Robert Grützmann

Inhibition of Hedgehog Signaling Enhances Delivery of Chemotherapy in a Mouse Model of Pancreatic Cancer

Its All in the Delivery Pancreatic cancer is almost universally associated with a poor prognosis, in part because the tumors are resistant to chemotherapeutic drugs. Working with a mouse tumor model that displays many features of the human disease, Olive et al. (p. 1457, published online 21 May; see the Perspective by Olson and Hanahan) found that the tumors were poorly vascularized, a factor likely to impede drug delivery. Treatment of the mice with the chemotherapeutic drug gemcitabine in combination with a drug that depletes tumor-associated stromal tissue led to an increase in tumor vasculature, enhanced delivery of gemcitabine, and a delay in disease progression. Thus, drugs targeting the tumor stroma may merit investigation as a way to enhance the efficacy of conventional chemotherapy for pancreatic cancer. Pancreatic tumors are unresponsive to chemotherapy because their limited vasculature precludes efficient drug delivery. Pancreatic ductal adenocarcinoma (PDA) is among the most lethal human cancers in part because it is insensitive to many chemotherapeutic drugs. Studying a mouse model of PDA that is refractory to the clinically used drug gemcitabine, we found that the tumors in this model were poorly perfused and poorly vascularized, properties that are shared with human PDA. We tested whether the delivery and efficacy of gemcitabine in the mice could be improved by coadministration of IPI-926, a drug that depletes tumor-associated stromal tissue by inhibition of the Hedgehog cellular signaling pathway. The combination therapy produced a transient increase in intratumoral vascular density and intratumoral concentration of gemcitabine, leading to transient stabilization of disease. Thus, inefficient drug delivery may be an important contributor to chemoresistance in pancreatic cancer.

Whole genomes redefine the mutational landscape of pancreatic cancer

Pancreatic cancer remains one of the most lethal of malignancies and a major health burden. We performed whole-genome sequencing and copy number variation (CNV) analysis of 100 pancreatic ductal adenocarcinomas (PDACs). Chromosomal rearrangements leading to gene disruption were prevalent, affecting genes known to be important in pancreatic cancer (TP53, SMAD4, CDKN2A, ARID1A and ROBO2) and new candidate drivers of pancreatic carcinogenesis (KDM6A and PREX2). Patterns of structural variation (variation in chromosomal structure) classified PDACs into 4 subtypes with potential clinical utility: the subtypes were termed stable, locally rearranged, scattered and unstable. A significant proportion harboured focal amplifications, many of which contained druggable oncogenes (ERBB2, MET, FGFR1, CDK6, PIK3R3 and PIK3CA), but at low individual patient prevalence. Genomic instability co-segregated with inactivation of DNA maintenance genes (BRCA1, BRCA2 or PALB2) and a mutational signature of DNA damage repair deficiency. Of 8 patients who received platinum therapy, 4 of 5 individuals with these measures of defective DNA maintenance responded.

Circulating Methylated SEPT9 DNA in Plasma Is a Biomarker for Colorectal Cancer

BACKGROUND The presence of aberrantly methylated SEPT9 DNA in plasma is highly correlated with the occurrence of colorectal cancer. We report the development of a new SEPT9 biomarker assay and its validation in case-control studies. The development of such a minimally invasive blood-based test may help to reduce the current gap in screening coverage. METHODS A new SEPT9 DNA methylation assay was developed for plasma. The assay comprised plasma DNA extraction, bisulfite conversion of DNA, purification of bisulfite-converted DNA, quantification of converted DNA by real-time PCR, and measurement of SEPT9 methylation by real-time PCR. Performance of the SEPT9 assay was established in a study of 97 cases with verified colorectal cancer and 172 healthy controls as verified by colonoscopy. Performance based on predetermined algorithms was validated in an independent blinded study with 90 cases and 155 controls. RESULTS The SEPT9 assay workflow yielded 1.9 microg/L (CI 1.3-3.0) circulating plasma DNA following bisulfite conversion, a recovery of 45%-50% of genomic DNA, similar to yields in previous studies. The SEPT9 assay successfully identified 72% of cancers at a specificity of 93% in the training study and 68% of cancers at a specificity of 89% in the testing study. CONCLUSIONS Circulating methylated SEPT9 DNA, as measured in the new (m)SEPT9 assay, is a valuable biomarker for minimally invasive detection of colorectal cancer. The new assay is amenable to automation and standardized use in the clinical laboratory.

Sensitive detection of colorectal cancer in peripheral blood by septin 9 DNA methylation assay.

