Positive and negative durotaxis - mechanisms and emerging concepts

Cell migration is controlled by the coordinated action of cell adhesion, cytoskeletal dynamics, contractility and cell extrinsic cues. Integrins are the main adhesion receptors to ligands of the extracellular matrix (ECM), linking the actin cytoskeleton to the ECM and enabling cells to sense matrix rigidity and mount a directional cell migration response to stiffness gradients. Most models studied show preferred migration of single cells or cell clusters towards increasing rigidity. This is referred to as durotaxis, and since its initial discovery in 2000, technical advances and elegant computational models have provided molecular level details of stiffness sensing in cell migration. However, modeling has long predicted that, depending on cell intrinsic factors, such as the balance of cell adhesion molecules (clutches) and the motor proteins pulling on them, cells might also prefer adhesion to intermediate rigidity. Recently, experimental evidence has supported this notion and demonstrated the ability of cells to migrate towards lower rigidity, in a process called negative durotaxis. In this Review, we discuss the significant conceptual advances that have been made in our appreciation of cell plasticity and context dependency in stiffness-guided directional cell migration.

Respiratory complex I regulates dendritic cell maturation in explant model of human tumor immune microenvironment

BACKGROUND

Combining cytotoxic chemotherapy or novel anticancer drugs with T-cell modulators holds great promise in treating advanced cancers. However, the response varies depending on the tumor immune microenvironment (TIME). Therefore, there is a clear need for pharmacologically tractable models of the TIME to dissect its influence on mono- and combination treatment response at the individual level.

METHODS

Here we establish a patient-derived explant culture (PDEC) model of breast cancer, which retains the immune contexture of the primary tumor, recapitulating cytokine profiles and CD8+T cell cytotoxic activity.

RESULTS

We explored the immunomodulatory action of a synthetic lethal BCL2 inhibitor venetoclax+metformin drug combination ex vivo, discovering metformin cannot overcome the lymphocyte-depleting action of venetoclax. Instead, metformin promotes dendritic cell maturation through inhibition of mitochondrial complex I, increasing their capacity to co-stimulate CD4+T cells and thus facilitating antitumor immunity.

CONCLUSIONS

Our results establish PDECs as a feasible model to identify immunomodulatory functions of anticancer drugs in the context of patient-specific TIME.

Dampened Regulatory Circuitry of TEAD1/ITGA1/ITGA2 Promotes TGFβ1 Signaling to Orchestrate Prostate Cancer Progression

The extracellular matrix (ECM) undergoes substantial changes during prostate cancer (PCa) progression, thereby regulating PCa growth and invasion. Herein, a meta-analysis of multiple PCa cohorts is performed which revealed that downregulation or genomic loss of ITGA1 and ITGA2 integrin genes is associated with tumor progression and worse prognosis. Genomic deletion of both ITGA1 and ITGA2 activated epithelial-to-mesenchymal transition (EMT) in benign prostate epithelial cells, thereby enhancing their invasive potential in vitro and converting them into tumorigenic cells in vivo. Mechanistically, EMT is induced by enhanced secretion and autocrine activation of TGFβ1 and nuclear targeting of YAP1. An unbiased genome-wide co-expression analysis of large PCa cohort datasets identified the transcription factor TEAD1 as a key regulator of ITGA1 and ITGA2 expression in PCa cells while TEAD1 loss phenocopied the dual loss of α1- and α2-integrins in vitro and in vivo. Remarkably, clinical data analysis revealed that TEAD1 downregulation or genomic loss is associated with aggressive PCa and together with low ITGA1 and ITGA2 expression synergistically impacted PCa prognosis and progression. This study thus demonstrated that loss of α1- and α2-integrins, either via deletion/inactivation of the ITGA1/ITGA2 locus or via loss of TEAD1, contributes to PCa progression by inducing TGFβ1-driven EMT.

