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Abernethy A.,Duke University | Abrahams E.,Personalized Medicine Coalition | Barker A.,Arizona State University | Buetow K.,Arizona State University | And 11 more authors.
Clinical Cancer Research | Year: 2014

An ever-expanding understanding of the molecular basis of the more than 200 unique diseases collectively called cancer, combined with efforts to apply these insights to clinical care, is forming the foundation of an era of personalized medicine that promises to improve cancer treatment. At the same time, these extraordinary opportunities are occurring in an environment of intense pressure to contain rising healthcare costs. This environment presents a challenge to oncology research and clinical care, because both are becoming progressively more complex and expensive, and because the current tools to measure the cost and value of advances in care (e.g., comparative effectiveness research, cost-effectiveness analysis, and health technology assessments) are not optimized for an ecosystem moving toward personalized, patient-centered care. Reconciling this tension will be essential to maintaining progress in a cost-constrained environment, especially because emerging innovations in science (e.g., increasing identification of molecular biomarkers) and in clinical process (implementation of a learning healthcare system) hold potential to dramatically improve patient care, and may ultimately help address the burden of rising costs. For example, the rapid pace of innovation taking place within oncology calls for increased capability to integrate clinical research and care to enable continuous learning, so that lessons learned from each patient treated can inform clinical decision making for the next patient. Recognizing the need to define the policies required for sustained innovation in cancer research and care in an era of cost containment, the stakeholder community must engage in an ongoing dialogue and identify areas for collaboration. This article reflects and seeks to amplify the ongoing robust discussion and diverse perspectives brought to this issue by multiple stakeholders within the cancer community, and to consider how to frame the research and regulatory policies necessary to sustain progress against cancer in an environment of constrained resources. © 2014 AACR.


Hertz D.L.,University of Michigan | McLeod H.L.,Personalized Medicine Institute | McLeod H.L.,DeBartolo Family Personalized Medicine Institute
Clinical Cancer Research | Year: 2014

The patient (germline) genome can influence the pharmacokinetics and pharmacodynamics of cancer therapy. The field of pharmacogenetics (PGx) has primarily focused on genetic predictors of pharmacokinetics, largely ignoring pharmacodynamics, using a candidate approach to assess single-nucleotide polymorphisms (SNP) with known relevance to drug pharmacokinetics such as enzymes and transporters. A more comprehensive approach, the genome-wide association study, circumvents candidate selection but suffers because of the necessity for substantial statistical correction. Pharmacogene panels, which interrogate hundreds to thousands of SNPs in genes with known relevance to drug pharmacokinetics or pharmacodynamics, represent an attractive compromise between these approaches. Panels with defined or customizable SNP lists have been used to discover SNPs that predict pharmacokinetics or pharmacodynamics of cancer drugs, most of which await successful replication. PGx discovery, particularly for SNPs that influence drug pharmacodynamics, is limited by weaknesses in both genetic and phenotypic data. Selection of candidate SNPs for inclusion on pharmacogene panels is difficult because of limited understanding of biology and pharmacology. Phenotypes used in analyses have primarily been complex toxicities that are known to be multifactorial. A more measured approach, in which sensitive phenotypes are used in place of complex clinical outcomes, will improve the success rate of pharmacodynamics SNP discovery and ultimately enable identification of pharmacodynamics SNPs with meaningful effects on treatment outcomes. © 2014 American Association for Cancer Research.


PubMed | University of North Texas, Stanford University, Cornell University, University of Extremadura and 5 more.
Type: | Journal: Clinical pharmacology and therapeutics | Year: 2016

Voriconazole, a triazole antifungal agent, demonstrates wide interpatient variability in serum concentrations, due in part to variant CYP2C19 alleles. Individuals who are CYP2C19 ultrarapid metabolizers have decreased trough voriconazole concentrations, delaying achievement of target blood concentrations; whereas, poor metabolizers have increased trough concentrations and are at increased risk of adverse drug events. We summarize evidence from the literature supporting this association and provide therapeutic recommendations for the use of voriconazole for treatment based on CYP2C19 genotype (updates at https://cpicpgx.org/guidelines/ and www.pharmgkb.org). This article is protected by copyright. All rights reserved.


