Biology subjects

Kolch, W.

Publications and source records attributed to Kolch, W..

13 recordsLinked to original sources

bioRxiv2025

Inclusion of JNK-independent drugs within multi-agent chemotherapy improves response in relapsed high-risk neuroblastoma

The acquisition of a chemoresistant state underlies poor prognosis in many cancers, including neuroblastoma. We previously demonstrated that heterogeneity in apoptosis induction through c-Jun N-Terminal Kinase (JNK) promotes a form of non-genetic chemoresistance in neuroblastoma observable at both patient and single-cell levels. As the maintenance of this JNK-impaired state in the relapse setting is a significant barrier to the efficacy of many standard-of-care chemotherapy drugs, we combined a mechanistic, mathematical model of JNK activation with a paediatric focused drug screen and identified approved oncology drugs capable of inducing apoptosis in a JNK-independent manner. Functional genomics further revealed that synergy between these JNK-independent drugs and standard-of-care chemotherapies emerged from differential utilisation of apoptotic network components, rather than from their direct mechanistic targets. Efficacy studies with PDX models also confirmed that including a JNK-independent drug within existing chemotherapy backbones significantly improved response in the relapse setting, where new approaches are urgently needed. One Sentence SummaryDrug combinations utilising differential sets of network components can overcome the apoptotic impaired state of relapsed high-risk neuroblastoma.

cancer biology↗

bioRxiv2025

A selective inhibitor of oncogenic JNK signalling perturbs metastatic outgrowth of triple-negative breast cancer through metabolic blockade

Although c-Jun N-terminal Kinase (JNK) represents an attractive anti-cancer target, its pleiotropic functionality limits the use of direct JNK inhibitors. Here, we identify a distinct subcellular pattern of JNK activity as a therapeutic vulnerability in breast cancer, where cytoplasmic JNK activity predicts poor survival outcomes, is elevated in triple-negative breast cancers (TNBC) and is essential for metastatic outgrowth. Mechanistic analyses reveal cytoplasmic JNK acts through multiple mechanisms, with downstream targets involved in cellular metabolism and cytoskeletal regulation. On this basis, we leveraged actin-based phenotypic drug-screening and identified K12, an indirect but selective inhibitor of cytoplasmic JNK that blocks TNBC metastatic outgrowth in vivo. We reveal that K12 inhibits glutaminase-1 and the pyruvate dehydrogenase complex, and that this poly-pharmacology overcomes pyruvate anaplerosis, a known resistance mechanism of existing glutaminase inhibitors. These findings demonstrate the potential of selectively targeting the oncogenic function of JNK, offering new treatment options for early-stage metastatic TNBC.

cancer biology↗

bioRxiv2025

SAEG: A Novel Deep Learning Architecture for Somatic Alterations

Somatic alterations, like mutations and copy number changes, driver oncogenesis and cancer progression. Their inhibition has been exploited in the clinic, with several targeted therapies approved for patients with specific mutations or amplifications. However, the response rate of these treatments remains low. The causes are several, ranging from clonal heterogeneity to off target binding. For this reason, CRISPR assays have been developed to study the exact effect of a genes deletion. Still, the results from them are puzzling with the same alterations responding different to knockout even in the same cellular context. For this reason, we have developed SAEG, a novel deep learning architecture for somatic alterations in cancer. Our architecture is able to model mutations and copy number alterations and protein-protein interactions to predict if a cell will be susceptible to a gene knockout. SAEG outperforms other models and we show that it learns patterns that can be traced back to the biochemical and biological properties of genes and amino acids. Code Availabilityhttps://github.com/Luisiglm/SAEG Contactluis.iglesiarmatinez@ucd.ie

bioinformatics↗

bioRxiv2024

Diphenyleneiodonium chloride inhibits MYCN-amplified neuroblastoma by targeting MYCN induced mitochondrial alterations

