Application of cell line based genomic predictors to predict response to targeted therapies in breast cancer

Cancer cell lines can be treated with a drug and the molecular comparison of responders and non-responders may yield potential predictors that could be tested in the clinic. It is a bioinformatics challenge to apply the cell line-derived multivariable response predictors to patients who respond to therapy. Using the gene expression data from 23 breast cancer cell lines, I developed three predictors of dasatinib sensitivity by selecting differentially expressed genes and applying different classification algorithms. The performance of these predictors on independent cell lines with known dasatinib response was tested. The predictor based on weighted voting method has the best overall performance. It correctly predicted dasatinib sensitivity in 11 out of 12 (92%) breast and 17 out of 23 (74%) lung cancer cell lines. These predictors were then applied to the gene expression data from 133 breast cancer patients in an attempt to predict how the patients might respond to dasatinib therapy. Two predictors identified 13 patients in common to be dasatinib sensitive. Sixty two percent of these cases are triple negative (ER-negative, HER2-negative and PR-negative) and 76% are double negative. The result is consistent with the findings from other studies, which identified a target population for dasatinib treatment to be triple negative or basal breast cancer subtype. In conclusion, we think that the cell line-derived dasatinib classifiers can be applied to the human patients. ^

FANCM AND FAAP24 MAINTAIN GENOMIC STABILITY THROUGH COOPERATIVE AND UNIQUE FUNCTIONS

Fanconi anemia (FA) is a rare recessive genetic disease with an array of clinical manifestations including multiple congenital abnormalities, progressive bone marrow failure and profound cancer susceptibility. A hallmark of cells derived from FA patients is hypersensitivity to DNA interstrand crosslinking agents such as mitomycin C (MMC) and cisplatin, suggesting that FA- and FA-associated proteins play important roles in protecting cells from DNA interstrand crosslink (ICL) damage. Two genes involved in the FA pathway, FANCM and FAAP24, are of particular interest because they contain DNA interacting domains. However, there are no definitive patient mutations for these two genes, and the resulting lack of human genetic model system renders their functional studies difficult. In this study, I established isogenic human FANCM- and FAAP24-null mutants through homologous replacement-mediated gene targeting in HCT-116 cells, and systematically investigated the functions of FANCM and FAAP24 inchromosome stability, FA pathway activation, DNA damage checkpoint signaling, and ICL repair. I found that the FANCM-/-/FAAP24-/- double mutant was much more sensitive to DNA crosslinking agents than FANCM-/- and FAAP24-/- single mutants, suggesting that FANCM and FAAP24 possess epistatic as well as unique functions in response to ICL damage. I demonstrated that FANCM and FAAP24 coordinately support the activation of FA pathway by promoting chromatin localization of FA core complex and FANCD2 monoubiqutination. They also cooperatively function to suppress sister chromatid exchange and radial chromosome formation, likely by limiting crossovers in recombination repair. In addition, I defined novel non-overlapping functions of FANCM and FAAP24 in response to ICL damage. FAAP24 plays a major role in activating ICL-induced ATR-dependent checkpoint, which is independent of its interaction with FANCM. On the other hand, FANCM promotes recombination-independent ICL repair independently of FAAP24. Mechanistically, FANCM facilitates recruitment of nucleotide excision repair machinery and lesion bypass factors to ICL damage sites through its translocase activity. Collectively, my studies provide mechanistic insights into how genome integrity is both coordinately and independently protected by FANCM and FAAP24.

MOLECULAR AND GENOMIC BASED INSIGHTS INTO THE EVOLUTION OF ENTEROCOCCUS FAECIUM FROM COMMENSAL TO HOSPITAL-ADAPTED PATHOGEN

