Citations

Abstract Background: Whole genome/exome/RNA sequencing has revolutionized the ability to assess the genomic landscape of cancer and is increasingly being utilized for clinical decision-making. Initial clinical applications have been constrained by specimen quantity, analyte quality and the time from sample acquisition to results report. Methods: Patients with advanced cancers underwent surgical resection, excisional/core biopsies, or bone marrow biopsy. Samples were analyzed by whole genome or exome sequencing in addition to RNA sequencing, bioinformatics analysis, and therapeutic target prioritization by a multi-disciplinary Clinical Genomics Board. All prioritized targets were CLIA validated using Sanger sequencing, RT-qPCR, FISH, or IHC as appropriate. Treatment was delivered using off-label FDA approved drugs, clinical trials, or single patient INDs. Results: We have enrolled 40 patients for whom sequencing data is available on 33. The initial 6 patients were evaluated in a non-CLIA pilot phase and 27 in a CLIA-enabled phase. Tumor types in the CLIA-enabled phase with the highest enrollment were pancreatic cancer (n=8) and cholangiocarcinoma (n=8). We sought to quantify the targets identified along with clinical benefit, defining these as the “Actionable Index” (AI) (proportion of patients with ≥ 1 putative drug target) and “Utility Index” (UI) (proportion of patients who derive clinical benefit). Putative therapeutic targets were identified in 7/8 (AI=0.88) cholangiocarcinoma (CC) patients and in 5/8 (AI=0.63) pancreatic cancer (PC) patients. All 3 CC patients who received target directed treatment achieved a partial response (UI=0.38). In contrast, none of the 4 PC patients who received target directed therapy had treatment response (UI=0.0). Interestingly no actionable targets were identified in 1 CC and in 2 PCs. One CC with an identified target was unable to access the drug and subsequently died. A CC patient and a PC patient, each with identified targets, expired prior to the initiation of therapy. Conclusions: While whole genome/exome/RNA sequencing is providing unparalleled detail of tumor genomes, the application to the clinic must be carefully considered. Actionability of targets will eventually need to be defined in close relation to eventual clinical utility and appropriate refinements to disease-gene-drug databases implemented. Preliminary observations in pancreatic cancer and cholangiocarcinoma demonstrate disparity in correlation between utility indices and actionable indices. Application of these tools in larger cohorts and types of tumors will need to be conducted to ascertain more precise estimates. Additional measures that are organ-site agnostic but pertain to specific targets (e.g. BRAF) will also need to be developed in order to facilitate more judicious application of sequencing in the clinical setting. Citation Format: Jan B. Egan, Alan H. Bryce, Mia D. Champion, Winnie S. Liang, Rafael Fonseca, Ann E. McCullough, Michael T. Barrett, Katherine Hunt, Rachel M. Condjella, Robert R. McWilliams, Stephen D. Mastrian, Janine LoBello, Daniel Von Hoff, David W. Craig, A. Keith Stewart, John D. Carpten, Mitesh J. Borad. Indices of actionability and clinical utility in a CLIA-enabled study of whole genome/exome/RNA sequencing in 33 cancer patients: Actionable vs. utility. [abstract]. In: Proceedings of the 105th Annual Meeting of the American Association for Cancer Research; 2014 Apr 5-9; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2014;74(19 Suppl):Abstract nr 4694. doi:10.1158/1538-7445.AM2014-4694

SummaryWe constructed a multiple myeloma (MM)‐specific gene panel for targeted sequencing and investigated 72 untreated high‐risk (del17p) MM patients. Mutations were identified in 78% of the patients. While the majority of studied genes were mutated at similar frequency to published literature, the prevalence of TP53 mutation was increased (28%) and no mutations were found in FAM46C. This study provides a comprehensive insight into the mutational landscape of del17p high‐risk MM. Additionally, our work demonstrates the practical use of a customized sequencing panel, as an easy, cheap and fast approach to characterize the mutational profile of MM.

