Biology subjects

Ijsselsteijn, M. E.

Publications and source records attributed to Ijsselsteijn, M. E..

6 recordsLinked to original sources

bioRxiv2024

PENGUIN: A rapid and efficient image preprocessing tool for multiplexed spatial proteomics

Multiplex spatial proteomic methodologies can provide a unique perspective on the molecular and cellular composition of complex biological systems. Several challenges are associated to the analysis of imaging data, in particular regarding the normalization of signal-to-noise ratios across images and background noise subtraction. However, straightforward and user-friendly solutions for denoising multiplex imaging data that are applicable to large datasets are still lacking. We have developed PENGUIN -Percentile Normalization GUI Image deNoising: a rapid and efficient image preprocessing tool for multiplexed spatial proteomics. In comparison to existing approaches, PENGUIN stands out by eliminating the need for manual annotation or machine learning model training. It effectively preserves signal intensity differences and reduces noise, thereby enhancing downstream tasks like cell segmentation and phenotyping. PENGUINs simplicity, speed, and user-friendly interface, deployed both as script and as a Jupyter notebook, facilitate parameter testing and image processing. We illustrate the effectiveness of PENGUIN by comparing it with conventional image processing techniques and solutions tailored for multiplex imaging data. This comparison underscores PENGUINs capability to produce high-quality imaging data efficiently and consistently.

bioinformatics↗

bioRxiv2023

Multimodal profiling of chordoma immunity reveals distinct immune contextures

Chordomas are cancers from the axial skeleton presenting immunological hallmarks of unknown significance. In recent years, some clinical trials demonstrated that chordomas can respond to immunotherapy. We present a comprehensive characterisation of immunological features of 76 chordomas through application of a multimodal approach comprising transcriptional profiling, multidimensional immunophenotyping and TCR profiling. Chordomas generally presented an immune "hot" microenvironment in comparison to other sarcomas, as indicated by the immunologic constant of rejection transcriptional signature. We identified two distinct groups of chordomas based on T cell infiltration. The highly infiltrated group was further characterised by high dendritic cell infiltration and the presence of multicellular immune aggregates in tumours, whereas low T cell infiltration was associated with lower overall cell densities of immune and stromal cells. Interestingly, patients with higher T cell infiltration displayed a more pronounced clonal enrichment of the T cell receptor repertoire compared to those with low T cell counts. Furthermore, we observed that the majority of chordomas maintained HLA class I expression. Our findings shed light on the natural immunity against chordomas. Understanding their immune landscape could guide the development and application of immunotherapies in a tailored manner, ultimately leading to an improved clinical outcome for chordoma patients.

cancer biology↗

bioRxiv2023

Integration of Mass Cytometry and Mass Spectrometry Imaging for Spatially Resolved Single Cell Metabolic Profiling

Integration of spatial omics technologies can provide important insights into the biology of tissues. We combined mass spectrometry imaging-based metabolomics and imaging mass cytometry-based immunophenotyping on the same single tissue section to reveal metabolic heterogeneity within tissues and its association with specific cell populations like cancer cells or immune cells. This approach has the potential to greatly increase our understanding of tissue-level interplay between metabolic processes and their cellular components.

cancer biology↗

bioRxiv2022

Functional precision profiling reveals non-mutational rewiring of kinase signaling networks in colorectal cancer

