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Gene fusions can give rise to somatic alterations in cancers. Fusion genes have the potential to create chimeric RNAs, which can generate the phenotypic diversity of cancer cells, and could be associated with novel molecular functions related to cancer cell survival and proliferation. The expression of chimeric RNAs in cancer cells might impact diverse cancer-related functions, including loss of apoptosis and cancer cell plasticity, and promote oncogenesis. Due to their recurrence in cancers and functional association with oncogenic processes, chimeric RNAs are considered biomarkers for cancer diagnosis. Several recent studies demonstrated that chimeric RNAs could lead to the generation of new functionality for the resistance of cancer cells against drug therapy. Therefore, targeting chimeric RNAs in drug resistance cancer could be useful for developing precision medicine. So, understanding the functional impact of chimeric RNAs in cancer cells from an evolutionary perspective will be helpful to elucidate cancer evolution, which could provide a new insight to design more effective therapies for cancer patients in a personalized manner.
Sumit Mukherjee; Henry H. Heng; Milana Frenkel-Morgenstern. Emerging Role of Chimeric RNAs in Cell Plasticity and Adaptive Evolution of Cancer Cells. Cancers 2021, 13, 4328 .
AMA StyleSumit Mukherjee, Henry H. Heng, Milana Frenkel-Morgenstern. Emerging Role of Chimeric RNAs in Cell Plasticity and Adaptive Evolution of Cancer Cells. Cancers. 2021; 13 (17):4328.
Chicago/Turabian StyleSumit Mukherjee; Henry H. Heng; Milana Frenkel-Morgenstern. 2021. "Emerging Role of Chimeric RNAs in Cell Plasticity and Adaptive Evolution of Cancer Cells." Cancers 13, no. 17: 4328.
Here, we introduce a novel “evolution of protein domains” (EvoProDom) model for describing the evolution of proteins based on the “mix and merge” of protein domains. We assembled and integrated genomic and proteomic data comprising protein domain content and orthologous protein content from 109 organisms. In EvoProDom, we characterized evolutionary events, e.g., translocations, as reciprocal exchanges of protein domains between orthologous proteins in different organisms. We showed that protein domains that translocate with highly frequency are generated by transcripts enriched in trans-splicing events, i.e., the generation of novel transcripts from the fusion of two distinct genes. In EvoProDom, we describe a general method to define orthologous protein annotation and protein domain content by predicting these traits from protein sequences using tools such as KoFamKOAL and the Pfam search tool, respectively. In conclusion, EvoProDom presents a novel model for protein evolution based on the “mix and merge” view of protein domains rather than DNA-based models. This confers the advantage of considering chromosomal alterations in evolutionary events.
Gon Carmi; Alessandro Gorohovski; Milana Frenkel‐Morgenstern. EvoProDom: evolutionary modeling of protein families by assessing translocations of protein domains. FEBS Open Bio 2021, 1 .
AMA StyleGon Carmi, Alessandro Gorohovski, Milana Frenkel‐Morgenstern. EvoProDom: evolutionary modeling of protein families by assessing translocations of protein domains. FEBS Open Bio. 2021; ():1.
Chicago/Turabian StyleGon Carmi; Alessandro Gorohovski; Milana Frenkel‐Morgenstern. 2021. "EvoProDom: evolutionary modeling of protein families by assessing translocations of protein domains." FEBS Open Bio , no. : 1.
Circulating animal coronaviruses occasionally infect humans. The SARS‐CoV‐2 coronavirus is responsible for the current worldwide outbreak of COVID‐19 that has resulted in 2,112,844 deaths as of late January, 2021. We compared genetic code preferences in 496 viruses, including 34 coronaviruses, and 242 corresponding hosts, to uncover patterns that distinguish single and “promiscuous” multiple host‐infecting viruses. Based on a codon usage preference score, promiscuous viruses were shown to significantly employ non‐optimal codons, namely, codons that involve "wobble" binding to anti‐codons, as compared to single host viruses. The codon adaptation index (CAI) and the effective number of codons (ENC) were calculated for all viruses and hosts. Promiscuous viruses were less adapted hosts versus single host viruses (p‐value=4.392e‐11). All coronaviruses exploit non‐optimal codons to infect multiple hosts. We found that non‐optimal codon preferences at the beginning of viral coding sequences enhance the translational efficiency of viral proteins within the host. Finally, coronaviruses lack endogenous RNA degradation motifs to a significant degree, thereby increasing viral mRNA burden and infection load. To conclude, we found that promiscuously infecting coronaviruses prefer non‐optimal codon usage to remove degradation motifs from their RNAs and to dramatically increase their viral RNA production rates.
Gon Carmi; Alessandro Gorohovski; Sumit Mukherjee; Milana Frenkel‐Morgenstern. Non‐optimal codon usage preferences of coronaviruses determine their promiscuity for infecting multiple hosts. The FEBS Journal 2021, 1 .
AMA StyleGon Carmi, Alessandro Gorohovski, Sumit Mukherjee, Milana Frenkel‐Morgenstern. Non‐optimal codon usage preferences of coronaviruses determine their promiscuity for infecting multiple hosts. The FEBS Journal. 2021; ():1.
Chicago/Turabian StyleGon Carmi; Alessandro Gorohovski; Sumit Mukherjee; Milana Frenkel‐Morgenstern. 2021. "Non‐optimal codon usage preferences of coronaviruses determine their promiscuity for infecting multiple hosts." The FEBS Journal , no. : 1.
