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: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: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: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:On-Treatment Biomarkers Improve Prediction of Response to Neoadjuvant Chemotherapy in Breast Cancer
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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: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:Platinum-based treatment (e.g., cisplatin, carboplatin) is generally the first-line chemotherapy for muscle-invasive bladder cancer (MIBC) and mediates regression in approximately 50% of the patients. The goal of this study was to improve the response rate to platinum-based treatment by developing a genomics-based method capable of classifying MIBC patients as being either likely to respond to therapy versus not likely to respond. Aberrations in TP53 and its downstream effectors play a key role in promoting bladder cancer progression, however, TP53 mutation status is neither an independent indicator of treatment response nor survival in MIBC. The hypothesis of this study was that evaluating overall TP53 function would be informative in predicting responsiveness to therapy. Towards this goal, we developed a custom-designed “TP53 functional miRGE assay”, which assesses TP53 function by simultaneously measuring the expression of 105 TP53-responsive mRNAs and miRNAs using NanoString nCounter technology. Expression profiling was performed on a panel of 34 therapy-naïve MIBC specimens with known outcomes of either being responsive or resistant. Clustering analysis identified a 7-gene subset of TP53 network genes (BAK1, BAX, BBC3, CDKN1A, MDM2, PMAIP1, TP53), which identified patients who did not respond to chemotherapy with 92.3% accuracy. Furthermore, higher TP53 function was associated more with resistant MIBCs in that these exhibited higher relative expression of TP53 target genes. Our results demonstrate a 7-gene TP53 functional assay using NanoString technology has the potential to predict patient response to platinum-based chemotherapy, and that validation of this method using a larger patient sample set is warranted.
2019-02-01 | GSE80711 | GEO
Project description:Despite the advantages of neoadjuvant chemotherapy (NACT), associated toxicity is a serious complication that renders monitoring of the patients response to NACT highly important. Thus, prediction of tumor response to treatment is imperative to avoid exposure of potential non-responders to deleterious complications. We have performed genome-wide analysis of DNA methylation by XmaI-RRBS and selected CpG dinucleotides differential methylation of which discriminates luminal B breast cancer samples with different sensitivity to NACT. With this data, we have developed multiplex methylation sensitive restriction enzyme PCR (MSRE-PCR) protocol for determining the methylation status of 10 genes (SLC9A3, C1QL2, DPYS, IRF4, ADCY8, KCNQ2, TERT, SYNDIG1, SKOR2 and GRIK1) that distinguish BC samples with different NACT response. Analysis of these 10 markers by MSRE-PCR in biopsy samples allowed us to reveal three top informative combinations of markers, (1) IRF4 and C1QL2; (2) IRF4, C1QL2, and ADCY8; (3) IRF4, C1QL2, and DPYS, with the areas under ROC curves (AUCs) of 0.75, 0.78 and 0.74, respectively. A classifier based on IRF4 and C1QL2 better meets the diagnostic panel simplicity requirements, as it consists of only two markers. Diagnostic accuracy of the panel of these two markers is 0.75, with the sensitivity of 75% and specificity of 75%.
2020-01-25 | GSE144221 | GEO
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