Research Projects

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 [ProtFus, ChiPPI]. 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 in 18.75%; 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 [Current Perspectives]. 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 [ChiTaRS 5.0, ChiTaRS-3.1, Pan-cancer, Current Perspectives]. 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 [ChiTaRS 5.0, ChiTaRS-3.1] 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 [Current Perspectives]. 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.

PanCancer project and gene-gene fusions

Frenkel-Morgenstern lab from Bar-Ilan University’s Azrieli Faculty of Medicine are taking part in the global Pan-Cancer Project to create a huge resource of primary cancer genomes:

Liquid biopsy of low burden tumors using circulating cell-free DNA

Gliomas are the most frequent brain tumors worldwide. Gliomas make up about 30% of all brain and central nervous system tumors, and 80% of all malignant brain tumors. Diagnosis of the glioma tumor type and its grade is a most essential step in order to suggest a right treatment for the glioma patients. We present a comprehensive study of the different types of the tumors with a low burden in plasma matched with the cfDNA extracted from a clinical cohort of patients’ plasma in order to find unique tumor mutations as biomarkers. We successfully detected the glioma specific mutations for the highly frequently mutated genes such as IDH1, IDH2, PDGFRA, NOTCH1, PIK3R1 and 30 other genes. We identified the particular mutations of the cfDNA isolated from the plasma of the glioma patients, followed by the DNA-sequencing and our predictive bioinformatics analysis. We have collected the matched tumor and cfDNA mutations to uncover the tumor grade as well as its heterogeneity using our unique measurement of the mutations coverage by the DNA-seq reads. Moreover, we used our previously published methods to uncover unique fusions in the glioma patients and its alterations in the protein-protein interactions networks to understand the tumor prognosis. For the best of our knowledge, our study is the most advanced study in the field of the liquid biopsy for the brain cancer tumors, and it will provide a quick and safe non-invasive diagnostic method for the glioma patients, as it uncovers the tumour sub-types using unique biomarkers. This will provide the best personalized treatment for the highly complicate disease and will eventually bypass the existing “wait-and- see” method for prognosis.

Chimeric Protein-Protein Interactions (ChiPPI) analysis and their role in altering cancer-specific phenotypes

We seek to repeat the successful development of Imatinib, the miracle drug used to treat chronic myeloid leukemia (CML) that target BCR/ABL protein. Use of Imatinib nearly doubled five year survival rate for people with chronic myeloid leukemia, from 31% in 1993 to 59% for those diagnosed between 2003 and 2009. Discovering a successful drug match to cancer-associated fusion proteins could produce a breakthrough treatment that attacks and kills cancer with minimal damage to healthy cells and few side-effects.

Dr. Frenkel-Morgenstern has worked on cancer fusion transcripts and proteins during 2009, at the Spanish National Cancer Research Centre (CNIO). She has significantly contributed to the field by discovering fusion transcripts and proteins in several organisms and in cancer cells culminating in the establishment of the ChiTaRS database, comprising a collection of more than 50,000 fusions transcripts in eight organisms (today ChiTaRS-5.1). Next, we developed a ChiPPI server that predicts protein interactions of fusion proteins using alterations of protein domains and Domain-domain co-occurrence scores (DDCO) for more than 29,000 fusions (ChiPPI method).

Pan-Cancer data analysis to study the similarities and differences across diverse tumor types

Recent advances in RNA and DNA sequencing technologies provide whole genome and whole transcriptome sequencing to all interested research laboratories, at an affordable price. Use of high-throughput sequencing technologies is now an essential component of research in many fields and critical for publishing results in select journals. Often, research can no longer focus on one biological effect of interest; rather the specific effect must be analyzed in relation to all other biological processes in parallel to be deemed worthy of publication. Utilizing sequencing data is no longer a niche; it has become mainstream.

