AACR Project GENIE® data has been widely used to drive impactful cancer research and precision oncology advancements.
Summary, Key Findings and Authors
SUMMARY: Larotrectinib, a selective TRK inhibitor, was evaluated against real‑world standard therapies in patients with advanced solid tumors harboring NTRK gene fusions. In a matched comparative effectiveness study of 164 patients, larotrectinib demonstrated consistently improved outcomes across multiple metrics, including overall survival, time to next treatment, duration of therapy, and progression‑free survival. These advantages were observed after balancing clinical and demographic characteristics between larotrectinib‑treated patients and real‑world controls.
KEY FINDINGS: The study demonstrated that NTRK patients experienced improved overall survival and progression-free survival when treated with larotrectinib; the study also observed longer treatment durations, reinforcing its effectiveness across multiple tumor types harboring TRK fusions.
AUTHORS: Marcia S Brose, C Benedikt Westphalen, Xiaoyun Pan, Vadim Bernard-Gauthier, Milena Kurtinecz, Helen Guo, Virginie Aris, Neil R Brett, Abdelali Majdi, Vivek Subbiah, Nathan A Pennell, Kenneth L Kehl, Alexander Drilon
Summary, Key Findings and Authors
SUMMARY: The GENIE BPC is a precompetitive collaborative with industry partners and international sites to generate high-quality clinicogenomic data across ten solid cancer cohorts. Through standardized data collection and quality control across institutions, the GENIE Biopharma Collaborative provides a scalable real-world evidence platform for precision oncology and translational research.
KEY FINDINGS: Early analyses have identified resistance mutations and metastasis associated drivers, and upcoming automation efforts will further expand data scale and depth.
AUTHORS: A. Acebedo, P.L. Bedard, S. Brown 3, E. Ceca 4, M. Fiandalo 1, H. Fuchs 3, X. Guo 5, J.N. Hoppe 1, K.L. Kehl 4, R. Kundra 3, J.A. Lavery 3, M.L. LeNoue-Newton 6, E. Lepisto 4, B. Mastrogiacomo 3, C.M. Micheel 6, C. Nayan 5, A. Newcomb 4, C. Nichols 3, K.S. Panageas 3, B. Piening 7, S. Pillai 3, A. Postle 4, R. Potter 6, G.J. Riely 3, H. Rizvi 3, J. Rudolph 3, D. Schrag 3, S.M. Sweeney 1, E.A. Sweet-Cordero 8, M. Turski 8, E. Wingord 8, T.J. Wu 1, T. Yu 5, C. Yu 2
Summary, Key Findings and Authors
SUMMARY: This study examined how the timing of next-generation sequencing (NGS) in real-world oncology practice is influenced by patient and disease factors, using clinicogenomic data from more than 7,000 patients across six cancer types. NGS was performed significantly sooner in patients experiencing progressive disease, highlighting how clinical deterioration drives testing and can introduce bias into biomarker–survival analyses.
KEY FINDINGS: NGS tended to be performed earlier in patients whose disease was actively progressing, showing that clinical deterioration strongly drives testing decisions in real-world practice. This timing effect can introduce bias into biomarker–survival analyses, emphasizing the need to account for when testing occurs when interpreting clinicogenomic outcomes.
AUTHORS: Kenneth L. Kehl, MD, MPH , Jessica A. Lavery, MS , Samantha Brown, MS , Hannah Fuchs, MSPH , Gregory Riely, MD, PhD , Deborah Schrag, MD, MPH , Ashley Newcomb, MPH, Chelsea Nichols, MPH, Christine M. Micheel, PhD , Philippe L. Bedard, MD , Shawn M. Sweeney, PhD, Michael Fiandalo, PhD, MBA, PMP, and Katherine S. Panageas, DrPH, on behalf of the AACR Project GENIE BPC Core Team
Summary, Key Findings and Authors
SUMMARY: Using real world GENIE data, this study examined treatment approaches and outcomes for patients with metastatic castration-resistant prostate cancer (mCRPC) who carry homologous recombination repair (HRR) gene mutations. It showed that patients received a variety of first-line and later therapies, and clinical outcomes varied across specific HRR alterations, offering insight into how these mutations may influence treatment response. These findings support the importance of molecular profiling to better understand disease behavior and guide therapy decisions in HRR-mutated mCRPC.