Background Colorectal cancer (CRC) is the second leading cause of cancer deaths despite the fact that detection of this cancer in early stages results in over 90% survival rate. Currently less than 45% of at-risk individuals in the US are screened regularly, exposing a need for better screening tests. We performed two case-control studies to validate a blood-based test that identifies methylated DNA in plasma from all stages of CRC. Methodology/Principal Findings Using a PCR assay for analysis of Septin 9 (SEPT9) hypermethylation in DNA extracted from plasma, clinical performance was optimized on 354 samples (252 CRC, 102 controls) and validated in a blinded, independent study of 309 samples (126 CRC, 183 controls). 168 polyps and 411 additional disease controls were also evaluated. Based on the training study SEPT9-based classification detected 120/252 CRCs (48%) and 7/102 controls (7%). In the test study 73/126 CRCs (58%) and 18/183 control samples (10%) were positive for SEPT9 validating the training set results. Inclusion of an additional measurement replicate increased the sensitivity of the assay in the testing set to 72% (90/125 CRCs detected) while maintaining 90% specificity (19/183 for controls). Positive rates for plasmas from the other cancers (11/96) and non-cancerous conditions (41/315) were low. The rate of polyp detection (>1 cm) was ∼20%. Conclusions/Significance Analysis of SEPT9 DNA methylation in plasma represents a straightforward, minimally invasive method to detect all stages of CRC with potential to satisfy unmet needs for increased compliance in the screening population. Further clinical testing is warranted.

Foxp3 Expression in Pancreatic Carcinoma Cells as a Novel Mechanism of Immune Evasion in Cancer

The forkhead transcription factor Foxp3 is highly expressed in CD4+CD25+ regulatory T cells (Treg) and was recently identified as a key player in mediating their inhibitory functions. Here, we describe for the first time the expression and function of Foxp3 in pancreatic ductal adenocarcinoma cells and tumors. Foxp3 expression was induced by transforming growth factor-beta2 (TGF-beta2), but not TGF-beta1 stimulation in these cells, and was partially suppressed following antibody-mediated neutralization of TGF-beta2. The TGF-beta2 effect could be mimicked by ectopic expression of a constitutively active TGF-beta type I receptor/ALK5 mutant. Down-regulation of Foxp3 with small interfering RNA (siRNA) in pancreatic carcinoma cells resulted in the up-regulation of interleukin 6 (IL-6) and IL-8 expression, providing evidence for a negative transcriptional activity of Foxp3 also in these epithelial cells. Coculture of Foxp3-expressing tumor cells with naive T cells completely inhibited T-cell proliferation, but not activation, and this antiproliferative effect was partially abrogated following specific inhibition of Foxp3 expression. These findings indicate that pancreatic carcinoma cells share growth-suppressive effects with Treg and suggest that mimicking Treg function may represent a new mechanism of immune evasion in pancreatic cancer.

Neuroendocrine Tumors of the Pancreas

This literature review briefly summarizes the epidemiology, pathophysiology, clinical management, and outcomes of patients with pancreatic neuroendocrine tumors (PNETs) and highlights recent advances in PNET research. PNETs are rare neoplasms, compared with carcinomas arising from pancreatic exocrine tissue. They, like other neuroendocrine tumor types, display variable malignant potential, hormone-related syndromes (functionality), localization, and genetic background. Although tumor origin and molecular pathogenesis remain poorly understood, recently established grading and staging systems facilitate patient risk stratification, and thereby directly impact clinical decision making. Although the optimal clinical management of PNETs involves a multidisciplinary approach, surgery remains the only curative treatment for early-stage disease. Surgery may also have a role in patients with advanced-stage disease, including those with hepatic metastases. Alternative therapeutic approaches applied to PNETs, including chemotherapy, radiofrequency ablation, transarterial chemoembolization, biotherapy, polypeptide radionuclide receptor therapy, antiangiogenic therapy, and selective internal radiotherapy, have failed to demonstrate a long-term survival benefit. Surgery remains the primary therapeutic option for patients with PNETs. Research on PNETs is desperately needed to improve the therapeutic options for patients with this disease.

Meta-analysis of microarray data on pancreatic cancer defines a set of commonly dysregulated genes.

Pancreatic ductal adenocarcinoma is the eighth most common cancer with the lowest overall 5-year relative survival rate of any tumor type today. Expression profiling using microarrays has been widely used to identify genes associated with pancreatic cancer development. To extract maximum value from the available gene expression data, we applied a meta-analysis to search for commonly differentially expressed genes in pancreatic ductal adenocarcinoma. We obtained data sets from four different gene expression studies on pancreatic cancer. We selected a consensus set of 2984 genes measured in all four studies and applied a meta-analysis approach to evaluate the combined data. Of the genes identified as differentially expressed, several were validated using RT–PCR and immunohistochemistry. Additionally, we used a class discovery algorithm to identify a gene expression signature. Our meta-analysis revealed that the pancreatic cancer gene expression data sets shared a significant number of up- and downregulated genes, independent of the technology used. This interstudy crossvalidation approach generated a set of 568 genes that were consistently and significantly dysregulated in pancreatic cancer. Of these, 364 (64.1%) were upregulated and 204 (35.9%) were downregulated in pancreatic cancer. Only 127 (22%) were described in the published individual analyses. Functional annotation of the genes revealed that genes presumably associated with the cell adhesion-mediated drug resistance pathway are frequently overexpressed in pancreatic cancer. Meta-analysis is an important tool for the identification and validation of differentially expressed genes. These could represent good candidates for novel diagnostic and therapeutic approaches to pancreatic cancer.

