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1. Protocol for Delivery of CRISPR/dCas9 Systems for Epigenetic Editing into Solid Tumors Using Lipid Nanoparticles Encapsulating RNA

Author

Woodward, Eleanor A, Wang, Edina, Wallis, Christopher, Sharma, Rohit, Tie, Ash WJ, Murthy, Niren, and Blancafort, Pilar

Subjects
Biochemistry and Cell Biology, Medicinal and Biomolecular Chemistry, Chemical Sciences, Biological Sciences, Genetics, Infectious Diseases, Cancer, Breast Cancer, Women's Health, Nanotechnology, Bioengineering, Biotechnology, Gene Therapy, 5.2 Cellular and gene therapies, 2.1 Biological and endogenous factors, 5.1 Pharmaceuticals, Gene Editing, CRISPR-Cas Systems, Humans, Nanoparticles, Animals, Neoplasms, Epigenesis, Genetic, Mice, RNA, Guide, CRISPR-Cas Systems, Liposomes, Cell Line, Tumor, Lipids, CRISPR-Associated Protein 9, Genetic Therapy, Gene Transfer Techniques, CRISPR/dCas9, Lipid nanoparticle, RNA delivery, Other Chemical Sciences, Developmental Biology, Biochemistry and cell biology, Medicinal and biomolecular chemistry
Abstract

Genome editing tools, particularly the Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR) systems (e.g., CRISPR/Cas9), and their repurposing into epigenetic editing platforms, offer enormous potential as safe and customizable therapies for cancer. Specifically, various transcriptional abnormalities in human malignancies, such as silencing of tumor suppressors and ectopic re-expression of oncogenes, have been successfully targeted with virtually no off-target effects using CRISPR activation and repression systems. In these systems, the nuclease-deactivated Cas9 protein (dCas9) is fused to one or more domains inducing selective activation or repression of the targeted genes. Despite these advances, the efficient in vivo delivery of these molecules into the target cancer cells represents a critical barrier to accomplishing translation into a clinical therapy setting for cancer. Major obstacles include the large size of dCas9 fusion proteins, the necessity of multimodal delivery of protein and gRNAs, and the potential of these formulations to elicit detrimental immune responses.In this context, viral methods for delivering CRISPR face several limitations, such as the packaging capacity of the viral genome, the potential for integration of the nucleic acids into the host cells genome, and immunogenicity of viral proteins, posing serious safety concerns. The rapid development of mRNA vaccines in response to the COVID-19 pandemic has rekindled interest in mRNA-based approaches for CRISPR/dCas9 delivery. Simultaneously, due to their high loading capacity, scalability, customizable surface modification for cell targeting, and low immunogenicity, lipid nanoparticles (LNPs) have been widely explored as nonviral vectors. In this chapter, we first describe the design of optimized dCas9-effector mRNAs and gRNAs for epigenetic editing. We outline formulations of LNPs suitable for dCas9 mRNA delivery. Additionally, we provide a protocol for the co-encapsulation of the dCas9-effector mRNAs and gRNA into these LNPs, along with detailed methods for delivering these formulations to both cell lines (in vitro) and mouse models of breast cancer (in vivo).

Published
2024

2. Identifying correlates of suicide ideation during the COVID-19 pandemic: A cross-sectional analysis of 148 sociodemographic and pandemic-specific factors.

Author

Dolsen, Emily A, Nishimi, Kristen, LeWinn, Kaja Z, Byers, Amy L, Tripp, Paige, Woodward, Eleanor, Khan, Amanda J, Marx, Brian P, Borsari, Brian, Jiha, Ahmad, Neylan, Thomas C, and O'Donovan, Aoife

Subjects
Humans, Cross-Sectional Studies, Research Design, Adult, Female, Male, Pandemics, Suicidal Ideation, COVID-19, Covid-19, Depression, Machine learning, Posttraumatic stress disorder, Suicide, Prevention, Behavioral and Social Science, Mind and Body, Mental Health, Clinical Research, Mental health, Good Health and Well Being, Medical and Health Sciences, Psychology and Cognitive Sciences, Psychiatry
Abstract

The coronavirus disease 2019 (COVID-19) pandemic has created a global health crisis, with disproportionate effects on vulnerable sociodemographic groups. Although the pandemic is showing potential to increase suicide ideation (SI), we know little about which sociodemographic characteristics or COVID-19 experiences are associated with SI. Our United States-based sample (n = 837 adults [mean age = 37.1 years]) completed an online survey during August-September 2020. The study utilized an online convenience sample from a prior study, which was enriched for exposure to trauma and experiences of posttraumatic stress symptoms. We assessed SI using the Beck Depression Inventory-II. Traditional (i.e., logistic regression) and machine learning (i.e., LASSO, random forest) methods evaluated associations of 148 self-reported COVID-19 factors and sociodemographic characteristics with current SI. 234 participants (28.0%) reported SI. Twenty items were significantly associated with SI from logistic regression. Of these 20 items, LASSO identified seven sociodemographic characteristics (younger age, lower income, single relationship status, sexual orientation other than heterosexual as well as specifically identifying as bisexual, non-full-time employment, and living in a town) and six COVID-19 factors (not engaging in protective COVID-19 behaviors, receiving mental health treatment (medication and/or psychotherapy) due to the COVID-19 pandemic, socializing during the pandemic, losing one's job due to COVID-19, having a friend with COVID-19, and having an acquaintance with COVID-19) associated with SI. Random forest findings were largely consistent with LASSO. These findings may inform multidisciplinary research and intervention work focused on understanding and preventing adverse mental health outcomes such as SI during and in the aftermath of the pandemic.

Published
2022

3. A Molecularly Integrated Grade for Meningioma

Author

Driver, Joseph, Hoffman, Samantha E, Tavakol, Sherwin, Woodward, Eleanor, Maury, Eduardo A, Bhave, Varun, Greenwald, Noah F, Nassiri, Farshad, Aldape, Kenneth, Zadeh, Gelareh, Choudhury, Abrar, Vasudevan, Harish N, Magill, Stephen T, Raleigh, David R, Abedalthagafi, Malak, Aizer, Ayal A, Alexander, Brian M, Ligon, Keith L, Reardon, David A, Wen, Patrick Y, Al-Mefty, Ossama, Ligon, Azra H, Dubuc, Adrian M, Beroukhim, Rameen, Claus, Elizabeth B, Dunn, Ian F, Santagata, Sandro, and Bi, Wenya Linda

Subjects
Biomedical and Clinical Sciences, Clinical Sciences, Oncology and Carcinogenesis, Clinical Research, Brain Disorders, Brain Cancer, Rare Diseases, Human Genome, Cancer, Genetics, Good Health and Well Being, Adult, Cohort Studies, Humans, Meningeal Neoplasms, Meningioma, Neoplasm Grading, Neoplasm Recurrence, Local, Prognosis, Retrospective Studies, World Health Organization, meningioma, copy-number alterations, Neurosciences, Oncology & Carcinogenesis, Oncology and carcinogenesis
Abstract

BackgroundMeningiomas are the most common primary intracranial tumor in adults. Clinical care is currently guided by the World Health Organization (WHO) grade assigned to meningiomas, a 3-tiered grading system based on histopathology features, as well as extent of surgical resection. Clinical behavior, however, often fails to conform to the WHO grade. Additional prognostic information is needed to optimize patient management.MethodsWe evaluated whether chromosomal copy-number data improved prediction of time-to-recurrence for patients with meningioma who were treated with surgery, relative to the WHO schema. The models were developed using Cox proportional hazards, random survival forest, and gradient boosting in a discovery cohort of 527 meningioma patients and validated in 2 independent cohorts of 172 meningioma patients characterized by orthogonal genomic platforms.ResultsWe developed a 3-tiered grading scheme (Integrated Grades 1-3), which incorporated mitotic count and loss of chromosome 1p, 3p, 4, 6, 10, 14q, 18, 19, or CDKN2A. 32% of meningiomas reclassified to either a lower-risk or higher-risk Integrated Grade compared to their assigned WHO grade. The Integrated Grade more accurately identified meningioma patients at risk for recurrence, relative to the WHO grade, as determined by time-dependent area under the curve, average precision, and the Brier score.ConclusionWe propose a molecularly integrated grading scheme for meningiomas that significantly improves upon the current WHO grading system in prediction of progression-free survival. This framework can be broadly adopted by clinicians with relative ease using widely available genomic technologies and presents an advance in the care of meningioma patients.

Published
2022

4. Posttraumatic stress disorder symptoms associated with protective and risky behaviors for coronavirus disease 2019.

Author

Nishimi, Kristen, Borsari, Brian, Marx, Brian P, Tripp, Paige, Woodward, Eleanor, Rosen, Raymond C, Cohen, Beth E, Maven, David, Jiha, Ahmad, Woolley, Joshua D, Neylan, Thomas C, and O'Donovan, Aoife

Subjects
Humans, Cross-Sectional Studies, Risk-Taking, Stress Disorders, Post-Traumatic, Adult, United States, COVID-19, SARS-CoV-2, Basic Behavioral and Social Science, Brain Disorders, Post-Traumatic Stress Disorder (PTSD), Prevention, Mental Health, Behavioral and Social Science, Anxiety Disorders, Clinical Research, 2.3 Psychological, social and economic factors, Aetiology, Mental health, Good Health and Well Being, mental health, posttraumatic stress disorder, protective behaviors, risky behaviors, Medical and Health Sciences, Education, Psychology and Cognitive Sciences, Public Health
Abstract

ObjectivePsychiatric disorders increase risk for contracting coronavirus disease 2019 (COVID-19), but we know little about relationships between psychiatric symptoms and COVID-19 risky and protective behaviors. Posttraumatic stress disorder (PTSD) has been associated with increased propensity to engage in risky behaviors, but may also be associated with increased COVID-19 protective behaviors due to increased threat sensitivity and social isolation.MethodWe examined associations of PTSD symptoms with COVID-19-related protective and risky behaviors using data from a cross-sectional online United States study among 845 US adults in August through September 2020. PTSD symptoms (PTSD Checklist-5), sociodemographics, COVID-19-related experiences and vulnerabilities, and past 30-day engagement in 10 protective and eight risky behaviors for COVID-19 were assessed via self-report. We examined associations between PTSD symptoms and COVID-19 protective and risky behaviors with linear regressions, adjusting for covariates.ResultsProbable PTSD and higher PTSD symptom severity were associated with greater engagement in protective behaviors, but also greater engagement in risky behaviors. Associations were only slightly attenuated by adjustment for COVID-19 exposures and perceived likelihood and severity of COVID-19. Associations varied by PTSD clusters: intrusions and arousal were associated with both more protective and more risky behaviors, whereas negative cognitions or mood was associated only with more risky, and avoidance only with more protective, behaviors.ConclusionHigher PTSD symptoms were associated with engagement in more protective but also more risky behaviors for COVID-19. Mental health should be considered in the design of public health campaigns dedicated to limiting infectious disease spread. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

Published
2022

5. Clusters of COVID-19 protective and risky behaviors and their associations with pandemic, socio-demographic, and mental health factors in the United States.

Author

Nishimi, Kristen, Borsari, Brian, Marx, Brian P, Rosen, Raymond C, Cohen, Beth E, Woodward, Eleanor, Maven, David, Tripp, Paige, Jiha, Ahmad, Woolley, Joshua D, Neylan, Thomas C, and O'Donovan, Aoife

Subjects
ANOVA, analysis of variance, AWE, Approximate Weight of Evidence Criterion, AvePP, average posterior class probability, BF, Bayes Factors, BIC, Bayesian Information Criterion, COVID-19, COVID-19, coronavirus disease 2019, DASS, Depression Anxiety Stress Scale, LCA, latent class analysis, Latent class analysis, Mental health, OCC, odds of correct classification, PTSD Checklist-5, PCL-5, PTSD, posttraumatic stress disorder, Protective behaviors, Risky behaviors, cAIC, consistent Akaike's Information Criterion, mcaP, modal class assignment proportion, Infectious Diseases, Brain Disorders, Mental Health, Behavioral and Social Science, Depression, Prevention, 2.3 Psychological, social and economic factors, Aetiology, Good Health and Well Being, Public Health and Health Services
Abstract

Individual behaviors are critical for preventing the spread of coronavirus disease 2019 (COVID-19) infection. Given that both protective and risky behaviors influence risk of infection, it is critical that we understand how such behaviors cluster together and in whom. Using a data-driven approach, we identified clusters of COVID-19-related protective and risky behaviors and examined associations with socio-demographic, pandemic, and mental health factors. Data came from a cross-sectional online U.S. nationwide study of 832 adults with high levels of pre-pandemic trauma. Latent class analysis was performed with ten protective (e.g., washing hands, wearing masks) and eight risky (e.g., attending indoor restaurants, taking a flight) behaviors for COVID-19. Then, we examined distributions of socio-demographic and pandemic factors across behavior classes using ANOVA or Chi-square tests, and associations between mental health factors (depressive, anxiety, posttraumatic stress symptoms) and behavior classes using multinomial logistic regression. We identified four classes, including three classes with relatively low risky but high (28.8%), moderate (33.5%) and minimal (25.5%) protective behaviors and one high risky behaviors class with associated moderate protective behaviors (12.1%). Age, sexual orientation, political preference, and most pandemic factors differed significantly across behavior classes. Anxiety and posttraumatic stress symptoms, but not depression, were higher in the High Risk, but also Highly and Moderately Protective classes, relative to Minimally Protective. Prevention and intervention efforts should examine constellations of protective and risky behaviors to comprehensively understand risk, and consider current anxiety and posttraumatic stress symptoms as potential risk indicators.

Published
2022

9. Honeybee venom and melittin suppress growth factor receptor activation in HER2-enriched and triple-negative breast cancer.

Author

Duffy, Ciara, Sorolla, Anabel, Wang, Edina, Golden, Emily, Woodward, Eleanor, Davern, Kathleen, Ho, Diwei, Johnstone, Elizabeth, Pfleger, Kevin, Redfern, Andrew, Iyer, K Swaminathan, Baer, Boris, and Blancafort, Pilar

Abstract

Despite decades of study, the molecular mechanisms and selectivity of the biomolecular components of honeybee (Apis mellifera) venom as anticancer agents remain largely unknown. Here, we demonstrate that honeybee venom and its major component melittin potently induce cell death, particularly in the aggressive triple-negative and HER2-enriched breast cancer subtypes. Honeybee venom and melittin suppress the activation of EGFR and HER2 by interfering with the phosphorylation of these receptors in the plasma membrane of breast carcinoma cells. Mutational studies reveal that a positively charged C-terminal melittin sequence mediates plasma membrane interaction and anticancer activity. Engineering of an RGD motif further enhances targeting of melittin to malignant cells with minimal toxicity to normal cells. Lastly, administration of melittin enhances the effect of docetaxel in suppressing breast tumor growth in an allograft model. Our work unveils a molecular mechanism underpinning the anticancer selectivity of melittin, and outlines treatment strategies to target aggressive breast cancers.

Published
2020

12. Histone H3.3G34-Mutant Interneuron Progenitors Co-opt PDGFRA for Gliomagenesis

Author

Chen, Carol C.L., Deshmukh, Shriya, Jessa, Selin, Hadjadj, Djihad, Lisi, Véronique, Andrade, Augusto Faria, Faury, Damien, Jawhar, Wajih, Dali, Rola, Suzuki, Hiromichi, Pathania, Manav, A, Deli, Dubois, Frank, Woodward, Eleanor, Hébert, Steven, Coutelier, Marie, Karamchandani, Jason, Albrecht, Steffen, Brandner, Sebastian, De Jay, Nicolas, Gayden, Tenzin, Bajic, Andrea, Harutyunyan, Ashot S., Marchione, Dylan M., Mikael, Leonie G., Juretic, Nikoleta, Zeinieh, Michele, Russo, Caterina, Maestro, Nicola, Bassenden, Angelia V., Hauser, Peter, Virga, József, Bognar, Laszlo, Klekner, Almos, Zapotocky, Michal, Vicha, Ales, Krskova, Lenka, Vanova, Katerina, Zamecnik, Josef, Sumerauer, David, Ekert, Paul G., Ziegler, David S., Ellezam, Benjamin, Filbin, Mariella G., Blanchette, Mathieu, Hansford, Jordan R., Khuong-Quang, Dong-Anh, Berghuis, Albert M., Weil, Alexander G., Garcia, Benjamin A., Garzia, Livia, Mack, Stephen C., Beroukhim, Rameen, Ligon, Keith L., Taylor, Michael D., Bandopadhayay, Pratiti, Kramm, Christoph, Pfister, Stefan M., Korshunov, Andrey, Sturm, Dominik, Jones, David T.W., Salomoni, Paolo, Kleinman, Claudia L., and Jabado, Nada

Published
2020
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14. Supplementary Table S3 from Clinical and Genomic Predictors of Adverse Events in Newly Diagnosed Glioblastoma

Author

Lim-Fat, Mary Jane, primary, Iorgulescu, J. Bryan, primary, Rahman, Rifaquat, primary, Bhave, Varun, primary, Muzikansky, Alona, primary, Woodward, Eleanor, primary, Whorral, Sydney, primary, Allen, Marie, primary, Touat, Mehdi, primary, Li, Xiaomei, primary, Xy, Gongwen, primary, Patel, Jay, primary, Gerstner, Elizabeth R., primary, Kalpathy-Cramer, Jayashree, primary, Youssef, Gilbert, primary, Chukwueke, Ugonma, primary, McFaline-Figueroa, J. Ricardo, primary, Nayak, Lakshmi, primary, Lee, Eudocia Q., primary, Reardon, David A., primary, Beroukhim, Rameen, primary, Huang, Raymond Y., primary, Bi, Wenya Linda, primary, Ligon, Keith L., primary, and Wen, Patrick Y., primary

Published
2024
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15. Supplementary Figure S1 from Clinical and Genomic Predictors of Adverse Events in Newly Diagnosed Glioblastoma

