Using data from a person’s immune response, researchers have devised a blood test that may accurately predict the risk of breast cancer recurrence.
Many breast cancer survivors live with a continual worry that the condition will reemerge, while researchers are hard at work, trying to discern patterns of breast cancer recurrence.
For instance, studies of breast cancer receptors show that estrogen receptor (ER)-negative breast cancers are more likely to recur in the first 5 years after diagnosis, while ER-positive breast cancers are associated with a higher risk of recurrence in the following 10 years.
However, much remains to be known about breast tumor recurrence, and scientists are still trying to understand all the factors that come into play, from the nature of the cancerous cells to the timing of treatment.
New research looks at the body’s antitumor inflammatory response to devise a blood test that may soon predict a person’s chances of experiencing breast cancer recurrence.
Dr. Peter P. Lee, chair of the Department of Immuno-Oncology at the City of Hope Comprehensive Cancer Center, in Duarte, CA, is the senior author of the new study, which appears in the journal Nature Immunology.
The balance between the immune system’s pro- and anti-inflammatory signaling in response to cytokines can determine a person’s antitumor immune reaction, explain Dr. Lee and colleagues in their paper.
For the study, the researchers recruited 40 breast cancer survivors and clinically followed them for a median period of 4 years. The researchers also used an additional sample of 38 breast cancer survivors to attempt to replicate their findings from the previous group.
A person with cancer tends to have peripheral blood regulatory T cells (T-reg cells, for short) with less active pro-inflammatory cytokine signaling pathways and more active immune suppressive cytokine signaling pathways, explain the researchers.
Such an environment can lead to the spread of cancer. So, Dr. Lee and colleagues examined the signaling responses to pro- and anti-inflammatory cytokines in various types of peripheral blood immune cells from breast cancer survivors.
The researchers found that the signaling response in T-reg cells was altered for two pro-inflammatory and two anti-inflammatory cytokines in some breast cancer survivors.
These signaling responses correlated with the state of the participants’ immune systems and with accurate predictions of their breast cancer recurrence within the following 3–5 years.
Using this signaling data, the scientists created an index. The hope is that, eventually, healthcare professionals will be able to run data of a blood sample from a breast cancer survivor through an algorithm based on Lee and the team’s cytokine signaling index.
The goal is for physicians and breast cancer patients to know the risk of the disease recurring within the next 3–5 years.
“Knowing the chance of cancer relapse will inform doctors how aggressive a particular patient’s cancer treatment should be,” Dr. Lee explains. “The [cytokine signaling index] is an overall reflection of a patient’s immune system at diagnosis, which we now know is a major determinant of future relapse.”
“This is the first success [in] linking a solid tumor with blood biomarkers — an indicator of whether a patient will remain in remission.”
Dr. Peter P. Lee
The researcher goes on to explain the significance of the study and findings. “When patients are first diagnosed with cancer, it is important to identify those at higher risk for relapse for more aggressive treatments and monitoring,” he says.
“Staging and new tests based on genomics analysis of the tumor are currently available for risk stratification. However, a predictive blood test would be even more attractive but is not yet available. We are trying to change the status quo.”
The researcher also says that “These findings may go beyond cancer to address other diseases the immune system must battle,” because the balance of cytokine signaling responses among peripheral blood T-reg cells indicates how strong a person’s immune system is overall.
“This general approach may also be useful for predicting outcomes in patients with autoimmune and infectious diseases,” Dr. Lee explains.