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Optimal design of trials to demonstrate the utility of genomically-guided therapy: Putting Precision Cancer Medicine to the test.

ABSTRACT: The new age of Precision Cancer Medicine, with specific biomarkers being used to direct targeted agents, generally concerns only a subset of patients within a certain histopathologically defined tumor type. This paradigm is challenged by the need to perform widespread molecular screening in certified laboratories, with results available to clinicians within reasonable timeframe. Tumor heterogeneity and clonal evolution must be considered in the decision making process. Adaptive and innovative clinical trial designs exploring predictive algorithms and reconsideration of traditional efficacy endpoints are required to rapidly translate scientific discoveries into patient care. Furthermore, international collaboration in cancer research and open discussions on the availability of investigational agents will likely redefine the drug development and approval process in the coming years.

SUBMITTER: Dienstmann R

PROVIDER: S-EPMC5528747 | biostudies-literature | 2015 May

REPOSITORIES: biostudies-literature

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Optimal design of trials to demonstrate the utility of genomically-guided therapy: Putting Precision Cancer Medicine to the test.

Dienstmann Rodrigo R Rodon Jordi J Tabernero Josep J

Molecular oncology 20140715 5

The new age of Precision Cancer Medicine, with specific biomarkers being used to direct targeted agents, generally concerns only a subset of patients within a certain histopathologically defined tumor type. This paradigm is challenged by the need to perform widespread molecular screening in certified laboratories, with results available to clinicians within reasonable timeframe. Tumor heterogeneity and clonal evolution must be considered in the decision making process. Adaptive and innovative cl ...[more]

PMID: 25081646

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Project description:Polygenic risk scores (PRS) have predominantly been derived from genome-wide association studies (GWAS) conducted in European ancestry (EUR) individuals. In this study, we present an in-depth evaluation of PRS based on multi-ancestry GWAS for five cardiometabolic phenotypes in the Penn Medicine BioBank (PMBB) followed by a phenome-wide association study (PheWAS). We examine the PRS performance across all individuals and separately in African ancestry (AFR) and EUR ancestry groups. For AFR individuals, PRS derived using the multi-ancestry LD panel showed a higher effect size for four out of five PRSs (DBP, SBP, T2D, and BMI) than those derived from the AFR LD panel. In contrast, for EUR individuals, the multi-ancestry LD panel PRS demonstrated a higher effect size for two out of five PRSs (SBP and T2D) compared to the EUR LD panel. These findings underscore the potential benefits of utilizing a multi-ancestry LD panel for PRS derivation in diverse genetic backgrounds and demonstrate overall robustness in all individuals. Our results also revealed significant associations between PRS and various phenotypic categories. For instance, CAD PRS was linked with 18 phenotypes in AFR and 82 in EUR, while T2D PRS correlated with 84 phenotypes in AFR and 78 in EUR. Notably, associations like hyperlipidemia, renal failure, atrial fibrillation, coronary atherosclerosis, obesity, and hypertension were observed across different PRSs in both AFR and EUR groups, with varying effect sizes and significance levels. However, in AFR individuals, the strength and number of PRS associations with other phenotypes were generally reduced compared to EUR individuals. Our study underscores the need for future research to prioritize 1) conducting GWAS in diverse ancestry groups and 2) creating a cosmopolitan PRS methodology that is universally applicable across all genetic backgrounds. Such advances will foster a more equitable and personalized approach to precision medicine.

Dataset Information

Optimal design of trials to demonstrate the utility of genomically-guided therapy: Putting Precision Cancer Medicine to the test.

Publications

Optimal design of trials to demonstrate the utility of genomically-guided therapy: Putting Precision Cancer Medicine to the test.

Similar Datasets

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