scholarly journals Challenges in Implementing Genomic Medicine: The Mayo Clinic Center for Individualized Medicine

2013 ◽  
Vol 94 (2) ◽  
pp. 204-206 ◽  
Author(s):  
G Farrugia ◽  
R M Weinshilboum
Keyword(s):  
Mayo Clinic ◽  
Individualized Medicine ◽  
Genomic Medicine

Clinical utility of molecular testing to select therapy in relapsed/refractory non-Hodgkin lymphoma: Mayo Clinic Center for Individualized Medicine experience.

2017 ◽  
Vol 35 (15_suppl) ◽  
pp. 11571-11571
Author(s):  
Nabila Nora Bennani ◽  
Stephen Maxted Ansell ◽  
Thomas E. Witzig ◽  
Andew L. Feldman ◽  
Tammy M McAllister ◽  
...  
Keyword(s):  
Clinical Trial ◽  
Targeted Therapy ◽  
Precision Medicine ◽  
Mayo Clinic ◽  
Individualized Medicine ◽  
Tumor Board ◽  
Current Therapy ◽  
Molecular Profile ◽  
Molecular Testing ◽  
Molecular Alterations

11571 Background: Relapsed/refractory (R/R) non-Hodgkin lymphomas (NHL) have a poor prognosis with limited treatment options. Our expanding knowledge of molecular alterations seen in R/R NHL allows identification of patients that potentially may benefit from a precision medicine approach. However, experience in routine clinical implementation of precision medicine has been limited. Here, we summarize our clinical experience in molecular characterization of RR NHL targeted therapy (TT) using next-generation sequencing (NGS), and selection of targeted therapy (TT) based on molecular profile. Methods: We conducted a prospective study in RR NHL through the Center for Individualized Medicine at Mayo Clinic. Consenting patients underwent NGS using FoundationOne Heme panel from biopsies done at time of relapse. Results of NGS were discussed at the Genomic Tumor Board and recommendations for TT were given based on matching specific molecular alteration(s) with potential agent(s) predicted to be active based on NGS. The agents could include FDA-approved, off-label use and clinical trial therapies. Results: 28 cases were enrolled: 18 aggressive NHL, 10 follicular lymphoma (FL). Molecular alterations were present in all cases. In aggressive B-cell NHL, CDKN2A/B gene cluster alterations were seen in 73% (8/11), while seen in only 1/7 T-cell lymphomas (TCL), and 1/10 FL. TP53 deletions were second most common genomic alterations in DLBCL (57%) and seen in 40% FL. JAK-STAT and ERBB pathways were altered in TCL (2/7 each). IGH-BCl-2 gene rearrangement were common in FL (70%), followed by MLL gene alterations (50%). Targetable mutations were present in 86% (24/28) of cases. A TT was recommended in all 24 cases, but received by 2 patients only. Remaining patients did not due to benefit from current therapy (10/24), ineligibility or lack of clinical trial (7/24) or interim clinical deterioration (5/24). Conclusions: Targetable mutations were identified in most cases of RR NHL with TT recommended for all cases. However, access to TT limits potential clinical benefit of molecular-based matching strategy. More studies are needed to assess impact on clinical outcomes.

scholarly journals Empowering Mayo Clinic Individualized Medicine with Genomic Data Warehousing

2017 ◽  
Vol 7 (3) ◽  
pp. 7 ◽  
Author(s):  
Iain Horton ◽  
Yaxiong Lin ◽  
Gay Reed ◽  
Mathieu Wiepert ◽  
Steven Hart
Keyword(s):  
Mayo Clinic ◽  
Data Warehousing ◽  
Individualized Medicine ◽  
Genomic Data

scholarly journals The Return of Actionable Variants Empirical (RAVE) Study, a Mayo Clinic Genomic Medicine Implementation Study: Design and Initial Results

