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A radiation-derived gene expression signature predicts clinical outcome for breast cancer patients.


ABSTRACT: Activation of the DNA damage response pathway is a hallmark for early tumorigenesis, while loss of pathway activity is associated with disease progression. Thus we hypothesized that a gene expression signature associated with the DNA damage response may serve as a prognostic signature for outcome in cancer patients. We identified ionizing radiation-responsive transcripts in human lymphoblast cells derived from 12 individuals and used this signature to screen a panel of cancer data sets for the ability to predict long-term survival of cancer patients. We demonstrate that gene sets induced or repressed by ionizing radiation can predict clinical outcome in two independent breast cancer data sets, and we compare the radiation signature to previously described gene expression-based outcome predictors. While genes repressed in response to radiation likely represent the well-characterized proliferation signature predictive of breast cancer outcome, genes induced by radiation likely encode additional information representing other deregulated biological properties of tumors such as checkpoint or apoptotic responses.

SUBMITTER: Piening BD 

PROVIDER: S-EPMC2662705 | biostudies-literature | 2009 Feb

REPOSITORIES: biostudies-literature

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A radiation-derived gene expression signature predicts clinical outcome for breast cancer patients.

Piening Brian D BD   Wang Pei P   Subramanian Aravind A   Paulovich Amanda G AG  

Radiation research 20090201 2


Activation of the DNA damage response pathway is a hallmark for early tumorigenesis, while loss of pathway activity is associated with disease progression. Thus we hypothesized that a gene expression signature associated with the DNA damage response may serve as a prognostic signature for outcome in cancer patients. We identified ionizing radiation-responsive transcripts in human lymphoblast cells derived from 12 individuals and used this signature to screen a panel of cancer data sets for the a  ...[more]

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