KEY FINDINGS: Molecular profiling of metastatic castration-resistant‑resistant prostate cancer revealed that patients with homologous recombination repair (HRR) mutations receive diverse treatment regimens, and their clinical outcomes differ meaningfully by specific HRR gene alterations.
AUTHORS: Priyanka J. Bobbili ∙ Jasmina Ivanova ∙ David B. Solit ∙ Niharika B. Mettu ∙ Shannon J. McCall ∙ Mallika Dhawan ∙ Maral DerSarkissian ∙ Bhakti Arondekar ∙ Jane Chang ∙ Alexander Niyazov ∙ Jocelyn Lee ∙ Risha Huq ∙ Michelle Green ∙ Michelle Turski ∙ Phu Lam ∙ Aruna Muthukumar ∙ Tracy Guo ∙ Manasi Mohan ∙ Adina Zhang ∙ Mei Sheng Duh ∙ William K. Oh
Summary, Key Findings and Authors
SUMMARY: Peritoneal metastases (PM) occur in nearly one‑fifth of patients with metastatic colorectal cancer and are associated with distinct clinical and molecular features. Patients with PM were more often female, had higher‑grade tumors, and were less likely to have rectal primary tumors compared with those without PM. Genomically, APC mutations were less common and MED12 alterations more frequent in the PM group. Although progression‑free survival on first‑line therapy was similar, overall survival was significantly shorter for patients with PM, highlighting their poorer prognosis.
KEY FINDINGS: Patients with PM exhibit unique clinical and genomic characteristics, including higher‑grade tumors and distinct mutation patterns such as fewer APC and more MED12 alterations. PM is associated with significantly worse overall survival, underscoring it as a biologically and clinically distinct high‑risk subgroup in metastatic colorectal cancer.
AUTHORS: Enrique Sanz-Garcia Samantha Brown Jessica A. Lavery Jessica Weiss Hannah E. Fuchs Ashley Newcomb Asha Postle Jeremy L. Warner Michele L. LeNoue-Newton Shawn M. Sweeney Shirin Pillai Celeste Yu Chelsea Nichols Brooke Mastrogiacomo Ritika Kundra Nikolaus Schultz Kenneth L. Kehl Gregory J. Riely Deborah Schrag Anand Govindarajan Katherine S. Panageas Philippe L. Bedard Corresponding Author
Summary, Key Findings and Authors
SUMMARY: New enhancements to cBioPortal enable researchers to more effectively explore linked longitudinal genomic and clinical data from GENIE. To support deeper exploration of these linked datasets, cBioPortal has been significantly enhanced to enable patient-level visualization of clinical timelines, filtering based on treatment status, and survival analyses by specific regimens. These upgraded capabilities allow researchers to interactively examine complex clinicogenomic relationships and generate new hypotheses around therapeutic response and prognostic markers.
KEY FINDINGS: Enhanced cBioPortal functionalities now allow users to visualize and analyze longitudinal clinicogenomic data, including treatment sequences and outcomes, in a dynamic and patient-centered way. These improvements expand the utility of AACR Project GENIE Biopharma Collaborative data and support more robust discovery of genomic predictors of prognosis and treatment sensitivity.