BackgroundDespite major advances in the development of targeted therapies, precision (immuno)oncology approaches for patients with colorectal cancer continue to lag behind other solid cancers. Functional precision oncology - a strategy that is based on perturbing primary tumor cells from cancer patients with drugs - could provide an alternate road forward to personalize treatment. MethodsWe extend here the functional precision oncology paradigm to measuring phosphoproteome landscapes using patient-derived organoids (PDOs). We first employed steady-state multi-omics (exome sequencing, RNA sequencing, and proteomics) and single-cell characterization of the PDOs. The PDOs were then perturbed with kinase inhibitors (MEKi, PI3Ki, mTORi, TBKi, BRAFi, and TAKi), and large-scale phosphoproteomics profiling using data-independent acquisition was carried out. Further, we used imaging mass-cytometry-based single-cell proteomic profiling of the primary tumors to characterize cellular composition of the tumor-microenvironment (TME) and to quantify heterocellular signaling crosstalk. ResultsWe show that kinase inhibitors induce profound off-target effects resulting in a crosstalk with oncogenic and immune-related pathways. Reconstruction of the topologies of the kinase networks revealed that the patient-specific rewiring of the central EGFR-RAS-MAPK network is unaffected by mutations. Moreover, we show non-genetic heterogeneity of the PDOs and patient- and inhibitor-specific upregulation of stemness and differentiation genes by kinase inhibitors. We complemented our functional profiling by spatial proteomics profiling of the primary tumors using imaging mass cytometry. We quantify spatial heterocellular crosstalk and tumor-immune cell interactions, showing an avoidance of PD1+ immune cells and PD-L1+ tumor cells. ConclusionsCollectively, we provide a multi-modal framework for inferring tumor cell intrinsic signaling and external signaling from the TME to inform precision (immuno)-oncology in colorectal cancer.

cancer biology↗

bioRxiv2021

γδ T cells are effectors of immune checkpoint blockade in mismatch repair-deficient colon cancers with antigen presentation defects

DNA mismatch repair deficient (MMR-d) cancers present an abundance of neoantigens that likely underlies their exceptional responsiveness to immune checkpoint blockade (ICB)1,2. However, MMR-d colon cancers that evade CD8+ T cells through loss of Human Leukocyte Antigen (HLA) class I-mediated antigen presentation3-6, frequently remain responsive to ICB7 suggesting the involvement of other immune effector cells. Here, we demonstrate that HLA class I-negative MMR-d cancers are highly infiltrated by {gamma}{delta} T cells. These {gamma}{delta} T cells are mainly composed of V{delta}1 and V{delta}3 subsets, and express high levels of PD-1, activation markers including cytotoxic molecules, and a broad repertoire of killer-cell immunoglobulin-like receptors (KIRs). In vitro, PD-1+ {gamma}{delta} T cells, isolated from MMR-d colon cancers, exhibited a cytolytic response towards HLA class I-negative MMR-d colon cancer cell lines and {beta}2-microglobulin (B2M)-knockout patient-derived tumor organoids (PDTOs), which was enhanced as compared to antigen presentation-proficient cells. This response was diminished after blocking the interaction between NKG2D and its ligands. By comparing paired tumor samples of MMR-d colorectal cancer patients obtained before and after dual PD-1 and CTLA-4 blockade, we found that ICB profoundly increased the intratumoral frequency of {gamma}{delta} T cells in HLA class I-negative cancers. Taken together, these data indicate that {gamma}{delta} T cells contribute to the response to ICB therapy in patients with HLA class I-negative, MMR-d colon cancers, and illustrate the potential of {gamma}{delta} T cells in cancer immunotherapy.

cancer biology↗

bioRxiv2020

Semi-automated background removal limits loss of data and normalises the images for downstream analysis of imaging mass cytometry data

Imaging mass cytometry (IMC) allows the detection of multiple antigens (approximately 40 markers) combined with spatial information, making it a unique tool for the evaluation of complex biological systems. Due to its widespread availability and retained tissue morphology, formalin-fixed, paraffin-embedded (FFPE) tissues are often a material of choice for IMC studies. However, antibody performance and signal-to-noise ratio can differ considerably between FFPE tissues as a consequence of variations in tissue processing, including fixation. We investigated the effect of immunodetection-related signal intensity fluctuations on IMC analysis and phenotype identification in a cohort of twelve colorectal cancer tissues. Furthermore, we explored different normalisation strategies and propose a workflow to normalise IMC data by semi-automated background removal, using publicly available tools. This workflow can be directly applied to previously obtained datasets and considerably improves the quality of IMC data, thereby supporting the analysis and comparison of multiple samples.

immunology↗