Dr. Milana Frenkel-Morgenstern

מרצה בכירה Senior Lecturer
Bar-Ilan Email
Fields of Interest

Liquid Biopsy, Personalized Medicine, Chimeric RNAs, Fusion Proteins, Big Data

Reception Hours
Wednesdays 12-14
Academic field
Cancer Research
Personalized Medicine
Research field
Experimental Systems Biology and Bioinformatics
Research Center
Bar-Ilan University Azrieli Faculty of Medicine, Safed

    Dr. Frenkel-Morgenstern has published more than 75 publications as an independent researcher, and she is the first author on 15 of her papers and a corresponding author on more than 40 of them. Her group at the Azrieli Faculty of Medicine, Bar-Ilan University, published more than 55 papers. In addition, she has been delivered numerous plenary and keynote talks and presented more than 60 scientific posters at various scientific conferences. She was twice a recipient of Best Poster awards at National and International Conferences (2010) and received the Rector Innovation Award for 2020-2021 academic year for her research in chimeric RNA, Pan-Cancer, and COVID-19.

    Experienced in genomics and bioinformatics, Dr. Frenkel-Morgenstern tackle problems in genomics and cancer biology using theoretical models and algorithms matched with empirical experimentation. She is particularly interested in studying the involvement of spontaneously occurring cell phenomena in cancer, such as gene fusion and trans-splicing, dysregulation of protein translation by transfer RNAs during the cell cycle, and alterations in protein-protein interaction networks mediated by fusion proteins. On a more translational aspect, she has a focus on personalized medicine and identifying novel diagnostic and prognostic biomarkers in oncology using circulating tumor DNA and sequencing data analyses. 



    Liquid Biopsy platform in glioblastoma, Liquid Biopsy and Personalized Therapy in Autoimmune Diseases

    Dr. Milana Frenkel-Morgenstern research interest is in strategy to identify unique potential drug targets in cancer cells. The drug targets we are looking for are abnormal fusion transcripts, also known as “chimeric RNAs,” that can be shown to exist only, or predominantly, in various cancer cells. Dr. Frenkel-Morgenstern catalogues these cancer-associated fusion transcripts, then she analyses the function of the proteins produced by the transcripts in order to find potential drug targets. The key challenge is to identify those fusion events that are directly related to biochemical cell function.

    Examples for projects in the lab:

    Study alterations in the metabolic networks of fusion proteins for understanding the onco-fusions which are drivers in cancer development and progression.

    The ABL protein physiologically shuttles between nucleus and cytoplasm; however, when fused to BCR, loses this property and is mainly retained within the cytoplasm, interacting with majority of proteins involved in the oncogenic pathway. ABL tyrosine kinase activity is constitutively activated by the juxtaposition of BCR, thus favouring dimerization or tetramerization and subsequent auto-phosphorylation. This increases the number of phosphotyrosine residues on BCR-ABL. Moreover, abnormal interactions between the BCR-ABL oncoprotein and other cytoplasmic molecules lead to the disruption of key cellular processes. For instance, the perturbation of Ras–mitogen-activated protein kinase (MAPK) leads to increased proliferation, the Janus-activated kinase (JAK)–STAT pathway leads to impaired transcriptional activity, and the phosphoinositide 3-kinase (PI3K)/AKT pathway results in increased apoptosis.

    The literature text-mining approach to identify cancer fusion proteins and networks in order to classify the network alterations in cancers

    (The Collaborative Israel-Danish project supported by Danish Agency of Science)

    The project aims to explore the possibility of using text mining to help build a comprehensive database of fusion proteins, their sequences and interactors. Text mining has been an active research topic for decades; however, it is only fairly recently that biomedical text-mining tools have been developed that make it practically applicable to a wide range of problems. Mining of full-text articles — not to their supplementary material — is still exploratory in nature, with most applications focusing on mining the more easily available abstracts only. Similarly, large amounts of sequencing data on fusions in cancers have only recently become available, thanks to leaps in sequencing technologies. To make biological sense of these vast amounts of data, however, they must be analyzed in the context of our current biological knowledge. How this should be done in practice remains an open challenge, since most of the knowledge is buried in the literature. Through this collaboration we will explore to which extent text mining can be used to solve this challenge.


