Magdalena Matusiak

All Publications

• Spatially organized inflammatory myeloid-CD8+ T cell aggregates linked to Merkel-cell Polyomavirus driven Reorganization of the Tumor Microenvironment. bioRxiv : the preprint server for biology Haist, M., Matusiak, M., Tan, Y., Zimmer, S., Stege, H., Kempchen, T. N., Mitschke, S., Chu, P., Weidenthaler-Barth, B., Barlow, G. L., Rogall, F., Gonzalez, A. D., Baertsch, M. A., Albertini, S., Gariglio, M., Borgogna, C., Goltsev, Y., Grabbe, S., Hickey, J. W., Nolan, G. P. 2025

  Abstract

  Merkel cell carcinoma (MCC) is an aggressive skin cancer with high propensity for metastasis, caused by Merkel-cell-polyomavirus (MCPyV), or chronic UV-light-exposure. How MCPyV spatially modulates immune responses within the tumor microenvironment and how such are linked to patient outcomes remains unknown. We interrogated the cellular and transcriptional landscapes of 60 MCC-patients using a combination of multiplex proteomics, in-situ RNA-hybridization, and spatially oriented transcriptomics. We identified a spatial co-enrichment of activated CD8+ T-cells and CXCL9+PD-L1+ macrophages at the invasive front of virus-positive MCC. This spatial immune response pattern was conserved in another virus-positive tumor, HPV+ head-and-neck cancer. Importantly, we show that virus-negativity correlated with high risk of metastasis through low CD8+ T-cell infiltration and the enrichment of cancer-associated-fibroblasts at the tumor boundary. By contrast, responses to immune-checkpoint blockade (ICB) were independent of viral-status but correlated with the presence of a B-cell-enriched spatial contexts. Our work is the first to reveal distinct immune-response patterns between virus-positive and virus-negative MCC and their impact on metastasis and ICB-response.

  View details for DOI 10.1101/2025.06.06.657162

  View details for PubMedID 40501860

  View details for PubMedCentralID PMC12157451

• TissueViewer: A Web-Based Multiplexed Image Viewer. Bioinformatics (Oxford, England) van IJzendoorn, D. G., Matusiak, M., West, R., van de Rijn, M. 2025

  Abstract

  Datasets generated by spatial biology techniques such as multiplex immunofluorescence staining or spatial transcriptomics profiling of histologic sections carry a tremendous wealth of information. Several commercial platforms exist that can simultaneously acquire 1-1000 distinct marker signals (e.g., MIBI, CODEX, Orion, Nanostring CosMX SMI, Vizgen). However, due to the large size of these datasets, their viewing and sharing are slow, laborious, and require extensive computational resources.To overcome these challenges, we developed TissueViewer, an easy to setup and use web-based viewer designed to deliver high-resolution images over the internet with low bandwidth requirements and at high speed.TissueViewer is available on GitHub and can be used on the TissueViewer.org platform, where readers can upload their own data with a limit of 50 GB to share with colleagues.Supplementary data are available at Bioinformatics online.

  View details for DOI 10.1093/bioinformatics/btaf246

  View details for PubMedID 40279289

• Spatially Segregated Macrophage Populations Predict Distinct Outcomes In Colon Cancer. Cancer discovery Matusiak, M., Hickey, J. W., van IJzendoorn, D. G., Lu, G., Kidzinski, L., Zhu, S., Colburg, D. R., Luca, B., Phillips, D. J., Brubaker, S. W., Charville, G. W., Shen, J., Loh, K. M., Okwan-Duodu, D. K., Nolan, G. P., Newman, A. M., West, R. B., van de Rijn, M. 2024

  Abstract

  Tumor-associated macrophages are transcriptionally heterogeneous, but the spatial distribution and cell interactions that shape macrophage tissue roles remain poorly characterized. Here, we spatially resolve five distinct human macrophage populations in normal and malignant human breast and colon tissue and reveal their cellular associations. This spatial map reveals that distinct macrophage populations reside in spatially segregated micro-environmental niches with conserved cellular compositions that are repeated across healthy and diseased tissue. We show that IL4I1+ macrophages phagocytose dying cells in areas with high cell turnover and predict good outcome in colon cancer. In contrast, SPP1+ macrophages are enriched in hypoxic and necrotic tumor regions and portend worse outcome in colon cancer. A subset of FOLR2+ macrophages is embedded in plasma cell niches. NLRP3+ macrophages co-localize with neutrophils and activate an inflammasome in tumors. Our findings indicate that a limited number of unique human macrophage niches function as fundamental building blocks in tissue.

