGS can robustly detect genomic alterations requiring only limited DNA, that together with histology, contributes important diagnostic and prognostic information in the management of renal mass patients. |
| Databáze: | OpenAIRE |
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