Dataset Information

Validation of a radiosensitivity molecular signature in breast cancer.

ABSTRACT: PURPOSE:Previously, we developed a radiosensitivity molecular signature [radiosensitivity index (RSI)] that was clinically validated in 3 independent datasets (rectal, esophageal, and head and neck) in 118 patients. Here, we test RSI in radiotherapy (RT)-treated breast cancer patients. EXPERIMENTAL DESIGN:RSI was tested in 2 previously published breast cancer datasets. Patients were treated at the Karolinska University Hospital (n = 159) and Erasmus Medical Center (n = 344). RSI was applied as previously described. RESULTS:We tested RSI in RT-treated patients (Karolinska). Patients predicted to be radiosensitive (RS) had an improved 5-year relapse-free survival when compared with radioresistant (RR) patients (95% vs. 75%, P = 0.0212), but there was no difference between RS/RR patients treated without RT (71% vs. 77%, P = 0.6744), consistent with RSI being RT-specific (interaction term RSI × RT, P = 0.05). Similarly, in the Erasmus dataset, RT-treated RS patients had an improved 5-year distant metastasis-free survival over RR patients (77% vs. 64%, P = 0.0409), but no difference was observed in patients treated without RT (RS vs. RR, 80% vs. 81%, P = 0.9425). Multivariable analysis showed RSI is the strongest variable in RT-treated patients (Karolinska, HR = 5.53, P = 0.0987, Erasmus, HR = 1.64, P = 0.0758) and in backward selection (removal ? of 0.10), RSI was the only variable remaining in the final model. Finally, RSI is an independent predictor of outcome in RT-treated ER(+) patients (Erasmus, multivariable analysis, HR = 2.64, P = 0.0085). CONCLUSIONS:RSI is validated in 2 independent breast cancer datasets totaling 503 patients. Including prior data, RSI is validated in 5 independent cohorts (621 patients) and represents, to our knowledge, the most extensively validated molecular signature in radiation oncology.

SUBMITTER: Eschrich SA

PROVIDER: S-EPMC3993974 | biostudies-literature | 2012 Sep

REPOSITORIES: biostudies-literature

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Validation of a radiosensitivity molecular signature in breast cancer.

Eschrich Steven A SA Fulp William J WJ Pawitan Yudi Y Foekens John A JA Smid Marcel M Martens John W M JW Echevarria Michelle M Kamath Vidya V Lee Ji-Hyun JH Harris Eleanor E EE Bergh Jonas J Torres-Roca Javier F JF

Clinical cancer research : an official journal of the American Association for Cancer Research 20120725 18

<h4>Purpose</h4>Previously, we developed a radiosensitivity molecular signature [radiosensitivity index (RSI)] that was clinically validated in 3 independent datasets (rectal, esophageal, and head and neck) in 118 patients. Here, we test RSI in radiotherapy (RT)-treated breast cancer patients.<h4>Experimental design</h4>RSI was tested in 2 previously published breast cancer datasets. Patients were treated at the Karolinska University Hospital (n = 159) and Erasmus Medical Center (n = 344). RSI w ...[more]

PMID: 22832933

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Project description:Recently, we developed radiosensitivity (RSI), a clinically validated molecular signature that estimates tumor radiosensitivity. In the present study, we tested whether integrating RSI with the molecular subtype refines the classification of local recurrence (LR) risk in breast cancer.RSI and molecular subtype were evaluated in 343 patients treated with breast-conserving therapy that included whole-breast radiation therapy with or without a tumor bed boost (dose range 45-72 Gy). The follow-up period for patients without recurrence was 10 years. The clinical endpoint was LR-free survival.Although RSI did not uniformly predict for LR across the entire cohort, combining RSI and the molecular subtype identified a subpopulation with an increased risk of LR: triple negative (TN) and radioresistant (reference TN-radioresistant, hazard ratio [HR] 0.37, 95% confidence interval [CI] 0.15-0.92, P=.02). TN patients who were RSI-sensitive/intermediate had LR rates similar to those of luminal (LUM) patients (HR 0.86, 95% CI 0.47-1.57, P=.63). On multivariate analysis, combined RSI and molecular subtype (P=.004) and age (P=.001) were the most significant predictors of LR. In contrast, integrating RSI into the LUM subtype did not identify additional risk groups. We hypothesized that radiation dose escalation was affecting radioresistance in the LUM subtype and serving as a confounder. An increased radiation dose decreased LR only in the luminal-resistant (LUM-R) subset (HR 0.23, 95% CI 0.05-0.98, P=.03). On multivariate analysis, the radiation dose was an independent variable only in the LUMA/B-RR subset (HR 0.025, 95% CI 0.001-0.946, P=.046), along with age (P=.008), T stage (P=.004), and chemotherapy (P=.008).The combined molecular subtype-RSI identified a novel molecular subpopulation (TN and radioresistant) with an increased risk of LR after breast-conserving therapy. We propose that the combination of RSI and molecular subtype could be useful in guiding radiation therapy-based decisions in breast cancer.

