Abstract A12: Systematic identification of germline mutations in rhabdomyosarcoma and neuroblastoma using massively paralleled sequencing

Abstract

Abstract Despite improvement of survival rate with multimodal chemo- and immunotherapy, high mortality and morbidity is still substantial for patients with metastatic pediatric cancers. Recent studies of massively paralleled sequencing of pediatric tumors including rhabdomyosarcoma (RMS) and neuroblastoma (NB) have been focusing on somatic mutations, and revealed a low somatic mutation rate and surprisingly few recurrently somatic mutated genes in these childhood tumors. Therefore, only a small portion of pediatric cancer cases can be explained by somatic driver events; whereas the causal events for the majority of these diseases remain unknown. Here, we hypothesize that infrequent germline mutations may play a role in the initiation of sporadically occurring tumor. To identify rare expressed germline protein-coding changing mutations, we utilized two cancer patient cohorts consisting of RMS (n=83) and NB (n=93) patients, of which latter is a part of the Therapeutically Applicable Research to Generate Effective Treatments (TARGET) initiative for pediatric cancers. We first called high-quality protein-coding changing single nucleotide variants (SNVs) (≥100, Coverage ≥10, ≥3 variant reads, ≥30% variant allele frequency) in both paired germline and tumor genomic DNAs. Since both these two types of tumors are uncommon, we then excluded variants with frequencies of >0.1% in the normal human population using the 1000 Genomes data, but retained all disease-causing SNVs annotated either by the Human Gene Mutation Database (HGMD) or ClinVar. Previous studies have highlighted the importance of expression of variant genes (including tumor suppressor genes) for identification of driver mutations in cancers. Therefore we utilized transcriptome sequencing experiments to identify expressed variants in tumor. In addition, we performed Fisher's exact tests comparing germline mutations in these two patient cohorts with the ESP dataset comprising 6503 non-cancer subjects to identify significant overrepresentation of germline mutations in these cancers. Finally we performed pathway analyses using the significant genes. We initially identified a total of 783169 high-quality protein-coding changing SNVs detected in both paired germline and tumor genomic DNAs, corresponding to a median of 4818 (2093-7569) SNVs per patient. After exclusion of common variants of ≥0.1% frequency in the 1000 Genomes and inclusion of all disease-causing SNVs, there are total of 91924 SNVs, representing a median of 535 (155-877) SNVs per patient corresponding to a median of 468 (153-752) genes. Approximately 59% (total 54664, Median of 319 (94-549) SNVs) of these germline variants can be detected in the transcriptome in their corresponding tumors, suggesting potential functions in these tumors. Statistical analysis is currently underway to determine potential pathological or casual germline mutations associated with neuroblastoma and rhabdomyosarcoma. Citation Format: Jun S. Wei, Rajesh Patidar, John Shern, Shile Zhang, Trevor Pugh, Sharon J. Diskin, Sivasish Sindiri, Young K. Song, Hongling Liao, Xinyu Wen, Jianjun Wang, Stephen X. Skapek, James R. Anderson, Frederic G. Barr, Robert C. Seeger, John M. Maris, Douglas Hawkins, Javed Khan. Systematic identification of germline mutations in rhabdomyosarcoma and neuroblastoma using massively paralleled sequencing. [abstract]. In: Proceedings of the AACR Special Conference on Pediatric Cancer at the Crossroads: Translating Discovery into Improved Outcomes; Nov 3-6, 2013; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2013;74(20 Suppl):Abstract nr A12.