Integrating sequence information in microarray data analysis by free energy modeling

Microarray technology is a high-throughput method for genotyping and gene expression profiling. Limited sensitivity and specificity are one of the essential problems for this technology. Most of existing methods of microarray data analysis have an apparent limitation for they merely deal with the numerical part of microarray data and have made little use of gene sequence information. Because it's the gene sequences that precisely define the physical objects being measured by a microarray, it is natural to make the gene sequences an essential part of the data analysis. This dissertation focused on the development of free energy models to integrate sequence information in microarray data analysis. The models were used to characterize the mechanism of hybridization on microarrays and enhance sensitivity and specificity of microarray measurements. ^ Cross-hybridization is a major obstacle factor for the sensitivity and specificity of microarray measurements. In this dissertation, we evaluated the scope of cross-hybridization problem on short-oligo microarrays. The results showed that cross hybridization on arrays is mostly caused by oligo fragments with a run of 10 to 16 nucleotides complementary to the probes. Furthermore, a free-energy based model was proposed to quantify the amount of cross-hybridization signal on each probe. This model treats cross-hybridization as an integral effect of the interactions between a probe and various off-target oligo fragments. Using public spike-in datasets, the model showed high accuracy in predicting the cross-hybridization signals on those probes whose intended targets are absent in the sample. ^ Several prospective models were proposed to improve Positional Dependent Nearest-Neighbor (PDNN) model for better quantification of gene expression and cross-hybridization. ^ The problem addressed in this dissertation is fundamental to the microarray technology. We expect that this study will help us to understand the detailed mechanism that determines sensitivity and specificity on the microarrays. Consequently, this research will have a wide impact on how microarrays are designed and how the data are interpreted. ^

Roles of insulin-like growth factor binding protein-3 in gastrointestinal stromal tumors

Imatinib mesylate, a selective inhibitor of KIT, PDGFR, and Abl kinases, has shown significant success as a therapy for patients with advanced gastrointestinal stromal tumors (GISTs). However, the underlying mechanisms of imatinib-induced cytotoxicity are not well understood. Using gene expression profiling and real-time PCR for target validation, we identified insulin-like growth factor binding protein-3 (IGFBP3) to be to be up-regulated after imatinib treatment in imatinib-sensitive GISTs. IGFBP3 is a multifunctional protein that regulates cell proliferation and survival and mediates the effects of a variety of anti-cancer agents through IGF-dependent and IGF-independent mechanisms. Therefore, we hypothesized that IGFBP3 mediates GIST cell response to imatinib. To test this hypothesis, we manipulated IGFBP3 protein levels in two KIT mutant, imatinib-sensitive GIST cell lines and assessed the resultant changes in cell viability, survival, and imatinib sensitivity. In GIST882 cells, endogenous IGFBP3 was required for cell viability. However, inhibiting imatinib-induced IGFBP3 up-regulation by RNA interference or neutralization resulted in reduced drug sensitivity, suggesting that IGFBP3 sensitizes GIST882 cells to imatinib. GIST-T1 cells, on the other hand, had no detectable levels of endogenous IGFBP3, nor did imatinib induce IGFBP3 up-regulation, in contrast to our previous findings. IGFBP3 overexpression in GIST-T1 cells reduced viability but did not induce cell death; rather, the cells became polyploid through a mechanism that may involve attenuated Cdc20 expression and securin degradation. Moreover, IGFBP3 overexpression resulted in a loss of KIT activation and decreased levels of mature KIT. Consistent with this, GIST-T1 cells overexpressing IGFBP3 were less sensitive to imatinib. Furthermore, as neither GIST882 cells nor GIST-T1 cells expressed detectable levels of IGF-1R, IGFBP3 is likely not exerting its effects by modulating IGF signaling through IGF-1R or IR/IGF-1R hybrid receptors in these cell lines. Collectively, these findings demonstrate that IGFBP3 has cell-dependent effects and would, therefore, not be an ideal marker for identifying imatinib response in GISTs. Nevertheless, our results provide preliminary evidence that IGFBP3 may have some therapeutic benefits in GISTs. ^

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.