AUTHORS: Ino de Bruijn Corresponding Author Ritika Kundra Brooke Mastrogiacomo Thinh Ngoc Tran Luke Sikina Tali Mazor Xiang Li Angelica Ochoa Gaofei Zhao Bryan Lai Adam Abeshouse Diana Baiceanu Ersin Ciftci Ugur Dogrusoz Andrew Dufilie Ziya Erkoc Elena Garcia Lara Zhaoyuan Fu Benjamin Gross Charles Haynes Allison Heath David Higgins Prasanna Jagannathan Karthik Kalletla Priti Kumari James Lindsay Aaron Lisman Bas Leenknegt Pieter Lukasse Divya Madela Ramyasree Madupuri Pim van Nierop Oleguer Plantalech Joyce Quach Adam C. Resnick Sander Y.A. Rodenburg Baby A. Satravada Fedde Schaeffer Robert Sheridan Jessica Singh Rajat Sirohi Selcuk Onur Sumer Sjoerd van Hagen Avery Wang Manda Wilson Hongxin Zhang Kelsey Zhu Nicole Rusk Samantha Brown Jessica A. Lavery Katherine S. Panageas Julia E. Rudolph Michele L. LeNoue-Newton Jeremy L. Warner Xindi Guo Haley Hunter-Zinck Thomas V. Yu Shirin Pilai Chelsea Nichols Stuart M. Gardos John Philip AACR Project GENIE BPC Core Team, AACR Project GENIE Consortium; Kenneth L. Kehl Gregory J. Riely Deborah Schrag Jocelyn Lee Michael V. Fiandalo Shawn M. Sweeney Trevor J. Pugh Chris Sander Ethan Cerami Jianjiong Gao Nikolaus Schultz
Summary, Key Findings and Authors
SUMMARY: This study presents a deeply curated real world dataset of 1,846 patients with non–small cell lung cancer (NSCLC) from four institutions contributing to the AACR Project GENIE Biopharma Collaborative. The cohort demonstrated substantial genomic diversity, with 44% of tumors harboring actionable oncogenic drivers such as EGFR mutations, KRAS G12C, and ALK/RET/ROS1 fusions. Clinical outcomes were evaluated using standardized, longitudinal data, showing a median overall survival of 17.4 months for patients receiving first line platinum-based chemotherapy without immunotherapy.
KEY FINDINGS: The cohort revealed a high prevalence of actionable genomic alterations, underscoring the importance of molecular profiling in shaping treatment strategies. Survival outcomes from standard first‑line chemotherapy provide a valuable real‑world benchmark for evaluating and contextualizing emerging therapies in NSCLC.
AUTHORS: Noura J Choudhury , Jessica A Lavery , Samantha Brown , Ino de Bruijn , Justin Jee , Thinh Ngoc Tran , Hira Rizvi , Kathryn C Arbour , Karissa Whiting , Ronglai Shen , Matthew Hellmann , Philippe L Bedard , Celeste Yu , Natasha Leighl , Michele LeNoue-Newton , Christine Micheel , Jeremy L Warner , Michelle S Ginsberg , Andrew Plodkowski , Jeffrey Girshman , Peter Sawan , Shirin Pillai , Shawn M Sweeney , Kenneth L Kehl , Katherine S Panageas , Nikolaus Schultz , Deborah Schrag , Gregory J Riely ; AACR GENIE BPC Core Team
Summary, Key Findings and Authors
SUMMARY: The GENIE Biopharma Collaborative (BPC) dataset links rich clinical information with high throughput sequencing data across multiple institutions and cancer types, creating a deeply annotated resource for precision oncology research. To aid in analysis of this data, the authors developed the {genieBPC} R package, a user friendly pipeline that streamlines data cleaning, integration, and cohort construction. This tool enables researchers to efficiently generate analysis ready clinicogenomic datasets suitable for modeling, outcomes research, and translational studies.
KEY FINDINGS: The {genieBPC} R package provides a streamlined, standardized workflow for transforming complex GENIE BPC datasets into cohesive analytic cohorts. This functionality reduces technical barriers and accelerates the use of GENIE BPC data for clinicogenomic research in oncology.
AUTHORS: Jessica A Lavery , Samantha Brown , Michael A Curry , Axel Martin , Daniel D Sjoberg , Karissa Whiting
Summary, Key Findings and Authors
SUMMARY: Across more than 66,000 tumors, RAS mutations show clear differences by cancer type and patient characteristics, with each RAS variant displaying its own pattern of accompanying genetic alterations and mutational processes. These genotype‑specific features shape tumor behavior—including gene‑expression programs, immune microenvironment states, and treatment responses such as immunotherapy outcomes in KRAS G12C–mutant lung cancer. Together, the findings highlight biologically meaningful distinctions among RAS‑mutant tumors that point to opportunities for more precise, mutation‑informed therapeutic strategies.
KEY FINDINGS: RAS‑mutant tumors exhibit highly lineage‑ and allele‑specific genomic and phenotypic features, including distinct co‑mutation patterns and tumor microenvironment states. These differences point to therapeutically relevant vulnerabilities that may guide rational combinations of RAS‑targeted agents with other targeted or immunotherapy strategies.
