Triple-negative breast cancer, or TNBC, is one of the most aggressive and hard-to-treat forms of breast cancer. It lacks the 3 common hormonal markers used to guide treatment in other breast cancers: estrogen receptors, progesterone receptors, and HER2. This characteristic makes it difficult for clinicians to choose an effective treatment strategy.
Researchers have described TNBC as a mix of different diseases with varied molecular traits that affect how the cancer presents symptomatically or responds to treatment. They have used individual genes and gene products to classify TNBC. However, they note current classifications have several overlaps that may be explained by the presence and quantity of specific chemical molecules on the DNA. These molecules affect how genes are turned on or off in cells through a process called DNA methylation.
In this study, researchers from Sweden investigated how the distribution or patterns of DNA methylation define different forms of TNBC to influence the tumor’s behavior, its response to the body’s defense system or immune system, and its response to treatment. They used 235 tumor samples from different Swedish patients and cleaned their data to ensure their analysis focused on cancer cells rather than surrounding healthy tissue.
They used a statistical method called non-negative matrix factorization to identify 2 major groups of TNBC based on DNA methylation patterns: a Basal group and a non-Basal group. They noted the groups matched with previous classifications based on how cells interpret gene functions or generate proteins through a process called gene expression. The Basal group included tumors typically associated with higher immune activity and more frequent mutations linked to DNA repair problems, such as those in the common BRCA1 gene. On the other hand, they reported that the non-Basal group showed higher activity of genes that affect hormone response, even though these tumors still lacked hormone receptors.
Based on their statistical tests, the researchers further divided each major group into smaller subtypes. Among the Basal tumors, they found 3 subgroups, which they called Basal1, Basal2, and Basal3, with different levels of immune cell activity and gene expression profiles. One subgroup, Basal3, showed high expression of a protein that helps tumors evade the immune system. The team found that specific DNA methylation patterns might be responsible for turning that protein on or off, and suggested that patients with Basal3 tumors could benefit from existing cancer treatments that use drugs to block this protein. The Basal2 subgroup expressed genes that suppressed the immune system, while the Basal1 subgroup had no distinct immune-related behavior.
In the non-Basal group, the researchers identified 2 subtypes, nonBasal1 and nonBasal2. Both subgroups were common in older patients and showed lower survival rates than the Basal subgroups. The nonBasal2 group included tumors that affected hormone activities and fat-processing reactions, while the nonBasal1 group had more frequent disruptions in the gene meant to stop tumors from forming.
Across all groups, the researchers pinpointed multiple genes that methylation may regulate to affect how tumors grow and respond to their environment. To verify their findings in a broader context, they obtained independent tumor datasets from a global database and performed the same classification analyses. They showed that the methylation subtypes they identified were present in other TNBC samples. In addition, they linked methylation patterns to the tumor’s defense system and identified potential methods TNBC tumors use to evade the immune system.
The researchers also explained some limitations of their study. They focused on DNA methylation, which is only one type of many chemical changes that can affect the behavior of TNBC. Some of the independent data they used were from general breast cancer studies and not specific to TNBC. Most of these data came from Western European/Nordic populations, so their findings may not apply to people of other ethnic backgrounds. They stressed the need for larger and more complex datasets to understand TNBC subtypes.
The researchers concluded that analyzing DNA methylation in patient samples can divide TNBC into meaningful subtypes with distinct biological features, immune environments, and possibly treatment sensitivities. They suggested future researchers explore the origin of epigenetic changes, like DNA methylation, and how those changes translate to differences in TNBC subtypes.