Sentinel lymph node biopsy in colon cancer: A prospective multicenter trial

Introduction:The clinical impact of sentinel lymph node biopsy (SLNB) in colon cancer is still controversial. The purpose of this prospective multicenter trial was to evaluate its clinical value to predict the nodal status and identify factors that influence these results. Methods:Colon cancer patients without prior colorectal surgery or irradiation were eligible. The sentinel lymph node (SLN) was identified intraoperatively by subserosal blue dye injection around the tumor. The SLN underwent step sections and immunohistochemistry (IHC), if classified free of metastases after routine hematoxylin and eosin examination. Results:At least one SLN (median, n = 2) was identified in 268 of 315 enrolled patients (detection rate, 85%). Center experience, lymphovascular invasion, body mass index (BMI), and learning curve were positively associated with the detection rate. The false-negative rate to identify pN+ patients by SLNB was 46% (38 of 82). BMI showed a significant association to the false-negative rate (P < 0.0001), the number of tumor-involved lymph nodes was inversely associated. If only slim patients (BMI ≤24) were investigated in experienced centers (>22 patients enrolled), the sensitivity increased to 88% (14 of 16). Moreover, 21% (30 of 141) of the patients, classified as pN0 by routine histopathology, revealed micrometastases or isolated tumor cells (MM/ITC) in the SLN. Conclusions:The contribution of SLNB to conventional nodal staging of colon cancer patients is still unspecified. Technical problems have to be resolved before a definite conclusion can be drawn in this regard. However, SLNB identifies about one fourth of stage II patients to reveal MM/ITC in lymph nodes. Further studies must clarify the clinical impact of these findings in terms of prognosis and the indication of adjuvant therapy.

Variants in CPA1 are strongly associated with early onset chronic pancreatitis

Chronic pancreatitis is an inflammatory disorder of the pancreas. We analyzed CPA1, encoding carboxypeptidase A1, in subjects with nonalcoholic chronic pancreatitis (cases) and controls in a German discovery set and three replication sets. Functionally impaired variants were present in 29/944 (3.1%) German cases and 5/3,938 (0.1%) controls (odds ratio (OR) = 24.9, P = 1.5 × 10−16). The association was strongest in subjects aged ≤10 years (9.7%; OR = 84.0, P = 4.1 × 10−24). In the replication sets, defective CPA1 variants were present in 8/600 (1.3%) cases and 9/2,432 (0.4%) controls from Europe (P = 0.01), 5/230 (2.2%) cases and 0/264 controls from India (P = 0.02) and 5/247 (2.0%) cases and 0/341 controls from Japan (P = 0.013). The mechanism by which CPA1 variants confer increased pancreatitis risk may involve misfolding-induced endoplasmic reticulum stress rather than elevated trypsin activity, as is seen with other genetic risk factors for this disease.

Google Goes Cancer: Improving Outcome Prediction for Cancer Patients by Network-Based Ranking of Marker Genes

Predicting the clinical outcome of cancer patients based on the expression of marker genes in their tumors has received increasing interest in the past decade. Accurate predictors of outcome and response to therapy could be used to personalize and thereby improve therapy. However, state of the art methods used so far often found marker genes with limited prediction accuracy, limited reproducibility, and unclear biological relevance. To address this problem, we developed a novel computational approach to identify genes prognostic for outcome that couples gene expression measurements from primary tumor samples with a network of known relationships between the genes. Our approach ranks genes according to their prognostic relevance using both expression and network information in a manner similar to Googles PageRank. We applied this method to gene expression profiles which we obtained from 30 patients with pancreatic cancer, and identified seven candidate marker genes prognostic for outcome. Compared to genes found with state of the art methods, such as Pearson correlation of gene expression with survival time, we improve the prediction accuracy by up to 7%. Accuracies were assessed using support vector machine classifiers and Monte Carlo cross-validation. We then validated the prognostic value of our seven candidate markers using immunohistochemistry on an independent set of 412 pancreatic cancer samples. Notably, signatures derived from our candidate markers were independently predictive of outcome and superior to established clinical prognostic factors such as grade, tumor size, and nodal status. As the amount of genomic data of individual tumors grows rapidly, our algorithm meets the need for powerful computational approaches that are key to exploit these data for personalized cancer therapies in clinical practice.