AUTHORS: Robert B Scharpf , Archana Balan , Biagio Ricciuti , Jacob Fiksel , Christopher Cherry , Chenguang Wang , Michele L Lenoue-Newton , Hira A Rizvi , James R White , Alexander S Baras , Jordan Anaya , Blair V Landon , Marta Majcherska-Agrawal , Paola Ghanem , Jocelyn Lee , Leon Raskin , Andrew S Park , Huakang Tu , Hil Hsu , Kathryn C Arbour , Mark M Awad , Gregory J Riely , Christine M Lovly , Valsamo Anagnostou
Summary, Key Findings and Authors
SUMMARY: With more than 110,000 tumors from over 100,000 patients, the Project GENIE registry enables researchers to study real‑world genomic patterns across many cancer types. The data have already been used to predict eligibility for genome‑guided clinical trials, uncover driver mutations in rare cancers, and identify tumor types that may benefit from more comprehensive genomic testing. Project GENIE’s expanding infrastructure—including the addition of new data types like cell‑free DNA—continues to strengthen its role as a global precision‑medicine resource.
KEY FINDINGS: Project GENIE’s large, harmonized dataset enables new insights into clinical trial matching, rare‑tumor genomics, and unmet needs in cancer types lacking actionable mutations. The registry continues to expand as a powerful, real‑world platform supporting precision oncology research worldwide.
AUTHORS: Trevor J. Pugh Corresponding Author Jonathan L. Bell Jeff P. Bruce Gary J. Doherty Matthew Galvin Michelle F. Green Haley Hunter-Zinck Priti Kumari Michele L. Lenoue-Newton Marilyn M. Li James Lindsay Tali Mazor Andrea Ovalle Stephen-John Sammut Nikolaus Schultz Thomas V. Yu Shawn M. Sweeney Brady Bernard Corresponding Author for the AACR Project GENIE Consortium, Genomics and Analysis Working Group
Summary, Key Findings and Authors
SUMMARY: This multi institutional retrospective study explored whether ERBB2 (HER2) mutations influence prognosis or tumor characteristics in hormone receptor–positive, HER2 negative metastatic breast cancer and found no differences in overall survival compared with matched ERBB2–wild type cases. Tumors with ERBB2 mutations showed a higher frequency of lobular histology and distinct co mutation patterns—including more CDH1 alterations and fewer ESR1 mutations—while exhibiting similar responses to endocrine therapy and similar time to progression as ERBB2–wild type tumors.
KEY FINDINGS: ERBB2 mutations did not adversely impact survival or treatment response in hormone receptor–positive, HER2 negative metastatic breast cancer. Subtle genomic differences, such as more frequent CDH1 mutations, suggest biological distinctions but do not appear to alter clinical outcomes in this setting.
AUTHORS: Michele L. LeNoue-Newton ; Sheau-Chiann Chen ; Thomas Stricker; David M. Hyman; Natalie Blauvelt; Philippe L. Bedard ; Funda Meric-Bernstam ; Rinaa S. Punglia; Deborah Schrag; Eva M. Lepisto; Fabrice Andre ; Lillian Smyth ; Semih Dogan ; Celeste Yu; Chetna Wathoo; Mia Levy ; Lisa D. Eli; Feng Xu; Grace Mann; Alshad S. Lalani; Fei Ye; Christine M. Micheel ; Monica Arnedos on behalf of AACR Project GENIE Consortium
Summary, Key Findings and Authors
SUMMARY: This study evaluates how delayed entry into clinicogenomic datasets—caused by the time between cancer diagnosis and genomic testing—introduces left truncation and can bias survival analyses. Patients must survive long enough to undergo sequencing, which leads to systematic exclusion of those with early mortality and consequently inflates observed survival. This study outlines statistical approaches that appropriately adjust for delayed entry to yield more accurate and generalizable survival estimates.
