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Evaluation and validation of a robust single cell RNA-amplification protocol through transcriptional profiling of enriched lung cancer initiating cells.

ABSTRACT: BACKGROUND: Although profiling of RNA in single cells has broadened our understanding of development, cancer biology and mechanisms of disease dissemination, it requires the development of reliable and flexible methods. Here we demonstrate that the EpiStem RNA-Amp™ methodology reproducibly generates microgram amounts of cDNA suitable for RNA-Seq, RT-qPCR arrays and Microarray analysis. RESULTS: Initial experiments compared amplified cDNA generated by three commercial RNA-Amplification protocols (Miltenyi ?MACS™ SuperAmp™, NuGEN Ovation® One-Direct System and EpiStem RNA-Amp™) applied to single cell equivalent levels of RNA (25-50 pg) using Affymetrix arrays. The EpiStem RNA-Amp™ kit exhibited the highest sensitivity and was therefore chosen for further testing. A comparison of Affymetrix array data from RNA-Amp™ cDNA generated from single MCF7 and MCF10A cells to reference controls of unamplified cDNA revealed a high degree of concordance. To assess the flexibility of the amplification system single cell RNA-Amp™ cDNA was also analysed using RNA-Seq and high-density qPCR, and showed strong cross-platform correlations. To exemplify the approach we used the system to analyse RNA profiles of small populations of rare cancer initiating cells (CICs) derived from a NSCLC patient-derived xenograft. RNA-Seq analysis was able to identify transcriptional differences in distinct subsets of CIC, with one group potentially enriched for metastasis formation. Pathway analysis revealed that the distinct transcriptional signatures demonstrated in the CIC subpopulations were significantly correlated with published stem-cell and epithelial-mesenchymal transition signatures. CONCLUSIONS: The combined results confirm the sensitivity and flexibility of the RNA-Amp™ method and demonstrate the suitability of the approach for identifying clinically relevant signatures in rare, biologically important cell populations.

SUBMITTER: Rothwell DG

PROVIDER: S-EPMC4320548 | biostudies-literature | 2014

REPOSITORIES: biostudies-literature

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Evaluation and validation of a robust single cell RNA-amplification protocol through transcriptional profiling of enriched lung cancer initiating cells.

Rothwell Dominic G DG Li Yaoyong Y Ayub Mahmood M Tate Catriona C Newton Gillian G Hey Yvonne Y Carter Louise L Faulkner Suzanne S Moro Massimo M Pepper Stuart S Miller Crispin C Blackhall Fiona F Bertolini Giulia G Roz Luca L Dive Caroline C Brady Ged G

BMC genomics 20141217

<h4>Background</h4>Although profiling of RNA in single cells has broadened our understanding of development, cancer biology and mechanisms of disease dissemination, it requires the development of reliable and flexible methods. Here we demonstrate that the EpiStem RNA-Amp™ methodology reproducibly generates microgram amounts of cDNA suitable for RNA-Seq, RT-qPCR arrays and Microarray analysis.<h4>Results</h4>Initial experiments compared amplified cDNA generated by three commercial RNA-Amplificati ...[more]

PMID: 25519510

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Project description:BackgroundLung adenocarcinoma (LUAD) is the most common subtype of non-small cell lung cancer. Ferroptosis is a newly recognized process of cell death, which is different from other forms of cell death in morphology, biochemistry, and genetics, and has played a vital role in cancer biology. This study aimed to identify a ferroptosis-related gene signature associated with LUAD prognosis.MethodsDataset TCGA-LUAD which came from the TCGA portal was taken as the training cohort. GSE72094 and GSE68465 from the GEO database were treated as validation cohorts. Two hundred fifty-nine ferroptosis-related genes were retrieved from the FerrDb database. In the training cohort, Kaplan-Meier and univariate Cox analyses were conducted for preliminary screening of ferroptosis-related genes with potential prognostic capacity. These genes then entered into the LASSO Cox regression model, constructing a gene signature. The latter was then evaluated in the training and validation cohorts via Kaplan-Meier, Cox, and ROC analyses. In addition, the correlations between risk score and autophagy were examined by Pearson correlation coefficient. The analyses of GSEA and immune infiltrating were performed for better studying the function annotation of the gene signature and the character of each kind of immune cells played in the tumor microenvironment.ResultsA 15-gene signature was found from the training cohort and validated by Kaplan-Meier and Cox regression analyses, revealing its independent prognosis value in LUAD. Moreover, the ROC analysis was conducted, confirming a strong predictive ability that this signature owned for LUAD prognosis. One hundred fifty-one of 222 (68.01%) autophagy-related genes were discovered significantly correlated with risk scores. Analyses of GSEA and immune infiltration exhibited in detail the specific pathways that associate with the 15-gene signature and identified the crucial roles of resting mast cells and resting dendritic cells owned in the prognosis of the 15-gene signature.ConclusionIn this present study, a novel ferroptosis-related 15-gene signature (RELA, ACSL3, YWHAE, EIF2S1, CISD1, DDIT4, RRM2, PANX1, TLR4, ARNTL, LPIN1, HERPUD1, NCOA4, PEBP1, and GLS2) was built. It could accurately predict the prognosis of LUAD and was related to resting mast cells and resting dendritic cells, which provide potential for the personalized outcome prediction and the development of new therapies in LUAD population.

Dataset Information

Evaluation and validation of a robust single cell RNA-amplification protocol through transcriptional profiling of enriched lung cancer initiating cells.

Publications

Evaluation and validation of a robust single cell RNA-amplification protocol through transcriptional profiling of enriched lung cancer initiating cells.

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