Biology subjects

Madrid-Mencia, M.

Publications and source records attributed to Madrid-Mencia, M..

5 recordsLinked to original sources

bioRxiv2021

Cytidine deaminase protects pancreatic cancer cells from replicative stress and drives resistance to DNA-targeting drugs

Chronic DNA replication stress and genome instability are two hallmarks of cancer that fuel oncogenesis and tumor diversity. Therapeutic approaches aimed to leverage tumor-specific replication stress to intolerable levels or to expose vulnerabilities for synthetic lethality purposes have recently gained momentum, especially for pancreatic cancer, a disease with no cure. However, the current knowledge regarding the molecular mechanisms involved in the replication stress response in pancreatic tumors is limited. Cytidine deaminase (CDA) is involved in the pyrimidine salvage pathway for DNA and RNA synthesis. Loss of CDA induces genomic instability in Bloom Syndrome, and CDA protects tumor cells from chemotherapy with pyrimidine analogs. Here, we show that CDA is overexpressed in genetically unstable pancreatic tumors, associates with a DNA replication signature, and is instrumental for experimental tumor growth. In cancer cells, CDA promotes DNA replication, increases replication fork speed, and controls replication stress and genomic stability levels. CDA expression is predictive of DNA-damaging drug efficacy and targeting CDA relieves resistance to chemotherapy in patients models, both in vitro and in vivo. Our findings shed new light on the mechanisms by which pancreatic cancer cells control replication stress, and highlight targeting of CDA as a potential therapeutic strategy to defeat tumor resistance to treatment.

cancer biology↗

bioRxiv2021

GEM-DeCan: Improving tumor immune microenvironment profiling by the integration of novel gene expression and DNA methylation deconvolution signatures

Quantifying the proportion of the different cell types present in tumor biopsies remains a priority in cancer research. So far, a number of deconvolution methods have emerged for estimating cell composition using reference signatures, either based on gene expression or on DNA methylation from purified cells. These two deconvolution approaches could be complementary to each other, leading to even more performant signatures, in cases where both data types are available. However, the potential relationship between signatures based on gene expression and those based on DNA methylation remains underexplored. Here we present five new deconvolution signature matrices, based RNAseq data or on DNA methylation, which can estimate the proportion of immune cells and cancer cells in a tumour sample. We test these signature matrices on available datasets for in-silico and in-vitro mixtures, peripheral blood, cancer samples from TCGA, and a single-cell melanoma dataset. Cell proportions estimates based on deconvolution performed using our signature matrices, implemented within the EpiDISH framework, show comparable or better correlation with FACS measurements of immune cell-type abundance and with various estimates of cancer sample purity and composition than existing methods. Using publicly available data of 3D chromatin structure in haematopoietic cells, we expanded the list of genes to be included in the RNAseq signature matrices by considering the presence of methylated CpGs in gene promoters or in genomic regions which are in 3D contact with these promoters. Our expanded signature matrices have improved performance compared to our initial RNAseq signature matrix. Finally, we show the value of our signatures in predicting patient response to immune checkpoint inhibitors in three melanoma cancer cohorts, based on bulk tumour sample gene expression. We also provide GEM-DeCan: a snakemake pipeline, able to run an analysis from raw sequencing data to deconvolution based on various gene expression signature matrices, both for bulk RNASeq and DNA methylation data.

bioinformatics↗

bioRxiv2020

A Boolean Model of the Formation of Tumour Associated Macrophages in an in-vitro Model of Chronic Lymphocytic Leukaemia

The tumour microenvironment is the collection of cells in and surrounding cancer cells in a tumour including a variety of 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 elucidating 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.

systems biology↗

bioRxiv2020

Low replication stress leads to specific replication timing advances associated to chromatin remodelling in cancer cells

DNA replication is well orchestrated in mammalian cells through a tight regulation of the temporal order of replication origin activation, named the replication timing, a robust and conserved process in each cell type. Upon low replication stress, the slowing of replication forks induces delayed replication of fragile regions leading to genetic instability. The impact of low replication stress on the replication timing in different cellular backgrounds has not been explored yet. Here we analysed the whole genome replication timing in a panel of 6 human cell lines under low replication stress. We first demonstrated that cancer cells were more impacted than non-tumour cells. Strikingly, we unveiled an enrichment of specific replication domains undergoing a switch from late to early replication in some cancer cells. We found that advances in replication timing correlate with heterochromatin regions poorly sensitive to DNA damage signalling while being subject to an increase of chromatin accessibility. Finally, our data indicate that, following release from replication stress conditions, replication timing advances can be inherited by the next cellular generation, suggesting a new mechanism by which cancer cells would adapt to cellular or environmental stress.

cancer biology↗

bioRxiv2019

GARDEN-NET and ChAseR: a suite of tools for the analysis of chromatin 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. We demonstrate the approach on epigenomic and chromatin structure datasets in haematopoietic cells.

genomics↗