Researchers from Mass General Brigham Cancer Institute will present research discoveries and outcomes from clinical trials in cancer at the 2026 American Society of Clinical Oncology (ASCO) Annual Meeting, held May 29 – June 2, in Chicago 

 

ASCO brings together leading experts in clinical oncology to share the latest breakthroughs in cancer research, science and medicine. Presentations from Mass General Brigham Cancer Institute investigators include a study evaluating the outcomes of patients admitted to a dedicated oncology service within a multisite home hospital program; the results of a late-breaking plenary session on prostate cancer; efficacy and safety of a lung cancer drug; the efficacy of an app to support the psychosocial needs of patients with multiple myeloma; the creation of an electronic frailty index to inform risk ahead of CAR-T cell therapy treatments, and more.  

Below are a few highlights from this year’s presentations. All times are Central Time (CT). 

An overabundance of a common DNA repair protein can mimic the effects of a mutation in the BRCA gene — a genetic flaw linked to hereditary breast and ovarian cancer — even in tumors that test negative for it, according to a new study led by Penn State College of Medicine researchers. The finding raises the possibility of more personalized cancer treatment for patients whose tumors don't carry the genetic mutations doctors typically screen for.

A new study at The Ohio State University Comprehensive Cancer Center – Arthur G. James Cancer Hospital and Richard J. Solove Research Institute seeks to raise awareness of alcohol as a risk factor for cancer specifically among young women.

The MAF Test®, developed by the IRB Barcelona and ICREA spin-off Inbiomotion, is now available to oncology and pathology professionals in South Korea and is estimated to benefit around 34,000 new patients each year.

This is the first time a product resulting from research at IRB Barcelona has reached patients in South Korea.

This pioneering test helps oncology professionals predict recurrence and survival rates in breast cancer patients, as well as their potential eligibility to receive treatment with bisphosphonates.

With its entry into South Korea, Inbiomotion reinforces the international projection of the MAF Test® and consolidates a distribution network that already covers Spain, Europe, Africa, and Asia.

The SEOM-GEICAM-SOLTI Clinical Guidelines for early-stage breast cancer recommend the use of the MAF Test® in their 2025 update.

Harnessing artificial intelligence, researchers have created a risk model for breast cancer based on digital mammogram images that aims to identify people with the highest 10-year risk. The model outperformed the current standard clinical risk tool for 10-year risk and could identify 40% of breast cancers using clinical guidelines, suggesting it could be integrated into existing screening protocols to enhance primary prevention efforts. As the incidence of breast cancer rises worldwide, clinicians have leaned heavily on prevention through lifestyle modifications and screening tools such as mammograms. Known as primary prevention, these tactics work best when targeted towards women with the highest risk of developing tumors. Clinicians typically use lifestyle models such as the Tyrer-Cuzick-v8 model to identify these patients, but newer AI-based models have emerged that could surpass their performance. However, these AI models are primarily designed to predict short-term risk. To meet the need for a long-term risk assessment tool, Mikael Eriksson and colleagues created a 10-year, AI-based risk model for invasive and in situ breast cancer. They gathered digital mammogram data from a total of 8,696 people across two large cohorts in the US and Sweden from 2010 to 2020, including 1,633 patients with breast cancer. The model calculated overall 10-year risks of 3.83% and 3.14% for each cohort, respectively, and yielded promising performance while estimating the 10-year risk of invasive tumors. Furthermore, it outperformed both Tyrer-Cuzick-v8 and a 5-year AI risk model named Mirai at predicting cancers in the top 10% of high-risk people. Eriksson et al. caution that most of their study participants were of European ancestry. “This stresses the need for further evaluating the model in diverse populations and for its intended use before considering its clinical use,” they write. For reporters interested in trends, a May 20 study in Science Advances presents an AI-based mammogram risk score for breast cancer trained on data from more than 226,000 women of diverse ancestries that can overcome biases based on race or ethnicity. Please see this week’s VancePak for embargoed release information; when published, the paper will be available here: https://www.science.org/doi/10.1126/sciadv.ady3905 Also, an April 30 study in Science showed that the large language model OpenAI o1 could exceed a large group of human physicians at clinical reasoning and tasks such as diagnosis and evaluation of emergency room patients: https://www.science.org/doi/10.1126/science.adz4433

When it comes to assessing breast cancer risk, most datasets that inform existing models come from white women, with consequences for using such models with non-white patient populations. Now, researchers show that an emergent AI-based predictor trained on people from diverse demographics can evaluate breast cancer risk accurately regardless of patients’ race or ethnicity. They tested its risk assessment accuracy by having it evaluate mammographs from more than 226,000 women with diverse demographic backgrounds. Breast cancer is among the most common cancers diagnosed in women. Risk models can predict patients’ likelihood to develop the disease, facilitating early detection, but most datasets behind existing models come from white cohorts. Consequently, they don’t predict breast cancer risk as well for populations of non-European origins. However, Shu Jiang and colleagues write: “Recent work on the use of mammogram risk scores (MRS), an AI-based mammogram image texture summary feature, developed in a racially diverse population, has shown considerable promise.” Now, they have further assessed this tool’s performance across two major North American cohorts. Data came from routine mammography screenings of more than 226,000 women, aged 40 to 74, and involved East Asian, South Asian, Indigenous, Non-Hispanic white, and Non-Hispanic Black demographics. Score values came from AI-based analyses of breast tissue’s texture and characteristics. The scores, which encompassed risk over a period of 5 years, were significantly associated with breast cancer risk and highly calibrated with outcomes for each racial and ethnic subgroup. “This work shows that the MRS is independent of self-reported race and ethnicity, which allows for universal clinical implementation of personalized risk assessment,” Jiang et al. conclude.

Vitamin D deficiency is associated with more moderate to severe pain following breast cancer surgery and an increased consumption of opioid drugs, finds research published online in the journal Regional Anesthesia & Pain Medicine.