Gene Variants Help Determine Breast Cancer Type and Severity, Study Finds

Researchers at Stanford Medicine have made a significant breakthrough in understanding breast cancer. Their findings, published in Science, reveal that inherited genetic sequences play a crucial role in determining both the type and severity of breast cancer a person might develop.

Led by Christina Curtis, PhD, the RZ Cao Professor of Medicine, and Kathleen Houlahan, PhD, a postdoctoral scholar, the study suggests that hereditary factors, rather than random mutations or sheer bad luck, are more influential in the early stages of tumor development. This discovery not only challenges conventional wisdom but also opens up new avenues for predicting and treating breast cancer.

For the investigation, researchers meticulously analyzed the germline genome—the genetic material inherited from one's parents—and its role in cancer. They found that inherited genetic variants could predict which subtype of breast cancer a person is likely to develop and how aggressive that cancer might become. According to the study’s authors, these findings highlight the importance of understanding an individual's germline genome to tailor more effective treatment strategies.

In addition, researchers said the study underscores the interaction between cancer cells and the immune system. They explained that the body's immune cells continuously monitor and respond to unusual signals from potentially cancerous cells. They found that the visibility of these signals, influenced by the genetic makeup inherited by an individual, could determine whether a cancer cell evades detection or is eliminated by the immune system.

“At the early, pre-invasive stage, a high germline epitope burden is protective against cancer,” Dr. Houlahan said. “But once it’s been forced to wrestle with the immune system and come up with mechanisms to overcome it, tumors with high germline epitope burden are more aggressive and prone to metastasis. The pattern flips during tumor progression.”

The Stanford team also delved into the classification of breast cancers, using machine learning to differentiate among 11 distinct subtypes based on their genetic and molecular characteristics. According to the authors, this classification is crucial for clinicians as it helps in making informed treatment decisions and discussing long-term prognoses with patients.

This new understanding of cancer's origins, based on inherited factors, has profound implications for future research and treatment. The study suggests that a deeper examination of the germline genome could lead to better predictions of cancer risk and more personalized approaches to cancer therapy.

“We started with a bold hypothesis,” Dr. Curtis said. “The field had not thought about tumor origins and evolution in this way. We’re examining other cancers through this new lens of heredity and acquired factors and tumor-immune co-evolution.”