The cornerstone of ORIEN is the common Total Cancer Care® (TCC) protocol, a longitudinal and post-study surveillance study of cancer patients. ORIEN is harnessing technology-based collaboration to break down barriers between institutions, enable rapid learning, and accelerate research and discovery efforts to bring new treatments to patients. To enable even greater collaboration with ORIEN—for members and nonmembers alike—we offer a Project Submission feature. This gives scientists the opportunity to explore potential research collaborations utilizing the Network’s vast resources.
With over 280,000+ patients enrolled in the TCC protocol to date, the TCC protocol provides an opportunity to generate real-world data (RWD) for cancer patients undergoing treatment. RWD is health and treatment outcome-related information that is collected in real-world medical settings. This rich dataset may be utilized to generate insights, or real-world evidence (RWE) about a medication or treatment regimen effectiveness and safety in the real-world setting, outside of traditional controlled clinical trial environment.
The ORIEN Avatar program, which was launched in 2016, generates whole exome and transcriptome data for TCC-consented patients with high-risk cancers and links longitudinal clinical data throughout a patient’s lifetime. Through ORIEN, network members collect and share clinical data and specimens for analysis to foster and enable translational research. M2GEN has developed a network data model system to integrate data from multiple sources and institutions to support team science and address complex cancer research questions. The rich ORIEN data enables deeper understanding of the cancer drug pharmacodynamics in patients and stimulates novel hypotheses for preclinical, translational and clinical research.
Enrollment of patients in the TCC protocol offers patients increased probability of being matched to effective clinical trial. Additionally, the pace of clinical trial development can be accelerated by taking a proactive approach to rapidly identify eligible patients for the trial using the ORIEN Avatar data. This approach improves clinical trial efficiency by reducing study timeline and overall costs. Centrally managed by M2GEN, the OCTN provides the ability to identify patients for target-based clinical trials. In addition to the rapid patient identification process, OCTN further enhances trial efficiency through a centralized protocol review and approval process.
Aligning with the ORIEN Mission of accelerating cancer discovery and delivering hope through collaborative learning and partnerships, ORIEN Intermember Projects encourage research opportunities between ORIEN member institutions, and are inclusive of nonmember and industry partners. ORIEN Intermember Projects provide a forum for clinical and scientific experts to exchange ideas and identify areas for collaboration to address unmet needs; advancing cancer research and patient care.
For more information about proposing a project or to discuss research opportunities in your area of interest, submit a project inquiry below or contact ORIENprojects@M2Gen.com.
Our ecosystem is scientifically rooted and believes meaningful advancements for patients come from data-driven decisions. See how we are already contributing to the fight against cancer. The following publications were developed by ORIEN Members based on Total Cancer Care data.
Yun S, Sharma R, Chan O, Vincelette ND, Sallman DA, Sweet K, Padron E, Komrokji R, Lancet JE, Abraham I, Moscinski LC, Cleveland JL, List AF, Zhang L. Leuk Res. 2019 Sep;84:106194. doi: 10.1016/j.leukres.2019.106194. Epub 2019 Jul 18. PubMed PMID: 31357093. https://www.ncbi.nlm.nih.gov/pubmed/31357093
