Browsing by Author "Patel, Jai N."

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    Bevacizumab-induced hypertension and proteinuria: a genome-wide study of more than 1000 patients
    (Springer Nature, 2022) Quintanilha, Julia C.F.; Wang, Jin; Sibley, Alexander B.; Jiang, Chen; Etheridge, Amy S.; Shen, Fei; Jiang, Guanglong; Mulkey, Flora; Patel, Jai N.; Hertz, Daniel L.; Dees, Elizabeth Claire; McLeod, Howard L.; Bertagnolli, Monica; Rugo, Hope; Kindler, Hedy L.; Kelly, William Kevin; Ratain, Mark J.; Kroetz, Deanna L.; Owzar, Kouros; Schneider, Bryan P.; Lin, Danyu; Innocenti, Federico; Medicine, School of Medicine
    Background: Hypertension and proteinuria are common bevacizumab-induced toxicities. No validated biomarkers are available for identifying patients at risk of these toxicities. Methods: A genome-wide association study (GWAS) meta-analysis was performed in 1039 bevacizumab-treated patients of European ancestry in four clinical trials (CALGB 40502, 40503, 80303, 90401). Grade ≥2 hypertension and proteinuria were recorded (CTCAE v.3.0). Single-nucleotide polymorphism (SNP)-toxicity associations were determined using a cause-specific Cox model adjusting for age and sex. Results: The most significant SNP associated with hypertension with concordant effect in three out of the four studies (p-value <0.05 for each study) was rs6770663 (A > G) in KCNAB1, with the G allele increasing the risk of hypertension (p-value = 4.16 × 10-6). The effect of the G allele was replicated in ECOG-ACRIN E5103 in 582 patients (p-value = 0.005). The meta-analysis of all five studies for rs6770663 led to p-value = 7.73 × 10-8, close to genome-wide significance. The most significant SNP associated with proteinuria was rs339947 (C > A, between DNAH5 and TRIO), with the A allele increasing the risk of proteinuria (p-value = 1.58 × 10-7). Conclusions: The results from the largest study of bevacizumab toxicity provide new markers of drug safety for further evaluations. SNP in KCNAB1 validated in an independent dataset provides evidence toward its clinical applicability to predict bevacizumab-induced hypertension.
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    Correction: Bevacizumab-induced hypertension and proteinuria: a genome-wide study of more than 1000 patients
    (Springer Nature, 2022) Quintanilha, Julia C.F.; Wang, Jin; Sibley, Alexander B.; Jiang, Chen; Etheridge, Amy S.; Shen, Fei; Jiang, Guanglong; Mulkey, Flora; Patel, Jai N.; Hertz, Daniel L.; Dees, Elizabeth Claire; McLeod, Howard L.; Bertagnolli, Monica; Rugo, Hope; Kindler, Hedy L.; Kelly, William Kevin; Ratain, Mark J.; Kroetz, Deanna L.; Owzar, Kouros; Schneider, Bryan P.; Lin, Danyu; Innocenti, Federico; Medicine, School of Medicine
    Correction to: British Journal of Cancer 10.1038/s41416-021-01557-w, published online 06 October 2021 The original version of this article unfortunately contained a mistake in an author affiliation. Dr. Kouros Owzar was listed as “Department of Medicine, Indiana University School of Medicine, Indianapolis, IN, USA”, when it should be “Duke Cancer Institute, Duke University Medical Center, Durham, NC, USA”. The original article has been corrected.
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    The Pharmacogenomics Global Research Network Implementation Working Group: global collaboration to advance pharmacogenetic implementation
    (Wolters Kluwer, 2025) Cavallari, Larisa H.; Hicks, J. Kevin; Patel, Jai N.; Elchynski, Amanda L.; Smith, D. Max; Bargal, Salma A.; Fleck, Ashley; Aquilante, Christina L.; Killam, Shayna R.; Lemke, Lauren; Ochi, Taichi; Ramsey, Laura B.; Haidar, Cyrine E.; Ho, Teresa; El Rouby, Nihal; Monte, Andrew A.; Allen, Josiah D.; Beitelshees, Amber L.; Bishop, Jeffrey R.; Bousman, Chad; Campbell, Ronald; Cicali, Emily J.; Cook, Kelsey J.; Duong, Benjamin; Tsermpini, Evangelia Eirini; Girdwood, Sonya Tang; Gregornik, David B.; Grimsrud, Kristin N.; Lamb, Nathan; Lee, James C.; Lopez, Rocio Ortiz; Mazhindu, Tinashe Adrian; Morris, Sarah A.; Nagy, Mohamed; Nguyen, Jenny; Pasternak, Amy L.; Petry, Natasha; van Schaik, Ron H. N.; Schultz, April; Skaar, Todd C.; Al Alshaykh, Hana; Stevenson, James M.; Stone, Rachael M.; Tran, Nam K.; Tuteja, Sony; Woodahl, Erica L.; Yuan, Li-Chi; Lee, Craig R.; Medicine, School of Medicine
    Pharmacogenetics promises to optimize treatment-related outcomes by informing optimal drug selection and dosing based on an individual's genotype in conjunction with other important clinical factors. Despite significant evidence of genetic associations with drug response, pharmacogenetic testing has not been widely implemented into clinical practice. Among the barriers to broad implementation are limited guidance for how to successfully integrate testing into clinical workflows and limited data on outcomes with pharmacogenetic implementation in clinical practice. The Pharmacogenomics Global Research Network Implementation Working Group seeks to engage institutions globally that have implemented pharmacogenetic testing into clinical practice or are in the process or planning stages of implementing testing to collectively disseminate data on implementation strategies, metrics, and health-related outcomes with the use of genotype-guided drug therapy to ultimately help advance pharmacogenetic implementation. This paper describes the goals, structure, and initial projects of the group in addition to implementation priorities across sites and future collaborative opportunities.