Biology subjects

Turunen, M.

Publications and source records attributed to Turunen, M..

9 recordsLinked to original sources

bioRxiv2023

Identification and Pharmacological Targeting of Treatment-Resistant, Stem-like Breast Cancer Cells for Combination Therapy

Tumors frequently harbor isogenic yet epigenetically distinct subpopulations of multi-potent cells with high tumor-initiating potential--often called Cancer Stem-Like Cells (CSLCs). These can display preferential resistance to standard-of-care chemotherapy. Single-cell analyses can help elucidate Master Regulator (MR) proteins responsible for governing the transcriptional state of these cells, thus revealing complementary dependencies that may be leveraged via combination therapy. Interrogation of single-cell RNA sequencing profiles from seven metastatic breast cancer patients, using perturbational profiles of clinically relevant drugs, identified drugs predicted to invert the activity of MR proteins governing the transcriptional state of chemoresistant CSLCs, which were then validated by CROP-seq assays. The top drug, the anthelmintic albendazole, depleted this subpopulation in vivo without noticeable cytotoxicity. Moreover, sequential cycles of albendazole and paclitaxel--a commonly used chemotherapeutic --displayed significant synergy in a patient-derived xenograft (PDX) from a TNBC patient, suggesting that network-based approaches can help develop mechanism-based combinatorial therapies targeting complementary subpopulations. Statement of significanceNetwork-based approaches, as shown in a study on metastatic breast cancer, can develop effective combinatorial therapies targeting complementary subpopulations. By analyzing scRNA-seq data and using clinically relevant drugs, researchers identified and depleted chemoresistant Cancer Stem-Like Cells, enhancing the efficacy of standard chemotherapies.

systems biology↗

bioRxiv2023

Elucidating Compound Mechanism of Action and Polypharmacology with a Large-scale Perturbational Profile Compendium

Drug Mechanism of Action (MoA) is often represented as a small repertoire of tissue-independent, high-affinity binding targets. Yet drug activity and polypharmacology are also manifested through a broad range of off-target and tissue-specific effector proteins. To address this dichotomy, we generated a compendium of drug perturbation profiles for >700 oncology drugs in cell lines representing high-fidelity models of 23 aggressive tumor subtypes, as well as an integrative framework for the proteome-wide assessment of drug-mediated, tissue-specific differential protein activity. Extending MoA and polypharmacology assessment via proteome-wide, multi-tissue analyses revealed novel polypharmacology, including for MAPK, PI3K, and folate pathways inhibitors--as supported by Western blots, thermal shift assays, and structural analysis--as well as functional inhibitors of challenging oncoprotein targets, including MYC, CTNNB1, CENPF and UHRF1. The dataset and associated computational framework might be extensible to additional compound libraries, supporting global, quantitative approaches to defining the mechanisms of action of many drugs.

systems biology↗

bioRxiv2023

Network-based elucidation of colon cancer drug resistance by phosphoproteomic time-series analysis

Aberrant signaling pathway activity is a hallmark of tumorigenesis and progression, which has guided targeted inhibitor design for over 30 years. Yet, adaptive resistance mechanisms, induced by rapid, context-specific signaling network rewiring, continue to challenge therapeutic efficacy. By leveraging progress in proteomic technologies and network-based methodologies, over the past decade, we developed VESPA--an algorithm designed to elucidate mechanisms of cell response and adaptation to drug perturbations--and used it to analyze 7-point phosphoproteomic time series from colorectal cancer cells treated with clinically-relevant inhibitors and control media. Interrogation of tumor-specific enzyme/substrate interactions accurately inferred kinase and phosphatase activity, based on their inferred substrate phosphorylation state, effectively accounting for signal cross-talk and sparse phosphoproteome coverage. The analysis elucidated time-dependent signaling pathway response to each drug perturbation and, more importantly, cell adaptive response and rewiring that was experimentally confirmed by CRISPRko assays, suggesting broad applicability to cancer and other diseases.

systems biology↗

bioRxiv2022

Lineage-specific oncogenes drive growth of major forms of human cancer using common downstream mechanisms

Mutations in hundreds of genes have been associated with formation of human cancer, with different oncogenic lesions prevalent in different cancer types. Yet, the malignant phenotype is simple, characterized by unrestricted growth of cells that invade neighboring healthy tissue and in many cases metastasize to distant organs. One possible hypothesis explaining this dichotomy is that the cancer genes regulate a common set of target genes, which then function as master regulators of essential cancer phenotypes, such as growth, invasion and metastasis. To identify mechanisms that drive the most fundamental feature shared by all tumors - unrestricted cell proliferation - we used a multiomic approach to identify common transcriptional and posttranslational targets of major oncogenic pathways active in different cancer types, and combined this analysis with known regulators of the cell cycle. We identified translation and ribosome biogenesis as common targets of both transcriptional and posttranslational oncogenic pathways. By combining proteomic analysis of clinical samples with functional studies of cell cultures, we also establish NOLC1 as a key node whose convergent regulation both at transcriptional and posttranslational level is critical for tumor cell proliferation. Our results indicate that lineage-specific oncogenic pathways commonly regulate the same set of targets important for growth control, revealing novel key downstream nodes that could be targeted for cancer therapy or chemoprevention.

cancer biology↗

bioRxiv2022

Systematic Elucidation and Pharmacological Targeting of Tumor-Infiltrating Regulatory T Cell Master Regulators

