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Browsing by Author "Guinney, Justin"
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Item Brigatinib causes tumor shrinkage in both NF2-deficient meningioma and schwannoma through inhibition of multiple tyrosine kinases but not ALK(PLOS, 2021-07-15) Chang, Long-Sheng; Oblinger, Janet L.; Smith, Abbi E.; Ferrer, Marc; Angus, Steven P.; Hawley, Eric; Petrilli, Alejandra M.; Beauchamp, Roberta L.; Riecken, Lars Björn; Erdin, Serkan; Poi, Ming; Huang, Jie; Bessler, Waylan K.; Zhang, Xiaohu; Guha, Rajarshi; Thomas, Craig; Burns, Sarah S.; Gilbert, Thomas S.K.; Jiang, Li; Li, Xiaohong; Lu, Qingbo; Yuan, Jin; He, Yongzheng; Dixon, Shelley A.H.; Masters, Andrea; Jones, David R.; Yates, Charles W.; Haggarty, Stephen J.; La Rosa, Salvatore; Welling, D. Bradley; Stemmer-Rachamimov, Anat O.; Plotkin, Scott R.; Gusella, James F.; Guinney, Justin; Morrison, Helen; Ramesh, Vijaya; Fernandez-Valle, Cristina; Johnson, Gary L.; Blakeley, Jaishri O.; Clapp, D. Wade; Pediatrics, School of MedicineNeurofibromatosis Type 2 (NF2) is an autosomal dominant genetic syndrome caused by mutations in the NF2 tumor suppressor gene resulting in multiple schwannomas and meningiomas. There are no FDA approved therapies for these tumors and their relentless progression results in high rates of morbidity and mortality. Through a combination of high throughput screens, preclinical in vivo modeling, and evaluation of the kinome en masse, we identified actionable drug targets and efficacious experimental therapeutics for the treatment of NF2 related schwannomas and meningiomas. These efforts identified brigatinib (ALUNBRIG®), an FDA-approved inhibitor of multiple tyrosine kinases including ALK, to be a potent inhibitor of tumor growth in established NF2 deficient xenograft meningiomas and a genetically engineered murine model of spontaneous NF2 schwannomas. Surprisingly, neither meningioma nor schwannoma cells express ALK. Instead, we demonstrate that brigatinib inhibited multiple tyrosine kinases, including EphA2, Fer and focal adhesion kinase 1 (FAK1). These data demonstrate the power of the de novo unbiased approach for drug discovery and represents a major step forward in the advancement of therapeutics for the treatment of NF2 related malignancies.Item Outcomes of COVID-19 in Patients With Cancer: Report From the National COVID Cohort Collaborative (N3C)(ASCO, 2021-06-04) Sharafeldin, Noha; Bates, Benjamin; Song, Qianqian; Madhira, Vithal; Dong, Sharlene; Yan, Yao; Lee, Eileen; Kuhrt, Nathaniel; Shao, Yu Raymond; Liu, Feifan; Bergquist, Timothy; Guinney, Justin; Su, Jing; Topaloglu, Umit; Biostatistics, School of Public HealthPURPOSE Variation in risk of adverse clinical outcomes in patients with cancer and COVID-19 has been reported from relatively small cohorts. The NCATS’ National COVID Cohort Collaborative (N3C) is a centralized data resource representing the largest multicenter cohort of COVID-19 cases and controls nationwide. We aimed to construct and characterize the cancer cohort within N3C and identify risk factors for all-cause mortality from COVID-19. METHODS We used 4,382,085 patients from 50 US medical centers to construct a cohort of patients with cancer. We restricted analyses to adults ≥ 18 years old with a COVID-19–positive or COVID-19–negative diagnosis between January 1, 2020, and March 25, 2021. We followed N3C selection of an index encounter per patient for analyses. All analyses were performed in the N3C Data Enclave Palantir platform. RESULTS A total of 398,579 adult patients with cancer were identified from the N3C cohort; 63,413 (15.9%) were COVID-19–positive. Most common represented cancers were skin (13.8%), breast (13.7%), prostate (10.6%), hematologic (10.5%), and GI cancers (10%). COVID-19 positivity was significantly associated with increased risk of all-cause mortality (hazard ratio, 1.20; 95% CI, 1.15 to 1.24). Among COVID-19–positive patients, age ≥ 65 years, male gender, Southern or Western US residence, an adjusted Charlson Comorbidity Index score ≥ 4, hematologic malignancy, multitumor sites, and recent cytotoxic therapy were associated with increased risk of all-cause mortality. Patients who received recent immunotherapies or targeted therapies did not have higher risk of overall mortality. CONCLUSION Using N3C, we assembled the largest nationally representative cohort of patients with cancer and COVID-19 to date. We identified demographic and clinical factors associated with increased all-cause mortality in patients with cancer. Full characterization of the cohort will provide further insights into the effects of COVID-19 on cancer outcomes and the ability to continue specific cancer treatments.Item Outcomes of COVID-19 in Patients With Cancer: Report From the National COVID Cohort Collaborative (N3C)(American Society of Clinical Oncology, 2021) Sharafeldin, Noha; Bates, Benjamin; Song, Qianqian; Madhira, Vithal; Yan, Yao; Dong, Sharlene; Lee, Eileen; Kuhrt, Nathaniel; Shao, Yu Raymond; Liu, Feifan; Bergquist, Timothy; Guinney, Justin; Su, Jing; Topaloglu, Umit; Biostatistics, School of Public HealthPurpose: Variation in risk of