ArticleJournal of translational medicine2005
RNA amplification for successful gene profiling analysis.
Article in Journal of translational medicine, 2005. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 39 papers.
What it found
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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
39 citing papers in PubMed, 78 citations in OpenAlex.
- Gene expression profiling of cutaneous wound healing.Journal of translational medicine · 2007Trial
- Sequential gene profiling of basal cell carcinomas treated with imiquimod in a placebo-controlled study defines the requirements for tissue rejection.Genome biology · 2007Trial
- Bacterial Proteomics and Antibiotic Resistance Identification: Is Single-Cell Analysis a Worthwhile Pursuit?Pathogens (Basel, Switzerland) · 2025Review
- LINCATRA: Two-cycle method to amplify RNA for transcriptome analysis from formalin-fixed paraffin-embedded tissue.Heliyon · 2024Article
- High accuracy gene expression profiling of sorted cell subpopulations from breast cancer PDX model tissue.PloS one · 2020Article
- A Single Cell but Many Different Transcripts: A Journey into the World of Long Non-Coding RNAs.International journal of molecular sciences · 2020Review
- Identification of Changes in Gene expression of rats after Sensory and Motor Nerves Injury.Scientific reports · 2016Article
- Evaluating whole transcriptome amplification for gene profiling experiments using RNA-Seq.BMC biotechnology · 2015Article
- Ran signaling in melanoma: implications for the development of alternative therapeutic strategies.Cancer letters · 2015Article
- Insight into insulin secretion from transcriptome and genetic analysis of insulin-producing cells of Drosophila.Genetics · 2014Article
- Molecular signatures mostly associated with NK cells are predictive of relapse free survival in breast cancer patients.Journal of translational medicine · 2013Article
- Adjustment method for microarray data generated using two-cycle RNA labeling protocol.BMC genomics · 2013Article
- Combining laser microdissection and RNA-seq to chart the transcriptional landscape of fungal development.BMC genomics · 2012Article
- A signature of immune function genes associated with recurrence-free survival in breast cancer patients.Breast cancer research and treatment · 2012Article
- Regulators of gene expression as biomarkers for prostate cancer.American journal of cancer research · 2012Article
- Article
- Distinct signatures of the immune responses in low risk versus high risk neuroblastoma.Journal of translational medicine · 2011Article
- Amplification of viral RNA from drinking water using TransPlex™ whole-transcriptome amplification.Journal of applied microbiology · 2011Article
- CD4+ T cells inhibit the neu-specific CD8+ T-cell exhaustion during the priming phase of immune responses against breast cancer.Breast cancer research and treatment · 2011Article
- Viral-mediated oncolysis is the most critical factor in the late-phase of the tumor regression process upon vaccinia virus infection.BMC cancer · 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
1 author at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The study of clinical samples is often limited by the amount of material available to study. While proteins cannot be multiplied in their natural form, DNA and RNA can be amplified from small specimens and used for high-throughput analyses. Therefore, genetic studies offer the best opportunity to screen for novel insights of human pathology when little material is available. Precise estimates of DNA copy numbers in a given specimen are necessary. However, most studies investigate static variables such as the genetic background of patients or mutations within pathological specimens without a need to assess proportionality of expression among different genes throughout the genome. Comparative genomic hybridization of DNA samples represents a crude exception to this rule since genomic amplification or deletion is compared among different specimens directly. For gene expression analysis, however, it is critical to accurately estimate the proportional expression of distinct RNA transcripts since such proportions directly govern cell function by modulating protein expression. Furthermore, comparative estimates of relative RNA expression at different time points portray the response of cells to environmental stimuli, indirectly informing about broader biological events affecting a particular tissue in physiological or pathological conditions. This cognitive reaction of cells is similar to the detection of electroencephalographic patterns which inform about the status of the brain in response to external stimuli. As our need to understand human pathophysiology at the global level increases, the development and refinement of technologies for high fidelity messenger RNA amplification have become the focus of increasing interest during the past decade. The need to increase the abundance of RNA has been met not only for gene specific amplification, but, most importantly for global transcriptome wide, unbiased amplification. Now gene-specific, unbiased transcriptome wide amplification accurately maintains proportionality among all RNA species within a given specimen. This allows the utilization of clinical material obtained with minimally invasive methods such as fine needle aspirates (FNA) or cytological washings for high throughput functional genomics studies. This review provides a comprehensive and updated discussion of the literature in the subject and critically discusses the main approaches, the pitfalls and provides practical suggestions for successful unbiased amplification of the whole transcriptome in clinical samples.
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.