Biology subjects

Pircher, T.

Publications and source records attributed to Pircher, T..

3 recordsLinked to original sources

bioRxiv2025

Exploring the Anti-Tumor Effects of Brusatol in Aggressive B-Cell Lymphomas

Aggressive B-cell lymphomas are the most common lymphoid malignancies in adults, with an increasing incidence. Diffuse large B-cell lymphoma (DLBCL) is the most prevalent and highly heterogeneous type, often exhibiting poor responses to standard immuno-chemotherapy. One third of patients experience primary refractory disease or relapse, particularly those with high c-MYC and BCL-2 expression levels, which drive aggressiveness and resistance to treatment. Therefore, the development of new therapies is urgently needed. This study explores the anti-tumor properties of brusatol, both as single agent and in combination with the BCL-2 inhibitor, venetoclax, for the treatment of aggressive lymphoma cells. Brusatol inhibited lymphoma cell growth in a concentration-dependent manner in various cell lines. Further analysis revealed that brusatol is able to efficiently induce cell death in the lymphoma cells in vitro, as well as in patient-derived samples. Importantly, the effect of brusatol was strongly reduced in non-malignant lymphoid cells compared to lymphoma cells. We discovered that lymphoma cell lines highly sensitive to brusatol have elevated c-MYC expression. Brusatol treatment rapidly reduced protein expression of c-MYC and MCL-1. Protein biosynthesis analysis confirmed that brusatol induced translational inhibition in aggressive lymphoma cells. Furthermore, the combination of brusatol and venetoclax synergistically enhanced lymphoma cell death, particularly in samples with low c-MYC protein levels. Our findings suggest that brusatol has significant potential for the development of novel therapeutic strategies for aggressive lymphomas, especially for cases with high c-MYC content. Additionally, its combination with venetoclax represents a promising approach to improve treatment outcomes.

cancer biology↗

bioRxiv2021

Ionotropic glutamate receptors in the retina - a bioinformatical meta-analysis

Glutamate is an essential neurotransmitter for signal processing in the vertical pathway of the mammalian retina, where it is involved in the distribution of visual information into several parallel channels. The excitatory effects of glutamate are mediated by AMPA-, kainate-, and NMDA-type ionotropic glutamate receptors (iGluRs). The expression patterns of these receptors in the vertebrate retina have been investigated so far with mainly immunocytochemical, in-situ hybridization, and electrophysiological/pharmacological techniques. Here, we have used scRNA sequencing data from chicken, mouse, macaque, and human retina to describe and compare the profile of iGluR expression in major retinal cell types across species. Our results suggest that major retinal cell types each express a unique set of iGluRs with substantial differences between non-mammalian and mammalian retinae. Expression of iGluRs has been investigated in more detail for amacrine and bipolar cell types of the human retina, each showing minor variations of a common pattern. The differential expression of iGluRs is likely to convey unique signal processing properties to individual elements of the retinal circuitry.

neuroscience↗

bioRxiv2021

A novel machine learning-based approach for the detection and analysis of spontaneous synaptic currents

Spontaneous synaptic activity is a hallmark of neural networks. A thorough description of these synaptic signals is essential for understanding neurotransmitter release and the generation of a postsynaptic response. However, the complexity of synaptic current trajectories has either precluded an in-depth analysis or it has forced human observers to resort to manual or semi-automated approaches based on subjective amplitude and area threshold settings. Both procedures are time-consuming, error-prone and likely affected by human bias. Here, we present three complimentary methods for a fully automated analysis of spontaneous excitatory postsynaptic currents measured in major cell types of the mouse retina and in a primary culture of mouse auditory cortex. Two approaches rely on classical threshold methods, while the third represents a novel machine learning-based algorithm. Comparison with frequently used existing methods demonstrates the suitability of our algorithms for an unbiased and efficient analysis of synaptic signals in the central nervous system.

neuroscience↗