Publications by authors named "K Papenfuss"

Background: Current treatment strategies for head and neck cancer are associated with significant morbidity and up to 50% of patients relapse, highlighting the need for more specific and effective therapeutics. Tumour necrosis factor-related apoptosis-inducing ligand (TRAIL) and Smac mimetics (SMs) are promising anticancer agents, but their effect on head and neck squamous cell carcinoma (HNSCC) remains unknown.

Methods: We examined the response of a panel of nine HNSCC cell lines to TRAIL and SMs and investigated the mechanism of cell type-specific response by functional analysis.

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Tumor necrosis factor-related apoptosis-inducing ligand (TRAIL) can induce apoptosis in many cancer cells without causing toxicity in vivo. However, to date, TRAIL-receptor agonists have only shown limited therapeutic benefit in clinical trials. This can, most likely, be attributed to the fact that 50% of all cancer cell lines and most primary human cancers are TRAIL resistant.

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Basophilia is associated with allergic and parasitic diseases and advanced chronic myeloid leukemia. In the present study, we characterized the expression and function of the death receptors Fas/CD95 and tumor necrosis factor-related apoptosis-inducing ligand (TRAIL) receptors in basophils from healthy donors compared to neoplastic basophils. Peripheral blood basophils obtained from healthy donors (HD-PBB) and from patients with chronic myeloid leukemia (CML-PBB) were found to express high levels of Fas/CD95 and low levels of TRAIL-R2, whereas the basophil-like chronic myeloid leukemia cell line KU-812 expressed significant levels of TRAIL-R1 and TRAIL-R2.

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Background: The investigation of molecular mechanisms underlying transcriptional regulation, particularly in embryonic stem cells, has received increasing attention and involves the systematic identification of target genes and the analysis of promoter co-occupancy. High-throughput approaches based on chromatin immunoprecipitation (ChIP) have been widely used for this purpose. However, these approaches remain time-consuming, expensive, labor-intensive, involve multiple steps, and require complex statistical analysis.

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