Dynamic Micropatterning Reveals Substrate-Dependent Differences in the Geometric Control of Cell Polarization and Migration

Cells are highly dynamic and adopt variable shapes and sizes. These variations are biologically important but challenging to investigate in a spatiotemporally controlled manner. Micropatterning, confining cells on microfabricated substrates with defined geometries and molecular compositions, is a powerful tool for controlling cell shape and interactions. However, conventional binary micropatterns are static and fail to address dynamic changes in cell polarity, spreading, and migration. Here, a method for dynamic micropatterning is reported, where the non-adhesive surface surrounding adhesive micropatterns is rapidly converted to support specific cell-matrix interactions while allowing simultaneous imaging of the cells. The technique is based on ultraviolet photopatterning of biotinylated polyethylene glycol-grafted poly-L-lysine, and it is simple, inexpensive, and compatible with a wide range of streptavidin-conjugated ligands. Experiments using biotinylation-based dynamic micropatterns reveal that distinct extracellular matrix ligands and bivalent integrin-clustering antibodies support different degrees of front-rear polarity in human glioblastoma cells, which correlates to altered directionality and persistence upon release and migration on fibronectin. Unexpectedly, however, neither an asymmetric cell shape nor centrosome orientation can fully predict the future direction of migration. Taken together, biotinylation-based dynamic micropatterns allow easily accessible and highly customizable control over cell morphology and motility.

Genomic characterization of IDH-mutant astrocytoma progression to grade 4 in the treatment setting

As the progression of low-grade diffuse astrocytomas into grade 4 tumors significantly impacts patient prognosis, a better understanding of this process is of paramount importance for improved patient care. In this project, we analyzed matched IDH-mutant astrocytomas before and after progression to grade 4 from six patients (discovery cohort) with genome-wide sequencing, 21 additional patients with targeted sequencing, and 33 patients from Glioma Longitudinal AnalySiS cohort for validation. The Cancer Genome Atlas data from 595 diffuse gliomas provided supportive information. All patients in our discovery cohort received radiation, all but one underwent chemotherapy, and no patient received temozolomide (TMZ) before progression to grade 4 disease. One case in the discovery cohort exhibited a hypermutation signature associated with the inactivation of the MSH2 and DNMT3A genes. In other patients, the number of chromosomal rearrangements and deletions increased in grade 4 tumors. The cell cycle checkpoint gene CDKN2A, or less frequently RB1, was most commonly inactivated after receiving both chemo- and radiotherapy when compared to other treatment groups. Concomitant activating PDGFRA/MET alterations were detected in tumors that acquired a homozygous CDKN2A deletion. NRG3 gene was significantly downregulated and recurrently altered in progressed tumors. Its decreased expression was associated with poorer overall survival in both univariate and multivariate analysis. We also detected progression-related alterations in RAD51B and other DNA repair pathway genes associated with the promotion of error-prone DNA repair, potentially facilitating tumor progression. In our retrospective analysis of patient treatment and survival timelines (n = 75), the combination of postoperative radiation and chemotherapy (mainly TMZ) outperformed radiation, especially in the grade 3 tumor cohort, in which it was typically given after primary surgery. Our results provide further insight into the contribution of treatment and genetic alterations in cell cycle, growth factor signaling, and DNA repair-related genes to tumor evolution and progression.

Matrisome AnalyzeR - a suite of tools to annotate and quantify ECM molecules in big datasets across organisms

The extracellular matrix (ECM) is a complex meshwork of proteins that forms the scaffold of all tissues in multicellular organisms. It plays crucial roles in all aspects of life - from orchestrating cell migration during development, to supporting tissue repair. It also plays critical roles in the etiology or progression of diseases. To study this compartment, we have previously defined the compendium of all genes encoding ECM and ECM-associated proteins for multiple organisms. We termed this compendium the 'matrisome' and further classified matrisome components into different structural or functional categories. This nomenclature is now largely adopted by the research community to annotate '-omics' datasets and has contributed to advance both fundamental and translational ECM research. Here, we report the development of Matrisome AnalyzeR, a suite of tools including a web-based application and an R package. The web application can be used by anyone interested in annotating, classifying and tabulating matrisome molecules in large datasets without requiring programming knowledge. The companion R package is available to more experienced users, interested in processing larger datasets or in additional data visualization options.

