Johann Michael Kraus

While central nervous system (CNS) involvement in acute lymphoblastic leukemia (ALL) remains a major cause of treatment failure, underlying molecular mechanisms are not fully understood. Based on previous work implicating vascular endothelial growth factor A (VEGF), we dissected its contribution to VEGF receptor 2 (VEGFR2)-mediated CNS entry versus niche-dependent survival and evaluated VEGF-targeted strategies in translational xenograft models. Using the NOD/SCID/huALL model enabling temporally defined intervention before and after CNS dissemination, bevacizumab consistently reduced established CNS ALL but had only minor effects on CNS entry, indicating a predominant contribution of VEGF in CNS ALL survival. Consistently, neither genetic depletion nor pharmacologic inhibition of murine Vegfr2 impaired transendothelial migration (TEM) in vitro. To further substantiate the role of VEGF in CNS ALL, manifest disease was treated in vivo with the multi-kinase inhibitor Sorafenib that was previously shown effective in refractory CNS leukemia patients. Sorafenib reduced CNS ALL with the highest efficacy in this compartment. In vitro, Sorafenib decreased TEM but also induced lipid peroxidation in ALL cells accompanied by ferroptosis induction. Importantly, lipidomic profiling of CNS-derived ALL cells revealed enhanced peroxidizability linked to increased ferroptosis susceptibility, providing a mechanistic link for lipid peroxidation-driven cell death in the CNS. Collectively, our findings identify VEGF signaling and lipidomic remodeling as complementary mechanisms of CNS adaptation in ALL. While VEGF supports CNS persistence, lipidomic remodeling generates a highly peroxidizable state associated with increased ferroptosis susceptibility. These findings suggest that inhibiting VEGF signaling and simultaneously inducing ferroptosis may represent a therapeutic strategy for CNS ALL.

Understanding complex biological processes often requires modeling both deterministic logic and stochastic variability. In this work, we incorporate stochasticity into spiking neural network (SNN)-based Boolean networks through probabilistic inputs and variability in connectivity patterns. We present an approach to simulate synchronous Boolean networks with SNNs, representing Boolean variables as neuron populations, and logical functions by spiking subcircuits. The representation of genes with a set of neurons instead of a single one, enables new methods for incorporating stochasticity into the network by defining the pattern of the neuron connections between sets. In a case study, we implemented a Boolean model of hematopoietic stem cell regulation and analyze the network transitions between attractor states under different input scenarios, especially stochastic variations in external inputs and neuron connection patterns.

Published biomedical experiments provide an increasingly rich collection of results and identify genes potentially involved in diverse biological mechanisms. However, individual studies are often confined to narrow experimental contexts and are restricted to single omics layers. Cross-study knowledge aggregation can broaden this perspective and enable the construction of global, context-aware gene rankings. Recent developments in natural language processing have made large-scale literature mining increasingly feasible. This enables the systematic extraction and fusion of symbolic knowledge from published experiments. We present pathXcite, a software that extracts genes associated with specific contexts, such as diseases or biological mechanisms from the literature, and ranks them by contextual relevance. These relevance-based gene rankings can compress a scientific context into a symbolic representation. This representation enables diverse downstream analyses, including cross-context comparisons, network-based analysis, enrichment analysis, and integration with experimental omics data. In multiple use cases, we show how our extraction and fusion strategy can be applied to uncover hidden aspects in biological data.

Growing evidence suggests that somatic mutations may be a major cause of the aging process. However, it remains to be tested whether the predictions of the theory also apply to species with longer life spans than humans.Hydrais a genus of freshwater polyps with remarkable regeneration abilities and a potentially unlimited life span under laboratory conditions. By genome sequencing of single cells and whole animals, we found that the mutation rates inHydra’s stem cells are even slightly higher than in humans or mice. A potential explanation for this deviation from the prediction of the theory may lie in the adaptability offered by a higher mutation rate, as we were able to show that the genome of the widely studiedHydra magnipapillata strain 105 has undergone a process of strong positive selection since the strain's cultivation 50 years ago. This most likely represents a rapid adaptation to the drastically altered environmental conditions associated with the transition from the wild to laboratory conditions. Processes under positive selection in captive animals include pathways associated withHydra’s simple nervous system, its nucleic acid metabolic process, cell migration, and hydrolase activity.

E-Cadherin Expression upon INHBA knockdown. Representative western blot (of n = 3 replicates) showing E-Cadherin protein expression in Mock KD and INHBA KD1/KD2 at t24 and t48.

Cell migration upon INHBA knockdown. A, Migration of native UDSCC1 cells, Mock KD, INHBA KD1/KD2 and native UDSCC2 cells as assessed by scratch assay. Results are shown as mean ± SD of the open wound area (n = 3) at baseline (t0), t24, and t48. Conditions were compared with native UDSCC1 using unpaired t test with ***, P ≤ 0.001; ****, P ≤ 0.0001; and ns, P > 0.05. B, Representative images of processed light microscopy pictures taken at 10-fold magnification of each condition at t0, t24, and t48.

Correlation analysis between miRNAs and INHBA expression output

Correlation analyses between INHBA expression, immune infiltrates and miRNAs. A, Waterfall plot showing Spearman correlation between INHBA expression level and infiltrating ratios (IR) of different immune cells, as computed by immune cell deconvolution. Rho > 0.4 was considered relevant (dashed line). *, P ≤ 0.05; ***, P ≤ 0.001; ns, not significant. B, Correlation matrix between INHBA and the pro-tumor M1 signature showing Spearman rho and P-value symbols (*, P ≤ 0.05; **, P ≤ 0.01; ***, P ≤ 0.001) in the upper triangular matrix and scatter plots in the lower triangular matrix. TPM = transcripts per million. C, Waterfall plot showing Spearman correlation between INHBA expression level and miRNAs (TCGA cohort). miRNAs with Rho < −0.4 and P < 0.05 were considered relevant (dashed line). D, Venn diagram showing intersections between negatively correlating miRNAs from C and miRNAs predicted to interact with the 3′UTR of INHBA by miRDB and Targetscan resulting in three candidates of interest (hsa-mir-106a, hsa-mir-20b, hsa-mir-9-1/2/3). Their putative binding sites to the INHBA 3′UTR are highlighted. E–G, Kaplan–Meier plots with log-rank test for overall survival of patients with OPSCC (TCGA cohort) based on tumor miRNA expression of the outlined candidates (E: hsa-mir-106a, F: hsa-mir-20b, G: hsa-mir-9). Blue indicates low and red indicates high miRNA expression, as determined using median of raw counts as cutoff.

Gene set enrichment analysis output