Biology subjects

Swanson, N.

Publications and source records attributed to Swanson, N..

3 recordsLinked to original sources

bioRxiv2026

TALAVE in Breast Cancer: BRCA1/2 Mutation-Dependent Immune Remodeling after PARP Inhibition with Limited Checkpoint Engagement

PARP inhibitors (PARPi) drive efficacy in BRCA-mutant breast cancer (BC) via DNA damage-induced synthetic lethality and immune activation, supporting their combination with immune checkpoint blockade. In the TALAVE study, patients with advanced BRCA-mutant or wild-type (WT) HER2-negative BC received talazoparib followed by talazoparib plus avelumab. Only BRCA-mutant BC responded clinically. Serial multi-omic profiling revealed BRCA-dependent tumor-immune remodeling, including sustained H2AX-pTBK1 signaling with increased CD8+ T cells, tumor cell depletion, and enrichment of CD163+ macrophages. In contrast, BRCA-WT tumors remained compact and immunosuppressed with reduced T cells after therapy. PD-1+ T cells localized to CD4+-rich neighborhoods and correlated with longer progression-free survival in BRCA-mutant tumors. However, PD-L1+ cells were rapidly depleted or confined to immune-excluded regions, spatially segregating them from PD-1+ T cells, impairing effective checkpoint blockade. These findings suggest limited benefit of PD-1/PD-L1 blockade in augmenting PARPi activity and highlight the need for alternative strategies to sustain PARPi-induced immunity.

cancer biology↗

bioRxiv2025

Predicting microsatellite instability from whole slide images using texture features

Identifying MSI in whole slide images (WSIs), one of the most widely used diagnostic imaging formats, is of great importance and in demand. In this study we employed color-based texture features to predict MSI on both a tile and sample based level. We found that within cohorts of hematoxylin and eosin (H&E) stained WSIs, texture morphology is able to predict MSI on a tile level with an AUC of up to 0.95 and on a sample level with an AUC of up to 0.98. This runs in contrast to other methods for predicting MSI in H&E WSIs which either utilized artificial intelligence based models, or achieved lower accuracy scores. Our results demonstrate that texture morphology is a significantly notable factor when it comes to identifying MSI in H&E WSIs, and should be used when constructing future models for MSI identification in a clinical setting.

bioinformatics↗

bioRxiv2024

Phylogenetic mapping of sleep loss in wild-caught cavefish

Sleep is an evolutionarily ancient and nearly universal behavior throughout the animal kingdom. Multiple cave-dwelling populations of the Mexican tetra, Astyanax mexicanus, have converged on sleep loss compared to river-dwelling surface fish. However, sleep has not been assessed in the vast majority of the 34 known A. mexicanus cave populations. Moreover, whether cavefish sleep less than surface individuals in their natural habitats is currently unknown. Analyzing the distribution of sleep loss and its relationship with other regressive traits in a phylogenetic framework is critical to inform the selective pressures across the different lineages. We measured sleep and locomotor activity in 15 distinct populations of A. mexicanus, including lineages that are broadly representative of the 34 cavefish populations identified to date. Sleep was drastically reduced in all cave and hybrid populations that were tested. A subset of caves contain hybrid populations of A. mexicanus, which show a broad range of eye and pigmentation phenotypes, yet have evolved near-complete loss of sleep. Mapping behavioral changes onto the phylogeny of A. mexicanus populations revealed that loss of sleep and elevated locomotor activity have evolved at least three times. Analysis of sleep in the wild confirms that the sleep loss phenotype observed in lab-reared fish is also present in the natural environment. Together, these findings reveal deep evolutionary convergence on sleep loss in cavefish and provide evidence for sleep loss as a primary trait contributing to cave adaptation.

evolutionary biology↗