Literature DB >> 22999010

Personalized oncology: recent advances and future challenges.

Madhu Kalia1.   

Abstract

Personalized oncology is evidence-based, individualized medicine that delivers the right care to the right cancer patient at the right time and results in measurable improvements in outcomes and a reduction on health care costs. Evolving topics in personalized oncology such as genomic analysis, targeted drugs, cancer therapeutics and molecular diagnostics will be discussed in this review. Biomarkers and molecular individualized medicine are replacing the traditional "one size fits all" medicine. In the next decade the treatment of cancer will move from a reactive to a proactive discipline. The essence of personalized oncology lies in the use of biomarkers. These biomarkers can be from tissue, serum, urine or imaging and must be validated. Personalized oncology based on biomarkers is already having a remarkable impact. Three different types of biomarkers are of particular importance: predictive, prognostic and early response biomarkers. Tools for implementing preemptive medicine based on genetic and molecular diagnostic and interventions will improve cancer prevention. Imaging technologies such as Computed Tomography (CT) and Positron Emitted Tomography (PET) are already influencing the early detection and management of the cancer patient. Future advances in imaging are expected to be in the field of molecular imaging, integrated diagnostics, biology driven interventional radiology and theranostics. Molecular diagnostics identify individual cancer patients who are more likely to respond positively to targeted chemotherapies. Molecular diagnostics include testing for genes, gene expression, proteins and metabolites. The use of companion molecular diagnostics is expected to grow significantly in the future and will be integrated into new cancer therapies a single (bundled) package which will provide greater efficiency, value and cost savings. This approach represents a unique opportunity for integration, increased value in personalized oncology.
Copyright © 2013 Elsevier Inc. All rights reserved.

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Year:  2012        PMID: 22999010     DOI: 10.1016/j.metabol.2012.08.016

Source DB:  PubMed          Journal:  Metabolism        ISSN: 0026-0495            Impact factor:   8.694


  55 in total

1.  Perspectives in Radiomics for Personalized Medicine and Theranostics.

Authors:  Seunggyun Ha
Journal:  Nucl Med Mol Imaging       Date:  2019-01-23

Review 2.  Personalized oncology in interventional radiology.

Authors:  Nadine Abi-Jaoudeh; Austin G Duffy; Tim F Greten; Elise C Kohn; Timothy W I Clark; Bradford J Wood
Journal:  J Vasc Interv Radiol       Date:  2013-08       Impact factor: 3.464

3.  Genetic polymorphisms in cytochrome P450 and clinical outcomes of FOLFIRI chemotherapy in patients with metastatic colorectal cancer.

Authors:  Ningning Dong; Fandong Meng; Yongdong Wu; Mingyu Wang; Yongchun Cui; Shutian Zhang
Journal:  Tumour Biol       Date:  2015-05-02

4.  Impact of Appointment Waiting Time on Attendance Rates at a Clinical Cancer Genetics Service.

Authors:  Tarryn Shaw; Julie Metras; Zoe Ang Li Ting; Eliza Courtney; Shao-Tzu Li; Joanne Ngeow
Journal:  J Genet Couns       Date:  2018-05-24       Impact factor: 2.537

Review 5.  Striking a balance in communicating pharmacogenetic test results: promoting comprehension and minimizing adverse psychological and behavioral response.

Authors:  Susanne B Haga; Rachel Mills; Hayden Bosworth
Journal:  Patient Educ Couns       Date:  2014-06-21

6.  Some economics on personalized and predictive medicine.

Authors:  F Antoñanzas; C A Juárez-Castelló; R Rodríguez-Ibeas
Journal:  Eur J Health Econ       Date:  2014-11-08

Review 7.  Genetic Variants Associated with Cancer Pain and Response to Opioid Analgesics: Implications for Precision Pain Management.

Authors:  Gee Su Yang; Natalie M Barnes; Debra E Lyon; Susan G Dorsey
Journal:  Semin Oncol Nurs       Date:  2019-05-10       Impact factor: 2.315

8.  Making individualized drugs a reality.

Authors:  Huub Schellekens; Mohammed Aldosari; Herre Talsma; Enrico Mastrobattista
Journal:  Nat Biotechnol       Date:  2017-06-05       Impact factor: 54.908

9.  Prognostic impact of intra-field heterogeneity in oral squamous cell carcinoma.

Authors:  Andrea Gabusi; Davide Bartolomeo Gissi; Lucio Montebugnoli; Sofia Asioli; Achille Tarsitano; Claudio Marchetti; Tiziana Balbi; Timothy R Helliwell; Maria P Foschini; Luca Morandi
Journal:  Virchows Arch       Date:  2019-08-29       Impact factor: 4.064

10.  Improved decision making for prioritizing tumor targeting antibodies in human xenografts: Utility of fluorescence imaging to verify tumor target expression, antibody binding and optimization of dosage and application schedule.

Authors:  Michael Dobosz; Ute Haupt; Werner Scheuer
Journal:  MAbs       Date:  2016-09-23       Impact factor: 5.857

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