Personalized chemotherapy profiling using cancer cell lines from selectable mice.

Purpose: High-throughput chemosensitivity testing of low-passage cancer cell lines can be used to prioritize agents for personalized chemotherapy. However, generating cell lines from primary cancers is difficult because contaminating stromal cells overgrow the malignant cells.

Experimental Design: We produced a series of hypoxanthine phosphoribosyl transferase (hprt)-null immunodeficient mice.

Molecular profiling of matched samples identifies biomarkers of papillary thyroid carcinoma lymph node metastasis.

Biomarkers of papillary thyroid carcinoma (PTC) metastasis can accurately identify metastatic cells and aggressive tumor behavior. To find new markers, serial analysis of gene expression (SAGE) was done on three samples from the same patient: normal thyroid tissue, primary PTC, and a PTC lymph node metastasis. This genomewide expression analysis identified 31 genes expressed in lymph node metastasis, but not in the primary tumor.

Target discovery and validation in pancreatic cancer.

Pancreatic cancer is a lethal disease and rational strategies for early detection and targeted therapies are urgently required to alleviate the dismal prognosis of this neoplasm. The use of global RNA and protein expression-profiling technologies, such as DNA microarrays, serial analysis of gene expression, and mass spectrometric analysis of proteins, have led to identification of cellular targets with considerable potential for clinical application and patient care. These studies underscore the importance of pursuing large-scale profiling of human cancers not only for furthering our understanding of the pathogenesis of these malignancies but also for developing strategies to improve patient outcomes.

PLXDC1 (TEM7) is identified in a genome-wide expression screen of glioblastoma endothelium.

Glioblastomas are a highly aggressive brain tumor, with one of the highest rates of new blood vessel formation. In this study we used a combined experimental and bioinformatics strategy to determine which genes were highly expressed and specific for glioblastoma endothelial cells (GBM-ECs), compared to gene expression in normal tissue and endothelium. Starting from fresh glioblastomas, several rounds of negative and positive selection were used to isolate GBM-ECs and extract total RNA.