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. Eleven genes were evaluated by quantitative real-time reverse transcription-PCR (qPCR) on independent sets of matched samples to find genes that were consistently different between the tumor and metastatic samples. LIMD2 and PTPRC (CD45) showed a statistically significant difference in expression between tumor and metastatic samples (P < 0.0045), and an additional gene (LTB) had borderline significance. PTPRC and LTB were tested by immunohistochemistry in an independent set of paired samples, with both markers showing a difference in protein expression. All 20 metastases from 6 patients showed expression in both markers, with little or no expression in primary tumor. Some of these markers could provide an improved means to detect metastatic PTC cells during initial staging of a newly diagnosed carcinoma and/or to rule out recurrence. The functional role of these genes may also provide insight into mechanisms of thyroid cancer metastasis.

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.

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. During growth of human cancers in these mice, hprt-null murine stromal cells replace their human counterparts. RESULTS: Pancreatic and ovarian cancers explanted from these mice were grown in selection media to produce pure human cancer cell lines. We screened one cell line with a 3,131-drug panel and identified 77 U.S. Food and Drug Administration (FDA)-approved drugs with activity, and two novel drugs to which the cell line was uniquely sensitive. Xenografts of this carcinoma were selectively responsive to both drugs. CONCLUSION: Chemotherapy can be personalized using patient-specific cell lines derived in biochemically selectable mice.

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. Using Serial Analysis of Gene Expression (SAGE), 116,259 transcript tags (35,833 unique tags) were sequenced. From this expression analysis, we found 87 tags that were not expressed in normal brain. Further subtraction of normal endothelium, bone marrow, white blood cell and other normal tissue transcripts resulted in just three gene transcripts, ANAPC10, PLXDC1(TEM7), and CYP27B1, that are highly specific to GBM-ECs. Immunohistochemistry with an antibody for PLXDC1 showed protein expression in GBM microvasculature, but not in the normal brain endothelium tested. Our results suggest that this study succeeded in identifying GBM-EC specific genes. The entire gene expression profile for the GBM-ECs and other tissues used in this study are available at SAGE Genie (http://cgap.nci.nih.gov/SAGE). Functionally, the protein products of the three tags most specific to GBM-ECs have been implicated in processes critical to endothelial cell proliferation and differentiation, and are potential targets for anti-angiogenesis based therapy.