Craig, David W.

AbstractBackgroundLate‐onset Alzheimer's disease (AD) is heritable with 20 genes showing genome‐wide association in the International Genomics of Alzheimer's Project (IGAP). To identify the biology underlying the disease, we extended these genetic data in a pathway analysis.MethodsThe ALIGATOR and GSEA algorithms were used in the IGAP data to identify associated functional pathways and correlated gene expression networks in human brain.ResultsALIGATOR identified an excess of curated biological pathways showing enrichment of association. Enriched areas of biology included the immune response (P = 3.27 × 10−12 after multiple testing correction for pathways), regulation of endocytosis (P = 1.31 × 10−11), cholesterol transport (P = 2.96 × 10−9), and proteasome‐ubiquitin activity (P = 1.34 × 10−6). Correlated gene expression analysis identified four significant network modules, all related to the immune response (corrected P = .002–.05).ConclusionsThe immune response, regulation of endocytosis, cholesterol transport, and protein ubiquitination represent prime targets for AD therapeutics.

AbstractMatching molecularly targeted therapies with cancer subtype‐specific gene mutations is revolutionizing oncology care. However, for rare cancers this approach is problematic due to the often poor understanding of the disease's natural history and phenotypic heterogeneity, making treatment of these cancers a particularly unmet medical need in clinical oncology. Advanced Sézary syndrome (SS), an aggressive, exceedingly rare variant of cutaneous T‐cell lymphoma (CTCL) is a prototypical example of a rare cancer. Through whole genome and RNA sequencing (RNA‐seq) of a SS patient's tumor we discovered a highly expressed gene fusion between CTLA4 (cytotoxic T lymphocyte antigen 4) and CD28 (cluster of differentiation 28), predicting a novel stimulatory molecule on the surface of tumor T cells. Treatment with the CTLA4 inhibitor ipilimumab resulted in a rapid clinical response. Our findings suggest a novel driver mechanism for SS, and cancer in general, and exemplify an emerging model of cancer treatment using exploratory genomic analysis to identify a personally targeted treatment option when conventional therapies are exhausted.

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.

The role of the Alzheimer's Disease Neuroimaging Initiative Genetics Core is to facilitate the investigation of genetic influences on disease onset and trajectory as reflected in structural, functional, and molecular imaging changes; fluid biomarkers; and cognitive status. Major goals include (1) blood sample processing, genotyping, and dissemination, (2) genome‐wide association studies (GWAS) of longitudinal phenotypic data, and (3) providing a central resource, point of contact and planning group for genetics within the Alzheimer's Disease Neuroimaging Initiative. Genome‐wide array data have been publicly released and updated, and several neuroimaging GWAS have recently been reported examining baseline magnetic resonance imaging measures as quantitative phenotypes. Other preliminary investigations include copy number variation in mild cognitive impairment and Alzheimer's disease and GWAS of baseline cerebrospinal fluid biomarkers and longitudinal changes on magnetic resonance imaging. Blood collection for RNA studies is a new direction. Genetic studies of longitudinal phenotypes hold promise for elucidating disease mechanisms and risk, development of therapeutic strategies, and refining selection criteria for clinical trials.

A recently identified variant within the fat mass and obesity-associated ( FTO ) gene is carried by 46% of Western Europeans and is associated with an ~1.2 kg higher weight, on average, in adults and an ~1 cm greater waist circumference. With >1 billion overweight and 300 million obese persons worldwide, it is crucial to understand the implications of carrying this very common allele for the health of our aging population. FTO is highly expressed in the brain and elevated body mass index (BMI) is associated with brain atrophy, but it is unknown how the obesity-associated risk allele affects human brain structure. We therefore generated 3D maps of regional brain volume differences in 206 healthy elderly subjects scanned with MRI and genotyped as part of the Alzheimer's Disease Neuroimaging Initiative. We found a pattern of systematic brain volume deficits in carriers of the obesity-associated risk allele versus noncarriers. Relative to structure volumes in the mean template, FTO risk allele carriers versus noncarriers had an average brain volume difference of ~8% in the frontal lobes and 12% in the occipital lobes—these regions also showed significant volume deficits in subjects with higher BMI. These brain differences were not attributable to differences in cholesterol levels, hypertension, or the volume of white matter hyperintensities; which were not detectably higher in FTO risk allele carriers versus noncarriers. These brain maps reveal that a commonly carried susceptibility allele for obesity is associated with structural brain atrophy, with implications for the health of the elderly.

Human memory is a polygenic trait. We performed a genome-wide screen to identify memory-related gene variants. A genomic locus encoding the brain protein KIBRA was significantly associated with memory performance in three independent, cognitively normal cohorts from Switzerland and the United States. Gene expression studies showed that KIBRA was expressed in memory-related brain structures. Functional magnetic resonance imaging detected KIBRA allele–dependent differences in hippocampal activations during memory retrieval. Evidence from these experiments suggests a role for KIBRA in human memory.