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Van Egeren D, Kohli K, Warner JL, Bedard PL, Riely G, Lepisto E, Schrag D, LeNoue-Newton M, Catalano P, Kehl KL, Michor F, Fiandalo M, Foti M, Khotskaya Y, Lee J, Peters N, Sweeney S, Abraham J, Brenton JD, Caldas C, Doherty G, Nimmervoll B, Pinilla K, Martin JE, Rueda OM, Sammut SJ, Silva D, Cao K, Heath AP, Li M, Lilly J, MacFarland S, Maris JM, Mason JL, Morgan AM, Resnick A, Welsh M, Zhu Y, Johnson B, Li Y, Sholl L, Beaudoin R, Biswas R, Cerami E, Cushing O, Dand D, Ducar M, Gusev A, Hahn WC, Haigis K, Hassett M, Janeway KA, Jänne P, Jawale A, Johnson J, Kehl KL, Kumari P, Laucks V, Lepisto E, Lindeman N, Lindsay J, Lueders A, Macconaill L, Manam M, Mazor T, Miller D, Newcomb A, Orechia J, Ovalle A, Postle A, Quinn D, Reardon B, Rollins B, Shivdasani P, Tramontano A, Van Allen E, Van Nostrand SC, Bell J, Datto MB, Green M, Hubbard C, McCall SJ, Mettu NB, Strickler JH, Andre F, Besse B, Deloger M, Dogan S, Italiano A, Loriot Y, Ludovic L, Michels S, Scoazec J, Tran-Dien A, Vassal G, Freeman CE, Hsiao SJ, Ingham M, Pang J, Rabadan R, Roman LC, Carvajal R, DuBois R, Arcila ME, Benayed R, Berger MF, Bhuiya M, Brannon AR, Brown S, Chakravarty D, Chu C, de Bruijn I, Galle J, Gao J, Gardos S, Gross B, Kundra R, Kung AL, Ladanyi M, Lavery JA, Li X, Lisman A, Mastrogiacomo B, McCarthy C, Nichols C, Ochoa A, Panageas KS, Philip J, Pillai S, Riely GJ, Rizvi H, Rudolph J, Sawyers CL, Schrag D, Schultz N, Schwartz J, Sheridan R, Solit D, Wang A, Wilson M, Zehir A, Zhang H, Zhao G, Ahmed L, Bedard PL, Bruce JP, Chow H, Cooke S, Del Rossi S, Felicen S, Hakgor S, Jagannathan P, Kamel-Reid S, Krishna G, Leighl N, Lu Z, Nguyen A, Oldfield L, Plagianakos D, Pugh TJ, Rizvi A, Sabatini P, Shah E, Singaravelan N, Siu L, Srivastava G, Stickle N, Stockley T, Tang M, Virtaenen C, Watt S, Yu C, Bernard B, Bifulco C, Cramer JL, Lee S, Piening B, Reynolds S, Slagel J, Tittel P, Urba W, VanCampen J, Weerasinghe R, Acebedo A, Guinney J, Guo X, Hunter-Zinck H, Yu T, Dang K, Anagnostou V, Baras A, Brahmer J, Gocke C, Scharpf RB, Tao J, Velculescu VE, Alexander S, Bailey N, Gold P, Bierkens M, de Graaf J, Hudeček J, Meijer GA, Monkhorst K, Samsom KG, Sanders J, Sonke G, ten Hoeve J, van de Velde T, van den Berg J, Voest E, Steinhardt G, Kadri S, Pankhuri W, Wang P, Segal J, Moung C, Espinosa-Mendez C, Martell HJ, Onodera C, Quintanar Alfaro A, Sweet-Cordero EA, Talevich E, Turski M, Van’t Veer L, Wren A, Aguilar S, Dienstmann R, Mancuso F, Nuciforo P, Tabernero J, Viaplana C, Vivancos A, Anderson I, Chaugai S, Coco J, Fabbri D, Johnson D, Jones L, Li X, Lovly C, Mishra S, Mittendorf K, Wen L, Yang YJ, Ye C, Holt M, LeNoue-Newton ML, Micheel CM, Park BH, Rubinstein SM, Stricker T, Wang L, Warner J, Guan M, Jin G, Liu L, Topaloglu U, Urtis C, Zhang W, D’Eletto M, Hutchison S, Longtine J, Walther Z. Genomic analysis of early-stage lung cancer reveals a role for TP53 mutations in distant metastasis. Sci Rep 2022; 12:19055. [PMID: 36351964 PMCID: PMC9646734 DOI: 10.1038/s41598-022-21448-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/11/2022] [Accepted: 09/27/2022] [Indexed: 11/10/2022] Open
Abstract
Patients with non-small cell lung cancer (NSCLC) who have distant metastases have a poor prognosis. To determine which genomic factors of the primary tumor are associated with metastasis, we analyzed data from 759 patients originally diagnosed with stage I-III NSCLC as part of the AACR Project GENIE Biopharma Collaborative consortium. We found that TP53 mutations were significantly associated with the development of new distant metastases. TP53 mutations were also more prevalent in patients with a history of smoking, suggesting that these patients may be at increased risk for distant metastasis. Our results suggest that additional investigation of the optimal management of patients with early-stage NSCLC harboring TP53 mutations at diagnosis is warranted in light of their higher likelihood of developing new distant metastases.
