Search bioRxiv⌕ Search

Biology subjects

Geiger, L.

Publications and source records attributed to Geiger, L..

3 recordsLinked to original sources

Engineering Functional CLA-Targeting CAR Approaches for Pancreatic Ductal Adenocarcinoma

Pancreatic cancer remains a highly lethal malignancy with limited therapeutic options. Chimeric antigen receptor (CAR) therapy has revolutionized the treatment of hematological cancers but still faces major limitations in solid tumors, particularly due to the scarcity of tumor-specific targets. Cutaneous lymphocyte antigen (CLA) recently emerged as a promising PDAC target due to its high tumor expression and limited presence in healthy tissues. However, previously reported CLA-directed CAR constructs lacked antitumor functionality. Here, we investigated multiple strategies to generate functional CLA-targeting CAR approaches. We first hypothesized that impaired activity resulted from fratricide caused by CLA expression on activated T cells. CLA knockout was successfully achieved through deletion of fucosyltransferase-7, but not by knockout of the major CLA carrier backbones CD162, CD44 or CD43, suggesting additional CLA carriers or compensatory regulation. As CLA knockout alone did not restore CAR-mediated killing, we explored whether insufficient binding affinity limited CAR activity. Affinity maturation was performed in silico and in vitro using yeast surface display, identifying 39 candidate mutations, although none restored cytotoxicity. We finally switched to an AdCAR strategy using anti-biotin CAR T cells combined with biotinylated anti-CLA scFv-Fc adapters. This approach enabled efficient, concentration-dependent cytotoxicity with both CLA-targeting binders. Additionally, we identified a dynamic, cell density-dependent regulation of CLA expression. Finally, glycan profiling of CLA binders further revealed broader-than-expected glycan interactions, suggesting a potentially wider definition of the CLA family. Overall, our findings establish CLA as a functional PDAC immunotherapy target while revealing unexpected complexity in its regulation and molecular presentation.

immunology↗

Small interfering RNAs are highly effective inhibitors regarding Crimean-Congo hemorrhagic fever virus replication in vitro

Crimean-Congo hemorrhagic fever virus (CCHFV) is one of the prioritized diseases of World Health Organization, considering its potential to create a public health emergency and more importantly, the absence of efficacious drugs and/or vaccines regarding treatment. The highly lethal nature characteristic to CCHFV restricts research to BSL-4 laboratories, which complicates effective research and developmental strategies. In consideration of antiviral therapies, RNA interference can be used to suppress viral replication by targeting viral genes. RNA interference uses small interfering RNAs (siRNAs) to silence genes. The aim of our study was to design siRNAs that inhibit CCHFV replication and can serve as a basis for further antiviral therapies. A549 cells were infected with CCHFV after transfection with the siRNAs. Following 72 hours, nucleic acid from the supernatant was extracted for Droplet Digital PCR analysis. Among the investigated siRNAs we identified four effective candidates against all three segments of CCHF genome: one for the S and M segments, whilst two for the L segment. Consequently, blocking any segment of CCHFV leads to changes in the virus copy number that indicates an antiviral effect of the siRNAs in vitro. The most active siRNAs were demonstrated a specific inhibitory effect against CCHFV in a dose-dependent manner. In summary, we demonstrated the ability of specific siRNAs to inhibit CCHFV replication in vitro. This promising result can be used in future anti-CCHFV therapy developments.

microbiology↗

Generative network models identify biological mechanisms of altered structural brain connectivity in schizophrenia

BackgroundAlterations in the structural connectome of schizophrenia patients have been widely characterized, but the mechanisms leading to those alterations remain largely unknown. Generative network models have recently been introduced as a tool to test the biological underpinnings of the formation of altered structural brain networks.\n\nMethodsWe evaluated different generative network models to investigate the formation of structural brain networks in healthy controls (n=152), schizophrenia patients (n=66) and their unaffected first-degree relatives (n=32), and we identified spatial and topological factors contributing to network formation. We further investigated the association of these factors to cognition and to polygenic risk for schizophrenia.\n\nResultsStructural brain networks can be best accounted for by a two-factor model combining spatial constraints and topological neighborhood structure. The same wiring model explained brain network formation for all groups analyzed. However, relatives and schizophrenia patients exhibited significantly lower spatial constraints and lower topological facilitation compared to healthy controls. The model parameter for spatial constraint was correlated with the polygenic risk for schizophrenia and predicted reduced cognitive performance.\n\nConclusionsOur results identify spatial constraints and local topological structure as two interrelated mechanisms contributing to normal brain development as well as altered connectomes in schizophrenia. Spatial constraints were linked to the genetic risk for schizophrenia and general cognitive functioning, thereby providing insights into their biological basis and behavioral relevance.

neuroscience↗