Placement of an aortomonoiliac stent graft without femorofemoral revascularization in endovascular aneurysm repair: a case report

<p>Abstract</p> <p>Introduction</p> <p>Endovascular aortic repair, if technically feasible, is the treatment of choice for patients with a contained ruptured aortic aneurysm who are unfit for open surgery.</p> <p>Case presentation</p> <p>We report the case of an 80-year-old Caucasian man who presented with an unusually configured, symptomatic infrarenal aortic aneurysm. His aneurysm showed an erosion of the fourth lumbar vertebra and a severely arteriosclerotic pelvic axis. A high thigh amputation of his right leg had been performed 15 months previously. On his right side, occlusion of his external iliac artery, common femoral artery, and deep femoral artery had occurred. His aneurysm was treated by a left-sided aortomonoiliac stent graft without femorofemoral revascularization, resulting in occlusions of both internal iliac arteries. No ischemic symptoms appeared, although perfusion of his right side was maintained only over epigastric collaterals.</p> <p>Conclusions</p> <p>The placement of aortomonoiliac stent grafts for endovascular treatment of infrarenal aortic aneurysms without contralateral revascularization is a feasible treatment option in isolated cases. In this report, access problems and revascularization options in endovascular aneurysm repair are discussed.</p

A randomized multi-center phase II trial of the angiogenesis inhibitor Cilengitide (EMD 121974) and gemcitabine compared with gemcitabine alone in advanced unresectable pancreatic cancer

BACKGROUND: Anti-angiogenic treatment is believed to have at least cystostatic effects in highly vascularized tumours like pancreatic cancer. In this study, the treatment effects of the angiogenesis inhibitor Cilengitide and gemcitabine were compared with gemcitabine alone in patients with advanced unresectable pancreatic cancer. METHODS: A multi-national, open-label, controlled, randomized, parallel-group, phase II pilot study was conducted in 20 centers in 7 countries. Cilengitide was administered at 600 mg/m(2 )twice weekly for 4 weeks per cycle and gemcitabine at 1000 mg/m(2 )for 3 weeks followed by a week of rest per cycle. The planned treatment period was 6 four-week cycles. The primary endpoint of the study was overall survival and the secondary endpoints were progression-free survival (PFS), response rate, quality of life (QoL), effects on biological markers of disease (CA 19.9) and angiogenesis (vascular endothelial growth factor and basic fibroblast growth factor), and safety. An ancillary study investigated the pharmacokinetics of both drugs in a subset of patients. RESULTS: Eighty-nine patients were randomized. The median overall survival was 6.7 months for Cilengitide and gemcitabine and 7.7 months for gemcitabine alone. The median PFS times were 3.6 months and 3.8 months, respectively. The overall response rates were 17% and 14%, and the tumor growth control rates were 54% and 56%, respectively. Changes in the levels of CA 19.9 went in line with the clinical course of the disease, but no apparent relationships were seen with the biological markers of angiogenesis. QoL and safety evaluations were comparable between treatment groups. Pharmacokinetic studies showed no influence of gemcitabine on the pharmacokinetic parameters of Cilengitide and vice versa. CONCLUSION: There were no clinically important differences observed regarding efficacy, safety and QoL between the groups. The observations lay in the range of other clinical studies in this setting. The combination regimen was well tolerated with no adverse effects on the safety, tolerability and pharmacokinetics of either agent

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 Google's 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