High-risk neuroblastoma is one of the most lethal childhood cancers. Half of these tumors are driven by MYCN gene amplification (MNA). Despite intensive chemo- and radiotherapy, only 40% of patients survive, and they often suffer from severe long-term side effects of these genotoxic treatments. Thus, new therapies are needed that are less toxic and more efficacious. Here, we identified diphenyleneiodonium (DPI) as a tool compound that preferentially targets MNA neuroblastoma. Using proteomic assays we investigated the DPI mode of action, finding that DPI induces the proteasomal degradation of MYCN and could reverse some alterations induced by high levels of MYCN. These include profound changes in the expression of proteins participating in the mitochondrial electron transport chain. Metabolic and biological assays suggested that alterations in mitochondrial function and the associated production of reactive oxygen species (ROS) are critical DPI targets in the context of MNA. DPI reduced the survival, and malignant transformation of neuroblastoma across a panel of cell lines at clinically achievable concentrations. DPI also shrank tumors and prevented metastatic spread in zebrafish models of MYCN-driven neuroblastoma. These findings suggest that processes impacted by complex I inhibitors could be valuable new targets for the development of non-genotoxic drugs against high-risk MNA neuroblastoma. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=151 SRC="FIGDIR/small/619268v2_ufig1.gif" ALT="Figure 1"> View larger version (32K): org.highwire.dtl.DTLVardef@167e953org.highwire.dtl.DTLVardef@10749e4org.highwire.dtl.DTLVardef@1842598org.highwire.dtl.DTLVardef@c05d82_HPS_FORMAT_FIGEXP M_FIG C_FIG

cancer biology↗

bioRxiv2024

OXPHOS TARGETING OF MYCN-AMPLIFIED NEUROBLASTOMA

SummaryHigh risk - neuroblastoma (HR-NB) is a pediatric solid tumor with high lethality. Half of HR-NB are driven by MYCN gene amplification (MNA). These HR-NBs require high dosage chemotherapy and often relapse. Moreover, current therapies can cause severe long-term side effects and new therapies are urgently needed. This study investigates a novel therapeutic approach targeting the metabolic vulnerabilities of MNA NB cells. We discovered that Diphenyleneiodonium chloride (DPI), an inhibitor of flavoprotein enzymes and mitochondrial complex I, synergizes with mitoquinone mesylate (MitoQ), a mitochondria-targeted antioxidant in 2D and 3D in vitro models of NB. Similarly to DPI, MitoQ affects MNA cells in a MYCN-dependent fashion, being more toxic when MYCN levels are high. Furthermore, low nanomolar concentrations of MitoQ significantly decrease MYCN protein expression and induce differentiation of MNA cells. The DPI and MitoQ combination further synergizes with vincristine, a chemotherapeutic agent used in NB treatment. Phosphoproteomics and proteomics analysis suggests that the drug combination induces MNA NB cell death by arresting the cell cycle and inhibiting oxidative phosphorylation (OXPHOS) in the mitochondria. Thus, interference with mitochondrial metabolism may represent an effective strategy to enhance the activity of chemotherapeutic drugs in MNA-NB.

cancer biology↗

bioRxiv2024

Physical cell-cell interactions regulate transcriptional programmes that control the responses of high grade serous ovarian cancer patients to therapy.

The tumour microenvironment is composed of a complex cellular network involving cancer, stromal and immune cells in dynamic interactions. A large proportion of this network relies on direct physical interactions between cells, which may impact patient responses to clinical therapy. Doublets in scRNA-seq are usually excluded from analysis. However, they may represent directly interacting cells. To decipher the physical interaction landscape in relation to clinical prognosis, we inferred a physical cell-cell interaction (PCI) network from biological doublets in a scRNA-seq dataset of approximately 18,000 cells, obtained from 7 treatment-naive ovarian cancer patients. Focusing on cancer-stromal PCIs, we uncovered molecular interaction networks and transcriptional landscapes that stratified patients in respect to their clinical responses to standard therapy. Good responders featured PCIs involving immune cells interacting with other cell types including cancer cells. Poor responders lacked immune cell interactions, but showed a high enrichment of cancer-stromal PCIs. To explore the molecular differences between cancer-stromal PCIs between responders and non-responders, we identified correlating gene signatures. We constructed ligand-receptor interaction networks and identified associated downstream pathways. The reconstruction of gene regulatory networks and trajectory analysis revealed distinct transcription factor (TF) clusters and gene modules that separated doublet cells by clinical outcomes. Our results indicate (i) that transcriptional changes resulting from PCIs predict the response of ovarian cancer patients to standard therapy, (ii) that immune reactivity of the host against the tumour enhances the efficacy of therapy, and (iii) that cancer-stromal cell interaction can have a dual effect either supporting or inhibiting therapy responses.

