Molecular deconstruction, detection, and computational prediction of microenvironment-modulated cellular responses to cancer therapeutics

Mechanisms of mitotic inhibition in human aorta endothelial cells: Molecular and morphological in vitro spectroscopic studies

Mitotic inhibitors are drugs commonly used in chemotherapy, but their nonspecific and indiscriminate distribution throughout the body after intravenous administration can lead to serious side effects, particularly on the cardiovascular system. In this context, our investigation into the mechanism of the cytotoxic effects on endothelial cells of mitotic inhibitors widely used in cancer treatment, such as paclitaxel (also known as Taxol) and Vinca alkaloids, holds significant practical implications. Understanding these mechanisms can lead to more targeted and less harmful cancer treatments. Human aorta endothelial cells (HAECs) were incubated with selected mitotic inhibitors in a wide range of concentrations close to those in human plasma during anticancer therapy. The analysis of single cells imaged by Raman spectroscopy allowed for visualization of the nuclear, cytoplasmic, and perinuclear areas to assess biochemical changes induced by the drug's action. The results showed significant changes in the morphology and molecular composition of the nucleus. Moreover, an effect of a given drug on the cytoplasm was observed, which can be related to its mechanism of action (MoA). Raman data supported by fluorescence microscopy measurements identified unique changes in DNA form and proteins and revealed drug-induced inflammation of endothelial cells. The primary goal of mitotic inhibitors is based on the impairment of tubulin formation and the inhibition of the mitosis process. While all three drugs affect microtubules and disrupt cell division, they do so through different MoA, i.e., Vinca alkaloids inhibit microtubule formation, whereas paclitaxel stabilizes microtubules. To sum up, the work shows how a specific drug can interact with endothelial cells.

Automatic Transformation and Integration to Improve Visualization and Discovery of Latent Effects in Imaging Data

Proper data transformation is an essential part of analysis. Choosing appropriate transformations for variables can enhance visualization, improve efficacy of analytical methods, and increase data interpretability. However determining appropriate transformations of variables from high-content imaging data poses new challenges. Imaging data produces hundreds of covariates from each of thousands of images in a corpus. Each of these covariates will have a different distribution and need a potentially different transformation. As such imaging data produces hundreds of covariates, determining an appropriate transformation for each of them is infeasible by hand. In this paper we explore simple, robust, and automatic transformations of high-content image data. A central application of our work is to microenvironment microarray bio-imaging data from the NIH LINCS program. We show that our robust transformations enhance visualization and improve the discovery of substantively relevant latent effects. These transformations enhance analysis of image features individually and also improve data integration approaches when combining together multiple features. We anticipate that the advantages of this work will likely also be realized in the analysis of data from other high-content and highly-multiplexed technologies like Cell Painting or Cyclic Immunofluorescence. Software and further analysis can be found at gjhunt.github.io/rr.

Graphene-Augmented Nanofiber Scaffolds Trigger Gene Expression Switching of Four Cancer Cell Types

Three-dimensional (3D) customized scaffolds are anticipated to provide new frontiers in cell manipulation and advanced therapy methods. Here, we demonstrate the application of hybrid 3D porous scaffolds, representing networks of highly aligned self-assembled ceramic nanofibers, for culturing four types of cancer cells. Ultrahigh aspect ratio (∼10⁷) of graphene augmented fibers of tailored nanotopology is shown as an alternative tool to substantially affect cancerous gene expression, eventually due to differences in local biomechanical features of the cell–matrix interactions. Here, we report a clear selective up- and down-regulation of groups of markers for breast cancer (MDA-MB231), colorectal cancer (CaCO2), melanoma (WM239A), and neuroblastoma (Kelly) depending on only fiber orientation and morphology without application of any other stimulus. Changes in gene expression are also revealed for Mitomycin C treatment of MDA-MB231, making the scaffold a suitable platform for testing of anticancer agents. This allows an opportunity for selective “clean” guidance to a deep understanding of mechanisms of cancer cells progressive growth and tumor formation without possible side effects by manipulation with the specific markers.

