Biology subjects

Drake, C.

Publications and source records attributed to Drake, C..

6 recordsLinked to original sources

bioRxiv2024

A comprehensive pharmacological survey across heterogeneous patient-derived GBM stem cell models

Despite substantial drug discovery investments, the lack of any significant therapeutic advancement in the treatment of glioblastoma (GBM) over the past two decades calls for more innovation in the identification of effective treatments. The inter-and intra-patient heterogeneity of GBM presents significant obstacles to effective clinical progression of novel treatments by contributing to tumour plasticity and rapid drug resistance that confounds contemporary target directed drug discovery strategies. Phenotypic drug screening is ideally suited to heterogeneous diseases, where targeting specific oncogenic drivers have been broadly ineffective. Our hypothesis is that a modern phenotypic led approach using disease relevant patient-derived GBM stem cell systems will be the most productive approach to identifying new therapeutic targets, drug classes and future drug combinations that target the heterogeneity of GBM. In this study we incorporate a panel of patient-derived GBM stem cell lines into an automated and unbiased Cell Painting assay to quantify multiple GBM stem cell phenotypes. By screening several compound libraries at multiple concentrations across a panel of patient-derived GBM stem cells we provide the first comprehensive survey of distinct pharmacological classes and known druggable targets, including all clinically approved drug classes and oncology drug candidates upon multiple GBM stem cell phenotypes linked to cell proliferation, survival and differentiation. Our data set representing, 3866 compounds, 2.2million images and 64000 datapoints is the largest phenotypic screen carried out to date on a panel of patient-derived GBM stem cell models that we are aware of. We seek to identify agents and target classes which engender potent activity across heterogenous GBM genotypes and phenotypes, in this study we further characterize two validated target classes, histone deacetylase inhibitors and cyclin dependent kinases that exert broad and potent effects on the phenotypic and transcriptomic profiles of GBM stem cells. Here we present all validated hit compounds and their target assignments for the GBM community to explore.

cancer biology↗

bioRxiv2024

Drug combinations targeting FAK and MEK overcomes tumour heterogeneity in glioblastoma

Glioblastoma (GBM) is an aggressive brain tumour with limited treatment options and poor prognosis, largely due to its heterogeneity and the involvement of multiple intracellular signalling pathways that contribute to drug resistance. Standard therapies have not significantly improved patient outcomes over the past two decades. While recent advancements in targeted drug combination therapies, such as dabrafenib and trametinib, show promise for certain GBM subgroups, identifying drug combinations effective across the broader GBM population remains a challenge. Integrin-mediated signalling, particularly through Focal Adhesion Kinase (FAK), plays a pivotal role in GBM pathogenesis and invasion, making it a potential therapeutic target [1]. In our study, we utilized a chemogenomic screening approach to identify synergistic drug combinations that target FAK in glioblastoma. We initially employed a CRISPR-engineered GBM model to assess the effects of FAK depletion and discovered that combining FAK inhibitors with MEK inhibitors, particularly trametinib, demonstrated synergistic effects. This potent combination was validated through various 2D & 3D assays, including cell viability/apoptotic assessment, synergistic analysis, cellular imaging, and target engagement assays. The combination also effectively inhibited spheroid growth and invasion across a diverse panel of patient derived GBM stem cells. Molecular mechanisms underlying these effects included suppression of multiple kinase signalling pathways and enhanced apoptosis, elucidated using Reverse Phase Protein Array (RPPA) profiling and western blot validation. In vivo, the combination therapy significantly reduced tumour volume in orthotopic transplantation models. These findings suggest that combining FAK and MEK inhibitors represent a promising therapeutic strategy to overcome the challenges of GBM treatment.

cancer biology↗

bioRxiv2022

Improving 3D Edge Detection for Visual Inspection of MRI Coregistration and Alignment