bioinformatics↗

bioRxiv2024

Spatial proteomics and transcriptomics of placenta accreta spectrum

In severe Placenta Accreta Spectrum (PAS), trophoblasts gain deep access in the myometrium (placenta increta). This study investigated alterations at the fetal-maternal interface in PAS cases using a systems biology approach consisting of immunohistochemistry, spatial transcriptomics and proteomics. We identified spatial variation in the distribution of CD4+, CD3+ and CD8+ T-cells at the maternal-interface in placenta increta cases. Spatial transcriptomics identified transcription factors involved in promotion of trophoblast invasion such as AP-1 subunits ATF-3 and JUN, and NFKB were upregulated in regions with deep myometrial invasion. Pathway analysis of differentially expressed genes demonstrated that degradation of extracellular matrix (ECM) and class 1 MHC protein were increased in increta regions, suggesting local tissue injury and immune suppression. Spatial proteomics demonstrated that increta regions were characterised by excessive trophoblastic proliferation in an immunosuppressive environment. Expression of inhibitors of apoptosis such as BCL-2 and fibronectin were increased, while CTLA-4 was decreased and increased expression of PD-L1, PD-L2 and CD14 macrophages. Additionally, CD44, which is a ligand of fibronectin that promotes trophoblast invasion and cell adhesion was also increased in increta regions. We subsequently examined ligand receptor interactions enriched in increta regions, with interactions with ITG{beta}1, including with fibronectin and ADAMS, emerging as central in increta. These ITG{beta}1 ligand interactions are involved in activation of epithelial-mesenchymal transition and remodelling of ECM suggesting a more invasive trophoblast phenotype. In PAS, we suggest this is driven by fibronectin via AP-1 signalling, likely as a secondary response to myometrial scarring. Overall, this study suggests the biological processes leading to deep trophoblast invasion in the myometrium in placenta increta are as a result of upregulation of transcription factors and subsequent genes and proteins which promote trophoblast invasion. This occurs in a locally immune suppressed environment, with increased ECM degradation suggesting these findings are secondary to iatrogenic uterine injury. Significance statementPlacenta Accreta Spectrum (PAS) is a rare pregnancy complication, where the placenta fails to separate from the womb resulting in severe bleeding, which is associated with significant maternal morbidity and mortality. As Caesarean section rates increase, the incidence of PAS is increasing. The underlying pathophysiology of PAS is poorly understood. Here, we apply a spatial multi-omic approach to explore the biologic changes at the maternal-fetal interface in severe PAS (placenta increta). Using spatial transcriptomics and proteomics, we identified genes and proteins that are dysregulated in severe PAS involving processes such as extracellular matrix degradation, local immune suppression and promotion of epithelial-mesenchymal transition. This study provides new insights into the biological changes and underlying pathophysiology leading to placenta increta.

bioinformatics↗

bioRxiv2022

Kinase Suppressor of RAS 1 (KSR1) maintains the transformed phenotype of BRAFV600E mutant human melanoma cells

KSR1 is a scaffolding protein for the RAS-RAF-MEK-ERK pathway, which is one of the most frequently altered pathways in human cancers. Previous results have shown that KSR1 has a critical role in mutant RAS mediated transformation. Here, we examined the role of KSR1 in mutant BRAF transformation. We used CRISPR/Cas9 to knock out KSR1 in a BRAFV600E transformed melanoma cell line. KSR1 loss produced a complex phenotype characterized by impaired proliferation, cell cycle defects, decreased transformation, decreased invasive migration, increased cellular senescence, and increased apoptosis. To decipher this phenotype, we used a combination of proteomic ERK substrate profiling, global protein expression profiling, and biochemical validation assays. The results suggest that KSR1 directs ERK to phosphorylate substrates that have a critical role in ensuring cell survival. The results further indicate that KSR1 loss induces the activation of p38 Mitogen-Activated Protein Kinase (MAPK) and subsequent cell cycle aberrations and senescence. In summary, KSR1 function plays a key role in oncogenic BRAF transformation.

