A Georgia Institute of Technology team exploring genetic mechanisms in cancer has found evidence that a prevailing concept about how cells produce protein molecules, particularly when applied to cancer, could be erroneous as much as two-thirds of the time. Their research was published today in Scientific Reports.
Other researchers have also critiqued this concept, but this new study, led by cancer researcher John McDonald, employed novel analytical technology to explore it in detail. The study also turned up evidence for regulating mechanisms that could account for the prevailing concept's apparent shortcomings.
The concept stems from common knowledge about the assembly line inside cells that starts with code in DNA, is transcribed to messenger RNA, then translated into protein molecules. This model seems to have left the impression that cellular protein production works analogously to an old-style factory production line: That the amount of a messenger RNA encoded by DNA on the front end translates directly into the amount of a corresponding protein produced on the back end. That idea is at the core of how gene-based cancer drug developers choose their targets.
To put that assumed congruence between RNA production and protein production to the test, the researchers examined, in ovarian cancer cells donated by a patient, 4,436 genes, their subsequently transcribed messenger RNA, and the resulting proteins. The assumption, that proverbial factory orders passed down the DNA-RNA line determine in a straightforward manner the amount of a protein being produced, proved incorrect 62% of the time.
"The messenger RNA-protein connection is important because proteins are usually the targets of gene-based cancer therapies," McDonald said. "And drug developers typically measure messenger RNA levels thinking they will tell them what the protein levels are." But the significant variations in ratios of messenger RNA to protein that the researchers found make the common method of targeting proteins via RNA seem much less than optimal.
"The idea that any change in RNA level in cancerous development flows all the way up to the protein level could be leading to drug targeting errors," said McDonald, who heads Georgia Tech's Integrated Cancer Research Center. Drug developers often look for oddly high messenger RNA levels in a cancer then go after what they believe must be the resulting oddly high levels of a corresponding protein.
Taking messenger RNA as a protein level indicator could actually work some of the time. In the McDonald team's latest experiment, in 38% of the cases, the rise of RNA levels in cancerous cells did indeed reflect a comparable rise of protein levels. But in the rest of cases, they did not.
"So, there are going to be many instances where if you're predicting what to give therapeutically to a patient based on RNA, your prescription could easily be incorrect," McDonald said. "Drug developers could be aiming at targets that aren't there and also not shooting for targets that are there."
The analogy of a factory producing building materials can help illustrate what goes wrong in a cancerous cell, and also help describe the study's new insights into protein production. To complete the metaphor: The materials produced are used in the construction of the factory's own building, that is, the cell's own structures.
In cancer cells, a mutation makes protein production go awry usually not by deforming proteins but by overproducing them. "A lot of mutations in cancer are mutations in production levels. The proteins are being overexpressed," said McDonald, who is also a professor in Georgia Tech's School of Biological Sciences.
A bad factory order can lead to the production of too much of a good material and then force it into the structures of the cell, distorting it. The question is: Where in the production line do bad factory orders appear? According to the new study, the answer is less straightforward than perhaps previously thought. The orders don't all appear on the front end of the assembly line with DNA over-transcribing messenger RNA. Additionally, some mutations that do over-transcribe messenger RNA on the front end are tamped down or canceled by regulating mechanisms further down the line, and may never end up boosting protein levels on the back end.
Regulating mechanisms also appear to be making other messenger RNA, transcribed in normal amounts, unexpectedly crank out inordinate levels of proteins.
At the heart of those regulating systems, microRNA may be micromanaging how much, or little, of a protein is actually produced in the end. "We have evidence that microRNAs may be responsible for the non-correlation between the proteins and the RNA, and that's completely novel," McDonald said. "It's an emerging area of research."
Caption: An ovarian cancer tumor cross-section stained in blue. Georgia Tech/McDonald/Zhang