Molecular crosstalk between tumour and brain parenchyma instructs histopathological features in glioblastoma

The histopathological and molecular heterogeneity of glioblastomas represents a major obstacle for effective therapies. Glioblastomas do not develop autonomously, but evolve in a unique environment that adapts to the growing tumour mass and contributes to the malignancy of these neoplasms. Here, we show that patient-derived glioblastoma xenografts generated in the mouse brain from organotypic spheroids reproducibly give rise to three different histological phenotypes: (i) a highly invasive phenotype with an apparent normal brain vasculature, (ii) a highly angiogenic phenotype displaying microvascular proliferation and necrosis and (iii) an intermediate phenotype combining features of invasion and vessel abnormalities. These phenotypic differences were visible during early phases of tumour development suggesting an early instructive role of tumour cells on the brain parenchyma. Conversely, we found that tumour-instructed stromal cells differentially influenced tumour cell proliferation and migration in vitro, indicating a reciprocal crosstalk between neoplastic and non-neoplastic cells. We did not detect any transdifferentiation of tumour cells into endothelial cells. Cell type-specific transcriptomic analysis of tumour and endothelial cells revealed a strong phenotype-specific molecular conversion between the two cell types, suggesting co-evolution of tumour and endothelial cells. Integrative bioinformatic analysis confirmed the reciprocal crosstalk between tumour and microenvironment and suggested a key role for TGFβ1 and extracellular matrix proteins as major interaction modules that shape glioblastoma progression. These data provide novel insight into tumour-host interactions and identify novel stroma-specific targets that may play a role in combinatorial treatment strategies against glioblastoma.

Epigenetic assays for chemical biology and drug discovery

The implication of epigenetic abnormalities in many diseases and the approval of a number of compounds that modulate specific epigenetic targets in a therapeutically relevant manner in cancer specifically confirms that some of these targets are druggable by small molecules. Furthermore, a number of compounds are currently in clinical trials for other diseases including cardiovascular, neurological and metabolic disorders. Despite these advances, the approved treatments for cancer only extend progression-free survival for a relatively short time and being associated with significant side effects. The current clinical trials involving the next generation of epigenetic drugs may address the disadvantages of the currently approved epigenetic drugs.

The identification of chemical starting points of many drugs often makes use of screening in vitro assays against libraries of synthetic or natural products. These assays can be biochemical (using purified protein) or cell-based (using for example, genetically modified, cancer cell lines or primary cells) and performed in microtiter plates, thus enabling a large number of samples to be tested. A considerable number of such assays are available to monitor epigenetic target activity, and this review provides an overview of drug discovery and chemical biology and describes assays that monitor activities of histone deacetylase, lysine-specific demethylase, histone methyltransferase, histone acetyltransferase and bromodomain. It is of critical importance that an appropriate assay is developed and comprehensively validated for a given drug target prior to screening in order to improve the probability of the compound progressing in the drug discovery value chain.

Adaptive mechanisms of resistance to anti-neoplastic agents

Intrinsic and acquired resistance to conventional and targeted therapeutics is a fundamental reason for treatment failure in many cancer patients. Targeted approaches to overcome chemoresistance as well as resistance to targeted approaches require in depth understanding of the underlying molecular mechanisms. The anti-cancer activity of a drug can be limited by a broad variety of molecular events at different levels of drug action in a cell-autonomous and non-cell-autonomous manner. This review summarizes recent insights into the adaptive mechanisms used by tumours to resist therapy including cellular phenotypic plasticity, dynamic alterations of the tumour microenvironment, activation of redundant signal transduction pathways, modulation of drug target expression levels, and exploitation of pro-survival responses.

Microenvironment rigidity modulates responses to the HER2 receptor tyrosine kinase inhibitor lapatinib via YAP and TAZ transcription factors

Stiffness is a biophysical property of the extracellular matrix that modulates cellular functions, including proliferation, invasion, and differentiation, and it also may affect therapeutic responses. Therapeutic durability in cancer treatments remains a problem for both chemotherapies and pathway-targeted drugs, but the reasons for this are not well understood. Tumor progression is accompanied by changes in the biophysical properties of the tissue, and we asked whether matrix rigidity modulated the sensitive versus resistant states in HER2-amplified breast cancer cell responses to the HER2-targeted kinase inhibitor lapatinib. The antiproliferative effect of lapatinib was inversely proportional to the elastic modulus of the adhesive substrata. Down-regulation of the mechanosensitive transcription coactivators YAP and TAZ, either by siRNA or with the small-molecule YAP/TEAD inhibitor verteporfin, eliminated modulus-dependent lapatinib resistance. Reduction of YAP in vivo in mice also slowed the growth of implanted HER2-amplified tumors, showing a trend of increasing sensitivity to lapatinib as YAP decreased. Thus we address the role of stiffness in resistance to and efficacy of a HER2 pathway-targeted therapeutic via the mechanotransduction arm of the Hippo pathway.