KEY FINDINGS: Delayed study entry produces substantial left truncation bias in real world clinicogenomic datasets, leading to inflated survival estimates if unaddressed. Proper adjustment methods are essential to ensure valid, generalizable conclusions from real world oncology data
AUTHORS: Samantha Brown , Jessica A Lavery , Ronglai Shen , Axel S Martin , Kenneth L Kehl , Shawn M Sweeney , Eva M Lepisto , Hira Rizvi , Caroline G McCarthy , Nikolaus Schultz , Jeremy L Warner , Ben Ho Park , Philippe L Bedard , Gregory J Riely , Deborah Schrag , Katherine S Panageas ; AACR Project GENIE Consortium
Summary, Key Findings and Authors
SUMMARY: This study describes the development of a scalable, multi‑institution quality assurance process for curating electronic health record (EHR) data within the AACR Project GENIE Biopharma Collaborative. Four participating institutions constructed an observational oncology cohort and implemented a rigorous, transparent quality framework to ensure the accuracy and reliability of curated clinical data. The process included feasibility testing, programmatic validation against source data, systematic error correction, curator retraining, and reproducibility checks through double curation and code review. These measures collectively strengthened confidence that GENIE BPC data are robust enough to support research and inform clinical decision‑making in precision oncology. [europepmc.org]
KEY FINDINGS: The study demonstrates that a structured, transparent quality assurance framework can reliably produce high quality, reproducible EHR derived clinical data across institutions. These processes collectively strengthened confidence that GENIE BPC data are robust enough to support research and inform clinical decision‑making in precision oncology.
AUTHORS: Jessica A. Lavery, MS , Eva M. Lepisto, MA, MSc, Samantha Brown, MS , Hira Rizvi, BA, Caroline McCarthy, MPH, Michele LeNoue-Newton, PhD, Celeste Yu, MS , Jasme Lee, MS, Xindi Guo, BS , Thomas Yu, BS , Julia Rudolph, MPA, Shawn Sweeney, PhD, AACR Project GENIE Consortium, Ben Ho Park, MD, PhD , Jeremy L. Warner, MS , Philippe L. Bedard, MD , Gregory Riely, MD, PhD , Deborah Schrag, MD, MPH, and Katherine S. Panageas, DrPH
Summary, Key Findings and Authors
SUMMARY: This study evaluated which real‑world surrogate endpoints best reflect overall survival in patients with advanced non–small cell lung cancer or colorectal cancer whose tumors underwent genomic profiling. By comparing several candidate measures, the researchers found that progression‑free survival—when progression was confirmed by both radiologist review and medical oncologist assessment—showed the strongest correlation with overall survival. Measures like time to treatment discontinuation or time to next treatment were less reliable, showing weaker associations with survival outcomes.
KEY FINDINGS: Progression‑free survival confirmed by both radiology and oncology assessments was the surrogate endpoint most closely aligned with overall survival. Endpoints based on treatment timing alone were less robust, suggesting that carefully defined PFS may be the most reliable surrogate end point for observational studies using linked genomic and clinical data.
AUTHORS: Kenneth L. Kehl, MD, MPH; Gregory J. Riely, MD, PhD; Eva M. Lepisto, MA, MSc Jessica A. Lavery, MS; Jeremy L. Warner, MD, MS; Michele L. LeNoue-Newton, PhD; Shawn M. Sweeney, PhD; Julia E. Rudolph, MPA; Samantha Brown, MS; Celeste Yu, MS; Philippe L. Bedard, MD; Deborah Schrag, MD, MPH; Katherine S. Panageas, DrPH; for the American Association of Cancer Research (AACR) Project Genomics Evidence Neoplasia Information Exchange (GENIE) Consortium
Summary, Key Findings and Authors
SUMMARY: This study used clinical and genomic data from 956 patients with stage II–IV NSCLC to identify factors associated with later development of brain metastases. Etoposide use, Asian race, baseline bone metastases, and alterations in TP53, EGFR, and ERBB2—were all linked to a higher risk of developing brain metastases. Lower risk features included older age and mutations in NOTCH1 and KRAS. Machine learning models using these variables achieved moderate predictive accuracy, with ridge regression performing best (AUC 0.73).
KEY FINDINGS: Several genomic alterations and clinical factors were strongly associated with brain metastasis risk in NSCLC, and a ridge regression model achieved moderate predictive accuracy. These results point toward identifiable high risk subgroups who may benefit from targeted surveillance strategies and CNS active treatments.
