Literature DB >> 22322254

Cancer biomarkers: selecting the right drug for the right patient.

Gary J Kelloff1, Caroline C Sigman.   

Abstract

This Perspective highlights biomarkers that are expressed as a consequence of cancer development and progression. We focus on those biomarkers that are most relevant for identifying patients who are likely to respond to a given therapy, as well as those biomarkers that are most effective for measuring patient response to therapy. These two measures are necessary for selecting the right drug for the right patient, regardless of whether the setting is in drug development or in the post-approval use of the drug for patients with cancer. We also discuss the innovative designs of clinical trials and methodologies that are used to validate and qualify biomarkers for use in specific contexts. Furthermore, we look ahead to the promises and challenges in the field of cancer biomarkers.

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Year:  2012        PMID: 22322254     DOI: 10.1038/nrd3651

Source DB:  PubMed          Journal:  Nat Rev Drug Discov        ISSN: 1474-1776            Impact factor:   84.694


  111 in total

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Review 5.  Progress in chemoprevention drug development: the promise of molecular biomarkers for prevention of intraepithelial neoplasia and cancer--a plan to move forward.

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Journal:  Clin Cancer Res       Date:  2006-06-15       Impact factor: 12.531

Review 6.  Progress and promise of FDG-PET imaging for cancer patient management and oncologic drug development.

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  83 in total

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Journal:  J Natl Cancer Inst       Date:  2013-12-03       Impact factor: 13.506

3.  Repeatability of 18F-FDG PET/CT in Advanced Non-Small Cell Lung Cancer: Prospective Assessment in 2 Multicenter Trials.

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4.  Evaluation of FGFR3 as a Therapeutic Target in Head and Neck Squamous Cell Carcinoma.

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Journal:  Target Oncol       Date:  2016-10       Impact factor: 4.493

5.  Expression and prognostic role of SGTA in human breast carcinoma correlates with tumor cell proliferation.

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7.  Frequent PTEN loss and differential HER2/PI3K signaling pathway alterations in salivary duct carcinoma: Implications for targeted therapy.

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Review 8.  Personalized medicine and pharmacogenetic biomarkers: progress in molecular oncology testing.

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10.  Bayesian predictive modeling for genomic based personalized treatment selection.

Authors:  Junsheng Ma; Francesco C Stingo; Brian P Hobbs
Journal:  Biometrics       Date:  2015-11-17       Impact factor: 2.571

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