Dataset Information

Flexible multiplatform RNA profiling at the single cell level applied to enriched cancer initiating cells: RT-PCR

ABSTRACT: Accurate profiling of RNA expression of single cells is a valuable approach for broadening our understanding of cancer biology and mechanisms of dissemination, but requires the development of reliable methods for their molecular characterization. Here we evaluate a single cell methodology which generates microgram amounts of cDNA suitable for next generation sequencing (RNA-Seq), high throughput RT-qPCR and Affymetrix array analysis. The approach was tested by comparing expression profiles of amplified single MCF7 and MCF10A cells to profiles generated from unamplified RNA. The expression profiles were compared by Affymetrix-U133 arrays, RNA-Seq and high-density qPCR. There were strong cross-platform correlations of >80% and concordance between single cell and unamplified material of >70%. We exemplify the approach through analysis of rare sorted cancer initiating cells (CICs) derived from a NSCLC patient-derived xenograft. Populations of 10 cells from total tumour and two distinct subsets of CIC, putatively involved in primary tumor maintenance or metastasis formation were FACS sorted then directly amplified. CIC expression profiles strongly correlated with published stem-cell and epithelial-mesenchymal transition (EMT) signatures. Our results confirm the utility of the amplification system and our methodology to detect and distinguish RNA profiles in rare cell populations that inform on EMT and stem-cell characteristics. This GEO dataset comprises the RT-qPCR data for MCF7 and MCF10A unamplified cDNA from 1μg RNA, RNA-AMP cDNA from 1ng RNA and RNA-AMP cDNA from single cell samples.

ORGANISM(S): Homo sapiens

PROVIDER: GSE52714 | GEO | 2014/12/31

SECONDARY ACCESSION(S): PRJNA229891

REPOSITORIES: GEO

ACCESS DATA

Dataset's files

Source:

			Action	DRS
		Other

Items per page:

1 - 1 of 1

Similar Datasets

Project description:This SuperSeries is composed of the following subset Series: GSE3557: Effect of the amount of input total RNA on T7 amplification GSE3558: Effect of in vitro transcription time on the fidelity of T7-based RNA linear amplification GSE3559: Variation in cDNA microarray analysis of gene expression using unamplified poly(A)+ RNA GSE3560: Effects of template switching (TS) primer and cDNA cleanup columns on T7 based RNA linear amplification GSE3561: Effect of ligase on T7 based RNA linear amplification GSE3562: Effect of column cleanup on T7 based RNA linear amplification GSE3563: Correlation between expression levels of different tumors measured by poly(A)+RNA and aRNA Abstract: BACKGROUND: T7 based linear amplification of RNA is used to obtain sufficient antisense RNA for microarray expression profiling. We optimized and systematically evaluated the fidelity and reproducibility of different amplification protocols using total RNA obtained from primary human breast carcinomas and high-density cDNA microarrays. RESULTS: Using an optimized protocol, the average correlation coefficient of gene expression of 11,123 cDNA clones between amplified and unamplified samples is 0.82 (0.85 when a virtual array was created using repeatedly amplified samples to minimize experimental variation). Less than 4% of genes show changes in expression level by 2-fold or greater after amplification compared to unamplified samples. Most changes due to amplification are not systematic both within one tumor sample and between different tumors. Amplification appears to dampen the variation of gene expression for some genes when compared to unamplified poly(A)+ RNA. The reproducibility between repeatedly amplified samples is 0.97 when performed on the same day, but drops to 0.90 when performed weeks apart. The fidelity and reproducibility of amplification is not affected by decreasing the amount of input total RNA in the 0.3-3 micrograms range. Adding template-switching primer, DNA ligase, or column purification of double-stranded cDNA does not improve the fidelity of amplification. The correlation coefficient between amplified and unamplified samples is higher when total RNA is used as template for both experimental and reference RNA amplification. CONCLUSION: T7 based linear amplification reproducibly generates amplified RNA that closely approximates original sample for gene expression profiling using cDNA microarrays. Refer to individual Series

Dataset Information

Flexible multiplatform RNA profiling at the single cell level applied to enriched cancer initiating cells: RT-PCR

Dataset's files

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets