Genes Predict Cancer Patient’s Pain – or Lack of It

Sickness and pain go together. We think of them as a matched pair. Pain signals sickness, sickness causes pain. But this is not always the case. Especially in early stage cancer, often there is no pain – until the patient is treated. Now, UConn researchers report in the journal Biological Research for Nursing genetic clues that may reveal which individuals are likely to be vulnerable to post-treatment pain.

“We’ll hear women say ‘If I knew the pain would be this bad, I’d rather have died of breast cancer,’” says Erin Young, a pain geneticist in the School of Nursing.

The researchers ask whether such treatment can really be called a ‘cure.’ It would be better, they say, if we could know in advance which patients might suffer from which treatments.

Young, along with nurse-scientist and director of UConn’s Center for Advancement in Managing Pain Angela Starkweather and neuroscientist Kyle Baumbauer, and with colleagues at the University of Florida Gainesville and Kyung Hee University in Seoul, South Korea, found that common variants in two genes contribute to certain symptoms during and after chemotherapy treatment for breast cancer. Their results could one day help patients, and their nurses and doctors, make informed treatment decisions and prepare for, or avoid, damage to their quality of life.

UConn researchers report genetic clues that may reveal which individuals are likely to be vulnerable to post-treatment pain. Credit: Getty Images

The researchers looked at the genetics of 51 women with early-stage breast cancer who had had no previous chemotherapy and no history of depression. The women rated their well-being both before and after treatment for cancer, reporting on their pain, anxiety, depression, fatigue, and sleep quality. Young and her colleagues then looked for connections between genes and symptoms.

They looked at three genes in particular: NTRK1, NTRK2, and COMT. These genes are already associated with pain from other research. NTRK1 is connected to rapid-eye-movement sleep (dream sleep), and a specific variant is linked to pain insensitivity. NTRK2 is associated with the nervous system’s role in pain, fatigue, anxiety, and depression. And some common versions of COMT are linked to risks of developing certain painful conditions. The researchers also chose these genes because the variants associated with pain, fatigue, and other symptoms are fairly common, making it possible to get meaningful results from a sample size of just 51 people.

After the analysis, a couple of results jumped out at them. Two of the genes, COMT and NTRK2, had significant correlations with pain, anxiety, fatigue, and sleep disturbance. The other gene didn’t.

“I always like having a yes/no answer – if we get some ‘no’s’, then we know our analysis wasn’t just confirming what we wanted to see,” says Young.

Such a quick look at a small sample of cancer patients can’t give all the answers as to who is going to develop post-operative and post-chemotherapy pain. But what they did find is very suggestive. Some of the genes were associated with symptoms before surgery. For example, women with two copies of the A variant of COMT reported more anxiety than other women did. COMT was also linked with pain, both during and after cancer treatment: women with one variant of COMT reported more pain, while women with a different variant reported less.

Fatigue also seemed to have a genetic component. Women with one copy of the T variant of NTRK2 reported more post-treatment fatigue than others, and women with two copies reported much more.

Surprisingly, the genes linked to various symptoms worked independently, and didn’t work together to increase overall pain and discomfort. In other words, they weren’t synergistic; they didn’t make each other worse.

“We are focusing on how we can identify women who are at risk of experiencing persistent pain and fatigue, as these symptoms have the highest impact on reducing quality of life after treatment,” says Starkweather. “It’s a great example of how we can make progress toward the goal of personalized healthcare. The next piece of the puzzle is to identify the most effective symptom management interventions, based on the patient’s preferences and genetic information.”

Source: University of Connecticut

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