The recently emerged SARS-CoV-2 virus is responsible for the ongoing COVID-19 pandemic that has rapidly developed into a global public health threat. Patients severely affected with COVID-19 present distinct clinical features, including acute respiratory disorder, neutrophilia, cytokine storm, and sepsis. In addition, multiple pro-inflammatory cytokines are found in the plasma of such patients. Transcriptome sequencing of different specimens obtained from patients suffering from severe episodes of COVID-19 shows dynamics in terms of their immune responses. However, those host factors required for SARS-CoV-2 propagation and the underlying molecular mechanisms responsible for dysfunctional immune responses during COVID-19 infection remain elusive. In the present study, we analyzed the mRNA-long non-coding RNA (lncRNA) co-expression network derived from publicly available SARS-CoV-2-infected transcriptome data of human lung epithelial cell lines and bronchoalveolar lavage fluid (BALF) from COVID-19 patients. Through co-expression network analysis, we identified four differentially expressed lncRNAs strongly correlated with genes involved in various immune-related pathways crucial for cytokine signaling. Our findings suggest that the aberrant expression of these four lncRNAs can be associated with cytokine storms and anti-viral responses during severe SARS-CoV-2 infection of the lungs. Thus, the present study uncovers molecular interactions behind the cytokine storm activation potentially responsible for hyper-inflammatory responses in critical COVID-19 patients.
Sumit Mukherjee; Bodhisattwa Banerjee; David Karasik; Milana Frenkel-Morgenstern. mRNA-lncRNA Co-Expression Network Analysis Reveals the Role of lncRNAs in Immune Dysfunction during Severe SARS-CoV-2 Infection. Viruses 2021, 13, 402 .
AMA StyleSumit Mukherjee, Bodhisattwa Banerjee, David Karasik, Milana Frenkel-Morgenstern. mRNA-lncRNA Co-Expression Network Analysis Reveals the Role of lncRNAs in Immune Dysfunction during Severe SARS-CoV-2 Infection. Viruses. 2021; 13 (3):402.
Chicago/Turabian StyleSumit Mukherjee; Bodhisattwa Banerjee; David Karasik; Milana Frenkel-Morgenstern. 2021. "mRNA-lncRNA Co-Expression Network Analysis Reveals the Role of lncRNAs in Immune Dysfunction during Severe SARS-CoV-2 Infection." Viruses 13, no. 3: 402.
Acetylsalicylic acid (aspirin) is commonly used for primary and secondary prevention of cardiovascular diseases. Aspirin use is associated with better outcomes among COVID‐19 positive patients. We hypothesized that aspirin use for primary cardiovascular disease prevention might have a protective effect on COVID‐19 susceptibility and disease duration. We conducted a retrospective population‐based cross‐sectional study, utilizing data from the Leumit Health Services database. The proportion of patients treated with aspirin was significantly lower among the COVID‐19‐positive group, as compared to the COVID‐19‐negative group (73 (11.03 %) vs. 1548 (15.77%); p=0.001). Aspirin use was associated with lower likelihood of COVID‐19 infection, as compared to non‐users (adjusted OR 0.71 (95% CI, 0.52 to 0.99; p=0.041). Aspirin users were older (68.06 ± 12.79 vs. 56.63 ± 12.28 years of age; p<0.001), presented a lower BMI (28.77±5.4 vs. 30.37±4.55; p<0.0189) and showed higher prevalence of hypertension (56, 76.71%), diabetes (47, 64.38%) and COPD (11, 15.07%) than showed the aspirin non‐users (151, 25.64%, p<0.001; 130, 22.07%, p<0.001; and 43, 7.3%, p=0.023, respectively). Moreover, COVID‐19 disease duration (considered as the time between the first positive and second negative COVID‐19 RT‐PCR test results) among aspirin users was significantly shorter, as compared to aspirin non‐users (19.8±7.8 vs. 21.9± 7.9 p= 0.045). Among hospitalized COVID‐positive patients, a higher proportion of surviving subjects were treated with aspirin (20, 19.05%), as opposed to 1 dead subject (14.29%), although this difference was not significant (p=0.449). In conclusion, we observed inverse association between the likelihood of COVID‐19 infection, disease duration and mortality and aspirin use for primary prevention.
Eugene Merzon; Ilan Green; Shlomo Vinker; Avivit Golan‐Cohen; Alessandro Gorohovski; Eva Avramovich; Milana Frenkel‐Morgenstern; Eli Magen. The use of aspirin for primary prevention of cardiovascular disease is associated with a lower likelihood of COVID‐19 infection. The FEBS Journal 2021, 1 .
AMA StyleEugene Merzon, Ilan Green, Shlomo Vinker, Avivit Golan‐Cohen, Alessandro Gorohovski, Eva Avramovich, Milana Frenkel‐Morgenstern, Eli Magen. The use of aspirin for primary prevention of cardiovascular disease is associated with a lower likelihood of COVID‐19 infection. The FEBS Journal. 2021; ():1.
Chicago/Turabian StyleEugene Merzon; Ilan Green; Shlomo Vinker; Avivit Golan‐Cohen; Alessandro Gorohovski; Eva Avramovich; Milana Frenkel‐Morgenstern; Eli Magen. 2021. "The use of aspirin for primary prevention of cardiovascular disease is associated with a lower likelihood of COVID‐19 infection." The FEBS Journal , no. : 1.
The recent outbreak of COVID-19 has generated an enormous amount of Big Data. To date, the COVID-19 Open Research Dataset (CORD-19), lists ∼130,000 articles from the WHO COVID-19 database, PubMed Central, medRxiv, and bioRxiv, as collected by Semantic Scholar. According to LitCovid (11 August 2020), ∼40,300 COVID19-related articles are currently listed in PubMed. It has been shown in clinical settings that the analysis of past research results and the mining of available data can provide novel opportunities for the successful application of currently approved therapeutics and their combinations for the treatment of conditions caused by a novel SARS-CoV-2 infection. As such, effective responses to the pandemic require the development of efficient applications, methods and algorithms for data navigation, text-mining, clustering, classification, analysis, and reasoning. Thus, our COVID19 Drug Repository represents a modular platform for drug data navigation and analysis, with an emphasis on COVID-19-related information currently being reported. The COVID19 Drug Repository enables users to focus on different levels of complexity, starting from general information about (FDA-) approved drugs, PubMed references, clinical trials, recipes as well as the descriptions of molecular mechanisms of drugs’ action. Our COVID19 drug repository provide a most updated world-wide collection of drugs that has been repurposed for COVID19 treatments around the world.
