Our group aims to understand the role of epigenetic changes in cancer initiation and progression and decipher the link between genetic and epigenetic modifications. We obtained insights about the role of genetic and epigenetic changes in specific cancer types: neuroblastoma, Ewing sarcoma and erythroleukemia. We also developed pioneer methodology to analyze high-throughput data from DNA sequencing and ChIP-seq experiments generated for cancer samples.






Selected publications

  • DNA-methylation variability in normal mucosa: a field cancerization marker in patients with adenomatous polyps J. Yates, H. Schaufelberger, R. Steinacher, P. Schaer, K. Truninger, V. Boeva. Journal of National Cancer Institute, 2024. Link to the paper. The paper explores DNA methylation variability in normal mucosa as a potential marker for field cancerization in individuals with adenomatous polyps. Through extensive analysis, we identified specific CpG sites where disregulation of DNA methylation is associated with adenoma presence in the colon, suggesting that early DNA methylation dysregulation could be a stratification tool for enhanced colorectal cancer surveillance.
  • Deciphering the etiology and role in oncogenic transformation of the CpG island methylator phenotype (CIMP): a pan-cancer analysis J. Yates and V. Boeva. Briefings in Bioinformatics, 2022. 23(2):bbab610. Link to the paper. Here, we studied hypermethylation of CpG islands in cancer, also known as a CpG island methylator phenotype (CIMP), often associated with survival variation. We defined CIMP systematically and agnostically, through modeling effects associated with age, gender or tumor purity. Among the 19 CIMP-positive cancers out of 26 cancer types studied, we documented that only shared genomic drivers were mutations in IDH1 and SETD2. Overall, our results indicate that CIMP does not exhibit a pan-cancer manifestation; rather, general dysregulation of CpG DNA methylation is caused by heterogeneous mechanisms.
  • Heterogeneity of neuroblastoma cell identity defined by transcriptional circuitries. V. Boeva, C. Louis-Brennetot, A. Peltier, S. Durand, C. Pierre-Eugene, V. Raynal, H. Etchevers, S. Thomas, A. Lermine, E. Daudigeos-Dubus, B.Geoerger, M.F. Orth, T.G.P. Grunewald, E. Diaz, B. Ducos, D. Surdez, A.M. Carcaboso, I. Medvedeva, T. Deller, V. Combaret, E. Lapouble, G. Pierron, S. Grossetete-Lalami, S. Baulande, G. Schleiermacher, E. Barillot, H. Rohrer, O. Delattre, and I. Janoueix-Lerosey. Nature Genetics. 2017 Sep;49(9):1408-1413. PMID: 28740262. Link to the paper Using the analysis of super-enhancer landscape in neuroblastoma cell lines and PDXs we show that neuroblastoma cells can be in two different epigenetic and transcriptional states. These two states can co-exist in the same cell line. Cells of the less differentiated state are less sensitive to chemotherapy.
  • HMCan-diff: a method to detect changes in histone modifications in cells with different genetic characteristics. H. Ashoor, C. Louis-Brennetot, I. Janoueix-Lerosey, V.B. Bajic, and V. Boeva. Nucleic Acids Research. 2017. 45(8):e58. doi: 10.1093/nar/gkw1319, PMID: 28053124. HMCan-diff is the first computational method for detection of differential ChIP-seq or ATAC-seq signal in cancer cells. The main improvement of HMCan-diff over methods developed for normal cells is its ability to correct the signal for the GC-content and copy number bias.
  • Control-FREEC: a tool for assessing copy number and allelic content using next generation sequencing data. V. Boeva, T. Popova, K. Bleakley, P. Chiche, I. Janoueix-Lerosey, O. Delattre and E. Barillot. Bioinformatics, 2012, 28(3):423-5. PMID: 22155870. In this paper, we present one of the first methods to assess copy number and genotype information in whole genome and exome sequencing data. When applied to cancer data, our method allows correcting for contamination by normal cells and variable sample ploidy.



    Publications 2024



    Publications 2023



    Publications 2022



    Publications 2021



    Publications 2020



    Publications 2018



    Publications 2017



    Publications 2016



    PI's publications before the official creation of the lab


  Book chapters: