Abstract 92: Integrated analysis of copy number, sequence variant and gene expression data in kidney chromophobe cohort

Abstract

Abstract The Cancer Genome Atlas (TCGA) contains various types of genomic data from a wide variety of cancers, including several rare tumor types. Here we analyze copy number, sequence variant and RNA-Seq data from TCGA for kidney chromophobe (KICH). Level 1 (raw) data, rather than Level 3 (segmented) data, from TCGA was used for an integrated analysis of copy number and gene expression profiles of the two cancers. Using the copy number and SNP probes, re-processed tumor profiles were more consistent with a control set in terms of median number of copy number events, sample ploidy, and breakpoint genes than with the published level 3 TCGA data. Probe-level data were analyzed using Nexus Copy Number SNP-FASST2 algorithm (a multi-state HMM algorithm), with systematic correction applied to correct for GC biases. Additionally we performed manual baseline adjustment to correct for sample ploidy based on whole-genome B-allele frequency data for each sample. Overall, the median number of copy number events in the KICH TCGA data set was reduced from 408 (in the level 3 set) to 85. After manual inspection, more than 87% of the TCGA KICH samples available at level 3 were found to have incorrect baseline ploidy assignments. Given KICH samples are known to have low ploidy overall, this step was critical for downstream analysis. RNA-Seq results for the entire cohort were evaluated to obtain normalized relative RNA expression. Somatic sequence variation results from whole exome sequencing and relative RNA expression were integrated with the individual copy number profiles to yield integrated per-sample results across all three data modalities. Aggregate analysis indicates highly recurrent losses (50-85% of samples) on chromosomes 1, 2, 6, 10, 13, 17 and 21. Lower level recurrent losses (∼15-20% of samples) were identified on chromosomes 3, 5, 8, 9, 11 and 18. Concordance analysis revealed statistically significant subsets of samples with co-occurring lower level recurrent losses. Aggregate sequence mutation analysis of chromosomes among 3, 5, 8, 9, 11 and 18 did not identify any mutational hotspots. Integration with RNA-Seq expression data from each tumor type revealed statistically significant correlations (p<0.05) with these copy number alterations, identifying potential driver genes of interest. Closer evaluation of copy number alteration and RNA-Seq expression at the individual sample level confirmed co-occurrence of significantly downregulated RNA expression within these regions of loss but no expression changes in samples without loss. This correlated with an overall difference in survival but was not statistically significant, given the overall small size of the data set. While still limiting in sample size, the TCGA KICH data series offers unique insight into a rare tumor type. Cross data integration for individual samples offers additional strength and validity to findings initially uncovered through traditional aggregate analysis. Citation Format: Andrea J. O’Hara, Zhiwei Che, Soheil Shams. Integrated analysis of copy number, sequence variant and gene expression data in kidney chromophobe cohort. [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr 92.