Author

Lim-Fat, Mary Jane, primary, Iorgulescu, J. Bryan, primary, Rahman, Rifaquat, primary, Bhave, Varun, primary, Muzikansky, Alona, primary, Woodward, Eleanor, primary, Whorral, Sydney, primary, Allen, Marie, primary, Touat, Mehdi, primary, Li, Xiaomei, primary, Xy, Gongwen, primary, Patel, Jay, primary, Gerstner, Elizabeth R., primary, Kalpathy-Cramer, Jayashree, primary, Youssef, Gilbert, primary, Chukwueke, Ugonma, primary, McFaline-Figueroa, J. Ricardo, primary, Nayak, Lakshmi, primary, Lee, Eudocia Q., primary, Reardon, David A., primary, Beroukhim, Rameen, primary, Huang, Raymond Y., primary, Bi, Wenya Linda, primary, Ligon, Keith L., primary, and Wen, Patrick Y., primary

Published
2024
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16. Rip currents in the UK : incident analysis, public awareness, and education

Author

Woodward, Eleanor Molly

Subjects
363.1, Rip Currents, Beach Safety, Beach Lifeguards, Public Education, Questionnaires
Abstract

Rip currents present a severe hazard to water users worldwide, resulting in over 100 drownings and thousands of lifeguard rescues annually. This thesis examines the demographics of who is effected by rip currents in the UK, what activity they are undertaking, when and where incidents occur, how much the public know, what people have experienced, and how best to educate them. Analysis of 7909 rip current lifeguard rescues (16777 people) across the UK between 2006-2013 highlighted the most at risk group, and subsequent target audience for education, to be male teenagers aged between 13-17 years old (n=2906, 17%). Geographically, the highest incidents occurred on the beaches in the Southwest of England (n=6911, 87%). Incidents mostly occurred outside of lifeguard flagged areas (n=4302, 54%) and mainly involved those using bodyboards (n=5290, 52%). Through the analysis of 407 public beach-based rip current and beach safety questionnaires, it was established that beach users have a poor understanding of rip currents (n=263, 65%) but a good perception of the beach safety flags (n=389, 96%). People with greater knowledge were typically educated by a lifeguard, enter the sea more frequently or have been caught in rip currents themselves. The experiences of 553 people caught in rip currents were analysed using an online questionnaire. The gender split was 69% male (n= 382) to 31% female (n= 171), indicating that males are caught in rip currents more than females. Swimming directly to shore against the rip followed an initial panic (n=108, 34%) for most people caught in a rip. Swimming parallel to the beach was the most remembered, advised, utilised, and promoted safety message. Respondents advocated the use of lifeguards to disseminate rip current safety messages. A new and unique rip current education programme was developed from the synthesis of these results. A lifeguard delivered a pilot programme to 185 teenagers in three schools and two community groups in the Southwest of England. This interactive pilot consisted of exercises using videos, photographs, news reports, and a swimming machine. Levels of rip current knowledge were evaluated before and after, and at regular intervals, to assess knowledge retention. The short-term effects after 3 months were positive, showing statistically significant (p < 0.0005) improvements in mean knowledge levels. This thesis provides a new contribution to the expanding field of social and behavioural rip current research. The development of a unique rip current education programme presents an alternative method for increasing public awareness, and supports the worldwide prevention of rip current incidents and fatalities.

Published
2015

17. The oncogene AAMDC links PI3K-AKT-mTOR signaling with metabolic reprograming in estrogen receptor-positive breast cancer

Author

Golden, Emily, Rashwan, Rabab, Woodward, Eleanor A., Sgro, Agustin, Wang, Edina, Sorolla, Anabel, Waryah, Charlene, Tie, Wan Jun, Cuyàs, Elisabet, Ratajska, Magdalena, Kardaś, Iwona, Kozlowski, Piotr, Johnstone, Elizabeth K. M., See, Heng B., Duffy, Ciara, Parry, Jeremy, Lagerborg, Kim A., Czapiewski, Piotr, Menendez, Javier A., Gorczyński, Adam, Wasag, Bartosz, Pfleger, Kevin D. G., Curtis, Christina, Lee, Bum-Kyu, Kim, Jonghwan, Cursons, Joseph, Pavlos, Nathan J., Biernat, Wojciech, Jain, Mohit, Woo, Andrew J., Redfern, Andrew, and Blancafort, Pilar

Published
2021
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18. Clinical and Genomic Predictors of Adverse Events in Newly Diagnosed Glioblastoma

Author

Lim-Fat, Mary Jane, primary, Iorgulescu, J. Bryan, additional, Rahman, Rifaquat, additional, Bhave, Varun, additional, Muzikansky, Alona, additional, Woodward, Eleanor, additional, Whorral, Sydney, additional, Allen, Marie, additional, Touat, Mehdi, additional, Li, Xiaomei, additional, Xy, Gongwen, additional, Patel, Jay, additional, Gerstner, Elizabeth R., additional, Kalpathy-Cramer, Jayashree, additional, Youssef, Gilbert, additional, Chukwueke, Ugonma, additional, McFaline-Figueroa, J. Ricardo, additional, Nayak, Lakshmi, additional, Lee, Eudocia Q., additional, Reardon, David A., additional, Beroukhim, Rameen, additional, Huang, Raymond Y., additional, Bi, Wenya Linda, additional, Ligon, Keith L., additional, and Wen, Patrick Y., additional

Published
2024
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19. PATH-12. CONTEMPORARY MOLECULAR LANDSCAPE, SURVIVAL, AND PROGNOSTIC FACTORS IN OVER 4,000 GLIOMAS

Author

Ghosh, Hia, primary, Patel, Ruchit, additional, Woodward, Eleanor, additional, Greenwald, Noah, additional, Bhave, Varun, additional, Maury, Eduardo, additional, Hoffman, Samantha, additional, Li, Yvonne, additional, Gupta, Hersh, additional, Spurr, Liam, additional, Touat, Mehdi, additional, Dubois, Frank, additional, Cherniack, Andrew, additional, Cioffi, Gino, additional, Antonio Chiocca, E, additional, Reardon, David, additional, Wen, Patrick, additional, Meredith, David, additional, Santagata, Sandro, additional, Barnholtz-Sloan, Jill, additional, Ligon, Keith, additional, Beroukhim, Rameen, additional, and Bi, Wenya Linda, additional

Published
2023
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20. The use of gene expression profiling to identify novel minimal residual disease markers (MRD) in acute myeloid leukaemia (AML)

Author

Woodward, Eleanor

Subjects
616.99, R Medicine (General)
Abstract

Acute myeloid leukaemia (AML) is a heterogeneous disorder characterised by the accumulation of immature haematopoietic cells blocked at various stages of differentiation. Despite improved survival rates over the past decade, relapse occurs in approximately 70% patients undergoing chemotherapy. A potential reason for this is that current clinical protocols do not take account of the level of residual disease present at remission. Therefore, one strategy to reduce relapse rates is to monitor minimal residual disease and continue to treat until the patient is minimal residual disease negative. Current minimal residual disease markers are available for patients with characterised fusion genes but approximately 50% of patients have no detectable chromosomal aberration and therefore are without markers. Gene expression profiling is a powerful tool for disease classification, prognosis and therapeutic predictions. This study aimed to investigate the use gene expression profiling to identify novel minimal residual disease markers for specific AML sub-groups. Patient diagnostic samples were profiled to identify genes specific to AML patients with a favourable translocation in order to establish the "proof-of-principle". Several genes identified were followed in patient diagnostic and follow- up samples and compared to the markers currently used. Continuing with normal karyotype AML, genes were identified as specific to this sub-group. Several homeobox (HOX) genes and the Wilms' tumour (WT1) gene were identified and their MRD levels followed in diagnostic and follow-up samples. Only WT1 identified as specific to normal karyotype AML met the necessary criteria to be an MRD marker. Although the majority of genes selected from the GEP in this study proved unsuitable as markers, the identification and validation of a marker already used for MRD monitoring, WT1, demonstrates the ability of gene expression profiling to identify potential minimal residual disease markers in normal karyotype AML.

Published
2010

21. Molecular Landscape and Contemporary Prognostic Signatures of Gliomas

Author

Ghosh, Hia S., primary, Patel, Ruchit V., additional, Woodward, Eleanor, additional, Greenwald, Noah F., additional, Bhave, Varun M., additional, Maury, Eduardo A., additional, Cello, Gregory, additional, Hoffman, Samantha E., additional, Li, Yvonne, additional, Gupta, Hersh, additional, Spurr, Liam F., additional, Vogelzang, Jayne, additional, Touat, Mehdi, additional, Dubois, Frank, additional, Cherniack, Andrew D., additional, Guo, Xiaopeng, additional, Tavakol, Sherwin, additional, Cioffi, Gino, additional, Lindeman, Neal I., additional, Ligon, Azra H., additional, Chiocca, E. Antonio, additional, Reardon, David A., additional, Wen, Patrick Y., additional, Meredith, David, additional, Santagata, Sandro, additional, Barnholtz-Sloan, Jill S., additional, Ligon, Keith L., additional, Beroukhim, Rameen, additional, and Bi, Wenya Linda, additional

Published
2023
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23. Synthetic Epigenetic Reprogramming of Mesenchymal to Epithelial States Using the CRISPR/dCas9 Platform in Triple Negative Breast Cancer

Author

Waryah, Charlene, primary, Cursons, Joseph, additional, Foroutan, Momeneh, additional, Pflueger, Christian, additional, Wang, Edina, additional, Molania, Ramyar, additional, Woodward, Eleanor, additional, Sorolla, Anabel, additional, Wallis, Christopher, additional, Moses, Colette, additional, Glas, Irina, additional, Magalhães, Leandro, additional, Thompson, Erik W., additional, Fearnley, Liam G., additional, Chaffer, Christine L., additional, Davis, Melissa, additional, Papenfuss, Anthony T., additional, Redfern, Andrew, additional, Lister, Ryan, additional, Esteller, Manel, additional, and Blancafort, Pilar, additional

Published
2023
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27. Additional file 1 of Epigenetic reactivation of tumor suppressor genes with CRISPRa technologies as precision therapy for hepatocellular carcinoma

Author

Sgro, Agustin, Cursons, Joseph, Waryah, Charlene, Woodward, Eleanor A., Foroutan, Momeneh, Lyu, Ruqian, Yeoh, George C. T., Leedman, Peter J., and Blancafort, Pilar

Abstract

Additional file 1: Figure S1. Related to Fig. 1. A Scatter plots showing the associations between different integrated-data cluster (iClust) scores of individual tumor samples. Tumor samples with an iClust value specified in the original TCGA manuscript are shown (dark blue, dark orange, and dark green), together with inferred iClust annotations (light blue, light orange, and light green) obtained through a k-nearest neighbors’ classification (further details given in “Methods”).

