S6-4: Protein Kinase Mutation Patterns in Human Breast Cancer.
Authors: L Pusztai, Y Qi, W Shi, C-G Liu, B Wang, X Liu, D Booser, FJ Esteva, F Symmans, GN Hortobagyi
Journal: Cancer Research (2011)

Abstract Background: We performed next generation targeted sequencing of all known human protein kinases (n=530 genes) and 56 additional cancer related genes (BRCA1,2, p53, PTEN, etc..) in 112 samples to assess the kinase mutation landscape of breast cancer. Gene expression profiling was also performed on RNA from each specimen and DNA copy number variations were assessed in a subset of 59 cases using array CGH. The three types of genomic data were mapped to canonical biological pathways to identify frequently genomically disturbed pathways in these cancers. Methods: DNA and RNA extracted from fine needle biopsies of 92 breast cancers were analyzed, 20 samples were sequenced in duplicates or triplicates to assess technical variation of the results. Targeted sequencing was performed with Agilent SureSelect Human Kinome kit and the SOLiD sequencing platform. Gene expression profiling and array CGH were performed with Affymetrix U133A chips and Agilent 244K CGH array. Sequence data was mapped to hg19, functional impact scores were calculated with SWIFT, canonical pathways were obtained from the Broad Institute. Results: 0.1% of the entire genome was sequenced and &amp;gt;80% of target base pairs had &amp;gt; 20-fold coverage. The mean number of single nucleic acid variants (SNV) and indels per sample were 1043 (range: 493–1583, about 60% homozygous) and 159 (range: 75–269) respectively, 97% of SNVs and 78% of indels were already represented in dbSNP or COSMIC data bases. About 20% of SNVs were predicted to alter kinase or other biological function. The mean number of functionally high impact SNVs was 28 per sample (range 11–47). In addition to known p53 and PI3K mutations we detected frequent mutations in BRCA1 (20%) and observed several predicted high impact SNVs in HER2 (20%) as well as in many MAPK family enzymes. Not all SNVs were distributed equally across disease subsets, SNVs in ULK4, BMP2K, PALB2, ALPK3 were more frequent in triple negative cancers (TNBC) whereas SNVs in EPHA2 was more common in ER+ cancers. Among TNBC, those with residual cancer after neo-adjuvant chemotherapy (n=22) had significantly higher rates of SNVs in HUNK, TRPM7, NEK1 and HER3 compared to cases with pathologic complete response (n=25). When high impact SNVs, DNA copy number alterations and gene over-expression (relative to normal breast n=45) observed in individual cases were mapped to biological pathways a complex network of anomalies emerged for each case. Conclusion: We observed several known mutations in cancer genes and also detected many SNVs in important regulatory genes that were previously described as functional, germ-line variants with experimentally validated or suspected impact on protein function. Individual cancers have unique combinations of these events. This suggest that cancers arise in the context of complex genomic “germ line noise” which may determine which types of somatic events can or cannot “drive” individual cancers. The data also suggest therapeutic hypotheses about what biological pathways should be targeted in individuals and in subsets of cancers. Citation Information: Cancer Res 2011;71(24 Suppl):Abstract nr S6-4.