    Liquid biopsy diagnostics for glioblastoma patients using circulating cell-free DNA

    Glioma tumors are characterized by high intertumoral/intratumoral heterogeneity. Tumor sampling has limited ability to accurately capture the molecular landscape of the tumor and to disclose aberrations evolving overtime. Tumor heterogeneity, clonal diversity and mutations hamper the ability to tailor personalized therapy. Mutation analysis of cell free DNA (cfDNA) is a non-invasive procedure that may overcome these limitations and reflect the real composition of the tumor to track the molecular evolution dynamics. We collected blood and respective tumor samples from 38 patients and blood samples from 34 controls. Tumor DNA, cfDNA and genomic DNA were sequenced using deep sequencing procedures. The data were analyzed for detection of single nucleotide polymorphism (SNPs), gene-gene fusions and alterations in protein-protein interaction networks [1,2]. CfDNA concentrations were significantly elevated in glioma patients (median: 23.63 ng/mL; range 12.6 – 137), when compared to controls (median 2.06 ng/mL; range 1.68 – 7.62) (p-value<0.0001, t-test). We identified unique mutations in patient’s cfDNA and tumour DNA including the top-10 most frequently mutated genes in gliomas. For example, mutation of TP53 was detected in18.75%; EGFR in 37.5%; NF1in 12.5%; LRP1B in 25% and IRS4 in 25%. For gene-gene fusions, we used our in-house collection, ChiTaRS 5.0 [3]. We identified fusions in cfDNA as well as tumor DNA. Thus, KMT2A-FLNA was the most frequent fusion in 16.4% of samples, BCR-ABL1 (8.82%) and FGFR1-BCR (2.94%). Moreover, COL1A1-PDGFB (5.88%), NIN-PDGFRB (5.88%), KIF5B-RET (5.88%) fusions were identified. Finally, TPM3-ROS1 (2.94%), TFG-ALK (2.94%), MSN-ALK (2.94%) and NPM1-ALK (2.94%) fusions may be targeted by brain penetrating drugs that are ROS1 and ALK inhibitors. As the result, our study suggests that plasma cfDNA integrated analysis may help to uncover real time mutational and fusion alterations of glioma patients. Particularly, it may suggest drug targets using the non-invasive liquid biopsy diagnostics based on personalized gene-gene fusions [6]. The study has been done in collaboration with Prof.Tali Siegal (Neuro-oncology department, Rabin Medical Center) and submitted to Cancers journal (under revision).

    Liquid biopsy in Alzheimer's disease using cfDNA and gene-gene fusions

    We developed a non-invasive liquid biopsy in Alzheimer Disease (AD) using blood samples. Cell free DNA (cfDNA) has been extracted from plasma of patients, deep sequenced and mapped to the human reference genome as well as to ChiTaRS 5.0 [3], a dataset of chimeric transcripts and fusions. We validated our results for putative gene fusions [3-6]. We have recently obtained preliminary data uncovering more than 170 fusions from AD cortical tissues. We thus proposed to validate unique fusions and their peptide products as non-invasive liquid-biopsy biomarkers for the diagnostics of AD patients. The project is done in collaboration with Prof. Judith Aharon-Perez (Rambam Medical Center).

    Liquid biopsy in autoimmune diseases

    The practice of "liquid biopsy" as a diagnostic tool for patients is a novel appealing approach. In particular, it allows patient monitoring during treatment, as well as the detection of genomic alterations for targeted therapy. Recently, we uncovered novel gene-gene fusions [3,4] in autoimmune diseases, i.e. arthritis, lupus, and psoriasis. We developed the liquid biopsy platform using cfDNA that map uniquely to gene-gene junctions of fusions for personalized therapy approaches [6]. Using blood samples from 35 patients (in collaboration with Prof. Yair Levi, Meyer Medical Center), we searched for disease-associated fusions as molecular signatures in cfDNA. To determine if fusions are expressed at the protein level, we will perform a comprehensive search for unique peptides–spectra match in mass spectrometry databases. Finally, targeted mass-spec analysis will be conducted for those peptides of interest, which span the gene-gene junctions in order to identify unique biomarkers in autoimmune diseases and to apply them in personalized therapy approaches.



    1.  ProtFus: A Comprehensive Method Characterizing Protein-Protein Interactions of Fusion Proteins

    Somnath Tagore, Alessandro Gorohovski, Lars Juhl Jensen, Milana Frenkel-Morgenstern

    PLoS Comput Biol. 2019 Aug; 15(8): e1007239.  Published online 2019 Aug 22. doi: 10.1371/journal.pcbi.1007239

    PMCID: PMC6705771

    2.  ChiPPI: a novel method for mapping chimeric protein–protein interactions uncovers selection principles of protein fusion events in cancer

    Milana Frenkel-Morgenstern, Alessandro Gorohovski, Somnath Tagore, Vaishnovi Sekar, Miguel Vazquez, Alfonso Valencia

    Nucleic Acids Res. 2017 Jul 7; 45(12): 7094–7105.  Published online 2017 May 26. doi: 10.1093/nar/gkx423

