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Muranen, T.

Publications and source records attributed to Muranen, T..

10 recordsLinked to original sources

Metabolic-epigenetic coupling between leucine catabolism and glycolysis drives CDK4/6 inhibitor resistance

Resistance to CDK4/6 inhibitors limits the durability of therapy for ER+ breast cancer. Despite the identification of mechanisms that regulate resistance, the metabolic adaptations that enable therapeutic escape remain poorly understood. Here, we identify a metabolic-epigenetic circuit that drives resistance by coordinately rewiring amino acid and glucose metabolism. CDK4/6 inhibitor-resistant ER+ tumor cells upregulate the leucine transporter SLC7A5, enhancing leucine uptake. SLC7A5 overexpression is sufficient to confer palbociclib resistance across ER+ cell lines, patient-derived organoids and xenografts. Stable isotope tracing in cell lines and in xenograft tumors revealed that leucine is catabolized through BCAT2 and HMGCL to increase acetyl-CoA levels, and elevated acetyl-CoA promotes H3K27 acetylation at the GLUT1 promoter, upregulating GLUT1 expression and glycolytic activity. Disrupting leucine transport, catabolism, or availability suppresses GLUT1 expression and restores therapeutic sensitivity in resistant models. In patients receiving palbociclib-based therapy, high SLC7A5 expression and coordinated SLC7A5-GLUT1 co-expression are associated with shorter progression-free survival. Together, these findings define a metabolic-epigenetic mechanism linking branched-chain amino acid catabolism to glycolysis and identify a biomarker-associated metabolic vulnerability in advanced ER+ breast cancer.

cancer biology↗

MAPK signaling links BRD2 chromatin occupancy to PI3K/AKT inhibitor sensitivity

Bromodomain and extra-terminal (BET) proteins, BRD2, BRD3, BRD4, and BRDT, couple histone acetylation to transcription by recruiting elongation and transcription factor complexes to chromatin. Although BET proteins are promising therapeutic targets, the functions of individual family members remain incompletely understood. We identify BRD2 as a co-targetable vulnerability with PI3K/AKT inhibition in breast cancer. Pan-BET inhibition and BRD2 knockout synergized with PI3K pathway inhibitors in breast cancer cell lines, patient-derived organoids, and in vivo models. BRD2 knockout impaired proliferation of triple-negative breast cancer cells and upregulated signaling and stress-response pathways, including the DNA damage response. Mechanistically, BRD2 is phosphorylated at Ser37 by the mitogen- and stress-activated kinases MSK and RSK, and Ser37 phosphorylation is required for chromatin binding and reader function. Finally, mechanistic digital twin modeling identified BETi-PI3Ki regimens that maintained efficacy while reducing drug exposure. Together, these findings identify BRD2 as a phosphorylation-dependent, co-targetable vulnerability in PI3K-inhibited breast cancer.

cancer biology↗

An image analysis pipeline to quantify the spatial distribution of cell markers in stroma-rich tumors

1.Aggressive cancers, such as pancreatic ductal adenocarcinoma (PDAC), are often characterized by a complex and desmoplastic tumor microenvironment rich in stroma, a supportive connective tissue composed primarily of extracellular matrix (ECM) and non-cancerous cells. Desmoplasia, which is a dense deposition of stroma, is a major reason for therapy resistance, acting both as a physical barrier that interferes with drug penetration and as a supportive niche that protects cancer cells through diverse mechanisms. A precise understanding of spatial cell interactions within the tumor microenvironment in stroma-rich cancers is essential for optimizing therapeutic responses. It allows detailed mapping of stromal-tumor interfaces, comprehensive phenotyping of diverse cell types and their functional states, and insights into changes in cellular distribution and tissue architecture, thus leading to an improved assessment of drug responses. Recent advances in multiplexed immunofluorescence imaging have enabled the acquisition of large batches of whole-slide tumor images, but scalable and reproducible methods to analyze the spatial distribution of cell states relative to stromal regions remain limited. To address this gap, we developed an open-source computational pipeline that integrates QuPath (Bankhead et al. 2017), StarDist (Schmidt et al. 2018), and custom Python scripts to quantify biomarker expression at a single- and sub-cellular resolution across entire tumor sections. Our workflow includes: (i) automated nuclei segmentation using StarDist, (ii) machine learning-based cell classification using multiplexed marker expression, (iii) modeling of stromal regions based on fibronectin staining, (iv) sensitivity analyses on classification thresholds to ensure robustness across heterogeneous datasets, and (v) distance-based quantification of the proximity of each cell to the stromal border. To improve consistency across slides with variable staining intensities, we introduce a statistical strategy that translates classification thresholds by propagating a chosen reference percentile across the distribution of marker-related cell measurement in each image. We apply this approach to quantify spatial patterns of distribution of the phosphorylated form of the N-Myc downregulated gene 1 (NDRG1), a novel DNA repair protein that conveys signals from the ECM to the nucleus to maintain replication fork homeostasis, and a known cell proliferation marker Ki67 in fibronectin-defined stromal regions in PDAC xenografts. The pipeline is applicable for the analysis of various stroma-rich tissues and is publicly available: https://github.com/HMS-IAC/stroma-spatial-analysis-web. 2. Summary paragraphOur study introduces a scalable and reproducible image analysis pipeline that quantifies spatial biomarker distributions relative to the stroma in tumor tissues using open-source tools. By modeling cell-level intensity distributions and calibrating classification thresholds across heterogeneous images, we uncover spatially organized patterns of stroma sensing, DNA damage, and proliferative response in pancreatic tumors. This approach enables robust, quantitative analysis of tumor-stroma interactions and is readily adaptable to other tumor types and biomarker panels, providing a valuable resource for spatial pathology and tumor microenvironment research.

