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Grünwald, B. T.

Publications and source records attributed to Grünwald, B. T..

3 recordsLinked to original sources

Loss of the Y chromosome drives basal identity and metastatic potential via epigenetic reprogramming in pancreatic cancer

Loss of the Y chromosome (LOY) has been largely unexplored in pancreatic ductal adenocarcinoma (PDAC), and no mechanistic framework previously explained its role in tumor biology. We identify LOY as a recurrent, functionally consequential alteration affecting ~50% of male PDAC patients across two independent cohorts, with strong enrichment in advanced disease and, critically, in the basal subtype, establishing LOY as a clinically actionable biomarker. Comprehensive genomic profiling positions LOY as a distinct genetic event associated with TP53 mutations, implicating it in aggressive tumor evolution. Integrative analyses across bulk tumors, single-cell datasets and CRISPR-engineered PDAC models converge on epithelial-to-mesenchymal transition (EMT) as the dominant LOY-driven program. Y-chromosome deletion alone induces EMT transcriptional states, mesenchymal morphology and enhanced metastatic ability. Mechanistically, LOY disrupts epigenetic regulation through loss of Y-linked chromatin modifiers, reshaping DNA methylation at EMT- and basal-defining loci and reducing chemotherapy sensitivity. These findings establish LOY as a causal genetic driver of PDAC progression and a clinically accessible biomarker with direct therapeutic relevance.

cancer biology↗

Hourglass, a tool to mine bioimaging data, uncovers sex-disparities in the IL-6-associated T cell response in pancreatic tumors

Recent advances in digital pathology have led to an explosion in high-content multidimensional imaging approaches. Yet, our ability to gainfully process, visualize, integrate and mine the resulting mass of bioimaging data remains a challenge. We have developed Hourglass, an open access user-friendly software that streamlines complex biology-driven post-processing and visualization of multiparametric data. Directed at datasets derived from tissue microarrays or imaging methods that analyze multiple regions of interest per patient specimen, Hourglass systematically organizes observations across spatial and global levels as well as within patient subgroups. Application of Hourglass to our large and complex pancreatic cancer bioimaging dataset (540,617 datapoints derived from 26 bioimaging analyses applied to 596 specimens from 165 patients) consolidated a breadth of known IL-6 functions in a well-annotated human pancreatic cancer cohort and uncovered new unprecedented insights into a sex-linked Interleukin-6 (IL-6) association with immune phenotypes. Specifically, regional effects of IL-6 on the intratumoral T cell response were restricted to male patients only. In conclusion, Hourglass facilitates multi-layered knowledge extraction from complex multiparametric bioimaging datasets and provides tailored analytical means to productively harness heterogeneity at the sample and patient level.

cancer biology↗

Spatially confined sub-tumor microenvironments orchestrate pancreatic cancer pathobiology

Pancreatic ductal adenocarcinoma (PDAC) remains resistant to most treatments and demonstrates a complex pathobiology. Here, we deconvolute regional heterogeneity in the human PDAC tumor microenvironment (TME), a long-standing obstacle, to define precise stromal contributions to PDAC progression. Large scale integration of histology-guided multiOMICs with clinical data sets and functional in vitro models uncovers two microenvironmental programs in PDAC that were anchored in fibroblast differentiation states. These sub-tumor microenvironments (subTMEs) co-occurred intratumorally and were spatially confined, producing patient-specific cellular and molecular heterogeneity associated with shortened patient survival. Each subTME was uniquely structured to support discrete aspects of tumor biology: reactive regions rich in activated fibroblast communities were immune-hot and promoted aggressive tumor progression while deserted regions enriched in extracellular matrix supported tumor differentiation yet were markedly chemoprotective. In conclusion, PDAC regional heterogeneity derives from biologically distinct reactive and protective TME elements with a defined, active role in PDAC progression. Graphical Abstract & Key findings O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=191 SRC="FIGDIR/small/431890v1_ufig1.gif" ALT="Figure 1"> View larger version (73K): org.highwire.dtl.DTLVardef@17adabdorg.highwire.dtl.DTLVardef@aee778org.highwire.dtl.DTLVardef@deae00org.highwire.dtl.DTLVardef@1718272_HPS_FORMAT_FIGEXP M_FIG C_FIG O_LIPDAC regional heterogeneity originates in sub-tumor microenvironments (subTMEs) C_LIO_LISubTMEs exhibit distinct immune phenotypes and CAF differentiation states C_LIO_LIDifferent subTMEs are either tumor-promoting or chemoprotective C_LIO_LIIntratumoral subTME co-occurrence links stromal heterogeneity to patient outcome C_LI

cancer biology↗