2018 ◽  
Vol 93 (11) ◽  
pp. 1600-1610 ◽  
Author(s):  
Iftikhar J. Kullo ◽  
Janet Olson ◽  
Xiao Fan ◽  
Merin Jose ◽  
Maya Safarova ◽  
...  
Keyword(s):  
Study Design ◽  
Mayo Clinic ◽  
Genomic Medicine ◽  
Implementation Study ◽  
Initial Results ◽  
Actionable Variants

scholarly journals The Mayo Clinic Biobank: A Building Block for Individualized Medicine

2013 ◽  
Vol 88 (9) ◽  
pp. 952-962 ◽  
Author(s):  
Janet E. Olson ◽  
Euijung Ryu ◽  
Kiley J. Johnson ◽  
Barbara A. Koenig ◽  
Karen J. Maschke ◽  
...  
Keyword(s):  
Building Block ◽  
Mayo Clinic ◽  
Individualized Medicine

scholarly journals CCA based multi-view feature selection for multi-omics data integration

2018 ◽  
Author(s):  
Yasser El-Manzalawy
Keyword(s):  
Feature Selection ◽  
Feature Fusion ◽  
Individualized Medicine ◽  
Genomic Medicine ◽  
Renal Clear Cell Carcinoma ◽  
Omics Data ◽  
Single View ◽  
Technological Advances ◽  
Using Data ◽  
Omics Data Integration

AbstractRecent technological advances in high-throughput omics technologies and their applications in genomic medicine have opened up outstanding opportunities for individualized medicine. However, several challenges arise in the integrative analysis of such data including heterogeneity and high dimensionality of the omics data. In this study, we present a novel multi-view feature selection algorithm based on the well-known canonical correlation analysis (CCA) statistical method for jointly selecting discriminative features from multi-omics data sources (multi-views). Our results demonstrate that models for predicting kidney renal clear cell carcinoma (KIRC) survival using our proposed method for jointly selecting discriminative features from copy number alteration (CNA), gene expression RNA-Seq, and reverse-phase protein arrays (RPPA) views outperform models trained using single-view data as well as three integrated models developed using data fusion approaches including CCA-based feature fusion.

scholarly journals How Do Patients Experience Individualized Medicine? A Qualitative Interview-based Study of Gene Expression Analyses in the Treatment of Breast Cancer

2017 ◽  
Vol 77 (09) ◽  
pp. 984-992 ◽  
Author(s):  
Sebastian Schleidgen ◽  
Sandra Thiersch ◽  
Rachel Wuerstlein ◽  
Georg Marckmann
Keyword(s):  
Breast Cancer ◽  
Gene Expression ◽  
Individualized Medicine ◽  
Empirical Studies ◽  
Treatment Options ◽  
Genomic Medicine ◽  
Individualized Treatment ◽  
Joint Decision ◽  
Therapy Decision ◽  
Gene Expression Analyses

Abstract Introduction In recent years, the hopes and expectations associated with so-called individualized medicine have been the subject of intense debate as has the medical potential of this approach. Questions about the uses of gene expression analyses for decisions on adjuvant systemic treatment options for patients with breast cancer have played a prominent role in this debate. There are a number of empirical studies on the effect of gene expression tests on the therapy decisions of physicians and the potentially conflicted decisions for patients. Very little attention has been paid to how patients perceive such approaches, the extent to which they feel included in the therapy decision, and the expectations they associate with such an approach. Material and Methods Using qualitative explorative interviews, the study looked at how well patients with breast cancer understood the individualized treatment approaches and examined patientsʼ experiences and expectations with regard to gene expression analyses. The sample consisted of 8 patients who were diagnosed with primary hormone receptor-positive, HER2-negative breast cancer between 2013 and 2014 and who underwent gene expression analyses as part of their adjuvant therapy planning. Results Patients were found to have a quite realistic view of the benefits of gene expression analyses, although it also became clear that the treatment could also raise false hopes. The statements by the interviewed women also illustrated the necessity of continuing to explore the possibilities and limits to joint decision-making in such complex medical contexts as individualized molecular genomic medicine. And finally, the interviews reflected the hope for individualized treatment in the broadest sense of the word. Conclusion The results of the study highlight the challenge of taking psychosocial aspects of medical treatment sufficiently into consideration, given the ever increasing options for molecular genomic individualization.

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