👤 Silke Lassmann

Monte Carlo modelling of SPECT imaging in Molecular Radiotherapy can improve activity quantification. Until now, SPECT modelling with GATE only considered circular orbit (CO) acquisitions. This cannot reproduce auto-contour acquisitions, where the detector head moves close to the patient to improve image resolution. The aim of this work is to develop and validate an auto-contouring step-and-shoot acquisition mode for GATE SPECT modelling. Experimental and simulated SPECT images were compared using the gamma index, and were in good agreement with gamma index passing rate (GIPR) and gamma This work thereby justifies the need for auto-contouring modelling for isotopes with high septal penetration. Show less

Mammals are composed of hundreds of different cell types with specialized functions. Each of these cellular phenotypes are controlled by different combinations of transcription factors. Using a human non islet cell insulinoma cell line (TC-YIK) which expresses insulin and the majority of known pancreatic beta cell specific genes as an example, we describe a general approach to identify key cell-type-specific transcription factors (TFs) and their direct and indirect targets. By ranking all human TFs by their level of enriched expression in TC-YIK relative to a broad collection of samples (FANTOM5), we confirmed known key regulators of pancreatic function and development. Systematic siRNA mediated perturbation of these TFs followed by qRT-PCR revealed their interconnections with NEUROD1 at the top of the regulation hierarchy and its depletion drastically reducing insulin levels. For 15 of the TF knock-downs (KD), we then used Cap Analysis of Gene Expression (CAGE) to identify thousands of their targets genome-wide (KD-CAGE). The data confirm NEUROD1 as a key positive regulator in the transcriptional regulatory network (TRN), and ISL1, and PROX1 as antagonists. As a complimentary approach we used ChIP-seq on four of these factors to identify NEUROD1, LMX1A, PAX6, and RFX6 binding sites in the human genome. Examining the overlap between genes perturbed in the KD-CAGE experiments and genes with a ChIP-seq peak within 50 kb of their promoter, we identified direct transcriptional targets of these TFs. Integration of KD-CAGE and ChIP-seq data shows that both NEUROD1 and LMX1A work as the main transcriptional activators. In the core TRN (i.e., TF-TF only), NEUROD1 directly transcriptionally activates the pancreatic TFs HSF4, INSM1, MLXIPL, MYT1, NKX6-3, ONECUT2, PAX4, PROX1, RFX6, ST18, DACH1, and SHOX2, while LMX1A directly transcriptionally activates DACH1, SHOX2, PAX6, and PDX1. Analysis of these complementary datasets suggests the need for caution in interpreting ChIP-seq datasets. (1) A large fraction of binding sites are at distal enhancer sites and cannot be directly associated to their targets, without chromatin conformation data. (2) Many peaks may be non-functional: even when there is a peak at a promoter, the expression of the gene may not be affected in the matching perturbation experiment. Show less

DNA copy number changes represent molecular fingerprints of solid tumors and are as such relevant for better understanding of tumor development and progression. In this study, we applied genome-wide array comparative genomic hybridization (aCGH) to identify gene-specific DNA copy number changes in chromosomal (CIN)- and microsatellite (MIN)-unstable sporadic colorectal cancers (sCRC). Genomic DNA was extracted from microdissected, matching normal colorectal epithelium and invasive tumor cells of formalin-fixed and paraffin-embedded tissues of 22 cases with colorectal cancer (CIN = 11, MIN = 11). DNA copy number changes were determined by aCGH for 287 target sequences in tumor cell DNAs, using pooled normal DNAs as reference. aCGH data of tumor cell DNAs was confirmed by fluorescence in situ hybridization (FISH) for three genes on serial tissues as those used for aCGH. aCGH revealed DNA copy number changes previously described by metaphase CGH (gains 7, 8q, 13q, and 20q; losses 8p, 15q, 18q, and 17p). However, chromosomal regions 20q, 13q, 7, and 17p were preferentially altered in CIN-type tumors and included DNA amplifications of eight genes on chromosome 20q (TOP1, AIB1, MYBL2, CAS, PTPN1, STK15, ZNF217, and CYP24), two genes on chromosome 13q (BRCA2 and D13S25), and three genes on chromosome 7 (IL6, CYLN2, and MET) as well as DNA deletions of two genes on chromosome 17p (HIC1 and LLGL1). Finally, additional CIN-tumor-associated DNA amplifications were identified for EXT1 (8q24.11) and MYC (8q24.12) as well as DNA deletions for MAP2K5 (15q23) and LAMA3 (18q11.2). In contrast, distinct MIN-tumor-associated DNA amplifications were detected for E2F5 (8p22-q21.3), GARP (11q13.5-q14), ATM (11q22.3), KAL (Xp22.3), and XIST (Xq13.2) as well as DNA deletions for RAF1 (3p25), DCC (18q21.3), and KEN (21q tel). aCGH revealed distinct DNA copy number changes of oncogenes and tumor suppressor genes in CIN- and MIN-type sporadic colorectal carcinomas. The identified candidate genes are likely to have distinct functional roles in the carcinogenesis and progression of CIN- and MIN-type sporadic CRCs and may be involved in the differential response of CIN- and MIN-type tumor cells to (adjuvant) therapy, such as 5-fluorouracil. Show less