Detecting and visualizing edges is important in several neuroimaging and medical imaging applications. For example, it is common to use edge maps to ensure the automatic alignment of low-resolution functional MRI images to match a high-resolution structural image has been successful. Specifically, software toolboxes like FSL and AFNI generate volumetric edge maps that can be particularly useful for visually assessing the alignment of datasets, overlaying the edge map of one on the other. Therefore, edge maps play a crucial role in quality assurance. Popular methods for computing edges are based on either the first derivative of the image as in FSL, or a variation of the Canny Edge detection method as implemented in AFNI. The crucial algorithmic parameter for adjustment for each of these methods relates to the image intensity. However, image intensity is relative and can be quite variable in most neuroimaging modalities. Further, the existing approaches do not necessarily generate a closed edge/surface, which can reduce the ability to determine the correspondence between a represented edge and another image. We suggest that using the second derivative (difference of Gaussian, or DoG) of the image to generate edges resolves both these issues. This method primarily operates by specifying a spatial scale of interest (which is typically known in medical imaging) rather than a contrast scale, and creates closed surfaces by definition. We describe some convenient implementation features (for both efficiency and visual quality) developed here, and we provide open source implementations of this method as both online and high performance portable code. Finally, we include this method as part of both the AFNI and FSL software packages.

neuroscience↗

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

A Mouse Model of Brittle Cornea Syndrome caused by mutation in Zfp469.

Brittle Cornea Syndrome (BCS) is a rare recessive condition characterised by extreme thinning of the cornea and sclera. BCS results from loss-of-function mutations in the poorly understood genes ZNF469 or PRDM5. In order to determine the function of ZNF469 and to elucidate pathogenic mechanisms, we used genome editing to recapitulate a human ZNF469 BCS mutation in the orthologous mouse gene, Zfp469. Ophthalmic phenotyping showed that homozygous Zfp469 mutation causes significant central and peripheral corneal thinning arising from reduced stromal thickness. Expression of key components of the corneal stroma in primary keratocytes from Zfp469BCS/BCS mice is affected, including decreased Col1a1 and Col1a2 expression. This alters the type I:type V collagen ratio and results in collagen fibrils with smaller diameter and increased fibril density in homozygous mutant corneas, correlating with decreased biomechanical strength in the cornea. Cell-derived matrices generated by primary keratocytes show reduced deposition of type I collagen offering an in vitro model for stromal dysfunction. Work remains to determine whether modulating ZNF469 activity will have therapeutic benefit in BCS or in conditions such as keratoconus where the cornea thins progressively. Summary statementA mouse model of Brittle Cornea Syndrome was created to elucidate molecular mechanisms underlying pathology of this rare connective tissue disorder in which extremely thin corneas rupture, causing irreversible blindness.

genetics↗

bioRxiv2018

Network-Based Biomarkers Enable Cross-Disease Biomarker Discovery

Biomarkers lie at the heart of precision medicine, biodiversity monitoring, agricultural pathogen detection, amongst others. Surprisingly, while rapid genomic profiling is becoming ubiquitous, the development of biomarkers almost always involves the application of bespoke techniques that cannot be directly applied to other datasets. There is an urgent need for a systematic methodology to create biologically-interpretable molecular models that robustly predict key phenotypes. We therefore created SIMMS: an algorithm that fragments pathways into functional modules and uses these to predict phenotypes. We applied SIMMS to multiple data-types across four diseases, and in each it reproducibly identified subtypes, made superior predictions to the best bespoke approaches, and identified known and novel signaling nodes. To demonstrate its ability on a new dataset, we measured 33 genes/nodes of the PIK3CA pathway in 1,734 FFPE breast tumours and created a four-subnetwork prediction model. This model significantly out-performed existing clinically-used molecular tests in an independent 1,742-patient validation cohort. SIMMS is generic and can work with any molecular data or biological network, and is freely available at: https://cran.r-project.org/web/packages/SIMMS.

bioinformatics↗