Multi-resolution deep learning characterizestertiary lymphoid structures in solid tumors

van Rijthoven, M.; Obahor, S.; Pagliarulo, F.; van den Broek, M.; Schraml, P.; Moch, H.; van der Laak, J.; Ciompi, F.; Silina, K.

doi:10.1101/2023.04.03.535381

bioRxiv · 10.1101/2023.04.03.535381

Multi-resolution deep learning characterizestertiary lymphoid structures in solid tumors

van Rijthoven, M.·Obahor, S.·Pagliarulo, F.·van den Broek, M.·Schraml, P.·Moch, H.·van der Laak, J.·Ciompi, F.·Silina, K.

View original source ↗Export metadata ↓

Abstract

Tertiary lymphoid structures (TLSs) are dense accumulations of lym-phocytes in inflamed peripheral tissues, including cancer, and are associated with improved survival and response to immunotherapy in various solid tumors. Histological TLS quantification has been pro-posed as a novel predictive and prognostic biomarker, but lack of standardized methods of TLS characterization hampers assessment of TLS densities across different patients, diseases, and clinical centers. We introduce a novel approach based on HookNet-TLS, a multi-resolution deep learning model, for automated and unbiased TLS quantification and identification of germinal centers in routine hema-toxylin and eosin stained digital pathology slides. We developed a HookNet-TLS model using n=1019 manually annotated TCGA slides from clear cell renal cell carcinoma, muscle-invasive blad-der cancer, and lung squamous cell carcinoma. We show that HookNet-TLS automates TLS quantification with a human-level performance and demonstrates prognostic associations similar to visual assessment. We made HookNet-TLS publicly available to aid the adoption of objective TLS assessment in routine pathology.

Source connections

Published article ↗

Explore related subjects

pathology Preprint

Keep this discovery

Explore connections, maps & timelines

BibTeX RIS

van Rijthoven, M., Obahor, S., Pagliarulo, F., van den Broek, M., Schraml, P., Moch, H., van der Laak, J., Ciompi, F., Silina, K.. 2023-04-03. Multi-resolution deep learning characterizestertiary lymphoid structures in solid tumors. https://doi.org/10.1101/2023.04.03.535381

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related preprints

bioRxiv2026

NAE1-Dependent Protein Neddylation Preserves Endothelial Identity and Vascular Integrity

Background: Endothelial dysfunction is a central driver of cardiovascular and inflammatory diseases, yet the post-translational mechanisms that preserve endothelial homeostasis remain incompletely understood. Protein neddylation, the covalent conjugation of a ubiquitin-like modifier, regulates diverse cellular processes, yet its physiological role in the vascular endothelium remains unknown. This study investigated whether protein neddylation is required to preserve endothelial identity and vascular homeostasis. Methods: We generated tamoxifen-inducible endothelial-specific Nae1 knockout mice to inhibit neddylation and combined bulk RNA sequencing, single-cell and single-nucleus transcriptomics, quantitative proteomics, biochemical analyses, and gain- and loss-of-function approaches to define the role of endothelial neddylation in vascular homeostasis and inflammatory injury. Results: Endothelial-specific Nae1 deletion caused rapid mortality associated with vascular leakage, platelet accumulation, inflammation, and multi-organ injury. Multi-omics analyses demonstrated profound loss of endothelial identity, characterized by suppression of core endothelial programs and activation of inflammatory, procoagulant, and pyroptotic pathways. Single-cell analyses revealed progressive endothelial dysfunction culminating in depletion of the endothelial population and remodeling of the vascular niche. Mechanistically, endothelial neddylation deficiency activated gasdermin D (GSDMD)- and gasdermin E (GSDME)-dependent pyroptosis, whereas dual inhibition of GSDMD and GSDME markedly attenuated inflammatory transcriptomic remodeling, vascular injury, hepatocyte death, immune cell infiltration, and platelet accumulation. Translational analyses demonstrated reduced endothelial neddylation in experimental endotoxemia and decreased expression of neddylation pathway components in human atherosclerosis and COVID-19 datasets. Conversely, restoration of endothelial neddylation partially reversed inflammatory endothelial transcriptomic reprogramming in vivo. Conclusions: NAE1-dependent protein neddylation is an essential regulator of endothelial identity and vascular integrity. Loss of endothelial neddylation promotes gasdermin-dependent pyroptosis and thrombo-inflammatory vascular injury, whereas restoration of the neddylation pathway mitigates inflammatory endothelial dysfunction. These findings identify endothelial neddylation as a fundamental mechanism maintaining vascular homeostasis and a potential therapeutic target for cardiovascular and inflammatory diseases.

pathology↗

bioRxiv2024

Discovering cancer stem-like cells using Spatial transcriptomic analysis: Nuclear factor I X as a novel therapeutic target for gastric cancer

BackgroundGastric cancer (GC) is characterized by significant intratumoral heterogeneity and stem cells presenting as promising therapeutic targets. Despite advancements in spatial transcriptome analysis, unexplored targets for addressing cancer stemness remain unknown. This study aims to identify Nuclear Factor IX (NFIX) as a critical regulator of cancer stemness in GC and evaluate its clinicopathological significance and function. MethodsSpatial transcriptome analysis was conducted on GC. NFIX expressions correlation with clinicopathological factors and prognosis was assessed through immunostaining in 127 GC cases. Functional analyses in cancer cell lines validated these findings. ResultsSpatial transcriptome analysis stratified GC tissues based on genetic profiles, pinpointing CSC-like cells and further refined the classification to identify and highlight the NFIXs significance, validated by Monocle 3 and CytoTRACE analyses. Knockdown experiments in cancer cell lines demonstrated the involvement of NFIX in cancer cell proliferation and kinase activity. ConclusionsThis study underscores spatial transcriptome analysiss role in refining GC tissue classification and identifying therapeutic targets, highlighting NFIX as pivotal. NFIX expression correlates with poor prognosis and drives GC progression, suggesting its potential as a novel therapeutic target for personalized GC therapies.

pathology↗

bioRxiv2024

Uncovering microstructural architecture from histology

Mapping the brains fiber network is crucial for understanding its function and malfunction, but resolving nerve trajectories over large fields of view is challenging. Here, we show that computational scattered light imaging (ComSLI) can map fiber networks in histology independent of sample preparation, also in formalin-fixed paraffin-embedded (FFPE) tissues including whole human brain sections. We showcase this method in new and archived, animal and human brain sections, for different sample preparations (in paraffin, deparaffinized, various stains, unstained fresh-frozen). We convert microscopic orientations to microstructure-informed fiber orientation distributions (FODs). Adapting tractography tools from diffusion magnetic resonance imaging (dMRI), we trace axonal trajectories revealing white and gray matter connectivity. These allow us to identify altered microstructure or deficient tracts in demyelinating or neurodegenerating pathology, and to show key advantages over dMRI, polarization microscopy, and structure tensor analysis. Finally, we map fibers in non-brain tissues, including muscle, bone, and blood vessels, unveiling the tissues function. Our cost-effective, versatile approach enables micron-resolution studies of intricate fiber networks across tissues, species, diseases, and sample preparations, offering new dimensions to neuroscientific and biomedical research.

pathology↗