Gene expression-based prediction of neodjuvant chemotherapy response in early breast cancer
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PROVIDER: PRJNA589890 | ENA |
REPOSITORIES: ENA
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Project description:Background: Neoadjuvant chemotherapy is increasingly being used to preoperatively shrink breast tumours prior to surgery. This approach also provides the opportunity to study the molecular changes associated with treatment and evaluate whether on-treatment sequential samples can improve response and outcome predictions over diagnostic or excision samples alone. Methods: A total of 95 samples from a cohort of 50 neoadjuvant chemotherapy-treated primary breast cancer patients (aged 29-76, 48% ER+, 20% HER2+) enrolled in the NEO trial taken before, at 2 weeks on-treatment, mid-therapy and at resection were sequenced with Ion Ampliseq transcriptome yielding expression values for 12,635 genes. Differential expression analysis was performed across 16 responders and 34 non-responders defined by pathological complete response and over treatment time to identify significantly differentially expressed genes, pathways and markers indicative of response status. Prediction accuracy was compared with estimations of established gene signatures, for this dataset and validated using data from the I-SPY1 trial. Results: AAGAB was identified as a novel on-treatment biomarker for pathological complete response, with an accuracy of 100% in the NEO training dataset and 78% accuracy in the I-SPY1 Trial. AAGAB levels on treatment were also significantly predictive of term survival (p = 0.048, p = 0.031) in the two cohorts. This single gene on-treatment biomarker, had greater predictive accuracy than established prognostic tests, Mammaprint and Pam50 risk of recurrence score, although interesting both of these tests performed better in the on-treatment rather than the accepted pre-treatment setting (accuracy improving consistently by 2-8%). Conclusion: Changes in gene expression measured in sequential samples from breast cancer patients receiving neoadjuvant chemotherapy resulted in the identification of a novel on-treatment biomarker and suggest that established prognostic tests may have greater prediction accuracy on- than before treatment. These results support the potential use and further evaluation of on- treatment testing in breast cancer to improve the accuracy of tumour response prediction.
2019-07-02 | GSE122630 | GEO
Project description:Despite recent consensus on eligibility of adjuvant systemic therapy in lymph-node negative breast cancer (NNBC) patients based on clinico-pathological criteria, specific biological markers are needed to predict sensitivity to the different therapeutic options. We examined the feasibility of developing a genomic predictor of chemotherapy response and recurrence risk in 185 patients with NNBC using assembled arrays containing 2,460 BAC clones for scanning the genome for DNA copy number changes. After surgery, 90 patients received anthracycline-based chemotherapy whereas ninety-five did not. Tamoxifen was administered to patients with hormone-receptor positive tumors. Association of genomic and clinico-pathological data and outcome was computed using Cox proportional hazard models and multiple testing adjustment procedures. Analysis of NNBC genomes revealed a common genomic signature. Specific DNA copy number aberrations were associated with hormonal receptor status, but not with other clinico-pathological parameters. In patients treated with chemotherapy, none of the genomic changes was significantly correlated with recurrence. In patients not receiving chemotherapy, deletion of eight BAC clones clustered to chromosome 11q was independently associated with relapse (DFS at 10 years±SE, 40±14% vs. 86±6%;p<00001). The 54 patients with deletion of 11q (29%) did not present more aggressive clinical-pathological features than those without 11q loss. The adverse influence of 11q deletion in clinical outcome was confirmed in an independent validation series of 88 NNBC patients. Our data suggest that NNBC patients with 11q deletion may benefit from anthracycline-based chemotherapy despite other clinical, pathological or genetic features. However, these initial findings should be evaluated in randomized clinical trials. Keywords: CGH, breast cancer
2007-02-07 | GSE6448 | GEO
Project description:EORTC 10994 phase III breast cancer clinical trial comparing FEC (5-fluorouracil, cyclophosphamide, epirubicin) with ET (epirubicin, docetaxel). 161 needle biopsies of locally advanced or large operable breast tumours were hybridised to Affymetrix X3P chips. The array data from the ER negative tumours (28/65 pathological CR in the FEC arm, 27/59 pathological CR in the ET arm) were used to validate the cell line-based chemotherapy response predictors developed by the Potti/Nevins group at Duke University (doi:10.1038/nm1491). Keywords: Tumour profiling
2007-11-23 | GSE6861 | GEO
Project description:On-Treatment Biomarkers Improve Prediction of Response to Neoadjuvant Chemotherapy in Breast Cancer
| PRJNA505812 | ENA
Project description:Prospective, non-comparative Phase II multicenter trial (EXPRESSION EudraCT: 2008-006381-29) where the patients received three 3-week cycles of docetaxel (100 mg/m2) followed by three 3-week cycles of 5-fluorouracil (500 mg/m2), epirubicin (100 mg/m2), and cyclophosphamide (500 mg/m2) (FEC). The primary end point was the identification of a gene expression signature predictive of pathological complete response (pCR). In this trial, pCR was defined as absence of invasive or non-invasive cancer in the breast. External validation of the predictive performance was performed using publicly available data.
