Trial reportBMC cancer2011
Importance of pre-analytical steps for transcriptome and RT-qPCR analyses in the context of the phase II randomised multicentre trial REMAGUS02 of neoadjuvant chemotherapy in breast cancer patients.
Trial report in BMC cancer, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
18 citing papers in PubMed.
- When Two-Fold Is Not Enough: Quantifying Uncertainty in Low-Copy qPCR.International journal of molecular sciences · 2025Article
- Obtaining Reliable RT-qPCR Results in Molecular Diagnostics-MIQE Goals and Pitfalls for Transcriptional Biomarker Discovery.Life (Basel, Switzerland) · 2022Review
- Evaluating the transcriptional fidelity of cancer models.Genome medicine · 2021Article
- Annotation and cluster analysis of long noncoding RNA linked to male sex and estrogen in cancers.NPJ precision oncology · 2020Article
- Comedications influence immune infiltration and pathological response to neoadjuvant chemotherapy in breast cancer.Oncoimmunology · 2020Article
- Prioritization of metabolic genes as novel therapeutic targets in estrogen-receptor negative breast tumors using multi-omics data and text mining.Oncotarget · 2019Article
- Celecoxib With Neoadjuvant Chemotherapy for Breast Cancer Might Worsen Outcomes Differentially by COX-2 Expression and ER Status: Exploratory Analysis of the REMAGUS02 Trial.Journal of clinical oncology : official journal of the American Society of Clinical Oncology · 2019Article
- Parsimonious Gene Correlation Network Analysis (PGCNA): a tool to define modular gene co-expression for refined molecular stratification in cancer.NPJ systems biology and applications · 2019Article
- Enrichment of high-grade tumors in breast cancer gene expression studies.Breast cancer research and treatment · 2018Article
- Gene expression information improves reliability of receptor status in breast cancer patients.Oncotarget · 2017Article
- Article
- NanoString expression profiling identifies candidate biomarkers of RAD001 response in metastatic gastric cancer.ESMO open · 2016Article
- Orchestrated increase of dopamine and PARK mRNAs but not miR-133b in dopamine neurons in Parkinson's disease.Neurobiology of aging · 2014Article
- ERBB2 overexpression suppresses stress-induced autophagy and renders ERBB2-induced mammary tumorigenesis independent of monoallelic Becn1 loss.Autophagy · 2014Article
- An 18-gene signature for vascular invasion is associated with aggressive features and reduced survival in breast cancer.PloS one · 2014Article
- Gene interaction enrichment and network analysis to identify dysregulated pathways and their interactions in complex diseases.BMC systems biology · 2012Article
- Amplification and high-level expression of heat shock protein 90 marks aggressive phenotypes of human epidermal growth factor receptor 2 negative breast cancer.Breast cancer research : BCR · 2012Article
- Impact of the spotted microarray preprocessing method on fold-change compression and variance stability.BMC bioinformatics · 2011Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
16 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundIdentification of predictive markers of response to treatment is a major objective in breast cancer. A major problem in clinical sampling is the variability of RNA templates, requiring accurate management of tumour material and subsequent analyses for future translation in clinical practice. Our aim was to establish the feasibility and reliability of high throughput RNA analysis in a prospective trial.
methodsThis study was conducted on RNA from initial biopsies, in a prospective trial of neoadjuvant chemotherapy in 327 patients with inoperable breast cancer. Four independent centres included patients and samples. Human U133 GeneChips plus 2.0 arrays for transcriptome analysis and quantitative RT-qPCR of 45 target genes and 6 reference genes were analysed on total RNA.
resultsThirty seven samples were excluded because i) they contained less than 30% malignant cells, or ii) they provided RNA Integrity Number (RIN) of poor quality. Among the 290 remaining cases, taking into account strict quality control criteria initially defined to ensure good quality of sampling, 78% and 82% samples were eligible for transcriptome and RT-qPCR analyses, respectively. For RT-qPCR, efficiency was corrected by using standard curves for each gene and each plate. It was greater than 90% for all genes. Clustering analysis highlighted relevant breast cancer phenotypes for both techniques (ER+, PR+, HER2+, triple negative). Interestingly, clustering on trancriptome data also demonstrated a "centre effect", probably due to the sampling or extraction methods used in on of the centres. Conversely, the calibration of RT-qPCR analysis led to the centre effect withdrawing, allowing multicentre analysis of gene transcripts with high accuracy.
conclusionsOur data showed that strict quality criteria for RNA integrity assessment and well calibrated and standardized RT-qPCR allows multicentre analysis of genes transcripts with high accuracy in the clinical context. More stringent criteria are needed for transcriptome analysis for clinical applications.
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