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MicroRNAs for Risk Prediction

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Predicting whether or not cancer patients will develop another primary tumor or experience a relapse is a tricky business. University of Texas MD Anderson Cancer Center's Xifeng Wu and her colleagues have found 18 SNPs in microRNA biogenesis genes and miRNA binding sites that are associated with an increased risk of head and neck cancer patients developing a second primary tumor, or relapsing.

Their results could pave the way for better risk prediction models for head and neck cancer patients. Furthermore, they say their findings could eventually lead to improved risk prediction models for other cancers, including leukemia, breast, and lung, in which there is already evidence implicating the miRNA pathway.

"Eventually, we want to develop a genetic blueprint to screen the patients, which will lead to prevention and improve clinical outcomes," Wu says.

MicroRNAs regulate around one-third of gene function in the genome, and are critical for many cellular functions. While dysregulation of miRNAs has been implicated in cancer etiology, there are not many studies looking at the miRNA pathway as a predictor for second primary cancer or cancer recurrence, says Wu, despite the fact that about 10 percent of head and neck cancer patients have a recurrence and 15 to 25 percent develop a second primary tumor. By studying a very specific population — patients with early stage head and neck cancer — and using high-throughput genotyping, Wu and her colleagues were able to evaluate SNPs in the miRNA pathway.

The team examined 241 SNPs in eight genes involved in miRNA creation and 130 miRNA binding sites. They found 11 SNPs in three miRNA biogenesis genes and seven SNPs in miRNA binding sites that were associated with risk for either recurrence or for developing a second primary tumor.

Risk increases based on the number of unfavorable SNPs. Compared to patients with fewer than four SNPs, those with five to nine have a 2.4-fold increase in risk, while 10 or more SNPs increase a patient's risk 7.7 fold.

One particular SNP is associated with a 72 percent increase in risk. Wu says that they do not know the exact function of that SNP and will need to do further mapping and functional studies to determine its biological mechanisms. "It may not be the causal SNP, but only linked with the real causal SNP," she adds.

That particular SNP is located on the RNASEN gene, which is involved in processing primary miRNA into mature miRNA. Dysfunction of that gene results in dysregulation of miRNA, which, in turn, affects critical cellular functions that miRNAs regulate, Wu says.

The next step for Wu and her lab is to validate their results in other populations. Once that is done, the implicated SNPs can be incorporated into a "comprehensive risk prediction model combining epidemiologic profile, environmental exposure, clinical characteristics, and genetic predictors, which will help us identify patients who are at higher risk for second primary tumor and recurrence," Wu says. "Those patients at the highest risk will then be candidates for intensive monitoring and targeted cancer prevention."

Wu is also studying the miRNA pathway in other types of cancer, such as esophageal and oral cancer, and has found that genetic variation in those miRNAs can also lead to increased risk of another primary tumor or recurrence. She is examining other pathways as well, and has found that SNPs in a signaling pathway involved in cell survival can lead to an increased risk in bladder cancer. The ultimate goal, says Wu, is to combine the data from different pathways to form a complete picture of risk assessment.

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