  View details for DOI 10.1158/2159-8290.CD-23-1300

  View details for PubMedID 38552005

• A spatial map of human macrophage niches reveals context-dependent macrophage functions in colon and breast cancer. Research square Matusiak, M., Hickey, J. W., Luca, B., Lu, G., Kidziński, L., Zhu, S., Colburg, D. R., Phillips, D. J., Brubaker, S. W., Charville, G. W., Shen, J., Nolan, G. P., Newman, A. M., West, R. B., van de Rijn, M. 2023

  Abstract

  Tumor-associated macrophages (TAMs) display heterogeneous phenotypes. Yet the exact tissue cues that shape macrophage functional diversity are incompletely understood. Here we discriminate, spatially resolve and reveal the function of five distinct macrophage niches within malignant and benign breast and colon tissue. We found that SPP1 TAMs reside in hypoxic and necrotic tumor regions, and a novel subset of FOLR2 tissue resident macrophages (TRMs) supports the plasma cell tissue niche. We discover that IL4I1 macrophages populate niches with high cell turnover where they phagocytose dying cells. Significantly, IL4I1 TAMs abundance correlates with anti-PD1 treatment response in breast cancer. Furthermore, NLRP3 inflammasome activation in NLRP3 TAMs correlates with neutrophil infiltration in the tumors and is associated with poor outcome in breast cancer patients. This suggests the NLRP3 inflammasome as a novel cancer immunetherapy target. Our work uncovers context-dependent roles of macrophage subsets, and suggests novel predictive markers and macrophage subset-specific therapy targets.

  View details for DOI 10.21203/rs.3.rs-2393443/v1

  View details for PubMedID 36711732

  View details for PubMedCentralID PMC9882614

• Molecular classification and biomarkers of clinical outcome in breast ductal carcinoma in situ: Analysis of TBCRC 038 and RAHBT cohorts. Cancer cell Strand, S. H., Rivero-Gutierrez, B., Houlahan, K. E., Seoane, J. A., King, L. M., Risom, T., Simpson, L. A., Vennam, S., Khan, A., Cisneros, L., Hardman, T., Harmon, B., Couch, F., Gallagher, K., Kilgore, M., Wei, S., DeMichele, A., King, T., McAuliffe, P. F., Nangia, J., Lee, J., Tseng, J., Storniolo, A. M., Thompson, A. M., Gupta, G. P., Burns, R., Veis, D. J., DeSchryver, K., Zhu, C., Matusiak, M., Wang, J., Zhu, S. X., Tappenden, J., Ding, D. Y., Zhang, D., Luo, J., Jiang, S., Varma, S., Anderson, L., Straub, C., Srivastava, S., Curtis, C., Tibshirani, R., Angelo, R. M., Hall, A., Owzar, K., Polyak, K., Maley, C., Marks, J. R., Colditz, G. A., Hwang, E. S., West, R. B. 2022

  Abstract

  Ductal carcinoma in situ (DCIS) is the most common precursor of invasive breast cancer (IBC), with variable propensity for progression. We perform multiscale, integrated molecular profiling of DCIS with clinical outcomes by analyzing 774 DCIS samples from 542 patients with 7.3 years median follow-up from the Translational Breast Cancer Research Consortium 038 study and the Resource of Archival Breast Tissue cohorts. We identify 812 genes associated with ipsilateral recurrence within 5 years from treatment and develop a classifier that predicts DCIS or IBC recurrence in both cohorts. Pathways associated with recurrence include proliferation, immune response, and metabolism. Distinct stromal expression patterns and immune cell compositions are identified. Our multiscale approach employed in situ methods to generate a spatially resolved atlas of breast precancers, where complementary modalities can be directly compared and correlated with conventional pathology findings, disease states, and clinical outcome.