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Affiliation(s)
- Debra Van Egeren
- grid.65499.370000 0001 2106 9910Department of Data Science, Dana-Farber Cancer Institute, Boston, MA USA ,grid.38142.3c000000041936754XDepartment of Systems Biology, Harvard Medical School, Boston, MA USA ,grid.2515.30000 0004 0378 8438Stem Cell Program, Boston Children’s Hospital, Boston, MA USA ,grid.5386.8000000041936877XDepartment of Medicine, Weill Cornell Medicine, New York, NY USA
| | - Khushi Kohli
- grid.65499.370000 0001 2106 9910Department of Data Science, Dana-Farber Cancer Institute, Boston, MA USA
| | - Jeremy L. Warner
- grid.152326.10000 0001 2264 7217Department of Medicine, Vanderbilt University, Nashville, TN USA ,grid.152326.10000 0001 2264 7217Department of Biomedical Informatics, Vanderbilt University, Nashville, TN USA
| | - Philippe L. Bedard
- grid.17063.330000 0001 2157 2938Department of Medicine, University of Toronto, Toronto, ON Canada
| | - Gregory Riely
- grid.51462.340000 0001 2171 9952Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, NY USA
| | - Eva Lepisto
- grid.65499.370000 0001 2106 9910Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA USA ,grid.429426.f0000 0000 9350 5788Present Address: Multiple Myeloma Research Foundation, Norwalk, CT USA
| | - Deborah Schrag
- grid.51462.340000 0001 2171 9952Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, NY USA
| | - Michele LeNoue-Newton
- grid.412807.80000 0004 1936 9916Vanderbilt-Ingram Cancer Center, Vanderbilt University Medical Center, Nashville, TN USA
| | - Paul Catalano
- grid.65499.370000 0001 2106 9910Department of Data Science, Dana-Farber Cancer Institute, Boston, MA USA
| | - Kenneth L. Kehl
- grid.65499.370000 0001 2106 9910Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA USA
| | - Franziska Michor
- grid.65499.370000 0001 2106 9910Department of Data Science, Dana-Farber Cancer Institute, Boston, MA USA ,grid.38142.3c000000041936754XDepartment of Stem Cell and Regenerative Biology, Harvard University, Cambridge, MA USA ,grid.66859.340000 0004 0546 1623Broad Institute of MIT and Harvard, Cambridge, MA USA ,grid.38142.3c000000041936754XDepartment of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA USA ,grid.65499.370000 0001 2106 9910The Center for Cancer Evolution, Dana-Farber Cancer Institute, Boston, MA USA ,grid.38142.3c000000041936754XThe Ludwig Center at Harvard, Boston, MA USA
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Ma C, Sridharan M, Al-Sayegh H, Li A, Guo D, Auclair M, Kuragayala V, Bandaru C, Milne D, Cruse H, Beaudoin R, Orechia J, Bickel J, London WB. Building a Harmonized Datamart by Integrating Cross-Institutional Systems of Clinical, Outcome, and Genomic Data: The Pediatric Patient Informatics Platform ( PPIP). JCO Clin Cancer Inform 2021; 5:202-215. [PMID: 33591797 DOI: 10.1200/cci.20.00083] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/20/2022] Open
Abstract
PURPOSE Siloed electronic medical data limits utility and accessibility. At the Dana-Farber/Boston Children's Cancer and Blood Disorders Center, cross-institutional data were inconsistent and difficult to access. To unify data for clinical operations, administration, and research, we developed the Pediatric Patient Informatics Platform (PPIP), an integrated datamart harmonizing multiple source systems across two institutions into a common technology. PATIENTS AND METHODS Starting in 2009, user requirements were gathered and data sources were prioritized. Project teams, including biostatisticians, database developers, and an external contractor, were formed. Read-access to source systems was established. The 3-layer PPIP architecture was developed: STAGING, a