New gene classifier can predict the risk of cancer cells recurring or progressing

A team of researchers mapping a molecular atlas for ductal carcinoma in situ (DCIS) has made a major advance toward distinguishing whether the early pre-cancers in the breast will develop into invasive cancers or remain stable.

Analyzing samples from patients who had undergone surgery to remove areas of DCIS, the team identified 812 genes associated with cancer progression. Using this gene classifier, they were then able to predict the risk of cancer cells recurring or progressing.

The study, which published this week in the journal Cancer Cell, was led by E. Shelley Hwang, M.D., of the Duke Cancer Institute, and Rob West, M.D., Ph.D., of the Stanford University Medical Center. Their work is part of the Human Tumor Atlas Network under the Moonshot Initiative funded by the National Cancer Institute.

"There has been a long-standing debate over whether DCIS is cancer or a high-risk condition," Hwang said. "In the absence of a way to make that determination, we currently treat everyone with surgery, radiation, or both.

"DCIS is diagnosed in more than 50,000 women a year, and about a third of those women have a mastectomy, so we are increasingly concerned that we might be overtreating many women," Hwang said. "We need to understand the biology of DCIS better, and that's what our research has been designed to do."

Hwang, West and colleagues analyzed 774 DCIS samples from 542 patients who were a median of 7.4 years post-treatment. They identified 812 genes associated with recurrence within five years from treatment.

The gene classifier was able to predict both recurrence and invasive progression of cancer, with progression appearing to be dependent on a process that requires interactions between invasive DCIS cells and the unique features of the tumor environment.

Hwang said most of the DCIS cancers analyzed in the study were identified to be at low risk for cancer progression or recurrence - a factor that underscores the need to have an accurate predictive model that can be used during clinical visits to guide care.

We've made great progress in our understanding of DCIS, and this work gives us a real path forward to being able to personalize care by scaling treatments to the risk of cancer progression. The real goal is diminishing treatment-related harms without compromising outcomes, and we are excited to be getting closer to achieving this for our patients with DCIS."

E. Shelley Hwang, M.D., Duke Cancer Institute

In addition to Hwang and West, study authors include co-principal investigator Carlo Maley, Ph.D., of Arizona State School of Life Sciences, and Graham Colditz, Ph.D., of Washington University at St. Louis, for the Breast Pre-Cancer Atlas Center, as well as collaborators from 12 other institutions as part of the Translational Breast Cancer Consortium.

The study is part of the Human Tumor Atlas Network Consortium of the National Cancer Institute, which is part of the National Institutes of Health (R01 CA185138-01, U2C CA-17-035, UO1 CA214183, R01CA193694). Other funding support was from the Department of Defense (BC132057); The Breast Cancer Research Foundation (19-074, 19-028, 18-006); PRECISION CRUK Grand Challenge (AEI RYC2019- 026576-I); "la Caixa" Foundation (LCF/PR/PR17/51120011); the Lundbeck Foundation (R288-2018-35); the Danish Cancer Society (R229-A13616); and Susan G. Komen.

Source:
Journal reference:

Strand, S.H., et al. (2022) Molecular classification and biomarkers of clinical outcome in breast ductal carcinoma in situ: Analysis of TBCRC 038 and RAHBT cohorts. Cancer Cell. doi.org/10.1016/j.ccell.2022.10.021.

Comments

The opinions expressed here are the views of the writer and do not necessarily reflect the views and opinions of News Medical.
Post a new comment
Post

While we only use edited and approved content for Azthena answers, it may on occasions provide incorrect responses. Please confirm any data provided with the related suppliers or authors. We do not provide medical advice, if you search for medical information you must always consult a medical professional before acting on any information provided.

Your questions, but not your email details will be shared with OpenAI and retained for 30 days in accordance with their privacy principles.

Please do not ask questions that use sensitive or confidential information.

Read the full Terms & Conditions.

You might also like...
StitchR technology delivers large genes for muscular dystrophy treatment