Blood cells that infiltrate breast cancers can harbor mutations that may affect progression of the cancer and its response to therapy. Larry Norton and co-workers at the Memorial Sloan Kettering Cancer Center in New York, United States, analyzed DNA sequences in white blood cells — leukocytes — that had entered the breast cancer tissue of 15 untreated patients. In 14 out of 15 cases, the team identified mutations in these cells, including some affecting genes commonly mutated in hematological malignancies. Thus, the development of breast cancers may involve the interaction of primary breast cancer cells with mutant white blood cells. The possible influence of such interactions should therefore be considered during the investigation of breast cancers. Further study of the role of infiltrating mutant white blood cells could reveal new opportunities for prevention, detection, and treatment of breast cancer.
Editor's Highlights from npj Breast Cancer
Explore our collection of research highlights from npj Breast Cancer, curated by Editor-in-Chief Dr. Larry Norton, Medical Director of the Evelyn H. Lauder Breast Center at Memorial Sloan Kettering Cancer Center. The collection includes articles on diagnostics, cancer genetics and genomics, metastasis, treatment, and more.
MONARCH 3 final PFS: a randomized study of abemaciclib as initial therapy for advanced breast cancer
Patients with the most common form of breast cancer stand to benefit from taking a drug that blocks two cell cycle–regulating proteins in addition to hormonal therapy. In a phase III clinical trial, Stephen Johnston from the Royal Marsden NHS Foundation Trust in London, UK, and colleagues randomly gave 493 postmenopausal women with HR+/HER2− metastatic breast cancer a nonsteroidal aromatase inhibitor plus either a placebo or a drug called abemaciclib, a targeted inhibitor of CDK4 and CDK6. A planned interim analysis previously showed that abemaciclib was safe and effective. Johnson’s team now reports that abemaciclib nearly doubled the time women live without disease recurrence, from 15 months on placebo to 28 months on the drug. Additionally, responses were more common and lasted longer among women who received both abemaciclib and the hormonal therapy.
Image analysis with deep learning to predict breast cancer grade, ER status, histologic subtype, and intrinsic subtype
Artificial intelligence can accurately predict the histological subtype and molecular marker status of breast tumors from pathology slide pictures. Heather Couture from the University of North Carolina at Chapel Hill and coworkers developed a deep learning algorithm to analyze various molecular features found within pathology slide images from breast cancer tissue samples. They trained the algorithm on a set of 571 tumors with defined grade, subtype and hormone receptor status. They then tested the model on another set of 288 breast tumors, finding that the deep-learning method predicted assorted molecular features with an accuracy exceeding 75%. Artificial intelligence applied to breast tumor images in this way could thus help clinicians identify those patients who stand to benefit most from further RNA-based genomic testing, an expensive but more definitive diagnostic tool for disease classification.
Mutations in a tumor suppressor gene called NF1 may be an important prognostic indicator for women with breast cancer and a therapeutic target for tumors resistant to hormone therapy. A team led by Carrie Graveel and Matthew Steensma from the Van Andel Research Institute in Grand Rapids, Michigan, USA, studied a large dataset of well-characterized breast cancer cases. They showed that 25% harbored mutations in NF1, a genetic alteration that correlated with diminished survival. Gene network analyses revealed links between NF1 deficiency, RAS oncogene activity, and signaling through the estrogen receptor, including with genes known to mediate resistance to hormone therapy. The researchers also describe a newly created rat model of NF1-mutant breast cancer that they say could help further interrogate the importance of these genetic connections.