Clarence Wang

We have analyzed a systematic flaw in the current system of gene identification: the oligo(dT) primer widely used for cDNA synthesis generates a high frequency of truncated cDNAs through internal poly(A) priming. Such truncated cDNAs may contribute to 12% of the expressed sequence tags in the current dbEST database. By using a synthetic transcript and real mRNA templates as models, we characterized the patterns of internal poly(A) priming by oligo(dT) primer. We further demonstrated that the internal poly(A) priming can be effectively diminished by replacing the oligo(dT) primer with a set of anchored oligo(dT) primers for reverse transcription. Our study indicates that cDNAs designed for genomewide gene identification should be synthesized by use of the anchored oligo(dT) primers, rather than the oligo(dT) primers, to diminish the generation of truncated cDNAs caused by internal poly(A) priming.

Human umbilical vein endothelial cells (HUVEC) and human microvascular endothelial cells (HMVEC) have been the standards for cell-based assays in the field of angiogenesis research and in antiangiogenic drug discovery. These normal mature endothelial cells may not be most representative of human tumor endothelial cells. Human AC133+/CD34+ bone marrow progenitor cells were established in cell culture media containing vascular endothelial growth factor, basic fibroblast growth factor (bFGF), and heparin to drive differentiation toward the endothelial phenotype. The resulting cells designated endothelial precursor cells (EPC) have many of the same functional properties as mature endothelial cells represented by HUVEC and HMVEC. By SAGE analysis, the genes expressed by EPC are more similar to the genes expressed by endothelial cells isolated from fresh surgical specimens of human tumors than are the genes expressed by HUVEC and HMVEC. Analysis of several cell surface markers by flow cytometry showed that EPC, HUVEC, and HMVEC have similar expression of P1H12, vascular endothelial growth factor 2, and endoglin but that EPC have much lower expression of ICAM1, ICAM2, VCAM1, and thrombomodulin than do HUVEC and HMVEC. The EPC generated can form tubes/networks on Matrigel, migrate through porous membranes, and invade through thin layers of Matrigel similarly to HUVEC and HMVEC. However, in a coculture assay using human SKOV3 ovarian cancer cell clusters in collagen as a stimulus for invasion through Matrigel, EPC were able to invade into the malignant cell cluster, whereas HMVEC were not able to invade the malignant cell cluster. In vivo, a Matrigel plug assay where human EPC were suspended in the Matrigel allowed tube/network formation by human EPC to be carried out in a murine host. EPC may be a better model of human tumor endothelial cells than HUVEC and HMVEC and, thus, may provide an improved cell-based model for second generation antineoplastic antiangiogenic drug discovery.

To systematically identify genes related to invasion a three-dimensional multicellular matrix invasion assay was used to classify human tumor cell lines as stromal invasion positive or stromal invasion negative. Cells from two of the primary cell types of the stromal compartment [endothelial cells (HMVEC) and myofibroblasts (HDF)] were assayed for invasion into tumor cell clusters (breast carcinoma, ovarian carcinoma, prostate carcinoma, lung carcinoma, and melanoma). Four tumor cell lines (MDA-MB231, SKOV-3, A375, and MEL624) scored invasion positive, and four tumor cell lines (LNCaP, DU145, PC3, and A549) scored invasion negative. Serial analysis of gene expression (SAGE) libraries generated from the tumor cell lines were analyzed by GeneSpring Hierarchical clustering, t test, and chi(2) test. Clusters emerged that reflected the behavior in the cell culture assay. Of the 47 most highly differentially expressed genes, 30 were selected for confirmation by real-time PCR, and 9 had good correlation with normalized serial analysis of gene expression tag counts. The strongest correlations were for bone marrow stromal antigen 2, stathmin-like 3, tumor necrosis factor receptor superfamily member 5, and hepatocyte growth factor tyrosine kinase substrate. In situ hybridization of metastatic and nonmetastatic ovarian cancer demonstrated selective expression of bone marrow stromal antigen 2 and tumor necrosis factor receptor superfamily member 5 in the metastatic disease. This combination approach appears to be a powerful tool for identifying genes that may be useful as diagnostic markers and/or as therapeutic targets for invasive solid tumors.

BACKGROUND: The identification of a target-indication pair is regarded as the first step in a traditional drug discovery and development process. Significant investment and attrition occur during discovery and development before a molecule is shown to be safe and efficacious for the selected indication and becomes an approved drug. Many drug targets are functionally pleiotropic and might be good targets for multiple indications. Methodologies that leverage years of scientific contributions on drug targets to allow systematic evaluation of other indication opportunities are critical for both patients and drug discovery and development scientists. METHODS: We introduced a network-based approach to systematically screen and prioritize disease indications for drug targets. The approach fundamentally integrates disease genomics data and protein interaction network. Further, the methodology allows for indication identification by leveraging state-of-art network algorithms to generate and compare the target and disease subnetworks. RESULTS: We first evaluated the performance of our method on recovering FDA approved indications for 15 randomly selected drug targets. The results showed superior performance when compared with other state-of-art approaches. Using this approach, we predicted novel indications supported by literature evidence for several highly pursued drug targets such as IL12/IL23 combination. CONCLUSIONS: Our results demonstrated a potential global approach for indication expansion strategies. The proposed methodology enables rapid and systematic evaluation of both individual and combined drug targets for novel indications. Additionally, this approach provides novel insights on expanding the role of genes and pathways for developing therapeutic intervention strategies.