Published
2023
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28. Additional file 7 of Epigenetic reactivation of tumor suppressor genes with CRISPRa technologies as precision therapy for hepatocellular carcinoma

Author

Sgro, Agustin, Cursons, Joseph, Waryah, Charlene, Woodward, Eleanor A., Foroutan, Momeneh, Lyu, Ruqian, Yeoh, George C. T., Leedman, Peter J., and Blancafort, Pilar

Abstract

Additional file 7: Figure S6. Related to Fig. 5. Transcriptional reactivation of HHIP gene by novel CRISPRa combinations does not correlate with changes in promoter DNA methylation in transiently transfected Hep3B cells. A Fold change in HHIP mRNA expression evaluated by qRT-PCR 96 h after transient transfection in Hep3B cells. Cells were transfected with SpdCas9-VPR and MS2-MCP-p65-HSF1, or with SpdCas9-TET1-CD and MS2-MCP-p65-HSF1, along with gRNA G4 or with no gRNA (NO G) as control. Relative gene expression was normalized and compared to cells transfected with empty vector control (EV) for statistical analysis. Data presented as means ± SEM (n = 3), and P-values were determined by unpaired t-test (***P = 0.0001, ****P < 0.0001). B Heatmap showing HHIP promoter DNA methylation in Hep3B cells transiently transfected with the novel CRISPRa combinations. Data from Illumina Infinium 850 K methylation EPIC microarrays. For each probe (listed at left), the difference in β-value from the average is shown (at left; green-purple color map) together with the average probe β-value (at center; blue-yellow color map), and the adjusted P-value for differential methylation between gRNA G4 and NO G for the two combinations tested (at right; white-purple color map).

Published
2023
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29. Additional file 8 of Epigenetic reactivation of tumor suppressor genes with CRISPRa technologies as precision therapy for hepatocellular carcinoma

Author

Sgro, Agustin, Cursons, Joseph, Waryah, Charlene, Woodward, Eleanor A., Foroutan, Momeneh, Lyu, Ruqian, Yeoh, George C. T., Leedman, Peter J., and Blancafort, Pilar

Abstract

Additional file 8: Figure S7. Related to Fig. 5. Lentiviral transduction of SpdCas9-TET1-CD or SpdCas9-VPR targeting HHIP or MT1M genes in Hep3B cells. A Schematic representation of the “all-in-one” lentiviral vectors, SpdCas9-TET1-CD and SpdCas9-VPR, for the constitutive co-expression of a gRNA and TET1-CD or VPR, C-terminally fused to SpdCas9. B Fold change in HHIP mRNA expression assessed by qRT-PCR at 18, 30, and 40 days in Hep3B cells constitutively co-expressing SpdCas9-TET1-CD and the combination of four gRNAs (MIX 4G) targeting HHIP promoter. C Fold change in MT1M mRNA expression assessed by qRT-PCR at 20 days in Hep3B cells lentivirally co-transduced with SpdCas9-TET1-CD and individual gRNAs (G1, G2, G3, and G4) or the MIX 4G; or with SpdCas9-VPR and the most potent gRNA (G1). Data presented as means ± SEM (n = 3), compared to SpdCas9-TET1-CD NO G, and P-values were determined by two-way ANOVA with Šídák's multiple comparisons test for panel (B), and by two-way ANOVA with Dunnett's multiple comparisons test for panel (C) (****P < 0.0001). SpdCas9 Streptococcus pyogenes deactivated Cas9 protein adopted for epigenome engineering, TET1-CD Ten-Eleven Translocation methylcytosine dioxygenase 1-catalytic domain, VPR VP64, p65, Rta, hU6 RNA polymerase III promoter for human U6 snRNA, hUbC human ubiquitin C promoter, 3xFLAG three tandem FLAG® epitope tags, followed by an enterokinase cleavage site, SV40NLS nuclear localization signal of SV40 (simian virus 40) large T antigen, T2A 2A peptide from Thosea asigna virus capsid protein, cleavable linker, PuroR puromycin N-acetyltransferase gene that confers resistance to puromycin, MIX 4G combination of four gRNAs, ns not significant.

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2023
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30. Additional file 6 of Epigenetic reactivation of tumor suppressor genes with CRISPRa technologies as precision therapy for hepatocellular carcinoma

Author

Sgro, Agustin, Cursons, Joseph, Waryah, Charlene, Woodward, Eleanor A., Foroutan, Momeneh, Lyu, Ruqian, Yeoh, George C. T., Leedman, Peter J., and Blancafort, Pilar

Abstract

Additional file 6: Figure S5. Related to Fig. 5. Tiling the promoter of MT1M and TTC36 tumor suppressor genes with a CRISPRa toolbox in Hep3B HCC cells. A-B Fold change in MT1M (A) and TTC36 (B) mRNA expression evaluated by qRT-PCR 72 h after transient transfection in Hep3B cells. Cells were transfected with combinations of CRISPRa along with a mix of four gRNAs (MIX 4G), or with no gRNA (NO G) as control. Relative gene expression was normalized and compared to cells transfected with empty vector control (EV) for statistical analysis. Data presented as means ± SEM (n = 3), and P-values were determined by one-ANOVA with Dunnett's multiple comparisons test (****P < 0.0001). SpdCas9 Streptococcus pyogenes deactivated Cas9 protein adopted for epigenome engineering, VPR VP64, p65, Rta, MS2 RNA aptamer, MCP MS2-coat protein, HSF1 heat shock factor 1, TET1-CD Ten-Eleven Translocation methylcytosine dioxygenase 1-catalytic domain, MIX 4G combination of four gRNAs.

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2023
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31. Additional file 5 of Epigenetic reactivation of tumor suppressor genes with CRISPRa technologies as precision therapy for hepatocellular carcinoma

Author

Sgro, Agustin, Cursons, Joseph, Waryah, Charlene, Woodward, Eleanor A., Foroutan, Momeneh, Lyu, Ruqian, Yeoh, George C. T., Leedman, Peter J., and Blancafort, Pilar

Abstract

Additional file 5: Figure S4 (part 2). Related to Figs. 3–7. CRISPRa is highly specific in hit-and-run and lentiviral approaches in HCC cell lines. A-K The potential off-target genes (MMP11, MOCOS, PIR, SEMA5A, TMEM14C, HRH1, NACC2, NONO, PPA1, RBM39, NKAIN3, and ABCC3) found in proximity to genomic regulatory regions for the most potent gRNAs utilized were assessed by qRT-PCR 48 h post-transfection, employing SpdCas9-VPR and MS2-MCP-p65-HSF1 system in HuH-7 (A), (B), (C), (E) and Hep3B cells (F), (H), (J); and in stable Hep3B cell lines expressing SpdCas9-VPR (D), (G), (I), (K). Relative gene expression, expressed as fold change, was normalized to cells transfected with empty vector control (EV) or to cells transduced with SpdCas9-VPR NO G, and compared to either EV or NO G conditions for statistical analysis. Data presented as means ± SEM (n = 3), and P-values were determined by two-way ANOVA with Dunnett's multiple comparisons test for panels (A), (B), (C), (E), (F), (H), and (J) (A: ***P = 0.0001; B, C, E, F, and H: ****P < 0.0001; J: ***P = 0.0003, ****P < 0.0001); or by two-way ANOVA with Šídák's multiple comparisons test for panels D, G, I, and K (****P < 0.0001).

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2023
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32. Additional file 4 of Epigenetic reactivation of tumor suppressor genes with CRISPRa technologies as precision therapy for hepatocellular carcinoma

Author

Sgro, Agustin, Cursons, Joseph, Waryah, Charlene, Woodward, Eleanor A., Foroutan, Momeneh, Lyu, Ruqian, Yeoh, George C. T., Leedman, Peter J., and Blancafort, Pilar

Abstract

Additional file 4: Figure S4 (part 1). Related to Figs. 3–7. A Off-target analysis of the ten TSGs reactivated in this study, using the most potent gRNAs. The potential off-target genes (MMP11, MOCOS, PIR, SEMA5A, TMEM14C, HRH1, NACC2, NONO, PPA1, RBM39, NKAIN3, and ABCC3) were found in proximity to genomic regulatory regions.