  View details for DOI 10.1016/j.ccell.2022.10.021

  View details for PubMedID 36400020

• Interactions in CSF1-driven Tenosynovial Giant Cell Tumors. Clinical cancer research : an official journal of the American Association for Cancer Research van IJzendoorn, D. G., Matusiak, M., Charville, G. W., Spierenburg, G., Varma, S., Colburg, D. R., van de Sande, M. A., van Langevelde, K., Mohler, D. G., Ganjoo, K. N., Bui, N. Q., Avedian, R. S., Bovee, J. V., Steffner, R., West, R. B., van de Rijn, M. 2022

  Abstract

  A major component of cells in Tenosynovial Giant Cell Tumor (TGCT) consists of bystander macrophages responding to CSF1 that is overproduced by a small number of neoplastic cells with a chromosomal translocation involving the CSF1 gene. An autocrine loop was postulated where the neoplastic cells would be stimulated through CSF1R expressed on their surface. Here we use single cell RNA sequencing to investigate cellular interactions in TGCT.A total of 18,788 single cells from three TGCT and two Giant Cell Tumor of Bone (GCTB) samples underwent singe cell RNAseq. The three TGCTs were additionally analyzed using long read RNA sequencing. Immunofluorescence and immunohistochemistry for a range of markers was used to validate and extend the scRNAseq findings.Two recurrent neoplastic cell populations were identified in TGCT that are highly similar to non-neoplastic synoviocytes. We identified GFPT2 as a marker that highlights the neoplastic cells in TCGT. We show that the neoplastic cells themselves do not express CSF1R. We identified overlapping features between the giant cells in TGCT and GCTB.The neoplastic cells in TGCT are highly similar non-neoplastic synoviocytes. The lack of CSF1R on the neoplastic cells indicates they may be unaffected by current therapies. High expression of GFPT2 in the neoplastic cells is associated with activation of the YAP1/TAZ pathway. In addition, we identified expression of the PDGF receptor in the neoplastic cells. These findings suggest two additional pathways to target in this tumor.

  View details for DOI 10.1158/1078-0432.CCR-22-1898

  View details for PubMedID 36007098

• Prognostic relevance of the hexosamine biosynthesis pathway activation in leiomyosarcoma. NPJ genomic medicine Tolwani, A., Matusiak, M., Bui, N., Forgo, E., Varma, S., Baratto, L., Iagaru, A., Lazar, A. J., van de Rijn, M., Przybyl, J. 2021; 6 (1): 30

  Abstract

  Metabolic reprogramming of tumor cells and the increase of glucose uptake is one of the hallmarks of cancer. In order to identify metabolic pathways activated in leiomyosarcoma (LMS), we analyzed transcriptomic profiles of distinct subtypes of LMS in several datasets. Primary, recurrent and metastatic tumors in the subtype 2 of LMS showed consistent enrichment of genes involved in hexosamine biosynthesis pathway (HBP). We demonstrated that glutamine-fructose-6-phosphate transaminase 2 (GFPT2), the rate-limiting enzyme in HBP, is expressed on protein level in a subset of LMS and the expression of this enzyme is frequently retained in patient-matched primary and metastatic tumors. In a new independent cohort of 327 patients, we showed that GFPT2 is associated with poor outcome of uterine LMS but not extra-uterine LMS. Based on the analysis of a small group of patients studied by 18F-FDG-PET imaging, we propose that strong expression of GFPT2 in primary LMS may be associated with high metabolic activity. Our data suggest that HBP is a potential new therapeutic target in one of the subtypes of LMS.

  View details for DOI 10.1038/s41525-021-00193-w

  View details for PubMedID 33941787

• Relationships between highly recurrent tumor suppressor alterations in 489 leiomyosarcomas. Cancer Schaefer, I., Lundberg, M. Z., Demicco, E. G., Przybyl, J., Matusiak, M., Chibon, F., Ingram, D. R., Hornick, J. L., Wang, W., Bauer, S., Baker, L. H., Lazar, A. J., van de Rijn, M., Marino-Enriquez, A., Fletcher, J. A. 2021

