Methylation of the hTERT Promoter: A Novel Cancer Biomarker for Leptomeningeal Metastasis Detection in Cerebrospinal Fluids.

PURPOSE: The diagnosis of leptomeningeal metastases is usually confirmed by the finding of malignant cells by cytologic examination in the cerebrospinal fluid (CSF). More sensitive and specific cancer biomarkers may improve the detection of tumor cells in the CSF. Promoter methylation of the human telomerase reverse transcriptase (hTERT) gene characterizes most cancer cells. The aim of this study was to develop a sensitive method to detect hTERT methylation and to explore its use as a cancer biomarker in CSF. EXPERIMENTAL DESIGN: In 77 CSF specimens from 67 patients, hTERT promoter methylation was evaluated using real-time methylation-sensitive high-resolution melting (MS-HRM) and real-time TaqMan PCR and MS-HRM in a single-tube assay. RESULTS: Real-time MS-HRM assay was able to detect down to 1% hTERT-methylated DNA in a background of unmethylated DNA. PCR products were obtained from 90% (69/77) of CSF samples. No false positive hTERT was detected in the 21 non-neoplastic control cases, given to the method a specificity of 100%. The sensitivity of the real-time MS-HRM compared with the cytologic gold standard analysis was of 92% (11/12). Twenty-six CSFs from 22 patients with an hTERT-methylated primary tumor showed cytologic results suspicious for malignancy; in 17 (65%) of them, a diagnosis of leptomeningeal metastases could be confirmed by the hTERT methylation test. CONCLUSION: The hTERT real-time MS-HRM approach is fast, specific, sensitive, and could therefore become a valuable tool for diagnosis of leptomeningeal metastases as an adjunct to the traditional examination of CSF. Clin Cancer Res; 19(8); 2216-23. ©2013 AACR.

Comparison between a linear ion trap and a triple quadruple MS in the sensitive detection of large peptides at femtomole amounts on column.

In addition to the importance of sample preparation and extract separation, MS detection is a key factor in the sensitive quantification of large undigested peptides. In this article, a linear ion trap MS (LIT-MS) and a triple quadrupole MS (TQ-MS) have been compared in the detection of large peptides at subnanomolar concentrations. Natural brain natriuretic peptide, C-peptide, substance P and D-Junk-inhibitor peptide, a full D-amino acid therapeutic peptide, were chosen. They were detected by ESI and simultaneous MS(1) and MS(2) acquisitions. With direct peptide infusion, MS(2) spectra revealed that fragmentation was peptide dependent, milder on the LIT-MS and required high collision energies on the TQ-MS to obtain high-intensity product ions. Peptide adsorption on surfaces was overcome and peptide dilutions ranging from 0.1 to 25 nM were injected onto an ultra high-pressure LC system with a 1 mm id analytical column and coupled with the MS instruments. No difference was observed between the two instruments when recording in LC-MS(1) acquisitions. However, in LC-MS(2) acquisitions, a better sensitivity in the detection of large peptides was observed with the LIT-MS. Indeed, with the three longer peptides, the typical fragmentation in the TQ-MS resulted in a dramatic loss of sensitivity (> or = 10x).

Segmentation of Head and Neck Lymph Node Regions for Radiotherapy Planning Using Active Contour-Based Atlas Registration

In this paper, we present the segmentation of the headand neck lymph node regions using a new active contourbased atlas registration model. We propose to segment thelymph node regions without directly including them in theatlas registration process; instead, they are segmentedusing the dense deformation field computed from theregistration of the atlas structures with distinctboundaries. This approach results in robust and accuratesegmentation of the lymph node regions even in thepresence of significant anatomical variations between theatlas-image and the patient's image to be segmented. Wealso present a quantitative evaluation of lymph noderegions segmentation using various statistical as well asgeometrical metrics: sensitivity, specificity, dicesimilarity coefficient and Hausdorff distance. Acomparison of the proposed method with two other state ofthe art methods is presented. The robustness of theproposed method to the atlas selection, in segmenting thelymph node regions, is also evaluated.