cancer biology↗

bioRxiv2022

Small gene networks can delineate immune cell states and characterize immunotherapy response in melanoma

BackgroundSingle-cell sequencing studies have elucidated some of the underlying mechanisms responsible for immune checkpoint inhibitor (ICI) response, but are difficult to implement as a general strategy or in a clinical diagnostic setting. In contrast, bulk RNAseq is now routine for both research and clinical applications. Therefore, our analysis extracts small transcription factor-directed co-expression networks (regulons) from single-cell RNA-seq data and uses them to deconvolute immune functional states from bulk RNA-seq data to characterize patient responses. MethodsRegulons were inferred in pre-treatment CD45+ cells from metastatic melanoma samples (n=19) treated with first-line ICI therapy (discovery dataset). A logistic regression-based classifier identified immune cell states associated with response, which were characterized according to differentially active, cell-state specific regulons. The complexity of these regulons was reduced and scored in bulk RNAseq melanoma samples from four independent studies (n=209, validation dataset). Patients were clustered according to their regulon scores, and the associations between cluster assignment, response, and survival were determined. Intercellular communication analysis of cell states was performed, and the resulting effector genes were analyzed by trajectory inference. ResultsRegulons preserved the information of gene expression data and accurately delineated immune cell phenotypes, despite reducing dimensionality by > 100-fold. Four cell states, termed exhausted T cells, monocyte lineage cells, memory T cells, and B cells, were associated with therapeutic responses in the discovery dataset. The cell states were characterized by seven differentially active and specific regulons that showed low specificity in non-immune cells. Four clusters with significantly different response outcomes (P <0.001) were identified in the bulk RNAseq validation cohort. An intercellular link between exhausted T cells and monocyte lineage cells was established, whereby their cell numbers were correlated, and exhausted T cells predicted prognosis as a function of monocyte lineage cell number. Analysis of ligand - receptor expression suggested that monocyte lineage cells drive exhausted T cells into terminal exhaustion through programs that regulate antigen presentation, chronic inflammation, and negative co-stimulation. ConclusionsRegulon-based characterization of cell states provides robust and functionally informative markers that can deconvolve bulk RNA-seq data to identify ICI responders.

immunology↗

bioRxiv2022

Proteasomal downregulation of the pro-apoptotic MST2 pathway contributes to BRAF inhibitor resistance in melanoma

The RAS-RAF-MEK-ERK pathway is hyperactivated in almost all malignant melanomas, and mutations in BRAF or NRAS account for most of these cases. BRAF inhibitors are highly efficient for treating patients with BRAFV600E mutations, but tumours frequently acquire resistance within a few months. Multiple resistance mechanisms have been identified, due to mutations or network adaptations that revive ERK signalling. We have previously shown that RAF proteins inhibit the MST2 proapoptotic pathway in a kinase independent fashion. Here, we have investigated the role of the MST2 pathway in mediating resistance to BRAF inhibitors. We show that the BRAFV600E mutant protein, but not the wildtype BRAF protein, strongly binds to MST2 and inhibits MST2 pro-apoptotic signalling. Downregulation of MST2 reduces BRAF inhibitor induced apoptosis. In BRAF inhibitor resistant cell lines MST2 pathway proteins are downregulated by ubiquitination and subsequent proteasomal degradation rendering cells refractory to MST2 pathway induced apoptosis. Restoration of apoptosis can be achieved by increasing MST2 pathway protein expression using proteasome inhibitors. In summary, we show that the MST2 pathway plays a role in the acquisition of BRAF inhibitor resistance in melanoma.

molecular biology↗

bioRxiv2021

Transcriptional profiling of early differentiation of primary human mesenchymal stem cells into chondrocytes

