UT MD Anderson Cancer Center Department of Genomic Medicine Lipoasarcoma Data Access Committee
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PROVIDER: EGAC00001000821 | EGA |
REPOSITORIES: EGA
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Project description:Data Access Committee EGAC00001001252
| EGAC00001001252 | EGA
Project description:PURPOSE:We initiated a personalized medicine program in the context of early clinical trials, using targeted agents matched with tumor molecular aberrations. Herein, we report our observations. PATIENT AND METHODS:Patients with advanced cancer were treated in the Clinical Center for Targeted Therapy. Molecular analysis was conducted in the MD Anderson Clinical Laboratory Improvement Amendments (CLIA)-certified laboratory. Patients whose tumors had an aberration were treated with matched targeted therapy, when available. Treatment assignment was not randomized. The clinical outcomes of patients with molecular aberrations treated with matched targeted therapy were compared with those of consecutive patients who were not treated with matched targeted therapy. RESULTS:Of 1,144 patients analyzed, 460 (40.2%) had 1 or more aberration. In patients with 1 molecular aberration, matched therapy (n = 175) compared with treatment without matching (n = 116) was associated with a higher overall response rate (27% vs. 5%; P < 0.0001), longer time-to-treatment failure (TTF; median, 5.2 vs. 2.2 months; P < 0.0001), and longer survival (median, 13.4 vs. 9.0 months; P = 0.017). Matched targeted therapy was associated with longer TTF compared with their prior systemic therapy in patients with 1 mutation (5.2 vs. 3.1 months, respectively; P < 0.0001). In multivariate analysis in patients with 1 molecular aberration, matched therapy was an independent factor predicting response (P = 0.001) and TTF (P = 0.0001). CONCLUSION:Keeping in mind that the study was not randomized and patients had diverse tumor types and a median of 5 prior therapies, our results suggest that identifying specific molecular abnormalities and choosing therapy based on these abnormalities is relevant in phase I clinical trials.
| S-EPMC4454458 | biostudies-literature
Project description:Organisation EGAO00000000306
| EGAO00000000306 | EGA
Project description:Clinical heterogeneity of gastric cancer reflected in unequal outcome of treatment is poorly defined in molecular level, and molecular subtypes and their associated biomarkers have not been established to improve prognostification and treatment of gastric cancer. Using microarray technologies, we analyzed gene expression profiling data from patients with advanced gastric cancer and uncovered potential prognostic subtypes and identify gene expression signature associated with prognosis.
2012-04-30 | GSE28541 | GEO
Project description:Clinical heterogeneity of gastric cancer reflected in unequal outcome of treatment is poorly defined in molecular level, and molecular subtypes and their associated biomarkers have not been established to improve prognostification and treatment of gastric cancer. Using microarray technologies, we analyzed gene expression profiling data from patients with advanced gastric cancer and uncovered potential prognostic subtypes and identify gene expression signature associated with prognosis. Using microarray technologies, we analyzed gene expression profiling data from patients with advanced gastric cancer and uncovered potential prognostic subtypes and identify gene expression signature associated with prognosis.
2012-04-29 | E-GEOD-28541 | biostudies-arrayexpress
Project description:BACKGROUND/AIMS:In our 2009 article, we showed that Bayesian methods had established a foothold in developing therapies in our institutional oncology trials. In this article, we will document what has happened since that time. In addition, we will describe barriers to implementing Bayesian clinical trials, as well as our experience overcoming them. METHODS:We reviewed MD Anderson Cancer Center clinical trials submitted to the institutional protocol office for scientific and ethical review between January 2009 and December 2013, the same length time period as the previous article. We tabulated Bayesian methods implemented for design or analyses for each trial and then compared these to our previous findings. RESULTS:Overall, we identified 1020 trials and found that 283 (28%) had Bayesian components so we designated them as Bayesian trials. Among MD Anderson-only and multicenter trials, 56% and 14%, respectively, were Bayesian, higher rates than our previous study. Bayesian trials were more common in phase I/II trials (34%) than in phase III/IV (6%) trials. Among Bayesian trials, the most commonly used features were for toxicity monitoring (65%), efficacy monitoring (36%), and dose finding (22%). The majority (86%) of Bayesian trials used non-informative priors. A total of 75 (27%) trials applied Bayesian methods for trial design and primary endpoint analysis. Among this latter group, the most commonly used methods were the Bayesian logistic regression model (N?=?22), the continual reassessment method (N?=?20), and adaptive randomization (N?=?16). Median institutional review board approval time from protocol submission was the same 1.4?months for Bayesian and non-Bayesian trials. Since the previous publication, the Biomarker-Integrated Approaches of Targeted Therapy for Lung Cancer Elimination (BATTLE) trial was the first large-scale decision trial combining multiple treatments in a single trial. Since then, two regimens in breast cancer therapy have been identified and published from the cooperative Investigation of Serial Studies to Predict Your Therapeutic Response with Imaging and Molecular Analysis (I-SPY 2), enhancing cooperation among investigators and drug developers across the nation, as well as advancing information needed for personalized medicine. Many software programs and Shiny applications for Bayesian trial design and calculations are available from our website which has had more than 21,000 downloads worldwide since 2004. CONCLUSION:Bayesian trials have the increased flexibility in trial design needed for personalized medicine, resulting in more cooperation among researchers working to fight against cancer. Some disadvantages of Bayesian trials remain, but new methods and software are available to improve their function and incorporation into cancer clinical research.