Due to their immunosuppressive role, tumor-infiltrating regulatory T cells (TI-Tregs) represent attractive therapeutic targets. Analysis of TI vs. peripheral Tregs (P-Tregs) from 36 patients, across four malignancies, identified 17 candidate Master Regulators (MRs), predicted to mechanistically regulate TI-Tregs transcriptional state. In vivo, pooled CRISPR-KO screening, using a hematopoietic stem cell transplant model, confirmed essentiality of 7 of 17 MRs in TI-Treg recruitment and/or retention to the TME, without affecting other T cell subtypes, while individual knockout of the most significant MR (TRPS1) significantly reduced tumor allograft growth. TI-Treg drug perturbation profile analysis identified drugs capable of inverting the TI-Treg-specific MR activity signature at low concentration. Low dose treatment with gemcitabine (top prediction) inhibited tumor growth in immunocompetent but not immunocompromised allografts, increased PD-1 inhibitor efficacy, and depleted TI-Tregs in vivo. The study provides key insight into Treg infiltration mechanism and a gene reporter assay to identify additional small molecule inhibitors. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=140 HEIGHT=200 SRC="FIGDIR/small/481404v1_ufig1.gif" ALT="Figure 1"> View larger version (26K): org.highwire.dtl.DTLVardef@1cca60borg.highwire.dtl.DTLVardef@a93ce6org.highwire.dtl.DTLVardef@dd2aa2org.highwire.dtl.DTLVardef@1a2c98_HPS_FORMAT_FIGEXP M_FIG C_FIG

cancer biology↗

bioRxiv2021

Interrogation of genome-wide, experimentally dissected gene regulatory networks reveals mechanisms underlying dynamic cellular state control

Pooled CRISPRi-mediated silencing of >1,000 transcriptional regulators expressed in single colorectal adenocarcinoma cells, followed by single-cell RNA-seq profiling at two timepoints, 1 day and 4 days, allowed reverse engineering the underlying tumor context-specific, causal regulatory network. Furthermore, the availability of experimentally derived, highly multiplexed gene reporter assays for each regulator, as identified by this analysis, allowed accurate assessment of differential protein activity following silencing of each regulator, thus providing proof-of-concept for generating comprehensive, tissue-specific networks of transcriptional and post-translational interactions. Analysis of this causal network allowed elucidation of complex autoregulatory mechanisms that have eluded previous computational approaches and supported systematic elucidation of cooperative mechanisms, where one regulatory protein can modulate the activity of another regulatory protein, as well as transcriptional mimicry, where one regulatory protein can phenocopy others.

systems biology↗

bioRxiv2020

Pancreatic Ductal Adenocarcinoma Comprises Coexisting Regulatory States with both Common and Distinct Dependencies

Despite extensive efforts, reproducible assessment of pancreatic ductal adenocarcinoma (PDA) heterogeneity and plasticity at the single cell level remains elusive. Systematic, network-based analysis of regulatory protein activity in single cells identified three PDA Developmental Lineages (PDLs), coexisting in virtually all tumors, whose transcriptional states are mechanistically driven by aberrant activation of Master Regulator (MR) proteins associated with gastrointestinal lineages (GLS state), morphogen and EMT pathways (MOS state), and acinar-to-ductal metaplasia (ALS state), respectively. Each PDL is further subdivided into sub-states characterized by low vs. high MAPK pathway activity. This taxonomy was remarkably conserved across multiple cohorts, cell lines, and PDX models, and harmonized with bulk profile analyses. Cross-state plasticity and MR essentiality was confirmed by barcode-based lineage tracing and CRISPR/Cas9 assays, respectively, while MR ectopic expression induced PDL transdifferentiation. Together these data provide a mechanistic foundation for PDA heterogeneity and a roadmap for targeting PDA cellular subtypes.

cancer biology↗

bioRxiv2020

Diminishing effects of mechanical loading over time during rat Achilles tendon healing

Mechanical loading affects tendon healing and recovery. However, our understanding about how physical loading affects recovery of viscoelastic functions, collagen production and tissue organisation is limited. The objective of this study was to investigate how different magnitudes of loading affects biomechanical and collagen properties of healing Achilles tendons over time. Achilles tendon from female Sprague Dawley rats were cut transversely and divided into two groups; normal loading (control) and reduced loading by Botox (unloading). The rats were sacrificed at 1, 2- and 4-weeks post-injury and mechanical testing (creep test and load to failure), small angle x-ray scattering (SAXS) and histological analysis were performed. The effect of unloading was primarily seen at the early time points, with inferior mechanical and collagen properties (SAXS), and reduced histological maturation of the tissue in unloaded compared to loaded tendons. However, by 4 weeks no differences remained. SAXS and histology revealed heterogeneous tissue maturation with more mature tissue at the peripheral region compared to the center of the callus. Thus, mechanical loading advances Achilles tendon biomechanical and collagen properties earlier compared to unloaded tendons, and the spatial variation in tissue maturation and collagen organization across the callus suggests important regional (mechano-) biological activities that require more investigation.

bioengineering↗

bioRxiv2017

CRISPR/Cas9 screening using unique molecular identifiers

Loss of function screening by CRISPR/Cas9 gene knockout with pooled, lentiviral guide libraries is a widely applicable method for systematic identification of genes contributing to diverse cellular phenotypes. Here, random sequence labels (RSLs) are incorporated into the guide library, which act as unique molecular identifiers (UMIs) to allow massively parallel lineage tracing and lineage dropout screening. RSLs greatly improve the reproducibility of results by increasing both the precision and the accuracy of screens. They reduce the number of cells and sequencing reads needed to reach a set statistical power, or allow a more robust screen using the same number of cells.

genomics↗