Biology subjects

Ruzinova, M. B.

Publications and source records attributed to Ruzinova, M. B..

3 recordsLinked to original sources

bioRxiv2025

Targeting Tumor-intrinsic TAK1 triggers anti-tumor immunity and sensitizes pancreatic cancer to checkpoint blockade

Background and AimsTargeting the Transforming Growth Factor-{beta} (TGF-{beta}) pathway to reverse the immunologically "cold" tumor microenvironment (TME) of pancreatic ductal adenocarcinoma (PDAC) remains clinically unsuccessful, warranting novel therapeutic strategies. MethodsWe developed a novel tumor-CD8 T cell co-culture to interrogate the TGF-{beta} signaling pathways that promotes T cell-mediated cytotoxicity. We performed multiplex immunohistochemistry (mIHC) on human PDAC samples to correlate cell-type specific TGF-{beta} pathway activation and CD8 T cell abundance. We employed specific pathway inhibitor and newly generated genetically-engineered mouse models (GEMMs) and confirmed our findings using single-cell RNA sequencing, flow cytometry and mIHC. We performed proteomics and various in vitro assays to establish the molecular mechanisms. ResultsWe identify TGF-{beta}-activated kinase 1 (TAK1 or MAP3K7) as an aberrantly activated kinase in human and mouse PDAC tissues that is associated with T cell dysfunction. Pharmacological inhibition of TAK1 with Takinib, or genetic deletion of MAP3K7 in autochthonous p48-Cre;TP53flox/flox;LSL-KRASG12DGEMM, enhances intratumoral CD4+ and CD8+ effector T cell infiltration and renders immune checkpoint blockade (ICB) effective. Mechanistically, TAK1 inhibition induces DNA damage and cytoplasmic DNA leakage, which activates the cyclic GMP-AMP synthase-Stimulator of Interferon Genes (cGAS-STING) DNA sensing pathway, triggering inflammatory responses that promote adaptive immune cell infiltration. At the molecular level, TAK1 phosphorylates Ephrin Receptor A2 (EphA2) at Serine 897, which in turn phosphorylates RAD51 at Tyrosine 315, a key DNA repair protein involved in homologous recombination. ConclusionsWe uncover TAK1 as a critical mediator in maintaining genomic integrity and highlights its potential as a therapeutic target to induce an inflamed TME that sensitizes PDAC to ICB.

cancer biology↗

bioRxiv2025

Genomic and Immunogenomic Profiling of Extramedullary Acute Myeloid Leukemia Reveals Actionable Clonal Branching and Frequent Immune Editing

Extramedullary acute myeloid leukemia (eAML) is a rare form of myeloid neoplasm characterized by leukemic infiltration outside the bone marrow (BM). Despite its prognostic significance, eAML is often underdiagnosed and poorly characterized at molecular level. We performed a comprehensive genomic and immunogenomic profiling on paired BM and extramedullary specimens from 26 eAML patients, alongside over 400 AML cases without extramedullary involvement and 97 healthy controls. Clonal branching from BM was observed in 38.5% of extramedullary sites, frequently involving actionable mutations in FLT3, IDH2 and NPM1 genes. Both compartments were enriched in RAS pathway mutations and class II HLA losses, suggesting active immunoediting mechanisms driving eAML development. Strikingly all relapsed cases acquired FLT3 aberrations, highlighting therapeutic opportunities. These findings underpin the need for improved detection and routine genomic profiling, including targeted sequencing of suspected extramedullary lesions.

genomics↗

bioRxiv2022

IMC-Denoise: a content aware denoising pipeline to enhance Imaging Mass Cytometry

Imaging Mass Cytometry (IMC) is an emerging multiplexed imaging technology for analyzing complex microenvironments that has the ability to detect the spatial distribution of at least 40 cell markers. However, this new modality has unique image data processing requirements, particularly when applying this technology to patient tissue specimens. In these cases, signal-to-noise ratio for particular markers can be low despite optimization of staining conditions, and the presence of pixel intensity artifacts can deteriorate image quality and the subsequent performance of downstream analysis. Here we demonstrate an automated content-aware pipeline, IMC-Denoise, to restore IMC images. Specifically, we deploy a differential intensity map-based restoration (DIMR) algorithm for removing hot pixels and a self-supervised deep learning algorithm for filtering shot noise (DeepSNF). IMC-Denoise outperforms existing methods for adaptive hot pixel removal, and delivers significant image quality improvement and background noise removal to a diverse set of IMC channels and datasets. This includes a unique, technically challenging, human bone marrow IMC dataset; in which we achieve noise level reduction of 87% for a 5.6-fold higher contrast-to-noise ratio, and more accurate background noise removal with approximately two-fold improved F1 score. Our approach remarkably enhances both manual gating and automated phenotyping with cell-scale down-stream analysis on these complex data. We anticipate that IMC-Denoise will provide similar benefits in mass cytometry imaging domains to more deeply characterize the complex and diverse tissue microenvironment.

bioinformatics↗