  Abstract

  BACKGROUND: Leiomyosarcoma (LMS) is the most common soft tissue and uterine sarcoma, but no standard therapy is available for recurrent or metastatic LMS. TP53, p16/RB1, and PI3K/mTOR pathway dysregulations are recurrent events, and some LMS express estrogen receptor (ER) and/or progesterone receptor (PR). To characterize relationships between these pathway perturbations, the authors evaluated protein expression in soft tissue and uterine nonprimary leiomyosarcoma (np-LMS), including local recurrences and distant metastases.METHODS: TP53, RB1, p16, and PTEN expression aberrations were determined by immunohistochemistry (IHC) in tissue microarrays (TMAs) from 227 np-LMS and a comparison group of 262 primary leiomyosarcomas (p-LMS). Thirty-five of the np-LMS had a matched p-LMS specimen in the TMAs. Correlative studies included differentiation scoring, ER and PR IHC, and CDKN2A/p16 fluorescence in situ hybridization.RESULTS: Dysregulation of TP53, p16/RB1, and PTEN was demonstrated in 90%, 95%, and 41% of np-LMS, respectively. PTEN inactivation was more common in soft tissue np-LMS than uterine np-LMS (55% vs 31%; P = .0005). Moderate-strong ER expression was more common in uterine np-LMS than soft tissue np-LMS (50% vs 7%; P < .0001). Co-inactivation of TP53 and RB1 was found in 81% of np-LMS and was common in both soft tissue and uterine np-LMS (90% and 74%, respectively). RB1, p16, and PTEN aberrations were nearly always conserved in p-LMS and np-LMS from the same patients.CONCLUSIONS: These studies show that nearly all np-LMS have TP53 and/or RB1 aberrations. Therefore, therapies targeting cell cycle and DNA damage checkpoint vulnerabilities should be prioritized for evaluations in LMS.

  View details for DOI 10.1002/cncr.33542

  View details for PubMedID 33788262

• Self-Organizing Maps for Cellular In Silico Staining and Cell Substate Classification. Frontiers in immunology Yuan, E., Matusiak, M., Sirinukunwattana, K., Varma, S., Kidziński, Ł., West, R. 2021; 12: 765923

  Abstract

  Cellular composition and structural organization of cells in the tissue determine effective antitumor response and can predict patient outcome and therapy response. Here we present Seg-SOM, a method for dimensionality reduction of cell morphology in H&E-stained tissue images. Seg-SOM resolves cellular tissue heterogeneity and reveals complex tissue architecture. We leverage a self-organizing map (SOM) artificial neural network to group cells based on morphological features like shape and size. Seg-SOM allows for cell segmentation, systematic classification, and in silico cell labeling. We apply the Seg-SOM to a dataset of breast cancer progression images and find that clustering of SOM classes reveals groups of cells corresponding to fibroblasts, epithelial cells, and lymphocytes. We show that labeling the Lymphocyte SOM class on the breast tissue images accurately estimates lymphocytic infiltration. We further demonstrate how to use Seq-SOM in combination with non-negative matrix factorization to statistically describe the interaction of cell subtypes and use the interaction information as highly interpretable features for a histological classifier. Our work provides a framework for use of SOM in human pathology to resolve cellular composition of complex human tissues. We provide a python implementation and an easy-to-use docker deployment, enabling researchers to effortlessly featurize digitalized H&E-stained tissue.

  View details for DOI 10.3389/fimmu.2021.765923

  View details for PubMedID 34777384

  View details for PubMedCentralID PMC8588845

• Atlas of clinically distinct cell states and ecosystems across human solid tumors. Cell Luca, B. A., Steen, C. B., Matusiak, M., Azizi, A., Varma, S., Zhu, C., Przybyl, J., Espín-Pérez, A., Diehn, M., Alizadeh, A. A., van de Rijn, M., Gentles, A. J., Newman, A. M. 2021

  Abstract

  Determining how cells vary with their local signaling environment and organize into distinct cellular communities is critical for understanding processes as diverse as development, aging, and cancer. Here we introduce EcoTyper, a machine learning framework for large-scale identification and validation of cell states and multicellular communities from bulk, single-cell, and spatially resolved gene expression data. When applied to 12 major cell lineages across 16 types of human carcinoma, EcoTyper identified 69 transcriptionally defined cell states. Most states were specific to neoplastic tissue, ubiquitous across tumor types, and significantly prognostic. By analyzing cell-state co-occurrence patterns, we discovered ten clinically distinct multicellular communities with unexpectedly strong conservation, including three with myeloid and stromal elements linked to adverse survival, one enriched in normal tissue, and two associated with early cancer development. This study elucidates fundamental units of cellular organization in human carcinoma and provides a framework for large-scale profiling of cellular ecosystems in any tissue.