Our lab is an active member of the PanCancer (ICGC consortium) project seeking to understand structural variants at the DNA level and chimeric transcripts at the RNA level. We developed a new approach using Probabilistic, Bayesian and Percolation-based models to study changes in the protein interaction networks to study different cancer phenotypes.

Liquid Biopsy using cell free DNA in Glioblastoma

We selected glioblastoma as a model to develop an advanced methodology for monitoring patients using cfDNA or circulating tumour DNA (ctDNA) in the blood plasma. Gliomas, the most frequent brain tumours, comprise ~80% of all primary malignant brain tumours. Glioblastoma multiforme (GBM) is the most common type of glioma, and is uniformly fatal. The median survival of treated GBM patients is in the range of 12-15 months. Standard modalities of therapy are unselective and include surgery, radiation therapy and chemotherapy. Temozolomide (TMZ) is an alkylating agent that methylates DNA and is used as the standard chemotherapy for glioblastoma. Enrolling patients for clinical trials and tailoring therapies based on treatment response can be challenging in the absence of an objective method for measuring tumour burden and determining its genomic composition.

Currently, tumour heterogeneity, clonal diversity and mutation acquisition are major impedances for tailoring personalized therapy in gliomas. Thus, a Liquid Biopsy Diagnostics Platform that applies cfDNA diagnostics may identify the most appropriate therapeutic approach for each glioblastoma patient, by drugs or by radiotherapy, and may help determine the optimal combinations. We isolated cfDNA of 18 of 20 glioma patients vs. 10 healthy individuals. Moreover, we identified mutations, nucleosome maps and fusion biomarkers with 80% sensitivity and 90% specificity.

Comparative genomics and protein domain evolution

​In contrast to fossorial and above-ground organisms, subterranean species have adapted to the extreme stresses of living underground. We analyzed the predicted protein-protein interactions (PPIs) of all gene products, including those of stress-response genes, among nine subterranean, ten fossorial, and 13 aboveground species (PASTORAL).
We considered 10,314 unique orthologous protein families and constructed 5,879,879PPIs in all organisms using ChiPPI. We found strong association between PPI network modulation and adaptation to specific habitats, noting that mutations in genes and changes in protein sequences were not linked directly with niche adaptation in the organisms sampled. Thus, orthologous hypoxia, heat-shock, and circadian clock proteins were found to cluster according to habitat, based on PPIs rather than on sequence similarities. Curiously, “ordered” domains were preserved in aboveground species, while “disordered” domains were conserved in subterranean organisms, and confirmed for proteins in DistProt database. Furthermore, proteins with disordered regions were found to adopt significantly less optimal codon usage in subterranean species than in fossorial and above-ground species. These findings reveal design principles of protein networks by means of alterations in protein domains, thus providing insight into deep mechanisms of evolutionary adaptation, generally, and particularly of species to underground living and other confined habitats.

Codon-usage analysis and cell-cycle regulation

The cell cycle is a temporal program that regulates DNA synthesis and cell division. When we compared the codon usage of cell cycle-regulated genes with that of other genes, we discovered that there is a significant preference for non-optimal codons. Moreover, genes encoding proteins that cycle at the protein level exhibit non-optimal codon preferences. Remarkably, cell cycle-regulated genes expressed in different phases display different codon preferences. Here, we show empirically that transfer RNA (tRNA) expression is indeed highest in the G2 phase of the cell cycle, consistent with the non-optimal codon usage of genes expressed at this time, and lowest toward the end of G1, reflecting the optimal codon usage of G1 genes.

Accordingly, protein levels of human glycyl-, threonyl-, and glutamyl-prolyl tRNA synthetases were found to oscillate, peaking in G2/M phase. In light of our findings, we propose that non-optimal (wobbly) matching codons influence protein synthesis during the cell cycle. We describe a new mathematical model that shows how codon usage can give rise to cell-cycle regulation. In summary, our data indicate that cells exploit wobbling to generate cell cycle-dependent dynamics of proteins.