Dmitry Tworowski; Alessandro Gorohovski; Sumit Mukherjee; Gon Carmi; Eliad Levy; Rajesh Detroja; Sunanda Biswas Mukherjee; Milana Frenkel-Morgenstern. COVID19 Drug Repository: text-mining the literature in search of putative COVID19 therapeutics. Nucleic Acids Research 2020, 49, D1113 -D1121.
AMA StyleDmitry Tworowski, Alessandro Gorohovski, Sumit Mukherjee, Gon Carmi, Eliad Levy, Rajesh Detroja, Sunanda Biswas Mukherjee, Milana Frenkel-Morgenstern. COVID19 Drug Repository: text-mining the literature in search of putative COVID19 therapeutics. Nucleic Acids Research. 2020; 49 (D1):D1113-D1121.
Chicago/Turabian StyleDmitry Tworowski; Alessandro Gorohovski; Sumit Mukherjee; Gon Carmi; Eliad Levy; Rajesh Detroja; Sunanda Biswas Mukherjee; Milana Frenkel-Morgenstern. 2020. "COVID19 Drug Repository: text-mining the literature in search of putative COVID19 therapeutics." Nucleic Acids Research 49, no. D1: D1113-D1121.
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. We considered 10,314 unique orthologous protein families and constructed 5,879,879 PPIs 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.
Gon Carmi; Somnath Tagore; Alessandro Gorohovski; Aviad Sivan; Dorith Raviv-Shay; Milana Frenkel-Morgenstern. Design principles of gene evolution for niche adaptation through changes in protein–protein interaction networks. Scientific Reports 2020, 10, 1 -14.
AMA StyleGon Carmi, Somnath Tagore, Alessandro Gorohovski, Aviad Sivan, Dorith Raviv-Shay, Milana Frenkel-Morgenstern. Design principles of gene evolution for niche adaptation through changes in protein–protein interaction networks. Scientific Reports. 2020; 10 (1):1-14.
Chicago/Turabian StyleGon Carmi; Somnath Tagore; Alessandro Gorohovski; Aviad Sivan; Dorith Raviv-Shay; Milana Frenkel-Morgenstern. 2020. "Design principles of gene evolution for niche adaptation through changes in protein–protein interaction networks." Scientific Reports 10, no. 1: 1-14.
Aim To evaluate associations of plasma 25(OH)D status with the likelihood of coronavirus disease (COVID‐19) infection and hospitalization. Methods The study population included the 14,000 members of Leumit Health Services who were tested for COVID‐19 infection from February 1st to April 30th 2020, and who had at least one previous blood test for plasma 25(OH)D level. "Suboptimal" or "low" plasma 25(OH)D level was defined as plasma 25‐hydroxyvitamin D, or 25(OH)D, concentration below the level of 30 ng/mL. Results Of 7,807 individuals, 782 (10.1%) were COVID‐19‐positive, and 7,025 (89.9%) COVID‐19‐negative. The mean plasma vitamin D level was significantly lower among those who tested positive than negative for COVID‐19 [19.00 ng/mL (95% confidence interval [CI] 18.41‐19.59) vs . 20.55 (95% CI 20.32‐20.78)]. Univariate analysis demonstrated an association between low plasma 25(OH)D level and increased likelihood of COVID‐19 infection [crude odds ratio (OR) of 1.58 (95% CI 1.24‐2.01, p<0.001)], and of hospitalization due to the SARS‐CoV‐2 virus [crude OR of 2.09 (95% CI 1.01‐ 4.30, p<0.05)]. In multivariate analyses that controlled for demographic variables, and psychiatric and somatic disorders, the adjusted OR of COVID‐19 infection [1.45 (95% CI 1.08‐1.95, p<0.001)], and of hospitalization due to the SARS‐CoV‐2 virus [1.95 (95% CI 0.98‐4.845, p=0.061)] were preserved. In the multivariate analyses, age over 50 years, male gender and low‐medium socioeconomic status were also positively associated with the risk of COVID‐19 infection; age over 50 years was positively associated with the likelihood of hospitalization due to COVID‐19. Conclusion Low plasma 25(OH)D level appears to be an independent risk factor for COVID‐19 infection and hospitalization.
Eugene Merzon; Dmitry Tworowski; Alessandro Gorohovski; Shlomo Vinker; Avivit Golan Cohen; Ilan Green; Milana Frenkel‐Morgenstern. Low plasma 25(OH) vitamin D level is associated with increased risk of COVID‐19 infection: an Israeli population‐based study. The FEBS Journal 2020, 287, 3693 -3702.
AMA StyleEugene Merzon, Dmitry Tworowski, Alessandro Gorohovski, Shlomo Vinker, Avivit Golan Cohen, Ilan Green, Milana Frenkel‐Morgenstern. Low plasma 25(OH) vitamin D level is associated with increased risk of COVID‐19 infection: an Israeli population‐based study. The FEBS Journal. 2020; 287 (17):3693-3702.
Chicago/Turabian StyleEugene Merzon; Dmitry Tworowski; Alessandro Gorohovski; Shlomo Vinker; Avivit Golan Cohen; Ilan Green; Milana Frenkel‐Morgenstern. 2020. "Low plasma 25(OH) vitamin D level is associated with increased risk of COVID‐19 infection: an Israeli population‐based study." The FEBS Journal 287, no. 17: 3693-3702.
Aim To evaluate associations of plasma 25(OH)D status with the likelihood of coronavirus disease (COVID-19) infection and hospitalization. Methods The study population included the 14,000 members of Leumit Health Services who were tested for COVID-19 infection from February 1stto April 30th2020, and who had at least one previous blood test for plasma 25(OH)D level. “Suboptimal” or “low” plasma 25(OH)D level was defined as plasma 25-hydroxyvitamin D, or 25(OH)D, concentration below 30 ng/mL. Results Of 7,807 individuals, 782 (10.1%) were COVID-19-positive, and 7,025 (89.9%) COVID-19-negative. The mean plasma vitamin D level was significantly lower among those who tested positive than negative for COVID-19 [19.00 ng/mL (95% confidence interval [CI] 18.41-19.59)vs. 20.55 (95% CI 20.32-20.78)]. Univariate analysis demonstrated an association between low plasma 25(OH)D level and increased likelihood of COVID-19 infection [crude odds ratio (OR) of 1.58 (95% CI 1.24-2.01, p<0.001)], and of hospitalization due to the SARS-CoV-2 virus [crude OR of 2.09 (95% CI 1.01-4.30, p<0.05)]. In multivariate analyses that controlled for demographic variables, and psychiatric and somatic disorders, the adjusted OR of COVID-19 infection [1.45 (95% CI 1.08-1.95, p<0.001)], and of hospitalization due to the SARS-CoV-2 virus [1.95 (95% CI 0.98-4.845, p=0.061)] were preserved. In the multivariate analyses, age over 50 years, male gender and low-medium socioeconomic status were also positively associated with the risk of COVID-19 infection; age over 50 years was positively associated with the likelihood of hospitalization due to COVID-19. Conclusion Low plasma 25(OH)D level appears to be an independent risk factor for COVID-19 infection and hospitalization.