  View details for DOI 10.1016/j.cell.2021.09.014

  View details for PubMedID 34597583

• Immune cell topography predicts response to PD-1 blockade in cutaneous T cell lymphoma. Nature communications Phillips, D., Matusiak, M., Gutierrez, B. R., Bhate, S. S., Barlow, G. L., Jiang, S., Demeter, J., Smythe, K. S., Pierce, R. H., Fling, S. P., Ramchurren, N., Cheever, M. A., Goltsev, Y., West, R. B., Khodadoust, M. S., Kim, Y. H., Schürch, C. M., Nolan, G. P. 2021; 12 (1): 6726

  Abstract

  Cutaneous T cell lymphomas (CTCL) are rare but aggressive cancers without effective treatments. While a subset of patients derive benefit from PD-1 blockade, there is a critically unmet need for predictive biomarkers of response. Herein, we perform CODEX multiplexed tissue imaging and RNA sequencing on 70 tumor regions from 14 advanced CTCL patients enrolled in a pembrolizumab clinical trial (NCT02243579). We find no differences in the frequencies of immune or tumor cells between responders and non-responders. Instead, we identify topographical differences between effector PD-1+ CD4+ T cells, tumor cells, and immunosuppressive Tregs, from which we derive a spatial biomarker, termed the SpatialScore, that correlates strongly with pembrolizumab response in CTCL. The SpatialScore coincides with differences in the functional immune state of the tumor microenvironment, T cell function, and tumor cell-specific chemokine recruitment and is validated using a simplified, clinically accessible tissue imaging platform. Collectively, these results provide a paradigm for investigating the spatial balance of effector and suppressive T cell activity and broadly leveraging this biomarker approach to inform the clinical use of immunotherapies.

  View details for DOI 10.1038/s41467-021-26974-6

  View details for PubMedID 34795254

• Expression of SARS-CoV-2 entry receptors in the respiratory tract of healthy individuals, smokers and asthmatics. Respiratory research Matusiak, M., Schurch, C. M. 2020; 21 (1): 252

  Abstract

  SARS-CoV-2 is causing a pandemic with currently>29 million confirmed cases and>900,000 deaths worldwide. The locations and mechanisms of virus entry into the human respiratory tract are incompletely characterized. We analyzed publicly available RNA microarray datasets for SARS-CoV-2 entry receptors and cofactors ACE2, TMPRSS2, BSG (CD147) and FURIN. We found that ACE2 and TMPRSS2 are upregulated in the airways of smokers. In asthmatics, ACE2 tended to be downregulated in nasal epithelium, and TMPRSS2 was upregulated in the bronchi. Furthermore, respiratory epithelia were negative for ACE-2 and TMPRSS2 protein expression while positive for BSG and furin, suggesting a possible alternative entry route for SARS-CoV-2.

  View details for DOI 10.1186/s12931-020-01521-x

  View details for PubMedID 32993656

• Cellular neighborhoods predict pembrolizumab response in cutaneous T cell lymphoma Schurch, C. M., Phillips, D. J., Gutierrez, B., Matusiak, M., Bhate, S. S., Barlow, G. L., Fling, S. P., Ramchurren, N., Pierce, R. H., Cheever, M. A., Khodadoust, M. S., West, R., Kim, Y. H., Nolan, G. P. AMER ASSOC CANCER RESEARCH. 2020

  View details for DOI 10.1158/1538-7445.AM2020-6669

  View details for Web of Science ID 000590059307310

• Atlas of clinically-distinct cell states and cellular ecosystems across human solid tumors Luca, B. A., Steen, C. B., Azizi, A., Matusiak, M., Przybyl, J., Neishaboori, N., Perez, A., Diehn, M., Alizadeh, A. A., van de Rijn, M., Gentles, A. J., Newman, A. M. AMER ASSOC CANCER RESEARCH. 2020

  View details for DOI 10.1158/1538-7445.AM2020-3443

  View details for Web of Science ID 000590059301119