PubMed | Indiana University, University of Kentucky and DeBartolo Family Personalized Medicine Institute
Type: Journal Article | Journal: American journal of health-system pharmacy : AJHP : official journal of the American Society of Health-System Pharmacists | Year: 2016

Three different precision medicine practice models developed by oncology pharmacists are described, including strategies for implementation and recommendations for educating the next generation of oncology pharmacy practitioners.Oncology is unique in that somatic mutations can both drive the development of a tumor and serve as a therapeutic target for treating the cancer. Precision medicine practice models are a forum through which interprofessional teams, including pharmacists, discuss tumor somatic mutations to guide patient-specific treatment. The University of Wisconsin, Indiana University, and Moffit Cancer Center have implemented precision medicine practice models developed and led by oncology pharmacists. Different practice models, including a clinic, a clinical consultation service, and a molecular tumor board (MTB), were adopted to enhance integration into health systems and payment structures. Although the practice models vary, commonalities of three models include leadership by the clinical pharmacist, specific therapeutic recommendations, procurement of medications for off-label use, and a research component. These three practice models function as interprofessional training sites for pharmacy and medical students and residents, providing an important training resource at these institutions. Key implementation strategies include interprofessional involvement, institutional support, integration into clinical workflow, and selection of model by payer mix.MTBs are a pathway for clinical implementation of genomic medicine in oncology and are an emerging practice model for oncology pharmacists. Because pharmacists must be prepared to participate fully in contemporary practice, oncology pharmacy residents must be trained in genomic oncology, schools of pharmacy should expand precision medicine and genomics education, and opportunities for continuing education in precision medicine should be made available to practicing pharmacists.


Shain K.H.,H. Lee Moffitt Cancer Center and Research Institute | Dalton W.S.,H. Lee Moffitt Cancer Center and Research Institute | Dalton W.S.,DeBartolo Family Personalized Medicine Institute | Tao J.,University of South Florida
Oncogene | Year: 2015

B-cell tumorigenesis results from a host of known and unknown genetic anomalies, including non-random translocations of genes that normally function as determinants of cell proliferation or cell survival to regions juxtaposed to active immunoglobulin heavy chain enhancer elements, chromosomal aneuploidy, somatic mutations that further affect oncogenic signaling and loss of heterozygosity of tumor-suppressor genes. However, it is critical to recognize that even in the setting of a genetic disease, the B-cell/plasma cell tumor microenvironment (TME) contributes significantly to malignant transformation and pathogenesis. Over a decade ago, we proposed the concept of cell adhesion-mediated drug resistance to delineate a form of TME-mediated drug resistance that protects hematopoietic tumor cells from the initial effect of diverse therapies. In the interim, it has been increasingly appreciated that TME also contributes to tumor initiation and progression through sustained growth/proliferation, self-renewal capacity, immune evasion, migration and invasion as well as resistance to cell death in a host of B-cell malignancies, including mantle cell lymphoma, diffuse large B-cell lymphoma, Waldenstroms macroglobulinemia, chronic lymphocytic leukemia and multiple myeloma. Within this review, we propose that TME and the tumor co-evolve as a consequence of bidirectional signaling networks. As such, TME represents an important target and should be considered integral to tumor progression and drug response. © 2015 Macmillan Publishers Limited.


Hertz D.L.,University of Michigan | McLeod H.L.,DeBartolo Family Personalized Medicine Institute
Clinical Pharmacology and Therapeutics | Year: 2016

Tumor genome analysis is transforming cancer treatment by enabling identification of specific oncogenic drivers and selection of effective targeted agents. Meanwhile, patient genome analysis is being employed across therapeutic areas to inform selection of appropriate drugs and doses for treatment safety. Integration of patient genome analysis concurrent with preemptive tumor genetic testing will enable oncologists to make informed treatment decisions to select the right dose of the right drug for each patient and their tumor. © 2015 ASCPT.


He Y.,University of South Florida | McLeod H.L.,DeBartolo Family Personalized Medicine Institute
Medicine (United Kingdom) | Year: 2016

Pharmacokinetics is the science that describes (using the ADME approach) the absorption of a drug from its site of administration, its distribution throughout the body, its metabolism or conjugation, and its excretion from the body. Pharmacokinetics can be thought of as what the body does to the drug. This article describes the basic principles and outlines how an understanding of pharmacokinetics can support rational prescribing. © 2016 Elsevier Ltd. All rights reserved.


