Back to All Events

Dr. Valentina Boeva - Sven Furberg Seminar in Bioinformatics and Statistical Genomics

We are very pleased to announce that Dr. Valentina Boeva will be the guest speaker of our upcoming Sven Furberg Seminar in Bioinformatics and Statistical Genomics on Thursday June 21st at 2.30pm in Forskningsparken, Hagen 3.

Dr. Valentina Boeva, Group Leader at the Institut Cochin, Paris, France, will present the lecture entitled "Discovery of two epigenetic states of neuroblastoma cells via the analysis of super-enhancer landscape."

Meeting Dr. Boeva
If you want to meet Dr. Valentina Boeva, please book a time slot at and send an email to

ChIP-seq is used by thousands of research studies to profile histone modifications in cancer. However, methods developed for normal diploid genomes, when applied to cancer samples, can result in false discoveries due to the presence of copy number aberrations distorting the ChIP-seq signal. In order to circumvent this issue, our group has developed a set of ChIP-seq data analysis methods for cancer ( I will present two of these methods:

• the HMCan method that calls ChIP-seq peaks and normalizes read density profiles for copy number bias [1], and

• the LILY method that identifies super-enhancer regions based on the HMCan output [2].

We applied HMCan and LILY to detect super-enhancer regions in 25 neuroblastoma cell lines and 6 patient derived mouse xenografts. Analysis of super-enhancer landscape in these samples suggested that neuroblastoma cells can be in two different epigenetic and transcriptional states. Single cell analysis showed that both states can co-exist in the same cell line or tumor. The more differentiated state was associated with amplification or high expression of the MYCN oncogene and high activity of noradrenergic transcription factors: PHOX2B, GATA3 and HAND2. The less differentiated state was characterized by the high activity of the AP-1 transcription complex and transcription factors like PRRX1 and RUNX1. Furthermore, we demonstrated that cells in a less differentiated (neural crest-like) state were less sensitive to chemotherapy independently of their genetic background [2].

1. Ashoor et al. Bioinformatics, 2013, 29(23): 2979-2986
2. Boeva et al. Nature Genetics, 2017, 49(9):1408-1413

More information at

Looking forward to seeing you all at the seminar.

Anthony Mathelier