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Harder, O.

Publications and source records attributed to Harder, O..

2 recordsLinked to original sources

Targeting AXL Overcomes Adaptive Resistance to KRAS Inhibition in KRAS-Driven Cancer

Direct KRAS inhibitors have established mutant KRAS as a clinically actionable target, yet adaptive resistance remains a major barrier to durable responses. To identify therapeutically actionable resistance mechanisms, we performed an unbiased in vivo CRISPR activation screen in an autochthonous lung adenocarcinoma model, identifying the receptor tyrosine kinase AXL as a dominant adaptive resistance driver. Pharmacologic AXL inhibition enhanced the efficacy of both allele-specific inhibition and the RAS(ON) multi-selective inhibitor daraxonrasib across lung and pancreatic cancer models, resulting in deeper and more durable suppression of MAPK signaling and improved tumor control. Beyond tumor-intrinsic effects, combined KRAS and AXL inhibition remodeled the tumor immune microenvironment, promoting an IFN{gamma}-responsive program, increased recruitment of cytotoxic T cells and sensitization to FAS-mediated apoptosis. Collectively, our findings identify AXL as a convergence point for adaptive resistance to KRAS inhibition and provide a mechanistically informed combination strategy to extend the durability of KRAS-directed therapies. Statement of SignificanceAn unbiased in vivo functional (CRISPR activation) screen identifies AXL as a convergence point for adaptive resistance to KRAS inhibition. By integrating adaptive response to KRAS inhibition with anti-tumor immunity, AXL represents a mechanistically actionable vulnerability whose inhibition deepens and prolongs responses to both allele-specific and pan-KRAS-targeted therapies.

cancer biology↗

Mathematical Modeling Identifies the Role of Adaptive Immunity as a Key Controller of Respiratory Syncytial Virus (RSV) Titer in Cotton Rats

Respiratory syncytial virus (RSV) is a common virus that can have varying effects ranging from mild cold-like symptoms to mortality depending on the age and immune status of the individual. We combined mathematical modeling using ordinary differential equations (ODEs) with measurement of RSV infection kinetics in primary well differentiated human airway epithelial (HAE) cultures in vitro and in immunocompetent and immunosuppressed cotton rats to glean mechanistic details that underlie RSV infection kinetics in the lung. Quantitative analysis of viral titer kinetics in our mathematical model showed that the elimination of infected cells by the adaptive immune response generates unique RSV titer kinetic features including a faster time scale of viral titer clearance than viral production, and a monotonic decrease in the peak RSV titer with decreasing inoculum dose. Parameter estimation in the ODE model using a non-linear mixed effects approach revealed a very low rate (average single cell lifetime > 10 days) of cell lysis by RSV before the adaptive immune response is initiated. Our model predicted negligible changes in the RSV titer kinetics on earlier days (< 5 d.p.i) but a slower decay in RSV titer at later days (>5 d.p.i) in immunosuppressed cotton rats compared to that in non-suppressed cotton rats in silico. These predictions were in excellent agreement with the experimental results. Our combined approach quantified the importance of the adaptive immune response in suppressing RSV infection in cotton rats, which could be useful in testing RSV vaccine candidates.\n\nImportanceA major difficulty in developing vaccines against RSV infection is our rudimentary understanding of the mechanisms that underlie RSV infection. We addressed this challenge by developing a mechanistic computational model with predictive powers for describing RSV infection kinetics in cotton rats. The model was constructed synergistically with in vitro and in vivo measurements. The combined framework determined an important role for CD8+ T cells responses in reducing RSV titers in cotton rats. The framework can be used to design future experiments to elucidate mechanisms underlying RSV infection and test outcomes for potential vaccine candidates. In addition, estimation of the model parameters provides quantitative values for parameters of biological and clinical interest such as the replication rate of RSV, the death rate of infected cells, and the average number of new infections initiated by a single infected cell.

microbiology↗