Articular cartilage has only very limited regenerative capacities in humans. Tissue engineering techniques for cartilage damage repair are limited in the production of hyaline cartilage. Mesenchymal stem/stromal cells (MSCs) are multipotent stem cells and can be differentiated into mature cartilage cells, chondrocytes, which could be used for repairing damaged cartilage. Chondrogenesis is a highly complex, relatively inefficient process lasting over 3 weeks in vitro. In order to better understand chondrogenic differentiation, especially the commitment phase, we have performed transcriptional profiling of MSC differentiation into chondrocytes from early timepoints starting 15 minutes after induction to 16 hours and fully differentiated chondrocytes at 21 days. Transcriptional gene regulatory networks (GRN) were identified using time-course clustering and upstream-regulator predictions which revealed that cells start epigenetic reprogramming as early as 2 hours after induction and commit to differentiation within 4-6 hours. After that they adapt their gene expression to cater for differentiation specific protein production. These results suggest that interventions to improve the frequency and efficiency of differentiation should target early processes.

molecular biology↗

bioRxiv2020

Periodic propagating activation waves coordinate Rho GTPase network dynamics at the leading and trailing edges during cell migration

Migrating cells need to coordinate distinct leading and trailing edge dynamics but the underlying mechanisms are unclear. Here, we combine experiments and mathematical modeling to elaborate the minimal autonomous biochemical machinery necessary and sufficient for this dynamic coordination and cell movement. RhoA activates Rac1 via DIA and inhibits Rac1 via ROCK, while Rac1 inhibits RhoA through PAK. Our data suggest that in motile, polarized cells, RhoA-ROCK interactions prevail at the rear whereas RhoA-DIA interactions dominate at the front where Rac1/Rho oscillations drive protrusions and retractions. At the rear, high RhoA and low Rac1 activities are maintained until a wave of oscillatory GTPase activities from the cell front reaches the rear, inducing transient GTPase oscillations and RhoA activity spikes. After the rear retracts, the initial GTPase pattern resumes. Our findings show how periodic, propagating GTPase waves coordinate distinct GTPase patterns at the leading and trailing edge dynamics in moving cells.

systems biology↗

bioRxiv2018

Transcriptional regulatory mechanisms of fibrosis development in mouse lung tissue exposed to carbon nanotubes

BackgroundCarbon nanotubes (CNTs) usage has rapidly increased in the last few decades due to their unique properties, exploited in various industrial and commercial products. Certain types of CNTs cause adverse health effects, including chronic inflammation and fibrosis. Despite the large number of in vitro and in vivo studies evaluating these effects, many important questions remain unanswered due to a lack of mechanistic understanding of how CNTs induce cellular stress responses. In order to predict CNT toxicity, it is important to understand which transcriptional programs are specifically activated in response to CNTs, and what similarities and differences exist in relation to other toxic inducers exerting similar adverse effects.\n\nResultsA systems biology approach was applied to reveal complex interactions at the molecular level in mouse lung tissue in response to different fibrosis inducers: two types of multi-walled CNTs, NM-401 and NRCWE-26, and bleomycin (BLM). Based on mRNA gene expression profiles, we inferred gene regulatory networks (GRNs) to capture functional hierarchical regulatory structures between genes and their regulators. We found that activities of the transcription factors (TFs) Myc, Arid5a and Mxd1 were associated with the regulation of cytokine transcription in response to CNTs, while in response to BLM treatment, Myc was associated with p53 signaling. TF Litaf was identified as the essential regulator for noncanonical signaling of TLR2/4 driven by CNTs. Despite the different nature of the lung injury caused by CNTs and BLM, we identified common stress response modules, that included DNA damage (TFs: E2f8, E2f1, Foxm1), M1/M2 macrophage polarization (TF: Mafb), Interferon response (TFs: Irf7, Stat2 and Irf9) for all agents.\n\nConclusionsThese results suggest that the reconstruction and analysis of TF-centric gene interaction networks can reveal key targets and regulators of cellular stress responses to toxic agents.

pharmacology and toxicology↗