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2023
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33. Additional file 9 of Epigenetic reactivation of tumor suppressor genes with CRISPRa technologies as precision therapy for hepatocellular carcinoma

Author

Sgro, Agustin, Cursons, Joseph, Waryah, Charlene, Woodward, Eleanor A., Foroutan, Momeneh, Lyu, Ruqian, Yeoh, George C. T., Leedman, Peter J., and Blancafort, Pilar

Abstract

Additional file 9: Figure S8. Related to Fig. 7. Phenotypic reprogramming in Hep3B HCC cells lentivirally transduced with SpdCas9-VPR targeting and upregulating MT1M with G1, PZP with G2, TTC36 with G3, or with NO G as control. A-C Cell viability determined using a luminescence assay (CellTiter-Glo®). Data shown as fold change compared to SpdCas9-VPR NO G at 24, 48, and 72 h, presented as means ± SEM (n = 3), and P-values were determined by unpaired t-test with Welch's correction (From left to right: (A), ***P = 0.0001, **P = 0.0056; (B), **P = 0.0024, **P = 0.0011; and (C), ****P < 0.0001, *P = 0.0310). D Cell migration assessed by the Boyden chamber assay. Data normalized to SpdCas9-VPR NO G, presented as means ± SEM (n = 3), and P-values were determined by unpaired t-test. ns not significant.

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2023
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34. Search in diphoton and dielectron final states for displaced production of Higgs or $Z$ bosons with the ATLAS detector in $\sqrt{s} = 13$ TeV $pp$ collisions

