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Biology subjects

Wolf, I.

Publications and source records attributed to Wolf, I..

7 recordsLinked to original sources

Systematic functional drug testing in patient-derived models reveals ex vivo sensitivities associated with clinical outcome in rare solid tumors

Rare cancers are individually uncommon but collectively represent a substantial share of cancer burden, with limited systemic treatment options for many entities. Molecular profiling identifies targetable alterations, but actionable findings are limited and responses can vary despite a matched target. This motivates complementary approaches that directly assess tumor drug response. Here, we establish a biopsy-compatible ex vivo drug sensitivity testing platform optimized for low input and reproducibility. Patient-derived material was tested either directly or following ex vivo expansion. Functional profiling was performed within clinically relevant timelines across models from 126 patients with rare advanced solid tumors. Drug responses were consistent between model types. In most samples, we identified at least one potentially active compound, supporting feasibility at biopsy-scale. High in vitro sensitivity was associated with clinical benefit and progression-free survival. These findings support functional drug sensitivity testing as a complementary component in precision oncology for adults with rare cancers. Statement of SignificanceThis study presents a biopsy-compatible drug sensitivity testing platform for phenotype-based therapy stratification in rare cancers. It identifies actionable ex vivo drug responses and shows associations with clinical outcome in patients treated with screened therapies. These findings support functional testing as a complementary additional layer of stratification for therapeutic prioritization.

cancer biology↗

Biological insights from plasma proteomics of non-small cell lung cancer patients treated with immunotherapy

IntroductionImmune checkpoint inhibitors have made a paradigm shift in the treatment of non-small cell lung cancer (NSCLC). However, clinical response varies widely and robust predictive biomarkers for patient stratification are lacking. Here, we characterize early on-treatment proteomic changes in blood plasma to gain a better understanding of treatment response and resistance. MethodsPre-treatment (T0) and on-treatment (T1) plasma samples were collected from 225 NSCLC patients receiving PD-1/PD-L1 inhibitor-based regimens. Plasma was profiled using aptamer-based technology to quantify approximately 7000 plasma proteins per sample. Proteins displaying significant fold changes (T1:T0) were analyzed further to identify associations with clinical outcomes. Bioinformatic analyses of upregulated proteins were performed to determine potential cell origins and enriched biological processes. ResultsThe levels of 142 proteins were significantly increased in the plasma of NSCLC patients following ICI-based treatments. Soluble PD-1 exhibited the highest increase, with a positive correlation to tumor PD-L1 status. Bioinformatic analysis of the ICI monotherapy dataset revealed a set of 30 upregulated proteins that formed a single, highly interconnected network with CD8A serving as a central hub, suggesting T cell activation during ICI treatment. Notably, the T cell-related network was detected regardless of clinical benefit. Lastly, circulating proteins of alveolar origin were identified as potential biomarkers of limited clinical benefit, possibly due to a link with cellular stress and lung damage. ConclusionsOur study provides insights into the biological processes activated during ICI-based therapy, highlighting the potential of plasma proteomics to identify mechanisms of therapy resistance and potential biomarkers for outcome.

bioinformatics↗

Modeling Sepsis-Associated ARDS Using a Lung Endothelial Microphysiological System

Acute respiratory distress syndrome due to non-pulmonary causes exhibits prominent endothelial activation which is challenging to assess in critically ill patients. Preclinical in vivo models of sepsis and ARDS have failed to yield useful therapies in humans, perhaps due to interspecies differences in inflammatory responses. Use of microphysiological systems (MPS) offer improved fidelity to human biological responses and better predict pharmacological responses than traditional culture. We adapted a lung endothelial MPS based on the LumeNEXT platform to evaluate the effect of plasma from critically ill sepsis patients on endothelial permeability, adhesion molecule expression and inflammatory cytokine production. Lumens incubated with sepsis plasma exhibited areas of contraction, loss of cellular coverage, and luminal defects. Sepsis plasma-incubated lumens had significantly increased permeability compared to lumens incubated with healthy donor plasma. ICAM-1 expression increased significantly in lumens incubated with sepsis plasma compared with those incubated with healthy control plasma, while concentrations of IL-6, IL-18, and soluble VEGF-R1 increased in sepsis plasma before and after incubation in the MPS compared with healthy control plasma. Use of the lung endothelial MPS may enable interrogation of specific mechanisms of endothelial dysfunction that promote ARDS in sepsis patients.

cell biology↗

3D-Mass Spectrometry Imaging of Micro-scale 3D Cell Culture Models in Cancer Research