Eugene Merzon; Dmitry Tworowski; Alessandro Gorohovski; Shlomo Vinker; Avivit Golan Cohen; Ilan Green; Milana Frenkel Morgenstern. Low plasma 25(OH) vitamin D level is associated with increased risk of COVID-19 infection: an Israeli population-based study. 2020, 1 .
AMA StyleEugene Merzon, Dmitry Tworowski, Alessandro Gorohovski, Shlomo Vinker, Avivit Golan Cohen, Ilan Green, Milana Frenkel Morgenstern. Low plasma 25(OH) vitamin D level is associated with increased risk of COVID-19 infection: an Israeli population-based study. . 2020; ():1.
Chicago/Turabian StyleEugene Merzon; Dmitry Tworowski; Alessandro Gorohovski; Shlomo Vinker; Avivit Golan Cohen; Ilan Green; Milana Frenkel Morgenstern. 2020. "Low plasma 25(OH) vitamin D level is associated with increased risk of COVID-19 infection: an Israeli population-based study." , no. : 1.
A new coronavirus infection, COVID-19, has recently emerged, and has caused a global pandemic along with an international public health emergency. Currently, no licensed vaccines are available for COVID-19. The identification of immunodominant epitopes for both B- and T-cells that induce protective responses in the host is crucial for effective vaccine design. Computational prediction of potential epitopes might significantly reduce the time required to screen peptide libraries as part of emergent vaccine design. In our present study, we used an extensive immunoinformatics-based approach to predict conserved immunodominant epitopes from the proteome of SARS-CoV-2. Regions from SARS-CoV-2 protein sequences were defined as immunodominant, based on the following three criteria regarding B- and T-cell epitopes: (i) they were both mapped, (ii) they predicted protective antigens, and (iii) they were completely identical to experimentally validated epitopes of SARS-CoV. Further, structural and molecular docking analyses were performed in order to understand the binding interactions of the identified immunodominant epitopes with human major histocompatibility complexes (MHC). Our study provides a set of potential immunodominant epitopes that could enable the generation of both antibody- and cell-mediated immunity. This could contribute to developing peptide vaccine-based adaptive immunotherapy against SARS-CoV-2 infections and prevent future pandemic outbreaks.
Sumit Mukherjee; Dmitry Tworowski; Rajesh Detroja; Sunanda Biswas Mukherjee; Milana Frenkel-Morgenstern. Immunoinformatics and Structural Analysis for Identification of Immunodominant Epitopes in SARS-CoV-2 as Potential Vaccine Targets. Vaccines 2020, 8, 290 .
AMA StyleSumit Mukherjee, Dmitry Tworowski, Rajesh Detroja, Sunanda Biswas Mukherjee, Milana Frenkel-Morgenstern. Immunoinformatics and Structural Analysis for Identification of Immunodominant Epitopes in SARS-CoV-2 as Potential Vaccine Targets. Vaccines. 2020; 8 (2):290.
Chicago/Turabian StyleSumit Mukherjee; Dmitry Tworowski; Rajesh Detroja; Sunanda Biswas Mukherjee; Milana Frenkel-Morgenstern. 2020. "Immunoinformatics and Structural Analysis for Identification of Immunodominant Epitopes in SARS-CoV-2 as Potential Vaccine Targets." Vaccines 8, no. 2: 290.
Gliomas account for about 80% of all malignant brain tumours. Diagnosis is achieved by radiographic imaging followed by tumour resection, to determine tumour cell type, grade and molecular characteristics. Glioblastoma multiforme (GBM) is the most common type of glioma, and is uniformly fatal. The median survival of treated GBM patients is 12-15 months. Standard modalities of therapy are unselective and include surgery, radiation therapy and chemotherapy, while precision medicine has yet to demonstrate improvements in disease outcome. We therefore selected GBM as a model to develop a precision medicine methodology for monitoring patients using blood plasma circulating cell-free DNA (cfDNA). Currently, tumour heterogeneity, clonal diversity and mutation acquisition are the major impedances for tailoring personalized therapy in gliomas in general, and particularly in GBM. Thus, a liquid biopsy diagnostics platform based on cfDNA sequencing may improve treatment outcome for GBM patients, by guiding therapy selection. In this study, we processed from 27 patients with glioma, 27 plasma samples for cfDNA isolation and 5 tissue biopsy samples for tumour DNA isolation. From a control group of 14 healthy individuals, 14 plasma samples were processed for cfDNA isolation. In glioma patients, cfDNA concentration was elevated compared to controls. Point mutations found in glioma tissue biopsies were also found in the cfDNA samples (95% identity). Finally, we identified novel chimeric genes (gene-gene fusions) in both tumour and cfDNA samples. These fusions are predicted to alter protein interaction networks, by removing tumour suppressors and adding oncoproteins. Indeed, several of these fusions are potential drug targets, particularly, NTRK or ROS1 fusions, specifically for crizotinib analogues (like entrectinib and larotrectinib) with enhanced penetration of the central nervous system. Taken together, our results demonstrate that novel druggable targets in gliomas can be identified by liquid biopsy using cfDNA in patient plasma. These results open new perspectives and abilities of precision medicine in GBM.