Author

Aad, Georges, Abbott, Braden Keim, Abbott, Dale, Abeling, Kira, Abidi, Haider, Aboulhorma, Asmaa, Abramowicz, Halina, Abreu, Henso, Abulaiti, Yiming, Abusleme, Angel, Acharya, Bobby Samir, Achkar, Baida, Adam Bourdarios, Claire, Adamczyk, Leszek, Adamek, Lukas, Addepalli, Sagar, Adelman, Jahred, Adiguzel, Aytul, Adorni Braccesi Chiassi, Sofia, Adye, Tim, Affolder, Tony, Afik, Yoav, Agaras, Merve Nazlim, Agarwala, Jinky, Aggarwal, Anamika, Agheorghiesei, Catalin, Aguilar Saavedra, Juan Antonio, Ahmad, Ammara, Ahmadov, Faig, Ahmed, Waleed Syed, Ahuja, Sudha, Ai, Xiaocong, Aielli, Giulio, Aizenberg, Iakov, Akbiyik, Melike, Akesson, Torsten, Akimov, Andrei, Al Khoury, Konie, Alberghi, Gian Luigi, Albert, Justin, Albicocco, Pietro, Alderweireldt, Sara, Aleksa, Martin, Alexandrov, Igor, Alexa, Calin, Alexopoulos, Theodoros, Alfonsi, Alice, Alfonsi, Fabrizio, Alhroob, Muhammad, Ali, Babar, Ali, Shahzad, Aliev, Malik, Alimonti, Gianluca, Alkakhi, Wael, Allaire, Corentin, Allbrooke, Benedict, Allport, Philip Patrick, Aloisio, Alberto, Alonso, Francisco, Alpigiani, Cristiano, Alunno Camelia, Elio, Alvarez Estevez, Manuel, Alviggi, Mariagrazia, Aly, Mohamed, Do Amaral Coutinho, Yara, Ambler, Alessandro, Amelung, Christoph, Amerl, Maximilian, Ames, Christoph, Amidei, Dante, Amor dos Santos, Susana Patricia, Amoroso, Simone, Amos, Kieran Robert, Ananiev, Viktor, Anastopoulos, Christos, Andeen, Timothy Robert, Anders, John Kenneth, Andrean, Stefio Yosse, Andreazza, Attilio, Angelidakis, Stylianos, Angerami, Aaron, Anisenkov, Alexey, Annovi, Alberto, Antel, Claire, Anthony, Matthew Thomas, Antipov, Egor, Antonelli, Mario, Antrim, Daniel Joseph, Anulli, Fabio, Aoki, Masato, Aoki, Takumi, Aparisi Pozo, Javier Alberto, Aparo, Marco, Aperio Bella, Ludovica, Appelt, Christian, Aranzabal Barrio, Nordin, Araujo Ferraz, Victor, Arcangeletti, Chiara, Arce, Ayana Tamu, Arena, Eloisa, Arguin, Jean-Francois, Argyropoulos, Spyros, Arling, Jan-Hendrik, Armbruster, Aaron James, Arnaez, Olivier, Arnold, Hannah, Arrubarrena Tame, Zulit Paola, Artoni, Giacomo, Asada, Haruka, Asai, Kanae, Asai, Shoji, Asbah, Nedaa Alexandra, Assahsah, Jihad, Assamagan, Ketevi Adikle, Astalos, Robert, Atkin, Ryan Justin, Atkinson, Markus Julian, Atlay, Naim Bora, Atmani, Hicham, Atmasiddha, Prachi, Augsten, Kamil, Auricchio, Silvia, Auriol, Adrien, Austrup, Volker Andreas, Avner, Gal, Avolio, Giuseppe, Axiotis, Konstantinos, Ayoub, Mohamad Kassem, Azuelos, Georges, Babal, Dominik, Bachacou, Henri, Bachas, Konstantinos, Bachiu, Alexander, Backman, Karl Filip, Badea, Anthony, Bagnaia, Paolo, Bahmani, Marzieh, Bailey, Adam, Bailey, Virginia, Baines, John, Bakalis, Christos, Baker, Keith, Bakker, Pepijn Johannes, Bakos, Evelin, Bakshi Gupta, Debottam, Balaji, Shyam, Balasubramanian, Rahul, Baldin, Evgenii, Balek, Petr, Ballabene, Eric, Balli, Fabrice, Baltes, Lisa Marie, Balunas, William Keaton, Balz, Johannes, Banas, Elzbieta, Bandieramonte, Marilena, Bandyopadhyay, Anjishnu, Bansal, Shubham, Barak, Liron, Barberio, Elisabetta, Barberis, Dario, Barbero, Marlon Benoit, Barbour, Gregory, Barends, Kevin Nicholas, Barillari, Teresa, Barisits, Martin, Barklow, Tim, Barnett, Michael, Baron, Petr, Baron, Diego, Baroncelli, Toni, Barone, Gaetano, Barr, Alan, Barranco Navarro, Laura, Barreiro Alonso, Fernando, Barreiro Guimaraes da Costa, Joao, Barron, Uriel, Barros, Maura, Barsov, Sergey, Bartels, Falk, Bartoldus, Rainer, Barton, Adam Edward, Bartos, Pavol, Basalaev, Artem, Basan, Alexander, Baselga Bacardit, Marta, Bashta, Inna, Bassalat, Ahmed, Basso, Matthew Joseph, Basson, Candice Ruth, Bates, Richard, Batlamous, Souad, Batley, Richard, Batool, Binish, Battaglia, Marco, Battulga, Daariimaa, Bauce, Matteo, Bauer, Patrick, Bayirli, Arif, Beacham, James, Beau, Tristan, Beauchemin, Pierre-Hugues, Becherer, Fabian, Bechtle, Philip, Beck, Hans Peter, Becker, Kathrin, Beddall, Andrew, Bednyakov, Vadim, Bee, Chris, Beemster, Lars, Beermann, Thomas, Begalli, Marcia, Begel, Michael, Behera, Arabinda, Behr, Janna Katharina, Beirao da Cruz E Silva, Cristovao, Beirer, Joshua Falco, Beisiegel, Florian, Belfkir, Mohamed, Bella, Gideon, Bellagamba, Lorenzo, Bellerive, Alain, Bellos, Panagiotis, Beloborodov, Konstantin, Belotskiy, Konstantin, Belyaev, Nikita, Benchekroun, Driss, Bendebba, Fatima, Benhammou, Yan, Benjamin, Doug, Benoit, Mathieu, Bensinger, Jim, Bentvelsen, Stan, Beresford, Lydia Audrey, Beretta, Matteo Mario, Berge, David, Bergeaas Kuutmann, Elin, Berger, Nicolas, Bergmann, Benedikt Ludwig, Beringer, Juerg, Berlendis, Simon, Bernardi, Gregorio, Bernius, Catrin, Bernlochner, Florian Urs, Berry, Tracey, Berta, Peter, Berthold, Anne-Sophie, Bertram, Iain, Bethke, Siegfried, Betti, Alessandra, Bevan, Adrian, Bhamjee, Muaaz, Bhatta, Somadutta, Bhattacharya, Deb Sankar, Bhattarai, Prajita, Bhopatkar, Vallary Shashikant, Bi, Ran, Bianchi, Riccardo Maria, Biebel, Otmar, Bielski, Rafal, Biglietti, Michela, Billoud, Thomas, Bindi, Marcello, Bingul, Ahmet, Bini, Cesare, Biondi, Silvia, Biondini, Alessandro, Birch-Sykes, Callum Jacob, Bird, Gareth Adam, Birman, Mattias, Bisanz, Tobias, Bisceglie, Emanuele, Biswas, Diptaparna, Bitadze, Alexander, Bjoerke, Kristian, Bloch, Ingo, Blocker, Craig, Blue, Andrew James, Blumenschein, Ulla, Blumenthal, Julian, Bobbink, Gerjan, Bobrovnikov, Viktor, Boehler, Michael, Bogavac, Danijela, Bogdanchikov, Alexander, Bohm, Christian, Boisvert, Veronique, Bokan, Petar, Bold, Tomasz, Bomben, Marco, Bona, Marcella, Boonekamp, Maarten, Booth, Callum Dale, Borbely, Albert Gyorgy, Borecka-Bielska, Hanna Maria, Borgna, Lucas Santiago, Borissov, Guennadi, Bortoletto, Daniela, Boscherini, Davide, Fernandez-Bosman, Martine, Bossio, Jonathan, Bouaouda, Khalil, Bouchhar, Naseem, Boudreau, Joseph, Bouhova-Thacker, Eva, Boumediene, Djamel Eddine, Bouquet, Romain, Boveia, Antonio, Boyd, Jamie, Boye, Diallo, Boyko, Igor, Bracinik, Juraj, Brahimi, Nihal, Brandt, Gerhard Immanuel, Brandt, Oleg, Braren, Frued Erik, Brau, Benjamin Paul, Brau, Jim, Brendlinger, Kurt, Schimmel Brener, Roy, Brenner, Lydia, Brenner, Richard, Bressler, Shikma, Brickwedde, Bernard, Britton, David, Britzger, Daniel Andreas, Brock, Ian, Brooijmans, Gustaaf, Brooks, William King, Brost, Elizabeth, Bruckler, Tim Lukas, Bruckman de Renstrom, Pawel, Bruers, Ben, Bruncko, Dusan, Bruni, Alessia, Bruni, Graziano, Bruschi, Marco, Bruscino, Nello, Bryngemark, Lene Kristian, Buanes, Trygve, Buat, Quentin, Buchholz, Peter, Buckley, Andy, Budagov, Ioulian, Bugge, Magnar Kopangen, Bulekov, Oleg, Bullard, Brendon, Burdin, Sergey, Burgard, Carsten, Burger, Angela Maria, Burghgrave, Blake Oliver, Burr, Jon, Burton, Charles, Burzynski, Jackson Carl, Busch, Elena Laura, Buescher, Volker, Bussey, Peter John, Butler, John Mark, Buttar, Craig Macleod, Butterworth, Jonathan, Buttinger, Will, Buxo Vazquez, Carlos Josue, Buzykaev, Alexey, Cabras, Grazia, Cabrera Urban, Susana, Caforio, Davide, Cai, Huacheng, Cai, Yuchen, Cairo, Valentina, Cakir, Orhan, Calace, Noemi, Calafiura, Paolo, Calderini, Giovanni, Calfayan, Philippe, Callea, Giuseppe, Caloba, Luiz, Calvet, David, Calvet, Samuel, Calvet, Thomas Philippe, Calvetti, Milene, Camacho Toro, Reina Coromoto, Camarda, Stefano, Camarero Munoz, Daniel, Camarri, Paolo, Camerlingo, Maria Teresa, Cameron, David, Camincher, Clement, Campanelli, Mario, Camplani, Alessandra, Canale, Vincenzo, Canesse, Auriane, Bret Cano, Marc, Cantero Garcia, Josu, Cao, Yumeng, Capocasa, Francesca, Capua, Marcella, Carbone, Antonio, Cardarelli, Roberto, Cardenas, Juan Carlos, Cardillo, Fabio, Carli, Tancredi, Carlino, Giampaolo, Carlotto, Juan Ignacio, Carlson, Ben, Carlson, Evan Michael, Carminati, Leonardo, Carnesale, Maria, Caron, Sascha, Carquin Lopez, Edson, Carra, Sonia, Carratta, Giuseppe, Carrio Argos, Fernando, Carter, Joseph, Carter, Thomas Michael, Casado Lechuga, Pilar, Casha, Albert Francis, Castiglia, Emma Grace, Castillo, Florencia Luciana, Castillo Garcia, Lucia, Castillo Gimenez, Victoria, Castro, Nuno, Catinaccio, Andrea, Catmore, James, Cavaliere, Viviana, Cavalli, Noemi, Cavasinni, Vincenzo, Celebi, Emre, Celli, Federico, Centonze, Martino Salomone, Cerny, Karel, Santiago Cerqueira, Augusto, Cerri, Alex, Cerrito, Lucio, Cerutti, Fabio, Cervelli, Alberto, Cetin, Serkant, Chadi, Zakaria, Chakraborty, Dhiman, Chala, Mikael, Chan, Jay, Chan, Wai Yuen, Chapman, John Derek, Chargeishvili, Bakar, Charlton, Dave, Charman, Thomas Paul, Chatterjee, Meghranjana, Chekanov, Sergei, Chekulaev, Sergey, Shelkov, G, Chen, Andy, Chen, Boping, Chen, Charlie, Chen, Huirun, Chen, Hucheng, Chen, Jing, Chen, Jiayi, Chen, Shion, Chen, Shenjian, Chen, Xiang, Chen, Xin, Chen, Ye, Cheng, Alkaid, Cheng, Hok Chuen Tom, Cheong, Sanha, Cheplakov, Alexander, Cheremushkina, Evgeniya, Cherepanova, Elizaveta, Cherkaoui El Moursli, Rajaa, Cheu, Elliott, Cheung, Kingman, Chevalier, Laurent, Chiarella, Vitaliano, Chiarelli, Giorgio, Chiedde, Nemer, Chiodini, Gabriele, Chisholm, Andrew Stephen, Chitan, Adrian, Chitishvili, Mariam, Chiu, Justin, Chizhov, Mihail, Choi, Kyungeon, Chomont, Arthur, Chou, Yuan-Tang, Chow, Edwin, Chowdhury, Tasnuva, Christopher, Lawrence Davou, Chu, Michael Kwok Lam, Chu, Ming Chung, Chu, Xiaotong, Chudoba, Jiri, Chwastowski, Janusz, Cieri, Davide, Ciesla, Krzysztof, Cindro, Vladimir, Ciocio, Alessandra, Cirotto, Francesco, Citron, Zvi, Citterio, Mauro, Ciubotaru, Dan Andrei, Ciungu, Bianca Monica, Clark, Allan, Clark, Philip, Clavijo Columbie, Jose Manuel, Clawson, Savannah, Clement, Christophe, Clercx, Joshua, Clissa, Luca, Coadou, Yann, Cobal, Marina, Coccaro, Andrea, Barrue, Ricardo, Coelho Lopes de Sa, Rafael, Coelli, Simone, Cohen, Hadar, Coimbra, Artur, Cole, Brian, Collot, Johann, Conde Muino, Patricia, Connell, Matt, Connell, Simon, Connelly, Ian Allan, Conroy, Eimear Isobel, Conventi, Francesco, Cooke, Harry, Sarkar, Amanda, Cormier, Felix, Corpe, Louie Dartmoor, Corradi, Massimo, Corrigan, Eric Edward, Corriveau, Francois, Cortes Gonzalez, Arely, Costa Mezquita, Maria Jose, Costanza, Francesco, Costanzo, Davide, Cote, Benjamin, Cowan, Glen, Cowley, James William, Cranmer, Kyle Stuart, Crepe-Renaudin, Sabine, Crescioli, Francesco, Cristinziani, Markus, Cristoforetti, Marco, Croft, Vincent