The role of genomic techniques in predicting response to radiation therapy

Noelle L. Williams, Tu Dan, Nicholas Zaorsky, Shivank Garg, Robert B. Den

Research output: Contribution to journalReview article

Abstract

The understanding of the relationship between genetic variation and an individual patient’s response to radiation therapy (RT) has gained significant ground over the past several years. Genetic markers have been identified that could ultimately serve as the foundation for predictive models in clinical practice, and that hold the potential to revolutionize the delivery of precision medicine in oncology. Single nucleotide polymorphisms, single genes, and/or gene signatures could ultimately serve as the basis for patient stratification in prospective clinical trials. Currently, molecular markers relevant to breast, lung, and head and neck cancers have been integrated into clinical practice and serve as predictive tools to guide systemic therapy. In the future, the use of predictive models based on genomic determinants may become standard practice in radiation oncology, offering the potential to further personalize the delivery of RT and optimize the therapeutic ratio.

Original languageEnglish (US)
Pages (from-to)1-11
Number of pages11
JournalONCOLOGY (United States)
Volume31
Issue number7
StatePublished - Jul 15 2017

Fingerprint

Radiotherapy
Precision Medicine
Radiation Oncology
Head and Neck Neoplasms
Genetic Markers
Genes
Single Nucleotide Polymorphism
Lung Neoplasms
Breast
Clinical Trials
Therapeutics

All Science Journal Classification (ASJC) codes

  • Oncology
  • Cancer Research

Cite this

Williams, N. L., Dan, T., Zaorsky, N., Garg, S., & Den, R. B. (2017). The role of genomic techniques in predicting response to radiation therapy. ONCOLOGY (United States), 31(7), 1-11.
Williams, Noelle L. ; Dan, Tu ; Zaorsky, Nicholas ; Garg, Shivank ; Den, Robert B. / The role of genomic techniques in predicting response to radiation therapy. In: ONCOLOGY (United States). 2017 ; Vol. 31, No. 7. pp. 1-11.
@article{4edc0ddd0b4c46ffbd019c4ba878673e,
title = "The role of genomic techniques in predicting response to radiation therapy",
abstract = "The understanding of the relationship between genetic variation and an individual patient’s response to radiation therapy (RT) has gained significant ground over the past several years. Genetic markers have been identified that could ultimately serve as the foundation for predictive models in clinical practice, and that hold the potential to revolutionize the delivery of precision medicine in oncology. Single nucleotide polymorphisms, single genes, and/or gene signatures could ultimately serve as the basis for patient stratification in prospective clinical trials. Currently, molecular markers relevant to breast, lung, and head and neck cancers have been integrated into clinical practice and serve as predictive tools to guide systemic therapy. In the future, the use of predictive models based on genomic determinants may become standard practice in radiation oncology, offering the potential to further personalize the delivery of RT and optimize the therapeutic ratio.",
author = "Williams, {Noelle L.} and Tu Dan and Nicholas Zaorsky and Shivank Garg and Den, {Robert B.}",
year = "2017",
month = "7",
day = "15",
language = "English (US)",
volume = "31",
pages = "1--11",
journal = "Oncology",
issn = "0890-9091",
publisher = "UBM Medica Healthcare Publications",
number = "7",

}

Williams, NL, Dan, T, Zaorsky, N, Garg, S & Den, RB 2017, 'The role of genomic techniques in predicting response to radiation therapy', ONCOLOGY (United States), vol. 31, no. 7, pp. 1-11.

The role of genomic techniques in predicting response to radiation therapy. / Williams, Noelle L.; Dan, Tu; Zaorsky, Nicholas; Garg, Shivank; Den, Robert B.

In: ONCOLOGY (United States), Vol. 31, No. 7, 15.07.2017, p. 1-11.

Research output: Contribution to journalReview article

TY - JOUR

T1 - The role of genomic techniques in predicting response to radiation therapy

AU - Williams, Noelle L.

AU - Dan, Tu

AU - Zaorsky, Nicholas

AU - Garg, Shivank

AU - Den, Robert B.

PY - 2017/7/15

Y1 - 2017/7/15

N2 - The understanding of the relationship between genetic variation and an individual patient’s response to radiation therapy (RT) has gained significant ground over the past several years. Genetic markers have been identified that could ultimately serve as the foundation for predictive models in clinical practice, and that hold the potential to revolutionize the delivery of precision medicine in oncology. Single nucleotide polymorphisms, single genes, and/or gene signatures could ultimately serve as the basis for patient stratification in prospective clinical trials. Currently, molecular markers relevant to breast, lung, and head and neck cancers have been integrated into clinical practice and serve as predictive tools to guide systemic therapy. In the future, the use of predictive models based on genomic determinants may become standard practice in radiation oncology, offering the potential to further personalize the delivery of RT and optimize the therapeutic ratio.

AB - The understanding of the relationship between genetic variation and an individual patient’s response to radiation therapy (RT) has gained significant ground over the past several years. Genetic markers have been identified that could ultimately serve as the foundation for predictive models in clinical practice, and that hold the potential to revolutionize the delivery of precision medicine in oncology. Single nucleotide polymorphisms, single genes, and/or gene signatures could ultimately serve as the basis for patient stratification in prospective clinical trials. Currently, molecular markers relevant to breast, lung, and head and neck cancers have been integrated into clinical practice and serve as predictive tools to guide systemic therapy. In the future, the use of predictive models based on genomic determinants may become standard practice in radiation oncology, offering the potential to further personalize the delivery of RT and optimize the therapeutic ratio.

UR - http://www.scopus.com/inward/record.url?scp=85025449823&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85025449823&partnerID=8YFLogxK

M3 - Review article

VL - 31

SP - 1

EP - 11

JO - Oncology

JF - Oncology

SN - 0890-9091

IS - 7

ER -