bioinformatics↗

Suppression of Ovarian Cancer Cell Proliferation is Associated with Upregulation of Cell-Matrix Adhesion Programs and Integrin-β4-Induced Cell Protection from Cisplatin.

The role of extracellular matrix adhesion components in modulation of the treatment sensitivity of ovarian cancer (OC) cells is not well understood. Analysis of ovarian cancer TCGA gene expression data sets revealed an inverse correlation between genes involved in cell-cycle progression and extracellular matrix interactions including laminin-binding receptor integrin {beta}4, a major component of extracellular matrix adhesion. Gene ontology analysis also showed that in patient populations with low integrin {beta}4 expression, cell cycle-related programs were activated, while in populations with high expression of integrin {beta}4, the activation of these cell cycle programs was lower. Suppression of proliferation with CDK4/6 inhibitor Palbociclib stimulated integrin {beta}4 expression and induced protection against cisplatin in cells naturally expressing low levels of integrin {beta}4. Additionally, ovarian cancer patient-derived organoids showed reduced cisplatin sensitivity when pretreated with Palbociclib. Our data also showed that integrin {beta}4 overexpression decreased ovarian cancer cell proliferation and at the same time, attenuated cisplatin response. Our investigations reveal that expression of integrin {beta}4 inversely correlates with cell cycle progression programs, whether observed in expression data of OC patient samples or in various OC cell lines. Consistently with these results, the overexpression of ITGB4 gene in ovarian cancer cell lines correlated with reduced cell proliferation rates and diminished sensitivity to cisplatin, supporting the idea that integrin {beta}4 and likely its matrix ligands play critical roles in the regulation of cellular growth and chemoresistance of ovarian cancer cells.

cancer biology↗

A novel DNA repair protein, N-Myc downstream regulated gene 1 (NDRG1), links stromal tumour microenvironment to chemoresistance

