Thesis (Ph.D.)--University of California, San Francisco, 2008. / Source: Dissertation Abstracts International, Volume: 69-09, Section: B, page: 5135. Adviser: Bruce R. Conklin.

<p> Somatic copy number alterations (SCNAs) are a class of alterations that lead to deviations from diploidy in developing and established tumors. A feature that distinguishes SCNAs from other alterations is their genomic footprint. The large genomic footprint of SCNAs in a typical cancer's genome presents both a challenge and an opportunity to find targetable vulnerabilities in cancer. Because a single event affects many genes, it is often challenging to identify the tumorigenic targets of SCNAs. Conversely, events that affect multiple genes may provide specific vulnerabilities through "bystander" genes, in addition to vulnerabilities directly associated with the targets. </p><p> We approached the goal of understanding how the structure of SCNAs may lead to dependency in two ways. To improve our understanding of how SCNAs promote tumor progression we analyzed the SCNAs in 4934 primary tumors in 11 common cancers collected by the Cancer Genome Atlas (TCGA). The scale of this dataset provided insights into the structure and patterns of SCNA, including purity and ploidy rates across disease, mechanistic forces shaping patterns of SCNA, regions undergoing significantly recurrent SCNAs, and correlations between SCNAs in regions implicated in cancer formation. </p><p> In a complementary approach, we integrating SCNA data and pooled RNAi screening data involving 11,000 genes across 86 cell lines to find non-driver genes whose partial loss led to increased sensitivity to RNAi suppression. We identified a new set of cancer specific vulnerabilities predicted by loss of non-driver genes, with the most significant gene being PSMC2, an obligate member of the 26S proteasome. Biochemically, we found that PSMC2 is in excess of cellular requirement in diploid cells, but becomes the stoichiometric limiting factor in proteasome formation after partial loss of this gene. </p><p> In summary, my work improved our understanding of the structure and patterns of SCNA, both informing how cancers develop and predicting novel cancer vulnerabilities. Our characterization of the SCNAs present across 5000 tumors uncovered novel structure in SCNAs and significant regions likely to contain driver genes. Through integrating SCNA data with the results of a functional genetic screen, we also uncovered a new set of vulnerabilities caused by unintended loss of non-driver genes.</p>

<p> Tumorigenesis of relatively late onset occurring in patients with no family history of cancer syndromes is assumed to be driven by somatic mutations. The advent of high-throughput sequencing allows unbiased probing for genomic aberrations on an unprecedented scale. Somatic mutations, insertions and deletions, and copy number variations are able to be identified by parallel sequencing of tumor DNA and normal DNA from an individual patient. Somatic aberrations identified are classified as either passenger mutations that do not contribute to tumorigenesis or pathogenic driver mutations. Driver mutations are able to be identified due to their recurrence across multiple affected patients at a frequency greater than would be expected by chance.</p><p> Tumors occurring in the same tissue and from the same cell type often display diverse phenotypes with distinct mutational signatures. Therefore I applied high-throughput sequencing to probe for somatic mutations in two very specific endocrine tumor types - parathyroid-producing adenomas and insulin-producing adenomas (insulinomas). Prior to this study, neither tumor type had been probed for somatic mutations in a large-scale, unbiased manner. Though a limited number of mutated genes had been identified to play a role in familial and sporadic tumorigenesis in these tumor types, the majority of pathogenesis remained unexplained.</p><p> In order to maximize detection of variation in coding regions of the genome, an exome capture array was applied to the DNA prior to sequencing. In both tumor types, exome sequencing was applied to a small number of tumor-normal tissue pairs. Additional targeted sequencing of candidate driver mutations was then performed using Sanger sequencing on larger validation cohorts of tumors.</p><p> Exome sequencing revealed few somatic, protein-altering mutations in each tumor type (average &lt;4 per tumor), therefore any recurrent variation was highly probable to be tumorigenic. Exome sequencing of the parathyroid adenomas revealed that four of eight tumors harbored a frameshift deletion or nonsense mutation in <i>MEN1</i>, which was always accompanied by loss of heterozygosity (LOH) of the remaining wild-type allele. No other mutated genes were shared among the eight tumors. One tumor harbored a Y641N missense mutation of the histone methyltransferase <i>EZH2</i> gene, previously linked to myeloid and lymphoid malignancy formation. Targeted sequencing in an additional 185 parathyroid adenomas revealed somatic <i>MEN1</i> mutations in a large number of tumors (35%). Furthermore, this targeted sequencing identified an additional parathyroid adenoma that contained the identical, somatic <i>EZH2</i> mutation that was found by exome sequencing. This confirms the frequent role of LOH of chromosome 11 and <i>MEN1</i> gene alterations in sporadic parathyroid adenomas and implicates a previously unassociated methyltransferase gene, <i>EZH2</i>, in endocrine tumorigenesis. </p><p> Exome sequencing identified an identical somatic, heterozygous mutation in Yin Yang 1 transcription factor (<i>YY1</i>) in two of seven insulinomas. Targeted sequencing of an additional 36 insulinomas revealed twelve more insulinomas that harbored this identical T372R missense mutation in <i>YY1.</i> This mutation occurs at a highly-conserved residue in a highly-conserved zinc finger DNA-binding domain. ChIP-Seq demonstrated that this mutation changes the DNA motif bound by YY1. This altered binding likely drives pathogenesis due to aberrant regulation of genes not regulated by YY1^WT. With the goal of identifying differentially-expressed genes in <i>YY1^T372R</i> tumors, I performed gene expression analysis on eleven tumors; six that were <i>YY1^WT</i> and five that were <i>YY1^T372R.</i> This demonstrated that YY1^T372R imparts a unique expression signature. Interestingly, several differentially-expressed genes were involved in key pathways regulating insulin secretion, including <i>ADCY1</i> (an adenylyl cyclase) and <i>CACNA2D2</i> (a Ca²⁺ channel pore-forming subunit), both of which were upregulated in <i>YY1^T372R</i>-tumors. Importantly, <i>in vitro</i> studies using the INS-1 rat insulinoma cell line demonstrated that upregulation of each of gene is sufficient to markedly increase insulin secretion. Furthermore, both genes harbored specific YY1^T372R binding sites that may account for their significantly altered expression.</p><p> Both studies identify novel driver mutations that shed light on the mechanisms of endocrine tumorigenesis. Furthermore, my findings reinforce the notion that common somatic mutations within the exome account for the majority of instances of sporadic tumorigenesis.</p>

<p> In the past five years, Single Molecule Real Time (SMRT) sequencing technology has been found to be a reliable indicator of certain epigenetic modifications in bacterial genomes. The genome of the model organism <i>Saccharomyces cerevisiae</i> has long been thought to be free of DNA level modification, but literature surrounding this subject is conflicting. Additionally, the mitochondria of <i>S. cerevisiae</i> control the transition between three distinct chronological life phases &ndash; exponential, postdiauxic, and stationary - as defined by their main metabolic processes. This study attempted to identify base modifications to mtDNA using PacBio sequencing while additionally establishing gene expression changes as a result of altered mitochondrial metabolic capabilities. PacBio results showed intriguing results but statistical analysis proved experimentation with improved protocols were necessary. Multiple genes with unknown or uncharacterized function were also shown to have significant differential expression between metabolic life phases.</p>