2020-11-15 | GSE140494 | GEO
Project description:Reliable blood-based tests for identifying early-stage breast cancer remain elusive. Employing single-cell transcriptomic sequencing analysis, we illustrate a close correlation between nucleotide metabolism in breast tumor cells and activation of regulatory T cells (Tregs) in the tumor microenvironment, which show distinction in subtypes of triple-negative breast cancer (TNBC) and non-TNBC patients and likely to impact on prognosis of BC through A2AR-Treg pathway. Combining machine learning with absolute quantitative plasma metabolomics, we establish an effective diagnostic model for early-stage breast cancer, utilizing a four-metabolite panel including two nucleoside metabolites, inosine and uridine. This metabolomics study, involving 1111 participants, demonstrates high accuracy across training, test, and independent validation cohorts. Surprisingly, inosine and uridine prove predictive of the response to neoadjuvant chemotherapy (NAC) in TNBC patients. This study deepens the understanding of nucleotide metabolism in development of breast cancer and introduces a promising non-invasive approach with low radiation exposure for early breast cancer detection and predicting NAC response in TNBC patients.
2024-08-03 | GSE268662 | GEO
Project description:We report the ability of a gene expression signature to predict response to neoadjuvant chemotherapy in early breast cancer, and also describe transcriptomic changes during treatment
2021-09-30 | GSE180280 | GEO
Project description:Purpose:The identification of biomarkers predictive of neoadjuvant chemotherapy response in breast cancer patients would be an important advancement in personalized cancer therapy. We hypothesized that due to similarities between radiation and chemotherapy induced cellular response mechanisms, radiation responsive genes may be useful in predicting response to neoadjuvant chemotherapy. Materials and Methods: Murine p53 null breast cancer cell lines representative of the luminal, basal-like and claudin-low human breast cancer subtypes were irradiated to identify radiation responsive genes. These murine radiation induced genes were then converted to their human orthologs. These genes were then used to develop a predictor of pathologic complete response (pCR) that was validated on two independent published neoadjuvant chemotherapy data sets of genomic data with response. Results: A radiation induced gene signature consisting of 30 genes was identified on a training set of 337 human primary breast cancer tumor samples that was prognostic for survival. Mean expression of this signature was calculated for individual samples in two independent published datasets and was found to be significantly predictive of pathologic complete response. Multivariate logistic regression analysis in both independent datasets showed that this 30 gene signature added significant predictive information independent of that provided by standard clinical predictors and other gene expression based predictors of pathologic complete response. Conclusion: This study provides new biologic information regarding response to neoadjuvant chemotherapy and a means of possibly improving the prediction of pathologic complete response. reference x sample
2015-01-21 | E-GEOD-48073 | biostudies-arrayexpress
Project description:Changes in cellular lipid metabolism are a common feature in most solid tumors, which occur already in early stages of the tumor progression. However, it remains unclear if the tumor-specific lipid changes can be detected at the level of systemic lipid metabolism. The objective of this study was to perform comprehensive analysis of lipids in breast cancer patient serum samples. Lipidomic profiling using an established analytical platform was performed in two cohorts of breast cancer patients receiving neoadjuvant chemotherapy. The analyses were performed for 142 patients before and after neoadjuvant chemotherapy, and the results before chemotherapy were validated in an independent cohort of 194 patients. The analyses revealed that in general the tumor characteristics are not reflected in the serum samples. However, there was an association of specific triacylglycerols (TGs) in patients' response to chemotherapy. These TGs containing mainly oleic acid (C18:1) were found in lower levels in those patients showing pathologic complete response before receiving chemotherapy. Some of these TGs were also associated with estrogen receptor status and overall or disease-free survival of the patients. The results suggest that the altered serum levels of oleic acid in breast cancer patients are associated with their response to chemotherapy.
2014-06-17 | MTBLS92 | MetaboLights
Project description:We identified a 17-gene Her2-enriched tumor initiating cell (HTIC) signature in MMTV-Her2/Neu mouse mammary TICs. Here, we show that patients with HTICS+ HER2+:ERα− tumors are more likely to achieve a pathologic complete response to trastuzumab-based neoadjuvant chemotherapy compared with HER2+:ER+ tumors. Neoadjuvant study of 50 HER2-positive breast cancer cases treated with trastuzumab-based chemotherapy pre-operatively. Pre-treatment FNA from primary tumors were obtained and RNA extracted and hybridized to Affymetrix microarrays according to manufacturer protocol. Pathologic response was assessed at the end of neoadjuvant treatment.
2012-05-11 | E-GEOD-37946 | biostudies-arrayexpress