near-exact copy of source data; INTEGRATION, where data were reorganized into domains; and, CONSUMPTION, where data were optimized for rapid retrieval. The diverse systems were integrated into a common IBM Netezza technology. Data filters were defined to accurately capture the Center's patients, and derived data items were created for harmonization across sources. An interactive online query tool, PPIP360, was developed using Microstrategy Analytics. RESULTS Driven by scientific objectives, the PPIP datamart was created, including 33,674 patients, 2,983 protocols, and 3.6 million patient visits from 14 source databases, 164 source tables, and 2,622 source data items. The PPIP360 has 605 data items and 33 metrics across 11 reports and dashboards. Dana-Farber and Boston Children's established a legal data-sharing agreement. The PPIP has supported hundreds of faculty, staff, and projects, including planning clinical trials and informing strategic planning. CONCLUSION The PPIP has successfully harmonized and integrated diagnostic, demographic, laboratory, treatment, clinical outcome, pathology, transplant, meta-protocol, and -omics data, for efficient, daily operational and research activities at Dana-Farber/Boston Children's Cancer and Blood Disorders Center, and future external sharing.
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Affiliation(s)
- Clement Ma
- Dana-Farber/Boston Children's Cancer and Blood Disorders Center, Boston, MA.,Harvard Medical School, Boston, MA
| | | | - Hasan Al-Sayegh
- Dana-Farber/Boston Children's Cancer and Blood Disorders Center, Boston, MA
| | - Anran Li
- Dana-Farber/Boston Children's Cancer and Blood Disorders Center, Boston, MA
| | - Dongjing Guo
- Dana-Farber/Boston Children's Cancer and Blood Disorders Center, Boston, MA
| | | | | | | | - Dana Milne
- Dana-Farber Cancer Institute, Boston, MA
| | | | | | | | - Jonathan Bickel
- Harvard Medical School, Boston, MA.,Boston Children's Hospital, Boston, MA
| | - Wendy B London
- Dana-Farber/Boston Children's Cancer and Blood Disorders Center, Boston, MA.,Harvard Medical School, Boston, MA
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Orechia J, Pathak A, Shi Y, Nawani A, Belozerov A, Fontes C, Lakhiani C, Jawale C, Patel C, Quinn D, Botvinnik D, Mei E, Cotter E, Byleckie J, Ullman-Cullere M, Chhetri P, Chalasani P, Karnam P, Beaudoin R, Sahu S, Belozerova Y, Mathew JP. OncDRS: An integrative clinical and genomic data platform for enabling translational research and precision medicine. Appl Transl Genom 2015; 6:18-25. [PMID: 27054074 PMCID: PMC4803771 DOI: 10.1016/j.atg.2015.08.005] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/29/2015] [Accepted: 08/05/2015] [Indexed: 02/01/2023]
Abstract
We live in the genomic era of medicine, where a patient's genomic/molecular data is becoming increasingly important for disease diagnosis, identification of targeted therapy, and risk assessment for adverse reactions. However, decoding the genomic test results and integrating it with clinical data for retrospective studies and cohort identification for prospective clinical trials is still a challenging task. In order to overcome these barriers, we developed an overarching enterprise informatics framework for translational research and personalized medicine called Synergistic Patient and Research Knowledge Systems (SPARKS) and a suite of tools called Oncology Data Retrieval Systems (OncDRS). OncDRS enables seamless data integration, secure and self-navigated query and extraction of clinical and genomic data from heterogeneous sources. Within a year of release, the system has facilitated more than 1500 research queries and has delivered data for more than 50 research studies.
