Genetic Signatures Predict Outcomes, Advance Personalized Treatment

Baylor College of Medicine researchers have discovered a genetic signature that can predict poor patient outcomes in estrogen-receptor positive (ER+) breast cancer, potentially leading to personalized treatment for patients.

The 24-gene signature can identify the presence of mutation and translocations in the ER gene that enables the tumor to grow independently from estrogen. According to researchers, the finds could provide new strategies for breast cancer diagnosis and precision medicine.

“About 80% of all breast cancers depend on the hormone estrogen to grow. The hormone promotes tumor growth by binding to the ER,” corresponding author Matthew J. Ellis, MB, BChir, PhD, FRCP, said in a press release.

Interfering with the estrogen-ER interaction is a key therapeutic approach. Drugs including tamoxifen and fulvestrant pursue this method, but tumor cells can learn to avoid the attack and become resistant to the drugs.

“One of the predominant ways ER+ breast cancer cells evade treatment is by creating mutant ERs that no longer can be recognized and targeted by ER-targeting cancer drugs,” said first author Xuxu Gou, a graduate student in the Ellis lab.

The team began analyzing data and ESR1 gene translocation, which refers to the ER gene swapping a part of its sequence with genetic information from another gene. ER gene translocations develop chimeric ER proteins, meaning the protein contains only half of the ER protein with the other half coming from a different protein.

Some ER chimeras are extreme versions of mutant ERs because the drug-binding region is completely replaced with a region from another protein. These ER chimeras can then activate cancer activity.

“Not all ER translocations were active – some drive metastasis and resistance to treatment, but others do not,” Gou said. “To be able to determine whether any particular ESR1 translocation can promote disease progression, we developed a diagnostic genetic signature that detects the presence of an active ESR1 chimeric protein.”

With the assistance of the National Cancer Institute’s PDXnet program, the research team used genomics and transcriptomics on 20 mouse models of ER+ patient-derived tumors to showcase different degrees of dependence on estrogen for growth.

In this dataset, a 24-gene signature detected the presence of an active ESR1 fusion as well as common point mutations in ESR1. According to researchers, these findings were replicated in data from a human metastatic breast cancer cohort.

“In the future, a patient’s cancer cells could be analyzed and, once the MOTERA score indicates the presence of an ER mutation or translocation, then the tumor cells would be further studied to more precisely determine what kind of ER mutant or translocation is present. This would help guide the selection of a personalized, optimal treatment,” said co-author Charles E. Foulds, PhD, assistant professor at Baylor’s Lester and Sue Smith Breast Center.

According to researchers, this study is significant in the field of precision medicine, as it could provide more information regarding tumors and how to effectively treat them.