adverse clinical outcomes in patients with cancer and COVID-19 has been reported from relatively small cohorts. The NCATS' National COVID Cohort Collaborative (N3C) is a centralized data resource representing the largest multicenter cohort of COVID-19 cases and controls nationwide. We aimed to construct and characterize the cancer cohort within N3C and identify risk factors for all-cause mortality from COVID-19. Methods: We used 4,382,085 patients from 50 US medical centers to construct a cohort of patients with cancer. We restricted analyses to adults ≥ 18 years old with a COVID-19-positive or COVID-19-negative diagnosis between January 1, 2020, and March 25, 2021. We followed N3C selection of an index encounter per patient for analyses. All analyses were performed in the N3C Data Enclave Palantir platform. Results: A total of 398,579 adult patients with cancer were identified from the N3C cohort; 63,413 (15.9%) were COVID-19-positive. Most common represented cancers were skin (13.8%), breast (13.7%), prostate (10.6%), hematologic (10.5%), and GI cancers (10%). COVID-19 positivity was significantly associated with increased risk of all-cause mortality (hazard ratio, 1.20; 95% CI, 1.15 to 1.24). Among COVID-19-positive patients, age ≥ 65 years, male gender, Southern or Western US residence, an adjusted Charlson Comorbidity Index score ≥ 4, hematologic malignancy, multitumor sites, and recent cytotoxic therapy were associated with increased risk of all-cause mortality. Patients who received recent immunotherapies or targeted therapies did not have higher risk of overall mortality. Conclusion: Using N3C, we assembled the largest nationally representative cohort of patients with cancer and COVID-19 to date. We identified demographic and clinical factors associated with increased all-cause mortality in patients with cancer. Full characterization of the cohort will provide further insights into the effects of COVID-19 on cancer outcomes and the ability to continue specific cancer treatments.Item The National COVID Cohort Collaborative (N3C): Rationale, design, infrastructure, and deployment(Oxford University Press, 2021) Haendel, Melissa A.; Chute, Christopher G.; Bennett, Tellen D.; Eichmann, David A.; Guinney, Justin; Kibbe, Warren A.; Payne, Philip R. O.; Pfaff, Emily R.; Robinson, Peter N.; Saltz, Joel H.; Spratt, Heidi; Suver, Christine; Wilbanks, John; Wilcox, Adam B.; Williams, Andrew E.; Wu, Chunlei; Blacketer, Clair; Bradford, Robert L.; Cimino, James J.; Clark, Marshall; Colmenares, Evan W.; Francis, Patricia A.; Gabriel, Davera; Graves, Alexis; Hemadri, Raju; Hong, Stephanie S.; Hripscak, George; Jiao, Dazhi; Klann, Jeffrey G.; Kostka, Kristin; Lee, Adam M.; Lehmann, Harold P.; Lingrey, Lora; Miller, Robert T.; Morris, Michele; Murphy, Shawn N.; Natarajan, Karthik; Palchuk, Matvey B.; Sheikh, Usman; Solbrig, Harold; Visweswaran, Shyam; Walden, Anita; Walters, Kellie M.; Weber, Griffin M.; Zhang, Xiaohan Tanner; Zhu, Richard L.; Amor, Benjamin; Girvin, Andrew T.; Manna, Amin; Qureshi, Nabeel; Kurilla, Michael G.; Michael, Sam G.; Portilla, Lili M.; Rutter, Joni L.; Austin, Christopher P.; Gersing, Ken R.; Biomedical Engineering and Informatics, Luddy School of Informatics, Computing, and EngineeringObjective: Coronavirus disease 2019 (COVID-19) poses societal challenges that require expeditious data and knowledge sharing. Though organizational clinical data are abundant, these are largely inaccessible to outside researchers. Statistical, machine learning, and causal analyses are most successful with large-scale data beyond what is available in any given organization. Here, we introduce the National COVID Cohort Collaborative (N3C), an open science community focused on analyzing patient-level data from many centers. Materials and methods: The Clinical and Translational Science Award Program and scientific community created N3C to overcome technical, regulatory, policy, and governance barriers to sharing and harmonizing individual-level clinical data. We developed solutions to extract, aggregate, and harmonize data across organizations and data models, and created a secure data enclave to enable efficient, transparent, and reproducible collaborative analytics. Results: Organized in inclusive workstreams, we created legal agreements and governance for organizations and researchers; data extraction scripts to identify and ingest positive, negative, and possible COVID-19 cases; a data quality assurance and harmonization pipeline to create a single harmonized dataset; population of the secure data enclave with data, machine learning, and statistical analytics tools; dissemination mechanisms; and a synthetic data pilot to democratize data access. Conclusions: The N3C has demonstrated that a multisite collaborative learning health network can overcome barriers to rapidly build a scalable infrastructure incorporating multiorganizational clinical data for COVID-19 analytics. We expect this effort to save lives by enabling rapid collaboration among clinicians, researchers, and data scientists to identify treatments and specialized care and thereby reduce the immediate and long-term impacts of COVID-19.