Project description:BackgroundAdjuvant radiotherapy is the standard of care after breast-conserving surgery for primary breast cancer, despite a majority of patients being over- or under-treated. In contrast to adjuvant endocrine therapy and chemotherapy, no diagnostic tests are in clinical use that can stratify patients for adjuvant radiotherapy. This study presents the development and validation of a targeted gene expression assay to predict the risk of ipsilateral breast tumor recurrence and response to adjuvant radiotherapy after breast-conserving surgery in primary breast cancer.MethodsFresh-frozen primary tumors from 336 patients radically (clear margins) operated on with breast-conserving surgery with or without radiotherapy were collected. Patients were split into a discovery cohort (N = 172) and a validation cohort (N = 164). Genes predicting ipsilateral breast tumor recurrence in an Illumina HT12 v4 whole transcriptome analysis were combined with genes identified in the literature (248 genes in total) to develop a targeted radiosensitivity assay on the Nanostring nCounter platform. Single-sample predictors for ipsilateral breast tumor recurrence based on a k-top scoring pairs algorithm were trained, stratified for estrogen receptor (ER) status and radiotherapy. Two previously published profiles, the radiosensitivity signature of Speers et al., and the 10-gene signature of Eschrich et al., were also included in the targeted panel.ResultsDerived single-sample predictors were prognostic for ipsilateral breast tumor recurrence in radiotherapy-treated ER+ patients (AUC 0.67, p = 0.01), ER+ patients without radiotherapy (AUC = 0.89, p = 0.02), and radiotherapy-treated ER- patients (AUC = 0.78, p < 0.001). Among ER+ patients, radiotherapy had an excellent effect on tumors classified as radiosensitive (p < 0.001), while radiotherapy had no effect on tumors classified as radioresistant (p = 0.36) and there was a high risk of ipsilateral breast tumor recurrence (55% at 10 years). Our single-sample predictors developed in ER+ tumors and the radiosensitivity signature correlated with proliferation, while single-sample predictors developed in ER- tumors correlated with immune response. The 10-gene signature negatively correlated with both proliferation and immune response.ConclusionsOur targeted single-sample predictors were prognostic for ipsilateral breast tumor recurrence and have the potential to stratify patients for adjuvant radiotherapy. The correlation of models with biology may explain the different performance in subgroups of breast cancer.

Project description:Purpose To develop a radiosensitivity gene expression assay to predict the response to adjuvant radiotherapy (RT) after breast conserving surgery (BCS) in breast cancer. Patients and methods Fresh frozen primary tumors from 336 patients operated with BCS with or without RT were collected. Patients were split in a discovery cohort (N=172) and a validation cohort (N=164). Genes predicting ipsilateral breast tumor recurrence (IBTR) in an Illumina HT12 v4 whole transcriptome analysis were combined with genes from the literature (248 genes in total) to develop a targeted radiosensitivity assay on the Nanostring nCounter platform. Single sample predictors (SSPs) for IBTR based on a k-top scoring pairs algorithm were trained stratified for estrogen receptor (ER) status and RT. Two previously published profiles (radiosensitivity index, RSI, and radiosensitivity score, RSS) were also tested in our data Results The SSPs were prognostic for IBTR in ER+RT- patients (AUC 0.67, p=0.005), ER+RT- patients (AUC=0.89, p=0.015) and ER-RT+ patients (AUC=0.78, p<0.001). Among ER+ patients, radiosensitive tumors had an excellent effect of RT (p<0.001), while radioresistant tumors had no effect of RT (p=0.4) and a high risk of IBTR (55% at 10 years). Our SSPs developed in ER+ tumors and the RSS correlated with proliferation, while SSPs developed in ER- tumors correlated with immune response. RSI negatively correlated with both proliferation and immune response. Conclusions Our targeted SSPs were prognostic for IBTR and has the potential to stratify patients for RT. The biology behind models may explain the different performance in subgroups of breast cancer. Purpose To develop a radiosensitivity gene expression assay to predict the response to adjuvant radiotherapy (RT) after breast conserving surgery (BCS) in breast cancer. Patients and methods Fresh frozen primary tumors from 336 patients operated with BCS with or without RT were collected. Patients were split in a discovery cohort (N=172) and a validation cohort (N=164). Genes predicting ipsilateral breast tumor recurrence (IBTR) in an Illumina HT12 v4 whole transcriptome analysis were combined with genes from the literature (248 genes in total) to develop a targeted radiosensitivity assay on the Nanostring nCounter platform. Single sample predictors (SSPs) for IBTR based on a k-top scoring pairs algorithm were trained stratified for estrogen receptor (ER) status and RT. Two previously published profiles (radiosensitivity index, RSI, and radiosensitivity score, RSS) were also tested in our data Results The SSPs were prognostic for IBTR in ER+RT- patients (AUC 0.67, p=0.005), ER+RT- patients (AUC=0.89, p=0.015) and ER-RT+ patients (AUC=0.78, p<0.001). Among ER+ patients, radiosensitive tumors had an excellent effect of RT (p<0.001), while radioresistant tumors had no effect of RT (p=0.4) and a high risk of IBTR (55% at 10 years). Our SSPs developed in ER+ tumors and the RSS correlated with proliferation, while SSPs developed in ER- tumors correlated with immune response. RSI negatively correlated with both proliferation and immune response. Conclusions Our targeted SSPs were prognostic for IBTR and has the potential to stratify patients for RT. The biology behind models may explain the different performance in subgroups of breast cancer.

Dataset Information

Validation of a radiosensitivity molecular signature in breast cancer.

Publications

Validation of a radiosensitivity molecular signature in breast cancer.

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