Sinari, Shripad

Abstract Purpose: Pancreatic adenocarcinoma is among the most lethal forms of all malignancies. While significant research has implicated multiple genes in disease pathogenesis, identification of therapeutic leads has been difficult. The majority of currently available therapies provide only marginal benefit. To address this issue, our goal was to assess global somatic events across multiple pancreatic tumors by using next-generation sequencing technologies (NGS). Experimental Design: We performed whole genome sequencing (WGS) on paired tumor and normal samples from 3 pancreatic adenocarcinoma patients. Additionally, we performed whole transcriptome sequencing (WTS) on 2 of these patients’ tumors for which tumor RNA was available. Results: We generated on average 132 billion mappable bases across all patients using WGS, and identified 140 somatic coding events including point mutations, insertion/deletions, and chromosomal copy number variants. Data from WGS and WTS were integrated and analyzed to identify the most heavily affected pancreatic cancer pathways across all patients. The KRAS signaling pathway was identified as the most significant map. Unbiased global pathway analysis was also performed to identify processes that may be impacted. Consistent with the previous analysis, the most significant pathway from this analysis is also KRAS signaling. This integrated analysis specifically identifies heavily affected pathways in pancreatic cancer and pinpoints genes and processes that may be considered as targets for more effective therapies. Conclusions: While sequencing of additional patients is necessary to strengthen selection of key pathways, we demonstrate the utility of using NGS to understand the processes driving pancreatic adenocarcinoma so that standardized treatments for patients may be improved. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 103rd Annual Meeting of the American Association for Cancer Research; 2012 Mar 31-Apr 4; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2012;72(8 Suppl):Abstract nr 5104. doi:1538-7445.AM2012-5104

Abstract Background: In order to understand the genetic events associated with disease progression and the development of drug resistance in multiple myeloma, we studied four longitudinally collected samples from a single, high risk, t(4;14) multiple myeloma patient. Samples over a four-year period were available from diagnosis, at time of first progression on lenalidomide, second progression while on bortezomib, at time of relapsed refractory disease and with end stage plasma cell leukemia. To better understand these genetic events, we utilized DNA extracted from germline tissue and CD138 purified bone marrow tumor cells to conduct whole genome sequencing (WGS) utilizing the Life Technologies SOLiD™ platform. Results: We have sequenced over 100 billion bases per sample with whole genome fragment library sequencing providing an average of 30X aligned coverage at all four time points studied. Each sample was aligned to the reference genome (NCBI36/hg18) with BFAST and post-alignment removal of duplicates and recalibration performed with Picard and Genome Analysis Toolkit (GATK) respectively. We then called point mutations with SolSNP and compared the germline sample to each tumor sample utilizing the Paired Mutation Walker. To date, we have identified 224 nonsynonymous point mutations within 217 genes. We then utilized the Sorting Intolerant from Tolerant (SIFT) algorithm and identified 109 potentially damaging point mutations which include 108 novel mutations in coding exons. Of the 224 somatic mutations observed, only 20 of these mutations are common to all tumor time points. Interestingly, the diagnostic and bortezomib refractory (second progression) samples had 11 mutations in common while the lenalidomide refractory (first progression) sample shared only 4 mutations in common with the bortezomib refractory sample. This suggests the presence of multiple clones at diagnosis that, due to treatment selection pressure, may emerge or regress as the dominant clone. Preliminary pathway analysis reveals the presence of mutations in genes regulating NFKB and Akt, whose pathways are often dysregulated in cancer. Conclusions: Whole genome sequencing has revealed evidence of mutational differences in exons between tumor and germline DNA indicative of the presence of multiple clones at diagnosis and evolution of these clones over time. This data supports the use of multiple drug therapies that target multiple clones and challenges the long held assumption that a patient who becomes refractory to a particular treatment will always be refractory to that treatment. Additional evaluation in a larger population is needed to confirm these findings. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 102nd Annual Meeting of the American Association for Cancer Research; 2011 Apr 2-6; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2011;71(8 Suppl):Abstract nr 4838. doi:10.1158/1538-7445.AM2011-4838

Abstract The longitudinal evolution of a myeloma genome from diagnosis to plasma cell leukemia has not previously been reported. We used whole-genome sequencing (WGS) on 4 purified tumor samples and patient germline DNA drawn over a 5-year period in a t(4;14) multiple myeloma patient. Tumor samples were acquired at diagnosis, first relapse, second relapse, and end-stage secondary plasma cell leukemia (sPCL). In addition to the t(4;14), all tumor time points also shared 10 common single-nucleotide variants (SNVs) on WGS comprising shared initiating events. Interestingly, we observed genomic sequence variants that waxed and waned with time in progressive tumors, suggesting the presence of multiple independent, yet related, clones at diagnosis that rose and fell in dominance. Five newly acquired SNVs, including truncating mutations of RB1 and ZKSCAN3, were observed only in the final sPCL sample suggesting leukemic transformation events. This longitudinal WGS characterization of the natural history of a high-risk myeloma patient demonstrated tumor heterogeneity at diagnosis with shifting dominance of tumor clones over time and has also identified potential mutations contributing to myelomagenesis as well as transformation from myeloma to overt extramedullary disease such as sPCL.