PubMed | Central South University, Hunan Tumor Hospital and DeBartolo Family Personalized Medicine Institute
Type: Journal Article | Journal: Oncotarget | Year: 2016

Both preclinical and epidemiology studies associate -adrenoceptors-blockers (-blockers) with activity against melanoma. However, the underlying mechanism is still unclear, especially in acral melanoma. In this study, we explored the effect of propranolol, a non-selective -blocker, on the A375 melanoma cell line, two primary acral melanoma cell lines (P-3, P-6) and mice xenografts. Cell viability assay demonstrated that 50M-400M of propranolol inhibited viability in a concentration and time dependent manner with an IC50 ranging from 65.33M to 148.60M for 24h -72h treatment, but propranolol (less than 200M) had no effect on HaCaT cell line. Western blots showed 100M propranolol significantly reduced the expression of Bcl-2 while increasing the expressions of Bax, cytochrome c, cleaved capase-9 and cleaved caspase-3, and down-regulated the levels of p-AKT, p-BRAF, p-MEK1/2 and p-ERK1/2 in melanoma cells, after a 24h incubation. The in vivo data confirmed the isolation results. Mice received daily ip. administration of propranolol at the dose of 2 mg/kg for 3 weeks and the control group was treated with the same volume of saline. The mean tumor volume at day 21 in A375 xenografts was 82.33 3.75mm3vs. 2044.67 54.57mm3 for the propranolol-treated mice and the control group, respectively, and 31.66 4.67 mm3vs. 1074.67 32.17 mm3 for the P-3 xenografts. Propranolol also reduced Ki67, inhibited phosphorylation of AKT, BRAF, MEK1/2 and ERK1/2 in xenografts. These are the first data to demonstrate that propranolol might inhibit melanoma by activating the intrinsic apoptosis pathway and inactivating the MAPK and AKT pathways.


PubMed | H. Lee Moffitt Cancer Center and Research Institute, Central South University and DeBartolo Family Personalized Medicine Institute
Type: | Journal: Molecular diagnosis & therapy | Year: 2016

Differences in response to cancer treatments have been observed among racially and ethnically diverse gastric cancer (GC) patient populations. In the era of targeted therapy, mutation profiling of cancer is a crucial aspect of making therapeutic decisions. Mapping driver gene mutations for the GC patient population as a whole has significant potential to advance precision therapy.GC patients with sequencing data (N=473) were obtained from The Cancer Genome Atlas (TCGA; n=295), Moffitt Cancer Center Total Cancer Care (TCC; n=33), and three published studies (n=145). In addition, relevant somatic mutation frequency data were obtained from cBioPortal, the TCC database, and an in-house analysis tool, as well as relevant publications.We found that the somatic mutation rates of several driver genes vary significantly between GC patients of Asian and Caucasian descent, with substantial variation across different geographic regions. Non-parametric statistical tests were performed to examine the significant differences in protein-altering somatic mutations between Asian and Caucasian GC patient groups. The frequencies of somatic mutations of five genes were: APC (Asian: Caucasian 6.06 vs. 14.40%, p=0.0076), ARIDIA (20.7 vs. 32.1%, p=0.01), KMT2A (4.04 vs. 12.35%, p=0.003), PIK3CA (9.6 vs. 18.52%, p=0.01), and PTEN (2.52 vs. 9.05%, p=0.008), showing significant differences between Asian and Caucasian GC patients.Our study found significant differences in protein-altering somatic mutation frequencies in diverse geographic populations. In particular, we found that the somatic patterns may offer better insight and important opportunities for both targeted drug development and precision therapeutic strategies between Asian and Caucasian GC patients.


PubMed | University of Michigan and DeBartolo Family Personalized Medicine Institute
Type: Journal Article | Journal: Clinical pharmacology and therapeutics | Year: 2016

Tumor genome analysis is transforming cancer treatment by enabling identification of specific oncogenic drivers and selection of effective targeted agents. Meanwhile, patient genome analysis is being employed across therapeutic areas to inform selection of appropriate drugs and doses for treatment safety. Integration of patient genome analysis concurrent with preemptive tumor genetic testing will enable oncologists to make informed treatment decisions to select the right dose of the right drug for each patient and their tumor.

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