Analysis Finds Value in Pseudogenes

In a large, systematic analysis of the role of pseudogenes across seven types of cancer, researchers from The University of Texas MD Anderson Cancer Center in Houston have found that pseudogenes alone and in combination with other clinical and molecular markers may help define prognostic subgroups.

The findings point to new avenues of research into the roles pseudogenes may be playing in driving the growth of tumors, says principal investigator Han Liang, PhD, assistant professor of bioinformatics and computational biology (Nat Commun 2014 July 7 [Epub ahead of print]).

Pseudogenes, sometimes labeled as “junk” DNA, exist in the human genome in about the same abundance as protein-coding genes. Accumulated sequence changes prevent pseudogenes from encoding proteins, yet they are still transcribed into RNA sequences and, in turn, may play regulatory roles in cancer.

For instance, recent smaller studies have identified cases of transcribed pseudogenes acting as decoys that attract microRNAs away from tumor suppressor genes, such as PTEN, increasing their activity. Pseudogene transcription may also result in gene silencing, says Liang.

“People are beginning to realize that pseudogenes have functional effects,” says Zhaolei Zhang, PhD, professor of molecular genetics at the University of Toronto, who did not participate in the study, but who helped characterize the abundance of pseudogenes in 2003.

To assess the role of pseudogenes in cancer more broadly, Liang analyzed data from The Cancer Genome Atlas (TCGA), which provided a snapshot of transcript levels in over 2,600 tumor samples from patients with seven types of cancer—breast, brain, kidney, lung, colorectal, ovarian, and uterine. Liang's study, which extracted pseudogene expression levels from this data, is part of the TCGA Pan-Cancer Analysis project, an effort to look for patterns across cancer types and genomic dimensions, such as mutations (the genome) and expression levels (the transcriptome).

Liang found that unique sets of pseudogene transcripts were expressed in each form of cancer. In addition, subtypes defined by pseudogene expression levels corresponded closely with subtypes defined by other molecular markers, such as estrogen receptor expression in breast cancer.

In kidney cancer, by joining pseudogene markers with clinical variables, such as disease stage, Liang was able to divide patients into prognostic risk groups. Without pseudogenes, three groups emerge, but adding pseudogenes separates the middle group into two that differ in overall survival. Liang did not investigate the mechanistic roles of pseudogenes, but, he says, “pseudogenes are a novel dimension that we can use to further understand the subtypes.”

“The study included almost 10 times more samples than previous work, which really drives home the validity of the conclusions that pseudogenes can be used as cancer markers,” says Zhang.

Liang hopes to find another large dataset to validate his findings, and also to expand his current analysis across additional types of cancer. “If these patterns are robust, we can consider using pseudogene expression data to build prognostic models that have clinical value,” he says.

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