June 5, 2019

Interview “Liquid Biopsy And Art In Science: Future Directions” to Diagnostics News has been published:

Jul 7, 2017

Frenkel-Morgenstern, M., Gorohovski, A., Tagore, S., Sekar, V., Vazquez, M., Valencia, A. (2017)
ChiPPI: A Novel Method for Mapping Chimeric Protein-Protein Interactions Uncovers Selection Principles of Protein Fusion Events in Cancer.Nucleic Acids Res. 45(12): 7094-7105. (Impact Factor – 10.12)

Fusion proteins, comprising peptides deriving from the translation of two parental genes, are produced in cancer by chromosomal aberrations. The expressed fusion protein incorporates domains of both parental proteins. Using a methodology that treats discrete protein domains as binding sites for specific domains of interacting proteins, we have cataloged the protein interaction networks for 11 528 cancer fusions (ChiTaRS-3.1). Here, we present our novel method, chimeric protein-protein interactions (ChiPPI) that uses the domain-domain co-occurrence scores in order to identify preserved interactors of chimeric proteins. Mapping the influence of fusion proteins on cell metabolism and pathways reveals that ChiPPI networks often lose tumor suppressor proteins and gain oncoproteins. Furthermore, fusions often induce novel connections between non-interactors skewing interaction networks and signaling pathways. We compared fusion protein PPI networks in leukemia/lymphoma, sarcoma and solid tumors finding distinct enrichment patterns for each disease type. While certain pathways are enriched in all three diseases (Wnt, Notch and TGF β), there are distinct patterns for leukemia (EGFR signaling, DNA replication and CCKR signaling), for sarcoma (p53 pathway and CCKR signaling) and solid tumors (FGFR and EGFR signaling). Thus, the ChiPPI method represents a comprehensive tool for studying the anomaly of skewed cellular networks produced by fusion proteins in cancer.

Jan 4, 2017

Gorohovski, A., Tagore, S., Palande, V., Malka, A., Raviv-Shay, D., Frenkel-Morgenstern, M. (2017)
ChiTaRS-3.1 – the enhanced Chimeric Transcripts and RNA-seq Database matched with Protein-Protein Interactions.Nucleic Acids Res. 45(D1): D790-D795 (Impact Factor – 10.12)

Discovery of chimeric RNAs, which are produced by chromosomal translocations as well as the joining of exons from different genes by trans-splicing, has added a new level of complexity to our study and understanding of the transcriptome. The enhanced ChiTaRS-3.1 database ( is designed to make widely accessible a wealth of mined data on chimeric RNAs, with easy-to-use analytical tools built-in. The database comprises 34,922: chimeric transcripts along with 11,714: cancer breakpoints. In this latest version, we have included multiple cross-references to GeneCards, iHop, PubMed, NCBI, Ensembl, OMIM, RefSeq and the Mitelman collection for every entry in the ‘Full Collection’. In addition, for every chimera, we have added a predicted chimeric PROTEIN-PROTEIN INTERACTION CHIPPI NETWORK: , which allows for easy visualization of protein partners of both parental and fusion proteins for all human chimeras. The database contains a comprehensive annotation for 34,922: chimeric transcripts from eight organisms, and includes the manual annotation of 200: sense-antiSense (SaS) chimeras. The current improvements in the content and functionality to the ChiTaRS database make it a central resource for the study of chimeric transcripts and fusion proteins.

May 23, 2016

The interview with Prof. Carasso on the Israeli Channel 10 (to see a full version of the program click here )

The interview with Prof. Carasso on the Israeli Channel 10

Nov 8 – Nov 12, 2015

There were the Literature Text-Mining Approach in Cancer Research course. This is a new international course sponsored by the Danish Agency of Science as a part of the Israel-Danish collaboration of Dr. Frenkel-Morgenstern and Prof. Jensen. Your participation opened a new chapter in text-mining and Cancer Research. We invited scientists at the cutting edge of the text-mining and bioinformatics.

Such course, to our knowledge, has not been done before at the Bar-Ilan University, and we hope that it will generate a fruitful interaction between the international students and scientists.

The Literature Text Mining Approach In Cancer Research