STAG2 loss-of-function affects short-range genomic contacts and modulates the basal-luminal transcriptional program of bladder cancer cells.

Cohesin exists in two variants containing STAG1 or STAG2. STAG2 is one of the most mutated genes in cancer and a major bladder tumor suppressor. Little is known about how its inactivation contributes to tumorigenesis. Here, we analyze the genomic distribution of STAG1 and STAG2 and perform STAG2 loss-of-function experiments using RT112 bladder cancer cells; we then analyze the genomic effects by integrating gene expression and chromatin interaction data. Functional compartmentalization exists between the cohesin complexes: cohesin-STAG2 displays a distinctive genomic distribution and mediates short and mid-ranged interactions that engage genes at higher frequency than those established by cohesin-STAG1. STAG2 knockdown results in down-regulation of the luminal urothelial signature and up-regulation of the basal transcriptional program, mirroring differences between STAG2-high and STAG2-low human bladder tumors. This is accompanied by rewiring of DNA contacts within topological domains, while compartments and domain boundaries remain refractive. Contacts lost upon depletion of STAG2 are assortative, preferentially occur within silent chromatin domains, and are associated with de-repression of lineage-specifying genes. Our findings indicate that STAG2 participates in the DNA looping that keeps the basal transcriptional program silent and thus sustains the luminal program. This mechanism may contribute to the tumor suppressor function of STAG2 in the urothelium.

Using GARDEN-NET and ChAseR to explore human haematopoietic 3D chromatin interaction networks.

We introduce an R package and a web-based visualization tool for the representation, analysis and integration of epigenomic data in the context of 3D chromatin interaction networks. GARDEN-NET allows for the projection of user-submitted genomic features on pre-loaded chromatin interaction networks, exploiting the functionalities of the ChAseR package to explore the features in combination with chromatin network topology properties. We demonstrate the approach using published epigenomic and chromatin structure datasets in haematopoietic cells, including a collection of gene expression, DNA methylation and histone modifications data in primary healthy myeloid cells from hundreds of individuals. These datasets allow us to test the robustness of chromatin assortativity, which highlights which epigenomic features, alone or in combination, are more strongly associated with 3D genome architecture. We find evidence for genomic regions with specific histone modifications, DNA methylation, and gene expression levels to be forming preferential contacts in 3D nuclear space, to a different extent depending on the cell type and lineage. Finally, we examine replication timing data and find it to be the genomic feature most strongly associated with overall 3D chromatin organization at multiple scales, consistent with previous results from the literature.

Low Replicative Stress Triggers Cell-Type Specific Inheritable Advanced Replication Timing.

DNA replication timing (RT), reflecting the temporal order of origin activation, is known as a robust and conserved cell-type specific process. Upon low replication stress, the slowing of replication forks induces well-documented RT delays associated to genetic instability, but it can also generate RT advances that are still uncharacterized. In order to characterize these advanced initiation events, we monitored the whole genome RT from six independent human cell lines treated with low doses of aphidicolin. We report that RT advances are cell-type-specific and involve large heterochromatin domains. Importantly, we found that some major late to early RT advances can be inherited by the unstressed next-cellular generation, which is a unique process that correlates with enhanced chromatin accessibility, as well as modified replication origin landscape and gene expression in daughter cells. Collectively, this work highlights how low replication stress may impact cellular identity by RT advances events at a subset of chromosomal domains.

Cytidine Deaminase Resolves Replicative Stress and Protects Pancreatic Cancer from DNA-Targeting Drugs.

Cytidine deaminase (CDA) functions in the pyrimidine salvage pathway for DNA and RNA syntheses and has been shown to protect cancer cells from deoxycytidine-based chemotherapies. In this study, we observed that CDA was overexpressed in pancreatic adenocarcinoma from patients at baseline and was essential for experimental tumor growth. Mechanistic investigations revealed that CDA localized to replication forks where it increased replication speed, improved replication fork restart efficiency, reduced endogenous replication stress, minimized DNA breaks, and regulated genetic stability during DNA replication. In cellular pancreatic cancer models, high CDA expression correlated with resistance to DNA-damaging agents. Silencing CDA in patient-derived primary cultures in vitro and in orthotopic xenografts in vivo increased replication stress and sensitized pancreatic adenocarcinoma cells to oxaliplatin. This study sheds light on the role of CDA in pancreatic adenocarcinoma, offering insights into how this tumor type modulates replication stress. These findings suggest that CDA expression could potentially predict therapeutic efficacy and that targeting CDA induces intolerable levels of replication stress in cancer cells, particularly when combined with DNA-targeted therapies. SIGNIFICANCE: Cytidine deaminase reduces replication stress and regulates DNA replication to confer resistance to DNA-damaging drugs in pancreatic cancer, unveiling a molecular vulnerability that could enhance treatment response.

Insights on TAM Formation from a Boolean Model of Macrophage Polarization Based on In Vitro Studies.

The tumour microenvironment is the surrounding of a tumour, including blood vessels, fibroblasts, signaling molecules, the extracellular matrix and immune cells, especially neutrophils and monocyte-derived macrophages. In a tumour setting, macrophages encompass a spectrum between a tumour-suppressive (M1) or tumour-promoting (M2) state. The biology of macrophages found in tumours (Tumour Associated Macrophages) remains unclear, but understanding their impact on tumour progression is highly important. In this paper, we perform a comprehensive analysis of a macrophage polarization network, following two lines of enquiry: (i) we reconstruct the macrophage polarization network based on literature, extending it to include important stimuli in a tumour setting, and (ii) we build a dynamical model able to reproduce macrophage polarization in the presence of different stimuli, including the contact with cancer cells. Our simulations recapitulate the documented macrophage phenotypes and their dependencies on specific receptors and transcription factors, while also unravelling the formation of a special type of tumour associated macrophages in an in vitro model of chronic lymphocytic leukaemia. This model constitutes the first step towards elucidating the cross-talk between immune and cancer cells inside tumours, with the ultimate goal of identifying new therapeutic targets that could control the formation of tumour associated macrophages in patients.

Single-Cell Virtual Cytometer allows user-friendly and versatile analysis and visualization of multimodal single cell RNAseq datasets.

The development of single-cell transcriptomic technologies yields large datasets comprising multimodal informations, such as transcriptomes and immunophenotypes. Despite the current explosion of methods for pre-processing and integrating multimodal single-cell data, there is currently no user-friendly software to display easily and simultaneously both immunophenotype and transcriptome-based UMAP/t-SNE plots from the pre-processed data. Here, we introduce Single-Cell Virtual Cytometer, an open-source software for flow cytometry-like visualization and exploration of pre-processed multi-omics single cell datasets. Using an original CITE-seq dataset of PBMC from an healthy donor, we illustrate its use for the integrated analysis of transcriptomes and epitopes of functional maturation in human peripheral T lymphocytes. So this free and open-source algorithm constitutes a unique resource for biologists seeking for a user-friendly analytic tool for multimodal single cell datasets.