Biology subjects

Zijlstra, A.

Publications and source records attributed to Zijlstra, A..

5 recordsLinked to original sources

bioRxiv2024

Extracellular Vesicles heterogeneity through the lens of multiomics

Extracellular vesicles (EVs) are heterogenous in size, biogenesis, cargo and function. Beside small EVs, aggressive tumor cells release a population of particularly large EVs, namely large oncosomes (LO). This study provides the first resource of label-free quantitative proteomics of LO and small EVs obtained from distinct cancer cell types (prostate, breast, and glioma). This dataset was integrated with a SWATH Proteomic assay on LO, rigorously isolated from the plasma of patients with metastatic prostate cancer (PC). Proteins enriched in LO, which were identified also at the RNA level, and found in plasma LO significantly correlated with PC progression. Single EV RNA-Seq of the PC cell-derived LO confirmed some of the main findings from the bulk RNA-Seq, providing first evidence that single cell technologies can be successfully applied to EVs. This multiomics resource of cancer EVs can be leveraged for developing a multi-analyte approach for liquid biopsy.

cancer biology↗

bioRxiv2024

Secreted exosomes induce filopodia formation

Filopodia are dynamic adhesive cytoskeletal structures that are critical for directional sensing, polarization, cell-cell adhesion, and migration of diverse cell types. Filopodia are also critical for neuronal synapse formation. While dynamic rearrangement of the actin cytoskeleton is known to be critical for filopodia biogenesis, little is known about the upstream extracellular signals. Here, we identify secreted exosomes as potent regulators of filopodia formation. Inhibition of exosome secretion inhibited the formation and stabilization of filopodia in both cancer cells and neurons and inhibited subsequent synapse formation by neurons. Rescue experiments with purified small and large extracellular vesicles (EVs) identified exosome-enriched small EVs (SEVs) as having potent filopodia-inducing activity. Proteomic analyses of cancer cell-derived SEVs identified the TGF-{beta} family coreceptor endoglin as a key SEV-enriched cargo that regulates filopodia. Cancer cell endoglin levels also affected filopodia-dependent behaviors, including metastasis of cancer cells in chick embryos and 3D migration in collagen gels. As neurons do not express endoglin, we performed a second proteomics experiment to identify SEV cargoes regulated by endoglin that might promote filopodia in both cell types. We discovered a single SEV cargo that was altered in endoglin-KD cancer SEVs, the transmembrane protein Thrombospondin Type 1 Domain Containing 7A (THSD7A). We further found that both cancer cell and neuronal SEVs carry THSD7A and that add-back of purified THSD7A is sufficient to rescue filopodia defects of both endoglin-KD cancer cells and exosome-inhibited neurons. We also find that THSD7A induces filopodia formation through activation of the Rho GTPase, Cdc42. These findings suggest a new model for filopodia formation, triggered by exosomes carrying THSD7A.

cell biology↗

bioRxiv2023

Automated tumor immunophenotyping predicts clinical benefit from anti-PD-L1 immunotherapy

BackgroundCancer immunotherapy has transformed the clinical approach to patients with malignancies as profound benefits can be seen in a subset of patients. To identify this subset, biomarker analyses increasingly focus on phenotypic and functional evaluation of the tumor microenvironment (TME) to determine if density, spatial distribution, and cellular composition of immune cell infiltrates can provide prognostic and/or predictive information. Attempts have been made to develop standardized methods to evaluate immune infiltrates in the routine assessment of certain tumor types; however, broad adoption of this approach in clinical decision-making is still missing. MethodsWe developed approaches to categorize solid tumors into "Desert", "Excluded" and "Inflamed" types according to the spatial distribution of CD8+ immune effector cells to determine the prognostic and/or predictive implications of such labels. To overcome the limitations of this subjective approach we incrementally developed four automated analysis pipelines of increasing granularity and complexity for density and pattern assessment of immune effector cells. ResultsWe show that categorization based on "manual" observation is predictive for clinical benefit from anti-programmed cell death ligand-1 (PD-L1) therapy in two large cohorts of patients with non-small cell lung cancer (NSCLC) or triple-negative breast cancer (TNBC). For the automated analysis we demonstrate that a combined approach outperforms individual pipelines and successfully relates spatial features to pathologist-based read-outs and patient response to therapy. ConclusionsOur findings suggest tumor immunophenotype (IP) generated by automated analysis pipelines should be evaluated further as potential predictive biomarkers for cancer immunotherapy. What is already known on this topicClinical benefit from checkpoint inhibitor-targeted therapies is realized only in a subset of patients. Robust biomarkers to identify patients who may respond to such therapies are needed. What this study addsWe have developed manual and automated approaches to categorize tumors into immunophenotypes based on the spatial distribution of CD8+ T effector cells that predict clinical benefit from anti-PD-L1 immunotherapy for patients with advanced non-small cell lung cancer or triple-negative breast cancer. How this study might affect research, practice or policyTumor immunophenotypes should be further validated as predictive biomarker for checkpoint inhibitor-targeted therapies in prospective clinical studies.

pathology↗

bioRxiv2022

EV Fingerprinting: Resolving extracellular vesicle heterogeneity using multi-parametric flow cytometry

Mammalian cells release a heterogeneous array of extracellular vesicles (EVs) that impact human biology by contributing to intercellular communication. To resolve EV heterogeneity and define the EV populations associated with specific biological processes, we developed a method named "EV Fingerprinting" that discerns distinct vesicle populations using dimensional reduction of multi-parametric data collected by quantitative single-EV flow cytometry. After validating this method against synthetic standards, the EV Fingerprinting analysis of highly purified EVs enabled a much more granular resolution of biochemically distinct EV populations than previously established methods. The analysis of EVs produced after molecular perturbation of EV biogenesis through ablation of the GTPase Rab27a and overexpression of the tetraspanin CD63 revealed that EV Fingerprinting reflects the molecular state of a cell. Subsequent analysis of human plasma demonstrates the capacity of EV Fingerprinting to resolve EV populations in complex biological samples and detect tumor-cell derived EVs.

cell biology↗

bioRxiv2019

Comprehensive palmitoyl-proteomic analysis identifies distinct protein signatures for large and small cancer-derived extracellular vesicles

Extracellular vesicles (EVs) are membrane-enclosed particles that play an important role in cancer progression and have emerged as a promising source of circulating biomarkers. Protein S-acylation, also known as palmitoylation, has been proposed as a post-translational mechanism that modulates the dynamics of EV biogenesis and protein cargo sorting. However, technical challenges have limited large-scale profiling of the whole palmitoyl-proteins of EVs. We successfully employed a novel approach that combines low-background acyl-biotinyl exchange (LB-ABE) with label-free proteomics to analyze the palmitoyl proteome of large EVs (L-EVs) and small EVs (S-EVs) from prostate cancer cells. Here we report the first palmitoyl-protein signature of EVs, and demonstrate that L- and S-EVs harbor proteins associated with distinct biological processes and subcellular origin. We identified STEAP1, STEAP2, and ABBC4 as prostate cancer-specific palmitoyl proteins enriched in both EV populations in comparison with the originating cell lines. Importantly, the presence of the above proteins in EVs was significantly reduced upon inhibition of palmitoylation in the producing cells. These results suggest that palmitoylation may be involved in the differential sorting of proteins to distinct EV populations and allow for better detection of disease biomarkers.

cancer biology↗