Alexander, Crosetti, Nanni, Cueto Gomez, Ana Rosario, Cuhadar Donszelmann, Tulay, Cui, Han, Cui, Zhaoyuan, Cukierman, Aviv Ruben, Cunningham, Liam, Curcio, Francesco, Czodrowski, Patrick Karl, Czurylo, Marta, Sousa, Mario Jose, da Fonseca Pinto, Joao Victor, da Via, Cinzia, Dabrowski, Wladyslaw, Dado, Tomas, Dahbi, Salah-Eddine, Dai, Tiesheng, Dallapiccola, Carlo, Dam, Mogens, d'Amen, Gabriele, d'Amico, Valerio, Damp, Johannes Frederic, Dandoy, Jeff, Daneri, Maria Florencia, Danninger, Matthias, Dao, Valerio, Darbo, Nanni, Darmora, Smita, Das, Sruthy Jyothi, d'Auria, Saverio, David, Claire, Davidek, Tomas, Davis, Douglas Raymond, Davis-Purcell, Benjamin Richard, Dawson, Ian, De, Kaushik, de Asmundis, Riccardo, de Beurs, Marcus, de Biase, Nicola, de Castro, Stefano, de Groot, Nicolo, de Jong, Paul, de la Torre Perez, Hector, de Maria, Antonio, de Salvo, Alessandro, de Sanctis, Umberto, de Santo, Antonella, de Vivie de Regie, Jean-Baptiste, Dedovich, Dmitri, Degens, Jordy, Deiana, Allison Mccarn, del Corso, Francesca, del Peso, Jose, del Rio, Fer, Deliot, Frederic, Delitzsch, Chris Malena, Della Pietra, Massimo, Della Volpe, Domenico, Dell'Acqua, Andrea, Dell'Asta, Lidia, Delmastro, Marco, Delsart, Pierre Antoine, Demers Konezny, Sarah Marie, Demichev, Mikhail, Denisov, Serguei, d'Eramo, Louis, Derendarz, Dominik Karol, Derue, Frederic, Dervan, Paul, Desch, Klaus, Dette, Karola, Deutsch, Christopher, Deviveiros, Pier-Olivier, Di Bello, Francesco Armando, Di Ciaccio, Anna, Di Ciaccio, Lucia, Di Domenico, Antonio, Di Donato, Camilla, Di Girolamo, Alessandro, Di Gregorio, Giulia, Di Luca, Andrea, Di Micco, Biagio, Di Nardo, Roberto, Diaconu, Cristinel, de Almeida Dias, Flavia, Vale, Tiago, Diaz Gutierrez, Marco Aurelio, Diaz Capriles, Federico Guillermo, Didenko, Mariia, Diehl, Edward, Diehl, Leena, Diez Cornell, Sergio, Diez Pardos, Carmen, Dimitriadi, Christina, Dimitrievska, Aleksandra, Ding, Wei, Dingfelder, Jochen Christian, Dinu, Ioan-Mihail, Dittmeier, Sebastian, Dittus, Fido, Djama, Fares, Djobava, Tamar, Djuvsland, Julia Isabell, Doglioni, Caterina, Dolejsi, Jiri, Dolezal, Zdenek, Donadelli, Marisilvia, Dong, Binbin, Donini, Julien Noce, d'Onofrio, Adelina, d'Onofrio, Monica, Dopke, Jens, Doria, Alessandra, Dova, Maria Teresa, Doyle, Tony, Draguet, Maxence, Drechsler, Eric, Dreyer, Etienne, Drivas-Koulouris, Ioannis, Drobac, Alec Swenson, Drozdova, Mariia, Du, Dongshuo, Du Pree, Tristan Arnoldus, Dubinin, Filipp, Dubovsky, Michal, Duchovni, Ehud, Duckeck, Guenter, Ducu, Otilia Anamaria, Duda, Dominik, Dudarev, Alexey, d'Uffizi, Matteo, Duflot, Laurent, Duehrssen-Debling, Michael, Dulsen, Carsten, Dumitriu, Ana Elena, Dunford, Monica, Dungs, Sascha, Dunne, Katherine Elaine, Duperrin, Arnaud, Yildiz, Hatice, Dueren, Michael Johannes, Durglishvili, Archil, Dwyer, Brianna, Dyckes, Ian, Dyndal, Mateusz, Dysch, Samuel Dezso, Dziedzic, Bartosz Sebastian, Earnshaw, Zoe Olivia, Eckerova, Barbora, Eggleston, Michael Glenn, Purcino de Souza, Edmar Egidio, Ehrke, Lukas, Eigen, Gerald, Einsweiler, Kevin Frank, Ekelof, Tord Johan Carl, Ekman, Per Alexander, El Ghazali, Yassine, El Jarrari, Hassnae, El Moussaouy, Ali, Ellajosyula, Venugopal, Ellert, Mattias, Ellinghaus, Frank, Elliot, Alison, Ellis, Nick, Elmsheuser, Johannes, Elsing, Markus, Emeliyanov, Dmitry, Emerman, Alex, Enari, Yuji, Ene, Irina, Epari, Shalini, Erdmann, Johannes, Ereditato, Antonio, Erland, Paula Agnieszka, Errenst, Martin, Escalier, Marc, Escobar Ibanez, Carlos, Etzion, Erez, Gaspar de Andrade Evans, Guiomar, Evans, Hal, Evans, Meirin Oan, Ezhilov, Aleksei, Ezzarqtouni, Sanae, Fabbri, Federica, Fabbri, Laura, Facini, Gabriel, Fadeyev, Vitaliy, Fakhrutdinov, Rinat, Falciano, Speranza, Falke, Peter Johannes, Falke, Saskia, Faltova, Jana, Fan, Yunyun, Fang, Yaquan, Fanourakis, Georgios, Fanti, Marcello, Faraj, Mohammed, Farazpay, Zahra, Farbin, Amir, Farilla, Ada, Farooque, Trisha, Farrington, Sinead, Fassi, Farida, Fassouliotis, Dimitris, Faucci Giannelli, Michele, Fawcett, William James, Fayard, Louis, Federicova, Pavla, Fedin, Oleg, Fedotov, Gleb, Feickert, Matthew, Feligioni, Lorenzo, Fell, Alix, Fellers, Deion Elgin, Feng, Cunfeng, Feng, Minyu, Feng, Zhuoran, Fenton, Michael James, Fenyuk, Alexandre, Ferencz, Lars, Ferguson, Sarah Whitney, Pretel, Jose, Ferrando, James, Ferrari, Arnaud, Ferrari, Pamela, Ferrari, Roberto, Ferrere, Didier, Ferretti, Claudio, Fiedler, Frank, Filipcic, Andrej, Filmer, Emily, Filthaut, Frank, Castro Nunes Fiolhais, Miguel, Fiorini, Luca, Leitgeb, Florian Christoph, Fisher, Wade Cameron, Fitschen, Tobias, Fleck, Ivor, Fleischmann, Philipp, Flick, Tobias, Flores, Lucas Macrorie, Flores, Marvin, Flores Castillo, Luis Roberto, Follega, Francesco Maria, Fomin, Nikolai, Foo, Joel Hengwei, Forland, Blake Christopher, Formica, Andrea, Forti, Alessandra, Fortin, Etienne Marie, Fortman, Anne Winifred, Foti, Maria Giovanna, Fountas, Leonidas, Fournier, Daniel, Fox, Harald, Francavilla, Paolo, Francescato, Simone, Franchellucci, Stefano, Franchini, Matteo, Franchino, Silvia, Francis, David, Franco, Luca, Franconi, Laura, Franklin, Melissa, Frattari, Guglielmo, Freegard, Arran Charles, Freeman, Patrick Moriishi, Spolidoro Freund, Werner, Fritzsche, Nick, Froch, Alexander, Froidevaux, Daniel, Frost, James, Fu, Yao, Fujimoto, Minori, Fullana Torregrosa, Esteban, Fuster Verdu, Juan, Gabrielli, Alessandro, Gabrielli, Andrea, Gadow, Philipp, Gagliardi, Guido, Gagnon, Louis-Guillaume, Gallardo, Gabriel, Gallas, Elizabeth, Gallop, Bruce Joseph, Gamboa Goni, Rodrigo, Gan, Kock Kiam, Ganguly, Sanmay, Gao, Jun, Gao, Yanyan, Garay Walls, Francisca, Garcia, Berenice, Garcia, Carmen, Garcia Navarro, Jose Enrique, Garcia, Juanan, Garcia-Sciveres, Maurice, Gardner, Robert 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Irena, Nikolopoulos, Konstantinos, Nilsson, Paul, Nindhito, Herjuno Rah, Nisati, Aleandro, Nishu, Nishu, Nisius, Richard, Nitschke, Jan-Eric, Nkadimeng, Edward Khomotso, Noacco Rosende, Santiago, Nobe, Takuya, Noel, Daniel Louis, Noguchi, Yohei, Nommensen, Thomas, Nomura, Marcelo Ayumu, Norfolk, Mitchell Bradley, Bin Norisam, Raif Rafideen, Norman, Bryce John, Novak, Jakob, Novak, Tadej, Novgorodova, Olga, Novotny, Lukas, Novotny, Radek, Nozka, Libor, Ntekas, Kostas, Nunes de Moura, Natanael, Nurse, Emily Laura, Oakham, Gerald, Ocariz, Jose Humberto, Ochi, Atsuhiko, Ochoa, Ines, Ordek, Serhat, Ogrodnik, Agnieszka Ewa, Oh, Alexander, Ohm, Christian, Oide, Hideyuki, Oishi, Reiyo, Ojeda, Martina Laura, Okazaki, Yuta, O'Keefe, Michael William, Okumura, Yasuyuki, Olariu, Albert, Seabra, Luis, Olivares, Sebastian, Oliveira Damazio, Denis, Oliveira Goncalves, Dayane, Oliver, Jason, Olsson, Mats Joakim Robert, Olszewski, Andrzej, Olszowska, Jolanta, Oncel, Ogul, O'Neil, Dugan, O'Neill, Aaron 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Tianyi, Yang, Xiao, Yang, Xuan, Yang, Yi-Lin, Yang, Zhe, Yao, Wei-Ming, Yap, Yee Chinn, Ye, Hanfei, Ye, Hua, Ye, Jingbo, Ye, Shuwei, Ye, Xinmeng, Yeh, Yoran, Yeletskikh, Ivan, Yeo, Beom Ki, Yexley, Melissa, Yin, Pengqi, Yorita, Kohei, Younas, Sulman, Young, Christopher, Young, Charlie, Yuan, Man, Yuan, Rui, Yue, Luzhan, Yue, Xiaoguang, Zaazoua, Mohamed, Zabinski, Bartlomiej Henryk, Zaid, Estifa'A, Zakareishvili, Tamar, Zakharchuk, Nataliia, Zambito, Stefano, Zamora Saa, Jilberto Antonio, Zang, Jiaqi, Zanzi, Daniele, Zaplatilek, Ota, Zeissner, Sonja Verena, Zeitnitz, Christian, Zeng, Jiancong, Zenger, Todd, Zenin, Oleg, Zenis, Tibor, Zenz, Seth, Zerradi, Soufiane, Zerwas, Dirk, Zhang, Bowen, Zhang, Dengfeng, Zhang, Gang, Zhang, Jie, Zhang, Jinlong, Zhang, Kaili, Zhang, Lei, Zhang, Peng, Zhang, Rui, Zhang, Shuzhou, Zhang, Tingyu, Zhang, Xiangke, Zhang, Xueyao, Zhang, Yulei, Zhang, Zhicai, Zhang, Zhiqing Philippe, Zhao, Haoran, Zhao, Pingchuan, Zhao, Tongbin, Zhao, Yuzhan, Zhao, Zhengguo, Zhemchugov, Alexey, Zheng, Xiangxuan, Zheng, Zhi, Zhong, Dewen, Zhou, Bing, Zhou, Chen, Zhou, Hao, Zhou, Ning, Zhou, You, Zhu, Chengguang, Zhu, Chenzheng, Zhu, Heling, Zhu, Hongbo, Zhu, Junjie, Zhu, Yifan, Zhu, Yingchun, Zhuang, Xuai, Zhukov, Konstantin, Zhulanov, Vladimir, Zimine, Nikolai, Zinsser, Joachim, Ziolkowski, Michal, Zivkovic, Lidija, Zoccoli, Antonio, Zoch, Knut, Zorbas, Theodore, Zormpa, Olga, Zou, Wenkai, Zwalinski, Lukasz, Centre de Physique des Particules de Marseille (CPPM), Aix Marseille Université (AMU)-Institut National de Physique Nucléaire et de Physique des Particules du CNRS (IN2P3)-Centre National de la Recherche Scientifique (CNRS), Laboratoire d'Annecy de Physique des Particules (LAPP), Institut National de Physique Nucléaire et de Physique des Particules du CNRS (IN2P3)-Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Centre National de la Recherche Scientifique (CNRS), Laboratoire de Physique des 2 Infinis Irène Joliot-Curie (IJCLab), Institut National de Physique Nucléaire et de Physique des Particules du CNRS (IN2P3)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS), Institut de Recherches sur les lois Fondamentales de l'Univers (IRFU), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris-Saclay, Laboratoire de Physique Nucléaire et de Hautes Énergies (LPNHE (UMR_7585)), Institut National de Physique Nucléaire et de Physique des Particules du CNRS (IN2P3)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), AstroParticule et Cosmologie (APC (UMR_7164)), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut National de Physique Nucléaire et de Physique des Particules du CNRS (IN2P3)-Observatoire de Paris, Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Centre National de la Recherche Scientifique (CNRS)-Université Paris Cité (UPCité), Laboratoire de Physique de Clermont (LPC), Institut National de Physique Nucléaire et de Physique des Particules du CNRS (IN2P3)-Centre National de la Recherche Scientifique (CNRS)-Université Clermont Auvergne (UCA), Laboratoire de Physique Subatomique et de Cosmologie (LPSC), Institut National de Physique Nucléaire et de Physique des Particules du CNRS (IN2P3)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes (UGA)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP ), Université Grenoble Alpes (UGA), and ATLAS