Stewart PA, Welsh EA, Slebos RJC, Fang B, Izumi V, Chambers M, Zhang G, Cen L, Pettersson F, Zhang Y, Chen Z, Cheng CH, Thapa R, Thompson Z, Fellows KM, Francis JM, Saller JJ, Mesa T, Zhang C, Yoder S, DeNicola GM, Beg AA, Boyle TA, Teer JK, Ann Chen Y, Koomen JM, Eschrich SA, Haura EB. Nat Commun. 2019 Aug 8;10(1):3578. doi:10.1038/s41467-019-11452-x. PubMed PMID: 31395880; PubMed Central PMCID: PMC6687710. https://www.ncbi.nlm.nih.gov/pubmed/31395880
Mirza AS, Yun S, Ali NA, Shin H, O'Neil JL, Elharake M, Schwartz D, Robinson K, Nowell E, Engle G, Badat I, Brimer T, Kuc A, Sequeira A, Mirza S, Sikaria D, Vera JD, Hackney N, Abusrur S, Jesurajan J, Kuang J, Patel S, Khalil S, Bhaskar S, Beard A, Abuelenen T, Ratnasamy K, Visweshwar N, Komrokji R, Jaglal M. Thromb J. 2019 Jul 2;17:13. doi: 1186/s12959-019-0202-z. eCollection 2019. PubMed PMID: 31303864; PubMed Central PMCID: PMC6604148. https://www.ncbi.nlm.nih.gov/pubmed/31303864
Transcriptome-Wide Association Study Among 97,898 Women to Identify Candidate Susceptibility Genes for Epithelial Ovarian Cancer Risk. Lu Y, Beeghly-Fadiel A, Wu L, Guo X, Li B, Schildkraut JM, Im HK, Chen YA, Permuth JB, Reid BM, Teer JK, Moysich KB, Andrulis IL, Anton-Culver H, Arun BK, Bandera EV, Barkardottir RB, Barnes DR, Benitez J, Bjorge L, Brenton J, Butzow R, Caldes T, Caligo MA, Campbell I, Chang-Claude J, Claes KBM, Couch FJ, Cramer DW, Daly MB, deFazio A, Dennis J, Diez O, Domchek SM, Dörk T, Easton DF, Eccles DM, Fasching PA, Fortner RT, Fountzilas G, Friedman E, Ganz PA, Garber J, Giles GG, Godwin AK, Goldgar DE, Goodman MT, Greene MH, Gronwald J, Hamann U, Heitz F, Hildebrandt MAT, Høgdall CK, Hollestelle A, Hulick PJ, Huntsman DG, Imyanitov EN, Isaacs C, Jakubowska A, James P, Karlan BY, Kelemen LE, Kiemeney LA, Kjaer SK, Kwong A, Le ND, Leslie G, Lesueur F, Levine DA, Mattiello A, May T, McGuffog L, McNeish IA, Merritt MA, Modugno F, Montagna M, Neuhausen SL, Nevanlinna H, Nielsen FC, Nikitina-Zake L, Nussbaum RL, Offit K, Olah E, Olopade OI, Olson SH, Olsson H, Osorio A, Park SK, Parsons MT, Peeters PHM, Pejovic T, Peterlongo P, Phelan CM, Pujana MA, Ramus SJ, Rennert G, Risch H, Rodriguez GC, Rodríguez-Antona C, Romieu I, Rookus MA, Rossing MA, Rzepecka IK, Sandler DP, Schmutzler RK, Setiawan VW, Sharma P, Sieh W, Simard J, Singer CF, Song H, Southey MC, Spurdle AB, Sutphen R, Swerdlow AJ, Teixeira MR, Teo SH, Thomassen M, Tischkowitz M, Toland AE, Trichopoulou A, Tung N, Tworoger SS, van Rensburg EJ, Vanderstichele A, Vega A, Edwards DV, Webb PM, Weitzel JN, Wentzensen N, White E, Wolk A, Wu AH, Yannoukakos D, Zorn KK, Gayther SA, Antoniou AC, Berchuck A, Goode EL, Chenevix-Trench G, Sellers TA, Pharoah PDP, Zheng W, Long J. A Cancer Res. 2018 Sep 15;78(18):5419-5430. doi: 10.1158/0008-5472.CAN-18-0951. Epub 2018 Jul 27. PubMed PMID: 30054336; PubMed Central PMCID: PMC6139053. https://www.ncbi.nlm.nih.gov/pubmed/30054336
A gene expression model of intrinsic tumor radiosensitivity: prediction of response and prognosis after chemoradiation. Eschrich SA, Pramana J, Zhang H, Zhao H, Boulware D, Lee JH, Bloom G, Rocha-Lima C, Kelley S, Calvin DP, Yeatman TJ, Begg AC, Torres-Roca JF. Int J Radiat Oncol Biol Phys. 2009 Oct 1;75(2):489-96. doi: 10.1016/j.ijrobp.2009.06.014. PMID: 19735873. https://www.ncbi.nlm.nih.gov/pubmed/?term=19735873
Cancer biomarkers--an invitation to the table. Dalton WS, Friend SH. Science. 2006 May 26;312(5777):1165-8. https://www.ncbi.nlm.nih.gov/pubmed/16728629