| S-EPMC6904523 | biostudies-literature
Project description:Data Access Committee EGAC00001002802
| EGAC00001002802 | EGA
Project description:PurposeGenomic profiling is increasingly used in the management of cancer. We have previously reported preliminary results of our precision medicine program. Here, we present response and survival outcomes for 637 additional patients who were referred for phase I trials and were treated with matched targeted therapy (MTT) when available.Patients and methodsPatients with advanced cancer who underwent tumor genomic analyses were treated with MTT when available.ResultsOverall, 1,179 (82.1%) of 1,436 patients had one or more alterations (median age, 59.7 years; men, 41.2%); 637 had one or more actionable aberrations and were treated with MTT (n = 390) or non-MTT (n = 247). Patients who were treated with MTT had higher rates of complete and partial response (11% v 5%; P = .0099), longer failure-free survival (FFS; 3.4 v 2.9 months; P = .0015), and longer overall survival (OS; 8.4 v 7.3 months; P = .041) than did unmatched patients. Two-month landmark analyses showed that, for MTT patients, FFS for responders versus nonresponders was 7.6 versus 4.3 months (P < .001) and OS was 23.4 versus 8.5 months (P < .001), whereas for non-MTT patients (responders v nonresponders), FFS was 6.6 versus 4.1 months (P = .001) and OS was 15.2 versus 7.5 months (P = .43). Patients with phosphatidylinositol 3-kinase (PI3K) and mitogen-activated protein kinase pathway alterations matched to PI3K/Akt/mammalian target of rapamycin axis inhibitors alone demonstrated outcomes comparable to unmatched patients.ConclusionOur results support the use of genomic matching. Subset analyses indicate that matching patients who harbor a PI3K and mitogen-activated protein kinase pathway alteration to only a PI3K pathway inhibitor does not improve outcome. We have initiated IMPACT2, a randomized trial to compare treatment with and without genomic selection.
| S-EPMC5659750 | biostudies-literature
Project description:Data Access Committee EGAC00001000324
| EGAC00001000324 | EGA
Project description:In 2006, a remarkable collaboration between University of Texas MD Anderson Cancer Center clinicians and Texas and New Mexico State legislators led to the formation of a dedicated IBC Research Program and Clinic at MD Anderson. This initiative provided funding and infrastructure to foster coordination of an IBC World Consortium of national and international experts, and launch the first ever IBC international conference in 2008, which brought together experts from around the world to facilitate collaborations and accelerate progress. Indeed great progress has been made since then. National and international experts in IBC convened at the 10th Anniversary Conference of the MD Anderson IBC Clinic and Research Program and presented the most extensive sequencing analysis to date comparing IBC to non-IBC, gene- and protein-based immunoprofiling of IBC versus non-IBC patients, and converging lines of evidence on the specific role of the microenvironment in IBC. Novel models, unique metabolic mechanisms, and prominent survival pathways have been identified and were presented. Multiple clinical trials based on the work of the last decade are in progress or in development. The important challenges ahead were discussed. This progress and a coordinated summary of these works are presented herein.
| S-EPMC5687177 | biostudies-literature