Do We Need to Reinterpret all Published Gene Expression Studies?

A puzzling observation made by Richard Young’s group challenges standard assumptions made in gene expression analysis and suggests that most published expression studies need to be reanalyzed. The study is published in Cell.

Almost all global expression analysis involves isolation of RNA

from two or more cellular sources, introducing similar amounts

of RNA from the sources into the experimental platform and

analyzing the data by using algorithms that normalize the signal

from the samples. If the cellular sources

produce equivalent amounts of RNA/cell, and the yields of

RNA and its derivatives are equivalent throughout experimental

manipulation, then normalized expression data should produce

an accurate representation of the relative levels of each gene

product.

We recently found that cells with high levels of c-Myc can

amplify their gene expression program, producing two to three

times more total RNA and generating cells that are larger than

their low-Myc counterparts. This discovery has led us to question the common assumption that cells produce similar levels of RNA/cell and the general practice of introducing similar amounts of total RNA into analysis platforms without including standardized controls that would

reveal transcriptional amplification or repression. As described

below, it is likely that this assumption and practice has led to

erroneous interpretations.

Here is more from the author of the study -

Researchers led by Richard Young at the Whitehead Institute for Biological Research in Cambridge, Massachusetts, found that aggressive cancer cells produce several times more RNA than other cells. Moreover, three different commonly used methods for gene expression analysisDNA microarrays, RNA sequencing, and digital molecular barcodingmasked these differences.

We then realized that the common assumption that cells contain similar levels of mRNA is badly flawed and can lead to serious misinterpretations, Jakob Lovn, a postdoc in Youngs lab, said in a press release. Thus, expression data being used to gain insights into cancer cell behavior and regulation should be interpreted with caution.