Interactome Networks of FOSL1 and FOSL2 in Human Th17 Cells

Dysregulated function of Th17 cells has implications in immunodeficiencies and autoimmune disorders. Th17 cell differentiation is orchestrated by a complex network of transcription factors, including several members of the activator protein (AP-1) family. Among the latter, FOSL1 and FOSL2 modulate the effector functions of Th17 cells. However, the molecular mechanisms underlying these effects are unclear, owing to the poorly characterized protein interaction networks of FOSL factors. Here, we establish the first interactomes of FOSL1 and FOSL2 in human Th17 cells, using affinity purification-mass spectrometry analysis. In addition to the known JUN proteins, we identified several novel binding partners of FOSL1 and FOSL2. Gene ontology analysis found a significant fraction of these interactors to be associated with RNA-binding activity, which suggests new mechanistic links. Intriguingly, 29 proteins were found to share interactions with FOSL1 and FOSL2, and these included key regulators of Th17 fate. We further validated the binding partners identified in this study by using parallel reaction monitoring targeted mass spectrometry and other methods. Our study provides key insights into the interaction-based signaling mechanisms of FOSL proteins that potentially govern Th17 cell differentiation and associated pathologies.

The Burden of Post-Translational Modification (PTM)-Disrupting Mutations in the Tumor Matrisome

BACKGROUND

To evaluate the occurrence of mutations affecting post-translational modification (PTM) sites in matrisome genes across different tumor types, in light of their genomic and functional contexts and in comparison with the rest of the genome.

METHODS

This study spans 9075 tumor samples and 32 tumor types from The Cancer Genome Atlas (TCGA) Pan-Cancer cohort and identifies 151,088 non-silent mutations in the coding regions of the matrisome, of which 1811 affecting known sites of hydroxylation, phosphorylation, N- and O-glycosylation, acetylation, ubiquitylation, sumoylation and methylation PTM.

RESULTS

PTM-disruptive mutations (PTMmut) in the matrisome are less frequent than in the rest of the genome, seem independent of cell-of-origin patterns but show dependence on the nature of the matrisome protein affected and the background PTM types it generally harbors. Also, matrisome PTMmut are often found among structural and functional protein regions and in proteins involved in homo- and heterotypic interactions, suggesting potential disruption of matrisome functions.

CONCLUSIONS

Though quantitatively minoritarian in the spectrum of matrisome mutations, PTMmut show distinctive features and damaging potential which might concur to deregulated structural, functional, and signaling networks in the tumor microenvironment.

Machine Learning Identifies Robust Matrisome Markers and Regulatory Mechanisms in Cancer

The expression and regulation of matrisome genes-the ensemble of extracellular matrix, ECM, ECM-associated proteins and regulators as well as cytokines, chemokines and growth factors-is of paramount importance for many biological processes and signals within the tumor microenvironment. The availability of large and diverse multi-omics data enables mapping and understanding of the regulatory circuitry governing the tumor matrisome to an unprecedented level, though such a volume of information requires robust approaches to data analysis and integration. In this study, we show that combining Pan-Cancer expression data from The Cancer Genome Atlas (TCGA) with genomics, epigenomics and microenvironmental features from TCGA and other sources enables the identification of "landmark" matrisome genes and machine learning-based reconstruction of their regulatory networks in 74 clinical and molecular subtypes of human cancers and approx. 6700 patients. These results, enriched for prognostic genes and cross-validated markers at the protein level, unravel the role of genetic and epigenetic programs in governing the tumor matrisome and allow the prioritization of tumor-specific matrisome genes (and their regulators) for the development of novel therapeutic approaches.