Abstract Accumulation of eosinophils in the lung with concomitant tissue damage are defining histopathologic features of human asthma. Through degranulation and the release of proinflammatory proteins such as major basic protein (MBP), eosinophils may perpetuate this inflammatory response. We investigated the extent of eosinophil degranulation in a murine model of allergic pulmonary inflammation. In this paradigm, the mice develop pulmonary eosinophilia, mucus hypersecretion, tissue damage, and airway edema and hyperreactivity. To evaluate the degree of eosinophil degranulation, we used a polyclonal antibody to murine MBP (mMBP) to perform dot blot analysis of bronchoalveolar lavage (BAL) cells and fluids, and immunohistochemical fluorescent analysis of lung tissue sections. After ovalbumin antigen challenge, we were unable to detect immunoreactive mMBP in the BAL fluids from either nonsensitized or sensitized mice. However, after lysis of the recoverable BAL cells, we were able to detect mMBP by immunoblot analysis, with the levels of immunoreactive mMBP directly related to the number of recoverable eosinophils. We also examined paraffin-embedded, lung tissue sections for patterns of mMBP deposition. Whereas lung sections from allergic mice revealed prominent peribronchial eosinophilia after antigen challenge, tissue sections from nonsensitized animals rarely displayed eosinophils. Despite the presence of numerous eosinophils, no immunohistologic evidence of extracellular mMBP could be found in antigen-challenged allergic mice. Furthermore, rechallenged allergic mice displayed a significant increase in the number of recruited pulmonary eosinophils but all immunoreactive mMBP was still intracellular. We conclude that the recruited pulmonary eosinophils have not substantially degranulated. These results suggest that, in this murine model of allergic inflammation, eosinophil degranulation and release of mMBP does not contribute to the observed pulmonary inflammation and airway hyperreactivity.

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.

Abstract Emerging evidence indicates that tumors can follow several evolutionary paths over a patient's disease course. With the use of serial genomic analysis of samples collected at different points during the disease course of 28 patients with multiple myeloma, we found that the genomes of standard-risk patients show few changes over time, whereas those of cytogenetically high-risk patients show significantly more changes over time. The results indicate the existence of 3 temporal tumor types, which can either be genetically stable, linearly evolving, or heterogeneous clonal mixtures with shifting predominant clones. A detailed analysis of one high-risk patient sampled at 7 time points over the entire disease course identified 2 competing subclones that alternate in a back and forth manner for dominance with therapy until one clone underwent a dramatic linear evolution. With the use of the Vk*MYC genetically engineered mouse model of myeloma we modeled this competition between subclones for predominance occurring spontaneously and with therapeutic selection.

Abstract Purpose: Glioblastoma is a devastating, incurable disease with few known prognostic factors. Here, we present the first genome-wide survival and validation study for glioblastoma. Experimental Design: Cox regressions for survival with 314,635 inherited autosomal single-nucleotide polymorphisms (SNP) among 315 San Francisco Adult Glioma Study patients for discovery and three independent validation data sets [87 Mayo Clinic, 232 glioma patients recruited from several medical centers in Southeastern United States (GliomaSE), and 115 The Cancer Genome Atlas patients] were used to identify SNPs associated with overall survival for Caucasian glioblastoma patients treated with the current standard of care, resection, radiation, and temozolomide (total n = 749). Tumor expression of the gene that contained the identified prognostic SNP was examined in three separate data sets (total n = 619). Genotype imputation was used to estimate hazard ratios (HR) for SNPs that had not been directly genotyped. Results: From the discovery and validation analyses, we identified a variant in single-stranded DNA-binding protein 2 (SSBP2) on 5q14.1 associated with overall survival in combined analyses (HR, 1.64; P = 1.3 × 10−6). Expression of SSBP2 in tumors from three independent data sets also was significantly related to patient survival (P = 5.3 × 10−4). Using genotype imputation, the SSBP2 SNP rs17296479 had the strongest statistically significant genome-wide association with poorer overall patient survival (HR, 1.79; 95% CI, 1.45-2.22; P = 1.0 × 10−7). Conclusion: The minor allele of SSBP2 SNP rs17296479 and the increased tumor expression of SSBP2 were statistically significantly associated with poorer overall survival among glioblastoma patients. With further confirmation, previously unrecognized inherited variations influencing survival may warrant inclusion in clinical trials to improve randomization. Unaccounted for genetic influence on survival could produce unwanted bias in such studies. Clin Cancer Res; 18(11); 3154–62. ©2012 AACR.