Vikrant Palande; Rajesh Detroja; Alessandro Gorohovski; Rainer Glass; Charlotte Flueh; Marina Kurtz; Shira Perez; Dorith Raviv Shay; Tali Siegal; Milana Frenkel-Morgenstern. A liquid biopsy platform for detecting gene-gene fusions as glioma diagnostic biomarkers and drug targets. 2020, 1 .
AMA StyleVikrant Palande, Rajesh Detroja, Alessandro Gorohovski, Rainer Glass, Charlotte Flueh, Marina Kurtz, Shira Perez, Dorith Raviv Shay, Tali Siegal, Milana Frenkel-Morgenstern. A liquid biopsy platform for detecting gene-gene fusions as glioma diagnostic biomarkers and drug targets. . 2020; ():1.
Chicago/Turabian StyleVikrant Palande; Rajesh Detroja; Alessandro Gorohovski; Rainer Glass; Charlotte Flueh; Marina Kurtz; Shira Perez; Dorith Raviv Shay; Tali Siegal; Milana Frenkel-Morgenstern. 2020. "A liquid biopsy platform for detecting gene-gene fusions as glioma diagnostic biomarkers and drug targets." , no. : 1.
Here, we developed a novel evolution of protein domains (EvoProDom) model for evolution of proteins, which was based on mix and merge of protein domains. We collected and integrated genomic and proteome data for 109 organisms. These data include protein domain content and orthologous protein families. In EvoProDom, we defined evolutionary events, such as translocations, as reciprocal exchanges of protein domains between orthologous proteins of different organisms. We found that protein domains, which frequently appear in translocation events, were enriched in trans-splicing events, i.e., producing novel transcripts fused from two distinct genes. We presented in EvoProDom, a general method to obtain protein domain content and orthologous protein annotation, by predicting these data from protein sequences using the Pfam search tool and KoFamKOALA, respectively. This method can be implemented in other research such as proteomics, protein design and host-virus interactions.
Gon Carmi; Alessandro Gorohovski; Milana Frenkel-Morgenstern. EvoProDom: Evolutionary model of protein families by means of translocations of protein domains. 2020, 1 .
AMA StyleGon Carmi, Alessandro Gorohovski, Milana Frenkel-Morgenstern. EvoProDom: Evolutionary model of protein families by means of translocations of protein domains. . 2020; ():1.
Chicago/Turabian StyleGon Carmi; Alessandro Gorohovski; Milana Frenkel-Morgenstern. 2020. "EvoProDom: Evolutionary model of protein families by means of translocations of protein domains." , no. : 1.
Chromothripsis is a mutational phenomenon characterized by massive, clustered genomic rearrangements that occurs in cancer and other diseases. Recent studies in selected cancer types have suggested that chromothripsis may be more common than initially inferred from low-resolution copy-number data. Here, as part of the Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium of the International Cancer Genome Consortium (ICGC) and The Cancer Genome Atlas (TCGA), we analyze patterns of chromothripsis across 2,658 tumors from 38 cancer types using whole-genome sequencing data. We find that chromothripsis events are pervasive across cancers, with a frequency of more than 50% in several cancer types. Whereas canonical chromothripsis profiles display oscillations between two copy-number states, a considerable fraction of events involve multiple chromosomes and additional structural alterations. In addition to non-homologous end joining, we detect signatures of replication-associated processes and templated insertions. Chromothripsis contributes to oncogene amplification and to inactivation of genes such as mismatch-repair-related genes. These findings show that chromothripsis is a major process that drives genome evolution in human cancer.
Isidro Cortés-Ciriano; Jake June-Koo Lee; Ruibin Xi; Dhawal Jain; Youngsook L. Jung; Lixing Yang; Dmitry Gordenin; Leszek J. Klimczak; Cheng-Zhong Zhang; David S. Pellman; Kadir C. Akdemir; Eva G. Alvarez; Adrian Baez-Ortega; Rameen Beroukhim; Paul C. Boutros; David D. L. Bowtell; Benedikt Brors; Kathleen H. Burns; Peter J. Campbell; Kin Chan; Ken Chen; Ana Dueso-Barroso; Andrew J. Dunford; Paul A. Edwards; Xavier Estivill; Dariush Etemadmoghadam; Lars Feuerbach; J. Lynn Fink; Milana Frenkel-Morgenstern; Dale W. Garsed; Mark Gerstein; David Haan; James E. Haber; Julian M. Hess; Barbara Hutter; Marcin Imielinski; David T. W. Jones; Young Seok Ju; Marat D. Kazanov; Youngil Koh; Jan O. Korbel; Kiran Kumar; Eunjung Alice Lee; Yilong Li; Andy G. Lynch; Geoff Macintyre; Florian Markowetz; Iñigo Martincorena; Alexander Martinez-Fundichely; Satoru Miyano; Hidewaki Nakagawa; Fabio C. P. Navarro; Stephan Ossowski; Peter J. Park; John V. Pearson; Montserrat Puiggròs; Karsten Rippe; Nicola D. Roberts; Steven A. Roberts; Bernardo Rodriguez-Martin; Steven E. Schumacher; Ralph Scully; Mark Shackleton; Nikos Sidiropoulos; Lina Sieverling; Chip Stewart; David Torrents; Jose M. C. Tubio; Izar Villasante; Nicola Waddell; Jeremiah A. Wala; Joachim Weischenfeldt; Xiaotong Yao; Sung-Soo Yoon; Jorge Zamora; PCAWG Structural Variation Working Group; PCAWG Consortium. Comprehensive analysis of chromothripsis in 2,658 human cancers using whole-genome sequencing. Nature Genetics 2020, 52, 331 -341.
