Trial reportBreast cancer research : BCR2006
The effect of the stromal component of breast tumours on prediction of clinical outcome using gene expression microarray analysis.
Trial report in Breast cancer research : BCR, 2006. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 32 papers.
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Who cites it
32 citing papers in PubMed.
- Differences in the transcriptional response to fulvestrant and estrogen deprivation in ER-positive breast cancer.Clinical cancer research : an official journal of the American Association for Cancer Research · 2014Trial
- Molecular response to aromatase inhibitor treatment in primary breast cancer.Breast cancer research : BCR · 2007Trial
- Automated Prognosis Marker Assessment in Breast Cancers Using BLEACH&STAIN Multiplexed Immunohistochemistry.Biomedicines · 2023Article
- Systematic in vitro analysis of therapy resistance in glioblastoma cell lines by integration of clonogenic survival data with multi-level molecular data.Radiation oncology (London, England) · 2023Article
- Spatially-resolved quantification of proteins in triple negative breast cancers reveals differences in the immune microenvironment associated with prognosis.Scientific reports · 2020Article
- Schlafen-11 expression is associated with immune signatures and basal-like phenotype in breast cancer.Breast cancer research and treatment · 2019Article
- Article
- Accurate prediction of response to endocrine therapy in breast cancer patients: current and future biomarkers.Breast cancer research : BCR · 2016Review
- Breast cancer classification and prognostication through diverse systems along with recent emerging findings in this respect; the dawn of new perspectives in the clinical applications.Tumour biology : the journal of the International Society for Oncodevelopmental Biology and Medicine · 2016Review
- Prognostic stromal gene signatures in breast cancer.Breast cancer research : BCR · 2015Article
- Comparison of targeted next-generation sequencing and Sanger sequencing for the detection of PIK3CA mutations in breast cancer.BMC clinical pathology · 2015Article
- Profile of differentially expressed intratumoral cytokines to predict the immune-polarizing side effects of tamoxifen in breast cancer treatment.American journal of cancer research · 2015Article
- MMAD: microarray microdissection with analysis of differences is a computational tool for deconvoluting cell type-specific contributions from tissue samples.Bioinformatics (Oxford, England) · 2014Article
- Integrative molecular and functional profiling of ERBB2-amplified breast cancers identifies new genetic dependencies.Oncogene · 2014Article
- Thrombospondin-4 expression is activated during the stromal response to invasive breast cancer.Virchows Archiv : an international journal of pathology · 2013Article
- Characteristics of cross-hybridization and cross-alignment of expression in pseudo-xenograft samples by RNA-Seq and microarrays.Journal of clinical bioinformatics · 2013Article
- A self-directed method for cell-type identification and separation of gene expression microarrays.PLoS computational biology · 2013Article
- Integrative computational biology for cancer research.Human genetics · 2011Review
- Challenges translating breast cancer gene signatures into the clinic.Nature reviews. Clinical oncology · 2011Article
- Gene expression in oligodendroglial tumors.Cellular oncology (Dordrecht, Netherlands) · 2011Article
Corrections and comments
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Authors and funding
9 authors.
Funding
Abstract
introductionThe aim of this study was to examine the effect of the cellular composition of biopsies on the error rates of multigene predictors of response of breast tumours to neoadjuvant adriamycin and cyclophosphamide (AC) chemotherapy. MATERIALS AND
methodsCore biopsies were taken from primary breast tumours of 43 patients prior to AC, and subsequent clinical response was recorded. Post-chemotherapy (day 21) samples were available for 16 of these samples. Frozen sections of each core were used to estimate the proportion of invasive cancer and other tissue components at three levels. Transcriptional profiling was performed using a cDNA array containing 4,600 elements.
resultsTwenty-three (53%) patients demonstrated a 'good' and 20 (47%) a 'poor' clinical response. The percentage invasive tumour in core biopsies collected from these patients varied markedly. Despite this, agglomerative clustering of sample expression profiles showed that almost all biopsies from the same tumour aggregated as nearest neighbours. SAM (significance analysis of microarrays) regression analysis identified 144 genes which distinguished high- and low-percentage invasive tumour biopsies at a false discovery rate of not more than 5%. The misclassification error of prediction of clinical response using microarray data from pre-treatment biopsies (on leave-one-out cross-validation) was 28%. When prediction was performed on subsets of samples which were more homogeneous in their proportions of malignant and stromal cells, the misclassification error was considerably lower (8%-13%, p < 0.05 on permutation).
conclusionThe non-tumour content of breast cancer samples has a significant effect on gene expression profiles. Consideration of this factor improves accuracy of response prediction by expression array profiling. Future gene expression array prediction studies should be planned taking this into account.
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