The basis for the recent transition of Enterococcus faecium from a primarily commensal organism to one of the leading causes of hospital-acquired infections in the United States is not yet understood. To address this, the first part of my project assessed isolates from early outbreaks in the USA and South America using sequence analysis, colony hybridizations, and minimal inhibitory concentrations (MICs) which showed clinical isolates possess virulence and antibiotic resistance determinants that are less abundant or lacking in community isolates. I also revealed that the level of ampicillin resistance increased over time in clinical strains. By sequencing the pbp5 gene, I demonstrated an ~5% difference in the pbp5 gene between strains with MICs <4ug/ml and those with MICs >4µg/ml, but no specific sequence changes correlated with increases in MICs within the latter group. A 3-10% nucleotide difference was also seen in three other genes analyzed, which suggested the existence of two distinct subpopulations of E. faecium. This led to the second part of my project analyzing concatenated core gene sequences, SNPs, the 16S rRNA, and phylogenetics of 21 E. faecium genomes confirming two distinct clades; a community-associated (CA) clade and hospital-associated (HA) clade. Molecular clock calculations indicate that these two clades likely diverged ~ 300,000 to > 1 million years ago, long before the modern antibiotic era. Genomic analysis also showed that, in addition to core genomic differences, HA E. faecium harbor specific accessory genetic elements that may confer selection advantages over CA E. faecium. The third part of my project discovered 6 E. faecium genes with the newly identified “WxL” domain. My analyses, using RT-PCR, western blots, patient sera, whole-cell ELISA, and immunogold electron microscopy, indicated that E. faecium WxL genes exist in operons, encode bacterial cell surface localized proteins, that WxL proteins are antigenic in humans, and are more exposed on the surface of clinical isolates versus community isolates (even though they are ubiquitous in both clades). ELISAs and BIAcore analyses also showed that proteins encoded by these operons bind several different host extracellular matrix proteins, as well as to each other, suggesting a novel cell-surface complex. In summary, my studies provide new insights into the evolution of E. faecium by showing that there are two distantly related clades; one being more successful in the hospital setting. My studies also identified operons encoding WxL proteins whose characteristics could also contribute to colonization and virulence within this species.

A Genomic Approach to Identify The Notch Pathway as a Putative Tumor Suppressor in Endometrial Cancer

Endometrial cancer is the most common gynecological malignancy and the fourth most frequently diagnosed cancer among women. The molecular changes that distinguish normal endometrium from endometrial carcinoma are not thoroughly understood. Identification of these changes could potentially aid in identifying at-risk women who are especially prone to develop endometrial cancer, such as obese women and women with Lynch Syndrome. A microarray analysis was performed using normal endometrium from thin and obese women and cancerous endometrium from obese women. We validated the differential expression of ten genes whose expression was significantly up-regulated or down-regulated using qRT-PCR. All of the genes had distinct expression levels depending on the endometrial carcinoma histotype. As a result, they could serve as molecular markers to distinguish between normal endometrium and endometrial cancer, as well as between low grade endometrial carcinomas and high grade endometrial carcinomas. Two of the ten genes validated, HEYL and HES1, are down-stream targets of the Notch signaling pathway. HEYL and HES1 were identified by microarray and qRT-PCR to have a significant decrease in expression in endometrial carcinomas compared to normal endometrium. We further analyzed the differential expression of other components of the Notch signaling pathway, Notch4 and Jagged1. They were also identified by qRT-PCR to be significantly down-regulated in endometrial carcinomas compared to normal endometrium. Therefore, we believe the Notch signaling pathway to act as a tumor suppressor in endometrial carcinomas.

Species list of the flora on Banks Island

While engaged in palaeo-botanical and plantgeographical field work on Banks Island, N. W. T. during the summer of 1973, 225 new plants could be recorded for the vicinities of Sachs Harbour, Shoran Lake and Johnson Point; 21 of them were new for Banks Island, 7 for the western Canadian archipelago.

Multi-temporal mapping of seagrass cover, species and biomass of the Eastern Banks, Moreton Bay, Australia, with links to shapefiles

The spatial and temporal dynamics of seagrasses have been studied from the leaf to patch (100 m**2) scales. However, landscape scale (> 100 km**2) seagrass population dynamics are unresolved in seagrass ecology. Previous remote sensing approaches have lacked the temporal or spatial resolution, or ecologically appropriate mapping, to fully address this issue. This paper presents a robust, semi-automated object-based image analysis approach for mapping dominant seagrass species, percentage cover and above ground biomass using a time series of field data and coincident high spatial resolution satellite imagery. The study area was a 142 km**2 shallow, clear water seagrass habitat (the Eastern Banks, Moreton Bay, Australia). Nine data sets acquired between 2004 and 2013 were used to create seagrass species and percentage cover maps through the integration of seagrass photo transect field data, and atmospherically and geometrically corrected high spatial resolution satellite image data (WorldView-2, IKONOS and Quickbird-2) using an object based image analysis approach. Biomass maps were derived using empirical models trained with in-situ above ground biomass data per seagrass species. Maps and summary plots identified inter- and intra-annual variation of seagrass species composition, percentage cover level and above ground biomass. The methods provide a rigorous approach for field and image data collection and pre-processing, a semi-automated approach to extract seagrass species and cover maps and assess accuracy, and the subsequent empirical modelling of seagrass biomass. The resultant maps provide a fundamental data set for understanding landscape scale seagrass dynamics in a shallow water environment. Our findings provide proof of concept for the use of time-series analysis of remotely sensed seagrass products for use in seagrass ecology and management.