AUTHORS: Protiva Rahman, Michele LeNoue-Newton, Sandip Chaugai, Marilyn Holt, Neha M Jain, Christina Maxwell, Christine Micheel, Yuanchu J Yang, Cheng Ye, Nikolaus Schultz, Gregory J. Riely, Caroline G. McCarthy, Hira Rizvi, Deborah Schrag, Kenneth L. Kehl, Eva M Lepisto, Celeste Yu, Philippe L. Bedard, Daniel Fabbri, and Jeremy Lyle Warner
Summary, Key Findings and Authors
SUMMARY: As collaborative data sharing efforts grow, genomic and clinical datasets often rely on multiple evolving classification systems, creating challenges in mapping data elements consistently. To address this, the GENIE team developed the Linked Entity Attribute Pair (LEAP) framework to support iterative, transparent, and reusable mapping across systems such as OncoTree and ICD O 3. The LEAP framework streamlined how Project GENIE maps data elements to the NCI Genomic Data Commons, resolving 195 mapping issues and reducing mapping effort by 28%. This harmonization infrastructure enables more efficient data sharing while maintaining the integrity and traceability of clinical and genomic terms.
KEY FINDINGS: Implementing LEAP reduced mapping errors, streamlined remediation of inconsistent mappings, and significantly accelerated the data‑submission process to external repositories like the NCI’s Genomic Data Commons. By enabling iterative, reusable mappings and tracking changes over time, LEAP cut the time needed to align cancer ontologies from months to under a week and provides a more efficient, transparent process for harmonizing evolving classification systems.
AUTHORS: Stacy Thomas, MS , Tara Lichtenberg, BA, Kristen Dang, PhD, Michael Fitzsimons, PhD, Robert L. Grossman, PhD, Ritika Kundra, MS, Jessica A. Lavery, MS, Michele L. Lenoue-Newton, PhD, Katherine S. Panageas, DrPH, Charles Sawyers, MD, Nikolaus D. Schultz, PhD, Sahussapont J. Sirintrapun, MD, Umit Topaloglu, PhD, Angelica Welch, BA, Thomas Yu, BS, Ahmet Zehir, PhD, and Stuart Gardos, BA
Summary, Key Findings and Authors
SUMMARY: This study compared clinical outcomes in patients with metastatic breast cancer carrying the rare AKT1E17K mutation versus matched AKT1–wild‑type cases. Overall survival was similar between the two groups, indicating that the AKT1E17K mutation does not independently worsen prognosis. The analysis also revealed that AKT1‑mutant tumors had longer durations on mTOR inhibitor therapy, a finding not previously recognized due to the rarity of the mutation. Other clinical and treatment characteristics were largely comparable, demonstrating the value of large clinicogenomic registries for studying rare genomic subsets.
KEY FINDINGS: AKT1E17K‑mutant metastatic breast cancer showed no difference in overall survival compared with AKT1‑wild‑type disease, but patients with the mutation remained on mTOR inhibitors longer. These results illustrate how large real‑world datasets can clarify the natural history and therapeutic patterns of rare genomic subtypes.
AUTHORS: Lillian M. Smyth ; Qin Zhou; Bastien Nguyen; Celeste Yu; Eva M. Lepisto; Monica Arnedos ; Michael J. Hasset; Michele L. Lenoue-Newton; Natalie Blauvelt; Semih Dogan; Christine M. Micheel ; Chetna Wathoo; Hugo Horlings ; Jan Hudecek; Benjamin E. Gross; Ritika Kundra ; Shawn M. Sweeney ; JianJiong Gao; Nikolaus Schultz; Andrew Zarski; Stuart M. Gardos; Jocelyn Lee; Seth Sheffler-Collins; Ben H. Park; Charles L. Sawyers ; Fabrice André; Mia Levy ; Funda Meric-Bernstam; Philippe L. Bedard ; Alexia Iasonos; Deborah Schrag; David M. Hyman for the AACR Project GENIE Consortium
Summary, Key Findings and Authors
SUMMARY: This article outlines the creation, growth, and early implementation of Project GENIE – including how the project was conceived, how participating institutions collaborated to build the infrastructure, and the operational lessons learned while preparing the first data release consisting of more than 18,000 tumor samples. Contributors describe how challenges in data harmonization, governance, and coordination across institutions were addressed to enable successful data sharing. The article emphasizes how collective commitment and cross‑disciplinary teamwork set the foundation for the project’s ongoing expansion and impact.