In pancreatic ductal adenocarcinoma cancer (PDAC) drug resistance is a severe clinical problem and patients relapse within a few months after receiving the standard-of-care chemotherapy. One contributing factor to treatment resistance is the desmoplastic nature of PDAC; the tumours are surrounded by thick layers of stroma composing up to 90% of the tumour mass. This stroma, which is mostly comprised of extracellular matrix (ECM) proteins, is secreted by cancer-associated fibroblasts (CAFs) residing in the tumour microenvironment. However, the mechanistic basis by which the tumour stroma directly contributes to chemoresistance remains unclear. Here, we show that CAF-secreted ECM proteins induce chemoresistance by blunting chemotherapy-induced DNA damage. Mechanistically, we identify N-myc downstream regulated gene 1 (NDRG1) as a key protein required for stroma-induced chemoresistance that responds to signals from the ECM and adhesion receptors. We further show that NDRG1 is a novel DNA repair protein that physically interacts with replication forks, maintains DNA replication and functions to resolve stalled forks caused by chemotherapy. More specifically, NDRG1 reduces R-loops, RNA-DNA hybrids that are known to cause genomic instability. R-loops occur during replication-transcription conflicts in S-phase and after chemotherapy treatments, thus posing a major threat to normal replication fork homeostasis. We identify NDRG1 as highly expressed in PDAC tumours, and its high expression correlates with chemoresistance and poor disease-specific survival. Importantly, knock-out of NDRG1 or inhibition of its phosphorylation restores chemotherapy-induced DNA damage and resensitizes tumour cells to treatment. In conclusion, our data reveal an unexpected role for CAF-secreted ECM proteins in enhancing DNA repair via NDRG1, a novel DNA repair protein, directly linking tumour stroma to replication fork homeostasis and R-loop biology, with important therapeutic implications for restoring DNA damage response pathways in pancreatic cancer. Summary paragraphDrug resistance is a severe clinical problem in stroma-rich tumours, such as pancreatic ductal adenocarcinoma (PDAC), and patients often relapse within a few months on chemotherapy1-9. The stroma, comprised of extracellular matrix (ECM) proteins, is secreted by cancer-associated fibroblasts (CAFs) residing in the tumour microenvironment10-13. Prior work show that ECM proteins provide survival benefits to cancer cells14,15. However, the precise role of CAF-secreted ECM in resistance to DNA damaging chemotherapies remains poorly understood. Here, we link ECM proteins to chemoresistance by enhanced DNA damage repair (DDR). Mechanistically, we identify N-myc downstream-regulated gene 1 (NDRG1) as a key effector downstream of ECM and the integrin-Src-SGK1-signalling axis that mediates enhanced DDR. We show that NDRG1 loss, mutation of conserved His194, or inhibition of NDRG1 phosphorylation by SGK1 lead to replication fork stalling, increased R-loops, and higher transcription-replication conflicts, resulting in genomic instability and sensitivity to chemotherapies. Our analysis of PDAC patient cohorts16 found that high NDRG1 expression correlates with chemoresistance and poor patient survival. In conclusion, we uncover an unexpected role for CAF-secreted ECM proteins in promoting therapeutic resistance by enhancing DDR and establish NDRG1 as a novel DNA repair protein directly linking tumour stroma to DDR.

cancer biology↗

Cholesterol biosynthesis inhibition synergizes with AKT inhibitors in triple-negative breast cancer

Triple-negative breast cancer (TNBC) is responsible for a disproportionate number of breast cancer deaths due to its molecular heterogeneity, high recurrence rate and lack of targeted therapies. Dysregulation of the phosphoinositide 3-kinase (PI3K)/AKT pathway occurs in approximately 50% of TNBC patients. We performed a genome-wide CRISPR/Cas9 screen with PI3K and AKT inhibitors to find targetable synthetic lethalities in TNBC. We identified cholesterol homeostasis as a collateral vulnerability with AKT inhibition. Disruption of cholesterol homeostasis with pitavastatin synergized with AKT inhibition to induce TNBC cytotoxicity in vitro, in mouse TNBC xenografts and in patient-derived, estrogen receptor (ER)-negative breast cancer organoids. Neither ER-positive breast cancer cell lines nor ER-positive organoids were sensitive to combined AKT inhibitor and pitavastatin. Mechanistically, TNBC cells showed impaired sterol regulatory element-binding protein 2 (SREBP-2) activation in response to single agent or combination treatment with AKT inhibitor and pitavastatin. This was rescued by inhibition of the cholesterol trafficking protein Niemann-Pick C1 (NPC1). NPC1 loss caused lysosomal cholesterol accumulation, decreased endoplasmic reticulum cholesterol levels and promoted SREBP-2 activation. Taken together, these data identify a TNBC-specific vulnerability to the combination of AKT inhibitors and pitavastatin mediated by dysregulated cholesterol trafficking. Our work motivates combining AKT inhibitors with pitavastatin as a therapeutic modality in TNBC.

cancer biology↗

Deciphering Cancer Genomes with GenomeSpy: A Grammar-Based Visualization Toolkit

BackgroundVisualization is an indispensable facet of genomic data analysis. Despite the abundance of specialized visualization tools, there remains a distinct need for tailored solutions. However, their implementation typically requires extensive programming expertise from bioinformaticians and software developers, especially when building interactive applications. Toolkits based on visualization grammars offer a more accessible, declarative way to author new visualizations. Nevertheless, current grammar-based solutions fall short in adequately supporting the interactive analysis of large data sets with extensive sample collections, a pivotal task often encountered in cancer research. ResultsWe present GenomeSpy, a grammar-based toolkit for authoring tailored, interactive visualizations for genomic data analysis. Users can implement new visualization designs with little effort by using combinatorial building blocks that are put together with a declarative language. These fully customizable visualizations can be embedded in web pages or end-user-oriented applications. The toolkit also includes a fully customizable but user-friendly application for analyzing sample collections, which may comprise genomic and clinical data. Findings can be bookmarked and shared as links that incorporate provenance information. A distinctive element of GenomeSpys architecture is its effective use of the graphics processing unit (GPU) in all rendering. GPU usage enables a high frame rate and smoothly animated interactions, such as navigation within a genome. We demonstrate the utility of GenomeSpy by characterizing the genomic landscape of 753 ovarian cancer samples from patients in the DECIDER clinical trial. Our results expand the understanding of the genomic architecture in ovarian cancer, particularly the diversity of chromosomal instability. We also show how GenomeSpy enabled the discovery of clinically actionable genomic aberrations. ConclusionsGenomeSpy is a visualization toolkit applicable to a wide range of tasks pertinent to genome analysis. It offers high flexibility and exceptional performance in interactive analysis. The toolkit is open source with an MIT license, implemented in JavaScript, and available at https://genomespy.app/.