AMA StyleIsidro Cortés-Ciriano, Jake June-Koo Lee, Ruibin Xi, Dhawal Jain, Youngsook L. Jung, Lixing Yang, Dmitry Gordenin, Leszek J. Klimczak, Cheng-Zhong Zhang, David S. Pellman, Kadir C. Akdemir, Eva G. Alvarez, Adrian Baez-Ortega, Rameen Beroukhim, Paul C. Boutros, David D. L. Bowtell, Benedikt Brors, Kathleen H. Burns, Peter J. Campbell, Kin Chan, Ken Chen, Ana Dueso-Barroso, Andrew J. Dunford, Paul A. Edwards, Xavier Estivill, Dariush Etemadmoghadam, Lars Feuerbach, J. Lynn Fink, Milana Frenkel-Morgenstern, Dale W. Garsed, Mark Gerstein, David Haan, James E. Haber, Julian M. Hess, Barbara Hutter, Marcin Imielinski, David T. W. Jones, Young Seok Ju, Marat D. Kazanov, Youngil Koh, Jan O. Korbel, Kiran Kumar, Eunjung Alice Lee, Yilong Li, Andy G. Lynch, Geoff Macintyre, Florian Markowetz, Iñigo Martincorena, Alexander Martinez-Fundichely, Satoru Miyano, Hidewaki Nakagawa, Fabio C. P. Navarro, Stephan Ossowski, Peter J. Park, John V. Pearson, Montserrat Puiggròs, Karsten Rippe, Nicola D. Roberts, Steven A. Roberts, Bernardo Rodriguez-Martin, Steven E. Schumacher, Ralph Scully, Mark Shackleton, Nikos Sidiropoulos, Lina Sieverling, Chip Stewart, David Torrents, Jose M. C. Tubio, Izar Villasante, Nicola Waddell, Jeremiah A. Wala, Joachim Weischenfeldt, Xiaotong Yao, Sung-Soo Yoon, Jorge Zamora, PCAWG Structural Variation Working Group, PCAWG Consortium. Comprehensive analysis of chromothripsis in 2,658 human cancers using whole-genome sequencing. Nature Genetics. 2020; 52 (3):331-341.
Chicago/Turabian StyleIsidro Cortés-Ciriano; Jake June-Koo Lee; Ruibin Xi; Dhawal Jain; Youngsook L. Jung; Lixing Yang; Dmitry Gordenin; Leszek J. Klimczak; Cheng-Zhong Zhang; David S. Pellman; Kadir C. Akdemir; Eva G. Alvarez; Adrian Baez-Ortega; Rameen Beroukhim; Paul C. Boutros; David D. L. Bowtell; Benedikt Brors; Kathleen H. Burns; Peter J. Campbell; Kin Chan; Ken Chen; Ana Dueso-Barroso; Andrew J. Dunford; Paul A. Edwards; Xavier Estivill; Dariush Etemadmoghadam; Lars Feuerbach; J. Lynn Fink; Milana Frenkel-Morgenstern; Dale W. Garsed; Mark Gerstein; David Haan; James E. Haber; Julian M. Hess; Barbara Hutter; Marcin Imielinski; David T. W. Jones; Young Seok Ju; Marat D. Kazanov; Youngil Koh; Jan O. Korbel; Kiran Kumar; Eunjung Alice Lee; Yilong Li; Andy G. Lynch; Geoff Macintyre; Florian Markowetz; Iñigo Martincorena; Alexander Martinez-Fundichely; Satoru Miyano; Hidewaki Nakagawa; Fabio C. P. Navarro; Stephan Ossowski; Peter J. Park; John V. Pearson; Montserrat Puiggròs; Karsten Rippe; Nicola D. Roberts; Steven A. Roberts; Bernardo Rodriguez-Martin; Steven E. Schumacher; Ralph Scully; Mark Shackleton; Nikos Sidiropoulos; Lina Sieverling; Chip Stewart; David Torrents; Jose M. C. Tubio; Izar Villasante; Nicola Waddell; Jeremiah A. Wala; Joachim Weischenfeldt; Xiaotong Yao; Sung-Soo Yoon; Jorge Zamora; PCAWG Structural Variation Working Group; PCAWG Consortium. 2020. "Comprehensive analysis of chromothripsis in 2,658 human cancers using whole-genome sequencing." Nature Genetics 52, no. 3: 331-341.
Circulating tumor DNA (ctDNA) has recently emerged as a minimally invasive 'liquid biopsy' tool in precision medicine. ctDNA-genomic DNA fragments that are released into the bloodstream after the active secretion of microvesicles or tumor cell lysis-reflects tumor evolution and the genomic alterations present in primary and/or metastatic tumors. Notably, ctDNA analysis might allow the stratification of patients, the monitoring of the therapeutic response, and the establishment of an opportunity for early intervention independent of detection by imaging modalities or clinical symptoms. As oncology moves towards precision medicine, the information in ctDNA provides a means for the individual management of the patient based on their tumor's genetic profile. This review presents current evidence on the potential role for ctDNA in helping to guide individualized clinical treatment decisions for patients with melanoma, castration-resistant prostate cancer, breast cancer, metastatic colorectal cancer, and non-small cell lung cancer.
Kelly C. S. Oliveira; Iago Barroso Ramos; Jessica M. C. Silva; Williams Fernandes Barra; Gregory J. Riggins; Vikrant Palande; Catarina Torres Pinho; Milana Frenkel-Morgenstern; Sidney E.B. Santos; Paulo P. Assumpcao; Rommel R. Burbano; Danielle Queiroz Calcagno. Current Perspectives on Circulating Tumor DNA, Precision Medicine, and Personalized Clinical Management of Cancer. Molecular Cancer Research 2020, 18, 517 -528.
AMA StyleKelly C. S. Oliveira, Iago Barroso Ramos, Jessica M. C. Silva, Williams Fernandes Barra, Gregory J. Riggins, Vikrant Palande, Catarina Torres Pinho, Milana Frenkel-Morgenstern, Sidney E.B. Santos, Paulo P. Assumpcao, Rommel R. Burbano, Danielle Queiroz Calcagno. Current Perspectives on Circulating Tumor DNA, Precision Medicine, and Personalized Clinical Management of Cancer. Molecular Cancer Research. 2020; 18 (4):517-528.