Three-dimensional (3D) human cell culture models have emerged as a key technology for personalized medicine and for phenotypic compound screening in more disease-like in-vitro systems. Mass spectrometry imaging (MSI) is one of the most versatile label-free techniques that enables simultaneous generation of spatial maps for multiple relevant molecules in these 3D-models. Here, we present an integrated platform for 3D-MSI of 3D-cell cultures comprising 3D-printed metal casting molds for freezing and embedding, MS imaging of 100 serial cryosections and their computational elastic 3D-reconstruction. With this platform, we monitored multiple lipids that were selectively associated with different cell-types or cell-cell interactions within 300 m-scale fibroblast and colon cancer biculture spheroids. Our findings suggest that 3D-printing-aided precise preparation of serial sections from small spheroids and visualization of marker molecules in 3D can provide a detailed overview of the cellular metabolic interplay in 3D cell culture models in cancer research and drug discovery.

cancer biology↗

Genomic alterations drive brain metastases formation in colorectal cancer: The role of IRS2

Colorectal cancer (CRC) is currently the fourth leading etiology of brain metastasis (BM). Yet, mechanisms supporting the formation of CRC BM are mostly unknown. In order to identify drivers that lead to tropism and adaptation of CRC cells to the brain environment, we analyzed an extensive genomic database, consisting of over 36,000 human CRC primary and metastasis samples. Several genomic alterations specific for BM were noted, among them increased prevalence of insulin receptor substrate 2 (IRS2) amplification, observed in 7.6% of BM, compared to only 2.9% of primary tumors or other metastatic sites (p<7E-05). This observation was validated by Immunohistochemistry studies of human clinical samples, showing increased expression of IRS2 protein in BM. IRS2 is a cytoplasmic adaptor mediating effects of insulin and IGF-1 receptors and is involved in more aggressive behavior of different cancer types. In order to study the ability of IRS2 to promote growth of CRC cells under brain microenvironment conditions, we employed an in vitro system consisting of cultured human astrocytes or their conditioned media. Indeed, IRS2-overexpressed CRC cells survived better and formed larger 3D spheres when grown in brain-mimicking conditions, while IRS2-silenced CRC cells showed a mirror image. Similarly, In vivo studies, using intracranial CRC BM mouse model, demonstrated that IRS2-overexpressed cells generated larger brain lesions, while silencing IRS2 dramatically decreased tumor outgrowth and extended survival. Transcriptomic analysis revealed enrichment of oxidative phosphorylation (OXPHOS) and Wnt/{beta}-catenin pathways by IRS2. Indeed, IRS2-expressing cells showed increased mitochondrial activity and glycolysis-independent viability. Furthermore, IRS2-expressing cells had increased {beta}-catenin transcriptional activity, and either {beta}-catenin inhibition or IRS2 inhibition in IRS2-expressing cells decreased their viability, {beta}-catenin transcriptional activity, and mitochondrial activity. These data suggest involvement of IRS2 in modulating OXPHOS through {beta}-catenin. Exploiting this mechanism as a potential vulnerability allowed us to develop novel treatment strategies against CRC BM. NT219 is a novel IRS1/2 inhibitor already being tested in clinical trials. Treatment of mice harboring CRC BM with NT219 and 5-flourouracil reduced tumor growth and prolonged mice survival. These data reveal, for the first time, the unique genomic profile of CRC BM and imply the IRS2 role in promoting CRC BM. These effects may be mediated, at least in part, by modulation of the {beta}-catenin and OXPHOS pathway. These findings may pave the way for clinical trials evaluation this novel IRS2-based strategy for the treatment of CRC BM. Accession no GSE203017 and here is the link: https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE203017

cancer biology↗

Spatial Probabilistic Mapping of Metabolite Ensembles in Mass Spectrometry Imaging

Mass spectrometry imaging (MSI) vows to enable simultaneous spatially-resolved investigation of hundreds of metabolites in tissue sections, but it still relies on poorly defined ion images for data interpretation. Here, we outline moleculaR, a computational framework (https://github.com/CeMOS-Mannheim/moleculaR) that introduces probabilistic mapping and point-for-point statistical testing of metabolites in tissue. It enables collective molecular projections and consequently spatially-resolved investigation of ion milieus, lipid pathways or user-defined biomolecular ensembles within the same image.

bioinformatics↗

Neural network-based alterations during repeated heat pain stimulation in major depression

The current study aimed to identify alterations in brain activation and connectivity related to nociceptive processing and pain sensitization in major depressive disorder (MDD), using repeated heat pain stimulation during functional magnetic resonance imaging (fMRI) in 37 MDD patients and 33 healthy controls. Regional activation did not differ between groups, but functional connectivity was significantly decreased in MDD in a neural network connecting frontal, temporal and occipital areas (family-wise error (FWE)-corrected pFWE = 0.045). Supplemental analyses suggested a significant association between network connectivity and trait neuroticism (p = 0.007) but not with the clinical state or familiar risk of MDD (all p values > 0.13). Our data relate a network-based phenotype for altered pain processing and antinociceptive control to MDD and encourage future studies on the shared intermediate neural psychological risk architecture of MDD and chronic pain.

neuroscience↗