KEY FINDINGS: Early experiences from the Project GENIE consortium highlight the critical importance of robust data harmonization practices, cross‑institution coordination, and transparent governance to enable large‑scale genomic data sharing. The project’s successful first data release demonstrates the feasibility and value of multi‑institutional collaboration in building sustainable clinicogenomic resources.
AUTHORS: Christine M. Micheel, Shawn M. Sweeney, Michele L. LeNoue-Newton, Fabrice André, Philippe L. Bedard, Justin Guinney, Gerrit A. Meijer, Barrett J. Rollins, Charles L. Sawyers, Nikolaus Schultz, Kenna R. Mills Shaw, Victor E. Velculescu, and Mia A. Levy , on behalf of the AACR Project GENIE
Summary, Key Findings and Authors
SUMMARY: This paper reports early findings from Project GENIE’s first public dataset of roughly 19,000 tumor samples, demonstrating the consortium’s ability to harmonize real‑world clinicogenomic data across multiple international cancer centers. The consortium established standardized processes, data structures, and governance models to enable large‑scale, harmonized data sharing. High‑level analyses showed that more than 30% of tumors carried potentially actionable alterations, and Project GENIE data accurately predicted accrual patterns for precision medicine trials such as NCI‑MATCH. These results highlight the value of large, standardized real‑world genomic datasets for informing clinical research and guiding precision oncology.
KEY FINDINGS: Initial Project GENIE data releases show that large‑scale, harmonized real‑world genomic datasets can reliably inform clinical actionability and trial matching across tumor types. The consortium’s scalable framework positions Project GENIE as a cornerstone resource for precision oncology research and implementation.
AUTHORS: The AACR Project GENIE Consortium; Fabrice André; Monica Arnedos; Alexander S. Baras; José Baselga; Philippe L. Bedard; Michael F. Berger; Mariska Bierkens; Fabien Calvo; Ethan Cerami; Debyani Chakravarty; Kristen K. Dang; Nancy E. Davidson; Catherine Del Vecchio Fitz; Semih Dogan; Raymond N. DuBois; Matthew D. Ducar; P. Andrew Futreal; Jianjiong Gao; Francisco Garcia; Stu Gardos; Christopher D. Gocke; Benjamin E. Gross; Justin Guinney; Zachary J. Heins; Stephanie Hintzen; Hugo Horlings; Jan Hudeček; David M. Hyman; Suzanne Kamel-Reid; Cyriac Kandoth; Walter Kinyua; Priti Kumari; Ritika Kundra; Marc Ladanyi; Céline Lefebvre; Michele L. LeNoue-Newton; Eva M. Lepisto; Mia A. Levy; Neal I. Lindeman; James Lindsay; David Liu; Zhibin Lu; Laura E. MacConaill; Ian Maurer; David S. Maxwell; Gerrit A. Meijer; Funda Meric-Bernstam; Christine M. Micheel; Clinton Miller; Gordon Mills; Nathanael D. Moore; Petra M. Nederlof; Larsson Omberg; John A. Orechia; Ben Ho Park; Trevor J. Pugh; Brendan Reardon; Barrett J. Rollins; Mark J. Routbort; Charles L. Sawyers; Deborah Schrag; Nikolaus Schultz; Kenna R Mills Shaw; Priyanka Shivdasani; Lillian L. Siu; David B. Solit; Gabe S. Sonke; Jean Charles Soria; Parin Sripakdeevong; Natalie H. Stickle; Thomas P. Stricker; Shawn M. Sweeney; Barry S. Taylor; Jelle J. ten Hoeve; Stacy B. Thomas; Eliezer M. Van Allen; Laura J. Van 'T Veer; Tony van de Velde; Harm van Tinteren; Victor E. Velculescu; Carl Virtanen; Emile E. Voest; Lucy L. Wang; Chetna Wathoo; Stuart Watt; Celeste Yu; Thomas V. Yu; Emily Yu; Ahmet Zehir; Hongxin Zhang