Biology subjects

Zamloot, V.

Publications and source records attributed to Zamloot, V..

3 recordsLinked to original sources

bioRxiv2026

Morphological fingerprints enable machine learning based inference of neuroblastoma cell states without transcriptomics

Inference of cancer cell states is essential for understanding oncogenic mechanisms and predicting clinical outcomes, yet current reliance on transcriptomic profiling limits scalability and real-time monitoring. Here, we show that cell morphology provides a low-dimensional, observable representation of cellular identity and its dynamics. Using neuroblastoma (NB) as a model system, we establish a machine learning- morphology profiling framework that infers adrenergic (ADRN) and mesenchymal (MES) cell states directly from high-dimensional morphological fingerprints without reliance on transcriptomic measurements. By benchmarking against single-cell RNA sequencing (scRNA-seq), we demonstrate that morphology-defined states closely align with transcriptomic profiles at single-cell resolution. We further show that cell state transitions are represented as continuous trajectories within a morphology-defined state space. Perturbations targeting distinct regulatory layers, including ROCK signaling and epigenetic regulation via EZH2, drive convergent trajectories along a shared phenotypic axis. Together, these results establish cell morphology as a scalable and non-destructive readout of cell state with machine learning providing a unified framework for high-throughput phenotyping and real-time tracking of cancer cell state plasticity.

cell biology↗

bioRxiv2024

Differential cell-ECM interaction of rhabdomyosarcoma subtypes regulated by PAX3-FOXO1

Rhabdomyosarcoma (RMS) is the most common childhood soft tissue sarcoma, with two subtypes: Fusion-positive RMS (FPRMS), which has the PAX3-FOXO1 fusion gene, and fusion-negative RMS (FNRMS). Despite their distinct characteristics, treatments mainly rely on conventional chemotherapies without considering these differences. This study highlights that FNRMS cells exhibit significantly heightened interaction with the extracellular matrix (ECM) compared to FPRMS cells. Using single-cell RNA sequencing of skeletal muscle tissues and RNA sequencing of RMS samples, we identified the upregulation of genes related to cell-ECM interaction and TGF{beta} signaling in FNRMS compared to FPRMS. We also confirmed enhanced cell-ECM interaction stimulated by TGF{beta} signaling in FNRMS cells, using confocal reflection microscopy to monitor dynamic cell-ECM interaction and a live-cell sensor to quantitatively assess TGF{beta} signaling activity. Additionally, we discovered that the PAX3-FOXO1 fusion gene, characteristic of FPRMS, stimulated nitric oxide synthesis, which suppresses TGF{beta} signaling and reduces cell-ECM interaction. These findings suggest that PAX3-FOXO1 determines the diminished cell-ECM interactions in FPRMS. Experimental data show higher sensitivity of FNRMS to cell-ECM interaction disruption and TGF{beta} inhibition. Furthermore, the diminished cell-ECM interaction in FPRMS, allowing cells to survive in the ectopic environment through circulation, may partly explain its higher metastatic potential compared to FNRMS.

cell biology↗

bioRxiv2020

Restructuring of the Immune Contexture Improves Checkpoint Blockade Efficacy in Murine Lung Cancer

Therapeutic options for non-small cell lung cancer (NSCLC) treatment have changed dramatically in recent years with the advent of novel immunotherapeutic approaches. Among these, immune checkpoint blockade (ICB), using monoclonal antibodies, has shown tremendous promise in a small proportion of patients. In order to better predict patients that will respond to ICB treatment, biomarkers such as tumor-associated CD8+ T cell frequency, tumor checkpoint protein status and mutational burden have been utilized, however, with mixed success. In this study, we hypothesized that significantly altering the suppressive tumor immune landscape in NSCLC could potentially improve ICB efficacy. Using sub-therapeutic doses of our Salmonella typhimurium-based therapy targeting the suppressive molecule indoleamine 2,3-dioxygenase (shIDO-ST) in tumor-bearing mice, we observed dramatic changes in immune subset phenotypes that included increases in antigen presentation markers, decreased regulatory T cell frequency and overall reduced checkpoint protein expression. Combination shIDO-ST treatment with anti-PD-1/CTLA-4 antibodies enhanced tumor growth control, compared to either treatment alone, which was associated with a significant intratumoral influx of CD8+ and CD4+ T lymphocytes. These results suggest that the success of ICB therapy may be more accurately predicted by taking into account multiple factors such as potential for antigen presentation and frequency of suppressive immune subsets in addition to markers already being considered. Alternatively, combination treatment with agents such as shIDO-ST could be used to create a more conducive tumor microenvironment for improving response rates to immunotherapy.

cancer biology↗