Nikolaus Wick

Lymphatic endothelial progenitor cells contribute to de novo lymphangiogenesis in human renal transplants.

De novo lymphangiogenesis influences the course of different human diseases as diverse as chronic renal transplant rejection and tumor metastasis. The cellular mechanisms of lymphangiogenesis in human diseases are currently unknown, and could involve division of local preexisting endothelial cells or incorporation of circulating progenitors. We analyzed renal tissues of individuals with gender-mismatched transplants who had transplant rejection and high rates of overall lymphatic endothelial proliferation as well as massive chronic inflammation. Donor-derived cells were detected by in situ hybridization of the Y chromosome. We compared these tissues with biopsies of essentially normal skin and intestine, and two rare carcinomas with low rates of lymphatic endothelial proliferation that were derived from individuals with gender-mismatched bone marrow transplants. Here, we provide evidence for the participation of recipient-derived lymphatic progenitor cells in renal transplants. In contrast, lymphatic vessels of normal tissues and those around post-transplant carcinomas did not incorporate donor-derived progenitors. This indicates a stepwise mechanism of inflammation-associated de novo lymphangiogenesis, implying that potential lymphatic progenitor cells derive from the circulation, transmigrate through the connective tissue stroma, presumably in the form of macrophages, and finally incorporate into the growing lymphatic vessel.

Lymphatic Precollectors Contain a Novel, Specialized Subpopulation of Podoplaninlow, CCL27-Expressing Lymphatic Endothelial Cells

Expression of the lymphoendothelial marker membrane mucoprotein podoplanin (podo) distinguishes endothelial cells of both blood and lymphatic lineages. We have previously discovered two distinct subpopulations of lymphatic endothelial cells (LECs) in human skin that were defined by their cell surface densities of podoplanin and were designated LEC podo-low and LEC podo-high. LEC podo-low is restricted to lymphatic precollector vessels that originate from initial LEC podo-high-containing lymphatic capillaries and selectively express several pro-inflammatory factors. In addition to the chemokine receptor protein Duffy blood group antigen receptor for chemokines, these factors include the constitutively expressed chemokine CCL27, which is responsible for the accumulation of pathogenic CCR10+ T lymphocytes in human inflammatory skin diseases. In this study, we report that CCR10+ T cells accumulate preferentially both around and within CCL27+ LEC podo-low precollector vessels in skin biopsies of human inflammatory disease. In transmigration assays, isolated CCR10+ T lymphocytes are chemotactically attracted by LEC podo-low in a CCL27-dependent fashion, but not by LEC podo-high. These observations indicate that LEC podo-low-containing precollector vessels constitute a specialized segment of the initial lymphatic microvasculature, and we hypothesize that these LEC podo-low-containing vessels are involved in the trafficking of CCR10+ T cells during skin inflammation.

Expression of c-kit in human osteosarcoma and its relevance as a prognostic marker

Aims: To examine the prognostic relevance of c-kit expression in human osteosarcomas and to evaluate the mutation status in exon 9 and exon 11 of the c-kit gene. Methods: c-kit expression was examined in 100 human osteosarcomas by immunohistochemistry using paraffin embedded tumour tissues, and capillary sequencing of genomic DNA was performed to search for mutations in exons 9 and 11 of the c-kit gene. Results: 20 osteosarcomas showed c-kit expression ranging from 5% to 90% (mean 5.9%; SD 16.74%). Furthermore, DNA sequences of exon 9 and exon 11 of the c-kit gene were not altered in these tumours. Overall and disease free survival analysis did not reveal any differences between patients with osteosarcoma with c-kit expression and those with c-kit negative tumours. Conclusions: C-kit expression is not a prognostic marker in patients with osteosarcoma. The protein expression is not linked to mutations in exon 9 or exon 11 of the c-kit gene. Therefore, these exons may not function as targets for treatment modalities based on the suppression of c-kit tyrosine kinase activity.

Nonuniform hybridization: a potential source of error in oligonucleotide-chip experiments with low amounts of starting material.

Low amounts of starting material are a significant limitation of gene-expression profiling of microprepared pathologic specimens. Linear RNA amplification has become the method of choice to overcome this problem. Thus, transcriptomal analyses by oligonucleotide-chips or cDNA microarrays are now feasible with labeled complementary RNA generated from total RNA samples in the lower nanogram range. However, in case of oligonucleotide-chips, it has been underestimated so far that individual complementary RNA molecules are shorter in length than and display a 3′ bias in comparison to the sequence stretch represented by oligonucleotides on the chip. This can lead to incorrect interpretation of raw data. We have analyzed this problem testing ex vivo–microprepared endothelial cells with Affymetrix GeneChips U133A. Only a small subset of housekeeping genes showed adequate uniform hybridization. We developed a software tool for objective evaluation of oligonucleotide-chips based on automated analysis of as well as normalization to this subset of housekeeping genes. We analyzed the gene expression profile of microprepared lymphatic vascular endothelial cells. We show that optimized normalization prevented exclusion of angiopoietin-2, a lymphatic endothelial marker, from the lymphovascular transcriptome.

Expression of platelet-derived growth factor-AA and platelet-derived growth factor-α receptor in ameloblastomas

BACKGROUND Platelet-derived growth factor (PDGF)-AA isoform and its receptor, PDGF-alpha receptor (PDGFRA) regulate tooth development and growth. We investigated the expression of both proteins in ameloblastomas, to contribute the understanding of the potential role of the PDGF/PDGFR system in this odontogenic neoplasm. METHOD Twenty-nine specimens of ameloblastoma were analyzed for PDGF-AA and PDGFRA expression using immunohistochemistry. The proliferation activity was investigated with the MIB-1 antibody. Additionally, capillary sequencing of genomic DNA was performed to search for mutations in therapeutically relevant exons 12 and 18 of the PDGFRA gene. RESULTS PDGF-AA and PDGFRA expression were detectable in all cases with the exception of one tumor. However, protein expression levels did neither correlate with each other nor with MIB-1 expression. Unicystic ameloblastomas did not differ from solid tumors with regard to PDGF-AA, PDGFRA, and MIB-1 expression. One tumor revealed a somatic mutation of exon 12 of the PDGFRA gene. CONCLUSION PDGF-AA and PDGFRA proteins are regularly expressed in variable levels in ameloblastomas, and somatic mutations of exon 12 and exon 18 of the PDGFRA gene are rare findings.

Statistically Consistent Identification of Differentially Expressed Genes in DNA Chip Data Over the Whole Expression Range

AbstractBackground: It is a well known problem that standard techniques for analysing DNA chip data misspecify genes. In particular, genes that are confirmed to be active, often do not show up as potential candidates. This is possibly due to non-homogeneous distributions of expression levels over the whole expression range. Methods: We introduce a method that allows the detection of genes based on a self-adaptive threshold. The threshold is determined for equally-populated expression bands by assuming a normal distribution of logarithms of expression level ratios. By specifying a significance level, the threshold is set according to ‘local’ expression statistics within a band. We call this method the relative variance method (RVM). We derive a test statistic for the RVM and compare it with other methods. On this statistical basis, we show that RVM is a complementary approach to the t-test, significance analysis of microarrays (SAM) or empirical Bayes analysis of microarrays (EBAM). The RVM should be particularly useful for experiments with small sample size. Results: Using a clinical dataset, we demonstrate that the RVM can correctly identify known marker genes, which are not found by the t-test, SAM or EBAM. Conclusion: In situations with limited sample material and small number of replicates, as is often the case in clinical datasets, use of the proposed RVM provides a higher reliability of potential candidate genes.