Homo sapiens
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA118149 | ENA |
REPOSITORIES: ENA
Similar Datasets
Project description:Transcriptome of 17 tru-cut biopsies and 13 matched surgical samples from ER+ breast tumor patients, treated for 3 months with Anastrozole were anayzed to identify a robust expression signature predictive of response to Anastrozole neoadjuvant treatment in ER+ breast cancer patients and, at the same time, to delineate treatment effects.
2010-05-17 | GSE18378 | GEO
Project description:Neoadjuvant anastrozole alone or with gefitinib in early breast cancer
| PRJNA212259 | ENA
Project description:To identify the effect of 16 weeks of neoadjuvant anastrozole treatment on gene expression profiles of oestrogen receptor positive breast tumours from post-menopausal patients.
2021-04-01 | GSE161830 | GEO
Project description:Neoadjuvant Trastuzumab Response in Breast Cancer
| PRJNA371666 | ENA
Project description:Neoadjuvant Trastuzumab Response in Breast Cancer
| PRJNA252719 | ENA
Project description:Purpose Aromatase inhibitors (AIs) have an established role in breast cancer treatment. Response rates are only 50-70% in the neoadjuvant setting and lower in advanced disease. Accurate biomarkers are urgently needed to predict response in these settings and to determine which individuals will benefit from adjuvant AI therapy. Participants and Methods Pre- and on-treatment (after 2 weeks and 3 months) biopsies were obtained from 89 post-menopausal women with ER+ breast cancer receiving neoadjuvant letrozole for transcript profiling. Dynamic clinical response was assessed by three-dimensional ultrasound measurements. Results The molecular response to letrozole was characterised and a four gene classifier of clinical response was established (accuracy of 96%) based upon the level of two genes prior to treatment (one associated with immune signalling, IL6ST and the other with apoptosis, NGFRAP1) and two proliferation genes (ASPM, MCM4) at 2 weeks of therapy. The four gene signature was found to be 91% accurate in a blinded, completely independent validation dataset of patients treated with anastrozole. Matched 2 week on-treatment biopsies improved predictive power over pre-treatment biopsies alone. This signature also significantly predicted recurrence free survival (p=0.029) and breast cancer specific survival (p=0.009). We demonstrate that the test can also be performed using quantitative PCR or immunohistochemistry. Conclusion A four gene predictive model of clinical response to AIs by two weeks has been generated and validated. Deregulated immune and apoptotic responses before treatment and a failure to reduce proliferation by 2 weeks are functional characteristics of breast tumours that do not respond to AIs. 25 Pre treatment, 25 two week and 25 three month on-treatment primary breast tumour samples from the same patients. Data was analysed with two previously generated datasets, GSE55374 which was also processed on Illumina HT-12v4 BeadChips (GPL10558) and GSE20181 on Affymetrix U133A GeneChips (GPL96)
2015-07-06 | E-GEOD-59515 | biostudies-arrayexpress
Project description:Trial 223 was a placebo-controlled trial of neoadjuvant anastrozole alone or with gefitinib in early breast cancer. We used patients from arm B and C: anastrozole 1mg/d for the duration of the 16 week period plus placebo 1 tablet/d orally for 2 weeks. Patients in arm B were followed by gefitinib 250mg/d orally for 14 weeks whereas patients in arm C continued with placebo for 14 weeks. 96 samples
2014-01-08 | E-GEOD-48906 | biostudies-arrayexpress
Project description:Trial 223 was a placebo-controlled trial of neoadjuvant anastrozole alone or with gefitinib in early breast cancer. We used patients from arm B and C: anastrozole 1mg/d for the duration of the 16 week period plus placebo 1 tablet/d orally for 2 weeks. Patients in arm B were followed by gefitinib 250mg/d orally for 14 weeks whereas patients in arm C continued with placebo for 14 weeks.
2014-01-08 | GSE48906 | GEO
Project description:Purpose Aromatase inhibitors (AIs) have an established role in breast cancer treatment. Response rates are only 50-70% in the neoadjuvant setting and lower in advanced disease. Accurate biomarkers are urgently needed to predict response in these settings and to determine which individuals will benefit from adjuvant AI therapy. Participants and Methods Pre- and on-treatment (after 2 weeks and 3 months) biopsies were obtained from 89 post-menopausal women with ER+ breast cancer receiving neoadjuvant letrozole for transcript profiling. Dynamic clinical response was assessed by three-dimensional ultrasound measurements. Results The molecular response to letrozole was characterised and a four gene classifier of clinical response was established (accuracy of 96%) based upon the level of two genes prior to treatment (one associated with immune signalling, IL6ST and the other with apoptosis, NGFRAP1) and two proliferation genes (ASPM, MCM4) at 2 weeks of therapy. The four gene signature was found to be 91% accurate in a blinded, completely independent validation dataset of patients treated with anastrozole. Matched 2 week on-treatment biopsies improved predictive power over pre-treatment biopsies alone. This signature also significantly predicted recurrence free survival (p=0.029) and breast cancer specific survival (p=0.009). We demonstrate that the test can also be performed using quantitative PCR or immunohistochemistry. Conclusion A four gene predictive model of clinical response to AIs by two weeks has been generated and validated. Deregulated immune and apoptotic responses before treatment and a failure to reduce proliferation by 2 weeks are functional characteristics of breast tumours that do not respond to AIs.
2015-07-06 | GSE59515 | GEO