Chicago/Turabian StyleKelly C. S. Oliveira; Iago Barroso Ramos; Jessica M. C. Silva; Williams Fernandes Barra; Gregory J. Riggins; Vikrant Palande; Catarina Torres Pinho; Milana Frenkel-Morgenstern; Sidney E.B. Santos; Paulo P. Assumpcao; Rommel R. Burbano; Danielle Queiroz Calcagno. 2020. "Current Perspectives on Circulating Tumor DNA, Precision Medicine, and Personalized Clinical Management of Cancer." Molecular Cancer Research 18, no. 4: 517-528.
Chimeric RNA transcripts are formed when exons from two genes fuse together, often due to chromosomal translocations, transcriptional errors or trans-splicing effect. While these chimeric RNAs produce functional proteins only in certain cases, they play a significant role in disease phenotyping and progression. ChiTaRS 5.0 (http://chitars.md.biu.ac.il/) is the latest and most comprehensive chimeric transcript repository, with 111 582 annotated entries from eight species, including 23 167 known human cancer breakpoints. The database includes unique information correlating chimeric breakpoints with 3D chromatin contact maps, generated from public datasets of chromosome conformation capture techniques (Hi–C). In this update, we have added curated information on druggable fusion targets matched with chimeric breakpoints, which are applicable to precision medicine in cancers. The introduction of a new section that lists chimeric RNAs in various cell-lines is another salient feature. Finally, using text-mining techniques, novel chimeras in Alzheimer's disease, schizophrenia, dyslexia and other diseases were collected in ChiTaRS. Thus, this improved version is an extensive catalogue of chimeras from multiple species. It extends our understanding of the evolution of chimeric transcripts in eukaryotes and contributes to the analysis of 3D genome conformational changes and the functional role of chimeras in the etiopathogenesis of cancers and other complex diseases.
Deepak Balamurali; Alessandro Gorohovski; Rajesh Detroja; Vikrant Palande; Dorith Raviv-Shay; Milana Frenkel-Morgenstern. ChiTaRS 5.0: the comprehensive database of chimeric transcripts matched with druggable fusions and 3D chromatin maps. Nucleic Acids Research 2019, 48, D825 -D834.
AMA StyleDeepak Balamurali, Alessandro Gorohovski, Rajesh Detroja, Vikrant Palande, Dorith Raviv-Shay, Milana Frenkel-Morgenstern. ChiTaRS 5.0: the comprehensive database of chimeric transcripts matched with druggable fusions and 3D chromatin maps. Nucleic Acids Research. 2019; 48 ():D825-D834.
Chicago/Turabian StyleDeepak Balamurali; Alessandro Gorohovski; Rajesh Detroja; Vikrant Palande; Dorith Raviv-Shay; Milana Frenkel-Morgenstern. 2019. "ChiTaRS 5.0: the comprehensive database of chimeric transcripts matched with druggable fusions and 3D chromatin maps." Nucleic Acids Research 48, no. : D825-D834.
Chimeric RNA moieties typically consist of exons from two genes expressed from different genomic locations and produced by chromosomal translocations, trans-splicing or transcription errors. Recent advances in next-generation sequencing procedures have opened new horizons for identification of novel chimeric transcripts in various diseases in a personalized manner. Here we describe the detailed computational procedures to identify chimeric transcripts using RNA-seq reads. Moreover, we elaborate on the domain–domain co-occurrence method to detect alterations in chimeric protein–protein interaction (ChiPPI) networks produced by chimeric RNA that are translated to chimeric proteins.
Milana Frenkel-Morgenstern. Identification of Chimeric RNAs Using RNA-Seq Reads and Protein–Protein Interactions of Translated Chimeras. Methods in Molecular Biology 2019, 2079, 27 -40.
AMA StyleMilana Frenkel-Morgenstern. Identification of Chimeric RNAs Using RNA-Seq Reads and Protein–Protein Interactions of Translated Chimeras. Methods in Molecular Biology. 2019; 2079 ():27-40.
Chicago/Turabian StyleMilana Frenkel-Morgenstern. 2019. "Identification of Chimeric RNAs Using RNA-Seq Reads and Protein–Protein Interactions of Translated Chimeras." Methods in Molecular Biology 2079, no. : 27-40.
Tailored therapy aims to cure cancer patients effectively and safely, based on the complex interactions between patients' genomic features, disease pathology and drug metabolism. Thus, the continual increase in scientific literature drives the need for efficient methods of data mining to improve the extraction of useful information from texts based on patients' genomic features. An important application of text mining to tailored therapy in cancer encompasses the use of mutations and cancer fusion genes as moieties that change patients' cellular networks to develop cancer, and also affect drug metabolism. Fusion proteins, which are derived from the slippage of two parental genes, are produced in cancer by chromosomal aberrations and trans-splicing. Given that the two parental proteins for predicted fusion proteins are known, we used our previously developed method for identifying chimeric protein-protein interactions (ChiPPIs) associated with the fusion proteins. Here, we present a validation approach that receives fusion proteins of interest, predicts their cellular network alterations by ChiPPI and validates them by our new method, ProtFus, using an online literature search. This process resulted in a set of 358 fusion proteins and their corresponding protein interactions, as a training set for a Naïve Bayes classifier, to identify predicted fusion proteins that have reliable evidence in the literature and that were confirmed experimentally. Next, for a test group of 1817 fusion proteins, we were able to identify from the literature 2908 PPIs in total, across 18 cancer types. The described method, ProtFus, can be used for screening the literature to identify unique cases of fusion proteins and their PPIs, as means of studying alterations of protein networks in cancers. Availability: http://protfus.md.biu.ac.il/.
Somnath Tagore; Alessandro Gorohovski; Lars Juhl Jensen; Milana Frenkel-Morgenstern. ProtFus: A Comprehensive Method Characterizing Protein-Protein Interactions of Fusion Proteins. PLOS Computational Biology 2019, 15, e1007239 .
AMA StyleSomnath Tagore, Alessandro Gorohovski, Lars Juhl Jensen, Milana Frenkel-Morgenstern. ProtFus: A Comprehensive Method Characterizing Protein-Protein Interactions of Fusion Proteins. PLOS Computational Biology. 2019; 15 (8):e1007239.
