Identification and validation of single sample breast cancer radiosensitivity gene expression predictors
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PROVIDER: PRJNA406914 | ENA |
REPOSITORIES: ENA
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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.
2018-07-01 | GSE103745 | GEO
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.
2018-07-01 | GSE103744 | GEO
Project description:This SuperSeries is composed of the SubSeries listed below.
2018-07-01 | GSE103746 | GEO
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.
| S-EPMC6033283 | biostudies-literature
Project description:Sample Validation Study_microarrays
2011-11-01 | E-MTAB-360 | biostudies-arrayexpress
Project description:Low topo2a expression and ER-negative status were predictors of response to doxorubicin, while small tumor size and ER-negative status predicted response to docetaxel. Docetaxel was superior to doxorubicin in triple-negative/basal-like tumors, while no significant differences between these drugs were seen in the remaining intrinsic subtypes Keywords: reference x sample
2011-05-27 | GSE21997 | GEO
Project description:Gene expression profiles in normal fibroblasts from patients with breast cancer - comparison of clinical radiosensitivity
2007-02-01 | E-MEXP-821 | biostudies-arrayexpress
Project description:Low topo2a expression and ER-negative status were predictors of response to doxorubicin, while small tumor size and ER-negative status predicted response to docetaxel. Docetaxel was superior to doxorubicin in triple-negative/basal-like tumors, while no significant differences between these drugs were seen in the remaining intrinsic subtypes Keywords: reference x sample reference x sample
2011-05-27 | E-GEOD-21997 | biostudies-arrayexpress
Project description:Identification and validation of single sample breast cancer radiosensitivity gene expression predictors [Illumina HT12 v4 data]
| PRJNA406920 | ENA
Project description:Identification and validation of single sample breast cancer radiosensitivity gene expression predictors [Nanostring custom assay data]
| PRJNA406918 | ENA