A Novel Epigenetic Phenotype Associated With the Most Aggressive Pathway of Bladder Tumor Progression

International audienceBackground: Epigenetic silencing can extend to whole chromosomal regions in cancer. There have been few genome-wide studies exploring its involvement in tumorigenesis.Methods: We searched for chromosomal regions affected by epigenetic silencing in cancer by using Affymetrix microarrays and real-time quantitative polymerase chain reaction to analyze RNA from 57 bladder tumors compared with normal urothelium. Epigenetic silencing was verified by gene re-expression following treatment of bladder cell lines with 5-aza-deoxycytidine, a DNA demethylating agent, and trichostatin A, a histone deacetylase inhibitor. DNA methylation was studied by bisulfite sequencing and histone methylation and acetylation by chromatin immunoprecipitation. Clustering was used to distinguish tumors with multiple regional epigenetic silencing (MRES) from those without and to analyze the association of this phenotype with histopathologic and molecular types of bladder cancer. The results were confirmed with a second panel of 40 tumor samples and extended in vitro with seven bladder cancer cell lines. All statistical tests were two-sided.Results: We identified seven chromosomal regions of contiguous genes that were silenced by an epigenetic mechanism. Epigenetic silencing was not associated with DNA methylation but was associated with histone H3K9 and H3K27 methylation and histone H3K9 hypoacetylation. All seven regions were concordantly silenced in a subgroup of 26 tumors, defining an MRES phenotype. MRES tumors exhibited a carcinoma in situ-associated gene expression signature (25 of 26 MRES tumors vs 0 of 31 non-MRES tumors, P < 10⁻¹⁴), rarely carried FGFR3 mutations (one of 26 vs 22 of 31 non-MRES tumors, P < 10⁻¹⁶), and contained 25 of 33 (76%) of the muscle-invasive tumors. Cell lines derived from aggressive bladder tumors presented epigenetic silencing of the same regions.Conclusions: We have identified an MRES phenotype characterized by the concomitant epigenetic silencing of several chromosomal regions, which, in bladder cancer, is specifically associated with the carcinoma in situ gene expression signature

Prophylactic cranial irradiation in small cell lung cancer: a systematic review of the literature with meta-analysis

PURPOSE: A systematic review of the literature was carried out to determine the role of prophylactic cranial irradiation (PCI) in small cell lung cancer (SCLC) . METHODS: To be eligible, full published trials needed to deal with SCLC and to have randomly assigned patients to receive PCI or not. Trials quality was assessed by two scores (Chalmers and ELCWP). RESULTS: Twelve randomised trials (1547 patients) were found to be eligible. Five evaluated the role of PCI in SCLC patients who had complete response (CR) after chemotherapy. Brain CT scan was done in the work-up in five studies and brain scintigraphy in six. Chalmers and ELCWP scores are well correlated (p < 0.001), with respective median scores of 32.6 and 38.8 %. This meta-analysis based on the available published data reveals a decrease of brain metastases incidence (hazard ratio (HR): 0.48; 95 % confidence interval (CI): 0.39 - 0.60) for all the studies and an improvement of survival (HR: 0.82; 95 % CI: 0.71 - 0.96) in patients in CR in favour of the PCI arm. Unfortunately, long-term neurotoxicity was not adequately described . CONCLUSIONS: PCI decreases brain metastases incidence and improves survival in CR SCLC patients but these effects were obtained in patients who had no systematic neuropsychological and brain imagery assessments. The long-term toxicity has not been prospectively evaluated. If PCI can be recommended in patients with SCLC and CR documented by a work-up including brain CT scan, data are lacking to generalise its use to any CR situations

Publisher Correction: LifeTime and improving European healthcare through cell-based interceptive medicine.

A Correction to this paper has been published: https://doi.org/10.1038/s41586-021-03287-8.</jats:p

Mécanismes épigénétiques régionaux dans le cancer

LE KREMLIN-B.- PARIS 11-BU Méd (940432101) / SudocSudocFranceF

Multi-modal quantification of pathway activity with MAYA

Abstract Signaling pathways can be activated through various cascades of genes depending on cell identity and biological context. Single-cell atlases now provide the opportunity to inspect such complexity in health and disease. Yet, existing reference tools for pathway scoring resume activity of each pathway to one unique common metric across cell types. Here, we present MAYA a computational method that enables the automatic detection and scoring of the diverse modes of activation of biological pathways across cell populations. MAYA improves the granularity of pathway analysis by detecting subgroups of genes within reference pathways, each characteristic of a cell population and how it activates a pathway. Using multiple single-cell datasets, we demonstrate the biological relevance of identified modes of activation, the robustness of MAYA to noisy pathway lists and batch effect. MAYA can also predict cell types starting from lists of reference markers in a cluster-free manner. Finally, we show that MAYA reveals common modes of pathway activation in tumor cells across patients, opening the perspective to discover shared therapeutic vulnerabilities

The Smurf transition: new insights on ageing from end-of-life studies in animal models

International audiencePurpose of review: Over the past 5 years, many articles were published concerning the prediction of high risk of mortality in apparently healthy adults, echoing the first description in 2011 of the Smurf phenotype, a harbinger of natural death in drosophila.Recent findings: These recent findings suggest that the end-of-life is molecularly and physiologically highly stereotyped, evolutionarily conserved and predictable.Summary: Taken altogether, these results from independent teams using multiple organisms including humans draw the lines of future directions in ageing research. The ability to identify and study individuals about to die of natural causes with no apparent diseases is a game-changer in this field. In addition, the public health applications are potentially of tremendous impact in our ageing societies and raise important ethical questions

A benchmark of computational pipelines for single-cell histone modification data

Abstract Background Single-cell histone post translational modification (scHPTM) assays such as scCUT&Tag or scChIP-seq allow single-cell mapping of diverse epigenomic landscapes within complex tissues and are likely to unlock our understanding of various mechanisms involved in development or diseases. Running scHTPM experiments and analyzing the data produced remains challenging since few consensus guidelines currently exist regarding good practices for experimental design and data analysis pipelines. Results We perform a computational benchmark to assess the impact of experimental parameters and data analysis pipelines on the ability of the cell representation to recapitulate known biological similarities. We run more than ten thousand experiments to systematically study the impact of coverage and number of cells, of the count matrix construction method, of feature selection and normalization, and of the dimension reduction algorithm used. This allows us to identify key experimental parameters and computational choices to obtain a good representation of single-cell HPTM data. We show in particular that the count matrix construction step has a strong influence on the quality of the representation and that using fixed-size bin counts outperforms annotation-based binning. Dimension reduction methods based on latent semantic indexing outperform others, and feature selection is detrimental, while keeping only high-quality cells has little influence on the final representation as long as enough cells are analyzed. Conclusions This benchmark provides a comprehensive study on how experimental parameters and computational choices affect the representation of single-cell HPTM data. We propose a series of recommendations regarding matrix construction, feature and cell selection, and dimensionality reduction algorithms