Subjects
electron, p p, scattering, FOS: Physical sciences, GeV, decay modes, High Energy Physics - Experiment, High Energy Physics - Experiment (hep-ex), [PHYS.HEXP]Physics [physics]/High Energy Physics - Experiment [hep-ex], TeV, particle, long-lived, Higgs particle, production, two-photon, lifetime, background, photon, calorimeter, liquid argon, ATLAS, two-particle, pair production, electromagnetic, CERN LHC Coll, trajectory, supersymmetry, symmetry breaking, direct detection, branching ratio, transverse momentum, missing-energy, signature, Particle Physics - Experiment
Abstract

A search is presented for displaced production of Higgs bosons or $Z$ bosons, originating from the decay of a neutral long-lived particle (LLP) and reconstructed in the decay modes $H\rightarrow \gamma\gamma$ and $Z\rightarrow ee$. The analysis uses the full Run 2 data set of proton$-$proton collisions delivered by the LHC at an energy of $\sqrt{s}=13$ TeV between 2015 and 2018 and recorded by the ATLAS detector, corresponding to an integrated luminosity of 139 fb$^{-1}$. Exploiting the capabilities of the ATLAS liquid argon calorimeter to precisely measure the arrival times and trajectories of electromagnetic objects, the analysis searches for the signature of pairs of photons or electrons which arise from a common displaced vertex and which arrive after some delay at the calorimeter. The results are interpreted in a gauge-mediated supersymmetry breaking model with pair-produced higgsinos that decay to LLPs, and each LLP subsequently decays into either a Higgs boson or a $Z$ boson. The final state includes at least two particles that escape direct detection, giving rise to missing transverse momentum. No significant excess is observed above the background expectation. The results are used to set upper limits on the cross section for higgsino pair production, up to a $\tilde\chi^0_1$ mass of 369 (704) GeV for decays with 100% branching ratio of $\tilde\chi^0_1$ to Higgs ($Z$) bosons for a $\tilde\chi^0_1$ lifetime of 2 ns. A model-independent limit is also set on the production of pairs of photons or electrons with a significant delay in arrival at the calorimeter., Comment: 52 pages in total, author list starting page 29, 11 figures, 2 tables, submitted to Physical Review D. All figures including auxiliary figures are available at https://atlas.web.cern.ch/Atlas/GROUPS/PHYSICS/PAPERS/SUSY-2020-28/

Published
2023
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35. Additional file 2 of Epigenetic reactivation of tumor suppressor genes with CRISPRa technologies as precision therapy for hepatocellular carcinoma

Author

Sgro, Agustin, Cursons, Joseph, Waryah, Charlene, Woodward, Eleanor A., Foroutan, Momeneh, Lyu, Ruqian, Yeoh, George C. T., Leedman, Peter J., and Blancafort, Pilar

Abstract

Additional file 2: Figure S2. Related to Fig. 1. A The percentage of patients who have evidence of gene hypermethylation and no evidence of gene loss/deletion within each iCluster group (iClust1: blue; iClust2: orange; and iClust3: green) and across all patients (black). B The percentage of patients who have evidence of gene hypermethylation and no evidence of gene loss/deletion in at least one gene of the listed set, within each iCluster group and across all patients. Genes were defined as hypermethylated if their corresponding probe β-value was greater than all matched-adjacent/normal liver tissue samples

Published
2023
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41. Clusters of COVID-19 protective and risky behaviors and their associations with pandemic, socio-demographic, and mental health factors in the United States

Author

Nishimi, Kristen, primary, Borsari, Brian, additional, Marx, Brian P., additional, Rosen, Raymond C., additional, Cohen, Beth E., additional, Woodward, Eleanor, additional, Maven, David, additional, Tripp, Paige, additional, Jiha, Ahmad, additional, Woolley, Joshua D., additional, Neylan, Thomas C., additional, and O'Donovan, Aoife, additional

Published
2022
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42. A molecularly integrated grade for meningioma

Author

Driver, Joseph, primary, Hoffman, Samantha, additional, Tavakol, Sherwin, additional, Woodward, Eleanor, additional, Maury, Eduardo, additional, Bhave, Varun, additional, Abedalthagafi, Malak, additional, Aizer, Ayal, additional, Alexander, Brian, additional, Ligon, Keith, additional, Reardon, David, additional, Wen, Patrick, additional, Al-Mefty, Ossama, additional, Ligon, Azra, additional, Dubuc, Adrian, additional, Beroukhim, Rameen, additional, Claus, Elizabeth, additional, Dunn, Ian, additional, Santagata, Sandro, additional, and Bi, Wenya Linda, additional

Published
2022
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45. A molecularly integrated grade for meningioma

Author

Driver, Joseph, primary, Hoffman, Samantha E, additional, Tavakol, Sherwin, additional, Woodward, Eleanor, additional, Maury, Eduardo A, additional, Bhave, Varun, additional, Greenwald, Noah F, additional, Nassiri, Farshad, additional, Aldape, Kenneth, additional, Zadeh, Gelareh, additional, Choudhury, Abrar, additional, Vasudevan, Harish N, additional, Magill, Stephen T, additional, Raleigh, David R, additional, Abedalthagafi, Malak, additional, Aizer, Ayal A, additional, Alexander, Brian M, additional, Ligon, Keith L, additional, Reardon, David A, additional, Wen, Patrick Y, additional, Al-Mefty, Ossama, additional, Ligon, Azra H, additional, Dubuc, Adrian M, additional, Beroukhim, Rameen, additional, Claus, Elizabeth B, additional, Dunn, Ian F, additional, Santagata, Sandro, additional, and Linda Bi, Wenya, additional

Published
2021
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50. molecularly integrated grade for meningioma.

Author

Driver, Joseph, Hoffman, Samantha E, Tavakol, Sherwin, Woodward, Eleanor, Maury, Eduardo A, Bhave, Varun, Greenwald, Noah F, Nassiri, Farshad, Aldape, Kenneth, Zadeh, Gelareh, Choudhury, Abrar, Vasudevan, Harish N, Magill, Stephen T, Raleigh, David R, Abedalthagafi, Malak, Aizer, Ayal A, Alexander, Brian M, Ligon, Keith L, Reardon, David A, and Wen, Patrick Y

Published
2022
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