Faculty Bibliography

Pancreatic cancer is a deadly disease characterized by late diagnosis and resistance to therapy. Much progress has been made in defining gene defects in pancreatic cancer, but a full accounting of its molecular pathogenesis remains to be provided. Here, we show that expression of the ataxia-telangiectasia group D complementing gene (ATDC), also called TRIM29, is elevated in most invasive pancreatic cancers and pancreatic cancer precursor lesions. ATDC promoted cancer cell proliferation in vitro and enhanced tumor growth and metastasis in vivo. ATDC expression correlated with elevated beta-catenin levels in pancreatic cancer, and beta-catenin function was required for ATDC's oncogenic effects. ATDC was found to stabilize beta-catenin via ATDC-induced effects on the Disheveled-2 protein, a negative regulator of glycogen synthase kinase 3beta in the Wnt/beta-catenin signaling pathway.

Pancreatic cancer is a formidable disease and early detection biomarkers are needed to make inroads into improving the outcomes in these patients. In this work, lectin antibody microarrays were utilized to detect unique glycosylation patterns of proteins from serum. Antibodies to four potential glycoprotein markers that were found in previous studies were printed on nitrocellulose coated glass slides and these microarrays were hybridized against patient serum to extract the target glycoproteins. Lectins were then used to detect different glycan structural units on the captured glycoproteins in a sandwich assay format. The biotinylated lectins used to assess differential glycosylation patterns were Aleuria aurentia lectin (AAL), Sambucus nigra bark lectin (SNA), Maackia amurensis lectin II (MAL), Lens culinaris agglutinin (LCA), and Concanavalin A (ConA). Captured glycoproteins were evaluated on the microarray in situ by on-plate digestion and direct analysis using MALDI QIT-TOF mass spectroscopy. Analysis was performed using serum from 89 normal controls, 35 chronic pancreatitis samples, 37 diabetic samples and 22 pancreatic cancer samples. We found that this method had excellent reproducibility as measured by the signal deviation of control blocks as on-slide standard and 41 pairs of pure technical replicates. It was possible to discriminate cancer from the other disease groups and normal samples with high sensitivity and specificity where the response of Alpha-1-beta glycoprotein to lectin SNA increased by 69% in the cancer sample compared to the other noncancer groups (95% confidence interval 53-86%). These data suggest that differential glycosylation patterns detected on high-throughput lectin glyco-antibody microarrays are a promising biomarker approach for the early detection of pancreatic cancer.

Emerging evidence suggests that malignant tumors are composed of a small subset of distinct cancer cells, termed "cancer stem cells" (typically less than 5% of total cancer cells based on cell surface marker expression), which have great proliferative potential, as well as more differentiated cancer cells, which have very limited proliferative potential. Data have been provided to support the existence of cancer stem cells in several different types of cancer, including human blood, brain, prostate, ovarian, melanoma, colon, and breast cancers. We have recently reported the identification of a subpopulation of pancreatic cancer cells that express the cell surface markers CD44+CD24+ESA+ (0.2-0.8% of all human pancreatic cancer cells) that function as pancreatic cancer stem cells. The CD44+CD24+ESA+ pancreatic cancer cells are highly tumorigenic and possess the stem cell-like properties of self-renewal and the ability to produce differentiated progeny. Pancreatic cancer stem cells also demonstrate upregulation of molecules important in developmental signaling pathways, including sonic hedgehog and the polycomb gene family member Bmi-1. Of clinical importance, cancer stem cells in several tumor types have shown resistance to standard therapies and may play a role in treatment failure or disease recurrence. Identification of pancreatic cancer stem cells and further elucidation of the signaling pathways that regulate their growth and survival may provide novel therapeutic approaches to treat pancreatic cancer, which is notoriously resistant to standard chemotherapy and radiation.

Disease-related changes in serum proteins are reasonable targets for early detection particularly due to the noninvasive approach in obtaining samples. Glycoproteins specifically have been implicated in a variety of disease types ranging from immune diseases to cancers. High-throughput screening methods that can assess glycosylation states of all serum proteins in normal and diseased sample groups can facilitate early detection as well as shed light on disease progression mechanisms. Outlined here is a combination of liquid separation, protein microarray, and mass spectrometry approach to highlight candidate proteins involved in diseases through glycosylation mechanisms.

Protein glycosylation is the most versatile and common protein modification and plays important roles in various biological processes and disease progression. In this review, the development of microarray technology for protein glycosylation analysis is described. Three types are discussed: carbohydrate, lectin and natural glycoprotein microarrays. The advantages of microarray technology to study protein glycosylation are high-volume throughput coupled with a highly miniaturized platform. These techniques show great promise for detecting interactions that involve carbohydrates and as a screening tool to detect glycan patterns important for the early diagnosis of disease.

Pancreatic cancer is a highly lethal disease that is usually diagnosed at a late stage for which there are few effective therapies. Emerging evidence has suggested that malignant tumors are quite heterogeneous and that they are composed of a small subset of distinct cancer cells (usually defined by cell surface marker expression) that are responsible for tumor initiation and propagation, termed cancer stem cells. These cells are termed cancer stem cells because, like normal stem cells, they possess the ability to self-renew and make differentiated progeny. Recent studies of human pancreatic cancers have shown a population of pancreatic cancer stem cells that have aberrantly activated developmental signaling pathways, are resistant to standard chemotherapy and radiation, and have up-regulated signaling cascades that are integral for tumor metastasis. An improved understanding of the biological behavior of these cells may lead to more effective therapies to treat pancreatic cancer. In this review, approaches to develop and test therapeutics targeting pancreatic cancer stem cells are discussed.

Cystic tumors of the pancreas are an increasingly recognized clinical entity, and the management of these lesions continues to evolve. The Society for Surgery of the Alimentary Tract, American Gastroenterological Association, and American Society for Gastrointestinal Endoscopy recently held a "state-of-the-art" conference to discuss the current recommendations for diagnostic evaluation and clinical management of pancreatic cystic tumors. In this article, a brief review of the conference and important teaching points presented at the conference are highlighted.

The current study analyzed reverse phase protein arrays (RPPA) as a means to experimentally validate biomarkers in blood samples. One microliter samples of sera (n = 71), and plasma (n = 78) were serially diluted and printed on NC-coated slides. CA19-9 levels from RPPA results were compared with identical patient samples as measured by ELISA. There was a strong correlation between RPPA and ELISA (r = 0.87) as determined by scatter plots. Sample reproducibility of CA19-9 levels was excellent (interslide correlation r = 0.88; intraslide correlation r = 0.83). The ability of RPPA to accurately distinguish CA19-9 levels between cancer and noncancer samples were determined using receiver operating characteristic curves and compared with ELISA. The AUC for RPPA and ELISA was comparable (0.87 and 0.86, respectively). When the mean CA19-9 levels of normal samples was used as a cutoff for RPPA and compared with the standard clinical ELISA cutoff, comparable specificities (71% for both) were observed. Notably, RPPA samples normalized to albumin showed increased sensitivity compared to ELISA (90% vs. 75%). As RPPA is a high-throughput method that shows results comparable to that of ELISA, we propose that RPPA is a viable technique for rapid experimental screening and validation of candidate biomarkers in blood samples.