bioinformatics↗

Differences in syncytia formation by SARS-CoV-2 variants modify host chromatin accessibility and cellular senescence via TP53

COVID-19 remains a significant public health threat due to the ability of SARS-CoV-2 variants to evade the immune system and cause breakthrough infections. Although pathogenic coronaviruses such as SARS-CoV-2 and MERS-CoV lead to severe respiratory infections, how these viruses affect the chromatin proteomic composition upon infection remains largely uncharacterized. Here we used our recently developed integrative DNA And Protein Tagging (iDAPT) methodology to identify changes in host chromatin accessibility states and chromatin proteomic composition upon infection with pathogenic coronaviruses. SARS-CoV-2 infection induces TP53 stabilization on chromatin, which contributes to its host cytopathic effect. We mapped this TP53 stabilization to the SARS-CoV-2 spike and its propensity to form syncytia, a consequence of cell-cell fusion. Differences in SARS-CoV-2 spike variant-induced syncytia formation modify chromatin accessibility, cellular senescence, and inflammatory cytokine release via TP53. Our findings suggest that differences in syncytia formation alter senescence-associated inflammation, which varies among SARS-CoV-2 variants.

microbiology↗

L1 retrotransposition is regulated post-transcriptionally In High-Grade Serous Ovarian Cancer

L1 retrotransposons are the only protein-coding active transposable elements in the human genome. Although silenced during normal conditions, they are highly expressed in human epithelial cancers including high-grade serous ovarian cancer (HGSC), where they transcribe to form L1 mRNA and subsequently integrate into the genome by a process called retrotransposition. Despite of high L1 protein expression in the earliest phases of HGSC, these tumors do not accrue many somatic L1 insertions. To understand this unexplained disconnect, we monitored the transcription and retrotransposition activity of two frequently expressed retrotransposition-competent (RC)-L1 (RC-L1) in 64 clinical tumor specimens from 34 HGSC patients and found that despite the presence of RC-L1 mRNA, a third of samples did not acquire somatic L1 insertions. In addition to high inter-patient variability in retrotransposition frequency, there was remarkable intra-patient heterogeneity in L1 insertion patterns between tumor sites, indicating that L1 retrotransposition is highly dynamic in vivo. Comparison of genomic and transcriptomic features of L1-null tumors with L1-high tumors (those with [≥]5 somatic L1 insertions) showed that retrotransposition was favored by increased rate of cell proliferation.

cancer biology↗

Large-scale Characterization of Drug Responses of Clinically Relevant Proteins in Cancer Cell Lines

Perturbation biology is a powerful approach to developing quantitative models of cellular behaviors and gaining mechanistic insights into disease development. In recent years, large-scale resources for phenotypic and mRNA responses of cancer cell lines to perturbations have been generated. However, similar large-scale protein response resources are not available, resulting in a critical knowledge gap for elucidating oncogenic mechanisms and developing effective cancer therapies. Here we generated and compiled perturbed expression profiles of ~210 clinically relevant proteins in >12,000 cancer cell-line samples in response to >150 drug compounds using reverse-phase protein arrays. We show that integrating protein response signals substantially increases the predictive power for drug sensitivity and aids in gaining insights into mechanisms of drug resistance. We build a systematic map of protein-drug connectivity and develop an open-access, user-friendly data portal for community use. Our study provides a valuable information resource for a broad range of quantitative modeling and biomedical applications. HighlightsO_LIA large collection of cancer cell line protein responses to drug perturbations C_LIO_LIPerturbed protein responses greatly increase predictive power for drug sensitivity C_LIO_LIBuild a systematic map of protein-drug connectivity based on response profiles C_LIO_LIDevelop a user-friendly, interactive data portal for community use C_LI

systems biology↗