Biology subjects

Bruck, O.

Publications and source records attributed to Bruck, O..

4 recordsLinked to original sources

bioRxiv2024

Fibroblast activation protein defines aggressive EMT-associated cancer cell state and prognosis in localized ccRCC

Clear cell renal cell carcinoma (ccRCC) is among the most immune-infiltrated cancers, where high inflammation correlates with poor clinical outcomes. While epithelial-to-mesenchymal transition (EMT), immunosuppression, and cancer-associated fibroblasts (CAFs) have been linked with poor prognosis in metastatic ccRCC, their relevance and interplay in localized disease remain uncertain. To address this gap, we performed single-cell spatial profiling of highly inflamed localized tumors to characterize interactions between EMT-associated cancer cells and immune subsets, aiming to identify tumor microenvironment cell subsets and states responsible for the poor prognosis in highly inflamed ccRCC. Multiplexed immunofluorescence imaging with a 33-marker panel was applied to 1,728 tissue cores collected from tumor centers, invasive borders, and adjacent benign tissue from 435 localized ccRCC patients. Independent discovery (n=196) and validation (n=239) cohorts were used to confirm the significance of identified prognostic markers. Hierarchical clustering revealed TME subsets enriched for CD45 immune cells, CD31 endothelial cells, or fibroblasts. High CD45 cell density significantly correlated with poor recurrence-free survival across tumor regions, including tumor center, invasive border, and adjacent benign tissue. Within tumors exhibiting high CD45 infiltration, EMT-associated cancer cells strongly expressed fibroblast activation protein (FAP) at invasive borders, independently predicting worse prognosis and increased risk of liver metastasis. Furthermore, CD45high tumors with elevated FAP expression featured immunosuppressive FAP CAFs, M2-like macrophages, exhausted T cells, and regulatory T cells. Tumor-cell-specific FAP expression was validated as an independent prognostic biomarker in both early-stage localized ccRCC (pT1-2) and patients subsequently developing metastases who received sunitinib, highlighting its potential for improved patient stratification. SignificanceFAP expression identifies an aggressive, immunosuppressive EMT-associated subtype of localized ccRCC, uncovering critical interactions between cancer cells and the TME and revealing novel biological insights and therapeutic vulnerabilities driving early-stage ccRCC progression. Graphical AbstractO_ST_ABSTumor-cell FAP Expression Defines an Aggressive, Immunosuppressive EMT Subtype in Highly Inflamed Localized ccRCCC_ST_ABS O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=197 SRC="FIGDIR/small/620479v2_ufig1.gif" ALT="Figure 1"> View larger version (55K): org.highwire.dtl.DTLVardef@d25831org.highwire.dtl.DTLVardef@19c0de7org.highwire.dtl.DTLVardef@54bd9eorg.highwire.dtl.DTLVardef@16d0387_HPS_FORMAT_FIGEXP M_FIG C_FIG Localized ccRCC tumors were stratified by CD45 immune infiltration, revealing that CD45high tumors were associated with significantly poorer recurrence-free survival (5-year RFS rate: 39%). Among these, tumor cell-specific expression of fibroblast activation protein (FAP) identified a particularly aggressive subtype marked by epithelial-to-mesenchymal transition (EMT), reduced endothelial content, and an immunosuppressive tumor microenvironment enriched with M2-like macrophages, regulatory T cells, exhausted T cells, and FAP cancer-associated fibroblasts (CAFs). FAP tumors had an even lower 5-year RFS rate of 26%, compared to 50% in FAP- CD45high tumors. Tumor-cell FAP thus provides an additional layer of risk stratification within the CD45high subgroup and reflects a biologically distinct, immune-evasive tumor state. These findings highlight FAP as both a potential therapeutic target and imaging biomarker in localized ccRCC.

cancer biology↗

bioRxiv2022

Integrative Analysis of Histological Textures and Lymphocyte Infiltration in Renal Cell Carcinoma using Deep Learning

Evaluating tissue architecture from routine hematoxylin and eosin-stained (H&E) slides is prone to subjectivity and sampling bias. Here, we extensively annotated [~]40,000 images of five tissue texture types and [~]25,000 images of lymphocyte quantity to train deep learning models. We defined histopathological patterns in over 400 clear-cell renal cell carcinoma H&E-stained slides of The Cancer Genome Atlas (TCGA) and resolved sampling and staining differences by harmonizing textural composition. By integrating multi-omic and imaging data, we profiled their clinical, immunological, genomic, and transcriptomic phenotypes. Histological grade, stage, adaptive immunity, the epithelial-to-mesenchymal transition signature and lower mutation burden were more common in stroma-rich samples. Histological proximity between the malignant and normal renal tissues was associated with poor survival, cellular proliferation, tumor heterogeneity, and wild-type PBRM1. This study highlights textural characterization to standardize sampling differences, quantify lymphocyte infiltration and discover novel histopathological associations both in the intratumoral and peritumoral regions.

cancer biology↗

bioRxiv2020

Histopathological Landscape of Molecular Genetics and Clinical Determinants in MDS Patients

In myelodysplastic syndrome (MDS), bone marrow (BM) histopathology is visually assessed to identify dysplastic cellular morphology, cellularity, and blast excess. Yet, many morphological findings elude the human eye. Here, we extracted visual features of 236 MDS, 87 MDS/MPN, and 10 control BM biopsies with convolutional neural networks. Unsupervised analysis distinguished underlying correlations between tissue composition, leukocyte metrics, and clinical characteristics. We applied morphological features in elastic net-regularized regression models to predict genetic and cytogenetic aberrations, prognosis, and clinical variables. By parallelizing tile, pixel, and leukocyte-level image analysis, we deconvoluted each model to texture and cellular composition to dissect their pathobiological context. Model-based mutation predictions correlated with variant allele frequency and number of affected genes per pathway, demonstrating the models ability to identify relevant visual patterns. In summary, this study highlights the potential of deep histopathology in hematology by unveiling the fundamental association of BM morphology with genetic and clinical determinants.

bioinformatics↗

bioRxiv2019

Immunogenomic landscape of hematological malignancies

Understanding factors that shape the immune landscape across hematological malignancies is essential for immunotherapy development. Here, we integrated over 8,000 transcriptomes and over 1,000 samples with multilevel genomic data of hematological cancers to investigate how immunological features are linked to cancer subtypes, genetic and epigenetic alterations, and patient survival. Infiltration of cytotoxic immune cells was associated with distinct microenvironmental responses and driver alterations in different cancers, such as TP53 in acute myeloid leukemia and DTX1 in diffuse large B cell lymphoma. Epigenetic modification of CIITA regulating antigen presentation, cancer type-specific immune checkpoints such as VISTA in myeloid malignancies, and variation in cancer antigen expression further contributed to immune heterogeneity. Prognostic models highlighted the significance of immunological properties in predicting survival. Our study represents the most comprehensive effort to date to link immunology with cancer subtypes and genomics in hematological malignancies, providing a resource to guide future studies and immunotherapy development.

immunology↗