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 . 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 . 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 , 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 . 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.