Chicago/Turabian StyleSomnath Tagore; Alessandro Gorohovski; Lars Juhl Jensen; Milana Frenkel-Morgenstern. 2019. "ProtFus: A Comprehensive Method Characterizing Protein-Protein Interactions of Fusion Proteins." PLOS Computational Biology 15, no. 8: e1007239.
Chd1 is a chromatin remodeler that is involved in nucleosome positioning and transcription. Deletion of CHD1 is a frequent event in prostate cancer. The Structural Maintenance of Chromosome (SMC) complex cohesin mediates long-range chromatin interactions and is involved in maintaining genome stability. We provide new evidence that Chd1 is a regulator of cohesin. In the yeast S. cerevisiae, Chd1 is not essential for viability. We show that deletion of the gene leads to a defect in sister chromatid cohesion and in chromosome morphology. Chl1 is a non-essential DNA helicase that has been shown to regulate cohesin loading. Surprisingly, co-deletion of CHD1 and CHL1 results in an additive cohesion defect but partial suppression of the chromosome structure phenotype. We found that the cohesin regulator Pds5 is overexpressed when Chd1 and Chl1 are deleted. However, Pds5 expression is reduced to wild type levels when both genes are deleted. Finally, we show a correlation in the expression of CHD1 and cohesin genes in prostate cancer patients. Furthermore, we show that overexpression of cohesin subunits is correlated with the aggressiveness of the tumor. The biological roles of the interplay between Chd1, Chl1 and SMCs are discussed.
Alexandra Boginya; Rajesh Detroja; Avi Matityahu; Milana Frenkel-Morgenstern; Itay Onn. The chromatin remodeler Chd1 regulates cohesin in budding yeast and humans. Scientific Reports 2019, 9, 1 -10.
AMA StyleAlexandra Boginya, Rajesh Detroja, Avi Matityahu, Milana Frenkel-Morgenstern, Itay Onn. The chromatin remodeler Chd1 regulates cohesin in budding yeast and humans. Scientific Reports. 2019; 9 (1):1-10.
Chicago/Turabian StyleAlexandra Boginya; Rajesh Detroja; Avi Matityahu; Milana Frenkel-Morgenstern; Itay Onn. 2019. "The chromatin remodeler Chd1 regulates cohesin in budding yeast and humans." Scientific Reports 9, no. 1: 1-10.
SMURF2, an E3 ubiquitin ligase and suggested tumor suppressor, operates in normal cells to prevent genomic instability and carcinogenesis. However, the mechanisms underlying SMURF2 inactivation in human malignancies remain elusive, as SMURF2 is rarely found mutated or deleted in cancers. We hypothesized that SMURF2 might have a distinct molecular biodistribution in cancer versus normal cells and tissues. The expression and localization of SMURF2 were analyzed in 666 human normal and cancer tissues, with primary focus on prostate and breast tumors. These investigations were accompanied by SMURF2 gene expression analyses, subcellular fractionation and biochemical studies, including SMURF2's interactome analysis. We found that while in normal cells and tissues SMURF2 has a predominantly nuclear localization, in prostate and aggressive breast carcinomas SMURF2 shows a significantly increased cytoplasmic sequestration, associated with the disease progression. Mechanistic studies showed that the nuclear export machinery was not involved in cytoplasmic accumulation of SMURF2, while uncovered that its stability is markedly increased in the cytoplasmic compartment. Subsequent interactome analyses pointed to 14-3-3s as SMURF2 interactors, which could potentially affect its localization. These findings link the distorted expression of SMURF2 to human carcinogenesis and suggest the alterations in SMURF2 localization as a potential mechanism obliterating its tumor suppressor activities.
Andrea Emanuelli; Dhanoop Manikoth Ayyathan; Praveen Koganti; Pooja Anil Shah; Liat Apel-Sarid; Biagio Paolini; Rajesh Detroja; Milana Frenkel-Morgenstern; Michael Blank. Altered Expression and Localization of Tumor Suppressive E3 Ubiquitin Ligase SMURF2 in Human Prostate and Breast Cancer. Cancers 2019, 11, 556 .
AMA StyleAndrea Emanuelli, Dhanoop Manikoth Ayyathan, Praveen Koganti, Pooja Anil Shah, Liat Apel-Sarid, Biagio Paolini, Rajesh Detroja, Milana Frenkel-Morgenstern, Michael Blank. Altered Expression and Localization of Tumor Suppressive E3 Ubiquitin Ligase SMURF2 in Human Prostate and Breast Cancer. Cancers. 2019; 11 (4):556.
Chicago/Turabian StyleAndrea Emanuelli; Dhanoop Manikoth Ayyathan; Praveen Koganti; Pooja Anil Shah; Liat Apel-Sarid; Biagio Paolini; Rajesh Detroja; Milana Frenkel-Morgenstern; Michael Blank. 2019. "Altered Expression and Localization of Tumor Suppressive E3 Ubiquitin Ligase SMURF2 in Human Prostate and Breast Cancer." Cancers 11, no. 4: 556.
Mathematics has become essential in cancer biology. Recent developments in high-throughput molecular profiling techniques enable assessing molecular states of tumors in great detail. Cancer genome data are collected at a large scale in numerous clinical studies and in international consortia, such as The Cancer Genome Atlas and the International Cancer Genome Consortium. Developing mathematical models that are consistent with and predictive of the true underlying biological mechanisms is a central goal of cancer biology. In this work, we used percolations and power-law models to study protein-protein interactions in cancer fusions. We used site-directed knockouts to understand the modular components of fusion protein-protein interaction networks, thereby providing models for target-based drug predictions.
Somnath Tagore; Milana Frenkel-Morgenstern. When Mathematics Outsmarts Cancer. Transactions on Petri Nets and Other Models of Concurrency XV 2019, 477 -485.
AMA StyleSomnath Tagore, Milana Frenkel-Morgenstern. When Mathematics Outsmarts Cancer. Transactions on Petri Nets and Other Models of Concurrency XV. 2019; ():477-485.
Chicago/Turabian StyleSomnath Tagore; Milana Frenkel-Morgenstern. 2019. "When Mathematics Outsmarts Cancer." Transactions on Petri Nets and Other Models of Concurrency XV , no. : 477-485.