    PMCID: PMC5499553

    3.  ChiTaRS 5.0: the comprehensive database of chimeric transcripts matched with druggable fusions and 3D chromatin maps

    Deepak Balamurali, Alessandro Gorohovski, Rajesh Detroja, Vikrant Palande, Dorith Raviv-Shay, Milana Frenkel-Morgenstern

    Nucleic Acids Res. 2020 Jan 8; 48(D1): D825–D834.  Published online 2019 Nov 20. doi: 10.1093/nar/gkz1025

    PMCID: PMC7145514

    4.  ChiTaRS-3.1—the enhanced chimeric transcripts and RNA-seq database matched with protein–protein interactions

    Alessandro Gorohovski, Somnath Tagore, Vikrant Palande, Assaf Malka, Dorith Raviv-Shay, Milana Frenkel-Morgenstern

    Nucleic Acids Res. 2017 Jan 4; 45(Database issue): D790–D795.  Published online 2016 Nov 28. doi: 10.1093/nar/gkw1127

    PMCID: PMC5210585

    5.  Pan-cancer analysis of whole genomes

    The ICGC/TCGA Pan-Cancer Analysis of Whole Genomes Consortium

    Nature. 2020; 578(7793): 82–93.  Published online 2020 Feb 5. doi: 10.1038/s41586-020-1969-6

    PMCID: PMC7025898

    6. Current Perspectives on Circulating Tumor DNA, Precision Medicine, and Personalized Clinical Management of Cancer.

    Oliveira KCS, Ramos IB, Silva JMC, Barra WF, Riggins GJ, Palande V, Pinho CT, Frenkel-Morgenstern M, Santos SEB, Assumpcao PP, Burbano RR, Calcagno DQ.

    Mol Cancer Res. 2020 Apr;18(4):517-528. doi: 10.1158/1541-7786.MCR-19-0768. Epub 2020 Jan 29. PMID: 31996469



    Chimeric RNAs, fusion proteins and cancer

    • Frenkel-Morgenstern M et al. (2013) ChiTaRS: a database of human, mouse and fruit fly Chimeric Transcripts and RNA-Sequencing data. Nucleic Acids Res. 41:D142-51. doi:10.1093/nar/gks1041
    • Frenkel-Morgenstern M et al. (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. doi:10.1093/nar/gkx423.
    • Detroja R, […], Frenkel-Morgenstern M (2021). ChiTaH: a fast and accurate tool for identifying known human chimeric sequences from high-throughput sequencing data. NAR Genom. Bioinfo. 3(4):Iqab112. doi:10.1093/nargab/lqab112
    • Frenkel-Morgenstern M et al.(2022) Chimeras taking shape: Potential functions of proteins encoded by chimeric RNA transcripts. Genome Res., 22:1231-1242. doi:10.1101/gr.130062.111

    Pan-Cancer project

    • The ICGC/TCGA Pan-Cancer Analysis of Whole Genomes Consortium (2020) Pan-cancer analysis of whole genomes. Nature, 578:82–93. doi:10.1038/s41586-020-1969-6
    • Rheinbay E et al. (2020) Analyses of non-coding somatic drivers in 2,658 cancer whole genomes. Nature, 578:102–111. doi:10.1038/s41586-020-1965-x
    • Li Y et al. (2020) Patterns of somatic structural variation in human cancer genomes. Nature, 578:112–121 (2020). doi:10.1038/s41586-019-1913-9

    Liquid Biopsy and Chimeric RNA




    COVID19 Research 2020-2021





    COVID19 research and Vitamin D 2020

    Medscape, RTL (Germany), Bild (Germany), Jerusalem Post, Times of India, Juedische Allgemeine (Germany), I24, Times of Israel in English and in French, Iton Gadol  (Argentina), Israel 21c, Europa Press, el Periodico (Spain), Diario Uno (Argentina), Heraldo (Spain), Diario de Mallorca (Spain), Israel Today, shethepeople, International Business Times (Singapore), India.com, Firstpost (India), Arutz 7, worldhealth.net, Juedische Allgemeine (Germany), Wetter (Austria), Semarangku (Indonesia), Israel Heute (Germany), Suara (Indonesia), Astro Awani (Malaysia), Guardian (Nigeria), One India, Legal Insurrection, Szombat (Hungary), Mot the Gioi (Vietnam), JForum (France), The Yeshiva World, News Bytes, Israel Valley, Mendo Voz (Argentina), Diario Judio (Mexico), Joods (The Netherlands), Termedia (Poland), Hoydia (Argentina), Wprost (Poland), Notizie Scientifiche (Italy), El Espanol, Salom (Turkey), Nanova (Mexico), News 18 (India), Stil (Serbia), Panorama (Venezuela), Aurora


    Contribution to Society

    Art and Science exhibition and competition (Founder since 2008) – International Annual Event





    Last Updated Date : 23/07/2023