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Affiliation(s)
- John Orechia
- Dana-Faber Cancer Institute, 450 Brookline Ave., Boston, MA-02215, United States
| | - Ameet Pathak
- Dana-Faber Cancer Institute, 450 Brookline Ave., Boston, MA-02215, United States
| | - Yunling Shi
- Dana-Faber Cancer Institute, 450 Brookline Ave., Boston, MA-02215, United States
| | - Aniket Nawani
- Dana-Faber Cancer Institute, 450 Brookline Ave., Boston, MA-02215, United States
| | - Andrey Belozerov
- Dana-Faber Cancer Institute, 450 Brookline Ave., Boston, MA-02215, United States
| | - Caitlin Fontes
- Dana-Faber Cancer Institute, 450 Brookline Ave., Boston, MA-02215, United States
| | - Camille Lakhiani
- Dana-Faber Cancer Institute, 450 Brookline Ave., Boston, MA-02215, United States
| | - Chetan Jawale
- Dana-Faber Cancer Institute, 450 Brookline Ave., Boston, MA-02215, United States
| | - Chetansharan Patel
- Dana-Faber Cancer Institute, 450 Brookline Ave., Boston, MA-02215, United States
| | - Daniel Quinn
- Dana-Faber Cancer Institute, 450 Brookline Ave., Boston, MA-02215, United States
| | - Dmitry Botvinnik
- Dana-Faber Cancer Institute, 450 Brookline Ave., Boston, MA-02215, United States
| | - Eddie Mei
- Dana-Faber Cancer Institute, 450 Brookline Ave., Boston, MA-02215, United States
| | - Elizabeth Cotter
- Dana-Faber Cancer Institute, 450 Brookline Ave., Boston, MA-02215, United States
| | - James Byleckie
- Dana-Faber Cancer Institute, 450 Brookline Ave., Boston, MA-02215, United States
| | | | - Padam Chhetri
- Dana-Faber Cancer Institute, 450 Brookline Ave., Boston, MA-02215, United States
| | - Poornima Chalasani
- Dana-Faber Cancer Institute, 450 Brookline Ave., Boston, MA-02215, United States
| | - Purushotham Karnam
- Dana-Faber Cancer Institute, 450 Brookline Ave., Boston, MA-02215, United States
| | - Ronald Beaudoin
- Dana-Faber Cancer Institute, 450 Brookline Ave., Boston, MA-02215, United States
| | - Sandeep Sahu
- Dana-Faber Cancer Institute, 450 Brookline Ave., Boston, MA-02215, United States
| | - Yelena Belozerova
- Dana-Faber Cancer Institute, 450 Brookline Ave., Boston, MA-02215, United States
| | - Jomol P Mathew
- Dana-Faber Cancer Institute, 450 Brookline Ave., Boston, MA-02215, United States
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Oh WK, Hayes J, Evan C, Manola J, George DJ, Waldron H, Donovan M, Varner J, Orechia J, Katcher B, Lu D, Nevins A, Wright RL, Tormey L, Talcott J, Rubin MA, Loda M, Sellers WR, Richie JP, Kantoff PW, Weeks J. Development of an integrated prostate cancer research information system. Clin Genitourin Cancer 2006; 5:61-6. [PMID: 16859581 DOI: 10.3816/cgc.2006.n.019] [Citation(s) in RCA: 53] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/20/2022]
Abstract
BACKGROUND In this article, we describe the design and implementation of a comprehensive prostate cancer database developed to collect, store, and access clinical, treatment, and outcomes data for research and clinical care. PATIENTS AND METHODS The Prostate Cancer Clinical Research Information System is a relational database. Data are entered from multiple sources, including medical records, institutional laboratory, patient registration, pharmacy systems, and clinician forms. The history, design, and operational characteristics of the database are described. Issues regarding necessary staffing and funding of databases are reviewed. RESULTS Four thousand two hundred forty-six patients have information in the Prostate Cancer Clinical Research Information System. Mean age of patients is 62 years, and 89% are white. Seventy-one percent of patients presented at diagnosis with T1 or T2 disease, and 78% had biopsy Gleason scores of <or=7, 8-10 in 18%. Median prostate-specific antigen level at diagnosis was 7 ng/mL, and 77% of patients presented with increased prostate-specific antigen as a trigger symptom. Sixty-four percent of patients presented to our clinic having had no previous treatment for prostate cancer. The majority of approached patients provided consent for collection of clinical data, blood, and tissue. Quality control assessments demonstrate high levels of concordance among data entry personnel. CONCLUSION Clinical databases are difficult to implement and maintain; however, they represent a valuable resource, particularly when linked to blood and tissue banks. Elements needed for a successful clinical database include engagement of clinicians, utility for research, and the ability to integrate with legacy systems. As cancer centers develop such databases, lessons learned from each experience should be shared in order to optimize the process.
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Affiliation(s)
- William K Oh
- Lank Center for Genitourinary Oncology, Dana-Farber Cancer Institute, Boston, MA 02115, USA.
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