NCI Grant to Support AI Use to Improve Breast Cancer Treatment
A $3.3 million grant from NCI led researchers to explore the efficacy of AI in improving drug therapy for breast cancer treatment.
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By - After receiving a five-year grant from the National Cancer Institute (NCI), researchers from Rensselaer Polytechnic Institute (RPI) and Albany Medical College aim to determine the capabilities of artificial intelligence (AI) in improving breast cancer treatment.
According to the Centers for Disease Control and Prevention (CDC), about 264,000 cases of breast cancer in women and 2,400 cases in men are diagnosed in the United States annually.
After receiving $3.3 in funding from NCI, RPI and Albany Medical College are continuing their long-time partnership to determine how AI can assist in the treatment of breast cancer.
Although drugs can play a significant role in breast cancer therapy, drug resistance often occurs. According to previous research, intratumor heterogeneity (ITH) and microenvironmental factors can play a part in treatment failure for HER2-positive breast cancer. ITH describes a condition where cells within the same tumor have various profiles.
The new funding will support research into HER2-positive breast cancer, where ITH and microenvironmental factors are identified as playing a role in treatment failure. But researchers first need a better understanding of the mechanisms of therapy resistance and their relationship to ITH and microenvironments.
Non-invasive imaging methods for quantifying heterogeneities at the level of multiple tumor features are sparse. Current evaluation of these factors includes ex-vivo invasive practices that involve retrieving tissue for treatment and returning it to the patient.
The new research effort, however, aims to use mesoscopic fluorescence molecular tomography (MFMT) to analyze tumor heterogeneities. The study will use live animals.
“Through our research, we will develop a novel mesoscopic, multimodal preclinical imaging approach to test the hypothesis that the distribution of antibody-based therapeutics across tumors mediates not only drug efficacy but also the advent of tumor resistance,” said Xavier Intes, PhD, a Rensselaer professor of biomedical engineering and co-director of the Center for Modeling, Simulation and Imaging in Medicine, in a press release.
Intes will lead this research effort alongside Margarida Barroso, PhD, a molecular and cellular physiology professor and the director of the Albany Medical College Imaging Core Facility.
“Ultimately, we hope this imaging technology will allow biologists and clinicians to see exactly how a drug binds to a tumor, providing a better understanding of how tumors adapt or change during treatment,” said Barroso in the press release. “This could help determine a particular drug’s efficacy on a specific tumor, a key element of tackling drug resistance.”
Research efforts combining AI with breast cancer treatment have occurred in the past.
In November 2022, Google Health and a mammography AI vendor, iCAD, Inc., began a partnership to improve breast cancer detection.
Through the collaboration, the two organizations aim to add mammography AI technology from Google Health to the iCAD portfolio of breast imaging AI solutions. The focus of the partnership is to advance innovation and expand access to mammography resources through cloud-based solutions.
Further, iCAD aims to use Google Cloud infrastructure to extend cloud-hosted mammography solutions to underserved regions.
